{"table_id":"DEN170022-p17-t0","doc_id":"DEN170022","page_num":17,"bbox":[126.27,444.63,478.16,497.04],"n_rows":4,"n_cols":9,"columns":["","Years experience","","","Breast imaging","","","Breast MRI",""],"rows":[["","Years experience","","","Breast imaging","","","Breast MRI",""],["0 – 5","","","6","","","8","",""],["5 – 10","","","4","","","7","",""],["Greater than 10","","","9","","","4","",""]],"caption_candidate":"Table 1. Reader experience","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170022-p18-t0","doc_id":"DEN170022","page_num":18,"bbox":[126.27,402.19,539.71,454.56],"n_rows":4,"n_cols":9,"columns":["","1st READ","2nd READ","","2nd READ – 1st READ","","","",""],"rows":[["","1st READ","2nd READ","","2nd READ – 1st READ","","","",""],["","","","","Difference","","","95% CI",""],["Sensivity","90.4","94.2","3.8","","","[0.8, 7.4]","",""],["Specificity","28.6","27.6","-1.0","","","[-6.5, 4.3]","",""]],"caption_candidate":"positive call)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170022-p18-t1","doc_id":"DEN170022","page_num":18,"bbox":[126.27,495.55,539.71,547.92],"n_rows":4,"n_cols":9,"columns":["","1st READ","2nd READ","","2nd READ – 1st READ","","","",""],"rows":[["","1st READ","2nd READ","","2nd READ – 1st READ","","","",""],["","","","","Difference","","","95% CI",""],["Sensitivity","79.7","84.8","5.1","","","[-0.9, 10.9]","",""],["Specificity","52.2","51.7","-0.5","","","[-7.3, 6.0]","",""]],"caption_candidate":"positive call)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170022-p20-t0","doc_id":"DEN170022","page_num":20,"bbox":[104.67,435.88,518.61,715.92],"n_rows":4,"n_cols":6,"columns":["","Identified Risks to Health","","","Mitigation Measures",""],"rows":[["","Identified Risks to Health","","","Mitigation Measures",""],["Incorrect lesion(s) characterization\nleading to false positive results may\nresult in incorrect patient management\nwith possible adverse effects such as\nunnecessary treatment, unnecessary\nadditional medical imaging and/or\nunnecessary additional diagnostic\nworkup such as biopsy.","","","Certain design verification and\nvalidation activities identified in special\ncontrol (1)\nCertain labeling information identified in\nspecial control (2)","",""],["Incorrect lesion(s) characterization\nleading to false negative results may\nlead to complications, including\nincorrect diagnosis and delay in disease\nmanagement.","","","Certain design verification and\nvalidation activities identified in special\ncontrol (1)\nCertain labeling information identified in\nspecial control (2)","",""],["The device could be misused to analyze\nimages from an unintended patient\npopulation or on images acquired with\nincompatible imaging hardware or\nincompatible image acquisition\nparameters, leading to inappropriate\ndiagnostic information being displayed\nto the user.","","","Certain design verification and\nvalidation activities identified in special\ncontrol (1)\nCertain labeling information identified in\nspecial control (2)","",""]],"caption_candidate":"L. Identified Risks to Health and Mitigation Measures","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170022-p22-t0","doc_id":"DEN170022","page_num":22,"bbox":[64.53,72.32,532.56,606.16],"n_rows":6,"n_cols":2,"columns":["","The study was enriched and individual readers in practice may not\nexperience a significant improvement in diagnosing breast cancer\nlesions."],"rows":[["","The study was enriched and individual readers in practice may not\nexperience a significant improvement in diagnosing breast cancer\nlesions."],["Summary of Other\nFactors",""],["",""],["","Yes, the probable benefits outweigh the probable risks, given the\ncombination of required general controls and the special controls\nestablished for this device. The Special Controls will sufficiently assist\nin managing risks associated with incorrect lesion(s) characterization,\napplication of the device results to the wrong patient population,\nanalysis of incompatible images, and/or device failure by insuring\nproper performance and use of the device.\nBy providing a systematic automated analysis of a multiple factors in\nreviewing breast MRI lesions, the device may marginally improve\ndiagnostic performance and consistency in evaluating a multitude of\nclinical factors. The QuantX analytics calculate the morphological and\nenhancement characteristics of a breast lesion the QuantX package\nuses pattern recognition techniques and displays similar lesions from\na fixed database of biopsy-proven non-cancer and cancer. A user will\nbe able to view and interpret the lesion characteristics and similar\ncases during their diagnosis of a patient’s breast lesions.\nBy demonstrating an ability to assist users in the classification of\nbreast MRI lesions as BIRADS 2, or 3 or 4a, the device may provide\nimproved diagnostic accuracy as assessed by an improvement in\nAUC. In particular, secondary analyses suggest improved sensitivity\nbased on BI-RADS 3 as the cut-point without decreased specificity for\nsome readers.\nThe device provides information that may be useful in the\ncharacterization of breast abnormalities, but does not replace the\nphysician. The physician determines the diagnosis and the information\nprovided by the device is unlikely to decrease diagnostic performance\nof the user. Not all users may experience a substantial improvement in\ndiagnostic performance based on the use of the device. However, the\ndevice is not likely to lead to a substantial decline in reader\nperformance either.\nTherefore, given the available information concerning the benefits,\nrisks, and supporting data; the probable benefits outweigh the\nprobable risks, given the combination of required general controls and\nspecial controls established for this device."],["Conclusions\nDo the probable\nbenefits outweigh\nthe probable risks?",""],["",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170073-p11-t0","doc_id":"DEN170073","page_num":11,"bbox":[160.08,86.04,451.8,243.24],"n_rows":4,"n_cols":2,"columns":["Standard of Care\n(N=44)","Time to Notification of\nSpecialist for LVO cases (mins)"],"rows":[["Standard of Care\n(N=44)","Time to Notification of\nSpecialist for LVO cases (mins)"],["Average [95%CI]","58.72 [46.21, 71.23]"],["Median","51.50"],["Standard\nDeviation","41.14"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170073-p11-t1","doc_id":"DEN170073","page_num":11,"bbox":[160.08,354.48,451.8,511.8],"n_rows":4,"n_cols":2,"columns":["Viz ContaCT\n(N=44)","Time to Notification of\nSpecialist for LVO cases (mins)"],"rows":[["Viz ContaCT\n(N=44)","Time to Notification of\nSpecialist for LVO cases (mins)"],["Average [95%CI]","7.32 [5.51, 9.13]"],["Median","5.60"],["Standard\nDeviation","5.95"]],"caption_candidate":"generate a standard of care Time to Notification of Specialist.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170073-p14-t0","doc_id":"DEN170073","page_num":14,"bbox":[108.0,353.5,514.0,715.5],"n_rows":6,"n_cols":2,"columns":["Identified Risks","Mitieation Measures"],"rows":[["Identified Risks","Mitieation Measures"],["Failure to prioritize images for\nreview with positive findings may\nresult in incon ect and/or delayed\npatient management","Ce1iain design verification and validation\nactivities identified in special control (1)\nCe1iain labeling info1mation identified in\nspecial control (2)"],["Positive notifications may result in\ndeprioritization of review of\nimages from other patients.","Ce1iain design verification and validation\nactivities identified in special control (1)\nCe1iain labeling info1mation identified in\nspecial control (2)"],["The device could be misused to\nanalyze images from an unintended\npatient population or on images\nacquired with incompatible\nimaging hai·dwai·e or incompatible\nimage acquisition pai·ameters,\nleading to inappropriate\nnotifications being displayed to the\nuser.","Ce1iain design verification and validation\nactivities identified in special control (1)\nCe1iain labeling info1mation identified in\nspecial control (2)"],["Device failure could lead to the\nabsence of results, delay of results\nor inconect results, which could\nlikewise lead to inaccurate patient\nassessment.","Ce1iain design verification and validation\nactivities identified in special control (1)\nCe1iain labeling info1mation identified in\nspecial control (2)"],["The triage and notification outputs\nof the device ai·e inappropriately\nused for primary interpretation or","Ce1iain design verification and validation\nactivities identified in special control (1)"]],"caption_candidate":"L. Identified Risks to Health and Mitigation Measures","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170073-p15-t0","doc_id":"DEN170073","page_num":15,"bbox":[90.0,155.25,562.5,632.0],"n_rows":3,"n_cols":2,"columns":["Summary",""],"rows":[["Summary",""],["Summary of the\nBenefit(s)","In Viz.Al's study the average and median CTA -to-notification times were 58.72\nminutes and 51.50 minutes, respectively, for the Standard of Care (two-sided\n95% confidence interval for the mean: [46.21, 71 .23]. The average and median\nCTA-to-notification times were 7.32 minutes and 5.60 minutes, respectively, for\nContaCT (two-sided 95% confidence interval for the mean: [5.51, 9.131). This is\nalso lower than the average time to notification of 66 minutes reported in\nliterature for LVO's diagnosed with CT Angiogram. The notification is informed\nby the software algorithm with a sensitivity and specificity are 87.8% (81.2% -\n92.5%) and 89.6% (83.7% - 93.9%), respectively.\nThe clinical benefit is that the device identifies patients who may benefit from\nrapid intervention by a neurovascular specialist. The clinical benefit is that a\npatient may be eligible for use of mechanical thrombectomy and/or tPA\nadministration. By using one or both of these techniques, a substantial relative\nvolume of brain may be able to be saved by timely intervention.\nFrom an overall US public health perspective, by treating ischemic stroke of\nlarge vessels more aggressively, as is now done for acute coronary artery\nocclusion, the resulting amount of disability from ischemic stroke, which\nremains a major cause of US disability in both men and women can potentially\nbe significantly decreased."],["Summary of the\nRisk(s)","There are no major risks for the device because the device operates in parallel\nto the current usual standard of care.\nMinor risks include:\n• Failure to prioritize images for review with positive findings may result\nin incorrect and/or delayed patient management.\n• Positive notifications may result in deprioritisation of review of images\nfrom other patients.\n• The device could be misused to analyse images from an unintended\npatient population or on images acquired with incompatible imaging\nhardware or incompatible image acquisition parameters, leading to\ninappropriate notifications being displayed to the user.\n• Device failure could lead to the absence of results, delay of results or\nincorrect results, which could likewise lead to inaccurate patient\nassessment.\n• The triage and notification outputs of the device are inappropriately\nused for primary interpretation or as an adjunct for diagnosis outside\nthe intended use of the device."]],"caption_candidate":"M. Benefit/Risk Determination","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN170073-p16-t0","doc_id":"DEN170073","page_num":16,"bbox":[90.0,72.25,562.5,326.5],"n_rows":2,"n_cols":2,"columns":["","The device only notifies the neurovascular specialist. Beyond that it is up the\nregional healthcare delivery system to get the patient the neurovascular\nspecialist in the neurovascular interventional suite/operating room.\nIf adequately treated in time the patient will have no residual neurological\ndeficit. In some cases there may be a small residual neurological deficit. If the\ndisease is untreated, there may be loss of speech, recognition of words,\nmovement of the arms and/or legs, normal bowel and bladder control, or other\nneurologic functions resulting potentially in long term disability."],"rows":[["","The device only notifies the neurovascular specialist. Beyond that it is up the\nregional healthcare delivery system to get the patient the neurovascular\nspecialist in the neurovascular interventional suite/operating room.\nIf adequately treated in time the patient will have no residual neurological\ndeficit. In some cases there may be a small residual neurological deficit. If the\ndisease is untreated, there may be loss of speech, recognition of words,\nmovement of the arms and/or legs, normal bowel and bladder control, or other\nneurologic functions resulting potentially in long term disability."],["Conclusions\nDo the probable\nbenefits outweigh the\nprobable risks?","Yes. The benefit of ContaCT, namely, early identification and notification of a\nspecialist significantly outweighs the minimal risk of a small amount of the\nspecialists time needed to review and disregard a false positive. In the case of\na false negative, the standard of care workflow prevails, so there is no risk\ncompared to standard of care for the patient. In general, there is no direct risk\nto the patient as this is a notification only, software only device. There are no\nsignificant risks which have not been mitigated via clinical testing and labelling.\nTherefore, given the available information concerning the benefits, risks, and\nsupporting data, the probable benefits for the device outweighs the probable\nrisks, given the combination of general controls and special controls established\nfor this device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p11-t0","doc_id":"DEN180005","page_num":11,"bbox":[112.0,505.0,517.75,655.0],"n_rows":6,"n_cols":4,"columns":["","","Wilson's Confidence Intervals",""],"rows":[["","","Wilson's Confidence Intervals",""],["Performance\nMetric","Est imate","90%","95%"],["Sensitivity","0.921","(0.892, 0.942)","(0.886, 0.946)"],["Specificity","0.902","(0.882, 0.919)","(0.877, 0.922)"],["PPV","0.813","(0. 777, 0.844)","(0.769, 0.850)"],["NPV","0.961","(0.946, 0.972)","(0.943, 0.973)"]],"caption_candidate":"and 95% with Wilson's Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p12-t0","doc_id":"DEN180005","page_num":12,"bbox":[75.0,286.0,570.0,662.75],"n_rows":10,"n_cols":6,"columns":["Subgroup","","Performance Metric (90% Wilson's Cl)","","",""],"rows":[["Subgroup","","Performance Metric (90% Wilson's Cl)","","",""],["View","Characteristic","Sensitivity","Specificity","PPV","NPV"],["PA","Post-Surgical: No","0.904\n(0.832, 0.947)","0.934\n(0.902, 0.955)","0.805\n(0.724, 0.867)","0.970\n(0.945, 0.984)"],["","Post-Surgical: Yes","0.920\n(0.864, 0.954)","0.779\n(0.698, 0.844)","0.829\n(0.762, 0.880)","0.893\n(0.820, 0.939)"],["","Age < 80","0.908\n(0.863, 0.940)","0.897\n(0.866, 0.922)","0.813\n(0.759, 0.857)","0.952\n(0.928, 0.969)"],["","Age ;: 80","0.950\n(0.804, 0.989)","0.800\n(0.591 , 0.917)","0.864\n(0.703, 0.944)","0.923\n(0.718, 0.983)"],["LAT","Post-Surgical: No","0.940\n(0.874, 0.973)","0.951\n(0.925, 0.968)","0.818\n(0.736, 0.879)","0.985\n(0.968, 0.993)"],["","Post-Surgical: Yes","0.921\n(0.855, 0.959)","0.750\n(0.658, 0.824)","0.795\n(0.716, 0.857)","0.900\n(0.818, 0.947)"],["","Age < 80","0.925\n(0.878, 0.955)","0.912\n(0.883, 0.934)","0.804\n(0.746, 0.851)","0.969\n(0.949, 0.981 )"],["","Age ;: 80","1.000\n(0.787, 1.000)","0.875\n(0.684, 0.958)","0.833\n(0.601, 0.943)","1.000\n(0.838, 1.000)"]],"caption_candidate":"and all repo1ted characteristics:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p15-t0","doc_id":"DEN180005","page_num":15,"bbox":[111.0,479.0,591.75,577.75],"n_rows":3,"n_cols":9,"columns":["Model","Modality","AUC","Std.\nError","OD Aided ­\nOD Unaided","Std. Error","p-value","95%\nLower\nCL","95%\nUpper CL"],"rows":[["Model","Modality","AUC","Std.\nError","OD Aided ­\nOD Unaided","Std. Error","p-value","95%\nLower\nCL","95%\nUpper CL"],["ROC AUC\nFull Model","OD -Aided","0.889","0.029","0.049","0.013","0.0056","0.019","0.080"],["","OD ­ Unaided","0.840","0.029","-","-","-","-","-"]],"caption_candidate":"Modality --­ OD-Aided - - - OD-Unaided","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p16-t0","doc_id":"DEN180005","page_num":16,"bbox":[112.0,70.0,546.75,180.0],"n_rows":4,"n_cols":5,"columns":["","Estimate {95% Wilson's Cl)","","",""],"rows":[["","Estimate {95% Wilson's Cl)","","",""],["Modality","Sensitivity","Specificity","PPV","NPV"],["OD-Aided","0.803\n(0.785, 0.819)","0.914\n(0.903, 0.924)","0.883\n(0.868, 0.896)","0.853\n(0.839, 0.865)"],["OD-Unaided","0.747\n(0.728, 0.765)","0.889\n(0.876, 0.900)","0.844\n(0.826, 0.859)","0.814\n(0.800, 0.828)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p16-t1","doc_id":"DEN180005","page_num":16,"bbox":[112.0,228.0,480.0,308.75],"n_rows":4,"n_cols":5,"columns":["Modality","TP","TN","FP","FN"],"rows":[["Modality","TP","TN","FP","FN"],["OD-Aided","1715","2436","228","421"],["OD-Unaided","1596","2368","296","540"],["Total","3311","4804","524","961"]],"caption_candidate":"OsteoDetect-aided and OsteoDetect-unaided reads were repo1ied as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p16-t2","doc_id":"DEN180005","page_num":16,"bbox":[75.0,520.0,558.75,687.75],"n_rows":6,"n_cols":6,"columns":["","","Estimate (95% Wilson's Cl)","","",""],"rows":[["","","Estimate (95% Wilson's Cl)","","",""],["Modality","Number\n(Type) of\nViews","Sensitivity","Specificity","PPV","NPV"],["OD-Aided","2 (PA+ LAT)","0.810 (0.782,\n0.835)","0.915 (0.897,\n0.930)","0.871 (0.845,\n0.893)","0.872 (0.852,\n0.889)"],["OD-\nUnaided","2 (PA+ LAT)","0.732 (0.700,\n0.761 )","0.898 (0.879,\n0.914)","0.835 (0.806,\n0.860)","0.825 (0.803,\n0.845)"],["OD -Aided","3 (PA+LAT+\nOBL)","0.798 (0.776,\n0.819)","0.914 (0.899,\n0.927)","0.890 (0.871,\n0.907)","0.839 (0.820,\n0.856)"],["OD-\nUnaided","3 (PA+ LAT+\nOBL)","0.757 (0.733,\n0.779)","0.882 (0.865,\n0.898)","0.849 (0.827,\n0.868)","0.806 (0.786,\n0.824)"]],"caption_candidate":"views are available in a case:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p20-t0","doc_id":"DEN180005","page_num":20,"bbox":[107.75,424.0,516.0,704.75],"n_rows":5,"n_cols":2,"columns":["Identified Risks","Identified Mitigation\nMeasures"],"rows":[["Identified Risks","Identified Mitigation\nMeasures"],["False positive results","General controls and special controls\n(1) and (2)."],["False negative results","General controls and special controls\n(1) and (2)."],["Device misuse (analyzing images from\nunintended patient population or ofan\nunintended anatomical site; or images\nacquired with an unintended modality,\nincompatible imaging hai·dwai·e, or\nincompatible image acquisition\nparameters) resulting in lower device\nperfo1mance (inappropriate\ndetection/diagnosis info1m ation being\ndisplayed to the end user)","General controls and special controls\n(1) and (2)."],["Device failure could lead to absence of\nresults, delay ofresults, or inco1Tect\nresults, which can lead to delayed or\ninaccurate patient dia!lllosis","General controls and special controls\n(1) and (2)."]],"caption_candidate":"L. Identified Risks to Health and Identified Mitigations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p21-t0","doc_id":"DEN180005","page_num":21,"bbox":[90.0,99.75,562.5,709.0],"n_rows":3,"n_cols":2,"columns":["Summary",""],"rows":[["Summary",""],["Summary of the\nBenefit(s)","The clinical MRMC study demonstrated a statistically significant\nimprovement in reader perfo1mance in detecting distal radius fracture in\nadult patients (as measured by the prima1y endpoint of the ROC Area\nUnder the Curve) when aided with OsteoDetect as compared to\nperfonnance at the same task without OsteoDetect, according to clinical\nstandard ofcare.\nAUCaided -AUCunaided = 0.889 - 0.840= 0.049 (two sided 95%\nconfidence level [0.019,0.080])\nOsteoDetect-aided read perfo1mance also showed statistically significant\nimprovement as measured by sensitivity, specificity, PPV, and NPV as\ncompared with the unaided read perfo1mance. Specifically, Imagen's\nstudy demonstrated a device-aided sensitivity of 80.3% (two sided 95%\nconfidence interval for the mean: [78.5%,81.9%]) and device-aided\nspecificity of91.4% (two sided 95% confidence interval for the mean:\n[90.3%,92.4%]). By comparison, the study demonstrated non-aided\nsensitivity and specificity of 74.7% [72.8%,76.5%] and 88.9%\n[87.6%,90.0%], respectively.\nEarlier detection ofa distal radial fracture will allow earlier intervention,\npotentially allowing closed reduction and casting instead ofopen\nreduction, minimizing the risk of delayed pain and post-traumatic\naithritis."],["Summary of the\nRisk(s)","There are minimal potential risks associated with use of the device,\nincluding:\n• The device could provide false positive results, which could\ncontribute to the end user using this info1mation to make a false\npositive diagnosis. Such a false positive diagnosis can result in\nunnecessaiy patient treatment or followup.\n• The device could provide false negative results, which could\ncontribute to the end user using this info1mation to make a false\nnegative diagnosis. A false negative diagnosis could lead to\ndelays in diagnosis and treatment of the fracture and increase the\nlikelihood ofnegative outcomes such as incomplete fracture\nhealing.\n• The device could be inisused to analyze images from an\nunintended patient population or on images acquired with"]],"caption_candidate":"M. Benefit/Risk Determination","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN180005-p22-t0","doc_id":"DEN180005","page_num":22,"bbox":[90.0,72.5,562.5,717.0],"n_rows":3,"n_cols":2,"columns":["","incompatible imaging hardware or incompatible image\nacquisition parameters, leading to inappropriate information\nregarding the presence/location ofa fracture being provided to\nthe end user.\n• The device could fail and lead to absence of results, delay of\nresults, or inco1Tect results, which can lead to delayed or\ninaccurate patient diagnosis\nHowever, based on the perfonnance data and the application ofgeneral\ncontrols and special controls established for this device type, use ofthis\ndevice is unlikely to increase the rate offalse negative or false positive\ndiagnoses of distal radius fracture as compared with the cmTent clinical\nstandard ofpractice. Fmt her, possible misuse ofthe device does not\npresent additional risks compared with the misuse ofother types of\nradiological image processing devices."],"rows":[["","incompatible imaging hardware or incompatible image\nacquisition parameters, leading to inappropriate information\nregarding the presence/location ofa fracture being provided to\nthe end user.\n• The device could fail and lead to absence of results, delay of\nresults, or inco1Tect results, which can lead to delayed or\ninaccurate patient diagnosis\nHowever, based on the perfonnance data and the application ofgeneral\ncontrols and special controls established for this device type, use ofthis\ndevice is unlikely to increase the rate offalse negative or false positive\ndiagnoses of distal radius fracture as compared with the cmTent clinical\nstandard ofpractice. Fmt her, possible misuse ofthe device does not\npresent additional risks compared with the misuse ofother types of\nradiological image processing devices."],["Summary of\nOther Factors","CmTently, injuries to the hand and wrist account for approximately 20%\nofvisits to the emergency depaitment, with a total ofapproximately 3.5\nmillion hand and wrist injuries noted in 2009, for an incidence of 1130\ninjuries per 100,000 persons per yeai·. (Hand (NY) 2012; 7:18-22) By\ndetecting a potentially occult distal radial fracture earlier, pain, post­\ntraumatic aithritis, and possible disability are alleviated, resulting in a\npotential significant improvement in US public health.\nThis software tool brings the expe1tise ofmusculoskeletal radiologists\nand 01thopaedic surgeons specializing in hand surge1y to emergency\nmedicine physicians and physician assistants, fainily practice physicians,\nand internal medicine physicians. Therefore, subspecialty expertise is\npotentially available to emergency rooms across the countiy with the use\nofthis software device."],["Conclusions\nDo the probable\nbenefits outweigh\nthe probable risks?","The benefited population would include adult patients with clinically\nsuspected distal radius fracture. This softwai·e potentially brings\nsubspecialty expe1tise ofmusculoskeletal radiologists and 01thopaedic\nsurgeons specializing in hand and wrist surge1y to physicians and\nphysician assistants working in emergency rooms across the countiy.\nThe underlying statistics as discussed above justify that the perfo1m ance\nofthe device has been clinically validated in a fully crossed design. The\n4 types of clinical providers (emergency medicine physicians, emergency\nmedicine physician assistants, family medicine physicians, and internal\nmedicine physicians) most likely to staff emergency rooms were\nseparately evaluated, and all showed improvement in the detection ofa\ndistal radial fracture aided by the device. Given that the standai·d ofcare\nin 2018 is to cast and have a follow-up X-ray in 10-14 days or perfo1m\nan MRI in cases where a distal radial fracture is clinically suspected in"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN190040-p6-t0","doc_id":"DEN190040","page_num":6,"bbox":[113.5,198.5,536.5,347.0],"n_rows":5,"n_cols":3,"columns":["#","Clinical Paramt>tt>r","% of Scans of Sufficit>nt\nQuality\n(MRMC CI)"],"rows":[["#","Clinical Paramt>tt>r","% of Scans of Sufficit>nt\nQuality\n(MRMC CI)"],["1","Qualitative Visual Assessment of Left Ventricular Size","98.8%\n(96.7%, 100%)"],["2","Qualitative Visual Assessment of Global Left Ventricular\nFtmction","98.8%\n(96.7%, 100%)"],["3","Qualitative Visual Assessment of Right Ventricular Size","92.5%\n(88.1%, 96.9%)"],["4","Qualitative Visual Assessment of Non-Trivial Pericardia!\nEffusion","98.8%\n(96.7%, 100%)"]],"caption_candidate":"assessments in the following proportion of study exams conducted:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN190040-p6-t1","doc_id":"DEN190040","page_num":6,"bbox":[113.5,503.5,526.5,706.25],"n_rows":7,"n_cols":3,"columns":["#","Clinical Paramt>ter","% of Scans of Sufficient\nQuality\n(MRMC 95% CI)"],"rows":[["#","Clinical Paramt>ter","% of Scans of Sufficient\nQuality\n(MRMC 95% CI)"],["1","Qualitative visual assessment of inferior vena cava size","57.5%\n(41.5%, 73.5%)"],["2","Qualitative visual assessment of right ventricular ftmction","91.3%\n(85.7%, 96.8%)"],["3","Qualitative visual assessment of left atrial size","94.6%\n(90.7%, 98.5%)"],["4","Qualitative visual assessment of ao1t ic valve","91.7%\n(88.0%, 95.3%)"],["5","Qualitative visual assessment of mitral valve","96.3%\n(93.9%, 98.6%)"],["6","Qualitative visual assessment of tricuspid valve","83.3%\n(77.0%, 89.7%)"]],"caption_candidate":"conducted:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN190040-p7-t0","doc_id":"DEN190040","page_num":7,"bbox":[113.5,269.5,531.0,567.5],"n_rows":11,"n_cols":3,"columns":["#","View","% of Clips of Diagnostic Quality\n[MRMCCI]"],"rows":[["#","View","% of Clips of Diagnostic Quality\n[MRMCCI]"],["1","PLAX","92.1%\n(87.9%, 96.3%)"],["2","PSAX-AV","66.3%\n(59.0%, 73.5%)"],["3","PSAX-MV","75.8%\n(70.7%, 80.9%)"],["4","PSAX-PM","92.9%\n(89.1%, 96.7%)"],["5","AP4","88.8%\n(81.5%, 96.0%)"],["6","AP5","78.8%\n(66.9%, 90.6%)"],["7","AP3","80.0%\n(70.4%, 89.7%)"],["8","AP2","71.3%\n(61 .6%, 80.9%)"],["9","SubC4","76.3%\n(70.2%, 82.3%)"],["10","SC-IVC","59.2%\n(43.1%, 75.2%)"]],"caption_candidate":"views in the following proportion of study exams conducted:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN190040-p11-t0","doc_id":"DEN190040","page_num":11,"bbox":[72.22,72.24,545.24,268.14],"n_rows":2,"n_cols":2,"columns":["Device Error – Failure to provide guidance on\nacquiring diagnostic-quality images or signals,\nleading to delay, prolonged examination, or\nadditional unnecessary procedures, due to:\n Algorithm failure\n Hardware or software failure"," Design verification and validation\n Labeling"],"rows":[["Device Error – Failure to provide guidance on\nacquiring diagnostic-quality images or signals,\nleading to delay, prolonged examination, or\nadditional unnecessary procedures, due to:\n Algorithm failure\n Hardware or software failure"," Design verification and validation\n Labeling"],["User Error – Operator failure to follow the\nguidance provided by the device to acquire\ndiagnostic-quality images or signals, leading to\ndelay, prolonged examination, or additional\nunnecessary procedures, due to human error"," Design verification and validation\n Labeling"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN190040-p11-t1","doc_id":"DEN190040","page_num":11,"bbox":[72.22,328.68,545.24,719.16],"n_rows":3,"n_cols":2,"columns":["Benefit/Risk Summary",""],"rows":[["Benefit/Risk Summary",""],["Summary of Benefits"," Echocardiography is a highly valuable method for assessment of\nvarious structural and functional characteristics of the heart.\nAdditionally, with the development of point-of-care ultrasound\nimaging, echocardiography at the bedside could provide a valuable\nfirst line of cardiac assessment in settings outside of a traditional\ncardiology department, or hospitals. Caption Guidance is a tool to\nfulfill this important clinical need.\n Echocardiography is highly operator-dependent, and the training for\nechocardiography takes a significant amount of time, leading to a\nshortage of skilled cardiac sonographers. Caption Guidance\nprovides a tool to enable non-cardiac sonographers to acquire\nstandard echocardiography images that can be later reviewed by an\nexpert cardiac healthcare professional. The pivotal study for non-\nusers of cardiac ultrasound was significant and clinically\nmeaningful.\n Echocardiography is a highly operator-dependent imaging\nmodality, and there is variation of echocardiograms’ quality.\nCaption Guidance is a tool to address the variability of\nechocardiograms’ quality by providing a quantitative image quality\nmetric."],["Summary of Risks","Low-quality images from software/algorithm error, hardware error, or\nuser error, leading to additional unnecessary examinations, and/or delay\nof diagnosis."]],"caption_candidate":"BENEFIT/RISK DETERMINATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN230023-p5-t0","doc_id":"DEN230023","page_num":5,"bbox":[68.34,75.28,508.33,710.78],"n_rows":82,"n_cols":8,"columns":["","Analysis","","","","","",""],"rows":[["","Analysis","","","","","",""],["","","","Sensitivity","Sp","ecificity","",""],["","","n","","","","","AUC"],["","group","","","","","",""],["","","","","","","",""],["","OAI","298","0.22 (0.15-0.30)","0.98","(0.96-0.99)","0.79","(0.75-0.84)"],["","","","","","","",""],["Age decades sp","lit by dataset","","","","","",""],["","","","","","","",""],["","TNI","844","0.64 (0.61-0.68)","0.95","(0.92-0.97)","0.89","(0.87-0.90)"],["","","","","","","",""],["50-59","OMN","106","0.43 (0.33-0.53)","0.95","(0.88-1.00)","0.88","(0.82-0.93)"],["","","","","","","",""],["","OAI","177","0.26 (0.15-0.38)","0.98","(0.96-0.99)","0.77","(0.70-0.84)"],["","","","","","","",""],["","TNI","1339","0.65 (0.63-0.67)","0.94","(0.91-0.96)","0.90","(0.89-0.92)"],["","","","","","","",""],["60-69","OMN","181","0.48 (0.40-0.55)","0.91","(0.86-0.97)","0.83","(0.78-0.88)"],["","","","","","","",""],["","OAI","202","0.34 (0.25-0.43)","0.94","(0.90-0.97)","0.82","(0.77-0.87)"],["","","","","","","",""],["","TNI","1031","0.69 (0.66-0.71)","0.86","(0.82-0.90)","0.87","(0.85-0.89)"],["","","","","","","",""],["70-79","OMN","176","0.48 (0.39-0.56)","0.93","(0.88-0.97)","0.88","(0.84-0.92)"],["","","","","","","",""],["","OAI","181","0.38 (0.30-0.45)","0.88","(0.81-0.94)","0.78","(0.72-0.83)"],["","","","","","","",""],["","TNI","515","0.74 (0.71-0.78)","0.71","(0.62-0.80)","0.84","(0.80-0.88)"],["","","","","","","",""],["80+","OMN","50","0.35 (0.21-0.50)","0.95","(0.85-1.00)","0.80","(0.69-0.90)"],["","","","","","","",""],["","OAI","31","0.56 (0.35-0.75)","1.00","(1.00-1.00)","0.95","(0.88-1.00)"],["","","","","","","",""],["X-ray body par","ts split by data","set","","","","",""],["","","","","","","",""],["","NI","1331","0.83 (0.81-0.85)","0.80","(0.75-0.84)","0.89","(0.88-0.91)"],["Ches t","","","","","","",""],["","OMN","149","0.51 (0.39-0.62)","0.90","(0.80-1.00)","0.86","(0.81-0.92)"],["","","","","","","",""],["","TNI","791","0.57 (0.54-0.60)","0.95","(0.93-0.98)","0.91","(0.89-0.93)"],["Lumbar","","","","","","",""],["","OMN","99","0.39 (0.29-0.50)","0.93","(0.86-1.00)","0.85","(0.79-0.91)"],["","","","","","","",""],["","TNI","328","0.75 (0.71-0.80)","0.92","(0.84-1.00)","0.93","(0.89-0.95)"],["Thoracic","","","","","","",""],["","OMN","44","0.50 (0.35-0.65)","1.00","(1.00-1.00)","0.86","(0.76-0.94)"],["","","","","","","",""],["","TNI","457","0.72 (0.69-0.76)","0.99","(0.97-1.00)","0.96","(0.94-0.97)"],["","","","","","","",""],["Pelvis","OMN","82","0.56 (0.44-0.68)","0.97","(0.92-1.00)","0.90","(0.84-0.95)"],["","","","","","","",""],["","OAI","197","0.55 (0.45-0.64)","0.93","(0.89-0.97)","0.91","(0.88-0.94)"],["","","","","","","",""],["","Ni","250","0.56 (0.50-0.61)","0.91","(0.85-0.97)","0.85","(0.80-0.89)"],["","","","","","","",""],["Hand/wrist","OMN","54","0.45 (0.31-0.61)","0.81","(0.67-0.95)","0.73","(0.61-0.85)"],["","","","","","","",""],["","OAI","174","0.24 (0.15-0.33)","0.96","(0.92-0.98)","0.77","(0.70-0.82)"],["","","","","","","",""],["","NI","572","0.41 (0.37-0.44)","0.96","(0.93-0.99)","0.87","(0.84-0.90)"],["","","","","","","",""],["Knee","OMN","85","0.29 (0.18-0.39)","0.97","(0.92-1.00)","0.86","(0.79-0.92)"],["","","","","","","",""],["","OAI","220","0.28 (0.21-0.36)","0.94","(0.91-0.98)","0.76","(0.71-0.81)"],["","","","","","","",""],["Races split by d","ataset*","","","","","",""],["","","","","","","",""],["","TNI","3292","0.67 (0.66-0.69)","0.90","(0.88-0.92)","0.89","(0.88-0.90)"],["","","","","","","",""],["White","OMN","142","0.46(0.38-0.55)","0.98","(0.94-1.00)","0.90","(0.86-0.94)"],["","","","","","","",""],["","OAI","418","0.36 (0.30-0.42)","0.94","(0.91-0.96)","0.80","(0.77-0.84)"],["","","","","","","",""],["","TNI","24","0.33 (0.10-0.60)","1.00","(1.00-1.00)","0.77","(0.36-0.91)"],["","","","","","","",""],["Black","OMN","114","0.36 (0.25-0.46)","0.95","(0.90-0.99)","0.86","(0.80-0.91)"],["","","","","","","",""],["","OAI","147","0.40 (0.27-0.53)","0.95","(0.92-0.98)","0.86","(0.80-0.91)"],["","","","","","","",""],["","TNI","134","0.74 (0.67-0.81)","0.96","(0.88-1.00)","0.93","(0.89-0.96)"],["Asian","","","","","","",""],["","OMN","134","0.47 (0.38-0.56)","0.91","(0.84-0.98)","0.84","(0.78-0.89)"]],"caption_candidate":"Analysis","well_formed":true,"extraction_settings":"text"}
{"table_id":"DEN240047-p4-t0","doc_id":"DEN240047","page_num":4,"bbox":[148.65,274.8,463.35,589.56],"n_rows":21,"n_cols":6,"columns":["","Patient Demographics and","","","Training Dataset",""],"rows":[["","Patient Demographics and","","","Training Dataset",""],["","Other Characteristics","","","(number of exams)",""],["","Age","","","",""],["Age < 50","","","73,500","",""],["50 ≤ Age < 65","","","208,865","",""],["Age ≥ 65","","","83,551","",""],["","Race","","","",""],["White","","","225,309","",""],["Black","","","20,862","",""],["Asian","","","9,230","",""],["Indian","","","553","",""],["Hawaiian","","","440","",""],["Unknown","","","109,654","",""],["","BI-RADS","","","",""],["Positive","","","32,928","",""],["Negative","","","244,940","",""],["Unknown","","","8,8045","",""],["","Breast Density","","","",""],["Dense","","","170,398","",""],["Not Dense","","","160,974","",""],["Unknown","","","34,544","",""]],"caption_candidate":"Table 1. Distribution of Training Dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN240047-p10-t0","doc_id":"DEN240047","page_num":10,"bbox":[72.25,178.13,539.74,641.64],"n_rows":7,"n_cols":5,"columns":["Study Population Exams","Discrimination:","Calibration:","",""],"rows":[["Study Population Exams","Discrimination:","Calibration:","",""],["","AUC(5)\n[95% CIs]","GND Test\nStatistic","Non-\ncentrality\nparameter","P value"],["","","","",""],["Formally-Tested Endpoints","","","",""],["Total Study\nPopulation 77,511 0.70 [0.69, 0.72] 21.70 121.25 < .0001\nExcluding Current\nCancers 77,072 0.66 [0.66, 0.68] 95.27 132.08 0.0174","","","",""],["Sub-group Analyses (Total Study Population)","","","",""],["Race & Ethnicity\nAsian 5,735 0.72 [0.67, 0.77] 13.45 11.80 0.1830\nBlack 28,931 0.67 [0.65, 0.69] 24.81 43.29 0.0107\nWhite 34,743 0.73 [0.71, 0.74] 26.92 56.06 0.0016\nHispanic 7,617 0.70 [0.64, 0.75] 7.99 14.37 0.0139\nAge Group\n<50 20,156 0.68 [0.66, 0.72] 24.66 34.43 0.0498\n≥50, <65 35,310 0.69 [0.67, 0.71] 9.33 54.35 0.0000\n≥65 22,045 0.68 [0.66, 0.70] 46.80 38.11 0.5202\nBreast Density\nDense 30,912 0.69 [0.67, 0.71] 26.17 42.88 0.0168\nNot Dense 44,627 0.71 [0.69, 0.73] 20.99 83.14 < .0001\nBreast Implants\nPresent 1,738 0.73 [0.59, 0.87] 5.46 2.08 0.1153\nNot Present 75,773 0.70 [0.69, 0.72] 22.30 119.48 < .0001\nMammography Model\nLorad Selenia 22,093 0.72 [0.70, 0.75] 9.89 42.04 < .0001\nSelenia Dimensions 55,491 0.70 [0.68, 0.72] 29.01 77.52 < .0001","","","",""]],"caption_candidate":"Total Study Population and for Subgroup Analyses","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN240047-p12-t0","doc_id":"DEN240047","page_num":12,"bbox":[72.25,330.29,539.74,696.18],"n_rows":5,"n_cols":5,"columns":["Study Population Exams","Discrimination:","Calibration:","",""],"rows":[["Study Population Exams","Discrimination:","Calibration:","",""],["","AUC(5)\n[95% CIs]","GND Test\nStatistic","Non-\ncentrality\nparameter","P value"],["","","","",""],["Sub-group Analyses (Excluding Current Cancers)","","","",""],["Race & Ethnicity\nAsian 5,708 0.69 [0.63, 0.77] 23.27 13.40 0.5834\nBlack 28,761 0.63 [0.59, 0.66] 61.04 49.58 0.5915\nWhite 34,521 0.68 [0.66, 0.70] 41.64 62.84 0.0209\nHispanic 7,589 0.67 [0.61, 0.73] 23.46 16.21 0.4636\nAge Group\n<50 20,091 0.64 [0.60, 0.67] 73.20 38.84 0.9622\n≥50, <65 35,124 0.65 [0.63, 0.68] 56.09 60.99 0.1991\n≥65 21,857 0.64 [0.61, 0.66] 69.98 50.61 0.7680\nBreast Density\nDense 30,720 0.65 [0.62, 0.67] 31.47 43.83 0.0475\nNot Dense 44,383 0.67 [0.65, 0.69] 79.19 90.53 0.1466\nBreast Implants\nPresent 1,733 0.63 [0.49, 0.76] 8.88 2.50 0.3508\nNot Present 75,339 0.66 [0.65, 0.68] 105.34 135.85 0.0394\nMammography Model\nLorad Selenia 21,975 0.68 [0.65, 0.71] 55.57 48.34 0.4781\nSelenia Dimensions 55,164 0.66 [0.64, 0.68] 47.24 82.14 0.0035","","","",""]],"caption_candidate":"Table 4. Subgroup Analysis for the Total Study Population Excluding Patients with Current Cancer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN240047-p14-t0","doc_id":"DEN240047","page_num":14,"bbox":[119.34,150.84,492.6,320.82],"n_rows":11,"n_cols":4,"columns":["Decile","Mean model\nprediction","Observed\nTurnbull\nestimate","Calibration error\n(95% CI)"],"rows":[["Decile","Mean model\nprediction","Observed\nTurnbull\nestimate","Calibration error\n(95% CI)"],["1","0.91%","0.67%","0.23% (0.01%, 0.45%)"],["2","1.14%","1.19%","-0.05% (-0.34%, 0.24%)"],["3","1.41%","1.32%","0.09% (-0.24%, 0.42%)"],["4","1.68%","1.85%","-0.17% (-0.52%, 0.18%)"],["5","1.99%","2.54%","-0.55% (-1.00%, -0.10%)"],["6","2.33%","2.72%","-0.39% (-0.94%, 0.16%)"],["7","2.91%","3.20%","-0.29% (-0.80%, 0.22%)"],["8","3.63%","4.31%","-0.68% (-1.27%, -0.09%)"],["9","4.48%","4.94%","-0.45% (-1.10%, 0.20%)"],["10","9.05%","9.19%","-0.14% (-0.87%, 0.59%)"]],"caption_candidate":"Table 5. Decile-level Statistics for the Total Study Population","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN240047-p14-t1","doc_id":"DEN240047","page_num":14,"bbox":[119.34,372.3,492.6,542.28],"n_rows":11,"n_cols":4,"columns":["Decile","Mean model\nprediction","Observed\nTurnbull\nestimate","Calibration error\n(95% CI)"],"rows":[["Decile","Mean model\nprediction","Observed\nTurnbull\nestimate","Calibration error\n(95% CI)"],["1","0.91%","0.64%","0.27% (0.05%, 0.49%)"],["2","1.14%","1.08%","0.06% (-0.23%, 0.35%)"],["3","1.41%","1.10%","0.31% (-0.02%, 0.64%)"],["4","1.68%","1.80%","-0.12% (-0.47%, 0.23%)"],["5","1.99%","2.34%","-0.35% (-0.76%, 0.06%)"],["6","2.32%","2.37%","-0.05% (-0.56%, 0.46%)"],["7","2.89%","2.74%","0.15% (-0.32%, 0.62%)"],["8","3.61%","3.75%","-0.14% (-0.75%, 0.47%)"],["9","4.45%","4.24%","0.21% (-0.42%, 0.84%)"],["10","8.65%","5.73%","2.92% (2.29%, 3.55%)"]],"caption_candidate":"Table 6. Decile-level Statistics for the Total Study Population Excluding Patients with Current Cancer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN240047-p16-t0","doc_id":"DEN240047","page_num":16,"bbox":[72.75,155.68,546.39,591.98],"n_rows":4,"n_cols":2,"columns":["Risks to Health","Mitigation Measures"],"rows":[["Risks to Health","Mitigation Measures"],["Device provides inaccurate risk discrimination\nand/or calibration contributing to:\n• Falsely high risk output, leading to\npatients receiving unnecessary\nadditional imaging or preventive risk\nreduction measures\n• Falsely low risk output, leading to\npatients not receiving additional\nimaging or preventive risk reduction\nmeasures","Clinical performance testing\nSoftware verification, validation, and hazard\nanalysis\nLabeling\nPostmarket monitoring plan"],["Inconsistent device output due to differences in\nacquisition, equipment settings, or other\nfactors affecting image selection or quality","Clinical performance testing\nSoftware verification, validation and hazard\nanalysis\nLabeling\nPostmarket monitoring plan"],["User misinterpretation of device result(s)\ncontributing to:\n• Inappropriate categorization of patient\nrisk resulting in erroneous patient\nmanagement decisions related to\nadditional imaging or preventive risk\nreduction measures\n• Overreliance on device output\nPatient misinterpretation of device result(s)\ncontributing to\n• Considering low risk to be negligible\nwhich may contribute to not receiving\nstandard-of-care screening or\npreventive risk reduction measures","Labeling\nPostmarket monitoring plan"]],"caption_candidate":"risks.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN250007-p2-t0","doc_id":"DEN250007","page_num":2,"bbox":[69.34,639.14,542.78,713.26],"n_rows":5,"n_cols":6,"columns":["","Risks to Health","","","Mitigation Measures",""],"rows":[["","Risks to Health","","","Mitigation Measures",""],["Inappropriate patient management due to\ninaccurate prediction of actual delivery date,\nwhether significantly early or late","Inappropriate patient management due to","","","Clinical performance testing",""],["","inaccurate prediction of actual delivery date,","","","Software verification, validation, and hazard",""],["","whether significantly early or late","","","analysis",""],["","","","","Labeling",""]],"caption_candidate":"type are summarized in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"DEN250007-p3-t0","doc_id":"DEN250007","page_num":3,"bbox":[69.36,73.12,542.77,250.68],"n_rows":12,"n_cols":6,"columns":["","Risks to Health","","","Mitigation Measures",""],"rows":[["","Risks to Health","","","Mitigation Measures",""],["","","","","Postmarket monitoring plan",""],["Inappropriate patient management resulting\nfrom inconsistent device output due to\ndifferences in acquisitions, equipment settings,\nand other image input characteristics","","","","Clinical performance testing",""],["","","","","Software verification, validation, and hazard",""],["","","","","analysis",""],["","","","","Labeling",""],["","","","","Postmarket monitoring plan",""],["","User misinterpretation of the device’s output as","","Labeling\nDevice Characteristics","Labeling",""],["","being directly reflective of the gestational age","","","Device Characteristics",""],["","of the fetus, contributing to:","","","",""],["","- Inappropriate patient management","","","",""],["","- Overreliance on device output","","","",""]],"caption_candidate":"DEN250007 - Raymond Kelly Page 3","well_formed":true,"extraction_settings":"lines"}
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(cid:5)(cid:31)(cid:40)(cid:27)(cid:25)(cid:42)(cid:1)(cid:38)(cid:40)(cid:27)(cid:26)(cid:31)(cid:25)(cid:23)(cid:42)(cid:27)(cid:1)(cid:25)(cid:37)(cid:35)(cid:38)(cid:23)(cid:40)(cid:31)(cid:41)(cid:37)(cid:36)(cid:1)(cid:28)(cid:37)(cid:40)(cid:1)(cid:41)(cid:25)(cid:23)(cid:36)(cid:1)(cid:38)(cid:40)(cid:37)(cid:25)(cid:27)(cid:41)(cid:41)(cid:31)(cid:36)(cid:29)(cid:1)(cid:25)(cid:37)(cid:35)(cid:38)(cid:34)(cid:27)(cid:42)(cid:31)(cid:37)(cid:36)(cid:49)(cid:1)\n(cid:41)(cid:27)(cid:29)(cid:35)(cid:27)(cid:36)(cid:42)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:49)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)(cid:42)(cid:30)(cid:40)(cid:27)(cid:41)(cid:30)(cid:37)(cid:34)(cid:26)(cid:31)(cid:36)(cid:29)(cid:52)(cid:1)(cid:1)(cid:19)(cid:30)(cid:31)(cid:41)(cid:1)(cid:45)(cid:23)(cid:41)(cid:1)(cid:26)(cid:37)(cid:36)(cid:27)(cid:1)(cid:42)(cid:37)(cid:1)(cid:44)(cid:27)(cid:40)(cid:31)(cid:28)(cid:47)(cid:1)(cid:42)(cid:30)(cid:23)(cid:42)(cid:1)(cid:42)(cid:30)(cid:27)(cid:1)\n(cid:41)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:28)(cid:43)(cid:36)(cid:25)(cid:42)(cid:31)(cid:37)(cid:36)(cid:41)(cid:1)(cid:23)(cid:25)(cid:25)(cid:37)(cid:40)(cid:26)(cid:31)(cid:36)(cid:29)(cid:1)(cid:42)(cid:37)(cid:1)(cid:31)(cid:42)(cid:41)(cid:1)(cid:41)(cid:38)(cid:27)(cid:25)(cid:31)(cid:28)(cid:31)(cid:25)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:41)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)(cid:42)(cid:37)(cid:1)(cid:41)(cid:43)(cid:38)(cid:38)(cid:37)(cid:40)(cid:42)(cid:1)\n(cid:41)(cid:43)(cid:24)(cid:41)(cid:42)(cid:23)(cid:36)(cid:42)(cid:31)(cid:23)(cid:34)(cid:1)(cid:27)(cid:39)(cid:43)(cid:31)(cid:44)(cid:23)(cid:34)(cid:27)(cid:36)(cid:25)(cid:27)(cid:52)(cid:1)(cid:1)\n• (cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:44)(cid:27)(cid:40)(cid:31)(cid:28)(cid:31)(cid:25)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)(cid:44)(cid:23)(cid:34)(cid:31)(cid:26)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:42)(cid:27)(cid:41)(cid:42)(cid:31)(cid:36)(cid:29)(cid:1)(cid:28)(cid:37)(cid:40)(cid:1)(cid:27)(cid:23)(cid:25)(cid:30)(cid:1)(cid:40)(cid:27)(cid:39)(cid:43)(cid:31)(cid:40)(cid:27)(cid:35)(cid:27)(cid:36)(cid:42)(cid:1)\n(cid:41)(cid:38)(cid:27)(cid:25)(cid:31)(cid:28)(cid:31)(cid:25)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:52)(cid:1)\n• (cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:44)(cid:27)(cid:40)(cid:31)(cid:28)(cid:31)(cid:25)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)(cid:44)(cid:23)(cid:34)(cid:31)(cid:26)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:42)(cid:27)(cid:41)(cid:42)(cid:31)(cid:36)(cid:29)(cid:1)(cid:28)(cid:37)(cid:40)(cid:1)(cid:27)(cid:23)(cid:25)(cid:30)(cid:1)(cid:23)(cid:34)(cid:29)(cid:37)(cid:40)(cid:31)(cid:42)(cid:30)(cid:35)(cid:31)(cid:25)(cid:1)(cid:28)(cid:43)(cid:36)(cid:25)(cid:42)(cid:31)(cid:37)(cid:36)(cid:52)(cid:1)(cid:1)\n• (cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:44)(cid:27)(cid:40)(cid:31)(cid:28)(cid:31)(cid:25)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)(cid:44)(cid:23)(cid:34)(cid:31)(cid:26)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:1)(cid:42)(cid:27)(cid:41)(cid:42)(cid:31)(cid:36)(cid:29)(cid:1)(cid:23)(cid:42)(cid:1)(cid:42)(cid:30)(cid:27)(cid:1)(cid:43)(cid:36)(cid:31)(cid:42)(cid:49)(cid:1)(cid:31)(cid:36)(cid:42)(cid:27)(cid:29)(cid:40)(cid:23)(cid:42)(cid:31)(cid:37)(cid:36)(cid:49)(cid:1)(cid:23)(cid:36)(cid:26)(cid:1)\n(cid:41)(cid:47)(cid:41)(cid:42)(cid:27)(cid:35)(cid:1)(cid:34)(cid:27)(cid:44)(cid:27)(cid:34)(cid:1)\n(cid:1)\n(cid:19)(cid:30)(cid:27)(cid:1)(cid:28)(cid:37)(cid:34)(cid:34)(cid:37)(cid:45)(cid:31)(cid:36)(cid:29)(cid:1)(cid:39)(cid:43)(cid:23)(cid:34)(cid:31)(cid:42)(cid:47)(cid:1)(cid:23)(cid:41)(cid:41)(cid:43)(cid:40)(cid:23)(cid:36)(cid:25)(cid:27)(cid:1)(cid:35)(cid:27)(cid:23)(cid:41)(cid:43)(cid:40)(cid:27)(cid:41)(cid:1)(cid:45)(cid:27)(cid:40)(cid:27)(cid:1)(cid:23)(cid:38)(cid:38)(cid:34)(cid:31)(cid:27)(cid:26)(cid:1)(cid:26)(cid:43)(cid:40)(cid:31)(cid:36)(cid:29)(cid:1)(cid:41)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)\n(cid:26)(cid:27)(cid:44)(cid:27)(cid:34)(cid:37)(cid:38)(cid:35)(cid:27)(cid:36)(cid:42)(cid:51)(cid:1)\n• (cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:5)(cid:27)(cid:44)(cid:27)(cid:34)(cid:37)(cid:38)(cid:35)(cid:27)(cid:36)(cid:42)(cid:1)(cid:12)(cid:31)(cid:28)(cid:27)(cid:1)(cid:4)(cid:47)(cid:25)(cid:34)(cid:27)(cid:1)\n• (cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:1)(cid:17)(cid:31)(cid:41)(cid:33)(cid:1)(cid:2)(cid:41)(cid:41)(cid:27)(cid:41)(cid:41)(cid:35)(cid:27)(cid:36)(cid:42)(cid:52)(cid:1)\n• (cid:17)(cid:31)(cid:41)(cid:33)(cid:1)(cid:2)(cid:41)(cid:41)(cid:27)(cid:41)(cid:41)(cid:35)(cid:27)(cid:36)(cid:42)(cid:1)(cid:37)(cid:28)(cid:1)(cid:15)(cid:28)(cid:28)(cid:54)(cid:42)(cid:30)(cid:27)(cid:54)(cid:18)(cid:30)(cid:27)(cid:34)(cid:28)(cid:1)(cid:55)(cid:15)(cid:19)(cid:18)(cid:56)(cid:1)(cid:18)(cid:37)(cid:28)(cid:42)(cid:45)(cid:23)(cid:40)(cid:27)(cid:52)(cid:1)\n• 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{"table_id":"K141480-p6-t0","doc_id":"K141480","page_num":6,"bbox":[84.67,50.4,522.1,559.9],"n_rows":2,"n_cols":2,"columns":["(cid:32)(cid:26)(cid:45)(cid:44)(cid:39)(cid:26)","(cid:44)(cid:23)(cid:32)(cid:44)(cid:39)(cid:11)(cid:35)(cid:44)(cid:46)(cid:23)(cid:8)(cid:7)(cid:37)(cid:46)(cid:12)(cid:7)(cid:9)(cid:8)(cid:26)"],"rows":[["(cid:32)(cid:26)(cid:45)(cid:44)(cid:39)(cid:26)","(cid:44)(cid:23)(cid:32)(cid:44)(cid:39)(cid:11)(cid:35)(cid:44)(cid:46)(cid:23)(cid:8)(cid:7)(cid:37)(cid:46)(cid:12)(cid:7)(cid:9)(cid:8)(cid:26)"],["(cid:17)(cid:23)(cid:18)(cid:14)(cid:17)(cid:18)(cid:17)(cid:31)(cid:29)(cid:7)\n(cid:5)(cid:2)(cid:48)(cid:2)(cid:49)(cid:2)(cid:50)","To receive, store, transmit, post-process, display and allow\nmanipulation of reports and medical images from acquisition\ndevices, including optical or other non-DICOM format images,\nDICOM images with modality type XA, US, CR, DR, SPECT, NM\nand MG, and images from volumetric medical scanning devices such\nas EST, CT, PET or MRI. To provide access to images derived data\nand derived images via client-server software, web browser and\nmobile technology.\nVisualization in 2D, 3D and 4D are supported for single or multiple\ndatasets, or combinations thereof. Tools are provided to define and\nedit paths through structures such as centerlines, which may be used\nto analyze cross-sections of structures, or to provide flythrough\nvisualizations rendered along such a centerline. Segmentation of\nregions of interest and quantitative analysis tools are provided, for\nimages of vasculature, pathology and morphology, including\ndistance, angle, volume, histogram, ratios thereof, and tracking of\nquantities over time. A database is provided to track and compare\nresults using published comparison techniques such as RECIST and\nWHO. Calcium scoring for quantification of atherosclerotic plaque\nis supported.\nSupport is provided for digital image processing to derive metadata\nor new images from input image sets, for internal use or for\nforwarding to other devices using the DICOM protocol. Image\nprocessing tools are provided to extract metadata to derive\nparametric images from combinations of multiple input images, such\nas temporal phases, or images co-located in space but acquired with\ndifferent imaging parameters, such as different MR pulse sequences,\nor different CT image parameters (e.g. dual energy).\niNtuition is designed for use by healthcare professionals and is\nintended to assist the physician in diagnosis, who is responsible for\nmaking all final patient management decisions.\nInterpretation of mammographic images or digitized film screen\nimages is supported only when the software is used without\ncompression and with an FDA-Approved monitor that offers at least\n5Mpixel resolution and meets other technical specifications\nreviewed and accepted by the FDA."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K141480-p6-t1","doc_id":"K141480","page_num":6,"bbox":[84.67,588.3,527.45,732.1],"n_rows":4,"n_cols":4,"columns":["(cid:37)(cid:19)(cid:24)(cid:18)(cid:14)(cid:20)(cid:19)(cid:7)","(cid:17)(cid:23)(cid:18)(cid:14)(cid:17)(cid:18)(cid:17)(cid:31)(cid:29)(cid:7)","(cid:40)(cid:42)(cid:17)(cid:47)(cid:48)","(cid:12)(cid:19)(cid:16)(cid:24)(cid:20)(cid:51)(cid:22)(cid:7)"],"rows":[["(cid:37)(cid:19)(cid:24)(cid:18)(cid:14)(cid:20)(cid:19)(cid:7)","(cid:17)(cid:23)(cid:18)(cid:14)(cid:17)(cid:18)(cid:17)(cid:31)(cid:29)(cid:7)","(cid:40)(cid:42)(cid:17)(cid:47)(cid:48)","(cid:12)(cid:19)(cid:16)(cid:24)(cid:20)(cid:51)(cid:22)(cid:7)"],["(cid:22)(cid:26)(cid:23)(cid:52)(cid:7)(cid:63)","(cid:64)(cid:26)(cid:21)(cid:26)(cid:37)(cid:26)(cid:65)","(cid:32)(cid:31)(cid:44)",""],["(cid:44)(cid:6)(cid:11)(cid:2)(cid:4)(cid:6)(cid:7)(cid:1)(cid:5)(cid:8)(cid:12)(cid:12)","(cid:14)(cid:14)","(cid:14)(cid:14)",""],["(cid:44)(cid:6)(cid:11)(cid:2)(cid:4)(cid:6)(cid:7)(cid:1)(cid:5)(cid:8)(cid:12)(cid:12)(cid:2)(cid:41)(cid:2)(cid:4)(cid:8)(cid:20)(cid:2)(cid:10)(cid:17)","(cid:45)(cid:45)(cid:46)","(cid:45)(cid:45)(cid:46)",""]],"caption_candidate":"(cid:32)(cid:19)(cid:42)(cid:17)(cid:40)(cid:19)(cid:7)(cid:39)(cid:31)(cid:16)(cid:36)(cid:24)(cid:20)(cid:17)(cid:22)(cid:31)(cid:29)(cid:7)(cid:35)(cid:24)(cid:15)(cid:27)(cid:19)","well_formed":true,"extraction_settings":"lines"}
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(cid:30)(cid:7)(cid:6)&(cid:3)(cid:27)(cid:4)(cid:6)(cid:29)(cid:3)(cid:5)","\"’ (cid:31) (cid:7)(cid:6)(cid:2)(cid:3)(cid:4)(cid:5)(cid:6)(cid:31)(cid:3)(cid:6)(cid:31)( (cid:6)\"(cid:4)(cid:8)(cid:6)!(cid:31)(cid:8)(cid:2)(cid:2)(cid:6) (cid:5)(cid:8)(cid:16)","’(cid:6)(cid:8)(cid:7)(cid:7)(cid:4) !!(cid:6))","’(cid:3)*$%"],["","","",""],["(cid:7)8!(cid:10)4(cid:25)(cid:24)(cid:21)!(cid:23)(cid:10)(cid:30)(cid:28)(cid:27)!(cid:10)6(cid:20)(cid:24)(cid:10)(cid:30)8(cid:28)(cid:29)(cid:10)5(cid:20)99!5(cid:30)(cid:28)(cid:20)(cid:23)(cid:10)(cid:20)","6(cid:10)(cid:28)(cid:23)6(cid:20)(cid:24)(cid:27)(cid:22)(cid:30)(cid:28)(cid:20)(cid:23)(cid:10)(cid:28)(cid:29)(cid:10)!(cid:29)(cid:30)(cid:28)(cid:27)(cid:22)(cid:30)!(cid:21)(cid:10)(cid:30)(cid:20)(cid:10)(cid:22) !(cid:24)(cid:22)(cid:26)!(cid:10)/&(cid:10)8(cid:20)(cid:25)(cid:24)","(cid:29)(cid:10)(cid:31)!(cid:24)(cid:10)(cid:24)!(cid:29)(cid:31)(cid:20)(cid:23)(cid:29)","!.(cid:10)(cid:28)(cid:23)59(cid:25)(cid:21)(cid:28)(cid:23)(cid:26)(cid:10)(cid:30)8!(cid:10)"],["(cid:30)(cid:28)(cid:27)!(cid:10)(cid:30)(cid:20)(cid:10)(cid:24)! (cid:28)!;(cid:10)(cid:28)(cid:23)(cid:29)(cid:30)(cid:24)(cid:25)5(cid:30)(cid:28)(cid:20)(cid:23)(cid:29).(cid:10)(cid:29)!(cid:22)(cid:24)58(cid:10)!","*(cid:28)(cid:29)(cid:30)(cid:28)(cid:23)(cid:26)(cid:10)(cid:21)(cid:22)(cid:30)(cid:22)(cid:10)(cid:29)(cid:20)(cid:25)(cid:24)5!(cid:29).(cid:10)(cid:26)(cid:22)(cid:30)8!(cid:24)(cid:10)(cid:22)(cid:23)(cid:21)(cid:10)(cid:27)(cid:22)(cid:28)(cid:23)(cid:30)(cid:22)(cid:28)(cid:23)(cid:10)(cid:30)8","!(cid:10)(cid:21)(cid:22)(cid:30)(cid:22)(cid:10)(cid:23)!!(cid:21)!(cid:21)(cid:10)","(cid:22)(cid:23)(cid:21)(cid:10)5(cid:20)(cid:27)(cid:31)9!(cid:30)!(cid:10)(cid:10)"],["(cid:22)(cid:23)(cid:21)(cid:10)(cid:24)! 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{"table_id":"K153351-p6-t0","doc_id":"K153351","page_num":6,"bbox":[66.63,295.38,476.01,404.64],"n_rows":4,"n_cols":6,"columns":["","Quantib™ Brain","","","K050703 QBrain®",""],"rows":[["","Quantib™ Brain","","","K050703 QBrain®",""],["Brain tissue and WMH segmentation","","","Brain tissue segmentation (intracranial\ntissue volume GM+WM, CSF volume, lobe\nvolumes, cerebellum volume). WMH\nsegmentation (total WMH volume).","",""],["Absolute and relative volumes","","","Absolute volumes","",""],["Software plugs into the AW and AW server\nplatforms","","","Stand-alone application","",""]],"caption_candidate":"Following are the differences between Quantib™ Brain and the predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p4-t0","doc_id":"K153427","page_num":4,"bbox":[72.13,49.8,534.46,99.86],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","mtk1956-007-6","Rev. Date:","26th Dec 2015"],["","DMS Ref:","Eng/Angel","","Page 1 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p5-t0","doc_id":"K153427","page_num":5,"bbox":[72.26,49.8,534.46,99.86],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","mtk1956-007-6","Rev. Date:","26th Dec 2015"],["","DMS Ref:","Eng/Angel","","Page 2 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p5-t1","doc_id":"K153427","page_num":5,"bbox":[72.26,269.81,539.86,719.38],"n_rows":10,"n_cols":3,"columns":["","Predicate Device\nVolpara, 1.5.1 (K152028)","Submission Device,\nVolpara 1.5.2"],"rows":[["","Predicate Device\nVolpara, 1.5.1 (K152028)","Submission Device,\nVolpara 1.5.2"],["Intended Use (difference is underlined)","“Volpara is a software application\nintended for use with the raw data\nfrom digital breast x-ray systems,\nincluding tomosynthesis. Volpara\ncalculates a density map and from\nthat determines volumetric breast\ndensity as a ratio of fibroglandular\ntissue and total breast volume\nestimates. Volpara provides these\nnumerical values along with a BI-\nRADS breast density 4th or 5th\nEdition category to aid health care\nprofessionals in the assessment of\nbreast tissue composition. Volpara\nproduces adjunctive information. It\nis not an interpretive or diagnostic\naid“","“Volpara is a software application\nintended for use with the raw data\nfrom digital breast x-ray systems,\nincluding tomosynthesis. Volpara\ncalculates and quantifies a density\nmap and from that determines\nvolumetric breast density as a ratio\nof fibroglandular tissue and total\nbreast volume estimates. Volpara\nprovides these numerical values\nalong with a BI-RADS breast\ndensity 4th or 5th Edition category to\naid health care professionals in the\nassessment of breast tissue\ncomposition. Volpara is not an\ninterpretive or diagnostic aid and\nshould be used only as adjunctive\ninformation when the final\nassessment of breast density\ncategory is made by an MQSA-\nqualified interpreting physician.”"],["Intended Users","Health Care Professionals","Health Care Professionals"],["Image Source","Digital mammography images","Digital mammography images."],["Image Sources","Digital mammograms from\nmammography or tomosynthesis\nsystems.","Digital mammograms from\nmammography or tomosynthesis\nsystems."],["Anatomical Area","Breast","Breast"],["Assessment Scope","Volumetric","Volumetric"],["Operating Environment","Windows","Windows"],["Image Storage and Report Generation","Yes\nOutput to the console","Yes\nOutput to the console"],["Numeric Output","Volume of Fibroglandular tissue\nVolume of Breast","Volume of Fibroglandular tissue\nVolume of Breast"]],"caption_candidate":"Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p6-t0","doc_id":"K153427","page_num":6,"bbox":[72.17,49.8,534.46,99.86],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","mtk1956-007-6","Rev. Date:","26th Dec 2015"],["","DMS Ref:","Eng/Angel","","Page 3 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p6-t1","doc_id":"K153427","page_num":6,"bbox":[72.17,117.98,539.97,318.89],"n_rows":4,"n_cols":3,"columns":["","Volumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category","Volumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category\nAverage thickness of dense tissue\nMaximum thickness of dense\ntissue (and location).\nMaximum volume of dense tissue\nabove any 1cm2 square region\n(and location)."],"rows":[["","Volumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category","Volumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category\nAverage thickness of dense tissue\nMaximum thickness of dense\ntissue (and location).\nMaximum volume of dense tissue\nabove any 1cm2 square region\n(and location)."],["Image Output","None","Density map in DICOM SCI format,\nfor visualization as user requires."],["Classification","21 CFR 892.2050; LLZ","21 CFR 892.2050; LLZ"],["Software Level of Concern","Moderate","Moderate"]],"caption_candidate":"Title: Volpara Imaging Software 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p7-t0","doc_id":"K153427","page_num":7,"bbox":[72.24,49.8,534.46,99.86],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","mtk1956-007-6","Rev. Date:","26th Dec 2015"],["","DMS Ref:","Eng/Angel","","Page 4 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K153427-p8-t0","doc_id":"K153427","page_num":8,"bbox":[72.22,49.8,534.46,99.86],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","mtk1956-007-6","Rev. Date:","26th Dec 2015"],["","DMS Ref:","Eng/Angel","","Page 5 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K160088-p6-t0","doc_id":"K160088","page_num":6,"bbox":[72.03,377.59,562.54,712.8],"n_rows":8,"n_cols":8,"columns":["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],"rows":[["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],["","","","","","Nederland B.V.","",""],["Trade Name","","Cydar EV","","","VesselNavigator","",""],["","","(Subject device)","","","(Predicate device)","",""],["510(k)\nNumber","K160088","","","K151598","","","N/A"],["Product Code","OWB","","","OWB / LLZ","","","Similar; the Product\nCode LLZ is not\nconsidered as\nproduct is not a\nPACS system"],["Regulation\nNumber","892.1650","","","892.1650 / 892.2050","","","Similar; the\nregulation number\n892.2050 is not\nconsidered as\nproduct is not a\nPACS system"],["Regulation\nName","Interventional Fluoroscopic X-\nRay System","","","Interventional Fluoroscopic X-Ray\nSystem / Picture Archiving and","","","Similar; the\nregulation number"]],"caption_candidate":"Table 5A – Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K160088-p7-t0","doc_id":"K160088","page_num":7,"bbox":[72.03,58.51,562.54,706.08],"n_rows":9,"n_cols":8,"columns":["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],"rows":[["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],["","","","","","Nederland B.V.","",""],["Trade Name","","Cydar EV","","","VesselNavigator","",""],["","","(Subject device)","","","(Predicate device)","",""],["","","","","Communications System","","","892.2050, PACS, is\nnot considered as\nproduct is not a\nPACS system"],["Intended use","Display of combined live 2D X-\nray fluoroscopy and 3D\nanatomy for image guidance\nduring surgery.","","","Display of combined live 2D X-ray\nfluoroscopy and 3D anatomy for\nimage guidance during surgery.","","","Identical"],["3D imaging","Pre-operative","","","Pre-operative","","","Identical"],["X-ray\nfluoroscopy","Live","","","Live","","","Identical"],["Indications for\nUse","Cydar EV provides image\nguidance by overlaying\npreoperative 3D vessel\nanatomy, from a previously\nacquired contrast-enhanced,\ndiagnostic CT scan, onto live\nfluoroscopic images in order\nto assist in the positioning of\nguidewires, catheters and\nother endovascular devices.\nCydar EV is intended to assist\nfluoroscopy-guided\nendovascular procedures in\nthe lower thorax, abdomen\nand pelvis. Suitable\nprocedures include (but are\nnot limited to) endovascular\naortic aneurysm repair (AAA\nand mid-distal TAA),\nangioplasty, stenting and\nembolization in the common\niliac, proximal external iliac\nand proximal internal iliac\narteries and corresponding","","","VesselNavigator provides image\nguidance by superimposing live\nfluoroscopic images on a 3D\nvolume of the vessel anatomy to\nassist in catheter maneuvering\nand device placement.\nVesselNavigator is intended to\nassist in the treatment of\nendovascular diseases during\nprocedures such as (but not\nlimited to) AAA, TAA, carotid\nstenting, iliac interventions.","","","Similar; indications\nfor both devices\nemphasize image\nguidance for\nfluoroscopy-guided\nendovascular\nprocedures"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K160088-p8-t0","doc_id":"K160088","page_num":8,"bbox":[72.03,58.51,562.54,703.08],"n_rows":10,"n_cols":8,"columns":["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],"rows":[["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],["","","","","","Nederland B.V.","",""],["Trade Name","","Cydar EV","","","VesselNavigator","",""],["","","(Subject device)","","","(Predicate device)","",""],["","veins.\nCydar EV is not intended for\nuse in the X-ray guided\nprocedures in the liver,\nkidneys or pelvic organs.","","","","","",""],["Construction","Software product","","","Software product","","","Identical"],["Host\ncomputer","Separate interventional tools\nworkstation","","","Separate interventional tools\nworkstation","","","Identical"],["Registration\nOverview","2D-3D registration is achieved\nby machine vision tracking of\nvertebral anatomy","","","2D-3D registration is achieved by\nmanual initialization and/or\ncorrection followed by dead\nreckoning based on\nelectromechanical tracking of\ntable and C-arm","","","Different; the\npredicate and\nsubject devices use\ndifferent methods\nto perform the\nunderlying 2D-3D\nimage registrations\nthough viewing of\nthe image overlay\nfunctionality is\nthen performed the\nsame with no\nadditional\nquestions raised for\nsafety or efficacy"],["Registration\ntarget","Vertebral anatomy","","","X-ray C-arm and operating table","","","Different; targets\nreflect different\nregistration\nmethods with the\nimage overlay\nfunctionality being\nthe same with no\nadditional\nquestions raised for\nsafety or efficacy"],["Patient\ncontacting","No","","","No","","","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K160088-p9-t0","doc_id":"K160088","page_num":9,"bbox":[72.03,58.51,562.53,717.72],"n_rows":13,"n_cols":11,"columns":["Manufacturer","","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences","",""],"rows":[["Manufacturer","","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences","",""],["","","","","","","Nederland B.V.","","","",""],["Trade Name","","","Cydar EV","","","VesselNavigator","","","",""],["","","","(Subject device)","","","(Predicate device)","","","",""],["Energy\nemitted or\nabsorbed","","No","","","No","","","Identical","",""],["Dynamic\nupdate on C-\narm / table\nmotion","","Automatic","","","Automatic","","","Identical","",""],["Dynamic\nupdate on\npatient\nmotion","","Automatic","","","Semi-automatic based on\nmovement of the gantry","","","Similar; automatic\nresponse to patient\nmotion allows\nregistration to\ncontinuously occur\nwith no additional\nquestions raised for\nsafety or efficacy","",""],["Anatomical\nLocation","","Vascular anatomy of the\nchest, abdomen and pelvis.","","","All vascular anatomy except\ncoronaries and intracranial\nvessels","","","Similar; the subject\ndevice is restricted\nto anatomy\nconsidered\nimmobile with\nrespect to the\nvertebral column\nwith no additional\nquestions raised for\nsafety or efficacy","",""],["Ability to\nstore\nroadmaps","","Yes","","","Yes","","","Identical","",""],["Ability to\nstore\nsnapshots","","Yes","","","Yes","","","Identical","",""],["","Non-clinical performance data","","","","","","","","",""],["IEC 62304","","Applied","","","Applied","","","Identical","",""],["IEC 62366","","Applied","","","Applied","","","Identical","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K160088-p10-t0","doc_id":"K160088","page_num":10,"bbox":[72.05,58.51,562.52,213.84],"n_rows":6,"n_cols":8,"columns":["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],"rows":[["Manufacturer","Cydar Ltd","","","","Philips Medical Systems","","Significant\nDifferences"],["","","","","","Nederland B.V.","",""],["Trade Name","","Cydar EV","","","VesselNavigator","",""],["","","(Subject device)","","","(Predicate device)","",""],["ISO 14971","Applied","","","Applied","","","Identical"],["NEMA PS 3.1-\n3.20\nDICOM","Applied","","","Applied","","","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161148-p5-t0","doc_id":"K161148","page_num":5,"bbox":[70.88,249.95,293.39,445.09],"n_rows":7,"n_cols":2,"columns":["Name:","icometrix NV"],"rows":[["Name:","icometrix NV"],["Address:","Tervuursesteenweg 244\nB-3001 Leuven\nBelgium"],["Contact Person:","Dirk Loeckx"],["Telephone number:","+32 16 369 000"],["Fax Number:","N.A."],["E-mail:","dirk.loeckx@icometrix.com"],["Date Prepared:","21 Jun 2016"]],"caption_candidate":"5.1 Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161148-p5-t1","doc_id":"K161148","page_num":5,"bbox":[70.88,496.09,347.32,639.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","icobrain"],"rows":[["Device Trade Name:","icobrain"],["Common Name","Medical Image Processing Software"],["Classification Name","System, Image processing, Radiological"],["Number","892.2050"],["Product Code:","LLZ"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161148-p6-t0","doc_id":"K161148","page_num":6,"bbox":[70.88,121.88,299.44,260.11],"n_rows":3,"n_cols":2,"columns":["Device","TM\nNeuroQuant"],"rows":[["Device","TM\nNeuroQuant"],["510(k) Number","K061855"],["Manufacturer","CorTechs Labs, Inc.\n4690 Executive Drive, Suite 250\nSan Diego, CA 92121\nUSA"]],"caption_candidate":"5.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161201-p5-t0","doc_id":"K161201","page_num":5,"bbox":[66.6,251.64,509.4,553.14],"n_rows":3,"n_cols":5,"columns":["","Predicate:\nsyngo.CT Lung\nCAD (Siemens\nAG Medical\nSolutions)\nK143196","Predicate:\nsyngo.PET &\nCT Oncology\n(Siemens AG\nMedical\nSolutions)\nK093621","Predicate:\nClearRead\nBone\nSuppression\n(Riverain\nTechnologies)\nK092363","Subject Device:\nClearRead CT\n(Riverain\nTechnologies)"],"rows":[["","Predicate:\nsyngo.CT Lung\nCAD (Siemens\nAG Medical\nSolutions)\nK143196","Predicate:\nsyngo.PET &\nCT Oncology\n(Siemens AG\nMedical\nSolutions)\nK093621","Predicate:\nClearRead\nBone\nSuppression\n(Riverain\nTechnologies)\nK092363","Subject Device:\nClearRead CT\n(Riverain\nTechnologies)"],["Product Code","OEB","LLZ","LLZ","OEB/LLZ"],["Intended Use","Computer-aided\ndetection tool\ndesigned to\nassist\nradiologists in\nthe detection of\nsolid pulmonary\nnodules during\nreview of\nMDCT\nexaminations of\nthe chest","Viewing,\nmanipulation,\n3D-\nVisualization,\nand\ncomparison\nof medical\nimages from\nmultiple\nimaging\nmodalities.","Generating\nbone\nsuppressed\nimage from\nan original\nPA/AP chest\nradiograph","Computer\nassisted reading\ntools designed to\naid the\nradiologist in the\ndetection of\npulmonary\nnodules during\nreview of CT\nexaminations of\nthe chest"]],"caption_candidate":"effectiveness of ClearRead CT for its intended use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161322-p8-t0","doc_id":"K161322","page_num":8,"bbox":[108.21,111.48,539.76,672.48],"n_rows":7,"n_cols":4,"columns":["Attribute","CT CoPilotTM","NeuroQuant","Equivalence"],"rows":[["Attribute","CT CoPilotTM","NeuroQuant","Equivalence"],["510(k)","(Subject Device)","K061855",""],["Product Code","LLZ","LLZ","Yes"],["Intended Use","CT CoPilotTM is\nintended for automatic\nlabeling, visualization\nand volumetric\nquantification of\nsegmentable structures\nfrom sets of CT images\nof the brain. This\nsoftware is intended to\nautomate the current\nmanual process of\nidentifying, labeling\nand quantifying\nstructures identified on\nCT images of the brain\nand to provide\nautomated registration\nand reformatting of\ndata.","NeuroQuantTM is intended\nfor automatic labeling,\nvisualization and\nvolumetric quantification\nof segmentable brain\nstructures from sets of MR\nimages. This software is\nintended to automate the\ncurrent manual process of\nidentifying, labeling and\nquantifying the volume of\nsegmental brain structures\nidentified on MR images.","Yes"],["Data Source","CT Scanner","MRI Scanner","Different"],["Display\nimages","Reformatted, realigned\naxial, coronal, and sagittal\nimages.","Reformatted, realigned\naxial, coronal and sagittal\nimages.","Yes"],["Quantitative\nMetrics","CSF volumes, Intracranial\nvolume, Midline shift.","CSF volumes, Intracranial\nvolume, Brain structure\nvolumes.","Similar"]],"caption_candidate":"Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161322-p9-t0","doc_id":"K161322","page_num":9,"bbox":[108.22,85.08,539.76,575.52],"n_rows":14,"n_cols":4,"columns":["Physical\nCharacteristic\ns","• Software package\n• Operates off-the-shelf\nsoftware (multiple\nvendors)","• Software package\n• Operates off-the-shelf\nsoftware (multiple\nvendors)","Yes"],"rows":[["Physical\nCharacteristic\ns","• Software package\n• Operates off-the-shelf\nsoftware (multiple\nvendors)","• Software package\n• Operates off-the-shelf\nsoftware (multiple\nvendors)","Yes"],["Operating\nSystem","OS:Linux","OS: Linux,Mac,Windows","Yes"],["DICOM\ncompatible","Yes","Yes","Yes"],["Performance\nmeasurement\nTesting","Reproducibility and\nAccuracy testing","Reproducibility and\nAccuracy testing","Yes"],["Safety","Measurement data can be\nviewed, accepted or\nrejected by a physician","Measurement data can be\nviewed, accepted or\nrejected by a physician","Yes"],["In plane voxel\nResolution\n(Input Data)","0.1-1mm","1mm","Similar"],["Slice\nThickness\n(Input Data)","0.2-1mm","1.2mm","Similar"],["Automatic\nAlignment","Yes","Yes","Yes"],["Registration\nTarget Data","Atlas, Prior","Atlas","Similar"],["Skull\nStripping","Yes","Yes","Yes"],["Automatic\nSegmentation","Yes","Yes","Yes"],["Error\nDetection","Yes","Yes","Yes"],["Output Image\nData Format","3D Volumetric, 2D MPR\n-1mm isotropic volume\n-1-5mm thick MPR","3D Volumetric\n-1mm isotropic volume","Similar"],["Color-coded\nSegmentation\nSeries\n(Output Data)","Yes","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161382-p5-t0","doc_id":"K161382","page_num":5,"bbox":[95.6,258.63,530.44,549.91],"n_rows":12,"n_cols":4,"columns":["","Devices","",""],"rows":[["","Devices","",""],["","","",""],["","Submitted Device","Predicate Device","Predicate Device"],["Features/Characteristics","LVivo (Diacardio)","LVivoEF (Diacardio)","Syngo (Siemens)"],["Product Code","LLZ","LLZ","LLZ (K091286)\nIYN( K072090)"],["Intended Use","Calculate of\nEjection Fraction\nand measure\nstrain","Calculate of\nEjection Fraction","Calculate Ejection\nFraction and\nmeasure strain"],["Automation","Fully Automated","Fully Automated","Fully Automated"],["Bi plane EF evaluation","YES","YES","YES"],["Simultaneous 2CH and\n4CH evaluation","YES","YES","NO"],["Off line EF evaluation\nusing DICOM clips of\nany vendor","YES","YES","YES"],["Automated ED and ES\nframes selection","YES","YES","YES"],["Dynamic left ventricular\nassessment","YES. Frame by\nframe tracking","YES. Frame by\nframe tracking","YES. Frame by frame\ntracking"]],"caption_candidate":"calculated for biplane EF (r=0.88, p<0001).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K161959-p6-t0","doc_id":"K161959","page_num":6,"bbox":[102.62,497.47,544.66,700.42],"n_rows":8,"n_cols":3,"columns":["Product","BCAD (K050846)","ClearView cCAD"],"rows":[["Product","BCAD (K050846)","ClearView cCAD"],["Characteristics","Software for automated analysis of\nbreast ultrasound lesions.","Software for automated analysis of\nbreast ultrasound lesions."],["Intended Use","Computer aided analysis tool\nintended to assist skilled physicians\nin screening and diagnosis as well as\ncompliance with ACR BI-RADS®\nultrasound lexicon form.","Computer aided analysis tool\nintended to assist skilled physicians\nin screening and diagnosis as well as\ncompliance with ACR BI-RADS®\nultrasound lexicon form."],["Physical\nCharacteristics","Software Package\nOperates on off-the-shelf hardware","Software Package\nOperates on off-the-shelf hardware"],["Computer","PC compatible","PC compatible"],["Operating\nSystem","Windows XP, Windows 2000","Windows 7, and higher, Windows\nEmbedded"],["Storage","Storage not supported","Storage not supported"],["Image Input","DICOM","DICOM"]],"caption_candidate":"6. Substantial Equivalence Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K162830-p6-t0","doc_id":"K162830","page_num":6,"bbox":[66.61,466.99,545.5,711.58],"n_rows":4,"n_cols":5,"columns":["","SIS Software","Medtronic\nNavigation,\nInc.'s\nStealth Viz\nAdvanced\nPlanning\nApplication with\nStealthDTI\nPackage\n(K081512)","Medtronic\nNavigation,\nInc.’s\nStealthStation\n(K050438)","Braindreader\nApS’\nNeuroReader\nMedical\nImage\nProcessing\nSoftware\n(K140828)"],"rows":[["","SIS Software","Medtronic\nNavigation,\nInc.'s\nStealth Viz\nAdvanced\nPlanning\nApplication with\nStealthDTI\nPackage\n(K081512)","Medtronic\nNavigation,\nInc.’s\nStealthStation\n(K050438)","Braindreader\nApS’\nNeuroReader\nMedical\nImage\nProcessing\nSoftware\n(K140828)"],["Allows for importing of\ndigital imaging sets","Yes","Yes","Yes","Yes"],["Uses proprietary\nsoftware algorithm to\ngenerate 3D segmented\nanatomical models from\npatient’s MR scans","Yes","Yes","Yes","Yes"],["Allows for review and\nanalysis of data in\nvarious 2D and 3D\npresentation formats","Yes","Yes","Yes","Yes"]],"caption_candidate":"SIS Software Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K162830-p7-t0","doc_id":"K162830","page_num":7,"bbox":[66.61,72.36,545.5,375.17],"n_rows":5,"n_cols":5,"columns":["","SIS Software","Medtronic\nNavigation,\nInc.'s\nStealth Viz\nAdvanced\nPlanning\nApplication with\nStealthDTI\nPackage\n(K081512)","Medtronic\nNavigation,\nInc.’s\nStealthStation\n(K050438)","Braindreader\nApS’\nNeuroReader\nMedical\nImage\nProcessing\nSoftware\n(K140828)"],"rows":[["","SIS Software","Medtronic\nNavigation,\nInc.'s\nStealth Viz\nAdvanced\nPlanning\nApplication with\nStealthDTI\nPackage\n(K081512)","Medtronic\nNavigation,\nInc.’s\nStealthStation\n(K050438)","Braindreader\nApS’\nNeuroReader\nMedical\nImage\nProcessing\nSoftware\n(K140828)"],["Performs image fusion of\ndatasets using\nautomated or manual\nimage matching\ntechnique","Yes; atlas-based\nmapping (patient\nspecific);\nreference\ndatabase","Yes; atlas-based\nmapping","Yes, atlas-based\nmapping","Yes; reference\ndatabase"],["Segments structures in\nimages with manual and\nautomated tools and\nconverts them into 3D\nobjects for display","Yes","Yes","Yes","Yes"],["Creates hybrid datasets\nby filing in segmented\nregions slice-by-slice on\nanatomical datasets","Yes","Yes","Yes","Yes"],["Exports results to\nplanning system","Yes","No","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K163253-p4-t0","doc_id":"K163253","page_num":4,"bbox":[66.48,115.2,540.03,239.52],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Arterys Inc."],"rows":[["510(k) Sponsor","Arterys Inc."],["Address","51 Federal St. Suite 305\nSan Francisco, CA 94107"],["Correspondence Person","Golnaz Moeini, RAC\nDirector of Quality and Regulatory\nArterys Inc."],["Contact Information","Email: quality@arterys.com\nPhone: 408-504-3187"],["Date Prepared","11/17/2016"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p4-t1","doc_id":"K163253","page_num":4,"bbox":[66.48,286.08,540.03,366.24],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Arterys Cardio DL"],"rows":[["Proprietary Name","Arterys Cardio DL"],["Common Name","Arterys Cardio DL"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p4-t2","doc_id":"K163253","page_num":4,"bbox":[66.48,426.72,540.03,510.24],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Arterys Software v2.0"],"rows":[["Proprietary Name","Arterys Software v2.0"],["Premarket Notification","K162513"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"Primary Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p4-t3","doc_id":"K163253","page_num":4,"bbox":[66.48,538.32,540.03,623.04],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Medis Imaging QMass"],"rows":[["Proprietary Name","Medis Imaging QMass"],["Premarket Notification","K140587"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"Secondary Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p5-t0","doc_id":"K163253","page_num":5,"bbox":[70.56,103.2,541.44,489.84],"n_rows":27,"n_cols":3,"columns":["The following visualization, quantification and data-reporting functionalities are provided by the","",""],"rows":[["The following visualization, quantification and data-reporting functionalities are provided by the","",""],["software:","",""],["","",""],["Visualization:","",""],["","- 2D image review",""],["","- 3D image review by means of MIP, Surface MinIP, Surface or Average",""],["","- Multi-planer reconstruction (MPR) views (axial, coronal and sagittal)",""],["","- Image navigation tools",""],["","- Cine play",""],["","- Cardiac views",""],["","",""],["Quantification:","",""],["","- Anatomy and tissue segmentation",""],["","- Distance and area measurements",""],["","- Cardiac function quantification including stroke volume, ejection fraction, cardiac output,",""],["","end-diastolic mass and volume, end-systolic mass and volume",""],["","- Flow quantification, including net flow, forward flow, reverse flow, regurgitation",""],["","fraction, pressure gradient and primary flow direction, at user-specified locations where",""],["","contours have been created (e.g. aortic valve, pulmonary valve, mitral valve, tricuspid",""],["","valve, superior vena cava)",""],["","- Phase correction",""],["","",""],["Data reporting:","",""],["The distance, area, volume, and blood flow statistics, along with user-selected, annotated images,","",""],["are displayed to the user within the software client web browser. The user has the option to save","",""],["the data for later use. The user can also send the data to the clinician database, such as PACS, for","",""],["review.","",""]],"caption_candidate":"adolescent) and adult populations.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p6-t0","doc_id":"K163253","page_num":6,"bbox":[87.37,100.48,524.56,712.05],"n_rows":12,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],"rows":[["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],["Operating System","Linux","Linux","Not Applicable"],["Platform","Client-server, Chrome\nDesktop","Client-server, Chrome\nDesktop","Not Applicable"],["Scanners","Both 1.5T and 3.0T","Both 1.5T and 3.0T","Not Applicable"],["Image input","Supports DICOM 3.0","Supports DICOM 3.0","Not Applicable"],["Data acquisition\nprotocol for flow\nand volume analysis","Cardiovascular\nimages: multi-phase,\nmulti-slice and\nvelocity encoded\nimages acquired from\nMRI scanners","Cardiovascular\nimages: multi-phase,\nmulti-slice and\nvelocity encoded\nimages acquired from\nMRI scanners","Not Applicable"],["Workflows","Basic 2D, Basic 3D,\n4D Flow, 2D Phase\nContrast","Basic 2D, Basic 3D,\n4D Flow, 2D Phase\nContrast","Not Applicable"],["Image display mode","Static and cine","Static and cine","Not Applicable"],["Image Navigation\nTools","Pan, zoom, rotate,\nmaximize/minimize,\nslice scroll (view\nmultiple slices),\nadjust window/level,\nslab thickness, flow\ndirection and time\nscroll (view multiple\nphases), image ROI\nplacement; automated\n2D ROI (with edit\nfunctions); 2D speed\ncolor map.","Pan, zoom, rotate,\nmaximize/minimize,\nslice scroll (view\nmultiple slices),\nadjust window/level,\nslab thickness, flow\ndirection and time\nscroll (view multiple\nphases), image ROI\nplacement; automated\n2D ROI (with edit\nfunctions); 2D speed\ncolor map.","Not Applicable"],["3D (volume\nrendered) image\nreview","Yes","Yes","Not Applicable"],["Cardiac View","Yes","Yes","Not Applicable"],["Orientation label","Yes","Yes","Not Applicable"]],"caption_candidate":"6. Comparison of Technological Characteristics with the Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p7-t0","doc_id":"K163253","page_num":7,"bbox":[87.37,62.24,524.56,693.57],"n_rows":13,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],"rows":[["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],["Cross-reference\nindicator","Yes","Yes","Not Applicable"],["View DICOM data","Yes, users can view\nthe DICOM\ninformation about the\npatient, study and\ncurrent image","Yes, users can view\nthe DICOM\ninformation about the\npatient, study and\ncurrent image","Not Applicable"],["Secondary Capture","Yes","Yes","Not Applicable"],["Segmentation of\nregion of interest","Manual and semi-\nautomatic","Manual and semi-\nautomatic","Not Applicable"],["Phase error\ncorrection","Yes","Yes","Not Applicable"],["Quantitative\nAnalysis, flow","Yes, 4D Flow and 2D\nPhase Contrast","Yes, 4D Flow and 2D\nPhase Contrast","Not Applicable"],["Quantitative\nAnalysis, area","Yes","Yes","Not Applicable"],["Quantitative\nAnalysis, distance","Yes","Yes","Not Applicable"],["Quantitative\nAnalysis, Volume in\n4D Flow Workflow","Yes","Yes","Not Applicable"],["Quantitative\nAnalysis, Volume in\n3D Workflow for a\nshort axis stack","Yes","Not Applicable","Yes"],["Directional/vector\ndisplay of the blood\nparticle travel","Yes","Yes","Not Applicable"],["Flow quantification\nof valves","Yes","Yes","Not Applicable"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163253-p8-t0","doc_id":"K163253","page_num":8,"bbox":[87.41,62.24,524.56,214.29],"n_rows":2,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],"rows":[["Feature/\nFunction","Proposed Device:\nArterys Cardio DL","Primary Predicate\nDevice:\nArterys Software v2.0\n(K162513)","Secondary Predicate\nDevice:\nMedis Imaging\nQMass\n(K140587)"],["Automatic selection\nof the Temporal\nLandmark time\npoints","Yes","Yes","Not Applicable"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163623-p5-t0","doc_id":"K163623","page_num":5,"bbox":[56.43,520.2,555.67,706.92],"n_rows":4,"n_cols":8,"columns":["","","Quantra","","","Quantra","","Comparison"],"rows":[["","","Quantra","","","Quantra","","Comparison"],["","","SW Version 2.1","","","SW Version 2.2","",""],["","","Predicate (K142037)","","","(Proposed)","",""],["Indications\nfor Use","Quantra™ is a software\napplication intended for use with\nimages acquired using digital\nbreast x-ray systems. Quantra\ncalculates volumetric breast\ndensity as a ratio of\nfibroglandular tissue and total\nbreast volume estimates.\nQuantra also provides area\nbreast density as a ratio of","","","The Quantra™ software\napplication is intended for use\nwith mammographic images\nacquired using digital breast x-\nray systems. The Quantra\nsoftware segregates breast\ndensity into categories, which\nmay be useful in the reporting of\nconsistent BI-RADS® breast\ncomposition categories as","","","Similar"]],"caption_candidate":"Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163623-p6-t0","doc_id":"K163623","page_num":6,"bbox":[56.4,72.24,555.72,713.16],"n_rows":6,"n_cols":4,"columns":["","fibroglandular tissue area and\ntotal breast area estimates.\nQuantra segregates breast\ndensity into categories, which\nmay be useful in the reporting of\nconsistent BI-RADS® breast\ncomposition categories as\nmandated by certain state\nregulations. The Quantra results\nfor each image, breast, and\nsubject, are intended to aid\nradiologists in the assessment of\nbreast tissue composition.\nQuantra produces adjunctive\ninformation; it is not an\ninterpretive or diagnostic aid.","mandated by certain state\nregulations. The Quantra\nsoftware reports a result for each\nsubject, which is intended to aid\nradiologists in the assessment of\nbreast tissue composition. The\nQuantra software produces\nadjunctive information; it is not\na diagnostic aid.",""],"rows":[["","fibroglandular tissue area and\ntotal breast area estimates.\nQuantra segregates breast\ndensity into categories, which\nmay be useful in the reporting of\nconsistent BI-RADS® breast\ncomposition categories as\nmandated by certain state\nregulations. The Quantra results\nfor each image, breast, and\nsubject, are intended to aid\nradiologists in the assessment of\nbreast tissue composition.\nQuantra produces adjunctive\ninformation; it is not an\ninterpretive or diagnostic aid.","mandated by certain state\nregulations. The Quantra\nsoftware reports a result for each\nsubject, which is intended to aid\nradiologists in the assessment of\nbreast tissue composition. The\nQuantra software produces\nadjunctive information; it is not\na diagnostic aid.",""],["Level of\nConcern","Moderate","Moderate","Same"],["Input\nModality","Digital x-ray breast images","Digital x-ray breast images","Same"],["Software\nProduct","Yes","Yes","Same"],["Reportable\nInformation","• Fibroglandular (dense)\nTissue Volume\n• Total Breast Volume\n• Volumetric Breast Density\n• Area Breast Density\n• Volume of Fibroglandular\nTissue Score\n• Volumetric Breast Density\nScore\n• Estimate of Breast Density\n(integer)\n• Estimate of Breast Density\n(fractional)","• Quantra Generated Breast\nDensity Category","Similar. Uses\ndistribution of\nglandular\ntissue rather\nthan density of\nglandular\ntissue when\nassessing\nbreast\ncomposition."],["Statistical\ncomparison\nto a\nreference\npopulation","Yes","Yes","Same, with the\nproposed\ndevice also\nbeing\ncompared\nagainst a"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163623-p7-t0","doc_id":"K163623","page_num":7,"bbox":[56.4,72.24,555.72,205.44],"n_rows":3,"n_cols":4,"columns":["","","","dataset scored\nto BI-RADS\n5th edition."],"rows":[["","","","dataset scored\nto BI-RADS\n5th edition."],["BI-RADS®\nAtlas","Yes, 4th Edition 2003","Yes, 5th Edition 2013","Similar, with\nenhancements"],["Brest\nComposition\nEstimates","Yes, displayed as 1, 2, 3 and 4","Yes, displayed as a, b, c, d","Similar, with\nenhanced\naccuracy"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163623-p7-t1","doc_id":"K163623","page_num":7,"bbox":[94.53,351.96,425.88,465.0],"n_rows":8,"n_cols":11,"columns":["","Quantra 2.2- QDC 2D","","","","","","","","",""],"rows":[["","Quantra 2.2- QDC 2D","","","","","","","","",""],["BI-RADS- 5th\nEd.","","","","Fatty","","","Dense","","Per category\ntotal","Accuracy"],["","","","","(a+b)","","","(c+d)","","",""],["","Fatty","","105","","","8","","","113","92.9%"],["","(a+b)","","","","","","","","",""],["","Dense","","1","","","116","","","117","99.1%"],["","(c+d)","","","","","","","","",""],["","","","","","","Total","","","230",""]],"caption_candidate":"Quantra 2.2 2D Fatty vs. Dense","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K163623-p7-t2","doc_id":"K163623","page_num":7,"bbox":[94.53,503.4,419.88,616.2],"n_rows":6,"n_cols":11,"columns":["","Quantra2.2 – QDC Tomo (3D Center Projection)","","","","","","","","",""],"rows":[["","Quantra2.2 – QDC Tomo (3D Center Projection)","","","","","","","","",""],["BI-RADS- 5th\nEd.","","","","Fatty","","","Dense","","Per category\ntotal","Accuracy"],["","","","","(a+b)","","","(c+d)","","",""],["","Fatty\n(a+b)","","104","","","9","","","113","92.0%"],["","Dense\n(c+d)","","7","","","110","","","117","94.0%"],["","","","","","","Total","","","230",""]],"caption_candidate":"Quantra 2.2 Tomo Fatty vs. Dense","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170069-p7-t0","doc_id":"K170069","page_num":7,"bbox":[102.39,151.7,532.42,712.92],"n_rows":11,"n_cols":6,"columns":["Device","Proposed Device","","Primary Predicate","","Reference Device"],"rows":[["Device","Proposed Device","","Primary Predicate","","Reference Device"],["","","","Device","",""],["","AmCAD-UV","","QLAB Quantification","","ClearViewHD"],["","","","Software","",""],["Manufacturer","AmCad BioMed\nCorp.","Philips Ultrasound,\nInc.","","","ClearView\nDiagnostics Inc."],["510(k)\nNumber","K170069","K132165","","","K140139"],["Device\nCommon\nName","Picture archiving and\ncommunications\nsystems","Same","","","Image Enhancement\nSystem"],["Regulation\nNumber","21 CFR 892.2050 -\nClass II","Same","","","Same"],["Regulation\nName","Picture archiving and\ncommunications\nsystem","Picture archiving and\ncommunications\nsystem, workstation","","","Picture archiving and\ncommunication\nsystem"],["Product Code","LLZ","Same","","","Same"],["Indications for\nUse/Intended\nUse","AmCAD-UV is a\nsoftware device\ndesigned for\nclassifying the\nultrasonic color\nintensity data and\nallowing users to\nview classified\ncolor-coded signals,\nnamely, primary\npulsatile, secondary\npulsatile, and\nunidentified signals\nof flow Doppler\nultrasound images. It\nis intended as a\ngeneral-purpose\nmedical image\nprocessing tool for\nvascular pulsatility\nanalysis but must not","QLAB Quantification\nsoftware is a\nsoftware application\npackage. It is\ndesigned to view and\nquantify image data\nacquired on Philips\nHealthcare\nultrasound products.\nThe software allows\nusers to examine\ntissue Doppler\nimaging and provides\na tool for drawing\nregions of interest\nthat measure the\nmyocardial velocity,\nstrain, strain rate,\nand displacement\nalong those regions\nin the myocardium","","","The ClearView Image\nEnhancement\nSystem is intended\nfor use by a qualified\ntechnician or\ndiagnostician to\nreduce speckle noise,\nenhance contrast\nand transfer\nultrasound images.\nThe software\nprovides a\nDICOM-compliant\nClearViewHD-enhanc\ned image along with\nthe original\nultrasound image to\nassist in image\ninterpretation by the\ntrained physician.\nClearViewHD is"]],"caption_candidate":"Table 1.6.1 – The substantial equivalence comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170069-p8-t0","doc_id":"K170069","page_num":8,"bbox":[102.41,79.7,532.39,711.6],"n_rows":6,"n_cols":6,"columns":["Device","Proposed Device","","Primary Predicate","","Reference Device"],"rows":[["Device","Proposed Device","","Primary Predicate","","Reference Device"],["","","","Device","",""],["","AmCAD-UV","","QLAB Quantification","","ClearViewHD"],["","","","Software","",""],["","be used alone for\nprimary diagnostic\ninterpretation.","(excerpted from\nQLAB User Manual).","","","intended for use by a\nqualified\ntechnologist for\ntransfer and\nenhancement of\nultrasound images\nfrom a variety of\ndiagnostic systems."],["Functional\nCapability of\nImage\nProcessing","The device provides\ndual images for\nviewing original\ndynamic f and\nclassified color-coded\nsignals of flow\nDoppler ultrasound\nimages. The device\nalso provides a trend\nchart for displaying\nwaveforms of\npulsatile intensity\nchanges with\nsummarized\nstatistics. It is\nintended as a\ngeneral-purpose\nmedical image\nprocessing tool for\nvascular pulsatility\nanalysis, such as flow\nvelocity and flow\nenergy, over a\nnumber of cardiac\ncycles. AmCAD-UV\ncan export the\nquantified values of\nthe classified\npulsatile signals in\ntext format and\nexport the sequence","The software can\ndisplay the dynamic\nintensity information\nas color-coded image\nand provide a chart\nfor displaying the\nintensity changes\nover time on a\nwaveform, which is\nable to evaluate the\nperiodic strain\nfluctuation in\nmyocardial tissue\nmotion over a\nnumber of cardiac\ncycles.","","","The software\ngenerates an\nenhanced image\nwith reduced speckle\nnoise and improved\ncontrast\nenhancement for\nviewing and\ndiagnosing."]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-27152181","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170069-p9-t0","doc_id":"K170069","page_num":9,"bbox":[102.4,79.7,532.4,714.24],"n_rows":7,"n_cols":6,"columns":["Device","Proposed Device","","Primary Predicate","","Reference Device"],"rows":[["Device","Proposed Device","","Primary Predicate","","Reference Device"],["","","","Device","",""],["","AmCAD-UV","","QLAB Quantification","","ClearViewHD"],["","","","Software","",""],["","of color-coded\npulsatile images and\nthe waveform trend\nchart in Bitmap\n(*.bmp) and JPEG\n(*.jpg or\n*.jpeg)formats.","","","",""],["Software\nDesign/\nExample","Based on\nclassification method\nof ultrasonic color\nintensity data\ncontained in the\ndynamic flow\nDoppler ultrasound\nimages (i.e. color and\npower Doppler\nultrasound images).","Based on the strain\nrate method of\nvelocity of\nmyocardial tissue\nmotion contained in\nthe dynamic tissue\nDoppler images.","","","Based on a core\nnoise reduction and\ncontrast\nenhancement\nalgorithm in\ngray-scale ultrasound\nimages."],["Output\nGenerated by\nthe Device/\nExample","AmCAD-UV allows\nusers to view\nclassified color-coded\nsignals, namely,\nprimary pulsatile,\nsecondary pulsatile,\nand unidentified\nsignals of flow\nDoppler ultrasound\nimages and trend\nchart of intensity\nchanges over time on\na waveform. The\ndevice exports the\nquantified values of\nthe classified","The software can\ndisplay the dynamic\nintensity information\nas color-coded image\nand export the\nintensity changes\nover time on a\nwaveform.","","","The software can\ndisplay an image\nwith enhanced\ncontrast and reduced\nnoise."]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-27152181","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170069-p10-t0","doc_id":"K170069","page_num":10,"bbox":[102.4,79.7,532.4,713.52],"n_rows":7,"n_cols":6,"columns":["Device","Proposed Device","","Primary Predicate","","Reference Device"],"rows":[["Device","Proposed Device","","Primary Predicate","","Reference Device"],["","","","Device","",""],["","AmCAD-UV","","QLAB Quantification","","ClearViewHD"],["","","","Software","",""],["","pulsatile signals in\ntext format and\nexports the\nsequence of\ncolor-coded pulsatile\nimages and the\nwaveform trend\nchart in Bitmap\n(*.bmp) and JPEG\n(*.jpg or\n*.jpeg)formats.","","","",""],["Meaning of\nColor Pixels in\nthe Output","The classified\ncolor-coded signals\nof flow Doppler\nultrasound images\nindicate different\nintensity values\ndefined by the scale\nof the color bar.","The color pixels in\nthe virtual trace\nimage indicate\ndifferent values of\nmyocardial tissue\nmotion information\ndefined by the scale\nof the color bar.","","","Not available."],["Meaning of\nFluctuation in\nthe Waveform","The trends of\nintensity changes\nover a sequence of\nframes is used for\nevaluation of the\nperiodic fluctuation\nin vascular pulsatility\nover a number of","The trends of\nmyocardial\ninformation at the\nuser-selected specific\npoints for evaluation\nof the periodic\nfluctuation in\nmyocardial tissue","","","Not available."]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-27152181","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170069-p11-t0","doc_id":"K170069","page_num":11,"bbox":[102.4,79.7,532.41,449.35],"n_rows":9,"n_cols":6,"columns":["Device","Proposed Device","","Primary Predicate","","Reference Device"],"rows":[["Device","Proposed Device","","Primary Predicate","","Reference Device"],["","","","Device","",""],["","AmCAD-UV","","QLAB Quantification","","ClearViewHD"],["","","","Software","",""],["","cardiac cycles.","motion over a\nnumber of cardiac\ncycles.","","",""],["Measurement","Average, maximum,\nand minimum values\nfor the trends of\npulsatile intensity\nchanges.","Mean values for the\ntrends of dynamic\nintensity\ninformation.","","","Not available."],["Type of File to\nbe Processed\nby the device","Dynamic flow\nDoppler ultrasound\nimages in DICOM,\nBitmap, or JPEG\nformats (Vendor\nindependent).","Dynamic tissue\nDoppler image data\nacquired on Philips\nHealthcare\nultrasound products.","","","DICOM node that\naccepts DICOM3.O\ndigital medical files\nfrom an ultrasound\ndevice or another\nDICOM source."],["Platform/\nOperating\nSystem","Standard PC,\nworkstation, and\non-board\nFDA-cleared\nultrasound systems.","Standard PC,\nworkstation, and\non-board Philips'\nultrasound systems.","","","Windows XP or\nhigher, Windows\nEmbedded and\nDICOM-compliant\nmedical devices."],["Clinical\nApplication","Not specified; for\ngeneral intended use","Same","","","Same"]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-27152181","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170172-p5-t0","doc_id":"K170172","page_num":5,"bbox":[108.1,357.49,539.85,662.92],"n_rows":18,"n_cols":5,"columns":["Feature","","","UNiD Spine Analyzer","Surgimap 2.0"],"rows":[["Feature","","","UNiD Spine Analyzer","Surgimap 2.0"],["","Computer","","PC Compatible","PC Compatible"],["","Operating System","","Windows + MAC","Windows + MAC"],["","Image Input","","Local","Local + PACS connectivity"],["","Runs on Server","","Yes","No"],["","Osteotomy Module","","Yes","Yes"],["","Generic","","Yes","Yes"],["","measurements","","",""],["","Spine measurements","","Yes","Yes"],["","Pre-operative planning","","Yes","Yes"],["","Custom implants","","Yes","Yes"],["","Database","","No","Yes"],["","Case sharing","","No","Yes"],["","Human Intervention","","Required","Required"],["","for interpretation and","","",""],["","manipulation of","","",""],["","images","","",""],["","Web content","","Yes","Yes"]],"caption_candidate":"and its predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170250-p6-t0","doc_id":"K170250","page_num":6,"bbox":[114.84,66.6,533.4,738.0],"n_rows":5,"n_cols":2,"columns":["eciveD\ntegraTtramS\ndesoporP","si rofyrossecca lanoitnevretni serudecorp ,dnalg snaicisyhp fo noitazilausiv SURT cinilc swolla lacidem -eerht dezitigid a mrof sedivorp noitazilausiv ytiliba etareneg etatonna eht gnirud eb\necived etatsorp )D2( dnuosartlu ni etatsorp tI .sgnittes smrofrep ot ehT erawtfos eht dna fo ot dednetni dna a ni serudecorp\ntegraTtramS yb lanoisnemid-owt tnemges )D3( fo segami .emulov egami gnidulcni ,segami ,sweiv yfitnedi snoitacol detresni citsongaid\nna sa dednetni dediug-egami citsongaid eht gnivlovni desu eb decnahne latcersnart eht fo latipsoh ot ti dna lanoisnemid noitcurtsnocer oediv SURT tegraTtramS D3 ,serutaef weiver ranalp-itlum dna eht stnemurtsni .erudecorp si ecived tnemtaert\not segami resu segami SURT dna ,segami drocer ni\ndesu\nehT dna dna rof dna eht D3 D2 ehT\not"],"rows":[["eciveD\ntegraTtramS\ndesoporP","si rofyrossecca lanoitnevretni serudecorp ,dnalg snaicisyhp fo noitazilausiv SURT cinilc swolla lacidem -eerht dezitigid a mrof sedivorp noitazilausiv ytiliba etareneg etatonna eht gnirud eb\necived etatsorp )D2( dnuosartlu ni etatsorp tI .sgnittes smrofrep ot ehT erawtfos eht dna fo ot dednetni dna a ni serudecorp\ntegraTtramS yb lanoisnemid-owt tnemges )D3( fo segami .emulov egami gnidulcni ,segami ,sweiv yfitnedi snoitacol detresni citsongaid\nna sa dednetni dediug-egami citsongaid eht gnivlovni desu eb decnahne latcersnart eht fo latipsoh ot ti dna lanoisnemid noitcurtsnocer oediv SURT tegraTtramS D3 ,serutaef weiver ranalp-itlum dna eht stnemurtsni .erudecorp si ecived tnemtaert\not segami resu segami SURT dna ,segami drocer ni\ndesu\nehT dna dna rof dna eht D3 D2 ehT\not"],["2\neciveD\n923221K\nteJoiB\necnerefeR","ot ,tnemeganam\ndednetni D3\neht dna dnuosartlu .dnalg serutaef ,noitcurtsnocer\nni\n02 D-3\nsi snaicisyhp etatsorp\nerawtfos rof erawtfos atad egami dna\nlatipsoh\nfo tneitap ,stnemerusaem\neht ,noitatnemges\nnoitazilausiv\nteJoiB yb lanoitiddA ranalpitlum .noitartsiger\nfo\nro\ndesu segami edulcni\ncinilc\nehT\neb"],["1\neciveD\nxB\n661351K\nnoisuF\necnerefeR","egami ,noitcurtsnocer\nrof fo dna gnidrocer eht\ndna\ndednetni noitazilausiv fo gnidulcni ,noitalupinam ,noitartsiger erehw deriuqca\nrof gnigami cinilc tI D3 serutaef atad ,tnemerusaem egami\nsnaicisyhp\n.sgnittes dna\nsi ni D2 noitazilausiv .sloot tneitap ,tnemeganam ,noitatnemges dna snoitacol erew\nxB decnahne dnuosartlu etatsorp lanoitiddA ranalpitlum egami ,noitatonna eht .erudecorp\nnoisuF yb latipsoh sedivorp ,weiver sisylana edulcni egami eht seispoib gnirud\nesu eht D3\nfo"],["etaciderP 370351K\nvanorU","dediug-egami citsongaid etatsorp D3 dna dnuosartlU ot ytiliba segami sa hcus ,)RM( .cte ,yhpargomoT ot ytiliba fo egami hcus ,eriwediug taht neercs tegrat eht dna eht tnemurtsni tneitap erawtfos atad ranalp-itlum ,noitatnemges dna .noitartsiger\ncixatoerets loot a fo tneitap\nD2 eht eseht rehto ecnanoseR no ehtfo tnerruc htap stnemerusaem\ndna eht sedivorp fo dna retsiger morf seitiladom eht sedivorp detalumis noitresni ,eldeen eborp rotinom erutuf tnuocca rehtO edulcni ,noitcurtsnocer\na rof lanoitnevretni fo noitazilausiv segami ro segami eht lanoitnevretni ,tnemeganam egami\nsivaNorU yrossecca serudecorp tI .dnalg dna esoht gnigami citengaM detupmoC osla a yalpsid dekcart yspoib etalp retupmoc swohs dna nagro detcejorp otni gnikat .tnemevom serutaef egami D3/D2\n)SU( esuf htiw a dirg\ntI a sa"],["erutaeF","snoitacidnI\nesU\nrof"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170250-p7-t0","doc_id":"K170250","page_num":7,"bbox":[87.24,66.6,532.56,738.0],"n_rows":5,"n_cols":5,"columns":["si era nac ,eussit .eussit ,edulcni eldeen selpmas ;etatsorp ,seuqinhcet lacitpo ,ycneuqerfoidar ,yparehtoyrc -yllacol\ntaht eht evitcaoidar\na hcihw tnemurtsni etatsorp ro muenirep stnemurtsni ot yllanretxe tnemtaert etatsorp noitamrofni etatsorp serudecorp :ot eussit eht no desab eussit desucof cimanydotohp elbisreverri noitatnalpmi dna .seipareht\nni gnittes rehto eht taht ot morf detimil hcihw morf citsongaid lamreht gnisu ,resal ytisnetni-hgih ;noitaroportcele ;)yparehtyhcarb(\notni eht ro denoitisop os dereviled citsongaid ton devomer esoht ,evaworcim ;dnuosartlu gurd\nlacinilc ro eldeen detresni hguorht ,arhteru etatsorp deniatbo elpmaxE era ni yspoib utis sa ;gnisnes noitalba ;ypareht ecruos detcejni\nhcus\ntub era\neb ro ni ro","etatsorP","laenirepsnarT","seY","seY"],"rows":[["si era nac ,eussit .eussit ,edulcni eldeen selpmas ;etatsorp ,seuqinhcet lacitpo ,ycneuqerfoidar ,yparehtoyrc -yllacol\ntaht eht evitcaoidar\na hcihw tnemurtsni etatsorp ro muenirep stnemurtsni ot yllanretxe tnemtaert etatsorp noitamrofni etatsorp serudecorp :ot eussit eht no desab eussit desucof cimanydotohp elbisreverri noitatnalpmi dna .seipareht\nni gnittes rehto eht taht ot morf detimil hcihw morf citsongaid lamreht gnisu ,resal ytisnetni-hgih ;noitaroportcele ;)yparehtyhcarb(\notni eht ro denoitisop os dereviled citsongaid ton devomer esoht ,evaworcim ;dnuosartlu gurd\nlacinilc ro eldeen detresni hguorht ,arhteru etatsorp deniatbo elpmaxE era ni yspoib utis sa ;gnisnes noitalba ;ypareht ecruos detcejni\nhcus\ntub era\neb ro ni ro","etatsorP","laenirepsnarT","seY","seY"],["","etatsorP","laenirepsnarT\nlatcersnarT","seY","seY"],["","etatsorP","latcersnarT","seY","seY"],[",serudecorp eussit\ndesu ,edulcni lacinilc\nehT egami fo\na\nrof dna .serudecorp eb ni serudecorp tfos tnemecalp\n,lacinilc ro/dna ot dna serudecorp ot citsongaid\ndednetni ,seispoib\ngninnalp dednetni lanoitnevretni detimil dna .srekram\n.gnittes\nlanoitnevretni snoitanimaxe dna\nrof\nsi tnemtaert ecnadiug citsongaid si citsongaid elpmaxE ton rof eussit snoitalba\nvaNorU ecived lacinilc era noisuf laicudif\ntub tfos\nni","etatsorP","laenirepsnarT\nlatcersnarT","seY","seY"],["","ymotana\ntegraT","ymotanA\nssecca","SO\nswodniW","lacideM gnigami erawtfos"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K170540-p6-t0","doc_id":"K170540","page_num":6,"bbox":[54.75,358.78,540.71,659.97],"n_rows":10,"n_cols":8,"columns":["Manufacturer","","510(K) Submitter","","","Predicate","","Significant\nDifferences"],"rows":[["Manufacturer","","510(K) Submitter","","","Predicate","","Significant\nDifferences"],["","Densitas, Inc.","","","","iCAD, Inc. (formerly","",""],["","","","","","VuCOMP, Inc.)","",""],["Trade Name","DM-Density","","","","iReveal (formerly M-Vu","",""],["","","","","","Breast Density)","",""],["510(k) Numb er","N/A","","","K132742","","","N/A"],["Product Code","LLZ","","","LLZ","","","N/A"],["Regulation\nNumber","21 CFR Part 892.2050","","","21 CFR Part 892.2050","","","N/A"],["Regulati on Name","System, Image Processing,\nRadiological","","","System, Image Processing,\nRadiological","","","N/A"],["Intended Use /\nIndications for Use","DM-Density is a software\napplication intended for use\nwith compatible full field digital\nmammography systems. DM-\nDensity calculates percent\nbreast density defined as the\nratio of fibroglandular tissue to\ntotal breast area\nestimates. DM-Density\nprovides these numerical","","","M-Vu Breast Density is a\nsoftware application intended\nfor use with digital\nmammography systems. M-Vu\nBreast Density calculates breast\ndensity as a ratio of\nfibroglandular tissue and total\nbreast area estimates. M-Vu\nBreast Density provides these\nnumerical values for each","","","N/A"]],"caption_candidate":"Table 5A – Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170540-p8-t0","doc_id":"K170540","page_num":8,"bbox":[54.72,116.04,540.72,436.44],"n_rows":9,"n_cols":4,"columns":["Measurement\nScales","4-category breast density scale\nfrom 4th Ed. ACR BI-RADS Atlas\n2003","4-category breast density scale\nfrom 4th Ed. ACR BI-RADS Atlas\n2003","Subject device\nprovides users with\nthe option of utilizing\neither the 4th or 5th\nedition scales;\nPredicate Device\nutilizes 4th edition\nscale only"],"rows":[["Measurement\nScales","4-category breast density scale\nfrom 4th Ed. ACR BI-RADS Atlas\n2003","4-category breast density scale\nfrom 4th Ed. ACR BI-RADS Atlas\n2003","Subject device\nprovides users with\nthe option of utilizing\neither the 4th or 5th\nedition scales;\nPredicate Device\nutilizes 4th edition\nscale only"],["","4-category breast density scale\nfrom 5th Ed. ACR BI-RADS Atlas\n2013","",""],["Output Device","Mammography Workstation,\nPACS, and RIS","Same","N/A"],["Output Format","DICOM Structured Report and\nSecondary Capture","Same","N/A"],["Deployment","Standalone computer","Same","N/A"],["Data Throughput","600 cases per hour","60 – 120 cases per hour","N/A"],["Assessment scope","Results per image","Same","N/A"],["Assessment type","Area-based","Same","N/A"],["Anatomical\nLocation","Breast","Same","N/A"]],"caption_candidate":"DM-DENSITY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170747-p6-t0","doc_id":"K170747","page_num":6,"bbox":[138.1,199.38,553.55,729.79],"n_rows":24,"n_cols":9,"columns":["","Claim#","","","Feature /Component","","","Labeling Claim",""],"rows":[["","Claim#","","","Feature /Component","","","Labeling Claim",""],["1.","1.","","syngoTrueFusion","","","syngo TrueFusion –Add TEE guidance to live\nfluoroscopy with ease","",""],["","2.","","syngoTrueFusion","","","Navigate with improved anatomical orientation","",""],["","3.","","syngoTrueFusion","","","Integrated efficiency in TEE guidance","",""],["","4.","","syngoTrueFusion","","","Reduce complexity in challenging procedures","",""],["5.","5.","","syngoTrueFusion","","","Navigate with confidence through integrated\nTEE guidance","",""],["6.","","","syngoTrueFusion","","","Achieve automated co-registration with eSie\nSync\nAutomatedprobe detection in 2 single fluoro\nimages and automatedco-registration updates","",""],["7.","","","syngoTrueFusion","","","eSie Sync integrates co-registration efficiently in\nyour workflow","",""],["","8.","","syngoTrueFusion","","","Probe detection enhanced by machine learning","",""],["9.","9.","","syngoTrueFusion","","","Hardware markersand probe model enable\nrobust algorithm","",""],["","10.","","syngoTrueFusion","","","Trueintegration of ACUSON SC2000 PRIME","",""],["11.","11.","","syngoTrueFusion","","","Trueintegration and possibility to synchronize\nviews enhances communication","",""],["12.","","","syngoTrueFusion","","","Share perspectives efficiently with view\nsynchronization*","",""],["","13.","","syngoTrueFusion","","","Set landmarks swiftly with eSie Valves modeling","",""],["14.","14.","","syngoTrueFusion","","","Identify key anatomical landmarks with one-click\neSie Valves modeling","",""],["15.","","","syngoTrueFusion","","","Assess valves and fuse model with live\nfluoroscopy at any time during the procedure","",""],["16.","","","syngoTrueFusion","","","Valve modelreduced to the relevant structures\non the fusion image for a clear view of your\ndevices","",""],["17.","","","syngoTrueFusion","","","Annulus landmark overlay on live fluoroscopy\ncan help find the perpendicularview.","",""],["18.","","","syngoTrueFusion","","","Target-oriented guidance through TEE structural\ninformation fusion","",""],["19.","","","syngoTrueFusion","","","More intuitive orientation through overlay of TEE\ncone on live fluoro*","",""],["","20.","","syngoTrueFusion","","","Claim Removed","",""],["","21.","","syngoTrueFusion","","","Claim Removed","",""],["22.","22.","","syngoTrueFusion","","","Direct real-time guidance from the ultrasound\nsystem","",""],["23.","","","syngoTrueFusion","","","syngo TrueFusion can shorten the learning\ncurve in challenging procedures as it enables\nmore intuitive anatomical orientation*","",""]],"caption_candidate":"Proposed new product claims associated with “syngo TrueFusion”","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170747-p7-t0","doc_id":"K170747","page_num":7,"bbox":[138.08,75.18,553.55,475.92],"n_rows":16,"n_cols":9,"columns":["","Claim#","","","Feature /Component","","","Labeling Claim",""],"rows":[["","Claim#","","","Feature /Component","","","Labeling Claim",""],["24.","24.","","syngoTrueFusion","","","Synchronization of TEE and angioimage\norientation allows to deriveimplantation angles\nfrom TEE.","",""],["25.","","","syngoTrueFusion","","","Assessment of valve morphology with eSie\nValves™ modelingand fusion of relevant\nstructures supports accurate device placement","",""],["26.","","","syngoTrueFusion","","","Dedicated probe design enables rapid and\nreliable registration updates**","",""],["27.","","","syngoTrueFusion","","","Reliableimage fusion with dedicated probe\ndesign and eSie sync","",""],["28.","","","syngoTrueFusion","","","Target-oriented device navigation via True\nVolume TEE landmarks","",""],["29.","","","syngoTrueFusion","","","Direct export of fusion landmarksfrom the\ncompatible ultrasound system.","",""],["30.","","","syngoTrueFusion","","","Overlay of TEE cone on live fluoro for greater\nintuition in orientation*","",""],["31.","","","syngoTrueFusion","","","Fast and reliable documentation with integrated\npatient co-registration from angiography and\nultrasound systems","",""],["","32.","","syngoTrueFusion","","","C-arm angulation planning without fluoroscopy","",""],["","33.","","syngoTrueFusion","","","A confident clear view combined on one screen","",""],["34.","34.","","syngoTrueFusion","","","Facilitated communication through first-hand\nguidance from the modality expert","",""],["35.","","","syngoTrueFusion","","","Synchronized views can speed up orientation and\ncommunication*","",""],["36.","","","syngoTrueFusion","","","Synchronized views facilitating orientation / for a\nfaster grasp of orientation*","",""],["","37.","","syngoTrueFusion","","","Claim Removed","",""],["*This is the result of individual user experience –results may vary\n**The quality of registration depends on the orientation of the probe, the angular difference\nbetweenthe two projections, the C-arm position, and the zoom stage.","","","","","","","",""]],"caption_candidate":"syngoApplication Software K170747AI Response","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170747-p8-t0","doc_id":"K170747","page_num":8,"bbox":[131.09,471.79,580.49,611.76],"n_rows":4,"n_cols":7,"columns":["Property","Subject Device\nsyngo Application\nSoftware","","","Predicate Device","","Comparison Results"],"rows":[["Property","Subject Device\nsyngo Application\nSoftware","","","Predicate Device","","Comparison Results"],["","","","","syngo Application","",""],["","","","","Software (K163285)","",""],["SW VD20 New\nSoftware\nApplication","Newly added\nsoftware feature:\nsyngo TrueFusion","","“syngo TrueFusion” not\navailable.","","","The new syngo\nTrueFusion software\nfeature does not raise\nany new issues of\nsafety of\neffectiveness.\nValidation and testing\nwas conducted"]],"caption_candidate":"the Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K170747-p10-t0","doc_id":"K170747","page_num":10,"bbox":[143.47,197.88,579.26,663.62],"n_rows":20,"n_cols":5,"columns":["","Table 1: Validation Report Summary","","",""],"rows":[["","Table 1: Validation Report Summary","","",""],["1.","1.","","Subject Device Modification:",""],["","","Added software feature “syngo TrueFusion”","",""],["2.","","","Objective or Purpose of Test:",""],["","","Validate syngo TrueFusion results","",""],["3.","","","Explanation of sample size and Statistical Methods:",""],["","","28 phantom test data sets","",""],["4.","","","Summary of Test Methodology:",""],["","","Multiple Measurements were performed from different directions of the C-arm by a\nboard certified cardiologist.","",""],["5.","","","Explanation of Study Endpoints:",""],["","","All results are clinically accepted by a board certified radiologist.","",""],["6.","","","Explanation of Study Acceptance Criteria:",""],["","","Mean deviation shall not exceed 3mm with a standard deviation not exceeding\n2mm.","",""],["7.","","","Test Report Results:",""],["","","Multiple Measurements were performed from different directions of the C-arm. The\nmeasurements show these mean and standard deviations from three different C-\nArm positions (A, B, C): Experiment 1 position A mean 2,92mm with a standard\ndeviation of 1,29mm, position Bmean 2,59mm with a standard deviation of\n1,50mm, position C mean 2,31mm with a standard deviation of 1,62mm,\nexperiment 2 position A mean 2,76mm with a standard deviation of 1,31mm,\nposition B mean 2,57mm with a standard deviation of 1,69mm, position C mean\n2,13mm with a standard deviation of 1,48mm. The statistical significance –\n80% successful experiments – is 0,0 for experiment 1 position A, 0,002 for B,\n0,002 for C and 0,002 for experiment 2 position A, 0,015 for B and 0,002 for C.\nAll results were clinically accepted by a board certified cardiologist.","",""],["8.","","","Supportive article reference(s) with explanation as for how it supports the",""],["","","","modification:",""],["","","This is not applicable","",""],["9.","","","Conclusion Statement:",""],["","","The comparison of technological characteristic, non-clinical performance data,\nclinical images, Human Factor Usability data and software validation data\ndemonstrates that the subject device is as safe, and effective when compared to\nthe predicate device that is currently marketed for the same intended use.","",""]],"caption_candidate":"Performance Verification/Validation & Test Report Summaries","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K172385-p14-t0","doc_id":"K172385","page_num":14,"bbox":[168.72,80.64,416.4,616.44],"n_rows":10,"n_cols":2,"columns":["Clarius Ultrasound Scanner","Clarius Ultrasound System\n(K163138)"],"rows":[["Clarius Ultrasound Scanner","Clarius Ultrasound System\n(K163138)"],["Portable ultrasound system","Portable ultrasound system"],["Removable battery (Li-ion)","Removable battery (Li-ion)"],["iOS or Android mobile device","iOS or Android mobile device"],["Communicates wirelessly via Wi-\nFi and Bluetooth","Communicates wirelessly via Wi-\nFi and Bluetooth"],["Track 3","Track 3"],["− Convex Array\n− Linear Array\n− Phased Array","− Convex Array\n− Linear Array"],["Diagnostic ultrasound imaging and\nfluid flow analysis","Diagnostic ultrasound imaging and\nfluid flow analysis"],["− Ophthalmic\n− Fetal\n− Abdominal\n− Intraoperative (Ab/Vasc)\n−\n− Pediatric\n− Small organ\n−\n− Adult Cephalic\n−\n−\n− Musculo-skel. (Conv.)\n− Musculo-skel. (Superfic.)\n− Urology\n− Gynecology\n− Cardiac Adult\n− Cardiac Pediatric\n−\n− Fetal Echo\n− Peripheral vessel\n− Carotid\n− Needle guidance","−\n− Fetal\n− Abdominal\n−\n−\n− Pediatric\n− Small organ\n−\n−\n−\n−\n− Musculo-skel. (Conv.)\n− Musculo-skel. (Superfic.)\n− Urology\n− Gynecology\n− Cardiac Adult\n− Cardiac Pediatric\n−\n− Fetal Echo\n− Peripheral vessel\n− Carotid\n− Needle guidance"],["− B-mode\n− M-mode\n− Color Doppler\n−\n− Power Doppler\n−\n−\n−\n− Combined (B+M, B+CD, B+PD)","− B-Mode\n−\n−\n−\n−\n−\n−\n−\n−"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172385-p15-t0","doc_id":"K172385","page_num":15,"bbox":[71.96,120.28,539.96,447.53],"n_rows":27,"n_cols":3,"columns":["Reference No.","Year","Title"],"rows":[["Reference No.","Year","Title"],["AAMI/ANSI","2012","Medical Electrical Equipment - Part 1: General Requirements for Basic Safety and Essential"],["ES60601-1","","Performance"],["IEC 60601-1-2","2007","Medical electrical equipment – Part 1-2: General requirements for basic safety and essential"],["","&","performance – Collateral Standard: Electromagnetic Capability – Requirements and tests. (4th"],["","2014","Edition)"],["IEC 60601-1-6","2013","Medical electrical equipment - Part 1-6: General requirements for basic safety and essential"],["","","performance -Collateral standard: Usability"],["IEC 60601-1-12","2014","Medical Electrical Equipment — Part 1-12: General requirements for basic safety and essential"],["","","performance - Collateral Standard: Requirements for medical electrical equipment and medical"],["","","electrical systems used in the emergency medical services environment"],["IEC 60601-2-37","2004","Medical electrical equipment – Part 2-37: Particular requirements for the basic safety and essential"],["","","performance of ultrasonic medical diagnostic and monitoring equipment. (3rd and 4th Edition)"],["IEC 62133","2012","Secondary Cells and Batteries Containing Alkaline or Other Non-Acid Electrolytes - Safety"],["","","Requirements for Portable Sealed Secondary Cells, And for Batteries Made from Them, For Use in"],["","","Portable Applications [Including: Corrigendum 1 (2013)]"],["IEC 62366","2014","Consolidated Version Medical Devices - Application of Usability Engineering to Medical Devices"],["ISO 10993-1","2009","Biological evaluation of medical devices - Part 1: Evaluation and testing within a risk management"],["","","process"],["ISO 10993-5","2014","Biological Evaluation of Medical Devices - Part 5: Tests for In Vitro Cytotoxicity"],["ISO 10993-10","2014","Biological Evaluation of Medical Devices - Part 10: Tests for Irritation and Skin Sensitization"],["ISO-10993-12","2014","Biological Evaluation of Medical Devices - Part 12: Sample Preparation and Reference Materials"],["ISO 62304","2006","Medical Device Software - Software Life Cycle Processes"],["ISO 15223-1","2012","Medical Devices - Symbols to be Used with Medical Devices Labels, Labeling, and Information to be"],["","","Supplied - Part 1: General Requirements"],["ISO 14971","2007","Medical Devices - Applications of Risk Management to Medical Devices"],["NEMA UD 2","2009","Acoustic Output Measurement Standard for Diagnostic Ultrasound Equipment - Revision 3"]],"caption_candidate":"Nonclinical performance tests show compliance to the following standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p6-t0","doc_id":"K172803","page_num":6,"bbox":[63.16,84.33,548.94,717.7],"n_rows":8,"n_cols":12,"columns":["Category","","","Subject Device: INFINITT\nPACS 7.0","","","Predicate device: INFINITT\nG3 (K052545)","","","","Explain why",""],"rows":[["Category","","","Subject Device: INFINITT\nPACS 7.0","","","Predicate device: INFINITT\nG3 (K052545)","","","","Explain why",""],["","","","","","","","","","","differences do not",""],["","","","","","","","","","","affect patient safety",""],["","","","","","","","","","","or effectiveness.",""],["","Overview","","","","","","","","","",""],["General","",""," Same as predicate except\nfor the operating system.\n Runs on Microsoft\nWindows 7 / 8.1 / 10","",""," Runs on Microsoft\nWindows XP / Vista / 7 /\n8.1\n Supports a combination\nof various types of\nmonitors including VGA\nand high-resolution\nmonitors\n Integration-less\nsynchronization of PACS\nand 3D functions\n Automatically detects\nmonitor resolution and\nmagnification\n Intuitively applies setting\nvalues\n Links internal viewer to\nexternal HIS/RIS report\nsystem\n Supports launching\nexternal programs with\nvarious parameter from\nspecified exam\ninformation\n Supports Direct CD/USB\nBurning and Media\nserver backup\n Supports Anonymize\nDirect CD/USB Burning\nand Media server\n Stores all user settings in\nthe database (Roaming\nuser profile)","","","Differences: Subject\nDevice does not run on\nMicrosoft XP or Vista.\nThe differences\nbetween the subject\ndevice and the\npredicate device is due\nto the advancement in\ncomputer OS\ntechnology since the\ntime predicate device\nwas cleared by FDA.\nMicrosoft XP or Vista\nare no longer supported\nby Microsoft.\nThe differences\nindicated, do not raise\nany new potential\nsafety risks and\ntherefore, there is no\nimpact on safety or\nefficacy for the subject\ndevice.","",""],["Deploy","",""," Web-based deployment\n Smart upgrade","",""," Web-based deployment\n Smart upgrade","","","No differences","",""],["Compatibility\n- DICOM\nfunctions","",""," DICOM JPEG compression\n DICOM JPEG2K\ncompression\n DICOM Security (TLS)\n DICOM Multi-frame\n DICOM Storage (SCU)\n DICOM DIR - FSC, FSR,\nFSU\n DICOM Query/Retrieve\n(SCU)\n DICOM Grayscale Softcopy\nPresentation State (GSPS)","",""," DICOM JPEG\ncompression\n DICOM JPEG2K\ncompression\n DICOM Security (TLS)\n DICOM Multi-frame\n DICOM Storage (SCU)\n DICOM DIR - FSC, FSR,\nFSU\n DICOM Query/Retrieve\n(SCU)\n DICOM Grayscale","","","No differences","",""]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p7-t0","doc_id":"K172803","page_num":7,"bbox":[63.15,72.24,548.95,718.78],"n_rows":4,"n_cols":12,"columns":["","",""," DICOM Key Image Note\n DICOM Multi-bytes\ncharacter set\n DICOM Print","","","Softcopy Presentation\nState (GSPS)\n DICOM Key Image Note\n DICOM Multi-bytes\ncharacter set\n DICOM Print","","","","",""],"rows":[["","",""," DICOM Key Image Note\n DICOM Multi-bytes\ncharacter set\n DICOM Print","","","Softcopy Presentation\nState (GSPS)\n DICOM Key Image Note\n DICOM Multi-bytes\ncharacter set\n DICOM Print","","","","",""],["Cyber\nsecurity","",""," Supports secured network\nprotocol\n Supports auto log off\n Supports audit logging\n Restricting user behavior\nbased on user roles and\nthe institutional policies","",""," Supports secured\nnetwork protocol\n Supports auto log off\n Supports audit logging\n Restricting user behavior\nbased on user roles and\nthe institutional policies","","","No differences","",""],["","Worklist","","","","","","","","","",""],["Worklist","","","General\n Supports various worklist\nmode\n Study list\n Favorite folder\n DICOM QR\n DICOM DIR\n Case\n Conference\n Technician worklist\n Embedded web\nbrowser\n Viewed history\n Supports short cut button\nfor the specific folders of\neach worklist mode (Quick\naccess)\n Support open the DICOM\nfiles directly (local open)\nStudy list\n Searches the exams that\nmeet the multiple search\nconditions\n Configurable fetching count\nfor the exams.\n Exam list displays various\ninformation describing the\nexams.\n Add, delete, change\nposition and sort of each\ninformation with header\ncolumn control\n Supports refreshing the\nexam list automatically by\nuser configuration","","","General\n Supports various worklist\nmode\n Study list\n Favorite folder\n DICOM QR\n DICOM DIR\n Case\n Support open the DICOM\nfiles directly (local open)\nStudy list\n Searches the exams that\nmeet the multiple search\nconditions\n Configurable fetching\ncount for the exams.\n Exam list displays\nvarious information\ndescribing the exams.\n Add, delete, change\nposition and sort of each\ninformation with header\ncolumn control\n Supports refreshing the\nexam list automatically\nby user configuration\n Exports the list of the\nselected exams to text\nfile or MS Excel\ncompatible file (CSV)\n Supports\ncreate/edit/delete search\nfolders that contains the\npredefined search\nconditions","","","Yes, there are\ndifferences. There is\nadditional functionality\nin the subject device.\nThe added features and\nfunctions of the subject\ndevice is described in\nlabeling, so the User\nwill be aware of the\nsystem functionality.\nThe additional items do\nnot change the\nInductions for Use as\ncompared to the\npredicate. The\ndifferences do not raise\nany new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device.","",""]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p10-t0","doc_id":"K172803","page_num":10,"bbox":[63.12,72.24,548.98,714.82],"n_rows":3,"n_cols":4,"columns":[""," Searches order and exam\nList\n Matches or un-matches the\nselected order and exams\n Merges or un-merges the\nexam\n Splits the series from the\nexam to new one\n Modifies the information of\nthe exam or the series\nEmbedded web browser\n Browses the web pages\nwith predefined web URL\nDash Board\n Queries the number of\nexams that are met the\nspecified condition\n Shows the study list that\nare met the specified\nconditions\nNotification\n Notices predefined\nschedules or events to\nPACS user.","",""],"rows":[[""," Searches order and exam\nList\n Matches or un-matches the\nselected order and exams\n Merges or un-merges the\nexam\n Splits the series from the\nexam to new one\n Modifies the information of\nthe exam or the series\nEmbedded web browser\n Browses the web pages\nwith predefined web URL\nDash Board\n Queries the number of\nexams that are met the\nspecified condition\n Shows the study list that\nare met the specified\nconditions\nNotification\n Notices predefined\nschedules or events to\nPACS user.","",""],["General\nViewing"," Displays the DICOM\nimages which are stored in\nPACS storage\n Accesses historical exams\nand report : Timeline, Exam\nlist\n Supports image\narrangement and\nmanipulation using toolbar\nbuttons, shortcut keys or\nscreen shortcut\n Support user-configurable\nmouse button action\n Configures the initial\nsettings for each specific\nmodality\n Supports job saving\n Export or convert the\ndisplayed images as\nDICOM or general image\nformats"," Displays the DICOM\nimages which are stored\nin PACS storage\n Accesses historical\nexams and report : Exam\nlist\n Supports image\narrangement and\nmanipulation using\ntoolbar buttons or\nshortcut keys\n Support user-\nconfigurable mouse\nbutton action\n Configures the initial\nsettings for each specific\nmodality\n Supports job saving\n Export or convert the\ndisplayed images as\nDICOM or general image\nformats","Yes, there are\ndifferences. There is\nadditional functionality\nin the subject device.\nThe added features and\nfunctions of the subject\ndevice is described in\nlabeling, so the User\nwill be aware of the\nsystem functionality.\nThe additional items do\nnot change the\nInductions for Use as\ncompared to the\npredicate. The\ndifferences do not raise\nany new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],["Toolbar","Common tools\n Select\n Pan","Common tools\n Select\n Pan","Yes, there is an added\n“Findings List” feature\nin the subject device."]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p11-t0","doc_id":"K172803","page_num":11,"bbox":[63.12,72.24,548.98,717.82],"n_rows":2,"n_cols":4,"columns":[""," Zoom\n Windowing\n Magnification\n Fit\n Capture\n Reset\n Print: Report / Film\n 3D cursor\n Exam Refresh\n Dictation (play, record)\n Set as tape dictated\n Hide demographic\ninformation\n Save snapshot\n Apply previous / next HP\nsequence\n Specific zoom: 100%, 1:1\nDisplay (Monitor screen)\nAnnotation /\nMeasurement tools\nImage Display\n3D Tools\nEtc tools\n Display DICOM information\ntool\n Monitor cine controller\n Save\n Call case folder\n External link\n About"," Zoom\n Windowing\n Magnification\n Fit\n Capture\n Reset\n Print: Report / Film\n 3D cursor\n Exam Refresh\n Dictation (play, record)\n Set as tape dictated\n Hide demographic\ninformation\n Save snapshot\n Apply previous / next HP\n Specific zoom: 100%, 1:1\nDisplay (Monitor screen)\nAnnotation /\nMeasurement tools\nImage Display\n3D Tools\nEtc tools\n Display DICOM\ninformation tool\n Monitor cine controller\n Save\n Call case folder\n External link\n About","The added feature is\ndescribed in labeling,\nso the User will be\naware of the system\nfunctionality. The\nadditional item does not\nchange the Inductions\nfor Use as compared to\nthe predicate. The\ndifference does not\nraise any new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],"rows":[[""," Zoom\n Windowing\n Magnification\n Fit\n Capture\n Reset\n Print: Report / Film\n 3D cursor\n Exam Refresh\n Dictation (play, record)\n Set as tape dictated\n Hide demographic\ninformation\n Save snapshot\n Apply previous / next HP\nsequence\n Specific zoom: 100%, 1:1\nDisplay (Monitor screen)\nAnnotation /\nMeasurement tools\nImage Display\n3D Tools\nEtc tools\n Display DICOM information\ntool\n Monitor cine controller\n Save\n Call case folder\n External link\n About"," Zoom\n Windowing\n Magnification\n Fit\n Capture\n Reset\n Print: Report / Film\n 3D cursor\n Exam Refresh\n Dictation (play, record)\n Set as tape dictated\n Hide demographic\ninformation\n Save snapshot\n Apply previous / next HP\n Specific zoom: 100%, 1:1\nDisplay (Monitor screen)\nAnnotation /\nMeasurement tools\nImage Display\n3D Tools\nEtc tools\n Display DICOM\ninformation tool\n Monitor cine controller\n Save\n Call case folder\n External link\n About","The added feature is\ndescribed in labeling,\nso the User will be\naware of the system\nfunctionality. The\nadditional item does not\nchange the Inductions\nfor Use as compared to\nthe predicate. The\ndifference does not\nraise any new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],["Thumbnail"," Thumbnail display: series,\nimage\n Displays series number and\nhow many images are in\nspecific series\n Displays an icon about the\nproperty of the series: Only\none image in series,\nMultiple images in series,\nMulti-frame image in series\n Supports opening the\nseries or image by drag\nand drop the thumbnail or\nclick it"," Thumbnail display:\nseries, image\n Displays series number\nand how many images\nare in specific series\n Supports opening the\nseries or image by drag\nand drop the thumbnail\nor click it","Yes, there is a\ndifference in that the\nsubject device displays\nan icon about the\nproperty of the series:\nOnly one image in\nseries, Multiple images\nin series, Multi-frame\nimage in series. The\nadded feature is\ndescribed in labeling,\nso the User will be\naware of the system\nfunctionality. The\nadditional item does not\nchange the Inductions\nfor Use as compared to\nthe predicate. The\ndifference does not"]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p12-t0","doc_id":"K172803","page_num":12,"bbox":[63.12,72.24,548.98,710.26],"n_rows":4,"n_cols":4,"columns":["","","","raise any new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],"rows":[["","","","raise any new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],["Layout"," Supports monitor merge\n Supports displaying\nmultiple exams in a monitor\nby image set layout\n Supports displaying\nmultiple series or images in\nthe image set by cell layout"," Supports monitor merge\n Supports displaying\nmultiple exams in a\nmonitor by image set\nlayout\n Supports displaying\nmultiple series or images\nin the image set by cell\nlayout","No differences"],["Visual\nTimeline"," Displays the information of\nthe patients that are\nopened\n Displays the list of all\nhistorical exams or relevant\nexams only for specific\npatient\n Displays the report text of\nthe specific historical exam\n Displays the series\nthumbnails of the specific\nhistorical exam\n Displays jobs and\nsnapshots in this area\nwhen creating it. (Job\ncontainer)"," (N/A)","Yes, differences. This is\na new feature that is\nnot in the predicate\ndevice. The added\nfeatures and functions\nof the subject device is\ndescribed in labeling,\nso the User will be\naware of the system\nfunctionality. The\nadditional items do not\nchange the Inductions\nfor Use as compared to\nthe predicate. The\ndifferences do not raise\nany new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],["Advanced\nHanging\nProtocol"," Applies the user\nconfigurable hanging\nprotocol for each type of\nexam when it is opened\n Support tools for managing\nuser hanging protocols:\nCreate / Copy / Export /\nImport / Copy from another\nuser / Delete / Search\n Support user configuration\nfor below settings in a\nhanging protocol\n Support multiple layout\nsequences in a hanging\nprotocol (hanging protocol\nlayout group)"," Applies the user\nconfigurable hanging\nprotocol for each type of\nexam when it is opened\n Support tools for\nmanaging user hanging\nprotocols: Create / Copy\n/ Export / Import / Copy\nfrom another user /\nDelete / Search\n Support user\nconfiguration for below\nsettings in a hanging\nprotocol","Yes, there is a\ndifference between the\nsubject and predicate\ndevices. The subject\nsupport multiple layout\nsequences in a hanging\nprotocol (hanging\nprotocol layout group).\nThis is a new feature\nthat is not in the\npredicate device. The\nadded features and\nfunctions of the subject\ndevice is described in\nlabeling, so the User\nwill be aware of the\nsystem functionality.\nThe additional items do"]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p13-t0","doc_id":"K172803","page_num":13,"bbox":[63.15,72.24,548.94,709.78],"n_rows":8,"n_cols":6,"columns":["","","","","","not change the\nInductions for Use as\ncompared to the\npredicate. The\ndifferences do not raise\nany new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],"rows":[["","","","","","not change the\nInductions for Use as\ncompared to the\npredicate. The\ndifferences do not raise\nany new potential\nsafety risks and\ntherefore, we believe\nthere is no impact on\nsafety or efficacy for the\nsubject device."],["","Image","","","",""],["","Display","","","",""],["Common","",""," Support display mode:\nStack / Image / Preset (VR\n/ MPR / MIP / Web URL /\nReport)\n Maximize and restore\ndisplayed image\n Support crosslink among\nthe series in same study\n Support linked scrolling\namong the exams, even for\ndifference exams\n Support linked scrolling by\nmanual-selection\n Support monitor cine\ncontrol for stack mode\n Sets as key image\n Rearranges the images by\nimage information (Sort):\nimage time/number/echo\ntime/image position\n Supports sequence display\n(Position/Time) for specific\ndata"," Support display mode:\nSeries / Image / Preset\n(VR / MPR / MIP / Endo /\nFMX)\n Maximize and restore\ndisplayed image\n Support crosslink among\nthe series in same study\n Support linked scrolling\namong the exams, even\nfor difference exams\n Support linked scrolling\nby manual-selection\n Support monitor cine\ncontrol for series mode\n Sets as key image\n Rearranges the images\nby image information\n(Sort): image\ntime/number/echo\ntime/image position\n Supports sequence\ndisplay (Position/Time)\nfor specific data","No differences"],["","Advanced","","","",""],["","Display","","","",""],["Fusion","",""," Adjustable blending rate\n Separated windowing for\neach fusion data\n Screen capture for further\nuse"," Manually adjusted\nregistration\n Adjustable blending rate\nin MIP/MPR fusion\n Separated windowing for\neach fusion data","No differences"],["Mammo\nDisplay","",""," Mammo CAD interface: R2\n Mammo CAD interface : i-\nCAD SR\n Mammo Hanging Protocol\nLoop Sequence\n Mirror function: Zoom,"," Mammo CAD interface:\nR2\n Mammo CAD interface :\ni-CAD SR\n Mammo Loop Sequence\n Mirror function: Zoom,","No differences"]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172803-p14-t0","doc_id":"K172803","page_num":14,"bbox":[63.16,72.24,548.94,719.26],"n_rows":5,"n_cols":12,"columns":["","","","Magnification, Pan, B/W\nInvert\n Quadrant Zoom\n Clear Filter\n Custom View Layout\n Auto breast fit display\n Breast Tomosynthesis view\nmode\n Controlled with INFINITT\nMammo Keypad (option)","","","Magnification, Pan, B/W\nInvert\n Quadrant Zoom\n Clear Filter\n Custom View Layout\n Auto breast fit display\n Breast Tomosynthesis\nview mode\n Controlled with INFINITT\nMammo Keypad (option)","","","","",""],"rows":[["","","","Magnification, Pan, B/W\nInvert\n Quadrant Zoom\n Clear Filter\n Custom View Layout\n Auto breast fit display\n Breast Tomosynthesis view\nmode\n Controlled with INFINITT\nMammo Keypad (option)","","","Magnification, Pan, B/W\nInvert\n Quadrant Zoom\n Clear Filter\n Custom View Layout\n Auto breast fit display\n Breast Tomosynthesis\nview mode\n Controlled with INFINITT\nMammo Keypad (option)","","","","",""],["","3D Display","","","","","","","","","",""],["Image\ndisplay -\nCommon","","","Volume Rendering\n OTF windowing: See below\nin more detail\n Interactive 3D rendering\nreflecting the change of\nOTF\n VOI display (slab\nrendering): See below in\nmore detail\n Batch rendering\n Orientation cube display\n Orientation preset\n Bounding box display\n Synchronize VR with MIP\nMPR\n Supports classic\nreformation planes: Axial,\nSagittal, Coronal and\nOblique plane\n Supports image scroll using\nmouse drag on images\n Various crosshair shape:\nShow/Hide, Hollow, Small\nsize\n Double oblique MPR\n Curved MPR\n Rotate reformation plane\n Batch MPR with cine\nsupport\n Slab MPR: Raysum, MIP,\nMinIP","","","Volume Rendering\n OTF windowing: See\nbelow in more detail\n Interactive 3D rendering\nreflecting the change of\nOTF\n VOI display (slab\nrendering): See below in\nmore detail\n Batch rendering\n Orientation cube display\n Orientation preset\n Bounding box display\n Synchronize VR with MIP\nMPR\n Supports classic\nreformation planes: Axial,\nSagittal, Coronal and\nOblique plane\n Supports image scroll\nusing mouse drag on\nimages\n Various crosshair shape:\nShow/Hide, Hollow,\nSmall size\n Double oblique MPR\n Curved MPR\n Rotate reformation plane\n Batch MPR with cine\nsupport\n Slab MPR: Raysum,\nMIP, MinIP","","","No differences","",""],["","Output","","","","","","","","","",""],["Print","","","General\n Prints the images and\nreport with paper or DICOM\nprinter\n Sends the images and","","","General\n Prints the images and\nreport with paper or\nDICOM printer\n Sends the images and","","","No Differences","",""]],"caption_candidate":"510(k) Summary of Safety and Effectiveness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172983-p4-t0","doc_id":"K172983","page_num":4,"bbox":[72.95,550.07,531.59,644.63],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","CSCS-001A Calcium Scoring Package"],"rows":[["Proprietary Name","CSCS-001A Calcium Scoring Package"],["Premarket Notification","K072737 (5 Oct. 2007)"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"The HealthCCS device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172983-p5-t0","doc_id":"K172983","page_num":5,"bbox":[72.95,88.07,531.59,182.63],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Kodak Carestream PACS"],"rows":[["Proprietary Name","Kodak Carestream PACS"],["Premarket Notification","K053347"],["Classification Name","Picture archiving and communications system"],["Regulation Number","892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"Reference Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172983-p7-t0","doc_id":"K172983","page_num":7,"bbox":[73.28,395.8,547.34,685.88],"n_rows":7,"n_cols":5,"columns":["Technological\nCharacteristics","Proposed\nDevice:\nHealthCCS\nsoftware tool","Predicate Device:\nCSCS-001A,\nCalcium Scoring\nPackage (K072737)","Reference Device\nKodak Carestream\nPACS (K053347)","Summary"],"rows":[["Technological\nCharacteristics","Proposed\nDevice:\nHealthCCS\nsoftware tool","Predicate Device:\nCSCS-001A,\nCalcium Scoring\nPackage (K072737)","Reference Device\nKodak Carestream\nPACS (K053347)","Summary"],["General","","","",""],["Modality","CT","CT","CT","Same"],["Image format","DICOM","DICOM","DICOM","Same"],["Supported\nComputed\nTomography\n(CT) scan – body\npart","Heart/Chest","Heart/Chest","Heart/Chest","Same"],["Supported\nComputed\nTomography\n(CT) scan – dose","Typically Normal\nDose","Typically Normal\nDose","Typically Normal\nDose","Same"],["Supported\nComputed\nTomography\n(CT) scan – Use\nof IV contrast","No","No","No","Same"]],"caption_candidate":"devices is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K172983-p8-t0","doc_id":"K172983","page_num":8,"bbox":[73.27,72.74,547.35,610.02],"n_rows":13,"n_cols":5,"columns":["Supported\nComputed\nTomography\n(CT) scan – ECG\nGating/Triggering","ECG-Gated","ECG-Gated","ECG-Gated","Same"],"rows":[["Supported\nComputed\nTomography\n(CT) scan – ECG\nGating/Triggering","ECG-Gated","ECG-Gated","ECG-Gated","Same"],["Quantification","","","",""],["Calcification\nlocation marking","Automatic","Semi-automatic,\nManual","Semi-automatic,\nManual","Substantially\nequivalent"],["Selection of a\ncalcified plaques\nbased on voxel\nidentification\nabove a known\nthreshold","Yes","Yes","Yes","Same"],["Default threshold\nof Calcium","130 HU\n(Hounsfield\nUnits)","130 HU (Hounsfield\nUnits)","130 HU (Hounsfield\nUnits)","Same"],["Spatial threshold","1.5 mm2","1 mm2","1 mm2","Substantially\nequivalent"],["Coronary\nCalcification\ncalculation\nmethod","Agatston\nequivalent score\nbased on the\nAgatston method","- Agatston score\n- Mass score\n- Volume score","- Agatston score\n- Mass score\n- Volume score","Substantially\nequivalent"],["Computed\ncalcium scoring","Total calcium\nscore","Total calcium score,\nand per-artery\ncalcium score","Total calcium score,\nand per-artery\ncalcium score","Substantially\nequivalent"],["Data reporting","","","",""],["Generate patient\nreport","Yes","Yes","Yes","Same"],["Printable hard\ncopy reports","No","Yes","Yes","Substantially\nequivalent"],["Maintain a\npatient database\nfor future\nreference","No","Yes","Yes","Substantially\nequivalent"],["Report of the\ncalcium score\ncategory","Yes","Yes","Yes","Substantially\nequivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173420-p4-t0","doc_id":"K173420","page_num":4,"bbox":[66.62,136.82,534.24,318.29],"n_rows":4,"n_cols":2,"columns":["Submitter:","Microsoft Corp\n1 Microsoft Way\nRedmond, WA 98052\nPhone: 425-538-9419"],"rows":[["Submitter:","Microsoft Corp\n1 Microsoft Way\nRedmond, WA 98052\nPhone: 425-538-9419"],["Contact Person:","Ivan Tarapov\nIvan.Tarapov@microsoft.com"],["Submission Correspondent:","Donna-Bea Tillman, Ph.D, MPA\nBiologics Consulting Group, Inc.\n1555 King Street, Suite 300\nAlexandria, VA 22314\nPhone: 410-531-6542\ndtillman@biologicsconsulting.com"],["Date Prepared:","October 31, 2017"]],"caption_candidate":"1. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173420-p4-t1","doc_id":"K173420","page_num":4,"bbox":[66.62,364.85,534.24,450.19],"n_rows":5,"n_cols":2,"columns":["Name of Device:","Radiomics App v1.0"],"rows":[["Name of Device:","Radiomics App v1.0"],["Common or Usual Name:","Radiological Image Processing System"],["Classification Name:","Picture Archiving and Communications System\n21 CFR 892.2050"],["Regulatory Class:","Class II"],["Product Code:","LLZ"]],"caption_candidate":"2. DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173420-p4-t2","doc_id":"K173420","page_num":4,"bbox":[66.62,496.75,534.24,553.99],"n_rows":4,"n_cols":2,"columns":["Predicate Device Name:","MIM 5.2 (BRACHY)"],"rows":[["Predicate Device Name:","MIM 5.2 (BRACHY)"],["Manufacturer:","MIM Software Inc."],["510(k) Number:","K103576"],["Reference Devices:","No reference devices were used in this submission."]],"caption_candidate":"3. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173420-p6-t0","doc_id":"K173420","page_num":6,"bbox":[66.62,174.98,545.52,730.66],"n_rows":7,"n_cols":3,"columns":["","Proposed Device","Predicate Device"],"rows":[["","Proposed Device","Predicate Device"],["510(k) Number","TBD","K103576"],["Applicant","Microsoft","MIM Software"],["Device Name","Radiomics App","MIM 5.2"],["Classification\nRegulation","892.2050 – Picture Archiving and\nCommunication System","892.2050 – Picture Archiving and\nCommunication System"],["Product Code","LLZ","LLZ"],["Indications for Use","Microsoft Radiomics Advanced\nImage Contouring v1.0 (Radiomics\nApp) is a software-only medical\ndevice intended for use by trained\nradiation oncologists, dosimetrists\nand physicists to derive optimal organ\nand tumor contours for input to\nradiation treatment planning.\nSupported image modalities are\nComputed Tomography and Magnetic\nResonance. Radiomics App assists in\nthe following scenarios:\nLoad, save and display of medical\nimages and contours for treatment\nevaluation and treatment planning.\nCreation, transformation, and\nmodification of contours for\napplications including, but not limited\nto: transferring contours to\nradiotherapy treatment planning\nsystems, aiding adaptive therapy, and\narchiving contours for patient follow-\nup.\nLocalization and definition of both\nsolid tumors and healthy anatomical\nstructures.\nFusion display of compatible images\nfor treatment planning.\nThree-dimensional rendering of\nmedical images and the segmented\ncontours.\nImages reviewed using the Radiomics","MIM 5.2 software is used by trained\nmedical professionals as a tool to aid in\nevaluation and information management\nof digital medical images. The medical\nimage modalities include, but are not\nlimited to, CT, MRI, CR, DX, MG, US,\nSPECT, PET and XA as supported by\nACRINEMA DICOM 3.0. MIM 5.2\nassists in the following indications\nReceive, transmit, store, retrieve, display,\nprint, and process medical images and\nDICOM objects.\nCreate, display and print reports from\nmedical images.\nRegistration, fusion display, and review\nof medical images for diagnosis,\ntreatment evaluation, and treatment\nplanning.\nEvaluation of cardiac left ventricular\nfunction and perfusion, including left\nventricular end-diastolic volume, end-\nsystolic volume, and ejection fraction.\nLocalization and definition of objects\nsuch as tumors and normal tissues in\nmedical images.\nCreation, transformation, and\nmodification of contours for applications\nincluding, but not limited to, quantitative\nanalysis, aiding adaptive therapy,\ntransferring contours to radiation therapy\ntreatment planning systems, and\narchiving contours for patient follow-up"]],"caption_candidate":"proposed Radiomics App and the predicate MIM Software.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173420-p7-t0","doc_id":"K173420","page_num":7,"bbox":[66.62,50.76,545.52,631.18],"n_rows":12,"n_cols":3,"columns":["","Proposed Device","Predicate Device"],"rows":[["","Proposed Device","Predicate Device"],["","App software should not be used for\nprimary image interpretations.\nRadiomics App is not for use with\ndigital mammography.","and management.\nQuantitative and statistical analysis of\nPET/SPECT brain scans by comparing to\nother registered PET/SPECT brain scans.\nPlanning and evaluation of permanent\nimplant brachytherapy procedures.\nLossy compressed mammographic\nimages and digitized film screen images\nmust not be reviewed for primary image\ninterpretations. Images that are printed to\nfilm must be printed using a FDA-\napproved printer for the diagnosis of\ndigital mammography images.\nMammographic images must be viewed\non a display system that has been cleared\nby the FDA for the diagnosis of digital\nmammography images. The software is\nnot to be used for mammography CAD."],["Intended users","Healthcare providers","Healthcare providers"],["Contouring modes","Assisted and automatic","Assisted and automatic"],["Types of tissue\ncontoured","Tumors and normal tissues","Tumors and normal tissues"],["Measurements","2D distance measurement, average\ntissue density within a region (for\nCT), segmentation volume","2D distance measurement, segmentation\nvolume, average tissue density within a\nregion (for CT)"],["Image Fusion","Fuse only two 3D images, CT and\nMR","Fuse medical images from multiple\nmodalities"],["3D image\nrendering","Yes","Yes"],["Cardiac\napplications","No","Yes"],["Dose visualization\nand manipulation","No","Yes"],["Image modalities","CT and MR","CT, MRI, CR, DX, MG, US, SPECT,\nPET and XA"],["Platform","Stand-alone package which operates\non Microsoft Windows operating\nsystems only.","Stand-alone package which operates on\nboth Windows and Mac computer\nsystems."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173444-p6-t0","doc_id":"K173444","page_num":6,"bbox":[66.61,85.87,725.39,528.18],"n_rows":14,"n_cols":11,"columns":["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],"rows":[["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],["","","Extensible Imaging (QTxI)","","","EXINI, K122205","","","MIM4.1 (Seastar), K071964","",""],["","","","","","","","","","",""],["","","Subject Device","","","Predicate Device","","","Supporting Predicate Device","",""],["Product Code","LLZ","","","LLZ","","","LLZ","","","Nodifference"],["Regulation\nNumber","892.2050","","","892.2050","","","892.2050","","","Nodifference"],["Regulatory\nClass","II","","","II","","","II","","","Nodifference"],["Review Panel","Radiology","","","Radiology","","","Radiology","","","No difference"],["Predicate\nDevice","Exini Diagnostics AB;\nEXINI (K122205)","","","MEQIA, IBIS Explorer and Markup\nSoftware (K111319)","","","MIM4.0 (K060816); IKOEngelo\n(K061006); Centricity PACS\n(K043415)","","","N/A"],["510(k)/ Type","K173444, Traditional","","","K122205, Traditional","","","K071964, Traditional","","","No difference"],["Features","Receive, store, retrieve, display\nand process digital medical\nimages, as well as create,\ndisplay and print reports from\nthose images","","","Software tool set for acceptance, transfer,\nstorage, image display, manipulation and\nquantification of digital medical images.","","","Receive, transmit, store, retrieve,\ndisplay, print and process digital\nmedical images, as well as create,\ndisplay and print reports from those\nimages","","","No difference"],["Medical\nModalities","DICOM CT and PET as\nsupported by\nACR/NEMA DICOM 3.0","","","Nuclear imaging (NM) and computed\ntomography (CT) as supported by\nDICOM 3.0 standard.","","","CT, MRI, CR, DX, MG, US,\nSPECT, PET and XA as supported\nby ACR/NEMA DICOM 3.0.","","","QTxI does not utilize\nas many medical\nmodalities as\npredicate, but does\nutilize equivalent\nmodalities in those\nused by both systems."],["Operating\nSystem","Window 7 or Windows 10","","","Microsoft Windows operating system","","","Windows 2000/XP","","","QTxI uses newer\nversions of MicroSoft\nWindows software"],["Methodology","Identifies Regions of Interest\n(ROI) and performs ROI\ncontouring allowing\nquantitative/statistical analysis\nof full or partial-body scans\nthrough registration to template\nspace","","","The device uses image processing\ntechniques for segmentation of skeletal\nregions, normalization and hotspot\ncontouring/ segmentation. This device is\nsemi-automatic in that it requires a\nmanual step (hotspot verification step)\nwhere the user reviews and edits the\nselection of hotspots that are used as\ninput for quantitative analysis. The device\nperforms quantitative analysis based on\n2D ROI (regions of interests)\nmeasurements in whole body bone scans.","","","Generates contours using a\ndeformable registration technique\nwhich registers pre-contoured\npatients to target patients.\nRegistrations are either between a\nserial pair of intra-patient volumes\nor between a pre-existing atlas of\ncontoured patients and a patient\nvolume","","","All devices perform\ncentering analyses\nutilizing a template\nmodel. QTxI also\nregisters regions of the\npatient."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173444-p7-t0","doc_id":"K173444","page_num":7,"bbox":[66.65,85.87,725.35,476.64],"n_rows":5,"n_cols":11,"columns":["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],"rows":[["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],["","","Extensible Imaging (QTxI)","","","EXINI, K122205","","","MIM4.1 (Seastar), K071964","",""],["","","","","","","","","","",""],["","","Subject Device","","","Predicate Device","","","Supporting Predicate Device","",""],["Indications for\nUse","Quantitative Total Extensible\nImaging (QTxI) is a software\ntool used to aid in evaluation\nand information management of\ndigital medical images by\ntrained medical professionals\nincluding, but not limited to,\nradiologists, oncologists,\nnuclear medicine physicians,\nmedical imaging technologists,\ndosimetrists and physicists. The\nmedical modalities of these\nmedical images include DICOM\nCT and PET as supported by\nACR/NEMA DICOM 3.0.\nQTxI assists in the following\nindications:\n Receive, store, retrieve,\ndisplay and process digital\nmedical images\n Create, display and print\nreports from those images\n Provide medical\nprofessionals with the\nability to display, register,\nand fuse medical images","","","EXINI is intended to be used by trained\nhealthcare professionals and researchers\nfor acceptance, transfer, storage, image\ndisplay, manipulation, quantification and\nreporting of digital medical images. The\nsystem is intended to be used with images\nacquired using nuclear imaging (NM) and\ncomputed tomography (CT). The software\nprovides general\nPicture Archiving and Communications\nSystem (PACS) tools and a clinical\napplication for oncology including lesion\nmarking and analysis.","","","MIM 4.1 (SEASTAR) software is\nused by trained medical\nprofessionals as a tool to aid in\nevaluation and information\nmanagement of digital medical\nimages. The medical image\nmodalities include, but are not\nlimited to, CT, MRI, CR, DX, MG,\nUS, SPECT, PET and XA as\nsupported by ACR/NEMA DICOM\n3.0. MIM 4.1\n(SEASTAR) assists in the following\nindications:\n Receive, transmit, store,\nretrieve, display, print, and\nprocess medical images and\nDICOM objects.\n Create, display and print\nreports from medical images.\n Registration, fusion display,\nand review of medical images\nfor diagnosis, treatment,\nevaluation, and treatment\nplanning.\n Evaluation of cardiac left\nventricular function and\nperfusion, including left\nventricular end-diastolic\nvolume, end-systolic volume,\nand ejection fraction.","","","All systems are used to\nreceive, store, retrieve,\ndisplay, and process\nmedical images and\nDICOM objects.\nThis is accomplished\nvia registration to a\ntemplate space and\nsubsequent analysis of\nthe image data.\nThe predicate device\nhas multiple uses in\nthe therapeutic space,\nwhich is not specific to\nany device."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173444-p8-t0","doc_id":"K173444","page_num":8,"bbox":[66.65,85.87,725.35,351.84],"n_rows":5,"n_cols":11,"columns":["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],"rows":[["Specification /\nCharacteristic","","Quantitative Total","","","Exini Diagnostics AB;","","","MlMvista Corp.","","Comparison to\nPredicate(s)"],["","","Extensible Imaging (QTxI)","","","EXINI, K122205","","","MIM4.1 (Seastar), K071964","",""],["","","","","","","","","","",""],["","","Subject Device","","","Predicate Device","","","Supporting Predicate Device","",""],["Indications for\nUse\n(continued)"," Identify Regions of\nInterest (ROIs) and\nperform ROI contouring\nallowing quantitative/\nstatistical analysis of full or\npartial body scans\n Evaluate quantitative\nchange in ROIs (total or\npartial body; individual\nROI within individual) with\n3D interactive rendering of\nimages with highlighted\nROIs.","","","","",""," Localization and definition of\nobjects such as tumors and\nnormal tissues in medical\nimages.\n Creation, transformation, and\nmodification of contours for\napplications including, but not\nlimited to, quantitative analysis,\naiding adaptive therapy,\ntransferring contours to\nradiation therapy treatment\nplanning systems, and\narchiving contours for patient\nfollow-up and management\n Quantitative and statistical\nanalysis of PET/SPECT brain\nscans by comparing to other\nregistered PET/SPECT brain\nscans.","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p4-t0","doc_id":"K173542","page_num":4,"bbox":[86.04,126.0,540.55,237.64],"n_rows":5,"n_cols":4,"columns":["","510(k) Sponsor","","Arterys Inc."],"rows":[["","510(k) Sponsor","","Arterys Inc."],["Address","Address","","51 Federal St. Suite 305\nSan Francisco, CA 94107"],["Correspondence Person","","","John Axerio-Cilies\nCOO and Founder"],["Contact Information","","","Email: quality@arterys.com\nPhone: 650-391-7111"],["","Date Prepared","","Nov. 15, 2017"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p4-t1","doc_id":"K173542","page_num":4,"bbox":[86.04,270.48,540.55,350.44],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","Arterys Oncology DL"],"rows":[["","Proprietary Name","","Arterys Oncology DL"],["","Common Name","","Oncology"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","21 CFR 892.2050"],["","Product Code","","LLZ"],["","Regulatory Class","","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p4-t2","doc_id":"K173542","page_num":4,"bbox":[86.04,383.52,540.55,466.84],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","syngoTM TrueD"],"rows":[["","Proprietary Name","","syngoTM TrueD"],["Premarket Notification","Premarket Notification","","K101749"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","21 CFR 892.2050"],["","Product Code","","LLZ"],["","Regulatory Class","","II"]],"caption_candidate":"TM","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p4-t3","doc_id":"K173542","page_num":4,"bbox":[86.04,506.16,540.55,588.28],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","Arterys Cardio DL"],"rows":[["","Proprietary Name","","Arterys Cardio DL"],["Premarket Notification","Premarket Notification","","K163253"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","21 CFR 892.2050"],["","Product Code","","LLZ"],["","Regulatory Class","","II"]],"caption_candidate":"4. Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p5-t0","doc_id":"K173542","page_num":5,"bbox":[108.79,563.08,504.2,700.89],"n_rows":3,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device:\nArterys Oncology DL","Predicate Device\n(Primary):\nsyngoTM TrueD\n(K101749)","Reference\nDevice:\nArterys Cardio\nDL\n(K163253)"],"rows":[["Feature/\nFunction","Proposed Device:\nArterys Oncology DL","Predicate Device\n(Primary):\nsyngoTM TrueD\n(K101749)","Reference\nDevice:\nArterys Cardio\nDL\n(K163253)"],["Image input","Complies with\nDICOM Standard","Complies with\nDICOM & DICOM\nRT Standards",""],["Type of scans","MR, CT","MR, CT, PET,\nSPECT",""]],"caption_candidate":"Table 5.1: Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173542-p6-t0","doc_id":"K173542","page_num":6,"bbox":[108.77,73.0,504.21,608.73],"n_rows":10,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device:\nArterys Oncology DL","Predicate Device\n(Primary):\nsyngoTM TrueD\n(K101749)","Reference\nDevice:\nArterys Cardio\nDL\n(K163253)"],"rows":[["Feature/\nFunction","Proposed Device:\nArterys Oncology DL","Predicate Device\n(Primary):\nsyngoTM TrueD\n(K101749)","Reference\nDevice:\nArterys Cardio\nDL\n(K163253)"],["2D and 3D Image\nReview","Yes","Yes",""],["2D and 3D\nComparative\nReview","Yes","Yes",""],["Manual-\nVolumetric\nSegmentation","Yes","Yes",""],["Co-registration","Yes","Yes",""],["Longitudinal\nTracking","Yes, linked VOIs\nbetween timepoints","Yes, linked VOIs\nbetween timepoints",""],["Linear Dimension\nCalculation for\nVolumetric\nSegmentation","Yes,\nlongest linear\ndimension (mm) in\naxial plane, and\northogonal to longest\nlinear dimension","Yes, maximum\ndiameter (mm)\nmeasurement",""],["Volume\nCalculation","Yes","Yes",""],["Reporting","Yes, basic reporting\nand\nLI-RADS and Lung-\nRADS observation\nreporting based on\nstandard guidelines","Yes, basic reporting",""],["Semi-automated,\nVolumetric\nSegmentation","Yes, available only\nfor lung CT and liver\nMR studies","","Yes, available for\nventricular\nsegmentation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173574-p6-t0","doc_id":"K173574","page_num":6,"bbox":[79.58,118.18,532.7,666.82],"n_rows":12,"n_cols":3,"columns":["Characteristics","Predicate Device\nDENSEEMAMMO v1.0 (K152009)","Submission Device\nDENSEEMAMMO v1.2"],"rows":[["Characteristics","Predicate Device\nDENSEEMAMMO v1.0 (K152009)","Submission Device\nDENSEEMAMMO v1.2"],["Classification","LLZ\n892.2050","LLZ\n892.2050"],["Software level of concern","Moderate","Moderate"],["Device type","Not an interpretive or diagnostic aid","Not a diagnostic aid"],["Intended Use","DenSeeMammo is a software\napplication intended for use with digital\nmammography systems.\nDenSeeMammo estimates BI-RADS\nbreast density value by analyzing\nprocessed digital 2D mammograms\nusing a fully automated comparison\nprocedure.\nDenSeeMammo provides a BI-RADS\nbreast density 5th Edition category to\naid radiologists in the assessment of\nbreast density.\nDenSeeMammo produces adjunctive\ninformation. It is not an interpretive or\ndiagnostic aid when the final\nassessment of breast density category is\nmade by an MQSA-qualified interpreting\nphysician.\nDenSeeMammo core software has been\nbuilt and tested on OS X based\ncomputers. DenSeeMammo graphical\nuse interface software has been built\nand tested on Windows, OS X and Linux\nbased computers.","DenSeeMammo is a software application\nintended for use with Full Field Digital\nMammography systems.\nDenSeeMammo estimates BI-RADS\nbreast density category by analyzing\nprocessed digital 2D mammograms using\na fully automated comparison procedure.\nDenSeeMammo provides a BI-RADS\nbreast density 5th Edition category to aid\nradiologists in the assessment of breast\ndensity.\nDenSeeMammo produces adjunctive\ninformation. It is not a diagnostic aid\nsince the final assessment of breast\ndensity category is made by an MQSA\nqualified interpreting physician.\nDenSeeMammo core software has been\nbuilt and tested on OS X based\ncomputers.\nDenSeeMammo graphical use interface\nsoftware has been built and tested on\nWindows, OS X and Linux based\ncomputers.\nDenSeeMammo v1.2 is compatible for\nimages obtained from GE Senographe\nEssentials and Hologic Selenia Dimension\nsystems."],["Intended users","Radiologists","Radiologists"],["Patient population","Symptomatic and asymptomatic women\nundergoing mammography","Symptomatic and asymptomatic women\nundergoing mammography"],["Image source","Digital mammography images","Digital mammography images"],["Compatibility","GE Digital Mammography systems","GE and Hologic Digital Mammography\nsystems"],["Anatomical area","Breast","Breast"],["Assessment scope","Provides results per patient based on\nthe maximum density category of the\ntwo breasts","Provides results per patient based on the\nmaximum density category of the two\nbreasts"],["Assessment type","Comparison to qualified databases\ncontaining images previously visually\nassessed by MQSA-qualified radiologists\nusing ACR BI-RADS V recommendations","Comparison to qualified databases\ncontaining images previously visually\nassessed by MQSA-qualified radiologists\nusing ACR BI-RADS V recommendations"]],"caption_candidate":"Table 1 Substantial Equivalence comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173574-p7-t0","doc_id":"K173574","page_num":7,"bbox":[79.58,71.62,532.7,200.26],"n_rows":4,"n_cols":3,"columns":["Characteristics","Predicate Device\nDENSEEMAMMO v1.0 (K152009)","Submission Device\nDENSEEMAMMO v1.2"],"rows":[["Characteristics","Predicate Device\nDENSEEMAMMO v1.0 (K152009)","Submission Device\nDENSEEMAMMO v1.2"],["Measures provided","For each breast: BI-RADS V breast\ndensity category\nFor each patient: BI-RADS V breast\ndensity category","For each breast: BI-RADS V breast\ndensity category\nFor each patient: BI-RADS V breast\ndensity category"],["Operating environment","Software core: OS X based computers\nSoftware graphical user interface:\nWindows, OS X or Linux based\ncomputers","Software core: OS X based computers\nSoftware graphical user interface:\nWindows, OS X or Linux based\ncomputers"],["Deployment","Stand-alone computer","Stand-alone computer"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173588-p9-t0","doc_id":"K173588","page_num":9,"bbox":[74.57,175.46,570.42,710.86],"n_rows":22,"n_cols":7,"columns":["#","","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],"rows":[["#","","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],["","","","","","Informatics) System",""],["","","","","","(K160315)",""],["","","","","","(Primary Predicate Device)",""],["","","","","","",""],["1.","","Software Image\nmanagement system","Yes","Yes","",""],["2.","","Hardware Platform\nrequirements","Yes","Yes","",""],["","System Configuration","","","","",""],["","","","","","",""],["3.","","Windows Operating\nSystem","Yes","Yes","",""],["4.","","TCP-IP Network\nProtocol","Yes","Yes","",""],["5.","","Supports High\nResolution\nDiagnostic\nMonitors","Yes","Yes","",""],["6.","","Storage capabilities","Yes","Yes","",""],["7.","","Multiple monitor\nsupport","Yes","Yes","",""],["","Communication and Interoperability with other image management systems","","","","",""],["","","","","","",""],["8.","","Supports DICOM\nstudies received\nfrom different\nmodalities types","Yes\nCT, MR, US, XA, DX, CR,\nRF, PET, SC, SPECT,\nas well as hospital/radiology\ninformation system","Yes","",""],["9.","","Mammography","No","No","",""],["10.","","Accepts patient and\nexam updates","Yes","Yes","",""],["","Operating Platform requirements","","","","",""],["","","","","","",""],["11.","","Client-server\ntechnology","Yes","Yes","",""]],"caption_candidate":"Table No.2- 1 Technological characteristics comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173588-p10-t0","doc_id":"K173588","page_num":10,"bbox":[74.57,78.06,570.42,711.82],"n_rows":23,"n_cols":7,"columns":["#","","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],"rows":[["#","","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],["","","","","","Informatics) System",""],["","","","","","(K160315)",""],["","","","","","(Primary Predicate Device)",""],["","","","","","",""],["","","","","","",""],["12.","","Thin client installer","Yes","Yes","",""],["13.","","Multiple concurrent\nuser support","Yes\n▪ Up to 50 concurrent users\nusing hosted client\n▪ Up to 150 concurrent users\nusing Enterprise Viewer","Yes\n▪ Up to 10 concurrent users","",""],["","Management tools","","","","",""],["","","","","","",""],["14.","","Auditing Tool","Yes","Yes","",""],["15.","","Client installer","Yes","Yes","",""],["16.","","System\nmanagement","Yes","Yes","",""],["17.","","Security and\nPrivacy","Yes","Yes","",""],["","","","","","",""],["","Viewing and Image Processing","","","","",""],["","","","","","",""],["","","","","","",""],["","","","","","",""],["","","","","","",""],["","","","","","",""],["18.","","Supported Data and\nMulti Modalities","Supports receiving, sending,\nstoring and displaying studies\nreceived from the following\nmodalities via DICOM:\nCT, MR, US, XA, DX, CR,\nRF, PET, SPECT and SC as\nwell as hospital /radiology\ninformation systems.","Supports receiving, sending, storing\nand displaying studies received from\nthe following modalities via DICOM:\nCT, MR, US, XA, DX, CR, RF, PET\nand SC as well as hospital /radiology\ninformation systems.","",""],["19.","","2D viewing\ncapabilities","Yes","Yes","",""]],"caption_candidate":"Qsite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173588-p11-t0","doc_id":"K173588","page_num":11,"bbox":[74.56,78.06,570.44,678.7],"n_rows":14,"n_cols":6,"columns":["#","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],"rows":[["#","Specification /\nFeature","Illumeo System\n(Proposed device)","","I4 (Integrated Intelligent Imaging",""],["","","","","Informatics) System",""],["","","","","(K160315)",""],["","","","","(Primary Predicate Device)",""],["","","","","",""],["","","","","",""],["20.","3D viewing\ncapabilities","Yes","Yes","",""],["21.","Finding creation\nand management\ntool","Yes","Yes","",""],["22.","Comparison and\nSynchronization\nbetween volumetric\nseries","Yes","Yes","",""],["23.","Hanging protocols\n(HP)","Yes","Yes","",""],["24.","Advanced vessel\nanalysis\nvisualization and\nevaluation mode -\nVascular\nQuantification\nInspector (Vascular\nInspection Mode)","Yes","Yes","",""],["25.","Incorporation of\nnon-imaging data in\npatient context\n(Patient Briefing)","Yes","Yes","",""],["26.","Enterprise\nDiagnostic web\nviewer","Yes","Yes","",""],["27.","Non - Diagnostic\nEnterprise web\nviewer","Yes","Yes","",""]],"caption_candidate":"Qsite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173605-p5-t0","doc_id":"K173605","page_num":5,"bbox":[77.92,288.96,482.0,587.95],"n_rows":12,"n_cols":7,"columns":["Parameter","","Predicate Device","","","Subject Device",""],"rows":[["Parameter","","Predicate Device","","","Subject Device",""],["","","SharpView (K993802)","","","iQMR",""],["Intended use","Intended for use by qualified\ntrained medical professionals for\nenhancement of MRI images that\nare transferred in the network in\nDICOM format.","","","The same","",""],["21CFR section","892.2050","","","The same","",""],["Product Code","LLZ","","","The same","",""],["Technological\nCharacteristics","","","","","",""],["Device nature","SW package","","","The same","",""],["Operating System","Windows","","","Linux","",""],["Data input","MRI images in DICOM format","","","The same","",""],["Data output","MRI images in DICOM format","","","The same","",""],["Processing\nAlgorithms","GOP Enhancement Software","","","Medic Vision's\nAlgorithms","",""],["User Interface","Included","","","The same","",""]],"caption_candidate":"Comparison with the predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173780-p6-t0","doc_id":"K173780","page_num":6,"bbox":[66.27,508.0,533.77,717.42],"n_rows":5,"n_cols":9,"columns":["","","","","Bay Labs EchoMD Automated Ejection","","","DiaCardio, Ltd, LVivo EF Software",""],"rows":[["","","","","Bay Labs EchoMD Automated Ejection","","","DiaCardio, Ltd, LVivo EF Software",""],["","","","","Fraction Software Application","","","Application (K130779, Predicate)",""],["Product Code","","","LLZ","","","LLZ","",""],["Intended Use","","","The Bay Labs, Inc. EchoMD Automated\nEjection Fraction software is used to\nprocess previously acquired transthoracic\ncardiac ultrasound images, to store images,\nand to manipulate and make\nmeasurements on images using a personal\ncomputer or a compatible DICOM-\ncompliant PACS system in order to provide\nautomated estimation of left ventricular\nejection fraction. This measurement can be\nused to assist the clinician in a cardiac\nevaluation.","","","DiaCardio's L Vivo EF Software\nApplication is intended for non-invasive\nprocessing of already acquired\nechocardiographic images in order to\ndetect, measure, and calculate the left\nventricular wall for left ventricular\nfunction evaluation. This measurement\ncan be used to assist the clinician in a\ncardiac evaluation.","",""],["Machine Learning-\nBased Algorithm","","","Yes","","","Yes","",""]],"caption_candidate":"Comparison Table: EchoMD AutoEF versus Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173780-p7-t0","doc_id":"K173780","page_num":7,"bbox":[66.25,72.36,533.79,420.58],"n_rows":14,"n_cols":9,"columns":["","","","","Bay Labs EchoMD Automated Ejection","","","DiaCardio, Ltd, LVivo EF Software",""],"rows":[["","","","","Bay Labs EchoMD Automated Ejection","","","DiaCardio, Ltd, LVivo EF Software",""],["","","","","Fraction Software Application","","","Application (K130779, Predicate)",""],["Operates on DICOM\nclips","","","Yes","","","Yes","",""],["Automation level","","","Fully automated, including clip selection","","","Fully automated (with manually-\nselected clips)","",""],["EF Method","","","Biplane (non-segmentation/non-\nendocardial trace)","","","Biplane Method of Disks\nSegmentation (endocardial trace)","",""],["Offline EF evaluation\nusing clips from multiple\nultrasound scanners","","","Yes","","","Yes","",""],["Image Clip Selection","","","Automated","","","Manual","",""],["Automated Ejection\nFraction Calculation","","","Yes","","","Yes","",""],["Ejection Fraction\nreported","","","Whole number estimate (percentage)","","","Whole number estimate\n(percentage)","",""],["Algorithm Confidence","","","Qualitative and quantitative user\nfeedback on transthoracic cardiac\nultrasound image quality","","","Display of endocardial border tracing","",""],["EF Result shown with\nvideo clip","","","Yes","","","Yes","",""],["User confirmation/\nrejection of result","","","Yes","","","Yes","",""],["Manual editing of\nautomated result by\nuser","","","Yes (on PACS workstation)","","","Yes (in application)","",""],["Left ventricular volumes\nmeasurements","","","Not internal. Uses manual trace option\nPACS workstation","","","Yes","",""]],"caption_candidate":"K173780","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173810-p5-t0","doc_id":"K173810","page_num":5,"bbox":[72.26,307.61,539.86,653.74],"n_rows":2,"n_cols":3,"columns":["Feature/Characteristic","Predicate Device\nVentriPoint Medical System IS-1\n(K150628)","Submission Device\nVMS+"],"rows":[["Feature/Characteristic","Predicate Device\nVentriPoint Medical System IS-1\n(K150628)","Submission Device\nVMS+"],["Intended\nUse/Indications for Use","The VMS System is an adjunct to\nexisting ultrasound imaging\nsystems and is intended to record,\nanalyze, store and retrieve digital\nultrasound images for\ncomputerized 3-dimensional\nimage processing.\nThe VMS system is indicated for\nuse where RV volumes and\nejection fractions are warranted or\ndesired.","The VMS+ system is\nan adjunct to existing\nultrasound imaging\nsystems and is\nintended to record,\nanalyze, store and\nretrieve digital\nultrasound images for\ncomputerized 3-\ndimensional image\nprocessing.\nThe VMS+ system is\nindicated for use\nwhere Left Ventricle\n(LV), Right Ventricle\n(RV), Left Atrium (LA),\nand Right Atrium (RA)\nvolumes and ejection\nfractions are warranted\nor desired."]],"caption_candidate":"intended use and technological characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173810-p6-t0","doc_id":"K173810","page_num":6,"bbox":[72.27,86.9,539.85,354.05],"n_rows":10,"n_cols":3,"columns":["Freehand scanning\ndevice","Yes","Yes"],"rows":[["Freehand scanning\ndevice","Yes","Yes"],["RV volume\nmeasurement","Yes","Yes"],["3-D Reconstruction","Knowledge Based Reconstruction\ndatabase","Knowledge Based\nReconstruction\ndatabase"],["Software Based\nAnalysis Tool","Yes","Yes"],["UL 60601-1","Yes","Yes"],["UL 60601-2","Yes","Yes"],["Windows OS based\nanalysis system","Yes","Yes"],["Real-time Video\nCapture card","Yes","Yes"],["External ECG trigger","Yes","Yes"],["Pulsed DC 6DOF\nmagnetic tracking\nsystem","Yes","Yes"]],"caption_candidate":"510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173810-p6-t1","doc_id":"K173810","page_num":6,"bbox":[72.27,451.27,539.85,591.19],"n_rows":4,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","IEC 60601-1, Medical electrical equipment – Part 1:\nGeneral requirements for basic safety and essential\nperformance 3rd edition.","",""],["IEC 60601-1-2","","","Medical electrical equipment – Part 1-2: General\nrequirements for basic safety and essential performance\nCollateral standard: Electromagnetic compatibility –\nRequirements and tests 2nd edition.","",""],["ISO 14971:2007","","","Medical devices – Application of risk management to\nmedical devices","",""]],"caption_candidate":"comply with the following voluntary standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p4-t0","doc_id":"K173821","page_num":4,"bbox":[108.26,135.86,551.62,510.91],"n_rows":12,"n_cols":2,"columns":["Submitter","Thirona Corporation"],"rows":[["Submitter","Thirona Corporation"],["Contact Person","Eva van Rikxoort\nManaging Director\nThirona BV\nToernooiveld 300\n6525 EC Nijmegen\nthe Netherlands\nPhone: +31 (0)647142838\nE-mail: evavanrikxoort@thirona.eu"],["Date Prepared","June X, 2018"],["Trade Name","LungQ"],["Common Use/Usual\nName","Computer Tomography X-ray system"],["Product Code","JAK"],["Classification","Class II, 21 CFR 892.1750"],["Device Panel","Radiology"],["Predicate Device","VIDA PW2"],["Predicate Classification","Class II, 21 CFR 892.1750"],["Reference Device","Imbio CT Lung Density Analysis Software"],["Reference Classification","Class II, 21 CFR 892.1750"]],"caption_candidate":"Section 2.0 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p5-t0","doc_id":"K173821","page_num":5,"bbox":[108.28,191.16,539.84,453.43],"n_rows":12,"n_cols":6,"columns":["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],"rows":[["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],["","","","","Lung Density",""],["","","","","Analysis",""],["","","","","Software",""],["","","","","Imbio LLC",""],["","","","","K141069",""],["","","","","(Reference",""],["","","","","Device)",""],["Product Code","JAK","Identical","Identical","",""],["Regulation\nNumber","21 CFR 892.1750","Identical","Identical","",""],["Device\nClassification","Class II","Identical","Identical","",""],["Common Name","Software Accessory to a\nComputed tomography\nx-ray system","Identical","Identical","",""]],"caption_candidate":"reference devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p6-t0","doc_id":"K173821","page_num":6,"bbox":[108.28,108.35,539.84,694.54],"n_rows":13,"n_cols":6,"columns":["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],"rows":[["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],["","","","","Lung Density",""],["","","","","Analysis",""],["","","","","Software",""],["","","","","Imbio LLC",""],["","","","","K141069",""],["","","","","(Reference",""],["","","","","Device)",""],["Intended Use","The Thirona LungQ\nsoftware provides CT\nvalues for pulmonary\ntissue which is essential\nfor providing\nquantitative support for\ndiagnosis and follow up\nexamination. The\nLungQ software can be\nused to support\nphysician in the\ndiagnosis and\ndocumentation of\npulmonary tissues\nimages (e.g.,\nabnormalities) from CT\nthoracic datasets. Three-\nD segmentation and\nisolation of sub-\ncompartments,\nvolumetric analysis,\ndensity evaluations,\nfissure evaluation, and\nreporting tools are\nprovided.","Nearly Identical","Nearly Identical","",""],["Modality","CT","Identical","Identical","",""],["Data Loading","DICOM","Identical","Identical","",""],["Application","Command-line interface","Includes a\nworkstation","Identical","",""],["Segmentation","Provides 3D\nsegmentation","Identical","Identical","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p7-t0","doc_id":"K173821","page_num":7,"bbox":[108.28,108.35,539.84,676.9],"n_rows":12,"n_cols":6,"columns":["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],"rows":[["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],["","","","","Lung Density",""],["","","","","Analysis",""],["","","","","Software",""],["","","","","Imbio LLC",""],["","","","","K141069",""],["","","","","(Reference",""],["","","","","Device)",""],["","Provides Segmentation\nof the:\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper\nLobe\n• Right Middle\nLobe\n• Right Lower\nLobe","Identical","Similar","",""],["","Provides Airways\nSegmentation","Identical","Different","",""],["","User cannot manually\nedit segmentation","User can manually\nedit segmentation","Identical","",""],["Lung Volume\nAnalysis\nSupport","Ability to measure\nvolume for:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe","Identical","Similar","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p8-t0","doc_id":"K173821","page_num":8,"bbox":[108.28,108.35,539.84,601.18],"n_rows":13,"n_cols":6,"columns":["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],"rows":[["Item","LungQ\nThirona\n(Subject Device)","VIDA PW2\nVIDA\nDiagnostics\nK083227\n(Predicate\nDevice)","","Imbio CT",""],["","","","","Lung Density",""],["","","","","Analysis",""],["","","","","Software",""],["","","","","Imbio LLC",""],["","","","","K141069",""],["","","","","(Reference",""],["","","","","Device)",""],["Volume\nDensity\nAnalysis","Ability to measure\nvolume at multiple\ndensity ranges for:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe","Identical","Similar","",""],["","Ability to measure the\n15th percentile density\nanalysis","Identical","Different","",""],["","Does not perform low\ndensity cluster analysis","Does perform low\ndensity cluster\nanalysis","Identical","",""],["Fissure\nAnalysis","Ability to perform\nfissure evaluations","Identical","Does not\nperform fissure\nevaluations","",""],["Analyzed Data\nOutput","Provides a report","Identical","Identical","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p9-t0","doc_id":"K173821","page_num":9,"bbox":[108.26,273.89,526.3,429.19],"n_rows":6,"n_cols":4,"columns":["Category","Disease state","# of\nsubjects","% of\ndata set"],"rows":[["Category","Disease state","# of\nsubjects","% of\ndata set"],["Control subjects: current or former\nsmokers without airflow limitation","GOLD stage 0","112","44.80%"],["Subjects with COPD but with minimal\nairflow limitations","GOLD stage 1","26","10.40%"],["Subjects with COPD and with moderate to\nsevere airflow limitations","GOLD stage 2-\n4","76","30.40%"],["Subjects with preserved ratio but impaired\nspirometry","GOLD stage\nPRISm","33","13.20%"],["Control subjects: non-smokers","None","3","1.20%"]],"caption_candidate":"distribution of subjects with respect to their disease state is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173821-p10-t0","doc_id":"K173821","page_num":10,"bbox":[108.26,425.71,590.04,683.26],"n_rows":11,"n_cols":3,"columns":["Imaging parameters","Equivalence study","Fissure analysis"],"rows":[["Imaging parameters","Equivalence study","Fissure analysis"],["# of scans","250","55"],["Voxel spacing","0.50 - 0.97 mm","0.44 - 0.81 mm"],["Slice thickness","0.625 - 0.9 mm","0.6 - 1.5 mm"],["Slice spacing","0.45 - 0.625 mm","0.45 - 1.2 mm"],["Peak Kilovoltage","120 pKv","120 - 130 pKv"],["Scanner manufacture","GE MEDICAL SYSTEMS; SIEMENS;\nPhilips","SIEMENS; Philips"],["Scanner types","LightSpeed16; LightSpeed VCT;\nSensation 64; Definition; Sensation 16;\nDefinition AS+; SOMATOM Definition\nFlash; Brilliance 64; LightSpeed Pro 16;\nDiscovery CT750 HD; SOMATOM\nDefinition","Mx8000 IDT 16; iCT\n128; Volume Zoom;\nEmotion 16; Sensation\n64; Definition;\nSOMATOM Definition;"],["Reconstruction algorithms","Filtered back projection","Filtered back projection"],["Reconstruction kernels","STANDARD; B35f; B","B40f; B50s; B60f; B60s;\nB80f"],["milliampere second","200 mAs","NA"]],"caption_candidate":"analysis of LungQ 1.1.0 significantly outperforms the previously published version.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K173939-p7-t0","doc_id":"K173939","page_num":7,"bbox":[108.27,72.24,513.93,242.94],"n_rows":11,"n_cols":9,"columns":["","","","Dice index","","","Absolute difference of the relative\nvolumes [pp]","",""],"rows":[["","","","Dice index","","","Absolute difference of the relative\nvolumes [pp]","",""],["","CSF","","","0.78 ± 0.05","","","1.8 ± 1.0",""],["GM","","","0.84 ± 0.02","","","2.7 ± 2.0","",""],["","WM","","","0.86 ± 0.02","","","2.8 ± 1.9",""],["ICV","","","0.97 ± 0.00","","","","",""],["","Results of comparison between manual and automatic brain tissue segmentation. Reported values","","","","","","",""],["","are averages ± std. dev., computed over 6 segmented slices of 33 scans. The Dice index provides","","","","","","",""],["","a measure for overlap of manual and automatic segmentations (1 = perfect overlap). The absolute","","","","","","",""],["","differences of the relative volumes (of the brain tissues) are averages ± std. dev. in percentage","","","","","","",""],["","points.","","","","","","",""],["","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K180091-p5-t0","doc_id":"K180091","page_num":5,"bbox":[108.1,195.71,539.85,555.27],"n_rows":27,"n_cols":10,"columns":["Feature","","","","UNiD Spine Analyzer","","","UNiD Spine","","Surgimap 2.0\n(K141669)"],"rows":[["Feature","","","","UNiD Spine Analyzer","","","UNiD Spine","","Surgimap 2.0\n(K141669)"],["","","","","with additional","","","Analyzer (","",""],["","","","","component","","","K170172)","",""],["","Computer","","PC Compatible","","","PC Compatible","","","PC Compatible"],["","Operating","","Windows + MAC","","","Windows + MAC","","","Windows + MAC"],["","System","","","","","","","",""],["Image Input","","","Local","","","Local","","","Local + PACS\nconnectivity"],["","Runs on Server","","Yes","","","Yes","","","No"],["","Osteotomy","","Yes","","","Yes","","","Yes"],["","Module","","","","","","","",""],["","Generic","","Yes","","","Yes","","","Yes"],["","measurements","","","","","","","",""],["","Spine","","Yes","","","Yes","","","Yes"],["","measurements","","","","","","","",""],["","Pre-operative","","Yes","","","Yes","","","Yes"],["","planning","","","","","","","",""],["","Custom","","Yes","","","Yes","","","Yes"],["","implants","","","","","","","",""],["","Database","","Yes (implants)","","","No","","","Yes"],["","Case sharing","","No","","","No","","","Yes"],["","Human","","Required","","","Required","","","Required"],["","Intervention for","","","","","","","",""],["","interpretation","","","","","","","",""],["","and","","","","","","","",""],["","manipulation of","","","","","","","",""],["","images","","","","","","","",""],["","Web content","","Yes","","","Yes","","","Yes"]],"caption_candidate":"Table 1: Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K180161-p6-t0","doc_id":"K180161","page_num":6,"bbox":[67.44,151.08,544.56,718.92],"n_rows":7,"n_cols":3,"columns":["","Viz CTP","iSchemaView RAPID"],"rows":[["","Viz CTP","iSchemaView RAPID"],["Product Code","LLZ","LLZ"],["Regulation","21 C.F.R. § 892.2050","21 C.F.R. § 892.2050"],["Intended Use /\nIndications for\nUse","Viz CTP is an image processing\nsoftware package to be used by trained\nprofessionals, including but not limited\nto physicians and medical technicians.\nThe software runs on a standard \"off-\nthe-shelf\" computer or a virtual\nplatform, such as VMware, and can be\nused to perform image processing,\nanalysis, and communication of\ncomputed tomography (CT) perfusion\nscans of the brain. Data and images\nare acquired through DICOM-compliant\nimaging devices.\nViz CTP provides both analysis and\ncommunication capabilities for dynamic\nimaging datasets that are acquired with\nCT Perfusion imaging protocols.\nAnalysis includes calculation of\nparameters related to tissue flow\n(perfusion) and tissue blood volume.\nResults of image processing which\ninclude CT perfusion parameter maps\ngenerated from a raw CTP scan are\nexported in the standard DICOM format\nand may be viewed on existing\nradiological imaging viewers.","iSchemaView's RAPID is an image\nprocessing software package to be used\nby trained professionals, including but\nnot limited to physicians and medical\ntechnicians. The software runs on a\nstandard \"off-the-shelf\" computer or a\nvirtual platform, such as VMware, and\ncan be used to perform image viewing,\nprocessing and analysis of brain\nimages. Data and images are acquired\nthrough DICOM compliant imaging\ndevices.\niSchemaView's RAPID provides both\nviewing and analysis capabilities for\nfunctional and dynamic imaging\ndatasets acquired with CT Perfusion\nand MRI including a Diffusion Weighted\nMRI (DWl)Module and a Dynamic\nAnalysis Module (dynamic contrast\nenhanced imaging data for MRI and\nCT).\nThe DWl Module is used to visualize\nlocal water diffusion properties from the\nanalysis of diffusion weighted MRI data.\nThe Dynamic Analysis Module is used\nfor visualization and analysis of dynamic\nimaging data, showing properties of\nchanges in contrast over time. This\nfunctionality includes calculation of\nparameters related to tissue flow\n(perfusion) and tissue blood volume."],["PACS Functionality","",""],["Basic PACS\nFunctions","Yes","Same"],["Computer","Standard “Off-the-Shelf” PC","Same"]],"caption_candidate":"Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K180161-p7-t0","doc_id":"K180161","page_num":7,"bbox":[67.44,72.24,544.56,456.6],"n_rows":17,"n_cols":3,"columns":["Platform","Workstation or VMWare",""],"rows":[["Platform","Workstation or VMWare",""],["DICOM\nCompliance","Yes","Yes"],["Functional\nOverview","Viz CTP is a software package that\nprovides for the visualization and study\nof changes of tissue perfusion in digital\nimages captured by CT. Viz CTP allows\nviewing and quantification.","Same"],["Data\nAcquisition","Acquires medical image data from\nDICOM compliant imaging devices and\nmodalities.","Same"],["Data/Image\nTypes","Computed Tomography (CT)","Same"],["Acquisition and Modalities Features","",""],["CT","CT Perfusion (CTP)","Yes"],["Computed Parameter Maps","",""],["Perfusion CT","Cerebral Blood Flow (CBF)","Yes"],["","Cerebral Blood Volume (CBV)","Yes"],["","Mean Transit Time (MTT)","Yes"],["","Tissue residue function time to peak\n(TMax)","Yes"],["Measurements/Tools","",""],["CT Tools","Arterial Input Function (AIF)","Yes"],["","Brain mask","Yes"],["","Export perfusion files to PACS and\nDICOM file systems","Yes"],["","Acquire, transmit, process, and store\nmedical images.","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K180599-p13-t0","doc_id":"K180599","page_num":13,"bbox":[103.42,166.38,580.59,517.51],"n_rows":22,"n_cols":12,"columns":["Clinical Application\nAnatomy/Region of Interest","Mode of Operation","","","","","","","","","",""],"rows":[["Clinical Application\nAnatomy/Region of Interest","Mode of Operation","","","","","","","","","",""],["","B","M","PW\nDoppler","CW\nDoppler","Color\nDoppler","Color M\nDoppler","Power\nDoppler","Combined\nModes[*]","Harmonic\nImaging","Coded\nPulse(cid:105)","Other"],["Ophthalmic","","","","","","","","","","",""],["Fetal / Obstetrics","","","","","","","","","","",""],["Abdominal [1]","","","","","","","","","","",""],["Pediatric","","","","","","","","","","",""],["Small Organ [2]","","","","","","","","","","",""],["Neonatal Cephalic","","","","","","","","","","",""],["Adult Cephalic","","","","","","","","","","",""],["Pediatric Cardiac","","","","","","","","","","",""],["Adult Cardiac","P2","P2","P2","P2","P2","P2","","N","P2","P2","6"],["Peripheral Vascular","","","","","","","","","","",""],["Musculo-skeletal Conventional","","","","","","","","","","",""],["Musculo-skeletal Superficial","","","","","","","","","","",""],["Thoracic/Pleural [3]","","","","","","","","","","",""],["Exam Type, Means of Access","","","","","","","","","","",""],["Transesophageal","P2","P2","P2","P2","P2","P2","","N","P2","P2","6"],["Transrectal","","","","","","","","","","",""],["Transvaginal","","","","","","","","","","",""],["Interventional Guidance","","","","","","","","","","",""],["Vascular Access (IV, PICC)","","","","","","","","","","",""],["Nonvascular [5]","","","","","","","","","","",""]],"caption_candidate":"Intended Use: Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K180647-p6-t0","doc_id":"K180647","page_num":6,"bbox":[93.6,176.88,510.72,722.64],"n_rows":2,"n_cols":3,"columns":["","Aidoc Briefcase Software","Viz.AI ContaCT Software\n(DEN170073)"],"rows":[["","Aidoc Briefcase Software","Viz.AI ContaCT Software\n(DEN170073)"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-\nenhanced head CT images.\nThe device is intended to\nassist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of suspected\npositive findings of pathologies in\nhead CT images, namely\nIntracranial Hemorrhage (ICH).\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to\nthe ongoing standard of care\nimage interpretation. The user is\npresented with notifications for\ncases with suspected ICH\nfindings. Notifications\ninclude compressed preview\nimages that are\nmeant for informational purposes\nonly and not intended for\ndiagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing\nfull images per the standard of\ncare.","ContaCT is a notification-only,\nparallel workflow tool for use by\nhospital networks and\ntrained clinicians to identify and\ncommunicate images of specific\npatients to a specialist, independent\nof standard of care workflow.\nContaCT uses an artificial\nintelligence algorithm to analyze\nimages for findings\nsuggestive of a pre-specified clinical\ncondition and to notify an\nappropriate medical specialist of\nthese findings in parallel to standard\nof care image interpretation.\nIdentification of suspected findings\nis not for diagnostic use beyond\nnotification.\nSpecifically, the device analyzes CT\nangiogram images of the brain\nacquired in the acute setting, and\nsends notifications to a\nneurovascular specialist that a\nsuspected large vessel occlusion\nhas been identified and\nrecommends review of those\nimages. Images can be previewed\nthrough a mobile application.\nImages that are previewed through\nthe mobile application are\ncompressed and are for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification.\nNotified clinicians are responsible\nfor viewing non-compressed images\non a diagnostic viewer and\nengaging in appropriate patient\nevaluation and relevant discussion\nwith a treating physician before\nmaking care-related decisions or\nrequests. ContaCT is limited to\nanalysis of imaging data and should"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K180647-p7-t0","doc_id":"K180647","page_num":7,"bbox":[93.6,67.92,510.72,436.32],"n_rows":11,"n_cols":3,"columns":["","","not be used in-lieu of full patient\nevaluation or relied upon to make or\nconfirm diagnosis."],"rows":[["","","not be used in-lieu of full patient\nevaluation or relied upon to make or\nconfirm diagnosis."],["User population","Radiologist","Clinician (e.g. neurovascular\nspecialist)"],["Anatomical\nregion of interest","Head","Head"],["Data acquisition\nprotocol","Non contrast CT scan of the head\nor neck","CT angiogram images of the brain"],["View DICOM\ndata","DICOM Information about the\npatient, study and current image","DICOM Information about the\npatient, study and current image"],["Segmentation of\nregion of interest","No; device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the\noriginal image","No; device does not mark, highlight,\nor direct users’ attention to a\nspecific location in the original\nimage"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/Priorit\nization","Yes","Yes"],["Preview images","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases","Presentation of notification and\npreview of the study for initial\nassessment not meant for\ndiagnostic purposes\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases"],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K180799-p18-t0","doc_id":"K180799","page_num":18,"bbox":[71.96,178.84,539.97,553.87],"n_rows":31,"n_cols":3,"columns":["Reference No.","Year","Title"],"rows":[["Reference No.","Year","Title"],["AAMI/ANSI","2012","Medical Electrical Equipment - Part 1: General Requirements for Basic Safety and Essential"],["ES60601-1","","Performance"],["AAMI ANSI","2012","AAMI / ANSI ES60601-1:2005/(R)2012 And A1:2012, C1:2009/(R)2012 And A2:2010/(R)2012"],["ES60601-1","","(Consolidated Text) Medical Electrical Equipment - Part 1: General Requirements for Basic Safety"],["","","and Essential Performance (IEC 60601-1:2005, Mod). (General II (ES/EMC))"],["IEC 60601-1-2","2007","Medical electrical equipment – Part 1-2: General requirements for basic safety and essential"],["","&","performance – Collateral Standard: Electromagnetic Capability – Requirements and tests. (4th"],["","2014","Edition)"],["IEC 60601-1-6","2013","Medical electrical equipment - Part 1-6: General requirements for basic safety and essential"],["","","performance -Collateral standard: Usability"],["IEC 60601-1-12","2014","Medical Electrical Equipment — Part 1-12: General requirements for basic safety and essential"],["","","performance - Collateral Standard: Requirements for medical electrical equipment and medical"],["","","electrical systems used in the emergency medical services environment"],["IEC 60601-2-37","2004","Medical electrical equipment – Part 2-37: Particular requirements for the basic safety and essential"],["","","performance of ultrasonic medical diagnostic and monitoring equipment. (3rd and 4th Edition)"],["IEC 62133","2012","Secondary Cells and Batteries Containing Alkaline or Other Non-Acid Electrolytes - Safety"],["","","Requirements for Portable Sealed Secondary Cells, And for Batteries Made from Them, For Use in"],["","","Portable Applications [Including: Corrigendum 1 (2013)]"],["IEC 62366","2014","Consolidated Version Medical Devices - Application of Usability Engineering to Medical Devices"],["ISO 10993-1","2009","Biological evaluation of medical devices - Part 1: Evaluation and testing within a risk management"],["","","process"],["ISO 10993-5","2014","Biological Evaluation of Medical Devices - Part 5: Tests for In Vitro Cytotoxicity"],["ISO 10993-10","2014","Biological Evaluation of Medical Devices - Part 10: Tests for Irritation and Skin Sensitization"],["ISO 10993-11","2017","Biological evaluation of medical devices -- Part 11: Tests for systemic toxicity"],["ISO-10993-12","2014","Biological Evaluation of Medical Devices - Part 12: Sample Preparation and Reference Materials"],["ISO 62304","2006","Medical Device Software - Software Life Cycle Processes"],["ISO 15223-1","2012","Medical Devices - Symbols to be Used with Medical Devices Labels, Labeling, and Information to be"],["","","Supplied - Part 1: General Requirements"],["ISO 14971","2007","Medical Devices - Applications of Risk Management to Medical Devices"],["NEMA UD 2","2009","Acoustic Output Measurement Standard for Diagnostic Ultrasound Equipment - Revision 3"]],"caption_candidate":"Nonclinical performance tests show compliance to the following standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p4-t0","doc_id":"K181247","page_num":4,"bbox":[108.34,155.35,539.86,639.17],"n_rows":18,"n_cols":4,"columns":["Basis for the\nSubmission:","","","Vital Images, Inc. hereby submits this traditional 510(k) to provide a\nnotification submission for proposed software changes in the already\n510(k) cleared Vitrea CT Brain Perfusion software (K121213)."],"rows":[["Basis for the\nSubmission:","","","Vital Images, Inc. hereby submits this traditional 510(k) to provide a\nnotification submission for proposed software changes in the already\n510(k) cleared Vitrea CT Brain Perfusion software (K121213)."],["Submitter:","","","Vital Images, Inc.\n5850 Opus Parkway, Suite 300\nMinnetonka, MN, 55343-4414, USA"],["","Establishment","","2134213"],["","Registration:","",""],["Contact Person:","","","Susan Atwood\nPrincipal Quality Engineer\nPhone: 952-487-9759\nFax: 952-487-9510\nE-mail: satwood@vitalimages.com\nAlternate Contact Person:\nVince Swenson\nSr. Director of Quality and Regulatory\nPhone: 952-487-9548\nFax: 952-487-9510\nE-mail: vswenson@vitalimages.com"],["510(k) Type:","","","Traditional"],["Summary Date:","","","May 8, 2018"],["","Device Trade Name:","","Vitrea CT Brain Perfusion"],["","Device Common","","Picture Archiving and Communications System"],["","Name/ Regulatory","",""],["","Description:","",""],["","Device Classification","","System, Image Processing, Radiological"],["","Name:","",""],["Regulation Number:","","","21 CFR 892.2050"],["","Product Code:","","LLZ"],["","Regulatory","","Class II"],["","Classification:","",""],["Device Panel:","","","Radiology"]],"caption_candidate":"807.92(c).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p5-t0","doc_id":"K181247","page_num":5,"bbox":[108.31,115.58,539.81,184.46],"n_rows":2,"n_cols":9,"columns":["","Predicate Device","","","Manufacturer","","","FDA 510(k) Number",""],"rows":[["","Predicate Device","","","Manufacturer","","","FDA 510(k) Number",""],["Vitrea CT Brain Perfusion\nsoftware","","","Vital Images, Inc.\n5850 Opus Parkway, Suite 300\nMinnetonka, MN 55343\nUSA","","","K121213","",""]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p5-t1","doc_id":"K181247","page_num":5,"bbox":[108.31,213.59,539.81,282.41],"n_rows":2,"n_cols":9,"columns":["","Reference Device","","","Manufacturer","","","FDA 510(k) Number",""],"rows":[["","Reference Device","","","Manufacturer","","","FDA 510(k) Number",""],["Olea Sphere V3.0","","","Olea Medical\n93 Avenue Des Sorbiers,\nZone Athelia Iv\nLa Ciotat, FR 13600","","","K152602","",""]],"caption_candidate":"Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p6-t0","doc_id":"K181247","page_num":6,"bbox":[108.46,198.45,539.66,430.13],"n_rows":16,"n_cols":9,"columns":["Characteristic","","Subject","","","Predicate","","Reference","Comparison"],"rows":[["Characteristic","","Subject","","","Predicate","","Reference","Comparison"],["","","Device","","","Device","","Device",""],["","","Vitrea CT","","Vitrea CT\nBrain\nPerfusion\n(K121213)","","","",""],["","","Brain","","","","","",""],["","","","","","","","Olea Sphere",""],["","","Perfusion","","","","","",""],["","","","","","","","V3.0 (K152602)",""],["","","with Bayesian","","","","","",""],["","","","","","","","",""],["","","Algorithm","","","","","",""],["Classification Name","System, Image\nProcessing,\nRadiological","","","System, Image\nProcessing,\nRadiological","","","System, Image\nProcessing,\nRadiological","Same"],["Regulatory Number","892.2050","","","892.2050","","","892.2050","Same"],["Product Code","LLZ","","","LLZ","","","LLZ","Same"],["Classification","Class II","","","Class II","","","Class II","Same"],["Review Panel","Radiology","","","Radiology","","","Radiology","Same"],["Decision Date","Under Review","","","Nov. 02, 2012","","","Mar. 03, 2016","Predicate and\nreference\ndevices are\ncleared."]],"caption_candidate":"Regulatory Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p6-t1","doc_id":"K181247","page_num":6,"bbox":[108.46,456.03,539.66,718.66],"n_rows":3,"n_cols":4,"columns":["Criteria","Subject Device","Predicate Device","Comparison"],"rows":[["Criteria","Subject Device","Predicate Device","Comparison"],["","Vitrea CT Brain Perfusion\nwith Bayesian Algorithm","Vitrea CT Brain Perfusion\n(K121213)",""],["Indications\nfor Use","Vitrea CT Brain Perfusion is a\nnon-invasive post-processing\napplication designed to\nevaluate areas of brain\nperfusion. The software can\ncalculate cerebral blood flow\n(CBF), cerebral blood volume\n(CBV), local bolus timing (i.e.,\ndelay of tissue response, time\nto peak), and mean transit time\n(MTT) from dynamic CT image\ndata acquired after the injection\nof contrast media. The package\nalso allows the calculation of\nregions of interest and mirrored\nregions, as well as the visual\ninspection of time density\ncurves. Vitrea CT Brain","Vitrea CT Brain Perfusion is a\nnon-invasive post-processing\napplication designed to\nevaluate areas of brain\nperfusion. The software can\ncalculate cerebral blood flow\n(CBF), cerebral blood volume\n(CBV), local bolus timing (i.e.,\ndelay of tissue response, time\nto peak), and mean transit time\n(MTT) from dynamic CT image\ndata acquired after the injection\nof contrast media. The package\nalso allows the calculation of\nregions of interest and mirrored\nregions, as well as the visual\ninspection of time density\ncurves. Vitrea CT Brain","Same"]],"caption_candidate":"Indications for Use Comparison with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p7-t0","doc_id":"K181247","page_num":7,"bbox":[108.2,99.7,539.92,404.93],"n_rows":6,"n_cols":4,"columns":["Criteria","Subject Device","Predicate Device","Comparison"],"rows":[["Criteria","Subject Device","Predicate Device","Comparison"],["","Vitrea CT Brain Perfusion\nwith Bayesian Algorithm","Vitrea CT Brain Perfusion\n(K121213)",""],["","Perfusion supports the\nphysician in visualizing the\napparent blood perfusion in\nbrain tissue affected by acute\nstroke. Areas of decreased\nperfusion, as is observed in\nacute cerebral infarcts, appear\nas areas of changed signal\nintensity (lower for both CBF\nand CBV and higher for time to\npeak and MTT).","Perfusion supports the\nphysician in visualizing the\napparent blood perfusion in\nbrain tissue affected by acute\nstroke. Areas of decreased\nperfusion, as is observed in\nacute cerebral infarcts, appear\nas areas of changed signal\nintensity (lower for both CBF\nand CBV and higher for time to\npeak and MTT).",""],["Intended\nUsers","Qualified healthcare\nprofessionals including, but not\nrestricted to, radiologists, non-\nradiology specialists,\nphysicians and technologists.","Qualified healthcare\nprofessionals including, but not\nrestricted to, radiologists, non-\nradiology specialists,\nphysicians and technologists.","Same"],["Patient\nPopulation","Patients with suspected\ncompromised or abnormal\ncerebral blood flow.","Patients with suspected\ncompromised or abnormal\ncerebral blood flow.","Same"],["Modality\nSupport","CT","CT","Same"]],"caption_candidate":"Traditional 510(k) Pre-market Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p7-t1","doc_id":"K181247","page_num":7,"bbox":[108.2,430.85,539.92,693.7],"n_rows":11,"n_cols":4,"columns":["","Subject Device","Predicate",""],"rows":[["","Subject Device","Predicate",""],["","","",""],["","","Device",""],["","","",""],["","Vitrea CT Brain","Vitrea CT Brain",""],["Software Functionality","","","Comparison"],["","Perfusion with","Perfusion",""],["","Bayesian","(K121213)",""],["","Algorithm","",""],["Quantitative brain perfusion maps\nfor:\n• Regional cerebral blood\nvolume (rCBV)\n• Regional cerebral blood\nflow (rCBV)\n• Mean transit time (MTT)\n• Time to peak of tissue\n(TTP)\n• Delay of tissue response\n(Delay)","Yes","Yes","Same"],["Display:\n• Region of interest (ROI)\n• Mirrored regions\n• Time density curves","Yes","Yes","Same"]],"caption_candidate":"Similarities in Technology with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p8-t0","doc_id":"K181247","page_num":8,"bbox":[108.05,99.74,540.07,633.1],"n_rows":22,"n_cols":4,"columns":["","Subject Device","Predicate",""],"rows":[["","Subject Device","Predicate",""],["","","",""],["","","Device",""],["","","",""],["","Vitrea CT Brain","Vitrea CT Brain",""],["Software Functionality","","","Comparison"],["","Perfusion with","Perfusion",""],["","Bayesian","(K121213)",""],["","Algorithm","",""],["Display of Perfusion Maps in:\n• MPR orientations\n• 2D\n• 3D","Yes","Yes","Same"],["4D-DSA (digital subtraction\nangiography) view for visualizing\nflow of contrast through the vessels","Yes","Yes","Same"],["Perfusion maps in MPR orientations\nand 2D","Yes","Yes","Same"],["Automatic motion correction and\ncurve fitting","Yes","Yes","Same"],["Region of interest (ROI) templates","Yes","Yes","Same"],["Midline identification and display","Yes","Yes","Same"],["Manual and automatic detection of\nartery and vein locations","Yes","Yes","Same"],["Automatic calculation of\nquantitative brain perfusion\nresults","Yes","Yes","Same"],["Window leveling, edit mid-plane\nline, display mirrored ROIs,\nsnapshots, time-series batch,\nmovies for physician reporting","Yes","Yes","Same"],["Report generation for the Brain\nPerfusion patient study","Yes","Yes","Same"],["Perfusion measurement averages\nfor multiple ROIs with ability to\nmirror an ROI from one hemisphere\nto the other","Yes","Yes","Same"],["Window leveling, edit mid-plane\nline, display mirrored ROIs,\nsnapshots, time-series batch,\nmovies for physician reporting","Yes","Yes","Same"],["Color coded Summary maps","Yes","Yes","Same"]],"caption_candidate":"Traditional 510(k) Pre-market Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p9-t0","doc_id":"K181247","page_num":9,"bbox":[108.11,113.53,540.01,402.89],"n_rows":10,"n_cols":4,"columns":["","Subject Device","Predicate",""],"rows":[["","Subject Device","Predicate",""],["","","",""],["","","Device",""],["","","",""],["","Vitrea CT Brain","Vitrea CT",""],["Software","","","Comparison"],["Functionality","Perfusion with","Brain",""],["","Bayesian","Perfusion",""],["","Algorithm","(K121213)",""],["Bayesian Perfusion\nAlgorithm","Yes","No","Subject device provides user\nwith choice to use either the\nBayesian algorithm or SVD+\nalgorithm.\nPredicate device can use the\nSVD+ algorithm.\nNote: The added Bayesian\nalgorithm in the subject device is\nsimilar to the Bayesian algorithm\nin the reference device, Olea\nSphere 3.0, which was cleared\nby the FDA under K152602.\nTherefore, this added algorithm\ndoes not raise different\nquestions of safety and\neffectiveness."]],"caption_candidate":"Differences in Technology with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p9-t1","doc_id":"K181247","page_num":9,"bbox":[108.11,431.15,540.01,711.34],"n_rows":12,"n_cols":4,"columns":["","Subject Device","Reference",""],"rows":[["","Subject Device","Reference",""],["","","",""],["","","Device",""],["","","",""],["","Vitrea CT Brain","Olea Sphere",""],["Software Functionality","","","Comparison"],["","Perfusion with","V3.0 (K152602)",""],["","Bayesian","",""],["","Algorithm","",""],["Bayesian Algorithm:\nThe Bayesian estimation of the\nhemodynamical parameters\nintegrates a model-based\napproach especially robust to\nimage noise and fast analytical\nintegration techniques to compute\nthe posterior probabilities of the\nestimated blood flow, delay, MTT\nand time concentration curves\n(residue functions).","Yes","Yes","Same"],["Motion correction","Yes","Yes","Same"],["Automatic Arterial Input function\nand Vein Output function","Yes","Yes","Same"]],"caption_candidate":"Similarities in Technology with the Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p10-t0","doc_id":"K181247","page_num":10,"bbox":[108.08,99.74,540.04,357.29],"n_rows":14,"n_cols":4,"columns":["","Subject Device","Reference",""],"rows":[["","Subject Device","Reference",""],["","","",""],["","","Device",""],["","","",""],["","Vitrea CT Brain","Olea Sphere",""],["Software Functionality","","","Comparison"],["","Perfusion with","V3.0 (K152602)",""],["","Bayesian","",""],["","Algorithm","",""],["Automatic vessel removal","Yes","Yes","Same"],["Automatic Brain Midline detection","Yes","Yes","Same"],["Noise reduction is applied before\nthe Bayesian computation.","Yes","Yes","Same"],["Model based Bayesian estimation\nof perfusion parameters.","Yes","Yes","Same"],["Delay insensitive method.","Yes","Yes","Same"]],"caption_candidate":"Traditional 510(k) Pre-market Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181247-p12-t0","doc_id":"K181247","page_num":12,"bbox":[108.29,396.44,539.83,590.23],"n_rows":5,"n_cols":7,"columns":["Standard No.","","Standards","","Standard Title","Version","Date"],"rows":[["Standard No.","","Standards","","Standard Title","Version","Date"],["","","Organization","","","",""],["PS 3.1- 3.20 (2016)\n(Recognition\nNumber 12-300)","NEMA","","","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set (Radiology)","3","06/27/2016"],["ISO 14971:2007\n/(R)2010\n(Recognition\nNumber 5-70)","AAMI / ANSI\n/ ISO","","","Medical Devices -\nApplications of Risk\nManagement to Medical\nDevices","2007","06/27/2016"],["IEC 62304:2006\n(Recognition\nNumber 13-32)","AAMI / ANSI\n/ IEC","","","Medical Device Software -\nSoftware Life Cycle\nProcesses (Software /\nInformatics)","2006","08/20/2012"]],"caption_candidate":"consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181574-p4-t0","doc_id":"K181574","page_num":4,"bbox":[40.47,215.3,513.51,585.98],"n_rows":28,"n_cols":9,"columns":["Clinical Application","","Mode of Operation","","","","","",""],"rows":[["Clinical Application","","Mode of Operation","","","","","",""],["General\n(Track 1 Only)","Specific\n(Tracks 1 & 3)","B","M","PWD","CWD","Color\nDoppler","Combined\n(Specify)","Other*\n(Specify)"],["Ophthalmic","Ophthalmic","","","","","","",""],["Fetal Imaging\n& Other","Fetal","","","","","","",""],["","Abdominal","P","","","","","",""],["","Intra-operative (Specify)","","","","","","",""],["","Intra-operative (Neuro)","","","","","","",""],["","Laparoscopic","","","","","","",""],["","Pediatric","P","","","","","",""],["","Small Organ (Specify)","P","","","","","","1"],["","Neonatal Cephalic","","","","","","",""],["","Adult Cephalic","","","","","","",""],["","Trans-rectal","","","","","","",""],["","Trans-vaginal","","","","","","",""],["","Trans-urethral","","","","","","",""],["","Trans-esoph. (non-Card.)","","","","","","",""],["","Musculo-skeletal\n(Conventional)","P","","","","","",""],["","Musculo-skeletal\n(Superficial)","","","","","","",""],["","Intravascular","","","","","","",""],["","Other (Specify)","","","","","","",""],["Cardiac","Cardiac Adult","","","","","","",""],["","Cardiac Pediatric","","","","","","",""],["","Intravascular (Cardiac)","","","","","","",""],["","Trans-esoph. (Cardiac)","","","","","","",""],["","Intra-cardiac","","","","","","",""],["","Other (Specify)","","","","","","",""],["Peripheral\nVessel","Peripheral vessel","N","","","","","","2"],["","Other (Specify)","","","","","","",""]],"caption_candidate":"Intended Use: Diagnostic ultrasound imaging of the human body as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K181574-p5-t0","doc_id":"K181574","page_num":5,"bbox":[40.47,228.02,513.51,598.46],"n_rows":28,"n_cols":9,"columns":["Clinical Application","","Mode of Operation","","","","","",""],"rows":[["Clinical Application","","Mode of Operation","","","","","",""],["General\n(Track 1 Only)","Specific\n(Tracks 1 & 3)","B","M","PWD","CWD","Color\nDoppler","Combined\n(Specify)","Other*\n(Specify)"],["Ophthalmic","Ophthalmic","","","","","","",""],["Fetal Imaging\n& Other","Fetal","","","","","","",""],["","Abdominal","P","","","","","",""],["","Intra-operative (Specify)","","","","","","",""],["","Intra-operative (Neuro)","","","","","","",""],["","Laparoscopic","","","","","","",""],["","Pediatric","P","","","","","",""],["","Small Organ (Specify)","P","","","","","","1"],["","Neonatal Cephalic","","","","","","",""],["","Adult Cephalic","","","","","","",""],["","Trans-rectal","","","","","","",""],["","Trans-vaginal","","","","","","",""],["","Trans-urethral","","","","","","",""],["","Trans-esoph. (non-Card.)","","","","","","",""],["","Musculo-skeletal\n(Conventional)","P","","","","","",""],["","Musculo-skeletal\n(Superficial)","","","","","","",""],["","Intravascular","","","","","","",""],["","Other (Specify)","","","","","","",""],["Cardiac","Cardiac Adult","","","","","","",""],["","Cardiac Pediatric","","","","","","",""],["","Intravascular (Cardiac)","","","","","","",""],["","Trans-esoph. (Cardiac)","","","","","","",""],["","Intra-cardiac","","","","","","",""],["","Other (Specify)","","","","","","",""],["Peripheral\nVessel","Peripheral vessel","","","","","","",""],["","Other (Specify)","","","","","","",""]],"caption_candidate":"Intended Use: Diagnostic ultrasound imaging of the human body as follows:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K181574-p8-t0","doc_id":"K181574","page_num":8,"bbox":[67.01,250.53,548.41,702.74],"n_rows":10,"n_cols":6,"columns":["Feature","Uscan Ultrasound System\n(This submission)","Uscan Ultrasound System\n(K160420)","","SonoSite SII Ultrasound",""],"rows":[["Feature","Uscan Ultrasound System\n(This submission)","Uscan Ultrasound System\n(K160420)","","SonoSite SII Ultrasound",""],["","","","","System",""],["","","","","(K162045)",""],["Intended Use","Diagnostic ultrasound imaging\nof the human body","Diagnostic ultrasound imaging\nof the human body","Diagnostic ultrasound imaging\nor fluid flow analysis of the\nhuman body","",""],["Indications for\nUse","Abdominal\nPediatric\nSmall Organ (prostate)\nMusculo-skeletal\n(Conventional)\nPeripheral Vessel\nNeedle guidance","Abdominal\nPediatric\nSmall Organ (prostate)\nMusculo-skeletal\n(Conventional)","Opthalmic\nFetal – OB/GYN\nAbdominal\nPediatric\nSmall Organ (breast, thyroid,\ntesticle, prostate)\nNeonatal Cephalic\nAdult Cephalic\nTrans-Rectal\nTrans-Vaginal\nMusculo-skeletal\n(Conventional)\nMusculo-skeletal (Superficial)\nCardiac Adult\nCardiac Pediatric\nPeripheral Vessel\nNeedle guidance","",""],["Transducer\nTypes","Linear Array\nAnnular Array","Annular Array","Linear Array\nCurved Linear Array\nIntracavitary\nPhased Array","",""],["Transducer\nFrequency","3.0 – 14.0 MHz","3.0 – 7.0 MHz","1.0 – 15.0 MHz","",""],["Modes of\nOperation","2D / B-mode","2D / B-mode","2D / B-mode\nTissue Harmonic Imaging\nM-mode\nColor M-mode\nColor Power Doppler\nCombination Modes\nVelocity Color Doppler","",""],["PW Doppler","Not available","Not available","Not available","",""],["CW Doppler","Not available","Not available","Not available","",""]],"caption_candidate":"fundamental scientific technology. A comparison table is provided below.","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K181685-p5-t0","doc_id":"K181685","page_num":5,"bbox":[109.13,118.98,597.09,509.35],"n_rows":25,"n_cols":12,"columns":["(cid:38)(cid:79)(cid:76)(cid:81)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)(cid:36)(cid:83)(cid:83)(cid:79)(cid:76)(cid:70)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)\nAnatomy/Region of Interest","(cid:48)(cid:82)(cid:71)(cid:72)(cid:3)(cid:82)(cid:73)(cid:3)(cid:50)(cid:83)(cid:72)(cid:85)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)","","","","","","","","","",""],"rows":[["(cid:38)(cid:79)(cid:76)(cid:81)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)(cid:36)(cid:83)(cid:83)(cid:79)(cid:76)(cid:70)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)\nAnatomy/Region of Interest","(cid:48)(cid:82)(cid:71)(cid:72)(cid:3)(cid:82)(cid:73)(cid:3)(cid:50)(cid:83)(cid:72)(cid:85)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)","","","","","","","","","",""],["","B","M","PW\nDoppler","CW\nDoppler","Color\nDoppler","Color 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Vascular","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:27)(cid:64)(cid:3)"],["Musculo-skeletal Conventional","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:27)(cid:64)(cid:3)"],["Musculo-skeletal Superficial(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:27)(cid:64)(cid:3)"],["Other","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:23)(cid:15)(cid:25)(cid:15)(cid:27)(cid:15)(cid:28)(cid:64)(cid:3)"],["Exam Type, Means of Access","","","","","","","","","","",""],["Transesophageal","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:25)(cid:15)(cid:28)(cid:64)(cid:3)"],["Transrectal","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:62)(cid:27)(cid:64)(cid:3)"],["Transvaginal","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:62)(cid:27)(cid:64)(cid:3)"],["Transuretheral","","","","","","","","","","",""],["Intraoperative","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:51)(cid:3)","(cid:62)(cid:24)(cid:15)(cid:27)(cid:64)(cid:3)"],["Intraoperative 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{"table_id":"K182034-p4-t0","doc_id":"K182034","page_num":4,"bbox":[67.5,158.55,534.38,270.3],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Arterys Inc."],"rows":[["510(k) Sponsor","Arterys Inc."],["Address","51 Federal St. Suite 305\nSan Francisco, CA 94107"],["Correspondence Person","Sharon Cholowsky"],["Contact Information","Email: regulatory@arterys.com\nPhone: 403-923-9688"],["Date Prepared","July 26, 2018"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182034-p4-t1","doc_id":"K182034","page_num":4,"bbox":[67.5,304.05,534.38,415.8],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","Arterys® ​ MICA\n​"],"rows":[["Proprietary Name","Arterys® ​ MICA\n​"],["Common Name","MICA"],["Model Number","AMM5"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182034-p4-t2","doc_id":"K182034","page_num":4,"bbox":[67.5,449.55,534.38,498.3],"n_rows":3,"n_cols":2,"columns":["Primary Predicate Device","Arterys Viewer, K171544\n​"],"rows":[["Primary Predicate Device","Arterys Viewer, K171544\n​"],["Secondary Predicate Device","Arterys Cardio DL, K163253\n​"],["Tertiary Predicate Device","Arterys Oncology DL, K173542\n​"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182034-p6-t0","doc_id":"K182034","page_num":6,"bbox":[72.33,364.0,545.57,696.31],"n_rows":8,"n_cols":5,"columns":["Feature/\nFunction","Proposed Device\nArterys MICA","Primary\nPredicate\nArterys Viewer\n(K171544)","Secondary\nPredicate\nArterys Cardio\nDL (K163253)\n​​","Tertiary Predicate\nArterys Oncology\nDL (K173542)\n​​"],"rows":[["Feature/\nFunction","Proposed Device\nArterys MICA","Primary\nPredicate\nArterys Viewer\n(K171544)","Secondary\nPredicate\nArterys Cardio\nDL (K163253)\n​​","Tertiary Predicate\nArterys Oncology\nDL (K173542)\n​​"],["Ability to load\ndifferent\noptional modules\nfrom same\nworklist","Yes - all three modules\nare in drop down menu","No - Cardio\nmodule included\nin Viewer","No - Module\nincluded in\nViewer","No - Module loaded\nseparately"],["Operating\nSystem","Client server architecture\nusing Linux server and\nweb browser client","Same","Same","Same"],["Image storage/\ncompression","Support JPEG2000 and\ncompression","Same","Same","Same"],["DICOM\ncompliant","Yes","Same","Same","Same"],["Type of scans/\nModality","Viewer: MR, CT\nCardio: MR\nOnco: MR and CT","Same","Same","Same"],["Worklist with\nfilter and\nsearching","Yes. Added tags for\nfurther identification.","Yes.","N/A","N/A"],["Image upload","Yes","Same","N/A","N/A"]],"caption_candidate":"Table 5.1: Technological characteristics of the proposed device and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182034-p7-t0","doc_id":"K182034","page_num":7,"bbox":[72.36,72.34,545.56,703.39],"n_rows":12,"n_cols":5,"columns":["2D, 3D, MIP,\nMPR image\ndisplay","Yes","Same","Same","Same"],"rows":[["2D, 3D, MIP,\nMPR image\ndisplay","Yes","Same","Same","Same"],["Cine play","Yes","Same","Same","Same"],["Image navigation\ntools","Pan, zoom, rotate,\nmaximize/minimize, slice\nscroll (view multiple\nslices), adjust\nwindow/level, slab\nthickness, time scroll\n(view multiple phases)","Same","Same","Same"],["Image navigation\n- Cardio","Yes. Flow direction and\n2D speed color map","N/A","Same","N/A"],["Image layouts;\nside-by-side\nviewing","Yes. Added multi-study\nand that images are now\ncommonly aligned.","Yes.","Yes.","Yes."],["View DICOM\ndata","Patient, study,\norientation, and pixel\ninformation","Same","Same","Same"],["Measuring tools","Yes - linear, area, and\nvolume for all three\nmodules.","Yes - linear and\narea only.","Yes - linear and\narea only.","Yes - linear, area,\nand volume."],["Semi-automated\nsegmentation of\nregion of interest","Yes. Cardio and\nOncology only.","No","Yes","Yes"],["Cardio -\nidentification of\nlandmarks","Yes - Automatically\nidentified + user editable","N/A","Yes - Manually\nidentified +\neditable","N/A"],["Cardio\nVisualization,\nQuantification,\nVolume in 4D\nFlow","Yes. Added normalized\nvolume measurements\nbased on age and gender.\nAdded ability to edit the\nvalve plane to adjust\nvolume.","N/A","Yes","N/A"],["Cardio - 2D\nContour\ninference","Yes - Automatically\nidentified + user editable.\nAdded ability to edit the\nvalve plane to adjust\nvolume.","N/A","Yes - Manually\nidentified +\neditable","N/A"],["Cardio\nVisualization,\nQuantification,\nVolume in 3D\nWorkflow for a\nshort axis stack","Yes. Added normalized\nvolume measurements\nbased on age and gender.\nAdded ability to edit the\nvalve plane to adjust\nvolume.","N/A","Same","N/A"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182034-p8-t0","doc_id":"K182034","page_num":8,"bbox":[72.35,72.29,545.56,323.39],"n_rows":7,"n_cols":5,"columns":["Eddy current\ncorrection","Yes. Added ability to\ndownload data.","N/A","Same","N/A"],"rows":[["Eddy current\ncorrection","Yes. Added ability to\ndownload data.","N/A","Same","N/A"],["Cardio\nReporting","Yes. Added minimal\ncontent configurability.","N/A","Yes","N/A"],["Co-registration","Yes","N/A","N/A","Same"],["Onco\nLongitudinal\ntracking - linked\nVOIs between\ntimepoints","Yes","N/A","N/A","Same"],["Onco Reporting\n- LI-RADS and\nLung-RADS","Yes","N/A","N/A","Same"],["Secondary\nCapture","Yes","Same","Same","Same"],["Download report","Yes - to PACS and\ncomputer","Yes - to PACS\nonly","N/A","N/A"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K182177-p6-t0","doc_id":"K182177","page_num":6,"bbox":[66.63,93.29,545.49,384.17],"n_rows":16,"n_cols":7,"columns":["","","Subject Device:","","","Predicate Device:",""],"rows":[["","","Subject Device:","","","Predicate Device:",""],["","","MaxQ AI AccipioIx","","","Viz.AI ContaCT",""],["Notification-only, parallel workflow\ntool","Yes","","","Yes","",""],["Intended user","Hospital networks and trained\nclinicians","","","Hospital networks and trained\nclinicians","",""],["Setting","Acute care","","","Acute care","",""],["Identify patients with a pre-\nspecified clinical condition","Yes","","","Yes","",""],["Clinical condition","Cerebrovascular Event:\nIntracranial hemorrhage","","","Cerebrovascular Event: Large\nvessel occlusion","",""],["Alert to finding","Yes; flagged for review","","","Yes; flagged for review","",""],["Independent of standard of care\nworkflow","Yes; No cases are removed\nfrom worklist","","","Yes; No cases are removed from\nworklist","",""],["Modality","Non-Contrast CT","","","CT Angiogram","",""],["Artificial Intelligence algorithm","Yes","","","Yes","",""],["Limited to analysis of imaging data","Yes","","","Yes","",""],["Non-Diagnostic Preview","No","","","Yes","",""],["Aids prompt identification of\ncases with indicated findings","Yes","","","Yes","",""],["Output","Suspected hemorrhage / No\nsuspected hemorrhage","","","Suspected large vessel\nocclusion","",""],["Where results are received","PACS / Workstation","","","PACS / Mobile application","",""]],"caption_candidate":"A summary table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182218-p4-t0","doc_id":"K182218","page_num":4,"bbox":[104.88,123.83,393.94,771.96],"n_rows":58,"n_cols":2,"columns":["510(K) SUMMARY",""],"rows":[["510(K) SUMMARY",""],["",""],["This Summary has been prepared in acc","ordance with 21 CFR 807.9"],["",""],["GENERAL INFORMATIO","N"],["",""],["Date Prepared","28-Nov-2018"],["",""],["Submitted by","Resonance Health Analysis Se"],["",""],["","141 Burswood Rd"],["",""],["","Burswood 6100"],["",""],["","AUSTRALIA"],["",""],["Main Contact","Mrs Celine Royet"],["",""],["","Regulatory Affairs Manager"],["",""],["","celiner@resonancehealth.com"],["",""],["","Tel: +61 8 9286 5300"],["",""],["","Fax: +61 8 9286 5399"],["",""],["US Contact (US Agent)","Rene Van De Zande"],["",""],["","Director & GM"],["",""],["","Emergo Global Representatio"],["",""],["","2500 Bee Cave Road Buildin"],["",""],["","Austin, TX 78746"],["",""],["","Phone: 512 3279997"],["",""],["","Fax: 512 3279998"],["",""],["","Email: USAgent@ul.com"],["",""],["DEVICE INFORMATION",""],["",""],["Name of Device","FerriSmart"],["",""],["Trade/proprietary Name","FerriSmart"],["",""],["Classification","Class II"],["",""],["Product Code","90-PCS"],["",""],["CFR Section","892.1001 Liver Iron Conc"],["","Diagnostic For Deferasirox"],["",""],["Panel","Radiology"],["",""],["Resonance Health Analysis Services Pty Ltd",""]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"text"}
{"table_id":"K182218-p4-t1","doc_id":"K182218","page_num":4,"bbox":[99.69,559.88,521.04,711.16],"n_rows":6,"n_cols":4,"columns":["","Name of Device","","FerriSmart"],"rows":[["","Name of Device","","FerriSmart"],["","Trade/proprietary Name","","FerriSmart"],["","Classification","","Class II"],["","Product Code","","90-PCS"],["CFR Section","CFR Section","","892.1001 Liver Iron Concentration Imaging Companion\nDiagnostic For Deferasirox"],["","Panel","","Radiology"]],"caption_candidate":"DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182218-p6-t0","doc_id":"K182218","page_num":6,"bbox":[99.63,230.79,520.89,736.8],"n_rows":9,"n_cols":10,"columns":["","","Proposed Device","","","Predicate Device","","","Reference Device",""],"rows":[["","","Proposed Device","","","Predicate Device","","","Reference Device",""],["","FerriSmart","FerriSmart","","","FerriScan R2-MRI","","","FerriScan R2-MRI",""],["","","","","","Analysis System","","","Analysis System",""],["Regulatory Class","II","","","II","","","II","",""],["510(k) number","K182218","","","DEN130012 / K124065","","","K043271","",""],["Classification\nName","Liver Iron Concentration\nImaging Companion\nDiagnostic For\nDeferasirox","","","Liver Iron Concentration\nImaging Companion\nDiagnostic For\nDeferasirox","","","System, Nuclear\nMagnetic Resonance\nImaging, System, Image\nProcessing Radiological","",""],["CFR Section","892.1001","","","892.1001","","","892.1000","",""],["Product Code and\nClassification\nPanel","90 PCS","","","90 PCS","","","90 LNH","",""],["Description","Standalone software\npackage that\nautomatically analyses\nmulti-slice, spin-echo\nMRI data sets\nencompassing the\nabdomen to provide\nobjective and\nreproducible\ndetermination of liver\nparameters to support\nclinicians in the\nassessment of liver iron\nstatus.\nThe software tool\ndetermines the signal\ndecay rate (R ) that is\n2\nused to characterize iron\nloading in the liver,\nwhich is then transformed\nby a defined calibration\ncurve to provide a","","","Software tool to facilitate\nthe import and\nvisualization of\nmulti-slice, spin-echo\nMRI data sets\nencompassing the\nabdomen, with\nfunctionality independent\nof the MRI equipment\nvendor, to provide\nobjective and\nreproducible\ndetermination of liver\nparameters to support\nclinicians in the\nassessment of liver iron\nstatus.\nThe software tool also\ncalculates the signal\ndecay rate (R ) that is\n2\nused to characterize iron\nloading in the liver,\nwhich is then transformed","","","Software tool to facilitate\nthe import and\nvisualization of\nmulti-slice, spin-echo\nMRI data sets\nencompassing the\nabdomen, with\nfunctionality independent\nof the MRI equipment\nvendor, to provide\nobjective and\nreproducible\ndetermination of liver\nparameters to support\nclinicians in the\nassessment of liver iron\nstatus.\nThe software tool also\ncalculates the signal\ndecay rate (R ) that is\n2\nused to characterize iron\nloading in the liver,\nwhich is then transformed\nby a defined calibration","",""]],"caption_candidate":"predicate and the reference device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182218-p7-t0","doc_id":"K182218","page_num":7,"bbox":[99.64,105.12,520.89,732.84],"n_rows":8,"n_cols":10,"columns":["","","Proposed Device","","","Predicate Device","","","Reference Device",""],"rows":[["","","Proposed Device","","","Predicate Device","","","Reference Device",""],["","FerriSmart","FerriSmart","","","FerriScan R2-MRI","","","FerriScan R2-MRI",""],["","","","","","Analysis System","","","Analysis System",""],["","quantitative measure of\nliver iron concentrations\nin vivo.","","","by a defined calibration\ncurve to provide a\nquantitative measure of\nliver iron concentrations\nin vivo.","","","curve to provide a\nquantitative measure of\nliver iron concentrations\nin vivo.","",""],["Technology","Convolutional neural\nnetworks for the image\nanalysis.\nAlgorithmic for the\nimages quality checks\nand R conversion into\n2\nLIC.","","","Algorithmic, with human\ninteraction for Region of\nInterest (ROI) selection.","","","Algorithmic, with human\ninteraction for Region of\nInterest (ROI) selection.","",""],["Intended\npurpose(s)","1. Supporting clinical\ndiagnoses about the status\nof liver iron\nconcentration.\n2. Supporting the\nsubsequent clinical\ndecision-making\nprocesses.\n3. Supporting the use in\nclinical research trials,\ndirected at studying\nchanges in liver iron\nconcentration as a result\nof interventions.","","","1. Supporting clinical\ndiagnoses about the status\nof liver iron\nconcentration.\n2. Supporting the\nsubsequent clinical\ndecision-making\nprocesses.\n3. Supporting the use in\nclinical research trials,\ndirected at studying\nchanges in liver iron\nconcentration as a result\nof interventions.\n4. It contains an image\nviewer for importing\nDICOM images,\nbrowsing through patient\ndatasets, viewing images\nand performing region of\ninterest analysis.","","","1. Supporting clinical\ndiagnoses about the status\nof liver iron\nconcentration.\n2. Supporting the\nsubsequent clinical\ndecision-making\nprocesses.\n3. Supporting the use in\nclinical research trials,\ndirected at studying\nchanges in liver iron\nconcentration as a result\nof interventions.\n4. It contains an image\nviewer for importing\nDICOM images,\nbrowsing through patient\ndatasets, viewing images\nand performing region of\ninterest analysis.","",""],["Intended Use","Measurement of R and\n2\niron concentration in the\nliver from MRI scans","","","For the analysis of multi-\nslice, spin-echo MRI data\nsets of the liver for the\nmeasurement of liver R\n2\nand liver iron\nconcentration and to\nassist in the provision of\niron chelation therapy","","","Measurement of R and\n2\niron concentration in the\nliver from MRI scans.","",""],["Indications","Indicated to:\n• measure liver iron\nconcentration in\nindividuals with","","","Measure liver iron\nconcentration to aid in\nthe identification and\nmonitoring of non-\ntransfusion-dependent","","","The R2-MRI Analysis\nSystem is an accessory\ndiagnostic device to MRI\nscanners and is intended\nfor diagnostic use to","",""]],"caption_candidate":"K182218 – FerriSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182218-p8-t0","doc_id":"K182218","page_num":8,"bbox":[99.63,105.12,520.9,559.92],"n_rows":10,"n_cols":10,"columns":["","","Proposed Device","","","Predicate Device","","","Reference Device",""],"rows":[["","","Proposed Device","","","Predicate Device","","","Reference Device",""],["","FerriSmart","FerriSmart","","","FerriScan R2-MRI","","","FerriScan R2-MRI",""],["","","","","","Analysis System","","","Analysis System",""],["","confirmed or\nsuspected systemic\niron overload;\n• monitor liver iron\nburden in transfusion\ndependent\nthalassemia patients\nand patients with\nsickle cell disease\nreceiving blood\ntransfusions;.\n• aid in the\nidentification and\nmonitoring of non-\ntransfusion-dependent\nthalassemia patients\nreceiving therapy\nwith deferasirox.","","","thalassemia patients\nreceiving therapy with\ndeferasirox.","","","present images that\nreflect the magnetic\nresonance spectra for the\ndetermination of iron on\nthe liver.","",""],["User","Radiologist","","","Resonance Health’s\ntrained analyst","","","Resonance Health’s\ntrained analyst","",""],["Hosting platform","Cloud-based or on-site\nhosting","","","Resonance Health’s\ninternal server","","","Resonance Health’s\ninternal server","",""],["Image-type\nutilized","Magnetic Resonance","","","Magnetic Resonance","","","Magnetic Resonance","",""],["Image format","DICOM","","","DICOM","","","DICOM","",""],["Data Acquisition\nmethod","Single Spin Echo (SSE)","","","Single Spin Echo (SSE)","","","Single Spin Echo (SSE)","",""],["Anatomical Sites","Liver","","","Liver","","","Liver","",""]],"caption_candidate":"K182218 – FerriSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182218-p10-t0","doc_id":"K182218","page_num":10,"bbox":[99.78,341.04,536.58,369.67],"n_rows":2,"n_cols":3,"columns":["","Sensitivities and specificities of FerriSmart for predicting FerriScan LIC values greater than several",""],"rows":[["","Sensitivities and specificities of FerriSmart for predicting FerriScan LIC values greater than several",""],["","clinically relevant thresholds.",""]],"caption_candidate":"The sensitivities and specificities results are presented in the Table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p4-t0","doc_id":"K182310","page_num":4,"bbox":[72.13,49.8,534.46,97.94],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","Mtk3252-007-1","Rev. Date:","3rd Aug 2018"],["","DMS Ref:","Eng/Ultron","","Page 1 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p5-t0","doc_id":"K182310","page_num":5,"bbox":[72.24,49.8,534.46,97.94],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","Mtk3252-007-1","Rev. Date:","3rd Aug 2018"],["","DMS Ref:","Eng/Ultron","","Page 2 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p6-t0","doc_id":"K182310","page_num":6,"bbox":[72.26,49.8,534.46,97.94],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","Mtk3252-007-1","Rev. Date:","3rd Aug 2018"],["","DMS Ref:","Eng/Ultron","","Page 3 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p6-t1","doc_id":"K182310","page_num":6,"bbox":[72.26,157.46,539.86,713.86],"n_rows":10,"n_cols":3,"columns":["","Predicate Device\nVolpara 1.5.2 (K153427)","Submission Device,\nVolpara 1.5.6"],"rows":[["","Predicate Device\nVolpara 1.5.2 (K153427)","Submission Device,\nVolpara 1.5.6"],["Intended Use","VolparaDensity is a software\napplication intended for use with\nthe raw data from digital breast x-\nray systems, including\ntomosynthesis. VolparaDensity\ncalculates and quantifies a density\nmap and from that determines\nvolumetric breast density as a ratio\nof fibroglandular tissue and total\nbreast volume estimates. Volpara\nprovides these numerical values\nalong with a BI-RADS breast\ndensity 4th or 5th Edition category\nto aid health care professionals in\nthe assessment of breast tissue\ncomposition. VolparaDensity is not\nan interpretive or diagnostic aid\nand should be used only as\nadjunctive information when the\nfinal assessment of breast density\ncategory is made by an MQSA-\nqualified interpreting physician.","Same as predicate."],["Intended Users","Health Care Professionals.","Health Care Professionals."],["Image Source","Digital mammography images.","Digital mammography images."],["Image Sources","Digital mammograms from\nmammography or tomosynthesis\nsystems.","Digital mammograms from\nmammography or tomosynthesis\nsystems, including those obtained\nusing with curved paddles."],["Anatomical Area","Breast","Breast"],["Assessment Scope","Volumetric","Volumetric"],["Operating Environment","Windows","Windows"],["Image Storage and Report Generation","Yes\nOutput to the console.","Yes\nOutput to the console."],["Numeric Output","Volume of Fibroglandular tissue\nVolume of Breast\nVolumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category\nAverage thickness of dense tissue\nMaximum thickness of dense\ntissue (and location).","Volume of Fibroglandular tissue\nVolume of Breast\nVolumetric Breast Density\nBIRADS 4th or 5th Edition Breast\nDensity Category, with highlighting\nabove a certain volumetric\nthreshold or if focal density present\nAverage thickness of dense tissue"]],"caption_candidate":"Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p7-t0","doc_id":"K182310","page_num":7,"bbox":[72.24,49.8,534.46,97.94],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","Mtk3252-007-1","Rev. Date:","3rd Aug 2018"],["","DMS Ref:","Eng/Ultron","","Page 4 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p7-t1","doc_id":"K182310","page_num":7,"bbox":[72.24,116.06,539.86,257.57],"n_rows":4,"n_cols":3,"columns":["","Maximum volume of dense tissue\nabove any 1cm2 square region\n(and location).","Maximum thickness of dense\ntissue (and location).\nMaximum volume of dense tissue\nabove any 1cm2 square region\n(and location).\nImage quality assessment metrics"],"rows":[["","Maximum volume of dense tissue\nabove any 1cm2 square region\n(and location).","Maximum thickness of dense\ntissue (and location).\nMaximum volume of dense tissue\nabove any 1cm2 square region\n(and location).\nImage quality assessment metrics"],["Image Output","Density map in DICOM SCI format,\nfor visualization as user specifies.","Density map in DICOM SCI format,\nfor visualization as user specifies"],["Classification","21 CFR 892.2050; LLZ","21 CFR 892.2050; LLZ"],["Software Level of Concern","Moderate","Moderate"]],"caption_candidate":"Title: Volpara Imaging Software 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182310-p8-t0","doc_id":"K182310","page_num":8,"bbox":[72.2,49.8,534.46,97.94],"n_rows":4,"n_cols":5,"columns":["","Type:","Report","",""],"rows":[["","Type:","Report","",""],["","DMS No:","Mtk3252-007-1","Rev. Date:","3rd Aug 2018"],["","DMS Ref:","Eng/Ultron","","Page 5 of 5"],["","Title:","Volpara Imaging Software 510(k) Summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182336-p4-t0","doc_id":"K182336","page_num":4,"bbox":[72.24,136.26,532.5,639.12],"n_rows":17,"n_cols":2,"columns":["Submitter’s Name:","Subtle Medical, Inc."],"rows":[["Submitter’s Name:","Subtle Medical, Inc."],["Address:","880 Santa Cruz Ave, Suite 200\nMenlo Park, CA 94025"],["Contact Person:","Terese Bogucki"],["Title:","Regulatory Consultant"],["Telephone Number:","650-488-7799"],["Fax Number:","650-227-2264"],["Email:","terri@decusbiomedical.com"],["Date Summary Prepared:","5-NOV-2018"],["Device Proprietary Name:","SubtlePET"],["Model Number:","V 1.0.0"],["Common Name:","SubtlePET"],["Regulation Number:","21 CFR 892.2050"],["Regulation Name:","Picture archiving and communications system"],["Primary Product Code:","LLZ"],["Secondary Product Code:","KPS"],["Device Class:","Class II"],["Predicate Device:","Trade name: Sapheneia Clarity\nManufacturer: Sapheneia Commercial Products AB\nAddress: Teknikringen 8\nSE-583 30 Linkoping, Sweden\nRegulation Number: 21 CFR 892.2050\nRegulation Name: Picture Archiving and\nCommunications System\nDevice Class: Class II\nProduct Code: LLZ\n510(k) Number: K063391\n510(k) Clearance Date: April 26, 2007"]],"caption_candidate":"Table 5-1. Subject Device Overview.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182336-p5-t0","doc_id":"K182336","page_num":5,"bbox":[102.6,478.74,532.5,710.94],"n_rows":6,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Physical\nCharacteristics","Software package that operates on\noff-the-shelf hardware","Software package that operates\non a virtual machine (VM)"],["Computer","PC Compatible","Virtual machine host-\ncompatible system"],["Image\nProcessing\nEnhancement\nLocation","Onsite on the desktop computer\nserver","Onsite on the facility VM\nand/or offsite on the cloud VM,\ndepending on the site’s\nconfiguration"],["DICOM\nStandard\nCompliance","The software processes DICOM\ncompliant image data","Same"],["Operating\nSystem","Windows","CentOS 7 Linux"]],"caption_candidate":"Table 5-2. Summary of Technological Characteristics Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182336-p6-t0","doc_id":"K182336","page_num":6,"bbox":[102.6,72.24,532.5,514.44],"n_rows":6,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Modalities","Multi-modality","Multi-modality; specifically\nprocesses PET, PET/CT and\nPET/MR images"],["User Interface","The software is designed for use\non a radiology workstation. It is\nunknown whether there is a user\ninterface.","None – enhanced images are\nviewed on existing PACS\nworkstations"],["Protocols","Custom low dose protocols","Standard scanner protocols"],["Image\nEnhancement\nAlgorithm\nDescription","Sapheneia ClarityTM employs a\nsophisticated statistical analysis\nof the image structure in the\nneighborhood of each pixel.\nUsing robust estimation methods\nthe dominant structures are\nseparated from the embedding\nnoise. Once the structure has been\ndetermined, it is possible to\nstrengthen the interesting parts\nwhile simultaneously reducing the\nnoise.","The software employs a\nconvolutional neural network-\nbased method in a pixel’s\nneighborhood to generate the\nvalue for each pixel.\nUsing a residual learning\napproach, the software predicts\nthe noise components and\nstructural components. The\nsoftware separates these\ncomponents, which enhances\nthe structure while\nsimultaneously reducing the\nnoise."],["Image\nAcquisition","The acquisition remains the same,\ni.e. the image processing can be\ngenerated from multiple\nmodalities and with predefined or\nspecific acquisition protocol\nsettings.","The acquisition remains the\nsame."]],"caption_candidate":"Subtle Medical, Inc. K182336","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182373-p5-t0","doc_id":"K182373","page_num":5,"bbox":[77.3,142.52,518.28,211.88],"n_rows":2,"n_cols":4,"columns":["Device Name","Manufacturer","FDA DEN\nReference #","Decision Date"],"rows":[["Device Name","Manufacturer","FDA DEN\nReference #","Decision Date"],["OsteoDetect","Imagen","DEN180005","May 24, 2018"]],"caption_candidate":"legally marketed predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182373-p13-t0","doc_id":"K182373","page_num":13,"bbox":[42.84,79.7,727.06,483.22],"n_rows":4,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\niCAD Inc.\n®\nPowerLook Tomo Detection V2\nSoftware","Predicate Device\nImagen Inc.\nOsteoDetect\nDEN180005","Discussion of Differences and\nComments"],"rows":[["Features and\nCharacteristics","Subject Device\niCAD Inc.\n®\nPowerLook Tomo Detection V2\nSoftware","Predicate Device\nImagen Inc.\nOsteoDetect\nDEN180005","Discussion of Differences and\nComments"],["Regulation\nNumber/Name","21 CFR 892.2090 / Radiological Computer Assisted\nDetection and Diagnosis Software.","Same","NA"],["Regulation\nDescription","A radiological computer assisted detection and diagnostic\nsoftware is an image processing device intended to aid in\nthe detection, localization, and characterization of fracture,\nlesions, or other disease specific findings on acquired\nmedical images (e.g. radiography, MR, CT). The device\ndetects, identifies and characterizes findings based on\nfeatures or information extracted from images, and\nprovides information about the presence, location, and\ncharacteristics of the findings to the user. The analysis is\nintended to inform the primary diagnostic and patient\nmanagement decisions that are made by the clinical user.\nThe device is not intended as a replacement for a complete\nclinician's review or their clinical judgment that takes into\naccount other relevant information from the image or\npatient history.","Same","NA"],["Intended Use","®\nPowerLook Tomo Detection V2 software is a computer-\nassisted detection and diagnosis (CAD) software device\nintended to be used concurrently by interpreting physicians\nwhile reading digital breast tomosynthesis (DBT) exams\nfrom compatible DBT systems. The system detects soft\ntissue densities (masses, architectural distortions and\nasymmetries) and calcifications in the 3D DBT slices. The\ndetections and Certainty of Finding and Case Scores assist\ninterpreting physicians in identifying soft tissue densities\nand calcifications that may be confirmed or dismissed by\nthe interpreting physician.","OsteoDetect analyzes wrist radiographs\nusing machine learning techniques to identify\nand highlight distal radius fractures during\nthe review of posterior-anterior (PA) and\nlateral (LAT) radiographs of adult wrists.","Both devices have the same\nintended use per 21 CFR\n892.2090."]],"caption_candidate":"Summary of Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182373-p14-t0","doc_id":"K182373","page_num":14,"bbox":[42.84,52.08,727.06,413.26],"n_rows":9,"n_cols":4,"columns":["Type of CAD\nSoftware","Radiological computer assisted detection and\ndiagnostic software","Same","NA"],"rows":[["Type of CAD\nSoftware","Radiological computer assisted detection and\ndiagnostic software","Same","NA"],["Mode of Action","Image processing device intended to aid in the\ndetection, localization, and characterization of soft\ntissue densities (masses, architectural distortions\nand asymmetries) and calcifications in the 3D\nDBT slices.","Image processing device intended to aid in\nidentifying and highlighting distal radius\nfractures during the review of posterior-\nanterior (PA) and lateral (LAT) radiographs\nof adult wrists.","Both devices are intended to aid in the\ndetection, localization, and characterization\nof disease specific findings on acquired\nmedical images per 21 CFR 892.2090.\nPLTD detects a different disease specific\nfinding. However, special controls are in\nplace to mitigate any risk for this difference."],["Clinical Output","To inform the primary diagnostic and patient\nmanagement decisions that are made by the\nclinical user.","Same","The outputs of both devices serve as a\nconcurrent read. The output is used to\ninform the clinical user (who themselves\nmake the primary diagnostic and patient\nmanagement decisions) and will not replace\nthe clinical expertise and judgment of the\nclinical user."],["Patient\nPopulation","Symptomatic and asymptomatic women\nundergoing mammography.","Adult men and women undergoing\nradiographs of adult wrists.","PLTD is intended for a different patient\npopulation however special controls are\nin place to mitigate any risk for this\ndifference."],["End Users","Interpreting Physicians Radiologists","Clinicians","Same"],["Image Source\nModalities","Digital breast tomosynthesis slices","2D X-ray images","The Image Source Modalities are different.\nHowever, special controls are in place to\nmitigate any risk for this difference."],["Output Device","Softcopy Workstation","Softcopy Workstation, PACS, RIS","NA"],["Deployment","Stand-alone computer","Same","NA"],["Software Level\nof Concern","Moderate","Moderate","NA"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p4-t0","doc_id":"K182419","page_num":4,"bbox":[108.0,138.17,313.02,585.05],"n_rows":28,"n_cols":2,"columns":["In accordance with 21 CFR 8","07.92 the fol"],"rows":[["In accordance with 21 CFR 8","07.92 the fol"],["",""],["I. SUBMITTER",""],["",""],["GE Healthcare",""],["500 West Monroe",""],["Chicago, IL 60661",""],["",""],["Primary Contact Person:","Renee Webb"],["","Senior Regu"],["","GE Healthca"],["","Phone: 847-"],["",""],["Secondary Contact Person:","John Manar"],["","Regulatory A"],["","GE Healthca"],["","Phone: 224-"],["",""],["Date Prepared:","December 1"],["",""],["II. DEVICE",""],["",""],["Name of Device:","Centricity Un"],["Common Name:","Picture Arch"],["Classification Name:","21 CFR 892."],["","Radiological"],["Regulatory Class:","II"],["Product Code:","LLZ"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K182419-p7-t0","doc_id":"K182419","page_num":7,"bbox":[108.27,164.65,544.23,717.54],"n_rows":6,"n_cols":8,"columns":["Feature","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","Centricity Universal","","","Centricity Universal","",""],["","","Viewer","","","Viewer","",""],["","","(K150420)","","","with Cath Tools","",""],["Intended Use /\nIndications For\nUse","Centricity Universal\nViewer is a device that\ndisplays medical images\nand data from various\nimaging sources, and\nfrom other healthcare\ninformation sources.\nMedical images and data\ncan be displayed,\ncommunicated, stored,\nand processed.\nTypical users of this\nsystem are authorized\nhealthcare professionals.\nCentricity Universal\nViewer is intended to\nassist in the viewing,\nanalysis, diagnostic\ninterpretation, and\nsharing of images and\nother information.\nMammography images\nmay only be interpreted\nusing a monitor\ncompliant with\nrequirements of local\nregulations and must\nmeet other technical\nspecifications reviewed\nand accepted by the\nlocal regulatory\nagencies.","","","Identical to\npredicate device","","","No change"],["Contraindication","Centricity Universal Viewer\nis contraindicated for the\nuse of lossy compressed\nmammographic images.","","","Identical to\npredicate device","","","No change"]],"caption_candidate":"clearance K150420:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p8-t0","doc_id":"K182419","page_num":8,"bbox":[108.28,108.55,544.22,708.18],"n_rows":8,"n_cols":12,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences","",""],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences","",""],["","","","","Centricity Universal","","","Centricity Universal","","","",""],["","","","","Viewer","","","Viewer","","","",""],["","","","","(K150420)","","","with Cath Tools","","","",""],["","","","Lossy compressed\nmammographic images\nand digitized film screen\nimages must not be\nreviewed for primary image\ninterpretations.","","","","","","","",""],["Cath Analysis\nTools","","","Not supported","","","Supported in the\nsubject device.\nThe following tools\nare available to help\nperform an analysis\nof images received\nas a result of a\ncatheterization\nprocedure:\n1. Stenosis Analysis\n2. Left ventricular\nanalysis\n3. Catheter\ncalibration\n Point to Point\nCalibration\n Calibration\nextension\n4. Distance\nmeasurement","","","Equivalent. Cath\nTools modifications\ndo not change the\nIntended Use. The\nCath Tools\nfunctionality added is\nidentical to the Cath\nTools in GE\nHealthcare’s,\nCentricity Radiology\nRA600, Cardiology\nCA1000 cleared\nunder K063628. Test\nresults for these\nmodifications do not\nraise different issues\nof safety or\neffectiveness. There\nare no new potential\nhazards and no\nchanges to existing\npotential hazards,\nand no change in the\nfinal risk ratings for\nthe device.","",""],["","Workflow","","","","","","","","","",""],["Interactive\nsearch for\nstudies","","","Search by:\n1. Patient name\n2. ID\n3. Accession Number\n4. Study date\n5. Study description\n6. Modality\n7. Study status\n8. Referring Physician\n9. Date of Birth\n10. Referring Service","","","Same as predicate,\nexcept:\n- Retrieval of off-\nline study\n- Access to\nconfidential\npatient studies\nbased on\nprivileges\n- Increase number\nof studies the","","","Equivalent. Adding\nthe modifications\nunder interactive\nsearch for studies\ndoes not impact the\ndevice safety and\neffectiveness.","",""]],"caption_candidate":"K182419, Page 5 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p9-t0","doc_id":"K182419","page_num":9,"bbox":[108.28,108.55,544.22,713.88],"n_rows":9,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["","","","11. Priority\n12. Online status (CPACS\nonly)\n13. 0 image studies\n(CPACS only)\n14. Performing physician\n15. Location (Enterprise\nArchive (EA) only for\nCardiology)","","","worklist can\ndisplay and\nremove 30 study\nlimit on custom\nworklists\n- Support for\nTechnologist\nstudy verification\nworkflow and\nteaching folder\n- Create, access,\nsave and display\nkey images","","",""],["Search from\nDICOM server","","","Search for studies\nlocated on the external\nDICOM compliant server.\nSupported only on IW\nbackend","","","Same as predicate,\nexcept:\n- search and\nretrieve prior\nexams from\nexternal DICOM\nserver\n- save and display\nDICOM grayscale\npresentation\nstate object to\nwork with any\ntype of under\nlying hanging\nprotocol","","","Equivalent. Adding\nthe modifications\nunder the search\nfrom DICOM server\ndoes not impact the\ndevice safety and\neffectiveness."],["","Image Display","","","","","","","",""],["","","","","","","","","",""],["Ability to display\ninformation","","","Ability to display the\nfollowing:\n1. Image\n2. Report\n3. Patient information\n4. Exam information\n5. DICOM Header\ninformation\n6. GSPS\n7. RPPS\n8. FCE\n9. Key Image Notes\n10. Exam Notes","","","Same as predicate,\nexcept:\n- native support of\ndiagnostic\ninterpretation for\n2D and DBT\nmammo images\n- user, group and\nsystem level step\nprotocols\n- support DICOM\nmetadata in\noverlay /","","","Equivalent. These\nmodifications do not\nchange the Intended\nUse. The device\ncontinues to support\nthe display, storage,\nanalysis and\nprocessing of various\nmedical images using\na similar technology.\nTest results for these\nmodifications do not\nraise different issues"]],"caption_candidate":"K182419, Page 6 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p10-t0","doc_id":"K182419","page_num":10,"bbox":[108.26,108.55,544.24,715.2],"n_rows":8,"n_cols":8,"columns":["Feature","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","Centricity Universal","","","Centricity Universal","",""],["","","Viewer","","","Viewer","",""],["","","(K150420)","","","with Cath Tools","",""],["","11. Modality and VOI LUT\n12. Structured Reports","","","annotation editor\n- support\nsynchronized ECG\ncurve, ECG scroll\nand ECG curve\nheight selector\n- support Dorsal\nview (Reverse\nACR IHE) for\nmammography","","","of safety or\neffectiveness. There\nare no new potential\nhazards and no\nchanges to existing\npotential hazards,\nand no change in the\nfinal risk ratings for\nthe device."],["Image\nAnnotations and\nmeasurements","1. Line\n2. Angle\n3. SUV\n4. OB Measurements\n5. Digital Subtraction\nAngiography (DSA)\n6. Triangulation\n7. MIP/MPR\n8. Spine Labeling\n9. Using \"imager pixel\nspacing\" - DICOM field to\nenable measurements\nacross all CR/DX/US\nexams.\n10. Cardio Thoracic Ratio\n(CTR)\n11. Image Annotations","","","Same as predicate,\nexcept:\n- Automatically\nmark images as\nkey when image is\nannotated\n- Use “imager pixel\nspacing” DICOM\nfield to enable\nmeasurements\nacross CR/DX/US\nexams","","","Equivalent. Adding\nthe modifications for\nimage annotations\nand measurements\ndoes not impact the\ndevice safety and\neffectiveness. These\nenhancements\nprovide information\nalready available to\nbe used in the same\nway as the predicate,\nfor the same purpose\nand by the same\nusers."],["Customized\nHanging\nProtocols","Smart Reading Protocols\n-Regular Hanging\nprotocols to launch\nmultiple MIP/MPRs","","","Same as predicate,\nexcept:\n- multi-modality and\nmulti-vendor\nhanging protocol\n- dedicated toolbar\nfor mammography\nfeatures\n- smart reading\nprotocols learn\nuser’s preferences\nfor MRI\nmultiphasic\nstudies","","","Equivalent. Adding\nthe modifications for\ncustomized hanging\nprotocols does not\nimpact the device\nsafety and\neffectiveness. These\nenhancements\nprovide information\nto be used in the\nsame way as the\npredicate, for the\nsame purpose and by\nthe same users."],["Maximum\nIntensity","Maximum Intensity\nProjection (MIP) MIP with","","","Same as predicate,\nexcept:","","","Equivalent. These\nmodifications do not"]],"caption_candidate":"K182419, Page 7 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p11-t0","doc_id":"K182419","page_num":11,"bbox":[108.28,108.55,544.22,714.0],"n_rows":15,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["Projection (MIP)\nMIP with\ninteractive\nwindow-level\nclipping volume\nof interest,\nzoom, pan, and\nrotate","","","interactive window-level\nclipping volume of\ninterest, zoom, pan, and\nrotate","","","- Recalculate\nstandard update\nvalue on the fly for\nPET/CT images\n- Multi-planar\nreconstruction\nsupport multiple\noblique\nreconstruction\n- Support for non-\nsquare pixel image\ncalibration","","","change the Intended\nUse. The device\ncontinues to support\nthe display, storage,\nanalysis and\nprocessing of various\nmedical images using\na similar technology.\nTest results for these\nmodifications do not\nraise different issues\nof safety or\neffectiveness. There\nare no new potential\nhazards and no\nchanges to existing\npotential hazards,\nand no change in the\nfinal risk ratings for\nthe device."],["","Printing","","","","","","","",""],["","","","","","","","","",""],["Key\nImages/Print\nPages","","","Created Print Pages from\nselected Key Images,\none-click placement;\ncustomized templates;\none click-full screen\nsnapshot","","","Identical to\npredicate device","","","No change"],["Print to Film /\nPaper","","","Print collage of images to\nprinter","","","Identical to\npredicate device","","","No change"],["","Connectivity,","","","","","","","",""],["","Interfaces &","","","","","","","",""],["","Interoperability","","","","","","","",""],["","","","","","","","","",""],["Integration","","","Integration COM service","","","Identical to\npredicate device","","","No change"],["Interfaces","","","Generic interface to\nintegrate outbound with\nthird party applications\nand internal GEHC\napplications that meet\nthe interface\nrequirements.","","","Same as predicate,\nexcept:\n- Update to API\nconnectivity to\nlaunch newer\nversions of 3rd\nparty software","","","Equivalent. Adding\nmodifications for the\ninterfaces does not\nimpact the device\nsafety and\neffectiveness. There\nare no new potential"]],"caption_candidate":"K182419, Page 8 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p12-t0","doc_id":"K182419","page_num":12,"bbox":[108.27,108.55,544.23,715.38],"n_rows":12,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["","","","","","","applications such\nas GE Healthcare’s\nEchoPAC and\nAdvantage\nWorkstation\napplications","","","hazards and no\nchanges to existing\npotential hazards,\nand no change in the\nfinal risk ratings for\nthe device."],["External system\nlaunch","","","The viewer can be\nlaunched via a 3rd party\napplication using the\nfollowing methods:\n1. url launch\n2. IVAPI\n3. Inbound API","","","Same as predicate,\nexcept:\n- Updates in\ninterfaces with 3rd\nparty software\napplications\n- URL launch using\nSUID when study\nassociated with\nmultiple orders","","","Equivalent. Adding\nmodifications under\nexternal system\nlaunch does not\nimpact the device\nsafety and\neffectiveness. These\nenhancements\nprovide information\nto be used in the\nsame way as the\npredicate, for the\nsame purpose and by\nthe same users."],["","Administrative","","","","","","","",""],["","","","","","","","","",""],["Interactive\nquery","","","In console, supporting\nwildcards","","","Identical to\npredicate device","","","No change"],["Setup","","","Wizard and silent","","","Identical to\npredicate device","","","No change"],["On-line help","","","Yes","","","Identical to\npredicate device","","","No change"],["User Interface\nand User\nManual\nLanguages","","","1. English, 2. German,\n3. Japanese, 4. French,\n5. Simplified Chinese\n6. Italian, 7. Polish, 8.\nSpanish\n9. Turkish, 10. Brazilian\nPortuguese, 11. Dutch,\n12. Swedish, 13. Russian\n14. Korean, 15. Finnish,\n16. Danish, 17.\nNorwegian,\n18. Traditional Chinese\n19. Portuguese, 20.\nGreek,\n21. Hungarian","","","Identical to\npredicate device","","","No change"]],"caption_candidate":"K182419, Page 9 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p13-t0","doc_id":"K182419","page_num":13,"bbox":[108.27,108.55,544.23,716.7],"n_rows":12,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["Administrative\nrights\nassignment","","","Per user/group","","","Identical to\npredicate device","","","No change"],["Automatic\nnotification\nmessages","","","By email. HL7","","","Same as predicate,\nexcept:\n- auto refresh and\nnotification when\nnew images arrive\n- merge two studies\ninto one\n- audit log to track\nexport of images","","","Equivalent. Adding\nmodifications under\nautomatic\nnotification\nmessages does not\nimpact the device\nsafety and\neffectiveness. These\nenhancements\nprovide information\nto be used in the\nsame way as the\npredicate, for the\nsame purpose and by\nthe same users."],["System logging","","","Combined system log","","","Identical to\npredicate device","","","No change"],["Compression","","","Wavelet compression\n1. JPEG2000 lossless\n2. JPEG2000 lossy\nNon-wavelet\ncompression\n1. JPEG lossless\n2. JPEG lossy\nJPEG2000 lossless for\nimages received\nuncompressed","","","Identical to\npredicate device","","","No change"],["","Minimal System","","","","","","","",""],["","Requirements","","","","","","","",""],["Offering","","","1. Turnkey solution\n(GEHC IT provides both\nthe software and\nhardware required to\nfunction as a complete\nsystem)\n2. Software only solution\n(GEHC IT provides and\ndeploys the Software).","","","Identical to\npredicate device","","","No change"],["ESXi","","","VMware vSphere ESXi","","","Identical to\npredicate device","","","No change"]],"caption_candidate":"K182419, Page 10 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p14-t0","doc_id":"K182419","page_num":14,"bbox":[108.29,108.55,544.21,714.0],"n_rows":15,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["","Workstation","","","","","","","",""],["","Features","","","","","","","",""],["","","","","","","","","",""],["Operating\nSystem for\nDiagnostic\nWorkstation","","","Microsoft™ Windows 7 -\n64 bit\nMicrosoft™ Windows 8.1\n- 64 bit","","","Same as predicate,\nexcept:\n- adding support for\nWindows 10\noperating system\n32 or 64 bit with\nInternet Explorer\n11","","","Equivalent. Adding\nsupport for Windows\n10 operating system\n32 or 64 bit with\nInternet Explorer 11\ndoes not impact the\ndevice safety and\neffectiveness."],["Minimum\nHardware\nrequirement for\nDiagnostic\nWorkstation","","","2 Quad-core processor of\n2.0\nGHz or more\n8GB RAM minimum\n146GB drive in Raid 0\nconfiguration\nDVD-RW Optical drive\nOne 1GB NIC\n10/100/1000 Mb\nEthernet\nnetwork\n4 Mbps and faster TCP-IP\nnetwork","","","Identical to\npredicate device","","","No change"],["","Security","","","","","","","",""],["","","","","","","","","",""],["User\nAuthentication\nusing a 3rd\nParty\nAuthentication\nServer","","","Active Directory","","","Same as predicate,\nexcept:\n- Provides common\nauthentication\n- security\nhardening and\ncybersecurity\nimprovements","","","Equivalent. Adding\ncommon\nauthentication\nsupport and security\nhardening does not\nimpact the device\nsafety and\neffectiveness."],["","Enterprise","","","","","","","",""],["","Imaging","","","","","","","",""],["DICOM Protocol","","","1. Supports DICOM SOP\nclasses\n2. Receive images -\nDICOM storage SCP\n3. Support DICOM 3.0\ninput\n4. gray scale","","","Same as predicate,\nexcept:\n- support additional\ncolor (YBR)\ninterpretations\nwith US images\n- support saving","","","Equivalent. Adding\nmodifications under\nDICOM protocol does\nnot impact the device\nsafety and\neffectiveness. These\nenhancements"]],"caption_candidate":"K182419, Page 11 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182419-p15-t0","doc_id":"K182419","page_num":15,"bbox":[108.28,108.55,544.22,496.62],"n_rows":9,"n_cols":10,"columns":["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],"rows":[["Feature","","","","Predicate Device","","","Subject Device","","Discussion of\nDifferences"],["","","","","Centricity Universal","","","Centricity Universal","",""],["","","","","Viewer","","","Viewer","",""],["","","","","(K150420)","","","with Cath Tools","",""],["","","","presentation states","","","image calibration\ninformation in\nPresentation\nState","","","provide information\nto be used in the\nsame way as the\npredicate, for the\nsame purpose and by\nthe same users."],["(XED) Cross\nEnterprise\nDisplay","","","Provides the ability to\nview patient information\nacross multiple\nenterprise sites based on\nmatching patient ID\nnumbers.","","","Same as predicate,\nexcept:\n- New API to access\npatient history in\nFHIR format and\nfrom different\nsources\n- Enhance ability to\ngroup studies\nanatomically\n- matching patient\nstudies from\nremote sites with\nthe same patient","","","Equivalent. Adding\nmodifications under\ncross enterprise\ndisplay does not\nimpact the device\nsafety and\neffectiveness. These\nenhancements allow\npatient history to be\nused in the same way\nas the predicate, for\nthe same purpose\nand by the same\nusers."],["","User","","","","","","","",""],["","Environment","","","","","","","",""],["Designed to be\nutilized inside\nand outside of\nradiology","","","Designed to be utilized\ninside and outside of\nradiology and cardiology","","","Identical to\npredicate device","","","No change"]],"caption_candidate":"K182419, Page 12 of 13","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182564-p7-t0","doc_id":"K182564","page_num":7,"bbox":[108.03,254.76,553.4,390.6],"n_rows":5,"n_cols":11,"columns":["","","","DDDDaaaattttaaaasssseeeetttt","","DDDDiiiicccceeee iiiinnnnddddeeeexxxx","","","AAAAbbbbssssoooolllluuuutttteeee ddddiiiiffffffffeeeerrrreeeennnncccceeee ooooffff\ntttthhhheeee rrrreeeellllaaaattttiiiivvvveeee vvvvoooolllluuuummmmeeeessss [[[[pppppppp]]]]","",""],"rows":[["","","","DDDDaaaattttaaaasssseeeetttt","","DDDDiiiicccceeee iiiinnnnddddeeeexxxx","","","AAAAbbbbssssoooolllluuuutttteeee ddddiiiiffffffffeeeerrrreeeennnncccceeee ooooffff\ntttthhhheeee rrrreeeellllaaaattttiiiivvvveeee vvvvoooolllluuuummmmeeeessss [[[[pppppppp]]]]","",""],["","BBBBrrrraaaaiiiinnnn","","","A","","0.96 ± 0.01","","","1.7 ± 1.3",""],["CCCCSSSSFFFF","","","A","","0.78 ± 0.05","","","1.8 ± 1.3","",""],["","IIIICCCCVVVV","","","A","","0.98 ± 0.01","","","----",""],["HHHHiiiippppppppooooccccaaaammmmppppuuuussss ttttoooottttaaaallll\nHHHHiiiippppppppooooccccaaaammmmppppuuuussss rrrriiiigggghhhhtttt\nHHHHiiiippppppppooooccccaaaammmmppppuuuussss lllleeeefffftttt","","","B","","0.84 ± 0.03\n0.84 ± 0.03\n0.84 ± 0.03","","","0.03 ± 0.02\n0.01 ± 0.01\n0.01 ± 0.01","",""]],"caption_candidate":"comparison. The results are summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182564-p7-t1","doc_id":"K182564","page_num":7,"bbox":[102.64,476.4,548.79,717.32],"n_rows":10,"n_cols":11,"columns":["","","","DDDDaaaattttaaaasssseeeetttt","","","DDDDiiiicccceeee iiiinnnnddddeeeexxxx","","AAAAbbbbssssoooolllluuuutttteeee ddddiiiiffffffffeeeerrrreeeennnncccceeee ooooffff\ntttthhhheeee rrrreeeellllaaaattttiiiivvvveeee vvvvoooolllluuuummmmeeeessss [[[[pppppppp]]]]","",""],"rows":[["","","","DDDDaaaattttaaaasssseeeetttt","","","DDDDiiiicccceeee iiiinnnnddddeeeexxxx","","AAAAbbbbssssoooolllluuuutttteeee ddddiiiiffffffffeeeerrrreeeennnncccceeee ooooffff\ntttthhhheeee rrrreeeellllaaaattttiiiivvvveeee vvvvoooolllluuuummmmeeeessss [[[[pppppppp]]]]","",""],["","FFFFrrrroooonnnnttttaaaallll lllloooobbbbeeee ttttoooottttaaaallll","","C","","","0.95 ± 0.01\n0.94 ± 0.02\n0.94 ± 0.01","","","1.95 ± 0.90",""],["","FFFFrrrroooonnnnttttaaaallll lllloooobbbbeeee rrrriiiigggghhhhtttt","","","","","","","","1.02 ± 0.61",""],["","FFFFrrrroooonnnnttttaaaallll lllloooobbbbeeee lllleeeefffftttt","","","","","","","","0.93 ± 0.50",""],["OOOOcccccccciiiippppiiiittttaaaallll lllloooobbbbeeee ttttoooottttaaaallll\nOOOOcccccccciiiippppiiiittttaaaallll lllloooobbbbeeee rrrriiiigggghhhhtttt\nOOOOcccccccciiiippppiiiittttaaaallll lllloooobbbbeeee lllleeeefffftttt","","","C","","","0.88 ± 0.03\n0.88 ± 0.03\n0.87 ± 0.04","","0.87 ± 0.75\n0.43 ± 0.36\n0.53 ± 0.53","",""],["","PPPPaaaarrrriiiieeeettttaaaallll lllloooobbbbeeee ttttoooottttaaaallll","","C","","","0.89 ± 0.03\n0.88 ± 0.04\n0.88 ± 0.02","","","2.81 ± 1.13",""],["","PPPPaaaarrrriiiieeeettttaaaallll lllloooobbbbeeee rrrriiiigggghhhhtttt","","","","","","","","1.45 ± 0.80",""],["","PPPPaaaarrrriiiieeeettttaaaallll lllloooobbbbeeee lllleeeefffftttt","","","","","","","","1.36 ± 0.56",""],["TTTTeeeemmmmppppoooorrrraaaallll lllloooobbbbeeee ttttoooottttaaaallll\nTTTTeeeemmmmppppoooorrrraaaallll lllloooobbbbeeee rrrriiiigggghhhhtttt\nTTTTeeeemmmmppppoooorrrraaaallll lllloooobbbbeeee lllleeeefffftttt","","","C","","","0.91 ± 0.01\n0.91 ± 0.02\n0.91 ± 0.01","","1.33 ± 0.76\n0.72 ± 0.46\n0.61 ± 0.39","",""],["","CCCCeeeerrrreeeebbbbeeeelllllllluuuummmm ttttoooottttaaaallll","","","C","","0.98 ± 0.01","","","0.47 ± 0.20",""]],"caption_candidate":"percentage points.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182564-p8-t0","doc_id":"K182564","page_num":8,"bbox":[102.67,72.83,548.81,103.45],"n_rows":2,"n_cols":10,"columns":["","CCCCeeeerrrreeeebbbbeeeelllllllluuuummmm rrrriiiigggghhhhtttt","","","","0.97 ± 0.00","","","0.31 ± 0.13",""],"rows":[["","CCCCeeeerrrreeeebbbbeeeelllllllluuuummmm rrrriiiigggghhhhtttt","","","","0.97 ± 0.00","","","0.31 ± 0.13",""],["","CCCCeeeerrrreeeebbbbeeeelllllllluuuummmm lllleeeefffftttt","","","","0.97 ± 0.01","","","0.17 ± 0.11",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182616-p7-t0","doc_id":"K182616","page_num":7,"bbox":[66.59,339.24,546.0,496.56],"n_rows":4,"n_cols":5,"columns":["ROI","True Positive\nDetection\nFraction\n(%)","Lower Limit of Exact\n95% Confidence\nIntervals","True Negative\nDetection Fraction\n(%)","Lower Limit of\nExact 95%\nConfidence\nIntervals"],"rows":[["ROI","True Positive\nDetection\nFraction\n(%)","Lower Limit of Exact\n95% Confidence\nIntervals","True Negative\nDetection Fraction\n(%)","Lower Limit of\nExact 95%\nConfidence\nIntervals"],["Tissue Surface","92.9 (235/253)","89.0","95.0 (209/220)","91.2"],["Layering","89.6 (205/229)","84.8","97.8 (220/225)","94.9"],["Hypo-Reflective\nStructures","91.1 (175/192)","86.2","92.9 (247/266)","89.1"]],"caption_candidate":"Two-Sided Exact 95% Exact Confidence Intervals","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182901-p5-t0","doc_id":"K182901","page_num":5,"bbox":[113.64,81.12,594.0,162.66],"n_rows":2,"n_cols":7,"columns":["Product","Marketed\nby","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed\nby","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion Precision\n(TSX‐304A/2) V8.6","Canon\nMedical\nSystems,\nUSA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K173468","02/23/2018"]],"caption_candidate":"11. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K182901-p6-t0","doc_id":"K182901","page_num":6,"bbox":[107.52,54.32,567.0,272.52],"n_rows":11,"n_cols":5,"columns":["Item","Aquilion Precision\n(TSX‐304A/1 and 2) V8.8 with AiCE","","","Aquilion Precision\n(TSX‐304A/2) V8.6\nK173468"],"rows":[["Item","Aquilion Precision\n(TSX‐304A/1 and 2) V8.8 with AiCE","","","Aquilion Precision\n(TSX‐304A/2) V8.6\nK173468"],["Anatomical Region","","Whole Body (FBP, AIDR 3D, FIRST)","","Whole Body (FBP, AIDR 3D, FIRST)"],["","","Abdomen and pelvis (AiCE)","",""],["Noise Reduction\nProcessing","","AIDR 3D","","AIDR 3D\nAIDR 3D Enhanced"],["","","AIDR 3D Enhanced","",""],["","","AiCE","",""],["Central processing unit\nmemory size","128 Gbytes or more","128 Gbytes or more","","256 Gbytes or more"],["Patient couch ‐ Frame\nslide stroke","310 mm","","","330 mm"],["Handy Snap*\n(CAXS‐001A)","Optional","","","N/A"],["Dual energy system*\npackage (CSDP‐001A)","","Optional","","N/A"],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183012-p5-t0","doc_id":"K183012","page_num":5,"bbox":[66.6,422.49,545.4,665.13],"n_rows":10,"n_cols":5,"columns":["erutcurtS","","Lumen Area","","Bias: 0.81mm2 [0.3, 1.9], Intercept: 0.65mm2 [-0.6, 0.9],"],"rows":[["erutcurtS","","Lumen Area","","Bias: 0.81mm2 [0.3, 1.9], Intercept: 0.65mm2 [-0.6, 0.9],"],["","","tested range 0.3 - 290.1mm2","","Slope: 1.01 [0.9, 1.0], Quadratic term: 0.0 [0.0, 0.0], R2: 0.9987"],["","Wall Area,\ntested range 9.4 - 448.6mm2","","Bias: 0.50mm2 [-1.08, 1.29], Intercept: -0.59mm2 [-4.1, 2. 8.0],\nSlope: 1.0 [0.99, 1.04], Quadratic term: 0.0 [0.0, 0.0], R2: 0.9974",""],["","Stenosis**,\ntested range 33-69%","","Vessels ≥5.9mm: Bias: 3.7% [1.29, 4.47], Intercept: 5.99% [-0.81, 9.93],\nSlope: 0.96 [0.84, 1.1], Quadratic term: -0.01 [-0.02, 0.01], R2: 0.8034",""],["","","","Vessels <5.9mm: Bias: 9.3% [2.14, 12.72], Intercept: 34.0% [-2.3, 38.9],\nSlope: 0.55 [0.42, 1.21], Quadratic term: 0.001 [-0.02, 0.06], R2: 0.9549",""],["","Wall Thickness,\ntested range 1.0 - 9.0mm","","Bias: 0.5mm [0.3, 0.6], Intercept: 0.27mm [-0.1, 0.5],\nSlope: 1.05 [1.01, 1.1], Quadratic term: -0.008 [-0.02, 0.01], R2: 0.9855",""],["","Plaque Burden,\ntested range 0.4 -1.0 (ratio)","","Bias: -0.01 [-0.01, .004], Intercept: 0.01 [-0.1, 0.04],\nSlope: 0.99 [0.9, 1.1], Quadratic term: 0.03 [-0.1, 0.3], R2: 0.9794",""],["noitisopmoC","Calcified Area,\ntested range 0.0 - 51.2mm2","","Difference: 0.15mm2 [-0.5, 0.97], Intercept: 0.4mm2 [-0.02, 1.6],\nSlope: 0.9 [0.6, 1.1], Quadratic term: -0.01 [-0.1, 0.04], R2: 0.875",""],["","LRNC Area,\ntested range 0.0 - 26.8mm2","","Difference: 0.8mm2 [-0.7, 2.6], Intercept: 1.44mm2 [0.2, 3.4],\nSlope: 0.8 [0.2, 1.1], Quadratic term: 0.004 [-0.1, 0.3], R2: 0.5222",""],["","Matrix Area,\ntested range 2.6 - 57.1mm2","","Difference: -1.6mm2 [-3.6, 0.32], Intercept: 2mm2 [-3, 5],\nSlope: 0.83 [0.7, 1.0], Quadratic term: -0.01 [-0.04, 0.01], R2: 0.7469",""]],"caption_candidate":"established*:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p6-t0","doc_id":"K183019","page_num":6,"bbox":[85.5,404.52,535.02,453.12],"n_rows":2,"n_cols":4,"columns":["","N","Mean of Maximum Error","STD"],"rows":[["","N","Mean of Maximum Error","STD"],["Distance","5","0.242 mm","0.062 mm"]],"caption_candidate":"recorded. The average of all distances and its standard deviation are detailed in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p7-t0","doc_id":"K183019","page_num":7,"bbox":[85.5,273.12,535.02,346.02],"n_rows":3,"n_cols":4,"columns":["","N","Average Mean","STD"],"rows":[["","N","Average Mean","STD"],["COM","45","0.30 mm","0.12 mm"],["Orientation","45","1.00 Degrees","0.90 Degrees"]],"caption_candidate":"The table below summarizes the test data:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p8-t0","doc_id":"K183019","page_num":8,"bbox":[69.83,401.65,519.49,514.08],"n_rows":5,"n_cols":10,"columns":["","","Successful","Failed","TP","","","","",""],"rows":[["","","Successful","Failed","TP","","","","",""],["","Total","visualizations <","visualizations >","","","","","",""],["Version","cases","2mm","2 mm","","TN","FP","FN","Sensitivity","Specificity"],["1.0.0","68","65","3","0","60","5","3","0.00%","92.31%"],["3.3.0","68","66","2","1","59","7","1","50.00%","89.39%"]],"caption_candidate":"Table 1: Anomaly Detection Analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p8-t1","doc_id":"K183019","page_num":8,"bbox":[69.83,564.55,519.49,650.34],"n_rows":3,"n_cols":3,"columns":["","Success without AD","Success with AD"],"rows":[["","Success without AD","Success with AD"],["1.0.0","95.59%","95.24%"],["3.3.0","97.06%","98.33%"]],"caption_candidate":"Table 2: Overall System Performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p9-t0","doc_id":"K183019","page_num":9,"bbox":[85.5,511.62,545.46,711.6],"n_rows":6,"n_cols":4,"columns":["","SIS Software\nversion 3.3.0\n(subject)","SIS Software\nversion 1.0\n(K162830)","Merge PACS\n(K173475)"],"rows":[["","SIS Software\nversion 3.3.0\n(subject)","SIS Software\nversion 1.0\n(K162830)","Merge PACS\n(K173475)"],["Allows for importing of digital\nimaging sets","Yes","Yes","Yes"],["Uses proprietary software\nalgorithm for 3D image\nprocessing","Yes","Yes","Yes"],["Allows for review and\nanalysis of data in various\n2D and 3D presentation\nformats","Yes","Yes","Yes"],["Performs image fusion of\ndatasets using automated or\nmanual image matching\ntechnique","Yes","Yes","Yes"],["Segments structures in","Yes","Yes",""]],"caption_candidate":"SIS Software Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183019-p10-t0","doc_id":"K183019","page_num":10,"bbox":[85.5,72.36,545.46,490.08],"n_rows":9,"n_cols":4,"columns":["","SIS Software\nversion 3.3.0\n(subject)","SIS Software\nversion 1.0\n(K162830)","Merge PACS\n(K173475)"],"rows":[["","SIS Software\nversion 3.3.0\n(subject)","SIS Software\nversion 1.0\n(K162830)","Merge PACS\n(K173475)"],["images with manual and\nautomated tools and\nconverts them into 3D\nobjects for display","","","available information; but\nthese features are\nalready supported by the\npredicate."],["Creates hybrid datasets by\nfilling in segmented regions\nslice-by-slice on anatomical\ndatasets","Yes","Yes",""],["Results can be uploaded to\nplanning system","Yes","Yes","Yes"],["Segmentation of CT scan to\nidentify structures in relation\nto those visualized on MR","Yes","No","Processes images to\nenable cross-registration\nor cross-referencing."],["Cross-registration of two\nmulti-modality images and\ncreation of 3D (fused) model","Yes","No","Yes"],["Uploading and viewing\nimages via web-based portal\nor directly via separately\ncleared PACS","Yes","No","Yes"],["Anomaly Detection","Yes","Yes","No"],["STN Smoothing\nFunctionality","Yes; supported by\ntesting\ndemonstrating new\nfeature does not\nalter device output\ncompared to\npredicate device","No","No"]],"caption_candidate":"K183019","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183046-p5-t0","doc_id":"K183046","page_num":5,"bbox":[113.64,67.68,594.0,169.98],"n_rows":2,"n_cols":7,"columns":["Product","Marketed\nby","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed\nby","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion ONE\n(TSX‐305A/3) V8.3 with\nFIRST 2.1\n(Primary Predicate\nDevice)","Canon\nMedical\nSystems,\nUSA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K170177","06/30/2017"]],"caption_candidate":"11. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183046-p6-t0","doc_id":"K183046","page_num":6,"bbox":[107.52,54.36,567.0,392.88],"n_rows":25,"n_cols":5,"columns":["Item","","Aquilion ONE (TSX‐305A/6) V8.9","","Aquilion ONE (TSX‐305A/3) V8.3 with\nFIRST 2.1 (K170177)"],"rows":[["Item","","Aquilion ONE (TSX‐305A/6) V8.9","","Aquilion ONE (TSX‐305A/3) V8.3 with\nFIRST 2.1 (K170177)"],["","","with AiCE","",""],["Anatomical Region","","AIDR 3D","","AIDR 3D\n(Whole Body)\nFIRST\n(Abdomen, pelvis, lung, cardiac,\nextremities and head)"],["","","(Whole Body)","",""],["","","","",""],["","","FIRST","",""],["","","(Abdomen, pelvis, lung, cardiac,","",""],["","","extremities and head)","",""],["","","","",""],["","","AiCE","",""],["","","(Abdomen, pelvis, lung, and cardiac)","",""],["Noise Reduction\nProcessing","","AIDR 3D",")","AIDR 3D\nAIDR 3D Enhanced\nQuantum Denoising Smoothing (QDS)"],["","","AIDR 3D Enhanced","",""],["","","Quantum Denoising Smoothing (QDS","",""],["","","AiCE","",""],["Processing capability","","Console CKCN‐018B/1","","Console CKCN‐018A/3\nI‐REC BOX (FIRST only)"],["","","Reconstruction processing unit","",""],["","","(AiCE/FIRST)","",""],["Display console kit","","CGS‐94A (Optional)*","","CGS‐75A (Optional)"],["Image Quality Claim","","‐Improved Quantitative Spatial","","No change\nNo change\nNo change"],["","","Resolution over AIDR 3D","",""],["","","‐Improved Quantitative Dose","",""],["","","Reduction over AIDR 3D","",""],["","","‐Improved Low‐contrast Detectability","",""],["","","over AIDR 3D","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p6-t0","doc_id":"K183133","page_num":6,"bbox":[60.47,609.06,552.28,732.3],"n_rows":3,"n_cols":3,"columns":["Similarities Comparison","",""],"rows":[["Similarities Comparison","",""],["Characteristic","MRCP+v1 (Subject)","IQQA-Liver (Predicate)"],["Intended Use and\nIndications for Use","MRCP+v1 is indicated for use as a software-\nbased image processing system for non-\ninvasive, quantitative assessment of biliary\nsystem structures by facilitating the\ngeneration, visualisation and review of\nthree-dimensional quantitative biliary\nsystem models and anatomical image data.","IQQA-Liver Multimodality is a PC-based, self-\ncontained, non-invasive image analysis\nsoftware application for reviewing multiphase\nimages derived from CT scanners and MR\nscanners. Combining image viewing,\nprocessing and reporting tools, the software is\ndesigned to support the visualization,"]],"caption_candidate":"demonstrate substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p7-t0","doc_id":"K183133","page_num":7,"bbox":[60.47,63.39,552.29,694.83],"n_rows":10,"n_cols":5,"columns":["Similarities Comparison","","","",""],"rows":[["Similarities Comparison","","","",""],["Characteristic","","","MRCP+v1 (Subject)","IQQA-Liver (Predicate)"],["","","","MRCP+v1 calculates quantitative three-\ndimensional biliary system models that\nenable measurement of bile duct widths and\nautomatic detection of regions of variation\n(ROV) of tubular structures. MRCP+v1\nincludes tools for interactive segmentation\nand labelling of the biliary system and\ntubular structures. MRCP+v1 allows for\nregional volumetric analysis of segmented\ntree-like, tubular structures and the\ngallbladder.\nCombining image viewing, processing and\nreporting tools, the metrics provided is\ndesigned to support physicians in the\nvisualization, evaluation and reporting of\nhepatobiliary structures. These models and\nthe physical parameters derived from the\nmodels, when interpreted by a trained\nphysician, yield information that may assist\nin biliary system assessment.\nMRCP+v1 is designed to utilize DICOM\ncompliant MRCP datasets, acquired on\nsupported MR scanners using supported\nMRCP acquisition protocols.\nMRCP+v1 is suitable for all patients not\ncontra-indicated for MRI.","evaluation and reporting of liver and\nphysician-identified lesions.\nThe software supports a workflow based on\nautomated image registration for viewing and\nanalysing multiphase volume datasets. It\nincludes tools for interactive segmentation\nand labelling of liver segments and vascular\nstructures.\nThe software provides functionalities for\nmanual or interactive segmentation of\nphysician-identified lesions, interactive\ndefinition of virtual resection plane, and\nallows for regional volumetric analysis of such\nlesions in terms of size, position, margin and\nenhancement pattern, providing information\nfor physician's evaluation and treatment\nplanning.\nThe software is designed for use by trained\nprofessionals, including physicians and\ntechnicians.\nImage source: DICOM."],["Target Population","","","Patients suitable to undergo an MRI scan and\nnot contra-indicated for MRI.","Patients suitable to undergo an MRI/CT scan\nand not contra-indicated for MRI/CT."],["Device User","","","Trained operator with a background in\nradiological anatomy, such as an MR\nradiographer/ MR technician.","Trained professionals, including physicians\nand technicians."],["Report User","","","Interpreting clinician, reporting radiologist","N/A"],["Device Use\nEnvironment","","","Installation of MRCP+v1 is controlled and\ninstalled on general purpose workstations. In\nthe context of use, MRCP+v1 reports are\nmade available through existing MDDS\nsoftware devices.","IQQA-Liver is accessed from a cloud-based\nserver."],["","Anatomical","","Abdomen, liver, biliary tree, gallbladder","Abdomen, Liver, Gallbladder"],["","Location","","",""],["Energy\nConsiderations","Energy\nConsiderations","","Software only application. The device, a\nstandalone software application, does not\ndeliver or depend on energy delivered to or\nfrom patients.","Software only application. The device, a\nstandalone software application, does not\ndeliver or depend on energy delivered to or\nfrom patients."]],"caption_candidate":"RA317","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p8-t0","doc_id":"K183133","page_num":8,"bbox":[60.45,63.39,552.3,700.5],"n_rows":18,"n_cols":3,"columns":["Similarities Comparison","",""],"rows":[["Similarities Comparison","",""],["Characteristic","MRCP+v1 (Subject)","IQQA-Liver (Predicate)"],["Design: Purpose","Standalone software application to facilitate\nthe import and visualization of MR data sets\nencompassing the abdomen, including the\nliver with functionality independent of the\nMRI equipment vendor.\nCombining image viewing, processing and\nreporting tools, the metrics provided are\ndesigned to support physicians in the\nvisualization, evaluation and reporting of\nhepatobiliary structures.","Standalone software application to facilitate\nthe import and visualization of MR and CT\ndata sets encompassing the abdomen,\nincluding the liver with functionality\nindependent of the OEM equipment vendor.\nCombining image processing, viewing and\nreporting tools, the software supports the\nvisualization, evaluation and reporting of body\nimaging scans and physician identified lesions."],["Design: Tools","MRCP+v1 calculates quantitative three-\ndimensional biliary system models that\nenable measurement of bile duct widths and\nautomatic detection of regions of variation\n(ROV) of tubular structures. MRCP+v1\nincludes tools for interactive segmentation\nand labelling of the biliary system and\ntubular structures. MRCP+v1 allows for\nregional volumetric analysis of segmented\ntree-like, tubular structures and the\ngallbladder.","Manual or interactive segmentation of\nphysician-identified lesions and allows for\nregional volumetric analysis of such lesions in\nterms of size, position, margin and\nenhancement pattern."],["Design: Supported\nModalities","DICOM 3.0 compliant MR data.","DICOM 3.0 compliant MR data from CT/ MRI\nscanners."],["Compatibility with\nthe environment","Installation of MRCP+v1 is controlled and is\ninstalled on general purpose workstations\nwithin a controlled networked environment.\nMRCP+v1 reads in local files compliant with\nDICOM 3.0.","Cloud -based server access requiring a\nnetworked computer with the hospital\nintranet.\nReads in DICOM 3.0 compliant MR data from\nCT/ MRI scanners."],["Performance","Validated with digital synthetic\nphantoms/raw data, phantom scans, and in-\nvivo scans.","Experimental results on simulated images\ncontaining structures of interest. Phantom\ndata. Retrospective in-vivo data."],["Supported Systems","Validated across all supported\nmanufacturers.","Supported MR/CT systems."],["Standards","IEC 62304, IEC 62366-1, DICOM 3.0, ISO\n14971, ISO 13485","DICOM"],["System/Operating\nSystem","Apple/Mac OS","Standard PC hardware"],["Materials","Not applicable, standalone software.","Not applicable, standalone software."],["Biocompatibility","Not applicable, standalone software.","Not applicable, standalone software."],["Sterility","Not applicable, standalone software.","Not applicable, standalone software."],["","",""],["Electrical Safety\nMechanical Safety","Not applicable, standalone software.\nNot applicable, standalone software.","Not applicable, standalone software.\nNot applicable, standalone software."],["Chemical Safety","Not applicable, standalone software.","Not applicable, standalone software."],["Thermal Safety","Not applicable, standalone software.","Not applicable, standalone software."],["Radiation Safety","Not applicable, standalone software.","Not applicable, standalone software."]],"caption_candidate":"RA317","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p9-t0","doc_id":"K183133","page_num":9,"bbox":[60.23,101.91,552.01,724.9],"n_rows":45,"n_cols":6,"columns":["Differences Comparison","","","","",""],"rows":[["Differences Comparison","","","","",""],["Characteristic","MRCP+v1 (Subject)","","","IQQA-Liver (Predicate)",""],["Manufacturer","Perspectum Diagnostics Ltd","","","EDDA Technologies",""],["No new concerns with regards to safety and effectiveness are raised due to different manufacturer. Perspectum\nDiagnostics Ltd designed and manufactured MRCP+v1 under a QSR complaint quality management system using\nappropriate design controls and an ISO 14971 compliant risk management process. MRCP+v1 underwent a\nsubstantive performance evaluation.","","","","",""],["Intended Use and\nIndications for Use","","MRCP+v1 is indicated for use as a software-","","IQQA-Liver Multimodality is a PC-based, self-",""],["","","based image processing system for non-","","contained, non-invasive image analysis",""],["","","invasive, quantitative assessment of biliary","","software application for reviewing multiphase",""],["","","system structures by facilitating the","","images derived from CT scanners and MR",""],["","","generation, visualisation and review of","","scanners. Combining image viewing,",""],["","","three-dimensional quantitative biliary","","processing and reporting tools, the software is",""],["","","system models and anatomical image data.","","designed to support the visualization,",""],["","","","","evaluation and reporting of liver and",""],["","","MRCP+v1 calculates quantitative three-","","physician-identified lesions.",""],["","","dimensional biliary system models that","","",""],["","","enable measurement of bile duct widths and","","The software supports a workflow based on",""],["","","automatic detection of regions of variation","","automated image registration for viewing and",""],["","","(ROV) of tubular structures. MRCP+v1","","analysing multiphase volume datasets. It",""],["","","includes tools for interactive segmentation","","includes tools for interactive segmentation",""],["","","and labelling of the biliary system and","","and labelling of liver segments and vascular",""],["","","tubular structures. MRCP+v1 allows for","","structures.",""],["","","regional volumetric analysis of segmented","","",""],["","","tree-like, tubular structures and the","","The software provides functionalities for",""],["","","gallbladder.","","manual or interactive segmentation of",""],["","","","","physician-identified lesions, interactive",""],["","","Combining image viewing, processing and","","definition of virtual resection plane, and",""],["","","reporting tools, the metrics provided is","","allows for regional volumetric analysis of such",""],["","","designed to support physicians in the","","lesions in terms of size, position, margin and",""],["","","visualization, evaluation and reporting of","","enhancement pattern, providing information",""],["","","hepatobiliary structures. These models and","","for physician's evaluation and treatment",""],["","","the physical parameters derived from the","","planning.",""],["","","models, when interpreted by a trained","","",""],["","","physician, yield information that may assist","","The software is designed for use by trained",""],["","","in biliary system assessment.","","professionals, including physicians and",""],["","","","","technicians.",""],["","","MRCP+v1 is designed to utilize DICOM","","",""],["","","compliant MRCP datasets, acquired on","","Image source: DICOM.",""],["","","supported MR scanners using supported","",".",""],["","","MRCP acquisition protocols.","","",""],["","","","","",""],["","","MRCP+v1 is suitable for all patients not","","",""],["","","contra-indicated for MRI.","","",""],["Similar intended use and therefore does not raise any new concerns with regards to safety and effectiveness.","","","","",""],["Target Population","","Indicted for use in the general population for","","Indicted for use in the general population for",""],["","","any patients that are not contra-indicated","","any patients that are not contra-indicated for",""],["","","for MRI.","","MRI and CT.",""]],"caption_candidate":"why the differences do not impact safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p11-t0","doc_id":"K183133","page_num":11,"bbox":[79.92,464.31,531.76,576.17],"n_rows":7,"n_cols":3,"columns":["Manufacturer","Model","Field Strength"],"rows":[["Manufacturer","Model","Field Strength"],["Siemens MAGNETOM Prisma 3T","",""],["Siemens MAGNETOM Avantofit 1.5T","",""],["GE Discovery MR750 3T","",""],["GE Optima MR450w 1.5T","",""],["Philips Achieva 3T","",""],["Philips Achieva 1.5T","",""]],"caption_candidate":"MRCP+v1 underwent bench performance testing on the following MR Systems:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p11-t1","doc_id":"K183133","page_num":11,"bbox":[79.92,655.2,531.76,727.98],"n_rows":4,"n_cols":3,"columns":["Algorithmic Accuracy Digital Synthetic Data","",""],"rows":[["Algorithmic Accuracy Digital Synthetic Data","",""],["","",""],["Clinical Phantom","95% CI Upper Limit of Agreement\n0.9mm","95% CI Lower Limit of Agreement\n-0.9mm"],["Tube Width Phantom","1.3mm","-0.6mm"]],"caption_candidate":"phantoms, a dataset of digital synthetic data. The results of which are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p12-t0","doc_id":"K183133","page_num":12,"bbox":[79.9,171.96,533.09,230.76],"n_rows":4,"n_cols":3,"columns":["Algorithmic Accuracy Physical Phantoms","",""],"rows":[["Algorithmic Accuracy Physical Phantoms","",""],["","",""],["Clinical Phantom","95% CI Upper Limit of Agreement\n1.0 mm","95% CI Lower Limit of Agreement\n-1.1mm"],["Tube Width Phantom","0.7mm","-0.9mm"]],"caption_candidate":"are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p12-t1","doc_id":"K183133","page_num":12,"bbox":[73.42,338.57,539.02,427.86],"n_rows":5,"n_cols":10,"columns":["","Repeatability","","","","","","Reproducibility","",""],"rows":[["","Repeatability","","","","","","Reproducibility","",""],["Phantom Type","","U","p","per Limit of","Lower Limit\nAgreement (","of\nmm)","Up","Lower Limit of\nAgreement (mm)",""],["","","Agreement (mm)","","","","","","",""],["Clinical Phantom","0.4","","","","-0.4","","0.5","-1.1",""],["Tube Width Phantom","0.3","","","","-0.3","","0.7","-0.8",""]],"caption_candidate":"summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p12-t2","doc_id":"K183133","page_num":12,"bbox":[79.9,564.51,533.09,644.38],"n_rows":5,"n_cols":3,"columns":["Manufacturer Model","","Field Strength"],"rows":[["Manufacturer Model","","Field Strength"],["Siemens MAGNETOM Prisma 3T","",""],["Siemens MAGNETOM Avantofit 1.5T","",""],["GE Discovery MR750 3T","",""],["GE Optima MR450w 1.5T","",""]],"caption_candidate":"MRCP+v1 underwent in-vivo performance testing on the following MR Systems:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p13-t0","doc_id":"K183133","page_num":13,"bbox":[121.63,63.36,490.36,200.46],"n_rows":9,"n_cols":7,"columns":["","","Repeatability","","","",""],"rows":[["","","Repeatability","","","",""],["Measure","Measure","","","95% CI Upper Limit of\nAgreement","95% CI Lower Limit of",""],["","","","","","Agreement",""],["Tree Volume (ml)","","","3.4","","-3.5",""],["Gallbladder Volume (ml)","","","4.4","","-9.4",""],["3-5mm (%)","","","17.7","","-19.2",""],["5-7mm (%)","","","8.5","","-8.0",""],["Greater than 7mm (%)","","","1.6","","-1.8",""],["Less than 3mm (%)","","","20.2","","-19.2",""]],"caption_candidate":"RA317","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p13-t1","doc_id":"K183133","page_num":13,"bbox":[121.63,224.92,490.36,335.46],"n_rows":7,"n_cols":7,"columns":["","","Repeatability","","","",""],"rows":[["","","Repeatability","","","",""],["Measure","Measure","","","95% CI Upper Limit of\nAgreement","95% CI Lower Limit of",""],["","","","","","Agreement",""],["Duct Median (mm)","","","1.7","","-2.0",""],["Duct Minimum (mm)","","","1.9","","-2.2",""],["Duct Maximum (mm)","","","3.2","","-2.9",""],["Duct IQR (mm)","","","1.8","","-1.7",""]],"caption_candidate":"Less than 3mm (%) 20.2 -19.2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p13-t2","doc_id":"K183133","page_num":13,"bbox":[121.63,359.76,490.36,496.98],"n_rows":9,"n_cols":7,"columns":["","","Reproducibility","","","",""],"rows":[["","","Reproducibility","","","",""],["Measure","Measure","","","95% CI Upper Limit of\nAgreement","95% CI Lower Limit of",""],["","","","","","Agreement",""],["Tree Volume (ml)","","","4.7","","-6.9",""],["Gallbladder Volume (ml)","","","13.8","","-18.4",""],["3-5mm (%)","","","27.8","","-15.8",""],["5-7mm (%)","","","10.8","","-11.8",""],["Greater than 7mm (%)","","","2.6","","-3.1",""],["Less than 3mm (%)","","","30.8","","-23.4",""]],"caption_candidate":"Duct IQR (mm) 1.8 -1.7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p13-t3","doc_id":"K183133","page_num":13,"bbox":[121.63,521.28,490.36,631.86],"n_rows":7,"n_cols":7,"columns":["","","Reproducibility","","","",""],"rows":[["","","Reproducibility","","","",""],["Measure","Measure","","","95% CI Upper Limit of\nAgreement","95% CI Lower Limit of",""],["","","","","","Agreement",""],["Duct Median (mm)","","","2.6","","-2.8",""],["Duct Minimum (mm)","","","2.6","","-2.8",""],["Duct Maximum (mm)","","","4.0","","-3.5",""],["Duct IQR (mm)","","","1.9","","-2.3",""]],"caption_candidate":"Less than 3mm (%) 30.8 -23.4","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183133-p14-t0","doc_id":"K183133","page_num":14,"bbox":[52.63,63.39,559.54,253.86],"n_rows":13,"n_cols":12,"columns":["","Intra-Operator","","","","","","Inter-Operator","","","",""],"rows":[["","Intra-Operator","","","","","","Inter-Operator","","","",""],["Measure","","95% CI Upper Limit of","","","95% CI Lower Limit of","","","95% CI Upper Limit","","95% CI Lower Limit of\nAgreement",""],["","","Agreement","","","Agreement","","","of Agreement","","",""],["Tree Volume (ml)","0.9","","","-0.6","","","3.6","","","-6.8",""],["Gallbladder Volume","0.0","","","0.0","","","0.6","","","-0.7",""],["3-5mm (%)","7.4","","","-7.7","","","16.8","","","-11.1",""],["5-7mm (%)","5.0","","","-5.1","","","6.3","","","-6.3",""],["Greater than 7mm","3.9","","","-4.7","","","1.4","","","-1.7",""],["Less than 3mm (%)","11.7","","","-10.7","","","12.3","","","-17.4",""],["Duct Median (mm)","0.4","","","-0.4","","","1.1","","","-1.8",""],["Duct Minimum (mm)","0.5","","","-0.4","","","1.0","","","-1.3",""],["Duct Maximum (mm)","2.0","","","-1.6","","","2.0","","","-3.2",""],["Duct IQR (mm)","0.5","","","-0.4","","","1.6","","","-1.9",""]],"caption_candidate":"RA317","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183182-p4-t0","doc_id":"K183182","page_num":4,"bbox":[108.24,181.62,539.76,681.78],"n_rows":8,"n_cols":2,"columns":["Date:","August 7th, 2019"],"rows":[["Date:","August 7th, 2019"],["Submitter:","GE Medical Systems, LLC\n3000 N. Grandview Blvd\nWaukesha, WI 53188, USA"],["Primary Contact\nPerson:","Camille Vidal\nDirector of Regulatory Affairs Strategy\nGE Healthcare\n240‐280‐5356\nCamille.Vidal@ge.com"],["Secondary\nContact Person:","Diane Uriell\nRegulatory Affairs Director\nGE Healthcare\n262‐290‐8218\nDiane.Uriell@ge.com"],["Device Trade\nName:","Critical Care Suite"],["Common/Usual\nName:","Radiological Computer Assisted Triage and Notification Software"],["Classification\nNames:\nProduct Code:","Class II, Radiological Computer Assisted Triage and Notification Software,\n21 CFR 892.2080\nQFM"],["Predicate\nDevice(s):","HealthPNX by Zebra Medical Vision, K190362\nClass II, 21 CFR 892.2080, Product code: QFM"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183182-p5-t0","doc_id":"K183182","page_num":5,"bbox":[108.24,103.68,539.76,717.6],"n_rows":2,"n_cols":2,"columns":["Indications for use","Critical Care Suite is a computer aided triage and notification device that\nanalyzes frontal chest x‐ray images for the presence of prespecified\ncritical findings (pneumothorax). Critical Care Suite identifies images with\ncritical findings to enable case prioritization or triage in the\nPACS/workstation.\nCritical Care Suite is intended for notification only and does not provide\ndiagnostic information beyond the notification. Critical Care Suite should\nnot be used in‐lieu of full patient evaluation or solely relied upon to make\nor confirm a diagnosis. It is not intended to replace the review of the x‐\nray image by a qualified physician.\nCritical Care Suite is indicated for adult‐size patients."],"rows":[["Indications for use","Critical Care Suite is a computer aided triage and notification device that\nanalyzes frontal chest x‐ray images for the presence of prespecified\ncritical findings (pneumothorax). Critical Care Suite identifies images with\ncritical findings to enable case prioritization or triage in the\nPACS/workstation.\nCritical Care Suite is intended for notification only and does not provide\ndiagnostic information beyond the notification. Critical Care Suite should\nnot be used in‐lieu of full patient evaluation or solely relied upon to make\nor confirm a diagnosis. It is not intended to replace the review of the x‐\nray image by a qualified physician.\nCritical Care Suite is indicated for adult‐size patients."],["","Critical Care Suite is a software module that employs AI‐based image\nanalysis algorithms to identify pre‐specified critical findings\n(pneumothorax) in frontal chest X‐ray images and flag the images in the\nPACS/workstation to enable prioritized review by the radiologist.\nCritical Care Suite employs a sequence of vendor and system agnostic AI\nalgorithms to ensure that the input images are suitable for the\npneumothorax detection algorithm and to detect the presence of\npneumothorax in frontal chest X‐rays:\n‐ The Quality Care Suite algorithms conduct an automated check\nto confirm that the input image is compatible with the\npneumothorax detection algorithm and that the lung field\ncoverage is adequate;\n‐ the PTX Classifier determines whether a pneumothorax is\npresent in the image.\nIf a pneumothorax is detected, Critical Care Suite enables case\nprioritization or triage through direct communication of the Critical Care\nSuite notification during image transfer to the PACS. It can also produce\na Secondary Capture DICOM Image that presents the AI results to the\nradiologist.\nWhen deployed on a Digital Projection Radiographic Systems such as\nOptima XR240amx, Critical Care Suite is automatically run after image\nacquisition. Quality Care Suite algorithms produce an on‐device\nnotification if the lung field has atypical positioning to give the"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183182-p6-t0","doc_id":"K183182","page_num":6,"bbox":[108.6,355.77,539.43,712.02],"n_rows":6,"n_cols":3,"columns":["Predicate Device\nComparison","Critical Care Suite","HealthPNX (K190362)"],"rows":[["Predicate Device\nComparison","Critical Care Suite","HealthPNX (K190362)"],["Device classification","Radiological Computer Assisted Triage and\nNotification software,\nClass II, QFM","Radiological Computer Assisted Triage and\nNotification software,\nClass II, QFM"],["Targeted clinical\ncondition, anatomy\nand modality","Pneumothorax\nChest/Lung\nFrontal Chest X-ray","Pneumothorax\nChest/Lung\nChest X-ray"],["Input Validation","Quality Care Suitealgorithms conduct an\nautomated check to confirm image is\ncompatible with processing algorithm (age,\nfrontal chest, lung field)\nAtypical lung field positioning generates\nnotifications on the X-ray system and\nSecondary Capture DICOM Image when\ngenerated.","Validation feature of HealthPNX verifies that\ninput age, modality and view to ensure\ncompatibility with processing algorithm.\nIn case of failure during data validation, system\noutputs an error code."],["Algorithm for\nPneumothorax\ndetection","AI algorithm designed to detect pneumothorax\nin frontal chest X-ray images\nCritical Care Suite uses a vendor agnostic\nalgorithm compatible with DICOM frontal\nchest X-ray images acquired on fixed or mobile\nsystems.","AI algorithm designed to detect pneumothorax\nin chest X-ray images.\nHealthPNX employs a vendor agnostic\nalgorithm compatible with DICOM chest X-ray\nimages."],["Computational\nPlatform","Critical Care Suite is designed as a software\nmodule that can be deployed on several\ncomputing and X-ray imaging platforms such\nas Digital Projection Radiographic Systems,\nPACS, On Premise or On Cloud.","Cloud-based computation upon transfer to\nPACS of image"]],"caption_candidate":"radiographic imaging.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183182-p7-t0","doc_id":"K183182","page_num":7,"bbox":[108.66,103.8,539.38,619.98],"n_rows":6,"n_cols":3,"columns":["Predicate Device\nComparison","Critical Care Suite","HealthPNX (K190362)"],"rows":[["Predicate Device\nComparison","Critical Care Suite","HealthPNX (K190362)"],["","It processes images within seconds of image\nacquisition when deployed on Digital\nProjection Radiographic Systems.",""],["Device output in case\nof positive detection","Critical Care Suite enables case prioritization\nor triage through direct communication of the\nCritical Care Suite notification during image\ntransfer to the PACS.\nNo markup on original image\nUpon image acquisition on a Digital Projection\nRadiographic System, an on-device,\ntechnologist notification is generated 15\nminutes after exam closure, indicating which\ncases were prioritized by Critical Care Suite in\nPACS. The technologist notification is\ncontextual and does not provide any\ndiagnostic information. The on-device,\ntechnologist notification is not intended to\ninform any clinical decision, prioritization, or\naction.","Integration module notifies the\nPACS/workstation for prioritization through\nthe worklist interface.\nNo markup on original image"],["Notification:\nRecipient, timing and\nmeans of notification","Passive notification to radiologist. Images with\nsuspicion of pneumothorax are flagged in\nPACS/workstation.","Passive notification to radiologist. Images with\nsuspicion of pneumothorax are flagged in\nPACS/workstation."],["Performance level –\ntiming of notification","Exams arriveon PACS with the passive\nnotification already incorporated, therefore\nthere is no delay for image transfer or\ncomputation. The worklist prioritization\nhappens immediately once the exam is\nreceived on the PACS.","Passive notification is visible upon transfer to\nthe PACS with a delay of about 22 seconds for\nimage transfer to the cloud, computation and\nresults transfer."],["Performance level –\naccuracy of\nclassification","ROC AUC > 0.95\nAUC: 0.9607 (95% CI [0.9491, 0.9724])\nSpecificity 93.5% (95% CI [91.1%, 95.8%])\nSensitivity 84.3% (95% CI [80.6%, 88.0%])\nAUC on large pneumothorax 0.9888 (95% CI\n[0.9810, 0.9965])\nSensitivity on large pneumothorax 96.3% (95%\nCI [93.3%, 99.2%]\nAUC on small pneumothorax 0.9389 (95% CI\n[0.9209, 0.9570])\nSensitivity on small pneumothorax 75% (95%\nCI [69.2%, 80.8%])","ROC AUC > 0.95\nAUC: 0.983 (95% CI [0.9740, 0.9902]),\nSpecificity: 93%\nSensitivity: 93%\nStratified results on small vs. large\npneumothorax not assessed."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183182-p9-t0","doc_id":"K183182","page_num":9,"bbox":[108.66,103.68,539.4,705.42],"n_rows":2,"n_cols":2,"columns":["","The timing of the processing and prioritization is well within the clinical\noperational expectations of standard chest radiographic exam and its\nreading by radiologists.\nAccording to Gaskin, Cree M., et al. \"Impact of a Reading Priority Scoring\nSystem on the Prioritization of Examination Interpretations.\" American\nJournal of Roentgenology 206.5 (2016): 1031‐1039 and Rachh, Pratik, et\nal. \"Reducing STAT Portable Chest Radiograph Turnaround Times: A Pilot\nStudy.\" Current problems in diagnostic radiology (2017), the estimated\naverage Report Turnaround Time for non‐prioritized or ineffectively\nprioritized exams is between 7.23 hours and 8.67 hours.\nIncorporating the Critical Care Suite passive notification to help\nradiologists prioritize their exam reads would drastically reduce this\nturnaround time for the cases that have been flagged by Critical Care\nSuite as compared to standard of care (First‐In, First‐Out).\nSummary of Clinical Evaluation:\nCritical Care Suite was evaluated on a dataset of 804 frontal chest X‐rays\ncollected in North America and representative of the intended\npopulation. The algorithm prediction is compared to the ground truth\nestablished by 3 independent US‐board certified radiologists. The\nalgorithm ROC AUC meets the performance requirement of FDA product\ncode QFM (AUC>95%): AUC=96% (95% CI [94.9% ‐ 97.2%]) (PTX present:\nN=376; PTX absent: N=428). Stratified analyses showed consistent\nperformance across image view (AP/PA), system manufacturer (GE/non‐\nGE) and data sources.\nCritical Care Suite performs at high specificity 93.5% (95% CI [91.1% ‐\n95.8%]) and high sensitivity 84.3% (95% CI [80.6% – 88.0%]). Stratified\nanalysis by pneumothorax size shows that nearly all large\npneumothoraces are detected (96.3% with 95% CI [93.3% ‐ 99.2%])\nwhile 3 out 4 small pneumothoraces are detected (75% with 95% CI\n[69.2% ‐ 80.8%]) with limited false notifications thanks to the high\nspecificity."],"rows":[["","The timing of the processing and prioritization is well within the clinical\noperational expectations of standard chest radiographic exam and its\nreading by radiologists.\nAccording to Gaskin, Cree M., et al. \"Impact of a Reading Priority Scoring\nSystem on the Prioritization of Examination Interpretations.\" American\nJournal of Roentgenology 206.5 (2016): 1031‐1039 and Rachh, Pratik, et\nal. \"Reducing STAT Portable Chest Radiograph Turnaround Times: A Pilot\nStudy.\" Current problems in diagnostic radiology (2017), the estimated\naverage Report Turnaround Time for non‐prioritized or ineffectively\nprioritized exams is between 7.23 hours and 8.67 hours.\nIncorporating the Critical Care Suite passive notification to help\nradiologists prioritize their exam reads would drastically reduce this\nturnaround time for the cases that have been flagged by Critical Care\nSuite as compared to standard of care (First‐In, First‐Out).\nSummary of Clinical Evaluation:\nCritical Care Suite was evaluated on a dataset of 804 frontal chest X‐rays\ncollected in North America and representative of the intended\npopulation. The algorithm prediction is compared to the ground truth\nestablished by 3 independent US‐board certified radiologists. The\nalgorithm ROC AUC meets the performance requirement of FDA product\ncode QFM (AUC>95%): AUC=96% (95% CI [94.9% ‐ 97.2%]) (PTX present:\nN=376; PTX absent: N=428). Stratified analyses showed consistent\nperformance across image view (AP/PA), system manufacturer (GE/non‐\nGE) and data sources.\nCritical Care Suite performs at high specificity 93.5% (95% CI [91.1% ‐\n95.8%]) and high sensitivity 84.3% (95% CI [80.6% – 88.0%]). Stratified\nanalysis by pneumothorax size shows that nearly all large\npneumothoraces are detected (96.3% with 95% CI [93.3% ‐ 99.2%])\nwhile 3 out 4 small pneumothoraces are detected (75% with 95% CI\n[69.2% ‐ 80.8%]) with limited false notifications thanks to the high\nspecificity."],["Substantial\nEquivalence\nDiscussion:","Critical Care Suite and HealthPNX are software devices intended to aid in\ntriage and prioritization of radiological images. Both devices use artificial\nintelligence algorithms to identify suspicious findings suggestive of\npneumothorax in chest X‐ray images. Both devices are intended to"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183202-p6-t0","doc_id":"K183202","page_num":6,"bbox":[108.28,160.58,558.08,479.59],"n_rows":6,"n_cols":7,"columns":["Specification/\nAttribute","","ASiR-V","","","Deep Learning Image Reconstruction",""],"rows":[["Specification/\nAttribute","","ASiR-V","","","Deep Learning Image Reconstruction",""],["","","(Predicate Device, K133640)","","","(Proposed Device)",""],["Technology","Extensive system statistical\nmodel","","","Utilizes a dedicated Deep Neural\nNetwork (DNN) which is trained on the\nCT Scanner and designed specifically to\ngenerate high quality CT images","",""],["System statistics -\nNoise modeling of\nthe data collection\nimaging chain\n(photon noise and\nelectronic noise)","Characterization of the photon\nstatistics as it propagates\nthrough the preprocessing and\ncalibration imaging chain","","","Same","",""],["System statistics –\nNoise characteristics\nof the reconstructed\nimages","The characterization of the\nscanned object using\ninformation obtained from\nextensive phantom and clinical\ndata","","","Utilizes a trained Deep Neural Network\n(DNN) which models the scanned\nobject using information obtained from\nextensive phantom and clinical data","",""],["Clinical Workflow","Select recon type and strength\n(percentage)","","","Select recon type and strength (High,\nMedium, Low)","",""]],"caption_candidate":"between the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183204-p7-t0","doc_id":"K183204","page_num":7,"bbox":[208.14,128.88,576.18,472.92],"n_rows":5,"n_cols":3,"columns":["Specification","Syngo CT Bone Reading\n(K123584)","Proposed Device:\nBone VCAR"],"rows":[["Specification","Syngo CT Bone Reading\n(K123584)","Proposed Device:\nBone VCAR"],["Spine Labeling\nTool","Automated labeling with\nmanual editing capability","Automated labeling with\nmanual editing capability"],["Display of\ncurved spine\nstructures","Yes","Yes"],["Measurement\nTool","geometric measurement\ntools (distance line,\npolyline, marker, arrow,\nangle), HU measurement\ntools (Pixel lens, ROI\ncircle, ROI polygonal, ROI\nfreehand, VOl sphere)","Access to all standard\nVolume Viewer tools for\nmeasuring distances, areas,\nHounsfield unit values and\nannotating within the images"],["Image Display\nformats","Multiplanar reconstruction\n(MPR) thin/thick,\nmaximum intensity\nprojection (MIP) thin/thick,\ninverted MIP thin/thick,\nvolume rendering technique\n(VRT)","Multiplanar Reconstruction\n(MPR) displays of axial,\nsagittal, coronal, oblique, x-\nsection and curved views\nwhich can be displayed in\nthin/thick, Average,\nMaximum Intensity\nProjection (MIP), Minimum\nintensity Projection (MinIP),\nVolume Rendering (VR)\nmodes."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183231-p4-t0","doc_id":"K183231","page_num":4,"bbox":[86.28,201.6,523.68,765.96],"n_rows":10,"n_cols":2,"columns":["Date:","November 1(cid:28), 2018"],"rows":[["Date:","November 1(cid:28), 2018"],["Submitter:","GE Medical Systems, LLC (GE Healthcare)\n3200 N. Grandview Blvd.,\nWaukesha, WI 53188\nUSA"],["Primary Contact Person:","Brian R. Zielski\nRegulatory Affairs Leader\nGE Healthcare\nPhone: 262-521-6609"],["Secondary Contact Person:","James McMahon\nSenior Director, Regulatory Affairs\nGE Healthcare\nPhone: 508-382-2858"],["Device Trade Name:","SIGNA Premier"],["Common/Usual Name:","Magnetic Resonance Diagnostic Device"],["Classification Names:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH, LNI, MOS"],["Predicate Device(s):","SIGNA Premier (K171128)"],["Device Description:","SIGNA Premier is a whole body magnetic resonance\nscanner designed to support high resolution, high signal-\nto-noise ratio, and short scan times, and is designed for\nimproved patient comfort and workflow. The system\nfeatures a 3.0T superconducting magnet with a 70cm bore\nsize and can image in the sagittal, coronal, axial, oblique,\nand double oblique planes, using various pulse sequences,\nimaging techniques and reconstruction algorithms. The\nsystem is designed to conform to NEMA DICOM"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183231-p5-t0","doc_id":"K183231","page_num":5,"bbox":[86.28,132.12,523.68,765.96],"n_rows":4,"n_cols":2,"columns":["","standards (Digital Imaging and Communications in\nMedicine).\nThe modifications to this system include the AIRx\nsoftware features, which allows users the flexibility to\nautomate and standardize a number of connected steps\nrequired for an MRI examination of the brain."],"rows":[["","standards (Digital Imaging and Communications in\nMedicine).\nThe modifications to this system include the AIRx\nsoftware features, which allows users the flexibility to\nautomate and standardize a number of connected steps\nrequired for an MRI examination of the brain."],["Indications for Use","The SIGNA Premier system is a whole body magnetic\nresonance scanner designed to support high resolution,\nhigh signal-to-noise ratio, and short scan times. It is\nindicated for use as a diagnostic imaging device to\nproduce axial, sagittal, coronal, and oblique images,\nspectroscopic images, parametric maps, and/or spectra,\ndynamic images of the structures and/or functions of the\nentire body, including, but not limited to, head, neck,\nTMJ, spine, breast, heart, abdomen, pelvis, joints,\nprostate, blood vessels, and musculoskeletal regions of the\nbody. Depending on the region of interest being imaged,\ncontrast agents may be used.\nThe images produced by the SIGNA Premier system\nreflect the spatial distribution or molecular environment of\nnuclei exhibiting magnetic resonance. These images\nand/or spectra when interpreted by a trained physician\nyield information that may assist in diagnosis."],["Comparison of Indications\nfor Use","The indications for use statement and intended use are\nidentical to the predicate device, in accordance with the\nFDA’s guidance document “The 510(k) Program:\nEvaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],["Technology:","The SIGNA Premier with the proposed software feature\nemploy the same fundamental technology as the predicate\ndevice.\nThe SIGNA Premier has been modified to include the\nAIRx feature, which automates and standardizes a number\nof connected steps required for an MRI examination of the\nbrain. AIRx was developed using deep learning\nalgorithms."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183231-p6-t0","doc_id":"K183231","page_num":6,"bbox":[86.28,132.12,523.68,772.92],"n_rows":2,"n_cols":2,"columns":["","These technological differences do not raise any different\nquestions regarding safety and effectiveness. Both devices\nmust allow for an effective method to setup an appropriate\nscan prescription. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the performance of the SIGNA\nPremier compared to the predicate device."],"rows":[["","These technological differences do not raise any different\nquestions regarding safety and effectiveness. Both devices\nmust allow for an effective method to setup an appropriate\nscan prescription. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the performance of the SIGNA\nPremier compared to the predicate device."],["Determination of\nSubstantial Equivalence:","Summary of Non-Clinical Tests:\nThe modifications to SIGNA Premier include the AIRx\nsoftware only feature and complies with the following\nvoluntary standards:\n(cid:120) IEC 62304\n(cid:120) ANSI/AAMI 60601-1\n(cid:120) IEC 60601-2-33\nThe following quality assurance measures were applied to\nthe development of the subject device, as they were for\nthe predicate device:\n(cid:120) Risk Analysis\n(cid:120) Requirements Reviews\n(cid:120) Design Reviews\n(cid:120) Integration testing (System verification)\n(cid:120) Performance testing (Verification)\n(cid:120) Simulated use testing (Validation)\nThe non-clinical tests have been summarized in the\nverification and validation testing for AIRx. The testing\nwas completed with passing results per pass/fail criteria\ndefined in the test cases. This supports substantial\nequivalence to its predicate because it was also developed\nunder quality assurance Design Controls. In addition, the\nsoftware complies with the same applicable Standards.\nSummary of Clinical Tests:\nInternal scans were conducted as part of validation for\nAIRx workflow to confirm the productivity and\nconsistency benefits of the proposed feature. The AIRx\nfeature is a pre-scan algorithm, and the MR System"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183231-p7-t0","doc_id":"K183231","page_num":7,"bbox":[86.28,132.12,523.68,374.4],"n_rows":2,"n_cols":2,"columns":["","maintains the same imaging performance results as its\npredicate device (K171128)."],"rows":[["","maintains the same imaging performance results as its\npredicate device (K171128)."],["Conclusion:","The SIGNA Premier with the modified software feature\nhas the same intended use as the predicate. This 510(k)\nsubmission includes information on the technological\ncharacteristics of the proposed software feature, as well as\nperformance data demonstrating that the feature is as safe\nand effective as the predicate, and does not raise different\nquestions of safety and effectiveness.\nIn conclusion, GE Healthcare considers the SIGNA\nPremier to be as safe, as effective, and performance is\nsubstantially equivalent to the predicate devices."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183268-p6-t0","doc_id":"K183268","page_num":6,"bbox":[105.15,295.17,530.03,729.36],"n_rows":18,"n_cols":6,"columns":["Subject Device","","","Predicate Device","","Comparison Results"],"rows":[["Subject Device","","","Predicate Device","","Comparison Results"],["","Siemens","","Siemens\nsyngo.CT Cardiac Function\n(K123585)","",""],["","AI-Rad Companion","","","",""],["","(Cardiovascular)","","","",""],["AI-based Heart Segmentation","","","Model-based Heart Isolation","","Modified\nsubject device: deep learning-based algorithm\npredicate device:model-based segmentation\nalgorithm"],["Color overlay of MPR and\nVRT with evaluation results","","","Basic Reading Functionality","","Same"],["","Siemens","","Siemens\nsyngo CaScoring(K990426)","","Comparison Results"],["","AI-Rad Companion","","","",""],["","(Cardiovascular)","","","",""],["Calcium Detection","","","Automatic detection of coronary\nvessels and coronary calcium","","Modified\nsubject device: deep learning-based algorithm\npredicate device:model-based segmentation\nalgorithm"],["","Siemens","","Siemens\nValveGuide(K113027)","","Comparison Results"],["","AI-Rad Companion","","","",""],["","(Cardiovascular)","","","",""],["Aorta Segmentation","","","Aortic root segmentation","","Modified\nsubject device: deep learning-based algorithm\npredicate device:model-based segmentation\nalgorithm"],["Landmark Detection","","","Landmark detection","","Modified\nsubject device: deep learning-based\nalgorithm, 9 AHA positions\npredicate device:model-based segmentation\nalgorithm, aortic root plane"],["Aorta diameter measurements","","","Aorta diameter measurements","","Same"],["Aorta categories","","","N/A","","New\nmeasurements are compared with results from\na standard population, deviations are\nsignalized to the user"],["Color overlay of MPR and\nVRTwith evaluation results","","","Basic Reading Functionality","","Same"]],"caption_candidate":"Table 1: Predicate Device Comparable Properties","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183268-p7-t0","doc_id":"K183268","page_num":7,"bbox":[105.15,260.06,530.03,384.0],"n_rows":6,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1–3.20","06/27/2016","NEMA","",""],["13-32","Software","Medical Device Software –Software Life\nCycle Processes; 62304:2006 (1stEdition)","08/20/2012","AAMI, ANSI, IEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971\nSecond Edition 2007-03-01","08/20/2012","ISO","",""]],"caption_candidate":"Table 2: Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183271-p6-t0","doc_id":"K183271","page_num":6,"bbox":[107.98,387.58,528.74,686.58],"n_rows":5,"n_cols":12,"columns":["","Feature","","","Subject Device","","","Predicate Device","","","Comparison Results",""],"rows":[["","Feature","","","Subject Device","","","Predicate Device","","","Comparison Results",""],["","","","Siemens\nAI-Rad Companion\n(Pulmonary)","","","Siemens\nsyngo.CT Pulmo 3D\n(K123540, clearance\ndate 8/29/2013)","","","","",""],["Segmentation of\nlungs","","","Segmentation of lungs","","","Segmentation of left /\nright lung","","","Modified\nsubject device: segmentation of\ncomplete lungs\npredicate device: dedicated\nalgorithm for segmentation of\nboth lungs","",""],["Segmentation of\nlung lobes","","","Segmentation of lung\nlobes","","","Segmentation of lung\nthirds, lung core/peel,\nlung lobes","","","Modified\nsubject device: deep learning-\nbased algorithm for long lobes\nsegmentation\npredicate device: Model-based\nsegmentation algorithm","",""],["Parenchyma\nEvaluation","","","Calculation and\nvisualization of lung\ntissue below -950 HU","","","Calculation and\nvisualization of lung\ntissue below threshold","","","Modified\nSubject device: fixed threshold\nfor segmentation\nPredicate device: Configurable\nthreshold for segmentation","",""]],"caption_candidate":"Table 1: Predicate Device Comparable Properties","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183271-p7-t0","doc_id":"K183271","page_num":7,"bbox":[108.0,85.78,528.74,428.16],"n_rows":11,"n_cols":12,"columns":["","Feature","","","Subject Device","","","Predicate Device","","","Comparison Results",""],"rows":[["","Feature","","","Subject Device","","","Predicate Device","","","Comparison Results",""],["","","","Siemens\nAI-Rad Companion\n(Pulmonary)","","","Siemens\nsyngo.CT Pulmo 3D\n(K123540, clearance\ndate 8/29/2013)","","","","",""],["Visualization of\nsegmentation and\nparenchyma\nresults","","","Color overlay of MPR\nand VRT with evaluation\nresults","","","Color overlay of MPR\nand VRT with evaluation\nresults","","","Same","",""],["Feature","","","Siemens\nAI-Rad Companion\n(Pulmonary)","","","","Siemens","","Comparison Results","",""],["","","","","","","","syngo.PET&CT","","","",""],["","","","","","","","Oncology (K093621,","","","",""],["","","","","","","","clearance date","","","",""],["","","","","","","","02/23/2010)","","","",""],["Interface to\nLungCAD","","","Interface to syngo.CT\nLungCAD (K143196) is\nsupported","","","Interface to syngo.CT\nLungCAD (K143196) is\nsupported","","","Same","",""],["Lesion\nSegmentation","","","Segmentation of lung\nlesions","","","Segmentation of lesions\nof the lung, liver, and\nlymph nodes","","","Modified\nsubject device: segmentation of\nlung lesions and localization of\nfound lesion to lung lobe\npredicate device: segmentation\nof lesions of lung, liver, lymph\nnodes, and general anatomies","",""],["Visualization of\nlesion\nsegmentation\nresults","","","Color overlay of MPR\nand VRT with evaluation\nresults","","","Color overlay of MPR\nand VRT with evaluation\nresults","","","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183271-p8-t0","doc_id":"K183271","page_num":8,"bbox":[107.96,96.7,526.18,261.12],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-32","Software","Medical Device Software –Software Life\nCycle Processes; 62304:2006 (1st Edition)","08/20/2012","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971\nSecond Edition 2007-03-01","08/20/2012","ISO","",""],["5-95","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","06/27/2016","IEC","",""]],"caption_candidate":"Table 2: Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183272-p6-t0","doc_id":"K183272","page_num":6,"bbox":[108.01,132.11,530.99,611.4],"n_rows":10,"n_cols":6,"columns":["Feature","Subject Device","","Predicate Device","","Comparison Results"],"rows":[["Feature","Subject Device","","Predicate Device","","Comparison Results"],["","","","(K170952)","",""],["Software","Software version\nVA10A","SOMARIS/8 VB20A","","","Equivalent. The subject device\nsupports a new version of software\nthat is deployable on the Siemens\ncloud infrastructure"],["Extensibility","Extendable via\nadditional post-\nprocessing\nextensions","Extendable via\nadditional post-\nprocessing tools","","","Equivalent. The subject device\nhas been modified to support\nextensions that can perform\nautomated post-processing using\nartificial intelligence algorithms"],["Visualization","Standard\nvisualization tools\n(window levels,\nMPR, MIP, VRT)","Standard\nvisualization tools\n(window levels,\nMPR, MIP, VRT)","","","Same"],["Image\nDistribution and\nArchiving","In the Distribution\nstep it is shown to\nwhich DICOM nodes\na series will be sent\nwhen saving the\ncase, or to which\nnode a series has\nalready been sent.\nThe user can select\n(or deselect)\nwhether a series will\nbe sent to any\nDICOM node or to a\nsubset of nodes.","Sending of DICOM\ndata to DICOM\nnodes possible in\nthe export\nfunctionality","","","Equivalent. The subject device\nhas been modified to support\ntransfer to a preconfigured DICOM\nnode"],["User Interface\nConfirmation","Confirmation UI","syngo.via GUI","","","Equivalent. The subject device\nhas been modified to provide only\nbasic functionality for confirmation\nof processed results"],["User Interface\nConfiguration","Configuration UI","syngo.via GUI -\nconfiguration","","","Equivalent. The subject device\nhas been modified to expose\nconfiguration options of existent\nextensions"],["Archiving/Storing","CD-R, film, DVD,\nUSB, Network","CD-R, film, DVD,\nUSB, Network","","","Equivalent. The subject device\nhas been modified to only store\nmeta data"],["Communication","DICOM compatible","DICOM compatible","","","Same"]],"caption_candidate":"Table 1: Predicate Device Comparable Properties","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183272-p7-t0","doc_id":"K183272","page_num":7,"bbox":[108.02,120.57,535.54,333.0],"n_rows":8,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-32","Software","Medical Device Software –Software Life\nCycle Processes; 62304:2006 (1st\nEdition)","08/20/2012","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971\nSecond Edition 2007-03-01","08/20/2012","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","06/27/2016","IEC","",""],["","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\n[Including CORRIGENDUM 1 (2016)]","2/3/2016","IEC","",""]],"caption_candidate":"Table 2: Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p5-t0","doc_id":"K183274","page_num":5,"bbox":[72.3,120.25,540.3,190.88],"n_rows":2,"n_cols":4,"columns":["510(k) #","Device","510(k) Sponsor","510(k) Clearance\nDate"],"rows":[["510(k) #","Device","510(k) Sponsor","510(k) Clearance\nDate"],["K170090","RTHawk (ver 2.3.2)\nHeartVIsta Cardiac Package","HeartVista","07/14/2017"]],"caption_candidate":"6.0 Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p7-t0","doc_id":"K183274","page_num":7,"bbox":[72.35,342.25,520.85,499.88],"n_rows":6,"n_cols":2,"columns":["Safety Parameter","Safety Level"],"rows":[["Safety Parameter","Safety Level"],["Magnetic Field strength","1.5T, 3.0T"],["Operating Modes IEC 60601-2-33 (2010-03)","FIRST LEVEL CONTROLLED\nOPERATING MODE"],["Safety Parameter Display","SAR, dB/dt"],["Max SAR","< 4W/kg whole-body"],["Max dB/dt","FIRST LEVEL CONTROLLED\nOPERATING MODE"]],"caption_candidate":"RTHawk operates compatible MR scanners within the safety parameters listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p8-t0","doc_id":"K183274","page_num":8,"bbox":[72.35,435.25,540.35,695.62],"n_rows":7,"n_cols":2,"columns":["Reference #","Title"],"rows":[["Reference #","Title"],["IEC 60601-2-33 Ed 3.0\n(2010-03)","Medical electrical equipment - Part 2-33: Particular\nrequirements for the basic safety and essential performance of\nmagnetic resonance equipment for medical diagnostic\n(radiology)."],["MS1-2008","Determination of Signal-to-Noise Ratio (SNR) in Diagnostic\nMagnetic Resonance Imaging"],["MS3-2008","Determination of Image Uniformity in Diagnostic Magnetic\nResonance Images"],["MS4-2010","Acoustic Noise Measurement Procedure for Diagnostic\nMagnetic Resonance Imaging Devices"],["MS8-2008","Characterization of the Specific Absorption Rate (SAR) for\nMagnetic Resonance Imaging Systems"],["NEMA PS3.1 - 3.20 (2011)","Digital Imaging And Communications In Medicine (DICOM)\nSet."]],"caption_candidate":"the table below, as applicable to device features and components:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p9-t0","doc_id":"K183274","page_num":9,"bbox":[72.38,72.3,540.38,169.88],"n_rows":2,"n_cols":2,"columns":["ISO 14971:2007","Medical Devices - Application Of Risk Management To\nMedical Devices"],"rows":[["ISO 14971:2007","Medical Devices - Application Of Risk Management To\nMedical Devices"],["ES60601-1:2005/(R)2012\n+A1 +C1 +A2","(Consolidated Text) Medical Electrical Equipment - Part 1:\nGeneral Requirements For Basic Safety And Essential\nPerformance (IEC 60601-1:2005, Mod). Section 14\nProgrammable Electrical Medical Systems (PEMS)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p11-t0","doc_id":"K183274","page_num":11,"bbox":[72.3,192.25,541.05,714.38],"n_rows":2,"n_cols":3,"columns":["Attribute","Predicate Device\nK170090\nRTHawk (ver 2.3.2)\nHeartVista Cardiac Package","Modified Device\nK183274\nRTHawk (ver 2.5.1)\nHeartVista Cardiac Package"],"rows":[["Attribute","Predicate Device\nK170090\nRTHawk (ver 2.3.2)\nHeartVista Cardiac Package","Modified Device\nK183274\nRTHawk (ver 2.5.1)\nHeartVista Cardiac Package"],["Indications for Use","RTHawk is an accessory to 1.5T\nand 3.0T whole-body magnetic\nresonance diagnostic devices\n(MRDD or MR). It is intended to\noperate alongside, and in parallel\nwith, the existing MR console to\nacquire traditional, real-time, and\naccelerated images. The\nHeartVista Cardiac Package is a\ncollection of RTHawk Apps\ndesigned to acquire, reconstruct\nand display cardiovascular MR\n(CMR) images.\nRTHawk produces static and\ndynamic transverse, coronal,\nsagittal, and oblique\ncross-sectional images that display\nthe internal structures and/or\nfunctions of the entire body. The\nimages produced reflect the spatial\ndistribution of nuclei exhibiting\nmagnetic resonance. The magnetic\nresonance properties that\ndetermine image appearance are\nproton density, spin-lattice\nrelaxation time (T1), spin-spin\nrelaxation time (T2) and flow. When\ninterpreted by a trained physician,\nthese images provide information","RTHawk is an accessory to 1.5T\nand 3.0T whole-body magnetic\nresonance diagnostic devices\n(MRDD or MR). It is intended to\noperate alongside, and in parallel\nwith, the existing MR console to\nacquire traditional, real-time, and\naccelerated images. The\nHeartVista Cardiac Package is a\ncollection of RTHawk Apps\ndesigned to acquire, reconstruct\nand display cardiovascular MR\n(CMR) images.\nRTHawk produces static and\ndynamic transverse, coronal,\nsagittal, and oblique\ncross-sectional images that display\nthe internal structures and/or\nfunctions of the entire body. The\nimages produced reflect the spatial\ndistribution of nuclei exhibiting\nmagnetic resonance. The magnetic\nresonance properties that\ndetermine image appearance are\nproton density, spin-lattice\nrelaxation time (T1), spin-spin\nrelaxation time (T2) and flow. When\ninterpreted by a trained physician,\nthese images provide information"]],"caption_candidate":"predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183274-p12-t0","doc_id":"K183274","page_num":12,"bbox":[72.38,72.32,541.12,614.62],"n_rows":13,"n_cols":3,"columns":["","that may assist in the determination\nof a diagnosis.\nRTHawk is intended for use as an\naccessory to the following MRI\nsystems:\nManufacturer: GE Healthcare\n(GEHC)\nField Strength: 1.5T and 3.0T\nScanner Software Versions: 12, 15,\n16, 23, 24, 25","that may assist in the determination\nof a diagnosis.\nRTHawk is intended for use as an\naccessory to the following MRI\nsystems:\nManufacturer: GE Healthcare\n(GEHC)\nField Strength: 1.5T and 3.0T\nScanner Software Versions: 12, 15,\n16, 23, 24, 25, 26"],"rows":[["","that may assist in the determination\nof a diagnosis.\nRTHawk is intended for use as an\naccessory to the following MRI\nsystems:\nManufacturer: GE Healthcare\n(GEHC)\nField Strength: 1.5T and 3.0T\nScanner Software Versions: 12, 15,\n16, 23, 24, 25","that may assist in the determination\nof a diagnosis.\nRTHawk is intended for use as an\naccessory to the following MRI\nsystems:\nManufacturer: GE Healthcare\n(GEHC)\nField Strength: 1.5T and 3.0T\nScanner Software Versions: 12, 15,\n16, 23, 24, 25, 26"],["Magnetic Field\nStrength(s)","1.5T, 3.0T","1.5T, 3.0T"],["Imaging Planes","Transverse, Coronal, Sagittal,\nOblique, Double Oblique","Transverse, Coronal, Sagittal,\nOblique, Double Oblique"],["Time Course\nImaging","Yes","Yes"],["Parameter Mapping","T1, T2*","T1, T2, T2*"],["Ventricular Function","Free-Breathing and Breath-Held","Free-Breathing and Breath-Held"],["MDE","Free-Breathing and Breath-Held","Free-Breathing and Breath-Held"],["Gated MRA","Yes","Yes"],["Black Blood\nImaging","Yes","Yes"],["SPAMM Tagging","No","Yes"],["Flow Imaging","Real-Time","Real-Time, Multi-Slice, and 4D"],["Remote Scanning\nand Support","Yes","Yes"],["Automated Scan\nPlanning","No","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183285-p5-t0","doc_id":"K183285","page_num":5,"bbox":[36.02,503.14,567.0,642.82],"n_rows":7,"n_cols":4,"columns":["Characteristic","Predicate: Viz.AI ContaCT","cmTriage","Similarities or\nDifferences"],"rows":[["Characteristic","Predicate: Viz.AI ContaCT","cmTriage","Similarities or\nDifferences"],["FDA Clearance","DEN170073","TBD",""],["Clearance Date","2/13/18","TBD",""],["Product Code","QAS","QFR",""],["Class","II","II","Same"],["Regulation","892.2080","892.2080","Same"],["OTC vs. PUO","PUO","PUO","Same"]],"caption_candidate":"Summary of Comparison to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183285-p6-t0","doc_id":"K183285","page_num":6,"bbox":[36.04,50.02,567.0,683.86],"n_rows":9,"n_cols":4,"columns":["Intended Use.\nIndications for\nUse","ContaCT is a notification-only, parallel workflow\ntool for use by hospital networks and radiologists\nto identify and communicate images of specific\npatients to a radiologist, independent of standard\nof care workflow.\nContaCT uses an artificial intelligence algorithm to\nanalyze images for findings suggestive of a pre-\nspecified clinical condition and to notify an\nappropriate medical radiologist of these findings\nin parallel to standard of care image\ninterpretation. Identification of suspected findings\nis not for diagnostic use beyond notification.\nSpecifically, the device analyzes CT angiogram\nimages of the brain acquired in the acute setting,\nand sends notifications to neurovascular\nradiologist that a suspected large vessel occlusion\nhas been identified and recommends review of\nthose images. Images can be previewed through a\nmobile application.\nImages that are previewed through the mobile\napplication are compressed and are for\ninformational purposes only and not intended for\ndiagnostic use beyond notification. Notified\nradiologists are responsible for viewing non-\ncompressed images on a diagnostic viewer and\nengaging in appropriate patient evaluation and\nrelevant discussion with a treating physician\nbefore making care-related decisions or requests.\nContaCT is limited to analysis of imaging data and\nshould not be used in-lieu of full patient evaluation\nor relied upon to make or confirm diagnosis.","cmTriage is a passive notification for\nprioritization-only, parallel-workflow software\ntool used by radiologists to prioritize specific\npatients within the standard-of-care image\nworklist for 2D FFDM screening mammograms.\ncmTriage uses an artificial intelligence algorithm\nto analyze 2D FFDM screening mammograms and\nflags those that are suggestive of the presence of at\nleast one suspicious finding at the exam level.\nThese flags are viewed by the radiologist via their\nPicture Archiving and Communication System\n(PACS) worklist. The decision to use cmTriage\ncodes and how to use cmTriage codes is ultimately\nup to the radiologist. cmTriage does not send a\nproactive alert directly to the radiologist.\nRadiologists are responsible for reviewing each\nexam on a diagnostic viewer according to the\ncurrent standard of care.\ncmTriage is limited to the categorization of exams,\ndoes not provide any diagnostic information\nbeyond triage and prioritization, does not remove\nimages from the radiologist’s worklist, and should\nnot be used in lieu of full patient evaluation, or\nrelied upon to make or confirm diagnosis.\nc mTriage is for prescription use only.","Similarities\n• Used by radiologists\n• Identifies specific\npatients\n• Operates in parallel\nto standard of care\nworkflow\n• Uses artificial\nintelligence to\nanalyze images\n• Looking for findings\nsuggestive of a pre-\nspecified clinical\ncondition\n• Not intended for\ndiagnostic use\n• Radiologists are\nresponsible for\nviewing images on a\ndiagnostic viewer\n• Limited to analysis\nof imaging data and\nshould not be used\nin-lieu of full patient\nevaluation or relied\nupon to make or\nconfirm diagnosis\nNoted difference:\ncmTriage notification\nis passive vs. proactive\nand cmTriage codes\nare accessed by\nradiologist through\nPACS worklist and\nused for prioritization."],"rows":[["Intended Use.\nIndications for\nUse","ContaCT is a notification-only, parallel workflow\ntool for use by hospital networks and radiologists\nto identify and communicate images of specific\npatients to a radiologist, independent of standard\nof care workflow.\nContaCT uses an artificial intelligence algorithm to\nanalyze images for findings suggestive of a pre-\nspecified clinical condition and to notify an\nappropriate medical radiologist of these findings\nin parallel to standard of care image\ninterpretation. Identification of suspected findings\nis not for diagnostic use beyond notification.\nSpecifically, the device analyzes CT angiogram\nimages of the brain acquired in the acute setting,\nand sends notifications to neurovascular\nradiologist that a suspected large vessel occlusion\nhas been identified and recommends review of\nthose images. Images can be previewed through a\nmobile application.\nImages that are previewed through the mobile\napplication are compressed and are for\ninformational purposes only and not intended for\ndiagnostic use beyond notification. Notified\nradiologists are responsible for viewing non-\ncompressed images on a diagnostic viewer and\nengaging in appropriate patient evaluation and\nrelevant discussion with a treating physician\nbefore making care-related decisions or requests.\nContaCT is limited to analysis of imaging data and\nshould not be used in-lieu of full patient evaluation\nor relied upon to make or confirm diagnosis.","cmTriage is a passive notification for\nprioritization-only, parallel-workflow software\ntool used by radiologists to prioritize specific\npatients within the standard-of-care image\nworklist for 2D FFDM screening mammograms.\ncmTriage uses an artificial intelligence algorithm\nto analyze 2D FFDM screening mammograms and\nflags those that are suggestive of the presence of at\nleast one suspicious finding at the exam level.\nThese flags are viewed by the radiologist via their\nPicture Archiving and Communication System\n(PACS) worklist. The decision to use cmTriage\ncodes and how to use cmTriage codes is ultimately\nup to the radiologist. cmTriage does not send a\nproactive alert directly to the radiologist.\nRadiologists are responsible for reviewing each\nexam on a diagnostic viewer according to the\ncurrent standard of care.\ncmTriage is limited to the categorization of exams,\ndoes not provide any diagnostic information\nbeyond triage and prioritization, does not remove\nimages from the radiologist’s worklist, and should\nnot be used in lieu of full patient evaluation, or\nrelied upon to make or confirm diagnosis.\nc mTriage is for prescription use only.","Similarities\n• Used by radiologists\n• Identifies specific\npatients\n• Operates in parallel\nto standard of care\nworkflow\n• Uses artificial\nintelligence to\nanalyze images\n• Looking for findings\nsuggestive of a pre-\nspecified clinical\ncondition\n• Not intended for\ndiagnostic use\n• Radiologists are\nresponsible for\nviewing images on a\ndiagnostic viewer\n• Limited to analysis\nof imaging data and\nshould not be used\nin-lieu of full patient\nevaluation or relied\nupon to make or\nconfirm diagnosis\nNoted difference:\ncmTriage notification\nis passive vs. proactive\nand cmTriage codes\nare accessed by\nradiologist through\nPACS worklist and\nused for prioritization."],["Technical\nMethod","The device provides triage or notification that is\ninformed by machine learning, artificial\nintelligence or other image analysis algorithms","The device provides triage or notification that is\ninformed by machine learning, artificial\nintelligence or other image analysis algorithms","Same"],["Target Area","The device operates on radiological images of the\nhuman body.","The device operates on radiological images of the\nhuman body.","Same"],["Anatomical Site","Head","Breast","Different anatomic site"],["Where Used","Hospital or Clinic","Hospital or Clinic","Same"],["User Population","Radiologist","Radiologist","Same"],["Software","Device is software only","Device is software only","Same"],["Software Level\nof Concern","Moderate","Moderate","Same"],["Communication\nwith Patient","Communicates images of patients to a radiologist.","Does not communicate images of patients.\ncmTriage passively notifies the radiologist via the\nPACS worklist, whereas ContaCT notifies a pre-\nidentified specialist via direct message.","Noted difference: No\nimages are\ncommunicated from\ncmTriage to\nradiologist. Only\ncmTriage codes are\nreturned for viewing\nwithin the PACS\nworklist."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183460-p4-t0","doc_id":"K183460","page_num":4,"bbox":[153.02,387.71,458.95,594.25],"n_rows":9,"n_cols":2,"columns":["Device Classification Name","system, image processing, radiological"],"rows":[["Device Classification Name","system, image processing, radiological"],["510(k) Number","K160852"],["Device Name","Zia"],["Applicant","Zetta Medical Technologies, LLC.\n1313 Ensell Road\nLake Zurich, IL 60047"],["Regulation Number","892.2050"],["Classification Product Code","LLZ"],["Date Received","03/28/2016"],["Decision Date","12/15/2016"],["510k Review Panel","Radiology"]],"caption_candidate":"The ClariCT.AI software device is substantially equivalent to K160852:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K183460-p5-t0","doc_id":"K183460","page_num":5,"bbox":[126.28,263.43,549.08,592.27],"n_rows":8,"n_cols":5,"columns":["Item","Subject Device – ClariCT.AI","","Predicate- ZIA",""],"rows":[["Item","Subject Device – ClariCT.AI","","Predicate- ZIA",""],["","","","(K160852)",""],["Intended Use","ClariCT.AI is intended for\nnetworking, communication,\nprocessing and enhancement\nof CT images in DICOM\nformat.","ZIA image enhancement system is\nan image processing software that\ncan be used for reducing noise in\nCT images. Enhanced images will\nbe uploaded back to host/PACS\nsystems and exist in conjunction to\nthe original images. ZIA, is not\nintended for mammography\napplications. The device processing\nis not effective for lesion, mass or\nabnormalities of sizes less than 2.0\nmm.","",""],["Intended User","Radiologists and Specialists","Radiologists and Specialists","",""],["Modality Support","CT","CT","",""],["Noise Reduction\nMethod","Noise reduction is performed\nwith the use of pre-trained\ndeep learning models.","Regularization process at flat\nregions with data fidelity constraints\nat edges.","",""],["Image Format and\ncommunications","DICOM","DICOM","",""],["Components and\nHardware\nrequirement","Window Operating System,\nPC Hardware, CUDA\nsupported graphics card or\nequivalent.","Window Operating System,\nPC Hardware, CUDA supported\ngraphics card or equivalent.","",""]],"caption_candidate":"identical in performance to the legally marketed device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p4-t0","doc_id":"K190017","page_num":4,"bbox":[77.72,391.2,517.07,602.49],"n_rows":11,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","510(k) number","","K190017","","","K172685","",""],["","Legal Manufacturer","","Perspectum Diagnostics Ltd","","","Perspectum Diagnostics Ltd","",""],["","Owner/Owner Operator","","Perspectum Diagnostics Ltd","","","Perspectum Diagnostics Ltd","",""],["","NDeuvmicbee Nr ame","","LMSv3","","","LMSv2","",""],["","Proprietary/Common","","LiverMultiScan","","","LiverMultiScan","",""],["","nPaanmeel","","Radiology","","","Radiology","",""],["","Regulation","","21 CFR 892.1000","","","21 CFR 892.1000","",""],["","Risk Class","","Class II","","","Class II","",""],["","Product Class code","","LNH","","","LNH","",""],["Classification","Classification","","Magnetic Resonance Diagnostic\nDevice","","","Magnetic Resonance Diagnostic\nDevice","",""]],"caption_candidate":"2. Subject and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p6-t0","doc_id":"K190017","page_num":6,"bbox":[28.5,72.96,566.67,768.25],"n_rows":16,"n_cols":9,"columns":["","Comparison of subject and Predicate Device","","","","","","",""],"rows":[["","Comparison of subject and Predicate Device","","","","","","",""],["","Characteristic","","","LMSv3 (Subject device)","","","LMSv2 (Predicate device)",""],["Intended Use\nand Indications\nfor Use","","","“LiverMultiScan (LMSv3) is indicated for use as a\nmagnetic resonance diagnostic device software\napplication for non-invasive liver evaluation that\nenables the generation, display and review of 2D\nmagnetic resonance medical image data and\npixel maps for MR relaxation times.\nLiverMultiScan (LMSv3) is designed to utilize\nDICOM 3.0 compliant magnetic resonance image\ndatasets, acquired from compatible MR Systems,\nto display the internal structure of the abdomen\nincluding the liver. Other physical parameters\nderived from the images may also be produced.\nLiverMultiScan (LMSv3) provides a number of\ntools, such as automated liver segmentation and\nregion of interest (ROI) placements, to be used\nfor the assessment of selected regions of an\nimage. Quantitative assessment of selected\nregions includes the determination of\ntriglyceride fat fraction in the liver (PDFF), T2*\nand iron-corrected T1 (cT1) measurements. PDFF\nmay optionally be computed using the LMS\nIDEAL or three-point Dixon methodology.\nThese images and the physical parameters\nderived from the images, when interpreted by a\ntrained clinician, yield information that may\nassist in diagnosis.”","","","“LiverMultiScan is indicated for use\nas a magnetic resonance diagnostic device\nsoftware application for non-invasive liver\nevaluation that enables the generation, display\nand review of 2D magnetic resonance medical\nimage data and pixel maps for MR relaxation\ntimes.\nLiverMultiScan is designed to utilize DICOM 3.0\ncompliant magnetic resonance image datasets,\nacquired from compatible MR Systems, to\ndisplay the internal structure of the abdomen\nincluding the liver. Other physical parameters\nderived from the images may also be produced.\nLiverMultiScan provides a number\nof quantification tools, such as Region of Interest\n(ROI) placements, to be used for the assessment\nof regions of an image to quantify liver tissue\ncharacteristics, including the determination\nof triglyceride fat fraction in the liver, T2* and\niron-corrected T1 measurements.\nThese images and the physical parameters\nderived from the images, when interpreted by a\ntrained clinician, yield information that may\nassist in diagnosis.”","",""],["Target\nPopulation","","","Patients suitable to undergo an MRI scan and not\ncontra-indicated for MRI.","","","","Patients suitable to undergo an MRI scan and not",""],["","","","","","","","contra-indicated for MRI.",""],["","","","","","","","",""],["Device User","","","Trained PD operator","","","Trained PD operator","Trained PD operator",""],["Report User","","","","An interpreting clinician or healthcare","","","An interpreting clinician or healthcare",""],["","","","","practitioner","","","practitioner",""],["Device Use\nEnvironment","","","Installation of LMSv3 is controlled and installed\non general purpose workstations at PD’s image\nanalysis centre","Installation of LMSv3 is controlled and installed","","Installation of LMsv2 is controlled and installed\non general purpose workstations at PD’s image\nanalysis centre","Installation of LMsv2 is controlled and installed",""],["","","","","on general purpose workstations at PD’s image","","","on general purpose workstations at PD’s image",""],["","","","","analysis centre","","","analysis centre",""],["Clinical Setting","","","","LMSv3 is a standalone software device that’s","","","LMSv2 is a standalone software device that’s",""],["","","","","intended to be installed on general use","","","intended to be installed on general use",""],["","","","","workstations at PD’s image analysis centre. The","","","workstations at PD’s image analysis centre. The",""],["","","","","intended device users will log on to the","","","intended device users will log on to the",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p7-t0","doc_id":"K190017","page_num":7,"bbox":[28.51,72.96,566.64,789.24],"n_rows":16,"n_cols":9,"columns":["","Comparison of subject and Predicate Device","","","","","","",""],"rows":[["","Comparison of subject and Predicate Device","","","","","","",""],["","Characteristic","","","LMSv3 (Subject device)","","","LMSv2 (Predicate device)",""],["","","","","workstations, access the device, and use the","","","workstations, access the device, and use the",""],["","","","","device on general-use HD monitors.","","","device on general-use HD monitors.",""],["","","","","LMSv3 is a post-processing software, the","","","LMSv2 is a post-processing software, the",""],["","","","","intended device users are trained internal PD","","","intended device users are trained internal PD",""],["","","","","operators.","","","operators.",""],["","","","","The end-users for the output from the device,","","","The end-users for the output, the pdf report, are",""],["","","","","the pdf report, are clinicians who receive and","","","clinicians who receive and interpret LMSv2",""],["","","","","interpret LMSv3 reports.","","","reports.",""],["","Anatomical","","Abdomen, Liver","Abdomen, Liver","","Abdomen, Liver","Abdomen, Liver",""],["","Location","","","","","","",""],["Energy\nConsiderations","Energy","","Software only application. The device, a\nstandalone software application, does not\ndeliver, monitor or depend on energy delivered\nto or from patients.","","","Software only application. The device, a\nstandalone software application, does not\ndeliver, monitor or depend on energy delivered\nto or from patients.","",""],["","Considerations","","","","","","",""],["Design:\nPurpose","","","Standalone software application to facilitate the\nimport and visualization of MR data sets\nencompassing the abdomen, including the liver\nwith functionality independent of the MRI\nequipment vendor.\nSoftware application intended to display and\nvisualize 2D multi-slice, spin-echo MR data sets\nencompassing the abdomen. The user may\nprocess, and review DICOM 3.0 compliant\ndatasets within the system.","","","Standalone software application to facilitate the\nimport and visualization of MR data sets\nencompassing the abdomen, including the liver\nwith functionality independent of the MRI\nequipment vendor.\nSoftware application intended to display and\nvisualize 2D multi-slice, spin-echo MR data sets\nencompassing the abdomen. The user may\nprocess, and review DICOM 3.0 compliant\ndatasets within the system and/or across\ncomputer networks.","",""],["Design: Tools","","","Allows for the visualisation via parametric maps\nand quantification of metrics (cT1, T2* and PDFF)\nfrom liver tissue and exportation of results &\nimages to a deliverable pdf report*.\nLMSv3 allows for:\ncT1\n• ROI placed method on the cT1 map with IQR\nand median metrics from the placed ROI’s\npotentially across multiple acquired slices.\n• Full segmentation of the outer liver contour\nand liver vasculature of the cT1 parametric\nmap. IQR and median metrics are reported\nfrom the segmentation.\nT2*\n• ROI placed method on the T2* map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired","","","Allows for the visualisation via parametric maps\nand quantification of metrics (cT1, T2* and PDFF)\nfrom liver tissue and exportation of results &\nimages to a deliverable pdf report.\nLMSv2 allows for:\ncT1\n• ROI placed method on the cT1 map with IQR\nand median metrics from the placed ROI’s\npotentially across multiple acquired slices.\nT2*\n• ROI placed method on the T2* map with\nIQR and median metrics from the placed","",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p8-t0","doc_id":"K190017","page_num":8,"bbox":[28.5,72.96,566.64,691.56],"n_rows":23,"n_cols":9,"columns":["","Comparison of subject and Predicate Device","","","","","","",""],"rows":[["","Comparison of subject and Predicate Device","","","","","","",""],["","Characteristic","","","LMSv3 (Subject device)","","","LMSv2 (Predicate device)",""],["","","","slices T2* parametric maps are calculated\nfrom the Gradient Multi-Echo method.\nPDFF\n• ROI placed method on the PDFF map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices potentially across multiple acquired\nslices.\n• PDFF parametric maps can be calculated\nusing either the LMS IDEAL method [2] or\nthe three-point DIXON method. [1]\n• Full liver segmentation of the PDFF\nparametric map where IQR and median\nmetrics are reported from the\nsegmentation.","","","ROI’s potentially across multiple acquired\nslices T2* parametric maps are calculated\nfrom the Gradient Multi-Echo method.\nPDFF\n• ROI placed method on the PDFF map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices potentially across multiple acquired\nslices.\n• PDFF parametric maps are calculated from\nthe three-point DIXON method. [1]","",""],["Design:\nAlgorithms","","","","Previously cleared algorithms:","","• Noise Determination Algorithms\n• T1 mapping Algorithms\n• T2* mapping Algorithms\n• Unwrapping Phase Image Algorithms\n• Creation of cT1 image Algorithms\n• Water and Fat Mapping Algorithms","",""],["","","","","• Noise Determination Algorithms","","","",""],["","","","","• T1 mapping Algorithms","","","",""],["","","","","• T2* mapping Algorithms","","","",""],["","","","","• Unwrapping Phase Image Algorithms","","","",""],["","","","","• Creation of cT1 image Algorithms","","","",""],["","","","","• Water and Fat Mapping Algorithms","","","",""],["","","","","","","","",""],["","","","","New algorithms:","","","",""],["","","","","• IDEAL Processing Algorithms","","","",""],["","","","","• MAGO Processing Algorithms","","","",""],["","","","","• Quality Check for Shimming","","","",""],["","","","","• Automatic Liver Segmentation Algorithms","","","",""],["","","","","• Segmentation Mapping to T2*/PDFF","","","",""],["","","","","algorithms","","","",""],["","","","","","","","",""],["","","","","LMSv3 uses identical algorithms cleared in LMSv2","","","",""],["","","","","to quantify cT1, T2* and DIXON PDFF using ROI’s.","","","",""],["Design: MR\nRelaxometry","","","T1, iron-corrected T1 (cT1) and T2* mapping.","T1, iron-corrected T1 (cT1) and T2* mapping.","","T1, iron-corrected T1 (cT1) and T2* mapping.","",""],["Design: Liver\nFat\nQuantification","","","Utilizes MR images that exploit the difference in\nresonance frequencies between hydrogen nuclei\nin water and triglyceride fat using either LMS\nIDEAL method or three-point DIXON method.","","","Utilizes MR images that exploit the difference in\nresonance frequencies between hydrogen nuclei\nin water and triglyceride fat using the three-\npoint DIXON method.","",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p9-t0","doc_id":"K190017","page_num":9,"bbox":[28.49,72.96,566.67,758.22],"n_rows":10,"n_cols":9,"columns":["","Comparison of subject and Predicate Device","","","","","","",""],"rows":[["","Comparison of subject and Predicate Device","","","","","","",""],["","Characteristic","","","LMSv3 (Subject device)","","","LMSv2 (Predicate device)",""],["Design: Liver\nSegmentation","","","LMSv3 supports automatic multi-slice full liver\nsegmentation of the cT1 and PDFF parametric\nmap. Use of this functionality is at the discretion\nof the operator instead or in combination with\nthe ROI based method.\nThe cT1 segmented liver is presented in colour\nlevel window, while the rest of the cT1 image is\npresented in greyscale level window with ducts\nand liver vasculature excluded from the\nsegmented volume.","","","Does not support whole liver segmentation. See\nfirst reference device below, LiverLab.","",""],["Design: Regions\nof Interest\n(ROI)","","","Median and interquartile range measurements\ncreated from a cross sectional slice of liver\ntissue. For each parametric map, statistics from\nmultiple Regions of Interest (ROIs) – potentially\nplaced across multiple slices – are summarised.\nAlso supports the display of ‘Live’ ROI statistics\nwhen moving the ROI across the parametric\nmap.","","","Median and interquartile range measurements\ncreated from a cross sectional slice of liver\ntissue. For each parametric map, statistics from\nmultiple Regions of Interest (ROIs) – potentially\nplaced across multiple slices – are summarised.\nAlso supports the display of ‘Live’ ROI statistics\nwhen moving the ROI across the parametric\nmap.","",""],["Design:\nParametric\nMaps","","","Iron corrected T1 (cT1), T2* and triglyceride fat\n(i.e. DIXON or IDEAL Proton Density Fat Fraction\n(PDFF)) parametric maps are supported.\nPDFF parametric maps are calculated with either\nMAGNITUDE ONLY-IDEAL, when the data is\nreceived from GE and Phillips scanners, and\nCOMPLEX-IDEAL for Siemens. When analysing\nCOPLEX-IDEAL data a field map is also available\nduring analysis. PDFF may also be calculated\nusing the three-point DIXON method.","","","Iron corrected T1 (cT1), T2* and triglyceride fat\n(i.e. DIXON Proton Density Fat Fraction (PDFF))\nparametric maps are supported.","",""],["Design:\nVisualisation","","","Iron corrected T1 (cT1), T2* and triglyceride fat\n(also known as Proton Density Fat Fraction\n(PDFF)) parametric maps are supported.\nIron corrected T1 (cT1) displayed using LMSv3\ncolourmap, designed to have maximum contrast\non liver parenchymal tissue.","","","Iron corrected T1 (cT1), T2* and triglyceride fat\n(also known as Proton Density Fat Fraction\n(PDFF)) parametric maps are supported.\nIron corrected T1 (cT1) displayed using LMSv2\ncolourmap, designed to have maximum contrast\non liver parenchymal tissue.","",""],["","Design:","","DICOM 3.0 compliant MR data from supported\nMRI scanners.","","","DICOM 3.0 compliant MR data from supported\nMRI scanners.","",""],["","Supported","","","","","","",""],["","Modalities","","","","","","",""],["Design: Report","Design: Report","","Quantified metrics from liver tissue and image\nanalysis collated in a deliverable pdf report.\nHistogram of segmented area and proportion of\nPDFF intensities are included in the final report\nto give a better understanding on the\ndistribution of PDFF intensities.","","","Quantified metrics from liver tissue and images\nanalysis collated in a deliverable pdf report.","",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p10-t0","doc_id":"K190017","page_num":10,"bbox":[28.46,72.96,566.71,461.88],"n_rows":19,"n_cols":9,"columns":["","Comparison of subject and Predicate Device","","","","","","",""],"rows":[["","Comparison of subject and Predicate Device","","","","","","",""],["","Characteristic","","","LMSv3 (Subject device)","","","LMSv2 (Predicate device)",""],["Compatibility\nwith the\nenvironment","Compatibility","","","Installation of LMSv3 is controlled and is installed","","","Installation of LMSv2 is controlled and is installed",""],["","with the","","","on general purpose workstations at PD’s image","","","on general purpose workstations at PD’s image",""],["","environment","","","analysis centre.","","","analysis centre.",""],["","","","","LMSv3 reads in local files compliant with DICOM","","","LMSv2 reads in local files compliant with DICOM",""],["","","","","3.0.","","","3.0.",""],["Performance","","","Validated with phantom scans, synthetic raw\ndata and volunteer scans covering a range of\nphysiological values for cT1, T2* and PDFF.","","","Validated with phantom scans, synthetic raw\ndata and volunteer scans covering a range of\nphysiological values for cT1, T2* and PDFF.","",""],["Supported MRI\nSystems","","","Validated across all listed supported\nmanufacturers and field strengths.","","","Validated across all listed supported\nmanufacturers and field strengths.","",""],["Standards","","","IEC 62304, IEC 62366, DICOM 3.0, ISO 14971, ISO\n13485","","","IEC 62304, DICOM 3.0, ISO 14971, ISO 13485","",""],["System/Operati\nng System","","","Mac OS","","","Mac OS","",""],["Materials","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Biocompatibilit\ny","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Sterility","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Electrical Safety","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Mechanical\nSafety","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Chemical Safety","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Thermal Safety","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""],["Radiation\nSafety","","","Not applicable, standalone software.","","","Not applicable, standalone software.","",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p13-t0","doc_id":"K190017","page_num":13,"bbox":[35.89,72.96,539.92,214.44],"n_rows":8,"n_cols":3,"columns":["Phantom Metrics","","Accuracy"],"rows":[["Phantom Metrics","","Accuracy"],["","","95% CI Limits of Agreement"],["T1","Up to 18.89% lower to the ground truth",""],["T2*","- 9.31% to 7.53% of the ground truth",""],["DIXON PDFF < 30%","-7.37 % to 1.72%",""],["DIXON PDFF > 30%","-28.93% to 6.83%",""],["IDEAL PDFF < 30%","-1.17% to 1.43%",""],["IDEAL PDFF > 30%","-5.05% to 10.70%",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p13-t1","doc_id":"K190017","page_num":13,"bbox":[35.89,256.08,539.92,388.74],"n_rows":8,"n_cols":6,"columns":["Phantom Metrics","","Repeatability","","","Reproducibility"],"rows":[["Phantom Metrics","","Repeatability","","","Reproducibility"],["","","95% CI Limits of Agreement","","","95% CI Limits of Agreement"],["T1","- 13.88 to 14.47 ms","","","- 2.66 to 10.78%",""],["T2*","- 0.89 to 1.43 ms","","","- 3.43 to 2.42 ms",""],["DIXON PDFF < 30%","-0.66 to 0.82 %","","","-1.86 to 5.95%",""],["DIXON PDFF > 30%","-2.11 to 1.96%","","","-8.64 to 23.52%",""],["IDEAL PDFF < 30%","-1.27 to 0.87%","","","-1.99 to 2.80%",""],["IDEAL PDFF > 30%","-3.80 to 1.93 %","","","-13.46 to 6.98%",""]],"caption_candidate":"• LMSv3 measurements of T1, T2* and PDFF are reproducible between different scanners","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p13-t2","doc_id":"K190017","page_num":13,"bbox":[42.47,623.76,552.58,772.2],"n_rows":9,"n_cols":7,"columns":["Volunteer Metrics","","Repeatability","","","Reproducibility",""],"rows":[["Volunteer Metrics","","Repeatability","","","Reproducibility",""],["","","95% CI Limits of Agreement","","","95% CI Limits of Agreement",""],["cT1 (ROI)","- 94.38 to 63.38 ms","","","-89.70( Rtoa n1g2e0). 58 ms","",""],["cT1 (Segmentation)","- 76.93 to 59.39 ms","","","-84.91 to 121.79 ms","",""],["T2* (ROI)","- 6.07 to 5.70 ms","","","-3.68 to 6.35 ms","",""],["DIXON PDFF (ROI)","-1.77 to 3.64 %","","","-6.21 to 2.63%","",""],["DIXON PDFF (Segmentation)","-1.20 to 1.06%","","","-3.14 to 0.88%","",""],["IDEAL PDFF (ROI)","-1.92 to 1.54%","","","-2.66 to 2.77","",""],["IDEAL PDFF (Segmentation)","-1.83 to 1.28 %","","","-1.74 to 1.21","",""]],"caption_candidate":"• LMSv3 measurements of cT1, T2* and PDFF under the ‘worst case’ variability conditions are highly reproducible","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p14-t0","doc_id":"K190017","page_num":14,"bbox":[38.57,91.2,554.96,252.36],"n_rows":10,"n_cols":6,"columns":["Volunteer Metrics","","Intra-Operator","","","Inter-Operator"],"rows":[["Volunteer Metrics","","Intra-Operator","","","Inter-Operator"],["","","95% CI Limits of Agreement","","","95% CI Limits of Agreement\n(Range)"],["","","(Range)","","",""],["cT1 (ROI)","-27.38 to 28.33ms","","","- 48.05 to 39.89ms",""],["cT1 (Segmentation)","- 20.81 to 13.06ms","","","-37.84 to 26.51ms",""],["T2* (ROI)","- 2.29 to 2.91 ms","","","- 2.64 to 4.90 ms",""],["DIXON PDFF (ROI)","- 0.78 to 1.90 %","","","- 2.27 to 4.57%",""],["DIXON PDFF (Segmentation)","- 0.29 to 0.45%","","","- 0.55 to 1.22%",""],["IDEAL PDFF (ROI)","- 1.26 to 1.05%","","","- 2.09 to 1.82 %",""],["IDEAL PDFF (Segmentation)","- 0.16 to 0.14%","","","- 0.37 to 0.26%",""]],"caption_candidate":"LMSv3 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p14-t1","doc_id":"K190017","page_num":14,"bbox":[38.57,278.52,554.96,437.64],"n_rows":9,"n_cols":3,"columns":["Volunteer Metrics","","Worst-Case Variability"],"rows":[["Volunteer Metrics","","Worst-Case Variability"],["","","95% CI Limits of Agreement (Range)"],["cT1 (ROI)","-126.52 to 104.19 ms",""],["cT1 (Segmentation)","- 65.27 to 120.27 ms",""],["T2* (ROI)","-3.68 to 6.35 ms",""],["DIXON PDFF (ROI)","-2.04 to 0.76 %",""],["DIXON PDFF (Segmentation)","-2.72 to 1.24%",""],["IDEAL PDFF (ROI)","-3.75 to 2.83%",""],["IDEAL PDFF (Segmentation)","-1.92 to 1.35%",""]],"caption_candidate":"IDEAL PDFF (Segmentation) - 0.16 to 0.14% - 0.37 to 0.26%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p14-t2","doc_id":"K190017","page_num":14,"bbox":[38.57,579.12,554.96,677.32],"n_rows":5,"n_cols":3,"columns":["Phantom Metric","","Results (Range)\n95% CI Limits of Agreement"],"rows":[["Phantom Metric","","Results (Range)\n95% CI Limits of Agreement"],["T1","-1.96 to 2.09ms",""],["T2*","-0.08 to 0.08ms",""],["DIXON PDFF (< 30)","-0.18 to 0.10 %",""],["DIXON PDFF (> 30)","-1.62 to 1.02 %",""]],"caption_candidate":"device when measuring PDFF<30%, and within 2% when measuring PDFF>30%.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190017-p15-t0","doc_id":"K190017","page_num":15,"bbox":[36.15,113.76,553.29,195.72],"n_rows":5,"n_cols":4,"columns":["Volunteer Metric","","Results (Range)",""],"rows":[["Volunteer Metric","","Results (Range)",""],["","","95% CI Limits of Agreement",""],["T1","-28.08 to 28.73ms","",""],["T2*","-0.43 to 1.69ms","",""],["DIXON PDFF","-0.18 to 0.10 %","",""]],"caption_candidate":"values within 2ms. There is negligible difference in the measurement of PDFF between LMSv3 and the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190072-p6-t0","doc_id":"K190072","page_num":6,"bbox":[86.26,87.46,596.5,764.74],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for ICH triage (K180647)","Subject Device\nAidoc Briefcase for ICH and PE triage"],"rows":[["","Predicate Device\nAidoc Briefcase for ICH triage (K180647)","Subject Device\nAidoc Briefcase for ICH and PE triage"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of non-enhanced\nhead CT images. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by flagging\nand communication of suspected positive\nfindings of pathologies in head CT images,\nnamely Intracranial Hemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nICH findings. Notifications\ninclude compressed preview images that\nare meant for informational purposes only\nand not intended for diagnostic use\neyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of non-enhanced\nhead CT and CTPA images. The device is\nintended to assist hospital networks and\ntrained radiologists in workflow triage\nby flagging and communication of\nsuspected positive findings of Intracranial\nHemorrhage (ICH) and Pulmonary\nEmbolism (PE) pathologies. For the PE\npathology, the software is only intended to\nbe used on single-energy exams.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a\nstandalone desktop application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are\nmeant for informational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User population","Radiologist","Radiologist"],["Anatomical\nregion of\ninterest","Head","Head and chest"],["Data\nacquisition\nprotocol","Non-contrast head CT scan","Non-contrast head CT scan and CTPA\n(single energy exams only)"],["View DICOM\ndata","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient,\nstudy and current image"],["Segmentation\nof region of\ninterest","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/Prio\nritization","Yes","Yes"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190072-p7-t0","doc_id":"K190072","page_num":7,"bbox":[86.26,72.82,596.5,207.22],"n_rows":3,"n_cols":3,"columns":["Preview images","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases.","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],"rows":[["Preview images","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases.","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190072-p8-t0","doc_id":"K190072","page_num":8,"bbox":[83.94,182.12,528.26,306.23],"n_rows":8,"n_cols":19,"columns":["Parameter","","","N","","","Mean\nestimate","","Lower\nConfidence\nLimit","","","Upper","","Median","","","P-value","",""],"rows":[["Parameter","","","N","","","Mean\nestimate","","Lower\nConfidence\nLimit","","","Upper","","Median","","","P-value","",""],["","","","","","","","","","","","Confidence","","","","","","",""],["","","","","","","","","","","","Limit","","","","","","",""],["","Time-to-open-exam in","","","51","","","64.1","36.6","","","91.5","","","49.0","","","",""],["","the standard of care","","","","","","","","","","","","","","","","",""],["","Time-to-notification of","","","51","","","3.9","3.7","","","4.1","","","3.9","","","",""],["","BriefCase PE","","","","","","","","","","","","","","","","",""],["Difference","","","","51","","","60.2","32.7","","","87.6","","","45.2","","","<0.0001",""]],"caption_candidate":"Table 2. Time saving data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190362-p6-t0","doc_id":"K190362","page_num":6,"bbox":[57.86,88.57,594.97,710.45],"n_rows":5,"n_cols":4,"columns":["Technological\nCharacteristics","HealthPNX","Predicate: cmTriage\n(K183285)","Similarities or\nDifferences"],"rows":[["Technological\nCharacteristics","HealthPNX","Predicate: cmTriage\n(K183285)","Similarities or\nDifferences"],["Indication for use","The Zebra Pneumothorax\ndevice is a software\nworkflow tool designed to\naid the clinical assessment\nof adult Chest X-Ray cases\nwith features suggestive of\nPneumothorax in the\nmedical care environment.\nHealthPNX analyzes cases\nusing an artificial\nintelligence algorithm to\nidentify suspected findings.\nIt makes case-level output\navailable to a\nPACS/workstation for\nworklist prioritization or\ntriage. HealthPNX is not\nintended to direct attention\nto specific portions of an\nimage or to anomalies other\nthan Pneumothorax. Its\nresults are not intended to\nbe used on a stand-alone\nbasis for clinical decision-\nmaking nor is it intended to\nrule out Pneumothorax or\notherwise preclude clinical\nassessment of X-Ray cases","cmTriage is a passive notification\nfor prioritization-only, parallel-\nworkflow software tool used by\nradiologists to prioritize specific\npatients within the standard-of-care\nimage worklist for 2D FFDM\nscreening mammograms.\ncmTriage uses an artificial\nintelligence algorithm to analyze\n2D FFDM screening mammograms\nand flags those that are suggestive\nof the presence of at least one\nsuspicious finding at the exam\nlevel.\nThese flags are viewed by the\nradiologist via their Picture\nArchiving and Communication\nSystem (PACS) worklist. The\ndecision to use cmTriage codes and\nhow to use cmTriage codes is\nultimately up to the radiologist.\ncmTriage does not send a proactive\nalert directly to the radiologist.\nRadiologists are responsible for\nreviewing each exam on a diagnostic\nviewer according to the current\nstandard of care. cmTriage is limited to\nthe categorization of exams, does not\nprovide any diagnostic information\nbeyond triage and prioritization, does\nnot remove images from the\nradiologist’s worklist, and should not\nbe used in lieu of full patient\nevaluation, or relied upon to make or\nconfirm diagnosis.\ncmTriage is for prescription use only.","Similar except to\nanatomy, imaging\nmodality and lesion\ntype"],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Radiologist","Radiologist","Same"],["Radiological\nimages format","DICOM","DICOM","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190362-p7-t0","doc_id":"K190362","page_num":7,"bbox":[57.77,72.31,595.0,517.12],"n_rows":10,"n_cols":4,"columns":["Identify patients\nwith prespecified\nclinical condition","Yes","Yes","Same"],"rows":[["Identify patients\nwith prespecified\nclinical condition","Yes","Yes","Same"],["Clinical condition","Pneumothorax","Breast Cancer","Different but are\n“time sensitive\nimaging” per 21CFR\n892.2080"],["Alert to finding","Passive notification flagged for\nreview","Passive notification flagged for review","Same"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed\nfrom worklist","Same"],["Modality","X-Ray","FFDM screening mammograms","Different but both run\non “radiological\nmedical images” per\n21 CFR 892.2080"],["Body part","Chest","Breast","Different anatomical\nsites but both\n“operates on\nradiological images of\nthe human body” per\n21 CFR 892.2080"],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Same"],["Limited to\nanalysis of\nimaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with\nindicated findings","Yes","Yes","Same"],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190387-p4-t0","doc_id":"K190387","page_num":4,"bbox":[80.8,11.52,548.13,47.1],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-8.1 Traditional 510(k) Submission RayStation 8.1","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190387-p5-t0","doc_id":"K190387","page_num":5,"bbox":[80.8,11.52,548.13,47.1],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-8.1 Traditional 510(k) Submission RayStation 8.1","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190424-p4-t0","doc_id":"K190424","page_num":4,"bbox":[72.48,567.12,531.12,663.6],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Accipiolx"],"rows":[["Proprietary Name","Accipiolx"],["Premarket Notification","K182177"],["Classification Name","Radiological Computer-Assisted Triage and Notification\nSoftware"],["Regulation Number","21 CFR 892.2080"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"The HealthICH device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190424-p6-t0","doc_id":"K190424","page_num":6,"bbox":[72.84,351.18,539.16,696.92],"n_rows":2,"n_cols":4,"columns":["Technological\nCharacteristics","Proposed Device:\nHealthICH","Predicate Device:\nAccipiolx (K182177)","Summary"],"rows":[["Technological\nCharacteristics","Proposed Device:\nHealthICH","Predicate Device:\nAccipiolx (K182177)","Summary"],["Intended Use","The Zebra Head CT triage device is\na software workflow tool designed\nto aid the clinical assessment of\nadult non-contrast head CT cases\nwith features suggestive of\nintracranial hemorrhage in the\nmedical care\nenvironment. HealthICH analyzes\ncases using an artificial intelligence\nalgorithm to identify suspected\nfindings. It makes case-level output\navailable to a PACS/workstation for\nworklist prioritization or triage.\nHealthICH is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\nintracranial hemorrhage. Its results\nare not intended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it intended\nto rule out hemorrhage or otherwise\npreclude clinical assessment of CT\ncases.","AccipioIx is a software\nworkflow tool designed to\naid in prioritizing the clinical\nassessment of adult non-\ncontrast head CT cases with\nfeatures suggestive of acute\nintracranial hemorrhage in\nthe acute care environment.\nAccipioIx analyzes cases\nusing an artificial intelligence\nalgorithm to identify\nsuspected findings. It makes\ncase-level output available to\na PACS/workstation for\nworklist prioritization or\ntriage.\nAccipioIx is not intended to\ndirect attention to specific\nportions of an image or to\nanomalies other than acute\nintracranial hemorrhage. Its\nresults are not intended to be\nused on a stand-alone basis\nfor clinical decision-making\nnor is it intended to rule out\nhemorrhage or otherwise","Same"]],"caption_candidate":"A comparison of the technological characteristics with the predicate device is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190424-p7-t0","doc_id":"K190424","page_num":7,"bbox":[72.77,72.78,539.23,557.94],"n_rows":14,"n_cols":4,"columns":["","","preclude clinical assessment\nof CT cases.",""],"rows":[["","","preclude clinical assessment\nof CT cases.",""],["Notification-\nonly, parallel\nworkflow\ntool","Yes","Yes","Same"],["User","Prespecified clinical users\n(clinicians)","Prespecified clinical users\n(clinicians)","Same"],["Radiological\nimages format","DICOM","DICOM","Same"],["Identify patients\nwith\nprespecified\nclinical\ncondition","Yes","Yes","Same"],["Clinical\ncondition","Intracranial hemorrhage","Intracranial hemorrhage","Same"],["Alert to finding","Yes; flagged for review","Yes; flagged for review","Same"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed\nfrom worklist","Same"],["Modality","CT","CT","Same"],["Body part","Head","Head","Same"],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Same"],["Limited to\nanalysis of\nimaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with\nindicated\nfindings","Yes","Yes","Same"],["Where results\nare received","PACS / Workstation","PACS / Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190442-p8-t0","doc_id":"K190442","page_num":8,"bbox":[108.24,137.88,539.76,714.9],"n_rows":11,"n_cols":4,"columns":["Product","QuantX\n(DEN270022)","ClearView cCAD\n(K161959)","Koios DS for Breast"],"rows":[["Product","QuantX\n(DEN270022)","ClearView cCAD\n(K161959)","Koios DS for Breast"],["Characteristics","CADx device used to\nassist in the\nassessment and\ncharacterization of\nbreast abnormalities\nusing MR image data.","Decision support device\nused to assist in the\nassessment and\ncharacterization of\nbreast lesions using US\nimage data.","Decision support\ndevice used to assist in\nthe assessment and\ncharacterization of soft\ntissue breast lesions\nusing US image data."],["Intended Use","Diagnostic Aid using\nMachine Learning to\ncharacterize image\nfeatures with user\nprovided ROIs to\ngenerate a single\nvalue relative to\nreference\nabnormalities (QI\nScore).","Diagnostic Aid using\nMachine Learning to\ngenerate BI-RADS\nshape and orientation\nassessments coupled\nwith additional user\ninput BI-RADS\ndescriptors to generate a\npreliminary BI-RADS\nbucket assessment.","Diagnostic Aid using\nMachine Learning to\ncharacterize image\nfeatures with user\nprovided ROIs to\ngenerate categorical\noutput that aligns to\nBI-RADS and auto-\nclassified shape and\norientation."],["Target\nPopulation","High-risk screening;\ndiagnostic workup;\nevaluation of known\ndisease","Any patient that has an\nidentified breast lesion\nthat is referred for\ndiagnostic ultrasound\nexamination; excludes\nhigh-risk screening","Patients with soft\ntissue breast lesions\nwho are being referred\nfor further diagnostic\nultrasound\nexamination."],["Modality Used\nfor Analysis","Breast MR Data","Breast Ultrasound Data","Breast Ultrasound Data"],["Input","Medical images\nprovided in a DICOM\nformat","Medical images\nprovided in a DICOM\nformat","Medical images\nprovided in a DICOM\nformat"],["Output","“QI” score mapped\nonto histograms of\ndistributions of\nmalignant and benign\nlesions","BI-RADS bucket\nassessment of lesions\nbased on auto-classified\nshape and orientation\nand user supplied inputs","Koios defined\ncategorical and\ncontinuous outputs\n(confidence level\nindicator) that align to\nBI-RADS and auto-\nclassified shape and\norientation"],["Comparative\nPerformance\nTesting","Metric: AUC\nCases: 111\nReaders: 19","N/A","Metric: AUC\nCases: 900\nReaders: 15"],["Physical\nCharacteristics","Software Package\nOperates on off-the-\nshelf hardware","Software Package\nOperates on off-the-\nshelf hardware","Software Package\nOperates on off-the-\nshelf hardware"],["Storage","Storage not supported","Storage not supported","Storage not supported"],["Image Input","DICOM","DICOM","DICOM"]],"caption_candidate":"6. Substantial Equivalence Discussion","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190764-p6-t0","doc_id":"K190764","page_num":6,"bbox":[72.32,258.42,536.19,715.48],"n_rows":28,"n_cols":9,"columns":["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],"rows":[["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],["","","","","","","Device","",""],["","","","","SurgicalAR","VitreaView\n(K163232)","","",""],["Annotation and\nMeasurement Tools","• Line\n• Angle\n• Ruler\n• Arrow","","","Yes","Yes","","","Same"],["User Installation\nRequirements","","• Runs within","","No","Yes","","","Different.\nPredicate allows\nfor access via\nInternet."],["","","browser","","","","","",""],["","","using HTML","","","","","",""],["","","and","","","","","",""],["","","JavaScript","","","","","",""],["","","only","","","","","",""],["","","• No","","","","","",""],["","","installation is","","","","","",""],["","","required on","","","","","",""],["","","user’s machine","","","","","",""],["Data Type\nSupported","• DICOM\n• Non-DICOM","","","Yes","Yes","","","Same"],["Image\nView/Manipulation","","• Image Zoom","","No","Yes","","","Different.\nPredicate has\n“image invert”\nand “image\ncine” features."],["","","• Pan","","","","","",""],["","","• Window Level","","","","","",""],["","","•AutoWindow","","","","","",""],["","","• Level","","","","","",""],["","","• Reset","","","","","",""],["","","• Scout Lines","","","","","",""],["","","• Image Rotate","","","","","",""],["","","• Image Flip","","","","","",""],["","","• Magnify","","","","","",""],["","","• Image Invert","","","","","",""],["","","• Image Cine","","","","","",""],["Data Encryption","• HTTPS\n• SSL","","","Yes","Yes","","","Same"]],"caption_candidate":"and the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190764-p7-t0","doc_id":"K190764","page_num":7,"bbox":[72.33,72.37,536.18,707.73],"n_rows":27,"n_cols":13,"columns":["Criteria","","","Description","","","Subject Device","","Predicate","","Comparison","",""],"rows":[["Criteria","","","Description","","","Subject Device","","Predicate","","Comparison","",""],["","","","","","","","","Device","","","",""],["","","","","","","SurgicalAR","VitreaView\n(K163232)","","","","",""],["","Patient","","Capable of displaying\npatient demographic\ninformation","","","Yes","Yes","","","Same","",""],["","Demographic","","","","","","","","","","",""],["","Display","","","","","","","","","","",""],["Linking","","","Co-planar linking:\n• Autolink\n• Manual","","","Yes","Yes","","","Same","",""],["User and Password\nControl","","","","Users can be managed","","Yes","Yes","","","Same","",""],["","","","","via an internal","","","","","","","",""],["","","","","database, active","","","","","","","",""],["","","","","directory, or parent","","","","","","","",""],["","","","","application","","","","","","","",""],["Data Security","","","Stored on server","","","Yes","Yes","","","Same","",""],["","Audit Trail","","Audit trail logged","","","Yes","Yes","","","","Same",""],["User Management","","","Database structure\nallows mapping users\nto groups internally or\nmapping external\ngroups (AD, parent\napplication) to internal\ngroups and role","","","","","","","","",""],["Transmission\nModes","","","Via the web with\nInternet browsers","","","No","Yes","","","","Different.",""],["","","","","","","","","","","","Predicate allows",""],["","","","","","","","","","","","for access via",""],["","","","","","","","","","","","Internet.",""],["File Type Used","","","• JPEG for\nLossy\ndata\n• PNG for\nLossless data","","","Yes","Yes","","","Same","",""],["MPR Viewing","","","","This viewing feature","","Yes","Yes","","","Same","",""],["","","","","enables the display of","","","","","","","",""],["","","","","reformatted CT and","","","","","","","",""],["","","","","MR images into axial,","","","","","","","",""],["","","","","coronal and sagittal","","","","","","","",""],["","","","","orientations","","","","","","","",""],["3D Volume\nRendered Viewing","","","This viewing feature\nenables the display of\n3D perspective views\nof CT and MR image\nsets that have been\ntransformed into","","","Yes","Yes","","","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190764-p8-t0","doc_id":"K190764","page_num":8,"bbox":[72.32,72.37,536.18,706.73],"n_rows":23,"n_cols":13,"columns":["Criteria","","","Description","","","Subject Device","","Predicate","","Comparison","",""],"rows":[["Criteria","","","Description","","","Subject Device","","Predicate","","Comparison","",""],["","","","","","","","","Device","","","",""],["","","","","","","SurgicalAR","VitreaView\n(K163232)","","","","",""],["","","","volumes. It also\nprovides presets to\nenable users to alter\nthe visualization\nparameters\nof the 3D views to\nhighlight features.","","","","","","","","",""],["Active Target Tool","","","","This viewing feature","","Yes","Yes","","","Same","",""],["","","","","provides a facility to","","","","","","","",""],["","","","","view a single target","","","","","","","",""],["","","","","location within","","","","","","","",""],["","","","","multiple images.","","","","","","","",""],["Crosshair\nNavigation and\nSynchronization","","","This viewing feature\nprovides a facility to\nsynchronize and scroll\nthrough multiple\nviews at the same\ntime.","","","Yes","Yes","","","Same","",""],["Ability to clone\nimages side by side","","","Ability to clone\nimages side by side.","","","No","Yes","","","","Different.",""],["","","","","","","","","","","","Predicate",""],["","","","","","","","","","","","contains a",""],["","","","","","","","","","","","“clone”",""],["","","","","","","","","","","","copy/paste",""],["","","","","","","","","","","","feature.",""],["Ability to close an\nimage by clicking\nan “X” in the\nupper-left portion\nof the view port","","","Ability to close an\nimage by clicking an\n“X” in the upper-left\nportion of the\nviewport.","","","Yes","Yes","","","Same","",""],["","Ability to select","","Ability to select locale\nand language settings\non the login screen.","","","No","Yes","","","","Different.",""],["","","","","","","","","","","","Predicate has",""],["","locale and language","","","","","","","","","","support for",""],["","settings on the","","","","","","","","","","multiple",""],["","login screen","","","","","","","","","","languages.",""],["Ability to\ncustomize the\ncolumns in the\nstudy directory by\nselecting the\ndropdown arrow on","","","Ability to customize\nthe columns in the\nstudy directory by\nselecting the\ndropdown arrow on\nthe right side of each\ncolumn.","","","No","Yes","","","Different.\nPredicate has\nfeature to\ncustomize the\nview of the\ndirectory.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190764-p9-t0","doc_id":"K190764","page_num":9,"bbox":[72.32,72.37,536.19,719.23],"n_rows":43,"n_cols":9,"columns":["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],"rows":[["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],["","","","","","","Device","",""],["","","","","SurgicalAR","VitreaView\n(K163232)","","",""],["the right side of\neach column.","","","","","","","",""],["Help Tips","","Proactive help tips","","No","Yes","","","Different.\nPredicate has\nfeature to view\n“help tips”."],["","","appear for 10-15","","","","","",""],["","","seconds to educate","","","","","",""],["","","users on certain","","","","","",""],["","","functionality that may","","","","","",""],["","","not be obvious to a","","","","","",""],["","","new user.","","","","","",""],["Support for TIF\nFiles","Vitrea View can\ndisplay TIF files.","","","Yes","Yes","","","Same"],["Tablet\nsupport for\ninformation\npurpose\nonly\n(Not for diagnostic\nuse)","","This viewing feature","","No","Yes","","","Different.\nPredicate has\nsupport for iOS\nand Android for\nnon-diagnostic\nviewing."],["","","provides access of","","","","","",""],["","","Vitrea View software","","","","","",""],["","","on various iOS and","","","","","",""],["","","Android tablet","","","","","",""],["","","devices through the","","","","","",""],["","","default internet","","","","","",""],["","","browser. Key","","","","","",""],["","","features are:","","","","","",""],["","","• Two-finger","","","","","",""],["","","pinch to","","","","","",""],["","","zoom and","","","","","",""],["","","pan","","","","","",""],["","","• Touch and","","","","","",""],["","","drag to","","","","","",""],["","","scroll","","","","","",""],["","","• Double-tap to","","","","","",""],["","","access","","","","","",""],["","","Gesture","","","","","",""],["","","menu","","","","","",""],["","","• Tap","","","","","",""],["","","Carousel","","","","","",""],["","","thumbnail,","","","","","",""],["","","then tap","","","","","",""],["","","Image Pane","","","","","",""],["","","to swap","","","","","",""],["","","images","","","","","",""],["","","• Ambient","","","","","",""],["","","Lighting","","","","","",""],["","","Check","","","","","",""],["HMD support for\ninformation","This viewing feature\nprovides access of\nSurgicalAR software","","","No","Yes","","","Different.\nProposed device\nhas support for"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190764-p10-t0","doc_id":"K190764","page_num":10,"bbox":[72.32,72.37,536.18,302.01],"n_rows":12,"n_cols":9,"columns":["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],"rows":[["Criteria","Description","","","Subject Device","","Predicate","","Comparison"],["","","","","","","Device","",""],["","","","","SurgicalAR","VitreaView\n(K163232)","","",""],["purpose only (not\nfor diagnostic use)","on consumer, off-the-\nshelf-wireless, Wi-Fi\nenabled, stereoscopic\nhead-mounted display\nwith minimum of 2GB\nRAM","","","","","","","HMDs for non-\ndiagnostic\nviewing."],["Diagnostic\nquality medical\nimage review","","Ability to provide","","Yes","Yes","","","Same"],["","","diagnostic quality","","","","","",""],["","","medical image review","","","","","",""],["","","for multi-dimensional","","","","","",""],["","","digital images","","","","","",""],["","","acquired from a","","","","","",""],["","","variety of imaging","","","","","",""],["","","devices","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p4-t0","doc_id":"K190868","page_num":4,"bbox":[108.14,164.14,539.91,259.89],"n_rows":6,"n_cols":2,"columns":["510(k) Sponsor","Cleerly, Inc."],"rows":[["510(k) Sponsor","Cleerly, Inc."],["Address","101 Greenwich St, Suite 11C\nNew York, NY 10006"],["",""],["Phone/Fax #","646-362-4255"],["Contact Person","Kimberly Elmore"],["Date Prepared","October 9, 2019"]],"caption_candidate":"Table 1: Cleerly, Inc. Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p4-t1","doc_id":"K190868","page_num":4,"bbox":[108.14,310.33,539.91,440.15],"n_rows":8,"n_cols":2,"columns":["Trade Name","Cleerly Labs (K190868)"],"rows":[["Trade Name","Cleerly Labs (K190868)"],["Common Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050 Picture Archiving And Communications\nSystem"],["",""],["Classification","Class II"],["Product Code","LLZ"],["Predicate Device","Autoplaque (K122429)"],["Reference Device","SurePlaque (K043111)"]],"caption_candidate":"Table 2: Cleerly Labs Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p6-t0","doc_id":"K190868","page_num":6,"bbox":[108.09,134.18,540.01,705.7],"n_rows":14,"n_cols":3,"columns":["Feature","Subject Device:","Predicate Device:"],"rows":[["Feature","Subject Device:","Predicate Device:"],["","Cleerly Labs (K190868)","Autoplaque (K122429)"],["","",""],["Operating Requirements","",""],["","",""],["Platform","Client-Server Google\nChrome Application","Windows OS"],["Image Input","DICOM 3.0 Compliant (or\nhigher)","DICOM 3.0 Compliant (or\nhigher)"],["Image Acquisition","CT Images","CT Images"],["Navigation Tools","● Window Width/Level\n● Zoom\n● Pan\n● Rotation\n● Tracker","● Window Width/Level\n● Zoom\n● Pan\n● Rotation\n● Tracker"],["Visualization / Edit\nTools","● Lumen Wall\n● Vessel Wall\n● Segment\n● Stenosis\n● Centerline\n● Plaque\n● Chronic Total Occlusion\n(CTO)\n● Stent\n● Exclude\n● Distance","● Lumen Wall\n● Vessel Wall\n● Segment\n● Stenosis\n● Centerline\n● Plaque\n● Exclude\n● Distance"],["2D Imaging","Yes","Yes"],["3D Imaging","Yes","Yes"],["Multiplanar\nReformat (MPR)","Yes","Yes"],["Segmentation of\nregion of interest","Manual and Semi-Automatic","Manual and Semi-Automatic"]],"caption_candidate":"Table 3: Device Features Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p7-t0","doc_id":"K190868","page_num":7,"bbox":[108.12,72.72,539.98,582.67],"n_rows":11,"n_cols":3,"columns":["Feature","Subject Device:","Predicate Device:"],"rows":[["Feature","Subject Device:","Predicate Device:"],["","Cleerly Labs (K190868)","Autoplaque (K122429)"],["","",""],["Plaque\nComposition\nOverlay","User-Modifiable\nThresholds:\n● Non-Calcified Plaque\n(NCP)\n● Calcified Plaque (CP)\n● Low-Density Non-\nCalcified Plaque (LD-\nNCP)","User-Modifiable\nThresholds:\n● Non-Calcified Plaque (NCP)\n● Calcified Plaque (CP)\n● Low-Density Non-Calcified\nPlaque (LD-NCP)"],["Quantification","",""],["","",""],["Hounsfield Unit\n(HU)","Yes","Yes"],["Distance\nMeasurements","● Vessel\n● Lesion\n● Length","● Vessel\n● Lesion\n● Length"],["Volumetric\nMeasurements","● Total Vessel\n● Total Lumen\n● Non-Calcified Plaque\n(NCP)\n● Low-Density Non-\nCalcified Plaque (LD-\nNCP)\n● Calcified Plaque (CP)\n● Total Plaque","● Total Vessel\n● Non-Calcified Plaque (NCP)\n● Low-Density Non-Calcified\nPlaque (LD-NCP)\n● Calcified Plaque (CP)\n● Total Plaque"],["Remodeling Index","Yes","Yes"],["Stenosis","● % Area Stenosis\n● % Diameter Stenosis","● % Area Stenosis\n● % Diameter Stenosis"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p8-t0","doc_id":"K190868","page_num":8,"bbox":[107.93,245.48,540.22,554.75],"n_rows":8,"n_cols":5,"columns":["Standards","Standard","","",""],"rows":[["Standards","Standard","","",""],["","","Title","Version","Date"],["No","Organization","","",""],["","","","",""],["PS 3.1-\n3.20","NEMA","Digital Imaging\nAnd\nCommunications In\nMedicine (DICOM)\nSet","2016","06-27-2016"],["62304","ANSI/AAMI/\nIEC","Medical device\nsoftware - Software\nl ife cycle processes","2006+AMD1:2015\nEdition 1.1","06-26-2016"],["14971","ISO","Medical Devices -\nApplication Of Risk\nManagement To\nMedical Devices","2007\nEdition 2.0","03-01-2007"],["62366-1","ANSI AAMI\nIEC","Medical Devices -\nPart 1: Application\nOf Usability\nEngineering To\nMedical Device","2015\nEdition 1.1","02-24-2015"]],"caption_candidate":"Table 4: Standards applied to device development","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190868-p9-t0","doc_id":"K190868","page_num":9,"bbox":[106.58,255.39,540.95,677.14],"n_rows":27,"n_cols":3,"columns":["Non-Clinical Testing:","",""],"rows":[["Non-Clinical Testing:","",""],["Safety, performance, cybersecurity and usability of Cleerly Labs have been evaluated and","",""],["verified in accordance with software pre-defined specifications and applicable","",""],["performance standards through software verification and validation testing.","",""],["","",""],["","• Verification and validation testing confirmed that the software requirements",""],["","fulfilled the pre-defined acceptance criteria.",""],["","• A Usability test was conducted with U.S. board certified radiologists and",""],["","technicians to ensure the clinical acceptability of the device.",""],["","• The machine learning algorithms were evaluated by comparing the output of the",""],["","software to that of the ground truth using multiple ground truthers.",""],["","• A side-by-side comparison testing was conducted to evaluate the simple rule-based",""],["","calculations as they compared to an already cleared device with a similar intended",""],["","use.",""],["","• A cybersecurity penetration testing was conducted to ensure that there were no",""],["","unidentified vulnerabilities and that the appropriate risk control measures were",""],["","implemented to protect from known vulnerabilities when the device is subject to a",""],["","source of threat.",""],["","",""],["The non-clinical verification and validation test results established that the device meets","",""],["its design requirements and intended use. During the development, potential hazards were","",""],["evaluated and controlled through risk management activities. The performance testing","",""],["demonstrates that the device meets all its specifications.","",""],["","",""],["Clinical Testing","",""],["No clinical testing was conducted to demonstrate safety or effectiveness as the device’s","",""],["non-clinical (bench) testing was sufficient to support the intended use of the device.","",""]],"caption_candidate":"Calcified Plaque Volume","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190896-p6-t0","doc_id":"K190896","page_num":6,"bbox":[43.68,96.38,539.86,762.22],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for ICH triage (K180647)","Subject Device\nAidoc Briefcase for CSF triage"],"rows":[["","Predicate Device\nAidoc Briefcase for ICH triage (K180647)","Subject Device\nAidoc Briefcase for CSF triage"],["Intended\nUse /\nIndications\nfor Use","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of non-enhanced\nhead CT images. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by flagging\nand communication of suspected positive\nfindings of pathologies in head CT images,\nnamely Intracranial Hemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nICH findings. Notifications\ninclude compressed preview images that\nare meant for informational purposes only\nand not intended for diagnostic use\neyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of cervical spine CT\nimages. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by flagging\nand communication of suspected positive\nfindings of linear lucencies in the cervical\nspine bone in patterns compatible with\nfractures.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a\nstandalone desktop application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are\nmeant for informational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User\npopulation","Radiologist","Radiologist"],["Anatomical\nregion of\ninterest","Head","Cervical spine"],["Data\nacquisition\nprotocol","Non-contrast head CT scan","Non-contrast cervical spine CT scans"],["View\nDICOM data","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient,\nstudy and current image"],["Segmentatio\nn of region\nof interest","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/\nPrioritization","Yes","Yes"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190896-p7-t0","doc_id":"K190896","page_num":7,"bbox":[43.68,72.24,539.86,230.78],"n_rows":3,"n_cols":3,"columns":["Preview\nimages","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases.","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],"rows":[["Preview\nimages","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases.","Presentation of a small, compressed, black\nand white preview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],["Alteration of\noriginal\nimage","No","No"],["Removal of\ncases from\nworklist\nqueue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K190896-p8-t0","doc_id":"K190896","page_num":8,"bbox":[117.1,85.66,478.34,209.31],"n_rows":8,"n_cols":18,"columns":["Parameter","","","N","","","Mean\nestimate","","","","Lower","","","Upper","","Median","",""],"rows":[["Parameter","","","N","","","Mean\nestimate","","","","Lower","","","Upper","","Median","",""],["","","","","","","","","","","Confidence","","","Confidence","","","",""],["","","","","","","","","","","Limit","","","Limit","","","",""],["","Time-to- exam-open in","","","48","","","58.4","","","45.3","","","71.4","","","51.5",""],["","the standard of care","","","","","","","","","","","","","","","",""],["","Time-to-notification of","","","48","","","3.9","","","3.8","","","4.1","","","3.9",""],["","BriefCase CSF","","","","","","","","","","","","","","","",""],["Difference","","","","48","","","54.4","","","-","","","-","","","47.9",""]],"caption_candidate":"Table 2. Time saving data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191026-p4-t0","doc_id":"K191026","page_num":4,"bbox":[62.62,621.16,546.7,742.96],"n_rows":6,"n_cols":4,"columns":["","Trade Name","","MEDIP PRO"],"rows":[["","Trade Name","","MEDIP PRO"],["","Regulation Number","","21 CFR 892.2050"],["","Regulation Name","","Picture archiving and communications system"],["","Regulation Class","","II"],["","Product Code","","LLZ"],["","Product Code Name","","System, Image Processing, Radiological"]],"caption_candidate":"4. Trade Name, Regulation Name, Classification [21 CFR 807.92(a)(2)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191026-p6-t0","doc_id":"K191026","page_num":6,"bbox":[69.67,163.22,537.61,766.66],"n_rows":10,"n_cols":4,"columns":["","Proposed Device","Predicate Device","Reference Device"],"rows":[["","Proposed Device","Predicate Device","Reference Device"],["K Number","K191026","K173619","K161841"],["Manufacturer","MEDICALIP.CO.,LTD","Materialise N.V.","3D Systems, Inc."],["Model","MEDIP PRO","Mimics inPrint","D2P"],["Product Code","LLZ","LLZ","LLZ"],["Indications\nfor Use","MEDIP PRO is intended for\nuse as a software interface\nand image segmentation\nsystem for the transfer of\nDICOM imaging\ninformation from a medical\nscanner to an output file. It\nis also used as pre-operative\nsoftware for treatment\nplanning.\nThe 3D printed models\ngenerated from the output\nfile are meant for non-\ndiagnostic use. MEDIP PRO\nshould be used in\nconjunction with other\ndiagnostic tools and expert\nclinical judgement.","Mimics inPrint is intended\nfor use as a software\ninterface and image\nsegmentation system for the\ntransfer of DICOM imaging\ninformation from a medical\nscanner to an output file. It\nis also used as pre-operative\nsoftware for treatment\nplanning. For this purpose,\nthe Mimics inPrint output\nfile can be used for the\nfabrication of physical\nreplicas of the output file\nusing traditional or additive\nmanufacturing methods.\nThe physical replica can be\nused for diagnostic purposes\nin the field of orthopedic,\nmaxillofacial and\ncardiovascular applications.\nMimics inPrint should be\nused in conjunction with\nother diagnostic tools and\nexpert clinical judgement.","The D2P software is\nintended for use as a\nsoftware interface and\nimage segmentation system\nfor the transfer of imaging\ninformation from a medical\nscanner such as a CT\nscanner to an output file. It\nis also intended as pre-\noperative software for\nsurgical planning.\n3D printed models\ngenerated from the output\nfile are meant for visual,\nnon-diagnostic use."],["Type of Use","Prescription Use","Prescription Use","Prescription Use"],["Component","Stand-alone software","Stand-alone software","Stand-alone software"],["Image\nSupport Type","DICOM imaging\ninformation from CT, MRI","DICOM imaging\ninformation from CT, MRI","DICOM imaging\ninformation from CT, MRI"],["Feature/\nFunctionality","Analysis & Measurement\nImage Enhancement\n2D/3D visualization\nSegmentation\n3D Rendering\nExporting STL data for 3D\nPrinting","Analysis & Measurement\nImage Enhancement\n2D/3D visualization\nSegmentation\n3D Rendering\nExporting STL data for 3D\nPrinting","Analysis & Measurement\nImage Enhancement\n2D/3D visualization\nSegmentation\n3D Rendering\nExporting STL data for 3D\nPrinting"]],"caption_candidate":"Table 1. Technological Characteristics Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p4-t0","doc_id":"K191125","page_num":4,"bbox":[108.04,572.95,532.52,714.1],"n_rows":7,"n_cols":6,"columns":["","Characteristics / Feature","","","ADAS 3D",""],"rows":[["","Characteristics / Feature","","","ADAS 3D",""],["General Features","","","","",""],["Operation System","","","Min. 64-bit Microsoft Windows 10\nRec. 64-bit Microsoft® Windows® 10","",""],["CPU Type","","","Min. Intel® Pentium® 4 or AMD Athlon™ 64, 3 GHz or faster or Intel® or\nAMD dual core 2 GHz or faster\nRec. Intel® Core i74790 K or equivalent","",""],["Memory","","","Min. 8 GB RAM\nRec. 16 GB RAM","",""],["Disk Space","","","Min. 100 GB free disk space for local study database\nRec. 250 GB free disk space or more for local study database","",""],["Graphics","","","Min. Microsoft® DirectX 10® capable graphics card or higher","",""]],"caption_candidate":"The following table lists the principal characteristics and features of the software:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p5-t0","doc_id":"K191125","page_num":5,"bbox":[108.02,116.42,532.54,671.86],"n_rows":9,"n_cols":2,"columns":["","Rec. Microsoft® DirectX 11® or capable graphics card or higher (for\nexample GeForce GT 730)"],"rows":[["","Rec. Microsoft® DirectX 11® or capable graphics card or higher (for\nexample GeForce GT 730)"],["Other","1,280 x 1,024 or higher screen resolution"],["Input file formats","DICOM/DICOMDIR"],["System Interface","-DICOM: Digital Imaging and Communications in Medicine (DICOM) is a\nstandard for handling, storing, printing, and transmitting information in\nmedical imaging.\n-LIEBRE Study: A LIEBRE study is a set of files storing each processed\ncase.\n- Navigation System File Format: Format for Navigation system.\nSnapshots: Snapshots in PNG format.\n-Videos: Videos in MPEG format and MPEG-1 video codec."],["User Interface","-Application workflow navigation tool.\n-Toolbar.\n-Working area.\n-Toolbox."],["Functional Features",""],["Functions","-Importing Cardiac Imaging (MRI/CTA) in DICOM format\nMRI Images support:\n• Visualization of the distribution of the enhancement in a three-\ndimensional (3D) chamber of the heart\n• Quantification of the total volume of the enhancement within the\nLeft Ventricle (LV) and the visualization of the enhancement area\nin multiple layers through the cardiac structure\n• Calculation, quantification and visualization of corridors of\nintermediate signal intensity enhancement in the LV\n• Quantification and visualization of the total area and distribution of\nthe enhancement within the Left Atrium (LA)\nCTA images support:\n• Quantification of LV wall thickness\n• Identification and Visualization of other 3D anatomical structures\n- The ADAS 3D exports data into industry standard file formats supported\nby catheter navigation systems"],["Data Storage","All analysis results can be saved and reloaded again for reviewing and/or\nexporting. The analysis results include the input DICOM image, 3D\nmodels, numerical values, snapshots and videos."],["Software Algorithms","-Left Ventricle Layer Computation\n-Left Atrium Layer Computation Algorithm\n-Enhancement Quantification algorithm\n-3D Corridor Detection Algorithm\n-Heart Anatomy Extraction algorithm\n-From Binary image to surface mesh algorithm\n-Left Ventricle Wall Thickness algorithm"]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p7-t0","doc_id":"K191125","page_num":7,"bbox":[86.34,143.78,577.03,712.18],"n_rows":12,"n_cols":9,"columns":["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],"rows":[["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],["","","","","MR-CT VVA","","","",""],["","","","","(Medis Medical Imaging Systems,","","","",""],["","","","","b.v.)","","","",""],["","Regulatory Data","","","","","","",""],["Regulatory\nClass","","Class II","Class II","","","Identical","",""],["Classificatio\nn name","","Radiological Image processing system","Radiological Image processing\nsystem","","","Identical","",""],["Regulation\nNumber","","21 CFR 892.2050","21 CFR 892.2050","","","Identical","",""],["Product\nCode","","LLZ","LLZ","","","Identical","",""],["FDA\nClearance","","Pending","510(k) cleared: K140587","","","-","",""],["","Use","","","","","","",""],["Indication\nfor Use","","ADAS 3D is indicated for use in the\nclinical setting to support the\nvisualization and analysis of cardiac\nMR and CTA images for patients with\ncardiovascular disease.\nADAS 3D is indicated for patients with\nmyocardial scar produced by ischemic\nor non-ischemic heart disease. ADAS\n3D processes MR and CTA images.\nThe quality and the resolution of the\noriginal images determines the\nquality and the accuracy of the data\nproduced by ADAS 3D.\nADAS 3D is indicated to be used by\nqualified medical professionals\n(cardiologists, electrophysiologists,\nradiologists or trained technicians)\nfor the calculation, quantification and\nvisualization of cardiac images. The\ndata produced by ADAS 3D is\nindicated to be used to support\nclinical decision making and should\nnot be used on an irrefutable basis or\nas the sole source of information for","MR-CT VVA is indicated for use in\nclinical settings where more\nreproducible than manually derived\nquantified results are needed to\nsupport the visualization and\nanalysis of MR and CT images of the\nheart and blood vessels for use on\nindividual patients with\ncardiovascular disease. Further, MR-\nCT VVA allows the quantification of\ncerebral spinal fluid in MR velocity-\nencoded flow images.\nWhen the quantified results\nprovided by MR-CT VVA are used in\na clinical setting on MR and CT\nimages of an individual patient, they\ncan be used to support the clinical\ndecision making for the diagnosis of\nthe patient. In this case, the results\nare explicitly not to be regarded as\nthe sole, irrefutable basis for clinical\ndiagnosis, and they are only\nintended for use by the responsible\nclinicians.","","","Similar to\npredicate\ndevice","",""]],"caption_candidate":"Comparison of the proposed devices with the predicate device is summarized in the following table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p8-t0","doc_id":"K191125","page_num":8,"bbox":[86.35,116.54,577.01,238.34],"n_rows":5,"n_cols":6,"columns":["Elements of\nComparison","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","",""],"rows":[["Elements of\nComparison","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","",""],["","","","MR-CT VVA","",""],["","","","(Medis Medical Imaging Systems,","",""],["","","","b.v.)","",""],["","clinical diagnosis or patient\ntreatment.\nADAS 3D is not intended to identify\nregions for catheter ablation or\ntreatment of arrhythmias.","","","",""]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p10-t0","doc_id":"K191125","page_num":10,"bbox":[86.33,116.54,577.05,712.9],"n_rows":13,"n_cols":9,"columns":["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],"rows":[["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],["","","","","MR-CT VVA","","","",""],["","","","","(Medis Medical Imaging Systems,","","","",""],["","","","","b.v.)","","","",""],["",""," Identification and\nvisualization of other 3D\nanatomical structures.\nADAS-3D exports information to\nmultiple industry standard file\nformats suitable for documentation\nand information sharing purposes.\nThe 3D data is exported into industry\nstandard file formats supported by\ncatheter navigation systems. It is\nintended to be used by qualified\nmedical professionals (cardiologists,\nelectrophysiologists, radiologists or\ntrained technicians) experienced in\nexamining and evaluating\ncardiovascular MR and CTA images as\npart of the comprehensive diagnostic\ndecision-making process. ADAS-3D is\na standalone software application.","","","","","",""],["","Technical characteristics","","","","","","",""],["General\ndescription","","Is a software solution for the\nvisualization and analysis of\ncardiovascular MR and CT images.","Is software intended to be used for\nthe visualization and analysis of MR\nand CT images of the heart and\nblood vessels.","","","Identical to\npredicate\ndevice","",""],["Mode of\naction","","Software Solution","Software Solution","","","Identical to\npredicate\ndevice","",""],["Operating\nSystem","","Windows","Windows","","","Identical to\npredicate\ndevice","",""],["Principles of\noperation","","Analysis of MR and CT images","Analysis of MR and CT images","","","Identical to\npredicate\ndevice","",""],["User\nInterface","","Mouse, Keyboard","Mouse, Keyboard","","","Identical to\npredicate\ndevice","",""],["Target\nPopulation","","Patients with myocardial scar.","Individual patients with\ncardiovascular disease.","","","Similar to\npredicate\ndevice","",""],["Anatomical","","Left Ventricle and Left Atrium","Left ventricle and Right Ventricle","","","Similar than","",""]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p11-t0","doc_id":"K191125","page_num":11,"bbox":[86.33,116.54,577.04,717.82],"n_rows":12,"n_cols":9,"columns":["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],"rows":[["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],["","","","","MR-CT VVA","","","",""],["","","","","(Medis Medical Imaging Systems,","","","",""],["","","","","b.v.)","","","",""],["sites","","","","","","predicate\ndevice","",""],["Conditions\nof use","","It is intended to be used by qualified\nmedical professionals (cardiologists,\nradiologists or trained technicians)\nexperienced in examining and\nevaluating cardiovascular MR and\nCTA images as part of the\ncomprehensive diagnostic decision-\nmaking process.","Must be used by Cardiologist,\nradiologist or trained technicians\nwho are qualified to perform cardiac\nanalysis.","","","Identical to\npredicate\ndevice","",""],["Images\nsupported","","Vendor independent DICOM MR/CT\nimages (specific requirements\ndepends on type of analysis, but\nimaging viewing is possible on all\nMR/CT images)","Vendor independent DICOM MR/CT\nimages (specific requirements\ndepend on type of analysis, but\nimaging viewing is possible on all\nMR/CT images)","","","Identical to\npredicate\ndevice","",""],["","Image Features","","","","","","",""],["Image\nassessment","","By visualization and analysis of the\nimages","By visualization and analysis of the\nimages","","","Identical to\npredicate\ndevice","",""],["Image\ndisplay and\nmanipulatio\nn","","- 2D slice review\n- 3D Multiplanar reconstruction\n- Pan/zoom; magnify; maximize and\nminimize; scroll through slice stack;\nadjust window level, contrast and\nbrightness.","- 2D slice review\n- 3D Multiplanar reconstruction\n- Pan/zoom; magnify; maximize and\nminimize; scroll through slice stack;\nadjust window level, contrast and\nbrightness.\n- Cine loop\n- Performing caliper measurements","","","Similar to\npredicate\ndevice","",""],["Result\nvisualization","","- Numerical\n- Graph\n- 2D view\n- 3D view","- Numerical\n- Graph\n- Bulls Eye View\n- 2D view\n- 3D view","","","Similar to\npredicate\ndevice","",""],["Export\ncapabilities","","- Snapshots as PNG\n- Videos as MPEG\n- Numerical data as TXT\n- Study data as an internal file format","- Images, movie frames, movies,\ngraphs, snapshots and reports in\nvarious file formats or as DICOM\nsecondary captures\n- Reports can be exported in TXT,\nPDF, HTML, XML and as DICOM SC\ndirectly to PACS","","","Similar to\npredicate\ndevice","",""]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p12-t0","doc_id":"K191125","page_num":12,"bbox":[86.33,116.54,577.04,643.66],"n_rows":10,"n_cols":9,"columns":["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],"rows":[["Elements of\nComparison","","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","","","",""],["","","","","MR-CT VVA","","","",""],["","","","","(Medis Medical Imaging Systems,","","","",""],["","","","","b.v.)","","","",""],["","","- 3D surface meshes as VTK/DIF","- All analysis results can be saved\nand reloaded again for reviewing\nand/or exporting","","","","",""],["","Performing Function Analysis","","","","","","",""],["","","- Quantification of LV wall thickness","Cardiac Function Quantification:\nmass, wall motion, wall thickness\nand wall thickening","","","Similar to\npredicate\ndevice","",""],["","","- Identification and Visualization of\nother 3D anatomical structures","Anatomy and tissue segmentation","","","Similar to\npredicate\ndevice","",""],["","","- Visualization of the distribution of\nthe enhancement in a three-\ndimensional (3D) chamber of the\nheart.\n- Quantification of the total volume\nof the enhancement within the Left\nVentricle (LV) and the visualization\nof the enhancement area in\nmultiple layers through the cardiac\nstructure.\n- Calculation, quantification and\nvisualization of corridors of\nintermediate, signal intensity\nenhancement in the LV.","Signal intensity analysis for the\nmyocardium and infarct sizing. Also\nreferred as DSI (Delayed Signal\nIntensity)","","","Similar to\npredicate\ndevice (see\ndetailed\ncomparison\nin the\nsection\nbelow)","",""],["","","None","MR parametric maps (such as T1,\nT2, T2* relaxation)","","","N/A\n(additional\nspecificatio\nns for the\npredicate\ndevice, not\nincluded on\nthe\nproposed\ndevice)","",""]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191125-p14-t0","doc_id":"K191125","page_num":14,"bbox":[86.35,116.54,577.01,198.02],"n_rows":5,"n_cols":6,"columns":["Elements of\nComparison","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","",""],"rows":[["Elements of\nComparison","Proposed Device\nADAS 3D\n(GALGO MEDICAL S.L)","","Predicate Device","",""],["","","","MR-CT VVA","",""],["","","","(Medis Medical Imaging Systems,","",""],["","","","b.v.)","",""],["","intermediate, signal intensity\nenhancement in the LV.","","","","device"]],"caption_candidate":"Section 5 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191171-p4-t0","doc_id":"K191171","page_num":4,"bbox":[72.24,414.54,539.76,530.64],"n_rows":3,"n_cols":4,"columns":["Device","510(k)\nNumber","Device Name","Manufacturer"],"rows":[["Device","510(k)\nNumber","Device Name","Manufacturer"],["Predicate Device","K150122","TomTec Arena TTA2","TomTec Imaging Systems,\nGmbH"],["Reference Device","K173780","EchoMD Automated\nEjection Fraction\nSoftware","Bay Labs, Inc."]],"caption_candidate":"3. Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191262-p4-t0","doc_id":"K191262","page_num":4,"bbox":[72.0,40.39,389.98,710.36],"n_rows":44,"n_cols":3,"columns":["510(k) Summary","",""],"rows":[["510(k) Summary","",""],["","",""],["In accordance with 21 CFR 80","","7.87(h) and (21 CFR 807.92) the 51"],["provided below.","",""],["","",""],["1. SUBMITTER","",""],["","",""],["","",""],["Applicant:","","EXINI Diagnostics AB"],["","","Ideon Science Park"],["","","Scheelevägen 27"],["","","223 70 Lund"],["","","Sweden"],["","",""],["Contact:","","Aseem Anand, Ph.D."],["","","Vice President"],["","","EXINI Diagnostics AB"],["","","Ideon Science Park, Scheelevägen"],["","","Lund, Sweden"],["","","Tel: +46706604084"],["","","aseem.anand@exini.com"],["","",""],["Submission Correspondent:","","Donna-Bea Tillman, Ph.D."],["","","Senior Consultant"],["","","Biologics Consulting"],["","","1555 King Street, Suite 300"],["","","(410) 531-6542"],["","","dtillman@biologicsconsulting.com"],["","",""],["Date Prepared:","","May 9, 2019"],["","",""],["2. DEVICE","",""],["","",""],["Device Trade Name:","a","BSI"],["Device Common Name:","P","icture Archiving and Communicati"],["","(","PACS)"],["Classification Name","2","1 CFR 892.2050 System, Image Pr"],["","R","adiological"],["Regulatory Class:","I","I"],["Product Code:","L","LZ"],["","",""],["3. PREDICATE","D","EVICE"],["","",""],["Predicate Device: EXINI (K","","122205)"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K191262-p8-t0","doc_id":"K191262","page_num":8,"bbox":[72.1,450.6,553.68,651.36],"n_rows":3,"n_cols":5,"columns":["Study\nNumber","Title","Objective","Design","Patients"],"rows":[["Study\nNumber","Title","Objective","Design","Patients"],["I","Phase 3 validation of the\nautomated Bone Scan Index\nassociation with overall\nsurvival in men with metastatic\ncastration-resistant prostate\ncancer","Association of aBSI with\nclinical outcome –\noverall survival,\nprogression free survival,\nopioid induced survival","Prospective Planned\nAnalysis – A multi-site\nstudy phase III: NTC\n01234311","Prostate\nCancer\n(N=721)"],["II","Optimizing Radiographic\nProgression Free Survival by\nProstate Cancer Working\nGroup (PCWG) Criteria using\nthe Automated Bone Scan\nIndex (aBSI)","Comparison of aBSI\nincrease against counting\nnumber of new lesions\n(by PCWG criteria) in\nradiographic progression","Retrospective study at\nMemorial Sloan Kettering\nCancer Center – single site","Prostate\nCancer\n(N=169)"]],"caption_candidate":"essential clinical outcomes.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191278-p4-t0","doc_id":"K191278","page_num":4,"bbox":[92.1,168.38,550.44,580.63],"n_rows":29,"n_cols":2,"columns":["","MultiModal Imaging Services Corporation (dba HealthLytix)"],"rows":[["","MultiModal Imaging Services Corporation (dba HealthLytix)"],["Submitter’s Name",""],["",""],["","4747 Executive Drive, Suite 820\nSan Diego, CA 92121"],["Submitter’s Address",""],["",""],["","+001.619.340.0503"],["Submitter Telephone",""],["",""],["","Stephen Kosnosky PMP, ASQ CMQ/OE"],["Contact Name",""],["",""],["Date Prepared","Sept 18, 2019"],["Trade or Proprietary","RSI-MRI+"],["Name",""],["Common or Usual","Picture Archiving and Communications System"],["Name",""],["","System, Image Processing, Radiological) (21 CFR 892.2050)"],["Classification Name",""],["",""],["","Class II"],["Regulatory Class",""],["",""],["","LLZ"],["Product Code",""],["",""],["","Eigen ProFuse CAD (K173744)\nAs of submission date this predicate device has not been subject to\na design-related recall.\nNo reference devices were used in this submission."],["Predicate Device",""],["",""]],"caption_candidate":"Submission Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191278-p7-t0","doc_id":"K191278","page_num":7,"bbox":[134.49,117.19,477.96,565.92],"n_rows":21,"n_cols":3,"columns":["Function","RSI-MRI+\n(Subject Device)","ProFuse CAD"],"rows":[["Function","RSI-MRI+\n(Subject Device)","ProFuse CAD"],["","","(K173744)"],["Product Code","LLZ","LLZ"],["DICOM Input","DICOM compatible","DICOM compatible"],["Diffusion – series","Post-processing analysis of\nDiffusion MRI data with\nmulti-compartment RSI\nmodel.","Post-processing analysis of\nDiffusion MRI data with single\ncompartment DWI model."],["analysis","",""],["","",""],["Segmentation","Automated Prostate\nSegmentation: RSI-MRI+\nsoftware provides automatic\nprostate segmentation,\nquantification, and reporting\nof derived image metrics.","Manual Prostate\nSegmentation: ProFuse CAD\nhas a marking feature that\nallows the user to manually\nsegment the prostate and\nprovides quantification and\nreporting of derived image\nmetrics."],["","",""],["Co-Registration","Does not contain this\nfunctionality.","Performs co-registration of\nimages."],["","",""],["Fusion","Automated fusion of derived\nDiffusion MRI data with\nanatomical MRI data","Automated fusion of derived\nDiffusion MRI data with\nanatomical MRI data in\naddition to other data sources"],["","",""],["Report","Yes","Yes"],["DICOM output","DICOM compatible","DICOM compatible"],["Data Source","MRI Scanner","MRI Scanner, CT Scanner, PET\nScanner"],["","",""],["Safety","Display/measurement data\ncan be viewed, accepted, or\nrejected by a physician.","Display/measurement data\ncan be viewed, accepted, or\nrejected by a physician."],["","",""],["Environment for","Hospital, Clinic, Medical\nOffice","Hospital, Clinic, Medical Office,\nHome Office"],["use","",""]],"caption_candidate":"Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191384-p4-t0","doc_id":"K191384","page_num":4,"bbox":[72.48,36.48,539.76,72.12],"n_rows":2,"n_cols":2,"columns":["Document ID and Title","Version:"],"rows":[["Document ID and Title","Version:"],["RSL-D-RC-2D Traditional 510(k) Submission RayCare 2.3","2.0"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191384-p5-t0","doc_id":"K191384","page_num":5,"bbox":[72.48,36.48,539.76,72.12],"n_rows":2,"n_cols":2,"columns":["Document ID and Title","Version:"],"rows":[["Document ID and Title","Version:"],["RSL-D-RC-2D Traditional 510(k) Submission RayCare 2.3","2.0"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191550-p4-t0","doc_id":"K191550","page_num":4,"bbox":[56.73,105.32,554.52,632.57],"n_rows":15,"n_cols":2,"columns":["Submitter","Fluidda Inc."],"rows":[["Submitter","Fluidda Inc."],["Submission Number","K191550"],["Address","750 N San Vicente Blvd Ste. 800 West, West Hollywood, CA\n90069, USA"],["Contact Person","Anjali Nair\nRegulatory Affairs Specialist at Fluidda Inc.\nTel: +91 9324857705\nEmail: anjali.nair@fluidda.com"],["Date Prepared","January 28, 2020"],["Trade Name","Broncholab"],["Common Name","Quantitative CT analysis system"],["Classification Name","Computed Tomography X-Ray System"],["Regulation Number","21 CFR 892.1750"],["Classification","Class II"],["Product Code","JAK"],["Panel","Radiology"],["Legally marketed Primary Predicate Device","Vida Pulmonary Workstation 2 (PW2), Vida Diagnostics\n(K083227)"],["Predicate Regulation Number","21 CFR 892.1750"],["Predicate Classification & Product Code","Class II; Product Code- JAK\nThe predicate device has not been subject to a design-related\nrecall."]],"caption_candidate":"Section 5 - 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191550-p10-t0","doc_id":"K191550","page_num":10,"bbox":[56.77,544.77,554.48,691.02],"n_rows":3,"n_cols":2,"columns":["Imaging parameters","Equivalence study"],"rows":[["Imaging parameters","Equivalence study"],["Scanner manufacture","GE Healthcare; Philips; Siemens"],["Scanner types","LightSpeed VCT; LightSpeed Pro 16; LightSpeed 16; Revolution CT;\nRevolution EVO; iCT 256; Emotion 16; SOMATOM Definition AS; SOMATOM\nForce; SOMATOM Definition Flash; Brilliance 64; Definition; Definition AS+;\nDiscovery CT750 HD; Sensation 64"]],"caption_candidate":"datasets used for the performance testing are:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p4-t0","doc_id":"K191556","page_num":4,"bbox":[66.6,489.54,517.38,532.74],"n_rows":3,"n_cols":2,"columns":["Manufacturer Name","Zebra Medical Vision Ltd."],"rows":[["Manufacturer Name","Zebra Medical Vision Ltd."],["Devices Trade Name","HealthPNX"],["510(k) Number","K190362"]],"caption_candidate":"The red dot™ device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t0","doc_id":"K191556","page_num":8,"bbox":[66.62,113.76,525.15,263.4],"n_rows":5,"n_cols":6,"columns":["Disease Class","Total\nNumber\nof Cases","Site 1\nCases","Site 2\nCases","Site 3\nCases","Site 4\nCases"],"rows":[["Disease Class","Total\nNumber\nof Cases","Site 1\nCases","Site 2\nCases","Site 3\nCases","Site 4\nCases"],["PNX, Non-normal\nControl, Normal Control","888","419","319","77","73"],["PNX","299","177","95","14","13"],["Non-normal Control","167","50","50","36","31"],["Normal Control","422","192","174","27","29"]],"caption_candidate":"Behold.ai red dot™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t1","doc_id":"K191556","page_num":8,"bbox":[195.06,118.5,251.34,159.9],"n_rows":3,"n_cols":5,"columns":["","","Total","",""],"rows":[["","","Total","",""],["","Number","","",""],["","of Cases","","",""]],"caption_candidate":"Behold.ai red dot™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t2","doc_id":"K191556","page_num":8,"bbox":[262.14,125.4,318.42,153.0],"n_rows":2,"n_cols":3,"columns":["","Site 1",""],"rows":[["","Site 1",""],["","Cases",""]],"caption_candidate":"Total","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t3","doc_id":"K191556","page_num":8,"bbox":[329.28,125.4,385.56,153.0],"n_rows":2,"n_cols":3,"columns":["Site 2","",""],"rows":[["Site 2","",""],["","Cases",""]],"caption_candidate":"Total","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t4","doc_id":"K191556","page_num":8,"bbox":[396.36,125.4,452.64,153.0],"n_rows":2,"n_cols":3,"columns":["","Site 3",""],"rows":[["","Site 3",""],["","Cases",""]],"caption_candidate":"Total","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p8-t5","doc_id":"K191556","page_num":8,"bbox":[463.44,125.4,519.78,153.0],"n_rows":2,"n_cols":3,"columns":["","Site 4",""],"rows":[["","Site 4",""],["","Cases",""]],"caption_candidate":"Total","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191556-p9-t0","doc_id":"K191556","page_num":9,"bbox":[66.71,122.0,516.49,212.04],"n_rows":6,"n_cols":12,"columns":["888 Cases","","","","","","","","","","",""],"rows":[["888 Cases","","","","","","","","","","",""],["Processing\nTime (seconds)","","","Mean","Standard\nDev","","95% Lower","","","95% Upper","","Median"],["","","","","","","Confidence","","","Confidence","",""],["","","","","","","Limit","","","Limit","",""],["","red-dot™","","13.8","10.9","13.0","","","14.5","","","8.56"],["","processing time","","","","","","","","","",""]],"caption_candidate":"Behold.ai red dot™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191585-p8-t0","doc_id":"K191585","page_num":8,"bbox":[63.86,86.16,531.7,616.03],"n_rows":3,"n_cols":4,"columns":["","New Device","Predicate Device","Predicate Device"],"rows":[["","New Device","Predicate Device","Predicate Device"],["","","(Secondary)","(Primary)"],["","for the dimensions of vessels\nand structures.\nCalcium quantification and\nscoring.\nVarious visualization\ntechniques: 2D/3D/4D\nvisualization, MPR, Curved\nMPR, Stretched MPR, MIP,\nMinIP, Raysum and MAR.\nCapture and Report.","Support is provided for digital\nimage processing to derive\nmetadata or new images from input\nimage sets, for internal use or for\nforwarding to other devices using\nthe DICOM protocol. Image\nprocessing tools are provided to\nextract metadata to derive\nparametric images from\ncombinations of multiple input\nimages, such as temporal phases, or\nimages co-located in space but\nacquired with different imaging\nparameters, such as different MR\npulse sequences, or different CT\nimage parameters (e.g. dual\nenergy).\niNtuition is designed for use by\nhealthcare professionals and is\nintended to assist the physician in\ndiagnosis, who is responsible for\nmaking all final patient\nmanagement decisions.\nInterpretation of mammographic\nimages or digitized film screen\nimages is supported only when the\nsoftware is used without\ncompression and with an FDA-\nApproved monitor that offers at\nleast 5Mpixel resolution and meets\nother technical specifications\nreviewed and accepted by the FDA.\niNtuitionMOBILE provides\nwireless and portable access to\nmedical images. This device is not\nintended to replace full\nworkstations and should be used\nonly when there is no access to a\nworkstation. Not intended for\ndiagnostic use when used via a web\nbrowser or mobile device.","Measurement and annotation\ntools\nReporting tools"]],"caption_candidate":"TeraRecon, Inc. iNtuition-Structural Heart Module 510(K)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191585-p8-t1","doc_id":"K191585","page_num":8,"bbox":[63.86,629.74,531.7,769.54],"n_rows":3,"n_cols":4,"columns":["Technical Characteristics","","",""],"rows":[["Technical Characteristics","","",""],["Data Type","- CT, MR, Nuc, PET,\nAngio, US/Echo,\nSPECT,\n- CR/DR Review\n- 2D, 3D, 4D Medical\nImage review including\ncine play","- CT, MR, Nuc, PET, Angio,\nUS/Echo, SPECT, CR/DR\nReview\n- 2D, 3D, 4D Medical Image\nreview including cine play","- CT data in DICOM\nformat (vendor\nindependent)"],["Input Patient Data","- Manual through\nkeyboard/mouse\n- Command line interface","- Manual through\nkeyboard/mouse\n- Command line interface","- Manual through\nkeyboard/mouse\n- Command line interface"]],"caption_candidate":"browser or mobile device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191585-p9-t0","doc_id":"K191585","page_num":9,"bbox":[63.74,72.24,531.84,709.78],"n_rows":3,"n_cols":4,"columns":["Study list\nfunctionality","- Importing\n- Exporting\n- Deleting\n- Search\n- Anonymization","- Importing\n- Exporting\n- Deleting\n- Search\n- Anonymization","- Exporting\n- Deleting\n- Anonymizing (no\nautomatic deletion of\noriginal patient data)\n- Search"],"rows":[["Study list\nfunctionality","- Importing\n- Exporting\n- Deleting\n- Search\n- Anonymization","- Importing\n- Exporting\n- Deleting\n- Search\n- Anonymization","- Exporting\n- Deleting\n- Anonymizing (no\nautomatic deletion of\noriginal patient data)\n- Search"],["Centerline\nExtraction and","- Automatic and manual\ncenterlines\n- Centerline edits and\nrefinements.\n- Vessel Analysis\n- Automatic and manual\nsegmentation of\nstructures\n- Segmentation editing","- Automatic and manual\ncenterlines\n- Centerline edits and\nrefinements.\n- Vessel Analysis\n- Automatic and manual\nsegmentation of structures\n- Segmentation editing","- Realign orthogonal\nMPR's\n- Segmentation toolset:\n- Automatic segmentation\n- Automatic centerline\n- Manual centerline\n- Centerline editing\n- Undo/Redo operations\n- Volume sculpting"],["Image Assessment","- Linear (length, diameter,\nperimeter), distance pair,\nangular and ROI\nmeasurements\n- Area measurements\n- Volume measurements\nincluding volumetric\nhistogram, VOI and TVA\nfor Time Volume\nAnalysis for heart\nchamber segmentation\nand analysis\n- C-arm angulation\ncalculation\n- Text and arrow\nannotations\n- Anatomy ID (Landmark\nLabel Selection)\n- Calcium scoring for\nassessment of calcium in\nthe aortic root\n- Calcium scoring for\nassessment of calcium in\nthe coronary arteries\n- Segmentation and\nanalysis of coronary\nartery tree centerline\n- Synchronized side-by-\nside review\n- Synchronized center of\nrotation viewing\n- Findings workflow for\ntemporal correlative\nanalysis\n- 2D/3D Batch movie tool\nand export","- Linear (length, diameter,\nperimeter), distance pair,\nangular and ROI\nmeasurements\n- Area measurements\n- Volume measurements\nincluding volumetric\nhistogram, VOI and TVA for\nTime Volume Analysis for\nheart chamber segmentation\nand analysis\n- C-arm angulation calculation\n- Text and arrow annotations\n- Anatomy ID (Landmark Label\nSelection)\n- Calcium scoring for\nassessment of calcium in the\naortic root\n- Calcium scoring for\nassessment of calcium in the\ncoronary arteries\n- Segmentation and analysis of\ncoronary artery tree centerline\n- Synchronized side-by- side\nreview\n- Synchronized center of\nrotation viewing\n- Findings workflow for\ntemporal correlative analysis\n- 2D/3D Batch movie tool and\nexport","- Linear (length and\ndiameter), angular and\nROI measurements\n- Volume measurements\n- C-arm angulation\ncalculation\n- Text and arrow\nannotations\n- Calcium scoring for\nassessment of calcium in\nthe aortic root\n- Calcium scoring for\nassessment of calcium in\nthe coronary arteries\n- Segmentation and\nanalysis of coronary\nartery tree centerline"]],"caption_candidate":"TeraRecon, Inc. iNtuition-Structural Heart Module 510(K)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191585-p10-t0","doc_id":"K191585","page_num":10,"bbox":[63.78,85.02,531.78,571.99],"n_rows":7,"n_cols":4,"columns":["","New Device","Predicate Device","Predicate Device"],"rows":[["","New Device","Predicate Device","Predicate Device"],["","","(Secondary)","(Primary)"],["","","",""],["Image Assessment\nRendering","- Volume rendering, MIP,\nMPR, MinIP, Raysum\n(ThickMPR)\n- 3D triangulation\n- Perspective endoluminal\nview\n- Medial Axial Reformat\n(MAR)\n- Curved Planar Reformat\n(CPR)\n- Double-oblique MIP and\nMPR\n- Image enhancement\nfilters\n- Synchronized side-by-\nside viewing\n- Synchronized center of\nrotation viewing\n- Cube View\n- Workflow templates\n- Multi-Mask Display\n(multi- object display)\n- User-defined\nmeasurement protocols\n- Editing tools: crop, cut,\nfree- hand","- Volume rendering,\n- MIP, MPR, MinIP,\n- Raysum (ThickMPR)\n- 3D triangulation\n- Perspective endoluminal view\n- Medial Axial Reformat (MAR)\n- Curved Planar Reformat\n(CPR)\n- Double-oblique MIP and MPR\n- Image enhancement filters\n- Synchronized side-by- side\nviewing\n- Synchronized center of\nrotation viewing\n- Cube View\n- Workflow templates\n- Multi-Mask Display (multi-\nobject display)\n- User-defined measurement\nprotocols\n- Editing tools: crop, cut, free-\nhand","- Orthogonal, oblique,\ndouble oblique, curved,\ncross-curved, stretched\n- MPR rendering\n- MIP, AveIP, MinIP and\ncolor volume slabs\n- MIP volume rendering\n- Color volume rendering\n- Grayscale volume\nrendering\n- 2D slice review and stack\ncomparison\n- 4D cine\n- Interactive VOI clipping\n- Multi-tissue color and\nopacity control\n- Active presets\n- User-defined presets"],["Storage of Results","- Structured reporting with\nxml, text, xls output\n- Word and html report\n- DICOM SC\n- Workflow scenes: restore\nsaved state","- Structured reporting with xml,\ntext, xls output\n- Word and html report\n- DICOM SC\n- Workflow scenes: restore\nsaved state","-\n- Printout\n- Session state\n- PDF format\n- DICOM PDF report"],["Conferencing and\nCollaboration","Conferencing and\nCollaboration","Conferencing and Collaboration","N/A"],["Operating System","Microsoft Windows","Microsoft Windows","Microsoft Windows"]],"caption_candidate":"TeraRecon, Inc. iNtuition-Structural Heart Module 510(K)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191647-p5-t0","doc_id":"K191647","page_num":5,"bbox":[72.26,456.72,539.74,655.92],"n_rows":6,"n_cols":7,"columns":["Feature","Currently Marketed\nPredicate QLAB\n(Predicate Device -\nK181264)","","Currently Marketed","","Proposed QLAB 3D\nAuto RV\n(Modified Device)","Explanation of\nDifferences"],"rows":[["Feature","Currently Marketed\nPredicate QLAB\n(Predicate Device -\nK181264)","","Currently Marketed","","Proposed QLAB 3D\nAuto RV\n(Modified Device)","Explanation of\nDifferences"],["","","","Reference TomTec-Arena","","",""],["","","","TTA2","","",""],["","","","(Reference Device -","","",""],["","","","K150122)","","",""],["Indication\nfor Use","QLAB Quantification\nsoftware is a software\napplication package.\nIt is designed to view\nand quantify image\ndata acquired on\nPhilips ultrasound\nsystems.","Indications for use of\nTomTec-Arena TTA2\nsoftware are quantification\nand reporting of\ncardiovascular, fetal,\nabdominal structures and\nfunction of patients with\nsuspected disease to\nsupport the physicians in\nthe diagnosis","","","Same as QLAB\n(K181264)","Not applicable"]],"caption_candidate":"tables below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191647-p6-t0","doc_id":"K191647","page_num":6,"bbox":[62.91,120.96,575.62,717.0],"n_rows":9,"n_cols":7,"columns":["Feature","Currently Marketed\nPredicate QLAB\nHeartModel (K181264)","","Currently Marketed","","Proposed QLAB 3D\nAuto RV (Modified\nDevice)","Explanation of\nDifferences"],"rows":[["Feature","Currently Marketed\nPredicate QLAB\nHeartModel (K181264)","","Currently Marketed","","Proposed QLAB 3D\nAuto RV (Modified\nDevice)","Explanation of\nDifferences"],["","","","Reference TomTec-","","",""],["","","","Arena TTA2 4D RV","","",""],["","","","(Reference Device -","","",""],["","","","K150122)","","",""],["Application\ndescription","The HeartModel provides\nsemi-automatic 3D\nanatomical border\ndetection and\nidentification of the heart\nchambers for the end-\ndiastole (ED) and end-\nsystole (ES) cardiac\nphases.","The TOMTEC\nARENA 4D RV-\nFunction provides a\nmorphological and\nfunctional assessment\nof the right ventricle\nbased on a surface\nmodel of the RV.","","","The 3D Auto RV Q-App\nis an integration of the\nsegmentation engine of\nthe QLAB HeartModel\nand the TomTec-Arena\n4D RV-Function thereby\nproviding a dynamic\nRight Ventricle clinical\nfunctionality.","Integrates HeartModel\nauto-segmentation\ntechnology with\nTomTec Arena’s 4D-\nRV algorithm for RV\nborder placement."],["Quantification\nTechnology of\nRV","Semi-automatic border\ndetection and\nidentification of LV and\nLA chambers","Functional assessment\nof RV based on a RV\nsurface model.","","","Integrates HeartModel\nauto-segmentation\ntechnology with TomTec\nArena’s 4D-RV\nalgorithm for RV border\nplacement","Anatomical\nenhancement by Right\nVentricle"],["2D RV\nmeasurement\nparameters","No RV parameters"," RVDd base (RVD1):\nRight Ventricle\nDistance base (mm)\n RVDd mid (RVD2):\nRight Ventricle\nDistance medial\n(mm)\n RVLd (RVD3): Right\nVentricle Distance\nLongitudinal (mm)\n TAPSE: Tricuspid\nannular plane systolic\nexcursion (mm)\n FAC: Fractional area\nchange (%)\n RVLS (free wall):\nright ventricular\nlongitudinal strain\n(free wall) (%)\n RVLS\n(Septum): right\nventricular\nlongitudinal strain\n(septum) (%)","",""," RVDd base (RVD1):\nRight Ventricle\nDistance base (mm)\n RVDd mid (RVD2):\nRight Ventricle\nDistance medial (mm)\n RVLd (RVD3): Right\nVentricle Distance\nLongitudinal (mm)\n TAPSE: Tricuspid\nannular plane systolic\nexcursion (mm)\n FAC: Fractional area\nchange (%)\n RVLS (free wall): right\nventricular longitudinal\nstrain (free wall) (%)\n RVLS (Septum): right\nventricular longitudinal\nstrain (septum) (%)","Identical to 4D RV\npredicate"],["2D RV\ncalculated\nparameters","No RV parameters"," Global strain\n TAPSE: MMode\nmeasurement for\nmovement of TV\nbetween ED and ES","",""," Global strain\n TAPSE: MMode\nmeasurement for\nmovement of TV\nbetween ED and ES","Identical to 4D RV\npredicate"]],"caption_candidate":"Modific ations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191647-p7-t0","doc_id":"K191647","page_num":7,"bbox":[62.88,120.84,575.64,628.8],"n_rows":4,"n_cols":5,"columns":["",""," RV distance\nmeasurements: 3\ndistance\nmeasurements in the\nRV A4C in ED.\n RVD1: maximal\nshort-axis dimension\nin the basal one third\nof the right ventricle\n RVD2: distance is\nmeasured on 50% of\nRVLd (RVD3) and\nparallel to the RVD1\n RVD3: base–apex\nlength\n Fractional area\nchange (FAC)"," RV distance\nmeasurements: 3\ndistance measurements\nin the RV A4C in ED.\n RVD1: maximal short-\naxis dimension in the\nbasal one third of the\nright ventricle\n RVD2: distance is\nmeasured on 50% of\nRVLd (RVD3) and\nparallel to the RVD1\n RVD3: base–apex\nlength\n Fractional area change\n(FAC)",""],"rows":[["",""," RV distance\nmeasurements: 3\ndistance\nmeasurements in the\nRV A4C in ED.\n RVD1: maximal\nshort-axis dimension\nin the basal one third\nof the right ventricle\n RVD2: distance is\nmeasured on 50% of\nRVLd (RVD3) and\nparallel to the RVD1\n RVD3: base–apex\nlength\n Fractional area\nchange (FAC)"," RV distance\nmeasurements: 3\ndistance measurements\nin the RV A4C in ED.\n RVD1: maximal short-\naxis dimension in the\nbasal one third of the\nright ventricle\n RVD2: distance is\nmeasured on 50% of\nRVLd (RVD3) and\nparallel to the RVD1\n RVD3: base–apex\nlength\n Fractional area change\n(FAC)",""],["3D RV\nmeasurement\nparameters","No RV parameters"," EDV: End-diastolic\nVolume\n EDVI: End-diastolic\nVolume Index\n ESV: End-systolic\nVolume\n ESVI: End-systolic\nVolume Index\n SV: Stroke Volume\n EF: Ejection Fraction"," EDV: End-diastolic\nVolume\n EDVI: End-diastolic\nVolume Index\n ESV: End-systolic\nVolume\n ESVI: End-systolic\nVolume Index\n SV: Stroke Volume\n EF: Ejection Fraction","EDV measurement\nincludes semi-\nautomatic function\nintroduced in\n3DAutoRV. All other\nmeasurements identical\nto 4D RV predicate."],["3D RV\ncalculated\nparameters","No RV parameters"," EF: Ejection Fraction\n SV: Stroke Volume"," EF: Ejection Fraction\n SV: Stroke Volume","Identical to 4D RV\npredicate"],["Contour\nGeneration","3D surface model is\ncreated semi-\nautomatically without\nuser interaction.\nUser is required to edit,\naccept or reject the\ncontours","3D surface model is\ncreated based on user\ndefined anatomical\nlandmarks. User is\nable to edit the contour\nof the surface model.","3D surface model is\ncreated semi-\nautomatically using\nmachine learning\nalgorithms without user\ninteraction. User is able\nto edit, accept or reject\nthe contours or the\nanatomical landmarks.","Workflow\nimprovements for user\nconvenience.\nAlgorithm Training\nprocedure is same\nbetween the subject and\nthe predicate\nHeartModel, except\nthat the algorithm is\napplied to LV in\nHeartModel, while to\nRV in subject 3D auto\nRV."]],"caption_candidate":"Modific ations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191688-p4-t0","doc_id":"K191688","page_num":4,"bbox":[83.41,102.56,543.73,584.0],"n_rows":16,"n_cols":2,"columns":["Submitter’s Name:","Subtle Medical, Inc."],"rows":[["Submitter’s Name:","Subtle Medical, Inc."],["Address:","883 Santa Cruz Ave, Suite 205\nMenlo Park, CA 94025"],["Contact Person:","Jared Seehafer"],["Title:","Regulatory Consultant"],["Telephone Number:","415-857-9554"],["Fax Number:","415-367-1279"],["Email:","jared@enzyme.com"],["Date Summary Prepared:","24-JUN-2019"],["Device Proprietary Name:","SubtleMR"],["Model Number:","V 1.0.0"],["Common Name:","SubtleMR"],["Regulation Number:","21 CFR 892.2050"],["Regulation Name:","System, Image Processing, Radiological"],["Product Code:","LLZ"],["Device Class:","Class II"],["Predicate Device","Trade name: ZOOM\nManufacturer: Zetta Medical Technologies, LLC.\n1313 Ensell Road\nLake Zurich, IL 60047\nRegulation Number: 21 CFR 892.2050\nRegulation Name: System, Image Processing,\nRadiological\nDevice Class: Class II\nProduct Code: LLZ\n510(k) Number: K172768\n510(k) Clearance Date: April 24, 2018"]],"caption_candidate":"Table 5-1. Subject Device Overview.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191688-p5-t0","doc_id":"K191688","page_num":5,"bbox":[95.58,465.97,525.42,690.85],"n_rows":7,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Physical\nCharacteristics","Software package that operates on\noff-the-shelf hardware","Same"],["Computer","PC Compatible","Linux Compatible"],["DICOM\nStandard\nCompliance","The software processes DICOM\ncompliant image data","Same"],["Operating\nSystem","Windows","Linux"],["Modalities","MRI","Same"],["User Interface","The software is designed for use\non a radiology workstation.","None – enhanced images are\nviewed on existing PACS\nworkstations"]],"caption_candidate":"Table 5-2. Summary of Technological Characteristics Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191688-p6-t0","doc_id":"K191688","page_num":6,"bbox":[96.12,41.71,525.96,447.55],"n_rows":3,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Image\nEnhancement\nAlgorithm\nDescription","ZOOM image enhancement\nsoftware implements a noise\nreduction algorithm using\nwavelets and image guided\nfiltering. Original images are\ndecomposed into different\nwavelet sub bands and noise in\neach band is a soft threshold. De-\nnoised images are reconstructed\nfrom soft thresholded images\nusing inverse wavelet transform.","SubtleMR software implements\nan image enhancement\nalgorithm using convolutional\nneural network based filtering.\nOriginal images are enhanced\nby running through a cascade of\nfilter banks, where thresholding\nand scaling operations are\napplied. Separate neural\nnetwork based filters are\nobtained for noise reduction\nand sharpness increase. The\nparameters of the filters were\nobtained through an image-\nguided optimization process."],["Workflow","The software, which is installed\non a remote computer, receives\nDICOM images from MRI host\ncomputer, automatically\nprocesses the received images and\nsends the enhanced images to a\nPACS server. Enhanced images\nexist in conjunction to the original\nimages.","The software operates on\nDICOM files on the file system,\nenhances the images, and stores\nthe enhanced images on the file\nsystem. The receipt of original\nDICOM image files and\ndelivery of enhanced images as\nDICOM files depends on other\nsoftware systems. Enhanced\nimages co-exist with the\noriginal images."]],"caption_candidate":"Subtle Medical, Inc. 510(k) - SubtleMR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191713-p16-t0","doc_id":"K191713","page_num":16,"bbox":[99.01,290.62,548.75,487.68],"n_rows":15,"n_cols":3,"columns":["Test Description:","Reference:","Section:"],"rows":[["Test Description:","Reference:","Section:"],["Calibration Process","Doc#IK08-0118","7.1"],["Power- On","Doc#IK08-0118","7.2"],["ROI Control Panel","Doc#IK08-0118","7.3"],["Host System Communication via Relays","Doc#IK08-0118","7.4"],["Mag Modes","Doc#IK08-0118","7.5"],["Responses to MX- Ikomed Serial Link","Doc#IK08-0118","7.6"],["Responses to Abnormal Condition","Doc#IK08-0118","7.7"],["Responses to Abnormal Signals","Doc#IK08-0118","7.8"],["Video Bypass Button","Doc#IK08-0118","7.9"],["Housekeeping Task","Doc#IK08-0118","7.10"],["Auto ROI Processor Access","Doc#IK08-0118","7.11"],["Video Quality","Doc#IK08-0118","7.12"],["Shutter Blade Position Consistency","Doc#IK08-0118","7.13"],["Shutter Vibration","Doc#IK08-0118","7.14"]],"caption_candidate":"are listed in Table 1 below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191928-p7-t0","doc_id":"K191928","page_num":7,"bbox":[105.44,164.19,532.12,728.49],"n_rows":6,"n_cols":5,"columns":["ITEM","","Proposed Device","Predicate Device K182624",""],"rows":[["ITEM","","Proposed Device","Predicate Device K182624",""],["","Regulatory Information","","",""],["Regulation No.","","21CFR 892.2050","21CFR 892.2050",""],["Product Code","","QKB","LLZ",""],["Class","","II","II",""],["Indication for\nUse","","It is used by radiation oncology\ndepartment to register multimodality\nimages and segment (non-contrast) CT\nimages, to generate needed information\nfor treatment planning, treatment\nevaluation and treatment adaptation.","MIM software is used by trained medical\nprofessionals as a tool to aid in\nevaluation and information management\nof digital medical images. The medical\nimage modalities include, but are not\nlimited to, CT, MRI, CR, DX, MG, US,\nSPECT, PET and XA as supported by\nACR/NEMA DICOM 3.0. MIM assists\nin the following indications:\n• Receive, transmit, store, retrieve,\ndisplay, print, and process medical\nimages and DICOM objects.\n• Create, display and print reports from\nmedical images.\n• Registration, fusion display, and\nreview of medical images for diagnosis,\ntreatment evaluation, and treatment\nplanning.\n• Evaluation of cardiac left ventricular\nfunction and perfusion, including left\nventricular enddiastolic volume,\nend-systolic volume, and ejection\nfraction.\n• Localization and definition of objects\nsuch as tumors and normal tissues in\nmedical images.\n• Creation, transformation, and\nmodification of contours for applications\nincluding, but not limited to, quantitative\nanalysis, aiding adaptive therapy,\ntransferring contours to radiation therapy\ntreatment planning systems, and",""]],"caption_candidate":"Table 1 Comparison of Technology Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191928-p8-t0","doc_id":"K191928","page_num":8,"bbox":[105.43,118.74,532.13,729.9],"n_rows":10,"n_cols":10,"columns":["ITEM","","Proposed Device","","","","Predicate Device K182624","","",""],"rows":[["ITEM","","Proposed Device","","","","Predicate Device K182624","","",""],["","","","","","","archiving contours for patient follow-up\nand management.\n• Quantitative and statistical analysis of\nPET/SPECT brain scans by comparing to\nother registered PET/SPECT brain scans.\n• Planning and evaluation of permanent\nimplant brachytherapy procedures (not\nincluding radioactive microspheres).\n• Calculating absorbed radiation dose as\na result of administering a radionuclide.\nWhen using device clinically, the user\nshould only use FDA approved\nradiopharmaceuticals. If using with\nunapproved ones, this device should only\nbe used for research purposes.\nLossy compressed mammographic\nimages and digitized film screen images\nmust not be reviewed for primary image\ninterpretations. Images that are printed to\nfilm must be printed using an\nFDA-approved printer for the diagnosis\nof digital mammography images.\nMammographic images must be viewed\non a display system that has been cleared\nby the FDA for the diagnosis of digital\nmammography images. The software is\nnot to be used for mammography CAD.","","",""],["Label/labeling","","Conform with 21CFR Part 801","","","","Conform with 21CFR Part 801","","",""],["Operating System","","Windows","","","","Windows and MAC system","","",""],["","Segmentation Features","","","","","","","",""],["Algorithm","","","Deep Learning","","","Atlas-based","","",""],["Compatible\nModality","","Non-Contrast CT","Non-Contrast CT","","","Non-Contrast CT","","",""],["Compatible\nScanner Models","","No Limitation on scanner model,\nDICOM 3.0 compliance required.","","","","No Limitation on scanner model,\nDICOM3.0 compliance required.","","",""],["Compatible\nTreatment\nPlanning System","","No Limitation on TPS model, DICOM\n3.0 compliance required.","","","","No Limitation on TPS model, DICOM\n3.0 compliance required.","","",""],["Contraindications","","","None","","","","None","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191928-p9-t0","doc_id":"K191928","page_num":9,"bbox":[105.44,118.74,532.12,273.36],"n_rows":6,"n_cols":9,"columns":["ITEM","","Proposed Device","","","Predicate Device K182624","","",""],"rows":[["ITEM","","Proposed Device","","","Predicate Device K182624","","",""],["","Registration Features","","","","","","",""],["Algorithm","","","Intensity Based","","","Intensity Based","",""],["Compatible\nModality","","CT, MRI, PET","CT, MRI, PET","","CT, MRI, CR, DX, MG, US, SPECT,\nPET and XA","","",""],["Compatible\nScanner Models","","No Limitation on scanner model,\nDICOM 3.0 compliance required.","","","No Limitation on scanner model,\nDICOM3.0 compliance required.","","",""],["Compatible\nTreatment\nPlanning System","","No Limitation on TPS model, DICOM\n3.0 compliance required.","","","No Limitation on TPS model, DICOM\n3.0 compliance required.","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191994-p7-t0","doc_id":"K191994","page_num":7,"bbox":[66.26,144.26,548.74,619.3],"n_rows":7,"n_cols":3,"columns":["","UNMODIFIED Device\nProFound™ AI V2\n(PowerLook® Tomo Detection\nV2 Software)","MODIFIED Device\nProFound™ AI V2.1"],"rows":[["","UNMODIFIED Device\nProFound™ AI V2\n(PowerLook® Tomo Detection\nV2 Software)","MODIFIED Device\nProFound™ AI V2.1"],["Regulation Number","21 CFR 892.2090","21 CFR 892.2090"],["Product Code","QDQ","QDQ"],["510(k) #","K182373","Pending"],["Intended Use /\nIndication for Use","ProFound™ AI V2\n(PowerLook® Tomo Detection\nV2) is a computer-assisted\ndetection and diagnosis (CAD)\nsoftware device intended to be\nused concurrently by interpreting\nphysicians while reading digital\nbreast tomosynthesis (DBT)\nexams from compatible DBT\nsystems. The system detects soft\ntissue densities (masses,\narchitectural distortions and\nasymmetries) and calcifications\nin the 3D DBT slices. The\ndetections and Certainty of\nFinding and Case Scores assist\ninterpreting physicians in\nidentifying soft tissue densities\nand calcifications that may be\nconfirmed or dismissed by the\ninterpreting Physician.","ProFound™ AI V2.1 is a\ncomputer-assisted detection and\ndiagnosis (CAD) software device\nintended to be used concurrently\nby interpreting physicians while\nreading digital breast\ntomosynthesis (DBT) exams\nfrom compatible DBT systems.\nThe system detects soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in the 3D DBT\nslices. The detections and\nCertainty of Finding and Case\nScores assist interpreting\nphysicians in identifying soft\ntissue densities and calcifications\nthat may be confirmed or\ndismissed by the interpreting\nPhysician."],["End User","Radiologists","Radiologists"],["Patient Population","Symptomatic and asymptomatic\nwomen\nundergoing mammography.","Symptomatic and asymptomatic\nwomen\nundergoing mammography."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K191994-p8-t0","doc_id":"K191994","page_num":8,"bbox":[66.26,144.26,548.74,522.43],"n_rows":6,"n_cols":3,"columns":["","UNMODIFIED Device\nProFound™ AI V2\n(PowerLook® Tomo Detection\nV2 Software)","MODIFIED Device\nProFound™ AI V2.1"],"rows":[["","UNMODIFIED Device\nProFound™ AI V2\n(PowerLook® Tomo Detection\nV2 Software)","MODIFIED Device\nProFound™ AI V2.1"],["Mode of Action","Image processing device\nintended to aid in the detection,\nlocalization, and characterization\nof soft tissue densities (masses,\narchitectural distortions\nand asymmetries) and\ncalcifications in the 3D DBT\nslices.","Image processing device\nintended to aid in the detection,\nlocalization, and characterization\nof soft tissue densities (masses,\narchitectural distortions\nand asymmetries) and\ncalcifications in the 3D DBT\nslices."],["Image Source\nModalities","Digital breast tomosynthesis\nslices","Digital breast tomosynthesis\nslices"],["Output Device","Softcopy Workstation","Softcopy Workstation"],["Deployment","Standalone computer","Standalone computer"],["Supported Digital\nBreast Tomosynthesis\nSystems","ProFound AI V2 Software:\n• Hologic Selenia Dimensions\n• Ge Senographe SenoClaire\n• GE Senographe Pristina","Profound AI V2 Software:\n• Hologic Selenia Dimensions\n• Ge Senographe SenoClaire\n• GE Senographe Pristina\nProFound AI V2.1 Software:\n• Siemens Mammomat\nInspiration\n• Siemens Mammomat\nRevelation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p5-t0","doc_id":"K192051","page_num":5,"bbox":[42.72,360.06,484.55,501.92],"n_rows":8,"n_cols":2,"columns":["Device Trade Name","THINQ™"],"rows":[["Device Trade Name","THINQ™"],["Common Name","Medical Imaging Processing Software"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR §892.2050"],["Regulation Description","Picture archiving and communications system"],["Regulatory Class","Class II"],["Product Classification Code","LLZ"],["Classification Panel","Radiology"]],"caption_candidate":"2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p5-t1","doc_id":"K192051","page_num":5,"bbox":[42.72,569.16,484.55,746.5],"n_rows":10,"n_cols":2,"columns":["Device","NeuroQuant"],"rows":[["Device","NeuroQuant"],["510(k) Number","K170981"],["Manufacturer","CorTechs Labs, Inc."],["Common Name","Medical Imaging Processing Software"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR §892.2050"],["Regulation Description","Picture archiving and communications system"],["Regulatory Class","Class II"],["Product Classification Code","LLZ"],["Classification Panel","Radiology"]],"caption_candidate":"3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p6-t0","doc_id":"K192051","page_num":6,"bbox":[42.72,590.51,564.99,726.55],"n_rows":5,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Device","THINQ™","NeuroQuant v2.2"],["510(k) Number","K192051","K170981"],["Regulation\nNumber","21 CFR §892.2050","21 CFR §892.2050"],["Regulation\nDescription","Picture archiving and\ncommunications system","Picture archiving and\ncommunications system"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p7-t0","doc_id":"K192051","page_num":7,"bbox":[42.72,67.63,566.06,715.35],"n_rows":12,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Device:","THINQ™","NeuroQuant v2.2"],["Classification\nName","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological"],["Classification:","Class II","Class II"],["Product Code:","LLZ","LLZ"],["Indications\nfor Use","THINQ™ is intended for automatic\nlabeling, visualization and\nvolumetric quantification of\nsegmentable brain structures from\na set of MR images. Volumetric\nmeasurements may be compared\nto reference percentile data.","NeuroQuant is intended for\nautomatic labeling, visualization\nand volumetric quantification of\nsegmentable brain structures and\nlesions from a set of MR images.\nVolumetric measurements may be\ncompared to reference percentile\ndata."],["Design and\nIncorporated\nTechnology","• Automated measurement of brain\ntissue volumes and structures\n• Automatic segmentation and\nquantification of brain structures\nusing a probabilistic\nneuroanatomical atlas based on\nthe MR image intensity","• Automated measurement of brain\ntissue volumes and structures and\nlesions\n• Automatic segmentation and\nquantification of brain structures\nusing a dynamic probabilistic\nneuroanatomical atlas, with age\nand gender specificity, based on\nthe MR image intensity"],["Physical\nCharacteristics","• Software package\n• Operates on off-the-shelf\nhardware (multiple vendors)","• Software package\n• Operates on off-the-shelf\nhardware (multiple vendors)"],["Operating\nSystem","Supports Linux","Supports Linux, Mac OS X and\nWindows"],["Deployment:","Container installation","Cloud based or installed"],["Processing\nArchitecture","Automated internal pipeline that\nperforms:\n• Artifact correction\n• Segmentation\n• Volume calculation\n• Report generation","Automated internal pipeline that\nperforms:\n• Artifact correction\n• Segmentation\n• Lesion quantification\n• Volume calculation\n• Report generation"],["Data Source","• MRI scanner: 3D T1 MRI scans\nacquired with specified protocols\n• THINQ supports DICOM format as\ninput","• MRI scanner: 3D T1 MRI scans\nacquired with specified protocols\n• NeuroQuant supports DICOM\nformat as input"]],"caption_candidate":"THINQ™ 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p8-t0","doc_id":"K192051","page_num":8,"bbox":[42.72,67.63,519.78,419.11],"n_rows":4,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Device:","THINQ™","NeuroQuant v2.2"],["Output","• Provides volumetric\nmeasurements of brain structures\n• Includes segmented color\noverlays and morphometric reports\n• Automatically compares results to\nreference percentile data\n• Report output is PDF file format\n• Outputs segmentation results as\noverlay in DICOM Encapsulated\nJPEG format allowing display on\nDICOM workstations and Picture\nArchive and Communications\nSystem","• Provides volumetric\nmeasurements of brain structures\nand lesions\n• Includes segmented color\noverlays and morphometric reports\n• Automatically compares results to\nreference percentile data and to\nprior scans when available\n• Supports DICOM format as output\nof results that can be displayed on\nDICOM workstations and Picture\nArchive and Communications\nSystems"],["Safety","• Automated quality control\nfunctions:\n• Scan sequence (protocol) checks\n• Atlas alignment checks\n• Cortical surface checks\n• Result validity checks\n• Results must be reviewed by a\ntrained physician","• Automated quality control\nfunctions:\n• Tissue contrast check\n• Scan protocol verification\n• Atlas alignment check\n• Results must be reviewed by a\ntrained physician"]],"caption_candidate":"THINQ™ 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p9-t0","doc_id":"K192051","page_num":9,"bbox":[113.43,187.37,498.57,727.05],"n_rows":13,"n_cols":3,"columns":["Structure","Accuracy Metric","Mean (StDev)"],"rows":[["Structure","Accuracy Metric","Mean (StDev)"],["Whole Brain","Dice\nAVE (cm3)\nRVE","0.94 ( 0.01)\n327.00 (111.48)\n0.30 ( 0.13)"],["Total Gray Matter","Dice\nAVE (cm3)\nRVE","0.82 ( 0.02)\n174.63 (46.42)\n0.24 ( 0.05)"],["Total White Matter","Dice\nAVE (cm3)\nRVE","0.87 ( 0.04)\n65.67 (37.38)\n0.18 ( 0.12)"],["Left Cortical Gray Matter","Dice\nAVE (cm3)\nRVE","0.92 ( 0.06)\n10.59 ( 6.51)\n0.05 ( 0.03)"],["Right Cortical Gray Matter","Dice\nAVE (cm3)\nRVE","0.92 ( 0.07)\n10.43 ( 6.67)\n0.05 ( 0.03)"],["Left Frontal Lobe","Dice\nAVE (cm3)\nRVE","0.90 ( 0.06)\n5.44 ( 3.83)\n0.07 ( 0.05)"],["Right Frontal Lobe","Dice\nAVE (cm3)\nRVE","0.90 ( 0.06)\n5.07 ( 3.86)\n0.06 ( 0.05)"],["Left Parietal Lobe","Dice\nAVE (cm3)\nRVE","0.88 ( 0.08)\n4.06 ( 3.04)\n0.08 ( 0.06)"],["Right Parietal Lobe","Dice\nAVE (cm3)\nRVE","0.88 ( 0.08)\n3.85 ( 2.86)\n0.07 ( 0.06)"],["Left Occipital Lobe","Dice\nAVE (cm3)\nRVE","0.82 ( 0.07)\n1.57 ( 1.22)\n0.07 ( 0.05)"],["Right Occipital Lobe","Dice\nAVE (cm3)\nRVE","0.82 ( 0.08)\n1.92 ( 1.97)\n0.08 ( 0.09)"],["Left Temporal Lobe","Dice\nAVE (cm3)\nRVE","0.89 ( 0.06)\n2.08 ( 1.89)\n0.04 ( 0.04)"]],"caption_candidate":"Structure Accuracy Metric Mean (StDev)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p10-t0","doc_id":"K192051","page_num":10,"bbox":[113.43,98.36,498.57,710.66],"n_rows":14,"n_cols":3,"columns":["Left Cerebral White Matter","Dice\nAVE (cm3)\nRVE","0.86 ( 0.04)\n32.60 (18.80)\n0.18 ( 0.12)"],"rows":[["Left Cerebral White Matter","Dice\nAVE (cm3)\nRVE","0.86 ( 0.04)\n32.60 (18.80)\n0.18 ( 0.12)"],["Right Cerebral White Matter","Dice\nAVE (cm3)\nRVE","0.86 ( 0.04)\n33.07 (18.88)\n0.18 ( 0.12)"],["Left Lateral Ventricle","Dice\nAVE (cm3)\nRVE","0.86 ( 0.07)\n2.32 ( 1.69)\n0.17 ( 0.15)"],["Right Lateral Ventricle","Dice\nAVE (cm3)\nRVE","0.85 ( 0.07)\n2.19 ( 1.59)\n0.18 ( 0.14)"],["Left Hippocampus","Dice\nAVE (cm3)\nRVE","0.78 ( 0.03)\n0.45 ( 0.29)\n0.14 ( 0.09)"],["Right Hippocampus","Dice\nAVE (cm3)\nRVE","0.79 ( 0.03)\n0.39 ( 0.28)\n0.12 ( 0.10)"],["Left Amygdala","Dice\nAVE (cm3)\nRVE","0.66 ( 0.05)\n0.60 ( 0.17)\n0.68 ( 0.24)"],["Right Amygdala","Dice\nAVE (cm3)\nRVE","0.64 ( 0.06)\n0.69 ( 0.19)\n0.74 ( 0.27)"],["Left Caudate","Dice\nAVE (cm3)\nRVE","0.78 ( 0.07)\n0.50 ( 0.35)\n0.17 ( 0.14)"],["Right Caudate","Dice\nAVE (cm3)\nRVE","0.78 ( 0.07)\n0.53 ( 0.34)\n0.18 ( 0.13)"],["Left Putamen","Dice\nAVE (cm3)\nRVE","0.82 ( 0.04)\n0.83 ( 0.35)\n0.20 ( 0.10)"],["Right Putamen","Dice\nAVE (cm3)\nRVE","0.82 ( 0.03)\n0.89 ( 0.35)\n0.21 ( 0.08)"],["Left Thalamus","Dice\nAVE (cm3)\nRVE","0.82 ( 0.03)\n1.51 ( 0.53)\n0.19 ( 0.05)"],["Right Thalamus","Dice\nAVE (cm3)\nRVE","0.83 ( 0.03)\n1.38 ( 0.45)\n0.18 ( 0.04)"]],"caption_candidate":"Left Cerebral White Matter Dice 0.86 ( 0.04)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p11-t0","doc_id":"K192051","page_num":11,"bbox":[113.43,83.91,498.57,171.39],"n_rows":2,"n_cols":3,"columns":["Right Cerebellum","Dice\nAVE (cm3)\nRVE","0.92 ( 0.02)\n2.07 ( 1.49)\n0.03 ( 0.02)"],"rows":[["Right Cerebellum","Dice\nAVE (cm3)\nRVE","0.92 ( 0.02)\n2.07 ( 1.49)\n0.03 ( 0.02)"],["Intracranial Volume ICV","APD\nAVE (cm3)\nRVE","3.42 ( 2.05)\n50.18 (31.92)\n0.03 ( 0.02)"]],"caption_candidate":"Right Cerebellum Dice 0.92 ( 0.02)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192051-p11-t1","doc_id":"K192051","page_num":11,"bbox":[150.54,257.17,461.46,731.99],"n_rows":31,"n_cols":2,"columns":["Structure","Reproducibility APD\nMean (StDev)"],"rows":[["Structure","Reproducibility APD\nMean (StDev)"],["Whole Brain","0.34 ( 0.29)"],["Total Gray Matter","0.83 ( 0.80)"],["Total White Matter","1.04 ( 1.12)"],["Left Cortical Gray Matter","1.08 ( 0.89)"],["Right Cortical Gray Matter","1.04 ( 0.88)"],["Left Frontal Lobe","1.31 ( 1.30)"],["Right Frontal Lobe","1.57 ( 2.41)"],["Left Parietal Lobe","1.50 ( 1.31)"],["Right Parietal Lobe","1.67 ( 2.73)"],["Left Occipital Lobe","1.49 ( 1.16)"],["Right Occipital Lobe","2.00 ( 1.41)"],["Left Temporal Lobe","1.24 ( 1.37)"],["Right Temporal Lobe","1.39 ( 1.15)"],["Left Cerebral White Matter","1.15 ( 1.09)"],["Right Cerebral White Matter","1.10 ( 1.20)"],["Left Lateral Ventricle","1.44 ( 1.21)"],["Right Lateral Ventricle","1.55 ( 1.12)"],["Left Hippocampus","1.56 ( 1.76)"],["Right Hippocampus","1.49 ( 1.57)"],["Left Amygdala","1.25 ( 1.23)"],["Right Amygdala","1.72 ( 1.36)"],["Left Caudate","1.14 ( 1.22)"],["Right Caudate","1.24 ( 1.10)"],["Left Putamen","1.41 ( 1.15)"],["Right Putamen","1.29 ( 0.90)"],["Left Thalamus","0.86 ( 0.59)"],["Right Thalamus","0.75 ( 0.63)"],["Left Cerebellum","0.62 ( 0.58)"],["Right Cerebellum","0.60 ( 0.54)"],["Intracranial Volume ICV","0.30 ( 0.29)"]],"caption_candidate":"Structure Reproducibility APD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192065-p6-t0","doc_id":"K192065","page_num":6,"bbox":[122.32,153.65,512.71,576.08],"n_rows":7,"n_cols":6,"columns":["","Feature","","","Comparison of the Subject Device to the Predicate Device",""],"rows":[["","Feature","","","Comparison of the Subject Device to the Predicate Device",""],["Beam\nPlacement","","","Creation of new geometric treatment plans for photon radiotherapy. The syngo.via workflow\nsupports a more user intuitive workflow (i.e. a more modern look and feel).\nModification: Beam placement auto shape now also allows in creating rectangular block\nfields.","",""],["Reference\nPoint\nManagement","","","Reference Point Management allows the user to edit the position, color, and type of Points of\nInterest (POI).\nModification: The workflow for reference point creation has been simplified and a\nstreamlined workflow for breast iso-centering has been implemented.","",""],["Patient\nMarking","","","Sending of reference points with offset details to a laser system.\nModification:Support of simplified workflow for breast iso-centering. Enabled by combining\nimprovements in iso-centering contouring the breast. It identifies the breast boundaries and\nsuggests a proper iso-center for breast treatment.","",""],["Routine\nContouring","","","Routine Contouring tools (e. g. freehand drawing tools, creation of margins etc.)\nModificationsinclude capability of interpolating contours, 3D Pan/Scale options, and option\nto add rectangular and ellipse as contour shapes, improvement in nudge tool to enable auto\nfilling of the inner part of a closed contour, and restricting the margin extension to external\ncontour.","",""],["Advanced\nContouring","","","Advanced Contouring tools (automatic contouring of different structures, nudge 3D tool,\ncontour interpolation etc.). Automatic contouring of pelvic and head/neck regions, support of\nRapid Results Technology.\nModification: This subject device provides the following extensions:\n(cid:120) Automatic Contouring can be applied on further structures (thoracic and abdominal\nregions)\n(cid:120) A new deep learning-based approach that uses an adversarial network has been\nimplemented","",""],["Structure Set\nManagement","","","The Structure Set Management provides the following functionality:\n(cid:120) Loading and storing of DICOM RT structure sets, creating, editing and deletion of\nstructures and POIs.\n(cid:120) Creating, editing and deletion of structure templates.\n(cid:120) Customize predefined structure database with mapping to international nomenclature\nschemes.\nModificationincludes simplifying the user interface.","",""]],"caption_candidate":"provided as Table 4below for the software version SOMARIS/8 VB40:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K192130-p5-t1","doc_id":"K192130","page_num":5,"bbox":[70.88,516.26,349.39,684.79],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","icobrain"],"rows":[["Device Trade Name:","icobrain"],["Common Name:","Medical Image Processing Software"],["Classification Name:","System, Image processing, Radiological"],["Number","892.2050"],["Product Code:","LLZ"],["Classification Panel:","Radiology"]],"caption_candidate":"6.2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192167-p5-t0","doc_id":"K192167","page_num":5,"bbox":[90.6,426.0,521.52,639.36],"n_rows":10,"n_cols":3,"columns":["","CuraRad-ICH","Accipiolx"],"rows":[["","CuraRad-ICH","Accipiolx"],["Manufacturer","CuraCloud Corporation","MaxQ AI"],["Intended Clinical\nEnd User","Radiologists/Trained Clinicians","Radiologists/Trained Clinicians"],["Clinical Condition","Acute Intracranial hemorrhage","Acute Intracranial hemorrhage"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed\nfrom worklist"],["AI Used","Yes","Yes"],["Input Image\nModality","Non-contrast Head CT","Non-contrast Head CT"],["Non-Diagnostic\nPreview","No","No"],["Output","Suspected ICH (Yes or No)","Suspected ICH (Yes or No)"],["Results Receiver","PACS/Workstation","PACS/Workstation"]],"caption_candidate":"Both devices also flag the suspected ICH on the DICOM images for the radiologist to review.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192279-p5-t0","doc_id":"K192279","page_num":5,"bbox":[72.28,215.22,490.5,532.44],"n_rows":7,"n_cols":9,"columns":["","Company","","","OrthoGrid Systems, Inc.","","","OrthoGrid Systems, Inc.",""],"rows":[["","Company","","","OrthoGrid Systems, Inc.","","","OrthoGrid Systems, Inc.",""],["","Product Name","","","PhantomMSK Trauma","","","PhantomMSK",""],["","FDA 510(k) #","","","-","","","K182332",""],["Product Code","","","LLZ","","","LLZ","",""],["Principles of\nOperation","","","The subject device is an\nimage processing software. A\nfluoroscopic image is acquired\nfrom a C-arm by the software\nand displayed outside the\nsterile field, where the image\nanalysis tools can be used at\nthe surgeon’s discretion.","","","The predicate device is an image\nprocessing software. A\nfluoroscopic image is acquired\nfrom a C-arm by the software and\ndisplayed outside the sterile field,\nwhere the image analysis tools\ncan be used at the surgeon’s\ndiscretion.","",""],["Image Data","","","C-arm, X-ray","","","C-arm, X-ray","",""],["Features","","","Templating, distortion\ncorrection, measurements,\nPACS and Network\ncompatibility.","","","Templating, distortion correction,\nmeasurements.","",""]],"caption_candidate":"safety or effectiveness when used as labeled.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p5-t0","doc_id":"K192287","page_num":5,"bbox":[71.02,135.86,524.26,258.5],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara™"],"rows":[["Device trade name","Transpara™"],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Submission type","Traditional 510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p5-t1","doc_id":"K192287","page_num":5,"bbox":[71.02,338.69,524.26,461.35],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara™ 1.3.0 (K181704)"],"rows":[["Device trade name","Transpara™ 1.3.0 (K181704)"],["Legal Manufacturer","ScreenPoint Medical B.V."],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p5-t2","doc_id":"K192287","page_num":5,"bbox":[71.02,526.27,541.17,571.87],"n_rows":3,"n_cols":2,"columns":["","is a software-only device for aiding radiologists with the detection and"],"rows":[["","is a software-only device for aiding radiologists with the detection and"],["diagnosis of breast cancer in mammograms. The product consists of a processing server",""],["and an optional viewer. The",""]],"caption_candidate":"4. Device description","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p5-t3","doc_id":"K192287","page_num":5,"bbox":[71.02,589.75,541.17,667.06],"n_rows":5,"n_cols":2,"columns":["","Processing results"],"rows":[["","Processing results"],["of Transpara™ can be transmitted to external destinations, such as medical imaging",""],["workstations or archives, using the DICOM mammography CAD SR protocol. This allows",""],["PACS workstations to implement the interface of Transpara™ in mammography reading",""],["applications.",""]],"caption_candidate":"calcifications and soft tissue lesions, which are trained with large databases of biopsy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p6-t0","doc_id":"K192287","page_num":6,"bbox":[70.82,70.8,541.13,116.42],"n_rows":3,"n_cols":2,"columns":["","automatically processes mammograms and the output of the device can be"],"rows":[["","automatically processes mammograms and the output of the device can be"],["used by radiologists concurrently with the reading of mammograms. The user interface of",""],["Transpara™ has different functions:",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192287-p7-t0","doc_id":"K192287","page_num":7,"bbox":[71.1,502.63,524.23,655.66],"n_rows":4,"n_cols":9,"columns":["","Standard ID","","","Standard Title","","","FDA Recognition #",""],"rows":[["","Standard ID","","","Standard Title","","","FDA Recognition #",""],["ISO 14971:2007","","","Medical Devices - Application Of Risk\nManagement To Medical Devices","","","5-40","",""],["IEC 62304:2015","","","Medical Device Software - Software Life\nCycle Processes","","","13-79","",""],["DEN180005","","","Decision summary with special controls\nfor class II radiology device","","","","",""]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192304-p5-t0","doc_id":"K192304","page_num":5,"bbox":[72.02,317.58,539.98,704.04],"n_rows":8,"n_cols":7,"columns":["","","SIS Software version 3.6.0","","","SIS Software version 3.3.0",""],"rows":[["","","SIS Software version 3.6.0","","","SIS Software version 3.3.0",""],["","","(Subject)","","","(Predicate)",""],["Allows for importing of\ndigital imaging sets","Yes","","","Yes","",""],["Uses proprietary\nsoftware algorithm to\ngenerate 3D segmented\nanatomical models from\npatient’s MR scans","Yes","","","Yes","",""],["Allows for review and\nanalysis of data in 2D\nand 3D formats","Yes","","","Yes","",""],["Performs image fusion of\ndatasets using\nautomated or manual\nimage matching\ntechnique","Yes","","","Yes","",""],["Segments structures in\nimages with manual and\nautomated tools and\nconverts them into 3D\nobjects for display","Yes","","","Yes","",""],["Creates hybrid datasets\nby filing in segmented\nregions slice-by-slice on\nanatomical datasets","Yes","","","Yes","",""]],"caption_candidate":"SIS Software Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192304-p6-t0","doc_id":"K192304","page_num":6,"bbox":[72.03,72.54,539.97,345.96],"n_rows":7,"n_cols":7,"columns":["","","SIS Software version 3.6.0","","","SIS Software version 3.3.0",""],"rows":[["","","SIS Software version 3.6.0","","","SIS Software version 3.3.0",""],["","","(Subject)","","","(Predicate)",""],["Can be downloaded to\nplanning system","Yes","","","Yes","",""],["Segmentation of CT scan\nto identify structures in\nrelation to those\nvisualized on MR","Yes","","","Yes","",""],["Feature to Account for\nCT images with gantry tilt","Yes","","","No","",""],["Cross-registers images\nand creates 3D (fused)\nmodel","Yes","","","Yes","",""],["Different registration\nmethods (linear and non-\nlinear) by multiple\nregistration tools (ANTS\nand ELASTIX)","Yes","","","No","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192320-p4-t0","doc_id":"K192320","page_num":4,"bbox":[66.58,575.98,525.18,655.14],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","HealthPNX"],"rows":[["Proprietary Name","HealthPNX"],["Premarket Notification","K190362"],["Classification Name","Radiological Computer-Assisted Prioritization Software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QFM"],["Regulatory Class","II"]],"caption_candidate":"The HealthCXR device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192320-p6-t0","doc_id":"K192320","page_num":6,"bbox":[66.63,290.64,560.19,690.7],"n_rows":4,"n_cols":4,"columns":["Technological\nCharacteristics","Proposed Device\nHealthCXR","Predicate Device\nHealthPNX (K190362)","Summary"],"rows":[["Technological\nCharacteristics","Proposed Device\nHealthCXR","Predicate Device\nHealthPNX (K190362)","Summary"],["Indication for\nUse/Intended Use","The Zebra HealthCXR device is a\nsoftware workflow tool designed\nto aid the clinical assessment of\nadult Chest X-Ray cases with\nfeatures suggestive of pleural\neffusion in the medical care\nenvironment. HealthCXR\nanalyzes cases using an artificial\nintelligence algorithm to identify\nsuspected findings. It makes case-\nlevel output available to a\nPACS/workstation for worklist\nprioritization or triage.\nHealthCXR is not intended to\ndirect attention to specific\nportions or anomalies of an\nimage. Its results are not intended\nto be used on a stand-alone basis\nfor clinical decision-making nor\nis it intended to rule out Pleural\nEffusion or otherwise preclude\nclinical assessment of X-Ray\ncases.","The Zebra Pneumothorax\ndevice is a software\nworkflow tool designed to\naid the clinical assessment of\nadult Chest X-Ray cases with\nfeatures suggestive of\nPneumothorax in the medical\ncare environment.\nHealthPNX analyzes cases\nusing an artificial intelligence\nalgorithm to identify\nsuspected findings. It makes\ncase-level output available to\na PACS/workstation for\nworklist prioritization or\ntriage. HealthPNX is not\nintended to direct attention to\nspecific portions or\nanomalies of the image. Its\nresults are not intended to be\nused on a stand-alone basis\nfor clinical decision-making\nnor is it intended to rule out\nPneumothorax or otherwise\npreclude clinical assessment\nof X-Ray cases.","Similar expect for lesion\ntype"],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Radiologist","Radiologist","Same"]],"caption_candidate":"A comparison of the technological characteristics with the predicate is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192320-p7-t0","doc_id":"K192320","page_num":7,"bbox":[66.54,72.31,560.23,707.2],"n_rows":12,"n_cols":4,"columns":["Radiological images\nformat","DICOM","DICOM","Same"],"rows":[["Radiological images\nformat","DICOM","DICOM","Same"],["Identify patients with\nprespecified\nclinical condition","Yes","Yes","Same"],["Clinical condition","Pleural Effusion","Pneumothorax","Different but as per the\nproduct classification\ndefinition, both identify\n“time sensitive imaging.”"],["Alert to finding","Yes; notification flagged for\nreview on hospital worklist or\nZebra list","Yes; notification flagged for\nreview on hospital worklist.","Similar, HealthCXR can\nbe directly integrated for\nnotification on the\nhospital worklist or on\nthe Zebra list application.\nBoth notifications\noperate in parallel with\nthe standard of care."],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed\nfrom worklist","Same"],["Modality","X-Ray","X-Ray","Same"],["Body part","Chest","Chest","Same"],["Artificial Intelligence\nalgorithm","Yes","Yes","Same"],["Limited to analysis of\nimaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with indicated\nfindings","Yes","Yes","Same"],["Preview Image","Presentation of a preview of the\nstudy for initial assessment, not\nmeant for diagnostic purposes.\nThe device operated in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","Presentation of notification\nfor initial assessment not\nmeant for diagnostic\npurposes. The device\noperates in parallel with the\nstandard of care, which\nremains the default option for\nall cases.","Similar, HealthCXR\nprovides an additional\nthumbnail view of the\noriginal exam as preview\nonly on the Zebra list or\nRadiology Assistant, not\nfor diagnostic use."],["Multiple operating\npoints","Yes; 2 optional operating points","No; single operating point","Different, but both\noperating points are\nsubstantially equivalent\nto the performance\npredicate device and\ncomply with DEN\n170073 Special control\n1(iii)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p4-t0","doc_id":"K192377","page_num":4,"bbox":[225.11,425.21,549.34,483.31],"n_rows":4,"n_cols":2,"columns":["Ethos Treatment Management","Treatment Plan and Image Management Application"],"rows":[["Ethos Treatment Management","Treatment Plan and Image Management Application"],["Ethos Treatment Planning","Treatment Planning System"],["Ethos Radiotherapy System","Medical Linear Accelerator"],["Halcyon","Medical Linear Accelerator"]],"caption_candidate":"21 CFR 892.5050","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p4-t1","doc_id":"K192377","page_num":4,"bbox":[225.11,497.83,549.34,556.03],"n_rows":4,"n_cols":2,"columns":["Ethos Treatment Management","ARIA Radiation Therapy Management (K173838)"],"rows":[["Ethos Treatment Management","ARIA Radiation Therapy Management (K173838)"],["Ethos Treatment Planning","Eclipse Treatment Planning System (K181145)"],["Ethos Radiotherapy System","Halcyon (K181032)"],["Halcyon","Halcyon (K181032)"]],"caption_candidate":"Halcyon Medical Linear Accelerator","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p4-t2","doc_id":"K192377","page_num":4,"bbox":[225.11,570.55,549.34,758.02],"n_rows":4,"n_cols":2,"columns":["Ethos Treatment Management","Ethos Treatment Management is software designed\nfor radiation therapy medical professionals to\nsupport them in managing radiation treatments for\npatients."],"rows":[["Ethos Treatment Management","Ethos Treatment Management is software designed\nfor radiation therapy medical professionals to\nsupport them in managing radiation treatments for\npatients."],["Ethos Treatment Planning","Ethos Treatment Planning is software that is\ndesigned generate treatment plans, modify\ntreatment plans, and guide users within adaptive\ntreatment sessions."],["Ethos Radiotherapy System","Halcyon and Ethos Radiotherapy System are single\nenergy linacs designed to deliver Image Guided\nRadiation Therapy and radiosurgery, using Intensity\nModulated and Volumetric Modulated Arc Therapy\ntechniques. They consist of an accelerator and\npatient support within a radiation shielded\ntreatment room and a control console outside the\ntreatment room."],["Halcyon",""]],"caption_candidate":"Halcyon Halcyon (K181032)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p5-t0","doc_id":"K192377","page_num":5,"bbox":[225.29,42.84,549.34,235.7],"n_rows":4,"n_cols":2,"columns":["Ethos Treatment Management","Ethos Treatment Management is used to manage\nand monitor radiation therapy treatment plans and\nsessions; it is intended to be used with a treatment\nplanning system."],"rows":[["Ethos Treatment Management","Ethos Treatment Management is used to manage\nand monitor radiation therapy treatment plans and\nsessions; it is intended to be used with a treatment\nplanning system."],["Ethos Treatment Planning","Ethos Treatment Planning is used to generate and\nmodify radiation therapy treatment plans."],["Ethos Radiotherapy System\n(The intended use statement is\nidentical to the predicate)","Halcyon and Ethos Radiotherapy System are\nintended to provide stereotactic radiosurgery and\nprecision radiotherapy for lesions, tumors, and\nconditions anywhere in the body where radiation\ntreatment is indicated."],["Halcyon\n(The intended use statement is\nidentical to the predicate)",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p5-t1","doc_id":"K192377","page_num":5,"bbox":[225.29,250.22,549.34,431.81],"n_rows":4,"n_cols":2,"columns":["Ethos Treatment Management","Ethos Treatment Management is indicated for use in\nmanaging and monitoring radiation therapy\ntreatment plans and sessions."],"rows":[["Ethos Treatment Management","Ethos Treatment Management is indicated for use in\nmanaging and monitoring radiation therapy\ntreatment plans and sessions."],["Ethos Treatment Planning","Ethos Treatment Planning is indicated for use in\ngenerating and modifying radiation therapy\ntreatment plans."],["Ethos Radiotherapy System","Halcyon and Ethos Radiotherapy System are\nindicated for the delivery of stereotactic radiosurgery\nand precision radiotherapy for lesions, tumors and\nconditions anywhere in the body where radiation is\nindicated for adults and pediatric patients."],["Halcyon",""]],"caption_candidate":"identical to the predicate)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192377-p7-t0","doc_id":"K192377","page_num":7,"bbox":[45.12,70.92,540.31,311.44],"n_rows":15,"n_cols":6,"columns":["Applied Standard","Device Name","","","",""],"rows":[["Applied Standard","Device Name","","","",""],["IEC 62304","Ethos Treatment Management","Ethos Treatment Planning","","","Ethos Radiotherapy System and Halcyon"],["IEC 61217","","Ethos Treatment Planning","","","Ethos Radiotherapy System and Halcyon"],["IEC 62274","Ethos Treatment Management","","","","Ethos Radiotherapy System and Halcyon"],["IEC 62083","Ethos Treatment Management","Ethos Treatment Planning","","",""],["IEC 82304-1","Ethos Treatment Management","Ethos Treatment Planning","","",""],["IEC 62366-1","Ethos Treatment Management","Ethos Treatment Planning","","",""],["IEC 60825-1","Not applicable to the software devices","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60976","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-1","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-1-2","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-1-3","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-1-6","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-2-1","","","","","Ethos Radiotherapy System and Halcyon"],["IEC 60601-2-68","","","","","Ethos Radiotherapy System and Halcyon"]],"caption_candidate":"The devices conform in whole or in part to the following recognised standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192383-p7-t0","doc_id":"K192383","page_num":7,"bbox":[72.0,84.38,724.2,520.06],"n_rows":2,"n_cols":4,"columns":["","Subject Device\nAidoc Briefcase for LVO triage","Primary Predicate Device\nAidoc Briefcase for ICH triage\n(K180647)","Secondary Predicate Device\nViz.AI ContaCT Software\n(DEN170073)"],"rows":[["","Subject Device\nAidoc Briefcase for LVO triage","Primary Predicate Device\nAidoc Briefcase for ICH triage\n(K180647)","Secondary Predicate Device\nViz.AI ContaCT Software\n(DEN170073)"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nhead CTA images. The device is\nintended to assist hospital networks\nand trained radiologists in workflow\ntriage by flagging and\ncommunication of suspected positive\nfindings of Large Vessel Occlusion\n(LVO) pathologies.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are\nintended to be used in conjunction\nwith other patient information and\nbased on their professional\njudgment, to assist with","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nnon-enhanced head CT images.\nThe device is intended to\nassist hospital networks and trained\nradiologists in workflow triage\nby flagging and communication of\nsuspected positive findings of\npathologies in head CT images,\nnamely Intracranial Hemorrhage\n(ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected ICH on a\nstandalone desktop application in\nparallel to the ongoing standard of\ncare image interpretation. The user is\npresented with notifications for cases\nwith suspected ICH findings.\nNotifications include compressed\npreview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on","ContaCT is a notification-only, parallel\nworkflow tool for use by hospital\nnetworks and trained clinicians to\nidentify and communicate images of\nspecific patients to a specialist,\nindependent of standard of care\nworkflow.\nContaCT uses an artificial intelligence\nalgorithm to analyze images for\nfindings suggestive of a pre-specified\nclinical condition and to notify an\nappropriate medical specialist of these\nfindings in parallel to standard of care\nimage interpretation. Identification of\nsuspected findings is not for diagnostic\nuse beyond notification. Specifically,\nthe device analyzes CT angiogram\nimages of the brain acquired in the\nacute setting and sends notifications\nto a neurovascular specialist that a\nsuspected large vessel occlusion has\nbeen identified and recommends\nreview of those images. Images can\nbe previewed through a mobile\napplication.\nImages that are previewed through the\nmobile application are compressed\nand are for informational purposes\nonly and not intended for diagnostic\nuse beyond notification. Notified\nclinicians are responsible for viewing"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192383-p8-t0","doc_id":"K192383","page_num":8,"bbox":[72.0,72.26,724.2,521.14],"n_rows":4,"n_cols":4,"columns":["","triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","professional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","non-compressed images on a\ndiagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making care-related\ndecisions or requests. ContaCT is\nlimited to analysis of imaging data and\nshould not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis."],"rows":[["","triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","professional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","non-compressed images on a\ndiagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making care-related\ndecisions or requests. ContaCT is\nlimited to analysis of imaging data and\nshould not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis."],["User population","Radiologist","Radiologist","Clinician (e.g., neurovascular\nspecialist)"],["Anatomical\nregion of\ninterest","Head","Head","Head"],["Inclusion/\nExclusion\ncriteria","Inclusion criteria\n Head CTA protocol with a 64-\nslice scanner or higher;\n Scans performed on\nadults/transitional adults ≥ 18\nyears of age;\n Slice thickness 0.5 mm – 1.0 mm.\nExclusion Criteria\n All scans that are technically\ninadequate, including motion\nartifacts, severe metal artifacts,\nsub-optimal bolus timing or an\ninadequate field of view.","Inclusion Criteria\n Head non-enhanced CT (NECT)\nwith a 64-slice scanner or higher;\n Scans performed on\nadults/transitional adults ≥ 18\nyears of age;\n Slice thickness 0.625 mm to 5.1\nmm.\nExclusion Criteria\n All scans that are technically\ninadequate; including motion\nartifacts, severe metal artifacts,\ninadequate field of view, etc.","Inclusion Criteria:\n The patient is older than 22 years\nof age when presenting to the\nhealthcare facility;\n The images were from patients\nwho underwent a stroke protocol\nassessment;\nand\n Head and neck CTA.\nExclusion Criteria:\nSeries used to identify potential LVOs\nwere axial thin slice CTAs. CTA series\nmay have been excluded because of\ninsufficient technical quality. Exclusion\ncriteria included:\n Series containing metal artifacts in\nthe soft matter of the brain;\n Series that are non-axial;\n Series containing missing slices;\n Series displaying no visible"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192383-p9-t0","doc_id":"K192383","page_num":9,"bbox":[72.0,72.26,724.2,520.78],"n_rows":9,"n_cols":4,"columns":["","","","contrast due to bad bolus timing\nduring the series acquisition\nprocess;\n Series containing inconsistent pixel\nspacing;\n Series containing slices thicker\nthan 0.625mm;\n Series containing improperly\nordered slices (e.g. as a result of\nmanual correction by an Imaging\ntechnician); and\nSeries containing an incomplete skull."],"rows":[["","","","contrast due to bad bolus timing\nduring the series acquisition\nprocess;\n Series containing inconsistent pixel\nspacing;\n Series containing slices thicker\nthan 0.625mm;\n Series containing improperly\nordered slices (e.g. as a result of\nmanual correction by an Imaging\ntechnician); and\nSeries containing an incomplete skull."],["View DICOM\ndata","DICOM Information about the\npatient, study and current image","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient,\nstudy and current image"],["Segmentation\nof region of\ninterest","No; device does not mark, annotate,\nor direct users’ attention to a specific\nlocation in the original image.","No; device does not mark, annotate,\nor direct users’ attention to a specific\nlocation in the original image.","No; device does not mark, annotate,\nor direct users’ attention to a specific\nlocation in the original image."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm."],["Notification/Prio\nritization","Yes","Yes","Yes"],["Preview images","Presentation of a small, compressed,\nblack and white preview image that\nis labeled “Not for diagnostic use”;\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a small, compressed,\nblack and white preview image that is\nlabeled “Not for diagnostic use”;\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a small, compressed,\nblack and white preview image that is\nlabeled “Not for diagnostic use”."],["Alteration of\noriginal image","No","No","No"],["Removal of\ncases from\nworklist queue","No","No","No"],["Structure","- AHS module (image acquisition);","- AHS module (image acquisition);","- Image Forwarding Software"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192383-p11-t0","doc_id":"K192383","page_num":11,"bbox":[84.62,326.81,528.82,470.71],"n_rows":10,"n_cols":3,"columns":["Prevalence","PPV","NPV"],"rows":[["Prevalence","PPV","NPV"],["10%","43.5%","98.6%"],["15%","55.0%","97.8%"],["20%","63.4%","96.9%"],["25%","69.8%","95.9%"],["30%","74.8%","94.8%"],["35%","78.9%","93.5%"],["40%","82.2%","92.1%"],["45%","85.0%","90.5%"],["50%","87.4%","88.6%"]],"caption_candidate":"(PPV) and negative predictive value (NPV) with varying prevalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192383-p12-t0","doc_id":"K192383","page_num":12,"bbox":[139.3,85.68,456.02,186.29],"n_rows":7,"n_cols":11,"columns":["Parameter","","","N","Mean\nestimate","","Lower","","","Upper",""],"rows":[["Parameter","","","N","Mean\nestimate","","Lower","","","Upper",""],["","","","","","","Confidence","","","Confidence",""],["","","","","","","Limit","","","Limit",""],["","Time-to-notification","","111","3.8","3.6","","","4.0","",""],["","of BriefCase LVO","","","","","","","","",""],["","Time-to-notification","","59","4.46","4.10","","","4.83","",""],["","of BriefCase ICH","","","","","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192437-p4-t0","doc_id":"K192437","page_num":4,"bbox":[67.52,229.05,534.38,347.55],"n_rows":4,"n_cols":2,"columns":["Company Name","Arterys Inc."],"rows":[["Company Name","Arterys Inc."],["Company Address","51 Federal St., Suite 305\nSan Francisco, CA 94107"],["Contact Person","Sharon Cholowsky\nDirector of Regulatory & Compliance"],["Contact Information","Email: regulatory@arterys.com\nPhone: 1 (650) 319-7230"]],"caption_candidate":"Submitter Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192437-p4-t1","doc_id":"K192437","page_num":4,"bbox":[67.52,381.3,534.38,502.05],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","Arterys® MICA\n​\n​"],"rows":[["Proprietary Name","Arterys® MICA\n​\n​"],["Common Name","Medical image processing software"],["Model Number","AMM6"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH/LLZ"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192437-p4-t2","doc_id":"K192437","page_num":4,"bbox":[67.52,535.8,534.38,603.3],"n_rows":2,"n_cols":2,"columns":["Predicate Device","Arterys® MICA, K182034\n​\n​ ​\nProduct Code LLZ"],"rows":[["Predicate Device","Arterys® MICA, K182034\n​\n​ ​\nProduct Code LLZ"],["Reference Device","Medis MR-CT VVA, K140587\n​\nProduct Code LLZ"]],"caption_candidate":"Predicate & Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192455-p10-t0","doc_id":"K192455","page_num":10,"bbox":[72.26,92.16,751.54,486.22],"n_rows":8,"n_cols":8,"columns":["Category","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?"],"rows":[["Category","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?"],["","","","","","Predicate: Xelis","",""],["","","","","","Fusion (K111613)","",""],["General","Common Name\nof Device/\nClassification\nProduct code","Picture Archiving and\nCommunications System\n(PACS)\n21 CFR 892.2050\nLLZ- Radiological Image\nProcessing System","Picture Archiving and\nCommunications System\n(PACS)\n21 CFR 892.2050\nLLZ- Radiological Image\nProcessing System","Picture Archiving\nand\nCommunications\nSystem (PACS)\n21 CFR 892.2050\nLLZ- Radiological\nImage Processing\nSystem","","","No changes"],["","Operating\nSystem","Windows 10","Windows 7/8.1/10","Unknown","","","Not a clinically significant\ndifference – support for\nlatest Windows OS."],["","Browser\nSupport","Internet Explorer 11,\nEdge, Chrome","Internet Explorer 7, 8, 9,\n10, 11","Unknown","","","Not a clinically significant\ndifference – support for new\nbrowser only"],["","Server OS\nSupport","Windows 2016 64-bit,\nWindows 2012 R2","Windows 2012 R2","Windows 32 and 64-\nbit","","","Not a clinically significant\ndifference – support for\nlatest server OS"],["","Indication for\nUse Statement","Merge PACS™ is a Picture\nArchiving and\nCommunication System\n(PACS) for multi-modality\n(CT, MR, PT, US, MG,\nBTO, CR, DR/DX, NM, XA,","Merge PACS™ is a Picture\nArchiving and\nCommunication System\n(PACS) for multi-modality\n(CT, MR, PT, US, MG, BTO,\nCR, DR/DX, NM, XA, RF,","The Xelis Fusion is a\nsoftware device that\nreceives digital\nimages and data\nfrom various\nsources (e.g. CT","","","There is only a minor change\nin the indications for use\nstatement from the\nprevious Merge PACS\ndevice, with the removal of\nthe optional Reach"]],"caption_candidate":"Table 1: Comparison to predicates","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192455-p15-t0","doc_id":"K192455","page_num":15,"bbox":[72.29,72.36,751.51,482.86],"n_rows":6,"n_cols":10,"columns":["Category","","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?",""],"rows":[["Category","","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?",""],["","","","","","","Predicate: Xelis","","",""],["","","","","","","Fusion (K111613)","","",""],["","","","interpretation of\nmammography studies.","interpretation should be\nused for the\ninterpretation of\nmammography studies.","","","","",""],["","Significant change(s) introduced in subject device Merge PACS:","","","","","","","",""],["Measurement","","SUV Calculation\n(PET)","Probe Tool, ROI Tool\nRegional Area Analysis\nand Regional Volume\nAnalysis\n2D and 3D SUV\ncalculations","Probe Tool and ROI Tool\n2D SUV calculations only","Supports 3D region\nof interest (ROI) SUV\nanalysis","","","Addition of Region Area and\nVolume Analysis tools allows\nfor additional clinical\nanalysis of PET images for\npatient treatment, including\n3D SUV calculations. The\nreference predicate device\nshares this new feature with\nthe subject Merge PACS.\nApplicable verification and\nvalidation testing has been\nperformed to justify the\nsafety and efficacy of this\ndifference from the primary\npredicate.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192455-p16-t0","doc_id":"K192455","page_num":16,"bbox":[72.28,72.36,751.52,461.32],"n_rows":7,"n_cols":10,"columns":["Category","","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?",""],"rows":[["Category","","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?",""],["","","","","","","Predicate: Xelis","","",""],["","","","","","","Fusion (K111613)","","",""],["","Non-significant changes(s) introduced in subject device Merge PACS:","","","","","","","",""],["Viewer","","Terarecon\nIntegration","Yes - Terarecon\nembedded in Merge\nPACS, opens in same\nwindow","Yes – Terarecon opens in\nseparate window","Unknown","","","Not a clinically significant\ndifference. End functionality\nowned by Terarecon.\nSmoother integration with\nMerge PACS for user\nconvenience, but no clinical\nimpact to the patient.",""],["","","Automatic\nRegistration for\nseries that do\nnot share a\ncommon frame\nof reference","Yes","No – Automatic linking of\nseries with same frame of\nreference UID and\nmanually linking of series\nthat do not share a\ncommon frame of\nreference only","Yes","","","Not a clinically significant\ndifference for Merge PACS.\nAutomatic registration is\nthrough the functionality of\nBlackford to deliver DICOM\nobjects to Merge PACS for\nautomatic registration of\nseries that do not share a\ncommon frame of\nreference. No impact to\nsafety or effectiveness.",""],["","","Patient Synopsis\ninformation\nwithin Patient\nRecord","Yes","No","Similar functionality\n– can Integrate with\npatient record","","","Not a clinically significant\ndifferent, Watson Imaging\nPatient Synopsis provides a\nnew option for clinicians to\nview patient information.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192455-p17-t0","doc_id":"K192455","page_num":17,"bbox":[72.26,72.36,751.54,440.5],"n_rows":7,"n_cols":8,"columns":["Category","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?"],"rows":[["Category","Feature/\nInformation","Subject Merge PACS\n(K192455)","Primary Predicate: Merge\nPACS (K173475)","","Reference","","Clinically Significant\nChange?"],["","","","","","Predicate: Xelis","",""],["","","","","","Fusion (K111613)","",""],["","","","","","","","No clinical impact to the\npatient."],["Viewer – Mammo\nSupport","2D/3D Mammo\ntoggle tool","Yes","No – user must perform\nadditional key clicks to go\nbetween 2D and 3D\nimages","Unknown","","","Not a clinically significant\ndifference. Provides a user\nconvenience only to more\nquickly toggle between\nviews. No clinical impact to\nthe patient."],["DICOM user\naccounts","Allow flexibility\nin choosing the\ndesired local,\nnetwork (e.g\nLDAP), or Merge\nPACS accounts\nof various user\nservices","Yes","No","Unknown","","","Security enhancements only\nand allows for more\ncustomizable controls. No\nimpact to safety or\neffectiveness."],["Other changes","Security\nenhancements,\nand updates to\ngraphics in\nAbout Screen","Yes","No","Unknown","","","Not a clinically significant\ndifference. About Screen\nprovides information only\nand security enhancements\nhave no impact to safety or\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192531-p5-t0","doc_id":"K192531","page_num":5,"bbox":[94.74,214.44,562.74,713.22],"n_rows":10,"n_cols":3,"columns":["","Subject device","Predicate device"],"rows":[["","Subject device","Predicate device"],["","QyScore v1.7.0","NeuroQuant v2.2"],["510(k) number","N/A","K170981"],["Regulation\nnumber","21 CFR 892.2050","21 CFR 892.2050"],["Regulation\ndescription","Picture archiving and\ncommunications system","Picture archiving and\ncommunications system"],["Classification\nname","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological"],["Classification","Class II","Class II"],["Product Code","LLZ","LLZ"],["Indications for\nuse","QyScore is intended for automatic\nlabeling, visualization and\nvolumetric quantification of\nsegmentable brain structures and\nlesions from a set of MR images.\nVolumetric data may be compared to\nreference percentile data. QyScore is\nnot intended for use in clinical\nscenarios that require evaluation of\nthe number of the white matter\nhyperintensities.","NeuroQuant is intended for\nautomatic labeling, visualization and\nvolumetric quantification of\nsegmentable brain structures and\nlesions from a set of MR images.\nVolumetric measurements may be\ncompared to reference percentile\ndata."],["Design and\nincorporated\ntechnology","- Automated measurement of brain\ntissue volumes and structures and\nlesions\n- Automatic segmentation and\nquantification of brain structures\nusing a dynamic probabilistic\nneuroanatomical atlas based on the\nMR image intensity","- Automated measurement of brain\ntissue volumes and structures and\nlesions\n- Automatic segmentation and\nquantification of brain structures\nusing a dynamic probabilistic\nneuroanatomical atlas, with age and\ngender specificity, based on the MR\nimage intensity"]],"caption_candidate":"Summary Comparison to Predicate:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192531-p6-t0","doc_id":"K192531","page_num":6,"bbox":[94.74,54.24,562.74,680.52],"n_rows":7,"n_cols":3,"columns":["","- Results displayed through graphical\nuser interface",""],"rows":[["","- Results displayed through graphical\nuser interface",""],["Physical\ncharacteristics","- Software package\n- Operates on off-the-shelf hardware\n(multiple vendors)","- Software package\n- Operates on off-the-shelf hardware\n(multiple vendors)"],["Operating\nsystem","Supports Linux","Supports Linux, Mac OS X and\nWindows"],["Processing\narchitecture","Automated internal pipeline that\nperforms:\n- bias correction\n- segmentation\n- lesions quantification\n- volume calculation\n- report generation","Automated internal pipeline that\nperforms:\n- bias correction\n- segmentation\n- lesions quantification\n- volume calculation\n- report generation"],["Data Source","MRI scanner: 3DT1 and FLAIR MRI\nscans acquired with specified\nprotocols.\nSupports DICOM format as input.","MRI scanner: 3DT1 and FLAIR\nMRI scans acquired with specified\nprotocols.\nSupports DICOM format as input."],["Output","- Provides volumetric measurements\nof brain structures and lesions\n- Includes segmented color overlays\nand morphometric reports\n- Automatically compares results to\nreference percentile data and to prior\nscans when available\n- Supports DICOM format as output\nof results that can be displayed on\nDICOM workstations and Picture\nArchive and Communications\nSystems","- Provides volumetric measurements\nof brain structures and lesions\n- Includes segmented color overlays\nand morphometric reports\n- Automatically compares results to\nreference percentile data and to prior\nscans when available\n- Supports DICOM format as output\nof results that can be displayed on\nDICOM workstations and Picture\nArchive and Communications\nSystems"],["Safety","Automated quality control function:\nscan protocol verification\nResults must be reviewed by a\ntrained physician","Automated quality control functions:\n- Tissue contrast check\n- Scan protocol verification\n- Atlas alignment check\nResults must be reviewed by a\ntrained physician"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192574-p4-t0","doc_id":"K192574","page_num":4,"bbox":[93.42,208.32,448.92,318.42],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Classification\nRegulation Number:","90-LNH\n21 CFR § 892.1000"],["Trade Proprietary Name:","Vantage Galan 3T, MRT-3020, V6.0 with\nAiCE Reconstruction Processing Unit for\nMR"],["Model Number:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192574-p6-t0","doc_id":"K192574","page_num":6,"bbox":[93.42,159.69,404.1,312.11],"n_rows":9,"n_cols":5,"columns":["System","","Subject","","Predicate Device"],"rows":[["System","","Subject","","Predicate Device"],["","","Vantage Galan 3T,","","Vantage Galan 3T,\nMRT-3020/A7,\nV5.0"],["","","MRT-3020, V6.0 with","",""],["","","AiCE Reconstruction","",""],["","","Processing Unit for MR","",""],["Marketed By","","Canon Medical Systems","","Canon Medical Systems\nUSA"],["","","USA","",""],["510(k)\nNumber","This Submission","","","K181593"],["Clearance\nDate","","","","Aug 13, 2018"]],"caption_candidate":"Predicate Device (system): Vantage Galan 3T, MRT-3020/A7, V5.0 (K181593)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192574-p7-t0","doc_id":"K192574","page_num":7,"bbox":[93.44,386.13,561.4,667.5],"n_rows":10,"n_cols":6,"columns":["Item","","Subject Device:","","Predicate Device:\nVantage Galan 3.0T,\nMRT-3020/A7, V5.0","Notes"],"rows":[["Item","","Subject Device:","","Predicate Device:\nVantage Galan 3.0T,\nMRT-3020/A7, V5.0","Notes"],["","","Vantage Galan 3T, MRT-3020,","","",""],["","","V6.0 with AiCE Reconstruction","","",""],["","","Processing Unit for MR","","",""],["Static field strength","3T","","","3T","Same"],["Operational Modes","Normal and 1st Operating\nMode","","","Normal and 1st Operating\nMode","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33: 2010+A1:2013)","Same"],["Maximum dB/dt","1st operating mode specified in\nIEC 60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in\nIEC 60601-2-33: 2010+A1:2013","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192574-p8-t0","doc_id":"K192574","page_num":8,"bbox":[93.47,99.63,561.36,224.04],"n_rows":5,"n_cols":6,"columns":["Item","","Subject Device:","","Predicate Device:\nVantage Galan 3.0T,\nMRT-3020/A7, V5.0","Notes"],"rows":[["Item","","Subject Device:","","Predicate Device:\nVantage Galan 3.0T,\nMRT-3020/A7, V5.0","Notes"],["","","Vantage Galan 3T, MRT-3020,","","",""],["","","V6.0 with AiCE Reconstruction","","",""],["","","Processing Unit for MR","","",""],["Potential emergency\ncondition and means\nprovided for\nshutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard\nfor ferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard\nfor ferromagnetic objects","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192601-p7-t0","doc_id":"K192601","page_num":7,"bbox":[76.68,40.71,698.45,498.89],"n_rows":52,"n_cols":4,"columns":["Shanghai United Imaging Healthcare","Co., Ltd.","",""],"rows":[["Shanghai United Imaging Healthcare","Co., Ltd.","",""],["Tel: +86 (21) 67076888 Fax：+8","6 (21) 67076889","",""],["www.united-imaging.com","","",""],["","","",""],["","Table 1 Substantial equivalent discu","ssion for basic functions",""],["Item","Proposed Device","Predicate Device","Remark"],["","","",""],["","uWS-MR","uWS-MR (K183164)",""],["","","",""],["General","","",""],["","","",""],["Device Classification","Picture Archiving and Communications","Picture Archiving and Communications","Same"],["","","",""],["Name","System","System",""],["","","",""],["Product Code","QIH, LLZ","LLZ","Same"],["","","",""],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050","Same"],["","","",""],["Device Class","II","II","Same"],["","","",""],["Classification Panel","Radiology","Radiology","Same"],["","","",""],["","","","The propose"],["","","",""],["","","","device includ"],["","","",""],["","","","more"],["","","",""],["","","","applications,"],["","","",""],["","","","which is"],["","","",""],["","","","discussed in"],["","","",""],["","","","the following"],["","","",""],["Advanced Application","Yes","Yes","chapters, tha"],["","","",""],["","","","the predicate"],["","","",""],["","","","device. This"],["","","",""],["","","","difference wi"],["","","",""],["","","","not impact th"],["","","",""],["","","","safety and"],["","","",""],["","","","effectiveness"],["","","",""],["","","","of the device"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K192601-p9-t0","doc_id":"K192601","page_num":9,"bbox":[70.61,85.34,715.73,512.98],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uWS-MR","","","uWS-MR (K183164)","",""],["","complex MRS data. This application\nsupports the analysis for both SVS\n(Single Voxel Spectroscopy) and CSI\n(Chemical Shift Imaging) data.\n The MAPs application is intended to\nprovide a number of arithmetic and\nstatistical functions for evaluating\ndynamic processes and images. These\nfunctions are applied to the grayscale\nvalues of medical images.\n The MR Breast Evaluation application\nprovides the user a tool to calculate\nparameter maps from contrast-\nenhanced time-course images.\n The Brain Perfusion application is\nintended to allow the visualization of\ntemporal variations in the dynamic\nsusceptibility time series of MR\ndatasets.\n MR Vessel Analysis is intended to\nprovide a tool for viewing,\nmanipulating, and evaluating MR\nvascular images.","","","complex MRS data. This application\nsupports the analysis for both SVS\n(Single Voxel Spectroscopy) and CSI\n(Chemical Shift Imaging) data.\n The MAPs application is intended to\nprovide a number of arithmetic and\nstatistical functions for evaluating\ndynamic processes and images. These\nfunctions are applied to the grayscale\nvalues of medical images.\n The MR Breast Evaluation application\nprovides the user a tool to calculate\nparameter maps from contrast-\nenhanced time-course images.\n The Brain Perfusion application is\nintended to allow the visualization of\ntemporal variations in the dynamic\nsusceptibility time series of MR\ndatasets.\n MR Vessel Analysis is intended to\nprovide a tool for viewing,\nmanipulating, and evaluating MR\nvascular images.","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192601-p10-t0","doc_id":"K192601","page_num":10,"bbox":[70.57,85.34,715.77,530.04],"n_rows":12,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uWS-MR","","","uWS-MR (K183164)","",""],[""," The Inner view application is intended\nto perform a virtual camera view\nthrough hollow structures (cavities),\nsuch as vessels.\n The DCE analysis is intended to view,\nmanipulate, and evaluate dynamic\ncontrast-enhanced MRI images.\n The United Neuro is intended to view,\nmanipulate, and evaluate MR\nneurological images.\n The MR Cardiac Analysis application\nis intended to be used for viewing,\npost-processing and quantitative\nevaluation of cardiac magnetic\nresonance data.","",""," The Inner view application is intended\nto perform a virtual camera view\nthrough hollow structures (cavities),\nsuch as vessels.\n The DCE analysis is intended to view,\nmanipulate, and evaluate dynamic\ncontrast-enhanced MRI images.\n The United Neuro is intended to view,\nmanipulate, and evaluate MR\nneurological images.","","",""],["Specification","","","","","","",""],["Image communication","Yes","","","Yes","","","Same"],["Hardware /OS","Yes","","","Yes","","","Same"],["Patient Administration","Yes","","","Yes","","","Same"],["Review 2D","Yes","","","Yes","","","Same"],["Review 3D","Yes","","","Yes","","","Same"],["Filming","Yes","","","Yes","","","Same"],["Fusion","Yes","","","Yes","","","Same"],["Inner View","Yes","","","Yes","","","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192601-p11-t0","doc_id":"K192601","page_num":11,"bbox":[71.68,85.34,715.93,262.85],"n_rows":7,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uWS-MR","","","uWS-MR (K183164)","",""],["Visibility","Yes","","","Yes","","","Same"],["ROI/VOI","Yes","","","Yes","","","Same"],["MIP Display","Yes","","","Yes","","","Same"],["Compare","Yes","","","Yes","","","Same"],["Report","Yes","","","Yes","","","Optimized\nfunction which\nwill not impact\nthe safety and\neffectiveness."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192601-p11-t1","doc_id":"K192601","page_num":11,"bbox":[71.68,291.07,715.93,495.22],"n_rows":13,"n_cols":12,"columns":["","Advanced","","Function name","","","Proposed device","","","Reference Device#1","","Remark"],"rows":[["","Advanced","","Function name","","","Proposed device","","","Reference Device#1","","Remark"],["","Application","","","","","uWS-MR","","","cvi42 (K141480)","",""],["Cardiac Analysis\n(New application)","","","Cardiac Function","Type of imaging scans","MR","","","MR","","","Same"],["","","","","Image Loading and Viewing","Yes","","","Yes","","","Same"],["","","","","LV Contour Segmentation","Yes","","","Yes","","","Same"],["","","","","RV Contour Segmentation","Yes","","","Yes","","","Same"],["","","","","Extent Definition","Yes","","","Yes","","","Same"],["","","","","Parameters Calculation","Yes","","","Yes","","","Same"],["","","","","BSA standardized","Yes","","","Yes","","","Same"],["","","","","Polar Maps","Yes","","","Yes","","","Same"],["","","","","Volume Curve","Yes","","","Yes","","","Same"],["","","","","Result Saving","Yes","","","Yes","","","Same"],["","","","","Report","Yes","","","Yes","","","Same"]],"caption_candidate":"Table 2 Substantial equivalent discussion for MR Cardiac Analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192601-p12-t0","doc_id":"K192601","page_num":12,"bbox":[72.24,85.33,724.18,486.34],"n_rows":23,"n_cols":8,"columns":["","Function name","","Proposed device\nuWS-MR","Reference Device#2\nPhilips IntelliSpace Cardiovascular\n(K153022)","","Remark",""],"rows":[["","Function name","","Proposed device\nuWS-MR","Reference Device#2\nPhilips IntelliSpace Cardiovascular\n(K153022)","","Remark",""],["","Flow Analysis","Type of imaging scans","MR","MR","","Same",""],["","","Image Loading and Viewing","Yes","Yes","","Same",""],["","","Plot vessel contour","Yes","Yes","","Same",""],["","","Propagate Contour","Yes","Yes","","Same",""],["","","Doppler Map","Yes","Yes","","Same",""],["","","Parameters Calculation","Yes","Yes","","Same",""],["","","Flow Curve","Yes","Yes","","Same",""],["","","Result Saving","Yes","Yes","","Same",""],["","","Report","Yes","Yes","","Same",""],["Advanced Application","","Function name","Proposed device\nuWS-MR","","Predicate device\nuWS-MR (K183164)","","Remark"],["United Neuro\n(Modified Application)","","Type of imaging scan","MR","","MR","","Same"],["","","Motion correction","Yes","","Yes","","Same"],["","","Functional activation\ncalculation","Yes","","Yes","","Same"],["","","Diffusion parameter analysis","Yes","","Yes","","Same"],["","","Adjust display parameter","Yes","","Yes","","Same"],["","","Fusion","Yes","","Yes","","Same"],["","","Fiber tracking","Yes","","Yes","","Same"],["","","Time-Intensity curve","Yes","","Yes","","Same"],["","","ROI Statistics","Yes","","Yes","","Same"],["","","Result Saving","Yes","","Yes","","Same"],["","","Report","Yes","","Yes","","Same"],["","","MR Segmentation","Yes","","No","","Note1"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192763-p6-t0","doc_id":"K192763","page_num":6,"bbox":[65.65,188.92,482.61,612.12],"n_rows":10,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Devices",""],"rows":[["Feature","","Subject Device","","","Predicate Devices",""],["","syngo.CT CaScoring","","","Calcium Scoring\nK990426","",""],["","","","","HealthCCS\nK172983","",""],["Automated Calcium Scoring\nEvaluation","Assignment of a probability of a\ncandidate being a coronary\ncalcification based on location\nwithin the heart, density, shape\nand similar properties: if the\nprobability of a candidate is\nhigher than a predefined\nthreshold, the candidate is\nlabelled as a calcification.\nIn addition, results of the\nevaluation can be sent via Rapid\nResults Technology any generic\nDICOM viewer.","","","The technology is equivalent to\nHealthCCS:\nAssignment of a probability of a\ncandidate being a coronary\ncalcification based on location\nwithin the heart, density, shape\nand similar properties: if the\nprobability of a candidate is\nhigher than a predefined\nthreshold, the candidate is\nlabelled as a calcification.","",""],["Browsing, selecting, and\ndisplaying images for\nsearching calcium\nregions/lesions","Yes","","","Yes","",""],["Interactive definition of ROIs\nand assignment of the four\nmajor coronary arteries (LM,\nLAD,CRC and RCA) to the\nlesions","Yes","","","Yes","",""],["Displaying the score in form\nof result tables/reports on\npaper and/or film","Yes","","","Yes","",""],["Pan and Zoom\nfunctionality/windowing","Yes","","","Yes","",""],["Reformatting","Yes","","","Yes","",""],["Comparison of Score to\nCited Literature","Yes","","","Yes","",""]],"caption_candidate":"below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192763-p7-t0","doc_id":"K192763","page_num":7,"bbox":[65.66,217.96,483.82,413.4],"n_rows":9,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Publicatio\nn Date","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Publicatio\nn Date","","Standards",""],["","","","","","Developme",""],["","","","","","nt",""],["","","","","","Organizatio",""],["","","","","","n",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-32","Software","Medical Device Software –Software Life\nCycle Processes; 62304:2006 (1st\nEdition)","08/20/2012","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971\nSecond Edition 2007-03-01","08/20/2012","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","2/23/2016","IEC","",""]],"caption_candidate":"standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192828-p5-t0","doc_id":"K192828","page_num":5,"bbox":[113.64,67.68,594.0,311.88],"n_rows":5,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary:\nAquilion ONE (TSX‐\n306A/3) V10.0","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K192188","09/06/2019"],["Reference:\nAquilion ONE (TSX‐\n305A/6) V8.9 with\nAiCE","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K183046","06/12/2019"],["Reference:\nDual Energy System\nPackage, CSDP‐001A","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K132813","02/06/2014"],["Reference:\nRevolution CT","GE Medical\nSystems,\nL.L.C.","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K163213","12/16/2016"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192828-p6-t0","doc_id":"K192828","page_num":6,"bbox":[108.03,253.59,584.76,713.58],"n_rows":9,"n_cols":12,"columns":["","","","S","ubject Device","","P","redicate Device","","C","omment",""],"rows":[["","","","S","ubject Device","","P","redicate Device","","C","omment",""],["Device Name,\nModel Number","evice Name,","","A\n(\nS","quilion ONE","","Aquilion ONE\n(TSX‐306A/3) V10.0","quilion ONE","","","",""],["","Model Number","","","TSX‐306A/3) V10.0 with","","","TSX‐306A/3) V10.0","","","",""],["","","","","pectral Imaging System","","","","","","",""],["5","10(k) Number","","T","his submission","","K","192188","","","",""],["Spectral Imaging System\n(CSDE‐004A)\n Scan Type\n Scan Regions\n Spectral Reconstruction\nImages","","","Available\n‐Rapid kV Switching\n‐Abdomen and pelvis,\nChest and Extremities\n‐Basis material image\n‐Monochromatic image\n‐Iodine Map\n‐VNC (virtual non‐\ncontrast) image","","","N/A","","","Reference Predicate\nDevice: K132813\n‐Two consecutive volume\nscans with short tube\nvoltage switching\n‐Whole Body\nN/A","",""],["Advanced Intelligent Clear‐IQ\nEngine (AiCE)\n Scan Regions","","","Available\nAbdomen and Pelvis\nChest\nCardiac\nExtremities*\nBrain*\nInner ear*","","","N/A","","","Reference Predicate\nDevice: K183046\nAbdomen and Pelvis\nChest\nCardiac\n*New scan regions","",""],["FIRST\n(Forward projected model‐\nbased Iterative Reconstruction\nSoluTion)","","","Available","","","N/A","","","","",""],["Reconstruction processing\nunit (CCRS‐003A*)","","","Available","","","N/A","","","* Includes FIRST and AiCE","",""]],"caption_candidate":"the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192832-p4-t0","doc_id":"K192832","page_num":4,"bbox":[67.08,136.25,170.75,710.17],"n_rows":54,"n_cols":2,"columns":["1.","SUBMITTER’S NA"],"rows":[["1.","SUBMITTER’S NA"],["",""],["","Canon Medical S"],["",""],["","1385 Shimoishiga"],["",""],["","Otawara‐Shi, Toc"],["",""],["2.","OFFICIAL CORRE"],["",""],["","Naofumi Watana"],["",""],["","Senior Manager,"],["",""],["3.","ESTABLISHMENT"],["",""],["","9614698"],["",""],["4.","CONTACT PERSO"],["",""],["","Orlando Tadeo, J"],["",""],["","Sr. Manager, Reg"],["",""],["","Canon Medical S"],["",""],["","2441 Michelle Dr"],["",""],["","Tustin, CA 92780"],["",""],["","(714) 669‐7459"],["",""],["5.","Date Prepared:"],["",""],["","September 30, 2"],["",""],["6.","TRADE NAME(S):"],["",""],["","Aquilion Prime SP"],["",""],["7.","COMMON NAME"],["",""],["","System, X‐ray, Co"],["",""],["8.","DEVICE CLASSIFI"],["","a) Classification N"],["","b) Regulation Nu"],["","c) Regulatory Cla"],["",""],["9.","PRODUCT CODE"],["",""],["","JAK – System, Co"],["",""],["Michelle","Drive, Tustin, CA 92780"]],"caption_candidate":"1. SUBMITTER’S NAME:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K192832-p5-t0","doc_id":"K192832","page_num":5,"bbox":[90.0,87.66,585.0,236.88],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance Date"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance Date"],["Aquilion Prime SP,\nTSX‐303B/1, v8.4\n(Primary Predicate\nDevice)","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K172188","October 6, 2017"],["Aquilion ONE (TSX‐\n305A/6) V8.9 with\nAiCE\n(Reference Device)","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K183046","June 12, 2019"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192832-p6-t0","doc_id":"K192832","page_num":6,"bbox":[101.88,118.64,567.0,537.84],"n_rows":32,"n_cols":5,"columns":["Item","","Aquilion Prime SP (TSX‐303B/8)","","Aquilion Prime SP (TSX‐303B/1) V8.4"],"rows":[["Item","","Aquilion Prime SP (TSX‐303B/8)","","Aquilion Prime SP (TSX‐303B/1) V8.4"],["","","V10.2 with AiCE‐i","",""],["510(k) Clearance\nNumber","N/A","N/A","","K172188"],["Anatomical Region","","AIDR 3D (Whole Body)","","AIDR 3D (Whole Body)"],["","","","",""],["","","AiCE (Abdomen and Pelvis, Chest,","",""],["","","Cardiac, Extremities, Brain, Inner ear)","",""],["Noise Reduction\nProcessing","","AIDR 3D","","AIDR 3D\nAIDR 3D Enhanced\nQuantum Denoising Smoothing (QDS)"],["","","AIDR 3D Enhanced","",""],["","","Quantum Denoising Smoothing (QDS)","",""],["","","AiCE","",""],["Processing capability","","Console CKCN‐020C","","Console CKCN‐017B\nReconstruction processing system\n(N/A)"],["","","","",""],["","","Reconstruction processing system","",""],["","","(AiCE‐i: CSAL‐001A)","",""],["Display console kit","","CGS‐72B (Optional)","","CGS‐72A: TSX‐303B/1 (Optional)"],["Image Quality Claims","","‐ Improved Quantitative high contrast","","No change"],["","","Spatial Resolution over AIDR 3D with","",""],["","","reduced noise","",""],["","","","",""],["","","‐ Improved Quantitative Dose","",""],["","","Reduction over FBP","",""],["","","","",""],["","","‐ Better Low‐contrast Detectability","",""],["","","than AIDR 3D for abdomen at the","",""],["","","same dose","",""],["","","","",""],["","","‐Noise appearance/texture more","",""],["","","similar to high dose filtered","",""],["","","backprojection compared to MBIR","",""],["","","","",""],["Operating System","","Microsoft Windows 10","","Microsoft Windows 7"]],"caption_candidate":"technological characteristics between the subject and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p6-t0","doc_id":"K192854","page_num":6,"bbox":[72.25,360.53,539.85,673.9],"n_rows":9,"n_cols":6,"columns":["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],"rows":[["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],["","","","TransparaTM","",""],["","","","K181704","",""],["Classification\nRegulation","21 CFR 892.2090\nRadiological Computer Assisted\nDetection And Diagnosis Software","SAME","","","Yes, identical."],["Medical\nDevice\nClassification","Class II","SAME","","","Yes, identical."],["Product Code","QDQ","SAME","","","Yes, identical."],["Level of\nConcern","Moderate","SAME","","","Yes, identical."],["Intended Use","A concurrent reading aid for\nphysicians interpreting screening\nFFDM acquired with compatible\nmammography systems, to identify\nfindings and assess their level of\nsuspicion.","SAME","","","Yes, identical."],["Target patient\npopulation","Women undergoing FFDM\nscreening mammography","SAME","","","Yes, identical"]],"caption_candidate":"Predicate and Subject Device Comparison:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p7-t0","doc_id":"K192854","page_num":7,"bbox":[72.29,72.36,539.83,486.55],"n_rows":6,"n_cols":6,"columns":["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],"rows":[["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],["","","","TransparaTM","",""],["","","","K181704","",""],["Target user\npopulation","Physicians interpreting FFDM\nscreening mammograms","SAME","","","Yes, identical"],["Design","Software-only device","SAME","","","Yes, identical"],["Indication for\nUse","MammoScreen™ is intended for\nuse as a concurrent reading aid for\ninterpreting physicians, to help\nidentify findings on screening\nFFDM acquired with compatible\nmammography systems and assess\ntheir level of suspicion. Output of\nthe device includes marks placed on\nfindings on the mammogram and\nlevel of suspicion scores. The\nfindings could be soft tissue lesions\nor calcifications. The level of\nsuspicion score is expressed at the\nfinding level, for each breast and\noverall for the mammogram. Patient\nmanagement decisions should not\nbe made solely on the basis of\nanalysis by MammoScreen™.","The ScreenPoint Transpara™\nsystem is intended for use as a\nconcurrent reading aid for\nphysicians interpreting\nscreening mammograms, to\nidentify regions suspicious for\nbreast cancer and assess their\nlikelihood of malignancy.\nOutput of the device includes\nmarks placed on suspicious\nsoft tissue lesions and\nsuspicious calcifications;\nregion‐based scores, displayed\nupon the physician’s query,\nindicating the likelihood that\ncancer is present in specific\nregions; and an overall score\nindicating the likelihood that\ncancer is present on the\nmammogram.\nPatient management decisions\nshould not be made solely on\nthe basis of analysis by\nTranspara™.","","","Yes, identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p8-t0","doc_id":"K192854","page_num":8,"bbox":[72.3,72.36,539.82,485.83],"n_rows":5,"n_cols":6,"columns":["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],"rows":[["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],["","","","TransparaTM","",""],["","","","K181704","",""],["Score","Finding level:\n10-point scale score indicating the\nlevel of suspicion of malignancy\n(from low suspicion to high\nsuspicion).\nBreast level:\nThe same 10-point scale score as\nfinding level. The score of a breast\nis equal to the maximum score of\nthe findings detected in this breast.\nExam level:\nExam-level of suspicion resulting\ndirectly from the maximum score of\nboth breasts (1-to-1 mapping\nbetween the score and the exam-\nlevel of suspicion).","Finding level:\nContinuous score 1-100\nindicating the level of\nsuspicion of malignancy (from\nlow suspicion to high\nsuspicion).\nBreast level:\nNone\nExam level:\n10-point scale score indicative\nof higher frequency of cancer\npositive","","","Both scores are\nsubstantially\nequivalent.\nBoth scores increase\nwith the level of\nsuspicion. The\nminimum (resp. the\nmaximum) of the both\nscores describes the\nsame status.\nAt the Exam level,\nboth scores have a 10-\npoint scale."],["Finding\ndiscovery","Findings are by-default displayed\nwhen score is equal or higher to 5.\nUpon user request for findings of\nscore equal or less to 4.","Upon user request by clicking\nin a position of the image also\ndetected by TransparaTM.","","","Both are the\ndemonstration of the\nsame intention:\nreducing the number\nof findings the user\nhas to review. In this\nsense, both are\nequivalent."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p9-t0","doc_id":"K192854","page_num":9,"bbox":[72.29,72.36,539.83,526.27],"n_rows":6,"n_cols":6,"columns":["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],"rows":[["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],["","","","TransparaTM","",""],["","","","K181704","",""],["Performances","Reader study:\n- 240 cases\n- 14 radiologists\nReading time (two sessions mean):\n- 57,67 seconds (unaided\nsession)\n- 64, 13 seconds (with\nMammoScreen)\nAUC:\n- radiologists AUC\n(unaided) = 0,769\n- standalone AUC = 0,786","Reader study:\n- 240 cases\n- 14 radiologists\nReading time:\n- 146 seconds (unaided\nsession)\n- 149 seconds (with\nTranspara™)\nAUC:\n- radiologists AUC\n(unaided) = 0,866\n- standalone AUC =\n0,887","","","Despite a slightly\nhigher performance of\nMammoScreen\ncompared to\nTranspara™, gains\nare still comparable\nand do not raise new\nquestions regarding\nsafety and\neffectiveness of the\ndevice."],["Features","Distinguishes two types of\nsuspicious findings (calcifications\nand soft tissue lesions).\nThe CAD output provided by the\nserver includes the location and the\noutline of findings.\nMammoScreen processing server is\na standalone system WITH a user\ninterface.","Distinguishes two types of\nsuspicious findings\n(calcifications and soft tissue\nlesions).\nThe CAD output provided by\nthe server includes the location\nand the outline of findings.\nTranspara™ processing server\nis a standalone system\nWITHOUT a user interface.","","","Despite some\ndifferences between\nthe predicate device\nand MammoScreen,\nfeatures are still\ncomparable and do\nnot raise new\nquestions regarding\nsafety and\neffectiveness of the\ndevice."],["Imaging\nModality","FFDM","SAME","","","Yes, identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p10-t0","doc_id":"K192854","page_num":10,"bbox":[72.31,72.36,539.81,252.29],"n_rows":4,"n_cols":6,"columns":["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],"rows":[["","Subject Device\nMammoScreen","","Predicate Device","","Substantially\nEquivalent?"],["","","","TransparaTM","",""],["","","","K181704","",""],["Fundamental\nscientific\ntechnology","In MammoScreen, a range of\nmedical image processing and\nmachine learning techniques are\nimplemented. The system includes\n‘deep learning’ modules for\nrecognition of suspicious\ncalcifications and soft tissue\nlesions. These modules are trained\nwith very large databases of biopsy-\nproven examples of breast cancer\nand normal tissue.","SAME","","","Yes, identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p12-t0","doc_id":"K192854","page_num":12,"bbox":[72.22,575.95,545.5,631.18],"n_rows":2,"n_cols":5,"columns":["","Hologic®","GE®","Combined","FOM -FOM\nGE HOL"],"rows":[["","Hologic®","GE®","Combined","FOM -FOM\nGE HOL"],["ROC\nAUC","0.868 (0.851, 0.885)","0.887 (0.875, 0.898)","0.883 (0.873, 0.892)","0.018 (-0.002, 0.039)"]],"caption_candidate":"acquired on GE® devices, are given in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p13-t0","doc_id":"K192854","page_num":13,"bbox":[72.26,72.24,545.5,112.82],"n_rows":2,"n_cols":5,"columns":["Sensitivity","0.844 (0.815, 0.872)","0.849 (0.827, 0.871)","0.847 (0.829, 0.864)","0.005 (-0.032, 0.042)1"],"rows":[["Sensitivity","0.844 (0.815, 0.872)","0.849 (0.827, 0.871)","0.847 (0.829, 0.864)","0.005 (-0.032, 0.042)1"],["Specificity","0.705 (0.689, 0.722)","0.738 (0.728, 0.747)","0.729 (0.721, 0.737)","0.032 (0.014, 0.051)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p13-t1","doc_id":"K192854","page_num":13,"bbox":[72.26,539.11,545.5,635.02],"n_rows":4,"n_cols":5,"columns":["","Hologic®","GE®","Combined","FOM -FOM\nGE HOL"],"rows":[["","Hologic®","GE®","Combined","FOM -FOM\nGE HOL"],["ROC\nAUC","0.901 (0.886, 0.915)","0.916 (0.906, 0.926)","0.911 (0.902, 0.919)","0.015 (-0.002, 0.033)"],["Sensitivity","0.813 (0.781, 0.843)","0.830 (0.808, 0.853)","0.823 (0.805, 0.841)","0.017 (-0.023, 0.056)"],["Specificity","0.840 (0.831, 0.848)","0.846 (0.840, 0.851)","0.844 (0.839, 0.849)","0.006 (-0.004, 0.016)"]],"caption_candidate":"comparison with FFDM acquired on GE® devices, are given in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p15-t0","doc_id":"K192854","page_num":15,"bbox":[72.26,315.29,536.38,369.65],"n_rows":2,"n_cols":4,"columns":["MammoScreen Score","MS1","MS3","MS5"],"rows":[["MammoScreen Score","MS1","MS3","MS5"],["Filtering slider\nposition","Left (Lowest\nSuspicion shown)","Middle (Lowest\nSuspicion hidden)","Right (Low Suspicion\nhidden)"]],"caption_candidate":"5.3.1.1 Filtering of findings) and corresponding to MammoScreen scores 1, 3 and 5 respectively.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p15-t1","doc_id":"K192854","page_num":15,"bbox":[62.3,389.93,549.7,669.1],"n_rows":18,"n_cols":6,"columns":["Soft tissue lesions","","","","",""],"rows":[["Soft tissue lesions","","","","",""],["","","Hologic®","GE®","Combined","FOMGE-FOMHOL"],["LROC","AUC (primary)","0.837 (0.811, 0.861)","0.900 (0.884, 0.916)","0.877 (0.862, 0.890)","0.064 (0.034, 0.095)"],["","Sensitivity @ MS1","0.942 (0.921, 0.963)","0.976 (0.964, 0.987)","0.962 (0.951, 0.973)","0.034 (0.010, 0.060)"],["","Sensitivity @ MS3","0.926 (0.902, 0.949)","0.966 (0.951, 0.978)","0.950 (0.937, 0.963)","0.039 (0.012, 0.067)"],["","Sensitivity @ MS5","0.774 (0.735, 0.811)","0.852 (0.824, 0.879)","0.822 (0.799, 0.843)","0.080 (0.032, 0.128)"],["","","","","",""],["","Specificity @ MS1","0.109 (0.102, 0.116)","0.166 (0.161, 0.172)","0.150 (0.146, 0.155)","0.058 (0.048, 0.067)"],["","Specificity @ MS3","0.233 (0.222, 0.242)","0.222 (0.216, 0.228)","0.225 (0.219, 0.230)","-0.011 (-0.022, 0.002)"],["","Specificity @ MS5","0.780 (0.771, 0.791)","0.801 (0.795, 0.807)","0.795 (0.790, 0.800)","0.021 (0.010, 0.032)"],["","","","","",""],["FROC","Sensitivity @ MS1","0.895 (0.872, 0.915)","0.952 (0.940, 0.963)","0.930 (0.918, 0.940)","0.057 (0.033, 0.081)"],["","Sensitivity @ MS3","0.878 (0.854, 0.901)","0.943 (0.930, 0.955)","0.918 (0.906, 0.929)","0.064 (0.038, 0.090)"],["","Sensitivity @ MS5","0.750 (0.718, 0.782)","0.835 (0.814, 0.855)","0.802 (0.784, 0.819)","0.084 (0.047, 0.121)"],["","","","","",""],["","Avg false marks @ MS1","1.819 (1.815, 1.824)","1.268 (1.266, 1.270)","1.424 (1.422, 1.426)","NA"],["","Avg false marks @ MS3","1.182 (1.171, 1.193)","1.026 (1.021, 1.031)","1.070 (1.066, 1.075)","NA"],["","Avg false marks @ MS5","0.294 (0.286, 0.302)","0.218 (0.214, 0.222)","0.239 (0.235, 0.243)","NA"]],"caption_candidate":"position Suspicion shown) Suspicion hidden) hidden)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192854-p16-t0","doc_id":"K192854","page_num":16,"bbox":[104.16,124.28,539.98,756.1],"n_rows":30,"n_cols":16,"columns":["AUC (primar","y",")","0.974","(0.959,","0.985)","0.930","(0.912,","0.948)","0.942","(0.928,","0.954)","-0.044","(-0",".067,","-0.021)"],"rows":[["AUC (primar","y",")","0.974","(0.959,","0.985)","0.930","(0.912,","0.948)","0.942","(0.928,","0.954)","-0.044","(-0",".067,","-0.021)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S1","0.994","(0.979,","1.000)","0.971","(0.953,","0.987)","0.978","(0.964,","0.989)","-0.023","(-0",".043,","-0.001)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S3","0.994","(0.979,","1.000)","0.971","(0.953,","0.987)","0.978","(0.964,","0.989)","-0.023","(-0",".043,","-0.001)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S5","0.962","(0.930,","0.988)","0.804","(0.764,","0.844)","0.851","(0.820,","0.879)","-0.158","(-0",".209,","-0.108)"],["","","","","","","","","","","","","","","",""],["Specificity @","M","S1","0.549","(0.537,","0.561)","0.645","(0.638,","0.652)","0.619","(0.613,","0.625)","0.096","(0",".083,","0.110)"],["","","","","","","","","","","","","","","",""],["Specificity @","M","S3","0.584","(0.573,","0.597)","0.658","(0.652,","0.665)","0.638","(0.632,","0.644)","0.074","(0",".061,","0.088)"],["","","","","","","","","","","","","","","",""],["Specificity @","M","S5","0.869","(0.861,","0.878)","0.909","(0.905,","0.913)","0.898","(0.894,","0.901)","0.040","(0",".031,","0.048)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S1","0.994","(0.984,","1.000)","0.941","(0.923,","0.956)","0.957","(0.944,","0.969)","-0.052","(-0",".072,","-0.033)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S3","0.994","(0.984,","1.000)","0.938","(0.920,","0.955)","0.955","(0.941,","0.968)","-0.055","(-0",".075,","-0.036)"],["","","","","","","","","","","","","","","",""],["Sensitivity @","M","S5","0.942","(0.916,","0.968)","0.779","(0.747,","0.809)","0.828","(0.805,","0.851)","-0.163","(-0",".202,","-0.124)"],["","","","","","","","","","","","","","","",""],["Avg false mar","k","s @ MS1","0.870","(0.867,","0.873)","0.531","(0.529,","0.532)","0.627","(0.625,","0.628)","","","NA",""],["","","","","","","","","","","","","","","",""],["Avg false mar","k","s @ MS3","0.753","(0.748,","0.759)","0.479","(0.477,","0.482)","0.557","(0.554,","0.559)","","","NA",""],["","","","","","","","","","","","","","","",""],["Avg false mar","k","s @ MS5","0.238","(0.232,","0.245)","0.122","(0.119,","0.125)","0.155","(0.152,","0.158)","","","NA",""],["","","","","","","","","","","","","","","",""],["","","Figure 7.5: LR","OC (","left) an","d FROC","(right)","curves","on US soft","tissu","e lesion","s only.","","","",""],["","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","Pag","e","13","of 21"],["submission","M","ammoScre","en™","","","","","","","","","","","",""]],"caption_candidate":"0.974 (0.959, 0.985) 0.930 (0.912, 0.948) 0.942 (0.928, 0.954) -0.044 (-0.067, -0.021)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K192854-p20-t0","doc_id":"K192854","page_num":20,"bbox":[44.28,144.16,730.59,478.48],"n_rows":37,"n_cols":11,"columns":["FOM","MS1","MS2","MS3","MS4","MS5","MS6","MS7","MS8","MS9","MS10"],"rows":[["FOM","MS1","MS2","MS3","MS4","MS5","MS6","MS7","MS8","MS9","MS10"],["","","","","","","","","","",""],["","1.0000","1.0000","0.9991","0.9984","0.9979","0.9956","0.9939","0.9928","0.9922","0.9922"],["NPV (1.00","00 - 1.0000)","","","","","","","","",""],["","(1.00","00 - 1.0000) (0.99","87 - 0.9995) (0.99","77 - 0.9991) (0.99","70 - 0.9987) (0.99","46 - 0.9964) (0.99","27 - 0.9948) (0.99","16 - 0.9938) (0.99","11 - 0.9932) (0.99","11 - 0.9"],["","","","","","","","","","",""],["","0.0162","0.0460","0.2175","0.5632","0.7185","0.9690","0.9942","0.9987","1.0000","1.0000"],["Specificity","","","","","","","","","",""],["(0.01","29 - 0.0196) (0.03","90 - 0.0533) (0.20","51 - 0.2309) (0.54","24 - 0.5805) (0.70","15 - 0.7332) (0.96","27 - 0.9739) (0.99","22 - 0.9968) (0.99","68 - 0.9998) (1.00","00 - 1.0000) (1.00","00 - 1.0"],["","","","","","","","","","",""],["","0.0078","0.0079","0.0082","0.0097","0.0158","0.0221","0.1049","0.2443","0.3788","1.0000"],["PPV","","","","","","","","","",""],["(0.00","68 - 0.0089) (0.00","69 - 0.0091) (0.00","71 - 0.0094) (0.00","84 - 0.0111) (0.01","34 - 0.0180) (0.01","85 - 0.0250) (0.08","63 - 0.1267) (0.18","04 - 0.3734) (0.16","62 - 0.7885) (1.00","00 - 1.0"],["","","","","","","","","","",""],["","1.0000","1.0000","1.0000","0.9764","0.8882","0.8073","0.4584","0.2294","0.0844","0.0000"],["Sensitivity","","","","","","","","","(0.00","00 - 0.0"],["(1.00","00 - 1.0000) (1.00","00 - 1.0000) (1.00","00 - 1.0000) (0.96","17 - 0.9862) (0.83","97 - 0.9302) (0.73","31 - 0.8737) (0.40","40 - 0.5177) (0.19","56 - 0.2693) (0.06","43 - 0.1036)",""],["","","","","","","","","","",""],["","","","","","GE®","","","","",""],["","","","","","","","","","",""],["FOM","MS1","MS2","MS3","MS4","MS5","MS6","MS7","MS8","MS9","MS10"],["","","","","","","","","","",""],["","1.0000","1.0000","0.9996","0.9992","0.9988","0.9973","0.9965","0.9955","0.9953","0.9952"],["NPV","","","","","","","","","",""],["(1.00","00 - 1.0000) (1.00","00 - 1.0000) (0.99","94 - 0.9997) (0.99","87 - 0.9994) (0.99","82 - 0.9991) (0.99","69 - 0.9978) (0.99","60 - 0.9969) (0.99","50 - 0.9960) (0.99","47 - 0.9958) (0.99","47 - 0.9"],["","","","","","","","","","",""],["","0.0409","0.0610","0.4238","0.6339","0.7741","0.9808","0.9973","1.0000","1.0000","1.0000"],["Specificity","","","","","","","","","",""],["(0.03","72 - 0.0448) (0.05","58 - 0.0655) (0.41","08 - 0.4338) (0.62","32 - 0.6442) (0.76","59 - 0.7822) (0.97","86 - 0.9838) (0.99","62 - 0.9982) (1.00","00 - 1.0000) (1.00","00 - 1.0000) (1.00","00 - 1.0"],["","","","","","","","","","",""],["","0.0048","0.0050","0.0051","0.0079","0.0115","0.0166","0.1015","0.3154","1.0000","1.0000"],["PPV","","","","","","","","","",""],["(0.00","42 - 0.0053) (0.00","44 - 0.0055) (0.00","45 - 0.0056) (0.00","70 - 0.0088) (0.01","03 - 0.0127) (0.01","48 - 0.0184) (0.08","61 - 0.1235) (0.23","85 - 0.4166) (1.00","00 - 1.0000) (1.00","00 - 1.0"],["","","","","","","","","","",""],["","1.0000","1.0000","1.0000","0.9626","0.8936","0.7992","0.4513","0.2579","0.0516","0.0078"],["Sensitivity","","","","","","","","","",""],["(1.00","00 - 1.0000) (1.00","00 - 1.0000) (1.00","00 - 1.0000) (0.95","29 - 0.9731) (0.82","88 - 0.9233) (0.73","25 - 0.8514) (0.40","54 - 0.5004) (0.22","36 - 0.2983) (0.03","98 - 0.0635) (0.00","35 - 0.0"]],"caption_candidate":"FOM MS1 MS2 MS3 MS4 MS5 MS6 MS7 MS8 MS9 MS10","well_formed":true,"extraction_settings":"text"}
{"table_id":"K192880-p5-t0","doc_id":"K192880","page_num":5,"bbox":[85.01,445.83,706.99,557.1],"n_rows":3,"n_cols":8,"columns":["Item","","InferRead Lung CT.AI","","","ClearRead CT (K161201)","","Comparison"],"rows":[["Item","","InferRead Lung CT.AI","","","ClearRead CT (K161201)","","Comparison"],["","","(Subject Device)","","","(Predicate Device)","",""],["Indications for\nUse","InferRead Lung CT.AI is\ncomprised of computer\nassisted reading tools\ndesigned to aid the\nradiologist in the detection\nof pulmonary nodules","","","ClearRead CT™ is\ncomprised of computer\nassisted reading tools\ndesigned to aid the\nradiologist in the detection of\npulmonary nodules during","","","The indications for use of InferRead Lung\nCT.AI are identical to the indications for\nuse of the previously cleared ClearRead\nCT."]],"caption_candidate":"Detailed Comparison of the Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192880-p6-t0","doc_id":"K192880","page_num":6,"bbox":[84.96,71.22,707.04,543.9],"n_rows":7,"n_cols":4,"columns":["","during the review of CT\nexaminations of the chest on\nan asymptomatic population.\nInferRead Lung CT.AI\nrequires that both lungs be\nin the field of view.\nInferRead Lung CT.AI\nprovides adjunctive\ninformation and is not\nintended to be used without\nthe original CT series.","review of CT examinations\nof the chest on an\nasymptomatic population.\nThe ClearRead CT requires\nboth lungs be in the field of\nview. ClearRead CT provides\nadjunctive information and is\nnot intended to be used\nwithout the original CT\nseries.",""],"rows":[["","during the review of CT\nexaminations of the chest on\nan asymptomatic population.\nInferRead Lung CT.AI\nrequires that both lungs be\nin the field of view.\nInferRead Lung CT.AI\nprovides adjunctive\ninformation and is not\nintended to be used without\nthe original CT series.","review of CT examinations\nof the chest on an\nasymptomatic population.\nThe ClearRead CT requires\nboth lungs be in the field of\nview. ClearRead CT provides\nadjunctive information and is\nnot intended to be used\nwithout the original CT\nseries.",""],["Intended Use","Computer assisted reading\ntools designed to aid the\nradiologist in the detection\nof pulmonary nodules\nduring review of CT\nexaminations of the chest.","Computer assisted reading\ntools designed to aid the\nradiologist in the detection of\npulmonary nodules during\nreview of CT examinations\nof the chest.","The intended use of InferRead Lung\nCT.AI is identical to the intended use of\nthe previously cleared ClearRead CT."],["Accessories/Tools\nRequired by the\nUser (Platform)","Must be used in conjunction\nwith a PACS system or an\nImage Viewer that reads\nDICOM images.","Must be used in conjunction\nwith a PACS system or an\nImage Viewer that reads\nDICOM images.","The accessories required by the user for\nInferRead Lung CT.AI are identical to the\naccessories required by the user for the\npreviously cleared ClearRead CT."],["User Access\nPoint","Post Processing Application","Post Processing Application","The user access point of InferRead Lung\nCT.AI is identical to the user access point\nof the previously cleared ClearRead CT."],["Image Input","DICOM","DICOM","The image input of InferRead Lung CT.AI\nis identical to the image input of the\npreviously cleared ClearRead CT."],["Type of Scans","CT","CT","The type of scans for InferRead Lung\nCT.AI are identical to the type of scans for\nthe previously cleared ClearRead CT."],["Automatically\nLocate and\nIdentify Lung\nNodules","Yes","Yes","The function of automatically locating and\nidentifying lung nodules for InferRead\nLung CT.AI is identical to the function of\nautomatically locating and identifying"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192880-p7-t0","doc_id":"K192880","page_num":7,"bbox":[84.96,71.22,707.04,555.72],"n_rows":3,"n_cols":4,"columns":["","","","lung nodules for the previously cleared\nClearRead CT."],"rows":[["","","","lung nodules for the previously cleared\nClearRead CT."],["Modifies the\nOriginal CT\nScan","No","Yes","According to the device description of the\npredicate device found in its 510K\nsummary, “ClearRead CT is a dedicated\npost-processing application that generates\na secondary vessel suppressed Lung CT\nseries with CADe marks and associated\nregion descriptors intended to aid the\nradiologist in the detection of pulmonary\nnodules.” ClearRead CT modifies the\noriginal scan by performing vessel\nsuppression. On the contrary, InferRead\nLung CT.AI does not modify the original\nscan, only shows the locations of\npulmonary nodules.\nThis difference does not affect the\nintended use or safety and effectiveness of\nthe device."],["Requires a\nDisjoint\nComparison with\nthe Original CT\nScan","No","Yes","Since ClearRead CT creates a secondary\nvessel suppressed Lung CT series, it\nrequires the user to have an original CT\nseries on a separate window. There are 2\nseries open at the same time. We refer to\nthis setup as “disjoint comparison”. On the\ncontrary, InferRead Lung CT.AI does not\nrequire 2 series open, as its CADe marks\noverlay with the original CT scan and can\nbe toggled on and off. Therefore,\nInferRead Lung CT.AI does not require\n“disjoint comparison”\nThis difference does not affect the\nintended use or safety and effectiveness of\nthe device. CT scans processed by"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192880-p8-t0","doc_id":"K192880","page_num":8,"bbox":[84.96,71.22,707.04,418.74],"n_rows":5,"n_cols":4,"columns":["","","","InferRead Lung CT.AI display the original\nCT scans."],"rows":[["","","","InferRead Lung CT.AI display the original\nCT scans."],["Nodule Marking","A bounding box is provided\naround nodules","A bounding box is provided\naround nodules","The function of providing a bounding box\naround nodules for InferRead Lung CT.AI\nis identical to the indications for use of the\npreviously cleared ClearRead CT."],["Provides Nodule\nCharacteristics","Yes, the maximum axial\nplane longest diameter,\nmean diameter and volume\ninformation are provided.","Yes, the volume, maximum\naxial plane diameter,\nminimum axial plane\ndiameter, and average\ndensity in Hounsfield units\nare provided. (from website)","InferRead Lung CT.AI has mean diameter\nmeasurement function that is not provided\nby predicate device. Mean diameter is the\naverage of maximum axial plane diameter\nand minimum axial plane diameter. And\nthis difference does not affect the safety\nand effectiveness of the device."],["Detection\nTarget(s)","Solid, Sub Solid (part solid\nand ground glass) nodules","Solid, Sub Solid (part solid\nand ground glass) nodules","The detection targets of InferRead Lung\nCT.AI are identical to the detection targets\nof the previously cleared ClearRead CT.\nThey have the same definition principles\nfor actionable nodules classification."],["Size of Detection\nTargets","4mm and above, supports\nvisualization of nodules\nsmaller than 4mm","5mm and above, supports\nvisualization of nodules\nsmaller than 5mm","The InferRead Lung CT.AI detects smaller\nnodules. This difference does not affect\nthe intended use or safety and\neffectiveness of the device. This difference\nhas been addressed with the completion of\nstand-alone performance characteristics\ntesting."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192901-p4-t0","doc_id":"K192901","page_num":4,"bbox":[72.57,546.98,531.18,633.14],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","CmTriage"],"rows":[["Proprietary Name","CmTriage"],["Premarket Notification","K183285"],["Classification Name","Radiological Computer-Assisted Prioritization Software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QFM"],["Regulatory Class","II"]],"caption_candidate":"The HealthVCF device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192901-p7-t0","doc_id":"K192901","page_num":7,"bbox":[72.77,72.31,554.23,711.95],"n_rows":8,"n_cols":4,"columns":["","suggestive of the presence\nof at least one vertebral\ncompression at the exam\nlevel. These flags are\nviewed by the clinician in\nBone Health and Fracture\nLiaison Service programs\nin the medical setting via\na worklist application on\ntheir Picture Archiving\nand Communication\nSystem (PACS).\nHealthVCF does not send\na proactive alert directly\nto the user.\nHealthVCF does not\nprovide diagnostic\ninformation beyond triage\nand prioritization, it does\nnot remove cases from the\nradiology worklist, and\nshould not be used in\nplace of full patient\nevaluation, or relied upon\nto make or confirm\ndiagnosis.","exam level. These flags are\nviewed by the radiologist via\ntheir Picture Archiving and\nCommunication System\n(PACS) worklist. The\ndecision to use cmTriage\ncodes and how to use\ncmTriage codes is ultimately\nup to the radiologist.\ncmTriage does not send a\nproactive alert directly to the\nradiologist. Radiologists are\nresponsible for reviewing\neach exam on a diagnostic\nviewer according to the\ncurrent standard of care.\ncmTriage is limited to the\ncategorization of exams, does\nnot provide any diagnostic\ninformation beyond triage\nand prioritization, does not\nremove images from the\nradiologist’s worklist, and\nshould not be used in lieu of\nfull patient evaluation, or\nrelied upon to make or\nconfirm diagnosis. cmTriage\nis for prescription use only.",""],"rows":[["","suggestive of the presence\nof at least one vertebral\ncompression at the exam\nlevel. These flags are\nviewed by the clinician in\nBone Health and Fracture\nLiaison Service programs\nin the medical setting via\na worklist application on\ntheir Picture Archiving\nand Communication\nSystem (PACS).\nHealthVCF does not send\na proactive alert directly\nto the user.\nHealthVCF does not\nprovide diagnostic\ninformation beyond triage\nand prioritization, it does\nnot remove cases from the\nradiology worklist, and\nshould not be used in\nplace of full patient\nevaluation, or relied upon\nto make or confirm\ndiagnosis.","exam level. These flags are\nviewed by the radiologist via\ntheir Picture Archiving and\nCommunication System\n(PACS) worklist. The\ndecision to use cmTriage\ncodes and how to use\ncmTriage codes is ultimately\nup to the radiologist.\ncmTriage does not send a\nproactive alert directly to the\nradiologist. Radiologists are\nresponsible for reviewing\neach exam on a diagnostic\nviewer according to the\ncurrent standard of care.\ncmTriage is limited to the\ncategorization of exams, does\nnot provide any diagnostic\ninformation beyond triage\nand prioritization, does not\nremove images from the\nradiologist’s worklist, and\nshould not be used in lieu of\nfull patient evaluation, or\nrelied upon to make or\nconfirm diagnosis. cmTriage\nis for prescription use only.",""],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Bone Health Clinician","Radiologist","Different, but both\nusers include a\n“designated list of\nclinicians” per 21\nCFR 892.2080"],["Identify patients\nwith prespecified\nclinical condition","Yes","Yes","Same"],["Clinical condition","Vertebral compression\nfracture","Breast Cancer","Different but both\nfindings suggestive of\na pre-specified clinical\ncondition"],["Alert to finding","Yes; notification flagged\nfor review","Yes; notification flagged for\nreview","Same"],["Independent of\nstandard of care\nworkflow","Yes; No cases are\nremoved\nfrom worklist","Yes; No cases are removed\nfrom worklist","Same"],["Modality","CT","FFDM screening\nmammograms","Different, but both run\non “radiological"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192901-p8-t0","doc_id":"K192901","page_num":8,"bbox":[72.77,72.31,554.23,332.32],"n_rows":6,"n_cols":4,"columns":["","","","medical images” per\n21 CFR 892.2080"],"rows":[["","","","medical images” per\n21 CFR 892.2080"],["Body part","Chest and abdomen","Breast","Different anatomical\nsites but both\n“operates on\nradiological images of\nthe human body” per\n21 CFR 892.2080."],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Same"],["Limited to analysis\nof imaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with\nindicated findings","Yes","Yes","Same"],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K192962-p4-t0","doc_id":"K192962","page_num":4,"bbox":[70.88,296.62,297.94,550.46],"n_rows":7,"n_cols":2,"columns":["Name:","icometrix NV"],"rows":[["Name:","icometrix NV"],["Address:","Kolonel Begaultlaan 1b/12\n3012 Leuven\nBelgium"],["Contact Person:","Dirk Smeets"],["Telephone number:","+32 16 369 000"],["Fax Number:","N.A."],["E-mail:","dirk.smeets@icometrix.com"],["Date Prepared:","28 Feb 2020"]],"caption_candidate":"5.1 Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192962-p5-t0","doc_id":"K192962","page_num":5,"bbox":[70.88,138.04,349.39,306.56],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","icobrain ctp"],"rows":[["Device Trade Name:","icobrain ctp"],["Common Name","Medical Image Processing Software"],["Classification Name","System, Image processing, Radiological"],["Number","892.2050"],["Product Code:","LLZ"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192962-p5-t1","doc_id":"K192962","page_num":5,"bbox":[70.88,386.03,292.61,578.92],"n_rows":7,"n_cols":2,"columns":["Item","Description"],"rows":[["Item","Description"],["510(k) Number","K180161"],["Device Name","Viz CTP"],["Original Applicant","Viz.ai, Inc."],["Regulation Number","21 CFR 892.2050"],["Classification Product Code","LLZ"],["510k Review Panel","Radiology"]],"caption_candidate":"5.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192962-p7-t0","doc_id":"K192962","page_num":7,"bbox":[70.93,126.34,524.4,769.77],"n_rows":13,"n_cols":4,"columns":["","Device to market","Proposed predicate device","Proposed Reference device"],"rows":[["","Device to market","Proposed predicate device","Proposed Reference device"],["Device\nTrade Name","icobrain ctp","Viz CTP","RAPID"],["Common\nName","Medical Image Processing Software","Picture archiving and communications system","Picture archiving and communications\nsystem"],["510(k)\nNumber","K192962","K180161","K121447"],["Manufacturer","icometrix NV\nKolonel Begaultlaan 1b / 12\n3012 Leuven\nBELGIUM","Viz.ai, Inc.\n855 El Camino Real Suite 13A-252\nPalo Alto, CA 94301","iSchemaView, Inc.\n323 Olmsted Road\nStanford, CA 94305"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050"],["Device\nClassification\nName","System, Image processing,\nRadiological","System, Image processing, Radiological","System, Image processing, Radiological"],["Product\nCode","LLZ","LLZ","LLZ"],["Regulatory\nClass","II","II","II"],["Classification\nPanel","Radiology","Radiology","Radiology"],["Indications\nfor use","icobrain ctp is an image processing\nsoftware package to be used by\ntrained professionals, including but\nnot limited to physicians and\nmedical technicians. The software\nruns on a standard \"off-the-shelf\"\ncomputer or a virtual platform,\nsuch as VMware, and can be used\nto perform image processing,\nanalysis, and communication of\ncomputed tomography (CT)\nperfusion scans of the brain. Data\nand images are acquired through\nDICOM-compliant imaging devices.\nicobrain ctp provides both analysis\nand communication capabilities for\ndynamic imaging datasets that are\nacquired with CT Perfusion imaging\nprotocols. Analysis includes\ncalculation of parameters related to\ntissue flow (perfusion) and tissue\nblood volume. Results of image\nprocessing which include CT\nperfusion parameter maps\ngenerated from a raw CTP scan are\nexported in the standard DICOM\nformat and may be viewed on\nexisting radiological imaging viewers.","Viz CTP is an image processing software\npackage to be used by trained professionals,\nincluding but not limited to physicians and\nmedical technicians. The software runs on a\nstandard \"off-the-shelf\" computer or a virtual\nplatform, such as VMware, and can be used\nto perform image processing, analysis, and\ncommunication of computed tomography\n(CT) perfusion scans of the brain. Data and\nimages are acquired through DICOM-\ncompliant imaging devices.\nViz CTP provides both analysis and\ncommunication capabilities for dynamic\nimaging datasets that are acquired with CT\nPerfusion imaging protocols. Analysis\nincludes calculation of parameters related to\ntissue flow (perfusion) and tissue blood\nvolume. Results of image processing which\ninclude CT perfusion parameter maps\ngenerated from a raw CTP scan are\nexported in the standard DICOM format\nand may be viewed on existing radiological\nimaging viewers.","iSchemaView's RAPID is an image\nprocessing software package to be used\nby trained professionals, including but not\nlimited to physicians and medical\ntechnicians. The software runs on a\nstandard \"off-the-shelf\" computer or a\nvirtual platform, such as VMware, and can\nbe used to perform image viewing,\nprocessing and analysis of brain images.\nData and images are acquired through\nDICOM compliant imaging devices.\niSchemaView's RAPID provides both\nviewing and analysis capabilities for\nfunctional and dynamic imaging datasets\nacquired with CT Perfusion and MRI\nincluding a Diffusion Weighted MRI\n(DWl) Module and a Dynamic Analysis\nModule (dynamic contrast enhanced\nimaging data for MRI and CT)."],["","","",""],["PACS functionality","","",""]],"caption_candidate":"5.6 Comparison with predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192962-p8-t0","doc_id":"K192962","page_num":8,"bbox":[70.9,71.44,524.4,699.72],"n_rows":25,"n_cols":4,"columns":["Basic PACS\nfunctions","Yes","Yes","Yes"],"rows":[["Basic PACS\nfunctions","Yes","Yes","Yes"],["Computer\nplatform","Standard \"off-the-shelf\" computer\nor a virtual platform.","Same","Same"],["DICOM\ncompliance","Yes","Yes","Yes"],["Functional\noverview","icobrain ctp is a software package\nthat provides for the quantification\nand visualization of the perfusion of\ntissue based on dynamic contrast\nenhanced CT images.","Same","Automatic analysis for functional and\ndynamic imaging datasets acquired with\nCT Perfusion and MRI including a\nDiffusion Weighted MRI (DWl) Module\nand a Dynamic Analysis Module (dynamic\ncontrast enhanced imaging data for MRI\nand CT)."],["Data\nAcquisition","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities.","Same","Same"],["Data/Image\nTypes","Computed Tomography (CT)","Same","CT and MR scanner"],["Acquisition and Modalities Features","","",""],["CT","CT Perfusion","Yes","Yes"],["Computed Parameter Maps","","",""],["Perfusion CT","Cerebral Blood Flow (CBF)","Yes","Yes"],["","Cerebral Blood Volume (CBV)","Yes","Yes"],["","Mean Transit Time (MTT)","Yes","Yes"],["","Tissue residue function time to\npeak (TMax)","Yes","Yes"],["Measurements/Tools","","",""],["","Arterial Input Function (AIF) /\nVenous Output Function (VOF)","Same","Same"],["","Brain mask","Same","Same"],["","Export perfusion files to PACS and\nDICOM file systems","Same","Same"],["","Acquire, transmit, process, and\nstore medical images","Same","Same"],["Volumetry","","",""],["Default\nTmax\nabnormality","Tmax > 6s","Same","Same"],["Default CBF\nabnormality","CBF < 30%","Same","Same"],["Default\nMismatch\nvolume","(Tmax > 6s) - (CBF < 30%)","Same","Same"],["Default\nMismatch\nratio","(Tmax > 6s) / (CBF < 30%)","Same or not shown","Same"],["User\nadjustable","No","Yes","Yes"],["Validation","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192969-p6-t0","doc_id":"K192969","page_num":6,"bbox":[72.3,243.26,551.27,611.26],"n_rows":15,"n_cols":3,"columns":["Feature","Subject Device:\nEzra Plexo Software","Predicate Device:\nArterys Oncology DL\n(K173542)"],"rows":[["Feature","Subject Device:\nEzra Plexo Software","Predicate Device:\nArterys Oncology DL\n(K173542)"],["Platform","Chrome Desktop","Client-server, Chrome Desktop"],["DICOM Compliant","Yes","Yes"],["Type of Scans","MR","MR, CT"],["Image Navigation\nTools","Pan, zoom, rotate, slice scroll (view\nmultiple slices)\nAdjust window level, minimize/maxi-\nmize\nOrientation labels, scroll sync, ruler","Pan, zoom, rotate, slice scroll (view\nmultiple slices)\nAdjust window level, minimize/maxi-\nmize\nOrientation labels, cross-reference in-\ndicator"],["Image Display Modes","Yes, static","Yes, static and cine"],["Text Annotation on\nthe Image","Yes","Yes"],["Layout","Can select a viewport layout\nand add series to it","Can select a viewport layout\nand add series to it"],["2D Image Review","Yes","Yes"],["3D Image Review","Yes, 3D review of segmented region","Yes, 3D review of the full image"],["Create MPR Images","No","Yes"],["Manual Segmentation","Yes","Yes"],["2D Semi-Automated\nSegmentation","Yes, available only for MR prostate\nstudies","Yes, available only for lung CT and\nliver MR studies"],["Linear Dimension Cal-\nculation","Yes","Yes"],["Volume Calculation","Yes","Yes"]],"caption_candidate":"characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192973-p5-t0","doc_id":"K192973","page_num":5,"bbox":[61.07,515.5,547.09,676.12],"n_rows":7,"n_cols":4,"columns":["Manufacturer","510(K) Submitter","Predicate","Significant\nDifferences"],"rows":[["Manufacturer","510(K) Submitter","Predicate","Significant\nDifferences"],["","Densitas, Inc.","Densitas, Inc.",""],["Trade Name","densitas densityai\n​ ​™\n(formerly DM-Density )\n™","DM-Density\n™",""],["510(k) Number","K192973","K170540","N/A"],["Product Code","LLZ","LLZ","N/A"],["Regulation\nNumber","21 CFR Part 892.2050","21 CFR Part 892.2050","N/A"],["Regulation Name","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological","N/A"]],"caption_candidate":"Table 1 – Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192973-p6-t0","doc_id":"K192973","page_num":6,"bbox":[61.12,76.83,547.12,714.38],"n_rows":6,"n_cols":4,"columns":["​ ​\nIntended Use /\nIndications for Use","Densitas densityai is a\n​ ​™\nsoftware application intended\nfor use with compatible full\nfield digital mammography and\ndigital breast tomosynthesis\nsystems. Densitas densityai\n​ ​™\nprovides an ACR BI-RADS Atlas\n5th Edition breast density\ncategory to aid interpreting\nphysicians in the assessment of\nbreast tissue composition.\nDensitas densityai produces\n​ ​™\nadjunctive information. It is not\na diagnostic aid.","DM-Density is a software\napplication intended for use\nwith compatible full field digital\nmammography\nsystems. DM-Density calculates\npercent breast density defined\nas the ratio of fibroglandular\ntissue to total\nbreast area estimates.\nDM-Density provides these\nnumerical values for each\nbreast as well as a density\ncategory to aid interpreting\nphysicians in the assessment of\nbreast tissue composition.\nDM-Density produces\nadjunctive information. It is not\na diagnostic aid.","Addition of breast\ntomosynthesis\nsystems"],"rows":[["​ ​\nIntended Use /\nIndications for Use","Densitas densityai is a\n​ ​™\nsoftware application intended\nfor use with compatible full\nfield digital mammography and\ndigital breast tomosynthesis\nsystems. Densitas densityai\n​ ​™\nprovides an ACR BI-RADS Atlas\n5th Edition breast density\ncategory to aid interpreting\nphysicians in the assessment of\nbreast tissue composition.\nDensitas densityai produces\n​ ​™\nadjunctive information. It is not\na diagnostic aid.","DM-Density is a software\napplication intended for use\nwith compatible full field digital\nmammography\nsystems. DM-Density calculates\npercent breast density defined\nas the ratio of fibroglandular\ntissue to total\nbreast area estimates.\nDM-Density provides these\nnumerical values for each\nbreast as well as a density\ncategory to aid interpreting\nphysicians in the assessment of\nbreast tissue composition.\nDM-Density produces\nadjunctive information. It is not\na diagnostic aid.","Addition of breast\ntomosynthesis\nsystems"],["Patient Population","Symptomatic and\nasymptomatic women\nundergoing mammography","Symptomatic and\nasymptomatic women\nundergoing mammography","N/A"],["End Users","Interpreting Physicians","Interpreting Physicians","N/A"],["Image Source\nModalities","FFDM\nHologic Selenia Dimensions\nHologic Lorad Selenia\nGE Senographe Essential\nGE Senographe Pristina\nSiemens MAMMOMAT\nInspiration\nSiemens MAMMOMAT\nNovation DR\nSiemens MAMMOMAT Fusion\nSiemens MAMMOMAT\nInspiration Prime\nSiemens MAMMOMAT\nRevelation\nSynthetic 2D\nHologic C-View","Hologic Selenia Dimensions\nHologic Lorad Selenia","Addition of new FFDM\nscan types and\nsynthetic 2d\ncompatibility"],["Input: Image Data\nFormat","DICOM digital mammography\nimager – For Presentation;\nRCC, LCC, RMLO, LMLO","DICOM full field digital\nmammography imager – For\nPresentation; RCC, LCC, RMLO,\nLMLO","similar"],["Output Data","BI-RADS 5th Ed.","BI-RADS 4th Ed.\nFor each breast:\n● Area of fibroglandular tissue\n(cm²)","Removed BI-RADS 4th\nedition compatibility"]],"caption_candidate":"​ ​","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192973-p7-t0","doc_id":"K192973","page_num":7,"bbox":[61.12,76.83,547.12,532.88],"n_rows":10,"n_cols":4,"columns":["​ ​","For each patient: densitas\ndensityai breast density\n​ ™​ ​\ngrade","● Area of breast (cm²)\n● Area-based breast density\n(%)\nFor each patient: DM-Density\nbreast density grade and\npercent breast density\nBI-RADS 5th Ed.\nFor each patient: DM-Density\nbreast density grade",""],"rows":[["​ ​","For each patient: densitas\ndensityai breast density\n​ ™​ ​\ngrade","● Area of breast (cm²)\n● Area-based breast density\n(%)\nFor each patient: DM-Density\nbreast density grade and\npercent breast density\nBI-RADS 5th Ed.\nFor each patient: DM-Density\nbreast density grade",""],["Measurement\nScales","4-category breast density scale\nfrom 5th ​ Ed. ACR BI-RADS Atlas\n​\n2013","4-category breast density scale\nfrom 4th ​ Ed. ACR BI-RADS Atlas\n​\n2003","Removed BI-RADS 4th\nedition compatibility"],["","","4-category breast density scale\nfrom 5th ​ Ed. ACR BI-RADS Atlas\n​\n2013",""],["Output Device","Mammography Workstation,\nPACS, and RIS","Mammography Workstation,\nPACS, and RIS","N/A"],["Output Format","DICOM Structured Report and\nSecondary Capture","DICOM Structured Report and\nSecondary Capture","N/A"],["Deployment","Standalone computer","Standalone computer","N/A"],["Data Throughput","600 cases per hour","600 cases per hour","N/A"],["Assessment scope","Results per image","Results per image","N/A"],["Assessment type","Image feature-based","Area-based","Adjusted to reflect\nshift to image\nfeature-based\nassessment type"],["Anatomical\nLocation","Breast","Breast","N/A"]],"caption_candidate":"​ ​","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192973-p8-t0","doc_id":"K192973","page_num":8,"bbox":[72.22,490.75,539.19,688.88],"n_rows":8,"n_cols":7,"columns":["n=796; Kappa 0.87 (0.87, 0.87)","","","","","",""],"rows":[["n=796; Kappa 0.87 (0.87, 0.87)","","","","","",""],["","","the density software","","","","Accuracy"],["","","A","B","C","D",""],["Radiologist\nConsensus","A","72","20","0","0","78%"],["","B","23","225","47","0","76%"],["","C","0","16","262","37","83%"],["","D","0","0","10","84","89%"],["","Total","95","261","319","121",""]],"caption_candidate":"​","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K192973-p9-t0","doc_id":"K192973","page_num":9,"bbox":[72.32,145.75,466.84,297.38],"n_rows":6,"n_cols":5,"columns":["n=796; Kappa 0.84 (0.8, 0.88)","","","",""],"rows":[["n=796; Kappa 0.84 (0.8, 0.88)","","","",""],["","","the density software","","Accuracy"],["","","Fatty (A,B)","Dense (C,D)",""],["Consensus\nRadiologist","Fatty (A,B)","340","47","88%"],["","Dense (C,D)","16","393","96%"],["","Total","356","440",""]],"caption_candidate":"scan types)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193073-p5-t0","doc_id":"K193073","page_num":5,"bbox":[71.1,532.44,559.92,727.14],"n_rows":3,"n_cols":4,"columns":["Specification/\nAttribute","Primary Predicate Device\nFiltered Back Projection\n(FBP) on uCT 760/780\n(K172135)","Secondary Predicate\nDevice\nDeep Learning Image\nReconstruction (K183202)","Proposed Device\nDeep Recon"],"rows":[["Specification/\nAttribute","Primary Predicate Device\nFiltered Back Projection\n(FBP) on uCT 760/780\n(K172135)","Secondary Predicate\nDevice\nDeep Learning Image\nReconstruction (K183202)","Proposed Device\nDeep Recon"],["Technology","Basic analytic\nreconstruction method","Utilizes a dedicated Deep\nNeural Network (DNN)\nwhich is trained on the CT\nScanner and designed\nspecifically to generate\nhigh quality CT images","Dedicated deep neural\nnetwork (DNN) which is\ntrained on low dose FBP\nimages to get normal\ndose (high quality) FBP\nimages"],["Clinical\nWorkflow","Select recon type and\nconvolution kernel","Select recon type and\nstrength","Select recon type,\nconvolution kernel and\nstrength (noise index\nlevel)"]],"caption_candidate":"7. Comparison of Technological Characteristics with the Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193087-p8-t0","doc_id":"K193087","page_num":8,"bbox":[76.56,461.04,522.0,701.28],"n_rows":3,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison\nFeature","Aidoc Briefcase (K180647)","RAPID ICH"],["Indications\nfor Use","Aidoc Briefcase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-enhanced\nhead CT images.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive findings of\npathologies in head CT images,\nnamely Intracranial Hemorrhage\n(ICH).","RAPID ICH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-\nenhanced head CT images. The\ndevice is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive findings of\npathologies in head CT images,\nnamely Intracranial Hemorrhage\n(ICH)."]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193087-p9-t0","doc_id":"K193087","page_num":9,"bbox":[76.56,75.84,522.0,680.64],"n_rows":6,"n_cols":3,"columns":["","Aidoc Briefcase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not\nalter the original medical image and\nis not intended to be used as a\ndiagnostic device. The results of\nAidoc Briefcase are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","RAPID ICH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to\nthe ongoing standard of care\nimage interpretation. The user is\npresented with notifications for\ncases with suspected ICH\nfindings. Notifications include\ncompressed preview images that\nare meant for informational\npurposes only and not intended\nfor diagnostic use beyond\nnotification. The device does not\nalter the original medical image\nand is not intended to be used as a\ndiagnostic device. The results of\nRAPID ICH are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],"rows":[["","Aidoc Briefcase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not\nalter the original medical image and\nis not intended to be used as a\ndiagnostic device. The results of\nAidoc Briefcase are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","RAPID ICH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to\nthe ongoing standard of care\nimage interpretation. The user is\npresented with notifications for\ncases with suspected ICH\nfindings. Notifications include\ncompressed preview images that\nare meant for informational\npurposes only and not intended\nfor diagnostic use beyond\nnotification. The device does not\nalter the original medical image\nand is not intended to be used as a\ndiagnostic device. The results of\nRAPID ICH are intended to be\nused in conjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],["Stroke/Head","Stroke/Head","Stroke/Head"],["Removal of\ncases from\nworklist\nqueue","No","No"],["Primary\nImaging\nModalities","NCCT","NCCT"],["Technical\nImplementati\non","ML/AI/Neural Network","ML/AI/Neural Network"],["Segmentation\nof ROI","No, the device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file.","No, the device does not highlight\nor direct a user’s attention to a\nspecific location in the image file."]],"caption_candidate":"Section 5: 510(k) Summary (Ver. C)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193087-p10-t0","doc_id":"K193087","page_num":10,"bbox":[76.56,75.84,522.0,368.76],"n_rows":5,"n_cols":3,"columns":["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains."],"rows":[["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains."],["Primary\nUser(s)","Radiologist","Clinician"],["Alteration of\noriginal\nimage data\nbase","No","No"],["Alters\nStandard of\nCare\nWorkflow","In parallel to","In parallel to"],["Notification/\nPrioritization","Yes – PACS, Workstation","Yes – PACS, Workstation, email,\nmobile"]],"caption_candidate":"Section 5: 510(k) Summary (Ver. C)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193097-p4-t0","doc_id":"K193097","page_num":4,"bbox":[93.44,225.2,518.1,299.75],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193097-p5-t0","doc_id":"K193097","page_num":5,"bbox":[95.18,567.18,505.78,644.65],"n_rows":5,"n_cols":5,"columns":["System","","Subject Device","","Predicate Device"],"rows":[["System","","Subject Device","","Predicate Device"],["","","Vantage Orian 1.5T, MRT-1550, V6.0","","Vantage Orian 1.5T, MRT-1550, V6.0"],["Marketed By","","Canon Medical Systems USA, Inc.","","Canon Medical Systems USA, Inc."],["510(k) Number","","This Submission","","K193021"],["Clearance Date","","","","June 3, 2020"]],"caption_candidate":"TABLE No. 1: Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193097-p7-t0","doc_id":"K193097","page_num":7,"bbox":[95.08,100.22,563.15,341.57],"n_rows":11,"n_cols":6,"columns":["Item","","Subject Device:","","Predicate Device:\nVantage Orian 1.5T,\nMRT-1550, V6.0 (K193021)","Notes"],"rows":[["Item","","Subject Device:","","Predicate Device:\nVantage Orian 1.5T,\nMRT-1550, V6.0 (K193021)","Notes"],["","","Vantage Orian 1.5T, MRT-1550, V6.0","","",""],["","","with AiCE Reconstruction Processing","","",""],["","","Unit for MR","","",""],["Static field strength","1.5T","","","1.5T","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","Same"],["ii. Operating mode access\nrequirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","Same"],["Maximum SAR","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33: 2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33: 2010+A1:2013+A2:2015","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193109-p9-t0","doc_id":"K193109","page_num":9,"bbox":[191.07,96.81,534.29,539.82],"n_rows":13,"n_cols":7,"columns":["","Table 6‐1","","","","",""],"rows":[["","Table 6‐1","","","","",""],["","Comparison of the primary currently marketed and predicate","","","","",""],["","device, MRCAT Pelvis versus the proposed MRCAT Brain","","","","",""],["","","","","","",""],["Device","Device","MRCAT Pelvis","MRCAT Brain","","Similarities",""],["","","","","","and",""],["","","","","","Differences",""],["Manufacturer","","Philips Medical\nSystems MR\nFinland","Philips Medical\nSystems MR\nFinland","‐","",""],["510(k)\nNumber","","K182888","K193109","N/A","",""],["Product Code","","MUJ","MUJ","Identical","",""],["Regulation\nNumber","","892.5050","892.5050","Identical","",""],["Regulation\nName","","Accelerator,\nLinear, Medical","Accelerator,\nLinear, Medical","Identical","",""],["Intended use","","MRCAT imaging is\nintended to\nprovide the\noperator with\ninformation of\ntissue properties\nfor radiation\nattenuation\nestimation\npurposes\nin photon external\nbeam radiotherapy\ntreatment\nplanning.","MRCAT imaging is\nintended to\nprovide the\noperator with\ninformation of\ntissue properties\nfor radiation\nattenuation\nestimation\npurposes\nin photon external\nbeam radiotherapy\ntreatment\nplanning.","Identical","",""]],"caption_candidate":"Philips Medical Systems MR Finland","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193109-p10-t0","doc_id":"K193109","page_num":10,"bbox":[191.04,96.66,534.26,511.62],"n_rows":3,"n_cols":4,"columns":["Indications\nfor use","MRCAT Pelvis is\nindicated for\nradiotherapy\ntreatment\nplanning of soft\ntissue cancers in\nthe pelvic region.","MRCAT Brain is\nindicated for\nradiotherapy\ntreatment\nplanning for\nprimary and\nmetastatic brain\ntumor patients.","No significant\ndifference.\nMRCAT Pelvis\nand MRCAT\nBrain are\nboth\nindicated for\nradiotherapy\ntreatment\nplanning in a\ndefined\nregion.\nBrain tumors\nare soft tissue\ntumors."],"rows":[["Indications\nfor use","MRCAT Pelvis is\nindicated for\nradiotherapy\ntreatment\nplanning of soft\ntissue cancers in\nthe pelvic region.","MRCAT Brain is\nindicated for\nradiotherapy\ntreatment\nplanning for\nprimary and\nmetastatic brain\ntumor patients.","No significant\ndifference.\nMRCAT Pelvis\nand MRCAT\nBrain are\nboth\nindicated for\nradiotherapy\ntreatment\nplanning in a\ndefined\nregion.\nBrain tumors\nare soft tissue\ntumors."],["Primary\nimage\ndataset","MRCAT","MRCAT","No significant\ndifference"],["Secondary\nimage\ndataset","mDixon, MRI","mDixon, MRI","No significant\ndifference\nMR images\nobtained in\nthe same\nimaging\nsession are\ninherently in\nthe same\nframe of\nreference."]],"caption_candidate":"Philips Medical Systems MR Finland","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193109-p11-t0","doc_id":"K193109","page_num":11,"bbox":[191.04,96.66,534.28,718.08],"n_rows":4,"n_cols":4,"columns":["Registration\nbetween\nprimary and\nsecondary\nimage\ndatasets","Secondary mDixon\nMR image, source\ndata to MRCAT, is\ninherently\nregistered as part\nof MRCAT\nalgorithm with\nMRCAT image,\nwhich simplifies\nworkflow.\nOther MR images,\nlike T2w and\nfiducial marker\ndetection images\nare registered\nusing tools\navailable in RTP\nsystem","Secondary mDixon\nMR image, source\ndata to MRCAT, is\ninherently\nregistered as part\nof MRCAT\nalgorithm with\nMRCAT image,\nwhich simplifies\nworkflow.\nOther MR images,\nlike T2w images\nare registered\nusing tools\navailable in RTP\nsystem","No significant\ndifference\nSecondary\nMR images\nare obtained\nin the same\nimaging\nsession\nreducing the\npossibility of\npatient\nmotion\nbetween\nimages."],"rows":[["Registration\nbetween\nprimary and\nsecondary\nimage\ndatasets","Secondary mDixon\nMR image, source\ndata to MRCAT, is\ninherently\nregistered as part\nof MRCAT\nalgorithm with\nMRCAT image,\nwhich simplifies\nworkflow.\nOther MR images,\nlike T2w and\nfiducial marker\ndetection images\nare registered\nusing tools\navailable in RTP\nsystem","Secondary mDixon\nMR image, source\ndata to MRCAT, is\ninherently\nregistered as part\nof MRCAT\nalgorithm with\nMRCAT image,\nwhich simplifies\nworkflow.\nOther MR images,\nlike T2w images\nare registered\nusing tools\navailable in RTP\nsystem","No significant\ndifference\nSecondary\nMR images\nare obtained\nin the same\nimaging\nsession\nreducing the\npossibility of\npatient\nmotion\nbetween\nimages."],["Primary\nimage\ndensity\ninformation","MRCAT image\nintensity\ninformation is\nprovided in\nHounsfield Unit\n(HU) values.","MRCAT image\nintensity\ninformation is\nprovided in\nHounsfield Unit\n(HU) values.","No significant\ndifference.\nMRCAT Pelvis\nand MRCAT\nBrain both\nhave\ncontinuous\nHU value\napproach."],["Conversion\nfrom primary\nimage to\ndensity\nvalues used\nin dose\ncalculation","Primary image HU\nvalues are\nconverted to\ndensities through\ndensity table\nspecific for the\nMRCAT.","Primary image HU\nvalues are\nconverted to\ndensities through\ndensity table\nspecific for the\nMRCAT.","No significant\ndifference\nMRCAT has\nspecific\ndensity table\nthat is used in\na similar\nmanner to CT\nspecific\ndensity\ntables."],["MRCAT\nalgorithm","Bones are\nsegmented from\nmDixon inphase\nand water images\nusing model based","Bones are\nsegmented from\nmDixon inphase\nand water images\nusing machine","No significant\ndifference\nSegmentation\nis done for\nboth MRCAT"]],"caption_candidate":"Philips Medical Systems MR Finland","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193109-p14-t0","doc_id":"K193109","page_num":14,"bbox":[191.04,96.66,534.22,678.24],"n_rows":2,"n_cols":4,"columns":["Dose\naccuracy","The simulated\ndose based on\nMRCAT images\nshall not differ in\n95% of prostate\ncancer patients\n(gamma analysis\ncriterion 3%/3mm\nrealized in 99% of\nvoxels within the\nPTV or exceeding\n75% of the\nmaximum dose)\nwhen compared\nwith CT based\nplan.\nThe average\nsimulated dose\nbased on MRCAT\nimages shall not\ndeviate more than\n10% for voxels\nexceeding 5Gy in\n99% of the\nindicated patients\nin the volume of\nsensitive organs\nwhen compared\nwith CT based\nplan.","The simulated\ndose based on\nMRCAT Brain\nimages shall not\ndiffer in 95% of the\nindicated patients\n(gamma analysis\ncriterion 2%/2mm\nrealized in 98% of\nvoxels within the\nPTV or exceeding\n75% of the\nmaximum dose)\nwhen compared\nwith CT‐based\nplan.\nThe average\nsimulated dose\nbased on MRCAT\nBrain shall not\ndeviate more than\n5% or 1 Gy, which\never is greater, in\n99% of the\nindicated patients\nin the volume of\nsensitive organs\nwhen compared\nwith CT based\nplan.","No significant\ndifference.\nThe same\ndose\nevaluation\nmethodology\nis used for\nboth\nproducts. The\ncriteria are\nselected\nbased on the\nneeds of the\napplication."],"rows":[["Dose\naccuracy","The simulated\ndose based on\nMRCAT images\nshall not differ in\n95% of prostate\ncancer patients\n(gamma analysis\ncriterion 3%/3mm\nrealized in 99% of\nvoxels within the\nPTV or exceeding\n75% of the\nmaximum dose)\nwhen compared\nwith CT based\nplan.\nThe average\nsimulated dose\nbased on MRCAT\nimages shall not\ndeviate more than\n10% for voxels\nexceeding 5Gy in\n99% of the\nindicated patients\nin the volume of\nsensitive organs\nwhen compared\nwith CT based\nplan.","The simulated\ndose based on\nMRCAT Brain\nimages shall not\ndiffer in 95% of the\nindicated patients\n(gamma analysis\ncriterion 2%/2mm\nrealized in 98% of\nvoxels within the\nPTV or exceeding\n75% of the\nmaximum dose)\nwhen compared\nwith CT‐based\nplan.\nThe average\nsimulated dose\nbased on MRCAT\nBrain shall not\ndeviate more than\n5% or 1 Gy, which\never is greater, in\n99% of the\nindicated patients\nin the volume of\nsensitive organs\nwhen compared\nwith CT based\nplan.","No significant\ndifference.\nThe same\ndose\nevaluation\nmethodology\nis used for\nboth\nproducts. The\ncriteria are\nselected\nbased on the\nneeds of the\napplication."],["Geometric\naccuracy","MRCAT accuracy:\n± 1 mm accuracy:\n200 mm diameter\nsphere\n± 5 mm accuracy:\n500 mm diameter\nsphere (limited in\nthe bore direction\nby +/‐ 160 mm\nfrom the z=0 mm\nplane )","MRCAT accuracy:\n± 1 mm accuracy:\n200 mm diameter\nsphere\n± 5 mm accuracy:\n500 mm diameter\nsphere (limited in\nthe bore direction\nby +/‐ 160 mm\nfrom the z=0 mm\nplane )","No significant\ndifference"]],"caption_candidate":"Philips Medical Systems MR Finland","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193170-p6-t0","doc_id":"K193170","page_num":6,"bbox":[108.26,134.16,530.98,519.42],"n_rows":9,"n_cols":7,"columns":["Specification/\nAttribute","","Deep Learning Image","","","Deep Learning Image",""],"rows":[["Specification/\nAttribute","","Deep Learning Image","","","Deep Learning Image",""],["","","Reconstruction","","","Reconstruction",""],["","","Predicate Device, (K183202)","","","(Proposed Device)",""],["Technology","Utilizes a dedicated Deep Neural\nNetwork (DNN) which is trained\nfor the Revolution family CT\nScanners and designed\nspecifically to generate high\nquality CT images","","","Same","",""],["Clinical Workflow","Select recon type and strength\n(High, Medium, Low)","","","Same","",""],["Clinical Use","Routine Clinical Use","","","Same","",""],["Reference\nprotocols/dose","Using the same Reference\nprotocols provided on the\nRevolution CT system for ASiR-V","","","Using the same Reference\nprotocols provided on the\nRevolution EVO system for\nASiR-V","",""],["IQ performance vs\ndose","Image noise, low contrast\ndetectability, spatial resolution,\nand low signal artifact\nsuppression as good or better\nthan ASiR-V on Revolution CT","","","Image noise, low contrast\ndetectability, spatial resolution,\nand low signal artifact\nsuppression as good or better\nthan ASiR-V on Revolution EVO.","",""],["Deployment\nEnvironment","On CT console","","","On GE’s Edison Platform.","",""]],"caption_candidate":"between the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193178-p7-t0","doc_id":"K193178","page_num":7,"bbox":[96.74,197.76,533.26,685.74],"n_rows":30,"n_cols":6,"columns":["","Performance Criteria","","Results","Acceptance",""],"rows":[["","Performance Criteria","","Results","Acceptance",""],["","Resolution – Full Size","","","",""],["Transverse Resolution FWHM @ 1 cm","","","Pass","≤ 4.7 mm",""],["Transverse Resolution FWHM @ 10 cm","","","Pass","≤ 5.5 mm",""],["Transverse Resolution FWHM @ 20 cm","","","Pass","≤ 7.6 mm",""],["Axial Resolution FWHM @ 1 cm","","","Pass","≤ 5.0 mm",""],["Axial Resolution FWHM @ 10 cm","","","Pass","≤ 7.0 mm",""],["Axial Resolution FWHM @ 20 cm","","","Pass","≤ 11.3 mm",""],["","Resolution – 256 x 256","","","",""],["Transverse Resolution FWHM @ 1 cm","","","Pass","≤ 7.3 mm",""],["Transverse Resolution FWHM @ 10 cm","","","Pass","≤ 7.6 mm",""],["Transverse Resolution FWHM @ 20 cm","","","Pass","≤ 8.9 mm",""],["Axial Resolution FWHM @ 1 cm","","","Pass","≤ 6.1 mm",""],["Axial Resolution FWHM @ 10 cm","","","Pass","≤ 7.3 mm",""],["Axial Resolution FWHM @ 20 cm","","","Pass","≤ 11.9 mm",""],["","Count Rate / Scatter / Sensitivity","","","",""],["Sensitivity @435 keV LLD","","","Pass","≥ 5.8 cps/kBq\n≥ 10.9 cps/kBq (TrueV)",""],["Count Rate peak NECR","","","Pass","≥ 78 kcps @ ≤ 26 kBq/cc\n≥ 135 kcps @ ≤ 26 kBq/cc (TrueV)",""],["Count Rate peak trues","","","Pass","≥285 kcps @ ≤ 53 kBq/cc\n≥ 465 kcps @ ≤ 42 kBq/cc (TrueV)",""],["Scatter Fraction at peak NECR","","","Pass","≤ 40%",""],["Mean bias (%) at peak NEC","","","Pass","≤ +/‐ 6%",""],["","Image Quality (4 to 1) ‐ (% Contrast / Background Variability)","","","",""],["10mm sphere","","","Pass","≥ 10% / ≤ 10%",""],["13mm sphere","","","Pass","≥ 25% / ≤ 10%",""],["17mm sphere","","","Pass","≥ 40% / ≤ 10%",""],["22mm sphere","","","Pass","≥ 55% / ≤ 10%",""],["28mm sphere","","","Pass","≥ 60% / ≤ 10%",""],["37mm sphere","","","Pass","≥ 65% / ≤ 10%",""],["","Co‐Registration Accuracy","","","",""],["Max Error","","","Pass","≤ 5 mm",""]],"caption_candidate":"(TrueV).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193178-p8-t0","doc_id":"K193178","page_num":8,"bbox":[124.21,194.01,507.75,249.06],"n_rows":4,"n_cols":7,"columns":["","","","Anzai‐based OncoFreeze","","Deviceless OncoFreeze",""],"rows":[["","","","Anzai‐based OncoFreeze","","Deviceless OncoFreeze",""],["SUV (relative to static)\nmax","","+29% ± 22%","","","+27% ± 22%",""],["SUV (relative to static)\nmean","","+27% ± 22%","","","+26% ± 22%",""],["Volume (relative to static)","","-34% ± 23%","","","-31% ± 19%",""]],"caption_candidate":"images comparing Anzai based gating and deviceless gating.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193178-p8-t1","doc_id":"K193178","page_num":8,"bbox":[124.21,538.61,535.47,649.68],"n_rows":5,"n_cols":9,"columns":["","Difference from ground truth","","","Single Bed Scatter","","","Whole Body",""],"rows":[["","Difference from ground truth","","","Single Bed Scatter","","","Whole Body",""],["","In simulation study of phantom","","","Correction","","","Scatter correction",""],["Representative region of interest close to\nphantom exhibiting high signal","","","+87%","","","‐2%","",""],["Representative region of interest close to\nphantom exhibiting low signal","","","‐42%","","","‐3%","",""],["Representative region of interest inside\nphantom","","","+0.5%","","","‐0.4%","",""]],"caption_candidate":"using Single Bed Scatter compared to whole body scatter correction.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193210-p5-t0","doc_id":"K193210","page_num":5,"bbox":[59.1,486.9,546.48,765.9],"n_rows":6,"n_cols":5,"columns":["ITEM","Predicate Device 1\nuMI 780 (K172143)\nincluding a post-\nsmoothing function\nfor PET image\nreconstruction","Predicate Device 2\nuMI 550 (K182237)\nincluding a post-\nsmoothing function\nfor PET image\nreconstruction","Proposed Device\nHYPER DLR","NOTE"],"rows":[["ITEM","Predicate Device 1\nuMI 780 (K172143)\nincluding a post-\nsmoothing function\nfor PET image\nreconstruction","Predicate Device 2\nuMI 550 (K182237)\nincluding a post-\nsmoothing function\nfor PET image\nreconstruction","Proposed Device\nHYPER DLR","NOTE"],["Image\nProcessing\nLocation","Onsite on the facility\nPET/CT\nreconstruction\ncomputer.","Onsite on the facility\nPET/CT\nreconstruction\ncomputer.","Onsite on the\nfacility PET/CT\nreconstruction\ncomputer.","Same"],["Operating\nsystem","Windows","Windows","Windows","Same"],["Workflow","Support online &\noffline","Support online &\noffline","Support online &\noffline","Same"],["Protocols","Standard scanner\nprotocols","Standard scanner\nprotocols","Standard scanner\nprotocols","Same"],["Algorithm\ndescription","The post-smoothing\nfunction uses\nGaussian filtering to\nreduce the noise in","The post-smoothing\nfunction uses\nGaussian filtering to\nreduce the noise in","The software\nemploys a\nconvolutional\nneural network","Gaussian\nfiltering\nsuppresses the\nhigh frequency"]],"caption_candidate":"devices is provided as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p8-t0","doc_id":"K193216","page_num":8,"bbox":[107.8,294.71,522.34,326.92],"n_rows":2,"n_cols":9,"columns":["","Company","","","Product – Trade Name","","","510(k) #",""],"rows":[["","Company","","","Product – Trade Name","","","510(k) #",""],["Siemens AG Medical Solutions","","","Syngo.CT Lung CAD","","","K143196","",""]],"caption_candidate":"sistent.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p10-t0","doc_id":"K193216","page_num":10,"bbox":[51.19,108.52,725.8,488.02],"n_rows":6,"n_cols":5,"columns":["Subject Device\nCharacteristic","","Current Predicate Device","New Device\nsyngo.CT Lung CAD (VC30)","Type of Change and Impact to\nSafety & Effectiveness"],"rows":[["Subject Device\nCharacteristic","","Current Predicate Device","New Device\nsyngo.CT Lung CAD (VC30)","Type of Change and Impact to\nSafety & Effectiveness"],["","","syngo.CT Lung CAD (VC20E)","",""],["","","(K)143196","",""],["Manufacturer","Siemens AG Medical Solutions","","Siemens Healthcare GmbH","Legal manufacturer change1.\nNo Impact"],["Detection target","Solid pulmonary nodules in diag-\nnostic chest CT acquisitions","","Solid pulmonary nodules in diag-\nnostic chest CT acquisitions","[Unchanged] and no Impact"],["Intended Use","The LungCAD software device is a\nComputer-Aided Detection (CAD)\ntool designed to assist\nradiologists in the detection of solid\npulmonary nodules during review of\nmulti-detector\ncomputed tomographic (MDCT)\nthoracic examinations. The software\nis an adjunctive tool\nthat alerts the radiologist to regions\nof interest (ROI) that may be initial-\nly overlooked. The\nLungCAD software device use is\nintended to be used as a second\nreader after the radiologist has com-\npleted his/her initial read.","","The LungCAD software device is a\nComputer-Aided Detection (CAD)\ntool designed to assist\nradiologists in the detection of solid\npulmonary nodules during review of\nmulti-detector\ncomputed tomographic (MDCT)\nthoracic examinations. The software\nis an adjunctive tool\nthat alerts the radiologist to regions\nof interest (ROI) that may be initial-\nly overlooked. The\nLungCAD software device use is\nintended to be used as a second\nreader after the radiologist has com-\npleted his/her initial read.","[Unchanged] and no Impact"]],"caption_candidate":"© Siemens Healthcare GmbH, 2020","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p11-t0","doc_id":"K193216","page_num":11,"bbox":[51.19,108.47,725.8,527.08],"n_rows":2,"n_cols":4,"columns":["Indications For Use","• The syngo.CT Lung CAD de-\nvice is a computer-aided detec-\ntion (CAD) tool designed to as-\nsist radiologists in the detection\nof solid pulmonary nodules dur-\ning review of multi-detector\ncomputed tomography (MDCT)\nexaminations of the chest.\n• The software is an adjunctive\ntool to alert the radiologist to re-\ngions of interest (ROI) that may\nhave been initially overlooked.\n• The syngo.CT Lung CAD de-\nvice is intended to be used as a\nsecond reader after the radiolo-\ngist has completed his/her initial\nread.","• The syngo.CT Lung CAD de-\nvice is a computer-aided detec-\ntion (CAD) tool designed to as-\nsist radiologists in the detection\nof solid pulmonary nodules dur-\ning review of multi-detector\ncomputed tomography (MDCT)\nexaminations of the chest.\n• The software is an adjunctive\ntool to alert the radiologist to re-\ngions of interest (ROI) that may\nhave been initially overlooked.\n• The syngo.CT Lung CAD de-\nvice is intended to be used as a\nsecond reader after the radiolo-\ngist has completed his/her initial\nread.","[Unchanged] and no Impact"],"rows":[["Indications For Use","• The syngo.CT Lung CAD de-\nvice is a computer-aided detec-\ntion (CAD) tool designed to as-\nsist radiologists in the detection\nof solid pulmonary nodules dur-\ning review of multi-detector\ncomputed tomography (MDCT)\nexaminations of the chest.\n• The software is an adjunctive\ntool to alert the radiologist to re-\ngions of interest (ROI) that may\nhave been initially overlooked.\n• The syngo.CT Lung CAD de-\nvice is intended to be used as a\nsecond reader after the radiolo-\ngist has completed his/her initial\nread.","• The syngo.CT Lung CAD de-\nvice is a computer-aided detec-\ntion (CAD) tool designed to as-\nsist radiologists in the detection\nof solid pulmonary nodules dur-\ning review of multi-detector\ncomputed tomography (MDCT)\nexaminations of the chest.\n• The software is an adjunctive\ntool to alert the radiologist to re-\ngions of interest (ROI) that may\nhave been initially overlooked.\n• The syngo.CT Lung CAD de-\nvice is intended to be used as a\nsecond reader after the radiolo-\ngist has completed his/her initial\nread.","[Unchanged] and no Impact"],["Nodule Characteris-\ntics","Size\n• Solid nodules ≥ 3mm and <\n10mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","Diameter\n• Solid nodules ≥ 3mm and <\n20mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","Extended nodule size to 20mm.\nNo impact as assessed in the evi-\ndence provided in the benchmark\nanalysis provided in this substan-\ntial equivalence evaluation. At-\ntachment 10 and 12"]],"caption_candidate":"© Siemens Healthcare GmbH, 2020","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p12-t0","doc_id":"K193216","page_num":12,"bbox":[51.26,108.47,725.8,538.24],"n_rows":12,"n_cols":12,"columns":["Reader workflow","","","second reader workflow","","","second reader workflow","","","[Unchanged] and no Impact","",""],"rows":[["Reader workflow","","","second reader workflow","","","second reader workflow","","","[Unchanged] and no Impact","",""],["","","","","","","","","","","",""],["Input scanning pa-\nrameters","","","Scanners\nSiemens multi-detector CT (MDCT)\nscanners.","","","Scanners\nSiemens multi-detector CT (MDCT)\nscanners.","","","[Unchanged] and no Impact","",""],["","","","Detector rows\n4 or more detector rows","","","Detector rows\n4 or more detector rows","","","[Unchanged] and no Impact","",""],["","","","Scan area\nThe scan area needs to comprise the\nentire thorax covering the lung api-\nces to the bases","","","Scan area\nThe scan area needs to comprise the\nentire thorax covering the lung api-\nces to the bases","","","[Unchanged] and no Impact","",""],["","","","Scan direction\nCranio-caudal or caudal-cranial","","","Scan direction\nCranio-caudal or caudal-cranial","","","[Unchanged] and no Impact","",""],["","","","Voltage\n120 -140 kVp","","","Voltage\n120 -140 kVp","","","[Unchanged] and no Impact","",""],["","","","Exposure\n40–120 mAs","","","Exposure\n40–120 mAs","","","[Unchanged] and no Impact","",""],["","","","Collimation\n1 mm or less","","","Collimation\n1 mm or less","","","[Unchanged] and no Impact","",""],["","","","Slice width\n1.00 - 1.25 mm","","","Slice Thickness\n1.00 - 1.25 mm","","","[Unchanged] and no Impact – no-\nmenclature updating only","",""],["","","","Slice overlap\n0–25%\nNote: Reconstruction overlap is al-\nlowed, but gaps are not permitted","","","Slice Overlap\n0–25%\nNote: Reconstruction overlap is al-\nlowed, but gaps are not permitted","","","[Unchanged] and no Impact","",""],["","","","Number of images\nUp to 1000 images per series.","","","Number of images\nUp to 1000 images per series.","","","[Unchanged] and no Impact","",""]],"caption_candidate":"© Siemens Healthcare GmbH, 2020","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p13-t0","doc_id":"K193216","page_num":13,"bbox":[51.22,108.47,726.51,230.08],"n_rows":5,"n_cols":12,"columns":["","","","Kernel\nSiemens B60","","","Kernel\nSiemens B60","","","[Unchanged] and no Impact","",""],"rows":[["","","","Kernel\nSiemens B60","","","Kernel\nSiemens B60","","","[Unchanged] and no Impact","",""],["","","","","","","","","","","",""],["Hosting Platform","","","syngo.via","","","syngo.via","","","[Unchanged] and no Impact","",""],["Hosting Application","","","syngo MM Oncology","","","syngo MM Oncology","","","[Unchanged] and no Impact","",""],["Dose","","","Diagnostic","","","Diagnostic","","","[Unchanged] and no Impact","",""]],"caption_candidate":"© Siemens Healthcare GmbH, 2020","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193216-p13-t1","doc_id":"K193216","page_num":13,"bbox":[51.22,278.39,726.51,536.98],"n_rows":3,"n_cols":3,"columns":["Functional\nComponent","LungCAD VC20","LungCAD VC30"],"rows":[["Functional\nComponent","LungCAD VC20","LungCAD VC30"],["Preprocessing\nStandardization of\nthe input images\nand lung\nsegmentation","(a) isotropic volume resampling\n(b) lung segmentation is performed on a slice-by-\nslice approach by identifying the middle of the\nlung area, then processing first the upper half of\nthe lung and then the lower half of the lungs. Slice\nprocessing identifies starting points and traces the\nlung contour, slice-by slice. This is followed by\ncontour smooth and filling.","(a) isotropic volume resampling\n(b) lung segmentation is accomplished using a CCN. Initially a\ncoarse estimation of the lung is performed using a V-net\nprocess. Using two predefined bounding boxes left and right\nlungs are initialized. Another V-net is used to segment left and\nright lungs. This is followed by up-sampling to the original\nimage resolution."],["Candidate\nGeneration\nScans through all\nslices of the\nsegmented lung to\nsearch for","(a) isotropic volume is partitioned into subvolumes\n(b) Each volume is processed using the divergence\nof the 3D gradient field compute a “response vol-\nume” thresholded to yield a list of candidates.\nFeatures are computed (e.g. number of voxels,\nsphericity, maximum response value, etc.)\n(c) Cascade 1: candidates are passed to two-way","(a) isotropic volume is partitioned into subvolumes\n(b) Each subvolume is fed to a CNN to compute features\n(“response volume”). Filtering and non-maximum suppression\nyield a list of candidates for each subvolume\n(c) Cascade 1: candidates above a certain threshold score are\npassed to the next step."]],"caption_candidate":"Table 1 Summary of Differences between the Subject Device and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193220-p6-t0","doc_id":"K193220","page_num":6,"bbox":[36.31,524.23,559.16,743.71],"n_rows":14,"n_cols":9,"columns":["Characteristic","","","Subject Device","","Primary Predicate","","Reference Device","Reference Device"],"rows":[["Characteristic","","","Subject Device","","Primary Predicate","","Reference Device","Reference Device"],["","","","","","Device","","",""],["Device Name","","","AVIEW LCS","","Lung Nodule","","Lung Analysis\nSoftware","AVIEW"],["","","","","","Assessment and","","",""],["","","","","","Comparison Option","","",""],["","","","","","(LNA)","","",""],["Classification\nName","","","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","","","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological"],["","Regulatory","","21 CFR 892.2050","21 CFR 892.2050","","","21 CFR 892.2050","21 CFR 892.2050"],["","Number","","","","","","",""],["","Product Code","","LLZ, JAK","LLZ, JAK","","","LLZ, JAK","LLZ"],["","Review Panel","","Radiology","Radiology","","","Radiology","Radiology"],["","510k Number","","-","K162484","","","K151283","K171199"],["Indications\nfor use","","","AVIEW LCS","","","","",""],["","","","AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the\npurpose of characterizing nodules in the lung in a single study, or over the time course of several","","","","",""]],"caption_candidate":"tests, we conclude that the proposed device is substantially equivalent to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193220-p7-t0","doc_id":"K193220","page_num":7,"bbox":[36.32,84.55,559.18,749.83],"n_rows":16,"n_cols":7,"columns":["","","","thoracic studies. Characterizations include nodule type, location of the nodule and measurements\nsuch as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,\nthe volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU),\nMinimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures\n(Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid\n2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular\nto the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS\n(classification proposed to aid with findings). The system automatically performs the measurement,\nallowing lung nodules and measurements to be displayed and, also integrate with FDA certified\nMevis CAD (Computer-aided detection) (K043617).","","",""],"rows":[["","","","thoracic studies. Characterizations include nodule type, location of the nodule and measurements\nsuch as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,\nthe volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU),\nMinimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures\n(Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid\n2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular\nto the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS\n(classification proposed to aid with findings). The system automatically performs the measurement,\nallowing lung nodules and measurements to be displayed and, also integrate with FDA certified\nMevis CAD (Computer-aided detection) (K043617).","","",""],["","","","Lung Nodule Assessment and Comparison Option (LNA)","","",""],["","","","The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient-\nimaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative\nand characterizing information about nodules in the lung in a single study, or over the time course\nof several thoracic studies. Characterizations include diameter, volume and volume over time. The\nsystem automatically performs the measurements, allowing lung nodules and measurements to be\ndisplayed.","","",""],["","","","Toshiba’s Lung Analysis Software","","",""],["","","","The separately licensed Lung Analysis option is intended for the review and analysis of thoracic CT\nimages for the purpose of characterizing nodules in the lung in a single study, or over the time\ncourse of several thoracic studies. Characterization include diameter, volume and volume over time.\nThe system automatically performs the measurement, allowing lung nodules and measurement to\nbe displayed.","","",""],["","","","AVIEW","","",""],["","","","AVIEW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be\nused to support the physician quantitatively in the diagnosis. Follow-up evaluation and\ndocumentation of CT lung tissue images by providing image segmentation of sub-structures in the\nleft and right lung (e.g., the five lobes and airway), volumetric and structural analysis, density\nevaluations and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data\nsets. AVIEW is not meant for primary image Interpretation in mammography.","","",""],["Platform","","","IBM-compatible PC or\nPC network","IBM-compatible PC or\nPC network","IBM-compatible PC or\nPC network","IBM-compatible PC\nor PC network"],["User Interface","","","Monitor, Mouse,\nKeyboard","Monitor, Mouse,\nKeyboard","Monitor, Mouse,\nKeyboard","Monitor, Mouse,\nKeyboard"],["Image Input\nSources","","","Images can be scanned,\nloaded from card\nreaders, or imported\nfrom a radiographic\nimaging device","Images can be scanned,\nloaded from card\nreaders, or imported\nfrom a radiographic\nimaging device","Images can be scanned,\nloaded from card\nreaders, or imported\nfrom a radiographic\nimaging device","Images can be\nscanned, loaded from\ncard readers, or\nimported from a\nradiographic imaging\ndevice"],["","Image format","","DICOM","DICOM","DICOM","DICOM"],["","Intended","","Chest","Chest","Chest","Chest"],["","body part","","","","",""],["","Type of scans","","Thoracic CT images","Thoracic CT images","Thoracic CT images",""],["General\nDescription","","","AVIEW LCS","","",""],["","","","AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and\nanalysis of thoracic CT images. Provides following features as semi-automatic nodule measurement\n(segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules\ndetection by integration with 3rd party CAD. Also provides cancer risk based on PANCAN risk\nmodel which calculates the malignancy score based on numerical or Boolean inputs. Follow up\nsupport with automated nodule matching and automatically categorize Lung-RADS score which is\na quality assurance tool designed to standardize lung cancer screening CT reporting and","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193220-p8-t0","doc_id":"K193220","page_num":8,"bbox":[36.3,84.55,559.18,748.3],"n_rows":12,"n_cols":5,"columns":["","management recommendations that is based on type, size, size change and other findings that is\nreported.","","",""],"rows":[["","management recommendations that is based on type, size, size change and other findings that is\nreported.","","",""],["","Lung Nodule Assessment and Comparison Option (LNA)","","",""],["","The Lung Nodule Assessment and Comparison Option application is intended for use as a\ndiagnostic patient imaging tool. It is intended for the review and analysis of thoracic CT images,\nproviding quantitative and characterizing information about nodules in the lung in a single study,\nor over the time course of several thoracic studies. The system automatically performs the\nmeasurements, allowing lung nodules and measurements to be displayed. The user interface and\nautomated tools help to determine growth patterns and compose comparative reviews. The Lung\nNodule Assessment and Comparison Option application requires the user to identify a nodule and\nto determine the type of nodule in order to use the appropriate characterization tool. Lung Nodule\nAssessment and Comparison Option may be utilized in both diagnostic and screening evaluations\nsupporting Low Dose CT Lung Cancer Screening","","",""],["","Lung Analysis Software","","",""],["","Lung Analysis aids in measuring and characterizing lung nodules. The interface and automated tools\nhelp to efficiently determine growth patterns and compose comparative reviews. Lung Analysis is\nintended for the review and analysis of thoracic CT images for the purpose of characterizing nodules\nin the lung in a single study, or over the time course of several thoracic studies. Characterizations\ninclude diameter, volume and volume over time. The system automatically performs the\nmeasurements, allowing lung nodules and measurements to be displayed. The Lung Analysis\nSoftware requires the user to identify a nodule and to determine whether it is a GGO or solid nodule\nin order to use the appropriate characterization too.","","",""],["","AVIEW","","",""],["","The AVIEW is a software product which can be installed on a PC. It shows images taken with the\ninterface from various storage devices using DICOM 3.0 which is the digital image and\ncommunication standard in medicine. It also offers functions such as reading. Manipulation,\nanalyzing, post-processing, saving and sending images by using the software tools.","","",""],["Key\nFunctions","Providing ray sum\nimage, axial, sagittal,\ncoronal, and oblique\nplanes.","Providing axial,\nsagittal, coronal, and\noblique planes","Providing axial,\nsagittal, coronal, and\noblique planes","Providing ray sum\nimage, axial, sagittal,\ncoronal, and oblique\nplanes"],["","Rotating to Anterior,\nPosterior, Left, Right,\nHead, and Foot\ndirection","Rotating to Anterior,\nPosterior, Left, Right,\nHead, and Foot\ndirection","Rotating to Anterior,\nPosterior, Left, Right,\nHead, and Foot\ndirection","Rotating to Anterior,\nPosterior, Left,\nRight, Head, and\nFoot direction"],["","Providing VR (Volume\nrender), MIP\n(Maximum Intensity\nProjection), MinIP\n(Minimum Intensity\nProjection) image","Providing Average,\nMIP, VIP, MinIP,\nSurfaceMIP, Vol,\nRend.","Providing Average,\nMIP, VIP, MinIP,\nSurfaceMIP, Vol,\nRend.","Providing VR\n(Volume render),\nMIP (Maximum\nIntensity Projection),\nMinIP (Minimum\nIntensity Projection)\nimage"],["","Changing the color\nand transparency of\nthe VR image by\nadjusting the OTF\n(Opacity Transfer\nFunction) and saving\nas a preset to easily\napply in the VR\nsetting.","Changing the color\nand transparency of\nthe VR image","Changing the color\nand transparency of\nthe VR image","Changing the color\nand transparency of\nthe VR image by\nadjusting the OTF\n(Opacity Transfer\nFunction) and saving\nas a preset to easily\napply in the VR\nsetting."],["","2D and 3D image","2D and 3D image","2D and 3D image","2D and 3D image"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193220-p9-t0","doc_id":"K193220","page_num":9,"bbox":[36.32,84.52,559.18,753.7],"n_rows":10,"n_cols":5,"columns":["","review","review","review","review"],"rows":[["","review","review","review","review"],["","2D and 3D\ncomparative review","2D and 3D\ncomparative review","2D and 3D\ncomparative review","2D and 3D\ncomparative review"],["","2D and 3D\nmeasurements","2D measurements","2D measurements","2D and 3D\nmeasurements"],["","Segmentation of\nLungs and Lobes","Segmentation of lung\nairway, lungs and lung\nlobes","Segmentation of lung\nairway, lungs and lung\nlobes","Segmentation of\nlung airway, lungs\nand lung lobes"],["","Nodule Characteristics","Nodule Characteristics","Nodule Characteristics","-"],["","Automatic calculation\nof measurements for\neach segmented nodule\n Size of the Major\naxis and Minor\naxis(mm)\n Diameter of Major\n(3D), 2nd Major\n(3D), Major(2D),\nMinor(2D) (mm)\n Volume(mm³)\n Max, Min, Mean HU\nof the nodule((HU)\n Cancer probability\n(%)","Automatic calculation\nof measurements for\neach segmented nodule\n Short axis-Longest\ndiameter\nperpendicular to the\nlong axis on the\nslice(mm)\n Loung Axis-Longest\ndiameter on an axial\nslice(mm)\n Average/Max\n3D/Effective\ndiameter(mm)\n Volume(mm³) Mean\ndensities(HU)","Automatic calculation\nof measurements for\neach segmented nodule\n Volume(mm³)\n Mean\ndiameter(mm)\n Maximum\ndiameter(mm)\n Short axis\ndiameter(mm)\n Average/minimum/\nmaximum densities\n(HU)",""],["","Comparison and\nMatching","Comparison and\nMatching","Comparison and\nMatching","-"],["","Comparison and\nmatching automatic\ncalculations between\neach follow-up scan\nand the baseline scan\n Doubling time in\ndays\n Indicated the change\nof the size\n Auto generate Lung-\nRADS","Comparison and\nmatching automatic\ncalculations between\neach follow-up scan\nand the baseline scan\n Doubling time in\ndays\n Percent (%) and\nabsolute change of\nall numerical\nparameters (growth\nin nodule long axis,\nshort axis, average\ndiameter, max 3D\ndiameter, effective\ndiameter, volume,\nmean HU)","Comparison and\nmatching automatic\ncalculations between\neach follow-up scan\nand the baseline scan\n Elapsed time in\ndays\n Doubling time in\ndays Percent (%)\ngrowth in nodule\nvolume","-"],["","Loading multiple\nstudies","Loading multiple\nstudies\nUp to 3 studies","Loading multiple\nstudies\nUp to 3 studies","-"],["","Workflow\n Detect and Segment\n Comparison and\nMatching","Workflow\n Detect and Segment\n Comparison and\nMatching\n Results","Workflow\n Detect and Segment\n Point-and-click\ndetection\n Automated","-"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193220-p10-t0","doc_id":"K193220","page_num":10,"bbox":[36.32,84.52,559.18,341.43],"n_rows":4,"n_cols":5,"columns":[""," Results\nOption to integrate\nwith 3rd party CAD\nwhich automatically\ndetects the nodules and\ngenerate report.","","contouring\n Automated\nmeasurements\n Manual correction",""],"rows":[[""," Results\nOption to integrate\nwith 3rd party CAD\nwhich automatically\ndetects the nodules and\ngenerate report.","","contouring\n Automated\nmeasurements\n Manual correction",""],["","Supporting Low-dose\nCT","Supporting Low-dose\nCT","Supporting Low-dose\nCT","-"],["","Reporting results\nThe results include the\nfollowing.\n Lung-RADS\n PANCAN risk\ncalculator\n Auto detect nodule\nlocation by lobe","Reporting results\nThe results include the\nfollowing.\n Patient related\ninformation\n Dictation Table with\nNodule result table\nand additional\nfindings\n Lung-RADS\n Risk Calculator","Reporting results\nThe results include the\nfollowing.\n Dictation Table with\nNodule result table\n Lung-RADS\n Fleischer Criteria","-"],["","Printing Option","Printing Option","Printing Option","Printing Option"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193229-p5-t0","doc_id":"K193229","page_num":5,"bbox":[71.05,102.98,524.26,225.62],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara™ 1.6.0"],"rows":[["Device trade name","Transpara™ 1.6.0"],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Submission type","Traditional 510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193229-p5-t1","doc_id":"K193229","page_num":5,"bbox":[71.05,305.81,524.26,428.45],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara™ 1.3.0 (K181704)"],"rows":[["Device trade name","Transpara™ 1.3.0 (K181704)"],["Legal Manufacturer","ScreenPoint Medical B.V."],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193229-p7-t0","doc_id":"K193229","page_num":7,"bbox":[71.1,528.37,524.23,681.34],"n_rows":4,"n_cols":9,"columns":["","Standard ID","","","Standard Title","","","FDA Recognition #",""],"rows":[["","Standard ID","","","Standard Title","","","FDA Recognition #",""],["ISO 14971:2007","","","Medical Devices - Application Of Risk\nManagement To Medical Devices","","","5-40","",""],["IEC 62304:2015","","","Medical Device Software - Software Life\nCycle Processes","","","13-79","",""],["DEN180005","","","Decision summary with special controls\nfor class II radiology device","","","","",""]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193248-p8-t0","doc_id":"K193248","page_num":8,"bbox":[84.62,197.64,545.38,686.4],"n_rows":24,"n_cols":10,"columns":["Performance Criteria","","","Results","","","Biograph Vision 6-ring","","Biograph Vision 8-ring\nAcceptance",""],"rows":[["Performance Criteria","","","Results","","","Biograph Vision 6-ring","","Biograph Vision 8-ring\nAcceptance",""],["","","","","","","Acceptance","","",""],["","Resolution – Full Size","","","","","","","",""],["Transverse Resolution\nFWHM @ 1 cm","","","Pass","","≤ 4.0 mm","","","≤ 4.0 mm",""],["Transverse Resolution\nFWHM @ 10 cm","","","Pass","","≤ 4.8 mm","","","≤ 4.8 mm",""],["Transverse Resolution\nFWHM @ 20 cm","","","Pass","","≤ 5.2 mm","","","≤ 5.2 mm",""],["Axial Resolution FWHM\n@ 1 cm","","","Pass","","≤ 4.3 mm","","","≤ 4.3 mm",""],["Axial Resolution FWHM\n@ 10 cm","","","Pass","","≤ 5.4 mm","","","≤ 5.4 mm",""],["Axial Resolution FWHM\n@ 20 cm","","","Pass","","≤ 5.4 mm","","","≤ 5.4 mm",""],["","","","","Count Rate / Scatter / Sensitivity","","","","",""],["Sensitivity @435 keV LLD","","","Pass","","≥ 8.0 cps/kBq","","","≥ 15.0 cps/kBq",""],["Count Rate peak NECR","","","Pass","","≥ 140 kcps @ ≤ 32\nkBq/cc","","","≥ 250 kcps @ ≤ 32\nkBq/cc",""],["Count Rate peak trues","","","Pass","","≥600 kcps @ ≤ 56 kBq/cc","","","≥1100 kcps @ ≤ 56\nkBq/cc",""],["Scatter Fraction at peak\nNECR","","","Pass","","≤ 43%","","","≤ 43%",""],["Mean bias (%) at peak\nNEC","","","Pass","","≤ +/- 6%","","","≤ +/- 6%",""],["","","","","Image Quality (4 to 1) - (% Contrast / Background Variability)","","","","",""],["10mm sphere","","","Pass","","≥ 55% / ≤ 10%","","","≥ 55% / ≤ 10%",""],["13mm sphere","","","Pass","","≥ 60% / ≤ 9%","","","≥ 60% / ≤ 9%",""],["17mm sphere","","","Pass","","≥ 65% / ≤ 8%","","","≥ 65% / ≤ 8%",""],["22mm sphere","","","Pass","","≥ 70% / ≤ 7%","","","≥ 70% / ≤ 7%",""],["28mm sphere","","","Pass","","≥ 75% / ≤ 6%","","","≥ 75% / ≤ 6%",""],["37mm sphere","","","Pass","","≥ 80% / ≤ 5%","","","≥ 80% / ≤ 5%",""],["","","","","Co-Registration Accuracy","","","","",""],["Max Error","","","Pass","","≤ 5 mm","","","≤ 5 mm",""]],"caption_candidate":"two configurations of the Biograph mCT, a 3-ring version and a 4-ring version.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193248-p9-t0","doc_id":"K193248","page_num":9,"bbox":[84.62,72.36,545.38,561.0],"n_rows":24,"n_cols":10,"columns":["Performance Criteria","","","Results","","","Biograph mCT 3-ring","","Biograph mCT 4-ring\nAcceptance",""],"rows":[["Performance Criteria","","","Results","","","Biograph mCT 3-ring","","Biograph mCT 4-ring\nAcceptance",""],["","","","","","","Acceptance","","",""],["","Resolution – Full Size","","","","","","","",""],["Transverse Resolution\nFWHM @ 1 cm","","","Pass","","≤ 4.7 mm","","","≤ 4.0 mm",""],["Transverse Resolution\nFWHM @ 10 cm","","","Pass","","≤ 5.4 mm","","","≤ 4.8 mm",""],["Transverse Resolution\nFWHM @ 20 cm","","","Pass","","≤ 6.3 mm","","","≤ 5.2 mm",""],["Axial Resolution FWHM\n@ 1 cm","","","Pass","","≤ 4.9 mm","","","≤ 4.3 mm",""],["Axial Resolution FWHM\n@ 10 cm","","","Pass","","≤ 6.5 mm","","","≤ 5.4 mm",""],["Axial Resolution FWHM\n@ 20 cm","","","Pass","","≤ 8.8 mm","","","≤ 5.4 mm",""],["","","","","Count Rate / Scatter / Sensitivity","","","","",""],["Sensitivity @435 keV LLD","","","Pass","","≥ 5.0 cps/kBq","","","≥ 9.4 cps/kBq",""],["Count Rate peak NECR","","","Pass","","≥ 95 kcps @ ≤ 30 kBq/cc","","","≥ 165 kcps @ ≤ 28\nkBq/cc",""],["Count Rate peak trues","","","Pass","","≥350 kcps @ ≤ 46 kBq/cc","","","≥575 kcps @ ≤ 40 kBq/cc",""],["Scatter Fraction at peak\nNECR","","","Pass","","≤ 40%","","","≤ 40%",""],["Mean bias (%) at peak\nNEC","","","Pass","","≤ +/- 6%","","","≤ +/- 6%",""],["","","","","Image Quality (4 to 1) - (% Contrast / Background Variability)","","","","",""],["10mm sphere","","","Pass","","≥ 10% / ≤ 10%","","","≥ 10% / ≤ 10%",""],["13mm sphere","","","Pass","","≥ 25% / ≤ 10%","","","≥ 25% / ≤ 10%",""],["17mm sphere","","","Pass","","≥ 40% / ≤ 10%","","","≥ 40% / ≤ 10%",""],["22mm sphere","","","Pass","","≥ 55% / ≤ 10%","","","≥ 55% / ≤ 10%",""],["28mm sphere","","","Pass","","≥ 60% / ≤ 10%","","","≥ 60% / ≤ 10%",""],["37mm sphere","","","Pass","","≥ 65% / ≤ 10%","","","≥ 65% / ≤ 10%",""],["","","","","Co-Registration Accuracy","","","","",""],["Max Error","","","Pass","","≤ 5 mm","","","≤ 5 mm",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193248-p10-t0","doc_id":"K193248","page_num":10,"bbox":[140.45,84.96,489.55,145.44],"n_rows":4,"n_cols":9,"columns":["","","","","Anzai-based OncoFreeze","","","OncoFreeze AI",""],"rows":[["","","","","Anzai-based OncoFreeze","","","OncoFreeze AI",""],["∆SUV (relative to static)\nmax","","","+29% ± 22%","","","+27% ± 22%","",""],["∆SUV (relative to static)\nmean","","","+27% ± 22%","","","+26% ± 22%","",""],["∆Volume (relative to static)","","","-34% ± 23%","","","-31% ± 19%","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193248-p10-t1","doc_id":"K193248","page_num":10,"bbox":[120.65,321.72,530.95,450.0],"n_rows":6,"n_cols":5,"columns":["Difference from ground truth\nIn simulation study of phantom","","Single Bed","","Whole Body\nScatter correction"],"rows":[["Difference from ground truth\nIn simulation study of phantom","","Single Bed","","Whole Body\nScatter correction"],["","","Scatter","",""],["","","Correction","",""],["Representative region of interest close to\nphantom exhibiting high signal","+87%","","","-2%"],["Representative region of interest close to\nphantom exhibiting low signal","-42%","","","-3%"],["Representative region of interest inside\nphantom","+0.5%","","","-0.4%"]],"caption_candidate":"whole body scatter.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193267-p6-t0","doc_id":"K193267","page_num":6,"bbox":[72.59,98.5,564.35,417.39],"n_rows":5,"n_cols":6,"columns":["","Subject Device","","","Predicate Device",""],"rows":[["","Subject Device","","","Predicate Device",""],["Siemens\nAI‐Rad Companion (Musculoskeletal)","Siemens","","","Siemens",""],["","AI‐Rad Companion (Musculoskeletal)","","","syngo.CT Bone Reading",""],["","","","","(K123585)",""],["AI‐Rad Companion (Musculoskeletal) is an image processing\nsoftware that provides quantitative and qualitative analysis from\npreviously acquired Computed Tomography DICOM images to\nsupport radiologists and physicians from emergency medicine,\nspecialty care, urgent care, and general practice in the evaluation\nand assessment of musculoskeletal disease.\nIt provides the following functionality:\n Segmentation of vertebras\n Labelling of vertebras\n Measurements of heights in each vertebra and indication\nif they are critically different\n Measurement of mean Hounsfield value in volume of\ninterest within vertebra\nOnly DICOM images of adult patients are considered to be valid\ninput.","","","The syngo.CT Bone Reading is image analysis software for CT\nvolume data sets which has. been continuously acquired with\ncomputed tomography (CT) imaging systems. The software\ncombines following digital image processing and visualization tools:\n multiplanar reconstruction (MPR) thin/thick, maximum\nintensity projection (MIP) thin/thick, inverted MIP\nthin/thick, volume rendering technique (VRT)\n geometric measurement tools (distance line, polyline,\nmarker, arrow, angle)\n HU measurement tools (Pixel lens, ROI circle, ROi\npolygonal, ROI freehand, VOl sphere)\n curved MPR visualization (unfolded ribs and spine views),\ncrosssection MPRs\n tools for creation and editing of anatomical centerline\npaths\n tools for creation and editing of anatomical labels\nThe specific visualizations of spine and rib structures allow for easy\nmanual identification and marking of pathologies such as bone\nlesions or fractures.\nReporting and documentation of results is facilitated by using of\nappropriate reporting tool, statistics and creation of ranges and\nsnapshots","",""]],"caption_candidate":"Only DICOM images of adult patients are considered to be valid input.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193267-p7-t0","doc_id":"K193267","page_num":7,"bbox":[132.92,147.31,512.83,352.47],"n_rows":7,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nResults"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nResults"],["","Siemens AI‐Rad Companion\n(Musculoskeletal)","","","syngo.CT Bone Reading\n(K123584)","","",""],["Detection of\nvertebrae","Detection of Vertebras","","","Detection of Vertebras","","","Same"],["Labeling of\nvertebrae","Labelling of vertebras","","","Labelling of vertebras","","","Same"],["Segmentation of\nvertebrae","Deep‐learning‐based\nsegmentation of vertebras","","","Model‐based segmentation of\nvertebras","","","Equivalent\n*1)"],["Measurement of\nheights","Distance measurements\nbased on segmentation\nresults and comparison with\nneighboring measurements","","","Manual distance measurements\nin vertebra and visual\ncomparison with neighboring\nvertebra(s)","","","Equivalent\n*2)"],["Measurement of\nHounsfield (HU)\nvalue","HU measurements based on\nsegmentation results","","","HU measurement in region of\ninterest","","","Equivalent\n*3)"]],"caption_candidate":"Table 1 Predicate Device Comparable Properties","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193267-p7-t1","doc_id":"K193267","page_num":7,"bbox":[132.92,543.24,512.83,621.75],"n_rows":3,"n_cols":8,"columns":["Feature","","Subject Device","","","Reference Device","","Comparison\nResult"],"rows":[["Feature","","Subject Device","","","Reference Device","","Comparison\nResult"],["","Siemens AI‐Rad Companion\n(Musculoskeletal)","","","Siemens AI‐Rad Companion\n(Cardiovascular)\n(K183268)","","",""],["Deep Learning\nTechnology","Deep Image‐to‐image network\nfor 3D segmentation of organs","","","Deep Image‐to‐image network\nfor 3D segmentation of organs","","","Same"]],"caption_candidate":"Table 2 Reference Device Comparable Properties","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193267-p8-t0","doc_id":"K193267","page_num":8,"bbox":[132.93,547.67,526.33,708.06],"n_rows":6,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Publication\nDate","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12‐300","Radiology","Digital Imaging and Communications\nin Medicine (DICOM) Set; PS 3.1 –\n3.20","06/27/2016","NEMA","",""],["13‐79","Software","Medical Device Software –Software\nLife Cycle Processes;\nIEC 62304 Edition 1.1 2015‐06","06/26/2015","IEC","",""],["5‐40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices;\n14971 Second Edition 2007‐03‐01","08/20/2012","ISO","",""]],"caption_candidate":"Table 3 Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p7-t0","doc_id":"K193271","page_num":7,"bbox":[90.24,282.81,291.25,708.46],"n_rows":27,"n_cols":3,"columns":["Technological\nCharacteristics","","Subject Device"],"rows":[["Technological\nCharacteristics","","Subject Device"],["","","(K193271)"],["Indication for\nUse/Intended\nUse","","uAI EasyTriage-Rib is"],["","","radiological computer-"],["","","assisted triage and\nnotification software"],["","","device for analysis of"],["","","chest images. The dev"],["","","is intended to assist"],["","","hospital networks and"],["","","trained radiologists in\nworkflow triage by"],["","","flagging and prioritizin"],["","","trauma studies with\nsuspected positive"],["","","findings of multiple (3"],["","","more) acute rib fractur"],["","","uAI EasyTriage-Rib us"],["","","an artificial intelligence"],["","","algorithm to analyze\nimages and highlight"],["","","studies with suspected"],["","","multiple (3 or more) ac"],["","","rib fractures in a"],["","","standalone application"],["","","study list prioritization"],["","","triage in parallel to"],["","","ongoing standard of ca"],["","","The user is presented"],["","","with notifications of ca"],["","","with suspected finding"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p7-t1","doc_id":"K193271","page_num":7,"bbox":[314.88,282.81,426.71,708.46],"n_rows":26,"n_cols":2,"columns":["","Predicate Device"],"rows":[["","Predicate Device"],["","HealthVCF"],["","(K192901)"],["","HealthVCF is a passive"],["","notification for"],["","prioritization-only,"],["","parallel-workflow"],["","software tool used b"],["","clinicians to prioritiz"],["","specific patients within"],["","the standard-of-care"],["","bone health setting for"],["","suspected vertebral"],["","compression fractures."],["","HealthVCF uses an"],["","artificial intelligence"],["","algorithm to analyze"],["","chest and abdomina"],["","exam level. Thes"],["","flags are viewed by the"],["","clinician in Bone Health"],["","and Fracture Liaison"],["","Service programs in"],["","the medical setting via"],["","a worklist applicatio"],["","on their Picture"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p8-t0","doc_id":"K193271","page_num":8,"bbox":[90.24,72.32,521.75,712.41],"n_rows":48,"n_cols":9,"columns":["Technological\nCharacteristics","","","Subject Device","","Predicate Device\nHealthVCF\n(K192901)","Summary","",""],"rows":[["Technological\nCharacteristics","","","Subject Device","","Predicate Device\nHealthVCF\n(K192901)","Summary","",""],["","","","uAI EasyTriage-Rib","","HealthVCF","","",""],["","","","(K193271)","","(K192901)","","",""],["","","","Notifications include","Archiving and\nCommunication\nSystem (PACS).\nHealthVCF does not\nsend a proactive alert\ndirectly to the user.\nHealthVCF does not\nprovide diagnostic\ninformation beyond\ntriage and prioritization,\nit does not remove\ncases from the\nradiology worklist, and\nshould not be used in\nplace of full patient\nevaluation, or relied\nupon to make or\nconfirm diagnosis.","Archiving and","","",""],["","","","compressed preview","","Communication","","",""],["","","","images that are meant fo","","System (PACS).","","",""],["","","","informational purposes","","HealthVCF does n","","",""],["","","","only and not intended for","","send a proactive alert","","",""],["","","","diagnostic use beyond","","directly to the user.","","",""],["","","","notification. The device","","HealthVCF does n","","",""],["","","","does not alter the original","","provide diagnostic","","",""],["","","","medical image and is not","","information beyond","","",""],["","","","intended to be used as a","","triage and prioritization,","","",""],["","","","diagnostic device.","","it does not remove","","",""],["","","","The results of uAI","","cases from the","","",""],["","","","EasyTriage-Rib, in","","radiology worklist, and","","",""],["","","","","","should not be used in","","",""],["","","","clinical information and","","place of full patient","","",""],["","","","professional judgment,","","evaluation, or relie","","",""],["","","","are to be used to assis","","upon to make or","","",""],["","","","with triage/prioritization o","","","","",""],["","","","medical images. Notified","","","","",""],["","","","radiologists who read the","","","","",""],["","","","original medical image","","","","",""],["","","","are responsible for the","","","","",""],["","","","diagnostic decision.","","","","",""],["Notification-only,\nparallel workflow\ntool","","Yes","Yes","Yes","","","Same, both\ndevices\nproduce\npassive\nnotifications",""],["","","","","","","","devices",""],["","","","","","","","produce",""],["","","","","","","","passive",""],["","","","","","","","notifications",""],["User","","Radiologist","","Bone Health Clinician","","","Radiologists are",""],["","","","","","","","common users",""],["","","","","","","","for products",""],["","","","","","","","under product",""],["","","","","","","","code QFM for",""],["","","","","","","","Radiological",""],["","","","","","","","Computer-",""],["","","","","","","","Assisted",""],["","","","","","","","Prioritization",""],["","","","","","","","Software Fo",""],["","","","","","","","Lesions",""],["","Identify patients","Yes","","Yes","","Same","Same",""],["","with pre-","","","","","","",""],["","specified clinical","","","","","","",""],["","condition","","","","","","",""],["Clinical condition","Clinical condition","","Multiple (3 or more) acute","","Vertebral compression","","Different but",""],["","","","rib fractures","","fracture","","both findings",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p9-t0","doc_id":"K193271","page_num":9,"bbox":[90.24,72.32,521.75,555.21],"n_rows":35,"n_cols":12,"columns":["Technological\nCharacteristics","","","","Subject Device","","","Predicate Device","","Summary","",""],"rows":[["Technological\nCharacteristics","","","","Subject Device","","","Predicate Device","","Summary","",""],["","","","","uAI EasyTriage-Rib","","","HealthVCF","","","",""],["","","","","(K193271)","","","(K192901)","","","",""],["","","","","","","","","","","indicate pre-",""],["","","","","","","","","","","specified",""],["","","","","","","","","","","clinical",""],["","","","","","","","","","","conditions fo",""],["","","","","","","","","","","triage",""],["Alert to finding","","","","Yes; notification flagged","","","Yes; notification","","Same","Same",""],["","","","","for review","","","flagged for review","","","",""],["","Independent o","","Yes; No cases are\nremoved from worklist","Yes; No cases are","","Yes; No cases are\nremoved from worklist","Yes; No cases are","","Same","",""],["","standard of care","","","removed from worklist","","","removed from worklist","","","",""],["","workflow","","","","","","","","","",""],["","Modality","","","CT","","","CT","","","Same",""],["Body part","Body par","","Chest","Chest","","Chest and abdomen","Chest and abdomen","","","Similar, both",""],["","","","","","","","","","","include “chest”.",""],["","Artificial","","Yes","","","Yes","","","Same","Same",""],["","algorithm","","","","","","","","","",""],["","Limited t","","Yes","","","Yes","","","Same","",""],["","analysis of","","","","","","","","","",""],["","imaging dat","","","","","","","","","",""],["","Aids prompt","","Yes","","","Yes","","","Same","",""],["","identification o","","","","","","","","","",""],["","cases with","","","","","","","","","",""],["","indicated","","","","","","","","","",""],["","findings","","","","","","","","","",""],["Where results\nare received","","","Workstation","","","PACS / Workstation","","","","Different but",""],["","","","","","","","","","","both provide a",""],["","","","","","","","","","","passive",""],["","","","","","","","","","","notification to",""],["","","","","","","","","","","the workstation",""],["","","","","","","","","","","of the presence",""],["","","","","","","","","","","of suspected",""],["","","","","","","","","","","finding in the",""],["","","","","","","","","","","scan.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p10-t0","doc_id":"K193271","page_num":10,"bbox":[100.91,377.76,511.07,451.32],"n_rows":3,"n_cols":2,"columns":["Time-to-notification","Average performance time\n(seconds)"],"rows":[["Time-to-notification","Average performance time\n(seconds)"],["uAI EasyTriage-Rib","69.56"],["HealthVCF","61.36"]],"caption_candidate":"help of uAI EasyTriage-Rib.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p11-t0","doc_id":"K193271","page_num":11,"bbox":[89.3,553.33,522.95,573.97],"n_rows":2,"n_cols":2,"columns":["[13] Oikonomou A, Prassopoulos P. CT imaging of blunt chest trauma. Insights into imaging. 2011 Jun",""],"rows":[["[13] Oikonomou A, Prassopoulos P. CT imaging of blunt chest trauma. Insights into imaging. 2011 Jun",""],["1;2(3):281-95.",""]],"caption_candidate":"doi:10.1097/00005373-199412000-00018","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193271-p12-t0","doc_id":"K193271","page_num":12,"bbox":[89.3,429.84,522.9,465.96],"n_rows":3,"n_cols":2,"columns":["[27] Dehghan N, de Mestral C, McKee MD, Schemitsch EH, Nathens A. Flail chest injuries: a review of",""],"rows":[["[27] Dehghan N, de Mestral C, McKee MD, Schemitsch EH, Nathens A. Flail chest injuries: a review of",""],["outcomes and treatment practices from the National Trauma Data Bank. J Trauma Acute Care Surg.",""],["2014;76(2):462‐468. doi:10.1097/TA.0000000000000086",""]],"caption_candidate":"2004;70(4):193‐199","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193281-p4-t0","doc_id":"K193281","page_num":4,"bbox":[90.26,151.1,563.76,707.76],"n_rows":7,"n_cols":2,"columns":["Date:","Nov 26, 2019"],"rows":[["Date:","Nov 26, 2019"],["Submitter:","GE Medical Systems SCS (Establishment Registration Number – 9611343)\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact\nPerson:","Lifeng Wang\nRegulatory Affairs Manager\nGE Healthcare\nPhone: +86 10 57083145\nEmail: lifeng.wang@ge.com"],["Secondary Contact\nPerson:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE Healthcare\nPhone: (262) 424-7774\nEmail: Elizabeth.Mathew@ge.com"],["Proposed Device","➢ Device Name: Hepatic VCAR\n➢ Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography\nx-ray system / JAK\n➢ Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture\narchiving and communications system/ LLZ\n➢ Classification: Class II"],["Predicate Device:","➢ Device Name: Hepatic VCAR\n➢ 510(k) number: K133649\n➢ Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography\nx-ray system / JAK\n➢ Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture\narchiving and communications system/ LLZ\n➢ Classification: Class II"],["Device Description","Hepatic VCAR is a CT image analysis software package that allows the analysis\nand visualization of Liver CT data derived from DICOM 3.0 compliant CT scans.\nHepatic VCAR was designed for the purpose of assessing liver morphology,\nincluding liver lesion, provided the lesion has different CT appearance from\nsurrounding liver tissue; and its change over time through automated tools for\nliver, liver lobe, liver segments and liver lesion segmentation and measurement.\nHepatic VCAR is a post processing software medical device built on the Volume\nViewer (K041521) platform, and can be deployed on the Advantage Workstation"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193281-p5-t0","doc_id":"K193281","page_num":5,"bbox":[90.26,100.46,563.88,718.87],"n_rows":6,"n_cols":5,"columns":["","(AW) (K110834) and AW Server (K081985) platforms, CT Scanners, and PACS\nstations or cloud in the future.\nThis software will assist the user by providing initial 3D segmentation, vessel\nanalysis, visualization, and quantitative analysis of liver anatomy. The user has\nthe ability to adjust the contour and confirm the final segmentation.\nIn the proposed device, two new algorithms utilizing deep learning technology\nwere introduced. One such algorithm segments the liver producing a liver contour\neditable by the user; another algorithm segments the hepatic artery based on an\ninitial user input point. The hepatic artery segmentation is also editable by the\nuser.","","",""],"rows":[["","(AW) (K110834) and AW Server (K081985) platforms, CT Scanners, and PACS\nstations or cloud in the future.\nThis software will assist the user by providing initial 3D segmentation, vessel\nanalysis, visualization, and quantitative analysis of liver anatomy. The user has\nthe ability to adjust the contour and confirm the final segmentation.\nIn the proposed device, two new algorithms utilizing deep learning technology\nwere introduced. One such algorithm segments the liver producing a liver contour\neditable by the user; another algorithm segments the hepatic artery based on an\ninitial user input point. The hepatic artery segmentation is also editable by the\nuser.","","",""],["Intended Use/\nIndication for Use:","Hepatic VCAR is a CT image analysis software package that allows the analysis\nand visualization of Liver CT data derived from DICOM 3.0 compliant CT scans.\nHepatic VCAR is designed for the purpose of assessing liver morphology,\nincluding liver lesion, provided the lesion has different CT appearance from\nsurrounding liver tissue; and its change over time through automated tools for\nliver, liver lobe, liver segments and liver lesion segmentation and measurement. It\nis intended for use by clinicians to process, review, archive, print and distribute\nliver CT studies.\nThis software will assist the user by providing initial 3D segmentation, vessel\nanalysis, visualization, and quantitative analysis of liver anatomy. The user has\nthe ability to adjust the contour and confirm the final segmentation.","","",""],["Technology:","The modified Hepatic VCAR employs two deep learning convolutional neural\nnetworks to segment the liver contour and the hepatic artery on CT liver exams\nwhile the predicate device uses a traditional deterministic method to segment the\nliver and manual tools to segment the vascular structure including the hepatic\nartery. These changes do not change the Indications for Use from the predicate,\nand represent equivalent technological characteristics, with no impact on control\nmechanism, and operating principle.\nThe table below summarizes the feature/technological comparison between the\npredicate device and the proposed device:\nSpecification Predicate Device: Proposed Device:\nHepatic VCAR (K133649) Hepatic VCAR\nLiver Atlas algorithm based Deep Learning algorithm\nsegmentation segmentation based segmentation\nHepatic artery Manual segmentation tools Semi-automatic segmentation\nsegmentation (“autoselect” and scalpel) workflow based on deep\nlearning segmentation of the\nhepatic artery and edition","","",""],["","","Specification","Predicate Device:\nHepatic VCAR (K133649)","Proposed Device:\nHepatic VCAR"],["","","Liver\nsegmentation","Atlas algorithm based\nsegmentation","Deep Learning algorithm\nbased segmentation"],["","","Hepatic artery\nsegmentation","Manual segmentation tools\n(“autoselect” and scalpel)","Semi-automatic segmentation\nworkflow based on deep\nlearning segmentation of the\nhepatic artery and edition"]],"caption_candidate":"510(k) Premarket Notification Submission - Hepatic VCAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193281-p6-t0","doc_id":"K193281","page_num":6,"bbox":[90.26,100.75,563.82,487.15],"n_rows":3,"n_cols":5,"columns":["","","","","tools to correct/refine the\nresult."],"rows":[["","","","","tools to correct/refine the\nresult."],["Determination of\nSubstantial\nEquivalence:","Verification and validation including risk mitigations have been executed with\nresults demonstrating Hepatic VCAR met the design inputs and user needs with\nno unexpected results or risks.\nHepatic VCAR was designed and will be manufactured under the Quality System\nRegulations of 21CFR 820 and ISO 13485. The following quality assurance\nmeasures have been applied to the development of the device:\n• Risk Analysis\n• Requirements Reviews\n• Design Reviews\n• Performance testing (Verification, Validation)\n• Safety testing (Verification)\nBench tests that compare the output of the two new algorithms with ground truth\nannotated by qualified experts show that the algorithms performed as expected.\nA representative set of clinical sample images was assessed by 3 board certified\nradiologists using 5-point Likert scale. The assessment demonstrated that\ncapability of liver segmentation and hepatic artery segmentation utilizing the deep\nlearning algorithm by Hepatic VCAR.\nThe substantial equivalence was also based on software documentation for a\n\"Moderate\" level of concern device.","","",""],["Conclusion:","GE Healthcare considers proposed device Hepatic VCAR to be as safe, as\neffective, and performance is substantially equivalent to the predicate device.","","",""]],"caption_candidate":"510(k) Premarket Notification Submission - Hepatic VCAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193283-p7-t0","doc_id":"K193283","page_num":7,"bbox":[67.61,163.32,544.41,691.66],"n_rows":11,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison Results"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison Results"],["","Siemens\nAI-Rad Companion\nProstate MR","","","","Siemens","",""],["","","","","","syngo.MR","",""],["","","","","","Applications","",""],["","","","","","(K180336)","",""],["Software","AI-Rad Companion\nProstate MR","","","syngo.MR Applications\nwith SMRVB30A","","","Enhanced The subject\ndevice supports new\nsoftware version\noffering improvements\nand enhancements over\nthe predicate"],["Organ\nSegmentation &\nAnnotation","Automated\nsegmentation of the\nprostate gland with the\npossibility of manual\nadjustment and\nannotation","","","Manual measurements,\nsegmentations and\nmarks can be made\nwithin the prostate","","","Enhanced The subject\ndevice automates the\nprostate segmentation,\nwhile still permitting\nmanual manipulation\nand annotation"],["Image\nCommunication","DICOM compatible\nwith RTStruct object","","","DICOM compatible","","","Enhanced to provide\nadditional output format"],["Configuration","Confirmation UI","","","syngo.via GUI","","","Equivalent The subject\ndevice has been\nmodified to specific\nfunctionality for the\nProstate MR extension"],["Confirmation","Configuration UI","","","syngo.via GUI -\nconfiguration","","","Equivalent The subject\ndevice has been\nmodified to expose\nconfiguration options of\nexistent extensions."],["Architecture","Cloud only solution\nwith no components\ndeployed on customer\npremise.","","","Client-server\narchitecture where the\nserver processes and\nrenders the data from\nthe connected\nmodalities. Client\nprovides the UI for\ninteractive image\nviewing and processing.","","","Modified Architecture\nof the clinical extension\nis adapted to AI-Rad\nCompanion Engine and\ncloud-based\ndeployment."]],"caption_candidate":"A tabular comparison of the subject device is provided in Table 1 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193283-p8-t0","doc_id":"K193283","page_num":8,"bbox":[72.28,241.68,539.84,603.31],"n_rows":8,"n_cols":9,"columns":["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-40","General","Medical Devices –\napplication of risk\nmanagement to medical\ndevices","14971:2007","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle\nprocesses [Including\nAmendment 1 (2016)]","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""],["12-300","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 – 3.20\n(2016)","","","NEMA","",""],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1\n1994-02-15","","","ISO\nIEC","",""]],"caption_candidate":"as with the following voluntary FDA recognized Consensus Standards listed in Table 2 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193283-p9-t0","doc_id":"K193283","page_num":9,"bbox":[72.31,654.82,539.81,697.42],"n_rows":3,"n_cols":8,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],["","","Number","","","Date","",""],["syngo.MR Applications","K180336","","","April 19, 2018","","","LLZ, LNH"]],"caption_candidate":"device (Table3):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193287-p6-t0","doc_id":"K193287","page_num":6,"bbox":[67.14,268.68,572.04,701.76],"n_rows":2,"n_cols":2,"columns":["Category","Performance"],"rows":[["Category","Performance"],["Accuracy","CorInsights MRI hippocampal volume accuracy was tested using 80 subjects\nfrom the HaRP database as ground truth (Boccardi, et al.).\n CorInsights MRI measured hippocampal volume with an IntraClass\nCorrelation coefficient of 0.95 and a DICE coefficient of 83% left (standard\ndeviation 2.5%) and 83% right (standard deviation 2.7%) and a mean\nabsolute percentage difference of 6.2% left (standard deviation 4.4%) and\n5.9% right (standard deviation 5.1%) as compared to ground truth volumes.\nCorInsights MRI cortical segmentation accuracy was tested using 80\nsubjects from a variety of databases with manual ground truth segmentation\ngenerated by neuroanatomy experts.\n CorInsights MRI measured total gray volume with an IntraClass Correlation\ncoefficient of 0.99, a DICE coefficient of 95% (standard deviation 1.6%),\nand a mean absolute percentage difference of 4.5% (standard deviation,\n1.8%).\n CorInsights MRI measured cortical subregions with DICE coefficients\nranging from 81-93% and a mean absolute percentage difference range of\n4.6% to 13.8% across all regions.\nCorInsights MRI Intracranial Volume (ICV) and ventricular accuracy were tested\nusing an additional 70 subjects from a variety of databases with manual ground\ntruth segmentation generated by neuroanatomy experts.\n CorInsights MRI measured ICV with an IntraClass Correlation coefficient\nof 0.89, a DICE coefficient of 95% (standard deviation 1.1%) and a mean\nabsolute percentage difference of 5.2% (standard deviation of 4.4%).\n CorInsights MRI measured ventricular accuracy with an IntraClass\nCorrelation coefficient of 0.98 (left and right), a DICE coefficient of 88%\nleft (standard deviation 5.2%) and 87% right (standard deviation 5.6%) and\na mean absolute percentage difference of 13.9% left (standard deviation"]],"caption_candidate":"analyzed to support substantial equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193287-p7-t0","doc_id":"K193287","page_num":7,"bbox":[67.14,72.24,572.04,709.38],"n_rows":5,"n_cols":2,"columns":["Category","Performance"],"rows":[["Category","Performance"],["","9.2%) and 15.2% right (standard deviation 9.9%) compared to ground truth\nvolumes."],["Reproducibility","In test-retest processing of two different scans from the same subject on\nthe same scanner on the same day, CorInsights MRI measured volumes\nwith an average IntraClass Correlation coefficient of 0.97, a DICE\ncoefficient of 89% (standard deviation 4.0%) and a mean absolute\npercentage difference range of 0.7% to 5.8% with an average of 2.3%\n(standard deviation 2.7%) across all volumes listed in its report."],["Normative\nReference\nDatabase\nDevelopment","The CorInsights MRI reference database was developed using T1 weighted MRI\nscans from 269 male and 331 female individuals of age 42 to 95 who were\nclinically diagnosed to be cognitively normal.\nIn addition, these individuals were confirmed to be negative for amyloid pathology,\nand negative for a variety of other potential confounding abnormalities including\novert vascular disease as evidenced by white matter lesions, stroke or tumor,\nnormal pressure hydrocephalus, and with no history of traumatic brain injury or\nsevere neuropsychiatric illness as documented with the data set or provided in the\ndata set’s inclusion criteria. This screening was performed to ensure that the\nCorInsights MRI reference represented normal values without potential influence\nby disease, even when asymptomatic."],["Validation of\nVolume\nMeasurement\nin Clinically\nRelevant Cases","Testing of CorInsights MRI included scans acquired from scanners with 1.5T and\n3T field strengths, using accelerated and non-accelerated acquisition sequences,\nand representing a variety of scanner models from Siemens, GE, and Philips.\nValidation testing was conducted using patient scans from ages 45 to 95, with a\nbroad spectrum of clinical diagnoses including cognitively normal, Mild Cognitive\nImpairment, typical and atypical Alzheimer’s disease, and non-Alzheimer’s\ndementias. Alzheimer’s disease (AD) cases (confirmed for amyloid positivity)\nincluded late onset AD, Early Onset AD, Posterior Cortical Atrophy (PCA),\nLogopenic Progressive Aphasia, and Corticobasal Syndrome. Non-Alzheimer’s\ncases included behavioral variant (bv) Frontotemporal Dementia (FTD), semantic\nvariant (sv) FTD, Nonfluent Primary Progressive Aphasia, Primary Progressive\nAphasia (other), amyloid negative Corticobasal Syndrome, vascular disease,\nmoderate to severe white matter disease, and ventricular enlargement. Mild\nCognitive Impairment (MCI) cases included early MCI, late MCI, and persons who\nconverted to a clinical diagnosis of dementia at 12 months post-scan."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193287-p8-t0","doc_id":"K193287","page_num":8,"bbox":[67.14,72.24,572.04,294.0],"n_rows":2,"n_cols":2,"columns":["Category","Performance"],"rows":[["Category","Performance"],["","Volumes measured by CorInsights MRI were tested using normal subject scans, as\nwell as data sets expected to have below normal gray tissue volumes or above\nnormal ventricle volumes based upon well-established literature. These data sets\nincluded individuals with diagnoses of MCI, MCI who converted to a clinical\ndiagnosis of AD at 12 months post-scan, late onset AD, Early Onset AD, bvFTD,\nsvFTD, and PCA. CorInsights MRI values were compared to the percentile and z-\nscore ranges expected based upon peer reviewed published literature for these data\nsets, and were confirmed to be in these ranges. Relationships between regions\nbased on z-score ranking were also compared to published data and were in\nagreement with the literature. In all cases, the cognitively normal test group was\nconfirmed not to differ from the normative reference group or reference values.\nIn total, more than 1,400 scans from over 1,100 individuals were used in testing of\nCorInsights MRI."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193289-p5-t0","doc_id":"K193289","page_num":5,"bbox":[102.6,179.52,589.56,714.72],"n_rows":11,"n_cols":2,"columns":["Date:","November 5, 2020"],"rows":[["Date:","November 5, 2020"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact\nPerson:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE Healthcare, (GE Medical Systems, LLC)\n3000 N Grandview Blvd.,\nWaukesha, WI - 53188\nPhone: (262) 424-7774\nEmail: Elizabeth.Mathew@ge.com"],["Secondary Contact\nPerson:","Helen Peng\nSr. Regulatory Affairs Director\nGE Healthcare, (GE Medical Systems, LLC)\n3000 N Grandview Blvd.,\nWaukesha, WI - 53188\nPhone: 262-424-8222\nEmail: Hong.Peng@ge.com"],["Proposed Device:",""],["Device Name:","FastStroke, CT Perfusion 4D"],["Common/Usual\nName:","FastStroke, CT Perfusion 4D\nFastStroke Gen 2"],["Primary Regulation\nnumber:\nPrimary Product\nCode:","CFR 892.1750 Computed Tomography X-Ray System\nJAK"],["Secondary\nRegulation number:","21 CFR 892.2050 Picture archiving and communications system"],["Secondary Product\nCode:","LLZ"],["Classification:","Class II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193289-p6-t0","doc_id":"K193289","page_num":6,"bbox":[102.6,128.88,589.56,709.92],"n_rows":8,"n_cols":2,"columns":["Predicate Device:",""],"rows":[["Predicate Device:",""],["Device Name:","FastStroke"],["510(k) number:","K163281 cleared on January 26, 2017"],["Regulation number/\nProduct Code:","21 CFR 892.1750 Computed Tomography X-Ray System\nJAK"],["Classification:","Class II"],["Manufacturer:","GE Medical Systems SCS"],["Predicate Device:\nDevice Name:\n510(k) number:\nRegulation number/\nProduct Code:\nClassification:\nManufacturer:","CT Perfusion 4\nK052839 cleared on March 10, 2006\n21 CFR 892.1750 Computed Tomography X-Ray System\nJAK\nClass II\nGE Medical Systems SCS"],["Device Description:\nNeuroPackage is a solution which contains two medical devices FastStroke and CT Perfusion 4D (Neuro)\nin order to help streamline the CT Stroke Workflow. The configuration of NeuroPackage enables the user\nto open a single application, FastStroke, which provides them access to both the updated CT Perfusion 4D\nand FastStroke applications. However, same as the predicate devices, the capabilities in CT Perfusion 4D\nand FastStroke can be offered independently.\nCT perfusion 4D is an image analysis software package, which allows the user to produce dynamic image\ndata and to generate information with regards to changes in image intensity over time. It supports the\nanalysis of CT Perfusion images (in the head and body) after the intravenous injection of contrast, and\ncalculation of the various perfusion-related parameters (i.e. regional blood flow, regional blood volume,\nmean transit time and capillary permeability). The results are displayed in a user-friendly graphic format as\nparametric images.\nThis software will aid in the assessment of the extent and type of perfusion, blood volume, and capillary\npermeability changes, which may be related to stroke or tumor angiogenesis and the treatment thereof.\nFastStroke is a CT image analysis software package intended for the purpose of displaying stroke workup\nimages (i.e. vasculature of the head, non-contrast head and neck at different time points of enhancement) in\na single software, using an optimized workflow. The software is compatible with DICOM 3.0 images and\nwill assist the user by providing dedicated review steps and optimized display settings to enable fast review\nof the images in synchronized formats. In addition, if a multiphase CT Angiogram has been acquired, the\nsoftware will fuse the vascular information from these different time points into a single colorized view.\nThis multiphase information can aid the physician in visualizing the presence or absence of collateral\nvessels in the brain, as well as their delay.",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193289-p8-t0","doc_id":"K193289","page_num":8,"bbox":[107.44,359.4,585.6,716.38],"n_rows":14,"n_cols":6,"columns":["The table below summarizes the feature/technological comparison between the predicate device and the","","","","",""],"rows":[["The table below summarizes the feature/technological comparison between the predicate device and the","","","","",""],["proposed device:","","","","",""],["","","","","",""],["FastStroke:","","","","",""],["","","","","",""],["Specification","Predicate Device\nFastStroke\n(K163281)","Proposed Device\nFastStroke","","Comparison",""],["Send Email\nFeature","Not Available","Results from preprocessing\nwill be populated into email\nand sent to pre-defined\ndistribution list automatically.","","Substantial Equivalent\nImproved method to\ndistribute the report to\nfacilitate user workflow",""],["","","","","",""],["CT Perfusion 4D:","","","","",""],["","","","","",""],["","","","","",""],["Specification","Predicate Device\nCT Perfusion 4\n(K052839)","","P r oposed Device\nCT Perfusion 4D","","Comparison"],["Map Creation","Automatic based on HU\nthresholding","","Automatic Deep Learning\nAlgorithm","","Substantial Equivalent\nImproved method for\nremoving ventricles"],["Tissue\nClassification","In tissue classification it\nis restricted which input\nparameters can be used\n(Blood Volume only for","","In tissue classification there\nis no restriction as the\nsoftware allows the user to\nselect from 4 input","","Substantial Equivalent\nProposed device allows\nadditional input maps"]],"caption_candidate":"Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193289-p9-t0","doc_id":"K193289","page_num":9,"bbox":[102.6,129.26,589.56,661.12],"n_rows":4,"n_cols":6,"columns":["","","1st segmentation, Blood\nFlow, TMax or MTT only\nfor modified perfusion).","parameters (Blood Volume,\nBlodd Flow, TMax, MTT) to\ngenerate the tissue\nclassification display.","for Tissue Classification",""],"rows":[["","","1st segmentation, Blood\nFlow, TMax or MTT only\nfor modified perfusion).","parameters (Blood Volume,\nBlodd Flow, TMax, MTT) to\ngenerate the tissue\nclassification display.","for Tissue Classification",""],["","Send Email\nFeature","Manual method to export\nthe report.","Report with the images will\nbe populated into email and\nsent to pre-defined\ndistribution list\nautomatically.","Substantial Equivalent\nImproved method to\ndistribute the report",""],["Determination of Substantial Equivalence:\nNeuroPackage solution which contains FastStroke and CT Perfusion 4D software has successfully\ncompleted the required design control activities per GE’s quality management system that complies to\nQuality System Regulations of 21CFR 820 and ISO 13485. The following quality assurance measures have\nbeen applied to the development of the device:\n• Risk Analysis and Mitigation\n• Requirements Reviews\n• Design Reviews\n• Performance testing (Verification, Validation)\n• Safety testing (Verification)\nFor the brain ventricle segmentation deep learning algorithm, bench tests that compare the output of the\nnew algorithm with ground truth annotated by qualified experts show that the algorithm performed as\nexpected.\nThe software testing and the corresponding results for all the other changes in FastStroke and CT Perfusion\n4D software contained in NeuroPackage solution did not raise new questions of safety and effectiveness\nfrom those associated with predicate devices and demonstrated that modified FastStroke and CT Perfusion\n4D performs substantially equivalent to the predicate devices.\nThe substantial equivalence was also based on software documentation for a \"Moderate\" level of concern\ndevice.","","","","",""],["Conclusion\nGE Healthcare considers the modifications to FastStroke and CT Perfusion 4D contained within the\nNeuroPackage solution to be as safe, as effective as the predicate devices, and is substantially equivalent to\nthe predicate devices.","","","","",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193290-p6-t0","doc_id":"K193290","page_num":6,"bbox":[72.29,510.08,539.83,718.9],"n_rows":6,"n_cols":9,"columns":["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-40","General","Medical Devices –\napplication of risk\nmanagement to medical\ndevices","14971:2007","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""]],"caption_candidate":"following voluntary FDA recognized Consensus Standards listed in Table 1 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193290-p7-t0","doc_id":"K193290","page_num":7,"bbox":[72.29,72.85,539.83,281.81],"n_rows":6,"n_cols":9,"columns":["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["","","processes [Including\nAmendment 1 (2016)]","","","","","",""],["12-300","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 – 3.20\n(2016)","","","NEMA","",""],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1\n1994-02-15","","","ISO\nIEC","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193290-p8-t0","doc_id":"K193290","page_num":8,"bbox":[72.31,320.48,539.81,362.69],"n_rows":3,"n_cols":8,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],["","","Number","","","Date","",""],["syngo.MR Applications","K182904","","","July 5, 2019","","","LLZ"]],"caption_candidate":"2):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193294-p7-t0","doc_id":"K193294","page_num":7,"bbox":[72.2,87.69,539.69,449.34],"n_rows":8,"n_cols":9,"columns":["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product Area","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-40","General","Medical Devices –\napplication of risk\nmanagement to medical\ndevices","14971:2007","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle\nprocesses [Including\nAmendment 1 (2016)]","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""],["12-300","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 –3.20\n(2016)","","","NEMA","",""],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1\n1994-02-15","","","ISO\nIEC","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193294-p8-t0","doc_id":"K193294","page_num":8,"bbox":[72.24,511.1,539.66,573.66],"n_rows":2,"n_cols":4,"columns":["Predicate Device","FDA Clearance\nNumber","FDA Clearance\nDate","Main Product Code"],"rows":[["Predicate Device","FDA Clearance\nNumber","FDA Clearance\nDate","Main Product Code"],["AI-Rad Companion\n(Engine)","K183272","February 1, 2019","LLZ"]],"caption_candidate":"device (Table2):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193298-p6-t0","doc_id":"K193298","page_num":6,"bbox":[45.0,123.0,519.96,705.0],"n_rows":5,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for ICH triage\n(K180647)","Subject Device\nAidoc Briefcase for IFG triage"],"rows":[["","Predicate Device\nAidoc Briefcase for ICH triage\n(K180647)","Subject Device\nAidoc Briefcase for IFG triage"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nnon-enhanced head CT images.\nThe device is intended to\nassist hospital networks and trained\nradiologists in workflow triage\nby flagging and communication of\nsuspected positive findings of\npathologies in head CT images,\nnamely Intracranial Hemorrhage\n(ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected ICH on a\nstandalone desktop application in\nparallel to the ongoing standard of\ncare image interpretation. The user is\npresented with notifications for cases\nwith suspected ICH findings.\nNotifications include compressed\npreview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\neyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nabdominal CT images. The device is\nintended to assist hospital networks and\ntrained radiologists in workflow triage\nby flagging and communication of\nsuspected positive findings of Intra-\nabdominal Free Gas (IFG) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User population","Radiologist","Radiologist"],["Anatomical\nregion of\ninterest","Head","Abdomen"],["Data\nacquisition\nprotocol","Non-contrast head CT scan","Abdominal CT scan"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193298-p7-t0","doc_id":"K193298","page_num":7,"bbox":[45.0,72.24,519.96,326.4],"n_rows":7,"n_cols":3,"columns":["View DICOM\ndata","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient,\nstudy and current image"],"rows":[["View DICOM\ndata","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient,\nstudy and current image"],["Segmentation\nof region of\ninterest","No; device does not mark, annotate,\nor direct users’ attention to a specific\nlocation in the original image","No; device does not mark, annotate, or\ndirect users’ attention to a specific\nlocation in the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/Prio\nritization","Yes","Yes"],["Preview images","Presentation of a small, compressed,\nblack and white preview image that is\nlabeled “Not for diagnostic use”;\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a small, compressed,\nblack and white preview image that is\nlabeled “Not for diagnostic use”;\nThe device operates in parallel with the\nstandard of care, which remains the\ndefault option for all cases."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193298-p8-t0","doc_id":"K193298","page_num":8,"bbox":[114.24,218.45,480.95,378.94],"n_rows":20,"n_cols":19,"columns":["","","N","","","","","","Lower","","","Upper","","","","","","",""],"rows":[["","","N","","","","","","Lower","","","Upper","","","","","","",""],["","","","","","Mean","","","","","","","","","","","","",""],["","Parameter","","","","","","","","","","","","","Median","","","IQR",""],["","","","","","","","","Confidence","","","Confidence","","","","","","",""],["","","","","","estimate","","","","","","","","","","","","",""],["","","","","","","","","Limit","","","Limit","","","","","","",""],["","","","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","","","",""],["","Time-to-","","","","","","","","","","","","","","","","",""],["","exam-open in","22","","","94.1","","","49.9","","","138.2","","","50.1","","","79.9",""],["","the standard","","","","","","","","","","","","","","","","",""],["","of care","","","","","","","","","","","","","","","","",""],["","Time-to-","","","","","","","","","","","","","","","","",""],["","","22","","","4.4","","","3.7","","","5.0","","","4.2","","","2.5",""],["","notification of","","","","","","","","","","","","","","","","",""],["","BriefCase IFG","","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","","","",""],["","","22","","","89.7","","","45.5","","","133.9","","","47.4","","","76.7",""],["","Difference","","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 2. Time saving data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193300-p6-t0","doc_id":"K193300","page_num":6,"bbox":[117.38,98.78,494.74,166.7],"n_rows":3,"n_cols":5,"columns":["Category","N","Sensitivity","Specificity","AUROC"],"rows":[["Category","N","Sensitivity","Specificity","AUROC"],["NIH (US)","147","97.6%\n(93.2,99.2)","90.8%\n(84.5,94.7)","0.987\n(0.973,0.999)"],["PADCHEST\n(OUS)","153","85.3%\n(79.0,90.8)","89.7%\n(83.6,93.9)","0.949\n(0.918,0.979)"]],"caption_candidate":"Device Performance by Dataset and Region","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193300-p6-t1","doc_id":"K193300","page_num":6,"bbox":[103.7,207.74,508.42,395.71],"n_rows":4,"n_cols":5,"columns":["Spatial Resolution\nCategory","N","Sensitivity","Specificity","AUROC"],"rows":[["Spatial Resolution\nCategory","N","Sensitivity","Specificity","AUROC"],["High range\n<0.145\n(above 3.45 lp/mm)","133","89.5%\n(83.0,94.1)","85.1%\n(77.7,90.6)","0.976\n(0.944,0.999)"],["Mid range\n0.145-0.170\n(2.95-3.45 lp/mm)","88","92.6%\n(84.3,96.7)","93.4%\n(85.7,97.4)","0.983\n(0.961,0.999)"],["Low range\n>0.170\n(below 2.95 lp/mm)","64","93.1%\n(84.8,98.3)","91.4%\n(80.7,96.5)","0.946\n(0.911,0.980)"]],"caption_candidate":"Device Performance by Scanner Spatial Resolution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193300-p6-t2","doc_id":"K193300","page_num":6,"bbox":[72.1,590.68,543.15,719.04],"n_rows":2,"n_cols":9,"columns":["","","","","AIMI-Triage CXR PTX","","","HealthPNX (K190362)",""],"rows":[["","","","","AIMI-Triage CXR PTX","","","HealthPNX (K190362)",""],["Intended Use\n/ Indications\nfor Use","","","The AIMI-Triage CXR PTX Application is a\nnotification-only triage workflow tool for use by\nhospital networks and clinics to identify and help\nprioritize chest X-rays acquired in the acute setting\nfor review by hospital radiologists. The device\noperates in parallel to and independent of standard\nof care image interpretation workflow. Specifically,\nthe device uses an artificial intelligence algorithm to\nanalyze images for features suggestive of moderate\nto large sized pneumothorax; it makes case-level","","","The Zebra Pneumothorax\ndevice is a software workflow\ntool designed to aid the clinical\nassessment of adult Chest X-\nRay cases with features\nsuggestive of Pneumothorax in\nthe medical care environment.\nHealthPNX analyzes cases\nusing an artificial intelligence\nalgorithm to identify suspected","",""]],"caption_candidate":"Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193300-p7-t0","doc_id":"K193300","page_num":7,"bbox":[72.04,72.54,543.21,564.34],"n_rows":14,"n_cols":9,"columns":["","","","","AIMI-Triage CXR PTX","","","HealthPNX (K190362)",""],"rows":[["","","","","AIMI-Triage CXR PTX","","","HealthPNX (K190362)",""],["","","","output available to a PACS/workstation for worklist\nprioritization or triage. Identification of suspected\ncases of moderate to large sized pneumothorax is\nnot for diagnostic use beyond notification.\nThe AIMI-Triage CXR PTX Application is limited to\nanalysis of imaging data as a guide to possible\nurgency of adult chest X-ray image review, and\nshould not be used in lieu of full patient evaluation\nor relied upon to make or confirm diagnoses.\nNotified radiologists are responsible for engaging in\nappropriate patient evaluation as per local hospital\nprocedure before making care-related decisions or\nrequests. The device does not replace review and\ndiagnosis of the X-rays by radiologists. The device\nis not intended to be used with plain film X-rays.","","","findings. It makes case-level\noutput available to a\nPACS/workstation for worklist\nprioritization or triage.\nHealthPNX is not intended to\ndirect attention to specific\nportions or anomalies of an\nimage. Its results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it\nintended to rule out\nPneumothorax or otherwise\npreclude clinical assessment of\nX-Ray cases.","",""],["Classification","","","21 C.F.R. § 892,2080, Product Code QFM","","","","",""],["User","","","Radiologist","","","","",""],["Anatomical\nRegion","","","Lung","","","","",""],["Clinical\nCondition","","","Pneumothorax","","","","",""],["Modality","","","Chest X-ray","","","","",""],["Segmentation\nof region of\ninterest","","","No; device does not mark, highlight, or direct users’ attention to a specific location in\nthe original image","","","","",""],["Alteration of\noriginal\nimage","","","No","","","","",""],["Relation to\nstandard of\ncare workflow","","","Independent/parallel; no cases are removed from worklist queue","","","","",""],["Algorithm","","","Artificial intelligence algorithm with database of images","","","","",""],["Notification /\nPrioritization","","","Yes","","","","",""],["Alert to\nFinding","","","Passive notification – flagged for review","","","","",""],["Where\nResults are\nReceived","","","PACS / Workstation","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193306-p6-t0","doc_id":"K193306","page_num":6,"bbox":[207.93,468.12,575.94,710.4],"n_rows":5,"n_cols":3,"columns":["Specification","DynaCAD\nK192200\n(DynaCAD Prostaet)","Proposed Device:\nPROView"],"rows":[["Specification","DynaCAD\nK192200\n(DynaCAD Prostaet)","Proposed Device:\nPROView"],["Targeted clinical\ncondition","Male patient with suspected\nor known prostate lesions","Male patient with suspected\nor known prostate lesions"],["Anatomy","Prostate","Prostate"],["Imaging\nmodality","MRI","MRI"],["Gland\nsegmentation","Automatically performs a\n3D segmentation of the\ngland. Users can alter or\nmake adjustments to the\nsegmented results in all\nthree planes. The resulting\nsegmentation reports\noverall gland volume and\nsets the stage for UroNav\nMR/US guided fusion","The software provides a fully\nautomatic segmentation of\nthe prostate, based on a deep\nlearning model. Contour of\nthe prostate gland can be\nadjusted by the user. Prostate\nvolume is extracted from\nautomatic gland\nsegmentation."]],"caption_candidate":"(K192200) to which substantial equivalency is claimed.:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193306-p7-t0","doc_id":"K193306","page_num":7,"bbox":[207.52,128.88,576.12,320.64],"n_rows":4,"n_cols":3,"columns":["","biopsy",""],"rows":[["","biopsy",""],["Gland volume","The resulting segmentation\nreports overall gland\nvolume and sets the stage\nfor UroNav MR/US guided\nfusion biopsy","Prostate volume is extracted\nfrom automatic gland\nsegmentation after validation\nof the contour by the user."],["Segmentation\nalgorithm type","Model-based automatic\nprostate gland segmentation","Automatic segmentation of\nthe prostate based on a deep\nlearning model."],["Standardized\nreport","Following PI-RADSTM v2","Following PI-RADSTM v2.1"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p5-t0","doc_id":"K193351","page_num":5,"bbox":[67.32,577.37,535.18,710.96],"n_rows":11,"n_cols":9,"columns":["","","","","NinesAI (K193351)","","","AIDoc’s BriefCase (K180647)",""],"rows":[["","","","","NinesAI (K193351)","","","AIDoc’s BriefCase (K180647)",""],["Indications for Use","Indications for Use","","","NinesAI is a parallel workflow tool","","","BriefCase is a radiological computer",""],["","","","","indicated for use by hospital networks","","","aided triage and notification software",""],["","","","","and trained clinicians to identify","","","indicated for use in the analysis of",""],["","","","","images of specific patients to a","","","non-enhanced head CT images.",""],["","","","","radiologist, independent of standard","","","The device is intended to assist",""],["","","","","of care workflow, to aid in prioritizing","","","hospital networks and trained",""],["","","","","and performing the radiological","","","radiologists in workflow triage by",""],["","","","","review. NinesAI uses artificial","","","flagging and communication of",""],["","","","","intelligence algorithms to analyze","","","suspected positive findings of",""],["","","","","head CT images for findings","","","pathologies in head CT images,",""]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p6-t0","doc_id":"K193351","page_num":6,"bbox":[67.32,72.55,535.18,713.6],"n_rows":53,"n_cols":9,"columns":["","","","","NinesAI (K193351)","","","AIDoc’s BriefCase (K180647)",""],"rows":[["","","","","NinesAI (K193351)","","","AIDoc’s BriefCase (K180647)",""],["","","","","suggestive of a pre-specified","","namely Intracranial Hemorrhage\n(ICH).\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected ICH findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard\nof care.","namely Intracranial Hemorrhage",""],["","","","","emergent clinical condition.","","","(ICH).",""],["","","","","","","","BriefCase uses an artificial",""],["","","","","The software automatically analyzes","","","intelligence algorithm to analyze",""],["","","","","Digital Imaging and Communications","","","images and highlight cases with",""],["","","","","in Medicine (DICOM) images as they","","","detected ICH on a standalone",""],["","","","","arrive in the Picture Archive and","","","desktop application in parallel to the",""],["","","","","Communication System (PACS)","","","ongoing standard of care image",""],["","","","","using machine learning algorithms.","","","interpretation. The user is presented",""],["","","","","Identification of suspected findings is","","","with notifications for cases with",""],["","","","","not for diagnostic use beyond","","","suspected ICH findings. Notifications",""],["","","","","notification. 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Additionally, preview","","","viewing full images per the standard",""],["","","","","images displayed to the radiologist","","","of care.",""],["","","","","outside of the DICOM viewer are non-","","","",""],["","","","","diagnostic quality and should only be","","","",""],["","","","","used for informational purposes.","","","",""],["","User Population","","Radiologists","Radiologists","","Radiologists","",""],["Technological\nCharacteristics","Technological","","","Artificial Intelligence algorithms","","","Artificial Intelligence algorithms",""],["","Characteristics","","","detecting emergent findings sending","","","detecting emergent findings sending",""],["","","","","notifications to the workstation.","","","notifications to the workstation.",""],["Components","","","","- Artificial Intelligence","","","- Artificial Intelligence",""],["","","","","Algorithm","","","Algorithm",""],["","","","","- Notification Technology","","","- Notification Technology",""],["","Anatomical Region","","Head","Head","","Head","Head",""],["","of Interest","","","","","","",""],["Findings Covered","Findings Covered","","","Intracranial Hemorrhage and Mass","","Intracranial Hemorrhage","",""],["","","","","Effect","","","",""],["","Data Acquisition","","Non contrast CT scan of the head","Non contrast CT scan of the head","","","Non contrast CT scan of the head or",""],["","Protocol","","","","","","neck",""],["View DICOM Data","View DICOM Data","","","DICOM information about the patient,","","","DICOM information about the patient,",""],["","","","","study and current image","","","study and current image",""],["Preview Images","","","","Presentation of notification and","","","Presentation of notification and",""],["","","","","preview of the study for initial","","","preview of the study for initial",""],["","","","","assessment not meant for diagnostic","","","assessment not meant for diagnostic",""],["","","","","purposes. This is done via desktop","","","purposes. This is done via desktop",""],["","","","","notification or via DICOM series.","","","notification.",""],["","","","","","","","",""],["","","","","The device operates in parallel with","","","The device operates in parallel with",""],["","","","","the standard of care, which remains","","","the standard of care, which remains",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p7-t0","doc_id":"K193351","page_num":7,"bbox":[72.36,452.23,540.1,553.18],"n_rows":3,"n_cols":3,"columns":["Finding","Sensitivity [95% confidence\nintervals]","Specificity [95% confidence\nintervals]"],"rows":[["Finding","Sensitivity [95% confidence\nintervals]","Specificity [95% confidence\nintervals]"],["Intracranial Hemorrhage","0.899\n[0.837, 0.940]","0.974\n[0.994, 0.992]"],["Mass Effect","0.964\n[0.916, 0.987]","0.911\n[0.856, 0.948]"]],"caption_candidate":"The primary endpoints for each algorithm are listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p7-t1","doc_id":"K193351","page_num":7,"bbox":[130.58,634.54,481.63,702.6],"n_rows":2,"n_cols":3,"columns":["Metric","Mean (min)","Median (min)"],"rows":[["Metric","Mean (min)","Median (min)"],["Time-to-open-dictation\nstandard of care","159.4 [67.07, 251.7]","6.0"]],"caption_candidate":"The time-savings data for Intracranial Hemorrhage is listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p8-t0","doc_id":"K193351","page_num":8,"bbox":[130.58,72.48,481.63,128.06],"n_rows":2,"n_cols":3,"columns":["Metric","Mean (min)","Median (min)"],"rows":[["Metric","Mean (min)","Median (min)"],["Time-notification of\nNinesAI","0.23 [0.23, 0.24]","0.24"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193351-p8-t1","doc_id":"K193351","page_num":8,"bbox":[130.58,156.74,481.63,246.29],"n_rows":3,"n_cols":3,"columns":["Metric","Mean (min)","Median (min)"],"rows":[["Metric","Mean (min)","Median (min)"],["Time-to-open-dictation\nstandard of care","28.5 [14.1, 42.8]","7.5"],["Time-notification of\nNinesAI","0.23 [0.23, 0.24]","0.24"]],"caption_candidate":"The time-savings data for Mass Effect is listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193417-p3-t0","doc_id":"K193417","page_num":3,"bbox":[196.46,220.14,416.51,445.68],"n_rows":15,"n_cols":4,"columns":["","Study Type","","Radiographic View(s)\nSupported*"],"rows":[["","Study Type","","Radiographic View(s)\nSupported*"],["","(Anatomic Area","",""],["","of Interest+)","",""],["Ankle","","","Frontal, Lateral, Oblique"],["Clavicle","","","Frontal"],["Elbow","","","Frontal, Lateral"],["Femur","","","Frontal, Lateral"],["Forearm","","","Frontal, Lateral"],["Hip","","","Frontal, Frog Leg Lateral"],["Humerus","","","Frontal, Lateral"],["Knee","","","Frontal, Lateral"],["Pelvis","","","Frontal"],["Shoulder","","","Frontal, Lateral, Axillary"],["Tibia / Fibula","","","Frontal, Lateral"],["Wrist","","","Frontal, Lateral, Oblique"]],"caption_candidate":"FX is indicated for radiographs of the following industry-standard radiographic views and study types.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193417-p4-t0","doc_id":"K193417","page_num":4,"bbox":[72.0,40.39,385.54,699.56],"n_rows":45,"n_cols":2,"columns":["510(k) Summary – K1934","17"],"rows":[["510(k) Summary – K1934","17"],["",""],["In accordance with 21 CFR 80","7.87(h) and (21 CFR 807.92) the 5"],["FractureDetect (FX) is provid","ed below."],["",""],["1. SUBMITTER",""],["",""],["Submitter:","Imagen Technologies, Inc"],["","151 West 26th Street, Suite 1001"],["","New York, NY 10001"],["",""],["Primary Submission","Donna-Bea Tillman, Ph.D."],["Correspondent:","Senior Consultant"],["","Biologics Consulting"],["","1555 King St, Suite 300"],["","Alexandria, VA 22314"],["","410-531-6542"],["","dtillman@biologicsconsulting.com"],["",""],["Secondary Submission","Robert Lindsey, Ph.D."],["Correspondent:","Chief Science Officer"],["","Imagen Technologies, Inc"],["","151 West 26th Street, Suite 1001"],["","New York, NY 10001"],["","917-830-4721"],["","rob@imagen.ai"],["",""],["Date Prepared","June 23, 2020"],["",""],["2. DEVICE",""],["",""],["Device Trade Name:","FractureDetect (FX)"],["",""],["Device Common Name or","Radiological computer assisted det"],["Classification Name:","software for fracture"],["",""],["Regulation:","21 CFR 892.2090"],["",""],["Regulatory Class:","II"],["",""],["Product Code:","QBS"],["",""],["3. PREDICATE","DEVICE"],["",""],["Predicate Device: OsteoDet","ect (DEN180005)"]],"caption_candidate":"510(k) Summary – K193417","well_formed":true,"extraction_settings":"text"}
{"table_id":"K193417-p6-t0","doc_id":"K193417","page_num":6,"bbox":[195.97,170.64,416.03,450.24],"n_rows":15,"n_cols":4,"columns":["","Study Type","","Radiographic View(s)\nSupported*"],"rows":[["","Study Type","","Radiographic View(s)\nSupported*"],["","(Anatomic Area","",""],["","of Interest+)","",""],["Ankle","","","Frontal, Lateral, Oblique"],["Clavicle","","","Frontal"],["Elbow","","","Frontal, Lateral"],["Femur","","","Frontal, Lateral"],["Forearm","","","Frontal, Lateral"],["Hip","","","Frontal, Frog Leg Lateral"],["Humerus","","","Frontal, Lateral"],["Knee","","","Frontal, Lateral"],["Pelvis","","","Frontal"],["Shoulder","","","Frontal, Lateral, Axillary"],["Tibia / Fibula","","","Frontal, Lateral"],["Wrist","","","Frontal, Lateral, Oblique"]],"caption_candidate":"types.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193417-p7-t0","doc_id":"K193417","page_num":7,"bbox":[72.32,148.62,540.03,709.92],"n_rows":16,"n_cols":9,"columns":["","","","","FractureDetect (FX)","","","OsteoDetect",""],"rows":[["","","","","FractureDetect (FX)","","","OsteoDetect",""],["Number","","","TBD","","","DEN180005","",""],["Applicant","","","Imagen Technologies","","","Imagen Technologies","",""],["Device Name","","","FractureDetect","","","OsteoDetect","",""],["Classification Regulation","","","892.2090","","","892.2090","",""],["Product Code","","","QBS","","","QBS","",""],["Image Modality","","","X-ray","","","X-ray","",""],["Study Type\n(Anatomic Areas of Interest)","","","Ankle\nClavicle\nElbow\nFemur\nForearm\nHip\nHumerus\nKnee\nPelvis\nShoulder\nTibia / Fibula\nWrist","","","Wrist","",""],["Clinical Finding","","","Fracture","","","Fracture","",""],["Patient Population","","","Adults ≥ 22 years of age","","","Adults ≥ 22 years of age","",""],["Intended User","","","Clinicians","","","Clinicians","",""],["Machine Learning\nMethodology","","","Supervised Deep Learning","","","Supervised Deep Learning","",""],["Platform","","","Secure local processing and\ndelivery of DICOM images","","","Secure local processing and\ndelivery of DICOM images","",""],["Image Source","","","DICOM node\n(e.g., imaging device,\nintermediate DICOM node,\nPACS system, etc.)","","","Imaging device or intermediate\nDICOM node","",""],["Image Viewing","","","PACS system, image annotations\ntoggled on or off","","","PACS system, image annotations\nmade on copy of original image","",""],["Privacy","","","HIPAA Compliant","","","HIPAA Compliant","",""]],"caption_candidate":"Table 1: Technological Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193417-p9-t0","doc_id":"K193417","page_num":9,"bbox":[196.68,75.34,389.35,682.46],"n_rows":34,"n_cols":4,"columns":["FractureD","etect (FX)","ROC","Curve"],"rows":[["FractureD","etect (FX)","ROC","Curve"],["","","",""],["C=Area Under th","e Curve; RO","C=Rec","eiver"],["","","",""],["FractureDetec","t (FX) AU","C per S","tudy"],["","","",""],["Study Type","AUC","95% B","ootstr"],["(Anatomic","","",""],["Area of","","",""],["Interest)","","",""],["","","",""],["Ankle","0.983","(0.972,","0.991)"],["","","",""],["Clavicle","0.962","(0.948,","0.975)"],["","","",""],["Elbow","0.964","(0.940,","0.982)"],["","","",""],["Femur","0.989","(0.983,","0.994)"],["","","",""],["Forearm","0.987","(0.977,","0.995)"],["","","",""],["Hip","0.982","(0.962,","0.995)"],["","","",""],["Humerus","0.983","(0.974,","0.991)"],["","","",""],["Knee","0.996","(0.993,","0.998)"],["","","",""],["Pelvis","0.982","(0.973,","0.989)"],["","","",""],["Shoulder","0.962","(0.938,","0.982)"],["","","",""],["Tibia / Fibula","0.994","(0.991,","0.997)"],["","","",""],["Wrist","0.992","(0.988,","0.996)"]],"caption_candidate":"FractureDetect (FX) ROC Curve","well_formed":true,"extraction_settings":"text"}
{"table_id":"K193518-p4-t0","doc_id":"K193518","page_num":4,"bbox":[105.58,448.79,540.98,534.97],"n_rows":6,"n_cols":3,"columns":["Classification Name","21 CFR Number","Product Code"],"rows":[["Classification Name","21 CFR Number","Product Code"],["Ultrasonic Pulsed Doppler Imaging System","892.1550","IYN"],["Ultrasonic Pulsed Echo Imaging System","892.1560","IYO"],["Diagnostic Ultrasound Transducer","892.1570","ITX"],["Electronic Stethoscope","870.1875","DQD"],["Electrocardiograph","870.2340","DPS"]],"caption_candidate":"Classification Panel: Radiology, Cardiovascular","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193518-p6-t0","doc_id":"K193518","page_num":6,"bbox":[72.29,141.36,542.11,719.04],"n_rows":3,"n_cols":10,"columns":["Feature","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],"rows":[["Feature","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],["","","(This 510(k) submission)","","","System (K180995)","","","(K170874)",""],["Intended Use /\nIndications for\nUse","KOSMOS is intended to be used\nby qualified and trained healthcare\nprofessionals in the clinical\nassessment of the cardiac and\npulmonary systems and the\nabdomen by acquiring, processing,\ndisplaying, measuring, and storing\nsynchronized ultrasound images,\nelectrocardiogram (ECG) rhythms,\nand digital auscultation (DA)\nsounds and waveforms.\nWith respect to its ultrasound\nimaging capabilities, KOSMOS is\na general purpose diagnostic\nultrasound system used in the\nfollowing clinical applications and\nmodes of operation:\n• Clinical Applications: Cardiac,\nThoracic/Lung, Abdominal,\nPeripheral Vascular, and Image\nGuidance for Needle/Catheter\nPlacement\n• Modes of Operation: B-mode,\nM-mode, Color Doppler,\nCombined Modes of B+M and\nB+CD, and Harmonic Imaging\nKOSMOS is intended to be used\nin clinical care and medical\neducation settings on adult and\npediatric patient populations.\nThe device is non-invasive,\nreusable, and intended to be used\non one patient at a time.\nType of Use: Prescription Use\n(Part 21 CFR 801 Subpart D)","","","Vscan Extend is a general purpose\ndiagnostic ultrasound imaging\nsystem for use by qualified and\ntrained healthcare professionals\nenabling visualization and\nmeasurement of anatomical\nstructures and fluid. Its pocket-\nsized portability and simplified\nuser interface enables integration\ninto examination and training\nsessions indoors and in other\nenvironments described in the user\nmanual. The information can be\nused for basic/focused assessments\nand adjunctively with other\nmedical data for clinical diagnosis\npurposes during routine, periodic\nmonitoring, and triage.\nWith the phased array transducer\non the sector probe, the specific\nclinical applications and exam\ntypes include: Cardiac;\nAbdominal; Renal; OB/GYN;\nUrology; Fetal, Evaluation of\nPresence of Fluid; Imaging\nGuidance for Needle/Catheter\nPlacement (e.g. paracentesis,\npericardiocentesis, thoracentesis,\namniocentesis); Peripheral\nVascular Imaging (e.g. arteries\nand veins); Thoracic/Lung (e.g.\npleural motion/sliding, line\nartifacts); Adult Cephalic; and\nPediatrics.\nWith the addition of the linear\narray transducer on the single dual\nheaded probe solution, the specific\nclinical applications and exam\ntypes are expanded to include:\nPeripheral vascular imaging (e.g.\nlower extremity, carotid);\nProcedure Guidance for Arterial or\nVenous Vessels (e.g. central lines,\nupper extremity); Small Organs\n(e.g. thyroid); Musculoskeletal\n(Long Bone; Hip, shoulder, elbow\nand Knee Joints); Evaluation of\nPresence of Fluid; Thoracic/Lung\n(e.g. pleural motion/sliding, line\nartifacts); and Pediatrics.\nType of Use: Prescription Use\n(Part 21 CFR 801 Subpart D)","","","The Eko Model E5 System is\nintended to be used by healthcare\nprofessionals to electronically\namplify, filter, and transfer body\nsounds and single-channel\nelectrocardiogram (ECG)\nwaveforms. The Eko Model E5\nSystem also displays ECG\nwaveforms and phonocardiogram\nwaveforms on the accompanying\nmobile application for storage and\nsharing (when prescribed or used\nunder the care of a physician). It\ncan be used to record heart sounds\nand cardiac murmurs, bruits,\nrespiratory sounds, and abdominal\nsounds during physical\nexamination in normal patients or\nthose with suspected diseases of\nthe cardiac, vascular, pulmonary,\nor abdominal organ systems. The\ndevice can be used on adults and\npediatrics.\nThe data offered by the device is\nonly significant when used in\nconjunction with physician over\nread as well as consideration of\nother relevant patient data.\nThe device should not be used on\ninfants weighing less than 10kg.\nType of Use: Prescription Use (Part\n21 CFR 801 Subpart D)","",""]],"caption_candidate":"below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193518-p7-t0","doc_id":"K193518","page_num":7,"bbox":[72.26,72.36,542.11,717.57],"n_rows":21,"n_cols":11,"columns":["Feature","","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],"rows":[["Feature","","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],["","","","(This 510(k) submission)","","","System (K180995)","","","(K170874)",""],["","Ultrasound Substantial Equivalence (Technological Characteristics)","","","","","","","","",""],["Transducer Types","","Phased Array","","","Phased Array\nLinear Array","","","","",""],["Clinical\nApplications","","Phased Transducer:\nAnatomy/ Region of Interest:\nAbdominal\nPediatric\nCardiac Adult\nCardiac Pediatric\nPeripheral Vascular\nThoracic/Lung\nInterventional Guidance:\nNonvascular","","","Phased Transducer (only):\nAnatomy/ Region of Interest:\nFetal – OB/GYN\nAbdominal\nPediatric\nAdult Cephalic\nCardiac Adult\nCardiac Pediatric\nPeripheral Vascular\nThoracic/Pleural\nInterventional Guidance:\nNonvascular","","","","",""],["Transducer\nFrequency","","1.5 – 4.5 MHz","","","1.7 – 3.8 MHz","","","","",""],["Modes of\nOperation","","2D / B-mode\nM-mode\nColor Doppler\nCombination Modes\nHarmonic Imaging","","","2D / B-mode\nColor Doppler\nCombination Modes\nHarmonic Imaging","","","","",""],["PW Doppler","","Not available","","","Not available","","","","",""],["CW Doppler","","Not available","","","Not available","","","","",""],["510(k) Track","","Track 3","","","Track 3","","","","",""],["","DA and ECG Substantial Equivalence (Technological Characteristics)","","","","","","","","",""],["DA Pickup\nSensor and\nProcessing","","Audio microphone + digital signal\nprocessing\nSampling Rate: 12.7 kHz","","","","","","Audio microphone + digital signal\nprocessing\nSampling Rate: 4000 Hz","",""],["DA Filter Modes","","Heart/Midrange (50 – 600 Hz)","","","","","","Diaphragm (100 – 500 Hz), Bell\n(20 – 200 Hz, Midrange (50 – 500\nHz), Extended ((20 – 2000 Hz)","",""],["DA Sound\nAmplification","","Analog gain: 20 dB; Digital gain:\nuser adjustable up to 25 dB","","","","","","Amplifies up to 60x","",""],["DA Volume\nControl","","Yes; 15 volume steps available","","","","","","Yes; 12 volume settings","",""],["DA Ambient\nNoise Reduction","","Yes","","","","","","Yes","",""],["DA Direct\nListening","","Sounds can be listened to in real\ntime using a digital-to-analog\nbinaural headset","","","","","","Digital-only sound mode","",""],["ECG Non-\nContinuous\nMonitoring Leads","","3-lead, single-channel, user-\nsupplied commercial electrodes","","","","","","Single-channel, 2 stainless steel\nelectrodes","",""],["ECG Anatomical\nSites","","Chest (torso) and Leg","","","","","","Chest","",""],["ECG Leadwires\nand Trunk\nAssembly","","Combines trunk cable and three\nleadwires into a single, non-sterile,\nreusable assembly that forms a\nconduction channel for\ntransmitting signals from user-\nsupplied clip-style electrodes\naffixed to patient skin to the\nKosmos Torso (probe)","","","","","","No","",""],["DA and ECG\nVisualization","","Sounds and ECG waveforms can\nbe visualized and recorded on the\nKosmos Bridge (tablet) with or\nwithout an internet connection","","","","","","Sounds and ECG tracings can be\nvisualized on a Bluetooth device\nusing the Eko App. The app can be\nused to visualize waveforms and\ntracings without an internet\nconnection; however an internet\nconnection is necessary to save the\ndata.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193518-p8-t0","doc_id":"K193518","page_num":8,"bbox":[72.27,72.36,542.13,331.44],"n_rows":9,"n_cols":11,"columns":["Feature","","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],"rows":[["Feature","","","KOSMOS System","","","GE Vscan Extend Ultrasound","","","Eko Duo Model E5",""],["","","","(This 510(k) submission)","","","System (K180995)","","","(K170874)",""],["","System Characteristics","","","","","","","","",""],["Dimensions and\nWeight","","Handheld tablet display unit\n(proprietary): 146 x 216 x 59 mm,\n657 g\nDisplay: 8”\nProbe: 150 x 56 x 35 mm, 260 g","","","Handheld tablet display unit\n(proprietary): 168 x 76 x 22 mm,\n321 g\nDisplay: 12.7 cm, 720 x 1280\npixels resolution\nSector probe: 129 x 32 x 25 mm,\n85 g\nDual probe: 129 x 39 x 38 mm,\n120 g","","","Handheld Unit: 119 x 47 x 16 mm\nWeight: 208 g","",""],["Power Source","","Mains and battery operated\n(rechargeable lithium ion battery)","","","Battery operated","","","Battery operated (rechargeable\nlithium ion battery)","",""],["Patient Contact\nMaterials","","Probe Lens: RTV silicone 664\nProbe Housing: Polysulfone\nthermoplastic\nProbe Cemented Joint: RTV\nsilicone 832\nECG Leadwires: Thermoplastic\nurethane","","","Unknown (information not\npublicly available); however,\ntransducer material and other\npatient contact materials are\nbiocompatible","","","6061 machined aluminum\nenclosure\nHigh-impact ABS thermoplastic","",""],["Ingress Protection\n(IP) Rating","","Tablet: IP22\nProbe: IPX7","","","Unit: IP33\nProbe: IPX7","","","IP55","",""],["DICOM","","Yes","","","Yes","","","No","",""],["Wireless\nNetworking","","Wireless networking (IEEE\n802.11 b/g/n/ac supported)","","","Wireless networking (IEEE\n802.11 b/g/n supported)","","","Wireless networking (Bluetooth\n4.0 low-energy)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p6-t0","doc_id":"K193562","page_num":6,"bbox":[94.02,319.01,518.04,753.33],"n_rows":6,"n_cols":12,"columns":["","","","Subject Device","","","Predicate\nDevice","","","Reference Device","",""],"rows":[["","","","Subject Device","","","Predicate\nDevice","","","Reference Device","",""],["","Device","","Siemens","","","","Xiamen","","Siemens","",""],["","Manufacturer","","","","","","Manteia LTD.","","","",""],["Device Name","","","AI-Rad Companion\nOrgans RT","","","AccuContour","","","syngo.via RT Image Suite","",""],["","510(k) Number","","","K193562","","","K191928","","","K192065",""],["Indications for\nUse","","","AI-Rad Companion\nOrgans RT is a post-\nprocessing software\nintended to automatically\ncontour DICOM CT\nimaging data using deep-\nlearning-based\nalgorithms.\nContours that are\ngenerated by AI-Rad\nCompanion Organs RT\nmay be used as input for\nclinical workflows\nincluding external beam\nradiation therapy\ntreatment planning. AI-\nRad Companion Organs\nRT must be used in\nconjunction with\nappropriate software\nsuch as Treatment\nPlanning Systems and\nInteractive Contouring","","","It is used by\nradiation\noncology\ndepartment to\nregister\nmultimodality\nimages and\nsegment (non-\ncontrast) CT\nimages, to\ngenerate needed\ninformation for\ntreatment\nplanning,\ntreatment\nevaluation and\ntreatment\nadaptation.","","","syngo.via RT Image Suite is a\n3D and 4D image\nvisualization, multi-modality\nmanipulation and\ncontouring tool that helps the\npreparation and response\nassessment of treatments such\nas, but not limited to those\nperformed with radiation (for\nexample, Brachytherapy,\nParticle Therapy, External\nBeam Radiation Therapy).\nIt provides tools to efficiently\nview existing contours, create,\nedit, modify, copy contours of\nregions of the body, such as\nbut not limited to, skin\noutline, targets and organs-at-\nrisk. It also provides\nfunctionalities to create and\nmodify simple treatment\nplans. Contours, images and\ntreatment plans can\nsubsequently be exported to a\nTreatment Planning System.\nThe software combines","",""]],"caption_candidate":"not raise different questions of the safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p8-t0","doc_id":"K193562","page_num":8,"bbox":[93.96,73.56,518.1,750.06],"n_rows":8,"n_cols":4,"columns":["Segmentation Feature & Technological Characteristics","","",""],"rows":[["Segmentation Feature & Technological Characteristics","","",""],["Algorithm","Deep Learning","Deep Learning","Atlas-based, machine\nlearning and deep-learning\nbased contouring"],["Segmentation of\nOrgan at Risk in\nthe Anatomic\nRegions","Head & Neck, Thorax,\nAbdomen & Pelvis","Head & Neck,\nThorax,\nAbdomen &\nPelvis","Head & Neck, Thorax,\nAbdomen & Pelvis"],["Compatible\nModality","CT Images","Non-Contrast\nCT","CT Images"],["Compatible\nScanner Models","No Limitation on\nscanner model,\nDICOM compliance\nrequired.","No Limitation\non scanner\nmodel,\nDICOM 3.0\ncompliance\nrequired.","No Limitation on scanner\nmodel, DICOM\ncompliance required."],["Compatible\nTreatment\nPlanning System","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation\non TPS model,\nDICOM 3.0\ncompliance\nrequired.","No Limitation on TPS\nmodel, DICOM 3.0\ncompliance required."],["Contraindications","-Adult use only","-Adult use only\n-Not intended\nto be used as a\nstand-alone\ndiagnostic\ndevice","There are no known\nspecific situations that\ncontraindicate the use of\nthis device."],["Target\nPopulation","AI-Rad Companion\nOrgans RT is designed\nfor use only in adult\npopulations.\nAI-Rad Companion\nOrgans RT is designed\nfor any patient for\nwhom relevant\nmodality scans are\navailable. More\nspecifically, the\nsoftware is validated\non previously acquired\nCT DICOM volumes\nfor radiation therapy\ntreatment planning,\nincluding, head and","Any patient\ntype for whom\nrelevant\nmultimodality\nimages and\nsegment (non-\ncontrast) CT\nimages are\navailable.","Any patient type for whom\nthe relevant modality scan\ndata is available."]],"caption_candidate":"Traditional 510(k) Submission: AI-Rad Companion Organs RT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p9-t0","doc_id":"K193562","page_num":9,"bbox":[93.96,73.56,518.1,745.41],"n_rows":7,"n_cols":4,"columns":["","neck, thorax, abdomen,\nand pelvis.","",""],"rows":[["","neck, thorax, abdomen,\nand pelvis.","",""],["Clinical\ncondition the\ndevice is\nintended to\ndiagnose, treat or\nmanage","Limited to patients\npreviously selected for\nRadiation Therapy.","Limited to\npatients\npreviously\nselected for\nRadiation\nTherapy.\nHowever,\nAccuContour\ncan be used for\ntreatment\nevaluation and\ntreatment\nadaptation.","Limited to patients\npreviously selected for\nRadiation Therapy."],["Software\nArchitecture","AI-Rad Companion\n(Engine) architecture\nenabling the\ndeployment of AI Rad\nCompanion Organs RT\nin the Cloud. The UI is\nprovided using a web-\nbased interface.","Cloud and/or\nServer based","Client-server architecture\nwhere the server processes\nand renders the data. Client\nprovides the UI for\ninteractive image viewing\nand processing"],["Deployment\nFeature","Cloud Deployment","Cloud\nDeployment\nand Server","On-premise/standalone\ndeployment"],["Organ Templates","Creating, editing and\ndeletion of organ\ntemplates. Customize\npredefined structure\ndatabase with mapping\nto international\nnomenclature schemes.","No information\npublicly\navailable.","Creating, editing and\ndeletion of structure\ntemplates. Customize\npredefined structure\ndatabase with mapping to\ninternational nomenclature\nschemes."],["Automated\nworkflow","AI-Rad Companion\nOrgans RT\nautomatically\nprocesses input image\ndata and sends the\nresults as DICOM-RT\nStructure Sets to a\nuser-configurable\ntarget node.","AccuContour\nautomatically\nprocesses input\nimage data","Rapid Results workflow\nfeature allows the\nconfiguration of automatic\norgan contouring and\noptionally send DICOM-\nRT files to a target\nDICOM-Node for further\nprocessing."],["Contour\nvisualization and\nediting feature","AI-Rad Companion\nOrgans RT provides\nbasic result preview of\nautomatic","AccuContour\nprovides basic\nresult preview\nof automatic","syngo.via RT Image Suite\nprovides advanced contour\nvisualization feature of"]],"caption_candidate":"Traditional 510(k) Submission: AI-Rad Companion Organs RT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p10-t0","doc_id":"K193562","page_num":10,"bbox":[93.96,73.56,518.1,713.46],"n_rows":5,"n_cols":4,"columns":["","segmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","segmentation\nresults. Manual\ncontouring is\npossible.","contours and manual\nediting feature"],"rows":[["","segmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","segmentation\nresults. Manual\ncontouring is\npossible.","contours and manual\nediting feature"],["Segmentation\nPerformance","The target performance\nwas validated using\n113 cases distributed to\ntwo cohorts. Cohort\nA-Clinical Routine\nTreatment Planning\nCT (Siemens; Head\nand Neck, Thorax and\nAbdomen Pelvis) and\nCohort B-Multi\nVendor Coverage (GE\nand Phillips; Head and\nNeck).\nTo objectively evaluate\nthe target performance,\nthe DICE coefficient,\nthe absolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject and reference\ndevice were equivalent\nas well as the overall\nperformance compared\nto the predicate device.","The\nsegmentation\nperformance\nwas validated\nusing datasets\nfrom China\nand the USA\nusing three\nmajor vendors\n(GE, Siemens\nand Phillips).\nThe\nsegmentation\naccuracy is\nevaluated\nusing DICE\ncoefficient.","The target performance was\nvalidated using 32 cases\nwith various fields of view.\nTo objectively evaluate the\ntarget performance, the\nDICE coefficient & the\nabsolute symmetric surface\ndistance (ASSD) were\nevaluated. The\nsegmentation performance\nof the subject and predicate\ndevice were equivalent."],["User Interface –\nResults Preview\n(Confirmation)","Basic visualization\nfunctionality of\noriginal data and\ngenerated contours","Basic result\npreview of\nautomatic\nsegmentation\nresults. Manual\ncontouring is\npossible.","Standard visualization tools\n(window levels, MPR,\nMIP, VRT). Manual\ncontouring is possible."],["User Interface\nConfiguration","Configuration UI","Configuration\nmenu","syngo.via GUI"],["Human Factors","Design to be used by\ntrained clinicians.","Design to be\nused by trained\nclinicians.","Design to be used by\ntrained clinicians."]],"caption_candidate":"Traditional 510(k) Submission: AI-Rad Companion Organs RT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p11-t0","doc_id":"K193562","page_num":11,"bbox":[96.62,233.05,515.5,607.11],"n_rows":8,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-40","General","Medical Devices –\napplication of risk\nmanagement to medical\ndevices","14971:2007","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle\nprocesses [Including\nAmendment 1 (2016)]","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""],["12-300","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 – 3.20\n(2016)","","","NEMA","",""],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1 1994-\n02-15","","","ISO\nIEC","",""]],"caption_candidate":"Table 4 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p12-t0","doc_id":"K193562","page_num":12,"bbox":[94.44,515.23,519.06,581.12],"n_rows":4,"n_cols":9,"columns":["","","","","DICE","","","95% Hausdorff Distance (HD)",""],"rows":[["","","","","DICE","","","95% Hausdorff Distance (HD)",""],["","AccuContour (K191928)","","0.85 – 0.95","","","≤ 3.5 mm","",""],["","AI-Rad Companion Organs RT","","MED: 0.85","","","MED: 2.0 mm","",""],["","VA20","","","","","","",""]],"caption_candidate":"the subject device and predicate device are comparable in DICE and Hausdorff Distance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193562-p13-t0","doc_id":"K193562","page_num":13,"bbox":[110.93,267.43,501.13,334.02],"n_rows":3,"n_cols":10,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","","Main Product",""],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","","Main Product",""],["","","Number","","","Date","","","Code",""],["AccuContour","K191928","","","February 28, 2020","","","QKB","",""]],"caption_candidate":"AI-Rad Companion Organs RT is substantially equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p4-t0","doc_id":"K193658","page_num":4,"bbox":[102.6,513.72,545.4,561.12],"n_rows":3,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc. (Primary)","ContaCT","DEN170073"],["Aidoc Medical, Ltd.","BriefCase","K180647"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p6-t0","doc_id":"K193658","page_num":6,"bbox":[72.0,417.72,544.56,716.88],"n_rows":13,"n_cols":4,"columns":["","Viz ICH","ContaCT (DEN170073)","BriefCase (K180647)"],"rows":[["","Viz ICH","ContaCT (DEN170073)","BriefCase (K180647)"],["Technological Characteristics","","",""],["DICOM\nCompatible","Yes","Yes","Yes"],["Transfer, store,\nand process\nDICOM images","Yes","Yes","Yes"],["Data Acquisition","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities.","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities.","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities."],["Image Analysis","","",""],["Supported\nImaging Modality","Computed Tomography, non-\ncontrast (NCCT)","Computed Tomography,\ncontrast-enhanced (CTA)","Computed Tomography, non-\ncontrast (NCCT)"],["Alteration of\nOriginal Image","No","No","No"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking","Internal, no image marking"],["Image Viewing Functionality","","",""],["Preview Images","Initial assessment; non-\ndiagnostic purposes","Initial assessment; non-\ndiagnostic purposes","Initial assessment; non-\ndiagnostic purposes"],["View DICOM\nData","DICOM Information about the\npatient, study and current\nimage.","DICOM Information about the\npatient, study and current\nimage.","DICOM Information about the\npatient, study and current\nimage."],["Image viewing","Yes","Yes","Yes"]],"caption_candidate":"zoom, scroll through a cine).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p8-t0","doc_id":"K193658","page_num":8,"bbox":[107.52,470.88,539.52,545.16],"n_rows":4,"n_cols":3,"columns":["Performance Stratified by Clinical Site","",""],"rows":[["Performance Stratified by Clinical Site","",""],["Clinical Site","Sensitivity [95% Cl]","Specificity [95% Cl]"],["Erlanger","0.93 [0.85, 0.98]","0.92 [0.84, 0.97]"],["Mt. Sinai","0.92 [0.8, 0.98]","0.86 [0.75, 0.94]"]],"caption_candidate":"confounding variables:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p8-t1","doc_id":"K193658","page_num":8,"bbox":[107.52,558.96,539.52,651.84],"n_rows":5,"n_cols":3,"columns":["Performance Stratified by Age","",""],"rows":[["Performance Stratified by Age","",""],["Age Range (years)","Sensitivity [95% Cl]","Specificity [95% Cl]"],["<50","0.89 [0.52, 1.0]","0.95 [0.76, 1.0]"],["50 - 70","0.92 [0.82, 0.97]","0.9 [0.8, 0.96]"],[">70","0.94 [0.84, 0.99]","0.88 [0.76, 0.95]"]],"caption_candidate":"Mt. Sinai 0.92 [0.8, 0.98] 0.86 [0.75, 0.94]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p9-t0","doc_id":"K193658","page_num":9,"bbox":[107.52,72.24,539.52,146.52],"n_rows":4,"n_cols":3,"columns":["Performance Stratified by Gender","",""],"rows":[["Performance Stratified by Gender","",""],["Gender","Sensitivity [95% Cl]","Specificity [95% Cl]"],["Male","0.9 [0.8, 0.96]","0.9 [0.8, 0.96]"],["Female","0.95 [0.86, 0.99]","0.89 [0.8, 0.95]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p9-t1","doc_id":"K193658","page_num":9,"bbox":[107.52,160.32,539.52,308.88],"n_rows":8,"n_cols":2,"columns":["Performance Stratified by ICH Subtype",""],"rows":[["Performance Stratified by ICH Subtype",""],["ICH Subtype","Sensitivity [95% CI]"],["Intraparenchymal Hemorrhage (IPH)","0.98 [0.91, 1.0]"],["Intraventricular Hemorrhage (IVH)","1.00 [0.74, 1.0]"],["Subarachnoid Hemorrhage (SAH)","0.60 [0.26, 0.88]"],["Subdural Hemorrhage (SDH)","0.85 [0.62, 0.97]"],["Extradural Hemorrhage (EDH)","N/A"],["SDH or EDH","0.85 [0.62, 0.97]"]],"caption_candidate":"Female 0.95 [0.86, 0.99] 0.89 [0.8, 0.95]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p9-t2","doc_id":"K193658","page_num":9,"bbox":[107.52,322.68,539.52,396.96],"n_rows":4,"n_cols":3,"columns":["Performance Stratified by Slice Thickness","",""],"rows":[["Performance Stratified by Slice Thickness","",""],["Slice Thickness","Sensitivity","Specificity"],["2.5mm <= Slice Thickness < 3.5mm","0.93 [0.85, 0.98]","0.92 [0.83, 0.97]"],["3.5mm <= Slice Thickness <= 5.0mm","0.92 [0.81, 0.98]","0.88 [0.77, 0.95]"]],"caption_candidate":"SDH or EDH 0.85 [0.62, 0.97]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K193658-p9-t3","doc_id":"K193658","page_num":9,"bbox":[107.52,424.08,539.52,531.6],"n_rows":5,"n_cols":3,"columns":["Performance Stratified by ICH Volume","",""],"rows":[["Performance Stratified by ICH Volume","",""],["Minimal Volume Threshold\n(mL)","Sensitivity above Threshold\n[95% Cl]","Sensitivity below/equal\nThreshold [95% Cl]"],["1","0.95 [0.89, 0.98]","0.73 [0.39, 0.94]"],["5","0.97 [0.91, 0.99]","0.81 [0.64, 0.93]"],["10","0.99 [0.93, 1.0]","0.84 [0.7, 0.93]"]],"caption_candidate":"3.5mm <= Slice Thickness <= 5.0mm 0.92 [0.81, 0.98] 0.88 [0.77, 0.95]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200232-p5-t0","doc_id":"K200232","page_num":5,"bbox":[117.16,163.82,494.96,706.9],"n_rows":32,"n_cols":7,"columns":["","","","","Submitted Device","","Predicate Device"],"rows":[["","","","","Submitted Device","","Predicate Device"],["","","","","","",""],["Features/Characteristics","","","","LVivo","","TomTec-Arena 1.0 K132544"],["Product Code","","","","QIH","","LLZ"],["Intended Use","","","","Calculate\nand measurement\nof LV, RV and\nBladder","","Calculation and\nmeasurement LV, RV,\nfetal and abdomen"],["Indication for Use","","","","DiA’s LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected disease.","DiA’s LVivo platform is","Indication for use of Tom-\nTec- Arena software are\ndiagnostic review,\nquantification and reporting of\ncardiovascular, fetal, and\nabdominal structures and\nfunctions of patients with\nsuspected disease."],["","","","","","intended for non-",""],["","","","","","invasive processing of",""],["","","","","","ultrasound images to",""],["","","","","","detect, measure, and",""],["","","","","","calculate relevant",""],["","","","","","medical parameters of",""],["","","","","","structures and function",""],["","","","","","of patients with",""],["","","","","","suspected disease.",""],["Automation","","","","yes","","yes"],["Manual Adjustment","","","","yes","","yes"],["RV Calculation from","","","","2d","","3d"],["RV ED Volume","","","","no","","yes"],["FAC","","","","yes","","yes"],["ED Area","","","","yes","","no"],["EDVi","","","","no","","yes"],["ES Vol","","","","no","","yes"],["Es area","","","","yes","","no"],["EF","","","","no","","yes"],["SV","","","","no","","yes"],["TAPSE","","","","yes","","yes"],["Strain values free wall","","","","yes","","yes"],["Strain values septum","","","","no","","yes"],["","S prime","","","yes","","no"],["","View","","","4ch view","","Multi 2d view"],["","510(k) #","","","K200232","","K132544"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200232-p6-t0","doc_id":"K200232","page_num":6,"bbox":[117.17,83.9,494.95,678.6],"n_rows":23,"n_cols":4,"columns":["","Submitted Device","","Reference Devices"],"rows":[["","Submitted Device","","Reference Devices"],["Features/Characteristics","LVivo","","LVivo K130779 & K161382"],["Product Code","QIH","","LLZ"],["Indications For Use","DiA’s LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected disease.","DiA’s LVivo platform is","DiaCardio’s LVivo Software\nApplication is intended for\nnon-invasive processing of\nalready acquired\nechocardiographic images in\norder to detect, measure, and\ncalculate the left ventricular\nwall for left ventricular\nfunction evaluation. This\nmeasurement can be used to\nassist the clinician in a\ncardiac evaluation."],["","","intended for non-",""],["","","invasive processing of",""],["","","ultrasound images to",""],["","","detect, measure, and",""],["","","calculate relevant",""],["","","medical parameters of",""],["","","structures and function",""],["","","of patients with",""],["","","suspected disease.",""],["Modules","LVivo EF, LVivo SG,\nLVivo SAX, LVivo RV &\nLVivo Bladder","","LVivo EF, LVivo SG, LVivo\nSAX"],["Automation","Same","","Fully Automated"],["Bi plane EF evaluation","Yes","","Yes"],["Simultaneous 2CH\nand 4CH evaluation","Yes","","Yes"],["Off line EF\nevaluation using\nDICOM clips of any","Yes","","Yes"],["vendor\nAutomated ED and\nES frames selection","Yes","","Yes"],["Dynamic left ventricular","Yes. Frame by\nframe tracking","","Yes. Frame by frame\ntracking"],["assessment\nManual editing by user\ncapability","Minimum of 7 border\npoints manipulation\n(dragging) and online\ncontour presentation.\nPossible to apply to\nany frame in the clip.\nBorder detection is\nrecalculation is\napplied to the entire\nclip.","","Yes. 7 border points\nmanipulation (dragging) and\nonline contour presentation.\nPossible to apply to any\nframe in the clip.\nBorder detection is\nrecalculation is applied to\nthe entire clip."],["Visually confirm EF","Yes","","Yes"],["Automated rejection\nof false results","Yes","","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200232-p7-t0","doc_id":"K200232","page_num":7,"bbox":[117.14,72.24,494.98,710.16],"n_rows":11,"n_cols":3,"columns":["Volume calculation by\nSimson's method of\ndiscs","Yes","Yes"],"rows":[["Volume calculation by\nSimson's method of\ndiscs","Yes","Yes"],["Volume curve\nPresentation","Yes","Yes"],["EF results presentation","Displaying full clip with\nborder tracking. And\ntable with results for\neach cycle for selected\nED & ES frames for\neach beat.","Displaying full clip with border\ntracking. And table with\nresults for each cycle for\nselected ED & ES frames for\neach beat."],["Enables presentation EF\nresults for different cycle","Yes","Yes"],["Algorithm","Image segmentation for\nborder detection\nFor the RV- Deep\nLearning Technology","Image segmentation for\nborder detection\nFrom image processing"],["Calculation speed","Less than 1s per cycle\nfor biplane evaluation","Less than 1s per cycle for\nbiplane evaluation"],["Capability or a part of a\nbigger package (device)\nfor LV function\nevaluation","Yes","Yes"],["Segmental Longitudinal\nStrain Measure","Yes","Yes"],["Global Longitudinal\nStrain Measure","Yes","Yes"],["Segmental wall motion\nevaluation","Yes","Yes"],["RV Evaluation","Yes","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200232-p8-t0","doc_id":"K200232","page_num":8,"bbox":[117.17,72.24,494.95,174.62],"n_rows":3,"n_cols":3,"columns":["Bladder Measurement","Yes","No"],"rows":[["Bladder Measurement","Yes","No"],["Operating System","Windows/Linux (with\nAndroid Mobile\nOption for LVivo EF)","Windows"],["510(k) #","K200232","K130779 & K161382"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p5-t0","doc_id":"K200323","page_num":5,"bbox":[72.35,147.25,540.35,397.12],"n_rows":9,"n_cols":2,"columns":["Table 1 : Submitter’s Information",""],"rows":[["Table 1 : Submitter’s Information",""],["Submitter’s Name:","Kurt Sysock"],["Company:","Radformation, Inc."],["Address:","335 Madison Avenue, 16th Floor\nNew York, NY 10017"],["Contact Person:","Alan Nelson\nChief Science Officer, Radformation"],["Phone:","518-888-5727"],["Fax:","---------"],["Email:","anelson@radformation.com"],["Date of Summary Preparation","9/16/2020"]],"caption_candidate":"5.1. Submitter’s Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p5-t1","doc_id":"K200323","page_num":5,"bbox":[72.35,442.75,540.35,654.38],"n_rows":8,"n_cols":2,"columns":["Table 2 : Device Information",""],"rows":[["Table 2 : Device Information",""],["Trade Name:","AutoContour"],["Common Name:","AutoContour, AutoContouring, AutoContour Agent,\nAutoContour Web Application"],["Classification Name:","Class II"],["Classification:","Picture archiving and communications system"],["Regulation Number:","892.2050"],["Product Code:","QKB"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2. Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p6-t0","doc_id":"K200323","page_num":6,"bbox":[72.28,612.25,540.28,731.62],"n_rows":3,"n_cols":4,"columns":["Table 3: Substantial Equivalence AutoContour vs. RTx & Workflow Box","","",""],"rows":[["Table 3: Substantial Equivalence AutoContour vs. RTx & Workflow Box","","",""],["Characteristic","Subject Device:\nAutoContour\nRadformation","Predicate Device:\nWorkflow Box (K181572)","Predicate Device: Mirada\nRTx (K130393)"],["Target\nPopulation","Any patient type for\nwhom relevant modality\nscan data is available.","Any patient type for\nwhom relevant\nmodality scan data is","Any patient type for whom\nrelevant modality scan data\nis available."]],"caption_candidate":"1/20/2020)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p7-t0","doc_id":"K200323","page_num":7,"bbox":[72.38,72.33,540.38,727.12],"n_rows":7,"n_cols":4,"columns":["","(Substantially\nEquivalent)","available.",""],"rows":[["","(Substantially\nEquivalent)","available.",""],["Energy Used\nand/or\nDelivered","None – software only\napplication. The software\napplication does not\ndeliver or depend on\nenergy delivered to or\nfrom patients\n(Substantially\nEquivalent)","None – software only\napplication. The\nsoftware application\ndoes not deliver or\ndepend on energy\ndelivered to or from\npatients","None – software only\napplication. The software\napplication does not\ndeliver or depend on\nenergy delivered to or from\npatients"],["Intended users","Trained radiation\noncology personnel\n(Substantially\nEquivalent)","Designed to be used by\ntrained clinicians","Designed to be used by\ntrained clinicians"],["Design: Data\nVisualisation/Gr\naphical User\nInterface","Contains both an\nautomated processing\ncomponent and Data\nVisualisation / Graphical\nUser Interface\n(Substantially\nEquivalent)","None – the proposed\ndevice has no data\nvisualization\nfunctionality. All data\nprocessing is\nautomated and does\n​\nnot require user\ninteraction. A control\ninterface is provided for\nsystem administration\nand configuration only","Yes.\n​"],["Design: View\nmanipulation\nand Volume\nrendering","Window and level, pan,\nzoom, cross-hairs, slice\nnavigation, fused views.\n(Subject Device\nfunctionality is a subset\nof Predicate Devices)","None – Not applicable","Window and level, pan,\nzoom, cross-hairs, slice\nnavigation. Maximum or\n​\nminimum intensity projection\n(MIP), volume rendering,\ncolor rendering, surface\nrendering, multi-planar\nreconstruction (MPR), fused\n​\nviews, gallery views.\n​"],["Design: Image\nregistration","Manual Rigid\nregistration.\n(Subject Device\nfunctionality is a subset\nof Predicate Devices)","Registration for the\npurposes of\nreplanning/re-contouring\nand atlas based\ncontouring. The\nalgorithms used for\nimage registration are\nthe same for both\npredicate and proposed\ndevices.","Manual and Landmark\nRigid. Automatic multi-modal\n​\nrigid. Mono-modal and\nmulti-modal deformable\nregistration. Motion correction\nin hybrid scans and gated\nscans. Registration for the\npurposes of\nre-planning/recontouring and\natlas based contouring."],["Regions and\nVolumes of\ninterest (ROI)","Machine learning based\ncontouring and manual\nROI manipulation.\n(Subject Device","Atlas Based contouring,\nregistration based\nre-contouring, machine\n​","2D and 3D ROIs,\nsemi-automatic ROI\ndefinition, isocontour ROIs\nusing threshold and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p8-t0","doc_id":"K200323","page_num":8,"bbox":[72.38,72.33,540.38,715.88],"n_rows":6,"n_cols":4,"columns":["","functionality is a subset\nof Predicate Devices)","learning based\ncontouring","percentage of maximum,\none-click seed-pointing\ncontouring, manual ROI\n​\nmanipulation, ROI\n​\ntransformation, Atlas-based\ncontouring."],"rows":[["","functionality is a subset\nof Predicate Devices)","learning based\ncontouring","percentage of maximum,\none-click seed-pointing\ncontouring, manual ROI\n​\nmanipulation, ROI\n​\ntransformation, Atlas-based\ncontouring."],["Design:\nRegion/volume\nof interest\nmeasurements\nand size\nmeasurements","None – not applicable\n(Substantially\nEquivalent)","None – not applicable","Intensity, Hounsfield units,\nactivity and SUV\nmeasurements including min,\nmax, mean, peak, standard\ndeviation, total glycolytic\nactivity, median, histogram,\nmax and mean ratio to\nreference region. Gray for RT\nDose. Size measurements\ninclude 2D and 3D\nmeasurements including\nrulers and volume, line\nprofile."],["Design:\nRegion/Volume\nQuantification","None – not applicable\n(Substantially\nEquivalent)","None – not applicable","Regions table with charting\nsupports analysis of\nmeasurement over multiple\nstudies using standard\nprotocols such as RECIST,\nPERCIST and WHO"],["Design:\nSupported\nmodalities","CT input for contouring\nor manual\nregistration/fusion.\nMR, PET input for\nmanual\nregistration/fusion only.\nDICOM RTSTRUCT for\noutput\n(Minor differences)","CT, MR, DICOM\n​ ​\nRTSTRUCT for image\n​\nprocessing. Any valid\nDICOM data for data\nrouting","Static and gated CT and\n​\nPET, and static MR, SPECT,\n​\nNM, DICOM RT"],["Design:\nReporting and\ndata routing","No built-in reporting,\nsupports exporting\nDICOM RTSTRUCT file.\n(Minor differences)","Supports routing and\ndistribution of images to\nother DICOM nodes\nincluding to custom\nexecutables determined\nby the user.","Yes– Distribution of DICOM\ncompliant Images into other\nDICOM compliant systems.\nBuilt-in basic reporting"],["Compatibility\nwith the\nenvironment\nand other\ndevices","Compatible with data\nfrom any DICOM\ncompliant scanners for\nthe applicable modalities.\nAgent Uploader\ncomponent compatible\nwith Microsoft Windows.","Compatible with data\nfrom any DICOM\ncompliant scanners for\nthe applicable\nmodalities. Compatible\n​ ​\nwith Microsoft\nWindows. Integration\n​\nwith Mirada DBx","Compatible with data from\nany DICOM compliant\nscanners for the applicable\nmodalities. Compatible\n​ ​\nwith Microsoft Windows.\n​\nIntegration with Mirada DBx\napplication launcher and data\nbrowser."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200323-p9-t0","doc_id":"K200323","page_num":9,"bbox":[72.38,72.33,540.38,645.38],"n_rows":4,"n_cols":4,"columns":["","Cloud-based automatic\ncontouring service\ncompatible with Linux.\nWeb application Server\nbased application\ncompatible with Linux\nwith frontend compatible\nwith all modern web\nbrowsers..\n(Minor differences)","application launcher and\ndata browser",""],"rows":[["","Cloud-based automatic\ncontouring service\ncompatible with Linux.\nWeb application Server\nbased application\ncompatible with Linux\nwith frontend compatible\nwith all modern web\nbrowsers..\n(Minor differences)","application launcher and\ndata browser",""],["Communication\ns/Networking","TCP/IP\n(Subject Device\nfunctionality is a subset\nof Predicate Devices)","TCP/IP and SCP\n​","TCP/IP and SCP\n​"],["Computer\nplatform &\noperating\nsystem","Agent Uploader\nsupporting Microsoft\nWindows 10 (64-bit) and\nMicrosoft Windows\nServer 2016.\nCloud-based Server\nbased automatic\ncontouring application\ncompatible with Linux.\nWeb application Server\nbased application\ncompatible with Linux\nwith frontend compatible\nwith all modern web\nbrowsers.\n(Minor differences)","Server based application\nsupporting Microsoft\nWindows 10 (64-bit) and\nMicrosoft Windows\nServer 2016.","Workstation and Server\nbased application supporting\nWindows Server 2008 R2,\nSP1 and Windows 7 (64-bit)"],["Support for\nradiation\ntreatment\nplanning","AutoContour is intended\nto assist radiation\ntreatment planners in\ncontouring and reviewing\nstructures within medical\nimages in preparation for\nradiation therapy\ntreatment planning\n(Subject Device intended\nuse is a subset of\npredicate devices)","“Contours generated by\nWorkflow Box may be\nused as an input to\nclinical workflows\nincluding, but not limited\nto, radiation therapy\ntreatment planning”","“RTx supports the loading\nand saving of DICOM RT\nobjects and allows the user to\ndefine, import, display,\ntransform, store and export\nsuch objects including\nregions of interest structures\nand dose volumes to\nradiation therapy planning\nsystems.”"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K200714-p8-t0","doc_id":"K200714","page_num":8,"bbox":[14.76,689.53,581.82,764.53],"n_rows":6,"n_cols":13,"columns":["Characteristic","Subject Device","","Primary Predicate","","Reference Device","","","Reference Device","Reference Device","","","Reference Device"],"rows":[["Characteristic","Subject Device","","Primary Predicate","","Reference Device","","","Reference Device","Reference Device","","","Reference Device"],["","","","Device","","","","","","","","",""],["Device Name","AVIEW 2.0","AVIEW","AVIEW","","","Imbio CT Lung","","AVIEW LCS","","AI-Rad","","Calcium Scoring"],["","","","","","","Density Analysis","","","","Companion","",""],["","","","","","","Software","","","","(Cardiovascular)","",""],["Classification\nName","System, image\nProcessing Radiological","System, image\nProcessing\nRadiological","","","Computed Tomography\nx-ray system","","","System, image\nProcessing\nRadiological","Computed\nTomography x-ray\nsystem","","","Computed\nTomography x-ray\nsystem"]],"caption_candidate":"tests, we conclude that the proposed device is substantially equivalent to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200714-p9-t0","doc_id":"K200714","page_num":9,"bbox":[14.7,84.53,581.88,755.06],"n_rows":18,"n_cols":9,"columns":["Regulatory\nNumber","","","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.1750","21 CFR 892.2050","21 CFR 892.1750","21 CFR 892.1750"],"rows":[["Regulatory\nNumber","","","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.1750","21 CFR 892.2050","21 CFR 892.1750","21 CFR 892.1750"],["","Product Code","","LLZ, JAK","LLZ","JAK","LLZ, JAK","JAK","JAK"],["","Review Panel","","Radiology","Radiology","Radiology","Radiology","Radiology","Radiology"],["","510k Number","","-","K171199","K141069","K193220","K183268","K990426"],["Indications for\nuse","","","AVIEW 2.0","","","","",""],["","","","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This software could be used to support the physician\nquantitatively in the diagnosis, follow up evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in\nlung, lobe, airways and cardiac, registration of inspiration and expiration which could analyze air trapping on lung, volumetric and structure analysis,\ndensity evaluation and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on premise and as cloud environment as\nwell to allow users to connect by various environment such as mobile devices and chrome browser. Characterizing nodules in the lung in a single study,\nor over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major\naxis, minor axis), estimated effective diameter from the volume of the nodule, volume of the nodule, Mean HU(the average value of the CT pixel inside\nthe nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures(Solid major; length of the longest\ndiameter measured in 3D for solid portion of the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections\nperpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with\nfindings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, integrate with FDA\ncertified Mevis CAD (Computer aided detection) (K043617). It also provides CAC analysis by segmentation of four main artery (right coronary artery,\nleft main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score\nand mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.","","","","",""],["","","","AVIEW","","","","",""],["","","","AVEIW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be used to support the physician quantitatively in the\ndiagnosis, followup evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in the left and right lung\n(e.g., the five lobes and airway), volumetric and structural analysis, density evaluations and reporting tools. AVIEW is also used to store, transfer, inquire\nand display CT data sets. AVEIW is not meant for primary image Interpretation in mammography.","","","","",""],["","","","Imbio CT Lung Density Analysis Software","","","","",""],["","","","The Imbio CT Lung Density Analysis Software provides reproducible CT values for pulmonary tissue, which is essential for providing quantitative\nsupport for diagnosis follow up examinations. The Imbio CT Lung Density Analysis Software can be used to support the physician in the diagnosis and\ndocumentation of pulmonary tissue images (e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of sub-compartments,\nvolumetric analysis, density evaluation, and reporting tools are provided.","","","","",""],["","","","AVEIW LCS","","","","",""],["","","","AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single\nstudy, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size\n(major axis, minor axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU(the average value of the CT\npixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures (Solid Major, length\nof the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured\nin sections perpendicular to the Major axis of the solid portion of the nodule), VDT(Volume doubling time), and Lung-RADS (classification proposed\nto aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate\nwith FDA certified Mevis CAD (Computer-aided detection) (K043617)","","","","",""],["","","","AI-Rad Companion (Cardiovascular)","","","","",""],["","","","AI-Rad Companion (Cardiovascular) is processing software that provides quantitative and qualitative analysis from previously acquired Computed\nTomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the\nevaluation and assessment of cardiovascular disease.\nIt provides the following functionality:\n Segmentation and volume measurement of the heart\n Quantification of the total calcium volume in the coronary arteries\n Segmentation of the aorta\n Measurement of maximum diameters of the aorta at typical landmarks\n Threshold-based highlighting of enlarged diameters\nThe software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Helathineers, GE Healthcare,\nPhilips, and Toshiba/Canon, Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstruction\nform Siemens Healthineers.\nOnly DICOM images of adult patients are considered to be valid input.","","","","",""],["","","","Calcium Scoring","","","","",""],["","","","From user specified sets of CT cardiac images, Calcium Scoring can be used to;\n Allow the user to interactively indicate regions of detected calcification\n To allow the user to allocate each detected region to one of several coronary arteries\n To estimate algorithmically a score for the amount of detected calcification in each allocated artery\n To prepare reports including reports including calcium score data, Imagery, ECG traces, Comparison of scroe to cited literature and additional\nrelevant information.\nThe calcium-scoring package is a diagnostic tool that can be used to evaluate the calcified plaques in the coronary arteries, which is a risk factor for\ncoronary artery disease. Calcium scoring may be used to monitor the progression or regression overtime of the amount or volume of calcium in the\ncoronary arteries, which may be related to the prognosis of a cardiac attack.","","","","",""],["Platform","","","IBM-compatible PC or\nPC network","IBM-compatible PC\nor PC network","IBM-compatible PC or\nPC network","IBM-compatible PC or\nPC network","IBM-compatible PC\nor PC network","IBM-compatible PC\nor PC network"],["","User Interface","","Monitor, Mouse,","Monitor, Mouse,","Monitor, Mouse,","Monitor, Mouse,","Monitor, Mouse,","Monitor, Mouse,"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200714-p10-t0","doc_id":"K200714","page_num":10,"bbox":[14.7,84.52,581.88,748.87],"n_rows":16,"n_cols":9,"columns":["","","","Keyboard","Keyboard","Keyboard","Keyboard","Keyboard","Keyboard"],"rows":[["","","","Keyboard","Keyboard","Keyboard","Keyboard","Keyboard","Keyboard"],["Image Input\nSources","","","Images can be scanned,\nloaded from card\nreaders, or imported\nfrom a radiographic\nimaging device","Images can be\nscanned, loaded\nfrom card readers, or\nimported from a\nradiographic\nimaging device","Images can be scanned,\nloaded from card\nreaders, or imported\nfrom a radiographic\nimaging device","Images can be\nscanned, loaded from\ncard readers, or\nimported from a\nradiographic imaging\ndevice","Images can be\nscanned, loaded\nfrom card readers, or\nimported from a\nradiographic\nimaging device","Images can be\nscanned, loaded\nfrom card readers, or\nimported from a\nradiographic\nimaging device"],["","Image format","","DICOM","DICOM","DICOM","DICOM","DICOM","DICOM"],["Image\nMeasurement\nTools","","","Ruler (line and 3D),\nTapeline (curve, poly\nand3D), Angle (3-point,\n4point, and 3D), pixel\nvalues, area of ROI\n(rectangle, circle,\nellipse), volume","Ruler (line and 3D),\nTapeline (curve,\npoly and3D), Angle\n(3-point, 4point, and\n3D), pixel\nvalues, area of ROI\n(rectangle, circle,\nellipse), volume","-","Ruler (line and 3D),\nTapeline (curve, poly\nand3D), Angle (3-\npoint, 4point, and 3D),\npixel values, area of\nROI (rectangle, circle,\nellipse), volume","-","-"],["Image viewing","","","Axial, sagittal, and\ncoronal image, oblique\nslice, cube view","Axial, sagittal, and\ncoronal image,\noblique slice, cube\nview","-","Axial, sagittal, and\ncoronal image, oblique\nslice, cube view","-","-"],["Image\nmanipulation","","","Panning, rotating,\nzooming, windowing,\ninverting, Coloring,\nOblique, Note (text\noverlay), Coloring","Panning, rotating,\nzooming,\nwindowing,\ninverting, Coloring,\nOblique, Note (text\noverlay), Coloring","-","Panning, rotating,\nzooming, windowing,\nColoring, Oblique,\nNote (text\noverlay), Coloring","-","-"],["General\nDescription","","","AVIEW 2.0","","","","",""],["","","","The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM\n3.0 which is the digital image and communication standard in medicine. It also offers functions such as reading, manipulation, analyzing, post-processing,\nsaving and sending images by using the software tools. And is intended for use as diagnostic patient imaging which is intended for the review and analysis\nof CT scanning. Provides following features as semi-automatic nodule management, maximal plane measure, 3D measures and volumetric measures,\nautomatic nodule detection by integration with 3rd party CAD. Also provides Brocks model which calculated the malignancy score based on numerical\nor Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality assurance tool\ndesigned to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change and other findings\nthat is reported. It also automatically analyzes coronary artery calcification which support user to detect cardiovascular disease in early stage and reduce\nthe burden of medical.","","","","",""],["","","","AVIEW","","","","",""],["","","","The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM\n3.0 which is the digital image and communication standard in medicine. It also offers functions such as reading. Manipulation, analyzing, post-processing,\nsaving and sending images by using the software tools.","","","","",""],["","","","Imbio CT Lung Density Analysis Software","","","","",""],["","","","The Imbio CT Lung Density Analysis Software (Imbio LDA) IS A SET OF IMAGE POST-PROCESSING ALGORITHMS THAT PERFORM IAMGE\nSEGMENTATION, REGISTRATION, THRESHOLDING, AND CLASSIFICATION ON ct images of juman lungs.\nThe algorithms within the Imbio CT Lung Density Analysis Software are combined into a single command-line or through scripting. The Imbio CT Lung\nDensity Analysis Software program performs segmentation, then registration, then thresholding and classification. The program reads in DICOM\ndatasets, processes the data, then writes output DICOM files to a specified directory.\nThe Imbio CT Lung Density Analysis Software is a command-line software application that analyzed DICOM CT Lung images datasets and generated\nreports and DICOM output that show the lungs segmented and overlaid with colorpcodings representing the results of its thresholding and classification\nrules. It has simple file management functions for input and output, and separate modules that implement the CT image-processing algorithms. Imbio\nCT Lung Density Analysis Software does not interface directly with any CT or data collection equipment; instead the software imports data files\npreviously generated by such equipment.","","","","",""],["","","","AVIEW LCS","","","","",""],["","","","AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides following\nfeatures as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules\ndetection by integration with 3rd party CAD. Also provide cancer risk based on PANCAN risk model which calculated the malignancy score based on\nnumerical or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality\nassurance tool designed to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change\nand other findings that is reported.","","","","",""],["","","","AI-Rad Companion (Cardiovascular)","","","","",""],["","","","In general, AI-Rad Companion (Cardiovascular) is a software only image post-processing application that uses deep learning algorithms to post-process\nCT data of the thorax. As an update to the previously cleared devices, the following modifications have been made;\n1) Modified indication for Use Statement\n2) Support of software AI-Rad Companion CT VA10A\na) heart segmentation including measurement (modified)\nb) calcium detection based on deep learning algorithm (modified)\nc) Aorta segmentation (modified)","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200714-p11-t0","doc_id":"K200714","page_num":11,"bbox":[14.7,84.55,581.88,752.38],"n_rows":13,"n_cols":7,"columns":["","d) AHA landmarks for labeling and diameter measurement of the aorta, including threshold-based aorta diameter classification (modified)\n3) subject device claims list\nThe subject device AI-Rad Companion (Cardiovascular) is an image processing software that utilizes deep learning algorithms to provide quantitative\nand qualitative analysis from previously acquired Computed Tomography DICOM image to support radilogists and physicians from emergency medicine,\nspecialty care, urgent care, and general practice in the evaluation and assessment of disease of the thorax. The subject devcei support the following device\nspecific functionality.\n Segmentation and volume measurement of heart\n Identification and measurement of volume with high Hounsfield values- related to coronary calcification\n Segmentation of the aorta determination of 9 Landmarks.\n Computation of cross-sectional MPRs at the 9 landmarks and their maximum diameter\n Measurement of maximum diameters of the aorta at typical landmakrs.\nThreshold-based classification of diameters into different categories","","","","",""],"rows":[["","d) AHA landmarks for labeling and diameter measurement of the aorta, including threshold-based aorta diameter classification (modified)\n3) subject device claims list\nThe subject device AI-Rad Companion (Cardiovascular) is an image processing software that utilizes deep learning algorithms to provide quantitative\nand qualitative analysis from previously acquired Computed Tomography DICOM image to support radilogists and physicians from emergency medicine,\nspecialty care, urgent care, and general practice in the evaluation and assessment of disease of the thorax. The subject devcei support the following device\nspecific functionality.\n Segmentation and volume measurement of heart\n Identification and measurement of volume with high Hounsfield values- related to coronary calcification\n Segmentation of the aorta determination of 9 Landmarks.\n Computation of cross-sectional MPRs at the 9 landmarks and their maximum diameter\n Measurement of maximum diameters of the aorta at typical landmakrs.\nThreshold-based classification of diameters into different categories","","","","",""],["","Calcium Scoring","","","","",""],["","Calcium Scoring is a software package running on the 3Dvirtuoso workstation that allows the user to mark regions of detected calcification in CT cardiac\nimages, to assign each region to a coronary artery, and to calculate the Agatston score and other information from the identified pixels. Film and paper\nreports of the results can also be prepared. Calcium Scoring is also a cost-effective alternative to Electron Beam CT (EBCT), since it produces calcium\nscores that correlated to the EBCT’s gold standard, but at a much lower cost.","","","","",""],["DICOM","This receives DICOM\ndata from CT by\nDICOM communication\nConducts DICOM data\ncommunication with\nPACS. It also imports\nDICOM file directly,\nsaves by using export\nfunction.","This receives\nDICOM data from\nCT by DICOM\ncommunication\nConducts DICOM\ndata communication\nwith PACS. It also\nimports DICOM file\ndirectly, saves by\nusing export\nfunction.","Retrieve image data\nover the network via\nDICOM","This receives DICOM\ndata from CT by\nDICOM\ncommunication\nConducts DICOM data\ncommunication with\nPACS. It also imports\nDICOM file directly,\nsaves by using export\nfunction.","Retrieve image data\nover the network via\nDICOM","Retrieve image data\nover the network via\nDICOM"],["Lung Analysis\nFunctions","Fully automatic lungs,\nlobes and airways\nsegmentation using\ndeep-learning\nalgorithms","Semi-automatic\nsegmentation of\nlungs, lobes and\nairways.","","-","",""],["","Semi-automatic\nsegmentation of lungs,\nlobes and airways.","","","","",""],["","Visualization of multi-\nplanar reconstructed\n(MPR) images and 3D\nrendered images, with\ncolor-defined\nHounsfield Unit (HU)\nranges.","Visualization of\nmulti-planar\nreconstructed (MPR)\nimages and 3D\nrendered images,\nwith color-defined\nHounsfield Unit\n(HU) ranges.","","-","",""],["","Calculation of LAA\n(Lower Attenuation\nArea) index with HU\ndensity histogram.\nVolume measurements\nand percentile index","Calculation of LAA\n(Lower Attenuation\nArea) index with HU\ndensity histogram.\nVolume\nmeasurements and\npercentile index","","-","",""],["","Calculation of LAA\ncluster size distribution\nwith D-slope","Calculation of LAA\ncluster size\ndistribution with D-\nslope","","-","",""],["","Graphical visualization\nof the above\nquantification results for\nreporting","Graphical\nvisualization of the\nabove quantification\nresults for reporting","","-","",""],["","Export of quantification\nresults to CSV tables","Export of\nquantification results\nto CSV tables","","-","",""],["","Visualization of LAA%\nfor each of 5 lobes","Visualization of\nLAA% for each of 5\nlobes","","-","",""],["","Measurements of the\nairway branches, such\nas, lumen area and wall\narea","Measurements of the\nairway branches,\nsuch as, lumen area\nand wall area","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200714-p12-t0","doc_id":"K200714","page_num":12,"bbox":[14.69,84.52,581.88,745.9],"n_rows":9,"n_cols":7,"columns":["","Analyzes Air Trapping\nIndex by registration of\ninspiration and\nexpiration data. Could\ncompare both IN/EX\nafter the registration","-","Imbio provides\nsegmentation of lung\nand automatied\nregistration of\ninspiration and\nexpiration image part to\nclassify the analysis by\nthresholding the CT\ndata.\nIt also provides an\ninterctive visualliztion\nof the registered pairs to\nanalyze low-density\ncluster (air trap) and\nairway analysis.","","",""],"rows":[["","Analyzes Air Trapping\nIndex by registration of\ninspiration and\nexpiration data. Could\ncompare both IN/EX\nafter the registration","-","Imbio provides\nsegmentation of lung\nand automatied\nregistration of\ninspiration and\nexpiration image part to\nclassify the analysis by\nthresholding the CT\ndata.\nIt also provides an\ninterctive visualliztion\nof the registered pairs to\nanalyze low-density\ncluster (air trap) and\nairway analysis.","","",""],["","Fully automatic\nINSP/EXP registration\n(non-rigid elastic)\nalgorithm.","-","Uses advanced image\nprocessing techniques\nto spatially “register”\ntwo CT image of the\nlungs.","","",""],["Lung Cancer\nScreening","Fully automatic\nlung/lobe segmentation\nusing deep-learning\nalgorithms","-","-","same","",""],["","Automatic calculation of\nmeasurements for each\nsegmented nodule\n Size of the Major axis\nand Minor axis(mm)\n Diameter of Major\n(3D), 2nd Major\n(3D), Major(2D),\nMinor(2D) (mm)\n Volume(mm³)\n Max, Min, Mean HU\nof the nodule((HU)\nCancer probability (%)","-","-","same","",""],["","Comparison and\nmatching automatic\ncalculations between\neach follow-up scan and\nthe baseline scan\n Doubling time in\ndays\n Indicated the change\nof the size\nAuto generate Lung-\nRADS","-","-","Same","",""],["","Loading multiple studies","-","-","Same","",""],["","Workflow\n Detect and Segment\n Comparison and\nMatching\n Results\nOption to integrate with\n3rd party CAD which\nautomatically detects the\nnodules and generate\nreport","-","-","Same","",""],["","Supporting Low-dose\nCT","-","-","Same","",""],["","Reporting results\nThe results include the\nfollowing;\n Lung-RADS\n PANCAN risk\ncalculator\n Auto detect nodule\nlocation by lobe","-","-","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200750-p4-t0","doc_id":"K200750","page_num":4,"bbox":[72.24,167.16,508.5,349.62],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor:","TereRecon, Inc."],"rows":[["510(k) Sponsor:","TereRecon, Inc."],["Address:","4309 Emperor Blvd., Suite 310\nDurham, NC 27703, USA"],["Contact Person:","Patrick Willhite\nDirector of Quality Assurance and Regulatory Affairs"],["Contact Information:","Email: pwillhite@terarecon.com\nPhone: 919.670.1539\nFacsimile: 650.372.1101"],["Date Summary Prepared:","10/30/2020"]],"caption_candidate":"1. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200750-p4-t1","doc_id":"K200750","page_num":4,"bbox":[72.24,397.74,508.5,483.42],"n_rows":4,"n_cols":2,"columns":["Proprietary (Trade) Name:","Neuro.AI Algorithm (“Neuro.AI”)"],"rows":[["Proprietary (Trade) Name:","Neuro.AI Algorithm (“Neuro.AI”)"],["Common Name:","Medical Imaging System"],["Classification:","§ 892.2050, Picture Archiving and Communication\nSystem."],["Product Codes:","LLZ – System, Image Processing, Radiological"]],"caption_candidate":"2. DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200750-p7-t0","doc_id":"K200750","page_num":7,"bbox":[72.44,95.6,562.42,704.04],"n_rows":15,"n_cols":4,"columns":["","","Predicate Device","Reference Device"],"rows":[["","","Predicate Device","Reference Device"],["","Subject Device","",""],["","","iNtuition-TDA, TVA,","iNtuition system"],["","Neuro.AI Algorithm","",""],["","","Parametric Mapping","(K121916)"],["","(TBD)","",""],["","","(K131447)",""],["","","",""],["Areas of Use","Same and other trained\nclinical users","Radiology","Radiology"],["Modality Type","Same","Vendor-neutral - CT, MR and\nother volumetric imaging\nmodalities. Images are\nexposed over time.","Vendor-neutral - CT, MR,\nNuc, PET, Angio, US/Echo,\nSPECT, CR/DR Review"],["DICOM®\nformats","Same and DICOM 3.x","Yes, supports DICOM 3.0","Yes, supports DICOM 3.0"],["Operating\nSystem","Same and\nCentOS (Interoperability)","Microsoft\nWindows® executable on\noff-the-shelf hardware","Microsoft\nWindows® executable on\noff-the-shelf hardware"],["Body Part","Same","Head – entire brain or from\nlower edge of the base of\nnucleus to upper edge of the\nventricles.","Head and other regions and\norgans within the body"],["Key\nFunctionality/\nFeatures"," 2D, 3D and 4D viewing,\nmulti-phase series\nsupport, zoom, pan,\nwindow level, rotate, cine\nand display layouts and\ntemplates\n ROI Markers: Ability to\ncreate preset shapes or\nfreehand ROI for\nmeasurements or\nsegmentations\n Arterial and venous input\nfunction selection,\nautomatic and manual\n Ventricle segmentation"," 2D, 3D and 4D viewing,\nmulti-phase series\nsupport, zoom, pan,\nwindow level, rotate, cine\nand display layouts and\ntemplates\n ROI Markers: Ability to\ncreate preset shapes or\nfreehand ROI for\nmeasurements or\nsegmentations\n Arterial and venous input\nfunction selection,\nautomatic and manual"," 2D, 3D and 4D viewing,\nmulti-phase series\nsupport, zoom, pan,\nwindow level, rotate, cine\nand display layouts and\ntemplates\n ROI Markers: Ability to\ncreate preset shapes or\nfreehand ROI for\nmeasurements or\nsegmentations\n Arterial and venous input\nfunction selection,\nautomatic and manual\n Ventricle segmentation"],["Ventricle\nSegmentation","Setting allows software to\ndisplay maps with or\nwithout brain ventricles\nincluded","This device is a module of\niNtuition. When used with\niNtuition, the segmentation\ntools can be applied to any\npart of the body, including\nbrain ventricles.","Editing and segmentation\ntools are provided\nincluding freehand crop,\ncut, dynamic region grow,\nbone removal tools, rib\ncage removal, table\nremoval tools, and tools to\nprovide an initial selection\nof bone or air-filled vessels\n(e.g. lung or colon) for\nremoval or improvement.\nAny segmentation can be\ndisplayed or hidden and\nthis is applicable for any"]],"caption_candidate":"TABLE 1: TECHNOLOGICAL CHARACTERISTICS COMPARISON","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200750-p8-t0","doc_id":"K200750","page_num":8,"bbox":[72.44,72.62,562.42,699.9],"n_rows":15,"n_cols":4,"columns":["","","Predicate Device","Reference Device"],"rows":[["","","Predicate Device","Reference Device"],["","Subject Device","",""],["","","iNtuition-TDA, TVA,","iNtuition system"],["","Neuro.AI Algorithm","",""],["","","Parametric Mapping","(K121916)"],["","(TBD)","",""],["","","(K131447)",""],["","","",""],["","","","part of the body, including\nbrain ventricles."],["Perfusion\nmeasurements\nand color maps"," Same"," Time to Peak (TTP)\n Take off Time (TOT or\nMaximum Slope of\nIncrease)\n Recirculation Time (RT)\n Mean Transit Time (MTT)\n Blood Volume (BV/CBV)\n Blood Flow (BF/CBF)\n Perfusion Maps"," Time to Peak (TTP)\n Take off Time (TOT or\nMaximum Slope of\nIncrease)\n Recirculation Time (RT)\n Mean Transit Time\n(MTT)\n Blood Volume (BV/CBV)\n Blood Flow (BF/CBF)\n Perfusion Maps"],["Graph Displays","Same","Artery and Vein Fitted and\nRaw curves –time/activity","Artery and Vein Fitted and\nRaw curves –time/activity"],["Export Format","S ame","DICOM format","DICOM format plus JPEG,\nBMP, AVI, Word"],["Methods for\nMathematical\nModeling","Same","SVD","SVD"],["Arterial and\nVenous Input\nFunction\nSelection","Same","Automatic and manual","Automatic and manual"],["Interoperability/\nCompatibility"," CT and MR Scanners\n Third-party hospital\nsystems such as a PACS\nserver, EMR or other\n iNtuition Advanced\nVisualization system\n Algorithm dockerization\nusing DockerTM hosted in\nTeraRecon’s EnvoyAI platf\norm and viewed by"," CT and MR Scanners\n Third-party hospital\nsystems such as PACS\nserver, EMR or other\n iNtuition advanced\nvisualization system"," CT and MR Scanners\nplus other imaging\nmodalities\n Third-party hospital\nsystems such as PACS\nserver, EMR or other"]],"caption_candidate":"K200750","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200750-p9-t0","doc_id":"K200750","page_num":9,"bbox":[72.49,72.62,562.29,225.72],"n_rows":9,"n_cols":4,"columns":["","","Predicate Device","Reference Device"],"rows":[["","","Predicate Device","Reference Device"],["","Subject Device","",""],["","","iNtuition-TDA, TVA,","iNtuition system"],["","Neuro.AI Algorithm","",""],["","","Parametric Mapping","(K121916)"],["","(TBD)","",""],["","","(K131447)",""],["","","",""],["","Northstar AI Results\nExplorer\n Other image viewing\nsystems that can support\nDICOM results generated\nby the Neuro.AI Algorithm\n Notification systems","",""]],"caption_candidate":"K200750","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200760-p9-t0","doc_id":"K200760","page_num":9,"bbox":[76.64,101.78,522.13,745.9],"n_rows":3,"n_cols":9,"columns":["","Substantial Equivalence Table","","","","","","",""],"rows":[["","Substantial Equivalence Table","","","","","","",""],["","Comparison Feature","","","QuantX (DEN170022)","","","Rapid ASPECTS",""],["Indications for Use","","","QuantX is a computer-aided\ndiagnosis (CADx) software\ndevice used to assist radiologists\nin the assessment and\ncharacterization of breast\nabnormalities using MR image\ndata. The software automatically\nregisters images and segments\nand analyzes user-selected\nregions of interest (ROI). QuantX\nextracts image data from the ROI\nto provide volumetric analysis\nand computer analytics based on\nmorphological and enhancement\ncharacteristics. These imaging (or\nradiomic) features are then\nsynthesized by an artificial\nintelligence algorithm into a\nsingle\nvalue, the QI score, which is\nanalyzed relative to a database of\nreference abnormalities with\nknown ground truth.\nQuantX is indicated for\nevaluation of patients presenting\nfor high-risk screening, diagnostic\nimaging workup, or evaluation of\nextent of known disease. Extent\nof known disease refers to both\nthe assessment of the boundary of\na particular abnormality as well as\nthe assessment of the total disease\nburden in a particular patient. In\ncases where multiple\nabnormalities are present, QuantX\ncan be used to assess each\nabnormality independently.\nThis device provides information\nthat may be useful in the\ncharacterization of breast\nabnormalities during image\ninterpretation. For the QI score\nand component radiomic features,\nthe QuantX device provides\ncomparative analysis to lesions","","","Rapid ASPECTS is a computer-\naided diagnosis (CADx) software\ndevice used to assist the clinician in\nthe assessment and characterization\nof brain tissue abnormalities using\nCT image data. The Software\nautomatically registers images and\nsegments and analyzes ASPECTS\nRegions of Interest (ROIs). Rapid\nASPECTS extracts image data for\nthe ROI(s) to provide analysis and\ncomputer analytics based on\nmorphological characteristics. The\nimaging features are then\nsynthesized by an artificial\nintelligence algorithm into a single\nASPECT (Alberta Stroke Program\nEarly CT) Score.\nRapid ASPECTS is indicated for\nevaluation of patients presenting for\ndiagnostic imaging workup, or\nevaluation of extent of disease.\nExtent of disease refers to the\nnumber of ASPECTS regions\naffected which is reflected in the\ntotal score.\nThis device provides information\nthat may be useful in the\ncharacterization of early ischemic\nbrain tissue injury during image\ninterpretation. Rapid ASPECTS\nprovides a comparative analysis to\nthe ASPECTS standard of care\nradiologist assessment using the\nASPECTS atlas definitions and\natlas display including highlighted\nROIs and numerical scoring.\nLimitations:\n1.Rapid ASPECTS is not intended\nfor primary interpretation of CT\nimages. It is used to assist physician\nevaluation.\n2.Rapid ASPECTS has been\nvalidated in patients with known\nMCA or ICA occlusion prior to\nASPECT scoring.","",""]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200760-p10-t0","doc_id":"K200760","page_num":10,"bbox":[76.6,75.98,522.17,637.87],"n_rows":11,"n_cols":9,"columns":["","Substantial Equivalence Table","","","","","","",""],"rows":[["","Substantial Equivalence Table","","","","","","",""],["","Comparison Feature","","","QuantX (DEN170022)","","","Rapid ASPECTS",""],["","","","with known outcomes using an\nimage atlas and histogram display\nformat.\nQuantX may also be used as an\nimage viewer of multi-modality\ndigital images, including\nultrasound and mammography.\nThe software also includes tools\nthat allow users to measure and\ndocument images, and output in a\nstructured report.\nLimitations: QuantX is not\nintended for primary\ninterpretation of digital\nmammography images.","","","3. Use of the Rapid ASPECTS\nModule in clinical settings other than\nearly brain ischemia (within 6 hours)\ncaused by known ICA or MCA\nocclusions has not been tested.\n4. Rapid ASPECTS has been\nvalidated and is intended to be used\non GE Lightspeed VCT Scanners.\nContraindications/Exclusions/Cautio\nns:\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate.\n• Hemorrhagic Transformation,\nHematoma\n• Very thin or no Ventricles","",""],["Clinical\nApplication/Anatomi\ncal Region","","","Cancer Lesion Detection/Breast","","","Stroke/Head","",""],["Standard of Care\nRepresentation","","","QI Scoring","","","ASPECT Scoring","",""],["Primary Imaging\nModalities","","","MR","","","CT","",""],["Technical\nImplementation","","","ML/AI/Neural Network","","","ML/AI/Random Forest","",""],["Image Overlay","","","ROI box","","","ASPECTS Atlas ROIs, highlighted\nby algorithms.","",""],["Primary User(s)","","","Radiologist","","","Neuroradiologist/Clinician","",""],["Alteration of original\nimage data base","","","No","","","No","",""],["Alters Standard of\nCare Workflow","","","In parallel to","","","In parallel to","",""]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200760-p11-t0","doc_id":"K200760","page_num":11,"bbox":[95.56,101.78,539.94,744.7],"n_rows":8,"n_cols":4,"columns":["","Risk Benefit Summary","",""],"rows":[["","Risk Benefit Summary","",""],["Summary of Benefits:","","This device provides a systematic, automated analysis of\nNCCT scans of the head to provide a standardized, automated\nASPECT score for Stroke workup. The clinical reader study,\nwhich included 2 expert neuroradiologists and 6 non-expert\ntypical readers demonstrated a statistically significant\nimprovement in the accuracy of the 8 readers’ scores when\nscoring was performed in conjunction with the Rapid\nASPECTS output. In a subgroup analysis, the benefit of the\nsoftware was most substantial among the non-neuroradiologist\nreaders which typically evaluate CT scans in community\nhospitals and primary stroke centers. These non-expert\nreaders also evaluate CT scans in comprehensive centers,\nparticularly in the acute setting, when expert neuroradiologists\nare not immediately available. The software allows the non-\nexpert physician to perform at the expert-like level. Use of the\nsystem did not appear to have any significant impact (either\npositive or negative) on the scores of the 2 expert\nneuroradiologists who were included in the test reader group.\nOverall this system should provide a more consistent and\ntimely benefit of standardized reads regardless of physician\nand center specialty.",""],["Summary of the Risks","","There are minimal potential risks associated with the use of\nthe device.",""],["","","Incorrect scoring which may result in false positive\nresults and result to incorrect patient management with\npossible adverse effects such as, unnecessary additional\nmedical imaging and/or unnecessary additional\ndiagnostic workup.",""],["","","Incorrect scoring which may result in false negative\nresults may lead to complications, including incorrect\ndiagnosis and delay in disease management.",""],["","","The device could be misused to analyze images from an\nunintended patient population or on images acquired\nwith incompatible imaging hardware or incompatible\nimage acquisition parameters, leading to inappropriate\ndiagnostic information being displayed to the user.",""],["","","Device failure could lead to the absence of results, delay of\nresults or incorrect results, which could likewise lead to\ninaccurate patient assessment.",""],["","","However, based on the performance data and the\napplication of mitigating measures (general controls and\nspecial controls established for this device type), use of",""]],"caption_candidate":"Risk Benefit Analysis:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200760-p12-t0","doc_id":"K200760","page_num":12,"bbox":[95.57,75.98,539.92,723.58],"n_rows":4,"n_cols":4,"columns":["","Risk Benefit Summary","",""],"rows":[["","Risk Benefit Summary","",""],["","","the device is unlikely to decrease diagnostic\nperformance of the user and possible misuse of the\ndevice does not present additional risks compared with\nmisuse of other types of radiological image processing\ndevices.",""],["Summary of other\nFactors","","The study was enriched to cover the range of ASPECT scores;\nand, the readers in practice may not experience a significant\nimprovement in determining ASPECTS.",""],["Conclusions: Do the\nprobable benefits\noutweigh the probable\nrisks.","","Yes. The probable benefits outweigh the probable risks, given\nthe combination of required general controls and the special\ncontrols established for this device. The Special Controls\nwill sufficiently assist in managing risks associated with\nincorrect brain tissue characterization determining\nASPECT scoring, application of the device results to the\nwrong patient population, analysis of incompatible images,\nand/or device failure by ensuring proper performance and\nuse of the device\nBy providing a systematic, automated analysis of NCCT scans\nof the head to provide a standardized, automated ASPECT\nscore for Stroke workup. The Rapid ASPECTS analytics\ncalculates morphological characteristics of brain tissue using\nthe historical training data and providing results which the\nattending physician may evaluate and modify based on other\npresenting conditions of the patient. In addition to the Rapid\nASPECTS clinical module, other clinical information is easily\naccessible within the Rapid System framework such as CTA\nand CTP to inform the clinical decision-making process.\nThe clinical reader study demonstrates a statistically\nsignificant improvement of ASPECTS reads among a diverse\nsample of 8 typical readers representing multiple specialties,\nyears of practice, and practice settings.\nBy using a gating condition of LVO determination to guide\nASPECTS use, many of the risks of stroke mimics\nconfounding the scoring will be averted.\nOverall this system should provide a more consistent and\ntimely benefit of standardized reads regardless of physician\nand center specialty. Therefore, given the available\ninformation concerning the benefits, risks, and supporting\ndata; the probable benefits outweigh the probable risks,\ngiven the combination of required general controls and\nspecial controls established for this device.",""]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p8-t0","doc_id":"K200855","page_num":8,"bbox":[66.6,98.16,534.12,388.44],"n_rows":11,"n_cols":5,"columns":["Prevalence","CINA - ICH triage application","","CINA - LVO triage application",""],"rows":[["Prevalence","CINA - ICH triage application","","CINA - LVO triage application",""],["","PPV (%)","NPV (%)","PPV (%)","NPV (%)"],["10%","80.2","99.0","81.7","99.8"],["15%","86.6","98.5","87.7","99.6"],["20%","90.1","97.8","91.0","99.5"],["25%","92.4","97.1","93.1","99.3"],["30%","94.0","96.3","94.5","99.1"],["35%","95.2","95.5","95.6","98.8"],["40%","96.1","94.4","96.4","98.6"],["45%","96.8","93.2","97.1","98.2"],["50%","97.3","91.9","97.6","97.9"]],"caption_candidate":"Table 1: PPV and NVP values for ICH and LVO image processing applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p8-t1","doc_id":"K200855","page_num":8,"bbox":[66.6,496.56,534.12,601.68],"n_rows":3,"n_cols":5,"columns":["Time-to-Notification","MEAN ± SD\n(seconds)","MEDIAN\n(seconds)","MIN\n(seconds)","MAX\n(seconds)"],"rows":[["Time-to-Notification","MEAN ± SD\n(seconds)","MEDIAN\n(seconds)","MIN\n(seconds)","MAX\n(seconds)"],["CINA - ICH","21.6 ± 4.4","20.4","14.4","53.3"],["CINA - LVO","34.7 ± 10.7","33.4","14.3","63.3"]],"caption_candidate":"Table 2: Time-to-notification for ICH and LVO image processing applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p10-t0","doc_id":"K200855","page_num":10,"bbox":[66.6,149.88,725.4,535.92],"n_rows":2,"n_cols":4,"columns":["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],"rows":[["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],["Intended Use /\nIndications for Use","CINA is a radiological computer\naided triage and notification\nsoftware indicated for use in the\nanalysis of (1) non-enhanced head\nCT images and (2) CT\nangiographies of the head.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communicating\nsuspected positive findings of (1)\nhead CT images for Intracranial\nHemorrhage (ICH) and (2) CT\nangiographies of the head for large\nvessel occlusion (LVO).\nCINA uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected (1)\nICH or (2) LVO on a standalone\nWeb application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nnon-enhanced head CT images.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive findings of\npathologies in head CT images,\nnamely Intracranial Hemorrhage\n(ICH).\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected ICH findings.\nNotifications include compressed","ContaCT is a notification-only,\nparallel workflow tool for use by\nhospital networks and trained\nclinicians to identify and\ncommunicate images of specific\npatients to a specialist, independent\nof standard of care workflow.\nContaCT uses an artificial intelligence\nalgorithm to analyze images for\nfindings suggestive of a pre-specified\nclinical condition and to notify an\nappropriate medical specialist of\nthese findings in parallel to standard\nof care image interpretation.\nIdentification of suspected findings is\nnot for diagnostic use beyond\nnotification. Specifically, the device\nanalyzes CT angiogram images of\nthe brain acquired in the acute setting\nand sends notifications to a\nneurovascular specialist that a\nsuspected large vessel occlusion has\nbeen identified and recommends\nreview of those images. Images can"]],"caption_candidate":"Table 3: Comparison of key features between CINA and predicate device (Aidoc BriefCase) and reference device (Viz.AI ContaCT)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p11-t0","doc_id":"K200855","page_num":11,"bbox":[66.6,72.24,725.4,531.72],"n_rows":5,"n_cols":4,"columns":["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],"rows":[["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],["","suspected ICH or LVO findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only, and are\nnot intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image,\nand it is not intended to be used as\na diagnostic device.\nThe results of CINA are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nultimately responsible for reviewing\nfull images per the standard of care.","preview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","be previewed through a mobile\napplication.\nImages that are previewed through\nthe mobile application are\ncompressed and are for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nNotified clinicians are responsible for\nviewing non-compressed images on\na diagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making care-related\ndecisions or requests. ContaCT is\nlimited to analysis of imaging data\nand should not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis."],["User population","Radiologist","Radiologist","Clinician (e.g., neurovascular\nspecialist)"],["Anatomical region\nof interest","Head","Head","Head"],["Data acquisition\nprotocol","Non contrast CT scan of the head or\nneck and CT angiogram images of","Non contrast CT scan of the head or\nneck","CT angiogram images of the brain"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p12-t0","doc_id":"K200855","page_num":12,"bbox":[66.6,72.24,725.4,528.6],"n_rows":10,"n_cols":4,"columns":["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],"rows":[["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],["","the brain","",""],["View DICOM data","DICOM information about the\npatient, study and current image","DICOM information about the patient,\nstudy and current image","DICOM information about the patient,\nstudy and current image"],["Segmentation of\nregion of interest","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm"],["Notification /\nPrioritization","Yes","Yes","Yes"],["Preview images","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a preview of the study\nfor initial assessment not meant for\ndiagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a small, compressed,\nblack and white preview image that is\nlabeled “Not for diagnostic use”."],["Alteration of original\nimage","No","No","No"],["Removal of cases\nfrom worklist queue","No","No","No"],["Structure","- LVO and ICH image processing","- AHS module (image acquisition),","- Image Forwarding Software"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200855-p13-t0","doc_id":"K200855","page_num":13,"bbox":[66.6,72.24,725.4,192.6],"n_rows":2,"n_cols":4,"columns":["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],"rows":[["","Subject device: CINA Software","Predicate device: Aidoc BriefCase\nSoftware (K180647)","Reference device: Viz.AI ContaCT\nsoftware (DEN170073)"],["","applications\n- CINA Platform (worklist and Image\nViewer)","- ACS module (image processing),\n- Aidoc Worklist application for\nworkflow integration (worklist and\nImage Viewer).","- Image Processing and Analysis\nSoftware\n- Non-diagnostic DICOM viewing\nmobile application"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200873-p4-t0","doc_id":"K200873","page_num":4,"bbox":[74.78,157.15,367.9,607.39],"n_rows":41,"n_cols":3,"columns":["Date Prepared:","March 27, 2020",""],"rows":[["Date Prepared:","March 27, 2020",""],["","",""],["Manufacturer:","NICo-Lab B.V.",""],["","Paasheuvelweg 25, 1105BP",", Amsterda"],["","The Netherlands",""],["","",""],["Contact Person:","Merel Boers",""],["","CEO",""],["","Phone: +31202440852",""],["","E-mail: mboers@nico-lab.c","om"],["","",""],["Device:","Trade Name:","HALO"],["","",""],["","Classification Name:","Radiological"],["","","Notification"],["","",""],["","Classification","21 CFR 892."],["","Regulation:",""],["","",""],["","Classification Panel:","Radiology"],["","",""],["","Device Class:","Class II"],["","",""],["","Primary Product Code:","QAS"],["","",""],["Primary Predicate","Trade Name:","ContaCT"],["Device:","Manufacturer:","Viz.Al, Inc."],["","",""],["","DeNovo Clearance:","DEN170073"],["","",""],["","Classification Name:","Radiological"],["","","Notification"],["","",""],["","Classification","21 CFR 892."],["","Regulation:",""],["","",""],["","Classification Panel:","Radiology"],["","",""],["","Device Class:","Class II"],["","",""],["","Product Code:","QAS"]],"caption_candidate":"Date Prepared: March 27, 2020","well_formed":true,"extraction_settings":"text"}
{"table_id":"K200873-p6-t0","doc_id":"K200873","page_num":6,"bbox":[182.88,187.44,542.64,646.08],"n_rows":9,"n_cols":3,"columns":["","Predicate: ContaCT","Subject: HALO"],"rows":[["","Predicate: ContaCT","Subject: HALO"],["Clinical condition","Large vessel\nocclusion","Large vessel\nocclusion"],["Anatomical region of\ninterest","Head","Head"],["Data acquisition\nprotocol","CT angiogram images\nof the brain","CT angiogram images\nof the brain"],["Segmentation of\nregion of interest","No; device does not\nmark, highlight, or\ndirect users’ attention\nto a specific location\nin the original image.","No; device does not\nmark, highlight, or\ndirect users’ attention\nto a specific location\nin the original image."],["Core Algorithm","Artificial intelligence\nalgorithm with\ndatabase of images","Artificial intelligence\nalgorithm with\ndatabase of images"],["Device Output/\nNotification","The software sends a\nnotification to the\nspecialist identifying\nthe study of interest.\nAdditionally, the\ndevice also provides a\nDICOM viewing\nmobile application\nallow users preview\nthe images.","The software sends a\nnotification email to\nthe specialist\nidentifying the study\nof interest.\nAdditionally, the\ndevice provides user\nwith a link to DICOM\nWeb viewer allowing\nusers review the\nimages."],["Triage effectiveness","Notification time is\ndefined as the time\nfrom CTA to\nnotification.","Notification time is\ndefined as the time\nfrom CTA to\nnotification."],["Independent of\nstandard of care\nworkflow","No cases are removed\nfrom worklist","No cases are removed\nfrom worklist"]],"caption_candidate":"currently marketed and predicate device ContaCT are summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200905-p4-t0","doc_id":"K200905","page_num":4,"bbox":[72.57,546.98,531.18,633.14],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","CmTriage"],"rows":[["Proprietary Name","CmTriage"],["Premarket Notification","K183285"],["Classification Name","Radiological Computer-Assisted Prioritization Software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QFM"],["Regulatory Class","II"]],"caption_candidate":"The HealthMammo device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200905-p7-t0","doc_id":"K200905","page_num":7,"bbox":[72.78,72.31,554.23,719.2],"n_rows":13,"n_cols":4,"columns":["","make or confirm diagnosis. The\nHealthMammo device is\nintended for use with complete\n2D FFDM mammography\nexams acquired using validated\nFFDM systems only.","diagnosis. cmTriage is for\nprescription use only.",""],"rows":[["","make or confirm diagnosis. The\nHealthMammo device is\nintended for use with complete\n2D FFDM mammography\nexams acquired using validated\nFFDM systems only.","diagnosis. cmTriage is for\nprescription use only.",""],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Interpreting physician","Radiologist","Same"],["Identify patients with\nprespecified\nclinical condition","Yes","Yes","Same"],["Alert to finding","Yes; passive notification\nflagged for review","Yes; passive notification flagged\nfor review","Same"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed from\nworklist","Yes; No cases are removed from\nworklist","Same"],["Modality","FFDM screening mammograms","FFDM screening mammograms","Same"],["FFDM manufacturer","Hologic","Vendor agnostic","Different, the\nsubject device\nprocesses 2D\nFFDM scans\nacquired by\nHologic systems,\nwhile the predicate\ndevice may receive\nscans acquired from\nalternative vendors."],["Body part","Breast","Breast","Same"],["Artificial Intelligence\nalgorithm","Yes","Yes","Same"],["Limited to analysis of\nimaging data","Yes","Yes","Same"],["Inclusion Criteria","- 2D FFDM screening\nmammograms\n- Biopsy proven cancer studies\n(soft tissues and micro-\ncalcifications)\n- BIRADS 1 and 2 normal\ncases with 2 year follow-up\nStudies with 4 standard views\n(LCC, LMLO, RCC, RMLO)","- 2D FFDM screening\nmammograms\n- Biopsy proven cancer studies\n(soft tissues and micro-\ncalcifications)\n- BIRADS 1 and 2 normal cases\nwith 2 year follow-up\nStudies with 4 standard views\n(LCC, LMLO, RCC, RMLO)","Same"],["Exclusion Criteria","- Studies that do not include all\n4 views","- Studies that do not include all 4\nviews","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200905-p8-t0","doc_id":"K200905","page_num":8,"bbox":[72.77,72.31,554.23,396.84],"n_rows":5,"n_cols":4,"columns":["","- Digital Breast tomosynthesis\nstudies\n- 3D studies\nStudies that do not comply with\nthe inclusion criteria","- Digital Breast tomosynthesis\nstudies\n- 3D studies\nStudies that do not comply with\nthe inclusion criteria",""],"rows":[["","- Digital Breast tomosynthesis\nstudies\n- 3D studies\nStudies that do not comply with\nthe inclusion criteria","- Digital Breast tomosynthesis\nstudies\n- 3D studies\nStudies that do not comply with\nthe inclusion criteria",""],["Aids prompt\nidentification of\ncases with indicated\nfindings","Yes","Yes","Same"],["Multiple operating\npoints","Yes; 3 optional operating points","No; single operating point","Different,\nHealthMammo\nprovides an\nadditional 2\noperating points.\nPerformance\ncomplies with DEN\n170073 Special\ncontrol 1(iii)."],["Preview Images","Presentation of notification and\npreview of the study for initial\nassessment not meant for\ndiagnostic purposes. The device\noperates in parallel with the\nstandard of care, which remains\nthe default option for all cases.","Presentation of notification and\npreview of the study for initial\nassessment not meant for\ndiagnostic purposes. The device\noperates in parallel with the\nstandard of care, which remains\nthe default option for all cases.","Same"],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200921-p8-t0","doc_id":"K200921","page_num":8,"bbox":[66.65,95.18,580.49,709.92],"n_rows":6,"n_cols":9,"columns":["","Parameter","","","qER Device","","","Aidoc Briefcase Software",""],"rows":[["","Parameter","","","qER Device","","","Aidoc Briefcase Software",""],["","","","","Subject Device","","","(K180647)",""],["","","","","","","","",""],["Indications\nFor Use","","","qER is a radiological computer aided triage and\nnotification software indicated for use in the\nanalysis of non-contrast head CT images.\nThe device is intended to assist hospital networks\nand trained medical specialists in workflow triage\nby flagging the following suspected positive\nfindings of pathologies in head CT images:\nintracranial hemorrhage, mass effect, midline shift\nand cranial fracture.\nqER uses an artificial intelligence algorithm to\nanalyze images on a standalone cloud-based\napplication in parallel to the ongoing standard of\ncare image interpretation. The user is presented\nwith notifications for cases with suspected\nfindings. Notifications include non-diagnostic\npreview images that are meant for informational\npurposes only. The device does not alter the\noriginal medical image and is not intended to be\nused as a diagnostic device.\nThe results of the device are intended to be used\nin conjunction with other patient information and\nbased on professional judgment, to assist with\ntriage/prioritization of medical images. Notified\nclinicians are responsible for viewing full images\nper the standard of care.","","","BriefCase is a radiological computer aided triage\nand notification software indicated for use in the\nanalysis of non-enhanced head CT images.\nThe device is intended to assist hospital\nnetworks and trained radiologists in workflow\ntriage by flagging and communication of\nsuspected positive findings of pathologies in\nhead CT images, namely Intracranial\nHemorrhage (ICH).\nBriefCase uses an artificial intelligence algorithm\nto analyze images and highlight cases with\ndetected ICH on a standalone desktop\napplication in parallel to the ongoing standard of\ncare image interpretation. The user is presented\nwith notifications for cases with suspected ICH\nfindings. Notifications include compressed\npreview images that are meant for informational\npurposes only and not intended for diagnostic\nuse beyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be used\nin conjunction with other patient information\nand based on professional judgment, to assist\nwith triage/prioritization of medical images.\nNotified clinicians are responsible for viewing full\nimages per the standard of care.","",""],["Classification\n/\nProduct Code","","","21 CFR 892.2080/QAS","","","21 CFR 892.2080/QAS","",""],["Device\nComponents","","","1. An on-premise module that:\na. Performs de-identification of studies and pushes\nthem to the cloud module.\nb. Receives results after processing on the cloud\nmodule.\nc. Re-identifies the studies and sends them to the\nradiology PACS and radiology worklist.\n2. A cloud module that performs the analysis using\na pre-trained artificial intelligence algorithm.","","","1. An on-premise module that:\na. Performs de-identification of studies and\npushes them to the cloud module.\nb. Receives results after processing on the cloud\nmodule.\nc. Re-identifies the studies and sends them to\nthe radiology PACS and radiology worklist.\n2. A cloud module that performs the analysis\nusing a pre-trained artificial intelligence","",""]],"caption_candidate":"Table 1. Comparison of Technical Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200921-p9-t0","doc_id":"K200921","page_num":9,"bbox":[66.62,72.38,580.54,663.84],"n_rows":16,"n_cols":9,"columns":["","Parameter","","","qER Device","","","Aidoc Briefcase Software",""],"rows":[["","Parameter","","","qER Device","","","Aidoc Briefcase Software",""],["","","","","Subject Device","","","(K180647)",""],["","","","","","","","",""],["","","","","","","algorithm.","",""],["Anatomical\nregion of\ninterest","","","Head","","","Head","",""],["Data\nacquisition\nprotocol","","","Non contrast CT scan of the head","","","Non contrast CT scan of the head or neck","",""],["View DICOM\ndata","","","DICOM Information about the patient, study and\ncurrent image","","","DICOM Information about the patient, study and\ncurrent image","",""],["Segmentatio\nn of region of\ninterest","","","No; device does not mark, highlight, or direct\nusers’ attention to a specific location in the original\nimage.","","","No; device does not mark, highlight, or direct\nusers’ attention to a specific location in the\noriginal image.","",""],["Algorithm","","","Artificial intelligence algorithm with database of\nimages.","","","Artificial intelligence algorithm with database of\nimages.","",""],["Notification/\nPrioritization","","","Yes, with controls for the user to select the finding\nor combination of findings for triage","","","Yes","",""],["Preview\nimages","","","Presentation of a preview of the study for initial\nassessment not meant for diagnostic purposes.\nThe device operates in parallel with the standard\nof care, which remains the default option for all\ncases.","","","Presentation of a preview of the study for initial\nassessment not meant for diagnostic purposes.\nThe device operates in parallel with the standard\nof care, which remains the default option for all\ncases.","",""],["Alteration of\noriginal\nimage","","","No","","","No","",""],["Removal of\ncases from\nworklist\nqueue","","","No","","","No","",""],["Abnormalitie\ns triaged","","","Four findings: Intracranial haemorrhage, Mass\neffect, midline shift, cranial fracture and ICH","","","One finding: Intracranial hemorrhage","",""],["User control\nover triage","","","Triages non-contrast CT scan when any of the 4\nabnormalities are identified\nNotification/ prioritization with user provided\ncontrol for configuring the triage finding or\ncombination of finding(s)","","","Non contrast CT scan of the head or neck\nSingle configuration","",""],["Preview\nimage\ninformation","","","Preview images returned to the PACS\nPreview images are reduced in size and their\ndynamic range is limited","","","Preview images on hover over the worklist\nPreview images are compressed and/or reduced\nin size","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200921-p10-t0","doc_id":"K200921","page_num":10,"bbox":[90.24,291.36,521.76,447.0],"n_rows":6,"n_cols":4,"columns":["Abnormality","Sensitivity (95% CI),\nTP/P","Specificity (95% CI),\nTN/N","AUC (95% CI)"],"rows":[["Abnormality","Sensitivity (95% CI),\nTP/P","Specificity (95% CI),\nTN/N","AUC (95% CI)"],["Intracranial Hemorrhage","96.98 (95.32 - 98.17),\n610/629","93.92 (91.87 - 95.58),\n649/691","98.53 (98.00 - 99.15)"],["Cranial Fracture","96.77 (93.74 - 98.60),\n240/248","92.72 (91.00 - 94.21),\n994/1072","97.66 (96.88 - 98.57)"],["Mass Effect","96.39 (94.28 - 97.88),\n454/471","96.00 (94.45 - 97.21),\n815/849","99.09 (98.73 - 99.52)"],["Midline Shift","97.34 (95.30 - 98.67),\n403/414","95.36 (93.79 - 96.64),\n864/906","99.09 (98.74 - 99.51)"],["Any of the 4 target\nabnormalities","98.53 (97.45 - 99.24),\n807/819","91.22 (88.39 - 93.55),\n457/501","NA"]],"caption_candidate":"Table 2. Primary Endpoint Results in qER Standalone Performance Study","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200921-p11-t0","doc_id":"K200921","page_num":11,"bbox":[142.8,107.88,469.2,210.84],"n_rows":3,"n_cols":3,"columns":["Parameter","Mean (95% CI) in\nminutes","Median (95% CI) in\nminutes"],"rows":[["Parameter","Mean (95% CI) in\nminutes","Median (95% CI) in\nminutes"],["Time to open exam in\nthe standard of care","65.54 (59.14 -\n71.76)","60.01 (54.57 - 77.63)"],["Time-to-notification\nwith qER","2.11 (1.45 - 2.61)","1.21 (1.12 - 1.25)"]],"caption_candidate":"Containing One of the Target Abnormalities","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p4-t0","doc_id":"K200974","page_num":4,"bbox":[72.84,36.34,545.4,78.0],"n_rows":3,"n_cols":5,"columns":["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 1 of 8"],"rows":[["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 1 of 8"],["","","QLAB Advanced Quantification Software","",""],["","","System Modifications","",""]],"caption_candidate":"K200974","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p5-t0","doc_id":"K200974","page_num":5,"bbox":[72.3,36.34,545.4,78.0],"n_rows":3,"n_cols":5,"columns":["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 2 of 8"],"rows":[["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 2 of 8"],["","","QLAB Advanced Quantification Software","",""],["","","System Modifications","",""]],"caption_candidate":"K200974","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p5-t1","doc_id":"K200974","page_num":5,"bbox":[66.41,561.06,534.31,591.24],"n_rows":2,"n_cols":9,"columns":["","Classification Description","","","21 CFR Section","","","Product CCode",""],"rows":[["","Classification Description","","","21 CFR Section","","","Product CCode",""],["Automated Radiological Image Processing Software","","","892.2050","","","QIH","",""]],"caption_candidate":"Regulation Description:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p6-t0","doc_id":"K200974","page_num":6,"bbox":[72.84,36.34,545.4,78.0],"n_rows":3,"n_cols":5,"columns":["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 3 of 8"],"rows":[["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 3 of 8"],["","","QLAB Advanced Quantification Software","",""],["","","System Modifications","",""]],"caption_candidate":"K200974","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p7-t0","doc_id":"K200974","page_num":7,"bbox":[104.16,8.17,515.04,782.99],"n_rows":7,"n_cols":14,"columns":["","","","secnereffiD\nfo\nnoitanalpxEE","enoN","enoN","enoN","enoN","tcudorP neewteb yramirp\n,rebmuN\n,emaN .ecived\ndna lacitnedi dna\nnoitalugeR\nnoitalugeR ,noitacifissalC ecived etaciderp\nera\ntcejbus\nedoC","","","","fo metsyS etaciderp lacitnedi degnahc ecnaraelc spilihP anerA ni ralimis yalpsid sesoprup\nesU\n.resu\nrof ehT CETMOT\nBALQ era neeb suoiverp era egami noitacifitnauq\nsnoitacidnI yramirp dne\n.metsys\nmetsyS smetsyS\nton\ntcejbus ot eht\ndna\nevah sdrager\neht eht ot\nBALQ siht BALQ\nehT eht dna dna morf 2ATT dna\nfo","lla\nfo\nstnenopmoC metsyS sa ylno\nlacitnedi\nsecived\nerawtfos\nBALQ\netaciderp era\nmetsyS tcejbus era\ndeifitnedi\nsecived\nehT eht dna"],"rows":[["","","","secnereffiD\nfo\nnoitanalpxEE","enoN","enoN","enoN","enoN","tcudorP neewteb yramirp\n,rebmuN\n,emaN .ecived\ndna lacitnedi dna\nnoitalugeR\nnoitalugeR ,noitacifissalC ecived etaciderp\nera\ntcejbus\nedoC","","","","fo metsyS etaciderp lacitnedi degnahc ecnaraelc spilihP anerA ni ralimis yalpsid sesoprup\nesU\n.resu\nrof ehT CETMOT\nBALQ era neeb suoiverp era egami noitacifitnauq\nsnoitacidnI yramirp dne\n.metsys\nmetsyS smetsyS\nton\ntcejbus ot eht\ndna\nevah sdrager\neht eht ot\nBALQ siht BALQ\nehT eht dna dna morf 2ATT dna\nfo","lla\nfo\nstnenopmoC metsyS sa ylno\nlacitnedi\nsecived\nerawtfos\nBALQ\netaciderp era\nmetsyS tcejbus era\ndeifitnedi\nsecived\nehT eht dna"],["1\nelbaTT","dna\nmetsyS\nBALQ\nspilihP\n:secived\netaciderp\ndna\ndetekram\nyltnerruc\neht\not\nmetsyS\nBALQ\nspilihP\ndesoporp\neht\nfo\nnosirapmoCC","metsyS\n2ATT\nsmetsyS\ngnigamI\nceTmoTT","","","","","","","","","","",""],["","","","eciveD\netaciderPP\necnerefeRR","HbmG\n,smetsyS\ngnigamI\nCETMOT","2ATT\nanerA","tnemssessA-VM\nD4","221051K","0502.298\nRFC\n12","dna\n)SCAP(\n,gnissecorp gnivihcrA\nmetsyS\nerutciP\negamI\nsnoitacinummoC\n-\n,metsyS lacigoloidaR","II\nssalC","ZLL","anerA-CETMOT dna fo\not\ndna noitcnuf\n,latef esaesid eht\nnoitacifitnauq ni\n,ralucsavoidrac\nsnaicisyhp\ndna detcepsus\n.sisongaid\nfo serutcurts\nesu\nera htiw eht\nrof\nerawtfos fo troppus\nsnoitacidnI gnitroper lanimodba stneitap","metsys\nylno\nerawtfoS"],["","","","eciveD\netaciderPP",".cnI\n,dnuosartlU\nspilihP","metsyS\nBALQ","ledoMtraeH","746191K","0502.298\nRFC\n12","egamI\nerawtfoS\nlacigoloidaR\ngnissecorP\ndetamotuA","II\nssalC","HIQ","a si\nsi tI yfitnauq spilihP\nerawtfos\n.egakcap\n.smetsys\nno\ndna\nnoitacifitnauQ deriuqca\nnoitacilppa\nweiv\ndnuosartlu\not\natad\ndengised\nerawtfos\negami\nBALQ","metsys\nylno\nerawtfoS"],["","","","eciveD\ntcejbuSS",".cnI\n,dnuosartlU\nspilihP","metsyS\nBALQ","VM\notuA\nD3","gnidneP","0502.298\nRFC\n12","egamI\nerawtfoS\nlacigoloidaR\ngnissecorP\ndetamotuA","II\nssalC","HIQ","egami\na si dnuosartlu\nsi\ntI\nerawtfos\n.egakcap\nyfitnauq\nspilihP\nnoitacifitnauQ .smetsys\nnoitacilppa dna\nweiv no\nderiuqca\not\nerawtfos\ndengised\nBALQ\natad","metsys\nylno\nerawtfoS"],["","","","","rerutcafunaM","emaN\nedarT","erutaeF","rebmuN\n)k(015","rebmuN\nnoitalugeR","emaN\nnoitalugeR","noitacifissalC",")s(edoC\ntcudorP","esU\nrof\nsnoitacidnI","stnenopmoC\nmetsyS"],["","","","","","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p7-t1","doc_id":"K200974","page_num":7,"bbox":[36.34,66.6,78.0,539.16],"n_rows":5,"n_cols":3,"columns":["8\nfo\n4\negaP","",""],"rows":[["8\nfo\n4\negaP","",""],["","",""],[")k(015\nlanoitidarT","erawtfoS\nnoitacifitnauQ\ndecnavdA\nBALQ","snoitacifidoM\nmetsyS"],["","",""],[".cnI\n,dnuosartlU\nspilihP","",""]],"caption_candidate":"eraw","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p8-t0","doc_id":"K200974","page_num":8,"bbox":[36.34,66.6,78.0,539.16],"n_rows":5,"n_cols":3,"columns":["8\nfo\n5\negaP","",""],"rows":[["8\nfo\n5\negaP","",""],["","",""],[")k(015\nlanoitidarT","erawtfoS\nnoitacifitnauQ\ndecnavdA\nBALQ","snoitacifidoM\nmetsyS"],["","",""],[".cnI\n,dnuosartlU\nspilihP","",""]],"caption_candidate":",ledom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p9-t0","doc_id":"K200974","page_num":9,"bbox":[36.34,66.6,78.0,539.16],"n_rows":5,"n_cols":3,"columns":["8\nfo\n6\negaP","",""],"rows":[["8\nfo\n6\negaP","",""],["","",""],[")k(015\nlanoitidarT","erawtfoS\nnoitacifitnauQ\ndecnavdA\nBALQ","snoitacifidoM\nmetsyS"],["","",""],[".cnI\n,dnuosartlU\nspilihP","",""]],"caption_candidate":"eta","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p10-t0","doc_id":"K200974","page_num":10,"bbox":[104.04,5.16,222.36,783.0],"n_rows":6,"n_cols":2,"columns":[".noitacilppa\ntnemssessA","noitacilppa lacitnedi\nnepO na lartim rehto -VM .noitacilppa\not\nsa\nerusaem\nlatoT tnemerusaem eht llA D4\nera\netaciderp\nVM eht enifed .ymotana stnemerusaem\nlanoitidda tnemssessA\notuA\nsecudortni\nrehtruf\neht\nD3 evlav\naerA\nehT ot"],"rows":[[".noitacilppa\ntnemssessA","noitacilppa lacitnedi\nnepO na lartim rehto -VM .noitacilppa\not\nsa\nerusaem\nlatoT tnemerusaem eht llA D4\nera\netaciderp\nVM eht enifed .ymotana stnemerusaem\nlanoitidda tnemssessA\notuA\nsecudortni\nrehtruf\neht\nD3 evlav\naerA\nehT ot"],["","retemireP )mc(\nhtgneL\naerA htgneL\nsulunnA sulunnA\neniL\neniL\nerusolC\nerusolC\ndepahS depahS\nroiretsoP(cid:147)\nroiretnA(cid:147)\nelddaS(cid:147) elddaS(cid:147)\n)2mc(\n)mc( )mc("],["","sretemarap\n)VM(\nsiht\nevlav fo .noitacilppa\ntrap\nlartim noitacifitnauq sa\ndedulcni\nD3\noN"],["","retemireP )2mc( )mc(\nhtgneL\naerA htgneL\naerA\nsulunnA sulunnA\nnoitatpaoC eniL\neniL\nerusolC\nerusolC\ndepahS depahS\nnepO\nroiretsoP(cid:147)\nroiretnA(cid:147)\nelddaS(cid:147) elddaS(cid:147)\nlatoT(cid:147)\n)2mc(\n)mc( )mc("],["","sretemaraP\nVM\nD3"],["",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p10-t1","doc_id":"K200974","page_num":10,"bbox":[36.34,66.6,78.0,539.16],"n_rows":5,"n_cols":3,"columns":["8\nfo\n7\negaP","",""],"rows":[["8\nfo\n7\negaP","",""],["","",""],[")k(015\nlanoitidarT","erawtfoS\nnoitacifitnauQ\ndecnavdA\nBALQ","snoitacifidoM\nmetsyS"],["","",""],[".cnI\n,dnuosartlU\nspilihP","",""]],"caption_candidate":".noitacilppa","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200974-p11-t0","doc_id":"K200974","page_num":11,"bbox":[72.84,36.34,545.4,78.0],"n_rows":3,"n_cols":5,"columns":["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 8 of 8"],"rows":[["Philips Ultrasound, Inc.","","Traditional 510(k)","","Page 8 of 8"],["","","QLAB Advanced Quantification Software","",""],["","","System Modifications","",""]],"caption_candidate":"K200974","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200980-p4-t0","doc_id":"K200980","page_num":4,"bbox":[72.04,558.67,548.98,648.85],"n_rows":4,"n_cols":3,"columns":["Classification Name","Regulation Number","Product Code"],"rows":[["Classification Name","Regulation Number","Product Code"],["","",""],["Ultrasonic Pulsed Echo Imaging System","21 CFR 892.1560","IYO"],["Diagnostic Ultrasound Transducer","21 CFR 892.1570","ITX"]],"caption_candidate":"Classification Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200980-p6-t0","doc_id":"K200980","page_num":6,"bbox":[72.33,218.53,553.36,730.33],"n_rows":10,"n_cols":3,"columns":["Comparison Category","Butterfly Auto 3D","Predicate Verathon"],"rows":[["Comparison Category","Butterfly Auto 3D","Predicate Verathon"],["","Bladder Volume Tool","BladderScan Prime PLUS"],["","","System"],["","(This submission)","(K172356)"],["Comparison Overview","",""],["Intended Use/Indications\nFor Use","The Butterfly Auto 3D\nBladder Volume Tool is a\nsoftware application\npackage. It is designed to\nview, quantify and report\nresults acquired on Butterfly\nNetwork ultrasound\nsystems for noninvasive\nvolume measurements of\nthe bladder, to support\nphysician diagnosis.\nIndicated for use in adult\npopulations.","The BladderScan Prime\nSystem is an ultrasound\ndevice intended to be used for\nmeasuring the urine volume in\nthe bladder non- invasively."],["Contraindications","The Auto 3D Bladder\nVolume Tool is not\nintended for fetal or\npediatric use or for use on\npregnant patients, patients\nwith ascites, or patients\nwith open skin or wounds\nin the suprapubic region.","The BladderScan Prime\nSystem is not intended for fetal\nuse or for use on pregnant\npatients, patients with ascites,\nor patients with open skin or\nwounds in the suprapubic\nregion."],["Patient/User Characteristics","",""],["Target Population","Male and Female","Male, Female, and Pediatric"],["Anatomical Site","Identical to predicate","Bladder"]],"caption_candidate":"marketed predicate device are provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200980-p7-t0","doc_id":"K200980","page_num":7,"bbox":[72.28,68.41,553.43,558.25],"n_rows":20,"n_cols":3,"columns":["Users","Identical to predicate","Physicians/Medical\nProfessionals"],"rows":[["Users","Identical to predicate","Physicians/Medical\nProfessionals"],["Technological Characteristics and Performance","",""],["Technology","Identical to predicate","Neural network technology"],["Sterility","Identical to predicate","Non-sterile"],["Power Source","Identical to predicate","Battery powered"],["Energy Delivered","Identical to predicate","Ultrasound"],["Measurement Accuracy","0-100mL = ±7.5mL\n100-740 mL = ±7.5%","0-100mL = ±7.5mL\n100-999 mL = ±7.5%"],["Measurement Range","0 to 740 mL","0 to 999 mL"],["Modes of Operation","B-mode","B-mode"],["Transducer Type","Electronic Sector Scanning\n(Phased Array)","Mechanical Sector Probe"],["Sector Angle","100 degrees","120 degrees"],["Number of Scan Planes","25","12"],["Design and Usability Features","",""],["Portable","Identical to predicate","Yes"],["Display","Identical to predicate","LCD"],["Scan Button","Identical to predicate","Yes"],["Touchscreen Operation","Identical to predicate","Yes"],["Selectable Unit Orientation\n(Patient Right/Left)","No","Yes"],["Live Scan Image","Identical to predicate","Yes"],["Calibration","Identical to predicate","No calibration recommended"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200990-p4-t0","doc_id":"K200990","page_num":4,"bbox":[72.38,163.12,558.38,704.62],"n_rows":11,"n_cols":2,"columns":["Submitter:","VIDA Diagnostics, Inc.\n500 Crosspark Rd.\nW250 BioVentures Center\nCoralville, IA 52241 USA"],"rows":[["Submitter:","VIDA Diagnostics, Inc.\n500 Crosspark Rd.\nW250 BioVentures Center\nCoralville, IA 52241 USA"],["Date Prepared:","July 25, 2020"],["Contact Person:","Alex Morris, Director, Quality and Regulatory\nVIDA Diagnostics, Inc.\n2500 Crosspark Rd.\nW250 BioVentures Center\nCoralville, IA 52241 USA\nCell Phone: (647) 470.4363\nOffice Phone: (855) 900.8432\nEmail: amorris@vidalung.ai"],["Submission Date:","May 19, 2020"],["Trade Name:","VIDA|vision"],["Regulation\nDescription:","Computed tomography x-ray system"],["Common Name:","Medical Imaging Software for Computed Tomography Devices"],["Regulation:","21 CFR 892.1750"],["Product Code:","JAK"],["Regulatory Class:","Class II"],["Predicate Device:","Pulmonary Workstation 2 (PW2) by VIDA Diagnostics Inc.\nRegulation: 21 CFR 892.1750\nProduct Code: JAK\nRegulatory Class: Class II\nRegulation Description: Computed tomography x-ray system\nSubmission Number: K083227"]],"caption_candidate":"K200990","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K200990-p6-t0","doc_id":"K200990","page_num":6,"bbox":[72.38,331.88,558.38,718.12],"n_rows":8,"n_cols":4,"columns":["Manufacturer","510(k) Submitter","Predicate","Differences"],"rows":[["Manufacturer","510(k) Submitter","Predicate","Differences"],["","VIDA Diagnostics, Inc.","VIDA Diagnostics, Inc.",""],["Trade Name","VIDA|vision (formerly VIDA\nPulmonary Workstation 2\n(PW2))","VIDA Pulmonary\nWorkstation 2 (PW2)",""],["510(k) Number","K200990","K083227",""],["Product Code","JAK","JAK","n/a"],["Regulation\nNumber","21 CFR 892.1750","21 CFR 892.1750","n/a"],["Regulation\nName","System, X-Ray, Tomography,\nComputed","System, X-Ray,\nTomography, Computed","n/a"],["Intended\nUse/Indications\nfor Use","The VIDA|vision software\nprovides reproducible CT\nvalues for pulmonary tissue,\nwhich is essential for\nproviding quantitative\nsupport for diagnosis and\nfollow up examinations.\nVIDA|vision can be used to","The VIDA Pulmonary\nWorkstation 2 (PW2)\nsoftware provides\nreproducible CT values for\npulmonary tissue, which is\nessential for providing\nquantitative support for\ndiagnosis and follow up\nexaminations. The PW2 can","n/a"]],"caption_candidate":"Table 1 - Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p12-t0","doc_id":"K201012","page_num":12,"bbox":[39.63,135.21,750.57,531.12],"n_rows":4,"n_cols":5,"columns":["","Device","","Indications for Use",""],"rows":[["","Device","","Indications for Use",""],["Philips Lumify\nDiagnostic\nUltrasound\nSystem","","Philips Lumify Diagnostic Ultrasound System is intended for diagnostic ultrasound imaging in B (2D), Color Doppler, Combined\n(B+Color), and M modes. It is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications:\nFetal/Obstetric, Abdominal, Pediatric, Cephalic, Urology, Gynecological, Cardiac Fetal Echo, Small Organ, Musculoskeletal,\nPeripheral Vessel, Carotid, Cardiac. Lumify is a transportable ultrasound system intended for use in environments where\nhealthcare is provided by healthcare professionals.","",""],["Philips EPIQ\nDiagnostic\nUltrasound\nSystem","","The intended use of the EPIQ, EPIQ 5, EPIQ 7 Diagnostic Ultrasound Systems is diagnostic ultrasound imaging and fluid flow\nanalysis of the human body with the following Indications for Use: Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac\nPediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric, Gynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal (Conventional), Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral\nVessel, Small Organ (Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the EPIQ Diagnostic Ultrasound Systems can be used include Clinics, Hospitals, and clinical\npoint-of-care for diagnosis of patients.\nWhen integrated with Philips EchoNavigator, the systems can assist the interventionalist and surgeon with image guidance during\ntreatment of cardiovascular disease in which the procedure uses both live X-ray and live Echo Guidance.\nThe systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating\ninstructions given in the product user information, and only for the purposes for which it was designed. However, nothing stated\nin the user information reduces your responsibility for sound clinical judgement and best clinical procedure.","",""],["Philips Affiniti\nDiagnostic\nUltrasound\nSystem","","The intended use of the Affiniti 30, Affiniti 50 and Affiniti 70 Diagnostic Ultrasound Systems is diagnostic ultrasound imaging\nand fluid flow analysis of the human body with the following Indications for Use: Abdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle),\nTransesophageal (Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the Affiniti Diagnostic Ultrasound Systems can be used include Clinics, Hospitals, and clinical\npoint-of-care for diagnosis of patients.\nWhen integrated with Philips EchoNavigator, the systems can assist the interventionalist and surgeon with image guidance during\ntreatment of cardiovascular disease in which the procedure uses both live X-ray and live Echo Guidance.","",""]],"caption_candidate":"V. Indications for Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p13-t0","doc_id":"K201012","page_num":13,"bbox":[39.62,73.47,750.58,332.58],"n_rows":5,"n_cols":5,"columns":["","Device","","Indications for Use",""],"rows":[["","Device","","Indications for Use",""],["","","The systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating\ninstructions given in the product user information, and only for the purposes for which it was designed. However, nothing stated\nin the user information reduces your responsibility for sound clinical judgement and best clinical procedure","",""],["Philips CX50\nDiagnostic\nUltrasound\nSystem","","Philips CX50 Diagnostic Ultrasound Systems is intended for diagnostic ultrasound imaging in B (or 2- D), M-mode (including\nAnatomical M-mode), Pulse Wave Doppler, Continuous Wave Doppler, Color Doppler, Tissue Doppler Imaging and Harmonics\n(Tissue and Contrast) modes.\nIt is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications: Ophthalmic Intraoperative\nLaparoscopic Fetal Abdominal Pediatric Small Organ Adult Cephalic Neonatal Cephalic Trans-vaginal Musculo-skeletal\nGynecological Cardiac Adult Cardiac Pediatric Trans-Esoph. (Cardiac) Intracardiac echo Peripheral Vessel Other (Carotid)","",""],["Philips Sparq\nDiagnostic\nUltrasound\nSystem","","Philips Sparq Diagnostic Ultrasound System is intended for diagnostic ultrasound imaging in B (or 2- D), M-mode (including\nAnatomical M-mode), Pulse Wave Doppler, Continuous Wave Doppler, Color Doppler, Tissue Doppler Imaging and Harmonics\n(Tissue and Contrast) modes. It is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications:\nOphthalmic Fetal Abdominal Pediatric Small Organ Adult Cephalic Trans-vaginal Trans-rectal Musculo-skeletal Gynecological\nCardiac Adult Trans-Esoph. (Cardiac) Peripheral Vessel","",""],["QLAB\nAdvanced\nQuantification\nsoftware","","QLAB Advanced Quantification Software is a software application package. It is designed to view and quantify image data\nacquired on Philips ultrasound systems.","",""]],"caption_candidate":"Lumify/EPIQ/Affiniti/CX50/Sparq/QLAB Devices Page 5 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p14-t0","doc_id":"K201012","page_num":14,"bbox":[72.32,134.97,719.74,527.85],"n_rows":10,"n_cols":8,"columns":["Standard Feature","","","Philips Lumify Ultrasound System\nK# Pending\n(Subject Device)","","Philips Lumify Diagnostic","","Comparison"],"rows":[["Standard Feature","","","Philips Lumify Ultrasound System\nK# Pending\n(Subject Device)","","Philips Lumify Diagnostic","","Comparison"],["","","","","","Ultrasound System","",""],["","","","","","K192226","",""],["","","","","","(Predicate Device)","",""],["Indications for Use","","","Philips Lumify Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (2D), Color\nDoppler, Combined (B+Color), and M\nmodes. It is indicated for diagnostic\nultrasound imaging and fluid flow\nanalysis in the following applications:\nFetal/Obstetric, Abdominal, Pediatric,\nCephalic, Urology, Gynecological,\nCardiac Fetal Echo, Small Organ,\nMusculoskeletal, Peripheral Vessel,\nCarotid, Cardiac. Lumify is a\ntransportable ultrasound system\nintended for use in environments where\nhealthcare is provided by healthcare\nprofessionals.","Philips Lumify Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (2D), Color\nDoppler, Combined (B+Color), and M\nmodes. It is indicated for diagnostic\nultrasound imaging and fluid flow\nanalysis in the following applications:\nFetal/Obstetric, Abdominal, Pediatric,\nCephalic, Urology, Gynecological,\nCardiac Fetal Echo, Small Organ,\nMusculoskeletal, Peripheral Vessel,\nCarotid, Cardiac. Lumify is a\ntransportable ultrasound system\nintended for use in environments where\nhealthcare is provided by healthcare\nprofessionals.","","","Identical"],["Reusable?","","","Yes","Yes","","","Identical"],["Duration of Use","","","Limited (≤ 24 hours)","Limited (≤ 24 hours)","","","Identical"],["","Scientific","","Ultrasound Imaging","Ultrasound Imaging","","","Identical"],["","Technology","","","","","",""],["Operating\nprinciples","","","Compatible device generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.","Compatible device generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.","","","Identical"]],"caption_candidate":"Table 1: Technological Comparison of Subject Device (i.e., Philips Lumify Diagnostic Ultrasound System) & Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p15-t0","doc_id":"K201012","page_num":15,"bbox":[72.32,86.87,719.74,433.03],"n_rows":13,"n_cols":8,"columns":["Standard Feature","","","Philips Lumify Ultrasound System\nK# Pending\n(Subject Device)","","Philips Lumify Diagnostic","","Comparison"],"rows":[["Standard Feature","","","Philips Lumify Ultrasound System\nK# Pending\n(Subject Device)","","Philips Lumify Diagnostic","","Comparison"],["","","","","","Ultrasound System","",""],["","","","","","K192226","",""],["","","","","","(Predicate Device)","",""],["","","","Stimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","Stimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","",""],["","Type of Previously-","","Curved Array\nLinear Array\nSector Array","Curved Array\nLinear Array\nSector Array","","","Identical"],["","cleared","","","","","",""],["","Transducers","","","","","",""],["","Acoustic Outputs","","Yes","Yes","","","Identical"],["","Within Range?","","","","","",""],["","Previously cleared","","Yes","Yes","","","Identical"],["","Imaging Modes?","","","","","",""],["","Biocompatibility","","ISO 10993-1","ISO 10993-1","","","Identical"]],"caption_candidate":"Devices Page 7 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p16-t0","doc_id":"K201012","page_num":16,"bbox":[72.32,116.98,719.71,530.49],"n_rows":5,"n_cols":7,"columns":["Standard Feature","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],["","","","","System Series","",""],["","","","","K182857","",""],["","","","","(Predicate Device)","",""],["Indications for Use","The intended use of the EPIQ, EPIQ 5,\nEPIQ 7 Diagnostic Ultrasound Systems\nis diagnostic ultrasound imaging and\nfluid flow analysis of the human body\nwith the following Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric,\nPeripheral Vessel, Small Organ (Breast,\nThyroid, Testicle), Transesophageal\n(Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the\nEPIQ Diagnostic Ultrasound Systems\ncan be used include Clinics, Hospitals,\nand clinical point-of-care for diagnosis of\npatients.\nWhen integrated with Philips\nEchoNavigator, the systems can assist\nthe interventionalist and surgeon with\nimage guidance during treatment of","","The intended use of the EPIQ, EPIQ 5,\nEPIQ 7 Diagnostic Ultrasound Systems\nis diagnostic ultrasound imaging and\nfluid flow analysis of the human body\nwith the following Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric,\nPeripheral Vessel, Small Organ (Breast,\nThyroid, Testicle), Transesophageal\n(Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the\nEPIQ Diagnostic Ultrasound Systems\ncan be used include Clinics, Hospitals,\nand clinical point-of-care for diagnosis of\npatients.\nWhen integrated with Philips\nEchoNavigator, the systems can assist\nthe interventionalist and surgeon with\nimage guidance during treatment of","","","Identical"]],"caption_candidate":"Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p17-t0","doc_id":"K201012","page_num":17,"bbox":[72.32,86.88,719.74,536.43],"n_rows":10,"n_cols":9,"columns":["Standard Feature","","","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],["","","","","","","System Series","",""],["","","","","","","K182857","",""],["","","","","","","(Predicate Device)","",""],["","","","cardiovascular disease in which the\nprocedure uses both live X-ray and live\nEcho Guidance.\nThe systems are intended to be installed,\nused, and operated only in accordance\nwith the safety procedures and operating\ninstructions given in the product user\ninformation, and only for the purposes\nfor which it was designed. However,\nnothing stated in the user information\nreduces your responsibility for sound\nclinical judgement and best clinical\nprocedure.","","cardiovascular disease in which the\nprocedure uses both live X-ray and live\nEcho Guidance.\nThe systems are intended to be installed,\nused, and operated only in accordance\nwith the safety procedures and operating\ninstructions given in the product user\ninformation, and only for the purposes\nfor which it was designed. However,\nnothing stated in the user information\nreduces your responsibility for sound\nclinical judgement and best clinical\nprocedure.","","",""],["Reusable?","","","Yes","","Yes","","","Identical"],["Duration of Use","","","Limited (≤ 24 hours)","","Limited (≤ 24 hours)","","","Identical"],["","Scientific","","Ultrasound Imaging","","Ultrasound Imaging","","","Identical"],["","Technology","","","","","","",""],["Operating\nprinciples","","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are","","","Identical"]],"caption_candidate":"Devices Page 9 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p18-t0","doc_id":"K201012","page_num":18,"bbox":[72.32,86.88,719.74,338.53],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips EPIQ Diagnostic Ultrasound\nSystem Series\nK# Pending\n(Subject Device)","","","Philips EPIQ Diagnostic Ultrasound","","Comparison"],["","","","","","","System Series","",""],["","","","","","","K182857","",""],["","","","","","","(Predicate Device)","",""],["","","","reflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","reflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","",""],["","Type of Previously-","","Curved Array\nLinear Array\nSector Array","","Curved Array\nLinear Array\nSector Array","","","Identical"],["","cleared","","","","","","",""],["","Transducers","","","","","","",""],["","Acoustic Outputs","","Yes","","Yes","","","Identical"],["","Within Range?","","","","","","",""],["","Previously cleared","","Yes","","Yes","","","Identical"],["","Imaging Modes?","","","","","","",""],["","Biocompatibility","","ISO 10993-1","","ISO 10993-1","","","Identical"]],"caption_candidate":"Devices Page 10 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p19-t0","doc_id":"K201012","page_num":19,"bbox":[72.32,116.98,719.71,530.49],"n_rows":5,"n_cols":7,"columns":["Standard Feature","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],"rows":[["Standard Feature","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],["","","","","Ultrasound System Series","",""],["","","","","K182857","",""],["","","","","(Predicate Device)","",""],["Indications for Use","The intended use of the Affiniti 30,\nAffiniti 50 and Affiniti 70 Diagnostic\nUltrasound Systems is diagnostic\nultrasound imaging and fluid flow\nanalysis of the human body with the\nfollowing Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric,\nPeripheral Vessel, Small Organ (Breast,\nThyroid, Testicle), Transesophageal\n(Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the\nAffiniti Diagnostic Ultrasound Systems\ncan be used include Clinics, Hospitals,\nand clinical point-of-care for diagnosis of\npatients.\nWhen integrated with Philips\nEchoNavigator, the systems can assist\nthe interventionalist and surgeon with","","The intended use of the Affiniti 30,\nAffiniti 50 and Affiniti 70 Diagnostic\nUltrasound Systems is diagnostic\nultrasound imaging and fluid flow\nanalysis of the human body with the\nfollowing Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric,\nPeripheral Vessel, Small Organ (Breast,\nThyroid, Testicle), Transesophageal\n(Cardiac), Transrectal, Transvaginal.\nThe clinical environments where the\nAffiniti Diagnostic Ultrasound Systems\ncan be used include Clinics, Hospitals,\nand clinical point-of-care for diagnosis of\npatients.\nWhen integrated with Philips\nEchoNavigator, the systems can assist\nthe interventionalist and surgeon with","","","Identical"]],"caption_candidate":"Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p20-t0","doc_id":"K201012","page_num":20,"bbox":[72.32,86.88,719.74,529.77],"n_rows":10,"n_cols":9,"columns":["Standard Feature","","","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],"rows":[["Standard Feature","","","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],["","","","","","","Ultrasound System Series","",""],["","","","","","","K182857","",""],["","","","","","","(Predicate Device)","",""],["","","","image guidance during treatment of\ncardiovascular disease in which the\nprocedure uses both live X-ray and live\nEcho Guidance.\nThe systems are intended to be installed,\nused, and operated only in accordance\nwith the safety procedures and operating\ninstructions given in the product user\ninformation, and only for the purposes\nfor which it was designed. However,\nnothing stated in the user information\nreduces your responsibility for sound\nclinical judgement and best clinical\nprocedure.","","image guidance during treatment of\ncardiovascular disease in which the\nprocedure uses both live X-ray and live\nEcho Guidance.\nThe systems are intended to be installed,\nused, and operated only in accordance\nwith the safety procedures and operating\ninstructions given in the product user\ninformation, and only for the purposes\nfor which it was designed. However,\nnothing stated in the user information\nreduces your responsibility for sound\nclinical judgement and best clinical\nprocedure.","","",""],["Reusable?","","","Yes","","Yes","","","Identical"],["Duration of Use","","","Limited (≤ 24 hours)","","Limited (≤ 24 hours)","","","Identical"],["","Scientific","","Ultrasound Imaging","","Ultrasound Imaging","","","Identical"],["","Technology","","","","","","",""],["Operating\nprinciples","","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus","","","Identical"]],"caption_candidate":"Devices Page 12 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p21-t0","doc_id":"K201012","page_num":21,"bbox":[72.32,86.88,719.74,365.53],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],"rows":[["Standard Feature","","","Philips Affiniti Diagnostic\nUltrasound System Series\nK# Pending\n(Subject Device)","","","Philips Affiniti Diagnostic","","Comparison"],["","","","","","","Ultrasound System Series","",""],["","","","","","","K182857","",""],["","","","","","","(Predicate Device)","",""],["","","","membrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","membrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","",""],["","Type of Previously-","","Curved Array\nLinear Array\nSector Array","","Curved Array\nLinear Array\nSector Array","","","Identical"],["","cleared","","","","","","",""],["","Transducers","","","","","","",""],["","Acoustic Outputs","","Yes","","Yes","","","Identical"],["","Within Range?","","","","","","",""],["","Previously cleared","","Yes","","Yes","","","Identical"],["","Imaging Modes?","","","","","","",""],["","Biocompatibility","","ISO 10993-1","","ISO 10993-1","","","Identical"]],"caption_candidate":"Devices Page 13 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p22-t0","doc_id":"K201012","page_num":22,"bbox":[72.32,128.98,719.74,535.35],"n_rows":10,"n_cols":9,"columns":["Standard Feature","","","Philips CX50 Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips CX50 Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips CX50 Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips CX50 Diagnostic Ultrasound","","Comparison"],["","","","","","","System","",""],["","","","","","","K162329","",""],["","","","","","","(Predicate Device)","",""],["Indications for Use","","","Philips CX50 Diagnostic Ultrasound\nSystems is intended for diagnostic\nultrasound imaging in B (or 2- D), M-\nmode (including Anatomical M-mode),\nPulse Wave Doppler, Continuous Wave\nDoppler, Color Doppler, Tissue Doppler\nImaging and Harmonics (Tissue and\nContrast) modes.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: Ophthalmic\nIntraoperative Laparoscopic Fetal\nAbdominal Pediatric Small Organ Adult\nCephalic Neonatal Cephalic Trans-\nvaginal Musculo-skeletal Gynecological\nCardiac Adult Cardiac Pediatric Trans-\nEsoph. (Cardiac) Intracardiac echo\nPeripheral Vessel Other (Carotid)","","Philips CX50 Diagnostic Ultrasound\nSystems is intended for diagnostic\nultrasound imaging in B (or 2- D), M-\nmode (including Anatomical M-mode),\nPulse Wave Doppler, Continuous Wave\nDoppler, Color Doppler, Tissue\nDoppler Imaging and Harmonics (Tissue\nand Contrast) modes.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: Ophthalmic\nIntraoperative Laparoscopic Fetal\nAbdominal Pediatric Small Organ Adult\nCephalic Neonatal Cephalic Trans-\nvaginal Musculo-skeletal Gynecological\nCardiac Adult Cardiac Pediatric Trans-\nEsoph. (Cardiac) Intracardiac echo\nPeripheral Vessel Other (Carotid)","","","Identical"],["Reusable?","","","Yes","","Yes","","","Identical"],["Duration of Use","","","Limited (≤ 24 hours)","","Limited (≤ 24 hours)","","","Identical"],["","Scientific","","Ultrasound Imaging","","Ultrasound Imaging","","","Identical"],["","Technology","","","","","","",""],["Operating\nprinciples","","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its","","","Identical"]],"caption_candidate":"Table 4: Technological Comparison of Subject Device (i.e., Philips CX50 Diagnostic Ultrasound System) & Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p23-t0","doc_id":"K201012","page_num":23,"bbox":[72.32,86.88,719.74,446.53],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","","Philips CX50 Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips CX50 Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips CX50 Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips CX50 Diagnostic Ultrasound","","Comparison"],["","","","","","","System","",""],["","","","","","","K162329","",""],["","","","","","","(Predicate Device)","",""],["","","","piezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","piezoelectric elements at the distal end.\nStimulation causes the elements to\nexpand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","",""],["","Type of Previously-","","Curved Array\nLinear Array\nSector Array","","Curved Array\nLinear Array\nSector Array","","","Identical"],["","cleared","","","","","","",""],["","Transducers","","","","","","",""],["","Acoustic Outputs","","Yes","","Yes","","","Identical"],["","Within Range?","","","","","","",""],["","Previously cleared","","Yes","","Yes","","","Identical"],["","Imaging Modes?","","","","","","",""],["","Biocompatibility","","ISO 10993-1","","ISO 10993-1","","","Identical"]],"caption_candidate":"Devices Page 15 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p24-t0","doc_id":"K201012","page_num":24,"bbox":[72.32,128.98,719.74,535.35],"n_rows":10,"n_cols":9,"columns":["Standard Feature","","","Philips Sparq Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips Sparq Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips Sparq Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips Sparq Diagnostic Ultrasound","","Comparison"],["","","","","","","System","",""],["","","","","","","K162329","",""],["","","","","","","(Predicate Device)","",""],["Indications for Use","","","Philips Sparq Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (or 2- D), M-\nmode (including Anatomical M-mode),\nPulse Wave Doppler, Continuous Wave\nDoppler, Color Doppler, Tissue Doppler\nImaging and Harmonics (Tissue and\nContrast) modes. It is indicated for\ndiagnostic ultrasound imaging and fluid\nflow analysis in the following\napplications: Ophthalmic Fetal\nAbdominal Pediatric Small Organ Adult\nCephalic Trans-vaginal Trans-rectal\nMusculo-skeletal Gynecological Cardiac\nAdult Trans-Esoph. (Cardiac) Peripheral\nVessel","","Philips Sparq Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (or 2- D), M-\nmode (including Anatomical M-mode),\nPulse Wave Doppler, Continuous Wave\nDoppler, Color Doppler, Tissue\nDoppler Imaging and Harmonics (Tissue\nand Contrast) modes. It is indicated for\ndiagnostic ultrasound imaging and fluid\nflow analysis in the following\napplications: Ophthalmic Fetal\nAbdominal Pediatric Small Organ Adult\nCephalic Trans-vaginal Trans-rectal\nMusculo-skeletal Gynecological Cardiac\nAdult Trans-Esoph. (Cardiac) Peripheral\nVessel","","","Identical"],["Reusable?","","","Yes","","Yes","","","Identical"],["Duration of Use","","","Limited (≤ 24 hours)","","Limited (≤ 24 hours)","","","Identical"],["","Scientific","","Ultrasound Imaging","","Ultrasound Imaging","","","Identical"],["","Technology","","","","","","",""],["Operating\nprinciples","","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to","","System console generates electrical\ncurrent and sends to a connected,\ncompatible transducer to stimulate its\npiezoelectric elements at the distal end.\nStimulation causes the elements to","","","Identical"]],"caption_candidate":"Table 5: Technological Comparison of Subject Device (i.e., Philips Sparq Diagnostic Ultrasound System) & Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p25-t0","doc_id":"K201012","page_num":25,"bbox":[72.32,86.88,719.74,419.53],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","","Philips Sparq Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips Sparq Diagnostic Ultrasound","","Comparison"],"rows":[["Standard Feature","","","Philips Sparq Diagnostic Ultrasound\nSystem\nK# Pending\n(Subject Device)","","","Philips Sparq Diagnostic Ultrasound","","Comparison"],["","","","","","","System","",""],["","","","","","","K162329","",""],["","","","","","","(Predicate Device)","",""],["","","","expand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","expand and contract which creates a\nhigh-pressured wave (i.e., soundwave). A\nseries of soundwaves then propagate\ntoward tissue medium (e.g., mucus\nmembrane, bone). The transducer then\nreceives echoed soundwaves that are\nreflected from the tissue medium and\ntransmits it to the system. The system\nprocesses the echoed soundwaves into\nan image which is displayed on the\ndisplay monitor screen of the system for\nuser interpretation.","","",""],["","Type of Previously-","","Curved Array\nLinear Array\nSector Array","","Curved Array\nLinear Array\nSector Array","","","Identical"],["","cleared","","","","","","",""],["","Transducers","","","","","","",""],["","Acoustic Outputs","","Yes","","Yes","","","Identical"],["","Within Range?","","","","","","",""],["","Previously cleared","","Yes","","Yes","","","Identical"],["","Imaging Modes?","","","","","","",""],["","Biocompatibility","","ISO 10993-1","","ISO 10993-1","","","Identical"]],"caption_candidate":"Devices Page 17 of 19","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201012-p26-t0","doc_id":"K201012","page_num":26,"bbox":[72.32,103.48,719.73,266.85],"n_rows":6,"n_cols":7,"columns":["Standard Feature","QLAB Advanced Quantification\nSoftware\nK# Pending\n(Subject Device)","","","QLAB Advanced Quantification","","Comparison"],"rows":[["Standard Feature","QLAB Advanced Quantification\nSoftware\nK# Pending\n(Subject Device)","","","QLAB Advanced Quantification","","Comparison"],["","","","","Software","",""],["","","","","K191647","",""],["","","","","(Predicate Device)","",""],["Indications for Use","QLAB Advanced Quantification\nSoftware is a software application\npackage. It is designed to view and\nquantify image data acquired on Philips\nultrasound systems.","","QLAB Advanced Quantification\nSoftware is a software application\npackage. It is designed to view and\nquantify image data acquired on Philips\nultrasound systems.","","","Identical"],["Application\nDescriptions","Semiautomatic border detection,\nchamber identification, contour\ngeneration, measurement parameters","","Semiautomatic border detection,\nchamber identification, contour\ngeneration, measurement parameters","","","Identical"]],"caption_candidate":"Table 6: Technological Comparison of Subject Device (i.e., QLAB Advanced Quantification Software) & Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201019-p6-t0","doc_id":"K201019","page_num":6,"bbox":[52.14,116.36,558.16,591.52],"n_rows":4,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection","Predicate Device\niCAD Inc.\nPowerLook®\nTomo","Difference and\ncomments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection","Predicate Device\niCAD Inc.\nPowerLook®\nTomo","Difference and\ncomments"],["Regulation\nNumber/Name","21 CFR 892.2090 /\nRadiological Computer Assisted\nDetection and Diagnosis Software","DSaemteec tion V2","N/A"],["Product Code","QDQ","Same","N/A"],["Regulation\nDescription","A radiological computer assisted detection\nand diagnostic software is an image\nprocessing device intended to aid in the\ndetection, localization, and\ncharacterization of fracture, lesions, or\nother disease specific findings on acquired\nmedical images (e.g. radiography, MR, CT).\nThe device detects, identifies and\ncharacterizes findings based on features\nor information extracted from images, and\nprovides information about the presence,\nlocation, and characteristics of the\nfindings to the user. The analysis is\nintended to inform the primary diagnostic\nand patient management decisions that\nare made by the clinical user. The device\nis not intended as a replacement for a\ncomplete clinician's review or their\nclinical judgment that takes into account\nother relevant information from the\nimage or patient history.","Same","N/A"]],"caption_candidate":"Summary of Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201019-p7-t0","doc_id":"K201019","page_num":7,"bbox":[52.14,72.3,559.0,650.74],"n_rows":3,"n_cols":4,"columns":["Indications for\nUse","Genius AI Detection is a computer-aided\ndetection and diagnosis (CADe/CADx)\nsoftware device intended to be used with\ncompatible digital breast tomosynthesis\n(DBT) systems to identify and mark\nregions of interest including soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in DBT exams from\ncompatible DBT systems and provide\nconfidence scores that offer assessment\nfor Certainty of Findings and a Case Score.\nThe device intends to aid in the\ninterpretation of digital breast\ntomosynthesis exams in a concurrent\nfashion, where the interpreting physician\nconfirms or dismisses the findings during\nthe reading of the exam.","PowerLook® Tomo\nDetection V2 software\nis a computer-\nassisted detection and\ndiagnosis (CAD)\nsoftware device\nintended to be used\nconcurrently by\ninterpreting physicians\nwhile reading digital\nbreast tomosynthesis\n(DBT) exams from\ncompatible DBT\nsystems. The system\ndetects soft tissue\ndensities (masses,\narchitectural\ndistortions and\nasymmetries) and\ncalcifications in the 3D\nDBT slices. The\ndetections and\nCertainty of Finding\nand Case Scores assist\ninterpreting physicians\nin identifying soft\ntissue densities and",""],"rows":[["Indications for\nUse","Genius AI Detection is a computer-aided\ndetection and diagnosis (CADe/CADx)\nsoftware device intended to be used with\ncompatible digital breast tomosynthesis\n(DBT) systems to identify and mark\nregions of interest including soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in DBT exams from\ncompatible DBT systems and provide\nconfidence scores that offer assessment\nfor Certainty of Findings and a Case Score.\nThe device intends to aid in the\ninterpretation of digital breast\ntomosynthesis exams in a concurrent\nfashion, where the interpreting physician\nconfirms or dismisses the findings during\nthe reading of the exam.","PowerLook® Tomo\nDetection V2 software\nis a computer-\nassisted detection and\ndiagnosis (CAD)\nsoftware device\nintended to be used\nconcurrently by\ninterpreting physicians\nwhile reading digital\nbreast tomosynthesis\n(DBT) exams from\ncompatible DBT\nsystems. The system\ndetects soft tissue\ndensities (masses,\narchitectural\ndistortions and\nasymmetries) and\ncalcifications in the 3D\nDBT slices. The\ndetections and\nCertainty of Finding\nand Case Scores assist\ninterpreting physicians\nin identifying soft\ntissue densities and",""],["Compatible\nDBT Systems","Hologic Selenia Dimensions\nHologic 3Dimensions\nSupports both models in the following\nmodes:\n• standard resolution 1-mm slices\n• high resolution 1-mm slices\n(Clarity HD),\n• high resolution 6-mm SmartSlices\n(3DQuorum)","cHaolcloifgicica tSieolnesn itah at may\nbDeim ceonnsfiiromnse d(s otar ndard\ndreissmoliustsieodn ,b 1y- tmhme\nisnlitceersp) reting physician.\nGE Pristina","The subject\ndevice and\npredicate device\nare compatible\nwith different\nsystems as\nnoted."],["Type of CAD\nSoftware","Radiological computer assisted\ndetection and diagnostic software.","same","N/A"]],"caption_candidate":"Genius AI Detection","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201019-p9-t0","doc_id":"K201019","page_num":9,"bbox":[52.14,72.36,560.68,155.06],"n_rows":2,"n_cols":4,"columns":["Method Of Use","Concurrent read","Concurrent read. FFDM\nand 2D synthetic views\nwhen available are to\nbe reviewed before","N/A"],"rows":[["Method Of Use","Concurrent read","Concurrent read. FFDM\nand 2D synthetic views\nwhen available are to\nbe reviewed before","N/A"],["Supported Views","CC and MLO","marked 3D slices\nsame","N/A"]],"caption_candidate":"Genius AI Detection","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201020-p6-t0","doc_id":"K201020","page_num":6,"bbox":[66.6,176.04,528.72,768.12],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],"rows":[["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],["Intended Use /\nIndications for Use","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of CTPA\nimages. The device is intended\nto assist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of suspected\npositive findings of Pulmonary\nEmbolism (PE) pathology. The\nsoftware is only intended to be\nused on single-energy exams.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a\nstandalone desktop application in\nparallel to the ongoing\nstandard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected findings.\nNotifications include compressed\npreview images that are\nmeant for informational purposes\nonly and not intended for\ndiagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of contrast-\nenhanced chest CTs (but not\ndedicated CTPA protocol).\nThe device is intended to\nassist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of suspected\npositive cases of incidental\nPulmonary Embolism (iPE)\npathologies. For the iPE\npathology, the software is only\nintended to be used on single-\nenergy exams. The device is\nintended to work with GE and\nSiemens scanners only.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and flag suspect cases on\na standalone desktop application\nin parallel to the ongoing\nstandard of care image\ninterpretation. The user is\npresented with notifications for\nsuspect cases. Notifications\ninclude compressed preview\nimages that are\nmeant for informational purposes\nonly and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the\noriginal medical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in conjunction\nwith other patient information and\nbased on their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201020-p7-t0","doc_id":"K201020","page_num":7,"bbox":[66.6,72.24,528.72,694.56],"n_rows":13,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],"rows":[["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],["","","responsible for viewing full images\nper the standard of care."],["User population","Radiologist","Radiologist"],["Anatomical region of\ninterest","Chest","Chest"],["Inclusion/\nExclusion criteria","Inclusion Criteria\n- CTPA protocols.\n- Single energy exams.\n- Scans performed with 64-\nslice scanner or greater\nnumber of detectors.\n- Scans performed on\nadults/transitional adults ≥ 18\nyears of age.\n- Slice thickness 0.5 - 3.0 mm\naxial.\nExclusion Criteria\n- All studies that are technically\ninadequate, including studies\nwith motion artifacts, severe\nmetal artifacts, sub-optimal\nbolus or inadequate field of\nview.","Inclusion criteria\n- Contrast-enhanced chest CTs\n(but not dedicated CTPA\nprotocol.\n- Single energy exams.\n- Scans performed with a 64\nslice or greater number of\ndetectors.\n- Scans performed on\nadults/transitional adults ≥ 18\nyears of age.\n- Slice thickness: 0.5mm –\n2.0mm axial.\nExclusion Criteria\n- All studies that are technically\ninadequate, including studies\nwith motion artifacts, severe\nmetal artifacts, or inadequate\nfield of view."],["Data acquisition\nprotocol","CTPA protocol","Contrast-enhanced chest CTs (but\nnot dedicated CTPA protocol)"],["View DICOM data","DICOM Information about the\npatient, study and current image","DICOM Information about the\npatient, study and current image"],["Segmentation of region\nof interest","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image","No; device does not mark,\nannotate, or direct users’ attention\nto a specific location in the original\nimage"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a low-quality,\ncompressed, grayscale preview\nimage that is captioned “Not for\ndiagnostic use”.","Presentation of a low-quality,\ncompressed, grayscale preview\nimage that is captioned “Not for\ndiagnostic use”."],["Alteration of original\nimage","No","No"],["Removal of cases from\nworklist queue","No. The device operates in\nparallel with the standard of care,\nwhich remains the default option\nfor all cases. Unflagged cases\nare not de-prioritized.","No. The device operates in\nparallel with the standard of care,\nwhich remains the default option\nfor all cases. Unflagged cases are\nnot de-prioritized."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201020-p8-t0","doc_id":"K201020","page_num":8,"bbox":[66.6,72.24,528.72,206.04],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],"rows":[["","Predicate Device\nAidoc Briefcase for PE triage\n(K190072)","Subject Device\nAidoc Briefcase for iPE triage\n(K201020)"],["Structure","- AHS module (image\nacquisition).\n- ACS module (image\nprocessing).\n- Aidoc Worklist application for\nworkflow integration (worklist\nand non-diagnostic basic\nImage Viewer).","- AHS module (image\nacquisition).\n- ACS module (image\nprocessing).\n- Aidoc Worklist application for\nworkflow integration (worklist\nand non-diagnostic basic\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201020-p9-t0","doc_id":"K201020","page_num":9,"bbox":[77.96,85.66,517.24,222.0],"n_rows":9,"n_cols":18,"columns":["Parameter","","","N","","","Mean\nestimate","","","Lower","","","Upper\nConfidence\nLimit","Median","","IQR","",""],"rows":[["Parameter","","","N","","","Mean\nestimate","","","Lower","","","Upper\nConfidence\nLimit","Median","","IQR","",""],["","","","","","","","","","Confidence","","","","","","","",""],["","","","","","","","","","Limit","","","","","","","",""],["","Time-to-exam-open","","63","","","223.3","","125.8","","","320.7","","70.4","","217.65","",""],["","in the standard of","","","","","","","","","","","","","","","",""],["","care","","","","","","","","","","","","","","","",""],["","Time-to-notification","","","63","","","4.7","","4.4","","","5.1","5.0","","","2.3",""],["","BriefCase iPE","","","","","","","","","","","","","","","",""],["Difference","","","","63","","","220.9","","122.0","","","319.9","63.2","","","219.8",""]],"caption_candidate":"Table 2. Time saving data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201034-p6-t0","doc_id":"K201034","page_num":6,"bbox":[70.81,143.92,524.38,765.72],"n_rows":12,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Devices",""],"rows":[["Feature","","Subject Device","","","Predicate Devices",""],["","syngo.CT CaScoring\n(SOMARIS/8 VB50)","","","syngo.CT CaScoring\n(SOMARIS/8 VB40)","",""],["Modality","CT","","","CT","",""],["Loading of a series of\nappropriate CT from the patient\ndatabase","Yes","","","Yes","",""],["Body Part","Heart / Chest","","","Heart / Chest","",""],["Acquisition Part","ECG-gated / ECG-triggered","","","ECG-gated / ECG-triggered","",""],["Automated Calcium Scoring\nEvaluation","Assignment of a probability of a\ncandidate being a coronary\ncalcification based on location\nwithin the heart, density, shape and\nsimilar properties: if the probability\nof a candidate is higher than a\npredefined threshold, the candidate\nis labelled as a calcification.\nEach calcification is labeled\naccording to one of four coronary\narteries it most probably belongs to.\nIn addition, results of the evaluation\ncan be sent via Rapid Results\nTechnology to any generic DICOM\nviewer.\nComparison to the predicate\ndevice:\nThe first part of the automatic\nCalcium Scoring algorithm works in\nthe same manner as cleared with the\npredicate device. From functional\nperspective there are no differences.\nThe second part (labeling of\ncalcifications according to coronary\nartery) is new in the subject device.","","","Assignment of a probability of a candidate\nbeing a coronary calcification based on\nlocation within the heart, density, shape and\nsimilar properties: if the probability of a\ncandidate is higher than a predefined\nthreshold, the candidate is labelled as a\ncalcification.\nIn addition, results of the evaluation can be\nsent via Rapid Results Technology any\ngeneric DICOM viewer.","",""],["Browsing, selecting, and\ndisplaying images for searching\ncalcium regions/lesions","Yes","","","Yes","",""],["Interactive definition of ROIs and\nassignment of the four major\ncoronary arteries (LM, LAD,CRC\nand RCA) to the lesions","Yes","","","Yes","",""],["Automatic definition of ROIs and\nassignment of a generic calcium\nlabel to the lesions","Yes","","","Yes","",""],["Calculation and display of the\n2D-Agatston score/factor or\nother metric on the defined ROIs","Agatston, volume and mass scores","","","Agatston, volume and mass scores","",""],["Interactive definition of ROIs (for\nexample noise) to disqualify the\nregion from participation in the\nscore","Yes","","","Yes","",""]],"caption_candidate":"level in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201034-p8-t0","doc_id":"K201034","page_num":8,"bbox":[70.83,396.81,524.38,561.6],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)","01/14/2019","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Second\nEdition 2007-03-01","06/27/2016","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201039-p4-t0","doc_id":"K201039","page_num":4,"bbox":[77.66,165.08,385.98,705.08],"n_rows":49,"n_cols":2,"columns":["Date Prepared","4th December 2020"],"rows":[["Date Prepared","4th December 2020"],["",""],["Submitted by","Resonance Health Analysis S"],["",""],["","141 Burswood Rd"],["",""],["","Burswood 6100"],["",""],["","AUSTRALIA"],["",""],["Main Contact","Ms Alison Laws"],["",""],["","CEO"],["",""],["","alisonl@resonancehealth.com"],["",""],["","Tel: +61 8 9286 5300"],["",""],["","Fax: +61 8 9286 5399"],["",""],["US Contact (US Agent)","Michael van der Woude"],["",""],["","Director & GM"],["",""],["","Emergo Global Representatio"],["",""],["","2500 Bee Cave Road, Buildin"],["",""],["","Austin, TX 78746"],["",""],["","Phone: 512 3279997"],["",""],["","Fax: 512 3279998"],["",""],["","Email: USAgent@ul.com"],["",""],["DEVICE INFORMATION",""],["",""],["Name of Device","HepaFat-AI"],["",""],["Trade/proprietary Name","HepaFat-AI"],["",""],["Classification","Class II"],["",""],["Product Code","90-LNH"],["",""],["CFR Section","892.1000 Magnetic Resonan"],["",""],["Panel","Radiology"]],"caption_candidate":"th","well_formed":true,"extraction_settings":"text"}
{"table_id":"K201039-p4-t1","doc_id":"K201039","page_num":4,"bbox":[72.34,560.35,505.3,711.14],"n_rows":6,"n_cols":4,"columns":["","Name of Device","","HepaFat-AI"],"rows":[["","Name of Device","","HepaFat-AI"],["","Trade/proprietary Name","","HepaFat-AI"],["","Classification","","Class II"],["","Product Code","","90-LNH"],["","CFR Section","","892.1000 Magnetic Resonance Diagnostic Device"],["","Panel","","Radiology"]],"caption_candidate":"DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201039-p6-t0","doc_id":"K201039","page_num":6,"bbox":[72.28,247.85,504.45,717.94],"n_rows":9,"n_cols":9,"columns":["","","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFat-AI","","","HepaFat-Scan",""],["Regulatory Class","","","II","","","II","",""],["510(k) number","","","K201039","","","K122035","",""],["Classification Name","","","System, Nuclear Magnetic\nResonance Imaging, System, Image\nProcessing Radiological","","","System, Nuclear Magnetic Resonance\nImaging, System, Image Processing\nRadiological","",""],["CFR Section","","","892.1000","","","892.1000","",""],["Product Code and\nClassification Panel","","","90 LNH","","","90 LNH","",""],["Device Name","","","HepaFat-AI","","","HepaFat-Scan","",""],["Trade/Common Name","","","HepaFat-AI","","","HepaFat-Scan","",""],["Description","","","Standalone software platform\ndesigned to automatically analyse\nwithin seconds magnetic resonance\nimaging (MRI) datasets to generate\nan estimate of the patient’s\nvolumetric liver fat fraction (VLFF),\nconverted into proton density fat\nfraction (PDFF) and steatosis grade.\nNo user input is required for the\nanalysis thus minimising the impact\nof human error on obtained results.","","","Standalone software application to\nfacilitate the import and visualization\nof multi-slice, gradient-echo MRI\ndata sets encompassing the abdomen,\nwith functionality independent of the\nMRI equipment, to provide objective\nand reproducible determination of the\ntriglyceride fat fraction in magnetic\nresonance images of the liver. It\nutilises magnetic resonance images\nthat exploit the difference in\nresonance frequencies between\nhydrogen nuclei in water and\ntriglyceride fat. The quantitative\ntriglyceride fat fraction is based on\nthe measurement of a magnetic\nresonance parameter that reflects the\nratio of the proton density signal of\ntriglyceride fat to the total proton\ndensity signal in the liver.","",""]],"caption_candidate":"The table below summarizes the main similarities and differences between HepaFat-AI and the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201039-p7-t0","doc_id":"K201039","page_num":7,"bbox":[72.29,72.36,504.44,708.94],"n_rows":5,"n_cols":9,"columns":["","","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFat-AI","","","HepaFat-Scan",""],["Technology","","","Convolutional neural networks for\nthe image analysis.\nAlgorithmic for the images quality\nchecking and Alpha conversion into\nVLFF.","","","Algorithmic, with human interaction\nfor Region of Interest (ROI)\nselection.","",""],["Intended purpose(s)","","","1. Supporting clinical diagnoses\nabout the status of liver fat content.\n2. Supporting the subsequent\nclinical decision-making processes.\n3. Supporting the use in clinical\nresearch trials, directed at studying\nchanges in liver fat as a result of\ninterventions.","","","1. Supporting clinical diagnoses\nabout the status of liver fat content.\n2. Supporting the subsequent\nclinical decision-making processes.\n3. Supporting the use in clinical\nresearch trials, directed at studying\nchanges in liver fat as a result of\ninterventions.\n4. It contains an image viewer for\nimporting DICOM images, browsing\nthrough patient datasets, viewing\nimages and performing region of\ninterest analysis.","",""],["Intended Use","","","HepaFat-AI is intended for\nquantitative measurement of the\ntriglyceride fat fraction in magnetic\nresonance images of the liver, also\nknown as volumetric liver fat\nfraction (VLFF).\nIt utilises magnetic resonance images\nthat exploit the difference in\nresonance frequencies between\nhydrogen nuclei in water and\ntriglyceride fat. The quantitative\ntriglyceride fat fraction is based on\nthe measurement of a magnetic\nresonance parameter that reflects the\nratio of the proton density signal of\ntriglyceride fat to the total proton\ndensity signal in the liver.\nWhen interpreted by a trained\nphysician, the results provide\ninformation that can aid in\ndiagnosis.","","","HepaFat-Scan is a software device\nintended for quantitative\nmeasurement of the triglyceride fat\nfraction in magnetic resonance\nimages of the liver. It utilises\nmagnetic resonance images that\nexploit the difference in resonance\nfrequencies between hydrogen nuclei\nin water and triglyceride fat. The\nquantitative triglyceride fat fraction is\nbased on the measurement of a\nmagnetic resonance parameter that\nreflects the ratio of the proton density\nsignal of triglyceride fat to the total\nproton density signal in the liver.\nWhen interpreted by a trained\nphysician, the results provide\ninformation that can aid in diagnosis.","",""],["Indications","","","HepaFat-AI is indicated to:\nAssess the volumetric liver fat\nfraction, proton density fat\nfraction and steatosis grade\nin individuals with\nconfirmed or suspected fatty\nliver disease;","","","HepaFat-Scan is a software device\nintended for quantitative\nmeasurement of the triglyceride fat\nfraction in magnetic resonance\nimages of the liver. It utilises\nmagnetic resonance images that\nexploit the difference in resonance\nfrequencies between hydrogen nuclei","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201039-p8-t0","doc_id":"K201039","page_num":8,"bbox":[72.28,72.36,504.45,569.35],"n_rows":10,"n_cols":9,"columns":["","","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFat-AI","","","HepaFat-Scan",""],["","","","When interpreted by a trained\nphysician, the results can be used to\n• Monitor liver fat content in\npatients undergoing weight\nloss management and can be\nused to\n• Aid in the assessment and\nscreening of living donors\nfor liver transplant","","","in water and triglyceride fat. The\nquantitative triglyceride fat fraction is\nbased on the measurement of a\nmagnetic resonance parameter that\nreflects the ratio of the proton density\nsignal of triglyceride fat to the total\nproton density signal in the liver.\nWhen interpreted by a trained\nphysician, the results provide\ninformation that can aid in diagnosis.","",""],["User","","","Radiologist","","","Resonance Health’s trained analyst","",""],["Hosting platform","","","Cloud-based or onsite platform","","","Resonance Health’s internal server","",""],["Image-type utilized","","","Magnetic Resonance","","","Magnetic Resonance","",""],["Image format","","","DICOM","","","DICOM","",""],["Data Acquisition\nmethod","","","Gradient Recalled Echo (GRE)","","","Gradient Recalled Echo (GRE)","",""],["Anatomical Sites","","","Liver","","","Liver","",""],["Result report content","","","• Unique Report ID\n• Patient ID, patient name and date\nof birth for full identification of\nthe patient.\n• Scan date, and analysis date.\n• Referrer and MRI centre.\n• Results displayed: VLFF (%),\nPDFF (%) and Steatosis grade,\nassociated with confidence\nintervals and normal range.\n• Pictures of the 3 TEs of the\nanalysed slice.\n• Liver colour map (for illustration\npurpose only, not for diagnostic)","","","• Unique Report ID\n• Patient ID, patient name and date\nof birth for full identification of\nthe patient.\n• Scan date, and analysis date.\n• Referrer and MRI centre.\n• Results displayed: VLFF (%)\nassociated with confidence\nintervals and normal range.\n• Picture of the analysed slice.","",""],["Result report format","","","HTML and PDF","","","PDF","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201039-p9-t0","doc_id":"K201039","page_num":9,"bbox":[82.85,487.97,529.14,702.46],"n_rows":9,"n_cols":10,"columns":["Steatosis\nBoundary","","Grade 0 vs","","","Grades 0 & 1 vs","","","Grades 0-2 vs",""],"rows":[["Steatosis\nBoundary","","Grade 0 vs","","","Grades 0 & 1 vs","","","Grades 0-2 vs",""],["","","Grades 1-3","","","Grades 2 & 3","","","Grade 3",""],["VLFF Threshold\n(%)","4.1","","","12.1","","","16.2","",""],["HepaFat-Scan","","","","","","","","",""],["Sensitivity (%)\n(95% CI)","96.1 (91.2% to 98.3%)","","","88.6 (79.7% to 93.9%)","","","94.4 (74.2% to 99.0%)","",""],["Specificity (%)\n(95% CI)","88.2 (65.7% to 96.7%)","","","78.8 (67.5% to 86.9%)","","","74.8 (66.6% to 81.5%)","",""],["HepaFat-AI","","","","","","","","",""],["Sensitivity (%)\n(95% CI)","97.6 (93.3% to 99.2%)","","","86.1 (76.8% to 92.0%)","","","100.0 (81.6% to 100.0%)","",""],["Specificity (%)\n(95% CI)","88.2 (65.7% to 96.7%)","","","74.8 (66.6% to 81.5%)","","","71.4 (62.4% to 78.1%)","",""]],"caption_candidate":"biopsy at the three previously determined VLFF thresholds.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201103-p5-t0","doc_id":"K201103","page_num":5,"bbox":[149.34,560.1,470.76,615.84],"n_rows":4,"n_cols":2,"columns":["Device Name","Xeleris 4.0 Processing and Review Workstation"],"rows":[["Device Name","Xeleris 4.0 Processing and Review Workstation"],["510 (K) number","K153355"],["Regulation Nº","892.2050"],["Product Code","LLZ"]],"caption_candidate":"Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201103-p6-t0","doc_id":"K201103","page_num":6,"bbox":[149.34,118.32,470.76,174.06],"n_rows":4,"n_cols":2,"columns":["Device Name","EXINI’s aBSI"],"rows":[["Device Name","EXINI’s aBSI"],["510 (K) number","K191262"],["Regulation Nº","892.2050"],["Product Code","LLZ"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201103-p6-t1","doc_id":"K201103","page_num":6,"bbox":[149.34,187.92,470.76,243.66],"n_rows":4,"n_cols":2,"columns":["Device Name","GE’s Hepatic VCAR"],"rows":[["Device Name","GE’s Hepatic VCAR"],["510 (K) number","K133649"],["Regulation Nº","892.1750"],["Product Code","JAK, LLZ"]],"caption_candidate":"Product Code LLZ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201103-p10-t0","doc_id":"K201103","page_num":10,"bbox":[149.34,118.32,523.68,412.32],"n_rows":4,"n_cols":3,"columns":["Attribute","Predicate Device: Xeleris 4.0","Proposed Device: Xeleris V"],"rows":[["Attribute","Predicate Device: Xeleris 4.0","Proposed Device: Xeleris V"],["General\nWorkflows","Xeleris 4.0’s workflows use\nboth manual and automated\nprocesses.","Xeleris V’s workflows continue\nuse both manual and automated\nprocesses. Xeleris V also includes\ntwo new, DL-based automatic\nsegmentation algorithms."],["Use of\nDeep\nLearning","Xeleris 4.0 does not contain\nany DL processes/algorithms.","Xeleris V introduces two new DL-\nbased algorithms for:\n• Lung fissure segmentation as\nan alternative to the manual\nmethod.\n• Kidney segmentation as an\nenhancement to the non-DL\nautomatic segmentation."],["Hardware\nNeeded to\nSupport\nXeleris V’s\nsoftware","Xeleris 4.0 offered with a GE\nworkstation or as software\nthat can be loaded onto the\ncustomer’s workstation that\nmeets specification.","In addition to the two options for\nthe predicate, with Xeleris V the\nsoftware can also be installed on a\nremote server."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201195-p7-t0","doc_id":"K201195","page_num":7,"bbox":[84.63,124.5,545.37,315.12],"n_rows":5,"n_cols":6,"columns":["","Workflow","","","Workflow-specific Features",""],"rows":[["","Workflow","","","Workflow-specific Features",""],["MM Oncology No New Features","","","","",""],["MI General (MI Reading / Auto Lung 3D\nSPECT Processing) Dynamic Summing\nAutomatic Layouts\nAuto Ranges\nScanner Data Support for Organ Processing\nUsability Improvements","","","","",""],["MI Cardiology Normalization by Rate-Pressure Product (syngo MBF)\nCardiac Masking\nCardiac Auto Ranges\nUsability Improvements\nUpdates / redeployment to third party software","","","","",""],["","MI Neurology","","","Normals Database for FDOPA (Scenium)",""]],"caption_candidate":"software (K191309 and K110494) include the following new features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201232-p5-t0","doc_id":"K201232","page_num":5,"bbox":[85.34,394.25,551.38,725.26],"n_rows":4,"n_cols":4,"columns":["","Limbus AI","Radiomics App v1.0 –\nK173420","Similarities /\nDifferences"],"rows":[["","Limbus AI","Radiomics App v1.0 –\nK173420","Similarities /\nDifferences"],["Classification\nRegulation","892.2050 – Picture Archiving\nand Communication System","892.2050 – Picture Archiving\nand Communication System","Same"],["Product Code","LLZ","LLZ","Same"],["Indications for\nUse","Limbus Contour is a software-\nonly medical device intended\nfor use by trained radiation\noncologists, dosimetrists and\nphysicists to derive optimal\ncontours for input to radiation\ntreatment planning.\nSupported image modalities\nare Computed Tomography\nand Magnetic Resonance. The\nLimbus Contour Software\nassists in the following\nscenarios:\n• Operates in conjunction with\nradiation treatment planning\nsystems or DICOM viewing\nsystems to load, save, and\ndisplay medical images and\ncontours for treatment\nevaluation and treatment\nplanning.","Microsoft Radiomics App v1.0\nis a software-only medical\ndevice intended for use by\ntrained radiation oncologists,\ndosimetrists and physicists to\nderive optimal organ and\ntumor contours for input to\nradiation treatment planning.\nSupported image modalities\nare Computed Tomography\nand Magnetic Resonance.\nRadiomics App assists in the\nfollowing\nscenarios:\n• Load, save and display of\nmedical images and contours\nfor treatment evaluation and\ntreatment planning.\n• Creation, transformation, and\nmodification of contours for","Indications for\nuse are similar\nother than the\ndevice not\ndisplaying\nmedical\nimages and\ncontours.\nRelated to that\ndifference; the\ndevice is also\nnot capable of\nfusing\ncompatible\nimages for\ntreatment\nplanning or\nthree-\ndimensional\nrendering of\nmedical"]],"caption_candidate":"automatic contouring test to ensure the contours were accurate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201232-p6-t0","doc_id":"K201232","page_num":6,"bbox":[85.34,72.24,551.38,732.1],"n_rows":4,"n_cols":4,"columns":["","• Creation, transformation, and\nmodification of contours for\napplications including, but not\nlimited to: transferring\ncontours to radiotherapy\ntreatment planning systems,\naiding adaptive therapy and\narchiving contours for patient\nfollow-up.\n• Localization and definition\nof healthy anatomical\nstructures.\nLimbus Contour is not\nintended for use with digital\nmammography.\nLimbus Contour is not\nintended to automatically\ncontour tumors or tumor\nclinical target volumes.","applications including, but not\nlimited to: transferring\ncontours to radiotherapy\ntreatment planning systems,\naiding adaptive therapy, and\narchiving contours for patient\nfollowup.\n• Localization and definition of\nboth solid tumors and healthy\nanatomical structures.\n• Fusion display of compatible\nimages for treatment planning.\n• Three-dimensional rendering\nof medical images and the\nsegmented contours.\nImages reviewed using the\nRadiomics App software\nshould not be used for primary\nimage interpretations.\nRadiomics App is not for use\nwith digital mammography.","images and\nsegmented\ncontour.\nUnlike the\npredicate\ndevice, the\nLimbus\nContour does\nnot display\nimages, and\ntherefore it\ncannot be used\nfor “primary\nimage\ninterpretations”\nso that is not\nincluded in the\nLimbus\nContour\nindications.\nIn addition, the\ndevice only\nlocalizes and\ndefines healthy\nanatomical\nstructures (not\nsolid tumors\nlike the\npredicate\ndevice)."],"rows":[["","• Creation, transformation, and\nmodification of contours for\napplications including, but not\nlimited to: transferring\ncontours to radiotherapy\ntreatment planning systems,\naiding adaptive therapy and\narchiving contours for patient\nfollow-up.\n• Localization and definition\nof healthy anatomical\nstructures.\nLimbus Contour is not\nintended for use with digital\nmammography.\nLimbus Contour is not\nintended to automatically\ncontour tumors or tumor\nclinical target volumes.","applications including, but not\nlimited to: transferring\ncontours to radiotherapy\ntreatment planning systems,\naiding adaptive therapy, and\narchiving contours for patient\nfollowup.\n• Localization and definition of\nboth solid tumors and healthy\nanatomical structures.\n• Fusion display of compatible\nimages for treatment planning.\n• Three-dimensional rendering\nof medical images and the\nsegmented contours.\nImages reviewed using the\nRadiomics App software\nshould not be used for primary\nimage interpretations.\nRadiomics App is not for use\nwith digital mammography.","images and\nsegmented\ncontour.\nUnlike the\npredicate\ndevice, the\nLimbus\nContour does\nnot display\nimages, and\ntherefore it\ncannot be used\nfor “primary\nimage\ninterpretations”\nso that is not\nincluded in the\nLimbus\nContour\nindications.\nIn addition, the\ndevice only\nlocalizes and\ndefines healthy\nanatomical\nstructures (not\nsolid tumors\nlike the\npredicate\ndevice)."],["Intended User","Healthcare providers","Healthcare providers","Same"],["Contouring\nModes","Automatic","Assisted and Automatic","Contours\ngenerated from\nLimbus\nContour are\nedited in\nexternal\ntreatment-\nplanning or\ncontouring\ntools."],["Measurements","No measurement function.","2D distance measurement,\naverage tissue density within a\nregion (for CT), segmentation\nvolume","Limbus\nContour does\nnot contain an\nimage viewer.\nNo\nmeasurement\nfunctionality is\nprovided\nbecause of this.\nThese"]],"caption_candidate":"Limbus AI Limbus Contour 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201232-p7-t0","doc_id":"K201232","page_num":7,"bbox":[85.34,72.24,551.38,726.46],"n_rows":10,"n_cols":4,"columns":["","","","measurements\nare not\nnecessary to\nachieve\nintended use."],"rows":[["","","","measurements\nare not\nnecessary to\nachieve\nintended use."],["Image Fusion","No fusion support.","Fuse only two 3D images, CT\nand MR","Limbus\nContour does\nnot perform\nimage fusion\nand subsequent\ncontouring on\nfused images.\nNot necessary\nto achieve\nintended use."],["3D image\nrendering","No image rendering function.","Yes","Limbus\nContour does\nnot contain a\nviewer. Images\nare rendered in\na separate\nviewing tool."],["Image Modalities","CT and MR","CT and MR","Same"],["Platform","Stand-alone package which\noperates on Microsoft\nWindows operating system\nand MacOS operating system","Stand-alone package which\noperates on Microsoft\nWindows operating system\nonly.","Limbus\nContour will\nalso support\nMac OS\noperating\nsystems"],["Environment of\nUse","Healthcare environment","Healthcare environment","Same"],["Materials","N/A – Standalone Software","N/A – Standalone Software","Same"],["Energy Source","N/A – Standalone Software","N/A – Standalone Software","Same"],["Feature\nComparison:\n(cid:120) Operating\nSystem\n(cid:120) Hardware\nRequirements\n(cid:120) Etc.","Operating System\n(cid:120) Windows 10 / Windows\nServer 2016\n(cid:120) Mac OS 10.14\nHardware Requirements\n(cid:120) 2 GHz or faster multi-core\nprocessor\n(cid:120) 4 GB of RAM\n(cid:120) For GPU versions, a\nCUDA capable NVIDIA\nGPU is required","(cid:120) Not specified.",""],["Performance\nTesting","Two different types of\nverification testing were\nconducted to verify the\nsoftware requirements:","Two different types of\nverification testing were\nconducted to verify the\nsoftware requirements:","Rendering and\nmeasurement\ntests are not\napplicable for\nthe subject"]],"caption_candidate":"Limbus AI Limbus Contour 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201310-p6-t0","doc_id":"K201310","page_num":6,"bbox":[40.58,97.28,572.14,707.28],"n_rows":16,"n_cols":3,"columns":["","Subject Device:","Predicate Device:"],"rows":[["","Subject Device:","Predicate Device:"],["","MaxQ AI AccipioIx","MaxQ AI AccipioIx"],["","","(K182177)"],["Intended Use /\nIndications for Use","AccipioIx is a software workflow\ntool designed to aid in prioritizing\nthe clinical assessment of adult\nnon-contrast head CT cases with\nfeatures suggestive of acute\nintracranial hemorrhage in the\nacute care environment. AccipioIx\nanalyzes cases using an artificial\nintelligence algorithm to identify\nsuspected findings. It makes case-\nlevel output available to a\nPACS/workstation for worklist\nprioritization or triage.\nAccipioIx is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\nacute intracranial hemorrhage. Its\nresults are not intended to be used\non a stand- alone basis for clinical\ndecision-making nor is it intended\nto rule out hemorrhage or\notherwise preclude clinical\nassessment of CT cases.","AccipioIx is a software workflow\ntool designed to aid in prioritizing\nthe clinical assessment of adult\nnon-contrast head CT cases with\nfeatures suggestive of acute\nintracranial hemorrhage in the\nacute care environment. AccipioIx\nanalyzes cases using an artificial\nintelligence algorithm to identify\nsuspected findings. It makes case-\nlevel output available to a\nPACS/workstation for worklist\nprioritization or triage.\nAccipioIx is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\nacute intracranial hemorrhage. Its\nresults are not intended to be used\non a stand- alone basis for clinical\ndecision-making nor is it intended\nto rule out hemorrhage or\notherwise preclude clinical\nassessment of CT cases."],["Population","Adult patients (21 years of age and\nolder) indicated for head CT","Adult patients (21 years of age and\nolder) indicated for head CT"],["Notification-only, parallel workflow\ntool","Yes","Yes"],["Intended users","Hospital networks and trained\nclinicians","Hospital networks and trained\nclinicians"],["Setting","Acute care","Acute care"],["Identify patients with a pre-\nspecified clinical condition","Yes","Yes"],["Clinical condition","Cerebrovascular Event:\nIntracranial hemorrhage","Cerebrovascular Event:\nIntracranial hemorrhage"],["Alert to finding","Yes; flagged for review","Yes; flagged for review"],["Independent of standard of care\nworkflow","Yes; No cases are removed from\nworklist","Yes; No cases are removed from\nworklist"],["Modality","Non-Contrast head CT","Non-Contrast head CT"],["Artificial Intelligence algorithm","Yes","Yes"],["Software segmentation method","CNN-based segmentation","Machine-vision based segmentation"],["Case level assessment of clinical\ncondition probability","Yes – case-level assessment is\nderived both from detection of\nindividual aICH findings and\nalgorithmic assessment of the full\ncase.","Yes – case-level assessment is\nderived from detection of individual\naICH findings"]],"caption_candidate":"A summary table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201310-p7-t0","doc_id":"K201310","page_num":7,"bbox":[40.56,72.24,572.16,389.52],"n_rows":7,"n_cols":3,"columns":["Limited to analysis of imaging data","Yes","Yes"],"rows":[["Limited to analysis of imaging data","Yes","Yes"],["Non-Diagnostic DICOM Preview","No","No"],["Aids prompt identification and\nprioritization of cases with\nindicated findings","Yes","Yes"],["Medical systems/devices used in\nconjunction with the device","1. Device is used with CT systems\nfor DICOM input and with PACS\nsystems, which may present/use\nthe data.\n2. Device is used with Medical\nImage Communications Devices\n(MICDs), such as the Accipio\nAgent, to receive native CT\nimages for processing and to\ngenerate visual results","1. Device is used with CT systems\nfor DICOM input and with PACS\nsystems, which may present/use\nthe data.\n2. Device is used with Medical\nImage Communications Devices\n(MICDs), such as the Accipio\nAgent, to receive native CT\nimages for processing and to\ngenerate visual results"],["Output","Suspected hemorrhage /\nNo suspected hemorrhage","Suspected hemorrhage /\nNo suspected hemorrhage"],["Systems where results are\ndisplayed","PACS / Workstation","PACS / Workstation"],["Performance results","Sensitivity- 97%\n(95% CI: 92.8% - 98.8%)\nSpecificity- 93%\n(95% Cl: 88.6% - 96.6%)\nProcessing time – 1.17 minutes\n(95% Cl: 1.16 – 1.18 minutes)","Sensitivity - 92%\n(95% CI: 87.29 - 95.68%)\nSpecificity - 86%\n(95% CI: 80.18 - 90.81%)\nProcessing time – 4.1 minutes\n(95% CI: 3.8 - 4.3 minutes)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201369-p4-t0","doc_id":"K201369","page_num":4,"bbox":[108.0,238.92,320.16,640.92],"n_rows":47,"n_cols":2,"columns":["Date of Preparation",": September 14, 202"],"rows":[["Date of Preparation",": September 14, 202"],["",""],["","​"],["Prepared by:","Sadaf Monajemi, Ph"],["Manufacturer:","See-Mode Technolog"],["","32 Carpenter Street"],["","Singapore 059911"],["","SINGAPORE"],["","Email: sadaf@see-m"],["","​"],["",""],["","Tel: +61 415 952 78"],["","www.see-mode.com"],["",""],["Official Contact:","Dr. Sadaf Monajemi,"],["","See-Mode Technolog"],["","32 Carpenter Street"],["","Singapore 059911"],["","SINGAPORE"],["","Email: sadaf@see-m"],["","www.see-mode.com"],["",""],["E NAME AND CLASSI","FICATION"],["",""],["Trade/Proprietary","Name: AVA (Augme"],["",""],["Common Name: Pict","​\nure archiving and co"],["​",""],["",""],["Regulation Number",": 21 CFR 892.2050"],["","​"],["Regulation Name: P","icture archiving and"],["",""],["​",""],["",""],["Classification Name",": System, Image Proc"],["",""],["","​"],["Review Panel: Radio","logy"],["",""],["​",""],["",""],["Regulatory Class: C","lass II"],["",""],["​",""],["Product Code: LLZ",""],["",""]],"caption_candidate":"Date of Preparation: September 14, 2020","well_formed":true,"extraction_settings":"text"}
{"table_id":"K201369-p6-t0","doc_id":"K201369","page_num":6,"bbox":[53.62,428.62,573.38,710.62],"n_rows":7,"n_cols":4,"columns":["","Subject Device","Predicate Device","Notes"],"rows":[["","Subject Device","Predicate Device","Notes"],["Manufacturer","See-Mode Technologies Pte. Ltd.","Atheropoint LLC",""],["Product name","See-Mode AVA (Augmented Vascular\nAnalysis)","AtheroEdge",""],["510(k) number","Via this submission","K122022",""],["Classification","Class II - 90 LLZ 892.2050/LLZ","Class II - 90 LLZ\n892.2050/LLZ","Same"],["Intended Use","Analysis and reporting of vascular\nultrasound images","Analysis and reporting of\nvascular ultrasound images","Same"],["Indications for Use\n​","See-Mode AVA (Augmented Vascular\nAnalysis) is a stand-alone, image\nprocessing software for analysis,\nmeasurement, and reporting of\nDICOM-compliant vascular ultrasound\nimages obtained from carotid and lower","The AtheroEdgeTM\nsoftware is a\nWindows-based application\nprogram used on a personal\ncomputer for an automatic\nmeasurement of the","Nearly the\nsame. See\ndiscussion\nbelow."]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201369-p7-t0","doc_id":"K201369","page_num":7,"bbox":[53.62,139.08,573.38,704.62],"n_rows":7,"n_cols":4,"columns":["","limb arteries. The analysis includes\nsegmentation of vessels walls and\nmeasurement of the intima-media\nthickness (IMT) of the carotid artery in\nB-Mode images, finding velocities in\nDoppler images, and reading annotations\non the images. The software generates a\nvascular ultrasound report based on the\nimage analysis results to be reviewed and\napproved by a qualified clinician after\nperforming quality control. The client\nsoftware is designed to run on a standard\ndesktop or laptop computer.\nSee-Mode AVA is intended to be used by\ntrained medical professionals, including\nbut not limited to physicians and medical\ntechnicians. The software is not intended\nto be used as an independent source of\nmedical advice, or to determine or\nrecommend a course of action or\ntreatment for patients.","Intima-Media Thickness\n(IMT) of the carotid artery\nfrom images obtained from\nultrasound systems.",""],"rows":[["","limb arteries. The analysis includes\nsegmentation of vessels walls and\nmeasurement of the intima-media\nthickness (IMT) of the carotid artery in\nB-Mode images, finding velocities in\nDoppler images, and reading annotations\non the images. The software generates a\nvascular ultrasound report based on the\nimage analysis results to be reviewed and\napproved by a qualified clinician after\nperforming quality control. The client\nsoftware is designed to run on a standard\ndesktop or laptop computer.\nSee-Mode AVA is intended to be used by\ntrained medical professionals, including\nbut not limited to physicians and medical\ntechnicians. The software is not intended\nto be used as an independent source of\nmedical advice, or to determine or\nrecommend a course of action or\ntreatment for patients.","Intima-Media Thickness\n(IMT) of the carotid artery\nfrom images obtained from\nultrasound systems.",""],["Image Source","Ultrasound images","Ultrasound images","Same"],["Rx only?","Yes","Yes","Same"],["Operating\nPlatform","The software runs on a standard\n“off-the-shelf” computer and can be\naccessed within the software client web\nbrowser.","Stand-alone application\nprogram for use on a\npersonal computer with\nMicrosoft Windows.","Nearly the\nsame. See\ndiscussion\nbelow."],["Image Format","DICOM","DICOM, JPEG and Windows\nBMP","Same"],["Image storage and\nreport generation","Yes","Yes","Same"],["Automatic\ndistance\nmeasurement of\nthe Intima- Media\nthickness of\ncarotid artery","Yes","Yes","Same"]],"caption_candidate":"AVA (Augmented Vascular Analysis)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201369-p8-t0","doc_id":"K201369","page_num":8,"bbox":[53.62,139.08,573.38,259.12],"n_rows":2,"n_cols":4,"columns":["Image\nCompression","JPEG Loss-less","JPEG Loss-less","Same"],"rows":[["Image\nCompression","JPEG Loss-less","JPEG Loss-less","Same"],["Target Population","As the device is prescription only, the\ntarget population of the device is anyone\nin the general population that receives\nthe relevant carotid or lower limb artery\nultrasound scan","As the device is prescription\nonly, the target population of\nthe device is anyone in the\ngeneral population that\nreceives the relevant carotid\nultrasound scan","Same"]],"caption_candidate":"AVA (Augmented Vascular Analysis)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201411-p4-t0","doc_id":"K201411","page_num":4,"bbox":[61.82,184.22,305.85,748.78],"n_rows":55,"n_cols":2,"columns":["Name","Visage Imaging GmbH"],"rows":[["Name","Visage Imaging GmbH"],["",""],["Address","Lepsiusstrasse 70"],["",""],["","12163 Berlin"],["",""],["","Germany"],["",""],["Contact Person","Stefan Strowich"],["",""],["","Manager of Quality Systems an"],["",""],["E-mail","sstrowich@visageimaging.com"],["",""],["Phone Number","+49 30 700968-41"],["",""],["Date Prepared","January 28, 2021"],["",""],["evice",""],["",""],["Trade Name","Visage Breast Density"],["",""],["Common Name","Medical Imaging Software"],["",""],["Classification Name","Automated Radiological Image"],["",""],["Regulatory Number","21 CFR 892.2050"],["",""],["Product Code","QIH"],["",""],["Device Class","Class II"],["",""],["Review Panel","Radiology"],["",""],["redicate Device",""],["",""],["Trade Name","PowerLook Density Assessmen"],["",""],["Common Name","Medical Imaging Software"],["",""],["Classification Name","System, Image Processing, Rad"],["",""],["Regulatory Number","21 CFR 892.2050"],["",""],["Product Code","LLZ"],["",""],["Device Class","Class II"],["",""],["Review Panel","Radiology"],["",""],["Submitter","iCAD, Inc."],["",""],["510(k) Number","K180125"],["",""],["Clearance","April 5, 2018"]],"caption_candidate":"Name Visage Imaging GmbH","well_formed":true,"extraction_settings":"text"}
{"table_id":"K201444-p6-t0","doc_id":"K201444","page_num":6,"bbox":[72.27,467.32,525.33,714.9],"n_rows":3,"n_cols":6,"columns":["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],"rows":[["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],["Routine\nContouring","","","Routine Contouring tools (e. g. freehand drawing tools, creation of margins\netc.)\nModification:improvements in the contour interpolation tool and a tool to\nmerge multiple structures.","",""],["Advanced\nContouring","","","Advanced Contouring tools (automatic contouring of different structures,\nnudge 3D tool,contour interpolation.). Automatic contouring of pelvic and\nhead/neck regions, support of Rapid Results Technology.\nModification: This subject device provides the following extensions:\n• Automatic Contouring can be applied on further structures (thoracic and\npelvic regions)\n• Automatic Contouring in the head/neck region, which was previously atlas-\nbased, is now done with deep learning. The atlas method is entirely removed\nfrom this version.\n• Streamlined workflow to automatically adapt contours from a prior to a\ncurrent planning CT","",""]],"caption_candidate":"provided as Table 4 below for the software version SOMARIS/8 VB50:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201444-p7-t0","doc_id":"K201444","page_num":7,"bbox":[72.24,77.46,525.36,373.68],"n_rows":2,"n_cols":2,"columns":["Structure Set\nManagement","• Loading and storing of DICOM RT structure sets, creating, editing and\ndeletion of structures and POIs.\n• Creating, editing and deletion of structure templates.\n• Customize predefined structure database with mapping to international\nnomenclature schemes.\nModification:\n• multiselection of structures and POIs to apply basic operations such as copy\nor delete,\n• auto-completion for structure names,\n• manual and automatic save function for structure sets,\n• and modifications in the user interface of structure database and template\ncreation."],"rows":[["Structure Set\nManagement","• Loading and storing of DICOM RT structure sets, creating, editing and\ndeletion of structures and POIs.\n• Creating, editing and deletion of structure templates.\n• Customize predefined structure database with mapping to international\nnomenclature schemes.\nModification:\n• multiselection of structures and POIs to apply basic operations such as copy\nor delete,\n• auto-completion for structure names,\n• manual and automatic save function for structure sets,\n• and modifications in the user interface of structure database and template\ncreation."],["Deformable\nAlignment","Deformable registration of images of the same patient acquired with the same\nor different modalities within different imaging sessions. The transformation\nallows for local deformation to adapt to changing anatomy (many degrees of\nfreedom).\nModification: The deformation visualization tool was simplified and now\nutilizes color-coded vectors to display the deformation vector field and its\nmagnitude at the same time. The visualization is restricted to the patient outline\nfor CT images."]],"caption_candidate":"Traditional 510(k): syngo.via RT Image Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201444-p9-t0","doc_id":"K201444","page_num":9,"bbox":[72.02,199.26,525.58,431.76],"n_rows":7,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Date of","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Date of","","","Standards",""],["","","","","Recognitio","","","Development",""],["","","","","n","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications\nin Medicine (DICOM) Set; PS 3.1 –\n3.20","06/27/2016","","","NEMA","",""],["13-32","Software","Medical Device Software –Software\nLife Cycle Processes; 62304:2006 (1st\nEdition)","01/14/2019","","","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformati\ncs","Medical devices – Application of risk\nmanagement to medical devices; 14971\nSecond Edition 2007-03-01","06/27/2016","","","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application\nof usability engineering to medical\ndevices\nIEC 62366-1:2015","12/23/2016","","","IEC","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201560-p5-t0","doc_id":"K201560","page_num":5,"bbox":[129.37,157.82,540.35,253.7],"n_rows":7,"n_cols":2,"columns":["","Predicate Device"],"rows":[["","Predicate Device"],["Trade Name","ClearRead Detect"],["Classification Name","Medical image analyzer"],["Product Code","MYN"],["Regulation","21 CFR 892.2070"],["PMA#","P000041"],["Decision Date","July 12, 2001"]],"caption_candidate":"F. Decision Date: July 12, 2001","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201560-p6-t0","doc_id":"K201560","page_num":6,"bbox":[129.31,88.08,483.77,708.82],"n_rows":17,"n_cols":4,"columns":["","","Predicate Device","Proposed Device"],"rows":[["","","Predicate Device","Proposed Device"],["Device Name","","ClearRead Detect","Auto Lung Nodule\nDetection"],["Manufacture","","Riverain Medical Group,\nLLC","Samsung Electronics"],["PMA Number","","PMA P000041","-"],["Indication for use","","CLEARREAD DETECT is\na computer-aided detection\n(CAD) system intended to\nidentify and mark regions\nof interest (ROIs) on\ndigitized frontal chest\nradiographs. It identifies\nfeatures associated with\nsolitary pulmonary nodules\nfrom 9 to 30 mm in size,\nwhich could represent\nearly-stage lung cancer.\nThe device is intended for\nuse as an aid only after the\nphysician has performed\nan initial interpretation of\nthe radiograph.","The Auto Lung Nodule\nDetection is computer-\naided detection software to\nidentify and mark regions\nin relation to suspected\npulmonary nodules from 10\nto 30 mm in size. It is\ndesigned to aid the\nphysician to review the PA\nchest radiographs of adults\nas a second reader and be\nused as part of S-Station,\nwhich is operation software\ninstalled on Samsung\nDigital X-ray Imaging\nsystems. Auto Lung Nodule\nDetection cannot be used\non the patients who have\nlung lesions other than\nabnormal nodules."],["Intended users","","Physician","Physician"],["Intended body part","","Chest","Chest"],["Imaging modality","","X-ray","X-ray"],["Key feature","","Identification of lung\nnodules","Identification of lung\nnodules"],["Technology","","heuristic decision rules,\nartificial neural network, and\nfuzzy logic","Machine learning"],["Operating systems","","Standard PC/Windows","Standard PC/Windows"],["Input","Image\ntype","DICOM","DICOM"],["","Applicable\nProtocols","Chest PA/AP","Chest PA"],["Output","Output\ntype","ROI marked on the\nduplicated input image","Information for ROI to be\nmarked on the duplicated\ninput image"],["","Marker\ntype/size","Circular/Adjustable","Circular/Fixed"],["","Report","The number of findings","The number of nodule\nmarkers"],["Reader workflow","","Second reader workflow","Second reader workflow"]],"caption_candidate":"510(k) Premarket Notification - Traditional","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201615-p4-t0","doc_id":"K201615","page_num":4,"bbox":[72.2,185.2,509.6,716.2],"n_rows":8,"n_cols":2,"columns":["Date:","June 10, 2020"],"rows":[["Date:","June 10, 2020"],["Submitter:","GE Medical Systems, LLC (GE Healthcare)\n3200 N. Grandview Blvd.,\nWaukesha, WI 53188\nUSA"],["Primary Contact Person:","Brian R. Zielski\nRegulatory Affairs Leader\nPhone: 262-521-6609\nEmail: Brian.Zielski@GE.com"],["Secondary Contact Person:","James McMahon\nSenior Director, Regulatory Affairs\nPhone: 508-382-2858\nEmail: James.D.McMahon@GE.com"],["Device Trade Name:","SIGNA 7.0T"],["Common/Usual Name:","Magnetic Resonance Diagnostic Device"],["Classification Names:\nRegulation Number:","Magnetic Resonance Diagnostic Device\n21 CFR 892.1000"],["Product Code:\nPrimary:\nSecondary:","LNH\nLNI, MOS"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201615-p5-t0","doc_id":"K201615","page_num":5,"bbox":[72.2,111.8,509.6,709.2],"n_rows":4,"n_cols":2,"columns":["Predicate Device(s):","SIGNA Premier (K193282)"],"rows":[["Predicate Device(s):","SIGNA Premier (K193282)"],["Device Description:","SIGNA 7.0T is a high performance magnetic resonance\nimaging system designed to support high resolution\nimaging at 7.0T in particular anatomical regions\ndetermined by the available RF coils. The system includes\na 7.0T superconducting magnet and an ultra-high\nperformance gradient coil with a 60 cm patient bore,\nsupporting scanning in axial, coronal, sagittal, oblique,\nand double oblique planes using a variety of pulse\nsequences, imaging techniques, acceleration methods,\nand reconstruction algorithms."],["Indications for Use","The SIGNA 7.0T system is a whole-body magnetic resonance\nscanner designed to support high resolution, high signal-to-\nnoise ratio, and short scan times. It is indicated for use as a\ndiagnostic imaging device to produce axial, sagittal, coronal,\nand oblique images, spectroscopic images, parametric maps,\nand/or spectra, dynamic images of the structures and/or\nfunctions of the head and extremities.\nThe images produced by the SIGNA 7.0T system reflects the\nspatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance. These images and/or spectra\nwhen interpreted by a trained physician yield information that\nmay assist in diagnosis.\nThe device is intended for patients > 20 kg / 44 lb."],["Comparison of Indications for\nUse","The changes in technology do not impact the indications\nfor use. The indications for use have not changed, other\nthan to reflect the SIGNA 7.0T product name and\nsimplified anatomy of head and extremities, and patient\nweight limit."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201615-p6-t0","doc_id":"K201615","page_num":6,"bbox":[72.2,111.8,509.6,716.2],"n_rows":2,"n_cols":2,"columns":["","Therefore, the intended use is the same as the predicate\ndevice in accordance with FDA’s guidance document “The\n510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)]”, dated 28 July 2014."],"rows":[["","Therefore, the intended use is the same as the predicate\ndevice in accordance with FDA’s guidance document “The\n510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)]”, dated 28 July 2014."],["Technology:","The SIGNA 7.0T employs the same fundamental scientific\ntechnology as the predicate device.\nSystem Design:\nThe most notable technological difference between the\nSIGNA 7.0T and the predicate device is the 7.0T B0\nmagnetic field compared to 3.0T. The SIGNA 7.0T design\nenables the capabilities that this higher B0 magnetic field\ncontributes to MR imaging through the following key\ndifferences:\n• RF Transmit chain: The SIGNA 7.0T employs\nmultiple and independent channels for RF\ntransmission, and dedicated receiver array coils\nand detectors for high sensitivity signal reception.\n• Gradient system: The SIGNA 7.0T can deliver a\nmaximum gradient amplitude of 113 mT/m and\nmaximum gradient slew rate of 260 T/m/s\ncompared to the predicate’s maximum gradient\namplitude of 80 mT/m and maximum gradient\nslew rate of 200 T/m/s.\n• Applications: The SIGNA 7.0T uses the SIGNA\nWorks suite of applications, optimized for the\nadvanced hardware and for the higher field\nstrength to generate high resolution functional,\nstructural, anatomical, vascular, and\nspectroscopic images.\nOperating Principles: The SIGNA 7.0T functions using the\nsame operating principles as the predicate device.\nMaterials: The SIGNA 7.0T and the predicate device both\nuse flame retardant materials.\nSafety and Performance Testing: Both the SIGNA 7.0T\nand the predicate device comply with the same safety\nand performance testing (see Determination of\nSubstantial Equivalence, below)."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201615-p7-t0","doc_id":"K201615","page_num":7,"bbox":[72.2,111.8,509.6,693.6],"n_rows":2,"n_cols":2,"columns":["","These technological differences do not raise any different\nquestions regarding safety and effectiveness. Both\ndevices must address questions of whether they provide\nan adequate level of image quality appropriate for\ndiagnostic use. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the image quality performance\nof SIGNA 7.0T compared to the predicate device."],"rows":[["","These technological differences do not raise any different\nquestions regarding safety and effectiveness. Both\ndevices must address questions of whether they provide\nan adequate level of image quality appropriate for\ndiagnostic use. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the image quality performance\nof SIGNA 7.0T compared to the predicate device."],["Determination of Substantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe SIGNA 7.0T and the predicate device were subject to\nsimilar risk management testing to demonstrate substantial\nequivalence of safety and performance. Testing to the\nfollowing voluntary standards includes:\n• ANSI/AAMI ES60601-1\n• AAMI/ANSI/IEC 60601-1-2\n• IEC 60601-2-33\n• AAMI/ANSI/IEC 62304\n• AAMI/ANSI/ISO 10993-1\nIn addition, the SIGNA 7.0T complies with applicable NEMA MS\nstandards for MRI and NEMA PS3 standards for DICOM, as\ndoes the predicate device.\nThe following quality assurance measures were applied to the\ndevelopment of the subject device, as they were for the\npredicate device:\n• Risk Analysis\n• Requirements Reviews\n• Design Reviews\n• Testing on unit level (Module verification)\n• Integration testing (System verification)\n• Performance testing (Verification)\n• Simulated use testing (Validation)"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201615-p8-t0","doc_id":"K201615","page_num":8,"bbox":[72.2,111.8,509.6,617.2],"n_rows":2,"n_cols":2,"columns":["","Summary of Clinical Tests:\nTo evaluate the image quality performance of the SIGNA 7.0T\nsystem, assessments were performed by GE MR internal\nClinical Applications Specialists and external Radiologist as part\nof a Reader Evaluation Study.\nThe reader study was performed on images acquired on the\nproposed 7.0T system and predicate 3.0T system. Image\nseries ranged from brain MR scans performed on normal\nsubjects and subjects with self-reported common\nneuropathology, as well as knee images over a broad age\nrange representative of a range of knee health.\nThe study involved 4 U.S. board-certified radiologists\nevaluating proposed device’s image diagnostic quality and\nusability, personal preferences, and general commentary using\nradiology terms against same subject images scanned on the\npredicate device.\nTo set the PNS limits for the SIGNA 7.0T system, a direct\ndetermination study was conducted with adult human\nvolunteers without reported pathology."],"rows":[["","Summary of Clinical Tests:\nTo evaluate the image quality performance of the SIGNA 7.0T\nsystem, assessments were performed by GE MR internal\nClinical Applications Specialists and external Radiologist as part\nof a Reader Evaluation Study.\nThe reader study was performed on images acquired on the\nproposed 7.0T system and predicate 3.0T system. Image\nseries ranged from brain MR scans performed on normal\nsubjects and subjects with self-reported common\nneuropathology, as well as knee images over a broad age\nrange representative of a range of knee health.\nThe study involved 4 U.S. board-certified radiologists\nevaluating proposed device’s image diagnostic quality and\nusability, personal preferences, and general commentary using\nradiology terms against same subject images scanned on the\npredicate device.\nTo set the PNS limits for the SIGNA 7.0T system, a direct\ndetermination study was conducted with adult human\nvolunteers without reported pathology."],["Conclusion:","The proposed SIGNA 7.0T was developed under GE\nHealthcare’s quality system and is at least as safe and effective\nas the legally marketed predicate device. The performance\ntesting did not identify any new hazards, adverse effects, or\nsafety or performance concerns that are significantly different\nfrom those associated with MR imaging in general.\nIn conclusion, GE Healthcare believes that SIGNA 7.0T is\nsubstantially equivalent to the predicate device, and is safe\nand effective for its intended use."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p6-t0","doc_id":"K201632","page_num":6,"bbox":[48.51,126.79,736.41,522.81],"n_rows":11,"n_cols":11,"columns":["Feature","","","Primary Predicate Device","","","Secondary Predicate Device","","Subject Device\nTOMTEC-ARENEA","Discussion / Comment",""],"rows":[["Feature","","","Primary Predicate Device","","","Secondary Predicate Device","","Subject Device\nTOMTEC-ARENEA","Discussion / Comment",""],["","","","TomTec-Arena","","","QLAB","","","",""],["","","","(K150122)","","","(K200974)","","","",""],["","GENERAL COMPARISON","","","","","","","","",""],["Intended Use","","TomTec-Arena software is a clinical\nsoftware package designed for\nreview, quantification and reporting of\nstructures and function based on\nmulti-dimensional digital medical data\nacquired with different modalities.\nTomTec-Arena is not intended to be\nused for reading of mammography\nimages.","","","QLAB Quantification software is a\nsoftware application package. It is\ndesigned to view and quantify image\ndata acquired on Philips ultrasound\nsystems.","","","TOMTEC-ARENA software is a\nclinical software package designed\nfor review, quantification and\nreporting of structures and function\nbased on multi-dimensional digital\nmedical data acquired with different\nmodalities.TOMTEC-ARENA is not\nintended to be used for reading of\nmammography images.","Intended Use of primary and subject\ndevice are identical\n(unchanged)Intended Use/Indications\nfor use of secondary predicate and\nsubject device are comparable and\nconsidered equivalent.",""],["Indications for\nUse","","Indications for use of TomTec-Arena\nTTA2 software are quantification and\nreporting of cardiovascular, fetal,\nabdominal structures and function of\npatients with suspected disease to\nsupport the physicians in the\ndiagnosis","","","QLAB Quantification software is a\nsoftware application package. It is\ndesigned to view and quantify image\ndata acquired on Philips ultrasound\nsystems.","","","Indications for use of TOMTEC-\nARENA TTA2 software are\nquantification and reporting of\ncardiovascular, fetal, abdominal\nstructures and function of patients\nwith suspected disease to support the\nphysicians in the diagnosis","Indications for use of primary and\nsubject device are identical\n(unchanged).\nIntended Use/Indications for use of\nsecondary predicate and subject\ndevice are comparable and\nconsidered equivalent.",""],["Anatomical Site","","Quantification and reporting of\ncardiovascular, fetal, and abdominal\nstructures and function.","","","Quantification of imaging data\nacquired from ultrasound machines of\nvarious anatomical structures and\nfunction.","","","Quantification and reporting of\ncardiovascular, fetal, and abdominal\nstructures and function.","Identical to primary and secondary\npredicate.",""],["where used\n(hospital, home,\nambulance, etc.)","","Hospitals, clinics, and physician´s\noffices.","","","Hospitals, clinics, and physician´s\noffices.","","","Hospitals, clinics, and physician´s\noffices.","Identical to primary and secondary\npredicate.",""],["Design","","Software as a medical device","","","Software as a medical device","","","Software as a medical device","Identical to primary and secondary\npredicate.",""],["","4D RV-FUNCTION","","","","","","","","",""],["Application\nDescription","","4D RV-Function provides a\ncomprehensive evaluation of the right\nventricle including volumes and strain\nanalysis. It provides EDV, ESV,\nRVEF, SV, RVLS, TAPSE and FAC.\nDistance measurements can also be\nanalyzed. This software\ndelivers a quick and reproducible\nanalysis of the right ventricle, thus","","","The 3D Auto RV Q-App is an\nintegration of the segmentation\nengine of the QLAB HeartModel and\nthe TOMTEC-ARENA 4D RV-\nFunction thereby providing a dynamic\nRight Ventricle clinical functionality.","","","The 4D RV-Function is a right\nventricular quantification tool for\nroutine clinical work, pulmonary\nhypertension, and right-sided heart\nfailure. The application helps to\novercome complexity of right-\nventricle analysis by calculating\nstandard values based on a semi-","Revised for clarity. Considered\nequivalent to primary predicate. No\nimpact to the safety or effectiveness\nof the device.\nComparable and considered\nequivalent to secondary predicate.\nThis modification to QLAB was\ncleared by K191647.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p7-t0","doc_id":"K201632","page_num":7,"bbox":[48.49,113.58,736.43,520.95],"n_rows":8,"n_cols":7,"columns":["","","increasing your diagnostic confidence\nby visualizing the complexity of the\nRV shape in 3D.","","automatically generated 3D surface\nmodel.","",""],"rows":[["","","increasing your diagnostic confidence\nby visualizing the complexity of the\nRV shape in 3D.","","automatically generated 3D surface\nmodel.","",""],["SW Version","","2.0","15.0","3.0","Updated due to changes to SW code.\nIntegrates HeartModel auto-\nsegmentation technology with 4D RV-\nFunction algorithm for RV border\nplacement.",""],["Measurements","","Volume and function of Right\nVentricle","EDVI\nESVI","Added:\nEDVI\nESVI","Added measurements are identical to\nsecondary predicate device.",""],["Export Formats:","","As cleared","Beutel value export into .stl and .obj\nformat","Added:\nBeutel value export into .stl and .obj\nformat","Identical to secondary predicate.\nWorkflow improvements for user\nconvenience.\nNo impact to the safety or\neffectiveness of the device.",""],["Contour\nGeneration","","3D surface model is created based\non user defined anatomical\nlandmarks. User is able to edit the\ncontour of the surface model.","3D surface model is created\nautomatically using machine learning\nalgorithms without user interaction.\nUser is able to edit, accept or reject\nthe contours or the anatomical\nlandmarks.","3D surface model is created\nautomatically using machine learning\nalgorithms without user interaction.\nUser is able to edit, accept or reject\nthe contours or the anatomical\nlandmarks.","Identical to secondary predicate.\nWorkflow improvements for user\nconvenience.\nNo impact to the safety or\neffectiveness of the device.",""],["","4D MV-ASSESSMENT","","","","",""],["Application\nDescription","","4D MV-Assessment is used for\ncomprehensive morphological and\nfunctional assessment of the mitral\nvalve. Based on an easy and intuitive\nworkflow the application package\ngenerates models of anatomical\nstructures such as MV annulus,\nleaflet and the closure line.\nAutomatically derived parameters\nallow quantification of pre- and post-\noperative valvular function and\ncomparison of morphology. 4D MV-\nAssessment improves the\npresentation of anatomy and findings\nand visualizes the complex\nmorphology and dynamics of the\nmitral valve.","The 3D Auto MV Q-App is a semi-\nautomatic tool that essentially is an\nintegration of the machine-learning\nderived segmentation engine of the\nQLAB HeartModel and the TOMTEC-\nArena TTA2 4D MV-Assessment\napplication thereby providing a\ndynamic Mitral Valve clinical\nquantification tool.","4D MV-ASSESSMENT provides a\nmorphological and functional analysis\nof the mitral valve (MV) using 3D/4D\nechocardiography data. Models of\nanatomical structures such as MV\nannulus, leaflets and the closure line\nare generated. The derived\nparameters allow quantification of\npre- and post-operative valvular\nfunction and a comparison of\nmorphology.","Revised for clarity. Considered\nequivalent to primary predicate. No\nimpact to the safety or effectiveness\nof the device.\nComparable and considered\nequivalent to secondary predicate.\nThis modification to QLAB was\ncleared by K200974-",""],["SW Version","","2.3","15.0","2.5","Updated due to changes to SW code.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p8-t0","doc_id":"K201632","page_num":8,"bbox":[48.5,113.58,736.42,480.3],"n_rows":5,"n_cols":7,"columns":["Measurements","","As cleared","Prolapse Height\nOpen Coaptation Gap\nOpen Coaptation Width\nOpen Coaptation Area 3D\nC-shaped Annulus\nDistal Anterior Leaflet Angle","Added:\nProlapse Height\nOpen Coaptation Gap\nOpen Coaptation Width\nOpen Coaptation Area 3D\nC-shaped Annulus\nDistal Anterior Leaflet Angle","Identical to secondary predicate.",""],"rows":[["Measurements","","As cleared","Prolapse Height\nOpen Coaptation Gap\nOpen Coaptation Width\nOpen Coaptation Area 3D\nC-shaped Annulus\nDistal Anterior Leaflet Angle","Added:\nProlapse Height\nOpen Coaptation Gap\nOpen Coaptation Width\nOpen Coaptation Area 3D\nC-shaped Annulus\nDistal Anterior Leaflet Angle","Identical to secondary predicate.",""],["Contour\nGeneration","","3D surface model is created based\non user defined anatomical\nlandmarks.\nUser is able to edit the contour of the\nsurface model before proceeding with\nthe workflow.","3D surface model is created semi-\nautomatically using machine learning\nalgorithm without user interaction.\nUser is able to edit, accept, or reject\nthe initial landmark proposals of the\nmitral valve anatomical locations.","3D surface model is created semi-\nautomatically using machine learning\nalgorithm without user interaction.\nUser is able to edit, accept, or reject\nthe initial landmark proposals of the\nmitral valve anatomical locations.","Identical to secondary predicate.\nWorkflow improvements for user\nconvenience in initial model display\nand landmark proposal.\nUser is still able to edit, accept or\nreject the contours.\nNo impact to the safety or\neffectiveness of the device.",""],["","4D LV-ANALYSIS","","","","",""],["Application\nDescription","","Volume quantification and function\nanalysis of the left ventricle based on\n3D data has proven to be more\naccurate and reproducible than using\n2D clips. 4D LV-Analysis is a vendor\nindependent offline solution for 3D\nspeckle tracking. It provides an\nautomated workflow for quantitative\nand reproducible analysis of left\nventricular deformation and global\nstrain values. 4D LV Function is a\nbasic application for the assessment\nof left ventricular volumes, EF and\nGLS while 4D LV Analysis allows for\nadvanced investigations including\ntwist, regional strain and deformation\nanalysis. Results are mapped onto\nthe LV Beutel surface for clear\nvisualization. All results can be stored\nand exported.","The Dynamic HeartModel (DHM)\nprovides automatic 3D anatomical\nborders and left ventricle (LV) and left\natrium (LA) border tracking across all\nframes of the cardiac cycle or cycles.","4D LV-ANALYSIS provides\nmorphological and functional\nanalyses of the left ventricle. Based\non 3D echo datasets a 4D model\n(Beutel) is generated that represents\nthe cavity of the LV and optionally\nalso the LA. Volumes, Strain and\nDisplacement are quantified on a\nglobal and segmental level.","Revised for clarity. Considered\nequivalent to primary predicate. No\nimpact to the safety or effectiveness\nof the device.\nComparable and considered\nequivalent to secondary predicate.",""],["SW Version","","3.1","15.0","3.2","Updated due to changes to SW code.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p9-t0","doc_id":"K201632","page_num":9,"bbox":[48.5,113.58,736.42,520.56],"n_rows":6,"n_cols":7,"columns":["Measurements","","As cleared","LAVmin\nLAVmax\nLA EF","Added:\nLA EDV (LA EDVI)\nLA ESV (LA ESVI)\nLA PreAV (LA PreAVI)\nLA trueEF\nLA EF\nLA GLS","Same technology extended to Atrium\n(LA Option in 4D LV-Analysis).\nLA EDV corresponds to LAVmin, and\nLA ESV corresponds to LAVmax.\nLA PreAV is based on the same\ndynamic quantification as LA volume\ncurve (prior to contraction).\nLA trueEF uses the same formula as\nLA EF but different volume values\n(LA PreAV instead of LAVmax).\nLA GLS is a well-known parameter\nand described in clinical literature.",""],"rows":[["Measurements","","As cleared","LAVmin\nLAVmax\nLA EF","Added:\nLA EDV (LA EDVI)\nLA ESV (LA ESVI)\nLA PreAV (LA PreAVI)\nLA trueEF\nLA EF\nLA GLS","Same technology extended to Atrium\n(LA Option in 4D LV-Analysis).\nLA EDV corresponds to LAVmin, and\nLA ESV corresponds to LAVmax.\nLA PreAV is based on the same\ndynamic quantification as LA volume\ncurve (prior to contraction).\nLA trueEF uses the same formula as\nLA EF but different volume values\n(LA PreAV instead of LAVmax).\nLA GLS is a well-known parameter\nand described in clinical literature.",""],["Export formats:","","As cleared","Beutel value export into .stl and .obj\nformat","Added:\nBeutel value export into .stl and .obj\nformat","Identical to secondary predicate (see\n\"4D RV-Function\").",""],["Enhancements:","","As cleared","n/a","Adapted Bullseye based an ASE2015\nguideline.\nWorkflow improvements by removed\nBeutel revision step & contour\nproposal and retracking within\ntracking revision step.","Workflow improvements for user\nconvenience. No impact to the safety\nor effectiveness of the device.",""],["","AUTOSTRAIN","","","","",""],["Application\nDescription","","n/a - features and functionality were\npart of IMAGE-COM (AutoSTRAIN\nAddins) and 2D CPA","AutoStrain LV, LA, RV included","AutoStrain is a quantification tool of\nglobal and regional function based on\ncontour detection and tracking. It\nsupports a bull’s eye display of Time\nto Peak Longitudinal Strain and End-\nSystolic Longitudinal Strain. Further,\nthis CAP provides the calculation of\nGLS (Global Peak Longitudinal\nStrain).","Based on cleared Addins of IMAGE-\nCOM and 2D CPA, a dedicated\nmodule (CAP) was released.\nThis CAP only includes features and\nmeasurements that were already\navailable in IMAGE-COM (and\nrespective Addins), 2D CPA or have\nbeen cleared by QLAB. The\nintegration \"on cart\" requires\ndedicated CAPs (e.g. for the\napplication layout). This CAP is used\nin the same clinical context and\nworkflows. No impact to the safety or\neffectiveness of the device.",""],["SW Version","","n/a - features and functionality were\npart of IMAGE-COM (AutoSTRAIN\nAddins) and 2D CPA","15.0","2.1","No previous SW version as features\nand functionality were included in\nIMAGE-COM and/or 2D CPA",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p10-t0","doc_id":"K201632","page_num":10,"bbox":[48.51,208.87,736.52,503.55],"n_rows":8,"n_cols":8,"columns":["Feature","","","Primary Predicate Device","","Subject Device\nTOMTEC-ARENEA","Discussion / Comment",""],"rows":[["Feature","","","Primary Predicate Device","","Subject Device\nTOMTEC-ARENEA","Discussion / Comment",""],["","","","TomTec-Arena","","","",""],["","","","(K150122)","","","",""],["","IMAGE-COM","","","","","",""],["Application\ndescription","","Image-Com is a dedicated DICOM viewer for\ncardiovascular ultrasound and Cath Lab\nexaminations. Easy and quick\nimage review is supported by a variety of time\nsaving features. Prior studies can easily be\ncompared with current\nexaminations and the simultaneous display of Cath\nLab, echo or nuclear medicine examinations\nprovides additional\nclinical information.","","","IMAGE-COM is a basic module for reviewing and\nmeasuring digital medical data. It supports routine\nworkflows for loading, analyzing and saving\nmedical studies, e.g. for the purpose of creating\nreports. IMAGE-COM is where basic\nmeasurements can be performed and the entry\npoint for advanced analysis modules. Study related\nroutine measurements can be imported, displayed,\nedited and exported to accompanying reporting\nsystems.","Revised for clarity. Considered equivalent to\nprimary predicate. No impact to the safety or\neffectiveness of the device.",""],["SW Version","","5.4","","","5.5","Updated due to changes to SW code.",""],["Measurements","","ECHO","","","Added:\nAnnulus dmin\nAnnulus dmax\nAnnulus dmean\nAnnulus Area\nAnnulus Perimeter\nAnnulus d(area)\nAnn-Ost left diam\nAnn-Ost right diam\nMV E Valsalva\nMV A Valsalva\nMV E/A Valsalva","Existing ECHO measurements have been\nextended. No impact to the safety or effectiveness\nof the device.",""],["Measurements\n(continued)","","Vascular","","","Renal (AT & AI)","Existing Vascular measurements have been\nextended. No impact to the safety or effectiveness\nof the device.",""]],"caption_candidate":"LASct AC LASct AC","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p11-t0","doc_id":"K201632","page_num":11,"bbox":[48.49,113.58,736.55,528.18],"n_rows":12,"n_cols":6,"columns":["Exam Types","","ECHO and Vascular","Added:\nPediatric\nCath","ECHO and Vascular were extended to Pediatric.\nExtension of existing measurement methods to\nCath.",""],"rows":[["Exam Types","","ECHO and Vascular","Added:\nPediatric\nCath","ECHO and Vascular were extended to Pediatric.\nExtension of existing measurement methods to\nCath.",""],["Deployment","","Application based (FAT)","Browser support added","IMAGE-COM is available as a zero footprint\nsolution (TOMTEC ZERO). No change in intended\nuse or use environment. No impact to the safety or\neffectiveness of the device.",""],["Auto LV","","AutoLV enables IMAGE-COM to quantify left\nventricular function based on 4-chamber and 2-\nchamber views of the left ventricle (biplane\nSimpson) with a single mouse click per view","Unchanged","Identical to primary predicate.",""],["Auto Strain","","The AutoStrain application yields cardiac function\nanalysis based on a workflow. After selecting views\nto analyze, and starting the application results are\nshown directly for user’s review.","Unchanged","Identical to primary predicate.",""],["AutoSTRAIN\nMeasurements\n(continued)","","As cleared","Added:\nLVLd (A4C)\nLVLs (A4C)\nLVLd (A2C)\nLVLs (A2C)\nAVC","Length measurements/values added because of\nuser needs:\nUser is able to double check if LV axis is acquired\nwithout foreshortening. In this case both Diastolic\nand Systolic Major Axis should be similar.",""],["AutoSTRAIN\nEnhancements","","Bullseye (16 segments)","Bullseye (18 segments)","Adapted Bullseye based on ASE2015 guideline.",""],["Auto LA","","AutoLA* is a fast and intuitive automation of\nSimpson’s biplane method.\nBy selecting apical 4- and 2-chamber views,\nAutoLA finds end-systole and proposes tracings of\nthe left atrial blood tissue interface","Unchanged","Identical to primary predicate.",""],["Auto LA\nMeasurements","","LA Vol (Simpson)","Extension of existing left atrium LA volume\n(Simpson) measurements with contour proposal\nstep","Improvement for user convenience. No impact to\nthe safety or effectiveness of the device.",""],["Cath-QCA","","Cath QCA is a calculation of stenosis diameter and\narea, obstruction and reference diameters and\nobstruction length","Unchanged","Identical to primary predicate.",""],["Cath-QVLA\nMeasurements","","Cath-QVLA is a calculation of EDV and ESV, EF,\nSV, CO of the Left ventricle","Unchanged","Identical to primary predicate.",""],["","4D CARDIO-VIEW","","","",""],["Application\nDescription","","4D Cardio-View is a vendor independent offline\nsolution to review and analyze 3D echo data. It\noffers an easy and fast navigation to get the perfect\n3D view with just two clicks by using the unique","4D CARDIO-VIEW is an advanced analysis tool for\n3D/4D echocardiography data. Anatomical\nstructure visualization, volume measurements (LV\nand/or generic), and specified or manual","Revised for clarity. Considered equivalent to\nprimary predicate. No impact to the safety or\neffectiveness of the device.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p12-t0","doc_id":"K201632","page_num":12,"bbox":[48.49,113.58,736.55,505.77],"n_rows":8,"n_cols":6,"columns":["","","D’Art tool. Features like the multi-slice D’Art\n(multiple 2D slices), basic measurements and\nworkflow based volume measurements make 4D\nCardio-View an all-purpose solution for any cardiac\nstructure. All measurements and views can be\nstored as bookmarks for easy retrieval at any time.","measurements are possible. Various tools are\navailable for rendering that display 2- and 3-\ndimensional morphology and function for defined\nstructures.","",""],"rows":[["","","D’Art tool. Features like the multi-slice D’Art\n(multiple 2D slices), basic measurements and\nworkflow based volume measurements make 4D\nCardio-View an all-purpose solution for any cardiac\nstructure. All measurements and views can be\nstored as bookmarks for easy retrieval at any time.","measurements are possible. Various tools are\navailable for rendering that display 2- and 3-\ndimensional morphology and function for defined\nstructures.","",""],["SW Version","","3.0","3.1","Updated due to changes to SW code.",""],["Measurements","","as cleared","Unchanged","Identical to primary predicate.",""],["Export formats:","","as cleared","Added:\nBeutel value export into .stl and .obj format","Identical to secondary predicate (see \"4D RV-\nFunction\").",""],["","2D CARDIAC-PERFORMANCE ANALYSIS (Adult and Fetal)","","","",""],["Application\nDescription","","2D Cardiac Performance Analysis is a vendor\nindependent offline solution for the\nquantification of left ventricular deformation.\nDetailed analysis of myocardial velocity,\ndisplacement, strain and strain rate is\nperformed based on 2D speckle tracking in\nlong or short axis views. Basic parameter\nassessment and comprehensive result export\noptions make 2D CPA suitable for research\nand routine use.","2D CARDIAC PERFORMANCE ANALYSIS\n(2D CPA) provides parameters for myocardial\nfunction and deformation analysis. Based on\ntwo dimensional echo B-Mode datasets a\nspeckle tracking algorithm supports the\ncalculation of 2D-contour models of the\nendocardial and epicardial border.\nCorresponding velocities, displacements,\nstrains, strain rates and functional parameters\ncan be derived. The results are displayed as\nfigures, in charts or they are available as\nnumerical values.","Revised for clarity. Considered equivalent to\nprimary predicate. No impact to the safety or\neffectiveness of the device.",""],["","","","FETAL 2D CARDIAC PERFORMANCE\nANALYSIS (FETAL 2D CPA) is a vendor\nindependent, offline solution for the\nquantification of cardiac deformation of the\nfetal heart. Detailed analysis of myocardial\nvelocity, displacement, strain and strain rate is\nperformed based on 2D speckle tracking in\nthe long axis views of the left ventricle and\nright ventricle. Basic parameter assessment\nas well as advanced quantifications, together\nwith comprehensive result export options,\nmake FETAL 2D CPA suitable for research\nand routine use.","Analysis of the fetal heart can be performed\nbased on the cleared implementation of\nspeckle tracking that is available in 2D CPA.\nQuantification of fetal structures is part of the\ncleared Indications for Use. Technology\nalready available is applied within the\nIntended Use/Indications for Use of the\ndevice. Substantial evidence for this\nmodification is available.\nOptimized workflow (exclusively for 4CH clips)\nto analyze both ventricles in the same 4CH\nclip and within the same application session.\nSame algorithm for contour detection is used.",""],["SW Version","","1.2","1.4","Updated due to changes to SW code.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201632-p13-t0","doc_id":"K201632","page_num":13,"bbox":[48.5,113.58,736.54,369.09],"n_rows":5,"n_cols":6,"columns":["Measurements","","Left ventricle strain calculation","Extended to right ventricle strain and atrium\nstrain (e.g. GLS and segmental strain/strain\nrate values).\n- MAPSE (lateral and septal)\n- Basal ventricle diameter at ES and ED of RV\nand LV\n- Ventricle length at ES and ED of RV and LV\n- Myocardial area at ED of LV and RV","Existing measurements were extended to\nright ventricle strain and atrium strain (similar\nto LA Option).",""],"rows":[["Measurements","","Left ventricle strain calculation","Extended to right ventricle strain and atrium\nstrain (e.g. GLS and segmental strain/strain\nrate values).\n- MAPSE (lateral and septal)\n- Basal ventricle diameter at ES and ED of RV\nand LV\n- Ventricle length at ES and ED of RV and LV\n- Myocardial area at ED of LV and RV","Existing measurements were extended to\nright ventricle strain and atrium strain (similar\nto LA Option).",""],["","REPORTING","","","",""],["Application\nDescription","","Dedicated module for Ultrasound Reporting.","REPORTING provides various workspaces which\nare dedicated to different clinical applications and\nsupports the workflow within clinical institutions.\nMeasurements can be imported, modified and\nexported in order to support connected reporting\nsystems.","Revised for clarity. Considered equivalent to\nprimary predicate. No impact to the safety or\neffectiveness of the device.",""],["SW Version","","2.01","2.40","SW version is identical and correspond to the\nTOMTEC-ARENA version, due to release\ndependencies.",""],["Workspaces /\nAreas","","Echo","Added:\nVascular\nStress Echo\nPediatric\nFetal\nTEE Pre/Post OP","Based on existing and extended measurements,\nnew workspaces were added in order to display\nand structure those measurements in a dedicated\nworkspace (view) for easy clinical reporting. No\nimpact to the safety or effectiveness of the device.",""]],"caption_candidate":"TOMTEC-ARENA (TTA2.40)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201710-p7-t0","doc_id":"K201710","page_num":7,"bbox":[36.32,674.74,559.1,751.43],"n_rows":6,"n_cols":9,"columns":["Characteristic","Subject Device","","Primary Predicate","","Reference Device","","","Reference Device"],"rows":[["Characteristic","Subject Device","","Primary Predicate","","Reference Device","","","Reference Device"],["","","","Device","","","","",""],["Device Name","AVIEW LCS","AVIEW LCS","AVIEW LCS","","","Lung Nodule","","AVIEW"],["","","","","","","Assessment and","",""],["","","","","","","Comparison Option","",""],["","","","","","","(LNA)","",""]],"caption_candidate":"tests, we conclude that the proposed device is substantially equivalent to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201710-p8-t0","doc_id":"K201710","page_num":8,"bbox":[36.29,84.54,559.18,748.85],"n_rows":14,"n_cols":7,"columns":["Classification\nName","","","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological"],"rows":[["Classification\nName","","","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological"],["","Regulatory","","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050"],["","Number","","","","",""],["","Product Code","","LLZ, JAK","LLZ, JAK","LLZ, JAK","LLZ, JAK"],["","Review Panel","","Radiology","Radiology","Radiology","Radiology"],["","510k Number","","-","K193220","K162484","K200714"],["Indications for\nuse","","","AVIEW LCS","","",""],["","","","AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the\npurpose of characterizing nodules in the lung in a single study, or over the time course of several\nthoracic studies. Characterizations include nodule type, location of the nodule and measurements\nsuch as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,\nthe volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU),\nMinimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric\nmeasures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the\nnodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections\nperpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time),\nLung-RADS (classification proposed to aid with findings) and CAC score and LAA analysis. The\nsystem automatically performs the measurement, allowing lung nodules and measurements to be\ndisplayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection)\n(K043617).","","",""],["","","","AVIEW LCS","","",""],["","","","AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the\npurpose of characterizing nodules in the lung in a single study, or over the time course of several\nthoracic studies. Characterizations include nodule type, location of the nodule and measurements\nsuch as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,\nthe volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU),\nMinimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric\nmeasures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the\nnodule. Solid 2 Major: The length of the longest diameter of the solid part, measured in sections\nnd\nperpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time),\nand Lung-RADS (classification proposed to aid with findings). The system automatically\nperforms the measurement, allowing lung nodules and measurements to be displayed and, also\nintegrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).","","",""],["","","","Lung Nodule Assessment and Comparison Option (LNA)","","",""],["","","","The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient-\nimaging tool. It is intended for the review and analysis of thoracic CT images, providing\nquantitative and characterizing information about nodules in the lung in a single study, or over\nthe time course of several thoracic studies. Characterizations include diameter, volume and\nvolume over time. The system automatically performs the measurements, allowing lung nodules\nand measurements to be displayed.","","",""],["","","","AVIEW","","",""],["","","","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This\nsoftware could be used to support the physician quantitatively in the diagnosis, follow up\nevaluation and documentation of CT lung tissue images by providing image segmentation of sub-\nstructures in lung, lobe, airways and cardiac, registration of inspiration and expiration which could\nanalyze quantitative information such as air trapping volume, air trapped index, and\ninspiration/expiration ratio. And also, volumetric and structure analysis, density evaluation and\nreporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on premise\nand as cloud environment as well to allow users to connect by various environment such as mobile\ndevices and chrome browser. Characterizing nodules in the lung in a single study, or over the time","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201745-p5-t0","doc_id":"K201745","page_num":5,"bbox":[77.54,499.34,545.74,618.89],"n_rows":5,"n_cols":2,"columns":["Predicate Device Information",""],"rows":[["Predicate Device Information",""],["Device Name:","Deep Learning Image Reconstruction"],["Manufacturer:","GE Medical Systems, LLC"],["510(k) Number:","K183202 cleared on April 12, 2019"],["Regulation Number/\nProduct Code:","21 CFR 892.1750 Computed tomography x-ray system / JAK"]],"caption_candidate":"Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201745-p8-t0","doc_id":"K201745","page_num":8,"bbox":[72.17,104.78,531.31,599.45],"n_rows":10,"n_cols":5,"columns":["Specification/ Attribute","Deep Learning Image\nReconstruction\n(Predicate Device, K183202)","","Deep Learning Image",""],"rows":[["Specification/ Attribute","Deep Learning Image\nReconstruction\n(Predicate Device, K183202)","","Deep Learning Image",""],["","","","Reconstruction for Gemstone",""],["","","","Spectral Imaging",""],["","","","(Proposed Device)",""],["Compatible Image Types","Compatible with single energy scan\nmodes and standard kernel.","Compatible with dual energy\nscan modes and standard kernel.","",""],["IQ performance vs dose","Low contrast detectability (LCD),\nimage noise, contrast to noise ratio\n(CNR), and high contrast spatial\nresolution are as good or better\nthan ASiR-V when substituted using\nraw data from the same scan.","Same","",""],["Technology","Utilizes a dedicated neural network\nwhich is trained using single energy\nacquired images on the CT Scanner\nand designed specifically to\ngenerate high quality CT images.","Utilizes a dedicated neural\nnetwork which is trained using\ndual energy acquired images on\nthe CT Scanner and designed\nspecifically to generate high\nquality CT images.","",""],["System statistics - Noise\nmodeling of the data\ncollection imaging chain\n(photon noise and\nelectronic noise)","Characterization of the photon\nstatistics as it propagates through\nthe preprocessing and calibration\nimaging chain.","Same","",""],["System statistics – Noise\ncharacteristics of the\nreconstructed images","Utilizes a trained neural network\nwhich models the scanned object\nusing information obtained from\nextensive phantom and clinical\ndata.","Same","",""],["Clinical Workflow","Select recon type and strength\n(Low, Medium, High).","Same","",""]],"caption_candidate":"510(k) Premarket Notification Submission – DLIR-GSI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201836-p4-t0","doc_id":"K201836","page_num":4,"bbox":[67.08,136.24,170.75,710.17],"n_rows":54,"n_cols":2,"columns":["1.","SUBMITTER’S NA"],"rows":[["1.","SUBMITTER’S NA"],["",""],["","Canon Medical S"],["",""],["","1385 Shimoishiga"],["",""],["","Otawara‐Shi, Toc"],["",""],["2.","OFFICIAL CORRE"],["",""],["","Fumiaki Teshima"],["",""],["","Senior Manager,"],["",""],["3.","ESTABLISHMENT"],["",""],["","9614698"],["",""],["4.","CONTACT PERSO"],["",""],["","Orlando Tadeo, J"],["",""],["","Sr. Manager, Reg"],["",""],["","Canon Medical S"],["",""],["","2441 Michelle Dr"],["",""],["","Tustin, CA 92780"],["",""],["","(714)669‐7459"],["",""],["5.","Date Prepared:"],["",""],["","June 30, 2020"],["",""],["6.","TRADE NAME(S):"],["",""],["","Aquilion Lightnin"],["",""],["7.","COMMON NAME"],["",""],["","System, X‐ray, Co"],["",""],["8.","DEVICE CLASSIFI"],["","a)Classification N"],["","b)Regulation Nu"],["","c)Regulatory Cla"],["",""],["9.","PRODUCT CODE"],["",""],["","JAK – System, Co"],["",""],["Michelle","Drive, Tustin, CA 92780"]],"caption_candidate":"1. SUBMITTER’S NAME:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K201836-p5-t0","doc_id":"K201836","page_num":5,"bbox":[90.0,87.66,594.0,236.88],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance Date"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance Date"],["Aquilion Lightning,\nTSX‐036A/1, V8.4\n(Primary Predicate\nDevice)","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K170019","February 2, 2017"],["Aquilion Prime SP\n(TSX‐303B/8) V10.2\nwith AiCE‐i\n(Reference Device)","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K192832","February 21, 2020"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K201836-p6-t0","doc_id":"K201836","page_num":6,"bbox":[101.88,226.8,574.86,596.7],"n_rows":26,"n_cols":5,"columns":["Item","","Aquilion Lightning (TSX‐036A/7) V10.2","","Aquilion Lightning (TSX‐036A/1) V8.4"],"rows":[["Item","","Aquilion Lightning (TSX‐036A/7) V10.2","","Aquilion Lightning (TSX‐036A/1) V8.4"],["","","with AiCE‐i","",""],["510(k) Clearance\nNumber","N/A","N/A","","K170019"],["Anatomical Region","","AIDR 3D (Whole Body)","","AIDR 3D (Whole Body)"],["","","","",""],["","","AiCE (Abdomen and Pelvis, Chest,","",""],["","","Cardiac, Extremities, Brain, Inner ear)","",""],["Noise Reduction\nProcessing","","AIDR 3D","","AIDR 3D\nAIDR 3D Enhanced\nQuantum Denoising Smoothing (QDS)"],["","","AIDR 3D Enhanced","",""],["","","Quantum Denoising Smoothing (QDS)","",""],["","","AiCE","",""],["Processing\ncapability","","Console CKCN‐020C","","Console CKCN‐020C\nReconstruction processing system\n(N/A)"],["","","","",""],["","","Reconstruction processing system","",""],["","","(AiCE‐i: CSAL‐001A)","",""],["Image Quality\nClaim","","‐ Improved Quantitative high contrast","","‐N/A\n‐N/A\n‐N/A\n‐N/A"],["","","Spatial Resolution over AIDR 3D with","",""],["","","reduced noise","",""],["","","‐ Improved Quantitative Dose Reduction","",""],["","","over FBP","",""],["","","‐ Better Low‐contrast Detectability than","",""],["","","AIDR 3D for abdomen at the same","",""],["","","dose","",""],["","","‐Noise appearance/texture similar to","",""],["","","filtered backprojection","",""],["Operating System","","Microsoft Windows 10","","Microsoft Windows 10"]],"caption_candidate":"subject and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p4-t0","doc_id":"K202013","page_num":4,"bbox":[85.75,148.05,534.6,280.8],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Whiterabbit AI Inc."],"rows":[["510(k) Sponsor","Whiterabbit AI Inc."],["Address","3930 Freedom Cir., Ste 101\nSanta Clara, CA 95054"],["Correspondence\nPerson","Jason Su"],["Contact Information","914-275-1097\njason@whiterabbit.ai"],["Date Prepared","October 29, 2020"]],"caption_candidate":"5.1 General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p4-t1","doc_id":"K202013","page_num":4,"bbox":[85.75,320.55,534.6,428.55],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","WRDensity by Whiterabbit.ai"],"rows":[["Proprietary Name","WRDensity by Whiterabbit.ai"],["Common Name","WRDensity"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"5.2 Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p4-t2","doc_id":"K202013","page_num":4,"bbox":[85.75,468.3,534.6,576.3],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Densitas densityai"],"rows":[["Proprietary Name","Densitas densityai"],["Premarket Notification","K192973"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"5.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p5-t0","doc_id":"K202013","page_num":5,"bbox":[94.84,531.25,544.84,709.88],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nWRDensity","Predicate Device\ndensityai (K192973)"],"rows":[["","Subject Device\nWRDensity","Predicate Device\ndensityai (K192973)"],["Classification\nName","Automated Radiological Image\nProcessing Software","System, Image Processing,\nRadiological"],["Product Code","QIH","LLZ"],["Regulation\nNumber","892.2050","892.2050"],["Regulation\nDescription","Picture archiving and\ncommunication system","Picture archiving and\ncommunication system"]],"caption_candidate":"Table 5.1 Predicate Device Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p6-t0","doc_id":"K202013","page_num":6,"bbox":[94.84,105.25,545.59,717.38],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nWRDensity","Predicate Device\ndensityai (K192973)"],"rows":[["","Subject Device\nWRDensity","Predicate Device\ndensityai (K192973)"],["Indications for\nUse","WRDensity is a software\napplication intended for use with\ncompatible full field digital\nmammography and digital breast\ntomosynthesis systems.\nWRDensity provides an ACR\nBI-RADS Atlas 5th Edition breast\ndensity category to aid\ninterpreting physicians in the\nassessment of breast tissue\ncomposition. WRDensity\nproduces adjunctive information.\nIt is not a diagnostic aid.","Densitas densityai™ is a software\napplication intended for use with\ncompatible full field digital\nmammography and digital breast\ntomosynthesis systems. Densitas\ndensityai™ provides an ACR\nBI-RADS Atlas 5th Edition breast\ndensity category to aid interpreting\nphysicians in the assessment of\nbreast tissue composition. Densitas\ndensityai™ produces adjunctive\ninformation. It is not a diagnostic\naid."],["Patient\nPopulation","Symptomatic and\nasymptomatic women\nundergoing\nmammography","Symptomatic and\nasymptomatic women\nundergoing\nmammography"],["End Users","Interpreting Physicians","Interpreting Physicians"],["Image Source\nModalities","FFDM\nHologic Selenia Dimensions\nHologic Lorad Selenia\nSynthetic 2D\nHologic C-View","FFDM\nHologic Selenia Dimensions\nHologic Lorad Selenia\nGE Senographe Essential\nGE Senographe Pristina\nSiemens MAMMOMAT\nInspiration\nSiemens MAMMOMAT Novation\nDR\nSiemens MAMMOMAT Fusion\nSiemens MAMMOMAT\nInspiration Prime\nSiemens MAMMOMAT\nRevelation"]],"caption_candidate":"Table 5.2 Indications and Technological Characteristics Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202013-p7-t0","doc_id":"K202013","page_num":7,"bbox":[94.88,72.32,545.62,612.38],"n_rows":10,"n_cols":3,"columns":["","","Synthetic 2D\nHologic C-View"],"rows":[["","","Synthetic 2D\nHologic C-View"],["Input: Image\nData Format","DICOM digital mammography\nimages – For Presentation; RCC,\nLCC, RMLO, LMLO","DICOM digital mammography\nimages – For Presentation; RCC,\nLCC, RMLO, LMLO"],["Output Data","BIRADS 5th Ed.\nFor each patient:\nWhiterabbit.ai WRDensity Breast\nDensity Level, and Breast Density\nLevel Probability","BIRADS 5th Ed.\nFor each patient:\nDensitas densityai™ breast density\ngrade"],["Measurement\nScale","4-category breast density scale\nfrom 5th Ed. ACR BI-RADS\nAtlas 2013","4-category breast density scale\nfrom 5th Ed. ACR BI-RADS Atlas\n2013"],["Output Device","Mammography Workstation,\nPACS, RIS","Mammography Workstation,\nPACS, RIS"],["Output\nFormat","DICOM Structured\nReport and Secondary\nCapture\nText labels presented in a\nradiologist’s PACS\nand RIS patient worklist.","DICOM Structured\nReport and Secondary\nCapture"],["Deployment","Virtual Machine Software","Standalone computer"],["Assessment\nScope","Results per exam","Results per exam"],["Assessment\nType","Image feature-based with deep\nlearning","Image feature-based"],["Anatomical\nLocation","Breast","Breast"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p4-t0","doc_id":"K202170","page_num":4,"bbox":[77.72,368.16,517.07,579.45],"n_rows":11,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","510(k) number","","Not known","","","K190017","",""],["","Legal Manufacturer","","Perspectum Ltd.","","","Perspectum Diagnostics Ltd.","",""],["","Owner/Owner Operator","","10056574","","","10056574","",""],["","NDeuvmicbee Nr ame","","LiverMultiScan (LMSv4)","","","LiverMultiScan (LMSv3)","",""],["","Proprietary/Common","","LiverMultiScan","","","LiverMultiScan","",""],["","nPaanmeel","","Radiology","","","Radiology","",""],["","Regulation","","892.1000","","","892.1000","",""],["","Risk Class","","Class II","","","Class II","",""],["","Product Class code","","LNH","","","LNH","",""],["Classification","Classification","","System, Nuclear Magnetic\nResonance Imaging","","","System, Nuclear Magnetic\nResonance Imaging","",""]],"caption_candidate":"2. Subject and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p6-t0","doc_id":"K202170","page_num":6,"bbox":[36.18,158.88,558.78,763.72],"n_rows":8,"n_cols":9,"columns":["Comparison of Subject and Predicate Device","","","","","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","","","","","",""],["Characteristic","","","LMSv4 (Subject device)","","","LMSv3 (Predicate device)","",""],["Intended Use\nand Indications\nfor Use","","","“LiverMultiScan (LMSv4) is indicated for use as\na magnetic resonance diagnostic device\nsoftware application for non-invasive liver\nevaluation that enables the generation, display\nand review of 2D magnetic resonance medical\nimage data and pixel maps for MR relaxation\ntimes.\nLiverMultiScan (LMSv4) is designed to utilize\nDICOM 3.0 compliant magnetic resonance\nimage datasets, acquired from compatible MR\nsystems, to display the internal structure of the\nabdomen including the liver. Other physical\nparameters derived from the images may also\nbe produced.\nLiverMultiScan (LMSv4) provides a number of\ntools, such as automated liver segmentation\nand region of interest (ROI) placements, to be\nused for the assessment of selected regions of\nan image. Quantitative assessments of\nselected regions include the determination of\ntriglyceride fat fraction in the liver (PDFF), T2*\nand iron-corrected T1 (cT1) measurements.\nT2* may be optionally computed using the\nDIXON or LMS MOST methods.\nThese images and the physical parameters\nderived from the images, when interpreted by\na trained clinician, yield information that may\nassist in diagnosis.”","","","“LiverMultiScan (LMSv3) is indicated for use as\na magnetic resonance diagnostic device\nsoftware application for non-invasive liver\nevaluation that enables the generation, display\nand review of 2D magnetic resonance medical\nimage data and pixel maps for MR relaxation\ntimes.\nLiverMultiScan (LMSv3) is designed to utilize\nDICOM 3.0 compliant magnetic resonance\nimage datasets, acquired from compatible MR\nsystems, to display the internal structure of\nthe abdomen including the liver. Other\nphysical parameters derived from the images\nmay also be produced.\nLiverMultiScan (LMSv3) provides a number of\ntools, such as automated liver segmentation\nand region of interest (ROI) placements, to be\nused for the assessment of selected regions of\nan image. Quantitative assessments of\nselected regions include the determination of\ntriglyceride fat fraction in the liver (PDFF), T2*\nand iron-corrected T1 (cT1) measurements.\nPDFF may optionally be computed using the\nLMS IDEAL or three-point DIXON\nmethodology.\nThese images and the physical parameters\nderived from the images, when interpreted by\na trained clinician, yield information that may\nassist in diagnosis.”","",""],["","Target","","","Patients suitable to undergo an MRI scan and","","","Patients suitable to undergo an MRI scan and",""],["","Population","","","not contra-indicated for MRI.","","","not contra-indicated for MRI.",""],["Device User","Device User","","Trained Perspectum operator","Trained Perspectum operator","","Trained Perspectum operator","Trained Perspectum operator",""],["Report User","","","An interpreting clinician or healthcare\npractitioner.","","","An interpreting clinician or healthcare\npractitioner.","",""],["Device Use\nEnvironment","","","Installation of LMSv4 is controlled and installed\non general purpose workstations at\nPerspectum’s image analysis centre, by\nspecialist members of staff.","","","Installation of LMSv3 is controlled and\ninstalled on general purpose workstations at\nPerspectum’s image analysis centre by\nspecialist members of staff.","",""]],"caption_candidate":"demonstrate substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p7-t0","doc_id":"K202170","page_num":7,"bbox":[36.19,75.36,558.77,766.68],"n_rows":34,"n_cols":9,"columns":["Comparison of Subject and Predicate Device","","","","","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","","","","","",""],["Characteristic","","","LMSv4 (Subject device)","","","LMSv3 (Predicate device)","",""],["Clinical Setting","","","","LMSv4 is a standalone software device that is","","","LMSv3 is a standalone software device that is",""],["","","","","intended to be installed on general use","","","intended to be installed on general use",""],["","","","","workstations at Perspectum’s image analysis","","","workstations at Perspectum’s image analysis",""],["","","","","centre. The intended device users will log on to","","","centre. The intended device users will log on",""],["","","","","the workstations, access the device, and use","","","to the workstations, access the device, and",""],["","","","","the device on general-use HD monitors.","","","use the device on general-use HD monitors.",""],["","","","","LMSv4 is a post-processing software, the","","","LMSv3 is a post-processing software, the",""],["","","","","intended device users are trained internal","","","intended device users are trained internal",""],["","","","","Perspectum operators. Operators use LMS to","","","Perspectum operators. Operators use LMS to",""],["","","","","conduct quantitative analysis of liver tissue","","","conduct quantitative analysis of liver tissue",""],["","","","","characteristics to produce a report.","","","characteristics to produce a report.",""],["","","","","The end-users for the output from the device,","","","The end-users for the output from the device,",""],["","","","","the pdf report, are clinicians who receive and","","","the pdf report, are clinicians who receive and",""],["","","","","interpret LMSv4 reports through the QAS.","","","interpret LMSv3 reports through the QAS.",""],["","Anatomical","","Abdomen, Liver","Abdomen, Liver","","Abdomen, Liver","Abdomen, Liver",""],["","Location","","","","","","",""],["Energy\nConsiderations","Energy","","","Software only application. The device, a","","","Software only application. The device, a",""],["","Considerations","","","standalone software application, does not","","","standalone software application, does not",""],["","","","","deliver, monitor or depend on energy","","","deliver, monitor or depend on energy",""],["","","","","delivered to or from patients.","","","delivered to or from patients.",""],["Design: Purpose","","","LMS is a standalone software application that\nimports MR data sets encompassing the\nabdomen, including the liver. Visualisation and\ndisplay of 2D multi-slice, spin-echo MR data\ncan be analysed, and quantitative metrics of\ntissue characteristics are then reported.\nDatasets imported into LMS are DICOM 3.0\ncompliant, reported metrics are independent\nof the MRI equipment vendor.","LMS is a standalone software application that","","","LMS is a standalone software application that",""],["","","","","imports MR data sets encompassing the","","","imports MR data sets encompassing the",""],["","","","","abdomen, including the liver. Visualisation and","","","abdomen, including the liver. Visualisation",""],["","","","","display of 2D multi-slice, spin-echo MR data","","","and display of 2D multi-slice, spin-echo MR",""],["","","","","can be analysed, and quantitative metrics of","","","data can be analysed, and quantitative",""],["","","","","tissue characteristics are then reported.","","","metrics of tissue characteristics are then",""],["","","","","","","","reported.",""],["","","","","Datasets imported into LMS are DICOM 3.0","","","",""],["","","","","compliant, reported metrics are independent","","","Datasets imported into LMS are DICOM 3.0",""],["","","","","of the MRI equipment vendor.","","","compliant, reported metrics are independent",""],["","","","","","","","of the MRI equipment vendor.",""],["Design: Tools","","","","","","","",""]],"caption_candidate":"LMSv4 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p8-t0","doc_id":"K202170","page_num":8,"bbox":[36.16,75.36,558.8,763.32],"n_rows":7,"n_cols":5,"columns":["Comparison of Subject and Predicate Device","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","",""],["Characteristic","","","LMSv4 (Subject device)","LMSv3 (Predicate device)"],["","","","• ROI placed method on the cT1 map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\nT2*\n• ROI placed method on the T2* map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\n• T2* parametric maps are calculated from\nthe MOST method or the three-point\nDIXON method.\nPDFF\n• Full liver segmentation of the PDFF\nparametric map where IQR and median\nmetrics are reported from the\nsegmentation.\n• ROI placed method on the PDFF map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\n• PDFF parametric maps are calculated\nusing the LMS IDEAL method 1","• ROI placed method on the cT1 map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\nT2*\n• ROI placed method on the T2* map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\n• T2* parametric maps are calculated from\nthe three-point DIXON method.\nPDFF\n• Full liver segmentation of the PDFF\nparametric map where IQR and median\nmetrics are reported from the\nsegmentation.\n• ROI placed method on the PDFF map with\nIQR and median metrics from the placed\nROI’s potentially across multiple acquired\nslices.\n• PDFF parametric maps can be calculated\nusing either the LMS IDEAL method 1 or\nthe three-point DIXON method 2"],["","Design: MR","","T1, iron-corrected T1 (cT1) and T2* mapping.","T1, iron-corrected T1 (cT1) and T2* mapping."],["","Relaxometry","","",""],["Design: Liver Fat\nQuantification","","","Utilizes MR images that exploit the difference\nin resonance frequencies between hydrogen\nnuclei in water and triglyceride fat using the\nLMS IDEAL method.","Utilizes MR images that exploit the difference\nin resonance frequencies between hydrogen\nnuclei in water and triglyceride fat using either\nthe LMS IDEAL method or three-point DIXON\nmethod."],["Design: Liver\nSegmentation","","","LMSv4 supports automatic multi-slice full liver\nsegmentation of the cT1 and PDFF parametric\nmap, use of this functionality is at the\ndiscretion of the operator instead or in\ncombination with the ROI based method.\nThe cT1 segmented liver is presented in colour\nlevel window, while the rest of the cT1 image\nis presented in greyscale level window with\nducts and liver vasculature excluded from the\nsegmented volume.","LMSv3 supports automatic multi-slice full liver\nsegmentation of the cT1 and PDFF parametric\nmap, use of this functionality is at the\ndiscretion of the operator instead or in\ncombination with the ROI based method.\nThe cT1 segmented liver is presented in colour\nlevel window, while the rest of the cT1 image\nis presented in greyscale level window with\nducts and liver vasculature excluded from the\nsegmented volume."]],"caption_candidate":"LMSv4 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p9-t0","doc_id":"K202170","page_num":9,"bbox":[36.16,75.36,558.8,770.04],"n_rows":21,"n_cols":9,"columns":["Comparison of Subject and Predicate Device","","","","","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","","","","","",""],["Characteristic","","","LMSv4 (Subject device)","","","LMSv3 (Predicate device)","",""],["Design: Regions\nof Interest (ROI)","","","Median and interquartile range measurements\ncreated from a cross sectional slice of liver\ntissue. For each parametric map, statistics\nfrom multiple Regions of Interest (ROIs) –\npotentially placed across multiple slices – are\nsummarised.","","","Median and interquartile range measurements\ncreated from a cross sectional slice of liver\ntissue. For each parametric map, statistics\nfrom multiple Regions of Interest (ROIs) –\npotentially placed across multiple slices – are\nsummarised.","",""],["Design:\nParametric\nMaps","","","Iron corrected T1 (cT1), T2* and Proton\nDensity Fat Fraction (PDFF) parametric maps\ncan be created from all supported scanners.\nPDFF is quantified using the LMS IDEAL\nmethod. Parametric maps of T2* may be\noptionally be computed using either the\nthree-point DIXON method or the LMS MOST\nmethod.","","","Iron corrected T1 (cT1), T2* and Proton\nDensity Fat Fraction (PDFF) parametric maps\ncan be created from all supported scanners.\nPDFF is quantified using the LMS IDEAL\nmethod or the three-point DIXON method.","",""],["Design:\nVisualisation","","","Numerous views within the LMSv4 interface\ncan be used to assist in analysis, Iron-\ncorrected T1 (cT1), T2* and triglyceride fat\n(also known as Proton Density Fat Fraction\n(PDFF)) parametric maps can be created from\nall supported scanners. R2 maps can also be\nutilised to assess the quality of the map fitting.\nIron- corrected T1 (cT1) displayed using LMSv4\ncolourmap, designed to have maximum\ncontrast on liver parenchymal tissue.","","","Numerous views within the LMSv4 interface\ncan be used to assist in analysis, iron\ncorrected T1 (cT1), T2* and triglyceride fat\n(also known as Proton Density Fat Fraction\n(PDFF)) parametric maps can be created from\nall supported scanners.\nIron corrected T1 (cT1) displayed using the\nLMSv3 colourmap, designed to have maximum\ncontrast on liver parenchymal tissue.","",""],["","Design:","","DICOM 3.0 compliant MR data from supported\nMRI scanners.","","","DICOM 3.0 compliant MR data from supported\nMRI scanners.","",""],["","Supported","","","","","","",""],["","Modalities","","","","","","",""],["Design: Report","Design: Report","","","Quantified metrics and images derived from","","","Quantified metrics and images derived from",""],["","","","","the analysis conducted of liver tissue","","","the analysis conducted of liver tissue",""],["","","","","characteristic on parametric maps are collated","","","characteristic on parametric maps are",""],["","","","","into a report for evaluation and interpretation","","","collated into a report for evaluation and",""],["","","","","by a clinician.","","","interpretation by a clinician.",""],["Compatibility\nwith the\nenvironment","","","","Installation of LMSv4 is controlled and is","","","Installation of LMSv3 is controlled and is",""],["","","","","installed on general purpose workstations that","","","installed on general purpose workstations",""],["","","","","meet the minimum technical requirements at","","","that meet the minimum technical",""],["","","","","Perspectum’s image analysis centre by","","","requirements at PD’s image analysis centre by",""],["","","","","specialist members of staff.","","","specialist members of staff.",""],["Performance","","","Device performance was assessed with\npurpose-built phantoms and in-vivo acquired\ndata from volunteers covering a range of\nphysiological values for cT1, T2* and PDFF.","","","Device performance was assessed with\npurpose-built phantoms and in-vivo acquired\ndata from volunteers covering a range of\nphysiological values for cT1, T2* and PDFF.","",""],["Supported MRI\nSystems","","","Validated across all listed supported\nmanufacturers and field strengths.","","","Validated across all listed supported\nmanufacturers and field strengths.","",""],["Standards","","","IEC 62304, IEC 62366, DICOM 3.0, ISO 14971,\nISO 13485","","","IEC 62304, IEC 62366, DICOM 3.0, ISO 14971,\nISO 13485","",""]],"caption_candidate":"LMSv4 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p10-t0","doc_id":"K202170","page_num":10,"bbox":[36.14,75.36,558.82,268.92],"n_rows":11,"n_cols":3,"columns":["Comparison of Subject and Predicate Device","",""],"rows":[["Comparison of Subject and Predicate Device","",""],["Characteristic","LMSv4 (Subject device)","LMSv3 (Predicate device)"],["System/Operati\nng System","Mac OS","Mac OS"],["Materials","Not applicable, standalone software.","Not applicable, standalone software."],["Biocompatibility","Not applicable, standalone software.","Not applicable, standalone software."],["Sterility","Not applicable, standalone software.","Not applicable, standalone software."],["Electrical Safety","Not applicable, standalone software.","Not applicable, standalone software."],["Mechanical\nSafety","Not applicable, standalone software.","Not applicable, standalone software."],["Chemical Safety","Not applicable, standalone software.","Not applicable, standalone software."],["Thermal Safety","Not applicable, standalone software.","Not applicable, standalone software."],["Radiation Safety","Not applicable, standalone software.","Not applicable, standalone software."]],"caption_candidate":"LMSv4 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p10-t1","doc_id":"K202170","page_num":10,"bbox":[71.42,506.62,517.76,591.72],"n_rows":5,"n_cols":7,"columns":["Metric","","Accuracy","","","",""],"rows":[["Metric","","Accuracy","","","",""],["","","1.5T\nLimits of Agreement","","","3T",""],["cT1","-189.5 to -35.11 ms","","","-187.0 to -19.12 ms","",""],["T2*","-0.68 to 0.64 ms","","","-0.30 to 0.39 ms","",""],["IDEAL PDFF","(lowe-r3 t.h8a0n t og r6o.u08n%d truth","","","lower-1 t.h3a9n t ogr 5o.u5n8d% t ruth","",""]],"caption_candidate":"summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202170-p11-t0","doc_id":"K202170","page_num":11,"bbox":[71.42,75.35,523.54,208.92],"n_rows":8,"n_cols":7,"columns":["Metric","","Repeatability","","","Reproducibility",""],"rows":[["Metric","","Repeatability","","","Reproducibility",""],["","","Limits of Agreement","","","Limits of Agreement",""],["cT1 (ROI)","- 43.25 to 26.77 ms","","","-103 to 91.8 ms","",""],["cT1 (Segmentation)","- 40.75 to 25.02 ms","","","-102.3 to 93.69 ms","",""],["T2* (DIXON)","- 5.21 to 6.01 ms","","","-1.74 to 0.35 ms","",""],["T2* (MOST)","- 3.17 to 3.25 ms","","","-2.40 to 2.15 ms","",""],["IDEAL PDFF (ROI)","-1.48 to 1.42%","","","-2.88 to 2.53%","",""],["IDEAL PDFF (Segmentation)","-1.31 to 1.34 %","","","-2.94 to 2.53%","",""]],"caption_candidate":"LMSv4 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202212-p5-t0","doc_id":"K202212","page_num":5,"bbox":[103.92,454.8,507.96,710.28],"n_rows":5,"n_cols":4,"columns":["Measurement\n[units]","Description","Module /\nworkflow","Application"],"rows":[["Measurement\n[units]","Description","Module /\nworkflow","Application"],["Distance\n[mm]","Length between two points,\nfor both curved lines (splines)\nand straight lines, including\nthe diameter (including min,\nmax, average) resulting from\nclosed splines and depth of the\nLAA","All modules","Diameter & depth of\nLAA landing zone\n(LAA module);\ndistance between\npoints of interest"],["Perimeter\n[mm]","The perimeter of a contour\n(closed spline)","All modules","Perimeter of LAA\nlanding zone (LAA\nmodule); perimeter of\nother contours of\ninterest"],["Area [mm2]","The area within a contour","All modules","Area of LAA landing\nzone (LAA module);\narea of other contours\nof interest"],["Angle\n[degrees]","The angle of an\nobject/structure of interest","All modules","Angle between two\nlines of interest"]],"caption_candidate":"measurement application for which it is used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202212-p8-t0","doc_id":"K202212","page_num":8,"bbox":[72.02,108.72,532.66,701.16],"n_rows":7,"n_cols":5,"columns":["","","• Segmentation of\ncardiovascular structures\n• Visualization and image\nreconstruction techniques: 2D\nreview, Volume Rendering,\nMPR\n• Simulation of TEE views, ICE\nviews, and fluoroscopic\nrendering\n• Measurement and annotation\ntools\n• Reporting tools\nTruPlan’s intended patient\npopulation is comprised of adult\npatients.","(calcium scoring) in the\ncoronary arteries\nTo facilitate the above, 3mensio\nprovides general functionality such\nas:\n• Segmentation of cardiovascular\nstructures\n• Visualization and image\nreconstruction techniques: 2D\nreview, Volume Rendering,\nMPR, Curved MPR, Stretched\nCMPR, slabbing, MIP, AIP,\nMinIP\n• Measurement and annotation\ntools\n• Reporting tools\n• Automatic and manual\ncenterline detection",""],"rows":[["","","• Segmentation of\ncardiovascular structures\n• Visualization and image\nreconstruction techniques: 2D\nreview, Volume Rendering,\nMPR\n• Simulation of TEE views, ICE\nviews, and fluoroscopic\nrendering\n• Measurement and annotation\ntools\n• Reporting tools\nTruPlan’s intended patient\npopulation is comprised of adult\npatients.","(calcium scoring) in the\ncoronary arteries\nTo facilitate the above, 3mensio\nprovides general functionality such\nas:\n• Segmentation of cardiovascular\nstructures\n• Visualization and image\nreconstruction techniques: 2D\nreview, Volume Rendering,\nMPR, Curved MPR, Stretched\nCMPR, slabbing, MIP, AIP,\nMinIP\n• Measurement and annotation\ntools\n• Reporting tools\n• Automatic and manual\ncenterline detection",""],["","","","",""],["","Technological Characteristics","","",""],["","","","",""],["Input data type","","CT data in DICOM format (vendor\nindependent)","CT data in DICOM format (vendor\nindependent)",""],["Study list image\nfunctionality","","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search",""],["Image assessment –\nsimulated views","","• Fluoroscopy (grayscale\n3D rendering), to visualize\nrelationship among LAAC\nprocedure relevant\nanatomical structures\n• TEE, to provide similar\nviews to intraprocedural\nTEE\n• ICE, to provide similar\nviews to intraprocedural\nICE","• Grayscale 3D rendering, to\nvisualize relationship\namong LAAC procedure\nrelevant anatomical\nstructures\n• TEE, to provide similar\nviews to intraprocedural\nTEE",""]],"caption_candidate":"TruPlan 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202212-p9-t0","doc_id":"K202212","page_num":9,"bbox":[72.0,108.72,532.68,567.84],"n_rows":5,"n_cols":3,"columns":["Image assessment –\nother visualization\nfunctionality","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations\n• Curved MPR\n• Stretch CMPR\n• Slabbing\n• MIP\n• AIP\n• MinIP\n• Centreline extraction\n• Calcium scoring"],"rows":[["Image assessment –\nother visualization\nfunctionality","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations\n• Curved MPR\n• Stretch CMPR\n• Slabbing\n• MIP\n• AIP\n• MinIP\n• Centreline extraction\n• Calcium scoring"],["Image assessment –\nmeasurement functionality","• Distance (length,\ndiameter, perimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates","• Distance (length, diameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates\n• Volume"],["Report functionality","• Patient/study information\n• Screenshots\n• Measurements\n• Free text\n• Device sizing table (for\nreference only) for LAA\nprocedure","• Patient/study information\n• Screenshots\n• Measurements\n• Free text\n• Device-specific reports for\nprocedures covered in\nintended use"],["Operating system","Microsoft Windows","Microsoft Windows"],["DICOM compliant","YES","YES"]],"caption_candidate":"TruPlan 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p4-t0","doc_id":"K202229","page_num":4,"bbox":[72.08,273.38,540.38,483.38],"n_rows":4,"n_cols":2,"columns":["Submitter:","AI Metrics LLC\n432 Renaissance Dr. Hoover, AL 35226\nPhone: 205-573-3332\nWebsite: www.aimetrics.com"],"rows":[["Submitter:","AI Metrics LLC\n432 Renaissance Dr. Hoover, AL 35226\nPhone: 205-573-3332\nWebsite: www.aimetrics.com"],["Primary Contact:","Dr. Andrew Smith, Founder\nEmail: andrew@aimetrics.com\nPhone: (769) 610-6235"],["Company Contact:","Bob Jacobus, COO\nEmail: bob@aimetrics.com\nPhone: (205) 639-8618"],["Date Prepared:","September 9, 2020"]],"caption_candidate":"5.1 Identification of the Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p4-t1","doc_id":"K202229","page_num":4,"bbox":[72.08,536.62,540.38,685.12],"n_rows":6,"n_cols":2,"columns":["Trade Name:","AI Metrics"],"rows":[["Trade Name:","AI Metrics"],["Common Name:","Image Processing Software"],["Classification:","Picture Archiving and Communications System per 21 CFR 892.2050"],["Review Panel:","Radiology"],["Device Class:","Class II"],["Product Code:","LLZ"]],"caption_candidate":"5.2 Identification of the product","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p5-t0","doc_id":"K202229","page_num":5,"bbox":[73.12,184.88,540.38,308.62],"n_rows":5,"n_cols":2,"columns":["Device Name:","mint Lesion"],"rows":[["Device Name:","mint Lesion"],["Manufacturer:","Mint Medical GmbH Germany"],["510(k) Number:","K142647"],["Product Code:","LLZ"],["Classification:","Picture Archiving and Communications System per 21 CFR 892.2050"]],"caption_candidate":"5.3 Predicate Device to which Equivalence is claimed","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p7-t0","doc_id":"K202229","page_num":7,"bbox":[72.38,228.38,540.38,715.12],"n_rows":9,"n_cols":3,"columns":["Intended Use","Subject (AI Metrics)","Predicate (K142647)"],"rows":[["Intended Use","Subject (AI Metrics)","Predicate (K142647)"],["Thin client medical image viewer.","Yes.","Yes."],["Software only medical device deployed within\na customer’s IT infrastructure or on virtualized\nserver technology.","Yes.","Yes."],["Application supports anatomical datasets,\nsuch as CT and MR.","Yes.","Yes. Also supports\nfunctional datasets."],["To be used for viewing, manipulation,\ncommunication, storage, 3D-visualization and\ncomparison of medical images from multiple\nimaging modalities and/or multiple time points.","Yes.","Yes."],["Provides tools to help the user assess and\ndocument the extent of a disease and/or the\nresponse to therapy in accordance with user\nselected standards.","Yes.","Yes."],["Supports the interpretation and evaluation of\nexaminations and follow up documentation of\nfindings within healthcare institutions, for\nexample, in Radiology, Oncology, and other\nMedical Imaging environments.","Yes.","Yes. Includes\nNuclear Medicine\nenvironments."],["The medical professional retains the ultimate\nresponsibility for making the pertinent\ndiagnosis based on their standard practices.\nThe software is a complement to these\nstandard procedures.","Yes.","Yes."],["Not be used in mammography.","Yes.","Yes."]],"caption_candidate":"and the predicate device mint Lesion.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p8-t0","doc_id":"K202229","page_num":8,"bbox":[70.88,172.88,535.12,707.62],"n_rows":14,"n_cols":3,"columns":["Technological Characteristic","Subject (AI Metrics)","Mint Lesion (K142647)"],"rows":[["Technological Characteristic","Subject (AI Metrics)","Mint Lesion (K142647)"],["Design","",""],["Software-based Picture Archiving and\nCommunication System (PACS) used with\ngeneral purpose computing hardware.","Yes.","Yes."],["Operating system / Run environment","Windows 64 / native or\nvirtualized Microsoft\nWindows platform.","Linux / native or\nvirtualized Linux\nplatform."],["Software delivery method","CD ROM/DVD or\ninternet.","Internet software\ndownload."],["Features and Functionality","",""],["Image navigation tools (pan, zoom, scroll,\nwindow/level)","Yes.","Yes."],["Measurement tools (linear, ROI, HU)","Yes.","Yes."],["Automatic long and short axis calculations","Yes.","Yes."],["User controls functions with a system of\ninteractive menus and tools","Yes.","Yes."],["Semi-automatic lesion segmentation tools","Yes.","Yes."],["Anatomical location labelling tools","Yes.","Yes."],["Display output of measurements and\nanatomical location information","Yes.","Yes."],["Tabulation and summation of\nmeasurements, lesion categorization and\nstandard evaluation in accordance with\nselected criteria","Yes.","Yes."]],"caption_candidate":"www.aimetrics.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202229-p9-t0","doc_id":"K202229","page_num":9,"bbox":[70.88,157.82,535.12,253.12],"n_rows":3,"n_cols":3,"columns":["Longitudinal lesion analysis","Yes.","Yes."],"rows":[["Longitudinal lesion analysis","Yes.","Yes."],["Image co-registration for viewing images\nfrom different time points","Yes.","Yes."],["Report generation","Yes.","Yes."]],"caption_candidate":"www.aimetrics.com","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K202238-p4-t0","doc_id":"K202238","page_num":4,"bbox":[78.0,188.4,545.76,718.44],"n_rows":12,"n_cols":2,"columns":["Date:","August 06, 2020"],"rows":[["Date:","August 06, 2020"],["Submitter:","GE Healthcare (GE Healthcare (Tianjin) Company Limited)\nNo. 266 Jingsan Road,Tianjin Airport Economic Area\nTianjin, China 300308"],["Primary Contact\nPerson:","Qiang Ding\nRegulatory Affairs Leader\nPhone: +86 13311385163\nEmail: Ding.Qiang@ge.com"],["Secondary Contact\nPerson:","Glen Sabin\nRegulatory Affairs Director\nPhone: 262-894-4968\nEmail: Glen.Sabin@ge.com"],["Device Trade Name:","SIGNA Artist"],["Common/Usual Name:","Magnetic Resonance Diagnostic Device"],["Classification Names:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","21 CFR 892.1000"],["Primary Product Code:","LNH"],["Secondary Product Code:","LNI, MOS"],["Predicate Device:","SIGNA Artist (K163331)"],["Device Description:","The SIGNA Artist system is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and short scan\ntimes. The system features a superconducting magnet. The data acquisition\nsystem accommodates up to 128 independent receive channels in various\nincrements and multiple independent coil elements per channel during a\nsingle acquisition series. The system uses a combination of time varying\nmagnetic fields (gradients) and RF transmissions to obtain information\nregarding the density and position of elements exhibiting magnetic\nresonance. The system can image in the sagittal, coronal, axial, oblique, and\ndouble oblique planes, using various pulse sequences and reconstruction\nalgorithms.\nThis 510(k) submission is for the SIGNA Artist 1.5T MR system, and has\nbeen triggered by the addition of the AIR Recon DL software feature."]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202238-p5-t0","doc_id":"K202238","page_num":5,"bbox":[78.0,117.24,545.76,646.08],"n_rows":3,"n_cols":2,"columns":["","The AIR Recon DL feature has been previously cleared for use on the\nSIGNA Premier 3T system through K193282, which is used as a reference\ndevice for this submission."],"rows":[["","The AIR Recon DL feature has been previously cleared for use on the\nSIGNA Premier 3T system through K193282, which is used as a reference\ndevice for this submission."],["Indications for Use:","The Indications for Use statement for the proposed device is identical to\nthat of the predicate device:\nThe SIGNA Artist system is a whole body magnetic resonance\nscanner designed to support high resolution, high signal-to-noise\nratio, and short scan times. It is indicated for use as a diagnostic\nimaging device to produce axial, sagittal, coronal, and oblique\nimages, spectroscopic images, parametric maps, and/or spectra,\ndynamic images of the structures and/or functions of the entire\nbody, including, but not limited to, head, neck, TMJ, spine, breast,\nheart, abdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body. Depending on the region of\ninterest being imaged, contrast agents may be used.\nThe images produced by the SIGNA Artist system reflect the\nspatial distribution or molecular environment of nuclei exhibiting\nmagnetic resonance. These images and/or spectra when\ninterpreted by a trained physician yield information that may assist\nin diagnosis.\nThe addition of the AIR Recon DL feature does not impact the intended\nuse of the SIGNA Artist system."],["Technology\nCharacteristics:","Many of the technological characteristics of the proposed SIGNA Artist\nsystem are unchanged from the predicate device. The SIGNA Artist\nsystem has been introduced an additional configuration with IPM magnet.\nThere are no changes to gradient, and RF subsystems compared to the\npredicate K163331. Key performance specifications (such as magnet\nstability, maximum gradient strength and slew rate, etc.) for the system\nare also unchanged.\nThe software used on the proposed SIGNA Artist system has been\nmodified to include the AIR Recon DL feature. The User interface\nprovides operators of the system with new options for selecting AIR\nRecon DL and adjusting the associated level of image noise reduction.\nThe resulting images can have higher SNR and improved sharpness\ncompared to images reconstructed without AIR Recon DL.\nAIR Recon DL has been previously cleared for use with GE Healthcare’s\n3T SIGNA Premier system through K193282. Due to the technical\nsimilarities, SIGNA Premier (K193282) is used as a reference device for\nthis submission."]],"caption_candidate":"(cid:28595)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202238-p6-t0","doc_id":"K202238","page_num":6,"bbox":[78.0,117.24,545.76,699.24],"n_rows":2,"n_cols":2,"columns":["Determination of\nSubstantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe AIR Recon DL feature has undergone the performance testing.\nThese tests were designed to evaluate the AIR Recon DL feature and its\nimpact on image quality, including SNR, sharpness, low contrast\ndetectability, and noise spectral content. Analysis was performed to\nconfirm that the feature does not introduce significant bias that might\nimpact quantitative measurements based on signal intensity. The\ninfluence of motion during image acquisition on the performance of AIR\nRecon DL was also evaluated.\nThe nonclinical testing demonstrated that AIR Recon DL does improve\nSNR and image sharpness while maintaining low contrast detectability\nand having minimal impacts to noise spectral content, average signal\nintensity, or the appearance of motion artifacts. AIR Recon DL was also\nable to maintain image SNR and did not sacrifice sharpness for images\nacquired with a reduced scan time. The nonclinical testing passed the\ndefined acceptance criteria, and did not identify any adverse impacts to\nimage quality or other concerns related to safety and performance.\nSummary of Clinical Tests:\nObjective measures of in vivo images were analyzed to confirm that AIR\nRecon DL improves SNR and image sharpness for typical clinical use\ncases.\nAdditionally, sample images from clinically indicated scans were\nevaluated both with and without the AIR Recon DL feature. These\nsamples included images using exogenous contrast and images involving\npathology spanning a variety of anatomies and pulse sequences.\nRadiologists were asked to rate the images, and to comment on any\nnotable aspects related to image quality. This study showed that the AIR\nRecon DL feature provides images with equivalent or better image\nquality, lesion conspicuity is maintained, and that the radiologists\npreferred the AIR Recon DL images for clinical use."],"rows":[["Determination of\nSubstantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe AIR Recon DL feature has undergone the performance testing.\nThese tests were designed to evaluate the AIR Recon DL feature and its\nimpact on image quality, including SNR, sharpness, low contrast\ndetectability, and noise spectral content. Analysis was performed to\nconfirm that the feature does not introduce significant bias that might\nimpact quantitative measurements based on signal intensity. The\ninfluence of motion during image acquisition on the performance of AIR\nRecon DL was also evaluated.\nThe nonclinical testing demonstrated that AIR Recon DL does improve\nSNR and image sharpness while maintaining low contrast detectability\nand having minimal impacts to noise spectral content, average signal\nintensity, or the appearance of motion artifacts. AIR Recon DL was also\nable to maintain image SNR and did not sacrifice sharpness for images\nacquired with a reduced scan time. The nonclinical testing passed the\ndefined acceptance criteria, and did not identify any adverse impacts to\nimage quality or other concerns related to safety and performance.\nSummary of Clinical Tests:\nObjective measures of in vivo images were analyzed to confirm that AIR\nRecon DL improves SNR and image sharpness for typical clinical use\ncases.\nAdditionally, sample images from clinically indicated scans were\nevaluated both with and without the AIR Recon DL feature. These\nsamples included images using exogenous contrast and images involving\npathology spanning a variety of anatomies and pulse sequences.\nRadiologists were asked to rate the images, and to comment on any\nnotable aspects related to image quality. This study showed that the AIR\nRecon DL feature provides images with equivalent or better image\nquality, lesion conspicuity is maintained, and that the radiologists\npreferred the AIR Recon DL images for clinical use."],["Conclusion Drawn from\nPerformance Testing:","The nonclinical and clinical testing demonstrated that AIR Recon DL\nsatisfies the product claims of improved SNR and image sharpness, and\ncan enable shorter scan times while maintaining SNR and image\nsharpness.\nThe proposed SIGNA Artist system with AIR Recon DL has been\ndeveloped under GE Healthcare’s quality system and is at least as safe\nand effective as the legally marketed predicate. The performance testing\ndid not identify any new hazards, adverse effects, or safety and"]],"caption_candidate":"(cid:28595)","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K202280-p4-t1","doc_id":"K202280","page_num":4,"bbox":[71.64,317.6,539.52,414.52],"n_rows":6,"n_cols":2,"columns":["Trade Name","Cleerly Labs v2.0 (K202280)"],"rows":[["Trade Name","Cleerly Labs v2.0 (K202280)"],["Common Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050 Picture Archiving And Communications\nSystem"],["",""],["Regulatory Class","Class II"],["Product Code","LLZ"]],"caption_candidate":"Table 2: Cleerly Labs v2.0 Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202280-p4-t2","doc_id":"K202280","page_num":4,"bbox":[71.64,478.88,539.52,576.04],"n_rows":6,"n_cols":2,"columns":["Trade Name","Cleerly Labs (K190868)"],"rows":[["Trade Name","Cleerly Labs (K190868)"],["Common Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050 Picture Archiving And Communications\nSystem"],["",""],["Regulatory Class","Class II"],["Product Code","LLZ"]],"caption_candidate":"Table 3: Predicate Device Information","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K202280-p8-t0","doc_id":"K202280","page_num":8,"bbox":[107.92,136.2,540.23,298.56],"n_rows":7,"n_cols":3,"columns":["Output","Pearson Correlation\nCoefficient","Bland-Altman Agreement"],"rows":[["Output","Pearson Correlation\nCoefficient","Bland-Altman Agreement"],["Lumen Volume","0.91","96%"],["Vessel Volume","0.93","97%"],["Total Plaque Volume","0.85","95%"],["Calcified Plaque Volume","0.94","95%"],["Non-Calcified Plaque Volume","0.74","95%"],["Low-Density-Non-Calcified\nPlaque Volume","0.53","97%"]],"caption_candidate":"Table 6: Cleerly Labs Performance","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K202284-p7-t0","doc_id":"K202284","page_num":7,"bbox":[71.22,728.33,541.42,741.55],"n_rows":2,"n_cols":6,"columns":["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","","Baltimore, MD 21205 USA",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K202300-p18-t1","doc_id":"K202300","page_num":18,"bbox":[83.28,479.52,512.14,698.1],"n_rows":14,"n_cols":21,"columns":["Pilot Study Validation Set","","","","","","","","","","","","","","","","","","","",""],"rows":[["Pilot Study Validation Set","","","","","","","","","","","","","","","","","","","",""],["","","","","Malignant","","","","","","Benign","","","","","","Total","","","",""],["Scanner Manufacturer","","","N","","","%","","","N","","","%","","","N","","","%","",""],["","GE","","","60","","","67","","","30","","","33","","","90","","","30",""],["Philips","","","27 55","","","","","","22 45","","","","","","49 16","","","","",""],["","Siemens","","","41","","","47","","","46","","","53","","","87","","","29",""],["Canon/Toshiba","","","22 30","","","","","","52 70","","","","","","74 25","","","","",""],["","Total","","","150","","","50","","","150","","","50","","","300","","","100",""],["Reconstructed Slice Spacing (mm)","","","","","","","","","","","","","","","","","","","",""],["","<1.0","","","32","","","64","","","18","","","36","","","50","","","17",""],["1.0 - <1.5","","","69 68","","","","","","33 32","","","","","","102 34","","","","",""],["","1.5 - <2.0","","","1","","","33","","","2","","","67","","","3","","","1",""],["2.0 - <=2.5","","","48 33","","","","","","97 67","","","","","","145 48","","","","",""],["","Total","","","150","","","50","","","150","","","50","","","300","","","100",""]],"caption_candidate":"represented, and a variety of slice spacings up to 2.5mm.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202300-p19-t0","doc_id":"K202300","page_num":19,"bbox":[74.22,135.36,519.73,335.44],"n_rows":12,"n_cols":24,"columns":["Pilot Study Validation Set","","","","","","","","","","","","","","","","","","","","","","",""],"rows":[["Pilot Study Validation Set","","","","","","","","","","","","","","","","","","","","","","",""],["","","","","Malignant","","","","","","","","","Benign","","","","","","","","","",""],["Dose Information","","","N","","","Median Range","","","","","","N","","","Median Range","","","","","","N Total","",""],["","kVp <=100","","","","","","","","","","","","","","","","","","","","","",""],["CTDIvol","","","5/12 4.9 3.3-6.8","","","","","","","","","3/3 8.2 4.5-10.6","","","","","","","","","8/15","",""],["","Exposure (mAs)","","","9/12","","","69","","","1.0-108.0","","","3/3","","","98","","","56.0-126.0","","","12/15",""],["kVp 101-120","","","","","","","","","","","","","","","","","","","","","","",""],["","CTDIvol","","","64/138","","","7.4","","","1.6-32.8","","","39/144","","","7.3","","","1.6-32.8","","","103/282",""],["Exposure (mAs)","","","129/138 44 1.0-375.0","","","","","","","","","136/144 42.5 1.0-266.0","","","","","","","","","265/282","",""],["","kVp >120","","","","","","","","","","","","","","","","","","","","","",""],["CTDIvol","","","0/0 - -","","","","","","","","","1/3 12.6 12.6-12.6","","","","","","","","","1/3","",""],["","Exposure (mAs)","","","0/0","","","-","","","-","","","3/3","","","76","","","2.0-165.5","","","3/3",""]],"caption_candidate":"the category.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202300-p19-t1","doc_id":"K202300","page_num":19,"bbox":[74.22,451.5,525.55,647.4],"n_rows":13,"n_cols":19,"columns":["Reader","","LoM1 AUC","","","LoM1 AUC\n95%CI","","","LoM2 AUC","","","LoM2 AUC\n95% CI","","","Delta\nAUC","","Delta AUC\n95%CI","",""],"rows":[["Reader","","LoM1 AUC","","","LoM1 AUC\n95%CI","","","LoM2 AUC","","","LoM2 AUC\n95% CI","","","Delta\nAUC","","Delta AUC\n95%CI","",""],["1","","","75.3","","","69.6-80.5","","","85.2","","","80.8-89.2","","9.88","","","6.22-13.66",""],["2","","80.0","","","75.0-84.8","","","88.2","","","84.2-91.9","","","8.25","","5.74-10.97","",""],["3","","","79.2","","","74.0-84.1","","","89.4","","","85.7-92.7","","10.20","","","6.52-14.01",""],["4","","76.5","","","70.8-81.7","","","88.6","","","84.6-92.1","","","12.14","","8.11-16.40","",""],["5","","","87.5","","","83.5-91.2","","","89.9","","","86.2-93.1","","2.42","","","1.18-3.68",""],["6","","82.5","","","77.6-86.9","","","89.4","","","85.7-92.7","","","6.93","","4.01-10.10","",""],["7","","","85.7","","","81.3-89.7","","","89.5","","","85.7-92.8","","3.78","","","1.62-6.14",""],["8","","80.5","","","75.5-85.1","","","88.0","","","84.1-91.6","","","7.52","","5.02-10.13","",""],["9","","","85.4","","","80.8-89.5","","","90.2","","","86.6-93.5","","4.79","","","2.67-7.02",""],["10","","82.1","","","77.0-86.6","","","89.6","","","85.9-92.8","","","7.52","","4.16-11.08","",""],["11","","","83.8","","","79.2-88.1","","","89.2","","","85.4-92.6","","5.37","","","2.36-8.50",""],["12","","84.6","","","80.1-88.8","","","88.0","","","83.9-91.6","","","3.42","","1.58-5.34","",""]],"caption_candidate":"Table 6: Reader performance summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202404-p5-t0","doc_id":"K202404","page_num":5,"bbox":[84.32,106.86,551.68,162.96],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["SubtleMR","Subtle Medical, Inc.","K191688"]],"caption_candidate":"III. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202404-p5-t1","doc_id":"K202404","page_num":5,"bbox":[84.32,619.68,526.44,673.92],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["SubtleMR","Subtle Medical, Inc.","K191688"]],"caption_candidate":"the attributes suggested in FDA’s website guidance for this comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202404-p6-t0","doc_id":"K202404","page_num":6,"bbox":[72.13,106.78,523.78,397.08],"n_rows":6,"n_cols":7,"columns":["","Predicate Device\nSubtleMR","","","Subject Device","","Comment"],"rows":[["","Predicate Device\nSubtleMR","","","Subject Device","","Comment"],["","","","","BoneMRI","",""],["Intended Use","SubtleMR is an image\nprocessing software\nthat can be used for\nimage enhancement in\nMRI images. It can be\nused to reduce image\nnoise for head, spine,\nneck, and knee MRI,\nor increase image\nsharpness for non-\ncontrast-enhanced\nhead MRI.","","BoneMRI is an image\nprocessing software\nthat can be used for\nimage enhancement in\nMR images. It can be\nused to visualize the\nbone structures in MR\nimages with enhanced\ncontrast with respect\nto the surrounding soft\ntissue","","","Similar –\nIntended uses are\nthe same for Image\nenhancements for\nMRI. But the\nintended use\ndifferences does\nnot affect the\nsafety and\neffectiveness of the\ndevice when used\nas labeled and is\nsimilar to the\npredicate use."],["21CFR Section","892.2050","","892.2050","","","The same"],["Product Code","LLZ","","QIH","","","Similar"],["Target Population","Adults","","Adults","","","The same"]],"caption_candidate":"A. Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202404-p6-t1","doc_id":"K202404","page_num":6,"bbox":[72.13,439.06,523.78,702.36],"n_rows":7,"n_cols":7,"columns":["","Predicate Device\nSubtleMR","","","Subject Device","","Comment"],"rows":[["","Predicate Device\nSubtleMR","","","Subject Device","","Comment"],["","","","","BoneMRI","",""],["Device Nature","Software package","","Software package","","","The same"],["Operating System","Linux","","Linux","","","The same"],["Data input","MRI images in\nDICOM format","","MRI images in\nDICOM format","","","The same"],["Data output","MRI images in\nDICOM format","","MRI images in\nDICOM format","","","The same"],["Processing\nAlgorithms","SubtleMR software\nimplements an image\nenhancement\nalgorithm using\nconvolutional neural\nnetwork based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of filter","","MRIguidance\nsoftware implements\nan image\nenhancement\nalgorithm using\nconvolutional neural\nnetwork. Original\nimages are enhanced\nby running them\nthrough a cascade of","","","Different –\nThe algorithm while\nusing similar\nmethodology, uses\ndifferent filters and\noutputs to enhance\nthe image. The\ndifference does not\naffect the safety and"]],"caption_candidate":"B. Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202404-p7-t0","doc_id":"K202404","page_num":7,"bbox":[71.96,79.18,523.77,672.6],"n_rows":5,"n_cols":8,"columns":["","","Predicate Device","","","Subject Device","","Comment"],"rows":[["","","Predicate Device","","","Subject Device","","Comment"],["","","SubtleMR","","","BoneMRI","",""],["","banks, where\nthresholding and\nscaling operations are\napplied. Separate\nneural network based\nfilters are obtained\nfor noise reduction\nand sharpness\nincrease. The\nparameters of the\nfilters were obtained\nthrough an image\nguided optimization\nprocess.","","","filter banks, where\nthresholding and\nscaling operations\nare applied. Separate\nneural network-\nbased filters are\nobtained to assign a\nHounsfield Unit\n(HU) value to a\nsingle volume\nelement, based on\nintensity and\ncontextual\ninformation. The\nparameters of the\nmodel were obtained\nthrough an algorithm\ndevelopment\npipeline.","","","effectiveness of the\ndevice when used as\nlabeled and is similar\nto the predicate use."],["User Interface","None – enhanced\nimages are viewed on\nexisting PACS\nworkstations","","","None – enhanced\nimages are viewed\non existing PACS\nworkstations","","","The same"],["Workflow","The software\noperates on DICOM\nfiles on the file\nsystem, enhances the\nimages, and stores\nthe enhanced images\non the file system.\nThe receipt of\noriginal DICOM\nimage files and\ndelivery of enhanced\nimages as DICOM\nfiles depends on other\nsoftware systems.\nEnhanced images co-\nexist with the original\nimages.","","","The software\noperates on DICOM\nfiles on the file\nsystem, enhances the\nimages, and stores\nthe enhanced images\non the file system.\nThe receipt of\noriginal DICOM\nimage files and\ndelivery of enhanced\nimages as DICOM\nfiles depends on\nother software\nsystems. Enhanced\nimages co-exist with\nthe original images.","","","The same"]],"caption_candidate":"BoneMRI Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202414-p5-t0","doc_id":"K202414","page_num":5,"bbox":[108.47,394.07,539.99,684.95],"n_rows":7,"n_cols":3,"columns":["Device","Proposed Device","Predicate Device"],"rows":[["Device","Proposed Device","Predicate Device"],["","BrainInsight","NeuroQuant, K170981"],["Classification","Class II, LLZ, 21 CFR 892.2050","Class II, LLZ, 21 CFR 892.2050"],["Intended Use","Automatic labeling, spatial\nmeasurement, and volumetric\nquantification of brain structures\nfrom a set of low-field MR\nimages and returns annotated\nand segmented images, color\noverlays, and reports.","Automatic labeling, visualization\nand volumetric quantification of\nsegmentable brain structures and\nlesions from a set of MR images.\nVolumetric data may be\ncompared to reference percentile\ndata"],["Target Anatomical Sites","Brain","Brain"],["Technology","▪ Automated measurement of\nbrain tissue volumes and\nstructures\n▪ Automatic segmentation and\nquantification of brain structures\nusing machine learning","• Automated measurement of\nbrain tissue volumes and\nstructures and lesions\n• Automatic segmentation and\nquantification of brain structures\nusing a dynamic probabilistic\nneuroanatomical atlas, with age\nand gender specificity, based on\nthe MR image intensity"],["Method of Use","MR images are automatically\nsent to BrainInsight and\nprocessed images are\nautomatically returned in\napproximately 7 minutes.","User manually sends MR images\nto NeuroQuant and processed\nimages are automatically\nreturned in approximately 7\nminutes."]],"caption_candidate":"As required by 807.92(a)(6)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202414-p6-t0","doc_id":"K202414","page_num":6,"bbox":[108.47,108.71,539.99,618.47],"n_rows":8,"n_cols":3,"columns":["Device","Proposed Device","Predicate Device"],"rows":[["Device","Proposed Device","Predicate Device"],["","BrainInsight","NeuroQuant, K170981"],["User Interface / Physical\nCharacteristics","• No software required\n• Operates in a serverless cloud\nenvironment\n• User interface through PACS\n(multiple vendors)","• Software package installed on\nUser hardware\n• Operates on off-the-shelf\nhardware (multiple vendors)\n• User interface through the\nsoftware package"],["Operating System","Supports Linux","Supports Linux, Mac OS X and\nWindows"],["Processing Architecture","Automated internal pipeline that\nperforms:\n- segmentation\n- volume calculation\n- distance measurement\n- numerical information display","Automated internal pipeline that\nperforms:\n- artifact correction\n- segmentation\n- lesion quantification\n- volume calculation\n- report generation"],["Data Source","▪ MRI scanner: Hyperfine FSE\nMRI scans acquired with\nspecified protocols\n▪ Supports DICOM format as\ninput","▪ MRI scanner: 3D T1 MRI\nscans acquired with specified\nprotocols\n▪ NeuroQuant Supports DICOM\nformat as input"],["Output","Provides volumetric\nmeasurements of brain structures\n▪ Includes segmented color\noverlays and morphometric\nreports\n▪ Supports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and Communications\nSystems","Provides volumetric\nmeasurements of brain structures\nand lesions\n▪ Includes segmented color\noverlays and morphometric\nreports\n▪ Automatically compares results\nto reference percentile data and\nto prior scans when available\n▪ Supports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and Communications\nSystems"],["Safety","Automated quality control\nfunctions\n▪ Tissue contrast check\n▪ Scan protocol verification\n▪ Atlas alignment check\n▪ Results must be reviewed by a\ntrained physician","Automated quality control\nfunctions\n▪ Tissue contrast check\n▪ Scan protocol verification\n▪ Atlas alignment check\n▪ Results must be reviewed by a\ntrained physician"]],"caption_candidate":"As required by 807.92(a)(6)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202487-p4-t0","doc_id":"K202487","page_num":4,"bbox":[72.57,485.96,531.18,565.11],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Efficient Care 3D Planning"],"rows":[["Proprietary Name","Efficient Care 3D Planning"],["Premarket Notification","K183544"],["Classification Name","Picture Archiving and Communication System"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"The HealthJOINT device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202487-p6-t0","doc_id":"K202487","page_num":6,"bbox":[72.9,375.93,561.1,711.93],"n_rows":2,"n_cols":4,"columns":["Technological\nCharacteristics","Proposed Device:\nHealthJoint","Predicate Device:\nEfficient Care 3D Planning\n(K183544)","Summary"],"rows":[["Technological\nCharacteristics","Proposed Device:\nHealthJoint","Predicate Device:\nEfficient Care 3D Planning\n(K183544)","Summary"],["Intended\nUse/Indications for\nUse","The Zebra HealthJOINT device is\na software tool for 3D\nreconstruction of bones from a set\nof 2D radiographs. The device is\nintended for assisting clinicians\nin the preoperative planning of\nknee orthopedic surgical\nprocedures. Zebra’s\nHealthJOINT analyzes cases\nusing an artificial intelligence\nalgorithm for the 3D model\nreconstruction. In addition to the\nmodel, the software provides a list\nof anatomical landmarks with\ntheir position on the 3D model.\nThe result is made available via a\n3rd parties’ software interface for\nfurther display and analysis of the\n3D bone model.\nClinical judgement and\nexperience are required to\nproperly use the models produced\nby this software.","Efficient Care 3D Planning is\nsoftware indicated for assisting\northopedic surgeons in preoperative\nplanning of knee orthopedic\nsurgeries. The software allows for\nthe overlaying of 3D/2D implant\nmodels and for the visualization of\nthe radiological images and 3D\nreconstruction of bones, and\nincludes tools for performing\nmeasurements on the images or 3D\nmodel of bones, and for selecting\nand positioning the implant model.\nClinical judgments and experience\nare required to properly use the\nsoftware.\nEfficient Care 3D Planning is to be\nused with the following fixed\nbearing knee replacement systems\nin accordance with their indications\nand contraindications: NexGen®\nCR, NexGen CR-Flex, NexGen\nCR-Flex Gender, NexGen LPS,\nNexGen LPS-Flex, NexGen\nLPSFlex Gender, Persona® CR,","Similar. In\naddition to the 3D\nreconstruction and\n3D/2D overlay for\nthe visualization\nof radiological\nimages, the\npredicate device\nalso provide tools\nfor performing\nmeasurements and\nfor selecting the\nimplant model."]],"caption_candidate":"A comparison of the technological characteristics with the predicate device is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202487-p7-t0","doc_id":"K202487","page_num":7,"bbox":[72.84,72.84,561.17,368.31],"n_rows":12,"n_cols":4,"columns":["","","Persona PS, Vanguard® CR, and\nVanguard PS.",""],"rows":[["","","Persona PS, Vanguard® CR, and\nVanguard PS.",""],["Classification/Produc\nt code","21 CFR 892.2050/LLZ","21 CFR 892.2050/LLZ","Same"],["User","Prespecified clinical users\n(clinicians)","Prespecified clinical users\n(clinicians)","Same"],["Radiological images\nformat","DICOM","DICOM","Same"],["Modality","X-ray","X-ray","Same"],["Body part","Knee","Knee","Same"],["Software processing","Image segmentation and\nprocessing","Image segmentation and processing","Same"],["Output","3D bone reconstruction","3D bone reconstruction","Same"],["2D/3D Overlay","Yes","Yes","Same"],["Anatomic Landmarks","Yes","Yes","Same"],["Measurement Tools","No","Yes","Different, but do\nnot raise\nquestions of\nsafety and\neffectiveness."],["Implant Predictability","No","Yes","Different, but do\nnot raise\nquestions of\nsafety and\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202501-p7-t0","doc_id":"K202501","page_num":7,"bbox":[100.93,102.6,561.47,715.44],"n_rows":17,"n_cols":5,"columns":["Item","Quantib Prostate","","DynaCAD",""],"rows":[["Item","Quantib Prostate","","DynaCAD",""],["","","","K192200",""],["Target users\nEquivalent","Trained medical professionals","Trained medical professionals","",""],["Anatomical site\nPartially\nequivalent","Prostate","Any","",""],["Where used\nEquivalent","Hospital","Hospital","",""],["Human factors\nEquivalent","User can approve or reject results","User can approve or reject results.","",""],["","User can inspect and edit prostate\nsegmentation","User can inspect and edit prostate\nsegmentation.","",""],["","User can enter PSA value and compute\nPSA density","User can enter PSA value and compute\nPSA density","",""],["","User can create and update regions of\ninterest (ROIs)","User can create and update regions of\ninterest (ROIs)","",""],["","User can add and update annotations (text)\nto analysis","User can add and update annotations (text)\nto analysis","",""],["","User can manually set a PI-RADS score\nusing a PI-RADS interactive worksheet","User can manually set a PI-RADS score\nusing a PI-RADS interactive worksheet","",""],["Design\nPartially\nequivalent","Semi-automatic prostate segmentation,\nMulti-parametric image review,\nBiparametric combination image viewer,\nBasic image manipulation tools,\nThresholding tool,\nUser interface to create/update user-\ngenerated ROIs.","Semi-automatic prostate segmentation,\nMulti-parametric image review,\nBasic image manipulation tools,\nThresholding tool\nUser interface to create/update user-\ngenerated ROIs.","",""],["Performance data","","","",""],["Non-clinical\nperformance\nPartially\nequivalent","Bench testing performed to test the\nfunctionality of the system.\nThis included characterization of the stand-\nalone performance of the prostate\nsegmentation algorithm.","Bench testing performed to test the\nfunctionality of the system.","",""],["Clinical\nperformance\nPredicate\ndevice has no\ndata to\nassess\nequivalency","Prostate segmentation algorithm was tested\nin a clinical use context, i.e. as a semi-\nautomatic algorithm after correction by\ntrained clinicians.","No clinical performance data available.","",""],["Standards\nmet\nEquivalent","• IS0 14971 – Medical devices -Application\nof risk management to medical devices\n• IEC 62304 – Medical device software –\nSoftware life cycle processes\n• IEC 62366 – Medical devices -\nApplication of usability engineering to\nmedical devices","• IS0 14971 – Medical devices -Application\nof risk management to medical devices\n• IEC 62304 – Medical device software –\nSoftware life cycle processes","",""],["SW\nverification\nand validation\nEquivalent","Tested in accordance with verification and\nvalidation processes and planning. The\ntesting results support that all the system\nrequirements have met their acceptance\ncriteria and are adequate for its intended","Tested in accordance with verification and\nvalidation processes and planning. The\ntesting results support that all the system\nrequirements have met their acceptance\ncriteria and are adequate for its intended","",""]],"caption_candidate":"6 COMPARISON OF TECHNOLOGICAL CHARACTERISTICS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202501-p8-t0","doc_id":"K202501","page_num":8,"bbox":[100.94,72.36,561.46,249.36],"n_rows":6,"n_cols":5,"columns":["Item","Quantib Prostate","","DynaCAD",""],"rows":[["Item","Quantib Prostate","","DynaCAD",""],["","","","K192200",""],["","use.","use.","",""],["Compatibility with\nthe environment\nand other devices\nEquivalent","DICOM compatible","DICOM compatible","",""],["Reported\nmeasures\nEquivalent","Prostate gland volume, PSA density, ROIs\nwithin the prostate, with for each ROI:\n• Volume\n• Average ADC value\n• PI-RADS score\n• Location","Prostate gland volume, PSA density, ROIs\nwithin the prostate, with for each ROI:\n• Volume\n• Average ADC value\n• PI-RADS score\n• Location","",""],["Required input\nEquivalent","DICOM compatible data, type of MRI\nscans: T2-weighted, DWI, ADC, DCE","DICOM compatible data, type of MRI\nscans: T2-weighted, DWI, ADC, DCE","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p5-t0","doc_id":"K202700","page_num":5,"bbox":[79.61,153.66,509.35,200.52],"n_rows":3,"n_cols":13,"columns":["","Regulation","","Device","","Device","","","Product","","","Classification",""],"rows":[["","Regulation","","Device","","Device","","","Product","","","Classification",""],["","Number","","","","Class","","","Code","","","Panel",""],["892.2050","","","Medical device software,\nradiology","Class 2","","","QKB","","","Radiology","",""]],"caption_candidate":"Primary Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p6-t0","doc_id":"K202700","page_num":6,"bbox":[66.68,165.15,725.5,525.15],"n_rows":23,"n_cols":14,"columns":["","","","","","","","General Information","","","","","",""],"rows":[["","","","","","","","General Information","","","","","",""],["Property","Property","","Proposed Device\nART-Plan","Proposed Device","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","","ART-Plan","","","Predicate","","","","","",""],["","","","","","","","AccuContour","","","","","",""],["","","","","","","","","","","","","",""],["Common\nName","","","Radiological\nimage processing\nsoftware for\nradiation therapy","","","Radiological\nimage processing\nsoftware for\nradiation therapy","","System, image\nprocessing,\nradiological","System, image\nprocessing,\nradiological","System, image processing,\nradiological","N/A","",""],["","Device","","TheraPanacea","","","Xiamen Manteia\nTechnology LTD","","Mirada Medical Ltd.","Mirada Medical Ltd.","MIMvista Corp (now MIM Software\nInc)","N/A","",""],["","Manufacturer","","","","","","","","","","","",""],["","510k","","N/A","","","K191928","","K130393","K181572","K071964","N/A","",""],["","Device","","II","","","II","","II","II","II","N/A","",""],["","Classification","","","","","","","","","","","",""],["Primary\nProduct\nCode","Primary","","QKB","","","QKB","","LLZ","LLZ","LLZ","As advised by the FDA the new\nproduct code, QKB, has been\ncreated in-lieu of LLZ which uses\nAI algorithms and is intended for\nradiation therapy, and is the\nproposed product code for ART-\nPlan.","",""],["","Product","","","","","","","","","","","",""],["","Code","","","","","","","","","","","",""],["","Secondary","","-","","","-","","-","-","-","N/A","",""],["","Product","","","","","","","","","","","",""],["","Code","","","","","","","","","","","",""],["Target\nPopulation","Target","","Any patient type\nfor whom relevant\nmodality scan data\nis available","","","Not stated","","Any patient type for\nwhom relevant\nmodality scan data\nis available.","Any patient type for\nwhom relevant\nmodality scan data\nis available.","Not stated","The proposed device has\nidentical target populations to the\nsecondary predicates.","",""],["","Population","","","","","","","","","","","",""],["Environment","","","Hospital","","","Hospital","","Hospital","Hospital","Hospital","The proposed device and\npredicates have identical\ntarget environments","",""],["","Intended","","Intended Use\nART-Plan is a\nsoftware designed","","","It is used by\nradiation\noncology","","Workflow Box is a\nsystem designed to\nallow users to route","RTx is intended to\nbe used by trained\nmedical","Intended Use\nMIM 4.1 (SEASTAR) software is\nintended for trained medical","The intended use and\nindications for use of the\nproposed device, ART-Plan","",""],["","Use/","","","","","","","","","","","",""],["","Indication for","","","","","","","","","","","",""]],"caption_candidate":"General Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p7-t0","doc_id":"K202700","page_num":7,"bbox":[66.68,96.18,725.46,524.5],"n_rows":6,"n_cols":13,"columns":["","","","","","","General Information","","","","","",""],"rows":[["","","","","","","General Information","","","","","",""],["Property","Property","Proposed Device\nART-Plan","Proposed Device","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","ART-Plan","","","Predicate","","","","","",""],["","","","","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["Use","","to assist the\ncontouring\nprocess of the\ntarget\nanatomical\nregions on 3D-\nimages of cancer\npatients for whom\nradiotherapy\ntreatment has\nbeen planned.\nThe SmartFuse\nmodule allows the\nuser to register\ncombinations of\nanatomical and\nfunctional images\nand display them\nwith fused and\nnon-fused displays\nto facilitate the\ncomparison and\ndelineation of\nimage data by the\nuser.\nThe images\ncreated with rigid\nor elastic\nregistration require\nverifications,\npotential\nmodifications, and\nthen the validation\nof a trained user\nwith professional\nqualifications in\nanatomy and\nradiotherapy.\nWith the Annotate\nmodule, users can","","","department to\nregister\nmultimodality\nimages and\nsegment (non-\ncontrast) CT\nimages, to\ngenerate needed\ninformation for\ntreatment\nplanning,\ntreatment\nevaluation and\ntreatment\nadaptation.","","DICOM-compliant\ndata to and from\nautomated\nprocessing\ncomponents.\nWorkflow Box\nincludes processing\ncomponents for\nautomatically\ncontouring imaging\ndata using\ndeformable image\nregistration and\nmachine learning\nbased algorithms.\nWorkflow Box must\nbe used in\nconjunction with\nappropriate\nsoftware to review\nand edit results\ngenerated\nautomatically by\nWorkflow Box\ncomponents, for\nexample image\nvisualization\nsoftware must be\nused to facilitate the\nreview and edit of\ncontours generated\nby Workflow Box\ncomponent\napplications.\nWorkflow Box is not\nintended to\nautomatically detect\nlesions.","professionals\nincluding, but not\nlimited to,\nradiologists, nuclear\nmedicine\nphysicians,\nradiation\noncologists,\ndosimetrists and\nphysicists.\nRTx is a software\napplication intended\nto display and\nvisualize 2D & 3D\nmulti-modal medical\nimage data. The\nuser may process,\nrender, review,\nstore, print and\ndistribute DICOM\n3.0\ncompliant datasets\nwithin the system\nand/or across\ncomputer networks.\nSupported\nmodalities\ninclude static and\ngated a, PET, MR,\nSPECT and planar\nNM. The user may\nalso create, display,\nprint, store and\ndistribute reports\nresulting from\ninterpretation of the\ndatasets.\nRTx allows the user\nto register\ncombinations of","professionals including, but not\nlimited to, radiologists,\noncologists, physicians, medical\ntechnologists, dosimetrists and\nphysicists.\nMIM 4.1 (SEASTAR) is a\nmedical image and information\nmanagement system that is\nintended to receive, transmit,\nstore, retrieve, display, print and\nprocess digital medical images,\nas well as create, display and\nprint reports from those images.\nThe medical modalities of these\nmedical imaging systems\ninclude, but are not limited to,\nCT, MRI, CR, DX, MG, US,\nSPECT, PET and XA as\nsupported by ACR/NEMA\nDICOM 3.0.\nMIM 4.1 (SEASTAR) provides\nthe user with the means to\ndisplay, register and fuse\nmedical images from multiple\nmodalities. Additionally, it\nevaluates cardiac left ventricular\nfunction and perfusion, including\nleft ventricular end-diastolic\nvolume, end-systolic volume,\nand ejection fraction. The\nRegion of Interest (ROI) feature\nreduces the time necessary for\nthe user to define objects in\nmedical image volumes by\nproviding an initial definition of\nobject contours. The objects\ninclude, but are not limited to,\ntumors and normal tissues.","and the primary predicate\nAccuContour are the same in\nthat they are software\napplications intended for\nprofessional use to\ndisplay and visualize multi-\nmodal medical image data.\nSupported modalities include\nCT, PET, and MR.\nThe proposed device is also\nidentical to the primary\npredicate in that it offers the\nsame two key features of the\nplanning process in\nradiotherapy: image\nregistration and\nsegmentation.\nIn both devices, segmentation\ncan only be performed on CT\nmodality; registration can be\ndone from every supported\nmodality toward a CT with\ndeformable registration.\nThe proposed device may\ndiffer from the primary\npredicate in a) the list of\nstructures included in\nautomatic segmentation\nalgorithm b) the presence or\nnot of a rigid registration\nalgorithm, which is a\nreduction compared to the\ndeformable registration that is\nprovided by ART-Plan.\nHowever, not enough\ninformation on these two\naspects is provided on the","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p8-t0","doc_id":"K202700","page_num":8,"bbox":[66.68,96.18,725.46,524.5],"n_rows":6,"n_cols":13,"columns":["","","","","","","General Information","","","","","",""],"rows":[["","","","","","","General Information","","","","","",""],["Property","Property","Proposed Device\nART-Plan","Proposed Device","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","ART-Plan","","","Predicate","","","","","",""],["","","","","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["","","edit manually and\nsemi-automatically\nthe contours for\nthe regions of\ninterest. It\nalso allows to\ngenerate\nautomatically, and\nbased on medical\npractices, the\ncontours for the\norgans at risk and\nhealthy lymph\nnodes on CT\nimages.\nThe contours\ncreated\nautomatically,\nsemi-automatically\nor manually\nrequire\nverifications,\npotential\nmodifications, and\nthen the validation\nof a trained user\nwith professional\nqualifications in\nanatomy and\nradiotherapy.\nThe device is\nintended to be\nused in a clinical\nsetting, by trained\nprofessionals only.\n.","","","","","","anatomical and\nfunctional images\nand display\nthem with fused and\nnon-fused displays\nto facilitate the\ncomparison of\nimage data by the\nuser. The result of\nthe registration\noperation can assist\nthe user in\nassessing changes\nin image\ndata; either within or\nbetween\nexaminations and\naims to help the\nuser obtain a better\nunderstanding of\nthe combined\ninformation that\nwould otherwise\nhave to be visually\ncompared\ndisjointedly.\nRTx provides a\nnumber of tools\nsuch as rulers and\nregion of interests,\nwhich are intended\nto\nbe used for the\nassessment of\nregions of an image\nto support a clinical\nworkflow. Examples\nof\nsuch workflows\ninclude, but are not","MIM 4.1 (SEASTAR) provides\ntools to quickly create,\ntransform, and modify\ncontours for applications\nincluding, but not limited to,\nquantitative analysis, aiding\nadaptive therapy, transferring\ncontours to radiation therapy\ntreatment planning systems and\narchiving contours for patient\nfollow-up and management.\nMIM 4.1 (SEASTAR) also aids\nin the assessment of\nPET/SPECT brain scans. It\nprovides automated quantitative\nand statistical analysis by\nautomatically registering\nPET/SPECT brain scans to a\nstandard template and\ncomparing intensity values to a\nreference database or to other\nPET/SPECT scans on a voxel\nby voxel basis, within\nstereotactic surface projections\nor standardized regions of\ninterest.\nIndications for Use\nMIM 4.1 (SEASTAR) software is\nused by trained medical\nprofessionals as a tool to aid in\nevaluation and information\nmanagement of digital medical\nimages. The\nmedical image modalities\ninclude, but are not limited to,\nCT, MRI, CR, DX, MG,","side of the primary predicate.","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p9-t0","doc_id":"K202700","page_num":9,"bbox":[66.68,96.18,725.46,524.5],"n_rows":6,"n_cols":13,"columns":["","","","","","","General Information","","","","","",""],"rows":[["","","","","","","General Information","","","","","",""],["Property","Property","Proposed Device\nART-Plan","Proposed Device","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","ART-Plan","","","Predicate","","","","","",""],["","","","","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["","","","","","","","","limited to, the\nevaluation of the\npresence or\nabsence of\nlesions,\ndetermination of\ntreatment response\nand follow-up.\nRTx supports the\nloading and saving\nof DICOM RT\nobjects and allows\nthe user to define,\nimport, display,\ntransform, store and\nexport such objects\nincluding regions of\ninterest\nstructures and dose\nvolumes to radiation\ntherapy planning\nsystems. RTx\nallows the user to\ntransform regions of\ninterest associated\nwith a particular\nimaging dataset to\nanother,\nsupporting atlas-\nbased contouring\nand rapid re-\ncontouring of the\nsame patient.","US, SPECT, PET and XA as\nsupported by ACR/NEMA\nDICOM 3.0. MIM 4.1\n(SEASTAR) assists in the\nfollowing indications:\n* Receive, transmit, store,\nretrieve, display, print, and\nprocess medical images\nand DICOM objects.\n* Create, display and print\nreports from medical images.\n* Registration, fusion display,\nand review of medical images\nfor diagnosis,\ntreatment evaluation, and\ntreatment planning.\n* Evaluation of cardiac left\nventricular function and\nperfusion, including left\nventricular end-diastolic volume,\nend-systolic volume, and\nejection fraction.\n* Localization and definition of\nobjects such as tumors and\nnormal tissues in\nmedical images.\n* Creation, transformation, and\nmodification of contours for\napplications\nincluding, but not limited to,\nquantitative analysis, aiding\nadaptive therapy,\ntransferring contours to radiation\ntherapy treatment planning\nsystems, and\narchiving contours for patient\nfollow-up and management.\n* Quantitative and statistical\nanalysis of PET/SPECT brain\nscans by comparing to other","","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p10-t0","doc_id":"K202700","page_num":10,"bbox":[66.68,96.18,725.46,340.54],"n_rows":6,"n_cols":13,"columns":["","","","","","","General Information","","","","","",""],"rows":[["","","","","","","General Information","","","","","",""],["Property","Property","Proposed Device\nART-Plan","Proposed Device","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","ART-Plan","","","Predicate","","","","","",""],["","","","","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["","","","","","","","","","registered PET/SPECT brain\nscans\nLossy compressed\nmammographic images and\ndigitized film screen images\nmust not be reviewed for\nprimary image interpretations.\nImages that are printed to film\nmust be printed using a FDA-\napproved printer for the\ndiagnosis of digital\nmammography images.\nMammographic images must be\nviewed on a display\nsystem that has been cleared by\nthe FDA for the diagnosis of\ndigital mammography images.\nThe software is not to be used\nfor mammography CAD.","","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p11-t0","doc_id":"K202700","page_num":11,"bbox":[66.68,120.3,725.47,526.36],"n_rows":6,"n_cols":14,"columns":["","","","","","","System Information","","","","","","",""],"rows":[["","","","","","","System Information","","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","","","Primary\nPredicate\nAccuContour","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM 4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","","","","","","","",""],["","","","ART-Plan","","","","","","","","","",""],["Method of Use","","Standalone\nsoftware\napplication\naccessed via a\ncompliant\nbrowser (Chrome\nor Mozilla\nFirefox) on a\npersonal\ncomputer, tablet\nor phone (In\ncase of\nconnection to the\nplatform with a\nscreen of a\nphone or a\ntablet, the user\nmust choose the\noption for the\ndesktop site of\nhis\ncommunication\ndevice. The\nplatform is\noptimally used\nwith 17 inches\nand up screen.\nFacilitates\ndisplay and\nvisualization of\ndata by user.","","","","","Standalone\nsoftware","Standalone software\napplication","Standalone software\napplication","Standalone software package","The proposed device and\npredicates have identical\nmethods of use","",""],["Computer\nPlatform and\nOperating\nSystem","","Full web platform\nLaunch from\nGoogle Chrome\nor Mozilla Firefox","","","","","Windows","Workstation and\nServer based\napplication\nsupporting Windows\nServer 2008 R2,","Server based\napplication\nsupporting Microsoft\nWindows 10 (64-bit)\nand Microsoft","Windows 2000/XP","The proposed devices and\npredicates are compatible with\nidentical operating systems","",""]],"caption_candidate":"System Information Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p12-t0","doc_id":"K202700","page_num":12,"bbox":[66.68,96.18,725.48,526.0],"n_rows":7,"n_cols":14,"columns":["","","","","","","System Information","","","","","","",""],"rows":[["","","","","","","System Information","","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","","","Primary\nPredicate\nAccuContour","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM 4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","","","","","","","",""],["","","","ART-Plan","","","","","","","","","",""],["","","","","","","","","SP1 and Windows 7\n(64-bit)","Windows Server\n2016.","","","",""],["Data\nVisualization /\nGraphical\nInterface","","Yes","","","","","Yes","Yes","None – the\nproposed device\nhas no data\nvisualization\nfunctionality. All data\nprocessing is\nautomated and does\nnot require user\ninteraction. A control\ninterface is provided\nfor system\nadministration and\nconfiguration only.","Yes","The proposed device is identical\nto the primary predicate, and\nsecondary predicate, MIM 4.1, in\nthat it has a graphical interface.\nWorkflow Box is AI based but\nhas no interface. RTx is not AI\nbased but has an interface and\nthus most of the tools of\nAnnotate for contour\nedition/display","",""],["Supported\nModalities","","Registration:\nStatic and gated\nCT, MR, PET\n(via the\nregistration of\nthe CT of said\nPET)\nSegmentation:\nCT (injected or\nnot), DICOM\nRTSTRUCT","","","","","Registration:\nMultimodality\nDICOM fixed and\nmoving images\nincluding CT,\nMR, PET\nSegmentation:\nNon-contrast CT","Static and gated CT\nand PET, MR,\nSPECT, NM,\nDICOM RT","CT, MR, DICOM\nRTSTRUCT for\nimage\nprocessing\nAny valid DICOM\ndata for data routing","Medical image modalities include,\nbut are not limited to, CT, MRI,\nCR, DX, MG, US, SPECT, PET\nand XA as supported by\nACR/NEMA DICOM 3.0.","The proposed device is\ncompatible with the same\nmodalities as the primary\npredicate on the registration\nfeature, which are CT, MR and\nPET images in a DICOM format.\nFor both devices, supported\nimages can be fixed (static) or\nmoving (gated).\nThe primary predicate device\nand ART-Plan are both\ncompatible only with CT images\non the segmentation feature.\nThe predicate device claims to\nhandle only non-injected CTs\nwhile ART-Plan can be used\nwith injected CT images as well.\nThe predicate device does not","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p13-t0","doc_id":"K202700","page_num":13,"bbox":[66.68,96.18,725.48,524.32],"n_rows":7,"n_cols":14,"columns":["","","","","","","System Information","","","","","","",""],"rows":[["","","","","","","System Information","","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","","","Primary\nPredicate\nAccuContour","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM 4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","","","","","","","",""],["","","","ART-Plan","","","","","","","","","",""],["","","","","","","","","","","","explicitly mention the format\nRTStruct in supported\nmodalities which correspond to\nthe format used to store\nsegmentation masks in\nradiotherapy. The terms\n“medical images and DICOM\ndata” are used by the primary\npredicate device, which can\nimply the management of\nDICOM RTStruct.\nCompared to secondary\npredicates, ART-Plan claims\nless supported modalities.","",""],["Data Export","","Distribution of\nDICOM\ncompliant\nImages into\nother DICOM\ncompliant\nsystems.","","","","","Allows export of\nmedical images\nand DICOM data","Distribution of\nDICOM compliant\nImages into other\nDICOM compliant\nsystems.","Supports routing\nand distribution of\nimages to other\nDICOM nodes\nincluding to custom\nexecutables\ndetermined by the\nuser.","The system has the ability to send\ndata to DICOM-ready devices for\nimage storage, retrieval and\ntransmission.","The proposed device and\nprimary predicates have\nidentical data export\ncapabilities.","",""],["Comtibility","","Compatible with\ndata from any\nDICOM\ncompliant\nscanners for the\napplicable\nmodalities.","","","","","No Limitation on\nscanner model,\nDICOM 3.0\ncompliance\nrequired.\nCompatible with\nMicrosoft\nWindows.","Compatible with\ndata from any\nDICOM compliant\nscanners for the\napplicable\nmodalities.","Compatible with\ndata from any\nDICOM compliant\nscanners for the\napplicable\nmodalities.\nIntegration with\nMirada DBx\napplication launcher","The software can receive,\ntransmit, store, retrieve, display,\nprint, and process DICOM objects\nand medical image modalities\nincluding, but not limited to, CT,\nMRI, CR, DX, MG, US, SPECT,\nPET and XA as supported by\nACR/NEMA DICOM 3.0.","The proposed device and\nprimary predicates have\nidentical compatibilities","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p14-t0","doc_id":"K202700","page_num":14,"bbox":[66.68,96.18,725.46,232.42],"n_rows":5,"n_cols":14,"columns":["","","","","","","System Information","","","","","","",""],"rows":[["","","","","","","System Information","","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","","","Primary\nPredicate\nAccuContour","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM 4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","","","","","","","",""],["","","","ART-Plan","","","","","","","","","",""],["","","","","","","","No Limitation on\ntreatment\nplanning system\n(TPS) model,\nDICOM 3.0\ncompliance\nrequired.","","and data browser","","","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p15-t0","doc_id":"K202700","page_num":15,"bbox":[66.68,119.16,725.48,523.18],"n_rows":8,"n_cols":13,"columns":["","","","","","","Technical Information","","","","","",""],"rows":[["","","","","","","Technical Information","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","Predicate","","","","","",""],["","","","ART-Plan","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["Delineation\nMethod","","AI","","","AI","","Atlas","AI","Atlas","The proposed device, primary\npredicate and secondary\npredicate Workflow Box share\nan AI delineation method.","",""],["Image\nregistration","","Multi-modal\nand mono-\nmodal.\nRigid and\ndeformable\nAutomatic and\nmanual\ninitialization\n(landmarks,\nfusion box,\nalignment).\nRegistration for\nthe purposes of\nreplanning/\nrecontouring\nand AI-based\nautomatic\ncontouring.","","","Automatic\nregistration.\nMulti-modal and\nmono-modal.\nDeformable\nregistration.\nIntensity based\nalgorithm\nRegistration for\nthe purpose of\ntreatment\nplanning,\ntreatment\nevaluation and\ntreatment\nadaptation.","","Manual and Landmark\nRigid. Automatic multi-\nmodal rigid. Mono-\nmodal and multi-modal\ndeformable registration.\nMotion correction in\nhybrid scans and gated\nscans.\nRegistration for the\npurposes of\nreplanning/recontouring\nand atlas-based\ncontouring.","Registration for the\npurposes of\nreplanning/\nre-contouring and\nAI based\ncontouring. The\nalgorithms used\nfor image\nregistration are the\nsame for both RTx\nand Workflow Box\ndevices.","Registration, fusion display, and\nreview of medical images for\ndiagnosis, treatment\nevaluation, and treatment\nplanning.","Both the predicate device and\nART-Plan offer mono-modal (CT-\nCT) and multi-modal (CT/MR,\nCT/PET) deformable registration.\nThe SmartFuse module of ART-\nPlan also offers rigid\nregistration, which is a\nreduction of the deformable\nregistration since the degree of\nfreedom of the transformation\nare constrained.\nBoth devices offer an automatic\nsolution for registration. ART-\nPlan also offers semi-automatic\nregistration by including manual\ninitialization tools in addition to\nautomatic initialization.\nSecondary devices offer the\nsame options as the proposed\ndevice: rigid and deformable\ntransformation. No information\nis given on the possible\nautomatization of this process.","",""],["Segmentation\nFeatures","","Automatically\ndelineates\nOARs and\nhealthy lymph\nnodes (on any","","","Automatically\ndelineates OAR\n(on non-contrast\nCT images)","","Automatically\ndelineates any structure\n(OAR or lymph node)\nincluded in the atlas","Not stated.","The software automatically\ngenerates contours using a\ndeformable registration technique\nwhich registers pre-contoured\npatients to target patients.","The proposed device and\nprimary predicate are capable of\nautomatically contouring the\norgan-at-risk (OAR).","",""]],"caption_candidate":"Technical Information Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p16-t0","doc_id":"K202700","page_num":16,"bbox":[66.68,96.18,725.47,518.08],"n_rows":7,"n_cols":13,"columns":["","","","","","","Technical Information","","","","","",""],"rows":[["","","","","","","Technical Information","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","Predicate","","","","","",""],["","","","ART-Plan","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["","","CT images)\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n* head and\nneck\n* thorax/breast\n(for\nmale/female)\n* abdomen\n* pelvis (for\nmale only)\n* brain.","","","Deep learning\nalgorithm.\nIt can\nautomatically\ncontour the\norgan-at-risk,\nincluding head\nand neck,\nthorax, abdomen\nand pelvis (for\nboth male and\nfemale),","","images.\nAtlas algorithm (contour\nregistration)\nAutomatic\nsegmentation supports\nany anatomy included\nin atlas images.","","Registrations are either\nbetween a serial pair of intra-\npatient volumes or between a pre-\nexisting atlas of contoured patients\nand a patient volume. This process\nfacilitates contour creation or re-\ncontouring for adaptive therapy.","They differ in that ART-Plan can\nalso delineate healthy lymph\nnodes.\nPlus, there is a difference in\nintended anatomies. The\ncommon localizations are the\nhead and neck, thorax, abdomen\nand male pelvis. ART-Plan does\nnot claim to offer automatic\nsegmentation on female pelvis.\nHowever, in addition to the 4\nupper common localizations,\nART-Plan can also be used for\nbrain localizations.\nSecondary predicate using\natlas-based algorithms can be\napplied on any localization and\nfor any type of structure\ncontained in atlas images used\nby the center.","",""],["View\nManipulation\nand\nVolume\nRendering","","Window and\nlevel, pan,\nzoom, cross-\nhairs, slice\nnavigation.\nMaximum,\naverage and\nminimum\nintensity\nprojection (MIP,\nAVG, MinIP),\ncolor rendering,\nmulti-planar\nreconstruction\n(MPR), fused\nviews,\ngallery views.","","","Not stated","","Window and level, pan,\nzoom, cross-hairs, slice\nnavigation.\nMaximum or minimum\nintensity projection\n(MIP),\nvolume rendering, color\nrendering, surface\nrendering,\nmulti-planar\nreconstruction (MPR),\nfused views,\ngallery views.","None – Not\napplicable","Not stated","No information has been found\nregarding view manipulation and\nvolume rendering concerning\nthe primary predicate. The\npredicate device claims to offer\na feature to review the\nprocessed image and perform\nmanual contouring, which\nimplies at least the display of\nDICOM images with slice\nnavigation.\nThe proposed device has the\nmajority of the same tools as the\nsecondary RTx predicate, apart\nfrom volume and surface","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p17-t0","doc_id":"K202700","page_num":17,"bbox":[66.68,96.18,725.48,520.18],"n_rows":8,"n_cols":13,"columns":["","","","","","","Technical Information","","","","","",""],"rows":[["","","","","","","Technical Information","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","Predicate","","","","","",""],["","","","ART-Plan","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["","","","","","","","","","","rendering\nThe Workflow Box secondary\npredicate does not offer a\ngraphical interface.","",""],["Regions and\nVolumes\nof Interest\n(ROI)","","AI Based\nautocontouring,\nRegistration\nbased contour\nprojection (re-\ncontouring),\nManual ROI\nmanipulation\nand\ntransformation\n(margins,\nbooleans\noperators,\ninterpolation).","","","Automatic target\nvolume\ndelineation\nsystem.\nAutomatically\ndelineates\norgans-at-risk\n(OAR)\nManual Contour","","2D and 3D ROIs, semi-\nautomatic ROI\ndefinition, isocontour\nROIs using threshold\nand percentage of\nmaximum, one-click\nseed-pointing\ncontouring, manual ROI\nmanipulation, ROI\ntransformation, Atlas-\nbased contouring.","Atlas Based\ncontouring,\nregistration based\nrecontouring,\nmachine learning\nbased contouring","Atlas based contouring, tools to\nquickly create, transform, and\nmodify contours.","Both the proposed device and\nthe primary predicate allow AI\nautomatic contouring and\nmanual contouring","",""],["Region/volume\nof\ninterest\nmeasurements\nand\nsize\nmeasurements","","Intensity,\nHounsfield\nunits and SUV\nmeasurements\nSize\nmeasurements\ninclude 2D and\n3D\nmeasurements\n(number of\nslices, volume\nof a structure,\nstatic ruler)","","","Not stated","","Intensity, Hounsfield\nunits, activity and SUV\nmeasurements\nincluding min, max,\nmean, peak, standard\ndeviation, total\nglycolytic activity,\nmedian, histogram, max\nand mean ratio to\nreference region.\nGray for RT Dose.\nSize measurements\ninclude 2D and 3D\nmeasurements\nincluding rulers and\nvolume, line profile.","None – not\napplicable","Quantitative analysis tools.","ART-Plan offers the same\nIntensity, Hounsfield units and\nSUV\nmeasurements and size\nmeasurements including 2D and\n3D measurements (volume and\nruler) as secondary predicate\nRTx. However, this is only a\nfraction of the tools claimed by\nsecondary predicate RTx.","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p18-t0","doc_id":"K202700","page_num":18,"bbox":[66.68,96.18,725.46,242.44],"n_rows":6,"n_cols":13,"columns":["","","","","","","Technical Information","","","","","",""],"rows":[["","","","","","","Technical Information","","","","","",""],["Property","Property","Proposed\nDevice\nART-Plan","Proposed","","Primary\nPredicate\nAccuContour","Primary","Secondary\nPredicate\nRTx","Secondary\nPredicate\nWorkflow Box","Secondary Predicate\nMIM4.1 (SEASTAR)","Comment","Comment",""],["","","","Device","","","Predicate","","","","","",""],["","","","ART-Plan","","","AccuContour","","","","","",""],["","","","","","","","","","","","",""],["Region/Volume\nQuantification","","None","","","Not stated","","Regions table with\ncharting supports\nanalysis of\nmeasurement over\nmultiple studies using\nstandard protocols such\nas RECIST, PERCIST\nand WHO","None – not\napplicable","Quantitative analysis tools.","The secondary predicate RTx\noffers a range of tools for\nregion/volume quantification.\nART-Plan does not offer these\nkinds of tools. It is a reduction in\nclaim or equivalent to the\nprimary predicate for which no\ninformation was found.","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p19-t0","doc_id":"K202700","page_num":19,"bbox":[135.45,569.91,499.65,711.48],"n_rows":3,"n_cols":9,"columns":["","Test Name","","","Test Description","","","Results",""],"rows":[["","Test Name","","","Test Description","","","Results",""],["Usability Testing","","","The ART-Plan was assessed with\nregards to usability for compliance\nwith IEC 62366","","","Passed","",""],["Autosegmentation\nperformances","","","The study gathers the information on\nthe 3 tests performed on the\nautomatic segmentation performances\non European data.","","","Passed","",""]],"caption_candidate":"The ART-Plan was evaluated for its safety and effectiveness based on the following testing:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p20-t0","doc_id":"K202700","page_num":20,"bbox":[135.44,96.18,499.66,711.18],"n_rows":7,"n_cols":9,"columns":["","Test Name","","","Test Description","","","Results",""],"rows":[["","Test Name","","","Test Description","","","Results",""],["Autosegmentation\nperformances according to\nAAPM requirements","","","The testing demonstrated that the\nauto-segmentation algorithm of the\nmodule Annotate provides acceptable\ncontours for the concerned structures\non an image of a patient.","","","Passed","",""],["Autosegmentation\nperformances against MIM","","","The testing demonstrated that the\nauto-segmentation algorithm of the\nmodule Annotate provides acceptable\ncontours for the concerned structures\non an image of a patient.","","","Passed","",""],["Qualitative validation of\nautosegmentation\nperformances","","","The testing demonstrated that the\nauto-segmentation algorithm of the\nmodule Annotate provides acceptable\ncontours for the concerned structures\non an image of a patient.","","","Passed","",""],["External Contour\nperformances according to\nAAPM requirements","","","The testing demonstrated that the\nExternal Contour Automatic\nSegmentation algorithm of the module\nAnnotate provides acceptable\ncontours for the patient’s body on an\nimage of a patient.","","","Passed","",""],["Fusion performances\naccording to AAPM\nrecommendations","","","The testing evaluated the quality of\nthe rigid and deformable registration\ntools of the SmartFuse module on\nretrospective intra-patient images and\ninter-patient images of different\nmodalities, to ensure the safety of the\ndevice for clinical use.","","","Passed","",""],["Registration performances\non POPI-model","","","The testing evaluated the quality of\nthe deformable registration tools of the\nSmartFuse module on intra-patient CT\nimages.\nTesting was conducted according to\nPOPI-model protocol on\ncorresponding public data.","","","Passed","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202700-p21-t0","doc_id":"K202700","page_num":21,"bbox":[135.45,96.18,499.65,387.72],"n_rows":4,"n_cols":9,"columns":["","Test Name","","","Test Description","","","Results",""],"rows":[["","Test Name","","","Test Description","","","Results",""],["Autosegmentation\nperformances on US data","","","The testing demonstrated that the\nautosegmentation algorithm of the\nAnnotate module provides clinically\nacceptable contours for the concerned\nstructures when applied to US\npatients.","","","Passed","",""],["Pilot study for sample size\nestimation - literature\nreview","","","The testing was a pilot study\nestimating a consistent sample size of\ndataset for our performance testing’s\nconsidering the state-of-art studies in\nimage registration and segmentation.\nThe literature review was completed\non the most cited articles in the field of\nmedical vision.","","","Passed","",""],["System Verification and\nValidation Testing","","","The system verification and validation\ntesting was performed to verify the\nsoftware of the ART-Plan.","","","Passed","",""]],"caption_candidate":"For ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p4-t0","doc_id":"K202718","page_num":4,"bbox":[108.5,431.5,519.5,623.5],"n_rows":9,"n_cols":2,"columns":["Trade/Proprietary Name:","Mint Labs, Inc., d/b/a. QMENTA - QMENTA Imaging S.L."],"rows":[["Trade/Proprietary Name:","Mint Labs, Inc., d/b/a. QMENTA - QMENTA Imaging S.L."],["Common Name:","QMENTA CARE PLATFORM FAMILY"],["Classification Name:","Picture archiving and communication systems to\nmedical image management and processing system"],["","21 CFR 892.2050"],["Classification Regulations:","Class II"],["Product Code:","LLZ"],["",""],["Review panel:","Radiology"],["Performance standards:","None established under Food Drug and Cosmetic Act"]],"caption_candidate":"Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p5-t0","doc_id":"K202718","page_num":5,"bbox":[66.5,179.5,516.5,753.06],"n_rows":41,"n_cols":8,"columns":["Characteristic","Predicate Device","","","Proposed Device","Explanation of\ndifferences","",""],"rows":[["Characteristic","Predicate Device","","","Proposed Device","Explanation of\ndifferences","",""],["Manufacturer","Blackford Analysis LTD","","","Mint Labs, Inc., d/b/a.\nQMENTA -QMENTAImaging\nS.L.","-","",""],["Device Name","Blackford Analysis\nRegistration Product Family","","","QMENTA Care Platform\nFamily","-","",""],["510(k)\nnumber","K142337","","","N/A","-","",""],["Device\nClassification","Class II","","","Class II","-","",""],["Regulation Nº","892.2050","","","892.2050","-","",""],["Product Code","LLZ","","","LLZ","-","",""],["Indications for\nuse:","","The Blackford Registration","","QMENTA Care Platform\nFamily is asoftwaremedical\nimaging system used to\nreceive DICOM images and\ntextual reports, organize\nand store them in an\ninternal format, and to\nmake that information\navailable across a network\nvia web and customized\nuser interfaces. QMENTA\nCare Platform Family\nconsists of two\ncomponents:\n1. A Storage/archiving\nserver for the\nretrieval of DICOM\nimages from CT and\nMR modality data,\nand also PET/CT\ndata from PACS","","The devices are",""],["","","Product Family consists of","","","","highly similar in",""],["","","two components:","","","","their indications",""],["","","1. A Workflow Server that","","","","for use since they",""],["","","","","","","both focus on the",""],["","","calculates DICOM","","","","",""],["","","","","","","calculation of",""],["","","registration objects from","","","","",""],["","","","","","","DICOM objects",""],["","","CT and MR modality data,","","","","",""],["","","","","","","from CT and MR",""],["","","and also PET/CT data via","","","","",""],["","","","","","","modality data, and",""],["","","using the CT data for","","","","",""],["","","","","","","also PET/CT data.",""],["","","registration.","","","","",""],["","","2. A localizer tool that","","","","",""],["","","","","","","Both devices",""],["","","","","","","include a",""],["","","works across studies, or","","","","",""],["","","","","","","Workflow Server",""],["","","series in the same study","","","","",""],["","","","","","","component, that",""],["","","within a different frame of","","","","",""],["","","","","","","performs the",""],["","","reference.","","","","",""],["","","","","","","image processing",""],["","","The first intended clinical","","","","",""],["","","","","","","operations of the",""],["","","use, when reading studies","","","","DICOM objects.",""],["","","of the above modalities, is","","","","",""],["","","to aid navigation through,","","","","Blackford includes",""],["","","and comparative","","","","a localizer tool to",""],["","","interpretation of, a target","","","","help the user",""]],"caption_candidate":"Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p6-t0","doc_id":"K202718","page_num":6,"bbox":[66.5,101.17,516.5,754.5],"n_rows":36,"n_cols":6,"columns":["","","series with respect to a","","and/or OS-based\nfile storage.\n2. A workflow server\nthat allows to\nintegrate legally\nmarketed\napplications for\nclinical use into the\nQMENTA Care\nPlatformFamily.The\napplications are\ngeared toward\nspecific types of\nimage analysis and\nare marketed with\ncorresponding\nnames.\nThe results may be saved to\na DICOMimagefileandmay\nbe further visualized on an\nimaging workstation.\nQMENTA Care Platform\nFamily is designed to aid\nsuitablyqualifiedphysicians,\nwho will base their\ndiagnoses on training and\nprotocols that do not\nnecessarily rely on image\nmaps or image\nquantifications.","navigate through\nstudies, or series\nin the same study.\nSimilarly, QMENTA\nCare provides a\nstorage and\narchiving server\nwhere the user\ncan navigate\nthrough the\nstudies or series\nwithin a study."],"rows":[["","","series with respect to a","","and/or OS-based\nfile storage.\n2. A workflow server\nthat allows to\nintegrate legally\nmarketed\napplications for\nclinical use into the\nQMENTA Care\nPlatformFamily.The\napplications are\ngeared toward\nspecific types of\nimage analysis and\nare marketed with\ncorresponding\nnames.\nThe results may be saved to\na DICOMimagefileandmay\nbe further visualized on an\nimaging workstation.\nQMENTA Care Platform\nFamily is designed to aid\nsuitablyqualifiedphysicians,\nwho will base their\ndiagnoses on training and\nprotocols that do not\nnecessarily rely on image\nmaps or image\nquantifications.","navigate through\nstudies, or series\nin the same study.\nSimilarly, QMENTA\nCare provides a\nstorage and\narchiving server\nwhere the user\ncan navigate\nthrough the\nstudies or series\nwithin a study."],["","","source series. Normally,","","",""],["","","the source series will be","","",""],["","","within a current study and","","",""],["","","the target series will be","","",""],["","","within a prior study.","","",""],["","","However they may also be","","",""],["","","within the same study but","","",""],["","","have a different frame of","","",""],["","","reference. Aiding","","",""],["","","navigationmayinclude,but","","",""],["","","is not limited to, indicating","","",""],["","","corresponding anatomical","","",""],["","","locations, synchronized","","",""],["","","scrolling, matching","","",""],["","","orientations and/or","","",""],["","","reference lines in","","",""],["","","reformatted series and","","",""],["","","fusing two images from","","",""],["","","source and target series.","","",""],["","","Thesecondclinicaluseisto","","",""],["","","aid presentation of change","","",""],["","","between cross-sectional","","",""],["","","radiographic studies to","","",""],["","","clinical colleagues and","","",""],["","","patients.","","",""],["","","Registration-aided","","",""],["","","interpretation of images","","",""],["","","should be carried out by a","","",""],["","","suitablyqualifiedphysician,","","",""],["","","who will base their","","",""],["","","diagnoses on training and","","",""],["","","protocols that do not","","",""],["","","necessarily rely on","","",""],["","","registration for navigation","","",""],["Use Scenario","Registration-aided\ninterpretation of images\nshould be carried out by a\nsuitablyqualifiedphysician,\nwho will base their\ndiagnoses on training and","","","QMENTA Care Platform\nFamily is designed to aid\nsuitablyqualifiedphysicians,\nwho will base their\ndiagnoses on training and\nprotocols that do not","Not a clinically\nsignificant\ndifference."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p7-t0","doc_id":"K202718","page_num":7,"bbox":[66.5,99.5,516.5,747.5],"n_rows":5,"n_cols":4,"columns":["","protocols that do not\nnecessarily rely on\nregistration for navigation.","necessarily rely on image\nmaps or image\nquantifications.",""],"rows":[["","protocols that do not\nnecessarily rely on\nregistration for navigation.","necessarily rely on image\nmaps or image\nquantifications.",""],["Technological\nCharacteristics","Multiple applications\nHosts and manages a\nportfolio of Blackford® and\nPlatform Partner products,\nconfigured and managed\ncentrally, supporting\nautomated or triggered\nprocessing of imaging\napplications and AI\nalgorithms.","Multiple Applications\nAdditional legally marketed\napplications for clinical use\ncan be \"plugged in\"intothe\nQMENTA Care Platform\nFamily. The applications are\ngearedtowardspecifictypes\nof image analysis and are\nmarketed with\ncorresponding names.","Not a clinically\nsignificant\ndifference."],["","Flexible hosting and cloud\ndeployment\nFlexible hosting allows\nclinical applications to be\nlocally hosted on VM or\nDocker containers. Cloud\ndeployment enables\nstudies to be routed to\nseparate resource in the\ncloud, minimizing dataflow","Flexible hosting and cloud\ndeployment\nThe \"plugged in\" clinical\napplications are hosted on\nVM or Docker containers.\nStudies are routed to\nseparate resources in the\ncloud, minimizing dataflow.","Not a clinically\nsignificant\ndifference –\nhosted using\nresources in the\ncloud."],["","Fully DICOM compliant\nDICOM compliant and\nintegrated with DICOM\nmodality worklist to\npre-fetch prior studies for\nanalysis.","Fully DICOM compliant\nDICOM image studies\nretrieved from PACS and/or\nOS-based file storage. From\na workflow perspective,\nQMENTA Care can operate\nas a computing appliance\nthatiscapableofsupporting\nDICOMfiletransferforinput\nand output of results.","Not a clinically\nsignificant\ndifference."],["","Configurable dataflow\nConfigurable dataflow\nmanagement offers\nmultiple adaptable SCPs\nthat maximize data\ningestion speed,\ncustomizable AE titles for\nmanual triggering, and","Configurable dataflow\nQMENTA Care offers\nconfigurable dataflow\nmanagement, where image\nstudies can be transferred\nfrom multiple SCPs into the\nStorage/Archiving server.\nThen images can be","Not a clinically\nsignificant\ndifference."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p8-t0","doc_id":"K202718","page_num":8,"bbox":[66.5,99.5,516.5,719.19],"n_rows":10,"n_cols":8,"columns":["","comprehensive patient\nconsolidation from\nmultiple sources.","","","automatically processed by\nthe configured image\nprocessing applications, and\nresults can be automatically\ntransferred back to a third\nparty DICOM workstationor\nPACS.\nQMENTA PACS Nexus is a\nsmall application that runs\non alocalworkstationinside\nthe hospital network and\nautomates the task of\nexporting images to the\nQMENTA Care Platform and\nretrieving the results.","","",""],"rows":[["","comprehensive patient\nconsolidation from\nmultiple sources.","","","automatically processed by\nthe configured image\nprocessing applications, and\nresults can be automatically\ntransferred back to a third\nparty DICOM workstationor\nPACS.\nQMENTA PACS Nexus is a\nsmall application that runs\non alocalworkstationinside\nthe hospital network and\nautomates the task of\nexporting images to the\nQMENTA Care Platform and\nretrieving the results.","","",""],["","Relevancy Engine\nRelevancy engine\ndetermines which studies\nto send each clinical\napplication and collates\ndescriptor knowledge from\nall deployments. It\nautomates the process of\nmatching incoming study\ninformation with the\nappropriate application,\nprocesses the data, and\nensures results are quickly\nsent back to the right\nsystem.","","","Protocol Adherence Engine\nThe protocol adherence\nengine determinesifstudies\nfollow the configured\nrequirements for a clinical\napplication, taking into\naccount description\nknowledge and image\nparameters available in\nDICOM objects,e.g.number\nof timepoints, consistent\nspacing, etc.","","","Not a clinically\nsignificant\ndifference."],["","","Blackford Curated","","","QMENTA Software","","Not a clinically\nsignificant\ndifference."],["","","Marketplace™ provides a","","","Development Kit provides","",""],["","","vettedcuratedmarketplace","","","the possibility of integrating","",""],["","","of regulatory approved","","","curated legally marketed","",""],["","","medical imaging analysis","","","third-party applications for","",""],["","","applications and AI","","","clinical use accessed via","",""],["","","algorithms accessed via","","","QMENTA Care Platform","",""],["","","Blackford Platform.","","","Family.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202718-p9-t0","doc_id":"K202718","page_num":9,"bbox":[72.0,330.84,523.28,472.58],"n_rows":7,"n_cols":2,"columns":["QMENTA Care Platform Family (QMENTA Care) is a software medical imaging system that runs on",""],"rows":[["QMENTA Care Platform Family (QMENTA Care) is a software medical imaging system that runs on",""],["standard computer hardware that may compute legally marketed applications for clinical use based",""],["on DICOM images captured via MR, CT and PET modalities.",""],["These actions include:",""],["","● Retrieval of MR, CT and PET DICOM image studies fromPACS and/or OS-based file storage"],["","● Computation of legally marketed applications for clinicaluse"],["","● Generation of reports summarizing the computationsperformed"]],"caption_candidate":"Device description:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202767-p4-t0","doc_id":"K202767","page_num":4,"bbox":[113.8,229.1,517.43,299.31],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202767-p5-t0","doc_id":"K202767","page_num":5,"bbox":[95.16,567.07,505.66,657.61],"n_rows":5,"n_cols":5,"columns":["System","","Subject Device","","Predicate Device"],"rows":[["System","","Subject Device","","Predicate Device"],["","Vantage Orian 1.5T, MRT-1550, V6.0","","","Predicate Device (AiCE): Vantage\nOrian 1.5T, MRT-1550, V6.0"],["Marketed By","","Canon Medical Systems USA, Inc.","","Canon Medical Systems USA, Inc."],["510(k) Number","","This Submission","","K193097"],["Clearance Date","","","","July 14, 2020"]],"caption_candidate":"TABLE No. 1: Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202767-p6-t0","doc_id":"K202767","page_num":6,"bbox":[94.99,337.88,500.06,477.16],"n_rows":10,"n_cols":3,"columns":["Subject Device","","Predicate Device (K193097)"],"rows":[["Subject Device","","Predicate Device (K193097)"],["Anatomical Region","Sub-categories",""],["Head","Brain","Yes"],["MSK","Knee","Yes"],["Spine","Cervical, Lumbar, Thoracic","New"],["MSK","Shoulder, Hip, Elbow, Wrist/Hand,\nFoot/Ankle","New"],["Pelvis","Female, Pelvis (soft tissue), Prostate","New"],["Abdomen","Liver, Renal, Pancreas","New"],["Breast","No Sub-category","New"],["Cardiac","No Sub-category","New"]],"caption_candidate":"Addition of the following anatomical regions;","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202767-p6-t1","doc_id":"K202767","page_num":6,"bbox":[94.99,526.37,545.02,663.22],"n_rows":7,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Orian 1.5T,","","","Vantage Orian 1.5T,","",""],["","","MRT-1550, V6.0","","","MRT-1550, V6.0","",""],["Static field strength","1.5T","","","1.5T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"]],"caption_candidate":"19. SAFETY PARAMETERS (unchanged)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202767-p7-t0","doc_id":"K202767","page_num":7,"bbox":[95.01,84.43,545.01,268.76],"n_rows":6,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Orian 1.5T,","","","Vantage Orian 1.5T,","",""],["","","MRT-1550, V6.0","","","MRT-1550, V6.0","",""],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in\nIEC 60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in\nIEC 60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard\nfor ferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard\nfor ferromagnetic objects","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202928-p4-t0","doc_id":"K202928","page_num":4,"bbox":[72.0,233.37,374.64,609.93],"n_rows":25,"n_cols":3,"columns":["The","assigned 510(k) Number: K202928",""],"rows":[["The","assigned 510(k) Number: K202928",""],["","",""],["1.","Submitter",""],["","",""],["","Applicant Information:","DeepVoxel Inc."],["","","22 Talisman"],["","","Irvine, CA 92620"],["","",""],["","Phone:","858-281-8029"],["","Email:","support@deep-voxel.com"],["","",""],["","Contact Person:","Dr. Albert Rego"],["","","27001 La Paz Road, Suite"],["","","Mission Viejo, CA, 92691,"],["","",""],["","Date Prepared:","April 1, 2021"],["","",""],["2.","Device Name",""],["","",""],["","Trade Name:","DV.Target"],["","Device Common Name:","Radiological Image Proces"],["","Regulation Number:","21 CFR 892.2050"],["","Product Code:","QKB"],["","Classification Name:","Picture archiving and com"],["","Regulation Class:","Class II"]],"caption_candidate":"The assigned 510(k) Number: K202928","well_formed":true,"extraction_settings":"text"}
{"table_id":"K202928-p5-t0","doc_id":"K202928","page_num":5,"bbox":[72.29,168.84,588.91,311.76],"n_rows":2,"n_cols":9,"columns":["Device trade\nname","510(k)\nnumber","Date of\nclearance","Classification\nname","Product\ncode","Regulation","Class","Classification\npanel","Submitter’s\nname"],"rows":[["Device trade\nname","510(k)\nnumber","Date of\nclearance","Classification\nname","Product\ncode","Regulation","Class","Classification\npanel","Submitter’s\nname"],["Workflow\nBoxTM\n(including\nDLCExpert™,\nEmbrace:CT™,\nEmbrace:MR™,\nRe:Contour™)","K181572","July 10,\n2018","Picture\nArchiving and\nCommunicatio\nns System","LLZ","21CFR\n892.2050","Class II","Radiology","Mirada\nMedical Ltd"]],"caption_candidate":"Table 1. Identification of Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202928-p6-t0","doc_id":"K202928","page_num":6,"bbox":[90.0,453.12,535.68,626.4],"n_rows":4,"n_cols":3,"columns":["Anatomic Site","OARs","No. of OARs"],"rows":[["Anatomic Site","OARs","No. of OARs"],["Head & Neck","Brachial plexus, Brain Stem, Constrictor naris, Ear Left, Ear Right, Eye Left,\nEye Right, Hypophysis, Larynx, Lens Left, Lens Right, Mandible, Optic\nchiasm, Optic nerve Left, Optic nerve Right, Oral cavity, Parotid Left,\nParotid Right, Sublingual gland, Submandibular gland Left,\nSubmandibular gland Right, Spinal Cord, Temporal Lobe Left, Temporal\nLobe Right, Temporomandibular joint Left, Temporomandibular joint\nRight, Thyroid, Trachea","28"],["Thorax","Esophagus, Heart, Lung Left, Lung Right, Spinal Cord, Trachea","6"],["Abdomen &\nPelvis","Bladder, Duodenum, Gallbladder, Femur Left, Femur Right, Kidney Left,\nKidney Right, Large Bowel, Liver, Pancreas, Rectum, Small Bowel, Spleen,\nSpinal Cord, Stomach","15"]],"caption_candidate":"Table 2. List of OARs delineated by DV.Target across three anatomic sites.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202928-p7-t0","doc_id":"K202928","page_num":7,"bbox":[67.44,461.28,541.2,706.56],"n_rows":2,"n_cols":3,"columns":["","Proposed Device","Predicate Device"],"rows":[["","Proposed Device","Predicate Device"],["Indications\nfor use","• DV.Target is a software application\nthat enables the routing of image\ndata (CT Images) to automatic image\nprocessing workflows, using machine\nlearning learning-based algorithms to\nautomatically delineate OARs\n(Organs-at-risk). Contours generated\nby DV.Target may be used as an\ninput to clinical workflows for\ntreatment planning in radiation\ntherapy.\n• DV.Target is intended to be used by\ntrained medical professionals\nincluding radiologists, radiation\noncologists, dosimetrists, and\nphysicists.","• Workflow Box is a software system\ndesigned to allow users to route DICOM-\ncompliant data to and from automated\nprocessing components. Supported\nmodalities include CT, MR, RTSTRUCT.\n• Workflow Box includes processing\ncomponents for automatically\ncontouring imaging data using\ndeformable image registration to\nsupport atlas-based contouring, re-\ncontouring of the same patient\nand machine learning based contouring.\n• Workflow Box is a data routing and\nimage processing tool which\nautomatically applies contours to\ndata which is sent to one or more of the\nincluded image processing workflows."]],"caption_candidate":"Table 3. Comparison of Indications for Use with Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202990-p5-t0","doc_id":"K202990","page_num":5,"bbox":[67.32,424.56,535.08,717.49],"n_rows":25,"n_cols":9,"columns":["","","","NinesMeasure\nK202990","","","","Philips Medical Systems’",""],"rows":[["","","","NinesMeasure\nK202990","","","","Philips Medical Systems’",""],["","","","","","","","Lung Nodule Assessment and",""],["","","","","","","","Comparison Option",""],["","","","","","","","(LNA)(K162484)",""],["Device Classification Name","","","","System, Image","","System, Image\nprocessing,\nRadiological","System, Image",""],["","","","","processing,","","","processing,",""],["","","","","Radiological","","","Radiological",""],["","","","","","","","",""],["","Device Class","","","Class II","","","Class II",""],["","Classification Panel","","","Radiology","","","Radiology",""],["","Product Code","","","LLZ","","","LLZ, JAK",""],["Regulation\nDescription","Regulation","","","Radiological","","","Radiological",""],["","Description","","","Image Processing","","","Image Processing",""],["","","","","Software","","","Software",""],["","","","","","","","",""],["","Regulation","","","21 CFR 892.2050","","","21 CFR 892.2050",""],["","Number","","","","","","21CFR 892.1750",""],["Indications for Use","Indications for Use","","","NinesMeasure is a semi-","","","The Lung Nodule Assessment",""],["","","","","automatic tool indicated for use","","","and Comparison Option is",""],["","","","","by trained radiologiststo aid in","","","intended for use as a diagnostic",""],["","","","","the analysis and review of adult","","","patient-imaging tool. It is",""],["","","","","thoracic CT images.","","","intended for the review and",""],["","","","","NinesMeasure provides","","","analysis of thoracic CT images,",""],["","","","","quantitative information about","","","providing quantitative and",""],["","","","","pulmonary nodule size on a","","","characterizing information about",""]],"caption_candidate":"A table comparing the key features of the subject and predicate device is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202990-p6-t0","doc_id":"K202990","page_num":6,"bbox":[67.32,72.62,535.08,715.25],"n_rows":52,"n_cols":9,"columns":["","","","","single study or over the time","","nodules in the lung in a single\nstudy, or over the time course of\nseveral thoracic studies.\nCharacterizations include\ndiameter, volume and volume\nover time. The system\nautomatically performs the\nmeasurements, allowing lung\nnodules and measurements to\nbe displayed.","",""],"rows":[["","","","","single study or over the time","","nodules in the lung in a single\nstudy, or over the time course of\nseveral thoracic studies.\nCharacterizations include\ndiameter, volume and volume\nover time. The system\nautomatically performs the\nmeasurements, allowing lung\nnodules and measurements to\nbe displayed.","",""],["","","","","course of several thoracic","","","",""],["","","","","studies by providing long and","","","",""],["","","","","short axis diameter","","","",""],["","","","","measurements in the axial","","","",""],["","","","","plane.","","","",""],["","","","","Based on analysis of DICOM","","","",""],["","","","","images and provided input from","","","",""],["","","","","a radiologist, indicating the","","","",""],["","","","","location of the pulmonary","","","",""],["","","","","nodule, the device uses artificial","","","",""],["","","","","intelligence algorithms to","","","",""],["","","","","automatically perform the","","","",""],["","","","","measurements, and allows the","","","",""],["","","","","axial measurements to be","","","",""],["","","","","displayed and reviewed.","","","",""],["","","","","NinesMeasure is limited for use","","","",""],["","","","","on solid pulmonary nodules.","","","",""],["","","","","The device is intended to be","","","",""],["","","","","used as a measurement tool by","","","",""],["","","","","a trained radiologist and is","","","",""],["","","","","limited to analysis of imaging","","","",""],["","","","","data and should not be used in-","","","",""],["","","","","lieu of full patient evaluation or","","","",""],["","","","","relied upon to make or confirm a","","","",""],["","","","","diagnosis. The device does not","","","",""],["","","","","alter the original medical image.","","","",""],["","","","","","","","",""],["","User Population","","","Radiologists","","","Radiologists and Technologist",""],["Technological Characteristics","Technological Characteristics","","","Image processing algorithms","","Image processing algorithms\ncomputing pulmonary nodule\nmeasurements and returning\ncomputed measurements to the\nworkstation.","Image processing algorithms",""],["","","","","computing pulmonary nodule","","","computing pulmonary nodule",""],["","","","","measurements and returning","","","measurements and returning",""],["","","","","computed measurements to the","","","computed measurements to the",""],["","","","","workstation.","","","workstation.",""],["Components","","","Image processing algorithms for\nnodule measurement","Image processing algorithms for","","","-Image processing algorithms",""],["","","","","nodule measurement","","","-Display, comparison, and risk",""],["","","","","","","","calculations",""],["","Anatomical region of interest","","","Chest","","","Chest",""],["Features","Features","","-long axis measurement\n-short axis measurement\n(perpendicular to long axis)","-long axis measurement","","","-long axis measurement",""],["","","","","-short axis measurement","","","-short axis measurement",""],["","","","","(perpendicular to long axis)","","","(perpendicular to long axis)",""],["","","","","","","","-Average/Max 3D/Effective",""],["","","","","","","","diameter (mm)",""],["","","","","","","","-Volume (mm3)",""],["","","","","","","","-Mean Densities (HU)",""],["","","","","","","","-Segmentation of lung airway,",""],["","","","","","","","lungs and lung lobes",""],["","","","","","","","-Single click lung nodule",""],["","","","","","","","segmentation",""],["","","","","","","","-Nodule Characteristics",""],["","","","","","","","-Comparison and matching",""],["","","","","","","","-Automatic calculation of",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202990-p7-t0","doc_id":"K202990","page_num":7,"bbox":[67.32,72.6,529.44,164.98],"n_rows":8,"n_cols":4,"columns":["","","","doubling time, percent and"],"rows":[["","","","doubling time, percent and"],["","","","absolute change of all numerical"],["","","","parameters"],["","","","-Reporting results functions"],["","","","including dictation table, patient"],["","","","related information, LungRads,"],["","","","and Risk Calculator"],["","","","-Printing option"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202990-p7-t1","doc_id":"K202990","page_num":7,"bbox":[111.36,366.56,500.42,456.24],"n_rows":3,"n_cols":2,"columns":["Primary Endpoint - All Nodules","Result"],"rows":[["Primary Endpoint - All Nodules","Result"],["Normalized error on long axis diameter\n[95% CI]","0.113\n[Upper Bound 0.124]"],["Normalized error on short axis diameter\n[95% CI]","0.131\n[Upper Bound 0.143]"]],"caption_candidate":"The primary endpoints of the algorithm are listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K202990-p7-t2","doc_id":"K202990","page_num":7,"bbox":[72.46,492.88,538.89,628.83],"n_rows":9,"n_cols":4,"columns":["Nodule size","Number of nodules","Normalized error on","Normalized error on"],"rows":[["Nodule size","Number of nodules","Normalized error on","Normalized error on"],["","","long axis diameter\n[95% CI]","short axis diameter"],["","","","[95% CI]"],["3-6 mm","100","0.104 [Upper Bound:","0.123 [Upper Bound:"],["","","0.119]","0.139]"],["6-8 mm","63","0.119 [Upper Bound:","0.143 [Upper Bound:"],["","","0.138]","0.161]"],["8-10 mm","46","0.13 [Upper Bound","0.133 [Upper Bound"],["","","0.156]","0.166]"]],"caption_candidate":"The primary endpoint stratified by nodule size is listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203042-p5-t0","doc_id":"K203042","page_num":5,"bbox":[113.64,67.68,594.0,203.46],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary:\nAquilion Prime SP\n(TSX‐303B/8) V10.2\nwith AiCE‐i","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K192832","02/21/2020"],["Reference Device:\nAquilion LB, TSX‐\n201A/3, V6.0","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K150003","03/19/2015"]],"caption_candidate":"11. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203042-p6-t0","doc_id":"K203042","page_num":6,"bbox":[108.02,55.84,566.97,606.78],"n_rows":18,"n_cols":8,"columns":["","","","","Subject Device","","Primary Predicate Device",""],"rows":[["","","","","Subject Device","","Primary Predicate Device",""],["","Device Name,","","","Aquilion Exceed LB","","Aquilion Prime SP (TSX‐303B/8)\nV10.2 with AiCE‐i",""],["","Model Number","","","(TSX‐202A/3) V10.6 with AiCE‐i","","",""],["","510(k) Number","","","This submission","","K192832",""],["Scan (Rotation) time","","","(0.26), 0.4, 0.45, 0.5, 0.6, 0.75,\n1, 1.5, 2, 3 s","","","(0.23), 0.35, 0.375, 0.4, 0.45,\n0.5, 0.6, 0.75, 1, 1.5, 2, 3 s",""],["View rate","","","Max. 2400 views/s (0.5 s)","","","Max. 2572 views/s (0.35 s)",""],["Scan field diameter\n(Field of View)","","","320/550/700 mm","","","320/500 mm",""],["Extended Field of View","","","Available","","","Available",""],["Gantry opening diameter","","","900 mm","","","780 mm",""],["Gantry tilt","","","No tilt","","","±30°\nAxial and helical scanning\nGantry and remote controlled",""],["Wedge Filter Types","","","Two types\nSmall: FOV M\nLarge: FOV L and XL","","","Two types\nSmall: FOV M\nLarge: FOV L",""],["Detector","","","PURE ViSION detector","","","PURE ViSION detector",""],["Data acquisition","","","1136 channels  80 rows","","","896 channels  80 rows",""],["X‐ray generation\n Channel‐direction (fan) angle\n Slide‐direction (cone) angle\n Rated output\n X‐ray tube voltage\n X‐ray tube current\n X‐ray tube heat capacity\n X‐ray tube cooling rate","","","52.2°\n3.22°\nMax.72 kW\n80/100/120/135 kV\n10‐500 mA (10‐600 mA)\n7.5 MHU\nMax. 1,386 kHU/min (16.5 kW)\nActual 1,008 kHU/min (12.0 kW)","","","49.2°\n3.8°\nMax.72 kW\n80/100/120/135 kV\n10‐500 mA (10‐600 mA)\n7.5 MHU\nMax. 1,386 kHU/min (16.5 kW)\nActual 1,008 kHU/min (12.0 kW)",""],["Metal Artifact Reduction","","","Single Energy Metal Artifact\nReduction (SEMAR)","","","Single Energy Metal Artifact\nReduction (SEMAR)",""],["Noise reduction processing","",""," Quantum Denoising Software\n(QDS)\n Adaptive Integrative Dose\nReduction 3D (AIDR 3D)\n AIDR 3D Enhanced\n AiCE (Body, Lung, Bone, Brain,\nInner Ear)","",""," Quantum Denoising Software\n(QDS)\n Adaptive Integrative Dose\nReduction 3D (AIDR 3D)\n AIDR 3D Enhanced\n AiCE (Body, Lung, Cardiac,\nBone, Brain, Inner Ear)",""],["Respiratory‐gating system","","","Available","","","Available",""],["Couch lateral movement","","","±85mm","","","±42mm",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203103-p8-t0","doc_id":"K203103","page_num":8,"bbox":[70.45,116.45,539.76,708.84],"n_rows":18,"n_cols":9,"columns":["","","","","","","","Synapse 3D Base",""],"rows":[["","","","","","","","Synapse 3D Base",""],["","","","","Synapse 3D Base Tools","","","Tools(V3.0)",""],["","Device Parameters","","","(V6.1)","","","(K120361)",""],["","","","","(This submission)","","","(Primary predicate",""],["","","","","","","","device)",""],["","Basic features and basic imaging tools","","","","","","",""],["2D Viewing","","","Yes","","","Yes","",""],["Image Storing (DICOM\nSCP)","","","Yes","","","Yes","",""],["Image Communication\n(DICOM SCU)","","","Yes","","","Yes","",""],["DICOM Interface\n(SCP/SCU)","","","Yes","","","Yes","",""],["Printing (DICOM SCU)","","","Yes","","","Yes","",""],["Measurements (2D and\n3D)","","","Yes","","","Yes","",""],["Annotations -\nStandardized and Free\nText","","","Yes","","","Yes","",""],["Reporting","","","Yes","","","Yes","",""],["Cine","","","Yes","","","Yes","",""],["Volume Rendering and\n3D Viewing","","","Yes","","","Yes","",""],["MPR\n・ orthogonal / oblique /\ncurved Multi-Planar\nReconstructions (MPR),\n・ Sector and rectangular\nshape MPR image\nviewing\n・ MPR for dental images\n・ Multiple MPR images\nalong an object (Slicer)","","","Yes","","","Yes","",""],["Maximum, Average,\nMinimum Intensity","","","Yes","","","Yes","",""]],"caption_candidate":"Table 1 Device Features and Technical Characteristics Comparison Matrix","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203103-p9-t0","doc_id":"K203103","page_num":9,"bbox":[70.47,72.17,539.76,699.91],"n_rows":23,"n_cols":9,"columns":["","","","","","","","Synapse 3D Base",""],"rows":[["","","","","","","","Synapse 3D Base",""],["","","","","Synapse 3D Base Tools","","","Tools(V3.0)",""],["","Device Parameters","","","(V6.1)","","","(K120361)",""],["","","","","(This submission)","","","(Primary predicate",""],["","","","","","","","device)",""],["Projection","","","","","","","",""],["4D viewing","","","Yes","","","Yes","",""],["Image fusion","","","Yes","","","Yes","",""],["Surface rendering","","","Yes","","","Yes","",""],["Image subtraction (3D)","","","Yes","","","Yes","",""],["Time-density distribution","","","Yes","","","Yes","",""],["General image data\nmanagement and\nadministration tools","","","Yes","","","Yes","",""],["","In-depth analysis tools","","","","","","",""],["Segmentation","","","Yes\n(Some segmentation\napplications are\nimplemented using a deep\nlearning method called as\n“Fully Convolutional\nNetwork”)","","","Yes","",""],["Path definition","","","Yes","","","Yes","",""],["Boundary detection","","","Yes","","","Yes","",""],["","Modality specific imaging tools","","","","","","",""],["CT PET fusion","","","Yes","","","Yes","",""],["ADC image viewing\n(MRI)","","","Yes","","","Yes","",""],["Virtual Endoscopic\nSimulator","","","Yes","","","N/A","",""],["Diffusion-weighted MRI\nData Analysis","","","Yes","","","N/A","",""],["Delayed Enhancement\nImage Viewing","","","Yes","","","N/A","",""],["","Product characteristics","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203103-p10-t0","doc_id":"K203103","page_num":10,"bbox":[70.62,72.17,540.08,185.52],"n_rows":7,"n_cols":9,"columns":["","","","","","","","Synapse 3D Base",""],"rows":[["","","","","","","","Synapse 3D Base",""],["","","","","Synapse 3D Base Tools","","","Tools(V3.0)",""],["","Device Parameters","","","(V6.1)","","","(K120361)",""],["","","","","(This submission)","","","(Primary predicate",""],["","","","","","","","device)",""],["Product Availability","","","Software Product","","","Software Product","",""],["Hardware Platform","","","Windows PC","","","Windows PC","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203169-p4-t0","doc_id":"K203169","page_num":4,"bbox":[113.66,226.16,560.28,713.34],"n_rows":10,"n_cols":2,"columns":["Date:","October 22, 2020"],"rows":[["Date:","October 22, 2020"],["Submitter:","GE Healthcare Japan Corporation\n7-127, Asahigaoka, 4-chome\nHino-shi, Tokyo, 191-8503, Japan"],["Primary Contact Person:","Tomohiro Ito\nSr. Regulatory Affairs Leader\nPhone +81-42-585-5383 or +81-90-8346-6807\nEmail: tomohiro.ito@ge.com"],["Secondary Contact Persons:","Helen Peng\nSr Regulatory Affairs Director\nGE Healthcare\nPhone Number: 262-4248222\ne-mail: hong.peng@ge.com"],["","John Jaeckle\nChief Regulatory Affairs Strategist\nGE Healthcare\nPhone Number: 262-424-9547\ne-mail: John.Jaeckle.com"],["Product Identification","Revolution Ascend"],["Device Trade Name:","Revolution Ascend"],["Regulation Number\n/ Classification:","Computed Tomography X-ray System, 21 CFR 892.1750\n/ Class II"],["Product Code:","90-JAK"],["Manufacturer","GE Healthcare Japan Corporation\n7-127, Asahigaoka, 4-chome"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203169-p5-t0","doc_id":"K203169","page_num":5,"bbox":[113.66,118.74,560.28,278.54],"n_rows":6,"n_cols":2,"columns":["","Hino-shi, Tokyo, 191-8503, Japan"],"rows":[["","Hino-shi, Tokyo, 191-8503, Japan"],["Predicate Device Information:",""],["Device Name","Revolution Maxima"],["510 (K) number","K192686 cleared on October, 2019"],["Regualation Number/\nClassification","Computed Tomography X-ray System, 21 CFR 892.1750 /\nClass II"],["Product Code","90-JAK"]],"caption_candidate":"510(k) Premarket Notification Submission for Revolution Ascend","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203169-p7-t0","doc_id":"K203169","page_num":7,"bbox":[108.27,118.86,547.49,526.78],"n_rows":12,"n_cols":5,"columns":["Subsystem","","Predicate Device","","Proposed Device\nRevolution Ascend"],"rows":[["Subsystem","","Predicate Device","","Proposed Device\nRevolution Ascend"],["","","Revolution Maxima","",""],["","","(K192686)","",""],["Gantry","Revolution Maxima gantry\n- Bore: 70cm\n- Digital Tilt ( 30)","","","Revolution Ascend Gantry\n- Bore: 75cm\n- Physical Tilt ( 30)"],["Patient Table","VT1700v, Lite","","","VT1700v, VT2000, VT2000x"],["GUI","Legacy platform","","","Revolution platform"],["3D Guidance","Not Available","","","Available\n*3D Guidance was cleared in\nK153429 and ported to proposed\ndevice"],["Smart Plan","Not Available","","","Available\n*Smart Plan was cleared in K171013\nand ported to proposed device"],["Auto Prescription","Not Available","","","Available\n* Auto Prescription was cleared in\nK133705 and ported to proposed\ndevice"],["Auto Gating","Not Available","","","Available\n* Auto Gating was cleared in\nK133705 and ported to proposed\ndevice"],["Intelligent Protocoling by\nMachine Learning","Not Available","","","Available\n*workflow feature"],["Auto Positioning by Deep\nLearning","Available","","","Available"]],"caption_candidate":"510(k) Premarket Notification Submission for Revolution Ascend","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203182-p4-t0","doc_id":"K203182","page_num":4,"bbox":[83.41,102.95,543.67,556.73],"n_rows":16,"n_cols":2,"columns":["Submitter’s Name:","Subtle Medical, Inc."],"rows":[["Submitter’s Name:","Subtle Medical, Inc."],["Address:","883 Santa Cruz Ave, Suite 205\nMenlo Park, CA 94025"],["Contact Person:","Jared Seehafer"],["Title:","Regulatory Consultant"],["Telephone Number:","415-857-9554"],["Fax Number:","415-367-1279"],["Email:","jared@enzyme.com"],["Date Summary Prepared:","18-FEB-2021"],["Device Proprietary Name:","SubtleMR"],["Model Number:","V 2.0.0"],["Common Name:","SubtleMR"],["Regulation Number:","21 CFR 892.2050"],["Regulation Name:","System, Image Processing, Radiological"],["Product Code:","LLZ"],["Device Class:","Class II"],["Predicate Device","Trade name: SubtleMR\nManufacturer: Subtle Medical, Inc.\nRegulation Number: 21 CFR 892.2050\nRegulation Name: System, Image Processing,\nRadiological\nDevice Class: Class II\nProduct Code: LLZ\n510(k) Number: K191688\n510(k) Clearance Date: September 16, 2019"]],"caption_candidate":"Table 1. Subject Device Overview.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203182-p5-t0","doc_id":"K203182","page_num":5,"bbox":[94.71,538.94,524.61,661.52],"n_rows":4,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Physical\nCharacteristics","Software package that operates on\noff-the-shelf hardware","Same"],["Computer","Linux Compatible","Same"],["DICOM\nStandard\nCompliance","The software processes DICOM\ncompliant image data","Same"]],"caption_candidate":"Table 2. Summary of Technological Characteristics Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203182-p6-t0","doc_id":"K203182","page_num":6,"bbox":[108.87,42.51,538.77,525.57],"n_rows":7,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Operating\nSystem","Linux","Same"],["Modalities","MRI","Same"],["User Interface","None","Same"],["Image\nEnhancement\nAlgorithm\nDescription","SubtleMR software implements\nan image enhancement algorithm\nusing convolutional neural\nnetwork based filtering. Original\nimages are enhanced by running\nthrough a cascade of filter banks,\nwhere thresholding and scaling\noperations are applied. Separate\nneural network based filters are\nobtained for noise reduction and\nsharpness enhancement. The\nparameters of the filters were\nobtained through an image-guided\noptimization process.","Same"],["Workflow","The software operates on DICOM\nfiles on the file system, enhances\nthe images, and stores the\nenhanced images on the file\nsystem. The receipt of original\nDICOM image files and delivery\nof enhanced images as DICOM\nfiles depends on other software\nsystems. Enhanced images co-\nexist with the original images.","Same"],["Target\nAnatomical\nLocations","Head, spine, neck, and knee MRI","Head, spine, neck, abdomen,\npelvis, prostate, breast and\nmusculoskeletal MRI"]],"caption_candidate":"Subtle Medical, Inc. 510(k) - SubtleMR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203225-p5-t0","doc_id":"K203225","page_num":5,"bbox":[113.64,67.68,594.0,149.28],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion ONE (TSX‐\n306A/3) V10.0 with\nSpectral Imaging\nSystem","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K192828","02/13/2020"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203225-p6-t0","doc_id":"K203225","page_num":6,"bbox":[108.04,271.05,585.59,712.5],"n_rows":6,"n_cols":12,"columns":["","","","S","ubject Device","","P","redicate Device","","C","omment",""],"rows":[["","","","S","ubject Device","","P","redicate Device","","C","omment",""],["Device Name,\nModel Number","evice Name,","","A\n(\nS","quilion ONE","","A\n(\nS","quilion ONE","","","",""],["","Model Number","","","TSX‐306A/3) V10.4 with","","","TSX‐306A/3) V10.0 with","","","",""],["","","","","pectral Imaging System","","","pectral Imaging System","","","",""],["5","10(k) Number","","T","his submission","","K","192828","","","",""],["Spectral Imaging System\n(CSDE‐004A)\n Scan Type\n Scan Regions\n Spectral Reconstruction\nImages\n Metal Artifact\nReduction (MAR)\n ECG‐gated scan\n Gantry tilt\n Rotation time","","","Available\n‐Rapid kV Switching\n‐Abdomen and pelvis,\nChest, Extremities\nand Cardiac\n‐Basis material image\n‐Monochromatic\nimage\n‐Iodine Map\n‐VNC (virtual non‐\ncontrast) image\nAvailable\nAvailable\nAvailable\n0.275, 0.5, 0.75 and\n1.0 s","","","Available\n‐Rapid kV Switching\n‐Abdomen and pelvis,\nChest and Extremities\n‐Basis material image\n‐Monochromatic\nimage\n‐Iodine Map\n‐VNC (virtual non‐\ncontrast) image\nN/A\nN/A\nN/A\n0.5, 0.75 and 1.0 s","","","Addition of Cardiac\nscan region and image\nquality improvements\nto existing regions","",""]],"caption_candidate":"included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203235-p4-t0","doc_id":"K203235","page_num":4,"bbox":[72.64,224.22,536.16,297.98],"n_rows":4,"n_cols":2,"columns":["Contact Person:","Jen-Tang Lu, PhD (Chief Executive Officer)"],"rows":[["Contact Person:","Jen-Tang Lu, PhD (Chief Executive Officer)"],["Phone:","609-865-8659"],["Email:","jt@vysioneer.com"],["Date Summary Prepared:","February 09, 2021"]],"caption_candidate":"33 Rogers St. #308, Cambridge, MA 02142","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203235-p4-t1","doc_id":"K203235","page_num":4,"bbox":[72.64,375.32,536.16,442.9],"n_rows":4,"n_cols":2,"columns":["Trade Name:","VBrain"],"rows":[["Trade Name:","VBrain"],["Common Name:","Radiological Image Processing Software for\nRadiation Therapy"],["",""],["Regulation Number / Product Code:","21 CFR 892.2050 / QKB"]],"caption_candidate":"5.2 Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203235-p6-t0","doc_id":"K203235","page_num":6,"bbox":[72.68,370.63,539.63,703.89],"n_rows":15,"n_cols":4,"columns":["","Vysioneer Inc.","Xiamen Manteia",""],"rows":[["","Vysioneer Inc.","Xiamen Manteia",""],["","","","MIM Software Inc."],["Company","","Technology LTD.",""],["","","","(Primary)"],["","","(Primary)",""],["","","",""],["Device Name","VBrain","AccuContour™","MIM - MRT Dosimetry"],["510k Number","Pending","K191928","K182624"],["Regulation No.","21CFR 892.2050","21CFR 892.2050","21CFR 892.2050"],["Classification","II","II","II"],["Product Code","QKB","QKB","LLZ"],["","VBrain is a software\ndevice intended to assist\ntrained medical\nprofessionals, during\ntheir clinical workflows\nof radiation therapy\ntreatment planning, by\nproviding initial object\ncontours of known\n(diagnosed) brain tumors\n(i.e., the region of\ninterest, ROI) on axial\nT1 contrast-enhanced\nbrain MRI images.","It is used by radiation\noncology department to\nregister multimodality\nimages and segment\n(non-contrast) CT\nimages, to generate\nneeded information for\ntreatment planning,\ntreatment evaluation and\ntreatment adaptation.\nThe product has two\nimage process functions:\n(1)Deep learning\ncontouring: it can\nautomatically contour","MIM software is used by\ntrained medical\nprofessionals as a tool to\naid in evaluation and\ninformation management\nof digital medical\nimages. The medical\nimage modalities\ninclude, but are not\nlimited to, CT, MRI, CR,\nDX, MG, US, SPECT,\nPET and XA as\nsupported by\nACR/NEMA DICOM\n3.0."],["Intended","","",""],["Use/Indication for Use","","",""],["","","",""]],"caption_candidate":"Table 5-1. Comparison with the Predicate Devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203235-p8-t0","doc_id":"K203235","page_num":8,"bbox":[72.72,80.55,539.79,700.66],"n_rows":4,"n_cols":4,"columns":["","","","•Planning and\nevaluation of permanent\nimplant brachytherapy\nprocedures (not\nincluding\nradioactive\nmicrospheres).\n•Calculating absorbed\nradiation dose as a result\nof administering a\nradionuclide.\nWhen using device\nclinically, the user\nshould only use FDA\napproved\nradiopharmaceuticals. If\nusing with unapproved\nones, this device should\nonly be used for research\npurposes.\nLossy compressed\nmammographic images\nand digitized film screen\nimages must not be\nreviewed for\nprimary image\ninterpretations.\nImages that are printed\nto film must be printed\nusing an FDA-approved\nprinter for the diagnosis\nof digital mammography\nimages.\nMammographic images\nmust be viewed on a\ndisplay system that has\nbeen cleared by the FDA\nfor the diagnosis of\ndigital mammography\nimages. The software is\nnot to be used for\nmammography CAD."],"rows":[["","","","•Planning and\nevaluation of permanent\nimplant brachytherapy\nprocedures (not\nincluding\nradioactive\nmicrospheres).\n•Calculating absorbed\nradiation dose as a result\nof administering a\nradionuclide.\nWhen using device\nclinically, the user\nshould only use FDA\napproved\nradiopharmaceuticals. If\nusing with unapproved\nones, this device should\nonly be used for research\npurposes.\nLossy compressed\nmammographic images\nand digitized film screen\nimages must not be\nreviewed for\nprimary image\ninterpretations.\nImages that are printed\nto film must be printed\nusing an FDA-approved\nprinter for the diagnosis\nof digital mammography\nimages.\nMammographic images\nmust be viewed on a\ndisplay system that has\nbeen cleared by the FDA\nfor the diagnosis of\ndigital mammography\nimages. The software is\nnot to be used for\nmammography CAD."],["Segmentation","Deep learning","Deep learning","Atlas-based algorithm\nand propagation tools\n(requiring user’s input to"],["(Contouring)","","",""],["Technology","","",""]],"caption_candidate":"VBrain","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203235-p9-t0","doc_id":"K203235","page_num":9,"bbox":[72.73,80.55,539.81,700.41],"n_rows":19,"n_cols":4,"columns":["","","","start the image\nsegmentation process)"],"rows":[["","","","start the image\nsegmentation process)"],["","Linux operating system","Microsoft Windows","Microsoft Windows and\nApple macOS operating\nsystems"],["Operating System","","",""],["","","",""],["","Trained medical\nprofessionals including,\nbut not limited to,\nradiologists, oncologists,\nphysicians, medical\ntechnologists,\ndosimetrists, and\nphysicists.","It is used by radiation\noncology department.","Trained medical\nprofessionals"],["User Population","","",""],["","","",""],["","Axial T1 contrast-\nenhanced MRI images","Segmentation Features:\nNon-Contrast CT\nRegistration Features:\nCT, MRI, PET","CT, MRI, CR, DX, MG,\nUS, SPECT, PET and\nXA as supported by\nACR/NEMA DICOM\n3.0."],["Supported Modalities","","",""],["","","",""],["","Qualified brain tumors -\nbrain metastases,\nmeningiomas, and\nacoustic neuromas","Organ-at-risk, including\nhead and neck, thorax,\nabdomen and pelvis (for\nboth male and female)","Tumors and normal\ntissues"],["Localization and","","",""],["Definition of Objects","","",""],["(ROI)","","",""],["","","",""],["","To support the intended\nuse of the VBrain AI\nsoftware for brain tumor\ncontouring\n(segmentation)\nperformance, Vysioneer\nconducted a\nretrospective, blinded,\nmulticenter,\nmultinational study with\nthe VBrain software. The\ntest data sets consisted of\n116 cases acquired from\n4 different institutions (3\nUS and 1 non-US). Five\nmetrics are evaluated: (1)\nlesion-wise sensitivity,\n(2) false-positive rate, (3)\nlesion-wise Dice\ncoefficient, (4) average\nHausdorff distance, and\n(5) average centroid\ndistance between","Segmentation\nperformance test\nThe segmentation\nperformance test was\nperformed on proposed\ndevice and predicate\ndevice to evaluate the\nautomated segmentation\naccuracy. Two separate\ntests were performed.\nOne test involved\nimages generated in\nhealthcare institutions in\nChina using scanner\nmodels available in\nChina covering three\nmajor vendors. The other\ninvolved images\ngenerated in healthcare\ninstitutions in US using\nscanner models available\nin US covering three\nmajor vendors. The three\nmajor vendors were GE,","MIM Software Inc. has\nconducted performance\nand integration testing\non MIM - MRT\nDosimetry software with\na comparison to a\ncommercially available\nsolution for internal\nradionuclide dosimetry.\nStandard quality control\nphantoms, simulated\nphantoms based on the\nNEMA IEC Body\nPhantom, simulated\nphantoms based on\npatient data, and clinical\npatient data were used\nfor verification testing.\nAll tests were performed\nusing standard clinical\nacquisition and\nreconstruction protocols.\nThe accuracy of planar\ncorrections for"],["Performance Testing &","","",""],["Software V & V","","",""],["","","",""]],"caption_candidate":"VBrain","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p8-t0","doc_id":"K203258","page_num":8,"bbox":[57.12,108.24,729.54,460.2],"n_rows":4,"n_cols":4,"columns":["Subject\nDevice\nCharacteristic","Current Predicate Device\nsyngo.CT Lung CAD (VC30) (K193216)","New Device\nsyngo.CT Lung CAD (VD20)","Type of Change and Impact to\nSafety & Effectiveness"],"rows":[["Subject\nDevice\nCharacteristic","Current Predicate Device\nsyngo.CT Lung CAD (VC30) (K193216)","New Device\nsyngo.CT Lung CAD (VD20)","Type of Change and Impact to\nSafety & Effectiveness"],["Manufacturer","Siemens Healthcare GmbH","Siemens Healthcare GmbH","[Unchanged]\nNo Impact"],["Detection target","Solid pulmonary nodules in diagnostic\nchest CT acquisitions","Solid and subsolid (part-solid and\nground-glass) pulmonary nodules in\nscreening and diagnostic chest CT acqui-\nsitions","[Updated]\nReflecting parameters validated in the\nreader study."],["Intended Use","The LungCAD software device is a Com-\nputer-Aided Detection (CAD) tool de-\nsigned to assist\nradiologists in the detection of solid pul-\nmonary nodules during review of multi-\ndetector\ncomputed tomographic (MDCT) thoracic\nexaminations. The software is an adjunc-\ntive tool\nthat alerts the radiologist to regions of in-\nterest (ROI) that may be initially over-\nlooked. The\nLungCAD software device use is in-\ntended to be used as a second reader\nafter the radiologist has completed\nhis/her initial read.","syngo.CT Lung CAD software device is a\nComputer-Aided Detection (CAD) tool de-\nsigned to assist radiologists in the detec-\ntion of pulmonary nodules during review\nof multi-detector computed tomography\n(MDCT) thoracic examinations. The soft-\nware is an adjunctive tool to alert the ra-\ndiologist to regions of interest (ROI) that\nmay otherwise be overlooked.","[Updated]\nReflecting key aspects for the intended\nuse. Details that explicitly relate to the\nindication for use have been removed\nand are included in the indications for\nuse (see below)."]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p10-t0","doc_id":"K203258","page_num":10,"bbox":[57.14,108.24,729.52,528.3],"n_rows":7,"n_cols":12,"columns":["Nodule\nCharacteristics","","","Size\n• Solid ≥ 3mm and < 20mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","","","Diameter\n• Solid ≥ 3mm and < 30mm\n• Subsolid (part-solid and ground\nglass) ≥ 5mm and < 30mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","","","[Extended]\n- Solid nodules to 30mm\n- Included Subsolid (part-solid and\nground glass) nodules\n- Validated by reader study","",""],"rows":[["Nodule\nCharacteristics","","","Size\n• Solid ≥ 3mm and < 20mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","","","Diameter\n• Solid ≥ 3mm and < 30mm\n• Subsolid (part-solid and ground\nglass) ≥ 5mm and < 30mm\nLocations\n• full range: central, peripheral\nContours:\n• round, irregular","","","[Extended]\n- Solid nodules to 30mm\n- Included Subsolid (part-solid and\nground glass) nodules\n- Validated by reader study","",""],["Reader\nWorkflow","","","second reader workflow","","","concurrent first reader OR\nsecond reader workflow","","","[Updated]\nReflecting parameters validated in the\nreader study.","",""],["","","","","","","","","","","",""],["Input scanning\nparameters","","","Scanners\nSiemens multi-detector CT (MDCT)\nscanners.","","","Scanners\nMulti-vendor and multi-detector CT\n(MDCT) scanners (Siemens, GE, Philips,\nand Toshiba)","","","[Updated]\nReflecting parameters validated in the\nreader study.","",""],["","","","Detector rows\n4 or more detector rows","","","Detector rows\n16 or more detector rows","","","[Updated]\nRecommendation to use 16 or more\ndetector rows included, as recom-\nmended by FDA,\nReflecting parameters validated in the\nreader study.","",""],["","","","Scan area\nThe scan area needs to comprise the\nentire thorax covering the lung apices to\nthe bases","","","Scan area\nThe scan area needs to comprise the en-\ntire thorax covering the lung apices to the\nbases (single breath hold recommended)","","","[Updated]\nClarification added; no Impact","",""],["","","","Scan direction\nCranio-caudal or caudal-cranial","","","Scan direction\nCranio-caudal or caudal-cranial","","","[Unchanged]\nNo Impact","",""]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p11-t0","doc_id":"K203258","page_num":11,"bbox":[57.12,108.24,729.54,540.66],"n_rows":7,"n_cols":4,"columns":["","Voltage\n120 -140 kVp","Voltage\n100 -140 kVp","[Updated]\nReflecting parameters validated in the\nreader study."],"rows":[["","Voltage\n120 -140 kVp","Voltage\n100 -140 kVp","[Updated]\nReflecting parameters validated in the\nreader study."],["","Exposure\n40–120 mAs","None","[Removed]\nAspect captured by the Dose recom-\nmendation"],["","Collimation\n1 mm or less","Collimation\n1 mm or less","[Unchanged]\nNo Impact"],["","Slice width\n1.00 - 1.25 mm","Slice Thickness\nUp to and including 2.5mm, it is recom-\nmended that <= 1.25 mm be used for the\ndetection of smaller nodules (e.g.\n3.0mm)","[Updated]\nReflecting parameters validated in the\nreader study."],["","Slice overlap\n0–25%\nNote: Reconstruction overlap is allowed,\nbut gaps are not permitted","Slice Overlap\n0–50%\nNote: Reconstruction overlap is allowed,\nbut gaps are not permitted","[Updated]\nReflecting parameters validated in the\nreader study."],["","Number of images\nUp to 1000 images per series.","None","[Removed]\nNo longer a technological limitation"],["","Kernel\nSiemens B60","Kernel\nConsistent with thoracic CT protocols and\nin line with patient safety\nguidelines. Kernels were grouped as to\ntheir profile. Typical kernels\nvalidated by the reader study were:\nSmooth: B, B30f, Standard, FC10.\nMedium: C B45f, B50f, Lung, FC50,\nFC51, Bv49d_2, I50f_2, B60f.\nSharp: D, B70f, Bone, FC52 .","[Updated]\nReflecting parameters validated in the\nreader study."]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p12-t0","doc_id":"K203258","page_num":12,"bbox":[57.15,108.24,729.52,406.32],"n_rows":5,"n_cols":12,"columns":["","","","Contrast\nIntravenous contrast enhancement is op-\ntional","","","None","","","[Removed]\nInsufficient data in the reader study to\nsubstantiate this characteristic.","",""],"rows":[["","","","Contrast\nIntravenous contrast enhancement is op-\ntional","","","None","","","[Removed]\nInsufficient data in the reader study to\nsubstantiate this characteristic.","",""],["","","","Dose\nDiagnostic","","","Dose\nConsistent with thoracic CT protocols and\nin line with patient safety guidelines.\nTypical values are: CTDIvol < 8.0 mGy\n(milligray) in diagnostic protocols and\nCTDIvol of = 3.0 mGy in screening proto-\ncols. These values are defined for stand-\nard sized patient—5 ft 7 in., 154 lb (170\ncm, 70 kg)—based on a 32-cm reference\nphantom with appropriate reductions in\nCTDIvol for smaller patients and appro-\npriate increases in CTDIvol for larger pa-\ntients.","","","[Extended]\nDose characteristic has been updated,\nas discussed with FDA, to reflect the\ndata for diagnostic and screening pro-\ntocols included and validated as part of\nthe reader study.","",""],["","","","","","","","","","","",""],["Hosting Platform","","","syngo.via (VB50)","","","syngo.via (VB60)","","","[Unchanged] and no Impact","",""],["Hosting Application","","","syngo MM Oncology","","","syngo MM Oncology","","","[Unchanged] and no Impact","",""]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p13-t0","doc_id":"K203258","page_num":13,"bbox":[57.12,108.24,750.96,523.5],"n_rows":4,"n_cols":3,"columns":["Functional Compo-\nnent","LungCAD VC30","LungCAD VD20"],"rows":[["Functional Compo-\nnent","LungCAD VC30","LungCAD VD20"],["Preprocessing\nStandardization of\nthe input images and\nlung segmentation","(a) isotropic volume resampling\n(b) lung segmentation is accomplished using a CCN. Initially\na coarse estimation of the lung is performed using a V-net\nprocess. Using two predefined bounding boxes left and right\nlungs are initialized. Another V-net is used to segment left\nand right lungs. This is followed by up-sampling to the original\nimage resolution.","(a) isotropic volume resampling\n(b) lung segmentation is accomplished using a CCN. Initially a\ncoarse estimation of the lung is performed using a V-net process.\nUsing two predefined bounding boxes left and right lungs are ini-\ntialized. Another V-net is used to segment left and right lungs.\nThis is followed by up-sampling to the original image resolution."],["Candidate Genera-\ntion\nThe partitioned vol-\nume is processed us-\ning a CNN and fil-\ntered to yield a list of\ncandidates for each\nsubvolume.","(a) isotropic volume is partitioned into subvolumes\n(b) Each subvolume is fed to a CNN to compute features (“re-\nsponse volume”). Filtering and non-maximum suppression\nyield a list of candidates for each subvolume\n(c) candidates above a certain threshold score are passed to\nthe next step.","(a) isotropic volume is partitioned into subvolumes\n(b) Each subvolume is fed to a CNN to compute\nfeatures (“response volume”). Filtering and non-maximum sup-\npression yield a list of candidates for each subvolume\n(c) candidates above a certain threshold score are passed to the\nnext step."],["Candidate Classifi-\ncation utilizes a\nCNN-based classifier\nto process each can-\ndidate and estimate\nthe\nlikelihood of its type\nas either “nodule” or\n“non-nodule”.","CNN is used for feature computation for each candidate.\n(a) The input image patch is firstly processed by batch nor-\nmalization.\n(b) Three blocks of operations are computed. In each block, a\nconvolution, with stride 2, is used for down-sampling instead\nof max-pooling.\n(c) Semantic features from image features are computed us-\ning two fully connected layers.\n(d) A soft-max function, applied to each candidate, assigns 2\nvalues corresponding to the probability of being a nodule or\nbeing a false positive.\n(e) A weighted-sum of the scores from this phase and\nthe results of the prior step is computed. Candidates above a\ncertain threshold score are labeled as nodule candidates.","CNN is used for feature computation for each candidate.\n(a) The input image patch is firstly processed by batch normaliza-\ntion.\n(b) Three blocks of operations are computed. In each block, a\nconvolution, with stride 2, is used for down-sampling instead of\nmax-pooling.\n(c) Semantic features from image features are computed using\ntwo fully connected layers.\n(d) A soft-max function, applied to each candidate, assigns 2 val-\nues corresponding to the probability of being a nodule or being a\nfalse positive.\n(e) A weighted-sum of the scores from this phase and the results\nof the prior step is computed. Candidates above a certain thresh-\nold score are labeled as nodule candidates."]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203258-p14-t0","doc_id":"K203258","page_num":14,"bbox":[57.12,108.24,750.96,318.6],"n_rows":2,"n_cols":3,"columns":["Postfiltering1","","Postfiltering This step includes the application of two cascaded fil-\nters. The first one aims at removing false positives originating (a)\nfrom the colon and a second one from (b) calcified protrusions\n(for example, areas where the sternum meets the manubrium,\nspine malformations, and osteophytes, and so on).\nThe first filter is a CNN-based classifier that has a similar struc-\nture to that of the classifier in step 3.\nThe second filter uses three orthogonal slices at the candidate lo-\ncation as input to three CCN-based classifiers (one per slice).\nThe results from the three classifiers is then combined by a max-\nvoting mechanism. Any candidate deemed a false positive by ei-\nther filter is thus removed"],"rows":[["Postfiltering1","","Postfiltering This step includes the application of two cascaded fil-\nters. The first one aims at removing false positives originating (a)\nfrom the colon and a second one from (b) calcified protrusions\n(for example, areas where the sternum meets the manubrium,\nspine malformations, and osteophytes, and so on).\nThe first filter is a CNN-based classifier that has a similar struc-\nture to that of the classifier in step 3.\nThe second filter uses three orthogonal slices at the candidate lo-\ncation as input to three CCN-based classifiers (one per slice).\nThe results from the three classifiers is then combined by a max-\nvoting mechanism. Any candidate deemed a false positive by ei-\nther filter is thus removed"],["Final Candidate List","The location information of all the nodule candidates are col-\nlecte a final candidate list passed to the Hosting Application","The location information of all the nodule candidates are collected\ninto a final candidate list passed to Hosting Application."]],"caption_candidate":"© Siemens Healthcare GmbH, 2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203260-p5-t0","doc_id":"K203260","page_num":5,"bbox":[71.11,487.7,531.53,774.18],"n_rows":13,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],["","syngo.CT Brain Hemorrhage","","","MaxQ-AI AccipioIx","","",""],["Notification-only, parallel\nworkflow tool","Yes","","","Yes","","","Same"],["Intended User","Hospital networks and qualified\nclinicians","","","Hospital networks and qualified\nclinicians","","","Same"],["Setting","Acute Care","","","Acute Care","","","Same"],["Identify patients with a\nprespecified clinical\ncondition","Yes","","","Yes","","","Same"],["Clinical condition","Intracranial hemorrhage","","","Intracranial hemorrhage","","","Same"],["Alert to finding","Yes; flagged for review","","","Yes; flagged for review","","","Same"],["Independent of standard\nof care workflow","Yes; No cases are removed from\nworklist","","","Yes; No cases are removed from\nworklist","","","Same"],["Modality","Non-contrast CT","","","Non-contrast CT","","","Same"],["Body Part","Head","","","Head","","","Same"],["Artificial Intelligence\nalgorithm","Yes","","","Yes","","","Same"],["Limited to analysis of\nimaging data","Yes","","","Yes","","","Same"]],"caption_candidate":"in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203260-p6-t0","doc_id":"K203260","page_num":6,"bbox":[70.98,86.5,531.51,145.38],"n_rows":3,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],["","syngo.CT Brain Hemorrhage","","","MaxQ-AI AccipioIx","","",""],["Output","Suspected hemorrhage / No suspected\nhemorrhage","","","Suspected hemorrhage / No suspected\nhemorrhage","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203260-p6-t1","doc_id":"K203260","page_num":6,"bbox":[70.98,609.39,524.58,774.12],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)","01/14/2019","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Second\nEdition 2007-03-01","06/27/2016","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p4-t0","doc_id":"K203280","page_num":4,"bbox":[74.36,368.47,520.97,579.88],"n_rows":11,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","510(k) number","","K203280","","","K202170","",""],["","Legal Manufacturer","","Perspectum Ltd.","","","Perspectum Ltd.","",""],["","Owner/Owner Operator","","10056574","","","10056574","",""],["","NDeuvmicbee Nr ame","","Hepatica (Hepatica v1)","","","LiverMultiScan (LMSv4)","",""],["","Proprietary/Common","","Hepatica","","","LiverMultiScan","",""],["","nPaanmeel","","Radiology","","","Radiology","",""],["","Regulation","","892.1000","","","892.1000","",""],["","Risk Class","","Class II","","","Class II","",""],["","Product Class code","","LNH","","","LNH","",""],["Classification","Classification","","System, Nuclear Magnetic\nResonance Imaging","","","System, Nuclear Magnetic\nResonance Imaging","",""]],"caption_candidate":"2. Subject and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p6-t0","doc_id":"K203280","page_num":6,"bbox":[36.07,158.92,559.23,787.94],"n_rows":4,"n_cols":3,"columns":["Comparison of Subject and Predicate Device","",""],"rows":[["Comparison of Subject and Predicate Device","",""],["Characteristic","Hepatica v1 (Subject device)","LMSv4 (Predicate device)"],["Intended Use and\nIndications for Use","“Hepatica (Hepatica v1) is a post-processing\nmedical device software that presents\nquantified metrics which may contribute to\nthe assessment of a patient’s liver health.\nHepatica (Hepatica v1) uses image\nvisualisation and analysis tools to process\nDICOM 3.0 compliant magnetic resonance\nimage datasets to produce semi-automatic\nsegmented 3D models of the liver based on\nthe work of Couinaud and the Brisbane 2000\nterminology. For each identified Couinaud\nsegment, volumetric data is determined and\nreported.\nHepatica (Hepatica v1) may also report iron\ncorrected-T1 (cT1) and PDFF calculated using\nthe IDEAL method from multi-slice\nacquisitions, on a per segment basis, over\nthe whole liver. Both metrics present\nnumerical values of different fundamental\nliver tissue characteristics that can be used\nas measures of liver tissue health.\nHepatica (Hepatica v1) provides trained\nclinicians with additional information to\nevaluate the volume and health of a patient’s\nliver on a segmental basis. It is not intended\nto replace the established procedures for the\nassessment of a patient’s liver health.\nHowever, information gathered through\nexisting diagnostic tests, clinical evaluation of\nthe patient, as well Hepatica (Hepatica v1),\nmay support surgical decision making.”","“LiverMultiScan (LMSv4) is indicated for use\nas a magnetic resonance diagnostic device\nsoftware application for non-invasive liver\nevaluation that enables the generation,\ndisplay and review of 2D magnetic resonance\nmedical image data and pixel maps for MR\nrelaxation times.\nLiverMultiScan (LMSv4) is designed to utilize\nDICOM 3.0 compliant magnetic resonance\nimage datasets, acquired from compatible\nMR systems, to display the internal structure\nof the abdomen including the liver. Other\nphysical parameters derived from the images\nmay also be produced.\nLiverMultiScan (LMSv4) provides a number of\ntools, such as automated liver segmentation\nand region of interest (ROI) placements, to\nbe used for the assessment of selected\nregions of an image. Quantitative\nassessments of selected regions include the\ndetermination of triglyceride fat fraction in\nthe liver (PDFF), T2* and iron-corrected T1\n(cT1) measurements. T2* may be optionally\ncomputed using the DIXON or LMS MOST\nmethods.\nThese images and the physical parameters\nderived from the images, when interpreted\nby a trained clinician, yield information that\nmay assist in diagnosis.”"],["Target Population","Patients who are suitable to undergo an MRI\nscan and not contra-indicated for MRI.\nHepatica may benefit the clinical\nmanagement of patients who are being\nconsidered for liver resection(s).","Patients suitable to undergo an MRI scan and\nnot contra-indicated for MRI"]],"caption_candidate":"demonstrate substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p7-t0","doc_id":"K203280","page_num":7,"bbox":[36.1,75.4,559.23,787.48],"n_rows":47,"n_cols":8,"columns":["Comparison of Subject and Predicate Device","","","","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","","","","",""],["Characteristic","","","Hepatica v1 (Subject device)","Hepatica v1 (Subject device)","LMSv4 (Predicate device)","",""],["Device User","","","Trained Perspectum internal operator","Trained Perspectum internal operator","Trained Perspectum internal operator","",""],["Report User","","","An interpreting clinician or healthcare\npractitioner","An interpreting clinician or healthcare","An interpreting clinician or healthcare\npractitioner","",""],["","","","","practitioner","","",""],["Device Use\nEnvironment","","","","Installation of Hepatica v1 is controlled and is","","Installation of LMSv4 is controlled and is",""],["","","","","installed on general purpose workstations","","installed on general purpose workstations",""],["","","","","that meet the minimum technical","","that meet the minimum technical",""],["","","","","requirements at Perspectum’s image analysis","","requirements at Perspectum’s image analysis",""],["","","","","centre by specialist members of staff","","centre by specialist members of staff.",""],["Clinical Setting","","","","Hepatica v1 is a standalone software device","","LMSv4 is a standalone software device that is",""],["","","","","that is intended to be installed on general","","intended to be installed on general use",""],["","","","","use workstations at Perspectum’s image","","workstations at Perspectum’s image analysis",""],["","","","","analysis centres. The intended device users","","centres. The intended device users will log",""],["","","","","will log on to the workstations, access the","","on to the workstations, access the device,",""],["","","","","device, and use the device on general-use","","and use the device on general-use HD",""],["","","","","HD monitors.","","monitors.",""],["","","","","","","",""],["","","","","Hepatica v1 is a post-processing software","","LMSv4 is a post-processing software and the",""],["","","","","and the intended device users are trained","","intended device users are trained",""],["","","","","Perspectum internal operators.","","Perspectum internal operators.",""],["","","","","","","",""],["","","","","Operators use Hepatica v1 to conduct","","Operators use LMS to conduct quantitative",""],["","","","","quantitative analysis of liver tissue","","analysis of liver tissue characteristics to",""],["","","","","characteristics to produce a report.","","produce a report.",""],["","","","","","","",""],["","","","","The end-users for the output from the","","The end-users for the output from the",""],["","","","","device, the report, are clinicians who receive","","device, the report, are clinicians who receive",""],["","","","","and interpret Hepatica v1 reports.","","and interpret LMSv4 reports.",""],["","Anatomical","","Abdomen, including the Liver","Abdomen, including the Liver","Abdomen, including the liver","Abdomen, including the liver",""],["","Location","","","","","",""],["Energy\nConsiderations","Energy","","","Hepatica is a standalone software","LMS is a standalone software application. It\ndoes not deliver, monitor or depend on\nenergy delivered to or from patients.","",""],["","Considerations","","","application. It does not deliver, monitor or","","",""],["","","","","depend on energy delivered to or from","","",""],["","","","","patients.","","",""],["Design: Purpose","","","Hepatica is a standalone software application\nthat imports MR datasets encompassing the\nabdomen, including the liver. Visualisation\nand display of T1-weighted MR data which\ncan be analysed, and quantitative metrics of\ntissue characteristics and liver volume are\nthen reported.\nDatasets imported into Hepatica are DICOM\n3.0 compliant and reported metrics are\nindependent of the MRI equipment vendor.","Hepatica is a standalone software application","LMS is a standalone software application that\nimports MR data sets encompassing the\nabdomen, including the liver. Visualisation\nand display of 2D multi-slice, spin-echo MR\ndata can be analysed, and quantitative\nmetrics of tissue characteristics are then\nreported.\nDatasets imported into LMS are DICOM 3.0\ncompliant, reported metrics are independent\nof the MRI equipment vendor.","",""],["","","","","that imports MR datasets encompassing the","","",""],["","","","","abdomen, including the liver. Visualisation","","",""],["","","","","and display of T1-weighted MR data which","","",""],["","","","","can be analysed, and quantitative metrics of","","",""],["","","","","tissue characteristics and liver volume are","","",""],["","","","","then reported.","","",""],["","","","","","","",""],["","","","","Datasets imported into Hepatica are DICOM","","",""],["","","","","3.0 compliant and reported metrics are","","",""],["","","","","independent of the MRI equipment vendor.","","",""],["Design: Tools","","","Allows for the 3D visualisation of the liver\nand quantification of metrics (cT1, PDFF and\nvolumetry) from liver tissue and exportation\nof results and images to a deliverable report.","","Allows for the visualisation via parametric\nmaps and quantification of metrics (cT1, T2*\nand PDFF) from liver tissue and exportation\nof results and images to a deliverable report.","",""]],"caption_candidate":"Hepatica v1 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p8-t0","doc_id":"K203280","page_num":8,"bbox":[36.08,75.4,559.23,773.48],"n_rows":5,"n_cols":3,"columns":["Comparison of Subject and Predicate Device","",""],"rows":[["Comparison of Subject and Predicate Device","",""],["Characteristic","Hepatica v1 (Subject device)","LMSv4 (Predicate device)"],["","Hepatica v1 allows for:\nVolumetry\n• Reporting of whole liver and segmental\nvolume\n• Semi-automatic segmentation of the\nouter contour of the liver\n• Semi-automatic segmentation of the\nliver into Couinaud segments via placed\nlandmarks of anatomical areas of\ninterest\ncT1 and PDFF metrics may be quantified and\nloaded from LMS when analysis has been\nconducted on the same patient. Datasets\nimported from LMS contain all image analysis\nwarnings and cautions associated with the\nindividual analysis and are included in the\nhepatica report.","LMSv4 allows for:\ncT1\n• Full segmentation of the outer liver\ncontour and liver vasculature of the cT1\nparametric map. IQR and median metrics\nare reported from the segmentation.\n• ROI placed method on the cT1 map with\nIQR and median metrics from the placed\nROI’s potentially across multiple\nacquired slices.\nT2*\n• ROI placed method on the T2* map with\nIQR and median metrics from the placed\nROI’s potentially across multiple\nacquired slices.\n• T2* parametric maps are calculated from\nthe MOST method or the three-point\nDIXON method (1)\nPDFF\n• Full liver segmentation of the PDFF\nparametric map where IQR and median\nmetrics are reported from the\nsegmentation.\n• ROI placed method on the PDFF map\nwith IQR and median metrics from the\nplaced ROI’s potentially across multiple\nacquired slices\n• PDFF parametric maps are calculated\nusing the LMS IDEAL method (2)"],["Design: MR\nRelaxometry","Hepatica v1 does not support quantification\nof metrics from MR relaxometry. If cT1\nresults are imported from LMS, cT1 may be\nreported for all individual Couinaud\nsegments and for whole-liver analysis.\nMedian T2* values are given from the cT1\nquantification.","T1, iron- and fat- corrected T1 (cT1) and T2*\nmapping"],["Design: Liver Fat\nQuantification","Liver fat quantification data is imported from\nthe predicate device (LMSv4), where\navailable. If PDFF results are imported from\nLMS, PDFF may be reported for all individual\nCouinaud segments as well as Whole-liver\nPDFF based on the segmented outer-","Utilizes MR images that exploit the\ndifference in resonance frequencies between\nhydrogen nuclei in water and triglyceride fat\nusing the LMS IDEAL method (2)."]],"caption_candidate":"Hepatica v1 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p9-t0","doc_id":"K203280","page_num":9,"bbox":[36.06,75.4,559.23,729.73],"n_rows":6,"n_cols":3,"columns":["Comparison of Subject and Predicate Device","",""],"rows":[["Comparison of Subject and Predicate Device","",""],["Characteristic","Hepatica v1 (Subject device)","LMSv4 (Predicate device)"],["","contour. PDFF parametric maps are\ncalculated using the LMS IDEAL method (2).",""],["Design: Liver\nSegmentation","Hepatica v1 supports semi-automatic liver\nsegmentation of T1-weighted volumetric\ndata.\nLiver segmentation in Hepatica v1 requires\nthe placement of anatomical landmarks to\ndefine the outer contours of the liver and\ncan be adjusted by the operator, where\nnecessary.\nWhere available, whole liver and segmental\ncT1 and PDFF quantitative metrics derived\nfrom the predicate device may be presented\nin the final report.","LMSv4 supports automatic multi-slice full\nliver segmentation of the cT1 and PDFF\nparametric maps. Use of this functionality is\nat the discretion of the operator, instead or\nin combination, with the ROI based method.\nThe cT1 segmented liver is presented in\ncolour level window, while the rest of the\ncT1 image is presented in greyscale level\nwindow with liver vasculature excluded from\nthe segmented volume."],["Design: Regions of\nInterest (ROI)","Does not support ROI functionality.","Median and interquartile range\nmeasurements created from a cross\nsectional slice of liver tissue. For each\nparametric map, statistics from multiple\nRegions of Interest (ROIs) – potentially\nplaced across multiple slices – are\nsummarised.\nAlso supports the display of ‘Live’ ROI\nstatistics when moving the ROI across the\nparametric map."],["Design: Parametric\nMaps","Hepatica uses volumetric datasets to create\n2D anatomical views from all supported\nscanners.\nWhere available, cT1 and PDFF parametric\nmaps are derived from the predicate device.","Iron corrected T1 (cT1), T2* and Proton\nDensity Fat Fraction (PDFF) parametric maps\ncan be created from all supported scanners.\nIt is possible to use the T2* and PDFF maps\nand knowledge of the T2* and PDFF\nmeasurements and the scanner field\nstrength to correct for signal changes related\nto iron deposits, producing a cT1 map. The\ncT1 map eliminates the effects of elevated\niron from the T1 measurement (3) and\nstandardizes for the fat signal across scanner\nmanufacturers.\nPDFF is quantified using the LMS IDEAL\nmethod. Parametric maps of T2* may be\noptionally be computed using either the\nthree-point DIXON method or the LMS MOST\nmethod."]],"caption_candidate":"Hepatica v1 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p10-t0","doc_id":"K203280","page_num":10,"bbox":[36.08,75.4,559.23,775.23],"n_rows":6,"n_cols":5,"columns":["Comparison of Subject and Predicate Device","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","",""],["Characteristic","","","Hepatica v1 (Subject device)","LMSv4 (Predicate device)"],["Design:\nVisualisation","","","Numerous views in the Hepatica v1 interface\ncan be used to assist analysis.\nOperators are able to see live views of\ncrosshair placements during landmarking\nacross multiple image planes simultaneously\nand adjust contrast where required.\nLesion segmentation will be performed by\nnavigating through the axial slices using the\ncrosshair tool and “painting in” the segment\non each slice.\nOperators will be required to navigate\nthrough the axial, sagittal and coronal planes\nusing the crosshair tool to confirm that the\ndelineation carried out by the device is\naccurate. The borders can be adjusted\naccordingly.\nViews of the segmented liver and lesions are\nupdated in real-time and can be rotated in a\n3D space. Paint, eraser and zooming\nfunctionalities are also available to the\noperator.\nWhere available, operators can review the\nposition of cT1 and PDFF slices (derived from\nLMSv4) within the 3D view of the liver.","Numerous views within the LMSv4 interface\ncan be used to assist in analysis, Iron-\ncorrected T1 (cT1), T2* and triglyceride fat\n(also known as Proton Density Fat Fraction\n(PDFF)) parametric maps can be created\nfrom all supported scanners. R2 maps can\nalso be utilised to assess the quality of the\nmap fitting.\nIron- corrected T1 (cT1) displayed using\nLMSv4 colourmap, designed to have\nmaximum contrast on liver parenchymal\ntissue."],["","Design: Supported","","DICOM 3.0 compliant MR data from\nsupported MRI scanners.","DICOM 3.0 compliant MR data from\nsupported MRI scanners."],["","Modalities","","",""],["Design: Report","","","Quantified metrics and images derived from\nthe analysis of liver volume and tissue\ncharacteristics are collated into a report for\nevaluation and interpretation by a clinician.\nImages\nImages of the whole liver divided into\nCouinaud segments are presented in\ngreyscale in the report.\nWhere available, cT1 and PDFF slices are also\npresented from the imported LMSv4\nanalysis.\nValues\nWhole and segmental liver volume metrics\ncalculated during analysis are provided in the\nreport.","Quantified metrics and images derived from\nthe analysis of liver tissue characteristic on\nparametric maps are collated into a report\nfor evaluation and interpretation by a\nclinician.\nWhen segmentation analysis is used a\nrepresentative pie- chart is provided based\non the confirmed segmentation contour\nfrom the PDFF map. The voxels within the\nsegmentation are separated into 5\ncategories (<5% PDFF, 5-10% PDFF, 10-33%\nPDFF, 33-66% PDFF and >66%) to give\nproportions based on PDFF. These categories\nwere chosen based on the work of Kleiner et\nal (3) and Satkunasingham et al (4) on the\ngrading of histological features presented in\nNon-Alcoholic Fatty Liver Disease."]],"caption_candidate":"Hepatica v1 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p11-t0","doc_id":"K203280","page_num":11,"bbox":[36.05,75.4,559.23,555.92],"n_rows":21,"n_cols":6,"columns":["Comparison of Subject and Predicate Device","","","","",""],"rows":[["Comparison of Subject and Predicate Device","","","","",""],["Characteristic","Hepatica v1 (Subject device)","","LMSv4 (Predicate device)","",""],["","Where available, whole liver segmental cT1\nand PDFF values are provided. For each\nmetric, the median, IQR and a ‘reference\nrange’ are provided.","","Based on the placed ROIs, for each metric\nthe median and IQR are given as well as a\n‘reference range’.","",""],["Compatibility with\nthe environment","","Installation of Hepatica v1 is controlled and is\ninstalled on general purpose workstations\nthat meet the minimum technical\nrequirements at Perspectum’s image analysis\ncentre by specialist members of staff.","","Installation of LMSv4 is controlled and is",""],["","","","","installed on general purpose workstations",""],["","","","","that meet the minimum technical",""],["","","","","requirements at Perspectum’s image analysis",""],["","","","","centre by specialist members of staff.",""],["Performance","Device performance was assessed with\npreviously acquired in-vivo data from healthy\nand non-healthy volunteers.","","Device performance was assessed with\npurpose-built phantoms and in-vivo acquired\ndata from volunteers covering a range of\nphysiological values for cT1, T2* and PDFF.","",""],["Human Factors","Assessed in accordance with IEC 62366 and\nFDA guidance document ‘Applying Human\nFactors and Usability Engineering to Medical\nDevices.’","","Assessed in accordance with IEC 62366 and\nFDA guidance document ‘Applying Human\nFactors and Usability Engineering to Medical\nDevices.’","",""],["Supported MRI\nSystems","Validated across all listed supported\nmanufacturers and field strengths.","","Validated across all listed supported\nmanufacturers and field strengths.","",""],["Standards","IEC 62304, IEC 62366, DICOM 3.0, ISO 14971,\nISO 13485","","IEC 62304, IEC 62366, DICOM 3.0, ISO 14971,\nISO 13485","",""],["System/Operating\nSystem","Mac OS","","Mac OS","",""],["Materials","Not applicable, standalone software","","Not applicable, standalone software","",""],["Biocompatibility","Not applicable, standalone software","","Not applicable, standalone software","",""],["Sterility","Not applicable, standalone software","","Not applicable, standalone software","",""],["Electrical Safety","Not applicable, standalone software","","Not applicable, standalone software","",""],["Mechanical Safety","Not applicable, standalone software","","Not applicable, standalone software","",""],["Chemical Safety","Not applicable, standalone software","","Not applicable, standalone software","",""],["Thermal Safety","Not applicable, standalone software","","Not applicable, standalone software","",""],["Radiation Safety","Not applicable, standalone software","","Not applicable, standalone software","",""]],"caption_candidate":"Hepatica v1 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p12-t0","doc_id":"K203280","page_num":12,"bbox":[36.36,100.9,559.21,335.55],"n_rows":14,"n_cols":12,"columns":["Metric","","","","Volume (% of total liver","","cT1","","","PDFF","",""],"rows":[["Metric","","","","Volume (% of total liver","","cT1","","","PDFF","",""],["","","","","volume)","","","","","","",""],["Liver Segment","","","","Upper and Lower Limits of","","","Upper and Lower Limits","","","Upper and Lower Limits",""],["","","","","Agreement","","","of Agreement","","","of Agreement",""],["","Segment 1","","-0.49% to 0.95%","","","-1.13% to 0.61%","","","-0.26% to 0.21%","",""],["","Segment 2","","-3.09% to 5.06%","","","-2.38% to 1.56%","","","-0.33% to 0.38%","",""],["","Segment 3","","-5.01% to 3.9%","","","-1.51% to 1.31%","","","-0.16% to 0.17%","",""],["","Segment 4a","","-4.60% to 4.26%","","","-0.77% to 1.10%","","","-0.30% to 0.23%","",""],["","Segment 4b","","-5.50% to 2.56%","","","-1.32% to 1.13%","","","-0.16% to 0.14%","",""],["","Segment 5","","-1.54% to 3.38%","","","-1.11% to 0.87%","","","-0.16% to 0.18%","",""],["","Segment 6","","-4.34% to 4.29%","","","-1.00% to 0.83%","","","-0.16% to 0.26%","",""],["","Segment 7","","-3.30% to 1.79%","","","-0.88% to 0.64%","","","-0.12% to 0.18%","",""],["","Segment 8","","-3.86% to 5.54%","","","-0.91% to 1.09%","","","-0.24% to 0.32%","",""],["","Whole liver","","-4.16% to 0.54%","","","0.00% to 0.00%","","","-0.02% to 0.02%","",""]],"caption_candidate":"Accuracy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203280-p12-t1","doc_id":"K203280","page_num":12,"bbox":[36.36,383.99,559.21,586.61],"n_rows":13,"n_cols":9,"columns":["","Liver Segment (% of total liver","","","Repeatability","","","Reproducibility",""],"rows":[["","Liver Segment (% of total liver","","","Repeatability","","","Reproducibility",""],["","volume)","","","","","","",""],["","","","","Upper and Lower limits of Agreement","","","Upper and Lower Limits of Agreement",""],["","Segment 1","","-0.72% to 0.65%","","","-1.39% to 0.90%","",""],["","Segment 2","","-3.06% to 3.24%","","","-3.10% to 3.15%","",""],["","Segment 3","","-2.67% to 3.13%","","","-2.41% to 2.06%","",""],["","Segment 4a","","-2.48% to 2.43%","","","-2.54% to 2.58%","",""],["","Segment 4b","","-1.82% to 1.96%","","","-1.70% to 1.74%","",""],["","Segment 5","","-4.45% to 4.45%","","","-4.97% to 5.94%","",""],["","Segment 6","","-3.60% to 4.10%","","","-3.69% to 5.40%","",""],["","Segment 7","","-3.32% to 3.33%","","","-4.39% to 3.59%","",""],["","Segment 8","","-4.99% to 3.81%","","","-6.23% to 5.04%","",""],["","Whole liver","","-6.15% to 3.78%","","","-16.6% to 6.95%","",""]],"caption_candidate":"Precision","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203323-p4-t0","doc_id":"K203323","page_num":4,"bbox":[113.8,211.76,517.39,281.97],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Galan 3T, MRT-3020, V6.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203323-p5-t0","doc_id":"K203323","page_num":5,"bbox":[90.48,552.75,553.98,637.59],"n_rows":6,"n_cols":5,"columns":["System","","Subject Device","","Predicate Device"],"rows":[["System","","Subject Device","","Predicate Device"],["","","Vantage Galan3T, MRT-3020, V6.0with","","Vantage Galan 3T, MRT-3020, V6.0with AiCE\nReconstruction Processing Unit for MR"],["","","AiCE Reconstruction Processing Unit for MR","",""],["Marketed By","","Canon Medical Systems USA, Inc.","","Canon Medical Systems USA, Inc."],["510(k) Number","","This Submission","","K192574"],["Clearance Date","","","","March 9th, 2020"]],"caption_candidate":"TABLE No. 1: Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203323-p6-t0","doc_id":"K203323","page_num":6,"bbox":[90.5,291.22,562.97,418.14],"n_rows":10,"n_cols":7,"columns":["","Subject Device","","","","","Predicate Device (K192574)"],"rows":[["","Subject Device","","","","","Predicate Device (K192574)"],["","Anatomical Region","","","Sub-categories","",""],["Head","","","Brain","","","Yes"],["MSK","","","Knee","","","Yes"],["Spine","","","Cervical, Lumbar, Thoracic","","","New"],["MSK","","","Shoulder, Hip, Elbow, Wrist/Hand, Foot/Ankle","","","New"],["Pelvis","","","Female, Pelvis (soft tissue), Prostate","","","New"],["Abdomen","","","Liver, Renal, Pancreas","","","New"],["Breast","","","No Sub-category","","","New"],["Cardiac","","","No Sub-category","","","New"]],"caption_candidate":"Addition of the following anatomical regions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203323-p6-t1","doc_id":"K203323","page_num":6,"bbox":[90.5,457.57,562.97,685.38],"n_rows":10,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Galan 3T, MRT-3020, V6.0","","","Vantage Galan 3T, MRT-3020, V6.0","",""],["","","with AiCE Reconstruction Processing","","","with AiCE Reconstruction Processing","",""],["","","Unit for MR","","","Unit for MR (K192574)","",""],["Static field strength","3T","","","3T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33: 2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33: 2010+A1:2013+A2:2015","","","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203323-p7-t0","doc_id":"K203323","page_num":7,"bbox":[90.54,84.43,562.93,197.58],"n_rows":5,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Galan 3T, MRT-3020, V6.0","","","Vantage Galan 3T, MRT-3020, V6.0","",""],["","","with AiCE Reconstruction Processing","","","with AiCE Reconstruction Processing","",""],["","","Unit for MR","","","Unit for MR (K192574)","",""],["Potential emergency\ncondition and means\nprovided for\nshutdown","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203443-p8-t0","doc_id":"K203443","page_num":8,"bbox":[109.79,168.14,540.26,215.06],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA20A","K192924, cleared March\n11, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203443-p8-t1","doc_id":"K203443","page_num":8,"bbox":[109.79,280.73,540.26,432.54],"n_rows":6,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Sola with\nsyngo MR XA20A","K192496, cleared February\n28, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Lumina with\nsyngo MR XA20A","K192924, cleared March\n11, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Altea with\nsyngo MR XA20A","K192496, cleared February\n28, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Area,\nMAGNETOM Skyra,\nMAGNETOM\nPrisma/Prismafit with syngo\nMR XA30A","K202014, cleared\nSeptember 08, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"on the following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203443-p9-t0","doc_id":"K203443","page_num":9,"bbox":[109.65,483.31,534.72,659.74],"n_rows":8,"n_cols":2,"columns":["Feature / Function","Clinical Publication"],"rows":[["Feature / Function","Clinical Publication"],["SVS_EDIT","[1] Mescher et al, NMR Biomed 11, 266–272 (1998)"],["","[2] Mikkelsen et al, NeuroImage 159, 32–45 (2017)"],["","[3] Saleh et al, NeuroImage 189, 425–431 (2019)"],["GRE_WAVE","[4] B. Bilgic et al., “Wave-CAIPI for Highly Accelerated 3D Imaging.”\nMRM 73(6):2152-2162 (2015)"],["","[5] F. Breuer et al., Controlled aliasing in volumetric parallel imaging (2D\nCAIPIRINHA).” MRM 55(3):549-56 (2006)"],["Prostate Dot Engine","[6] Essner M, Zinsser D, Kündel M, et. al. Performance of an Automated\nWorkflow for Magnetic Resonance Imaging of the Prostate: Comparison\nWith a Manual Workflow. Invest Radiol. 2020 May;55(5):277-284. Doi:\n10.1097."],["","[7] Horger W, Thoermer G, Weiland E, et. al. Prostate Dot Engine – a\nsystem guided and assisted workflow to improve consistency in prostate\nMR exams."]],"caption_candidate":"of the following features and functions.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203443-p10-t0","doc_id":"K203443","page_num":10,"bbox":[109.66,103.1,534.76,440.59],"n_rows":10,"n_cols":2,"columns":["","[8] Yadong C, Siyuan H, Chunmei Li, et. al. Performance and\nReproducibility of a Day Optimizing Throughput (Dot) Workflow Engine in\nAutomated Prostate MRI Positioning. Abstract accepted for the 28th\nannual meeting of the International Society of Magnetic Resonance in\nMedicine (ISMRM)."],"rows":[["","[8] Yadong C, Siyuan H, Chunmei Li, et. al. Performance and\nReproducibility of a Day Optimizing Throughput (Dot) Workflow Engine in\nAutomated Prostate MRI Positioning. Abstract accepted for the 28th\nannual meeting of the International Society of Magnetic Resonance in\nMedicine (ISMRM)."],["Deep Resolve Gain","[9] Kellman P. et al. Image Reconstruction in SNR Units: A General"],["","Method for SNR Measurement. MRM 2005; 54:1439. Erratum in MRM"],["","2007; 58:311."],["","[10] Blu T. et al. The SURE-LET approach to image denoising. IEEE\nTransactions on Image Processing 16(11):2778-86"],["Improvement of\nTGSE_ASL","[11] D C. Alsop, J A. Detre, et al. Recommended Implementation of\nArterial Spin Labeled Perfusion MRI for Clinical Applications: A\nconsensus of the ISMRM Perfusion Study Group and the European\nConsortium for ASL in Dementia. Magn Reson Med. 2015 Jan; 73(1):\n102–116."],["","[12] R B. Buxton, L R. Frank, et al. A general kinetic model for\nquantitative perfusion imaging with arterial spin labeling. Magn Reson\nMed. 1998 Sep; 40(3):383-96."],["","[13] S. Yang, B. Zhao, et al. Improving the Grading Accuracy of\nAstrocytic Neoplasms Noninvasively by Combining Timing Information\nwith Cerebral Blood Flow: A Multi-TI Arterial Spin-Labeling MR Imaging\nStudy. Am. J. Neuroradiol. 2016 Dec; 37 (12) 2209-2216"],["","[14] P G Qiao, C Han, et al. Clinical assessment of cerebral\nhemodynamics in Moyamoya disease via multiple inversion time arterial\nspin labeling and dynamic susceptibility contrast-magnetic resonance\nimaging: A comparative study. J Neuroradiol. 2017 Jul;44(4):273-280."],["","[15] Y Shen, B Zhao, et al. Cerebral Hemodynamic and White Matter\nChanges of Type 2 Diabetes Revealed by Multi-TI Arterial Spin Labeling\nand Double Inversion Recovery Sequence. Front Neurol. 2017; 8: 717."]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203443-p11-t0","doc_id":"K203443","page_num":11,"bbox":[109.7,103.19,540.28,672.1],"n_rows":16,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognitio","n Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/\nEMC)","C1:2009/(R)2012 and\nA2:2010/(R)2012 (Consolidated\nText) Medical electrical\nequipment - Part 1: General\nrequirements for basic safety\nand essential performance (IEC\n60601-1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012","ANSI AAMI"],["19-8","General II\n(ES/\nEMC)","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2 Edition\n4.0 2014-02","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1:2015","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","62304:2006/A1:201\n6","ANSI AAMI\nIEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20\n(2016)","NEMA"],["2-220","Biocompati\nbility","Biological evaluation of medical\ndevices - Part 1: Evaluation and\ntesting within a risk\nmanagement process","10993-\n1:2009/(R)2013","ANSI AAMI\nISO"]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203448-p7-t0","doc_id":"K203448","page_num":7,"bbox":[86.5,269.27,568.55,710.57],"n_rows":13,"n_cols":8,"columns":["ITEM","","","Proposed Device","","Predicate Device","","Remark"],"rows":[["ITEM","","","Proposed Device","","Predicate Device","","Remark"],["","","","","","uCT 760, uCT 780","",""],["","","","","","(K172135)","",""],["Specifications","","","","","","",""],["Gantry","",""," 160mm Detector\n Rotation speed：\nup to\n0.25s/rotation\n 82cm bore"," 40mm Detector\n Rotation speed：up\nto 0.35s/rotation\n(uCT 760); up to\n0.3s/rotation (uCT\n780)\n 70cm bore","","","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Patient Table","","","Max. load capacity\n318kg","Max. load capacity 205kg","","","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Reconstruction Field\nof View","","","40mm-500mm\n40mm-600mm with\nextend FOV","40mm-500mm","","","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Maximum slices\ngenerated per\nrotation","","","640","uCT 760:128\nuCT 780:160","","","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Functions","","","","","","",""],["Low Dose CT Lung\nCancer Screening\nProtocol","","","Yes","--","","","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["","uAI Vision -","","Yes,","--","","","Substantially Equivalent"],["","EasyPositioning","","","","","",""],["","EasyISO","","","","","",""]],"caption_candidate":"Table 1 Comparisons to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203448-p8-t0","doc_id":"K203448","page_num":8,"bbox":[86.5,77.67,568.56,655.15],"n_rows":8,"n_cols":4,"columns":["","It’s a patient\npositioning assistance\nfunction based on deep\nlearning technology","","The changes did not raise new\nsafety and effectiveness\nconcerns."],"rows":[["","It’s a patient\npositioning assistance\nfunction based on deep\nlearning technology","","The changes did not raise new\nsafety and effectiveness\nconcerns."],["Auto ALARA kVp","Yes\nIt can recommend the\nsuitable kVp for the\nexamination.","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Organ-Based Auto\nALARA mA","Yes\nIt can optimize the\ndose modulation for\nthe combined chest\nand abdomen scan\nwith deep learning\nbased organ\nrecognition.","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["CardioXphase","Yes\nIt can recommend the\noptimal phase for\ncardiac reconstruction\nwith less motion\nartifact.","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["CardioCapture","Yes\nIt can reduce the\ncoronary motion\nartifact with deep\nlearning based\ncoronary artery\nextraction.","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["EasyRange","Yes\nIt can automatically\nrecommend the scan\nrange with a deep\nlearning organ\nrecognition\ntechnology","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Injector Linkage","Yes","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."],["Remote Assistance","Yes","--","Substantially Equivalent\nThe changes did not raise new\nsafety and effectiveness\nconcerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203448-p9-t0","doc_id":"K203448","page_num":9,"bbox":[81.84,89.54,563.67,409.85],"n_rows":10,"n_cols":7,"columns":["Item","Proposed device","","Reference device #1","","Reference device #2\nDeep Recon\n(K193073)","Discussion of\ndifferences"],"rows":[["Item","Proposed device","","Reference device #1","","Reference device #2\nDeep Recon\n(K193073)","Discussion of\ndifferences"],["","","","Aquilion ONE Vision","","",""],["","","","With FIRST 2.0","","",""],["","","","(CCRS-001B) V7.4","","",""],["","","","(K161009)","","",""],["Anatomical\nRegion","Abdomen, pelvis,\nchest","Abdomen, pelvis,\nchest, cardiac and\nextremities","","","Abdomen, pelvis,\nchest, cardiac and\nhead","Same"],["Exposure Dose\nReduction","Yes","Yes","","","Yes","Same"],["Quantitative\nDose Reduction\nClaim","Yes","Yes","","","Yes","Same"],["Image Quality\nImprovement\nClaim","Yes","Yes","","","Yes","Same"],["Reconstruction\nTechnology","It is an image\nreconstruction\nmethod that\ncombines a\nmodal-based\niterative\nreconstruction\nand deep learning\ntechnology.","It is an iterative\nreconstruction\nalgorithm.","","","Dedicated deep neural\nnetwork (DNN) which\nis trained on low dose\nFBP images to get\nnormal dose (high\nquality) FBP images","Substantially\nEquivalent\nTesting did not\nraise new safety\nand effectiveness\nconcerns."]],"caption_candidate":"Table 2 Deep IR Comparison to Reference devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203448-p9-t1","doc_id":"K203448","page_num":9,"bbox":[81.84,435.89,563.67,705.46],"n_rows":15,"n_cols":9,"columns":["Item","Proposed\nDevice","","Reference device #3","","","Reference device #4","","Discussion of\ndifferences"],"rows":[["Item","Proposed\nDevice","","Reference device #3","","","Reference device #4","","Discussion of\ndifferences"],["","","","Dual Energy System","","","Discovery CT750 HD","",""],["","","","Package (K132813)","","","(K120833)","",""],["Dual Energy Scan","Yes","Yes","","","Yes","","","Same"],["Dual Energy Analysis","","","","","","","",""],["Mono Energetic Image","Yes","Yes","","","--","","","Same"],["Mixed Enhanced Image","Yes","Yes","","","--","","","Same"],["CNR(Contrast Noise Ratio)\nImage","Yes","Yes","","","--","","","Same"],["Water-Iodine Base Material\nPair","Yes","--","","","Yes","","","Same"],["Water-Calcium Base\nMaterial Pair","Yes","--","","","Yes","","","Same"],["Calcium-Iodine Base\nMaterial Pair","Yes","--","","","Yes","","","Same"],["Uric acid-Calcium Base\nMaterial Pair","Yes","--","","","Yes","","","Same"],["Image Registration","Yes","Yes","","","--","","","Same"],["Effective Atomic Number\nImages","Yes","--","","","Yes","","","Same"],["Electron Density Image","Yes","--","","","Yes","","","Same"]],"caption_candidate":"Table 3 Dual Energy comparison to Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203448-p10-t0","doc_id":"K203448","page_num":10,"bbox":[81.86,77.64,563.64,177.98],"n_rows":3,"n_cols":5,"columns":["Virtual Non contrast Images","Yes","--","Yes","Same"],"rows":[["Virtual Non contrast Images","Yes","--","Yes","Same"],["Component analysis of\nkidney stones, uric acid\nstones or non-uric acid\nstones","Yes","Yes","--","Same"],["Component analysis of joint\ngout, uric acid gout or non-\nuric acid gout","Yes","Yes","--","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p10-t0","doc_id":"K203508","page_num":10,"bbox":[43.68,456.24,539.76,759.12],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K190896)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K190896)","Subject Device\nAidoc Briefcase (K203508)"],["Intended Use / Indications for\nUse","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of cervical\nspine CT images. The device is\nintended to assist hospital\nnetworks and trained radiologists\nin workflow triage by flagging\nand communication of suspected\npositive findings of linear\nlucencies in the cervical spine\nbone in patterns compatible with\nfractures.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a\nstandalone desktop application\nin parallel to the ongoing\nstandard of care image\ninterpretation. The user is\npresented with notifications for","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of cervical\nspine CT images. The device is\nintended to assist hospital\nnetworks and appropriately\ntrained medical specialists in\nworkflow triage by flagging and\ncommunication of suspected\npositive findings of linear\nlucencies in the cervical spine\nbone in patterns compatible with\nfractures.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a\nstandalone desktop application\nin parallel to the ongoing\nstandard of care image\ninterpretation. The user is"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p11-t0","doc_id":"K203508","page_num":11,"bbox":[43.68,72.24,539.76,694.08],"n_rows":12,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K190896)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K190896)","Subject Device\nAidoc Briefcase (K203508)"],["","cases with suspected findings.\nNotifications include compressed\npreview images that are meant\nfor informational purposes only\nand not intended for diagnostic\nuse beyond notification. The\ndevice does not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","presented with notifications for\ncases with suspected findings.\nNotifications include compressed\npreview images that are\nmeant for informational purposes\nonly and not intended for\ndiagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based on\ntheir professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],["User population","Radiologist","Appropriately trained medical\nspecialists"],["Anatomical region of interest","Cervical spine","Cervical spine"],["Data acquisition protocol","Non-contrast cervical spine CT\nscan","Non-contrast cervical spine CT\nscans"],["View DICOM data","DICOM Information about the\npatient, study and current image","DICOM Information about the\npatient, study and current image"],["Segmentation of region of\ninterest","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm\nwith database of images"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases."],["Alteration of original image","No","No"],["Removal of cases from worklist\nqueue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p14-t0","doc_id":"K203508","page_num":14,"bbox":[72.0,492.36,515.76,759.12],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K180647)"],"rows":[["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K180647)"],["Intended Use / Indications for\nUse","BriefCase is a radiological\ncomputer aided triage and\nnotification software\nindicated for use in the\nanalysis of non-enhanced\nhead CT images.\nThe device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialist in workflow triage\nby flagging and\ncommunication of suspected\npositive findings of\npathologies in head CT\nimages, namely Intracranial\nHemorrhage (ICH).\nBriefCase uses an artificial\nintelligence algorithm to","BriefCase is a radiological\ncomputer aided triage and\nnotification software\nindicated for use in the\nanalysis of non-enhanced\nhead CT images.\nThe device is intended to\nassist hospital networks and\ntrained radiologists in\nworkflow triage by flagging\nand communication of\nsuspected positive findings\nof pathologies in head CT\nimages, namely Intracranial\nHemorrhage (ICH).\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p15-t0","doc_id":"K203508","page_num":15,"bbox":[72.0,72.24,515.76,765.48],"n_rows":10,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K180647)"],"rows":[["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K180647)"],["","analyze images and highlight\ncases with detected ICH on a\nstandalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The\nuser is presented\nwith notifications for cases\nwith suspected ICH findings.\nNotifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not\nintended for diagnostic use\nbeyond notification. The\ndevice does not alter the\noriginal medical image and is\nnot intended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and\nbased on professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","cases with detected ICH on a\nstandalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The\nuser is presented\nwith notifications for cases\nwith suspected ICH findings.\nNotifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not\nintended for diagnostic use\nbeyond notification. The\ndevice does not alter the\noriginal medical image and is\nnot intended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and\nbased on professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],["User population","Appropriately trained medical\nspecialist","Radiologist"],["Anatomical region of interest","Head","Head"],["Data acquisition protocol","Non contrast CT scan of the\nhead or neck","Non contrast CT scan of the\nhead or neck"],["View DICOM data","DICOM Information about\nthe patient, study and current\nimage","DICOM Information about\nthe patient, study and current\nimage"],["Segmentation of region of\ninterest","No; device does not mark,\nhighlight, or direct users’\nattention to a specific\nlocation in the original image","No; device does not mark,\nhighlight, or direct users’\nattention to a specific\nlocation in the original image"],["Algorithm","Artificial intelligence\nalgorithm with database of\nimages","Artificial intelligence\nalgorithm with database of\nimages"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a preview of\nthe study for initial\nassessment not meant for\ndiagnostic purposes\nThe device operates in\nparallel with the standard of","Presentation of notification\nand preview of the study for\ninitial assessment not meant\nfor diagnostic purposes\nThe device operates in\nparallel with the standard of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p18-t0","doc_id":"K203508","page_num":18,"bbox":[77.64,467.16,523.13,757.92],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],["Intended Use /\nIndications for Use","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of non-\nenhanced head CT and CTPA\nimages. The device is intended\nto assist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of suspected\npositive findings of Intracranial\nHemorrhage (ICH) and\nPulmonary Embolism (PE)\npathologies. For the PE\npathology, the software is only\nintended to be used on single-\nenergy exams.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight\ncases with detected findings on","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of non-\nenhanced head CT and CTPA\nimages. The device is intended\nto assist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication\nof suspected positive findings of\nIntracranial Hemorrhage (ICH)\nand Pulmonary Embolism (PE)\npathologies. For the PE\npathology, the software is only\nintended to be used on single-\nenergy exams.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight\ncases with detected findings on"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p19-t0","doc_id":"K203508","page_num":19,"bbox":[77.64,72.24,523.08,765.48],"n_rows":10,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],["","a standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected findings.\nNotifications include\ncompressed preview images\nthat are meant for informational\npurposes only and not intended\nfor diagnostic use beyond\nnotification. The device does\nnot alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","a standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected findings.\nNotifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not intended\nfor diagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based\non their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing\nfull images per the standard of\ncare."],["User population","Radiologist","Appropriately trained medical\nspecialists"],["Anatomical region of\ninterest","Head and chest","Head and chest"],["Data acquisition\nprotocol","Non-contrast head CT scan and\nCTPA (single energy exams\nonly)","Non-contrast head CT scan and\nCTPA (single energy exams\nonly)"],["View DICOM data","DICOM Information about the\npatient, study and current\nimage","DICOM Information about the\npatient, study and current\nimage"],["Segmentation of region\nof interest","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm\nwith database of images"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for\nall cases.","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for\nall cases."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p20-t0","doc_id":"K203508","page_num":20,"bbox":[77.64,72.24,523.08,146.16],"n_rows":3,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K190072)","Subject Device\nAidoc Briefcase (K203508)"],["Alteration of original\nimage","No","No"],["Removal of cases from\nworklist queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p22-t0","doc_id":"K203508","page_num":22,"bbox":[50.7,538.32,525.6,768.78],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],["Intended Use / Indications\nfor Use","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of abdominal\nCT images. The device is intended\nto assist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of suspected\npositive findings of Intra-abdominal\nFree Gas (IFG) pathologies.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\ndesktop application in parallel to","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of\nabdominal CT images.\nThe device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication\nof suspected positive findings\nof Intra-abdominal Free Gas\n(IFG) pathologies.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p23-t0","doc_id":"K203508","page_num":23,"bbox":[50.7,72.24,525.6,765.96],"n_rows":11,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],["","the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for\ncases with suspected findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are\nintended to be used in conjunction\nwith other patient information and\nbased on their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","cases with detected findings on\na standalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor cases with suspected\nfindings. Notifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not intended\nfor diagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based\non their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing\nfull images per the standard of\ncare."],["User population","Radiologist","Appropriately trained medical\nspecialists"],["Anatomical region of\ninterest","Abdomen","Abdomen"],["Data acquisition protocol","Abdominal CT scan","Abdominal CT scan"],["View DICOM data","DICOM Information about the\npatient, study and current image","DICOM Information about the\npatient, study and current\nimage"],["Segmentation of region of\ninterest","No; device does not mark,\nannotate, or direct users’ attention\nto a specific location in the original\nimage","No; device does not mark,\nannotate, or direct users’\nattention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm\nwith database of images"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a small,\ncompressed, black and white\npreview image that is labeled “Not\nfor diagnostic use”;\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in parallel\nwith the standard of care,\nwhich remains the default\noption for all cases."],["Alteration of original image","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p24-t0","doc_id":"K203508","page_num":24,"bbox":[50.7,72.24,525.6,121.56],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K193298)","Subject Device\nAidoc Briefcase (K203508)"],["Removal of cases from\nworklist queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p26-t0","doc_id":"K203508","page_num":26,"bbox":[77.64,573.36,523.08,767.58],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],["Intended Use /\nIndications for Use","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of\ncontrast-enhanced chest CTs\n(but not dedicated CTPA\nprotocol). The device is\nintended to assist hospital\nnetworks and trained\nradiologists in workflow triage\nby flagging and communication\nof suspected positive cases of\nincidental Pulmonary Embolism\n(iPE) pathologies. For the iPE","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of\ncontrast-enhanced chest CTs\n(but not dedicated CTPA\nprotocol). The device is\nintended to assist hospital\nnetworks and appropriately\ntrained medical specialists in\nworkflow triage by flagging and\ncommunication of suspected\npositive cases of incidental\nPulmonary Embolism (iPE)"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p27-t0","doc_id":"K203508","page_num":27,"bbox":[77.64,72.24,523.08,766.5],"n_rows":5,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],["","pathology, the software is only\nintended to be used on single-\nenergy exams. The device is\nintended to work with GE and\nSiemens scanners only.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and flag suspect cases\non a standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\nsuspect cases. Notifications\ninclude compressed preview\nimages that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","pathologies. For the iPE\npathology, the software is only\nintended to be used on single-\nenergy exams. The device is\nintended to work with GE and\nSiemens scanners only.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and flag\nsuspect cases on a standalone\ndesktop application in parallel\nto the ongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor suspect cases. Notifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not intended\nfor diagnostic use\nbeyond notification. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based\non their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing\nfull images per the standard of\ncare."],["User population","Radiologist","Appropriately trained medical\nspecialists"],["Anatomical region of\ninterest","Chest","Chest"],["Inclusion/\nExclusion criteria","Inclusion Criteria\n- Contrast-enhanced chest\nCTs (but not dedicated\nCTPA protocol.\n- Single energy exams.\n- Scans performed with a\n64 slice or greater\nnumber of detectors.\n- Scans performed on\nadults/transitional adults ≥\n18 years of age.","Inclusion criteria\n- Contrast-enhanced chest\nCTs (but not dedicated\nCTPA protocol.\n- Single energy exams.\n- Scans performed with a 64\nslice or greater number of\ndetectors.\n- Scans performed on\nadults/transitional adults ≥\n18 years of age."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p28-t0","doc_id":"K203508","page_num":28,"bbox":[77.64,72.24,523.08,636.6],"n_rows":11,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],"rows":[["","Predicate Device\nAidoc Briefcase (K201020)","Subject Device\nAidoc Briefcase (K203508)"],["","- Slice thickness: 0.5mm –\n2.0mm axial.\nExclusion Criteria\n- - All studies that are\ntechnically inadequate,\nincluding studies with motion\nartifacts, severe metal\nartifacts, or inadequate field\nof view..","- Slice thickness: 0.5mm –\n2.0mm axial.\nExclusion Criteria\n- All studies that are\ntechnically inadequate,\nincluding studies with motion\nartifacts, severe metal\nartifacts, or inadequate field\nof view."],["Data acquisition\nprotocol","Contrast-enhanced chest CTs\n(but not dedicated CTPA\nprotocol)","Contrast-enhanced chest CTs\n(but not dedicated CTPA\nprotocol)"],["View DICOM data","DICOM Information about the\npatient, study and current image","DICOM Information about the\npatient, study and current\nimage"],["Segmentation of region\nof interest","No; device does not mark,\nannotate, or direct users’\nattention to a specific location in\nthe original image","No; device does not mark,\nannotate, or direct users’\nattention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm\nwith database of images"],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a low-quality,\ncompressed, grayscale preview\nimage that is captioned “Not for\ndiagnostic use”.","Presentation of a low-quality,\ncompressed, grayscale preview\nimage that is captioned “Not for\ndiagnostic use”."],["Alteration of original\nimage","No","No"],["Removal of cases from\nworklist queue","No. The device operates in\nparallel with the standard of\ncare, which remains the default\noption for all cases. Unflagged\ncases are not de-prioritized.","No. The device operates in\nparallel with the standard of\ncare, which remains the default\noption for all cases. Unflagged\ncases are not de-prioritized."],["Structure","- AHS module (image\nacquisition).\n- ACS module (image\nprocessing).\n- Aidoc Worklist application for\nworkflow integration (worklist\nand non-diagnostic basic\nImage Viewer).","- AHS module (image\nacquisition).\n- ACS module (image\nprocessing).\n- Aidoc Worklist application\nfor workflow integration\n(worklist and non-diagnostic\nbasic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p31-t0","doc_id":"K203508","page_num":31,"bbox":[77.64,531.12,538.38,761.52],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],"rows":[["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],["Intended Use / Indications for\nUse","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of head\nCTA images. The device is\nintended to assist hospital\nnetworks and appropriately\ntrained medical specialists in\nworkflow triage by flagging\nand communication of\nsuspected positive findings of\nLarge Vessel Occlusion (LVO)\npathologies.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight","BriefCase is a radiological\ncomputer aided triage and\nnotification soft-ware indicated\nfor use in the analysis of head\nCTA images. The device is\nintended to assist hospital\nnetworks and trained medical\nspecialists in workflow triage\nby flagging and\ncommunication of suspected\npositive findings of Large\nVessel Occlusion (LVO)\npathologies.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p32-t0","doc_id":"K203508","page_num":32,"bbox":[77.64,72.24,538.38,692.4],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],"rows":[["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],["","cases with detected findings\non a standalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor cases with suspected\nfindings. Notifications\ninclude compressed preview\nimages that are\nmeant for informational\npurposes only and not\nintended for diagnostic use\nbeyond notification. The\ndevice does not alter the\noriginal medical image and is\nnot intended to be used as a\ndiagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other\npatient information and based\non their professional\njudgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing\nfull images per the standard of\ncare.","cases with detected findings\non a standalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor cases with suspected\nfindings. Notifications include\ncompressed preview images\nthat are meant for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. The device does\nnot alter the original medical\nimage and is not intended to\nbe used as a diagnostic\ndevice.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to\nassist with triage/prioritization\nof medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],["User population","Appropriately trained medical\nspecialists","Radiologist"],["Anatomical region of interest","Head","Head"],["Inclusion/\nExclusion criteria","Inclusion criteria\n• Head CTA protocol with a\n64-slice scanner or higher;\n• Scans performed on\nadults/transitional adults ≥\n18 years of age;\n• Slice thickness 0.5 mm –\n1.0 mm.\nExclusion Criteria\n• All scans that are\ntechnically inadequate,\nincluding motion artifacts,\nsevere metal artifacts, sub-\noptimal bolus timing or an\ninadequate field of view.","Inclusion Criteria\n• Head CTA protocol with a\n64-slice scanner or higher;\n• Scans performed on\nadults/transitional adults ≥\n18 years of age;\n• Slice thickness 0.5 mm –\n1.0 mm.\nExclusion Criteria\n• All scans that are\ntechnically inadequate,\nincluding motion artifacts,\nsevere metal artifacts, sub-\noptimal bolus timing or an\ninadequate field of view."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203508-p33-t0","doc_id":"K203508","page_num":33,"bbox":[77.64,72.24,538.38,535.56],"n_rows":9,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],"rows":[["","Subject Device\nAidoc Briefcase (K203508)","Predicate Device\nAidoc Briefcase (K192383)"],["View DICOM data","DICOM Information about the\npatient, study and current\nimage","DICOM Information about the\npatient, study and current\nimage"],["Segmentation of region of\ninterest","No; device does not mark,\nannotate, or direct users’\nattention to a specific location\nin the original image.","No; device does not mark,\nannotate, or direct users’\nattention to a specific location\nin the original image."],["Algorithm","Artificial intelligence algorithm\nwith database of images.","Artificial intelligence algorithm\nwith database of images."],["Notification/Prioritization","Yes","Yes"],["Preview images","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in\nparallel with the standard of\ncare, which remains the\ndefault option for all cases.","Presentation of a small,\ncompressed, black and white\npreview image that is labeled\n“Not for diagnostic use”;\nThe device operates in\nparallel with the standard of\ncare, which remains the\ndefault option for all cases."],["Alteration of original image","No","No"],["Removal of cases from\nworklist queue","No","No"],["Structure","- AHS module (image\nacquisition);\n- ACS module (image\nprocessing);\n- Aidoc Worklist application\nfor workflow integration\n(worklist and Image\nViewer).\nAddition of minor changes in\nthe software platform, e.g.\nnotification filter, which\nneither impacts the order in\nwhich notification come in,\nnor affects the safety and\nefficacy profile of the device.","- AHS module (image\nacquisition);\n- ACS module (image\nprocessing);\n- Aidoc Worklist application\nfor workflow integration\n(worklist and Image\nViewer).\nAddition of minor changes in\nthe software platform, e.g.\nnotification filter, which\nneither impacts the order in\nwhich notification come in,\nnor affects the safety and\nefficacy profile of the device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203514-p4-t0","doc_id":"K203514","page_num":4,"bbox":[84.6,185.04,516.12,713.76],"n_rows":30,"n_cols":3,"columns":["Date Prepared:","November 18, 2020",""],"rows":[["Date Prepared:","November 18, 2020",""],["Manufacturer:","Philips Healthcare (Suzhou) Co., Ltd.",""],["","No. 258, ZhongYuan Road, Suzhou Industrial Park, 215024",""],["","Suzhou, Jiangsu Province, PEOPLE'S REPUBLIC OF CHINA",""],["","Establishment Registration Number: 3009529630",""],["Primary Contact\nPerson:","Shiguang An",""],["","Advanced Regulatory Engineer",""],["","Phone: +86-13940106467",""],["","E-mail: shiguang.an@philips.com",""],["Secondary Contact\nPerson:","Erhong Wang",""],["","Senior Regulatory Affairs Manager",""],["","Phone: +86-13021019589",""],["","E-mail: erhong.wang@philips.com",""],["Device Name:","Precise position",""],["Classification:","Classification Name","Computed tomography x-ray\nsystem"],["","Classification Regulation:","21CFR §892.1750"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary product code:","JAK"],["","",""],["Predicate Device:","Trade Name:","Philips Incisive CT"],["","Manufacturer:","Philips Healthcare (Suzhou)\nCo., Ltd."],["","510(k) Clearance:","K180015-March 20, 2018"],["","Classification Regulation:","21 CFR, Part 892.1750"],["","Classification Name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Product Code","JAK"],["","",""],["Reference Device:","Manufacturer:","Auto Positioning"]],"caption_candidate":"with 21 CFR §807.92.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203514-p5-t0","doc_id":"K203514","page_num":5,"bbox":[84.6,99.96,516.12,227.64],"n_rows":7,"n_cols":3,"columns":["","","GE Hangwei Medical System\nCo., Ltd."],"rows":[["","","GE Hangwei Medical System\nCo., Ltd."],["","510(k) Clearance:","K192956 (January 16, 2020)"],["","Classification Regulation:","21 CFR, Part 892.1750"],["","Classification Name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Product Code","JAK"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203514-p7-t0","doc_id":"K203514","page_num":7,"bbox":[84.6,99.96,534.24,716.82],"n_rows":2,"n_cols":2,"columns":["Fundamental\nscientific\ntechnology:","Based on the information provided above, the precise position is\nconsidered substantially equivalent to the primary currently\nmarketed and predicate device Philips Incisive CT (K180015,\n20/March/2018) in terms of fundamental scientific technology.\nAttribute Predicate Device Proposed Device Precise\nPhilips Incisive CT Position\n(K180015)\nPatient Manually position Precise position provides\npositioning the patient via the the auto workflow to set\nworkflow couch motion button the surview start/end\nand laser. Normally, position, center of patient\nneed several round anatomy, and patient\nadjustments by user. orientation.\nDetection The manual Precise position adopt the\nalgorithm workflow does not AI algorithm (Convolution\nneed special Neural Network) to detect\nalgorithm. the joints of the patient\nbody automatically, and\nthen automatic detect\nsurview start/end position,\ncenter of patient anatomy\nand patient orientation.\nHardware Manual patient Precision position feature\nneed to positioning does not need color and depth\nsupport the need any unique camera, high speed USB\npatient hardware except transmission cable, and\npositioning traditional exiting power cable, and relative\nhardware on the CT the enhanced workflow.\nor other system. The tradition exiting\nExiting hardware patient positioning\nincludes table hardware still be available\nmotion button for user all the time, it is\n(in/out, up/down) on convenient to switch\ngantry panel or between the camera\nCTBOX, lasers and automatically detecting\netc. mode and manual mode.\nPatient All ages More than 16 years old.\npopulation\nEnvironment Hospitals, outpatient Hospitals, outpatient\nof use clinics, research clinics, research\ninstitutions, and institutions, and other\nother clinical clinical facilities.\nfacilities."],"rows":[["Fundamental\nscientific\ntechnology:","Based on the information provided above, the precise position is\nconsidered substantially equivalent to the primary currently\nmarketed and predicate device Philips Incisive CT (K180015,\n20/March/2018) in terms of fundamental scientific technology.\nAttribute Predicate Device Proposed Device Precise\nPhilips Incisive CT Position\n(K180015)\nPatient Manually position Precise position provides\npositioning the patient via the the auto workflow to set\nworkflow couch motion button the surview start/end\nand laser. Normally, position, center of patient\nneed several round anatomy, and patient\nadjustments by user. orientation.\nDetection The manual Precise position adopt the\nalgorithm workflow does not AI algorithm (Convolution\nneed special Neural Network) to detect\nalgorithm. the joints of the patient\nbody automatically, and\nthen automatic detect\nsurview start/end position,\ncenter of patient anatomy\nand patient orientation.\nHardware Manual patient Precision position feature\nneed to positioning does not need color and depth\nsupport the need any unique camera, high speed USB\npatient hardware except transmission cable, and\npositioning traditional exiting power cable, and relative\nhardware on the CT the enhanced workflow.\nor other system. The tradition exiting\nExiting hardware patient positioning\nincludes table hardware still be available\nmotion button for user all the time, it is\n(in/out, up/down) on convenient to switch\ngantry panel or between the camera\nCTBOX, lasers and automatically detecting\netc. mode and manual mode.\nPatient All ages More than 16 years old.\npopulation\nEnvironment Hospitals, outpatient Hospitals, outpatient\nof use clinics, research clinics, research\ninstitutions, and institutions, and other\nother clinical clinical facilities.\nfacilities."],["Summary of Non-\nClinical","The Precise Position complies with the following international and\nFDA-recognized consensus standards:"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203514-p8-t0","doc_id":"K203514","page_num":8,"bbox":[84.6,99.96,534.24,709.26],"n_rows":2,"n_cols":2,"columns":["Performance data:","• AAMI / ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)\n2012 and A2:2010/(R) 2012\n(Consolidated Text) Medical Electrical Equipment - Part 1: General\nRequirements. For Basic Safety and Essential Performance (IEC\n60601-1:2012, MOD).\nFDA/CDRH recognition number 19-4\n• IEC 60601-1-2:2014, Medical electrical equipment – Part 1-2:\nGeneral requirements for basic safety and essential performance -–\nCollateral standard: Electromagnetic disturbances - Requirements and\ntests.\nFDA/CDRH recognition number 19-8\n• ISO 14971 Medical devices – Application of risk management to\nmedical devices. FDA/CDRH recognition number 5-40.\n• IEC 62304:2015, Medical device software -- Software life cycle\nprocesses\nFDA/CDRH recognition number 13-79\nThere are no risks identified in risk management documentation that\nrequire clinical data for the purpose of clinical evaluation; Risk\nManagement Plan as Appendix 001, Risk Management Report as\nAppendix 002, and Risk Management Matrix as Appendix 003 of\nPrecise Position.\nThere are no clinical risks identified by the evaluated clinical data.\nSufficient evidence is available to demonstrate the ability of Precise\nPosition achieve the intended performances during normal condition\nof use.\nFull consistency exists between the state-of-the-art, the evaluated data,\nthe risk management documentation and the information materials\nsupplied.\nTherefore, the Precise Position is substantially equivalent to the\nprimary currently marketed and predicate device (K180015,\n20/March/2018) in terms of safety and effectiveness."],"rows":[["Performance data:","• AAMI / ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)\n2012 and A2:2010/(R) 2012\n(Consolidated Text) Medical Electrical Equipment - Part 1: General\nRequirements. For Basic Safety and Essential Performance (IEC\n60601-1:2012, MOD).\nFDA/CDRH recognition number 19-4\n• IEC 60601-1-2:2014, Medical electrical equipment – Part 1-2:\nGeneral requirements for basic safety and essential performance -–\nCollateral standard: Electromagnetic disturbances - Requirements and\ntests.\nFDA/CDRH recognition number 19-8\n• ISO 14971 Medical devices – Application of risk management to\nmedical devices. FDA/CDRH recognition number 5-40.\n• IEC 62304:2015, Medical device software -- Software life cycle\nprocesses\nFDA/CDRH recognition number 13-79\nThere are no risks identified in risk management documentation that\nrequire clinical data for the purpose of clinical evaluation; Risk\nManagement Plan as Appendix 001, Risk Management Report as\nAppendix 002, and Risk Management Matrix as Appendix 003 of\nPrecise Position.\nThere are no clinical risks identified by the evaluated clinical data.\nSufficient evidence is available to demonstrate the ability of Precise\nPosition achieve the intended performances during normal condition\nof use.\nFull consistency exists between the state-of-the-art, the evaluated data,\nthe risk management documentation and the information materials\nsupplied.\nTherefore, the Precise Position is substantially equivalent to the\nprimary currently marketed and predicate device (K180015,\n20/March/2018) in terms of safety and effectiveness."],["Summary of\nClinical Data:","Precise Position is evaluation covered total 80 clinical scan positions\nin which 40 cases used with Precise Position and another 40 cases\nwithout the usage of Precise Position in order to meet the sample size\ncalculation of 40 cases performed average on a CT scanner per day.\nThe thorough clinical evaluation of this feature is done by 5 Clinical\nexperts.\nThe testing did not deliver radiation to volunteers as Precise Position\nis only for supporting the positioning of the patient for the localization\nradiograph and therefore “radiation” was not required for those\nvolunteers."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203514-p9-t0","doc_id":"K203514","page_num":9,"bbox":[84.6,99.96,534.24,696.06],"n_rows":2,"n_cols":2,"columns":["","The clinical evaluation was done with 3 major objectives as follows,\nTo calculate the time saved per surview planning with and without\nPrecise Position.\nTo calculate the accuracy of vertical (iso)center positioning and\nSurview (horizontal) start /end position with and without Precise\nPosition\nIntra operator consistency in positioning the patient and surview scan\nrange\nThe summary of clinical evaluation testing was clearly demonstrating\nthe objectives in terms of user benefits as shown below\nAverage Time taken to position without Precise Position and with\nPrecise Position is recorded. Time at user select the patient from\nGantry Panel, to time when user pressed Go button from Gantry Panel\nis measured and concluded that up to 23% time reduction in patient\npositioning achieved with “Precise Positioning workflow”.\nThe average offset in mm for vertical (iso) center position among 5\noperators without Precise Position and with Precise Position is\nrecorded and results shown that with “Precise Position” the vertical\nposition accuracy is increased up to 50%.\nStandard deviation in mm for vertical (iso)center positioning &\nSurview (horizontal) start position among 5 operators without Precise\nPosition and with Precise Position is recorded and results shown up to\n70% increase in Vertical and horizontal position consistency with\nPrecise Position.\nOverall, the Precise Position Clinical Review Report. (Appendix_007)\nconcluded that Philips Incisive CT systems with Precise Position,\nunder normal condition of use, perform as intended, are safe for its\nintended use and have a favorable benefit-risk ratio. Further clinical\ninvestigations are not necessary, as sufficient evidence exists to\nsupport these conclusions."],"rows":[["","The clinical evaluation was done with 3 major objectives as follows,\nTo calculate the time saved per surview planning with and without\nPrecise Position.\nTo calculate the accuracy of vertical (iso)center positioning and\nSurview (horizontal) start /end position with and without Precise\nPosition\nIntra operator consistency in positioning the patient and surview scan\nrange\nThe summary of clinical evaluation testing was clearly demonstrating\nthe objectives in terms of user benefits as shown below\nAverage Time taken to position without Precise Position and with\nPrecise Position is recorded. Time at user select the patient from\nGantry Panel, to time when user pressed Go button from Gantry Panel\nis measured and concluded that up to 23% time reduction in patient\npositioning achieved with “Precise Positioning workflow”.\nThe average offset in mm for vertical (iso) center position among 5\noperators without Precise Position and with Precise Position is\nrecorded and results shown that with “Precise Position” the vertical\nposition accuracy is increased up to 50%.\nStandard deviation in mm for vertical (iso)center positioning &\nSurview (horizontal) start position among 5 operators without Precise\nPosition and with Precise Position is recorded and results shown up to\n70% increase in Vertical and horizontal position consistency with\nPrecise Position.\nOverall, the Precise Position Clinical Review Report. (Appendix_007)\nconcluded that Philips Incisive CT systems with Precise Position,\nunder normal condition of use, perform as intended, are safe for its\nintended use and have a favorable benefit-risk ratio. Further clinical\ninvestigations are not necessary, as sufficient evidence exists to\nsupport these conclusions."],["Substantial\nEquivalence\nConclusion:","The Precise Position is substantially equivalent to the primary\ncurrently marketed and predicate device (K180015, 20/March/2018) in\nterms of design features, fundamental scientific technology,\nindications for use, and safety and effectiveness. Additionally,\nsubstantial equivalence was demonstrated with non-clinical\nperformance tests, which complied with the requirements specified in\nthe international and FDA-recognized consensus standards, IEC 62304\nand ISO 14971. The results of these tests demonstrate that Precise\nPosition met the acceptance criteria and is adequate for this intended\nuse."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203517-p5-t0","doc_id":"K203517","page_num":5,"bbox":[72.25,592.81,545.53,711.37],"n_rows":2,"n_cols":4,"columns":["","Subject device\nSaige-Q\nDeepHealth Inc.","Predicate device\ncmTriage\nCureMetrix.\nK183285","Summary"],"rows":[["","Subject device\nSaige-Q\nDeepHealth Inc.","Predicate device\ncmTriage\nCureMetrix.\nK183285","Summary"],["Regulation\nnumber","21 CFR 892.2080 -\nRadiological Computer-\nAssisted Prioritization","21 CFR 892.2080 -\nRadiological Computer-\nAssisted Prioritization Software","Same"]],"caption_candidate":"comparison with the predicate device is provided in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203517-p6-t0","doc_id":"K203517","page_num":6,"bbox":[72.25,72.73,545.53,719.29],"n_rows":5,"n_cols":4,"columns":["","Software","",""],"rows":[["","Software","",""],["Product code","QFM","QFM","Same"],["Class","II","II","Same"],["Intended use","Saige-Q is a software\nworkflow tool designed to aid\nradiologists in prioritizing\nexams within the standard-of-\ncare image worklist for full-\nfield digital mammography\n(FFDM) and digital breast\ntomosynthesis (DBT)\nscreening mammograms.\nSaige-Q uses an artificial\nintelligence algorithm to\ngenerate a code for a given\nmammogram, indicative of\nthe software’s suspicion that\nthe mammogram contains at\nleast one suspicious finding.\nSaige-Q makes the assigned\ncodes available to a\nPACS/EPR/RIS/workstation\nfor worklist prioritization or\ntriage.\nSaige-Q is intended for\npassive notification only and\ndoes not provide any\ndiagnostic information\nbeyond triage and\nprioritization. Thus, it is not\nintended to replace the review\nof images or be used on a\nstand-alone basis for clinical\ndecision-making. The\ndecision to use Saige-Q codes\nand how to use those codes is\nultimately up to the\ninterpreting radiologist. The\ninterpreting radiologist is\nresponsible for reviewing\neach exam on a diagnostic\nviewer and evaluating each\npatient according to the\ncurrent standard of care.","cmTriage is a passive\nprioritization-only, parallel-\nworkflow software tool used by\nradiologists to prioritize specific\npatients within the standard-of-\ncare image worklist for 2D\nFFDM screening mammograms.\ncmTriage uses an artificial\nintelligence algorithm to\nanalyze 2D FFDM screening\nmammograms and flags those\nthat are suggestive of the\npresence of at least one\nsuspicious finding at the exam\nlevel. These flags are viewed by\nthe radiologist via their PACS\nworklist. The decision to use\ncmTriage codes and how to use\ncmTriage codes is ultimately up\nto the radiologist. cmTriage\ndoes not send a proactive alert\ndirectly to the radiologist.\nRadiologists are responsible for\nreviewing each exam on a\ndiagnostic viewer according to\nthe current standard of care.\ncmTriage is limited to the\ncategorization of exams, does\nnot provide any diagnostic\ninformation beyond triage and\nprioritization, does not remove\nimages from the radiologist’s\nworklist, and should not be used\nin lieu of full patient evaluation,\nor relied upon to make or\nconfirm diagnosis.\ncmTriage is for prescription use\nonly.","Both devices have the\nsame intended use\nper 21 CFR 892.2080"],["Technical\nMethod","The device provides triage or\nnotification that is informed\nby artificial intelligence\nalgorithms.","The device provides triage or\nnotification that is informed by\nartificial intelligence\nalgorithms.","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203517-p7-t0","doc_id":"K203517","page_num":7,"bbox":[72.25,72.73,545.53,713.05],"n_rows":11,"n_cols":4,"columns":["Anatomical Site","Breast","Breast","Same"],"rows":[["Anatomical Site","Breast","Breast","Same"],["Clinical\ncondition","Breast cancer","Breast cancer","Same"],["Notification-\nonly, parallel\nworkflow tool","Yes","Yes","Same"],["Alert to finding","Passive notification flagged\nfor review","Passive notification flagged for\nreview","Same"],["Preview Image","Preview of the\nstudy for initial assessment,\nnot meant for diagnostic\npurposes.\nThe device operates in\nparallel with the standard of\ncare, which remains the\ndefault option for all cases.","Preview of the study for initial\nassessment, not meant for\ndiagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for\nall cases.","Same"],["Multiple\noperating\npoints","Yes; 3 operating points","Yes; a continuous range of\noperating points.","Similar but Saige-Q\nuses a more\nconservative\napproach by pre-\nspecifying a discrete\nnumber of operating\npoints."],["Independent of\nstandard of care\nworkflow","Yes; no cases are removed\nfrom worklist","Yes; no cases are removed from\nworklist","Same"],["End users","Radiologists","Radiologists","Same"],["Type of\nmammograms","FFDM and DBT screening\nmammograms.","FFDM screening mammograms.","Both devices operate\non screening\nmammograms (x-ray\nimages), but\ncmTriage is intended\nfor FFDM cases only\nwhereas Saige-Q is\nintended for both\nFFDM and DBT\ncases."],["Deployment","On-premise","On-premise with cloud\nprocessing","Different, but does\nnot raise any new\nquestions regarding\nsafety and\neffectiveness."],["Output device","The end user interacts with","The end user interacts with the","There is no"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203517-p8-t0","doc_id":"K203517","page_num":8,"bbox":[72.25,72.73,545.53,155.05],"n_rows":2,"n_cols":4,"columns":["","the output of the device in the\nfacility’s PACS/EPR/RIS\nsoftware (worklist).","output of the device in the\nfacility’s PACS software\n(worklist).","significant difference."],"rows":[["","the output of the device in the\nfacility’s PACS/EPR/RIS\nsoftware (worklist).","output of the device in the\nfacility’s PACS software\n(worklist).","significant difference."],["Software levels\nof concern","Moderate","Moderate","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203555-p6-t0","doc_id":"K203555","page_num":6,"bbox":[102.36,403.56,518.88,711.84],"n_rows":7,"n_cols":3,"columns":["","AmCAD-UT","AmCAD-UT® Detection 2.2"],"rows":[["","AmCAD-UT","AmCAD-UT® Detection 2.2"],["Manufacturer","AmCad BioMed Corp.","AmCad BioMed Corp."],["510(k) Number","K203555","K180006"],["Regulation\nNumber","21 CFR 892.2050 - Class II","21 CFR 892.2050 - Class II"],["Regulation\nName","Medical Image Management\nand Processing System","Medical Image Management\nand Processing System"],["ProductCode","QIH","LLZ"],["Intended Use","AmCAD-UT is intended to\nassist the medical\nprofessionals in analyzing\nthyroid ultrasound images by\nquantification and visualization\nof sonographic characteristics\nof thyroid nodules.","AmCAD-UT® Detection 2.2 is\nintended to assist the medical\nprofessionals in analyzing\nthyroid ultrasound images of\nuser-selected regions of\ninterest (ROI). After the initial\nreview of the ultrasound\nimages by the physicians, the\ndevice further provides\ndetailed information with"]],"caption_candidate":"The comparison as described in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203555-p7-t0","doc_id":"K203555","page_num":7,"bbox":[102.36,79.56,518.88,710.76],"n_rows":4,"n_cols":3,"columns":["","AmCAD-UT","AmCAD-UT® Detection 2.2"],"rows":[["","AmCAD-UT","AmCAD-UT® Detection 2.2"],["","","quantification and visualization\nof sonographic characteristics\nof thyroid nodules."],["Indications for\nUse","AmCAD-UT is a\nWindows-based\ncomputer-aided detection\n(CADe) device intended to\nassist the medical\nprofessionals in analyzing\nthyroid ultrasound images,\nacquired from FDA-cleared\nultrasound systems. The\nregion of interest (ROI) of a\nuser-selected thyroid nodule is\ndefined by users or suggested\nby an AI contouring algorithm.\nAfter the initial review of the\nultrasound images by the\nphysicians, the device further\nprovides detailed information\nwith quantification and\nvisualization of sonographic\ncharacteristics of thyroid\nnodules. The device is\nintended for use on ultrasound\nimages of discrete thyroid\nnodules larger than 1cm, for\nwhich a biopsy\nrecommendation is required.","AmCAD-UT® Detection 2.2 is a\nWindows-based\ncomputer-aided detection\n(CADe) device intended to\nassist the medical\nprofessionals in analyzing\nthyroid ultrasound images,\nacquired from FDA-cleared\nultrasound systems, with\nuser-selected regions of\ninterest (ROI). After the initial\nreview of the ultrasound\nimages by the physicians, the\ndevice further provides\ndetailed information with\nquantification and visualization\nof sonographic characteristics\nof thyroid nodules. The device\nis intended for use on\nultrasound images of discrete\nthyroid noduleslarger than\n1cm, for which a biopsy\nrecommendation is required."],["Functional\nCapability of\nImage\nProcessing","AmCAD-UT analyzes the\nuser-defined or AI-suggested\nregions of interest (ROI) of a\nuser-selected thyroid nodule\nfor detection and\nquantification of sonographic\ncharacteristics (hyperechoic","AmCAD-UT® Detection 2.2\nanalyzes the user-selected\nregions of interest (ROI) of\nthyroid ultrasound image for\nthe detection and\nquantification of sonographic\ncharacteristics (hyperechoic"]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-25140245","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203555-p8-t0","doc_id":"K203555","page_num":8,"bbox":[102.36,79.56,518.88,692.04],"n_rows":10,"n_cols":3,"columns":["","AmCAD-UT","AmCAD-UT® Detection 2.2"],"rows":[["","AmCAD-UT","AmCAD-UT® Detection 2.2"],["","foci, echogenicity, texture,\nmargin, orientation and\nanechoic areas). The device\nfurther provides detailed\ninformation with visualization\nof sonographic characteristics\nof thyroid nodules.","foci, echogenicity, texture,\nmargin, orientation and\nanechoic areas). The device\nfurther provides detailed\ninformation with visualization\nof sonographic characteristics\nof thyroid nodules."],["Reading\nParadigm","AmCAD-UT is to provide\nquantification and\nvisualization of sonographic\ncharacteristics after\nphysicians’ initial review of the\nimages.","AmCAD-UT® Detection 2.2 is\nto provide quantification and\nvisualization of sonographic\ncharacteristics after\nphysicians’ initial review of the\nimages."],["Output\nGenerated by\nthe CAD Device","The image can be annotated\nwith the detected sonographic\ncharacteristics and be\nrecorded by the device. The\nsoftware also automatically\ngenerates reports given the\nuser preference inputs in the\nanalysis process.","The image can be annotated\nwith the detected sonographic\ncharacteristics and be\nrecorded by the device. The\nsoftware also automatically\ngenerates reports given the\nuser preference inputs in the\nanalysis process."],["Type of Film to\nbe Processed\nby the CAD\nDevice","Digital ultrasound image","Digital ultrasound image"],["Software\nDesign","Based on AI, Statistical Pattern\nRecognition and Quantification\nmethod","Based on Statistical Pattern\nRecognition and Quantification\nmethod"],["Ground Truth\nEstablishment","The ground truth to be\nestablished for performance\nstudies of the device is the ROI\nlabeled by a panel of\nspecialists.","The ground truth to be\nestablished for performance\nstudies of the device includes\nthe ROI, the presence of each\nsonographic characteristic, and\nthe surgical pathology\nexamination result."],["Platform","Window-based","Window-based"],["Operating\nSystem","Standard PCor review station","Standard PC or review station"],["Clinical\nApplication","Thyroid cancers","Thyroid cancers"]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-25140245","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203555-p9-t0","doc_id":"K203555","page_num":9,"bbox":[102.36,79.56,518.88,320.04],"n_rows":7,"n_cols":3,"columns":["","AmCAD-UT","AmCAD-UT® Detection 2.2"],"rows":[["","AmCAD-UT","AmCAD-UT® Detection 2.2"],["Image Type","Ultrasound Image","Ultrasound Image"],["Image Format","DICOM3.0, Bitmap, JPEG","DICOM3.0, Bitmap, JPEG"],["ROI\nQuantification","Yes","Yes"],["Automatically\nGenerating\nReport","Yes","Yes"],["Report Storage","Paper printers, Local disk","Paper printers, Local disk"],["Performance\nTesting Data to\nSupport SE\nDetermination","Results from standalone\nperformance testing of the AI\nsuggested ROI’s of\nuser-selected nodules","Results from standalone\nperformance testing and\nclinical performance testing\n(MRMC study)"]],"caption_candidate":"Tel: +886-2-27136227 Fax: +886-2-25140245","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203578-p5-t0","doc_id":"K203578","page_num":5,"bbox":[72.08,347.72,553.44,717.1],"n_rows":13,"n_cols":6,"columns":["Characteristic","","Perimeter OTIS™ 2.1","","","Perimeter OTIS™ 2.0\n[Predicate Device]"],"rows":[["Characteristic","","Perimeter OTIS™ 2.1","","","Perimeter OTIS™ 2.0\n[Predicate Device]"],["","","[Subject Device]","","",""],["Intended Use","Imaging tool in the evaluation of human\ntissue microstructure by providing two-\ndimensional, cross-sectional, real-time depth\nvisualization.","","","Same",""],["Indications for Use","The OTIS 2.1 Optical Coherence Tomography\nSystem is indicated for use as an imaging\ntool in the evaluation of excised human tissue\nmicrostructure, by providing two-\ndimensional, cross-sectional, real-time depth\nvisualization, with image review manipulation\nsoftware for identifying and annotating\nregions of interest.","","","Same",""],["Measurement Technique","Optical Coherence Tomography","","","Same",""],["Center Wavelength","1325 ± 15 μm","","","Same",""],["Optical Source","Super Luminescent Diode","","","Same",""],["Optical Radiation Safety","Safe for Indicated Use\nClass 1 Laser","","","Same",""],["Lateral Resolution","20 μm","","","Same",""],["Lateral Range","870 mm","","","Same",""],["Axial Resolution","10 – 15 μm in tissue","","","Same",""],["Scan Acquisition Time","< 1 minute\n[5 x 5 cm area]","","","Same",""],["Input Devices","Touchscreen","","","Same",""]],"caption_candidate":"6. Predicate Device Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203578-p6-t0","doc_id":"K203578","page_num":6,"bbox":[72.31,72.38,553.85,144.02],"n_rows":3,"n_cols":7,"columns":["Characteristic","","Perimeter OTIS™ 2.1","","","Perimeter OTIS™ 2.0",""],"rows":[["Characteristic","","Perimeter OTIS™ 2.1","","","Perimeter OTIS™ 2.0",""],["","","[Subject Device]","","","[Predicate Device]",""],["Electrical Voltage\nFrequency","108 – 132 V, 60 Hz\n[North American Use]","","","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p7-t0","doc_id":"K203582","page_num":7,"bbox":[78.28,432.03,540.36,709.93],"n_rows":15,"n_cols":3,"columns":["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],"rows":[["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],["","",""],["REGULATORY DATA","",""],["","",""],["Regulatory Class","II","II"],["Regulation name","Picture archiving and\ncommunications\nsystem (PACS)","Picture archiving and\ncommunications system (PACS)"],["Regulation number","21 CFR 892.2050","21 CFR 892.2050"],["Classification Panel","Radiology","Radiology"],["Product code","LLZ","LLZ"],["Manufacturer","QUIBIM","Olea Medical"],["FDA clearance","-","K152602"],["","",""],["INTENDED USE","",""],["","",""],["Indications for use","qp-Prostate is an image processing\nsoftware package to be used by\ntrained professionals, including","Olea Sphere V3.0 is an image\nprocessing software package to\nbe used by trained professionals"]],"caption_candidate":"device (OLEA Sphere 3.0, OLEA Medical)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p8-t0","doc_id":"K203582","page_num":8,"bbox":[78.16,72.47,540.32,705.9],"n_rows":22,"n_cols":3,"columns":["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],"rows":[["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],["","radiologists specialized in prostate\nimaging, urologists and oncologists.\nThe software runs on a standard\n\"off-the-shelf\" workstation and can\nbe used to perform image viewing,\nprocessing and analysis of prostate\nMR images. Data and images are\nacquired through DICOM compliant\nimaging devices and modalities.\nPatient management decisions\nshould not be based solely on the\nresults of qp-Prostate. qp-Prostate\ndoes not perform a diagnostic\nfunction, but instead allows the\nusers to visualize and analyze\nDICOM data.","including, but not limited to,\nphysicians and medical\ntechnicians. The software runs on\na standard \"off-the-shelf\"\nworkstation and can be used to\nperform image viewing,\nprocessing, image collage and\nanalysis of medical images. Data\nand images are acquired through\nDICOM compliant imaging\ndevices and modalities."],["","",""],["CHARACTERISTICS","",""],["","",""],["Supported image\nformat","DICOM 3.0","DICOM 3.0"],["Type of scans","MR","MR, CT"],["Data import","PACS","PACS or file system"],["Data export","PACS","PACS or file system"],["Image loading and\nsaving","Yes","Yes"],["Integrated slice viewer","Yes","Yes"],["Multi-planar","Yes","Yes"],["MPR/3D","Yes","Yes"],["Segmentation tools","Yes","Yes"],["ROI tools","Yes","Yes"],["Image Processing","Yes","Yes"],["Study Management\ntools","Yes","Yes"],["Structured report\ngeneration","Yes","Yes"],["License Management\nSystem","Yes","Yes"],["Unique user log-in and\npassword","Yes","Yes"],["User audit trails","Yes","Yes"],["Modular analysis plug-\nins","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p9-t0","doc_id":"K203582","page_num":9,"bbox":[78.1,72.47,540.3,586.6],"n_rows":10,"n_cols":3,"columns":["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],"rows":[["FEATURE","qp-Prostate","Olea Sphere V3.0\nK152602"],["Intended use\nenvironment","Hospitals / imaging centers or\nclinics","Hospitals / imaging centers or\nclinics"],["Intended user","Radiologists specialized in\nprostate imaging, urologists and\noncologists.","Trained professionals including\nbut not limited to\nphysicians and medical\ntechnicians"],["Intended patient\npopulation","Any patient for which PACS MR\nprostate data exists.","Any patient for which PACS data\nexists."],["Image post-processing\nand analysis plugins","Not included","DCE (for MR Imaging) Kinetics –\nsemi quantitative maps\n(AUC, Peak enhancement map,\nPeak percentage enhancement,\nTime to maximum enhancement,\nWashin, Washout, Relative\nwashout,\nSignal Enhancement Ratio)"],["","DCE (for prostate MR\nimaging) Perfusion –\nPharmacokinetics\nModelling\n(Ktrans [min-1], kep [min-1], ve [%])","DCE (for MR imaging) Permeability\n– Quantitative parameter maps\n(Ktrans, kep, Vp, ve, signal to\nconcentration time curve\nconversion with fixed blood\nand tissue T1 values)"],["","Not included","DWI (for MR Imaging) Intra – Voxel\nIncoherent Motion IVIM\n(ADC, D, D*, f)"],["","DWI (for MR Imaging) Apparent\nDiffusion\nCoefficient (ADC [mm2/s])","DWI (for MR Imaging) Apparent\nDiffusion Coefficient\n(ADC)"],["","Not included","Yes (T1 and T2 Mapping)"],["","Not included","Metabolic (hepatic fat fraction FF)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p10-t0","doc_id":"K203582","page_num":10,"bbox":[143.96,215.98,468.14,363.97],"n_rows":4,"n_cols":5,"columns":["","qp-Prostate","","Test type","Dataset"],"rows":[["","qp-Prostate","","Test type","Dataset"],["","functionality","","",""],["Diffusion – ADC\nanalysis module","","","Digital Reference\nObject Analysis\n(Diffusion – ADC)","QIBA’s Diffusion\nWeighted Imaging\n(DWI) Digital\nReference Object\n(DRO)"],["Perfusion -\nPharmacokinetics\nanalysis module","","","Digital Reference\nObject Analysis\n(Perfusion –\nPharmacokinetics)","QIBA’s Dynamic\nContrast-Enhanced\n(DCE) MR perfusion\nDRO"]],"caption_candidate":"Modules","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p10-t1","doc_id":"K203582","page_num":10,"bbox":[121.52,585.15,490.57,719.53],"n_rows":4,"n_cols":5,"columns":["","qp-Prostate","","Test type","Dataset"],"rows":[["","qp-Prostate","","Test type","Dataset"],["","functionality","","",""],["Motion Correction\nalgorithm","","","Performance\ntesting with\nprostate MR\ncases","155 DCE-MR and DWI-MR\nprostate sequences acquired form\n155 different patients in different\nmachines with multiple acquisition\nprotocols"],["Registration algorithm","","","Performance\ntesting with","112 T2-Weighted MR, DCE-MR\nand 108 DWI-MR prostate\nsequences acquired from different"]],"caption_candidate":"Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203582-p11-t0","doc_id":"K203582","page_num":11,"bbox":[121.35,72.47,490.63,367.18],"n_rows":5,"n_cols":3,"columns":["","prostate MR\ncases","patients in different machines with\nmultiple acquisition parameters"],"rows":[["","prostate MR\ncases","patients in different machines with\nmultiple acquisition parameters"],["Spatial Smoothing\nalgorithm","Performance\ntesting with\nprostate MR\ncases","51 transverse T2-weighted, DCE-\nMR and DWI-MR prostate\nsequences acquired from 51\ndifferent patients in different\nmachines with multiple acquisition\nprotocols"],["AIF selection\nalgorithm","Performance\ntesting with\nprostate MR\ncases","242 DCE-MR prostate sequences\nacquired from 242 different\npatients in different machines with\nmultiple acquisition protocols"],["Prostate\nSegmentation\nalgorithm","Performance\ntesting with\nprostate MR\ncases","243 transverse T2-weighted MR\nprostate sequences acquired from\n243 different patients in different\nmachines with multiple acquisition\nprotocols."],["Comparison to the\nPredicate Device\n(OLEA Sphere, v3.0,\nK152602)","Comparison to\npredicate\ndevice","157 T2-weighted MR, DCE-MR\nand 141 DWI-MR prostate\nsequences acquired form different\npatients in different machines with\nmultiple acquisition protocols"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203617-p6-t0","doc_id":"K203617","page_num":6,"bbox":[72.02,104.94,580.54,353.71],"n_rows":10,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","Wide View (K023332)","","","MaxFOV 2",""],["Patient Population","Patients of all ages","","","Same","",""],["Intended users","Dosimetrist\nMedical Physicists\nRadiation Oncologists","","","Same","",""],["Clinical Use","Routine Clinical Use","","","Same","",""],["Targeted clinical condition,\nanatomy","Part of scanned object is located out of\nthe scan field of view.","","","Same","",""],["Compatible Scan modes","Compatible with Axial, Helical, and Cine\nscan modes.","","","Same","",""],["Technology/Principles","Analytical model – classic algorithm where\nthe measured sinogram is expanded to\ncover a FOV larger than SFOV.","","","MaxFOV 2 uses a CNN which is trained on\nmultiple CT scanners. MaxFOV 2’s\nreconstruction process (algorithm) contains\na Deep Learning based component.","",""],["Extended Field of View Spec","Allows visualization of up to 65cm","","","","Allows visualization of up to 80cm, same as",""],["","","","","","reference device",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203744-p6-t0","doc_id":"K203744","page_num":6,"bbox":[67.0,249.25,534.17,409.5],"n_rows":4,"n_cols":2,"columns":["Company Name","Arterys Inc."],"rows":[["Company Name","Arterys Inc."],["Company Address","2100 Fillmore Street #100, San\nFrancisco, CA 94115, U.S.A"],["Contact Person","John Axerio-Cilies\nCEO and CTO"],["Contact Information","Email: regulatory@arterys.com\nPhone: 1 (650) 391-7111"]],"caption_candidate":"Submitter Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203744-p6-t1","doc_id":"K203744","page_num":6,"bbox":[67.0,443.37,534.17,600.63],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Arterys®MICA"],"rows":[["Proprietary Name","Arterys®MICA"],["Common Name","Medical image processing software"],["Model Number","AMM7"],["Regulation Number","21 CFR 892.2050 Medical image management and processing system"],["Product Code","QIH/LLZ"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203783-p4-t0","doc_id":"K203783","page_num":4,"bbox":[71.06,412.99,425.38,614.98],"n_rows":9,"n_cols":2,"columns":["Device Classification\nName","System, Image processing, Radiological\n(Predicate device)"],"rows":[["Device Classification\nName","System, Image processing, Radiological\n(Predicate device)"],["510(k) Number","K103480"],["Device Name","THORACIC VCAR"],["Applicant","GE MEDICAL SYSTEMS, LLC\n3000 N GRANDVIEW\nWaukesha, WI 53188, USA"],["Regulation Number","892.2050"],["Classification Product\nCode","LLZ"],["Date Received","11/26/2010"],["Decision Date","03/07/2011"],["510k Review Panel","Radiology"]],"caption_candidate":"The following table shows the predicate devices of the proposed ClariPulmo:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203783-p5-t0","doc_id":"K203783","page_num":5,"bbox":[71.06,72.24,457.9,453.55],"n_rows":10,"n_cols":4,"columns":["Device\nClassification\nName","System, X-Ray,\nTomography,\nComputed\n(Reference\nDevice)","System, X-Ray,\nTomography,\nComputed\n(Reference\nDevice)","System, Image\nprocessing,\nRadiological\n(Reference\nDevice)"],"rows":[["Device\nClassification\nName","System, X-Ray,\nTomography,\nComputed\n(Reference\nDevice)","System, X-Ray,\nTomography,\nComputed\n(Reference\nDevice)","System, Image\nprocessing,\nRadiological\n(Reference\nDevice)"],["510(k) Number","K141069","K200990","K183460"],["Device Name","Imbio CT Lung\nDensity Analysis\nSoftware","VIDA|vision\n(formerly VIDA\nPulmonary\nWorkstation 2\n(PW2))","ClariCT.AI"],["Applicant","IMBIO LLC\n227 COLFAX AVE\nNSUITE 144\nMinneapolis, MN 5\n5405 USA","VIDA Diagnostics,\nInc. 500 Crosspark\nRd. W250\nBioVentures Center\nCoralville, IA 52241\nUSA","ClariPi Inc.\n3F, 70-15,\nIhwajang-gil,\nJongno-gu, Seoul,\nRepublic of Korea\n[03088]"],["Regulation\nNumber","892.1750","892.1750","892.2050"],["Classification\nProduct Code","JAK","JAK","LLZ"],["Date Received","04/24/2014","04/15/2020","12/13/2018"],["Decision Date","09/17/2014","08/07/2020","06/13/2019"],["Decision","Substantially\nEquivalent (SE)","Substantially\nEquivalent (SE)","Substantially\nEquivalent (SE)"],["Regulation\nMedical\nSpecialty","Radiology","Radiology","Radiology"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203783-p6-t0","doc_id":"K203783","page_num":6,"bbox":[97.94,458.95,559.8,725.62],"n_rows":2,"n_cols":2,"columns":["Subject Device (K203783)","Predicate Device (103480)"],"rows":[["Subject Device (K203783)","Predicate Device (103480)"],["ClariPulmo is a non-invasive image analysis\nsoftware for use with CT images which is\nintended to support the quantification of lung CT\nimages. The software is designed to support the\nphysician in the diagnosis and documentation of\npulmonary tissue images (e.g., abnormalities)\nfrom the CT thoracic datasets. (The software is\nnot intended for the diagnosis of pneumonia or\nCOVID-19). The software provides automated\nsegmentation of the lungs and quantification of\nlow-attenuation and high-attenuation areas\nwithin the segmented lungs by using predefined\nHounsfield unit thresholds. The software\ndisplays by color the segmented lungs and\nanalysis results. ClariPulmo provides optional\ndenoising and kernel normalization functions for\nimproved quantification of lung CT images in\ncases when CT images were taken at low-dose\nconditions or with sharp reconstruction kernels.","Thoracic VCAR is a CT, non-invasive\nimage analysis software package,\nwhich may be used in conjunction with\nCT lung images to aid in the\nassessment of thoracic disease\ndiagnosis and management. The\nsoftware will provide automatic\nsegmentation of the lungs and\nautomatic segmentation and tracking of\nthe airway tree. The software will\nprovide quantification of Hounsfield\nunits and display by color the\nthresholds within a segmented region."]],"caption_candidate":"at low-dose conditions or with sharp reconstruction kernels.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203783-p7-t0","doc_id":"K203783","page_num":7,"bbox":[97.96,172.46,560.14,726.58],"n_rows":15,"n_cols":8,"columns":["Feature","ClariPulmo\n(Subject\nDevice)","Thoracic\nVCAR\nK103480\n(Predicate\nDevice)","Imbio CT\nLung Density\nAnalysis\nSoftware\nK141069\n(Reference\nDevice)","","VIDA|vision","","ClariCT.AI\nK183460\n(Reference\nDevice)"],"rows":[["Feature","ClariPulmo\n(Subject\nDevice)","Thoracic\nVCAR\nK103480\n(Predicate\nDevice)","Imbio CT\nLung Density\nAnalysis\nSoftware\nK141069\n(Reference\nDevice)","","VIDA|vision","","ClariCT.AI\nK183460\n(Reference\nDevice)"],["","","","","","(formerly VIDA","",""],["","","","","","Pulmonary","",""],["","","","","","Workstation 2","",""],["","","","","","(PW2))","",""],["","","","","","K200990","",""],["","","","","","(Reference","",""],["","","","","","Device)","",""],["Algorithm","Deep\nlearning","unknown","Image post-\nprocessing\nalgorithm","Self-contained\nimage\nanalysis","","","Deep\nlearning"],["Modality","CT","CT","CT","CT","","","CT"],["Type of scan","Thoracic\nCT","Thoracic\nCT","Thoracic CT","Thoracic CT","","","Head,\nheart, chest\nand\nabdomen\nCT"],["DICOM standard","Yes","Yes","Yes","Yes","","","Yes"],["Automatic segmentation\nof both the left and right\nlungs and airways","Yes","Yes","Yes","Yes","","","Not relevant"],["Lung volume analysis\nsupport: Both, Left, and\nRight Lungs","Yes","Yes","Yes","Yes","","","Not relevant"],["Low attenuation analysis","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange,\nvolume\nmeasurem\nent, lung\ndensity\nindex and\nPerc15\nmeasurem\nent","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange,\nvolume\nmeasurem\nent","Yes\nLung density\nresult\nquantification\nwith HU\ndensity\nrange,\nvolume\nmeasurement\n, lung density\nindex and\nPercX (where\n”X”\ncorresponds\nto the desired\npercentile)\ncalculated in\nthe\nInspiration\nAssessment\nonly.","Yes\nLung density\nresult\nquantification\nwith HU\ndensity range,\nvolume\nmeasurement,\nlung density\nindex and\nPerc15\nmeasurement","","","Not relevant"]],"caption_candidate":"VII. SUBSTANTIAL EQUIVALENCE TABLE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203783-p8-t0","doc_id":"K203783","page_num":8,"bbox":[97.94,72.24,560.16,457.27],"n_rows":6,"n_cols":6,"columns":["High attenuation analysis","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange and\nvolume\nmeasurem\nent based\non selected\nHU ranges\nset by user","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange and\nvolume\nmeasurem\nent based\non selected\nHU ranges\nset by user","Not\nsupported","unknown","Not relevant"],"rows":[["High attenuation analysis","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange and\nvolume\nmeasurem\nent based\non selected\nHU ranges\nset by user","Yes\nLung\ndensity\nresult\nquantificati\non with HU\ndensity\nrange and\nvolume\nmeasurem\nent based\non selected\nHU ranges\nset by user","Not\nsupported","unknown","Not relevant"],["Adjustable density\nthresholds for refining\nand optimizing HU range","Yes","Yes","Not\nsupported","Yes","Not relevant"],["Viewer displays lung\ndensity in color\naccording to Hounsfield\nUnit (HU) range.","Yes","Yes","Yes","Yes","Not relevant"],["Viewer displays density\ngraph/histogram of the\nclassified lung voxels’\nrelative frequencies","Yes","Unknown","Yes","Yes","Not relevant"],["Report includes overlay\nof density quantification\nresults and density graph\nhistogram","Yes","Unknown","Yes","Yes","Not relevant"],["Low-dose CT support","Yes","Not\nsupported","Yes","Yes","Yes"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203785-p4-t0","doc_id":"K203785","page_num":4,"bbox":[127.77,395.61,521.71,604.89],"n_rows":9,"n_cols":2,"columns":["Device Classification Name","System, Image processing, Radiological"],"rows":[["Device Classification Name","System, Image processing, Radiological"],["510(k) Number","K170540"],["Device Name","DM-Density"],["Applicant","Densitas, Inc.\n1344 Summer Street, Suite 311.2\nHalifax, CA B3h 0A8"],["Regulation Number","892.2050"],["Classification Product Code","LLZ"],["Date Received","02/13/2017"],["Decision Date","02/23/2018"],["510k Review Panel","Radiology"]],"caption_candidate":"substantially equivalent to the following commercially available software:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203785-p6-t0","doc_id":"K203785","page_num":6,"bbox":[126.34,231.9,521.69,731.64],"n_rows":9,"n_cols":4,"columns":["","Subject Device –","Predicate Device-","Reference Device -"],"rows":[["","Subject Device –","Predicate Device-","Reference Device -"],["Item","","DM-Density","M-Vu Breast Density"],["","ClariSIGMAM","",""],["","","(K170540)","(K132742)"],["","","",""],["Intended\nUse /\nIndication\nfor Use","ClariSIGMAM is a\nsoftware application\nintended for use with\ncompatible full field\ndigital mammography\nsystems.\nClariSIGMAM\ncalculates percent\nbreast density defined\nas the ratio of\nfibroglandular tissue to\ntotal breast area\nestimates and\nprovides breast\ndensity group\ninformation (BI-RADS\nA+B as fatty and BI-\nRADS C+D as dense)\nto aid radiologists in\nthe assessment of\nbreast tissue\ncomposition.\nClariSIGMAM\nproduces adjunctive\ninformation. It is not a\ndiagnostic aid.","DM-Density is a\nsoftware application\nintended for use with\ncompatible full field\ndigital mammography\nsystems. DM-Density\ncalculates percent\nbreast density defined\nas the ratio of\nfibroglandular tissue to\ntotal breast area\nestimates. DM-Density\nprovides these\nnumerical values for\neach breast as well as\na density category to\naid interpreting\nphysicians in the\nassessment of breast\ntissue composition.\nDM-Density produces\nadjunctive information.\nIt is not a diagnostic\naid.","M-Vu Breast Density is\na software application\nintended for use with\ndigital mammography\nsystems. M-Vu Breast\nDensity calculates\nbreast density as a\nratio of fibroglandular\ntissue and total breast\narea estimates. M-Vu\nBreast Density\nprovides these\nnumerical values for\neach breast as well as\na density category to\naid radiologists in the\nassessment of breast\ntissue composition. M-\nVu Breast Density\nproduces adjunctive\ninformation, It is not an\ninterpretive or\ndiagnostic aid."],["Intended\nUser","Interpreting\nPhysicians,\nRadiologists and\nSpecialists","Interpreting Physicians","Interpreting Physicians"],["Image\nSource\nModalities","GE Senograph 2000D\nGE Senograph DS\nGE Senographe\nPristina\nHologic Selenia\nDimensions\nHologic Lorad Selenia","Hologic Selenia\nDimensions\nHologic Lorad Selenia","All digital radiography\n(DR) systems and\ncomputed radiography\n(CR) systems"],["Image","DICOM digital","DICOM full field digital","DICOM digital"]],"caption_candidate":"The following information compares the predicate devices and the subject device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203785-p7-t0","doc_id":"K203785","page_num":7,"bbox":[126.36,93.9,521.66,367.8],"n_rows":7,"n_cols":4,"columns":["","Subject Device –","Predicate Device-","Reference Device -"],"rows":[["","Subject Device –","Predicate Device-","Reference Device -"],["Item","","DM-Density","M-Vu Breast Density"],["","ClariSIGMAM","",""],["","","(K170540)","(K132742)"],["","","",""],["Format","mammography imager\n– For Presentation;\nRCC, LCC, RMLO,\nLMLO","mammography imager\n– For Presentation;\nRCC, LCC, RMLO,\nLMLO","mammography imager\n– For Processing;\nRCC, LCC, RMLO,\nLMLO"],["Output\nData","For each breast:\n• Area of fibroglandular\ntissue (cm²)\n• Area of breast (cm²)\n• Area-based breast\ndensity (%)\nFor each patient:\n• Breast density group\ninformation for the\npatient (BI-RADS\nA+B as fatty and BI-\nRADS C+D as\ndense)","BI-RADS 4th Ed.\nFor each breast:\n• Area of fibroglandular\ntissue (cm²)\n• Area of breast (cm²)\n• Area-based breast\ndensity (%)\nFor each patient: DM-\nDensity breast density\ngrade and percent\nbreast density\nBI-RADS 5th Ed.\nFor each patient: DM-\nDensity breast density\ngrade","For each breast:\n• Area of fibroglandular\ntissue (cm²)\n• Area of breast (cm²)\n• Area-based breast\ndensity (%)\nFor each patient:\nVuCOMP density\ngrade/BIRADS breast\ndensity"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203785-p8-t0","doc_id":"K203785","page_num":8,"bbox":[132.6,262.92,526.02,328.08],"n_rows":5,"n_cols":5,"columns":["","","Readers’ consensus","","Accuracy"],"rows":[["","","Readers’ consensus","","Accuracy"],["","","Fatty","Dense",""],["ClariSIGMAM","Fatty","293","63","86.6%"],["","Dense","45","436","87.3%"],["","Total","338","499",""]],"caption_candidate":"n=837; Kappa 0.734 [0.688, 0.781]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203822-p6-t0","doc_id":"K203822","page_num":6,"bbox":[48.24,252.5,490.66,714.58],"n_rows":9,"n_cols":3,"columns":["","UNMODIFIED Device\nProFound™ AI V2.1","MODIFIED Device\nProFound™ AI V3.0"],"rows":[["","UNMODIFIED Device\nProFound™ AI V2.1","MODIFIED Device\nProFound™ AI V3.0"],["Manufacturer","iCAD, Inc.","iCAD, Inc."],["Classification Name","Radiological Computer Assisted\nDetection and Diagnosis Software","Radiological Computer Assisted\nDetection and Diagnosis Software"],["Regulation Number","21 CFR 892.2090","21 CFR 892.2090"],["Product Code","QDQ","QDQ"],["510(k) #","K191994","Pending"],["Intended Use / Indication for\nUse","ProFound™ AI V2.1 is a\ncomputer-assisted detection and\ndiagnosis (CAD) software device\nintended to be used concurrently\nby interpreting physicians while\nreading digital breast\ntomosynthesis (DBT) exams from\ncompatible DBT systems. The\nsystem detects soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in the 3D DBT\nslices. The detections and\nCertainty of Finding and Case\nScores assist interpreting\nphysicians in identifying soft\ntissue densities and calcifications\nthat may be confirmed or\ndismissed by the interpreting\nPhysician.","ProFound AI® V3.0 is a\ncomputer-assisted detection and\ndiagnosis (CAD) software device\nintended to be used concurrently\nby interpreting physicians while\nreading digital breast\ntomosynthesis (DBT) exams from\ncompatible DBT systems. The\nsystem detects soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in the 3D DBT\nslices. The detections and\nCertainty of Finding and Case\nScores assist interpreting\nphysicians in identifying soft\ntissue densities and calcifications\nthat may be confirmed or\ndismissed by the interpreting\nPhysician."],["End User","Radiologists","Radiologists"],["Patient Population","Symptomatic and asymptomatic\nwomen\nundergoing mammography.","Symptomatic and asymptomatic\nwomen\nundergoing mammography."]],"caption_candidate":"Comparison with Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K203822-p7-t0","doc_id":"K203822","page_num":7,"bbox":[48.24,72.24,490.66,501.07],"n_rows":6,"n_cols":3,"columns":["","UNMODIFIED Device\nProFound™ AI V2.1","MODIFIED Device\nProFound™ AI V3.0"],"rows":[["","UNMODIFIED Device\nProFound™ AI V2.1","MODIFIED Device\nProFound™ AI V3.0"],["Mode of Action","Image processing device intended\nto aid in the detection,\nlocalization, and characterization\nof soft tissue densities (masses,\narchitectural distortions\nand asymmetries) and\ncalcifications in the 3D DBT\nslices.","Image processing device intended\nto aid in the detection,\nlocalization, and characterization\nof soft tissue densities (masses,\narchitectural distortions\nand asymmetries) and\ncalcifications in the 3D DBT\nslices."],["Image Source Modalities","Digital breast tomosynthesis\nslices","Digital breast tomosynthesis\nslices"],["Output Device","Softcopy Workstation","Softcopy Workstation"],["Deployment","Standalone computer","Standalone computer"],["Supported Digital Breast\nTomosynthesis Systems","ProFound AI V2 Software:\n• Hologic Selenia\nDimensions/3Dimensions\n• GE Senographe Esssential\nwith SenoClaire\n• GE Senographe Pristina\nProFound AI V2.1 Software:\n• Siemens Inspiration both\nStandard and Empire\nReconstruction\n• Siemens Revelation both\nStandard and Empire\nReconstruction","Profound AI V3.0 Software:\n• Hologic Selenia\nDimensions/3Dimensions\n• GE Senographe Esssential\nwith SenoClaire\n• GE Senographe Pristina\nProFound AI V2.1 Software:\n• Siemens Inspiration both\nStandard and Empire\nReconstruction\n• Siemens Revelation both\nStandard and Empire\nReconstruction"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210071-p7-t0","doc_id":"K210071","page_num":7,"bbox":[72.26,72.36,539.74,700.08],"n_rows":6,"n_cols":7,"columns":["","","SIS System version 5.1.0","","","SIS Software version 3.6.0",""],"rows":[["","","SIS System version 5.1.0","","","SIS Software version 3.6.0",""],["","","(subject device)","","","(predicate device)",""],["Intended Use /\nIndications for Use","SIS System is an application\nintended for use in the\nviewing, presentation and\ndocumentation of medical\nimaging, including different\nmodules for image\nprocessing, image fusion,\nand intraoperative functional\nplanning where the 3D\noutput can be used with\nstereotactic image guided\nsurgery or other devices for\nfurther processing and\nvisualization. The device\ncan be used in conjunction\nwith other clinical methods\nas an aid in visualization of\nthe subthalamic nuclei\n(STN) and globus pallidus\nexterna and interna (GPe\nand GPi, respectively).\nTypical users of the SIS\nSystem are medical\nprofessionals, including but\nnot limited to surgeons,\nneurologists and\nradiologists.","","","SIS Software is an application\nintended for use in the\nviewing, presentation and\ndocumentation of medical\nimaging, including different\nmodules for image\nprocessing, image fusion, and\nintraoperative functional\nplanning where the 3D output\ncan be used with stereotactic\nimage guided surgery or\nother devices for further\nprocessing and visualization.\nThe device can be used in\nconjunction with other clinical\nmethods as an aid in\nvisualization of the\nsubthalamic nuclei (STN).\nTypical users of SIS Software\nare medical professionals,\nincluding but not limited to\nsurgeons, neurologists, and\nradiologists.","",""],["User Population","Medical professionals,\nincluding but not limited to\nsurgeons, neurologists and\nradiologists.","","","Medical professionals,\nincluding but not limited to\nsurgeons, neurologists, and\nradiologists.","",""],["Allows for importing of\ndigital imaging sets","Yes","","","Yes","",""],["Uses proprietary\nsoftware algorithm to\ngenerate 3D segmented\nanatomical models from\npatient’s MR scans","Yes","","","Yes","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210071-p8-t0","doc_id":"K210071","page_num":8,"bbox":[72.25,72.36,539.75,618.84],"n_rows":11,"n_cols":7,"columns":["","","SIS System version 5.1.0","","","SIS Software version 3.6.0",""],"rows":[["","","SIS System version 5.1.0","","","SIS Software version 3.6.0",""],["","","(subject device)","","","(predicate device)",""],["Allows for review and\nanalysis of data in 2D\nand 3D formats","Yes","","","Yes","",""],["Performs image fusion\nof datasets using\nautomated or manual\nimage matching\ntechnique","Yes","","","Yes","",""],["Segments structures in\nimages with manual and\nautomated tools and\nconverts them into 3D\nobjects for display","Yes","","","Yes","",""],["Creates hybrid datasets\nby filing in segmented\nregions slice-by-slice\non anatomical datasets","Yes","","","Yes","",""],["Can be downloaded to\nplanning system","Yes","","","Yes","",""],["Segmentation of CT\nscan to identify\nstructures in relation to\nthose visualized on MR","Yes","","","Yes","",""],["Feature to Account for\nCT images with gantry\ntilt","Yes","","","Yes","",""],["Cross-registers images\nand creates 3D (fused)\nmodel","Yes","","","Yes","",""],["Uses registration\nmethods (linear and\nnon-linear) by multiple\nregistration tools (ANTS\nand ELASTIX)","Yes","","","Yes","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p4-t0","doc_id":"K210085","page_num":4,"bbox":[66.5,536.5,524.5,623.5],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","HealthCCS"],"rows":[["Proprietary Name","HealthCCS"],["Premarket Notification","K172983"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"The HealthCCSng device is substantially equivalent to the following Primary Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p4-t1","doc_id":"K210085","page_num":4,"bbox":[66.5,652.5,524.5,710.5],"n_rows":4,"n_cols":2,"columns":["Proprietary Name","AI-Rad Companion"],"rows":[["Proprietary Name","AI-Rad Companion"],["Premarket Notification","K183268"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR 892.1750"]],"caption_candidate":"Secondary Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p5-t0","doc_id":"K210085","page_num":5,"bbox":[66.5,81.5,524.5,110.5],"n_rows":2,"n_cols":2,"columns":["Product Code","JAK"],"rows":[["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p6-t0","doc_id":"K210085","page_num":6,"bbox":[66.62,166.3,534.25,283.5],"n_rows":4,"n_cols":2,"columns":["Estimated Coronary Calcium\nDetection","Corresponding Estimated Coronary Calcium\nDetection Category"],"rows":[["Estimated Coronary Calcium\nDetection","Corresponding Estimated Coronary Calcium\nDetection Category"],["0-99","Low"],["100-399","Medium"],[">400","High"]],"caption_candidate":"The software output will include the following calcium categories:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p8-t0","doc_id":"K210085","page_num":8,"bbox":[67.0,82.0,552.25,663.0],"n_rows":2,"n_cols":4,"columns":["","Proposed Device:\nHealthCCSng","Primary Predicate Device:\nHealthCCS Device v3.0\n(K172983)","Secondary Predicate Device:\nAI-Rad Companion (K183268)"],"rows":[["","Proposed Device:\nHealthCCSng","Primary Predicate Device:\nHealthCCS Device v3.0\n(K172983)","Secondary Predicate Device:\nAI-Rad Companion (K183268)"],["Intended\nUse/\nIndications\nfor Use","The HealthCCSng device\nis intended for use as a\nnon-invasive\npost-processing software to\nevaluate calcified plaques\nin the coronary arteries,\nwhich present a risk for\ncoronary artery disease.\nThe software generates an\nestimated coronary artery\ncalcium detection category.\nThe HealthCCSng device\nanalyzes existing\nnon-cardiac-gated CT\nstudies that include the\nheart of adult patients\nabove the age of 30. The\ndevice generates a\nthree-category output\nrepresenting the estimated\nquantity of calcium\ndetected together with\npreview axial images of the\ndetected calcium meant for\ninformational purposes\nonly. The device output\nwill be available to the\nradiologist as part of their\nstandard workflow. The\nHealthCCSng results are\nnot intended to be used on\na stand-alone basis for risk\nattribution, clinical\ndecision-making or\notherwise preclude clinical\nassessment of CT studies.","The HealthCCS Device is\nintended for use as a\nnon-invasive\npost-processing software\nthat can be used to evaluate\ncalcified plaques in the\ncoronary arteries, which\nmay be a risk factor for\ncoronary artery disease.\nThe software can be used to\ngenerate reports of the total\nrisk category of coronary\ncalcium. This information\ncan then be used by a\nphysician for further\nanalysis and treatment. The\nHealthCCS Device\nanalyzes pre-existing heart\nor chest\nECG-Gated/Triggered CT\nscans. The Device is\nindicated for use only on\npatients whose age at the\ntime, when the CT scan\nwas taken, was above 20\nyears old. This device\ngenerates a 4-category\nAgatston-equivalent risk\nscore, and the patient\nmanagement, especially for\nthe patient with the score\nfrom 0-10, will depend on\nthe physician’s own\njudgment. It may require\nfurther testing to evaluate\nthe appropriate clinical\nmanagement.","AI-Rad Companion\n(Cardiovascular) is image\nprocessing software that\nprovides quantitative and\nqualitative analysis from\npreviously acquired Computed\nTomography DICOM images to\nsupport radiologists and\nphysicians from emergency\nmedicine, specialty care, urgent\ncare, and general practice in the\nevaluation and assessment of\ncardiovascular diseases.\nIt provides the following\nfunctionality:\n• Segmentation and volume\nmeasurement of the heart\n• Quantification of the total\ncalcium volume in the coronary\narteries\n• Segmentation of the aorta\n• Measurement of maximum\ndiameters of the aorta at typical\nlandmarks\n•Threshold-based highlighting\nof enlarged diameters The\nsoftware has been validated for\nnon-cardiac chest CT data with\nfiltered backprojection\nreconstruction from Siemens\nHealthineers, GE Healthcare,\nPhilips, and Toshiba/Canon.\nAdditionally, the calcium\ndetection feature has been\nvalidated on non-cardiac chest\nCT data with iterative\nreconstruction from Siemens\nHealthineers.\nOnly DICOM images of adult\npatients are considered to be\nvalid input."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210085-p9-t0","doc_id":"K210085","page_num":9,"bbox":[71.25,82.8,513.61,740.85],"n_rows":49,"n_cols":5,"columns":["Comparison of Techn","ological Characteri","stics","",""],"rows":[["Comparison of Techn","ological Characteri","stics","",""],["","","","",""],["Technological","Proposed Device:","Primary Predicate","Secondary","Summary"],["Characteristics","HealthCCSng","Device:","Predicate Device:",""],["","Device v1.0","HealthCCS Device","AI-Rad Companion",""],["","","v3.0 (K172983)","(K183268)",""],["","","","",""],["Regulation","","","",""],["","","","",""],["Product Code","JAK","JAK","JAK","Same"],["","","","",""],["Regulation Number","21 CFR §892.1750","21 CFR §892.1750","21 CFR §892.1750","Same"],["","","","",""],["General","","","",""],["","","","",""],["Modality","CT","CT","CT","Same"],["","","","",""],["Image format","DICOM","DICOM","DICOM","Same"],["","","","",""],["Contrast","Non-contrast","Non-contrast","Non-contrast","Same"],["","","","",""],["Supported CT scan","Non-cardiac-gated","Cardiac-gated CT","Non-cardiac-gated","Different"],["","CT scan","scan","CT scan","supported"],["","","","","scans by t"],["","","","","subject de"],["","","","","and prima"],["","","","","predicate"],["","","","",""],["Slice thickness","Up to 3mm","Up to 3mm","Up to 3mm","Same"],["","","","",""],["Quantification","","","",""],["","","","",""],["Calcification","Automatic","Automatic","Automatic","Same"],["detection","","","",""],["","","","",""],["Default threshold of","130 HU","130 HU","130 HU","Same"],["calcium","(Hounsfield Units)","(Hounsfield Units)","(Hounsfield Units)",""],["","","","",""],["Coronary artery","CAC detection","Agatston","Calcium volume","Similar, p"],["calcification","category","equivalent CAC","","detected c"],["quantification method","","risk category,","","for assess"],["","","based on the","",""],["","","Agatston method","",""],["","","","",""],["Display and Visualizati","on","","",""],["","","","",""],["Main Image Quality","DICOM","DICOM","Not applicable","Same"],["","","","",""],["Zebra Medical Vision Ltd.","","","","5-6"]],"caption_candidate":"Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"text"}
{"table_id":"K210085-p10-t0","doc_id":"K210085","page_num":10,"bbox":[66.75,81.5,551.25,479.0],"n_rows":6,"n_cols":5,"columns":["Compressed preview\nimage","Yes","No","Not applicable","Does not\nintroduce\nquestions of\nsafety and\neffectiveness"],"rows":[["Compressed preview\nimage","Yes","No","Not applicable","Does not\nintroduce\nquestions of\nsafety and\neffectiveness"],["Annotation of\ndetected calcium","Yes","Yes","Not applicable","Same"],["Visualization tools","Zooming, panning,\nwindowing","Zooming, panning","Not applicable","Similar, does not\nintroduce\nquestions of\nsafety and\neffectiveness"],["Data reporting","","","",""],["Generate patient\nreport","Optional to copy\nresult to clipboard,\ninsert in report,\nDICOM Secondary\nCapture","Optional to copy\nresult to clipboard,\ninsert in report","Optional to insert\nresults in report","Similar, does not\nintroduce\nquestions of\nsafety and\neffectiveness"],["Report of the calcium\nscore","Yes, Coronary\nCalcium Detection\nCategory\n3 categories:\n0-99\n100-399\n>400","Yes, Coronary\nartery calcium risk\ncategory\n4 categories\n0-10\n11-100\n101-400\n>400","Not applicable","Both the subject\nand primary\npredicate device\nprovide calcium\ndetection and\ncategory"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p4-t0","doc_id":"K210209","page_num":4,"bbox":[108.24,553.32,539.76,584.88],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc.","Viz ICH","K193658"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p6-t0","doc_id":"K210209","page_num":6,"bbox":[108.0,387.72,540.0,711.72],"n_rows":16,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz ICH","Viz ICH"],["Application No.","K210209","K193658"],["Product Code","QAS","QAS"],["Regulation No.","21 C.F.R. § 892.2080","21 C.F.R. § 892.2080"],["Anatomical Region","Head","Head"],["Diagnostic\nApplication","Notification-only","Notification-only"],["Notification/\nPrioritization","Yes","Yes"],["Intended User","Neurovascular or Neurosurgical\nSpecialist","Neurovascular or Neurosurgical Specialist"],["DICOM Compatible","Yes","Yes"],["Data Acquisition","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities.","Acquires medical image data from DICOM\ncompliant imaging devices and modalities."],["Supported Imaging\nModality","Computed Tomography, non-\ncontrast (NCCT)","Computed Tomography, non-contrast\n(NCCT)"],["Alteration of Original\nImage","No","No"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-diagnostic\npurposes","Initial assessment; non-diagnostic\npurposes"],["View DICOM Data","DICOM Information about the\npatient, study and current image.","DICOM Information about the patient, study\nand current image."]],"caption_candidate":"predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p8-t0","doc_id":"K210209","page_num":8,"bbox":[108.0,151.08,539.93,206.28],"n_rows":4,"n_cols":3,"columns":["Device Performance by Clinical Site","",""],"rows":[["Device Performance by Clinical Site","",""],["Clinical Site","Sensitivity [95% CI]","Specificity [95% CI]"],["Site 001","0.94 [0.86, 0.98]","0.97 [0.89, 1.0]"],["Site 002","0.96 [0.91, 0.99]","0.95 [0.90, 0.98]"]],"caption_candidate":"Stratification of Device Performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p8-t1","doc_id":"K210209","page_num":8,"bbox":[108.0,222.0,539.93,290.88],"n_rows":5,"n_cols":3,"columns":["Device Performance by Age","",""],"rows":[["Device Performance by Age","",""],["Age Range (Years)","Sensitivity [95% CI]","Specificity [95% CI]"],["<50","1.0 [0.83, 1.0]","0.91 [0.71, 0.99]"],["50-70","0.93 [0.85, 0.97]","0.97 [0.91, 1.0]"],["70<","0.97 [0.90, 0.99]","0.96 [0.89, 0.99]"]],"caption_candidate":"Site 002 0.96 [0.91, 0.99] 0.95 [0.90, 0.98]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p8-t2","doc_id":"K210209","page_num":8,"bbox":[108.0,306.48,539.93,471.96],"n_rows":12,"n_cols":4,"columns":["Device Performance by Gender","","",""],"rows":[["Device Performance by Gender","","",""],["Gender (Years)","Sensitivity [95% CI]","","Specificity [95% CI]"],["Male","0.94 [0.88, 0.98]","","0.97 [0.90, 0.99]"],["Female","0.97 [0.91, 0.99]","","0.95 [0.89, 0.98]"],["Device Performance by ICH Subtype","","",""],["ICH Subtype","","Sensitivity [95% CI]",""],["Intraparenchymal Hemorrhage (IPH)","","0.96 [0.92, 0.99]",""],["Intraventricular Hemorrhage (IVH)","","1.0 [0.81, 1.0]",""],["Subarachnoid Hemorrhage (SAH)","","0.86 [0.64, 0.97]",""],["Subdural Hemorrhage (SDH)","","0.93 [0.66, 1.0]",""],["Extradural Hemorrhage (EDH)","","1.0 [0.16, 1.0]",""],["SDH or EDH","","0.94 [0.70, 1.0]",""]],"caption_candidate":"70< 0.97 [0.90, 0.99] 0.96 [0.89, 0.99]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p8-t3","doc_id":"K210209","page_num":8,"bbox":[108.0,487.56,539.93,542.76],"n_rows":4,"n_cols":3,"columns":["Device Performance by Slice Thickness","",""],"rows":[["Device Performance by Slice Thickness","",""],["Slice Thickness","Sensitivity [95% CI]","Specificity [95% CI]"],["2.5mm ≤ Slice Thickness < 3.5mm","0.94 [0.86, 0.98]","0.97 [0.89, 1.0]"],["3.5mm ≤ Slice Thickness ≤ 5.0mm","0.96 [0.91, 0.99]","0.95 [0.90, 0.98]"]],"caption_candidate":"SDH or EDH 0.94 [0.70, 1.0]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p8-t4","doc_id":"K210209","page_num":8,"bbox":[108.0,556.44,539.93,625.44],"n_rows":5,"n_cols":3,"columns":["Device Performance by Scanner Manufacturer","",""],"rows":[["Device Performance by Scanner Manufacturer","",""],["Manufacturer","Sensitivity [95% CI]","Specificity [95% CI]"],["General Electric","0.95 [0.89, 0.98]","0.97 [0.91, 0.99]"],["Siemens","0.93 [0.82, 0.98]","0.94 [0.84, 0.98]"],["Toshiba","1.0 [0.92, 1.0]","0.97 [0.82, 1.0]"]],"caption_candidate":"3.5mm ≤ Slice Thickness ≤ 5.0mm 0.96 [0.91, 0.99] 0.95 [0.90, 0.98]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p9-t0","doc_id":"K210209","page_num":9,"bbox":[108.0,122.64,539.84,288.12],"n_rows":12,"n_cols":4,"columns":["Device Performance by CT Scanner Make/Model","","",""],"rows":[["Device Performance by CT Scanner Make/Model","","",""],["Manufacturer","Model","Sensitivity [95% CI]","Specificity [95% CI]"],["GE Medical\nSystems","LightSpeed VCT","0.94 [0.85, 0.98]","0.97 [0.88, 1.0]"],["","Optima CT660","1.0 [0.66, 1.0]","1.0 [0.63, 1.0]"],["","Revolution EVO","1.0 [0.29, 1]","N/A"],["","Revolution HD","0.95 [0.75, 1.0]","0.95 [0.77, 1.0]"],["","BrightSpeed","1.0 [0.16, 1.0]","1.0 [0.72, 1.0]"],["Siemens","Sensation 64","0.80 [0.28, 0.99]","1.0 [0.03, 1.0]"],["","SOMATOM Definition AS+","1.0 [0.86, 1]","0.96 [0.82, 1.0]"],["","SOMATOM Perspective","0.88 [0.69, 0.97]","0.91 [0.76, 0.98]"],["Toshiba","Aquilion PRIME","1.0 [0.75, 1.0]","1.0 [0.79, 1.0]"],["","Aquilion","1.0 [0.88, 1.0]","0.92 [0.64, 1.0]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p9-t1","doc_id":"K210209","page_num":9,"bbox":[108.0,303.72,539.84,389.04],"n_rows":5,"n_cols":3,"columns":["Device Performance by ICH Volume","",""],"rows":[["Device Performance by ICH Volume","",""],["Minimal Volume\nThreshold (mL)","Sensitivity Above\nThreshold [95% CI]","Sensitivity Below/Equal\nThreshold [95% CI]"],["1","0.98 [0.94, 0.99]","0.69 [0.41, 0.89]"],["5","1.0 [0.98, 1.0]","0.78 [0.62, 0.89]"],["10","1.0 [0.97, 1.0]","0.88 [0.79, 0.95]"]],"caption_candidate":"Aquilion 1.0 [0.88, 1.0] 0.92 [0.64, 1.0]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210209-p9-t2","doc_id":"K210209","page_num":9,"bbox":[108.0,402.72,539.84,552.84],"n_rows":9,"n_cols":4,"columns":["Device Performance by Scanner Reconstruction Method","","",""],"rows":[["Device Performance by Scanner Reconstruction Method","","",""],["Manufact\nurer","Reconstruction\nMethod","Sensitivity","Specificity"],["GE\nMedical\nSystems","SS60","0.96 [0.82, 1.0]","0.97 [0.85, 1.0]"],["","STANDARD","0.94 [0.86, 0.98]","0.97 [0.89, 1.0]"],["Siemens","H40s","0.8 [0.28, 0.99]","1.0 [0.03, 1.0]"],["","J30s^3","0.88 [0.69, 0.97]","0.91 [0.76, 0.98]"],["","J45s^1","1.0 [0.85, 1.0]","0.96 [0.82, 1.0]"],["Toshiba","FC23","1.0 [0.75, 1.0]","1.0 [0.78, 1.0]"],["","FC62","1.0 [0.88, 1.0]","0.92 [0.62, 1.0]"]],"caption_candidate":"10 1.0 [0.97, 1.0] 0.88 [0.79, 0.95]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210237-p8-t0","doc_id":"K210237","page_num":8,"bbox":[72.27,263.13,539.73,410.52],"n_rows":7,"n_cols":11,"columns":["Time-to-\nNotification","MEAN ±\nSD\n(seconds)","MEDIAN\n(seconds)","","Lower","","","Upper","","MIN\n(seconds)","MAX\n(seconds)"],"rows":[["Time-to-\nNotification","MEAN ±\nSD\n(seconds)","MEDIAN\n(seconds)","","Lower","","","Upper","","MIN\n(seconds)","MAX\n(seconds)"],["","","","","Confidence","","","Confidence","","",""],["","","","","Limit","","","Limit","","",""],["","","","","(seconds)","","","(seconds)","","",""],["","","","","","","","","","",""],["CINA CHEST –\nPE\n(N = 396)","63 ± 16.1","60.8","61.5","","","64.6","","","36.6","122.7"],["CINA CHEST –\nAD\n(N = 298)","36.5 ± 9.1","34.1","35.4","","","37.5","","","17.8","90.5"]],"caption_candidate":"Table 1: Time-to-Notification for PE and AD Image Processing Applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210237-p9-t0","doc_id":"K210237","page_num":9,"bbox":[72.24,368.28,539.76,712.68],"n_rows":2,"n_cols":4,"columns":["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],"rows":[["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],["Intended Use\n/ Indications\nforUse","CINA CHEST is a\nradiological computer\naided triage and\nnotification software\nindicated for use in the\nanalysis of Chest and\nThoraco-abdominal CT\nangiography. The device\nis intended to assist\nhospital networks and\ntrained radiologists in\nworkflow triage by\nflagging and\ncommunicating\nsuspected positive\nfindings of (1) Chest CT\nangiographyfor\nPulmonary Embolism\n(PE) and (2) Chest or\nThoraco-abdominal CT","BriefCase is a\nradiological computer\naided triage and\nnotification software\nindicated for use in the\nanalysis of non-enhanced\nhead CT and CTPA\nimages.\nThe device is intended to\nassist hospital networks\nand trainedradiologists in\nworkflow triage by\nflagging and\ncommunication of\nsuspected positive\nfindings of Intracranial\nHemorrhage (ICH) and\nPulmonary Embolism\n(PE) pathologies. For the\nPE pathology, the","CINA is a radiological\ncomputer aided triage\nand notification software\nindicated for use in the\nanalysis of (1) non-\nenhanced head CT\nimages and (2) CT\nangiographies of the\nhead.\nThe device isintended to\nassist hospital networks\nand trained radiologists in\nworkflow triage by\nflagging and\ncommunicating\nsuspected positive\nfindings of (1) head CT\nimages for Intracranial\nHemorrhage (ICH) and\n(2)CT angiographies of"]],"caption_candidate":"BriefCase) and Reference Device (Avicenna.AI CINA)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210237-p11-t0","doc_id":"K210237","page_num":11,"bbox":[72.24,72.24,539.76,709.08],"n_rows":10,"n_cols":4,"columns":["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],"rows":[["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],["","full images per the\nstandard of care.","",""],["User\npopulation","Radiologist","Radiologist","Radiologist"],["Anatomical\nregion of\ninterest","Chest","Headand chest","Head"],["Data\nacquisition\nprotocol","Chest and Thoraco-\nabdominal CT\nangiography","Non contrast head CT\nscan and CTPA (single\nenergy exams only)","Non contrast CT scan of\nthe head or neck and CT\nangiogram images of the\nbrain"],["View DICOM\ndata","DICOM information\nabout the patient, study\nand current image","DICOM information about\nthe patient, study and\ncurrent image","DICOM information about\nthe patient, study and\ncurrent image"],["Segmentation\nof region of\ninterest","No; device does not\nmark, highlight, or direct\nusers’ attention to a\nspecific location in the\noriginal image","No; device does not\nmark, highlight, or direct\nusers’ attention to a\nspecific location in the\noriginal image","No; device does not\nmark, highlight, or direct\nusers’ attention to a\nspecific location in the\noriginal image"],["Algorithm","Artificial intelligence\nalgorithm with database\nof images","Artificial intelligence\nalgorithm with database\nof images","Artificial intelligence\nalgorithm"],["Notification /\nPrioritization","Yes","Yes","Yes"],["Preview\nimages","Presentation of a small,\ncompressed, black and\nwhite preview image that\nis labeled“not for\ndiagnostic use”;\nThe device operates in\nparallel with the standard\nof care, which remains\nthe default option for all","Presentation of a small,\ncompressed, black and\nwhite preview image that\nis labeled“not for\ndiagnostic use”;\nThe device operates in\nparallel with the standard\nof care, which remains\nthe default option for all","Presentation of a preview\nof the study for initial\nassessment not meant for\ndiagnostic purposes.\nThe device operates in\nparallel with the standard\nof care, which remains\nthe default option for all\ncases."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210237-p12-t0","doc_id":"K210237","page_num":12,"bbox":[72.24,72.24,539.76,436.44],"n_rows":5,"n_cols":4,"columns":["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],"rows":[["","Subject device: CINA\nCHESTSoftware","Predicate device: Aidoc\nBriefCase Software\n(K190072)","Reference device:\nAvicenna.AI CINA\nsoftware (K200855)"],["","cases.","cases.",""],["Alteration of\noriginal\nimage","No","No","No"],["Removal of\ncases from\nworklist\nqueue","No","No","No"],["Structure","-PEand ADimage\nprocessing applications\n-Compatibility of use\nwith the CINA Platform\nreference device\n(worklist and Image\nViewer)","-AHS module (image\nacquisition),\n-ACS module (image\nprocessing),\n-AidocWorklist\napplication for workflow\nintegration (worklist and\nnon-diagnostic basic\nImage Viewer).","-LVO and ICH image\nprocessing applications\n-CINA Platform (worklist\nandImage Viewer)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p6-t0","doc_id":"K210365","page_num":6,"bbox":[75.36,100.8,570.6,610.2],"n_rows":7,"n_cols":4,"columns":["Item","Candidate device:\nSecond Opinion®","Predicate Device:\nLogicon Caries\nDetection (P980025)","Comments"],"rows":[["Item","Candidate device:\nSecond Opinion®","Predicate Device:\nLogicon Caries\nDetection (P980025)","Comments"],["Manufacturer","Pearl Inc.","Carestream Dental LLC","N/A"],["Classification","892.2070","892.2070","Same"],["Product Code","MYN","MYN","Same (Product code MYN\nwas recently\nreclassified to class II)"],["Image Modality","Radiograph","Radiograph","Same"],["Intended Use","To aid in clinical detection of\npathologic and/or non-\npathologic dental features in\nradiographs\nof permanent teeth, as a\nsecond reader, only after the\ninitial read is completed","To aid in clinical\ndetection of pathologic\nfeatures in\nradiographs of adult teeth","Same indication as\npredicate device as both\ndevices are intended to\nidentify pathologic features\nin dental radiographs."],["Indications for\nUse","Second Opinion® is a\ncomputer aided detection\n(\"CADe”) software to\nidentify and mark regions in\nrelation to suspected dental\nfindings which include\nCaries, Discrepancy at the\nmargin of an existing\nrestoration, Calculus,\nPeriapical radiolucency,\nCrown (metal, including\nzirconia & non-metal),\nFilling (metal & non- metal),\nRoot canal, Bridge and\nImplants. It is designed to\naid dental health\nprofessionals to review\nbitewing and periapical\nradiographs of permanent\nteeth in patients 12 years of\nage or older as a second\nreader.","The Logicon Caries\nDetector is a software\ndevice that is an aid in the\ndiagnosis of caries that\nhave penetrated into the\ndentin, on un- restored\nproximal surfaces of\nsecondary dentition\nthrough the statistical\nanalysis of digital intraoral\nradiographic imagery. The\ndevice provides additional\ninformation for the\nclinician to use in his/her\ndiagnosis of a tooth\nsurface suspected of\nbeing carious. It is\ndesigned to work in\nconjunction with an\nexisting Carestream\nDental RVG digital x-ray\nradiographic system with\nCarestream Dental\nImaging Software\n(DIS/CSI) for WINDOWS\n7 or higher.",""]],"caption_candidate":"For substantial equivalence comparison, the follow table is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p7-t0","doc_id":"K210365","page_num":7,"bbox":[75.36,76.68,570.0,715.56],"n_rows":7,"n_cols":4,"columns":["Intended body part","Dental","Dental","Same as predicate device"],"rows":[["Intended body part","Dental","Dental","Same as predicate device"],["Intended User","Dental Clinicians","Dental Clinicians","Same as predicate\ndevice"],["Marker\nType/Size","Bounding boxes /\nFixed","User may mark ROI with V\ntool (to select a pie-wedge\nshape: narrow end at the\ncenter of the tooth, wide\nend extending through\nsurface over the\nsuspicious region)\nor the pencil tool to draw\nthe ROIs.",""],["Prescription\nor OTC","For Prescription Use","For Prescription Use","Same"],["Algorithm","Utilizes computer vision\nneural network algorithms,\ndeveloped from open-source\nmodels using supervised\nmachine learning\ntechniques.","Utilizes computer vision\nneural network algorithms\ndeveloped using proprietary\ntechniques.","Same"],["Reader\nworkflow","Second reader workflow","The user can select specific\nregions of interest (ROI) to\nbe analyzed by the\nprogram",""],["Clinical Study","Standalone study for\npathological (Caries,\ndiscrepancy at the\nmargin, calculus, and\nperiapical radiolucency)\nand non-pathologic\nfeature detection\nperformance (Crowns,\nfillings, root canal,\nbridges, and Implants).\n• Multiple-Reader,\nMultiple-Case\n(MRMC) study for\npathologic dental\nfeatures\n• Analysis included:\n• wAFROC-FOM\nanalysis for\nprimary endpoints\n• Determination of\nthe changes in\nsensitivity and\nchange in number\nof false positive","• MRMC study for two\ntypes of dental caries:\napproximal/enamel into\ndentin\n• Analysis included: ROC\nanalysis for primary\nendpoints","All devices included\nMRMC studies to assess\neffectiveness."]],"caption_candidate":"Pearl Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p8-t0","doc_id":"K210365","page_num":8,"bbox":[75.36,73.2,570.0,292.92],"n_rows":5,"n_cols":4,"columns":["","dental pathologies\nof a given type per\nimage (FPPI).","",""],"rows":[["","dental pathologies\nof a given type per\nimage (FPPI).","",""],["Image Source","Accepts image formats\nfrom RVG, DICOM,\nJPEG, TIFF,\nand PNG and\nconverts to JPEG.","Limited to\nCarestream\nproprietary\nradiography\nequipment.","Different"],["Type of\nDevice","CADe","CADe","Same"],["Hardware\nRequirements","WINDOWS 7 or higher","WINDOWS 7 or\nhigher","Same"],["Analysis of digital\nintraoral\nradiographic\nimagery","Bitewing & Periapical","Bitewing only","Similar"]],"caption_candidate":"Pearl Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p10-t0","doc_id":"K210365","page_num":10,"bbox":[143.16,197.4,469.68,303.96],"n_rows":5,"n_cols":5,"columns":["Feature","Caries","MD","Calculus","PR"],"rows":[["Feature","Caries","MD","Calculus","PR"],["# of normal radiographs","1,640","1,741","1,766","1,887"],["# of lesion-containing radiographs","370","269","244","123"],["Number of lesions","655","355","467","144"],["Average # of lesions/image","1.77","1.32","1.91","1.17"]],"caption_candidate":"and MRMC studies:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p12-t0","doc_id":"K210365","page_num":12,"bbox":[113.34,211.08,499.68,257.16],"n_rows":2,"n_cols":2,"columns":["Unaided Reader Accuracy","Aided Readers Accuracy"],"rows":[["Unaided Reader Accuracy","Aided Readers Accuracy"],["0.756","0.883"]],"caption_candidate":"determined using the ROC paradigm and showed an improvement of 12.8 percent:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210365-p12-t1","doc_id":"K210365","page_num":12,"bbox":[113.34,475.8,499.68,521.88],"n_rows":2,"n_cols":2,"columns":["Unaided Reader wAFROC-FOM","Aided Reader wAFROC-FOM"],"rows":[["Unaided Reader wAFROC-FOM","Aided Reader wAFROC-FOM"],["0.740","0.758"]],"caption_candidate":"aided readers with Second Opinion® is:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210404-p6-t0","doc_id":"K210404","page_num":6,"bbox":[71.13,104.3,524.26,226.94],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara® 1.7.0"],"rows":[["Device trade name","Transpara® 1.7.0"],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Submission type","Traditional 510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210404-p6-t1","doc_id":"K210404","page_num":6,"bbox":[71.13,308.33,524.26,446.47],"n_rows":8,"n_cols":2,"columns":["Device trade name","Transpara® 1.6.0"],"rows":[["Device trade name","Transpara® 1.6.0"],["Legal Manufacturer","ScreenPoint Medical B.V."],["Device","Radiological Computer Assisted Detection and\nDiagnosis Software"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Clearance number","K193229"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210404-p7-t0","doc_id":"K210404","page_num":7,"bbox":[88.82,165.08,541.17,227.54],"n_rows":4,"n_cols":2,"columns":["d) An exam score which categorizes exams on a scale of 1-10 with increasing",""],"rows":[["d) An exam score which categorizes exams on a scale of 1-10 with increasing",""],["","likelihood of cancer. The score is calibrated in such a way that approximately 10"],["","percent of mammograms in a population of mammograms without cancer falls in"],["","each category."]],"caption_candidate":"be utilized to enhance user interfaces and workflow.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210404-p8-t0","doc_id":"K210404","page_num":8,"bbox":[73.56,598.8,524.18,696.59],"n_rows":6,"n_cols":8,"columns":["Standard ID","","","Standard Title","","","FDA Recognition #",""],"rows":[["Standard ID","","","Standard Title","","","FDA Recognition #",""],["IEC 62366-1\nEdition 1.1 2020-\n06","","Medical devices - Part 1: Application of\nusability engineering to medical devices","Medical devices - Part 1: Application of","","5-129","5-129",""],["","","","usability engineering to medical devices","","","",""],["IEC 62366-1\nEdition 1.0 2015-\n02","","","Medical devices - Part 1: Application of","","5-114","",""],["","","","usability engineering to medical devices","","","",""],["","","","[Including CORRIGENDUM 1 (2016)]","","","",""]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210404-p9-t0","doc_id":"K210404","page_num":9,"bbox":[72.62,71.25,524.23,294.89],"n_rows":10,"n_cols":6,"columns":["ISO, 14155 Third\nedition 2020-07","","","Clinical investigation of medical devices","","2-282"],"rows":[["ISO, 14155 Third\nedition 2020-07","","","Clinical investigation of medical devices","","2-282"],["","","","for human subjects - Good clinical","",""],["","","","practice","",""],["ISO, 14155\nSecond edition\n2011-02-01,","","","Clinical investigation of medical devices","","2-205"],["","","","for human subjects - Good clinical","",""],["","","","practice","",""],["ISO 14971:2019","","Medical Devices - Application Of Risk\nManagement To Medical Devices","","","5-125"],["IEC 62304:2015","","Medical Device Software - Software Life\nCycle Processes","","","13-79"],["ISO, 15223-1\nThird Edition\n2016-11-01,","","Medical devices - Symbols to be used\nwith medical device labels labelling and\ninformation to be supplied - Part 1:\nGeneral requirements","","","5-117"],["DEN180005","","Decision summary with special controls\nfor class II radiology device","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210426-p6-t0","doc_id":"K210426","page_num":6,"bbox":[132.88,334.61,526.76,590.95],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012,\nC1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text)\nMedical electrical equipment - Part 1: General requirements for\nbasic safety and essential performance (IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2014(4th Edition) , Medical electrical equipment -\nPart 1-2: General requirements for basic safety and essential\nperformance - EMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment –\nPart 2-37: Particular requirements for the basic safety and essential\nperformance of ultrasonic medical diagnostic and monitoring\nequipment","",""],["ISO10993-1","","","ISO 10993-1:2009/(R)2013, Biological evaluation of medical\ndevices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2007, Medical devices - Application of risk management\nto medical devices","",""],["NEMA UD 2-\n2004","","","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound\nEquipment Revision 3","",""]],"caption_candidate":"FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p4-t0","doc_id":"K210458","page_num":4,"bbox":[71.64,93.0,566.01,697.2],"n_rows":14,"n_cols":4,"columns":["","510(k) Summary","",""],"rows":[["","510(k) Summary","",""],["","Per 21 CFR §807.92","",""],["510(k) Number","","K210458",""],["Date Prepared","","May 6, 2021",""],["Submitter\nName &\nAddress","","Abbott Medical\n4 Robbins Road\nWestford, MA, 01886",""],["Contact Person","","Steven Vitale\n(m)612-214-9102\nsteve.vitale@abbott.com",""],["Alternative\nContact Person","","Jose Marquez\n(m)978-846-2640\njose.marquez1@abbott.com",""],["Proprietary /\nTrade Name","","OPTIS™ Mobile Next Imaging System, OPTIS™ Integrated Next Imaging System\nwith Ultreon™ Software 1.0",""],["Common /\nUsual Name","","OPTIS Next",""],["Product\nClassification","","Product Code: NQQ",""],["Product\nRegulation\nNumber","","21 CFR 892.1560\n21 CFR 870.1425\n21 CFR 870.1110",""],["Device Class","","II",""],["Predicate\nDevice","","K192019: Dragonfly Opstar™ Imaging Catheter, AptiVue™ Software version E.5.1,\ncleared November 8, 2019",""],["Device\nDescription","","The OPTIS™ Next Imaging System is comprised of two devices providing the same set\nof features:\n• The OPTIS™ Mobile Next Imaging System is comprised of a cart-mounted\npersonal computer, imaging engine, and power supply that are placed inside an\nergonomically designed mobile cart. This system includes a keyboard, display\nmonitors, mouse, tableside controller, and a Drive-motor and Optical Controller\n(DOC).\n• The OPTIS™ Integrated Next is comprised of a PC, imaging engine, and power\nsupply that are housed in stationary cabinet which is located in the clinic/hospital\nequipment closet of a catheter lab. The tableside controller, DOC and DOC Holster\nare located in the procedure room, and the keyboard, display monitor, and mouse\nare located in the control room.",""]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p5-t0","doc_id":"K210458","page_num":5,"bbox":[71.6,72.4,566.0,701.2],"n_rows":2,"n_cols":2,"columns":["","With the Ultreon™ 1.0 software application, these systems perform Optical Coherence\nTomography (OCT) imaging of coronary arteries using compatible Dragonfly imaging\ncatheters. Resting Full-cycle Ratio (RFR), Fractional Flow Reserve (FFR), and Pd/Pa\nat rest physiological waveforms are also measured by the system to assess the severity\nof a coronary lesion by measuring the pressure drop across the lesion (distal vs\nproximal pressure). The physician may use the RFR or FFR parameter, along with\nknowledge of patient history, medical expertise, and clinical judgment to determine if\ntherapeutic intervention is indicated."],"rows":[["","With the Ultreon™ 1.0 software application, these systems perform Optical Coherence\nTomography (OCT) imaging of coronary arteries using compatible Dragonfly imaging\ncatheters. Resting Full-cycle Ratio (RFR), Fractional Flow Reserve (FFR), and Pd/Pa\nat rest physiological waveforms are also measured by the system to assess the severity\nof a coronary lesion by measuring the pressure drop across the lesion (distal vs\nproximal pressure). The physician may use the RFR or FFR parameter, along with\nknowledge of patient history, medical expertise, and clinical judgment to determine if\ntherapeutic intervention is indicated."],["Indications for\nUse / Intended\nUse","Indications for Use (Software)\nThe Ultreon™ 1.0 Software is intended to be used only with compatible OPTIS™ Next\nImaging Systems.\nThe OPTIS Next Imaging System with a compatible Dragonfly™ OPTIS™ Imaging\nCatheter or Dragonfly OpStar™ Imaging Catheter is intended for the imaging of\ncoronary arteries and is indicated in patients who are candidates for transluminal\ninterventional procedures. The Dragonfly OPTIS Imaging Catheter or Dragonfly\nOpStar Imaging Catheter is intended for use in vessels 2.0 to 3.5 mm in diameter. The\nDragonfly OPTIS Imaging Catheter or Dragonfly OpStar Imaging Catheter is not\nintended for use in the left main coronary artery or in a target vessel which has\nundergone a previous bypass procedure.\nThe OPTIS Next Imaging System is intended for use in the catheterization and related\ncardiovascular specialty laboratories and will further compute and display various\nphysiological parameters based on the output from one or more electrodes, transducers,\nor measuring devices. The physician may use the acquired physiological parameters,\nalong with knowledge of patient history, medical expertise, and clinical judgment to\ndetermine if therapeutic intervention is indicated.\nIndications for Use (capital equipment hardware)\nThe OPTIS™ Mobile Next [and OPTIS™ Integrated Next] with a compatible\nDragonfly™ OPTIS™ or Dragonfly™ OpStar™ Imaging Catheter is intended for the\nimaging of coronary arteries and is indicated in patients who are candidates for\ntransluminal interventional procedures. The Dragonfly OPTIS or Dragonfly OpStar\nImaging Catheter is intended for use in vessels 2.0 to 3.5 mm in diameter. The\nDragonfly OPTIS or Dragonfly OpStar Imaging Catheter is not intended for use in the\nleft main coronary artery or in a target vessel which has undergone a previous bypass\nprocedure.\nThe OPTIS Mobile Next [and OPTIS™ Integrated Next] is intended for use in the\ncatheterization and related cardiovascular specialty laboratories and will further\ncompute and display various physiological parameters based on the output from one or\nmore electrodes, transducers, or measuring devices. The physician may use the"]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p6-t0","doc_id":"K210458","page_num":6,"bbox":[71.6,72.4,566.04,710.0],"n_rows":8,"n_cols":8,"columns":["","acquired physiological parameters, along with knowledge of patient history, medical\nexpertise, and clinical judgment to determine if therapeutic intervention is indicated.","","","","","",""],"rows":[["","acquired physiological parameters, along with knowledge of patient history, medical\nexpertise, and clinical judgment to determine if therapeutic intervention is indicated.","","","","","",""],["Comparison of\nSubject to\nPredicate Device","The OPTIS™ Next Imaging System with Ultreon™ Software version 1.0 is equivalent\nto the predicate OPTIS™ Imaging System with AptiVue™ Software version E.5.1\n(K192019) in terms of intended use, indications for use, operational characteristics,\nfundamental design, and technological characteristics. Changes to technological\ncharacteristics of the device do not raise new questions of safety or effectiveness.","","","","","",""],["","Feature","","Predicate Device:","","","Proposed Device:",""],["","","","OPTIS System with","","","OPTIS Next Imaging System",""],["","","","AptiVue™ Software Version","","","with Ultreon Software version",""],["","","","E.5.1 (K192019)","","","1.0",""],["","Intended Use","The AptiVue™ E-series\nsoftware is intended for use only\nwith compatible OPTIS™\nimaging systems. OPTIS™\nimaging systems are intended\nfor use in the catheterization and\nrelated cardiovascular specialty\nlaboratories.","","","The Ultreon™ 1.0 Software is\nintended to be used only with\ncompatible OPTIS™ Next\nImaging Systems.","",""],["","Indications for\nUse","The AptiVue™ E series\nsoftware is intended to be used\nonly with compatible OPTIS™\nimaging systems.\nThe OPTIS imaging system\nwith a compatible Dragonfly™\nimaging catheter is intended for\nthe imaging of coronary arteries\nand is indicated in patients who\nare candidates for transluminal\ninterventional procedures. The\ncompatible Dragonfly™\nimaging catheters are intended\nfor use in vessels 2.0 to 3.5 mm\nin diameter. The compatible\nDragonfly™ imaging catheters\nare not intended for use in the\nleft main coronary artery or in a\ntarget vessel which has\nundergone a previous bypass\nprocedure.\nThe OPTIS imaging system is\nintended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further\ncompute and display various\nphysiological parameters based\non the output from one or more","","","The OPTIS Next Imaging System\nwith a compatible Dragonfly™\nOPTIS™ Imaging Catheter or\nDragonfly OpStar™ Imaging\nCatheter is intended for the\nimaging of coronary arteries and\nis indicated in patients who are\ncandidates for transluminal\ninterventional procedures. The\nDragonfly OPTIS Imaging\nCatheter or Dragonfly OpStar\nImaging Catheter is intended for\nuse in vessels 2.0 to 3.5 mm in\ndiameter. The Dragonfly OPTIS\nImaging Catheter or Dragonfly\nOpStar Imaging Catheter is not\nintended for use in the left main\ncoronary artery or in a target\nvessel which has undergone a\nprevious bypass procedure.\nThe OPTIS Next Imaging System\nis intended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further","",""]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p7-t0","doc_id":"K210458","page_num":7,"bbox":[71.6,72.4,566.04,697.05],"n_rows":6,"n_cols":8,"columns":["","","electrodes, transducers, or\nmeasuring devices. The\nphysician may use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise and\nclinical judgment to determine\nif therapeutic intervention is\nindicated.","","","compute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The physician\nmay use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine if\ntherapeutic intervention is\nindicated.","",""],"rows":[["","","electrodes, transducers, or\nmeasuring devices. The\nphysician may use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise and\nclinical judgment to determine\nif therapeutic intervention is\nindicated.","","","compute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The physician\nmay use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine if\ntherapeutic intervention is\nindicated.","",""],["","Measurement\n& Display\nFeatures","OCT recordings, FFR, Pd/Pa at\nrest, and RFR physiological\nwaveforms","","","OCT recordings, FFR, Pd/Pa at\nrest, and RFR physiological\nwaveforms","",""],["","Design\nModifications","N/A","","","Modifications to the Ultreon 1.0\nsoftware have been made to\ninclude automated morphology\nassessment of External Elastic\nLamina (EEL) and calcium,\ndisplay of live angiography\nimagery on the OPTIS Next\nImaging System display\nmonitors, and user interface\nguided workflows for image data\nacquisition and review. Software\nupdates were made to the\nfollowing existing features:\n• OCT image color map\n• OCT pullback auto-trigger\n• Angio co-registration\n• Vessel sizing\n• Stent analysis\n• Stent expansion\n• Cybersecurity\nSoftware design verification and\nvalidation testing have been\nperformed which concludes these\nmodifications demonstrate claims\nof substantial equivalence to the\nAptiVue E.5.1 software.","",""],["","Feature","","OPTIS Mobile, OPTIS","","","OPTIS Mobile Next, OPTIS",""],["","","","Integrated Hardware","","","Integrated Next Hardware",""],["","","","(Predicate)","","","(Proposed)",""]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p8-t0","doc_id":"K210458","page_num":8,"bbox":[71.6,72.4,566.0,712.4],"n_rows":2,"n_cols":4,"columns":["","Indications for\nUse","The OPTIS™ mobile system\n[and OPTIS™ integrated\nsystem] with a compatible\nDragonfly™ imaging catheter is\nintended for the imaging of\ncoronary arteries and is\nindicated in patients who are\ncandidates for transluminal\ninterventional procedures. The\nDragonfly imaging catheter is\nintended for use in vessels 2.0 to\n3.5 mm in diameter. The\nDragonfly imaging catheter is\nnot intended for use in the left\nmain coronary artery or in a\ntarget vessel which has\nundergone a previous bypass\nprocedure.\nThe OPTIS mobile system [and\nOPTIS integrated system] is\nintended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further\ncompute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The\nphysician may use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine\nif therapeutic intervention is\nindicated.","The OPTIS™ Mobile Next [and\nOPTIS™ Integrated Next] with a\ncompatible Dragonfly™\nOPTIS™ or Dragonfly™\nOpStar™ Imaging Catheter is\nintended for the imaging of\ncoronary arteries and is indicated\nin patients who are candidates for\ntransluminal interventional\nprocedures. The Dragonfly\nOPTIS or Dragonfly OpStar\nImaging Catheter is intended for\nuse in vessels 2.0 to 3.5 mm in\ndiameter. The Dragonfly OPTIS\nor Dragonfly OpStar Imaging\nCatheter is not intended for use in\nthe left main coronary artery or in\na target vessel which has\nundergone a previous bypass\nprocedure.\nThe OPTIS Mobile Next [and\nOPTIS Integrated Next] is\nintended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further\ncompute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The physician\nmay use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine if\ntherapeutic intervention is\nindicated."],"rows":[["","Indications for\nUse","The OPTIS™ mobile system\n[and OPTIS™ integrated\nsystem] with a compatible\nDragonfly™ imaging catheter is\nintended for the imaging of\ncoronary arteries and is\nindicated in patients who are\ncandidates for transluminal\ninterventional procedures. The\nDragonfly imaging catheter is\nintended for use in vessels 2.0 to\n3.5 mm in diameter. The\nDragonfly imaging catheter is\nnot intended for use in the left\nmain coronary artery or in a\ntarget vessel which has\nundergone a previous bypass\nprocedure.\nThe OPTIS mobile system [and\nOPTIS integrated system] is\nintended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further\ncompute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The\nphysician may use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine\nif therapeutic intervention is\nindicated.","The OPTIS™ Mobile Next [and\nOPTIS™ Integrated Next] with a\ncompatible Dragonfly™\nOPTIS™ or Dragonfly™\nOpStar™ Imaging Catheter is\nintended for the imaging of\ncoronary arteries and is indicated\nin patients who are candidates for\ntransluminal interventional\nprocedures. The Dragonfly\nOPTIS or Dragonfly OpStar\nImaging Catheter is intended for\nuse in vessels 2.0 to 3.5 mm in\ndiameter. The Dragonfly OPTIS\nor Dragonfly OpStar Imaging\nCatheter is not intended for use in\nthe left main coronary artery or in\na target vessel which has\nundergone a previous bypass\nprocedure.\nThe OPTIS Mobile Next [and\nOPTIS Integrated Next] is\nintended for use in the\ncatheterization and related\ncardiovascular specialty\nlaboratories and will further\ncompute and display various\nphysiological parameters based\non the output from one or more\nelectrodes, transducers, or\nmeasuring devices. The physician\nmay use the acquired\nphysiological parameters, along\nwith knowledge of patient\nhistory, medical expertise, and\nclinical judgment to determine if\ntherapeutic intervention is\nindicated."],["","Design\nModifications","N/A","Modifications to the OPTIS\nMobile Next, OPTIS Integrated\nNext Hardware have been made\nto support of the computational\nspeed, display, electrical\ncompliance, and cybersecurity\nrequirements of the system.\n• Graphics processing unit\n• Memory\n• Power supply\n• Main motherboard and CPU\n• Solid-state drive storage"]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p9-t0","doc_id":"K210458","page_num":9,"bbox":[71.6,72.4,566.0,718.0],"n_rows":3,"n_cols":4,"columns":["","","","• Trusted Platform Module\n(TPM) chip supporting\ncybersecurity\n• Ferrites added to the USB-\nover-Ethernet Extender Cable\nDesign verification and validation\ntesting has been performed which\nconcludes these modifications\ndemonstrate claims of substantial\nequivalence to the OPTIS\nMobile, OPTIS Integrated\nHardware."],"rows":[["","","","• Trusted Platform Module\n(TPM) chip supporting\ncybersecurity\n• Ferrites added to the USB-\nover-Ethernet Extender Cable\nDesign verification and validation\ntesting has been performed which\nconcludes these modifications\ndemonstrate claims of substantial\nequivalence to the OPTIS\nMobile, OPTIS Integrated\nHardware."],["Summary on\nNon-Clinical\nTesting","Verification and Validation testing were completed to demonstrate safety and\neffectiveness and ensure that the subject device performs as intended. Design\nverification and validation included the following:\n• Software Verification and Validation – performed to ensure that the subject\ndevice meets requirements and functions as intended\n• Human Factors -Summative Usability Study – performed to demonstrate that the\nupdated user interface, 1) does not trigger any serious harm based on use error or use\nproblems, for the intended uses, and under the expected use conditions; and, 2) shows\nno pattern of use errors or problems that could result in serious harm and that could be\neliminated or reduced through further modification of the user interface, device\nlabeling, or user training.\n• Hardware/System/packaging Verification – performed to demonstrate that the\nOPTIS Next Imaging System products and packaging meet specifications, are\nappropriate for their intended use, and do not raise new questions of safety or\neffectiveness.","",""],["Summary of\nClinical Testing","No new clinical testing was completed, nor relied upon, in support of this Traditional\n510(k). However, clinical analysis of published literature was used to support a labeling\nchange to reflect the resting full cycle ratio (RFR) cut-off of 0.89\nRFR Interpretation\nRFR Value Interpretation 1,2\nRFR ≤ 0.89 Indicates that a lesion is hemodynamically significant.\nRFR > 0.89 Indicates that a lesion is not hemodynamically significant.\nRFR has been validated for clinical accuracy and outcomes in over 2,500 patients 1-6. Multiple\npeer-reviewed publications demonstrate the equivalence of RFR to other non-hyperemic\npressure ratios (NHPR). IRIS-FFR and 3V FFR-FRIENDS studies compared all NHPRs and\nconcluded that all have the same class effect and are broadly equivalent in terms of diagnostic\nand prognostic performance 3-5. Therefore, RFR-guided treatment at a cut-off of 0.89 is\nequivalent to other NHPR-guided treatment.\nThe above RFR dichotomous cut-off of 0.89 represents a threshold for lesions indicative of\nhemodynamically significant. An RFR of 0.89 is, therefore, equivalent to an FFR of 0.80 as a\nthreshold for ischemia detection.\nReferences:\n1. Svanerud et. al. Validation of a novel non-hyperaemic index of coronary artery stenosis\nseverity: the Resting Full-cycle Ratio (VALIDATE RFR) study. EuroIntervention 2018;\n14(7): 806-814.\n2. Kumar et. al. Real world validation of the nonhyperemic index of coronary artery stenosis","",""]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p9-t1","doc_id":"K210458","page_num":9,"bbox":[174.0,482.8,560.4,718.0],"n_rows":5,"n_cols":2,"columns":["RFR Interpretation",""],"rows":[["RFR Interpretation",""],["RFR Value","Interpretation 1,2"],["RFR ≤ 0.89","Indicates that a lesion is hemodynamically significant."],["RFR > 0.89","Indicates that a lesion is not hemodynamically significant."],["RFR has been validated for clinical accuracy and outcomes in over 2,500 patients 1-6. Multiple\npeer-reviewed publications demonstrate the equivalence of RFR to other non-hyperemic\npressure ratios (NHPR). IRIS-FFR and 3V FFR-FRIENDS studies compared all NHPRs and\nconcluded that all have the same class effect and are broadly equivalent in terms of diagnostic\nand prognostic performance 3-5. Therefore, RFR-guided treatment at a cut-off of 0.89 is\nequivalent to other NHPR-guided treatment.\nThe above RFR dichotomous cut-off of 0.89 represents a threshold for lesions indicative of\nhemodynamically significant. An RFR of 0.89 is, therefore, equivalent to an FFR of 0.80 as a\nthreshold for ischemia detection.\nReferences:\n1. Svanerud et. al. Validation of a novel non-hyperaemic index of coronary artery stenosis\nseverity: the Resting Full-cycle Ratio (VALIDATE RFR) study. EuroIntervention 2018;\n14(7): 806-814.\n2. Kumar et. al. Real world validation of the nonhyperemic index of coronary artery stenosis",""]],"caption_candidate":"change to reflect the resting full cycle ratio (RFR) cut-off of 0.89","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210458-p10-t0","doc_id":"K210458","page_num":10,"bbox":[71.6,72.67,566.0,376.4],"n_rows":2,"n_cols":2,"columns":["","severity-Resting full-cycle ratio-RE-VALIDATE. Catheter Cardiovasc Interv. 2020;\n96(1): E53-E58.\n3. Lee et. al. Physiologic and Clinical Assessment of Resting Physiologic Indices. Circulation\n2019; 139:889-900.\n4. Ahn J et al. Fractional Flow Reserve and Cardiac Events in Coronary Artery Disease.\nCirculation. 2017 Jun 6; 135(23): 2241-2251.\n5. Lee et al. Clinical Outcome of Lesions with Discordant Results Among Different Invasive\nPhysiologic Indices. Circulation J 2019; 83: 2210-2221.\n6. Jeremias et al. RFR: A Novel Physiologic Index Compared to FFR."],"rows":[["","severity-Resting full-cycle ratio-RE-VALIDATE. Catheter Cardiovasc Interv. 2020;\n96(1): E53-E58.\n3. Lee et. al. Physiologic and Clinical Assessment of Resting Physiologic Indices. Circulation\n2019; 139:889-900.\n4. Ahn J et al. Fractional Flow Reserve and Cardiac Events in Coronary Artery Disease.\nCirculation. 2017 Jun 6; 135(23): 2241-2251.\n5. Lee et al. Clinical Outcome of Lesions with Discordant Results Among Different Invasive\nPhysiologic Indices. Circulation J 2019; 83: 2210-2221.\n6. Jeremias et al. RFR: A Novel Physiologic Index Compared to FFR."],["Statement of\nEquivalence","As demonstrated by risk management activities, software verification, and HFE\nusability study testing the proposed OPTIS Next Imaging System does not raise new\nquestions of safety or effectiveness, as compared to the predicate device, meets\nrequirements, supports claims of substantial equivalence, and is acceptable for use.\nModifications to the software of the device do no raise new questions of safety or\neffectiveness.\nAs demonstrated by risk management activities, hardware/system verification, and\nelectrical compliance testing the proposed OPTIS Next Imaging System does not raise\nnew questions of safety or effectiveness, as compared to the predicate device, meets\nrequirements, supports claims of substantial equivalence, and is acceptable for use.\nModifications to the hardware of the device do no raise new questions of safety or\neffectiveness."]],"caption_candidate":"K210458","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210556-p13-t0","doc_id":"K210556","page_num":13,"bbox":[64.0,77.49,562.77,265.98],"n_rows":19,"n_cols":4,"columns":["Control of life","No","No","N/A"],"rows":[["Control of life","No","No","N/A"],["supporting","","",""],["devices","","",""],["","","",""],["Human","Yes","Yes","N/A"],["","","",""],["intervention","","",""],["","","",""],["for image","","",""],["","","",""],["interpretation","","",""],["","","",""],["Ability to add","Yes","Yes","N/A"],["","","",""],["additional","","",""],["","","",""],["modules when","","",""],["","","",""],["available","","",""]],"caption_candidate":"Control of life","well_formed":true,"extraction_settings":"text"}
{"table_id":"K210611-p7-t0","doc_id":"K210611","page_num":7,"bbox":[109.91,484.75,540.2,532.87],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Sempra\nwith syngo MR XA12","K183221,\ncleared February 14, 2019","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210611-p7-t1","doc_id":"K210611","page_num":7,"bbox":[109.91,595.99,540.2,677.98],"n_rows":4,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Aera with\nsyngo MR XA30A","K202014,\ncleared September 8, 2020","LNH\nLNI, MOS","Siemens AG / Siemens\nHealthcare GmbH"],["MAGNETOM C!","K082331,\ncleared October 1, 2008","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."]],"caption_candidate":"listed as a reference device as well:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210611-p9-t0","doc_id":"K210611","page_num":9,"bbox":[109.66,159.74,534.75,700.18],"n_rows":13,"n_cols":2,"columns":["Feature / Function","Clinical Publication"],"rows":[["Feature / Function","Clinical Publication"],["SMS Averaging for TSE","[1] C. H. OH et al., 1984. Line-Integral Projection\nReconstruction (LPR) with Slice Encoding Techniques:\nMultislice Regional Imaging in NMR Tomography, IEEE\nTrans Med Imaging. 1984; 3(4):170-178"],["Ramp sampling mode\nfor Beat","[2] Matt A.Bernstein, Kevin F.king, Xiaohong Joe Zhou,\nHandbook Of MRI Pulse Sequences, 2004: P706-P712."],["SWI with 3D segmented\nEPI","[3] Zwanenburg JJ, et al. Fast high resolution whole brain\nT2* weighted imaging using echo planar imaging at 7T.\nNeuroimage. 2011; 56:1902-1907.\n[4] Liu W, et al. 3D Flow Compensated Interleaved EPI for a\nFast High-Resolution Susceptibility-Weighted Imaging at\n1.5T. Proc. Intl. Soc. Mag. Reason. Med 2019; 27: 3326."],["Accelerated Shim\n(STEAM-based field\nmap)","[5] Nehrke, K., and Börnert, P. \"DREAM—a novel approach"],["","for robust, ultrafast, multislice B1 mapping.\" Magnetic"],["","resonance in medicine 68.5 (2012): 1517-1526."],["Skewed SPAIR","[6] Hwang, T. L., van Zijl, P. C., and Garwood, M. 1999.\nAsymmetric adiabatic pulses for NH selection. J. Magn.\nReson. 138: 173–177.\n[7] Pfeuffer J. et al. “Zoomed Functional Imaging in the\nHuman Brain at 7 Tesla with Simultaneous High Spatial and\nHigh Temporal Resolution” NeuroImage 17(1), 2002, p. 272-\n286."],["Deep Resolve Gain","[8] Kellman P. et al. Image Reconstruction in SNR Units: A\nGeneral Method for SNR Measurement. MRM 2005;\n54:1439. Erratum in MRM 2007; 58:311."],["","[9] Blu T. et al. The SURE-LET approach to image denoising.\nIEEE Transactions on Image Processing 16(11):2778-86"],["Deep Resolve Sharp","[10] Yulun Zhang, et al. Residual Dense Network for Image\nSuper-Resolution, IEEE conference on computer vision and\npattern recognition. 2018"],["","[11] Eirikur Agustsson, Radu Timofte. NTIRE 2017\nChallenge on Single Image Super-Resolution: Dataset and\nStudy. CVPRW, 2017. 5"],["","[12] Justin Johnson, et al. Perceptual Losses for Real-Time\nStyle Transfer and Super-Resolution. European conference\non computer vision. Springer, Cham, 2016"]],"caption_candidate":"features and functions.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210611-p10-t0","doc_id":"K210611","page_num":10,"bbox":[109.77,298.82,540.23,693.7],"n_rows":13,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognitio","n Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General","Medical electrical equipment -\npart 1: general requirements for\nbasic safety and essential\nperformance","ES60601-\n1:2005/(R) 2012\nand A1:2012","AAMI / ANSI"],["19-8","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2, Ed.\n4.0:2014","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33, Ed.\n3.2 b:2015","IEC"],["5-40","General","Medical devices - Application of\nrisk management to medical\ndevices","14971, Ed. 2:2007","ISO"],["5-114","General","Medical devices – Application of\nusability engineering to medical\ndevices","62366, Edition\n1.0:2015","AAMI\nANSI\nIEC"],["13-79","Software","Medical device software -\nSoftware life cycle processes","62304:2006 +\nA1:2015","AAMI\nANSI\nIEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"]],"caption_candidate":"recognized and international IEC, ISO and NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210611-p11-t0","doc_id":"K210611","page_num":11,"bbox":[109.89,103.1,540.46,254.06],"n_rows":3,"n_cols":5,"columns":["12-288","Radiology","Characterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images\n(MRI)","MS 9:2008","NEMA"],"rows":[["12-288","Radiology","Characterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images\n(MRI)","MS 9:2008","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20:2016","NEMA"],["2-258","Biocompati\nbility","biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process\n(Biocompatibility)","10993-1:2018","AAMI\nANSI\nISO"]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210645-p4-t0","doc_id":"K210645","page_num":4,"bbox":[94.71,34.37,533.21,67.83],"n_rows":2,"n_cols":4,"columns":["Document ID and Title","","","Version:"],"rows":[["Document ID and Title","","","Version:"],["RSL-D-RS-10.1 510(k) Summary RayStation 10.1","","1.0",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210645-p5-t0","doc_id":"K210645","page_num":5,"bbox":[94.71,34.37,533.21,67.83],"n_rows":2,"n_cols":4,"columns":["Document ID and Title","","","Version:"],"rows":[["Document ID and Title","","","Version:"],["RSL-D-RS-10.1 510(k) Summary RayStation 10.1","","1.0",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210645-p6-t0","doc_id":"K210645","page_num":6,"bbox":[94.71,34.37,533.21,67.83],"n_rows":2,"n_cols":4,"columns":["Document ID and Title","","","Version:"],"rows":[["Document ID and Title","","","Version:"],["RSL-D-RS-10.1 510(k) Summary RayStation 10.1","","1.0",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210645-p7-t0","doc_id":"K210645","page_num":7,"bbox":[94.71,34.37,533.21,67.83],"n_rows":2,"n_cols":4,"columns":["Document ID and Title","","","Version:"],"rows":[["Document ID and Title","","","Version:"],["RSL-D-RS-10.1 510(k) Summary RayStation 10.1","","1.0",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210666-p4-t0","doc_id":"K210666","page_num":4,"bbox":[72.03,39.38,378.14,640.04],"n_rows":41,"n_cols":3,"columns":["510(k) Summary","",""],"rows":[["510(k) Summary","",""],["","",""],["In accordance with 21 CFR 80","","7.87(h) (and 21 CFR 807.92) the"],["is provided below.","",""],["","",""],["1. SUBMITTER","",""],["","",""],["Applicant:","","Imagen Technologies, Inc."],["","","151 West 26th Street, Suite 1001"],["","","New York, NY 10001"],["","",""],["Contact and Primary","","Robert Lindsey, Ph.D."],["Correspondent:","","Chief Science Officer"],["","","Imagen Technologies, Inc."],["","","151 West 26th Street, Suite 1001"],["","","New York, NY 10001"],["","","917-830-4721"],["","","rob@imagen.ai"],["","",""],["Secondary Correspondent:","","Becky Ditty"],["","","Consultant"],["","","Biologics Consulting"],["","","1555 King St., Suite 300"],["","","Alexandria, VA 22314"],["","","269-888-2516"],["","","bditty@biologicsconsulting.com"],["","",""],["Date Prepared:","","July 12th, 2021"],["","",""],["2. DEVICE","",""],["","",""],["Device Trade Name:","C","hest-CAD"],["","",""],["Device Common Name or","","Medical Image Analyzer"],["Classification Name:","",""],["","",""],["Regulation","2","1 CFR 892.2070"],["","",""],["Regulatory Class:","I","I"],["","",""],["Product Code:","","MYN"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K210666-p6-t0","doc_id":"K210666","page_num":6,"bbox":[72.35,334.66,540.63,707.6],"n_rows":14,"n_cols":9,"columns":["","","","","Proposed Device","","","Predicate",""],"rows":[["","","","","Proposed Device","","","Predicate",""],["Number","","","K210666","","","P000041","",""],["Applicant","","","Imagen Technologies","","","Riverain Medical Group","",""],["Device Name","","","Chest-CAD","","","RapidScreen™ RS-2000","",""],["Classification Regulation","","","892.2070","","","892.2070","",""],["Product Code","","","MYN","","","MYN","",""],["Image Modality","","","X-ray","","","X-ray","",""],["Study Type","","","Chest","","","Chest","",""],["Clinical Output","","","Identify and mark regions of\ninterest (ROIs) on chest\nradiographs","","","Identify and mark regions of\ninterest (ROIs) on chest\nradiographs","",""],["Clinical Finding","","","Identified ROIs are assigned to\none of the following categories:\nCardiac, Mediastinum/Hila,\nLungs, Pleura, Bones, Soft\nTissues, Hardware, or Other","","","Identified ROIs are assigned to a\nsingle category (i.e., features\nassociated with solitary\npulmonary nodules from 9 to 30\nmm in size)","",""],["Intended Users","","","Physician","","","Physician","",""],["Intended User Workflow","","","Device intended for use as a\nreading aid for physicians\ninterpreting chest radiographs","","","Device intended for use as a\nreading aid for physicians\ninterpreting chest radiographs","",""],["Patient Population","","","Adults with Chest Radiographs","","","Adults with Chest Radiographs","",""],["Algorithm Methodology","","","Artificial Neural Networks","","","Artificial Neural Networks","",""]],"caption_candidate":"Table 1: Technological Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210666-p7-t0","doc_id":"K210666","page_num":7,"bbox":[72.25,72.59,540.68,175.42],"n_rows":4,"n_cols":9,"columns":["","","","","Proposed Device","","","Predicate",""],"rows":[["","","","","Proposed Device","","","Predicate",""],["Platform","","","Secure cloud-based processing\nand delivery of chest radiographs","","","Secure on-premise processing\nand delivery of chest radiographs","",""],["Image Source","","","Digital X-ray","","","Film X-ray","",""],["Image Viewing","","","Image displayed on PACS system","","","Image displayed on video\nmonitor","",""]],"caption_candidate":"510(k) Summary Page 4 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210666-p9-t0","doc_id":"K210666","page_num":9,"bbox":[72.37,112.84,539.65,280.72],"n_rows":9,"n_cols":7,"columns":["","Category","","","AUC","95% Bootstrap CI",""],"rows":[["","Category","","","AUC","95% Bootstrap CI",""],["Cardiac","","","0.961","","0.959, 0.963",""],["Mediastinum/Hila","","","0.921","","0.918, 0.924",""],["Lungs","","","0.967","","0.966, 0.969",""],["Pleura","","","0.973","","0.972, 0.975",""],["Bones","","","0.930","","0.926, 0.934",""],["Soft Tissues","","","0.981","","0.977, 0.985",""],["Hardware","","","0.994","","0.994, 0.995",""],["Other","","","0.953","","0.950, 0.957",""]],"caption_candidate":"Table 2: AUC of the ROC Curve for Chest-CAD Model Predictions by Category","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210666-p9-t1","doc_id":"K210666","page_num":9,"bbox":[72.37,319.16,539.65,639.57],"n_rows":10,"n_cols":5,"columns":["Category","Sensitivity","","Specificity",""],"rows":[["Category","Sensitivity","","Specificity",""],["","","95%\nWilson's CI","95%\nWilson's CI",""],["Cardiac","0.889\n(0.881, 0.897)","","0.892\n(0.887, 0.897)",""],["Mediastinum/Hila","0.856\n(0.844, 0.867)","","0.830\n(0.824, 0.835)",""],["Lungs","0.888\n(0.882, 0.893)","","0.915\n(0.908, 0.921)",""],["Pleura","0.919\n(0.912, 0.925)","","0.899\n(0.894, 0.904)",""],["Bones","0.854\n(0.838, 0.868)","","0.856\n(0.850, 0.861)",""],["Soft Tissues","0.938\n(0.916, 0.955)","","0.919\n(0.916, 0.923)",""],["Hardware","0.967\n(0.963, 0.970)","","0.960\n(0.956, 0.964)",""],["Other","0.906\n(0.889, 0.920)","","0.872\n(0.867, 0.877)",""]],"caption_candidate":"Table 3: Sensitivity and Specificity for Chest-CAD Model Predictions by Category","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p4-t0","doc_id":"K210670","page_num":4,"bbox":[72.0,135.96,558.0,192.72],"n_rows":3,"n_cols":2,"columns":["Submitter:","TaiHao Medical Inc."],"rows":[["Submitter:","TaiHao Medical Inc."],["Address:","6F.-1, No.100, Sec. 2, Heping E. Rd., Da’an Dist., Taipei City 106, Taiwan\n(R.O.C.)"],["Phone:","886-2-2736-5679"]],"caption_candidate":"I. Identification of Submitter K210670","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p4-t1","doc_id":"K210670","page_num":4,"bbox":[72.0,207.0,558.0,278.52],"n_rows":5,"n_cols":2,"columns":["Contact:","HSIN HUNG (Simon) LAI"],"rows":[["Contact:","HSIN HUNG (Simon) LAI"],["Title:","President"],["Phone:","886-2-2736-5679"],["Email:","simonlai@taihaomed.com"],["Manufacturer:","TaiHao Medical Inc."]],"caption_candidate":"Phone: 886-2-2736-5679","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p4-t2","doc_id":"K210670","page_num":4,"bbox":[72.0,292.8,558.0,391.92],"n_rows":5,"n_cols":2,"columns":["Additional\nContact:","HONG HAO CHEN, Ph.D."],"rows":[["Additional\nContact:","HONG HAO CHEN, Ph.D."],["Title:","Regulatory Affairs Manager"],["Address:","6F.-1, No.100, Sec. 2, Heping E. Rd., Da’an Dist., Taipei City 106, Taiwan\n(R.O.C.)"],["Phone:","886-2-2736-5679"],["Email:","honghowc@taihaomed.com"]],"caption_candidate":"Manufacturer: TaiHao Medical Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p4-t3","doc_id":"K210670","page_num":4,"bbox":[72.0,471.96,558.0,599.16],"n_rows":6,"n_cols":2,"columns":["Device Name:","BU-CAD"],"rows":[["Device Name:","BU-CAD"],["Regulation Number:","892.2090"],["Device Classification:","Class II\nClassification Product Code: QDQ\nSubsequent Product Code: LLZ"],["Classification Name:","Radiological Computer Assisted Detection/Diagnosis Software For\nLesions Suspicious For Cancer"],["Review Panel:","Radiology"],["Manufacturer:","TaiHao Medical Inc."]],"caption_candidate":"II. Identification of Product","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p4-t4","doc_id":"K210670","page_num":4,"bbox":[72.0,656.52,558.0,685.2],"n_rows":2,"n_cols":2,"columns":["Predicate Device:","TransparaTM (K181704) (primary), QuantX (K170195)"],"rows":[["Predicate Device:","TransparaTM (K181704) (primary), QuantX (K170195)"],["Reference Device:","Koios DS for Breast (K190442)"]],"caption_candidate":"III. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p6-t0","doc_id":"K210670","page_num":6,"bbox":[72.02,270.66,562.52,396.72],"n_rows":4,"n_cols":6,"columns":["","Region-based Analysis Item","","","Range",""],"rows":[["","Region-based Analysis Item","","","Range",""],["Score of lesion characteristics (SLC)","","","[0,100]\nThe SLC ranging from 0 to 25 corresponds to BI-RADS 2,\nfrom 26 to 50 corresponds to BI-RADS 3, from 51 to 97\ncorresponds to BI-RADS 4, and from 98 to 100 corresponds\nto BI-RADS 5.","",""],["BI-RADS category","","","2 / 3 / 4a / 4b / 4c / 5","",""],["BI-RADS descriptors (mass)","","","Shape, Orientation, Margin, Echo Pattern, Posterior Features\n(with limitations specified in User Manual)","",""]],"caption_candidate":"Output of BU-CAD analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p7-t0","doc_id":"K210670","page_num":7,"bbox":[72.26,191.26,523.18,760.44],"n_rows":9,"n_cols":8,"columns":["","BU-CAD","","TransparaTM","","","QuantX",""],"rows":[["","BU-CAD","","TransparaTM","","","QuantX",""],["","","","(K181704)","","","(K170195)",""],["","","","Predicate Device","","","Predicate Device",""],["Manufacturer","TaiHao Medical Inc.","ScreenPoint Medical\nBV","","","Quantitative Insights,\nInc.","",""],["Regulation\nSection","21 CFR 892.2090","21 CFR 892.2090","","","21 CFR 892.2050","",""],["Product Code","QDQ, LLZ","QDQ","","","LLZ","",""],["Intended Use","Intended to be used by\nclinicians interpreting\nradiological images, to\nhelp them with\nlocalizing and\ncharacterizing breast\nabnormalities.\nIntended to be used\nconcurrently with the\nreading of images and\nare not intended as a\nreplacement for the\nreview of a clinician\nor their clinical\njudgement.","Intended to be used by\nclinicians interpreting\nradiological images, to\nhelp them with\nlocalizing and\ncharacterizing breast\nabnormalities.\nIntended to be used\nconcurrently with the\nreading of images and\nare not intended as a\nreplacement for the\nreview of a clinician\nor their clinical\njudgement.","","","QuantX is a\nquantitative image\nanalysis software\ndevice used to assist\nradiologists in the\nassessment and\ncharacterization of\nbreast abnormalities\nusing MR image data.","",""],["Characteristics","CADe and CADx\nsoftware used to assist\nin localizing\nsuspicious soft tissue\nlesions and region-\nbased analyze of\nmalignancy using\nultrasound image data.","CADe and CADx\nsoftware used to assist\nin localizing\nsuspicious soft tissue\nlesions and suspicious\ncalcifications; region-\nbased analyze of\nmalignancy using\nmammography image\ndata.","","","The software\nautomatically registers\nimages, and segments\nand analyzes user-\nselected regions of\ninterest (ROI). QuantX\nextracts image data\nfrom the ROI to\nprovide volumetric\nand surface area\nanalysis.","",""],["Target\nPopulation","Patients with soft\ntissue breast lesions\nwho are being referred\nfor ultrasound\ninterpreting.","Patients with soft\ntissue breast lesions\nand suspicious\ncalcifications who are\nbeing referred for","","","Patients who are being\nreferred for breast\nMRI interpretation.","",""]],"caption_candidate":"VI. Comparison with Predicate Device/Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p8-t0","doc_id":"K210670","page_num":8,"bbox":[72.21,72.34,523.23,606.96],"n_rows":13,"n_cols":8,"columns":["","BU-CAD","","TransparaTM","","","QuantX",""],"rows":[["","BU-CAD","","TransparaTM","","","QuantX",""],["","","","(K181704)","","","(K170195)",""],["","","","Predicate Device","","","Predicate Device",""],["","","mammogram\ninterpreting.","","","","",""],["Anatomical\nLocation","Breast","Breast","","","Breast","",""],["Design","Software-only device","Software-only device","","","Software-only device","",""],["Modality Used\nfor Analysis","Breast ultrasound data","Mammography","","","Breast MRI","",""],["Input","Medical images\nprovided in a DICOM\nformat","Medical images\nprovided in a DICOM\nformat","","","Medical images\nprovided in a DICOM\nformat","",""],["Output","ROIs and lesion\ncontours placed on\nsuspicious soft tissue\nlesion.\nA region-based score\nof lesion malignancy,\na BI-RADS category,\nand BI-RADS\ndescriptors.","Marks placed on\nsuspicious soft tissue\nlesion and suspicious\ncalcifications.\nA region-based score\nof lesion malignancy,\nand an overall score of\nthe mammogram.","","","QuantX extracts image\ndata from the ROI to\nprovide volumetric\nand surface area\nanalysis.","",""],["Physical\nCharacteristics","Software Package\nOperates on off-the-\nshelf hardware","Software Package\nOperates on off-the-\nshelf hardware","","","Software Package\nOperates on off-the-\nshelf hardware","",""],["Comparative\nPerformance\nTesting\n(MRMC)","Metric: AUC\nCases: 628\nReaders: 16","Metric: AUC\nCases: 240\nReaders: 14","","","N/A","",""],["Modality Used\nfor Viewing","Breast Ultrasound and\nMammography\n(FFDM)","N/A","","","Breast MRI, breast\nultrasound, and\nmammography","",""],["Primary\nInterpretation\nof Digital\nMammography\nImages","BU-CAD is not\nintended for the\nprimary interpretation\nof digital\nmammography\nimages.","N/A","","","QuantX is not\nintended for primary\ninterpretation of\ndigital mammography\nimages","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p14-t0","doc_id":"K210670","page_num":14,"bbox":[95.21,550.44,500.28,666.51],"n_rows":9,"n_cols":9,"columns":["","Statistical Parameter","","","Unaided (95% CI)","","","Aided (95% CI)",""],"rows":[["","Statistical Parameter","","","Unaided (95% CI)","","","Aided (95% CI)",""],["","Sensitivity","","","0.9225 (0.8896, 0.9554)","","","0.9353 (0.9050, 0.9655)",""],["","Specificity","","","0.3165 (0.2694, 0.3636)","","","0.3611 (0.3124, 0.4098)",""],["","NPV (unadjusted)","","","0.8623 (0.8048, 0.9198)","","","0.8945 (0.8456, 0.9434)",""],["","NPV_U.S. (adjusted)","","","0.9982 (0.9902, 1.0000)","","","0.9986 (0.9918, 1.0000)",""],["","NPV_Taiwan (adjusted)","","","0.9969 (0.9767, 1.0000)","","","0.9975 (0.9809, 1.0000)",""],["","PPV (unadjusted)","","","0.4876 (0.4433, 0.5319)","","","0.5056 (0.4607, 0.5505)",""],["","PPV_U.S. (adjusted)","","","0.0108 (-0.0001, 0.0216)","","","0.0113 (0.0000, 0.0225)",""],["","PPV_Taiwan (adjusted)","","","0.0256 (-0.0002, 0.0514)","","","0.0283 (0.0006, 0.0560)",""]],"caption_candidate":"Sensitivity, Specificity, PPV, and NPV between Unaided and Aided Reading Scenarios","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p18-t0","doc_id":"K210670","page_num":18,"bbox":[72.28,94.44,523.19,300.6],"n_rows":11,"n_cols":8,"columns":["","Statistical Parameter","","Standalone (Frequency)","","","95% CI",""],"rows":[["","Statistical Parameter","","Standalone (Frequency)","","","95% CI",""],["","With Modification for Wrong-location Penalty)","","","","","",""],["","Sensitivity (%)","","88.33 (439/497)","","","(0.8551, 0.9115)",""],["","Specificity (%)","","57.94 (372/642)","","","(0.5413, 0.6176)",""],["","PPV (%) [unadjusted]","","61.92 (439/709)","","","(0.5834, 0.6549)",""],["","PPV_US (%)","","1.28","","","",""],["","PPV_TW (%)","","4.74","","","",""],["","NPV (%) [unadjusted]","","86.51 (372/430)","","","",""],["","NPV_US (%)","","99.82","","","",""],["","NPV_TW (%)","","99.67","","","",""],["* The 95% Confidence Interval (CI) was estimated conditioning on the obtained prevalence rates of","","","","","","",""]],"caption_candidate":"Standalone Sensitivity, Specificity, PPV, NPV","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p18-t1","doc_id":"K210670","page_num":18,"bbox":[53.88,489.32,558.0,580.2],"n_rows":7,"n_cols":18,"columns":["","Statistical","","3","","","4A*","","","4 B","","","4C","","","5","",""],"rows":[["","Statistical","","3","","","4A*","","","4 B","","","4C","","","5","",""],["","Parameter","","","","","","","","","","","","","","","",""],["Sensitivity","","","","0.9416","","","0.8833","","","0.8249","","","0.6962","","","0.4588",""],["","","","","(0.9210, 0.9623)","","","(0.8551, 0.9115)","","","(0.7915, 0.8584)","","","(0.6557, 0.7366)","","","(0.4149, 0.5026)",""],["Specificity","","","","0.3302","","","0.5794","","","0.6994","","","0.8271","","","0.9252",""],["","","","","(0.2938, 0.3666)","","","(0.5413, 0.6176)","","","(0.6639, 0.7348)","","","(0.7979, 0.8564)","","","(0.9049, 0.9456)",""],["* The cut-off value used in the standalone study.","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Standalone Sensitivity and Specificity by Using Different Cut-Off Points","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p19-t0","doc_id":"K210670","page_num":19,"bbox":[72.16,356.16,523.26,454.68],"n_rows":4,"n_cols":6,"columns":["","Standard","","","Standard Title",""],"rows":[["","Standard","","","Standard Title",""],["ISO 14971:2007","ISO 14971:2007","","Medical Devices - Application Of Risk Management To Medical Devices","Medical Devices - Application Of Risk Management To Medical Devices",""],["IEC 62304:2015","","","Medical Device Software - Software Life Cycle Processes","",""],["DEN180005","","","Evaluation of automatic class III designation for OsteoDetect – Decision\nsummary with special controls","",""]],"caption_candidate":"recognized standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p19-t1","doc_id":"K210670","page_num":19,"bbox":[72.16,512.64,523.26,735.36],"n_rows":4,"n_cols":6,"columns":["","FDA Guidance","","","Issued Date",""],"rows":[["","FDA Guidance","","","Issued Date",""],["Guidance for Industry and FDA Staff - Guidance for the Content of\nPremarket Submissions for Software Contained in Medical Devices.","Guidance for Industry and FDA Staff - Guidance for the Content of","","May 11, 2005","",""],["Guidance for Industry and Food and Drug Administration Staff -\nComputer-Assisted Detection Devices Applied to Radiology Images\nand Radiology Device Data – Premarket Notification [510(k)]\nSubmissions.","","","July 3, 2012","",""],["Guidance for Industry and FDA Staff - Clinical Performance\nAssessment: Considerations for Computer-Assisted Detection\nDevices Applied to Radiology Images and Radiology Device Data\nin - Premarket Notification (510(k)) Submissions.","","","January 22, 2020","",""]],"caption_candidate":"The following guidance documents were used to support this submission:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210670-p20-t0","doc_id":"K210670","page_num":20,"bbox":[72.1,72.36,523.33,211.8],"n_rows":3,"n_cols":6,"columns":["","FDA Guidance","","","Issued Date",""],"rows":[["","FDA Guidance","","","Issued Date",""],["Guidance for Industry and Food and Drug Administration Staff -\nThe 510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)].","Guidance for Industry and Food and Drug Administration Staff -","","July 28, 2014","",""],["Draft Guidance for Industry and Food and Drug Administration\nStaff - Content of Premarket Submissions for Management of\nCybersecurity in Medical Devices.","","","October 18, 2018","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210719-p7-t0","doc_id":"K210719","page_num":7,"bbox":[81.32,329.88,544.49,694.44],"n_rows":19,"n_cols":5,"columns":["","Description","","Subject Device","Predicate Device"],"rows":[["","Description","","Subject Device","Predicate Device"],["","","","",""],["","Device proprietary","","Change Healthcare Anatomical\nAI","AquariusAPS Server"],["","name","","",""],["Manufacturer","Manufacturer","","Change Healthcare Canada\nCompany","TeraRecon, Inc."],["","510(k) Number","","K210719","K061214"],["","Classification","","Class II","Class II"],["","Product Code","","QIH","LLZ"],["","Regulatory Number","","892.2050","892.2050"],["Platform","Platform","","Change Healthcare Enterprise\nImaging Network (EIN) cloud\nplatform","TeraRecon"],["","Intended for use in","","Yes","Yes"],["","primary diagnostic","","",""],["","workflow","","",""],["","Process DICOM images","","Yes","Yes"],["Identify locations of\nanatomical structures","Identify locations of","","Abdomen, breast (MR only),\ncalf, chest, elbow, foot, forearm,\nhand, head, arm, knee, neck,\npelvis, shoulder, spine cervical,\nspine thoracic, spine lumbar, and\nthigh","Brain, Heart, Heart\nVasculature, Liver, Lung"],["","anatomical structures","","",""],["","Modalities supported","","CT and MR","CT"],["","for identification of","","",""],["","anatomical structures","","",""]],"caption_candidate":"currently marketed predicate device is provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210719-p8-t0","doc_id":"K210719","page_num":8,"bbox":[81.32,108.42,544.48,345.28],"n_rows":15,"n_cols":5,"columns":["","Description","","Subject Device","Predicate Device"],"rows":[["","Description","","Subject Device","Predicate Device"],["","","","",""],["Algorithm","Algorithm","","Machine learning based\nalgorithm\n(non-adaptive)","Image processing based\nalgorithm"],["","Manual review of","","Yes","Yes"],["","identified anatomical","","",""],["","structures","","",""],["","Can be used to navigate","","Yes","Yes"],["","to a study based on an","","",""],["","identified anatomical","","",""],["","structure","","",""],["","Performing actions","","Yes","Yes"],["","based on DICOM and","","",""],["","other data identified","","",""],["","from the DICOM image","","",""],["","set","","",""]],"caption_candidate":"Change Healthcare Anatomical AI K210719","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210747-p7-t0","doc_id":"K210747","page_num":7,"bbox":[63.84,72.0,561.12,686.88],"n_rows":7,"n_cols":3,"columns":["Comparison of Features between Proposed Subject Device and Predicate Device","",""],"rows":[["Comparison of Features between Proposed Subject Device and Predicate Device","",""],["","Caption Health, Inc., Caption\nInterpretation Automated\nEjection Fraction (“AutoEF\n2.5”) (K210747) - Proposed\nDevice","Caption Health, Inc., Caption\nInterpretation Automated\nEjection Fraction Software\nApplication (“AutoEF 2.0”)\n(K200621) - Predicate Device"],["Product Code","QIH","QIH"],["Intended Use","The Caption Health, Inc.\nCaption Interpretation\nAutomated Ejection Fraction\nsoftware is used to process\npreviously acquired\ntransthoracic cardiac\nultrasound images, to store\nimages, and to manipulate\nand make measurements on\nimages using an ultrasound\ndevice, personal computer, or\na compatible DICOM-\ncompliant PACS system in\norder to\nprovide automated estimation of\nleft ventricular ejection fraction.\nThis measurement can be used\nto assist the clinician in a cardiac\nevaluation.\nThe Caption Interpretation\nAutomated Ejection Fraction\nSoftware is indicated for use in\nadult patients.","The Caption Health, Inc. Caption\nInterpretation Automated Ejection\nFraction software is used to process\npreviously acquired transthoracic\ncardiac ultrasound images, to store\nimages, and to manipulate and make\nmeasurements on images using an\nultrasound device, personal\ncomputer, or a compatible DICOM-\ncompliant PACS system in order to\nprovide automated estimation of left\nventricular ejection fraction. This\nmeasurement can be used to assist\nthe clinician in a cardiac evaluation.\nThe Caption Interpretation\nAutomated Ejection Fraction\nSoftware is indicated for use in\nadult patients."],["General Principles of Operation","",""],["Machine Learning- Based\nAlgorithm","Yes","Yes"],["Operates on DICOM clips","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210747-p8-t0","doc_id":"K210747","page_num":8,"bbox":[63.84,72.0,561.12,614.64],"n_rows":11,"n_cols":3,"columns":["Automation level","Fully automated, including clip\nselection","Fully automated, including clip\nselection"],"rows":[["Automation level","Fully automated, including clip\nselection","Fully automated, including clip\nselection"],["User Alert to Use Multiple\nViews","Yes","Yes"],["Automated Ejection\nFraction Calculation","Yes","Yes"],["Ejection Fraction reported","Whole number estimate","Whole number estimate"],["Quantitative feedback\nto enable clinician to\nassess EF calculation","● Confidence Metric\n● Qualitative Bin Likelihood","● Confidence Metric\n● Qualitative Bin Likelihood"],["EF Result shown with\nvideo clip","Yes","Yes"],["User confirmation/\nrejection of result","Yes","Yes"],["Technological Characteristics","",""],["Network Architecture","Simple Pooling","Advanced Pooling"],["Regressor algorithm","Linear Support Vector Machine","Radial-basis-function (RBF) Support\nVector Machine"],["Image Processing","Grayscaling done first and integer\nresizing.","Floating point resizing and grayscaling\ndone at the end"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210760-p6-t0","doc_id":"K210760","page_num":6,"bbox":[63.0,124.92,540.0,655.44],"n_rows":14,"n_cols":4,"columns":["Technological Characteristics Comparison\nDesign and Fundamental Scientific Technology","","",""],"rows":[["Technological Characteristics Comparison\nDesign and Fundamental Scientific Technology","","",""],["Device","Predicate Device:\nIncisive CT System\n(K180015)","Proposed Device:\nPrecise Image software\napplication","Conclusion"],["","","",""],["Application","Head, Body, Vascular\nand Cardiac","Head, Body and Vascular","Proposed device has scan\ntypes found in the\npredicate,"],["Scan Regime","Continuous Rotation","Continuous Rotation","Scan data used for\nreconstruction - Identical,"],["Scan Field of\nView","Up to 500 mm","Up to 500 mm","Identical"],["Scan modes","Surview\nAxial-after-Axial\nDynamic Scan\nHelical Scan","Axial-after-Axial\nHelical Scan","Proposed device has scan\ntypes found in the\npredicate"],["Low Contrast\nResolution (20 cm\nCatphan\nphantom)","4 mm @ 0.3% @ 22 mGy\nCTDIvol","5 mm @ 0.3% @ 5.5\nmGy CTDIvol","Improved, better low\ncontrast resolution at lower\ndose levels."],["Minimum Scan\nTime","0.35 sec for 360° rotation","0.35 sec for 360° rotation","Identical"],["Noise in Standard\nMode (as\nmeasured on\n21.6 cm water-\nequivalent)","0.27% at 27 mGY","0.27% at 27 mGY","Identical"],["Noise Reduction\nand Low Contrast\nDetectability","N/A – Standard mode\n(baseline for claim)","achieving up to 85% lower\nnoise at 80% lower dose\nand 60% better low\ncontrast detectability","Improved, better noise\nreduction and low contrast\ndetectability"],["Noise Power\nSpectrum","N/A – Standard mode\n(baseline for claim)","Where noise is reduced\nby at least 50%, the\nsystem shall shift the\nnoise power spectrum of\nimages by no more than\n6% as compared to the\nsame data reconstructed\nwithout Precise Image","Will not shift NPS more\nthan 6%"],["Application","Head, Body, Vascular\nand Cardiac","Head, Body and Vascular","Proposed device has scan\ntypes found in the\npredicate."],["Scan Regime","Continuous Rotation","Continuous Rotation","Scan data used for\nreconstruction - Identical."]],"caption_candidate":"CT/AMI Page: 3 of 5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210791-p4-t0","doc_id":"K210791","page_num":4,"bbox":[113.62,117.22,551.96,615.74],"n_rows":17,"n_cols":2,"columns":["Submission Number:","K210791"],"rows":[["Submission Number:","K210791"],["Submitter’s Name:","Eko.ai Pte. Ltd. (d/b/a Us2.ai)"],["Address:","2 College Road, #02-00, Singapore 169850"],["Contact Person:","Jared Seehafer"],["Title:","Regulatory Consultant"],["Telephone Number:","415-857-9554"],["Fax Number:","415-367-1279"],["Email:","jared@enzyme.com"],["Date Summary Prepared:","July 15, 2021"],["Device Proprietary Name:","Us2.v1"],["Model Number:","V 1.0.0"],["Common Name:","Us2.v1"],["Regulation Number:","21 CFR 892.2050"],["Regulation Name:","System, Image Processing, Radiological"],["Product Code:","QIH"],["Device Class:","Class II"],["Predicate Device","Trade name: EchoMD Automated Ejection Fraction\nSoftware\nManufacturer: Bay Labs, Inc.\n(now known as Caption Health, Inc.)\n290 King Street\nSan Francisco, CA 94107\nRegulation Number: 21 CFR 892.2050\nRegulation Name: System, Image Processing, Radiological\nDevice Class: Class II\nProduct Code: LLZ\n510(k) Number: K173780\n510(k) Clearance Date: June 14, 2018"]],"caption_candidate":"Table 5-1. Subject Device Overview.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210791-p6-t0","doc_id":"K210791","page_num":6,"bbox":[119.18,156.75,528.7,676.08],"n_rows":32,"n_cols":5,"columns":["Topic","Predicate Device","Subject Device","",""],"rows":[["Topic","Predicate Device","Subject Device","",""],["Physical\nCharacteristics","Software package that operates\nutilizing off-the-shelf hardware","Same","",""],["DICOM Standard\nCompliance","The software processes DICOM\ncompliant image data","Same","",""],["Modalities","Cardiac echocardiogram","Same","",""],["User Interface","The software is designed for use on\na personal computer that has been\nreceived images from a compatible\nPACS","Same","",""],["Automation level","Fully automated, including clip\nselection","Same","",""],["User\nconfirmation/\nrejection of result","Yes","Yes","",""],["Manual editing\nof automated\nresult by user","Yes (on PACS workstation)","Yes (in application)","",""],["Automated\ncalculations","Ejection Fraction","Region","Measurement",""],["","","LV","DecT",""],["","","LV","MV-A",""],["","","LV","MV-Adur",""],["","","LV","MV-E",""],["","","LV","e’ lateral",""],["","","LV","e’ septal",""],["","","LV","a’ lateral",""],["","","LV","a’ septal",""],["","","LV","s’ lateral",""],["","","LV","s’ septal",""],["","","LV","LVEDV MOD biplane",""],["","","LV","LVEF MOD biplane",""],["","","LV","LVESV MOD biplane",""],["","","LV","LVSV MOD biplane",""],["","","LV","IVSd",""],["","","LV","LVIDd",""],["","","LV","LVIDs",""],["","","LV","LVPWd",""],["","","LV","E/e’ mean",""],["","","RV","RVIDd",""],["","","LA","LAESV MOD biplane",""],["","","RA","Raa",""],["","","TrV","TR Vmax",""]],"caption_candidate":"Table 5-2. Summary of Technological Characteristics Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210791-p8-t0","doc_id":"K210791","page_num":8,"bbox":[133.31,378.6,538.61,593.63],"n_rows":8,"n_cols":3,"columns":["","Normal Cohort","HFrEF Cohort"],"rows":[["","Normal Cohort","HFrEF Cohort"],["Age","40.0 (± 7.5) years","64.3 (± 12.5) years"],["% Male","72.6%","67.4%"],["Height","168.1 (± 9.4) cm","172.2 (± 10.3) cm"],["Weight","76.6 (± 9.2) kg","93.4 (± 24.9) kg"],["Heart Rate","62.7 (± 7.1) bpm","72.2 ( ± 11.9) bpm"],["Systolic Blood Pressure","112.0 (± 9.7) mmHg","124.6 (± 18.1) mmHg"],["Diastolic Blood Pressure","71.2 (± 7.9) mmHg","74.1 (± 11.5) mmHg"]],"caption_candidate":"Table 1. Demographics of Cohort","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210807-p4-t0","doc_id":"K210807","page_num":4,"bbox":[72.24,144.84,539.76,701.46],"n_rows":7,"n_cols":2,"columns":["Date:","October 20, 2021"],"rows":[["Date:","October 20, 2021"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number ‐ 9611343\n283, rue de la Minière\n78530 Buc, France"],["Primary Contact:","Ning WEN\nRegulatory Affairs Leader\nGE Healthcare, (GE Medical Systems SCS)\nTel: +33 6 4637 3852\nEmail: ning.wen@ge.com"],["Secondary Contact","John Jaeckle\nChief Regulatory Affairs Strategist\nTel: +1 262 424 9547\nEmail: john.jaeckle@ge.com"],["Device Trade Name:\nCommon/Usual Name:\nRegulation Number:\nProduct Code:\nRegulatory Class:","FlightPlan for Liver\nFlightPlan for Liver, with Parenchyma Analysis option\n21CFR 892.2050, Medical image management and processing system\nLLZ\nClass II"],["Predicate Device:\nDevice Name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nRegulatory Class:","FlightPlan for Liver\nGE Medical Systems SCS\nK121200\n21CFR 892.2050, Medical image management and processing system\nLLZ\nClass II"],["Reference Device:\nDevice Name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nRegulatory Class:","FlightPlan for Embolization\nGE Medical Systems SCS\nK193261\n21CFR 892.2050, Medical image management and processing system\nLLZ\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210807-p6-t0","doc_id":"K210807","page_num":6,"bbox":[72.27,552.46,539.79,715.56],"n_rows":6,"n_cols":5,"columns":["Specification","","Predicate Device:","","Proposed Device:\nFlightPlan for Liver"],"rows":[["Specification","","Predicate Device:","","Proposed Device:\nFlightPlan for Liver"],["","","FlightPlan for Liver","",""],["","","[K121200]","",""],["Multi‐modality 3D review &\ncomparison of CBCT, CT, MR,\nPET, NM datasets","Identical","","","Identical"],["Semi‐automatic segmentation\nof the liver arterial tree","Yes","","","Yes"],["Definition by operator of\ntarget(s)","Yes","","","Yes"]],"caption_candidate":"the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210807-p7-t0","doc_id":"K210807","page_num":7,"bbox":[72.25,96.52,539.81,480.12],"n_rows":11,"n_cols":5,"columns":["Specification","","Predicate Device:","","Proposed Device:\nFlightPlan for Liver"],"rows":[["Specification","","Predicate Device:","","Proposed Device:\nFlightPlan for Liver"],["","","FlightPlan for Liver","",""],["","","[K121200]","",""],["Semi‐automatic segmentation\nof “vicinity vessels”","Yes","","","Yes"],["Ability to manually add and\nremove “vicinity vessels”","Identical","","","Identical"],["Segmentation and selective\ndisplay of parts of the\nvasculature","Yes, using target\ndefined by user.","","","Yes, using tool for Live Tracking of vessels."],["Ability to mark POIs","Yes","","","Yes"],["Deep learning‐based full Liver\nSegmentation","No, full liver\nsegmentation can only\nbe done manually.","","","Yes, DL based automated segmentation of\nthe full liver."],["Selective display of the\nestimated distal liver region\n(Virtual Parenchyma)","No","","","Yes, the non‐deep learning Virtual\nParenchyma Visualization algorithm\nselectively displays, for visualization\npurposes, the estimated distal liver region\nadjacent to the distal parts of the\ncomputed skeleton of the vessel\nsegmentation (Virtual Parenchyma)."],["Save and export","Identical","","","Identical"],["Platform","Advantage\nWorkstation","","","Advantage Workstation, AW Server"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p4-t0","doc_id":"K210831","page_num":4,"bbox":[87.97,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 1 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p4-t1","doc_id":"K210831","page_num":4,"bbox":[116.63,390.71,522.1,544.79],"n_rows":7,"n_cols":2,"columns":["Device Trade Name","OnQ Neuro"],"rows":[["Device Trade Name","OnQ Neuro"],["Common Name","Medical Image Processing Software"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Regulation Description","Medical image management and processing system"],["Product Code","QIH"],["Classification Panel","Radiology"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p4-t2","doc_id":"K210831","page_num":4,"bbox":[116.63,605.99,522.1,689.51],"n_rows":4,"n_cols":2,"columns":["Device","Multi-Modality Tumor Tracking (MMTT)"],"rows":[["Device","Multi-Modality Tumor Tracking (MMTT)"],["510(k) Number","K162955"],["Manufacturer","Philips Medical Systems"],["Product Code","LLZ"]],"caption_candidate":"Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p5-t0","doc_id":"K210831","page_num":5,"bbox":[87.97,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 2 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p6-t0","doc_id":"K210831","page_num":6,"bbox":[84.8,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 3 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p7-t0","doc_id":"K210831","page_num":7,"bbox":[85.15,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 4 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p7-t1","doc_id":"K210831","page_num":7,"bbox":[85.15,112.67,546.23,393.23],"n_rows":26,"n_cols":4,"columns":["","","Fully-automated","Semi-Automated and manual"],"rows":[["","","Fully-automated","Semi-Automated and manual"],["Tumor Segmentation Type","","",""],["","","",""],["","","Yes. Prior segmentation results\nare provided numerically.","Yes."],["Findings management of","","",""],["identified tumors","","",""],["","","",""],["Quantitative Analysis of\nRegions-of-Interest","","Yes. Including ROI Volumes, and\nhistogram statistics of optional\nquantitative maps.","Yes. Including Volume,\nMin/Max/Mean"],["","","Results displayed in tabular and\ngraphical formats.","Results displayed in tabular and\ngraphical formats."],["Reporting","","",""],["","","",""],["","","Yes","Yes"],["DICOM Communication","","",""],["","","",""],["","","Yes, including single and multi-\ncompartment diffusion models.","No"],["Diffusion Analysis","","",""],["","","",""],["","","Automated fusion of segmentation\nresults and parametric maps.","Automated fusion of\nsegmentation results."],["Image Fusion","","",""],["","","",""],["","","Display/measurement data can be\nviewed, accepted, or rejected by a\nphysician.","Display/measurement data can\nbe viewed, accepted, or rejected\nby a physician."],["Safety","","",""],["","","",""],["","","Hospital, Clinic, Imaging Center,\nMedical Offices","Hospital, Clinic, Medical Offices"],["Environment for use","","",""],["","","",""]],"caption_candidate":"Revision: 03 Pages 4 of 6 Date: 11/19/2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p8-t0","doc_id":"K210831","page_num":8,"bbox":[87.97,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 5 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210831-p9-t0","doc_id":"K210831","page_num":9,"bbox":[87.97,37.45,537.69,90.54],"n_rows":3,"n_cols":6,"columns":["","510(k) Section/Document Number","","","5",""],"rows":[["","510(k) Section/Document Number","","","5",""],["","Title","OnQ Neuro: 510(k) Summary","","",""],["","Revision: 03","","Pages 6 of 6","","Date: 11/19/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210999-p4-t0","doc_id":"K210999","page_num":4,"bbox":[88.56,385.32,523.44,534.84],"n_rows":13,"n_cols":2,"columns":["","Primary Predicate Device: SubtleMR – K191688 by Subtle Medical, Inc., Class II, CFR"],"rows":[["","Primary Predicate Device: SubtleMR – K191688 by Subtle Medical, Inc., Class II, CFR"],["","892.2050, classification with product code LLZ."],["",""],["IV.DEVICE DESCRIPTION",""],["","SwiftMR, is software used as a Medical Device (SaMD) consisting of a software algorithm"],["","that enhances images taken by MRI scanners. The device only processes DICOM"],["","images for the end User and is intended to be used by radiology technologists in an"],["","imaging center, clinic, or hospital."],["",""],["","The device’s inputs are standard of care MRI images in DICOM format. The deep"],["","learning algorithm produces enhanced images as outputs with reduced noise and"],["","increased sharpness in DICOM format. The device applies both denoising and sharpness"],["","increase functions simultaneously."]],"caption_candidate":"III.PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210999-p5-t0","doc_id":"K210999","page_num":5,"bbox":[98.93,556.3,545.14,711.6],"n_rows":4,"n_cols":8,"columns":["Item","","Predicate Device","","","Subject Device","","Differences"],"rows":[["Item","","Predicate Device","","","Subject Device","","Differences"],["","","(K191688)","","","(SwiftMR)","",""],["Physical\nCharacteristics","Software device that\noperates on off-the-\nshelf computer\nhardware","","","Same as predicate","","","No Difference"],["Computer","Linux Compatible","","","PC Compatible","","","Differences are basically in the\ncomputer operating system but also\nmay have some differences in the\nprocessor speeds, amount of RAM\nmemory, monitors, and hard drive\nspace requirements. However, the\nsubject device and the predicate\ndevice are substantially equivalent"]],"caption_candidate":"and is equivalent in performance to existing legally marketed devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K210999-p6-t0","doc_id":"K210999","page_num":6,"bbox":[98.88,119.64,545.16,701.04],"n_rows":5,"n_cols":4,"columns":["","","","in the areas of technical\ncharacteristics, general function,\napplication, and intended use and\nthe computer platform differences\ndo not raise any new potential\nsafety risks. Therefore, it is our\ndetermination that there is “No\nimpact on safety or efficacy” and\nthere are no new potential or\nincreased safety risks."],"rows":[["","","","in the areas of technical\ncharacteristics, general function,\napplication, and intended use and\nthe computer platform differences\ndo not raise any new potential\nsafety risks. Therefore, it is our\ndetermination that there is “No\nimpact on safety or efficacy” and\nthere are no new potential or\nincreased safety risks."],["DICOM\nStandard\nCompliance","The software processes\nDICOM\ncompliant image data","Same as predicate","No Difference"],["Modalities","MRI","Same as predicate","No Difference"],["Image\nEnhancement\nAlgorithm\nDescription","The predicate software\nimplements an image\nenhancement algorithm\nusing convolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Separate\nneural network-based\nfilters are obtained for\nnoise reduction and\nsharpness increase.\nThe parameters of the\nfilters were obtained\nthrough an image\nguided optimization\nprocess.","SwiftMR implements an\nimage enhancement\nalgorithm using\nconvolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Neural\nnetwork-based filters\nthat simultaneously\nperform noise reduction\nand sharpness\nincrease functions are\nobtained. The\nparameters of the filters\nwere obtained through\nan image guided\noptimization process.","The only difference is in how the\nneural network-based filter exists.\nAs for the predicate device, there\nare separate filters for noise\nreduction and sharpness increase.\nOn the other hand, there are neural\nnetwork-based filters that\nsimultaneously perform both\nfunctions for the subject device.\nHowever, the same functions, which\nare noise reduction and sharpness\nincrease, are applied by the filters.\nTherefore, the difference does not\nraise new questions of safety or\neffectiveness."],["Workflow","The predicate software\noperates on DICOM\nfiles on the file system,\nenhances the images,\nand stores the\nenhanced images on\nthe file system. The\nreceipt of original\nDICOM image files and\ndelivery of enhanced\nimages as DICOM files\ndepends on other\nsoftware systems.\nEnhanced images co-\nexist with the original\nimages.","Same as predicate","No Difference"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211118-p4-t0","doc_id":"K211118","page_num":4,"bbox":[86.2,173.6,523.6,629.2],"n_rows":9,"n_cols":2,"columns":["Date:","April 13, 2021"],"rows":[["Date:","April 13, 2021"],["Submitter:","GE Medical Systems, LLC (GE Healthcare)\n3200 N. Grandview Blvd.,\nWaukesha, WI 53188\nUSA"],["Primary Contact Person:","Brian R. Zielski\nRegulatory Affairs Leader\nPhone: 262-227-3596\nEmail: Brian.Zielski@GE.com"],["Secondary Contact\nPerson:","Glen Sabin\nSenior Director, Regulatory Affairs\nPhone: 262-894-4968\nEmail: Glen.Sabin@GE.com"],["Device Trade Name:","SIGNA 7.0T"],["Common/Usual Name:","Magnetic Resonance Diagnostic Device"],["Classification Names:\nRegulation\nNumber:","Magnetic Resonance Diagnostic Device\n21 CFR 892.1000"],["Product Code:\nPrimary:\nSecondary:","LNH\nLNI, MOS"],["Predicate Device(s):","SIGNA 7.0T (K201615)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211118-p5-t0","doc_id":"K211118","page_num":5,"bbox":[86.2,132.2,523.6,769.0],"n_rows":3,"n_cols":2,"columns":["Device Description:","SIGNA 7.0T is a high performance magnetic resonance\nimaging system designed to support high resolution imaging\nat 7.0T in particular anatomical regions determined by the\navailable RF coils. The system includes a 7.0T\nsuperconducting magnet and an ultra-high performance\ngradient coil with a 60 cm patient bore, supporting scanning\nin axial, coronal, sagittal, oblique, and double oblique planes\nusing a variety of pulse sequences, imaging techniques,\nacceleration methods, and reconstruction algorithms.\nThis 510(k) submission is for the SIGNA 7.0T MR System, and\nhas been triggered by the addition of the AIR Recon DL\nsoftware feature and inclusion of installed base magnet\nsystem upgrades."],"rows":[["Device Description:","SIGNA 7.0T is a high performance magnetic resonance\nimaging system designed to support high resolution imaging\nat 7.0T in particular anatomical regions determined by the\navailable RF coils. The system includes a 7.0T\nsuperconducting magnet and an ultra-high performance\ngradient coil with a 60 cm patient bore, supporting scanning\nin axial, coronal, sagittal, oblique, and double oblique planes\nusing a variety of pulse sequences, imaging techniques,\nacceleration methods, and reconstruction algorithms.\nThis 510(k) submission is for the SIGNA 7.0T MR System, and\nhas been triggered by the addition of the AIR Recon DL\nsoftware feature and inclusion of installed base magnet\nsystem upgrades."],["Indications for Use","The addition of the AIR Recon DL feature and installed base\nmagnet system upgrades does not impact the intended use\nof the SIGNA 7.0T system. The Indications for Use remain\nidentical:\nThe SIGNA 7.0T system is a whole-body magnetic resonance\nscanner designed to support high resolution, high signal-to-\nnoise ratio, and short scan times. It is indicated for use as a\ndiagnostic imaging device to produce axial, sagittal, coronal,\nand oblique images, spectroscopic images, parametric maps,\nand/or spectra, dynamic images of the structures and/or\nfunctions of the head and extremities.\nThe images produced by the SIGNA 7.0T system reflects the\nspatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance. These images and/or spectra\nwhen interpreted by a trained physician yield information\nthat may assist in diagnosis.\nThe device is intended for patients > 20 kg / 44 lb."],["Technology:","The SIGNA 7.0T employs the same fundamental scientific\ntechnology as its predicate device.\nThe software used on the proposed SIGNA 7.0T system has\nbeen modified to include the AIR Recon DL feature. The user\ninterface provides operators of the system with new options"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211118-p6-t0","doc_id":"K211118","page_num":6,"bbox":[86.2,132.2,523.6,774.8],"n_rows":2,"n_cols":2,"columns":["","for selecting AIR Recon DL and adjusting the associated level\nof image noise reduction. The resulting images can have\nhigher SNR and improved sharpness compared to images\nreconstructed without AIR Recon DL.\nAIR Recon DL has been previously cleared for use with GE\nHealthcare’s 3T SIGNA Premier system through K193282.\nDue to the technical similarities, SIGNA Premier (K193282) is\nused as a reference device for this submission.\nUpgrades to SIGNA 7.0T are also being expanded to be\ncompatible with additional 7.0T magnets in the installed\nbase."],"rows":[["","for selecting AIR Recon DL and adjusting the associated level\nof image noise reduction. The resulting images can have\nhigher SNR and improved sharpness compared to images\nreconstructed without AIR Recon DL.\nAIR Recon DL has been previously cleared for use with GE\nHealthcare’s 3T SIGNA Premier system through K193282.\nDue to the technical similarities, SIGNA Premier (K193282) is\nused as a reference device for this submission.\nUpgrades to SIGNA 7.0T are also being expanded to be\ncompatible with additional 7.0T magnets in the installed\nbase."],["Determination of\nSubstantial Equivalence:","Summary of Non-Clinical Tests:\nThe AIR Recon DL feature has undergone performance\ntesting. These tests were designed to evaluate the AIR Recon\nDL feature and its impact on image quality, including SNR,\nsharpness, and low contrast detectability.\nThe nonclinical testing demonstrated that AIR Recon DL does\nimprove SNR and image sharpness while maintaining low\ncontrast detectability. AIR Recon DL was also able to\nmaintain image SNR and did not sacrifice sharpness for\nimages acquired with a reduced scan time. The nonclinical\ntesting passed the defined acceptance criteria, and did not\nidentify any adverse impacts to image quality or other\nconcerns related to safety and performance.\nSimulations and analyses were performed for the different\ninstalled base magnet types to ensure equivalence.\nSummary of Clinical Tests:\nObjective measures of in vivo images were analyzed to\nconfirm that AIR Recon DL improves SNR and image\nsharpness for typical clinical use cases.\nA reader study was performed on images with and without\nAIR Recon DL feature. Radiologists were asked to rate the\nimages, and to comment on any notable aspects related to\nimage quality. This study showed that AIR Recon DL feature\nprovides images with better SNR and equivalent or better\nsharpness. The radiologists uniformly preferred the AIR\nRecon DL images for clinical evaluation."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211161-p5-t0","doc_id":"K211161","page_num":5,"bbox":[67.44,152.16,558.0,704.04],"n_rows":8,"n_cols":2,"columns":["Date:","September 27, 2021"],"rows":[["Date:","September 27, 2021"],["Submitter:","GE Healthcare, (GE Medical Systems, LLC)\n3000 N. Grandview Blvd\nWaukesha, WI 53188 USA"],["Primary\nContact\nPerson:","Chris Paulik\nRegulatory Affairs Program Manager\nGE Healthcare\n262-894-5415\nChristopher.A.Paulik@ge.com"],["Secondary\nContact\nPerson:","Diane Uriell\nRegulatory Affairs Director\nGE Healthcare\n262-290-8218\nDiane.Uriell@ge.com"],["Device Trade\nName:","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm"],["Common /\nUsual Name:","Automated Radiological Image Processing Software"],["Classification\nNames and\nProduct Code:","Regulation Name: Medical Image Management and Processing System\nRegulation: 21 CFR 892.2050\nClassification: Class II\nProduct Codes: QIH"],["Predicate\nDevice:","QLAB Advanced Quantification Software (K191647)\nRegulation Name: Picture archiving and communications system\nRegulation: 21 CFR 892.2050\nClassification: Class II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211161-p6-t0","doc_id":"K211161","page_num":6,"bbox":[67.44,103.68,558.0,706.44],"n_rows":5,"n_cols":2,"columns":["","Product Codes: QIH"],"rows":[["","Product Codes: QIH"],["Reference\nDevice:","Critical Care Suite (K183182)\nRegulation Name: Radiological computer aided triage and notification software\nRegulation: 21 CFR 892.2080\nClassification: Class II\nProduct Codes: QFM"],["Device\nDescription:","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm is an additional AI\nAlgorithm incorporated into the Critical Care Suite software previously cleared under\nK183182. It introduces the Endotracheal Tube Positioning AI Algorithm which is a\nquantification tool that analyzes frontal chest x-ray images and based on the data in the\nimage determines the location of the tip of an intubated patient’s endotracheal tube,\ndetermines the location of the carina, and then calculates and displays the vertical\ndistance between them. The distance provided is within the x-ray detector imaging\nplane and does not take into account the geometric magnification resultant from the\ngeometry of the x-ray acquisition based on source to image distance (SID), patient size,\nor any impacts due to patient rotation or tube rotation. This information can aide\nclinical care teams and radiologists to determine the proper placement of the\nendotracheal tube in an intubated patient. All algorithms previously cleared under\nK183182 are still available with Critical Care Suite, including the Pneumothorax Detection\nAlgorithm for triage and notification.\nThe benefit of the proposed modification is not specific to the platform on which it is\ndeployed. This benefit applies to all previously cleared computational platforms for\nCritical Care Suite, including PACS, On Premise, On Cloud and Digital Projection\nRadiographic Systems. The Optima XR240amx was chosen as the initial platform for\ndeployment because endotracheal tube placement images are almost exclusively\nacquired on mobile X-ray systems due to the immobilization of the patients being\nintubated with an endotracheal tube."],["Intended Use:","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm is intended to\nprovide automated radiological image processing and analysis tools implementing\nartificial intelligence including nonadaptive machine learning algorithms trained with\nclinical and/or artificial data."],["Indications for\nUse:","Critical Care Suite is a suite of AI algorithms for the automated image analysis of frontal\nchest X-rays acquired on a digital x-ray system.\nCritical Care Suite with the Endotracheal Tube Positioning AI algorithm produces an on-\nscreen image overlay that detects and localizes an endotracheal tube, locates the\nendotracheal tube tip, locates the carina, and automatically calculates the vertical\ndistance between the endotracheal tube tip and carina. This information is also\ntransmitted to the radiologist for review."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211161-p7-t0","doc_id":"K211161","page_num":7,"bbox":[67.44,103.68,558.0,470.4],"n_rows":2,"n_cols":2,"columns":["","Intended users include licensed qualified healthcare professionals (HCPs) trained to\nindependently place and/or assess endotracheal tube placement and radiologists.\nCritical Care Suite with Endotracheal Tube Positioning AI Algorithm should not be used\nin-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is\nnot intended to replace the review of the X-ray image by a qualified healthcare\nprofessional. Critical Care Suite with the Endotracheal Tube Positioning AI Algorithm is\nindicated for adult-size patients."],"rows":[["","Intended users include licensed qualified healthcare professionals (HCPs) trained to\nindependently place and/or assess endotracheal tube placement and radiologists.\nCritical Care Suite with Endotracheal Tube Positioning AI Algorithm should not be used\nin-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is\nnot intended to replace the review of the X-ray image by a qualified healthcare\nprofessional. Critical Care Suite with the Endotracheal Tube Positioning AI Algorithm is\nindicated for adult-size patients."],["Technology:","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm employs the same\nfundamental scientific technology as its predicate device. It is a deep learning locked AI\nalgorithm that can be deployed on several computing platforms such as PACS, On\nPremise, On Cloud or Imaging Systems. The patient and user populations are identical to\nwhat is provided with Critical Care Suite, adult-sized patients. The Endotracheal Tube\nPositioning AI Algorithm is an automated radiological image processing and analysis tool,\nwhich is equivalent to the image analysis and quantification algorithms provided in the\nQLAB Advanced Quantification Software.\nThe differences between Critical Care Suite with Endotracheal Tube Positioning AI\nAlgorithm and QLAB Advanced Quantification Software are the acquisition systems that\nprovide the images as well as the specific anatomies that are being analyzed. Critical\nCare Suite with Endotracheal Tube Positioning AI Algorithm analyzes chest radiographic\nimages where QLAB Advanced Quantification Software analyzes ultrasound images of\nthe heart. This difference does not impact the safety or efficacy of Critical Care Suite\nwith Endotracheal Tube Positioning AI Algorithm since both devices analyze images using\ndeep learning AI technology to identify/visualize anatomical structure and then provide\nquantification measurements based on that data to aide qualified healthcare\nprofessionals trained on endotracheal tube placement and radiologists."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211161-p7-t1","doc_id":"K211161","page_num":7,"bbox":[67.44,485.52,558.0,679.2],"n_rows":4,"n_cols":3,"columns":["Product Device\nComparison","Critical Care Suite with Endotracheal Tube\nPositioning AI Algorithm","QLAB Advanced Quantification Software\n(K191647)"],"rows":[["Product Device\nComparison","Critical Care Suite with Endotracheal Tube\nPositioning AI Algorithm","QLAB Advanced Quantification Software\n(K191647)"],["Device\nClassification","Picture archiving and communications system\nClass II, QIH","Picture archiving and communications system\nClass II, QIH"],["Targeted clinical\ncondition,\nanatomy, and\nimaging modality","Endotracheal Tube Positioning Visualization and\nQuantification\nChest/Lung\nFrontal Chest X-Ray Imaging","Right Ventricle Visualization and Quantification\nHeart\nUltrasound Heart Imaging"],["Algorithm\nInferencing\nMechanism","AI deep learning algorithms designed to visualize\nand quantify endotracheal tube positioning in\nfrontal chest X-ray images","AI deep learning algorithm designed to visualize and\nquantify the right ventricle within heart ultrasound\nimages"]],"caption_candidate":"professionals trained on endotracheal tube placement and radiologists.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211161-p9-t0","doc_id":"K211161","page_num":9,"bbox":[67.44,103.68,558.0,573.24],"n_rows":2,"n_cols":2,"columns":["","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm specific verification\nwas conducted to demonstrate proper implementation of Critical Care Suite software\ndesign requirements.\nRegression testing on the Optima XR240amx feature functionality was conducted to\nverify proper integration of Critical Care Suite with Endotracheal Tube Positioning AI\nAlgorithm into the Optima XR240amx software and device. Validation was performed on\nOptima XR240amx with integrated Critical Care Suite with Endotracheal Tube Positioning\nAI Algorithm.\nDesign verification and validation testing was performed to confirm that the safety and\neffectiveness of the device has not been affected. The test plans and results have been\nexecuted with acceptable results.\nSummary of Clinical Tests:\nThe performance of the Endotracheal Tube Positioning AI Algorithm was tested against a\nground truth dataset. The ground truth dataset contained a sufficient number of images\nto adequately analyze all the primary and secondary endpoints and the results met the\ndefined passing criteria.\nThe Endotracheal Tube Positioning AI Algorithm achieved an AUC of 0.9999 (0.9998,\n1.0000), a sensitivity of 0.9941 (0.9859, 1.0000) and a specificity of 1.0000 (1.0000,\n1.0000) for ETT detection. Additionally, the Endotracheal Tube Positioning AI Algorithm\nachieved an ETT tip to Carina distance measurement success rate of 0.9851 (0.9722,\n0.9981), a carina localization success rate 0.9851 (0.9722, 0.9981), an ETT tip localization\nsuccess rate of 0.9524 (0.9296, 0.9752) and an ETT localization success rate (DICE) of\n0.9881 (0.9765, 0.9997)."],"rows":[["","Critical Care Suite with Endotracheal Tube Positioning AI Algorithm specific verification\nwas conducted to demonstrate proper implementation of Critical Care Suite software\ndesign requirements.\nRegression testing on the Optima XR240amx feature functionality was conducted to\nverify proper integration of Critical Care Suite with Endotracheal Tube Positioning AI\nAlgorithm into the Optima XR240amx software and device. Validation was performed on\nOptima XR240amx with integrated Critical Care Suite with Endotracheal Tube Positioning\nAI Algorithm.\nDesign verification and validation testing was performed to confirm that the safety and\neffectiveness of the device has not been affected. The test plans and results have been\nexecuted with acceptable results.\nSummary of Clinical Tests:\nThe performance of the Endotracheal Tube Positioning AI Algorithm was tested against a\nground truth dataset. The ground truth dataset contained a sufficient number of images\nto adequately analyze all the primary and secondary endpoints and the results met the\ndefined passing criteria.\nThe Endotracheal Tube Positioning AI Algorithm achieved an AUC of 0.9999 (0.9998,\n1.0000), a sensitivity of 0.9941 (0.9859, 1.0000) and a specificity of 1.0000 (1.0000,\n1.0000) for ETT detection. Additionally, the Endotracheal Tube Positioning AI Algorithm\nachieved an ETT tip to Carina distance measurement success rate of 0.9851 (0.9722,\n0.9981), a carina localization success rate 0.9851 (0.9722, 0.9981), an ETT tip localization\nsuccess rate of 0.9524 (0.9296, 0.9752) and an ETT localization success rate (DICE) of\n0.9881 (0.9765, 0.9997)."],["Determination\nof Substantial\nEquivalence:","The introduction of Critical Care Suite with Endotracheal Tube Positioning AI Algorithm\ndoes not result in any new potential safety risks, and has the same technological\ncharacteristics, and performs as well as the predicate devices currently on the market.\nAfter analyzing design verification and validation testing on the bench it is the conclusion\nof GE Healthcare that the Critical Care Suite with Endotracheal Tube Positioning AI\nAlgorithm software to be as safe, as effective, and performance is substantially\nequivalent to the predicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211179-p4-t0","doc_id":"K211179","page_num":4,"bbox":[72.27,610.7,539.98,710.73],"n_rows":7,"n_cols":2,"columns":["Primary Predicate",""],"rows":[["Primary Predicate",""],["Trade Name","BriefCase"],["510(k) Submitter/Holder","Aidoc"],["Class","Class II"],["Regulation Number","21 CFR 892.2080"],["Classification Panel","Radiology"],["Product Code","QAS"]],"caption_candidate":"Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211179-p7-t0","doc_id":"K211179","page_num":7,"bbox":[72.33,224.22,720.93,528.73],"n_rows":3,"n_cols":8,"columns":["Item","","InferRead CT Stroke.AI","","","Aidoc Briefcase ICH (K180647)","","Comparison"],"rows":[["Item","","InferRead CT Stroke.AI","","","Aidoc Briefcase ICH (K180647)","","Comparison"],["","","(Subject Device)","","","(Predicate Device)","",""],["Intended Use /\nIndications for Use","InferRead CT Stroke.AI is a\nradiological computer aided triage\nand notification software for use in\nthe analysis of Non-Enhanced Head\nCT images. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging suspected positive findings\nof intracranial hemorrhage (ICH).\nInferRead CT Stroke.AI uses an\nartificial intelligence algorithm to\nanalyze images and highlight cases\nwith detected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith a worklist with marked cases of\nsuspected ICH findings. The device\ndoes not alter the original medical","","","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of non-\nenhanced head CT images. The device is\nintended to assist hospital networks and\ntrained radiologists in workflow triage\nby flagging and communication of\nsuspected positive findings of\npathologies in head CT images, namely\nIntracranial Hemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with\ndetected ICH on a standalone desktop\napplication in parallel to the ongoing\nstandard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected ICH","","","InferRead CT Stroke.AI\nand the previously cleared\nBriefCase (K180647)\nhave the same intended\nuse and\\indications for use\nin terms of finding\nsuspected intracranial\nhemorrhage in non\ncontrast head CT, flagging\nsuspected cases, and\nindicating the case to the\nattention of the clinician."]],"caption_candidate":"Detailed Comparison of the Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211179-p8-t0","doc_id":"K211179","page_num":8,"bbox":[72.27,72.28,720.98,530.23],"n_rows":5,"n_cols":4,"columns":["","image, does not remove cases from\nqueue, and is not intended to be used\nas a diagnostic device. If the clinician\ndoes not view the case, or if a case is\nnot flagged, cases remain to be\nprocessed per the standard of care.\nThe results of InferRead CT\nStroke.AI are intended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","findings. Notifications include\ncompressed preview images that are\nmeant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation and based on professional\njudgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.",""],"rows":[["","image, does not remove cases from\nqueue, and is not intended to be used\nas a diagnostic device. If the clinician\ndoes not view the case, or if a case is\nnot flagged, cases remain to be\nprocessed per the standard of care.\nThe results of InferRead CT\nStroke.AI are intended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","findings. Notifications include\ncompressed preview images that are\nmeant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation and based on professional\njudgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.",""],["User Population","Radiologist","Radiologist","Both are designed to be\nused by the radiologist,\nprompt the radiologist to\nstart preemptive triage of\na flagged case"],["Anatomical Region\nof Interest","Head","Head","Both are indicated for use\nin analysis of non-\nenhanced head CT"],["Data Acquisition\nProtocol","Non contrast CT scan of the head","Non contrast CT scan of the head or\nneck","Both are indicated for use\nin analysis of non-\nenhanced head CT"],["View DICOM data","DICOM information about the\npatient, study and current image","DICOM information about the patient,\nstudy and current image","Both display DICOM\ninformation for\ninformational purposes\nonly"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211179-p9-t0","doc_id":"K211179","page_num":9,"bbox":[72.27,72.28,720.98,447.93],"n_rows":6,"n_cols":4,"columns":["Segmentation of\nregion of interest","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image","Neither marks, highlights\nor directs attention to a\nspecific location in the\noriginal image"],"rows":[["Segmentation of\nregion of interest","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image","Neither marks, highlights\nor directs attention to a\nspecific location in the\noriginal image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images","Both use artificial\nintelligence algorithm\nwith a database of images"],["Notification /\nPrioritization","Yes, Case level indicator","Yes, pop-up notifications, case level\nindicator","In both, the suspected\ncases are indicated to the\nuser. The subject device\nprovides case level\nindicator and allow the\nuser to sort suspected\ncases to the top."],["Preview Images","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases","Both allow the user to\nview the image. The\ndevice is intended to work\nin parallel with standard\nof care."],["Alteration of\noriginal image","No","No","Neither alters the original\nimage."],["Removal of cases\nfrom worklist\nqueue","No","No","Neither removes cases\nfrom the worklist queue."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p4-t0","doc_id":"K211222","page_num":4,"bbox":[108.3,336.6,522.98,496.15],"n_rows":6,"n_cols":2,"columns":["Name of Device:","qER-Quant"],"rows":[["Name of Device:","qER-Quant"],["Common or Usual Name:","Automated Radiological Image Processing Software"],["Classification Name:","Medical image management and processing system"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2050"],["Product Code:","QIH"]],"caption_candidate":"1.2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p4-t1","doc_id":"K211222","page_num":4,"bbox":[108.3,548.9,522.98,628.67],"n_rows":3,"n_cols":2,"columns":["Name of Device:","Icobrain"],"rows":[["Name of Device:","Icobrain"],["Manufacturer:","Icometrix NV"],["510(k) Number:","K181939"]],"caption_candidate":"1.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p7-t0","doc_id":"K211222","page_num":7,"bbox":[72.3,72.4,547.21,765.63],"n_rows":5,"n_cols":3,"columns":["","qER-Quant Device\nSubject Device","Predicate Device"],"rows":[["","qER-Quant Device\nSubject Device","Predicate Device"],["Intended Use/\nIndications for Use","The qER-Quant device is intended for\nautomatic labeling, visualization and\nquantification of segmentable brain\nstructures from a set of Non-Contrast\nhead CT (NCCT) images. The software is\nintended to automate the current\nmanual process of identifying, labeling\nand quantifying the volume of\nsegmentable brain structures identified\non NCCT images.\nqER-Quant provides volumes from NCCT\nimages acquired at a single time point\nand provides a table with comparative\nanalysis for two or more images that\nwere acquired on the same scanner with\nthe same image acquisition protocol for\nthe same individual at multiple time\npoints.\nThe qER-Quant software is indicated for\nuse in the analysis of the following\nstructures: Abnormal Intracranial\nHyperdensities, Lateral Ventricles and\nMidline Shift.","The Icobrain device is intended for\nautomatic labeling, visualization and\nvolumetric quantification of segmentable\nbrain structures from a set of MR or NCCT\nimages. This software is intended to\nautomate the current manual process of\nidentifying, labeling and quantifying the\nvolume of segmentable brain structures\nidentified on MR or NCCT images.\nIcobrain consists of two distinct image\nprocessing pipelines: icobrain cross and\nicobrain long.\nicobrain cross is intended to provide\nvolumes from MR or NCCT images acquired\nat a single time point.\nicobrain long is intended to provide changes\nin volumes between two MR images that\nwere acquired on the same scanner, with\nthe same image acquisition protocol and\nwith same contrast at two different\ntimepoints.\nThe results of icobrain cross cannot be\ncompared with the results of icobrain long."],["Technological\nCharacteristics","- Software package\n- Operates on off-the-shelf hardware\n(multiple vendors)\n- DICOM compatible\n- Segmentation by deep learning\n(supervised voxel classification with\nConvolutional Neural Networks)","- Software package\n- Operates on off-the-shelf hardware\n(multiple vendors)\n- DICOM compatible\n- Segmentation by classical machine\nlearning and deep learning (supervised\nvoxel classification with Convolutional\nNeural Networks)"],["Output","Multiple electronic reports with\nvolumetric information of brain\nstructures and midline shift AND\nAnnotated DICOM Images","Multiple electronic reports with volumetric\ninformation of brain structures and midline\nshift AND\nAnnotated DICOM Images"],["Reference\nStandard for\nPerformance\ntesting","Accuracy\nManually labeled images for all\nstructures\nReproducibility","Accuracy\nManually labelled or simulated ground truth\nfor MRI images\nManually labeled images (lesions and\nmidline shift) and images labeled by\npreviously cleared Icobrain MRI software for\nCT images (lateral ventricles and whole\nbrain)\nReproducibility"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p8-t0","doc_id":"K211222","page_num":8,"bbox":[72.55,72.4,547.21,298.35],"n_rows":5,"n_cols":3,"columns":["","qER-Quant Device\nSubject Device","Predicate Device"],"rows":[["","qER-Quant Device\nSubject Device","Predicate Device"],["","Test-retest images","MRI measurement changes compared on\ntest-retest images; simulation study used\nfor CT measurements"],["Comparison of Differences between qER-Quant and the predicate device","",""],["Input Images","Non-contrast CT from a single or\nmultiple time points","T1-weighted and fluid-attenuated inversion\nrecovery (FLAIR) MR images from a single or\nmultiple time points and/or\nNon-contrast CT from a single time point"],["Target structures\nanalyzed on NCCT\nscans","Intracranial hyperdensities, lateral\nventricles and midline shift","Intracranial hyperdensities, lateral\nventricles, basal cisterns and midline shift"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p8-t1","doc_id":"K211222","page_num":8,"bbox":[72.55,591.51,518.61,757.32],"n_rows":6,"n_cols":10,"columns":["","Absolute error versus ground truth\n(volume in ml or shift in mm)","","","","","","Dice Score","",""],"rows":[["","Absolute error versus ground truth\n(volume in ml or shift in mm)","","","","","","Dice Score","",""],["Structure (Number of Scans)","","Mean (Standard","","","Median (10th -","","","Mean (95%",""],["","","Deviation)","","","90th percentile)","","","confidence interval)",""],["Intracranial Hyperdensity (183)","6.56 (7.33) ml","","","3.98 (0.52 - 17.35)\nml","","","0.75 (0.72 - 0.78)","",""],["Midline Shift (188)","1.37 (1.23) mm","","","","1.15 (0.23 - 2.59)","","Not applicable","",""],["","","","","","mm","","","",""]],"caption_candidate":"Table 2: Results of performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211222-p9-t0","doc_id":"K211222","page_num":9,"bbox":[72.64,72.62,518.62,154.89],"n_rows":3,"n_cols":6,"columns":["Left Lateral Ventricle (210)","2.09 (1.88) ml","1.60 (0.29 - 4.24)\nml","","","0.79 (0.78 - 0.81)"],"rows":[["Left Lateral Ventricle (210)","2.09 (1.88) ml","1.60 (0.29 - 4.24)\nml","","","0.79 (0.78 - 0.81)"],["Right Lateral Ventricle (210)","2.18 (1.72) ml","","1.88 (0.40 - 4.53)","","0.75 (0.73 - 0.77)"],["","","","ml","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211279-p5-t0","doc_id":"K211279","page_num":5,"bbox":[72.26,541.03,523.18,716.62],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],"rows":[["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],["Intended Use","VolparaDensity is a software\napplication intended for use with the\nraw data from digital breast x-ray\nsystems, including tomosynthesis.\nVolparaDensity calculates and\nquantifies a density map and from\nthat determines volumetric breast\ndensity as a ratio of fibroglandular\ntissue and total breast volume\nestimates. Volpara provides these","Volpara Imaging Software1 is a\nsoftware application intended for use\nwith the raw data from digital breast\nx-ray systems, including\ntomosynthesis. Volpara Imaging\nSoftware calculates and quantifies a\ndensity map and from that\ndetermines volumetric breast density\nas a ratio of fibroglandular tissue and\ntotal breast volume estimates."]],"caption_candidate":"Table 1. Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211279-p6-t0","doc_id":"K211279","page_num":6,"bbox":[72.26,99.02,523.18,708.94],"n_rows":10,"n_cols":3,"columns":["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],"rows":[["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],["","numerical values along with a BI-RADS\nbreast density 4th or 5th Edition\ncategory to aid health care\nprofessionals in the assessment of\nbreast tissue composition.\nVolparaDensity is not an interpretive\nor diagnostic aid and should be used\nonly as adjunctive information when\nthe final assessment of breast density\ncategory is made by an MQSA-\nqualified interpreting physician.","Volpara Imaging Software provides\nthese numerical values along with a\nBI-RADS breast density 4th or 5th\nEdition category and quality\nassurance metrics (i.e., dose and\npressure) to aid healthcare\nprofessionals in the assessment of\nbreast composition. Volpara Imaging\nSoftware is not a diagnostic aid and\nshould be used only as adjunctive\ninformation when the final\nassessment of breast density category\nis made by an MQSA-qualified\ninterpreting physician."],["Intended Users","Health Care Professionals","Health Care Professionals"],["Image Source","Digital mammography images","Digital mammography images"],["Image Sources","Digital mammograms from\nmammography or tomosynthesis\nsystems, including those obtained\nusing with curved paddles.","Digital mammograms from\nmammography or tomosynthesis\nsystems, including those obtained\nusing with curved paddles."],["Anatomical\nArea","Breast","Breast"],["Assessment\nScope","Volumetric","Volumetric"],["Operating\nEnvironment","Windows/Linux2","Windows/Linux"],["Image Storage\nand Report\nGeneration","Yes; output to console","Yes; output to console"],["Numeric Output","• Volume of Fibroglandular tissue\n• Volume of Breast\n• Volumetric Breast Density\n• BIRADS 4th or 5th Edition Breast\nDensity Category, with\nhighlighting above a certain\nvolumetric threshold or if focal\ndensity present\n• Average thickness of dense tissue\n• Maximum thickness of dense\ntissue (and location)","• Volume of Fibroglandular tissue\n• Volume of Breast\n• Volumetric Breast Density\n• BIRADS 4th or 5th Edition Breast\nDensity Category, with\nhighlighting above a certain\nvolumetric threshold or if focal\ndensity present\n• Average thickness of dense tissue\n• Maximum thickness of dense\ntissue (and location)"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211279-p7-t0","doc_id":"K211279","page_num":7,"bbox":[72.26,99.02,523.18,284.81],"n_rows":5,"n_cols":3,"columns":["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],"rows":[["","Predicate Device\nVolpara Imaging Software 1.5.6\n(K182310)","Submission Device\nVolpara Imaging Software 3.2"],["","• Maximum volume of dense tissue\nabove any 1 cm2 square region\n(and location)\n• Image quality assessment metrics","• Maximum volume of dense tissue\nabove any 1 cm2 square region\n(and location)\n• Image quality assessment metrics"],["Image Output","Density map in DICOM SCI format, for\nvisualization as user specifies","Density map in DICOM SCI format, for\nvisualization as user specifies"],["Classification","21 CFR 892.2050; LLZ","21 CFR 892.2050; LLZ"],["Level of\nConcern","Moderate","Moderate"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211379-p6-t0","doc_id":"K211379","page_num":6,"bbox":[71.06,197.2,524.14,782.64],"n_rows":6,"n_cols":6,"columns":["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],"rows":[["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],["Reference\nPoint\nManagement","","","Reference Point Management allows to edit the position, color, and type\nof Points of Interest (POI).\nModification:\nThe workflow for POI creation and editing has been slightly adapted to improve\nusability without modification of the functionality.","",""],["Patient\nMarking","","","Transmission of reference points with the offset details to a movable laser system\nfor patient marking.\nModification:\n• Saving of sent POIs\n• Removal of default value for laser calibration offset\n• Consistency checks for laser calibration offset (only for integrated laser)\n• Minor usability improvements","",""],["Contouring\n(Routine\nContouring)","","","With Contouring, the user can create, delete, and edit Volumes of Interest (VOIs).\nModification:\nThe routine contouring feature has been enhanced for the subject device to\ninclude a tool to cut a structure at a user-defined axial level.","",""],["Structure Set\nManagement","","","• Loading and storing of DICOM RT structure sets, creating, editing and deletion\nof structures and POIs.\n• Creating, editing and deletion of structure templates.\n• Customize predefined structure database with mapping to international\nnomenclature schemes.\nModifications:\nThe Structure Set Management provides a set of improvements to optimize the\nworkflow including:\n• Structure Set approval\n• Enhanced color picker\n• Structure sorting by type\n• Manual and automated merging of structure sets\n• Streamlined rapid results configuration\n• Filter for auto-contourable structures\n• Merge / expand structure via structure templates","",""],["Synthetic CT","","","The synthetic CT feature provides functionality to create a CT-density equivalent\nimage series out of multiple MR-image-series.\nModification:\nThe algorithm for brain and pelvis synthetic CTs has been changed from Atlas\nbased to a deep-learning algorithm.","",""]],"caption_candidate":"provided as Table 4 below for the software version SOMARIS/8 VB60:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211379-p7-t0","doc_id":"K211379","page_num":7,"bbox":[76.56,81.75,221.48,143.31],"n_rows":5,"n_cols":2,"columns":["Basic Feature","The set provid"],"rows":[["Basic Feature","The set provid"],["of syngo.via",""],["RT Image Suite","Modification:"],["","For the subject"],["","workflow have"]],"caption_candidate":"Basic Feature The set provides basic feature of the subject device.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K211379-p8-t0","doc_id":"K211379","page_num":8,"bbox":[70.83,655.41,524.37,782.88],"n_rows":6,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2015-06 (Edition 1.1)","01/14/2019","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Second\nEdition 2007-03-01","06/27/2016","ISO","",""]],"caption_candidate":"covering electrical and mechanical safety listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211379-p9-t0","doc_id":"K211379","page_num":9,"bbox":[70.85,76.89,524.36,150.6],"n_rows":4,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"Traditional: 510(k): syngo.via RT Image Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211443-p4-t0","doc_id":"K211443","page_num":4,"bbox":[90.05,117.32,360.58,667.47],"n_rows":37,"n_cols":2,"columns":["Contact:","Howard Schrayer"],"rows":[["Contact:","Howard Schrayer"],["","AIbolit Technologies, LL"],["","9616 Moritz Way"],["","Delray Beach, FL 33446"],["",""],["","Telephone: 609-273-73"],["","hs.ss@lucidmedical.net"],["",""],["Date Prepared:","January 7, 2022"],["",""],["Device Trade Name:","AIBOLIT 3D+"],["",""],["Manufacturer:","AIbolit Technologies, LL"],["","9616 Moritz Way"],["","Delray Beach, FL 33446"],["",""],["Common Name:","Automated Radiological"],["","Medical image manage"],["",""],["Classification:","Class II"],["",""],["Product Code:","QIH - LLZ"],["",""],["Regulation:","21 CFR 892.2050"],["",""],["Predicate Devices:",""],["",""],["Primary Predicate",""],["","Ceevra, Inc."],["","Ceevra Reveal 2.0"],["","Image Processing Syste"],["","[510(k) K173274]"],["",""],["Reference Predicate",""],["","Intuitive Surgical, Inc."],["","IRIS 1.0 System"],["","[510(k) K182643]"]],"caption_candidate":"Contact: Howard Schrayer","well_formed":true,"extraction_settings":"text"}
{"table_id":"K211443-p6-t0","doc_id":"K211443","page_num":6,"bbox":[90.31,102.15,580.74,715.98],"n_rows":9,"n_cols":9,"columns":["","Manufacturer","","","AIbolit Technologies, LLC","","","Ceevra",""],"rows":[["","Manufacturer","","","AIbolit Technologies, LLC","","","Ceevra",""],["Trade Name","","","AIBOLIT 3D+\nImage Processing System","","","Ceevra Reveal 2.0\nImage Processing System","",""],["510(k) Number","","","Subject Device - TBD","","","K173274","",""],["Type of Device/\nProduct Code /","","","Radiological Image\nProcessing System / QIH -\nLLZ","","","Radiological Image Processing\nSystem / LLZ","",""],["Regulation / Class","","","21 CFR 892.2050 – Class II","","","21 CFR 893.2050 – Class II","",""],["Indications for Use","","","Aibolit 3D+ is intended as a\nmedical imaging system that\nallows the processing, review,\nanalysis, communication and\nmedia interchange of multi-\ndimensional digital images\nacquired from CT imaging\ndevices. It is also intended as\nsoftware for preoperative\nsurgical planning, training,\npatient information and as\nsoftware for the intraoperative\ndisplay of the multidimensional\ndigital images. Aibolit 3D+ is\ndesigned for use by health\ncare professionals and is\nintended to assist the clinician\nwho is responsible for making\nall final patient management\ndecisions.","","","Ceevra Reveal 2.0 is intended as\na medical imaging system that\nallows the processing, review,\nanalysis, communication\nand media interchange of multi-\ndimensional digital images\nacquired from CT or MR imaging\ndevices. It is also intended as\nsoftware for preoperative surgical\nplanning, and as software for the\nintraoperative display of the\naforementioned multidimensional\ndigital images. Ceevra Reveal 2.0\nis designed for use by health care\nprofessionals and is intended to\nassist the clinician who is\nresponsible for making all final\npatient management decisions.","",""],["Mechanism of\nAction","","","Capture and enhancement of\n(DICOM) digital video images\nvia software-based conversion\nto 2-D and 3-D anatomical\nstructure images that can be\nmanipulated for viewing","","","Capture and enhancement of\n(DICOM) digital video images via\nsoftware-based conversion to 2-D\nand 3-D anatomical structure\nimages that can be manipulated\nfor viewing","",""],["Intended Users","","","Health care professionals","","","Health care professionals","",""],["Intended Use\nEnvironment","","","Healthcare facilities such as\nhospitals and clinics","","","Healthcare facilities such as\nhospitals and clinics","",""]],"caption_candidate":"Predicate Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211443-p7-t0","doc_id":"K211443","page_num":7,"bbox":[90.3,72.28,580.75,697.48],"n_rows":7,"n_cols":3,"columns":["Format of Captured\nImages","DICOM","DICOM"],"rows":[["Format of Captured\nImages","DICOM","DICOM"],["Intended Use","AIBOLIT 3D+ is intended for\nuse as a medical imaging\nsystem that allows the\nprocessing, review, analysis,\ncommunication and media\ninterchange of multi-\ndimensional digital images\nacquired from CT imaging\ndevices. It is also intended as\nsoftware for preoperative\nsurgical planning, and as\nsoftware for the intraoperative\ndisplay of multi- dimensional\ndigital images. AIBOLIT 3D+\nis designed for use by health\ncare professionals and is\nintended to assist the clinician\nwho is responsible for making\npatient management\ndecisions.","Intended as a medical imaging\nsystem that allows the\nprocessing, review, analysis,\ncommunication and media\ninterchange of multi- dimensional\ndigital images acquired from CT\nor MR imaging devices. It is also\nintended as software for\npreoperative surgical planning,\nand as software for the\nintraoperative display of the\naforementioned multi-\ndimensional digital images.\nCeevra Reveal 2.0 is designed for\nuse by health care professionals\nand is intended to assist the\nclinician who is responsible for\nmaking all final patient\nmanagement decisions."],["Security","Data coded and HIPAA\ncompliant","Data coded and HIPAA compliant"],["Form of Device","AIBOLIT 3D+ is a software\nonly device that permits\nelectronic image uploads,\nprovides image conversion\nand allows viewing on a\nmobile device or standard\ncomputer monitor.","The Ceevra Reveal 2.0 Video\nProcessor is a software only\ndevice that permits electronic\nimage uploads, provides image\nconversion and allows viewing on\na mobile device or standard\ncomputer monitor."],["Image processing","High-definition digital images\nup to 4K","High-definition digital images"],["Functions","Generation of 2D and 3D\nimages from DICOM data\nOrgan segmentation and\nstructure identification\nDimensional and volume\nreferences\nMulti-axis image rotation\nOrgan transparency\nOrgan retraction animation","Generation of 2D and 3D images\nfrom DICOM data\nOrgan segmentation and structure\nidentification\nDimensional and volume\nreferences\nMulti-axis image rotation"],["Body contact","None","None"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211443-p8-t0","doc_id":"K211443","page_num":8,"bbox":[90.11,72.28,580.75,714.98],"n_rows":13,"n_cols":3,"columns":["User Interface and\nSystem Work-Flow","Physician uploads DICOM\nimages and specifies desired\nanatomical segments of\ninterest\nRadiologist annotates sample\n(segments) images\nAI software facilitates\nannotation of available images\nunder guidance and control by\nthe Radiologist\nImaging technician generates\nmulti-axis rotatable image and\nretraction model\nRadiologist reviews images\ngenerated by imaging\ntechnician and returns output\nfile to requesting physician","Physician uploads DICOM images\nand specifies desired anatomical\nsegments of interest\nImaging technician annotates\nsample (segments) images\nImaging technician generates\nmulti-axis rotatable image and\nreturns output file to requesting\nphysician"],"rows":[["User Interface and\nSystem Work-Flow","Physician uploads DICOM\nimages and specifies desired\nanatomical segments of\ninterest\nRadiologist annotates sample\n(segments) images\nAI software facilitates\nannotation of available images\nunder guidance and control by\nthe Radiologist\nImaging technician generates\nmulti-axis rotatable image and\nretraction model\nRadiologist reviews images\ngenerated by imaging\ntechnician and returns output\nfile to requesting physician","Physician uploads DICOM images\nand specifies desired anatomical\nsegments of interest\nImaging technician annotates\nsample (segments) images\nImaging technician generates\nmulti-axis rotatable image and\nreturns output file to requesting\nphysician"],["External / Internet\nConnections","Web-based software","Web-based software"],["","",""],["CT Image\nUploading","By requesting physician","By requesting physician"],["","",""],["Other User Inputs","List of organ structures to be\nannotated and displayed,\npatient ID and demographics","List of organ structures to be\nannotated and displayed, patient\nID and demographics"],["","",""],["Image\nSegmentation","By Radiologist (MD) – Manual\nannotation is done for all CT\nslices with optional use of\nAI/ML algorithms as\ndetermined by Radiologist and\nwith Radiologist’s approval","By Imaging Technician – Manual\nannotation done for all CT slices –\nNo software used for annotation"],["","",""],["Organ\nidentification","By Radiologist","Unknown proprietary method\nused to identify organ structures"],["","",""],["3D Image\ngeneration","3D image file generated by 3rd\nparty software (3D Slicer)\nfollowing Radiologist review\nand approval of annotation","3D image file generated by 3rd\nparty software"],["","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211443-p9-t0","doc_id":"K211443","page_num":9,"bbox":[90.05,72.28,580.75,463.15],"n_rows":9,"n_cols":3,"columns":["Organ structure\nidentification","Proprietary software assigns\ncolor coding to each structure\nidentified by Radiologist and\ndisplays color-coded image\nwith labeled key to\ncolor/structure identity","Proprietary software assigns color\ncoding to each structure identified\nby imaging technician and\ndisplays color-coded image with\nkey to color/structure identity"],"rows":[["Organ structure\nidentification","Proprietary software assigns\ncolor coding to each structure\nidentified by Radiologist and\ndisplays color-coded image\nwith labeled key to\ncolor/structure identity","Proprietary software assigns color\ncoding to each structure identified\nby imaging technician and\ndisplays color-coded image with\nkey to color/structure identity"],["","",""],["Image editing\npermission","Only the radiologist can alter\nor edit images following review\n– User physicians cannot edit\nimages - Physicians have\noption to show or hide organs\non display","Imaging technician can edit\nimages generated by the system\nsoftware – User physicians\ncannot edit images - Physicians\nhave option to show or hide\norgans on display"],["","",""],["Device Output\nDevices","3D image can be displayed on\nstandard monitor","3D image can be displayed on\nstandard monitor, smart phone\n(with separate software) or Virtual\nImaging 3D headset"],["","",""],["Supplemental\noutputs","Organ structure dimensions,\nvolume, organ labels, patient\nID, CT date and demographics","Organ structure dimensions,\nvolume, organ labels, patient ID\nand demographics"],["","",""],["Output image\nmanipulation by\nuser","Physician user can show or\nhide individual organ\nstructures, zoom capability,\nrotational capability and\ntransparency capability","Physician user can show or hide\nindividual organ structures, zoom\ncapability, rotational capability,\ntransparency capability (current\nversion)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211459-p7-t0","doc_id":"K211459","page_num":7,"bbox":[95.9,111.93,539.56,315.31],"n_rows":6,"n_cols":6,"columns":["","Workflow","","","Workflow-specific Features",""],"rows":[["","Workflow","","","Workflow-specific Features",""],["MM Oncology Updated syngo.CT LungCAD Integration (K203258)","","","","",""],["MI Workflows Visualization of 4D data in all layouts\n(MI General, FAST Ranges Enhancements\nMI Cardiology, Auto Layout Improvements\nGaussian filtering of PET Data\nInteractive Spectral Imaging\nUsability Improvements","","","","",""],["MI Cardiology OpenApps framework for ISAs (including Cedars, Corridor\n4DM, and syngo MBF)\nSpill-Over Factors (within syngo MBF)\nAutomatic window/level for each frame (within syngo MBF)\nGlobal Time Activity Curve (within syngo MBF)","","","","",""],["MI Neurology","","","","Calibrated I123-FP-CIT normal databases in Striatal",""],["","","","","Analysis (within Striatal Analysis workflow of Scenium)",""]],"caption_candidate":"include the following new features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211506-p5-t0","doc_id":"K211506","page_num":5,"bbox":[48.24,473.16,530.64,632.88],"n_rows":6,"n_cols":3,"columns":["","UNMODIFIED Device\nPowerLook Density Assessment","MODIFIED Device\nPowerLook Density Assessment V4.0"],"rows":[["","UNMODIFIED Device\nPowerLook Density Assessment","MODIFIED Device\nPowerLook Density Assessment V4.0"],["Manufacturer","iCAD, Inc.","iCAD, Inc."],["Classification Name","System, Image Processing,\nRadiological","Medical Image Management and\nProcessing System"],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050"],["Product Code","LLZ","QIH"],["510(k) #","K180125","Pending"]],"caption_candidate":"Comparison with Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211506-p6-t0","doc_id":"K211506","page_num":6,"bbox":[48.24,72.24,530.64,665.4],"n_rows":10,"n_cols":3,"columns":["","UNMODIFIED Device\nPowerLook Density Assessment","MODIFIED Device\nPowerLook Density Assessment V4.0"],"rows":[["","UNMODIFIED Device\nPowerLook Density Assessment","MODIFIED Device\nPowerLook Density Assessment V4.0"],["Intended Use / Indication for\nUse","PowerLook Density Assessment is a\nsoftware application intended for use\nwith digital breast tomosynthesis\nsynthesized 2D images from\ntomosynthesis exams. PowerLook\nDensity Assessment provides an ACR\nBI-RADS Atlas 5th Edition breast\ndensity category to aid health care\nprofessionals in the assessment of\nbreast tissue composition. PowerLook\nDensity Assessment produces\nadjunctive information. It is not a\ndiagnostic aid.","PowerLook Density Assessment is a\nsoftware application intended for use\nwith digital breast tomosynthesis\nsynthesized 2D images from\ntomosynthesis exams. PowerLook\nDensity Assessment provides an ACR\nBI-RADS Atlas 5th Edition breast\ndensity category to aid health care\nprofessionals in the assessment of\nbreast tissue composition. PowerLook\nDensity Assessment produces\nadjunctive information. It is not a\ndiagnostic aid."],["End User","Radiologists","Radiologists"],["Patient Population","Symptomatic and asymptomatic women\nundergoing mammography.","Symptomatic and asymptomatic women\nundergoing mammography."],["Image Source Modalities","Synthetic views from tomosynthesis\nsystems","Synthetic views from tomosynthesis\nsystems"],["Input: Image Data Format","DICOM synthetic 2D images generated\nfrom breast tomosynthesis data","DICOM synthetic 2D images generated\nfrom breast tomosynthesis data"],["Output Format","DICOM structured report or DICOM\nsecondary capture.","DICOM structured report or DICOM\nsecondary capture."],["Output Data","For each patient:\n• ACR BI-RADS® Atlas 5th\nEdition breast density\ncategory\n• Fractional indication of\ndistance inside breast density\ncategory","For each patient:\n• ACR BI-RADS® Atlas 5th\nEdition breast density\ncategory\n• Fractional indication of\ndistance inside breast density\ncategory"],["Deployment","Standalone computer","Standalone computer"],["Supported Digital Breast\nTomosynthesis Systems","• Hologic Selenia\nDimensions/3Dimensions\n(C-View)\n• GE Senographe Essential\nwith SenoClaire (V-Preview)\n• GE Senographe Pristina (V-\nPreview)","• Hologic Selenia\nDimensions/3Dimensions\n(C-View)\n• GE Senographe Essential\nwith SenoClaire (V-Preview)\n• GE Senographe Pristina (V-\nPreview)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211541-p7-t0","doc_id":"K211541","page_num":7,"bbox":[72.32,653.82,539.74,683.11],"n_rows":2,"n_cols":6,"columns":["","Subject Device","Predicate Device","","Substantially",""],"rows":[["","Subject Device","Predicate Device","","Substantially",""],["","","","","Equivalent?",""]],"caption_candidate":"Technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211541-p8-t0","doc_id":"K211541","page_num":8,"bbox":[72.29,72.34,539.77,194.3],"n_rows":3,"n_cols":6,"columns":["","MammoScreen (K192854)","","MammoScreen","",""],"rows":[["","MammoScreen (K192854)","","MammoScreen","",""],["","","","2.0 (K211541)","",""],["Fundamental\nscientific\ntechnology","In MammoScreen, a range of medical image\nprocessing and machine learning techniques are\nimplemented. The system includes ‘deep learning’\nmodules for recognition of suspicious\ncalcifications and soft tissue lesions. These\nmodules are trained with very large databases of\nbiopsy-proven examples of breast cancer and\nnormal tissue.","SAME","","","Yes, identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211597-p7-t0","doc_id":"K211597","page_num":7,"bbox":[72.39,105.36,728.91,523.75],"n_rows":9,"n_cols":2,"columns":["Device","Indications for Use"],"rows":[["Device","Indications for Use"],["Philips EPIQ Series","The intended use of Philips EPIQ series diagnostic ultrasound systems is diagnostic ultrasound imaging and fluid flow analysis of\nthe human body, with the following indications for use:\nAbdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal),\nFetal/Obstetric, Gynecological, Intra-cardiac Echo, Intra-luminal, Intraoperative (Vascular), Intraoperative (Cardiac),\nMusculoskeletal (Conventional), Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ\n(Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal, Transvaginal, Lung.\nThe clinical environments where Philips EPIQ diagnostic ultrasound systems can be used include clinics, hospitals, and clinical\npoint-of-care for diagnosis of patients.\nWhen integrated with Philips EchoNavigator, the systems can assist the interventionalist and surgeon with image guidance during\ntreatment of cardiovascular disease in which the procedure uses both live X-ray and live echo guidance.\nThe systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating\ninstructions given in the product user information. Systems are to be operated only by appropriately trained healthcare\nprofessionals for the purposes for which they were designed. However, nothing stated in the user information reduces your\nresponsibility for sound clinical judgement and best clinical procedure."],["Diagnostic Ultrasound",""],["System",""],["",""],["Philips Affiniti Series","The intended use of the Affiniti Series Diagnostic Ultrasound Systems is diagnostic ultrasound imaging and fluid flow analysis of\nthe human body with the following Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal),\nFetal/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle),\nTransesophageal (Cardiac), Transrectal, Transvaginal, Lung.\nThe clinical environments where the Affiniti Diagnostic Ultrasound Systems can be used include Clinics, Hospitals, and clinical\npoint-of-care for diagnosis of patients.\nThe systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating\ninstructions given in the product user information. Systems are to be operated only by appropriately trained healthcare\nprofessionals for the purposes for which they were designed. However, nothing stated in the user information reduces your\nresponsibility for sound clinical judgment and best clinical procedure."],["Diagnostic Ultrasound",""],["System",""],["",""]],"caption_candidate":"V. Indications for Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211611-p7-t0","doc_id":"K211611","page_num":7,"bbox":[124.8,180.82,471.34,767.75],"n_rows":20,"n_cols":7,"columns":["Features","","QIR Suite v4.1","","","Segment CMR",""],"rows":[["Features","","QIR Suite v4.1","","","Segment CMR",""],["","","(MR)","","","(MR)",""],["Trade name","QIR Suite","","","Segment CMR","",""],["Applicant name","CASIS","","","Medviso AB","",""],["Regulation Name","Medical Image\nManagement and\nProcessing System","","","Picture archiving\nand communication\nsystem","",""],["510(k) number","K211611","","","K163076","",""],["CE marked","2017 – (CE 0459)","","","2014 – (CE 0413)","",""],["FDA Clearance date","TBD","","","April 5, 2017","",""],["Regulatory Class","II","","","II","",""],["Product code","QIH*\nAutomated\nradiological image\nprocessing software","","","LLZ\nSystem, image\nprocessing,\nradiological","",""],["Regulation","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Manufacturer","CASIS\n(France)","","","Medviso AB\n(Sweden)","",""],["1. Patient population","Adult","","","Pediatric and Adult","",""],["2. Receive, store, transmit,\npost process, display and\nallow manipulation of\nmedical MR images","Yes","","","Yes","",""],["3. Client/server functionality\nto connect to a PACS\n(Picture Archiving and\nCommunication System) and\nto activate software license.","Yes","","","Yes","",""],["4. Visualization of 2D and 2D\n+ time of single or multiple\ndatasets.","Yes","","","Yes","",""],["5. Segmentation of regions\nof interest.","Yes","","","Yes","",""],["6. Measurement of distance\nand area.","Yes","","","Yes","",""],["7. Cardiac function analysis\nincluding ejection fraction\nassessment, local\nmyocardial mass, thickness\nand thickening.","Yes","","","Yes","",""],["8. Aorta study including\nlength and area\nmeasurements, compliance,","Yes","","","Yes","",""]],"caption_candidate":"Table 1: Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211611-p8-t0","doc_id":"K211611","page_num":8,"bbox":[124.84,71.62,471.3,126.23],"n_rows":3,"n_cols":7,"columns":["Features","","QIR Suite v4.1","","","Segment CMR",""],"rows":[["Features","","QIR Suite v4.1","","","Segment CMR",""],["","","(MR)","","","(MR)",""],["regurgitant fraction, and\ndelay wave.","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211655-p4-t0","doc_id":"K211655","page_num":4,"bbox":[72.0,39.2,394.77,699.99],"n_rows":43,"n_cols":2,"columns":["510(k) Summary","K21 1655"],"rows":[["510(k) Summary","K21 1655"],["",""],["In accordance with 21 CFR 807",".87(h) and 21 CFR 807.92 the 510("],["is provided below.",""],["",""],["1. SUBMITTER",""],["",""],["Applicant:","EXINI Diagnostics AB"],["","Ideon Science Park"],["","Scheelevägen 27"],["","223 70 Lund"],["","Sweden"],["",""],["Contact:","Aseem Anand, Ph.D."],["","Vice President"],["","EXINI Diagnostics AB"],["","Ideon Science Park, Scheelevägen"],["","Lund, Sweden"],["","Tel: +46706604084"],["","aseem.anand@exini.com"],["",""],["Submission Correspondent:","Donna-Bea Tillman, Ph.D."],["","Senior Consultant"],["","Biologics Consulting"],["","1555 King Street, Suite 300"],["","Alexandria, Virginia 22314"],["","(410) 531-6542"],["","dtillman@biologicsconsulting.com"],["",""],["Date Prepared:","May 28, 2021"],["",""],["2. DEVICE",""],["",""],["Device Trade Name:","aPROMISE"],["Device Common Name:","Picture Archiving and Communica"],["Classification Name","21 CFR 892.2050 Medical Image"],["","Processing System"],["Regulatory Class:","II"],["Product Code:","LLZ"],["",""],["3. PREDICATE D","EVICE"],["",""],["Predicate Device:","Exini aBSI (K191262)"]],"caption_candidate":"510(k) Summary K211655","well_formed":true,"extraction_settings":"text"}
{"table_id":"K211678-p11-t0","doc_id":"K211678","page_num":11,"bbox":[155.21,117.73,586.43,507.12],"n_rows":10,"n_cols":3,"columns":["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],"rows":[["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],["Classification\nRegulation","21 CFR 892.2090\nRadiological Computer Assisted\nDetection and Diagnosis software","21 CFR 892.2090\nRadiological Computer Assisted\nDetection and Diagnosis software"],["Medical Device\nClassification","Class II","Class II"],["Product Code","QDQ","QDQ"],["Level of\nConcern","Moderate","Moderate"],["Intended Use","A reading aid for physicians\ninterpreting screening FFDM\nacquired with compatible\nmammography systems, to identify\nfindings and assess their level of\nsuspicion.","A reading aid for physicians\ninterpreting screening FFDM\nacquired with compatible\nmammography systems, to identify\nfindings and assess their level of\nsuspicion."],["Target patient\npopulation","Women undergoing FFDM screening\nmammography","Women undergoing FFDM screening\nmammography"],["Target user\npopulation","Physicians interpreting FFDM\nscreening mammograms","Physicians interpreting FFDM\nscreening mammograms"],["Design","Software-only device","Software-only device"],["Indication for\nUse","Lunit INSIGHT MMG is a radiological\nComputer-Assisted Detection and\nDiagnosis (CADe/x) software device\nbased on an artificial intelligence\nalgorithm intended to aid in the\ndetection, localization, and","The ScreenPoint Transpara™\nsystem is intended for use as a\nconcurrent reading aid for physicians\ninterpreting screening mammograms\nfrom compatible FFDM system, to\nidentify regions suspicious for breast"]],"caption_candidate":"Table 1 – Comparison Between Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211678-p12-t0","doc_id":"K211678","page_num":12,"bbox":[155.2,93.37,586.43,503.05],"n_rows":4,"n_cols":3,"columns":["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],"rows":[["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],["","characterization of suspicious areas\nfor breast cancer on mammograms\nfrom compatible FFDM systems. As\nan adjunctive tool, the device is\nintended to be viewed by interpreting\nphysicians after completing their\ninitial read. It is not intended as a\nreplacement for a complete\nphysician’s review or their clinical\njudgement that takes into account\nother relevant information from the\nimage or patient history. The Lunit\nINSIGHT MMG uses screening\nmammograms of the female\npopulation.","cancer and assess their likelihood of\nmalignancy. Output of the device\nincludes marks placed on suspicious\nsoft tissue lesions and suspicious\ncalcifications; region based scores,\ndisplayed upon the physician’s query,\nindicating the likeliho‐od that cancer is\npresent in specific regions; and an\noverall score indicating the likelihood\nthat cancer is present on the\nmammogram. Patient management\ndecisions should not be made solely\non the basis of analysis by\nTranspara™."],["Device output\nin case of\npositive\ndetection","Output of the device includes marks\nwith visualized map such as heatmap\nplaced on suspicious lesions for\nbreast cancer; lesion score,\nindicating the likelihood of presence\nof the malignancy in specific regions;\nand an abnormality score indicating\nthe likelihood of the presence of\nmalignancy per-breast in the\nmammogram. The per-breast\nabnormality score takes maximum\nscore from two views (i.e., CC, MLO)\nof a breast which is the maximum\nlesion score in the breast.","Output of the device includes marks\nin outlines placed on suspicious soft\ntissue lesions and suspicious\ncalcifications; region based scores,\ndisplayed upon the physician’s query,\nindicating the likeliho‐od that cancer is\npresent in specific regions; and an\noverall score indicating the likelihood\nthat cancer is present on the\nmammogram."],["Score","Finding level:","Finding level:"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211678-p13-t0","doc_id":"K211678","page_num":13,"bbox":[155.2,93.37,586.43,505.92],"n_rows":3,"n_cols":3,"columns":["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],"rows":[["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],["","Score 1-100 indicating likelihood of\npresence of malignancy (from low\nsuspicion to high suspicion).\nBreast level:\nScore 1-100 indicating the level of\nsuspicious of malignancy.\nThe maximum scores from two view\n(i.e., CC, MLO) of a breast which is\nthe maximum lesion score in the\nbreast\nExam level: None","Continuous score 1-100 indicating\nthe level of suspicion of malignancy\n(from low suspicion to high\nsuspicion).\nBreast level: None\nExam level: 10-point scale score\nindicative of higher frequency of\ncancer positive"],["Performance","Reader study:\n 240 cases\n 12 radiologists\ncf. Reading time was not measured\nin this study.\nROC AUC:\nradiologists AUC (unaided) = 0.754\nradiologists AUC (aided) = 0.805\nStandalone Performance Test:\n 2412 cases","Reader study:\n 240 cases\n 14 radiologists\nReading time:\n 146 seconds (unaided\nsession)\n 149 seconds (with\nTranspara™)\nAUC:\n radiologists AUC (unaided) =\n0.866\n radiologists AUC (aided) =\n0.886"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211678-p14-t0","doc_id":"K211678","page_num":14,"bbox":[155.2,93.37,586.43,369.37],"n_rows":4,"n_cols":3,"columns":["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],"rows":[["Technical\nCharacteristics","Subject Device\nLunit INSIGHT MMG","Predicate Device\nTranspara™ (K192287)"],["","ROC AUC = 0.903"," standalone AUC = 0.887"],["Image Source\nModality","FFDM","FFDM"],["Fundamental\nscientific\ntechnology","In Lunit INSIGHT MMG, a range of\nmedical image processing and\nmachine learning techniques are\nimplemented. The system includes\n‘deep learning’ algorithm applied to\nimages for recognition of suspicious\nlesions for breast cancer. The\nmachine learning components are\ntrained to detect suspicious lesions\nfor breast cancer with large\ndatabases of biopsy-proven cases of\nbreast cancer, benign lesions and\nnormal tissues.","In Transpara, a range of medical\nimage processing and machine\nlearning techniques are implemented.\nThe system includes ‘deep learning’\nalgorithm applied to images for\nrecognition of suspicious lesions for\nbreast cancer. The machine learning\ncomponents are trained to detect\nsuspicious lesions for breast cancer\nwith large databases of biopsy-\nproven cases of breast cancer,\nbenign lesions and normal tissues."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p3-t0","doc_id":"K211733","page_num":3,"bbox":[36.3,37.11,568.8,710.29],"n_rows":48,"n_cols":6,"columns":["","","12345672869:;24<6;","481;=748>25?@A2>","",":BFI4ZZFB[\\C]97^8B_‘ab‘c‘bd‘"],"rows":[["","","12345672869:;24<6;","481;=748>25?@A2>","",":BFI4ZZFB[\\C]97^8B_‘ab‘c‘bd‘"],["","","","","",""],["","",":BBCDEC1FGH","4CIJEJKLFDLJBE","","2eZJFDLJBE1DL\\]‘fgh‘gd‘dh"],["","","","","",""],["","","","","",""],["","","MNOPQRSPTN","UVTWXUY","","ijjklminonjpjqnrjstuv"],["","","","","",""],["","","","","",""],["wb‘xyz8G","I{\\F|}~(cid:127)","qtuq(cid:128)","","",""],["","","","","",""],["‹›)).’’","","","","",""],["","","","","",""],["1\\[J(cid:129)\\8D","I\\","","","",""],["fi(cid:26) (cid:29)fl(cid:176)–(cid:24)","(cid:176)†‡·(cid:25)","(cid:181)¶·#(cid:29)•!\"","","",""],["","","","","",""],["@ECJ(cid:129)DLJBE","K(cid:130)BF=K\\","|(cid:131)j(cid:132)(cid:133)(cid:134)}rj(cid:128)","","",""],["","","","","",""],["fi(cid:26) 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{"table_id":"K211733-p4-t0","doc_id":"K211733","page_num":4,"bbox":[90.34,432.27,521.86,478.19],"n_rows":3,"n_cols":4,"columns":["","Manufacturer Name","","Zebra Medical Vision, Ltd."],"rows":[["","Manufacturer Name","","Zebra Medical Vision, Ltd."],["","Device Trade Name","","HealthCXR"],["","510(k) Number","","K192320"]],"caption_candidate":"Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p4-t1","doc_id":"K211733","page_num":4,"bbox":[90.34,508.47,521.86,554.39],"n_rows":3,"n_cols":4,"columns":["","Manufacturer Name","","GE Medical Systems, LLC"],"rows":[["","Manufacturer Name","","GE Medical Systems, LLC"],["","Device Trade Name","","Critical Care Suite"],["","510(k) Number","","K183182"]],"caption_candidate":"Secondary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p9-t0","doc_id":"K211733","page_num":9,"bbox":[72.32,103.22,719.82,538.63],"n_rows":4,"n_cols":12,"columns":["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],"rows":[["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],["","Characteristics","","","Lunit INSIGHT CXR Triage","","","HealthCXR (K192320)","","","Critical Care Suite (K183182)",""],["Device\nclassification","","","Radiological Computer Assisted\nPrioritization Software Class II,\nQFM","","","Radiological Computer Assisted\nPrioritization Software Class II,\nQFM","","","Radiological Computer Assisted\nPrioritization Software Class II,\nQFM","",""],["Indication for\nUse/Intended\nUse","","","Lunit INSIGHT CXR Triage is a\nradiological computer-assisted triage\nand notification software that\nanalyzes adult chest X-ray images for\nthe presence of pre-specified\nsuspected critical findings (pleural\neffusion and/or pneumothorax).\nLunit INSIGHT CXR Triage uses an\nartificial intelligence algorithm to\nanalyze images for features\nsuggestive of critical findings and\nprovides case-level output available\nin the PACS/workstation for\nworklist prioritization or triage.\nAs a passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nLunit INSIGHT CXR Triage does\nnot send a proactive alert directly to\nthe appropriately trained medical\nspecialists. Lunit INSIGHT CXR\nTriage is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than","","","The Zebra HealthCXR device is a\nsoftware workflow tool designed to\naid the clinical assessment of adult\nChest X-Ray cases with features\nsuggestive of pleural effusion in the\nmedical care environment.\nHealthCXR analyzes cases using an\nartificial intelligence algorithm to\nidentify suspected findings. It makes\ncase-level output available to a\nPACS/workstation for worklist\nprioritization or triage. HealthCXR is\nnot intended to direct attention to\nspecific portions or anomalies of an\nimage. Its results are not intended to\nbe used on a stand-alone basis for\nclinical decision-making nor is it\nintended to rule out Pleural Effusion\nor otherwise preclude clinical\nassessment of X-Ray cases.","","","Critical Care Suite is a computer\naided triage and notification device\nthat analyzes frontal chest x-ray\nimages for the presence of pre-\nspecified critical findings\n(pneumothorax). Critical Care Suite\nidentifies images with critical findings\nto enable case prioritization or triage\nin the PACS/workstation.\nCritical Care Suite is intended for\nnotification only and does not\nprovide diagnostic information\nbeyond the notification. Critical Care\nSuite should not be used in-lieu of\nfull patient evaluation or solely relied\nupon to make or confirm a diagnosis.\nIt is not intended to replace the\nreview of the x-ray image by a\nqualified physician.\nCritical Care Suite is indicated for\nadult-size patients.","",""]],"caption_candidate":"Table 1 Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p10-t0","doc_id":"K211733","page_num":10,"bbox":[72.32,87.13,719.85,539.11],"n_rows":16,"n_cols":12,"columns":["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],"rows":[["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],["","Characteristics","","","Lunit INSIGHT CXR Triage","","","HealthCXR (K192320)","","","Critical Care Suite (K183182)",""],["","","","pleural effusion and/or\npneumothorax. Its results are not\nintended to be used on a stand-alone\nbasis for clinical decision-making.","","","","","","","",""],["","Notification-","","Yes","","","Yes","","","Yes","",""],["","only, parallel","","","","","","","","","",""],["","workflow tool","","","","","","","","","",""],["User","","","Appropriately trained medical\nspecialists who are qualified to\ninterpret chest radiographs.","","","Radiologist","","","Radiologist","",""],["","Targeted","","Pleural effusion, pneumothorax\nChest/Lung\nFrontal Chest X-ray","","","Pleural effusion\nChest/Lung\nFrontal Chest X-ray","","","Pneumothorax\nChest/Lung\nFrontal Chest X-ray","",""],["","clinical","","","","","","","","","",""],["","condition,","","","","","","","","","",""],["","anatomy, and","","","","","","","","","",""],["","modality","","","","","","","","","",""],["Algorithm for\npre-specified\ncritical findings\ndetection","","","AI algorithm designed to detect\npleural effusion and pneumothorax\nin chest X-ray images.\nLunit INSIGHT CXR Triage uses a\nvendor agnostic algorithm\ncompatible with DICOM chest X-ray\nimages.","","","AI algorithm designed to detect\npleural effusion in chest X-ray\nimages.\nHealthCXR employs a vendor\nagnostic algorithm compatible with\nDICOM chest X-ray images.","","","AI algorithm designed to detect\npneumothorax in frontal chest X-ray\nimages.\nCritical Care Suite uses a vendor\nagnostic algorithm compatible with\nDICOM frontal chest X-ray images.","",""],["","Radiological","","DICOM","","","DICOM","","","DICOM","",""],["","images format","","","","","","","","","",""],["Computational\nPlatform","","","Lunit INSIGHT CXR Triage is\ndesigned as a software module that\ncan be deployed on several","","","HealthCXR is designed as a software\nmodule that can be deployed on","","","Critical Care Suite is designed as a\nsoftware module that can be\ndeployed on several computing and","",""]],"caption_candidate":"Republic of Korea","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p11-t0","doc_id":"K211733","page_num":11,"bbox":[72.32,87.13,719.82,539.35],"n_rows":4,"n_cols":12,"columns":["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],"rows":[["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],["","Characteristics","","","Lunit INSIGHT CXR Triage","","","HealthCXR (K192320)","","","Critical Care Suite (K183182)",""],["","","","computing and X-ray imaging\nplatforms such as radiological\nimaging equipment, PACS, On\nPremise or On Cloud.","","","PACS and Standalone desktop\napplication, Zebra Worklist.","","","X-ray imaging platforms such as\nDigital Projection Radiographic\nSystems, PACS, On Premise or On\nCloud.","",""],["Device output\nin case of\npositive\ndetection","","","When deployed on other radiological\nimaging equipment, Lunit INSIGHT\nCXR Triage automatically runs after\nimage acquisition and prioritizes and\ndisplays the analysis result through\nthe worklist interface of\nPACS/workstation.\nNo markup on original image.\nSecondary capture of the finding.\nUpon image acquisition from other\nradiological imaging equipment (e.g.\nX-ray systems), an on-device,\ntechnologist notification indicating\nwhich cases were flagged by Lunit\nINSIGHT CXR Triage in PACS, is\ngenerated 15 minutes after\ninterpretation by the user. The on-\ndevice notification is contextual and\ndoes not provide any diagnostic\ninformation. It is not intended to","","","Integration module notifies the\nPACS/workstation for prioritization\nthrough the worklist interface.\nNo markup on original image.","","","Critical Care Suite enables case\nprioritization or triage through direct\ncommunication of the Critical Care\nSuite notification during image\ntransfer to the PACS.\nNo markup on original image\nUpon image acquisition on a Digital\nProjection Radiographic System, an\non-device, technologist notification is\ngenerated 15 minutes after exam\nclosure, indicating which cases were\nprioritized by Critical Care Suite in\nPACS. The technologist notification\nis contextual and does not provides\nany diagnostic information. The on-\ndevice, technologist notification is\nnot intended to inform any clinical\ndecision, prioritization, or action.","",""]],"caption_candidate":"Republic of Korea","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p12-t0","doc_id":"K211733","page_num":12,"bbox":[72.32,87.13,719.84,509.23],"n_rows":14,"n_cols":12,"columns":["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],"rows":[["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],["","Characteristics","","","Lunit INSIGHT CXR Triage","","","HealthCXR (K192320)","","","Critical Care Suite (K183182)",""],["","","","inform any clinical decision,\nprioritization, or action to the\ntechnologist.","","","","","","","",""],["","Notification","","Passive notification.\nImages with suspicion of pleural\neffusion and/or pneumothorax are\nflagged in PACS/workstation.","","","Passive notification.\nImages with suspicion of pleural\neffusion are flagged in\nPACS/workstation.","","","Passive notification.\nImages with suspicion of\npneumothorax are flagged in\nPACS/workstation.","",""],["","(i.e., recipient,","","","","","","","","","",""],["","timing and","","","","","","","","","",""],["","means of","","","","","","","","","",""],["","notification)","","","","","","","","","",""],["","Where","","PACS/Workstation","","","PACS/Workstation","","","PACS/Workstation","",""],["","generated","","","","","","","","","",""],["","results (i.e.,","","","","","","","","","",""],["","DICOM files)","","","","","","","","","",""],["","are stored","","","","","","","","","",""],["Performance\nlevel –\nTiming of\nnotification","","","The average time taken for the\nnotification to travel from the Lunit\nINSIGHT CXR Triage to the point\nat which the result is displayed in the\ndestination PACS/RIS/EPR worklist\nis 14.66 seconds.","","","Passive notification is visible upon\ntransfer to the PACS with a delay of\nabout 22 seconds for image transfer\nto the cloud, computation, and\nresults transfer.","","","The average time to acquire,\nannotate, process and transfer an\nimage from the x-ray system to\nPACS was measured and found to\ntake 42 seconds on average. Exams\narrive on PACS with the passive\nnotification already incorporated,\ntherefore there is no delay for image\ntransfer or computation. The\nworklist prioritization happens\nimmediately once the exam is\nreceived on the PACS.","",""]],"caption_candidate":"Republic of Korea","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211733-p13-t0","doc_id":"K211733","page_num":13,"bbox":[72.32,87.13,719.81,383.56],"n_rows":3,"n_cols":12,"columns":["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],"rows":[["","Technological","","","Proposed Device:","","","Primary Predicate Device:","","","Secondary Predicate Device:",""],["","Characteristics","","","Lunit INSIGHT CXR Triage","","","HealthCXR (K192320)","","","Critical Care Suite (K183182)",""],["Performance\nlevel –\naccuracy of\nclassification","","","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.9686 (95% CI: [0.9547,\n0.9824])\nSensitivity 89.86% (95% CI: [86.72,\n93.00])\nSpecificity 93.48% (95% CI: [91.06,\n95.91])\nPneumothorax\nROC AUC > 0.95\nAUC: 0.9630 (95% CI: [0.9521,\n0.9739])\nSensitivity 88.92% (95% CI: [85.60,\n92.24])\nSpecificity 90.51% (95% CI: [88.18,\n92.83])","","","ROC AUC > 0.95\nAUC: 0.9885 (95% CI: [0.9815,\n0.9956]),\nFirst operating point\nSensitivity 96.74% (95% CI: [92.79;\n96.48])\nSpecificity 93.17% (95% CI: [89.57;\n95.58])\n“High-specificity” operating\npoint\nSensitivity 93.84% (95% CI:\n[90.36;96.12)\nSpecificity 97.12% (95% CI:\n[94.43;98.53])","","","ROC AUC > 0.95\nAUC: 0.9607 (95% CI [0.9491,\n0.9724])\nSpecificity 93.5% (95% CI [91.1%,\n95.8%])\nSensitivity 84.3% (95% CI [80.6%,\n88.0%])\nAUC on large pneumothorax 0.9888\n(95% CI [0.9810, 0.9965])\nSensitivity on large pneumothorax\n96.3% (95% CI [93.3%, 99.2%]\nAUC on small pneumothorax 0.9389\n(95% CI [0.9209, 0.9570])\nSensitivity on small pneumothorax\n75% (95% CI [69.2%, 80.8%])","",""]],"caption_candidate":"Republic of Korea","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K211803-p4-t0","doc_id":"K211803","page_num":4,"bbox":[66.5,548.5,524.5,645.5],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","AIMI-Triage CXR PTX"],"rows":[["Proprietary Name","AIMI-Triage CXR PTX"],["Premarket Notification","K193300"],["Classification Name","Radiological Computer-Assisted Prioritization Software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QFM"],["Regulatory Class","II"]],"caption_candidate":"The HealthPPT device is substantially equivalent to the following device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211803-p6-t0","doc_id":"K211803","page_num":6,"bbox":[66.0,296.0,532.5,720.5],"n_rows":2,"n_cols":4,"columns":["Technological\nCharacteristics","Proposed Device\nHealthPPT","Predicate Device\nAIMI-Triage CXR PTX\n(K193300)","Summary"],"rows":[["Technological\nCharacteristics","Proposed Device\nHealthPPT","Predicate Device\nAIMI-Triage CXR PTX\n(K193300)","Summary"],["Indication for\nUse/Intended Use","The Zebra HealthPPT device\nis a software workflow tool\ndesigned to aid the clinical\nassessment of adult frontal\nChest X-Ray cases with\nfeatures suggestive of\npneumoperitoneum in the\nmedical care environment.\nHealthPPT analyzes cases\nusing an artificial intelligence\nalgorithm to identify\nsuspected findings. It makes\ncase-level output available to\na PACS/workstation for\nworklist prioritization or\ntriage. HealthPPT is not\nintended to direct attention to\nanomalies other than\npneumoperitoneum.\nNotifications include\ncompressed preview images\nthat are meant for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. The device does\nnot alter the original medical\nimage and is not intended to\nbe used as a diagnostic\ndevice. Its results are not","The AIMI-Triage CXR\nPTX Application is a\nnotification-only triage\nworkflow tool for use by\nhospital networks and\nclinics to identify and\nhelp prioritize chest\nX-rays acquired in the\nacute setting for review\nby hospital radiologists.\nThe device operates in\nparallel to and\nindependent of standard\nof care image\ninterpretation workflow.\nSpecifically, the device\nuses an artificial\nintelligence algorithm to\nanalyze images for\nfeatures suggestive of\nmoderate to large sized\npneumothorax; it makes\ncaselevel output available\nto a PACS/workstation\nfor worklist prioritization\nor triage. Identification of\nsuspected cases of\nmoderate to large sized\npneumothorax is not for\ndiagnostic use beyond","Similar expect for\nlesion type"]],"caption_candidate":"A comparison of the technological characteristics with the predicate is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211803-p7-t0","doc_id":"K211803","page_num":7,"bbox":[66.25,75.0,532.5,718.5],"n_rows":7,"n_cols":4,"columns":["","intended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it\nintended to rule out\npneumoperitoneum or\notherwise preclude clinical\nassessment of X-Ray cases.","notification. The\nAIMI-Triage CXR PTX\nApplication is limited to\nanalysis of imaging data\nas a guide to possible\nurgency of adult chest\nX-ray image review, and\nshould not be used in lieu\nof full patient evaluation\nor relied upon to make or\nconfirm diagnoses.\nNotified radiologists are\nresponsible for engaging\nin appropriate patient\nevaluation as per local\nhospital procedure before\nmaking care-related\ndecisions or requests. The\ndevice does not replace\nreview and diagnosis of\nthe X-rays by\nradiologists. The device is\nnot intended to be used\nwith plain film X-rays.",""],"rows":[["","intended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it\nintended to rule out\npneumoperitoneum or\notherwise preclude clinical\nassessment of X-Ray cases.","notification. The\nAIMI-Triage CXR PTX\nApplication is limited to\nanalysis of imaging data\nas a guide to possible\nurgency of adult chest\nX-ray image review, and\nshould not be used in lieu\nof full patient evaluation\nor relied upon to make or\nconfirm diagnoses.\nNotified radiologists are\nresponsible for engaging\nin appropriate patient\nevaluation as per local\nhospital procedure before\nmaking care-related\ndecisions or requests. The\ndevice does not replace\nreview and diagnosis of\nthe X-rays by\nradiologists. The device is\nnot intended to be used\nwith plain film X-rays.",""],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Radiologist","Radiologist","Same"],["Radiological\nimages format","DICOM","DICOM","Same"],["Identify patients\nwith prespecified\nclinical condition","Yes","Yes","Same"],["Clinical condition","Pneumoperitoneum","Pneumothorax","Different but as\nper the product\nclassification\ndefinition, both\nidentify “time\nsensitive imaging.”"],["Alert to finding","Yes; notification flagged for\nreview on hospital worklist or\nZebra application","Yes; notification flagged\nfor review","Similar,\nHealthPPT can be\ndirectly integrated\nfor notification on\nthe hospital\nworklist or on the\nZebra application.\nBoth notifications\noperate in parallel"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211803-p8-t0","doc_id":"K211803","page_num":8,"bbox":[66.25,74.5,532.5,497.5],"n_rows":9,"n_cols":4,"columns":["","","","with the standard\nof care."],"rows":[["","","","with the standard\nof care."],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are\nremoved from worklist","Same"],["Modality","Chest X-Ray","Chest X-Ray","Same"],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Same"],["Limited to analysis\nof imaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with\nindicated findings","Yes","Yes","Same"],["Preview Image","Presentation of a compressed\npreview image for initial\nassessment, not meant for\ndiagnostic purposes.\nThe device operated in\nparallel with the standard of\ncare, which remains the\ndefault option for all cases.","Presentation of\nnotification for initial\nassessment not meant for\ndiagnostic purposes. The\ndevice operates in parallel\nwith the standard of care,\nwhich remains the default\noption for all cases.","Similar,\nHealthPPT\nprovides an\nadditional\ncompressed image\nas a preview only,\nnot for diagnostic\nuse."],["Multiple operating\npoints","Yes; 2 optional operating\npoints","No; single operating point","Different, but all\noperating points\ncomply with DEN\n170073 Special\ncontrol 1(iii)."],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211824-p5-t0","doc_id":"K211824","page_num":5,"bbox":[52.35,437.91,541.38,769.3],"n_rows":4,"n_cols":5,"columns":["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],"rows":[["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],["Manufacturer","SAMSUNG MEDISON\nCO.,LTD","SAMSUNG MEDISON\nCO.,LTD","SAMSUNG MEDISON\nCO.,LTD","GE Medical Systems\nUltrasound and\nPrimary Care\nDiagnostics, LLC"],["Intended Use","The HERA W9/ HERA\nW10 Diagnostic\nUltrasound System and\ntransducers are intended\nfor diagnostic\nultrasound imaging and\nfluid analysis of the\nhuman body.","The HERA W9/ HERA\nW10 Diagnostic\nUltrasound System and\ntransducers are intended\nfor diagnostic ultrasound\nimaging and fluid\nanalysis of the human\nbody.","The RS85 Ultrasound\nDiagnostic System and\nprobes are designed to\nobtain ultrasound images\nand analyze body fluids.","The Voluson SWIFT,\nVoluson SWIFT+ is\na general-purpose\ndiagnostic\nultrasound system\nintended for use by\nqualified and trained\nhealthcare\nprofessionals for\nultrasound imaging,\nmeasurement,\ndisplay and analysis\nof the human body\nand fluid."],["Functionality","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+",""]],"caption_candidate":"(Changed an algorithm of BiometryAssist to AI version).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211824-p6-t0","doc_id":"K211824","page_num":6,"bbox":[52.35,72.34,541.37,759.7],"n_rows":3,"n_cols":5,"columns":["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],"rows":[["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],["","- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for\nThyroid\n- ADVR\n- 3D Imaging\n- (Volume Data\nAcquisition)\n- 3D Imaging\npresentation\n- 3D Cine/4D Cine\n- 3D Rendering\nMPR\n- 3D XI\nMSV/Oblique\nView\n- Volume CT\n- 3D MagiCut\n- Volume\nCalculation\n- (VOCAL, XI\nVOCAL)\n- XI STIC\n- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*\n- Slice A\n- HeartAssist *\n- ViewAssist","- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for\nThyroid\n- ADVR\n- 3D Imaging\n- (Volume Data\nAcquisition)\n- 3D Imaging\npresentation\n- 3D Cine/4D Cine\n- 3DRendering MPR\n- 3D XI\nMSV/Oblique View\n- Volume CT\n- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI\nVOCAL)\n- XI STIC\n- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*","- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for\nThyroid\n- ADVR\n- 3D Imaging\n- (Volume Data\nAcquisition)\n- 3D Imaging\npresentation\n- 3D Cine/4D Cine\n- 3D Rendering MPR\n- 3D XI\nMSV/Oblique View\n- Volume CT\n- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI\nVOCAL)\n- XI STIC\n- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow\n-\n-\n-\n-\n-\n-\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- LumiFlow\n- ShadowHDR","- VCIA\n- SonoLystIR\n- SonoLystIR"],["Transducers","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A","- L3-12A\n- LA2-9A\n- LA4-18B\n-\n-\n- CA3-10A\n- CF4-9\n- E3-12A","Unknown"]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211824-p7-t0","doc_id":"K211824","page_num":7,"bbox":[52.37,72.34,541.35,253.22],"n_rows":2,"n_cols":5,"columns":["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],"rows":[["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10\n(K192319)\nPrimary Predicate","RS85\n(K192903)\nSecondary Predicate","Voluson SWIFT\n(K201828)\nReference"],["","- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A","- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR","- EA2-11B\n-\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A",""]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211824-p8-t0","doc_id":"K211824","page_num":8,"bbox":[78.64,184.22,529.65,331.61],"n_rows":8,"n_cols":4,"columns":["Difference","","HERA W9","HERA W10"],"rows":[["Difference","","HERA W9","HERA W10"],["Software","CrystalVue Flow","Not Supported","Supported"],["","MPI+","Not Supported","Supported"],["","HeartAssist","Not Supported","Supported"],["Hardware","Internal DVD","Not Included","Included"],["","Caster size","5\"","6\""],["","Active array probe port","3 port (default), 4 port(option)","4 port"],["","Main monitor","21.5\"/ 23.8\"","21.5\"/ 23\" / 23.8\""]],"caption_candidate":"The differences between HERA W9 and HERA W10 in the subject device are as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211824-p8-t1","doc_id":"K211824","page_num":8,"bbox":[78.64,420.71,541.4,597.79],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","ANSI AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and A2:2010\n/(R)2012\nMedical Electrical Equipment - Part 1: General Requirements for basic safety and\nessential performance.","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2014(4th Edition), Medical electrical equipment - Part 1-2: General\nrequirements for basic safety and essential performance - EMC","",""],["IEC 60601-2-37","","","IEC60601-2-37:2007 + A1:2015, Particular requirements for the safety of ultrasonic\nmedical diagnostic and monitoring equipment","",""],["ISO10993-1","","","ISO 10993-1, Biological evaluation of medical devices -- Part 1: Evaluation and testing\nwithin a risk management process.","",""],["ISO14971","","","ISO 14971:2007, Medical devices - Application of risk management to medical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound Equipment Revision\n3","",""]],"caption_candidate":"applications comply with voluntary standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211828-p5-t0","doc_id":"K211828","page_num":5,"bbox":[113.64,67.68,594.0,203.46],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary:\nAquilion Exceed LB\n(TSX‐202A/3) V10.6\nwith AiCE‐i","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K203042","12/10/2020"],["Reference:\nDual Energy System\nPackage, CSDP‐001A","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX‐ray System","JAK:\nSystem, X‐ray,\nTomography,\nComputed","K132813","02/06/2014"]],"caption_candidate":"11. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211828-p5-t1","doc_id":"K211828","page_num":5,"bbox":[107.07,630.33,571.48,727.67],"n_rows":7,"n_cols":5,"columns":["","","Subject Device","","Primary Predicate Device"],"rows":[["","","Subject Device","","Primary Predicate Device"],["Device Name,\nModel Number","","Aquilion Exceed LB","","Aquilion Exceed LB\n(TSX‐202A/3) V10.6 with AiCE‐i"],["","","(TSX‐202A/3) V10.9 with AiCE‐i","",""],["510(k) Number","","This submission","","K203042"],["SUREStart","","12 measurements/s","","12 measurements/s"],["","","Applicable to the XL scan field.","",""],["","","","",""]],"caption_candidate":"predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211828-p6-t0","doc_id":"K211828","page_num":6,"bbox":[107.09,54.36,571.49,694.62],"n_rows":46,"n_cols":5,"columns":["","","Subject Device","","Primary Predicate Device"],"rows":[["","","Subject Device","","Primary Predicate Device"],["Device Name,\nModel Number","","Aquilion Exceed LB","","Aquilion Exceed LB\n(TSX‐202A/3) V10.6 with AiCE‐i"],["","","(TSX‐202A/3) V10.9 with AiCE‐i","",""],["510(k) Number","","This submission","","K203042"],["Parameter editing","","Up to 7 pairs of Volume and","","Up to 3 pairs of Volume and\nMultiview reconstructions can be\nprescribed."],["","","Multiview reconstructions can be","",""],["","","prescribed.","",""],["","","","",""],["Metal Artifact Reduction","","Single Energy Metal Artifact","","Single Energy Metal Artifact\nReduction (SEMAR)"],["","","Reduction (SEMAR)","",""],["","","Applicable to the XL scan field.","",""],["Noise Reduction\nProcessing","","Quantum Denoising Software","","Quantum Denoising Software\n(QDS)\nAdaptive Integrative Dose\nReduction 3D (AIDR 3D),\nAIDR 3D Enhanced\nAiCE\n(Advanced Intelligent Clear‐IQ\nEngine)\n Abdomen and Pelvis\n Chest\n Extremities\n Brain\n Inner ear"],["","","(QDS)","",""],["","","Adaptive Integrative Dose","",""],["","","Reduction 3D (AIDR 3D),","",""],["","","AIDR 3D Enhanced","",""],["","","","",""],["","","AiCE","",""],["","","(Advanced Intelligent Clear‐IQ","",""],["","","Engine)","",""],["",""," Abdomen and Pelvis","",""],["",""," Chest","",""],["",""," Extremities","",""],["",""," Brain","",""],["",""," Inner ear","",""],["",""," Cardiac","",""],["","","","",""],["Dual energy system\npackage\n(CSDP‐001A)","","Available","","N/A"],["","","New Features:","",""],["","","Generation of Electron Density","",""],["","","Map","",""],["","","","",""],["","","Generation of Effective Atomic","",""],["","","Number Map","",""],["","","","",""],["Extended field of view\n(CSTC‐005A)","Available\nCan be set with SEMAR","Available","","Available"],["","","Can be set with SEMAR","",""],["Magnified\nreconstruction ‐\nAvailable magnification\nSize (D‐FOV)","","BODY / BODY SHARP: Min. 100 mm","","BODY / BODY SHARP: Min. 100\nmm\nLUNG: Min. 100 mm\nBONE: Min. 50 mm\nINNER EAR: Min. 50 mm\nBRAIN LCD / CTA: Min. 100 mm\nMax. 700 (900*) mm\n*Option"],["","","LUNG: Min. 100 mm","",""],["","","BONE: Min. 50 mm","",""],["","","INNER EAR: Min. 50 mm","",""],["","","BRAIN LCD / CTA: Min. 100 mm","",""],["","","CARDIAC: Min. 70 mm","",""],["","","Max. 700 (900*) mm","",""],["","","*Option","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211841-p4-t0","doc_id":"K211841","page_num":4,"bbox":[73.8,184.65,524.4,766.35],"n_rows":7,"n_cols":2,"columns":["Date Prepared","August 25, 2022"],"rows":[["Date Prepared","August 25, 2022"],["Contact details","Spectronic Medical AB\nKarbingatan 36\n254 67 Helsingborg\nSWEDEN"],["Contact Person","Per Bruhn\nManager of Quality Assurance and Regulatory Affairs\nSpectronic Medical AB\nTel: +46 735 116042\nEmail: per.bruhn@spectronic.se"],["Device trade name:\nCommon Name:\nClassification Regulation:\nClassification Name:\nPanel:\nClassification:\nProduct Code:","MRI Planner\nMRI Planner\n21 CFR 892.5050\nMedical charged-particle radiation therapy system\nRadiology\nClass II\nMUJ, QKB"],["Predicate Device","Device name: MRCAT Brain\nManufacturer: Philips Medical Systems MR Finland\n510(k) Clearance: K193109\nClassification Regulation: 21 CFR 892.5050\nClassification Name: Medical charged-particle radiation therapy system\nClassification Panel: Radiology\nDevice Class: II\nProduct Code: MUJ"],["Reference Devices","Reference Device 1:\nDevice name: MRCAT Pelvis\nManufacturer: Philips Medical Systems MR Finland\n510(k) Clearance: K182888\nClassification Regulation: 21 CFR 892.5050\nClassification Name: Medical charged-particle radiation therapy system\nClassification Panel: Radiology\nDevice Class: II\nProduct Code: MUJ\nReference Device 2:\nDevice name: Limbus Contour\nManufacturer: Limbus AI, Inc.\n510(k) Clearance: K201232\nClassification Regulation: 21 CFR 892.2050\nClassification Name: Medical image management and processing system\nClassification Panel: Radiology\nDevice Class: II\nProduct Code: LLZ"],["Device Description Summary","The product MRI Planner is a stand-alone software providing information\nto the treatment planning process prior to radiotherapy. Based on a DICOM"]],"caption_candidate":"The following summary of the present 510(k) submission is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211841-p5-t0","doc_id":"K211841","page_num":5,"bbox":[73.8,93.45,524.4,768.45],"n_rows":3,"n_cols":2,"columns":["","MR image stack, the software generates synthetic CT images that can be\nused for attenuation calculations in radiotherapy treatment planning for the\npelvis, brain and head-neck regions. In addition, the software also\ngenerates contours of anatomical structures in the MR image stack, to be\nused as a starting point for the manual delineation work required in\nradiotherapy treatment planning. Contours are generated for prostate cancer\npatients only (bladder, colon and femoral heads).\nMRI Planner utilizes pre-trained machine learning models to perform both\nthe conversion to synthetic CT and the automated structure contouring. The\nmodels for synthetic CT generation was trained using a dataset comprising\nMR and CT images for 244 patients acquired in the treatment position at\nfour hospitals. The model for prostate cancer patient auto contouring was\ntrained using a dataset comprising MR images for 175 patients acquired in\nthe treatment position at four hospitals, together with in-house generated\nexpert manual contours. MRI Planner does not display or store DICOM\nimages. The user is advised to use existing softwares for radiotherapy\ntreatment planning to display and modify generated images and contours.\nMRI Planner runs on a standard x86-64 compatible system with a CUDA\ncapable NVIDIA GPU and requires Ubuntu Linux 18.04 operating system."],"rows":[["","MR image stack, the software generates synthetic CT images that can be\nused for attenuation calculations in radiotherapy treatment planning for the\npelvis, brain and head-neck regions. In addition, the software also\ngenerates contours of anatomical structures in the MR image stack, to be\nused as a starting point for the manual delineation work required in\nradiotherapy treatment planning. Contours are generated for prostate cancer\npatients only (bladder, colon and femoral heads).\nMRI Planner utilizes pre-trained machine learning models to perform both\nthe conversion to synthetic CT and the automated structure contouring. The\nmodels for synthetic CT generation was trained using a dataset comprising\nMR and CT images for 244 patients acquired in the treatment position at\nfour hospitals. The model for prostate cancer patient auto contouring was\ntrained using a dataset comprising MR images for 175 patients acquired in\nthe treatment position at four hospitals, together with in-house generated\nexpert manual contours. MRI Planner does not display or store DICOM\nimages. The user is advised to use existing softwares for radiotherapy\ntreatment planning to display and modify generated images and contours.\nMRI Planner runs on a standard x86-64 compatible system with a CUDA\ncapable NVIDIA GPU and requires Ubuntu Linux 18.04 operating system."],["Indications For Use","MRI Planner is a software-only medical device intended for use by trained\nradiation oncologists, dosimetrists and physicists to process images from\nMRI systems to\n1) provide the operator with information of tissue properties for radiation\nattenuation estimation purposes in photon external beam radiotherapy\ntreatment planning, and to\n2) derive contours for input to radiation treatment planning by assisting in\nlocalization and definition of healthy anatomical structures.\nMRI Planner is not intended to automatically contour tumors or tumor\nclinical target volumes.\nMRI Planner is indicated for radiotherapy planning of adult patients for\nprimary and metastatic cancers in the brain and head-neck regions, as well\nas soft tissue cancers in the pelvis region.\nMRI Planner generates synthetic CT images for radiation attenuation\nestimation purposes for the pelvis, brain and head-neck regions only. MRI\nPlanner generates automatically derived contours of the bladder, colon and\nfemoral heads, for prostate cancer patients only."],["Indications for Use comparison","MRI Planner provides the indications for use of the Predicate Device. The\nPredicate Device has the intended use to provide the operator with\ninformation of tissue properties for radiation attenuation estimation\npurposes in photon external beam radiotherapy treatment planning.\nMRI Planner includes the intended use of the Predicate Device, as it\nprovides the operator with information of tissue properties for radiation\nattenuation estimation purposes in photon external beam radiotherapy\ntreatment planning. Additionally, it provides the functionality of auto\ncontouring, which is not believed to raise additional safety concerns.\nAs such, the indications for use of MRI Planner does not raise any"]],"caption_candidate":"Spectronic Medical 510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211841-p6-t0","doc_id":"K211841","page_num":6,"bbox":[73.8,93.45,524.4,768.45],"n_rows":3,"n_cols":2,"columns":["","additional or different concerns regarding safety or effectiveness as\ncompared to the Predicate Device."],"rows":[["","additional or different concerns regarding safety or effectiveness as\ncompared to the Predicate Device."],["Technological comparison","Both MRI Planner and the Predicate Device are machine learning based.\nReference Device 1 was used as predicate device for the Predicate Device\nand is therefore also technologically equivalent. Both the Predicate Device\nand Reference Device 1 generates similar outputs as MRI Planner in the\nform of synthetic CT images. Since MRI Planner has similar technological\ncharacteristics as both the Predicate Device and Reference Device 1 with\nregard to synthetic CT generation, no differences in risk have been\nidentified between the products.\nBoth MRI Planner and Reference Device 2 use pre-trained machine\nlearning models to derive contours. Since MRI Planner has similar\ntechnological characteristics as Reference Device 2 with regard to deriving\ncontours, no differences in risk have been identified between the products."],["Summary of performance\ntesting","Dose accuracy bench test\nThe conducted bench tests evaluate the dosimetric equivalence of MRI\nPlanner generated synthetic CT (sCT) and conventional CT. Dosimetric\nagreement was evaluated by comparing mean doses to target and non-target\nvolumes as well as by means of gamma evaluation. The non-target sCT-CT\ndose difference was evaluated by computing the mean dose difference in\nall sub-volumes of the dose matrix not overlapping the target. The\nacceptance criteria was that 99% of cases should have no sub-volumes with\nan sCT-CT dose difference in excess of 1.0 Gy or 5% of the CT-dose. Two\nvariations of gamma evaluation were conducted; one focusing on the high\ndose area (cut off at 75% of the maximum dose) and the other considering\nalso the medium dose regions (cut off at 25% of the maximum dose). In the\nhigh dose gamma a 3%/3mm criteria was used for the pelvic and head-neck\nanatomical regions, while a 2%/2mm criteria was used for brain cases. The\ngamma index passing rate requirement was 99% for pelvis and head-neck,\nand 98% for brain. In the medium dose range gamma evaluation the stricter\n2%/2mm criteria was used for all anatomical regions, while requiring a\n99% gamma index passing rate.\nThe average sCT-CT mean target dose difference was found to be 0.02% ±\n0.31% and -0.02% ± 0.25% for the anatomical regions pelvis, and head-\nneck and brain, respectively. No cases displayed any sub-volumes with\nsCT-CT dose differences in excess of 5% or 1.0 Gy.\nAt least 95% of cases met the passing criteria across all gamma evaluations\nand anatomical regions. In the high dose gamma evaluation, 100.0% of\ncases passed the individual passing rate criterion for all anatomical regions,\nwhile the average gamma index passing rate was 99.9%, 99.8% and 99.8%\nfor pelvis, head neck and brain, respectively. In the medium dose gamma\nevaluation, 98.3% and 100.0% of cases passed the individual passing rate\ncriterion for pelvis, and head-neck and brain, respectively, while the\naverage gamma index passing rate was 99.7%, 99.5% and 99.9% for pelvis,\nhead neck and brain, respectively.\nDosimetric bench test data for pelvis consisted of MR (T2w) and CT\nimages for 58 unique pelvis cancer patients acquired in the treatment\nposition at six different hospitals. Patient distribution was 16% female and\n84% male, age range 51-88 years, 41% of patient images were acquired in\nthe US and 59% outside the US."]],"caption_candidate":"Spectronic Medical 510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211841-p7-t0","doc_id":"K211841","page_num":7,"bbox":[73.8,93.45,524.4,762.95],"n_rows":2,"n_cols":2,"columns":["","Dosimetric bench test data for head-neck-brain consisted of MR (T1-\nDixon) and CT images for 75 unique head-neck-brain cancer patients\nacquired in the treatment position at four different hospitals. Patient\ndistribution was 39% female and 64% male, age range 41-85 years, 55% of\npatient images were acquired in the US and 45% outside the US.\nMRI data was acquired at six different MRI scanner models, from two\ndifferent vendors, with field strengths of 1.5T and 3T.\nAuto contouring bench test\nThe conducted bench tests evaluates the automatically generated prostate\npatient delineations (of bladder, colon and femoral heads) against manual\ndelineations, using two common metrics; Dice score (DSC) and 95%\nHausdorff distance (HD).\nThe average DSC was found to be 0.95 ± 0.03, 0.90 ± 0.04 and 0.96 ± 0.01\nfor bladder, colon and femoral head delineations, respectively. The average\n95% HD was found to be 2.69 ± 1.82, 4.96 ± 3.91 and 2.04 ± 0.49 for\nbladder, colon and femoral head delineations, respectively.\nAuto contouring bench test data for prostate cancer patients consisted of\nMR (T2w) images for 51 unique male prostate cancer patients acquired in\nthe treatment position at five different hospitals, together with manually\ngenerated delineations of bladder, colon and femoral heads. Patient age\nrange was 51-88 years, 39% of patient images were acquired in the US and\n61% outside the US.\nManual delineations were generated by two expert truthers using the\nconsensus approach, based on US clinical guidelines. The manual\ndelineations for the bench tests were generated at a separate time from the\ngeneration of the training dataset. The truthers were involved in the\ndevelopment of the product and the generation of the training dataset, but\nnot in the training and tuning of the segmentation model. Both truthers\nwere employed by the manufacturer at the time of performing the manual\ndelineations for the bench test."],"rows":[["","Dosimetric bench test data for head-neck-brain consisted of MR (T1-\nDixon) and CT images for 75 unique head-neck-brain cancer patients\nacquired in the treatment position at four different hospitals. Patient\ndistribution was 39% female and 64% male, age range 41-85 years, 55% of\npatient images were acquired in the US and 45% outside the US.\nMRI data was acquired at six different MRI scanner models, from two\ndifferent vendors, with field strengths of 1.5T and 3T.\nAuto contouring bench test\nThe conducted bench tests evaluates the automatically generated prostate\npatient delineations (of bladder, colon and femoral heads) against manual\ndelineations, using two common metrics; Dice score (DSC) and 95%\nHausdorff distance (HD).\nThe average DSC was found to be 0.95 ± 0.03, 0.90 ± 0.04 and 0.96 ± 0.01\nfor bladder, colon and femoral head delineations, respectively. The average\n95% HD was found to be 2.69 ± 1.82, 4.96 ± 3.91 and 2.04 ± 0.49 for\nbladder, colon and femoral head delineations, respectively.\nAuto contouring bench test data for prostate cancer patients consisted of\nMR (T2w) images for 51 unique male prostate cancer patients acquired in\nthe treatment position at five different hospitals, together with manually\ngenerated delineations of bladder, colon and femoral heads. Patient age\nrange was 51-88 years, 39% of patient images were acquired in the US and\n61% outside the US.\nManual delineations were generated by two expert truthers using the\nconsensus approach, based on US clinical guidelines. The manual\ndelineations for the bench tests were generated at a separate time from the\ngeneration of the training dataset. The truthers were involved in the\ndevelopment of the product and the generation of the training dataset, but\nnot in the training and tuning of the segmentation model. Both truthers\nwere employed by the manufacturer at the time of performing the manual\ndelineations for the bench test."],["Non-clinical test summary and\nconclusion","MRI Planner complies with the following international and FDA-\nrecognized consensus standards:\nISO 14971 Second edition 2007-03-01\nMedical devices – Application of risk management to medical devices\nIEC 62304 Edition 1.1 2015-06\nCONSOLIDATED VERSION Medical device software – Software life\ncycle processes\nIEC 62366-1:2015\nMedical devices – Part 1: Application of usability engineering to medical\ndevices\nIEC 82304-1 Edition 1.0 2016-10\nHealth software – Part 1: General requirements for product safety\nNon-clinical verification and validation tests have been performed"]],"caption_candidate":"Spectronic Medical 510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211846-p9-t0","doc_id":"K211846","page_num":9,"bbox":[108.26,103.7,540.12,466.75],"n_rows":7,"n_cols":3,"columns":["Specification/\nAttribute","Predicate Device\nDiscovery MI K161574","Proposed Device"],"rows":[["Specification/\nAttribute","Predicate Device\nDiscovery MI K161574","Proposed Device"],["PET Gantry","Multiple detector ring size\nconfigurations (15, 20, 25 cm axial\nFOV)","Multiple detector ring size\nconfigurations (15, 20, 25, 30 cm\naxial FOV)."],["Detector Unit","SiPM-based light sensor with ASIC","Same"],["","LYSO scintillator crystal","LYSO or LGSO scintillator crystals"],["CT System","Revolution EVO - Full suite of cleared\nCT application software with\nmodifications (K131576)","Revolution EVO - Full suite of cleared\nCT application software with\nmodifications including Deep\nLearning Image Reconstruction\n(DLIR) K193170"],["Whole Body\nDynamic Acquisition\n(WBDA)","Whole body dynamic acquisition\ncapability enabled by manually\nperforming multiple passes that are\nalso referred as static scans of a\npatient","Whole body dynamic acquisition\ncapability with automation to help\nthe user to perform the scan with\nadequate user interface and\ndedicated tools to improve the user\nexperience"],["AutoIN","-","Allows the operator to move the\npatient table from the operator\nconsole within the operator room,\nrather than from the gantry control\npanel for landmarking"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211867-p5-t0","doc_id":"K211867","page_num":5,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-11.0 510(k) Summary RayStation 11.0","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211867-p6-t0","doc_id":"K211867","page_num":6,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-11.0 510(k) Summary RayStation 11.0","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211867-p7-t0","doc_id":"K211867","page_num":7,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-11.0 510(k) Summary RayStation 11.0","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211867-p8-t0","doc_id":"K211867","page_num":8,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["RSL-D-RS-11.0 510(k) Summary RayStation 11.0","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211945-p6-t0","doc_id":"K211945","page_num":6,"bbox":[111.64,406.25,543.92,624.7],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2014(4th Edition) , Medical electrical equipment - Part 1-\n2: General requirements for basic safety and essential performance - EMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["ISO10993-1","","","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2007, Medical devices - Application of risk management to\nmedical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3","",""]],"caption_candidate":"FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211964-p4-t0","doc_id":"K211964","page_num":4,"bbox":[70.06,102.95,530.32,556.73],"n_rows":16,"n_cols":2,"columns":["Submitter’s Name:","Subtle Medical, Inc."],"rows":[["Submitter’s Name:","Subtle Medical, Inc."],["Address:","883 Santa Cruz Ave, Suite 205\nMenlo Park, CA 94025"],["Contact Person:","Jared Seehafer"],["Title:","Regulatory Consultant"],["Telephone Number:","415-857-9554"],["Fax Number:","415-367-1279"],["Email:","jared@enzyme.com"],["Date Summary Prepared:","23-SEPT-2021"],["Device Proprietary Name:","SubtlePET"],["Model Number:","V 2.0.0"],["Common Name:","SubtlePET"],["Regulation Number:","21 CFR 892.1200"],["Regulation Name:","Emission computed tomography system"],["Product Codes:","KPS, LLZ"],["Device Class:","Class II"],["Predicate Device","Trade name: SubtlePET\nManufacturer: Subtle Medical, Inc.\nRegulation Number: 21 CFR 892.1200\nRegulation Name: Emission computed tomography\nsystem\nDevice Class: Class II\nProduct Codes: KPS, LLZ\n510(k) Number: K182336\n510(k) Clearance Date: November 30, 2018"]],"caption_candidate":"Table 1. Subject Device Overview.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211964-p5-t0","doc_id":"K211964","page_num":5,"bbox":[93.63,384.32,523.35,590.54],"n_rows":2,"n_cols":3,"columns":["Predicate Device","Subject Device","Differences"],"rows":[["Predicate Device","Subject Device","Differences"],["SubtlePET is an image\nprocessing software\nintended for use by\nradiologists and nuclear\nmedicine physicians for\ntransfer, storage, and noise\nreduction of\nfluorodeoxyglucose (FDG)\nand amyloid PET images\n(including PET/CT and\nPET/MRI).”","SubtlePET is an image\nprocessing software\nintended for use by\nradiologists and nuclear\nmedicine physicians for\ntransfer, storage, and\nnoise reduction of\nfluorodeoxyglucose\n(FDG), amyloid, 18F-\nDOPA, 18F-DCFPyL, Ga-\n68 Dotatate, and Ga-68\nPSMA radiotracer PET\nimages.","Substantially similar. The\nsubject device IFU\nremoves reference to\nPET/CT and PET/MRI\nimages as the specific\nmodels for those images\nhave been removed, while\nlisting additional tracers to\nreflect the update of the\nmain machine learning\nmodel for PET images to\naccommodate those\ntracers."]],"caption_candidate":"Table 2. Indications of Use Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211964-p6-t0","doc_id":"K211964","page_num":6,"bbox":[98.15,58.05,528.04,537.99],"n_rows":10,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Physical\nCharacteristics","Software package that operates on\noff-the-shelf hardware","Same"],["Computer","Linux Compatible","Same"],["DICOM\nStandard\nCompliance","The software processes DICOM\ncompliant image data","Same"],["Operating\nSystem","Linux","Same"],["Modalities","PET","Same"],["User Interface","None","Same"],["Image\nEnhancement\nAlgorithm\nDescription","The software employs a\nconvolutional neural network-\nbased method in a pixel’s\nneighborhood to generate the\nvalue for each pixel.\nUsing a residual learning\napproach, the software predicts\nthe noise components and\nstructural components. The\nsoftware separates these\ncomponents, which enhances the\nstructure while simultaneously\nreducing the noise.","Same"],["Radiotracers\nsupported","fluorodeoxyglucose (FDG),\namyloid","fluorodeoxyglucose (FDG),\namyloid, 18F-DOPA,\n18F-DCFPyL, Ga-68 Dotatate,\nGa-68 PSMA"],["Deep learning\nmodel(s)","PET, PET/CT, PET/MRI","PET"]],"caption_candidate":"Table 3. Summary of Technological Characteristics Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211966-p6-t0","doc_id":"K211966","page_num":6,"bbox":[77.94,145.16,517.44,682.96],"n_rows":24,"n_cols":9,"columns":["","System","","","Segment 3DPrint","","","Mimics Medical",""],"rows":[["","System","","","Segment 3DPrint","","","Mimics Medical",""],["Version","","","3.2","","","23.0.2","",""],["Manufacturer","","","Medviso AB","","","Materialise NV","",""],["510(k) number","","","K211966","","","K183105","",""],["Classification","","","892.2050\nLLZ, Class II","","","892.2050\nLLZ, Class II","",""],["Intended use","","","same","","","same","",""],["Patient population","","","All with images from\nmedical scanner.","","","Unspecified","",""],["Graphical user interface","","","Yes","","","Yes","",""],["Platform","","","PC","","","PC","",""],["Operating system","","","MS Windows 10","","","MS Windows 10","",""],["Image display monitor","","","Unspecified","","","Resolution of 1280x1024 or\nhigher","",""],["Report display monitor","","","No","","","No","",""],["Patient demographics","","","Yes","","","Yes","",""],["Networking","","","TCP/IP","","","TCP/IP","",""],["DICOM compliant image\ncompression","","","Lossless","","","Lossless","",""],["Image communication","","","Yes","","","Yes","",""],["Image processing annotations","","","Yes","","","Yes","",""],["Linear measurement tools","","","Yes","","","Yes","",""],["Automatic and manual\nsegmentation of object","","","Yes","","","Yes","",""],["Automatic filling and\nsmoothing tools","","","Yes","","","Yes","",""],["Local and remote image\nstorage","","","Yes","","","Yes","",""],["Type of software – custom\nintegrated","","","Yes","","","Yes","",""],["Viewing","","","Yes","","","Yes","",""],["Safety - For use only by a\nlicensed professional","","","Yes","","","Yes","",""]],"caption_candidate":"conclude that Segment 3DPrint is substantially equivalent to the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211966-p8-t0","doc_id":"K211966","page_num":8,"bbox":[134.78,120.48,460.62,200.66],"n_rows":4,"n_cols":6,"columns":["Set","Dice","Jacc","||Dist||\n[mm]","Dist\n[mm]","95th percentile\n[mm]"],"rows":[["Set","Dice","Jacc","||Dist||\n[mm]","Dist\n[mm]","95th percentile\n[mm]"],["Mean","0.96","0.92","0.23","0.03","-"],["SD","0.03","0.05","0.18","0.26","-"],["Max","-","-","-","-","0.93"]],"caption_candidate":"signed distance difference, and 95th is the 95th percentile of the absolute distance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211980-p4-t0","doc_id":"K211980","page_num":4,"bbox":[108.26,118.1,539.86,649.66],"n_rows":11,"n_cols":2,"columns":["Date:","January 10, 2022"],"rows":[["Date:","January 10, 2022"],["Submitter:","GE Healthcare (Tianjin) Company Limited\nNo. 266 Jingsan Road, Tianjin Airport Economic Area\nTianjin, P.R. China 300308"],["Distributor","GE Medical Systems, LLC\n3200 N Grandview BLVD. Waukesha, WI USA 53188"],["Primary Contact\nPerson:","Glen Sabin\nDirector, Regulatory Affairs\nGE Healthcare\nPhone: 262- 5216848\nE-mail: glen.sabin@ge.com"],["Secondary\nContact Person:","Huande Li\nRegulatory Affairs Manager\nGE Healthcare\nPhone: 86-010-57083027\nE-mail: huande.li@ge.com"],["Device Trade\nName:","SIGNA™ Prime"],["Common/Usual\nName:","Magnetic Resonance Diagnostic Device"],["Classification\nNames:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH"],["Predicate\nDevice(s):","SIGNA™ Creator (K143251)"],["Reference\nDevice:","SIGNA™ Premier (K193282)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211980-p5-t0","doc_id":"K211980","page_num":5,"bbox":[108.26,72.24,539.86,663.7],"n_rows":3,"n_cols":2,"columns":["Device\nDescription:","SIGNA™ Prime is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal to-noise ratio, and\nshort scan times. The systems use a combination of time-varying\nmagnet fields (Gradients) and RF transmissions to obtain\ninformation regarding the density and position of elements\nexhibiting magnetic resonance. The system can image in the\nsagittal, coronal, axial, oblique, and oblique planes, using various\npulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 1.5T superconducting magnet\nwith 60cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],"rows":[["Device\nDescription:","SIGNA™ Prime is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal to-noise ratio, and\nshort scan times. The systems use a combination of time-varying\nmagnet fields (Gradients) and RF transmissions to obtain\ninformation regarding the density and position of elements\nexhibiting magnetic resonance. The system can image in the\nsagittal, coronal, axial, oblique, and oblique planes, using various\npulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 1.5T superconducting magnet\nwith 60cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],["Indications for\nUse","The SIGNA Prime is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and\nshort scan times. It is indicated for use as a diagnostic imaging\ndevice to produce axial, sagittal, coronal, and oblique images,\nspectroscopic images, parametric maps, and/or spectra, dynamic\nimages of the structures and/or functions of the entire body,\nincluding, but not limited to, head, neck, TMJ, spine, breast, heart,\nabdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body.\nDepending on the region of interest being imaged, contrast agents\nmay be used. The images produced by SIGNA Prime\nreflect the spatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance.\nThese images and/or spectra when interpreted by a trained\nphysician yield information that may assist in diagnosis."],["Technology:","The SIGNA™ Prime employs the same fundamental scientific\ntechnology as its predicate devices.\nSIGNA™ Prime builds on the 1.5T IPM magnet, newly designed\nGradient Driver, new designed RF transmit architecture, new"]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211980-p6-t0","doc_id":"K211980","page_num":6,"bbox":[108.26,72.24,539.86,648.22],"n_rows":3,"n_cols":2,"columns":["","designed RF receiving chain and new software platform\napplication suite."],"rows":[["","designed RF receiving chain and new software platform\napplication suite."],["Comparison of\nIndications\nfor Use","The changes in technology do not impact the indications for use.\nThe indications for use have not changed, other than to reflect the\nSIGNA™ Prime product name.\nTherefore, the intended use is the same as the predicate device in\naccordance with the FDA’s guidance document “The 510(k)\nProgram: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],["Comparison of\nTechnological\nCharacteristics","Overall, the SIGNA™ Prime employs the same fundamental\nscientific technology as the predicate device.\nSystem Design: There are five notable technological differences\nbetween the SIGNA™ Prime and the predicate device: the 1.5T\nIPM magnet, newly designed Gradient Driver, new designed RF\ntransmit architecture, new designed RF receiving chain and\nnew software platform application suite.\nOperating Principles: The SIGNA™ Prime functions using the\nsame operating principles as the predicate device.\nMaterials: The SIGNA™ Prime and the predicate device both use\nflame retardant materials.\nSafety and Performance Testing: Both the SIGNA™ Prime and\nthe predicate device comply with the same safety and performance\ntesting (see Determination of Substantial Equivalence, below).\nThese technological differences do not raise any different\nquestions regarding safety and effectiveness. Both devices must\naddress questions of whether they provide an adequate level of\nimage quality appropriate for diagnostic use. The performance\ndata described in this submission include results of both bench\ntesting and clinical testing that show the image quality\nperformance of SIGNA™ Prime compared to the predicate device."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K211980-p8-t0","doc_id":"K211980","page_num":8,"bbox":[108.26,72.24,539.86,395.81],"n_rows":2,"n_cols":2,"columns":["","The sample clinical images demonstrate acceptable diagnostic\nimage performance of the SIGNA™ Prime in accordance with the\nFDA Guidance “Submission of Premarket Notifications for\nMagnetic Resonance Diagnostic Devices” issued on November 18,\n2016. The image quality of the SIGNA™ Prime is substantially\nequivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNA™ Prime employs\nequivalent technology to the claimed predicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Prime is substantially equivalent to the predicate device\nto which it has been compared."],"rows":[["","The sample clinical images demonstrate acceptable diagnostic\nimage performance of the SIGNA™ Prime in accordance with the\nFDA Guidance “Submission of Premarket Notifications for\nMagnetic Resonance Diagnostic Devices” issued on November 18,\n2016. The image quality of the SIGNA™ Prime is substantially\nequivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNA™ Prime employs\nequivalent technology to the claimed predicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Prime is substantially equivalent to the predicate device\nto which it has been compared."],["Conclusion:","In conclusion, GE Healthcare considers the SIGNA™\nPrime to be as safe, as effective, with performance that\nis substantially equivalent to the predicate device."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212005-p4-t0","doc_id":"K212005","page_num":4,"bbox":[72.0,63.52,300.93,686.53],"n_rows":47,"n_cols":4,"columns":["","","","510(k)"],"rows":[["","","","510(k)"],["","","",""],["","","","UNi"],["","","",""],["","","","Analyz"],["","","",""],["1.","Submission Sponsor","",""],["","","",""],["","MEDICREA International, In","c.",""],["","","",""],["","5389 Route de Strasbourg -","Vancia",""],["","","",""],["","Rillieux La Pape","",""],["","","",""],["","69140","",""],["","","",""],["","France","",""],["","","",""],["2.","Submission Correspondent","",""],["","","",""],["","Sterling Medical Devices","",""],["","","",""],["","250 Moonachie Road, Suite","400",""],["","","",""],["","Moonachie, NJ 07074","",""],["","","",""],["","Office Phone: (201) 227-756","9",""],["","","",""],["","Contact: Carrie Hetrick, DDS",", MScRSc",""],["","","",""],["","Title: Director of Regulatory","Affairs",""],["","","",""],["3.","Date Prepared","",""],["","","",""],["","June 25, 2021","",""],["","","",""],["4.","Device Identification","",""],["","","",""],["","Trade/Proprietary Name:","UNiD Sp","ine Analyz"],["","","",""],["","Common/Usual Name:","Medical","Image Ma"],["","","",""],["","Classification Name:","System,","image pro"],["","","",""],["","Regulation Number:","21 CFR §","892.2050"],["","","",""],["","Product Code:","LLZ",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K212005-p6-t0","doc_id":"K212005","page_num":6,"bbox":[72.26,257.4,557.74,681.96],"n_rows":12,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","MEDICREA UNiD™ Spine Analyzer v4.0","","","MEDICREA UNiD™ Spine Analyzer v2.0",""],["Manufacturer","MEDICREA International, Inc.","","","MEDICREA International, Inc.","",""],["510(k) Number","To be determined","","","K180091 (Special)","",""],["Device Class","II","","","II","",""],["Product Code(s)","LLZ","","","LLZ","",""],["Regulation\nDescription","Medical Image Management and\nProcessing System (MIMPS)","","","Picture Archiving and Communication\nSystem (PACS)","",""],["Regulation Number","21 CFR §892.2050","","","21 CFR §892.2050","",""],["Indications for use:","The UNiD Spine Analyzer is intended\nfor assisting healthcare professionals\nin viewing and measuring images as\nwell as planning orthopedic surgeries.\nThe device allows surgeons and service\nproviders to perform generic, as well\nas spine related measurements on\nimages, and to plan surgical\nprocedures. The device also includes\ntools for measuring anatomical\ncomponents for placement of surgical\nimplants. Clinical judgment and\nexperience are required to properly\nuse the software.","","","The UNiD Spine Analyzer is intended\nfor assisting healthcare professionals\nin viewing and measuring images as\nwell as planning orthopedic surgeries.\nThe device allows surgeons and service\nproviders to perform generic, as well\nas spine related measurements on\nimages, and to plan surgical\nprocedures. The device also includes\ntools for measuring anatomical\ncomponents for placement of surgical\nimplants. Clinical judgment and\nexperience are required to properly\nuse the software.","",""],["Computer","PC Compatible","","","PC Compatible","",""],["Operating System","Windows + MAC","","","Windows + MAC","",""],["Image Input","Local","","","Local","",""]],"caption_candidate":"Table 5A – Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212005-p7-t0","doc_id":"K212005","page_num":7,"bbox":[72.26,58.44,557.74,686.28],"n_rows":9,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","MEDICREA UNiD™ Spine Analyzer v4.0","","","MEDICREA UNiD™ Spine Analyzer v2.0",""],["Runs on Server","Yes","","","Yes","",""],["Osteotomy Module","Yes","","","Yes","",""],["Generic\nmeasurements","No additional changes","","","The measurement panel allows a user\nto view the measured values of each\ntool. The device allows surgeons and\nservice providers to perform generic,\nas well as spine related measurements\non images, and to plan surgical\nprocedures. The device also includes\ntools for measuring anatomical\ncomponents for placement of surgical\nimplants. Complementary to the pre-\nop measure, this panel also displays\nthe simulated values and shows the\nnormative value. Quality for the\nmeasurement is given coloring, the\nsimulated values depending on\nreference values.","",""],["Spine measurements","MEASURING TOOLS: Contains all\nmeasurement tools (angle, LLordo,\nline, circle, pelvic, T1SPi, SVA)\nNew features internally documented\nand released include SA Analysis,\nSagittal wizard, Coronal wizard,\nTransitional anatomy, Cervical, Lenke\nclassification, and Guide spline.","","","MEASURING TOOLS: Contains all\nmeasurement tools (angle, LLordo,\nline, circle, pelvic, T1SPi, SVA).","",""],["Pre-operative\nplanning","SURGICAL TOOLS: Contains all surgery\ntools (wedge, open, resect)\nNew features internally documented\nand released include wedge auto,\nopen auto, and resect auto surgical\ntools.","","","SURGICAL TOOLS: Contains all surgery\ntools (wedge, open, resect).","",""],["Custom implants","IMPLANTS: Contains all implants (UNiD\nRod, cage, cage selection, screw, screw\nselection).\nNew features internally documented\nand released include UNiD Rod Auto,\ncage auto, screw wizard, and postop\nscrew.","","","IMPLANTS: Contains all implants (UNiD\nRod, cage, cage selection, screw, screw\nselection)","",""],["Database","Yes (implants)","","","Yes (implants)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212005-p8-t0","doc_id":"K212005","page_num":8,"bbox":[72.27,58.44,557.73,422.64],"n_rows":7,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","MEDICREA UNiD™ Spine Analyzer v4.0","","","MEDICREA UNiD™ Spine Analyzer v2.0",""],["","The subject device update also\nincludes the addition of a selection of\nimplant templates among a\npreselected database of Medtronic\nstandard implants cleared in in the\nfollowing 510(k)s: K073291, K083026,\nK091813, K100175, K110543, K113528,\nK120368, K150135, K152277, K172199,\nK172328, and K201267.","","","","",""],["Case sharing","Yes","","","Yes","",""],["Human intervention\nfor interpretation and\nmanipulation of\nimages","Required","","","Required","",""],["Web content","Yes","","","Yes","",""],["Reference\ninformation provided\nto user during surgical\nplanning","Display of reference data to user\nduring surgery planning:\nNormative data\nPredictive model outputs from one of\nthree predictive models, depending on\nprocedure type (degenerative, adult\ndeformity, pediatric deformity)","","","Display of reference data to user\nduring surgery planning:\nNormative data","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212012-p5-t0","doc_id":"K212012","page_num":5,"bbox":[66.63,360.78,562.52,762.96],"n_rows":12,"n_cols":13,"columns":["","","QLAB","","","Voluson","","","Follicle Clarity","","","Equivalence",""],"rows":[["","","QLAB","","","Voluson","","","Follicle Clarity","","","Equivalence",""],["","","(Predicate Device)","","","(Reference Device)","","","(Subject Device)","","","Description",""],["Administrative Information","","","","","","","","","","","",""],["Product Name","QLAB Advanced\nQuantification Software\n13.0","","","Voluson E6/E8/\nE8Expert/E10 Diagnostic\nUltrasound System","","","Follicle Clarity Software","","","N/A","",""],["510(k) Holder","Philips Ultrasound, Inc.","","","GE Healthcare Austria\nGmbH & Co OG","","","Cycle Clarity LLC","","","N/A","",""],["510(k) Number","K191647","","","K122327","","","TBD","","","N/A","",""],["Common Name","Picture Archiving and\nCommunications\nSystem","","","-Ultrasonic Pulsed Doppler\nImaging System\n-Ultrasonic Pulsed Echo\nImaging System\n-Diagnostic Ultrasound\nTransducer","","","Picture Archiving and\nCommunications System","","","Identical to\npredicate","",""],["Regulation","21 C.F.R. § 892.2050","","","21 C.F.R. §892.1550\n21 C.F.R. §892.1560\n21 C.F.R. §892.1570","","","21 C.F.R. § 892.2050","","","Identical to\npredicate","",""],["Product Code","QIH","","","IYN, IYO, ITX","","","QIH","","","Identical to\npredicate","",""],["Regulatory Class","II","","","II","","","II","","","Identical to\npredicate","",""],["Intended Use","","","","","","","","","","","",""],["Intended Use","QLAB Advanced\nQuantification Software\nis a software application\npackage. It is designed\nto view and quantify\nimage data acquired on\nPhilips ultrasound\nsystems.","","","The device is a general-\npurpose ultrasound system.\nSpecific clinical\napplications remain the\nsame as previously\ncleared: Fetal/OB,\nAbdominal (including\nGYN, pelvic and infertility\nmonitoring/follicle\ndevelopment); Pediatric;\nSmall Organ (breast,\ntestes, thyroid, etc.);\nNeonatal and Adult","","","Follicle Clarity Software\nis a software application\npackage. It is designed to\nview and quantify image\ndata acquired on\ncompatible ultrasound\nsystems.","","","Same2\nPredicate and\nsubject devices are\nsoftware intended to\nquantify image data\non compatible\nultrasounds.\nThe subject device\nintended use is the\nsame as the\nSonoAVC software\nincluded in the\nreference device.","",""]],"caption_candidate":"Table 1: Overview of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212012-p6-t0","doc_id":"K212012","page_num":6,"bbox":[66.61,80.4,562.54,696.84],"n_rows":9,"n_cols":7,"columns":["","","","Cephalic; Cardiac (adult\nand pediatric); Musculo-\nskeletal Conventional and\nSuperficial; Peripheral\nVascular; Transvaginal;\nTransrectal; and\nIntraoperative (abdominal,\nPV and neurological).1","","",""],"rows":[["","","","Cephalic; Cardiac (adult\nand pediatric); Musculo-\nskeletal Conventional and\nSuperficial; Peripheral\nVascular; Transvaginal;\nTransrectal; and\nIntraoperative (abdominal,\nPV and neurological).1","","",""],["Prescription\nOnly?","","Yes","Yes","Yes","Identical to\npredicate",""],["","Technological Characteristics","","","","",""],["Application\nDescription","","QLAB software\nincludes multiple\nfeatures for automated\ndetection and\nmeasurement of\nstructures in\ngynecological,\nobstetrics, cardiac, and\nother clinical\napplications. K191647\ndescribes the particular\napplication for\nmeasuring cardiac\nstructures within the\nultrasound images using\nautomatic segmentation\ntechnology. The\nsoftware utilizes\n“locked” (non-adaptive)\nmachine learning\nalgorithms to identify\nthe contours of the\ntargeted structure within\nthe ultrasound image.\nA report of\nmeasurement data is\ndisplayed.","SonoAVC software detects\nhypoechoic structures (i.e.,\nfollicles) in transvaginal\nultrasound images and\nmeasures their size. The\nsoftware utilizes\nalgorithms to identify the\ncontours of the targeted\nstructure within the\nultrasound image. A\nreport of measurement\ndata is displayed.","Follicle Clarity software\ndetects hypoechoic\nstructures (i.e., follicles)\nin transvaginal ultrasound\nimages and measures\ntheir size. The application\nmeasures structures\nwithin the ultrasound\nimages using automatic\nsegmentation technology.\nThe software utilizes\n“locked” (non-adaptive)\nmachine learning\nalgorithms to identify the\ncontours of the targeted\nstructure within the\nultrasound image. A\nreport of measurement\ndata is displayed.","Equivalent\nAll of the software\nsystems utilize\nproprietary\nalgorithms to detect\nand quantify\nstructures within\nultrasound images.\nSubject and\npredicate devices\nutilize machine\nlearning/AI\nalgorithms to\nidentify specific\ncontours of the\nanatomy using\nautomatic\nsegmentation\ntechnology and\nquantify structures\nbased on this\nanalysis.\nSubject and\nreference devices\nspecifically detect\nand analyze follicle\nnumber and size.",""],["Target User\nPopulation","","Interpreting clinicians","Interpreting clinicians","Interpreting clinicians","Identical to\npredicate",""],["How Supplied?","","Software application","Software application\n(SonoAVC software is\nsupplied with the Voluson\nultrasound hardware)","Software application","Identical to\npredicate",""],["Use of machine\nlearning\nalgorithm?","","Yes","Unknown","Yes","Identical to\npredicate",""],["Required Patient\nClinical Data\n(Imaging) Format","","DICOM","NA","DICOM","Identical to\npredicate",""],["Ultrasound\nCompatibility","","Philips","Voluson\nE6/E8/E8Expert/E10","-Voluson, E6, E8, E10\n-Philips\n-Siemens Acuson\nVersion","Equivalent\nSubject device has\nbeen validated to\nprocess ultrasound\nimages from Philips\nand Voluson\nultrasound systems\nand others.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212067-p7-t0","doc_id":"K212067","page_num":7,"bbox":[72.17,102.38,531.31,502.22],"n_rows":9,"n_cols":7,"columns":["Specification/\nAttribute","","Deep Learning Image","","","Deep Learning Image",""],"rows":[["Specification/\nAttribute","","Deep Learning Image","","","Deep Learning Image",""],["","","Reconstruction","","","Reconstruction",""],["","","(Predicate Device, K193170)","","","(Proposed Device)",""],["Technology","Utilizes a dedicated Deep Neural\nNetwork (DNN) which was\ntrained on the Revolution family\nCT Scanners and designed\nspecifically to generate high\nquality CT images","","","Same","",""],["Clinical Workflow","Select recon type and strength\n(Low, Medium, High).","","","Same","",""],["Clinical Use","Routine Clinical Use","","","Same","",""],["Reference\nprotocols/dose","Using the same Reference\nprotocols provided on the\nRevolution EVO system for\nASiR-V","","","Using the same Reference\nprotocols provided on the\nRevolution Ascend system for\nASiR-V","",""],["IQ performance vs dose","Image noise, low contrast\ndetectability, spatial resolution,\nand low signal artifact\nsuppression as good or better\nthan ASiR-V on Revolution EVO","","","Image noise, low contrast\ndetectability, spatial resolution,\nand low signal artifact\nsuppression as good or better\nthan ASiR-V on Revolution\nAscend","",""],["Deployment\nEnvironment","On GE’s Edison Platform.","","","Same","",""]],"caption_candidate":"510(k) Premarket Notification Submission – DLIR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212074-p4-t0","doc_id":"K212074","page_num":4,"bbox":[126.86,425.65,520.34,626.56],"n_rows":9,"n_cols":2,"columns":["Device Classification Name","Medical Image Management and Processing System"],"rows":[["Device Classification Name","Medical Image Management and Processing System"],["510(k) Number","K183460"],["Device Name","ClariCT.AI"],["Applicant","ClariPi Inc.\n3F, 70-15, Ihwajang-gil, Jongno-gu\nSeoul, Korea, Republic of [03088]"],["Regulation Number","892.2050"],["Classification Product Code","LLZ"],["Date Received","12/13/2018"],["Decision Date","06/13/2019"],["510k Review Panel","Radiology"]],"caption_candidate":"equivalent to the following commercially available software:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212074-p5-t0","doc_id":"K212074","page_num":5,"bbox":[126.28,388.6,549.08,687.1],"n_rows":8,"n_cols":7,"columns":["Item","","Subject Device","","","Predicate Device",""],"rows":[["Item","","Subject Device","","","Predicate Device",""],["","","ClariCT.AI","","","ClariCT.AI (K183460)",""],["Intended\nUse","ClariCT.AI, is a software device\nintended for networking,\ncommunication, processing and\nenhancement of CT images in\nDICOM format regardless of the\nmanufacturer of CT scanner or\nmodel.","","","ClariCT.AI, is a software device\nintended for networking,\ncommunication, processing and\nenhancement of CT images in\nDICOM format regardless of the\nmanufacturer of CT scanner or\nmodel.","",""],["Intended\nUser","Radiologists and specialists","","","Radiologists and specialists","",""],["Modality\nSupport","CT","","","CT","",""],["Noise\nReduction\nMethod","Noise reduction is performed with the\nuse of pre-trained deep learning\nmodels.","","","Noise reduction is performed with the\nuse of pre-trained deep learning\nmodels.","",""],["Image\nFormat","DICOM","","","DICOM","",""],["Components\nAnd\nHardware\nRequirement","Window Operating System,\nPC Hardware, CUDA supported\ngraphics card or equivalent.","","","Window or Linux Operating System.\nPC Hardware supported graphics\ncard or equivalent.","",""]],"caption_candidate":"and the subject device is identical in performance to the legally marketed device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p5-t0","doc_id":"K212100","page_num":5,"bbox":[72.04,72.4,554.96,194.05],"n_rows":6,"n_cols":9,"columns":["","Classification Name","","","21 CFR Number","","","Product Code",""],"rows":[["","Classification Name","","","21 CFR Number","","","Product Code",""],["Ultrasonic Pulsed Doppler Imaging System","","","892.1550","","","IYN","",""],["Ultrasonic Pulsed Echo Imaging System","","","892.1560","","","IYO","",""],["Diagnostic Ultrasound Transducer","","","892.1570","","","ITX","",""],["Electronic Stethoscope","","","870.1875","","","DQD","",""],["Electrocardiograph","","","870.2340","","","DPS","",""]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p7-t0","doc_id":"K212100","page_num":7,"bbox":[72.08,86.15,539.93,717.73],"n_rows":4,"n_cols":7,"columns":["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison"],"rows":[["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison"],["","","Kosmos (This 510(k)","","","",""],["","","Submission)","","","",""],["Intended Use\n/ Indications\nfor Use","Kosmos is intended to be\nused by qualified and\ntrained healthcare\nprofessionals in the\nclinical assessment for\nthe following clinical\napplications by acquiring,\nprocessing, displaying,\nmeasuring, and storing\nultrasound images, or\nsynchronized ultrasound\nimages,\nelectrocardiogram (ECG)\nrhythms, and digital\nauscultation (DA) sounds\nand waveforms.\nWith respect to its\nultrasound imaging\ncapabilities, Kosmos is a\ngeneral purpose\ndiagnostic ultrasound\nsystem used in the\nfollowing clinical\napplications and modes\nof operation:\n• Clinical\nApplications:\nCardiac,\nThoracic/Lung,\nAbdominal,\nVascular/Peripheral\nVascular,\nMusculoskeletal, and\ninterventional\nguidance (includes\nneedle/catheter\nplacement, fluid\ndrainage, and nerve\nblock)\n• Modes of Operation:\nB-mode, M-mode,\nColor Doppler,\nPulsed-Wave (PW)\nDoppler,\nContinuous-Wave\n(CW) Doppler,\nCombined Modes of\nB+M, and B+CD,\nB+PW, B+CW, and\nHarmonic Imaging\nKosmos is intended to be\nused in clinical care and\nmedical education\nsettings on adult and\npediatric patient\npopulations.","","","Kosmos is intended to be\nused by qualified and\ntrained healthcare\nprofessionals in the clinical\nassessment of the cardiac\nand pulmonary systems and\nthe abdomen by acquiring,\nprocessing, displaying,\nmeasuring, and storing\nsynchronized ultrasound\nimages, electrocardiogram\n(ECG) rhythms, and digital\nauscultation (DA) sounds\nand waveforms.\nWith respect to its\nultrasound imaging\ncapabilities, Kosmos is a\ngeneral purpose diagnostic\nultrasound system used in\nthe following clinical\napplications and modes of\noperation:\n• Clinical Applications:\nCardiac,\nThoracic/Lung,\nAbdominal, Peripheral\nVascular, and Image\nGuidance for\nNeedle/Catheter\nPlacement\n• Modes of Operation:\nB-mode, M-mode,\nColor Doppler,\nCombined Modes of\nB+M and B+CD, and\nHarmonic Imaging\nKosmos is intended to be\nused in clinical care and\nmedical education settings\non adult and pediatric\npatient populations. The\ndevice is non-invasive,\nreusable, and intended to\nbe used on one patient at a\ntime.\nType of Use: Prescription\nUse (Part 21 CFR 801\nSubpart D)","Vscan Air is a battery-\noperated software-based\ngeneral-purpose\nultrasound imaging\nsystem for use by\nqualified and trained\nhealthcare professionals\nor practitioners that are\nlegally authorized or\nlicensed by law in the\ncountry, state or other\nlocal municipality in\nwhich he or she practices.\nThe users may or may not\nbe working under\nsupervision or authority\nof a physician. Users may\nalso include medical\nstudents working under\nthe supervision or\nauthority of a physician\nduring their education /\ntraining. The device is\nenabling visualization and\nmeasurement of\nanatomical structures and\nfluid including blood\nflow.\nVscan Air’s pocket-sized\nportability and simplified\nuser interface enables\nintegration into training\nsessions and examinations\nin professional healthcare\nfacilities (ex. Hospital,\nclinic, medical office),\nhome environment,\nroad/air ambulance and\nother environments as\ndescribed in the user\nmanual. The information\ncan be used for\nbasic/focused assessments\nand adjunctively with\nother medical data for\nclinical diagnosis\npurposes during routine,\nperiodic follow-up, and\ntriage.\nVscan Air supports Black/\nwhite (B-mode), Color\nflow (Color doppler),\nCombined (B + Color\nDoppler) and Harmonic\nimaging modes with both\nthe curved and linear","Addition of the following\nClinical Applications:\n• Vascular\n• Musculoskeletal\n• Fluid Drainage\n• Nerve Block\nAddition of the following\nmodes of operation:\n• Pulsed-Wave (PW)\nDoppler\n• Continuous-Wave\n(CW) Doppler\n• Combined Modes of\nB+PW and B+CW"]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p8-t0","doc_id":"K212100","page_num":8,"bbox":[72.07,72.4,539.93,609.45],"n_rows":6,"n_cols":9,"columns":["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],"rows":[["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],["","","","Kosmos (This 510(k)","","","","",""],["","","","Submission)","","","","",""],["","","The device is non-\ninvasive, reusable, and\nintended to be used on\none patient at a time.\nType of Use:\nPrescription Use (Part 21\nCFR 801 Subpart D)","","","","array transducers.\nWith the curved array\ntransducer of the dual\nheaded probe solution, the\nspecific clinical\napplications and exam\ntypes include: abdominal,\nfetal/obstetrics,\ngynecological, urology,\nthoracic/lung, cardiac\n(adult and pediatric, 40 kg\nand above),\nvascular/peripheral\nvascular, musculoskeletal\n(conventional), pediatrics,\ninterventional guidance\n(includes free hand\nneedle/catheter\nplacement, fluid drainage,\nnerve block and biopsy).\nWith the linear array\ntransducer of the dual\nheaded probe solution, the\nspecific clinical\napplications and exam\ntypes include:\nvascular/peripheral\nvascular, musculoskeletal\n(conventional and\nsuperficial), small organs,\nthoracic/lung, ophthalmic,\npediatrics, neonatal\ncephalic, interventional\nguidance (includes free\nhand needle/catheter\nplacement, fluid drainage,\nnerve block, vascular\naccess and biopsy).\nType of Use: Prescription\nUse (Part 21 CFR 801\nSubpart D)","",""],["","Ultrasound Substantial Equivalence (Technological Characteristics)","","","","","","",""],["Transducer\nTypes","","• Phased Array\n• Linear Array","","","• Phased Array","• Curved Array\n• Linear Array","Addition of Linear Array\nTransducer",""]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p9-t0","doc_id":"K212100","page_num":9,"bbox":[72.04,72.4,539.96,719.45],"n_rows":8,"n_cols":7,"columns":["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison"],"rows":[["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison"],["","","Kosmos (This 510(k)","","","",""],["","","Submission)","","","",""],["Clinical\nApplications","Phased Array\nTransducer:\nAnatomy/ Region of\nInterest:\n• Abdominal\n• Pediatric\n• Cardiac Adult\n• Cardiac Pediatric\n• Peripheral Vascular\n• Thoracic/Lung\nInterventional Guidance:\n• Nonvascular","","","Phased Array\nTransducer:\nAnatomy/ Region of\nInterest:\n• Abdominal\n• Pediatric\n• Cardiac Adult\n• Cardiac Pediatric\n• Peripheral Vascular\n• Thoracic/Lung\nInterventional Guidance:\nNonvascular","","Remains unchanged"],["","Linear Array\nTransducer:\nAnatomy/ Region of\nInterest:\n• Vascular/Peripheral\nVascular\n• Musculoskeletal\nInterventional guidance\n• Needle/catheter\nplacement\n• Fluid drainage\n• Nerve block","","","","Linear Array\nTransducer:\nAnatomy/ Region of\nInterest:\n• Vascular/peripheral\nvascular\n• Musculoskeletal\n(conventional and\nsuperficial)\n• Small organs\n• Thoracic/lung\n• Ophthalmic\n• Pediatrics\n• Neonatal cephalic\nInterventional guidance\n• Free hand\nneedle/catheter\nplacement\n• Fluid drainage\n• Nerve block\n• Vascular access and\nbiopsy","Addition of Linear Array\nTransducer Clinical\nApplications"],["Transducer\nFrequency","Phased Array\nTransducer:\n1.5 – 4.5 MHz with center\nfrequency 3Hz","","","Phased Array\nTransducer:\n1.5 – 4.5 MHz with center\nfrequency 3Hz","","Remains unchanged"],["","Linear Array\nTransducer:\n4-11 MHz with center\nfrequency 7.5 MHz","","","","Linear Array\nTransducer :\n3-12 MHz with center\nfrequency of 7.7 MHz","Addition of technological\ncharacteristics for Linear\nArray Transducer"],["Modes of\nOperation","Phased Array\nTransducer:\n• B-mode\n• M-mode\n• Color Doppler","","","Phased Array\nTransducer:\n• B-mode\n• M-mode\n• Color Doppler","","Addition of the following\nmodes of operation:\n• Pulsed-Wave (PW)\nDoppler\n• Continuous-Wave"]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p10-t0","doc_id":"K212100","page_num":10,"bbox":[72.04,72.4,539.96,680.21],"n_rows":16,"n_cols":9,"columns":["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],"rows":[["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],["","","","Kosmos (This 510(k)","","","","",""],["","","","Submission)","","","","",""],["","","• Pulsed-Wave (PW)\nDoppler\n• Continuous-Wave\n(CW) Doppler\n• Combined Modes:\nB+M, B+CD,\nB+PW, and B+CW\n• Harmonic Imaging","","","• Combination Modes:\nB+M, B+CD\n• Harmonic Imaging","","(CW) Doppler\n• Combined Modes:\nB+PW and B+CW",""],["","","Linear Array\nTransducer:\n• B-mode","","","","Linear Array\nTransducer:\n• B-mode\n• Color Doppler\n• Combined Modes of\nB + CD\n• Harmonic Imaging","Addition of Linear Array\nTransducer B-mode",""],["510(k) Track","","Phased Array\nTransducer:\nTrack 3","","","Phased Array\nTransducer:\nTrack 3","","Remains unchanged",""],["","","Linear Array\nTransducer:\nTrack 3","","","","Linear Array\nTransducer:\nTrack 3","Remains unchanged",""],["","DA (Digital Auscultation) and ECG Substantial Equivalence (Technological Characteristics)","","","","","","",""],["DA Pickup\nSensor and\nProcessing","","Audio microphone +\ndigital signal processing\nSampling Rate: 12.7 kHz","","","Audio microphone + digital\nsignal processing\nSampling Rate: 12.7 kHz","","Remains unchanged",""],["DA Filter\nModes","","Heart/Midrange (50 – 600\nHz)","","","Heart/Midrange (50 – 600\nHz)","","Remains unchanged",""],["DA Sound\nAmplification","","Analog gain: 20 dB\nDigital gain: user\nadjustable up to 25 dB","","","Analog gain: 20 dB\nDigital gain: user\nadjustable up to 25 dB","","Remains unchanged",""],["DA Volume\nControl","","Yes; 15 volume steps\navailable","","","Yes; 15 volume steps\navailable","","Remains unchanged",""],["DA Ambient\nNoise\nReduction","","Yes","","","Yes","","Remains unchanged",""],["DA Direct\nListening","","Sounds can be listened to\nin real time using a\ndigital-to-analog binaural\nheadset","","","Sounds can be listened to\nin real time using a\ndigital-to-analog\nbinaural headset","","Remains unchanged",""],["ECG Non-\nContinuous\nMonitoring\nLeads","","3-lead, single-channel,\nuser-supplied commercial\nelectrodes","","","3-lead, single-channel,\nuser-supplied\ncommercial electrodes","","Remains unchanged",""],["ECG\nAnatomical\nSites","","Chest (torso) and Leg","","","Chest (torso) and Leg","","Remains unchanged",""]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p11-t0","doc_id":"K212100","page_num":11,"bbox":[72.07,72.4,539.94,714.98],"n_rows":7,"n_cols":9,"columns":["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],"rows":[["Feature","","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","Comparison",""],["","","","Kosmos (This 510(k)","","","","",""],["","","","Submission)","","","","",""],["ECG\nLeadwires\nand Trunk\nAssembly","","Combines trunk cable and\nthree leadwires into a\nsingle, non-sterile,\nreusable assembly that\nforms a conduction\nchannel for transmitting\nsignals from user-supplied\nclip-style electrodes\naffixed to patient skin to\nthe Thor probe","","","Combines trunk cable and\nthree leadwires into a\nsingle, non-sterile, reusable\nassembly that forms a\nconduction channel for\ntransmitting signals from\nuser-supplied clip-style\nelectrodes affixed to patient\nskin to the Thor probe","","Remains unchanged",""],["DA and ECG\nVisualization","","Sounds and ECG\nwaveforms can be\nvisualized and recorded\non the Thor tablet with or\nwithout an internet\nconnection","","","Sounds and ECG\nwaveforms can be\nvisualized and recorded on\nthe Thor tablet with or\nwithout an internet\nconnection","","Remains unchanged",""],["","System Characteristics","","","","","","",""],["Dimensions\nand Weight","","Handheld tablet display\nunit (proprietary) –\nKosmos Bridge\n• Height: 146 mm\n• Width: 216mm\n• Depth: 59mm\n• Weight: 657g\nKosmos Torso Probe\n(Phased Array – ECG,\nDA, and Ultrasound)\n• Height: 150mm\n(excluding cable (the\nhard plastic housing\nlength))\n• Width: 56mm\n• Depth: 35mm\n• Weight: 290 grams\n(with ferrite-\nequipped cable)\n• Cable dimensions:\n1.8 meters\nKosmos Torso-One Probe\n(Phased Array –\nUltrasound Only)\n• Height: 150 mm\n(excluding cable (the\nhard plastic housing\nlength))\n• Width: 56 mm\n• Depth: 35 mm\n• Weight: 275 grams\n(with ferrite-\nequipped cable)\n• Cable dimensions:","","","Handheld tablet display\nunit (proprietary) –\nKosmos Bridge\n• Height: 146 mm\n• Width: 216mm\n• Depth: 59mm\n• Weight: 657g\nKosmos Torso Probe\n• Height: 150mm\n(excluding cable (the\nhard plastic housing\nlength))\n• Width: 56mm\n• Depth: 35mm\n• Weight: 290 grams\n(with ferrite-equipped\ncable)\n• Cable dimensions: 1.8\nmeters","Dimension and weight\n(maximum)\n• Length: 131\n• Width: 64\n• Height: 31\n• Weight: 205 +/- 3g\nLinear Array Transducer\n• Footprint: 40 mm x 7\nmm (lens)","Addition of the following\ntransducers:\n• Kosmos Torso-One\n(Ultrasound-Only\nProbe)\n• Kosmos Torso-One\n– USB (Ultrasound-\nOnly Probe)\n• Kosmos Lexsa\n(Linear Probe)",""]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p12-t0","doc_id":"K212100","page_num":12,"bbox":[72.04,72.4,539.96,624.18],"n_rows":9,"n_cols":9,"columns":["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","","","Comparison"],"rows":[["Feature","","Subject Device:","","Predicate Device:\nKosmos (K193518)","Reference Device:\nVscan Air (K202035)","","","Comparison"],["","","Kosmos (This 510(k)","","","","","",""],["","","Submission)","","","","","",""],["","1.8 meters\nKosmos Torso-One Probe\nUSB (Phased Array –\nUltrasound Only)\n• Height: 150 mm\n(excluding cable (the\nhard plastic housing\nlength))\n• Width: 56 mm\n• Depth: 35 mm\n• Weight: 267 grams\n(with ferrite-\nequipped cable)\n• Cable dimensions:\n1.5 meters\nKosmos Lexsa Probe\n(Linear Array)\n• Height: 150 mm\n(excluding cable (the\nhard plastic housing\nlength))\n• Width: 56 mm\n• Depth: 35 mm\n• Weight: 275 grams\n(with ferrite-\nequipped cable)\n• Cable dimensions:\n1.8 meters","","","","","","",""],["Power\nSource","Mains and battery\noperated (rechargeable\nlithium ion battery)","","","Mains and battery operated\n(rechargeable lithium ion\nbattery)","","","","Remains unchanged"],["Patient\nContact\nMaterials","Probe and ECG\nLeadwires materials are\nbiocompatible","","","Probe and ECG Leadwires\nare biocompatible","","","","Remains unchanged"],["Ingress\nProtection\n(IP) Rating","• Kosmos Bridge:\nIP22\n• All Probes: IPX7","","","• Kosmos Bridge: IP22\n• Torso Probe: IPX7","","","","Remains unchanged"],["DICOM","Yes","","","Yes","","","","Remains unchanged"],["Wireless\nNetworking","• IEEE 802.11\na/b/g/n/ac\n• Bluetooth 4.2 or later","","","• IEEE 802.11\na/b/g/n/ac\n• Bluetooth 4.2 or later","","","","Remains unchanged"]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p13-t0","doc_id":"K212100","page_num":13,"bbox":[72.04,116.9,539.97,712.73],"n_rows":13,"n_cols":5,"columns":["","Standards","","Standard Designation\nNumber and Date","Title of Standard"],"rows":[["","Standards","","Standard Designation\nNumber and Date","Title of Standard"],["","Developing","","",""],["","Organization","","",""],["CISPR/CIS/B","","","CISPR 11:2015+\nAMD1:2016+AMD2:2019\nCSV Consolidated version","Industrial, scientific and medical equipment -\nRadio-frequency disturbance characteristics -\nLimits and methods of measurement"],["ANSI AAMI\nIEC","","","ES60601-1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012 and\nA2:2010/(R)2012","Medical electrical equipment - Part 1: General\nrequirements for basic safety and essential\nperformance (IEC 60601-1:2005, MOD)"],["ANSI AAMI\nIEC","","","60601-1-2:2014","Medical electrical equipment - Part 1-2:\nGeneral requirements for basic safety and\nessential performance - Collateral Standard:\nElectromagnetic disturbances - Requirements\nand tests"],["IEC","","","60601-1-6 Edition 3.1\n2013-10","Medical electrical equipment - Part 1-6:\nGeneral requirements for basic safety and\nessential performance - Collateral standard:\nUsability"],["IEC","","","60601-2-37 Edition 2.1\n2015","Medical electrical equipment - Part 2-37:\nParticular requirements for the basic safety and\nessential performance of ultrasonic medical\ndiagnostic and monitoring equipment"],["ISO","","","10993-1:2018","Biological evaluation of medical devices - Part\n1: Evaluation and testing within a risk\nmanagement proce"],["ISO","","","14971:2019","Medical devices - Application of risk\nmanagement to medical devices"],["IEC","","","62304 Edition 1.1 2015-06\nCONSOLIDATED\nVERSION","Medical device software - Software life cycle\nprocesses"],["IEC","","","62366-1 Edition 1.0 2015-\n02","Medical devices - Part 1: Application of\nusability engineering to medical devices\n[Including CORRIGENDUM 1 (2016)]"],["ISO","","","15223-1 Third Edition\n2016-11-01","Medical devices - Symbols to be used with\nmedical device labels, labelling, and\ninformation to be supplied - Part 1: General\nrequirements"]],"caption_candidate":"characteristics as the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212100-p14-t0","doc_id":"K212100","page_num":14,"bbox":[72.04,72.38,539.93,380.12],"n_rows":9,"n_cols":5,"columns":["","Standards","","Standard Designation\nNumber and Date","Title of Standard"],"rows":[["","Standards","","Standard Designation\nNumber and Date","Title of Standard"],["","Developing","","",""],["","Organization","","",""],["IEC","","","62359 Edition 2.1 2017-09\nCONSOLIDATED\nVERSION","Ultrasonics - Field characterization - Test\nmethods for the determination of thermal and\nmechanical indices related to medical\ndiagnostic ultrasonic fields"],["NEMA","","","UD 2-2004 (R2009)","Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3"],["AIM","","","Standard 7351731 Rev.\n2.00 2017-02-23","Ultrasonics - Field characterization - Test\nmethods for the determination of thermal and\nmechanical indices related to medical\ndiagnostic ultrasonic fields"],["ANSI AAMI","","","EC53:2013","ECG trunk cables and patient leadwires"],["AAMI","","","TIR57:2016","Principles for medical device security - Risk\nmanagement."],["AAMI","","","TIR 30:2011","A Compendium Of Processes, Materials, Test\nMethods, And Acceptance Criteria For\nCleaning Reusable Medical Devices"]],"caption_candidate":"Traditional 510(k) Premarket Notification – Kosmos","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p4-t0","doc_id":"K212116","page_num":4,"bbox":[72.66,224.18,536.26,298.01],"n_rows":4,"n_cols":2,"columns":["Contact Person:","Vicki Lin (Regulatory Specialist)"],"rows":[["Contact Person:","Vicki Lin (Regulatory Specialist)"],["Phone:","609-865-8659"],["Email:","vicki.lin@vysioneer.com"],["Date Summary Prepared:","September 10, 2021"]],"caption_candidate":"33 Rogers St. #308, Cambridge, MA 02142","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p4-t1","doc_id":"K212116","page_num":4,"bbox":[72.66,375.41,536.26,442.9],"n_rows":4,"n_cols":2,"columns":["Trade Name:","VBrain-OAR"],"rows":[["Trade Name:","VBrain-OAR"],["Common Name:","Radiological Image Processing Software for\nRadiation Therapy"],["",""],["Regulation Number / Product Code:","21 CFR 892.2050 / QKB"]],"caption_candidate":"5.2 Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p6-t0","doc_id":"K212116","page_num":6,"bbox":[72.7,483.18,539.76,708.73],"n_rows":16,"n_cols":4,"columns":["","Proposed Device","Primary Predicate",""],"rows":[["","Proposed Device","Primary Predicate",""],["","","","Reference Device"],["","","Device",""],["","","",""],["","Vysioneer Inc.","Xiamen Manteia\nTechnology LTD.","Brainlab AG"],["Company","","",""],["","","",""],["Device Name","VBrain-OAR","AccuContour™","iPlan"],["510k Number","K212116","K191928","K113732"],["Regulation No.","21CFR 892.2050","21CFR 892.2050","21CFR 892.1750"],["Classification","II","II","II"],["Product Code","QKB","QKB","JAK/LLZ"],["","VBrain-OAR is a\nsoftware device intended\nto assist trained\nradiotherapy personnel","It is used by radiation\noncology department to\nregister multimodality\nimages and segment\n(non-contrast) CT","iPlan's indications for\nuse are the viewing,\npresentation and\ndocumentation of\nmedical imaging,"],["Intended","","",""],["Use/Indication for Use","","",""],["","","",""]],"caption_candidate":"Table 5-1. Comparison with the Predicate and Reference Devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p8-t0","doc_id":"K212116","page_num":8,"bbox":[72.52,81.12,539.65,712.45],"n_rows":8,"n_cols":4,"columns":["","Proposed Device","Primary Predicate","Reference Device"],"rows":[["","Proposed Device","Primary Predicate","Reference Device"],["","","",""],["","","Device",""],["","","",""],["","brain; it is not intended\nto be used with images\nof other body parts.\nVBrain-OAR also\ncontains the automatic\nimage registration\nfeature to register\nvolumetric medical\nimage data. (e.g., MR,\nCT). It allows rigid\nimage registration to\nadjust the spatial\nposition and orientation\nof two images.\nRadiation therapy\ntreatment personnel\nmust finalize (confirm or\nmodify) the contours\ngenerated by VBrain-\nOAR, as necessary,\nusing an external\nplatform available at the\nfacility that supports\nDICOM-RT\nviewing/editing\nfunctions, such as image\nvisualization software\nand treatment planning\nsystem.","","professionals, including\nbut not limited to\nsurgeons and\nradiologists."],["","VBrain-OAR is a\nsoftware application\nsystem indicated for use\nin the contouring\n(segmentation) of brain\nMRI images for the\norgans at risk (OAR) in\nthe brain during\nradiation treatment\nplanning and in the\nregistration of multi-\nmodality images. The\ndevice consists of 2\nalgorithm modules,\nwhich are contouring","The proposed device,\nAccuContour, is a\nstandalone software\nwhich is used by\nradiation oncology\ndepartment to register\nmultimodality images\nand segment (non-\ncontrast) CT images, to\ngenerate needed\ninformation for\ntreatment planning,\ntreatment evaluation and\ntreatment adaptation.","iPlan is a software based\ntreatment planning\napplication providing\nfunctionalities like\nviewing, processing and\ndocumentation of\nmedical data including\ndifferent modules for\nimage preparation,\nimage fusion, image\nsegmentation where the\nresult is a treatment plan\nthat can be used e.g. for\nstereotactic and/or image\nguided surgery."],["Device Description","","",""],["","","",""]],"caption_candidate":"VBrain-OAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p9-t0","doc_id":"K212116","page_num":9,"bbox":[72.44,81.12,539.58,700.33],"n_rows":5,"n_cols":4,"columns":["","Proposed Device","Primary Predicate","Reference Device"],"rows":[["","Proposed Device","Primary Predicate","Reference Device"],["","","",""],["","","Device",""],["","","",""],["","algorithm module and\nregistration algorithm\nmodule, and a workflow\nmanagement module.\nThe modules can work\nindependently, and yet\ncan be integrated with\neach other.\nThe contouring\n(segmentation)\nalgorithm module\nconsists of image\npreprocessing, deep\nlearning neural\nnetworks, and\npostprocessing\ncomponents, and is\nintended to contour\norgans at risk in the\nbrain on the axial T1\ncontrast-enhanced MR\nimages. It utilizes deep\nlearning neural networks\nto generate contours for\nthe organs at risk in the\nbrain and export the\nresults as DICOM-RT\nobjects (using the RT\nStructure Set ROI\nContour attribute,\nRTSTRUCT).\nThe registration\nalgorithm module\nregisters volumetric\nmedical image data (e.g.,\nMR, CT). It allows rigid\nimage registration to\nadjust the spatial\nposition and orientation\nof two images.\nThe workflow\nmanagement module is\nconfigured to work on a\nPACS network. Upon","The product has two\nimage process functions:\n(1) Deep learning\ncontouring: it can\nautomatically contour\nthe organ-at-risk,\nincluding head and neck,\nthorax, abdomen and\npelvis (for both male and\nfemale),\n(2) Automatic\nRegistration, and\n(3) Manual Contour.\nIt also has the following\ngeneral functions:\nReceive, add/edit/delete,\ntransmit, input/export,\nmedical images and\nDICOM data;\nPatient management;\nReview of processed\nimages;\nOpen and Save of files.",""]],"caption_candidate":"VBrain-OAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p10-t0","doc_id":"K212116","page_num":10,"bbox":[72.84,81.12,539.76,693.26],"n_rows":23,"n_cols":4,"columns":["","Proposed Device","Primary Predicate",""],"rows":[["","Proposed Device","Primary Predicate",""],["","","","Reference Device"],["","","Device",""],["","","",""],["","user’s request, it will\npull patient scans or\nusers can send\ncorresponding DICOM\nimages, and it will\ntrigger a predefined\nworkflow, in which\ndifferent algorithm\nmodules are executed to\ngenerate the DICOM\noutput. The DICOM\noutput of a workflow are\nsent back to the PACS.","",""],["Segmentation","Deep learning","Deep learning","Atlas-based"],["(Contouring)","","",""],["Technology","","",""],["Operating System","Linux operating system","Microsoft Windows","Microsoft Windows"],["","Trained radiotherapy\npersonnel including, but\nnot limited to,\nradiologists, radiation\noncologists, physicians,\ndosimetrists, and\nmedical physicists.","It is used by radiation\noncology department.","Typical users of iPlan\nare medical\nprofessionals, including\nbut not limited to\nsurgeons and\nradiologists."],["User Population","","",""],["","","",""],["","Segmentation Features\nfor organs at risk in the\nbrain: axial T1 contrast-\nenhanced MR images.\nRegistration Features:\nCT, MR","Segmentation Features:\nNon-Contrast CT\nRegistration Features:\nCT, MRI, PET","CT, MRI, PET and\nSPECT"],["Supported Modalities","","",""],["","","",""],["","Organs at risk in the\nbrain","Organ-at-risk, including\nhead and neck, thorax,\nabdomen and pelvis (for\nboth male and female)","Outline anatomical\nstructures using manual\nor automatic\nsegmentation methods.\nAdvanced manipulation\nfor 3D objects with\nscaling, logical\noperations and object\nsplitting."],["Image segmentation:","","",""],["Localization and","","",""],["Definition of Objects","","",""],["(ROI)","","",""],["","","",""],["Image Registration","Intensity-based","Intensity-based","Intensity-based"],["Algorithm","","",""]],"caption_candidate":"VBrain-OAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212116-p11-t0","doc_id":"K212116","page_num":11,"bbox":[72.74,81.12,539.58,142.74],"n_rows":6,"n_cols":4,"columns":["","Proposed Device","Primary Predicate","Reference Device"],"rows":[["","Proposed Device","Primary Predicate","Reference Device"],["","","",""],["","","Device",""],["","","",""],["Alteration of Original","No","No","No"],["Images","","",""]],"caption_candidate":"VBrain-OAR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212218-p5-t0","doc_id":"K212218","page_num":5,"bbox":[115.8,465.12,534.36,683.28],"n_rows":8,"n_cols":3,"columns":["Technological Characteristic","AATMA™\n(Subject Device","Workflow Box\nPredicate Device\nK181572"],"rows":[["Technological Characteristic","AATMA™\n(Subject Device","Workflow Box\nPredicate Device\nK181572"],["Automatic contouring of imaging data using\nmachine learning based models","",""],["No Graphical User Interface","",""],["View manipulation and Volume rendering – Not\nApplicable","",""],["Image registration","N/A",""],["Reporting and Data Routing","N/A",""],["Supported modalities: Standard DICOM image\nmodality support","\nSubject device\nvalidated with CT\nimages for image\nprocessing.","\nPredicate device\nvalidated with CT,\nMR, DICOM\nRTSTRUCT for\nimage processing."],["TCP/IP Networking and Communication","",""]],"caption_candidate":"PREDICATE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212261-p8-t0","doc_id":"K212261","page_num":8,"bbox":[72.0,87.12,535.56,713.64],"n_rows":7,"n_cols":3,"columns":["Manufacturer","Circle Neurovascular Imaging","Viz.AI"],"rows":[["Manufacturer","Circle Neurovascular Imaging","Viz.AI"],["510(k) number","(cid:46)(cid:21)(cid:20)(cid:21)(cid:21)(cid:25)(cid:20)","DEN170073"],["Device Class","II","II"],["Device classification","QAS","QAS"],["Regulation Name","Radiological Computer-Assisted\nTriage And Notification Software","Radiological Computer-Assisted Triage\nAnd Notification Software"],["Regulation number","21 CFR 892.2080","21 CFR 892.2080"],["Indications for Use /\nIntended Use","StrokeSENS LVO is a\nradiological computer-aided\ntriage and notification (CADt)\nsoftware indicated for use in the\nanalysis of CTA head images.\nThe device is intended to assist\nhospital networks and trained\nclinicians in workflow triage by\nflagging and communication of\nsuspected positive findings of\nLarge Vessel Occlusion (LVO) in\nhead CTA images.\nStrokeSENS LVO uses a\nsoftware algorithm to identify\nsuspected LVO findings. In the\ncase of a suspected LVO, the\nsystem will send a notification to\na pre-configured destination(s),\nnotifying the clinicians of the\nexistence of a suspected LVO\nthat requires review. The\nnotification system is intended to\nbe used in parallel to the standard\nof care workflow to notify\nclinicians of the existence of the\ncase earlier that they may have\nbeen notified as part of the\nstandard of care workflow.\nNotifications may include a\ncompressed preview of images.\nNotifications are meant for\ninformational purposes only and\nare not intended for diagnostic\nuse beyond notification. The\nStrokeSENS LVO device does\nnot alter the original medical","ContaCT is a notification-only, parallel\nworkflow tool for use by hospital networks\nand trained clinicians to identify and\ncommunicate images of specific patients\nto a specialist, independent of standard of\ncare workflow.\nContaCT uses an artificial intelligence\nalgorithm to analyze images for findings\nsuggestive of a pre-specified clinical\ncondition and to notify an appropriate\nmedical specialist of these findings in\nparallel to standard of care image\ninterpretation. Identification of suspected\nfindings is not for diagnostic use beyond\nnotification. Specifically, the device\nanalyzes CT angiogram images of the\nbrain acquired in the acute setting, and\nsends notifications to a neurovascular\nspecialist that a suspected large vessel\nocclusion has been identified and\nrecommends review of those images.\nImages can be previewed through a\nmobile application. Images that are\npreviewed through the mobile application\nare compressed and are for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nNotified clinicians are responsible for\nviewing non-compressed images on a\ndiagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making care-related\ndecisions or requests. ContaCT is limited\nto analysis of imaging data and should not\nbe used in-lieu of full patient evaluation or\nrelied upon to make or confirm diagnosis."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212261-p9-t0","doc_id":"K212261","page_num":9,"bbox":[72.02,87.12,535.53,709.2],"n_rows":14,"n_cols":5,"columns":["","","image and is not intended to be\nused as a diagnostic device.\nThe results of StrokeSENS LVO\nare intended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgement, to assist\nwith triage / prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per standard\nof care.","",""],"rows":[["","","image and is not intended to be\nused as a diagnostic device.\nThe results of StrokeSENS LVO\nare intended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgement, to assist\nwith triage / prioritization of\nmedical images. Notified\nclinicians are responsible for\nviewing full images per standard\nof care.","",""],["","","","",""],["","Clinical Characteristics","","",""],["","","","",""],["User Population","","Hospital Networks and trained\nclinicians","Same",""],["Clinical\napplication/Anatomical\nRegion","","Acute Stroke / Head","Same",""],["Relationship to\nstandard of care\nworkflow","","In Parallel / Concurrently","Same",""],["","","","",""],["","Technological Characteristics","","",""],["","","","",""],["Input data type","","CTA data in DICOM format\n(vendor independent)","CTAdata in DICOM format (vendor\nindependent)",""],["Algorithm\nImplementation","","Artificial Intelligence / Machine\nLearning\nAlgorithms are static and locked.\nAlgorithms are not dynamic or\nlearning while in the market.","Same",""],["Alteration of original\nimage database","","No","Same",""],["Notification / Workflow","","Email, Workstation, Mobile\nNotification message of\nSuspected LVO","Mobile\nNotification message of Suspected LVO",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212261-p11-t0","doc_id":"K212261","page_num":11,"bbox":[72.48,87.36,485.04,175.44],"n_rows":2,"n_cols":3,"columns":["Specificity","Specificity > 80 %","87.4%, (95% CI = 82.6, 92.2)"],"rows":[["Specificity","Specificity > 80 %","87.4%, (95% CI = 82.6, 92.2)"],["Processing Time","<5 minutes","Mean: 0.75 mins\nS.D: ±0.17 mins\nMin: 0.46 mins\nMax: 1.23 mins"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212265-p5-t0","doc_id":"K212265","page_num":5,"bbox":[67.67,67.38,566.35,221.19],"n_rows":6,"n_cols":6,"columns":["Device","Manufacturer","Model","Device\nClass","Product\nCode","510K\nNumber"],"rows":[["Device","Manufacturer","Model","Device\nClass","Product\nCode","510K\nNumber"],["1. Primary\npredicatedevice","Mindray","TE7","II","IYN,IYO,ITX","K203391"],["2.Referencedevice","Mindray","ResonaI9","II","IYN,IYO,ITX，","K210699"],["3.Referencedevice","Mindray","MX7","II","IYN,IYO,ITX","K200001"],["4.Referencedevice","Mindray","M9","II","IYN,IYO,ITX","K210416"],["5.Referencedevice","Mindray","Resona7","II","IYN,IYO,ITX","K202785"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212265-p7-t0","doc_id":"K212265","page_num":7,"bbox":[149.8,425.74,553.4,727.89],"n_rows":7,"n_cols":2,"columns":["Printerbracket","It is usedfor holdingthe printer"],"rows":[["Printerbracket","It is usedfor holdingthe printer"],["Rearstorage bin","It is usedfor keeping thecases, towelette, etc."],["AirCharge\nModule","Configured withthe airstation tocharge themain unit."],["AirProbeCharing\nHolder","It is usedto chargewireless probe."],["Airstation","Cover wired power into wireless to provide power for Air\nCharge Module"],["iVocal Plus\nMicrophone Array","The iVocal Plus is an improvement of iVocal (cleared in\nK210699), which both enables the system to perform\noperations through vocal commands and through tapping\nicons on the touch screen. The iVocal Plus Microphone\narray is a hardware used with iVocal Plus, it consists of\nmicrophone arrays (including wireless transceivers) and\nUSB cables."],["X-Link","The Ultrasound System supportsinterconnecting\ninformation withthebedside device through X-Link. The"]],"caption_candidate":"and hardware optionshave been met.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212265-p8-t0","doc_id":"K212265","page_num":8,"bbox":[149.8,69.24,553.4,287.39],"n_rows":3,"n_cols":2,"columns":["","interconnection function of X-Link mainly includes:\nObtaining data:Thedata ofthesame patient are matched\nthrough network connection;\nUsing data:Real-timedata are obtained and displayed in\ncombination with ultrasound image data;\nStoring andreviewing data:The dataare stored in\ncombination with theultrasound image dataand canbe\nreviewed ontheultrasound device."],"rows":[["","interconnection function of X-Link mainly includes:\nObtaining data:Thedata ofthesame patient are matched\nthrough network connection;\nUsing data:Real-timedata are obtained and displayed in\ncombination with ultrasound image data;\nStoring andreviewing data:The dataare stored in\ncombination with theultrasound image dataand canbe\nreviewed ontheultrasound device."],["ClamAV","It is an antivirus software"],["Smart Nerve","It is an AI(artificial intelligence) based feature.\nIt is usedto recognizetheinterscalene and supraclavicular\nbrachial plexus.It isintended for visualization purpose only\nand not intended forliveguidance during interventional\nprocedure."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212269-p5-t0","doc_id":"K212269","page_num":5,"bbox":[125.42,204.5,552.05,498.1],"n_rows":8,"n_cols":7,"columns":["","","Proposed Device","","","Predicate Device",""],"rows":[["","","Proposed Device","","","Predicate Device",""],["Trade Name","Intelligent NR","","","Enhanced Feature Software Pack for CXDI Series","",""],["510(k)\nSubmitter\n[Number]","Canon Inc.\n[TBD]","","","Canon Inc.\n[K190368]","",""],["Indication for\nUse","As a part of the Canon radiography system, the CXDI\nControl Software when used with a compatible Canon\ndetector is intended to provide digital image capture,\nprocessing, and display for conventional film/screen\nradiographic examinations. This device is intended to\nreplace radiographic film/screen systems in all general\npurpose diagnostic procedures including specialist\nareas like intensive care, trauma, and pediatric work.\nThis device is not intended for fluoroscopic,\nangiographic, or mammography applications.","","","As a part of the CXDI series radiography system, the\nCXDI Control Software when used with a compatible\nCXDI detector is intended to provide digital image\ncapture, processing, and display for conventional\nfilm/screen radiographic examinations. This device is\nintended to replace radiographic film/screen systems\nin all general purpose diagnostic procedures including\nspecialist areas like intensive care, trauma, and\npediatric work. This device is not intended for\nfluoroscopic, angiographic, or mammography\napplications.","",""],["Software /\nVersion","CXDI Control Software V3.10","","","CXDI Control Software V2.17","",""],["Scatter\nCorrection","An image can be created (with high contrasts) by\nusing software algorithm, in clinical field, without a\ngrid","","","An image can be created (with high contrasts) by\nusing software algorithm, in clinical field, without a\ngrid","",""],["One Shot\nLong Length\nImaging","One exposure to obtain images across multiple\ndetectors, automatically stitched together with ability\nto make manual adjustments after the automatic\nstitching.","","","One exposure to obtain images across multiple\ndetectors, automatically stitched together with ability\nto make manual adjustments after the automatic\nstitching.","",""],["Intelligent NR\nFunction","Process to reduce noise from the taken images by\nusing function machine trained on characteristics of\nnoises included in X-ray image signals using an\nexisting clinical image database","","","N/A","",""]],"caption_candidate":"Characteristics:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212274-p7-t0","doc_id":"K212274","page_num":7,"bbox":[72.28,310.1,539.98,693.73],"n_rows":8,"n_cols":3,"columns":["Topic","Predicate Device","Subject Device"],"rows":[["Topic","Predicate Device","Subject Device"],["Physical\nCharacteristics","Software package that operates on\noff-the-shelf hardware","Software package that operates on a\nvirtual machine within the off-the-shelf\nhardware"],["Computer","PC Compatible","Same"],["Operating\nSystem","Windows","Ubuntu (18.04 & 20.04)"],["DICOM Standard\nCompliance","The software processes DICOM\ncompliant image data, including\nRTSTRUCT","Same"],["Modalities","CT & MRI","Same"],["User Interface","The software is designed for use on a\nradiotherapy workstation with a native\nuser interface.","The software is designed for use on a\nradiotherapy workstation with a web-\nbased user interface"],["Segmentation\nStructures","Organs at risk and target volumes","Same"]],"caption_candidate":"Table 1. Summary of Technological Characteristic Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212274-p8-t0","doc_id":"K212274","page_num":8,"bbox":[72.27,72.28,539.98,359.12],"n_rows":4,"n_cols":3,"columns":["Overall\nSegmentation\nMethod","Model-based approach using a library\nof expert contours","Same"],"rows":[["Overall\nSegmentation\nMethod","Model-based approach using a library\nof expert contours","Same"],["Detailed\nImplementation\nof Segmentation\nAlgorithm","Smart Segmentation – knowledge-\nbased contouring used an atlas-based\nmethod to deform expert contours to\nthe target images to generate contours","INTContour used a machine learning-\nbased method to train CNNs from\nexpert contours to perform\nsegmentation on the target images to\ngenerate contours"],["Support of\nManual Editing","Yes","No"],["Provide Expert\nCase Library to\nUsers","Yes","No"]],"caption_candidate":"Innovative and Intelligent","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212274-p9-t0","doc_id":"K212274","page_num":9,"bbox":[72.5,359.2,540.64,713.76],"n_rows":11,"n_cols":5,"columns":["Head and Neck","","Thorax","Abdomen","Male Pelvis"],"rows":[["Head and Neck","","Thorax","Abdomen","Male Pelvis"],["Brainstem","Pituitary","SpinalCanal","Spleen","Bladder"],["OpticChiasm","InnerEar_L","Lung_R","Kidney_R","Femur_Head_L"],["Bone_Mandible","InnerEar_R","Lung_L","Kidney_L","Femur_Head_R"],["OpticNrv_L","Lens_L","Heart","Gallbladder","PenileBulb"],["OpticNrv_R","Lens_R","Esophagus","Esophagus","Prostate"],["Parotid_L","Lobe_Temporal_L","Trachea","Liver","SeminalVesicle"],["Parotid_R","Lobe_Temporal_R","BronchialTree","Stomach","Rectum"],["Glnd_Submand_L","Larynx","SpinalCord","A_Aorta",""],["Glnd_Submand_R","Cavity_Oral","","V_Venacava_I",""],["Eye_L","Pharynx","","PortalVein",""]],"caption_candidate":"The table below shows the list of all supported organs:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212274-p10-t0","doc_id":"K212274","page_num":10,"bbox":[72.53,72.34,540.64,265.87],"n_rows":6,"n_cols":5,"columns":["Eye_R","Brain","","Pancreas",""],"rows":[["Eye_R","Brain","","Pancreas",""],["MidEar_L","Cochlea_L","","AdrenalGland_R",""],["MidEar_R","Cochlea_R","","AdrenalGland_L",""],["Joint_TM_L","Glnd_Lacrimal_L","","SplenicVein",""],["Joint_TM_R","Glnd_Lacrimal_R","","",""],["BrachialPlex_L","BrachialPlex_R","","",""]],"caption_candidate":"Innovative and Intelligent","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212333-p5-t0","doc_id":"K212333","page_num":5,"bbox":[106.14,112.5,544.38,167.28],"n_rows":2,"n_cols":4,"columns":["Product","Marketed by","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","510(k) Number","Clearance Date"],["Aplio i900/i800/i700 Diagnostic\nUltrasound System, Software\nV5.1","Canon Medical\nSystems USA","K201972","October 08, 2020"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K212365-p4-t0","doc_id":"K212365","page_num":4,"bbox":[72.5,177.26,539.74,367.3],"n_rows":3,"n_cols":2,"columns":["Submitter","GLEAMER SAS\n5, avenue du Général de Gaulle\n94160 Saint-Mandé - FRANCE"],"rows":[["Submitter","GLEAMER SAS\n5, avenue du Général de Gaulle\n94160 Saint-Mandé - FRANCE"],["Primary Contact\nPerson","Antoine Tournier\nHead of Quality & Regulatory Affairs\nTel: 0033 6 15 81 23 45\nEmail: antoine.tournier@gleamer.ai"],["Secondary Contact\nPerson","Christian Allouche\nCEO\nTel: 0033 6 58 53 70 46\nEmail: christian@gleamer.ai"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p4-t1","doc_id":"K212365","page_num":4,"bbox":[72.5,415.39,539.74,537.27],"n_rows":6,"n_cols":4,"columns":["","Trade Name","","BoneView"],"rows":[["","Trade Name","","BoneView"],["","510(k) reference","","K212365"],["Common Name","Common Name","","Radiological computer assisted detection/diagnosis software for\nfracture"],["","Regulation","","21 CFR 892.2090"],["","Product Code","","QBS"],["","Classification","","Class II"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p4-t2","doc_id":"K212365","page_num":4,"bbox":[72.5,585.46,539.74,620.94],"n_rows":2,"n_cols":4,"columns":["","Predicate Device","","Imagen Technologies, Inc - FractureDetect"],"rows":[["","Predicate Device","","Imagen Technologies, Inc - FractureDetect"],["","510(k) reference","","K193417"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p5-t0","doc_id":"K212365","page_num":5,"bbox":[70.58,146.66,541.53,701.86],"n_rows":32,"n_cols":2,"columns":["BoneView can be deployed on-premises or on cloud and be connected to several computing",""],"rows":[["BoneView can be deployed on-premises or on cloud and be connected to several computing",""],["platforms and X-ray imaging platforms such as X-ray radiographic systems, or PACS. More",""],["precisely, BoneView can be deployed:",""],["","● In the cloud with a PACS as the DICOM Source"],["","● On-premises with a PACS as the DICOM Source"],["","● On-premises with an X-ray system as the DICOM Source"],["",""],["It is important to note that no matter the deployment mode that is chosen for BoneView, the",""],["overall principle of use of BoneView and its user interface remain the same; only the place",""],["where BoneView is housed, and the DICOM Source/DICOM Destination with which BoneView",""],["communicates, may vary. Below is a description of the data flow.",""],["",""],["After the acquisition of the radiographs on the patient and their storage in the DICOM Source,",""],["the radiographs are automatically received by BoneView from the user’s DICOM Source",""],["through an intermediate DICOM node (for example, a specific Gateway, or a dedicated API). The",""],["DICOM Source can be the user’s image storage system (for example, the Picture Archiving and",""],["Communication System, or PACS), or other radiological equipment (for example X-ray",""],["systems).",""],["",""],["Once received by BoneView, the radiographs are automatically processed by the AI algorithm",""],["to identify regions of interest. Based on the processing result, BoneView generates result files",""],["in DICOM format. These result files consist of a summary table and result images (annotations",""],["on a copy of the original images or annotations to be toggled on/off). BoneView does not alter",""],["the original images, nor does it change the order of original images or delete any image from",""],["the DICOM Source.",""],["",""],["Once available, the result files are sent by BoneView to the DICOM Destination through the",""],["same intermediate DICOM node. Similar to the DICOM Source, the DICOM Destination can be",""],["the user’s image storage system (for example, the Picture Archiving and Communication",""],["System, or PACS), or other radiological equipment (for example X-ray systems). The DICOM",""],["Source and the DICOM Destination are not necessarily identical.",""],["",""]],"caption_candidate":"and highlight fractures during the review of radiographs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p11-t0","doc_id":"K212365","page_num":11,"bbox":[73.92,379.61,538.62,473.79],"n_rows":6,"n_cols":5,"columns":["","High-sensitivity operating point","","High-specificity operating point",""],"rows":[["","High-sensitivity operating point","","High-specificity operating point",""],["Standalone","Specificity – 95%\nClopper-Pearson CI","Sensitivity – 95%","Specificity – 95%","Sensitivity – 95%"],["Performance","","Clopper-Pearson CI","Clopper-Pearson CI","Clopper-Pearson CI"],["Global","0.811 [0.8 - 0.821]","0.928 [0.919 - 0.936]","0.932 [0.925 - 0.939]","0.841 [0.829 - 0.853]"],["n(positive)= 3,886","","","",""],["n(negative)= 5,032","","","",""]],"caption_candidate":"merged datasets","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p11-t1","doc_id":"K212365","page_num":11,"bbox":[73.92,530.58,538.62,700.62],"n_rows":4,"n_cols":5,"columns":["","High-sensitivity operating point\nDOUBT FRACT","","High-specificity operating point\nFRACT",""],"rows":[["","High-sensitivity operating point\nDOUBT FRACT","","High-specificity operating point\nFRACT",""],["Anatomical\nAreas of\nInterest","Specificity – 95%\nClopper-Pearson\nCI","Sensitivity –\n95% Clopper-\nPearson CI","Specificity – 95%\nClopper-Pearson\nCI","Sensitivity –\n95% Clopper-\nPearson CI"],["Ankle\nn(positive)= 378\nn(negative)= 805","0.784 [0.754 -\n0.812]","0.95 [0.923 - 0.969]","0.897 [0.874 -\n0.917]","0.899 [0.865 -\n0.928]"],["Clavicle\nn(positive)= 147\nn(negative)= 255","0.757 [0.699 -\n0.808]","0.905 [0.845 -\n0.947]","0.929 [0.891 -\n0.958]","0.83 [0.759 - 0.887]"]],"caption_candidate":"operating point and high-specificity operating point on the merged datasets","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212365-p12-t0","doc_id":"K212365","page_num":12,"bbox":[77.66,107.18,523.04,774.93],"n_rows":88,"n_cols":10,"columns":["Anatomical Specif","icity –","95%","Sen","sitivity","–","Specificity – 95%","Sensi","tivity","–"],"rows":[["Anatomical Specif","icity –","95%","Sen","sitivity","–","Specificity – 95%","Sensi","tivity","–"],["","","","","","","","","",""],["Areas of Clopp","er-Pea","rson","95%","Clopp","er-","Clopper-Pearson 9","5% C","loppe","r"],["","","","","","","","","",""],["Interest","CI","","Pe","arson C","I","CI","Pear","son C","I"],["","","","","","","","","",""],["Elbow","","","","","","","","",""],["","","","","","","","","",""],["0.71","8 [0.65","5 -","0.9","24 [0.86","8 -","0.899 [0.852 -","0.531","[0.446","-"],["","","","","","","","","",""],["n(positive)= 145","0.776]","","","0.962]","","0.935]","0.","614]",""],["n(negative)= 227","","","","","","","","",""],["","","","","","","","","",""],["Femur","","","","","","","","",""],["","","","","","","","","",""],["0.73","3 [0.65","8 -","0.9","37 [0.84","5 -","0.944 [0.897 -","0.825","[0.709","-"],["","","","","","","","","",""],["n(positive)= 63","0.799]","","","0.982]","","0.974]","0.","909]",""],["n(negative)= 161","","","","","","","","",""],["","","","","","","","","",""],["Foot","","","","","","","","",""],["","","","","","","","","",""],["0.79","3 [0.76","8 -","0.9","34 [0.91","7 -","0.924 [0.907 -","0.874","[0.852","-"],["","","","","","","","","",""],["n(positive)= 985","0.817]","","","0.949]","","0.939]","0.","894]",""],["n(negative)= 1,097","","","","","","","","",""],["","","","","","","","","",""],["Forearm","","","","","","","","",""],["0.67","6 [0.57","7 -","","","","0.912 [0.839 -","0.851","[0.763","-"],["","","","0.989","[0.942 -","1.0]","","","",""],["n(positive)= 94","0.766]","","","","","0.959]","0.","916]",""],["n(negative)= 102","","","","","","","","",""],["","","","","","","","","",""],["Hand","","","","","","","","",""],["","","","","","","","","",""],["0.80","9 [0.78","3 -","0.9","66 [0.95","4 -","0.917 [0.898 -","0.915","[0.898","-"],["","","","","","","","","",""],["n(positive)= 1,168","0.832]","","","0.975]","","0.934]","0.","931]",""],["n(negative)= 1,003","","","","","","","","",""],["","","","","","","","","",""],["Hip","","","","","","","","",""],["","","","0.9","38 [0.88","5 -","0.953 [0.918 -","0.793","[0.718","-"],["n(positive)= 145 0.77 [0",".711 - 0",".822]","","0.971]","","0.976]","0.","856]",""],["n(negative)= 235","","","","","","","","",""],["","","","","","","","","",""],["Humerus","","","","","","","","",""],["0.73","1 [0.65","9 -","0.9","04 [0.83","4 -","","0.833","[0.752","-"],["n(positive)= 114","0.796]","","","0.951]","","0.92 [0.869 - 0.956]","0.","897]",""],["n(negative)= 175","","","","","","","","",""],["","","","","","","","","",""],["Knee","","","","","","","","",""],["","","","","","","","","",""],["0.88","9 [0.86","8 -","0.8","91 [0.82","3 -","0.975 [0.964 -","0.797","[0.717","-"],["","","","","","","","","",""],["n(positive)= 128","0.907]","","","0.939]","","0.984]","0.","863]",""],["n(negative)= 1,045","","","","","","","","",""],["","","","","","","","","",""],["Lumbosacral","","","","","","","","",""],["","","","","","","","","",""],["Spine 0.73","7 [0.67","2 -","0.7","76 [0.69","3 -","0.947 [0.908 -","","",""],["","","","","","","0.","6 [0.50","9 - 0.6","8"],["n(positive)= 125","0.795]","","","0.846]","","0.973]","","",""],["","","","","","","","","",""],["n(negative)= 209","","","","","","","","",""],["","","","","","","","","",""],["Pelvis","","","","","","","","",""],["","","","","","","","","",""],["0.74","5 [0.70","4 -","0.8","87 [0.83","9 -","0.939 [0.914 -","0.743","[0.682","-"],["","","","","","","","","",""],["n(positive)= 230","0.784]","","","0.925]","","0.959]","0.","799]",""],["n(negative)= 479","","","","","","","","",""],["","","","","","","","","",""],["Ribs","","","","","","","","",""],["0.68","4 [0.58","1 -","","","","","0.488","[0.425","-"],["n(positive)= 252","0.776]","","0.753","[0.7 - 0.","802]","0.926 [0.854 - 0.97]","0.","552]",""],["n(negative)= 95","","","","","","","","",""],["","","","","","","","","",""],["Shoulder","","","","","","","","",""],["","","","","","","","","",""],["0.78","2 [0.74","6 -","0.9","29 [0.89","1 -","0.947 [0.926 -","0.851","[0.801","-"],["","","","","","","","","",""],["n(positive)= 255","0.814]","","","0.958]","","0.964]","0.","892]",""],["n(negative)= 586","","","","","","","","",""],["","","","","","","","","",""],["","","","G","LEAMER","","","","",""],["5","avenue","du Généra","l de Ga","ulle, 941","60 Saint-","Mandé - FRANCE","","",""],["","SAS au","capital de","115 37","2 euros –","RCS Crét","eil 834 105 470","","",""],["","SIR","ET : 834 1","05 470","00027 – a","dmin@g","leamer.ai","","",""]],"caption_candidate":"Anatomical Specificity – 95% Sensitivity – Specificity – 95% Sensitivity –","well_formed":true,"extraction_settings":"text"}
{"table_id":"K212365-p13-t0","doc_id":"K212365","page_num":13,"bbox":[72.34,72.71,539.82,286.43],"n_rows":14,"n_cols":15,"columns":["","","","","High-sensitivity operating point","","","","","","High-specificity operating point","","","",""],"rows":[["","","","","High-sensitivity operating point","","","","","","High-specificity operating point","","","",""],["","","","","DOUBT FRACT","","","","","","FRACT","","","",""],["","Anatomical","","","Specificity – 95%","","","Sensitivity –","","","Specificity – 95%","","","Sensitivity –",""],["","Areas of","","","Clopper-Pearson","","","95% Clopper-","","","Clopper-Pearson","","","95% Clopper-",""],["","Interest","","","CI","","","Pearson CI","","","CI","","","Pearson CI",""],["","Thoracic Spine","","0.676 [0.578 -\n0.764]","","","0.878 [0.782 -\n0.943]","","","0.905 [0.832 -\n0.953]","","","0.689 [0.571 -\n0.792]","",""],["","n(positive)= 74","","","","","","","","","","","","",""],["","n(negative)= 105","","","","","","","","","","","","",""],["","Tibia/Fibula","","0.712 [0.641 -\n0.776]","","","0.972 [0.903 -\n0.997]","","","0.815 [0.751 -\n0.869]","","","0.931 [0.845 -\n0.977]","",""],["","n(positive)= 72","","","","","","","","","","","","",""],["","n(negative)= 184","","","","","","","","","","","","",""],["","Wrist","","0.771 [0.732 -\n0.807]","","","0.97 [0.953 - 0.983]","","","0.892 [0.862 -\n0.918]","","","0.934 [0.91 - 0.953]","",""],["","n(positive)= 573","","","","","","","","","","","","",""],["","n(negative)= 502","","","","","","","","","","","","",""]],"caption_candidate":"Page 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p6-t0","doc_id":"K212383","page_num":6,"bbox":[39.26,153.66,542.74,731.52],"n_rows":8,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["Medical Device Software\nTrade Name","EndoNaut","","","EndoNaut","","","Identical","",""],["Accessory 1","Separate interventional tools\nworkstation","","","EndoNaut Workstation","","","Different.\nDesignation adjustment\nonly.\nWe have reclarified the qual-\nification of hardware versus\nsoftware. By definition,\nhere, the hardware (Endo-\nNaut Workstation) is an ac-\ncessory to the software med-\nical device. To better differ-\nentiate what is applicable to\none and the other, we have\nidentified the software by\n“EndoNaut Software” and\nthe hardware by “EndoNaut\nWorkstation”. The Endo-\nNaut Workstation alone is\nnot subject to any regulatory\nsubmission. It is integrated\nwith the System submitted\nfor FDA approval under the\nname, EndoNaut.","",""],["Accessory 1 Ref.","TS1CA2DS1-1","","","TS1CA2DS1-2","","","Different\nChange of the Panel PC, the\nControl Panel model and Ca-\nblings.\nDue to these changes, the\nProduct number\n“TS1CA2DS1-2” has been\nchanged. New testings have\nbeen performed.","",""],["Accessory 2","EndoSize Software\n(K160376)","","","EndoSize Software\n(K160376)","","","Identical\nEndoSize Software is an ac-\ncessory that is intended to\nsupplement the performance\nof EndoNaut.","",""],["Identification and traceabil-\nity","Name: EndoNaut\nNo UDI","","","Trade name: EndoNaut\nCommon name: EndoNaut\nSystem\nUDI-DI: 3760262480046","","","Different\nNo risk related to idenfica-\ntion between older and\nnewer EndoNaut device.\nEndoNaut is now referring to\nthe EndoNaut System while\nthe EndoNaut Software is\nnamed EndoNaut Software.","",""]],"caption_candidate":"sion","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p7-t0","doc_id":"K212383","page_num":7,"bbox":[39.25,127.86,542.75,728.4],"n_rows":12,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["","","","","","","","No unit of the predicate de-\nvice was sold in the USA.","",""],["Manufacturer","Therenva SAS","","","Therenva SAS","","","Identical","",""],["Product Code","OWB","","","OWB","","","Identical","",""],["Regulation Number","892.1650","","","892.1650","","","Identical","",""],["Regulation Name","Interventional Fluoroscopic\nX-Ray System","","","Interventional Fluoroscopic\nX-Ray System","","","Identical","",""],["Software Safety class (62304)","B","","","B","","","Identical","",""],["Level of concern","Moderate","","","Moderate","","","Identical","",""],["Intended use","Intended use and indications\nfor use were mixed.\nSee below Indications for\nuse.","","","EndoNaut provides image\nguidance by overlaying pre-\noperative 3D vessel anatomy\nonto live fluoroscopic im-\nages in order to assist in the\npositioning of the guide-\nwires, catheters and other\nendovascular devices.","","","Different\nA distinction between \"In-\ntended use\" and \"indications\nfor use\" has been made based\non the recommendations of\nthe FDA Guidance \" The\n510(k) Program: Evaluating\nSubstantial Equivalence in\nPremarket Notifications\n[510(k)]” (section IV, D, 1).","",""],["Indications for use","EndoNaut provides image\nguidance by overlaying pre-\noperative 3D vessel anatomy\nonto live fluoroscopic im-\nages in order to assist in the\npositioning of the guide-\nwires, catheters and other\nendovascular devices.\nEndoNaut is intended to as-\nsist endovascular procedures\nin the thorax, abdomen,\nneck, pelvis and lower limbs.\nSuitable procedures include\n(but not limited to) endovas-\ncular aortic aneurysm repair\n(AAA and TAA), angio-\nplasty, stenting and emboli-\nzation in iliac arteries and\ncorresponding veins.\nEndoNaut is not intended for\nuse in the X-ray guided pro-\ncedures in the liver, kidneys\nor pelvic organs.","","","EndoNaut is indicated for\nthe treatment of patients with\nendovascular diseases and\nwho needs for example\n(without this list being re-\nstrictive):\n• endovascular aortic an-\neurysm repair (AAA\nand TAA),\n• angioplasty,\n• stenting,\n• embolization in iliac ar-\nteries and corresponding\nveins.\nEndoNaut is indicated for\nendovascular procedures in\nthe thorax, abdomen, pelvis\nand lower limbs.","","","Different\nA distinction between \"In-\ntended use\" and \"indications\nfor use\" has been made based\non the recommendations of\nthe FDA Guidance \" The\n510(k) Program: Evaluating\nSubstantial Equivalence in\nPremarket Notifications\n[510(k)]” (section IV, D, 1).","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p8-t0","doc_id":"K212383","page_num":8,"bbox":[39.26,127.86,542.74,737.04],"n_rows":7,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["Labelling","1 label in the “about” section\nfor the Medical Device Soft-\nware with the Trade Name\n“EndoNaut”\n+\n1 label for the Separate inter-\nventional tools workstation\nwith the Trade Name “Endo-\nNaut” and Product Number\n= TS1CA2DS1-1 + unique\nSerial (production) Number","","","1 label in the “about” section\nfor the Medical Device Soft-\nware with the Trade Name\n“EndoNaut Software”.\n+\n1 label on the workstation\nwith the Trade Name “Endo-\nNaut” (for the whole Sys-\ntem) and Workstation model\nNumber = TS1CA2DS1-2 +\nunique Serial (production)\nNumber (for the whole Sys-\ntem)","","","Different\nEach component of the En-\ndoNaut System has its\nproper labelling.\nComplete review of Label-\nling design. Use of symbols\nof ISO 15223-1.\nAddition of UDI.\nIdentical\nThe system has a unique\nidentifier (S/N).","",""],["Directions for use (User\nGuide(s))","1 User guide for EndoNaut","","","1 User Guide for EndoNaut\nSoftware\n1 User Guide for EndoNaut\nWorkstation +\n1 addendum for informing\nabout the conditions govern-\ning the marketing of Endo-\nNaut.","","","Different\nThe directions for use have\nbeen enhanced to clearly dis-\ntinguish the instructions spe-\ncific to the medical device\nSoftware, “EndoNaut SW”\nfrom the instructions specific\nto the EndoNaut Work-\nstation, accessory to Endo-\nNaut SW.","",""],["Hardware compatibility","Software only product; runs\non a separate interventional\ntools (imaging) workstation.","","","EndoNaut Software is the\nclass II medical device Soft-\nware which runs on a sepa-\nrate interventional tools (im-\naging) workstation, the so-\nnamed EndoNaut Work-\nstation which is the acces-\nsory of the medical device\nsoftware.","","","Different\nEndoNaut (legacy device)\nwas intended to be sold with\nand installed on the separate\ninterventional tools work-\nstation (ref: TS1CA2DS1-1)\nor installed on any hardware\nmeeting the minimum re-\nquirements.\nThe conditions for installing\nthe software on the work-\nstation are identical.\nOnly the model number of\nthe workstation has changed\n(ref: TS1CA2DS1-2).","",""],["Software Operating System","Win Pro 7 SP1x64\nWin Pro 10 64bits","","","Win Pro 10 64bits","","","Different\nSupport for Windows 7\nended on January 14, 2020.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p9-t0","doc_id":"K212383","page_num":9,"bbox":[39.26,127.86,542.74,713.76],"n_rows":7,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["Software interoperability","EndoNaut software requires\nthe use of EndoSize software\n(K160376) to prepare patient\ndata and perform preopera-\ntive sizing.\nData imported from En-\ndoSize include 3D volume,\npreoperative images, sizing\nreport (comments and meas-\nurements), and snapshots\ntaken during sizing.","","","EndoNaut requires the use of\nEndoSize software\n(K160376) to prepare patient\ndata and perform preopera-\ntive sizing.\nData imported from En-\ndoSize include 3D volume,\npreoperative images, sizing\nreport (comments and meas-\nurements), and snapshots\ntaken during sizing.","","","Similar\nSome clarifications are\nmade.\nPreoperative data is a man-\ndatory input for the use of AI\nmodule, but it is not for the\nPAD module.\nPreoperative data include\npre-op CT images and sizing\nreport (in case of AI module\nuse).\nThe stent placement strategy\nand sizing are usually per-\nformed pre-operatively via\nthe use of software devices\nsuch as EndoSize.\nAlternatives to EndoSize ex-\nist: other sizing or visualiza-\ntion software. In such cases,\nthe data is then printed on\npaper and used in the operat-\ning room as is.","",""],["Data management","The user can import and\nmanage patient data within\nthe software. Patient data in-\nclude pre-op CT images and\nsizing report.","","","The user can import and\nmanage patient data within\nthe software. Patient data in-\nclude pre-op CT images and\nsizing report.","","","Similar\nEndoNaut Software now en-\nables import and export of\ndata with a PACS.","",""],["Visualization","Intra-operative fluoroscopy\nor angiography, pre-opera-\ntive CT scan image, pre-op-\nerative 3D scanner volume\nreconstruction (if any in case\nof PAD module).\nAI module only:\nBefore and during the inter-\nvention, the user can access\ninformation from pre-opera-\ntive sizing report such as pre-\nop CT images, measure-\nments, comments, snap-\nshots and strategy.","","","Intra-operative fluoroscopy\nor angiography, pre-opera-\ntive CT scan image, pre-op-\nerative 3D scanner volume\nreconstruction (if any in case\nof PAD module).\nAI module only:\nBefore and during the inter-\nvention, the user can access\ninformation from pre-opera-\ntive sizing report such as pre-\nop CT images, measure-\nments, comments, snap-\nshots and strategy.","","","Identical","",""],["Export","Take and export snapshots.\nExport panoramas in case of\nPAD module.","","","Take and export snapshots.\nExport panoramas in case of\nPAD module.","","","Identical","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p10-t0","doc_id":"K212383","page_num":10,"bbox":[39.27,127.86,542.73,746.76],"n_rows":6,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["3D-2D / 2D-2D Registration","AI module:\nDisplay 2D-3D fusion: 3D\nvolume pre-op overlay on\nper-op 2D fluoroscopy.\nSemi-automatic registration\n(automatic or manual initial-\nization, automatic computa-\ntion and manual validation).\nLower limbs module:\nPanorama creation: Acquisi-\ntion and save of fluoroscopy\nand angiography stage by\nstage keeping the same C-\nArm orientation.\nDisplay 2D-2D fusion: 2D\npre-op angiographic overlay\non per-op 2D fluoroscopy.\nSynchronization between\ncurrent per-op 2D fluoros-\ncopy and 2D fluoroscopy\nfrom recorded panorama.","","","AI module:\nDisplay 2D-3D fusion: 3D\nvolume pre-op overlay on\nper-op 2D fluoroscopy.\nSemi-automatic registration\n(automatic or manual initial-\nization, automatic computa-\ntion and manual validation).\nPAD (lower limbs) module:\nPanorama creation: Acquisi-\ntion and save of fluoroscopy\nand angiography stage by\nstage keeping the same C-\nArm orientation.\nDisplay 2D-2D fusion: 2D\npre-op angiographic overlay\non per-op 2D fluoroscopy.\nSynchronization between\ncurrent per-op 2D fluoros-\ncopy and 2D fluoroscopy\nfrom recorded panorama.","","","Identical","",""],["Dynamic update on C-arm /\ntable / patient motion","Automatic motion\ndetection; registration is\nupdated manually.","","","Automatic motion detection\nRegistration: auto-\nmatic/manual initialization\nand manual user validation.","","","Different\nImprovement of semi-auto-\nmatic registration (already\nexisting requirement). The\nchange does not significantly\naffect the use of the device.\nNo new risks or possible er-\nrors were detected or identi-\nfied. New clinical data were\nnot necessary. V&V activi-\nties were performed and suc-\ncessful. No additional ques-\ntions raised for safety and ef-\nfectiveness.","",""],["Tools","AI module:\nDraw markers on intra-oper-\native images, locate/track\npoints between per-op and\npre-op images, and take\nmeasurements on pre-op CT\nscan images and fusion\nview.\nLower limbs module:\nDraw lesions markers on\npanorama (stenosis and","","","AI module:\nDraw markers on intra-oper-\native images, locate/track\npoints between per-op and\npre-op images, and take\nmeasurements on pre-op CT\nscan images and fusion\nview.\nPAD (lower limbs) module:\nDraw lesions markers on\npanorama (stenosis and","","","Identical","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p11-t0","doc_id":"K212383","page_num":11,"bbox":[39.25,127.86,542.75,730.2],"n_rows":11,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["","thrombosis), calibrate the\nlength of previous marked\nlesions due to inserted mate-\nrial, draw markers, create a\ncontrol panorama.","","","thrombosis), calibrate the\nlength of previous marked\nlesions due to inserted mate-\nrial, draw markers, create a\ncontrol panorama.","","","","",""],["Patient contacting","No","","","No","","","Identical","",""],["Energy emitted or absorbed","No","","","No","","","Identical","",""],["Workstation main display &\ncomputer","Panel PC Baaske, model e-\nmedic Silence TP 4\nRated AC 100-240V, 2.3-\n0.8A 50-60Hz\nMonitor size: 24’’ LCD\nBrigthness: 250 cd/ m² typi-\ncal\nResolution: 1920 x 1080\nCooling Fanless (no mainte-\nnance)","","","Panel PC ACL OR-PC\n27LP\nRated AC 100-240V, 1.5-0.6\nA ~47 – 63 Hz\nMonitor size: 27’’ LCD\nBrightness: 300 cd/m2\nResolution: 1920 x 1080\nCooling Fanless (no mainte-\nnance)","","","Different\nNo new risks or possible er-\nrors were detected or identi-\nfied. V&V activities were\nperformed and successful.\nNo additional questions\nraised for safety and effec-\ntiveness.","",""],["Workstation secondary dis-\nplay (touch screen)","One Touch monitor ELO,\nmodel 1519LM,\nrated AC 100-240V 1.2-\n0.63A 60/50Hz\nMonitor size: 15.6’’ LCD\nResolution: 1366 x 768\nBrightness: 225 cd/m2\nTouch technology: PCAP","","","One Touch monitor ELO\nmodel 1502L,\nrated AC 100-240 V\nInput frequency: 50-60 Hz\nMonitor size: 15.6’’ LCD\nResolution: 1920 x 1080\nBrightness: 270 cd/m2\nTouch technology: PCAP","","","Similar\nNew monitor provides\nmore effective visual image\nresolution.\nNo new risks or possible er-\nrors were detected or identi-\nfied.","",""],["Workstation cart","One mobile frame holder\nITD, including one isolating\ntransformer, rated AC 115V\n/ 230V 50/60Hz 1240VA.","","","One mobile frame holder\nITD, including one isolating\ntransformer, rated AC 115V\n/ 230V 50/60Hz 1240VA.","","","Identical","",""],["Workstation dimensions","Height: 1742 mm\nWidth (footprint): 661 (640)\nmm\nDepth (footprint): 950 (660)\nmm\nWeight: 71 kg","","","Height: 1740 mm\nWidth (footprint): 661 (640)\nmm\nDepth (footprint): 950 (660)\nmm\nWeight: 70 kg","","","Similar\nMinor dimensional and\nweight changes do not result\nin additional risks.","",""],["Connectors","Digital video input: DVI-D\nor DVI-I*\nAnalog video input: BNC\nVideo output: DisplayPort\nNetwork:\n10/100/1000 Mbps\nEthernet (RJ45)\nUSB interface USB 3.0\n(x2)","","","Digital video input: DVI-D\nor DVI-I*\nVideo output: HDMI\nNetwork: 10/100/1000 Mbps\nEthernet (RJ45)\nUSB interface USB 3.0\n(x2)","","","Similar\nSimply a new more common\nvideo interface is now used.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p12-t0","doc_id":"K212383","page_num":12,"bbox":[39.25,127.86,542.75,705.48],"n_rows":10,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["Power supply","Input voltage:\n100 – 230 VAC / 50 – 60 Hz","","","Input voltage:\n100 – 230 VAC / 50 – 60 Hz","","","Identical","",""],["Workstation cablings","Connection Box\nFront cable RJ45\nDVI front cable\nBNC front cable\nUSB 3.0 front cable 1m\n(x2)\nPower supplies\nPower supply extension jack\n2.5mm 3m IEC extension\ncable 1m (red)\nIEC extension cable 0.5m\n(blue)\nExternal power sup-\nply ELO TOUCH\n1519LM\nExternal power sup-\nply Baaske\nVideo cabling: DVI 5m\nOther cables:\nDisplayPort DVI ca-\nble 1.5m\nUSB 3.0 A/B 1m\nUSB 2.0 2m","","","Connection Box\nFront cable RJ45\nDVI front cable\nUSB 3.0 front cable\n1m (x2)\nPower supplies\nPower supply extension IEC\nC7-C14\nPower supply extension jack\n2.5mm 3m\nIEC extension cable 1m\n(red)\nIEC extension cable 0.5m\n(blue)\nExternal power supply XP\nPOWER (for ELO TOUCH\n1502L)\nExternal power supply\nBICKER (for ACL ORPC-\n27LP) BET-1012M\nVideo cabling: DVI 5m\nOther cables:\nHDMI cable 1.5m\nHDMI/DP adapter\nUSB 3.0 A/B 1m\nUSB 2.0 2m\nEquipotential 1,5m","","","Different\nNo new risks or possible er-\nrors were detected or identi-\nfied. V&V activities were\nperformed and successful.\nNo additional questions\nraised for safety and effec-\ntiveness.","",""],["IEC 62304","Applied","","","Applied","","","Identical","",""],["IEC 62366","Applied","","","Applied","","","Identical","",""],["ISO 14971","Applied","","","Applied","","","Identical","",""],["DICOM Standard parts 1-20","Applied","","","Applied","","","Similar\nA newer DICOM Conform-\nance Statement has been\nwritten for EndoNaut Sys-\ntem Software and is pro-\nvided in Appendix 2.","",""],["Conformity to IEC 60601-1\nof the separate interventional\ntools workstation","Yes\nFor CENELEC countries","","","Yes\nFor CENELEC countries","","","Identical\nIEC 60601-1 is not a FDA\nrecognized standard version\nbut is applied and included in\nV&V protocol and results.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212383-p13-t0","doc_id":"K212383","page_num":13,"bbox":[39.27,127.86,542.73,371.28],"n_rows":6,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K171829","","","","","","Equivalence Discussion",""],["Conformity to ANSI AAMI\nES60601-1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012 and\nA2:2010/(R)2012 (Consoli-\ndated Text) of the separate\ninterventional tools work-\nstation","No","","","Yes","","","Different\nUS deviations to IEC 60601-\n1 are taken into account for\nthe new model of separate\ninterventional tools work-\nstation (TS1CA2DS1-2).","",""],["Conformity to IEC 60601-2\nof the separate interventional\ntools workstation","Yes","","","Yes","","","Identical\nIEC 60601-2 FDA recog-\nnized standard version is ap-\nplied and included in V&V\nprotocol and results.","",""],["Conformity to IEC 60601-1-\n6 of the separate interven-\ntional tools workstation","Yes","","","Yes","","","Identical\nIEC 60601-1-6 FDA recog-\nnized standard version is ap-\nplied and included in V&V\nprotocol and results.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p4-t0","doc_id":"K212441","page_num":4,"bbox":[90.24,164.24,515.32,710.76],"n_rows":25,"n_cols":3,"columns":["Date Prepared:","July 30, 2021",""],"rows":[["Date Prepared:","July 30, 2021",""],["Manufacturer:","Philips Healthcare (Suzhou) Co., Ltd.\nNo. 258, Zhongyuan Road, Suzhou Industrial Park,\nSuzhou Jiangsu, CHINA, 215024\nEstablishment Registration Number: 3009529630",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","Shiguang An\nRegulatory Affaires Engineer\nPhone: +86-24-28206367\nE-mail: shiguang.an@philips.com\nErhong Wang\nSenior Manager Regulatory Affairs\nPhone: +86-512-67336804\nE-mail: ErHong.WANG@philips.com",""],["Device Name:","Philips Incisive CT",""],["Classification:","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Regulation:","21CFR 892.1750"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary Product Code:","JAK"],["Primary Predicate\nDevice:","Trade name:","Philips Ingenuity CT"],["","Manufacturer:","Philips Medical Systems\n(Cleveland), Inc."],["","510(k) Clearance:","K160743"],["","Classification Regulation:","21CFR 892.1750"],["","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","JAK"],["Secondary Predicate\nDevice:","Trade name:","Philips Incisive CT"],["","Manufacturer:","Philips Healthcare (Suzhou)\nCo., Ltd."],["","510(k) Clearance:","K180015"],["","Classification Regulation:","21CFR 892.1750"],["","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","JAK"]],"caption_candidate":"[As required by 21 CFR 807.92(c)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p6-t0","doc_id":"K212441","page_num":6,"bbox":[90.24,91.08,515.32,661.3],"n_rows":2,"n_cols":2,"columns":["Indications for Use:","The Incisive CT is a Computed Tomography X-Ray System\nintended to produce images of the head and body by\ncomputer reconstruction of x-ray transmission data taken at\ndifferent angles and planes. These devices may include\nsignal analysis and display equipment, patient and\nequipment supports, components and accessories. The\nIncisive CT is indicated for head, whole body, cardiac and\nvascular X-ray Computed Tomography applications in\npatients of all ages.\nThese scanners are intended to be used for diagnostic\nimaging and for low dose CT lung cancer screening for the\nearly detection of lung nodules that may represent cancer*.\nThe screening must be performed within the established\ninclusion criteria of programs / protocols that have been\napproved and published by either a governmental body or\nprofessional medical society.\n*Please refer to clinical literature, including the results of the\nNational Lung Screening Trial (N Engl J Med 2011;\n365:395-409) and subsequent literature, for further\ninformation."],"rows":[["Indications for Use:","The Incisive CT is a Computed Tomography X-Ray System\nintended to produce images of the head and body by\ncomputer reconstruction of x-ray transmission data taken at\ndifferent angles and planes. These devices may include\nsignal analysis and display equipment, patient and\nequipment supports, components and accessories. The\nIncisive CT is indicated for head, whole body, cardiac and\nvascular X-ray Computed Tomography applications in\npatients of all ages.\nThese scanners are intended to be used for diagnostic\nimaging and for low dose CT lung cancer screening for the\nearly detection of lung nodules that may represent cancer*.\nThe screening must be performed within the established\ninclusion criteria of programs / protocols that have been\napproved and published by either a governmental body or\nprofessional medical society.\n*Please refer to clinical literature, including the results of the\nNational Lung Screening Trial (N Engl J Med 2011;\n365:395-409) and subsequent literature, for further\ninformation."],["Fundamental\nScientific\nTechnology:","The proposed Philips Incisive CT is advanced continuous-\nrotation computed tomography systems suitable for a wide\nrange of computed tomographic (CT) applications.\nThe proposed Philips Incisive CT is used clinically as a\ndiagnostic patient imaging device that produces images that\ncorrespond to tissue density. The quality of the images\ndepends on the level and amount of X-ray energy delivered\nto the tissue. CT imaging displays both high-density tissue,\nsuch as bone, and soft tissue.\nThe principal technological components (rotating x-ray tube,\ndetector and gantry) of the proposed Philips Incisive CT\nsubstantially equivalent to the currently marketed predicate\ndevice Philips Ingenuity CT (K160743, 08/08/2016)\nBased on the information provided above, the proposed\nPhilips Incisive CT does not raise different questions of\nsafety and effectiveness compare to the currently marketed\npredicate device Philips Ingenuity CT (K160743,\n08/08/2016)."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p9-t0","doc_id":"K212441","page_num":9,"bbox":[89.29,91.08,515.32,222.62],"n_rows":2,"n_cols":2,"columns":["","The test results demonstrate that the proposed Philips\nIncisive CT meets the acceptance criteria and is adequate\nfor its intended use. Additionally, the risk management\nactivities show that all risks are sufficiently mitigated, that no\nnew risks are introduced, and that the overall residual risks\nare acceptable."],"rows":[["","The test results demonstrate that the proposed Philips\nIncisive CT meets the acceptance criteria and is adequate\nfor its intended use. Additionally, the risk management\nactivities show that all risks are sufficiently mitigated, that no\nnew risks are introduced, and that the overall residual risks\nare acceptable."],["Summary of Clinical\nData:","The proposed Philips Incisive CT did not require clinical\nstudy since substantial equivalence to the legally marketed\npredicate device was proven with the verification/validation\ntesting."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p9-t1","doc_id":"K212441","page_num":9,"bbox":[89.29,276.86,536.84,679.45],"n_rows":7,"n_cols":9,"columns":["","Scan characteristics Comparison","","","","","","",""],"rows":[["","Scan characteristics Comparison","","","","","","",""],["","","Proposed Philips\nIncisive CT","","Predicate Device","","Conclusion","Conclusion",""],["","","","","Philips Ingenuity","","","",""],["","","","","CT(K160743)","","","",""],["No. of Slices","","64/128","64/128","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Scan Modes","","Surview\nAxial Scan\nHelical Scan","Surview\nAxial Scan\nHelical Scan","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Minimum Scan\nTime","","0.35 sec for 360°\nrotation","0.42 sec for 360° rotation","","","The proposed Philips\nIncisive CT rotation\nspeed faster than\nIngenuity CT to meet\nthe wider heart rate\napplication.\nSafety and\neffectiveness are not\naffected.\nTherefore,\ndemonstrating\nsubstantial\nequivalence.","",""]],"caption_candidate":"Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p10-t0","doc_id":"K212441","page_num":10,"bbox":[89.08,91.65,536.9,675.79],"n_rows":6,"n_cols":4,"columns":["Image (Spatial)\nResolution","High resolution mode:\n16 lp/cm\nStandard resolution\nmode: 13 lp/cm","High resolution mode:16\nlp/cm\nStandard resolution mode:\n13 lp/cm","Identical.\nTherefore, substantially\nequivalent."],"rows":[["Image (Spatial)\nResolution","High resolution mode:\n16 lp/cm\nStandard resolution\nmode: 13 lp/cm","High resolution mode:16\nlp/cm\nStandard resolution mode:\n13 lp/cm","Identical.\nTherefore, substantially\nequivalent."],["Image Noise","0.27% at 120 kV, 230\nmAs, 10 mm slice\nthickness","0.27% at 120 kV, 250\nmAs, 10 mm slice\nthickness","Identical.\nTherefore, substantially\nequivalent."],["Slice\nThicknesses","Helical: 0.67mm – 5mm\nAxial: 0.625mm –\n10.0mm","Helical: 0.67mm – 5mm\nAxial: 0.625mm – 12.5mm","Essentially the same\nslice thickness, does\nnot affect safety and\neffectiveness.\nTherefore,\ndemonstrating\nsubstantial\nequivalence."],["Scan Field of\nView","Up to 500 mm","Up to 500 mm","Identical.\nTherefore, substantially\nequivalent."],["Image Matrix","Up to 1024 * 1024","Up to 1024 * 1024","Identical.\nTherefore, substantially\nequivalent."],["Display","1920 * 1080","1024 * 1280","The proposed Philips\nIncisive CT provide\nhigher resolution than\nIngenuity CT.\nSafety and\neffectiveness are not\naffected.\nTherefore,\ndemonstrating\nsubstantial\nequivalence."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p11-t0","doc_id":"K212441","page_num":11,"bbox":[89.1,91.65,536.89,372.29],"n_rows":3,"n_cols":4,"columns":["Host\nInfrastructure","Windows 10","Windows 7","Same supplier, same\ntechnology and similar\nfunction.\nTherefore, substantially\nequivalent."],"rows":[["Host\nInfrastructure","Windows 10","Windows 7","Same supplier, same\ntechnology and similar\nfunction.\nTherefore, substantially\nequivalent."],["Communication","Compliance with\nDICOM","Compliance with DICOM","Identical.\nTherefore, substantially\nequivalent."],["Dose Reporting\nand\nManagement","Compliance with NEMA\nXR25 , XR28 and XR29","Compliance with NEMA\nXR25 and XR29","Compliance with more\nNEMA standard.\nSafety and\neffectiveness are not\naffected.\nTherefore,\ndemonstrating\nsubstantial\nequivalence."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p11-t1","doc_id":"K212441","page_num":11,"bbox":[89.1,402.2,536.89,699.06],"n_rows":5,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Incisive CT\nFeatures\nName","","Feature description","Secondary\nPredicate\nDevice Philips\nIncisive\nCT(K180015)","Conclusion\n(Function/ User\ninterface/\nWorkflow)",""],["2D Viewer","","In 2D Viewer mode operator can review\noriginal axial images as acquired by the\nscanner.","Yes","Identical.",""],["MPR","","Use the MPR mode to view three-plane\northogonal images. In this mode, the three\nshown planes can be easily correlated.\nThree orthogonal cut\nplanes are shown:\n• Axial Orientation\n• Coronal Orientation\n• Sagittal Orientation","Yes","Identical.",""],["3D(volume\nmode)","","The volume mode is used to display CT\nscanner data in a full volume image. It","Yes","Identical.",""]],"caption_candidate":"equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p12-t0","doc_id":"K212441","page_num":12,"bbox":[89.01,91.33,536.97,702.06],"n_rows":14,"n_cols":4,"columns":["","provides basic tools for image editing and\ngeneration of cine movies.","",""],"rows":[["","provides basic tools for image editing and\ngeneration of cine movies.","",""],["Virtual\nEndoscopy\n(Endo)","The CT Endo viewer is a review function\nthat allows you to perform a general\nflythrough of any suitable anatomical\nstructure that is filled with air or with\ncontrast material, including general vessels,\ncardiac vessels, the bronchus, and the\ncolon.","Yes","Identical."],["Filming","The Filming application is used for viewing,\nrearranging, windowing and zooming\nimages prior to sending them to be printed.","Yes","Identical."],["Image matrix","1024 * 1024","Yes","Identical."],["O-MAR","O-MAR stands for orthopedic metal artifact\nreduction. This post processing capability\nreduces metal induced artifacts and is\ndirected for large orthopedics metals that\ncause photon starvation of the rays that\npass through the metal object.","Yes","Identical."],["Dose\nModulation","Dose-Modulation is a scanner function\nwhich modulates the tube current in two\nways (angular and longitudinal modulation)\nsimultaneously.","Yes","Identical."],["Scan\nPreparation","iPlanning / Manual","Yes","Identical."],["On line MPR","Use the on line MPR mode to view three-\nplane orthogonal images. In this mode, the\nthree shown planes can be easily\ncorrelated.","Yes","Identical."],["Control\nPanel","iStation (Touch Panel)","Yes","Identical."],["iBatch","iBatch application enables the system to\nassist the user to identify the lumbar disk\nspace automatically and creating a batch\nbased on the protocol selected.","Yes","Identical."],["Bolus\nTracking","The Bolus tracking function maximizes the\nefficiency of CT scans that are enhanced\nthrough the use of a contrast agent. This is\ndone by preceding the Clinical scan with\nLocator and Tracker scans.","Yes","Identical."],["SAS(Spiral\nAuto Start)","This feature enable the usage of the injector\nscan trigger.","Yes","Identical."],["Worklist","The Worklist displays patient information\nprovided by the HIS/RIS.","Yes","Identical."],["MPPS","If the patient is from the Worklist and the\nMPPS function is enabled, feedback\nregarding the study status of the patient can\nbe sent to the hospital HIS/RIS.","Yes","Identical."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p13-t0","doc_id":"K212441","page_num":13,"bbox":[89.01,91.33,536.97,692.52],"n_rows":7,"n_cols":4,"columns":["Reporting","The Reporting package allows you to create\ncustomized reports using pre-formatted\ntemplates.\nA template is a specially designed\nformatting document that places the\nanalytical information and images that you\nsend from an application into an organized\nreport which can be printed and saved.","Yes","Identical."],"rows":[["Reporting","The Reporting package allows you to create\ncustomized reports using pre-formatted\ntemplates.\nA template is a specially designed\nformatting document that places the\nanalytical information and images that you\nsend from an application into an organized\nreport which can be printed and saved.","Yes","Identical."],["CCT(Contin\nuous CT)","Continuous CT (CCT) is a scanning mode\nthat allows the physician to perform\nextended, low-dose scans while performing\na biopsy.\nThe resulting images display on a remote\nmonitor in the scan room, providing visual\nfeedback during the biopsy.","Yes","Identical."],["Brain\nPerfusion","Brain Perfusion is a blood flow imaging\napplication that analyzes the uptake of\ninjected contrast in order to determine\nperfusion-related information about one or\nmore regions of interest.","Yes","Identical."],["Dental\n(Dental\nplanning)","Dental application uses to create true-size\n(life size) film images of the mandible and\nmaxilla for assisting oral surgeons in\nplanning implantation of prostheses. Using\na special dental planning procedure, and\nthe images will be created from this scan\nwhich can be input into the Dental planning\napplication.","Yes","Identical."],["iDose4","iDose4 is an iterative reconstruction\ntechnique that improves image quality\nthrough artifact prevention and increased\nspatial resolution at low dose.","Yes","Identical."],["Helical\nRetrospectiv\ne Tagging","Helical retrospective cardiac scanning\nenables the system to acquire a volume of\ndata while the patient’s ECG is recorded.\nThe acquired data is tagged and\nreconstructed retrospectively at any desired\nphase of the cardiac cycle.","Yes","Identical."],["Axial\nProspective\nGating\ncalcium\nscoring","Axial prospective gating uses an external\nECG gating system to synchronize\nindividual axial scans with the patient’s\nheartbeat. The ECG-triggered scans\nsignificantly minimize heart-motion artifacts.","Yes","Identical."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p14-t0","doc_id":"K212441","page_num":14,"bbox":[89.01,91.33,536.97,707.04],"n_rows":6,"n_cols":4,"columns":["Step &\nShoot","Step & Shoot Cardiac provides high quality\nCT images of the coronary arteries and\nheart anatomy at very low radiation dose\nlevels. During Step & Shoot Cardiac, X-rays\nare generated only during the cardiac phase\nof interest.","Yes","Identical."],"rows":[["Step &\nShoot","Step & Shoot Cardiac provides high quality\nCT images of the coronary arteries and\nheart anatomy at very low radiation dose\nlevels. During Step & Shoot Cardiac, X-rays\nare generated only during the cardiac phase\nof interest.","Yes","Identical."],["CCS(Cardia\nc calcium\nscoring)","The Cardiac Calcium Scoring application is\nused to quantify the buildup of calcium\nplaque on the walls of the patient's coronary\narteries and other relevant locations. The\npotential calcifications are highlighted by the\napplication during launch.","Yes","Identical."],["Precise\nimage","Precise image reconstruction is a recon\nmode where the system uses a\ntrained deep learning neural network to\ngenerate noise reduction images\nand improve low contrast detectability\nwith reduced dose compared with\nstandard FBP recon mode.","No","Different:\nsafety and\neffectiveness\nrefer to\nK210760 for\nPrecise Image"],["Precise\ncardiac","Precise Cardiac is a reconstruction\ntechnique with the potential to\nprovide compensation for cardiac\nmotion.","No","Different:\nsafety and\neffectiveness\nrefer to\nK203020 for\nPrecise Cardiac"],["Precise\nposition","Precise Position is a camera based\nworkflow designed to assist with\npositioning the patient automatically\nfrom console or OnPlan, it can:\n• automatically select patient orientation.\n• automatically set vertical centering &\npositioning of the patient to the\nSurview start and end positions.\n• support editing Surview start & end\nrange and scan direction.","No","Different:\nSafety and\neffectiveness\nrefer to\nK203514 for\nPrecise Position"],["Precise\nintervention","In Precise Intervention viewer there are\nseveral tools, they will help\nyou to navigate the needle safely during\nthe intervention.","No","Different: Precise\nintervention is a\nfunction that\nsupport user to\nview the\ndistance, angle\nbetween the\ninjector and the\nobject, system\nvalidation report\nproved that"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p15-t0","doc_id":"K212441","page_num":15,"bbox":[89.13,91.33,536.85,417.67],"n_rows":3,"n_cols":4,"columns":["","","","there is no\nimpact on\nsystem safety\nand effectiveness"],"rows":[["","","","there is no\nimpact on\nsystem safety\nand effectiveness"],["Direct\nresults","Direct Result-With Direct Result the user\nis able to choose a desired\nresult during scan planning phase and get\nthe result for diagnosis without\nfurther intervention.","No","Different: Direct\nresult is\nworkflow\nenhancement to\nmake user direct\nget derived\nimage after\nacquisition no\nimpact on\nsystem safety\nand effectiveness"],["Parallel\nworkflow","Parallel workflow\nThe system support Parallel workflow using\nDual monitor as below:\n- main monitor: Patients, scan, service, \"show\nall\" for scan planning, Help.\n- extend monitor: Completed, viewers, Analysis,\nrecon, filming, report","No","The Parallel\nworkflow of\nIncisive CT is the\nworkflow\nupdate, no\nimpact safety\nand\neffectiveness."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p15-t1","doc_id":"K212441","page_num":15,"bbox":[89.13,447.94,536.85,680.11],"n_rows":8,"n_cols":9,"columns":["","Supplementary Imaging features Comparison","","","","","","",""],"rows":[["","Supplementary Imaging features Comparison","","","","","","",""],["Incisive CT\nFeatures\nName","Incisive CT","Feature description","","Secondary","","Conclusion\n(Function/ User\ninterface/\nWorkflow)","Conclusion",""],["","Features","","","Predicate","","","(Function/ User",""],["","Name","","","Device Philips","","","interface/",""],["","","","","Incisive","","","Workflow)",""],["","","","","CT(K180015)","","","",""],["CTC(CT\nColonoscopy\n)","","CT Colonoscopy (CTC) application enables\nfast and easy visualization of colon scans,\nusing acquired CT images.","Yes","","","Identical.","",""],["VA(Vessel\nAnalysis)","","Vessel Analysis (VA) offers a set of tools for\ngeneral vascular analysis. With VA the user\ncan easily remove bone, and extract\nvessels. User also can perform\nmeasurements such as intraluminal\ndiameter, cross-sectional lumen area,\nlength.","Yes","","","Identical.","",""]],"caption_candidate":"effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212441-p16-t0","doc_id":"K212441","page_num":16,"bbox":[89.21,91.65,536.89,371.51],"n_rows":4,"n_cols":4,"columns":["LNA(Lung\nNodule\nAnalysis)","The Lung Nodule Analysis (LNA)\napplication assists the radiologist with the\ndetection and quantification of pulmonary\nnodules and lesions.","Yes","Identical."],"rows":[["LNA(Lung\nNodule\nAnalysis)","The Lung Nodule Analysis (LNA)\napplication assists the radiologist with the\ndetection and quantification of pulmonary\nnodules and lesions.","Yes","Identical."],["CAA(Cardiac\nArtery\nAnalysis)","The Coronary Artery Analysis provides\nviewing and measuring tools that allow you\nto perform dimensional and quantitative\nmeasurements of the coronary arteries to\nhelp you identify and examine the patient\nstudy for stenosis.","Yes","Identical."],["CFA(Cardiac\nFunction\nAnalysis)","Cardiac Function Analysis (CFA) application\nis used to assess the state of the left\nventricle (LV) and to analyze functional\nheart data.","Yes","Identical."],["DE(Dual\nEnergy)","Spin / Spin scan mode\nDual energy Viewer is an application for\nreview and analysis of CT dual-energy\nscans. User need to load CT dual-energy\nscan data which is two series with similar\nKV. It provides registration function and can\ngenerate different weighted KV images.\nUser can use the tools to separate\nmaterials.","Yes","Identical."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p4-t0","doc_id":"K212442","page_num":4,"bbox":[62.5,664.73,195.93,758.13],"n_rows":2,"n_cols":2,"columns":["Business Name","Cydar Ltd"],"rows":[["Business Name","Cydar Ltd"],["Address","Bulbeck Mill\nBarrington\nCambridgeshire\nCB22 7QY\nUK"]],"caption_candidate":"S05.1.1 Submitter Details","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p5-t0","doc_id":"K212442","page_num":5,"bbox":[62.5,175.75,266.15,340.6],"n_rows":6,"n_cols":2,"columns":["Contact Name","Michael van der Woude"],"rows":[["Contact Name","Michael van der Woude"],["Business Name","Emergo Global Representation LLC"],["Address","2500 Bee Cave Road\nBldg 1, Suite 300\nAustin, TX 78746\nUnited States"],["Phone","512 327-9997"],["Fax","512 327-9998"],["Email","USAgent@UL.com"]],"caption_candidate":"US Agent:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p5-t1","doc_id":"K212442","page_num":5,"bbox":[62.5,545.5,406.34,714.02],"n_rows":8,"n_cols":2,"columns":["Type of 510(k) Submission","Traditional"],"rows":[["Type of 510(k) Submission","Traditional"],["Trade or Proprietary Name","Cydar EV Also referred to as Cydar EV Series B, Cydar EV Maps"],["Common or Usual Name","Interventional Fluoroscopic X-Ray System"],["Regulation Number","21 CFR 892.1650"],["Product Code","OWB, Interventional Fluoroscopic X-Ray System"],["Class of Device","Class II"],["Panel","Radiology"],["Multiple Devices","None."]],"caption_candidate":"next version number will be assigned to the first release of that device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p6-t0","doc_id":"K212442","page_num":6,"bbox":[62.5,139.0,501.48,202.2],"n_rows":3,"n_cols":4,"columns":["Device","Manufacturer","510(k)","Scope"],"rows":[["Device","Manufacturer","510(k)","Scope"],["Cydar EV (primary predicate)","Cydar Ltd","K160088","CT import, intra-operative overlay, post-operative review"],["Endosize","Therenva SAS","K141475","Measurements and segmentation on CT scans"]],"caption_candidate":"devices listed below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p7-t0","doc_id":"K212442","page_num":7,"bbox":[62.5,572.0,532.53,656.85],"n_rows":2,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["1. Technical Characteristics","","","",""]],"caption_candidate":"targeted anatomy is clarified in Cydar EV Series B. See section (add Section references)in this summary.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p8-t0","doc_id":"K212442","page_num":8,"bbox":[62.5,56.5,532.53,590.25],"n_rows":2,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["Intended Use","Cydar EV provides tools\nto:\n• Import and visualise CT\ndata\n• Segment and annotate\nvascular anatomy from\nCT data\n• Place and edit virtual\nguidewires and\nmeasure lengths on\nthem\n• Make measurements of\nanatomical structures\non planar sections of\nthe CT data\n• Produce an operative\nplan from\nmeasurements and\nsegmentation of\npreoperative vessel\nanatomy\n• Overlay planning\ninformation such as\npreoperative vessel\nanatomy onto live\nfluoroscopic images,\naligned based on the\nposition of anatomical\nfeatures present in both\n• Non-rigidly transform\nthe visualisation of\nanatomy when intra-\noperative vessel\ndeformation is\nobserved\n• Post-operatively review\ndata relating to\nprocedures where the\nsystem was used","Cydar EV is intended to\ndisplay combined live 2D X-\nray fluoroscopy and 3D\nanatomy for image guidance\nduring surgery.\nFeatures of the device\ninclude:\nImport and visualise CT scan\ndata.\nSegment and annotate\nvascular anatomy from CT\ndata.\nProduce an operative plan\nOverlay planning\ninformation such\nas preoperative vessel\nanatomy onto live\nfluoroscopic images, aligned\nbased on the position of\nanatomical features present\nin the fluoroscopic images.\nNon-rigidly transform the\nvisualisation of anatomy\nwhen intra-operative vessel\ndeformation is observed.","EndoSize is a software\nsolution that is intended\nto provide Physicians and\nClinical Specialists with\nadditional information to\nassist them in reading and\ninterpreting DICOM CT\nscan images of structures\nof the heart and vessels.\nEndoSize enables the user\nto visualize and measure\n(diameters, lengths,\nvolumes, angles)\nstructures of the heart\nand vessels.","Conclusion: Cydar EV Series B\nis similar intended use to the\nprimary predicate device\ndiffering only in additional\nfeatures; placement and\nediting virtual guidewires,\nmeasurement of lengths and\nmeasurement of anatomical\nstructures on planar sections\nof CT data is similar to the\nsecondary predicate device.\nMeasurement accuracy\nverification testing and\nsummative user study is\nperformed as part of the\ndesign and development\nprocess"]],"caption_candidate":"Cydar Ltd 510(k) Submission: Cydar EV Series B","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p9-t0","doc_id":"K212442","page_num":9,"bbox":[62.5,56.5,532.53,762.35],"n_rows":2,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["Indications for\nuse","Cydar EV is intended to\nassist fluoroscopic X-ray\nguided endovascular\nprocedures in the chest,\nabdomen, and pelvis by\npresenting the operative\nplan in the context of\nintraoperative\nfluoroscopy.\nCydar EV is intended to be\nused for patients\nundergoing a fluoroscopic\nX-ray guided endovascular\nsurgery in the chest\nabdomen and pelvis, and\nwho have had a pre-\noperative CT-scan.\nThe performance of the\nCydar EV software in the\npresence of immature\nvertebral anatomy is\nunknown. The\nInstructions for Use\nexplicitly state this\nuncertainty and that the\nsoftware is therefore not\nrecommended for use in\npatients under the age of\n18.\nIMPORTANT: Pre-\nOperative Maps show\nstatic anatomy derived\nfrom the pre-operative\nCT. Real-time anatomy\nmoves with the\ncardiorespiratory cycle;\nprogressive disease may\ncause the anatomy to\nchange over time; and stiff\nwires, stents or other\nsurgical instruments, may\nstraighten and displace\nblood vessels from the\npre-operative position\nIt is therefore\nmandatory to check the\nreal-time anatomy with\na suitable imaging\ntechnique, such as\ncontrast angiography,\nbefore deploying any\ninvasive medical device.","Cydar EV provides image\nguidance by overlaying\npreoperative 3D vessel\nanatomy from a previously\nacquired contrast-\nenhanced, diagnostic CT\nscan onto live X-ray\nfluoroscopy images in order\nto assist in the positioning of\nguidewires, catheters and\nother endovascular devices.\nCydar EV is intended to\nassist X-ray fluoroscopy-\nguided endovascular\nprocedures in the lower\nthorax, abdomen and pelvis.\nSuitable procedures include\nendovascular aortic\naneurysm repair,\nangioplasty, stenting and\nembolization in the\ncommon iliac, proximal\nexternal iliac and proximal\ninternal iliac arteries and\ncorresponding veins.\nCydar EV is not intended for\nuse in X-ray guided\nprocedures in the liver,\nkidneys or pelvic organs.","Therenva Endosize\nenables visualization and\nmeasurement of\nstructures of the heart\nand vessels for pre-\noperational planning and\nsizing for cardiovascular\ninterventions and surgery\nGeneral functionalities\nare provided such as:\n• Segmentation of\ncardiovascular\nstructures\n• Automatic and manual\ncentreline detection\n• Visualisation of CT scan\nimages in every planes,\n2D review, 3D\nreconstruction, Volume\nRendering, MPR,\nStretched CMPR\n• Measurement and\nannotation tools\n• Reporting tools","Conclusion: Changes in\nwording clarifying target\nanatomy between Cydar EV\nSeries B and primary predicate\nare detailed in the section\nbeneath this table. Other\ndifferences these statements\nincludes clarifications for the\nfollowing which are present\nand equivalent in both\ndevices:\nAdjustment in anatomy to\nhave the option to non-rigidly\ntransform the visualisation of\nthe anatomy in the Map\nStatement clarifies device has\nnot been tested on under 18's\nimmature vertebral anatomy.\nCydar EV series B allows\npreoperative and\nintraoperative imaging,\nEndosize allows preoperative\nimaging only.Other differences\nbetween Cydar EV Series B and\nprimary predicate are as\ndetailed in the section beneath\nthis table, the additional\nfeatures: placement and\nediting virtual guidewires,\nmeasurement of lengths and\nmeasurement of anatomical\nstructures on planar sections\nof CT data. Measurement\naccuracy verification testing\nand summative user study is\nperformed as part of the\ndesign and development\nprocess."]],"caption_candidate":"Cydar Ltd 510(k) Submission: Cydar EV Series B","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p10-t0","doc_id":"K212442","page_num":10,"bbox":[62.5,56.5,532.53,648.93],"n_rows":4,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["Classification\nProduct code /\nregulation","OWB; Interventional\nFluoroscopic X-Ray\nSystem: Regulation:\n892.1660","OWB; Interventional\nFluoroscopic X-Ray System\nRegulation Regulation:\n892.1660","LLZ ; System image\nprocessing radiology\nRegulation: 892.2050","OWB sufficiently covers the\nintended use of Cydar EV."],["Construction","Software product","Software product","Software Product","No difference"],["Performance","Preoperative planning:\nImport and visualise CT\ndata; Segment and\nannotate vascular\nanatomy from CT data;\nPlace and edit virtual\nguidewires and measure\nlengths on them; Make\nmeasurements of\nanatomical structures on\nplanar sections of the CT\ndata; Visualise the\nsegmented vascular\nanatomy, annotations +/-\nmeasurements together\n(the ‘Operative Plan’)\nIntra-operative (Fusion\nimaging functions):\nOverlay planning\ninformation such as\npreoperative vessel\nanatomy onto live\nfluoroscopic images,\naligned based on the\nposition of anatomical\nfeatures present in both;\nNon-rigidly transform the\nvisualisation of anatomy\nwhen intra-operative\nvessel deformation is\nobserved\nPost-operative (Review\nfunctions): Post-\noperatively review data\nrelating to procedures\nwhere the system was\nused","Preoperative planning:\nImport and visualise CT\ndata; Segment and annotate\nvascular anatomy from CT\ndata; Visualise the\nsegmented vascular\nanatomy, annotations +/-\nmeasurements together (the\n‘Operative Plan’)\nIntra-operative (Fusion\nimaging functions: Overlay\nplanning information such\nas preoperative vessel\nanatomy onto live\nfluoroscopic images, aligned\nbased on the position of\nanatomical features present\nin both; Non-rigidly\ntransform the visualisation\nof anatomy when intra-\noperative vessel\ndeformation is observed\nPost-operative (Review\nfunctions): Post-operatively\nreview data relating to\nprocedures where the\nsystem was used","Preoperative planning:\nVisualisation, annotations\nand measurement\nperformed by clinicians\nintended to provide\nreferring physicians with\nclinically relevant\ninformation for diagnosis,\nsurgery, and treatment\nplanning.","Conclusion: Difference\nbetween Cydar EV Series B and\nprimary predicate are features;\nplace and edit virtual\nguidewires and measure\nlengths on them and make\nmeasurements of anatomical\nstructures on planar sections\nof the CT data\nEndoSize is indicated for\npreoperative planning only\nMeasurement accuracy\nverification testing and\nsummative user study is\nperformed as part of the\ndesign and development\nprocess"]],"caption_candidate":"Cydar Ltd 510(k) Submission: Cydar EV Series B","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p11-t0","doc_id":"K212442","page_num":11,"bbox":[62.5,56.5,532.53,725.53],"n_rows":5,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["Design","Cydar EV Series B device is\na software only medical\ndevice that runs on a\nstandard computer that\nmeets the minimum\nrequirements. It can use\nlocal DICOM files or\ndistant PACS server. The\ndevice does not contact\nthe patient, nor does it\ncontrol any life sustaining\ndevices. The information\nand measurements\ndisplayed, exported or\nprinted are validated and\ninterpreted by Physicians.\nEV Maps complies with\nthe DICOM voluntary\nstandards (ACR/NEMA\nDigital Imaging and\nCommunication in\nMedicine).","Cydar EV is a software only\nmedical device that runs on\na standard computer that\nmeets the minimum\nrequirements. It can use\nlocal DICOM files or distant\nPACS server. The device\ndoes not contact the\npatient, nor does it control\nany life sustaining devices.\nThe information and\nmeasurements displayed,\nexported or printed are\nvalidated and interpreted by\nPhysicians.\nEV complies with the DICOM\nvoluntary standards (ACR/\nNEMA Digital Imaging and\nCommunication in\nMedicine).","EndoSize is a software-\nonly device that runs on a\nstandard computer that\nmeets the minimum\nrequirements. It can use\nlocal DICOM files or\ndistant PACS server. The\ndevice does not contact\nthe patient, nor does it\ncontrol any life sustaining\ndevices. The information\nand measurements\ndisplayed, exported or\nprinted are validated and\ninterpreted by Physicians.\nEndoSize complies with\nthe DICOM voluntary\nstandards (ACR/NEMA\nDigital Imaging and\nCommunication in\nMedicine)","Conclusion: No difference to\ndesign between Cydar EV\nSeries B and primary\npredicate, this includes no\ndifference to algorithim or\ndevelopment process."],["2. Clinical Characteristics","","","",""],["Same clinical\ncondition or\npurpose,\nincluding\nsimilar\nseverity and\nstage of\ndisease","Cydar EV is intended only\nto be used for patients\nundergoing a fluoroscopic\nX-ray guided endovascular\nsurgery in the chest,\nabdomen, and pelvis, and\nwho have had a pre-\noperative CT-scan.\nThe clinical procedures\nindicated for the Cydar EV\ndevices are the same. For\nthese procedures a\nclinical specialist will\ndetermine the stage of\ndisease is advanced and\nrequires intervention.\nCydar EV devices are used\nfor guidance during the\nprocedure.","Cydar EV (Series A) is\nintended to assist\nfluoroscopy-guided\nendovascular procedures in\nthe lower thorax, abdomen\nand pelvis. Suitable\nprocedures include (but are\nnot limited to) endovascular\naortic aneurysm repair, (AAA\nand mid-distal TAA),\nstenting, and embolisation\nin the common iliac,\nproximal external iliac and\nproximal internal iliac\narteries and their\ncorresponding veins. Cydar\nEV (Series A) is not intended\nfor use in X-ray guided\nprocedures in the liver,\nkidneys or pelvis organs.","Intended for patients who\nrequire cardiovascular\ninterventions, EVAR,\nTEVAR, TAVI and\nPeripheral",""],["Anatomical\nSite","Device is used indicated\nfor fluoroscopic X-ray\nguided endovascular\nprocedures in the chest,\nabdomen, and pelvis","Device is used indicated for\nfluoroscopic X-ray guided\nendovascular procedures in\nthe lower thorax,\nabdomen, and pelvis","Device is used indicated\nfor heart and vessels","No significant difference. The\nanatomy is clarified in this\ndocument (add Section\nreferences)."]],"caption_candidate":"Cydar Ltd 510(k) Submission: Cydar EV Series B","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212442-p12-t0","doc_id":"K212442","page_num":12,"bbox":[62.5,56.5,532.53,575.76],"n_rows":7,"n_cols":5,"columns":["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],"rows":[["Assessment\nCriteria","Cydar EV Series B\nCydar Medical Ltd\nDevice under\nassessment","Cydar EV Series A\nCydar Medical Ltd\nPrimary Equivalent Device\nK160088","EndoSize\nTherenva\nSecondary Equivalent\nDevice\nK141475","Identified differences or\nconclusion of no difference"],["User Profile","The target clinical users\nfor the Cydar EV Series B\ndevice are experienced\nmedical practitioners\nspecialising in\nendovascular surgery\n(such as vascular\nsurgeons and\ninterventional\nradiologists)\nradiographers, and\nspecialist nurses. Other\nusers of the planning\nfunctions may include\nmedical device company\nrepresentatives and\nproduct specialists.","The target clinical users for\nthe Cydar EV Series B device\nare experienced medical\npractitioners specialising in\nendovascular surgery (such\nas vascular surgeons and\ninterventional radiologists)\nradiographers, and\nspecialist nurses.","Physicians and clinical\nspecialists, users involved\nin preoperative planning","No difference in targeted users"],["Patient\nContact","No patient contact","No patient contact","No patient contact","No difference"],["Clinical\nEnvironment","Operating room, office\n(during planning)","Operating room, office\n(during procedure planning)","Office (during procedure\nplanning)","Conclusion: No significant\ndifference. Cydar EV Series B\nand secondary predicate differ\nslightly in intended clinical\nenvironment as the predicate\nis not intended for intra-\noperative use."],["3. Non-clinical performance data","","","",""],["Standards","IEC 62304\nIEC 62366\nISO 14971","IEC 62304\nIEC 62366\nISO 14971","IEC 62304\nISO 14971","Equivalent standards applied"],["NEMA PS 3.1-\n3.20 DICOM","Applied","Applied","Applied","Conclusion: No difference"]],"caption_candidate":"Cydar Ltd 510(k) Submission: Cydar EV Series B","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K212466-p7-t0","doc_id":"K212466","page_num":7,"bbox":[228.77,284.81,506.74,320.57],"n_rows":2,"n_cols":4,"columns":["Measurement","Accuracy\n(Mean±1.96STD)","Data Range","Correlation"],"rows":[["Measurement","Accuracy\n(Mean±1.96STD)","Data Range","Correlation"],["GLS","-1.4% ± 3.93%","-4% - -24%","0.88"]],"caption_candidate":"GLS by AFI. Statistical analysis was done by Correlation, Bland-Altman:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212519-p7-t0","doc_id":"K212519","page_num":7,"bbox":[92.38,115.6,519.63,678.5],"n_rows":11,"n_cols":3,"columns":["Device","Carestream\nLogicon\nCaries Detector","Overjet Caries\nAssist\n(proposed)"],"rows":[["Device","Carestream\nLogicon\nCaries Detector","Overjet Caries\nAssist\n(proposed)"],["510k","P980025","K212519"],["Regulation No.\n/ Description","CFR 892.2070\nMedical image analyzer","CFR 892.2070\nMedical image analyzer"],["Indications","The Logicon Caries Detector is a\nsoftware device that is an aid in the\ndiagnosis of caries that have\npenetrated into the dentin, on\nun-restored proximal surfaces of\nsecondary dentition through the\nstatistical analysis of digital\nintra-oral radiographic imagery. The\ndevice provides additional\ninformation for the clinician to use\nin his/her diagnosis of a tooth\nsurface suspected of being carious.\nIt is designed to work in conjunction\nwith an existing Carestream dental\nRVG digital X-ray radiographic\nsystem with dental imaging\nsoftware (dis) for Windows XP or\nhigher.","The Overjet Caries Assist (OCA) is a\nradiological, automated, concurrent\nread, computer-assisted detection\nsoftware intended to aid in the\ndetection and segmentation of caries\non bitewing radiographs. The device\nprovides additional information for\nthe dentist to use in their diagnosis of\na tooth surface suspected of being\ncarious. The device is not intended as\na replacement for a complete dentist's\nreview or their clinical judgment that\ntakes into account other relevant\ninformation from the image, patient\nhistory, and actual in vivo clinical\nassessment."],["End User","Dentist","Dentist"],["Patient Population","Patients requiring dental services,\nall sexes, no age restriction","Patients requiring dental services,\nall sexes, at least 18 years of age,\nand with permanent dentition."],["Platform","Windows PC","Web - Edge, Chrome, Firefox"],["OS","Microsoft Window 7, 8, 10","Any"],["User Interface","Mouse, Keyboard","Mouse, Keyboard, Trackpad"],["Image Input\nSources","Images can be scanned, loaded\nfrom connected Carestream image\nsolutions","Images imported from the\nradiographic device, or from the\npractice management system, from\nCarestream or Schick sensors"],["Image format","Carestream","jpg, png, eop, jif, dicom"]],"caption_candidate":"9. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212519-p8-t0","doc_id":"K212519","page_num":8,"bbox":[92.5,72.5,519.5,404.5],"n_rows":5,"n_cols":3,"columns":["Processing\nArchitectu\nre","The software provides graphical\nrepresentation of the density change\nin a tooth, by looking for a pattern\nof density dips starting at the tooth\nsurface, penetrating the enamel and\ngoing into the dentin. Enamel is\nrepresented by 10 green lines and\ndentin by 5 blue lines. If a pattern\nsuggestive of caries exists, the dips\nare highlighted with red dots to\nwarn the dentist.","Three layers:\n- The Network layer works with the\npractice PACS or EMR to transmit\nthe image and meta-data to Overjet.\n- The decision layer processes the\nimage to ensure it is the correct data\ntype, and then annotates it via the\nalgorithm\n- The presentation layer displays the\nannotated image in a non-diagnostic\nviewer. The dentist can filter,\ndisplay, hide, create and edit the\nannotations presented."],"rows":[["Processing\nArchitectu\nre","The software provides graphical\nrepresentation of the density change\nin a tooth, by looking for a pattern\nof density dips starting at the tooth\nsurface, penetrating the enamel and\ngoing into the dentin. Enamel is\nrepresented by 10 green lines and\ndentin by 5 blue lines. If a pattern\nsuggestive of caries exists, the dips\nare highlighted with red dots to\nwarn the dentist.","Three layers:\n- The Network layer works with the\npractice PACS or EMR to transmit\nthe image and meta-data to Overjet.\n- The decision layer processes the\nimage to ensure it is the correct data\ntype, and then annotates it via the\nalgorithm\n- The presentation layer displays the\nannotated image in a non-diagnostic\nviewer. The dentist can filter,\ndisplay, hide, create and edit the\nannotations presented."],["Data Source","Bitewing radiographs acquired\nfrom Carestream dental RVG\ndigital X-ray radiographic\nsystem","Digital files of Bitewing radiographs\nwhose longer edge is greater than 500\npixel resolution"],["Output","● Outline of suspected region\n● Tooth Density\n● Lesion (caries) probability","Caries detection and segmentation\non radiograph resulting in outline of\nsuspected caries"],["Performance\nTesting","Increase in dentist’s sensitivity of\napproximately 20%","Increase in dentist’s sensitivity of\ngreater than 15%"],["Level of Concern","Moderate","Moderate"]],"caption_candidate":"Overjet Inc. Overjet Caries Assist Software: K212519","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212519-p10-t0","doc_id":"K212519","page_num":10,"bbox":[142.5,84.61,533.3,215.04],"n_rows":4,"n_cols":5,"columns":["","","Ground Truth","",""],"rows":[["","","Ground Truth","",""],["Assessment","Overjet\nAI","Caries\nPresent","No Caries\nPresent","Total (%)"],["Observed Counts","Caries Present\nNo Caries\nTotal (%)","175 (2.5%)\n68 (1.0%)\n243 (3.4%)","131 (1.8%)\n6755 (94.8%)\n6886 (96.6%)","306 (4.3%)\n6823 (95.7%)\n7129"],["Diagnostic\nStatistic","Measure\nSensitivity\nSpecificity","Estimate\n72.0% (175/243)\n98.1% (6755/6886)","95% CI1\n62.9%, 81.1%\n97.7%, 98.5%",""]],"caption_candidate":"Standalone Performance of Overjet AI Algorithm based on Surfaces","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p10-t0","doc_id":"K212616","page_num":10,"bbox":[61.92,101.3,543.38,708.35],"n_rows":45,"n_cols":9,"columns":["Product","","","","Koios DS for Breast","","","Koios DS",""],"rows":[["Product","","","","Koios DS for Breast","","","Koios DS",""],["","","","","(K190442)","","","(subject device)",""],["","Physical","","","Software Package","","","Software Package",""],["","Characteristics","","","Operates on off-the-shelf hardware","","","Operates on off-the-shelf hardware",""],["","Storage","","","Storage not supported","","","Storage not supported",""],["","Image Input","","","DICOM","","","DICOM",""],["Characteristics","Characteristics","","","Decision support device used to assist","","","Decision support device used to assist in",""],["","","","","in the assessment and","","","the assessment and characterization of",""],["","","","","characterization of breast lesions","","","breast lesions and thyroid nodules using US",""],["","","","","using US image data.","","","image data.",""],["Intended\nUse/Indications\nfor Use","","","","Koios Decision Support (DS) for Breast","","","Koios Decision Support (DS) is an artificial",""],["","","","","is a software application designed to","","","intelligence (AI)/machine learning (ML)-",""],["","","","","assist trained interpreting physicians","","","based computer-aided diagnosis (CADx)",""],["","","","","in analyzing the breast ultrasound","","","software device intended for use as an",""],["","","","","images of patients with soft tissue","","","adjunct to diagnostic ultrasound",""],["","","","","breast lesions who are being referred","","","examinations of lesions suspicious for",""],["","","","","for further diagnostic ultrasound","","","breast or thyroid cancer.",""],["","","","","examination.","","","",""],["","","","","","","","Koios DS allows the user to select or",""],["","","","","Koios DS for Breast is a machine","","","confirm regions of interest (ROIs) within an",""],["","","","","learning-based decision support","","","image representing a single lesion or",""],["","","","","system, indicated as an adjunct to","","","nodule to be analyzed. The software then",""],["","","","","diagnostic ultrasound for breast","","","automatically characterizes the selected",""],["","","","","cancer.","","","image data to generate an AI/ML-derived",""],["","","","","","","","cancer risk assessment and selects",""],["","","","","Koios DS for Breast automatically","","","applicable lexicon-based descriptors",""],["","","","","classifies user-selected region(s) of","","","designed to improve overall diagnostic",""],["","","","","interest (ROIs) containing a breast","","","accuracy as well as reduce interpreting",""],["","","","","lesion into four BI-RADS-aligned","","","physician variability.",""],["","","","","categories (Benign, Probably Benign,","","","",""],["","","","","Suspicious, Probably Malignant), and","","","Koios DS software may also be used as an",""],["","","","","displays a continuous graphical","","","image viewer of multi-modality digital",""],["","","","","confidence level indicator of where","","","images, including ultrasound and",""],["","","","","the lesion falls across all categories.","","","mammography. The software includes",""],["","","","","Koios DS for Breast also automatically","","","tools that allow users to adjust, measure",""],["","","","","classifies lesion shape and orientation","","","and document images, and output into a",""],["","","","","according to BI-RADS descriptors.","","","structured report.",""],["","","","","","","","",""],["","","","","The software requires a user to select","","","Koios DS software is designed to assist",""],["","","","","up to two ROIs, from up to two","","","trained interpreting physicians in analyzing",""],["","","","","orthogonal views, that represent a","","","the breast ultrasound images of adult (>=",""],["","","","","single lesion to be selected and","","","22 years) female patients with soft tissue",""],["","","","","processed. When utilized by an","","","breast lesions and/or thyroid ultrasounds",""],["","","","","interpreting physician who has","","","of all adult (>= 22 years) patients with",""],["","","","","completed the prescribed training,","","","thyroid nodules suspicious for cancer.",""]],"caption_candidate":"6. Substantial Equivalence Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p11-t0","doc_id":"K212616","page_num":11,"bbox":[61.92,72.35,543.38,718.32],"n_rows":48,"n_cols":7,"columns":["","","this device provides information that","","When utilized by an interpreting physician\nwho has completed the prescribed\ntraining, this device provides information\nthat may be useful in recommending\nappropriate clinical management.","",""],"rows":[["","","this device provides information that","","When utilized by an interpreting physician\nwho has completed the prescribed\ntraining, this device provides information\nthat may be useful in recommending\nappropriate clinical management.","",""],["","","may be useful in rendering an","","","",""],["","","accurate diagnosis.","","","",""],["","","","","","",""],["","","Patient management decisions should","","","",""],["","","not be made solely on the results of","","","",""],["","","the Koios DS for Breast analysis. This","","","",""],["","","device is intended to help trained","","","",""],["","","interpreting physicians improve their","","","",""],["","","overall accuracy as well as reduce","","","",""],["","","inter- and intra-operator variability.","","","",""],["","","","","","",""],["","","Koios DS for Breast may also be used","","","",""],["","","as an image viewer of multi-modality","","","",""],["","","digital images, including ultrasound","","","",""],["","","and mammography. The software","","","",""],["","","includes tools that allow users to","","","",""],["","","adjust, measure and document","","","",""],["","","images, and output into a structured","","","",""],["","","report.","","","",""],["Target Population\n(subset of above\nfor comparison\npurposes)","","Koios Decision Support (DS) for Breast","","Koios DS software is designed to assist\ntrained interpreting physicians in analyzing\nthe breast ultrasound images of adult (>=\n22 years) female patients with soft tissue\nbreast lesions and/or thyroid ultrasounds\nof all adult (>= 22 years) patients with\nthyroid nodules suspicious for cancer.","",""],["","","is a software application designed to","","","",""],["","","assist trained interpreting physicians","","","",""],["","","in analyzing the breast ultrasound","","","",""],["","","images of patients with soft tissue","","","",""],["","","breast lesions who are being referred","","","",""],["","","for further diagnostic ultrasound","","","",""],["","","examination.","","","",""],["","","","","","",""],["Limitations for\nUse\n(subset of above\nfor comparison\npurposes)","Limitations:\nKoios DS for Breast is not to be used\non sites of post-surgical excision, or\nimages with doppler, elastography, or\nother overlays present in them.\nKoios DS for Breast is not intended for\nthe primary interpretation of digital\nmammography images.\nKoios DS for Breast is not intended for\nuse on mobile devices.","Limitations:","","","Limitations:",""],["","","Koios DS for Breast is not to be used","","","• Patient management decisions should",""],["","","on sites of post-surgical excision, or","","","not be made solely on the results of the",""],["","","images with doppler, elastography, or","","","Koios DS analysis.",""],["","","other overlays present in them.","","","• Koios DS software is not to be used for",""],["","","","","","the evaluation of normal tissue, on sites of",""],["","","Koios DS for Breast is not intended for","","","post-surgical excision, or images with",""],["","","the primary interpretation of digital","","","doppler, elastography, or other overlays",""],["","","mammography images.","","","present in them.",""],["","","","","","• Koios DS software is not intended for use",""],["","","Koios DS for Breast is not intended for","","","on portable handheld devices (e.g.",""],["","","use on mobile devices.","","","smartphones or tablets) or as a primary",""],["","","","","","diagnostic viewer of mammography",""],["","","","","","images.",""],["","","","","","• The software does not predict the",""],["","","","","","presence of the thyroid nodule margin",""],["","","","","","descriptor, extra-thyroidal extension. In",""],["","","","","","the event that this condition is present, the",""],["","","","","","user may select this category manually",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p12-t0","doc_id":"K212616","page_num":12,"bbox":[61.92,72.33,543.38,651.0],"n_rows":42,"n_cols":9,"columns":["","","","","","","","from the margin descriptor list.",""],"rows":[["","","","","","","","from the margin descriptor list.",""],["","Modality Used for","","Breast Ultrasound Data","","","","Breast Ultrasound Data",""],["","Analysis","","","","","","Thyroid Ultrasound Data",""],["Input","Input","","","Medical images provided in a DICOM","","","Medical images provided in a DICOM",""],["","","","","format","","","format",""],["ROI\nRequirements","","","The software requires a user to select\nup to two ROIs, from up to two\northogonal views, that represent a\nsingle lesion to be selected and\nprocessed.","The software requires a user to select","","","Breast",""],["","","","","up to two ROIs, from up to two","","","The software requires a user to select up to",""],["","","","","orthogonal views, that represent a","","","two ROIs, from up to two orthogonal",""],["","","","","single lesion to be selected and","","","views, that represent a single lesion to be",""],["","","","","processed.","","","selected and processed.",""],["","","","","","","","",""],["","","","","","","","Thyroid",""],["","","","","","","","Two ROIs that represent a single lesion to",""],["","","","","","","","be selected and processed are required for",""],["","","","","","","","analysis.",""],["","","","","","","","",""],["","","","","","","","The first ROI is drawn on the transverse",""],["","","","","","","","view of the nodule. The second is drawn on",""],["","","","","","","","the longitudinal view.",""],["Output (Breast)","","","","Koios defined categorical and","","","Koios DS Breast defined categorical and",""],["","","","","continuous outputs (confidence level","","","continuous outputs (confidence level",""],["","","","","indicator) that align to BI-RADS and","","","indicator) that align to BI-RADS, U1-U5, and",""],["","","","","auto-classified shape and orientation","","","auto-classified shape and orientation.",""],["Output (Thyroid)","","","N/A","N/A","","","Koios DS Thyroid software automatically",""],["","","","","","","","classifies thyroid nodules suspicious for",""],["","","","","","","","cancer based on image data generating an",""],["","","","","","","","output aligned to either the TI-RADS or",""],["","","","","","","","ATA classification guidelines. The system",""],["","","","","","","","automatically generates user-modifiable",""],["","","","","","","","nodule descriptors (Composition,",""],["","","","","","","","Echogenicity, Shape, Margin, Echogenic",""],["","","","","","","","Foci) and a direct, image-derived cancer",""],["","","","","","","","risk assessment that is translated into an",""],["","","","","","","","optional lexicon-specific modifier.",""],["","Comparative","","Metric: AUC\nCases: 900\nReaders: 15","","","Metric: AUC\nCases: 900\nReaders: 15","Metric: AUC",""],["","Clinical","","","","","","Cases: 900",""],["","Performance","","","","","","Readers: 15",""],["","Testing (Breast)","","","","","","",""],["","Comparative","","N/A","","","Metric: AUC\nCases: 650\nReaders: 15","",""],["","Clinical","","","","","","",""],["","Performance","","","","","","",""],["","Testing (Thyroid)","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p18-t0","doc_id":"K212616","page_num":18,"bbox":[71.62,134.15,480.26,473.98],"n_rows":34,"n_cols":18,"columns":["Reader\nID","","","Board\nCertification/\nSpecialty","","","","Breast","","Years of\nExperience –\nMammography\nand/or Breast\nUltrasound","","","Academic\nInstitution\nAffiliation\n(Yes/No)","","","MQSA\nQualified\nInterpreting\nPhysician","",""],"rows":[["Reader\nID","","","Board\nCertification/\nSpecialty","","","","Breast","","Years of\nExperience –\nMammography\nand/or Breast\nUltrasound","","","Academic\nInstitution\nAffiliation\n(Yes/No)","","","MQSA\nQualified\nInterpreting\nPhysician","",""],["","","","","","","","Fellowship","","","","","","","","","",""],["","","","","","","","Trained","","","","","","","","","",""],["","","","","","","","and/or","","","","","","","","","",""],["","","","","","","","Dedicated","","","","","","","","","",""],["","","","","","","","Breast Imager","","","","","","","","","",""],["1","","","","Diagnostic","","No","","","13 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["2","","","","Diagnostic","","No","","","4 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["3","","","","Diagnostic","","Yes","","","7 years","","","Yes","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["4","","","","Breast","","No","","","0 years","","","No","","","No","",""],["","","","","Surgeon","","","","","","","","","","","","",""],["","5","","","OB/GYN","","","No","","","20 years","","","No","","","No",""],["6","","","","Diagnostic","","No","","","13 years","","","Yes","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["7","","","","Diagnostic","","No","","","3 years","","","Yes","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["","8","","","OB/GYN","","","No","","","0 years","","","No","","","No",""],["9","","","","Diagnostic","","Yes","","","15 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["10","","","","Diagnostic","","No","","","13 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["11","","","","Diagnostic","","Yes","","","30 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["12","","","","Diagnostic","","Yes","","","10 years","","","Yes","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["13","","","","Diagnostic","","No","","","0 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["14","","","","Interventional","","No","","","4 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["15","","","","Breast","","No","","","25 years","","","Yes","","","No","",""],["","","","","Surgeon","","","","","","","","","","","","",""]],"caption_candidate":"Reader Background","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p22-t0","doc_id":"K212616","page_num":22,"bbox":[52.38,404.4,348.18,707.88],"n_rows":19,"n_cols":3,"columns":["Reader","","Experience (post-"],"rows":[["Reader","","Experience (post-"],["","Reader Category",""],["ID","","residency)"],["","",""],["R1","Domestic Endocrinologist (End)","< 10 years"],["R2","Domestic Radiologist (Rad)","≥ 20 years"],["R3","Domestic Rad","≥ 20 years"],["R4","Domestic Rad","≥ 10 and < 20 years"],["R5","Domestic Rad","≥ 10 and < 20 years"],["R6","Domestic Rad","≥ 10 and < 20"],["R7","Domestic Rad","≥ 20 years"],["R8","Domestic Rad","< 10 years"],["R9","Domestic Rad","≥ 20 years"],["R10","Domestic Rad","≥ 20 years"],["R11","Domestic End","< 10 years"],["R12","European Rad","≥ 20 years"],["R13","European Rad","≥ 20 years"],["R14","European End","≥ 20 years"],["R15","European End","≥ 20 years"]],"caption_candidate":"Reader Experience","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p27-t0","doc_id":"K212616","page_num":27,"bbox":[26.88,72.48,525.7,711.1],"n_rows":8,"n_cols":3,"columns":["FNA","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(US readers, US data)","+0.053 [0.026, 0.080] (sensitivity)\n+0.180 [0.161, 0.198] (specificity)"],"rows":[["FNA","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(US readers, US data)","+0.053 [0.026, 0.080] (sensitivity)\n+0.180 [0.161, 0.198] (specificity)"],["","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(EU readers, EU data)","+0.060 [-0.009, 0.129] (sensitivity)\n+0.296 [0.238, 0.354] (specificity)"],["Secondary Analysis 3","Change in average AUC with Koios DS\n(EU Readers, EU Data)","+ 0.079 [0.024, 0.134] (parametric)\n+ 0.066 [0.014, 0.118] (non-parametric)"],["Secondary Analysis 4","Inter-Reader Variability measuring the\nassociation of TI-RADS points assigned\nwith and without decision support\nDifference (Relative Change %)","40.7% (all readers, all data)\n37.4% (US readers, US data)\n49.7% (EU Readers, EU Data)"],["Secondary Analysis 5","Impact on Interpretation Time","-23.6% (all readers, all data)\n-22.7% (US readers, US data)\n-32.4% (EU Readers, EU Data)"],["Secondary Analysis 6","Change in average AUC with Koios DS\ndescriptor classifiers only (without AI\nAdapter) (parametric)","+0.022 [0.005, 0.039]\n(all readers, all data)\n+0.017 [-0.007, 0.041]\n(US readers, US data)\n+0.010 [-0.051, 0.071]\n(EU Readers, EU Data)"],["","Change in average AUC with Koios DS\ndescriptor classifiers only (without AI\nAdapter) (non-parametric)","+0.019 [0.001, 0.037]\n(all readers, all data)\n+0.015 [-0.010, 0.039]\n(US readers, US data)\n+0.004 [-0.054, 0.062]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of FNA with Koios DS\ndescriptor classifiers only (without AI\nAdapter)","Sensitivity:\n+0.052 [0.022, 0.081]\n(all readers, all data)\n+0.026 [-0.014, 0.066]\n(US readers, US data)\n+0.109 [-0.004, 0.221]\n(EU Readers, EU Data)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p28-t0","doc_id":"K212616","page_num":28,"bbox":[26.88,72.48,525.7,709.9],"n_rows":3,"n_cols":3,"columns":["","","Specificity\n-0.009 [-0.024, 0.006]\n(all readers, all data)\n-0.001 [-0.022, 0.019]\n(US readers, US data)\n-0.032 [-0.095, 0.031]\n(EU Readers, EU Data)"],"rows":[["","","Specificity\n-0.009 [-0.024, 0.006]\n(all readers, all data)\n-0.001 [-0.022, 0.019]\n(US readers, US data)\n-0.032 [-0.095, 0.031]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of Follow-up with Koios DS\ndescriptor classifiers only (without AI\nAdapter) – excluding cases\nrecommended for FNA","Sensitivity\n0.079 [0.031, 0.128]\n(all readers, all data)\n0.072 [0.008, 0.135]\n(US readers, US data)\n0.133 [-0.068, 0.334]\n(EU Readers, EU Data)\nSpecificity\n0.015 [-0.010, 0.040]\n(all readers, all data)\n0.012 [-0.021, 0.045]\n(US readers, US data)\n0.010 [-0.093, 0.113]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of Follow-up with Koios DS\ndescriptor classifiers only (without AI\nAdapter) – including cases\nrecommended for FNA","Sensitivity\n+0.047 [0.026, 0.067]\n(all readers, all data)\n+0.037 [0.009, 0.065]\n(US readers, US data)\n+0.067 [0.000, 0.134]\n(EU Readers, EU Data)\nSpecificity\n+0.000 [-0.013, 0.012]\n(all readers, all data)\n+0.003 [-0.014, 0.019]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212616-p29-t0","doc_id":"K212616","page_num":29,"bbox":[21.48,194.54,502.51,610.42],"n_rows":7,"n_cols":4,"columns":["","All Readers, All Data","US Readers, US Data","EU Readers, EU Data"],"rows":[["","All Readers, All Data","US Readers, US Data","EU Readers, EU Data"],["Change in average Sensitivity/Specificity of FNA","","",""],["TI-RADS categorization\nw/AI Adapter + size\ncriteria","+0.084 [0.054, 0.113]\n(sensitivity)\n+0.140 [0.125, 0.155]\n(specificity)","+0.058 [0.017, 0.098]\n(sensitivity)\n+0.130 [0.110, 0.151]\n(specificity)","+0.125 [0.014, 0.237]\n(sensitivity)\n+0.171 [0.109, 0.233]\n(specificity)"],["TI-RADS categorization +\nsize criteria","+0.052 [0.022, 0.081]\n(sensitivity)\n-0.009 [-0.024, 0.006]\n(specificity)","+0.026 [-0.014, 0.066]\n(sensitivity)\n-0.001 [-0.022, 0.019]\n(specificity)","+0.109 [-0.004, 0.221]\n(sensitivity)\n-0.032 [-0.095, 0.031]\n(specificity)"],["Change in average Sensitivity/Specificity of Follow-up","","",""],["TI-RADS categorization\nw/AI Adapter + size\ncriteria","+0.060 [0.040, 0.080]\n(sensitivity)\n+0.206 [0.192, 0.219]\n(specificity)","+0.053 [0.026, 0.080]\n(sensitivity)\n+0.180 [0.161, 0.198]\n(specificity)","+0.060 [-0.009, 0.129]\n(sensitivity)\n+0.296 [0.238, 0.354]\n(specificity)"],["TI-RADS categorization +\nsize criteria","+0.047 [0.026, 0.067]\n(sensitivity)\n+0.000 [-0.013, 0.012]\n(specificity)","+0.037 [0.009, 0.065]\n(sensitivity)\n+0.003 [-0.014, 0.019]\n(specificity)","+0.067 [0.000, 0.134]\n(sensitivity)\n-0.012 [-0.065, 0.041]\n(specificity)"]],"caption_candidate":"Summary of System Clinical Performance Using TI-RADS RSS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212624-p4-t0","doc_id":"K212624","page_num":4,"bbox":[56.16,235.86,300.45,633.46],"n_rows":33,"n_cols":2,"columns":["Company:","EVER FORTUNE.AI Co.,"],"rows":[["Company:","EVER FORTUNE.AI Co.,"],["",""],["","8 F., No. 573, Sec. 2, Taiwa"],["",""],["","West Dist., Taichung City 4"],["",""],["","Phone: (886)-4-2322-6363"],["",""],["","Fax: (886)-4-2322-9797"],["",""],["","ra99@everfortuneai.com.tw"],["",""],["Contact:","MING-FONG, CHEN (Chai"],["",""],["","ra99@everfortuneai.com.tw"],["",""],["Date Prepared:","March 09, 2022"],["",""],["I.Name of the Device",""],["",""],["Name of Device:","EFAI Intelligent Cardiothor"],["",""],["Common Name:","EFAI iCTR"],["",""],["Classification Name:","Medical image management"],["",""],["Review Panel:","Radiology"],["",""],["Regulation:","21 CFR 892.2050"],["",""],["Device Class:","Class II"],["",""],["Product Code:","QIH"]],"caption_candidate":"Company: EVER FORTUNE.AI Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K212624-p5-t0","doc_id":"K212624","page_num":5,"bbox":[54.02,113.25,541.06,153.36],"n_rows":2,"n_cols":9,"columns":["","Name","","","Manufacturer","","","510(K)#",""],"rows":[["","Name","","","Manufacturer","","","510(K)#",""],["Imbio RV/LV Software","","","Imbio, LLC","","","K203256","",""]],"caption_candidate":"III. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212624-p6-t0","doc_id":"K212624","page_num":6,"bbox":[53.91,85.56,542.85,752.28],"n_rows":17,"n_cols":8,"columns":["Table - Comparison Table","","","","","","",""],"rows":[["Table - Comparison Table","","","","","","",""],["","","","","","","",""],["Feature","","EFAI iCTR\n(K212624)","","Imbio RV/LV","","Difference",""],["","","","","Software","","",""],["","","","","(K203256)","","",""],["","","","","","","",""],["Manufacturer","","Ever Fortune.AI Co.,\nLtd.","Imbio LLC","","","NA",""],["Regulation Number","","21 CFR §890.2050","21 CFR §890.2050","","","Same",""],["Regulatory Class","","Class II","Class II","","","Same",""],["Product Code","","QIH","QIH","","","Same",""],["Regulation\nName","","Medical image\nmanagement and\nprocessing system","Medical image\nmanagement and\nprocessing system","","","Same",""],["Device Property","","SaMD","SaMD","","","Same",""],["","","","","","","",""],["","Intended Use / Indications For Use","","","","","",""],["","","","","","","",""],["EFAI iCTR (K212624)","","EFAI Intelligent Cardiothoracic Ratio Assessment System (or iCTR) is a software\nfor use by hospital and clinics to automatically assess the cardiothoracic ratio\n(CTR) of a chest X-ray image from the X-ray imager subject. The iCTR is\ndesigned to measure the maximal transverse diameter\nof heart and maximal inner transverse diameter of thoracic cavity and calculate\nthe CTR of a chest X-ray image in posterior-anterior (PA) chest view using an\nartificial intelligence algorithm.\nIntended users of the software are aimed to the physicians or other licensed\npractitioners in the healthcare institutions, such as clinics, hospitals, healthcare\nfacilities, residential care facilities and long-term care services. The system is\nsuitable for adults between 20 - 80 years of age.\nIts results are not intended to be used on a stand-alone basis for clinical-decision\nmaking orotherwise preclude clinical assessment of cardiothoracic ratio (CTR)\ncases.","","","","",""],["Imbio RV/LV Software\n(K203256)","","The Imbio RV/LV Software device is designed to measure the maximal diameters\nof the right and left ventricles of the heart from a volumetric CTPA acquisition\nand report the ratio of those measurements. RV/LV analyzes cases using an\nartificial intelligence algorithm to identify the location and measurements of the","","","","",""]],"caption_candidate":"EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212624-p7-t0","doc_id":"K212624","page_num":7,"bbox":[53.91,85.56,542.85,756.84],"n_rows":9,"n_cols":6,"columns":["","ventricles. The RV/LV software provides the user with annotated images showing\nventricular measurements. Its results are not intended to be used on a stand-alone\nbasis for clinical decision-making or otherwise preclude clinical assessment of\nCTPA cases.","","","",""],"rows":[["","ventricles. The RV/LV software provides the user with annotated images showing\nventricular measurements. Its results are not intended to be used on a stand-alone\nbasis for clinical decision-making or otherwise preclude clinical assessment of\nCTPA cases.","","","",""],["","","","","",""],["Technical\nCharacteristics","EFAI iCTR\n(K212624)","","Imbio RV/LV","","Difference"],["","","","Software","",""],["","","","(K203256)","",""],["","","","","",""],["Input","Post-anterior (PA) view\nchest X-ray image","Non-gated, CT\nPulmonary\nangiography images","","","Yes, there is difference.\nThe proposed device used\nchest x-ray images in PA\nview as input to identify\nthe maximal diameters of\nthe maximal transverse\ndiameter of heart and\nmaximal inner transverse\ndiameter of thoracic cavity.\nThe primary device used\nCTPA images as input to\nidentify the maximal\ndiameters of the right and\nleft ventricles of the heart.\nThe verification report can\nverify the difference does\nnot raise the impact of the\nsafety and effectiveness.\nBoth of the devices are in\nDICOM images as input."],["Output","Reports, DICOM\nSecondary Capture\nseries","Reports, DICOM\nSecondary Capture\nseries","","","Same"],["Report Structure","Report will be output in\nthe DICOM and JSON\nfile format which is\nstructured with","Report will be output\nin DICOM file format\nwhich is structured\nwith following","","","Similar.\nThe subject device is\nintended to output the\nmaximal inner border\ndiameter of thoracic cavity"]],"caption_candidate":"EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212624-p9-t0","doc_id":"K212624","page_num":9,"bbox":[53.88,85.56,542.88,731.28],"n_rows":6,"n_cols":4,"columns":["Imaging Modality","Chest X-ray in Digital\nRadiography (DR)","Computed\nTomography\nPulmonary\nAngiography (CTPA)\nimages","Yes, there is a difference.\nDespite two compared\ndevices is present with the\ndifferent imaging modality.\nThe verification &\nvalidation result has shown\nno impact raise in the\nsafety and effectiveness."],"rows":[["Imaging Modality","Chest X-ray in Digital\nRadiography (DR)","Computed\nTomography\nPulmonary\nAngiography (CTPA)\nimages","Yes, there is a difference.\nDespite two compared\ndevices is present with the\ndifferent imaging modality.\nThe verification &\nvalidation result has shown\nno impact raise in the\nsafety and effectiveness."],["Intended Use\nEnvironment","Healthcare institutions\n(Clinics, hospitals,\nhealthcare facilities,\nresidential care facilities\nand long-term care\nservices)","No restrictions","Yes, there is a difference.\nThe usability report can\nverify the different\nenvironment does not raise\nthe impact of safety and\neffectiveness."],["Software device that\noperates on off-the-shelf\nhardware","Yes","Yes","Same"],["Software devices uses\nsoftware algorithms for\nimage","Yes","Yes","Same"],["Diameter Measurement","Yes - Automated","Yes - Automated","Same"],["Storage","Saved in JSON and\nDICOM file format text\nfor DICOM and\nDICOM file format","Saved in PDF and\nDICOM compatible\nformat","They have same DICOM\nformat storage. The\nstorage of subject device in\nJASON format has been\nvalidated through the\nsystem test. There is no\nimpact on safety or\neffectiveness of the subject\ndevice."]],"caption_candidate":"EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p6-t0","doc_id":"K212654","page_num":6,"bbox":[72.26,502.24,539.74,706.56],"n_rows":8,"n_cols":8,"columns":["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],"rows":[["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],["","","Micro C Medical Imaging","","","C Medical Imaging","",""],["","","System, M01","","","System, M01 (K211473)","",""],["Product Code","IZL (Mobile X-Ray\nSystem)","","","IZL (Mobile X-Ray\nSystem)","","","Identical"],["Regulation","21 CFR 892.1720","","","21 CFR 892.1720","","","Identical"],["Classification\nName","Mobile X-Ray System","","","Mobile X-Ray System","","","Identical"],["Classification","Class 2","","","Class 2","","","Identical"],["Indication for\nUse","The Micro C Medical\nImaging System, M01 is a\nhandheld and portable\ngeneral purpose X-ray\nsystem that is indicated\nfor use by","","","The Micro C Medical\nImaging System, M01 is\na handheld and\nportable general\npurpose X-ray system\nthat is indicated for use","","","Identical"]],"caption_candidate":"Table 5-2: Device Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p7-t0","doc_id":"K212654","page_num":7,"bbox":[72.25,72.34,539.75,707.88],"n_rows":11,"n_cols":8,"columns":["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],"rows":[["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],["","","Micro C Medical Imaging","","","C Medical Imaging","",""],["","","System, M01","","","System, M01 (K211473)","",""],["","qualified/trained\nclinicians on adult and\npediatric patients for\ntaking diagnostic static\nand serial radiographic\nexposures of extremities.\nThe device is not\nintended to replace a\nradiographic system that\nhas both variable tube\ncurrent and voltages\n(kVp) in the range that\nmay be required for full\noptimization of image\nquality and radiation\nexposure for different\nexam types.","","","by qualified/trained\nclinicians on adult and\npediatric patients for\ntaking diagnostic static\nand serial radiographic\nexposures of\nextremities.\nThe device is not\nintended to replace a\nradiographic system\nthat has both variable\ntube current and\nvoltages (kVp) in the\nrange that may be\nrequired for full\noptimization of image\nquality and radiation\nexposure for different\nexam types.","","",""],["Contraindicat\nions","● Surgical applications\n● Pediatric patients\n● Fluoroscopy\n● For cardiac and\nvascular applications\n● Mammography\n● Dental applications\n● Contact with non-\nintact skin","","","● Surgical\napplications\n● Pediatric patients\n● Fluoroscopy\n● For cardiac and\nvascular\napplications\n● Mammography\n● Dental applications\n● Contact with non-\nintact skin","","","Identical"],["Age of Device\nUse","Adults and Pediatric","","","Adults and Pediatric","","","Identical"],["Principle of\nOperation","General purpose\ndiagnostic X-ray","","","General purpose\ndiagnostic X-ray","","","Identical"],["Image type\nproduced","Static, serial radiographic\nand photographic images\nfor convenience.","","","Static, serial\nradiographic and\nphotographic images for\nconvenience.","","","Identical"],["Detector","6 x 6” digital detector","","","6 x 6” digital detector","","","Identical"],["Collimator","The removable fixed\ncollimators (referred to\nas pucks)","","","The removable fixed\ncollimators (referred to\nas pucks)","","","Identical"],["Weight","Emitter: 2.86kg (6.3lbs)","","","Emitter: 2.86kg (6.3lbs)","","","Identical"]],"caption_candidate":"510(k) Summary Micro C Medical Imaging, M01","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p8-t0","doc_id":"K212654","page_num":8,"bbox":[72.25,72.34,539.75,697.44],"n_rows":17,"n_cols":8,"columns":["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],"rows":[["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],["","","Micro C Medical Imaging","","","C Medical Imaging","",""],["","","System, M01","","","System, M01 (K211473)","",""],["","Cassette: 6.5kg (14.3lbs)\nControl Unit: 8.6kg\n(19.0lbs)","","","Cassette: 6.5kg (14.3lbs)\nControl Unit: 8.6kg\n(19.0lbs)","","",""],["Dimension/\nSize","Emitter: 9.3”H x 3.5”W x\n8.3”L (excluding SSD\nCone)\nCassette: 15.5”H x\n15.5”W x 2.8”L\nControl Unit: 16.4”H x\n12.9”W x 5.5”L","","","Emitter: 9.3”H x 3.5”W x\n8.3”L (excluding SSD\nCone)\nCassette: 15.5”H x\n15.5”W x 2.8”L\nControl Unit: 16.4”H x\n12.9”W x 5.5”L","","","Identical"],["Triggering\nMechanism","Two stage triggering","","","Two stage triggering","","","Identical"],["Minimum\nSource to\nskin distance\n(SSD)","20 cm SSD Cone ensures\nminimum SSD of 20 cm","","","20 cm SSD Cone ensures\nminimum SSD of 20 cm","","","Identical"],["Source to\nDetector\ndistance","20 - 45 cm","","","20 - 45 cm","","","Identical"],["Light Field","Virtual light field on\nMonitor UI. No projected\nlight field.","","","Virtual light field on\nMonitor UI. No\nprojected light field.","","","Identical"],["Energy\nSource","120 VAC / 60 Hz (no\nrechargeable battery)","","","120 VAC / 60 Hz (no\nrechargeable battery)","","","Identical"],["Exposure\nTime","33 ms - 99 ms","","","33 ms, 66 ms, 99 ms","","","Similar- The overall range is\nidentical. Single AiLARA\nmode allows for ms values\nthroughout the range. Serial\nAiLARA mode has a fixed\noutput of 33 ms."],["mA","1.0 mA fixed","","","1.0 mA fixed","","","Identical"],["kVp","40kVp-60kVp","","","40kVp, 50kVp, and\n60kVp","","","Similar- The overall range is\nidentical. AiLARA allows for\nkVp values throughout the\nrange."],["Scintillator","Cesium Iodide (CsI)","","","Cesium Iodide (CsI)","","","Identical"],["Resolution/\nPixel size","99 μm","","","99 μm","","","Identical"],["DQE @\n0Lp/mm","70%","","","70%","","","Identical"],["MTF @ 1\nLp/mm,\nRQA5","60%","","","60%","","","Identical"]],"caption_candidate":"510(k) Summary Micro C Medical Imaging, M01","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p9-t0","doc_id":"K212654","page_num":9,"bbox":[72.26,72.34,539.74,451.26],"n_rows":8,"n_cols":8,"columns":["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],"rows":[["","","Subject Device:","","","Predicate Device: Micro","","Comparison"],["","","Micro C Medical Imaging","","","C Medical Imaging","",""],["","","System, M01","","","System, M01 (K211473)","",""],["Ingress\nProtection\nRating","IP00","","","IP00","","","Identical"],["Image\nProcessing","User Interface can be\nused to drag, zoom,\nrotate and also adjust\nbrightness, contrast, and\nsharpness.","","","User Interface can be\nused to drag, zoom,\nrotate and also adjust\nbrightness, contrast,\nand sharpness.","","","Identical"],["Connectivity\nOptions","WiFi, Ethernet, Four USB\n2.0 ports","","","WiFi, Ethernet, Four\nUSB 2.0 ports","","","Identical"],["DICOM","Yes- DICOM 3.0\nCompliant","","","Yes- DICOM 3.0\nCompliant","","","Identical"],["Device\nPackage\nContents","● Cassette\n● Control Unit\n● Emitter\n● Collimation Pucks\n● SSD Cone\n● Cassette Power\nCable\n● Cassette Data Cable\n● Control Unit Power\nCable\n● Connector Covers\n● Instructions for Use\n● Case","","","● Cassette\n● Control Unit\n● Emitter\n● Collimation Pucks\n● SSD Cone\n● Cassette Power\nCable\n● Cassette Data Cable\n● Control Unit Power\nCable\n● Connector Covers\n● Instructions for Use\n● Case","","","Identical"]],"caption_candidate":"510(k) Summary Micro C Medical Imaging, M01","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p10-t0","doc_id":"K212654","page_num":10,"bbox":[72.26,145.5,539.74,716.4],"n_rows":5,"n_cols":2,"columns":["Performance Test","Description"],"rows":[["Performance Test","Description"],["AiLARA Algorithm\nVerification","AiLARA’s full development dataset was split into a training set (80% of\nthe data) and a testing set for algorithm verification (20% of the data)\nper Good Machine Learning Practices as outlined in FDA’s Proposed\nRegulatory Framework for Modifications to Artificial\nintelligence/Machine Learning (AI/ML) Based Software as a Medical\nDevice (SaMD)(2019). AiLARA’s model was trained, and at the end of\nevery epoch, the full testing set was sent into the model and was\npredicted to show the model’s performance on unseen data. The model\nwas able to learn the trend of the training dataset (truth). The mean\nsquared error of the training and verification testing datasets were\nplotted, and the trend lines showed that the model had learned the\ngeneral trend present in the data. Both training and testing Mean\nSquared Error and Mean Absolute Error showed that additional training\n(epochs) would have no added benefit."],["Software Verification","Software verification was performed to ensure the updated Micro C\nsoftware met system-level software requirements. Software outputs\nmet the expected result in all cases, with no anomalies found."],["Image Quality Validation\nStudy","An image quality study validation dataset was collected after the\nAiLARA algorithm was frozen, finalized, and transferred to the Micro C\ndevice. This validation set was completely independent of the algorithm\ntraining and verification testing set. The emitter can move freely in\nspace (not attached to the detector), therefore the validation images\nwere collected with independent inputs that the algorithm had not\nseen previously. The independent inputs were achieved by taking\nimages of phantoms at different emitter orientations and angles\n(geometries). The validation dataset included images taken from ankle,\nelbow, hand, foot, knee, toe, and wrist phantoms; each phantom was\ncaptured at multiple distinct SIDs that spanned the full device SID range\nof 20 cm to 45 cm. Additionally, each phantom view/SID combination\nwas captured at multiple orientations. Once the validation images were\ncollected, the images were reviewed and rated by board certified\nradiologists and an orthopedic surgeon. All images were determined to\nbe diagnostically and clinically relevant."],["Radiation Dose Testing","AiLARA technique and dose evaluation testing was performed to\nevaluate AiLARA mode’s radiation outputs as compared to diagnostic\nreference levels from literature, to ensure an acceptable amount of\nradiation was delivered. Additionally, AiLARA’s dose outputs from the\nauto-selected techniques were compared to the predicate device’s\nmanual mode dose outputs that result from the techniques\nrecommended in the Instructions for Use. Results showed that all\nAiLARA dose values were below the established Diagnostic Reference"]],"caption_candidate":"Table 5-3: Non-Clinical Performance Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212654-p11-t0","doc_id":"K212654","page_num":11,"bbox":[72.24,72.24,539.76,409.44],"n_rows":3,"n_cols":2,"columns":["","Levels (DRLs) and there was no statistical difference between AiLARA\nand Manual mode calculated entrance skin exposure doses."],"rows":[["","Levels (DRLs) and there was no statistical difference between AiLARA\nand Manual mode calculated entrance skin exposure doses."],["Radiation Dose Testing on\nSmall/Pediatric Anatomies","Testing was conducted to evaluate AiLARA’s radiation outputs for small\nsize extremity anatomies (representing low thicknesses seen for small\npatients, especially pediatrics) as compared to diagnostic reference\nlevels from literature to ensure an acceptable amount of radiation was\ndelivered. This study also included recording dose outputs at different\nSource to Image Distance (SID) and emitter orientation configurations\nto ensure doses are consistently acceptable at various emitter\norientations and small anatomy thicknesses. Results showed that all\nAiLARA dose values were below the established Diagnostic Reference\nLevels (DRLs) for small size anatomies, and doses were similar among\ncaptures for each orientation within the same target thickness and SID\ncategory."],["Usability Evaluation","A usability evaluation was performed for the addition of the AiLARA\nmodes for single radiography and serial radiography (DDR) imaging to\nensure the Micro C Medical Imaging System, M01 has acceptable use-\nrelated risks and effectiveness during use. The study included 15\nparticipants who were licensed to perform x-ray procedures and had\nprevious experience operating x-ray devices. All the identified critical\nuse tasks were completed with a passing result by 100% of participants.\nThe usability evaluation was performed in accordance with IEC 62366-\n1:2020, Medical devices - Part 1: Application of usability engineering to\nmedical devices and Guidance for Industry and FDA Staff – Applying\nHuman Factors and Usability Engineering to Medical Devices (2016)."]],"caption_candidate":"510(k) Summary Micro C Medical Imaging, M01","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212690-p4-t0","doc_id":"K212690","page_num":4,"bbox":[108.24,336.48,522.72,496.08],"n_rows":6,"n_cols":2,"columns":["Name of Device:","qXR-BT"],"rows":[["Name of Device:","qXR-BT"],["Common or Usual Name:","Automated Radiological Image Processing Software"],["Classification Name:","Medical image management and processing system"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2050"],["Product Code:","QIH"]],"caption_candidate":"2 DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212690-p4-t1","doc_id":"K212690","page_num":4,"bbox":[108.24,548.64,522.72,628.56],"n_rows":3,"n_cols":2,"columns":["Name of Device:","ClearRead+Confirm Image Processing System"],"rows":[["Name of Device:","ClearRead+Confirm Image Processing System"],["Manufacturer:","Riverain Technologies LLC"],["510(k) Number:","K123526"]],"caption_candidate":"3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212690-p6-t0","doc_id":"K212690","page_num":6,"bbox":[72.01,177.72,503.99,750.24],"n_rows":14,"n_cols":5,"columns":["","","Predicate Device","","Subject Device\nqXR-BT"],"rows":[["","","Predicate Device","","Subject Device\nqXR-BT"],["","","ClearRead+Confirm","",""],["","","(K123526)","",""],["","","","",""],["Device Name","ClearRead+Confirm","","","qXR-BT"],["510(k) Number","K123526","","","K212690"],["Regulation","21 CFR 892.2050","","","21 CFR 892.2050"],["Regulation Description","Medical image management\nand processing system\nFormerly: Picture archiving\nand communications system","","","Medical image management and\nprocessing system"],["Product Code","LLZ","","","QIH"],["Device type","Radiological Image\nProcessing System","","","Automated Radiological Image\nProcessing Software"],["Manufacturer","Riverain Technologies","","","Qure.ai Technologies"],["Intended use / Indications\nfor Use","ClearRead+Confirm is\nintended to generate an\nenhanced, secondary digital\nradiographic image of the\nchest to facilitate\nconfirmation of line/tubes.\nThe enhanced AP or PA\nimage of the chest provides\nimproved visibility of lines\nand tubes. The ClearRead\n+Confirm image provides\nadjunctive information and\nis not a substitute for the\noriginal PA/AP image. This\ndevice is intended to be used\nby trained professionals,\nsuch as physicians,\nradiologists, and technicians,\non patients with lines and\ntubes and is not intended to\nbe used on pediatric\npatients.","","","The qXR-BT device is intended to\ngenerate a secondary digital chest X-\nray image that facilitates\nconfirmation of the position of a\nbreathing tube and an anatomical\nlandmark on adult chest X-rays. This\ndevice is intended for use by licensed\nphysicians who are trained in the\nevaluation of breathing tube\nplacement on chest X-rays. The qXR-\nBT image provides adjunctive\ninformation and is not a substitute\nfor the original PA/AP image."],["Modality","Digital chest radiograph","","","Digital chest radiograph"],["Input format","DICOM","","","DICOM"]],"caption_candidate":"Table 1: Comparison between qXR-BT and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212690-p7-t0","doc_id":"K212690","page_num":7,"bbox":[72.03,72.36,503.97,494.4],"n_rows":10,"n_cols":7,"columns":["","","","Predicate Device","","Subject Device\nqXR-BT",""],"rows":[["","","","Predicate Device","","Subject Device\nqXR-BT",""],["","","","ClearRead+Confirm","","",""],["","","","(K123526)","","",""],["","","","","","",""],["Output Format","","Secondary digital chest X-ray\nimage","","","Secondary digital chest X-ray image\nand other Multiple electronic reports\nwith localization information of\nsegmented structures",""],["Intended User","","Physicians, radiologists and\ntechnicians","","","Physicians and radiologists",""],["Hardware","","No additional hardware;\nstandalone software device\nthat integrates with PACS\nthrough DICOM protocols","","","qXR-BT is standalone software\ndeployed on-premise or on the\ncloud, that integrates with PACS or\nother hardware or software imaging\nplatforms, including digital\nradiographic processing systems\nthrough DICOM protocols",""],["","Comparison of Differences between qXR-BT and the predicate device","","","","",""],["Types of lines and tubes","","Various medically inserted\ntubes, lines, tubes and wires","","","Medically inserted breathing tubes\n(tracheal tubes) only",""],["Internal algorithms used\nfor image processing and\nthe mechanism by which\nthe output is displayed to\nthe clinician","","ClearRead+Confirm uses a\nbone suppression\nmechanism with overall\nimage enhancements to\nimprove the visibility of lines\nand tubes and provides no\nboxes or markings to the\nuser.","","","qXR-BT uses pre-trained\nconvolutional neural networks to\nprocess the images, and the device\nhighlights the tip of the tube and the\ncarina using markings on the\nsecondary image.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212690-p8-t0","doc_id":"K212690","page_num":8,"bbox":[72.11,138.72,495.01,389.34],"n_rows":9,"n_cols":16,"columns":["Target\nStructure\n(Number of\nscans)","","","Metric","","","Mean\n(Standard\nDeviation)","Median (10th -\n90th percentile)","","","Mean (95% CI)","","","Success Criteria","",""],"rows":[["Target\nStructure\n(Number of\nscans)","","","Metric","","","Mean\n(Standard\nDeviation)","Median (10th -\n90th percentile)","","","Mean (95% CI)","","","Success Criteria","",""],["Carina (162)","","","","Absolute","","2.15 (1.25)","","1.86 (0.63 -","","","2.15 (1.96 –","","","Upper bound of",""],["","","","","Distance","","","","4.05)","","","2.35)","","","95% CI ≤ 3mm",""],["Tip of\nBreathing\nTube (162)","","","Absolute\nDistance","","","1.97 (1.09)","1.8 (0.7 - 3.64)","","","1.97 (1.80 –\n2.13)","","","Upper bound of\n95% CI ≤ 3mm","",""],["","Distance","","Absolute\nError","","","1.98 (1.41)","1.64 (0.27 -\n4.12)","","","1.98 (1.76 –\n2.20)","","","Upper bound of\n95% CI ≤ 6mm","",""],["","between tip","","","","","","","","","","","","","",""],["","of breathing","","","","","","","","","","","","","",""],["","tube and","","","","","","","","","","","","","",""],["","carina (162)","","","","","","","","","","","","","",""]],"caption_candidate":"Table 2: Overall Results of Accuracy Testing in mm","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212704-p7-t0","doc_id":"K212704","page_num":7,"bbox":[68.74,86.98,540.1,695.09],"n_rows":2,"n_cols":2,"columns":["Philips EPIQ\nDiagnostic Ultrasound\nSystem","The intended use of Philips EPIQ series diagnostic ultrasound systems is\ndiagnostic ultrasound imaging and fluid flow analysis of the human body,\nwith the following indications for use:\nAbdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric,\nGynecological, Intra-cardiac Echo, Intra-luminal, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal (Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ\n(Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.\nThe clinical environments where Philips EPIQ diagnostic ultrasound systems\ncan be used include clinics, hospitals, and clinical point-of-care for diagnosis\nof patients.\nWhen integrated with Philips EchoNavigator, the systems can assist the\ninterventionalist and surgeon with image guidance during treatment of\ncardiovascular disease in which the procedure uses both live X-ray and live\necho guidance.\nThe systems are intended to be installed, used, and operated only in\naccordance with the safety procedures and operating instructions given in the\nproduct user information. Systems are to be operated only by appropriately\ntrained healthcare professionals for the purposes for which they were\ndesigned. However, nothing stated in the user information reduces your\nresponsibility for sound clinical judgement and best clinical procedure."],"rows":[["Philips EPIQ\nDiagnostic Ultrasound\nSystem","The intended use of Philips EPIQ series diagnostic ultrasound systems is\ndiagnostic ultrasound imaging and fluid flow analysis of the human body,\nwith the following indications for use:\nAbdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric,\nGynecological, Intra-cardiac Echo, Intra-luminal, Intraoperative (Vascular),\nIntraoperative (Cardiac), Musculoskeletal (Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ\n(Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.\nThe clinical environments where Philips EPIQ diagnostic ultrasound systems\ncan be used include clinics, hospitals, and clinical point-of-care for diagnosis\nof patients.\nWhen integrated with Philips EchoNavigator, the systems can assist the\ninterventionalist and surgeon with image guidance during treatment of\ncardiovascular disease in which the procedure uses both live X-ray and live\necho guidance.\nThe systems are intended to be installed, used, and operated only in\naccordance with the safety procedures and operating instructions given in the\nproduct user information. Systems are to be operated only by appropriately\ntrained healthcare professionals for the purposes for which they were\ndesigned. However, nothing stated in the user information reduces your\nresponsibility for sound clinical judgement and best clinical procedure."],["Philips Affiniti\nDiagnostic Ultrasound\nSystem","The intended use of the Affiniti Series Diagnostic Ultrasound Systems is\ndiagnostic ultrasound imaging and fluid flow analysis of the human body\nwith the following Indications for Use:\nAbdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral\nVascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular), Intraoperative (Cardiac),\nMusculoskeletal (Conventional), Musculoskeletal (Superficial), Other:\nUrology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,\nTesticle), Transesophageal (Cardiac), Transrectal, Transvaginal, Lung.\nThe clinical environments where the Affiniti Diagnostic Ultrasound Systems\ncan be used include Clinics, Hospitals, and clinical point-of-care for\ndiagnosis of patients.\nThe systems are intended to be installed, used, and operated only in\naccordance with the safety procedures and operating instructions given in the\nproduct user information. Systems are to be operated only by appropriately\ntrained healthcare professionals for the purposes for which they were\ndesigned. However, nothing stated in the user information reduces your\nresponsibility for sound clinical judgment and best clinical procedure."]],"caption_candidate":"Liver Fat Quantification Module","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212758-p4-t0","doc_id":"K212758","page_num":4,"bbox":[72.26,450.79,539.86,550.42],"n_rows":6,"n_cols":2,"columns":["Device Proprietary Name:","Autoplaque 3.0"],"rows":[["Device Proprietary Name:","Autoplaque 3.0"],["Common or Usual Name:","Image Processing System, Radiological"],["Classification Name:","Automated Radiological Image Processing Software\nRadiological Imaging Processing System"],["Regulation Number:","21 CFR § 892.2050"],["Product Code:","QIH, LLZ"],["Device Classification","II"]],"caption_candidate":"III. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212758-p6-t0","doc_id":"K212758","page_num":6,"bbox":[72.26,371.11,540.1,715.2],"n_rows":15,"n_cols":3,"columns":["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],"rows":[["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],["Computer operating system","Windows OS\nMac OS","Windows OS only"],["Stand-alone software","Yes","No, ORS Visual add-on"],["DICOM compliance","DICOM 3.1","Same"],["2D Imaging","Review of coronary vessels in 2D\nMPR, curved MPR, and straightened\nview.","Same"],["2D Measurement","2D measurement tools of vessel\ndiameter and contour","Same"],["3D Imaging","Review of structures in 3D","Same"],["Maximum intensity\nprojection (MIP)","MIP with interactive control","Same"],["Multiplanar reformatting\n(MPR)","MPR with oblique slicing and\nvariable slab thickness","Same"],["Quantitative Measurements","",""],["NCP volume: non-calcified\nplaque volume","Yes","Same"],["CP volume: calcified plaque\nvolume","Yes","Same"],["LD-NCP volume: low-\ndensity noncalcified plaque\nvolume","Yes","Same"],["Total plaque volume","Yes","Same"],["Vessel volume","Yes","Same"]],"caption_candidate":"devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212758-p7-t0","doc_id":"K212758","page_num":7,"bbox":[72.26,72.26,540.1,705.36],"n_rows":15,"n_cols":3,"columns":["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],"rows":[["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],["NCP burden: noncalcified\nplaque volume/analyzed\nvessel volume","Yes","Same"],["LD-NCP burden: low-\ndensity noncalcified plaque\nvolume/analyzed vessel\nvolume","Yes","Same"],["CP burden: calcified plaque\nvolume/analyzed vessel\nvolume","Yes","Same"],["Total plaque burden: total\nplaque volume/analyzed\nvessel volume","Yes","Same"],["Plaque composition NCP:\nNoncalcified plaque\ncomposition (NCP volume\n/total plaque volume)","Yes","Same"],["Plaque composition CP:\nCalcified plaque composition\n(CP volume/total plaque\nvolume)","Yes","Same"],["Plaque composition LD-\nNCP: low-density\nnoncalcified plaque\ncomposition (LD-NCP\nvolume/ NCP volume)","Yes","Same"],["Diameter stenosis: maximal\ndiameter stenosis, with\nrespect to proximal and\ndistal references","Yes","Same"],["QCAD: Maximal diameter\nstenosis, with respect to\nproximal and distal\nreferences","Yes","Same"],["Remodeling index: ratio of\nmaximum vessel\narea/proximal and distal\nreferences","Yes","Same"],["Area stenosis: maximum\narea stenosis, with respect to\nproximal and distal\nreferences","Yes","Same"],["Plaque length: diseased\nvessel length","Yes","Same"],["Contrast density difference:\nmaximum difference in\ncontrast density over lesion\nwith respect to proximal","Yes","Same"],["MLD: minimal luminal\ndimeter over lesion","Yes","Same"]],"caption_candidate":"K212758","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212758-p8-t0","doc_id":"K212758","page_num":8,"bbox":[72.26,72.26,540.1,287.81],"n_rows":5,"n_cols":3,"columns":["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],"rows":[["Parameter","Subject Device: Autoplaque 3.0\n(K212758)","Predicate Device: Autoplaque add-on\nORS Visual\n(K122429)"],["MLA: minimum luminal\narea over lesion","Yes","Same"],["Vessel profile: Area,\nmaximum diameter,\nminimum diameter measured\nfrom selected vessel cross\nsection","Yes","Same"],["Lumen profile: Area,\nmaximum diameter,\nminimum diameter measured\nfrom selected lumen cross\nsection","Yes","Same"],["Vessel, plaque, and lumen\nsegmentation","Deep learning based, validated with\nground truth by clinician expert\nreaders, with full option to edit.","Algorithm based, validated with ground\ntruth by clinician expert readers, with full\noption to edit."]],"caption_candidate":"K212758","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212783-p8-t0","doc_id":"K212783","page_num":8,"bbox":[90.04,96.0,546.53,509.28],"n_rows":12,"n_cols":4,"columns":["Technological","Transpara","ProstatID","Rationale of no Change to"],"rows":[["Technological","Transpara","ProstatID","Rationale of no Change to"],["","","","Safety and"],["Characteristic","","",""],["","","","Effectiveness"],["","","",""],["Device is utilized to assist radiologists in\nassessment of breast abnormalities using full-\nfield digital mammography exams and digital\nbreast tomosynthesis exam.","Yes","No","ProstatID is utilized to assist\nradiologists in assessment of\nprostate abnormalities using MR\nimage data. Safety and\neffectiveness are supported\nthrough performance assessments."],["Software automatically registers images.","Yes","Yes","Same"],["Detects and marks locations suspicious of\nlesions.","Yes","Yes","Same with different marking"],["Decision Support by region scores with higher\nscores indicating a higher level of suspicion","Yes","Yes","Similar with different scale"],["Features are synthesized by an artificial\nintelligence algorithm into a single exam\nscore.","Yes","Yes","Same."],["Device Neural Net was trained on a database\nof reference normal tissues and abnormalities\nwith known ground truth.","Yes","No","ProstatID was trained on a database\nwith reference normal tissues and\nabnormalities with known ground\ntruths; however, the detection\nalgorithm uses Random Forest vs.\nNeural Nets"],["May be used as an image viewer.","Yes","No","ProstatID does not include a\nstandalone graphical user interface.\nRather, ProstatID outputs are in\nDICOM format and may be viewed on\nDICOM- compliant image viewers."]],"caption_candidate":"Table 1: Technical comparison between the predicate device and ProstatID","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212783-p11-t0","doc_id":"K212783","page_num":11,"bbox":[124.01,448.8,496.99,521.64],"n_rows":5,"n_cols":4,"columns":["Modality-Specific AUC","AUC","95% CI","p-value"],"rows":[["Modality-Specific AUC","AUC","95% CI","p-value"],["","","",""],["AUC (without CAD)\n1st Read","0.629","[0.549, 0.711]","-"],["AUC (with CAD)\n2nd Read","0.671","[0.590, 0.752]","-"],["AUC = AUC - AUC\n2nd Read 1st Read","+0.042","[0.005, 0.080]","0.0291"]],"caption_candidate":"Table 2: MRMC estimate of summary modality-specific trapezoidal area under the ROC curve (AUC).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212915-p4-t0","doc_id":"K212915","page_num":4,"bbox":[71.34,159.86,524.24,364.49],"n_rows":14,"n_cols":2,"columns":["","C/O Terkko Health Hub"],"rows":[["","C/O Terkko Health Hub"],["","Haartmaninkatu 4"],["","00290 Helsinki"],["","Finland"],["","Tel: +358 (0) 40 5489 229"],["","info@mvision.ai"],["",""],["Primary Contact Person Kalpana Jha",""],["","Quality and Compliance Manager"],["","kalpana.jha@mvision.ai"],["","Tel: +358 44 9214 354"],["",""],["Subject Device",""],["",""]],"caption_candidate":"Name and Address MVision AI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212915-p5-t0","doc_id":"K212915","page_num":5,"bbox":[70.73,72.0,532.14,198.44],"n_rows":9,"n_cols":3,"columns":["and approval workflow. The segmentations are produced by pre-trained and locked models that are","",""],"rows":[["and approval workflow. The segmentations are produced by pre-trained and locked models that are","",""],["based on deep artificial neural networks. To take the device into use, the user does not have to provide","",""],["any contouring atlases. The models have been trained with the order of hundreds of scans, depending","",""],["on the ROI in question. The MVision AI Segmentation device creates initial contours of pre-defined","",""],["structures of common anatomical sites, i.e. Head and Neck, Brain, Breast, Lung and Abdomen, Male","",""],["Pelvis, and Female Pelvis. Supported anatomical sites and ROI listing of the organs for which the device","",""],["creates initial contours for, are listed below:","",""],["","",""],["Lung and Abdomen","Brain","Breast"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K212915-p6-t0","doc_id":"K212915","page_num":6,"bbox":[72.74,75.89,518.98,769.06],"n_rows":93,"n_cols":3,"columns":["Female Pelvis","Head and Neck","Male Pelvis"],"rows":[["Female Pelvis","Head and Neck","Male Pelvis"],["","",""],["Bag_Bowel","A_Carotid_R/L","A_Aorta"],["","",""],["Bladder","Arytenoid_R/L","Bag_Bowel"],["","",""],["Body","Body","Bladder"],["","",""],["Bone_Pelvic","Bone_Mandible","Body"],["","",""],["Bowel_Large","BrachialPlex_R/L","Bone_Pelvic"],["","",""],["Bowel_Small","Brain","Bowel_Large"],["","",""],["Femur_R/L","Brainstem","Bowel_Small"],["","",""],["Kidney_R/L","Buccal_Mucosa_R/L","Femur_R/L"],["","",""],["L4_VB","Cavity_Oral","Kidney_R/L"],["","",""],["L5_VB","Cochlea_R/L","L4_VB"],["","",""],["Rectum","Cricophar_inlet","L5_VB"],["","",""],["Sacrum","Esophagus_S","LN_Pivotal"],["","",""],["SpinalCanal","Eye_Ant_R/L","LN_RTOG"],["UteroCervix","Eye_Post_R/L","Markers"],["","",""],["","Eye_R/L","Musc_Coccygeus_R/L"],["","",""],["","Glnd_Lacrimal_R/L","Musc_Iliacus_R/L"],["","",""],["","Glnd_Submand_R/L","Musc_Obt_Int_R/L"],["","",""],["","Glnd_Thyroid","Musc_Pirifor_R/L"],["","",""],["","Glottis","Musc_Psoas_Maj_R/L"],["","",""],["","LN_Neck_IA","PenileBulb"],["","",""],["","LN_Neck_IB_R/L","Prostate"],["","",""],["","LN_Neck_III_R/L","Rectum"],["","",""],["","LN_Neck_II_R/L","Sacrum"],["","",""],["","LN_Neck_IVA_R/L","SeminalVes"],["","LN_Neck_IVB_R/L","V_Venacava_I"],["","",""],["","LN_Neck_IX_R/L","Vessels_Long_R/L"],["","",""],["","LN_Neck_VC_R/L","Vessels_R/L"],["","",""],["","LN_Neck_VIA",""],["","",""],["","LN_Neck_VIB",""],["","",""],["","LN_Neck_VIIA_R/L",""],["","",""],["","LN_Neck_VIIB_R/L",""],["","",""],["","LN_Neck_V_R/L",""],["","",""],["","LN_Neck_XA_R/L",""],["","",""],["","LN_Neck_XB_R/L",""],["","",""],["","Larynx_SG",""],["","Lens_R/L",""],["","",""],["","Lips",""],["","",""],["","Lung_R/L",""],["","",""],["","Musc_Constrict",""],["","",""],["","OpticChiasm",""],["","",""],["","OpticChiasm_cnv",""],["","",""],["","OpticNrv_R/L",""],["","",""],["","OpticNrv_cnv_R/L",""],["","",""],["","Parotid_R/L",""],["","",""],["","Pituitary",""],["","",""],["","SpinalCanal",""],["","SpinalCord",""],["","",""],["","Trachea",""]],"caption_candidate":"Female Pelvis Head and Neck Male Pelvis","well_formed":true,"extraction_settings":"text"}
{"table_id":"K212960-p4-t0","doc_id":"K212960","page_num":4,"bbox":[71.99,159.1,391.37,599.75],"n_rows":33,"n_cols":3,"columns":["1.","SUBMITTER’S NAME",""],"rows":[["1.","SUBMITTER’S NAME",""],["","Fumiaki Teshima",""],["","Sr. Manager, Quality Assurance Dept.",""],["","Quality, Safety and Regulation Center",""],["","Canon Medical Systems Corporation",""],["","1385 Shimoishigami",""],["","Otawara‐shi, Tochigi‐ken, Japan 324‐8550",""],["","",""],["2.","ESTABLISHMENT REGISTRATION",""],["","9614698",""],["","",""],["3.","OFFICIAL CORRESPONDENT/CONTACT PERSON",""],["","Yoshiaki Cook",""],["","Manager, Regulatory Affairs",""],["","Canon Medical Systems USA, Inc.",""],["","2441 Michelle Drive",""],["","Tustin, CA 92780",""],["","ycook@us.medical.canon",""],["","",""],["4.","DATE PREPARED",""],["","Sept. 14, 2021",""],["","",""],["5.","DEVICE NAME/TRADE NAME",""],["","Aplio a550, Aplio a450, and Aplio a, Diagnostic Ultrasound","System,"],["","",""],["6.","COMMON NAME",""],["","System, Diagnostic Ultrasound",""],["","",""],["7.","DEVICE CLASSIFICATION",""],["","Class II",""],["","Ultrasonic Pulsed Doppler Imaging System – Product Code:","90‐IYN"],["","Ultrasonic Pulsed Echo Imaging System – Product Code: 90","‐IYO [pe"],["","Diagnostic Ultrasonic Transducer – Product Code: 90‐ITX [p","er 21 C"]],"caption_candidate":"1. SUBMITTER’S NAME","well_formed":true,"extraction_settings":"text"}
{"table_id":"K212960-p5-t0","doc_id":"K212960","page_num":5,"bbox":[106.14,112.5,544.38,167.28],"n_rows":2,"n_cols":4,"columns":["Product","Marketed by","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","510(k) Number","Clearance Date"],["Aplio a550, Aplio a450 and\nAplio a, Diagnostic Ultrasound\nSystem, Software V5.1","Canon Medical\nSystems USA, Inc.","K202364","October 15, 2020"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213096-p8-t0","doc_id":"K213096","page_num":8,"bbox":[72.05,311.56,532.64,690.08],"n_rows":11,"n_cols":7,"columns":["Subject Device","","Primary Predicate Device","Secondary Predicate Device","","Comparison",""],"rows":[["Subject Device","","Primary Predicate Device","Secondary Predicate Device","","Comparison",""],["AI-Rad Companion\n(Pulmonary) VA13A\n(K213096)","","AI-Rad Companion\n(Pulmonary) VA10A\n(K183271)","syngo.CT Extended\nFunctionality VB51\n(K203699)","","",""],["Segmentation of Lung","","","","","",""],["Creation of a lung\nsegmentation mask by\ncombining the segmentation\nmasks of 5 lung lobes.","","Creation of a lung\nsegmentation mask by\ncombining the segmentation\nmasks of 5 lung lobes.","Creation of a lung\nsegmentation mask by\ncombining the segmentation\nmasks of 5 lung lobes.","","The same algorithm as cleared with\nthe predicate devices is used.\nAdditional training data was added\nas compared to the primary predicate\nfor the Pulmonary Density Feature.\nThis same data and method were\nused with the secondary predicate\ndevice (K203699).",""],["","Segmentation of Lobes","","","","",""],["Computation of segmentation\nmasks of the five lung lobes\n(right upper (RUL), right\nmiddle (RML), right lower\n(RLL), left upper (LUL) and left\nlower (LLL) lobe) for a given\nCT data set of the chest.","","Computation of segmentation\nmasks of the five lung lobes\n(right upper (RUL), right\nmiddle (RML), right lower\n(RLL), left upper (LUL) and left\nlower (LLL) lobe) for a given\nCT data set of the chest.","Computation of segmentation\nmasks of the five lung lobes\n(right upper (RUL), right\nmiddle (RML), right lower\n(RLL), left upper (LUL) and left\nlower (LLL) lobe) for a given\nCT data set of the chest.","","",""],["","Opacity Detection","","","","",""],["AI-based identification of\nareas with elevated\nHounsfield values. Threshold-\nbased identification of\nhighest elevated Hounsfield\nvalues inside these elevated\nregions, by a predefined\nthreshold of -200 HU.","","N/A","AI-based identification of\nareas with elevated\nHounsfield values. Threshold-\nbased identification of\nhighest elevated Hounsfield\nvalues inside these elevated\nregions, by a predefined\nthreshold of -200 HU.","","The Opacity Detection is the same as\nthe secondary predicate devices\nsyngo.CT Extended Functionality\n(K203699).",""],["","Measurement Results","","","","",""],["Lung lesion, lung\nparenchyma, and pulmonary\ndensity measurements.","","Lung lesion, and lung\nparenchyma measurements.","Pulmonary density\nmeasurements.","","Extended with Pulmonary Density\nresults, as cleared in the secondary\npredicate device (syngo.CT Extended\nFunctionality (K203699).",""],["","Parenchyma Evaluation","","","","",""]],"caption_candidate":"predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213096-p9-t0","doc_id":"K213096","page_num":9,"bbox":[72.04,73.36,532.66,573.72],"n_rows":10,"n_cols":7,"columns":["Subject Device","","Primary Predicate Device","Secondary Predicate Device","","Comparison",""],"rows":[["Subject Device","","Primary Predicate Device","Secondary Predicate Device","","Comparison",""],["AI-Rad Companion\n(Pulmonary) VA13A\n(K213096)","","AI-Rad Companion\n(Pulmonary) VA10A\n(K183271)","syngo.CT Extended\nFunctionality VB51\n(K203699)","","",""],["The parenchyma evaluation\nuses the lobe mask, counts all\nvoxels per lobe, counts image\nvoxels below -950 HU, and\ncalculates the percentages of\nthese voxels relative to the\ntotal number of voxels.\nAdditionally, it sums the\nindividual lobe results and\ncalculates the percentage for\nthe complete lung.","","The parenchyma evaluation\nuses the lobe mask, counts all\nvoxels per lobe, counts image\nvoxels below -950 HU, and\ncalculates the percentages of\nthese voxels relative to the\ntotal number of voxels.\nAdditionally, it sums the\nindividual lobe results and\ncalculates the percentage for\nthe complete lung.","N/A","","Same as the primary predicate device\nAI-Rad Companion (Pulmonary)\nVA10A (K183271).",""],["","Parenchyma Ranges","","","","",""],["The percentages are likewise\ndedicated to the 4 ranges.\nName of ranges and their\nranges are configurable by\nthe user.","","The percentages are likewise\ndedicated to the 4 ranges.\nName of ranges and their\nranges are configurable by\nthe user.","N/A","","",""],["","Visualization of Segmentation and Parenchyma Results","","","","",""],["Color overlay of MPR and VRT\nwith evaluation results.","","Color overlay of MPR and VRT\nwith evaluation results.","N/A","","",""],["","LungCAD Interface","","","","",""],["The external device syngo.CT\nLungCAD is connected.","","The external device syngo.CT\nLungCAD is connected.","The external device syngo.CT\nLungCAD is connected.","","Same as both predicate devices.",""],["Based on the positions\nprovided via the LungCAD\nInterface, a segmentation of\nsuspicious lung areas is\nstarted. Within the derived\ncontours the maximum\ndiameter within one slice, the\n3-dimensional diameter, and\nthe volume are determined.\nThe lesion is dedicated to a\nlung lobe.\nAdditionally, the maximum\northogonal 2D diameter is\nmeasured and the mean from\nmaximum 2D diameter and\nmaximum orthogonal 2D\ndiameter is shown.","","Based on the positions\nprovided via the LungCAD\nInterface, a segmentation of\nsuspicious lung areas is\nstarted. Within the derived\ncontours the maximum\ndiameter within one slice, the\n3-dimensional diameter, and\nthe volume are determined.\nThe lesion is dedicated to a\nlung lobe.","Based on positions provided\nby the user, a segmentation\nof suspicious lung areas is\nstarted. Within the derived\ncontours the maximum\ndiameter within one slice, the\n3-dimensional diameter, and\nthe volume are determined.\nThe lesion is dedicated to a\nlung lobe.\nAdditionally, the maximum\northogonal 2D diameter is\nmeasured and the mean from\nmaximum 2D diameter and\nmaximum orthogonal 2D\ndiameter is shown.","","The Bi-directional lesion diameter is\nthe same as the secondary predicate\ndevice syngo.CT Extended\nFunctionality VB51 (K203699).",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213096-p11-t0","doc_id":"K213096","page_num":11,"bbox":[72.02,190.53,525.58,363.48],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)","01/14/2019","AAMI, ANSI, IEC","",""],["5-125","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Third\nEdition 2019-12","12/23/2019","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"covering electrical and mechanical safety listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213155-p7-t0","doc_id":"K213155","page_num":7,"bbox":[93.6,147.72,537.84,716.76],"n_rows":15,"n_cols":4,"columns":["ITEM","Proposed Device","Predicate Device\nK191928","Remark"],"rows":[["ITEM","Proposed Device","Predicate Device\nK191928","Remark"],["Product Code","QKB","QKB","Same"],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050","Same"],["Class","II","II","Same"],["Indication for Use","It is used by radiation oncology\ndepartment to segment\n(non-contrast) CT images, to\ngenerate needed information for\ntreatment planning, treatment\nevaluation and treatment\nadaptation","It is used by radiation oncology\ndepartment to register\nmultimodality images and segment\n(non-contrast) CT images, to\ngenerate needed information for\ntreatment planning, treatment\nevaluation and treatment\nadaptation.","Different"],["Label/labeling","Conform with 21CFR Part 801","Conform with 21CFR Part 801","Same"],["Operation System","Windows","Windows","Same"],["Segmentation Features","","",""],["Algorithm","Deep Learning","Deep Learning","Same"],["Segmentation of\nOrgan at Risk in the\nAnatomic Regions","Head & Neck, Thorax, Abdomen\n&Pelvis","Head & Neck, Thorax, Abdomen\n&Pelvis","Same"],["Compatible\nModality","Non-Contrast CT","Non-Contrast CT","Same"],["Compatible Scanner\nModels","No Limitation on scanner model,\nDICOM 3.0 compliance required","No Limitation on scanner model,\nDICOM 3.0 compliance required","Same"],["Compatible\nTreatment Planning\nSystem","No limitation on TPS model,\nDICOM 3.0 compliance required","No limitation on TPS model,\nDICOM 3.0 compliance required","Same"],["Target Population","Adults Only (greater than 21 years\nof age)","Any patient type for whom\nRelevant multimodality images\nand segment (noncontrast) CT\nimages are available.","Different"],["Clinical condition\nthe device is\nintended to\ndiagnose, treat or\nmanage","Limited to patients previously\nselected for Radiation Therapy.\nHowever, RT-Mind-AI can be used\nfor treatment evaluation and\ntreatment adaptation.","Limited to patients previously\nselected for Radiation Therapy.\nHowever, AccuContour can be\nused for treatment evaluation and\ntreatment adaptation.","Same"]],"caption_candidate":"Table 1 Comparison of Technology Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213155-p8-t0","doc_id":"K213155","page_num":8,"bbox":[93.6,85.32,537.84,479.76],"n_rows":9,"n_cols":4,"columns":["Software\nArchitecture","Server based","Cloud and/or Server based","Different"],"rows":[["Software\nArchitecture","Server based","Cloud and/or Server based","Different"],["Deployment\nFeature","Server","Cloud Deployment and Server","Different"],["Automated\nworkflow","RT-Mind-AI automatically\nprocesses input image data","AccuContour automatically\nprocesses input image data","Same"],["Contour\nvisualization and\nediting feature","RT-Mind-AI provides basic result\npreview of automatic segmentation\nresults. Manual segment is\npossible.","AccuContour provides basic result\npreview of automatic segmentation\nresults. Manual segment is\npossible.","Same"],["Segmentation\nPerformance","The segmentation performance\nwas validated using datasets from\nthe USA using three major vendors\n(GE, Siemens and Phillips). The\nsegmentation accuracy is evaluated\nusing DICE coefficient.","The segmentation performance\nwas validated using datasets from\nChina and the USA using three\nmajor vendors (GE, Siemens and\nPhillips). The segmentation\naccuracy is evaluated using DICE\ncoefficient.","Different"],["User Interface –\nResults Preview\n(Confirmation)","Basic result preview of automatic\nsegmentation results. Manual\nsegment is possible.","Basic result preview of automatic\nsegmentation results. Manual\nsegment is possible.","Same"],["User Interface\nConfiguration","Configuration menu","Configuration menu","Same"],["Human Factors","Design to be used by trained\nclinicians.","Design to be used by trained\nclinicians.","Same"],["Contraindications","None","None","Same"]],"caption_candidate":"K213155","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213165-p12-t0","doc_id":"K213165","page_num":12,"bbox":[78.14,76.48,683.86,538.45],"n_rows":6,"n_cols":4,"columns":["","Perfusion can be used by physicians to\naid in the selection of acute stroke\npatients (with known occlusion of the\nintracranial internal carotid artery or\nproximal middle cerebral artery)\nInstructions for the use of contrast agents\nfor this indication can be found in\nAppendix A of the User’s Manual.\nAdditional information for safe and\neffective drug use is available in the\nproduct-specific iodinated CT and\ngadolinium-based MR contrast drug\nlabeling.\nIn addition to the Rapid imaging criteria,\npatients must meet the clinical\nrequirements for thrombectomy, as\nassessed by the physician, and have none\nof the following contraindications or\nexclusions.\nContraindications/Exclusions:\n• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate\n• Presence of Hemorrhage","","parameters related to tissue flow\n(perfusion) and tissue blood volume.\nRapid CT-Perfusion and Rapid MR-\nPerfusion can be used by physicians to aid in\nthe selection of acute stroke patients (with\nknown occlusion of the intracranial internal\ncarotid artery or proximal middle cerebral\nartery)\nInstructions for the use of contrast agents for\nthis indication can be found in Appendix A\nof the User’s Manual. Additional\ninformation for safe and effective drug use is\navailable in the product-specific iodinated\nCT and gadolinium-based MR contrast drug\nlabeling.\nIn addition to the Rapid imaging criteria,\npatients must meet the clinical requirements\nfor thrombectomy, as assessed by the\nphysician, and have none of the following\ncontraindications or exclusions.\nContraindications/Exclusions:\n• Bolus Quality: absent or inadequate\nbolus.\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate\n• Presence of hemorrhage"],"rows":[["","Perfusion can be used by physicians to\naid in the selection of acute stroke\npatients (with known occlusion of the\nintracranial internal carotid artery or\nproximal middle cerebral artery)\nInstructions for the use of contrast agents\nfor this indication can be found in\nAppendix A of the User’s Manual.\nAdditional information for safe and\neffective drug use is available in the\nproduct-specific iodinated CT and\ngadolinium-based MR contrast drug\nlabeling.\nIn addition to the Rapid imaging criteria,\npatients must meet the clinical\nrequirements for thrombectomy, as\nassessed by the physician, and have none\nof the following contraindications or\nexclusions.\nContraindications/Exclusions:\n• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate\n• Presence of Hemorrhage","","parameters related to tissue flow\n(perfusion) and tissue blood volume.\nRapid CT-Perfusion and Rapid MR-\nPerfusion can be used by physicians to aid in\nthe selection of acute stroke patients (with\nknown occlusion of the intracranial internal\ncarotid artery or proximal middle cerebral\nartery)\nInstructions for the use of contrast agents for\nthis indication can be found in Appendix A\nof the User’s Manual. Additional\ninformation for safe and effective drug use is\navailable in the product-specific iodinated\nCT and gadolinium-based MR contrast drug\nlabeling.\nIn addition to the Rapid imaging criteria,\npatients must meet the clinical requirements\nfor thrombectomy, as assessed by the\nphysician, and have none of the following\ncontraindications or exclusions.\nContraindications/Exclusions:\n• Bolus Quality: absent or inadequate\nbolus.\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate\n• Presence of hemorrhage"],["","PACS Functionality","",""],["Basic PACS Functions","Software package which interfaces to a\nPACS or allows viewing within the\napplication","Viewing through user PACS","Same"],["Computer Platform","Standard off-the-shelf Hardware: On-\nPremise","Standard off-the-shelf Hardware: On-\nPremise and Secure Cloud","Standard off-the-shelf Hardware: On-\nPremise"],["Software","Traditional Coding","AI/ML","Mixed Traditional and AI/ML(NCCT\nMotion Filter)"],["DICOM Compliance","Yes","Yes","Yes"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213165-p13-t0","doc_id":"K213165","page_num":13,"bbox":[78.07,76.54,683.94,532.08],"n_rows":25,"n_cols":4,"columns":["Functional Overview","Rapid is a software package that\nprovides for the visualization and\nstudy of changes of tissue in digital\nimages captured by CT and MRI.\nRapid provides viewing and\nquantification.","Same","Same"],"rows":[["Functional Overview","Rapid is a software package that\nprovides for the visualization and\nstudy of changes of tissue in digital\nimages captured by CT and MRI.\nRapid provides viewing and\nquantification.","Same","Same"],["Data/Image Types","Computed Tomography (CT) via\nDICOM Format","Same","Same"],["","Magnetic Image Resonance (MRI) via\nDICOM Format","Not supported","Supported"],["","Acquisition and Modalities Features","",""],["MRI","Diffusion Weighted Image (DWI)","Not supported","Supported"],["","Dynamic Analysis tissue flow\n(perfusion) and tissue blood volume","Not supported","Supported"],["CT","CT Perfusion (CTP)","Not supported","Supported"],["","CTA-large vessel density analysis","Not Supported","Supported"],["","Computed Parameter Maps","",""],["Diffusion MRI","Isotropic DWI (isoDWI)","Not supported","Supported"],["","ADC","Not supported","Supported"],["","Trace of diffusion tensor (Trace)","Not supported","Supported"],["","Fractional Anisotropy (FA) and color\nFA","Not supported","Supported"],["Perfusion MRI and\nPerfusion CT","Cerebral blood flow (CBF)","Not supported","Supported"],["","Cerebral blood volume (CBV)","Not supported","Supported"],["","Mean transit time (MTT)","Not supported","Supported"],["","Tissue residue function time to peak\n(Tmax)","Not supported","Supported"],["","Measurement Tools","",""],["MRI and CT Tools","Arterial input function (AIF)Venous\noutput function\n(VOF)","Not supported","Supported"],["","Time-course","Not supported","Supported"],["","Mask","Not supported","Supported"],["","Region of interest (ROI) and\nVolumetry","Not supported","Supported"],["","Volumetric comparison between 2\nROIs","Not supported","Supported"],["","Motion correction","Not supported","Supported"],["","Export perfusion and diffusion files to\nPACS and DICOM file systems","Not supported","Supported"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213165-p14-t0","doc_id":"K213165","page_num":14,"bbox":[78.0,76.06,684.0,177.98],"n_rows":5,"n_cols":4,"columns":["","Acquire, transmit, process, and store\nmedical images","Not supported","Supported"],"rows":[["","Acquire, transmit, process, and store\nmedical images","Not supported","Supported"],["Thrombectomy","Selection of Patients meeting criteria\nfor Thrombectomy","Supported","Supported"],["NCCT","Hyperdensity (Not included)","Supported","Supported"],["","Hypodensity (Not included)","Not supported","Supported"],["","Motion Artifact Filter (Not included)","Not supported","Supported"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213272-p2-t0","doc_id":"K213272","page_num":2,"bbox":[257.72,430.78,570.36,527.38],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"For","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213272-p5-t0","doc_id":"K213272","page_num":5,"bbox":[79.18,303.68,539.54,793.32],"n_rows":9,"n_cols":9,"columns":["Device","","","","Subject Device","","","Predicate Device",""],"rows":[["Device","","","","Subject Device","","","Predicate Device",""],["","","","","Formus Hip","","","PeekMed",""],["","","","","(K213272)","","","K182464",""],["","Manufacturer","","Formus Labs Ltd.","","","Peek Health, S.A.","",""],["Product Code","Product Code","","QIH","","","LLZ","",""],["Regulation Number","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Regulation Name","","","System, Image\nProcessing, Radiological","","","System, Image\nProcessing, Radiological","",""],["Intended Use","","","Formus Hip is a preoperative surgical\nplanning software. It is\nintended to assist qualified medical\nprofessionals in the preoperative\nplanning of orthopedic surgical\nprocedures.","","","PeekMed is a preoperative\nplanning software for surgery","",""],["Indications for Use","","","Formus Hip is a pre-operative planning\nsoftware for orthopedic surgery. The\nstandalone software application imports\npatient diagnostic imaging studies (e.g.\npre-dimensioned CT scans) from\nPACS-systems or other conventional\nmedias. The Formus Hip system\ncontains an integrated database of\northopedic hip implant geometries that\ncan be overlayed to assist surgeons in\ntheir planning of orthopedic hip\nsurgeries. The software application\nfurther enables the healthcare\nprofessional to customize their\npreoperative planning by means of an\ninteractive graphical user interface.\nFinalized plans can be printed to a PDF\nreport. The qualified healthcare\nprofessional can digitally perform the\nsurgical planning and also make it\navailable as a printable report. Clinical\njudgment and experience with the\nsoftware are required for its successful\nuse.","","","PeekMed is a software system\ndesigned to help surgeons’\nspecialists carry out the preoperative\nplanning in a prompt and efficient\nmanner for several surgical\nprocedures, based on their patients’\nimaging studies. The software imports\ndiagnostics imaging studies such as x-\nrays, CT or magnetic resonance image\n(MRI). The import process can retrieve\nfiles from a CD ROM, a local folder or\nthe PACS. In parallel, there is a\ndatabase of digital representations\nrelated to prosthetic materials supplied\nby their producing companies.\nPeekMed allows health professional to\ndigitally perform the surgical planning\nwithout adding any additional steps to\nthat process. This software system\nrequires no imaging study acquisition\nspecification (no protocol). Experience\nin usage and a clinical assessment are\nnecessary for a proper use of the\nsoftware.","",""]],"caption_candidate":"marketed predicate device (PeekMed, K182464).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213272-p6-t0","doc_id":"K213272","page_num":6,"bbox":[79.18,82.74,539.55,772.0],"n_rows":40,"n_cols":9,"columns":["Device","","","","Subject Device","","","Predicate Device",""],"rows":[["Device","","","","Subject Device","","","Predicate Device",""],["","","","","Formus Hip","","","PeekMed",""],["","","","","(K213272)","","","K182464",""],["","Patient Population","","Adults (≥ 21 years)","","","Adults and pediatrics","",""],["","End Users","","Qualified medical professionals","","","Surgeons","",""],["","Computer","","Personal computer or workstation","","","Personal computer or workstation","",""],["","Operating System","","Windows with a Chrome browser","","","Windows or OS X","",""],["","Radiological Image","","DICOM","","","DICOM","",""],["","Format","","","","","","",""],["Device Availability","Device Availability","","Can be accessed from the Chrome\ninternet browser launched from a\nstandalone PC or workstation with\ninternet access.","","","It can be set to start from a workstation\nor standalone for planning procedures.","",""],["Image Source","","","Receive digital images from various\nsources (including PACS system)","","","Receive digital images from various\nsources (including PACS system)","",""],["Data Processing","","","The software processes pre-\ndimensioned CT imaging to produce\ndigital representations of the patient\nanatomy to which digital\nrepresentations of prosthetic\ncomponents are overlapped.","","","The software processes data in\norder to provide an overlap and\ndimensioning of digital representations\nof the prosthetic material","",""],["Digital Overlap of\nProsthetic Material","","","Allows the overlap of the digital\nrepresentation of prosthetic\ncomponents","","","Allows the overlap of models and the\nintersection of the models","",""],["","Interactive Model","","Yes","","","Yes","",""],["","Positioning","","","","","","",""],["","Interactive Model","","Yes","","","Yes","",""],["","Dimensioning","","","","","","",""],["","Model Rotation","","Yes","","","Yes","",""],["","Support for Digital","","Yes","","","Yes","",""],["","Prosthetic materials","","","","","","",""],["","Provided by the","","","","","","",""],["","Manufacturers","","","","","","",""],["","Anatomical","","Yes","","","Yes","",""],["","Landmarks","","","","","","",""],["","Medical","","Hip","","","Hip, Knee, Spine, Upper Limb, Foot-\nand-Ankle, Trauma","",""],["","Subspecialities","","","","","","",""],["Pre-specified\nProcedures","Pre-specified","","Total Hip Arthroplasty","","","Total Hip Arthroplasty\n(Additional joint replacements and\nassociated procedures specific to\nproduct intended for expanded\nindications)","",""],["","Procedures","","","","","","",""],["","Pre-surgical","","Yes","","","Yes","",""],["","Planning","","","","","","",""],["","Contact with the","","No","","","No","",""],["","Patient","","","","","","",""],["","Control of Life","","No","","","No","",""],["","Supporting Devices","","","","","","",""],["","Human Intervention","","Yes","","","Yes","",""],["","for Image","","","","","","",""],["","Interpretation","","","","","","",""],["","Ability to Add","","Yes","","","Yes","",""],["","Additional Modules","","","","","","",""],["","When Available","","","","","","",""]],"caption_candidate":"Formus Hip – K213272","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213272-p7-t0","doc_id":"K213272","page_num":7,"bbox":[78.85,493.19,539.55,786.52],"n_rows":9,"n_cols":9,"columns":["","Endpoint","","","Acceptance Criteria","","","Results",""],"rows":[["","Endpoint","","","Acceptance Criteria","","","Results",""],["3D models from image\nsegmentation","","","The average Dice score must be equal\nor greater than 0.9","","","Hemipelvis: 0.95\nFemur: 0.97","",""],["","","","The average MAD must be equal or\nless than 2 mm","","","Hemipelvis: 1.15\nFemur: 1.35","",""],["","","","The average HD must be equal or less\nthan 5 mm in the femoral head and\nacetabulum","","","Femoral head: 2.84\nAcetabulum: 3.04","",""],["3D models of the proximal\nshaft inner cortical surface","","","The average MAD must be equal or\nless than 2 mm","","","Inner cortical surface:\n1.02","",""],["","","","The average HD must be equal or less\nthan 5 mm","","","Inner cortical surface:\n2.80","",""],["3D models generated from\nstatistical shape modelling","","","The average Dice score must be equal\nor greater than 0.9","","","Hemipelvis: 0.95\nFemur: 0.97","",""],["","","","The average MAD must be equal or\nless than 2 mm","","","Hemipelvis: 1.25\nFemur: 1.49","",""],["","","","The average HD must be equal or less\nthan 5 mm in the femoral head and\nacetabulum","","","Femoral head: 2.47\nAcetabulum: 2.93","",""]],"caption_candidate":"acceptance criteria were met, as shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213275-p6-t0","doc_id":"K213275","page_num":6,"bbox":[36.23,535.52,559.23,784.98],"n_rows":8,"n_cols":7,"columns":["Characteristic","","Subject Device","","","Predicate Device",""],"rows":[["Characteristic","","Subject Device","","","Predicate Device",""],["","","EchoGo Core 2.0","","","EchoGo Core 1.0",""],["Intended use","Identical","","","Quantification of cardiovascular\nfunction from an echocardiogram","",""],["Indications for use","Identical","","","Quantification and reporting of\nresults of cardiovascular function\nto support physician diagnosis.\nEchoGo Core is indicated for use\nin adult populations","",""],["Anatomical site","Identical","","","Cardiovascular structures","",""],["Users","Identical","","","Accredited echocardiographers\nand sonographers at Ultromics","",""],["Machine learning-based\nalgorithm","Yes","","","Yes","",""],["Algorithms","• Auto-Contouring\n• DICOM Handling","","","• Auto-Contouring\n• DICOM Handling","",""]],"caption_candidate":"A comparison of technological differences between the subject and predicate devices follows.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213275-p7-t0","doc_id":"K213275","page_num":7,"bbox":[36.26,78.9,559.25,791.23],"n_rows":28,"n_cols":7,"columns":["Characteristic","","Subject Device","","","Predicate Device",""],"rows":[["Characteristic","","Subject Device","","","Predicate Device",""],["","","EchoGo Core 2.0","","","EchoGo Core 1.0",""],["","• Technical QC\n• Auto-View Classification\n• Manual Labelling UI\n• Contour Selection and\nApproval\n• Metrics Calculation\n• Auditing\n• Service Webhooks\n• Reporting","","","• Technical QC\n• Manual Labelling UI\n• Contour Selection and\nApproval\n• Metrics Calculation\n• Auditing\n• Reporting","",""],["Operates on DICOM clips","Yes","","","Yes","",""],["Average GLS A2C/A4C views","Yes","","","Yes","",""],["Average GLS A2C/A4C/A3C views","Yes","","","No","",""],["Per view GLS, EF and LV volume","Yes","","","No","",""],["Segmental LS","Yes","","","No","",""],["Echocardiogram images on device\nreport","Yes","","","Yes","",""],["Horseshoe and bullseye\nrepresentations","Yes","","","No","",""],["Mechanical dispersion plot","Yes","","","No","",""],["Strain temporal intensity\nplot/CAMM plot","Yes","","","No","",""],["Contours overlayed on\nechocardiogram images","Yes","","","No","",""],["Auto-view classification","Yes","","","No","",""],["Automatic ED/ES frame detection","Yes","","","Yes","",""],["EF Reported","Yes","","","Yes","",""],["Automated EF calculation","Yes","","","Yes","",""],["Simpson’s biplane LV volume\ncalculation","Yes","","","Yes","",""],["Non-Simpson’s bi-plane LV\nvolume calculation methods","Yes","","","No","",""],["LV ED/ES volume indexed values","Yes","","","No","",""],["EF results shown with video clip","Yes","","","Yes","",""],["User confirmation / rejection of\nresult","Yes","","","Yes","",""],["Manual editing of automated\nresult by user","No","","","No","",""],["LV stroke volume","Yes","","","No","",""],["LV length","Yes","","","No","",""],["Operating system","Windows","","","Windows","",""],["Operating platform","Single software application\nplatform","","","Single software application\nplatform","",""],["Software","Complies with IEC 62304:2015\nand developed under an FDA QSR","","","Complies with IEC 62304:2006\nand developed under an FDA QSR","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213275-p8-t0","doc_id":"K213275","page_num":8,"bbox":[36.3,78.9,560.11,242.08],"n_rows":5,"n_cols":7,"columns":["Characteristic","","Subject Device","","","Predicate Device",""],"rows":[["Characteristic","","Subject Device","","","Predicate Device",""],["","","EchoGo Core 2.0","","","EchoGo Core 1.0",""],["","compliant QMS incorporating risk\nmanagement per ISO 14971:2019","","","compliant QMS incorporating risk\nmanagement per ISO\n14971:2007","",""],["Usability","Complies with IEC 62366-1:2020\nand general use of FDA guidance\non usability engineering","","","General use of FDA guidance on\nusability engineering","",""],["Performance testing","Equivalent to reference\ncomparator TomTec Arena TTA2\n(K150122)","","","Equivalent to reference\ncomparator TomTec Arena TTA2\n(K150122)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213275-p8-t1","doc_id":"K213275","page_num":8,"bbox":[36.3,360.97,560.11,495.57],"n_rows":9,"n_cols":6,"columns":["Standard","","","","Recognition",""],"rows":[["Standard","","","","Recognition",""],["","","","","Number",""],["","ISO 14971:2019 – Medical Devices – Application of Risk Management to Medical Devices","","5-125","",""],["","IEC 62304:2015 – Medical Device Software – Software Life Cycle Processes","","13-79","",""],["","IEC 62366-1:2020 – Medical Devices – Application of Usability Engineering to Medical","","5-129","",""],["","Devices","","","",""],["","NEMA PS 3.1 – PS 3.20 (2016) – Digital Imaging and Communications in Medicine (DICOM)","","12-300","",""],["","Set","","","",""],["","IEC ISO 10918-1:1994 – Digital Compression and Coding of Continuous-tone Still Images","","12-261","",""]],"caption_candidate":"The following consensus standards were used in the design and manufacture of EchoGo Core 2.0.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213275-p9-t0","doc_id":"K213275","page_num":9,"bbox":[36.31,418.24,559.23,524.07],"n_rows":7,"n_cols":6,"columns":["","Left Ventricular Metric","","","% Root Mean Square Error",""],"rows":[["","Left Ventricular Metric","","","% Root Mean Square Error",""],["","Length","","3.06 – 4.59","",""],["","Volume at End Diastole and End Systole","","8.57 – 16.59","",""],["","Ejection Fraction","","6.69 – 8.50","",""],["","Stroke Volume","","10.57 – 13.68","",""],["","Global Longitudinal Strain","","3.36 – 4.79","",""],["","Systolic Segmental Longitudinal Strain","","5.51 – 9.98","",""]],"caption_candidate":"as follows.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213305-p4-t0","doc_id":"K213305","page_num":4,"bbox":[93.42,225.14,555.24,304.7],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Fortian 1.5T, MRT-1550, V8.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213305-p5-t0","doc_id":"K213305","page_num":5,"bbox":[90.48,550.36,545.04,699.91],"n_rows":9,"n_cols":7,"columns":["System","Subject Device","","","Predicate Device","Reference Device","Reference Device"],"rows":[["System","Subject Device","","","Predicate Device","Reference Device","Reference Device"],["","","Vantage Fortian 1.5T,","","Vantage Orian 1.5T,\nMRT-1550, V7.0 with\nAiCE Reconstruction\nProcessing Unit for MR","Vantage Orian 1.5T,\nMRT-1550, V6.0","Vantage E lan 1.5T,\nMRT-2020, V6.0"],["","","MRT-1550, V8.0 with","","","",""],["","","AiCE Reconstruction","","","",""],["","","Processing Unit for MR","","","",""],["Marketed\nBy","","Canon Medical Systems","","Canon Medi cal Systems\nUSA, Inc.","Canon Medical Systems\nUSA, Inc.","Canon Medi cal Systems\nUSA, Inc."],["","","USA, Inc.","","","",""],["510(k)\nNumber","This Submission","","","K211633","K202210","K210 164"],["Clearance\nDate","","","","July 22, 2021","September 22, 2020","March 10, 2021"]],"caption_candidate":"V6.0 (K210164)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213305-p6-t0","doc_id":"K213305","page_num":6,"bbox":[135.5,501.6,549.54,624.77],"n_rows":8,"n_cols":6,"columns":["System","Subject Device","","","Predicate Device\nK211633","Reference Device\nK202210"],"rows":[["System","Subject Device","","","Predicate Device\nK211633","Reference Device\nK202210"],["","","Vantage Fortian 1.5T,","","Vantage Orian 1.5T,\nMRT-1550, V7.0 with AiCE\nReconstruction Processing\nUnit for MR","Vantage Orian 1.5T,\nMRT-1550, V6.0"],["","","MRT-1550, V8.0 with AiCE","","",""],["","","Reconstruction Processing","","",""],["","","Unit for MR","","",""],["Maximum Gradient\nAmplitude","35 [mT/m]","","","45 [mT/m]","34 [mT/m]"],["Rise Time","","0.226 [ms]","","0.225 [ms]","0.220 [ms]"],["Maximum Slew Rate","","155 [mT/m/ms]","","200 [mT/m/ms]","155 [mT/m/ms]"]],"caption_candidate":"time [ms] changes:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213305-p8-t0","doc_id":"K213305","page_num":8,"bbox":[95.0,418.57,549.53,642.37],"n_rows":17,"n_cols":8,"columns":["Item","Subject Device:\nVantage Fortian 1.5T, MRT-1550, V8.0","","","","Predicate Device:","","Notes"],"rows":[["Item","Subject Device:\nVantage Fortian 1.5T, MRT-1550, V8.0","","","","Predicate Device:","","Notes"],["","","","","","Vantage Orian 1.5T, MRT-1550, V7.0","",""],["","","","","","K211633","",""],["Static field strength","","1.5T","","1.5T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","Normal and 1st Operating Mode","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","","Allows screen access to 1st level","","Allows screen access to 1st level\noperating mode","","","Same"],["","","operating mode","","","","",""],["Maximum SAR","","4W/kg for whole body (1st operating","","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["","","mode specified in IEC 60601-2-33:","","","","",""],["","","2010+A1:2013+A2:2015)","","","","",""],["Maximum dB/dt","","1st operating mode specified in IEC","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["","","60601-2-33:","","","","",""],["","","2010+A1:2013+A2:2015","","","","",""],["Potential emergency\ncondition and means\nprovided for\nshutdown","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","Shutdown by Emergency Ramp Down","","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","","","Same"],["","","Unit for collision hazard for","","","","",""],["","","ferromagnetic objects","","","","",""]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p4-t0","doc_id":"K213319","page_num":4,"bbox":[108.24,537.12,539.76,582.0],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Shanghai United Imaging\nIntelligence Co., Ltd.","uAI EasyTriage-Rib","K193271"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p6-t0","doc_id":"K213319","page_num":6,"bbox":[54.0,497.4,558.0,685.92],"n_rows":6,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz ANEURYSM","uAI EasyTriage-Rib"],["Application No.","K213319","K193271"],["Product Code","QFM","QFM"],["Regulation No.","21 C.F.R. § 892.2080","21 C.F.R. § 892.2080"],["Intended Use /\nIndications for Use","Viz ANEURYSM (Viz ANX) is a radiological\ncomputer-assisted triage and notification\nsoftware device for analysis of CT images of the\nhead. The device is intended to assist hospital\nnetworks and trained radiologists in workflow\ntriage by flagging and prioritizing studies with\nsuspected aneurysms during routine patient\ncare.","uAI EasyTriage-Rib is a radiological computer-\nassisted triage and notification software device\nfor analysis of CT chest images. The device is\nintended to assist hospital networks and trained\nradiologists in workflow triage by flagging and\nprioritizing trauma studies with suspected\npositive findings of multiple (3 or more) acute rib\nfracture(s)."]],"caption_candidate":"as the sole-basis for decision making.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p7-t0","doc_id":"K213319","page_num":7,"bbox":[54.0,122.76,558.0,688.8],"n_rows":10,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz ANEURYSM uses an artificial intelligence\nalgorithm to analyze images and highlight\nstudies with suspected aneurysms in a\nstandalone application for study list prioritization\nor triage in parallel to ongoing standard of care.\nThe device generates compressed preview\nimages that are meant for informational purposes\nonly and not intended for diagnostic use. The\ndevice does not alter the original medical image\nand is not intended to be used as a diagnostic\ndevice.\nAnalyzed images are available for review\nthrough the standalone application. When\nviewed through the standalone application the\nimages are for informational purposes only and\nnot for diagnostic use. The results of Viz\nANEURYSM, in conjunction with other clinical\ninformation and professional judgment, are to be\nused to assist with triage/prioritization of medical\nimages. Radiologists who read the original\nmedical images are responsible for the\ndiagnostic decision. Viz ANEURYSM is limited to\nanalysis of imaging data and should not be used\nin-lieu of full patient evaluation or relied upon to\nmake or confirm diagnosis.\nViz ANEURYSM is limited to detecting\naneurysms at least 4mm in diameter.","uAI EasyTriage-Rib uses an artificial intelligence\nalgorithm to analyze images and highlight\nstudies with suspected multiple (3 or more) acute\nrib fracture(s) in a standalone application for\nstudy list prioritization or triage in parallel to\nongoing standard of care. The user is presented\nwith notifications of cases with suspected\nfindings. Notifications include compressed\npreview images that are meant for informational\npurposes only and not intended for diagnostic\nuse beyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of uAI EasyTriage-Rib, in conjunction\nwith other clinical information and professional\njudgment, are to be used to assist with\ntriage/prioritization of medical images. Notified\nradiologists who read the original medical\nimages are responsible for the diagnostic\ndecision."],["Anatomical Region","Head","Chest"],["Independent\nStandard of Care\nWorkflow","Yes","Yes"],["Notification/\nPrioritization","Yes","Yes"],["Identify patients\nwith pre-specified\nclinical condition","Yes","Yes"],["Clinical Condition","Aneurysm","Multiple (3 or more) acute rib fractures."],["Intended User","Radiologist","Radiologist"],["DICOM Compatible","Yes","Yes"],["Data Acquisition","Acquires medical image data from DICOM\ncompliant imaging devices and modalities.","Acquires medical image data from DICOM\ncompliant imaging devices and modalities."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p8-t0","doc_id":"K213319","page_num":8,"bbox":[54.0,122.76,558.0,358.92],"n_rows":8,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Supported Imaging\nModality","Computed Tomography Angiography (CTA)","Computed Tomography (CT)"],["Alteration of\nOriginal Image","No","No"],["Artificial\nIntelligence\nAlgorithm","Yes","Yes"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-diagnostic purposes","Initial assessment; non-diagnostic purposes"],["View DICOM Data","DICOM Information about the patient, study and\ncurrent image.","DICOM Information about the patient, study and\ncurrent image."],["Results Returned\nin Standalone\nApplication","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p8-t1","doc_id":"K213319","page_num":8,"bbox":[128.76,530.28,486.0,598.2],"n_rows":3,"n_cols":2,"columns":["","Point Estimate [95% CI]"],"rows":[["","Point Estimate [95% CI]"],["Sensitivity\n(Positives = 67)","0.93 [0.83, 0.98]"],["Specificity\n(Negatives = 248)","0.89 [0.85, 0.93]"]],"caption_candidate":"Table 1: Primary Endpoint Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p10-t0","doc_id":"K213319","page_num":10,"bbox":[108.0,149.28,540.0,190.56],"n_rows":3,"n_cols":3,"columns":["Clinical Site","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Clinical Site","Sensitivity [95% CI]","Specificity [95% CI]"],["Site 001","0.91 [0.76, 0.98]","0.87 [0.80, 0.92]"],["Site 002","0.94 [0.80, 0.99]","0.92 [0.85, 0.96]"]],"caption_candidate":"Table 2: Device Performance per Clinical Site","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p10-t1","doc_id":"K213319","page_num":10,"bbox":[108.0,235.68,540.0,290.76],"n_rows":4,"n_cols":3,"columns":["Age Range (Years)","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Age Range (Years)","Sensitivity [95% CI]","Specificity [95% CI]"],["<50","0.91 [0.59, 1.0]","0.88 [0.75, 0.95]"],["50-70","0.93 [0.77, 0.99]","0.90 [0.83, 0.95]"],["70<","0.93 [0.76, 0.99]","0.89 [0.80, 0.94]"]],"caption_candidate":"Table 3: Device Performance per Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p10-t2","doc_id":"K213319","page_num":10,"bbox":[108.0,331.68,540.0,373.08],"n_rows":3,"n_cols":3,"columns":["Sex","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Sex","Sensitivity [95% CI]","Specificity [95% CI]"],["Male","0.95 [0.77, 1.0]","0.92 [0.85, 0.96]"],["Female","0.91 [0.79, 0.98]","0.87 [0.80, 0.92]"]],"caption_candidate":"Table 4: Device Performance per Sex","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p10-t3","doc_id":"K213319","page_num":10,"bbox":[171.0,413.4,490.56,482.4],"n_rows":5,"n_cols":2,"columns":["Maximum Aneurysm Diameter","Sensitivity [95% CI]"],"rows":[["Maximum Aneurysm Diameter","Sensitivity [95% CI]"],["4 ≤ d < 7 mm","0.93 [0.82, 0.99]"],["7 ≤ d < 13 mm","0.88 [0.64, 0.99]"],["13 ≤ d < 25 mm","1.0 [0.40, 1.0]"],["d ≥ 25 mm","-"]],"caption_candidate":"Table 5: Device Performance by Aneurysm Diameter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p10-t4","doc_id":"K213319","page_num":10,"bbox":[126.0,519.84,526.56,629.64],"n_rows":7,"n_cols":2,"columns":["Saccular Aneurysm Location","Sensitivity [95% CI]"],"rows":[["Saccular Aneurysm Location","Sensitivity [95% CI]"],["AComm (including Acomm/ACA junction)","1.0 [0.63, 1.0]"],["Basilar Artery Tip","1.0 [0.48, 1.0]"],["Bifurcation of the M2 segments of the MCA","1.0 [0.78, 1.0]"],["PComm (including PComm/PCA junction)","0.91 [0.59, 1.0]"],["ICA or MCA-M1 segment (including ICA/ACA\njunction)","0.82 [0.60, 0.95]"],["Other","1.0 [0.54, 1.0]"]],"caption_candidate":"Table 6: Device Performance by Saccular Aneurysm Location","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p11-t0","doc_id":"K213319","page_num":11,"bbox":[108.0,135.96,540.0,206.4],"n_rows":3,"n_cols":3,"columns":["Slice Thickness","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Slice Thickness","Sensitivity [95% CI]","Specificity [95% CI]"],["0.5mm ≤ Slice Thickness\n<0.625mm","0.93 [0.83, 0.98]","0.89 [0.84, 0.93]"],["0.625mm ≤ Slice Thickness ≤\n1.0mm","0.89 [0.52, 1.0]","0.92 [0.75, 0.99]"]],"caption_candidate":"Table 7: Device Performance by Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p11-t1","doc_id":"K213319","page_num":11,"bbox":[108.0,243.96,540.0,301.56],"n_rows":4,"n_cols":3,"columns":["Manufacturer","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Manufacturer","Sensitivity [95% CI]","Specificity [95% CI]"],["General Electric","0.91 [0.78, 0.97]","0.89 [0.83, 0.93]"],["Siemens","1.0 [0.77, 1.0]","0.87 [0.74, 0.95]"],["Toshiba","0.89 [0.52, 1.0]","0.93 [0.76, 0.99]"]],"caption_candidate":"Table 8: Device Performance by Scanner Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p11-t2","doc_id":"K213319","page_num":11,"bbox":[108.0,341.88,540.0,693.36],"n_rows":12,"n_cols":4,"columns":["Manufacturer","Model","Sensitivity\n[95% CI]","Specificity\n[95% CI]"],"rows":[["Manufacturer","Model","Sensitivity\n[95% CI]","Specificity\n[95% CI]"],["GE Medical\nSystems","LightSpeed VCT","0.86 [0.65, 0.97]","0.88 [0.80, 0.93]"],["","Optima CT660","1.0 [0.16, 1.0]","0.89 [0.52, 1.0]"],["","Revolution EVO","1.0 [0.16, 1]","1.0 [0.40, 1]"],["","Revolution HD","1.0 [0.40, 1.0]","0.96 [0.79, 1.0]"],["","BrightSpeed","0.93 [0.66, 1.0]","0.87 [0.70, 0.96]"],["Siemens","Sensation 64","N/A","1.0 [0.03, 1.0]"],["","SOMATOM Definition\nAS+","1.0 [0.66, 1]","1.0 [0.81, 1.0]"],["","SOMATOM Edge Plus","N/A","0.5 [0.16, 0.84]"],["","SOMATOM\nPerspective","1.0 [0.48, 1.0]","0.89. [0.67, 0.99]"],["Toshiba","Aquilion PRIME","1.0 [0.40, 1.0]","0.92 [0.62, 1.0]"],["","Aquilion","0.8 [0.28, 0.99]","0.94 [0.70, 1.0]"]],"caption_candidate":"Table 9: Device Performance by CT Scanner (Manufacturer/Model)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213319-p12-t0","doc_id":"K213319","page_num":12,"bbox":[108.0,183.24,540.0,255.12],"n_rows":5,"n_cols":3,"columns":["Detector Rows","Sensitivity [95% CI]","Specificity [95% CI]"],"rows":[["Detector Rows","Sensitivity [95% CI]","Specificity [95% CI]"],["16","0.93 [0.66, 1.0]","0.87 [0.70, 0.96]"],["32","N/A","1.0 [0.03, 1.0]"],["64","0.92 [0.80, 0.98]","0.89 [0.84, 0.93]"],["80","1.0 [0.40, 1.0]","0.92 [0.62, 1.0]"]],"caption_candidate":"Table 10: Device Performance by Scanner Row Detectors","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p4-t0","doc_id":"K213436","page_num":4,"bbox":[66.67,271.14,534.11,326.76],"n_rows":4,"n_cols":9,"columns":["","Regulation Number","","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","","Regulation Name","","","Product Code",""],["21 CFR § 892.1550","","","Ultrasonic Pulsed Doppler Imaging System","","","IYN","",""],["21 CFR § 892.1560","","","Ultrasound Pulsed Echo Imaging System","","","IYO","",""],["21 CFR § 892.1570","","","Diagnostic Ultrasonic Transducer","","","ITX","",""]],"caption_candidate":"Regulation Number, Name and Product Codes:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p4-t1","doc_id":"K213436","page_num":4,"bbox":[66.67,558.0,534.11,682.72],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Clarius Ultrasound Scanner"],"rows":[["","Device Trade Name:","","Clarius Ultrasound Scanner"],["","510(k) Reference:","","K192107"],["","Submitter Name:","","Clarius Mobile Health Corp."],["","Regulation Name:","","Ultrasonic Pulsed Doppler Imaging System"],["","Classification Product Code(s):","","IYN"],["","Subsequent Product Codes","","IYO, ITX"],["Regulation Number:","Regulation Number:","","21 CFR § 892.1550; 21 CFR § 892.1560; 21 CFR §\n892.1570"],["","Classification:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p5-t0","doc_id":"K213436","page_num":5,"bbox":[66.67,312.29,534.12,386.95],"n_rows":3,"n_cols":2,"columns":["Transducers/ Scanners (various models)","C3 HD3, C7 HD3, EC7 HD3, L7 HD3, L15 HD3, PA HD3,\nL20 HD3"],"rows":[["Transducers/ Scanners (various models)","C3 HD3, C7 HD3, EC7 HD3, L7 HD3, L15 HD3, PA HD3,\nL20 HD3"],["Software","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"],["Accessories","Clarius Charger\nClarius Fan"]],"caption_candidate":"The Clarius Ultrasound Scanner comprises the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p5-t1","doc_id":"K213436","page_num":5,"bbox":[66.67,590.16,548.25,708.9],"n_rows":9,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["","510(k) Holder/","","Clarius Mobile Health Corp.","","","Clarius Mobile Health Corp.","",""],["","Manufacturer","","","","","","",""],["","Submission","","Current Submission","","","K192107","",""],["","Reference","","","","","","",""],["","510(k) Track","","Track 3","","","Track 3","",""],["","Product Codes","","IYN1, IYO2, ITX3","","","IYN1, IYO2, ITX3","",""]],"caption_candidate":"Comparison of the Subject Device and Predicate Device for Demonstration of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p6-t0","doc_id":"K213436","page_num":6,"bbox":[66.67,72.36,548.25,712.27],"n_rows":10,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["Regulation\nNumber","","","21 CFR 892.15501\n21 CFR 892.15602\n21 CFR 892.15703","","","21 CFR 892.15501\n21 CFR 892.15602\n21 CFR 892.15703","",""],["Regulation Name","","","Ultrasonic Pulsed Doppler Imaging System1;\nUltrasonic Pulsed Echo Imaging System2;\nDiagnostic Ultrasonic Transducer3","","","Ultrasonic Pulsed Doppler Imaging System1;\nUltrasonic Pulsed Echo Imaging System2;\nDiagnostic Ultrasonic Transducer3","",""],["","Transducer","","C3 HD3, C7 HD3, EC7 HD3, L7 HD3, L15 HD3,\nPA HD3, L20 HD3","","","C3 HD, C7 HD, EC7 HD, L7 HD, L15 HD, PA HD,\nL20 HD","",""],["","Models","","","","","","",""],["Transducer Types","Transducer Types","","Convex Array\nLinear Array\nPhased Array\nIntracavity","","","Convex Array\nLinear Array\nPhased Array\nIntracavity","",""],["Intended Use","","","Diagnostic ultrasound imaging and fluid flow\nanalysis of the human body","","","Diagnostic ultrasound imaging and fluid flow\nanalysis of the human body","",""],["Indications for\nUse and Clinical\nUsage","","","The Clarius Ultrasound Scanner is a software-\nbased ultrasound imaging system and\naccessories, intended for diagnostic imaging.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: ophthalmic, fetal,\nabdominal, intra-operative (non-\nneurological), pediatric, small organ, cephalic\n(adult), trans-rectal, trans-vaginal, musculo-\nskeletal (conventional, superficial), urology,\ngynecology, cardiac (adult, pediatric),\nperipheral vessel, carotid, and procedural\nguidance of needles into the body.\nThe system is a transportable ultrasound\nsystem intended for use in environments\nwhere healthcare is provided by trained\nhealthcare professionals.\n• Ophthalmic\n• Fetal\n• Abdominal\n• Intraoperative (Ab/Vasc)\n• Pediatric\n• Small Organ\n• Adult cephalic\n• Trans-rectal\n• Trans-vaginal\n• Musculoskeletal (conventional)\n• Musculoskeletal (superficial)\n• Urology\n• Gynecology\n• Cardiac adult","","","The Clarius Ultrasound Scanner is a software-\nbased ultrasound imaging system and\naccessories, intended for diagnostic imaging.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: ophthalmic, fetal,\nabdominal, intra-operative (non-\nneurological), pediatric, small organ, cephalic\n(adult), trans-rectal, trans-vaginal, musculo-\nskeletal (conventional, superficial), urology,\ngynecology, cardiac (adult, pediatric),\nperipheral vessel, carotid, and procedural\nguidance of needles into the body.\nThe system is a transportable ultrasound\nsystem intended for use in environments\nwhere healthcare is provided by trained\nhealthcare professionals.\n• Ophthalmic\n• Fetal\n• Abdominal\n• Intraoperative (Ab/Vasc)\n• Pediatric\n• Small Organ\n• Adult cephalic\n• Trans-rectal\n• Trans-vaginal\n• Musculoskeletal (conventional)\n• Musculoskeletal (superficial)\n• Urology\n• Gynecology\n• Cardiac adult","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p7-t0","doc_id":"K213436","page_num":7,"bbox":[66.68,72.36,548.26,574.17],"n_rows":14,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["","","","• Cardiac pediatric\n• Peripheral vessel\n• Carotid\n• Needle guidance","","","• Cardiac pediatric\n• Peripheral vessel\n• Carotid\n• Needle guidance","",""],["Principle of\nOperation","","","Piezoelectric material in the system’s\ntransducer transmits high frequency, non-\nionizing sound waves to the designated\nregion of the body and converts the\nsubsequent echoes detected to electronic\nsignals in order to construct an image of the\ninternal structures of an anatomical field. The\nimage is sent wirelessly from the transducer\nto an external iOS or Android viewing device\non which the image can be displayed.","","","Piezoelectric material in the system’s\ntransducer transmits high frequency, non-\nionizing sound waves to the designated\nregion of the body and converts the\nsubsequent echoes detected to electronic\nsignals in order to construct an image of the\ninternal structures of an anatomical field. The\nimage is sent wirelessly from the transducer\nto an external iOS or Android viewing device\non which the image can be displayed.","",""],["Power Source","","","Internal integrated built-in (non-removable)\nlithium-ion battery","","","Removable lithium-ion battery","",""],["","Display","","iOS or Android mobile device","","","iOS or Android mobile device","",""],["","Wireless","","Communicates wirelessly via Wi-Fi and\nBluetooth","","","Communicates wirelessly via Wi-Fi and\nBluetooth","",""],["","Capability","","","","","","",""],["","Portability","","Portable ultrasound system","","","Portable ultrasound system","",""],["System\nComponents","System","","Transducers/scanners\nSoftware (Clarius App)\nAccessories (Charger and Fan)","","","Transducers/scanners\nSoftware (Clarius App)\nAccessories (Charger and Fan)","",""],["","Components","","","","","","",""],["Modes of\nOperation","","","B-mode\nM-mode\nColor Doppler\nPower Doppler\nPulse-Wave Doppler (PWD)\nCombined (B+M; B+CD; B+PD; B+PWD)","","","B-mode\nM-mode\nColor Doppler\nPower Doppler\nPulse-Wave Doppler (PWD)\nCombined (B+M; B+CD; B+PD; B+PWD)","",""],["Safety Standards","","","The Clarius Ultrasound Scanner complies with\nthe following safety standards:\n60601-1\n60601-1-2\n60601-1-6\n60601-1-12\n60601-2-37","","","The Clarius Ultrasound Scanner complies with\nthe following safety standards:\n60601-1\n60601-1-2\n60601-1-6\n60601-1-12\n60601-2-37","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213436-p8-t0","doc_id":"K213436","page_num":8,"bbox":[66.61,112.68,545.39,535.56],"n_rows":16,"n_cols":6,"columns":["","Standard","","","Title of Standard",""],"rows":[["","Standard","","","Title of Standard",""],["IEC 60601-1:2012","","","Medical electrical equipment – Part 1: General requirements for basic safety\nand essential performance","",""],["IEC 60601-1-2:2014","","","Medical electrical equipment – Part 1-2: General requirements for basic safety\nand essential performance – Collateral Standard: Electromagnetic\nCompatibility – Requirements and tests","",""],["IEC 60601-1-6 Edition 3.1 2013-\n10","","","Medical electrical equipment - Part 1-6: General Requirements for Basic Safety\nand Essential Performance - Collateral Standard: Usability","",""],["IEC 60601-1-12 Edition 1.0 2014-\n06","","","Medical electrical equipment - Part 1-12: General Requirements for Basic\nSafety and Essential Performance - Collateral Standard: Requirements for\nMedical Electrical Equipment and Medical Electrical Systems Intended for Use\nin the Emergency Medical Services Environment","",""],["IEC 60601-2-37:2015","","","Medical electrical equipment – Part 2-37: Particular requirements for the basic\nsafety and essential performance of ultrasonic medical diagnostic and\nmonitoring equipment","",""],["ISO 10993-1:2018","","","Biological evaluation of medical devices – Part 1: Evaluation and testing within\na risk management process","",""],["AIUM/NEMA UD 2-2004","","","NEMA Standards Publication UD 2-2004 (R2009) Acoustic Output\nMeasurement Standard for Diagnostic Ultrasound Equipment Revision 3.\n(Radiology)","",""],["AIUM/NEMA UD 3-2004","","","NEMA Standards Publication UD 3-2004 (R2009) Standard for Real-Time\nDisplay of Thermal and Mechanical Acoustic Output Indices on Diagnostic\nUltrasound Equipment","",""],["IEC 62304:2006/AMD 1:2015","","","Medical device software – Software life cycle processes","",""],["IEC 62366-1:2015","","","Medical devices – Application of usability engineering to medical devices","",""],["ISO 15223-1:2016","","","Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied","",""],["ISO 14971:2019","","","Medical Devices – Application of Risk Management to Medical Devices","",""],["IEC 60529:2013","","","Degrees of protection provided by enclosures (IP Code)","",""],["IEC 62133:2012","","","Secondary cells and batteries containing alkaline or other non-acid electrolytes\n–Safety requirements for portable sealed secondary cells, and for batteries\nmade from them, for use in portable applications","",""],["IEC 61157:2013","","","IEC 61157: Standard means for the reporting of the acoustic output of medical\ndiagnostic ultrasonic equipment","",""]],"caption_candidate":"demonstrate compliance to the following standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213504-p10-t0","doc_id":"K213504","page_num":10,"bbox":[113.66,67.68,594.06,162.68],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary:\nAquilion ONE (TSX-\n306A/3) V10.4 with\nSpectral Imaging\nSystem","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K203225","03/24/2021"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213504-p15-t0","doc_id":"K213504","page_num":15,"bbox":[114.96,586.56,549.96,666.57],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],["Vitrea Software\nPackage,\nVSTP-001A\n(Primary Predicate)","Canon\nMedical\nSystems, USA","21 CFR\n892.2050","Medical Image\nManagement\nand Processing\nSystem","LLZ","K203312","02/16/2021"]],"caption_candidate":"9. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213504-p16-t0","doc_id":"K213504","page_num":16,"bbox":[114.96,93.87,549.96,183.3],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],["Aquilion ONE (TSX-\n306A/3) V10.4 with\nSpectral Imaging\nSystem\n(Reference Predicate)","Canon\nMedical\nSystems, USA","21 CFR\n892.1750","Computed\nTomography\nX-ray system","JAK","K203225","03/24/2021"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213504-p18-t0","doc_id":"K213504","page_num":18,"bbox":[92.94,93.87,533.25,668.31],"n_rows":7,"n_cols":4,"columns":["Item","Vitrea Software Package,\nVSTP-001A (8.10)","Vitrea Software Package,\nVSTP-001A (V8.8)","Comment"],"rows":[["Item","Vitrea Software Package,\nVSTP-001A (8.10)","Vitrea Software Package,\nVSTP-001A (V8.8)","Comment"],["510(k) Number","Subject Device","K203312",""],["Anatomical\nregion","Whole body","Whole body","No change"],["Type of Input\nData","Acquired by spectral scan\n(TSX-306A/3, V10.11 or earlier\nand V10.12 and later)","Acquired by spectral scan\n(TSX-306A/3, V10.3 or earlier\nand V10.4 and later)",""],["","Spectral Analysis\n• Basis material images and\nmonochromatic image\no Dual Energy scan (AiCE\nBrain reconstruction*\no Segmentation Data derived\nfrom*\n Vitrea CT Myocardial\nPerfusion\n Vitrea Coronary Artery\nAnalysis","Spectral Analysis\n• Basis material images and\nmonochromatic image","*New"],["Type of Output\nData","Spectral Analysis\n• Analysis result display\n• Secondary capture (RGB\nimage)\n• Batch MPR and DICOM\nvolume save","Spectral Analysis\n• Analysis result display\n• Secondary capture (RGB\nimage)\n• Batch MPR and DICOM\nvolume save","No change"],["Image Processing","Spectral Analysis\n• Generation of\nmonochromatic images\n(ranging from 35keV –\n200keV)\no Smoothing filter\n• Generation of Iodine map\n• VNC image\n• Generation of Electron\nDensity Image\n• Generation of Effective Z\nImage\n• Generation of Basis material\nimage (bone/water)","Spectral Analysis\n• Generation of\nmonochromatic images\n(ranging from 35keV –\n200keV)\no Smoothing filter\n• Generation of Iodine map\n• VNC image\n• Generation of Electron\nDensity Image\n• Generation of Effective Z\nImage\n• Generation of Basis material\nimage (bone/water)","No change"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213504-p19-t0","doc_id":"K213504","page_num":19,"bbox":[92.94,93.87,533.25,578.46],"n_rows":4,"n_cols":4,"columns":["Item","Vitrea Software Package,\nVSTP-001A (8.10)","Vitrea Software Package,\nVSTP-001A (V8.8)","Comment"],"rows":[["Item","Vitrea Software Package,\nVSTP-001A (8.10)","Vitrea Software Package,\nVSTP-001A (V8.8)","Comment"],["510(k) Number","Subject Device","K203312",""],["Analysis","Spectral Analysis\n• Monochromatic image\no Basis material dual\nenergy analysis\n• Iodine map\no Three material\ndecomposition\n• Electron density\no Basis material dual\nenergy analysis\n• Effective Z\no Basis material dual\nenergy analysis\n• Basis material image\n(bone/water)\nBasis material dual energy\nanalysis","Spectral Analysis\n• Monochromatic image\no Basis material dual\nenergy analysis\n• Iodine map\no Three material\ndecomposition\n• Electron density\no Basis material dual\nenergy analysis\n• Effective Z\no Basis material dual\nenergy analysis\n• Basis material image\n(bone/water)\nBasis material dual energy\nanalysis","No change"],["Display","• MPR, Fusion image, MIP\nimage, MinIP image,\nDisplaying three MPR planes,\n• New:\no 3D*\no Chamber View*\no Polar map*\no Curved Planar\nReconstruction (CPR)*\no Stretched Planar\nReconstruction (SPR)*\no Crosscut*\no Fusion to CPR/SPR* and\nCrosscut*","MPR, Fusion image, MIP\nimage, MinIP image,\nDisplaying three MPR\nplanes","* New"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213544-p7-t0","doc_id":"K213544","page_num":7,"bbox":[62.28,45.24,770.29,562.9],"n_rows":36,"n_cols":6,"columns":["510(k) Summary","","","","",""],"rows":[["510(k) Summary","","","","",""],["TOMTEC-ARENA (TT","A2.50)","","","",""],["","","","","",""],["GENERAL COMPA","RISON","","","",""],["","","","","",""],["Feature","Predicate Device","Reference Device","","Subject Device","Discussion /"],["","TOMTEC-ARENA","Philips EPIQ and Affiniti Ultrasou","nd","TOMTEC-ARENA","Comment"],["","","Systems with Auto Measure","","",""],["K-number","K201632","K211597","","Not available","Subject of this"],["","","","","","submission is"],["","","","","","TOMTEC-ARENA."],["Regulation Number","21 CFR 892.2050;","21 CRF 892.1550","","21 CFR 892.2050;","Identical to predica"],["and Regulation Name","System, Image processing,","Ultrasonic pulsed doppler imaging s","ystem.","System, Image processing,","device."],["","Radiological -","","","Radiological -",""],["","Picture Archiving and","","","Picture Archiving and",""],["","Communications System","","","Communications System",""],["","(PACS)","","","(PACS)",""],["Classification Product","LLZ","IYN","","QIH","Identical to predica"],["Code","","","","","device (primary an"],["","","","","","secondary product"],["","","","","","code switched)."],["Subsequent Product","QIH","ITX, IYO, OBJ, QIH","","LLZ","Identical to predica"],["Codes","","","","","device (primary an"],["","","","","","secondary product"],["","","","","","code switched)."],["Class","2","2","","2","Identical to predica"],["","","","","","and reference devi"],["Classification Panel","Radiology","Radiology","","Radiology","Identical to predica"],["","","","","","and reference devi"],["Device Name","TOMTEC-ARENA","EPIQ Series Diagnostic Ultrasound","System,","TOMTEC-ARENA","Identical to predica"],["","","Affiniti Series Diagnostic Ultrasound","System","","device."],["Version","TTA2.40","VM 9.0","","TTA2.50","Version of subject"],["","","(Ultrasound System Software","","","device changed du"],["","","version/platform)","","","new features."],["","","","","",""],["TOMTEC Imaging Systems GmbH","","Pa","ge 4 of 10","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K213544-p8-t0","doc_id":"K213544","page_num":8,"bbox":[57.19,93.18,795.6,535.27],"n_rows":3,"n_cols":5,"columns":["Intended Use","TOMTEC-ARENA software is\na clinical software package\ndesigned for review,\nquantification and reporting of\nstructures and function based\non multi-dimensional digital\nmedical data acquired with\ndifferent modalities.TOMTEC-\nARENA is not intended to be\nused for reading of\nmammography images.","The intended use of Philips EPIQ series\ndiagnostic ultrasound systems is diagnostic\nultrasound imaging and fluid flow analysis of the\nhuman body, with the following indications for\nuse:Abdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral Vascular,\nCephalic (Adult), Cephalic (Neonatal),\nFetal/Obstetric, Gynecological, Intra-cardiac\nEcho, Intra-luminal, Intraoperative (Vascular),\nIntraoperative (Cardiac),\nMusculoskeletal(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric, Peripheral\nVessel, Small Organ (Breast, Thyroid, Testicle),\nTransesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.\nThe clinical environments where Philips EPIQ\ndiagnostic ultrasound systems can be used\ninclude clinics, hospitals, and clinical point-of care\nfor diagnosis of patients.\nWhen integrated with Philips EchoNavigator, the\nsystems can assist the interventionalist and\nsurgeon with image guidance during treatment of\ncardiovascular disease in which the procedure\nuses both live X-ray and live echo guidance.The\nsystems are intended to be installed, used, and\noperated only in accordance with the safety\nprocedures and operating instructions given in\nthe product user information. Systems are to be\noperated only by appropriately trained healthcare\nprofessionals for the purposes for which they\nwere designed.\nHowever, nothing stated in the user information\nreduces your responsibility for sound clinical\njudgement and best clinical procedure.","TOMTEC-ARENA software is\na clinical software package\ndesigned for review,\nquantification and reporting of\nstructures and function based\non multi-dimensional digital\nmedical data acquired with\ndifferent modalities.TOMTEC-\nARENA is not intended to be\nused for reading of\nmammography images.","Intended Use/\nIndications for use of\npredicate and subject\ndevice are identical\n(unchanged).Intended\nUse/ Indications for\nuse of reference\ndevice and subject\ndevice are similar and\nconsidered equivalent\n(specifically if\ncompared for the\nclinical use case/\nworkflow of the subject\nfeature)."],"rows":[["Intended Use","TOMTEC-ARENA software is\na clinical software package\ndesigned for review,\nquantification and reporting of\nstructures and function based\non multi-dimensional digital\nmedical data acquired with\ndifferent modalities.TOMTEC-\nARENA is not intended to be\nused for reading of\nmammography images.","The intended use of Philips EPIQ series\ndiagnostic ultrasound systems is diagnostic\nultrasound imaging and fluid flow analysis of the\nhuman body, with the following indications for\nuse:Abdominal, Cardiac Adult, Cardiac other\n(Fetal), Cardiac Pediatric, Cerebral Vascular,\nCephalic (Adult), Cephalic (Neonatal),\nFetal/Obstetric, Gynecological, Intra-cardiac\nEcho, Intra-luminal, Intraoperative (Vascular),\nIntraoperative (Cardiac),\nMusculoskeletal(Conventional), Musculoskeletal\n(Superficial), Other: Urology, Pediatric, Peripheral\nVessel, Small Organ (Breast, Thyroid, Testicle),\nTransesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.\nThe clinical environments where Philips EPIQ\ndiagnostic ultrasound systems can be used\ninclude clinics, hospitals, and clinical point-of care\nfor diagnosis of patients.\nWhen integrated with Philips EchoNavigator, the\nsystems can assist the interventionalist and\nsurgeon with image guidance during treatment of\ncardiovascular disease in which the procedure\nuses both live X-ray and live echo guidance.The\nsystems are intended to be installed, used, and\noperated only in accordance with the safety\nprocedures and operating instructions given in\nthe product user information. Systems are to be\noperated only by appropriately trained healthcare\nprofessionals for the purposes for which they\nwere designed.\nHowever, nothing stated in the user information\nreduces your responsibility for sound clinical\njudgement and best clinical procedure.","TOMTEC-ARENA software is\na clinical software package\ndesigned for review,\nquantification and reporting of\nstructures and function based\non multi-dimensional digital\nmedical data acquired with\ndifferent modalities.TOMTEC-\nARENA is not intended to be\nused for reading of\nmammography images.","Intended Use/\nIndications for use of\npredicate and subject\ndevice are identical\n(unchanged).Intended\nUse/ Indications for\nuse of reference\ndevice and subject\ndevice are similar and\nconsidered equivalent\n(specifically if\ncompared for the\nclinical use case/\nworkflow of the subject\nfeature)."],["Indications for Use","Indications for use of TomTec-\nArena TTA2 software are\nquantification and reporting of\ncardiovascular, fetal,\nabdominal structures and\nfunction of patients with\nsuspected disease to support\nthe physician in the diagnosis","","Indications for use of\nTOMTEC-ARENA TTA2\nsoftware are quantification and\nreporting of cardiovascular,\nfetal, abdominal structures\nand function of patients with\nsuspected disease to support\nthe physician in the diagnosis",""],["where used\n(hospital, home,\nambulance, etc.)","Hospitals, clinics, and\nphysician´s offices.","Clinics, hospitals, and clinical point-of care\nfor diagnosis of patients.","Inside and outside of\nHospitals, Clinics, and\nPhysician´s offices.","Subject of submission;\nThe intended use\nenvironment was\nrevised and extended.\nEnvironmental\nconditions have been\nconsidered."]],"caption_candidate":"TOMTEC-ARENA (TTA2.50)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213544-p9-t0","doc_id":"K213544","page_num":9,"bbox":[57.19,145.19,795.2,458.48],"n_rows":5,"n_cols":8,"columns":["","IMAGE-COM","","","","","",""],"rows":[["","IMAGE-COM","","","","","",""],["Feature","Feature","Predicate Device\nTOMTEC-ARENA","Reference Device\nPhilips EPIQ and Affiniti Ultrasound\nSystems\nwith Auto Measure","Subject Device\nTOMTEC-ARENA","Discussion /\nComment","Discussion /",""],["","","","","","","Comment",""],["Application\ndescription","","IMAGE-COM is a basic\nmodule for reviewing and\nmeasuring digital medical\ndata. It supports routine\nworkflows for loading,\nanalyzing and saving medical\nstudies, e.g. for the purpose of\ncreating reports. IMAGE-COM\nis where basic measurements\ncan be performed and the\nentry point for advanced\nanalysis modules. Study\nrelated routine measurements\ncan be imported, displayed,\nedited and exported to\naccompanying reporting\nsystems.","Auto Measure is an optional software feature\non the EPIQ/Affinity Series Diagnostic\nUltrasound System that provides the end\nuser with semi automated adult\nechocardiography 2D and Doppler\nmeasurements through an AI-algorithm,\ntraining via machine-learning techniques. It\nis intended to be used with an Adult\nCardiology Transthoracic transducer and\nacquisitions that include an ECG. These\nmeasurements are routinely collected during\na transthoracic ECG, per The American\nSociety of Echo cardiography (ASE)\nrecommendations","unchanged","Identical to predicate\ndevice.\nSimilar and considered\nequivalent to the\nreference device\n(specifically if\ncompared for the\nclinical use\ncase/workflow of the\nsubject feature).","",""],["SW Version","","5.5.5","9.0","5.5.7","Version of module\nIMAGE-COM changed\ndue to new features.","",""]],"caption_candidate":"and reference device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213544-p12-t0","doc_id":"K213544","page_num":12,"bbox":[57.18,93.18,795.6,508.37],"n_rows":2,"n_cols":5,"columns":["Semi-Automation\nTechnology","As cleared","Semi-automated adult echocardiography 2D\nand Doppler measurements are generated\nusing an artificial intelligence (AI) detection\nalgorithm without user interaction. After\nmeasurement is generated, the user can edit\n(manually adjust the caliper positions),\naccept, or reject the measurements.The\nautomation of measurements is constrained\nto the specific imaging mode (2D, Doppler)\nas recommended by ASE guidelines.","Semi-automated adult\nechocardiography 2D and\nDoppler measurements are\ngenerated using an artificial\nintelligence (AI) detection\nalgorithm without user\ninteraction. After\nmeasurement is generated,\nthe user can edit (manually\nadjust the caliper positions),\naccept, or reject the\nmeasurements.The\nautomation of measurements\nis constrained to the specific\nimaging mode (2D, Doppler)\nas recommended by ASE\nguidelines.","Subject of submission;\nProposed feature\nincludes optional semi-\nautomation of existing\nmeasurements\navailable to the end\nuser during routine\nultrasound exam\nsimilar to reference\ndevice. Semi-\nautomated\nmeasurements\nquantify image data\nthrough an AI-based\nalgorithm that was\ntrained with a\nmachine-learning\nmodel.Workflow\nimprovements for user\nconvenience.No\nimpact to the safety or\neffectiveness of the\ndevice."],"rows":[["Semi-Automation\nTechnology","As cleared","Semi-automated adult echocardiography 2D\nand Doppler measurements are generated\nusing an artificial intelligence (AI) detection\nalgorithm without user interaction. After\nmeasurement is generated, the user can edit\n(manually adjust the caliper positions),\naccept, or reject the measurements.The\nautomation of measurements is constrained\nto the specific imaging mode (2D, Doppler)\nas recommended by ASE guidelines.","Semi-automated adult\nechocardiography 2D and\nDoppler measurements are\ngenerated using an artificial\nintelligence (AI) detection\nalgorithm without user\ninteraction. After\nmeasurement is generated,\nthe user can edit (manually\nadjust the caliper positions),\naccept, or reject the\nmeasurements.The\nautomation of measurements\nis constrained to the specific\nimaging mode (2D, Doppler)\nas recommended by ASE\nguidelines.","Subject of submission;\nProposed feature\nincludes optional semi-\nautomation of existing\nmeasurements\navailable to the end\nuser during routine\nultrasound exam\nsimilar to reference\ndevice. Semi-\nautomated\nmeasurements\nquantify image data\nthrough an AI-based\nalgorithm that was\ntrained with a\nmachine-learning\nmodel.Workflow\nimprovements for user\nconvenience.No\nimpact to the safety or\neffectiveness of the\ndevice."],["User Interface\nPresentation","As cleared","User selects an adult echocardiography 2D\nor Doppler measurement to perform then the\ncaliper positions are initialized based on the\noutput of the AI detection algorithm.\nThe user can edit, accept, or reject the\nmeasurements.","User selects an adult\nechocardiography 2D or\nDoppler measurement to\nperform then the caliper\npositions are initialized based\non the output of the AI\ndetection algorithm.\nThe user can edit, accept, or\nreject the measurements.","Similar to predicate\nand reference device.\nThe set of available\nmeasurements are\nunchanged to the\npredicate device.\nWorkflow\nimprovements for user\nconvenience.\nNo impact to the safety\nor effectiveness of the\ndevice."]],"caption_candidate":"TOMTEC-ARENA (TTA2.50)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p6-t0","doc_id":"K213566","page_num":6,"bbox":[108.26,72.24,536.74,506.83],"n_rows":11,"n_cols":3,"columns":["","Predicate:\nAIMI-Triage CXR PTX\n(RADLogics, Inc.)\nK193300","Subject Device:\nClearRead Xray\nPneumothorax\n(Riverain Technologies, Inc.)\nK213566"],"rows":[["","Predicate:\nAIMI-Triage CXR PTX\n(RADLogics, Inc.)\nK193300","Subject Device:\nClearRead Xray\nPneumothorax\n(Riverain Technologies, Inc.)\nK213566"],["Product Code","QFM","QFM"],["Intended Use","The AIMI-Triage CXR PTX\nprovides a chest X-ray\nprioritization service for use\nby radiologists to identify\nfeatures suggestive of\nmoderate to large sized\npneumothorax.","ClearRead Xray\nPneumothorax provides a\nchest X-ray prioritization\nservice for use by radiologists\nto identify features suggestive\nof pneumothoraces in a\nPA/AP chest x-ray scan."],["Intended User","Radiologist","Radiologist"],["Modality","X-ray","X-ray"],["Anatomical Region","Lungs","Lungs"],["Clinical Condition","Pneumothorax","Pneumothorax"],["Notification /\nPrioritization","Yes, passive","Yes, passive"],["ROI Segmentation","No","No"],["Algorithm","Artificial intelligence\nalgorithm with database of\nimages","Machine learning and image\nprocessing"],["Alteration of input\nimages","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p7-t0","doc_id":"K213566","page_num":7,"bbox":[203.45,575.74,444.7,656.86],"n_rows":4,"n_cols":2,"columns":["AUC","0.974"],"rows":[["AUC","0.974"],["Sensitivity","0.922"],["Specificity","0.951"],["Time to Notification","9.73 seconds"]],"caption_candidate":"Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p8-t0","doc_id":"K213566","page_num":8,"bbox":[252.17,389.69,395.95,508.27],"n_rows":8,"n_cols":2,"columns":["Manufacturer","# of cases"],"rows":[["Manufacturer","# of cases"],["Carestream","782"],["GE","220"],["Fuji","117"],["Kodak","12"],["Agfa","3"],["Other","4"],["Total","1138"]],"caption_candidate":"Data distribution with respect to device characteristics are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p9-t0","doc_id":"K213566","page_num":9,"bbox":[179.93,72.24,467.98,251.09],"n_rows":12,"n_cols":3,"columns":["","# of cases",""],"rows":[["","# of cases",""],["Disease","PTX","No PTX"],["Atelectasis","87","108"],["Cardiomegaly","30","112"],["Consolidation","23","20"],["Edema","15","69"],["Enlarged Cardiomediastinum","9","13"],["Fracture","23","11"],["Lung Lesion/mass","21","34"],["Lung Opacity","43","131"],["Pleural Effusion","115","114"],["Pneumonia","5","20"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p9-t1","doc_id":"K213566","page_num":9,"bbox":[179.93,354.17,467.98,428.71],"n_rows":5,"n_cols":3,"columns":["","# of cases",""],"rows":[["","# of cases",""],["Gender","PTX","No PTX"],["Male","227","328"],["Female","176","319"],["Unknown","56","32"]],"caption_candidate":"Table 5.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213566-p11-t0","doc_id":"K213566","page_num":11,"bbox":[143.3,398.09,504.7,446.95],"n_rows":2,"n_cols":6,"columns":["Image\nPerformance","TP","FP","FN","Se","Sp"],"rows":[["Image\nPerformance","TP","FP","FN","Se","Sp"],["Threshold of 0.50","278","7","22","92.7%","97.7%"]],"caption_candidate":"found below in Table 6.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213583-p5-t0","doc_id":"K213583","page_num":5,"bbox":[72.26,130.22,544.66,662.5],"n_rows":17,"n_cols":3,"columns":["Date Prepared:","Nov. 10, 2021",""],"rows":[["Date Prepared:","Nov. 10, 2021",""],["Manufacturer:","Philips Medical Systems Nederland B.V.\nVeenpluis 4-6, 5684 PC, Best, The Netherlands\nEstablishment Registration Number: 3003768277",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","Jan van de Kerkhof\nSr. Manager Regulatory Affairs\nTelephone: +31 613300542\nE-mail: jan.van.de.kerkhof@philips.com\nSusan Quick\nRegulatory Affairs Specialist\nTelephone: (440) 8694612\nE-mail: susan.quick@philips.com",""],["Device Name:","Achieva, Ingenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR\nSystems",""],["Classification:","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification\nRegulation:","21CFR 892.1000"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary Product Code:","90LNH\n90LNI"],["Primary Predicate\nDevice:","Trade name:","Achieva, Intera, Ingenia, Ingneia CX, Ingenia\nElition, And Ingenia Ambition MR Systems\nR5.7"],["","Manufacturer:","Philips Medical Systems Nederland B.V."],["","510(k) Clearance:","K193215"],["","Classification\nRegulation:","21CFR 892.1000"],["","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","90LNH\n90LNI"]],"caption_candidate":"CFR §807.92.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213583-p7-t0","doc_id":"K213583","page_num":7,"bbox":[72.26,78.6,540.1,685.78],"n_rows":2,"n_cols":2,"columns":["","1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils"],"rows":[["","1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils"],["Indications for\nUse:","There are no changes to the indications for use statement, provided\nbelow, of the proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems.\nPhilips Magnetic Resonance (MR) systems are Medical Electrical\nSystems indicated for use as a diagnostic device.\nThis MR system enables trained physicians to obtain cross-sectional\nimages, spectroscopic images and/or spectra of the internal structure of\nthe head, body or extremities, in any orientation, representing the spatial\ndistribution of protons or other nuclei with spin.\nImage appearance is determined by many different physical properties\nof the tissue and the anatomy, the MR scan technique applied, and\npresence of contrast agents.\nThe use of contrast agents for diagnostic imaging applications should be\nperformed consistent with the approved labeling for the contrast agent.\nThe trained clinical user can adjust the MR scan parameters to\ncustomize image appearance, accelerate image acquisition, and\nsynchronize with the patient’s breathing or cardiac cycle. The systems\ncan use combinations of images to produce physical parameters, and\nrelated derived images. Images, spectra, and measurements of physical\nparameters, when interpreted by a trained physician, provide information\nthat may assist diagnosis and therapy planning. The accuracy of\ndetermined physical parameters depends on system and scan\nparameters and must be controlled and validated by the clinical user.\nIn addition, the Philips MR systems provide imaging capabilities, such\nas MR fluoroscopy, to guide and evaluate interventional and minimally\ninvasive procedures in the head, body and extremities. MR\nInterventional procedures, performed inside or adjacent to the Philips\nMR system, must be performed with MR Conditional or MR Safe\ninstrumentation as selected and evaluated by the clinical user for use\nwith the specific MR system configuration in the hospital. The\nappropriateness and use of information from a Philips MR system for a\nspecific interventional procedure and specific MR system configuration\nmust be validated by the clinical user."]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213583-p8-t0","doc_id":"K213583","page_num":8,"bbox":[72.26,78.6,540.1,698.02],"n_rows":2,"n_cols":2,"columns":["Design Features/\nFundamental\nScientific\nTechnology:","The proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems are based on the principle that certain\natomic nuclei present in the human body will emit a weak relaxation\nsignal when placed in a strong magnetic field and excited by a radio\nsignal at the precession frequency. The emitted relaxation signals are\nanalyzed by the system and a computed image reconstruction is\ndisplayed on a video screen.\nThe principal technological components (magnet, transmit body coil,\ngradient coil, gradient amplifier, RF amplifier and patient support) of the\nproposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia\nAmbition MR Systems are identical to those used in the legally\nmarketed predicate device Achieva, Intera, Ingenia, Ingenia CX,\nIngenia Elition and Ingenia Ambition MR systems R5.7 (K193215,\n04/10/2020).\nThe software R11 used on the proposed Achieva, Ingenia, Ingenia\nCX, Ingenia Elition and Ingenia Ambition MR Systems has been\nmodified to include the SmartSpeed AI feature combining the\npreviously cleared and legally marketed feature Compressed-SENSE\n(K193215, 04/10/2020) with machine learning to allow for higher\naccelerations with equal or better image quality."],"rows":[["Design Features/\nFundamental\nScientific\nTechnology:","The proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems are based on the principle that certain\natomic nuclei present in the human body will emit a weak relaxation\nsignal when placed in a strong magnetic field and excited by a radio\nsignal at the precession frequency. The emitted relaxation signals are\nanalyzed by the system and a computed image reconstruction is\ndisplayed on a video screen.\nThe principal technological components (magnet, transmit body coil,\ngradient coil, gradient amplifier, RF amplifier and patient support) of the\nproposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia\nAmbition MR Systems are identical to those used in the legally\nmarketed predicate device Achieva, Intera, Ingenia, Ingenia CX,\nIngenia Elition and Ingenia Ambition MR systems R5.7 (K193215,\n04/10/2020).\nThe software R11 used on the proposed Achieva, Ingenia, Ingenia\nCX, Ingenia Elition and Ingenia Ambition MR Systems has been\nmodified to include the SmartSpeed AI feature combining the\npreviously cleared and legally marketed feature Compressed-SENSE\n(K193215, 04/10/2020) with machine learning to allow for higher\naccelerations with equal or better image quality."],["Summary of Non-\nClinical\nPerformance Data:","The proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems are compliance with the following\ninternational and FDA-recognized consensus standards:\n• IEC60601-1 Edition 3\n• IEC60601-1-2 Edition 4\n• IEC60601-1-6 Edition 3\n• IEC62366-1 Edition 1\n• IEC60601-1-8 Edition 2\n• IEC60601-2-33 Edition 3\n• IEC 62304 Edition 1\n• NEMA MS-1 2008\n• NEMA MS-4 2010\n• NEMA MS-8 2008\n• NEMA PS 3.1-PS 3.20\n• ISO 14971 Edition 2\n• Device specific guidance document, entitled “Guidance for the\nSubmission Of Premarket Notifications for Magnetic Resonance\nDiagnostic Devices” (issued November 18, 2016 – document\nnumber 340)\n• Guidance for Industry and FDA Staff – Guidance for the\nContent of Premarket Submissions for Software Contained in\nMedical Devices (issued May 11, 2005 – document number\n337)\n• Guidance for Industry and FDA Staff – Content of Premarket\nSubmissions for Management of Cybersecurity in Medical\nDevices (issued October 2, 2014 – document number 1825)"]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213583-p10-t0","doc_id":"K213583","page_num":10,"bbox":[72.26,78.6,540.1,638.98],"n_rows":3,"n_cols":2,"columns":["","Ambition MR Systems meet the acceptance criteria and are adequate\nfor the intended use.\nAdditionally, the risk management activities show that all risks are\nsufficiently mitigated; that new risks that were identified are mitigated to\nan acceptable level; and that the overall residual risk is acceptable.\nTherefore, the proposed Achieva, Ingenia, Ingenia CX, Ingenia\nElition and Ingenia Ambition MR Systems are substantially\nequivalent to the legally marketed predicate devices Achieva, Intera,\nIngenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR\nsystems R5.7 (K193215, 04/10/2020), in terms of safety and\neffectiveness."],"rows":[["","Ambition MR Systems meet the acceptance criteria and are adequate\nfor the intended use.\nAdditionally, the risk management activities show that all risks are\nsufficiently mitigated; that new risks that were identified are mitigated to\nan acceptable level; and that the overall residual risk is acceptable.\nTherefore, the proposed Achieva, Ingenia, Ingenia CX, Ingenia\nElition and Ingenia Ambition MR Systems are substantially\nequivalent to the legally marketed predicate devices Achieva, Intera,\nIngenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR\nsystems R5.7 (K193215, 04/10/2020), in terms of safety and\neffectiveness."],["Summary of\nClinical Data:","The proposed Ingenia Achieva, Ingenia, Ingenia CX, Ingenia Elition\nand Ingenia Ambition MR Systems did not require a clinical study\nsince substantial equivalence to the legally marketed predicate device\nwas proven with the verification/validation testing."],["Substantial\nEquivalence:\nConclusion:","The proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems and the legally marketed predicate\ndevice Achieva, Intera, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR systems R5.7 (K193215, 04/10/2020), have the\nsame indications for use with respect to the following:\n• Providing cross-sectional images based on the magnetic resonance\nphenomenon\n• Interpretation of the images is the responsibility of trained\nphysicians\n• Images can be used for interventional and treatment planning\npurposes\nThe proposed Achieva, Ingenia, Ingenia CX, Ingenia Elition and\nIngenia Ambition MR Systems are substantially equivalent to the\nlegally marketed predicate device Achieva, Intera, Ingenia, Ingenia\nCX, Ingenia Elition and Ingenia Ambition MR systems R5.7\n(K193215, 04/10/2020), in terms of design features, fundamental\nscientific technology, indications for use, and safety and effectiveness.\nAdditionally, substantial equivalence is demonstrated with non-clinical\nperformance (verification and validation) tests, which complied with the\nrequirements specified in the international and FDA-recognized\nconsensus standards and device-specific guidance.\nThe results of these tests demonstrate that the proposed Achieva,\nIngenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR\nSystems meet the acceptance criteria and are adequate for the intended\nuse."]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213603-p4-t0","doc_id":"K213603","page_num":4,"bbox":[108.0,133.32,540.0,697.5],"n_rows":13,"n_cols":2,"columns":["Date:","November 12, 2021"],"rows":[["Date:","November 12, 2021"],["Submitter:","GE Healthcare (GE Healthcare (Tianjin) Company Limited)\nNo. 266 Jingsan Road,Tianjin Airport Economic Area\nTianjin, China 300308"],["Primary\nContact\nPerson:","Qiang Ding\nRegulatory Affairs Program Manager\nPhone: +86 13311385163\nEmail: Ding.Qiang@ge.com"],["Secondary\nContact\nPerson:","Glen Sabin\nRegulatory Affairs Director\nPhone: 262-894-4968\nEmail: Glen.Sabin@ge.com"],["Device Trade\nName:","SIGNATM Artist Evo"],["Common/Usual\nName:","Magnetic Resonance Diagnostic Device"],["Classification\nNames:","Magnetic Resonance Diagnostic Device"],["Regulation\nNumber:","21 CFR 892.1000"],["Primary\nProduct Code:","LNH"],["Secondary\nProduct Code:","LNI, MOS"],["Predicate\nDevice:","SIGNATM Artist (K202238)"],["Reference\nDevice","SIGNA Architect (K202966)"],["Device\nDescription:","The SIGNATM Artist Evo system is a whole body magnetic resonance\nscanner designed to support high resolution, high signal-to-noise\nratio, and short scan times. The system features a superconducting\nmagnet. The data acquisition system accommodates up to 128\nindependent receive channels in various increments and multiple\nindependent coil elements per channel during a single acquisition\nseries. The system uses a combination of time varying magnetic fields\n(gradients) and RF transmissions to obtain information regarding the\ndensity and position of elements exhibiting magnetic resonance. The\nsystem can image in the sagittal, coronal, axial, oblique, and double"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213603-p5-t0","doc_id":"K213603","page_num":5,"bbox":[108.0,72.24,540.0,699.0],"n_rows":4,"n_cols":2,"columns":["","oblique planes, using various pulse sequences and reconstruction\nalgorithms."],"rows":[["","oblique planes, using various pulse sequences and reconstruction\nalgorithms."],["Indications for\nUse:","The Indications for Use statement for the proposed device is\nidentical to that of the predicate device:\nThe SIGNATM Artist Evo system is a whole-body magnetic\nresonance scanner designed to support high resolution, high\nsignal-to-noise ratio, and short scan times. It is indicated for use as\na diagnostic imaging device to produce axial, sagittal, coronal, and\noblique images, spectroscopic images, parametric maps, and/or\nspectra, dynamic images of the structures and/or functions of the\nentire body, including, but not limited to, head, neck, TMJ, spine,\nbreast, heart, abdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body. Depending on the region of\ninterest being imaged, contrast agents may be used.\nThe images produced by the SIGNATM Artist Evo system reflect the\nspatial distribution or molecular environment of nuclei exhibiting\nmagnetic resonance. These images and/or spectra when\ninterpreted by a trained physician yield information that may assist\nin diagnosis."],["Technology\nCharacteristics:","Many of the technological characteristics of the proposed SIGNATM\nArtist Evo system are unchanged from the predicate device. The\nSIGNATM Artist Evo system reuses GE Healthcare 1.5T LCC\nmagnets in the installed base, and introduces the new IRMW\ngradient coil. There are no changes to the RF transmit and receive\nsubsystems compared to the predicate K202238. Key performance\nspecifications (such as magnet stability and spatial homogeneity,\nmaximum gradient strength, etc.) for the system are also\nunchanged.\nThe SIGNATM Artist Evo system also uses the same version\nsoftware as the predicate device with some minor changes to\naccommodate the hardware differences. There are no changes to\nthe pulse sequences, imaging protocols and image processing."],["Determination\nof\nSubstantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe SIGNATM Artist Evo and the predicate device were subject to\nsimilar risk management activities and performance testing to\ndemonstrate substantial equivalence of safety and performance.\nTesting included compliance to the following voluntary standards:\n AAMI/ANSI ES60601-1\n IEC 60601-1-2\n IEC 60601-2-33\n AAMI/ANSI 62304\n ISO 10993-1"]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213603-p6-t0","doc_id":"K213603","page_num":6,"bbox":[108.0,72.24,540.0,678.54],"n_rows":2,"n_cols":2,"columns":["","In addition, the SIGNATM Artist Evo was tested in accordance with\napplicable NEMA MS standards for MRI, and complies with the\nNEMA PS3 standard for DICOM, as does the predicate device.\nBoth the SIGNATM Artist Evo and the predicate device are\ncompliant with ISO 10993.\nThe following quality assurance measures were applied to the\ndevelopment of the subject device, as they were for the predicate\ndevice:\n Risk Analysis\n Requirements Reviews\n Design Reviews\n Testing on unit level (Module verification)\n Integration testing (System verification)\n Performance testing (Verification)\n Simulated use testing (Validation)\nSummary of Clinical Tests:\nThe subject of this premarket submission, the SIGNATM Artist Evo,\ndid not require clinical studies to support substantial equivalence.\nSample clinical images have been included in this submission. The\nsample clinical images demonstrate acceptable diagnostic image\nperformance of the SIGNATM Artist Evo in accordance with the FDA\nGuidance “Submission of Premarket Notifications for Magnetic\nResonance Diagnostic Devices” issued on November 18, 2016.\nThe image quality of the SIGNATM Artist Evo is substantially\nequivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNATM Artist Evo employs\nequivalent technology to the claimed predicate device. Additionally,\nthe results from the above non-clinical tests demonstrate that the\ndevice performs as intended. Therefore, the SIGNATM Artist Evo is\nsubstantially equivalent to the predicate device to which it has been\ncompared."],"rows":[["","In addition, the SIGNATM Artist Evo was tested in accordance with\napplicable NEMA MS standards for MRI, and complies with the\nNEMA PS3 standard for DICOM, as does the predicate device.\nBoth the SIGNATM Artist Evo and the predicate device are\ncompliant with ISO 10993.\nThe following quality assurance measures were applied to the\ndevelopment of the subject device, as they were for the predicate\ndevice:\n Risk Analysis\n Requirements Reviews\n Design Reviews\n Testing on unit level (Module verification)\n Integration testing (System verification)\n Performance testing (Verification)\n Simulated use testing (Validation)\nSummary of Clinical Tests:\nThe subject of this premarket submission, the SIGNATM Artist Evo,\ndid not require clinical studies to support substantial equivalence.\nSample clinical images have been included in this submission. The\nsample clinical images demonstrate acceptable diagnostic image\nperformance of the SIGNATM Artist Evo in accordance with the FDA\nGuidance “Submission of Premarket Notifications for Magnetic\nResonance Diagnostic Devices” issued on November 18, 2016.\nThe image quality of the SIGNATM Artist Evo is substantially\nequivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNATM Artist Evo employs\nequivalent technology to the claimed predicate device. Additionally,\nthe results from the above non-clinical tests demonstrate that the\ndevice performs as intended. Therefore, the SIGNATM Artist Evo is\nsubstantially equivalent to the predicate device to which it has been\ncompared."],["Conclusion\nDrawn from\nPerformance\nTesting:","The proposed SIGNATM Artist Evo system has been developed\nunder GE Healthcare’s quality system and is at least as safe and\neffective as the legally marketed predicate. The performance testing\ndid not identify any new hazards, adverse effects, or safety or\nperformance concerns that are significantly different from those\nassociated with MR imaging in general.\nTherefore, GE Healthcare believes that SIGNATM Artist Evo is\nsubstantially equivalent to the predicate device, and is safe and\neffective for its intended use."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213628-p4-t0","doc_id":"K213628","page_num":4,"bbox":[72.67,251.06,536.26,324.89],"n_rows":4,"n_cols":2,"columns":["Contact Person:","Vicki Lin"],"rows":[["Contact Person:","Vicki Lin"],["Phone:","609-865-8659"],["Email:","vicki.lin@vysioneer.com"],["Date Summary Prepared:","November 1(cid:21), 2021"]],"caption_candidate":"33 Rogers St. #308, Cambridge, MA 02142","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213628-p4-t1","doc_id":"K213628","page_num":4,"bbox":[72.67,381.41,536.26,502.75],"n_rows":8,"n_cols":2,"columns":["Trade Name:","VBrain"],"rows":[["Trade Name:","VBrain"],["Common Name:","Radiological Image Processing Software for\nRadiation Therapy"],["",""],["Classification Name:","Medical image management and processing\nsystem(21 CFR 892.2050)"],["",""],["Regulatory Class:","II"],["",""],["Product Code:","QKB"]],"caption_candidate":"Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213668-p5-t0","doc_id":"K213668","page_num":5,"bbox":[108.24,118.08,539.76,687.0],"n_rows":10,"n_cols":2,"columns":["Date:","Nov 19, 2021"],"rows":[["Date:","Nov 19, 2021"],["Submitter:","GE Medical Systems, LLC\n3200 N Grandview Blvd.\nWaukesha, WI USA 53188"],["Primary Contact\nPerson:","Sandra Westphal\nRegulatory Affairs Leader\nGE Healthcare\nPhone: 262-720-8872\nE-mail: Sandra.westphal@ge.com"],["Secondary\nContact Person:","Glen Sabin\nDirector, Regulatory Affairs\nGE Healthcare\nPhone: 262-521-6848\nE-mail: glen.sabin@ge.com"],["Device Trade\nName:","SIGNA™ Hero"],["Common/Usual\nName:","Magnetic Resonance Diagnostic Device"],["Classification\nNames:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH, LNI"],["Predicate\nDevice(s):","SIGNA™ Pioneer (K160621)"],["Device\nDescription:","SIGNA™ Hero is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal to-noise ratio, and\nshort scan times. The systems use a combination of time-varying\nmagnet fields (Gradients) and RF transmissions to obtain\ninformation regarding the density and position of elements\nexhibiting magnetic resonance. The system can image in the"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213668-p6-t0","doc_id":"K213668","page_num":6,"bbox":[108.24,72.24,539.76,642.96],"n_rows":3,"n_cols":2,"columns":["","sagittal, coronal, axial, oblique, and oblique planes, using various\npulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 3.0T superconducting magnet\nwith 70cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],"rows":[["","sagittal, coronal, axial, oblique, and oblique planes, using various\npulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 3.0T superconducting magnet\nwith 70cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],["Indications for\nUse","The SIGNA™ Hero is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and\nshort scan times. It is indicated for use as a diagnostic imaging\ndevice to produce axial, sagittal, coronal, and oblique images,\nspectroscopic images, parametric maps, and/or spectra, dynamic\nimages of the structures and/or functions of the entire body,\nincluding, but not limited to, head, neck, TMJ, spine, breast, heart,\nabdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body.\nDepending on the region of interest being imaged, contrast agents\nmay be used. The images produced by SIGNA™ Hero\nreflect the spatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance.\nThese images and/or spectra when interpreted by a trained\nphysician yield information that may assist in diagnosis."],["Technology:","The SIGNA™ Hero employs the same fundamental scientific\ntechnology as its predicate device.\nSIGNA™ Hero offers two magnet configurations, building on the\n3.0T 3TLC magnet, and introducing the newly designed 3.0T\nARES (Platform) magnet. SIGNA™ Hero builds on the existing\nGradient Driver design, RF transmit architecture design, RF\nreceive chain design and software platform. SIGNA™ Hero offers\na detachable eXpress patient table, similar to detachable tables\navailable on other GEHC 3T MR systems."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213668-p7-t0","doc_id":"K213668","page_num":7,"bbox":[108.24,72.24,539.76,688.68],"n_rows":3,"n_cols":2,"columns":["Comparison of\nIndications\nfor Use","The changes in technology do not impact the indications for use.\nThe indications for use have not changed, other than to reflect the\nSIGNA™ Hero product name.\nTherefore, the intended use is the same as the predicate device in\naccordance with the FDA’s guidance document “The 510(k)\nProgram: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],"rows":[["Comparison of\nIndications\nfor Use","The changes in technology do not impact the indications for use.\nThe indications for use have not changed, other than to reflect the\nSIGNA™ Hero product name.\nTherefore, the intended use is the same as the predicate device in\naccordance with the FDA’s guidance document “The 510(k)\nProgram: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],["Comparison of\nTechnological\nCharacteristics","Overall, the SIGNA™ Hero employs the same fundamental\nscientific technology as the predicate device.\nSystem Design: There are one notable technological difference\nbetween the SIGNA™ Hero and the predicate device: the 3.0T\nARES (Platform) magnet.\nOperating Principles: The SIGNA™ Hero functions using the\nsame operating principles as the predicate device.\nMaterials: The SIGNA™ Hero and the predicate device both use\nflame retardant materials.\nSafety and Performance Testing: Both the SIGNA™ Hero and\nthe predicate device comply with the same safety and performance\ntesting (see Determination of Substantial Equivalence, below).\nThese technological differences do not raise any different\nquestions regarding safety and effectiveness. Both devices must\naddress questions of whether they provide an adequate level of\nimage quality appropriate for diagnostic use. The performance\ndata described in this submission include results of both bench\ntesting and clinical testing that show the image quality\nperformance of SIGNA™ Hero compared to the predicate device."],["Determination of\nSubstantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe SIGNA™ Hero and the predicate device were subject to\nsimilar risk management testing to demonstrate substantial\nequivalence of safety and performance.\nTesting to the following voluntary standards included:\n• ANSI/AAMI ES60601-1\n• IEC 60601-1-2"]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213668-p9-t0","doc_id":"K213668","page_num":9,"bbox":[108.24,72.24,539.76,282.0],"n_rows":2,"n_cols":2,"columns":["","Substantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNA™ Hero employs\nequivalent technology to the claimed predicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Hero is substantially equivalent to the predicate device to\nwhich it has been compared."],"rows":[["","Substantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate device. The SIGNA™ Hero employs\nequivalent technology to the claimed predicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Hero is substantially equivalent to the predicate device to\nwhich it has been compared."],["Conclusion:","In conclusion, GE Healthcare considers the SIGNA™\nHero to be as safe, as effective, with performance that\nis substantially equivalent to the predicate device."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213693-p6-t0","doc_id":"K213693","page_num":6,"bbox":[94.41,460.08,499.69,504.09],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA31A","K203443, cleared March\n31, 2021","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213693-p7-t0","doc_id":"K213693","page_num":7,"bbox":[94.33,378.57,494.11,691.77],"n_rows":26,"n_cols":2,"columns":["Feature / Function","Clinical Publication"],"rows":[["Feature / Function","Clinical Publication"],["Deep Resolve Swift\nBrain","[1] Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE:"],["","Sensitivity encoding for fast MRI. Magn Reson Med. 1999;42:952-962."],["",""],["","[2] Hyun CM, Kim HP, Lee SM, Lee S, Seo JK. Deep learning for"],["","undersampled MRI reconstruction. Phys Med Biol. 2018;63(13):135007."],["","doi:10.1088/1361-6560/aac71a"],["",""],["","[3] Wang S, Su Z, Ying L, et al. Accelerating magnetic resonance imaging"],["","via deep learning. In: 2016 IEEE 13th International Symposium on"],["","Biomedical Imaging (ISBI). Prague, Czech Republic: IEEE; 2016:514-517."],["","doi:10.1109/ISBI.2016.7493320"],["",""],["","[4] Yu S, Park B, Jeong J. Deep iterative down-up CNN for image"],["","denoising. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit.; 2019:9."],["",""],["","[5] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D."],["","Σ-net: Systematic evaluation of iterative deep neural networks for fast"],["","parallel MR image reconstruction. ArXiv191209278 Cs Eess. December"],["","2019. http://arxiv.org/abs/1912.09278. Accessed January 9, 2020."],["",""],["","[6] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D."],["","Systematic evaluation of iterative deep neural networks for fast parallel"],["","MRI reconstruction with sensitivity-weighted coil combination. Magn."],["","Reson. Med. 2021;86(4):1859-1872. doi:10.1002/mrm.28827"],["",""]],"caption_candidate":"of the following features and functions.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213693-p8-t0","doc_id":"K213693","page_num":8,"bbox":[94.2,87.26,494.21,714.54],"n_rows":22,"n_cols":2,"columns":["","[7] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality"],"rows":[["","[7] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality"],["","assessment: From error visibility to structural similarity. IEEE Trans Image"],["","Process. 2004;13(4):600-612. doi:10.1109/TIP.2003.819861"],["",""],["","[8] Schlemper J, Caballero J, Hajnal JV, Price AN, Rueckert D. A deep"],["","cascade of convolutional neural networks for dynamic MR image"],["","reconstruction,” IEEE Trans. Med. Imag. 2018;37:491-503"],["",""],["","[9] Zbontar J, Knoll F, Sriram A, et al. fastMRI: An open dataset and"],["","benchmarks for accelerated MRI. arXiv:181108839 [physics, stat]."],["","December 2019. http://arxiv.org/abs/1811.08839. Accessed March 5,"],["","2020."],["",""],["","[10] Demir et al., Optimization of Magnetization Transfer Contrast for EPI\nFLAIR Brain Imaging, Proceedings of the ISMRM 2021, abstract 4179"],["","[11] Clifford et al., Clinical evaluation of an AI-accelerated two-minute\nmulti-shot EPI protocol for comprehensive high-quality brain imaging,\nProceedings of the ISMRM 2021, abstract 300"],["","[12] Filho et al., Clinical Evaluation of An AI-Accelerated Two-Minute\nMulti-Shot EPI Protocol For Comprehensive High-Quality Brain MRI In An\nEmergency And Inpatient Setting, Proceedings of the RSNA 2021,\naccepted, abstract 16890"],["","[13] Pistocchi et al., AI-enhanced multi-shot multi-contrast EPI protocol:\nPreliminary clinical experience, Proceedings of the ECR 2022, submitted"],["Deep Resolve Boost","[14] Gassenmaier S et al., Deep learning–accelerated T2-weighted\nimaging of the prostate: Reduction of acquisition time and improvement\nof image quality, European Journal of Radiology, 137 (2021)"],["","[15] Herrmann J et al., Diagnostic Confidence and Feasibility of a Deep\nLearning Accelerated HASTE Sequence of the Abdomen in a Single\nBreath-Hold, Investigative Radiology, Volume 56, Number 5, May 2021"],["","[16] Shanbhogue K et al. Accelerated single-shot T2-weighted fat-\nsuppressed (FS) MRI of the liver with deep learning-based image\nreconstruction: qualitative and quantitative comparison of image quality\nwith conventional T2-weighted FS sequence. Eur Radiol. 2021 May 7."],["","[17] Herrmann J et al., Development and Evaluation of Deep Learning-\nAccelerated Single-Breath-Hold Abdominal HASTE at 3 T Using Variable\nRefocusing Flip Angles. Invest Radiol. 2021 Apr 22."],["","[18] Gassenmaier S et al., Accelerated T2-Weighted TSE Imaging of the\nProstate Using Deep Learning Image Reconstruction: A Prospective\nComparison with Standard T2-Weighted TSE Imaging, Cancers, 13,\n3593 (2021)"]],"caption_candidate":"5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213693-p9-t0","doc_id":"K213693","page_num":9,"bbox":[94.2,87.18,494.28,630.78],"n_rows":11,"n_cols":2,"columns":["","[19] Herrmann J et al., Feasibility and implementation of a Deep Learning\nMR reconstruction for TSE sequences in musculoskeletal imaging,\nDiagnostics, 11, 1484 (2021)"],"rows":[["","[19] Herrmann J et al., Feasibility and implementation of a Deep Learning\nMR reconstruction for TSE sequences in musculoskeletal imaging,\nDiagnostics, 11, 1484 (2021)"],["","Publications under review:\n[20] Judith Herrmann et al., Feasibility and diagnostic confidence of deep\nlearning reconstructed TSE imaging of the knee at 1.5 and 3 T. A\nprospective study."],["BLADE_Diffusion","[21] Alsop, D. C. (1997). Phase insensitive preparation of single\nshot RARE: application to diffusion imaging in humans. Magnetic\nresonance in medicine, 527-533."],["","[22] Fu, Q., Kong, X.-c., Liu, D.-x., Guo, Y.-h., Zhou, K., Lei, Z.-q., &\nZheng, C.-s. (2021). Clinical utility of turbo gradient and spin echo\nBLADE-DWI (TGSE-BLADE-DWI) for orbital tumors compared\nwith readout-segmented echo-planar DWI. Proc. Intl. Soc. Mag.\nReson. Med., (p. 3933)."],["","[23] Fu, Q., Kong, X.-c., Liu, D.-x., Guo, Y.-h., Zhou, K., Lei, Z.-q., &\nZheng, C.-s. (2021). The efficacy 2D turbo gradient- and spin-echo\ndiffusion-weighted imaging for cerebellopontine angle tumors.\nProc. Intl. Soc. Mag. Reson. Med., (p. 3934)."],["","[24] Hu, H. H., McAllister, A. S., Jin, N., Lubeley, L. J., Selvaraj, B.,Smith,\nM., . . . Zhou, K. (2019). Comparison of 2D BLADE turbo gradient-and\nspin-Echo and 2D spin-Echo Echo-planar diffusion-weighted brain MRI at\n3 T: preliminary experience in children. Academic radiology, 1597-1604."],["","[25] Pipe, J. G., Farthing, V. G., & Forbes, K. P. (2002). Multishot\nDiffusion-Weighted FSE UsingPROPELLER MRI. Magnetic Resonance\nin Medicine , 42-52."],["","[26] Sheng, Y., Hong, R., Sha, Y., Zhang, Z., Zhou, K., & Fu, C. (2020).\nPerformance of TGSE BLADE DWI compared with RESOLVE DWI in the\ndiagnosis of cholesteatoma. BMC medical imaging, 1-9."],["","[27] Srinivasan, G., Rangwala, N., & Zhou, X. J. (2018). Steer-PROP: a\nGRASE-PROPELLER sequence with interecho steering gradient pulses.\nMagnetic resonance in medicine, 2533-2541."],["","[28] Yuan, T., Sha, Y., Zhang, Z., Liu, X., Ye, X., Sheng, Y., . . . Fu, C.\n(2020). TGSE diffusion-weighted pulse sequence in the evaluation of\noptic neuritis: Acomprehensive comparison of image quality with\nRESOLVE DWI. Proc. Intl. Soc. Mag. Reson. Med., (p. 4137)."],["","[29] Zhou, K., Liu, W., & Cheng, S. (2018). Non-CPMG PROPELLER\ndiffusion imaging: comparison of phase insensitive preparation with split\nacquisition. Proc. Intl. Soc. Mag. Reson. Med., (p. 5320)."]],"caption_candidate":"6","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213693-p10-t0","doc_id":"K213693","page_num":10,"bbox":[94.33,218.02,499.77,676.89],"n_rows":15,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognition","Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/\nEMC)","C1:2009/(R)2012 and\nA2:2010/(R)2012 (Consolidated\nText) Medical electrical\nequipment - Part 1: General\nrequirements for basic safety\nand essential performance (IEC\n60601-1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012","ANSI AAMI"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1:2015","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","62304:2006/A1:201\n6","ANSI AAMI\nIEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20\n(2016)","NEMA"],["12-331","Radiology","Characterization of\nRadiofrequency (RF) Coil\nHeating in Magnetic Resonance\nImaging Systems","Standards\nPublication MS 14-\n2019","NEMA"]],"caption_candidate":"FDA recognized and international IEC, ISO and NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p6-t0","doc_id":"K213706","page_num":6,"bbox":[72.29,547.96,539.76,714.42],"n_rows":5,"n_cols":6,"columns":["","Subject Device:\nAI-Rad Companion\nBrain MR VA40","","Predicate Device:","","Reference Device:\nicobrain (K192130)"],"rows":[["","Subject Device:\nAI-Rad Companion\nBrain MR VA40","","Predicate Device:","","Reference Device:\nicobrain (K192130)"],["","","","AI-Rad Companion","",""],["","","","Brain MR VA20","",""],["","","","(K193290)","",""],["Indications for\nUse","AI-Rad Companion\nBrain MR is a post-\nprocessing image\nanalysis software that\nassists clinicians in\nviewing, analyzing, and\nevaluating MR brain\nimages.","AI-Rad Companion\nBrain MR is a post-\nprocessing image\nanalysis software that\nassists clinicians in\nviewing, analyzing, and\nevaluating MR brain\nimages.","","","icobrain is intended\nfor automatic\nlabeling,\nvisualization and\nvolumetric\nquantification of\nsegmentable brain\nstructures"]],"caption_candidate":"raise different questions of the safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p8-t0","doc_id":"K213706","page_num":8,"bbox":[72.24,72.72,539.81,715.86],"n_rows":7,"n_cols":4,"columns":["","and volumetry of\nMPRAGE data.","and volumetry of\nMPRAGE data.","volumetry of\nMPRAGE data."],"rows":[["","and volumetry of\nMPRAGE data.","and volumetry of\nMPRAGE data.","volumetry of\nMPRAGE data."],["Brain\nMorphometry\nQuantification","Calculation of label\nmaps (display of brain\nsegmentation) and\npartially combined label\nmaps (fused with the\nprocessed MPRAGE\ndata).","Calculation of label\nmaps (display of brain\nsegmentation) and\npartially combined\nlabel maps (fused with\nthe processed\nMPRAGE data).","Normalized and\nunnormalized\nvolume and volume\nchanges of different\nbrain structures."],["Brain\nMorphometry:\nDeviation Map","Calculation of deviation\nmap (representation of\nbrain status in relation to\nreference data) and\npartially combined\ndeviation maps (fused\nwith the processed\nMPRAGE data) User\ncustomizable color labels\nfor the overlay map.","Calculation of\ndeviation map\n(representation of brain\nstatus in relation to\nreference data) and\npartially combined\ndeviation maps (fused\nwith the processed\nMPRAGE data) User\ncustomizable color\nlabels for the overlay\nmap.","Not available"],["Brain White\nMatter\nHyperintensities\nSegmentation","Pre-processing\nfunctionality for\nautomatic segmentation\nand volumetry of\nMPRAGE and FLAIR\ndata.","Not available","Image processing for\nautomatic\nsegmentation and\nvolumetry of FLAIR\ndata."],["Brain White\nMatter\nHyperintensities\nQuantification","Calculation of white\nmatter hyperintensities\ncount and volume as per\n4 brain regions.","Not available","Unnormalized\nvolume and volume\nchanges of FLAIR\nwhite matter\nhyperintensities as\nper 4 brain regions"],["Brain White\nMatter\nHyperintensities\nMap","Calculation of white\nmatter hyperintensities\nmap fused with the\nprocessed FLAIR data\nUser customizable color\nlabels for the overlay\nmap.","Not available","Calculation of white\nmatter\nhyperintensities map\noverlaid with the\nFLAIR data"],["Distribution &\nArchiving","Creation of an image\nseries for a morphometry","Creation of an image\nseries for a","Automatic transfer\nof generated image"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p9-t0","doc_id":"K213706","page_num":9,"bbox":[72.24,72.72,539.81,345.86],"n_rows":5,"n_cols":4,"columns":["","report. Automatic\ntransfer of generated\nmaps and morphometry\nreport to a PACS system.","morphometry report.\nAutomatic transfer of\ngenerated maps and\nmorphometry report to\na PACS system.","series and report to a\nPACS system."],"rows":[["","report. Automatic\ntransfer of generated\nmaps and morphometry\nreport to a PACS system.","morphometry report.\nAutomatic transfer of\ngenerated maps and\nmorphometry report to\na PACS system.","series and report to a\nPACS system."],["User Interface\nConfirmation","Confirmation UI with\nbasic visualization\nfunctionality","Confirmation UI with\nbasic visualization\nfunctionality","Not available."],["User Interface\nConfiguration","Configuration UI","Configuration UI","Not available"],["Architecture","Cloud solution and Edge\ncomponents deployed on\ncustomer premise.","Cloud only solution\nwith no components\ndeployed on customer\npremise.","Cloud only solution\nwith no components\ndeployed on\ncustomer premise."],["DICOM SR","DICOM structured\nreport representation of a\nnatural language report","Basic morphometry\nreport","DICOM structured\nreport"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p11-t0","doc_id":"K213706","page_num":11,"bbox":[73.4,72.87,538.63,214.34],"n_rows":6,"n_cols":4,"columns":["Validation Type","","","Acceptance Criteria"],"rows":[["Validation Type","","","Acceptance Criteria"],["Volumetric Segmentation Accuracy","","PCC 95% Confidence Interval includes 0.91",""],["","","ICC 95% Confidence Interval includes 0.95",""],["Voxel-wise Segmentation Accuracy","","Mean Dice score >= 0.58",""],["WMH Lesion-wise Segmentation Accuracy","","Mean F1-score >= 0.57",""],["Reproducibility","","Lower Bound of the 95% Bootstrap CI Dice >=\n0.63",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p11-t1","doc_id":"K213706","page_num":11,"bbox":[73.4,247.82,538.63,382.76],"n_rows":7,"n_cols":8,"columns":["","Volumetric Segmentation","","Voxel-wise\nSegmentation","","WMH Lesion-","","Reproducibility"],"rows":[["","Volumetric Segmentation","","Voxel-wise\nSegmentation","","WMH Lesion-","","Reproducibility"],["","","","","","wise","",""],["","","","","","Segmentation","",""],["","PCC","ICC","Dice","F1-score","","","Dice"],["AVG","0.98","0.97","0.60","0.60","","","0.79"],["STD","n.a.","n.a.","0.18","0.14","","","0.11"],["95% CI","[0.97,0.99]","[0.96,0.98]","[0.53,0.63]","[0.57,0.64]","","","[0.77,0.81]"]],"caption_candidate":"Summary Performance data, Standard Deviations & CIs:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p11-t2","doc_id":"K213706","page_num":11,"bbox":[73.4,442.96,538.63,613.66],"n_rows":6,"n_cols":3,"columns":["","Reproducibility Cohort","Testing Cohort"],"rows":[["","Reproducibility Cohort","Testing Cohort"],["# Subjects","25","64"],["# Studies","100","64"],["# of Females","12","35"],["# of Males","13","29"],["Age Range","23-55","19-83"]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213706-p12-t0","doc_id":"K213706","page_num":12,"bbox":[74.34,72.72,537.64,403.88],"n_rows":5,"n_cols":3,"columns":["Medical Indication","MS – all","MS – 36\nCognitive Impairment – 17\nOther neurological disease – 5\nCognitive Normal – 5\nUnknown – 1"],"rows":[["Medical Indication","MS – all","MS – 36\nCognitive Impairment – 17\nOther neurological disease – 5\nCognitive Normal – 5\nUnknown – 1"],["Scan Protocol","3D T1w MPRAGE\n3D T2w FLAIR","T1w MPRAGE\nT2w FLAIR"],["Field Strength","3T","1.5T: 30\n3.0T: 34"],["Manufacturer","Siemens","Siemens"],["Data Origin","Cleveland (US): 16\nBaltimore (US): 9","New York (US): 25\nADNI (US): 12\nLausanne (CH): 8\nCLEMENS (CH): 10\nMontpellier (FR): 9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213713-p7-t0","doc_id":"K213713","page_num":7,"bbox":[72.25,257.51,540.17,715.17],"n_rows":9,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","","AI-Rad Companion (Pulmonary)","","","AI-Rad Companion (Pulmonary)",""],["","","VA20","","","(K183271)",""],["Modality","CT","","","CT","",""],["Segmentation\nof lungs","Creation of a lung segmentation mask\nby combining the segmentation masks\nof 5 lung lobes.","","","Creation of a lung segmentation mask\nby combining the segmentation masks\nof 5 lung lobes.","",""],["Segmentation\nof lung lobes","Computation of segmentation masks\nof the five lung lobes (right upper\n(RUL), right middle (RML), right\nlower (RLL), left upper (LUL) and\nleft lower (LLL) lobe) for a given CT\ndata set of the chest.","","","Computation of segmentation masks\nof the five lung lobes (right upper\n(RUL), right middle (RML), right\nlower (RLL), left upper (LUL) and\nleft lower (LLL) lobe) for a given CT\ndata set of the chest.","",""],["Parenchyma\nevaluation","The parenchyma evaluation uses the\nlobe mask, counts all voxels per lobe,\ncounts image voxels below -950 HU,\nand calculates the percentages of\nthese voxels relative to the total\nnumber of voxels. Additionally, it\nsums the individual lobe results and\ncalculates the percentage for the\ncomplete lung.","","","The parenchyma evaluation uses the\nlobe mask, counts all voxels per lobe,\ncounts image voxels below -950 HU,\nand calculates the percentages of\nthese voxels relative to the total\nnumber of voxels. Additionally, it\nsums the individual lobe results and\ncalculates the percentage for the\ncomplete lung.","",""],["Parenchyma\nRanges","The percentages are likewise\ndedicated to the 4 ranges. Name of\nranges and their ranges are\nconfigurable by the user.","","","The percentages are likewise\ndedicated to the 4 ranges. Name of\nranges and their ranges are\nconfigurable by the user.","",""],["Pulmonary\nDensity","AI‐based identification of areas with\nelevated Hounsfield values.\nThreshold‐based identification of\nhighest elevated Hounsfield values","","","N/A","",""]],"caption_candidate":"following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213713-p8-t0","doc_id":"K213713","page_num":8,"bbox":[72.23,72.83,540.18,597.55],"n_rows":7,"n_cols":3,"columns":["","inside these elevated regions, by a\npredefined threshold of ‐200 HU",""],"rows":[["","inside these elevated regions, by a\npredefined threshold of ‐200 HU",""],["Visualization\nof\nsegmentation\nand\nparenchyma\nresults","Color overlay of MPR and VRT with\nevaluation results","Color overlay of MPR and VRT with\nevaluation results"],["Interface to\nLungCAD","Interface to syngo.CT LungCAD","Interface to syngo.CT LungCAD"],["Lesion\nsegmentation","Segmentation of lung lesions\nincluding the following data:\n• Relative change of maximum\n2D diameter [%]\n• relative change of maximum\northogonal 2D diameter [%]\n• relative change of mean 2D\ndiameter [%],\n• relative change of maximum\n3D diameter [%]\n• Relative change of volume\n(volume doubling time [d],\nnegative growth [%])","Segmentation of lung lesions with the\nfollowing data (not shown to the\nuser):\n• Relative change of maximum\n2D diameter [%]\n• relative change of maximum\northogonal 2D diameter [%]\n• relative change of mean 2D\ndiameter [%],\n• relative change of maximum\n3D diameter [%]\n• Relative change of volume\n(volume doubling time [d],\nnegative growth [%])"],["Visualization\nof lesion\nsegmentation\nresults","Color overlay of MPR and VRT with\nevaluation","Color overlay of MPR and VRT with\nevaluation"],["Lesion\nfollow-up","Correlation of segmented lung lesions\nwith known priors using the data from\nthe lesion segmentation.","N/A"],["Deployment","Cloud and Edge (on-premise)\ndeployments","Cloud deployment"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213713-p9-t0","doc_id":"K213713","page_num":9,"bbox":[72.26,132.44,539.96,452.7],"n_rows":8,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to medical\ndevices","14971:2019","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n(2016)","","","NEMA","",""],["12-261","Radiology","Information Technology –\nDigital Compression and coding\nof continuous -tone still images:\nRequirements and Guidelines\n[including: Technical\nCorrigendum 1(2005)]","10918-1\n1994-02-15","","","ISO\nIEC","",""]],"caption_candidate":"following voluntary FDA recognized Consensus Standards listed in Table 1 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213713-p10-t0","doc_id":"K213713","page_num":10,"bbox":[72.31,486.09,539.94,541.92],"n_rows":3,"n_cols":8,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],["","","Number","","","Date","",""],["AI-Rad Companion\n(Pulmonary)","K183271","","","July 26, 2019","","","JAK"]],"caption_candidate":"(Table 2):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213721-p6-t0","doc_id":"K213721","page_num":6,"bbox":[50.87,109.68,561.24,685.45],"n_rows":3,"n_cols":3,"columns":["","Predicate Device\nAidoc BriefCase for ICH triage\n(K203508)","Subject Device\nAidoc Briefcase for BA triage"],"rows":[["","Predicate Device\nAidoc BriefCase for ICH triage\n(K203508)","Subject Device\nAidoc Briefcase for BA triage"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of non-enhanced head\nCT images. The device is intended to\nassist hospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communication of\nsuspected positive findings of pathologies\nin head CT images, namely Intracranial\nHemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected ICH on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected ICH\nfindings Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended\nto be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on professional\njudgment, to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care.","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of head CT Angio (CTA)\nimages. The device is intended to assist\nhospital networks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspected\npositive cases of Brain Aneurysm (BA)\nfindings above 5 mm size.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag suspect\ncases on a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is presented\nwith notifications for suspect cases.\nNotifications include compressed preview\nimages that are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original medical\nimage and is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on professional\njudgment, to assist with triage/prioritization of\nmedical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care."],["User\npopulation","Hospital networks and appropriately trained\nmedical specialists","Hospital networks and appropriately trained\nmedical specialists"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213721-p7-t0","doc_id":"K213721","page_num":7,"bbox":[50.87,72.25,561.24,598.8],"n_rows":11,"n_cols":3,"columns":["","Predicate Device\nAidoc BriefCase for ICH triage\n(K203508)","Subject Device\nAidoc Briefcase for BA triage"],"rows":[["","Predicate Device\nAidoc BriefCase for ICH triage\n(K203508)","Subject Device\nAidoc Briefcase for BA triage"],["Anatomical\nregion of\ninterest","Head","Head"],["Data\nacquisition\nprotocol","Non-contrast head CT scans","Head CTA"],["View DICOM\ndata","DICOM Information about the patient, study\nand current image","DICOM Information about the patient, study\nand current image"],["Segmentation\nof region of\ninterest","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image.","No; the device does not mark, annotate, or\ndirect users’ attention to a specific location in\nthe original image."],["Algorithm","Artificial intelligence Deep-learning\nalgorithm with database of images.","Artificial intelligence Deep-learning algorithm\nwith database of images."],["Notification/Pri\noritization","Yes","Yes"],["Preview\nimages","Presentation of a small, compressed, black\nand white preview image that is labeled “Not\nfor diagnostic use”.","Presentation of a small, compressed, black\nand white preview image that is labeled “Not\nfor diagnostic use”."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No. The device operates in parallel with the\nstandard of care, which remains the default\noption for all cases.","No. The device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],["Structure","- AHS module (image acquisition).\n- ACS module (image processing).\n- Aidoc Worklist application (worklist\nand Image Viewer).","- AHS module (image acquisition).\n- ACS module (image processing).\n- Aidoc Worklist application (worklist and\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213721-p9-t0","doc_id":"K213721","page_num":9,"bbox":[118.39,85.83,493.59,185.54],"n_rows":7,"n_cols":16,"columns":["","Parameter","","","N","","Mean","","","95%","","","95%","","Median","IQR"],"rows":[["","Parameter","","","N","","Mean","","","95%","","","95%","","Median","IQR"],["","","","","","","Estimate","","","Lower CL","","","Upper CL","","",""],["","Standard of care Time-","","65","","","89.4","","56.0","","","122.7","","","66.0","50.7"],["","to- exam-open","","","","","","","","","","","","","",""],["","BriefCase BA","","65","","","4.2","","3.9","","","4.5","","","4.2","1.8"],["","Time-to-notification","","","","","","","","","","","","","",""],["Difference","","","65","","","85.2","","51.8","","","118.6","","","63.1","50.1"]],"caption_candidate":"Table 2. Time Saving Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213725-p4-t0","doc_id":"K213725","page_num":4,"bbox":[72.24,195.6,539.76,670.08],"n_rows":7,"n_cols":2,"columns":["Date:","November 23, 2021"],"rows":[["Date:","November 23, 2021"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact Person:","Yonghui Han\nRegulatory Affairs Leader\nGE Healthcare\n(86)10 57083350/(+86) 13311387032\nYonghui.Han@ge.com"],["Secondary Contact Person:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE Healthcare\nTel:(262)424-7774\nEmail: Elizabeth.Mathew@ge.com"],["Device Trade Name:","CardIQ Suite"],["Common/Usual Name:","CardIQ Suite"],["Primary Regulation Number:\nPrimary Product Code:\nSecondary Product Code:\nClassification:","Computed Tomography X-Ray System (21 CFR 892.1750)\nJAK\nLLZ\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213725-p5-t0","doc_id":"K213725","page_num":5,"bbox":[72.24,118.32,539.76,612.72],"n_rows":2,"n_cols":2,"columns":["Predicate Device\nDevice name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nClassification:","SmartScore 4.0\nGE Medical Systems SCS\nK020929\n21 CFR 892.1750 Computed tomography X-Ray System\nJAK\nClass II"],"rows":[["Predicate Device\nDevice name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nClassification:","SmartScore 4.0\nGE Medical Systems SCS\nK020929\n21 CFR 892.1750 Computed tomography X-Ray System\nJAK\nClass II"],["Reference Devices\nDevice name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nClassification:\nDevice name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nClassification:","CardIQ Xpress 2.0\nGE Medical Systems SCS\nK073138\n21 CFR 892.1750 Computed tomography X-Ray System\nJAK\nClass II\nSyngo.CT CaScoring\nSiemens Medical Solutions USA, Inc.\nK201034\n21 CFR 892.1750 Computed tomography X-Ray System\nJAK\nClass II"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213725-p7-t0","doc_id":"K213725","page_num":7,"bbox":[72.26,190.14,589.53,612.0],"n_rows":5,"n_cols":4,"columns":["Specification","Predicate\nDevice:\nSmartScore 4.0\n(K020929)","Proposed\nDevice:\nCardIQ Suite","Comparison"],"rows":[["Specification","Predicate\nDevice:\nSmartScore 4.0\n(K020929)","Proposed\nDevice:\nCardIQ Suite","Comparison"],["Segmentation\nand labeling\ncalcific regions\nin the\ncoronaries","Manual","Automated","Substantial Equivalent\nDeep Learning Algorithm is incorporated in CardIQ Suite to\nautomatically segment and label the calcific regions in the\ncoronary arteries in order to improve workflow efficiency\nover the manual approach that exists in the predicate\ndevice.\nAutomated calcium scoring evaluation already exists in the\nreference device Syngo.CT CaScoring (K201034)."],["Manual\nSegmentation\nand labeling of\ncalcific regions","Yes","Yes","Identical"],["Computation\nof Agatston\nscore","Yes","Yes","Identical"],["Coronary 2D\nReview","Not Available","Yes","Substantial Equivalent\nCoronary 2D Reviews Toolset is available in CardIQ Suite to\nassist users for a seamless integrated review of coronary\nartery imaging along with automated calcium scoring\nfeature.\nThis tool set contains identical features to what already\nexists in the reference device CardIQ Xpress 2.0 (K073138)"]],"caption_candidate":"predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213737-p7-t0","doc_id":"K213737","page_num":7,"bbox":[99.76,577.08,548.24,713.04],"n_rows":5,"n_cols":12,"columns":["","","","Dataset","","","Dice index","","","Absolute difference of\nthe relative volumes [pp]","",""],"rows":[["","","","Dataset","","","Dice index","","","Absolute difference of\nthe relative volumes [pp]","",""],["","Brain","","","A","","","0.96 ± 0.01","","","1.63 ± 1.06",""],["CSF","","","A","","","0.78 ± 0.05","","","1.67 ± 1.06","",""],["","ICV","","","A","","","0.98 ± 0.00","","","-",""],["Hippocampus total\nHippocampus right\nHippocampus left","","","B","","","0.84 ± 0.03\n0.84 ± 0.03\n0.84 ± 0.04","","","0.03 ± 0.02\n0.01 ± 0.01\n0.01 ± 0.01","",""]],"caption_candidate":"comparison. The results are summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213737-p8-t0","doc_id":"K213737","page_num":8,"bbox":[102.64,157.56,548.84,426.97],"n_rows":12,"n_cols":10,"columns":["","","","Dataset","Dice index","","","Absolute difference of\nthe relative volumes [pp]","",""],"rows":[["","","","Dataset","Dice index","","","Absolute difference of\nthe relative volumes [pp]","",""],["","Frontal lobe total","","C","","0.95 ± 0.01","","","1.21 ± 1.22",""],["","Frontal lobe right","","","","0.94 ± 0.02","","","0.76 ± 0.58",""],["","Frontal lobe left","","","","0.94 ± 0.02","","","0.60 ± 0.67",""],["Occipital lobe total\nOccipital lobe right\nOccipital lobe left","","","C","0.89 ± 0.03\n0.88 ± 0.04\n0.88 ± 0.03","","","0.75 ± 0.83\n0.54 ± 0.48\n0.44 ± 0.36","",""],["","Parietal lobe total","","C","","0.89 ± 0.03","","","1.21 ± 1.31",""],["","Parietal lobe right","","","","0.88 ± 0.04","","","0.73 ± 0.76",""],["","Parietal lobe left","","","","0.88 ± 0.03","","","0.64 ± 0.67",""],["Temporal lobe total\nTemporal lobe right\nTemporal lobe left","","","C","0.91 ± 0.02\n0.91 ± 0.02\n0.90 ± 0.03","","","0.87 ± 0.74\n0.46 ± 0.33\n0.47 ± 0.46","",""],["","Cerebellum total","","C","","0.99 ± 0.00","","","0.19 ± 0.13",""],["","Cerebellum right","","","","0.97 ± 0.01","","","0.12 ± 0.07",""],["","Cerebellum left","","","","0.97 ± 0.01","","","0.17 ± 0.11",""]],"caption_candidate":"percentage points.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213760-p6-t0","doc_id":"K213760","page_num":6,"bbox":[72.29,423.97,539.86,707.4],"n_rows":11,"n_cols":7,"columns":["Feature","Subject Device\nABMD Software","Predicate\nDevice\nQCT Bone\nMineral Density\nAnalysis\nSoftware\nK894854","","Reference","","Summary"],"rows":[["Feature","Subject Device\nABMD Software","Predicate\nDevice\nQCT Bone\nMineral Density\nAnalysis\nSoftware\nK894854","","Reference","","Summary"],["","","","","Device","",""],["","","","","QCT Pro","",""],["","","","","Asynchronous","",""],["","","","","Calibration","",""],["","","","","Module,","",""],["","","","","CliniQCT","",""],["","","","","K140342","",""],["Indication for\nUse/Intended\nUse","Estimate bone\nmineral density\nwithin the spine.","Estimate bone\nmineral density\nwithin the spine.","Estimate bone\nmineral density\nwithin the spine.","","","Equivalent."],["Modality","CT scan images\n(DICOM)","CT scan images\n(DICOM)","CT scan images\n(DICOM)","","","Equivalent."],["Device provides\nestimates of","Yes","Yes","Yes","","","Equivalent."]],"caption_candidate":"the ABMD Software is substantially equivalent to the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213760-p7-t0","doc_id":"K213760","page_num":7,"bbox":[72.26,132.86,539.88,716.52],"n_rows":8,"n_cols":5,"columns":["bone mineral\ndensity from the\nspine.","","","",""],"rows":[["bone mineral\ndensity from the\nspine.","","","",""],["Device provides\nthe bone mineral\ndensity value.","Yes","Yes","Yes","Equivalent."],["Device provides\nZ-score.","Yes","Yes","Yes","Equivalent."],["Device provides\nT-score.","Yes","Yes","Yes","Equivalent."],["User","Healthcare\nProviders","Healthcare\nProviders","Healthcare\nProviders","Equivalent."],["Operating\nSystem","Linux","Windows","Windows","Equivalent,\nsoftware\nfunction is\nindependent\nfrom\noperating\nsystem."],["Retrospective\nmeasurements\nfrom CT scans.","CT scan images\ncan be selected and\ninputted to the\nsoftware.","CT scan images\ncan be selected\nand inputted to\nthe software.","CT scan images\ncan be selected\nand inputted to\nthe software.","Equivalent."],["Automatic\nAveraging\nHounsfield\nUnits","Software\nautomatically\nmeasures and\naverages\nHounsfield units in\nthe trabecular","Software\nautomatically\nmeasures and\naverages\nHounsfield units\nin the trabecular","Software\nautomatically\nmeasures and\naverages\nHounsfield units\nin the trabecular","Equivalent."]],"caption_candidate":"Torrance, CA 90502","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213760-p8-t0","doc_id":"K213760","page_num":8,"bbox":[72.26,132.86,539.88,354.65],"n_rows":2,"n_cols":5,"columns":["","region of spinal\nbones.","region of spinal\nbones.","region of spinal\nbones.",""],"rows":[["","region of spinal\nbones.","region of spinal\nbones.","region of spinal\nbones.",""],["Calibration","Inputting CT\nscanner-specific\ncalibration factor is\nrequired. Software\noutputs calibrated\nBMD score.","Simultaneous\nscanning of\ncalibration\nphantom is\nrequired.\nSoftware outputs\ncalibrated BMD\nscore.","Asynchronous\nscanning of\ncalibration\nphantom is\nrequired.\nSoftware outputs\ncalibrated BMD\nscore.","Equivalent.\nSoftware\nprovides\nmeasurements\ncorrected for\ncalibration\ndata."]],"caption_candidate":"Torrance, CA 90502","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213760-p9-t0","doc_id":"K213760","page_num":9,"bbox":[72.25,250.61,553.08,493.51],"n_rows":5,"n_cols":3,"columns":["","Study 1","Study 2"],"rows":[["","Study 1","Study 2"],["Reference\nDataset","993 quantitative CT (QCT) readings of a\ncohort of asymptomatic cases who\nunderwent CT scans.","172 asymptomatic cases who underwent\nwhole-body DXA scans as well as CT\nscans."],["Truthing Process","QCT BMD, T-score, and Z-score values\nderived from manual measurement by\ntrained operators.","DXA scans derived T-score, and Z-score\nvalues plus QCT BMD, T-score, and Z-\nscore values derived from manual\nmeasurement by trained operators."],["Analysis methods","Pearson Correlation, Deming\nRegressions, and Bland Altman\nAgreement","Pearson Correlation, Deming\nRegressions, and Bland Altman\nAgreement"],["Results","Strong correlations and agreements were\nfound between manual QCT and ABMD\nSoftware","Strong correlations and agreements were\nfound between manual QCT and ABMD\nSoftware. Modest but significant\ncorrelations and agreement were found\nbetween DXA, and ABMD Software."]],"caption_candidate":"ABMD Software Performance Studies","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p4-t0","doc_id":"K213776","page_num":4,"bbox":[111.9,163.85,437.27,703.61],"n_rows":49,"n_cols":2,"columns":["Date Prepared","23 December 2021"],"rows":[["Date Prepared","23 December 2021"],["",""],["Submitted by","Resonance Health Analysis Servi"],["",""],["","141 Burswood Rd"],["",""],["","Burswood 6100"],["",""],["","AUSTRALIA"],["",""],["Main Contact","Mr Mitchell Wells"],["",""],["","Managing Director"],["",""],["","mitchellw@resonancehealth.com"],["",""],["","Tel: +61 8 9286 5300"],["",""],["","Fax: +61 8 9286 5399"],["",""],["US Contact (US Agent)","Michael van der Woude"],["",""],["","Director & GM"],["",""],["","Emergo Global Representation L"],["",""],["","2500 Bee Cave Road, Building 1"],["",""],["","Austin, TX 78746"],["",""],["","Phone: 512 3279997"],["",""],["","Fax: 512 3279998"],["",""],["","Email: USAgent@ul.com"],["",""],["EVICE INFORMATION",""],["",""],["Name of Device","LiverSmart"],["",""],["Trade/proprietary Name","LiverSmart™"],["",""],["Classification","Class II"],["",""],["Product Code","90-PCS and LNH"],["",""],["CFR Section","892.1001 and 892.1000"],["",""],["Panel","Radiology"]],"caption_candidate":"Date Prepared 23 December 2021","well_formed":true,"extraction_settings":"text"}
{"table_id":"K213776-p4-t1","doc_id":"K213776","page_num":4,"bbox":[106.37,558.28,540.27,709.18],"n_rows":6,"n_cols":4,"columns":["","Name of Device","","LiverSmart"],"rows":[["","Name of Device","","LiverSmart"],["","Trade/proprietary Name","","LiverSmart™"],["","Classification","","Class II"],["","Product Code","","90-PCS and LNH"],["","CFR Section","","892.1001 and 892.1000"],["","Panel","","Radiology"]],"caption_candidate":"DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p7-t0","doc_id":"K213776","page_num":7,"bbox":[62.0,150.36,721.82,532.77],"n_rows":7,"n_cols":12,"columns":["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],"rows":[["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],["Regulatory Class","","","II","","","II","","","II","",""],["510(k) number","","","K213776","","","K182218","","","K201039","",""],["Classification\nName","","","Liver Iron Concentration Imaging\nCompanion Diagnostic for Deferasirox\nSystem, Nuclear Magnetic Resonance\nImaging, System, Image Processing\nRadiological","","","Liver Iron Concentration Imaging\nCompanion Diagnostic for Deferasirox","","","System, Nuclear Magnetic Resonance\nImaging, System, Image Processing\nRadiological","",""],["CFR Section","","","892.1001 and 892.1000","","","892.1001","","","892.1000","",""],["Product Code and\nClassification\nPanel","","","90 PCS and 90 LNH","","","90 PCS","","","90 LNH","",""],["Description","","","Standalone software package that\nautomatically analyses magnetic resonance\nimaging (MRI) datasets to generate an\nestimate of the patient’s volumetric liver fat\nfraction (VLFF), proton density fat fraction\n(PDFF), steatosis grade, and liver iron\nconcentration (LIC). LiverSmart evaluates\nimages acquired using the FerriSmart and\nHepaFat-AI protocols and analyses the\nacquired data to produce a ‘multi-\nparametric’ reporting both fat metrics and\nLIC.","","","Standalone software package that\nautomatically analyses multi-slice, spin-\necho MRI data sets encompassing the\nabdomen to provide objective and\nreproducible determination of liver\nparameters to support clinicians in the\nassessment of liver iron status. The\nsoftware tool determines the signal decay\nrate (R2) that is used to characterize iron\nloading in the liver, which is then\ntransformed by a defined calibration curve\nto provide a quantitative measure of liver\niron concentrations in vivo.","","","Standalone software platform designed to\nautomatically analyse within seconds\nmagnetic resonance imaging (MRI) datasets to\ngenerate an estimate of the patient’s\nvolumetric liver fat fraction (VLFF),\nconverted into proton density fat fraction\n(PDFF) and steatosis grade. No user input is\nrequired for the analysis thus minimising the\nimpact of human error on obtained results.","",""]],"caption_candidate":"The table below summarizes the main similarities and differences between LiverSmart and the predicates.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p8-t0","doc_id":"K213776","page_num":8,"bbox":[62.05,106.81,721.84,532.77],"n_rows":4,"n_cols":12,"columns":["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],"rows":[["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],["Technology","","","Convolutional neural networks for the\nimage analysis.\nAlgorithmic for the image’s quality checks,\nR2 conversion into LIC, and Alpha\nconversion into VLFF.","","","Convolutional neural networks for the\nimage analysis.\nAlgorithmic for the image’s quality checks\nand R2 conversion into LIC.","","","Convolutional neural networks for the image\nanalysis.\nAlgorithmic for the image’s quality checking\nand Alpha conversion into VLFF.","",""],["Intended\npurpose(s)","","","1. Supporting clinical diagnoses about the\nstatus of LIC and the status of liver fat\ncontent.\n2. Supporting the subsequent clinical\ndecision-making processes.\n3. Supporting the use in clinical research\ntrials, directed at studying changes in\nLIC and liver fat as a result of\ninterventions.","","","1. Supporting clinical diagnoses about the\nstatus of LIC.\n2. Supporting the subsequent clinical\ndecision-making processes.\n3. Supporting the use in clinical research\ntrials, directed at studying changes in\nLIC as a result of interventions.","","","1. Supporting clinical diagnoses about the\nstatus of liver fat content.\n2. Supporting the subsequent clinical\ndecision-making processes.\n3. Supporting the use in clinical research\ntrials, directed at studying changes in liver\nfat as a result of interventions.","",""],["Intended Use","","","1. For the measurement of R2 and iron\nconcentration in the liver from MRI\nscans.\n2. For quantitative measurement of the\ntriglyceride fat fraction in magnetic\nresonance images of the liver, also\nknown as volumetric liver fat fraction\n(VLFF).","","","1. Measurement of R2 and iron\nconcentration in the liver from MRI\nscans","","","1. For quantitative measurement of the\ntriglyceride fat fraction in magnetic\nresonance images of the liver, also known\nas volumetric liver fat fraction (VLFF).\n*It utilises magnetic resonance images that\nexploit the difference in resonance frequencies\nbetween hydrogen nuclei in water and\ntriglyceride fat. The quantitative triglyceride\nfat fraction is based on the measurement of a\nmagnetic resonance parameter that reflects the\nratio of the proton density signal of\ntriglyceride fat to the total proton density\nsignal in the liver.\nWhen interpreted by a trained physician, the\nresults provide information that can aid in\ndiagnosis.","",""]],"caption_candidate":"Special 510(k): LiverSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p9-t0","doc_id":"K213776","page_num":9,"bbox":[62.05,106.81,721.84,509.51],"n_rows":4,"n_cols":12,"columns":["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],"rows":[["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],["Indications","","","LiverSmart is indicated to:\nFor Liver Iron Concentration\n1. measure liver iron concentration in\nindividuals with confirmed or suspected\nsystemic iron overload;\n2. monitor liver iron burden in transfusion\ndependent thalassemia patients and\npatients with sickle cell disease\nreceiving blood transfusions;\n3. aid in the identification and monitoring\nof non-transfusion-dependent\nthalassemia patients receiving therapy\nwith Deferasirox.\nFor Liver Fat Assessment\n1. assess the volumetric liver fat fraction,\nproton density fat fraction and steatosis\ngrade in individuals with confirmed or\nsuspected fatty liver disease.\nWhen interpreted by a trained physician, the\nresults can be used to:\n2. monitor liver fat content in patients\nundergoing weight loss management;\n3. aid in the assessment and screening of\nliving donors for liver transplant.","","","FerriSmart is Indicated to:\n1. measure liver iron concentration in\nindividuals with confirmed or\nsuspected systemic iron overload;\n2. monitor liver iron burden in\ntransfusion dependent thalassemia\npatients and patients with sickle cell\ndisease receiving blood transfusions;\n3. aid in the identification and monitoring\nof non-transfusion-dependent\nthalassemia patients receiving therapy\nwith Deferasirox.","","","HepaFat-AI is indicated to:\n1. assess the volumetric liver fat fraction,\nproton density fat fraction and steatosis\ngrade in individuals with confirmed or\nsuspected fatty liver disease.\nWhen interpreted by a trained physician, the\nresults can be used to:\n2. monitor liver fat content in patients\nundergoing weight loss management;\n3. aid in the assessment and screening of\nliving donors for liver transplant.","",""],["User","","","Radiologist","","","Radiologist","","","Radiologist","",""],["Hosting platform","","","Cloud-based or on-site hosting","","","Cloud-based or on-site hosting","","","Cloud-based or onsite platform","",""]],"caption_candidate":"Special 510(k): LiverSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p10-t0","doc_id":"K213776","page_num":10,"bbox":[62.01,106.81,721.82,525.25],"n_rows":6,"n_cols":12,"columns":["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],"rows":[["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],["Image-type\nutilized","","","Magnetic Resonance","","","Magnetic Resonance","","","Magnetic Resonance","",""],["Image format","","","DICOM","","","DICOM","","","DICOM","",""],["Data Acquisition\nmethod","","","Single Spin Echo (SSE)\nGradient Recalled Echo (GRE)","","","Single Spin Echo (SSE)","","","Gradient Recalled Echo (GRE)","",""],["Anatomical Sites","","","Liver","","","Liver","","","Liver","",""],["Analysis System\nComponents","","","LiverSmart:\n(i) Data Preparation Module; and\n(ii) Report Generation Module\nFerriSmart:\n(i) Magnetic Resonance Imaging\nProtocol;\n(ii) FerriSmart Analysis Software; and\n(iii) Liver Iron Concentration\nMeasurement.\nHepaFat-AI:\n(i) Magnetic Resonance Imaging\nProtocol;\n(ii) HepaFat-AI Analysis Software;\n(iii) Volumetric Liver Fat Fraction\nMeasurement;\n(iv) Proton Density Fat Fraction\nMeasurement; and","","","(i) Magnetic Resonance Imaging\nProtocol\n(ii) FerriSmart Analysis Software\n(iii) Liver Iron Concentration\nMeasurement","","","(i) Magnetic Resonance Imaging Protocol\n(ii) HepaFat-AI Analysis Software\n(iii) Volumetric Liver Fat Fraction\nMeasurement\n(iv) Proton Density Fat Fraction\nMeasurement\n(v) Steatosis Grade Measurement","",""]],"caption_candidate":"Special 510(k): LiverSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213776-p11-t0","doc_id":"K213776","page_num":11,"bbox":[62.05,106.81,721.84,468.2],"n_rows":4,"n_cols":12,"columns":["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],"rows":[["","","","","LiverSmart (Subject Device)","","","FerriSmart (Predicate)","","","HepaFat-AI (Predicate)",""],["","","","(v) Steatosis Grade Measurement","","","","","","","",""],["Result report\ncontent","","","Page 1\n(i) Report No., patient ID, patient name and\ndate of birth for full identification of the\npatient.\n(ii) Scan date, and analysis date.\n(iii) Referrer and MRI centre.\n(iv) Results displayed: LIC (mg/g dry\ntissue), LIC (mmol/kg dry tissue),\nassociated with confidence intervals and\nnormal range.\n(v) Results displayed: VLFF (%), PDFF (%)\nand Steatosis grade, associated with\nconfidence intervals and normal range.\nPage 2\nAs per FerriSmart report\nPage 3\nAs per HepaFat-AI report","","","(i) Patient ID, patient name and date of\nbirth for full identification of the\npatient.\n(ii) Scan date, and analysis date.\n(iii) Referrer and MRI centre.\n(iv) Results displayed: LIC (mg/g dry\ntissue), LIC (mmol/kg dry tissue),\nassociated with confidence intervals\nand normal range.\n(v) Pictures of the 5 TEs of the analysed\nslice.\n(vi) LIC thresholds table","","","(i) Patient ID, patient name and date of\nbirth for full identification of the patient.\n(ii) Scan date, and analysis date.\n(iii) Referrer and MRI centre.\n(iv) Results displayed: VLFF (%), PDFF (%)\nand Steatosis grade, associated with\nconfidence intervals and normal range.\n(v) NASH-CRN Steatosis Grading Guide\n(vi) Pictures of the 3 TEs of the analysed\nslice.\n(vii) Liver colour map (for illustration\npurpose only, not for diagnostic)","",""],["Result report\nformat","","","HTML and PDF","","","HTML and PDF","","","HTML and PDF","",""]],"caption_candidate":"Special 510(k): LiverSmart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213779-p4-t0","doc_id":"K213779","page_num":4,"bbox":[72.27,417.12,426.68,514.67],"n_rows":5,"n_cols":2,"columns":["Trade or proprietary or model name","Preview Shoulder"],"rows":[["Trade or proprietary or model name","Preview Shoulder"],["510(k) number","K210556"],["Decision date","21 April 2021"],["Classification product code","QIH"],["Manufacturer","Genesis Software\nInnovations"]],"caption_candidate":"The predicate device to which substantial equivalence is claimed:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213795-p5-t0","doc_id":"K213795","page_num":5,"bbox":[66.63,603.16,545.47,699.96],"n_rows":5,"n_cols":9,"columns":["","","","","Proposed Device","","","Predicate Device",""],"rows":[["","","","","Proposed Device","","","Predicate Device",""],["510(k) Number","","","TBD","","","P980025","",""],["Applicant","","","VideaHealth, Inc.","","","Carestream Dental LLC","",""],["Device Name","","","Videa Caries Assist","","","Logicon Caries Detector","",""],["Classification Regulation","","","892.2070","","","892.2070","",""]],"caption_candidate":"Table 1: Technological Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213795-p6-t0","doc_id":"K213795","page_num":6,"bbox":[66.68,72.55,545.42,698.98],"n_rows":20,"n_cols":9,"columns":["","","","","Proposed Device","","","Predicate Device",""],"rows":[["","","","","Proposed Device","","","Predicate Device",""],["Product Code","","","MYN","","","MYN","",""],["Indications for Use","","","Videa Caries Assist is a\ncomputer-assisted detection\n(CADe) device that analyzes\nintraoral radiographs to\nidentify and localize carious\nlesions. Videa Caries Assist is\nindicated for use by board\nlicensed dentists for the\nconcurrent review of bitewing\n(BW) radiographs acquired\nfrom adult patients aged 22\nyears or older.","","","Logicon Caries Detector is a\nsoftware device that is an aid in the\ndiagnosis of caries that have\npenetrated into the dentin on un-\nrestored proximal surfaces of\nsecondary dentition through the\nstatistical analysis of digital intra-\noral radiographic imagery. The\ndevice provides additional\ninformation for the clinician to use in\nhis/her diagnosis of a tooth surface\nsuspected of being carious. It is\ndesigned to work in conjunction with\nan existing CareStream Dental RVG\nDigital X-Ray Radiographic System\nwith Dental Imaging Software (DIS)\nfor Windows XP or higher.","",""],["Image Modality","","","X-Ray","","","X-Ray","",""],["Study Type","","","Bitewing Images","","","Digital intra-oral radiographic\nimagery","",""],["Clinical Finding","","","Active and Secondary Caries\nat all penetration depths","","","Caries penetrating into dentin","",""],["Tooth Surface","","","Proximal, Buccal/Lingual,\nOcclusal, Root, Cervical","","","Proximal","",""],["Clinical Output","","","","Message indicating if and","","Message indicating if a carious\nlesion was detected.\nAn outline of the potential lesion site\nis shown","",""],["","","","","how many carious lesion were","","","",""],["","","","","detected","","","",""],["","","","","Set of togglable bounding","","","",""],["","","","","boxes around suspected","","","",""],["","","","","lesions","","","",""],["","Patient Population","","Adults ≥ 22 years of age","Adults ≥ 22 years of age","","Adults ≥ 22 years of age","",""],["","Intended User","","","US licensed dentists","","","Dentists",""],["","Development Technology","","","Supervised Deep Learning","","","Computer Vision",""],["","Image Source","","","X-Ray Sensor","","","X-Ray Sensor",""],["Image Viewing","Image Viewing","","Image Viewer","Image Viewer","","","CareStream Dental RVG Digital X-",""],["","","","","","","","Ray Radiographic System with",""],["","","","","","","","Dental Imaging Software (DIS)",""]],"caption_candidate":"510(k) Summary – K213795 Page 3 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213795-p7-t0","doc_id":"K213795","page_num":7,"bbox":[72.25,536.98,539.21,711.48],"n_rows":6,"n_cols":3,"columns":["","Mean","95% Confidence Interval"],"rows":[["","Mean","95% Confidence Interval"],["Overall average FOM","0.740","(0.721, 0.760)"],["Overall average Se - image-based (%)","70.8","(68.0, 73.7)"],["Overall average PPV - image-based (%)","59.5","(56.5, 62.5)"],["Overall average Se (%) - lesion-based (pooled)","73.6","(71.1, 76.0)"],["Overall average PPV (%) - lesion-based\n(pooled)","64.9","(62.3, 67.6)"]],"caption_candidate":"Table 2: Standalone: AFROC FOM, Image-based Se, PPV. Lesion-based estimates in italics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213795-p9-t0","doc_id":"K213795","page_num":9,"bbox":[72.13,92.42,540.3,172.7],"n_rows":3,"n_cols":4,"columns":["","Aided","Unaided","Difference"],"rows":[["","Aided","Unaided","Difference"],["Overall, average FOM","0.739","0.667","0.072"],["95% Confidence Interval","(0.705, 0.773)","(0.633, 0.701)","(0.047, 0.097)"]],"caption_candidate":"Table 3: Overall Image-based AFROC FOM for Aided vs Unaided reads","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213886-p6-t0","doc_id":"K213886","page_num":6,"bbox":[50.64,203.28,532.03,760.68],"n_rows":7,"n_cols":4,"columns":["","Predicate Device\nAidoc Briefcase iPE triage (K203508)","Subject Device\nAidoc Briefcase iPE triage (K213886)",""],"rows":[["","Predicate Device\nAidoc Briefcase iPE triage (K203508)","Subject Device\nAidoc Briefcase iPE triage (K213886)",""],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\ncontrast-enhanced chest CTs (but not\ndedicated CTPA protocol). The device is\nintended to assist hospital networks and\nappropriately trained medical specialists\nin workflow triage by flagging and\ncommunication of suspected positive\ncases of incidental Pulmonary Embolism\n(iPE) pathologies. For the iPE pathology,\nthe software is only intended to be used\non single-energy exams. The device is\nintended to work with GE and Siemens\nscanners only.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag\nsuspect cases on a standalone desktop\napplication in parallel to the ongoing\nstandard of care image interpretation. The\nuser is presented with notifications for\nsuspect cases. Notifications\ninclude compressed preview images that\nare meant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of contrast-enhanced\nchest CTs (not dedicated CTPA protocol) in",""],["","","","in"],["","","adults or transitional adolescents age 18",""],["","","and older",""],["User population","Appropriately trained medical specialists","Appropriately trained medical specialists",""],["Anatomical\nregion of\ninterest","Chest","Chest",""]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213886-p7-t0","doc_id":"K213886","page_num":7,"bbox":[50.64,72.24,532.68,579.96],"n_rows":10,"n_cols":3,"columns":["Inclusion/\nExclusion\ncriteria","Inclusion criteria\n- Contrast-enhanced chest CTs (not\ndedicated CTPA protocol.\n- Single energy exams.\n- Scans performed with a 64 slice or\ngreater number of detectors.\n- Scans performed on adults/transitional\nadults ≥ 18 years of age.\n- Slice thickness; 0.5 - 2.0 mm axial.\nExclusion Criteria\nAll studies that are technically inadequate,\nincluding studies with motion artifacts,\nsevere metal artifacts, or inadequate field\nof view.","Inclusion Criteria\n- Contrast-enhanced chest CTs (not\ndedicated CTPA protocol.\n- Single energy exams.\n- Scans performed with a 64 slice or\ngreater number of detectors.\n- Scans performed on adults/ transitional\nadolescents ≥ 18 years of age.\n- Slice thickness; 0.5 - 2.0 mm axial.\nExclusion Criteria\nAll studies that are technically inadequate,\nincluding studies with motion artifacts,\nsevere metal artifacts, or inadequate field of\nview."],"rows":[["Inclusion/\nExclusion\ncriteria","Inclusion criteria\n- Contrast-enhanced chest CTs (not\ndedicated CTPA protocol.\n- Single energy exams.\n- Scans performed with a 64 slice or\ngreater number of detectors.\n- Scans performed on adults/transitional\nadults ≥ 18 years of age.\n- Slice thickness; 0.5 - 2.0 mm axial.\nExclusion Criteria\nAll studies that are technically inadequate,\nincluding studies with motion artifacts,\nsevere metal artifacts, or inadequate field\nof view.","Inclusion Criteria\n- Contrast-enhanced chest CTs (not\ndedicated CTPA protocol.\n- Single energy exams.\n- Scans performed with a 64 slice or\ngreater number of detectors.\n- Scans performed on adults/ transitional\nadolescents ≥ 18 years of age.\n- Slice thickness; 0.5 - 2.0 mm axial.\nExclusion Criteria\nAll studies that are technically inadequate,\nincluding studies with motion artifacts,\nsevere metal artifacts, or inadequate field of\nview."],["Data acquisition\nprotocol","Contrast-enhanced chest CTs (not\ndedicated CTPA protocol)","Contrast-enhanced chest CTs (not\ndedicated CTPA protocol)"],["View DICOM\ndata","DICOM Information about the patient,\nstudy and current image","DICOM Information about the patient, study\nand current image"],["Segmentation of\nregion of\ninterest","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image","No; device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification/\nPrioritization","Yes","Yes"],["Preview images","Presentation of a low-quality, compressed,\ngrayscale preview image that is captioned\n“Not for diagnostic use”.","Presentation of a low-quality, compressed,\ngrayscale preview image that is captioned\n“Not for diagnostic use”."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No. The device operates in parallel with\nthe standard of care, which remains the\ndefault option for all cases.","No. The device operates in parallel with the\nstandard of care, which remains the default\noption for all cases."],["Structure","- AHS module/Orchestrator (image\nacquisition).\n- ACS module (image processing).\n- Aidoc Worklist application for workflow\nintegration (worklist and non-diagnostic\nbasic Image Viewer).","- AHS module/Orchestrator (image\nacquisition).\n- ACS module (image processing).\n- Aidoc Worklist application for workflow\nintegration (worklist and non-diagnostic\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213886-p8-t0","doc_id":"K213886","page_num":8,"bbox":[151.82,228.52,443.5,299.28],"n_rows":6,"n_cols":4,"columns":["","","95%","95%"],"rows":[["","","95%","95%"],["Parameter","Estimate","",""],["","","Lower CL","Upper CL"],["","","",""],["Negative Predictive Value","99.7%","99.4%","99.8%"],["Positive Predictive Value","19.5%","11.1%","32.0%"]],"caption_candidate":"positive = 2.6%1, Confidence limits computed using the \"exact\" Clopper-Pearson method","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213886-p8-t1","doc_id":"K213886","page_num":8,"bbox":[151.82,325.67,443.5,396.43],"n_rows":4,"n_cols":8,"columns":["Parameter","","Estimate","","95%\nLower CL","","95%",""],"rows":[["Parameter","","Estimate","","95%\nLower CL","","95%",""],["","","","","","","Upper CL",""],["","Negative Likelihood Ratio","","0.11","0.06","","0.22",""],["","Positive Likelihood Ratio","","9.09","4.69","","17.62",""]],"caption_candidate":"Table 3. PLR/NLR Ratios with Two-Sided 95% Confidence Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213938-p7-t0","doc_id":"K213938","page_num":7,"bbox":[72.05,332.13,540.06,710.76],"n_rows":4,"n_cols":7,"columns":["Subsystem","","Revolution Ascend","","","Revolution Ascend",""],"rows":[["Subsystem","","Revolution Ascend","","","Revolution Ascend",""],["","","(Predicate Device, K203169)","","","(Proposed Device)",""],["Gantry","Revolution Ascend Gantry\n- Bore size: 75cm\n- Physical Tilt (± 30°)\nPerformix 40 Plus X-Ray Tube\n- Supports 40 mm beamwidth\n- Liquid Metal rotor bearing\nJEDI60DC High Voltage Generator\n- Peak Power: 72 kW\nNGX Collimator (75cm bore)\n- 40 mm max z-coverage\nMerc40L Detector\n- Backlit Diode technology\n- Chiclet Module design\n- GE low noise ASIC technology\nused for signal conversion","","","Revolution Ascend Gantry\n- Bore size: 75cm\n- Physical Tilt (± 30°)\nPerformix 40 Plus X-Ray Tube\n- Supports 40 mm beam width\n- Liquid Metal rotor bearing\nJEDI60DC High Voltage Generator\n- Peak Power: 72 kW\nNGX Collimator (75cm bore)\n- 40 mm max z-coverage\nMerc40H Detector\n(with alternative material)\n- Backlit Diode technology\n- Chiclet Module design\n- GE low noise ASIC technology\nused for signal conversion","",""],["Operator\nConsole","NIO Console:\n- Host computer, keyboard,\nscan control unit, two\nmonitors.","","","Same","",""]],"caption_candidate":"device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213938-p8-t0","doc_id":"K213938","page_num":8,"bbox":[72.05,111.49,540.06,362.78],"n_rows":4,"n_cols":7,"columns":["Subsystem","","Revolution Ascend","","","Revolution Ascend",""],"rows":[["Subsystem","","Revolution Ascend","","","Revolution Ascend",""],["","","(Predicate Device, K203169)","","","(Proposed Device)",""],["Deep Learning\nImage\nReconstruction\n(DLIR)","DLIR cleared with Revolution Ascend\n(K212067).","","","Same","",""],["Standards","IEC 60601-1 Ed. 3.1\nIEC 60601-1-2 Ed 4.0\nIEC 60601-1-3 Ed 2.1\nIEC 60601-2-28 Ed 3.0\nIEC 60601-2-44 Ed. 3.2\nIEC 61223-3-5 Ed. 1.0\nNEMA XR-25\nNEMA XR-26\nNEMA XR-28","","","IEC 60601-1 Ed. 3.1\nIEC 60601-1-2 Ed 4.0\nIEC 60601-1-3 Ed 2.1\nIEC 60601-2-28 Ed 3.0\nIEC 60601-2-44 Ed. 3.2\nIEC 61223-3-5 Ed. 2.0\nNEMA XR-25\nNEMA XR-26\nNEMA XR-28","",""]],"caption_candidate":"510(k) Premarket Notification Submission for Revolution Ascend","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213941-p4-t0","doc_id":"K213941","page_num":4,"bbox":[72.79,173.59,540.23,272.55],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level 21, 60 Margaret Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 2 7204 0817"],["","Contact Person","","Michele Houldsworth"],["","Date Prepared","","December 16, 2021"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213941-p4-t1","doc_id":"K213941","page_num":4,"bbox":[72.79,344.95,540.23,415.83],"n_rows":4,"n_cols":4,"columns":["","Device Name","","Annalise Enterprise CXR Triage Pneumothorax"],"rows":[["","Device Name","","Annalise Enterprise CXR Triage Pneumothorax"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","Class II"],["","Product Code","","QFM"]],"caption_candidate":"II. DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213941-p4-t2","doc_id":"K213941","page_num":4,"bbox":[72.79,488.23,540.23,587.67],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Behold.AI Technologies Limited"],"rows":[["","Manufacturer Name","","Behold.AI Technologies Limited"],["","Device Name","","Red Dot"],["","510(k) reference","","K191556"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213944-p4-t0","doc_id":"K213944","page_num":4,"bbox":[72.48,546.88,540.54,661.48],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Predicate Device:\nAI-Rad Companion (Musculoskeletal)"],"rows":[["Proprietary Name","Predicate Device:\nAI-Rad Companion (Musculoskeletal)"],["Premarket Notification","K193267"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"The HealthOST device is substantially equivalent to the following Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213944-p8-t0","doc_id":"K213944","page_num":8,"bbox":[72.84,207.76,540.69,610.91],"n_rows":2,"n_cols":3,"columns":["","Proposed Device:\nHealthOST Device","Primary Predicate Device:\nAI-Rad Companion\n(Musculoskeletal) (K193267)"],"rows":[["","Proposed Device:\nHealthOST Device","Primary Predicate Device:\nAI-Rad Companion\n(Musculoskeletal) (K193267)"],["Intended Use/\nIndications for\nUse","HealthOST is an image processing\nsoftware that provides qualitative and\nquantitative analysis of the spine from\nCT images to support clinicians in the\nevaluation and assessment of\nmusculoskeletal disease of the spine.\nThe HealthOST software provides the\nfollowing functionality:\n• Labelling of T1-L4 vertebrae\n• Measurement of height loss in\neach vertebra (T1-L4)\n• Measurement of mean\nHounsfield Units in volume of\ninterest within vertebra (T11-\nL4)\nHealthOST is indicated for use in\npatients aged 50 and over undergoing\nCT scan for any clinical indication that\nincludes at least two vertebrae in the T1-\nL4 portion of the spine (for vertebral\nheight loss) and/or T11-L4 (for bone\nattenuation) portions of the spine.\nThe device is indicated for FBP-\nreconstructed images only.","AI-Rad Companion (Musculoskeletal)\nis an image processing software that\nprovides quantitative and qualitative\nanalysis from previously acquired\nComputed Tomography DICOM\nimages to support radiologists and\nphysicians from emergency medicine,\nspecialty care, urgent care, and general\npractice in the evaluation and\nassessment of musculoskeletal disease.\nIt provides the following functionality:\n• Segmentation of vertebras\n• Labelling of vertebras\n• Measurements of heights in each\nvertebra and indication if they are\ncritically different\n• Measurement of mean Hounsfield\nvalue in volume of interest within\nvertebra.\nOnly DICOM images of adult patients\nare considered to be valid input"]],"caption_candidate":"(Musculoskeletal) K193267.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213944-p9-t0","doc_id":"K213944","page_num":9,"bbox":[72.89,218.75,540.69,709.83],"n_rows":12,"n_cols":6,"columns":["Technological\nCharacteristics","","Proposed Device:\nHealthOST Device","Primary Predicate\nDevice:\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Summary",""],"rows":[["Technological\nCharacteristics","","Proposed Device:\nHealthOST Device","Primary Predicate\nDevice:\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Summary",""],["Regulation","","","","",""],["Product Code","","JAK","JAK","Same",""],["Regulation Number","","21 CFR §892.1750","21 CFR §892.1750","",""],["General","","","","",""],["Modality","","CT","CT","Same",""],["Image format","","DICOM","DICOM","Same",""],["","Analysis and Measurement","","","",""],["Detection of Vertebra","","Yes","Yes","Same",""],["Labeling of Vertebra","","Yes","Yes","Same",""],["Segmentation of\nVertebra","","Deep-learning-based\nsegmentation of\nvertebras","Deep-learning-based\nsegmentation of\nvertebras","Same",""],["Measurement of\nVertebral Heights","","Yes, comparison with\nneighboring\nmeasurements\nApplication of Genant\ncriteria, indication if\ncritically different","Yes, comparison with\nneighboring\nmeasurements.\nApplication of Genant\ncriteria, indication if\ncritically different","Same",""]],"caption_candidate":"Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213944-p10-t0","doc_id":"K213944","page_num":10,"bbox":[72.92,80.97,540.64,400.86],"n_rows":3,"n_cols":4,"columns":["Measurement of\nHounsfield (HU) value","HU measurements\nbased on segmentation\nresults\nIndication to user if\noutside reference range","HU measurements\nbased on segmentation\nresults","Similar, the subject\ndevice highlights HU\noutside of reference\nrange. This does not\nraise new questions of\nsafety and\neffectiveness."],"rows":[["Measurement of\nHounsfield (HU) value","HU measurements\nbased on segmentation\nresults\nIndication to user if\noutside reference range","HU measurements\nbased on segmentation\nresults","Similar, the subject\ndevice highlights HU\noutside of reference\nrange. This does not\nraise new questions of\nsafety and\neffectiveness."],["Reporting","","",""],["Device output","1. Vertebrae\nlabel/name\n2. 3 lines representing\nthe anterior, middle,\nand posterior points\nmeasures, together\nwith relative\nmeasurements\n3. % Height loss and\nrelative Genant\ncategory (20)\n4. Bone density\nmeasured in HU","1. Vertebrae\nlabel/name\n2. 3 lines representing\nthe anterior, middle,\nand posterior points\nmeasures, together\nwith relative\nmeasurements\n3. Bone density\nmeasured in HU","Similar, new\ninformation does not\nraise new questions of\nsafety and\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p4-t0","doc_id":"K213960","page_num":4,"bbox":[28.98,443.74,567.41,669.92],"n_rows":11,"n_cols":12,"columns":["","","","","Subject Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],"rows":[["","","","","Subject Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],["","510(k) number","","Not known","","","K202170","","","K043271","",""],["","Legal Manufacturer","","Perspectum Ltd.","","","Perspectum Ltd.","","","Inner Vision Biometrics Pty","",""],["","Owner/Owner Operator","","10056574","","","10056574","","","Ltd / /","",""],["NDeuvmicbee Nr ame","NDeuvmicbee Nr ame","","LiverMultiScan v5.0.0","","","LiverMultiScan v4.0.0","","","R2-MRI Analysis System\n(FerriScan)","",""],["","Proprietary/Common","","LiverMultiScan, LMSv5, LMS","","","LiverMultiScan, LMSv4, LMS","","","FerriScan","",""],["","nPaanmeel","","Radiology","","","Radiology","","","Radiology","",""],["","Regulation","","892.1000","","","892.1000","","","892.1000","",""],["","Risk Class","","Class II","","","Class II","","","Class II","",""],["","Product Class code","","LNH","","","LNH","","","LNH","",""],["Classification","Classification","","System, Nuclear Magnetic\nResonance Imaging","","","System, Nuclear Magnetic\nResonance Imaging","","","System, Nuclear Magnetic\nResonance Imaging","",""]],"caption_candidate":"Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p7-t0","doc_id":"K213960","page_num":7,"bbox":[148.94,125.98,716.71,442.66],"n_rows":4,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["Intended\nUse","","","","",""]],"caption_candidate":"The following characteristics were compared between the subject device and the predicate device in order to demonstrate substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p8-t0","doc_id":"K213960","page_num":8,"bbox":[148.93,76.06,716.72,504.1],"n_rows":5,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["","LMSv5 provides several tools, such as\nautomated liver segmentation and\nregion of interest (ROI) placements,\nto be used for the assessment of\nselected regions of an image.\nQuantitative assessment of selected\nregions includes the determination of\ntriglyceride fat fraction in the liver\n(PDFF), T2*, LIC (Liver Iron\nConcentration) and iron corrected T1\n(cT1) measurements.\nThese images and the physical\nparameters derived from the images,\nwhen interpreted by a trained\nclinician, yield information that may\nassist in diagnosis.","LiverMultiScan (LMSv4) provides a\nnumber of tools, such as automated\nliver segmentation and region of\ninterest (ROI) placements, to be used\nfor the assessment of selected\nregions of an image. Quantitative\nassessments of selected regions\ninclude the determination of\ntriglyceride fat fraction in the liver\n(PDFF), T2* and iron-corrected T1\n(cT1) measurements. T2* may be\noptionally computed using the DIXON\nor LMS MOST methods.\nThese images and the physical\nparameters derived from the images,\nwhen interpreted by a trained\nclinician, yield information that may\nassist in diagnosis.","","",""],["Indications\nfor Use","Same as intended use","Same as intended use","The R2-MRI Analysis System\nis an accessory diagnostic\ndevice to MRI scanners and\nis intended for diagnostic\nuse to present images that\nreflect the magnetic\nresonance spectra for the\ndetermination of iron on the\nliver.","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p9-t0","doc_id":"K213960","page_num":9,"bbox":[148.92,76.06,716.73,520.66],"n_rows":9,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["Target\nPopulation","Patients suitable to undergo an MRI\nscan and not contra-indicated for MRI","Patients suitable to undergo an MRI\nscan and not contra-indicated for MRI","Patients suitable to undergo\nan MRI scan and not contra-\nindicated for MRI","",""],["Device User","Trained Perspectum internal operator","Trained Perspectum internal operator","Resonance Health’s trained\nanalyst","",""],["Report User","An interpreting clinician or healthcare\npractitioner","An interpreting clinician or healthcare\npractitioner","An interpreting clinician or\nhealthcare practitioner","",""],["Device Use\nEnvironment","Installation of LiverMultiScan v5 is\ncontrolled and is installed on general\npurpose workstations that meet the\nminimum technical requirements at\nPerspectum’s image analysis centre\nby specialist members of staff.","Installation of LMSv4 is controlled and\nis installed on general purpose\nworkstations that meet the minimum\ntechnical requirements at\nPerspectum’s image analysis centre\nby specialist members of staff.","Image analysis and LIC\nreporting is performed at a\ncentral ISO 13485 certified\nService Centre. Hosting\nplatform is resonance\nhealth’s internal server.","",""],["Clinical\nSetting","LiverMultiScan v5 is a standalone\npost-processing software device that\nis intended to be installed on general\nuse workstations at Perspectum’s\nimage analysis centre.\nOperators use LMSv5 to conduct\nquantitative analysis of liver tissue\ncharacteristics to produce a report.\nThe end-users for the output from\nthe device, the report, are clinicians\nwho receive and interpret\nLiverMultiScan (LMSv5) reports.","LMSv4 is a standalone post-\nprocessing software device that is\nintended to be installed on general\nuse workstations at Perspectum’s\nimage analysis centre.\nOperators use LMS to conduct\nquantitative analysis of liver tissue\ncharacteristics to produce a report.\nThe end-users for the output from\nthe device, the report, are clinicians\nwho receive and interpret LMSv4\nreports.","FerriScan is a standalone\nsoftware tool that is\nintended to be used by\nResonance Health’s trained\nanalyst, FerriScan is installed\nand runs on the Resonance\nHealth’s internal server.\nThe report result is overseen\nby the radiologist and the\nfinal decision for clinical\nmanagement of the patient\nis made by their treating\nclinician.","",""],["Anatomical\nLocation","Abdomen, including the liver","Abdomen, including the Liver","Abdomen, including the\nLiver.","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p10-t0","doc_id":"K213960","page_num":10,"bbox":[148.94,76.06,716.71,495.94],"n_rows":5,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["Energy","LiverMultiScan v5 is a standalone\nsoftware application, it does not\ndeliver, monitor or depend on energy\ndelivered to or from patients.","LMS is a standalone software\napplication, it does not deliver,\nmonitor or depend on energy\ndelivered to or from patients.","FerriScan is a standalone\nsoftware application. It does\nnot deliver, monitor or\ndepend on energy delivered\nto or from patients.","",""],["Design:\nPurpose","LiverMultiScan v5 is a standalone\nsoftware application that imports MR\ndata sets encompassing the\nabdomen, including the liver.\nVisualisation and display of 2D multi-\nslice, spin-echo MR data can be\nanalysed and quantitative metrics of\ntissue characteristics are then\nreported.\nDatasets imported into\nLiverMultiScan (LMSv5) are DICOM\n3.0 compliant, reported metrics are\nindependent of the MRI equipment\nvendor.","LMS is a standalone software\napplication that imports MR data sets\nencompassing the abdomen,\nincluding the liver. Visualisation and\ndisplay of 2D multi-slice, spin-echo\nMR data can be analysed and\nquantitative metrics of tissue\ncharacteristics are then reported.\nDatasets imported into LMS are\nDICOM 3.0 compliant, reported\nmetrics are independent of the MRI\nequipment vendor.","FerriScan is intended for:\n• Supporting clinical\ndiagnoses about the\nstatus of liver iron\nconcentration.\n• Supporting the\nsubsequent clinical\ndecision-making\nprocesses.\n• Supporting the use in\nclinical research trials,\ndirected at studying\nchanges in liver iron\nconcentration as a\nresult of interventions.\n• It contains an image\nviewer for importing\nDICOM images,\nbrowsing through\npatient datasets,\nviewing images and\nperforming region of\ninterest analysis","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p11-t0","doc_id":"K213960","page_num":11,"bbox":[148.92,76.06,716.72,534.82],"n_rows":7,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["Design: Tools","Allows for the visualisation via\nparametric maps and quantification\nof metrics (cT1, LIC and PDFF) from\nliver tissue and exportation of results\n& images to a deliverable report.\nQuantification is through either full\nsegmentation of the outer liver\ncontour and liver vasculature or\nmanual placement of ROI’s on the\nparametric maps. IQR and median\nmetrics are reported from the\nsegmentation/ROI quantification.\nautomatically detects artefacts on the\nand are delineated on the parametric\nmap computed images as well as\nrecommends slices to be used as the\nquantitative output of the device.","Allows for the visualisation via\nparametric maps and quantification\nof metrics (cT1, T2* and PDFF) from\nliver tissue and exportation of results\n& images to a deliverable report.\nQuantification is through either full\nsegmentation of the outer liver\ncontour and liver vasculature or\nmanual placement of ROI’s on the\nparametric maps. IQR and median\nmetrics are reported from the\nsegmentation/ROI quantification.","Allows for the visualisation\nof images that reflect the\nmagnetic resonance spectra\nfor the determination of\niron on the liver. It contains\nan image viewer for\n• importing DICOM\nimages,\n• browsing through\npatient datasets,\n• viewing images and\nperforming ROI analysis.","",""],["Design: MR\nRelaxometry","T1, iron corrected T1 (cT1) mapping\nand LIC","T1, iron corrected T1 (cT1) and T2*\nmapping","R2 (Signal Decay Rate)\nmapping","",""],["Design: Liver\nFat\nQuantificatio\nn","Utilizes MR images that exploit the\ndifference in resonance frequencies\nbetween hydrogen nuclei in water\nand triglyceride fat using the\nLiverMultiScan v5 IDEAL method.","Utilizes MR images that exploit the\ndifference in resonance frequencies\nbetween hydrogen nuclei in water\nand triglyceride fat using the LMS\nIDEAL method.","N/A","",""],["Design:\nParametric\nMaps","Iron corrected T1 (cT1), Proton\nDensity Fat Fraction (PDFF) and LIC\nparametric maps can be created from\nall supported scanners.","Iron corrected T1 (cT1), T2* and\nProton Density Fat Fraction (PDFF)\nparametric maps can be created from\nall supported scanners.","FerriScan calculates the\nsignal decay rate (R2) that is\nused to characterise iron\nloading in the liver. It\nproduces an output report","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p12-t0","doc_id":"K213960","page_num":12,"bbox":[148.94,76.06,716.71,533.86],"n_rows":5,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["","It is possible to use the LIC maps and\nknowledge of the measurements and\nthe scanner field strength to correct\nfor signal changes related to iron\ndeposits, producing a cT1 map. The\ncT1 map eliminates the effects of\nelevated iron from the T1\nmeasurement (3) and standardizes\nfor the fat signal across scanner\nmanufacturers.\nPDFF is quantified using the LMS\nIDEAL method. Parametric maps of\nLIC are quantified using the LMS\nMOST method.\nLMSv5 uses the measured T2* value\nand uses them to characterise iron\nloading in the liver which is then\ntransformed by a defined calibration\ncurve to provide a quantitative\nmeasure of liver iron concentration in\nvivo. LMSv5 presents images that\nreflect the magnetic resonance\nspectra for iron determination on the\nliver.","It is possible to use the T2* and PDFF\nmaps and knowledge of the T2* and\nPDFF measurements and the scanner\nfield strength to correct for signal\nchanges related to iron deposits,\nproducing a cT1 map. The cT1 map\neliminates the effects of elevated iron\nfrom the T1 measurement (3) and\nstandardizes for the fat signal across\nscanner manufacturers.\nPDFF is quantified using the LMS\nIDEAL method. Parametric maps of\nT2* may optionally be computed\nusing either the three-point DIXON\nmethod or the LMS MOST method.","comprising R2 which is\ntransformed by a defined\ncalibration curve into a\nquantitative measure of liver\niron concentration in vivo.\nFerriScan presents images\nthat reflect the magnetic\nresonance spectra for iron\ndetermination on the liver.","",""],["Design:\nVisualisation","Numerous views within the\nLiverMultiScan v5 interface can be\nused to assist in analysis of Iron\ncorrected T1 (cT1), triglyceride fat\n(also known as Proton Density Fat\nFraction (PDFF)) and LIC parametric","Numerous views within the LMSv4\ninterface can be used to assist in\nanalysis, Iron-corrected T1 (cT1), T2*\nand triglyceride fat (also known as\nProton Density Fat Fraction (PDFF))\nparametric maps can be created from","Visualisation of multi-slice,\nspin-echo MRI data sets\nencompassing the\nabdomen.\nSoftware tool calculates the\nsignal decay rate (R2) that is","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213960-p13-t0","doc_id":"K213960","page_num":13,"bbox":[148.94,76.06,716.71,292.18],"n_rows":5,"n_cols":6,"columns":["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],"rows":[["Characteristi\nc","LMSv5 (Subject device)","LMSv4 (Primary Predicate Device)","","R2-MRI Analysis System",""],["","","","","(FerriScan) (Secondary",""],["","","","","Predicate)",""],["","maps can be created from all\nsupported scanners.\nParametric maps displayed using the\nLMSv5 colourmap, designed to have\nmaximum contrast on liver\nparenchymal tissue.","all supported scanners. R2 maps can\nalso be utilised to assess the quality\nof the map fitting.\nIron- corrected T1 (cT1) displayed\nusing LMSv4 colourmap, designed to\nhave maximum contrast on liver\nparenchymal tissue.","used to characterise iron\nloading in the liver, which is\nthen transformed by a\ndefined calibration curve to\nprovide a quantitative\nmeasure of liver iron\nconcentration in vivo.\nLIC is displayed on a map\nand histogram within the\nFerriScan LIC report.","",""],["Design:\nSupported\nModalities","DICOM 3.0 compliant MR data from\nsupported MRI scanners.","DICOM 3.0 compliant MR data from\nsupported MRI scanners.","DICOM Image Format.\nFunctionality independent\nof MRI equipment vendor.","",""]],"caption_candidate":"LMSv5 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213976-p12-t0","doc_id":"K213976","page_num":12,"bbox":[184.79,607.8,463.2,708.96],"n_rows":5,"n_cols":3,"columns":["Structure:","MIM Atlas","Contour ProtégéAI"],"rows":[["Structure:","MIM Atlas","Contour ProtégéAI"],["A_Aorta_Desc","0.73 ± 0.15","0.78 ± 0.07 (0.68) *"],["Bladder","0.80 ± 0.12","0.94 ± 0.02 (0.86) *"],["Bone","0.80 ± 0.03","0.83 ± 0.05 (0.76) *"],["Bone_Mandible","0.79 ± 0.16","0.83 ± 0.04 (0.74) *"]],"caption_candidate":"Results over the validation set compared to the reference device are presented here:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213976-p13-t0","doc_id":"K213976","page_num":13,"bbox":[184.7,127.7,463.3,700.44],"n_rows":28,"n_cols":3,"columns":["Structure:","MIM Atlas","Contour ProtégéAI"],"rows":[["Structure:","MIM Atlas","Contour ProtégéAI"],["Bowel †","0.60 ± 0.13","0.75 ± 0.07 (0.68) *"],["Bowel_Large","0.15 ± 0.12","0.28 ± 0.20 (0.15) *"],["Bowel_Small","0.29 ± 0.17","0.42 ± 0.19 (0.29) *"],["BrachialPlex_L","0.32 ± 0.11","0.37 ± 0.13 (0.27) *"],["BrachialPlex_R","0.38 ± 0.13","0.41 ± 0.10 (0.31) *"],["Brain","0.97 ± 0.01","0.96 ± 0.01 (0.95) *"],["Brainstem","0.77 ± 0.12","0.76 ± 0.12 (0.68) *"],["Breast_L","0.81 ± 0.06","0.81 ± 0.06 (0.76) *"],["Breast_R","0.83 ± 0.06","0.83 ± 0.06 (0.77) *"],["Bronchus","0.57 ± 0.12","0.62 ± 0.11 (0.54) *"],["Carina","0.54 ± 0.18","0.64 ± 0.17 (0.52) *"],["CaudaEquina","0.74 ± 0.09","0.72 ± 0.06 (0.64) *"],["Cavity_Oral","0.79 ± 0.10","0.81 ± 0.11 (0.73) *"],["Cochlea_L","0.39 ± 0.15","0.41 ± 0.17 (0.30) *"],["Cochlea_R","0.43 ± 0.15","0.46 ± 0.17 (0.34) *"],["Colon_Sigmoid","0.08 ± 0.09","0.50 ± 0.19 (0.33) *"],["Esophagus","0.43 ± 0.17","0.56 ± 0.19 (0.47) *"],["Eye_L","0.83 ± 0.10","0.82 ± 0.06 (0.77) *"],["Eye_R","0.81 ± 0.13","0.78 ± 0.06 (0.71) *"],["Femur_Head_L","0.93 ± 0.04","0.90 ± 0.06 (0.86) *"],["Femur_Head_R","0.93 ± 0.03","0.93 ± 0.03 (0.91) *"],["Femur_L","0.96 ± 0.01","0.95 ± 0.01 (0.93) *"],["Femur_R","0.96 ± 0.02","0.94 ± 0.01 (0.91) *"],["Genitals","0.64 ± 0.11","0.68 ± 0.13 (0.53) *"],["Glnd_Lacrimal_L","0.29 ± 0.15","0.39 ± 0.20 (0.24) *"],["Glnd_Lacrimal_R","0.31 ± 0.15","0.38 ± 0.22 (0.23) *"],["Glnd_Submand_L","0.68 ± 0.10","0.78 ± 0.07 (0.71) *"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213976-p14-t0","doc_id":"K213976","page_num":14,"bbox":[184.7,127.7,463.3,700.44],"n_rows":28,"n_cols":3,"columns":["Structure:","MIM Atlas","Contour ProtégéAI"],"rows":[["Structure:","MIM Atlas","Contour ProtégéAI"],["Glnd_Submand_R","0.67 ± 0.11","0.76 ± 0.06 (0.69) *"],["Glnd_Thyroid","0.51 ± 0.14","0.57 ± 0.18 (0.44) *"],["GreatVes","0.75 ± 0.06","0.71 ± 0.08 (0.65) *"],["Heart","0.85 ± 0.08","0.89 ± 0.04 (0.86) *"],["Humerus_Head_L †","0.88 ± 0.07","0.91 ± 0.04 (0.87) *"],["Humerus_Head_R †","0.88 ± 0.09","0.91 ± 0.03 (0.85) *"],["Kidney_L","0.76 ± 0.14","0.91 ± 0.03 (0.83) *"],["Kidney_R","0.74 ± 0.18","0.89 ± 0.04 (0.80) *"],["Larynx","0.52 ± 0.15","0.57 ± 0.18 (0.44) *"],["Lens_L","0.30 ± 0.17","0.52 ± 0.10 (0.41) *"],["Lens_R","0.36 ± 0.14","0.65 ± 0.09 (0.56) *"],["Lips","0.39 ± 0.14","0.57 ± 0.18 (0.43) *"],["Liver","0.84 ± 0.12","0.93 ± 0.04 (0.87) *"],["LN_Pelvic","0.76 ± 0.03","0.80 ± 0.04 (0.77) *"],["Lung_L","0.94 ± 0.03","0.95 ± 0.02 (0.93) *"],["Lung_R","0.95 ± 0.02","0.95 ± 0.02 (0.94) *"],["Musc_Constrict","0.44 ± 0.12","0.50 ± 0.17 (0.38) *"],["OpticChiasm","0.34 ± 0.16","0.37 ± 0.17 (0.25) *"],["OpticNrv_L","0.46 ± 0.12","0.52 ± 0.10 (0.44) *"],["OpticNrv_R","0.50 ± 0.10","0.54 ± 0.09 (0.47) *"],["Parotid_L","0.68 ± 0.13","0.81 ± 0.04 (0.74) *"],["Parotid_R","0.71 ± 0.10","0.78 ± 0.05 (0.72) *"],["PenileBulb","0.62 ± 0.12","0.65 ± 0.11 (0.56) *"],["Pituitary","0.53 ± 0.15","0.56 ± 0.18 (0.43) *"],["Prostate","0.71 ± 0.12","0.82 ± 0.06 (0.74) *"],["Rectum","0.67 ± 0.14","0.76 ± 0.08 (0.67) *"],["SeminalVes","0.58 ± 0.15","0.70 ± 0.08 (0.60) *"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213976-p15-t0","doc_id":"K213976","page_num":15,"bbox":[184.79,127.7,463.2,228.84],"n_rows":5,"n_cols":3,"columns":["Structure:","MIM Atlas","Contour ProtégéAI"],"rows":[["Structure:","MIM Atlas","Contour ProtégéAI"],["Spinal_Cord","0.76 ± 0.10","0.82 ± 0.07 (0.78) *"],["Spleen","0.78 ± 0.14","0.91 ± 0.07 (0.80) *"],["Stomach","0.45 ± 0.20","0.79 ± 0.09 (0.69) *"],["Trachea","0.77 ± 0.09","0.73 ± 0.07 (0.67) *"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p4-t0","doc_id":"K213986","page_num":4,"bbox":[108.26,451.87,540.22,480.43],"n_rows":2,"n_cols":4,"columns":["510(k) Number","Product Code","Trade Name","Manufacturer"],"rows":[["510(k) Number","Product Code","Trade Name","Manufacturer"],["K192692","LLZ","Brainomix 360° e-CTA","Brainomix Limited"]],"caption_candidate":"Table 1 Predicate device information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p5-t0","doc_id":"K213986","page_num":5,"bbox":[72.26,486.31,534.12,671.76],"n_rows":6,"n_cols":3,"columns":["Characteristics","Predicate Device","Subject Device"],"rows":[["Characteristics","Predicate Device","Subject Device"],["","Brainomix 360° e-CTA\n(K192692)","CerebralGo Plus\n(K213986)"],["","Brainomix Limited","Yukun (Beijing) Technology Co.,\nLtd"],["Regulatory Class","Class II","Class II"],["Product Code","LLZ","QIH, LLZ"],["Regulation","21 CFR 892.2050","21 CFR 892.2050"]],"caption_candidate":"Table 2 Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p6-t0","doc_id":"K213986","page_num":6,"bbox":[72.26,72.26,534.12,690.48],"n_rows":5,"n_cols":3,"columns":["Device Description","Brainomix 360° e-CTA is a\nsoftware package that provides\nfor the study of changes of\ntissue in digital images\ncaptured by CT. Brainomix\n360° e-CTA provides viewing\nand quantification for CTA\nimages.","CerebralGo Plus is a software\npackage that provides for the\nvisualization digital images\ncapture by\nCTA."],"rows":[["Device Description","Brainomix 360° e-CTA is a\nsoftware package that provides\nfor the study of changes of\ntissue in digital images\ncaptured by CT. Brainomix\n360° e-CTA provides viewing\nand quantification for CTA\nimages.","CerebralGo Plus is a software\npackage that provides for the\nvisualization digital images\ncapture by\nCTA."],["Intended\nUse/Indications for\nUse","Brainomix 360° e-CTA is an\nimage processing software\npackage to be used by trained\nprofessionals, including, but\nnot\nlimited to physicians and\nmedical technicians. The\nsoftware runs on standard “off-\nthe-shelf” hardware (physical\nor virtualized) and can be used\nto perform image viewing,\nprocessing and analysis of\nimages. Data and images are\nacquired through DICOM\ncompliant imaging devices.\nBrainomix 360° e-CTA\nprovides viewing and analysis\ncapabilities for imaging\ndatasets acquired with CTA\n(CT Angiography).\nBrainomix 360° e-CTA is not\nintended for mobile diagnostic\nuse.","CerebralGo Plus is an image\nprocessing software package to be\nused by trained professionals,\nincluding, but not limited to\nphysicians and medical\ntechnicians. The software runs on\nstandard “off-the-shelf” hardware\nand can be used for image\nviewing and processing. Data and\nimages are acquired through\nDICOM compliant imaging\ndevices.\nCerebralGo Plus provides\nviewing and processing\ncapabilities for imaging datasets\nacquired with adult’s CTA (CT\nAngiography).\nCerebralGo Plus is not intended\nfor primary diagnostic use."],["Environment of Use","Clinical/Hospital Environment","Clinical/Hospital Environment"],["Energy used an/or\ndelivered","None—software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","None—software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to or\nfrom patients"],["End User","Trained clinicians","Trained clinicians"]],"caption_candidate":"CerebralGo Plus, Yukun (Beijing) Technology Co., Ltd.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p7-t0","doc_id":"K213986","page_num":7,"bbox":[72.26,72.26,534.12,358.39],"n_rows":7,"n_cols":3,"columns":["Supported Modalities\nfor image processing\nand visualization","CTA","CTA"],"rows":[["Supported Modalities\nfor image processing\nand visualization","CTA","CTA"],["PACS Functionality","View process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and listing","View process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and listing"],["DICOM Compliance","Yes","Yes"],["Computer Platform","Standard Physical and Virtual\noff-the shelf Server","Standard off-the shelf server"],["Data Acquisition","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities"],["CTA modality","CTA large vessel","CTA large vessel"],["Performance Data","Stand-alone software\nperformance testing","Stand-alone software\nperformance testing"]],"caption_candidate":"CerebralGo Plus, Yukun (Beijing) Technology Co., Ltd.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p7-t1","doc_id":"K213986","page_num":7,"bbox":[137.18,574.54,474.94,708.33],"n_rows":6,"n_cols":3,"columns":["Demographic information","","Quantity"],"rows":[["Demographic information","","Quantity"],["Gender","Male","68"],["","Female","73"],["Age","＜40","6"],["","40~70","58"],["","＞70","54"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p8-t0","doc_id":"K213986","page_num":8,"bbox":[136.53,72.26,475.59,215.18],"n_rows":6,"n_cols":3,"columns":["","Unknown","23"],"rows":[["","Unknown","23"],["Ethnicity","Black or African American","1"],["","Hispanic/Latino","2"],["","Non-Hispanic/Latino","82"],["","White","5"],["","Unknown","51"]],"caption_candidate":"CerebralGo Plus, Yukun (Beijing) Technology Co., Ltd.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p8-t1","doc_id":"K213986","page_num":8,"bbox":[136.53,229.61,475.59,340.94],"n_rows":5,"n_cols":3,"columns":["Equipment information","","Quantity"],"rows":[["Equipment information","","Quantity"],["Equipment","GE","4"],["","Siemens","6"],["","Philips","101"],["","Toshiba","30"]],"caption_candidate":"Unknown 51","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213986-p8-t2","doc_id":"K213986","page_num":8,"bbox":[122.06,499.66,490.06,698.16],"n_rows":9,"n_cols":4,"columns":["Parameter","","Dice","HD95"],"rows":[["Parameter","","Dice","HD95"],["Equipment","TOSHIBA","0.936","3.979"],["","Philips","0.945","3.494"],["","SIEMENS","0.942","1.328"],["","GE","0.924","10.098"],["Gender","Female","0.941","3.702"],["","Male","0.944","3.682"],["Age","<40","0.955","1.000"],["","40-70","0.946","2.426"]],"caption_candidate":"results were shown in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213998-p7-t0","doc_id":"K213998","page_num":7,"bbox":[54.44,123.42,737.48,538.69],"n_rows":40,"n_cols":13,"columns":["","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],"rows":[["","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],["","","cvi42 Auto (K213998)","","","cmr42 (K082628)","","","cvi42 (K141480)","","","ct42 (K111373)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["Intended Use","","Viewing, post-processing,","","Viewing, post-processing,\nqualitative and quantitative\nevaluation of cardiovascular MR\nimages in DICOM format.","Viewing, post-processing,","","","Viewing, post-processing,","","Viewing, post-processing,\nqualitative and quantitative\nevaluation of cardiovascular CT\nimages in DICOM format.","Viewing, post-processing,",""],["","","qualitative and quantitative","","","qualitative and quantitative","","","qualitative and quantitative","","","qualitative and quantitative",""],["","","evaluation of blood vessels and","","","evaluation of cardiovascular MR","","","evaluation of blood vessels and","","","evaluation of cardiovascular CT",""],["","","cardiovascular MR and CT images","","","images in DICOM format.","","","cardiovascular MR and CT images","","","images in DICOM format.",""],["","","in DICOM format.","","","","","","in DICOM format.","","","",""],["Indications for\nUse","","cvi42 Auto is intended to be used","","cmr42 is intended to be used for\nviewing, post-processing and\nquantitative evaluation of\ncardiovascular magnetic resonance\n(MR) images in a Digital Imaging\nand Communications in Medicine\n(DICOM) Standard format.\nIt enables;\n• Importing Cardiac MR Images in\nDICOM format\n• Supporting clinical diagnostics by\nqualitative analysis of the cardiac\nMR images using display\nfunctionality such as panning,\nwindowing, zooming, navigation\nthrough series/slices and phases.\n• Supporting clinical diagnostics by\nquantitative measurement of the\nheart and adjacent vessels in\ncardiac MR images, specifically\ndistance, area, volume and mass\n• Supporting clinical diagnostics by\nusing area and volume\nmeasurements for measuring LV\nfunction and derived parameters\ncardiac output and cardiac index in\nlong axis and short axis cardiac MR\nimages.\n• Flow quantifications based on\nvelocity encodes images","","","","cvi42 vascular analysis add-on is","","","ct42 is intended to be used for",""],["","","for viewing, post-processing,","","","","","","an image analysis software","","","viewing, post-processing and",""],["","","qualitative and quantitative","","","","","","package add-on for evaluating CT","","","quantitative evaluation of",""],["","","evaluation of cardiovascular","","","","","","and MR images of blood vessels.","","","cardiovascular computed",""],["","","magnetic resonance (MR) and","","","","","","Combining digital image processing","","","tomography (CT) images in a",""],["","","computed tomography (CT) images","","","","","","and visualization tools such as","","","Digital Imaging and",""],["","","in a Digital Imaging and","","","","","","multiplaner reconstruction (MPR),","","","Communications in Medicine",""],["","","Communications in Medicine","","","","","","thin/think maximum intensity","","","(DICOM) Standard format.",""],["","","(DICOM) Standard format.","","","","","","projection (MIP) thin and think,","","","It enables:",""],["","","","","","","","","inverted MIP thin and think, volume","","","• Importing Cardiac CT Images in",""],["","","It enables a set of tools to assist","","","","","","rendering technique (VRT), curved","","","DICOM format",""],["","","physicians in qualitative","","","","","","planner reformation, processing","","","• Supporting clinical diagnostics by",""],["","","assessment of cardiac images and","","","","","","tools such as bone removal (based","","","qualitative analysis of the cardiac",""],["","","quantitative measurements of the","","","","","","on both single energy and dual","","","CT images using display",""],["","","heart and adjacent vessels;","","","","","","energy) table removal and","","","functionality such as panning,",""],["","","perform calcium scoring; and to","","","","","","evaluation tools (vessel centerline","","","windowing, zooming, navigation",""],["","","confirm the presence or absence of","","","","","","calculation, lumen calculation,","","","through series/slices and phases,",""],["","","physician-identified lesion in blood","","","","","","stenosis calculation) and reporting","","","3D reconstruction of images",""],["","","vessels.","","","","","","tools (lesion location, lesion","","","including multi-lanner",""],["","","","","","","","","characteristics) and key images),","","","reconstructions of the images.",""],["","","The target population for cvi42","","","","","","the software package is designed","","","• Supporting clinical diagnostics by",""],["","","Auto’s manual workflows is not","","","","","","to support the physician in","","","quantitative measurement of the",""],["","","restricted; however, cvi42 Auto’s","","","","","","conforming the presence or","","","heart and adjacent vessels in",""],["","","semi-automated machine learning","","","","","","absence of physician identified","","","cardiac CT images, specifically",""],["","","algorithms are intended for an adult","","","","","","lesion in blood vessels and","","","distance, area, volume and mass",""],["","","population.","","","","","","evaluation, documentation and","","","• Supporting clinical diagnostics by",""],["","","","","","","","","follow up of any such lesions.","","","using area and volume",""],["","","cvi42 Auto shall be used only for","","","","","","","","","measurements for measuring LV",""],["","","cardiac images acquired from an","","","","","","It shall be used by qualified medical","","","function and derived parameters",""],["","","MR or CT scanner. It shall be used","","","","","","professionals, experienced in","","","cardiac output and cardiac index in",""],["","","by qualified medical professionals,","","","","","","examining and evaluating","","","long axis and short axis cardiac CT",""],["","","experienced in examining and","","","","","","cardiovascular CT or MR images,","","","images.",""]],"caption_candidate":"Table 1. Comparison to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213998-p8-t0","doc_id":"K213998","page_num":8,"bbox":[54.44,108.84,737.48,482.19],"n_rows":36,"n_cols":13,"columns":["","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],"rows":[["","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],["","","cvi42 Auto (K213998)","","","cmr42 (K082628)","","","cvi42 (K141480)","","","ct42 (K111373)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["","evaluating cardiovascular MR or\nCT images, for the purpose of\nobtaining diagnostic information as\npart of a comprehensive diagnostic\ndecision-making process.","evaluating cardiovascular MR or","","It shall be used by qualified medical\nprofessionals, experienced in\nexamining and evaluating\ncardiovascular MR images, for the\npurpose of obtaining diagnostic\ninformation as part of a\ncomprehensive diagnostic decision-\nmaking process. cmr42 is a software\napplication that can be used as a\nstand-alone product or in a\nnetworked environment.\nThe target population for the cmr42\nis not restricted, however the image\nacquisition by a cardiac magnetic\nresonance scanner may limit the\nuse of the device for certain sectors\nof the general public.\ncmr42 shall not be used to view or\nanalyze images of any part of the\nbody except the cardiac magnetic\nresonance images acquired from a\ncardiovascular magnetic resonance\nscanner.","It shall be used by qualified medical","","for the purpose of obtaining\ndiagnostic information as part of a\ncomprehensive diagnostic decision-\nmaking process. cvi42 is a software\napplication that can be used as a\nstand-alone product or in a\nnetworked environment.\nThe target population for the cvi42\nis not restricted.","for the purpose of obtaining","","","• Supporting clinical diagnostics by",""],["","","CT images, for the purpose of","","","professionals, experienced in","","","diagnostic information as part of a","","","quantitative measurements of",""],["","","obtaining diagnostic information as","","","examining and evaluating","","","comprehensive diagnostic decision-","","","calcified plaques in the coronary",""],["","","part of a comprehensive diagnostic","","","cardiovascular MR images, for the","","","making process. cvi42 is a software","","","arteries (calcium scoring),",""],["","","decision-making process.","","","purpose of obtaining diagnostic","","","application that can be used as a","","","specifically Agatston and volume",""],["","","","","","information as part of a","","","stand-alone product or in a","","","and mass calcium scores",""],["","","","","","comprehensive diagnostic decision-","","","networked environment.","","","",""],["","","","","","making process. cmr42 is a software","","","","","","It shall be used by qualified",""],["","","","","","application that can be used as a","","","The target population for the cvi42","","","medical professionals, experienced",""],["","","","","","stand-alone product or in a","","","is not restricted.","","","in examining and evaluating",""],["","","","","","networked environment.","","","","","","cardiovascular CT images, for the",""],["","","","","","","","","","","","purpose of obtaining diagnostic",""],["","","","","","The target population for the cmr42","","","","","","information as part of a",""],["","","","","","is not restricted, however the image","","","","","","comprehensive diagnostic",""],["","","","","","acquisition by a cardiac magnetic","","","","","","decision-making process. ct42 is a",""],["","","","","","resonance scanner may limit the","","","","","","software application that can be",""],["","","","","","use of the device for certain sectors","","","","","","used as a stand-alone product or",""],["","","","","","of the general public.","","","","","","in a networked environment.",""],["","","","","","","","","","","","",""],["","","","","","cmr42 shall not be used to view or","","","","","","The target population for the ct42 is",""],["","","","","","analyze images of any part of the","","","","","","not restricted, however the image",""],["","","","","","body except the cardiac magnetic","","","","","","acquisition by a cardiac CT",""],["","","","","","resonance images acquired from a","","","","","","scanner may limit the use of the",""],["","","","","","cardiovascular magnetic resonance","","","","","","device for certain sectors of the",""],["","","","","","scanner.","","","","","","general public.",""],["","","","","","","","","","","","",""],["","","","","","","","","","","","ct42 shall not be used to view or",""],["","","","","","","","","","","","analyze images of any part of the",""],["","","","","","","","","","","","body except the cardiac CT",""],["","","","","","","","","","","","images acquired from a",""],["","","","","","","","","","","","cardiovascular CT scanner.",""],["","","","","","","","","","","","",""],["","","","","","","","","","","","",""]],"caption_candidate":"K213998 - cvi42 Auto 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213998-p9-t0","doc_id":"K213998","page_num":9,"bbox":[98.04,138.0,693.91,529.96],"n_rows":37,"n_cols":15,"columns":["Feature","","","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],"rows":[["Feature","","","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],["","","","","cvi42 Auto (K213998)","","","cmr42 (K082628)","","","cvi42 (K141480)","","","ct42 (K111373)",""],["","","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["","Device Class","","","II","","","II","","","II","","","II",""],["","Device Classification","","","QIH, LLZ","","","LLZ","","","LLZ","","","LLZ",""],["Regulation Name","Regulation Name","","","Medical image management","","","Picture Archiving and","","","Picture Archiving and","","Picture Archiving and\nCommunications System","",""],["","","","","and processing system","","","Communications System","","","Communications System","","","",""],["","Regulation Number","","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","","21 CFR 892.2050","",""],["","Imaging Modalities","","","MR and CT","","","MR","","","MR and CT","","CT","",""],["","DICOM Compliant","","","Yes","","","Yes","","","N/A","","","N/A",""],["","Import and display","","Yes","Yes","","Yes (MR only)","Yes (MR only)","","Yes","Yes","","Yes (CT only)","",""],["","MR/CT images","","","","","","","","","","","","",""],["","Post process CMR/CCT","","Yes","","","Yes (MR only)","","","Yes","","","Yes (CT only)","",""],["","images","","","","","","","","","","","","",""],["","Images can be","","Yes","","","Yes","","","N/A","","","N/A","",""],["","displayed by study and","","","","","","","","","","","","",""],["","series","","","","","","","","","","","","",""],["","Store images","","","Yes","","","Yes","","","N/A","","","N/A",""],["","2D Imaging","","","Yes","","","Yes","","","N/A","","","N/A",""],["","3D Imaging","","","Yes","","","No","","","Yes","","Yes","",""],["","Multiplanar Reformat","","Yes","Yes","","No","No","","Yes","Yes","","Yes","",""],["","(MPR)","","","","","","","","","","","","",""],["Navigation Tools","Navigation Tools","","","Panning,","","","Panning,","","N/A","","","N/A","",""],["","","","","Windowing,","","","Windowing,","","","","","","",""],["","","","","Zooming","","","Zooming","","","","","","",""],["","","","","Series/slices and phases","","","Series/slices and phases","","","","","","",""],["Measurements","","","","Distance","","","Distance","","N/A","","","N/A","",""],["","","","","Perimeter","","","Perimeter","","","","","","",""],["","","","","Area","","","Area","","","","","","",""],["","","","","Signal Intensity","","","Signal Intensity","","","","","","",""],["","","","","Volume","","","Volume","","","","","","",""],["Quantitative assessment\nof cardiac function","","","","Manual segmentation, and","","Manual segmentation of four\nheart chambers in long and\nshort-axis views","Manual segmentation of four","","Manual segmentation,\nand semi-automatic\nsegmentation of four\nheart chambers in long\nand short-axis views","","","Manual segmentation,\nand semi-automatic\nsegmentation of four\nheart chambers in short-\naxis views","",""],["","","","","semi-automatic segmentation","","","heart chambers in long and","","","","","","",""],["","","","","using Machine Learning","","","short-axis views","","","","","","",""],["","","","","technique of four heart","","","","","","","","","",""],["","","","","chambers in long and short-","","","","","","","","","",""],["","","","","axis views","","","","","","","","","",""]],"caption_candidate":"Cells marked as N/A are features already supported by the primary predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213998-p10-t0","doc_id":"K213998","page_num":10,"bbox":[98.04,108.84,693.88,214.08],"n_rows":10,"n_cols":15,"columns":["Feature","","","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],"rows":[["Feature","","","","Subject Device","","","Primary Predicate","","","Secondary Predicate","","","Tertiary Predicate",""],["","","","","cvi42 Auto (K213998)","","","cmr42 (K082628)","","","cvi42 (K141480)","","","ct42 (K111373)",""],["","","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["Centerline placement in\ncoronary vessels","","","","Manual and semi-automatic","","Manual","Manual","","Manual and semi-\nautomatic","Manual and semi-","","Manual and semi-\nautomatic","Manual and semi-",""],["","","","","using Machine Learning","","","","","","automatic","","","automatic",""],["","","","","technique","","","","","","","","","",""],["Calcium Scoring","","","Yes, using ML methodology","Yes, using ML methodology","","No","","","No","","","","Yes, using non-ML",""],["","","","","","","","","","","","","","methodology",""],["","Workstation operating","","","macOS,","","","macOS,","","","macOS,","","","macOS,",""],["","system","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows",""]],"caption_candidate":"K213998 - cvi42 Auto 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K213999-p7-t0","doc_id":"K213999","page_num":7,"bbox":[72.12,211.14,530.98,558.36],"n_rows":8,"n_cols":5,"columns":["Specification/ Attribute","Predicate Device\nDLIR for Revolution CT (K183202)","","Proposed Device",""],"rows":[["Specification/ Attribute","Predicate Device\nDLIR for Revolution CT (K183202)","","Proposed Device",""],["","","","Modified DLIR for",""],["","","","Revolution CT/Apex",""],["","","","platform",""],["Technology","DLIR uses a dedicated Deep Neural\nNetwork (DNN) which is trained on the\nCT scanner and therefore models the\npropagation of noise through the system\nto identify and remove the noise","Same DNN technology with\nrevised network\narchitecture with retraining\nand inferencing techniques","",""],["System statistics - Noise\nmodeling of the data\ncollection imaging chain\n(photon noise and\nelectronic noise)","Characterization of the photon statistics\nas it propagates through the\npreprocessing and calibration imaging\nchain","Same","",""],["System statistics – Noise\ncharacteristics of the\nreconstructed images","DLIR uses a trained DNN which models\nthe scanned object using information\nobtained from extensive phantom and\nclinical data to identify the noise\ncharacteristics and remove it","Same","",""],["Clinical Workflow","Select recon type and strength (Low,\nMedium, High).","Same","",""]],"caption_candidate":"similarities and differences between the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214019-p6-t0","doc_id":"K214019","page_num":6,"bbox":[70.83,220.6,510.2,660.36],"n_rows":5,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","syngo.CT Extended Functionality\n(SOMARIS/8 VB60)","","","syngo.CT Extended Functionality\n(SOMARIS/8 VB51)","",""],["1. Trauma","The trauma reading plugin allows the user\nconvenient sorting of a large number of\nreconstruction series and displays them\ninto body region specific layouts. The\nfeatures are:\n• Set of pre-configured layouts for\nreading trauma reconstructions.\n• The reconstruction series\ncorresponding to different body regions\nare assigned to body region specific\nlayouts.","","","N/A","",""],["2. Interactive Spectral\nImaging","Display different representations of Dual\nEnergy data.\nModifications:\nThe software has been modified to:\n• accept and display additional data sets\nreceived from CT scanners, and\n• display mean values of ROIs in addition\nto the measured values.","","","Display different representations of Dual\nEnergy data.","",""],["3. Vascular Extension","The user can perform a vascular\nevaluation supporting the following main\nfunctionalities:\n• Measuring vessels\n• Creating DICOM snapshots or result\nseries for documenting findings\n• Working on images that are acquired\nwith CT or MR scanner systems\nconstituting one or more volumes of\nvascular structures\nModification:\nSupport for display and processing of\nimages > 512x512.","","","The user can perform a vascular\nevaluation supporting the following main\nfunctionalities:\n• Measuring vessels\n• Creating DICOM snapshots or result\nseries for documenting findings\n• Working on images that are acquired\nwith CT or MR scanner systems\nconstituting one or more volumes of\nvascular structures","",""]],"caption_candidate":"level in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214019-p7-t0","doc_id":"K214019","page_num":7,"bbox":[70.83,497.13,524.38,670.2],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)/A1:2016","01/14/2019","AAMI, ANSI, IEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Second\nEdition 2007-03-01","06/27/2016","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214036-p6-t0","doc_id":"K214036","page_num":6,"bbox":[60.14,229.54,549.4,705.1],"n_rows":32,"n_cols":8,"columns":["Characteristic","","","Subject Device","","Predicate Device","Reference Device","Reference Device"],"rows":[["Characteristic","","","Subject Device","","Predicate Device","Reference Device","Reference Device"],["Device Name","","","AVIEW","","AVIEW","ClariCT.AI","Broncholab"],["Classification\nName","","","System, image\nProcessing\nRadiological","","System, image\nProcessing\nRadiological","System, image\nProcessing\nRadiological","System, X-Ray,\nTomography,\nComputed"],["Regulatory\nNumber","","","21 CFR 892.2050","","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.1750"],["","Product Code","","QIH, JAK","","LLZ, JAK","LLZ","JAK"],["Review Panel","Review Panel","","Radiology","","Radiology","Radiology","Radiology"],["510k Number","","","-","","K200714","K183460","K191550"],["Indications for\nuse","","","AVIEW","","","",""],["","","","","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This","","",""],["","","","","software can be used to support the physician providing quantitative analysis of CT images by","","",""],["","","","","image segmentation of sub-structures in the lung, lobe, airways, fissures completeness, cardiac,","","",""],["","","","","density evaluation, and reporting tools. AVIEW is also used to store, transfer, inquire and","","",""],["","","","","display CT data set on-premises and as a cloud environment to allow users to connect by","","",""],["","","","","various environments such as mobile devices and Chrome browsers. Converts the sharp kernel","","",""],["","","","","to soft kernel for quantitative analysis of segmenting low attenuation areas of the lung.","","",""],["","","","","Characterizing nodules in the lung in a single study or over the time course of several thoracic","","",""],["","","","","studies. Characterizations include nodule type, location of the nodule, and measurements such","","",""],["","","","","as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,","","",""],["","","","","the volume of the nodule, Mean HU(the average value of the CT pixel inside the nodule in","","",""],["","","","","HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric","","",""],["","","","","measures(Solid major; length of the longest diameter measure in 3D for a solid portion of the","","",""],["","","","","nodule, Solid 2nd Major: The size of the longest diameter of the solid part, measured in sections","","",""],["","","","","perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling","","",""],["","","","","time), and Lung-RADS (classification proposed to aid with findings.) ). The system","","",""],["","","","","automatically performs the measurement, allowing lung nodules and measurements to be","","",""],["","","","","displayed and, integrate with FDA certified Mevis CAD (Computer aided detection)","","",""],["","","","","(K043617). It also provides the Agatston score, volume score, and mass score by the whole and","","",""],["","","","","each artery by segmenting four main arteries (right coronary artery, left main coronary, left","","",""],["","","","","anterior descending, and left circumflex artery). Based on the calcium score provides CAC risk","","",""],["","","","","based on age and gender.","","",""],["","","","AVIEW","","","",""],["","","","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This\nsoftware could be used to support the physician quantitatively in the diagnosis, follow up","","","",""]],"caption_candidate":"tests, we conclude that the proposed device is substantially equivalent to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214036-p7-t0","doc_id":"K214036","page_num":7,"bbox":[60.14,79.52,549.42,702.64],"n_rows":9,"n_cols":2,"columns":["","evaluation and documentation of CT lung tissue images by providing image segmentation of\nsub-structures in lung, lobe, airways and cardiac, registration of inspiration and expiration\nwhich could analyze quantitative information such as air trapping volume, air trapped index,\nand inspiration/expiration ratio. And, volumetric and structure analysis, density evaluation and\nreporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on\npremise and as cloud environment as well to allow users to connect by various environment\nsuch as mobile devices and chrome browser. Characterizing nodules in the lung in a single\nstudy, or over the time course of several thoracic studies. Characterizations include nodule type,\nlocation of the nodule and measurements such as size (major axis, minor axis), estimated\neffective diameter from the volume of the nodule, volume of the nodule, Mean HU(the average\nvalue of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated\nfrom the CT pixel value), and volumetric measures(Solid major; length of the longest diameter\nmeasured in 3D for solid portion of the nodule, Solid 2nd Major: The length of the longest\ndiameter of the solid part, measured in sections perpendicular to the Major axis of the solid\nportion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed\nto aid with findings). The system automatically performs the measurement, allowing lung\nnodules and measurements to be displayed and, integrate with FDA certified Mevis CAD\n(Computer aided detection) (K043617).It also provides CAC analysis by segmentation of four\nmain artery (right coronary artery, left main coronary, left anterior descending and left\ncircumflex artery then extracts calcium on coronary artery to provide Agatston score, volume\nscore and mass score by whole and each segmented artery type. Based on the score, provides\nCAC risk based on age and gender."],"rows":[["","evaluation and documentation of CT lung tissue images by providing image segmentation of\nsub-structures in lung, lobe, airways and cardiac, registration of inspiration and expiration\nwhich could analyze quantitative information such as air trapping volume, air trapped index,\nand inspiration/expiration ratio. And, volumetric and structure analysis, density evaluation and\nreporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on\npremise and as cloud environment as well to allow users to connect by various environment\nsuch as mobile devices and chrome browser. Characterizing nodules in the lung in a single\nstudy, or over the time course of several thoracic studies. Characterizations include nodule type,\nlocation of the nodule and measurements such as size (major axis, minor axis), estimated\neffective diameter from the volume of the nodule, volume of the nodule, Mean HU(the average\nvalue of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated\nfrom the CT pixel value), and volumetric measures(Solid major; length of the longest diameter\nmeasured in 3D for solid portion of the nodule, Solid 2nd Major: The length of the longest\ndiameter of the solid part, measured in sections perpendicular to the Major axis of the solid\nportion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed\nto aid with findings). The system automatically performs the measurement, allowing lung\nnodules and measurements to be displayed and, integrate with FDA certified Mevis CAD\n(Computer aided detection) (K043617).It also provides CAC analysis by segmentation of four\nmain artery (right coronary artery, left main coronary, left anterior descending and left\ncircumflex artery then extracts calcium on coronary artery to provide Agatston score, volume\nscore and mass score by whole and each segmented artery type. Based on the score, provides\nCAC risk based on age and gender."],["","ClariCT.AI"],["","ClariCT.AI, is a software device intended for networking, communication, processing, and\nenhancement of CT images in DICOM format regardless of the manufacturer of CT scanner or\nmodel."],["","Broncholab"],["","Broncholab provides physicians with reproducible CT values for pulmonary tissue for\nproviding quantitative support for diagnosis and follow-up examination. Broncholab can be\nused to support physicians in the diagnosis and documentation of pulmonary tissues images\n(e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of\nsubcompartments, volumetric analysis, density evaluations, low density cluster analysis,\nfissure evaluation and reportingtools are combined with a dedicated workflow."],["General\nDescription","AVIEW"],["","The AVIEW is a software product that can be installed on a PC. It shows images taken with the\ninterface from various storage devices using DICOM 3.0, the digital image and communication\nstandard in medicine. It also offers functions such as reading, manipulation, analyzing, post-\nprocessing, saving, and sending images by using software tools. And is intended for use as a\nquantitative analysis of CT scanning. It provides the following features such as segmentation\nof lung, lobe, airway, fissure completeness, semi-automatic nodule management, maximal\nplane measure, 3D measures and volumetric measures, automatic nodule detection by\nintegration with 3rd party CAD. It also provides the Brocks model, which calculates the\nmalignancy score based on numerical or Boolean inputs. Follow-up support with automated\nnodule matching and automatically categorize Lung-RADS score, which is a quality assurance\ntool designed to standardize lung cancer screening CT reporting and management\nrecommendations that are based on type, size, size change, and other findings that are reported.\nIt also provides a calcium score by automatically analyzing coronary arteries from the\nsegmented arteries."],["","AVIEW"],["","The AVIEW is a software product which can be installed on a PC. It shows images taken with\nthe interface from various storage devices using DICOM 3.0 which is the digital image and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214036-p8-t0","doc_id":"K214036","page_num":8,"bbox":[60.16,79.52,549.42,706.68],"n_rows":5,"n_cols":2,"columns":["","communication standard in medicine. It also offers functions such as reading, manipulation,\nanalyzing, post-processing, saving, and sending images by using the software tools. And is\nintended for use as diagnostic patient imaging which is intended for the review and analysis of\nCT scanning. Provides following features as semi-automatic nodule management, maximal\nplane measure, 3D measures and columetric measures, automatic nodule detection by\nintegration with 3rdparty CAD. Also provides Brocks model which calculated the malignancy\nscore based on numerical or Boolean inputs. Follow up support with automated nodule\nmatching and automatically categorize Lung-RADS score which is a quality assurance tool\ndesigned to standardize lung cancer screening CT reporting and management recommendations\nthat is based on type, size, size change and other findings that is reported. It also automatically\nanalyzes coronary artery calcification which support user to detect cardiovascular disease in\nearly stage and reduce the burden of medical."],"rows":[["","communication standard in medicine. It also offers functions such as reading, manipulation,\nanalyzing, post-processing, saving, and sending images by using the software tools. And is\nintended for use as diagnostic patient imaging which is intended for the review and analysis of\nCT scanning. Provides following features as semi-automatic nodule management, maximal\nplane measure, 3D measures and columetric measures, automatic nodule detection by\nintegration with 3rdparty CAD. Also provides Brocks model which calculated the malignancy\nscore based on numerical or Boolean inputs. Follow up support with automated nodule\nmatching and automatically categorize Lung-RADS score which is a quality assurance tool\ndesigned to standardize lung cancer screening CT reporting and management recommendations\nthat is based on type, size, size change and other findings that is reported. It also automatically\nanalyzes coronary artery calcification which support user to detect cardiovascular disease in\nearly stage and reduce the burden of medical."],["","ClariCT.AI"],["","ClariCT.AI software is intended for denoise processing and enhancement of CT DICOM\nimages when higher image quality and/or lower dose acquisitions are desired. ClariCT.AI\nsoftware can be used to reduce noises in CT images of the head, chest, and abdomen, in\nparticular in CT images with a lower radiation dose. ClariCT.AI may also improve the image\nquality of low dose nonpdiagnostic Filtered Back Projection images as well as lterative\nReconstruction images.\nThe system enables the receipt of DICOM images from CT imaging devices (modalities),\nenables their denoise processing and enhancement, and transmission to a PACS workstation."],["","Broncholab"],["","Broncholab is a SaMD (Software as Medical Device) which provides quantitative CT values\nthat are intended to support the physician in the diagnosis and documentation of pulmonary\ntissues images (abnormalities) from CT scans. The CT scan images are transformed into 3D\nmodels of the patient-specific lungs using several image processing steps. Broncholab can be\nused to assess the effectiveness of therapy based on CT scan data. It is used along with the\nfollowingaccessories:\n(cid:130) Web Portal: Enables the uploading of CT scans and patient data\n(cid:130) ClientReport: Enables the conversion of the output of Broncholab (CT values) into a\ndesired digital format (PDF\nReport) and transfers this Report to the physician via email.\nInspiratory CT scan images uploaded by the users are converted into quantitative CT values\nusing a combination of software tools. Quality checks (both manual and automated) are\nimplemented to assure the quality of the final data.\nThe outputs are provided as absolute values and as a percentage of the total airway volume/\nlung volume/ lobarvolume depending on the parameter. The device can be used on a computer\nwith a web browser installed and consistsof two accessories:\n(cid:130) An online portal to upload the CT scans\n(cid:130) An accessory that enables the creation of the Report\nThe CT values include:\n1) Lung and Lobar Volume is the volume of the 3D model of each lung lobe.\n2) Airway Volume is defined as the region from the trachea until the segmental bronchi.\n3) Lung Density Scores/ Volumes is defined as all the intrapulmonary voxels with\nHounsfield Units between -1024\nand -950 using the inspiratory scans:\n• Low attenuation areas below -950 HU (LAA-950HU)\n• 15th percentile of density histogram: Percentile density (PD) can also be used to\nexpress Emphysema.\n• Blood vessel density: Blood vessel density can be determined through segmentation\nand 3-D reconstruction of the blood vessels. The segmentation is based on local"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214036-p12-t0","doc_id":"K214036","page_num":12,"bbox":[60.15,79.5,549.42,463.1],"n_rows":6,"n_cols":5,"columns":["","(cid:130) PANCAN risk\ncalculator\nAuto detect nodule\nlocation by lobe","","",""],"rows":[["","(cid:130) PANCAN risk\ncalculator\nAuto detect nodule\nlocation by lobe","","",""],["","Supports kernel\nconversion of LAA on\nLCS Page","-","Noise reduction is\nperformed with the\nuse of pre-trained\ndeep learning\nmodels.",""],["Cardiac (CAC)","Extracting Calcium on\nCoronary Artery and\nprovides Agatston\nscore, volume score\nand mass score.","same","",""],["","Automatically\nsegments calcium area\nof coronary artery\nbased on deep\nlearning.","same","",""],["Thin client\nservice","• Connected from\nanywhere,\nanyplace, anytime\n• Supports mobile\nview through\nvarious mobile\ndevices served by\nios and Android.\n• Comparable with\nChrome browser","same","",""],["Easy processing\nmanagement","Rule-based automatic\nprocessing server\n(APS)","same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214043-p6-t0","doc_id":"K214043","page_num":6,"bbox":[42.48,84.38,552.96,768.36],"n_rows":10,"n_cols":3,"columns":["","Predicate Device\nBehold.ai red dot™ device (K191556)","Subject Device\nAidoc Briefcase (K214043)"],"rows":[["","Predicate Device\nBehold.ai red dot™ device (K191556)","Subject Device\nAidoc Briefcase (K214043)"],["Intended Use /\nIndications for\nUse","The red dot™ software platform is a software\nworkflow tool designed to aid the clinical\nassessment of adult Chest XRay cases with\nfeatures suggestive of Pneumothorax in the\nmedical care environment. red dot™ analyzes\ncases\nusing an artificial intelligence algorithm to\nidentify suspected findings. It makes case-level\noutput available to a PACS/ workstation for\nworklist prioritization or triage. red dot™ is not\nintended to direct attention to specific portions\nof an image or to anomalies other than\nPneumothorax. Its results are not intended to be\nused on a stand-alone basis for clinical\ndecision-making nor is it intended to rule out\nPneumothorax or otherwise preclude clinical\nassessment of X-Ray cases.","BriefCase is a radiological computer aided triage\nand notification software indicated for use in the\nanalysis of Chest X-Ray cases in adults or\ntransitional adolescents aged 18 and older. The\ndevice is intended to assist hospital networks\nand appropriately trained medical specialists in\nworkflow triage by flagging and communication\nof suspect positive cases with Pneumothorax\n(Ptx) findings.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag suspect\ncases on a standalone desktop application in\nparallel to the ongoing standard of care image\ninterpretation. The user is notified for suspect\ncases. Notifications include compressed preview\nimages that are meant for informational purposes\nonly and not intended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended to be used\nin conjunction with other patient information\nand based on their professional judgment, to\nassist with triage/prioritization of medical\nimages. Notified clinicians are responsible for\nviewing full images per the standard of care."],["User population","Trained clinicians","Appropriately trained medical specialists"],["Anatomical\nregion","Chest","Chest"],["Data\nacquisition\nprotocol","Chest X-ray","Chest X-ray"],["Notification-\nonly, parallel\nworkflow tool","Yes (passive)","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or de-prioritized.","No. No cases are removed from\nworklist or de-prioritized"],["Algorithm","Artificial intelligence algorithm with database\nof images","Artificial intelligence algorithm with database of\nimages"],["Structure","- Image input, validation and anonymization\n- Image Analysis Algorithm\n- PACS Integration Feature","- AHS module (image acquisition).\n- ACS module (image processing).\n- Aidoc Worklist application for workflow\nintegration (worklist and non-diagnostic\nbasic Image Viewer)."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214043-p8-t0","doc_id":"K214043","page_num":8,"bbox":[227.09,117.38,385.19,676.42],"n_rows":27,"n_cols":3,"columns":["Pathology","N","%"],"rows":[["Pathology","N","%"],["","",""],["Fully Negative","270","60.8%"],["","",""],["ung Pathologies","117","26.4%"],["","",""],["rdiac Pathologies","15","3.4%"],["","",""],["Vascular","14","3.2%"],["","",""],["Inflammatory","9","2.0%"],["","",""],["(Pneumonia)","",""],["","",""],["Other","8","1.8%"],["","",""],["Diaphragmatic","4","0.9%"],["","",""],["Pathologies","",""],["","",""],["Post-Op","3","0.7%"],["","",""],["Trauma","2","0.5%"],["","",""],["Mechanical","1","0.2%"],["","",""],["Neoplastic","1","0.2%"]],"caption_candidate":"Pathology N %","well_formed":true,"extraction_settings":"text"}
{"table_id":"K214043-p9-t0","doc_id":"K214043","page_num":9,"bbox":[121.54,377.92,473.78,427.51],"n_rows":4,"n_cols":18,"columns":["","Time-to-","","","Mean","","","95%","","","95%","","Median","","","IQR","",""],"rows":[["","Time-to-","","","Mean","","","95%","","","95%","","Median","","","IQR","",""],["","notification","","","estimate","","","Lower CL","","","Upper CL","","","","","","",""],["","BriefCase","","","13.1","","","10.6","","","15.7","","","11.8","","","15.8",""],["","Red dotTM","","","13.8","","","10.9","","","13.0","","","14.5","","","8.56",""]],"caption_candidate":"Table 4 . TTN Comparison Subject & Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214081-p8-t0","doc_id":"K214081","page_num":8,"bbox":[153.96,99.36,530.86,681.72],"n_rows":14,"n_cols":7,"columns":["","Table 1","","","","",""],"rows":[["","Table 1","","","","",""],["","Comparison of the primary currently marketed and predicate device,","","","","",""],["","MRCAT Brain versus the proposed MRCAT Head & Neck","","","","",""],["","","","","","",""],["Device","Device","MRCAT Brain","MRCAT Head & Neck","","Similarities",""],["","","","","","and",""],["","","","","","Differences",""],["Manufacturer","","Philips Oy","Philips Oy","-","",""],["510(k)\nNumber","","K193109","-","-","",""],["Product Code","","MUJ","MUJ","Identical","",""],["Regulation\nNumber","","892.5050","892.5050","Identical","",""],["Regulation\nName","","Accelerator, Linear,\nMedical","Accelerator, Linear,\nMedical","Identical","",""],["Intended use","","MRCAT imaging is\nintended to provide the\noperator with\ninformation of tissue\nproperties for radiation\nattenuation estimation\npurposes in photon\nexternal\nbeam radiotherapy\ntreatment planning.","MRCAT imaging is\nintended to provide\nthe operator with\ninformation of tissue\nproperties for\nradiation attenuation\nestimation purposes\nin photon external\nbeam radiotherapy\ntreatment planning.","Identical","",""],["Indications\nfor use","","MRCAT Brain is\nindicated for\nradiotherapy treatment\nplanning for primary\nand metastatic brain\ntumor patients.","MRCAT Head and\nNeck is indicated for\nradiotherapy\ntreatment planning\nfor patients with soft\ntissue tumors in the\nHead and Neck\nregion","No significant\ndifference.\nMRCAT Brain\nand MRCAT\nHead & Neck\nare both\nindicated for\nradiotherapy\ntreatment\nplanning in a\ndefined\nregion.\nBrain tumors\nare soft tissue\ntumors.","",""]],"caption_candidate":"technological","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214081-p9-t0","doc_id":"K214081","page_num":9,"bbox":[153.72,78.6,530.88,580.56],"n_rows":4,"n_cols":4,"columns":["Primary\nimage\ndataset","MRCAT","MRCAT","Identical"],"rows":[["Primary\nimage\ndataset","MRCAT","MRCAT","Identical"],["Secondary\nimage\ndataset","mDixon, MRI","mDixon, MRI","Identical\nMR images\nobtained in\nthe same\nimaging\nsession are\ninherently in\nthe same\nframe of\nreference."],["Registration\nbetween\nprimary and\nsecondary\nimage\ndatasets","Secondary mDixon MR\nimage, source data to\nMRCAT, is inherently\nregistered as part of\nMRCAT algorithm with\nMRCAT image, which\nsimplifies workflow.\nOther MR images, like\nT2w and fiducial\nmarker detection\nimages are registered\nusing tools available in\nRTP system","Secondary mDixon\nMR image, source\ndata to MRCAT, is\ninherently registered\nas part of MRCAT\nalgorithm with\nMRCAT image, which\nsimplifies workflow.\nOther MR images,\nlike T2w images are\nregistered using tools\navailable in RTP\nsystem","No significant\ndifference\nSecondary MR\nimages are\nobtained in\nthe same\nimaging\nsession\nreducing the\npossibility of\npatient\nmotion\nbetween\nimages."],["Primary\nimage\ndensity\ninformation","MRCAT image intensity\ninformation is provided\nin Hounsfield Unit (HU)\nvalues.","MRCAT image\nintensity information\nis provided in\nHounsfield Unit (HU)\nvalues.","Identical.\nMRCAT Brain\nand MRCAT\nHead & Neck\nboth have\ncontinuous\nHU value\napproach."]],"caption_candidate":"Philips Oy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214081-p10-t0","doc_id":"K214081","page_num":10,"bbox":[153.43,78.6,530.88,712.44],"n_rows":2,"n_cols":4,"columns":["Conversion\nfrom primary\nimage to\ndensity\nvalues used\nin dose\ncalculation","Primary image HU\nvalues are converted to\ndensities through\ndensity table specific\nfor the MRCAT.","Primary image HU\nvalues are converted\nto densities through\ndensity table specific\nfor the MRCAT.","No significant\ndifference\nMRCAT has\nspecific\ndensity table\nthat is used in\na similar\nmanner to CT\nspecific\ndensity tables."],"rows":[["Conversion\nfrom primary\nimage to\ndensity\nvalues used\nin dose\ncalculation","Primary image HU\nvalues are converted to\ndensities through\ndensity table specific\nfor the MRCAT.","Primary image HU\nvalues are converted\nto densities through\ndensity table specific\nfor the MRCAT.","No significant\ndifference\nMRCAT has\nspecific\ndensity table\nthat is used in\na similar\nmanner to CT\nspecific\ndensity tables."],["MRCAT\nalgorithm","Bones are segmented\nfrom mDixon in-phase\nand water images using\nmachine learning based\nsegmentation. The\nsegmented bones are\nin skull, upper C-spine\nand jaw.\nBody outline is\nsegmented using in-\nphase and water\nimages.\nBones are assigned a\ncontinuum of HU\nvalues between dense\ncortical bone and light\nspongy bone depending\non the fat and water\nintensities of the\nvoxels.\nSoft tissue are assigned\na continuum of HU\nvalues depending on\nthe fat and water\nintensities of the\nvoxels.\nThe HU values for the\nMRCAT Brain are\ncalibrated using\nregistered CT images\nfrom several sites.\nMRCAT Brain algorithm\nis fully trained before\nproduct release, after","Bones are segmented\nfrom mDixon in-\nphase and water\nimages using\nmachine learning\nbased segmentation.\nThe segmented\nbones are in skull, C-\nspine, jaw, and\nshoulder girdle.\nBody outline is\nsegmented using in-\nphase and water\nimages.\nBones are assigned a\ncontinuum of HU\nvalues between\ndense cortical bone\nand light spongy\nbone depending on\nthe fat and water\nintensities of the\nvoxels.\nSoft tissue are\nassigned a\ncontinuum of HU\nvalues depending on\nthe fat and water\nintensities of the\nvoxels.\nThe HU values for the\nMRCAT Head & Neck\nare calibrated using","No significant\ndifference\nSegmentation\nis done for\nboth MRCAT\nBrain and\nMRCAT Head\n& Neck using\nthe mDIXON\nimage\ncontrasts.\nHU value\nassignment is\ndone based\non mDixon\nimage\nintensities.\nThe models\nused are\nequivalent in\nrelation to\ndose and\npositioning\naccuracy.\nBoth\nalgorithms are\nlocked; they\ndo not change\nafter\ninstallation\nbased on new\ndata during\nthe use."]],"caption_candidate":"Philips Oy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214081-p11-t0","doc_id":"K214081","page_num":11,"bbox":[153.43,78.6,530.88,439.32],"n_rows":2,"n_cols":4,"columns":["","which the algorithm is\nlocked.","registered CT images\nfrom several sites.\nMRCAT Head & Neck\nalgorithm is fully\ntrained before\nproduct release, after\nwhich the algorithm\nis locked.",""],"rows":[["","which the algorithm is\nlocked.","registered CT images\nfrom several sites.\nMRCAT Head & Neck\nalgorithm is fully\ntrained before\nproduct release, after\nwhich the algorithm\nis locked.",""],["Patient\npositioning","Ingenia MR-RT with\nMRCAT Brain supports\nMR Only simulation\nwith relative patient\nmarking.\nPatient positioning in\nthe treatment machine\nmust be checked either\nwith cone beam\ncomputed tomography\n(CBCT) or plain\nradiographs by\nregistering bone\nstructures.","Ingenia MR-RT with\nMRCAT Head & Neck\nsupports MR Only\nsimulation with\nrelative patient\nmarking.\nPatient positioning in\nthe treatment\nmachine must be\nchecked either with\ncone beam\ncomputed\ntomography (CBCT)\nor plain radiographs\nby registering bone\nstructures.","No significant\ndifference\nThe visibility\nof bone\nstructures is\nequivalent for\nboth\nproducts."]],"caption_candidate":"Philips Oy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K214081-p12-t0","doc_id":"K214081","page_num":12,"bbox":[153.43,78.6,530.88,706.44],"n_rows":2,"n_cols":4,"columns":["Dose\naccuracy","The simulated dose\nbased on MRCAT Brain\nimages shall not differ\nin 95% of the indicated\npatients (gamma\nanalysis criterion\n2%/2mm realized in\n98% of voxels within\nthe PTV or exceeding\n75% of the maximum\ndose) when compared\nwith CT-based plan.\nThe average simulated\ndose based on MRCAT\nBrain shall not deviate\nmore than 5% or 1 Gy,\nwhich ever is greater, in\n99% of the indicated\npatients in the volume\nof sensitive organs\nwhen compared with\nCT based plan.","The simulated dose\nbased on MRCAT\nHead & Neck images\nshall not differ in\n95% of the indicated\npatients (gamma\nanalysis criterion\n2%/2mm realized in\n98% of voxels within\nthe PTV or exceeding\n75% of the maximum\ndose) when\ncompared with CT-\nbased plan.\nThe average\nsimulated dose based\non MRCAT Head &\nNeck shall not\ndeviate more than\n5% or 1 Gy, which\never is greater, in\n99% of the indicated\npatients in the\nvolume of sensitive\norgans when\ncompared with CT\nbased plan.","Identical\nThe same\ndose\nevaluation\nmethodology\nis used for\nboth\nproducts. The\ncriteria are\nselected\nbased on the\nneeds of the\napplication."],"rows":[["Dose\naccuracy","The simulated dose\nbased on MRCAT Brain\nimages shall not differ\nin 95% of the indicated\npatients (gamma\nanalysis criterion\n2%/2mm realized in\n98% of voxels within\nthe PTV or exceeding\n75% of the maximum\ndose) when compared\nwith CT-based plan.\nThe average simulated\ndose based on MRCAT\nBrain shall not deviate\nmore than 5% or 1 Gy,\nwhich ever is greater, in\n99% of the indicated\npatients in the volume\nof sensitive organs\nwhen compared with\nCT based plan.","The simulated dose\nbased on MRCAT\nHead & Neck images\nshall not differ in\n95% of the indicated\npatients (gamma\nanalysis criterion\n2%/2mm realized in\n98% of voxels within\nthe PTV or exceeding\n75% of the maximum\ndose) when\ncompared with CT-\nbased plan.\nThe average\nsimulated dose based\non MRCAT Head &\nNeck shall not\ndeviate more than\n5% or 1 Gy, which\never is greater, in\n99% of the indicated\npatients in the\nvolume of sensitive\norgans when\ncompared with CT\nbased plan.","Identical\nThe same\ndose\nevaluation\nmethodology\nis used for\nboth\nproducts. The\ncriteria are\nselected\nbased on the\nneeds of the\napplication."],["Geometric\naccuracy","MRCAT accuracy:\n± 1 mm accuracy: 200\nmm diameter sphere\n± 2 mm accuracy: 400\nmm diameter sphere\n(limited in the bore\ndirection by +/- 160\nmm from the z=0 mm\nplane)\n± 5 mm accuracy: 500\nmm diameter sphere\n(limited in the bore\ndirection by +/- 160\nmm from the z=0 mm\nplane)","MRCAT accuracy:\n± 1 mm accuracy:\n200 mm diameter\nsphere\n± 2 mm accuracy:\n400 mm diameter\nsphere (limited in the\nbore direction by +/-\n160 mm from the z=0\nmm plane)\n± 5 mm accuracy:\n500 mm diameter\nsphere (limited in the\nbore direction by +/-\n160 mm from the z=0\nmm plane)","Identical"]],"caption_candidate":"Philips Oy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p4-t0","doc_id":"K220034","page_num":4,"bbox":[108.26,36.29,551.44,77.07],"n_rows":2,"n_cols":5,"columns":["","","","NEUROShield 510k Premarket Submission",""],"rows":[["","","","NEUROShield 510k Premarket Submission",""],["","","","Revision: 01","Date: 11 Sept 2023"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p4-t1","doc_id":"K220034","page_num":4,"bbox":[144.59,313.49,542.2,455.95],"n_rows":7,"n_cols":2,"columns":["Device Trade Name","NEUROShieldTM"],"rows":[["Device Trade Name","NEUROShieldTM"],["Common Name","Medical Image Processing Software"],["Classification Name","Medical image management and processing system"],["Regulation Number","21 CFR 892.2050"],["Regulation Description","Picture archiving and communications system"],["Product Code","QIH"],["Classification Panel","Radiology"]],"caption_candidate":"II. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p4-t2","doc_id":"K220034","page_num":4,"bbox":[144.59,500.11,542.2,579.19],"n_rows":4,"n_cols":2,"columns":["Device","NeuroQuant"],"rows":[["Device","NeuroQuant"],["510(k) Number","K170981"],["Manufacturer","CorTechs Labs, Inc"],["Product Code:","LLZ"]],"caption_candidate":"III. Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p5-t0","doc_id":"K220034","page_num":5,"bbox":[144.26,254.21,539.81,736.66],"n_rows":10,"n_cols":3,"columns":["Feature","Subject Device","Predicate Device"],"rows":[["Feature","Subject Device","Predicate Device"],["Device Name","NEUROShield™","NeuroQuant"],["Organization","In Med Prognostics L3C","CorTechs Labs, Inc"],["Classification","Class II","Class II"],["Product Code","QIH","LLZ"],["Indications for Use","Automatic labelling,\nvisualization, and volumetric\nquantification of the\nHippocampus brain structure\nfrom a set of MR images.","Automatic labelling, visualization\nand volumetric quantification of\nsegmentable brain structures\nand lesions from a set of MR\nimages. Volumetric data may be\ncompared to reference\npercentile data."],["Design and\nIncorporated\nTechnology","•Software as a medical\ndevice to be used in the\nprocess of Imaging and\nquantification of the\nHippocampus brain\nstructure from a set of MR\nimages.\n•Fully automated brain\ngeometry-based quantifying\nanalytics tool/cloud platform\ndeveloped using DeepNet /\nU-Net methodologies.","•Automated measurement of\nbrain tissue volumes and\nstructures and lesions\n•Automatic segmentation and\nquantification of brain structures\nusing a dynamic probabilistic\nneuroanatomical atlas, with age\nand gender specificity, based on\nthe MR image intensity."],["Physical\nCharacteristics","• Software package\n(accessible via web browser)\n• Operates on off-the-shelf\nhardware (multiple vendors)","• Software package\n• Operates on off-the-shelf\nhardware (multiple vendors)"],["Operating System","Supports Windows and Mac\nOS latest (No older than\nCatalina)","Supports Linux, Mac OS X and\nWindows."],["Processing\nArchitecture","An automated internal\npipeline that performs:\n- segmentation\n- volume calculation\n- report generation","Automated internal pipeline that\nperforms:\n- artifact correction\n- segmentation\n- lesion quantification"]],"caption_candidate":"VI. Comparison of Technological Characteristics with the Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p6-t0","doc_id":"K220034","page_num":6,"bbox":[144.22,36.24,539.76,476.95],"n_rows":5,"n_cols":3,"columns":["","","- volume calculation\n- report generation"],"rows":[["","","- volume calculation\n- report generation"],["Feature","Subject Device","Predicate Device"],["Data Source •","• MRI scanner: 3D T1 MRI\nscans acquired with specified\nprotocols\n• NEUROShield requires\nuncompressed DICOM files\nas input.","• MRI scanner: 3D T1 MRI\nscans acquired with specified\nprotocols • NeuroQuant\nSupports DICOM format as input"],["Output","Provides volumetric\nmeasurements of\nHippocampus brain structure.","Provides volumetric\nmeasurements of brain\nstructures and lesions.\nIncludes segmented color\noverlays and morphometric\nreports\n▪Automatically compares results\nto reference percentile data and\nto prior scans when available\n▪Supports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture Archive\nand Communications Systems"],["Safety","• Automated quality control\nfunctions\n- Scan protocol verification\n• Results must be reviewed\nby a trained physician.","• Automated quality control\nfunctions\n- Tissue contrast check\n- Scan protocol verification\n- Atlas alignment check\n• Results must be reviewed by a\ntrained physician."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p7-t0","doc_id":"K220034","page_num":7,"bbox":[180.86,36.36,417.07,214.94],"n_rows":11,"n_cols":3,"columns":["Subgroups","","Count"],"rows":[["Subgroups","","Count"],["","Healthy controls","186"],["Magnetic field\nstrength","1.5T","109"],["","3 T","77"],["Slice thickness","1","81"],["","1.2","50"],["","2","7"],["","2.2","48"],["Equipment\nManufacturers","GE","57"],["","Siemens","112"],["","Philips","17"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p7-t1","doc_id":"K220034","page_num":7,"bbox":[180.86,622.18,318.89,737.02],"n_rows":7,"n_cols":2,"columns":["Age group","Count"],"rows":[["Age group","Count"],["55-64","109"],["65-69","56"],["70-74","50"],["75-79","29"],["80-84","20"],["85-90","16"]],"caption_candidate":"The distribution for age bands is as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p8-t0","doc_id":"K220034","page_num":8,"bbox":[180.86,112.22,473.14,345.29],"n_rows":13,"n_cols":5,"columns":["Subgroups","","Count","Mean\n(mL)","Standard\ndeviation\n(mL)"],"rows":[["Subgroups","","Count","Mean\n(mL)","Standard\ndeviation\n(mL)"],["Clinical Sub-\ngroups","ADNI-control","140","6.8","1"],["","ADNI-MCI","70","6.6","1.1"],["","ADNI-AD","70","5.5","1.1"],["Gender","Male","140","6.6","1.1"],["","Female","140","6.2","1.3"],["Magnetic field\nstrength","1.5T","139","6.2","1.2"],["","3 T","141","6.7","1.1"],["Slice thickness","1","118","6.7","1"],["","1.2","162","6.2","1.2"],["US Region","East","100","6.5","1.2"],["","West","87","6.3","1.3"],["","Central","93","6.5","1"]],"caption_candidate":"criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p9-t0","doc_id":"K220034","page_num":9,"bbox":[132.74,444.31,479.38,515.35],"n_rows":3,"n_cols":4,"columns":["Measure","Threshold","NEUROShield™ 95 %\nconfidence intervals","Criteria\n(Pass/Fail)"],"rows":[["Measure","Threshold","NEUROShield™ 95 %\nconfidence intervals","Criteria\n(Pass/Fail)"],["Dice","0.75","(0.90, 0.92)","Pass"],["Hausdorff distance","6.1","(3.57, 4.06)","Pass"]],"caption_candidate":"respectively. The following table shows the 95% confidence interval for both.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p9-t1","doc_id":"K220034","page_num":9,"bbox":[72.38,574.27,539.0,737.02],"n_rows":5,"n_cols":7,"columns":["","Dice score","","","Hausdorff distance (mm)","",""],"rows":[["","Dice score","","","Hausdorff distance (mm)","",""],["Clinical\nsubgroups","Control","MCI","AD","Control","MCI","AD"],["Measured\nvalue","0.91","0.92","0.9","3.77","3.43","4.3"],["NEUROShield\n™ 95 %\nconfidence\nintervals","(0.9, 0.92)","(0.91, 0.93)","(0.88, 0.91)","(3.42, 4.13)","(3.03, 3.82)","(3.75, 4.85)"],["Criteria","Pass","Pass","Pass","Pass","Pass","Pass"]],"caption_candidate":"a) Clinical subgroups:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p10-t0","doc_id":"K220034","page_num":10,"bbox":[72.38,123.62,537.89,268.97],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff distance (mm)",""],"rows":[["","Dice score","","Hausdorff distance (mm)",""],["Gender","Female","Male","Female","Male"],["Measured value","0.91","0.91","3.92","3.71"],["NEUROShield™ 95 %\nconfidence intervals","(0.90,0.92)","(0.90,0.92)","(3.5,4.3)","(3.4,4.02)"],["Criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"b) Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p10-t1","doc_id":"K220034","page_num":10,"bbox":[72.38,313.25,537.89,444.55],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff distance (mm)",""],"rows":[["","Dice score","","Hausdorff distance (mm)",""],["MRI strength","3T","1.5T","3T","1.5T"],["Measured value","0.92","0.9","3.66","3.9"],["NEUROShield™\n95 % confidence\nintervals","(0.92,0.93)","(0.89, 0.91)","(3.36, 3.96)","(3.59, 4.37)"],["criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"c) Magnetic field strength:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p10-t2","doc_id":"K220034","page_num":10,"bbox":[72.38,488.95,537.89,620.26],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff distance (mm)",""],"rows":[["","Dice score","","Hausdorff distance (mm)",""],["slice thickness","1 mm","1.2mm","1 mm","1.2mm"],["Average value","0.92","0.9","3.5","4"],["NEUROShield™\n95 % confidence\nintervals","(0.92,0.93)","(0.89,0.91)","(3.21, 3.8)","(3.68,4.41)"],["criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"d) Slice thickness:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p10-t3","doc_id":"K220034","page_num":10,"bbox":[72.38,664.54,537.89,738.46],"n_rows":3,"n_cols":7,"columns":["","Dice score","","","Hausdorff distance","",""],"rows":[["","Dice score","","","Hausdorff distance","",""],["Region","East US","West US","Central US","East US","West US","Central US"],["Average\nvalue","0.91","0.9","0.92","3.78","3.94","3.73"]],"caption_candidate":"e) US geographical regions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220034-p11-t0","doc_id":"K220034","page_num":11,"bbox":[72.38,36.36,538.97,106.46],"n_rows":2,"n_cols":7,"columns":["95 %\nconfidence\nintervals","(0.9, 0.92)","(0.88, 0.91)","(0.91, 0.93)","(3.37, 4.19)","(3.43, 4.45)","(3.38, 4.09)"],"rows":[["95 %\nconfidence\nintervals","(0.9, 0.92)","(0.88, 0.91)","(0.91, 0.93)","(3.37, 4.19)","(3.43, 4.45)","(3.38, 4.09)"],["Criteria","Pass","Pass","Pass","Pass","Pass","Pass"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220043-p5-t0","doc_id":"K220043","page_num":5,"bbox":[52.35,387.29,541.38,764.62],"n_rows":4,"n_cols":3,"columns":["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10 (K211824)\nPrimary Predicate"],"rows":[["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10 (K211824)\nPrimary Predicate"],["Manufacturer","SAMSUNG MEDISON CO.,LTD","SAMSUNG MEDISON CO.,LTD"],["Intended Use","The HERA W9/ HERA W10 Diagnostic\nUltrasound System and transducers are\nintended for diagnostic ultrasound imaging\nand fluid analysis of the human body.","The HERA W9/ HERA W10 Diagnostic\nUltrasound System and transducers are\nintended for diagnostic ultrasound imaging\nand fluid analysis of the human body."],["Functionality","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+\n- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for Thyroid\n- ADVR\n- 3D Imaging\n- (Volume Data Acquisition)\n- 3D Imaging presentation\n- 3D Cine/4D Cine\n- 3D Rendering MPR\n- 3D XI MSV/Oblique View\n- Volume CT\n- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI VOCAL)\n- XI STIC","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+\n- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for Thyroid\n- ADVR\n- 3D Imaging\n- (Volume Data Acquisition)\n- 3D Imaging presentation\n- 3D Cine/4D Cine\n- 3DRendering MPR\n- 3D XI MSV/Oblique View\n- Volume CT\n- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI VOCAL)\n- XI STIC"]],"caption_candidate":"to intended use, imaging capabilities, technological characteristics and safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220043-p6-t0","doc_id":"K220043","page_num":6,"bbox":[52.35,72.32,541.37,610.15],"n_rows":3,"n_cols":3,"columns":["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10 (K211824)\nPrimary Predicate"],"rows":[["Feature","HERA W9 /HERA W10\n(Under Review)","HERA W9/HERA W10 (K211824)\nPrimary Predicate"],["","- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*\n- Slice A\n- HeartAssist *\n- ViewAssist","- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*\n- Slice A\n- HeartAssist *\n- ViewAssist"],["Transducers","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A\n- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A\n- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A"]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220043-p7-t0","doc_id":"K220043","page_num":7,"bbox":[78.64,259.34,529.65,402.65],"n_rows":8,"n_cols":10,"columns":["","Difference","","","","HERA W9","","","HERA W10",""],"rows":[["","Difference","","","","HERA W9","","","HERA W10",""],["Software","","CrystalVue Flow","","Not Supported","","","Supported","",""],["","","MPI+","","Not Supported","","","Supported","",""],["","","HeartAssist","","Not Supported","","","Supported","",""],["Hardware","","Internal DVD","","Not Included","","","Included","",""],["","","Caster size","","5\"","","","6\"","",""],["","","Active array probe port","","3 port (default), 4 port(option)","","","4 port","",""],["","","Main monitor","","21.5\"/ 23.8\"","","","21.5\"/ 23\" / 23.8\"","",""]],"caption_candidate":"The differences between HERA W9 and HERA W10 in the subject device are as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220043-p7-t1","doc_id":"K220043","page_num":7,"bbox":[78.64,491.83,541.4,668.98],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","ANSI AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and A2:2010\n/(R)2012\nMedical Electrical Equipment - Part 1: General Requirements for basic safety and\nessential performance.","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2014(4th Edition), Medical electrical equipment - Part 1-2: General\nrequirements for basic safety and essential performance - EMC","",""],["IEC 60601-2-37","","","IEC60601-2-37:2007 + A1:2015, Particular requirements for the safety of ultrasonic\nmedical diagnostic and monitoring equipment","",""],["ISO10993-1","","","ISO 10993-1, Biological evaluation of medical devices -- Part 1: Evaluation and testing\nwithin a risk management process.","",""],["ISO14971","","","ISO 14971:2007, Medical devices - Application of risk management to medical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound Equipment Revision\n3","",""]],"caption_candidate":"applications comply with voluntary standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220068-p6-t0","doc_id":"K220068","page_num":6,"bbox":[72.25,58.5,540.25,713.5],"n_rows":3,"n_cols":4,"columns":["Comparison\nCategory","ButterflyiQ/iQ+\nUltrasound System\n(Subject Device)","ButterflyiQ\nUltrasound System\n(PrimaryPredicate)\n(K202406)","Comparison"],"rows":[["Comparison\nCategory","ButterflyiQ/iQ+\nUltrasound System\n(Subject Device)","ButterflyiQ\nUltrasound System\n(PrimaryPredicate)\n(K202406)","Comparison"],["GeneralDevice\nDescription","Hand heldportable\ndiagnosticultrasound\nsystem","Hand heldportable\ndiagnosticultrasound\nsystem","Remains\nUnchanged"],["Indicationsfor\nUse","TheButterflyiQ/iQ+\nUltrasoundSystemis\nindicatedfor use by\ntrainedhealthcare\nprofessionalsin\nenvironmentswhere\nhealthcareisprovidedto\nenablediagnostic\nultrasoundimagingand\nmeasurementof\nanatomicalstructuresand\nfluidsof adultand\npediatricpatientsfor the\nfollowingclinical\napplications:\nPeripheralVessel\n(includingcarotid,deep\nveinthrombosisand\narterialstudies),\nProceduralGuidance,\nSmallOrgans (including\nthyroid,scrotumand\nbreast),Cardiac,\nAbdominal,Lung,\nUrology,Fetal/Obstetric,\nGynecological,\nMusculoskeletal\n(conventional),\nMusculoskeletal\n(superficial)and\nOphthalmic.\nModes of operation\nincludeB-mode,B-mode\n+M-mode,B-mode+\nColorDoppler,B-mode+","TheButterflyiQ\nUltrasoundSystemis\nindicatedfor use by\ntrainedhealthcare\nprofessionalsin\nenvironmentswhere\nhealthcareisprovided\ntoenablediagnostic\nultrasoundimagingand\nmeasurementof\nanatomicalstructures\nandfluidsof adultand\npediatricpatientsfor the\nfollowingclinical\napplications:\nPeripheralVessel\n(includingcarotid,deep\nveinthrombosisand\narterialstudies),\nProceduralGuidance,\nSmallOrgans\n(includingthyroid,\nscrotumandbreast),\nCardiac,Abdominal,\nUrology,\nFetal/Obstetric,\nGynecological,\nMusculoskeletal\n(conventional),\nMusculoskeletal\n(superficial)and\nOphthalmic.\nModes of operation\nincludeB-mode,\nB-mode+M-mode,\nB-mode+Color","Additionof “lung”\ntoIndicationsfor\nUse andSpectral\nPulsedWave\nDopplerto\noperatingmode."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220068-p7-t0","doc_id":"K220068","page_num":7,"bbox":[72.5,58.5,540.5,346.5],"n_rows":6,"n_cols":4,"columns":["","Power Doppler,Spectral\nPulsedWaveDoppler.","Doppler,B-mode+\nPower Doppler.",""],"rows":[["","Power Doppler,Spectral\nPulsedWaveDoppler.","Doppler,B-mode+\nPower Doppler.",""],["Type","Singleprobe2D phased\narray","Singleprobe2D phased\narray","Remains\nUnchanged"],["Sterility","Non-sterile","Non-sterile","Remains\nUnchanged"],["Durationof Use","Limited(≤24hours)","Limited(≤24hours)","Remains\nUnchanged"],["Reusable","Yes","Yes","Remains\nUnchanged"],["Principlesof\nOperation\n(subjectAuto\nB-LineCounter)","Automaticdetectionand\ncountingof B-linesfrom\nlungultrasoundimages","Manualcountingof\nB-linesfromlung\nultrasoundimages","AutoB-Line\nCounteraddedto\nexistingButterfly\niQ/ButterflyiQ+\nUltrasoundSystem\nApp"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220080-p5-t0","doc_id":"K220080","page_num":5,"bbox":[186.32,410.03,531.88,713.04],"n_rows":7,"n_cols":9,"columns":["","Technological","","","New Device [K220080]","","Predicate Device [K200905]\nHealthMammo ‐ Zebra Medical Vision Ltd.","","Status"],"rows":[["","Technological","","","New Device [K220080]","","Predicate Device [K200905]\nHealthMammo ‐ Zebra Medical Vision Ltd.","","Status"],["","Characteristics","","","CogNet QmTRIAGE ‐ MedCognetics","","","",""],["Indication for Use\n/ Intended Use","","","The MedCognetics (CogNet) QmTRIAGE\nsoftware is a passive notification for\nprioritization‐only, parallel‐workflow software\ntool used by MQSA qualified interpreting\nphysicians to prioritize patients with suspicious\nfindings in the medical care environment.\nQmTRIAGE utilizes an artificial intelligence\nalgorithm to analyze 2D FFDM screening\nmammograms and flags those that are\nsuggestive of the presence of at least one\nsuspicious finding at the exam level.\nQmTRIAGE produces an exam level output to a\nPACS/Workstation for flagging the suspicious\nstudy and allows for worklist prioritization.\nMQSA qualified interpreting physicians are\nresponsible for reviewing each exam on a\ndisplay approved for use in mammography,\naccording to the current standard of care. The\nQmTRIAGE device is limited to the\ncategorization of exams, does not provide any\ndiagnostic information beyond triage and\nprioritization, does not remove images from\nthe interpreting physician’s worklist, and\nshould not be used in lieu of full patient\nevaluation, or relied upon to make or confirm\ndiagnosis.\nThe QmTRIAGE device is intended for use with\ncomplete 2D FFDM mammography exams\nacquired using validated FFDM systems only.","","","The Zebra HealthMammo is a passive\nnotification for prioritization‐only, parallel‐\nworkflow software tool used by MQSA‐\nqualified interpreting physicians to prioritize\npatients with suspicious findings in the\nmedical care environment. HealthMammo\nutilizes an artificial intelligence algorithm to\nanalyze 2D FFDM screening mammograms\nand flags those that are suggestive of the\npresence of at least one suspicious finding at\nthe exam‐level. HealthMammo produces an\nexam level output to a PACS/Workstation for\nflagging the suspicious case and allows\nworklist prioritization.\nMQSA‐qualified interpreting physicians are\nresponsible for reviewing each exam on a\ndisplay approved for use in mammography\naccording to the current standard of care.\nHealthMammo device is limited to the\ncategorization of exams, does not provide any\ndiagnostic information beyond triage and\nprioritization, does not remove images from\nthe interpreting physician's worklist, and\nshould not be used in lieu of full patient\nevaluation, or relied upon to make or confirm\ndiagnosis.\nThe HealthMammo device is intended for use\nwith complete 2D FFDM mammography\nexams acquired using validated FFDM systems\nonly.","","Same"],["Notification Only","","","Yes","","","Yes","","Same"],["Parallel Workflow","","","Yes","","","Yes","","Same"],["User","","","Interpreting physician","","","Interpreting physician","","Same"],["Alert to finding","","","Yes.\nPassive notification flagged for review","","","Yes.\nPassive notification flagged for review","","Same"]],"caption_candidate":"substantial equivalence of the device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220080-p6-t0","doc_id":"K220080","page_num":6,"bbox":[186.31,72.43,531.89,449.88],"n_rows":15,"n_cols":10,"columns":["","Technological","","","","New Device [K220080]","","Predicate Device [K200905]\nHealthMammo ‐ Zebra Medical Vision Ltd.","","Status"],"rows":[["","Technological","","","","New Device [K220080]","","Predicate Device [K200905]\nHealthMammo ‐ Zebra Medical Vision Ltd.","","Status"],["","Characteristics","","","","CogNet QmTRIAGE ‐ MedCognetics","","","",""],["Independent of\nSoC workflow","","","","Yes.\nNo cases are removed from worklist","","","Yes.\nNo cases are removed from worklist","","Same"],["Modality","","","","FFDM screening mammograms","","","FFDM screening mammograms","","Same"],["FFDM\nManufacturer","","","","Hologic","","","Hologic","","Same"],["Body Part","","","","Breast","","","Breast","","Same"],["AI algorithm","","","","Yes","","","Yes","","Same"],["Limited to analysis\nof imaging data","","","","Yes","","","Yes","","Same"],["ydutS\necnamrofreP","","Inclusion\nCriteria",""," Standard 2D FFDM screening\nmammograms\n Biopsy proven cancer studies studies (soft\ntissues and microcalcifications)\n BIRADS 1 and 2 normal/benign cases with\n2‐year follow‐up of a negative diagnosis\n Female patients 22 and older\n Bilateral Studies with 4 standard views\n(LCC, LMLO, RCC, RMLO)","",""," 2D FFDM screening\nmammograms\n Biopsy proven cancer studies\n(soft tissues and microcalcifications)\n BIRADS 1 and 2 normal cases with 2 year\nfollow‐up\n\n Studies with 4 standard views (LCC,\nLMLO, RCC, RMLO) BIRADS 1 and 2\nnormal cases with 2 year follow‐up","","Different"],["","","Exclusion\nCriteria",""," Digital breast tomosynthesis images\n 2D synthetic views from tomosynthesis","",""," Digital Breast tomosynthesis studies\n 3D studies\n Studies that did not include all four views\n Studies that do not comply with the\ninclusion criteria","","Different"],["","","Multiple\nOperating\npoints","","Not Applicable","","","Yes. Three optional operating points","","Different"],["Aids in prompt\nidentification of\ncases with indicated\nfindings","","","","Yes","","","Yes","","Same"],["Results Preview","","","","The device operates in parallel with the\nstandard of care, which remains the default\noption for all cases. Encapsulated PDF stored\nwith original DICOM study and may be\ndownloaded and viewed as a PDF.","","","Presentation of notification and preview of\nthe study for initial assessment not meant for\ndiagnostic purposes. The device operates in\nparallel with the standard of care, which\nremains the default option for all cases.","","Equivalent"],["Deployment","","","","Cloud based","","","Cloud based\nOn‐premise option","","Different"],["Where results are\nreceived","","","","PACS / Workstation","","","PACS / Workstation","","Same"]],"caption_candidate":"K220080","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220141-p5-t0","doc_id":"K220141","page_num":5,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["510(k) Summary RayStation 11B","","","1.0","",""]],"caption_candidate":"K220141","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220141-p6-t0","doc_id":"K220141","page_num":6,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["510(k) Summary RayStation 11B","","","1.0","",""]],"caption_candidate":"K220141","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220141-p7-t0","doc_id":"K220141","page_num":7,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["510(k) Summary RayStation 11B","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220141-p8-t0","doc_id":"K220141","page_num":8,"bbox":[72.46,36.54,539.79,72.12],"n_rows":2,"n_cols":6,"columns":["","Document ID and Title","","","Version:",""],"rows":[["","Document ID and Title","","","Version:",""],["510(k) Summary RayStation 11B","","","1.0","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220151-p6-t0","doc_id":"K220151","page_num":6,"bbox":[109.9,391.14,540.1,438.06],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Sola with\nsyngo MR XA31A","K203443,\ncleared March 31, 2021","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220151-p6-t1","doc_id":"K220151","page_num":6,"bbox":[109.9,492.03,540.1,598.56],"n_rows":5,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA31A","K203443,\ncleared March 31, 2021","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Avanto with\nsoftware syngo MR E11D","K181613,\ncleared November 6, 2018","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Avantofit\nwith software syngo MR\nE11E","K190757,\ncleared May 31, 2019","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"software already cleared on the following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220151-p8-t0","doc_id":"K220151","page_num":8,"bbox":[109.92,326.31,540.03,662.7],"n_rows":11,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recogniti","on Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/ EMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012\nand\nA2:2010/(R)2012\n(Consolidated Text)","ANSI AAMI"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/ RM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices\n[Including CORRIGENDUM 1\n(2016)]","62366-1 Edition 1.0\n2015-02","IEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"]],"caption_candidate":"following FDA recognized and international IEC, ISO and NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220151-p9-t0","doc_id":"K220151","page_num":9,"bbox":[110.2,103.02,540.3,184.56],"n_rows":2,"n_cols":5,"columns":["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"],"rows":[["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20:2016","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220164-p8-t0","doc_id":"K220164","page_num":8,"bbox":[170.08,200.3,432.43,370.6],"n_rows":7,"n_cols":2,"columns":["Knee","Frontal, Lateral"],"rows":[["Knee","Frontal, Lateral"],["Pelvis","Frontal"],["Shoulder","Frontal, Lateral, Axillary"],["Tibia/fibula","Frontal, Lateral"],["Wrist","Frontal, Lateral, Oblique"],["Hand","Frontal, Lateral"],["Foot","Frontal, Lateral"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220164-p9-t0","doc_id":"K220164","page_num":9,"bbox":[64.02,200.3,531.73,725.45],"n_rows":4,"n_cols":4,"columns":["Intended use\n/Indication for\nuse","FractureDetect (FX)\nis a computer-\nassisted detection and\ndiagnosis (CAD)\nsoftware device to\nassist clinicians in\ndetecting fractures\nduring the review of\nradiographs of the\nmusculoskeletal\nsystem. FX is\nindicated for adults\nonly.","Rayvolve is a\ncomputer-assisted\ndetection and\ndiagnosis (CAD)\nsoftware device to\nassist radiologists\nand emergency\nphysicians in\ndetecting fractures\nduring the review of\nradiographs of the\nmusculoskeletal\nsystem. Rayvolve is\nindicated for adults\nonly (≥ 22 years old).","Same"],"rows":[["Intended use\n/Indication for\nuse","FractureDetect (FX)\nis a computer-\nassisted detection and\ndiagnosis (CAD)\nsoftware device to\nassist clinicians in\ndetecting fractures\nduring the review of\nradiographs of the\nmusculoskeletal\nsystem. FX is\nindicated for adults\nonly.","Rayvolve is a\ncomputer-assisted\ndetection and\ndiagnosis (CAD)\nsoftware device to\nassist radiologists\nand emergency\nphysicians in\ndetecting fractures\nduring the review of\nradiographs of the\nmusculoskeletal\nsystem. Rayvolve is\nindicated for adults\nonly (≥ 22 years old).","Same"],["Image\nModality","X-ray","X-ray","Same"],["Study Type\n(Anatomic\nAreas of\nInterest)","Ankle\nClavicle\nElbow\nFemur\nForearm\nHip\nHumerus\nKnee\nPelvis\nShoulder\nTibia / Fibula\nWrist","Ankle\nClavicle\nElbow\nForearm\nHip\nHumerus\nKnee\nPelvis\nShoulder\nTibia / Fibula\nWrist\nHand\nFoot","Rayvolve covers 2 more\nanatomical regions than FX;\nbut the intended use is\nsimilar since both FX and\nRayvolve are intended to\nidentify fractures in\nradiographs, and all those\nanatomical regions are\nincluded in the definition of\nanatomic area of interest and\nradiographic views\nconsistently with the\nAmerican College of\nRadiology (ACR) standard\nand guidelines."],["Clinical\nFinding","Fracture","Fracture","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220164-p10-t0","doc_id":"K220164","page_num":10,"bbox":[64.03,200.3,531.73,617.67],"n_rows":7,"n_cols":4,"columns":["Patient\nPopulation","Adults ≥ 22 years of\nage","Adults ≥ 22 years of\nage","Same"],"rows":[["Patient\nPopulation","Adults ≥ 22 years of\nage","Adults ≥ 22 years of\nage","Same"],["Intended User","Clinicians","Clinicians (MSK and\nnon-MSK radiologist\nand emergency\nphysicians)","Same"],["Machine\nLearning\nMethodology","Supervised Deep\nLearning","Supervised Deep\nLearning","Same"],["Platform","Secure local\nprocessing and\ndelivery of DICOM\nimages","Secure local\nprocessing and\ndelivery of DICOM\nimages","Same"],["Image Source","DICOM node (e.g.,\nimaging device,\nintermediate DICOM\nnode, PACS system,\netc.)","DICOM node (e.g.,\nimaging device,\nintermediate DICOM\nnode, PACS system,\netc.)","Same as FX"],["Image\nViewing","PACS system, image\nannotations toggled\non or off","PACS system, image\nannotations made on\na copy of the original\nimage","Same, with a copy of the\noriginal image"],["Privacy","HIPAA compliant","HIPAA compliant","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220164-p14-t0","doc_id":"K220164","page_num":14,"bbox":[154.33,243.96,483.31,737.31],"n_rows":38,"n_cols":4,"columns":["All (2626)","","0.98607",""],"rows":[["All (2626)","","0.98607",""],["","(0.9","8104; 0.99","058)"],["","","",""],["mic Area (Nb of images)","AUC (B","ootstrap","ped CI)"],["","","",""],["Ankle (232)","0.99137","(0.98374;","0.99727)"],["","","",""],["Clavicle (171)","0.97806","(0.94626;","0.99761)"],["","","",""],["Elbow (192)","0.996","4 (0.99059","; 1.0)"],["","","",""],["Forearm (157)","0.9953","(0.98909; 0",".99937)"],["","","",""],["Humerus (181)","0.9955","(0.98960; 0",".99943)"],["","","",""],["Hip (198)","0.95821","(0.93239;","0.98014)"],["","","",""],["Knee (239)","0.97742","(0.95084;","0.99592)"],["","","",""],["Pelvis (149)","0.97676","(0.95241;","0.99638)"],["","","",""],["Shoulder (150)","0.97814","(0.94147;","0.99958)"],["","","",""],["Tibia/Fibula (232)","0.98285","(0.95925;","0.9978)"],["","","",""],["Wrist (225)","0.99567","(0.99126;","0.99897)"],["","","",""],["Hand (252)","0.99552","(0.99074;","0.99898)"],["","","",""],["Foot (248)","0.99162","(0.98238;","0.99823)"],["","","",""],["nder (Nb of images)","AUC (B","ootstrap","ped CI)"],["","","",""],["Male (1306) 0",".98822","(0.98186;","0.99409)"],["","","",""],["Female (1320) 0",".98395","(0.97589;","0.99101)"],["","","",""],["iew (Nb of images)","AUC (B","ootstrap","ped CI)"]],"caption_candidate":"All (2626) 0.98607","well_formed":true,"extraction_settings":"text"}
{"table_id":"K220164-p15-t0","doc_id":"K220164","page_num":15,"bbox":[71.39,200.51,524.38,299.76],"n_rows":4,"n_cols":2,"columns":["Frontal (1279)","0.97872 (0.96845; 0.98805)"],"rows":[["Frontal (1279)","0.97872 (0.96845; 0.98805)"],["Lateral (1033)","0.99218 (0.98903; 0.99477)"],["Oblique (268)","0.9958 (0.98979; 0.99977)"],["Axillary (46)","0.99675 (0.98734; 1.0)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220164-p16-t0","doc_id":"K220164","page_num":16,"bbox":[71.37,200.51,510.39,274.99],"n_rows":3,"n_cols":2,"columns":["Non complex & uncommon (2079)","0.99607 (0.98862; 0.99701)"],"rows":[["Non complex & uncommon (2079)","0.99607 (0.98862; 0.99701)"],["weight-bearing (1298)","0.98059 (0.96162; 0.99458)"],["Non-weight-bearing (1328)","0.99143 (0.97916; 0.99912)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220192-p4-t0","doc_id":"K220192","page_num":4,"bbox":[93.42,196.2,555.18,275.76],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Galan 3T, MRT-3020, V8.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220192-p5-t0","doc_id":"K220192","page_num":5,"bbox":[90.24,449.28,540.24,520.14],"n_rows":5,"n_cols":3,"columns":["System","Predicate Device","Reference Device"],"rows":[["System","Predicate Device","Reference Device"],["","Vantage Galan 3T, MRT-3020, V7.0 with AiCE\nReconstruction Processing Unit for MR","Vantage Fortian 1.5T, MRT-1550, V8.0 with AiCE\nReconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc.","Canon Medical Systems USA, Inc."],["510(k) Number","K212056","K213305"],["Clearance Date","August 4, 2021","December 1, 2021"]],"caption_candidate":"Reference Device: Vantage Fortian, MRT 1550, V8.0 (K213305)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220192-p7-t0","doc_id":"K220192","page_num":7,"bbox":[86.0,472.23,558.47,685.03],"n_rows":17,"n_cols":8,"columns":["Item","Subject Device:\nVantage Galan 3T, MRT-3020, V8.0","","","","Predicate Device:","","Notes"],"rows":[["Item","Subject Device:\nVantage Galan 3T, MRT-3020, V8.0","","","","Predicate Device:","","Notes"],["","","","","","Vantage Galan 3T, MRT-3020, V7.0","",""],["","","","","","K212056","",""],["Static field strength","","3T","","3T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","Normal and 1st Operating Mode","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","","Allows screen access to 1st level","","Allows screen access to 1st level\noperating mode","","","Same"],["","","operating mode","","","","",""],["Maximum SAR","","4W/kg for whole body (1st operating","","4W/kg for whole body (1st operating\nmode specified in IEC 60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["","","mode specified in IEC 60601-2-33:","","","","",""],["","","2010+A1:2013+A2:2015)","","","","",""],["Maximum dB/dt","","1st operating mode specified in IEC","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["","","60601-2-33:","","","","",""],["","","2010+A1:2013+A2:2015","","","","",""],["Potential emergency\ncondition and means\nprovided for shutdown","","Shutdown by Emergency Ramp Down","","Shutdown by Emergency Ramp Down\nUnit for collision hazard for\nferromagnetic objects","","","Same"],["","","Unit for collision hazard for","","","","",""],["","","ferromagnetic objects","","","","",""]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220264-p4-t0","doc_id":"K220264","page_num":4,"bbox":[72.32,136.78,545.74,315.17],"n_rows":7,"n_cols":4,"columns":["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],"rows":[["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],["Address","Address","","Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.\nWest Dist.\nTaichung City 403020\nTAIWAN"],["","Applicant","","Joseph Chang"],["Contact Information","Contact Information","","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["","Correspondence Person","","Ti-Hao Wang, MD"],["Contact Information","Contact Information","","886-04-23213838 #168\ntihao.wang@everfortune.ai"],["","Date Prepared","","January 29, 2022"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220264-p4-t1","doc_id":"K220264","page_num":4,"bbox":[72.32,351.49,545.74,451.43],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","EFAI RTSuite CT HN-Segmentation System v1.0"],"rows":[["","Proprietary Name","","EFAI RTSuite CT HN-Segmentation System v1.0"],["","Common Name","","EFAI HNSeg v1.0"],["","Classification Name","","Picture Archiving and Communications System"],["","Regulation Number","","21 CFR 892.2050"],["","Regulation Name","","Medical Image Management and Processing System"],["","Product Code","","QKB"],["","Regulatory Class","","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220264-p4-t2","doc_id":"K220264","page_num":4,"bbox":[72.32,487.71,545.74,590.03],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","AccuContour"],"rows":[["","Proprietary Name","","AccuContour"],["","Premarket Notification","","K191928"],["","Classification Name","","Picture Archiving and Communications System"],["","Regulation Number","","21 CFR 892.2050"],["","Regulation Name","","Medical Image Management and Processing System"],["","Product Code","","QKB"],["","Regulatory Class","","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220264-p6-t0","doc_id":"K220264","page_num":6,"bbox":[72.17,118.2,526.41,716.2],"n_rows":11,"n_cols":7,"columns":["Company","","","","Ever Fortune.AI Co., Ltd. (EFAI)","","Xiamen Manteia Technology LTD."],"rows":[["Company","","","","Ever Fortune.AI Co., Ltd. (EFAI)","","Xiamen Manteia Technology LTD."],["","Device Name","","EFAI HNSeg","","","AccuContour™"],["","510k Number","","Pending","","","K191928"],["","Regulation No.","","21CFR 892.2050","","","21CFR 892.2050"],["","Classification","","II","","","II"],["","Product Code","","QKB","","","QKB"],["Intended Use/Indication\nfor Use","","","EFAI HNSeg is a software device\nintended to assist trained radiation\noncology professionals, including,\nbut not limited to, radiation\noncologists, medical physicists,\nand dosimetrists, during their\nclinical workflows of radiation\ntherapy treatment planning by\nproviding initial contours of organs\nat risk in the head and neck region\non non-contrast CT images. EFAI\nHNSeg is intended to be used on\nadult patients only.\nThe contours are generated by\ndeep-learning algorithms and then\ntransferred to radiation therapy\ntreatment planning systems. EFAI\nHNSeg must be used in conjunction\nwith a DICOM-compliant\ntreatment planning system to\nreview and edit results generated.\nEFAI HNSeg is not intended to be\nused for decision making or to\ndetect lesions.\nEFAI HNSeg is an adjunct tool and\nis not intended to replace a\nclinician's judgment and manual\ncontouring of the normal organs on\nCT. Clinicians must not use the\nsoftware generated output alone\nwithout review as the primary\ninterpretation.","","","It is used by radiation oncology\ndepartment to register\nmultimodality images and segment\n(non-contrast) CT images, to\ngenerate needed information for\ntreatment planning, treatment\nevaluation and treatment adaptation.\nThe product has two image process\nfunctions:\n(1)Deep learning contouring: it can\nautomatically contour the organ-at-\nrisk, including head and neck,\nthorax, abdomen and pelvis (for\nboth male and female),\n(2)Automatic Registration, and\n(3)Manual Contour.\nIt also has the following general\nfunctions:\n(1)Receive, add/edit/delete,\ntransmit, input/export, medical\nimages and DICOM data;\n(2)Patient management;\n(3)Review of processed images;\n(4)Open and save of files."],["","Segmentation","","Deep learning","","","Deep learning"],["","(Contouring)","","","","",""],["","Technology","","","","",""],["","Operating System","","Linux Ubuntu 20.04","","","Microsoft Windows"]],"caption_candidate":"Table - Comparison with the Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220264-p7-t0","doc_id":"K220264","page_num":7,"bbox":[72.16,97.61,526.42,430.43],"n_rows":12,"n_cols":5,"columns":["User Population","","","Trained medical professionals\nincluding, but not limited to,\nradiation oncologists, medical\nphysicists, and dosimetrists.","It is used by radiation oncology\ndepartment."],"rows":[["User Population","","","Trained medical professionals\nincluding, but not limited to,\nradiation oncologists, medical\nphysicists, and dosimetrists.","It is used by radiation oncology\ndepartment."],["Supported Modalities","","","Non-contrast CT","Segmentation Features: Non-\nContrast CT\nRegistration Features: CT, MRI,\nPET"],["","Image Input","","Complies with DICOM standard","Complies with DICOM standard"],["Compatible Scanner\nModels","","","No Limitation on scanner model\nDICOM 3.0 compliance required.","No Limitation on scanner model\nDICOM 3.0 compliance\nrequired."],["","Localization and","","Organ-at risk of head and neck\nregion","Organ-at-risk, including head and\nneck, thorax, abdomen and pelvis\n(for both male and female)"],["","Definition of Objects","","",""],["","(ROI)","","",""],["","Compatible","","No Limitation on TPS model,\nDICOM compliance required.","No Limitation on TPS model,\nDICOM 3.0 compliance required."],["","Treatment Planning","","",""],["","System","","",""],["Automated\nWorkflow","","","EFAI HNSeg automatically\nprocesses input image data and\nsends the results as DICOM-RT\nStructure Sets to a user-\nconfigurable\ntarget node.","AccuContour automatically\nprocesses input image data"],["","User Interface","","No","Yes"]],"caption_candidate":"K220264","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p8-t0","doc_id":"K220332","page_num":8,"bbox":[65.06,513.91,547.18,709.54],"n_rows":6,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],["General","","",""],["Product Code","LNH","LNH","Same"],["Regulation No.","21 CFR 892.1000","21 CFR 892.1000","Same"],["Class","II","II","Same"],["Indications For\nUse","The uMR Omega system is\nindicated for use as a\nmagnetic resonance\ndiagnostic device (MRDD)\nthat produces sagittal,\ntransverse, coronal, and\noblique cross sectional\nimages, and spectroscopic","The uMR Omega\nsystem is indicated for\nuse as a magnetic\nresonance diagnostic\ndevice (MRDD) that\nproduces sagittal,\ntransverse, coronal, and\noblique cross sectional","Same"]],"caption_candidate":"Table 1 Comparison of Hardware configuration","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p10-t0","doc_id":"K220332","page_num":10,"bbox":[65.06,85.34,547.18,710.26],"n_rows":26,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],["Resonant\nfrequencies","128.23 MHz","128.23 MHz","Same"],["Number of\ntransmit\nchannels","2","2","Same"],["Number of\nreceive channels","Up to 96","Up to 96","Same"],["Amplifier peak\npower per\nchannel","18 kW","18 kW","Same"],["RF Coils","","",""],["Volume\nTransmit Coil","Yes","Yes","Same"],["Head & Neck\nCoil -24","Yes","Yes","Same"],["Body Array Coil\n- 12","Yes","Yes","Same"],["Breast Coil - 10","Yes","Yes","Same"],["Flex Coil Large -\n8","Yes","Yes","Same"],["Flex Coil Small -\n8","Yes","Yes","Same"],["Knee Coil - 12","Yes","Yes","Same"],["Lower Extremity\nCoil - 36","Yes","Yes","Same"],["Shoulder Coil -\n12","Yes","Yes","Same"],["Small Loop Coil","Yes","Yes","Same"],["Spine Coil - 32","Yes","Yes","Same"],["Wrist Coil - 12","Yes","Yes","Same"],["Cardiac Coil -\n24","Yes","Yes","Same"],["Temporomandib\nular Joint Coil -\n4","Yes","Yes","Same"],["Foot & Ankle\nCoil - 24","Yes","Yes","Same"],["Head Coil - 32","Yes","Yes","Same"],["Head Coil - 12","Yes","Yes","Same"],["Carotid Coil - 8","Yes","Yes","Same"],["Infant Coil - 24","Yes","Yes","Same"],["Body Array Coil\n- 24","Yes","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p11-t0","doc_id":"K220332","page_num":11,"bbox":[65.06,85.34,547.18,715.18],"n_rows":6,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],["Head & Neck -\n48","Yes","No","The intended use of Head\n& Neck Coil - 48 is\nequivalent to previously\ncleared Head & Neck\nCoil - 24. More coil\nelements in the new coil\ncan better cover the\nscanning parts."],["Spine Coil - 48","Yes","No","The intended use of Spine\nCoil - 48 is equivalent to\npreviously cleared Spine\nCoil - 32. More coil\nelements in the new coil\ncan better cover the\nscanning parts."],["Head Coil - 64","Yes","No","The intended use of Head\nCoil - 64 is equivalent to\npreviously cleared Head\nCoil - 32. More coil\nelements in the new coil\ncan better cover the\nscanning parts."],["SuperFlex Body\n- 24","Yes","No","The intended use of\nSuperFlex Body - 24 is\nessentially identical to\npreviously cleared Body\nArray Coil - 12. The\ndifferences are the\nnumber of channels of the\ncoil and the material used\non the surface of the coil.\nMore coil elements in the\nnew coil can better cover\nthe scanning parts and the\nflexible material is\nbeneficial to wrap the\nscanning parts."],["SuperFlex Large\n- 12","Yes","No","The intended use of\nSuperFlex Large - 12 is\nessentially identical to\npreviously cleared Flex\nCoil Large - 8. The\ndifferences are the\nnumber of channels of the\ncoil\nand the material used on\nthe surface of the coil.\nMore coil elements in the\nnew coil can better cover\nthe scanning parts and the"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p12-t0","doc_id":"K220332","page_num":12,"bbox":[65.06,85.34,547.18,719.14],"n_rows":14,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],["","","","flexible material is\nbeneficial to wrap the\nscanning parts."],["SuperFlex Small\n- 12","Yes","No","The intended use of\nSuperFlex Small - 12 is\nessentially identical to\npreviously cleared Flex\nCoil Small - 8. The\ndifferences are the\nnumber of channels of the\ncoil and the material used\non the surface of the coil.\nMore coil elements in the\nnew coil can better cover\nthe scanning parts and the\nflexible material is\nbeneficial to wrap the\nscanning parts."],["Patient table","","",""],["Dimensions","width 640mm, height\n880mm, length 2620mm","width 640mm, height\n880mm, length\n2620mm","Same"],["Maximum\nsupported\npatient weight","310 kg","310 kg","Same"],["Accessories","","",""],["Vital Signal\nGating","ECG, Peripheral Pulse Gating,\nRespiratory Gating","ECG, Peripheral Pulse\nGating, Respiratory Gating","Same"],["Safety","","",""],["Electrical Safety","Comply with ES60601-1","Comply with ES60601-\n1","Same"],["EMC","Comply with IEC60601-1-\n2","Comply with\nIEC60601-1-2","Same"],["Max SAR for\nTransmit Coil","Comply with IEC 60601-\n2-33","Comply with IEC\n60601-2-33","Same"],["Max dB/dt","Comply with IEC 60601-\n2-33","Comply with IEC\n60601-2-33","Same"],["Biocompatibility","Patient Contact Materials\nwere tested and\ndemonstrated no\ncytotoxicity (ISO 10993-\n5), no evidence for\nirritation and sensitization\n(ISO 10993-10).","Patient Contact\nMaterials were tested\nand demonstrated no\ncytotoxicity (ISO\n10993-5), no evidence\nfor irritation and","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p13-t0","doc_id":"K220332","page_num":13,"bbox":[65.06,85.34,547.18,316.85],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K193200)","Remark"],["","","sensitization (ISO\n10993-10).",""],["Surface Heating","NEMA MS 14","ES 60601-1","The NEMA standards\npublication MS 14-\n2019 describes the\nprocedure for heating\nRF coil heating under\nworst-case normal\noperating conditions.\nThe results for the\nsurface heating test\nshowed that proposed\ndevices perform as\nwell as or better than\npredicate devices."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p13-t1","doc_id":"K220332","page_num":13,"bbox":[68.66,374.69,543.53,706.99],"n_rows":18,"n_cols":6,"columns":["ITEM","Proposed\nDevice\nuMR Omega","Predicate\nDevice\nuMR Omega\n(K193200)","Remark","",""],"rows":[["ITEM","Proposed\nDevice\nuMR Omega","Predicate\nDevice\nuMR Omega\n(K193200)","Remark","",""],["Imaging Features","","","","",""],["Fat Analysis\nand\nCalculation\nTechnique\n(FACT)","Yes","No","FACT is short for fat analysis and calculation\ntechnique and substantially equivalent to WFI.\nIt not only separates water and fat signal and\nquantifies fat fraction and R2* mapping\naccording to chemical shift effect and T2*\neffect.","",""],["Inline T1/T2*\nMapping","Yes","No","","Inline T1/T2* Mapping is substantially equivalent to",""],["","","","","T1/T2* Mapping processed by post-processing",""],["","","","","module. The map result displays inline without extra",""],["","","","","operation by post-processing module.",""],["Inline T2\nMapping","Yes","No","","Inline T2 Map is substantially equivalent to T2 Map",""],["","","","","processed by post-processing module. The map result",""],["","","","","displays inline without extra operation by post-",""],["","","","","processing module.",""],["Arterial Spin\nLabeling\n(ASL)","Yes","No","","ASL is substantially equivalent to FSE and uses extra",""],["","","","","arterial spin labeling preparation and imaging",""],["","","","","processing for cerebral blood flow (CBF) imaging",""],["","","","","without contrast agent.",""],["Flow\nQuantification\n(FQ)","Yes","No","FQ is substantially equivalent to GRE and uses extra\nflow encoding and imaging processing for flow\nquantification.","FQ is substantially equivalent to GRE and uses extra",""],["","","","","flow encoding and imaging processing for flow",""],["","","","","quantification.",""]],"caption_candidate":"Table 2 Comparison of the new Application Software Features","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p14-t0","doc_id":"K220332","page_num":14,"bbox":[68.59,85.39,543.62,550.51],"n_rows":21,"n_cols":6,"columns":["Cardiac T1\nMapping","Yes","No","","Cardiac T1 mapping is substantially equivalent to",""],"rows":[["Cardiac T1\nMapping","Yes","No","","Cardiac T1 mapping is substantially equivalent to",""],["","","","","GRE and uses multiple TI acquisitions with IR",""],["","","","","preparation and imaging processing for cardiac T1",""],["","","","","mapping.",""],["Cardiac T2\nMapping","Yes","No","","Cardiac T2 mapping is substantially equivalent to",""],["","","","","GRE and uses multiple T2-prep duration preparation",""],["","","","","acquisitions and imaging processing for cardiac T2",""],["","","","","mapping.",""],["Cardiac T2*\nMapping","Yes","No","","Cardiac T2* mapping is substantially equivalent to",""],["","","","","GRE and uses multiple TE acquisitions and imaging",""],["","","","","processing for cardiac T2* mapping.",""],["DeepRecon","Yes","No","","Note 1",""],["Workflow Features","","","","",""],["Easy Scan","Yes","No","Easy Scan feature allows automatic slice positioning\nfor Shoulder, Abdomen, L-spine and T-spine\nimaging. The positioning can also be adjusted\nmanually by user. The final positioning effect is\nequivalent to manual operation without Easy Scan\nfeature.","",""],["Function","","","","",""],["MR\nconditional\nimplant mode","Yes","No","In MR conditional implant mode，user can set the\nsafety conditions of the MR conditional implant, and\nuMR Omega system ensure the scanning complies\nwith the conditions.","",""],["Remote\nAssistance","Yes","No","Remote Assistance intends for remote support and\nservice.","",""],["Spectroscopy Sequences","","","","",""],["Liver\nSpectroscopy","Yes","No","Liver spectroscopy is substantially equivalent to\nSpectroscopy and uses multi-echo acquisition and\npost-processing instead of single echo for fat\nquantification of liver.","",""],["Prostate\nSpectroscopy","Yes","No","Prostate spectroscopy is substantially equivalent to\nSpectroscopy and uses characteristic metabolites\ndetection post processing for prostate spectroscopy.","",""],["Breast\nSpectroscopy","Yes","No","Breast spectroscopy is substantially equivalent to\nSpectroscopy and uses characteristic metabolites\ndetection post processing for breast spectroscopy.","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p15-t0","doc_id":"K220332","page_num":15,"bbox":[176.25,144.57,490.83,446.47],"n_rows":21,"n_cols":6,"columns":["","Subjects' Characteristics","","","Total(N=77)",""],"rows":[["","Subjects' Characteristics","","","Total(N=77)",""],["","Gender","","","",""],["","Male","","","37",""],["","Female","","","40",""],["","Age","","","",""],["","18-29","","","14",""],["","30-44","","","30",""],["","45-64","","","24",""],["",">=65","","","9",""],["","Ethnicity","","","",""],["","White","","","36",""],["","Black","","","19",""],["","Asian","","","5",""],["","Hispanic (of any race)","","","17",""],["","Body Mass Index (BMI)","","","",""],["","Underweight (<18.5)","","","1",""],["Healthy weight (18.5-24.9)","","","18","",""],["Overweight (25.0-29.9)","","","28","",""],["Class1 Obesity (30.0-34.9)","","","14","",""],["Class2 Obesity (35-39.9)","","","8","",""],["Class3 Obesity (>=40)","","","8","",""]],"caption_candidate":"Table a. DeepRecon American Volunteers' Demographic Distribution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p15-t1","doc_id":"K220332","page_num":15,"bbox":[128.06,543.55,539.02,718.82],"n_rows":5,"n_cols":4,"columns":["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],"rows":[["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],["Image SNR","DeepRecon images achieve higher\nSNR compared to the images\nwithout DeepRecon (NADR)","NADR:\n209.41±1.08","PASS"],["","","DeepRecon:\n302.48±0.78",""],["Image\nuniformity","Uniformity difference between\nDeepRecon images and NADR\nimages under 5%","0.15%","PASS"],["Image\ncontrast","Intensity difference between\nDeepRecon images and NADR\nimages under 5%","0.9%","PASS"]],"caption_candidate":"Table b. The performance evaluation report criteria of DeepRecon","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p16-t0","doc_id":"K220332","page_num":16,"bbox":[58.57,322.01,553.78,648.22],"n_rows":11,"n_cols":5,"columns":["ITEM","Function name","Proposed device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],"rows":[["ITEM","Function name","Proposed device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],["MRS","Type of imaging\nscans","MRI","MRI","Same"],["","Intended Body\npart","Brain, Body","Brain","Provides spectroscopy\nprotocol of the body\nincluding prostate,\nbreast and liver, which\ndoes not affect safety\nand effectiveness."],["","Single-voxel Spectrum Data\nAnalysis","Yes","Yes","Same"],["","Chemical Shift Imaging\nData","Yes","Yes","Same"],["","Protocol Management","Yes","Yes","Same"],["","Metabolite Pseudo-color\nMap","Yes","Yes","Same"],["","Curve Peak Setting","Yes","Yes","Same"],["","Save Image Data","Yes","Yes","Same"],["","Print Image Data","Yes","Yes","Same"],["","Report","Yes","Yes","Same"]],"caption_candidate":"Table 3 Comparison of the new Post Processing Features","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p17-t0","doc_id":"K220332","page_num":17,"bbox":[61.7,85.34,550.49,174.31],"n_rows":4,"n_cols":6,"columns":["ITEM","Proposed Device\nuMR Omega","Reference Device #2\nuMR 780 (K193176)","Remark","",""],"rows":[["ITEM","Proposed Device\nuMR Omega","Reference Device #2\nuMR 780 (K193176)","Remark","",""],["Image Processing Features","","","","",""],["AI-assisted compressed sensing","Yes","Yes","","Same",""],["Inline T1/T2* Mapping","Yes","Yes","","Same",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p17-t1","doc_id":"K220332","page_num":17,"bbox":[89.9,252.17,522.1,708.1],"n_rows":9,"n_cols":4,"columns":["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],"rows":[["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],["General","","",""],["Device\nClassification\nName","Medical image management and\nprocessing system","Medical image management and\nprocessing system","Same"],["Product Code","QIH LLZ","QIH LLZ","Same"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same"],["Device Class","II","II","Same"],["Classification\nPanel","Radiology","Radiology","Same"],["Advanced\nApplication","Yes","Yes","Same"],["Indications\nfor use","uWS-MR is a software solution\nintended to be used for viewing,\nmanipulation, communication, and\nstorage of medical images. It\nsupports interpretation and\nevaluation of examinations within\nhealthcare institutions. It has the\nfollowing additional indications:\n The MR Stitching is intended\nto create full-format images\nfrom overlapping MR volume\ndata sets acquired at multiple\nstages.\n The Dynamic application is\nintended to provide a general\npost-processing tool for time\ncourse studies.\n The Image Fusion application\nis intended to combine two","uWS-MR is a software solution\nintended to be used for viewing,\nmanipulation, communication,\nand storage of medical images. It\nsupports interpretation and\nevaluation of examinations\nwithin healthcare institutions. It\nhas the following additional\nindications:\n The MR Stitching is\nintended to create full-\nformat images from\noverlapping MR volume\ndata sets acquired at\nmultiple stages.\n The Dynamic application is\nintended to provide a\ngeneral post-processing tool\nfor time course studies.","Same"]],"caption_candidate":"Table 5 Comparison of the Basic Functions of uWS-MR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p18-t0","doc_id":"K220332","page_num":18,"bbox":[89.9,85.34,522.1,711.82],"n_rows":2,"n_cols":4,"columns":["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],"rows":[["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],["","different image series so that\nthe displayed anatomical\nstructures match in both\nseries.\n MRS (MR Spectroscopy) is\nintended to evaluate the\nmolecule constitution and\nspatial distribution of cell\nmetabolism. It provides a set\nof tools to view, process, and\nanalyze the complex MRS\ndata. This application\nsupports the analysis for both\nSVS (Single Voxel\nSpectroscopy) and CSI\n(Chemical Shift Imaging)\ndata.\n The MAPs application is\nintended to provide a number\nof arithmetic and statistical\nfunctions for evaluating\ndynamic processes and\nimages. These functions are\napplied to the grayscale\nvalues of medical images.\n The MR Breast Evaluation\napplication provides the user\na tool to calculate parameter\nmaps from contrast-enhanced\ntime-course images.\n The Brain Perfusion\napplication is intended to\nallow the visualization of\ntemporal variations in the\ndynamic susceptibility time\nseries of MR datasets.\n MR Vessel Analysis is\nintended to provide a tool for\nviewing, manipulating, and\nevaluating MR vascular\nimages.\n The Inner view application is\nintended to perform a virtual\ncamera view through hollow\nstructures (cavities), such as\nvessels."," The Image Fusion\napplication is intended to\ncombine two different\nimage series so that the\ndisplayed anatomical\nstructures match in both\nseries.\n MRS (MR Spectroscopy) is\nintended to evaluate the\nmolecule constitution and\nspatial distribution of cell\nmetabolism. It provides a\nset of tools to view, process,\nand analyze the complex\nMRS data. This application\nsupports the analysis for\nboth SVS (Single Voxel\nSpectroscopy) and CSI\n(Chemical Shift Imaging)\ndata.\n The MAPs application is\nintended to provide a\nnumber of arithmetic and\nstatistical functions for\nevaluating dynamic\nprocesses and images.\nThese functions are applied\nto the grayscale values of\nmedical images.\n The MR Breast Evaluation\napplication provides the\nuser a tool to calculate\nparameter maps from\ncontrast-enhanced time-\ncourse images.\n The Brain Perfusion\napplication is intended to\nallow the visualization of\ntemporal variations in the\ndynamic susceptibility time\nseries of MR datasets.\n MR Vessel Analysis is\nintended to provide a tool\nfor viewing, manipulating,\nand evaluating MR vascular\nimages.",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220332-p19-t0","doc_id":"K220332","page_num":19,"bbox":[89.9,85.34,522.1,379.85],"n_rows":2,"n_cols":4,"columns":["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],"rows":[["Item","Proposed Device\nuWS-MR","Reference Device #1\nuWS-MR (K192601)","Remark"],[""," The DCE analysis is intended\nto view, manipulate, and\nevaluate dynamic contrast-\nenhanced MRI images.\n The United Neuro is intended\nto view, manipulate, and\nevaluate MR neurological\nimages.\n The MR Cardiac Analysis\napplication is intended to be\nused for viewing, post-\nprocessing and quantitative\nevaluation of cardiac\nmagnetic resonance data."," The Inner view application\nis intended to perform a\nvirtual camera view through\nhollow structures (cavities),\nsuch as vessels.\n The DCE analysis is\nintended to view,\nmanipulate, and evaluate\ndynamic contrast-enhanced\nMRI images.\n The United Neuro is\nintended to view,\nmanipulate, and evaluate\nMR neurological images.\n The MR Cardiac Analysis\napplication is intended to be\nused for viewing, post-\nprocessing and quantitative\nevaluation of cardiac\nmagnetic resonance data.",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p4-t0","doc_id":"K220349","page_num":4,"bbox":[72.26,172.82,539.92,294.53],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor:","TereRecon, Inc."],"rows":[["510(k) Sponsor:","TereRecon, Inc."],["Address:","4309 Emperor Blvd.,\nDurham, NC 27703, USA"],["Contact Person:","Michael Sosebee\nSenior Manager RAQA"],["Contact Information:","Email: msosebee@terarecon.com\nPhone: 704-651-6828"],["Date Summary Prepared:","10Feb2022"]],"caption_candidate":"1.1 Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p4-t1","doc_id":"K220349","page_num":4,"bbox":[72.26,325.73,539.92,480.43],"n_rows":7,"n_cols":2,"columns":["Proprietary (Trade) Name of Subject Device","TeraRecon Neuro"],"rows":[["Proprietary (Trade) Name of Subject Device","TeraRecon Neuro"],["Model Number","2.0.0"],["Device Class","2"],["Common / Classification Name","System, Image Processing, Radiological"],["Product Code","LLZ"],["Regulation Number","892.2050"],["510(k) Number","K220349"]],"caption_candidate":"1.2 Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p4-t2","doc_id":"K220349","page_num":4,"bbox":[72.26,511.75,539.92,666.46],"n_rows":7,"n_cols":2,"columns":["Proprietary (Trade) Name of Predicate Device","Neuro.AI Algorithm"],"rows":[["Proprietary (Trade) Name of Predicate Device","Neuro.AI Algorithm"],["Model Number","1.0.0"],["Device Class","2"],["Common / Classification Name","System, Image Processing, Radiological"],["Product Code","LLZ"],["Regulation Number","892.2050"],["510(k) Number","K200750"]],"caption_candidate":"1.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p8-t0","doc_id":"K220349","page_num":8,"bbox":[31.47,97.68,750.7,416.83],"n_rows":10,"n_cols":9,"columns":["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],"rows":[["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],["","","","","(Used in Qualitative","","","(Used in Qualitative",""],["","","","","Assessment)","","","Assessment)",""],["","","","","","","","",""],["","","","","FastStroke, CT Perfusion 4D","","","iSchemaView RAPID",""],["","","","","(K193289)","","","(K182130)",""],["Areas of Use","Same as predicate device","Radiology and could also include\nother clinical specialty areas\nsuch as emergency, neurology,\nsurgery and more","Not specified in K193289’s\n510(k) summary.","","","Hospital LAN, inside the\nHospital Firewall\nTo be used by trained\nprofessionals.\nRadiological data network.","",""],["Modality\nSupport","Same as predicate device","Vendor-neutral - CT, MR and\nother volumetric imaging\nmodalities.\nImages are exposed over time.","CT","","","CT and MRI","",""],["Body Part","Same as predicate device","Head – entire brain or from\nlower edge of the base of nucleus\nto upper edge of the ventricles.","Head and Body","","","Not specified in K182130’s\n510(k) summary","",""],["DICOM®\nformats","Same as predicate device","NEMA PS 3.1 – 3.20 (2016)","DICOM 3.0 image compatibility","","","NEMA PS 3.1 – 3.20 (2016)","",""]],"caption_candidate":"Table 1: Technological Characteristics Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p9-t0","doc_id":"K220349","page_num":9,"bbox":[31.51,72.36,750.67,301.01],"n_rows":7,"n_cols":9,"columns":["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],"rows":[["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],["","","","","(Used in Qualitative","","","(Used in Qualitative",""],["","","","","Assessment)","","","Assessment)",""],["","","","","","","","",""],["","","","","FastStroke, CT Perfusion 4D","","","iSchemaView RAPID",""],["","","","","(K193289)","","","(K182130)",""],["Operating\nSystem","Same as predicate device","Microsoft Windows® executable\non off the shelf hardware and\nCentOS (Interoperability)","Not specified in K193289’s\n510(k) summary","","","The software runs on a standard\noff-the-shelf computer or a\nvirtual platform, such as\nVMware,\nand can be used to perform\nimage viewing, processing and\nanalysis of images. Data and\nimages\nare acquired through DICOM\ncompliant imaging devices.\nLinux-based server","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p10-t0","doc_id":"K220349","page_num":10,"bbox":[31.51,72.36,750.67,465.46],"n_rows":7,"n_cols":9,"columns":["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],"rows":[["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],["","","","","(Used in Qualitative","","","(Used in Qualitative",""],["","","","","Assessment)","","","Assessment)",""],["","","","","","","","",""],["","","","","FastStroke, CT Perfusion 4D","","","iSchemaView RAPID",""],["","","","","(K193289)","","","(K182130)",""],["Key\nFunctionality/\nFeature and\nRegion-of-\nInterest (ROI)\nMarkers","Same as predicate device","• Automatic arterial and venous\ninput function selection\n• Ventricle subtraction","CT perfusion 4D is an image\nanalysis software package, which\nallows the user to produce\ndynamic image\ndata and to generate information\nwith regards to changes in image\nintensity over time. It supports\nthe\nanalysis of CT Perfusion images\n(in the head and body) after the\nintravenous injection of contrast,\nand\ncalculation of the various\nperfusion-related parameters (i.e.\nregional blood flow, regional\nblood volume,\nmean transit time and capillary\npermeability).","","","The iSchemaView RAPID\nprovides both viewing and\nanalysis capabilities for\nfunctional and\ndynamic imaging datasets\nacquired with CT Perfusion (CT-\nP), CT Angiography (CTA), and\nMRI including a Diffusion\nWeighted MRI (DWI) Module\nand a Dynamic Analysis Module\n(dynamic contrast-enhanced\nimaging data for MRI and CT).\nThe DWI Module is used to\nvisualize local water diffusion\nproperties from the analysis of\ndiffusion - weighted MRI data.\nThe Dynamic Analysis Module\nis used for visualization and\nanalysis of dynamic imaging\ndata, showing properties of\nchanges in contrast over time.\nThis functionality includes\ncalculation of parameters related\nto tissue flow (perfusion) and\ntissue blood volume.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p11-t0","doc_id":"K220349","page_num":11,"bbox":[31.47,72.36,750.7,492.46],"n_rows":11,"n_cols":9,"columns":["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],"rows":[["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],["","","","","(Used in Qualitative","","","(Used in Qualitative",""],["","","","","Assessment)","","","Assessment)",""],["","","","","","","","",""],["","","","","FastStroke, CT Perfusion 4D","","","iSchemaView RAPID",""],["","","","","(K193289)","","","(K182130)",""],["Perfusion\nmeasurements\nand color maps","• Same as predicate device and\n• Time to Maximum (Tmax)\n• Hypoperfusion maps and\nvolumes\n• Mismatch maps\n(penumbra/umbra maps that\nare derived from combinations\nof measurement parameters)\nand related volumes and ratios","• Time to peak (or Time to\nMinimum)\n• Take off time (or Maximum\nSlope of Increase)\n• Recirculation time (RT)\n• Mean transit time (MTT)\n• Blood volume (BV/CBV)\n• Blood flow (BF/CBF)\n• User c onfigurable settings","• Blood Flow\n• Blood Volume\n• Mean Transit Time\n• Capillary Permeability\n• Time to Maximum","","","• Blood Flow\n• Blood Volume\n• Mean Transit Time\n• Time to Maximum","",""],["Graph Displays","Same as predicate device","Artery and Vein Fitted and Raw\ncurves – time/activity","Not specified in K193289’s\n510(k) summary","","","Not specified in K182130’s\n510(k) summary","",""],["Export\nCapability","• Same as predicate device and\n• Artery Intensity Profile","DICOM files","Not specified in K193289’s\n510(k) summary","","","Not specified in K182130’s\n510(k) summary","",""],["Methods for\nMathematical\nModeling","Same as predicate device","SVD","Not specified in K193289’s\n510(k) summary","","","Not specified in K182130’s\n510(k) summary","",""],["Arterial and\nVenous Input\nFunction\nSelection","Same as predicate device","Automatic","Not specified in K193289’s\n510(k) summary","","","Arterial input function (AIF) and\nVenous output function (VOF)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220349-p12-t0","doc_id":"K220349","page_num":12,"bbox":[31.49,72.36,750.69,463.42],"n_rows":8,"n_cols":9,"columns":["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],"rows":[["Functionality","Subject Device\nTeraRecon Neuro version 2.0.0\n(TBD)","Predicate Device\nNeuro.AI Algorithm version\n1.0.0\n(K200750)","","Reference Device","","","Reference Device",""],["","","","","(Used in Qualitative","","","(Used in Qualitative",""],["","","","","Assessment)","","","Assessment)",""],["","","","","","","","",""],["","","","","FastStroke, CT Perfusion 4D","","","iSchemaView RAPID",""],["","","","","(K193289)","","","(K182130)",""],["Containerization\n/ dockerization\nof algorithm that\nenables\ninteroperability\nwith 3rd party\nresults including\nviewing such\nresults","Same as predicate device","• Neuro.AI Algorithm is hosted\non the Eureka platform within\nits own docker. The algorithm\nis triggered based on input\ndata and generates result\nwhich will be delivered to\nthird party system.\n• CT and MR Scanners\n• 3rd party hospital systems\nsuch as a PACS server, EMR\nor other\n• TeraRecon Intuition\n• Visualization system\n• Other image viewing\nsystems that can support\nresults generated by the\nNeuro.AI Algorithm\n• Notification systems","The configuration of\nNeuroPackage enables the user\nto open a single application,\nFastStroke, which provides them\naccess to both the updated CT\nPerfusion 4D\nand FastStroke applications.\nThe capabilities in CT Perfusion\n4D\nand FastStroke can be offered\nindependently.","","","RAPID is available in the\nfollowing configurations:\n• Standard RAPID, which is\ninstalled directly on a customer's\nLinux-based server and\nintegrated with medical image\nprocessing software such as\ncommercial PACS.\n• Virtual RAPID, wherein the\nuser accesses RAPID online and\nuses it to process DICOM\nimages otherwise available on\nhis/her computer.","",""],["Ventricle\nSubtraction","Same as predicate device","Setting allows software to\ncalculate maps with or without\nventricle included.","Ventricle Segmentation","","","Not specified in K182130’s\n510(k) summary","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220408-p12-t0","doc_id":"K220408","page_num":12,"bbox":[206.2,176.13,295.46,527.25],"n_rows":4,"n_cols":2,"columns":["Distance","Comparison"],"rows":[["Distance","Comparison"],["e 5. 95%","HD (mm) fo"],["",""],["e 6. 95%","HD (mm) fo"]],"caption_candidate":"Hausdorff Distance Comparison (95% HD)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K220416-p4-t0","doc_id":"K220416","page_num":4,"bbox":[88.56,391.08,523.44,489.96],"n_rows":8,"n_cols":2,"columns":["","Primary Predicate Device: SwiftMR – K210999 by AIRS Medical, Inc., Class II,"],"rows":[["","Primary Predicate Device: SwiftMR – K210999 by AIRS Medical, Inc., Class II,"],["","CFR 892.2050, classification with product code LLZ."],["",""],["IV. DEVICE DESCRIPTION",""],["","SwiftMR, is software used as a Medical Device (SaMD) consisting of a software"],["","algorithm that enhances images taken by MRI scanners. The device only"],["","processes DICOM images for the end User and is intended to be used by radiology"],["","technologists in an imaging center, clinic, or hospital."]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220416-p6-t0","doc_id":"K220416","page_num":6,"bbox":[98.9,119.9,545.15,716.76],"n_rows":10,"n_cols":8,"columns":["Item","","Predicate Device","","","Subject Device","","Differences"],"rows":[["Item","","Predicate Device","","","Subject Device","","Differences"],["","","(SwiftMR (K210999))","","","(SwiftMR)","",""],["Physical\nCharacteristics","Software device that\noperates on off-the-\nshelf computer\nhardware","","","Same as predicate","","","No Difference"],["Computer","PC Compatible","","","Same as predicate","","","No Difference"],["DICOM\nStandard\nCompliance","The software processes\nDICOM-compliant\nimage data","","","Same as predicate","","","No Difference"],["Modalities","MRI","","","Same as predicate","","","No Difference"],["Image\nEnhancement\nAlgorithm\nDescription","SwiftMR implements an\nimage enhancement\nalgorithm using\nconvolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Neural\nnetwork-based filters\nthat simultaneously\nperform noise reduction\nand sharpness increase\nfunctions are obtained.\nThe parameters of the\nfilters were obtained\nthrough an image\nguided optimization\nprocess.","","","SwiftMR implements an\nimage enhancement\nalgorithm using\nconvolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Neural\nnetwork-based filters\nthat perform noise\nreduction are obtained.\nThe parameters of the\nfilters were obtained\nthrough an image\nguided optimization\nprocess.\nSharpening filter is\nadditionally applied to\nthe deep learning\nprocessed image.","","","The deep learning algorithm using\nconvolutional neural network-based\nfiltering performs denoising function\nand newly added sharpness filter\nperforms sharpening function in the\nsubject device."],["Deep learning\nmodels","1 General sequence\nmodel\n1 TOF sequence model","","","3 General sequence\nmodels\n1 TOF sequence model","","","The general sequence model was\ndivided into three separate models\nfor each MRI manufacturer.\nThe TOF sequence model remains\nthe same as the predicate device."],["Supported body\nparts","Brain","","","Brain, Spine, knee,\nankle, shoulder, and\nhip","","","Supported body parts have been\nexpanded to spine and MSK (knee,\nankle, shoulder, and hip) in addition\nto brain."],["Workflow","The predicate software\noperates on DICOM\nfiles on the file system,\nenhances the images,\nand stores the\nenhanced images on\nthe file system. The","","","SwiftMR operates on\nDICOM files, enhances\nthe images, and stores\nthe enhanced images\non PACS.","","","The subject device can receive\nDICOM files either from PACS or\nfrom MR device.\nIt is possible to store only the\nprocessed images."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220416-p7-t0","doc_id":"K220416","page_num":7,"bbox":[98.95,119.85,545.14,240.48],"n_rows":3,"n_cols":8,"columns":["Item","","Predicate Device","","","Subject Device","","Differences"],"rows":[["Item","","Predicate Device","","","Subject Device","","Differences"],["","","(SwiftMR (K210999))","","","(SwiftMR)","",""],["","receipt of original\nDICOM image files and\ndelivery of enhanced\nimages as DICOM files\ndepends on other\nsoftware systems.\nEnhanced images co-\nexist with the original\nimages.","","","Enhanced images can\nbe stored with the\noriginal images or only\nthe enhanced images\ncan be stored.","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220437-p6-t0","doc_id":"K220437","page_num":6,"bbox":[72.27,99.94,542.84,708.82],"n_rows":11,"n_cols":4,"columns":["","Subject Device","Primary predicate Device","Reference Device"],"rows":[["","Subject Device","Primary predicate Device","Reference Device"],["Device name","Neurophet AQUA v2.1","NeuroQuant® v2.2","BrainInsight"],["510(k)","K220437","K170981","K202414"],["Manufacturer","NEUROPHET, Inc.","CorTechs Labs, Inc","Hyperfine Research, Inc"],["Product Code","LLZ","LLZ","LLZ"],["Indications for\nUse","Neurophet AQUA is\nintended for Automatic\nlabeling, visualization\nand volumetric\nquantification of\nsegmentable brain\nstructures from a set of\nMR images. Volumetric\ndata may be compared to\nreference percentile data.","NeuroQuant is intended for\nautomatic labeling,\nvisualization and\nvolumetric quantification of\nsegmentable brain\nstructures and lesions from\na set of MR images.\nVolumetric data may be\ncompared to reference\npercentile data.","Automatic labeling, spatial\nmeasurement, and\nvolumetric\nquantification of brain\nstructures from a set of\nlow-field MR images and\nreturns annotated and\nsegmented images, color\noverlays, and reports."],["Target\nAnatomical\nSites","Brain","Brain","Brain"],["Design and\nIncorporated\nTechnology","• Automated\nmeasurement of brain\ntissue volumes and\nstructures\n▪ Automatic\nsegmentation and\nquantification of brain\nstructures using deep\nlearning","• Automated measurement\nof brain tissue volumes and\nstructures and lesions\n• Automatic segmentation\nand quantification of brain\nstructures using a dynamic\nprobabilistic\nneuroanatomical atlas, with\nage and gender specificity,\nbased on the MR image\nintensity","▪ Automated measurement\nof\nbrain tissue volumes and\nstructures\n▪ Automatic segmentation\nand quantification of brain\nstructures using machine\nlearning"],["Physical\ncharacteristics","• Software package\n• Operates on off-the-\nshelf hardware (multiple\nvendors)","• Software package\n• Operates on off-the-shelf\nhardware (multiple\nvendors)","No software required\n• Operates in a serverless\ncloud environment\n• User interface through\nPACS (multiple vendors)"],["Operating\nSystem","Windows","Supports Linux, Mac OS X\nand Windows.","Supports Linux"],["Processing\nArchitecture","Automated internal\npipeline that performs:\n- segmentation\n- volume calculation\n- report generation","Automated internal pipeline\nthat performs:\n- artifact correction\n- segmentation\n- lesion quantification\n- volume calculation","Automated internal\npipeline that performs:\n- segmentation\n- volume calculation\n- distance measurement\n- numerical information"]],"caption_candidate":"10. Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220437-p7-t0","doc_id":"K220437","page_num":7,"bbox":[72.26,72.24,542.86,529.03],"n_rows":4,"n_cols":4,"columns":["","","- report generation","display"],"rows":[["","","- report generation","display"],["Data Source","• MRI scanner: 3D T1\nscans acquired with\nspecified protocols\n• Supports DICOM\nformat as input","• MRI scanner: 3D T1 and\nFLAIR MRI scans acquired\nwith specified protocols\n• Supports DICOM format\nas input","▪ MRI scanner: Hyperfine\nFSE MRI scans acquired\nwith\nspecified protocols\n▪ Supports DICOM format\nas\ninput"],["Output","▪ Provides volumetric\nmeasurements of brain\nstructures\n▪ Includes segmented\ncolor overlays and\nmorphometric reports\n▪ Automatically\ncompares results to\nreference percentile data\nand to prior scans when\navailable\n▪ Supports DICOM\nformat as output of\nresults that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and\nCommunications\nSystems","▪ Provides volumetric\nmeasurements of brain\nstructures and lesions\n▪ Includes segmented color\noverlays and\nmorphometric reports\n▪ Automatically compares\nresults to reference\npercentile data and to prior\nscans when available\n▪ Supports DICOM format\nas output of results that can\nbe displayed on DICOM\nworkstations and Picture\nArchive and\nCommunications Systems","Provides volumetric\nmeasurements of brain\nstructures\n▪ Includes segmented color\noverlays and\nmorphometric\nreports\n▪ Supports DICOM format\nas\noutput of results that can\nbe\ndisplayed on DICOM\nworkstations and Picture\nArchive and\nCommunications Systems"],["Safety","• Automated quality\ncontrol functions\n- Tissue contrast check\n- Scan protocol\nverification\n• Results must be\nreviewed by a trained\nphysician","• Automated quality control\nfunctions\n- Tissue contrast check\n- Scan protocol verification\n- Atlas alignment check\n• Results must be reviewed\nby a trained physician","Automated quality control\nfunctions\n▪ Tissue contrast check\n▪ Scan protocol\nverification\n▪ Atlas alignment check\n▪ Results must be reviewed\nby a trained physician"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220437-p8-t0","doc_id":"K220437","page_num":8,"bbox":[72.26,127.46,510.22,239.9],"n_rows":4,"n_cols":3,"columns":["","Neurophet AQUA","NeuroQuant"],"rows":[["","Neurophet AQUA","NeuroQuant"],["Processing\narchitecture","Segmentation based on deep\nlearning tools, volume\ncalculation and report\ngeneration.","Artifact correction, atlas-based\nsegmentation, lesion\nquantification, volume calculation\nand report generation."],["Operating\nSystem","Windows","Supports Linux, Mac OS X and\nWindows."],["Deployment","Installed","Cloud based or installed"]],"caption_candidate":"Following are the differences between Neurophet AQUA and the predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p4-t0","doc_id":"K220439","page_num":4,"bbox":[108.24,472.8,539.76,501.96],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc.","Viz ICH","K210209"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p6-t0","doc_id":"K220439","page_num":6,"bbox":[108.0,165.36,540.0,622.44],"n_rows":17,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz SDH","Viz ICH"],["Application No.","K220439","K210209"],["Product Code","QAS","QAS"],["Regulation No.","21 C.F.R. § 892.2080","21 C.F.R. § 892.2080"],["Anatomical\nRegion","Head","Head"],["Diagnostic\nApplication","Notification-only","Notification-only"],["Notification/\nPrioritization","Yes","Yes"],["Intended User","Neurovascular or\nNeurosurgical Specialist","Neurovascular or Neurosurgical\nSpecialist"],["DICOM\nCompatible","Yes","Yes"],["Data Acquisition","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities.","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities."],["Supported\nImaging Modality","Computed Tomography, non-\ncontrast (NCCT)","Computed Tomography, non-\ncontrast (NCCT)"],["Alteration of\nOriginal Image","No","No"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-\ndiagnostic purposes","Initial assessment; non-diagnostic\npurposes"],["View DICOM\nData","DICOM Information about the\npatient, study and current\nimage.","DICOM Information about the\npatient, study and current image."],["Time to\nNotification","1.15±0.57 minutes","1.15±0.83 minutes"]],"caption_candidate":"has the same non-diagnostic warning on the image viewing screen as the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t0","doc_id":"K220439","page_num":8,"bbox":[108.0,166.44,534.48,235.44],"n_rows":5,"n_cols":3,"columns":["Device Performance by Clinical Site","",""],"rows":[["Device Performance by Clinical Site","",""],["Clinical Site","Sensitivity [95% CI]","Specificity [95% CI]"],["Site 001","0.93 [0.83, 0.98]","0.91 [0.86, 0.95]"],["Site 002","0.93[0.81,0.99]","0.95[0.87,0.99]"],["Site 003","0.95 [0.89, 0.99]","0.92 [0.85, 0.96]"]],"caption_candidate":"Stratification of Device Performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t1","doc_id":"K220439","page_num":8,"bbox":[108.0,249.72,539.96,318.72],"n_rows":5,"n_cols":3,"columns":["Device Performance by Age","",""],"rows":[["Device Performance by Age","",""],["Age Range (Years)","Sensitivity [95% CI]","Specificity [95% CI]"],["<50","1.0 [0.54, 1.0]","0.95 [0.84, 0.99]"],["50-70","1.0 [0.88, 1.0]","0.92 [0.82, 0.97]"],["70<","0.91 [0.82, 0.96]","0.91 [0.81, 0.97]"]],"caption_candidate":"Site 003 0.95 [0.89, 0.99] 0.92 [0.85, 0.96]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t2","doc_id":"K220439","page_num":8,"bbox":[108.0,333.12,539.96,388.2],"n_rows":4,"n_cols":3,"columns":["Device Performance by Gender","",""],"rows":[["Device Performance by Gender","",""],["Gender (Years)","Sensitivity [95% CI]","Specificity [95% CI]"],["Male","0.97 [0.92, 0.99]","0.9 [0.84, 0.94]"],["Female","0.9 [0.80, 0.96]","0.94 [0.90, 0.97]"]],"caption_candidate":"70< 0.91 [0.82, 0.96] 0.91 [0.81, 0.97]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t3","doc_id":"K220439","page_num":8,"bbox":[108.0,402.6,539.96,489.6],"n_rows":5,"n_cols":3,"columns":["Device Performance by Presence of Subdural Hemorrhage and Other Hemorrhage","",""],"rows":[["Device Performance by Presence of Subdural Hemorrhage and Other Hemorrhage","",""],["Hemorrhage Subtypes","Sensitivity [95% CI]","Specificity [95% CI]"],["Subdural hemorrhage only","0.93 ['0.88', '0.97']","-"],["Subdural hemorrhage and\nother hemorrhage present","0.97 ['0.86', '1.00']","-"],["Other, non-subdural\nhemorrhage present","-","1.0 ['0.40', '1.00']"]],"caption_candidate":"Female 0.9 [0.80, 0.96] 0.94 [0.90, 0.97]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t4","doc_id":"K220439","page_num":8,"bbox":[108.0,517.8,539.96,573.0],"n_rows":4,"n_cols":3,"columns":["Device Performance by Slice Thickness","",""],"rows":[["Device Performance by Slice Thickness","",""],["Slice Thickness","Sensitivity [95% CI]","Specificity [95% CI]"],["2.5mm ≤ Slice Thickness < 3.5mm","0.95 [0.89, 0.98]","0.93 [0.88, 0.96]"],["3.5mm ≤ Slice Thickness ≤ 5.0mm","0.93 [0.83, 0.98]","0.91 [0.86, 0.95]"]],"caption_candidate":"hemorrhage present","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t5","doc_id":"K220439","page_num":8,"bbox":[108.0,600.0,539.96,669.0],"n_rows":5,"n_cols":2,"columns":["Device Performance by SDH Thickness",""],"rows":[["Device Performance by SDH Thickness",""],["Thickness","Sensitivity [95% CI]"],["3mm ≤ Thickness < 6mm","0.81 [0.58, 0.95]"],["6mm ≤ Thickness < 10mm","0.91 [0.8, 0.98]"],["Thickness > 10mm","0.97 [0.93, 0.99]"]],"caption_candidate":"3.5mm ≤ Slice Thickness ≤ 5.0mm 0.93 [0.83, 0.98] 0.91 [0.86, 0.95]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p8-t6","doc_id":"K220439","page_num":8,"bbox":[108.0,682.68,539.96,710.28],"n_rows":2,"n_cols":2,"columns":["Device Performance by SDH Type",""],"rows":[["Device Performance by SDH Type",""],["SDH Type","Sensitivity [95% CI]"]],"caption_candidate":"Thickness > 10mm 0.97 [0.93, 0.99]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p9-t0","doc_id":"K220439","page_num":9,"bbox":[108.0,72.29,539.91,113.35],"n_rows":3,"n_cols":4,"columns":["Acute","","0.92 [0.85, 0.97]",""],"rows":[["Acute","","0.92 [0.85, 0.97]",""],["Non-Acute (Chronic)","","0.93 [0.82, 0.99]",""],["Both (Acute and Chronic)","","0.98 [0.88, 1.00]",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p9-t1","doc_id":"K220439","page_num":9,"bbox":[108.0,140.64,539.91,209.26],"n_rows":5,"n_cols":6,"columns":["Device Performance by SDH Location","","","","",""],"rows":[["Device Performance by SDH Location","","","","",""],["SDH Location","Sensitivity [95% CI]","","","",""],["Tentorial","","","1.0 CI: [0.79, 1.00]","",""],["Falcine","","0.87 CI: [0.69, 0.96]","","",""],["Posterior Fossa","","0.33 CI: ['0.01', '0.91']","","",""]],"caption_candidate":"Both (Acute and Chronic) 0.98 [0.88, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p9-t2","doc_id":"K220439","page_num":9,"bbox":[108.0,236.64,539.91,305.52],"n_rows":5,"n_cols":3,"columns":["Device Performance by Scanner Manufacturer","",""],"rows":[["Device Performance by Scanner Manufacturer","",""],["Manufacturer","Sensitivity [95% CI]","Specificity [95% CI]"],["General Electric","0.92 [0.84, 0.97]","0.92 [0.87, 0.95]"],["Siemens","0.94 [0.83, 0.99]","0.94 [0.87, 0.98]"],["Toshiba","0.98 [0.89, 1.0]","0.92 [0.81, 0.97]"]],"caption_candidate":"Posterior Fossa 0.33 CI: ['0.01', '0.91']","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p9-t3","doc_id":"K220439","page_num":9,"bbox":[76.92,334.56,535.2,709.08],"n_rows":21,"n_cols":4,"columns":["Device Performance by Scanner Manufacturer/Model","","",""],"rows":[["Device Performance by Scanner Manufacturer/Model","","",""],["Manufacturer","Model","Sensitivity [95% CI]","Specificity [95% CI]"],["GE Medical\nSystems","BRIGHTSPEED","1.0 [0.63, 1.0]","0.82 [0.57, 0.96]"],["","RIGHTSPEED S","1.0 [0.29, 1.0]","1.0 [0.29, 1.0]"],["","DISCOVERY 610","1.0 [0.69, 1]","0.94 [0.70, 1]"],["","DISCOVERY CT750 HD","0.85 [0.65, 0.96]","0.93 [0.88, 0.97]"],["","LIGHTSPEED VCT","1.0 [0.48, 1.0]","0.5 [0.01, 0.99]"],["","LIGHTSPEED16","1.0 ['0.03', '1.00']","0.5 ['0.01', '0.99']"],["","OPTIMA CT540","1.0 ['0.03', '1.00']","N/A"],["","OPTIMA CT660","1.0 ['0.03', '1.00']","1.0 ['0.03', '1.00']"],["","REVOLUTION CT","1.0 ['0.74', '1.00']","0.67 ['0.09', '0.99']"],["","REVOLUTION EVO","0.86 ['0.65', '0.97']","0.94 ['0.81', '0.99']"],["Siemens","EMOTION 16","N/A","1.0 [0.03, 1.0]"],["","PERSPECTIVE","0.94 ['0.74',\n'1.00']","0.93 ['0.77', '0.99']"],["","SENSATION 64","1.0 [0.03, 1.0]","N/A"],["","SOMATOM DEFINITION\nAS","1.0 ['0.29', '1.00']","1.0 ['0.59', '1.00']"],["","SOMATOM DEFINITION\nAS+","0.89 ['0.67', '0.99']","0.95 ['0.83', '0.99']"],["","SOMATOM DEFINITION\nFLASH","1.0 ['0.16', '1.00']","N/A"],["","SOMATOM GO.ALL","1.0 ['0.29', '1.00']","0.88 ['0.47', '1.00']"],["","SOMATOM PERSPECTIVE","1.0 [0.03, 1.0]","N/A"],["Toshiba","AQUILION","1.0 ['0.84', '1.00']","0.95 ['0.76', '1.00']"]],"caption_candidate":"Toshiba 0.98 [0.89, 1.0] 0.92 [0.81, 0.97]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p10-t0","doc_id":"K220439","page_num":10,"bbox":[76.92,72.24,535.2,148.44],"n_rows":4,"n_cols":4,"columns":["Device Performance by Scanner Manufacturer/Model","","",""],"rows":[["Device Performance by Scanner Manufacturer/Model","","",""],["Manufacturer","Model","Sensitivity [95% CI]","Specificity [95% CI]"],["","AQUILION ONE","1.0 ['0.54', '1.00']","1.0 ['0.63', '1.00']"],["","AQUILION PRIME","0.95 ['0.75', '1.00']","0.87 ['0.69', '0.96']"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p10-t1","doc_id":"K220439","page_num":10,"bbox":[131.64,175.44,521.28,258.12],"n_rows":6,"n_cols":2,"columns":["Device Performance by Subdural Hemorrhage Volume",""],"rows":[["Device Performance by Subdural Hemorrhage Volume",""],["Volume (mL)","Sensitivity [95% CI]"],["Volume <1","0.33 [0.04, 0.78]"],["1<= Volume < 5","0.85 [0.65, 0.96]"],["5 <= Volume < 10","1.0 [0.75, 1.0]"],["Volume >= 10","0.98 [0.94, 1.0]"]],"caption_candidate":"AQUILION PRIME 0.95 ['0.75', '1.00'] 0.87 ['0.69', '0.96']","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220439-p10-t2","doc_id":"K220439","page_num":10,"bbox":[83.4,286.56,528.72,437.64],"n_rows":10,"n_cols":4,"columns":["Device Performance by Scanner Reconstruction Method","","",""],"rows":[["Device Performance by Scanner Reconstruction Method","","",""],["Manufacturer","Reconstruction\nMethod","Sensitivity [95% CI]","Specificity [95% CI]"],["GE Medical\nSystems","SOFT","0.79 ['0.49', '0.95']","1.0 ['0.79', '1.00']"],["","STANDARD","0.94 ['0.85', '0.98']","0.91 ['0.86', '0.95']"],["","STND#","1.0 ['0.66', '1.00']","0.67 ['0.09', '0.99']"],["Siemens","H30s","1.0 ['0.40', '1.00']","1.0 ['0.40', '1.00']"],["","['Hc40f', '2']","1.0 ['0.29', '1.00']","0.88 ['0.47', '1.00']"],["","['J30s', '2']","0.92 ['0.79', '0.98']","0.94 ['0.86', '0.98']"],["Toshiba","FC26","0.96 ['0.81', '1.00']","0.9 ['0.76', '0.97']"],["","FC68","1.0 ['0.82', '1.00']","0.95 ['0.75', '1.00']"]],"caption_candidate":"Volume >= 10 0.98 [0.94, 1.0]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p2-t0","doc_id":"K220497","page_num":2,"bbox":[257.72,430.78,570.36,527.38],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p7-t0","doc_id":"K220497","page_num":7,"bbox":[72.24,94.32,729.0,528.48],"n_rows":6,"n_cols":6,"columns":["","Predicate Device -\nAI-Rad Companion\nBrain MR\n(K193290)","Reference Device 1 -\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Reference Device 2 -\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Subject Device\nCoLumbo","Remark/Discussion"],"rows":[["","Predicate Device -\nAI-Rad Companion\nBrain MR\n(K193290)","Reference Device 1 -\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Reference Device 2 -\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Subject Device\nCoLumbo","Remark/Discussion"],["Intended User","Radiologist","Radiologists &\nPhysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice","Radiologists &\nPhysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice","Radiologist and neuro-\nand spine-surgeons","Highly similar"],["Intended Patient\nPopulation","The intended patient\ntarget group consists\nof patients of age 2\nyears or higher. In\nthis age range the\nbrain segmentation\nalgorithm\nworks properly.","The intended patient\npopulation is not\nsubject to any\nrestrictions.\nAutomation support\nrequires images of\npatients of 22 years\nand older.","The intended patient\npopulation is not\nsubject to any\nrestrictions.\nAutomation support\nrequires images of\npatients of 22 years\nand older.","The intended patient\npopulation is not subject\nto any restrictions.\nAutomation support\nrequires images of\npatients of 18 years and\nolder, not pregnant,\nwithout post-operational\ncomplications, scoliosis,\ntumors, infections,\nfractures.","Similar"],["Supported Body\nPart","Brain","Thorax","Thorax (including\nthoracic spine)","Lumbar Spine","Similar to Reference\nDevices;\nDifferent from Primary\nDevice"],["Segmentation","Yes\nSegmentation and\nquantitative analysis","Yes\nSegmentation and\nquantitative analysis","Yes\nSegmentation of\nvertebras","Yes\nSegmentation and\nquantitative analysis","Same"],["Measurement","Yes\nQuantitative\ncomparison of\nstructure with\nnormative data or\nuser-set thresholds","Yes\nVolume\nmeasurement of the\nheart, total calcium\nvolume in the\ncoronary arteries,","Yes\nMeasure Hounsfield\nvalues within the\nvertebras","Yes\nQuantitative comparison\nof structure with\nnormative data or user-set\nthresholds","Same"]],"caption_candidate":"Table 8.1 – Comparison of Technological Characteristics with Predicate/Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p8-t0","doc_id":"K220497","page_num":8,"bbox":[72.24,72.24,729.0,518.52],"n_rows":7,"n_cols":6,"columns":["","Predicate Device -\nAI-Rad Companion\nBrain MR\n(K193290)","Reference Device 1 -\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Reference Device 2 -\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Subject Device\nCoLumbo","Remark/Discussion"],"rows":[["","Predicate Device -\nAI-Rad Companion\nBrain MR\n(K193290)","Reference Device 1 -\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Reference Device 2 -\nAI-Rad Companion\n(Musculoskeletal)\n(K193267)","Subject Device\nCoLumbo","Remark/Discussion"],["","","maximum diameters\nof the aorta at typical\nlandmarks","","",""],["Threshold-Based\nOut-of-Range\nMeasurements","Yes\nQuantitative\ncomparison of\nstructure with\nnormative data or\nuser-set thresholds","Yes\nThreshold-based\nhighlighting of\nfindings.\nClassify each finding\n(e.g., enlarged\ndiameters) by\ncomparing\nmeasurements\nagainst user-set\nthresholds","Yes\nLabeling of vertebras\nbased on the\nindividual heights of\nthe vertebras and\nwhether they\ncritically differ from\ntheir direct neighbors","Yes\nQuantitative comparison\nof structure with\nnormative data or user-set\nthresholds","Similar"],["Reporting","Yes\nExportation of results\nwith the findings for\nfurther reporting","Yes\nExportation of results\nwith the findings for\nfurther reporting","Yes\nExportation of results\nwith the findings for\nfurther reporting","Yes\nExportation of results with\nthe measurements for\nfurther reporting","Same\nNone of the reports are\nto be used as final\nreports. Trained\nradiologist or neuro-\nand spine-surgeons\nneed to review, edit and\napprove the final report"],["SaMD","Yes","Yes","Yes","Yes","Same"],["Algorithm","(no information)","3D Deep Image‐to‐\nImage Network","3D Deep Image‐to‐\nImage Network","Deep Convolutional\nImage-to-Image Neural\nNetwork","Similar"],["Supported\nModality","MR","CT","CT","MR","Same as Primary\nPredicate Device 1;\nSimilar to Reference\nDevices"]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcar","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p9-t0","doc_id":"K220497","page_num":9,"bbox":[86.18,360.96,543.58,565.56],"n_rows":7,"n_cols":4,"columns":["","Recognition","","Standard"],"rows":[["","Recognition","","Standard"],["","#","",""],["13-79","","","IEC 62304:2006/AMD 1:2015 Medical device software — Software life cycle\nprocesses — Amendment 1"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical\ndevices"],["5-129","","","IEC 62366-1:2015+AMD1:2020 Medical devices — Part 1: Application of usability\nengineering to medical devices"],["5-117","","","ISO 15223-1:2016 Medical devices — Symbols to be used with medical device\nlabels, labelling and information to be supplied — Part 1: General requirements"],["12-300","","","NEMA PS 3.1 - 3.20 (2016) Digital Imaging and Communications in Medicine\n(DICOM) Set"]],"caption_candidate":"Table 8.2 - Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p10-t0","doc_id":"K220497","page_num":10,"bbox":[90.12,375.84,539.84,533.64],"n_rows":12,"n_cols":3,"columns":["","Number of Subjects","Percent of Total"],"rows":[["","Number of Subjects","Percent of Total"],["Total Number of Subjects","101","100%"],["Gender – Male","53","52.5%"],["Gender - Female","48","47.5%"],["Age – 18 through 21","3","3.0%"],["Age – 22 through 50","74","73.3%"],["Age – 51 and above","24","23.8%"],["Racial – Caucasian","83","82.2%"],["Racial – Black/African American","9","8.9%"],["Racial – Hispanic","3","3.0%"],["Racial – American Indian","3","3.0%"],["Racial – Others","3","3.0%"]],"caption_candidate":"Study Subjects:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p10-t1","doc_id":"K220497","page_num":10,"bbox":[90.12,626.4,539.84,717.96],"n_rows":6,"n_cols":3,"columns":["Manufacturer","Number of MRI Exams\nCollected","Percent of Total"],"rows":[["Manufacturer","Number of MRI Exams\nCollected","Percent of Total"],["Toshiba (1.5T & 3.0T)","65","64.4%"],["Siemens (1.5T)","17","16.8%"],["Philips (1.5T)","1","1.0%"],["Hitachi (1.5T)","1","1.0%"],["GE (1.5T)","17","16.8%"]],"caption_candidate":"one axial and sagittal T2 series.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p11-t0","doc_id":"K220497","page_num":11,"bbox":[90.12,334.92,539.78,400.2],"n_rows":4,"n_cols":4,"columns":["Measurement","Mean Absolute\nError (MAE)","95% Confidence Interval (CI)","MAE\nLimit"],"rows":[["Measurement","Mean Absolute\nError (MAE)","95% Confidence Interval (CI)","MAE\nLimit"],["Dural Sac Area (Axial)","14.8 mm2","12.4 - 17.3 mm2","20 mm2"],["Lordotic Angle (Sagittal)","2.6°","1.9 - 3.3°","6°"],["Listhesis/AP Slip (Sagittal)","0.9 mm","0.8 - 1.1 mm","2 mm"]],"caption_candidate":"Primary end point results: all primary endpoints were met.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p11-t1","doc_id":"K220497","page_num":11,"bbox":[90.12,528.24,539.78,714.48],"n_rows":8,"n_cols":4,"columns":["Measurement","Mean Absolute\nError (MAE)","95% Confidence Interval (CI)","MAE\nLimit"],"rows":[["Measurement","Mean Absolute\nError (MAE)","95% Confidence Interval (CI)","MAE\nLimit"],["Disc Material Outside\nIV Space (Axial)","1.4 mm","1.1 - 1.6 mm","2 mm"],["Disc Material\nMigration (Sagittal)","1.2 mm","1.0 - 1.4 mm","2 mm"],["Disc Material Bulge\n(Axial)","1.0 mm","0.8 - 1.2 mm","2 mm"],["Dural Sac AP\nDiameter (Axial)","1.0 mm","0.8 - 1.1 mm","2 mm"],["Intervertebral Angle\n(Sagittal)","2.2°","1.9 - 2.5°","6°"],["Anterior VB Height\n(Sagittal)","0.8 mm","0.7 - 0.9 mm","2 mm"],["Middle VB Height","0.8 mm","0.7 - 0.9 mm","2 mm"]],"caption_candidate":"Secondary endpoint results: all secondary endpoints on measurement and segmentation were met.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p12-t0","doc_id":"K220497","page_num":12,"bbox":[90.08,74.16,539.35,185.4],"n_rows":5,"n_cols":4,"columns":["(Sagittal)","","",""],"rows":[["(Sagittal)","","",""],["Posterior VB Height\n(Sagittal)","1.0 mm","0.9 – 1.2 mm","2 mm"],["Anterior Disc Height\n(Sagittal)","1.0 mm","0.7 – 1.0 mm","2 mm"],["Middle Disc Height\n(Sagittal)","0.8 mm","0.7 – 0.9 mm","2 mm"],["Posterior Disc Height\n(Sagittal)","1.1 mm","1.0 – 1.2 mm","2 mm"]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p12-t1","doc_id":"K220497","page_num":12,"bbox":[90.08,207.48,539.35,382.68],"n_rows":10,"n_cols":4,"columns":["Tissue Segmentation","Mean Dice\nCoefficient (MDC)","95% Confidence\nInterval (CI)","MDC\nLimit"],"rows":[["Tissue Segmentation","Mean Dice\nCoefficient (MDC)","95% Confidence\nInterval (CI)","MDC\nLimit"],["Disc/Vertebral Body (Axial)","0.97","0.96 - 0.97","0.8"],["Vertebral Arch and\nAdjacent Ligaments (Axial)","0.87","0.86 - 0.88","0.8"],["Dural Sac (Axial)","0.92","0.92 - 0.93","0.8"],["Nerve Roots (Axial)","0.75","0.72 - 0.78","0.6"],["Disc Material Outside\nIntervertebral Space (Axial)","0.76","0.72 - 0.80","0.6"],["Disc (Sagittal)","0.93","0.93 - 0.94","0.8"],["Vertebral Body (Sagittal)","0.95","0.94 - 0.95","0.8"],["Sacrum S1 (Sagittal)","0.93","0.92 - 0.94","0.8"],["Disc Mat. Outside IV Space\nand/or Bulging Part (Sagittal)","0.69","0.66 - 0.72","0.6"]],"caption_candidate":"(Sagittal)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p12-t2","doc_id":"K220497","page_num":12,"bbox":[90.08,489.27,539.35,654.6],"n_rows":8,"n_cols":22,"columns":["","Measurement","","","MAE","","","","","","","","","95% Confidence Intervals","","","","","","","","MAE\nLimit"],"rows":[["","Measurement","","","MAE","","","","","","","","","95% Confidence Intervals","","","","","","","","MAE\nLimit"],["","Type","","","Toshiba","","","Siemens","","","GE","","","Toshiba","","","Siemens","","","GE","",""],["Angular\nMeasurements","","","2.0°","","","2.3°","","","3.6°","","","1.8 - 2.3°","","","1.6° -\n3.0°","","","1.7° -\n5.6°","","","6°"],["Linear\nMeasurements","","","0.9 mm","","","0.9 mm","","","1.0 mm","","","0.9 - 1.0\nmm","","","0.8 - 1.0\nmm","","","0.9 - 1.1\nmm","","","2 mm"],["","Segmentation","","","MDC","","","","","","","","","95% Confidence Intervals","","","","","","","","MDC\nLimit"],["","Type","","","Toshiba","","","Siemens","","","GE","","","Toshiba","","","Siemens","","","GE","",""],["Compression-\nrelated Tissue\nSegmentations","","","0.73","","","0.69","","","0.76","","","0.71 -\n0.76","","","0.63 -\n0.75","","","0.71 -\n0.81","","","0.6"],["Other Tissue\nSegmentations","","","0.93","","","0.93","","","0.94","","","0.92 -\n0.93","","","0.92 -\n0.93","","","0.93 -\n0.95","","","0.8"]],"caption_candidate":"manufacturer:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p13-t0","doc_id":"K220497","page_num":13,"bbox":[90.03,74.28,537.07,215.04],"n_rows":7,"n_cols":11,"columns":["","","White","","","Non-White","","","White","Non-White",""],"rows":[["","","White","","","Non-White","","","White","Non-White",""],["Angular\nMeasurements","2.4°","","","2.3°","","","1.9 - 2.9°","","1.7 - 2.9°","6°"],["Linear Measurements","0.9 mm","","","1.1 mm","","","0.9 - 1.0 mm","","1.0 - 1.2 mm","2 mm"],["Segmentation Type","","MDC","","","MDC","","","95% Confidence Intervals","","MDC\nLimit"],["","","White","","","Non-White","","","White","Non-White",""],["Compression-related\nTissue Segmentations","0.73","","","0.72","","","0.71 - 0.75","","0.67 - 0.78","0.6"],["Other Tissue\nSegmentations","0.93","","","0.93","","","0.925 - 0.933","","0.92 - 0.94","0.8"]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p13-t1","doc_id":"K220497","page_num":13,"bbox":[95.61,258.93,537.07,437.28],"n_rows":8,"n_cols":7,"columns":["Measurement Type","MAE\nMale","MAE\nFemale","","95% Confidence\nIntervals","","MAE\nLimit"],"rows":[["Measurement Type","MAE\nMale","MAE\nFemale","","95% Confidence\nIntervals","","MAE\nLimit"],["","","","","Male","Female",""],["Angular\nMeasurements","2.3°","2.4°","1.7 - 3.1°","","2.1 - 2.7°","6°"],["Linear Measurements","0.8 mm","0.9 mm","0.9 - 1.0 mm","","0.9 - 1.0 mm","2 mm"],["Segmentation Type","MDC\nMale","MDC\nFemale","","95% Confidence\nIntervals","","MDC\nLimit"],["","","","","Male","Female",""],["Compression-related\nTissue Segmentations","0.75","0.71","0.72 - 0.78","","0.68 - 0.74","0.6"],["Other Tissue\nSegmentations","0.93","0.93","0.92 - 0.94","","0.92 - 0.93","0.8"]],"caption_candidate":"MAE for software measurements and MDC for software segmentations by gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p13-t2","doc_id":"K220497","page_num":13,"bbox":[90.03,494.88,537.07,712.68],"n_rows":14,"n_cols":15,"columns":["Tissue Segmentation Type\nor Measurement","","","Acceptance\nCriteria","","","Between","","","","","Standard\nDeviation","Number\nof\nSamples","Confidence\nInterval","Confidence"],"rows":[["Tissue Segmentation Type\nor Measurement","","","Acceptance\nCriteria","","","Between","","","","","Standard\nDeviation","Number\nof\nSamples","Confidence\nInterval","Confidence"],["","","","","","","18 and","","","","","","","","Interval"],["","","","","","","21 years","","","","","","","",""],["","","","","","","old","","","","","","","",""],["Angle-based Measurements","","","6°","","1.14°","","","","","","1.41°","6","(0.48 – 1.81°)",""],["Linear Measurements","","","2 mm","","0.83 mm","","","","","","1.06mm","36","(0.60 –\n1.05mm)",""],["Compression-related Tissue\nSegmentations","","","0.6","","0.76","","","","","","0.087","7","(0.70 – 0.83)",""],["Other Tissue Segmentations","","","0.8","","0.92","","","","","","0.039","18","(0.91 – 0.94)",""],["","Tissue Segmentation Type","","","Acceptance","","","","","Between 22 and\n50 years old","","","Confidence Interval","",""],["","or Measurement","","","Criteria","","","","","","","","","",""],["Angle-based Measurements","","","6°","","","","","2.43°","","","","(1.94 – 2.93°)","",""],["Linear Measurements","","","2 mm","","","","","0.95 mm","","","","(0.90 – 1.00mm)","",""],["Compression-related Tissue\nSegmentations","","","0.6","","","","","0.73","","","","(0.71 – 0.76)","",""],["Other Tissue Segmentations","","","0.8","","","","","0.93","","","","(0.926 – 0.934)","",""]],"caption_candidate":"aforementioned table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220497-p14-t0","doc_id":"K220497","page_num":14,"bbox":[90.02,74.28,539.98,162.36],"n_rows":6,"n_cols":10,"columns":["","Tissue Segmentation Type","","","Acceptance","","","51 years old and","","Confidence Interval"],"rows":[["","Tissue Segmentation Type","","","Acceptance","","","51 years old and","","Confidence Interval"],["","or Measurement","","","Criteria","","","above","",""],["Angle-based Measurements","","","6°","","","2.09°","","","(1.63 – 2.56°)"],["Linear Measurements","","","2 mm","","","0.97 mm","","","(0.87 – 1.06mm)"],["Compression-related Tissue\nSegmentations","","","0.6","","","0.72","","","(0.68 – 0.76)"],["Other Tissue Segmentations","","","0.8","","","0.93","","","(0.92 – 0.93)"]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p5-t0","doc_id":"K220499","page_num":5,"bbox":[49.57,467.95,553.43,721.34],"n_rows":4,"n_cols":3,"columns":["Parameter","K190072 - Predicate Device","Rapid PETN – Subject Device"],"rows":[["Parameter","K190072 - Predicate Device","Rapid PETN – Subject Device"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Intended Use/\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nnon-enhanced head CT and CTPA\nimages. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive findings of\nIntracranial Hemorrhage (ICH) and\nPulmonary Embolism (PE)\npathologies. For the PE pathology,\nthe software is only intended to be\nused on single-energy exams.","Rapid PE Triage and Notification (PETN)\nis a radiological computer aided triage and\nnotification software indicated for use in\nthe analysis of CTPA images. The device\nis intended to assist hospital networks and\ntrained clinicians in workflow triage by\nflagging and communication of suspected\npositive findings of central pulmonary\nembolism (PE) pathology in adults. The\nsoftware is only intended to be used on\nsingle-energy exams.\nRapid PETN uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a server or"]],"caption_candidate":"PETN that is the subject of this Traditional 510(k) submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p6-t0","doc_id":"K220499","page_num":6,"bbox":[49.58,53.47,553.42,689.51],"n_rows":11,"n_cols":3,"columns":["Parameter","K190072 - Predicate Device","Rapid PETN – Subject Device"],"rows":[["Parameter","K190072 - Predicate Device","Rapid PETN – Subject Device"],["","BriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on\ntheir professional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","standalone desktop application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to\nbe used as a diagnostic device.\nThe results of Rapid PETN are intended to\nbe used in conjunction with other patient\ninformation and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare. Rapid PETN is validated for use on\nGE, Siemens and Toshiba scanners."],["User","Radiologist","Radiologist, Clinician"],["Basic PACS\nFunctions","Software package which interfaces\nto a PACS or allows viewing within\nthe application","Same"],["Computer Platform","PC","Server or Workstation"],["Software","AI/ML","AI/ML"],["DICOM Compliance","Yes, using CT and CTPA","Yes, using CTPA"],["Segmentation","No, Device does not mark,\nannotate, or direct users’ attention\nto a specific location in the original\nimage","No, Device does not mark, annotate, or\ndirect users’ attention to a specific location\nin the original image"],["Preview Images","Presentation of a small,\ncompressed, black and white\npreview image that is labeled “Not\nfor diagnostic use”; The device\noperates in parallel with the\nstandard of care, which remains\nthe default option for all cases.","Presentation of a small, compressed, black\nand white preview image that is labeled “Not\nfor diagnostic use”; The device operates in\nparallel with the standard of care, which\nremains the default option for all cases."],["Alteration of\noriginal image","No","No"],["Removal of cases from\nworkflow queue","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t0","doc_id":"K220499","page_num":7,"bbox":[114.77,147.66,497.23,214.08],"n_rows":4,"n_cols":15,"columns":["","Table 1: Age Distribution for Development & Training","","","","","","","","","","","","",""],"rows":[["","Table 1: Age Distribution for Development & Training","","","","","","","","","","","","",""],["","PE status","","","Mean age","","","Median age","","","Min age","","","Max age",""],["Positive (N=300)","","","63","","","64","","","22","","","93","",""],["Negative (N=300)","","","51","","","51","","","17","","","89","",""]],"caption_candidate":"Specificity = 0.97. The development data included the following distributions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t1","doc_id":"K220499","page_num":7,"bbox":[148.52,234.48,463.46,297.84],"n_rows":4,"n_cols":12,"columns":["","Table 2: Gender Distribution for Development & Training","","","","","","","","","",""],"rows":[["","Table 2: Gender Distribution for Development & Training","","","","","","","","","",""],["","PE status","","","Female","","","Male","","","Unknown",""],["Positive (N=300)","","","52%","","","47%","","","< 1%","",""],["Negative (N=300)","","","63%","","","37%","","","0%","",""]],"caption_candidate":"Negative (N=300) 51 51 17 89","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t2","doc_id":"K220499","page_num":7,"bbox":[84.05,318.24,527.95,381.72],"n_rows":4,"n_cols":18,"columns":["","Table 3: Scanner Distribution for Development & Training","","","","","","","","","","","","","","","",""],"rows":[["","Table 3: Scanner Distribution for Development & Training","","","","","","","","","","","","","","","",""],["","PE status","","","GE","","","Siemens","","","Philips","","","Toshiba","","","Unknown",""],["Positive (N=300)","","","39%","","","22%","","","13%","","","24%","","","< 2%","",""],["Negative (N=300)","","","72%","","","9%","","","< 1%","","","19%","","","0%","",""]],"caption_candidate":"Negative (N=300) 63% 37% 0%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t3","doc_id":"K220499","page_num":7,"bbox":[114.77,427.92,497.23,474.96],"n_rows":3,"n_cols":15,"columns":["","Table 4: Age Distribution for Development Validation","","","","","","","","","","","","",""],"rows":[["","Table 4: Age Distribution for Development Validation","","","","","","","","","","","","",""],["","PE status","","","Mean age","","","Median age","","","Min age","","","Max age",""],["Negative (N=276)","","","56","","","58","","","19","","","91","",""]],"caption_candidate":"model. The data included the following distributions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t4","doc_id":"K220499","page_num":7,"bbox":[148.52,495.36,463.46,542.4],"n_rows":3,"n_cols":12,"columns":["","Table 5: Gender Distribution for Development Validation","","","","","","","","","",""],"rows":[["","Table 5: Gender Distribution for Development Validation","","","","","","","","","",""],["","PE status","","","Female","","","Male","","","Unknown",""],["Negative (N=276)","","","55%","","","45%","","","0%","",""]],"caption_candidate":"Negative (N=276) 56 58 19 91","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p7-t5","doc_id":"K220499","page_num":7,"bbox":[84.05,562.8,527.95,609.84],"n_rows":3,"n_cols":18,"columns":["","Table 6: Scanner Distribution for Development Validation","","","","","","","","","","","","","","","",""],"rows":[["","Table 6: Scanner Distribution for Development Validation","","","","","","","","","","","","","","","",""],["","PE status","","","GE","","","Siemens","","","Philips","","","Toshiba","","","Unknown",""],["Negative (N=276)","","","25%","","","4%","","","0%","","","72%","","","0%","",""]],"caption_candidate":"Negative (N=276) 55% 45% 0%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p8-t0","doc_id":"K220499","page_num":8,"bbox":[107.1,476.51,504.56,504.02],"n_rows":4,"n_cols":5,"columns":["Gender","","","Lower 95%","Upper 95%"],"rows":[["Gender","","","Lower 95%","Upper 95%"],["","Measure","Estimate","",""],["","","","CI","CI"],["","","","",""]],"caption_candidate":"Table 1: Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p8-t1","doc_id":"K220499","page_num":8,"bbox":[70.05,595.06,543.56,622.58],"n_rows":4,"n_cols":6,"columns":["","","N","","Lower 95%","Upper 95%"],"rows":[["","","N","","Lower 95%","Upper 95%"],["Age","Measure","","Estimate","",""],["","","","","CI","CI"],["","","","","",""]],"caption_candidate":"Table 2: Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p9-t0","doc_id":"K220499","page_num":9,"bbox":[68.1,52.9,543.56,80.42],"n_rows":2,"n_cols":6,"columns":["Age","Measure","N","Estimate","Lower 95%\nCI","Upper 95%"],"rows":[["Age","Measure","N","Estimate","Lower 95%\nCI","Upper 95%"],["","","","","","CI"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K220499-p9-t2","doc_id":"K220499","page_num":9,"bbox":[78.0,129.6,549.6,245.64],"n_rows":5,"n_cols":6,"columns":["Mfr","Measure","N","Estimat","Lower 95%","Upper 95%"],"rows":[["Mfr","Measure","N","Estimat","Lower 95%","Upper 95%"],["","","","e","CI","CI"],["","Sensitivity\nSpecificity","41\n51","0.976\n0.882","0.874\n0.766",""],["","Sensitivity\nSpecificity","21\n58","0.952\n0.966","0.773\n0.883",""],["","Sensitivity\nSpecificity","16\n43","0.938\n0.860","0.717\n0.727",""]],"caption_candidate":"Table 3: Scanner Brand","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p9-t3","doc_id":"K220499","page_num":9,"bbox":[68.1,270.82,543.56,298.46],"n_rows":4,"n_cols":6,"columns":["Slice Thickness","Measure","","Estimate","Lower 95%\nCI","Upper 95%"],"rows":[["Slice Thickness","Measure","","Estimate","Lower 95%\nCI","Upper 95%"],["","","N","","",""],["","","","","","CI"],["","","","","",""]],"caption_candidate":"Table 4: Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p9-t4","doc_id":"K220499","page_num":9,"bbox":[68.1,383.38,543.56,410.9],"n_rows":4,"n_cols":6,"columns":["Rows","Measure","","Estimate","Lower 95%\nCI","Upper 95%"],"rows":[["Rows","Measure","","Estimate","Lower 95%\nCI","Upper 95%"],["","","N","","",""],["","","","","","CI"],["","","","","",""]],"caption_candidate":"Table 5: Detector Rows","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p9-t5","doc_id":"K220499","page_num":9,"bbox":[101.34,683.64,510.66,713.88],"n_rows":2,"n_cols":4,"columns":["Manufacturer","Reconstruction Method","N","% of Total"],"rows":[["Manufacturer","Reconstruction Method","N","% of Total"],["","STANDARD","84",""]],"caption_candidate":"Table 6: Scanner Mix w/Convolution Kernel Type","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220499-p10-t0","doc_id":"K220499","page_num":10,"bbox":[101.34,52.92,510.66,591.48],"n_rows":35,"n_cols":4,"columns":["Manufacturer","Reconstruction Method","N","% of Total"],"rows":[["Manufacturer","Reconstruction Method","N","% of Total"],["","FC08","2",""],["","SOFT","1",""],["","B40s","1",""],["","B","1",""],["","['Br38f', '2']","1",""],["","Missing","2",""],["","['Br38f', '2']","14",""],["","Tr20f","14",""],["","['Br40d', '3']","4",""],["","Br36f","3",""],["","FC08","3",""],["","STANDARD","2",""],["","['Br40d', '2']","2",""],["","['Bv36d', '3']","2",""],["","B31s","2",""],["","B26s","1",""],["","B30f","1",""],["","B40s","1",""],["","B70s","1",""],["","B","1",""],["","['Bf37f', '3']","1",""],["","['Br36f', '3']","1",""],["","['Br38f', '3']","1",""],["","Missing","7",""],["","FC08","54",""],["","FC14","11",""],["","FC02","2",""],["","FC18","2",""],["","STANDARD","1",""],["","C","1",""],["","B","1",""],["","Missing","6",""],["","Other","75",""],["","All","306",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220575-p6-t0","doc_id":"K220575","page_num":6,"bbox":[72.55,71.28,485.04,773.76],"n_rows":13,"n_cols":6,"columns":["","MAGNETOM Free.Max","","","MAGNETOM Free.Star",""],"rows":[["","MAGNETOM Free.Max","","","MAGNETOM Free.Star",""],["","software version syngo MR XA50A","","","",""],["New/Modified Hardware","","","","",""],["Common for both subject devices:","","","","",""],["• Scanner User Interface (SUI): introduce option to have two SUI set on both\nsides of the scanner, while there is only one set available on the left hand\nside as the standard configuration for the predicate device MAGNETOM\nFree.Max with software version syngo MR XA40A (K210611); Swap the\norientation of patient pictogram on Select&GO is supported syngo MR\nXA50A.\n• myExam 3D Camera: auto registration with detection of patient height,\nweight and orientation are supported in the subject device software version\nsyngo MR XA50A. The hardware remains unchanged as cleared with\nK210611 on July 1, 2021.\n• New Patient Video: A new patient video with 1920×1080 pixels is\nintroduced.","","","","",""],["Applicable to the following subject device(s)","","","","",""],["","MAGNETOM Free.Max","","","MAGNETOM Free.Star",""],["• New Local Coils","","","","",""],["Contour M Coil","","","Contour M Coil","",""],["• New Patient table –\nHigh-load patient table: a new\nfixed patient table with vertical\nmovement for heavy load patient is\nintroduced.","","","N/A","",""],["Software Features","","","","",""],["Common for both subject devices:","","","","",""],["New Software Platform/Workflow\nmyExam Autopilot is extended the supporting body region to shoulder:\n• myExam Shoulder Autopilot: it helps users to automate a shoulder\nexamination.\nMigrated Software feature\n• EP2D_FID: Single-shot FID EPI pulse sequence type optimized for\nperfusion-imaging in the brain.\n• Inline Perfusion: Automatic real-time calculation of parameter maps with\nInline technology based on image data acquired with the ep2d_fid pulse\nsequence type.\n• Access-i: Provides an interface to enable the connection of a 3rd party\nworkstation to the MR syngo Acquisition Workplace via a network router\nand secure local network connection.\nModified Software Platform/Workflow\nModify in Scan assistance: Modified guidance of off-center imaging is provided\nto users who encounter the scan suspension by too off-centered shim volume.","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220575-p7-t0","doc_id":"K220575","page_num":7,"bbox":[72.72,150.0,502.95,264.3],"n_rows":8,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Free.Max\nwith syngo MR XA40A","K210611,\ncleared on July 1, 2021","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["","FDA Clearance Number","Product",""],["Reference Device","","","Manufacturer"],["","and Date","Code",""],["","","",""],["MAGNETOM Sola with\nsyngo MR XA20A","K192496, cleared on\nFebruary 28, 2020","LNH,\nLNI,\nMOS","Siemens Healthcare GmbH"]],"caption_candidate":"features from the following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220575-p8-t0","doc_id":"K220575","page_num":8,"bbox":[72.65,330.27,503.53,759.66],"n_rows":13,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognition","Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/\nEMC)","C1:2009/(R)2012 and\nA2:2010/(R)2012 (Consolidated\nText) Medical electrical\nequipment - Part 1: General\nrequirements for basic safety\nand essential performance (IEC\n60601-1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012","ANSI AAMI"],["19-8","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2, Ed.\n4.0:2014","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-125","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third Edition\n2 019-12","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1:2015","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","62304:2006/A1:201\n6","ANSI AAMI\nIEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"]],"caption_candidate":"NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220575-p9-t0","doc_id":"K220575","page_num":9,"bbox":[72.48,71.1,503.76,222.12],"n_rows":3,"n_cols":5,"columns":["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"],"rows":[["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20\n(2016)","NEMA"],["2-258","Biocompati\nbility","biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process\n(Biocompatibility)","10993-1:2018","AAMI\nANSI\nISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220589-p6-t0","doc_id":"K220589","page_num":6,"bbox":[109.82,363.61,540.07,410.46],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA31A","K203443,\ncleared March 31, 2021","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220589-p6-t1","doc_id":"K220589","page_num":6,"bbox":[109.82,464.52,540.07,547.5],"n_rows":4,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Verio with\nsoftware syngo MR E11D","K181613,\ncleared November 6, 2018","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Skyrafit with\nsoftware syngo MR E11C-\nAP04","K173592,\ncleared February 13, 2018","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"software already cleared on the following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220589-p8-t0","doc_id":"K220589","page_num":8,"bbox":[109.71,190.25,540.08,608.04],"n_rows":13,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognitio","n Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/ EMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012\nand\nA2:2010/(R)2012\n(Consolidated Text)","ANSI AAMI"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/ RM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices\n[Including CORRIGENDUM 1\n(2016)]","62366-1 Edition 1.0\n2015-02","IEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20:2016","NEMA"]],"caption_candidate":"FDA recognized and international IEC, ISO and NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p4-t0","doc_id":"K220598","page_num":4,"bbox":[66.62,144.62,534.63,385.5],"n_rows":9,"n_cols":2,"columns":["Table 1 : Submitter’s Information",""],"rows":[["Table 1 : Submitter’s Information",""],["Submitter’s Name:","Kurt Sysock"],["Company:","Radformation, Inc."],["Address:","335 Madison Avenue, 4th Floor\nNew York, NY 10017"],["Contact Person:","Alan Nelson\nChief Science Officer, Radformation"],["Phone:","518-888-5727"],["Fax:","---------"],["Email:","anelson@radformation.com"],["Date of Summary Preparation","08/22/2022"]],"caption_candidate":"5.1. Submitter’s Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p4-t1","doc_id":"K220598","page_num":4,"bbox":[66.62,429.5,534.63,633.5],"n_rows":8,"n_cols":2,"columns":["Table 2 : Device Information",""],"rows":[["Table 2 : Device Information",""],["Trade Name:","AutoContour RADAC V2"],["Common Name:","Radiological Image Processing Software For Radiation\nTherapy"],["Classification Name:","Class II"],["Classification:","Medical image management and processing system"],["Regulation Number:","892.2050"],["Product Code:","QKB"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2. Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p6-t0","doc_id":"K220598","page_num":6,"bbox":[121.5,86.52,489.67,709.5],"n_rows":5,"n_cols":3,"columns":["Table 3: Technological Characteristics\nAutoContour RADAC V2 vs. AutoContour RADAC (K200323)","",""],"rows":[["Table 3: Technological Characteristics\nAutoContour RADAC V2 vs. AutoContour RADAC (K200323)","",""],["Characteristic","Subject Device: AutoContour\nRADAC V2","Predicate Device:\nAutoContour RADAC\n(K200323)"],["Design: Image\nregistration","Manualand Automatic Rigid\nregistration.Automatic\nDeformable Registration","Manual Rigid registration."],["Design:\nSupported\nmodalities","CTor MRinput for contouring\nor registration/fusion.\nPET/CTinput for\nregistration/fusion only. DICOM\nRTSTRUCT for output","CT input for contouring or\nmanual registration/fusion.\nMR,PET/CTinput for\nmanual registration/fusion\nonly. DICOM RTSTRUCT\nfor output"],["Regions and\nVolumes of\ninterest (ROI)","CTor MRinput for contouring of\nanatomical regions: Head and\nNeck, Thorax, Abdomen and\nPelvis.\nCT Models:\n● A_Aorta\n● A_Aorta_Asc\n● A_Aorta_Dsc\n● A_LAD\n● Bladder\n● Bone_Ilium_L\n● Bone_Ilium_R\n● Bone_Mandible\n● Bowel_Bag\n● BrachialPlex_L\n● BrachialPlex_R\n● Brain\n● Brainstem\n● Breast_L\n● Breast_R\n● Bronchus\n● Carina\n● CaudaEquina\n● Cavity_Oral\n● Cochlea_L\n● Cochlea_R\n● Ear_Internal_L\n● Ear_Internal_R\n● Esophagus\n● External\n● Eye_L\n● Eye_R\n● Femur_L\n● Femur_R\n● Femur_RTOG_L","CT input for contouring of\nanatomical regions: Head\nand Neck, Thorax,\nAbdomen and Pelvis.\nCT Models:\n● Bladder\n● Bone_Mandible\n● Brain\n● Brainstem\n● Bronchus\n● Bronchus_Main\n● Carina\n● Cavity_Oral\n● Cochlea_L\n● Cochlea_R\n● Esophagus\n● Eye_L\n● Eye_R\n● Femur_L\n● Femur_R\n● Glnd_Lacrimal_L\n● Glnd_Lacrimal_R\n● Glnd_Submand_L\n● Glnd_Submand_R\n● Heart\n● Kidney_L\n● Kidney_R\n● Lens_L\n● Lens_R\n● Liver\n● Lung_L\n● Lung_R\n● OpticNrv_L\n● OpticNrv_R\n● Parotid_L"]],"caption_candidate":"K220598","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p7-t0","doc_id":"K220598","page_num":7,"bbox":[225.75,79.35,442.78,709.3],"n_rows":61,"n_cols":4,"columns":["●","Femur_RTOG_R","●","Parotid_R"],"rows":[["●","Femur_RTOG_R","●","Parotid_R"],["●","Glnd_Lacrimal_L","●","Prostate"],["●","Glnd_Lacrimal_R","●","Rectum"],["●","Glnd_Submand_L","●","SpinalCord"],["●","Glnd_Submand_R","●","Stomach"],["●","Glnd_Thyroid","",""],["●","HDR_Cylinder","",""],["●","Heart","",""],["●","Humerus_L","",""],["●","Humerus_R","",""],["●","Kidney_L","",""],["●","Kidney_R","",""],["●","Kidney_Outer_L","",""],["●","Kidney_Outer_R","",""],["●","Larynx","",""],["●","Lens_L","",""],["●","Lens_R","",""],["●","Lips","",""],["●","LN_Ax_L","",""],["●","LN_Ax_R","",""],["●","LN_IMN_L","",""],["●","LN_IMN_R","",""],["●","LN_Neck_IA","",""],["●","LN_Neck_IB-V_L","",""],["●","LN_Neck_IB-V_R","",""],["●","LN_Neck_II_L","",""],["●","LN_Neck_II_R","",""],["●","LN_Neck_II-IV_L","",""],["●","LN_Neck_II-IV_R","",""],["●","LN_Neck_III_L","",""],["●","LN_Neck_III_R","",""],["●","LN_Neck_IV_L","",""],["●","LN_Neck_IV_R","",""],["●","LN_Neck_VIA","",""],["●","LN_Neck_VIIA_L","",""],["●","LN_Neck_VIIA_R","",""],["●","LN_Neck_VIIB_L","",""],["●","LN_Neck_VIIB_R","",""],["●","LN_Pelvics","",""],["●","LN_Sclav_L","",""],["●","LN_Sclav_R","",""],["●","Liver","",""],["●","Lung_L","",""],["●","Lung_R","",""],["●","Marrow_Ilium_L","",""],["●","Marrow_Ilium_R","",""],["●","Musc_Constrict","",""],["●","OpticChiasm","",""],["●","OpticNrv_L","",""],["●","OpticNrv_R","",""],["●","Parotid_L","",""],["●","Parotid_R","",""],["●","PenileBulb","",""],["●","Pituitary","",""],["●","Prostate","",""],["●","Rectum","",""],["●","Rib","",""],["●","SeminalVes","",""],["●","SpinalCanal","",""],["●","SpinalCord","",""],["●","Stomach","",""]],"caption_candidate":"● Femur_RTOG_R ● Parotid_R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K220598-p8-t0","doc_id":"K220598","page_num":8,"bbox":[121.5,72.5,489.5,404.5],"n_rows":2,"n_cols":3,"columns":["","● Trachea\n● V_Venacava_S\nMR Models:\n● OpticChiasm\n● OpticNrv_L\n● OpticNrv_R\n● Brainstem\n● Hippocampus_L\n● Hippocampus_R",""],"rows":[["","● Trachea\n● V_Venacava_S\nMR Models:\n● OpticChiasm\n● OpticNrv_L\n● OpticNrv_R\n● Brainstem\n● Hippocampus_L\n● Hippocampus_R",""],["Computer\nplatform &\noperating\nsystem","Windows based .NET front-end\napplication that also serves as\nagent Uploader supporting\nMicrosoft Windows 10 (64-bit)\nand Microsoft Windows Server\n2016.\nCloud-based Server based\nautomatic contouring application\ncompatible with Linux.\nWindows python-based\nautomatic contouring application\nsupporting Microsoft Windows\n10 (64-bit) and Microsoft\nWindows Server 2016.","Agent Uploader supporting\nMicrosoft Windows 10\n(64-bit) and Microsoft\nWindows Server 2016.\nCloud-based Server based\nautomatic contouring\napplication compatible with\nLinux.\nWeb application Server\nbased application\ncompatible with Linux with\nfrontend compatible with all\nmodern web browsers."]],"caption_candidate":"K220598","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p12-t0","doc_id":"K220598","page_num":12,"bbox":[83.37,202.86,529.33,703.5],"n_rows":25,"n_cols":7,"columns":["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],"rows":[["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],["A_Aorta","240","60","Large","0.91","0.03","0.86"],["A_Aorta_Asc","240","60","Large","0.90","0.03","0.85"],["A_Aorta_Dsc","240","60","Large","0.93","0.02","0.90"],["A_LAD","461","116","Small","0.57","0.13","0.36"],["Bladder","1000","372","Large","0.92","0.09","0.77"],["Bone_Ilium_L","120","31","Large","0.94","0.01","0.92"],["Bone_Ilium_R","120","31","Large","0.94","0.01","0.92"],["Bone_Mandible","230","58","Medium","0.90","0.03","0.85"],["Bowel_Bag","131","33","Large","0.93","0.04","0.86"],["BrachialPlex_L","78","20","Medium","0.73","0.08","0.60"],["BrachialPlex_R","78","20","Medium","0.73","0.08","0.60"],["Brain","1000","28","Large","0.96","0.01","0.94"],["Brainstem","236","60","Medium","0.90","0.02","0.87"],["Breast_L","462","116","Large","0.93","0.04","0.86"],["Breast_R","462","116","Large","0.93","0.04","0.86"],["Bronchus","200","50","Medium","0.73","0.09","0.58"],["Carina","2312","578","Medium","0.82","0.08","0.69"],["CaudaEquina","87","22","Medium","0.90","0.02","0.87"],["Cavity_Oral","532","133","Medium","0.83","0.1","0.67"],["Cochlea_L","106","26","Small","0.65","0.1","0.49"],["Cochlea_R","106","26","Small","0.65","0.1","0.49"],["Ear_Internal_L","1289","324","Small","0.64","0.21","0.29"],["Ear_Internal_R","1289","324","Small","0.64","0.21","0.29"],["Esophagus","1116","279","Medium","0.76","0.13","0.55"]],"caption_candidate":"and 0.61+/-0.14 respectively:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p13-t0","doc_id":"K220598","page_num":13,"bbox":[83.37,72.06,528.63,701.5],"n_rows":32,"n_cols":7,"columns":["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],"rows":[["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],["External","3173","826","Large","0.99","0.04","0.92"],["Eye_L","336","85","Medium","0.92","0.02","0.89"],["Eye_R","336","85","Medium","0.92","0.02","0.89"],["Femur_L","1315","330","Large","0.96","0.06","0.86"],["Femur_R","1315","330","Large","0.96","0.06","0.86"],["Femur_RTOG_L","1315","330","Large","0.96","0.06","0.86"],["Femur_RTOG_R","1315","330","Large","0.96","0.06","0.86"],["Glnd_Lacrimal_L","353","86","Small","0.54","0.18","0.24"],["Glnd_Lacrimal_R","353","86","Small","0.54","0.18","0.24"],["Glnd_Submand_L","814","43","Medium","0.82","0.15","0.57"],["Glnd_Submand_R","814","43","Medium","0.82","0.15","0.57"],["Glnd_Thyroid","169","43","Medium","0.79","0.06","0.69"],["HDR_Cylinder","15","4","Large","0.97","0.01","0.97"],["Heart","2060","515","Large","0.93","0.05","0.85"],["Humerus_L","451","114","Large","0.95","0.02","0.92"],["Humerus_R","451","114","Large","0.95","0.02","0.92"],["Kidney_L","1083","271","Medium","0.94","0.03","0.89"],["Kidney_R","1083","271","Medium","0.94","0.03","0.89"],["Kidney_Outer_L","590","148","Medium","0.93","0.05","0.85"],["Kidney_Outer_R","590","148","Medium","0.93","0.05","0.85"],["Larynx","172","43","Medium","0.85","0.05","0.77"],["Lens_L","1114","278","Small","0.66","0.14","0.43"],["Lens_R","1114","278","Small","0.66","0.14","0.43"],["Lips","432","110","Small","0.52","0.16","0.26"],["LN_Ax_L","437","110","Medium","0.83","0.07","0.71"],["LN_Ax_R","437","110","Medium","0.83","0.07","0.71"],["LN_IMN_L","390","97","Medium","0.68","0.07","0.56"],["LN_IMN_R","390","97","Medium","0.68","0.07","0.56"],["LN_Neck_IA","272","68","Medium","0.78","0.06","0.68"],["LN_Neck_IB-V_L","316","79","Medium","0.86","0.05","0.78"],["LN_Neck_IB-V_R","316","79","Medium","0.86","0.05","0.78"]],"caption_candidate":"K220598","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p14-t0","doc_id":"K220598","page_num":14,"bbox":[83.37,72.06,528.63,701.5],"n_rows":32,"n_cols":7,"columns":["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],"rows":[["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],["LN_Neck_II_L","271","68","Medium","0.84","0.04","0.77"],["LN_Neck_II_R","271","68","Medium","0.84","0.04","0.77"],["LN_Neck_II-IV_L","325","82","Medium","0.86","0.03","0.81"],["LN_Neck_II-IV_R","325","82","Medium","0.86","0.03","0.81"],["LN_Neck_III_L","328","83","Medium","0.80","0.09","0.65"],["LN_Neck_III_R","328","83","Medium","0.80","0.09","0.65"],["LN_Neck_IV_L","328","82","Medium","0.77","0.07","0.65"],["LN_Neck_IV_R","328","82","Medium","0.77","0.07","0.65"],["LN_Neck_VIA","262","66","Medium","0.79","0.07","0.67"],["LN_Neck_VIIA_L","272","69","Medium","0.71","0.07","0.59"],["LN_Neck_VIIA_R","272","69","Medium","0.71","0.07","0.59"],["LN_Neck_VIIB_L","332","84","Medium","0.79","0.06","0.69"],["LN_Neck_VIIB_R","332","84","Medium","0.79","0.06","0.69"],["LN_Pelvics","502","126","Medium","0.87","0.05","0.79"],["LN_Sclav_L","460","115","Medium","0.88","0.05","0.8"],["LN_Sclav_R","460","115","Medium","0.88","0.05","0.8"],["Liver","480","120","Large","0.96","0.02","0.93"],["Lung_L","3491","748","Large","0.97","0.02","0.94"],["Lung_R","3491","748","Large","0.97","0.02","0.94"],["Marrow_Ilium_L","121","31","Large","0.91","0.02","0.88"],["Marrow_Ilium_R","121","31","Large","0.91","0.02","0.88"],["Musc_Constrict","272","69","Medium","0.75","0.06","0.65"],["OpticChiasm","158","40","Small","0.63","0.07","0.51"],["OpticNrv_L","741","185","Small","0.51","0.18","0.21"],["OpticNrv_R","741","185","Small","0.51","0.18","0.21"],["Parotid_L","739","48","Medium","0.82","0.04","0.75"],["Parotid_R","739","48","Medium","0.82","0.04","0.75"],["PenileBulb","232","58","Small","0.76","0.09","0.61"],["Pituitary","201","41","Small","0.68","0.09","0.53"],["Prostate","708","177","Medium","0.86","0.04","0.79"],["Rectum","1436","359","Medium","0.88","0.05","0.8"]],"caption_candidate":"K220598","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p15-t0","doc_id":"K220598","page_num":15,"bbox":[83.37,72.06,529.55,262.5],"n_rows":8,"n_cols":7,"columns":["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],"rows":[["Structure","#\nTraining\nData Sets","# Test\nData Sets","Size","DSC\nMean","DSC STD","Lower\nBound 95%\nConfidence\nInterval"],["Rib","64","17","Large","0.87","0.02","0.84"],["SeminalVes","236","60","Medium","0.79","0.07","0.67"],["SpinalCanal","87","22","Large","0.90","0.02","0.87"],["SpinalCord","1000","24","Medium","0.68","0.09","0.53"],["Stomach","431","83","Large","0.88","0.07","0.76"],["Trachea","196","49","Medium","0.87","0.05","0.79"],["V_Venacava_S","162","41","Medium","0.81","0.06","0.71"]],"caption_candidate":"K220598","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p15-t1","doc_id":"K220598","page_num":15,"bbox":[108.0,287.0,540.0,707.0],"n_rows":30,"n_cols":5,"columns":["These DSC results were compared with state-of-the-art contouring results","","","",""],"rows":[["These DSC results were compared with state-of-the-art contouring results","","","",""],["published in the literature as well as to the Reference Device MIM Contour ProtégéAI","","","",""],["(K213976) and were found to be consistent with the state-of-the-art for those structures","","","",""],["which had such data available.","","","",""],["The test datasets were independent from that used for training and consisted of","","","",""],["20% of the number of training images sets used as input for the model. For CT structure","","","",""],["models there were an average of 700 training and 140 testing image sets. Datasets","","","",""],["used for testing were removed from the training dataset pool before model training","","","",""],["began, and used exclusively for testing. Among the patients used for CT testing 51.7%","","","",""],["were male and 48.3% female. Patient ages range 11-30 : 0.3%, 31-50 : 6.2%, 51-70 :","","","",""],["43.3%, 71-100 : 50.3%. Race 84.0% White, 12.8% Black or African American, 3.2%","","","",""],["Other.","CT testing data spanned across treatment subgroups most typically found in a","","",""],["radiation therapy treatment clinic with the most common diagnosis being cancers of the","","","",""],["Prostate (21%), Breast (21%), Lung (29%), Head and Neck (16%), Other (13%).","","CT","",""],["datasets used for testing were acquired using a Philips Big Bore CT simulator with the","","","",""],["majority of scans having an average slice thickness of 2mm, In-plane resolution between","","","",""],["1-1.2 mm, and acquisition parameters of 120kVp, 674+/-329 average mAs. Ground","","","",""],["truthing of each test data set were generated manually using consensus (NRG/RTOG)","","","",""],["guidelines as appropriate by three clinically experienced experts consisting of 2 radiation","","","",""],["therapy physicists and 1 radiation dosimetrist.","","","",""],["Sensitivity and specificity for each CT structure model was evaluated on 50","","","",""],["unique patients independent of the training data. 75 structure models had a sensitivity of","","","",""],["100%, 14 models had a sensitivity > 95%, 3 models had a sensitivity > 90%, and 1","","","",""],["model had a sensitivity > 85%.","","","",""],["For CT specificity, 29 structure models had a specificity of 100%, 14 models had","","","",""],["a specificity > 90%, 12 models had a specificity > 80%, and the remaining 38 models","","","",""],["ranged from 0 to 80%. Note that false positives generally occur when the structure is not","","","",""],["actually in the image, and in such cases this issue is mitigated by AutoContour’s","","","",""],["user-specified structure template system that filters structure results that are not selected","","","",""],["by the user.","","","",""]],"caption_candidate":"V_Venacava_S 162 41 Medium 0.81 0.06 0.71","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p16-t0","doc_id":"K220598","page_num":16,"bbox":[108.0,100.46,539.47,157.38],"n_rows":4,"n_cols":2,"columns":["cases from the",""],"rows":[["cases from the",""],["Bortfeld, T. (2021). Glioma Image Segmentation for Radiotherapy: RT targets, barriers to",""],["cancer spread, and organs at risk [Data set]. The Cancer Imaging Archive.",""],["https://doi.org/10.7937/TCIA.T905-ZQ20",")."]],"caption_candidate":"image sets. These training sets consisted primarily of glioblastoma and astrocytoma -","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p16-t1","doc_id":"K220598","page_num":16,"bbox":[133.5,376.77,478.29,548.55],"n_rows":7,"n_cols":6,"columns":["Structure","Size","Pass\nCriteria\n(DSC\nMean)","DSC\nMean","DSC\nSTD","Lower\nBound 95%\nConfidence\nInterval"],"rows":[["Structure","Size","Pass\nCriteria\n(DSC\nMean)","DSC\nMean","DSC\nSTD","Lower\nBound 95%\nConfidence\nInterval"],["Brainstem","Medium","0.65","0.90","0.02","0.87"],["OpticChiasm","Small","0.50","0.53","0.11","0.35"],["OpticNrv_L","Small","0.50","0.64","0.08","0.51"],["OpticNrv_R","Small","0.50","0.64","0.08","0.51"],["Hippocampus_R","Medium","0.65","0.65","0.09","0.50"],["Hippocampus_L","Medium","0.65","0.65","0.09","0.50"]],"caption_candidate":"models a mean DSC of 0.67+/-0.08 was found across all structure models.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220598-p16-t2","doc_id":"K220598","page_num":16,"bbox":[72.0,574.0,539.47,706.0],"n_rows":9,"n_cols":2,"columns":["","Sensitivity and Specificity was evaluated on the 16 validation MR datasets that"],"rows":[["","Sensitivity and Specificity was evaluated on the 16 validation MR datasets that"],["","were not included in the training. All structure models had a sensitivity of 100% and a"],["","specificity of >85% in these test cases."],["","Limitations of AutoContour related to structure contouring performance and"],["","limitations of the training data are disclosed in the product labeling. AutoContour also"],["","mitigates risk of incorrect contours being propagated into a treatment plan through a"],["","review process that requires users to review every slice and approve the structure prior"],["","to being able to export it to a treatment planning system."],["",""]],"caption_candidate":"Hippocampus_L Medium 0.65 0.65 0.09 0.50","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p2-t0","doc_id":"K220624","page_num":2,"bbox":[257.72,430.78,570.36,527.38],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p4-t0","doc_id":"K220624","page_num":4,"bbox":[66.7,136.32,540.63,261.44],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","AI4MedImaging Medical Solutions S.A."],"rows":[["510(k) Sponsor","AI4MedImaging Medical Solutions S.A."],["Address","Rua do Parque Poente, lt 32\n4705-002 Sequeira, Braga Portugal"],["Correspondence Person","Rory A. Carrillo\nQuality and Regulatory Consultant\nCosm"],["Contact Information","Email: rory@cosmhq.com\nPhone: 562-533-7010"],["Date Prepared","June 17, 2022"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p4-t1","doc_id":"K220624","page_num":4,"bbox":[66.7,308.5,540.63,402.37],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","AI4CMR v1.0"],"rows":[["Proprietary Name","AI4CMR v1.0"],["Common Name","AI4CMR"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"2. Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p4-t2","doc_id":"K220624","page_num":4,"bbox":[66.7,449.42,540.63,546.67],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","Imbio RV/LV Software"],"rows":[["Proprietary Name","Imbio RV/LV Software"],["Premarket Notification","K203256"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p6-t0","doc_id":"K220624","page_num":6,"bbox":[72.14,75.33,540.33,171.25],"n_rows":6,"n_cols":3,"columns":["Metric","Unit","Accuracy"],"rows":[["Metric","Unit","Accuracy"],["Cardiac index2","L/(min m^2)","n/a1"],["Notes:","",""],["1These values are derived by performing simple mathematicaloperations and are derived from EDV, ESV, EF, and","",""],["Mass metrics.","",""],["2These values are only provided if the patient'sheight and weight are included in the DICOM data.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p6-t1","doc_id":"K220624","page_num":6,"bbox":[76.75,520.5,523.5,699.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV (K203256)"],"rows":[["","Subject Device\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV (K203256)"],["Intended Use","AI4CMR software is designed to\nreport cardiac function\nmeasurements (ventricle volumes,\nejection fraction, indices etc.) from\n1.5T and 3T magnetic resonance\n(MR) scanners. AI4CMR uses\nartificial intelligence to\nautomatically segment and\nquantify the different cardiac\nmeasurements. Its results are not\nintended to be used on a","The Imbio RV/LV Software device\nis designed to measure the\nmaximal diameters of the right and\nleft ventricles of the heart from a\nvolumetric CTPA acquisition and\nreport the ratio of those\nmeasurements. RV/LV analyzes\ncases using an artificial\nintelligence algorithm to identify\nthe location and measurements of\nthe ventricles. The RV/LV software"]],"caption_candidate":"6. Substantial Equivalence & Technical Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p7-t0","doc_id":"K220624","page_num":7,"bbox":[76.5,75.33,523.5,224.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV (K203256)"],"rows":[["","Subject Device\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV (K203256)"],["","stand-alone basis for clinical\ndecision-making.\nThe user incorporating AI4CMR\ninto their DICOM application of\nchoice is responsible for\nimplementing a user interface.","provides the user with annotated\nimages showing ventricular\nmeasurements. Its results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making or otherwise\npreclude clinical assessment of\nCTPA cases."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220624-p7-t1","doc_id":"K220624","page_num":7,"bbox":[72.25,253.42,540.25,529.5],"n_rows":10,"n_cols":4,"columns":["Feature/\nFunction","Subject Device:\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV\n(K203256)","Substantially\nEquivalent?"],"rows":[["Feature/\nFunction","Subject Device:\nAI4CMR v1.0","Predicate Device:\nImbio RV/LV\n(K203256)","Substantially\nEquivalent?"],["Indication for Use","See table above","See table above","Yes"],["Input Data\nRequirements","Cardiovascular images:\nmulti-phase,\nmulti-slice acquired from\nMRI scanners","Non-gated, CT Pulmonary\nAngiography images","Yes1"],["DICOM Compliant","Yes","Yes","Yes"],["LV Segmentation","Yes","Yes","Yes"],["RV Segmentation","Yes","Yes","Yes"],["Diameter Measurements","Yes","Yes","Yes"],["Fully Automated\nSegmentation","Yes","Yes","Yes"],["Interface","3rd party Viewer as a\nplug-in","Command line","Yes"],["Outputs","Report only","Report, DICOM\nSecondary Capture Series","Yes"]],"caption_candidate":"CTPA cases.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p6-t0","doc_id":"K220709","page_num":6,"bbox":[77.66,149.54,548.74,715.42],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of head\nCTA images. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication of\nsuspected positive findings of Large\nVessel Occlusion (LVO) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of head\nCTA images in adults or transitional\nadolescents aged 18 and older.\nThe device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication of\nsuspected positive findings of complete\nLarge Vessel Occlusion (LVO) - MCA-\nM1, PCA-P1, ACA-A1, ICA, Basilar;\nand Medium Vessel Occlusions\n(MeVO) - MCA-M2, MCA-proximal M3,\nPCA-P2, PCA-proximal P3, ACA-A2,\nACA-proximal A3, and Vertebral-V4.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with for cases with\nsuspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images."]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p7-t0","doc_id":"K220709","page_num":7,"bbox":[77.66,72.24,548.74,698.74],"n_rows":11,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],["","","Notified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of\ninterest","Head","Head"],["Data\nacquisition\nprotocol","Head CTA","Head CTA"],["Notification-\nonly\n(/notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria","Inclusion criteria\nHead CTA protocol with a 64-slice\n●\nscanner or higher.\nScans performed on adults/\n●\ntransitional adults ≥ 18 years of age.\nSlice thickness 0.5 mm – 1.0 mm.\n●\nExclusion Criteria\nAll scans that are technically\n●\ninadequate, including motion\nartifacts, severe metal artifacts,\nsuboptimal bolus timing or an\ninadequate field of view.","Inclusion criteria\nHead CTA protocol with a 64-slice\n●\nscanner or higher.\nScans performed on adults/\n●\ntransitional adults ≥ 18 years of age.\nSlice thickness 0.5 mm – 1.25 mm.\n●\nExclusion Criteria\nAll scans that are technically\n●\ninadequate, including motion\nartifacts, severe metal artifacts,\nsuboptimal bolus timing or an\ninadequate field of view."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- AHS module (image acquisition);\n- ACS module (image processing));","- AHS module (orchestrator, image\nacquisition);\n- ACS module (image processing));"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p8-t0","doc_id":"K220709","page_num":8,"bbox":[77.66,72.24,548.74,148.46],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K220709)"],["","- Aidoc Worklist application for\nworkflow integration (worklist and\nnon-diagnostic Image Viewer).","- Aidoc Desktop application for\nworkflow integration (feed and non-\ndiagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p9-t0","doc_id":"K220709","page_num":9,"bbox":[111.81,85.1,499.85,198.16],"n_rows":13,"n_cols":5,"columns":["Time -to-","Mean Estimate","95%","95%","Median"],"rows":[["Time -to-","Mean Estimate","95%","95%","Median"],["notification","","Lower CL","Upper CL",""],["","","","",""],["Predicate","3.80","3.60","4.00","3.8"],["","","","",""],["K203508Time-","","","",""],["","","","",""],["to-notification","","","",""],["BriefCase VO","2.23","2.22","2.23","2.03"],["","","","",""],["Time-to-","","","",""],["","","","",""],["notification","","","",""]],"caption_candidate":"Table 2. Time-to- Notification Comparison for BriefCase Devices (minutes)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p9-t1","doc_id":"K220709","page_num":9,"bbox":[111.81,398.25,499.85,431.6],"n_rows":2,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age (Years)","","64.8","","","17.1","","","18","","","65.0","","","90","","","342","",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p9-t2","doc_id":"K220709","page_num":9,"bbox":[80.8,474.19,531.36,630.49],"n_rows":12,"n_cols":9,"columns":["Ground","","","","","","","",""],"rows":[["Ground","","","","","","","",""],["Truth","Gender","","","","","","",""],["Results","","","","","","","",""],["","","","","","","","All",""],["","","","","","","","",""],["","","","","","","","",""],["","Male","","Female","","Other","","",""],["","","","","","","","",""],["","N","%","N","%","N","%","N","%"],["Positive","37","40.2%","54","58.7%","1","1.1%","92","100"],["Negative","108","43.2%","139","55.6%","3","1.2%","250","100"],["All","145","42.4%","193","56.4%","4","1.2%","342","100"]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220709-p10-t0","doc_id":"K220709","page_num":10,"bbox":[234.8,99.52,377.11,239.72],"n_rows":8,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["GE MEDICAL\nSYSTEMS","",""],["","124","36%"],["","",""],["TOSHIBA","72","21%"],["Philips","81","24%"],["SIEMENS","65","19%"],["Total","342","100.0%"]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220783-p7-t0","doc_id":"K220783","page_num":7,"bbox":[71.07,218.8,524.14,633.0],"n_rows":5,"n_cols":6,"columns":["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],"rows":[["","Feature","","","Description and Comparison of the Subject Device to the Predicate Device",""],["Patient Marking","","","General Description:\nTransmission of reference points with the offset details to a movable laser\nsystem for patient marking.\nModification:\n• Simplified workflow to place isocenters in the spine\n• Consistent user-configured default names for POIs throughout the\napplication","",""],["Contouring","","","General Description\nWith Contouring, the user can create, delete, and edit Volumes of Interest\n(VOIs).\nModification:\n• Tool to convert isodose lines from a DICOM RT dose file to contours\n• Minor usability improvement in the structure display in the image\nsegment","",""],["4D Features","","","General Description:\nThe subject device provides features to handle 4D image data, such as the\ndisplay of a cine loop of images acquired through gated CT.\nModification:\n• Contouring on 4D Image Data improved\n• Lobe-based Lung Ventilation implemented","",""],["Basic Feature of\nsyngo.via RT\nImage Suite","","","General Description:\nThe set provides basic feature of the subject device.\nModification:\nA software interface was added to provide additional advanced visualization\nand measurement tools to extend the subject device","",""]],"caption_candidate":"provided as Table 4 below for the software version SOMARIS/8 VB70:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220783-p9-t0","doc_id":"K220783","page_num":9,"bbox":[70.83,536.61,524.38,701.28],"n_rows":7,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2015-06 (Edition 1.1)","01/14/2019","AAMI, ANSI,\nIEC","",""],["5-40","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Second\nEdition 2007-03-01","06/27/2016","ISO","",""],["5-114","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015","12/23/2016","IEC","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p4-t0","doc_id":"K220813","page_num":4,"bbox":[79.6,512.13,509.48,571.5],"n_rows":2,"n_cols":5,"columns":["Regulation\nNumber","Device","Device\nClass","Product\nCode","Classification\nPanel"],"rows":[["Regulation\nNumber","Device","Device\nClass","Product\nCode","Classification\nPanel"],["892.2050","Medical image\nmanagement and\nprocessing system","Class II","QKB","Radiology"]],"caption_candidate":"Primary Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p5-t0","doc_id":"K220813","page_num":5,"bbox":[84.95,280.21,504.0,408.15],"n_rows":10,"n_cols":3,"columns":["","●","Multi-modal visualization and rigid- and deformable registration of anatomical and"],"rows":[["","●","Multi-modal visualization and rigid- and deformable registration of anatomical and"],["","functional images such as CT, MR, PET-CT, 4D-CT and CBCT",""],["","●","Display of fused and non-fused images to facilitate the comparison and delineation"],["","of image data by the user",""],["","●","Manual modification and semi-automatic generation of contours for the regions of"],["","interest",""],["","●","Automatic generation of contours for organs at risk and healthy lymph nodes, based"],["","on medical practices, on medical images such as CT and MR images.",""],["","●","Generation of pseudo-CT for supported anatomies"],["","",""]],"caption_candidate":"preparation of radiotherapy treatment:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p6-t0","doc_id":"K220813","page_num":6,"bbox":[66.72,176.36,765.67,525.27],"n_rows":8,"n_cols":9,"columns":["","General Information","","","","","","",""],"rows":[["","General Information","","","","","","",""],["Property","Proposed Device\nART-Plan v1.10.0","Primary\nPredicate\nART-Plan\nv1.6.1","Reference\ndevice\nContour\nProtégéAI","Reference\ndevice\nMIM 4.1","Reference\ndevice\nMRCAT Pelvis","Reference\ndevice\nMRCAT Brain","Reference\ndevice\nSyngo.via RT\nImage Suite","Comment"],["Common\nName","Radiological image\nprocessing software for\nradiation therapy","Radiological image\nprocessing software\nfor radiation therapy","Radiological\nImage\nProcessing\nSoftware For\nRadiation\nTherapy","System, image\nprocessing,\nradiological","System,\nPlanning,\nRadiation\nTherapy\nTreatment","System,\nPlanning,\nRadiation\nTherapy\nTreatment","System,\nPlanning,\nRadiation\nTherapy\nTreatment","N/A"],["Device\nManufacturer","TheraPanacea","TheraPanacea","MIM Software,\nInc","MIMvista Corp\n(now MIM\nSoftware Inc)","Philips Medical\nSystems","Philips Medical\nSystems","Siemens\nMedical\nSolutions USA,\nInc.","N/A"],["510k","N/A","K202700","K210632","K071964","K182888","K193109","K173635","N/A"],["Device\nClassification","II","II","II","II","II","II","II","N/A"],["Primary\nProduct Code","QKB","QKB","QKB","LLZ","MUJ","MUJ","MUJ","The primary product code\nis QKB “Radiological\nImage Processing\nSoftware For Radiation\nTherapy” as the software\nuses AI algorithms and is\nintended for radiation\ntherapy, just like the\nprimary predicate device"],["Secondary\nProduct Code","LLZ, MUJ","LLZ","-","-","-","-","LLZ","As secondary product\ncode:\n- LLZ (System, Image\nProcessing,\nRadiological) was\nincluded as the\nsoftware is used in"]],"caption_candidate":"General Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p7-t0","doc_id":"K220813","page_num":7,"bbox":[66.7,95.65,765.5,525.52],"n_rows":4,"n_cols":9,"columns":["","","","","","","","","image processing and\nsome predicates use it\nas primary or\nsecondary product\ncode;\n- MUJ (System,\nPlanning, Radiation\nTherapy Treatment)\nwas includes as it is a\nsoftware used in the\nplanning of\nradiotherapy\ntreatment and some of\nthe reference devices\nuse it as their primary\ncode"],"rows":[["","","","","","","","","image processing and\nsome predicates use it\nas primary or\nsecondary product\ncode;\n- MUJ (System,\nPlanning, Radiation\nTherapy Treatment)\nwas includes as it is a\nsoftware used in the\nplanning of\nradiotherapy\ntreatment and some of\nthe reference devices\nuse it as their primary\ncode"],["Target\nPopulation","Any patient type for\nwhom relevant modality\nscan image data is\navailable","Any patient type for\nwhom relevant\nmodality scan data is\navailable","Not stated","Not stated","Any patient with\nsoft tissue\ncancers in the\npelvic region for\nwhom\nradiotherapy\ntreatment has\nbeen planned","Any patient with\nprimary and\nmetastatic brain\ntumor for whom\nradiotherapy\ntreatment has\nbeen planned","Not stated","The proposed device has\nidentical target\npopulations to the primary\nand reference devices."],["Environment","Hospital","Hospital","Hospital","Hospital","Hospital","Hospital","Hospital","The proposed device\nand predicates have\nidentical target\nenvironments"],["Intended Use/\nIndication for\nUse","Intended Use\nART-Plan is a software\nfor multi-modal\nvisualization, contouring\nand processing of 3D\nimages of cancer\npatients for whom\nradiotherapy treatment\nhas been prescribed.\nIt allows the user to\nview, create and modify\ncontours for the regions\nof interest. It also allows\nto generate\nautomatically, and\nbased on medical","Intended Use\nART-Plan is a\nsoftware designed to\nassist the contouring\nprocess of the target\nanatomical regions\non 3D-images of\ncancer patients for\nwhom radiotherapy\ntreatment has been\nplanned.\nThe SmartFuse\nmodule allows the\nuser to register\ncombinations of\nanatomical and","Intended Use\nContour\nProtégéAI is an\naccessory to\nMIM software\nused for the\ncontouring of\nanatomical\nstructures in\nimaging data\nusing\nmachine-learnin\ng-based\nalgorithms\nautomatically.\nAppropriate","Intended Use\nMIM 4.1\n(SEASTAR)\nsoftware is\nintended for\ntrained medical\nprofessionals\nincluding, but not\nlimited to,\nradiologists,\noncologists,\nphysicians,\nmedical\ntechnologists,\ndosimetrists and\nphysicists.","Intended Use:\nMRCAT imaging\nis\nintended to\nprovide the\noperator with\ninformation of\ntissue\nproperties\nfor radiation\nattenuation\nestimation\npurposes\nin photon\nexternal beam\nradiotherapy","Intended Use:\nMRCAT imaging\nis intended to\nprovide the\noperator with\ninformation of\ntissue\nproperties for\nradiation\nattenuation\nestimation\npurposes in\nphoton external\nbeam\nradiotherapy","Intended use:\nNot available in\nthe summary\nIndication for\nuse:\nsyngo.via RT\nImage Suite is a\n3D and 4D\nimage\nvisualization,\nmultimodality\nmanipulation\nand\ncontouring tool\nthat helps the","The intended use and\nindications for use of\nthe proposed device,\nART-Plan v1.10.0 and\nthe primary predicate\nART-Plan v1.6.1 are\nsimilar as they are\nboth intended for\nmedical image\nregistration and\nsegmentation in the\ncontext of radiotherapy\ntreatment planning:\nthey allow multi-modal\nand mono-modal rigid"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p13-t0","doc_id":"K220813","page_num":13,"bbox":[66.67,349.25,756.17,522.44],"n_rows":3,"n_cols":9,"columns":["","System Information","","","","","","",""],"rows":[["","System Information","","","","","","",""],["Property","Proposed\nDevice\nART-Plan\nv1.10.0","Primary\nPredicate\nART-Plan\nv1.6.1","Reference\ndevice\nContour\nProtégéAI","Reference\ndevice\nMIM 4.1","Reference\ndevice\nMRCAT Pelvis","Reference\ndevice\nMRCAT Brain","Reference\ndevice\nSyngo.via RT\nImage Suite","Comment"],["Method of\nUse","Standalone\nsoftware\napplication\naccessed via\na compliant\nbrowser\n(Chrome or\nMozilla\nFirefox) on a\npersonal\ncomputer,\ntablet or","Standalone\nsoftware\napplication\naccessed via\na compliant\nbrowser\n(Chrome or\nMozilla\nFirefox) on a\npersonal\ncomputer,\ntablet or","Standalone\nsoftware\napplication","Standalone\nsoftware\npackage","Provided as a\nplug-in clinical\napplication to\nIngenia MR-RT. It\nis compatible with\nIngenia 1.5T and\n3.0T MR-RT,\nIngenia Ambition\n1.5T MR-RT and\nIngenia Elition\n3.0T MR-R. It runs\nparallel to image","Provided as a\nplug-in clinical\napplication to\nIngenia MR-RT. It\nis compatible with\nIngenia 1.5T and\n3.0T MR-RT,\nIngenia Ambition\n1.5T MR-RT and\nIngenia Elition\n3.0T MR-RT. It\nruns parallel to","syngo.via can be\nused as a\nstandalone device\nor together with a\nvariety of\nsyngo.via-based\nsoftware options,\nwhich are medical\ndevices in their\nown right.","The proposed device and\npredicates (especially the\nprimary predicate) have\nidentical methods of use"]],"caption_candidate":"System InformationComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p14-t0","doc_id":"K220813","page_num":14,"bbox":[66.7,95.65,756.5,500.27],"n_rows":4,"n_cols":9,"columns":["","phone (In\ncase of\nconnection to\nthe platform\nwith a screen\nof a phone or\na tablet, the\nuser must\nchoose the\noption for the\ndesktop site of\nhis\ncommunicatio\nn device. The\nplatform is\noptimally used\nwith 17 inches\nand up\nscreen.\nFacilitates\ndisplay and\nvisualization\nof data by\nuser.","phone (In\ncase of\nconnection to\nthe platform\nwith a screen\nof a phone or\na tablet, the\nuser must\nchoose the\noption for the\ndesktop site\nof his\ncommunicatio\nn device. The\nplatform is\noptimally used\nwith 17 inches\nand up\nscreen.\nFacilitates\ndisplay and\nvisualization of\ndata by user.","","","acquisition on the\nMR console,\nembedded\npost-processing\ngenerates MRCAT\nimages using: •\nAutomated\nsegmentation and\ntissue\nclassification •\nAutomated\nassignment of\nCT-based density\nvalues","image acquisition\non the MR\nconsole,\nembedded\npost-processing\ngenerates MRCAT\nimages using: •\nAutomated\nsegmentation and\ntissue\nclassification •\nAutomated\nassignment of\nCT-based density\nvalues","",""],"rows":[["","phone (In\ncase of\nconnection to\nthe platform\nwith a screen\nof a phone or\na tablet, the\nuser must\nchoose the\noption for the\ndesktop site of\nhis\ncommunicatio\nn device. The\nplatform is\noptimally used\nwith 17 inches\nand up\nscreen.\nFacilitates\ndisplay and\nvisualization\nof data by\nuser.","phone (In\ncase of\nconnection to\nthe platform\nwith a screen\nof a phone or\na tablet, the\nuser must\nchoose the\noption for the\ndesktop site\nof his\ncommunicatio\nn device. The\nplatform is\noptimally used\nwith 17 inches\nand up\nscreen.\nFacilitates\ndisplay and\nvisualization of\ndata by user.","","","acquisition on the\nMR console,\nembedded\npost-processing\ngenerates MRCAT\nimages using: •\nAutomated\nsegmentation and\ntissue\nclassification •\nAutomated\nassignment of\nCT-based density\nvalues","image acquisition\non the MR\nconsole,\nembedded\npost-processing\ngenerates MRCAT\nimages using: •\nAutomated\nsegmentation and\ntissue\nclassification •\nAutomated\nassignment of\nCT-based density\nvalues","",""],["Computer\nPlatform and\nOperating\nSystem","Full web\nplatform\nLaunch from\nGoogle\nChrome or\nMozilla Firefox\nAvailable on\nserver-based\napplication or\nCloud-based\ndeployment","Full web\nplatform\nLaunch from\nGoogle\nChrome or\nMozilla Firefox","Server-based\napplication\nsupporting\nLinux-based OS\n- and -\nLocal\ndeployment on\nWindows or Mac\nCloud-based\ndeployment","Windows\n2000/XP","As the density\ninformation is\ngenerated directly\non the MR\nconsole, the\nresulting data is\navailable at the\nconsole for\nimmediate review.","As the density\ninformation is\ngenerated directly\non the MR\nconsole, the\nresulting data is\navailable at the\nconsole for\nimmediate review.","This solution is\nalso available\ncloud-based,\nproviding\nscalability with\nflexible use\nmodels and cloud\ndeployment1","The proposed device and\npredicates are compatible with\nidentical operating systems."],["Data\nVisualization\n/ Graphical\nInterface","Yes","Yes","Yes","Yes","Yes","Yes","Yes","The proposed device and all\nthe predicates have a data\nvisualisation and graphical\ninterface"],["Synthetic CT","Generation of\nCT density","N/A","N/A","N/A","Generation of CT\ndensity image","Generation of CT\ndensity image","Generation of CT-","The proposed device and\nreference devices such as"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p16-t0","doc_id":"K220813","page_num":16,"bbox":[66.69,95.65,756.5,391.4],"n_rows":3,"n_cols":9,"columns":["","","","","","","","","Compared to reference\ndevices, the proposed device\nclaims less supported\nmodalities"],"rows":[["","","","","","","","","Compared to reference\ndevices, the proposed device\nclaims less supported\nmodalities"],["Data Export","Distribution of\nDICOM\ncompliant\nImages into\nother DICOM\ncompliant\nsystems.","Distribution of\nDICOM\ncompliant\nImages into\nother DICOM\ncompliant\nsystems.","As supported by\nACR/NEMA\nDICOM 3.0.","The system has\nthe ability to\nsend data to\nDICOM-ready\ndevices for\nimage storage,\nretrieval and\ntransmission.","MRCAT images\ncan be exported in\nDICOM format\nenabling the use\nas primary images\nin the treatment\nplanning systems","MRCAT images\ncan be exported in\nDICOM format\nenabling the use\nas primary images\nin the treatment\nplanning systems","DICOM, HL7 and\nIHE-RO standard\ncompliance","The proposed device and\npredicates (especially the\nprimary one) have identical\ndata export capabilities with\nDICOM format."],["Compatibility","Compatible\nwith data from\nany DICOM\ncompliant\nscanners for\nthe applicable\nmodalities.","Compatible\nwith data from\nany DICOM\ncompliant\nscanners for\nthe applicable\nmodalities.","supported by\nACR/NEMA\nDICOM 3.0","The software can\nreceive, transmit,\nstore, retrieve,\ndisplay, print,\nand process\nDICOM objects\nand medical\nimage modalities\nincluding, but not\nlimited to, CT,\nMRI, CR, DX,\nMG, US, SPECT,\nPET and XA as\nsupported by\nACR/NEMA\nDICOM 3.0.","MR console:\nCompatible with\nIngenia 1.5T and\n3.0T MR-RT,\nIngenia Ambition\n1.5T MR-RT and\nIngenia Elition\n3.0T MR-RT\nAfter export,\ncompatible with\nany DICOM\ncompliant\nscanners.","MR console:\nCompatible with\nIngenia 1.5T and\n3.0T MR-RT,\nIngenia Ambition\n1.5T MR-RT and\nIngenia Elition\n3.0T MR-RT\nAfter export,\ncompatible with\nany DICOM\ncompliant\nscanners.","Compatible with\nDICOM\nAutomatic send to\nTPS configuration","The proposed device and\npredicates (especially the\nprimary one) have identical\ncompatibility (DICOM format)"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p17-t0","doc_id":"K220813","page_num":17,"bbox":[66.7,130.36,754.5,496.4],"n_rows":4,"n_cols":9,"columns":["","","Technical Information","","","","","",""],"rows":[["","","Technical Information","","","","","",""],["Property","Proposed\nDevice\nART-Plan\nv1.10.0","Primary\nPredicate\nART-Plan\nv1.6.1","Reference\ndevice\nContour\nProtégéAI","Reference\ndevice\nMIM 4.1","Reference\ndevice\nMRCAT Pelvis","Reference\ndevice\nMRCAT Brain","Reference\ndevice\nSyngo.via RT\nImage Suite","Comment"],["Delineation\nMethod","AI","AI","AI","Atlas","N/A","N/A","Deep learning\nautocontouring\nfor organs at risk\n(incl. lymph\nnodes)2","The proposed device,\nprimary predicate and\nmost of the reference\ndevices share an AI\ndelineation method."],["Image\nregistration","Multi-modal\nand\nmono-modal.\nRigid and\ndeformable\nAutomatic and\nmanual\ninitialization\n(landmarks,\nfusion box,\nalignment).\nRegistration for\nthe purposes\nof replanning/\nrecontouring\nand AI-based\nautomatic\ncontouring.","Multi-modal and\nmono-modal.\nRigid and\ndeformable\nAutomatic and\nmanual\ninitialization\n(landmarks,\nfusion box,\nalignment).\nRegistration for\nthe purposes of\nreplanning/\nrecontouring\nand AI-based\nautomatic\ncontouring.","N/A","Registration, fusion\ndisplay, and review\nof medical images\nfor diagnosis,\ntreatment\nevaluation, and\ntreatment planning.","N/A","N/A","Image Fusion\nRigid and\nDeformable\nRegistration with\nregion-of interest\nbased\nregistration and\nmultiple\nregistrations per\nimage pair\nManual editing\nof registrations\nSave\nregistrations and\nsave deformed\nimages as\nreformatted\ndataset2\nContour warping\nand display of\nprior and new\nstructure set\nRegistration\nQuality Check\nwith spyglass,\ndeformation\nvector map,","Both the predicate device\nand ART-Plan offer\nmono-modal (CT-CT) and\nmulti-modal (CT/MR,\nCT/PET) rigid and\ndeformable registration.\nHowever, the proposed\ndevice supports 2\nadditional modalities:\n- CBCT (covered\nby the reference\ndeviceSyngo.via\nRT Image Suite)\n- 4D-CT (covered\nby the reference\ndeviceSyngo.via\nRT Image Suite\nBoth devices offer an\nautomatic solution for\nregistration and\nsemi-automatic registration\nby including manual\ninitialization tools in\naddition to automatic\ninitialization."]],"caption_candidate":"Technical Information Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p18-t0","doc_id":"K220813","page_num":18,"bbox":[66.67,95.65,754.5,508.4],"n_rows":2,"n_cols":9,"columns":["","","","","","","","magnitude color\nmap","Reference device such as\nSyngo.via RT Image Suite\noffers the same options as\nthe proposed device: rigid\nand deformable\nregistration."],"rows":[["","","","","","","","magnitude color\nmap","Reference device such as\nSyngo.via RT Image Suite\noffers the same options as\nthe proposed device: rigid\nand deformable\nregistration."],["Segmentation\nFeatures","Automatically\ndelineates\nOARs and\nhealthy lymph\nnodes\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n* head and\nneck (on CT\nimages)\n* thorax/breast\n(for\nmale/female\nand on CT\nimages)\n* abdomen (on\nCT images and\nMR images)\n* pelvis\nmale(on CT\nimages and\nMR images)\n* pelvis female\n(on CT\nimages)\n* brain (on CT\nimages and\nMR images)","Automatically\ndelineates\nOARs and\nhealthy lymph\nnodes (on any\nCT images)\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n* head and\nneck\n* thorax/breast\n(for\nmale/female)\n* abdomen\n* pelvis (for\nmale only)\n* brain.","Creation of\ncontours using\nmachine-learning\nalgorithms for\napplications\nincluding, but not\nlimited to,\nquantitative\nanalysis, aiding\nadaptive therapy,\ntransferring\ncontours to\nradiation therapy\ntreatment planning\nsystems, and\narchiving contours\nfor patient follow-up\nand management.\nSegmenting\nanatomical\nstructures across a\nvariety of CT\nanatomical\nlocations.\nAnd segmenting\nnormal structures\nof the prostate,\nseminal vesicles,\nand urethra within\nT2-weighted MR\nimages.","The software\nautomatically\ngenerates contours\nusing a deformable\nregistration\ntechnique which\nregisters\npre-contoured\npatients to target\npatients.\nRegistrations are\neither\nbetween a serial\npair of intra-patient\nvolumes or\nbetween a\npre-existing atlas of\ncontoured patients\nand a patient\nvolume. This\nprocess facilitates\ncontour creation or\nre-contouring for\nadaptive therapy.","N/A","N/A","Multimodality\ncontouring\nFreehand 2D,\n3D image-based\nSmart Freehand\nsegmentation, s\nContour on any\narbitrary plane\nincluding oblique\nplanes\ndeep learning\nautocontouring\nfor organs at risk\n(inclusive LNs)\nOne-click\nadaptive\ncontouring\nUser\nconfigurable\nOrgan\nTemplates\nMultiple\nstructure set\nsupport (1 per\nimage series)\nMolecular\nimaging data\nsuch as PET,\nthreshold-based\nand skin, gray\nvalue-based\nsegmentation1\n“CT-free”\ncontouring:\nnative PET or\nMR contouring","The proposed device and\nprimary predicate are\ncapable of automatically\ncontouring the\norgan-at-risk (OAR) and\nhealthy lymph nodes using\nAI (deep learning)\nalgorithm.\nThere is a difference in\nintended anatomies for CT\nimages as the proposed\ndevice also includes pelvis\nfemale.\nFor MR images, all\nanatomies included in the\nproposed device are also\nincluded in the primary\npredicate."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p19-t0","doc_id":"K220813","page_num":19,"bbox":[66.67,95.65,754.5,522.15],"n_rows":2,"n_cols":9,"columns":["","","","","","","","Parallel\ncontouring:\ncontouring\nperformed on\nany image is\nreflected on all\nother images\nVisualization of\npreviously drawn\nstructures on the\ncurrent image\nseries\nContour copy\nand warping\nbetween image\nseries2",""],"rows":[["","","","","","","","Parallel\ncontouring:\ncontouring\nperformed on\nany image is\nreflected on all\nother images\nVisualization of\npreviously drawn\nstructures on the\ncurrent image\nseries\nContour copy\nand warping\nbetween image\nseries2",""],["View\nManipulation\nand\nVolume\nRendering","Window and\nlevel, pan,\nzoom,\ncross-hairs,\nslice\nnavigation.\nMaximum,\naverage and\nminimum\nintensity\nprojection\n(MIP, AVG,\nMinIP),\ncolor\nrendering,\nmulti-planar\nreconstruction\n(MPR), fused\nviews,\ngallery views.","Window and\nlevel, pan,\nzoom,\ncross-hairs,\nslice\nnavigation.\nMaximum,\naverage and\nminimum\nintensity\nprojection (MIP,\nAVG, MinIP),\ncolor rendering,\nmulti-planar\nreconstruction\n(MPR), fused\nviews,\ngallery views.","Not stated","Not stated","N/A","N/A","Organ algebra\n(union,\nintersection,\nexclusion)\nSymmetric and\nasymmetric\nstructure growth\nor contraction\nSmart 2D/3D\nNudge, brush\nPan, scale,\nrotate contour\nGeometrical and\nsmart\nimage-based\ncontour\ninterpolation\nMulti-modality\nImage\nManipulation\nMultiplanar\nreconstruction\n(MPR) thin/thick,\nminimum\nintensity\nprojection (MIP),\nvolume","The proposed device has\nthe same tools as the\nprimary predicate."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p20-t0","doc_id":"K220813","page_num":20,"bbox":[66.69,95.65,754.5,432.52],"n_rows":3,"n_cols":9,"columns":["","","","","","","","rendering\ntechnique\n(VRT)2",""],"rows":[["","","","","","","","rendering\ntechnique\n(VRT)2",""],["Regions and\nVolumes\nof Interest\n(ROI)","AI Based\nautocontouring\n,\nRegistration\nbased contour\nprojection\n(re-contouring),\nManual ROI\nmanipulation\nand\ntransformation\n(margins,\nbooleans\noperators,\ninterpolation).","AI Based\nautocontouring,\nRegistration\nbased contour\nprojection\n(re-contouring),\nManual ROI\nmanipulation\nand\ntransformation\n(margins,\nbooleans\noperators,\ninterpolation).","AI Based\ncontouring, tools to\nquickly create,\ntransform, and\nmodify contours.","Atlas based\ncontouring, tools to\nquickly create,\ntransform, and\nmodify contours.","N/A","N/A","syngo.via RT\nImage Suite\nprovides\ndedicated tools,\nwhich help the\nmedical\nprofessional in\ncontouring\nand evaluating\nvolumes of\ninterest.\nFreehand and\nsemi-automatic\ncontouring of\nregions-of-intere\nst on any\norientation\nincluding\noblique2","Both the proposed device\nand the primary predicate\nallow AI automatic\ncontouring and manual\ncontouring"],["Region/volum\ne of\ninterest\nmeasurement\ns and\nsize\nmeasurement\ns","Intensity,\nHounsfield\nunits and SUV\nmeasurements\nSize\nmeasurements\ninclude 2D and\n3D\nmeasurements\n(number of\nslices, volume\nof a structure,\nstatic ruler)","Intensity,\nHounsfield units\nand SUV\nmeasurements\nSize\nmeasurements\ninclude 2D and\n3D\nmeasurements\n(number of\nslices, volume\nof a structure,\nstatic ruler)","N/A","Quantitative\nanalysis tools.","N/A","N/A","N/A","The proposed device\noffers the same kind of\nregion/volume of interest\nmeasurements and size\nmeasurements as the\nprimary predicate"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p22-t0","doc_id":"K220813","page_num":22,"bbox":[108.0,118.79,527.05,697.22],"n_rows":50,"n_cols":5,"columns":["Information about your training dataset:","","","",""],"rows":[["Information about your training dataset:","","","",""],["","","","",""],["","● Summary test statistics or other test results including acceptance criteria or","","",""],["","other information supporting the appropriateness of the characterised","","",""],["","performance","","",""],["","","","",""],["AcceptancecriteriaforperformanceofART-Planmoduleswereestablishedusingperformance","","","",""],["ranges extracted from benchmarkdevicesandalternativetechnologiesintheliterature.Foran","","","",""],["auto segmentation model to be judged acceptable, every organ included in the model must","","","",""],["pass at least one acceptance criterion with success across the different testings it has been","","","",""],["submitted to. These criteria are as follows:","","","",""],["","","","",""],["","","A. The Dice Similarity Coefficient(DSC)isequaltoorsuperiortotheacceptance","",""],["","","criteria set by the AAPM: DSC (mean)≥ 0.8.","",""],["","","","Or",""],["","","B. The Dice Similarity Coefficient (DSC) is equal to or superior to inter-expert","",""],["","","variability: DSC (mean)≥ 0.54 or DSC (mean) ≥ mean (DSC inter-expert) + 5%","",""],["","","","Or",""],["","","C. The clinicians’ s qualitative evaluation of the auto-segmentationisconsidered","",""],["","","acceptable for clinical use without modifications (A) or with minor","",""],["","","modifications / corrections (B) with a A+B % above or equal to 85%","",""],["","","considering the following scale:","",""],["","","","","A: the contour is acceptable for a clinical use without any modification"],["","","","","B: the contour would be acceptable for clinical use after minor"],["","","","","modifications/corrections"],["","","","","C: the contour requires major modifications (e.g.itwouldbefasterfor"],["","","","","the expert to manually delineate the structure)”"],["","","","",""],["For the synthetic-CT generation tool, the acceptance criteria are as follows:","","","",""],["","","","",""],["","","A. A median 2%/2mm gamma passing criteria of ≥95%","",""],["","","B. A median 3%/3mm gamma passing criteria of ≥99.0%","",""],["","","C. A mean dose deviation (pseudo-CT compared to standard CT) of ≤2% in","",""],["","","≥88% of patients","",""],["","","","",""],["","● Total number of individual patients images in the reported auto segmentation","","",""],["","tools and independence of test data and training data","","",""],["","","","",""],["Our training, validation andtestcohortsarebuiltfromreal-worldretrospectivedatawhichwere","","","",""],["initially used for treatmentofcancerpatients.Forthestructuresofagivenanatomyforagiven","","","",""],["modality (MR or CT),twonon-overlappingdatasetswereseparated:thetestpatients(number","","","",""],["selected based on thorough literature review and statistical power) and the train data. We","","","",""],["make sure that those sets are non-overlapping and further split the train cases into train and","","","",""],["validation sets and ensure enough train cases for the machine learning models to converge","","","",""],["and achieve good performances of the validation set.","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p23-t0","doc_id":"K220813","page_num":23,"bbox":[161.33,95.7,472.5,170.01],"n_rows":4,"n_cols":3,"columns":["","Sample Size","%"],"rows":[["","Sample Size","%"],["Training","299142","0.8"],["Validation","75018","0.2"],["Total","374160","1"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p24-t0","doc_id":"K220813","page_num":24,"bbox":[108.0,95.79,527.05,700.96],"n_rows":49,"n_cols":2,"columns":["In addition, automatic delineation of the device demonstrated equivalent performances",""],"rows":[["In addition, automatic delineation of the device demonstrated equivalent performances",""],["between non-US and US population.",""],["",""],["","● On the “truthing” and data collection process"],["",""],["The contouring guidelines followed to produce the contours were confirmed with the centers",""],["which provided the data. Our truthing process includes a mix of data created by different",""],["delineators (clinical experts) and assessmentofintervariability,groundtruthcontoursprovided",""],["by the centers and validated by a second expert of the center, and qualitative evaluationand",""],["validation of the contours. This processensuresthatthedatausedfortrainingandtestingcan",""],["be considered representative of the delineation practice across centers and following",""],["international guidelines.",""],["",""],["","● On clinical subgroups, confounders and equipment details"],["",""],["In general, confounding factors affecting health status present in the dataset could berelated",""],["to patient clinical variables such as age, gender, ethnicity, economicalandeducationallevels.",""],["As shown in “Demographic distribution including gender, age and ethnicity”, our datais",""],["representative of the demographic cancer distribution in terms ofgenderandage.Inaddition,",""],["our models when appropriate (i.e. for gender independent anatomies) are shared across",""],["gender removing any further bias and augmenting substantially training cohorts.",""],["",""],["Variables like ethnicity, economical and educational status that could be associated with",""],["obesity are further confounding factors that could impact global patient's anatomy and",""],["introduce bias in the performance of the obtained solution. To address this aspect, we have",""],["adopted a strategy that projects a patient's specific anatomy to common, multiple, differentin",""],["size, full-body female and male patient templates, allowing a direct harmonization of data",""],["resulting in potential removal of bias of anatomical diversity across ethnic, economical and",""],["educational groups. Please note that this information (ethnic group, educational/economical",""],["level, etc.) is often not available in the pseudo-anonymised data and therefore performing",""],["statistical tests and increasing thenumberofoperationsallowingtoseparatecorrelationsfrom",""],["causality is often unattainable.",""],["",""],["Regarding variables associated with treatment therapeutic and treatment implementation",""],["strategies;wecanimagineimagingdevicesandtreatmentdevicesbeingpotentialconfounding",""],["factors as differences exist among CT and MR scanners manufacturers that could potentially",""],["introduce bias. We have addressed this concern through a statistical analysis of the different",""],["imaging vendors in EU & USA towards the creation of a data training, validation and testing",""],["cohort that globally appropriately representsthemarketshareofthedifferentvendorsallowing",""],["generalization and removing hardware specific bias. In terms of treatment implementation, it",""],["should be noted that differentguidelinesexistanddependingonthetreatmentdevicedifferent",""],["therapeutic constraints and guidelines are applied. This is reflected in our database since",""],["different strategies and constraints are used depending on the choice of treatment (e.g",""],["external radiotherapy vs stereotactic treatment). Our solution, due to its concept of removing",""],["bias through projection to patient template anatomies as well asduetothecomponent-based",""],["approach that is abletoaggregatetrainingdataacrossimagingandtreatmentvendors,isable",""],["to address the maximum set of constraints. Therefore, we do not introduce any bias on the",""],["type oftreatmentthatwillbedelivered(supportinganytypeofclinicallyconventionallyadopted",""],["treatment from manufactures such as Varian, Elekta, Accuray, GE, Siemens, ViewRay & Zap",""]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p25-t0","doc_id":"K220813","page_num":25,"bbox":[85.5,395.74,519.25,687.5],"n_rows":5,"n_cols":3,"columns":["Test Name","Test Description/Results","Results"],"rows":[["Test Name","Test Description/Results","Results"],["Usability Report\n(V1.10.0)","This document is intended to document the\nusability test results for the ART-Plan v1.10.0 for\ncompliance with IEC 62366-1:2015+AMD1:2020 -\nMedical devices - Application of usability\nengineering to medical devices.","Passed"],["Usability file - ART-USR-09\n(V1.10.0)","The ART-Plan was assessed with regards to\nusability for compliance with each section of IEC\n62366","Passed"],["Usability - Testers qualification\n(V1.10.0)","This table shows that European medical physicists\nwho have participated in the evaluation have at\nleast an equivalent expertise level compared to a\njunior US medical physicist (MP), and\nresponsibilities in the radiotherapyclinicalworkflow\nare equivalent","N/A"],["Literature Review and\nPerformance Criteria\nExtraction Report for ART-Plan\n(V1.9.0 and V1.10.0)","A literature review is performed to establish\nacceptance criteria for performance of ART-Plan\nmodules using performance ranges observed from\nbenchmark devices and alternative technologies in\nthe literature. All measures of performance that\nwere established in this document were supported\nby clinical evidence. It was also demonstrated,\nfrom the clinical data, that ART-Plan has a clear","N/A"]],"caption_candidate":"The ART-Plan was evaluated for its safety and effectiveness based on the following testing:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p26-t0","doc_id":"K220813","page_num":26,"bbox":[85.5,95.5,519.5,699.5],"n_rows":6,"n_cols":3,"columns":["","clinical relevance in accordance with the clinical\nstate of the art.",""],"rows":[["","clinical relevance in accordance with the clinical\nstate of the art.",""],["ART-Plan performance testing\n- Overview\n(V1.6.1-V1.10.0)","The document summarises all performance tests\nthat have been performed since the last FDA\ncleared version (1.6.1). It also showswhichcriteria\nhave been met in each test for all modules of\nART-Plan. It demonstrates that all modules of\nART-Plan pass at least one performance\nacceptance criterion and hence are clinically\nacceptable for release.","Passed"],["Study Protocol and Report\nAnnotate Performances\nSummary (V1.9.0)","The testing demonstrated that Annotate provides\nacceptable contours for the concerned structures\non an image of a patient.","Passed"],["Abdo MRI auto-segmentation\nperformances according to\nAAPM requirements (V1.8.0)","Mean DSC of each organ was compared with the\ntolerance threshold of 0.8. After comparing the\ncontours of 3 different experts on the samepatient\nthe mean DSC was calculated, compared with the\nauto-segmentation and was observed to be in\nevery case superior. It is concluded that the\nauto-segmentation algorithm provides clinical\nacceptable contours.","Passed"],["Testing protocol/report - Brain\nMRI autosegmentation\nperformances according to\nAAPM requirements\nQualitative validation of\nautosegmentation\nperformances - Brain (V1.8.0)","In this test, some organs did not meet the\nacceptance criteria. However, the value of 0.80 is\nindicated by the AAPM as the “uncertainty of\ncontouring of the structure” which in fact can be\nsignificantly below 0.80 depending on the organ.\nThus, we also decided to evaluate in parallel the\nmodels with a qualitative evaluation of our\npredictions (see additional qualitative test below).\nAll organs except left and right cochlea passed at\nleast one of the acceptance criteria demonstrating\nthat the Annotate module provides acceptable\ncontours on MR brain structures. The MR brain\nmodel has been further improved, subjected to\nfurther testing, and, after providing acceptable\ncontours for all structures (incl. the cochlea),\nreleased in v1.10.0. (see Study Protocol and\nReport- Autosegmentation performances against\ninter-expert variability - Brain MR (V1.10.0)).","Passed"],["Qualitative validation of\nauto-segmentation\nperformances - Gyneco\n(V1.8.0)","The testing demonstrates that Annotate provides\nacceptable contours for a specific list of\ngynecological structures on a Female pelvis CT\nimage. Three testing methods are used: DICE\ncalculation, Inter-expert DICE calculation and","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p27-t0","doc_id":"K220813","page_num":27,"bbox":[85.5,95.5,519.5,688.5],"n_rows":9,"n_cols":3,"columns":["","qualitative Indicator. All structures passed at least\none of the acceptance criteria and were released.",""],"rows":[["","qualitative Indicator. All structures passed at least\none of the acceptance criteria and were released.",""],["Pelvis MRI auto-segmentation\ntool performances according to\nAAPM requirements (V1.8.0)","The testing demonstrates that the\nauto-segmentation algorithm for Pelvis MRIs\nprovides acceptable contours for the concerned\nstructures on an image of a patient.Allorgansmet\nat least one of the acceptance criteria and\ntherefore were considered acceptable.","Passed"],["Qualitative & Quantitative\nvalidation of fusion\nperformances (V1.9.0)","The study was developed to cover the major\nclinical use cases in which fusions are used in the\nradiotherapy workflow and split into as many\nsub-studies as clinical use cases of fusion in\nradiotherapy workflow. The results show that both\ntypes of fusion algorithms (Rigid & Deformable) in\nSmartFuse pass the performed tests, and provide\nvalid results for further clinical use in radiotherapy.","Passed"],["Study Protocol and Report for\nqualitative validation of fusion\nperformances for\ntCT_sCT_injected/PET\nmodality (V1.9.0)","The study evaluated the quality oftherigidandthe\ndeformable fusion algorithms of the SmartFuse\nmodule for the following cases:\n- CT injected image fuse towards CT image\n- CT-PET image fuse towards CT image.\nBoth types of fusion algorithms, rigid and\ndeformable, provided clinically acceptable results\nfor the desired clinical uses.","Passed"],["Study Protocol & Report for\nqualitative validation of ITV\ncalculation performances for\n4D_CT modality (V1.9.0)","The testing evaluated the quality of ITVcalculation\nalgorithm of the Annotate module in the case of\n4D-CT examinations. Acceptable results were\nreached for the evaluation of contours propagation.","Passed"],["Study Protocol and Report for\nvalidation of fusion\nperformances for tCT_sMR\nmodality (V1.9.0)","This testing evaluated the performances of the\nSmartFuse module for the clinical caseoffusionof\nan MRI towards a planning CT to aid in the\ndelineation. Acceptable results were reached for\nthis evaluation.","Passed"],["Study Protocol and Report for\nqualitative validation of fusion\nperformances for tMR_sCT\nmodality (V1.9.0)","This study evaluated the performances of the\nSmartFuse module for fusion of CTs towards\nplanning MRIs for the purpose of electron density\ntransfer. Acceptable results were reached for this\nevaluation.","Passed"],["Study Protocol and Report for\nqualitative & quantitative\nvalidation of fusion\nperformances for tMR_sMR\nmodality (V1.9.0)","This study evaluated the performances of the\nSmartFuse module on the clinical case of using\nfusion for MRI replannification.Favorableresultsto\nthe established performance criteria for rigid and\ndeformable registrations, and for all organs, were\nobtained.","Passed"],["Protocol for qualitative &\nquantitative validation of fusion\nperformances for\ntCT_sCT_replanning modality\n(V1.9.0)","This study evaluated thequalityoftherigidandthe\ndeformable fusion algorithms of the SmartFuse\nmodule for replanification of CT-based treatments.\nAcceptable results were reached for this\nevaluation.","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p28-t0","doc_id":"K220813","page_num":28,"bbox":[85.5,95.5,519.5,699.5],"n_rows":8,"n_cols":3,"columns":["Pilot study for sample size\nestimation - literature review\n(V1.9.0)","Theliteraturereviewwasperformedtoestimatethe\nappropriate sample size of the testing data set\ntowards demonstrating the performance of the\nimage registration, segmentation and pseudo-CT\ngeneration solutions on the basis of the most\nrecent and most relevant scientific literature.","N/A"],"rows":[["Pilot study for sample size\nestimation - literature review\n(V1.9.0)","Theliteraturereviewwasperformedtoestimatethe\nappropriate sample size of the testing data set\ntowards demonstrating the performance of the\nimage registration, segmentation and pseudo-CT\ngeneration solutions on the basis of the most\nrecent and most relevant scientific literature.","N/A"],["Autoseg 2D regression test for\nintegration in ART-Plan V1.9.0","The objective of the test was to demonstrate\nequivalence between the version (V1.9.0) and\nprevious versions of Annotate (V.1.8 and v1.6.1).\nAll organs passed at least one of the defined\ncriteria, and hence were accepted for release in\nv1.9. Given that equivalence TheraPanacea\nconsiders all tests (especially the qualitative ones)\nperformed on previous versions of the software to\nbe still relevant.","Passed"],["Study Protocol & Report\n(SPR): External contour\nnon-regression protocol for\nintegration in ART-Plan\nV1.10.0","This test demonstrates equivalence between the\nversion V.1.10 and V.1.9 of the external contours\nand show that the new added anatomies in the\nmodule Annotate provides clinically acceptable\ncontours. The external contour for all anatomies\npassed the defined criteria, and hence were\naccepted for release in the v1.10.","Passed"],["Testing Protocol/Report -\nAutoseg CT, MR\nnon-regression test for\nintegration in ART-Plan\nV1.10.0","This test demonstrates equivalence between the\nversion v.1.10 and v.1.9 of the auto-segmentation\nmodels for all structures and shows that the\nupdated models provide clinically acceptable\ncontours. All organs passed the defined criteria,\nand were hence accepted for release in the v1.10.","Passed"],["Study Protocol and Report\nQualitative Validation of\nAnnotate in ART-Plan V1.10.0\nfor Thorax","This test demonstrates that Annotate provides\nacceptable contours for structures of the thorax\nregion: thoracic aorta and bronchial trees. This\nqualitative test was performed as an addition to\nSection 18.21 to ensure the contours are clinically\nacceptable.","Passed"],["Study Protocol and Report-\nAutosegmentation\nperformances against\ninter-expert variability - Brain\nMR (V1.10.0)","This test demonstrates that the Annotate provides\nclinically acceptable (compared to inter-expert\nvariability) for all MR-T1 Brain structures. Existing\nstructures present in the previous version (v.1.8 -\nsee Section 18.8) were also re-evaluated since a\ncomplete retraining of the model was done.","Passed"],["Study Protocol and Report\nQualitative Validation of\nAnnotate in ART-Plan V1.10.0\nfor Pelvis Truefisp model","This test demonstrates that the module Annotate\nprovides acceptable contours for 9 organs\nevaluated on MR Truefisp images of patients. All\norgans have passed the acceptance criterion of\nreaching a percentage of at least 85% of A or B\n(qualitative evaluation) and hence can be released\nin v.1.10.0.","Passed"],["Study Protocol and Report\nQualitative Validation of\nAnnotate in ART-Plan V1.10.0\nfor H&N Lymph nodes","This test demonstrates that Annotate provides\nacceptable contours for following cervical lymph\nnodes levels: Ia, Ib right, VIIa left, VIIb right, IIleft,\nIII right, V left, IVb right, IVb left. All cervicallymph\nnodes having reached a percentage of at least","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p29-t0","doc_id":"K220813","page_num":29,"bbox":[85.5,95.5,519.5,701.65],"n_rows":8,"n_cols":4,"columns":["","","85% of A or B, the performance of auto\nsegmentation is demonstrated, and hence all\nstructures were included in V1.10.",""],"rows":[["","","85% of A or B, the performance of auto\nsegmentation is demonstrated, and hence all\nstructures were included in V1.10.",""],["Study Protocol and Report\nQualitative Validation of\nAnnotate in ART-Plan V1.10.0","","This test demonstrates that Annotate provides\nclinically acceptable contours, following qualitative\nmeasures, for the new version v.1.10. It serves as\nan additional evaluation to Section 18.21, andwas\ndone on a set of organs of all anatomies for both\nthe CT and MR models. The benchmarking was\ndone not only against thequalitativeevaluationbut\nalso against the manual contours and a previously\nvalidated version of the models. All contours can\nbe considered as acceptable as at least one\ncriterion was met for each of the included\nstructures.","Passed"],["Study Protocol and Report\nAnnotate Performances\nSummary (V1.10.0)","","The purpose of this document is todescribeallthe\ntesting protocols and testing results for validating\nthe performance of the Annotate module.\nSince all organs added in v.1.10.0 of Annotate\nhave passed at least one test andmetatleastone\nacceptance criteria, all organs have been released.","Passed"],["Testing: pseudo-CT clinical\nperformance and comparison\nto predicates (pelvis)\n(V1.10.0)","","The evaluation demonstrated the non-inferiority of\nusing Annotate’s pseudo-CTfortreatmentplanning\nin terms of dosimetric measures as compared to\nCT-based treatment planning. Our pseudo-CT for\npelvis has shown to produce results thatmeetthe\nacceptance criteria derived from clinical practice\nand literature review as well as to perform at least\nas good as two FDA cleared devices for\npseudo-CT generation.","Passed"],["Testing: pseudo-CT clinical\nperformance and comparison\nto predicates (brain)\n(V1.10.0)","","The evaluation demonstrated the non-inferiority of\nusing Annotate’s pseudo-CTfortreatmentplanning\nin terms of dosimetric measures as compared to\nCT-based treatment planning. Our pseudo-CT for\npelvis has shown to produce results thatmeetthe\nacceptance criteria derived from clinical practice\nand literature review as well as to perform at least\nas good as two FDA cleared devices for\npseudo-CT generation.","Passed"],["Study Protocol & Report\n(SPR): Testing:\nAutosegmentation\nperformances against\npredicates\n(V1.10.0)","","This evaluation demonstrated the non-inferiority of\nusing ART-Planv1.10.0forannotationoforgansas\ncompared to other devices which have been\ncleared for use in the US. In addition, ART-Plan\nv1.10.0 offers almost 3 times (2.72) more organs\nthan MIM/ContourProtege AI, which represents an\nadditionalbenefittotheusersascomparedtoother\ndevices.","Passed"],["","Study Protocol & Report","In this test, Annotate demonstrated equivalent\nperformances between non-US and US population","Passed"],["","(SPR): Autosegmentation","",""]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220813-p30-t0","doc_id":"K220813","page_num":30,"bbox":[85.5,96.02,519.5,500.5],"n_rows":3,"n_cols":3,"columns":["performances on Thorax US\ndata\n(V1.10.0)","for the Thorax localisation. Considering that this is\na worst case scenario of morphological\ndeformation due to factors such as age, gender or\nweight in abdominal region, we claim that\nconsidering any localisation included in the\nintended use of ART-Plan, any autosegmentation\nresult demonstrated on a non-US population can\nbe generalized to a US population. Nonetheless,\nTheraPanacea has performed an additional\nevaluation on pediatric US-data covering all other\nlocalisations included in the intended use of the\ndevice.",""],"rows":[["performances on Thorax US\ndata\n(V1.10.0)","for the Thorax localisation. Considering that this is\na worst case scenario of morphological\ndeformation due to factors such as age, gender or\nweight in abdominal region, we claim that\nconsidering any localisation included in the\nintended use of ART-Plan, any autosegmentation\nresult demonstrated on a non-US population can\nbe generalized to a US population. Nonetheless,\nTheraPanacea has performed an additional\nevaluation on pediatric US-data covering all other\nlocalisations included in the intended use of the\ndevice.",""],["Clinical evaluation of automatic\nsegmentation on Pediatric\nimages\n(V1.10.0)","Considering the fact that all the structures have\nreached a percentage of 90% (>=85%) of A or B\nfor the MR brain model, and that 11/15 structures\npassed with success for the CT model,\nTherapanacea claims that the performance ofauto\nsegmentation on said organs has been\ndemonstrated for the studied population.\nThese results highlight the high generalizability of\nthe commercial tool, initially made for adults, to\npediatric cases and its clinical implementation\nfeasibility. Note that this study served to\ndemonstrate that ART-Plan’s Annotate, trained on\nEuropean data, can be generalised to the US\npopulation given that it would be clinically\nacceptable even for pediatric cases where a more\nprominent change in size is expected thantheone\nbetween two adults from different countries. This\ndoes not mean that TheraPanacea is claimingthat\nART-Plan should be used for pediatric patients.","Passed"],["System Verification and\nValidation Testing","The system verification and validation testing was\nperformed to verify the software of the ART-Plan.","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220815-p2-t0","doc_id":"K220815","page_num":2,"bbox":[257.72,417.02,570.36,513.58],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220815-p5-t0","doc_id":"K220815","page_num":5,"bbox":[72.25,254.76,557.99,702.24],"n_rows":11,"n_cols":9,"columns":["","Attribute","","","Subject BrainInsight","","","Predicate BrainInsight (K202414)",""],"rows":[["","Attribute","","","Subject BrainInsight","","","Predicate BrainInsight (K202414)",""],["Indications for Use","","","BrainInsight is intended for automatic labeling,\nspatial measurement, and volumetric\nquantification of brain structures from a set of\nlow-field MR images and returns annotated and\nsegmented images, color overlays and reports.","","","Same","",""],["Target Anatomical\nSites","","","Brain","","","Same","",""],["Patient Population","","","Adult (≥ 18 years)","","","Same","",""],["Technology","","","● Automated measurement of brain tissue\nvolumes and structures of AI-reconstructed\nlow-field MR images\n● Automatic segmentation and quantification\nof brain structures of AI-reconstructed low-\nfield MR images using machine learning\ntools","","","● Automated measurement of brain\ntissue volumes and structures of\nconventional low-field MR images\n● Automatic segmentation and\nquantification of brain structures of\nconventional low-field MR images\nusing machine learning tools","",""],["Method of Use","","","MR images are automatically sent to\nBrainInsight, and processed images are\nautomatically returned in ~7 minutes","","","Same","",""],["User Interface /\nPhysical\nCharacteristics","","","● No software required\n● Operates in a serverless cloud environment\n● User interface through PACS (multiple\nvendors)","","","Same","",""],["Operating System","","","Supports Linux","","","Same","",""],["Processing\nArchitecture","","","Automated internal pipeline that performs:\n● segmentation\n● volume calculation\n● distance measurement\n● numerical information display","","","Same","",""],["Data Source","","","● MRI Scanner: Hyperfine Swoop FSE MRI\nscans acquired with specified protocols\n● Supports DICOM format as input","","","Same","",""],["Output","","","Provides volumetric measurements of brain\nstructures:\n● Includes segmented color overlays and\nmorphometric reports","","","Same","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220815-p6-t0","doc_id":"K220815","page_num":6,"bbox":[72.24,72.24,558.0,183.12],"n_rows":2,"n_cols":3,"columns":["","● Supports DICOM format as output of results\nthat can be displayed on DICOM\nworkstations and PACS",""],"rows":[["","● Supports DICOM format as output of results\nthat can be displayed on DICOM\nworkstations and PACS",""],["Safety","Automated quality control functions:\n● Tissue contrast check\n● Scan protocol verification\n● Atlas alignment check\n● Results must be reviewed by a trained\nphysician","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220882-p3-t0","doc_id":"K220882","page_num":3,"bbox":[36.31,30.25,578.64,703.15],"n_rows":48,"n_cols":4,"columns":["","(cid:39)(cid:40)(cid:51)(cid:36)(cid:53)(cid:55)(cid:48)(cid:40)(cid:49)(cid:55)(cid:3)(cid:50)(cid:41)(cid:3)(cid:43)(cid:40)(cid:36)(cid:47)(cid:55)(cid:43)","(cid:3)(cid:36)(cid:49)(cid:39)(cid:3)(cid:43)(cid:56)(cid:48)(cid:36)(cid:49)(cid:3)(cid:54)(cid:40)(cid:53)(cid:57)(cid:44)(cid:38)(cid:40)(cid:54)(cid:3)","(cid:41)(cid:82)(cid:85)(cid:80)(cid:3)(cid:36)(cid:83)(cid:83)(cid:85)(cid:82)(cid:89)(cid:72)(cid:71)(cid:29)(cid:3)(cid:50)(cid:48)(cid:37)(cid:3)(cid:49)(cid:82)(cid:17)(cid:3)(cid:19)(cid:28)(cid:20)(cid:19)(cid:16)(cid:19)(cid:20)(cid:21)(cid:19)"],"rows":[["","(cid:39)(cid:40)(cid:51)(cid:36)(cid:53)(cid:55)(cid:48)(cid:40)(cid:49)(cid:55)(cid:3)(cid:50)(cid:41)(cid:3)(cid:43)(cid:40)(cid:36)(cid:47)(cid:55)(cid:43)","(cid:3)(cid:36)(cid:49)(cid:39)(cid:3)(cid:43)(cid:56)(cid:48)(cid:36)(cid:49)(cid:3)(cid:54)(cid:40)(cid:53)(cid:57)(cid:44)(cid:38)(cid:40)(cid:54)(cid:3)","(cid:41)(cid:82)(cid:85)(cid:80)(cid:3)(cid:36)(cid:83)(cid:83)(cid:85)(cid:82)(cid:89)(cid:72)(cid:71)(cid:29)(cid:3)(cid:50)(cid:48)(cid:37)(cid:3)(cid:49)(cid:82)(cid:17)(cid:3)(cid:19)(cid:28)(cid:20)(cid:19)(cid:16)(cid:19)(cid:20)(cid:21)(cid:19)"],["","","",""],["","(cid:41)(cid:82)(cid:82)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:39)(cid:85)(cid:88)(cid:74)(cid:3)","(cid:36)(cid:71)(cid:80)(cid:76)(cid:81)(cid:76)(cid:86)(cid:87)(cid:85)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)","(cid:40)(cid:91)(cid:83)(cid:76)(cid:85)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:39)(cid:68)(cid:87)(cid:72)(cid:29)(cid:3)(cid:19)(cid:25)(cid:18)(cid:22)(cid:19)(cid:18)(cid:21)(cid:19)(cid:21)(cid:22)"],["","","",""],["","(cid:44)(cid:81)(cid:71)(cid:76)(cid:70)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)","(cid:86)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:56)(cid:86)(cid:72)","See PRA Statement below."],["","","",""],["(cid:24)(cid:20)(cid:19)(cid:11)(cid:78)(cid:12)(cid:3)(cid:49)(cid:88)","(cid:80)(cid:69)(cid:72)(cid:85)(cid:3)(if known)","",""],["","","",""],["K22088","2","",""],["","","",""],["(cid:39)(cid:72)(cid:89)(cid:76)(cid:70)(cid:72)(cid:3)(cid:49)(cid:68)","(cid:80)(cid:72)","",""],["(cid:3)","","",""],["(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:27)(cid:19)","(cid:3)(cid:18)(cid:3)(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:28)(cid:19)(cid:3)(cid:18)(cid:3)(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:28)(cid:24)","",""],["","","",""],["(cid:44)(cid:81)(cid:71)(cid:76)(cid:70)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:86)","(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:56)(cid:86)(cid:72)(cid:3)(Describe)","",""],["(cid:3)","","",""],["(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:27)","(cid:19)(cid:18)(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:28)(cid:19)(cid:18)(cid:57)(cid:76)(cid:89)(cid:76)(cid:71)(cid:3)(cid:40)(cid:28)(cid:24)(cid:3)(cid:76)(cid:86)(cid:3)(cid:68)(cid:3)(cid:74)(cid:72)(cid:81)(cid:72)(cid:85)(cid:68)","(cid:79)(cid:16)(cid:83)(cid:88)(cid:85)(cid:83)(cid:82)(cid:86)(cid:72)(cid:3)(cid:88)(cid:79)(cid:87)(cid:85)(cid:68)(cid:86)(cid:82)(cid:88)(cid:81)(cid:71)(cid:3)(cid:86)(cid:92)(cid:86)(cid:87)(cid:72)(cid:80)(cid:15)(cid:3)(cid:86)(cid:83)(cid:72)(cid:70)(cid:76)(cid:68)(cid:79)(cid:76)(cid:93)(cid:72)(cid:71)(cid:3)(cid:73)","(cid:82)(cid:85)(cid:3)(cid:88)(cid:86)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:70)(cid:68)(cid:85)(cid:71)(cid:76)(cid:68)(cid:70)(cid:3)(cid:76)(cid:80)(cid:68)(cid:74)(cid:76)(cid:81)(cid:74)(cid:17)(cid:3)(cid:44)(cid:87)(cid:3)(cid:76)(cid:86)(cid:3)"],["(cid:76)(cid:81)(cid:87)(cid:72)(cid:81)(cid:71)(cid:72)(cid:71)(cid:3)","(cid:73)(cid:82)(cid:85)(cid:3)(cid:88)(cid:86)(cid:72)(cid:3)(cid:69)(cid:92)(cid:15)(cid:3)(cid:82)(cid:85)(cid:3)(cid:88)(cid:81)(cid:71)(cid:72)(cid:85)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)(cid:71)(cid:76)(cid:85)(cid:72)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:82)","(cid:73)(cid:3)(cid:68)(cid:3)(cid:84)(cid:88)(cid:68)(cid:79)(cid:76)(cid:73)(cid:76)(cid:72)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:87)(cid:85)(cid:68)(cid:76)(cid:81)(cid:72)(cid:71)(cid:3)(cid:83)(cid:75)(cid:92)(cid:86)(cid:76)(cid:70)(cid:76)(cid:68)(cid:81)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:88)(cid:79)(cid:87)(cid:85)","(cid:68)(cid:86)(cid:82)(cid:88)(cid:81)(cid:71)(cid:3)(cid:76)(cid:80)(cid:68)(cid:74)(cid:76)(cid:81)(cid:74)(cid:15)(cid:3)(cid:80)(cid:72)(cid:68)(cid:86)(cid:88)(cid:85)(cid:72)(cid:80)(cid:72)(cid:81)(cid:87)(cid:15)(cid:3)"],["(cid:71)(cid:76)(cid:86)(cid:83)(cid:79)(cid:68)(cid:92)(cid:3)(cid:68)","(cid:81)(cid:71)(cid:3)(cid:68)(cid:81)(cid:68)(cid:79)(cid:92)(cid:86)(cid:76)(cid:86)(cid:3)(cid:82)(cid:73)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)(cid:75)(cid:88)(cid:80)(cid:68)(cid:81)(cid:3)(cid:69)(cid:82)(cid:71)(cid:92)(cid:3)(cid:68)(cid:81)(cid:71)","(cid:3)(cid:73)(cid:79)(cid:88)(cid:76)(cid:71)(cid:17)(cid:3)(cid:3)(cid:55)(cid:75)(cid:72)(cid:3)(cid:71)(cid:72)(cid:89)(cid:76)(cid:70)(cid:72)(cid:3)(cid:76)(cid:86)(cid:3)(cid:76)(cid:81)(cid:87)(cid:72)(cid:81)(cid:71)(cid:72)(cid:71)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:88)(cid:86)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:68)(cid:3)","(cid:75)(cid:82)(cid:86)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:3)(cid:72)(cid:81)(cid:89)(cid:76)(cid:85)(cid:82)(cid:81)(cid:80)(cid:72)(cid:81)(cid:87)(cid:3)(cid:76)(cid:81)(cid:70)(cid:79)(cid:88)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:72)(cid:70)(cid:75)(cid:82)(cid:3)"],["(cid:79)(cid:68)(cid:69)(cid:15)(cid:3)(cid:82)(cid:87)(cid:75)(cid:72)(cid:85)","(cid:3)(cid:75)(cid:82)(cid:86)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:3)(cid:86)(cid:72)(cid:87)(cid:87)(cid:76)(cid:81)(cid:74)(cid:86)(cid:15)(cid:3)(cid:82)(cid:83)(cid:72)(cid:85)(cid:68)(cid:87)(cid:76)(cid:81)(cid:74)(cid:3)(cid:85)(cid:82)(cid:82)(cid:80)(cid:15)","(cid:3)(cid:38)(cid:68)(cid:87)(cid:75)(cid:3)(cid:79)(cid:68)(cid:69)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:40)(cid:51)(cid:3)(cid:79)(cid:68)(cid:69)(cid:3)(cid:82)(cid:85)(cid:3)(cid:76)(cid:81)(cid:3)(cid:83)(cid:85)(cid:76)(cid:89)(cid:68)(cid:87)(cid:72)(cid:3)(cid:80)(cid:72)(cid:71)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)","(cid:82)(cid:73)(cid:73)(cid:76)(cid:70)(cid:72)(cid:86)(cid:17)(cid:3)(cid:55)(cid:75)(cid:72)(cid:3)(cid:86)(cid:92)(cid:86)(cid:87)(cid:72)(cid:80)(cid:86)(cid:3)(cid:86)(cid:88)(cid:83)(cid:83)(cid:82)(cid:85)(cid:87)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)"],["(cid:73)(cid:82)(cid:79)(cid:79)(cid:82)(cid:90)(cid:76)(cid:81)(cid:74)","(cid:3)(cid:70)(cid:79)(cid:76)(cid:81)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)(cid:68)(cid:83)(cid:83)(cid:79)(cid:76)(cid:70)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:86)(cid:29)(cid:3)(cid:41)(cid:72)(cid:87)(cid:68)(cid:79)(cid:18)(cid:50)(cid:69)(cid:86)(cid:87)(cid:72)","(cid:87)(cid:85)(cid:76)(cid:70)(cid:86)(cid:15)(cid:3)(cid:36)(cid:69)(cid:71)(cid:82)(cid:80)(cid:76)(cid:81)(cid:68)(cid:79)(cid:3)(cid:11)(cid:76)(cid:81)(cid:70)(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{"table_id":"K220928-p5-t0","doc_id":"K220928","page_num":5,"bbox":[90.0,246.96,535.44,716.88],"n_rows":10,"n_cols":3,"columns":["Device","Carestream\nLogicon\nCaries Detector","Overjet Calculus Assist\n(proposed)"],"rows":[["Device","Carestream\nLogicon\nCaries Detector","Overjet Calculus Assist\n(proposed)"],["510k","P980025","K220928"],["Regulation No /\nDescription","CFR 892.2070\nMedical image analyzer","CFR 892.2070\nMedical image analyzer"],["Intended Use","The Logicon Caries Detector is a\nsoftware device that is an aid in the\ndiagnosis of caries that have\npenetrated into the dentin, on un-\nrestored proximal surfaces of\nsecondary dentition through\nthe statistical analysis of digital\nintraoral radiographic imagery. The\ndevice provides\nadditional information for the clinician\nto use in his/her diagnosis of a tooth\nsurface suspected of being carious. It\nis designed to work in conjunction\nwith an existing Carestream dental\nRVG digital X-ray radiographic\nsystem with dental imaging software\n(dis) for Windows XP or higher.","Overjet’s Calculus Assist (OCalA)\nsoftware automatically detects\ninterproximal calculus on bitewing and\nperiapical radiographs. It is intended to aid\ndentists in the detection of calculus. It\nshould not be used in lieu of full patient\nevaluation or solely relied upon to make or\nconfirm a diagnosis. The system is to be\nused by professionally trained and licensed\ndentists."],["Type of CAD","CADe","CADe"],["End User","Dentist","Dentist"],["Patient\nPopulation","Patients requiring dental services, all\nsexes, no\nage restriction","Patients requiring dental services, all sexes,\n18 years of age or older."],["Platform","Windows PC","Web - Edge, Chrome, Firefox"],["OS","Microsoft Window 7, 8, 10","Any"],["User Interface","Mouse, Keyboard","Mouse, Keyboard, Trackpad"]],"caption_candidate":"9. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220928-p6-t0","doc_id":"K220928","page_num":6,"bbox":[90.0,72.48,535.44,460.08],"n_rows":7,"n_cols":3,"columns":["Image Input\nSources","Images can be scanned, loaded from\nconnected Carestream image solutions","Images imported from the radiographic\ndevice, or from the practice management\nsystem"],"rows":[["Image Input\nSources","Images can be scanned, loaded from\nconnected Carestream image solutions","Images imported from the radiographic\ndevice, or from the practice management\nsystem"],["Image format","","JPEG, PNG, JFIF, JIF, TIFF, EOP, BMP,\nDICOM"],["Processing\nArchitecture","The software provides graphical\nrepresentation of the density change in\na tooth, by looking for a\npattern of density dips starting at the\ntooth surface, penetrating the enamel\nand going into the dentin. Enamel is\nrepresented by 10 green lines and\ndentin by 5 blue lines. If a pattern\nsuggestive of caries exists, the dips are\nhighlighted with red dots to warn the\ndentist.","Three layers:\n1 - The Network layer works with the\npractice PACS or EMR to transmit the\nimage and meta-data to Overjet.\n2 - The decision layer processes the image\nto ensure it is the correct data type, and\nthen annotates it via the algorithm\n3 - The presentation layer displays the\nannotated image in a non-diagnostic\nviewer. The dentist can filter, display, hide,\ncreate and edit the annotations presented."],["Data Source","Bitewing radiographs acquired from\nCarestream\ndental RVG digital X-ray radiographic\nsystem","Bitewing and periapical radiographs of at\nleast 500 x 500 pixels."],["Output","●Outline of suspected region\n●Tooth Density\n●Lesion (caries) probability","Calculus detection on radiograph resulting\nin bounding box outline of suspected\ncalculus"],["Performance\nTesting","Increase in dentist’s sensitivity of\napproximately 20%","Superiority of aided reader versus unaided\nreader performance"],["Level of\nConcern","Moderate","Moderate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220928-p8-t0","doc_id":"K220928","page_num":8,"bbox":[119.76,130.56,492.24,203.22],"n_rows":4,"n_cols":3,"columns":["Image Type","AUC","95% CI1"],"rows":[["Image Type","AUC","95% CI1"],["Bitewing","0.859","0.823, 0.894"],["Periapical","0.867","0.828, 0.903"],["1 Based on m=10000 bootstrap samples.","",""]],"caption_candidate":"curve and associated AUC. Results are shown in the following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220939-p9-t0","doc_id":"K220939","page_num":9,"bbox":[109.78,209.64,540.45,279.96],"n_rows":4,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Lumina with\nsyngo MR XA31A","K203443, cleared March\n31, 2021","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Vida Fit with\nsyngo MR XA20A","K192924, cleared on March\n11, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"are substantially equivalent to the following predicate devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220939-p9-t1","doc_id":"K220939","page_num":9,"bbox":[109.78,345.61,540.45,415.92],"n_rows":4,"n_cols":4,"columns":["Reference Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA50A","K213693, cleared February\n25, 2022","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Vida with\nsyngo MR XA11A","K181433, cleared October\n19, 2018","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"reference device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220939-p10-t0","doc_id":"K220939","page_num":10,"bbox":[109.95,103.25,540.21,161.58],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Verification and validation","Transferred hardware and\nsoftware features","Guidance for the Content of\nPremarket Submissions for\nSoftware Contained in Medical\nDevices / 21 CFR §820.30"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220939-p11-t0","doc_id":"K220939","page_num":11,"bbox":[109.58,103.02,540.66,556.02],"n_rows":9,"n_cols":5,"columns":["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],"rows":[["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1:2015","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","62304:2006/A1:201\n6","ANSI AAMI\nIEC"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20\n(2016)","NEMA"],["19-8","General II\n(ES/\nEMC)","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2 Edition\n4.0 2014-02","IEC"],["12-331","Radiology","Characterization of\nRadiofrequency (RF) Coil\nHeating in Magnetic Resonance\nImaging Systems","Standards\nPublication MS 14-\n2019","NEMA"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p2-t0","doc_id":"K220956","page_num":2,"bbox":[257.72,430.78,570.36,527.38],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p4-t0","doc_id":"K220956","page_num":4,"bbox":[72.34,150.1,545.74,304.29],"n_rows":5,"n_cols":4,"columns":["","510(k) Sponsor","","Dyad Medical, Inc"],"rows":[["","510(k) Sponsor","","Dyad Medical, Inc"],["Address","","","215 Brighton Avenue, Suite 203\nBoston, MA 02134"],["Correspondence Person","","","Yervant Chijian\nQuality and Regulatory Consultant\nPharmalex Pty Ltd"],["Contact Information","","","Email: Yervant.Chijian@pharmalex.com\nPhone: +61 (0)2 9906 2984"],["","Date Prepared","","31st March 2022"]],"caption_candidate":"5.1 General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p4-t1","doc_id":"K220956","page_num":4,"bbox":[72.34,337.57,545.74,468.47],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","Libby™ Echo:Prio"],"rows":[["","Proprietary Name","","Libby™ Echo:Prio"],["","Common Name","","Echo:Prio"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","21 CFR 892.2050"],["","Regulation Name","","Automated Radiological Image Processing Software"],["","Product Code","","QIH"],["","Regulatory Class","","II"]],"caption_candidate":"5.2 Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p4-t2","doc_id":"K220956","page_num":4,"bbox":[72.34,501.75,545.74,632.54],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","EchoMD Automated Ejection Fraction Software"],"rows":[["","Proprietary Name","","EchoMD Automated Ejection Fraction Software"],["","Premarket Notification","","K173780"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","21 CFR 892.2050"],["","Regulation Name","","Picture archiving and communications system"],["","Product Code","","LLZ"],["","Regulatory Class","","II"]],"caption_candidate":"5.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p5-t0","doc_id":"K220956","page_num":5,"bbox":[60.38,684.07,535.01,760.39],"n_rows":4,"n_cols":6,"columns":["Topic","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],"rows":[["Topic","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],["","","","EchoMD Automated Ejection Fraction","",""],["","","","Software","",""],["Intended Use/Indications for\nUse","Libby™ Echo:Prio is software that\nis used to process previously\nacquired DICOM-compliant","The Bay Labs, Inc. EchoMD\nAutomated Ejection Fraction\nsoftware is used to process","","","Same"]],"caption_candidate":"Table 1: Libby™ Echo:Prio Device Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p6-t0","doc_id":"K220956","page_num":6,"bbox":[60.38,95.27,535.05,754.03],"n_rows":26,"n_cols":8,"columns":["Topic","","","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],"rows":[["Topic","","","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],["","","","","","EchoMD Automated Ejection Fraction","",""],["","","","","","Software","",""],["","","","cardiac ultrasound images, and to\nmake measurements on these\nimages in order to provide\nautomated estimation of several\ncardiac measurements. The data\nproduced by this software is\nintended to be used to support\nqualified cardiologists,\nsonographers, or other licensed\nprofessional healthcare\npractitioners for clinical decision-\nmaking.\nLibby™ Echo:Prio is indicated for\nuse in adult patients.","previously acquired transthoracic\ncardiac ultrasound images, to store\nimages, and to manipulate and\nmake measurements on images\nusing a personal computer or a\ncompatible DICOM-compliant\nPACS system in order to provide\nautomated estimation of left\nventricular ejection fraction. This\nmeasurement can be used to assist\nthe clinician in a cardiac\nevaluation. The EchoMD\nAutomated Ejection Fraction\nSoftware is indicated for use in\nadult patients.","","",""],["","Intended User","","Cardiologists and sonographers","Cardiologists and sonographers","","","Same"],["","Rx or OTC","","Rx","Rx","","","Same"],["","Intended Location","","Medical facility","Medical facility","","","Same"],["High Level Device\nDescription","High Level Device","","The Libby™ Echo:Prio is an image\npost-processing analysis software\ndevice used for viewing and\nquantifying cardiovascular\nultrasound images.","EchoMD software is process\nacquired transthoracic cardiac\nultrasound images, to analyze and\nmake measurements on images in\norder to provide automated\nestimation of left ventricular\nejection fraction","","","Same"],["","Description","","","","","",""],["","Automated Chamber","","Yes","Yes","","","Same"],["","analysis Features & Analysis","","","","","",""],["","Automated measurements","","LV Ejection fraction (EF)","Left ventricular ejection fraction","","","Same"],["","Machine Learning Based","","Yes","Yes","","","Same"],["","Algorithm","","","","","",""],["","Operate on DICOM clips","","Yes","Yes","","","Same"],["","Automated View","","Yes","Yes","","","Same"],["","Classification including:","","","","","",""],["","1. long axis view (PLAX)","","","","","",""],["","2. short axis view (PSAX)","","","","","",""],["","3. four-chamber view (A4C)","","","","","",""],["","4. five-chamber view (A5C)","","","","","",""],["","5. two-chamber view (A2C)","","","","","",""],["","6. long axis view (A3C)","","","","","",""],["Automation Level","Automation Level","","Fully automated, including clip\nselection","Fully automated, including clip\nselection","","","Same"],["Algorithm Confidence","","","Qualitative user feedback on\ntransthoracic cardiac\nultrasound image quality","Qualitative and quantitative user\nfeedback on transthoracic cardiac\nultrasound image quality","","","Same"],["EF Method","","","Single plane & biplane (with\nsegmentation and endocardial\ntrace)","Biplane (non-segmentation/ non-\nendocardial trace)","","","Same"]],"caption_candidate":"LIBBY™ ECHO:PRIO Traditional 510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220956-p7-t0","doc_id":"K220956","page_num":7,"bbox":[60.38,95.27,535.05,435.38],"n_rows":17,"n_cols":8,"columns":["Topic","","","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],"rows":[["Topic","","","Subject Device\nLibby™ Echo:Prio","","Predicate Device","","Substantial\nEquivalence"],["","","","","","EchoMD Automated Ejection Fraction","",""],["","","","","","Software","",""],["","Offline EF evaluation using","","Yes","Yes","","","Same"],["","clips from multiple","","","","","",""],["","ultrasound scanners","","","","","",""],["","Automated Ejection Fraction","","Yes","Yes","","","Same"],["","Calculation","","","","","",""],["Ejection Fraction reported","Ejection Fraction reported","","Whole number estimate\n(percentage)","Whole number estimate\n(percentage)","","","Same"],["","User Confirmation/rejection","","Yes","Yes","","","Same"],["","of result","","","","","",""],["","Manual editing of","","Yes","Yes","","","Same"],["","automated result by user","","","","","",""],["Physical Characteristics","Physical Characteristics","","Software package that operates on\noff-the-shelf hardware","Software package that operates on\noff-the-shelf hardware","","","Not equivalent\nbut no issues\nwith safety and\nefficacy."],["DICOM Standard Compliance","","","The software processes DICOM\ncompliant image data","The software processes DICOM\ncompliant image data","","","Same"],["","Modalities","","Ultrasound","Ultrasound","","","Same"],["User Interface","User Interface","","The software is designed for use\nwithin a web browser on a personal\ncomputer.","The software is designed for use\non personal computer or a\ncompatible DICOM-compliant\nPACS system.","","","Not equivalent\nbut no issues\nwith safety and\nefficacy."]],"caption_candidate":"LIBBY™ ECHO:PRIO Traditional 510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220961-p6-t0","doc_id":"K220961","page_num":6,"bbox":[72.15,317.39,543.53,706.26],"n_rows":9,"n_cols":6,"columns":["Specification/ Attribute","","Deep Learning Image","","","Deep Learning Image\nReconstruction\n(Proposed Device)"],"rows":[["Specification/ Attribute","","Deep Learning Image","","","Deep Learning Image\nReconstruction\n(Proposed Device)"],["","","Reconstruction","","",""],["","","(Predicate Device, K183202)","","",""],["Technology","Utilizes a dedicated Deep Neural\nNetwork (DNN) designed specifically\nto generate high quality CT images","","","Same",""],["Clinical Workflow","Select recon type and strength (Low,\nMedium, High)","","","Same",""],["Clinical Use","Routine Clinical Use","","","Same",""],["Reference\nprotocols/dose","Using the same Reference protocols\nprovided on the Revolution CT\nfamily systems for ASiR-V","","","Using the same Reference protocols\nprovided on the Discovery CT750\nHD family CT systems for ASiR-V",""],["IQ performance vs dose","Image noise, low contrast\ndetectability, spatial resolution, and\nlow signal artifact suppression as\ngood or better than ASiR-V on\nRevolution CT family systems","","","Image noise, low contrast\ndetectability, spatial resolution, and\nlow signal artifact suppression as\ngood or better than ASiR-V on\nDiscovery CT750 HD family CT\nsystems",""],["Deployment\nEnvironment","On CT Console","","","On GE’s Edison Platform.",""]],"caption_candidate":"predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220975-p6-t0","doc_id":"K220975","page_num":6,"bbox":[127.75,306.89,524.63,550.63],"n_rows":7,"n_cols":2,"columns":["Reference No.","Title"],"rows":[["Reference No.","Title"],["IEC 60601-1","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012,\nC1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text) Medical\nelectrical equipment - Part 1: General requirements for basic safety\nand essential performance (IEC 60601-1:2005, MOD)"],["IEC 60601-1-2","IEC60601-1-2: 2014(4th Edition) , Medical electrical equipment -\nPart 1-2: General requirements for basic safety and essential\nperformance - EMC"],["IEC 60601-2-37","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment –\nPart 2-37: Particular requirements for the basic safety and essential\nperformance of ultrasonic medical diagnostic and monitoring\nequipment"],["ISO10993-1","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk\nmanagement process"],["ISO14971","ISO 14971:2007, Medical devices - Application of risk management\nto medical devices"],["NEMA UD 2-\n2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard\nfor Diagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220975-p7-t0","doc_id":"K220975","page_num":7,"bbox":[125.32,92.42,526.85,153.26],"n_rows":2,"n_cols":3,"columns":["Accuracy (%)","Number of correctly detected frames\n×100\nTotal number of frames with nerve","≥ 80%"],"rows":[["Accuracy (%)","Number of correctly detected frames\n×100\nTotal number of frames with nerve","≥ 80%"],["Speed (FPS)","1000\nAverage latency time of each frame (msec)","≥ 2 FPS"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220975-p7-t1","doc_id":"K220975","page_num":7,"bbox":[125.32,179.18,526.85,221.18],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","91.7","","","5.6","","","89.5 to 93.9","",""],["Speed (FPS)","","","7.93","","","1.11","","","7.04 to 8.82","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220975-p7-t2","doc_id":"K220975","page_num":7,"bbox":[125.32,247.1,526.85,352.25],"n_rows":8,"n_cols":12,"columns":["","","","","Females","","","Males","","","Total",""],"rows":[["","","","","Females","","","Males","","","Total",""],["Number of Subjects","","","13","","","5","","","18","",""],["Number of Images","","","1,168","","","978","","","2,146","",""],["Age range","","","32~68","","","22~50","","","22~68","",""],["Average age","","","45.7","","","35.0","","","42.7","",""],["BMI range","","","16~27.1","","","31.5","","","16~31.5","",""],["Average BMI","","","20.5","","","31.5","","","21.5","",""],["Ethnicity","","","All Koreans","","","","","","","",""]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220986-p5-t0","doc_id":"K220986","page_num":5,"bbox":[113.64,67.68,594.0,149.28],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion Precision\n(TSX-304A/1 and /2)\nV8.8 with AiCE","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K182901","July 5, 2019"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220986-p6-t0","doc_id":"K220986","page_num":6,"bbox":[108.78,55.22,589.46,712.03],"n_rows":49,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["D","evice Name,","","","Aquilion Precision (TSX‐","","","Aquilion Precision (TSX‐","","","",""],["","Model Number","","","304A/4) V10.10 with AiCE","","","304A/1 and /2) V8.8 with AiCE","","","",""],["","510(k) Number","","","This submission","","","K182901","","","",""],["AiCE Modifications","","","","","","","","","","",""],["• Scan Regions","","","","Abdomen and Pelvis / Chest","","Abdomen and Pelvis","","","","",""],["","","","","/ Cardiac","","","","","","",""],["","","","","","","","","","","",""],["• Available Scan\nTypes","","","- Helical scan\n- Volume scan\n- vHP*","- Helical scan","","-Helical scan\n(Not applicable to tilt scans)\n- Volume scan\n(Not applicable to W-Volume\ntilt scans)\n- vHP*","","","Tilt scans are applicable\nwith AiCE BODY SHARP,\nLUNG and CARDIAC. For\nBODY parameters, ECG-\ngated scan, respiratory-\ngated scan, W-Volume\ntilt scan and tilt helical\nscan cannot be applied.\n*: Option","",""],["","","","","","","","","","","",""],["","","","","","","","","","","",""],["","","","","- Volume scan","","","","","","",""],["","","","","","","","","","","",""],["","","","","","","","","","","",""],["","","","","","","","","","","",""],["","","","","- vHP*","","","","","","",""],["","","","","","","","","","","",""],["• ECG-gated scan","","","","Available in BODY SHARP,","","N/A","","","","",""],["","","","","LUNG and CARDIAC","","","","","","",""],["","","","","","","","","","","",""],["• Respiratory-\ngated scan","","","","Available in BODY SHARP,","","N/A","","","","",""],["","","","","LUNG and CARDIAC","","","","","","",""],["","","","","","","","","","","",""],["• Applicable\nanatomical\nregions","","","","- BODY and BODY SHARP","","-BODY (For Abdomen and\nPelvis)","","","","",""],["","","","","(For Abdomen and Pelvis)","","","","","","",""],["","","","","- LUNG (For Chest)","","","","","","",""],["","","","","- CARDIAC (For Cardiac)","","","","","","",""],["","","","","","","","","","","",""],["• Image thickness","","","","0.25, 0.5, 1, 2, 3*, 4, 5, 7*, 8","","0.25 and 0.5 mm","","","*: Excluding volume scan\nand dynamic volume\nscan.","",""],["","","","","and 10 mm","","","","","","",""],["","","","","","","","","","","",""],["• Magnified\nreconstruction -\nAvailable\nmagnification\nSize (D-FOV)","","","","BODY / BODY SHARP: Min.","","Min. 100 mm\nMax. 500 mm","","","","",""],["","","","","100 mm","","","","","","",""],["","","","","LUNG: Min. 100 mm","","","","","","",""],["","","","","CARDIAC: Min. 70 mm","","","","","","",""],["","","","","Max. 500 mm","","","","","","",""],["","","","","","","","","","","",""],["Gantry tilt","","","±30°\nAxial and helical scanning\n• Tilt scans are applicable\nwith AiCE BODY SHARP,\nLUNG and CARDIAC\n• For BODY parameters,\nECG-gated scan,\nrespiratory-gated scan,\nW-Volume tilt scan and\ntilt helical scan cannot be\napplied","±30°","","±30°\nAxial and helical scanning\n• Helical and W-Volume tilt\nscans are not applicable\nwith AiCE","","","Gantry and remote\ncontrolled","",""],["","","","","Axial and helical scanning","","","","","","",""],["","","","","• Tilt scans are applicable","","","","","","",""],["","","","","with AiCE BODY SHARP,","","","","","","",""],["","","","","LUNG and CARDIAC","","","","","","",""],["","","","","","","","","","","",""],["","","","","• For BODY parameters,","","","","","","",""],["","","","","ECG-gated scan,","","","","","","",""],["","","","","respiratory-gated scan,","","","","","","",""],["","","","","W-Volume tilt scan and","","","","","","",""],["","","","","tilt helical scan cannot be","","","","","","",""],["","","","","applied","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K220986-p7-t0","doc_id":"K220986","page_num":7,"bbox":[108.8,55.22,589.44,156.63],"n_rows":7,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["D","evice Name,","","","Aquilion Precision (TSX‐","","","Aquilion Precision (TSX‐","","","",""],["","Model Number","","","304A/4) V10.10 with AiCE","","","304A/1 and /2) V8.8 with AiCE","","","",""],["","510(k) Number","","","This submission","","","K182901","","","",""],["Console","","","AiCE/FIRST (CCRS-003B) can\nbe installed in the console\nunit","AiCE/FIRST (CCRS-003B) can","","Separate unit, I-REC BOX, was\nused as the AiCE/FIRST (CCRS-\n002A) server","","","","",""],["","","","","be installed in the console","","","","","","",""],["","","","","unit","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221100-p4-t0","doc_id":"K221100","page_num":4,"bbox":[108.24,486.36,539.76,518.04],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Imbio","Imbio RV/LV Software","K203256"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221100-p7-t0","doc_id":"K221100","page_num":7,"bbox":[72.24,196.44,539.76,703.2],"n_rows":12,"n_cols":3,"columns":["","Predicate Device\nImbio RV/LV Software","Subject Device\nViz RV/LV"],"rows":[["","Predicate Device\nImbio RV/LV Software","Subject Device\nViz RV/LV"],["Device Class","2","2"],["Product Code","QIH","QIH"],["Regulation\nNumber:","21 C.F.R. § 892.2050","21 C.F.R. § 892.2050"],["Indications for\nUse:","The Imbio RV/LV Software device is\ndesigned to measure the maximal\ndiameters of the right and left ventricles of\nthe heart from a volumetric CTPA\nacquisition and report the ratio of those\nmeasurements. RV/LV analyzes cases\nusing an artificial intelligence algorithm to\nidentify the location and measurements of\nthe ventricles. The RV/LV software\nprovides the user with annotated images\nshowing ventricular measurements. Its\nresults are not intended to be used on a\nstand-alone basis for clinical decision-\nmaking or otherwise preclude clinical\nassessment of CTPA cases.","The Viz RV/LV Software device is\ndesigned to measure the maximal\ndiameters of the right and left ventricles of\nthe heart from a volumetric CTPA\nacquisition and report the ratio of those\nmeasurements. Viz RV/LV analyzes cases\nusing an artificial intelligence algorithm to\nidentify the location and measurements of\nthe ventricles. The Viz RV/LV software\nprovides the user with annotated images\nshowing ventricular measurements. Its\nresults are not intended to be used on a\nstand-alone basis for clinical decision-\nmaking or otherwise preclude clinical\nassessment of CTPA cases."],["Input Data\nRequirements:","Non-gated, CT Pulmonary Angiography\n(CTPA)","Same"],["DICOM\nCompliant","Yes","Same"],["Left Ventricle\nSegmentation","Yes","Same"],["Right Ventricle\nSegmentation","Yes","Same"],["Diameter\nMeasurements","Yes – Automated","Same"],["Fully automated\nsegmentation","Yes","Same"],["Outputs","Reports, DICOM Secondary Capture\nSeries","Same"]],"caption_candidate":"Table 1 Technological Characteristic Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221219-p6-t0","doc_id":"K221219","page_num":6,"bbox":[92.65,135.4,519.4,726.3],"n_rows":13,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Devices",""],"rows":[["Feature","","Subject Device","","","Predicate Devices",""],["","syngo.CT CaScoring\n(SOMARIS/8 VB70)","","","syngo.CT CaScoring\n(SOMARIS/8 VB50)","",""],["Modality","CT","","","CT","",""],["Loading of a series of\nappropriate CT from the patient\ndatabase","Yes","","","Yes","",""],["Body Part","Heart / Chest","","","Heart/Chest","",""],["Acquisition Part","ECG-gated / ECG-triggered","","","ECG-gated / ECG-triggered","",""],["Automated Calcium Scoring\nEvaluation","Assignment of a probability of a\ncandidate being a coronary\ncalcification based on location\nwithin the heart, density, shape and\nsimilar properties: if the probability\nof a candidate is higher than a\npredefined threshold, the candidate\nis labelled as a calcification.\nEach calcification is labeled\naccording to one of four coronary\narteries it most probably belongs to.\nIn addition, results of the evaluation\ncan be sent via Rapid Results\nTechnology to any generic DICOM\nviewer.\nComparison to the predicate\ndevice:\nThe algorithm was re-trained on a\nlarger database.\nA configuration option was added so\nthe user can disable the automated\ncalcium scoring evaluation.","","","Assignment of a probability of a candidate\nbeing a coronary calcification based on\nlocation within the heart, density, shape and\nsimilar properties: if the probability of a\ncandidate is higher than a predefined\nthreshold, the candidate is labelled as a\ncalcification.\nEach calcification is labeled according to one\nof four coronary arteries it most probably\nbelongs to.\nIn addition, results of the evaluation can be\nsent via Rapid Results Technology to any\ngeneric DICOM viewer.","",""],["Browsing, selecting, and\ndisplaying images for searching\ncalcium regions/lesions","Yes","","","Yes","",""],["Interactive definition of ROIs and\nassignment of the four major\ncoronary arteries (LM, LAD,CRC\nand RCA) to the lesions","Yes","","","Yes","",""],["Automatic definition of ROIs and\nassignment of a generic calcium\nlabel to the lesions","Yes","","","Yes","",""],["Calculation and display of the\n2D-Agatston score/factor or\nother metric on the defined ROIs","Agatston, volume and mass scores","","","Agatston, volume and mass scores","",""],["Interactive definition of ROIs (for\nexample noise) to disqualify the\nregion from participation in the\nscore","Yes","","","Yes","",""],["Displaying the score in form of\nresult tables/reports on paper\nand/or film","Yes","","","Yes","",""]],"caption_candidate":"level in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221219-p8-t0","doc_id":"K221219","page_num":8,"bbox":[92.66,134.66,519.4,334.47],"n_rows":8,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2015-06 (Edition 1.1)","01/14/2019","AAMI, ANSI,\nIEC","",""],["5-125","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Third\nEdition 2019-12","12/23/2019","ISO","",""],["5-129","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2015 +AMD1:2020","07/06/2020","ANSI, AAMI, IEC","",""],["5-117","General I\n(QS/RM)","Medical devices - Symbols to be used with\nmedical device labels, labelling, and\ninformation to be supplied - Part 1: General\nrequirements 15223-1:2016","8/21/2017","ISO","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221240-p6-t0","doc_id":"K221240","page_num":6,"bbox":[77.66,72.24,548.76,761.64],"n_rows":5,"n_cols":3,"columns":["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of non-\nenhanced head CT images. The device\nis intended to assist hospital networks\nand appropriately trained medical\nspecialists in workflow triage by\nflagging and communication of\nsuspected positive findings of\npathologies in head CT images, namely\nIntracranial Hemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected ICH on a\nstandalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of non-\nenhanced head CT images in adults or\ntransitional adolescents aged 18 and\nolder. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication of\nsuspected positive findings of\nIntracranial Hemorrhage (ICH)\npathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with for cases with\nsuspected ICH findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],"rows":[["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of non-\nenhanced head CT images. The device\nis intended to assist hospital networks\nand appropriately trained medical\nspecialists in workflow triage by\nflagging and communication of\nsuspected positive findings of\npathologies in head CT images, namely\nIntracranial Hemorrhage (ICH).\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected ICH on a\nstandalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of non-\nenhanced head CT images in adults or\ntransitional adolescents aged 18 and\nolder. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage\nby flagging and communication of\nsuspected positive findings of\nIntracranial Hemorrhage (ICH)\npathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with for cases with\nsuspected ICH findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of\ninterest","Head","Head"],["Data\nacquisition\nprotocol","Non-enhanced CT scan of the head or\nneck","Non-enhanced CT scan of the head or\nneck"],["Notification-\nonly\n(/notification","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221240-p7-t0","doc_id":"K221240","page_num":7,"bbox":[77.66,72.24,548.76,473.11],"n_rows":6,"n_cols":3,"columns":["alerts), parallel\nworkflow tool","",""],"rows":[["alerts), parallel\nworkflow tool","",""],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion criteria\nNon-enhanced head or neck CT\n●\nprotocol with a 64-slice scanner or\nhigher.\nScans performed on adults/\n●\ntransitional adults ≥ 18 years of age.\nSlice thickness 0.625mm – 5.0mm.\n●\nExclusion Criteria\nAll scans that are technically\n●\ninadequate, including motion\nartifacts, severe metal artifacts,\nsuboptimal bolus timing or an\ninadequate field of view.","Inclusion criteria\nNon-enhanced head or neck CT\n●\nprotocol with a 64-slice scanner or\nhigher.\nScans performed on adults/\n●\ntransitional adults ≥ 18 years of age.\nSlice thickness 0.625 mm – 5.0 mm.\n●\nExclusion Criteria\nAll scans that are technically\n●\ninadequate, including motion\nartifacts, severe metal artifacts,\nsuboptimal bolus timing or an\ninadequate field of view."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","● AHS module (image acquisition);\n● ACS module (image processing));\n● Aidoc Worklist application for\nworkflow integration (worklist and\nnon-diagnostic Image Viewer).","● AHS module ( image acquisition);\n● ACS module (image processing));\n● Aidoc Desktop application for\nworkflow integration (non-\ndiagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221240-p8-t0","doc_id":"K221240","page_num":8,"bbox":[101.83,364.57,493.36,511.06],"n_rows":12,"n_cols":6,"columns":["Time -to-notification","Mean","95% Lower","95% Upper","Median","IQR"],"rows":[["Time -to-notification","Mean","95% Lower","95% Upper","Median","IQR"],["","","","","",""],["","Estimate","CL","CL","",""],["(in seconds)","","","","",""],["","","","","",""],["","","","","",""],["Predicate K203508","267.6","246.0","289.8","N/A","N/A"],["","","","","",""],["Processing Time","","","","",""],["BriefCase Time-to-","33.5","30.9","36.1","30.4","20.2"],["","","","","",""],["notification","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p5-t0","doc_id":"K221241","page_num":5,"bbox":[72.5,560.47,540.34,706.06],"n_rows":5,"n_cols":4,"columns":["","Subject","Predicate","Comparison"],"rows":[["","Subject","Predicate","Comparison"],["510(k) Number","Subject of submission","K190362","Subject Device Under\nReview"],["Device Name","DrAidTM for Radiology\nv1","HealthPNX","Subject Device Under\nReview"],["Manufacturer","VinBrain Joint Stock\nCompany","Zebra Medical Vision Ltd.","Subject Device Under\nReview"],["Regulation\nNumber","892.2080, Radiological\ncomputer aided triage and\nnotification software","892.2080, Radiological\ncomputer aided triage and\nnotification software","Identical"]],"caption_candidate":"A comparison of the subject and predicate device is provided in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p6-t0","doc_id":"K221241","page_num":6,"bbox":[72.5,75.96,540.34,727.66],"n_rows":6,"n_cols":4,"columns":["","Subject","Predicate","Comparison"],"rows":[["","Subject","Predicate","Comparison"],["Product Code","QFM, Radiological\nComputer-Assisted\nPrioritization Software\nFor Lesions","QFM, Radiological\nComputer-Assisted\nPrioritization Software For\nLesions","Identical"],["Target Anatomy","Chest/Lung","Chest/Lung","Identical"],["Image Modality","Frontal Chest X-ray","Frontal Chest X-ray","Identical"],["Targeted Clinical\nCondition","Pneumothorax","Pneumothorax","Identical"],["Indications for\nUse","The DrAid™ for\nRadiology v1 is a\nradiological computer-\nassisted triage &\nnotification software\nproduct designed to aid\nthe clinical assessment of\nadult Chest X-Ray cases\nwith features suggestive\nof pneumothorax in\nmedical care\nenvironment. DrAid™\nanalyzes cases using an\nartificial intelligence\nalgorithm to features\nsuggestive of suspected\nfindings. It makes case-\nlevel output available to a\nPACS for worklist\nprioritization or triage.\nAs a passive notification\nfor prioritization-only\nsoftware tool with\nstandard of care\nworkflow, DrAid™ does\nnot send a proactive alert\ndirectly to appropriately\ntrained medical\nspecialists. DrAid™ is\nnot intended to direct\nattention to specific\nportions or anomalies of\nan image. Its results are\nnot intended to be used\non a stand-alone basis for\nclinical decision-making\nnor is it intended to rule","The Zebra Pneumothorax\ndevice is a software\nworkflow tool designed to\naid the clinical assessment\nof adult Chest X-Ray cases\nwith features suggestive of\nPneumothorax in the\nmedical care environment.\nHealthPNX analyzes cases\nusing an artificial\nintelligence algorithm to\nidentify suspected findings.\nIt makes case-level output\navailable to a\nPACS/workstation for\nworklist prioritization or\ntriage. HealthPNX is not\nintended to direct attention\nto specific portions or\nanomalies of an image. Its\nresults are not intended to\nbe used on a stand-alone\nbasis for clinical decision-\nmaking nor is it intended to\nrule out Pneumothorax or\notherwise preclude clinical\nassessment of X-Ray\ncases.","Similar; different only\nin semantics but not\nsubstance."]],"caption_candidate":"Appendix F: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p7-t0","doc_id":"K221241","page_num":7,"bbox":[72.5,75.96,540.34,728.02],"n_rows":14,"n_cols":4,"columns":["","Subject","Predicate","Comparison"],"rows":[["","Subject","Predicate","Comparison"],["","out pneumothorax or\notherwise preclude\nclinical assessment of X-\nRay cases.","",""],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Identical"],["User","Radiologist","Radiologist","Identical"],["Radiological\nimages format","DICOM","DICOM","Identical"],["Computational\nPlatform","DrAid is designed as a\nsoftware module that can\nbe deployed on several\ncomputing and X-ray\nimaging platforms such\nas radiological imaging\nequipment, PACS, On\nPremise or On Cloud","HealthPNX is designed as\na software module that can\nbe deployed on PACS and\nStandalone desktop\napplication, Zebra\nWorklist.","Similar"],["Alert to finding","Passive notification\nflagged for review","Passive notification\nflagged for review","Identical"],["Independent of\nstandard of care\nworkflow","Yes; No cases are\nremoved from worklist","Yes; No cases are removed\nfrom worklist","Identical"],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Identical"],["Limited to\nanalysis of\nimaging data","Yes","Yes","Identical"],["Aids prompt\nidentification of\ncases with\nindicated findings","Yes","Yes","Identical"],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Identical"],["Performance level\n– Timing of\nnotification","Passive notification is\nvisible upon transfer to\nthe PACS with a delay of\nabout 3.83 minutes for\nimage transfer to the\ncloud, computation, and\nresults transfer.","Passive notification is\nvisible upon transfer to the\nPACS with a delay of\nabout 22.1 seconds for\nimage transfer to the cloud,\ncomputation, and\nresults transfer.","Similar"],["Total Validation\nData","Total: 850 chest X-ray\ncases","Total: 588 chest X-ray\ncases","Similar"]],"caption_candidate":"Appendix F: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p8-t0","doc_id":"K221241","page_num":8,"bbox":[72.5,75.96,540.34,330.89],"n_rows":3,"n_cols":4,"columns":["","Subject","Predicate","Comparison"],"rows":[["","Subject","Predicate","Comparison"],["","Positive Pneumothorax:\n354 cases\nNegative Pneumothorax:\n496 cases","Positive Pneumothorax:\n146 cases\nNegative Pneumothorax:\n442 cases",""],["Performance","AUC: 96.10% (95% CI:\n[94.73, 97.30])\nSensitivity: 94.61% (95%\nCI: [92.16, 96.76])\nSpecificity:97.58% (95%\nCI: [96.36, 98.65])","AUC: 98.3% (95% CI:\n[97.40, 99.02])\nSensitivity: 93.15% (95%\nCI: [87.76%, 96.67%])\nSpecificity: 92.99% (95%\nCI: [90.19%, 95.19%])","Similar"]],"caption_candidate":"Appendix F: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p9-t0","doc_id":"K221241","page_num":9,"bbox":[60.6,164.9,551.5,235.82],"n_rows":4,"n_cols":5,"columns":["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],"rows":[["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],["Sensitivity","0.9387","0.0180","0.9721","0.8994"],["Specificity","0.9947","0.0036","1.0000","0.9845"],["AUC","0.9667","0.0091","0.9834","0.9473"]],"caption_candidate":"table of the results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p9-t1","doc_id":"K221241","page_num":9,"bbox":[60.6,263.93,551.5,435.55],"n_rows":12,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Number of Images","565"],["Number of Patients","565"],["Male","326"],["Female","239"],["Age (22 – 35)","102"],["Age (35-60)","295"],["Age (> 60)","168"],["Ethnicity","Representative of the US Population"],["View Position (AP)","380"],["View Position (PA)","185"],["Scanner Type","Unknown"]],"caption_candidate":"A summary of the NIH data set characteristics are provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p9-t2","doc_id":"K221241","page_num":9,"bbox":[60.6,546.43,528.22,627.82],"n_rows":4,"n_cols":5,"columns":["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],"rows":[["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],["Sensitivity","0.9535","0.0160","0.9826","0.9186"],["Specificity","0.9464","0.0126","0.9687","0.9216"],["AUC","0.9500","0.0102","0.9691","0.9288"]],"caption_candidate":"table of the results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p9-t3","doc_id":"K221241","page_num":9,"bbox":[60.6,683.5,551.5,726.46],"n_rows":3,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Number of Images","285"],["Number of Patients","285"]],"caption_candidate":"A summary of the Vietnamese data set characteristics are provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p10-t0","doc_id":"K221241","page_num":10,"bbox":[60.6,75.96,551.5,233.3],"n_rows":11,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Male","202"],["Female","83"],["Age (22 – 35)","52"],["Age (35-60)","102"],["Age (60-80)","131"],["Ethnicity","Vietnamese"],["Cannon (CXDI Control Software NE)","30"],["Siemens (Fluorospot Compact FD)","82"],["Conmed (Titan 2000)","22"],["GE (GE Healthcare)","151"]],"caption_candidate":"Appendix F: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p10-t1","doc_id":"K221241","page_num":10,"bbox":[60.6,275.21,528.22,346.25],"n_rows":4,"n_cols":5,"columns":["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],"rows":[["Metrics","Mean","Standard\nDeviation","Upper 95% CI\nbound","Lower 95% CI\nbound"],["Sensitivity","0.9461","0.0117","0.9676","0.9216"],["Specificity","0.9758","0.0056","0.9865","0.9636"],["AUC","0.9610","0.0065","0.9730","0.9473"]],"caption_candidate":"The aggregate results for both the NIH and Vietnamese data sets are provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221241-p10-t2","doc_id":"K221241","page_num":10,"bbox":[60.6,401.93,453.31,472.99],"n_rows":4,"n_cols":4,"columns":["Metrics","Mean","Upper 95% CI\nbound","Lower 95% CI\nbound"],"rows":[["Metrics","Mean","Upper 95% CI\nbound","Lower 95% CI\nbound"],["Sensitivity","93.15","87.76","96.67"],["Specificity","92.99","90.19","95.19"],["AUC","98.3","97.40","99.02"]],"caption_candidate":"predicate results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p6-t0","doc_id":"K221248","page_num":6,"bbox":[78.22,106.43,512.9,718.7],"n_rows":7,"n_cols":3,"columns":["Parameter","Rapid LVO (K200941)","Rapid LVO"],"rows":[["Parameter","Rapid LVO (K200941)","Rapid LVO"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Intended Use/\nIndications for Use","Rapid LVO is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of CTA head\nimages. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive Large Vessel\nOcclusion (LVO) findings in head\nCTA images.\nRapid LVO uses a software\nalgorithm to analyze images and\nhighlight cases with suspected\nLVO on a server or standalone\ndesktop application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected LVO findings.\nNotifications include compressed\npreview images, that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of Rapid LVO are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","Rapid LVO is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of CTA head\nimages. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive ICA or MCA-M1\nLarge Vessel Occlusion (LVO)\nfindings in head CTA images.\nRapid LVO uses a software\nalgorithm to analyze images and\nhighlight cases with suspected LVO\non a server or standalone desktop\napplication in parallel to the ongoing\nstandard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected LVO findings.\nNotifications include compressed\npreview images. These are meant\nfor informational purposes only and\nare not intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be used\nas a diagnostic device.\nThe results of Rapid LVO are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care."],["PACS Functionality","",""],["Stroke/Head","Intracranial Stroke/Head","Same"],["Region of Interest","ICA and MCA-M1","Same"]],"caption_candidate":"LVO that is the subject of this Special 510(k) submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p7-t0","doc_id":"K221248","page_num":7,"bbox":[78.15,72.83,512.94,520.89],"n_rows":16,"n_cols":3,"columns":["Parameter","Rapid LVO (K200941)","Rapid LVO"],"rows":[["Parameter","Rapid LVO (K200941)","Rapid LVO"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Computer Platform","Standard off-the-shelf PC\nworkstation/server","Same"],["","Virtual platform such as VMware","Same"],["DICOM\nCompliance","Yes","Same"],["Imaging Type","CT Angiography","Same"],["Data Acquisition","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities","Same"],["Technical Implementation","",""],["SaMD","Traditional Algorithms","Same"],["Notification/Workflow","",""],["Pathways","PACS, email, mobile","Same"],["Preview/Prioritizati\non","Notification Message of Suspected\nLVO.\nPresentation of a compressed preview\nof the study for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains.","Same"],["SoC Workflow","In parallel to the SoC","Same"],["Original Image","No Alteration","Same"],["Primary Users","Clinician","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p8-t0","doc_id":"K221248","page_num":8,"bbox":[112.65,605.16,499.24,714.55],"n_rows":7,"n_cols":12,"columns":["","LVO Performance by Geography","","","","","","","","","",""],"rows":[["","LVO Performance by Geography","","","","","","","","","",""],["Location","Location","Measure","Measure","Estimate","","","Lower 95%","","Upper 95% CI","Upper 95% CI",""],["","","","","","","","CI","","","",""],["US","","","Se","","0.963","","0.897","","","0.987",""],["","","","Sp","","0.963","","0.875","","","0.990",""],["OUS","","","Se","","0.964","","0.823","","","0.994",""],["","","","Sp","","1.000","","0.934","","","1.000",""]],"caption_candidate":"Demographics:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p9-t0","doc_id":"K221248","page_num":9,"bbox":[112.59,92.16,499.3,177.84],"n_rows":6,"n_cols":11,"columns":["","LVO Performance by Gender","","","","","","","","",""],"rows":[["","LVO Performance by Gender","","","","","","","","",""],["","Location","","","Measure","Estimate","Lower 95% CI","","","Upper 95% CI",""],["Female","","","Se","","0.981","0.902","","0.997","",""],["","","","Sp","","1.000","0.923","","1.000","",""],["Male","","","Se","","0.963","0.875","","0.990","",""],["","","","Sp","","0.968","0.890","","0.991","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p9-t1","doc_id":"K221248","page_num":9,"bbox":[112.59,210.24,499.3,331.32],"n_rows":8,"n_cols":11,"columns":["","Age Group Performance","","","","","","","","",""],"rows":[["","Age Group Performance","","","","","","","","",""],["","Age Groups","","","Measure","Estimate","Lower 95% CI","","","Upper 95% CI",""],["20-39","","","Se","","1.000","0.646","","1.000","",""],["","","","Sp","","1.000","0.722","","1.000","",""],["40-59","","","Se","","1.000","0.883","","1.000","",""],["","","","Sp","","0.974","0.868","","0.995","",""],["60+","","","Se","","0.959","0.886","","0.986","",""],["","","","Sp","","0.983","0.909","","0.997","",""]],"caption_candidate":"Sp 0.968 0.890 0.991","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p9-t2","doc_id":"K221248","page_num":9,"bbox":[112.59,363.72,499.3,487.93],"n_rows":8,"n_cols":13,"columns":["","Performance by Scanner Manufacturer","","","","","","","","","","",""],"rows":[["","Performance by Scanner Manufacturer","","","","","","","","","","",""],["","Brand","","","Measure","","Estimate","","Lower 95% CI","","","Upper 95% CI",""],["GE","","","","Se","","0.969","","0.893","","","0.991",""],["","","","","Sp","","0.970","","0.847","","","0.995",""],["SIEMENS","","","","Se","","1.000","","0.785","","","1.000",""],["","","","","Sp","","0.978","","0.887","","","0.996",""],["TOSHIBA","","","","Se","","0.929","","0.774","","","0.980",""],["","","","","Sp","","1.000","","0.879","","","1.000",""]],"caption_candidate":"Scanner/Manufacturer:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p9-t3","doc_id":"K221248","page_num":9,"bbox":[106.35,520.44,505.65,611.16],"n_rows":6,"n_cols":11,"columns":["","LVO Performance by Slice Thickness","","","","","","","","",""],"rows":[["","LVO Performance by Slice Thickness","","","","","","","","",""],["","Thickness(mm)","","","Measure","Estimate","Lower 95% CI","","","Upper 95% CI",""],["≤ 0.65","","","Se","","0.981","0.899","","0.997","",""],["","","","Sp","","0.959","0.863","","0.989","",""],["> 0.65","","","Se","","0.965","0.881","","0.990","",""],["","","","Sp","","1.000","0.939","","1.000","",""]],"caption_candidate":"Sp 1.000 0.879 1.000","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221248-p10-t0","doc_id":"K221248","page_num":10,"bbox":[117.67,72.36,494.33,231.48],"n_rows":10,"n_cols":5,"columns":["Reference LVO by Site","","","",""],"rows":[["Reference LVO by Site","","","",""],["Location","Study/Site","1","0","All"],["US","Study/Site 1","65","3","68"],["","Study/Site 2","0","29","29"],["","Study/Site 3","16","0","16"],["","Study/Site 4","0","15","15"],["","Study/Site 5","0","7","7"],["OUS","Study/Site 6","1","27","28"],["","Study/Site 7","11","26","37"],["","Study/Site 8","16","1","17"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p7-t0","doc_id":"K221305","page_num":7,"bbox":[72.32,175.26,539.8,715.42],"n_rows":5,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Reference Device",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Reference Device",""],["Device\nManufacturer","","","Siemens","","","Siemens","","","MIM Software Inc.","",""],["Device Name","","","AI-Rad Companion\nOrgans RT\n(SW Version VA40)","","","AI-Rad Companion\nOrgans RT\n(SW Version VA20)","","","Contour ProtégéAI","",""],["","510(k) Number","","","K221305","","","K193562","","","K213976",""],["Indications for\nUse","","","AI-Rad Companion\nOrgans RT is a post-\nprocessing software\nintended to\nautomatically contour\nDICOM CT imaging\ndata using deep-\nlearning-based\nalgorithms.\nContours that are\ngenerated by AI-Rad\nCompanion Organs RT\nmay be used as input\nfor clinical workflows\nincluding external\nbeam radiation therapy\ntreatment planning.\nAI-Rad Companion\nOrgans RT must be\nused in conjunction\nwith appropriate\nsoftware such as\nTreatment Planning\nSystems and\nInteractive Contouring\napplications, to review,","","","AI-Rad Companion\nOrgans RT is a post-\nprocessing software\nintended to\nautomatically contour\nDICOM CT imaging\ndata using deep-\nlearning-based\nalgorithms.\nContours that are\ngenerated by AI-Rad\nCompanion Organs RT\nmay be used as input\nfor clinical workflows\nincluding external\nbeam radiation therapy\ntreatment planning. AI-\nRad Companion\nOrgans RT must be\nused in conjunction\nwith appropriate\nsoftware such as\nTreatment Planning\nSystems and\nInteractive Contouring\napplications, to review,","","","Trained medical\nprofessionals use\nContour ProtégéAI as a\ntool to assist in the\nautomated processing\nof digital medical\nimages of modalities\nCT and MR, as\nsupported by\nACR/NEMA DICOM\n3.0. In addition,\nContour ProtégéAI\nsupports the following\nindications:\n• Creation of\ncontours using\nmachine-learning\nalgorithms for\napplications\nincluding, but not\nlimited to,\nquantitative\nanalysis, aiding\nadaptive therapy,\ntransferring\ncontour to radiation","",""]],"caption_candidate":"effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p8-t0","doc_id":"K221305","page_num":8,"bbox":[72.26,75.72,539.86,700.54],"n_rows":5,"n_cols":4,"columns":["","edit, and accept\ncontours generated by\nAI-Rad Companion\nOrgans RT.\nThe output of AI-Rad\nCompanion Organs RT\nin the format of\nRTSTRUCT objects\nare intended to be used\nby trained medical\nprofessionals.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","edit, and accept\ncontours generated by\nAI-Rad Companion\nOrgans RT.\nThe output of AI-Rad\nCompanion Organs RT\nin the format of\nRTSTRUCT objects\nare intended to be used\nby trained medical\nprofessionals.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","therapy treatment\nplanning systems,\nand archiving\ncontours for patient\nfollow-up and\nmanagement.\n• Segmenting normal\nstructures across a\nvariety of CT\nanatomical\nlocations\n• And segmenting\nnormal structures\nof the prostate,\nseminal vesicles,\nand urethra within\nT2-weighted MR\nimages.\nAppropriate image\nvisualization software\nmust be used to review\nand, if necessary, edit\nresults automatically\ngenerated by Contour\nProtégéAI."],"rows":[["","edit, and accept\ncontours generated by\nAI-Rad Companion\nOrgans RT.\nThe output of AI-Rad\nCompanion Organs RT\nin the format of\nRTSTRUCT objects\nare intended to be used\nby trained medical\nprofessionals.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","edit, and accept\ncontours generated by\nAI-Rad Companion\nOrgans RT.\nThe output of AI-Rad\nCompanion Organs RT\nin the format of\nRTSTRUCT objects\nare intended to be used\nby trained medical\nprofessionals.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","therapy treatment\nplanning systems,\nand archiving\ncontours for patient\nfollow-up and\nmanagement.\n• Segmenting normal\nstructures across a\nvariety of CT\nanatomical\nlocations\n• And segmenting\nnormal structures\nof the prostate,\nseminal vesicles,\nand urethra within\nT2-weighted MR\nimages.\nAppropriate image\nvisualization software\nmust be used to review\nand, if necessary, edit\nresults automatically\ngenerated by Contour\nProtégéAI."],["Algorithm","Deep Learning","Deep Learning","Marchine-learning"],["Segmentation of\nOrgan at Risk in\nthe Anatomic\nRegions","Head & Neck, Thorax,\nAbdomen & Pelvis\nHead & Neck lymph\nnodes\n(108 OAR)","Head & Neck, Thorax,\nAbdomen & Pelvis\n(79 OAR)","Head & Neck,\nProstate, Thorax,\nAbdomen, Lungs &\nLiver, MRT structures\n(spleen, pelvic lymph\nnodes, descending\naorta, bone)"],["Compatible\nModality","CT Images","CT Images","CT & MR"],["Compatible\nScanner Models","No Limitation on\nscanner model,\nDICOM compliance\nrequired.","No Limitation on\nscanner model,\nDICOM compliance\nrequired.","No information\npublicly available"]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p9-t0","doc_id":"K221305","page_num":9,"bbox":[72.26,75.72,539.86,712.54],"n_rows":7,"n_cols":4,"columns":["Compatible\nTreatment\nPlanning System","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No information\npublicly available"],"rows":[["Compatible\nTreatment\nPlanning System","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No information\npublicly available"],["Contraindications","Adult use only","Adult use only","Adult use only"],["Target\nPopulation","AI-Rad Companion\nOrgans RT is designed\nfor use only in adult\npopulations.\nAI-Rad Companion\nOrgans RT is designed\nfor any patient for\nwhom relevant\nmodality scans are\navailable. More\nspecifically, the\nsoftware is validated\non previously acquired\nCT DICOM volumes\nfor radiation therapy\ntreatment planning,\nincluding, head and\nneck, thorax, abdomen,\nand pelvis.","AI-Rad Companion\nOrgans RT is designed\nfor use only in adult\npopulations.\nAI-Rad Companion\nOrgans RT is designed\nfor any patient for\nwhom relevant\nmodality scans are\navailable. More\nspecifically, the\nsoftware is validated\non previously acquired\nCT DICOM volumes\nfor radiation therapy\ntreatment planning,\nincluding, head and\nneck, thorax, abdomen,\nand pelvis.","No information\npublicly available"],["Clinical\ncondition the\ndevice is\nintended to\ndiagnose, treat or\nmanage","Limited to patients\npreviously selected for\nRadiation Therapy.","Limited to patients\npreviously selected for\nRadiation Therapy.","No information\npublicly available"],["Software\nArchitecture","AI-Rad Companion\n(Engine) architecture\nenabling the\ndeployment of AI Rad\nCompanion Organs RT\nusing Edge and in the\nCloud. The UI is\nprovided using a web-\nbased interface.","AI-Rad Companion\n(Engine) architecture\nenabling the\ndeployment of AI Rad\nCompanion Organs RT\nin the Cloud. The UI is\nprovided using a web-\nbased interface.","Server-based\napplication supporting\nLinux-based OS and\nLocal deployment on\nWindows or Mac"],["Deployment\nFeature","Edge & Cloud\nDeployment","Cloud Deployment","Cloud-based or locally\ndeployed"],["Organ Templates","Creating, editing and\ndeletion of organ\ntemplates. Customize","Creating, editing and\ndeletion of organ\ntemplates. Customize","No information\npublicly available"]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p10-t0","doc_id":"K221305","page_num":10,"bbox":[72.26,75.72,539.86,707.74],"n_rows":4,"n_cols":4,"columns":["","predefined structure\ndatabase with mapping\nto international\nnomenclature schemes.","predefined structure\ndatabase with mapping\nto international\nnomenclature schemes.",""],"rows":[["","predefined structure\ndatabase with mapping\nto international\nnomenclature schemes.","predefined structure\ndatabase with mapping\nto international\nnomenclature schemes.",""],["Automated\nworkflow","AI-Rad Companion\nOrgans RT\nautomatically\nprocesses input image\ndata and sends the\nresults as DICOM-RT\nStructure Sets to a\nuser-configurable\ntarget node.","AI-Rad Companion\nOrgans RT\nautomatically\nprocesses input image\ndata and sends the\nresults as DICOM-RT\nStructure Sets to a\nuser-configurable\ntarget node.","Automatic contouring\nworking using\nmachine-learning"],["Contour\nvisualization and\nediting feature","AI-Rad Companion\nOrgans RT provides\nbasic result preview of\nautomatic\nsegmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","AI-Rad Companion\nOrgans RT provides\nbasic result preview of\nautomatic\nsegmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","No information\npublicly available"],["Segmentation\nPerformance","The target performance\nwas validated using\n113 cases distributed\nto two cohorts. Cohort\nA is clinical routine\ntreatment planning CT\nand it is split into two\nsub-cohort and Cohort\nB is PET-CT data. To\nobjectively evaluate\nthe target performance,\nthe DICE coefficient,\nthe absolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject and reference\ndevice were equivalent\nas well as the overall\nperformance compared\nto the predicate device.","The target performance\nwas validated using\n113 cases distributed to\ntwo cohorts. Cohort\nA-Clinical Routine\nTreatment Planning\nCT (Siemens; Head\nand Neck, Thorax and\nAbdomen Pelvis) and\nCohort B-Multi\nVendor Coverage (GE\nand Phillips; Head and\nNeck).\nTo objectively evaluate\nthe target performance,\nthe DICE coefficient,\nthe absolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject and reference","739 CT Images from\n12 clinical sites were\nused for testing. The\nmean and standard\ndeviation Dice\ncoefficients, along with\nthe lower 95th\npercentile confidence\nbound were calculated."]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p11-t0","doc_id":"K221305","page_num":11,"bbox":[72.26,75.72,539.86,341.33],"n_rows":5,"n_cols":4,"columns":["","","device were equivalent\nas well as the overall\nperformance compared\nto the predicate device.",""],"rows":[["","","device were equivalent\nas well as the overall\nperformance compared\nto the predicate device.",""],["User Interface –\nResults Preview\n(Confirmation)","Basic visualization\nfunctionality of\noriginal data and\ngenerated contours","Basic visualization\nfunctionality of\noriginal data and\ngenerated contours","No information\npublicly available"],["User Interface\nConfiguration","Configuration UI","Configuration UI","No information\npublicly available"],["Automated\nWorkflow to TPS","Results send to\nConfirmation UI &\nOptional bypassing of\nConfirmation UI to\nTPS","Results send to\nConfirmation UI &\nOptional bypassing of\nConfirmation UI to\nTPS","No information\npublicly available"],["Human Factors","Design to be used by\ntrained clinicians.","Design to be used by\ntrained clinicians.","Designed to be used by\ntrained clinicians"]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p11-t1","doc_id":"K221305","page_num":11,"bbox":[83.46,572.5,528.77,708.22],"n_rows":5,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","62366-1: 2015-\n02","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to\nmedical devices","14971:2007","","","ISO","",""]],"caption_candidate":"Standards (Table 2).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p12-t0","doc_id":"K221305","page_num":12,"bbox":[83.42,75.72,528.82,373.73],"n_rows":5,"n_cols":5,"columns":["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","AAMI\nANSI\nIEC"],"rows":[["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","AAMI\nANSI\nIEC"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n(2016)","NEMA"],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1 1994-\n02-15","ISO\nIEC"],["5-134","General","Medical devices – symbols to\nbe used with information to\nbe supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","ISO\nIEC"],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","IEC"]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p14-t0","doc_id":"K221305","page_num":14,"bbox":[72.33,75.84,539.83,348.77],"n_rows":3,"n_cols":6,"columns":["","Validation Testing Subject","","","Acceptance Criteria",""],"rows":[["","Validation Testing Subject","","","Acceptance Criteria",""],["Organs in Predicate Device","","","• All the organs segmented in the predicate\ndevice are also segmented in the subject\ndevice\n• The lower bound of 95th percentile CI of\nthe segmentation is greater than 0.1 Dice\nlower than the mean of the predicate\ndevice segmentation","",""],["Head & Neck Lymph Nodes","","","• The overall fail rate of each\norgan/anatomical structures is smaller\nthan 15%\n• The lower bound of 95th percentile CI of\nthe segmentation is greater than 0.1 Dice\nlower than the mean of the reference\ndevice segmentation","",""]],"caption_candidate":"K221305","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p14-t1","doc_id":"K221305","page_num":14,"bbox":[72.33,380.57,517.59,516.91],"n_rows":4,"n_cols":11,"columns":["","","DICE","","","","ASSD","","","",""],"rows":[["","","DICE","","","","ASSD","","","",""],["","","Median","","","95% CI (Bootstrap)","Median","","","95% CI (Bootstrap)",""],["AI-Rad\nCompanion\nOrgans RT VA40","0.85","","","[80.23,84.61]","","0.93","","[0.86,1.14]","",""],["AI-Rad\nCompanion\nOrgans RT VA20","0.85","","","N.A","","0.94","","[0.85.1.16]","",""]],"caption_candidate":"Table 3: Acceptance Criteria of AIRC Organs RT VA40","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p14-t2","doc_id":"K221305","page_num":14,"bbox":[67.5,548.71,535.48,697.78],"n_rows":4,"n_cols":9,"columns":["","AI-Rad Companion Organs RT VA40\n(Head and Neck lymph node class)","","","","Contour ProtégéAI from MIM\nSoftware Inc\n(Pelvic lymph node class)","","",""],"rows":[["","AI-Rad Companion Organs RT VA40\n(Head and Neck lymph node class)","","","","Contour ProtégéAI from MIM\nSoftware Inc\n(Pelvic lymph node class)","","",""],["","","Sample Size: 60\n# of Datasites: 5","","","Sample Size: 739\n# of Datasites: 12","","",""],["","Avg","","Std","95 % CI Bootstrap","Avg","Std","95 % CI\nBootstrap",""],["Dice [%]","81.32","","3.45","[80.32,82.12]","80","4","[77,N.A]",""]],"caption_candidate":"Table 4: Performance comparison between subject device and predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p15-t0","doc_id":"K221305","page_num":15,"bbox":[72.27,157.22,535.64,389.45],"n_rows":8,"n_cols":8,"columns":["","","","","Cohort A","","Cohort B",""],"rows":[["","","","","Cohort A","","Cohort B",""],["# of Subject","","","73","","40","",""],["# of Clinical Sites","","","3\n(Germany: 14, Brazil: 59)","","4\n(Canada: 40)","",""],["Sex","","","Male: 25\nFemale: 48","","Male: 19\nFemale: 21","",""],["Age","","",">40: 7\nUnknown: 66\n*unknown due to data\nminimization on customer site","","<30: 0\n30 – 50: 3\n50 – 70: 25\n>70: 12","",""],["Manufacturer","","","Siemens: 73","","GE: 18\nPhilips: 22","",""],["Body Region","","","Head & Neck: 24\nThorax: 19\nAbdomen Pelvis: 30","","Head & Neck: 40","",""],["Slice Thickness","","","<1 to > 3","","<1 to >3","",""]],"caption_candidate":"Table 5: Performance comparison between subject device and reference device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221305-p15-t1","doc_id":"K221305","page_num":15,"bbox":[72.27,416.33,539.86,714.82],"n_rows":6,"n_cols":2,"columns":["# of Datasets","160"],"rows":[["# of Datasets","160"],["Data Origin","Stanford (US): 15\nNNord (DE): 4\nUKH (DE): 25\nHCG (IND): 116"],["Sex","Male: 12\nFemale: 17\nUnknown: 131"],["Age","<30 : 1\n30 – 50: 3\n50 – 70: 2\n>= 70: 3\nUnknown: 152*\n*unknown due to data minimization on customer\nsite"],["Manufacturer","Siemens: 103\nGE: 50\nUnknown: 7"],["Slice Thickness","<= 1: 1\n1 – 2: 12\n2 – 3 : 141\n>3: 6"]],"caption_candidate":"Table 6: Validation Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p6-t0","doc_id":"K221314","page_num":6,"bbox":[77.66,85.1,562.66,692.02],"n_rows":5,"n_cols":3,"columns":["","Predicate Device\nAidoc BriefCase for LVO triage (K203508)","Subject Device\nAidoc BriefCase for M1-LVO triage (K221314)"],"rows":[["","Predicate Device\nAidoc BriefCase for LVO triage (K203508)","Subject Device\nAidoc BriefCase for M1-LVO triage (K221314)"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of head CTA images.\nThe device is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage\nby flagging and communication of\nsuspected positive findings of Large Vessel\nOcclusion (LVO) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a\nstandalone desktop application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of head CTA images in\nadults or transitional adolescents aged 18 and\nolder. The device is intended to assist hospital\nnetworks and appropriately trained medical\nspecialists in workflow triage by flagging and\ncommunication of M1 Large Vessel Occlusion\n(M1-LVO) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a standalone\ndesktop application in parallel to the ongoing\nstandard of care image interpretation. The\nuser is presented with notifications for cases\nwith suspected findings. Notifications include\ncompressed preview images that are meant\nfor informational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of care."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately trained\nmedical specialists"],["Anatomical\nregion of interest","Head","Head"],["Data acquisition\nprotocol","Head CTA scans","Head CTA scans"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p7-t0","doc_id":"K221314","page_num":7,"bbox":[77.66,72.24,562.66,552.19],"n_rows":7,"n_cols":3,"columns":["","Predicate Device\nAidoc BriefCase for LVO triage (K203508)","Subject Device\nAidoc BriefCase for M1-LVO triage (K221314)"],"rows":[["","Predicate Device\nAidoc BriefCase for LVO triage (K203508)","Subject Device\nAidoc BriefCase for M1-LVO triage (K221314)"],["Notification-only\n(/notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion criteria\nfor clinical\nperformance\ntesting","Inclusion criteria\nHead CTA protocol with a 64-slice\n●\nscanner or higher;\nScans performed on\n●\nadults/transitional adults ≥ 18 years of\nage;\nSlice thickness 0.5 mm – 1.0 mm.\n●\nExclusion Criteria\nAll studies that are technically\n●\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, sub or an inadequate field of\nview.","Inclusion criteria\nHead CTA protocol with a 64-slice scanner\n●\nor higher;\nScans performed on adults/transitional\n●\nadults ≥ 18 years of age;\nSlice thickness 0.5 mm – 1.0 mm.\n●\nExclusion Criteria\nAll studies that are technically\n●\ninadequate, including studies with motion\nartifacts, severe metal artifacts, sub or an\ninadequate field of view."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with database\nof images."],["Structure","- AHS module (image acquisition);\n- ACS module (image processing));\n- Aidoc Worklist application for\nworkflow integration (worklist and\nnon-diagnostic Image Viewer).","- AHS module ( image acquisition);\n- ACS module (image processing));\n- Aidoc Desktop application for workflow\nintegration (non-diagnostic Image\nViewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p8-t0","doc_id":"K221314","page_num":8,"bbox":[117.22,326.19,494.9,445.18],"n_rows":8,"n_cols":12,"columns":["Parameter","","","N","Mean\nestimate","","Lower","","","Upper\nConfidence\nLimit","Median",""],"rows":[["Parameter","","","N","Mean\nestimate","","Lower","","","Upper\nConfidence\nLimit","Median",""],["","","","","","","Confidence","","","","",""],["","","","","","","Limit","","","","",""],["","Time-to-notification","","111","3.8","3.6","","","4.0","","3.8",""],["","of BriefCase M1-LVO","","","","","","","","","",""],["","Time-to-notification","","59","4.46","4.10","","","4.83","","-",""],["","of BriefCase ICH","","","","","","","","","",""],["","K180647","","","","","","","","","",""]],"caption_candidate":"Table 2. Time-to-Notification Comparison for BriefCase Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p8-t1","doc_id":"K221314","page_num":8,"bbox":[130.66,604.18,481.54,634.35],"n_rows":2,"n_cols":21,"columns":["","","","","Mean","","","Std","","","","","Min","","","Median","","","Max","N",""],"rows":[["","","","","Mean","","","Std","","","","","Min","","","Median","","","Max","N",""],["","Age (Y)","","","65.1","","","","17.5","","","","18.0","","","67.0","","","90.0","383",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p9-t0","doc_id":"K221314","page_num":9,"bbox":[250.45,87.14,364.16,196.58],"n_rows":5,"n_cols":7,"columns":["Gender","","","N","","","%"],"rows":[["Gender","","","N","","","%"],["Male","","","153","","3","9.9%"],["Female","","","227","","5","9.3%"],["Unknown","","","3","","","0.8%"],["All","","","383","","1","00.0"]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221314-p9-t1","doc_id":"K221314","page_num":9,"bbox":[244.25,226.82,364.16,358.25],"n_rows":6,"n_cols":6,"columns":["","Manufacturer","","","N","%"],"rows":[["","Manufacturer","","","N","%"],["","Siemens","","","32","8%"],["","GE","","","212","55%"],["","Canon","","","73","19%"],["","Philips","","","66","17%"],["","Total","","","383","100%"]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p6-t0","doc_id":"K221330","page_num":6,"bbox":[72.02,176.06,543.1,719.62],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],"rows":[["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\ncontrast enhanced chest CTs (but not\ndedicated CTPA protocol). The device\nis intended to assist hospital networks\nand trained medical specialists in\nworkflow triage by flagging and\ncommunication of suspect positive\ncases of incidental Pulmonary\nEmbolism (iPE) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag\nsuspect cases on a standalone desktop\napplication in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with notifications\nfor suspect cases. Notifications include\ncompressed preview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image and\nis not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for","BriefCase is a radiological computer-\naided triage and notification software\nindicated for use in the analysis of\nfrontal chest X-ray (CXR) images in\nadults or transitional adolescents aged\n18 and older. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage by\nflagging and communicating suspected\npositive cases of vertically\nmalpositioned endotracheal tube (ETT)\nin relation to the carina.\nFindings are flagged when the ETT\ndistal tip is assessed as being more\nthan 5 cm above the carina, less than 2\ncm above the carina, or when it is below\nthe carina (i.e in the right or left\nmainstem bronchus).\nThe device assesses solely the vertical\nposition of the ETT distal tip relative to\nthe carina, does not factor patient\npositioning, and cannot detect\nesophageal intubation. The device\ndoes not provide results when the\ncarina is not well-visualized on the x-ray\nimage. The device does not\ndiscriminate types of ETTs, as such a\nproperly positioned double lumen ETT\nmay trigger a false prioritization alert.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p7-t0","doc_id":"K221330","page_num":7,"bbox":[72.02,72.24,543.1,704.86],"n_rows":7,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],"rows":[["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],["","viewing full images per the standard of\ncare.","highlight cases with detected findings\non a standalone application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on the\nuser’s professional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images per\nthe standard of care."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of\ninterest","Chest","Chest"],["Data\nacquisition\nprotocol","Contrast-enhanced chest CTs (but not\ndedicated CTPA protocol)","Frontal Chest X-ray (CXR)"],["Notification-\nonly\n(/notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p8-t0","doc_id":"K221330","page_num":8,"bbox":[72.02,72.24,543.1,524.47],"n_rows":5,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],"rows":[["","Predicate Device\nAidoc Briefcase for iPE Triage\n(K203508)","Subject Device\nAidoc Briefcase for Vertically\nMalpositioned ETT in Relation to the\nCarina Triage (K221330)"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria","Inclusion criteria\n● Contrast-enhanced chest CTs (but\nnot dedicated CTPA protocol.\n● Single energy exams.\n● Scans performed with a 64 slice or\ngreater number of detectors.\n● Scans performed on adults/\ntransitional adults ≥ 18 years of age.\n● Slice thickness: 0.5mm – 2.0mm\naxial.\nExclusion Criteria\n● All studies that are technically\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, or inadequate field of view.","Inclusion criteria\n● Frontal Chest X-ray protocol.\n● Images performed on adults/\ntransitional adults ≥ 18 years of age.\nExclusion Criteria\n● All x-ray images that have\ninadequate field of view.The device\ndoes not provide results when the\ncarina is not well-visualized on the\nx-ray image."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","● AHS module (image acquisition);\n● ACS module (image processing);\n● Aidoc Worklist application for\nworkflow integration (worklist and\nnon-diagnostic Image Viewer).","● AHS module (orchestrator, image\nacquisition);\n● ACS module (image processing);\n● Aidoc Desktop application for\nworkflow integration (feed and non-\ndiagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p10-t0","doc_id":"K221330","page_num":10,"bbox":[130.65,179.58,481.57,227.43],"n_rows":3,"n_cols":20,"columns":["","","","","Mean","","","Std","","","Min","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","Median","","","Max","","","N",""],["","Age","","62.5","62.5","","17.0","17.0","","18.0","","64.0","64.0","","90","90","","921","921",""],["","(Years)","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p10-t1","doc_id":"K221330","page_num":10,"bbox":[174.06,283.11,438.09,425.27],"n_rows":6,"n_cols":16,"columns":["Ground\nTruth\nResults","","","","Gender","","","","","","","All","","","",""],"rows":[["Ground\nTruth\nResults","","","","Gender","","","","","","","All","","","",""],["","","","","Male","","","","Female","","","","","","",""],["","","","","N","","%","","N","%","","","N","","%",""],["","Positive","","","112","","12.16","","70","7.60","","","182","","19.76",""],["","Negative","","","427","","46.36","","311","33.77","","","738","","80.13",""],["","All","","","439","","58.52","","381","41.37","","","920*","","100.0",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p10-t2","doc_id":"K221330","page_num":10,"bbox":[216.1,481.19,396.02,622.26],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["","Carestream","","","358","","","38.9",""],["","Canon","","","223","","","24.2",""],["","Siemens","","","186","","","20.2",""],["","Philips","","","154","","","16.7",""],["","Total","","","921","","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221330-p11-t0","doc_id":"K221330","page_num":11,"bbox":[126.38,108.92,473.97,620.32],"n_rows":31,"n_cols":5,"columns":["Pathology","N","%","N","%"],"rows":[["Pathology","N","%","N","%"],["","","","",""],["","(w/o (w","/o ETT) (w","/ ETT) (","w/ ETT"],["","","","",""],["","ETT)","","",""],["","","","",""],["Fully Negative","84","11.4%","0","0.0%"],["","","","",""],["Other (non ETT ) tubes,lines","220","29.8%","164","22.2%"],["","","","",""],["and life support devices*","","","",""],["","","","",""],["Inflammatory","185","25.1%","57","7.7%"],["","","","",""],["Post op","133","18.0%","58","7.9%"],["","","","",""],["Cardiovascular","94","12.7%","45","6.1%"],["","","","",""],["Lung pathologies","46","6.2%","7","0.9%"],["","","","",""],["Pneumothorax","36","4.9%","5","0.7%"],["","","","",""],["Infectious","33","4.5%","6","0.8%"],["","","","",""],["Trauma","14","1.9%","2","0.3%"],["","","","",""],["Neoplastic","13","1.8%","3","0.4%"],["","","","",""],["Chronic diseases","2","0.3%","0","0.0%"],["","","","",""],["None of the above","28","3.8%","7","0.9%"]],"caption_candidate":"Pathology N % N %","well_formed":true,"extraction_settings":"text"}
{"table_id":"K221347-p5-t0","doc_id":"K221347","page_num":5,"bbox":[71.05,104.3,524.26,223.7],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara® 1.7.2"],"rows":[["Device trade name","Transpara® 1.7.2"],["Device","Radiological Computer Assisted Detection and Diagnosis\nSoftware"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Submission type","Traditional 510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221347-p5-t1","doc_id":"K221347","page_num":5,"bbox":[71.05,305.21,524.26,439.63],"n_rows":8,"n_cols":2,"columns":["Device trade name","Transpara® 1.7.0"],"rows":[["Device trade name","Transpara® 1.7.0"],["Legal Manufacturer","ScreenPoint Medical B.V."],["Device","Radiological Computer Assisted Detection and Diagnosis\nSoftware"],["Classification regulation","21 CFR 892.2090"],["Panel","Radiology"],["Device class","II"],["Product code","QDQ"],["Clearance number","K210404"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221347-p6-t0","doc_id":"K221347","page_num":6,"bbox":[88.82,165.08,541.17,227.54],"n_rows":4,"n_cols":2,"columns":["d) An exam score which categorizes exams on a scale of 1-10 with increasing",""],"rows":[["d) An exam score which categorizes exams on a scale of 1-10 with increasing",""],["","likelihood of cancer. The score is calibrated in such a way that approximately 10"],["","percent of mammograms in a population of mammograms without cancer falls in"],["","each category."]],"caption_candidate":"be utilized to enhance user interfaces and workflow.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221347-p7-t0","doc_id":"K221347","page_num":7,"bbox":[71.09,535.15,524.24,699.22],"n_rows":6,"n_cols":9,"columns":["","Standard ID","","","Standard Title","","","FDA Recognition #",""],"rows":[["","Standard ID","","","Standard Title","","","FDA Recognition #",""],["IEC 62366-1 Edition\n1.0 2015-02","","","Medical devices - Part 1: Application of usability\nengineering to medical devices [Including\nCORRIGENDUM 1 (2016)]","","","5-114","",""],["ISO, 14155 Second\nedition 2011-02-01,","","","Clinical investigation of medical devices for\nhuman subjects - Good clinical practice","","","2-205","",""],["ISO 14971:2019","","","Medical Devices - Application Of Risk\nManagement To Medical Devices","","","5-125","",""],["IEC 62304:2015","","","Medical Device Software - Software Life Cycle\nProcesses","","","13-79","",""],["IEC 82304-1: 2016","","","Health software - Part 1: General requirements\nfor product safety","","","13-97","",""]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221347-p9-t0","doc_id":"K221347","page_num":9,"bbox":[112.7,228.38,499.42,338.81],"n_rows":4,"n_cols":5,"columns":["","Number of\nExams","Normal","Benign","Cancer"],"rows":[["","Number of\nExams","Normal","Benign","Cancer"],["FFDM","5,867","4,841","149","877"],["DBT","4,823","3,988","240","595"],["Total","10,690","8,829","389","1,472"]],"caption_candidate":"Table 1: Data used for evaluation of stand-alone performance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221393-p5-t0","doc_id":"K221393","page_num":5,"bbox":[77.54,301.86,565.66,717.12],"n_rows":20,"n_cols":9,"columns":["","Specification","","","Subject Swoop® System","","","Predicate Swoop® System (K212456)",""],"rows":[["","Specification","","","Subject Swoop® System","","","Predicate Swoop® System (K212456)",""],["Intended Use/Indications for Use:","","","The Swoop® Portable MR Imaging\nSystem is a bedside magnetic\nresonance imaging device for\nproducing images that display the\ninternal structure of the head where\nfull diagnostic examination is not\nclinically practical. When interpreted\nby a trained physician, these images\nprovide information that can be\nuseful in determining a diagnosis.","","","Same","",""],["Patient Population:","","","Adult and pediatric patients (≥ 0\nyears)","","","Same","",""],["Anatomical Sites:","","","Head","","","Same","",""],["Environment of Use:","","","At the point of care in medical\nfacilities, including emergency rooms,\ncritical care units, hospital or\nrehabilitation rooms.","","","Same","",""],["Energy Used and/or delivered:","","","Magnetic Resonance","","","Same","",""],["","Magnet:","","","","","","",""],["Physical Dimensions","","","835 mm x 630 mm x 652 mm","","","Same","",""],["Bore Opening","","","610 mm x 315 mm","","","Same","",""],["Weight","","","320 kg","","","Same","",""],["Field Strength","","","63.3 mT permanent magnet","","","Same","",""],["","Gradient:","","","","","","",""],["Strength","","","24 mT/m","","","Same","",""],["Rise Time","","","1.1 ms","","","Same","",""],["Slew Rate","","","22 T/m/s","","","Same","",""],["Computer Display","","","Hyperfine-supplied tablet","","","Same","",""],["","RF Coils:","","","","","","",""],["Number of Coils","","","1 head coil","","","Same","",""],["Coil Type","","","TX/RX","","","Same","",""],["Coil Geometry","","","Form-fitting","","","Same","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221393-p6-t0","doc_id":"K221393","page_num":6,"bbox":[77.54,72.42,564.62,361.2],"n_rows":14,"n_cols":8,"columns":["","Specification","","","Subject Swoop® System","","","Predicate Swoop® System (K212456)"],"rows":[["","Specification","","","Subject Swoop® System","","","Predicate Swoop® System (K212456)"],["Inner Dimensions (mm)","","","205 mm x 240 mm","","","Same",""],["Coil Design","","","Linear Volume","","","Same",""],["Patient Weight Capacity","","","200 kg","","","Same",""],["Operation Temperature","","","15-30 C","","","Same",""],["Warm Up Time","","","<3 minutes","","","Same",""],["Temperature Control","","","No","","","Same",""],["Humidity Control","","","No","","","Same",""],["","Image Reconstruction Algorithm","","","","","",""],["T1W\n- T1-Standard\n- T1-Gray/White Contrast","","","Advanced Gridding","","","Advanced Gridding\n(T1-Gray/White Contrast only)",""],["T2W\n- T2\n- T2-Fast","","","Advanced Gridding","","","Advanced Gridding (T2 only)",""],["FLAIR","","","Advanced Gridding","","","Same",""],["DWI","","","Conjugate Gradient","","","Same",""],["Image Post-Processing","","","- Advanced Denoising (applies to\nT1W, T2W, and FLAIR only)\n- Image orientation transform\n- Geometric distortion correction\n- Receive coil intensity correction\n- DICOM output","","","Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221393-p6-t1","doc_id":"K221393","page_num":6,"bbox":[72.26,537.72,564.62,695.28],"n_rows":5,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Software\nVerification","","","Testing to verify that the advanced reconstruction\nmodels do not alter image features or introduce\nartifacts.","","","● IEC 62304:2006\n● FDA Guidance, “Guidance for the\nContent of Premarket Submissions\nfor Software Contained in Medical\nDevices”","",""],["","","","Testing to verify that image quality with advanced\nreconstruction is acceptable.","","","","",""],["","","","Testing to verify basic software functionality is\nunchanged between releases.","","","","",""],["","","","NESSUS scan test to verify any vulnerabilities and\nserve as a security baseline.","","","","",""]],"caption_candidate":"accordance with internal requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221393-p7-t0","doc_id":"K221393","page_num":7,"bbox":[72.25,72.24,562.55,323.28],"n_rows":3,"n_cols":3,"columns":["Image\nPerformance","Testing to verify image performance with advanced\nreconstruction meets all image quality criteria.","● NEMA MS 1-2008 (R2020)\n● NEMA MS 3-2008 (R2020)\n● NEMA MS 9-2008 (R2020)\n● NEMA MS 12-2016\n● American College of Radiology (ACR)\nPhantom Test Guidance for Use of\nthe Large MRI Phantom for the ACR\nMRI Accreditation Program\n● American College of Radiology\nstandards for named sequences"],"rows":[["Image\nPerformance","Testing to verify image performance with advanced\nreconstruction meets all image quality criteria.","● NEMA MS 1-2008 (R2020)\n● NEMA MS 3-2008 (R2020)\n● NEMA MS 9-2008 (R2020)\n● NEMA MS 12-2016\n● American College of Radiology (ACR)\nPhantom Test Guidance for Use of\nthe Large MRI Phantom for the ACR\nMRI Accreditation Program\n● American College of Radiology\nstandards for named sequences"],["Software\nValidation","Validation studies to ensure the device meets user\nneeds and performs as intended.","● FDA Guidance, “Guidance for the\nContent of Premarket Submissions\nfor Software Contained in Medical\nDevices”"],["Cybersecurity","Testing to verify cybersecurity controls and\nmanagement.","● Cybersecurity as recommended in\nFDA guidance, “Content of\nPremarket Submissions for\nManagement of Cybersecurity in\nMedical Devices”"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221393-p7-t1","doc_id":"K221393","page_num":7,"bbox":[72.25,392.28,562.55,620.88],"n_rows":5,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Biocompatibility","","","Biocompatibility testing of patient-contacting\nmaterials.","","","● ISO 10993-1:2018\n● ISO 10993-5:2009\n● ISO 10993-10:2010","",""],["Cleaning/\nDisinfection","","","Cleaning and disinfection validation of patient-\ncontacting materials.","","","● FDA Guidance, “Reprocessing\nMedical Devices in Health Care\nSettings: Validation Methods and\nLabeling”\n● ISO 17664:2017\n● ASTM F3208-17","",""],["Safety","","","Electrical Safety, EMC, and Essential Performance\ntesting.","","","● ANSI/AAMI ES 60601-\n1:2005/(R)2012\n● IEC 60601-1-2:2014\n● IEC 60601-1-6:2013","",""],["Performance","","","Characterization of the Specific Absorption Rate for\nMagnetic Resonance Imaging Systems.","","","● NEMA MS 8-2016","",""]],"caption_candidate":"modifications did not introduce a new worst-case configuration or scenario for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221432-p4-t0","doc_id":"K221432","page_num":4,"bbox":[72.29,431.0,504.44,604.2],"n_rows":9,"n_cols":6,"columns":["","Item","","","Description",""],"rows":[["","Item","","","Description",""],["Device Classification Name","","","Automated Radiological Image Processing Software","",""],["510(k) number","","","K213779","",""],["Trade or proprietary or\nmodel name","","","Customize","",""],["Original Applicant","","","3D-Side SA","",""],["Regulation Number","","","21 CFR 892.2050","",""],["Decision date","","","March 16, 2022","",""],["Classification product code","","","QIH","",""],["510(k) Review Panel","","","Radiology","",""]],"caption_candidate":"The predicate device to which substantial equivalence is claimed:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221449-p6-t0","doc_id":"K221449","page_num":6,"bbox":[52.2,130.92,560.04,598.36],"n_rows":5,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection","Difference and\ncomments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection","Difference and\ncomments"],["510(k) Number","Pending","K201019",""],["Regulation\nNumber/Name","21 CFR 892.2090 /\nRadiological Computer Assisted Detection\nand Diagnosis Software","Same","N/A"],["Product Code","QDQ","Same","N/A"],["Regulation\nDescription","A radiological computer assisted\ndetection and diagnostic software is an\nimage processing device intended to aid\nin the detection, localization, and\ncharacterization of fracture, lesions, or\nother disease specific findings on\nacquired medical images (e.g.\nradiography, MR, CT). The device\ndetects, identifies and characterizes\nfindings based on features or\ninformation extracted from images, and\nprovides information about the\npresence, location, and characteristics\nof the findings to the user. The analysis\nis intended to inform the primary\ndiagnostic and patient management\ndecisions that are made by the clinical\nuser. The device is not intended as a\nreplacement for a complete clinician's\nreview or their clinical judgment that\ntakes into account other relevant\ninformation from the image or patient\nhistory.","Same","N/A"]],"caption_candidate":"Summary of Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221449-p7-t0","doc_id":"K221449","page_num":7,"bbox":[52.2,72.3,560.57,702.18],"n_rows":8,"n_cols":4,"columns":["Indications\nfor Use","Genius AI Detection is a computer-aided\ndetection and diagnosis (CADe/CADx)\nsoftware device intended to be used\nwith compatible digital breast\ntomosynthesis (DBT) systems to identify\nand mark regions of interest including\nsoft tissue densities (masses,\narchitectural distortions and\nasymmetries) and calcifications in DBT\nexams from compatible DBT systems\nand provide confidence scores that\noffer assessment for Certainty of\nFindings and a Case Score.\nThe device intends to aid in the\ninterpretation of digital breast\ntomosynthesis exams in a concurrent\nfashion, where the interpreting\nphysician confirms or dismisses the\nfindings during the reading of the\nexam.","Same","N/A"],"rows":[["Indications\nfor Use","Genius AI Detection is a computer-aided\ndetection and diagnosis (CADe/CADx)\nsoftware device intended to be used\nwith compatible digital breast\ntomosynthesis (DBT) systems to identify\nand mark regions of interest including\nsoft tissue densities (masses,\narchitectural distortions and\nasymmetries) and calcifications in DBT\nexams from compatible DBT systems\nand provide confidence scores that\noffer assessment for Certainty of\nFindings and a Case Score.\nThe device intends to aid in the\ninterpretation of digital breast\ntomosynthesis exams in a concurrent\nfashion, where the interpreting\nphysician confirms or dismisses the\nfindings during the reading of the\nexam.","Same","N/A"],["Compatible\nDBT\nSystems","Hologic Selenia Dimensions\nHologic 3Dimensions\nSupports both models in the following","Same","N/A"],["Type of CAD\nSoftware","mRaoddioelso:g i cal computer assisted\n•detescttaionnd aarnddr edsiaogluntoiosntic1 s-mofmtwsalricee. s\n• high resolution1-mmslices(Clarity","Same","N/A"],["Mode of Action","ImagHeD p)rocessing device utilizing\nmachine learning to aid in the\nhighresolution6-mmSmartSlices\ndetection, localization, and\n(3DQuorum)\ncharacterization of soft tissue densities\n(masses, architectural distortions and\nasymmetries) and calcifications in the\n1-mm 3D DBT slices. Findings are co-\nregistered to 6-mm SmartSlices.","Same","N/A"],["Clinical\nOutput","To inform the primary diagnostic and\npatient management decisions that\nare made by the clinical user.","Same","N/A"],["Patient\nPopulation","Symptomatic and asymptomatic\nwomen undergoing\nmammography","Same","N/A"],["End Users","MQSA-Qualified Interpreting Physicians\nand Radiologists","Same","N/A"],["Image Source\nModalities","Digital breast tomosynthesis slices","Same","N/A"]],"caption_candidate":"Genius AI Detection 2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221449-p8-t0","doc_id":"K221449","page_num":8,"bbox":[52.2,72.36,560.64,266.78],"n_rows":4,"n_cols":4,"columns":["Output Device","Softcopy Workstation","Same","N/A"],"rows":[["Output Device","Softcopy Workstation","Same","N/A"],["Deployment","Stand-alone computer","Same","N/A"],["Method Of Use","Concurrent read","Same","N/A"],["Visualization\nFeatures","Places mark within suspicious lesion by\ndefault (Emphasize™; RightOn™) and\nreports confidence of finding next to each\nidentified lesion in the image. CAD display\nmay be toggled on/off. Option to\nautomatically zoom into or contour the\nsuspicious region of interest (PeerView™).","Same","N/A"]],"caption_candidate":"Genius AI Detection 2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p2-t0","doc_id":"K221456","page_num":2,"bbox":[257.72,417.02,570.36,513.58],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging"],["","Devices and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p5-t0","doc_id":"K221456","page_num":5,"bbox":[76.56,433.08,526.56,714.84],"n_rows":3,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison\nFeature","Rapid ICH (K193087)","Rapid ICH – Subject Device"],["Indications\nfor Use","Rapid ICH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-enhanced\nhead CT images. The device is\nintended to assist hospital networks\nand trained radiologists in\nworkflow triage by flagging and\ncommunication of suspected\npositive findings of pathologies in\nhead CT images, namely\nIntracranial Hemorrhage (ICH).\nRapid ICH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone","Rapid ICH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-enhanced\nhead CT images. The device is\nintended to assist hospital networks\nand trained radiologists in\nworkflow triage by flagging and\ncommunication of suspected\npositive findings of pathologies in\nhead CT images, for IPH, IVH,\nSAH, and SDH Intracranial\nHemorrhages (ICH).\nRapid ICH uses an artificial\nintelligence algorithm to analyze"]],"caption_candidate":"and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p6-t0","doc_id":"K221456","page_num":6,"bbox":[76.56,75.84,526.56,708.72],"n_rows":7,"n_cols":3,"columns":["","desktop application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device. The\nresults of Rapid ICH are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","images and highlight cases with\ndetected ICH on a server or\nstandalone desktop application in\nparallel to the ongoing standard of\ncare image interpretation. The user\nis presented with notifications for\ncases with suspected ICH findings.\nNotifications include compressed\npreview images, which are meant\nfor informational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of Rapid ICH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified\nradiologists are responsible for\nviewing full images per the\nstandard of care."],"rows":[["","desktop application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device. The\nresults of Rapid ICH are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care.","images and highlight cases with\ndetected ICH on a server or\nstandalone desktop application in\nparallel to the ongoing standard of\ncare image interpretation. The user\nis presented with notifications for\ncases with suspected ICH findings.\nNotifications include compressed\npreview images, which are meant\nfor informational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of Rapid ICH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified\nradiologists are responsible for\nviewing full images per the\nstandard of care."],["Stroke/Head","Stroke/Head","Stroke/Head"],["Removal of\ncases from\nworklist\nqueue","No","No"],["Primary\nImaging\nModalities","NCCT","NCCT"],["Technical\nImplementati\non","AI/ML/Neural Network","AI/ML/Neural Network"],["Segmentation\nof ROI","No, the device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file.","No, the device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file."],["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes."]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p7-t0","doc_id":"K221456","page_num":7,"bbox":[76.56,75.84,526.56,299.76],"n_rows":5,"n_cols":3,"columns":["","The device operates in parallel with\nthe standard of care, which remains.","The device operates in parallel with\nthe standard of care, which remains."],"rows":[["","The device operates in parallel with\nthe standard of care, which remains.","The device operates in parallel with\nthe standard of care, which remains."],["Primary\nUser(s)","Clinician","Radiologist"],["Alteration of\noriginal\nimage data","No","No"],["Alters\nStandard of\nCare\nWorkflow","In parallel to","In parallel to"],["Notification/\nPrioritization","Yes – PACS, Workstation, email,\nmobile","Yes – PACS, Workstation, email,\nmobile"]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p8-t0","doc_id":"K221456","page_num":8,"bbox":[132.87,607.86,479.13,706.32],"n_rows":5,"n_cols":8,"columns":["Parameter","Mean","","95% CI","","","95% CI",""],"rows":[["Parameter","Mean","","95% CI","","","95% CI",""],["","","","Lower","","","Upper",""],["Time to open in standard of\ncare (Minutes)","72.58","45.02","","","100.14","",""],["Time to notification of Rapid\nICH (Minute)","0.65","0.63","","","0.67","",""],["Difference (Minutes)","71.93","NA","","","NA","",""]],"caption_candidate":"notification of the Rapid ICH software (0.65 minutes: 95% CI 0.63 – 0.67).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p9-t0","doc_id":"K221456","page_num":9,"bbox":[95.28,78.44,522.96,628.11],"n_rows":68,"n_cols":7,"columns":["rmance","across su","btype differentiation","shows:","","",""],"rows":[["rmance","across su","btype differentiation","shows:","","",""],["","","","","","",""],["","","Performan","ce Metrics by","Gender","",""],["","","","","","",""],["","","","","Lo","wer 95% Up","per 9"],["","","","","","",""],["Gender","","Measure","N","Estimate","",""],["","","","","","CI","CI"],["","","","","","",""],["Female","","Sensitivity","63","1.000","0.943","1.000"],["","","","","","",""],["","","Specificity","64","1.000","0.943","1.000"],["","","","","","",""],["Male","","Sensitivity","72","0.932","0.849","0.970"],["","","","","","",""],["","","Specificity","97","1.000","0.962","1.000"],["","","","","","",""],["","","Performance","Metrics by A","ge Groups","",""],["","","","","","",""],["","","","","Lo","wer 95% Up","per 9"],["","","","","","",""],["ge Grou","p","Measure","N","Estimate","",""],["","","","","","CI","CI"],["","","","","","",""],["Age ≤ 50","","Sensitivity","27","0.926","0.766","0.979"],["","","","","","",""],["","","Specificity","26","1.000","0.871","1.000"],["","","","","","",""],["< Age <","70","Sensitivity","54","0.963","0.875","0.990"],["","","","","","",""],["","","Specificity","62","1.000","0.942","1.000"],["","","","","","",""],["Age ≥ 70","","Sensitivity","63","0.984","0.915","0.997"],["","","","","","",""],["","","Specificity","70","1.000","0.948","1.000"],["","","","","","",""],["","","Performa","nce by ICH S","ubtype","",""],["","","","","","",""],["","Subtype","N","Se","Se LCL","Se UCL",""],["","","","","","",""],["","IPH","45","1.000","0.921","1.000",""],["","","","","","",""],["","IVH","4","1.000","0.510","1.000",""],["","","","","","",""],["I","PH, IVH","41","1.000","0.914","1.000",""],["","","","","","",""],["","SAH","11","1.000","0.741","1.000",""],["","","","","","",""],["","SDH","19","0.895","0.686","0.971",""],["","","","","","",""],["","Multiple","24","1.000","0.862","1.000",""],["","","","","","",""],["","Other","9","0.667","0.354","0.879",""],["","","","","","",""],["","","Performanc","e Metrics by","Volume","",""],["","","","","","",""],["","","","","Lo","wer 95% Up","per 9"],["","","","","","",""],["ume Gr","oup","Measure","N","Estimate","",""],["","","","","","CI","CI"],["","","","","","",""],["All","","Sensitivity","159","0.937","0.888","0.965"],["","","","","","",""],["Vol ≥ 0.","4","Sensitivity","153","0.967","0.926","0.986"],["","","","","","",""],["Vol ≥ 1","","Sensitivity","145","0.966","0.922","0.985"],["","","","","","",""],["Vol ≥ 5","","Sensitivity","112","1.000","0.967","1.000"]],"caption_candidate":"Performance across subtype differentiation shows:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K221456-p9-t1","doc_id":"K221456","page_num":9,"bbox":[68.02,115.54,543.64,143.18],"n_rows":4,"n_cols":6,"columns":["","","","","Lower 95%","Upper 95%"],"rows":[["","","","","Lower 95%","Upper 95%"],["Gender","Measure","N","Estimate","",""],["","","","","CI","CI"],["","","","","",""]],"caption_candidate":"Performance Metrics by Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p9-t2","doc_id":"K221456","page_num":9,"bbox":[68.02,229.22,543.64,256.82],"n_rows":4,"n_cols":6,"columns":["","","","","Lower 95%","Upper 95%"],"rows":[["","","","","Lower 95%","Upper 95%"],["Age Group","Measure","N","Estimate","",""],["","","","","CI","CI"],["","","","","",""]],"caption_candidate":"Performance Metrics by Age Groups","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p9-t3","doc_id":"K221456","page_num":9,"bbox":[68.02,539.98,543.64,567.62],"n_rows":4,"n_cols":6,"columns":["","","","","Lower 95%","Upper 95%"],"rows":[["","","","","Lower 95%","Upper 95%"],["Volume Group","Measure","N","Estimate","",""],["","","","","CI","CI"],["","","","","",""]],"caption_candidate":"Performance Metrics by Volume","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p10-t0","doc_id":"K221456","page_num":10,"bbox":[75.0,95.75,536.68,123.3],"n_rows":4,"n_cols":6,"columns":["Slice Thickness","","N","Estimate","Lower 95%\nCI","Upper 95%"],"rows":[["Slice Thickness","","N","Estimate","Lower 95%\nCI","Upper 95%"],["","Measure","","","",""],["","","","","","CI"],["","","","","",""]],"caption_candidate":"Performance Metrics by Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p10-t1","doc_id":"K221456","page_num":10,"bbox":[68.1,239.26,543.56,266.78],"n_rows":3,"n_cols":6,"columns":["","","N","","Lower 95%\nCI","Upper 95%\nCI"],"rows":[["","","N","","Lower 95%\nCI","Upper 95%\nCI"],["Manufacturer","Measure","","Estimate","",""],["","","","","",""]],"caption_candidate":"Performance Metrics by Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p10-t2","doc_id":"K221456","page_num":10,"bbox":[68.1,438.34,543.56,465.86],"n_rows":3,"n_cols":6,"columns":["","","N","","Lower 95%\nCI","Upper 95%\nCI"],"rows":[["","","N","","Lower 95%\nCI","Upper 95%\nCI"],["Make/Model","Measure","","Estimate","",""],["","","","","",""]],"caption_candidate":"Performance within Make/Model of Scanners","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p11-t0","doc_id":"K221456","page_num":11,"bbox":[69.14,75.94,544.68,103.58],"n_rows":2,"n_cols":6,"columns":["Make/Model","Measure","N","Estimate","Lower 95%\nCI","Upper 95%"],"rows":[["Make/Model","Measure","N","Estimate","Lower 95%\nCI","Upper 95%"],["","","","","","CI"]],"caption_candidate":"Section 5: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221456-p11-t1","doc_id":"K221456","page_num":11,"bbox":[69.14,190.66,544.68,218.18],"n_rows":4,"n_cols":6,"columns":["","Measure","N","Estimate","Lower 95%","Upper 95%\nCI"],"rows":[["","Measure","N","Estimate","Lower 95%","Upper 95%\nCI"],["Make/Model","","","","",""],["","","","","CI",""],["","","","","",""]],"caption_candidate":"Performance within Reconstruction Methods of Make/Model of Scanners","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221463-p4-t0","doc_id":"K221463","page_num":4,"bbox":[94.54,489.55,517.5,521.95],"n_rows":2,"n_cols":9,"columns":["","Manufacturer","","","Device Name","","","K-Number",""],"rows":[["","Manufacturer","","","Device Name","","","K-Number",""],["Elucid Bioimaging Inc.","","","vascuCAP A.1.2","","","K183012","",""]],"caption_candidate":"Predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221463-p7-t0","doc_id":"K221463","page_num":7,"bbox":[72.02,113.3,522.12,509.35],"n_rows":8,"n_cols":3,"columns":["erutcurtS","Lumen Area,\ntested range 0.3-\n290.1mm2","Bias: 0.81mm2 [0.3, 1.9], Intercept: 0.65mm2 [-0.6, 0.9],\nSlope: 1.01 [0.9, 1.0],\nRMSE: 2.50 [1.30,2.80], wSD: 2.30 [1.20,2.60]"],"rows":[["erutcurtS","Lumen Area,\ntested range 0.3-\n290.1mm2","Bias: 0.81mm2 [0.3, 1.9], Intercept: 0.65mm2 [-0.6, 0.9],\nSlope: 1.01 [0.9, 1.0],\nRMSE: 2.50 [1.30,2.80], wSD: 2.30 [1.20,2.60]"],["","Wall Area,\ntested range 9.4-\n448.6mm2","Bias: 0.50mm2 [-1.08, 1.29], Intercept: -0.59mm2 [-4.1, 2.\n8.0], Slope: 1.0 [0.99, 1.04], RMSE: 4.10 [2.60,6.60], wSD:\n3.90 [2.40,6.30]"],["","Stenosis,\ntested range 33-69%","Bias: 6.10 [3.10,8.90], Slope: 0.97 [0.83,1.20], Intercept: 7.90\n[-4.60,15.00],\nRMSE: 7.00 [3.60,11.00], wSD: 6.20 [3.20,9.60]"],["","Wall Thickness,\ntested range 1.0-\n9.0mm","Bias: 0.5mm [0.3, 0.6], Intercept: 0.27mm [-0.1, 0.5],\nSlope: 1.05 [1.01, 1.1], RMSE: 0.24 [0.17,0.31], wSD: 0.21\n[0.15,0.28]"],["","Plaque Burden,\ntested range 0.4-1.0\n(ratio)","Bias: -0.01 [-0.01, .004], Intercept: 0.01 [-0.1, 0.04],\nSlope: 0.99 [0.9, 1.1], RMSE: 0.018 [0.012,0.038], wSD: 0.017\n[0.012,0.036]"],["noitisopmoC","Calcified Area\n(mm2):\nTested range: 0-14","Difference: -0.06 [-0.09,-0.03], Slope: 0.99 [0.91,1.07],\nIntercept: -0.04 [-0.08,0.01], RMSE: 1.46 [1.32,1.59], wSD:\n1.43 [1.31,1.56]"],["","LRNC Area (mm2):\nTested range: 0-10","Difference: 0.15 [0.10,0.20], Slope: 0.92 [0.87,0.96], Intercept:\n0.34 [0.27,0.42], RMSE: 2.79 [2.70,2.89], wSD: 2.76\n[2.67,2.85]"],["","Matrix Area (mm2):\nTested range: 4-52","Difference: 0.02 [-0.22,0.26], Slope: 0.91 [0.88,0.94],\nIntercept: 1.34 [1.00,1.67], RMSE: 3.77 [3.64,3.89], wSD: 3.58\n[3.46,3.69]"]],"caption_candidate":"K221463","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221552-p4-t0","doc_id":"K221552","page_num":4,"bbox":[72.32,133.9,545.74,312.33],"n_rows":7,"n_cols":4,"columns":["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],"rows":[["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],["Address","Address","","Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.\nWest Dist.\nTaichung City 403020\nTAIWAN"],["","Applicant","","Joseph Chang"],["Contact Information","Contact Information","","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["","Correspondence Person","","Ti-Hao Wang, MD"],["Contact Information","Contact Information","","886-04-23213838 #168\ntihao.wang@everfortune.ai"],["","Date Prepared","","May 31, 2022"]],"caption_candidate":"1. General Information K221552","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221552-p4-t1","doc_id":"K221552","page_num":4,"bbox":[72.32,367.93,545.74,481.67],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","EFAI ChestSuite XR Pneumothorax Assessment System v1.0"],"rows":[["","Proprietary Name","","EFAI ChestSuite XR Pneumothorax Assessment System v1.0"],["","Common Name","","EFAI PNXXR v1.0"],["Classification Name","Classification Name","","Radiological Computer-Assisted Prioritization Software For\nLesions"],["","Regulation Number","","21 CFR 892.2080"],["","Regulation Name","","Radiological Computer Aided Triage and Notification Software"],["","Product Code","","QFM"],["","Regulatory Class","","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221552-p4-t2","doc_id":"K221552","page_num":4,"bbox":[72.32,537.27,545.74,653.42],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","red dot™"],"rows":[["","Proprietary Name","","red dot™"],["","Premarket Notification","","K191556"],["Classification Name","Classification Name","","Radiological Computer-Assisted Prioritization Software For\nLesions"],["","Regulation Number","","21 CFR 892.2080"],["","Regulation Name","","Radiological Computer Aided Triage and Notification Software"],["","Product Code","","QFM"],["","Regulatory Class","","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221552-p6-t0","doc_id":"K221552","page_num":6,"bbox":[72.16,205.8,526.41,698.1],"n_rows":9,"n_cols":7,"columns":["Company","","","","Ever Fortune.AI Co., Ltd.","","Behold.AI Technologies Limited"],"rows":[["Company","","","","Ever Fortune.AI Co., Ltd.","","Behold.AI Technologies Limited"],["","","","","(EFAI)","",""],["","Device Name","","EFAI PNXXR","","","red dot™"],["","510k Number","","K221552","","","K191556"],["","Regulation No.","","21CFR 892.2080","","","21CFR 892.2080"],["","Classification","","II","","","II"],["","Product Code","","QFM","","","QFM"],["Intended\nUse/Indication for\nUse","","","EFAI PNXXR is a software\nworkflow tool designed to aid\nthe clinical assessment of adult\n(22 years of age or older)\nPosteroanterior (PA) view Chest\nX-Ray cases with features\nsuggestive of pneumothorax in\nthe medical care environment.\nEFAI PNXXR analyzes cases\nusing an artificial intelligence\nalgorithm to identify suspected\nfindings. It makes case-level\noutput available to a\nPACS/workstation for worklist\nprioritization or triage. EFAI\nPNXXR is not intended to direct\nattention to specific portions or\nanomalies of an image. Its\nresults are not intended to be\nused on a stand-alone basis for\nclinical decision-making nor is\nit intended to rule out\npneumothorax or otherwise\npreclude clinical assessment of\nX-Ray cases.","","","The red dot™ software platform\nis a software workflow tool\ndesigned to aid the clinical\nassessment of adult Chest X-Ray\ncases with features suggestive of\nPneumothorax in the medical\ncare environment. red dot™\nanalyzes cases using an artificial\nintelligence algorithm to identify\nsuspected findings. It makes\ncase-level output available to a\nPACS/workstation for worklist\nprioritization or triage. red dot™\nis not intended to direct attention\nto specific portions of an image\nor to anomalies other than\nPneumothorax. Its results are not\nintended to be used on a stand-\nalone basis for clinical decision-\nmaking nor is it intended to rule\nout Pneumothorax or otherwise\npreclude clinical assessment of\nX-Ray cases."],["Intended user","","","Hospital networks and trained\nclinicians","","","Hospital networks and trained\nclinicians"]],"caption_candidate":"Table - Comparison with the Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221552-p7-t0","doc_id":"K221552","page_num":7,"bbox":[72.18,75.39,526.42,445.64],"n_rows":21,"n_cols":5,"columns":["Supported Modalities","","","X-Ray (PA view)","X-Ray (PA or AP view)"],"rows":[["Supported Modalities","","","X-Ray (PA view)","X-Ray (PA or AP view)"],["Body Part","","","Chest","Chest"],["","Artificial Intelligence","","Yes","Yes"],["","Algorithm","","",""],["","Limited to analysis of","","Yes","Yes"],["","imaging data","","",""],["","Aids prompt","","Yes","Yes"],["","identification of cases","","",""],["","with indicated","","",""],["","findings","","",""],["Image Input","","","DICOM","DICOM"],["","Identify patients","","Yes","Yes"],["","with a pre-specified","","",""],["","clinical condition","","",""],["Clinical condition","","","Pneumothorax","Pneumothorax"],["Alert to finding","","","Passive notification flagged for\nreview","Passive notification flagged for\nreview"],["","Independent of","","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed from\nworklist"],["","standard of care","","",""],["","workflow","","",""],["","Where results are","","PACS / RIS / EPR\n/Workstation","PACS / RIS / EPR / Workstation"],["","received","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221564-p5-t0","doc_id":"K221564","page_num":5,"bbox":[71.8,472.02,487.15,512.05],"n_rows":2,"n_cols":3,"columns":["510(k) Number","Trade Name","Manufacturer"],"rows":[["510(k) Number","Trade Name","Manufacturer"],["K200760","Rapid ASPECTS","iSchemaView Inc"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221564-p17-t0","doc_id":"K221564","page_num":17,"bbox":[72.3,626.1,523.17,748.17],"n_rows":2,"n_cols":2,"columns":["Risk Benefit Summary",""],"rows":[["Risk Benefit Summary",""],["Summary of Benefits","This device provides a systematic, automated\nanalysis of NCCT scans of the head to provide a\nstandardized, automated ASPECT score for\nStroke workup.\nThe clinical reader study, which included 4\nneurologists and 6 neuroradiologists,"]],"caption_candidate":"Risk Benefit Analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221564-p19-t0","doc_id":"K221564","page_num":19,"bbox":[72.3,134.83,523.17,741.67],"n_rows":6,"n_cols":2,"columns":["","patient benefit. The study demonstrates\nimprovement in the assessment for readers\ninterpreting NCCT scans for overall ASPECTS\nassessment.\nThis device additionally also provides\ntransparent AI processing enabling users to\nunderstand how the automated output has\nbeen determined and enables users to perform\na more technically informed review of the\nautomated output. This is a significant benefit\nwhich may help mitigate risks related to false\nnegatives or false positives in the automated\noutput, particularly for more challenging cases."],"rows":[["","patient benefit. The study demonstrates\nimprovement in the assessment for readers\ninterpreting NCCT scans for overall ASPECTS\nassessment.\nThis device additionally also provides\ntransparent AI processing enabling users to\nunderstand how the automated output has\nbeen determined and enables users to perform\na more technically informed review of the\nautomated output. This is a significant benefit\nwhich may help mitigate risks related to false\nnegatives or false positives in the automated\noutput, particularly for more challenging cases."],["Summary of the Risks","There are minimal potential risks associated\nwith the use of the device."],["","Incorrect scoring which may result in false\npositive results and result to incorrect patient\nmanagement with possible adverse effects such\nas, unnecessary additional medical imaging\nand/or unnecessary additional diagnostic\nworkup."],["","Incorrect scoring which may result in false\nnegative results may lead to complications,\nincluding incorrect diagnosis and delay in\ndisease management."],["","The device could be misused to analyze images\nfrom an unintended patient population or on\nimages acquired with incompatible imaging\nhardware or incompatible image acquisition\nparameters, leading to inappropriate diagnostic\ninformation being displayed to the user."],["","Device failure could lead to the absence of\nresults, delay of results or incorrect results,\nwhich could likewise lead to inaccurate patient\nassessment."]],"caption_candidate":"Oxford OX2 7HN","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221564-p20-t0","doc_id":"K221564","page_num":20,"bbox":[72.3,134.83,523.17,743.17],"n_rows":2,"n_cols":2,"columns":["Summary of additional factors","However, based on the performance data and\nthe application of mitigating measures\n(including but not limited to general controls\nand special controls established for this device\ntype), use of the device is unlikely to decrease\ndiagnostic performance of the user and\npossible misuse of the device does not present\nadditional risks compared with misuse of\nother types of radiological image processing\ndevices.\nThe device includes a gating condition in\nsoftware to help ensure that the software is not\nused on stroke mimics or the incorrect patient\npopulation.\nThe physician may either confirm or overrule\nthe device\nHeatmap provides additional transparency on\nregions evaluated by the ASPECTS, which may\nbe used by the clinician to qualify or correct\ndevice outputs\nThe study was enriched to cover the range of\nASPECT scores; and, the readers in practice may\nnot experience a significant improvement in\ndetermining ASPECTS.\nThis device may improve the diagnostic\naccuracy of less experienced or less confident\nphysicians in rating NCCT for the ASPECT score\nin the context of acute ischemic stroke caused\nby ICA or MCA occlusion (confirmed using\nvascular imaging such as CTA or MRA)."],"rows":[["Summary of additional factors","However, based on the performance data and\nthe application of mitigating measures\n(including but not limited to general controls\nand special controls established for this device\ntype), use of the device is unlikely to decrease\ndiagnostic performance of the user and\npossible misuse of the device does not present\nadditional risks compared with misuse of\nother types of radiological image processing\ndevices.\nThe device includes a gating condition in\nsoftware to help ensure that the software is not\nused on stroke mimics or the incorrect patient\npopulation.\nThe physician may either confirm or overrule\nthe device\nHeatmap provides additional transparency on\nregions evaluated by the ASPECTS, which may\nbe used by the clinician to qualify or correct\ndevice outputs\nThe study was enriched to cover the range of\nASPECT scores; and, the readers in practice may\nnot experience a significant improvement in\ndetermining ASPECTS.\nThis device may improve the diagnostic\naccuracy of less experienced or less confident\nphysicians in rating NCCT for the ASPECT score\nin the context of acute ischemic stroke caused\nby ICA or MCA occlusion (confirmed using\nvascular imaging such as CTA or MRA)."],["Conclusion","This device shows positive improvement in\ndiagnostic accuracy in comparison to the\nreference standard.\nAlthough some performance data may suggest\nthat sensitivity for some ASPECTS regions may\nbe diminished or inconsistent in comparison to\nother region however, sample size limitations"]],"caption_candidate":"Oxford OX2 7HN","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p6-t0","doc_id":"K221592","page_num":6,"bbox":[36.29,87.3,567.2,747.41],"n_rows":17,"n_cols":15,"columns":["","Characteristic","","","Subject Device","","","Predicate Device","","","Reference Device","","","Reference Device",""],"rows":[["","Characteristic","","","Subject Device","","","Predicate Device","","","Reference Device","","","Reference Device",""],["Device Name","Device Name","","","AVIEW Lung","","","syngo. CT Lung","","","InferRead","","AVIEW","",""],["","","","","Nodule CAD","","","CAD (VD20)","","","Lung CT.AI","","","",""],["Classification\nName","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","",""],["","Regulatory","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["","Number","","","","","","","","","","","","",""],["","Product Code","","OEB, LLZ","","","OEB","","","OEB, LLZ","","","LLZ, JAK","",""],["","Review Panel","","Radiology","","","Radiology","","","Radiology","","","Radiology","",""],["","510k Number","","K221592","","","K203258","","","K192880","","","K200714","",""],["Indications for\nuse","","","AVIEW Lung Nodule CAD","","","","","","","","","","",""],["","","","AVIEW Lung Nodule CAD is a Computer-Aided Detection (CAD) software designed to assist\nradiologists in the detection of pulmonary nodules (with diameter 3-20 mm) during the review of\nCT examinations of the chest for asymptomatic populations. AVIEW Lung Nodule CAD provides\nadjunctive information to alert the radiologists to regions of interest with suspected lung nodules\nthat may otherwise be overlooked. AVIEW Lung Nodule CAD may be used as a second reader\nafter the radiologist has completed their initial read. The algorithm has been validated using non-\ncontrast CT images, the majority of which were acquired on Siemens SOMATOM CT series\nscanners; therefore, limiting device use to use with Siemens SOMATOM CT series is\nrecommended.","","","","","","","","","","",""],["","","","syngo. CT Lung CAD (VD20)","","","","","","","","","","",""],["","","","The syngo. CT Lung CAD device is a Computer-Aided Detection (CAD) tool designed to assist\nradiologists in the detection of solid and subsolid (part-solid and ground glass) pulmonary nodules\nduring review of multi-detector computed tomography (MDCT) from multivendor examinations\nof the chest. The software is an adjunctive tool to alert the radiologist to regions of interest (ROI)\nthat may otherwise be overlooked.\nThe syngo. CT Lung CAD device may be used as a concurrent first reader followed by a full\nreview of the case by the radiologist or as second reader after the radiologist has completed his/her\ninitial read.\nThe software device is an algorithm which does not have its own user interface component for\ndisplaying of CAD marks.\nThe Hosting Application incorporating syngo. CT Lung CAD is responsible for implementing a\nuser interface.","","","","","","","","","","",""],["","","","InferRead Lung CT.AI","","","","","","","","","","",""],["","","","lnferRead Lung CT.AI is comprised of computer-assisted reading tools designed to aid the\nradiologist in the detection of pulmonary nodules during the review of CT examinations of the\nchest on an asymptomatic population. Infer Read Lung CT.AI requires that both lungs be in the\nfield of view. lnferRead Lung CT.AI provides adjunctive information and is not intended to be\nused without the original CT series.","","","","","","","","","","",""],["","","","AVIEW","","","","","","","","","","",""],["","","","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This\nsoftware could be used to support the physician quantitatively in the diagnosis, follow up\nevaluation and documentation of CT lung tissue images by providing image segmentation of sub-\nstructures in lung, lobe, airways and cardiac, registration of inspiration and expiration which could\nanalyze quantitative information such as air trapping volume, air trapped index, and\ninspiration/expiration ratio. And, volumetric and structure analysis, density evaluation and\nreporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on premise\nand as cloud environment as well to allow users to connect by various environment such as mobile\ndevices and chrome browser. Characterizing nodules in the lung in a single study, or over the time\ncourse of several thoracic studies. Characterizations include nodule type, location of the nodule","","","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p7-t0","doc_id":"K221592","page_num":7,"bbox":[36.27,87.19,567.22,748.46],"n_rows":12,"n_cols":4,"columns":["","and measurements such as size (major axis, minor axis), estimated effective diameter from the\nvolume of the nodule, volume of the nodule, Mean HU(the average value of the CT pixel inside\nthe nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and\nvolumetric measures(Solid major; length of the longest diameter measured in 3D for solid portion\nof the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured in\nsections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling\ntime), and Lung-RADS (classification proposed to aid with findings). The system automatically\nperforms the measurement, allowing lung nodules and measurements to be displayed and, integrate\nwith FDA certified Mevis CAD (Computer aided detection) (K043617). It also provides CAC\nanalysis by segmentation of four main artery (right coronary artery, left main coronary, left anterior\ndescending and left circumflex artery then extracts calcium on coronary artery to provide Agatston\nscore, volume score and mass score by whole and each segmented artery type. Based on the score,\nprovides CAC risk based on age and gender.","",""],"rows":[["","and measurements such as size (major axis, minor axis), estimated effective diameter from the\nvolume of the nodule, volume of the nodule, Mean HU(the average value of the CT pixel inside\nthe nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and\nvolumetric measures(Solid major; length of the longest diameter measured in 3D for solid portion\nof the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured in\nsections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling\ntime), and Lung-RADS (classification proposed to aid with findings). The system automatically\nperforms the measurement, allowing lung nodules and measurements to be displayed and, integrate\nwith FDA certified Mevis CAD (Computer aided detection) (K043617). It also provides CAC\nanalysis by segmentation of four main artery (right coronary artery, left main coronary, left anterior\ndescending and left circumflex artery then extracts calcium on coronary artery to provide Agatston\nscore, volume score and mass score by whole and each segmented artery type. Based on the score,\nprovides CAC risk based on age and gender.","",""],["General\nDescription","AVIEW Lung Nodule CAD","",""],["","The AVIEW Lung Nodule CAD is a software product that detects nodules in the lung. The lung\nnodule detection model was trained by Deep Convolution Neural Network (CNN) based algorithm\nfrom the chest CT image. Automatic detection of lung nodules of 3 to 20mm in chest CT images.\nBy complying with DICOM standards, this product can be linked with the Picture Archiving and\nCommunication System (PACS) and provides a separate user interface to provide functions such\nas analyzing, identifying, storing, and transmitting quantified values related to lung nodules. The\nCAD’s results could be displayed after the user’s first read, and the user could select or de-select\nthe mark provided by the CAD. The device’s performance was validated with SIEMENS’\nSOMATOM series manufacturing. The device is intended to be used with a cleared AVIEW\nplatform.","",""],["","syngo. CT Lung CAD (VD20)","",""],["","Simens Healthcare GmbH intends to market the syngo. CT Lung CAD which is a medical device\nthat is designed to perform CAD processing in thoracic CT examinations for the detection of solid\npulmonary nodules (between 3.0 mm and 30.0mm) and subsolid (part-solid and ground glass)\nnodules (between 5.0mm and 30.0mm) in average diameter. The device processes image acquired\nwith multi-detector CT scanners with 16 or more detector rows.\nThe syngo. CT Lung CAD device supports the full range of nodule locations (central, pe-ripheral)\nand contours (round, irregular).\nThe syngo. CT Lung CAD sends a list of nodule candidate locations to a visualization application,\nsuch as syngo MM Oncology, or a visualization rendering component, which\ngenerates output images series with the CAD marks superimposed on the input thoracic CT images\nto enable the radiologist’s review. syngo MM Oncology (FDA clearance k191309) is deployed on\nthe syngo.via platform (FDA clearance k191040), which provides a common framework for\nvarious other applications implementing specific clinical workflows (but are not part of this\nclearance) to display the CAD marks. The syngo. CT Lung CAD device may be used either as a\nconcurrent first reader, followed by a review of the case, or as a second reader only after the initial\nread is completed\nThe subject device and predicate device have the same basic technical characteristics. This does\nnot introduce new types of safety or effectiveness concerns as demonstrated by the statistical\nanalyses and results of the reader study and additional evaluations results documented in the\nStatistical Analysis.","",""],["","InferRead Lung CT.AI","",""],["","","InferRead Lung CT.AI uses the Browser/Server architecture and is provided as Software as a",""],["","","Service (SaaS) via a URL. The system integrates algorithm logic and database in the same server",""],["","","to ensure the simplicity of the system and the convenience of system maintenance. The server is",""],["","","able to accept chest CT images from a PACS system, Radiological Information System (RIS",""],["","","system) or directly from a CT scanner, analyze the images and provide output annotations",""],["","","regarding lung nodules. Users are then able to use an existing PACS system to view the annotations",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p8-t0","doc_id":"K221592","page_num":8,"bbox":[36.32,87.24,567.22,664.98],"n_rows":13,"n_cols":8,"columns":["","","","","on their workstations. Dedicated servers can be located at hospitals and are directly.","","",""],"rows":[["","","","","on their workstations. Dedicated servers can be located at hospitals and are directly.","","",""],["","","","","connected to the hospital networks. The software consists of 4 modules which are Image reception","","",""],["","","","","(Docking Toolbox), Image predictive processing (DLServer), Image storage (RePACS) and Image","","",""],["","","","","display (NeoViewer).","","",""],["","","","AVIEW","","","",""],["","","","The AVIEW is a software product which can be installed on a PC. It shows images taken with the\ninterface from various storage devices using DICOM 3.0 which is the digital image and\ncommunication standard in medicine. It also offers functions such as reading, manipulation,\nanalyzing, post-processing, saving, and sending images by using the software tools. And is\nintended for use as diagnostic patient imaging which is intended for the review and analysis of CT\nscanning. Provides following features as semi-automatic nodule management, maximal plane\nmeasure, 3D measures and columetric measures, automatic nodule detection by integration with\n3rd party CAD. Also provides Brocks model which calculated the malignancy score based on\nnumerical or Boolean inputs. Follow up support with automated nodule matching and\nautomatically categorize Lung-RADS score which is a quality assurance tool designed to\nstandardize lung cancer screening CT reporting and management recommendations that is based\non type, size, size change and other findings that is reported. It also automatically analyzes\ncoronary artery calcification which support user to detect cardiovascular disease in early stage and\nreduce the burden of medical.","","","",""],["Detection\ntarget(s)","","","pulmonary nodules in\nnon-contrast chest CT\nacquisitions","","Solid and subsolid\n(part-solid and\nground-glass)\npulmonary nodules in\nscreening and\ndiagnostic chest CT\nacquisitions.","solid pulmonary\nnodules in diagnostic\nchest CT acquistions","-"],["Nodule\nCharacteristics","","","Diameter:\n Pulmanoary\nnodules ≥ 3 mm\nand <20 mm\nLocations:\n Full range: central,\nperipheral\nContours:\n round, irregular","","Diameter:\n solid ≥ 3mm and\n≤30mm\n Subsolid (part-\nsolid and ground\nglass) ≥ 5mm and ≤\n30mm\nLocations:\n Full range: central,\nperipheral\nContours:\nround, irregular","Solid nodules ≥\n3mm and 10mm and\nfull rande, central,\nperipheral round.\nirregular","-"],["","Image format","","DICOM","","DICOM","DICOM","DICOM"],["","Hosting","","AVIEW","","syngo.via","-","-"],["","Platform","","","","","",""],["","Hosting","","AVIEW LCS","","Syngo MM Oncology","-","-"],["","Application","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p9-t0","doc_id":"K221592","page_num":9,"bbox":[36.27,87.15,567.22,746.95],"n_rows":10,"n_cols":7,"columns":["Outputs","","","DICOM GSPS\n(Grayscale Softcopy\nPresentation State)\nXML (Coordinate of\ndetected nodules)\nAble to view results\non AVIEW, AVIEW\nLCS viewer page","Generates output\nimages series with the\nCAD makrs\nsuperimposed.\nAble to view results\nsyngo MM Oncology\nviewer page.","-","-"],"rows":[["Outputs","","","DICOM GSPS\n(Grayscale Softcopy\nPresentation State)\nXML (Coordinate of\ndetected nodules)\nAble to view results\non AVIEW, AVIEW\nLCS viewer page","Generates output\nimages series with the\nCAD makrs\nsuperimposed.\nAble to view results\nsyngo MM Oncology\nviewer page.","-","-"],["","Type of Scans","","CT","CT","CT","CT"],["Input scanning\nparameters","","","Scanners\nSiemens SOMATOM\nCT Scanners","Scanners\nMulti-vendor and\nmulti-detector CT\n(MDCT) scanners\n(Siemens, GE, Philips,\nand Toshiba)","-","-"],["","","","Detector rows\n16 or more detector\nrows","Detector rows\n16 or more detector\nrows","",""],["","","","Voltage\n100~140 kVp","Voltage\n100~140 kVp","",""],["","","","Exposure\nNone","Exposure\nNone","",""],["","","","Collimation\n1mm or less","Collimation\n1mm or less","",""],["","","","Slice Thickness\nUp to and including\n2.5mm, it is\nrecommended that\n<=1.25mm be used\nfor the detection of\nsmaller nodules (e.g.,\n4.0mm)","Slice Thickness\nUp to and including\n2.5mm, it is\nrecommended that\n<=1.25mm be used for\nthe detection of\nsmaller nodules (e.g.,\n3.0mm)","",""],["","","","Slice Overlap\n0~50%\nNote: Reconstruction\noverlap is allowed,\nbut gaps are not\npermitted","Slice Overlap\n0~50%\nNote: Reconstruction\noverlap is allowed,\nbut gaps are not\npermitted","",""],["","","","Number of images\nNone","Number of images\nNone","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p10-t0","doc_id":"K221592","page_num":10,"bbox":[36.32,87.15,567.22,715.04],"n_rows":3,"n_cols":5,"columns":["","Kernel\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nKernels were grouped\nas to their profile.\nTypical kernels\nvalidated by the reader\nstudy were:\nSmooth: B, B30f,\nStandard, FC10\nMedium: C, B45f,\nBr49d, B50f, I50f,\nBr60f, Lung, FC50,\nFC51\nSharp: D, B70f, I70f,\nB80s, I80s, Bone","Kernel\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nKernels were grouped\nas to their profile.\nTypical kernels\nvalidated by the reader\nstudy were:\nSmooth: B, B30f,\nStandard, FC10.\nMedium: C B45f,\nB50f, Lung, FC50,\nFC51, Bv49d_2,\nI50f_2, B60f.\nSharp: D, B70f, Bone,\nFC52","",""],"rows":[["","Kernel\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nKernels were grouped\nas to their profile.\nTypical kernels\nvalidated by the reader\nstudy were:\nSmooth: B, B30f,\nStandard, FC10\nMedium: C, B45f,\nBr49d, B50f, I50f,\nBr60f, Lung, FC50,\nFC51\nSharp: D, B70f, I70f,\nB80s, I80s, Bone","Kernel\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nKernels were grouped\nas to their profile.\nTypical kernels\nvalidated by the reader\nstudy were:\nSmooth: B, B30f,\nStandard, FC10.\nMedium: C B45f,\nB50f, Lung, FC50,\nFC51, Bv49d_2,\nI50f_2, B60f.\nSharp: D, B70f, Bone,\nFC52","",""],["","Contrast\nNone","Contrast\nNone","",""],["","Dose\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nTypical values are:\nCTDIvol < 8.0 mGy\n(milligray) in\ndiagnostic protocols\nand\nCTDIvol of = 3.0\nmGy in screening\nprotocols.\nThese values are\ndefined for standard\nsized patient—5 ft 7\nin., 154 lb (170\ncm, 70 kg)—based on\na 32-cm reference\nphantom with\nappropriate reductions\nin\nCTDIvol for smaller\npatients and\nappropriate\nincreases in CTDIvol\nfor larger patients.","Dose\nConsistent with\nthoracic CT protocols\nand in line with patient\nsafety guidelines.\nTypical values are:\nCTDIvol < 8.0 mGy\n(milligray) in\ndiagnostic protocols\nand\nCTDIvol of = 3.0 mGy\nin screening protocols.\nThese values are\ndefined for standard\nsized patient—5 ft 7\nin., 154 lb (170\ncm, 70 kg)—based on\na 32-cm reference\nphantom with\nappropriate reductions\nin\nCTDIvol for smaller\npatients and\nappropriate\nincreases in CTDIvol\nfor larger patients.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221592-p11-t0","doc_id":"K221592","page_num":11,"bbox":[94.22,389.21,507.1,444.17],"n_rows":4,"n_cols":4,"columns":["","Unaided","Aided","Difference in point estimate"],"rows":[["","Unaided","Aided","Difference in point estimate"],["AUC","0.73 (0.66 – 0.79)","0.92 (0.89 – 0.95)","0.19"],["Sensitivity","0.68 (0.62 – 0.73)","0.91 (0.89 – 0.94)","0.23"],["FP/scan","0.48 (0.28 – 0.69)","0.28 (0.15 – 0.42)","0.24"]],"caption_candidate":"1. Overall unaided/aider reader performacne comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221599-p6-t0","doc_id":"K221599","page_num":6,"bbox":[132.88,419.33,526.76,675.7],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012,\nC1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text)\nMedical electrical equipment - Part 1: General requirements for\nbasic safety and essential performance (IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2014(4th Edition) , Medical electrical equipment -\nPart 1-2: General requirements for basic safety and essential\nperformance - EMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment –\nPart 2-37: Particular requirements for the basic safety and essential\nperformance of ultrasonic medical diagnostic and monitoring\nequipment","",""],["ISO10993-1","","","ISO 10993-1:2009/(R)2013, Biological evaluation of medical\ndevices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2007, Medical devices - Application of risk management\nto medical devices","",""],["NEMA UD 2-\n2004","","","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound\nEquipment Revision 3","",""]],"caption_candidate":"FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221599-p7-t0","doc_id":"K221599","page_num":7,"bbox":[125.32,201.5,526.89,280.01],"n_rows":3,"n_cols":9,"columns":["","Validation Type","","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly detected frames\n×100\nTotal number of frames with nerve","","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221599-p7-t1","doc_id":"K221599","page_num":7,"bbox":[125.32,305.93,526.89,348.05],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","91.7","","","5.6","","","89.5 to 93.9","",""],["Speed (FPS)","","","7.93","","","1.11","","","7.04 to 8.82","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221599-p7-t2","doc_id":"K221599","page_num":7,"bbox":[125.32,373.91,526.89,478.99],"n_rows":8,"n_cols":12,"columns":["","","","","Females","","","Males","","","Total",""],"rows":[["","","","","Females","","","Males","","","Total",""],["Number of Subjects","","","13","","","5","","","18","",""],["Number of Images","","","1,168","","","978","","","2,146","",""],["Age range","","","32~68","","","22~50","","","22~68","",""],["Average age","","","45.7","","","35.0","","","42.7","",""],["BMI range","","","16~27.1","","","31.5","","","16~31.5","",""],["Average BMI","","","20.5","","","31.5","","","21.5","",""],["Ethnicity","","","All Koreans","","","","","","","",""]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221624-p9-t0","doc_id":"K221624","page_num":9,"bbox":[72.29,86.19,719.71,536.04],"n_rows":4,"n_cols":8,"columns":["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],"rows":[["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],["","","Planning Software","","","Quantitative Insights, Inc. QuantX","",""],["","","(Proposed Device)","","","(DEN170022)","",""],["Indications for Use","The Avenda Health AI Prostate Cancer\nPlanning Software is an artificial\nintelligence (AI)-based decision support\nsoftware, indicated as an adjunct to the\nreview of magnetic resonance (MR)\nprostate images and biopsy findings in the\nprostate oncological workflow. The\nAvenda Health AI Prostate Cancer\nPlanning Software is designed to support\nthe prostate oncological workflow by\nhelping the user with the segmentation of\nMR image features, including the prostate;\nin the evaluation, quantification, and\ndocumentation of lesions; and in pre-\nplanning for diagnostic and interventional\nprocedures such as biopsy and/or soft\ntissue ablation. The device is intended to\nbe used by physicians trained in the\noncological workflow in a clinical setting\nfor planning and guidance for clinical,\ninterventional, diagnostic, and/or treatment\nprocedures of the prostate.\nThe Avenda Health AI Prostate Cancer\nPlanning Software’s lesion\ncharacterization functions are intended for\nuse on patients with a pathology-confirmed\nGleason Grade Group (GGG)≥ 2 lesion\nand for whom corresponding biopsy\ncoordinate information have been\nuploaded. These functions are indicated\nfor the evaluation of the extent of known\ndisease. Extent of known disease refers to\nthe boundary of a pathology confirmed\nlesion of GGG≥ 2 for a particular patient.\nSpecifically, using prostate MR images,","","","QuantX is a computer-aided diagnosis\n(CADx) software device used to assist\nradiologists in the assessment and\ncharacterization of breast abnormalities\nusing MR image data. The software\nautomatically registers images, and\nsegments and analyzes user-selected\nregions of interest (ROI). QuantX extracts\nimage data from the ROI to provide\nvolumetric analysis and computer\nanalytics based on morphological and\nenhancement characteristics. These\nimaging (or radiomic) features are then\nsynthesized by an artificial intelligence\nalgorithm into a single value, the QI score,\nwhich is analyzed relative to a database of\nreference abnormalities with known\nground truth.\nQuantX is indicated for evaluation of\npatients presenting for high-risk screening,\ndiagnostic imaging workup, or evaluation\nof extent of known disease. Extent of\nknown disease refers to both the\nassessment of the boundary of a particular\nabnormality as well as the assessment of\nthe total disease burden in a particular\npatient. In cases where multiple\nabnormalities are present, QuantX can be\nused to assess each abnormality\nindependently.\nThis device provides information that may\nbe useful in the characterization of breast\nabnormalities during image interpretation.\nFor the QI score and component radiomic\nfeatures, the QuantX device provides","","","Similar to the predicate device."]],"caption_candidate":"Table 1: Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221624-p10-t0","doc_id":"K221624","page_num":10,"bbox":[72.27,72.34,719.73,500.28],"n_rows":5,"n_cols":8,"columns":["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],"rows":[["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],["","","Planning Software","","","Quantitative Insights, Inc. QuantX","",""],["","","(Proposed Device)","","","(DEN170022)","",""],["","biopsy, pathology, and clinical data, the\ndevice creates and displays a cancer map\nthat assigns a probability to each voxel\nwithin the prostate, indicating its\nprobability for containing clinically\nsignificant prostate cancer (csPCa, defined\nas GGG ≥2). A user selects a threshold for\nthe cancer map to create a boundary of the\nlesion. The lesion boundary is assigned an\nEncapsulation Confidence Score indicating\nthe confidence that all csPCa is\nencapsulated within the boundary. The\nEncapsulation Confidence Score is from a\nlookup table generated by a database of\ncases with known ground-truth. When\ninterpreted by a trained physician, this\ninformation may be useful in supporting\nlesion characterization and subsequent\npatient management.\nThe Avenda Health AI Prostate Planning\nSoftware may also be used as a medical\nimage application, for the viewing,\nmanipulation, 3D-visualization, and\ncomparison of MR prostate images. The\nimages can be viewed in a number of\noutput formats including volume\nrendering. It enables visualization of\ninformation that would otherwise have to\nbe visually compared disjointedly.","","","comparative analysis to lesions with\nknown outcomes using an image atlas and\nhistogram display format.\nQuantX may also be used as an image\nviewer of multi-modality digital images,\nincluding ultrasound and mammography.\nThe software also includes tools that allow\nusers to measure and document images,\nand output in a structured report.\nLimitations: QuantX is not intended for\nprimary interpretation of digital\nmammography images.","","",""],["Regulation Number","§892.2060, Radiological computer-assisted\ndiagnostic software for lesions suspicious\nof cancer.","","","§892.2060, Radiological computer-\nassisted diagnostic software for lesions\nsuspicious of cancer.","","","Same as the predicate device."]],"caption_candidate":"5.0 510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221624-p11-t0","doc_id":"K221624","page_num":11,"bbox":[72.25,72.34,719.75,515.28],"n_rows":12,"n_cols":8,"columns":["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],"rows":[["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],["","","Planning Software","","","Quantitative Insights, Inc. QuantX","",""],["","","(Proposed Device)","","","(DEN170022)","",""],["Product Codes:","POK, Computer-Assisted Diagnostic\nSoftware For Lesions Suspicious For\nCancer","","","POK, Computer-Assisted Diagnostic\nSoftware For Lesions Suspicious For\nCancer","","","Same as the predicate device."],["Primary Intended User","Trained physicians in the intended\nworkflow (Radiologist/Urologist)","","","Trained physicians in the intended\nworkflow (Radiologist)","","","Same as the predicate device –\nintended for use by the\nappropriate trained physicians."],["Anatomical Site:","Prostate only","","","Breast only","","","Different, but same intended\nuse and the differences do not\nraise different questions of\nsafety or effectiveness."],["Oncological Workflow of\nInterest","Prostate Cancer","","","Breast Cancer","","","Different, but same intended\nuse within the workflow and\nthe differences do not raise\ndifferent questions of safety or\neffectiveness."],["Clinical Workflow Steps\nWhere Used:","Image Review and Workflow Support\nInterventional/Treatment Planning and\nGuidance for Diagnostic and Interventional\nProcedures","","","Image Review and Workflow Support","","","Similar to the predicate device."],["Platform/Architecture","Cloud-only solution","","","Software-only platform","","","Similar – both devices are\nWeb-based software devices."],["DICOM Compatible","Yes","","","Yes","","","Same as the predicate device."],["Type of Scans","MR, DICOM-compatible","","","MR, DICOM-compatible","","","Same as the predicate device."],["Image Navigation Tools","● Pan, zoom, rotate, slice scroll (view\nmultiple slices),","","","● Pan, zoom, rotate, change in contrast,\nslice scroll (view multiple slices)","","","Same as the predicate device."]],"caption_candidate":"5.0 510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221624-p12-t0","doc_id":"K221624","page_num":12,"bbox":[72.25,72.34,719.75,516.36],"n_rows":10,"n_cols":8,"columns":["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],"rows":[["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],["","","Planning Software","","","Quantitative Insights, Inc. QuantX","",""],["","","(Proposed Device)","","","(DEN170022)","",""],["","● Adjust window level,\nminimize/maximize","","","","","",""],["Image Review tools:","● 2D\n● 3D\n● MPR","","","● 2D\n● 3D\n● MIPs","","","Similar to the predicate device."],["Image Manipulation and\nAnalysis","Interventional tool, trajectory, and damage\nvolume overlay (overlay profiles\ncustomizable by the user)","","","Measure and document images","","","Different, but same intended\nuse and the differences do not\nraise different questions of\nsafety or effectiveness."],["Image Segmentation:","Algorithm-driven segmentation of the\nprostate gland with the possibility of\nmanual adjustment","","","Automated segmentation of the ROI","","","Similar to the predicate device."],["Measurement Functionalities","Prostate gland:\n● Volume\n● ROIs within the prostate\nFor each Lesion:\n● Location\n● Volume","","","For each lesion:\n• Volume\n• Surface Area","","","Similar to the predicate device."],["CADx Task","Assessment and characterization of\nprostate lesions/abnormalities confirmed to\ncontain csPCA through biopsy and MR\nimage data.","","","Assessment and characterization of breast\nabnormalities using MR image data.","","","Similar to the predicate device\nwith respect to analysis of\nimage-based information for\nassessment of lesions."],["Lesion Analysis Supported","Extent of Disease (boundary and total\nburden)","","","Risk Stratification, Classification, Extent\nof Disease (boundary and total burden)","","","Subset of the functionalities of\nthe predicate device."]],"caption_candidate":"5.0 510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221624-p13-t0","doc_id":"K221624","page_num":13,"bbox":[72.26,72.34,719.74,403.44],"n_rows":7,"n_cols":8,"columns":["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],"rows":[["","","Avenda Health AI Prostate Cancer","","","Predicate Device:","","Rationale for Substantial\nEquivalence"],["","","Planning Software","","","Quantitative Insights, Inc. QuantX","",""],["","","(Proposed Device)","","","(DEN170022)","",""],["CADx Algorithm","Machine learning-based algorithm based\non patient information and image\nmorphological, intensity, and geometric\ncharacteristics.","","","Machine learning-based algorithm based\non image morphological and enhancement\ncharacteristics.","","","Similar to the predicate device."],["CADx Outputs","Cancer Estimation Map\nDefault Lesion Contour\nEncapsulation Confidence Score","","","QI Score\nSimilar Cases Database (via Image Atlas\nand Histogram Display)","","","The Proposed Device utilizes\ndifferent outputs from the\npredicate device. As these\noutputs do not impact the\nintended use and are similarly\nsupplementary to information\nreviewed by the physician as a\npart of standard of care, they\ndo not raise different questions\nof safety or effectiveness."],["User Must Approve/ Reject\nResults:","Yes","","","Yes","","","Same as the predicate device."],["Export Formats:","● DICOM\n● Planning assets\n● Intervention plan for supported\nsystems","","","● DICOM","","","Similar – both devices allow\nexport of findings for use in\nfuture oncological steps."]],"caption_candidate":"5.0 510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221632-p4-t0","doc_id":"K221632","page_num":4,"bbox":[72.0,114.24,534.34,711.84],"n_rows":20,"n_cols":4,"columns":["Submitter Information [21 CFR 807.929(a)(1)]","","",""],"rows":[["Submitter Information [21 CFR 807.929(a)(1)]","","",""],["Name","","Medical Metrics, Inc.",""],["Address","","2121 Sage Road, Suite 300\nHouston, Texas 77056",""],["Phone number","","+1 713 850-7500",""],["Fax number","","+1 713 850-7527",""],["Establishment Registration\nNumber","","Pending 510(k) clearance and marketing of device",""],["Name of contact person","","Kirk Johnson",""],["Date prepared","","17-October-2022",""],["Name of the device [21 CFR 807.92(a)(2)]","","",""],["Trade name","","Spine CAMP™",""],["Classification name","","Automated Radiological Image Processing Software",""],["Review panel","","Radiology",""],["Regulation Number","","892.2050",""],["Product Code","","QIH",""],["Legally marketed device to which\nequivalence is claimed\n[21 CFR 807.92(a)(3)]","","KIMAX QMA® (K022585)",""],["Device description\n[21 CFR 807.92(a)(4)]","","Spine CAMP™ is a fully-automated image processing software\ndevice. It is designed to be used with X-ray images and is\nintended to aid medical professionals in the measurement and\nassessment of spinal parameters. Spine CAMP™ is capable of\ncalculating distances, angles, linear displacements, angular\ndisplacements, and mathematical combinations of these metrics\nto characterize the morphology, alignment, and motion of the\nspine. These analysis results are presented in the form of\nreports, annotated images, and visualizations of intervertebral\nmotion to support their interpretation.",""],["Indications for use\n[21 CFR 807.92(a)(5)]","","Spine CAMP™ is a fully-automated software that analyzes X-\nray images of the spine to produce reports that contain static\nand/or motion metrics. Spine CAMP™ can be used to obtain\nmetrics from sagittal plane radiographs of the lumbar and/or\ncervical spine and it can be used to visualize intervertebral\nmotion via an image registration method referred to as\n“stabilization.” The radiographic metrics can be used to\ncharacterize and assess spinal health in accordance with\nestablished guidance. For example, common clinical uses\ninclude assessing spinal stability, alignment, degeneration,\nfusion, motion preservation, and implant performance. The\nmetrics produced by Spine CAMP™ are intended to be used to\nsupport qualified and licensed professional healthcare\npractitioners in clinical decision-making for skeletally mature\npatients of age 18 and above.",""],["Summary of the technological characteristics of the device compared to the predicate device\n[21 CFR 807.92(a)(6)]","","",""],["Feature","Spine CAMP™\n(Subject Device)","","KIMAX QMA®\n(Predicate Device K022585)"],["Classification Name","Automated Radiological Image\nProcessing Software","","System, Image Processing,\nRadiological"]],"caption_candidate":"510(K) SUMMARY 510(K) # K221632","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221632-p5-t0","doc_id":"K221632","page_num":5,"bbox":[72.0,72.24,534.93,699.96],"n_rows":18,"n_cols":3,"columns":["Product Code","QIH*\n* The product code for the predicate\ndevice is LLZ. The QIH product\ncode was created subsequent to\nclearance of the predicate device\nand appears to be a better match for\nSpine CAMP™ than LLZ since\nSpine CAMP™ employs non-\nadaptive machine learning\nalgorithms that were trained from\ndata generated by the predicate\ndevice to automate the radiological\nimage processing and analysis.","LLZ"],"rows":[["Product Code","QIH*\n* The product code for the predicate\ndevice is LLZ. The QIH product\ncode was created subsequent to\nclearance of the predicate device\nand appears to be a better match for\nSpine CAMP™ than LLZ since\nSpine CAMP™ employs non-\nadaptive machine learning\nalgorithms that were trained from\ndata generated by the predicate\ndevice to automate the radiological\nimage processing and analysis.","LLZ"],["Runs on Server","Yes","Yes"],["Image Input","DICOM","AVI, DICOM, JPEG, TIFF, BMP"],["Anatomical Area","Spine","Musculoskeletal (including Spine)"],["Image Processing","Vertebral body detection;\nVertebral body landmark\nspecification; Vertebral body\nregistration","Landmark specification; rigid body\nregistration"],["Linear Measurements","Yes","Yes"],["Angular Measurements","Yes","Yes"],["2D Motion Analysis","Yes","Yes"],["Image Registration","Yes","Yes"],["Display of Image Alignment /\nStabilization","Yes","Yes"],["Clinical Reporting","Yes","Yes"],["Human Intervention for\nInterpretation","Required","Required"],["Intended User","Trained professionals","Trained professionals"],["Comparison Summary","",""],["Spine CAMP™ is designed to utilize the same analysis methodology as the predicate device, KIMAX\nQMA®, except that software operations performed manually in the predicate device software are\nautomated in Spine CAMP™ through the use of non-adaptive AI models – specifically for lumbar and\ncervical spine X-rays. The types of inputs and outputs are identical between the two devices. The data\nlabels used to train Spine CAMP™’s AI models were derived directly from the KIMAX QMA®\ntechnology. Similarly, substantial equivalence between Spine CAMP™ and the predicate device was\nestablished by directly running the same images through both systems and evaluating the correlation\nand statistical equivalence of their outputs.","",""],["Performance Data [21 CFR 807.92(b)]","",""],["Summary of bench tests (non-clinical) conducted for determination of substantial equivalence\n[21 CFR 807.92(b)(1)]","",""],["Software verification and validation testing was completed to demonstrate functionality of the device\nacross multiple datasets that had not been used to train any of the AI models and that had ground truth\nestablished directly from the predicate device. Ground-truth results for these validation datasets were\nobtained from experienced operators using the predicate device. The software functioned as intended\nand all results observed were as expected.\nAdditional bench testing was performed by evaluating Spine CAMP™’s performance on a large dataset\nthat was previously analyzed by five experienced operators using the predicate device. This dataset\nincluded 215 lateral cervical spine radiographs and 232 lateral lumbar spine radiographs. Statistical\ncorrelations and equivalence tests were performed by directly comparing vertebral landmark\ncoordinates, image calibration, and radiographic metrics between Spine CAMP™ and the predicate\ndevice. This analysis demonstrated correlation and statistical equivalence for all variables evaluated.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221680-p6-t0","doc_id":"K221680","page_num":6,"bbox":[77.54,478.15,545.38,584.23],"n_rows":5,"n_cols":2,"columns":["Predicate Device Information",""],"rows":[["Predicate Device Information",""],["Device Name:","Xeleris V Processing and Review System"],["Manufacturer:","GE Medical Systems Israel, Functional Imaging"],["510(k) Number:","K201103"],["Regulation Number/\nProduct Code:","21CFR 892.2050\nLLZ"]],"caption_candidate":"Product Codes: LLZ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221680-p6-t1","doc_id":"K221680","page_num":6,"bbox":[77.54,607.3,545.38,713.38],"n_rows":5,"n_cols":2,"columns":["Reference Device Information",""],"rows":[["Reference Device Information",""],["Device Name:","Olinda/EXM v2.0"],["Manufacturer:","Hermes Medical Solutions AB"],["510(k) Number:","K163687"],["Regulation Number/\nProduct Code:","21 CFR 892.1100\nIYX"]],"caption_candidate":"Product Code: LLZ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221680-p7-t0","doc_id":"K221680","page_num":7,"bbox":[77.66,94.82,545.26,200.9],"n_rows":5,"n_cols":2,"columns":["Reference Device Information",""],"rows":[["Reference Device Information",""],["Device Name:","Xeleris 4.0 Processing and Review System"],["Manufacturer:","GE Medical Systems Israel, Functional Imaging"],["510(k) Number:","K153355"],["Regulation Number/\nProduct Code:","21CFR 892.2050\nLLZ"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221680-p10-t0","doc_id":"K221680","page_num":10,"bbox":[80.95,94.93,531.28,413.33],"n_rows":9,"n_cols":8,"columns":["Attributes","","","Predicate Device","","","Proposed Device",""],"rows":[["Attributes","","","Predicate Device","","","Proposed Device",""],["","","","Xeleris V Processing and Review","","","Xeleris V Processing and Review",""],["","","","System (K201103)","","","System",""],["","Q.Thera AI Application","","","","","",""],["Supported Input Data","","- NM Imaging Data: SPECT-CT and\nWhole-body Planar","","","- NM Imaging Data: SPECT-CT, PET-\nCT, and Whole-body Planar\n- Non-Imaging Data","",""],["Image Pre-Processing\nApplication","","- Preparation for Dosimetry Toolkit","","","- Preparation for Dosimetry Toolkit\n- Q.Volumetrix MI for Q.Thera AI","",""],["Supported Dosimetry\nCalculations","","- Organ and Lesion isotope\nresidence time","","","- Organ and Lesion isotope\nresidence time\n- Radiation dose calculations per\nMIRD committee of SNM and\nICRP Publication 89","",""],["","Generate Planar Application","","","","","",""],["Derived Planar\nImages","","Not Available","","","- Derived planar images from\nSPECT-CT studies, as cleared on\nthe reference Xeleris 4.0.\n- Derived planar images from\nSPECT only studies.","",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221706-p4-t0","doc_id":"K221706","page_num":4,"bbox":[84.6,524.64,510.7,605.14],"n_rows":5,"n_cols":3,"columns":["Device","510(k)Number","ProductName"],"rows":[["Device","510(k)Number","ProductName"],["PredicateDevice","K191928","AccuContourTM"],["ReferenceDevice","K182624","MIM-MRTDosimetry"],["ReferenceDevice","K173636","Velocity"],["ReferenceDevice","K181572","WorkflowBox"]],"caption_candidate":"Ⅲ.PREDICATEDEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221706-p6-t0","doc_id":"K221706","page_num":6,"bbox":[22.73,121.44,816.45,498.24],"n_rows":5,"n_cols":6,"columns":["ITEM","ProposedDevice","PredicateDevice\nK191928","ReferenceDevice\nK182624","ReferenceDevice\nK173636","ReferenceDevice\nK181572"],"rows":[["ITEM","ProposedDevice","PredicateDevice\nK191928","ReferenceDevice\nK182624","ReferenceDevice\nK173636","ReferenceDevice\nK181572"],["RegulatoryInformation","","","","",""],["RegulationNo.","21CFR892.2050","21CFR892.2050","21CFR892.2050","21CFR892.2050","21CFR892.2050"],["ProductCode","QKB","QKB","LLZ","LLZ","LLZ"],["Indication for\nUse","It is used by radiation\noncology department\nto register\nmulti-modality images\nand segment\n(non-contrast) CT\nimages, to generate\nneeded information for\ntreatment planning,\ntreatment evaluation\nand treatment\nadaptation.","It is used by radiation oncology\ndepartment to register\nmulti-modality images and\nsegment (non-contrast) CT\nimages, to generate needed\ninformation for treatment\nplanning, treatment evaluation\nandtreatmentadaptation.","MIMsoftwareisusedbytrained\nmedical professionals as a tool\nto aid in evaluation and\ninformation management of\ndigital medical images. The\nmedical image modalities\ninclude, but are not limited to,\nCT, MRI, CR, DX, MG, US,\nSPECT, PET and XA as\nsupported by ACR/NEMA\nDICOM 3.0. MIM assists in the\nfollowingindications:\nReceive, transmit, store,\n\nretrieve, display, print, and\nprocess medical images\nandDICOMobjects.\nCreate, display and print\n\nreports from medical\nimages.","Velocityisasoftwarepackagethat\nprovides the physicians a means\nfor comparison of medical data\nincluding imaging data that is\nDICOMcompliant.\nIt allows the display, annotation,\nvolume operation, volume\nrendering, registration, and\nfusion of medical images as an\naid during use by diagnostic\nradiology, oncology, radiation\ntherapy planning and other\nmedical specialties. Velocity is\nnotintendedformammography.","Workflow Box is a software\nsystem designed to allow users\nto route DICOM-compliant data\nto and from automated\nprocessing components.\nSupported modalities include\nCT,MR,RTSTRUCT.\nWorkflow Box includes\nprocessing components for\nautomatically contouring\nimaging data using deformable\nimage registration to support\natlas based contouring,\nre-contouringofthesamepatient\nand machine learning based\ncontouring.\nWorkflow Box is a data routing\nandimage processing toolwhich\nautomaticallyappliescontoursto"]],"caption_candidate":"Table1ComparisonofTechnologyCharacteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221706-p9-t0","doc_id":"K221706","page_num":9,"bbox":[22.73,90.24,816.45,498.24],"n_rows":5,"n_cols":6,"columns":["","","","ones, this device should\nonly be used for research\npurposes.\nLossy compressed\nmammographic images and\ndigitized film screen images\nmust not be reviewed for\nprimary image interpretations.\nImages that are printed to film\nmust be printed using an\nFDA-approved printer for the\ndiagnosis of digital\nmammography images.\nMammographic images must be\nviewed on a display system that\nhasbeen clearedbythe FDAfor\nthe diagnosis of digital\nmammography images. The\nsoftware is not to be used for\nmammographyCAD.","",""],"rows":[["","","","ones, this device should\nonly be used for research\npurposes.\nLossy compressed\nmammographic images and\ndigitized film screen images\nmust not be reviewed for\nprimary image interpretations.\nImages that are printed to film\nmust be printed using an\nFDA-approved printer for the\ndiagnosis of digital\nmammography images.\nMammographic images must be\nviewed on a display system that\nhasbeen clearedbythe FDAfor\nthe diagnosis of digital\nmammography images. The\nsoftware is not to be used for\nmammographyCAD.","",""],["Label/labeling","Conform with 21CFR\nPart801","Conformwith21CFRPart801","Conformwith21CFRPart801","Conformwith21CFRPart801","Conformwith21CFRPart801"],["Operating\nSystem","Windows","Windows","WindowsandMACsystem","WindowsandMACsystem","Windows"],["SegmentationFeatures","","","","",""],["Algorithm","DeepLearning","DeepLearning","Atlas-based","Atlas-based","Atlas Based contouring,"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221706-p10-t0","doc_id":"K221706","page_num":10,"bbox":[22.73,90.24,816.45,500.24],"n_rows":9,"n_cols":6,"columns":["","","","","","registrationbased\nre-contouring, machine learning\nbasedcontouring"],"rows":[["","","","","","registrationbased\nre-contouring, machine learning\nbasedcontouring"],["Compatible\nModality","Non-ContrastCT","Non-ContrastCT","Non-ContrastCT","Non-ContrastCT","CT、MR"],["Compatible\nScannerModels","No Limitation on\nscanner model,\nDICOM 3.0\ncompliancerequired.","No Limitation on\nscanner model,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM3.0compliancerequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired."],["Compatible\nTreatment\nPlanning\nSystem","No Limitation on TPS\nmodel,DICOM\n3.0 compliance\nrequired.","No Limitation on TPS model,\nDICOM\n3.0compliancerequired.","No Limitation on TPS model,\nDICOM\n3.0compliancerequired.","No Limitation on TPS model,\nDICOM\n3.0compliancerequired.","No Limitation on TPS model,\nDICOM\n3.0compliancerequired."],["Unattended\nworkstation","Yes","No","Notstated","No","Yes"],["RegistrationFeatures","","","","",""],["Algorithm","IntensityBased.","IntensityBased.","IntensityBased.","IntensityBased.","IntensityBased."],["Image\nregistration","Auto rigid registration\nand auto deformable\nregistration.","Autorigidregistration","Auto rigid registration and\ndeformableregistration.","Auto rigid registration and\ndeformableregistration.","Auto rigid registration and\ndeformableregistration."],["Compatible\nModality","Auto rigid registration:\nCT,MRI,PET\nAuto deformable\nregistration: CT, MRI,\nCBCT","CT,MRI,PET","CT, MRI, CR, DX, MG, US,\nSPECT,PETandXA","PET/SPECT/CT/MRI","CT,MRI"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221706-p11-t0","doc_id":"K221706","page_num":11,"bbox":[22.75,90.24,816.43,483.84],"n_rows":10,"n_cols":6,"columns":["Compatible\nScannerModels","No Limitation on\nscanner model,\nDICOM 3.0\ncompliancerequired.","No Limitation on\nscanner model,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM3.0compliancerequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired."],"rows":[["Compatible\nScannerModels","No Limitation on\nscanner model,\nDICOM 3.0\ncompliancerequired.","No Limitation on\nscanner model,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM3.0compliancerequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired."],["Compatible\nTreatment\nPlanning\nSystem","No Limitation on\nscanner model,\nDICOM 3.0\ncompliancerequired.","No Limitation on\nscanner model,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM3.0compliancerequired.","No Limitation on scanner\nmodel,\nDICOM 3.0 compliance\nrequired."],["PlanEvaluationFeature","","","","",""],["Display of\nDICOM RT\nPlans","Yes","No","Notstated","Yes","No"],["Isodose Line\nDisplay","Yes","No","Notstated","Yes","No"],["DVH statistics\ndisplay","Yes","No","Notstated","Yes","No"],["RT Plans\ncomparison","Yes","No","Notstated","Yes","No"],["DoseAnalysisFeature","","","","",""],["Display of\nDICOM RT\nDoses","Yes","No","Notstated","Yes","No"],["Dose\naccumulation","Yes","No","Notstated","Yes","No"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221716-p7-t0","doc_id":"K221716","page_num":7,"bbox":[71.03,97.71,524.13,762.73],"n_rows":2,"n_cols":3,"columns":["","Subject device: Cina Software","Predicate device: Cina software\n(K200855)"],"rows":[["","Subject device: Cina Software","Predicate device: Cina software\n(K200855)"],["Intended Use /\nIndications for\nUse","Cina is a radiological computer\naided triage and notification\nsoftware indicated for use in the\nanalysis of (1) non-enhanced head\nCT images and (2) CT angiography\nof the head.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communicating\nsuspected positive findings of (1)\nhead CT images for Intracranial\nHemorrhage (ICH) and (2) CT\nangiography of the head for large\nvessel occlusion (LVO) of the\nanterior circulation (distal ICA,\nMCA-M1 or proximal MCA-M2).\nCina uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected (1)\nICH or (2) LVO on a standalone\nWeb application in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH or LVO\nfindings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only, and\nare not intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage, and it is not intended to be\nused as a diagnostic device.\nThe results of Cina are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nultimately responsible for reviewing\nfull images per the standard of care.","Cina is a radiological computer aided\ntriage and notification software\nindicated for use in the analysis of (1)\nnon-enhanced head CT images and\n(2) CT angiographies of the head.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by\nflagging and communicating\nsuspected positive findings of (1) head\nCT images for Intracranial\nHemorrhage (ICH) and (2) CT\nangiographies of the head for large\nvessel occlusion (LVO).\nCina uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected (1) ICH\nor (2) LVO on a standalone Web\napplication in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with\nnotifications for cases with suspected\nICH or LVO findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only, and are\nnot intended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image, and it is\nnot intended to be used as a\ndiagnostic device.\nThe results of Cina are intended to be\nused in conjunction with other patient\ninformation and based on professional\njudgment to assist with\ntriage/prioritization of medical images.\nNotified clinicians are ultimately\nresponsible for reviewing full images\nper the standard of care."]],"caption_candidate":"Table 1: Substantial Equivalence Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221716-p8-t0","doc_id":"K221716","page_num":8,"bbox":[71.03,71.04,524.13,541.92],"n_rows":12,"n_cols":3,"columns":["","Subject device: Cina Software","Predicate device: Cina software\n(K200855)"],"rows":[["","Subject device: Cina Software","Predicate device: Cina software\n(K200855)"],["User\npopulation","Radiologist","Radiologist"],["Anatomical\nregion of\ninterest","Head","Head"],["Data\nacquisition\nprotocol","Non contrast CT scan of the head\nor neck and CT angiogram images\nof the brain","Non contrast CT scan of the head or\nneck and CT angiogram images of the\nbrain"],["View DICOM\ndata","DICOM information about the\npatient, study and current image","DICOM information about the patient,\nstudy and current image"],["Segmentation\nof region of\ninterest","No; device does not mark, highlight,\nor direct users’ attention to a\nspecific location in the original\nimage","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification /\nPrioritization","Yes","Yes"],["Preview\nimages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases.","Presentation of a preview of the study\nfor initial assessment not meant for\ndiagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No","No"],["Structure","- LVO and ICH image processing\napplications\n- Cina Platform (worklist and Image\nViewer)","- LVO and ICH image processing\napplications\n- Cina Platform (worklist and Image\nViewer)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221716-p9-t0","doc_id":"K221716","page_num":9,"bbox":[71.03,640.33,524.13,762.24],"n_rows":8,"n_cols":5,"columns":["Prevalence","Cina - ICH triage application","","Cina - LVO triage application",""],"rows":[["Prevalence","Cina - ICH triage application","","Cina - LVO triage application",""],["","PPV (%)","NPV (%)","PPV (%)","NPV (%)"],["10%","80.2","99.0","81.7","99.8"],["15%","86.6","98.5","87.7","99.6"],["20%","90.1","97.8","91.0","99.5"],["25%","92.4","97.1","93.1","99.3"],["30%","94.0","96.3","94.5","99.1"],["35%","95.2","95.5","95.6","98.8"]],"caption_candidate":"Table 1: PPV and NVP values for ICH and LVO image processing applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221716-p10-t0","doc_id":"K221716","page_num":10,"bbox":[71.03,71.04,524.26,119.27],"n_rows":3,"n_cols":5,"columns":["40%","96.1","94.4","96.4","98.6"],"rows":[["40%","96.1","94.4","96.4","98.6"],["45%","96.8","93.2","97.1","98.2"],["50%","97.3","91.9","97.6","97.9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221716-p10-t1","doc_id":"K221716","page_num":10,"bbox":[71.03,217.8,524.26,306.6],"n_rows":3,"n_cols":7,"columns":["Time-to-\nNotification","MEAN ± SD\n(seconds)","MEDIAN\n(seconds)","Lower\n95% CI\n(seconds)","Upper\n95% CI\n(seconds)","MIN\n(seconds)","MAX\n(seconds)"],"rows":[["Time-to-\nNotification","MEAN ± SD\n(seconds)","MEDIAN\n(seconds)","Lower\n95% CI\n(seconds)","Upper\n95% CI\n(seconds)","MIN\n(seconds)","MAX\n(seconds)"],["Cina-ICH\n(N = 814)","13.2 ± 2.9","13.2","13.0","13.4","8.6","39.1"],["Cina-LVO\n(N = 476)","25.8 ± 7.0","24.7","25.1","26.4","13.0","55.3"]],"caption_candidate":"Table 2: Time-to-notification for ICH and LVO image processing applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221727-p6-t0","doc_id":"K221727","page_num":6,"bbox":[70.88,126.88,510.27,658.8],"n_rows":6,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","syngo.CT Extended Functionality\n(SOMARIS/8 VB70)","","","syngo.CT Extended Functionality\n(SOMARIS/8 VB60)","",""],["1. Average","The extension offers the possibility to\naverage on a pixel-by-pixel basis of two\ndifferent DICOM images. The “Average”\nfunctionality can be used on individual\nframes of the same series, or for frames\nbelonging to different series. The tool\nsaves a DICOM image as result series. This\nextension does not introduce any new\nclinical algorithms or features.","","","N/A","",""],["2. Vessel Extension","The user can perform a vascular\nevaluation supporting the following main\nfunctionalities:\n• Measuring vessels\n• Creating DICOM snapshots or result\nseries for documenting findings\n• Working on images that are acquired\nwith CT or MR scanner systems\nconstituting one or more volumes of\nvascular structures\nModification:\nImproved quality of the bone removal\nalgorithm for the head & neck region.\nSegmentation of the bones use a deep\nlearning algorithm instead of a\ntraditional image processing.","","","The user can perform a vascular\nevaluation supporting the following main\nfunctionalities:\n• Measuring vessels\n• Creating DICOM snapshots or result\nseries for documenting findings\n• Working on images that are acquired\nwith CT or MR scanner systems\nconstituting one or more volumes of\nvascular structures","",""],["3. Interactive Spectral\nImaging","Display different representations of Dual\nEnergy data.\nModifications:\nSupport of circular and elliptic ROIs. In\nVB70 version the measurement tool\nsupports all others ROIs (ROI Circle (incl.\nelliptic) / ROI Freehand / ROI Auto\nContour / ROI Polygonal).","","","Display different representations of Dual\nEnergy data.","",""],["4. Oncology","The oncology extension offers tools for\nlocalization and evaluation of nodules.\nModifications:\nWith SOMARIS/8 VB70, the spectral\ninformation displayed for circular ROIs\nwas extended to arbitrarily shaped ROIs.","","","The oncology extension offers tools for\nlocalization and evaluation of nodules.","",""]],"caption_candidate":"level in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221727-p7-t0","doc_id":"K221727","page_num":7,"bbox":[70.88,499.88,524.44,723.06],"n_rows":8,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-300","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set; PS 3.1 – 3.20","06/27/2016","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)/A1:2016","01/14/2019","AAMI, ANSI, IEC","",""],["5-125","Software/\nInformatics","Medical devices – Application of risk\nmanagement to medical devices; 14971 Third\nEdition 2019-12","12/23/2019","ISO","",""],["5-129","General I\n(QS/RM)","Medical devices - Part 1: Application of\nusability engineering to medical devices\nIEC 62366-1:2016","07/06/2020","ANSI, AAMI, IEC","",""],["5-117","General I\n(QS/RM)","Medical devices - Symbols to be used with\nmedical device labels, labelling, and\ninformation to be supplied - Part 1: General\nrequirements 15223-1:2016","8/21/2017","ISO","",""]],"caption_candidate":"commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221733-p6-t0","doc_id":"K221733","page_num":6,"bbox":[94.37,219.08,499.69,263.16],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsyngo MR XA50A","K213693, cleared on\nFebruary 25, 2022","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"MR XA51A is substantially equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221733-p7-t0","doc_id":"K221733","page_num":7,"bbox":[94.37,442.57,499.68,737.34],"n_rows":11,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognition","Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/\nEMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012\nand\nA2:2010/(R)2012\n(Consolidated Text)","ANSI AAMI"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-40","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Second\nedition 2007-03-01","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1:2015","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"]],"caption_candidate":"and NEMA standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221738-p4-t0","doc_id":"K221738","page_num":4,"bbox":[85.5,158.41,534.5,293.78],"n_rows":7,"n_cols":3,"columns":["510(k) Sponsor","Neosoma, Inc.",""],"rows":[["510(k) Sponsor","Neosoma, Inc.",""],["Address","44 Farmers Row\nGroton, MA 01450",""],["Correspondence\nPerson","","Aly H. Abayazeed, MD."],["","","Co-founder and Chief Medical Officer"],["Contact Information","","aly.abayazeed@neosomainc.com"],["","","443-804-8096"],["Date Prepared","June 14, 2022",""]],"caption_candidate":"1.1 General Information K221738","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221738-p4-t1","doc_id":"K221738","page_num":4,"bbox":[85.5,350.39,534.5,440.39],"n_rows":5,"n_cols":2,"columns":["Proprietary Name","NS-HGlio"],"rows":[["Proprietary Name","NS-HGlio"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"1.2 Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221738-p4-t2","doc_id":"K221738","page_num":4,"bbox":[85.5,496.63,534.5,604.63],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","NeuroQuant"],"rows":[["Proprietary Name","NeuroQuant"],["Premarket Notification","K170981"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","LLZ"],["Regulatory Class","II"]],"caption_candidate":"1.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221738-p5-t0","doc_id":"K221738","page_num":5,"bbox":[72.25,419.5,545.37,718.5],"n_rows":4,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nNS-HGlio","Predicate Device\nNeuroQuant manufactured by\nCorTechs Labs\nK170981"],"rows":[["Feature/\nFunction","Subject Device:\nNS-HGlio","Predicate Device\nNeuroQuant manufactured by\nCorTechs Labs\nK170981"],["Type of Scans","MRI:\nAcquired using four different MRI\nsequences either in 2D or 3D using\na specified protocol\n(T1 pre-contrast, T1 post-contrast,\nT2 and FLAIR)","MRI:\nNeuroquant: 3D T1 pre-contrast scans\nacquired with specified protocols\nLesionquant: 3D FLAIR scan acquired\nwith specified protocol"],["Intended\nAnatomy","Brain","Brain"],["Lesion Review","2D and 3D","2D"]],"caption_candidate":"1.6 Comparison of Technological Characteristics with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221738-p6-t0","doc_id":"K221738","page_num":6,"bbox":[72.33,72.13,545.42,514.5],"n_rows":6,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nNS-HGlio","Predicate Device\nNeuroQuant manufactured by\nCorTechs Labs\nK170981"],"rows":[["Feature/\nFunction","Subject Device:\nNS-HGlio","Predicate Device\nNeuroQuant manufactured by\nCorTechs Labs\nK170981"],["Segmentation","Semi-automatic and manual\nsegmentation of high-grade glioma","Semi-automatic and manual\nsegmentation of brain structures"],["Quantification","Volumetric measurement of the\nsub-components of high-grade\nglioma","Automated measurement of brain\ntissue volumes and structures and\nlesions"],["Output","- Provides volumetric\nmeasurements of high-grade\nbrain glioma and\nsub-components\n- Includes segmented color\noverlays of sub-components and\nreports\n- Automatically compares results\nto prior scans when available","- Provides volumetric measurements\nof brain structures and lesions\n- Includes segmented color overlays\nand morphometric reports\n- Automatically compares results to\nreference percentile data and to prior\nscans when available"],["Image Format","DICOM","DICOM"],["Report","YES","YES"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p5-t0","doc_id":"K221762","page_num":5,"bbox":[84.32,172.14,551.64,228.24],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["BoneMRI v1.2","MRIguidance B.V.","K202404"]],"caption_candidate":"Table 5-1 Predicate Device – BoneMRI v1.2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p6-t0","doc_id":"K221762","page_num":6,"bbox":[72.19,513.42,523.77,705.6],"n_rows":6,"n_cols":4,"columns":["","Predicate Device","Subject Device",""],"rows":[["","Predicate Device","Subject Device",""],["","","","Comment"],["","BoneMRI v1.2","BoneMRI v1.4",""],["","","",""],["","","",""],["Indications for\nUse","BoneMRI is an\nimage processing\nsoftware that can be\nused for image\nenhancement in\nMRI images. It can\nbe used to visualize\nthe bone structures\nin MRI images with\nenhanced contrast\nwith respect to the","BoneMRI is an\nimage processing\nsoftware that can be\nused for image\nenhancement in\nMRI images. It can\nbe used to visualize\nthe bone structures\nin MRI images with\nenhanced contrast\nwith respect to the","Similar –\nBoneMRI\nv1.4 has an\nexpanded\nindications for\nuse\nincluding the\nboney structures\nof the lumbar\nspine."]],"caption_candidate":"A. Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p7-t0","doc_id":"K221762","page_num":7,"bbox":[72.23,116.76,523.76,516.72],"n_rows":9,"n_cols":4,"columns":["","Predicate Device","Subject Device",""],"rows":[["","Predicate Device","Subject Device",""],["","","","Comment"],["","BoneMRI v1.2","BoneMRI v1.4",""],["","","",""],["","","",""],["","surrounding soft\ntissue. It is to be\nused in the pelvic\nregion, which\nincludes the boney\nanatomy of the\nsacrum, hip bones\nand femoral heads.\nWarning: BoneMRI\nimages are not\nintended to replace\nCT images and are\nnot to be used for\ndiagnosis or\nmonitoring of\n(primary or\nmetastatic) tumors.","surrounding soft\ntissue. It is to be\nused in the pelvic\nregion, which\nincludes the bony\nanatomy of the\nsacrum, hip bones\nand femoral heads;\nand the lumbar\nspine region, which\nincludes the bony\nanatomy of the\nvertebrae from L3 to\nS1. BoneMRI is not\nto be used for\ndiagnosis or\nmonitoring of\n(primary or\nmetastatic) tumors.\nWarning: BoneMRI\nimages are not\nintended to replace\nCT images",""],["21CFR Section","892.2050","892.2050","The same"],["Product Code","QIH","QIH","The same"],["Target Population","Adults","Adults","The same"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p7-t1","doc_id":"K221762","page_num":7,"bbox":[72.23,582.48,523.76,692.88],"n_rows":8,"n_cols":4,"columns":["","Predicate Device","Subject Device",""],"rows":[["","Predicate Device","Subject Device",""],["","","","Comment"],["","BoneMRI v1.2","BoneMRI v1.4",""],["","","",""],["","","",""],["Device Nature","Software package","Software package","The same"],["Operating\nSystem","Linux","Linux","The same"],["Data input","MRI images in\nDICOM format","MRI images in\nDICOM format","The same"]],"caption_candidate":"B. Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p8-t0","doc_id":"K221762","page_num":8,"bbox":[72.13,116.76,523.61,696.36],"n_rows":8,"n_cols":4,"columns":["","Predicate Device","Subject Device",""],"rows":[["","Predicate Device","Subject Device",""],["","","","Comment"],["","BoneMRI v1.2","BoneMRI v1.4",""],["","","",""],["","","",""],["Data output","MRI images in\nDICOM format","MRI images in\nDICOM format","The same"],["Processing\nAlgorithms","MRIguidance\nsoftware\nimplements an\nimage\nenhancement\nalgorithm using\nconvolutional\nneural network.\nOriginal images are\nenhanced by\nrunning them\nthrough a cascade\nof filter banks,\nwhere thresholding\nand scaling\noperations are\napplied. Separate\nneural network-\nbased filters are\nobtained to assign\na Hounsfield Unit\n(HU) value to a\nsingle volume\nelement, based on\nintensity and\ncontextual\ninformation. The\nparameters of the\nmodel were\nobtained through\nan algorithm\ndevelopment\npipeline.","MRIguidance\nsoftware\nimplements an\nimage\nenhancement\nalgorithm using\nconvolutional\nneural network.\nOriginal images\nare enhanced by\nrunning them\nthrough a cascade\nof filter banks,\nwhere thresholding\nand scaling\noperations are\napplied. Separate\nneural network-\nbased filters are\nobtained to assign\na Hounsfield Unit\n(HU) value to a\nsingle volume\nelement, based on\nintensity and\ncontextual\ninformation. The\nparameters of the\nmodel were\nobtained through\nan algorithm\ndevelopment\npipeline.","The same"],["User Interface","None – enhanced\nimages are viewed\non existing PACS\nworkstations","None – enhanced\nimages are viewed\non existing PACS\nworkstations","The same"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221762-p9-t0","doc_id":"K221762","page_num":9,"bbox":[72.21,116.76,523.66,418.8],"n_rows":6,"n_cols":4,"columns":["","Predicate Device","Subject Device",""],"rows":[["","Predicate Device","Subject Device",""],["","","","Comment"],["","BoneMRI v1.2","BoneMRI v1.4",""],["","","",""],["","","",""],["Workflow","The software\noperates on\nDICOM files on the\nfile system,\nenhances the\nimages, and stores\nthe enhanced\nimages on the file\nsystem. The receipt\nof original DICOM\nimage files and\ndelivery of\nenhanced images\nas DICOM files\ndepends on other\nsoftware systems.\nEnhanced images\nco-exist with the\noriginal images.","The software\noperates on\nDICOM files on the\nfile system,\nenhances the\nimages, and stores\nthe enhanced\nimages on the file\nsystem. The\nreceipt of original\nDICOM image files\nand delivery of\nenhanced images\nas DICOM files\ndepends on other\nsoftware systems.\nEnhanced images\nco-exist with the\noriginal images.","The same"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p8-t0","doc_id":"K221868","page_num":8,"bbox":[34.68,226.08,577.32,708.96],"n_rows":8,"n_cols":4,"columns":["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],"rows":[["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],["510(k) No.","K221868","K190362","－"],["Proprietary Name","QOCA® image Smart CXR\nImage Processing System","HealthPNX","－"],["Manufacturer","Quanta Computer Inc.","Zebra Medical Vision Ltd.","－"],["Regulation\nNumber","21 CFR 892.2080","21 CFR 892.2080","Same"],["Product Code","QFM","QFM","Same"],["Classification","Class II","Class II","Same"],["Intended Use","QOCA® image Smart CXR\nImage Processing System is a\nsoftware as medical device\n(SaMD) used, through artificial\nintelligence/deep learning\ntechnology, to analyze chest\nX-ray images of adult patient,\nand then identify cases with\nsuspected pneumothorax. This\nproduct shall be used in\nconjunction with Picture\nArchiving and Communication\nSystem (PACS) at the hospital.\nThis product will automatically\nanalyze the DICOM files","The Zebra Pneumothorax device\nis a software workflow tool\ndesigned to aid the clinical\nassessment of adult Chest X-Ray\ncases with features suggestive of\nPneumothorax in the medical\ncare environment.\nHealthPNX analyzes cases using\nan artificial intelligence\nalgorithm to identify suspected\nfindings.\nIt makes case-level output\navailable to a PACS/workstation\nfor worklist prioritization or\ntriage. HealthPNX is not","Similar\nBoth devices are\nintended to aid in\nworklist triage by\nproviding notification\nof suspected\npneumothorax cases\nusing an artificial\nintelligence algorithm.\nThey are not intended\nto be used on a\nstand-alone basis for\nclinical\ndecision-making or\nclinical diagnosis."]],"caption_candidate":"raise any new issue of substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p9-t0","doc_id":"K221868","page_num":9,"bbox":[34.68,127.32,577.32,708.84],"n_rows":11,"n_cols":4,"columns":["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],"rows":[["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],["","automatically pushed from\nPACS, and then make a notation\nnext to the cases with suspected\npneumothorax. This product is\nonly used to remind radiologists\nto prioritize reviewing cases with\nsuspected pneumothorax. Its\nresults cannot be used as a\nsubstitute for a diagnosis by a\nradiologist, nor can it be used on\na stand-alone basis for clinical\ndecision-making.","intended to direct attention to\nspecific portions or anomalies of\nan image. Its results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it\nintended to rule out\nPneumothorax or otherwise\npreclude clinical assessment of\nX-Ray cases",""],["Notification-only,\nparallel workflow\ntool","Yes","Yes","Same"],["User","Radiologist","Radiologist","Same"],["Radiological image\nformat","DICOM","DICOM","Same"],["Identify patients\nwith prespecified\nclinical condition","Yes","Yes","Same"],["Clinical condition","Pheumothorax","Pheumothorax","Same"],["Alert to finding","Passive notification flagged\nfor review","Passive notification flagged\nfor review","Same"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed\nfrom worklist","Same"],["Modality","X-Ray","X-Ray","Same"],["Body part","Chest","Chest","Same"]],"caption_candidate":"Image Processing System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p10-t0","doc_id":"K221868","page_num":10,"bbox":[34.68,127.32,577.32,637.92],"n_rows":6,"n_cols":4,"columns":["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],"rows":[["Item","Subject device","Predicate device","Substantial\nequivalence\ndetermination"],["Artificial\nIntelligence\nalgorithm","Yes","Yes","Same"],["Limited to analysis\nof imaging data","Yes","Yes","Same"],["Aids prompt\nidentification of\ncases with indicated\nfindings","Yes","Yes","Same"],["Where results are\nreceived","Workstation","PACS/Workstation","Similar\nThe subject device will\nbe connected with\nPACS and receives\npatients’ chest X-ray\nimages. The results will\nonly be presented on\nthe workstation.\nIt will not raise any\nnew issues of safety or\nefficacy."],["Time-to-notification","The average performance time\nis 4.94 seconds.","The average performance time\nis 22.1 seconds.","Same\nBoth devices can\nprovide effective\ntriage."]],"caption_candidate":"Image Processing System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p12-t0","doc_id":"K221868","page_num":12,"bbox":[106.34,575.66,517.3,705.0],"n_rows":7,"n_cols":3,"columns":["Characteristics","Subset","Quantity"],"rows":[["Characteristics","Subset","Quantity"],["Age","22 ≤ age < 65","2,449"],["","65 ≤ age","656"],["Gender","Male","1,516"],["","Female","1,589"],["Radiographic positioning","PA view","2,272"],["","AP erect view","24"]],"caption_candidate":"The characteristics of the MIMIC dataset summarizes in below table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p13-t0","doc_id":"K221868","page_num":13,"bbox":[106.33,127.46,517.31,238.32],"n_rows":6,"n_cols":3,"columns":["Characteristics","Subset","Quantity"],"rows":[["Characteristics","Subset","Quantity"],["","Supine view","809"],["Race and ethnicity","Asian","200"],["","Black/African American","402"],["","Hispanic or Latino","598"],["","White","1,905"]],"caption_candidate":"Image Processing System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221868-p13-t1","doc_id":"K221868","page_num":13,"bbox":[106.33,411.74,517.31,615.12],"n_rows":11,"n_cols":3,"columns":["Characteristics","Subset","Quantity"],"rows":[["Characteristics","Subset","Quantity"],["Age","22 ≤ age < 65","2,697"],["","65 ≤ age","250"],["Gender","Male","1,262"],["","Female","1,685"],["Radiographic positioning","PA view","501"],["","AP erect view","1,431"],["","Supine view","1,015"],["Race and ethnicity","Taiwan population","2,947"],["Imaging equipment","MRAD-A50S","287"],["","MRAD-A80S","185"]],"caption_candidate":"The characteristics of the Taiwanese dataset summarizes in below table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221921-p7-t0","doc_id":"K221921","page_num":7,"bbox":[64.89,116.99,679.32,535.98],"n_rows":12,"n_cols":9,"columns":["Criteria","","DTX Studio Clinic\n3.0\n(Subject Device)\n(K221921)","Videa Caries Assist\nPredicate Device\n(Primary)\n(K213795)","","Pearl - Second","","Comments",""],"rows":[["Criteria","","DTX Studio Clinic\n3.0\n(Subject Device)\n(K221921)","Videa Caries Assist\nPredicate Device\n(Primary)\n(K213795)","","Pearl - Second","","Comments",""],["","","","","","Opinion","","",""],["","","","","","Secondary Predicate","","",""],["","","","","","Device","","",""],["","","","","","(K210365)","","",""],["","Regulatory Information","","","","","","",""],["Regulation #","","892.2070","892.2070","892.2070","","","Same",""],["Classification Name","","Medical Image\nAnalyzer","Medical Image\nAnalyzer","Medical Image\nAnalyzer","","","Same",""],["Device Class","","II","II","II","","","Same",""],["Product Code","","MYN","MYN","MYN","","","Same",""],["","Indication for Use / Intended Use","","","","","","",""],["Indications for Use\nStatement","","DTX Studio Clinic is a\ncomputer assisted\ndetection (CADe)\ndevice that analyses\nintraoral radiographs\nto identify and localize\ndental findings, which\ninclude caries,\ncalculus, periapical\nradiolucency, root\ncanal filling\ndeficiency,\ndiscrepancy at the","Videa Caries Assist is\na computer-assisted\ndetection (CADe)\ndevice that analyzes\nintraoral radiographs\nto identify and localize\ncarious lesions. Videa\nCaries Assist is\nindicated for use by\nboard licensed dentists\nfor the concurrent\nreview of bitewing\n(BW) radiographs","Second Opinion® is a\ncomputer aided\ndetection (\"CADe”)\nsoftware to identify\nand mark regions in\nrelation to suspected\ndental findings which\ninclude Caries,\nDiscrepancy at the\nmargin of an existing\nrestoration, Calculus,\nPeriapical\nradiolucency, Crown","","","Similar to Primary\nPredicate, except for\nsome additional dental\nfindings and age of\npatient population.\nPatient population is\nsame as the Secondary\nPredicate, but the\ndifferences do not\nraise a concern of\nsubstantial",""]],"caption_candidate":"Table 1: Comparison of DTX Studio Clinic to Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221921-p8-t0","doc_id":"K221921","page_num":8,"bbox":[64.87,86.83,679.33,537.37],"n_rows":4,"n_cols":5,"columns":["","margin of an existing\nrestoration and bone\nloss. The DTX Studio\nClinic CADe\nfunctionality is\nindicated for use by\ndentists for the\nconcurrent review of\nbitewing and\nperiapical radiographs\nof permanent teeth in\npatients 15 years of\nage or older.","acquired from adult\npatients aged 22 years\nor older.","(metal, including\nzirconia & non-metal),\nFilling (metal & non-\nmetal), Root canal,\nBridge and Implants. It\nis designed to aid\ndental health\nprofessionals to review\nbitewing and\nperiapical radiographs\nof permanent teeth in\npatients 12 years of\nage or older as a\nsecond reader.","equivalence as\ndemonstrated by\nperformance testing"],"rows":[["","margin of an existing\nrestoration and bone\nloss. The DTX Studio\nClinic CADe\nfunctionality is\nindicated for use by\ndentists for the\nconcurrent review of\nbitewing and\nperiapical radiographs\nof permanent teeth in\npatients 15 years of\nage or older.","acquired from adult\npatients aged 22 years\nor older.","(metal, including\nzirconia & non-metal),\nFilling (metal & non-\nmetal), Root canal,\nBridge and Implants. It\nis designed to aid\ndental health\nprofessionals to review\nbitewing and\nperiapical radiographs\nof permanent teeth in\npatients 12 years of\nage or older as a\nsecond reader.","equivalence as\ndemonstrated by\nperformance testing"],["Technological Characteristics","","","",""],["Focus Area Detection","Automated Detection\nOutput\nMessage indicating if\nand how many dental\nfindings are detected\nSet of togglable\nbounding boxes\naround suspected\ndental findings","Automated Detection\nOutput\nMessage indicating if\nand how many carious\nlesions were detected.\nSet of togglable\nbounding boxes\naround suspected\nlesions","Automated Detection\nOutput\nBounding boxes","Same as Primary\nPredicate"],["","Dental Findings\nCaries, periapical\nradiolucency, root","Dental Findings\nCaries","Dental Findings\nCaries, discrepancy at\nthe margin, calculus,","Similar to Predicate\nDevices, additional\ndental findings are"]],"caption_candidate":"Traditional 510(k) K221921","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221921-p9-t0","doc_id":"K221921","page_num":9,"bbox":[64.83,86.83,679.35,532.57],"n_rows":6,"n_cols":5,"columns":["","canal filling\ndeficiency,\ndiscrepancy at the\nmargin of an existing\nrestoration, bone loss\nand calculus","","and periapical\nradiolucency","identified but the\ndifferences do not\nraise a concern of\nsubstantial\nequivalence as\ndemonstrated by\nperformance testing."],"rows":[["","canal filling\ndeficiency,\ndiscrepancy at the\nmargin of an existing\nrestoration, bone loss\nand calculus","","and periapical\nradiolucency","identified but the\ndifferences do not\nraise a concern of\nsubstantial\nequivalence as\ndemonstrated by\nperformance testing."],["","Reader workflow\nConcurrent Reading","Reader workflow\nConcurrent Reading","Reader workflow\nSecond reader","Same as Primary\nPredicate"],["","Algorithm\nSupervised machine\nlearning","Algorithm\nSupervised machine\nlearning","Algorithm\nSupervised machine\nlearning","Same"],["","Patient population\nPermanent teeth in\npatients 15 years of\nage or older","Patient population\nAdults ≥ 22 years","Patient population\nPermanent teeth in\npatients 12 years of\nage or older","Similar to Predicate\nDevices, the\ndifferences do not\nraise a concern of\nsubstantial\nequivalence as\ndemonstrated by\nperformance testing."],["","Radiographs\nBitewing and\nPeriapical","Radiographs\nBitewing","Radiographs\nBitewing and\nPeriapical","Same as Secondary\nPredicate, the\ndifferences do not\nraise a concern of\nsubstantial\nequivalence as\ndemonstrated by\nperformance testing."],["Intended user","Dentists","US license dentists","Dentists","Same"]],"caption_candidate":"Traditional 510(k) K221921","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221921-p11-t0","doc_id":"K221921","page_num":11,"bbox":[86.42,86.62,540.17,110.42],"n_rows":2,"n_cols":6,"columns":["","ROOT CANAL FILLING","","0.95 [0.91, 0.99]","51.9 [49.3, 54.6]","66.9 [64.3, 69.4]"],"rows":[["","ROOT CANAL FILLING","","0.95 [0.91, 0.99]","51.9 [49.3, 54.6]","66.9 [64.3, 69.4]"],["","DEFICIENCY","","","",""]],"caption_candidate":"Traditional 510(k) K221921","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221923-p5-t0","doc_id":"K221923","page_num":5,"bbox":[77.55,275.71,574.98,713.48],"n_rows":22,"n_cols":9,"columns":["Specification","","","","Subject Swoop® Portable MR","","","Predicate Swoop® Portable MR",""],"rows":[["Specification","","","","Subject Swoop® Portable MR","","","Predicate Swoop® Portable MR",""],["","","","","Imaging System™","","","Imaging System™ (K201722/K221393)",""],["Intended Use/Indications for Use:","","","The Swoop® Portable MR Imaging\nSystem™ is a bedside magnetic\nresonance imaging device for\nproducing images that display the\ninternal structure of the head where\nfull diagnostic examination is not\nclinically practical. When interpreted\nby a trained physician, these images\nprovide information that can be\nuseful in determining a diagnosis.","","","Same","",""],["Patient Population:","","","Adult and pediatric patients (≥ 0\nyears)","","","Same","",""],["Anatomical Sites:","","","Head","","","Same","",""],["Environment of Use:","","","At the point of care in medical\nfacilities, including emergency rooms,\ncritical care units, hospital, or\nrehabilitation rooms.","","","Same","",""],["Energy Used and/or delivered:","","","Magnetic Resonance","","","Same","",""],["","Magnet:","","","","","","",""],["Physical Dimensions","","","835 mm x 630 mm x 652 mm","","","Same","",""],["Bore Opening","","","610 mm x 315 mm","","","Same","",""],["Weight","","","320 kg","","","Same","",""],["Field Strength","","","63.3 mT permanent magnet","","","Same","",""],["","Gradient:","","","","","","",""],["Strength","","","X: 24 mT/m, Y: 23 mT/m, Z: 39 mT/m","","","24 mT/m","",""],["Rise Time","","","X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms","","","1.1 ms","",""],["Slew Rate","","","X: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/s","","","22 T/m/s","",""],["Computer Display","","","Hyperfine-supplied tablet","","","Same","",""],["","RF Coils:","","","","","","",""],["Number of Coils","","","1 head coil","","","Same","",""],["Coil Type","","","TX/RX","","","Same","",""],["Coil Geometry","","","Form-fitting","","","Same","",""],["Inner Dimensions (mm)","","","205 mm x 240 mm","","","Same","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221923-p6-t0","doc_id":"K221923","page_num":6,"bbox":[77.56,72.39,574.98,359.62],"n_rows":14,"n_cols":9,"columns":["Specification","","","","Subject Swoop® Portable MR","","","Predicate Swoop® Portable MR",""],"rows":[["Specification","","","","Subject Swoop® Portable MR","","","Predicate Swoop® Portable MR",""],["","","","","Imaging System™","","","Imaging System™ (K201722/K221393)",""],["Coil Design","","","Linear Volume","","","Same","",""],["Patient Weight Capacity","","","1.6kg-200 kg","","","2.6kg-200 kg","",""],["Operation Temperature","","","15-30 C","","","Same","",""],["Warm Up Time","","","<3 minutes","","","Same","",""],["Temperature Control","","","No","","","Same","",""],["Humidity Control","","","No","","","Same","",""],["","Image Reconstruction Algorithm","","","","","","",""],["T1W\n- T1-Standard\n- T1-Gray/White Contrast","","","Advanced Gridding","","","Same","",""],["T2W\n- T2\n- T2-Fast","","","Advanced Gridding","","","Same","",""],["FLAIR","","","Advanced Gridding","","","Same","",""],["DWI","","","Conjugate Gradient","","","Same","",""],["Image Post-Processing","","","- Advanced Denoising (applies to\nT1W, T2W, and FLAIR only)\n- Image orientation transform\n- Geometric distortion correction\n- Receive coil intensity correction\n- DICOM output","","","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221923-p6-t1","doc_id":"K221923","page_num":6,"bbox":[72.31,536.04,562.69,709.98],"n_rows":3,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Imaging\nPerformance","","","Testing to verify image performance meets all\nimage quality criteria.","","","● NEMA MS 1-2008 (R2020)\n● NEMA MS 3-2008 (R2020)\n● NEMA MS 9-2008 (R2020)\n● NEMA MS 12-2016\n● American College of Radiology (ACR)\nPhantom Test Guidance for Use of\nthe Large MRI Phantom for the ACR\nMRI Accreditation Program\n● American College of Radiology\nstandards for named sequences","",""],["Safety","","","Testing to verify electrical safety and EMC meet the\ncriteria.","","","● ANSI/AAMI ES 60601-\n1:2005/(R)2012\n● IEC 60601-1-2:2014","",""]],"caption_candidate":"requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221923-p7-t0","doc_id":"K221923","page_num":7,"bbox":[72.77,72.84,563.07,140.28],"n_rows":2,"n_cols":3,"columns":["","","● IEC 60601-2-33:2015"],"rows":[["","","● IEC 60601-2-33:2015"],["","Characterization of the specific absorption rate for\nmagnetic resonance imaging systems","● NEMA MS 8-2016"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K221923-p7-t1","doc_id":"K221923","page_num":7,"bbox":[72.77,209.28,563.07,593.16],"n_rows":6,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Biocompatibility","","","Biocompatibility testing of patient-contacting\nmaterials.","","","● ISO 10993-1:2018\n● ISO 10993-5:2009\n● ISO 10993-10:2010","",""],["Cleaning/\nDisinfection","","","Cleaning and disinfection validation of patient-\ncontacting materials.","","","● FDA Guidance, “Reprocessing\nMedical Devices in Health Care\nSettings: Validation Methods and\nLabeling”\n● ISO 17664:2017\n● ASTM F3208-17","",""],["Cybersecurity","","","Testing to verify cybersecurity controls and\nmanagement.","","","● Cybersecurity as recommended in\nFDA guidance, “Content of\nPremarket Submissions for\nManagement of Cybersecurity in\nMedical Devices”","",""],["Software\nVerification","","","Verification testing to ensure the design outputs\nmeet the design input requirements.","","","● IEC 62304:2006\n● FDA Guidance, “Guidance for the\nContent of Premarket Submissions\nfor Software Contained in Medical\nDevices”","",""],["Software\nValidation","","","Validation studies to ensure the device meets user\nneeds and performs as intended.","","","● FDA Guidance, “Guidance for the\nContent of Premarket Submissions\nfor Software Contained in Medical\nDevices”","",""]],"caption_candidate":"for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p4-t0","doc_id":"K222036","page_num":4,"bbox":[98.28,280.08,524.76,473.16],"n_rows":2,"n_cols":2,"columns":["510(k) Owner (Manufacturer)","Medipixel, Inc.\nDooam Building 7F, 61, Yanghwa-ro, Mapo-gu, Seoul, Republic of Korea,\n04037\nPhone: +82-70-4699-0460\nFax: +82-50-7534-4375\nE-mail: contact@medipixel.io"],"rows":[["510(k) Owner (Manufacturer)","Medipixel, Inc.\nDooam Building 7F, 61, Yanghwa-ro, Mapo-gu, Seoul, Republic of Korea,\n04037\nPhone: +82-70-4699-0460\nFax: +82-50-7534-4375\nE-mail: contact@medipixel.io"],["Correspondence Person","Seokjin Ham\nQuality Management Representative of Medipixel, Inc.\nPhone: +82-10-3664-3896\nE-mail: harry.ham@medipixel.io\nHye-Ri Choi\nRA Manager of Medipixel, Inc.\nPhone: +82-70-4699-0460\nE-mail: contact@medipixel.io"]],"caption_candidate":"2) SUBMITTER’S INFORMATION [21 CFR 807.92(a)(1)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p4-t1","doc_id":"K222036","page_num":4,"bbox":[98.28,513.0,524.76,620.22],"n_rows":8,"n_cols":2,"columns":["Proprietary name","Medipixel XA"],"rows":[["Proprietary name","Medipixel XA"],["Model Name","MPXA-2000"],["Common/Usual Name","Cardiovascular Image Analysis Software"],["Product Code","QIH"],["Regulation Number","21 CFR 892.2050"],["Classification Names","Automated Radiological Image Processing Software"],["Device Class","II"],["Classification Panel","Radiology"]],"caption_candidate":"3) SUBJECT DEVICE [21 CFR 807.92(a)(2)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p4-t2","doc_id":"K222036","page_num":4,"bbox":[98.28,683.52,524.76,735.0],"n_rows":3,"n_cols":2,"columns":["Proprietary Name","QAngio XA (X-RAY VVA, K112807)"],"rows":[["Proprietary Name","QAngio XA (X-RAY VVA, K112807)"],["Common/Usual Name:","Radiological Image Processing Software"],["Product Code","LLZ"]],"caption_candidate":"The identified predicate devices within this submission are shown as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p6-t0","doc_id":"K222036","page_num":6,"bbox":[103.33,253.1,532.55,722.76],"n_rows":10,"n_cols":3,"columns":["Item","New device","Predicate Device"],"rows":[["Item","New device","Predicate Device"],["Device Name","MPXA-2000","QAngio XA (X-RAY VVA)"],["Manufacturer","Medipixel, Inc.","Medis Medical Imaging\nSystems, B.V."],["510(k) Number","-","K112807"],["Product code","QIH","LLZ"],["Regulation No.","21 CFR 892.2050","21 CFR 892.2050"],["Class","II","II"],["Indications for Use","MPXA-2000 is indicated for use\nin clinical settings where\nvalidated and reproducible\nquantified results are needed to\nsupport the calculations in X-ray\nangiographic images of the\ncoronary arteries, for use on\nindividual patients with coronary\nartery disease (CAD). MPXA-\n2000 is indicated for use in adult\npatients only.\nWhen the quantified results\nprovided by MPXA-2000 are\nused in a clinical setting on X-\nray images of an individual\npatient, they can be used to\nsupport the clinical decisions\nmaking for the diagnosis of the\npatient or the evaluation of the\ntreatment applied. In this case,\nthe results are explicitly not to be\nregarded as the sole, irrefutable\nbasis for clinical diagnosis, and\nthey are only intended for use by\nthe responsible clinicians.","X-RAY VVA is indicated for\nuse in clinical settings where\nvalidated and reprodlucible\nquantified results are needed to\nsupport the calculations in X-\nray angiographic images of the\nchambers of the and heart of\nblood vessels, for use on\nindividual patients with\ncardiovascular disease.\nWhen the quantified results\nprovided by X-RAY VVA are\nused in a clinical setting on X-\nray images of an individual\npatient, they can be used to\nsupport the clinical decisions\nmaking for the diagnosis of the\npatient or the evaluation of the\ntreatment applied. In this case,\nthe results are explicitly not to\nbe regarded as the sole,\nirrefutable basis for clinical\ndiagnosis, and they are only\nintended for use by the\nresponsible clinicians."],["Patient Population","Patient with cardiovascular\ndisease.","Patient with cardiovascular\ndisease."],["Intended Users","Cardiologists, Radiologists","Cardiologists, Radiologists"]],"caption_candidate":"General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p7-t0","doc_id":"K222036","page_num":7,"bbox":[103.32,161.88,532.56,732.6],"n_rows":12,"n_cols":4,"columns":["Input data type","","X-ray angiographic data in\nDICOM format\n(vendor-independent)","X-ray angiographic data in\nDICOM format\n(vendor-independent)"],"rows":[["Input data type","","X-ray angiographic data in\nDICOM format\n(vendor-independent)","X-ray angiographic data in\nDICOM format\n(vendor-independent)"],["Manual editing of automatic results by\nuser","","Yes","Yes"],["Calibration","","- Automatic calibration\nbased on isocenter\ncalibration factor in\nDICOM file\n- Other manual calibration\noptions (catheter\ncalibration)","- Automatic calibration\nbased on isocenter\ncalibration factor in\nDICOM file\n- Other manual calibration\noptions (catheter, marker\ncatheter, sphere, grid,\ncircle manual and line\ncalibration)"],["Automatic angiographic series\nloading into the software from the\nangiography equipment","","Yes","No"],["Visualization/ Edit Tools",""," Zooming, panning\n Editing vessel\ncontours\n Angle, Length, Area,\nText Annotation"," Zooming, panning\n Editing vessel\ncontours"],["Quantitative\nAnalysis","Automated 2D\narterial contour\nsegmentation","Yes","Yes"],["","Classification of\nvessel types","Yes\nLAD, LCX, and RCA","No"],["","Optional Stent\nanalysis including\nstent edges","No","Yes"],["Analysis\nResults","Results for multiple\nlesions and additional\nuser-defined ROIa)","Results for multiple lesions and\nadditional user-defined ROIa)","Results for multiple lesions and\nadditional user-defined ROIa)"],["","Vessel analysis","main and side branch","Straight (main), ostial, and\nbifurcation (side branch)"],["","Vessel quantifications","- % Diameter Stenosis\n- Minimum lumen diameter\n(MLD)\n- Proximal and distal\ndiameters (at P- and D-\nmarker positions)\n- ROIa) length\n- Reference Diameter","- % Diameter Stenosis\n- Minimum lumen diameter\n(MLD)\n- Proximal and distal\ndiameters (at P- and D-\nmarker positions)\n- Lesion length\n- Reference Diameter"],["","Stent related statistics","No","- Length of stent and stent"]],"caption_candidate":"Technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222036-p8-t0","doc_id":"K222036","page_num":8,"bbox":[103.32,119.52,532.56,316.2],"n_rows":6,"n_cols":4,"columns":["","","","edges\n- MLD and its position\n- In-stent Mean diameter"],"rows":[["","","","edges\n- MLD and its position\n- In-stent Mean diameter"],["Ventricle analysis","","No","Yes"],["Automatically load and visualize ECG\ndata acquired from the DICOM file","","Yes","No"],["Automatic EoD (End of Diastole)\nphase detection in DICOM file based\non ECG.","","Yes","No"],["Data Reporting","","Patient and study details,\ncalibration, annotation,\nmeasurement, and analysis\ndetails.","Patient and study details,\ncalibration, annotation,\nmeasurement, and analysis\ndetails."],["Export file formats","","PDF, Excel","DICOM, BMP, JPEG, AVI and\nthe raw file format"]],"caption_candidate":"MPXA-2000","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p5-t0","doc_id":"K222070","page_num":5,"bbox":[75.36,394.56,542.88,436.8],"n_rows":2,"n_cols":3,"columns":["Predicate medical\ndevice name","Manufacturer","510K number"],"rows":[["Predicate medical\ndevice name","Manufacturer","510K number"],["EndoNaut","Therenva","K212383"]],"caption_candidate":"3. Predicate device and accessories","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p7-t0","doc_id":"K222070","page_num":7,"bbox":[39.37,137.64,542.85,734.16],"n_rows":10,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["System Trade (and Com-\nmon) Name","EndoNaut System","","","EndoNaut System","","","Identical\nTwo new system configura-\ntions have been added (MHS\nand FHS). The tests carried\nout and the risk analyses did\nnot reveal any particular risk\nand validated the safety and\nperformance of the systems.","",""],["Medical Device Software\nTrade Name","EndoNaut","","","EndoNaut SW","","","Similar\nBecause a new variant of En-\ndoNaut Software is intro-\nduced, we introduce a new\nnaming convention to avoid\nconfusion between Endo-\nNaut (Standalone) SW and\nEndoNaut (Server) SW.\nThe naming convention is\ndetailed in Section 6 (Endo-\nNaut System Device De-\nscription).\nNo risk related to identifica-\ntion between the two soft-\nware variants.","",""],["Manufacturer","Therenva SAS","","","Therenva SAS","","","Identical","",""],["Accessory 1","EndoNaut Workstation","","","EndoNaut Workstation","","","Minor change\nSee below “Workstation\ncart”","",""],["Accessory 2","EndoSize Software\n(K160376)","","","EndoSize Software\n(K160376)","","","Identical\nTherefore, substantially\nequivalent.","",""],["Accessory 3","EndoNaut Workstation\nMain Display","","","EndoNaut Server Main Dis-\nplay","","","New","",""],["Identification and traceabil-\nity (UDI)","EndoNaut (system):\n3760262480046\nEndoNaut SW\n(Standalone):\n3760262480022","","","EndoNaut (system) (Variant\n1 = EndoNaut SW + Endo-\nNaut Workstation):\n3760262480046\nEndoNaut System MHS:\n3760262480084\nEndoNaut System FHS:\n3760262480077\nEndoNaut (Standalone)SW:","","","Similar\nNo risk related to identifica-\ntion between EndoNaut\nmedical device software/sys-\ntem because different UDI-\nDIs are allocated.\nNo risk related to identifica-\ntion of EndoNaut System\nbecause different UDI-DIs\nare allocated.","",""]],"caption_candidate":"discussion","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p8-t0","doc_id":"K222070","page_num":8,"bbox":[39.37,127.8,542.86,730.08],"n_rows":11,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["","EndoNaut Workstation\nTS1CA2DS1-2:\n3760262480039","","","3760262480022\nEndoNaut (Server) SW:\n3760262480053\nEndoNaut Workstation\nTS1CA2DS1-2:\n3760262480039\nEndoNaut Server Main Dis-\nplay SW: 3760262480091","","","New UDI-DI allocated to\nEndoNaut SW medical de-\nvice software variant, Endo-\nNaut Server and its new ac-\ncessory EndoNaut Server\nMain Display\nSee also “Labelling” here af-\nter.","",""],["Software versioning","2-level versioning\nVersion x.y","","","3-level versioning\nVersion x.y.z","","","Similar\nAdoption of a more tradi-\ntional versioning system\nmore commonly applied by\nsoftware publishers to Endo-\nNaut (Server) SW and Endo-\nNaut Server Main Display\nSW.\nThis change did not raise any\nparticular risk nor questions\nof safety and effectiveness.","",""],["Product Code","OWB","","","OWB (Primary product\ncode), LLZ (Secondary\nproduct code)","","","Similar\nOWB is used as Primary\nproduct code in reference to\nour original predicates but in\nno case does EndoNaut pro-\nduce x-rays. LLZ product\ncode is much more relevant.","",""],["Regulation Number","892.1650","","","892.1650\n892.2050","","","Similar\nSecondary code added.","",""],["Regulation Names","Interventional Fluoroscopic\nX-Ray System","","","Interventional Fluoroscopic\nX-Ray System\nMedical Image Management\na nd Processing System","","","Similar\nRegulation name of second-\nary code added which is\nmore adequate for our ad-\nvanced medical imaging de-\nvice.","",""],["Software Safety class (62304)","B","","","B","","","Identical\nTherefore, substantially\nequivalent.","",""],["Level of concern","Moderate","","","Moderate","","","Identical\nTherefore, substantially\nequivalent.","",""],["Intended use","EndoNaut provides image\nguidance by overlaying pre-\noperative 3D vessel anatomy\nonto live fluoroscopic im-\nages in order to assist in the","","","EndoNaut is an image fusion\nsoftware solution and com-\nputerized navigational sys-\ntem intended to assist X-ray\nfluoroscopy-guided","","","Similar\nMinor rewording of the In-\ntended Use has been made to\nfacilitate the understanding\nby the users and recipients of","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p9-t0","doc_id":"K222070","page_num":9,"bbox":[39.39,127.8,542.81,727.17],"n_rows":41,"n_cols":11,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","","Substantial",""],["","","K212383","","","","","","","Equivalence Discussion",""],["","positioning of the guide-\nwires, catheters and other\nendovascular devices.","","","procedures in the positioning\nof surgical instruments and\nendovascular devices.","","","","the information but also to\nmake the \"imaging input\ndata\" consistent with the \"in-\ndications for use\".\nThe general purpose of the\ndevice and its function re-\nmain unchanged. The minor\nrewording of the Intended\nUse does not raise different\nquestions of safety and ef-\nfectiveness.","",""],["Indications for use","EndoNaut is indicated for\nthe treatment of patients with\nendovascular diseases and\nwho needs for example\n(without this list being re-\nstrictive):\n• endovascular aortic an-\neurysm repair (AAA\nand TAA),\n• angioplasty,\n• stenting,\n• embolization in iliac ar-\nteries and correspond-\ning veins.\nEndoNaut is indicated for\nendovascular procedures in\nthe thorax, abdomen, pelvis\nand lower limbs.","","","EndoNaut is an image fusion\nsoftware solution and com-\nputerized navigational sys-\ntem intended to assist X-ray\nfluoroscopy-guided proce-\ndures in the positioning of\nsurgical instruments and\nendovascular devices.\nEndoNaut is indicated for\nuse by Physicians for pa-\ntients undergoing a fluoros-\ncopy X-ray guided proce-\ndure in the chest, abdomen,\npelvis, neck and lower limbs,\nsuch as aneurysm repair, ar-\ntery/vein embolization, or\nperipheral artery disease\ntreatment.\nThe information provided by\nthe software or system is in\nno way intended to substitute\nfor, in whole or in part, the\nsurgeon's judgment and\nanalysis of the patient's con-\ndition.\nIt is mandatory to check the\nreal-time anatomy with a\nsuitable imaging technique,\nsuch as a contrast-enhanced\nangiography, before deploy-\ning any invasive medical de-\nvice.","EndoNaut is an image fusion","","","Similar\nWithout being a X-ray de-\nvice itself, as a matter of\nprinciple, EndoNaut works\nwith fluoroscopic images to\nproduce image fusion. The\nclear reference to X-ray\nguided procedures aims at\nproviding more transpar-\nency.\nConditions and anatomical\nlocations are the same, just\nwritten in a slightly different\nway.","",""],["","","","","","software solution and com-","","","","",""],["","","","","","puterized navigational sys-","","","","",""],["","","","","","tem intended to assist X-ray","","","","",""],["","","","","","fluoroscopy-guided proce-","","","","",""],["","","","","","dures in the positioning of","","","","",""],["","","","","","surgical instruments and","","","","",""],["","","","","","endovascular devices.","","","","",""],["","","","","","","","","","",""],["","","","","","EndoNaut is indicated for","","","","",""],["","","","","","use by Physicians for pa-","","","","",""],["","","","","","tients undergoing a fluoros-","","","","",""],["","","","","","copy X-ray guided proce-","","","","",""],["","","","","","dure in the chest, abdomen,","","","","",""],["","","","","","pelvis, neck and lower limbs,","","","","",""],["","","","","","such as aneurysm repair, ar-","","","","",""],["","","","","","tery/vein embolization, or","","","","",""],["","","","","","peripheral artery disease","","","","",""],["","","","","","treatment.","","","","",""],["","","","","","","","","","",""],["","","","","","The information provided by","","","","",""],["","","","","","the software or system is in","","","","",""],["","","","","","no way intended to substitute","","","","",""],["","","","","","for, in whole or in part, the","","","","",""],["","","","","","surgeon's judgment and","","","","",""],["","","","","","analysis of the patient's con-","","","","",""],["","","","","","dition.","","","","",""],["","","","","","","","","","",""],["","","","","","It is mandatory to check the","","","","",""],["","","","","","real-time anatomy with a","","","","",""],["","","","","","suitable imaging technique,","","","","",""],["","","","","","such as a contrast-enhanced","","","","",""],["","","","","","angiography, before deploy-","","","","",""],["","","","","","ing any invasive medical de-","","","","",""],["","","","","","vice.","","","","",""],["","","","","","","","","","",""],["","","","","","","","","","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p10-t0","doc_id":"K222070","page_num":10,"bbox":[39.39,127.8,542.83,727.68],"n_rows":6,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["Labelling","1 label in the “about” section\nfor the Medical Device Soft-\nware with the Trade Name\n“EndoNaut Software”.\n+\n1 label on the workstation\nwith the Trade Name “Endo-\nNaut” (for the whole Sys-\ntem) and Workstation model\nNumber = TS1CA2DS1-2 +\nunique Serial (production)\nNumber (for the whole Sys-\ntem)","","","For EndoNaut System:\n1 label in the “about” section\nfor the Medical Device Soft-\nware with the Trade Name\n“EndoNaut Software”.\n+\n1 label on the workstation\nwith the Trade Name “Endo-\nNaut” (for the whole Sys-\ntem) and Workstation model\nNumber = TS1CA2DS1-2 +\nunique Serial (production)\nNumber (for the whole Sys-\ntem)\nFor EndoNaut Server:\n1 label in the “about” section\nfor the Medical Device Soft-\nware server with the Trade\nName “EndoNaut Server”.","","","Identical (EndoNaut Soft-\nware and EndoNaut Work-\nstation)\nNew\nThe label on the new Soft-\nware variant follows the\nsame rule as for EndoNaut\nSoftware.\nAs EndoNaut Server has no\nuser interface, if it is inte-\ngrated into a System, it will\nkeep its own labelling and\nthe labelling of the System\nwill be indicated on another\ncomponent of the System (a\nclient for example). This will\nbe done under the responsi-\nbility of the integrator.","",""],["Directions for use (User\nGuide(s))","1 User Guide for EndoNaut\nSoftware\n1 User Guide for EndoNaut\nWorkstation +\n1 addendum for informing\nabout the conditions govern-\ning the marketing of Endo-\nNaut.","","","For EndoNaut System:\n1 User Guide for EndoNaut\nSoftware\n1 User Guide for EndoNaut\nWorkstation +\n1 addendum for informing\nabout the conditions govern-\ning the marketing of Endo-\nNaut System.\nFor EndoNaut System\ncomposed of EndoNaut\n(Server) SW:\nIntegration manual, Com-\nmunication Protocol and\nDeveloper Documentation.","","","Slight changes to EndoNaut\nStandalone SW IFU only\nfollowing minor SW release.\nNo change to EndoNaut\nWorkstation IFU.\nNew\nEndoNaut Server will be\nprovided with an integration\nmanual and Communication\nProtocol.\nEndoNaut Server Main Dis-\nplay SW will be provided\nwith an integration manual\nand Developer Documenta-\ntion.","",""],["Input data","DICOM Images\nEndoNaut archive produced\nwith Therenva EndoSize\nPlanning Software.\nC-Arm video stream","","","DICOM Images\nEndoNaut archive produced\nwith Therenva EndoSize\nPlanning Software.\nC-Arm video stream","","","Similar\nNo new input data. No new\nfeatures.\nOnly the minimum hardware\nand software requirements\ndiffer slightly due to the","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p11-t0","doc_id":"K222070","page_num":11,"bbox":[39.39,127.8,542.81,554.64],"n_rows":5,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["","Minimum HW and SW re-\nquirements\nClinical and performance re-\nquirements (display of fu-\nsion data, measurements,\nmotion detection, data re-\nfresh, interoperability)","","","Minimum HW and SW re-\nquirements\nClinical and performance re-\nquirements (display of fu-\nsion data, measurements,\nmotion detection, data re-\nfresh, interoperability)","","","different deployment config-\nurations.\nThe hardware compatibility\nevaluation was carried out\nduring the design validation\nof EndoNaut. The require-\nments for hardware were\nalso assessed during the clin-\nical protocol by collecting\ndata on hardware used by the\nsurgeon during the study.\nThe difference did not raise\nany risk nor safety or perfor-\nmance concerns.","",""],["Output data","Verified and validated fea-\ntures (Image visualization,\nmeasurements, fusion, regis-\ntration, motion detection,\ncontrast detection)\nCode and technical docu-\nmentation","","","Verified and validated fea-\ntures (Image visualization,\nmeasurements, fusion, regis-\ntration, motion detection,\ncontrast detection)","","","Similar\nV&V's activities demon-\nstrate an equivalent level of\nperformance of the Endo-\nNaut. For its server version,\ndue to the different architec-\nture, in some cases (recali-\nbration in particular) we\neven note a gain in terms of\nexecution speed. No unac-\nceptable risk for the security\nof users, patients or IT has\nbeen identified. No changes\nwere made to production\nmethods, code review and\nassociated documentation.\nThe outputs produced are\ncompliant with the stand-\nards.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p12-t0","doc_id":"K222070","page_num":12,"bbox":[39.38,127.8,542.84,732.72],"n_rows":7,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["Machine-Learning algo-\nrithms","The algorithms are carried\nby the EndoNaut software\nonly.\nFeatures which call ma-\nchine-learning algorithms:\n• Registration 3D/2D\n• Motion detection\n• Contrast injection\ndetection","","","The algorithms are carried\nby the EndoNaut (standalone\nand server) software only.\nFeatures which call ma-\nchine-learning algorithms:\n• Registration 3D/2D\n• Motion detection\n• Contrast injection\ndetection","","","Similar\nThe algorithms have not\nbeen changed. Only the way\nthey are implemented is dif-\nferent between the EndoNaut\nStandalone Software and the\nEndoNaut Server Software\n(different architectures).\nThese implementation\nchanges do not change the\npurpose of the algorithms\n(they do what they did be-\nfore). The validation carried\nout raised no additional\nquestions for safety and ef-\nfectiveness.","",""],["Hardware compatibility","EndoNaut Software is the\nclass II medical device Soft-\nware which runs on a sepa-\nrate interventional tools (im-\naging) workstation, the so-\nnamed EndoNaut Work-\nstation which is the acces-\nsory of the medical device\nsoftware.","","","EndoNaut system consists of\n• a software part that car-\nries the medical features\nand technologies that\nare controlled\nand\n• a hardware part that en-\nables the medical device\nto be used in accordance\nwith its intended pur-\npose. The hardware part\ncan be:\nthe EndoNaut\no\nWorkstation or\na computer meeting\no\nthe minimum Hard-\nware and Software\nrequirements for\nEndoNaut\nstandalone SW or\nEndoNaut Server.\nThe Hardware part\nmust be compliant\nwith the US regula-\ntions.","","","Similar\nHardware and Software re-\nquirements have been ad-\njusted to EndoNaut Server\nand are indicated in the Di-\nrections for use as a prereq-\nuisite. V&V activities didn’t\nshow any risk or failure. No\nadditional questions raised\nfor safety and effectiveness.","",""],["Software Operating System","Windows 10 64 bits","","","Windows 10 64 bits","","","Identical\nTherefore, substantially\nequivalent.","",""],["Software interoperability","EndoNaut requires the use of\nEndoSize software\n(K160376) to prepare patient","","","EndoNaut is interoperable\nwith the EndoSize software\n(K160376) which is de-\nsigned to prepare patient","","","Similar as regards EndoSize\nand New for EndoNaut\n(Server) SW and EndoNaut\nServer Main Display SW","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p13-t0","doc_id":"K222070","page_num":13,"bbox":[39.39,127.8,542.83,682.08],"n_rows":6,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["","data and perform preopera-\ntive sizing.\nData imported from En-\ndoSize include 3D volume,\npreoperative images, sizing\nreport (comments and meas-\nurements), and snapshots\ntaken during sizing.","","","data and perform pre-opera-\ntive sizing.\nData imported from En-\ndoSize include 3D volume,\npreoperative images, sizing\nreport (comments and meas-\nurements), and snapshots\ntaken during sizing.\nEndoNaut Server does not\nhave a user interface. The\nUser interface is provided by\nthe clients.\nExternal interface with cli-\nents is provided through a\ncommunication protocol.","","","Some clarifications are\nmade.\nPreoperative data is a man-\ndatory input for the use of AI\nfeatures, but it is not for the\nPAD features.\nPreoperative data include\npre-op CT images and sizing\nreport (in case of AI proce-\ndures). The stent placement\nstrategy and sizing are usu-\nally performed pre-opera-\ntively via the use of software\ndevices such as EndoSize.\nAlternatives to EndoSize ex-\nist: other sizing or visualiza-\ntion software. In such cases,\nthe data is then printed on\npaper and used in the operat-\ning room as is.\nThe communication protocol\nof EndoNaut (Server) SW\ndid not raise any risk nor\nsafety or performance con-\ncerns.","",""],["Visualization","Intra-operative fluoroscopy\nor angiography, pre-opera-\ntive CT scan image, pre-op-\nerative 3D scanner volume\nreconstruction (if any in case\nof PAD procedures).\nFor AI procedures:\nBefore and during the inter-\nvention, the user can access\ninformation from pre-opera-\ntive sizing report such as pre-\nop CT images, measure-\nments, comments, snap-\nshots and strategy.","","","Intra-operative fluoroscopy\nor angiography, pre-opera-\ntive CT scan image, pre-op-\nerative 3D scanner volume\nreconstruction (if any in case\nof PAD procedures).\nFor AI procedures:\nBefore and during the inter-\nvention, the user can access\ninformation from pre-opera-\ntive sizing report such as pre-\nop CT images, measure-\nments, comments, snap-\nshots and strategy.","","","Identical","",""],["Export","Take and export snapshots.\nExport panoramas in case of\nPAD module.","","","Take and export snapshots.\nExport panoramas in case of\nPAD module.","","","Identical\nTherefore, substantially\nequivalent.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p14-t0","doc_id":"K222070","page_num":14,"bbox":[39.39,127.8,542.81,730.8],"n_rows":5,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["3D-2D / 2D-2D Registration","Display 2D-3D fusion: 3D\nvolume pre-op overlay on\nper-op 2D fluoroscopy.\nSemi-automatic registration\n(automatic or manual initial-\nization, automatic computa-\ntion and manual validation).\nPanorama creation: Acquisi-\ntion and save of fluoroscopy\nand angiography stage by\nstage keeping the same C-\nArm orientation.\nDisplay 2D-2D fusion: 2D\npre-op angiographic overlay\non per-op 2D fluoroscopy.\nSynchronization between\ncurrent per-op 2D fluoros-\ncopy and 2D fluoroscopy\nfrom recorded panorama.","","","Display 2D-3D fusion: 3D\nvolume pre-op overlay on\nper-op 2D fluoroscopy.\nSemi-automatic registration\n(automatic or manual initial-\nization, automatic computa-\ntion and manual validation).\nPanorama creation: Acquisi-\ntion and save of fluoroscopy\nand angiography stage by\nstage keeping the same C-\nArm orientation.\nDisplay 2D-2D fusion: 2D\npre-op angiographic overlay\non per-op 2D fluoroscopy.\nSynchronization between\ncurrent per-op 2D fluoros-\ncopy and 2D fluoroscopy\nfrom recorded panorama.","","","Identical","",""],["Dynamic update on C-arm /\ntable / patient motion","Automatic motion detection\nRegistration: auto-\nmatic/manual initialization\nand manual user validation.","","","Automatic motion detection\nRegistration: auto-\nmatic/manual initialization\nand manual user validation.","","","Similar\nSlight change for EndoNaut\n(Standalone) SW:\nThe registration workflow is\nmodified to be more con-\nsistent with clinical expecta-\ntions.\nThe possibility to start again\na registration in automatic\nmode is offered instead of\nswitching to semi-automatic\nmode after a first try in auto-\nmatic mode. The way the\nautomatic mode works and\nits performance, safety char-\nacteristics are unchanged.\nWithout any change being\nmade to the automatic mode\n(so no impact on safety or\nperformance, risks), users\nhave the possibility to adapt\nthe image received from the\nCArm to display more bone\nstructures for example. Once\nhe relaunches the registra-\ntion in automatic mode, it","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p15-t0","doc_id":"K222070","page_num":15,"bbox":[39.38,127.8,542.84,731.04],"n_rows":8,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["","","","","","","","may get better results at the\nend of the registration pro-\ncess.\nFor EndoNaut (Server) SW:\nThese features have been\ntransferred in the new soft-\nware architecture.\nFinal validation is always re-\nquired. It is implemented at\nthe integrator's discretion via\nthe SYNC_CT_ACCEPT\ncommand.\nNew risks due to the new\nsoftware architecture have\nbeen addressed. New clinical\ndata were not necessary.\nV&V activities were per-\nformed and successful. No\nadditional questions raised\nfor safety and effectiveness.","",""],["Patient contacting","No","","","No","","","Identical","",""],["Energy emitted or absorbed","No","","","No","","","Identical","",""],["Workstation main display &\ncomputer","Panel PC ACL OR-PC 27LP\nRated AC 100-240V, 1.5-0.6\nA ~47 – 63 Hz\nMonitor size: 27’’ LCD\nBrightness: 300 cd/m2\nResolution: 1920 x 1080\nCooling Fanless (no mainte-\nnance)","","","Panel PC ACL OR-PC 27LP\nRated AC 100-240V, 1.5-0.6\nA ~47 – 63 Hz\nMonitor size: 27’’ LCD\nBrightness: 300 cd/m2\nResolution: 1920 x 1080\nCooling Fanless (no mainte-\nnance)","","","Identical","",""],["Workstation secondary dis-\nplay (touch screen)","One Touch monitor ELO\nmodel 1502L,\nrated AC 100-240 V\nInput frequency: 50-60 Hz\nMonitor size: 15.6’’ LCD\nNative resolution:\nFull HD : 1920 x 1080 ;\nHD (WXGA) : 1366 x 768\nBrightness:\nTouch Pro 270 nits\nTouch technology: PCAP","","","One Touch monitor ELO\nmodel 1502L or 1519LM\nrated AC 100-240 V\nInput frequency: 50-60 Hz\nMonitor size: 15.6’’ LCD\nNative resolution:\nFull HD : 1920 x 1080\n(1502L);\nHD (WXGA) : 1366 x 768\n(1502L, 1519 LM)\nBrightness:\n1502L: Touch Pro 270 nits","","","Similar\nSimilar for ELO Touch\n1502L, one reference added\n(1519LM) which offers very\nsimilar performance.\nThe brightness offered by\nthe ELO 1519LM ap-\nproaches the full HD ELO\n1502L.\nThe slight differences be-\ntween the two models do not","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p16-t0","doc_id":"K222070","page_num":16,"bbox":[39.38,127.8,542.85,729.2],"n_rows":9,"n_cols":10,"columns":["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","K212383","","","","","","Equivalence Discussion",""],["","","","","1519LM: 225 nits\nTouch technology: PCAP","","","raise risk, safety nor perfor-\nmance concerns.","",""],["Workstation cart","One mobile frame holder\nITD, including one isolating\ntransformer, rated AC 115V\n/ 230V 50/60Hz 1240VA","","","One mobile frame holder\nITD, including one isolating\ntransformer, rated AC 115V\n/ 230V 50/60Hz 1240VA.","","","Minor change\nChange of pro-cart Basic\nframe: column raised by 16\ncm for better visibility. No\nchange of pro-cart supplier.\nNo change of materials. In-\nstability hazards have been\nevaluated and tested.\nNo confusion possible be-\ntween the old mobile frame\nholder and the new mobile\nframe holder because they\nare different part reference.\nNo overbalance or hazards\nthat could jeopardize the\nsafety of the users and bene-\nficiaries and call into ques-\ntion the performance\nof the medical device could\nbe observed.","",""],["Workstation dimensions","Height: 1740 mm\nWidth (footprint): 661 (640)\nmm\nDepth (footprint): 950 (660)\nmm\nWeight: 70 kg","","","Height: 1850 mm\nWidth (footprint): 661 (640)\nmm\nDepth (footprint): 950 (660)\nmm\nWeight: 72 kg","","","Similar\nMinor dimensional and\nweight changes do not result\nin additional risks.","",""],["Workstation Connectors","Digital video input: DVI-D\nor DVI-I*\nVideo output: HDMI\nNetwork: 10/100/1000 Mbps\nEthernet (RJ45)\nUSB interface USB 3.0\n(x2)","","","Digital video input: DVI-D\nor DVI-I*\nVideo output: HDMI\nNetwork: 10/100/1000 Mbps\nEthernet (RJ45)\nUSB interface USB 3.0\n(x2)","","","Identical","",""],["Workstation Power supply","Input voltage:\n100 – 230 VAC / 50 – 60 Hz","","","Input voltage:\n100 – 230 VAC / 50 – 60 Hz","","","Identical","",""],["Workstation cablings","Connection Box\nFront cable RJ45\nDVI front cable\nUSB 3.0 front cable\n1m (x2)\nPower supplies","","","Connection Box\nFront cable RJ45\nDVI front cable\nUSB 3.0 front cable\n1m (x2)\nPower supplies","","","Identical","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222070-p17-t0","doc_id":"K222070","page_num":17,"bbox":[39.37,127.8,542.86,729.6],"n_rows":12,"n_cols":12,"columns":["Medical Device Software\nName","","","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],"rows":[["Medical Device Software\nName","","","","EndoNaut","","","EndoNaut","","","Comparable Properties an",""],["","","","","(Predicate Device)","","","(Subject Device)","","","Substantial",""],["","","","","K212383","","","","","","Equivalence Discussion",""],["","","","Power supply extension IEC\nC7-C14\nPower supply extension jack\n2.5mm 3m\nIEC extension cable 1m\n(red)\nIEC extension cable 0.5m\n(blue)\nExternal power supply XP\nPOWER (for ELO TOUCH\n1502L)\nExternal power supply\nBICKER (for ACL ORPC-\n27LP) BET-1012M\nVideo cabling: DVI 5m\nOther cables:\nHDMI cable 1.5m\nHDMI/DP adapter\nUSB 3.0 A/B 1m\nUSB 2.0 2m\nEquipotential 1.5m","","","Power supply extension IEC\nC7-C14\nPower supply extension jack\n2.5mm 3m\nIEC extension cable 1m\n(red)\nIEC extension cable 0.5m\n(blue)\nExternal power supply XP\nPOWER (for ELO TOUCH\n1502L)\nExternal power supply\nBICKER (for ACL ORPC-\n27LP) BET-1012M\nVideo cabling: DVI 5m\nOther cables:\nHDMI cable 1.5m\nHDMI/DP adapter\nUSB 3.0 A/B 1m\nUSB 2.0 2m\nEquipotential 1.5m","","","","",""],["IEC 62304","","","Applied","","","Applied","","","Identical","",""],["IEC 62366","","","Applied","","","Applied","","","Identical","",""],["ISO 14971","","","Applied","","","Applied","","","Identical","",""],["","DICOM Standard parts 1-20","","Applied","","","Applied","","","Identical","",""],["Conformity to IEC 60601-1\nof EndoNaut workstation","","","Yes\nFor CENELEC countries","","","Yes\nFor CENELEC countries","","","Identical\nIEC 60601-1 is not a FDA\nrecognized standard version\nbut is applied and included in\nV&V protocol and results.","",""],["Conformity to ANSI AAMI\nES60601-1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012 and\nA2:2010/(R)2012 (Consoli-\ndated Text) of EndoNaut\nworkstation","","","Yes","","","Yes","","","Identical","",""],["Conformity to IEC 60601-2\nof the separate Workstation\nfor navigation tools","","","Yes","","","Yes","","","Identical\nIEC 60601-2 FDA recog-\nnized standard version is ap-\nplied and included in V&V\nprotocol and results.","",""],["Conformity to IEC 60601-1-\n6 of EndoNaut workstation","","","Yes","","","Yes","","","Identical\nIEC 60601-1-6 FDA recog-\nnized standard version is ap-\nplied and included in V&V\nprotocol and results.","",""]],"caption_candidate":"Tel: +33 9 72 52 29 20","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222076-p6-t0","doc_id":"K222076","page_num":6,"bbox":[72.32,129.94,545.74,308.37],"n_rows":7,"n_cols":4,"columns":["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],"rows":[["","510(k) Sponsor","","Ever Fortune.AI Co., Ltd."],["Address","Address","","Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.\nWest Dist.\nTaichung City 403020\nTAIWAN"],["","Applicant","","Joseph Chang"],["Contact Information","Contact Information","","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["","Correspondence Person","","Ti-Hao Wang, MD"],["Contact Information","Contact Information","","886-04-23213838 #168\ntihao.wang@everfortune.ai"],["","Date Prepared","","July 13, 2022"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222076-p6-t1","doc_id":"K222076","page_num":6,"bbox":[72.32,349.97,545.74,463.75],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","EFAI ChestSuite XR Pleural Effusion Assessment System"],"rows":[["","Proprietary Name","","EFAI ChestSuite XR Pleural Effusion Assessment System"],["","Common Name","","EFAI PUEXR v1.0"],["Classification Name","Classification Name","","Radiological Computer-Assisted Prioritization Software For\nLesions"],["","Regulation Number","","21 CFR 892.2080"],["","Regulation Name","","Radiological Computer Aided Triage and Notification Software"],["","Product Code","","QFM"],["","Regulatory Class","","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222076-p6-t2","doc_id":"K222076","page_num":6,"bbox":[72.32,505.35,545.74,621.5],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","HealthCXR"],"rows":[["","Proprietary Name","","HealthCXR"],["","Premarket Notification","","K192320"],["Classification Name","Classification Name","","Radiological Computer-Assisted Prioritization Software For\nLesions"],["","Regulation Number","","21 CFR 892.2080"],["","Regulation Name","","Radiological Computer Aided Triage and Notification Software"],["","Product Code","","QFM"],["","Regulatory Class","","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222076-p8-t0","doc_id":"K222076","page_num":8,"bbox":[72.15,205.32,526.4,720.78],"n_rows":8,"n_cols":7,"columns":["Company","","","","Ever Fortune.AI Co., Ltd.","","Zebra Medical Vision Ltd."],"rows":[["Company","","","","Ever Fortune.AI Co., Ltd.","","Zebra Medical Vision Ltd."],["","","","","(EFAI)","",""],["Device Name","","","EFAI Chestsuite XR Pleural\nEffusion Assessment System","","","HealthCXR"],["","510k Number","","K222076","","","K192320"],["","Regulation No.","","21CFR 892.2080","","","21CFR 892.2080"],["","Classification","","II","","","II"],["","Product Code","","QFM","","","QFM"],["Intended\nUse/Indication for\nUse","","","EFAI Chestsuite XR Pleural\nEffusion Assessment System is\na software workflow tool\ndesigned to aid the clinical\nassessment of adult (18 years of\nage or older) Chest X-Ray cases\nwith features suggestive of\npleural effusion in the medical\ncare environment. EFAI\nChestsuite XR Pleural Effusion\nAssessment System analyzes\ncases using an artificial\nintelligence algorithm to\nidentify suspected findings on\nchest x-ray images taken in PA\nposition. It makes case-level\noutput available to a\nPACS/workstation for worklist\nprioritization or triage. EFAI\nChestsuite XR Pleural Effusion\nAssessment System is not\nintended to direct attention to\nspecific portions or anomalies of\nan image. Its results are not\nintended to be used on a stand-\nalone basis for clinical decision-\nmaking nor is it intended to rule\nout pleural effusion or otherwise\npreclude clinical assessment of","","","The Zebra HealthCXR device is\na software workflow tool\ndesigned to aid the clinical\nassessment of adult Chest X-Ray\ncases with features suggestive of\npleural effusion in the medical\ncare environment. HealthCXR\nanalyzes cases using an artificial\nintelligence algorithm to identify\nsuspected findings. It makes\ncase-level output available to a\nPACS/workstation for worklist\nprioritization or triage.\nHealthCXR is not intended to\ndirect attention to specific\nportions or anomalies of an\nimage. Its results are not intended\nto be used on a stand-alone basis\nfor clinical decision-making nor\nis it intended to rule out pleural\neffusion or otherwise preclude\nclinical assessment of X-Ray\ncases."]],"caption_candidate":"Table - Comparison with the Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222076-p9-t0","doc_id":"K222076","page_num":9,"bbox":[72.18,85.49,526.42,487.89],"n_rows":23,"n_cols":5,"columns":["","","","X-Ray cases.",""],"rows":[["","","","X-Ray cases.",""],["","Intended user","","Radiologist","Radiologist"],["Supported Modalities","","","X-Ray (PA view)","X-Ray (PA or AP view)"],["Body Part","","","Chest","Chest"],["","Artificial Intelligence","","Yes","Yes"],["","Algorithm","","",""],["","Limited to analysis of","","Yes","Yes"],["","imaging data","","",""],["","Aids prompt","","Yes","Yes"],["","identification of cases","","",""],["","with indicated","","",""],["","findings","","",""],["Image Input","","","DICOM","DICOM"],["","Identify patients","","Yes","Yes"],["","with a pre-specified","","",""],["","clinical condition","","",""],["Clinical condition","","","Pleural Effusion","Pleural Effusion"],["Alert to finding","","","Yes; Passive notification\nflagged for review","Yes; notification flagged for\nreview on hospital worklist"],["","Independent of","","Yes; No cases are removed\nfrom worklist","Yes; No cases are removed from\nworklist"],["","standard of care","","",""],["","workflow","","",""],["","Where results are","","PACS / RIS / Workstation","PACS / Workstation"],["","received","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222172-p8-t0","doc_id":"K222172","page_num":8,"bbox":[94.52,356.64,545.44,576.84],"n_rows":8,"n_cols":6,"columns":["","FDA","","Standard","Version","Content"],"rows":[["","FDA","","Standard","Version","Content"],["","Recognition","","","",""],["","Number","","","",""],["13-79","","","IEC 62304","2006+A1:\n2015","Medical Device Software - Software\nLife Cycle Processes"],["12-300","","","NEMA\nStandard PS\n3.1-3.20","2016","Digital Imaging and Communications in\nMedicine (DICOM)"],["5-125","","","ISO 14971","2019","Application of Risk Management to\nMedical Devices"],["5-114","","","AAMI / ANSI /\nIEC 62366-1","2015","Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1","2021","Symbols to be used with information to\nbe supplied by the manufacturer - Part\n1: General requirements"]],"caption_candidate":"The device meets the following recognized US FDA Consensus Standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p2-t0","doc_id":"K222174","page_num":2,"bbox":[257.81,460.39,570.36,557.02],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p4-t0","doc_id":"K222174","page_num":4,"bbox":[72.25,133.48,545.5,246.23],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Synapsica Healthcare, Inc."],"rows":[["510(k) Sponsor","Synapsica Healthcare, Inc."],["Address","2591 Dallas Parkway Suite 300\nFrisco, TX 75034"],["Correspondence Person","Rory A. Carrillo\nRegulatory Consultant | Cosm"],["Contact Information","Email: rory@cosmhq.com\nPhone: (562) 533-7010"],["Date Prepared","July 22, 2022"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p4-t1","doc_id":"K222174","page_num":4,"bbox":[72.25,293.34,545.5,386.71],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","RadioLens v1.0"],"rows":[["Proprietary Name","RadioLens v1.0"],["Common Name","RadioLens v1.0"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"2. Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p4-t2","doc_id":"K222174","page_num":4,"bbox":[72.25,434.26,545.5,531.51],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","Spine CAMP™"],"rows":[["Proprietary Name","Spine CAMP™"],["Premarket Notification","K221632"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p6-t0","doc_id":"K222174","page_num":6,"bbox":[90.25,399.4,521.38,691.5],"n_rows":9,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nRadioLens v1.0","Predicate Device:\nSpine CAMP™\n(K221632)"],"rows":[["Feature/\nFunction","Subject Device:\nRadioLens v1.0","Predicate Device:\nSpine CAMP™\n(K221632)"],["Intended Users","Qualified medical practitioners","Radiologists"],["Intended\nEnvironment","Clinical settings","Clinical settings"],["Device Class","II","II"],["Image Input","DICOM","DICOM"],["Image Display","Static","Static"],["Anatomical\nArea","Spine","Spine"],["Body Part\nDetection","Yes, only through the optional\nSpindleX module (Cervical, Lumbar\nand others for digital x-rays of\nspine)","No"],["Body Position\nDetection","Yes, only through the optional\nSpindleX module\n(Flexion, extension or neutral)","N/A"]],"caption_candidate":"6. Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p7-t0","doc_id":"K222174","page_num":7,"bbox":[90.33,75.33,521.42,353.5],"n_rows":5,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nRadioLens v1.0","Predicate Device:\nSpine CAMP™\n(K221632)"],"rows":[["Feature/\nFunction","Subject Device:\nRadioLens v1.0","Predicate Device:\nSpine CAMP™\n(K221632)"],["Quantitative\nAnalysis","Only through the optional SpindleX\nmodule the following measurements\nare provided:\n-Ruth Jackson’s angle\n-Ferguson's angle\n-Canal diameter\n-Displacement of L3 vertebrae\n-Vertebral offset\n-Motion Segment Integrity,\nTranslational & Angular","-Linear measurements\n-Angular measurements\n-Vertebral body detection\n-Vertebral body landmark\nspecification\n-Vertebral body registration"],["2D Motion\nAnalysis","N/A","Yes"],["Image\nRegistration","N/A","Yes"],["Report\nCreation","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p8-t0","doc_id":"K222174","page_num":8,"bbox":[81.67,370.47,545.33,610.5],"n_rows":9,"n_cols":3,"columns":["CERVICAL","",""],"rows":[["CERVICAL","",""],["Measurement for pathology","Radiologists ICC","Rads & Model ICC"],["Stress Lines (degrees)","0.957 (E)","0.953 (E)"],["Canal Diameter (mm)","0.950 (E)","0.955 (E)"],["Vertebral Offset Neutral (mm)","0.698 (M)","0.707 (M)"],["Angular MSI (degrees)","0.769 (G)","0.781 (G)"],["Translational Motion 5th Edition (mm)","0.712 (M)","0.717 (M)"],["Translational Motion 6th Edition - Flexion\n(mm)","0.793 (G)","0.802 (G)"],["Translational Motion 6th Edition - Extension\n(mm)","0.707 (M)","0.716 (M)"]],"caption_candidate":"The following tables capture the aided versus unaidedagreement:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p8-t1","doc_id":"K222174","page_num":8,"bbox":[81.67,638.31,545.33,709.5],"n_rows":3,"n_cols":3,"columns":["LUMBAR","",""],"rows":[["LUMBAR","",""],["Measurement for pathology","Radiologists ICC","Rads & Model ICC"],["Stress Lines (degrees)","0.979 (E)","0.968 (E)"]],"caption_candidate":"(mm)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222174-p9-t0","doc_id":"K222174","page_num":9,"bbox":[81.62,75.33,545.38,339.5],"n_rows":10,"n_cols":3,"columns":["LUMBAR","",""],"rows":[["LUMBAR","",""],["Measurement for pathology","Radiologists ICC","Rads & Model ICC"],["Canal Diameter (mm)","0.826 (G)","0.784 (G)"],["Ferguson’s Angle (degrees)","0.968 (E)","0.939 (E)"],["Integrity of 3rd Lumbar Vertebra (mm)","0.997 (E)","0.996 (E)"],["Vertebral Offset Neutral (mm)","0.820 (G)","0.777 (G)"],["Angular MSI (degrees)","0.792 (G)","0.771 (G)"],["Translational Motion 5th Edition (mm)","0.710 (M)","0.656 (M)"],["Translational Motion 6th Edition - Flexion\n(mm)","0.809 (G)","0.774 (G)"],["Translational Motion 6th Edition - Extension\n(mm)","0.823 (G)","0.769 (G)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222176-p2-t0","doc_id":"K222176","page_num":2,"bbox":[257.81,430.87,570.36,527.47],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222176-p4-t0","doc_id":"K222176","page_num":4,"bbox":[72.49,430.83,539.68,539.72],"n_rows":6,"n_cols":4,"columns":["","Trade Name","","BoneView 1.1-US"],"rows":[["","Trade Name","","BoneView 1.1-US"],["","510(k) reference","","K222176"],["","Common Name","","Radiological computer assisted detection/diagnosis software for fracture"],["","Regulation","","21 CFR 892.2090"],["","Product Code","","QBS"],["","Classification","","Class II"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222176-p4-t1","doc_id":"K222176","page_num":4,"bbox":[72.49,592.07,539.68,628.15],"n_rows":2,"n_cols":4,"columns":["","Predicate Device","","Gleamer BoneView"],"rows":[["","Predicate Device","","Gleamer BoneView"],["","510(k) reference","","K212365"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K222179-p4-t0","doc_id":"K222179","page_num":4,"bbox":[72.32,161.64,539.76,260.54],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level P, 24 Campbell St\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800 958 487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","July 22, 2022"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222179-p4-t1","doc_id":"K222179","page_num":4,"bbox":[72.32,319.23,539.76,418.64],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CXR Triage Trauma"],["","510(k) reference","","K222179"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM+, QAS*"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222179-p4-t2","doc_id":"K222179","page_num":4,"bbox":[72.32,518.7,539.76,618.1],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CXR Triage Pneumothorax"],["","510(k) reference","","K213941"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222179-p5-t0","doc_id":"K222179","page_num":5,"bbox":[72.32,117.45,539.76,216.82],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Zebra Medical Vision Ltd."],"rows":[["","Manufacturer Name","","Zebra Medical Vision Ltd."],["","Device Name","","HealthPPT"],["","510(k) reference","","K211803"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"IV. REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222179-p8-t0","doc_id":"K222179","page_num":8,"bbox":[72.13,389.76,539.71,446.16],"n_rows":3,"n_cols":9,"columns":["","Finding","","","Product Code","","","AUC (95% CI)",""],"rows":[["","Finding","","","Product Code","","","AUC (95% CI)",""],["Pleural effusion","","","QFM","","","0.980 (0.972-0.986)","",""],["Pneumoperitoneum","","","QAS","","","0.969 (0.950-0.984)","",""]],"caption_candidate":"study are summarized in the tables below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222179-p8-t1","doc_id":"K222179","page_num":8,"bbox":[72.13,474.43,539.71,605.2],"n_rows":7,"n_cols":4,"columns":["Finding","Operating point","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Finding","Operating point","Sensitivity (95% CI)","Specificity (95% CI)"],["Pleural effusion","0.2302","96.0 (94.2,97.7)","88.3 (85.3,91.1)"],["","0.2990","93.8 (91.5,95.8)","91.7 (89.3,94.1)"],["","0.4355","86.3 (83.0,89.4)","95.6 (93.7,97.2)"],["Pneumoperitoneum","0.0322","90.1 (84.2,95.0)","87.4 (82.4,92.3)"],["","0.0484","86.1 (79.2,92.1)","89.6 (85.2,94.0)"],["","0.2266","82.2 (75.2,89.1)","96.2 (93.4, 98.9)"]],"caption_candidate":"Pneumoperitoneum QAS 0.969 (0.950-0.984)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p4-t0","doc_id":"K222268","page_num":4,"bbox":[72.32,150.06,539.76,248.92],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level P, 24 Campbell St\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800 958 487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","July 28, 2022"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p4-t1","doc_id":"K222268","page_num":4,"bbox":[72.32,296.04,539.76,395.44],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CXR Triage Trauma"],["","510(k) reference","","K222268"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p4-t2","doc_id":"K222268","page_num":4,"bbox":[72.32,442.53,539.76,541.9],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CXR Triage Pneumothorax"],["","510(k) reference","","K213941"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p4-t3","doc_id":"K222268","page_num":4,"bbox":[72.32,616.8,539.76,716.2],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Zebra Medical Vision Ltd."],"rows":[["","Manufacturer Name","","Zebra Medical Vision Ltd."],["","Device Name","","HealthVCF"],["","510(k) reference","","K192901"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM"]],"caption_candidate":"IV. REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p7-t0","doc_id":"K222268","page_num":7,"bbox":[72.28,505.28,539.72,537.96],"n_rows":2,"n_cols":2,"columns":["Finding","Results"],"rows":[["Finding","Results"],["Vertebral compression fracture","AUC: 0.954 (95% CI: 0.939-0.968)"]],"caption_candidate":"in the tables below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222268-p7-t1","doc_id":"K222268","page_num":7,"bbox":[72.28,552.53,539.72,603.3],"n_rows":4,"n_cols":8,"columns":["Finding","","Operating\nPoint","Sensitivity (Se)\n(95% CI)","","","Specificity (Sp)",""],"rows":[["Finding","","Operating\nPoint","Sensitivity (Se)\n(95% CI)","","","Specificity (Sp)",""],["","","","","","","(95% CI)",""],["Vertebral compression\nfracture","0.3849","","89.3 (85.7-93.0)","","89.0 (85.8-92.1)","",""],["","0.4834","","85.3 (80.9-89.3)","","90.9 (87.7-94.0)","",""]],"caption_candidate":"Vertebral compression fracture AUC: 0.954 (95% CI: 0.939-0.968)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222275-p6-t0","doc_id":"K222275","page_num":6,"bbox":[72.25,483.37,540.25,525.13],"n_rows":3,"n_cols":2,"columns":["","The cases were gathered from unique female patients 35 years of"],"rows":[["","The cases were gathered from unique female patients 35 years of"],["age or older and included different modalities (DBT and FFDM), manufacturers (Hologic and GE),",""],["and exam types (screening and diagnostic).",""]],"caption_candidate":"pivotal study did not overlap with those used previously to collect data for training or testing the","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p6-t0","doc_id":"K222277","page_num":6,"bbox":[77.66,179.66,545.74,716.26],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],["Intended Use / Indications for\nUse","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of non-\nenhanced head CT and CTPA\nimages. The device is intended\nto assist hospital networks and\ntrained radiologists in workflow\ntriage by flagging and\ncommunication of Intracranial\nHemorrhage (ICH) and\nPulmonary Embolism (PE)\npathologies. For the PE\npathology, the software is only\nintended to be used on single-\nenergy exams.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight\ncases with detected findings on\na standalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor cases with suspected\nfindings. Notifications include\ncompressed preview images\nthat are meant for informational\npurposes only and not intended\nfor diagnostic use beyond\nnotification. The device does\nnot alter the original medical\nimage and is not intended to be\nused as a diagnostic device.","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of CTPA\nimages in adults or transitional\nadolescents aged 18 and older.\nThe device is intended to assist\nhospital networks and\nappropriately trained medical\nspecialists in workflow triage by\nflagging and communication of\nsuspected positive findings of\nPulmonary Embolism (PE)\npathologies.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight\ncases with detected findings on\na standalone desktop\napplication in parallel to the\nongoing standard of care\nimage interpretation. The user\nis presented with notifications\nfor cases with suspected PE\nfindings. Notifications include\ncompressed preview images\nthat are meant for informational\npurposes only and not intended\nfor diagnostic use beyond\nnotification. The device does\nnot alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p7-t0","doc_id":"K222277","page_num":7,"bbox":[77.66,72.24,545.74,695.86],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],["","The results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to\nassist with triage/prioritization\nof medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.","information and based on their\nprofessional judgment, to\nassist with triage/prioritization\nof medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."],["User Population","Hospital networks and\nappropriately trained medical\nspecialists","Hospital networks and\nappropriately trained medical\nspecialists"],["Anatomical Region of Interest","Chest","Chest"],["Data Acquisition Protocol","CTPA","CTPA"],["Notification-Only (/notification\nalerts), Parallel Workflow Tool","Yes","Yes"],["Images\nFormat","DICOM","DICOM"],["Interference with Standard\nWorkflow","No. No cases are removed\nfrom Worklist or deprioritized.","No. No cases are removed\nfrom desktop application or\ndeprioritized."],["Inclusion/\nExclusion Criteria for Clinical\nPerformance Testing","Inclusion criteria\nCT pulmonary angiogram\n●\n(CTPA) with a 64-slice\nscanner or higher;\nSlice thickness 0.5 mm –\n●\n3.0 mm.\nScans performed on adults/\n●\ntransitional adults ≥ 18\nyears of age.\nExclusion Criteria\nAll studies that are\n●\ntechnically inadequate,\nincluding studies with\nmotion artifacts, severe\nmetal artifacts, sub-optimal\nbolus timing or an\ninadequate field of view.","Inclusion criteria\nCT pulmonary angiogram\n●\n(CTPA) with a 64-slice\nscanner or higher;\nSlice thickness 0.5 mm –\n●\n3.0 mm.\nScans performed on adults/\n●\ntransitional adults ≥ 18\nyears of age.\nExclusion Criteria\nAll studies that are\n●\ntechnically inadequate,\nincluding studies with\nmotion artifacts, severe\nmetal artifacts, sub-optimal\nbolus timing or an\ninadequate field of view."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p8-t0","doc_id":"K222277","page_num":8,"bbox":[77.66,72.24,545.74,258.77],"n_rows":3,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],"rows":[["","Predicate Device\nAidoc Briefcase (K203508)","Subject Device\nAidoc Briefcase (K222277)"],["Algorithm","Artificial intelligence algorithm\nwith database of images.","Artificial intelligence algorithm\nwith database of images."],["Structure","- AHS module (image\nacquisition);\n- ACS module (image\nprocessing);\n- Aidoc Worklist application\nfor workflow integration\n(worklist and non-diagnostic\nImage Viewer).","- AHS module (image\nacquisition);\n- ACS module (image\nprocessing);\n- Aidoc Desktop Application\nfor workflow integration\n(Feed/Worklist (alternate\nnames) and non-diagnostic\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p9-t0","doc_id":"K222277","page_num":9,"bbox":[130.63,534.71,481.59,579.7],"n_rows":3,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age","","62.1","","","17.3","","","18","","","64","","","90","","","499","",""],["","(Years)","","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p10-t0","doc_id":"K222277","page_num":10,"bbox":[176.7,100.34,435.38,233.62],"n_rows":6,"n_cols":21,"columns":["Ground\nTruth\nResults","","","","Gender","","","","","","","","","","","All","","","","",""],"rows":[["Ground\nTruth\nResults","","","","Gender","","","","","","","","","","","All","","","","",""],["","","","","Male","","","","","","Female","","","","","","","","","",""],["","","","","N","","","%","","","N","","","%","","","N","","","%",""],["","Positive","","","113","","","22.6","","","100","","","20.0","","","213","","","42.7",""],["","Negative","","","127","","","25.5","","","154","","","30.9","","","281","","","56.6",""],["","All","","","240","","","48.1","","","254","","","50.9","","","494","","","99.0",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222277-p10-t1","doc_id":"K222277","page_num":10,"bbox":[227.52,318.33,384.75,489.52],"n_rows":14,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["","","","201","","","40.3%","",""],["","Siemens","","","","","","",""],["","","","","","","","",""],["","","","100","","","20.0%","",""],["","GE","","","","","","",""],["","","","","","","","",""],["","","","99","","","19.8%","",""],["","Canon","","","","","","",""],["","","","","","","","",""],["","","","99","","","19.8%","",""],["","Philips","","","","","","",""],["","","","","","","","",""],["","Total","","","499","","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p5-t0","doc_id":"K222312","page_num":5,"bbox":[104.06,72.48,506.73,523.51],"n_rows":25,"n_cols":5,"columns":["Planning activity","Module","","Available in",""],"rows":[["Planning activity","Module","","Available in",""],["","","","RayPlan",""],["Automated planning","Plan explorer","No","",""],["","Automated breast planning","No","",""],["","Fallback planning","No","",""],["","Fallback protocol management","No","",""],["Patient data management","Patient data management","Yes","",""],["Patient modeling","Image registration","Yes","",""],["","Structure definition","Yes","",""],["","Deformable registration","No","",""],["","Eye modeling","No","",""],["Plan design","Virtual simulation","Yes","",""],["","Plan setup","Yes","",""],["","3D-CRT beam design","Yes","",""],["","Electron beam design","Yes","",""],["","Proton beam design","No","",""],["","Brachy planning","Yes","",""],["Plan optimization","Plan optimization","Yes","",""],["","Multi criteria optimization","No","",""],["Plan evaluation","Plan evaluation","Yes","",""],["","Robust evaluation","No","",""],["","Biological evaluation","No","",""],["QA preparation","QA preparation","Yes","",""],["Treatment adaptation","Dose tracking","No","",""],["","Adaptive replanning","No","",""]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p6-t0","doc_id":"K222312","page_num":6,"bbox":[72.03,394.61,536.73,778.78],"n_rows":12,"n_cols":5,"columns":["Item","","Compared to","","Comment"],"rows":[["Item","","Compared to","","Comment"],["","","RayStation 11B","",""],["Hardware platform","Substantially Equivalent","","","Both systems use standard office PCs as hardware platform."],["Operating system","Substantially Equivalent","","","Both systems use Windows 10 Professional (or higher) and\nWindows Server 2012 R2 (or higher)."],["Target population","Substantially Equivalent","","","RayStation 11B and RayStation 12A are intended for the\nsame target population and anatomical sites; persons that\nhave been prescribed an external beam radiation therapy or\nmedical oncology treatment."],["Anatomical sites","Substantially Equivalent","","",""],["Human factors","Substantially Equivalent","","","In terms of human factors, the systems are considered\nequivalent. The user interfaces are almost identical."],["Standards met","Substantially Equivalent","","","Both systems comply with the following FDA-recognized\nconsensus standards: IEC 61217:2011, IEC 62083, IEC\n62304:2015, IEC 62366-1:2015, ISO 14971:2019 and with\nIEC 60601-2-68:2014 standard."],["Image types","Substantially Equivalent","","","RayStation 11B and RayStation 12A both support CT, PET\nand MR images for identifying patient organs and contouring."],["Reporting aspects","Substantially Equivalent","","","When evaluating and approving treatment plans, all necessary\ndata is presented to the user and available in print in both\nsystems."],["Image storing","Substantially Equivalent","","","None of the systems is intended for long term storage of\nimages or other patient data."],["Network / remote\nconnections and\ncapabilities","Substantially Equivalent","","","Both systems are capable of network transfer of patient data\nusing the DICOM protocol. RayStation 12A and RayStation\n11B are designed for desktop use and for remote access using\nstandard virtualization techniques. Remote connection to the\nsystem is verified in detail and equivalent to local connection."]],"caption_candidate":"RayStation 12A is compared to the predicate device RayStation 11B.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p7-t0","doc_id":"K222312","page_num":7,"bbox":[72.25,151.4,538.37,780.34],"n_rows":13,"n_cols":7,"columns":["Feature","Description","","Present in","","Present in\nRayStation\n12A","Significantly\nchanged?"],"rows":[["Feature","Description","","Present in","","Present in\nRayStation\n12A","Significantly\nchanged?"],["","","","RayStation","","",""],["","","","11B","","",""],["","","","(K220141)","","",""],["3D\nvisualization","Displays the patient geometry and\nstructures in three dimensions, with the\npossibility to rotate the patient image. If\navailable, the dose distribution and beam\nmodifiers are shown as well.","Yes","","","Yes","No"],["Adaptive\nreplanning","The process of replanning the treatment\nfor a patient, based on information about\ne.g. patient geometry, biology and dose\ndelivery acquired during treatment.","Yes","","","Yes","No"],["Beam\ncommissioning","Modeling of the radiation beam using a\nlimited set of measurements on the clinical\nbeam for commissioning treatment\nmachines to make them available for\ntreatment planning.","Yes","","","Yes","No"],["Beam design","Definition of beam orientations, apertures\nand various beam modifiers in order to\nmanually create a treatment plan.","Yes","","","Yes","No"],["Beam set-up","Manual or automatic definition of\nisocenter, selection of treatment unit from\nthe set of commissioned treatment\nmachines, and specification of\ngantry/couch/collimator angles.","Yes","","","Yes","Yes, new\nfunctionality\nAutomatic\nField in Field\nplanning was\nadded."],["Beam’s eye\nview","Displays the beam’s eye view of the\npatient structures, fluence and beam\nmodifier settings for any beam.","Yes","","","Yes","No"],["Brachy\nplanning","Tools for planning of HDR brachytherapy\ntreatments. Includes channel\nreconstruction and optimization and\nediting of dwell times.","Yes","","","Yes","Yes. Now\nsupports\nElekta\nFlexitron\nafterloaders."],["CyberKnife\nplanning","CyberKnife planning is completely\nintegrated in RayStation. This includes\noptimization of high quality treatment\nplans collimated with MLC, fixed cones\nor iris cones, as well as support for all\nCyberKnife Synchrony techniques for\ntarget tracking and real time motion\nsynchronization.","Yes","","","Yes","No"],["Deformable\nregistration","Establishing a point-to-point mapping\nbetween two images using a deformation\nmodel. Used for mapping of dose and\nstructures between images.","Yes","","","Yes","No"]],"caption_candidate":"Detailed technology comparison table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p8-t0","doc_id":"K222312","page_num":8,"bbox":[72.26,72.24,538.54,667.9],"n_rows":3,"n_cols":5,"columns":["DICOM RT\nexport","Export of images, structure set, plan, and\ndose according to the DICOM RT\nstandard.","Yes","Yes","No"],"rows":[["DICOM RT\nexport","Export of images, structure set, plan, and\ndose according to the DICOM RT\nstandard.","Yes","Yes","No"],["DICOM RT\nimport","Import of images, structure set, plan, and\ndose according to the DICOM RT\nstandard.","Yes","Yes","No"],["Dose\ncalculation\nelectrons","For electron beams RayStation calculates\ndose by the Monte Carlo technique. The\nelectron beam phase space is generated in\nrun time by sampling from a phase space\nmodel where the electrons are created at\nthe secondary scattering foil. Both the\nelectron transport through the treatment\nhead and the in-patient dose computation\nis performed using the Monte Carlo\nalgorithm.\nIn versions prior to RayStation 11A, the\ntransport through the treatment head has\nbeen handled by a Monte Carlo algorithm\ndeveloped by RaySearch, while the in-\npatient transport and dose computation has\nbeen the responsibility of the plug-in dose\nengine VMC++. In RayStation 12A, the\nVMC++ dose engine has been exchanged\nwith an in-patient Monte Carlo transport\nand dose scoring algorithm fully\ndeveloped by RaySearch. Additionally,\nsome minor improvements have been\nmade to the treatment head transport, but\nthis part is essentially the same as in\nRayStation 11B.\nThere are substantial similarities between\nthe replaced VMC++ code and the\nEGSnrc code and these two Monte Carlo\ndose engines agrees on sub-percent level\n[1][2]. The dose engine developed by\nRaySearch is similar to the EGSnrc, as has\nbeen described in references 11, 12, 17, 24\nand 108 in the 008 RSL-D-RS-12A-REF-\nEN-1.0-2022-06-23 RayStation 12A\nReference Manual. Therefore, we\nconclude that the electron dose engine\nused in RayStation 12A (fully developed\nby RaySearch) is substantially equivalent\nto the electron dose engine used in\nRayStation 11B (in-patient dose\ncomputation handled by VMC++).","Yes","Yes","Yes"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p9-t0","doc_id":"K222312","page_num":9,"bbox":[72.26,72.24,538.54,757.9],"n_rows":3,"n_cols":5,"columns":["","The supporting testing confirms\nequivalence between the RayStation 11B\nand RayStation 12A dose engines.\nRegression tests performed during the\nelectron dose engine validation between\nthe two versions are within tolerance\nlimits which shows a similar level of\naccuracy between the two dose engines.\nAcceptance criteria for comparison with\nprevious RayStation dose: The calculated\ndoses shall fail for less than 2% of the data\npoints for gamma 2%/2mm.\nReferences:\n[1] Kawrakow I and Fippel M, \"VMC++,\na MC algorithm optimized for electron\nand photon beam dose calculations for\nRTP,\" Proceedings of the 22nd Annual\nInternational Conference of the IEEE\nEngineering in Medicine and Biology\nSociety (Cat. No.00CH37143), Chicago,\nIL, USA, 2000, pp. 1490-1493 vol.2, doi:\n10.1109/IEMBS.2000.898024.\n[2] Kawrakow I, Fippel M, Friedrich K.\n3D electron dose calculation using a\nVoxel based Monte Carlo algorithm\n(VMC). Med Phys. 1996 Apr;23(4):445-\n57. doi: 10.1118/1.597673. PMID:\n9157256.","","",""],"rows":[["","The supporting testing confirms\nequivalence between the RayStation 11B\nand RayStation 12A dose engines.\nRegression tests performed during the\nelectron dose engine validation between\nthe two versions are within tolerance\nlimits which shows a similar level of\naccuracy between the two dose engines.\nAcceptance criteria for comparison with\nprevious RayStation dose: The calculated\ndoses shall fail for less than 2% of the data\npoints for gamma 2%/2mm.\nReferences:\n[1] Kawrakow I and Fippel M, \"VMC++,\na MC algorithm optimized for electron\nand photon beam dose calculations for\nRTP,\" Proceedings of the 22nd Annual\nInternational Conference of the IEEE\nEngineering in Medicine and Biology\nSociety (Cat. No.00CH37143), Chicago,\nIL, USA, 2000, pp. 1490-1493 vol.2, doi:\n10.1109/IEMBS.2000.898024.\n[2] Kawrakow I, Fippel M, Friedrich K.\n3D electron dose calculation using a\nVoxel based Monte Carlo algorithm\n(VMC). Med Phys. 1996 Apr;23(4):445-\n57. doi: 10.1118/1.597673. PMID:\n9157256.","","",""],["Dose\ncalculation\nphotons","For photon beams RayStation calculates\ndose by the point kernel superposition\nmethod (a.k.a. Collapsed Cone) or a\nMonte Carlo algorithm for radiation\ntransport. The incident energy fluence is\nmodeled as a superposition of a primary\nenergy fluence and a scatter energy\nfluence. The dose contribution from\ncontamination electrons is calculated by a\npencil beam algorithm.","Yes","Yes","No"],["Dose\ncalculation\nproton","For proton beams RayStation uses either\nthe pencil beam algorithm with the Fermi-\nEyges formalism, or a Monte Carlo\nalgorithm for radiation transport. For\npassive beams the beam model accounts\nfor the collimator and compensator block.\nFor scanning beams the beam model\naccounts for the spot phase space\nincluding effects of air-scatter and beam\npaths through magnetic deflection\nelements. The user defined block aperture\nis taken into account in spot selection and\noptimization. In addition to this the\nrelative biological effect (RBE) of proton\nbeams is taken into account, resulting in a\nphoton equivalent dose.","Yes","Yes","No"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p10-t0","doc_id":"K222312","page_num":10,"bbox":[72.26,72.24,538.54,717.82],"n_rows":7,"n_cols":5,"columns":["Dose\ncalculation\nbrachy","For brachy plans RayStation calculates\ndose based on the TG43 formalism.","Yes","Yes","No"],"rows":[["Dose\ncalculation\nbrachy","For brachy plans RayStation calculates\ndose based on the TG43 formalism.","Yes","Yes","No"],["Dose display\n(2D)","Displays the patient geometry with\nstructures superimposed on the image data\ntogether with the dose distribution in\ntransversal, sagittal, and coronal\ndirections.","Yes","Yes","No"],["Dose tracking","Dose tracking scenarios including\ndeformable registration of one CT or\nCBCT to another and subsequent\ndeformation and accumulation of dose.","Yes","Yes","No"],["Eye planning","Tools for specifying a highly detailed\ngeometrical model of the eye based on\nmeasurements from ultrasound and\nsurgery. Support for positioning of\ntantalum clips. Import and visualization of\nfundus images. Creation and dose\ncomputation of proton plans with gaze\nangle-based treatment directions.","Yes","Yes","Yes, Now\nsupports eye\nplanning with\nwedges."],["Fallback\nplanning","Automatic generation of fallback plans\nusing alternative treatment machines and\ntreatment techniques. User-defined\nprotocols specifies the setup of the\nfallback plans which are automatically\ngenerated from the protocols and\noptimized using dose mimicking\nfunctions.","Yes","Yes","No"],["Image\nconversion","Conversion of CBCT images to synthetic\nCT images that can be used for more\naccurate dose calculations.","Yes","Yes","No"],["Inverse\nplanning","The user can define optimization settings\nsuch as optimization tolerance and\nmaximum number of iterations as well as\nsegmentation settings on the multileaf\ncollimator and the Pencil Beam Scanning\nspot pattern. An interface for controlling\nthe optimization process is provided and\nthe progress of optimization is displayed\nin a view. The system generates control\npoints for step-and shoot MLC plans,\nSliding Window plans (DMLC), rotational\nplans (VMAT), 3DCRT plans, Wave Arc\nplans, TomoTherapy plans and proton\nPencil Beam Scanning plans, using the\ndefined optimization problem. The inverse\nplanning can be carried out either through\na conventional inverse approach or by\nusing multi-criteria optimization (photons\nand protons only).","Yes","Yes","No"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p11-t0","doc_id":"K222312","page_num":11,"bbox":[72.26,72.24,538.54,746.74],"n_rows":8,"n_cols":5,"columns":["LET evaluation","Computation and evaluation of dose-\naveraged LET (Linear Energy Transfer)\nfor proton plans. LET is an additional\nphysical quantity that can be used to\nassess the radiobiological effect of the\nproton radiation.","Yes","Yes","No"],"rows":[["LET evaluation","Computation and evaluation of dose-\naveraged LET (Linear Energy Transfer)\nfor proton plans. LET is an additional\nphysical quantity that can be used to\nassess the radiobiological effect of the\nproton radiation.","Yes","Yes","No"],["Machine\ndatabase","Microsoft SQL database for storage of\nbeam model parameters, machine\nconstraints and dose curves with\ndosimetric data for treatment units.","Yes","Yes","No"],["MR based\nplanning","Allowing MR-images as planning images\nand base dose computation on material\noverride ROIs.","Yes","Yes","No"],["Optimization\nfunctions","The optimization functions are specified in\nterms of objectives and constraints to form\nthe optimization problem that is solved by\nthe optimization engine.","Yes","Yes","No"],["Patient\nanatomy\nmodeling","Manual and semi-automatic segmentation\ntools for contouring ROIs slice by slice\ntogether with semi-automated generation\nof the patient outline ROI.\nThe model-based segmentation technique\nallows for semi-automatic delineation of\nstructures by matching 3D shape models\nof the structures to new image data.\nWith atlas-based segmentation, the user\ncan define templates consisting of already\nsegmented image data and use this\ntemplate for segmentation of new patient\nimages.\nWith deep learning segmentation, the user\ncan use trained deep learning models for\nautomatic segmentation of new patient\nimages. (The model training is performed\noffline on clinical CT and structure data.)","Yes","Yes","No"],["Patient\ndatabase","Microsoft SQL database for storage of all\npatient and plan data. Not for long term\nstorage.","Yes","Yes","No"],["Plan Explorer","The system computes a large set of plans\naccording to given rules and the user is\nprovided with tools to select good plans\nfrom these.","Yes","Yes","No"],["Quality\nassurance\npreparation","Tools for transferring the clinical plan to a\nphantom and recalculate dose. The output\nis the dose distribution in DICOM format\nor a 2D dose plane and a QA report.\nPredicted EPID response is retrieved by\nphoton dose computation in a specially\ndesigned phantom.","Yes","Yes","No"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p12-t0","doc_id":"K222312","page_num":12,"bbox":[72.26,72.24,538.54,743.86],"n_rows":11,"n_cols":5,"columns":["RBE dose\nhandling","RBE (Relative Biological Effectiveness)\nmodels can be defined and commissioned.\nFor proton treatments, the user can select\nwhether to look at RBE-corrected dose or\nphysical dose. Dose summation is only\npossible for photon doses and RBE-\ncorrected proton doses.","Yes","Yes","No"],"rows":[["RBE dose\nhandling","RBE (Relative Biological Effectiveness)\nmodels can be defined and commissioned.\nFor proton treatments, the user can select\nwhether to look at RBE-corrected dose or\nphysical dose. Dose summation is only\npossible for photon doses and RBE-\ncorrected proton doses.","Yes","Yes","No"],["Robust\nevaluation","Tools used to answer questions of how the\ndose distribution would appear if the\npatient setup at the time of treatment does\nnot fully correspond to the planning CT. A\nmodel of patient uncertainties such as CT\ninaccuracy and setup errors is used to\ncompute a set of scenario doses for\nevaluation.","Yes","Yes","No"],["Robust\noptimization","Optimization where a model of patient\nuncertainties such as CT inaccuracy, setup\nerrors or organ motion is used during the\noptimization.","Yes","Yes","No"],["Scripting","Scripting gives programmatic access to\nfunctionality, excluding user risk\nmitigations. Through scripting, the clinic\nspecific procedures can be automated. The\noperating system and other applications\ncan be accessed.","Yes","Yes","No"],["Supported\ntreatment\npositions","HFS, FFS, HFP, FFP","Yes","Yes","No"],["","Decubitus left/right","Yes","Yes","No"],["","Seated position (for ions)","Yes","Yes","No"],["System\nintegrity tools","Hardware based license, preventing\nunauthorized useable copies to be made.\nChecksum control of binary files to\nprevent tampering. Data in the patient and\nmachine databases only available for users\nwith administrator rights.","Yes","Yes","No"],["TomoTherapy\nplanning","Planning for TomoTherapy machines is\ncompletely integrated in RayStation. Also\nprovides tools for selection of targets and\nimaging angles for the TomoTherapy\nmachine to use for target tracking during\ndelivery.","Yes","Yes","No"],["Treatment\nadaptation","A general concept where the treatment\nplan is adapted during the course of\ntreatment. Tools available today include\ndeformable dose accumulation, CBCT\ndose calculation and replanning scenarios.","Yes","Yes","No"],["Treatment plan\napproval","Approval of the preferred treatment plan\nand referenced ROIs by authorized\nmedical staff. Once a treatment plan is\napproved, it is locked for any further\nmodification.","Yes","Yes","No"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222312-p13-t0","doc_id":"K222312","page_num":13,"bbox":[72.26,72.24,538.54,328.37],"n_rows":5,"n_cols":5,"columns":["Treatment plan\ncreation","Treatment plan creation with specification\nof plan properties such as number of\nfractions and delivery technique.","Yes","Yes","No"],"rows":[["Treatment plan\ncreation","Treatment plan creation with specification\nof plan properties such as number of\nfractions and delivery technique.","Yes","Yes","No"],["Treatment plan\nevaluation","Evaluation of a single plan. Comparison\nof dose distributions and DVH curves of\ntwo or three plans.","Yes","Yes","No"],["Treatment\ndelivery","An approved plan can be assigned to\nfractions in a treatment course and sent to\nthe treatment delivery device. RayTreat\noffer treatment room interfaces for patient\npositioning, imaging and plan delivery.","Yes","Yes","No"],["Undo/redo and\nauto recovery","The undo stack is saved to the database,\nenabling recovery of RayStation after\ncrash. The user may redo all or selected\nchanges at reopen of patient after crash.","Yes","Yes","No"],["Virtual\nSimulation","Setup of isocenter, beam arrangements\nand basic aperture design. Export to laser\nsystems for patient marking.","Yes","Yes","No"]],"caption_candidate":"K222312","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p5-t0","doc_id":"K222329","page_num":5,"bbox":[72.12,650.37,542.92,677.0],"n_rows":2,"n_cols":3,"columns":["","Predicate Device","Subject Device"],"rows":[["","Predicate Device","Subject Device"],["","CINA CHEST (K210237)","Aidoc Briefcase"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p6-t0","doc_id":"K222329","page_num":6,"bbox":[72.04,632.88,542.95,750.9],"n_rows":5,"n_cols":3,"columns":["","Predicate Device","Subject Device"],"rows":[["","Predicate Device","Subject Device"],["","CINA CHEST (K210237)","Aidoc Briefcase"],["User population","Hospital networks and trained\nradiologists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of interest","Chest and thoraco-abdominal","Chest, abdomen and thoraco-\nabdominal"],["Data acquisition\nprotocol","Chest and Thoraco-abdominal CT\nangiography","CT exams with contrast (CTA and CT\nwith contrast) that include the chest"]],"caption_candidate":"064","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p7-t0","doc_id":"K222329","page_num":7,"bbox":[72.0,0.24,543.0,232.14],"n_rows":5,"n_cols":3,"columns":["Notification-only\n(notification\nalerts), parallel\nworkflow tool","Yes","Yes"],"rows":[["Notification-only\n(notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference with\nstandard\nworkflow","No","No"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- PE and AD image processing\napplications\n- Compatibility of use with the\nCINA Platform reference device\n(worklist and Image Viewer)","- AHS module (orchestrator, image\nacquisition);\n- ACS module (image processing);\n- Aidoc Desktop application for\nworkflow integration (feed and non-\ndiagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p8-t0","doc_id":"K222329","page_num":8,"bbox":[72.24,14.64,539.58,97.14],"n_rows":3,"n_cols":7,"columns":["Time-to-notification","N","Mean\nEstimate","95% Lower\nCL","95% Upper\nCL","Median","IQR"],"rows":[["Time-to-notification","N","Mean\nEstimate","95% Lower\nCL","95% Upper\nCL","Median","IQR"],["BriefCase Aortic\nDissection","499","38","35.5","40.4","31.1","32.5"],["CINA CHEST","298","36.5","35.4","37.5","34.1","n/a"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p8-t1","doc_id":"K222329","page_num":8,"bbox":[160.2,297.54,451.68,325.14],"n_rows":2,"n_cols":7,"columns":["","Mean","Std","Min","Median","Max","N"],"rows":[["","Mean","Std","Min","Median","Max","N"],["Age (Years)","60.02","17.19","18","62","90","499"]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p8-t2","doc_id":"K222329","page_num":8,"bbox":[172.56,392.94,439.44,511.98],"n_rows":6,"n_cols":7,"columns":["Ground Truth\nResults","Gender","","","","All",""],"rows":[["Ground Truth\nResults","Gender","","","","All",""],["","Male","","Female","","",""],["","N","%","N","%","N","%"],["Positive","129","25.9","63","12.6","192","38.6"],["Negative","130","26.1","176","35.3","306","61.4"],["All","239","48.0","259","52.0","498*","100.0"]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222329-p8-t3","doc_id":"K222329","page_num":8,"bbox":[219.36,568.14,392.7,687.18],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["Siemens","167","33.47%"],["GE","145","29.06%"],["Philips","103","20.64%"],["Canon","84","16.83%"],["Total","499","100%"]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222360-p8-t0","doc_id":"K222360","page_num":8,"bbox":[72.28,173.78,549.09,713.64],"n_rows":11,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Result"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Result"],["","","AI-Rad Companion","","","AI-Rad Companion","",""],["","","(Cardiovascular)","","","(Cardiovascular)","",""],["","","VA20","","","(K183268)","",""],["Modality","CT","","","CT","","","Identical"],["Segmentation of\nheart","AI-based Heart\nSegmentation","","","AI-based Heart\nSegmentation","","","Identical"],["Detection of\ncoronary\ncalcium &\nquantification of\ncoronary\ncalcium volume","Calcium Detection with\ndeep learning-based\nalgorithm","","","Calcium Detection with\ndeep learning-based\nalgorithm","","","Identical"],["Visualization of\nheart and of\ncalcium","Color overlay of MPR\nand VRT with\nevaluation results","","","Color overlay of MPR\nand VRT with\nevaluation results","","","Identical"],["Detection of\naortic\nlandmarks","Landmark Detection\nwith deep learning-\nbased algorithms, 9\nAHA positions","","","Landmark Detection\nwith deep learning-\nbased algorithms, 9\nAHA positions","","","Identical"],["Segmentation of\naorta","Aorta Segmentation\nwith deep learning-\nbased algorithm with\nimproved performance\nby adding training data\n(+ 267 additional\nannotations)","","","Aorta Segmentation\nwith deep learning-\nbased algorithm","","","Modified: improved\nperformance of the\nalgorithm"],["Aorta diameter\nmeasurements","Aorta diameter\nmeasurements at nine\npredefined locations\naccording to the AHA\nguidelines and at the\nlocations of the","","","Threshold-based\nclassification of\ndiameters into different\ncategories","","","Modified: maximum\ndiameter of ascending\nand descending aorta\nadded"]],"caption_candidate":"Table 1 Comparison of technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222360-p9-t0","doc_id":"K222360","page_num":9,"bbox":[72.26,72.72,549.1,501.91],"n_rows":5,"n_cols":4,"columns":["","maximum diameter of\nthe ascending and\ndescending aorta","",""],"rows":[["","maximum diameter of\nthe ascending and\ndescending aorta","",""],["Visualization of\naorta’s VRT and\nas cross-\nsectional MPRs","Visualization VRT and\ncross-sectional MPRs at\nnine predefined\nlocations according to\nthe AHA guidelines and\nof the maximum\ndiameter of ascending\nand descending aorta","Visualization VRT and\ncross-sectional MPRs at\nnine predefined\nlocations according to\nthe AHA guidelines","Modified:\nmaximum diameter of\nascending and\ndescending aorta added"],["Categorization\nof diameter\nmeasurements","Categorization of\ndiameter measurements\nat locations according\nto the AHA guidelines\nand at locations of the\nmaximum diameter of\nascending and\ndescending aorta","Categorization of\ndiameter measurements\nat locations according\nto the AHA guidelines","Modified:\nmaximum diameter of\nascending and\ndescending aorta added"],["Reports","Results in form of\nquantitative, structured\nand textual reports, and\nDICOM Secondary\nCapture as well as\nDICOM Structured\nReport (TID 1500)","Results in form of\nquantitative, structured\nand textual reports, and\nDICOM Secondary\nCapture","Modified: format of\nDICOM report changed"],["Deployment","Cloud and Edge (on-\npremise) deployments","Cloud deployment","Modified: edge\ndeployment added"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222360-p10-t0","doc_id":"K222360","page_num":10,"bbox":[72.29,93.24,539.84,330.29],"n_rows":7,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","62366-1:\n2015-02","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to medical\ndevices","14971:2019","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","","","AAMI\nANSI\nIEC","",""],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n(2016)","","","NEMA","",""]],"caption_candidate":"Table 2 Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222360-p12-t0","doc_id":"K222360","page_num":12,"bbox":[72.31,310.95,539.81,367.13],"n_rows":3,"n_cols":8,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],["","","Number","","","Date","",""],["AI-Rad Companion\n(Cardiovascular)","K183268","","","September 10, 2019","","","JAK"]],"caption_candidate":"Table 3 Predicate device for AI-Rad Companion (Cardiovascular)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p6-t0","doc_id":"K222361","page_num":6,"bbox":[72.29,554.47,540.08,713.74],"n_rows":8,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","","AI-Rad Companion","","","AI-Rad Companion",""],["","","(Musculoskeletal)","","","(Musculoskeletal)",""],["","","VA20","","","(K193267)",""],["Modality","CT","","","CT","",""],["Detection of\nVertebrae","Detection of Vertebras","","","Detection of Vertebras","",""],["Labeling of\nVertebrae","Labeling of Vertebras","","","Labeling of Vertebras","",""],["Segmentation\nof Vertebrae","Deep learning based segmentation of\nvertebras","","","Deep learning based segmentation of\nvertebras","",""]],"caption_candidate":"following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p7-t0","doc_id":"K222361","page_num":7,"bbox":[72.26,72.72,540.1,292.61],"n_rows":5,"n_cols":3,"columns":["Measurement\nof Heights","Distance measurements based on\nsegmentation results and comparison\nwith neighboring measurements","Distance measurements based on\nsegmentation results and comparison\nwith neighboring measurements"],"rows":[["Measurement\nof Heights","Distance measurements based on\nsegmentation results and comparison\nwith neighboring measurements","Distance measurements based on\nsegmentation results and comparison\nwith neighboring measurements"],["Measurement\nof\nHounsfield\n(HU) Values","HU measurements based on\nsegmentation results","HU measurements based on\nsegmentation results"],["Algorithm","Deep learning image to image\nnetwork for 3D segmentation","Deep learning image to image\nnetwork for 3D segmentation"],["Deployment","Cloud and on-premise deployment","Cloud deployment"],["Reports","Quantitative, Structured and Text\nreports with DICOM secondary\ncapture & TID 1500 in both human\nand machine readable formats.","Quantitative, Structured and Text\nreports with DICOM secondary\ncapture images"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p7-t1","doc_id":"K222361","page_num":7,"bbox":[83.46,559.13,528.77,694.78],"n_rows":5,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-114","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","62366-1: 2015-\n02","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to\nmedical devices","14971:2007","","","ISO","",""]],"caption_candidate":"with the following voluntary FDA recognized Consensus Standards listed in Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p8-t0","doc_id":"K222361","page_num":8,"bbox":[83.42,72.72,528.82,370.73],"n_rows":5,"n_cols":5,"columns":["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","AAMI\nANSI\nIEC"],"rows":[["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304:\n2006/A1:2016","AAMI\nANSI\nIEC"],["12-300","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n(2016)","NEMA"],["12-261","Radiology","Information Technology –\nDigital Compression and\ncoding of continuous -tone\nstill images: Requirements\nand Guidelines [including:\nTechnical Corrigendum\n1(2005)]","10918-1 1994-\n02-15","ISO\nIEC"],["5-134","General","Medical devices – symbols to\nbe used with information to\nbe supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","ISO\nIEC"],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","IEC"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p9-t0","doc_id":"K222361","page_num":9,"bbox":[72.29,266.81,539.84,508.51],"n_rows":5,"n_cols":6,"columns":["","Validation Type","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Acceptance Criteria",""],["Mislabeling of Vertebrae or absence of height\nmeasurement","","","Ratio of cases that are mislabeled or missing\nmeasurements shall be <10% of all cases","",""],["Inter-reader variability: heights calculated by\nAIRC & the ground truth should be within the\nLoA reported","","","For cases with slice thickness ≤1.0 mm, the\ndifference should be within the LoA for ≥95%\nof cases","",""],["","","","For cases with slice thickness >1.0mm, the\ndifference should be within the LoA for ≥85%\nof cases","",""],["Consistency of height and density\nmeasurement across critical sub-groups","","","For each sub-group, the ratio of\nmeasurements within the corresponding LoA\nshould not drop by more than 5% compared\nto the ratio for all data sets","",""]],"caption_candidate":"Acceptance Criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p10-t0","doc_id":"K222361","page_num":10,"bbox":[72.33,86.65,539.7,300.89],"n_rows":5,"n_cols":6,"columns":["","Validation Type","","","Results",""],"rows":[["","Validation Type","","","Results",""],["Mislabeling of Vertebrae or absence of height\nmeasurement","","","Failure Rate of 8.6%","",""],["Inter-reader variability: heights calculated by\nAIRC & the ground truth should be within the\nLoA reported","","","For cases with slice thickness ≤1.0 mm, the\ndifference was 95.5%","",""],["","","","For cases with slice thickness >1.0mm, the\ndifference was 92.6%","",""],["Consistency of height and density\nmeasurement across critical sub-groups","","","Overall failure rate of the subject device was\nconsistent with the predicate as well as having\nthe results of all sub-group analysis rated\nequal or superior to the predicate","",""]],"caption_candidate":"Summary Performance Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222361-p10-t1","doc_id":"K222361","page_num":10,"bbox":[72.33,343.69,539.7,665.9],"n_rows":14,"n_cols":4,"columns":["","# data sets","","140 Chest CTs (1,553 thoracic vertebrae)"],"rows":[["","# data sets","","140 Chest CTs (1,553 thoracic vertebrae)"],["Pathologies /\nPatient info","","","KUM (N=80):\nPrimary indications: Lung/airways 10; infect focus 10; malignancy 22,\nfollow-up 10; (cardio-)vascular 14; ischemia 2; bleeding 4; trauma 1;\nlymph nodes 3; inflammation 1; unknown 3.\nNLST (N=60):\nComorbidities: diabetes 7; heart disease 10; hypertension 24; cancer 9;\nemphysema/COPD 14; asthma 2; pneumonia 13; chron. bronchitis 1.\nSmoking history (pack years): median: 47, IQR: [38, 70]"],["","Sex","","male: 47, female: 93"],["Age [yrs]","","","≤55: 16, (55, 65]: 59, (65, 75]: 38, >75: 25\nmedian: 65, IQR: [60, 72]"],["","Manufacturer","","GE: 32, Philips: 20, Siemens: 68, Toshiba: 20"],["","Slice Thickness","","≤1.0: 60, (1.0, 1.5]: 24, (1.5, 2.0]: 56"],["","[mm]","",""],["Dose","","","KUM: CTDIVol [mGy]: median 4.8, IQR: [1.3, 10.7]\nNLST: low dose (screening)"],["","Reconstruction","","Filtered backprojection: 107\nIterative reconstruction: 33"],["","method","",""],["","Reconstruction","","soft: 25, medium: 68, hard: 47"],["","kernel","",""],["","Contrast","","enhanced: 59, native: 81"],["","Enhancement","",""]],"caption_candidate":"Testing Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p2-t0","doc_id":"K222406","page_num":2,"bbox":[257.72,458.38,570.36,554.98],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p4-t0","doc_id":"K222406","page_num":4,"bbox":[72.31,277.2,539.75,305.04],"n_rows":2,"n_cols":8,"columns":["","Regulation Number","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","Regulation Name","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","","","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p4-t1","doc_id":"K222406","page_num":4,"bbox":[72.31,536.24,539.75,647.56],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","LVivo Software Application"],"rows":[["","Device Trade Name:","","LVivo Software Application"],["","510(k) Reference:","","K200232"],["","Manufacturer Name:","","DiA Imaging Analysis Ltd"],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Product Code(s):","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p5-t0","doc_id":"K222406","page_num":5,"bbox":[72.31,99.2,539.76,210.4],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","CoLumbo"],"rows":[["","Device Trade Name:","","CoLumbo"],["","510(k) Reference:","","K220497"],["","Manufacturer Name:","","Smart Soft Healthcare AD"],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Product Code(s):","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Reference Device #1 Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p5-t1","doc_id":"K222406","page_num":5,"bbox":[72.31,251.36,539.76,362.68],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","AI-Rad Companion (Musculoskeletal)"],"rows":[["","Device Trade Name:","","AI-Rad Companion (Musculoskeletal)"],["","510(k) Reference:","","K193267"],["","Manufacturer Name:","","Siemens Medical Solutions USA, Inc."],["","Regulation Name:","","Computed tomography x-ray system"],["","Device Classification Name:","","Computed tomography x-ray system"],["","Product Code(s):","","JAK"],["","Regulation Number:","","21 CFR § 892.1750"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Reference Device #2 Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p6-t0","doc_id":"K222406","page_num":6,"bbox":[72.16,193.16,539.76,230.71],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducers","","L7 and L15"],"rows":[["","Clarius Ultrasound Transducers","","L7 and L15"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"and K213436):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p7-t0","doc_id":"K222406","page_num":7,"bbox":[72.31,97.8,702.83,535.9],"n_rows":13,"n_cols":18,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],["","","","","","","","","","","","","","","","","(if subject device",""],["","","","Clarius AI","","","","LVivo Software","","","CoLumbo","","","AI-Rad Companion","","","differs from predicate",""],["","","","","","","","Application","","","","","","(Musculoskeletal)","","","device)",""],["","510(k) Holder/","","Clarius Mobile Health\nCorp.","","","DiA Imaging Analysis\nLtd","","","Smart Soft Healthcare\nAD","","","Siemens Medical\nSolutions USA, Inc.","","","Not applicable","",""],["","Manufacturer","","","","","","","","","","","","","","","",""],["","Submission Reference","","Current Submission","","","K200232","","","K220497","","","K193267","","","Not applicable","",""],["Product Code(s)","Product Code(s)","","QIH","","","QIH","","","QIH","","","JAK","","","Same as predicate\ndevice and reference\ndevice #1","",""],["Device Classification\nName","","","Automated\nRadiological Image\nProcessing Software","","","Automated\nRadiological Image\nProcessing Software","","","Automated\nRadiological Image\nProcessing Software","","","Computed\ntomography x-ray\nsystem","","","Same as predicate\ndevice and reference\ndevice #1","",""],["Regulation Number","","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.1750","","","Same as predicate\ndevice and reference\ndevice #1","",""],["Regulation Name","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","","","Computed\ntomography x-ray\nsystem","","","Same as predicate\ndevice and reference\ndevice #1","",""],["Intended Use","","","Non-invasive\nprocessing of\nultrasound images\nusing automatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence\nalgorithms.","","","Non-invasive\nprocessing of\nultrasound images\nusing automatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence\nalgorithms.","","","Non-invasive\nprocessing of MR\nimages using\nautomatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence\nalgorithms.","","","Non-invasive\nprocessing of CT\nimages using\nautomatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence\nalgorithms.","","","Same as predicate\ndevice and similar to\nreference devices","",""],["Indications for Use","","","Clarius AI is intended\nfor use by trained\nhealthcare\nprofessionals to semi-\nautomatically place","","","LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and","","","CoLumbo is an image\npost-processing and\nmeasurement\nsoftware tool that\nprovides quantitative","","","AI-Rad Companion\n(Musculoskeletal) is an\nimage processing\nsoftware that provides\nquantitative and","","","Clarius AI indications\nfor use are similar to\nthe predicate device’s\nindications for use as\nboth devices are","",""]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p8-t0","doc_id":"K222406","page_num":8,"bbox":[72.3,72.36,702.81,531.45],"n_rows":5,"n_cols":16,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],["","","","","","","","","","","","","","","(if subject device",""],["","Clarius AI","","","","LVivo Software","","","CoLumbo","","","AI-Rad Companion","","","differs from predicate",""],["","","","","","Application","","","","","","(Musculoskeletal)","","","device)",""],["","calipers for non-\ninvasive anatomical\nmeasurements on\nultrasound data\nacquired by the Clarius\nUltrasound Scanner.","","","calculate relevant\nmedical parameters of\nstructures and\nfunction of patients\nwith suspected\ndisease.","","","spine measurements\nfrom previously-\nacquired DICOM\nlumbar spine Magnetic\nResonance (MR)\nimages for users’\nreview, analysis, and\ninterpretation. It\nprovides the following\nfunctionality to assist\nusers in visualizing,\nmeasuring and\ndocumenting out-of-\nrange measurements:\n-Feature\nsegmentation;\n-Feature\nmeasurement;\nThreshold based\nlabeling of out of\nrange measurement;\nand\n-Export of\nmeasurement results\nto a written report for\nuser’s review, revise\nand approval.\nCoLumbo does not\nproduce or\nrecommend any type\nof medical diagnosis or\ntreatment. Instead, it\nsimply helps users to","","","qualitative analysis\nfrom previously\nacquired Computed\nTomography DICOM\nimages to support\nradiologists and\nphysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice in the\nevaluation and\nassessment of\nmusculoskeletal\ndisease. It provides\nthe following\nfunctionality:\n-Segmentation of\nvertebras\n-Labelling of vertebras\n-Measurements of\nheights in each\nvertebra and\nindication if they are\ncritically different\n-Measurement of\nmean Hounsfield value\nin volume of interest\nwithin vertebra.\nOnly DICOM images of\nadult patients are\nconsidered to be valid\ninput.","","","indicated for non-\ninvasive processing of\nultrasound data/\nimages for\nmeasurements of\nanatomical structures.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p9-t0","doc_id":"K222406","page_num":9,"bbox":[72.3,72.36,702.81,531.45],"n_rows":5,"n_cols":16,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],["","","","","","","","","","","","","","","(if subject device",""],["","Clarius AI","","","","LVivo Software","","","CoLumbo","","","AI-Rad Companion","","","differs from predicate",""],["","","","","","Application","","","","","","(Musculoskeletal)","","","device)",""],["","","","","","","","more easily identify\nand classify features in\nlumbar MR images and\ncompile a report. The\nuser is responsible for\nconfirming/ modifying\nsettings, reviewing and\nverifying the software-\ngenerated\nmeasurements,\ninspecting out-of-\nrange measurements,\nand approving draft\nreport content using\ntheir medical\njudgment and\ndiscretion.\nThe device is intended\nto be used only by\nhospitals and other\nmedical institutions.\nOnly DICOM images of\nMRI acquired from\nlumbar spine exams of\npatients aged 18 and\nabove are considered\nto be valid input.\nCoLumbo does not\nsupport DICOM images\nof patients that are\npregnant, undergo\nMRI scan with contrast\nmedia, or have post-","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p11-t0","doc_id":"K222406","page_num":11,"bbox":[72.31,72.36,702.82,520.66],"n_rows":13,"n_cols":18,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],["","","","","","","","","","","","","","","","","(if subject device",""],["","","","Clarius AI","","","","LVivo Software","","","CoLumbo","","","AI-Rad Companion","","","differs from predicate",""],["","","","","","","","Application","","","","","","(Musculoskeletal)","","","device)",""],["","Automation","","Yes","","","Yes","","","Yes","","","Yes","","","Same as predicate\ndevice and reference\ndevices","",""],["","(Yes or No)","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","","",""],["Display Calipers","Display Calipers","","Yes","","","Yes","","","Yes","","","Yes","","","Same as predicate\ndevice and reference\ndevices","",""],["","Manual adjustment/","r","Yes","","","Yes","","","Yes","","","Yes","","","Same as predicate\ndevice and reference\ndevices","",""],["","Manual editing by use","","","","","","","","","","","","","","","",""],["","capability","","","","","","","","","","","","","","","",""],["","(Yes or No)","","","","","","","","","","","","","","","",""],["Anatomical Site","Anatomical Site","","Foot, Ankle, Knee","","","Bladder, Heart","","","Lumbar Spine","","","Thoracic Spine","","","Although the\nanatomical sites/\nstructures for use of\nthe predicate device\n(bladder, heart) are\ndifferent from the\nsubject device (foot,\nankle, knee), the\npredicate device and\nsubject device share a\nvery similar intended\nuse in terms of\nidentifying/ viewing,\nmeasuring/\nquantifying and\nreporting results\nacquired by ultrasound\ndevices for non-\ninvasive\nmeasurements of\nanatomical structures\nutilizing artificial","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p12-t0","doc_id":"K222406","page_num":12,"bbox":[72.31,72.36,702.82,264.34],"n_rows":8,"n_cols":16,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","","","REFERENCE DEVICE #1","","","REFERENCE DEVICE #2","","","","RATIONALE",""],["","","","","","","","","","","","","","","(if subject device",""],["","Clarius AI","","","","LVivo Software","","","CoLumbo","","","AI-Rad Companion","","","differs from predicate",""],["","","","","","Application","","","","","","(Musculoskeletal)","","","device)",""],["","","","","","","","","","","","","","intelligence\nalgorithms.","",""],["Environment of Use","Healthcare setting\n(e.g., hospital, clinic)","","","Healthcare setting\n(e.g., hospital, clinic)","","","Healthcare setting\n(e.g., hospital, clinic)","","","Healthcare setting\n(e.g., hospital, clinic)","","","Same as predicate\ndevice and reference\ndevices","",""],["Intended Users","Licensed healthcare\nprofessionals","","","Licensed healthcare\nprofessionals","","","Licensed healthcare\nprofessionals","","","Licensed healthcare\nprofessionals","","","Same as predicate\ndevice and reference\ndevices","",""],["Patient Population","Adults","","","Adults","","","Adults","","","Adults","","","Same as predicate\ndevice and reference\ndevices","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222406-p13-t0","doc_id":"K222406","page_num":13,"bbox":[72.26,181.44,539.74,306.36],"n_rows":8,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-40","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["12-300","","","NEMA PS 3.1 - 3.20 (2016) Digital Imaging and Communications in Medicine (DICOM) Set"],["5-114","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-117","","","ISO 15223-1:2016 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222428-p6-t0","doc_id":"K222428","page_num":6,"bbox":[72.07,78.94,540.05,347.69],"n_rows":4,"n_cols":4,"columns":["Subject Device\nsyngo Dynamics VA40F","","Predicate Device",""],"rows":[["Subject Device\nsyngo Dynamics VA40F","","Predicate Device",""],["","","syngo Dynamics VA40E",""],["","","K220832",""],["syngo Dynamics is a multimodality, vendor\nagnostic Cardiology image and information\nsystem intended for medical image management\nand processing that provides capabilities relating\nto the review and digital processing of medical\nimages.\nsyngo Dynamics supports clinicians by providing\npost image processing functions for image\nmanipulation, and/or quantification that are\nintended for use in the interpretation and analysis\nof medical images for disease detection,\ndiagnosis, and/or patient management within the\nhealthcare institution’s network.\nsyngo Dynamics is not intended to be used for\ndisplay or diagnosis of digital mammography\nimages in the U.S.","syngo Dynamics is a multimodality, vendor\nagnostic Cardiology image and information\nsystem intended for medical image management\nand processing that provides capabilities relating\nto the review and digital processing of medical\nimages.\nsyngo Dynamics supports clinicians by providing\npost image processing functions for image\nmanipulation, and/or quantification that are\nintended for use in the interpretation and analysis\nof medical images for disease detection,\ndiagnosis, and/or patient management within\nhealthcare institution’s network.\nsyngo Dynamics is not intended to be used for\ndisplaying of digital mammography images for\ndiagnosis in the U.S.","",""]],"caption_candidate":"syngo Dynamics (Version VA40F) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222428-p7-t0","doc_id":"K222428","page_num":7,"bbox":[72.28,78.93,539.84,628.78],"n_rows":8,"n_cols":6,"columns":["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],["","","","syngo Dynamics VA40E","",""],["","","","K220832","",""],["Architecture","Client-server","Client-server","","","Identical"],["Supported\nmodalities","• US\n• XA\n• DX\n• CT\n• MR\n• SC\n• NM\n• PT","• US\n• XA\n• DX\n• CT\n• MR\n• SC\n• NM\n• PT","","","Identical"],["Supported\ndeployment","• Standalone medical device\nincluding a DICOM Server\n• Integrated model within an\nElectronic Health Record\n(EHR) System with a\nDICOM Archive\n• Multimodality\nCardiovascular (MMCV)\ndeployment with native\nsupport of 2D/3D CT/MR\nimage types","• Standalone medical device\nincluding a DICOM Server\n• Integrated model within an\nElectronic Health Record\n(EHR) System with a\nDICOM Archive\n• Multimodality\nCardiovascular (MMCV)\ndeployment with native\nsupport of 2D/3D CT/MR\nimage types","","","Identical"],["Image\nCommunication","Within the network, the\nfollowing communication\nprotocols are used:\n• TCP/IP: for communication\nand transport\n• DICOM and HL7 at\napplication level\n• HTTP for communication\nand transport of images,\nMP4s and thumbnails","Within the network, the\nfollowing communication\nprotocols are used:\n• TCP/IP for communication\nand transport\n• DICOM and HL7 at\napplication level\n• HTTP(S) for\ncommunication and\ntransport of images, MP4s\nand thumbnails","","","Identical"],["Image Data\nCompression","Lossless compression with\ncompression factor 2 to 3 and\nlossy compression (JPEG and\nMP4) with higher compression\nrate.","Lossless compression with\ncompression factor 2 to 3 and\nlossy compression (JPEG and\nMP4) with higher compression\nrate.","","","Identical"]],"caption_candidate":"syngo Dynamics (Version VA40F) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222428-p8-t0","doc_id":"K222428","page_num":8,"bbox":[72.29,78.93,539.84,594.67],"n_rows":7,"n_cols":6,"columns":["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],["","","","syngo Dynamics VA40E","",""],["","","","K220832","",""],["Imaging\nAlgorithms","• Window/Leveling\n• Edge Enhancement\n• Digital Subtraction\n• Multiplanar reconstruction\n(MPR)\n• Maximum and Minimum\nIntensity Projection\n(MIP/MinIP)\n• Volume Rendering\nTechnique (VRT)\n• Gamma Correction\n• Manual and semi-\nautomated calculation for\nleft ventricular ejection\nfraction (Auto EF)","• Window/Leveling\n• Edge Enhancement\n• Digital Subtraction\n• Multiplanar reconstruction\n(MPR)\n• Maximum and Minimum\nIntensity Projection\n(MIP/MinIP)\n• Volume Rendering\nTechnique (VRT)\n• Gamma Correction\n• Manual calculation for left\nventricular ejection fraction","","","Updated by\nadding semi-\nautomated\nejection\nfraction"],["Quantitative\nalgorithms","• Pixel Size Evaluation\n• Distance line\n• Angle\n• volume","• Pixel Size Evaluation\n• Distance line\n• Angle\n• Volume","","","Identical"],["Decision\nSupport","Ability to interface with a third-\nparty rules engine (BizTalk),\nwhere rules are configured by\nthe end customer to determine\nclinical relevance of selected\nobservations.\nCustomers identify and store\nselected patient data.\nOrchestrations provide a trigger\nto pull in previously stored\nrelevant data for a given study.","Ability to interface with a third-\nparty rules engine (BizTalk),\nwhere rules are configured by\nthe end customer to determine\nclinical relevance of selected\nobservations.\nCustomers identify and store\nselected patient data.\nOrchestrations provide a trigger\nto pull in previously stored\nrelevant data for a given study.","","","Identical"],["Reporting","• Customizable DICOM\nStructured Reporting\n• Collaborative reporting\n• Web reporting","• Customizable DICOM\nStructured Reporting\n• Collaborative reporting\n• Remote reporting","","","Identical"]],"caption_candidate":"syngo Dynamics (Version VA40F) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222428-p9-t0","doc_id":"K222428","page_num":9,"bbox":[72.28,78.93,539.84,652.18],"n_rows":8,"n_cols":6,"columns":["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],["","","","syngo Dynamics VA40E","",""],["","","","K220832","",""],["Access\nstrategies for\nimaging and\nreporting","• Workplace (thick client)-\naccess for reading and\nreporting.\n• Remote Workplace (MP4\nimage display with access\nto full DICOM image for\nUS/XA and full DICOM\nimage for CT/MR) – access\nfor reading and reporting\n• WebViewer – (Web Client\nwith MP4 Image display) –\nAccess for review only\n• Portal – (Web Client for\nreading and reporting with\nlimited functionality.)","• Workplace (thick client) –\naccess for reading and\nreporting.\n• Remote Workplace (MP4\nimage display with access\nto full DICOM image for\nUS/XA and full DICOM\nimage for CT/MR) – access\nfor reading and reporting.\n• WebViewer- (Web Client\nwith MP4 Image display) –\nAccess for review only","","","Similar.\nAdditional\nportal access\nfor review and\nlimited\nfunctionality\nin subject\ndevice."],["Mobile Device\nSupport","Yes –Through the Common\nLogin and Portal Image\nReview, images can be viewed\non mobile devices, WebViewer,\nsupports iOS and Android\ndevices, but are non-diagnostic\nuse.","Yes – Through WebViewer,\nSupports iOS and Android\ndevices, but non-diagnostic use.","","","Similar.\nAdditional\nportal access\nfor review and\nlimited\nfunctionality\nin subject\ndevice."],["Long Term\nArchive","Provide long term archive and\nretrieve of DICOM studies\nto/from either VNA (Vendor\nNeutral Archive) or HSM\n(Hierarchical Storage\nManagement) archiving\nSystems.","Provide long term archive and\nretrieve of DICOM studies\nto/from either VNA (Vendor\nNeutral Archive) or HSM\n(Hierarchical Storage\nManagement) archiving\nSystems.","","","Identical"],["Hardware","Software-only option for server\nWorkstation: software only\n(HW is not part of the medical\ndevice, but needs to meet\nrecommended requirements as\nspecified by syngo Dynamics)","Software-only option for server\nWorkstation: software only\n(HW is not part of the medical\ndevice, but needs to meet\nrecommended requirements as\nspecified by syngo Dynamics)","","","Identical"],["Virtualization","Provides virtualization of server\nand client machines","Provides virtualization of server\nand client machines","","","Identical"]],"caption_candidate":"syngo Dynamics (Version VA40F) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222428-p10-t0","doc_id":"K222428","page_num":10,"bbox":[72.3,78.93,539.82,671.5],"n_rows":5,"n_cols":6,"columns":["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","Subject Device\nsyngo Dynamics VA40F","","Predicate Device","","Equivalency\nAnalysis"],["","","","syngo Dynamics VA40E","",""],["","","","K220832","",""],["Operating\nsystem","Server:\nMicrosoft Windows server 2016\nStandard edition (64\nbit)\nMicrosoft Windows Server\n2019 Standard Edition (64\nBit)\nClient Software: Microsoft\nWindows 10 x64 version\n1803 or greater\nPortal Website Host:\nMicrosoft Windows Server\n2016 Standard edition (64-bit),\nMicrosoft Windows Server\n2019 Standard edition (64-bit)\nServer:\nWindows 2012 R2 Server\nStandard Edition R2 (64-bit)\nPortal Client:\nWindows 7 SP1 or higher (64-\nbit)\nPortal Website Host:\nWindows 2012 R2 Server\nStandard Edition R2 (64-bit)","Server:\nMicrosoft Windows server 2016\nStandard edition (64\nbit)\nMicrosoft Windows Server\n2019 Standard Edition (64\nBit)\nClient Software: Microsoft\nWindows 10 x64 version\n1803 or greater\nPortal Website Host:\nMicrosoft Windows Server\n2016 Standard edition (64-bit),\nMicrosoft Windows Server\n2019 Standard edition (64-bit)\nServer: Windows 2012 R2\nServer Standard Edition R2 (64-\nbit)\nPortal Client:\nWindows 7 SP1 or higher (64-\nbit)\nPortal Website Host: Windows\n2012 R2 Server Standard\nEdition R2 (64-bit)","","","Identical"],["Deployment\nstrategy","• The use of syngo Dynamics\nVA30 server/workplace in\nthe context of\ncardiovascular\nconfiguration.\n• EHR/EHS Integrated\nconfiguration with syngo\nDynamics server.\n• Multi-modality\ncardiovascular\nconfiguration with\nnative/syngo server and\nsyngo Dynamics workplace\nwith native/syngo\ncomponents.","• The use of syngo Dynamics\nVA40E server/workplace in\nthe context of\ncardiovascular\nconfiguration.\n• EHR/EHS Integrated\nconfiguration with syngo\nDynamics server.\n• Multi-modality\ncardiovascular\nconfiguration with\nnative/syngo server and\nsyngo Dynamics workplace\nwith native/syngo\ncomponents.","","","Identical"]],"caption_candidate":"syngo Dynamics (Version VA40F) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222458-p4-t0","doc_id":"K222458","page_num":4,"bbox":[90.44,144.85,361.17,690.37],"n_rows":37,"n_cols":2,"columns":["Contact:","Howard Schrayer"],"rows":[["Contact:","Howard Schrayer"],["","AIbolit Technologies, LL"],["","9616 Moritz Way"],["","Delray Beach, FL 33446"],["",""],["","Telephone: 609-273-73"],["","hs.ss@lucidmedical.net"],["",""],["Date Prepared:","January 11, 2023"],["",""],["Device Trade Name:","AIBOLIT 3D+"],["",""],["Manufacturer:","AIbolit Technologies, LL"],["","9616 Moritz Way"],["","Delray Beach, FL 33446"],["",""],["Common Name:","Automated Radiological"],["","Medical image manage"],["",""],["Classification:","Class II"],["",""],["Product Code:","QIH - LLZ"],["",""],["Regulation:","21 CFR 892.2050"],["",""],["Predicate Devices:",""],["",""],["Primary Predicate",""],["","Aibolit Technologies, LL"],["","[510(k) K211443]."],["",""],["Reference Predicate",""],["",""],["","Ceevra, Inc."],["","Ceevra Reveal 2.0"],["","Image Processing Syste"],["","[510(k) K173274]"]],"caption_candidate":"Contact: Howard Schrayer","well_formed":true,"extraction_settings":"text"}
{"table_id":"K222458-p6-t0","doc_id":"K222458","page_num":6,"bbox":[80.4,61.31,570.7,725.03],"n_rows":10,"n_cols":9,"columns":["","Manufacturer","","","AIbolit Technologies, LLC","","","Ceevra",""],"rows":[["","Manufacturer","","","AIbolit Technologies, LLC","","","Ceevra",""],["Trade Name","","","AIBOLIT 3D+\nImage Processing System","","","Ceevra Reveal 2.0\nImage Processing System","",""],["510(k) Number","","","Subject Device - TBD","","","K173274","",""],["Type of Device/\nProduct Code /","","","Radiological Image Processing\nSystem / QIH - LLZ","","","Radiological Image Processing\nSystem / LLZ","",""],["Regulation / Class","","","21 CFR 892.2050 – Class II","","","21 CFR 892.2050 – Class II","",""],["Indications for\nUse","","","Aibolit 3D+ is intended as a\nmedical imaging system that\nallows the processing, review,\nanalysis, communication and\nmedia interchange of multi-\ndimensional digital images\nacquired from CT or MR\nimaging devices. It is also\nintended as software for\npreoperative surgical planning,\ntraining, patient information and\nas software for the\nintraoperative display of the\nmultidimensional digital images.\nAibolit 3D+ is designed for use\nby health care professionals and\nis intended to assist the clinician\nwho is responsible for making all\nfinal patient management\ndecisions.","","","Ceevra Reveal 2.0 is intended as\na medical imaging system that\nallows the processing, review,\nanalysis, communication\nand media interchange of multi-\ndimensional digital images\nacquired from CT or MR imaging\ndevices. It is also intended as\nsoftware for preoperative surgical\nplanning, and as software for the\nintraoperative display of the\naforementioned multidimensional\ndigital images. Ceevra Reveal\n2.0 is designed for use by health\ncare professionals and is\nintended to assist the clinician\nwho is responsible for making all\nfinal patient management\ndecisions.","",""],["Mechanism of\nAction","","","Capture and enhancement of\n(DICOM) digital video images\nvia software-based conversion\nto 2-D and 3-D anatomical\nstructure images that can be\nmanipulated for viewing","","","Capture and enhancement of\n(DICOM) digital video images via\nsoftware-based conversion to 2-\nD and 3-D anatomical structure\nimages that can be manipulated\nfor viewing","",""],["Intended Users","","","Health care professionals","","","Health care professionals","",""],["Intended Use\nEnvironment","","","Healthcare facilities such as\nhospitals and clinics","","","Healthcare facilities such as\nhospitals and clinics","",""],["Format of\nCaptured Images","","","DICOM","","","DICOM","",""]],"caption_candidate":"Predicate Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222458-p7-t0","doc_id":"K222458","page_num":7,"bbox":[80.39,30.47,570.71,725.75],"n_rows":7,"n_cols":3,"columns":["Intended Use","AIBOLIT 3D+ is intended for use\nas a medical imaging system\nthat allows the processing,\nreview, analysis, communication\nand media interchange of multi-\ndimensional digital images\nacquired from CT or MR\nimaging devices. It is also\nintended as software for\npreoperative surgical planning,\nand as software for the\nintraoperative display of multi-\ndimensional digital images.\nAIBOLIT 3D+ is designed for\nuse by health care professionals\nand is intended to assist the\nclinician who is responsible for\nmaking patient management\ndecisions.","Intended as a medical imaging\nsystem that allows the\nprocessing, review, analysis,\ncommunication and media\ninterchange of multi- dimensional\ndigital images acquired from CT\nor MR imaging devices. It is also\nintended as software for\npreoperative surgical planning,\nand as software for the\nintraoperative display of the\naforementioned multi-\ndimensional digital images.\nCeevra Reveal 2.0 is designed\nfor use by health care\nprofessionals and is intended to\nassist the clinician who is\nresponsible for making all final\npatient management decisions."],"rows":[["Intended Use","AIBOLIT 3D+ is intended for use\nas a medical imaging system\nthat allows the processing,\nreview, analysis, communication\nand media interchange of multi-\ndimensional digital images\nacquired from CT or MR\nimaging devices. It is also\nintended as software for\npreoperative surgical planning,\nand as software for the\nintraoperative display of multi-\ndimensional digital images.\nAIBOLIT 3D+ is designed for\nuse by health care professionals\nand is intended to assist the\nclinician who is responsible for\nmaking patient management\ndecisions.","Intended as a medical imaging\nsystem that allows the\nprocessing, review, analysis,\ncommunication and media\ninterchange of multi- dimensional\ndigital images acquired from CT\nor MR imaging devices. It is also\nintended as software for\npreoperative surgical planning,\nand as software for the\nintraoperative display of the\naforementioned multi-\ndimensional digital images.\nCeevra Reveal 2.0 is designed\nfor use by health care\nprofessionals and is intended to\nassist the clinician who is\nresponsible for making all final\npatient management decisions."],["Security","Data coded and HIPAA\ncompliant","Data coded and HIPAA\ncompliant"],["Form of Device","AIBOLIT 3D+ is a software only\ndevice that permits electronic\nimage uploads, provides image\nconversion and allows viewing\non a mobile device or standard\ncomputer monitor.","The Ceevra Reveal 2.0 Video\nProcessor is a software only\ndevice that permits electronic\nimage uploads, provides image\nconversion and allows viewing on\na mobile device or standard\ncomputer monitor."],["Image processing","High-definition digital images","High-definition digital images"],["Functions","Generation of 2D and 3D\nimages from DICOM data\nOrgan segmentation and\nstructure identification\nDimensional and volume\nreferences\nMulti-axis image rotation\nOrgan transparency","Generation of 2D and 3D images\nfrom DICOM data\nOrgan segmentation and\nstructure identification\nDimensional and volume\nreferences\nMulti-axis image rotation\nOrgan transparency"],["Body contact","None","None"],["User Interface and\nSystem Work-\nFlow","Physician uploads DICOM\nimages and specifies desired\nanatomical segments of interest\nRadiologist annotates sample\n(segments) images","Physician uploads DICOM\nimages and specifies desired\nanatomical segments of interest\nImaging technician annotates\nsample (segments) images"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222458-p9-t0","doc_id":"K222458","page_num":9,"bbox":[80.15,30.47,570.71,353.03],"n_rows":7,"n_cols":3,"columns":["Image editing\npermission","Only the radiologist can edit\nimages following review – User\nphysicians cannot edit images -\nPhysicians have option to show\nor hide organs on display","Imaging technician can edit\nimages generated by the system\nsoftware – User physicians\ncannot edit images - Physicians\nhave option to show or hide\norgans on display"],"rows":[["Image editing\npermission","Only the radiologist can edit\nimages following review – User\nphysicians cannot edit images -\nPhysicians have option to show\nor hide organs on display","Imaging technician can edit\nimages generated by the system\nsoftware – User physicians\ncannot edit images - Physicians\nhave option to show or hide\norgans on display"],["","",""],["Device Output\nDevices","3D image can be displayed on\nstandard monitor or another\nappropriate display","3D image can be displayed on\nstandard monitor, smart phone\n(with separate software) or\nVirtual Imaging 3D headset"],["","",""],["Supplemental\noutputs","Organ structure dimensions,\nvolume, organ labels, patient ID,\nimage date and demographics","Organ structure dimensions,\nvolume, organ labels, patient ID\nand demographics"],["","",""],["Output image\nmanipulation by\nuser","Physician user can show or hide\nindividual organ structures,\nzoom capability, rotational\ncapability and transparency\ncapability","Physician user can show or hide\nindividual organ structures, zoom\ncapability, rotational capability,\ntransparency capability (current\nversion)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222593-p6-t0","doc_id":"K222593","page_num":6,"bbox":[72.0,296.52,582.36,684.84],"n_rows":7,"n_cols":4,"columns":["Measurement [units]","Description","Module /\nWorkflow","Application"],"rows":[["Measurement [units]","Description","Module /\nWorkflow","Application"],["Distance [mm]","Length between two points,\nfor both curved lines\n(splines) and straight lines,\nincluding the diameter\n(including min, max,\naverage) resulting from\nclosed splines and depth of\nthe LAA","All modules","Diameter & depth of LAA\nlanding zone (LAA module);\ndistance between points of\ninterest; diameter of a peri-\ndevice leak (Follow-up\nmodule)"],["Perimeter [mm]","The perimeter of a contour\n(closed spline)","All modules","Perimeter of LAA landing zone\n(LAA module); perimeter of\nother contours of interest"],["Area [mm2]","The area within a contour","All modules","Area of LAA landing zone\n(LAA module); area of other\ncontours\nof interest"],["Angle [degrees]","The angle of an object /\nstructure of interest","All modules","Angle between two lines of\ninterest"],["Signal intensity\n[HU]","Hounsfield value (in\nHounsfield Units, HU) of the\nunderlying pixels","All modules","Signal intensity of pixels in the\nregular vs. delayed scan\n(Thrombus module); average\nsignal intensity within distal\nLAA (Follow-up module);\nintensity of other pixels of\ninterest"],["Coordinates\n[mm, mm, mm]","Location in the x-, y-, and z-\nplanes of a point","All modules","Coordinates of points of\ninterest on a 3D rendering,\nfor export purposes"]],"caption_candidate":"measurement application for which it is used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222593-p8-t0","doc_id":"K222593","page_num":8,"bbox":[36.68,287.22,582.24,614.3],"n_rows":31,"n_cols":9,"columns":["","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],"rows":[["","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],["","TruPlan v3.0 (K222593)","","","TruPlan v1.0 (K202212)","","","3mensio (K153736)",""],["","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Pie Medical Imaging",""],["TruPlan enables visualization and\nmeasurement of structures of the heart\nand vessels for:\n• Pre-procedural planning and sizing for\nthe left atrial appendage closure\n(LAAC) procedure\n• Post-procedural evaluation for the\nLAAC procedure\nTo facilitate the above, TruPlan provides\ngeneral functionality such as:\n• Segmentation of cardiovascular\nstructures\n• Visualization and image\nreconstruction techniques: 2D review,\nVolume Rendering, MPR\n• Simulation of TEE views, ICE views,\nand fluoroscopic rendering\n• Measurement and annotation tools\n• Reporting tools\nTruPlan’s intended patient population is\ncomprised of adult patients.","TruPlan enables visualization and","","TruPlan enables visualization and\nmeasurement of structures of the heart\nand vessels for pre-procedural planning\nand sizing for the left atrial appendage\nclosure (LAAC) procedure.\nTo facilitate the above, TruPlan provides\ngeneral functionality such as:\n• Segmentation of cardiovascular\nstructures\n• Visualization and image\nreconstruction techniques: 2D review,\nVolume Rendering, MPR\n• Simulation of TEE views, ICE views,\nand fluoroscopic rendering\n• Measurement and annotation tools\n• Reporting tools\nTruPlan’s intended patient population is\ncomprised of adult patients.","TruPlan enables visualization and","","","3mensio Workstation enables visualization",""],["","measurement of structures of the heart","","","measurement of structures of the heart","","","and measurement of structures of the",""],["","and vessels for:","","","and vessels for pre-procedural planning","","","heart and vessels for:",""],["","• Pre-procedural planning and sizing for","","","and sizing for the left atrial appendage","","","• Pre-operational planning and sizing",""],["","the left atrial appendage closure","","","closure (LAAC) procedure.","","","for cardiovascular interventions and",""],["","(LAAC) procedure","","","","","","surgery",""],["","• Post-procedural evaluation for the","","","To facilitate the above, TruPlan provides","","","• Postoperative evaluation",""],["","LAAC procedure","","","general functionality such as:","","","• Support of clinical diagnosis by",""],["","","","","• Segmentation of cardiovascular","","","quantifying dimensions in coronary",""],["","To facilitate the above, TruPlan provides","","","structures","","","arteries",""],["","general functionality such as:","","","• Visualization and image","","","• Support of clinical diagnosis by",""],["","• Segmentation of cardiovascular","","","reconstruction techniques: 2D review,","","","quantifying calcifications (calcium",""],["","structures","","","Volume Rendering, MPR","","","scoring) in the coronary arteries",""],["","• Visualization and image","","","• Simulation of TEE views, ICE views,","","","",""],["","reconstruction techniques: 2D review,","","","and fluoroscopic rendering","","","To facilitate the above, 3mensio",""],["","Volume Rendering, MPR","","","• Measurement and annotation tools","","","Workstation provides general functionality",""],["","• Simulation of TEE views, ICE views,","","","• Reporting tools","","","such as:",""],["","and fluoroscopic rendering","","","","","","• Segmentation of cardiovascular",""],["","• Measurement and annotation tools","","","TruPlan’s intended patient population is","","","structures",""],["","• Reporting tools","","","comprised of adult patients.","","","• Automatic and manual centerline",""],["","","","","","","","detection",""],["","TruPlan’s intended patient population is","","","","","","• Visualization and image",""],["","comprised of adult patients.","","","","","","reconstruction techniques: 2D review,",""],["","","","","","","","Volume Rendering, MPR, Curved",""],["","","","","","","","MPR, Stretched CMPR, Slabbing,",""],["","","","","","","","MIP, AIP, MinIP",""],["","","","","","","","• Measurement and annotation tools",""],["","","","","","","","• Reporting tools",""]],"caption_candidate":"Table 2. Indications for Use comparison to predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222593-p9-t0","doc_id":"K222593","page_num":9,"bbox":[36.61,115.44,582.35,718.32],"n_rows":15,"n_cols":10,"columns":["Feature","","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],"rows":[["Feature","","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],["","","TruPlan v3.0 (K222593)","","","TruPlan v1.0 (K202212)","","","3mensio (K153736)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Pie Medical",""],["Device Class","II","","","II","","","II","",""],["Device Classification","QIH\nLLZ","","","LLZ","","","LLZ","",""],["Regulation Name","Medical image management and\nprocessing system","","","Picture Archiving and\nCommunications System","","","Picture Archiving and\nCommunications System","",""],["Regulation Number","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Input data type","CT data in DICOM format (vendor\nindependent)","","","CT data in DICOM format (vendor\nindependent)","","","CT data in DICOM (vendor\nindependent)","",""],["Landing Zone\nDetection","Semi-automatic initialization of the\nlanding zone using Machine\nLearning techniques; manual\nconfirmation of the landing zone","","","Manual initialization and\nconfirmation of the landing zone","","","Manual initialization and\nconfirmation of the landing zone","",""],["Left Heart\nSegmentation","Semi-automatic segmentation for\n3D visualization of the left heart\nusing Machine Learning\ntechniques; manual editing of 3D\nviews possible","","","Semi-automatic segmentation for\n3D visualization of the left heart\nusing Machine Learning\ntechniques; manual editing of 3D\nviews possible","","","Semi-automatic segmentation for\n3D visualization of the left heart;\nmanual editing of 3D views possible","",""],["Study list image\nfunctionality","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search","","","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search","","","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search","",""],["Image assessment –\nsimulated views","• Fluoroscopy (grayscale 3D\nrendering), to visualize\nrelationship among LAAC\nprocedure relevant\nanatomical structures\n• TEE, to provide similar views\nto intraprocedural TEE\n• ICE, to provide similar views\nto intraprocedural ICE","","","• Fluoroscopy (grayscale 3D\nrendering), to visualize\nrelationship among LAAC\nprocedure relevant\nanatomical structures\n• TEE, to provide similar views\nto intraprocedural TEE\n• ICE, to provide similar views\nto intraprocedural ICE","","","• Grayscale 3D rendering, to\nvisualize relationship among\nLAAC procedure relevant\nanatomical structures\n• TEE, to provide similar views to\nintraprocedural TEE","",""],["Image assessment –\nother visualization\nfunctionality","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• MIP\n• Annotations","","","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations","","","• 2D\n• 3D (with manual & semi-\nautomatic segmentation)\n• 4D (cine)\n• MPR\n• Annotations\n• Curved MPR\n• Stretch CMPR\n• Slabbing\n• MIP\n• AIP\n• MinIP\n• Centreline extraction\n• Calcium coring","",""],["Image assessment –\nmeasurement\nfunctionality","• Distance (length, diameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates","","","• Distance (length, diameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates","","","• Distance (length, diameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates\n• Volume","",""],["Report functionality","• Patient/study information","","","• Patient/study information","","","• Patient/study information","",""]],"caption_candidate":"Table 3. Feature comparison to primary and secondary predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222593-p10-t0","doc_id":"K222593","page_num":10,"bbox":[36.63,100.92,582.32,229.32],"n_rows":6,"n_cols":10,"columns":["Feature","","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],"rows":[["Feature","","Subject Device","","","Primary Predicate","","","Secondary Predicate",""],["","","TruPlan v3.0 (K222593)","","","TruPlan v1.0 (K202212)","","","3mensio (K153736)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Pie Medical",""],["","• Screenshots\n• Measurements\n• Free text\n• Device sizing table (for\nreference only) for LAA\nprocedure","","","• Screenshots\n• Measurements\n• Free text\n• Device sizing table (for\nreference only) for LAA\nprocedure","","","• Screenshots\n• Measurements\n• Free text\n• Device-specific reports for\nprocedures covered in intended\nuse","",""],["Operating system","Microsoft Windows\nApple macOS","","","Microsoft Windows","","","Microsoft Windows","",""],["DICOM compliant","Yes","","","Yes","","","Yes","",""]],"caption_candidate":"K222593 - TruPlan 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p4-t0","doc_id":"K222676","page_num":4,"bbox":[72.08,126.47,539.5,255.09],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Ceevra,Inc."],"rows":[["510(k) Sponsor","Ceevra,Inc."],["Address","149New MontgomerySt,4thFloor\nSanFrancisco,CA 94105"],["Correspondence Person","Ken Koster\nCTO, Ceevra,Inc."],["Contact Information","Email:kkoster@ceevra.com\nPhone:415-305-5326"],["Date Prepared","April18,2023"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p4-t1","doc_id":"K222676","page_num":4,"bbox":[78.0,129.99,435.84,528.5],"n_rows":40,"n_cols":2,"columns":["510(k) Sponsor","Ceevra,Inc."],"rows":[["510(k) Sponsor","Ceevra,Inc."],["",""],["Address","149New MontgomerySt,4thFloor"],["","SanFrancisco,CA 94105"],["",""],["Correspondence Person","Ken Koster"],["","CTO, Ceevra,Inc."],["",""],["Contact Information","Email:kkoster@ceevra.com"],["","Phone:415-305-5326"],["",""],["Date Prepared","April18,2023"],["",""],[". Subject Device",""],["",""],["ProprietaryName","CeevraReveal3"],["",""],["Common Name","Reveal3"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessing"],["",""],["RegulationNumber","21CFR 892.2050"],["",""],["Product Code","QIH"],["",""],["RegulatoryClass","II"],["",""],[". Predicate Device",""],["",""],["ProprietaryName","CeevraReveal2.0"],["",""],["PremarketNotification","K173274"],["",""],["ClassificationName","System,ImageProcessing, Radiological"],["",""],["RegulationNumber","21CFR 892.2050"],["",""],["Product Code","LLZ"],["",""],["RegulatoryClass","II"]],"caption_candidate":"510(k) Sponsor Ceevra,Inc.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K222676-p4-t2","doc_id":"K222676","page_num":4,"bbox":[72.08,292.74,539.5,392.24],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","CeevraReveal3"],"rows":[["ProprietaryName","CeevraReveal3"],["Common Name","Reveal3"],["ClassificationName","AutomatedRadiologicalImageProcessing Software"],["RegulationNumber","21CFR 892.2050"],["Product Code","QIH"],["RegulatoryClass","II"]],"caption_candidate":"2. Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p4-t3","doc_id":"K222676","page_num":4,"bbox":[72.08,430.35,539.5,529.35],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","CeevraReveal2.0"],"rows":[["ProprietaryName","CeevraReveal2.0"],["PremarketNotification","K173274"],["ClassificationName","System,ImageProcessing, Radiological"],["RegulationNumber","21CFR 892.2050"],["Product Code","LLZ"],["RegulatoryClass","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p5-t0","doc_id":"K222676","page_num":5,"bbox":[72.25,558.69,538.5,663.5],"n_rows":2,"n_cols":2,"columns":["SubjectDevice:\nCeevraReveal3(K222676)","PrimaryPredicate:\nCeevraReveal2.0(K173274)"],"rows":[["SubjectDevice:\nCeevraReveal3(K222676)","PrimaryPredicate:\nCeevraReveal2.0(K173274)"],["CeevraReveal3isintendedasamedicalimaging\nsystemthatallowstheprocessing,review,analysis,\ncommunicationandmediainterchangeof\nmulti-dimensionaldigitalimagesacquiredfromCTor\nMRimagingdevicesandthatsuchprocessingmay\nincludethegenerationofpreliminarysegmentationsof\nnormalanatomyusingsoftwarethatemploysmachine","CeevraReveal2.0isintendedasamedicalimaging\nsystemthatallowstheprocessing,review,analysis,\ncommunicationandmediainterchangeof\nmulti-dimensionaldigitalimagesacquiredfromCTor\nMRimagingdevices.Itisalsointendedassoftware\nforpreoperativesurgicalplanning,andassoftwarefor\ntheintraoperativedisplayoftheaforementioned"]],"caption_candidate":"Table6.1:ComparisonofIndicationsforUseStatements","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p6-t0","doc_id":"K222676","page_num":6,"bbox":[72.33,273.6,537.67,548.5],"n_rows":14,"n_cols":3,"columns":["Feature/\nFunction","SubjectDevice\nCeevraReveal3\n(K222676)","PrimaryPredicate\nCeevraReveal2.0\n(K173274)"],"rows":[["Feature/\nFunction","SubjectDevice\nCeevraReveal3\n(K222676)","PrimaryPredicate\nCeevraReveal2.0\n(K173274)"],["SupportedimageModalities","CTandMR","CTandMR"],["Intendedusers","HealthcareProfessionals","HealthcareProfessionals"],["Intendedenvironment","Healthcarefacilitiessuchas\nhospitalsandclinics","Healthcarefacilitiessuch\nashospitalsandclinics"],["DeviceClass","ClassII","ClassII"],["Imageanalysisfeatures","Interactivemanipulation\nand3Dvisualization","Interactivemanipulation\nand3Dvisualization"],["Preoperativeviewingof3Dimages","Yes","Yes"],["Intraoperativeviewingof3Dimages","Yes","Yes"],["3Dimagesusedintraoperativelyforreal-time\nguidance,navigationorotherwiseintegrated\nwithsurgicalinstruments","No","No"],["Segmentationworkperformedby","InternalOperators","InternalOperators"],["Built-infeaturesforend-usertocompare\nCT/MRtodeviceoutput","No","No"],["Quantitativeoutputscalculatedbydevice","No","No"],["Softwaregeneratessemi-automated\nsegmentationsofabnormalanatomy","No","No"],["Softwaregeneratessemi-automated\nsegmentationsofcertainnormalanatomy","Yes","No"]],"caption_candidate":"Table7.2:ComparisonofDeviceCharacteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222676-p7-t0","doc_id":"K222676","page_num":7,"bbox":[72.0,183.82,539.71,224.9],"n_rows":3,"n_cols":2,"columns":["","The data used in the device validation ensured"],"rows":[["","The data used in the device validation ensured"],["diversity in patient population and scanner manufacturers. Subgroup analysis was performed for patient age,",""],["patient sex, and scanner manufacturers.",""]],"caption_candidate":"at the level of the scanning institution, namely, studies sourced from a specific institution were used for","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222692-p6-t0","doc_id":"K222692","page_num":6,"bbox":[77.58,96.3,545.64,697.38],"n_rows":2,"n_cols":3,"columns":["","Predicate Device HealthVCF\n(K192901)","Subject Device\nAidoc Briefcase for\nVertebral Compression\nFractures (VCFx) Triage"],"rows":[["","Predicate Device HealthVCF\n(K192901)","Subject Device\nAidoc Briefcase for\nVertebral Compression\nFractures (VCFx) Triage"],["Intended Use / Indications for\nUse","HealthVCF is a passive\nnotification for prioritization-\nonly, parallel-workflow software\ntool used by clinicians to\nprioritize specific patients\nwithin the standard-of-care\nbone health setting for\nsuspected vertebral\ncompression fractures.\nHealthVCF uses an artificial\nintelligence algorithm to\nanalyze chest and abdominal\nCT scans and flags those that\nare suggestive of the presence\nof at least one vertebral\ncompression at the exam level.\nThese flags are viewed by the\nclinician in Bone Health and\nFracture Liaison Service\nprograms in the medical setting\nvia a worklist application on\ntheir Picture Archiving and\nCommunication System\n(PACS). HealthVCF does not\nsend a proactive alert directly\nto the user.\nHealthVCF does not provide\ndiagnostic information beyond\ntriage and prioritization, it does\nnot remove cases from the\nradiology worklist, and should\nnot be used in place of full\npatient evaluation, or relied\nupon to make or confirm\ndiagnosis.","BriefCase is a radiological\ncomputer aided triage and\nnotification software indicated\nfor use in the analysis of chest\nand abdominal CT images. The\ndevice is intended to assist\nhospital networks and\nappropriately trained medical\nspecialists within the standard-\nof-care bone health setting in\nworkflow triage by flagging and\ncommunication of suspected\npositive cases of Vertebral\nCompression Fractures (VCFx)\nfindings.\nBriefCase uses an artificial\nintelligence algorithm to\nanalyze images and highlight\ncases with detected findings on\na standalone application in\nparallel to the ongoing standard\nof care image interpretation.\nThe device does not alter the\noriginal medical image and is\nnot intended to be used as a\ndiagnosis device.\nThe results of BriefCase are\nintended to be used in\nconjunction with other patient\ninformation and based on their\nprofessional judgment, to\nassist with triage/prioritization\nof medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222692-p7-t0","doc_id":"K222692","page_num":7,"bbox":[77.58,72.18,545.64,453.9],"n_rows":8,"n_cols":3,"columns":["","Predicate Device HealthVCF\n(K192901)","Subject Device\nAidoc Briefcase for\nVertebral Compression\nFractures (VCFx) Triage"],"rows":[["","Predicate Device HealthVCF\n(K192901)","Subject Device\nAidoc Briefcase for\nVertebral Compression\nFractures (VCFx) Triage"],["User population","Bone Health Clinicians","Hospital networks and\nappropriately trained medical\nspecialists within the standard-\nof-care bone health setting."],["Anatomical region of interest","Chest and abdomen","Chest and abdomen"],["Data acquisition protocol","Chest and abdominal CT scans","Chest and abdominal CT scans"],["Notification-only, parallel\nworkflow tool","Yes","Yes"],["Interference with standard\nworkflow","No","No"],["Algorithm","Artificial intelligence algorithm","Artificial intelligence algorithm"],["Structure","- Data input and\nvalidation (to ensure\ncompatibility for\nprocessing by the\nalgorithm)\n- HealthVCF algorithm.\n- Zebra Worklist.","- AHS module (orchestrator,\nimage acquisition);\n- ACS module (image\nprocessing));\n- Aidoc Desktop application\nfor workflow integration\n(feed and non-diagnostic\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222692-p9-t0","doc_id":"K222692","page_num":9,"bbox":[121.42,154.3,490.59,187.6],"n_rows":2,"n_cols":20,"columns":["","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age (Years)","","65.7","","","16.9","","","18","","","68","","","90","","","318",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222692-p9-t1","doc_id":"K222692","page_num":9,"bbox":[149.05,229.67,462.99,396.26],"n_rows":12,"n_cols":7,"columns":["Ground\nTruth\nResults","Gender","","","","All",""],"rows":[["Ground\nTruth\nResults","Gender","","","","All",""],["","Male","","Female","","",""],["","N","%","N","%","N","%"],["","92","28.9%","92","28.9%","184","57.9%"],["Positive","","","","","",""],["","","","","","",""],["","56","17.6%","78","24.5%","134","42.1%"],["Negative","","","","","",""],["","","","","","",""],["","148","46.5%","170","53.5%","318",""],["All","","","","","","100.0%"],["","","","","","",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222692-p9-t2","doc_id":"K222692","page_num":9,"bbox":[224.65,438.66,387.29,626.44],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["GE MEDICAL\nSYSTEMS","","","114","","","35.9%","",""],["SIEMENS","","","91","","","28.6%","",""],["TOSHIBA","","","57","","","17.9%","",""],["Philips","","","56","","","17.6%","",""],["","Total","","","318","","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p6-t0","doc_id":"K222728","page_num":6,"bbox":[72.33,99.98,539.8,544.42],"n_rows":10,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","","","Radiation Planning Assistant (RPA)","","","","Eclipse Treatment Planning System Version",""],["","","","","","","","15.6",""],["","","","","","","","K181145",""],["","CFR","","892.5050","","","892.5050","",""],["","Citation","","","","","","",""],["","Product","","MUJ","","","MUJ","",""],["","Code","","","","","","",""],["Indications\nfor Use","","","The Radiation Planning Assistant (RPA) is\nused to plan radiotherapy treatments for\npatients with cancers of the head and neck,\ncervix, breast, and metastases to the brain. The\nRPA is used to plan external beam irradiation\nwith photon beams using computerized\ntomography (CT) images. The RPA is used to\ncreate contours and treatment plans that the\nuser imports into their own Treatment Planning\nSystem (TPS) for review, editing, and re-\ncalculation of the dose.\nSome functions of the RPA use Eclipse\nv.15.6. The RPA is not intended to be used as\na primary treatment planning system. All\nautomatically generated contours and plans\nmust be imported into the user’s own\ntreatment planning system for review, edit,\nand final dose calculation.","","","The Eclipse Treatment Planning System\n(Eclipse TPS) is used to plan radiotherapy\ntreatments for patients with malignant or\nbenign diseases. Eclipse TPS is used to plan\nexternal beam irradiation with photon, electron,\nand proton beams, as well as for internal\nirradiation (brachytherapy) treatments.","",""],["Device\nDescription","","","The Radiation Planning Assistant (RPA) is a\nweb-based contouring and radiotherapy\ntreatment planning software tool that\nincorporates the basic radiation planning\nfunctions from automated contouring,\nautomated planning with dose optimization,\nand quality control checks. The system is\nintended for use for patients with cancer of the\nhead and neck, cervix, breast, and metastases to\nthe brain. The RPA system is integrated with\nthe Eclipse Treatment Planning System v.15.6\nsoftware cleared under K181145.","","","The Varian Eclipse™ Treatment Planning\nSystem (Eclipse TPS) provides software tools\nfor planning the treatment of malignant or\nbenign diseases with radiation. Eclipse TPS is\na computer-based software device used by\ntrained medical professionals to design and\nsimulate radiation therapy treatments.\nEclipse TPS is capable of planning treatments\nfor external beam irradiation with photon,\nelectron, and proton beams, as well as for\ninternal irradiation (brachytherapy) treatments.","",""]],"caption_candidate":"Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p7-t0","doc_id":"K222728","page_num":7,"bbox":[40.75,81.56,747.77,498.1],"n_rows":6,"n_cols":11,"columns":["","Comparison of the RPA System’s Software Functions with","","","","","","","","",""],"rows":[["","Comparison of the RPA System’s Software Functions with","","","","","","","","",""],["","Eclipse Treatment Planning System Version 15.6 (K181145)","","","","","","","","",""],["","Software","","","Description of Functions Available in","","Differences","Similarities","","Rationale for",""],["","Function","","","Eclipse","","","","","Substantial Equivalence",""],["Software\nContouring\nFunctions","","","1. Organ-specific autocontouring algorithms. Eclipse\nv.15.6 includes the following organ-specific\nautocontouring algorithms for the following organs:\nspine, lung, brain, eye, bone.\n2. Expert Segmentation. Eclipse v.15.6 includes an atlas-\nbased contouring approach (“expert segmentation”) for\nautocontouring of many structures, including:\n• Head / neck region: Body, bones, brainstem,\ncochlea, esophagus, eyes, mandible, oral cavity,\nvarious lymph nodes\n• Breast region: Body, heart, trachea, various\nlymph nodes\n• Pelvis: Body, bladder, femoral heads, pelvic\nbones, rectum, spinal canal\nThe system calculates the anatomical points, image\nfeatures, and similarity scores of the patient image and\ncompares them with pre-stored expert cases. Rigid\nregistration is used both for initializing the deformable\nregistration algorithm and for displaying the expert case\nand patient image in aligned preview. The\nautocontouring approach depends on the selected\nstructures. Either the structures are heuristically\nsegmented from the patient image, or the structures are\ngenerated via deformable registration and structure\npropagation from the expert cases. If multiple expert\ncases are used, the propagated structures from the\ndifferent atlases are fused by means of the simultaneous\ntruth and performance level estimation (STAPLE)\nalgorithm.","","","The RPA uses deep learning algorithms\nwhich Eclipse does not.\nUse and function: In Eclipse, the user edits\nthe contours prior to planning. This is the\nsame for complex planning in the RPA\n(VMAT planning for head / neck and cervix).\nIt is different for simple plans, where the plan\nis generated before the user reviews the\ncontours. If the user edits the contours in the\nRPA, they will have to delete the plan as\nwell.","Use and function: The RPA\nprovides autocontouring for a\nrange of structures, including\nmost of those listed here for\nEclipse.\nPerformance data: The\nalgorithm for Expert\nSegmentation in Eclipse is\nvery similar to the Multi-Atlas\nContouring System (MACS)\nthat is used to contour\nstructures for the chest wall\nplanning in the RPA.\nSafety and effectiveness: Both\nEclipse and the RPA are\ndesigned to provide contours\nthat the users review and edit.","Devices are Substantially\nEquivalent. Both devices\nprovide autocontouring\nfunctions for the same\nanatomical regions. Both\ndevices require user edits of\ncontours with ‘complex plans’\nprior to planning.","",""],["Eclipse,\nOther Plan\nPreparation","","","Automatic marker detection - Eclipse v.15.6 includes a\nfunction (‘Calypso Beacon Detection’) to automatically\ndetect a specific type of marker (Calypso transponders)\non CT images.","","","Use and function: The Eclipse function is for\na specific type of marker that is different\nfrom the generic markers that the RPA is\ndesigned for.","Use and function: Both Eclipse\nand the RPA can automatically\ndetect markers.","Devices are Substantially\nEquivalent. Both devices can\nautomatically detect markers.","",""]],"caption_candidate":"Table 2: Comparison of Functions of the Subject Device with Functions of the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p8-t0","doc_id":"K222728","page_num":8,"bbox":[40.75,61.74,746.9,522.34],"n_rows":6,"n_cols":11,"columns":["","Comparison of the RPA System’s Software Functions with the","","","","","","","","",""],"rows":[["","Comparison of the RPA System’s Software Functions with the","","","","","","","","",""],["","Eclipse Treatment Planning System Version 15.6 (K181145)","","","","","","","","",""],["","Software","","","Description of Functions Available in","","Differences","Similarities","","Rationale for Substantial",""],["","Function","","","Eclipse","","","","","Equivalence",""],["Eclipse\nAutomated\nPlanning,\nVMAT","","","1. Photon Optimizer (PO) algorithm. This algorithm\nis used to optimize IMRT or VMAT plans based on\nDVH constraints / objectives.\n2. Automated Optimization Workflow. Enabling this\ncan automate the optimization workflow for IMRT\nplanning so that, after optimization, the leaf motion\ncalculation and final dose calculation are\nautomatically initiated, and the results are then\nautomatically saved. A similar feature exists for\nVMAT plans.\n3. DVH Estimation Models for RapidPlan. DVH\nestimation models are created from information\nextracted from a set of previous treatment plans\n(called ‘treatment plans’). The estimation models\npredict the DVH that is achievable from the current\ntreatment plan (based on the geometry in the current\nplan), and also creates a set of optimization objects\nthat can be based on the DVH estimates or fixed\n(i.e., not based on the DVH estimates).","","","Use and function: The main difference for\nVMAT planning is that Eclipse generally\ncreates a plan that the user reviews, makes\nedits to the optimization constraints, and\nrepeats the process to improve the plan\nquality. The RPA uses the same\noptimization tools (i.e., the tools in Eclipse),\nbut the optimization objectives and\nconstraints have been pre-set to give optimal\nplans for the majority of patients. The user\nis not able to easily edit the RPA VMAT\nplans so, if they do not approve the plan for\nclinical use, they must delete it and create\none using their own routine processes (i.e.,\nin their own treatment planning system).","Use and function: The RPA\nuses some Eclipse features,\nincluding DVH Estimates for\nRapidPlan and the Photon\nOptimizer for optimizing\nVMAT plans. The plans look\nvery similar.\nSafety and effectiveness: Both\nEclipse and the RPA are\ndesigned to create plans that\nthe users then edit and review\nfor clinical acceptability prior\nto use.","Devices are Substantially\nEquivalent. Both devices provide\nautoplanning features and create\nplans that the users then edit and\nreview for clinical acceptability\nprior to use. Both devices provide\nPhoton Optimizer, automated\noptimization workflow and DVH\nestimation models.","",""],["Autoplanning,\nOther","","","1. Beam Angle Optimization (BAO). This tool\noptimizes the number and angle of treatment beams.\nIt optimizes the objective function, which is\ndetermined by DVH goals / constraints and a normal\ntissue objective (which falls off with distance from\nthe PTV). BAO can be used for IMRT plans or as a\nstarting point for conformal treatment plans.\n2. Collimator Angle Optimization (CAO). This\nfunction optimizes collimator angle for each arc of a\nHyperArc plan such that, whenever possible, a given\npair of MLC leaves delineates only one target in the\nbeam’s-eye-view.\n3. Optimize collimator jaws. Adjusts the collimator\njaws to best fit the MLC leaves to the structure.\n4. Use recommended jaw positions. Adjusts the\ncollimator jaw positions with an additional margin.\n5. Optimize collimator rotation. Optimizes the\ncollimator rotation around a structure.","","","Use and function: Autoplanning in Eclipse\nis mostly automation of individual tasks that\nare controlled by the user. The user does\nnot control these tasks with the RPA.\nUse and function: Review and editing of 3D\nplans (cervix 4-field box, post-mastectomy\nbreast plans, whole brain plans) for the RPA\nhappens in the users’ own treatment\nplanning system.","Use and function: Many of the\ntreatment plan details in\nEclipse and RPA use functions\nwith similar algorithms, such\nas optimizing the jaw\npositions.\nSafety and effectiveness: Both\nEclipse and the RPA are\ndesigned to create plans that\nthe users then edit and review\nfor clinical acceptability prior\nto use.","Devices are Substantially\nEquivalent. Both devices create\nplans that the users then edit and\nreview for clinical acceptability\nprior to use through the use of AI\nsoftware. Both devices provide\nBeam Angle Optimization,\nCollimator Angle Optimization and\ncollimator jaw optimization.","",""]],"caption_candidate":"510(k) Summary Radiation Planning Assistant (RPA)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p10-t0","doc_id":"K222728","page_num":10,"bbox":[72.29,137.76,719.86,472.63],"n_rows":6,"n_cols":8,"columns":["","Anatomical","","Tissue Type(s)","Training Data Set","","Test Data",""],"rows":[["","Anatomical","","Tissue Type(s)","Training Data Set","","Test Data",""],["","Location","","","","","Independence",""],["Head and Neck","","","Normal Tissue\n(primary)","3,288 patients (3,495 CT scans) who received radiation therapy at MD\nAnderson Cancer Center between September 2004 and June 2018. Any\npatient who received a simulation CT scan of the head/neck region in a\nhead -first supine position was eligible.","174 CT scans were\nrandomly selected from\nthis group (and excluded\nfor training) plus\nqualitative evaluation 24\nCT scans from an\nexternal dataset.","",""],["","","","Normal Tissue\n(secondary)","160 patients who received radiation therapy at MD Anderson Cancer\nCenter from 2018 to 2020. Any patient who received a simulation CT\nscan of the head/neck region in a head-first supine position was eligible.","Test patients were\nrandomly selected and\nexcluded from the\ntraining set.","",""],["","","","Lymph Node\nCTVs","61 patients who received radiation therapy at MD Anderson Cancer\nCenter between 2010 and 2019. Any patient who received a simulation\nCT scan of the head/neck region in a head-first supine position was\neligible.","These 71 cases were\nrandomly placed in 3\ngroups: training (51 pts.),\ncross-validation (10 pts.)\nand final test (10 pts.).","",""],["Whole Brain","","","Whole Brain","The whole brain primary segmentation models used the same models as\nused for head and neck segmentation, described above, as well as an\nadditional vertebral body localization and segmentation model (Vertebral\nBodies model: spinal canal CNN: 1,966, VB labeling: 803, VB\nsegmentation: 107, from 930 MDACC patients and 355 external\npatients). Patients who received spinal radiotherapy for spinal metastases\n(3DCRT and VMAT) at MD Anderson, or for whom data was publicly\navailable (MICCAI challenge data).","Test patients were\nrandomly selected from\nthis group (and excluded\nfor training).","",""]],"caption_candidate":"Table 3: Software Training for Anatomical Locations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p11-t0","doc_id":"K222728","page_num":11,"bbox":[72.28,72.36,719.86,416.83],"n_rows":7,"n_cols":8,"columns":["","Anatomical","","Tissue Type(s)","Training Data Set","","Test Data",""],"rows":[["","Anatomical","","Tissue Type(s)","Training Data Set","","Test Data",""],["","Location","","","","","Independence",""],["GYN","","","Normal Tissue\n(primary)","1,999 patients (2,254 CT scans) who received radiation therapy at MD\nAnderson from September 2004 and June 2018. Any patient who\nreceived a simulation CT scan of the pelvic region in a head-first supine\nposition was eligible.","140 CT scans were\nrandomly selected from\nthis group (and excluded\nfor training) plus\nqualitative evaluation\nwith 30 cervical cancer\npatients from 3 centers in\nS. Africa.","",""],["","","","Normal Tissue\n(secondary)","192 patients (316 CT scans) who were treated for locally advanced\ncervical cancer between 2006 and 2020.","Test patients were\nrandomly selected from\nthis group (and excluded\nfor training).","",""],["","","","CTVs (primary)","406 CT scans from 308 patients (UteroCervix), 250 CT scans from 201\npatients (Nodal CTV), 146 CT scans from 131 patients (PAN), 490 CT\nscans from 388 patients (Vagina), 487 CT scans from 388 patients\n(Parametria) who received radiation therapy at MD Anderson Cancer\nCenter between 2006 and 2020.","Test patients were\nrandomly selected from\nthis group (and excluded\nfor training).","",""],["","","","Liver","Training data for GYN Liver (normal) comprised 119 patients (169 CT\nscans) who had received contrast-enhanced and non-contrast CT imaging\nof the liver at MD Anderson Cancer Center.","Test patients were\nrandomly selected from\nthis group (and excluded\nfor training).","",""],["Chest Wall","","","Whole Body\n(secondary for\nchest wall)","Training data for whole body (secondary for chest wall) comprised 250\npatients who were treated at MD Anderson between August 2016 and\nJune 2021, with CT imaging in the thoracic region.","Test patients were\nrandomly selected from\nthis group (and excluded\nfor training).","",""]],"caption_candidate":"510(k) Summary Radiation Planning Assistant (RPA)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p14-t0","doc_id":"K222728","page_num":14,"bbox":[72.54,86.44,540.55,495.91],"n_rows":8,"n_cols":5,"columns":["","Criteria","","Criteria","Results"],"rows":[["","Criteria","","Criteria","Results"],["","Number","","",""],["1","","","Assess the safety of using the RPA plan for normal structures for treatment\nplanning by comparing the number of patient plans that pass accepted\ndosimetric metrics when assessed on the RPA contour with the number that\npass when assessed on the clinical contour. The difference should be 5% or\nless. When there are multiple metrics for a single structure at least one\nshould pass this criterion.","< 5% difference\nbetween RPA Plan and\nClinical Plan for all\nbony structures and\ncritical soft tissue\nstructures with VMAT\nand 4 field box.*"],["2","","","Assess the effectiveness of the RPA plan for normal structures by\ncomparing the dose to RPA normal structures for RPA plans and clinical\nnormal structures for clinical plans. The difference in the number of RPA\nplans that pass accepted dosimetric metrics and the number of clinical plans\nthat pass accepted dosimetric metrics should be 5% or less. When there are\nmultiple metrics for a single structure at least one should pass this criterion.","< 5% difference\nbetween RPA Plan and\nClinical Plan for all\nbony structures and\ncritical soft tissue\nstructures with VMAT\nand 4 field box.**"],["3","","","Assess the effectiveness of the RPA plan for target structures by comparing\nthe number of RPA plans that pass accepted dosimetric metrics (e.g.,\npercentage volume of the PTV receiving 95% of the prescribed dose) when\ncompared with clinical plans. The difference should be 5% or less. When\nthere are multiple metrics used to assess a single structure, at least one\ncoverage and one maximum criterion should pass this criterion.","< 5% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures"],["4","","","Assess the geometric effectiveness of the RPA targets using recall. A low\nvalue for this metric represents under-contouring. The 25th percentile of the\nrecall must be 0.7 or greater.","25th percentile for\nrecall > 0.7"],["5","","","Assess the quality of body contouring generated by the RPA by comparing\nprimary and secondary body contours generated by the RPA with manual\nbody contours. Surface DSC (2mm) should be greater than 0.8 for 95% of\nthe CT scans.","Surface DSC > 0.8 for\n95% of CT scans"],["6","","","Assess the ability of the RPA to accurately identify the marked isocenter.\nThis is achieved by comparing the automatically generated isocenters with\nmanually generated ones. 95% of automatically generated marked\nisocenters (primary and verification approaches) should agree with\nmanually generated marked isocenters within 3mm in all orthogonal\ndirections (AP, lateral, cranial-caudal).","< 3mm difference\nbetween RPA Plan and\nClinical Plan for all\northogonal directions"]],"caption_candidate":"Table 5: Summary of Statistical Results—Cervix","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p15-t0","doc_id":"K222728","page_num":15,"bbox":[72.53,86.48,539.83,468.25],"n_rows":10,"n_cols":6,"columns":["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],"rows":[["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],["","Number","","","",""],["1","","","CT scan of the female pelvic anatomy.","Poor Image Quality","Test datasets were chosen\ngoing forward in time\nuntil sufficient data were\ncollected, starting with CT\nscans collected on January\n1, 2022. If insufficient\npatient scans were found,\ndata collection was\nrestarted with January 1,\n2021 (for patients treated\nin 2021) and so forth, until\nsufficient data was\ncollected."],["2","","","Clear CT image of the pelvic region without\ndistortions.","-",""],["3","","","Test datasets consisted of CT images of\npatients previously treated for cervical\ncancer using radiotherapy following one of\nthe following treatment schemes:\n• 4-field box (based on bony\nlandmarks or soft tissue)\n• VMAT","-",""],["4","","","Scan was obtained with patient head-first,\nsupine.","-",""],["5","","","The datasets included CT images, original\nclinical contours of anatomic structures and\ntreatment targets, and the dose distributions\nused for patient treatment.","-",""],["6","","","Test datasets were chosen going forward in\ntime until sufficient data was collected,\nstarting with CT scans collected on January\n1, 2022. If insufficient patient scans were\nfound, data collection could be restarted with\nJanuary 1, 2021 (for patients treated in 2021)\nand so forth, until sufficient data was\ncollected.","-",""],["7","","","Testing datasets were unique, with no\noverlap with data used for model creation or\nin previous validation studies.","-",""],["8","","","CT scans included the manufacturer and\nmodel of the scanner used to obtain the CT\nimage.","-",""]],"caption_candidate":"Table 6: Summary of Cervix Protocol","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p16-t0","doc_id":"K222728","page_num":16,"bbox":[72.56,86.16,540.53,320.33],"n_rows":5,"n_cols":5,"columns":["","Criteria","","Criteria","Results"],"rows":[["","Criteria","","Criteria","Results"],["","Number","","",""],["1","","","Assess the safety of use of the RPA by comparing the number of patient\nplans that pass accepted dosimetric metrics when assessed on the RPA\ncontour with the number that pass when assessed on the clinical contour.\nThe difference should be 5% or less. When multiple metrics were used to\nassess a single structure at least one had to pass the criteria (similar to the\nmanner in which doses are assessed in clinical practice).","<7% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures."],["2","","","Assess the effectiveness of use of the RPA by comparing the number of\nRPA plans that pass accepted dosimetric metrics (e.g., mean dose to the\norgan-at-risk) when compared with clinical plans.\nThe difference should be 5% or less. When multiple metrics were used to\nassess a single structure, at least one should pass this criterion (similar to\nthe manner in which doses are assessed in clinical practice). This was\nconsidered on a structure-by-structure basis.","<5% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures."],["3","","","Assess the quality of body contouring generated by the RPA by\ncomparing primary and secondary body contours generated by the RPA\nwith manual body contours. Surface DSC (2mm) should be greater than\n0.8 for 95% of the CT scans.","Surface DSC > 0.8 for\n95% of CT scans"]],"caption_candidate":"Table 7: Chest Wall Summary of Statistical Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p17-t0","doc_id":"K222728","page_num":17,"bbox":[72.53,86.48,539.83,501.28],"n_rows":10,"n_cols":6,"columns":["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],"rows":[["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],["","Number","","","",""],["1","","","CT scan of the breast (thorax) region.","Poor Image Quality","Test datasets were chosen\ngoing forward in time\nuntil sufficient data was\ncollected, starting with CT\nscans collected on January\n1, 2022. If insufficient\npatient scans were found,\ndata collection was\nrestarted with January 1,\n2021 (for patients treated\nin 2021) and so forth, until\nsufficient data was\ncollected."],["2","","","Clear CT image of the breast (thorax) region\nwithout distortions.","-",""],["3","","","Test datasets must consist of CT images of\npatients previously treated for\npostmastectomy breast radiotherapy\nfollowing one of the following treatment\nschemes:\ni. Tangent fields with supraclavicular\nfields. Similar approaches,\nincluding those that also treat the\nintramammary lymph nodes are\nalso acceptable.","-",""],["4","","","Scan was obtained with patient head-first,\nsupine.","-",""],["5","","","The datasets must include CT images,\noriginal clinical contours of anatomic\nstructures and treatment targets, and the dose\ndistributions used for patient treatment.","-",""],["6","","","Test datasets were chosen going forward in\ntime until sufficient data was collected,\nstarting with CT scans collected on January\n1, 2022. If insufficient patient scans were\nfound, data collection can be restarted with\nJanuary 1, 2021 (for patients treated in 2021)\nand so forth, until sufficient data was\ncollected.","-",""],["7","","","Testing datasets must be unique, with no\noverlap with data used for model creation or\nin previous validation studies.","-",""],["8","","","CT scan must include the manufacturer and\nmodel of the scanner used to obtain the CT\nimage or recorded separately.","-",""]],"caption_candidate":"Table 8: Chest Wall Protocol Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p18-t0","doc_id":"K222728","page_num":18,"bbox":[72.54,86.44,540.55,495.91],"n_rows":8,"n_cols":5,"columns":["","Criteria","","Criteria","Results"],"rows":[["","Criteria","","Criteria","Results"],["","Number","","",""],["1","","","Assess the safety of use of RPA normal structures for treatment planning\nby comparing the number of patient plans that passed accepted dosimetric\nmetrics (e.g., mean dose to the parotid) when assessed on the RPA\ncontour with the number that passed when assessed on the clinical\ncontour. The difference should be 5% or less. When multiple metrics\nwere used to assess a single structure at least one should pass this\ncriterion.","<5% difference\nbetween RPA Plan and\nClinical Plan for the\nmajority of assessed\nstructures."],["2","","","Assess the effectiveness of use of RPA normal structures for treatment\nplanning by comparing the number of RPA plans that passed accepted\ndosimetric metrics (e.g., mean dose to the parotid) when compared with\nclinical plans. The difference should be 5% or less. When multiple\nmetrics were used to assess a single structure, at least one should pass this\ncriterion.","<5% difference\nbetween RPA Plan and\nClinical Plan for the\nmajority of assessed\nstructures*."],["3","","","Assess the effectiveness of the RPA plan for target structures by\ncomparing the number of RPA plans that pass accepted dosimetric metrics\n(e.g., percentage volume of the PTV receiving 95% of the prescribed\ndose) when compared with clinical plans. The difference should be 5% or\nless. When there are multiple metrics used to assess a single structure, at\nleast one coverage and one maximum criterion should pass this criterion.","<5% difference\nbetween RPA Plan and\nClinical Plan for the\nmajority of assessed\ncriteria."],["4","","","Assess the geometric effectiveness of the RPA targets using recall. A\nlow value for this metric represents under-contouring and a potential risk\nof creating a plan that misses the target (although the user is expected to\nreview and edit contours). The 25th percentile of the recall must be 0.7 or\ngreater.","25th percentile for\nrecall > 0.7"],["5","","","Assess the quality of body contouring generated by the RPA by\ncomparing body contours generated by the RPA with manual body\ncontours. Surface DSC (2mm) should be greater than 0.8 for 95% of the\nCT scans.","Surface DSC > 0.8 for\n>95% of CT scans"],["6","","","Assess the ability of the RPA to accurately identify the marked isocenter.\nThis is achieved by comparing the automatically generated isocenters with\nmanually generated ones. 95% of automatically generated marked should\nagree with manually generated marked isocenters within 3mm in all\northogonal directions (AP, lateral, cranial-caudal).","<3mm difference\nbetween RPA Plan and\nClinical Plan for all\northogonal directions."]],"caption_candidate":"Table 9: Head and Neck Summary of Statistical Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p19-t0","doc_id":"K222728","page_num":19,"bbox":[72.53,86.48,539.83,455.29],"n_rows":10,"n_cols":6,"columns":["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],"rows":[["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],["","Number","","","",""],["1","","","CT scan of head and neck anatomy.","Poor Image Quality","Test datasets were chosen\ngoing forward in time\nuntil sufficient data was\ncollected, starting with CT\nscans collected on January\n1, 2022. If insufficient\npatient scans were found,\ndata collection was\nrestarted with January 1,\n2021 (for patients treated\nin 2021) and so forth, until\nsufficient data was\ncollected."],["2","","","Clear CT image of head and/or neck\nwithout distortions.","-",""],["3","","","Test datasets consisted of CT images of\npatients previously treated for head and\nneck cancer using radiotherapy following\nthis treatment scheme:\ni. VMAT or IMRT treatments\nii. 1-3 dose levels in the prescription","-",""],["4","","","Scan was obtained with patient head-first,\nsupine.","-",""],["5","","","The datasets included CT images, original\nclinical contours of anatomic structures and\ntreatment targets, and the dose distributions\nused for patient treatment.","-",""],["6","","","Test datasets were chosen going forward in\ntime until sufficient data was collected,\nstarting with CT scans collected on January\n1, 2022. If insufficient patient scans were\nfound, data collection could be restarted\nwith January 1, 2021 (for patients treated in\n2021) and so forth, until sufficient data was\ncollected.","-",""],["7","","","Testing datasets were unique, with no\noverlap with data used for model creation\nor in previous validation studies.","-",""],["8","","","CT scans included the manufacturer and\nmodel of the scanner used to obtain the CT\nimage or were recorded separately.","-",""]],"caption_candidate":"Table 10: Head and Neck Protocol Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p20-t0","doc_id":"K222728","page_num":20,"bbox":[72.54,86.44,540.54,439.63],"n_rows":7,"n_cols":5,"columns":["","Criteria","","Criteria","Results"],"rows":[["","Criteria","","Criteria","Results"],["","Number","","",""],["1","","","Assess the safety of using the RPA plan for normal structures by\ncomparing the number of patient plans that pass accepted dosimetric\nmetrics when assessed on the RPA contour with the number that pass\nwhen assessed on the clinical contour. The difference should be 5% or\nless. When there are multiple metrics for a single structure at least one\nshould pass this criterion.","<6% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures\n(Right and Left\nLens)*."],["2","","","Assess the effectiveness of the RPA plan for normal structures by\ncomparing the number of RPA plans that pass accepted dosimetric metrics\nwhen compared with clinical plans. The difference should be 5% or less.\nWhen there are multiple metrics for a single structure at least one should\npass this criterion.","<9% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures\n(Right and Left\nLens)**."],["3","","","Assess the effectiveness of the RPA plan for target structures by\ncomparing the number of RPA plans that pass accepted dosimetric metrics\n(e.g., percentage volume of the brain receiving 95% of the prescribed\ndose) when compared with clinical plans. The difference should be 5% or\nless. When there are multiple metrics used to assess a single structure, at\nleast one coverage and one maximum criterion should pass this criterion.","<5% difference\nbetween RPA Plan and\nClinical Plan for all\nassessed structures."],["4","","","Assess the quality of body contouring generated by the RPA by\ncomparing primary and secondary body contours generated by the RPA\nwith manual body contours. Surface DSC (2mm) should be greater than\n0.8 for 95% of the CT scans.","> 0.8 difference\nbetween RPA Plan and\nClinical Plan for all\nassessments."],["5","","","Assess the ability of the RPA to accurately identify the marked isocenter.\nThis is achieved by comparing the automatically generated isocenters with\nmanually generated ones. 95% of automatically generated marked\nisocenters (primary and verification approaches) should agree with\nmanually generated marked isocenters within 3mm in all orthogonal\ndirections.","<3mm difference\nbetween RPA Plan and\nClinical Plan for all\northogonal directions."]],"caption_candidate":"Table 11: Whole Brain Summary of Statistical Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222728-p21-t0","doc_id":"K222728","page_num":21,"bbox":[72.53,86.48,539.83,443.77],"n_rows":10,"n_cols":6,"columns":["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],"rows":[["","Criteria","","Inclusion Criteria","Exclusion Criteria","Sampling Method"],["","Number","","","",""],["1","","","CT scan of the head/neck region.","Poor Image Quality","Test datasets were chosen\ngoing forward in time\nuntil sufficient data was\ncollected, starting with CT\nscans collected on January\n1, 2022. If insufficient\npatient scans were found,\ndata collection was\nrestarted with January 1,\n2021 (for patients treated\nin 2021) and so forth, until\nsufficient data was\ncollected."],["2","","","Clear CT image of the head/neck region\nwithout distortions.","-",""],["3","","","Test datasets consisted of CT images of\npatients previously treated for whole brain\nradiotherapy following one of the following\ntreatment schemes:\ni. Opposed laterals or slight obliques.","-",""],["4","","","Scan was obtained with patient head-first,\nsupine.","-",""],["5","","","The datasets included CT images, original\nclinical contours of anatomic structures and\ntreatment targets, and the dose distributions\nused for patient treatment.","-",""],["6","","","Test datasets were chosen going forward in\ntime until sufficient data was collected,\nstarting with CT scans collected on January\n1, 2022. If insufficient patient scans were\nfound, data collection could be restarted with\nJanuary 1, 2021 (for patients treated in 2021)\nand so forth, until sufficient data was\ncollected.","-",""],["7","","","Testing datasets were unique, with no\noverlap with data used for model creation or\nin previous validation studies.","-",""],["8","","","CT scans included the manufacturer and\nmodel of the scanner used to obtain the CT\nimage.","-",""]],"caption_candidate":"Table 12: Whole Brain Protocol Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p2-t0","doc_id":"K222745","page_num":2,"bbox":[257.81,458.47,570.34,568.87],"n_rows":8,"n_cols":2,"columns":["Jessica Lamb,",""],"rows":[["Jessica Lamb,",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""],["Center for Devices and Radiological Health",""]],"caption_candidate":"for Jessica Lamb","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p6-t0","doc_id":"K222745","page_num":6,"bbox":[54.32,125.88,584.32,188.04],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["Axial3D Cloud Segmentation Service","Axial Medical Printing Limited","K221511"]],"caption_candidate":"Table 5-1 – Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p7-t0","doc_id":"K222745","page_num":7,"bbox":[54.28,125.88,584.48,717.96],"n_rows":16,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","","Service","(Reference","Comparison"],["","(Proposed Device)","","",""],["","","(Predicate","Device)",""],["","","","",""],["","","Device)","",""],["Device\nManufacturer","Axial Medical\nPrinting Limited","Axial Medical\nPrinting Limited","Materialise N.V.","N/A"],["Device Name","Axial3D Insight","Axial3D Insight","Mimics inPrint","N/A"],["Device Trade\nor Proprietary\nName","Axial3D Insight","Axial3D Insight","Mimics inPrint","N/A"],["510(k)\nNumber","TBD","K221511","K173619","N/A"],["Device\nRegulation\nName:","Automated\nRadiological Image\nProcessing Software","Medical image\nmanagement and\nprocessing\nsystem","Picture archiving\nand\ncommunications\nsystem","Different –\nUpdated based\non additional\nprocessing"],["Device\nRegulation\nNumber:","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","Equivalent"],["Device\nProduct\nCode:","QIH","LLZ","LLZ","Different –\nUpdated based\non additional\nprocessing"],["Device\nClassification\nFDA:","Class II","Class II","Class II","Equivalent"],["Indication for\nUse","Axial3D Insight is\nintended for use as a\ncloud-based service\nand image\nsegmentation\nframework for the\ntransfer of DICOM\nimaging information\nfrom a medical\nscanner to an output\nfile.","Axial3D Cloud\nSegmentation\nService is\nintended for use\nas a cloud based\nservice and\nimage\nsegmentation\nsystem for the\ntransfer of\nDICOM imaging","Mimics inPrint is\nintended for use\nas a software\ninterface and\nimage\nsegmentation\nsystem for the\ntransfer of\nDICOM imaging\ninformation from\na medical","Equivalent"]],"caption_candidate":"Table 5-2 – Predicate Device Comparison: Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p8-t0","doc_id":"K222745","page_num":8,"bbox":[54.36,77.34,584.4,711.24],"n_rows":8,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","","Service","(Reference","Comparison"],["","(Proposed Device)","","",""],["","","(Predicate","Device)",""],["","","","",""],["","","Device)","",""],["","The Axial3D Insight\noutput file can be\nused for the\nfabrication of\nphysical replicas of\nthe output file using\nadditive\nmanufacturing\nmethods.\nThe output file or\nphysical replica can\nbe used for treatment\nplanning.\nThe output file or\nphysical replica can\nbe used for\ndiagnostic purposes\nin the field of trauma,\northopedic,\nmaxillofacial, and\ncardiovascular\napplications.\nAxial3D Insight\nshould be used with\nother diagnostic tools\nand expert clinical\njudgment.","information from\na medical\nscanner to an\noutput file.\nThe Axial3D\nCloud\nSegmentation\nService output\nfile can be used\nfor the fabrication\nof physical\nreplicas of the\noutput file using\nadditive\nmanufacturing\nmethods.\nThe output file or\nphysical replica\ncan be used for\ntreatment\nplanning.\nThe physical\nreplica can be\nused for\ndiagnostic\npurposes in the\nfield of\northopedic,\nmaxillofacial and\ncardiovascular\napplications.\nAxial3D Cloud\nSegmentation\nService should\nbe used in\nconjunction with\nother diagnostic\ntools and expert\nclinical judgment.","scanner to an\noutput file. It is\nalso used as pre-\noperative\nsoftware for\ntreatment\nplanning. For this\npurpose, the\nMimics inPrint\noutput file can be\nused for the\nfabrication of\nphysical replicas\nof the output file\nusing traditional\nor additive\nmanufacturing\nmethods.\nThe physical\nreplica can be\nused for\ndiagnostic\npurposes in the\nfield of\northopedic,\nmaxillofacial, and\ncardiovascular\napplications.\nMimics inPrint\ncan be used for\ndiagnostic\npurposes in the\nfield of\northopedic,\nmaxillofacial, and\ncardiovascular\napplications.\nMimics inPrint\nshould be used in\nconjunction with",""]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p9-t0","doc_id":"K222745","page_num":9,"bbox":[54.34,77.34,584.42,714.72],"n_rows":9,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","","Service","(Reference","Comparison"],["","(Proposed Device)","","",""],["","","(Predicate","Device)",""],["","","","",""],["","","Device)","",""],["","","","other diagnostic\ntools and expert\nclinical\njudgement.",""],["Intended Use","Axial Medical\nPrinting Limiteds,\nAxial3D Insight\nprovides patient-\nspecific 1:1 scale\nreplica models, either\nas a digital file or as\na 3D printed physical\nmodel.\nThe digital file or 3D\nprinted physical\nmodel is intended to\nbe used in\nconjunction with the\nDICOM images and\nexpert clinical\njudgement. The\napplications for using\nthe physical 3D\nprinted physical\nmodel as a\npresurgical planning\ntool are as follows:\nPreoperative\nplanning of surgical\ntreatment options\nincluding planning for\nsurgical instruments,\naiding decisions on\nimplants, and aiding\nthe surgical\ntreatment plan., All\nplanning using the\n3D replica model\nshould be carried out","Axial3D Cloud\nSegmentation\nService is\nintended for use\nas a cloud based\nservice and\nimage\nsegmentation\nsystem for the\ntransfer of\nDICOM imaging\ninformation from\na medical\nscanner to an\noutput file.\nThe Axial3D\nCloud\nSegmentation\nService output\nfile can be used\nfor the fabrication\nof physical\nreplicas of the\noutput file using\nadditive\nmanufacturing\nmethods.\nThe output file or\nphysical replica\ncan be used for\ntreatment\nplanning.\nThe physical\nreplica can be\nused for","Mimics inPrint is\nintended for use\nas a software\ninterface and\nimage\nsegmentation\nsystem for the\ntransfer of\nDICOM imaging\ninformation from\na medical\nscanner to an\noutput file. It is\nalso used as pre-\noperative\nsoftware for\ntreatment\nplanning. For this\npurpose, the\nMimics inPrint\noutput file can be\nused for the\nfabrication of\nphysical replicas\nof the output file\nusing traditional\nor additive\nmanufacturing\nmethods. The\nphysical replica\ncan be used for\ndiagnostic\npurposes in the\nfield of\northopedic,\nmaxillofacial and","Similar"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p10-t0","doc_id":"K222745","page_num":10,"bbox":[54.31,77.34,584.45,701.28],"n_rows":11,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","","Service","(Reference","Comparison"],["","(Proposed Device)","","",""],["","","(Predicate","Device)",""],["","","","",""],["","","Device)","",""],["","with the assistance\nof the DICOM\nimages\nCommunication with\nthe surgical team to\ndiscuss the surgical\ntreatment plan in\nconjunction with\nDICOM images\nCommunication with\nthe patient to discuss\nthe surgical\ntreatment plan in\nconjunction with\nDICOM images\nEducation tool for\nsurgical planning.\nThe 3D printed\nphysical model can\nbe used for surgical\nplanning in the\nfollowing\napplications:\northopedics and\ntrauma, maxillofacial,\nand cardiovascular\nsurgery.","diagnostic\npurposes in the\nfield of\northopedic,\nmaxillofacial and\ncardiovascular\napplications.\nAxial3D Cloud\nSegmentation\nService should\nbe used in\nconjunction with\nother diagnostic\ntools and expert\nclinical judgment.","cardiovascular\napplications.\nMimics inPrint\nshould be used in\nconjunction with\nother diagnostic\ntools and expert\nclinical\njudgement.",""],["Method of\nUse","Used in conjunction\nwith other diagnostic\ntools and expert\nclinical judgement.","Used in\nconjunction with\nother diagnostic\ntools and expert\nclinical\njudgement.","Used in\nconjunction with\nother diagnostic\ntools and expert\nclinical\njudgement.","Equivalent"],["Environment","Hospital","Hospital","Hospital","Equivalent"],["OTC or\nPrescription\nDevice","Prescription Use","Prescription Use","Prescription Use","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p11-t0","doc_id":"K222745","page_num":11,"bbox":[54.34,77.34,584.42,237.72],"n_rows":9,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","","Service","(Reference","Comparison"],["","(Proposed Device)","","",""],["","","(Predicate","Device)",""],["","","","",""],["","","Device)","",""],["Level of\nConcern","Moderate","Moderate","Moderate","Equivalent"],["V&V","Complies with FDA\nGuidance\nRequirement","Complies with\nFDA Guidance\nRequirement","Complies with\nFDA Guidance\nRequirement","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p12-t0","doc_id":"K222745","page_num":12,"bbox":[54.29,77.34,584.47,687.0],"n_rows":12,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","(Proposed","Service","(Reference","Comparison"],["","Device)","(Predicate","Device)",""],["","","Device)","",""],["","","","","substantial\nequivalence\nas the output\nof the\nproposed\ndevice and\npredicate\ndevices is\nequivalent."],["Supported\nModalities","CT and CTA","CT","CT, MRI, X-ray","The proposed\ndevice uses a\nsubset of the\npredicate\ndevice image\nmodalities"],["Image\nregistration","Yes","Yes","Yes","Equivalent"],["Segmentation\nFeatures","A combination of\nautomated tools\nwith smart editing\ntools","A combination of\nautomated tools\nwith smart editing\ntools","Combination of\nautomated tools\nwith smart editing\ntools","Equivalent"],["View\nManipulation\nand Volume\nRendering","Yes","Yes","Yes","Equivalent"],["Regions and\nVolumes of\nInterest (ROI)","Orthopedics /\nTrauma\nCardiovascular\nCranio-\nMaxillofacial","Orthopedics /\nTrauma\nCardiovascular\nCranio-\nMaxillofacial","Orthopedics /\nTrauma\nCardiovascular\nCranio-Maxillofacial","Equivalent"],["Region/volume\nof interest\nmeasurements\nand size\nmeasurements","Yes","Yes","Yes","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p13-t0","doc_id":"K222745","page_num":13,"bbox":[54.36,77.34,584.4,189.84],"n_rows":6,"n_cols":5,"columns":["","","Axial3D Cloud","",""],"rows":[["","","Axial3D Cloud","",""],["","Axial3D Insight","Segmentation","Mimics InPrint",""],["Attribute","(Proposed","Service","(Reference","Comparison"],["","Device)","(Predicate","Device)",""],["","","Device)","",""],["Region/Volume\nQuantification","Yes","Yes","Yes","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p14-t0","doc_id":"K222745","page_num":14,"bbox":[54.43,192.0,585.21,416.14],"n_rows":17,"n_cols":5,"columns":["","Cardiac","Neuro","Ortho CT","Trauma CT"],"rows":[["","Cardiac","Neuro","Ortho CT","Trauma CT"],["","","","",""],["","CT/CTa","CT/CTa*","",""],["","","","",""],["Number of Images","4,838","4,041","10,857","19,134"],["Used for Validation","","","",""],["Slice Spacing Range","0.4 - 0.8","0.44 - 1.0","0.3 - 2.0","0.2 - 2.0"],["(Min, Max [mm])","","","",""],["","","","",""],["Slice Spacing","0.54","0.63","0.79","0.76"],["Average","","","",""],["[mm]","","","",""],["Pixel Size Range","0.23 - 0.78","0.34 - 0.70","0.18 - 0.98","0.22 - 0.98"],["(Min, Max [mm])","","","",""],["Pixel Size Average","0.46","0.51","0.44","0. 51"],["[mm]","","","",""],["","","","",""]],"caption_candidate":"Table 5-4 – Software Validation Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p14-t1","doc_id":"K222745","page_num":14,"bbox":[54.43,509.4,580.44,706.08],"n_rows":3,"n_cols":2,"columns":["Manufacturer","Model"],"rows":[["Manufacturer","Model"],["GE Medical Systems","Lightspeed Pro 16\nLightspeed Pro 32\nRevolution CT\nOptima CT660\nDiscovery CT750 HD"],["Siemens","SOMATOM Definition Flash\nSOMATOM Definition Edge\nSOMATOM Definition AS\nSOMATOM Definition AS+\nSOMATOM Perspective"]],"caption_candidate":"Table 5-5 – Imaging scanner manufacturers and models used for the validation datasets","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222745-p15-t0","doc_id":"K222745","page_num":15,"bbox":[54.58,77.82,580.46,292.2],"n_rows":4,"n_cols":2,"columns":["Manufacturer","Model"],"rows":[["Manufacturer","Model"],["","SOMATOM Force\nSensation 16\nAXIOM-Artis\nEmotion 16"],["Phillips","IQON Spectral CT\niCT 128\niCT 256\nIngenuity Core 128\nBrilliance 62"],["Toshiba","Aquillon PRIME\nAquillon PRIME SP"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222746-p6-t0","doc_id":"K222746","page_num":6,"bbox":[90.96,98.52,543.96,665.4],"n_rows":12,"n_cols":3,"columns":["Device","Overjet Caries Assist\n(Predicate)","Overjet Caries Assist\n(Proposed)"],"rows":[["Device","Overjet Caries Assist\n(Predicate)","Overjet Caries Assist\n(Proposed)"],["510k","K212519","TBD"],["Regulation No /\nDescription","CFR 892.2070\nMedical image analyzer","CFR 892.2070\nMedical image analyzer"],["Indications","The Overjet Caries Assist is a\nradiological, automated, concurrent\nread, computer-assisted detection\nsoftware intended to aid in the\ndetection and segmentation of caries\non bitewing radiographs. The device\nprovides additional information for\nthe dentist to use in their diagnosis of\na tooth surface suspected of being\ncarious. The device is not intended as\na replacement for a complete\ndentist’s review or their clinical\njudgment that takes into account\nother relevant information from the\nimage, patient history, or actual in\nvivo clinical assessment.","Overjet Caries Assist (OCA) is a\nradiological, automated, concurrent read,\ncomputer-assisted detection (CADe)\nsoftware intended to aid in the detection\nand segmentation of caries on bitewing\nand periapical radiographs. The\ndevice provides additional information\nfor the dentist to use in their diagnosis\nof a tooth surface suspected of being\ncarious. The device is not intended as a\nreplacement for a complete dentist’s\nreview or their clinical judgment that\ntakes into account other relevant\ninformation from the image, patient\nhistory, or actual in vivo clinical\nassessment."],["Type of CAD","CADe","CADe"],["End User","Dentist","Dentist"],["Patient Population","Patients requiring dental services, all\nsexes, 18 years of age or older","Patients requiring dental services, all\nsexes, 12 years of age or older with\npermanent teeth"],["Platform","Web - Edge, Chrome, Firefox","Web - Edge, Chrome, Firefox"],["OS","Any","Any"],["User Interface","Mouse, Keyboard, Trackpad","Mouse, Keyboard, Trackpad"],["Image Input Sources","Images imported from the\nradiographic device, or from the\npractice management system, from\nCarestream or Schick sensors.","Images imported from the radiographic\ndevice, or from the practice management\nsystem from multiple sensor\nmanufacturers"],["Image format","jpg, png, eop, jif, dicom","jpg, png, eop, tiff, dicom"]],"caption_candidate":"10. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222746-p7-t0","doc_id":"K222746","page_num":7,"bbox":[57.48,82.08,510.48,457.56],"n_rows":6,"n_cols":3,"columns":["Device","Overjet Caries Assist\n(Predicate)","Overjet Caries Assist\n(Proposed)"],"rows":[["Device","Overjet Caries Assist\n(Predicate)","Overjet Caries Assist\n(Proposed)"],["Processing\nArchitecture","Three layers:\n1 - The Network layer works\nwith the practice PACS or EMR\nto transmit the image and meta-\ndata to Overjet.\n2 - The decision layer processes\nthe image to ensure it is the correct\ndata type, and then annotates it via\nthe algorithm\n3 - The presentation layer displays\nthe annotated image in a non-\ndiagnostic viewer. The dentist can\nfilter, display, hide, create and edit\nthe annotations presented.","Three layers:\n1 - The Network layer works\nwith the practice PACS or EMR to\ntransmit the image and meta-data to\nOverjet.\n2 - The decision layer processes the\nimage to ensure it is the correct data\ntype, and then annotates it via the\nalgorithm\n3 - The presentation layer displays\nthe annotated image in a non-diagnostic\nviewer. The dentist can filter, display,\nhide, create and edit the annotations\npresented."],["Data Source","Digital files of bitewing radiographs\nwhose longer edge is greater than 500\npixel resolution.","Digital files of bitewing and periapical\nradiographs whose longer edge is greater\nthan 500 pixel resolution."],["Output","Caries detection and segmentation on\nradiograph resulting in outline of\nsuspected caries","Caries detection and segmentation on\nradiograph resulting in outline or fill\nof suspected caries"],["Performance Testing","Increase in dentist’s sensitivity of\ngreater than 15%","Increase in dentist’s sensitivity of greater\nthan 15%"],["Level of Concern","Moderate","Moderate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p5-t0","doc_id":"K222755","page_num":5,"bbox":[121.94,347.93,553.68,700.3],"n_rows":8,"n_cols":4,"columns":["ITEM","This submission\nuMR 680","Predicate Device\nuMR 570","Remark"],"rows":[["ITEM","This submission\nuMR 680","Predicate Device\nuMR 570","Remark"],["General","","",""],["Product Code","LNH","LNH","Same"],["Regulation\nNo.","21 CFR 892.1000","21 CFR 892.1000","Same"],["Class","II","II","Same"],["Indications\nFor Use","The uMR 680 system is indicated\nfor use as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse,\ncoronal, and oblique cross\nsectional images, and\nspectroscopic images, and that\ndisplay internal anatomical\nstructure and/or function of the\nhead, body and extremities.\nThese images and the physical\nparameters derived from the\nimages when interpreted by a\ntrained physician yield\ninformation that may assist the\ndiagnosis. Contrast agents may be\nused depending on the region of\ninterest of the scan.","The uMR 570 system is indicated\nfor use as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse,\ncoronal, and oblique cross\nsectional images, and\nspectroscopic images, and that\ndisplay internal anatomical\nstructure and/or function of the\nhead, body and extremities.\nThese images and the physical\nparameters derived from the\nimages when interpreted by a\ntrained physician yield\ninformation that may assist the\ndiagnosis. Contrast agents may be\nused depending on the region of\ninterest of the scan.","Same"],["Magnet system","","",""],["Field Strength","1.5 Tesla","1.5 Tesla","Same"]],"caption_candidate":"Table 1 Comparison of Hardware configuration","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p6-t0","doc_id":"K222755","page_num":6,"bbox":[113.18,40.23,532.66,738.42],"n_rows":75,"n_cols":9,"columns":["Sha","nghai United Imaging","Healthcare Co., Ltd.","","","","","",""],"rows":[["Sha","nghai United Imaging","Healthcare Co., Ltd.","","","","","",""],["Tel:","+86 (21) 67076888","Fax：+86 (21) 67076","8","89","","","",""],["www",".united-imaging.com","","","","","","",""],["","","","","","","","",""],["","","This sub","m","ission","Predicate","","Device",""],["","","","","","","","",""],["","ITEM","","","","","","","Rem"],["","","uMR","6","80","uMR","5","70",""],["","Type of","","","","","","",""],["","","","","","","","",""],["","","Superconducting","","","Superconducting","","","Same"],["","Magnet","","","","","","",""],["","Patient-","","","","","","",""],["","accessible","","","","","","",""],["","","","","","","","",""],["","","70cm","","","70cm","","","Same"],["","bore","","","","","","",""],["","dimensions","","","","","","",""],["","Type of","Actively shielded,","","OIS","Actively shielded,","O","IS",""],["","","","","","","","",""],["","","","","","","","","Same"],["","Shielding","technology","","","technology","","",""],["","","1.40ppm @ 50cm","D","SV","1.40ppm @ 50cm","D","SV",""],["","","0.90ppm @ 45cm","D","SV","0.90ppm @ 45cm","D","SV",""],["","Magnet","0.45ppm @ 40cm","D","SV","0.72ppm @ 40cm","D","SV",""],["","","","","","","","",""],["","","","","","","","","Note"],["","Homogeneity","0.190ppm @ 30cm","","DSV","0.420ppm @ 30cm","","DSV",""],["","","0.120ppm @ 20cm","","DSV","0.240ppm @ 20cm","","DSV",""],["","","0.040ppm @ 10cm","","DSV","0.040ppm @ 10cm","","DSV",""],["","","","","","","","",""],["","Gradient system","","","","","","",""],["","","","","","","","",""],["","Max gradient","","","","","","",""],["","","","","","","","",""],["","","45mT/m","","","45mT/m","","","Same"],["","amplitude","","","","","","",""],["","Max slew rate","200T/m/s","","","200T/m/s","","","Same"],["","Shielding","active","","","active","","","Same"],["","Cooling","water","","","water","","","Same"],["","","","","","","","",""],["","RF system","","","","","","",""],["","","","","","","","",""],["","Resonant","","","","","","",""],["","","","","","","","",""],["","","63.87 MHz","","","63.87 MHz","","","Same"],["","frequencies","","","","","","",""],["","Number of","","","","","","",""],["","transmit","1","","","1","","","Same"],["","channels","","","","","","",""],["","Number of","Up to 96","","","Up to 48","","",""],["","receive","","","","","","","Note"],["","channels","","","","","","",""],["","Amplifier","18 kW","","","20 kW","","","Note"],["","peak power","","","","","","",""],["","per channel","","","","","","",""],["","","","","","","","",""],["","RF Coils","","","","","","",""],["","","","","","","","",""],["","Head & Neck","No","","","Yes","","","Note"],["","Coil -16","","","","","","",""],["","Head & Neck","Yes","","","No","","","Note"],["","Coil -24","","","","","","",""],["","Spine Coil -","No","","","Yes","","","Note"],["","24","","","","","","",""],["","Spine Coil -","Yes","","","No","","","Note"],["","32","","","","","","",""],["","Body Array","No","","","Yes","","","Note"],["","Coil - 6","","","","","","",""],["","Body Array","Yes","","","Yes","","","Same"],["","Coil - 12","","","","","","",""],["","Body Array","Yes","","","No","","","Note"],["","Coil - 24","","","","","","",""],["","","","","","","","",""],["","","","","Page 3 of 1","1","","",""]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K222755-p7-t0","doc_id":"K222755","page_num":7,"bbox":[113.18,40.23,532.66,704.02],"n_rows":59,"n_cols":5,"columns":["Sha","nghai United Imaging","Healthcare Co., Ltd.","",""],"rows":[["Sha","nghai United Imaging","Healthcare Co., Ltd.","",""],["Tel:","+86 (21) 67076888","Fax：+86 (21) 67076889","",""],["www",".united-imaging.com","","",""],["","","","",""],["","","This submission","Predicate Device",""],["","","","",""],["","ITEM","","","Rem"],["","","uMR 680","uMR 570",""],["","Breast Coil -","Yes","Yes","Same"],["","10","","",""],["","Knee Coil -","Yes","Yes","Same"],["","12","","",""],["","Lower","Yes","Yes","Same"],["","Extremity","","",""],["","Coil - 24","","",""],["","Shoulder Coil","Yes","Yes","Same"],["","- 12","","",""],["","Small Loop","Yes","Yes","Same"],["","Coil","","",""],["","Wrist Coil -","Yes","Yes","Same"],["","12","","",""],["","Cardiac Coil -","Yes","Yes","Same"],["","24","","",""],["","Foot & Ankle","Yes","Yes","Same"],["","Coil - 24","","",""],["","Temporoman","Yes","Yes","Same"],["","dibular Joint","","",""],["","Coil - 4","","",""],["","Head Coil -","No","Yes","Note"],["","24","","",""],["","Head Coil -","No","Yes","Note"],["","12","","",""],["","Carotid Coil -","Yes","Yes","Same"],["","8","","",""],["","Flex Coil","No","Yes","Note"],["","Large - 4","","",""],["","Flex Coil","Yes","No","Note"],["","Large - 8","","",""],["","Flex Coil","No","Yes","Note"],["","Small - 4","","",""],["","Flex Coil","Yes","No","Note"],["","Small - 8","","",""],["","Infant Coil-24","Yes","No","Note"],["","SuperFlex","Yes","No","Note"],["","Large - 12","","",""],["","SuperFlex","Yes","No","Note"],["","Small - 12","","",""],["","SuperFlex","Yes","No","Note"],["","Body - 24","","",""],["","","","",""],["","Patient table","","",""],["","","","",""],["","","Patient Table:","Patient Table:","Same"],["","Maximum","250 kg","250 kg",""],["","supported","","",""],["","patient weight","Dockable Patient Table:","No","Note"],["","","310kg","",""],["","","","",""],["","Accessories","","",""]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K222755-p8-t0","doc_id":"K222755","page_num":8,"bbox":[121.94,78.84,554.3,145.34],"n_rows":2,"n_cols":4,"columns":["ITEM","This submission\nuMR 680","Predicate Device\nuMR 570","Remark"],"rows":[["ITEM","This submission\nuMR 680","Predicate Device\nuMR 570","Remark"],["Vital Signal\nGating","Support\nECG/Respiratory/Pulse signal\ntriggering the scan","Support\nECG/Respiratory/Pulse\nsignal triggering the scan","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p8-t1","doc_id":"K222755","page_num":8,"bbox":[121.94,159.62,554.3,709.54],"n_rows":13,"n_cols":2,"columns":["Note 1","The homogeneity of the magnet is equal or better at typical DSVs thus the clinical\nscanning of the proposed device is not limited compared to the predicate device."],"rows":[["Note 1","The homogeneity of the magnet is equal or better at typical DSVs thus the clinical\nscanning of the proposed device is not limited compared to the predicate device."],["Note 2","More receive channels allow the proposed device to use new high-channel count and\nbigger coverage receive coils."],["Note 3","The RF Amplifier power is just one of the influence factors to affect the B1 field,\nother influence factors such as efficiency of transmitting coil, damping of\ntransmitting chain, the distance between coil and target location will also affect the\nintensity of B1 field, and the intensity of B1 field can be adjusted by different\nsequences. Generally the target B1 field is achieved by system calibration\nprocedures and the required RF power is always less than the maximum RF\nAmplifier power output, so this difference from predicate device will not affect the\nsystem effectiveness, and the system safety is explained in device description and\nverified by the third party safety report."],["Note 4","Compared to the predicate device, the proposed device removes Head & Neck Coil -\n16 but adds Head & Neck Coil -24. The intended use of Head & Neck Coil -24 is\nequivalent to previously cleared Head & Neck Coil -16. More coil elements in the\nnew coil allow larger coverage for bigger patient."],["Note 5","The intended use of Head & Neck Coil -24 is equivalent to previously cleared Head\n& Neck Coil -16. More coil elements in the new coil allow larger coverage for\nbigger patient."],["Note 6","Compared to the predicate device, the proposed device removes Spine Coil - 24 but\nadds Spine Coil - 32. The intended use of Spine Coil - 32 is equivalent to previously\ncleared Spine Coil - 24. More coil elements in the new coil allow larger coverage for\nbigger patient."],["Note 7","The intended use of Spine Coil - 32 is equivalent to previously cleared Spine Coil -\n24. More coil elements in the new coil allow larger coverage for bigger patient."],["Note 8","Compared to the predicate device, the proposed device removes Body Array Coil-6\nbut adds Body Array Coil-24. The intended use of Body Array Coil-24 is equivalent\nto previously cleared Body Array Coil-6. More coil elements in the new coil allow\nlarger coverage for bigger patient."],["Note 9","Compared to the predicate device, the proposed device removes Head Coil – 12 and\nHead Coil – 24. The intended use of Head Coil can be overridden by Head & Neck\nCoil -24, so this difference from predicate device will not affect the system\neffectiveness."],["Note 10","Compared to the predicate device, the proposed device removes Flex Coil Large - 4\nbut adds Flex Coil Large - 8. The intended use of Flex Coil Large - 8 is equivalent to\npreviously cleared Flex Coil Large - 4. More coil elements in the new coil allow\nlarger coverage for bigger patient."],["Note 11","Compared to the predicate device, the proposed device removes Flex Coil Small - 4\nbut adds Flex Coil Small - 8. The intended use of Flex Coil Small - 8 is equivalent to\npreviously cleared Flex Coil Small - 4. More coil elements in the new coil allow\nlarger coverage for bigger patient."],["Note 12","The proposed device adds Infant Coil-24 to facilitate the exam of infant."],["Note 13","The intended use of SuperFlex Large - 12 is essentially identical to previously\ncleared Flex Coil Large - 8. The differences are the number of channels of the coil"]],"caption_candidate":"triggering the scan signal triggering the scan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p9-t0","doc_id":"K222755","page_num":9,"bbox":[121.94,78.84,554.4,262.01],"n_rows":4,"n_cols":2,"columns":["","and the material used on the surface of the coil. More coil elements in the new coil\ncan better cover the scanning parts and the flexible material is beneficial to wrap the\nscanning parts."],"rows":[["","and the material used on the surface of the coil. More coil elements in the new coil\ncan better cover the scanning parts and the flexible material is beneficial to wrap the\nscanning parts."],["Note 14","The intended use of SuperFlex Small - 12 is essentially identical to previously\ncleared Flex Coil Small - 8. The differences are the number of channels of the coil\nand the material used on the surface of the coil. More coil elements in the new coil\ncan better cover the scanning parts and the flexible material is beneficial to wrap the\nscanning parts."],["Note 15","The intended use of SuperFlex Body - 24 is essentially identical to previously\ncleared Body Array Coil - 12. The differences are the number of channels of the coil\nand the material used on the surface of the coil. More coil elements in the new coil\ncan better cover the scanning parts and the flexible material is beneficial to wrap the\nscanning parts."],["Note 16","The proposed device adds Dockable Patient Table to facilitate patient transfer and\nhave a higher load capacity."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p9-t1","doc_id":"K222755","page_num":9,"bbox":[126.02,317.69,537.48,714.7],"n_rows":10,"n_cols":4,"columns":["ITEM","This\nsubmission\nuMR 680","Predicate\nDevice\nuMR 570","Remark"],"rows":[["ITEM","This\nsubmission\nuMR 680","Predicate\nDevice\nuMR 570","Remark"],["Imaging Features","","",""],["Non-uniformity\nCorrection","Yes","Yes","Non-uniformity correction is used for\ncorrecting image intensity non-\nuniformity caused by transmit field or\nreceive field."],["Distortion Correction","Yes","Yes","Distortion correction is used for\ncorrecting the distortion caused by the\nnon-linear gradient field in image\ndomain."],["Image Filter","Yes","Yes","Image filter is used for denoising,\nenhancement and edge smoothness."],["WFI","Yes","Yes","WFI is short for water fat imaging and\nseparates water and fat signal according\nto chemical shift effect."],["SWI","Yes","Yes","Susceptibility Weighted Imaging (SWI)\nuses high-pass filter to generate local\nphase map, then it is multiplied onto the\nmagnitude data to generate SWI image."],["PC","Yes","Yes","PC combines two images with flow\nencoding and without flow encoding to\nachieve angiography imaging."],["GETI","Yes","Yes","GETI is short for gradient echo train\nimaging. It combines multi-echo images\nby sum-of-square to generate hybrid\nT2* contrast."],["ADC","Yes","Yes","Apparent diffusion coefficient (ADC)\nfits logarithm-linear least squares model\nto represent water molecular diffusion\nmotion by DWI technique."]],"caption_candidate":"Table 2 Comparison of the new Application Software Features","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p10-t0","doc_id":"K222755","page_num":10,"bbox":[126.02,78.84,537.48,712.78],"n_rows":12,"n_cols":4,"columns":["FACT","Yes","Yes","FACT is short for fat analysis and\ncalculation technique and substantially\nequivalent to WFI. It not only separates\nwater and fat signal and quantifies fat\nfraction and R2* mapping according to\nchemical shift effect and T2* effect."],"rows":[["FACT","Yes","Yes","FACT is short for fat analysis and\ncalculation technique and substantially\nequivalent to WFI. It not only separates\nwater and fat signal and quantifies fat\nfraction and R2* mapping according to\nchemical shift effect and T2* effect."],["PSIR","Yes","Yes","PSIR is substantially equivalent to FFT\nreconstruction and acquire real image\nfrom two TI(time-inversion) images\nwhich is benefit for more stable\ncontrast."],["cDWI","Yes","Yes","cDWI is substantially equivalent to\nDWI and generates fitting b-value from\nmultiple acquisition b values."],["Inline T1/T2* Map","Yes","Yes","Inline T1/T2* Map is substantially\nequivalent to T1/T2* Map processed by\npost-processing module. The map result\ndisplays inline without extra operation\nby post-processing module."],["Inline T2 Map","Yes","No","Inline T2 Map is substantially\nequivalent to T2 Map processed by\npost-processing module. The map result\ndisplays inline without extra operation\nby post-processing module."],["SWI+","Yes","Yes","SWI+ is substantially equivalent to SWI\nand acquires multi-echo to achieve more\ninformation than SWI."],["Arterial Spin\nLabeling (ASL)","Yes","Yes","ASL is substantially equivalent to FSE\nand uses extra arterial spin labeling\npreparation and imaging processing for\ncerebral blood flow (CBF) imaging\nwithout contrast agent."],["Flow Quantification\n(FQ)","Yes","No","FQ is substantially equivalent to GRE\nand uses extra flow encoding and\nimaging processing for flow\nquantification."],["Cardiac T1 Mapping","Yes","No","Cardiac T1 mapping is substantially\nequivalent to GRE and uses multiple TI\nacquisitions with IR preparation and\nimaging processing for cardiac T1\nmapping."],["Cardiac T2 Mapping","Yes","No","Cardiac T2 mapping is substantially\nequivalent to GRE and uses multiple\nT2-prep duration preparation\nacquisitions and imaging processing for\ncardiac T2 mapping."],["Cardiac T2*\nMapping","Yes","No","Cardiac T2* mapping is substantially\nequivalent to GRE and uses multiple TE\nacquisitions and imaging processing for\ncardiac T2* mapping."],["DeepRecon","Yes","No","DeepRecon is a deep-learning based\nimage processing algorithm for image"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p11-t0","doc_id":"K222755","page_num":11,"bbox":[126.01,78.84,537.48,537.79],"n_rows":11,"n_cols":4,"columns":["","","","de-noising and K-space-interpolation\nbased image super-resolution."],"rows":[["","","","de-noising and K-space-interpolation\nbased image super-resolution."],["QScan","Yes","No","QScan is short for quiet scan. It doesn’t\nchange the sequence mechanism and\nonly optimizes gradient waveform to\nreduce MR scan acoustic noise."],["Workflow Features","","",""],["EasyScan","Yes","No","EasyScan feature allows automatic slice\npositioning for Head, cardiac, c-spine, t-\nspine, l-spine, shoulder, abdomen and\nknee imaging. The positioning can also\nbe adjusted manually by user. The final\npositioning effect is equivalent to\nmanual operation without EasyScan\nfeature."],["Function","","",""],["Remote Assistance","Yes","No","Remote Assistance intends for remote\nsupport and service."],["MR conditional\nimplant mode","Yes","No","In MR conditional implant mode，user\ncan set the safety conditions of the MR\nconditional implant, and uMR 680\nsystem ensure the scanning complies\nwith the conditions."],["Spectroscopy Sequences","","",""],["Liver Spectroscopy","Yes","No","Liver spectroscopy is substantially\nequivalent to Spectroscopy and uses\nmulti-echo acquisition and post-\nprocessing instead of single echo for fat\nquantification of liver."],["Prostate\nSpectroscopy","Yes","No","Prostate spectroscopy is substantially\nequivalent to Spectroscopy and uses\ncharacteristic metabolites detection post\nprocessing for prostate spectroscopy."],["Breast Spectroscopy","Yes","No","Breast spectroscopy is substantially\nequivalent to Spectroscopy and uses\ncharacteristic metabolites detection post\nprocessing for breast spectroscopy."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p13-t0","doc_id":"K222755","page_num":13,"bbox":[165.45,204.5,480.03,506.47],"n_rows":21,"n_cols":6,"columns":["","Subjects' Characteristics","","","Total(N=68)",""],"rows":[["","Subjects' Characteristics","","","Total(N=68)",""],["","Gender","","","",""],["","Male","","","24",""],["","Female","","","44",""],["","Age","","","",""],["","18-29","","","11",""],["","30-44","","","14",""],["","45-64","","","24",""],["",">=65","","","19",""],["","Ethnicity","","","",""],["","White","","","26",""],["","Black","","","17",""],["","Asian","","","19",""],["","Hispanic (of any race)","","","6",""],["","Body Mass Index (BMI)","","","",""],["","Underweight (<18.5)","","","2",""],["Healthy weight (18.5-24.9)","","","17","",""],["Overweight (25.0-29.9)","","","25","",""],["Class1 Obesity (30.0-34.9)","","","14","",""],["Class2 Obesity (35-39.9)","","","5","",""],["Class3 Obesity (>=40)","","","5","",""]],"caption_candidate":"Table a. DeepRecon American Volunteers' Demographic Distribution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222755-p14-t0","doc_id":"K222755","page_num":14,"bbox":[108.02,92.66,518.98,368.21],"n_rows":7,"n_cols":4,"columns":["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],"rows":[["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],["Image SNR","DeepRecon images achieve higher\nSNR compared to the images\nwithout DeepRecon (NADR)","NADR: 137.03","PASS"],["","","DeepRecon:\n186.87",""],["Image\nUniformity","Uniformity difference between\nDeepRecon images and NADR\nimages under 5%","0.03%","PASS"],["Image\nResolution","DeepRecon images achieve 10% or\nhigher resolution compared to the\nNADR images","15.57%","PASS"],["Image\nContrast","Intensity difference between\nDeepRecon images and NADR\nimages under 5%","1.0%","PASS"],["Structure\nMeasurement","Measurements on NADR and\nDeepRecon images of same\nstructures, measurement difference\nunder 5%","0%","PASS"]],"caption_candidate":"Table b. The performance evaluation report criteria of DeepRecon","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p4-t0","doc_id":"K222803","page_num":4,"bbox":[72.0,726.12,539.76,750.0],"n_rows":3,"n_cols":6,"columns":["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","","Baltimore, MD 21205 USA",""],["","","","","","/7"]],"caption_candidate":"targets, and organs at risk (OAR);","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p5-t0","doc_id":"K222803","page_num":5,"bbox":[72.0,726.12,539.76,750.0],"n_rows":3,"n_cols":6,"columns":["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","","Baltimore, MD 21205 USA",""],["","","","","","/7"]],"caption_candidate":"oncologists, and dosimetrists). This device is for prescription use by order of a physician.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p6-t0","doc_id":"K222803","page_num":6,"bbox":[72.23,319.32,539.75,701.4],"n_rows":7,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["Device Name","Oncospace","Oncospace","Identical"],["510(k) Owner","Oncospace, Inc.","Oncospace, Inc.",""],["510(k) Number","K222803","K202284",""],["Product Code","MUJ","MUJ","Identical"],["Product Name","System, Planning, Radiation\nTherapy Treatment","System, Planning, Radiation\nTherapy Treatment","Identical"],["Intended Use","Oncospace is used to\nconfigure and review\nradiotherapy treatment plans\nfor a patient with malignant or\nbenign disease in the prostate,\nhead, and neck regions. It\nallows for set up of\nradiotherapy treatment\nprotocols, association of a\npotential treatment plan with\nthe protocol(s), submission of\na dose prescription and\nachievable dosimetric goals to\na treatment planning system,\nand review of the treatment\nplan. It is intended for use by\nqualified, trained radiation\ntherapy professionals (such as\nmedical physicists,\noncologists, and dosimetrists).","Oncospace is used to\nconfigure and review\nradiotherapy treatment plans\nfor a patient with malignant or\nbenign disease in the prostate,\nthoracic, pancreas, or head &\nneck regions. It allows for set\nup of radiotherapy treatment\nprotocols, association of a\npotential treatment plan with\nthe protocol(s), submission of\na dose prescription and\nachievable dosimetric goals to\na treatment planning system,\nand review of the treatment\nplan. It is intended for use by\nqualified, trained radiation\ntherapy professionals (such as\nmedical physicists,\noncologists, and dosimetrists).","Removed\nthoracic and\npancreas since\nplan-matching\nmethodology\nwas removed.\nProstate, head,\nand neck use the\nML models."]],"caption_candidate":"prior to clinical use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p6-t1","doc_id":"K222803","page_num":6,"bbox":[72.23,726.12,539.75,750.0],"n_rows":3,"n_cols":5,"columns":["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","Baltimore, MD 21205 USA",""],["","","","","/7"]],"caption_candidate":"oncologists, and dosimetrists). oncologists, and dosimetrists).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p7-t0","doc_id":"K222803","page_num":7,"bbox":[72.23,152.28,539.75,698.4],"n_rows":12,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["","This device is for prescription\nuse by order of a physician.","This device is for prescription\nuse by order of a physician.",""],["Operating\nSystem","Windows/Web-browser","Windows/Web-browser","Identical"],["Platform","Client-Server (Clinic-provided\nclient machines, cloud\nWindows servers controlled\nby Oncospace)","Client-Server (Clinic-provided\nclient machines, cloud\nWindows servers controlled\nby Oncospace)","Identical"],["DICOM-RT\nCompliant","Yes","Yes","Identical"],["Full Treatment\nPlanning\nSystem","No","No","Identical"],["Connected to or\nControlling of\nRadiation\nDelivery\nDevices","No","No","Identical"],["Typical Users","Medical professionals,\nincluding but not limited to,\nradiation oncologists, medical\nphysicists or physicians.","Medical professionals,\nincluding but not limited to,\nradiation oncologists, medical\nphysicists or physicians.","Identical"],["Patient\nPopulation","There are no demographic,\nregional, or cultural limitations\nfor patients. It is up to the user\nto determine if the system can\nbe used for a patient.","There are no demographic,\nregional, or cultural limitations\nfor patients. It is up to the user\nto determine if the system can\nbe used for a patient.","Identical"],["Environment","The system can be used in a\nhospital environment or in a\ndoctor’s office.","The system can be used in a\nhospital environment or in a\ndoctor’s office.","Identical"],["JPEG image\nsupport","Yes","Yes","Identical"],["Import\nTreatment\nPlans","Yes. Import existing plans\nfrom third-party systems to\ncompare dose objectives\nagainst templates.","Yes. Import existing plans\nfrom third-party systems to\ncompare dose objectives\nagainst templates.","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p7-t1","doc_id":"K222803","page_num":7,"bbox":[72.23,726.12,539.75,750.0],"n_rows":3,"n_cols":5,"columns":["","oncospace.com","","1812 Ashland Ave., Suite 100K\nBaltimore, MD 21205 USA",""],"rows":[["","oncospace.com","","1812 Ashland Ave., Suite 100K\nBaltimore, MD 21205 USA",""],["","info@oncospace.com","","",""],["","","","","/7"]],"caption_candidate":"against templates. against templates.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p8-t0","doc_id":"K222803","page_num":8,"bbox":[72.23,152.28,539.75,685.32],"n_rows":10,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["“Template”\nTreatment\nPlans","Yes. Factory-default plans\nwith dose goals exist and users\ncan configure a dose template.","Yes. Factory-default plans\nwith dose goals exist and users\ncan configure a dose template.","Identical"],["Automatic\nInitial Tumor\nSelection","Yes. Regions of interest are\nmatched as the study is opened\nin the device. Users can adjust\nor match to more available\nregions of interest.","Yes. Regions of interest are\nmatched as the study is opened\nin the device. Users can adjust\nor match to more available\nregions of interest.","Identical"],["Dose Objective\nComparison","Yes. Comparison can be done\nbetween more than one\nselected treatment plan. Dose\nis based on calculated dose\nand curated, gold-standard\ntreatment plans.","Yes. Comparison can be done\nbetween more than one\nselected treatment plan. Dose\nis based on calculated dose\nand curated, gold-standard\ntreatment plans.","Identical"],["Image Viewer\nCapabilities","Yes. Display, pan, zoom,\nscroll, windowing, viewport\nlayout.","Yes. Display, pan, zoom,\nscroll, windowing, viewport\nlayout.","Identical"],["Calculate and\nDisplay Isodose\nLines","Yes","Yes","Identical"],["Calculate and\nDisplay Dose\nVolume\nHistograms","Yes","Yes","Identical"],["Compare Dose\nfrom Multiple\nPlans","Yes","Yes","Identical"],["Dose\nSummation/\nTreatment-\nOver-Time\nData","Yes","Yes","Identical"],["Plan Review","Yes. Contains features for\nreview of isodose lines, review\nof DVHs, dose comparison\nand dose summation.","Yes. Contains features for\nreview of isodose lines, review\nof DVHs, dose comparison\nand dose summation.","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p8-t1","doc_id":"K222803","page_num":8,"bbox":[72.23,726.12,539.75,750.0],"n_rows":3,"n_cols":5,"columns":["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","Baltimore, MD 21205 USA",""],["","","","","/7"]],"caption_candidate":"and dose summation. and dose summation.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p9-t0","doc_id":"K222803","page_num":9,"bbox":[72.21,152.28,539.73,278.52],"n_rows":2,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["Export Plan\nInformation","Yes. Can export the selected\nplan for review and setup by a\ndosimetrist.\nOncospace does not export a\nfinal plan, it will not export to\na record-and-verify system.","Yes. Can export the selected\nplan for review and setup by a\ndosimetrist.\nOncospace does not export a\nfinal plan, it will not export to\na record-and-verify system.","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p9-t1","doc_id":"K222803","page_num":9,"bbox":[72.21,726.12,539.73,750.0],"n_rows":3,"n_cols":5,"columns":["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","Baltimore, MD 21205 USA",""],["","","","","/7"]],"caption_candidate":"glands, left and right cochlea, thyroid gland, and pharyngeal constrictor muscle(s). For the head","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222803-p10-t0","doc_id":"K222803","page_num":10,"bbox":[70.97,726.12,540.96,750.0],"n_rows":3,"n_cols":6,"columns":["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],"rows":[["","oncospace.com","","","1812 Ashland Ave., Suite 100K",""],["","info@oncospace.com","","","Baltimore, MD 21205 USA",""],["","","","","","/7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222819-p5-t0","doc_id":"K222819","page_num":5,"bbox":[112.82,67.68,594.0,230.34],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary Predicate:\nAquilion Lightning\n(TSX-036A/7) V10.2\nwith AiCE-i","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K201836","01/12/2021"],["Reference Predicate:\nAquilion Prime SP\n(TSX-303B/8) V10.2\nwith AiCE-i","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K192832","02/21/2020"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222819-p5-t1","doc_id":"K222819","page_num":5,"bbox":[112.82,607.76,580.44,720.66],"n_rows":5,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["","Device Name,","","","Aquilion Serve","","","Aquilion Lightning","","","",""],["","Model Number","","","(TSX-307A/1) V1.2 with AiCE-i","","","(TSX-036A/7) V10.2 with AiCE-i","","","",""],["","510(k) Number","","","This submission","","","K201836","","","",""],["Scan modes","","","Conventional scan (Axial Scan*)\nVolume, Dynamic volume scan\nHelical scan","","","Conventional scan (S&S, S&V)\nVolume, Dynamic volume scan\nHelical scan","","","*: S&V is not\nsupported\nS&S is called\n“Axial Scan”","",""]],"caption_candidate":"included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222819-p6-t0","doc_id":"K222819","page_num":6,"bbox":[112.52,55.22,580.46,731.46],"n_rows":11,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["","Device Name,","","","Aquilion Serve","","","Aquilion Lightning","","","",""],["","Model Number","","","(TSX-307A/1) V1.2 with AiCE-i","","","(TSX-036A/7) V10.2 with AiCE-i","","","",""],["","510(k) Number","","","This submission","","","K201836","","","",""],["Positioning Scan","","","Positioning:\nSingle\nDual\n3D Landmark Scan","","","Scanoscopy:\nScano\nDual Scano","","","","",""],["3D Landmark Scan","","","Available","","","Not Available","","","","",""],["Anatomical\nLandmark\nDetection","","","Available","","","Not Available","","","","",""],["Scan planning assist\nfunction*","","","Available","","","Not Available","","","*: If 3D Landmark\nScan is set in a\nscan protocol.","",""],["Scan slice thickness","","","[Conventional scan (Axial scan)]\n4-row scan: 0.5, 1, 2, 3, 4, 5, 8\nmm\n1-row scan: 1 mm\n[Volume, Dynamic volume scan]\n(80-row scan*: 0.5 mm)\n40-row scan: 0.5 mm\n[Helical scan]\n(80-row scan*: 0.5 mm)\n40-row scan: 0.5 mm and 1 mm\n20-row scan: 0.5 mm\n4-row scan: 0.5 mm\n[3D Landmark Scan]\n40-row scan: 1.0 mm","","","[Conventional scan (S&S, S&V)]\n4-row scan: 0.5, 1, 2, 3, 4, 5, 8,\n10 mm\n1-row scan: 1 mm\n[Volume, Dynamic volume scan]\n(80-row scan*: 0.5 mm)\n40-row scan: 0.5 mm and 1 mm\n4-row scan: 8 mm and 10 mm\n[Helical scan]\n(80-row scan*: 0.5 mm)\n40-row scan: 0.5 mm and 1 mm\n20-row scan: 0.5 mm and 1 mm\n4-row scan: 0.5 mm","","","*: Option","",""],["Image\nreconstruction time","","","Up to 30 images/s with AIDR 3D\n(0.033 s/image)\nUp to 50 images/s with AIDR 3D\n(0.02 s/image)*1\nUp to 70 images/s with AIDR 3D\n(0.014 s/image)*2\nUp to 100 images/s with AIDR 3D\n(0.01 s/image)*3\n(Depending on the scan and\nreconstruction conditions)","","","Up to 20 images/s with AIDR 3D\n(0.05 s/image)\nUp to 50 images/s with AIDR 3D\n(0.02 s/image) *2\n(Depending on the scan and\nreconstruction conditions)","","","*1: When the Fast\nscan kit (CGS-\n041A) is installed.\n*2: Option\nWhen the Fast\nImage\nReconstruction kit\n(CCFR-010A) is\ninstalled.\n*3: When the Fast\nImage\nReconstruction kit\n(CCFR-010A) and\nthe Fast scan kit\n(CGS-041A) are\ninstalled.","",""],["Flex e-Tilt","","","Available","","","Not Available","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222819-p7-t0","doc_id":"K222819","page_num":7,"bbox":[112.51,55.22,580.48,724.74],"n_rows":10,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["","Device Name,","","","Aquilion Serve","","","Aquilion Lightning","","","",""],["","Model Number","","","(TSX-307A/1) V1.2 with AiCE-i","","","(TSX-036A/7) V10.2 with AiCE-i","","","",""],["","510(k) Number","","","This submission","","","K201836","","","",""],["Gantry opening\ndiameter (aperture)","","","800 mm in diameter","","","780 mm in diameter","","","","",""],["Wedge filter types","","","Three (3) types\n･ Small\n･ Large\n･ SilverBeam Filter*","","","Two (2) types\n･ Small\n･ Large","","","*Previously\ncleared under\nK213504\n(TSX-306A)","",""],["Gantry internal\ncameras","","","Available","","","Not Available","","","Two cameras\nmounted inside\nthe system at a\n90-degree phase\ndifference.","",""],["Reconstruction\nfunctions","","","Identified as anatomical regions*","","","Identified as numbered\nfunctions","","","*Previously\ncleared under\nK213504\n(TSX-306A)","",""],["Noise reduction\nprocessing","","","Adaptive Iterative Dose\nReduction 3D (AIDR 3D)\nAIDR 3D Enhanced\nAdvanced Intelligent Clear-IQ\nEngine (AiCE)","","","Adaptive Iterative Dose\nReduction 3D (AIDR 3D)\nAIDR 3D Enhanced\nAdvanced Intelligent Clear-IQ\nEngine (AiCE)\nQuantum Denoising Software\n(QDS)","","","","",""],["NewUX Console*\nDisplay monitor\nUser Input\nData processor\nWindow width/level\nPreset windows\nWindow types\nROI shape available","","","Available\n27 inch (3840 x 2160)\nKeyboard and Control Pad\n(Performs scan operation and\ncontrols voice messages)\nCPU : 64-bit\nMemory size: 64 Gbyte or more\nControlled and continuously\nvariable using the mouse\n1/image\nLinear only\nPoint, Circular","","","Not Available\n19 inch (1280 x 1024)\nScan Keyboard\nCPU : 64-bit\nMemory size: 32 Gbyte or more\nControlled and continuously\nvariable using a speed-sensitive\nrotary encoder\n3/image\nLinear and non-linear (6 user-\nprogrammable), and double\nwindows\nPoint, square, free-form,\ncircular, polygon","","","*Previously\ncleared under\nK213504\n(TSX-306A)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222884-p7-t0","doc_id":"K222884","page_num":7,"bbox":[76.56,123.24,526.56,742.08],"n_rows":3,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison\nFeature","Avicenna CINA (K200855)","Rapid NCCT Stroke – Subject\nDevice"],["Indications\nfor Use","CINA is a radiological computer\naided triage and notification\nsoftware indicated for use in the\nanalysis of (1) non-enhanced head\nCT images and (2) CT\nangiographies of the head. The\ndevice is intended to assist hospital\nnetworks and trained radiologists in\nworkflow triage by flagging and\ncommunicating suspected positive\nfindings of (1) head CT images for\nIntracranial Hemorrhage (ICH) and\n(2) CT angiographies of the head\nfor large vessel occlusion (LVO).\nCINA uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected (1)\nICH or (2) LVO on a standalone\nWeb application in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH or LVO\nfindings. Notifications include\ncompressed preview images that\nare meant for informational\npurposes only, and are not intended\nfor diagnostic use beyond\nnotification. The device does not\nalter the original medical image,\nand it is not intended to be used as a\ndiagnostic device.\nThe results of CINA are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment to assist with\ntriage/prioritization of medical\nimages. Notified clinicians are\nultimately responsible for","Rapid NCCT Stroke is a\nradiological computer aided triage\nand notification software indicated\nfor use in the analysis of (1)\nnonenhanced head CT (NCCT)\nimages. The device is intended to\nassist hospital networks and trained\nclinicians in workflow triage by\nflagging and communicating\nsuspected positive findings of (1)\nhead CT images for Intracranial\nHemorrhage (ICH) and (2) NCCT\nlarge vessel occlusion (LVO) of the\nICA and MCA-M1.\nRapid NCCT Stroke uses an\nartificial intelligence algorithm to\nanalyze images and highlight cases\nwith detected (1) ICH or (2) NCCT\nLVO on the Rapid server on\npremise or in the cloud in parallel\nto the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for\ncases with suspected ICH or LVO\nfindings via PACS, email or mobile\ndevice. Notifications include\ncompressed preview images that\nare meant for informational\npurposes only, and are not intended\nfor diagnostic use beyond\nnotification.\nThe device does not alter the\noriginal medical image, and it is not\nintended to be used as a primary\ndiagnostic device. The results of\nRapid NCCT Stroke are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgment to assist with\ntriage/prioritization of medical"]],"caption_candidate":"features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222884-p8-t0","doc_id":"K222884","page_num":8,"bbox":[76.56,75.84,526.56,753.48],"n_rows":6,"n_cols":3,"columns":["","reviewing full images per the\nstandard of care.","images. Notified clinicians are\nultimately responsible for\nreviewing full images per the\nstandard of care. Rapid NCCT\nStroke is for Adults only.\nCautions:\n• All patients should get adequate\ncare for their symptoms including\nCTA or MRA and/or other\nappropriate care per the standard\nclinical practice, irrespective of the\ndevice output.\n• The device is not intended to be a\nrule-out device and for cases that\nhave been processed by the device\nwithout notification for “Suspected\nLVO” should not be viewed as\nindicating that LVO is excluded.\nAll cases should undergo CTA or\nMRA, per the standard stroke\nworkup.\nLimitations:\n• Rapid NCCT Stroke does not\nreplace the need for CTA in\nischemic stroke workup, it\nprovides workflow prioritization\nand notification only.\n• Rapid ICH has been shown to\nreliably identify hemorrhages of ≥\n0.4ml.\nContraindications/Exclusions/Cauti\nons:\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate.\n• Hemorrhagic Transformation,\nHematoma\n• Very thin or no Ventricles"],"rows":[["","reviewing full images per the\nstandard of care.","images. Notified clinicians are\nultimately responsible for\nreviewing full images per the\nstandard of care. Rapid NCCT\nStroke is for Adults only.\nCautions:\n• All patients should get adequate\ncare for their symptoms including\nCTA or MRA and/or other\nappropriate care per the standard\nclinical practice, irrespective of the\ndevice output.\n• The device is not intended to be a\nrule-out device and for cases that\nhave been processed by the device\nwithout notification for “Suspected\nLVO” should not be viewed as\nindicating that LVO is excluded.\nAll cases should undergo CTA or\nMRA, per the standard stroke\nworkup.\nLimitations:\n• Rapid NCCT Stroke does not\nreplace the need for CTA in\nischemic stroke workup, it\nprovides workflow prioritization\nand notification only.\n• Rapid ICH has been shown to\nreliably identify hemorrhages of ≥\n0.4ml.\nContraindications/Exclusions/Cauti\nons:\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate.\n• Hemorrhagic Transformation,\nHematoma\n• Very thin or no Ventricles"],["User","Radiologist","Clinician"],["Anatomy","Head","Head"],["Input Data","NCCT (ICH) and CTA(LVO)","NCCT (ICH and LVO)"],["Technology","AI/ML/Neural Network","AI/ML/Neural Network"],["Segmentation\nof ROI","The device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file.","The device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222884-p9-t0","doc_id":"K222884","page_num":9,"bbox":[76.56,75.84,526.56,375.24],"n_rows":6,"n_cols":3,"columns":["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care."],"rows":[["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care."],["Annotation /\nLocalization","Device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image","Device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image"],["Prioritization\nNotification","Yes","Yes"],["Clinical SoC\nWorkflow","In parallel to","In parallel to"],["Technical\nPipeline","Two independent Algorithms","Two cascaded functions (ICH then\nLVO) using three integrated\nalgorithms"],["Removal of\nCases from\nSoC review","No","No"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222884-p10-t0","doc_id":"K222884","page_num":10,"bbox":[132.87,271.56,476.99,370.08],"n_rows":5,"n_cols":7,"columns":["Parameter","Mean","","95% CI","","","95% CI\nUpper"],"rows":[["Parameter","Mean","","95% CI","","","95% CI\nUpper"],["","","","Lower","","",""],["Time to open in standard of\ncare (Minutes)","58.72","51.50","","","71.23",""],["Time to notification of Rapid\nNCCT Stroke (Minutes)","2.5","2.4","","","2.6",""],["Difference (Minutes)","70.08","NA","","","NA",""]],"caption_candidate":"longer than the parallel time-to-notification of the Rapid NCCT Stroke software.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K222970-p7-t0","doc_id":"K222970","page_num":7,"bbox":[208.13,518.35,542.38,601.18],"n_rows":3,"n_cols":2,"columns":["End point number","Results"],"rows":[["End point number","Results"],["a.","In 90% of the patients with image quality 3-5\nby visual estimation it was possible to obtain\nat least “Medium” quality score by LVivo IQS"],["b.","93% of the above saved clips were clinically\ninterpretable"]],"caption_candidate":"The results are summarized in Table-1:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223028-p6-t0","doc_id":"K223028","page_num":6,"bbox":[100.7,421.73,554.4,683.02],"n_rows":5,"n_cols":4,"columns":["ITEM","Proposed Device","Predicate Device","Discussion"],"rows":[["ITEM","Proposed Device","Predicate Device","Discussion"],["Specifications","","",""],["Gantry","Rotation speed: up to\n0.25s/rotation\n82cm bore","Rotation speed: up to\n0.25s/rotation\n82cm bore","Same"],["Detector","40mm Detector\nMaterial: Solid-state GOS\n80 rows,\n936 channels/row\nSize of detector element in\nZ-plane: 0.5mm","160mm Detector\nMaterial: Solid-state GOS\n320 rows,\n936 channels/row\nSize of detector element in\nZ-plane: 0.5mm","Note 1"],["X-ray tube","60, 70, 80, 100, 120, 140\nkV\nmA range: 10mA-667mA,\n10mA-833mA(option)","60, 70, 80, 100, 120, 140\nkV\nmA range: 10mA-833mA","Note 2"]],"caption_candidate":"Table 1 Comparisons to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223028-p7-t0","doc_id":"K223028","page_num":7,"bbox":[106.1,40.23,549.0,677.69],"n_rows":73,"n_cols":5,"columns":["","Shanghai United Imaging He","althcare Co., Ltd.","",""],"rows":[["","Shanghai United Imaging He","althcare Co., Ltd.","",""],["","Tel: +86 (21) 67076888 F","ax：+86 (21) 67076889","",""],["","www.united-imaging.com","","",""],["","","","",""],["I","TEM","Proposed Device","Predicate Device","Discussion"],["","","","",""],["","","Anode heat capacity:","Anode heat capacity:",""],["","","","",""],["","","30MHU equivalently","30MHU equivalently",""],["","","","",""],["","","Maximum anode heat","Maximum anode heat",""],["","","","",""],["","","dissipation:","dissipation:",""],["","","","",""],["","","20kW(1696kHU/min)","20kW(1696kHU/min)",""],["","","","",""],["","","Focal spot size:","Focal spot size:",""],["","","","",""],["","","0.4mm × 0.7mm","0.4mm × 0.8mm",""],["","","","",""],["","","0.6mm × 0.7mm","0.6mm × 0.8mm",""],["","","","",""],["","","1.1mm × 1.2mm","1.1mm × 1.2mm",""],["","","","",""],["H","igh Voltage","80kW, 100kW(option)","100kW","Note 3"],["","","","",""],["G","enerator","60, 70, 80, 100, 120, 140","60, 70, 80, 100, 120, 140",""],["","","","",""],["","","kV","kV",""],["","","","",""],["P","atient Table","Max load capacity","Max load capacity","Note 4"],["","","","",""],["","","205kg (Standard","318kg",""],["","","","",""],["","","Configuration);","",""],["","","","",""],["","","318kg (High Configuration)","",""],["","","","",""],["R","econstruction","40-500mm","40-500mm","Same"],["","","","",""],["F","ield of View","40-600mm with extended","40-600mm with extended",""],["","","","",""],["","","FOV","FOV",""],["","","","",""],["M","aximum slices","160","640","Note 5"],["","","","",""],["g","enerated per","","",""],["","","","",""],["ro","tation","","",""],["","","","",""],["F","unctions","","",""],["","","","",""],["L","ow Dose CT","Yes","Yes","Same"],["","","","",""],["L","ung Cancer","","",""],["","","","",""],["S","creening","","",""],["","","","",""],["P","rotocol","","",""],["","","","",""],["u","AI Vision-","Yes","Yes","Same"],["","","","",""],["E","asyPositioning","","",""],["","","","",""],["E","asyISO","","",""],["","","","",""],["E","asy Range","Yes","Yes","Same"],["","","","",""],["In","jector Linkage","Yes","Yes","Same"],["","","","",""],["R","emote","Yes","Yes","Same"],["","","","",""],["A","ssistance","","",""]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223028-p8-t0","doc_id":"K223028","page_num":8,"bbox":[100.7,77.64,554.4,306.41],"n_rows":9,"n_cols":4,"columns":["ITEM","Proposed Device","Predicate Device","Discussion"],"rows":[["ITEM","Proposed Device","Predicate Device","Discussion"],["Auto ALARA\nkVp","Yes","Yes","Same"],["Auto ALARA mA","Yes","Yes","Same"],["Organ-Based Auto\nALARA mA","Yes","Yes","Same"],["Deep IR (which is\nalso named AIIR)","Yes","Yes","Same"],["KARL 3D","Yes","Yes","Same"],["CardioXphase","Yes","Yes","Note 6"],["CardioCapture","Yes","Yes","Note 7"],["Metal Artifact\nCorrection","Yes","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223028-p8-t1","doc_id":"K223028","page_num":8,"bbox":[100.7,349.49,554.4,701.02],"n_rows":13,"n_cols":4,"columns":["Item","Proposed device","Predicate Device","Discussion"],"rows":[["Item","Proposed device","Predicate Device","Discussion"],["Dual Energy Scan","Yes","Yes","Same"],["Dual Energy Analysis","","",""],["Mono Energetic Image","Yes","Yes","Same"],["Mixed Enhanced Image","Yes","Yes","Same"],["CNR(Contrast Noise Ratio) Image","Yes","Yes","Same"],["Water-Iodine Base Material Pair","Yes","Yes","Same"],["Water-Calcium Base Material Pair","Yes","Yes","Same"],["Calcium-Iodine Base Material Pair","Yes","Yes","Same"],["Uric acid-Calcium Base\nMaterial Pair","Yes","Yes","Same"],["Image Registration","Yes","Yes","Same"],["Effective Atomic Number Images\n Component analysis of kidney\nstones, uric acid stones or non-\nuric acid stones\n Component analysis of joint\ngout, uric acid gout or non-uric\nacid gout","Yes","Yes","Same"],["Electron Density Image","Yes","Yes","Same"]],"caption_candidate":"Table 2 Dual Energy comparison to Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223028-p9-t0","doc_id":"K223028","page_num":9,"bbox":[100.7,116.06,554.4,688.78],"n_rows":7,"n_cols":2,"columns":["Justification",""],"rows":[["Justification",""],["Note 1","The detector dimension of the proposed device is shorter than that of the\npredicate device. Detector rows of the proposed device is less than those of the\npredicate device. The shorter detector Z-plane coverage, the longer scanning\ntime for CT imaging. The smaller number of rows, the less image information\nobtained.\nThe difference did not raise new safety and effectiveness concerns."],["Note 2","The proposed device is configured with two different ranges of mA ranges. One\nis same with the predicate device, one is smaller than the predicate device,\nbased on the x-ray tube hardware. Smaller mA output that induces lower ability\nof x-ray penetration when scanning the object with high BMI with higher\npossibility of photon starvation.\nFocal spot size of the proposed device is smaller than that of the predicate\ndevice. Smaller size is helpful for the improvement of resolution.\nThe differences did not raise new safety and effectiveness concerns."],["Note 3","The proposed device is configured with two kinds of Maximum Output Power.\nOne is same with the predicate device, one is smaller than the predicate device.\nSmaller power, lower mA or kV level in X-ray.\nThe differences did not raise new safety and effectiveness concerns."],["Note 4","The proposed device is configured with two kinds of patient table. One is same\nwith the predicate device, one is with lower load capacity than the predicate\ndevice. The two tables being a major component of the proposed device\nconform to the safety standards such as IEC 60601-1 series and satisfy the\nclinical use.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","Maximum slices generated per rotation of the proposed device is less than those\nof the predicate device. The less slices, the longer scanning time for CT\nimaging.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","The predicate device can use this function both on axial scan mode and helical\nscan mode. The proposed device only can use this function on helical scan\nmode.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"Virtual Non contrast Images Yes Yes Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223032-p6-t0","doc_id":"K223032","page_num":6,"bbox":[56.42,72.35,555.66,714.24],"n_rows":6,"n_cols":8,"columns":["","","SIS System version","","","SIS System version","","Comparison"],"rows":[["","","SIS System version","","","SIS System version","","Comparison"],["","","5.6.0","","","5.1.0 (K210071)","",""],["","","(subject device)","","","(predicate device)","",""],["Intended Use /\nIndications for Use","SIS System is intended\nfor use in the viewing,\npresentation and\ndocumentation of\nmedical imaging,\nincluding different\nmodules for image\nprocessing, image\nfusion, and\nintraoperative functional\nplanning where the 3D\noutput can be used with\nstereotactic image\nguided surgery or other\ndevices for further\nprocessing,\nvisualization and\nlocalization. The device\ncan be used in\nconjunction with other\nclinical methods as an\naid in visualization and\nlocation of the\nsubthalamic nuclei\n(STN) and globus\npallidus externa and\ninterna (GPe and GPi,\nrespectively) in\nneurological\nprocedures. The system\nis indicated for surgical\nprocedures in which\nanatomical structure\nlocations are identified\nin images, including\nDeep Brain Stimulation\nLead Placement.\nTypical users of the SIS\nSoftware are medical\nprofessionals, including\nbut not limited to\nsurgeons, neurologists\nand radiologists.","","","SIS System is an\napplication intended for\nuse in the viewing,\npresentation and\ndocumentation of\nmedical imaging,\nincluding different\nmodules for image\nprocessing, image\nfusion, and\nintraoperative functional\nplanning where the 3D\noutput can be used with\nstereotactic image\nguided surgery or other\ndevices for further\nprocessing and\nvisualization. The\ndevice can be used in\nconjunction with other\nclinical methods as an\naid in visualization of\nthe subthalamic nuclei\n(STN) and globus\npallidus externa and\ninterna (GPe and GPi,\nrespectively).\nTypical users of the SIS\nSystem are medical\nprofessionals, including\nbut not limited to\nsurgeons, neurologists\nand radiologists.","","","Similar. Addition of\nclarifying statement\n(about use in medical\nprocedures in which\nanatomical structure\nlocations such as STN,\nGPe and GPi are\nidentified in images,\nincluding deep brain\nstimulation lead\nplacement) does not\nraise different questions\nof safety or\neffectiveness because\npredicate was already\nintended for use in such\nprocedures and other\nreference devices (e.g.,\nStealthStation with\nCranial Software,\nK153660) with similar\nfunctions include this\nlanguage."],["User Population","Medical professionals,\nincluding but not limited\nto surgeons,\nneurologists and\nradiologists.","","","Medical professionals,\nincluding but not limited\nto surgeons,\nneurologists and\nradiologists.","","","Same"],["Allows for importing\nof digital imaging sets","Yes","","","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223032-p7-t0","doc_id":"K223032","page_num":7,"bbox":[56.41,72.35,555.68,633.13],"n_rows":13,"n_cols":8,"columns":["","","SIS System version","","","SIS System version","","Comparison"],"rows":[["","","SIS System version","","","SIS System version","","Comparison"],["","","5.6.0","","","5.1.0 (K210071)","",""],["","","(subject device)","","","(predicate device)","",""],["Uses proprietary\nsoftware algorithm to\ngenerate 3D\nsegmented anatomical\nmodels from patient’s\nMR scans","Yes","","","Yes","","","Same"],["Allows for review and\nanalysis of data in 2D\nand 3D formats","Yes","","","Yes","","","Same"],["Performs image fusion\nof datasets using\nautomated or manual\nimage matching\ntechnique","Yes","","","Yes","","","Same"],["Segments structures\nin images with manual\nand automated tools\nand converts them\ninto 3D objects for\ndisplay","Yes","","","Yes","","","Same"],["Creates hybrid\ndatasets by filing in\nsegmented regions\nslice-by-slice on\nanatomical datasets","Yes","","","Yes","","","Same"],["Can be downloaded to\nplanning system","Yes","","","Yes","","","Same"],["Segmentation of CT\nscan to identify\nstructures in relation\nto those visualized on\nMR","Yes","","","Yes","","","Same"],["Feature to Account for\nCT images with gantry\ntilt","Yes","","","Yes","","","Same"],["Cross-registers\nimages and creates 3D\n(fused) model","Yes","","","Yes","","","Same"],["Uses registration\nmethods (linear and\nnon-linear) by multiple\nregistration tools\n(ANTS and ELASTIX)","Yes","","","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223042-p4-t0","doc_id":"K223042","page_num":4,"bbox":[108.24,588.0,539.76,619.56],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc.","ContaCT","DEN170073"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223042-p7-t0","doc_id":"K223042","page_num":7,"bbox":[54.0,256.2,558.0,707.52],"n_rows":7,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz LVO","ContaCT"],["Application No.","KXXXXXX","DEN170073"],["Product Code","QAS","QAS"],["Regulation No.","21 C.F.R. § 892.2080","21 C.F.R. § 892.2080"],["Intended Use /\nIndications for Use","Viz LVO is a notification-only, parallel workflow\ntool for use by hospital networks and trained\nclinicians to identify and communicate images of\nspecific patients to a specialist, independent of\nstandard of care workflow.\nViz LVO uses an artificial intelligence algorithm to\nanalyze images for findings suggestive of a pre-\nspecified clinical condition and to notify an\nappropriate medical specialist of these findings in\nparallel to standard of care image interpretation.\nIdentification of suspected findings is not for\ndiagnostic use beyond notification. Specifically,\nthe device analyzes CT angiogram images of the\nbrain acquired in the acute setting, and sends\nnotifications to a neurovascular specialist that a\nsuspectedlarge vessel occlusion has been\nidentified and recommends review of those\nimages. Images can be previewed through a\nmobile application. Viz LVO is intended to analyze\nterminal ICA and MCA-M1 vessels for LVOs.\nImages that are previewed through the mobile\napplication are compressed and are for\ninformational purposes only and not intended for\ndiagnostic use beyond notification. Notified\nclinicians are responsible for viewing non-\ncompressed images on a diagnostic viewer and\nengaging in appropriate patient evaluation and\nrelevant discussion with a treating physician\nbefore making care-related decisions or requests.\nViz LVO is limited to analysis of imaging data and\nshould not be used in-lieu of full patient evaluation\nor relied upon to make or confirm diagnosis.","ContaCT is a notification-only, parallel workflow\ntool for use by hospital networks and trained\nclinicians to identify and communicate images of\nspecific patients to a specialist, independent of\nstandard of care workflow.\nContaCT uses an artificial intelligence algorithm\nto analyze images for findings suggestive of a\npre-specified clinical condition and to notify an\nappropriate medical specialist of these findings in\nparallel to standard of care image interpretation.\nIdentification of suspected findingsis not for\ndiagnostic use beyond notification. Specifically,\nthe device analyzes CT angiogram images of the\nbrain acquired in the acute setting, and sends\nnotifications to a neurovascular specialist that a\nsuspected large vessel occlusion has been\nidentified and recommends review of those\nimages. Images can be previewed through a\nmobile application.\nImages that are previewed through the mobile\napplication are compressed and are for\ninformational purposes only and not intended for\ndiagnostic use beyond notification. Notified\nclinicians are responsible for viewing non-\ncompressed images on a diagnostic viewer and\nengaging in appropriate patient evaluation and\nrelevant discussion with a treating physician\nbefore making care-related decisions or\nrequests. ContaCT is limited to analysis of\nimaging data and should not be used in-lieu of\nfull patient evaluation or relied upon to make or\nconfirm diagnosis."],["Anatomical\nRegion","Head","Head"]],"caption_candidate":"Table 1: Substantial Equivalence Table Comparing Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223042-p8-t0","doc_id":"K223042","page_num":8,"bbox":[54.0,121.56,558.0,350.16],"n_rows":11,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Diagnostic\nApplication","Notification-only","Notification-only"],["Notification/\nPrioritization","Yes","Yes"],["Intended User","Neurovascular Specialist","Neurovascular Specialist"],["DICOM\nCompatible","Yes","Yes"],["Data Acquisition","Acquires medical image data from DICOM\ncompliant imaging devices and modalities.","Acquires medical image data from DICOM\ncompliant imaging devices and modalities."],["Supported\nImaging Modality","Computed TomographyAngiography (CTA)","Computed TomographyAngiography (CTA)"],["Alteration of\nOriginal Image","No","No"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-diagnostic purposes","Initial assessment; non-diagnostic purposes"],["View DICOM Data","DICOM Information about the patient, study and\ncurrent image.","DICOM Information about the patient, study and\ncurrent image."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p4-t0","doc_id":"K223106","page_num":4,"bbox":[74.28,155.04,529.8,607.08],"n_rows":15,"n_cols":2,"columns":["General Information",""],"rows":[["General Information",""],["Manufacturer","Brainlab AG; Olof-Palme Str.9; 81829, Munich, Germany"],["Establishment Registration","8043933"],["Trade Names","• Brainlab Elements Image Fusion\n• Brainlab Elements Image Fusion Angio\n• Brainlab Elements Contouring\n• Brainlab Elements BOLD MRI Mapping\n• Brainlab Elements Fibertracking"],["Classification Name","Medical image management and processing system"],["Product Code (primary)","QIH"],["Product Codes\n(secondary)","LLZ, JAK"],["Regulation Number","892.2050"],["Regulatory Class","II"],["Panel","Radiology"],["Primary Predicate Device","K212420\nBrainlab Elements, Brainlab Elements Contouring (4.0), Brainlab\nElements Fibertracking (2.0), Brainlab Elements Image Fusion\n(4.0), Brainlab Elements Image Fusion Angio (1.0)"],["Secondary Predicate\nDevice","K113732\niPlan (iPlan Cranial, iPlan Stereotaxy, iPlan ENT, iPlan CMF, iPlan\nView, iPlan Spine)"],["Contact Information",""],["Primary Contact","Marc Bergenthal\nManager Regulatory Affairs\nRegulatory Affairs\nPhone: +49 89 99 15 68 0\nEmail: regulatory.affairs@brainlab.com"],["Alternate Contact","Sadwini Suresh\nQM Consultant\nPhone: +49 89 99 15 68 0\nEmail: regulatory.affairs@brainlab.com"]],"caption_candidate":"July 14, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p6-t0","doc_id":"K223106","page_num":6,"bbox":[75.17,654.28,527.21,760.1],"n_rows":2,"n_cols":5,"columns":["Predicate Device","","","Name",""],"rows":[["Predicate Device","","","Name",""],["Subject Device","","Brainlab Elements, Brainlab Elements Contouring (4.5), Brainlab\nElements Fibertracking (2.0), Brainlab Elements Image Fusion (4.5),\nBrainlab Elements Image Fusion Angio (1.0), Brainlab Elements BOLD\nMRI Mapping (1.0)","",""]],"caption_candidate":"devices. An overview of the similarities and differences can be found in the tables below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p7-t0","doc_id":"K223106","page_num":7,"bbox":[75.44,100.36,527.21,253.22],"n_rows":3,"n_cols":5,"columns":["Predicate Device","","","Name",""],"rows":[["Predicate Device","","","Name",""],["Primary Predicate\ndevice (K212420)","","Brainlab Elements, Brainlab Elements Contouring (4.0), Brainlab\nElements Fibertracking (2.0), Brainlab Elements Image Fusion (4.0),\nBrainlab Elements Image Fusion Angio (1.0)","",""],["Secondary\nPredicate device\n(K113732)","","iPlan (iPlan Cranial, iPlan Stereotaxy, iPlan ENT, iPlan CMF, iPlan View,\niPlan Spine)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p7-t1","doc_id":"K223106","page_num":7,"bbox":[51.12,295.32,564.24,765.24],"n_rows":4,"n_cols":4,"columns":["Topic/ Feature","Primary Predicate Device\n(Brainlab Elements Image Fusion\n4.0 (K212420))","Subject Device (Brainlab\nElements Image Fusion 4.5)","Comment"],"rows":[["Topic/ Feature","Primary Predicate Device\n(Brainlab Elements Image Fusion\n4.0 (K212420))","Subject Device (Brainlab\nElements Image Fusion 4.5)","Comment"],["Indications for use","Brainlab Elements Image Fusion\nis an application for the co-\nregistration of image data within\nmedical procedures by using\nrigid and deformable registration\nmethods. It is intended to align\nanatomical structures between\ndata sets.\nThe device itself does not have\nclinical indications.","Brainlab Elements Image\nFusion is an application for\nthe co-registration of image\ndata within medical\nprocedures by using rigid\nand deformable registration\nmethods. It is intended to\nalign anatomical structures\nbetween data sets.\nThe device itself does not\nhave clinical indications.","Same as the\npredicate."],["Use Environment","The system shall be used in a\nhospital office environment or\nrooms appropriate for surgical\ninterventions or radiotherapy\nplanning.","The system shall be used in\na hospital office\nenvironment or rooms\nappropriate for surgical\ninterventions or\nradiotherapy planning.","Same as the\npredicate."],["Computer\nHardware\nRequirements","Brainlab Elements can be used\non hardware that fulfills the\ndefined minimum requirements:\n- Operating System:\nWindows 8.1 64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X\ncompatible","Brainlab Elements can be\nused on hardware that\nfulfills the defined minimum\nrequirements:\n- Operating System:\nWindows 8.1 64bit\n- Minimum 4 logical\ncores","Same as the\npredicate."]],"caption_candidate":"Brainlab Elements – Image Fusion 4.5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p8-t0","doc_id":"K223106","page_num":8,"bbox":[51.12,99.24,564.24,500.04],"n_rows":3,"n_cols":4,"columns":["","- Display Resolution: 1920\nx 1080 (Full HD)","- Minimum RAM: 6\nGB\n- Graphics: Direct X\ncompatible\n- Display Resolution:\n1920 x 1080 (Full HD)",""],"rows":[["","- Display Resolution: 1920\nx 1080 (Full HD)","- Minimum RAM: 6\nGB\n- Graphics: Direct X\ncompatible\n- Display Resolution:\n1920 x 1080 (Full HD)",""],["Image Data Sets\nFormat","DICOM 3D imaging Modalities,\ne.g. CT/XT, MRI, NM/PET, OT,\nare supported for automatic\nfusion.\nOther modalities are supported\nfor manual fusion (alignment)","DICOM 3D imaging\nModalities, e.g. CT/XT, MRI,\nNM/PET, OT, are supported\nfor automatic fusion.\nOther modalities are\nsupported for manual fusion\n(alignment)","Same as the\npredicate."],["Rigid co-\nregistration, rigid\nimage fusion","Automatic rigid co-registration\n(rigid fusion) of 3D DICOM image\ndata: CT (incl. low-dose CT), MR,\nOT (e.g. Perfusion), MR-DTI, MR-\nBOLD, NM/PET\nManual rigid co-registration (rigid\nfusion) of other (unknown) 3D\nDICOM image data, e.g. US\n(ultrasound).","Automatic rigid co-\nregistration (rigid fusion) of\n3D DICOM image data: CT\n(incl. low-dose CT), MR, OT\n(e.g. Perfusion), MR-DTI,\nMR-BOLD, NM/PET, US\n(ultrasound).\nManual rigid co-registration\n(rigid fusion) of other\n(unknown) 3D DICOM\nimage data.","The subject device\nadditionally\nprovides\nfunctionality to\nautomatically fuse\nUS to MR images.\nSafety and efficacy\nof this feature was\nverified via Risk\nManagement and\nVerification\nactivities."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p8-t1","doc_id":"K223106","page_num":8,"bbox":[51.12,554.28,564.24,748.08],"n_rows":2,"n_cols":4,"columns":["Topic/ Feature","Primary Predicate Device\n(Brainlab Elements Image Fusion\n4.0 (K212420))","Subject Device (Contouring\n4.5)","Comment"],"rows":[["Topic/ Feature","Primary Predicate Device\n(Brainlab Elements Image Fusion\n4.0 (K212420))","Subject Device (Contouring\n4.5)","Comment"],["Indications for Use","Brainlab Elements Contouring\nprovides an interface with tools\nand views to outline, refine,\ncombine and manipulate\nstructures in patient image data.\nThe generated 3D structures are\nnot intended to create physical\nreplicas used for diagnostic\npurposes.","Brainlab Elements\nContouring provides an\ninterface with tools and\nviews to outline, refine,\ncombine and manipulate\nstructures in patient image\ndata. The generated 3D\nstructures are not intended\nto create physical replicas","Same as the\npredicate."]],"caption_candidate":"Brainlab Elements Contouring 4.5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p9-t0","doc_id":"K223106","page_num":9,"bbox":[51.12,99.24,564.24,768.48],"n_rows":5,"n_cols":4,"columns":["","The device itself does not have\nclinical indications","used for diagnostic\npurposes.\nThe device itself does not\nhave clinical indications",""],"rows":[["","The device itself does not have\nclinical indications","used for diagnostic\npurposes.\nThe device itself does not\nhave clinical indications",""],["Use Environment","The system shall be used in a\nhospital office environment or\nrooms appropriate for surgical\ninterventions or radiotherapy\nplanning.","The system shall be used in\na hospital office\nenvironment or rooms\nappropriate for surgical\ninterventions or\nradiotherapy planning.","Same as the\npredicate."],["Automatic\nSegmentation of\nObjects","The application automatically\ncreates segmentation objects\nprovided by the Universal Atlas.\nWorkflow relevant segmentation\nobjects are created automatically\nor, if required by a workflow, on\na single button click.\nThe application also offers the\npossibility to define customized\nsegmentation templates.","The application\nautomatically creates\nsegmentation objects\nprovided by the Universal\nAtlas.\nWorkflow relevant\nsegmentation objects are\ncreated automatically or, if\nrequired by a workflow, on\na single button click.\nThe application also offers\nthe possibility to define\ncustomized segmentation\ntemplates.","Same as the\npredicate."],["Manual Creation\nand Refinement of\nObjects","The application provides tools for\nthe manipulation of objects:\nThe application provides tools for\nmanual creation and refinement\nof segmentation objects:\n- SmartShaper\n- Brush 3D / Erase 3D\n- Brush 2D / Erase 2D\n- Smart Brush\n- Threshold Segmentation","The application provides\ntools for the manipulation of\nobjects:\nThe application provides\ntools for manual creation\nand refinement of\nsegmentation objects:\n- SmartShaper\n- Brush 3D / Erase 3D\n- Brush 2D / Erase 2D\n- Smart Brush\n- Threshold\nSegmentation","Same as the\npredicate."],["Object Manipulation","The application provides tools for\nthe manipulation of objects:\n- Copy","The application provides\ntools for the manipulation of\nobjects:","Same as the\npredicate."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223106-p10-t0","doc_id":"K223106","page_num":10,"bbox":[51.12,99.24,564.24,611.16],"n_rows":3,"n_cols":4,"columns":["","- Margins\n- Smoothing\n- Mirroring\n- Shifting and Rotation\n- Splitting\n- Automatic Object Fitting","- Copy\n- Margins\n- Smoothing\n- Mirroring\n- Shifting and\nRotation\n- Splitting\n- Automatic Object\nFitting",""],"rows":[["","- Margins\n- Smoothing\n- Mirroring\n- Shifting and Rotation\n- Splitting\n- Automatic Object Fitting","- Copy\n- Margins\n- Smoothing\n- Mirroring\n- Shifting and\nRotation\n- Splitting\n- Automatic Object\nFitting",""],["Object Review","The application provides\nfunctionality to control the review\nstate of objects. In case of\nleaving the application with\nunreviewed semi-automatically\nor automatically created objects,\na message is displayed.","The application provides\nfunctionality to control the\nreview state of objects. In\ncase of leaving the\napplication with unreviewed\nsemi-automatically or\nautomatically created\nobjects, a message is\ndisplayed.","Same as the\npredicate."],["Volumetric Report","It is possible to create a printable\nreport for an object in a platform\nindependent file format, giving\ninformation about the object's\nvolume, its diameter according to\nthe Macdonald criteria and its\nresponse evaluation criteria\n(RECIST).\nIf multiple objects are selected\nand a volumetric report is\ncreated, it contains information\nabout all objects.","It is possible to create a\nprintable report for an\nobject in a platform\nindependent file format,\ngiving information about the\nobject's volume, its\ndiameter according to the\nMacdonald criteria and its\nresponse evaluation criteria\n(RECIST).\nIf multiple objects are\nselected and a volumetric\nreport is created, it contains\ninformation about all\nobjects.","Same as the\npredicate."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223133-p6-t0","doc_id":"K223133","page_num":6,"bbox":[83.4,127.53,528.24,435.27],"n_rows":30,"n_cols":5,"columns":["","","","Chest","Chest"],"rows":[["","","","Chest","Chest"],["","Study Type","","",""],["","","","",""],["","","","Lung lesion detection using marked\nregions of interest (ROIs)","Lung lesion detection using marked\nregions of interest (ROIs)"],["Clinical Finding","","","",""],["","","","",""],["","","","Physician","Physician"],["","Intended Users","","",""],["","","","",""],["","","","Device intended as a second-reader\nfor physicians interpreting chest\nradiographs","Device intended as a second-reader\nfor physicians interpreting chest\nradiographs"],["Intended User\nWorkflow","","","",""],["","","","",""],["","","","Adults with Chest Radiographs","Adults with Chest Radiographs"],["","Patient Population","","",""],["","","","",""],["","","","Machine learning","Machine learning"],["","T echnology","","",""],["","","","",""],["","","","Digital X-rays in DICOM format","Digital X-rays in DICOM format"],["","Input Type","","",""],["","","","",""],["","","","Chest AP/PA","Chest PA"],["","Imaging protocols","","",""],["","","","",""],["","","","ROI marked on duplicated input\nimage","Information for ROI to be\nmarked on the duplicated\ninput image"],["Output","","","",""],["","","","",""],["","","","Secure cloud-based processing and\ndelivery of outputs","Secure on-premise processing\nand delivery of outputs"],["Platform","","","",""],["","","","",""]],"caption_candidate":"Section 05: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223180-p5-t0","doc_id":"K223180","page_num":5,"bbox":[70.09,399.12,525.35,751.68],"n_rows":7,"n_cols":3,"columns":["Characteristic","New Device","Predicate Device"],"rows":[["Characteristic","New Device","Predicate Device"],["510(k) Number","K223180","K192130"],["Device Name,\nModel","AIRAscore","icobrain"],["Manufacturer","AIRAmed GmbH","icometrix NV"],["Regulation\nNumber","892.2050","892.2050"],["Product Code","LLZ","LLZ"],["Intended Use /\nIndications for\nUse","AIRAscore is intended for automatic\nlabeling, visualization and volumetric\nquantification of segmentable brain\nstructures from a set of MR images. This\nsoftware is intended to automate the\ncurrent manual process of identifying,\nlabeling and quantifying the volume of\nsegmentable brain structures identified\non MR images.","icobrain is intended for automatic\nlabeling, visualization and volumetric\nquantification of segmentable brain\nstructures from a set of MR or NCCT\nimages. This software is intended to\nautomate the current manual process\nof identifying, labeling and quantifying\nthe volume of segmentable brain\nstructures identified on MR or NCCT\nimages.\nicobrain consists of two distinct image\nprocessing pipelines: icobrain cross\nand icobrain long.\nicobrain cross is intended to provide\nvolumes from images acquired at a\nsingle timepoint. icobrain long is\nintended to provide changes in\nvolumes between two images that\nwere acquired on the same scanner,"]],"caption_candidate":"Table 1: Predicate Device Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223180-p6-t0","doc_id":"K223180","page_num":6,"bbox":[70.08,97.56,525.36,753.12],"n_rows":5,"n_cols":3,"columns":["","","with the same image acquisition\nprotocol and with the same contrast at\ntwo different timepoints. The results of\nicobrain cross cannot be compared\nwith the results of icobrain long."],"rows":[["","","with the same image acquisition\nprotocol and with the same contrast at\ntwo different timepoints. The results of\nicobrain cross cannot be compared\nwith the results of icobrain long."],["Technical\nCharacteristics"," AIRAscore is a software as medical\ndevice (SaMD) that runs on\nAIRAmed internal servers (Software\nas a Service - SaaS).\nFor sending and receiving DICOM\ndata dedicated interfaces are\nsupplied as accessory.\n Operates on off-the-shelf hardware\n(multiple vendors)\n DICOM compatible\n Segmentation by machine learning\n(supervised voxel classification by a\nConvolutional Neuronal Network)\nInput:\n T1-weighted and (optional) fluid-\nattenuated inversion recovery\n(FLAIR) MR images from a single\ntime point\nOutput:\n Multiple electronic report with\nvolumetric information of brain\nstructures (Encapsulated PDF\nDICOM)\n Annotated DICOM images for visual\ninspection by an expert (Secondary\nCapture DICOM)"," Software package\n Operates on off-the-shelf hardware\n(multiple vendors)\n DICOM compatible\n Segmentation by classical machine\nlearning and deep learning\n(supervised voxel classification by a\nConvolutional Neuronal Network)\nInput:\n T1-weighted and fluid-attenuated\ninversion recovery (FLAIR) MR\nimages from a single or multiple\ntime points\n Non-contrast CT from a single time\npoint\nOutput:\n Multiple electronic reports with\nvolumetric information of brain\nstructures and midline shift\n Annotated DICOM images"],["Performance\nMeasurement\nTesting","Accuracy\n Brain segmentable structure volumes\n/ volume changes compared to\nmanually labeled ground truth\nReproducibility\n Brain segmentable structure volumes\n/ volume changes compared on test-\nretest images","Accuracy\n Brain segmentable structure\nvolumes / volume changes\ncompared to simulated and/or\nmanually labeled ground truth\nReproducibility\n Brain segmentable structure\nvolumes / volume changes\ncompared on test-retest images"],["Environment of\nUse","Primary users of the system are\nphysicians with finished course of\nstudies, medical license and expert\nknowledge in neuroanatomy and MR-\nimaging of the head. The reports and\ncontrol images are looked at and\nevaluated in a professional healthcare\nsetting (diagnostic workstation or\ndoctor’s office).","icobrain is used by trained\nprofessionals in hospitals, imaging\ncenters or in image processing labs."],["Testing","• Product Risk assessment\n• Software verification tests\n• Software validation tests","• Product Risk assessment\n• Software verification tests\n Software validation tests"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223212-p5-t0","doc_id":"K223212","page_num":5,"bbox":[77.42,542.11,545.5,648.22],"n_rows":5,"n_cols":2,"columns":["Predicate Device Information",""],"rows":[["Predicate Device Information",""],["Device Name:","Omni Legend"],["Manufacturer:","GE Medical Systems Israel, Functional Imaging"],["510(k) Number:","K221932"],["Regulation Number/\nProduct Code:","21CFR 892.1200 & 21CFR 892.1750\nKPS & JAK"]],"caption_candidate":"Product Codes: KPS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223212-p6-t0","doc_id":"K223212","page_num":6,"bbox":[77.66,122.06,545.26,228.14],"n_rows":5,"n_cols":2,"columns":["Reference Device Information",""],"rows":[["Reference Device Information",""],["Device Name:","Discovery MI"],["Manufacturer:","GE Medical Systems, LLC."],["510(k) Number:","K161574"],["Regulation Number/\nProduct Code:","21CFR 892.1200 & 21CFR 892.1750\nKPS & JAK"]],"caption_candidate":"Precision DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223212-p7-t0","doc_id":"K223212","page_num":7,"bbox":[72.02,211.85,540.1,332.33],"n_rows":5,"n_cols":5,"columns":["Specification","","Predicate Device","","Proposed Device\nPrecision DL\non Omni Legend"],"rows":[["Specification","","Predicate Device","","Proposed Device\nPrecision DL\non Omni Legend"],["","","Omni Legend (K221932)","",""],["","","including non-ToF Q.Clear Image","",""],["","","Reconstruction","",""],["Technology","Iterative non-ToF image\nreconstruction algorithm","","","Deep learning-based image\nprocessing trained to enhance non-\nToF images to have IQ performance\nsimilar to ToF images."]],"caption_candidate":"proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223240-p5-t0","doc_id":"K223240","page_num":5,"bbox":[62.68,197.64,530.1,296.54],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level P, 24 Campbell Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","March 31, 2023"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223240-p5-t1","doc_id":"K223240","page_num":5,"bbox":[62.68,353.43,530.1,438.52],"n_rows":5,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CTB Triage Trauma"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223240-p5-t2","doc_id":"K223240","page_num":5,"bbox":[62.68,495.42,530.1,594.82],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Infervision Medical Technology Co., Ltd."],"rows":[["","Manufacturer Name","","Infervision Medical Technology Co., Ltd."],["","Device Name","","InferRead CT Stroke.AI"],["","510(k) reference","","K211179"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223240-p10-t0","doc_id":"K223240","page_num":10,"bbox":[62.78,85.5,551.37,359.94],"n_rows":21,"n_cols":5,"columns":["","","","Sensitivity % (Se)","Specificity % (Sp)"],"rows":[["","","","Sensitivity % (Se)","Specificity % (Sp)"],["Finding","Slice Thickness Range","Operating Point","",""],["","","","(95% CI)","(95% CI)"],["","","","",""],["Acute subdural/ Epidural\nhematoma","≤1.5mm","0.060177","91.4 (88.1,94.4)","86.7 (79.6,92.9)"],["","","0.101143","89.1 (85.5,92.4)","94.9 (89.8,99.0)"],["","","0.135700","86.5 (82.5,90.1)","96.9 (92.9,100.0)"],["",">1.5mm & ≤5.0mm","0.060177","82.4 (78.6,86.1)","89.6 (83.7,94.8)"],["Acute subarachnoid\nhemorrhage","≤1.5mm","0.014372","98.0 (95.2,100.0)","89.4 (82.4,95.3)"],["","","0.060162","93.9 (89.8,97.3)","96.5 (91.8,100.0)"],["","","0.082652","89.8 (85.0,94.6)","100 (100.0,100.0)"],["",">1.5mm & ≤5.0mm","0.020255","90.7 (86.3,95.1)","92.4 (86.7,97.1)"],["","","0.030010","87.4 (82.4,91.8)","96.2 (92.4,99.0)"],["Intra-axial hemorrhage","≤1.5mm","0.322700","93.1 (90.8,95.2)","85.6 (81.1,89.6)"],["",">1.5mm & ≤5.0mm","0.203600","93.4 (91.3,95.1)","85.1 (80.9,88.9)"],["","","0.322700","90.3 (87.9,92.5)","90.3 (86.8,93.8)"],["Intraventricular hemorrhage","≤1.5mm","0.015487","95.9 (90.4,100.0)","90.9 (84.4,97.4)"],["","","0.051859","90.4 (83.6,97.3)","97.4 (93.5,100.0)"],["",">1.5mm & ≤5.0mm","0.008430","95.6 (91.2,98.9)","86.0 (78.5,92.5)"],["","","0.015487","92.3 (86.8,96.7)","89.2 (82.8,94.6)"],["","","0.051859","87.9 (80.2,94.5)","97.8 (94.6,100.0)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223268-p5-t0","doc_id":"K223268","page_num":5,"bbox":[78.68,387.23,558.7,709.67],"n_rows":8,"n_cols":9,"columns":["","Attribute","","","Subject BrainInsight","","","Predicate BrainInsight (K220815)",""],"rows":[["","Attribute","","","Subject BrainInsight","","","Predicate BrainInsight (K220815)",""],["Indications for Use","","","BrainInsight is intended for automatic labeling,\nspatial measurement, and volumetric\nquantification of brain structures from a set of\nlow-field MR images and returns annotated and\nsegmented images, color overlays and reports.","","","Same","",""],["Target Anatomical\nSites","","","Brain","","","Same","",""],["Patient Population","","","● Adult and pediatric (≥ 2 years) - Lateral\nventricles and midline shift applications\n● Adult (≥ 18 years) - Whole brain application","","","Adult (≥ 18 years) - Lateral ventricles,\nmidline shift, and whole brain applications","",""],["Technology","","","● Automated measurement of brain tissue\nvolumes and structures of AI-reconstructed\nlow-field MR images\n● Automatic segmentation and quantification\nof brain structures of AI-reconstructed low-\nfield MR images using machine learning\ntools","","","Same","",""],["Method of Use","","","MR images are automatically sent to\nBrainInsight, and processed images are\nautomatically returned in ~7 minutes","","","Same","",""],["User Interface /\nPhysical\nCharacteristics","","","● No software required\n● Operates in a serverless cloud environment\n● User interface through PACS (multiple\nvendors)","","","Same","",""],["Operating System","","","Supports Linux","","","Same","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223268-p6-t0","doc_id":"K223268","page_num":6,"bbox":[78.71,72.71,558.71,355.43],"n_rows":4,"n_cols":3,"columns":["Processing\nArchitecture","Automated internal pipeline that performs:\n● segmentation\n● volume calculation\n● distance measurement\n● numerical information display","Same"],"rows":[["Processing\nArchitecture","Automated internal pipeline that performs:\n● segmentation\n● volume calculation\n● distance measurement\n● numerical information display","Same"],["Data Source","● MRI Scanner: Hyperfine Swoop FSE MRI T1-\nGray/White Contrast, T2, T2-Fast and FLAIR\nscans acquired with specified protocols\n● Supports DICOM format as input","● MRI Scanner: Hyperfine Swoop FSE\nMRI T1 and T2 scans acquired with\nspecified protocols\n● Supports DICOM format as input"],["Output","Provides volumetric measurements of brain\nstructures:\n● Includes segmented color overlays and\nmorphometric reports\n● Supports DICOM format as output of results\nthat can be displayed on DICOM\nworkstations and PACS","Same"],["Safety","Automated quality control functions:\n● Tissue contrast check\n● Scan protocol verification\n● Atlas alignment check\n● Results must be reviewed by a trained\nphysician\n● LV segmentation output quality check","Automated quality control functions:\n● Tissue contrast check\n● Scan protocol verification\n● Atlas alignment check\n● Results must be reviewed by a trained\nphysician"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223287-p4-t0","doc_id":"K223287","page_num":4,"bbox":[72.02,362.33,540.1,430.99],"n_rows":3,"n_cols":3,"columns":["Classification Name","Regulation","Product Code"],"rows":[["Classification Name","Regulation","Product Code"],["Ultrasonic Pulsed Echo Imaging\nSystem","21 CFR §892.1560","IYO"],["Diagnostic Ultrasonic\nTransducer","21 CFR §892.1570","ITX"]],"caption_candidate":"Common Name: Ultrasound elastography system","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p4-t0","doc_id":"K223296","page_num":4,"bbox":[67.5,171.5,487.5,357.5],"n_rows":3,"n_cols":2,"columns":["Applicant:","VideaHealth, Inc.\n179 South Street, Floor 5\nBoston, MA, 02111\n+1 617-340-9940\nflorian@videa.ai"],"rows":[["Applicant:","VideaHealth, Inc.\n179 South Street, Floor 5\nBoston, MA, 02111\n+1 617-340-9940\nflorian@videa.ai"],["Contact & Submission\nCorrespondent:","Adam Foresman\nDirector of Quality & Regulatory Affairs\nVideaHealth, Inc.\n+1 617-340-9940\nadam@videa.ai"],["Date Prepared:","October 14, 2022"]],"caption_candidate":"1. S UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p4-t1","doc_id":"K223296","page_num":4,"bbox":[67.5,417.5,487.5,595.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","Videa Perio Assist"],"rows":[["Device Trade Name:","Videa Perio Assist"],["Device Common Name:","Interproximal bone level measurement"],["Classification Name","Medical image management and processing system"],["Classification Regulation\nNumber","21 CFR 892.2050"],["Device Class:","2"],["Product Code:","QIH"]],"caption_candidate":"2. D EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p6-t0","doc_id":"K223296","page_num":6,"bbox":[66.25,294.53,545.31,733.5],"n_rows":12,"n_cols":3,"columns":["","Proposed Device","Predicate Device"],"rows":[["","Proposed Device","Predicate Device"],["510(k) Number","TBD","K210187"],["Applicant","VideaHealth, Inc.","Overjet, Inc."],["Device Name","Videa Perio Assist","Overjet Dental Assist"],["Classification Regulation","892.2050","892.2050"],["Product Code","QIH","LLZ"],["Image Modality","X-Ray","X-Ray"],["Study Type","Bitewing and periapical Images","Bitewing and periapical\nImages"],["Patient Population","Patients ≥12 years of age with\npermanent dentition present in the\nradiograph","Adults ≥ 22 years of age"],["OS","Any","Any"],["Intended User","Dentists and dental hygienists","Dentists and dental hygienists"],["Image Input Source","Images imported from the\nradiographic device, or from the\npractice management system","Images imported from the\nradiographic device, or from\nthe practice management\nsystem"]],"caption_candidate":"Table 1: Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p8-t0","doc_id":"K223296","page_num":8,"bbox":[77.5,236.5,240.83,379.5],"n_rows":6,"n_cols":2,"columns":["Subject Age","Percentage"],"rows":[["Subject Age","Percentage"],["12 - 21","31%"],["22 - 40","35%"],["41 - 60","21%"],["61 - 75","9%"],["75 +","4%"]],"caption_candidate":"Table 2: Demographic breakdown by age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p8-t1","doc_id":"K223296","page_num":8,"bbox":[77.5,406.5,240.83,478.5],"n_rows":3,"n_cols":2,"columns":["Subject Gender","Percentage"],"rows":[["Subject Gender","Percentage"],["Male","47%"],["Female","53%"]],"caption_candidate":"Table 3: Demographic breakdown by gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p8-t2","doc_id":"K223296","page_num":8,"bbox":[77.5,505.5,240.83,626.5],"n_rows":4,"n_cols":2,"columns":["Sensor\nManufacturer","Percentage"],"rows":[["Sensor\nManufacturer","Percentage"],["Dentsply Sirona","13%"],["KaVo Kerr","48%"],["Carestream\nDental","39%"]],"caption_candidate":"Table 4: Intraoral sensor breakdown by manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p9-t0","doc_id":"K223296","page_num":9,"bbox":[77.38,208.78,544.5,449.5],"n_rows":6,"n_cols":5,"columns":["Radiographic\nView Type","Line Type","Sensitivity (%)","Specificity (%)","Mean Absolute Error\n(mm)"],"rows":[["Radiographic\nView Type","Line Type","Sensitivity (%)","Specificity (%)","Mean Absolute Error\n(mm)"],["Bitewing","CEJ->ABL","Met acceptance\ncriteria","Met acceptance\ncriteria","Met acceptance criteria"],["Periapical","All","Met acceptance\ncriteria","Met acceptance\ncriteria","Met acceptance criteria"],["","CEJ->ABL","Met acceptance\ncriteria","Did not meet\nacceptance criteria","Met acceptance criteria"],["","CEJ->RT","Met acceptance\ncriteria","Met acceptance\ncriteria","Met acceptance criteria"],["","ABL->RT","Met acceptance\ncriteria","Met acceptance\ncriteria","Met acceptance criteria"]],"caption_candidate":"Table 5: Clinical Performance Metrics of VPA by radiographic view type and line type.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p10-t0","doc_id":"K223296","page_num":10,"bbox":[77.38,98.46,555.0,260.5],"n_rows":3,"n_cols":4,"columns":["Radiographic\nView Type","Dentsply Sirona","KaVo Kerr","Carestream Dental"],"rows":[["Radiographic\nView Type","Dentsply Sirona","KaVo Kerr","Carestream Dental"],["Bitewing\nMeasurements","Met acceptance criteria for\nsensitivity and mean\nabsolute error.\nSpecificity did not meet\nacceptance criteria.","Met acceptance criteria\nfor all 3 metrics","Met acceptance criteria for all\n3 metrics"],["Periapical\nMeasurements","Met acceptance criteria for\nall 3 metrics","Met acceptance criteria\nfor all 3 metrics","Met acceptance criteria for all\n3 metrics"]],"caption_candidate":"Table 6: Clinical Performance Metrics of VPA by intraoral sensor manufacturer across all models.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223296-p10-t1","doc_id":"K223296","page_num":10,"bbox":[77.38,391.36,555.0,610.5],"n_rows":3,"n_cols":5,"columns":["Radiographic\nView Type","Patients 12 to 21\nYears of Age","Patients 22 to 40\nYears of Age","Patients 41 to 60\nYears of Age","Patients 61 Years of\nAge and Older"],"rows":[["Radiographic\nView Type","Patients 12 to 21\nYears of Age","Patients 22 to 40\nYears of Age","Patients 41 to 60\nYears of Age","Patients 61 Years of\nAge and Older"],["Bitewing\nMeasurements","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for sensitivity\nand mean absolute\nerror.\nSpecificity did not\nmeet acceptance\ncriteria."],["Periapical\nMeasurements","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for all 3\nmetrics","Met acceptance\ncriteria for all 3\nmetrics"]],"caption_candidate":"Table 7: Clinical Performance Metrics of VPA by patient age.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p5-t0","doc_id":"K223311","page_num":5,"bbox":[90.29,133.97,515.47,608.11],"n_rows":17,"n_cols":3,"columns":["Date Prepared:","October 26, 2022",""],"rows":[["Date Prepared:","October 26, 2022",""],["Manufacturer:","Philips Healthcare (Suzhou) Co., Ltd.\nNo. 258, Zhongyuan Road, Suzhou Industrial Park,\nSuzhou Jiangsu, CHINA, 215024\nEstablishment Registration Number: 3009529630",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","Diana Xu\nAssociated Regulatory Affairs Manager\nPhone: +86-18940060508\nE-mail: diana.xu@philips.com\nErhong Wang\nSenior Manager Regulatory Affairs\nPhone: +86-512-67336804\nE-mail: ErHong.WANG@philips.com",""],["Device Name:","Philips CT 3500",""],["Classification:","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Regulation:","21CFR 892.1750"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary Product Code:","JAK"],["Predicate Device:","Trade name:","Philips Incisive CT"],["","Manufacturer:","Philips Healthcare (Suzhou)\nCo., Ltd."],["","510(k) Clearance:","K212441, K211168"],["","Classification Regulation:","21CFR 892.1750"],["","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","JAK"]],"caption_candidate":"[As required by 21 CFR 807.92(c)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p7-t0","doc_id":"K223311","page_num":7,"bbox":[90.32,72.26,515.47,676.54],"n_rows":2,"n_cols":2,"columns":["","Couch is used to position the patient. Carries the patient in\nand out through the Gantry bore synchronized with the\nscan.\n3. Console\nIt is used to operate the system and monitor the scan. The\nOperator console includes computer, monitor and CTBOX.\n4. CT on Trailer Kit\nPhilips CT 3500 installed and secured on trailer requires\nlocking motion parts during trailer transportation and\nunlocking motion parts before CT operations. CT on Trailer\nKit is used to install and secure the CT system on trailers,\ntrailers are provided by trailer manufactures and are not\ncomponents of the proposed Philips CT 3500.\nIn addition to the above components and the software\noperating them, each system includes hardware and\nsoftware for data acquisition, display, manipulation, storage\nand filming as well as post-processing into views other than\nthe original axial images."],"rows":[["","Couch is used to position the patient. Carries the patient in\nand out through the Gantry bore synchronized with the\nscan.\n3. Console\nIt is used to operate the system and monitor the scan. The\nOperator console includes computer, monitor and CTBOX.\n4. CT on Trailer Kit\nPhilips CT 3500 installed and secured on trailer requires\nlocking motion parts during trailer transportation and\nunlocking motion parts before CT operations. CT on Trailer\nKit is used to install and secure the CT system on trailers,\ntrailers are provided by trailer manufactures and are not\ncomponents of the proposed Philips CT 3500.\nIn addition to the above components and the software\noperating them, each system includes hardware and\nsoftware for data acquisition, display, manipulation, storage\nand filming as well as post-processing into views other than\nthe original axial images."],["Indications for Use:","The Philips CT 3500 is a Computed Tomography X-Ray\nSystem intended to produce images of the head and body\nby computer reconstruction of X-Ray transmission data\ntaken at different angles and planes. These devices may\ninclude signal analysis and display equipment, patient and\nequipment supports, components and accessories. The\nPhilips CT 3500 is indicated for head, whole body, cardiac\n(Cardiac Calcium Scoring) and vascular X-ray Computed\nTomography applications in patients of all ages.\nThese scanners are intended to be used for diagnostic\nimaging and for low dose CT lung cancer screening for the\nearly detection of lung nodules that may represent cancer*.\nThe screening must be performed within the established\ninclusion criteria of programs / protocols that have been\napproved and published by either a governmental body or\nprofessional medical society.\n*Please refer to clinical literature, including the results of the\nNational Lung Screening Trial (N Engl J Med 2011;\n365:395-409) and subsequent literature, for further\ninformation."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p11-t0","doc_id":"K223311","page_num":11,"bbox":[90.32,72.26,515.47,561.29],"n_rows":2,"n_cols":2,"columns":["","The systems comply with industry guidance and\nperformance standards for Computed Tomography (CT)\nEquipment and Laser products (21 CFR 1020.33 and 21\nCFR 1040.10, respectively).\nThe systems performed a comparison to the predicate\ndevice using these technological characteristics and image\nquality metrics to establish that the subject device is\nsubstantially equivalent to the predicate device for its\nintended use.\nThe systems pass the design verification, design validation\nand consensus standards test as nonclinical tests. The\nsystem verification is conducted against the system\nrequirement specifications (SRS). System verification\nactivities demonstrate the system meet the established\nsystem design input requirements. System requirements\nmay be verified by manual test, automated test,\ninspection/analysis, or any combination of the three. Non-\nClinical design validation testing covered the intended use\nand commercial claims. Validation testing included workflow\nvalidation.\nThe test results demonstrate that the proposed Philips CT\n3500 meets the acceptance criteria and is adequate for its\nintended use. Additionally, the risk management activities\nshow that all risks are sufficiently mitigated, that no new\nrisks are introduced, and that the overall residual risks are\nacceptable."],"rows":[["","The systems comply with industry guidance and\nperformance standards for Computed Tomography (CT)\nEquipment and Laser products (21 CFR 1020.33 and 21\nCFR 1040.10, respectively).\nThe systems performed a comparison to the predicate\ndevice using these technological characteristics and image\nquality metrics to establish that the subject device is\nsubstantially equivalent to the predicate device for its\nintended use.\nThe systems pass the design verification, design validation\nand consensus standards test as nonclinical tests. The\nsystem verification is conducted against the system\nrequirement specifications (SRS). System verification\nactivities demonstrate the system meet the established\nsystem design input requirements. System requirements\nmay be verified by manual test, automated test,\ninspection/analysis, or any combination of the three. Non-\nClinical design validation testing covered the intended use\nand commercial claims. Validation testing included workflow\nvalidation.\nThe test results demonstrate that the proposed Philips CT\n3500 meets the acceptance criteria and is adequate for its\nintended use. Additionally, the risk management activities\nshow that all risks are sufficiently mitigated, that no new\nrisks are introduced, and that the overall residual risks are\nacceptable."],["Summary of Clinical\nData:","The proposed Philips CT 3500 did not require clinical study\nsince substantial equivalence to the legally marketed\npredicate device was proven with the verification/validation\ntesting."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p12-t0","doc_id":"K223311","page_num":12,"bbox":[89.41,97.5,536.46,711.94],"n_rows":6,"n_cols":8,"columns":["Installed Environment Comparison","","","","","","",""],"rows":[["Installed Environment Comparison","","","","","","",""],["","Proposed Philips CT\n3500","","Predicate Device","","Conclusion","Conclusion",""],["","","","Philips Incisive CT","","","",""],["","","","(K212441, K211168)","","","",""],["Installed\nenvironment","In hospital, on trailer","In hospital, on trailer","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["CT on Trailer","Besides installed in\nhospital, the proposed\nPhilips CT 3500 may\nalso be installed on\ntrailer and be\ntransported to\ndesignated locations for\nuse. And Philips CT\n3500 installed on trailer\nhas the same intended\nuse as installed in\nhospital.\nThe design, intended\nuse, fundamental\nscientific technology\nand principal\ntechnological\ncomponents (Tube,\nGenerator, Detector,\ngantry, patient table\nand console) are same\nas the proposed Philips\nCT 3500 in hospital\nexcept for the addition\nof a CT on Trailer Kit to\nsecure the CT system\nin a trailer.\nCT on Trailer Kit\nincludes:\n(cid:1068) Couch vertical lock\nand horizontal lock\nASSY,\n(cid:1068) UPS lock ASSY,\n(cid:1068) Console lock ASSY,","Besides installed in\nhospital, the proposed\nPhilips Incisive CT may\nalso be installed on\ntrailer and be\ntransported to\ndesignated locations for\nuse. And Incisive CT\ninstalled on trailer has\nthe same intended use\nas installed in hospital.\nThe design, intended\nuse, fundamental\nscientific technology\nand principal\ntechnological\ncomponents (Tube,\nGenerator, Detector,\ngantry, patient table\nand console) are same\nas the Philips Incisive\nCT in hospital except\nfor the addition of a CT\non Trailer Kit to secure\nthe CT system in a\ntrailer.\nCT on Trailer Kit\nincludes:\n(cid:1068) Gantry tilt lock\nASSY,\n(cid:1068) Couch vertical lock\nASSY,\n(cid:1068) Couch horizontal\nlock ASSY,","","","The proposed\nPhilips CT 3500\nGantry has no tilt\nfunction. All motion\nparts can be fixed\nby on trailer kit.\nThe design,\nintended use,\nfundamental\nscientific\ntechnology and\nprincipal\ntechnological\ncomponents are\nidentical to the\npredicate device.\nSafety and\neffectiveness are\nnot affected.\nTherefore,\ndemonstrating\nsubstantial\nequivalence.","",""]],"caption_candidate":"Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p13-t0","doc_id":"K223311","page_num":13,"bbox":[89.02,72.98,536.46,242.83],"n_rows":5,"n_cols":8,"columns":["Installed Environment Comparison","","","","","","",""],"rows":[["Installed Environment Comparison","","","","","","",""],["","Proposed Philips CT\n3500","","Predicate Device","","Conclusion","Conclusion",""],["","","","Philips Incisive CT","","","",""],["","","","(K212441, K211168)","","","",""],["","(cid:1068) Isolation\nTransformer lock\nASSY","(cid:1068) UPS lock Kits,\n(cid:1068) Console fixation\ndevice,\n(cid:1068) Isolation\nTransformer lock\nKits","","","","",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p13-t1","doc_id":"K223311","page_num":13,"bbox":[89.02,268.94,536.46,701.14],"n_rows":7,"n_cols":8,"columns":["Scan characteristics Comparison","","","","","","",""],"rows":[["Scan characteristics Comparison","","","","","","",""],["","Proposed Philips CT\n3500","","Predicate Device","","Conclusion","Conclusion",""],["","","","Philips Incisive CT","","","",""],["","","","(K212441, K211168)","","","",""],["No. of Slices","32/64","64/128","","","The Philips CT\n3500 uses the\nsame DMS (20mm)\nas the Philips\nIncisive CT to\nsupport 64 slices.\nTherefore,\ndemonstrating\nSubstantial\nequivalence.","",""],["Scan Modes","Surview\nAxial Scan\nHelical Scan","Surview\nAxial Scan\nHelical Scan","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Minimum Scan\nTime","0.5 sec for 360°\nrotation","0.35 sec for 360°\nrotation","","","The proposed\nPhilips CT 3500\nrotation speed\nlower than Philips\nIncisive CT.\nSafety and\neffectiveness are\nnot affected.","",""]],"caption_candidate":"Kits","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p14-t0","doc_id":"K223311","page_num":14,"bbox":[88.88,72.98,536.52,707.38],"n_rows":11,"n_cols":8,"columns":["Scan characteristics Comparison","","","","","","",""],"rows":[["Scan characteristics Comparison","","","","","","",""],["","Proposed Philips CT\n3500","","Predicate Device","","Conclusion","Conclusion",""],["","","","Philips Incisive CT","","","",""],["","","","(K212441, K211168)","","","",""],["","","","","","Therefore,\ndemonstrating\nsubstantial\nequivalence.","",""],["Image (Spatial)\nResolution","High resolution\nmode:16 lp/cm\nStandard resolution\nmode: 13 lp/cm","High resolution mode:\n16 lp/cm\nStandard resolution\nmode: 13 lp/cm","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Image Noise","≤0.18% at 120kV,\nCTDI\ncenter\n(head) ≤ 33mGy, 10mm\nimage thickness,\niDose4","≤0.18% at 120kV,\nCTDI\ncenter\n(head) ≤ 33mGy, 10mm\nimage thickness, iDose4","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Slice\nThicknesses","Helical:\n0.67mm – 5mm\nAxial:\n0.625mm – 10.0mm","Helical:\n0.67mm – 5mm\nAxial:\n0.625mm-10.0mm","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Scan Field of\nView","Up to 500 mm","Up to 500 mm","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Image Matrix","Up to 1024 * 1024","Up to 1024 * 1024","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Display","1920 * 1080","1920 * 1080","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p15-t0","doc_id":"K223311","page_num":15,"bbox":[89.4,72.98,536.65,429.38],"n_rows":7,"n_cols":8,"columns":["Scan characteristics Comparison","","","","","","",""],"rows":[["Scan characteristics Comparison","","","","","","",""],["","Proposed Philips CT\n3500","","Predicate Device","","Conclusion","Conclusion",""],["","","","Philips Incisive CT","","","",""],["","","","(K212441, K211168)","","","",""],["Host\nInfrastructure","Windows 10","Windows 10","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Communication","Compliance with\nDICOM","Compliance with\nDICOM","","","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Dose Reporting\nand\nManagement","Compliance with NEMA\nXR25, XR26, XR28 and\nXR29","Compliance with NEMA\nXR25, XR28 and XR29","","","Compliance with\nmore NEMA\nstandard.\nSafety and\neffectiveness are\nnot affected.\nTherefore,\nsubstantially\nequivalent.","",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p15-t1","doc_id":"K223311","page_num":15,"bbox":[89.4,455.24,536.65,712.9],"n_rows":4,"n_cols":5,"columns":["Imaging features Comparison","","","",""],"rows":[["Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["2D Viewer","In 2D Viewer mode operator can\nreview original axial images as\nacquired by the scanner.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["MPR","Use the MPR mode to view\nthree-plane orthogonal images.\nIn this mode, the three shown\nplanes can be easily correlated.\nThree orthogonal cut planes are\nshown:\n• Axial Orientation","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"equivalent.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p16-t0","doc_id":"K223311","page_num":16,"bbox":[89.19,72.56,537.06,718.18],"n_rows":8,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["","","• Coronal Orientation\n• Sagittal Orientation","","",""],["3D (Volume\nmode)","","The volume mode is used to\ndisplay CT scanner data in a full\nvolume image. It provides basic\ntools for image editing and\ngeneration of cine movies.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Virtual\nEndoscope\n(Endo)","","The CT Endo viewer is a review\nfunction that allows you to\nperform a general flythrough of\nany suitable anatomical\nstructure that is filled with air or\nwith contrast material, including\ngeneral vessels, cardiac\nvessels, the bronchus, and the\ncolon.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Image matrix","","The Image Matrix parameter\nsets the number of pixels that\nthe reconstructed image will\ncontain. Select 512, 768, or\n1024.","Yes","Identical\nTherefore,\nsubstantially\nequivalent.",""],["O-MAR","","O-MAR stands for orthopedic\nmetal artifact reduction. This\npost processing capability\nreduces metal induced artifacts\nand is directed for large\northopedics metals that cause\nphoton starvation of the rays\nthat pass through the metal\nobject.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["DoseRight\nIndex\n(DRI)","","DoseRight Index (DRI) is\naccording to the current scan\nsite and body size of the patient,\nthe mAs suitable for the patient\nis automatically recommended,\nso that the image quality can\nmeet the requirements of the\ndiagnosis, and the radiation\ndose of the patient can be\nreduced as far as possible.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p17-t0","doc_id":"K223311","page_num":17,"bbox":[89.23,72.56,537.05,718.42],"n_rows":6,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["3D-DOM","","3D-DOM combines angular and\nlongitudinal information to\nmodulate dose in three\ndimensions. Personalizes dose\nfor each patient by automatically\nsuggesting tube current settings\naccording to the estimated\npatient diameter in the scan\nregion. Angular dose modulation\nvaries the tube current during\nhelical scans according to\nchanges in patient shape\n(eccentricity) and tissue\nattenuation as the tube rotates.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Precise\nPlanning","","Precise Planning can\nautomatically adjust the scan\nrange of subsequent Axial or\nHelical scan series, based on\nthe Surview Image.","iPlanning","Only the name\nchanges.\nSafety and\neffectiveness\nare not\naffected.\nTherefore,\nsubstantially\nequivalent.",""],["Oblique MPR","","Support the adjustment of\nsagittal / coronal image\nconstruction in the planned\nscanning phase, and finally\nobtain the adjusted tilted\nmultiplane image.\nOn the basis of Insert MPR,\nsurface reconstruction is carried\nout by interpolation of axial\nimage and corresponding tilted\nimage is generated.","Insert MPR","On the basis of\nInsert MPR,\nAdded the ability\nfor users to tilt\nthe MPR image\nSafety and\neffectiveness\nare not\naffected.\nTherefore,\nsubstantially\nequivalent.",""],["OnPlan","","OnPlan (Touch Panel)\nOnPlan is a brand-new gantry\noperational touch panel located\non both sides of the gantry. The\nOnPlan gantry controls are used\nto active the laser marker,\ncontrols patient table","iStation (Touch\nPanel)","Only the name\nchanges.\nSafety and\neffectiveness\nare not\naffected.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p18-t0","doc_id":"K223311","page_num":18,"bbox":[89.18,72.56,537.06,701.38],"n_rows":9,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["","","movements, display patient\ninformation and images, and\nconduct a new patient exam.","","Therefore,\nsubstantially\nequivalent.",""],["Precise Spine","","Precise Spine\nPrecise Spine application\nenables the system to assist the\nuser to identify the lumbar disk\nspace automatically and\ncreating a batch based on the\nprotocol selected.","iBatch\niBatch application\nenables the\nsystem to assist\nthe user to identify\nthe lumbar disk\nspace\nautomatically and\ncreating a batch\nbased on the\nprotocol selected.","Only the name\nchanges.\nSafety and\neffectiveness\nare not\naffected.\nTherefore,\nsubstantially\nequivalent.",""],["Bolus Tracking","","The Bolus tracking function\nmaximizes the efficiency of CT\nscans that are enhanced\nthrough the use of a contrast\nagent. This is done by preceding\nthe Clinical scan with Locator\nand Tracker scans.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Spiral Auto\nStart (SAS)","","This feature enable the usage of\nthe injector scan trigger.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Filming","","The Filming application is used\nfor viewing, rearranging,\nwindowing and zooming images\nprior to sending them to be\nprinted.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Worklist","","The Worklist displays patient\ninformation provided by the\nHIS/RIS.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["MPPS","","If the patient is from the Worklist\nand the MPPS function is\nenabled, feedback regarding the","Yes","Identical.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p19-t0","doc_id":"K223311","page_num":19,"bbox":[89.21,72.56,537.05,694.66],"n_rows":7,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["","","study status of the patient can\nbe sent to the hospital HIS/RIS.","","Therefore,\nsubstantially\nequivalent.",""],["Reporting","","The Reporting package allows\nyou to create customized\nreports using pre-formatted\ntemplates.\nA template is a specially\ndesigned formatting document\nthat places the analytical\ninformation and images that you\nsend from an application into an\norganized report which can be\nprinted and saved.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["CCT\n(Continuous\nCT)","","Continuous CT (CCT) is a\nscanning mode that allows the\nphysician to perform extended,\nlow-dose scans while\nperforming a biopsy.\nThe resulting images display on\na remote monitor in the scan\nroom, providing visual feedback\nduring the biopsy.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Brain\nPerfusion","","Brain Perfusion is a blood flow\nimaging application that\nanalyzes the uptake of injected\ncontrast in order to determine\nperfusion-related information\nabout one or more regions of\ninterest.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Dental\nplanning","","Dental application uses to\ncreate true-size (life size) film\nimages of the mandible and\nmaxilla for assisting oral\nsurgeons in planning\nimplantation of prostheses.\nUsing a special dental planning\nprocedure, and the images will\nbe created from this scan which","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p20-t0","doc_id":"K223311","page_num":20,"bbox":[89.21,72.56,537.05,713.62],"n_rows":7,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["","","can be input into the Dental\nplanning application.","","",""],["Axial Gating","","Axial prospective gating uses an\nexternal ECG gating system to\nsynchronize individual axial\nscans with the patient’s\nheartbeat. The ECG-triggered\nscans significantly minimize\nheart-motion artifacts.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Parallel\nworkflow","","The system support Parallel\nworkflow using Dual monitor as\nbelow:\n- main monitor: Patients, scan,\nservice, \"show all\" for scan\nplanning, Help.\n- extend monitor: Completed,\nviewers, Analysis, recon, filming,\nreport","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Precise image","","Precise image reconstruction is\na recon mode where the system\nuses a trained deep learning\nneural network to generate\nnoise reduction images and\nimprove low contrast\ndetectability with reduced dose\ncompared with standard FBP\nrecon mode.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Precise\nposition","","Precise Position is a camera-\nbased workflow designed to\nassist with positioning the\npatient automatically from\nconsole or OnPlan, it can:\n• automatically select patient\norientation.\n• automatically set vertical\ncentering & positioning of the\npatient to the Surview start and\nend positions.\n• support editing Surview start &\nend range and scan direction.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p21-t0","doc_id":"K223311","page_num":21,"bbox":[89.19,72.56,537.06,701.62],"n_rows":8,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["Direct results","","Direct Result-With Direct Result\nthe user is able to choose a\ndesired result during scan\nplanning phase and get the\nresult for diagnosis without\nfurther intervention.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["CT\nColonoscopy\n(CTC)","","CT Colonoscopy (CTC)\napplication enables fast and\neasy visualization of colon\nscans, using acquired CT\nimages.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Vessel\nAnalysis (VA)","","Vessel Analysis (VA) offers a\nset of tools for general vascular\nanalysis. With VA the user can\neasily remove bone, and extract\nvessels. User also can perform\nmeasurements such as\nintraluminal diameter, cross-\nsectional lumen area, length.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Lung Nodule\nAnalysis (LNA)","","The Lung Nodule Analysis\n(LNA) application assists the\nradiologist with the detection\nand quantification of pulmonary\nnodules and lesions.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Dual Energy","","Dual energy Viewer is an\napplication for review and\nanalysis of CT dual-energy\nscans. Users need to load CT\ndual-energy scan data which is\ntwo series with similar KV. It\nprovides registration function\nand can generate different\nweighted KV images. User can\nuse the tools to separate\nmaterials.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Precise\nintervention","","In Precise Intervention viewer\nthere are several tools, they will\nhelp you to navigate the needle\nsafely during the intervention.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223311-p22-t0","doc_id":"K223311","page_num":22,"bbox":[89.36,72.56,537.02,484.34],"n_rows":6,"n_cols":6,"columns":["","Imaging features Comparison","","","",""],"rows":[["","Imaging features Comparison","","","",""],["Philips CT\n3500 Features\nName","","Feature description","Predicate Device\nPhilips Incisive\nCT (K212441,\nK211168)","Conclusion\n(Function/\nUser interface/\nWorkflow)",""],["iDose4","","iDose4 is an iterative\nreconstruction technique that\nimproves image quality through\nartifact prevention and\nincreased spatial resolution at\nlow dose.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Cardiac\ncalcium\nscoring","","The Cardiac Calcium Scoring\napplication is used to quantify\nthe buildup of calcium plaque on\nthe walls of the patient's\ncoronary arteries and other\nrelevant locations. The potential\ncalcifications are highlighted by\nthe application during launch.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Adaptive\nFiltering","","Adaptive filters (AF) reduce\npattern noise (streaks) in non-\nhomogenous bodies, improving\noverall image quality.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["Precise Brain","","Precise Brain application for a\nseries of brain tissue slices that\nare parallel or vertical in the\nplane of the cranial CT scan.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223325-p7-t0","doc_id":"K223325","page_num":7,"bbox":[118.88,105.24,526.5,334.28],"n_rows":9,"n_cols":3,"columns":["ITEM","Proposed Device\nuMI Panorama","Predicate Device\nuMI 780 (K172143)"],"rows":[["ITEM","Proposed Device\nuMI Panorama","Predicate Device\nuMI 780 (K172143)"],["Patient bore size","760mm","700mm"],["PET System","Scintillator material: LYSO\nNumber of detector rings:\n• 96 (uMI Panorama 28)\n• 120 (uMI Panorama 35)\nAxial FOV:\n• 280mm (uMI Panorama 28)\n• 350mm (uMI Panorama 35)","Scintillator material: LYSO\nNumber of detector rings: 112\nAxial FOV: 300mm"],["CT System","uCT ATLAS Astound (K223028)","uCT 780 (K172135)"],["Maximum table load","318kg","250kg"],["Post-processing software","",""],["uExcel Iterative","Yes","No"],["uExcel DPR","Yes","No"],["uExcel Focus","Yes","No"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223343-p8-t0","doc_id":"K223343","page_num":8,"bbox":[72.67,71.04,327.65,486.79],"n_rows":2,"n_cols":2,"columns":["","liver, knee, hip, ankle,\nshoulder, hand and lumbar\nspine. All publications have\nconcluded that the work-in-\nprogress package and the\nreconstruction algorithm can\nbe beneficially used for clinical\nroutine imaging. No cases\nhave been reported where the\nnetwork led to a\nmisinterpretation of the images\nor where anatomical\ninformation has been altered,\nsuppressed, or introduced. In\nmost cases the new algorithm\nhas been used to acquire\nimages faster and significant\ntime savings are reported."],"rows":[["","liver, knee, hip, ankle,\nshoulder, hand and lumbar\nspine. All publications have\nconcluded that the work-in-\nprogress package and the\nreconstruction algorithm can\nbe beneficially used for clinical\nroutine imaging. No cases\nhave been reported where the\nnetwork led to a\nmisinterpretation of the images\nor where anatomical\ninformation has been altered,\nsuppressed, or introduced. In\nmost cases the new algorithm\nhas been used to acquire\nimages faster and significant\ntime savings are reported."],["Reference\nstandard","The acquired datasets\nrepresent the ground truth for\nthe training and validation.\nInput data was retrospectively\ncreated from the ground truth\nby data manipulation and\naugmentation. This process\nincludes further under-\nsampling of the data by\ndiscarding k-space lines,\nlowering of the SNR level by\naddition of noise and mirroring\nof k-space data."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223343-p8-t1","doc_id":"K223343","page_num":8,"bbox":[72.67,582.45,501.96,783.1],"n_rows":12,"n_cols":4,"columns":["","","Product",""],"rows":[["","","Product",""],["Predicate Device","FDA Clearance Number and Date","","Manufacturer"],["","","Code",""],["","","",""],["MAGNETOM Amira with\nsyngo MR XA12M","K183221, cleared on February 14, 2019","LNH,\nLNI,\nMOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."],["MAGNETOM Sempra with\nsyngo MR XA12M","K183221, cleared on February 14, 2019","LNH,\nLNI,\nMOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."],["","","Product",""],["Reference Device","FDA Clearance Number and Date","","Manufacturer"],["","","Code",""],["","","",""],["MAGNETOM Sola with\nsyngo MR XA51A","K221733, cleared on September 13, 2022","LNH,\nLNI,\nMOS","Siemens Healthcare\nGmbH"],["MAGNETOM Free.Max with\nsyngo MR XA50A","K220575, cleared on June 24, 2022","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."]],"caption_candidate":"Table 2. Predicate devices and reference devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223343-p9-t0","doc_id":"K223343","page_num":9,"bbox":[72.54,265.51,498.66,567.88],"n_rows":18,"n_cols":13,"columns":["Feature","","","Subject Device","","Predicate Device","","","Subject Device","","Predicate Device","",""],"rows":[["Feature","","","Subject Device","","Predicate Device","","","Subject Device","","Predicate Device","",""],["","","","MAGNETOM\nAmira with\nsoftware syngo\nMR XA50M","","","MAGNETOM","","MAGNETOM\nSempra with\nsoftware syngo\nMR XA50M","","","MAGNETOM",""],["","","","","","","Amira with","","","","","Sempra with",""],["","","","","","","software syngo","","","","","software syngo",""],["","","","","","","MR XA12M","","","","","MR XA12M",""],["","","","","","","(K183221)","","","","","(K183221)",""],["","Magnet","","same","","","","","same","","","",""],["","System","","","","","","","","","","",""],["","RF System","","","same","","","","","same","","",""],["","Transmission","","same","","","","","same","","","",""],["","Technique","","","","","","","","","","",""],["","Gradient","","same","","","","","same","","","",""],["","System","","","","","","","","","","",""],["","Patient Table","","","same","","","","","same","","",""],["Computer","","","same","","","","","same","","","",""],["Coils","","","same","","","","","New coils:\n-Flex Large 8,\n-Flex Small 8,\n-Flex 8 Coil\nInterface","","-","",""],["","Other HW","","same","","","","","same","","","",""],["","components","","","","","","","","","","",""]],"caption_candidate":"Table 3. Hardware Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223343-p11-t0","doc_id":"K223343","page_num":11,"bbox":[72.74,280.34,503.62,358.25],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for\ncoils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance\nDiagnostic Devices"]],"caption_candidate":"devices and can be reused for the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223347-p6-t0","doc_id":"K223347","page_num":6,"bbox":[72.26,202.32,539.74,715.68],"n_rows":5,"n_cols":4,"columns":["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],"rows":[["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],["Classification\nname","Image Acquisition And/ Or\nOptimization Guided By\nArtificial Intelligence","Image Acquisition And/ Or\nOptimization Guided By\nArtificial Intelligence","Identical"],["Product Code","QJU","QJU","Identical"],["Intended Use","The Caption Guidance\nsoftware is intended to\nassist medical\nprofessionals in the\nacquisition of cardiac\nultrasound images.\nCaption Guidance\nsoftware is an accessory\nto compatible general\npurpose diagnostic\nultrasound systems","The UltraSight AI\nGuidance software is\nintended to assist medical\nprofessionals in the\nacquisition of cardiac\nultrasound images.\nUltraSight AI Guidance\nsoftware is an accessory\nto compatible general\npurpose diagnostic\nultrasound systems","Identical"],["Indications for\nuse","Caption Guidance\nsoftware is indicated for\nuse in two-dimensional\ntransthoracic\nechocardiography (2D-\nTTE) for adult patients,\nspecifically in the\nacquisition of the following\nstandard views:\nParasternal Long-Axis\n(PLAX), Parasternal\nShort-Axis at the Aortic\nValve (PSAX-AV),\nParasternal Short-Axis at\nthe Mitral Valve (PSAX-\nMV), Parasternal Short-\nAxis at the Papillary\nMuscle (PSAX-PM),\nApical 4-Chamber (AP4),\nApical 5-Chamber (AP5),","UltraSight AI Guidance\nsoftware is indicated for\nuse in two-dimensional\ntransthoracic\nechocardiography (2D-\nTTE) for adult patients,\nspecifically in the\nacquisition of the following\nstandard views:\nParasternal Long-Axis\n(PLAX), Parasternal\nShort-Axis at the Aortic\nValve (PSAX-AV),\nParasternal Short-Axis at\nthe Mitral Valve (PSAX-\nMV), Parasternal Short-\nAxis at the Papillary\nMuscle (PSAX-PM),\nApical 4-Chamber (AP4),\nApical 5-Chamber (AP5),","Similar\nSince the use of the\nUltraSight AI Guidance\nand its impact to expert\nsonographers has not\nbeen evaluated, this\nusers’ population is\nexcluded from the device’s\nintended users."]],"caption_candidate":"A table comparing the key features of the subject and the predicate devices is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223347-p7-t0","doc_id":"K223347","page_num":7,"bbox":[72.27,79.28,539.73,708.0],"n_rows":4,"n_cols":4,"columns":["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],"rows":[["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],["","Apical 2-Chamber (AP2),\nApical 3-Chamber (AP3),\nSubcostal 4-Chamber\n(SubC4), and Subcostal\nInferior Vena Cava (SC-\nIVC).","Apical 2-Chamber (AP2),\nApical 3-Chamber (AP3),\nSubcostal 4-Chamber\n(SubC4), and Subcostal\nInferior Vena Cava (SC-\nIVC).\nThe UltraSight AI\nGuidance is not intended\nto be used by\nSonographers.",""],["Intended user","Medical professionals\n(including expert\nsonographers)","Medical professionals (not\nincluding expert\nsonographers)","Substantially Equivalent:\nIt should be noted that\nthe intended users’\npopulation of the\nUltraSight AI Guidance is\nslightly narrower than the\npredicate and does not\ninclude sonographers.\nHowever, the intended\nuser population of the\nUltraSight AI Guidance is\na subset of the broader\nuser population for the\npredicate; thus, the\nintended use and\nindications are fully\nencompassed within the\npredicate indications.\nTherefore, the first\ncriterion for a finding of\nsubstantial equivalence\nis satisfied."],["Compatible\nUltrasound\nsystem and\nprobe","The uSmart 3200t Plus\nultrasound system with the\n3200t-compatible Terason\n4V2A linear phased array\nprobe","Philips Lumify With S4-1\nprobe and Samsung Tab\nS6 and S7 tablets","Substantially Equivalent:\nBoth the predicate device\nand the proposed device\nfunction as a software\naccessory to a cleared to\nmarket ultrasound device.\nBoth ultrasound devices\nare cleared for the\ndiagnostic ultrasound\nclinical application of\nacquiring cardiac images"]],"caption_candidate":"UltraSight Ltd. SECTION 5 SUMMARY Page: 5-4 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223347-p8-t0","doc_id":"K223347","page_num":8,"bbox":[72.26,79.28,539.74,707.16],"n_rows":5,"n_cols":4,"columns":["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],"rows":[["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],["","","","of adult patients. Since\nboth ultrasound devices\nare cleared for the\nrequired clinical use, the\nuse of different ultrasound\ndevices does not raise\nnew questions of safety\nand/or effectiveness."],["Clinical Features","","",""],["Image\nacquisition\nguidance","Prescriptive Guidance:\nThe prescriptive guidance\nfeature in Caption\nGuidance provides\ndirection to the user to\nemulate how a\nsonographer would\nmanipulate the transducer\nto acquire the optimal view","Probe Guidance: The\nprobe guidance feature\nprovides graphic on-\nscreen instructions for\nthe user to emulate how\na sonographer would\nmanipulate the\ntransducer to acquire the\ntarget cardiac view.","Substantially Equivalent:\nWhile the user interface is\nslightly different, the\nfunctionality and type of\nguidance provided to the\nuser will be the same.\nSpecifically, both devices\nprovide to the user\ninstructions on how to\nmanipulate the probe\n(translational, tilt and\nrotation guidance cues)\ntogether with real-time\nfeedback on the\nexpected diagnostic\nquality of the resulting clip\nto direct the user to a\nprobe position that will\nenable acquisition of a\ndiagnostic quality clip.\nHence, this difference\ndoes not raise new\nquestions of safety and/or\neffectiveness."],["Real time\nfeedback on\nimage quality","Quality Meter: a real-time\nfeedback from the Quality\nMeter advises the user on\nthe expected diagnostic\nquality of the resulting clip,\nsuch that the user can\nmake decisions to further\noptimize the quality, for\nexample by following the\nprescriptive guidance\nfeature below.","Quality Bar: a real-time\nquality bar providing\nfeedback on the clip’s\nquality advises the user on\nthe expected diagnostic\nquality of the current\nimage. This information\ncan be used by the users\nto assess how close they\nare to capturing a\ndiagnostic-quality image.","Substantially Equivalent"]],"caption_candidate":"UltraSight Ltd. SECTION 5 SUMMARY Page: 5-5 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223347-p9-t0","doc_id":"K223347","page_num":9,"bbox":[72.26,79.28,539.74,548.52],"n_rows":5,"n_cols":4,"columns":["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],"rows":[["Parameters","Caption Guidance\nDEN190040","Proposed UltraSight AI\nGuidance","Conclusion"],["","","",""],["Automatic\ncapture of clips\nwith predicted\ndiagnostic\nquality","Auto-Capture: The\nCaption Guidance Auto-\nCapture feature triggers\nan automatic capture of a\nclip when the quality is\npredicted to be diagnostic,\nemulating the way in\nwhich a sonographer\nknows when an image is\nof sufficient quality to be\ndiagnostic and records it.","None","Substantially Equivalent:\nThis feature is not\nprovided; the UltraSight\nsoftware provides to the\nuser the view detection\nand quality bar features\nwhich enable any user to\nclearly identify when a\ndiagnostic quality image\nhas been achieved and to\nmanually save the clip."],["Retrospectively\nrecording of\nhighest quality\nclip","Save Best Clip: This\nfeature continually\nassesses clip quality while\nthe user is scanning and,\nin the event that the user\nis not able to obtain a clip\nsufficient for Auto-\nCapture, the software\nallows the user to\nretrospectively record the\nhighest quality clip\nobtained so far, mimicking\nthe choice a sonographer\nmight make when\nrecording an exam.","None","Substantially Equivalent:\nAlthough this feature is not\nprovided, the\nUltraSight software\nprovides to the user the\nview detection and quality\nbar features which enable\nany user to clearly identify\nwhen a diagnostic quality\nhas been achieved and to\nmanually save the clip."],["Deep Learning\nBased\nAlgorithm","Yes","Yes","Substantially Equivalent"]],"caption_candidate":"UltraSight Ltd. SECTION 5 SUMMARY Page: 5-6 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223347-p10-t0","doc_id":"K223347","page_num":10,"bbox":[72.38,396.05,539.88,489.21],"n_rows":7,"n_cols":4,"columns":["Phase","Algorithm development","Performance tests for Quality Bar","Performance test for View\nDetection and Guidance tests"],"rows":[["Phase","Algorithm development","Performance tests for Quality Bar","Performance test for View\nDetection and Guidance tests"],["","","",""],["Number of","580","312","75"],["subjects","","",""],["Number of","5 million frames\nof ultrasound images","5,800 clips","2.3 million frames\nof ultrasound images"],["samples","","",""],["","","",""]],"caption_candidate":"Table 1: Data used for Algorithm Development and Performance Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223387-p6-t0","doc_id":"K223387","page_num":6,"bbox":[111.65,555.19,543.91,683.62],"n_rows":4,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical equipment - Part\n1-2: General requirements for basic safety and essential performance -\nEMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance","",""]],"caption_candidate":"FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223387-p7-t0","doc_id":"K223387","page_num":7,"bbox":[111.62,92.42,543.94,195.62],"n_rows":4,"n_cols":2,"columns":["","of ultrasonic medical diagnostic and monitoring equipment"],"rows":[["","of ultrasonic medical diagnostic and monitoring equipment"],["ISO10993-1","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess"],["ISO14971","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223387-p7-t1","doc_id":"K223387","page_num":7,"bbox":[125.32,298.1,526.89,376.61],"n_rows":3,"n_cols":8,"columns":["","Validation Type","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly detected frames\n×100\nTotal number of frames with nerve","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223387-p7-t2","doc_id":"K223387","page_num":7,"bbox":[125.32,402.53,526.89,451.15],"n_rows":3,"n_cols":11,"columns":["","Validation Type","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","90.3","","","4.8","","","88.6 to 92.0","",""],["Speed (FPS)","","3.54","","","0.13","","","3.47 to 3.61","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223387-p7-t3","doc_id":"K223387","page_num":7,"bbox":[125.32,477.07,526.89,582.19],"n_rows":8,"n_cols":12,"columns":["","","","","Females","","","Males","","","Total",""],"rows":[["","","","","Females","","","Males","","","Total",""],["Number of Subjects","","","13","","","5","","","18","",""],["Number of Images","","","1,168","","","978","","","2,146","",""],["Age range","","","32~68","","","22~50","","","22~68","",""],["Average age","","","45.7","","","35.0","","","42.7","",""],["BMI range","","","16~27.1","","","31.5","","","16~31.5","",""],["Average BMI","","","20.5","","","31.5","","","21.5","",""],["Ethnicity","","","All Koreans","","","","","","","",""]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223396-p5-t0","doc_id":"K223396","page_num":5,"bbox":[78.13,341.18,544.43,717.47],"n_rows":5,"n_cols":3,"columns":["Parameter","Imbio RV/LV Software\nK203256 - Predicate Device","Rapid RV/LV – Subject Device\nK223396"],"rows":[["Parameter","Imbio RV/LV Software\nK203256 - Predicate Device","Rapid RV/LV – Subject Device\nK223396"],["Product Code","QIH","QIH"],["Regulation","21 CFR §892.2050","21 CFR §892.2050"],["Intended Use/\nIndications for\nUse","The Imbio RV/LV Software\ndevice is designed to measure\nthe maximal diameters of the\nright and left ventricles of the\nheart from a volumetric CTPA\nacquisition and report the ratio\nof those measurements. RV/LV\nanalyzes cases using an artificial\nintelligence algorithm to\nidentify the location and\nmeasurements of the ventricles.\nThe RV/LV software provides\nthe user with annotated images\nshowing ventricular\nmeasurements. Its results are\nnot intended to be used on a\nstand-alone basis for clinical\ndecision-making or otherwise\npreclude clinical assessment of\nCTPA cases.","The Rapid RV/LV software\ndevice is designed to measure the\nmaximal diameters of the right\nand left ventricles of the heart\nfrom a volumetric CTPA\nacquisition and report the ratio of\nthose measurements for adults.\nRapid RV/LV analyzes cases\nusing machine learning\nalgorithms to identify locations\nand measurements of the\nventricles. The Rapid RV/LV\ndevice provides the user with\nannotated images showing\nventricular measurements. Its\nresults are not intended to be used\non a stand-alone basis for clinical\ndecision-making or otherwise\npreclude clinical assessment of\nCTPA cases."],["Input Data\nRequirements","Non-gated, CT\nPulmonary","Same"]],"caption_candidate":"submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223396-p6-t0","doc_id":"K223396","page_num":6,"bbox":[78.14,76.58,544.42,275.27],"n_rows":8,"n_cols":3,"columns":["","Angiography images",""],"rows":[["","Angiography images",""],["DICOM\nCompliance","Yes, using CTPA","Same"],["LV Segmentation","Yes","Same"],["RV Segmentation","Yes","Same"],["Diameter\nMeasurements","Yes – Automated","Same"],["Fully Automated\nSegmentation","Yes","Same"],["Interface","Command Line","Command Line"],["Outputs","Reports, DICOM Secondary\nCapture Series","Reports, DICOM Secondary\nCapture Series"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223424-p4-t0","doc_id":"K223424","page_num":4,"bbox":[76.3,198.37,540.17,673.17],"n_rows":7,"n_cols":2,"columns":["Date:","July 7, 2023"],"rows":[["Date:","July 7, 2023"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact Person:","Yonghui Han\nSenior Regulatory Affairs Leader\nGE HealthCare\n(+1) (262)225-1914\nYonghui.Han@ge.com"],["Secondary Contact Person:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE HealthCare\nTel: (+1) (262)424-7774\nEmail: Elizabeth.Mathew@ge.com"],["Device Trade Name:","Spine Auto Views"],["Common/Usual Name:","Spine Auto Views"],["Primary Regulation Number:\nPrimary Product Code:\nSecondary Product Code:\nClassification:","Computed Tomography X-Ray System (21 CFR 892.1750)\nJAK\nQIH\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223424-p6-t0","doc_id":"K223424","page_num":6,"bbox":[53.95,521.2,585.28,687.7],"n_rows":2,"n_cols":4,"columns":["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],"rows":[["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],["CT Spine Labeling\nalgorithm\n(Vertebrae\nDetection and\nVertebrae Labels)","Yes","Yes","Identical"]],"caption_candidate":"Table 5.1: Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223424-p7-t0","doc_id":"K223424","page_num":7,"bbox":[53.88,120.95,585.26,718.2],"n_rows":4,"n_cols":4,"columns":["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],"rows":[["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],["Disc Detection\nalgorithm\n(Disc Position, Disc\nOrientation & Disc\nLabels)","Not available","Yes","Substantially\nEquivalent.\nSpine Auto Views\nintroduces a new deep\nlearning Disc detection\nalgorithm which can\ndetect discs positions,\nplanes/orientations\nand generate disc\nlabels."],["Image Display\nFormats","Traditional reformat\norientations (axial, coronal,\nsagittal)","Traditional reformat orientations\n(axial, coronal, sagittal)","Identical"],["","Curved coronal and curved\nsagittal views of the spine\nas well as oblique axial\nviews perpendicular to the\n3D curved trace.","Curved coronal and curved sagittal\nviews of the spine as well as oblique\naxial views through the\nintervertebral spaces.","Substantially\nEquivalent\nBoth the subject device\nand predicate device\ncan output curved\ncoronal and curved\nsagittal views and\noblique axial view.\nHowever, the\nmethodology in which\nthese reformat series\nare generated are\ndifferent between the\nsubject device and\npredicate device.\nFor the curved\nreformats, Bone VCAR\nuses the centerline\ntraced through the\nvertebrae centers;\nSpine Auto Views use\nthe centerline traced\nthrough the posterior"]],"caption_candidate":"510(k) Premarket Notification Submission -Spine Auto Views","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223424-p8-t0","doc_id":"K223424","page_num":8,"bbox":[53.87,120.95,585.25,719.73],"n_rows":5,"n_cols":4,"columns":["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],"rows":[["Specification","Predicate Device:\nBone VCAR (K183204)","Subject Device:\nSpine Auto Views","Comparison"],["","","","edge of the disc\ncenters.\nFor oblique axial views\ngeneration, the oblique\naxial of Bone VCAR is\nperpendicular to its\ncenterline. Spine Auto\nViews uses the\ncomputed position and\norientation of the discs."],["Field of View","Bone VCAR uses input\nvolume field of view and\nmanually adjusted by the\nuser.","Spine Auto Views uses input volume\nfield of view and additionally has an\noption to automatically set the field\nof view to focus on the spine","Substantially\nEquivalent\nThe subject device has\ntwo configurations:\ninput series field of\nview, or automated\nfield of view focused\non the spine."],["Export","Manual","Automated","Substantially\nEquivalent\nIn the subject device,\nall generated series can\nbe automatically\nexported to DICOM\ndestinations, such as\nPACS, ready for review\nand interpretation."],["Measurement Tool","Access to all standard\nVolume Viewer tools for\nmeasuring distances, areas,\nHounsfield unit values and\nannotating within the\nimages","Not available","Subject device doesn't\nhave a user interface\nand doesn't include\nmeasurement tools.\nSubject device provides\nDICOM reformat\nimages for export."]],"caption_candidate":"510(k) Premarket Notification Submission -Spine Auto Views","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p6-t0","doc_id":"K223426","page_num":6,"bbox":[139.71,84.26,540.1,287.21],"n_rows":17,"n_cols":8,"columns":["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],"rows":[["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],["","","ECHELON OVAL V6.0A (K172110)","ECHELON Synergy","","","",""],["Standards Met","","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5, MS\n8,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5,\nMS 8, MS 14\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","","","",""],["Type and Field\nStrength","","Super-conducting magnet, horizontal bore,\n1.5 Tesla","Super-conducting magnet, horizontal\nbore, 1.5 Tesla","","","",""],["Resonant Frequency","","63.86 MHz","63.86MHz","","","",""],["Bore dimension","","Oval shape with 74cm x 65cm","Circle shape with diameter 70cm","","","",""],["Gradient Strength","","34mT/m","33mT/m","","","",""],["Slew Rate","","150 T/m/sec","130 T/m/sec","","","",""],["Rise Time","","227μsec to 34mT/m","254μsec to 33mT/m","","","",""],["","Audible Noise (MCAN)","","","","","",""],["Ambient","","58 dBA","59.9 dBA","","","",""],["Lpeak","","125 dBA","122.7 dBA","","","",""],["Leq","","117 dB","116.5 dBA","","","",""],["Transmitter channels","","2","1","","","",""],["Peak Envelop Power","","40 kW","18 kW","","","",""],["Duty Cycle","","100% (Gating max), 12.5% at full power","85% (Gating max), 10% at full power","","","",""],["RF receiver channel","","16, 32","32","","","",""]],"caption_candidate":"Table 1 Comparison: Hardware","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p6-t1","doc_id":"K223426","page_num":6,"bbox":[139.71,433.15,409.63,469.03],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"Summary NEMA MS 14.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p6-t2","doc_id":"K223426","page_num":6,"bbox":[132.02,557.11,462.7,716.86],"n_rows":11,"n_cols":3,"columns":["","PREDICATE DEVICE","SUBJECT DEVICE"],"rows":[["","PREDICATE DEVICE","SUBJECT DEVICE"],["","ECHELON OVAL V6.0A (K172110)","ECHELON Synergy"],["Transmit Coil","T/R Body","T/R Body"],["Receiver Coils","WIT Posterior Head/Neck coil, WIT Anterior\nHead attachment\nWIT Posterior Head/Neck coil B","FlexFit Neuro Coil"],["","WIT Torso coil\nWIT Torso coil 12\nWIT Torso coil 8","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B"],["","Extremity coil (Knee)","Extremity Coil"],["","WIT Anterior Neck attachment\nWIT Anterior Neck attachment B","N/A"],["","Hand/Wrist coil","Hand/Wrist Coil"],["","WIT Anterior NV attachment","N/A"],["","Breast","Breast Coil"],["","","Breast Support Kit 2"]],"caption_candidate":"Table 3 Comparison: RF Coils","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p7-t0","doc_id":"K223426","page_num":7,"bbox":[201.41,72.12,462.7,210.38],"n_rows":9,"n_cols":2,"columns":["PREDICATE DEVICE","SUBJECT DEVICE"],"rows":[["PREDICATE DEVICE","SUBJECT DEVICE"],["ECHELON OVAL V6.0A (K172110)","ECHELON Synergy"],["MP coil 140A, B\nMicro coil (S) A, B","Micro Coil A, Micro Coil B"],["Shoulder coil\nShoulder coil 8","Shoulder Coil"],["WIT Spine coil 12\nWIT Spine coil A\nWIT Spine coil 8\nWIT Spine coil B","Spine Coil"],["Foot/Ankle coil","Foot/Ankle Coil"],["Flexible Extremity coil (Long Bone)","Flex M coil, Flex S Coil"],["WIT Cardiac coil","N/A"],["PV coil","N/A"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p7-t1","doc_id":"K223426","page_num":7,"bbox":[138.98,459.55,409.63,495.43],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"・ Breast Support Kit 2 is available for Breast Coil as the accessories.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p7-t2","doc_id":"K223426","page_num":7,"bbox":[72.02,583.79,540.1,713.12],"n_rows":11,"n_cols":9,"columns":["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],"rows":[["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],["","Operating System","","","Going from Windows 7 to Windows 10 IoT","","","See Table 6",""],["","CPU Platform","","","Xeon E3-1275 v6 3.8GHz, Xeon Silver 4210 2CPU, Core i5-7440EQ","","","See Table 6",""],["","Application Software","","","Going from V6.0A to V9.0A","","","See Table 6",""],["Scan Tasks","Scan Tasks","","","Following positioning application of Scan Tasks are added in Auto Pose.","","See Table 6","See Table 6",""],["","","","","-Knee, Shoulder, Spine","","","",""],["","2D Processing Tasks","","","Add the parameter R1 in Parameter Analysis","","","See Table 6",""],["3D Processing Tasks","3D Processing Tasks","","","Following 3D Processing Tasks are added.","","See Table 6","See Table 6",""],["","","","","- Auto VR","","","",""],["","","","","- Auto Clip","","","",""],["","Analysis Tasks","","","None","","","No",""]],"caption_candidate":"Table 5 Comparison: Functionality","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p8-t0","doc_id":"K223426","page_num":8,"bbox":[72.02,72.4,540.1,445.38],"n_rows":34,"n_cols":9,"columns":["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],"rows":[["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],["","Maintenance Tasks","","","None","","","No",""],["","Viewport Tools","","","None","","","No",""],["","Film, Archive Tools","","","None","","","No",""],["","Network Tools","","","None","","","No",""],["Protocol Enhancements","Protocol Enhancements","","","Following protocol enhancement are added.","","See Table 6","See Table 6",""],["","","","","- HiMAR Advanced","","","",""],["","","","","- Double-IR isoFSE","","","",""],["","","","","- AutoExam","","","",""],["","","","","- Auto Table Centering","","","",""],["","","","","- IP-Recon","","","",""],["","","","","- IP-Scan","","","",""],["","","","","- MSDE","","","",""],["","","","","- Golden Random Sampling","","","",""],["","","","","- Deep Learning Reconstruction (DLR)","","","",""],["","","","","- IterativeRAPID","","","",""],["","","","","- Dynamic slice count per study changes 4096 to 200.","","","",""],["","","","","- Presaturation pulses changes 8 to 6.","","","",""],["","","","","- 2D opFSE, 2D opFIR, 2D/3D Prime FSE and 2D/3D Prime FIR are integrated to FSE or FIR in","","","",""],["","","","","“RADAR” category.","","","",""],["","","","","- 3D Soft RSSG and 3D Soft RSSG EPI are added in “Soft Sound” category.","","","",""],["Pulse Sequences","","","","Following Pulse sequence are added.","","","",""],["","","","","- 3D RF Spoiled SARGE (3D Soft RSSG)","","","",""],["","","","","- 3D RF Spoiled SARGE Echo Planar Imaging (3D Soft RSSG EPI)","","","",""],["","","","","- 2D T1Map Sequence (2D T1Map)","","","",""],["","","","","- 2D Phase Sensitive Inversion Recovery (2D PSIR)","","","",""],["","","","","- 2D IR sequence is integrated to SE using with IR-pulse.","","","",""],["","","","","- 2D opFSE, 2D opFIR, 2D/3D Prime FSE and 2D/3D Prime FIR are integrated to FSE or FIR.","","","",""],["","","","","- 2D Time Reversed SARGE (2D TRSG) is not available.","","","",""],["","","","","- 3D Time Reversed SARGE (3D TRSG) is not available.","","","",""],["Powered by Machine\nLearning\n-","","","","Following functions are added as powered by Machine Learning","","","",""],["","","","","⁻AutoPose (Knee, Shoulder, Spine)","","","",""],["","","","","⁻AutoClip","","","",""],["","","","","-Deep Learning Reconstruction (DLR)","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p9-t0","doc_id":"K223426","page_num":9,"bbox":[138.98,219.02,409.03,254.81],"n_rows":2,"n_cols":3,"columns":["☐Manufacturing Process","☐Labeling","☐Technology"],"rows":[["☐Manufacturing Process","☐Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"- 2D Phase Sensitive Inversion Recovery (2D PSIR)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p11-t0","doc_id":"K223426","page_num":11,"bbox":[121.23,136.65,491.15,272.31],"n_rows":9,"n_cols":2,"columns":["","ECHELON OVAL\n(1.5T MRI, FUJIFILM Healthcare Corporation)\nECHELON Smart\n(1.5T MRI, FUJIFILM Healthcare Corporation)\nECHELON Synergy\n(1.5T MRI, FUJIFILM Healthcare Corporation)"],"rows":[["","ECHELON OVAL\n(1.5T MRI, FUJIFILM Healthcare Corporation)\nECHELON Smart\n(1.5T MRI, FUJIFILM Healthcare Corporation)\nECHELON Synergy\n(1.5T MRI, FUJIFILM Healthcare Corporation)"],["Data acquisition MRI system",""],["",""],["Data acquisition site","FUJIFILM Healthcare Corporation and clinical site"],["Subject type","Healthy volunteer and patient"],["","Head, Spine, Cardiac, Breast, Abdomen, Pelvis,\nShoulder, Wrist, Knee, Ankle"],["Anatomical coverage",""],["",""],["Number of cases","110"]],"caption_candidate":"The information about the data in the above evaluations is shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p11-t1","doc_id":"K223426","page_num":11,"bbox":[121.23,357.94,491.15,475.27],"n_rows":8,"n_cols":2,"columns":["","ECHELON Synergy\n(1.5T MRI, FUJIFILM Healthcare Corporation)"],"rows":[["","ECHELON Synergy\n(1.5T MRI, FUJIFILM Healthcare Corporation)"],["Data acquisition MRI system",""],["",""],["Data acquisition site","FUJIFILM Healthcare Corporation"],["Subject type","J apanese healthy volunteers"],["Number of cases","40"],["Anatomical coverage","Brain"],["Scan sequence","3D TOF, 3D Soft TOF"]],"caption_candidate":"shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223426-p11-t2","doc_id":"K223426","page_num":11,"bbox":[121.23,596.7,491.15,691.14],"n_rows":5,"n_cols":4,"columns":["","Spine","Shoulder","Knee"],"rows":[["","Spine","Shoulder","Knee"],["Data acquisition MRI system","ECHELON Synergy\n(1.5T MRI, FUJIFILM Healthcare Corporation)","",""],["Data acquisition site","FUJIFILM Healthcare Corporation","",""],["Subject type","Japanese heal thy volunteers","",""],["Number of cases","146","48","38"]],"caption_candidate":"positioning. The information about the data in the above tests is shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223439-p6-t0","doc_id":"K223439","page_num":6,"bbox":[108.26,118.02,539.82,649.54],"n_rows":11,"n_cols":2,"columns":["Date:","November 10, 2022"],"rows":[["Date:","November 10, 2022"],["Submitter:","GE Healthcare (Tianjin) Company Limited\nNo. 266 Jingsan Road, Tianjin Airport Economic Area\nTianjin, P.R. China 300308"],["Distributor","GE Medical Systems, LLC\n3200 N Grandview BLVD. Waukesha, WI USA 53188"],["Primary Contact\nPerson:","Huande Li\nRegulatory Affairs Manager\nGE Healthcare\nPhone: 86-18101131237\nE-mail: huande.li@ge.com"],["Secondary\nContact Person:","Glen Sabin\nDirector, Regulatory Affairs\nGE Healthcare\nPhone: 262- 5216848\nE-mail: glen.sabin@ge.com"],["Device Trade\nName:","SIGNA™ Victor"],["Common/Usual\nName:","Magnetic Resonance Diagnostic Device"],["Classification\nNames:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH"],["Predicate\nDevice(s):","SIGNA™ Explorer (K143251)\nSIGNA™ Prime (K211980)"],["Reference\nDevice(s):","SIGNA Voyager (K161567)\nSIGNA Artist Evo (K213603)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223439-p7-t0","doc_id":"K223439","page_num":7,"bbox":[108.26,72.24,539.82,661.96],"n_rows":3,"n_cols":2,"columns":["Device\nDescription:","SIGNA™ Victor is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and\nshort scan time. The system uses a combination of time-varying\nmagnet fields (Gradients) and RF transmissions to obtain\ninformation regarding the density and position of elements\nexhibiting magnetic resonance. The system can image in the\nsagittal, coronal, axial, oblique, and double oblique planes, using\nvarious pulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 1.5T superconducting magnet\nwith 60cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],"rows":[["Device\nDescription:","SIGNA™ Victor is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and\nshort scan time. The system uses a combination of time-varying\nmagnet fields (Gradients) and RF transmissions to obtain\ninformation regarding the density and position of elements\nexhibiting magnetic resonance. The system can image in the\nsagittal, coronal, axial, oblique, and double oblique planes, using\nvarious pulse sequences, imaging techniques and reconstruction\nalgorithms. The system features a 1.5T superconducting magnet\nwith 60cm bore size. The system is designed to conform to NEMA\nDICOM standards (Digital Imaging and Communications in\nMedicine)."],["Indications for\nUse","The SIGNA Victor is a whole body magnetic resonance scanner\ndesigned to support high resolution, high signal-to-noise ratio, and\nshort scan times. It is indicated for use as a diagnostic imaging\ndevice to produce axial, sagittal, coronal, and oblique images,\nspectroscopic images, parametric maps, and/or spectra, dynamic\nimages of the structures and/or functions of the entire body,\nincluding, but not limited to, head, neck, TMJ, spine, breast, heart,\nabdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body.\nDepending on the region of interest being imaged, contrast agents\nmay be used. The images produced by SIGNA Victor\nreflect the spatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance.\nThese images and/or spectra when interpreted by a trained\nphysician yield information that may assist in diagnosis."],["Technology:","The SIGNA™ Victor employs the same fundamental scientific\ntechnology as its predicate devices.\nSIGNA™ Victor is built with superconducting magnet, RF transmit\narchitecture, RF receive chain and software application suite."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223439-p8-t0","doc_id":"K223439","page_num":8,"bbox":[108.26,72.24,539.82,680.92],"n_rows":3,"n_cols":2,"columns":["Comparison of\nIndications\nfor Use","The changes in technology do not impact the indications for use.\nThe indications for use have not been changed, other than to\nreflect the SIGNA™ Victor product name.\nTherefore, the intended use is the same as the predicate devices\nin accordance with the FDA’s guidance document “The 510(k)\nProgram: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],"rows":[["Comparison of\nIndications\nfor Use","The changes in technology do not impact the indications for use.\nThe indications for use have not been changed, other than to\nreflect the SIGNA™ Victor product name.\nTherefore, the intended use is the same as the predicate devices\nin accordance with the FDA’s guidance document “The 510(k)\nProgram: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]”, dated 28 July 2014."],["Comparison of\nTechnological\nCharacteristics","Overall, the SIGNA™ Victor employs the same fundamental\nscientific technology as the predicate devices.\nSystem Design: Both SIGNA™ Victor and the predict devices\nincludes the 1.5T magnets, RF transmit architecture, RF receive\nchain and software application suite.\nOperating Principles: The SIGNA™ Victor functions using the\nsame operating principles as the predicate devices.\nMaterials: The SIGNA™ Victor and the predicate devices both\nuse flame retardant materials.\nSafety and Performance Testing: Both the SIGNA™ Victor and\nthe predicate devices comply with the same safety and\nperformance testing (see Determination of Substantial\nEquivalence, below).\nThese technological differences do not raise any different\nquestions regarding safety and effectiveness. Both devices must\naddress questions of whether they provide an adequate level of\nimage quality appropriate for diagnostic use. The performance\ndata described in this submission include results of both bench\ntesting and clinical testing that show the image quality\nperformance of SIGNA™ Victor compared to the predicate\ndevices."],["Determination of\nSubstantial\nEquivalence:","Summary of Non-Clinical Tests:\nThe SIGNA™ Victor and the predicate devices were subject to\nsimilar risk management testing to demonstrate substantial\nequivalence of safety and performance."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223439-p10-t0","doc_id":"K223439","page_num":10,"bbox":[108.26,72.24,539.82,319.94],"n_rows":2,"n_cols":2,"columns":["","2016. The image quality of the SIGNA™ Victor is substantially\nequivalent to that of the predicate devices.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate devices. The SIGNA™ Victor employs\nequivalent technology to the claimed predicate devices.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Victor is substantially equivalent to the predicate devices\nto which it has been compared."],"rows":[["","2016. The image quality of the SIGNA™ Victor is substantially\nequivalent to that of the predicate devices.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are comparable to\nthe claimed predicate devices. The SIGNA™ Victor employs\nequivalent technology to the claimed predicate devices.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended. Therefore, the\nSIGNA™ Victor is substantially equivalent to the predicate devices\nto which it has been compared."],["Conclusion:","In conclusion, GE Healthcare considers the SIGNA™\nVictor to be as safe, as effective, with performance that\nis substantially equivalent to the predicate devices."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p4-t0","doc_id":"K223442","page_num":4,"bbox":[72.26,130.22,544.66,708.58],"n_rows":20,"n_cols":3,"columns":["Date Prepared:","Nov. 14, 2022",""],"rows":[["Date Prepared:","Nov. 14, 2022",""],["Manufacturer:","Philips Medical Systems Nederland B.V.\nVeenpluis 6, 5684 PC, Best, The Netherlands\nEstablishment Registration Number: 3003768277",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","Susan Quick\nRegulatory Affairs Manager\nTelephone: (440) 869-4612\nE-mail: susan.quick@philips.com\nJan van de Kerkhof\nAssociate Director Regulatory Affairs\nTelephone: +31 613300542\nE-mail: jan.van.de.kerkhof@philips.com",""],["Device Name:","MR 5300 and MR 7700 R11 MR Systems",""],["Classification:","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification\nRegulation:","21CFR 892.1000"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary Product Code:","90LNH\n90LNI"],["Primary Predicate\nDevice:","Trade name:","Achieva, Ingenia, Ingneia CX, Ingenia Elition,\nAnd Ingenia Ambition MR Systems R11"],["","Manufacturer:","Philips Medical Systems Nederland B.V."],["","510(k) Clearance:","K213583"],["","Classification\nRegulation:","21CFR 892.1000"],["","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","90LNH\n90LNI"],["Secondary\nPredicate Device:","Trade name:","Ingenia 3.0T, Ingenia 3.0T CX, Ingenia\nElition, and MR 7700 with distributed Multi\nNuclei"],["","Manufacturer:","Philips Medical Systems Nederland B.V."],["","510(k) Clearance:","K213516"]],"caption_candidate":"CFR §807.92.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p5-t0","doc_id":"K223442","page_num":5,"bbox":[72.26,78.61,544.66,361.61],"n_rows":13,"n_cols":3,"columns":["","Classification\nRegulation:","21CFR 892.1000"],"rows":[["","Classification\nRegulation:","21CFR 892.1000"],["","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","90LNH\n90LNI"],["Secondary\nPredicate Device:","Trade name:","MR 5300"],["","Manufacturer:","Philips Medical Systems Nederland B.V."],["","510(k) Clearance:","K212673"],["","Classification\nRegulation:","21CFR 892.1000"],["","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","90LNH\n90LNI"]],"caption_candidate":"Special 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p6-t0","doc_id":"K223442","page_num":6,"bbox":[72.26,78.61,540.1,710.98],"n_rows":2,"n_cols":2,"columns":["","In this 510(k) submission, Philips Medical Systems Nederland B.V. will\nbe addressing the following minor software enhancements to the\nproposed MR 5300 and MR 7700 R11 MR Systems when compared\nto the legally marketed primary predicate, Achieva, Ingenia, Ingenia\nCX, Ingenia Elition and Ingenia Ambition MR Systems R11\n(K213583, 05/16/2022) and the secondary predicate devices Ingenia\n3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700 with\ndistributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021):\n1. SmartSpeed AI\n2. SmartSpeed MotionFree\n3. SmartSpeed 3D FreeBreathing\n4. SmartSpeed Implant\n5. SmartSpeed DWI\n6. MR Workspace\n7. ISP MR Packages\n8. MR Elastography (MR 5300 only)\nThis 510(k) submission will also address the following minor hardware\nenhancements:\n1. Introduction of a graphical processing unit in the host recon\ncomputer for image reconstruction\n2. Additional monitor as part of the operating console\nThe supporting documentation provided for the proposed MR 5300 and\nMR 7700 R11 MR Systems, includes software and hardware\nmodifications that are addressed in test reports for system level\ndevelopment project, Voyager R11.1.\nThe proposed MR 5300 and MR 7700 R11 MR Systems are intended\nto be marketed with the following pulse sequences and coils that are\npreviously cleared by FDA:\n1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils"],"rows":[["","In this 510(k) submission, Philips Medical Systems Nederland B.V. will\nbe addressing the following minor software enhancements to the\nproposed MR 5300 and MR 7700 R11 MR Systems when compared\nto the legally marketed primary predicate, Achieva, Ingenia, Ingenia\nCX, Ingenia Elition and Ingenia Ambition MR Systems R11\n(K213583, 05/16/2022) and the secondary predicate devices Ingenia\n3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700 with\ndistributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021):\n1. SmartSpeed AI\n2. SmartSpeed MotionFree\n3. SmartSpeed 3D FreeBreathing\n4. SmartSpeed Implant\n5. SmartSpeed DWI\n6. MR Workspace\n7. ISP MR Packages\n8. MR Elastography (MR 5300 only)\nThis 510(k) submission will also address the following minor hardware\nenhancements:\n1. Introduction of a graphical processing unit in the host recon\ncomputer for image reconstruction\n2. Additional monitor as part of the operating console\nThe supporting documentation provided for the proposed MR 5300 and\nMR 7700 R11 MR Systems, includes software and hardware\nmodifications that are addressed in test reports for system level\ndevelopment project, Voyager R11.1.\nThe proposed MR 5300 and MR 7700 R11 MR Systems are intended\nto be marketed with the following pulse sequences and coils that are\npreviously cleared by FDA:\n1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils"],["Indications for\nUse:","There are no changes to the indications for use statement, provided\nbelow, of the proposed MR 5300 and MR 7700 R11 MR Systems\nwhen compared to the primary predicate Achieva, Ingenia, Ingenia CX,\nIngenia Elition and Ingenia Ambition MR Systems R11 (K213583,\n05/16/2022).\nPhilips Magnetic Resonance (MR) systems are Medical Electrical\nSystems indicated for use as a diagnostic device."]],"caption_candidate":"Special 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p7-t0","doc_id":"K223442","page_num":7,"bbox":[72.26,78.61,540.1,699.58],"n_rows":2,"n_cols":2,"columns":["","This MR system enables trained physicians to obtain cross-sectional\nimages, spectroscopic images and/or spectra of the internal structure\nof the head, body or extremities, in any orientation, representing the\nspatial distribution of protons or other nuclei with spin.\nImage appearance is determined by many different physical properties\nof the tissue and the anatomy, the MR scan technique applied, and\npresence of contrast agents.\nThe use of contrast agents for diagnostic imaging applications should\nbe performed consistent with the approved labeling for the contrast\nagent.\nThe trained clinical user can adjust the MR scan parameters to\ncustomize image appearance, accelerate image acquisition, and\nsynchronize with the patient’s breathing or cardiac cycle. The systems\ncan use combinations of images to produce physical parameters, and\nrelated derived images. Images, spectra, and measurements of\nphysical parameters, when interpreted by a trained physician, provide\ninformation that may assist diagnosis and therapy planning. The\naccuracy of determined physical parameters depends on system and\nscan parameters and must be controlled and validated by the clinical\nuser.\nIn addition, the Philips MR systems provide imaging capabilities, such\nas MR fluoroscopy, to guide and evaluate interventional and minimally\ninvasive procedures in the head, body and extremities. MR\nInterventional procedures, performed inside or adjacent to the Philips\nMR system, must be performed with MR Conditional or MR Safe\ninstrumentation as selected and evaluated by the clinical user for use\nwith the specific MR system configuration in the hospital. The\nappropriateness and use of information from a Philips MR system for a\nspecific interventional procedure and specific MR system configuration\nmust be validated by the clinical user."],"rows":[["","This MR system enables trained physicians to obtain cross-sectional\nimages, spectroscopic images and/or spectra of the internal structure\nof the head, body or extremities, in any orientation, representing the\nspatial distribution of protons or other nuclei with spin.\nImage appearance is determined by many different physical properties\nof the tissue and the anatomy, the MR scan technique applied, and\npresence of contrast agents.\nThe use of contrast agents for diagnostic imaging applications should\nbe performed consistent with the approved labeling for the contrast\nagent.\nThe trained clinical user can adjust the MR scan parameters to\ncustomize image appearance, accelerate image acquisition, and\nsynchronize with the patient’s breathing or cardiac cycle. The systems\ncan use combinations of images to produce physical parameters, and\nrelated derived images. Images, spectra, and measurements of\nphysical parameters, when interpreted by a trained physician, provide\ninformation that may assist diagnosis and therapy planning. The\naccuracy of determined physical parameters depends on system and\nscan parameters and must be controlled and validated by the clinical\nuser.\nIn addition, the Philips MR systems provide imaging capabilities, such\nas MR fluoroscopy, to guide and evaluate interventional and minimally\ninvasive procedures in the head, body and extremities. MR\nInterventional procedures, performed inside or adjacent to the Philips\nMR system, must be performed with MR Conditional or MR Safe\ninstrumentation as selected and evaluated by the clinical user for use\nwith the specific MR system configuration in the hospital. The\nappropriateness and use of information from a Philips MR system for a\nspecific interventional procedure and specific MR system configuration\nmust be validated by the clinical user."],["Design Features/\nFundamental\nScientific\nTechnology:","The proposed MR 5300 and MR 7700 R11 MR Systems are based on\nthe principle that certain atomic nuclei present in the human body will\nemit a weak relaxation signal when placed in a strong magnetic field\nand excited by a radio signal at the precession frequency. The emitted\nrelaxation signals are analyzed by the system and a computed image\nreconstruction is displayed on a video screen.\nThe principal technological components (magnet, transmit body coil,\ngradient coil, gradient amplifier, RF amplifier and patient support) of the\nproposed MR 5300 and MR 7700 R11 MR Systems are identical to\nthose used in the legally marketed primary predicate, Achieva,\nIngenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR\nSystems R11 (K213583, 05/16/2022) and the secondary predicate\ndevices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700"]],"caption_candidate":"Special 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p8-t0","doc_id":"K223442","page_num":8,"bbox":[72.26,78.61,540.1,713.62],"n_rows":2,"n_cols":2,"columns":["","with distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021).\nThe software R11 used on the proposed MR 5300 and MR 7700 R11\nMR Systems is previously cleared on the legally marketed primary\npredicate, Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia\nAmbition MR Systems R11 (K213583, 05/16/2022)."],"rows":[["","with distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021).\nThe software R11 used on the proposed MR 5300 and MR 7700 R11\nMR Systems is previously cleared on the legally marketed primary\npredicate, Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia\nAmbition MR Systems R11 (K213583, 05/16/2022)."],["Summary of Non-\nClinical\nPerformance Data:","The proposed MR 5300 and MR 7700 R11 MR Systems are in\ncompliance with the following international and FDA-recognized\nconsensus standards:\n• IEC60601-1 Edition 3\n• IEC60601-1-2 Edition 4\n• IEC60601-1-6 Edition 3\n• IEC62366-1 Edition 1\n• IEC60601-1-8 Edition 2\n• IEC60601-2-33 Edition 3\n• IEC 62304 Edition 1\n• NEMA MS-1 2008\n• NEMA MS-4 2010\n• NEMA MS-8 2008\n• NEMA PS 3.1-PS 3.20\n• ISO 14971 Edition 2\n• Device specific guidance document, entitled “Guidance for the\nSubmission Of Premarket Notifications for Magnetic Resonance\nDiagnostic Devices” (issued November 18, 2016 – document\nnumber 340)\n• Guidance for Industry and FDA Staff – Guidance for the\nContent of Premarket Submissions for Software Contained in\nMedical Devices (issued May 11, 2005 – document number\n337)\n• Guidance for Industry and FDA Staff – Content of Premarket\nSubmissions for Management of Cybersecurity in Medical\nDevices (issued October 2, 2014 – document number 1825)\n• Guidance for Industry and FDA Staff – Applying Human Factors\nand Usability Engineering to Medical Devices (issued February\n3, 2016 – document number 1757)\n• Guidance for Industry and FDA Staff – Use of International\nStandard ISO 10993-1, “Biological evaluation of medical\ndevices - Part 1: Evaluation and testing within a risk\nmanagement process” (issued June 16, 2016 – document\nnumber 1811)\n• Guidance for Industry and FDA Staff – Information to Support a\nClaim of Electromagnetic Compatibility (EMC) of Electrically-\nPowered Medical Devices (issued July 11, 2016 – document\nnumber 1400057)\n• Guidance for Industry and FDA Staff – Design Considerations\nand Premarket Submission Recommendations for Interoperable\nMedical Devices (issued September 6, 2017 – document\nnumber 1500015)"]],"caption_candidate":"Special 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223442-p9-t0","doc_id":"K223442","page_num":9,"bbox":[72.26,78.61,540.1,714.94],"n_rows":3,"n_cols":2,"columns":["","Non-Clinical verification and or validation tests have been performed\nwith regards to the intended use, the technical claims, the requirement\nspecifications and the risk management results.\nThe verification and/or validation test results demonstrate that the\nproposed MR 5300 and MR 7700 R11 MR Systems meet the\nacceptance criteria and are adequate for the intended use.\nAdditionally, the risk management activities show that all risks are\nsufficiently mitigated; that new risks that were identified are mitigated to\nan acceptable level; and that the overall residual risk is acceptable.\nTherefore, the proposed MR 5300 and MR 7700 R11 MR Systems are\nsubstantially equivalent to the legally marketed primary predicate,\nAchieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition\nMR Systems R11 (K213583, 05/16/2022) and the secondary predicate\ndevices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700\nwith distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021), in terms of safety and effectiveness."],"rows":[["","Non-Clinical verification and or validation tests have been performed\nwith regards to the intended use, the technical claims, the requirement\nspecifications and the risk management results.\nThe verification and/or validation test results demonstrate that the\nproposed MR 5300 and MR 7700 R11 MR Systems meet the\nacceptance criteria and are adequate for the intended use.\nAdditionally, the risk management activities show that all risks are\nsufficiently mitigated; that new risks that were identified are mitigated to\nan acceptable level; and that the overall residual risk is acceptable.\nTherefore, the proposed MR 5300 and MR 7700 R11 MR Systems are\nsubstantially equivalent to the legally marketed primary predicate,\nAchieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition\nMR Systems R11 (K213583, 05/16/2022) and the secondary predicate\ndevices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700\nwith distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300\n(K212673, 11/19/2021), in terms of safety and effectiveness."],["Summary of\nClinical Data:","The proposed Ingenia MR 5300 and MR 7700 R11 MR Systems did\nnot require a clinical study since substantial equivalence to the legally\nmarketed predicate device was proven with the verification/validation\ntesting."],["Substantial\nEquivalence:\nConclusion:","The proposed MR 5300 and MR 7700 R11 MR Systems and the\nlegally marketed primary predicate, Achieva, Ingenia, Ingenia CX,\nIngenia Elition and Ingenia Ambition MR Systems R11 (K213583,\n05/16/2022) and the secondary predicate devices Ingenia 3.0T,\nIngenia 3.0T CX, Ingenia Elition, and MR 7700 with distributed\nMulti Nuclei (K213516, 03/03/2022) and MR 5300 (K212673,\n11/19/2021) have the same indications for use with respect to the\nfollowing:\n• Providing cross-sectional images based on the magnetic\nresonance phenomenon\n• Interpretation of the images is the responsibility of trained\nphysicians\n• Images can be used for interventional and treatment planning\npurposes\nThe proposed MR 5300 and MR 7700 R11 MR Systems are\nsubstantially equivalent to the legally marketed primary predicate\ndevice, Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia\nAmbition MR Systems R11 (K213583, 05/16/2022) and the\nsecondary predicate devices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia\nElition, and MR 7700 with distributed Multi Nuclei (K213516,\n03/03/2022) and MR 5300 (K212673, 11/19/2021), in terms of design\nfeatures, fundamental scientific technology, indications for use, and\nsafety and effectiveness.\nAdditionally, substantial equivalence is demonstrated with non-clinical\nperformance (verification and validation) tests, which complied with the"]],"caption_candidate":"Special 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p4-t0","doc_id":"K223443","page_num":4,"bbox":[72.48,608.4,544.56,662.4],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc.","Viz ANEURYSM, Viz ANX","K213319"]],"caption_candidate":"Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p7-t0","doc_id":"K223443","page_num":7,"bbox":[67.44,120.12,544.56,715.44],"n_rows":6,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","Viz AAA","Viz ANEURYSM (Viz ANX)"],["Application No.","K223443","K213319"],["Product Code","QFM","QFM"],["Regulation No.","21 C.F.R. § 892.2080","21 C.F.R. § 892.2080"],["Intended Use/\nIndications for\nUse","Viz AAA is a radiological computer-\nassisted triage and notification\nsoftware device for analysis of CTA\nimages of the abdomen. The device\nis intended to assist hospital\nnetworks and vascular or\nendovascular specialists in\nworkflow triage by flagging and\nprioritizing studies with suspected\nabdominal aortic aneurysms during\nroutine patient care.\nViz AAA uses an artificial\nintelligence algorithm to analyze\nimages and highlight studies with\nsuspected abdominal aortic\naneurysms in a standalone\napplication for study list\nprioritization or triage in parallel to\nongoing standard of care. The\ndevice generates compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use. The\ndevice does not alter the original\nmedical image and is not intended\nto be used as a diagnostic device.\nAnalyzed images are available for\nreview through the standalone\napplication. When viewed through\nthe standalone application the\nimages are for informational\npurposes only and not for\ndiagnostic use. The results of Viz\nAAA, in conjunction with other\nclinical information and professional\njudgment, are to be used to assist\nwith triage/prioritization of medical\nimages. Vascular or endovascular\nspecialists who read the original\nmedical images are responsible for","Viz ANEURYSM (Viz ANX) is a\nradiological computer-assisted triage\nand notification software device for\nanalysis of CT images of the head. The\ndevice is intended to assist hospital\nnetworks and trained radiologists in\nworkflow triage by flagging and\nprioritizing studies with suspected\naneurysms during routine patient care.\nViz ANEURYSM uses an artificial\nintelligence algorithm to analyze\nimages and highlight studies with\nsuspected aneurysms in a standalone\napplication for study list prioritization or\ntriage in parallel to ongoing standard of\ncare. The device generates\ncompressed preview images that are\nmeant for informational purposes only\nand not intended for diagnostic use.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nAnalyzed images are available for\nreview through the standalone\napplication. When viewed through the\nstandalone application the images are\nfor informational purposes only and not\nfor diagnostic use. The results of Viz\nANEURYSM, in conjunction with other\nclinical information and professional\njudgment, are to be used to assist with\ntriage/prioritization of medical images.\nRadiologists who read the original\nmedical images are responsible for the\ndiagnostic decision. Viz ANEURYSM is\nlimited to analysis of imaging data and\nshould not be used in-lieu of full patient\nevaluation or relied upon to make or\nconfirm diagnosis."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p8-t0","doc_id":"K223443","page_num":8,"bbox":[67.44,120.12,544.56,648.6],"n_rows":12,"n_cols":3,"columns":["","the diagnostic decision. Viz AAA is\nlimited to analysis of imaging data\nand should not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis.\nViz AAA is limited to detecting\naneurysms at least 3 cm in\ndiameter. Viz AAA is intended to\nidentify infra-renal, fusiform\nabdominal aortic aneurysms.","Viz ANEURYSM is limited to detecting\naneurysms at least 4mm in diameter."],"rows":[["","the diagnostic decision. Viz AAA is\nlimited to analysis of imaging data\nand should not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis.\nViz AAA is limited to detecting\naneurysms at least 3 cm in\ndiameter. Viz AAA is intended to\nidentify infra-renal, fusiform\nabdominal aortic aneurysms.","Viz ANEURYSM is limited to detecting\naneurysms at least 4mm in diameter."],["Anatomical\nRegion","Abdomen","Head"],["Diagnostic\nApplication","Notification-only, highlighting for\nprioritization and review.","Notification-only, highlighting for\nprioritization and review."],["Notification/\nPrioritization","Yes","Yes"],["Intended User","Vascular or Endovascular\nSpecialists","Radiologists"],["DICOM\nCompatible","Yes","Yes"],["Data Acquisition","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities","Acquires medical image data from\nDICOM compliant imaging devices and\nmodalities"],["Supported\nImaging Modality","Computed Tomography\nAngiography (CTA)","Computed Tomography Angiography\n(CTA)"],["Alteration of\nOriginal Image","No","No"],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-diagnostic\npurposes","Initial assessment; non-diagnostic\npurposes"],["Results returned\nin Standalone\nApplication","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p9-t0","doc_id":"K223443","page_num":9,"bbox":[140.04,322.92,454.2,398.16],"n_rows":3,"n_cols":2,"columns":["","Performance (95% C.I.)"],"rows":[["","Performance (95% C.I.)"],["Sensitivity (N=167)","96% [0.92, 0.98]"],["Specificity (N=299)","95% [0.92, 0.97]"]],"caption_candidate":"Table 1: Device Sensitivity and Specificity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p10-t0","doc_id":"K223443","page_num":10,"bbox":[114.72,526.44,497.16,673.68],"n_rows":4,"n_cols":3,"columns":["Device Performance by Health Care System","",""],"rows":[["Device Performance by Health Care System","",""],["Health Care System\n(Clinical Site)","Sensitivity [95% CI]","Specificity [95% CI]"],["Site 001","0.94\n[0.85, 0.98]","0.96\n[0.92, 0.99]"],["Site 002","0.97\n[0.92, 0.99]","0.94\n[0.89, 0.98]"]],"caption_candidate":"Table 2: Performance Stratified by Health Care System (Clinical Site)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p11-t0","doc_id":"K223443","page_num":11,"bbox":[114.24,158.64,497.88,332.28],"n_rows":5,"n_cols":3,"columns":["Device performance by Patient Age","",""],"rows":[["Device performance by Patient Age","",""],["Age Group (years)","Sensitivity [95% CI]","Specificity [95% CI]"],["< 50","N/A","1\n[0.90, 1.00]"],["50 - 70","0.95\n[0.83, 0.99]","0.96\n[0.91, 0.99]"],[">=70","0.96\n[0.91. 0.99]","0.94\n[0.88, 0.97]"]],"caption_candidate":"Table 3: Performance Stratified by Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p11-t1","doc_id":"K223443","page_num":11,"bbox":[114.24,377.28,497.88,510.6],"n_rows":4,"n_cols":3,"columns":["Device Performance by Patient Sex","",""],"rows":[["Device Performance by Patient Sex","",""],["Sex","Sensitivity [95% CI]","Specificity [95% CI]"],["Male","0.96\n[0.91, 0.99]","0.95\n[0.90, 0.98]"],["Female","0.94\n[0.80, 0.99]","0.96\n[0.91, 0.99]"]],"caption_candidate":"Table 4: Performance Stratified by Sex","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p11-t2","doc_id":"K223443","page_num":11,"bbox":[164.28,555.72,447.6,634.8],"n_rows":3,"n_cols":2,"columns":["Device Performance by Aneurysm Location",""],"rows":[["Device Performance by Aneurysm Location",""],["Location","Sensitivity [95% CI]"],["Infra-renal","0.97 [0.93, 0.99]"]],"caption_candidate":"Table 5: Performance Stratified by Abdominal Aortic Aneurysm Location","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p12-t0","doc_id":"K223443","page_num":12,"bbox":[165.8,139.32,446.08,297.72],"n_rows":6,"n_cols":2,"columns":["Device Performance by Aneurysm Diameter",""],"rows":[["Device Performance by Aneurysm Diameter",""],["Diameter Range (mm)","Sensitivity [95% CI]"],["3.0 – 3.9","0.91 [0.80, 0.97]"],["4.0 – 4.9","0.98 [0.91, 1.00]"],["5.0 – 5.3","1.00 [0.78, 1.00]"],[">= 5.4","0.97 [0.87, 1.00]"]],"caption_candidate":"Table 6: Performance Stratified by Abdominal Aortic Aneurysm Diameter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p12-t1","doc_id":"K223443","page_num":12,"bbox":[165.8,342.72,446.08,421.92],"n_rows":3,"n_cols":2,"columns":["Device Performance by Aneurysm Type",""],"rows":[["Device Performance by Aneurysm Type",""],["Type","Sensitivity [95% CI]"],["Fusiform","0.97 [0.94, 0.99]"]],"caption_candidate":"Table 7: Performance Stratified by Aneurysm Type","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p12-t2","doc_id":"K223443","page_num":12,"bbox":[119.28,466.92,492.84,640.56],"n_rows":5,"n_cols":3,"columns":["Device Performance by Manufacturer","",""],"rows":[["Device Performance by Manufacturer","",""],["Manufacturer","Sensitivity [95% CI]","Specificity [95% CI]"],["GE MEDICAL\nSYSTEMS","0.94\n[0.84, 0.98]","0.95\n[0.89, 0.98]"],["SIEMENS","0.97\n[0.91, 0.99]","0.96\n[0.92, 0.98]"],["TOSHIBA","1.00\n[0.63, 1.00]","0.88\n[0.64, 0.99]"]],"caption_candidate":"Table 8: Performance Stratified by CT Scanner Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p13-t0","doc_id":"K223443","page_num":13,"bbox":[72.0,139.32,553.56,700.2],"n_rows":17,"n_cols":4,"columns":["Device Performance by Manufacturer and Model","","",""],"rows":[["Device Performance by Manufacturer and Model","","",""],["Manufacturer","Model","Sensitivity [95% CI]","Specificity [95% CI]"],["GE MEDICAL\nSYSTEMS","Discovery 610","0.85\n[0.65, 0.96]","0.97\n[0.88, 1.00]"],["","InteleViewer","1.00\n[0.29, 1.00]","1.00\n[0.29, 1.00]"],["","LightSpeed Pro 32","1.00\n[0.4,0 1.00]","0.91\n[0.59, 1.00]"],["","Optima CT660","1.00\n[0.4,0 1.00]","1.00\n[0.59, 1.00]"],["","Revolution EVO","1.00\n[0.80, 1.00]","0.90\n[0.70, 0.99]"],["","Revolution Maxima","1.00\n[0.4,0 1.00]","1.00\n[0.16, 1.00]"],["","Model N/A","1\n[0.40, 1.00]","N/A"],["Siemens","InteleViewer","1.00\n[0.48, 1.00]","1.00\n[0.54, 1.00]"],["","Perspective","0.83\n[0.36, 1.00]","0.83\n[0.52, 0.98]"],["","SOMATOM Definition\nAS","1.00\n[0.92, 1.00]","0.98\n[0.93, 1.00]"],["","SOMATOM Definition\nFlash","0.95\n[0.75, 1.00]","0.97\n[0.86, 1.00]"],["","SOMATOM\nPerspective","1.00\n[0.74, 1.00]","0.80\n[0.44, 0.97]"],["","Sensation 40","0.80\n[0.28, 0.99]","1.0\n[0.29, 1.00]"],["","Sensation 64","N/A","1.0\n[0.29, 1.00]"],["","Model N/A","1\n[0.40. 1.00]","1\n[0.03, 1.00]"]],"caption_candidate":"Table 9: Performance Stratified by CT Scanner Manufacturer and Model","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p14-t0","doc_id":"K223443","page_num":14,"bbox":[72.0,120.12,553.56,195.12],"n_rows":3,"n_cols":4,"columns":["Device Performance by Manufacturer and Model","","",""],"rows":[["Device Performance by Manufacturer and Model","","",""],["Manufacturer","Model","Sensitivity [95% CI]","Specificity [95% CI]"],["Toshiba","Aquilion ONE","1.00\n[0.63, 1.00]","0.88\n[0.64, 0.99]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p14-t1","doc_id":"K223443","page_num":14,"bbox":[142.92,240.24,526.22,500.28],"n_rows":7,"n_cols":3,"columns":["Device Performance by Scanner Detector Rows","",""],"rows":[["Device Performance by Scanner Detector Rows","",""],["Detector Rows","Sensitivity [95% CI]","Specificity [95% CI]"],["<=24","0.8\n[0.28, 0.99]","1.00\n[0.40, 1.00]"],["32","0.99\n0.94, 1.00]","0.96\n[0.91, 0.98]"],["64","0.93\n[0.84, 0.98]","0.96\n[0.90, 0.99]"],["80","1.00\n[0.63, 1.00]","0.88\n[0.64, 0.99]"],["Unknown Rows","1\n[0.03, 1.00]","1\n[0.16, 1.00]"]],"caption_candidate":"Table 10: Performance by CT Scanner Row Detectors","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p15-t0","doc_id":"K223443","page_num":15,"bbox":[117.0,139.32,526.56,312.96],"n_rows":5,"n_cols":3,"columns":["Device Performance by Slice Thickness","",""],"rows":[["Device Performance by Slice Thickness","",""],["Slice Thickness","Sensitivity [95% CI]","Specificity [95% CI]"],["Slice thickness <= 2.0","0.95\n[0.83, 0.99]","0.94\n[0.85, 0.98]"],["2.0 < Slice thickness <= 2.5","0.94\n[0.85, 0.98]","0.95\n[0.89, 0.98]"],["Slice thickness > 2.5","0.98\n[0.91, 1.00]","0.96\n[0.91, 0.99]"]],"caption_candidate":"Table 11: Performance by Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p15-t1","doc_id":"K223443","page_num":15,"bbox":[146.76,358.2,465.24,570.96],"n_rows":6,"n_cols":3,"columns":["Type","Sensitivity [95% CI]","Specificity [95%\nCI]"],"rows":[["Type","Sensitivity [95% CI]","Specificity [95%\nCI]"],["Abdomen","1.00\n[0.85, 1.00]","0.93\n[076, 0.99]"],["Abdomen-Pelvis","0.99\n[0.92, 1.00]","0.96\n[0.92, 0.99]"],["Chest-Abdomen","0.94\n[0.71, 1.00]","0.94\n[0.80, 0.99]"],["Chest-Abdomen-Pelvis","0.9\n[0.55, 1.00]","0.98\n[0.88. 100]"],["Undetermined","0.92\n[0.81, 0.98]","0.94\n[0.84, 0.99]"]],"caption_candidate":"Table 12: Performance by Imaging Protocol","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223443-p15-t2","doc_id":"K223443","page_num":15,"bbox":[93.12,616.44,518.88,708.72],"n_rows":4,"n_cols":3,"columns":["Presence of Metal Artifact","Sensitivity (95% C.I.)","Specificity (95% C.I.)"],"rows":[["Presence of Metal Artifact","Sensitivity (95% C.I.)","Specificity (95% C.I.)"],["No metallic artifact","0.98 [0.93, 1.00]","0.94 [0.89, 0.97]"],["Metal is present, not obscuring the aorta","0.95 [0.87, 0.99]","0.98 [0.94, 1.00]"],["Metal is present obscuring the aorta","0.67 [0.22, 0.96]","0.93 [0.66, 1.00]"]],"caption_candidate":"Table 13: Performance by Presence of Metal Artifact","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p4-t0","doc_id":"K223458","page_num":4,"bbox":[72.25,152.82,544.49,709.92],"n_rows":20,"n_cols":5,"columns":["Date Prepared:","","Apr. 05, 2023","",""],"rows":[["Date Prepared:","","Apr. 05, 2023","",""],["Manufacturer:","","Philips Medical Systems Nederland B.V.\nVeenpluis 6, 5684 PC, Best, The Netherlands\nEstablishment Registration Number: 3003768277","",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","","Ioana Ulea\nSenior Regulatory Affairs Specialist\nPhone: +31 618345875\nE-mail: ioana.ulea@philips.com\nJan van de Kerkhof\nAssociate Director Regulatory Affairs\nPhone: +31 613300542\nE-mail: jan.van.de.kerkhof@philips.com","",""],["Device Name:","","Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and\nMR 7700 MR Systems","",""],["Classification:","","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)",""],["","","Classification\nRegulation:","21CFR 892.1000",""],["","","Classification Panel:","Radiology",""],["","","Device Class:","Class II",""],["","","Primary Product Code:","90LNH\n90LNI",""],["","","","",""],["Primary Predicate\nDevice:","","Trade name:","Achieva, Ingenia, Ingenia CX, Ingenia Elition,\nand Ingenia Ambition MR Systems (R11)",""],["","","Manufacturer:","Philips Medical Systems Nederland B.V.",""],["","","510(k) Clearance:","K213583",""],["","","Classification\nRegulation:","21CFR 892.1000",""],["","","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)",""],["","","Classification Panel:","Radiology",""],["","","Device class","Class II",""],["","","Product Code:","90LNH\n90LNI",""],["","","","",""],["","","Trade name:","MR 5300 and MR 7700 R11 MR Systems",""]],"caption_candidate":"CFR §807.92.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p5-t0","doc_id":"K223458","page_num":5,"bbox":[72.25,78.6,544.49,406.68],"n_rows":16,"n_cols":5,"columns":["Secondary\nPredicate Device:","","Manufacturer:","Philips Medical Systems Nederland B.V.",""],"rows":[["Secondary\nPredicate Device:","","Manufacturer:","Philips Medical Systems Nederland B.V.",""],["","","510(k) Clearance:","K223442",""],["","","Classification\nRegulation:","21CFR 892.1000",""],["","","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)",""],["","","Classification Panel:","Radiology",""],["","","Device class","Class II",""],["","","Product Code:","90LNH\n90LNI",""],["","","","",""],["Reference\nDevice","","Trade name:","SIGNA Premier",""],["","","Manufacturer:","GE Medical Systems, LLC",""],["","","510(k) Clearance:","K193282",""],["","","Classification\nRegulation:","21CFR 892.1000",""],["","","Classification name:","Magnetic Resonance Diagnostic Device\n(MRDD)",""],["","","Classification Panel:","Radiology",""],["","","Device class","Class II",""],["","","Product Code:","90LNH\n90LNI",""]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p6-t0","doc_id":"K223458","page_num":6,"bbox":[72.24,78.6,540.06,704.4],"n_rows":2,"n_cols":2,"columns":["","the following pulse sequences and coils that are previously cleared by\nFDA:\n1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils\nThe accessories to be used with the proposed device Ingenia, Ingenia\nCX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR\nSystems have not changed compared to the primary predicate device and\nsecondary predicate device and can be found in the Instructions for Use\naccompanying the device:\n• System coils\n• PPU Sensor for wireless physiology\n• Pediatric PPU Sensor\n• FlexTrak trolleys (FlexTrak / HA FlexTrak II)\n• Acoustic Hood\n• MR Elastography\nWhen Philips MRI system is used in combination with the Philips MR-RT\nor MR-OR solutions, the user is referred to the dedicated MR-RT and MR-\nOR Instructions for Use for information on additional accessories that may\napply:\n• Flextrak OR\n• MR-RT CouchTop\n• RT CouchTop XD"],"rows":[["","the following pulse sequences and coils that are previously cleared by\nFDA:\n1. mDIXON (K102344)\n2. SWIp (K131241)\n3. mDIXON-Quant (K133526)\n4. MRE (K140666)\n5. mDIXON XD (K143128)\n6. O-MAR (K143253)\n7. 3D APT (K172920)\n8. Compatible System Coils\nThe accessories to be used with the proposed device Ingenia, Ingenia\nCX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR\nSystems have not changed compared to the primary predicate device and\nsecondary predicate device and can be found in the Instructions for Use\naccompanying the device:\n• System coils\n• PPU Sensor for wireless physiology\n• Pediatric PPU Sensor\n• FlexTrak trolleys (FlexTrak / HA FlexTrak II)\n• Acoustic Hood\n• MR Elastography\nWhen Philips MRI system is used in combination with the Philips MR-RT\nor MR-OR solutions, the user is referred to the dedicated MR-RT and MR-\nOR Instructions for Use for information on additional accessories that may\napply:\n• Flextrak OR\n• MR-RT CouchTop\n• RT CouchTop XD"],["Indications for\nUse:","The indications for Use statement provided below for the proposed device\nis identical to the one of the primary and secondary predicate devices. The\nintended use is also not impacted by the introduction of Precise Image\nfeature.\nPhilips Magnetic Resonance (MR) systems are Medical Electrical Systems\nindicated for use as a diagnostic device.\nThis MR system enables trained physicians to obtain cross-sectional\nimages, spectroscopic images and/or spectra of the internal structure of\nthe head, body or extremities, in any orientation, representing the spatial\ndistribution of protons or other nuclei with spin.\nImage appearance is determined by many different physical properties of\nthe tissue and the anatomy, the MR scan technique applied, and presence\nof contrast agents."]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p7-t0","doc_id":"K223458","page_num":7,"bbox":[72.24,78.6,540.06,664.56],"n_rows":2,"n_cols":2,"columns":["","The use of contrast agents for diagnostic imaging applications should be\nperformed consistent with the approved labeling for the contrast agent.\nThe trained clinical user can adjust the MR scan parameters to customize\nimage appearance, accelerate image acquisition, and synchronize with\nthe patient’s breathing or cardiac cycle. The systems can use\ncombinations of images to produce physical parameters, and related\nderived images. Images, spectra, and measurements of physical\nparameters, when interpreted by a trained physician, provide information\nthat may assist diagnosis and therapy planning. The accuracy of\ndetermined physical parameters depends on system and scan parameters\nand must be controlled and validated by the clinical user.\nIn addition, the Philips MR systems provide imaging capabilities, such as\nMR fluoroscopy, to guide and evaluate interventional and minimally\ninvasive procedures in the head, body and extremities. MR Interventional\nprocedures, performed inside or adjacent to the Philips MR system, must\nbe performed with MR Conditional or MR Safe instrumentation as selected\nand evaluated by the clinical user for use with the specific MR system\nconfiguration in the hospital. The appropriateness and use of information\nfrom a Philips MR system for a specific interventional procedure and\nspecific MR system configuration must be validated by the clinical user."],"rows":[["","The use of contrast agents for diagnostic imaging applications should be\nperformed consistent with the approved labeling for the contrast agent.\nThe trained clinical user can adjust the MR scan parameters to customize\nimage appearance, accelerate image acquisition, and synchronize with\nthe patient’s breathing or cardiac cycle. The systems can use\ncombinations of images to produce physical parameters, and related\nderived images. Images, spectra, and measurements of physical\nparameters, when interpreted by a trained physician, provide information\nthat may assist diagnosis and therapy planning. The accuracy of\ndetermined physical parameters depends on system and scan parameters\nand must be controlled and validated by the clinical user.\nIn addition, the Philips MR systems provide imaging capabilities, such as\nMR fluoroscopy, to guide and evaluate interventional and minimally\ninvasive procedures in the head, body and extremities. MR Interventional\nprocedures, performed inside or adjacent to the Philips MR system, must\nbe performed with MR Conditional or MR Safe instrumentation as selected\nand evaluated by the clinical user for use with the specific MR system\nconfiguration in the hospital. The appropriateness and use of information\nfrom a Philips MR system for a specific interventional procedure and\nspecific MR system configuration must be validated by the clinical user."],["Design Features/\nFundamental\nScientific\nTechnology:","Just as the primary and secondary predicate devices, the proposed\nIngenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and\nMR 7700 MR Systems are based on the principle that certain atomic\nnuclei present in the human body will emit a weak relaxation signal when\nplaced in a strong magnetic field and excited by a radio signal at the\nprecession frequency. The emitted relaxation signals are analyzed by the\nsystem and a computed image reconstruction is displayed on a video\nscreen.\nThe principal technological components (magnet, transmit body coil,\ngradient coil, gradient amplifier, RF amplifier and patient support) of the\nproposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR\n5300 and MR 7700 MR Systems are unchanged compared to primary\npredicate (K213583) and the secondary predicate device (K223442).\nThe reconstruction software of the proposed Ingenia, Ingenia CX,\nIngenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems\nhas been modified to include the Precise Image, offering an alternative to\nthe current way of increasing resolution, available on the primary and\nsecondary predicate devices. The resulting images can have higher SNR,\nincreased sharpness and decreased ringing artefacts compared to\nprimary and secondary predicate devices. The user interface provides\noperators of the system with new options for selecting Precise Image\nfeature and adjusting the associated level of image noise reduction."]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p8-t0","doc_id":"K223458","page_num":8,"bbox":[182.05,149.88,534.4,614.22],"n_rows":11,"n_cols":6,"columns":["No.","Recognition\nNumber","","Standard","","Standard Name"],"rows":[["No.","Recognition\nNumber","","Standard","","Standard Name"],["","","","Number and","",""],["","","","Date","",""],["1","12-295","IEC60601-2-33\nEd. 3.2:2010 +\nAmd 1:2013 +\nAmd 2:2015","","","Medical electrical equipment - Part\n2-33: Particular requirements for the\nbasic safety and essential\nperformance of magnetic\nresonance equipment for medical\ndiagnosis"],["2","19-4","ANSI / AAMI\nES60601-\n1:2005/(R)2012\nand A1:2012","","","Medical Electrical Equipment -\nPart 1: General Requirements\nFor Basic Safety And Essential\nPerformance (IEC 60601-1:2006,\nMOD)."],["3","19-8","IEC60601-1-2\nEd. 4.0:2014","","","Medical electrical equipment - Part\n1-2: General requirements for basic\nsafety and essential performance -\nCollateral standard:\nElectromagnetic disturbances -\nRequirements and tests"],["4","5-89","IEC 60601-1-6\nEd. 3.1:2010 +\nAmd 1:2013","","","Medical electrical equipment - Part\n1-6: General requirements for basic\nsafety and essential performance -\nCollateral Standard: Usability"],["5","5-76","IEC 60601-1-8\nEd. 2.1:2006 +\nAmd 1:2012\n(Ed.2.1)","","","Medical electrical equipment - Part\n1-8: General requirements for basic\nsafety and essential performance -\nCollateral Standard: General\nrequirements, tests and guidance\nfor alarm systems in medical\nelectrical equipment and medical\nelectrical systems"],["6","5-125","ISO 14971 Third\nEdition 2019","","","Medical devices – Application of risk\nmanagement to medical devices."],["7","5-114","IEC 62366-1 Ed.\n1.0:2015","","","Medical devices – Part 1:\nApplication of usability engineering\nto medical devices"],["8","13-79","IEC 62304 Ed.\n1.1:2015","","","Medical device software – Software\nlife cycle processes."]],"caption_candidate":"Data:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223458-p9-t0","doc_id":"K223458","page_num":9,"bbox":[72.24,78.6,540.06,714.12],"n_rows":3,"n_cols":2,"columns":["","review, reproducibility of Precise in comparison to predicate device\nreconstruction technique can be considered established. Additionally, a\nreader evaluation by ABR board certified radiologists was performed,\nwhere following properties have been analyzed as part of the comparison:\nsignal-to-noise ratio (SNR), artifact level, sharpness, and contrast-to-noise\nratio (CNR). Furthermore, the radiologists have assessed the quality of the\nvisualization of abnormalities and pathologies in case they were present\nin the images as well as if the images were of sufficient quality for\ndiagnostic purposes. The review evaluation shows that the proposed\ndevice is assessed as equivalent for diagnosis and holds significantly\nbetter SNR and sharpness compared to the predicate reconstruction\ntechnology, also in the presence of (subtle) abnormalities and pathology.\nThe verification and/or validation test results demonstrate that the\nproposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR\n5300 and MR 7700 MR Systems meet the acceptance criteria and are\nadequate for the intended use.\nThe risk management activities show that all risks are sufficiently\nmitigated, that no new risks are introduced, and that the overall residual\nrisks are acceptable.\nTherefore, the proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia\nAmbition, MR 5300 and MR 7700 MR Systems are substantially\nequivalent to the legally marketed primary predicate device Achieva,\nIngenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR Systems\n(R11) (K213583, 16/05/2022) and the secondary predicate device MR\n5300 and MR 7700 R11 MR Systems (K223442) in terms of safety and\neffectiveness."],"rows":[["","review, reproducibility of Precise in comparison to predicate device\nreconstruction technique can be considered established. Additionally, a\nreader evaluation by ABR board certified radiologists was performed,\nwhere following properties have been analyzed as part of the comparison:\nsignal-to-noise ratio (SNR), artifact level, sharpness, and contrast-to-noise\nratio (CNR). Furthermore, the radiologists have assessed the quality of the\nvisualization of abnormalities and pathologies in case they were present\nin the images as well as if the images were of sufficient quality for\ndiagnostic purposes. The review evaluation shows that the proposed\ndevice is assessed as equivalent for diagnosis and holds significantly\nbetter SNR and sharpness compared to the predicate reconstruction\ntechnology, also in the presence of (subtle) abnormalities and pathology.\nThe verification and/or validation test results demonstrate that the\nproposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR\n5300 and MR 7700 MR Systems meet the acceptance criteria and are\nadequate for the intended use.\nThe risk management activities show that all risks are sufficiently\nmitigated, that no new risks are introduced, and that the overall residual\nrisks are acceptable.\nTherefore, the proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia\nAmbition, MR 5300 and MR 7700 MR Systems are substantially\nequivalent to the legally marketed primary predicate device Achieva,\nIngenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR Systems\n(R11) (K213583, 16/05/2022) and the secondary predicate device MR\n5300 and MR 7700 R11 MR Systems (K223442) in terms of safety and\neffectiveness."],["Summary of\nClinical Data:","With the proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia\nAmbition, MR 5300 and MR 7700 MR Systems the indications for use\nremain unchanged and there were no technological characteristics relative\nto the primary and secondary predicate device that would require clinical\ntesting."],["Substantial\nEquivalence:\nConclusion:","The proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition,\nMR 5300 and MR 7700 MR Systems and the legally marketed primary\npredicate device Achieva, Ingenia, Ingenia CX, Ingenia Elition, and\nIngenia Ambition MR Systems (R11) (K213583, 16/05/2022) and the\nsecondary predicate device MR 5300 and MR 7700 R11 MR Systems\n(K223442), have the same indications for use with respect to the following:\n• Providing cross-sectional images based on the magnetic resonance\nphenomenon\n• Interpretation of the images is the responsibility of trained physicians\n• Images can be used for interventional and treatment planning\npurposes\nThe proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition,\nMR 5300 and MR 7700 MR Systems are substantially equivalent to the\nlegally marketed primary predicate device Achieva, Ingenia, Ingenia CX,\nIngenia Elition, and Ingenia Ambition MR Systems (R11) (K213583) and\nthe secondary predicate device MR 5300 and MR 7700 R11 MR Systems"]],"caption_candidate":"Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223490-p2-t0","doc_id":"K223490","page_num":2,"bbox":[257.81,444.67,570.36,541.27],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223490-p4-t0","doc_id":"K223490","page_num":4,"bbox":[72.24,152.64,539.76,590.76],"n_rows":6,"n_cols":2,"columns":["Date:","March 20, 2023"],"rows":[["Date:","March 20, 2023"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283, rue de la Minière\n78530 Buc, France"],["Primary Contact:","Ning WEN\nRegulatory Affairs Program Manager Associate\nGE HealthCare, (GE Medical Systems SCS)\nTel: +33 6 2324 6023\nEmail: ning.wen@ge.com"],["Secondary Contact","Rachel Schandel\nSenior Regulatory Affairs Leader\nTel: +1 385 237 7519\nEmail: rachel.schandel@ge.com"],["Device Trade Name:\nCommon/Usual Name:\nRegulation Number:\nProduct Code:\nRegulatory Class:","FlightPlan for Embolization\nFlightPlan for Embolization, with AI Segmentation option\n21CFR 892.2050, Medical image management and processing system\nQIH\nClass II"],["Predicate Device:\nDevice Name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nRegulatory Class:","FlightPlan for Embolization\nGE Medical Systems SCS\nK193261\n21CFR 892.2050, Medical image management and processing system\nLLZ\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223490-p6-t0","doc_id":"K223490","page_num":6,"bbox":[72.25,334.25,539.75,663.72],"n_rows":13,"n_cols":7,"columns":["Specification","","Predicate Device:","","","Proposed Device:",""],"rows":[["Specification","","Predicate Device:","","","Proposed Device:",""],["","","FlightPlan for Embolization","","","FlightPlan for Embolization",""],["","","[K193261]","","","[K223490]",""],["Indication for Use","Identical","","","Identical","",""],["Patient Population","No limitations on the patient\npopulation.","","","AI Segmentation option is validated\nfor adult population only.","",""],["Semi-automatic segmentation\nof vasculature","Identical","","","Identical","",""],["Automatic segmentation of\nvasculature","No, segmentation of\nvasculature can only be done\nsemi-automatically","","","Yes, automatic segmentation of\nvasculature powered by Deep-\nLearning based algorithm","",""],["Automatic definition of the root\npoint","No, definition of the root\npoint can only be done\nmanually","","","Yes, automatic definition of the\nroot point powered by Deep-\nLearning based on algorithm","",""],["Selective display (Live Tracking)","Identical","","","Identical","",""],["Segment part of the vasculature","Yes","","","Yes","",""],["Mark points of interest (POI)","Yes","","","Yes","",""],["Save and Export","Yes","","","Yes","",""],["General features","Identical","","","Identical","",""]],"caption_candidate":"the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p4-t0","doc_id":"K223491","page_num":4,"bbox":[67.44,152.16,558.0,704.04],"n_rows":8,"n_cols":2,"columns":["Date:","May 25, 2023"],"rows":[["Date:","May 25, 2023"],["Submitter:","GE HealthCare, (GE Medical Systems, LLC)\n3000 N. Grandview Blvd\nWaukesha, WI 53188 USA"],["Primary\nContact\nPerson:","Chris Paulik\nSenior Regulatory Affairs Manager\nGE HealthCare\n262-894-5415\nChristopher.A.Paulik@ge.com"],["Secondary\nContact\nPerson:","Gregory Pessato\nRegulatory Affairs Director\nGE HealthCare\n+33 (6) 34423240\nGregoryPessato@ge.com"],["Device Trade\nName:","Critical Care Suite with Pneumothorax Detection AI Algorithm"],["Common /\nUsual Name:","Radiological computer assisted detection and diagnosis software"],["Classification\nNames and\nProduct Code:","Regulation Name: Radiological computer assisted detection and diagnosis software\nRegulation: 21 CFR 892.2090\nClassification: Class II\nProduct Codes: QBS"],["Predicate\nDevice:","BoneView (K212365)\nRegulation Name: Radiological computer assisted detection and diagnosis software\nRegulation: 21 CFR 892.2090\nClassification: Class II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p5-t0","doc_id":"K223491","page_num":5,"bbox":[67.44,103.68,558.0,687.0],"n_rows":5,"n_cols":2,"columns":["","Product Codes: QBS"],"rows":[["","Product Codes: QBS"],["Reference\nDevice:","Critical Care Suite (K183182)\nRegulation Name: Radiological computer aided triage and notification software\nRegulation: 21 CFR 892.2080\nClassification: Class II\nProduct Codes: QFM"],["Device\nDescription:","Critical Care Suite is a suite of AI algorithms for the automated image analysis of frontal\nchest X-rays acquired on a digital x-ray system for the presence of critical findings.\nCritical Care Suite with Pneumothorax Detection AI Algorithm is indicated for adults and\ntransitional adolescents (18 to <22 years old but treated like adults) and is intended to\nbe used by licensed qualified healthcare professionals (HCPs) trained to independently\nassess the presence of pneumothoraxes in radiographic images and radiologists. Critical\nCare Suite is a software module that can be deployed on several computing platforms\nsuch as PACS, On Premise, On Cloud or X-ray Imaging Systems.\nToday’s clinical workflow, hospitals are overburdened by large volume of orders and long\nturnaround times for radiologist reports. Critical Care Suite with the Pneumothorax\nDetection AI Algorithm enables effective prioritization and assists in the detection /\ndiagnosis of pneumothoraxes for radiologists and HCPs that have been trained to\nindependently assess the presence of pneumothoraxes in radiographic images. It\nperforms this task by flagging images with a suspicious finding and providing a\nlocalization overlay of the suspected pneumothorax as well as a graphical representation\nof the algorithm’s confidence in the resultant finding. These outputs can be displayed\nwherever the reviewing physician normally conducts their reads per their standard of\ncare, including PACS, On Premise, On Cloud and Digital Projection Radiographic Systems."],["Intended Use:","Critical Care Suite with Pneumothorax Detection AI Algorithm is intended to aide a\nclinician in the detection and localization of a pneumothorax on frontal chest\nradiographic images."],["Indications for\nUse:","Critical Care Suite with Pneumothorax Detection AI Algorithm is a computer-aided triage,\nnotification, and diagnostic device that analyzes frontal chest X-ray images for the\npresence of a pneumothorax. Critical Care Suite identifies and highlights images with a\npneumothorax to enable case prioritization or triage and assist as a concurrent reading\naid during interpretation of radiographs.\nIntended users include qualified independently licensed healthcare professionals (HCPs)\ntrained to independently assess the presence of pneumothoraxes in radiographic images\nand radiologists.\nCritical Care Suite should not be used in-lieu of full patient evaluation or solely relied\nupon to make or confirm a diagnosis. It is not intended to replace the review of the X-ray"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p6-t0","doc_id":"K223491","page_num":6,"bbox":[67.44,103.68,558.0,437.52],"n_rows":2,"n_cols":2,"columns":["","image by a qualified physician. Critical Care Suite is indicated for adults and Transitional\nAdolescents (18 to <22 years old but treated like adults)."],"rows":[["","image by a qualified physician. Critical Care Suite is indicated for adults and Transitional\nAdolescents (18 to <22 years old but treated like adults)."],["Technology:","Critical Care Suite with Pneumothorax Detection AI Algorithm employs the same\nfundamental scientific technology as its predicate and reference devices. They are all\ndeep learning locked AI algorithms that can be deployed on several computing platforms\nsuch as PACS, On Premise, On Cloud or X-ray Imaging Systems. The patient and user\npopulations are equivalent to what was provided with Critical Care Suite with\nPneumothorax Detection AI Algorithm. The output is equivalent since both predicate\nand proposed devices produce a result if a suspicious finding is detected, provide a\nlocalization overlay of the suspected pathology within the image and a representation of\nthe algorithm’s confidence in the resultant finding. The intended use has been expanded\nfrom the original release of Critical Care Suite (K183182) to display an overlay to the\nreviewing physician that helps localize a detected pneumothorax. It also provides a\nconfidence level to the reviewing physician that provides contextual information in the\nalgorithm’s confidence for its pneumothorax detection output.\nThe differences between Critical Care Suite with Pneumothorax Detection AI Algorithm\nand BoneView are the specific pathologies that are being detected. Critical Care Suite\nwith Pneumothorax Detection AI Algorithm analyzes frontal chest radiographic images\nfor the presence of a suspected pneumothorax where BoneView analyzes radiographic\nimages for the presence of suspected fractures. This difference does not impact the\nsafety or efficacy of Critical Care Suite with Pneumothorax Detection AI Algorithm since\nboth devices analyze images using deep learning AI technology to detect pathologies\nproducing an output that can aide clinicians and radiologists with their diagnosis."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p6-t1","doc_id":"K223491","page_num":6,"bbox":[67.44,452.64,558.0,718.8],"n_rows":5,"n_cols":3,"columns":["Product Device\nComparison","Critical Care Suite with Pneumothorax\nDetection AI Algorithm","BoneView (K212365)"],"rows":[["Product Device\nComparison","Critical Care Suite with Pneumothorax\nDetection AI Algorithm","BoneView (K212365)"],["Device\nClassification","Radiological computer assisted detection and\ndiagnosis software\nClass II, QBS","Radiological computer assisted detection and\ndiagnosis software\nClass II, QBS"],["Targeted clinical\ncondition,\nanatomy, and\nimaging modality","Pneumothorax\nChest/Lung\nAP/PA Chest X-Ray Imaging","Fracture\nAnkle, Foot, Knee, Femur, Wrist, Hand, Elbow,\nForearm, Humerus, Shoulder, Clavicle, Pelvis, Hip,\nRibs, Thoracic Spine, Lumbar Spine\n2D Radiographic Images"],["Algorithm\nInferencing\nMechanism","AI deep learning algorithms designed to detect\npneumothorax in frontal chest X-ray images to aide\nin identifying and highlighting pneumothoraxes\nduring the review of radiographs.","AI supervised deep learning algorithm designed to\naide in identifying and highlighting fractures during\nthe review of radiographs."],["Computational\nPlatform","Critical Care Suite is designed as a self-contained\nsoftware module deployable on various\ncomputational and x-ray imaging system platforms","Deployment on-premises or on cloud and connection\nto several computing platforms and X-ray imaging"]],"caption_candidate":"producing an output that can aide clinicians and radiologists with their diagnosis.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p7-t0","doc_id":"K223491","page_num":7,"bbox":[67.44,103.68,558.0,408.24],"n_rows":4,"n_cols":3,"columns":["Product Device\nComparison","Critical Care Suite with Pneumothorax\nDetection AI Algorithm","BoneView (K212365)"],"rows":[["Product Device\nComparison","Critical Care Suite with Pneumothorax\nDetection AI Algorithm","BoneView (K212365)"],["","such as Digital Projection Radiographic Systems,\nPACS, On Premise or On Cloud.","platforms such as X-ray radiographic systems, or\nPACS"],["Algorithm Outputs","1. Configurable DICOM tag that identifies if a\nsuspected pneumothorax was detected.\n2. Image annotations that contain:\n Flag if a suspected pneumothorax was\ndetected\n Graphical representation of the\nalgorithms confidence in the algorithms\nresult\n Overlay (color or grayscale) that localizes\nthe pneumothorax within the image","1. Optional Summary Table with the results of the\noverall study\n2. Results Image that contains\n Region of Interest that is a solid or dotted\nrectangle based on confidence of the\nalgorithm\n Summary including the number of regions\nof interest that are displayed and a caution\nmessage if it was identified that the image\nwas not part of the indications for use of\nBoneView."],["Destination for\nViewing Algorithm\nResults","Image annotation on a secondary DICOM image and\na DICOM message that identifies if a suspected\npneumothorax was detected within the study.\nThe output can be immediately used to visualize the\nresults on any DICOM destination such as a user’s\nimages storage system (PACS) or the x-ray system.","Image annotations made on copy of original image or\nimage annotations toggled on/off.\nThe output can be immediately used to visualize the\nresult on any DICOM destination such as a user’s\nimages storage system (PACS) or other radiological\nequipment (X-Ray System)"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223491-p9-t0","doc_id":"K223491","page_num":9,"bbox":[67.44,103.68,558.0,572.16],"n_rows":2,"n_cols":2,"columns":["","clinical users who would interact with the Critical Care Suite with Pneumothorax\nDetection AI Algorithm: radiologists (Rad.), internal medicine (IM) physicians, emergency\nmedicine (ER) physicians, and nurse practitioners. This study contained 400 images from\nthe original validation ground truth dataset used to determine the standalone\nperformance of the algorithm, and adequately analyzed that all the primary and\nsecondary endpoints met the defined passing criteria.\nCritical Care Suite with Pneumothorax Detection AI Algorithm improved reader\nperformance for detection of pneumothorax, measured by mean AUC, by 14.5%\n(7.0%,22.0%; p=.002), from 76.8% non-aided to 91.3% aided. Reader sensitivity\nincreased by 16.3% (13.1%, 19.5%; p<.001) from 67.4% non-aided to 83.7% aided.\nReader specificity increased by 12.4% (9.6%, 15.1%; p<.001) from 76.6% non-aided to\n89.0% aided. The overall performance by size was also improved. The readers showed\nan improvement for detection of large pneumothorax measured by mean AUC 10.5%\n(3.2%, 17.8%, p=0.009) and sensitivity 13.4% (10.0%, 16.9%, p<.001). The readers\nshowed an improvement for detection of small pneumothorax measured by mean AUC\n17.6% (9.3%, 25.9%, p<0.001) and sensitivity 18.7% (13.8%, 23.6%, p<.001). The\ndifferent clinical user’s improvements in mean AUC were assessed, and it was noted that\nall physicians (Rad, IM, ER) improved 10.4% (2.8%, 17.9%, p=0.015), nurse practitioners\nimproved 24.1% (1.2%, 47.0%, p=0.045), radiologists improved 2.4% (-1.0%, 5.7%,\np=0.095), and non-radiologists (ER, IM, NP) improved 17.5% (9.6%, 25.4%, p<0.001)."],"rows":[["","clinical users who would interact with the Critical Care Suite with Pneumothorax\nDetection AI Algorithm: radiologists (Rad.), internal medicine (IM) physicians, emergency\nmedicine (ER) physicians, and nurse practitioners. This study contained 400 images from\nthe original validation ground truth dataset used to determine the standalone\nperformance of the algorithm, and adequately analyzed that all the primary and\nsecondary endpoints met the defined passing criteria.\nCritical Care Suite with Pneumothorax Detection AI Algorithm improved reader\nperformance for detection of pneumothorax, measured by mean AUC, by 14.5%\n(7.0%,22.0%; p=.002), from 76.8% non-aided to 91.3% aided. Reader sensitivity\nincreased by 16.3% (13.1%, 19.5%; p<.001) from 67.4% non-aided to 83.7% aided.\nReader specificity increased by 12.4% (9.6%, 15.1%; p<.001) from 76.6% non-aided to\n89.0% aided. The overall performance by size was also improved. The readers showed\nan improvement for detection of large pneumothorax measured by mean AUC 10.5%\n(3.2%, 17.8%, p=0.009) and sensitivity 13.4% (10.0%, 16.9%, p<.001). The readers\nshowed an improvement for detection of small pneumothorax measured by mean AUC\n17.6% (9.3%, 25.9%, p<0.001) and sensitivity 18.7% (13.8%, 23.6%, p<.001). The\ndifferent clinical user’s improvements in mean AUC were assessed, and it was noted that\nall physicians (Rad, IM, ER) improved 10.4% (2.8%, 17.9%, p=0.015), nurse practitioners\nimproved 24.1% (1.2%, 47.0%, p=0.045), radiologists improved 2.4% (-1.0%, 5.7%,\np=0.095), and non-radiologists (ER, IM, NP) improved 17.5% (9.6%, 25.4%, p<0.001)."],["Determination\nof Substantial\nEquivalence:","The introduction of Critical Care Suite with Pneumothorax Detection AI Algorithm does\nnot result in any new potential safety risks and uses the same fundamental deep learning\nbased technology to detect pathological finding on 2D X-ray images. Technological\ndifferences were assessed through bench testing and clinical validation. Like its predicate\nthe device has been shown to improve intended user accuracy at detecting the targeted\npathological finding by licensed healthcare professionals, thus demonstrating that the\nproposed device is substantially equivalent to its predicate.\nAfter analyzing design verification and validation testing on the bench and the clinical\ntesting results it is the conclusion of GE HealthCare that the Critical Care Suite with\nPneumothorax Detection AI Algorithm software to be as safe, as effective, and\nperformance is substantially equivalent to the predicate device."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223501-p7-t0","doc_id":"K223501","page_num":7,"bbox":[72.26,132.18,528.82,763.36],"n_rows":9,"n_cols":9,"columns":["Feature","Subject device","","Predicate device","","Comparison","","Impact to",""],"rows":[["Feature","Subject device","","Predicate device","","Comparison","","Impact to",""],["","","","(K212621)","","","","Safety &",""],["","","","","","","","Effectiveness",""],["Regulation\nDescription","System, image\nprocessing, radiological","System, image\nprocessing, radiological","","","Equivalent","None","",""],["Device name\nand version (K\nnumber)","ViewFinder Software\nVersion 1.1","MAMMOVISTA\nB.smart Software","","","Different","None","",""],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","","","Equivalent","None","",""],["Classification\nProduct Code","QIH","LLZ","","","Equivalent","None","",""],["Manufacturer","Elaitra Ltd","Siemens. Medical\nSystems, Inc.","","","Different\nmanufacturer","None","",""],["Indications for\nUse","ViewFinder is a\ndedicated softcopy\nreview environment for\nboth screening and\ndiagnostic digital breast\ntomosynthesis.\nIts user interface and\nworkflow have been\noptimized to support\nqualified interpreting\nphysicians in both\nscreening and\ndiagnostic reading.\nEfficiency and reading\nquality are supported\nby various specialized\nfeatures.\nViewFinder provides\nvisualization and image\nenhancement tools to\naid a qualified\ninterpreting physician\nin the review of digital\nbreast tomosynthesis\ndatasets. The qualified\ninterpreting physician\nis responsible for","MAMMOVISTA B.smart\nis a dedicated\nsoftcopy review\nenvironment for both\nscreening and\ndiagnostic\nmammography as well\nas digital breast\ntomosynthesis.\nIts user interface and\nworkflow have been\noptimized to support\nexperienced\nmammography and\ntomosynthesis\nreviewers in both\nscreening and\ndiagnostic reading.\nEfficiency and reading\nquality are supported\nby various specialized\nfeatures.\nMAMMOVISTA B.smart\nprovides visualization\nand image\nenhancement tools to\naid a qualified\nradiologist in the\nreview of digital\nmammography and\ndigital breast\ntomosynthesis\ndatasets, as well as","","","Equivalent\nThe subject\ndevice is more\nexplicit.\nThe predicate\ndevice includes\nmulti-modality\nimages (e.g.,\nMRI and\nultrasound).","None","",""]],"caption_candidate":"(MAMMOVISTA B.smart)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223501-p8-t0","doc_id":"K223501","page_num":8,"bbox":[72.25,72.36,528.83,757.56],"n_rows":14,"n_cols":9,"columns":["Feature","Subject device","","Predicate device","","Comparison","","Impact to",""],"rows":[["Feature","Subject device","","Predicate device","","Comparison","","Impact to",""],["","","","(K212621)","","","","Safety &",""],["","","","","","","","Effectiveness",""],["","making the diagnosis of\nthe images presented.","other modalities of\nbreast images.","","","","","",""],["Architecture","Client / server\nenvironment","Client / server\nenvironment","","","Equivalent","None","",""],["Display of 3rd\nparty\nComputer\nAided\nDiagnostics\n(CAD) markers","No","Yes","","","The subject\nhas fewer\nfunctions","None","",""],["Display and\nprocessing of\nDBT images","Yes","Yes","","","Equivalent","None","",""],["DICOM 3.0","Yes","Yes","","","Equivalent","None","",""],["DICOM\ncompatible\nmodalities","MG Tomo\n(Mammography\nTomosynthesis images)\nDICOM DSR\n(Deformable Spatial\nRegistration)","MG (Digital\nMammography X-Ray)\nMG Tomo\n(Mammography\nTomosynthesis images)\nMR (Magnetic\nResonance)\nUS (Ultrasound)","","","The subject\nhas an\nadditional\nconformant\nmodality\nstoring tissue\ncorrelation.\nThe subject\nomits MR and\nUS","None","",""],["Display of\nbreast density\nvalues","No","Yes","","","The subject\nhas fewer\nfunctions","None","",""],["Ipsilateral DBT\ntissue\nregistration","Yes","Yes","","","Equivalent","None","",""],["DBT\nRegistration\nAlgorithms","Finite Element Model\nand Deep Learning","Finite Element Model","","","ViewFinder’s\nDeep Learning\nimproves\naccuracy","No detrimental\nimpact","",""],["Measurements","Distance\nmeasurements","Distance and angle\nmeasurements","","","The subject\ndevice\nexcludes angle\nmeasurements","No detrimental\nimpact","",""],["Supported\nImage\nGenerating\nManufacturers\nand Models","Only DBTs produced on\nHologic’s Selenia\nDimensions and GE\nHealthcare’s SenoClaire\nand Senographe\nPristina","No restriction given for\nmanufacturer or\nmodel.","","","The subject\ndevice is\nrestricted to\nfewer\nmanufacturers\nand models. It\ndoes not\nprocess\ncombinations\nwhich are out\nof scope.","None","",""]],"caption_candidate":"ViewFinder 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223501-p9-t0","doc_id":"K223501","page_num":9,"bbox":[128.72,233.52,522.75,364.08],"n_rows":6,"n_cols":4,"columns":["","Standards Reference Number and","","Title of Standard"],"rows":[["","Standards Reference Number and","","Title of Standard"],["","Date","",""],["ISO 14971: 2019","","","Medical devices – application of risk management\nto medical devices"],["IEC 62304:2006/A1:2016","","","Medical device software - Software life cycle\nprocesses"],["NEMA PS 3.1 - 3.20 2016","","","Digital Imaging and Communications in Medicine\n(DICOM) Set"],["IEC 82304-1: 2016","","","Health software – Part 1: General requirements\nfor product safety"]],"caption_candidate":"standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223501-p10-t0","doc_id":"K223501","page_num":10,"bbox":[72.01,483.54,575.96,637.27],"n_rows":9,"n_cols":21,"columns":["Frequency that ground truth is\ninside oval (n)","","","","","","Density","","","","","","","","","","","","","",""],"rows":[["Frequency that ground truth is\ninside oval (n)","","","","","","Density","","","","","","","","","","","","","",""],["","Cancer","","","Feature Size","","A","","","B","","","C","","","D","","","Grand Total","",""],["","Status","","","(mm^2)","","","","","","","","","","","","","","","",""],["All Patients","","","0 - 40","","","1.000 (1/1)","","","0.739 (17/23)","","","1.000 (7/7)","","","0.000 (0/)","","","0.806 (25/31)","",""],["","","","40 - 200","","","1.000 (1/1)","","","0.700 (7/10)","","","1.000 (1/1)","","","0.000 (0/)","","","0.750 (9/12)","",""],["","","","200- 500","","","0.000 (0/)","","","1.000 (3/3)","","","1.000 (5/5)","","","1.000 (2/2)","","","1.000 (10/10)","",""],["","","",">500","","","1.000 (2/2)","","","1.000 (6/6)","","","0.857 (6/7)","","","0.000 (0/)","","","0.933 (14/15)","",""],["","","","Total","","","1.000 (4/4)","","","0.786 (33/42)","","","0.950 (19/20)","","","1.000 (2/2)","","","0.853 (58/68)","",""],["","","","","Number of cases","","","2","","","16","","","9","","","1","","","28",""]],"caption_candidate":"table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223502-p4-t0","doc_id":"K223502","page_num":4,"bbox":[70.8,655.08,541.27,715.44],"n_rows":5,"n_cols":6,"columns":["The device does not alter the original medical image.","","","MR Diffusion Perfusion Mismatch V1.0","is not",""],"rows":[["The device does not alter the original medical image.","","","MR Diffusion Perfusion Mismatch V1.0","is not",""],["intended to be used as a standalone diagnostic device and shall not be used to make decisions with","","","","",""],["diagnosis or therapeutic purposes. Patient management decisions should not solely be based on","","","","","MR"],["Diffusion Perfusion Mismatch V1.0","results.","","","",""],["","","","","",""]],"caption_candidate":"per the standard of care.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223502-p6-t0","doc_id":"K223502","page_num":6,"bbox":[121.71,169.7,518.49,224.76],"n_rows":4,"n_cols":8,"columns":["","MR Diffusion Perfusion Mismatch V1.0","","","","Olea Sphere® V3.0 (K152602)","",""],"rows":[["","MR Diffusion Perfusion Mismatch V1.0","","","","Olea Sphere® V3.0 (K152602)","",""],["Parametric maps","","","","YES","","",""],["Volumes segmentation","","","","YES","","",""],["Mismatch computation","","","","YES","","",""]],"caption_candidate":"Substantial equivalence comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223514-p6-t0","doc_id":"K223514","page_num":6,"bbox":[72.16,104.78,540.31,708.43],"n_rows":7,"n_cols":7,"columns":["Specification/\nAttribute","","GSI Viewer with VUE Option","","","Spectral Bone Marrow",""],"rows":[["Specification/\nAttribute","","GSI Viewer with VUE Option","","","Spectral Bone Marrow",""],["","","(Predicate Device, K121827)","","","(Proposed Device)",""],["Bone\nSegmentation\nTechnology","Manual segmentation","","","Deep learning based segmentation","",""],["Clinical Workflow","Manual","","","Automated - In the predicate device, the user\nhas to manually segment the bone region,\ngenerate the MD images and fuse it/overlay\nthem onto the monochromatic base images,\nand then export the output images as DICOM\nsecondary captures and send them to desired\nDICOM destinations.\nIn the subject device, a fully automated\nworkflow generates the desired images\n(colored MD images of the segmented bone\nregion overlaid on the monochromatic base or\nVirtual Unenhanced images) as secondary\ncapture DICOM objects and networks them to\nthe preconfigured DICOM destinations (e.g.\nPACS) for the user to review.\nThis change in the subject device greatly\nimproves the overall efficiency of the review\nworkflow.","",""],["Deployment\nEnvironment","CT Console, AW Workstation\n(K110834), AW Server (K081985)","","","CT Console, Edison Health Link (EHL)","",""],["Algorithm Input","Dual energy DICOM images","","","Same","",""],["Algorithm\nOutput","Dual energy images, including\nmonochromatic, Virtual\nUnenhanced, and material\ndensity images and has the\nability to output fused colored\nmaterial density (MD) images\n(e.g Water (HAP)) of a\nsegmented bone region overlaid\non a monochromatic image as\nsecondary capture DICOM\nseries.","","","Fused image of colored material density (MD)\nimages (e.g water (HAP)) of the segmented\nbone region overlaid onto the base\nmonochromatic spectral CT images or Virtual\nUnenhanced images, as secondary capture\nDICOM series.","",""]],"caption_candidate":"510(k) Premarket Notification Submission – Spectral Bone Marrow","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p2-t0","doc_id":"K223556","page_num":2,"bbox":[257.72,444.58,570.36,541.18],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p4-t0","doc_id":"K223556","page_num":4,"bbox":[107.18,378.63,518.07,567.04],"n_rows":8,"n_cols":2,"columns":["510(k)Number","K223556"],"rows":[["510(k)Number","K223556"],["Trade/Device/ModelName","DeepCatch"],["ProductName","Picturearchivingand communicationssystem"],["DeviceClassificationName","Medical(cid:3)Image(cid:3)management(cid:3)and(cid:3)processing(cid:3)system"],["RegulationNumber","21CFR892.2050"],["ClassificationProductCode","QIH"],["DeviceClass","II"],["510(k)ReviewPanel","Radiology"]],"caption_candidate":"3.TradeName,CommonName,Classification[21CFR807.92(a)(2)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p5-t0","doc_id":"K223556","page_num":5,"bbox":[113.42,164.37,377.66,517.66],"n_rows":29,"n_cols":2,"columns":["510(k)Number","K191026"],"rows":[["510(k)Number","K191026"],["",""],["Trade/Device/ModelName","MEDIPPRO"],["",""],["DeviceClassificationName","System,ImageProcessing,"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ClassificationProductCode","LLZ"],["",""],["DeviceClass","II"],["",""],["510(k)ReviewPanel","Radiology"],["",""],["redicateDevice#2",""],["",""],["510(k)Number","K130542"],["",""],["Trade/Device/ModelName","SYNAPSE 3D LUNGANDAB"],["",""],["DeviceClassificationName","System,ImageProcessing,"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ClassificationProductCode","LLZ"],["",""],["DeviceClass","II"],["",""],["510(k)ReviewPanel","Radiology"]],"caption_candidate":"510(k)Number K191026","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223556-p7-t0","doc_id":"K223556","page_num":7,"bbox":[110.33,198.1,523.65,723.87],"n_rows":4,"n_cols":4,"columns":["Item","ProposedDevice","PredicateDevice#1","PredicateDevice#2"],"rows":[["Item","ProposedDevice","PredicateDevice#1","PredicateDevice#2"],["KNumber\nManufacturer\nModelName\nProductCode\nRegulation\nNumber","K223556\nMEDICALIPCO., LTD.\nDeepCatch\nQIH\n21CFR892.2050","K191026\nMEDICALIPCO., LTD.\nMEDIPPRO\nLLZ\n21CFR892.2050","K130542\nFUJIFILMMEDICAL\nSYSTEMU.S.A.,INC.\nSYNAPSE 3D LUNGAND\nABDOMENANALYSIS\nLLZ\n21CFR892.2050"],["Technologicalcharacteristics","","",""],["Indications for\nUse","DeepCatch(cid:3) analyzes(cid:3) CT(cid:3)\nimages(cid:3)and(cid:3)auto-segments(cid:3)\nanatomical(cid:3)structures(cid:3)(skin,(cid:3)\nbone,(cid:3)muscle,(cid:3)visceral(cid:3)fat,(cid:3)\nsubcutaneous(cid:3) fat,(cid:3) internal(cid:3)\norgans(cid:3)and(cid:3)central(cid:3)nervous(cid:3)\nsystem).(cid:3) Then,(cid:3) its(cid:3) volume(cid:3)\nand(cid:3) proportions(cid:3) are(cid:3)\ncalculated(cid:3)and(cid:3)provided(cid:3)with(cid:3)\nthe(cid:3)relevant(cid:3)3D(cid:3)model.\nBy(cid:3) using(cid:3) DeepCatch,(cid:3) it(cid:3) is(cid:3)\npossible(cid:3)to(cid:3)obtain(cid:3)accurate(cid:3)\nvalues(cid:3)for(cid:3)the(cid:3)volume(cid:3)and(cid:3)\nproportion(cid:3) of(cid:3) each(cid:3)\nanatomical(cid:3) structures(cid:3) by(cid:3)\nsecondary(cid:3)utilization(cid:3)of(cid:3)CT(cid:3)\nimages(cid:3)obtained(cid:3)for(cid:3)various(cid:3)\npurposes(cid:3) in(cid:3) the(cid:3) medical(cid:3)\nfield.(cid:3)This(cid:3)device(cid:3)is(cid:3)intended(cid:3)\nto(cid:3)be(cid:3)used(cid:3)in(cid:3)conjunction(cid:3)\nwith(cid:3) professional(cid:3) clinical(cid:3)\njudgement.(cid:3) The(cid:3) type(cid:3) of(cid:3)\ninput(cid:3)data(cid:3)is(cid:3)whole(cid:3)body(cid:3)CT.(cid:3)\nThe(cid:3)physician(cid:3)is(cid:3)responsible(cid:3)\nfor(cid:3) inspecting(cid:3) and(cid:3)\nconfirming(cid:3)all(cid:3)results.","MEDIP PRO is intended for\nuse as a software interface\nand image segmentation\nsystem for the transfer of\nDICOM imaging information\nfromamedicalscannertoan\noutputfile.Itisalsousedas\npre-operative software for\ntreatmentplanning.\nThe 3D printed models\ngenerated from the output\nfile are meant for non-\ndiagnostic use. MEDIP PRO\nshould be used in\nconjunction with other\ndiagnostic tools and expert\nclinicaljudgement.","Synapse 3D Lung and\nAbdomenAnalysisismedical\nimaging software used with\nSynapse 3D Base Tools that\nis intended to provide\ntrained medical\nprofessionals with tools to\naid them in reading,\ninterpreting, and treatment\nplanning. Synapse 3D Lung\nand Abdomen Analysis\naccepts DICOM compliant\nmedical images acquired\nfromCT.\nThisproductis notintended\nfor use with or for the\nprimary diagnostic\ninterpretation of\nMammographyimages.\nAdditiontoSynapse3DBase\nTools,Synapse3DLungand\nAbdomen Analysis is\nintendedto:\n- use non-contrast and\ncontrast enhanced\ncomputed tomographic\nimages of the lung, provide\ncustom workflows and UI,\nand reporting functions for\nlung analysis including\nboundary detection and\nvolume calculation for\npulmonary nodules in the\nlung based on the location\nspecified by the user,\nsegmentation of bronchial\ntubes in the lung,\napproximation of air supply\nregion by the user specified\nbronchial tube, identifying,"]],"caption_candidate":"[Table1.ComparisonofProposedDevicetoPredicateDevices]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p8-t0","doc_id":"K223556","page_num":8,"bbox":[112.75,92.99,521.16,715.53],"n_rows":56,"n_cols":4,"columns":["","","","displaying and processing"],"rows":[["","","","displaying and processing"],["","","","lowabsorptionregionsinthe"],["","","","lung."],["","","","- use non-contrasted CT"],["","","","images and calculate"],["","","","subcutaneous fat and"],["","","","visceral fat areas in 2D and"],["","","","bothvolumesin3D."],["","","","-analyzeabronchuspathto"],["","","","reach a lung nodule using"],["","","","the volume data collected"],["","","","with CT, and simulate"],["","","","insertion of bronchoscope"],["","","","intothepath."],["Typeofuse","PrescriptionUse","Prescription Use","PrescriptionUse"],["Userpopulation","Clinicalexpert","Clinicalexpert","Clinicalexpert"],["ImageModalities","DICOMimaging","DICOMimaging","DICOMimaging"],["","informationfromCT","informationfromCT,MRI","informationfromCT"],["Feature/","-Analysis&Measurement","-Analysis&Measurement","-Analysis&Measurement"],["Functionality","-2D/3D visualization","-ImageEnhancement","-ImageEnhancement"],["","-Segmentation","-2D/3D visualization","-2D/3D visualization"],["","-3D Rendering","-Segmentation","-Segmentation"],["","-ExportingCSVdata","-3D Rendering","-3D Rendering"],["","-CalculationofBMI","-Exporting STLdatafor","-ExportReport"],["","","3DPrinting","-CalculationofBMI"],["","","","-Abdominal"],["","","","Circumference"],["Segmentation","Skin,Bone,Muscle,","Skin,Bone,Muscle,","Visceralfat,"],["Regions","abdominalvisceralfat,","abdominalvisceralfat,","Subcutaneousfat"],["","subcutaneousfat,","subcutaneousfat,",""],["","internalorgans, central","internalorgans, central",""],["","nervoussystem","nervoussystem, Lung",""],["","","Pulmonary Vessel",""],["","","Liver",""],["","","Femur",""],["","","Etc.(Manual",""],["","","segmentation)",""],["Visualization/Edit","*2DView","*2DView","*2DView"],["Tools","-zoomin","-zoomin","-CinePlay"],["","-zoomout","-zoomout","-Switchdisplaytypes"],["","","","-Realtimestack"],["","*3DView","*3DView","reconstruction"],["","-Anterior","-Anterior","-Linkcoordinates"],["","-Posterior","-Posterior","-Captureslice"],["","-Superior","-Superior","-Browsestudydata"],["","-Inferior","-Inferior","-Imagestoreandrestore"],["","-Right","-Right",""],["","-Left","-Left","*3DView"],["","-Smooth","-Smooth","-2D crosssection"],["","","","-Comparewithpast"],["","","","studies"],["","","","-Switchbetween"],["","","","SYNC/ASYNC"],["","","","-Seriesregistration"],["","","","-Virtualendoscope"],["Datareporting","Yes","Yes","Yes"]],"caption_candidate":"Item ProposedDevice PredicateDevice#1 PredicateDevice#2","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223556-p9-t0","doc_id":"K223556","page_num":9,"bbox":[112.89,80.48,519.58,115.25],"n_rows":2,"n_cols":4,"columns":["Item","ProposedDevice","PredicateDevice#1","PredicateDevice#2"],"rows":[["Item","ProposedDevice","PredicateDevice#1","PredicateDevice#2"],["Exportfile\nformats","Yes","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p9-t1","doc_id":"K223556","page_num":9,"bbox":[112.89,565.67,519.58,690.12],"n_rows":4,"n_cols":5,"columns":["Datasets","Items","Group","Nullhypothesis","Alternativehypothesis"],"rows":[["Datasets","Items","Group","Nullhypothesis","Alternativehypothesis"],["Internal\nDatasets\n(n=100)","DSC","DSCbetween‘GT’and\n‘segmentationresultsof\nDeepCatch’","Group'sDSCmeanis\nlessthan0.900.","Group'sDSCmeanis\ngreaterthanorequalto\n0.900."],["External\nDatasets\n(n=580)","DSC","DSCbetween‘GT’and\n‘segmentationresultsof\nDeepCatch’","Group'sDSCmeanis\nlessthan0.900.","Group'sDSCmeanis\ngreaterthanorequalto\n0.900."],["","Volume","Differencebetween‘GT’\nand‘measurementresults\nofDeepCatch’","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±10%\n(0.10).","Themeanofthewithin-\ngroupdifferenceisless\nthan±10%(0.10)."]],"caption_candidate":"a)Performancetest usingdatasetfromKorea(562)andFrance(18)with DeepCatch","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223556-p10-t0","doc_id":"K223556","page_num":10,"bbox":[113.87,80.59,517.96,194.93],"n_rows":3,"n_cols":5,"columns":["","Area","","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±10%\n(0.10).","Themeanofthewithin-\ngroupdifferenceisless\nthan±10%(0.10)."],"rows":[["","Area","","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±10%\n(0.10).","Themeanofthewithin-\ngroupdifferenceisless\nthan±10%(0.10)."],["","Ratio","","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±1%(0.01).","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±1%(0.01)."],["","Body\nCircumference","","Themeanofthewithin-\ngroupdifferenceis\ngreaterthan±5%(0.05).","Themeanofthewithin-\ngroupdifferenceisless\nthan±5%(0.05)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223621-p6-t0","doc_id":"K223621","page_num":6,"bbox":[72.01,72.34,539.75,568.56],"n_rows":13,"n_cols":8,"columns":["Feature","DeepXray\n(Subject Device)","","KOALA","","","RBknee",""],"rows":[["Feature","DeepXray\n(Subject Device)","","KOALA","","","RBknee",""],["","","","(K192109,","","","(K203696,",""],["","","","Predicate Device)","","","Predicate Device)",""],["Classification Name\nand Product Code","Automated Radiological\nImage Processing\nSoftware (QIH)","System, Image\nProcessing, Radiological\n(LLZ)","","","System, Image\nProcessing, Radiological\n(LLZ)","",""],["Anatomical Area","Joint (knee)","Joint (knee)","","","Joint (knee)","",""],["Image Input","DICOM compliant images\nin either digitally\ncomputed (CR) or directly\ndigital (DX) formats","DICOM compliant images\nin either digitally\ncomputed (CR) or directly\ndigital (DX) formats","","","DICOM compliant images\nin either digitally\ncomputed (CR) or directly\ndigital (DX) formats","",""],["Image Processing","Knee detection;\nLandmark detection; Joint\nspace detection","Knee detection;\nLandmark detection; Joint\nspace detection","","","Knee detection;\nLandmark detection; Joint\nspace detection","",""],["Human Intervention\nfor interpretation","Required","Required","","","Required","",""],["Intended User","Trained professionals","Trained professionals","","","Trained professionals","",""],["Output Format","Web report with quality\nwarning, markup images\nand editing interface","A single DICOM Image","","","Markup images and\ntextual report as static\nDICOM images","",""],["Output Information","- Knee OA status:\nKL grade ≥2 or ≤1\n- JSN status:\nAbsent/Present\n- Osteophyte status:\nAbsent/Present\n- Sclerosis status:\nAbsent/Present\n- Minimum Joint Space\nWidth\n- Femoral-Tibial Angle","- Knee OA status:\nKL grade ≥2 or ≤1\n- JSN status:\nAbsent/Present\n- Osteophyte status:\nAbsent/Present\n- Sclerosis status:\nAbsent/Present\n- Minimum Joint Space\nWidth","","","- Knee OA status:\nKL grade ≥2 or <2\n- JSN status:\nNot present/Present\n- Osteophyte status:\nNot present/Present\n- Sclerosis status:\nNot present/Present\n- Minimum Joint Space\nWidth","",""],["Runs on Server","Yes","Yes","","","Yes","",""],["Operating\nEnvironment","Linux/Docker","Linux/Docker","","","Linux/Docker","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223621-p7-t0","doc_id":"K223621","page_num":7,"bbox":[90.8,118.92,503.51,699.0],"n_rows":40,"n_cols":5,"columns":["Items","","","Testing Dataset","Training Dataset"],"rows":[["Items","","","Testing Dataset","Training Dataset"],["","#Patients","","1121","3387"],["","Male","","499 (44.5%)","1390 (41%)"],["","Female","","622 (55.5%)","1997 (59%)"],["","Age > 60","","601 (53.6%)","1642 (48.5%)"],["","Ethnicity","","",""],["","White","","937 (83.6%)","2675 (79.0%)"],["","Black or African American","","159 (14.2%)","626 (18.5%)"],["","Asian","","13 (1.2%)","25 (0.8%)"],["","Unknown or not reported","","12 (1.1%)","61 (1.9%)"],["","#DICOM","","6125","18406"],["","CR","","5783 (94.4%)","11213 (60.9%)"],["","DX","","342 (5.6%)","3438 (18.7%)"],["","RG","","0 (0%)","3755 (20.4%)"],["","Visiting Timepoint:","","",""],["","Baseline","","1121 (18.3%)","3385 (18.4%)"],["","12 month","","1058 (17.3%)","3158 (17.2%)"],["","24 month","","978 (16%)","2999 (16.3%)"],["","36 month","","939 (15.3%)","2877 (15.6%)"],["","48 month","","897 (14.6%)","2757 (15.0%)"],["","72 month","","558 (9.1%)","1602 (8.7%)"],["","96 month","","574 (9.4%)","1628 (8.8%)"],["","X-ray Manufacturer:","","",""],["","Agfa","","4671 (76.3%)","3914 (21.3%)"],["","Fujifilm","","1144 (18.7%)","3030 (16.5%)"],["","GE","","310 (5.1%)","3450 (18.7%)"],["","Konica-Minolta","","0 (0%)","2055 (11.2%)"],["","Philips","","0 (0%)","66 (0.4%)"],["","Siemens","","0 (0%)","318 (1.7%)"],["","Swissray","","0 (0%)","3873 (21.0%)"],["","Others (Not reported)","","0 (0%)","1700 (9.2%)"],["","#Knees:","","11816","35217"],["","KL ≤ 1","","6850 (58%)","20536 (58.3%)"],["","KL ≥ 2","","4966 (42%)","14681 (41.7%)"],["","JSN Absent","","6862 (58.1%)","21089 (59.9%)"],["","JSN Present","","4954 (41.9%)","14128 (40.1%)"],["","Osteophyte Absent","","8018 (69.4%)","18997 (55.0%)"],["","Osteophyte Present","","3538 (30.6%)","15533 (45.0%)"],["","Sclerosis Absent","","8520 (74.8%)","25813 (75.6%)"],["","Sclerosis Present","","2865 (25.2%)","8336 (24.4%)"]],"caption_candidate":"findings are shown below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223621-p8-t0","doc_id":"K223621","page_num":8,"bbox":[64.85,150.31,546.95,427.72],"n_rows":10,"n_cols":8,"columns":["","DeepXray","","Sample Number","Performance Metric","","Result",""],"rows":[["","DeepXray","","Sample Number","Performance Metric","","Result",""],["","Output","","","","","(95% C.I.)",""],["Kellgren-\nLawrence\nGrade","","","11775 knees/\n6114 DICOM/\n1121 subjects","Sensitivity\n(KL Grade ≥2)","0.87 (0.86/0.88)","",""],["","","","","Specificity\n(KL Grade ≥2)","0.84 (0.83/0.85)","",""],["Joint Space\nNarrowing","","","11775 knees/\n6114 DICOM/\n1121 subjects","Sensitivity\n(OARSI Grade ≥1)","0.88 (0.87/0.89)","",""],["","","","","Specificity\n(OARSI Grade ≥1)","0.82 (0.81/0.83)","",""],["Osteophyte","","","11518 knees/\n5993 DICOM/\n1121 subjects","Sensitivity\n(OARSI Grade ≥1)","0.86 (0.85/0.87)","",""],["","","","","Specificity\n(OARSI Grade ≥1)","0.80 (0.79/0.81)","",""],["Sclerosis","","","11348 knees/\n5904 DICOM/\n1119 subjects","Sensitivity\n(Presence/Absence)","0.84 (0.83/0.85)","",""],["","","","","Specificity\n(Presence/Absence)","0.88 (0.87/0.89)","",""]],"caption_candidate":"below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223621-p8-t1","doc_id":"K223621","page_num":8,"bbox":[64.85,504.43,546.95,668.56],"n_rows":10,"n_cols":6,"columns":["","DeepXray","","Sample Number","Orthogonal linear regression","Result (95% C.I.)"],"rows":[["","DeepXray","","Sample Number","Orthogonal linear regression","Result (95% C.I.)"],["","Output","","","",""],["Medial\nmJSW (mm)","","","7748 knees/\n4432 DICOM/\n862 subjects","Slope","1.02 (1.00, 1.03)"],["","","","","Intercept","0.04 (-0.03, 0.11)"],["Lateral\nmJSW (mm)","","","7605 knees/\n4377 DICOM/\n861 subjects","Slope","0.98 (0.95, 1.01)"],["","","","","Intercept","0.06 (-0.10, 0.26)"],["","Femoral-","","7546 knees/\n4310 DICOM/\n854 subjects","Slope","0.97 (0.96, 0.99)"],["","Tibial Angle","","","",""],["","","","","Intercept","-0.10 (-0.17, -0.04)"],["","(degree˚)","","","",""]],"caption_candidate":"measurements from the OAI study. The performance test results are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223623-p4-t0","doc_id":"K223623","page_num":4,"bbox":[72.28,136.3,532.73,615.2],"n_rows":20,"n_cols":2,"columns":["Date Summary Prepared:","2023-05-08"],"rows":[["Date Summary Prepared:","2023-05-08"],["Contact Details",""],["Applicant Name:","Subtle Medical, Inc."],["Applicant Address:","883 Santa Cruz Ave, Suite 205\nMenlo Park, CA 94025 United States"],["Applicant Contact:","Mr. Ajit Shankaranarayanan"],["Applicant Contact Telephone:","(650) 397-8709"],["Applicant Contact Email:","ajit@subtlemedical.com"],["Correspondent Name:","Enzyme Corporation"],["Correspondent Address:","611 Gateway Blvd, Ste 120\nSouth San Francisco, CA 94080 United States"],["Correspondent Contact:","Mr. Jared Seehafer"],["Correspondent Contact\nTelephone:","(415) 638-9554"],["Correspondent Contact\nEmail:","jared@enzyme.com"],["Device Name",""],["Device Trade Name:","SubtleMR (2.3.x)"],["Common Name:","Medical image management and processing system"],["Classification Name:","System, Image Processing, Radiological"],["Regulation Number:","21 CFR 892.2050"],["Product Code:","LLZ"],["Device Class:","Class II"],["Legally Marketed Predicate\nDevice:","Predicate #: K203182\nPredicate Trade Name: SubtleMR\nPredicate Manufacturer: Subtle Medical, Inc."]],"caption_candidate":"Table 1. Contact Details & Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223639-p4-t0","doc_id":"K223639","page_num":4,"bbox":[72.72,453.96,540.36,554.52],"n_rows":8,"n_cols":2,"columns":["510(k) Number","K202297"],"rows":[["510(k) Number","K202297"],["Trade Name","Aline Ablation Intelligence"],["Manufacturer","Mirada Medical Ltd"],["Device Name","Aline Ablation Intelligence"],["Regulation Number","892.2050"],["Regulation Name","Picture Archiving and Communications System"],["Regulatory Class","Class II"],["Primary Product Code","LLZ"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223639-p6-t0","doc_id":"K223639","page_num":6,"bbox":[72.54,632.28,540.3,709.32],"n_rows":4,"n_cols":3,"columns":["Characteristic","VisAble.IO","Aline Ablation Intelligence"],"rows":[["Characteristic","VisAble.IO","Aline Ablation Intelligence"],["","",""],["510(K) number","K223639","K202297"],["Classification","Class II. 892.2050 QTZ, QIH, LLZ","Class II. 892.2050 LLZ"]],"caption_candidate":"comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223639-p7-t0","doc_id":"K223639","page_num":7,"bbox":[72.48,71.28,540.36,706.56],"n_rows":4,"n_cols":3,"columns":["Indications for\nUse","VisAble.IO is a Computed Tomography\n(CT) image processing software\npackage available for use with liver\nablation procedures.\nVisAble.IO is controlled by the user via a\nuser interface.\nVisAble.IO imports images from CT\nscanners and facility PACS systems for\ndisplay and processing during liver\nablation procedures.\nVisAble.IO is used to assist physicians\nin planning liver ablation procedures,\nincluding identifying ablation targets and\nvirtual ablation needle placement.\nVisAble.IO is used to assist physicians\nin confirming ablation zones.\nThe software is not intended for\ndiagnosis. The software is not intended\nto predict ablation volumes or predict\nablation success.","Aline Ablation Intelligence is a\nComputed Tomography (CT) and\nMagnetic Resonance (MR) image\nprocessing software package available\nfor use with ablation procedures.\nAline Ablation Intelligence is controlled\nby the user via a user interface on a\nworkstation.\nAline Ablation intelligence imports\nimages from CT and MR scanners and\nfacility PACS systems for display and\nprocessing during ablation procedures.\nAline Ablation Intelligence is used to\nassist physicians in planning ablation\nprocedures, including identifying\nablation targets and virtual ablation\nneedle placement. Aline Ablation\nIntelligence is used to assist physicians\nin confirming ablation zones.\nThe software is not intended for\ndiagnosis. The software is not intended\nto predict ablation volumes or predict\nablation success."],"rows":[["Indications for\nUse","VisAble.IO is a Computed Tomography\n(CT) image processing software\npackage available for use with liver\nablation procedures.\nVisAble.IO is controlled by the user via a\nuser interface.\nVisAble.IO imports images from CT\nscanners and facility PACS systems for\ndisplay and processing during liver\nablation procedures.\nVisAble.IO is used to assist physicians\nin planning liver ablation procedures,\nincluding identifying ablation targets and\nvirtual ablation needle placement.\nVisAble.IO is used to assist physicians\nin confirming ablation zones.\nThe software is not intended for\ndiagnosis. The software is not intended\nto predict ablation volumes or predict\nablation success.","Aline Ablation Intelligence is a\nComputed Tomography (CT) and\nMagnetic Resonance (MR) image\nprocessing software package available\nfor use with ablation procedures.\nAline Ablation Intelligence is controlled\nby the user via a user interface on a\nworkstation.\nAline Ablation intelligence imports\nimages from CT and MR scanners and\nfacility PACS systems for display and\nprocessing during ablation procedures.\nAline Ablation Intelligence is used to\nassist physicians in planning ablation\nprocedures, including identifying\nablation targets and virtual ablation\nneedle placement. Aline Ablation\nIntelligence is used to assist physicians\nin confirming ablation zones.\nThe software is not intended for\ndiagnosis. The software is not intended\nto predict ablation volumes or predict\nablation success."],["Target\nPopulation","The intended patient population is the\npatient demographic chosen by\ninterventional radiologists to undergo\nablation treatment (including patient with\nsoft tissue lesions).","The intended patient population is the\npatient demographic chosen by\ninterventional radiologists to undergo\nablation treatment (including patient with\nsoft tissue lesions)."],["Where Used","The application’s use environment is the\nOperating Room and the hospital\nhealthcare environment such as\ninterventional radiology control room.","The application’s use environment is the\nOperating Room and the hospital\nhealthcare environment such as\ninterventional radiology control room."],["Energy Used","None – software only application. The\nsoftware application does not deliver or\ndepend on energy delivered to or from\npatients","None – software only application. The\nsoftware application does not deliver or\ndepend on energy delivered to or from\npatients"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223639-p8-t0","doc_id":"K223639","page_num":8,"bbox":[72.48,71.28,540.36,470.4],"n_rows":7,"n_cols":3,"columns":["Intended Users","Physicians","Physicians"],"rows":[["Intended Users","Physicians","Physicians"],["Design:\nSupported\nmodalities","CT","CT;MRI"],["Design: Data\nVisualization","Window and level, pan, zoom, cross-\nhairs, slice navigation","Window and level, pan, zoom, cross-\nhairs, slice navigation"],["Design; Image\nSegmentation","Tools for segmenting 3D VOIs, including\ntarget tissues, ablation zones, vessels\nand anatomy of the liver.","Tools for segmenting 3D VOIs, including\ntarget tissues and ablation zones."],["Design: Image\nregistration","Registration of multiple images into a\nsingle view.","Registration of multiple images and\nimaging modalities into a single view."],["Design:\nAblation zone\nconfirmation","Registration of the planning scan,\ncontaining the identified target tissue,\nwith the confirmation scan showing the\nablation zone. The delineated target\ntissue on the planning scan is then\nprojected onto the confirmation scan and\noverlaid onto the delineated ablation\nzone segmentation. This helps the user\nin analyzing if the ablation zone covers\nthe target tissue with the desired amount\nof margin.","Registration of the planning scan,\ncontaining the identified target tissue,\nwith the confirmation scan showing the\nablation zone. The delineated target\ntissue on the planning scan is then\nprojected onto the confirmation scan and\noverlaid onto the delineated ablation\nzone segmentation. This helps the user\nin analyzing if the ablation zone covers\nthe target tissue with the desired amount\nof margin."],["Design: Save\nkey images","Key images can be acquired which may\nbe saved locally.","Key images can be acquired which may\nbe saved back to PACS or any DICOM\nnodes."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223639-p10-t0","doc_id":"K223639","page_num":10,"bbox":[36.03,67.38,548.97,299.64],"n_rows":7,"n_cols":8,"columns":["Algorithm","N","Gender","Mean","N per","CT Brand","Primary","Primary Endpoint"],"rows":[["Algorithm","N","Gender","Mean","N per","CT Brand","Primary","Primary Endpoint"],["","","","Age","Region","","Performance Goal",""],["Liver\nSegmentation","50","M: 52%\nF: 48%","60.6","US: 32\nOUS: 18","GE Medical\nSystems,\nSiemens","Mean DICE =0.92","Mean DICE =0.98"],["Ablation\nTarget\nSegmentation","59","M: 54%\nF: 46%","60.0","US: 30\nOUS: 29","GE Medical\nSystems,\nSiemens,\nPhilips","Mean DICE = 0.70","Mean DICE = 0.80"],["Ablation Zone\nSegmentation","59","M:64%\nF: 36%","66.0","US: 30\nOUS: 29","GE Medical\nSystems,\nSiemens","Mean DICE = 0.70","Mean DICE = 0.86"],["Liver Vessels\nSegmentation","100","M: 52%\nF: 48%","58.5","US: 72\nOUS: 28","GE Medical\nSystems,\nSiemens","Mean DICE = 0.70","Mean DICE = 0.72"],["PrePost\nAblation\nImage\nRegistration","46","M: 59%\nF: 41%","63.3","US: 13\nOUS: 33","GE Medical\nSystems,\nSiemens,\nPhilips","MCD*= 6.06 mm","MCD*=4.11 mm"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p2-t0","doc_id":"K223646","page_num":2,"bbox":[257.72,428.8,570.36,527.38],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices"],["","and Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p4-t0","doc_id":"K223646","page_num":4,"bbox":[64.67,487.32,371.55,659.5],"n_rows":8,"n_cols":2,"columns":["","predicatedevice"],"rows":[["","predicatedevice"],["Manufacturer:","IBLabGmbH\nZehetnergasse6/2/2\n1140Wien\nAustria"],["TradeName","KOALA"],["510(k)documentcontrolnumber","K192109"],["DeviceClass","ClassII"],["GrantedmarketingclearancebyFDA","Yes"],["Productcode","LLZ/892.2050,\nJAK/892.1750"],["ClearanceDate","November6,2019"]],"caption_candidate":"PredicateDevices/ReferenceDevices807.92(a)(3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p7-t0","doc_id":"K223646","page_num":7,"bbox":[48.47,132.36,745.35,493.5],"n_rows":2,"n_cols":4,"columns":["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],"rows":[["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],["Indicationsforuse","IBLabKOALAisaradiological\nfully-automatedimageprocessing\nso\u0000waredeviceofeithercomputed\n(CR)ordirectlydigital(DX)images\nintendedtoaidmedical\nprofessionalsinthemeasurementof\nminimumjointspacewidth;the\nassessmentofthepresenceor\nabsenceofsclerosis,jointspace\nnarrowing,andosteophytesbased\nOARSIcriteriafortheseparameters;\nand,thepresenceorabsenceof\nradiographickneeOAbasedon\nKellgren&LawrenceGradingof\nstanding,fixed-flexionradiographs\noftheknee.Itshouldnotbeused\nin-lieuoffullpatientevaluationor\nsolelyreliedupontomakeor\nconfirmadiagnosis.Thesystemisto\nbeusedbytrainedprofessionals\nincluding,butnotlimitedto,\nradiologists,orthopedics,physicians\nandmedicaltechnicians.","IBLabLAMAisafully-automated\nradiologicalimageprocessingso\u0000ware\ndeviceintendedtoaidusersinthe\nmeasurementoflimb-lengthdiscrepancy\nandquantitativekneealignment\nparametersonuni-andbilateralAPfullleg\nradiographsofindividualsatleast22years\nofage.Itshouldnotbeusedin-lieuoffull\npatientevaluationorsolelyrelieduponto\nmakeorconfirmadiagnosis.Theso\u0000ware\ndeviceisintendedtobeusedbyhealthcare\nprofessionalstrainedinradiology.\nIBLabLAMAisnotindicatedforuseon\nradiographsonwhichAnkleArthroplasties\nand/orUnicompartmentalKnee\nArthroplastiesarepresent.","Thesubjectdeviceperformsmeasurementsoflengths\nandanglesonfulllegimages.Thepredicatedevice\nperformslengthandgrademeasurementsonknee\nimages.Thisdifferenceinspecificanatomiclocations\ndoesnotraisenewtypesofquestionsforsafetyor\neffectivenessandthereforedoesnotinducechangesin\ntheintendeduse.Forbothdevices,thekeyquestionis\nwhethertheso\u0000wareisabletogenerateaccurateand\nreproducibleanatomicalmeasurementswithinthe\ntargetpopulation."]],"caption_candidate":"ComparisonoftheTechnologicalCharacteristicswiththePredicateDevices 807.92(a)(6)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p8-t0","doc_id":"K223646","page_num":8,"bbox":[48.48,102.22,745.4,438.5],"n_rows":6,"n_cols":4,"columns":["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],"rows":[["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],["Productcode","LLZ/892.2050,JAK/892.1750","QIH/892.2050","Similar.TheproductcodeQIHwasnotyetavailable\nwhenthepredicatewascleared."],["HumanIntervention\nforinterpretation","Required","Required","Same."],["ImageRequirements","DICOMcompliantimagescollected\ninotherdevicesineitherdigitally\ncomputed(CR)ordirectlydigital\n(DX)formats","DICOMcompliantplainradiographs\ncollectedinotherdevices intheCR,DX,SC\nformats.","Similar.Thisdifferencedoesnotraisenewquestions\naboutsafetysincetheadditionalformatSCis\nstandardlyusedforprocessedDICOMimages.For\nlong-legradiographspost-processingisthestandard\nsincetheimagesaregenerallyassembledbycleared\nmedicalso\u0000ware."],["Anatomicalarea","knee","fullleg","Similar.Theanatomicalregiondoesnotraisenew\nquestionsregardingsafetyoreffectivenesswith\nrespecttothetechnologicalcharacteristics.The\ntechniquesusedforcapturingfulllegimagesandknee\nimagesarebothstandardprocedures."],["Workflow/Principles\nofOperation","1. UserorPACSsendsimage\ntodevice\n2. Deviceperformsanalysis\n3. ImageissentbacktoPACS\n4. Userreviewsand\naccepts/rejectsreport","1. UserorPACSsendsimageto\ndevice\n2. Deviceperformsanalysis\n3. ImageissentbacktoPACS\n4. Userreviewsandaccepts/rejects\nreport","Same."]],"caption_candidate":"IBLabLAMA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p9-t0","doc_id":"K223646","page_num":9,"bbox":[48.48,102.22,745.4,491.5],"n_rows":3,"n_cols":4,"columns":["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],"rows":[["Characteristic","KOALA\nIBLabGmbH\nPredicateDevice(K192109)","IBLabLAMA\nIBLabGmbH\nSubjectDevice","DiscussionofDifferences"],["Processing\nArchitecture","1. Pre-processtheinputimage\n2. Classifyuniorbilateral\nimage\n3. Computeregionsofinterest\nforeachside.\n4. Detectlandmarksand\nsegmentations\n5. Computedistances\n6. ComputeOAparameters\n7. Generatereports","1. Pre-processtheinputimage\n2. Classifyuniorbilateralimage\n3. Computeregionsofinterestfor\neachside.\n4. Detectlandmarksand\nsegmentations\n5. Computelinesanddistances\n6. Computeangles\n7. Generatereports","1. Same.\n2. Same.\n3. Same.\n4. Same.\n5. Similar.Thesubjectalsovisualizeslinesof\nwhichdistancesaremeasuredandthusraises\nnonewquestionsregardingsafetyand\neffectiveness.Standaloneperformancetesting\nisperformedtoshowthatthesubjectdevice\nperformsasintended.SeeSection20:\nPerformanceTesting-Clinical.\n6. ThepredicatemeasuresOAparameters\n(grades),whilethesubjectcomputesangles.\nStandaloneperformancetestingisperformed\ntoshowthatthesubjectdeviceperformsas\nintended.SeeSection20:Performance\nTesting-Clinical.\n7. Same"],["Technology","● Convolutionalneural\nnetworksfor\n○ classification\n○ landmarking\n○ segmentation\n○ grading","● Convolutionalneuralnetworksfor\n○ classification\n○ landmarking\n○ segmentation\n● Classicalmethodsforcomputing:\n○ auxiliarypoints\n○ lengths","● Similar.Thetechnologyofthesubjectdevice\niscontainedinthepredicateandthusraises\nnonewquestionsregardingsafetyand\neffectiveness.Standaloneperformancetesting\nisperformedtoshowthatthesubjectdevice\nperformsasintended.SeeSection20:\nPerformanceTesting-Clinical"]],"caption_candidate":"IBLabLAMA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p11-t0","doc_id":"K223646","page_num":11,"bbox":[76.67,566.57,534.42,630.5],"n_rows":2,"n_cols":7,"columns":["IBLabLAMAvs.GT-PrimaryObjective:Agreement","","","","","",""],"rows":[["IBLabLAMAvs.GT-PrimaryObjective:Agreement","","","","","",""],["Variable","Unit","No.1","MeanDiff.","Std.Dev.","Lower\nLOA","Upper\nLOA"]],"caption_candidate":"coefficient(ICC)foreachmeasurement.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223646-p12-t0","doc_id":"K223646","page_num":12,"bbox":[104.94,111.36,524.9,617.72],"n_rows":37,"n_cols":6,"columns":["","","","","(lowerCI)","(upperCI)"],"rows":[["","","","","(lowerCI)","(upperCI)"],["","","","","",""],["MAD","[mm]","244 -1.37","2.54","-6.89","4.15"],["","","","","",""],["FemurLength","[cm]","208 0.09","0.16","-0.26","0.45"],["","","","","",""],["TibiaLength","[cm]","244 0.01","0.13","-0.27","0.28"],["","","","","",""],["LegLength","[cm]","208 0.05","0.12","-0.23","0.32"],["","","","","",""],["LLD","[mm]","77 0.13","1.4","-3.16","3.43"],["","","","","",""],["HKA","[°]","244 -0.19","0.73","-1.79","1.4"],["","","","","",""],["aTFA","[°]","244 -0.51","1.18","-3.08","2.05"],["","","","","",""],["AMA","[°]","244 0.06","0.89","-1.88","1.99"],["","","","","",""],["JLCA","[°]","244 0.22","1.35","-2.72","3.15"],["","","","","",""],["mLPFA","[°]","208 2.48","2.45","-2.89","7.85"],["","","","","",""],["mLDFA","[°]","244 -0.37","0.96","-2.46","1.72"],["","","","","",""],["mMPTA","[°]","244 -0.01","1.28","-2.79","2.77"],["","","","","",""],["mLDTA","[°]","244 -0.62","2.05","-5.08","3.85"],["","","","","",""],["","","IBLabLAMA -SecondaryObje","ctive","",""],["","","","","",""],["","","ArthroplastyDetection(TKAand","THA)","",""],["","","","","",""],["","Sensit","ivity","Specificity","",""],["","","","","",""],["","95.0","5%","99.80%","",""],["","","","","",""],["","(90.29%,","98.96%)","(99.39%,100.00","%)",""]],"caption_candidate":"(lowerCI) (upperCI)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223646-p12-t1","doc_id":"K223646","page_num":12,"bbox":[129.39,506.6,481.76,652.72],"n_rows":5,"n_cols":2,"columns":["IBLabLAMA -SecondaryObjective",""],"rows":[["IBLabLAMA -SecondaryObjective",""],["ArthroplastyDetection(TKAandTHA)",""],["Sensitivity","Specificity"],["95.05%\n(90.29%,98.96%)","99.80%\n(99.39%,100.00%)"],["FailureRate",""]],"caption_candidate":"mLDTA [°] 244 -0.62 2.05 -5.08 3.85","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223659-p6-t0","doc_id":"K223659","page_num":6,"bbox":[48.99,138.59,539.25,661.19],"n_rows":6,"n_cols":5,"columns":["","Device","","Jazz","IcoBrain"],"rows":[["","Device","","Jazz","IcoBrain"],["Regulation Number","","","21 CFR 892.2050","21 CFR 892.2050"],["Device Classification\nName","","","System, Image processing, Radiological","System, Image processing, Radiological"],["Product Code","","","QIH (LLZ)","LLZ"],["Regulatory Class","","","II","II"],["Intended Use /\nIndications for use","","","Jazz is intended for the labeling,\nvisualization and volumetric\nquantification of segmentable brain\nstructures from a set of MR images, for\npatients with a known diagnosis of\nmultiple sclerosis (for the multiple\nsclerosis pipeline) and/or brain\nmetastasis (for the metastasis pipeline),\nand the production of a radiological\nreport.","icobrain is intended for automatic\nlabeling, visualization and volumetric\nquantification of segmentable brain\nstructures from a set of MR or NCCT\nimages. This software is intended to\nautomate the current manual process of\nidentifying, labeling and quantifying the\nvolume of segmentable brain structures\nidentified on MR or NCCT images.\nicobrain consists of two distinct image\nprocessing pipelines: icobrain cross and\nicobrain long.\n• icobrain cross is intended to provide\nvolumes from MR or NCCT images\nacquired at a single time point.\n• icobrain long is intended to provide\nchanges in volumes between two MR\nimages that were acquired on the same\nscanner, with the same image acquisition\nprotocol and with same contrast at two\ndifferent timepoints.\nThe results of icobrain cross cannot be\ncompared with the results of icobrain\nlong."]],"caption_candidate":"classification.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223659-p8-t0","doc_id":"K223659","page_num":8,"bbox":[49.13,196.44,552.12,304.49],"n_rows":6,"n_cols":2,"columns":["","• This summary includes only information that is also covered in the body of the 510(k)."],"rows":[["","• This summary includes only information that is also covered in the body of the 510(k)."],["","• This summary does not contain any puffery or unsubstantiated labeling claims."],["","• This summary does not contain any raw data, i.e., contains only summary data."],["Declarations:","• This summary does not contain any trade secret or confidential commercial"],["","information."],["","• This summary does not contain any patient identification information."]],"caption_candidate":"safe and effective as the predicate, and does not raise different questions of safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p4-t0","doc_id":"K223724","page_num":4,"bbox":[90.0,169.52,505.27,757.52],"n_rows":63,"n_cols":2,"columns":["1.","SUBMITTER"],"rows":[["1.","SUBMITTER"],["",""],["","NameandAddress: ManteiaTechnologiesCo.,Ltd."],["",""],["","1903-1904,BTower,ZijinPlaza,"],["",""],["","No.1811HuandaoEastRoad,"],["",""],["","Xiamen,China"],["",""],["","EstablishmentRegistration"],["",""],["","Number: 3016686005"],["",""],["","ContactPerson: ChaoFang"],["",""],["","RA&QAManager"],["",""],["","Email:fangchao@manteiatech.com"],["",""],["","DateofPreparation: July9,2023"],["",""],["2.","DEVICE"],["",""],["","Device/TradeName: MOZITPS"],["",""],["","CommonName: MOZITreatmentPlanningSystem(MOZITPS)"],["",""],["","ProductClassification: ClassII"],["",""],["","ClassificationName: System,Planning,RadiationTherapyTreatment"],["",""],["","ProductCode: MUJ"],["",""],["","RegulationNumber: 21CFR892.5050"],["",""],["","RegulationDescription: Medicalcharged-particleradiationtherapysystem"],["",""],["3.","PREDICATEDEVICE"],["",""],["","PredicateDevice: K172163(EclipseTreatmentPlanningSystem(Eclipse"],["",""],["","TPS))"],["",""],["","ReferenceDevice1: K191928(AccuContourTM)"],["",""],["","ReferenceDevice2: K182624(MIM-MRTDosimetry)"],["",""],["4.","DeviceDescription:"],["",""],["","Theproposeddevice,MOZI TreatmentPlanningSystem (MOZITPS), is astandalonesoftware"],["",""],["","which is used to plan radiotherapy treatments (RT) for patients with malignant or benign"],["",""],["","diseases."],["",""],["","Itscorefunctionsincludeimageprocessing,structuredelineation,plandesign,optimizationand"],["",""],["","evaluation. Other functions include user login, graphical interface, system and patient"],["",""],["","management.ItcanprovideaplatformforcompletingtherelatedworkofthewholeRTplan."],["",""],["","Theproductusesgenerallyacceptedmethodsforbelowautomaticfunction:"]],"caption_candidate":"1. SUBMITTER","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223724-p6-t0","doc_id":"K223724","page_num":6,"bbox":[62.52,105.84,775.02,498.72],"n_rows":6,"n_cols":5,"columns":["ITEM","SubjectDevice","PredicateDevice\nK172163","ReferenceDevice\nK191928","ReferenceDevice\nK182624"],"rows":[["ITEM","SubjectDevice","PredicateDevice\nK172163","ReferenceDevice\nK191928","ReferenceDevice\nK182624"],["RegulatoryInformation","","","",""],["RegulationNo.","21CFR892.2050","21CFR892.2050","21CFR892.2050","21CFR892.2050"],["ProductCode","MUJ","MUJ","QKB","LLZ"],["Class","II","II","II","II"],["IndicationforUse","TheMOZITreatment\nPlanningSystem(MOZI\nTPS)isusedtoplan\nradiotherapytreatments\nforpatientswith\nmalignantorbenign\ndiseases.MOZITPSis\nusedtoplanexternal\nbeamirradiationwith\nphotonbeams.","TheEclipseTreatment\nPlanningSystem(Eclipse\nTPS)isusedtoplan\nradiotherapytreatments\nforpatientswith\nmalignantorbenign\ndiseases.EclipseTPSis\nusedtoplanexternal\nbeamirradiationwith\nphoton,electronand\nprotonbeams,aswellas\nforinternalIrradiation\n(brachytherapy)\ntreatments.\nInaddition,theEclipse\nProtonEyealgorithmis\nspecificallyindicatedfor\nplanning proton treatment\nofneoplasmsoftheeye.","Itisusedbyradiation\noncology department to\nregistermulti-modality\nimages and segment\n(non-contrast)CT\nimages,togenerate\nneededinformationfor\nTreatmentplanning,\ntreatmentevaluationand\ntreatmentadaptation.","MIMsoftwareisusedbytrained\nmedicalprofessionalsasatooltoaid\ninevaluationandInformation\nmanagementofdigitalmedical\nimages.Themedicalimage\nmodalitiesinclude,butarenotlimited\nto,CT,MRI,CR,DX,MG,US,\nSPECT,PETandXAassupportedby\nACR/NEMADICOM3.0.MIM\nassistsinthefollowingindications:\nReceive,transmit,store,\n\nretrieve,display,print,and\nprocessmedicalimagesand\nDICOMobjects.\nCreate,displayandprintreports\n\nfrommedicalimages.\nRegistration,fusiondisplay,and\n\nreviewofmedicalimagesfor\ndiagnosis,treatmentevaluation,"]],"caption_candidate":"DeviceComparisonTable","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p7-t0","doc_id":"K223724","page_num":7,"bbox":[62.52,90.24,774.99,504.24],"n_rows":17,"n_cols":5,"columns":["","","","","andtreatmentplanning.\nEvaluationofcardiacleft\n\nventricularfunctionand\nperfusion.\nLocalizationanddefinitionof\n\nobjectssuchastumorsand\nnormaltissuesinmedical\nimages."],"rows":[["","","","","andtreatmentplanning.\nEvaluationofcardiacleft\n\nventricularfunctionand\nperfusion.\nLocalizationanddefinitionof\n\nobjectssuchastumorsand\nnormaltissuesinmedical\nimages."],["Label/labeling","Conformwith21CFR\nPart801","Conformwith21CFR\nPart801","Conformwith21CFR\nPart801","Conformwith21CFR\nPart801"],["OperatingSystem","Windows","Windows","Windows","WindowsandMAC"],["TechnologicalCharacteristics","","","",""],["Dosecalculationalgorithms","MonteCarlo(photon)","AAA、AXB","N/A","N/A"],["Autorigidregistrationalgorithms","Intensitybased","Intensitybased","Intensitybased","Intensitybased"],["Autodeformableregistrationalgorithms","Intensitybased","Intensitybased","Intensitybased","Intensitybased"],["Autosegmentationalgorithms","Deeplearning","Atlasbased","Deeplearning","Atlasbased"],["GraphicalUserInterfaceFeatures","","","",""],["Multiple-instanceapplication","Yes","Yes","N/A","N/A"],["Multiple-workspacelayout","Yes","Yes","N/A","N/A"],["Graphicaldisplay/editingoffield\nparameters","Yes","Yes","N/A","N/A"],["Beam's-Eye-Viewdisplay","Yes","Yes","N/A","N/A"],["3Dpatientimagedisplay","Yes","Yes","N/A","N/A"],["Dose-VolumeHistogramdisplay","Yes","Yes","N/A","N/A"],["PatientManagementFeatures","","","",""],["DICOMRT","Yes","Yes","N/A","N/A"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p8-t0","doc_id":"K223724","page_num":8,"bbox":[62.52,90.24,774.99,489.12],"n_rows":18,"n_cols":5,"columns":["","(the device supports RT\nImage/ RT Structure/ RT\nPlan/RTDose)","(the device supports RT\nImage/ RT Structure/ RT\nPlan/RTDose)","",""],"rows":[["","(the device supports RT\nImage/ RT Structure/ RT\nPlan/RTDose)","(the device supports RT\nImage/ RT Structure/ RT\nPlan/RTDose)","",""],["Import/Delete/Export/Edit/Retrieve\npatientdata","Yes","Yes","N/A","N/A"],["ImageProcessingFeatures","","","",""],["CT/MRmanualimageregistration","Yes","Yes","Yes","Yes"],["Autorigidregistration","Yes(IntensityBased)","Yes(IntensityBased)","Yes(IntensityBased)","Yes(IntensityBased)"],["Autodeformableregistration","Yes(IntensityBased)","Yes(IntensityBased)","Yes(IntensityBased)","Yes(IntensityBased)"],["StructureDelineationFeatures","","","",""],["AutomaticCTsegmentationtool","Yes(deeplearning)","Yes(Atlasbased)","Yes(deeplearning)","Yes(Atlasbased)"],["ManualCTsegmentationtool","Yes","Yes","Yes","Yes"],["PlanDesign&PlanOptimizationFeatures","","","",""],["PhotonCalculation","Yes","Yes","N/A","N/A"],["-EnergyRange","1MeV–20MeV","1MeV–50MeV","N/A","N/A"],["-3-dimensionalconformalradiation\ntherapyPlanning","Yes","Yes","N/A","N/A"],["-Intensitymodulatedradiotherapy\nPlanning","Yes","Yes","N/A","N/A"],["-Volumetricmodulatedarctherapy\nPlanning","Yes","Yes","N/A","N/A"],["-Directionalheterogeneity\ncorrection","Yes","Yes","N/A","N/A"],["-TreatmentHeadmodelling","Yes","Yes","N/A","N/A"],["-DoseDynamicArcplanning","Yes","Yes","N/A","N/A"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p9-t0","doc_id":"K223724","page_num":9,"bbox":[62.52,90.24,775.02,476.64],"n_rows":24,"n_cols":5,"columns":["-IMRToptimization","Yes","Yes","N/A","N/A"],"rows":[["-IMRToptimization","Yes","Yes","N/A","N/A"],["-VMAToptimization","Yes","Yes","N/A","N/A"],["-DoseCalculation","Yes(MonteCarlo)","Yes(AAA、AXB)","N/A","N/A"],["-Plannormalization","Yes","Yes","N/A","N/A"],["PlanEvaluationFeatures","","","",""],["CreateQAplan","Yes","Yes","N/A","N/A"],["Planevaluationtools","Yes","Yes","N/A","N/A"],["Isodoselevelsdisplay","2D","2D,3D","N/A","N/A"],["Referencepointdosesummary","Yes","Yes","N/A","N/A"],["DoseVolumeHistogramplot","Yes","Yes","N/A","N/A"],["Plansummingtool","Yes","Yes","N/A","N/A"],["Plancomparisontools","Yes","Yes","N/A","N/A"],["Planardoseexport","Yes","Yes","N/A","N/A"],["Planningreportoutput","Yes","Yes","N/A","N/A"],["-Graphicswindowscreendump","Yes","Yes","N/A","N/A"],["-Imagesetinformation","Yes","Yes","N/A","N/A"],["-ContouringStructuralinformation","Yes","Yes","N/A","N/A"],["-Patientadministrationdata","Yes","Yes","N/A","N/A"],["-Patientorientation","Yes","Yes","N/A","N/A"],["-Planparameters","Yes","Yes","N/A","N/A"],["-Geometricaldisplaysofplandata","Yes","Yes","N/A","N/A"],["-Fieldinformation","Yes","Yes","N/A","N/A"],["-Dosedistribution","Yes","Yes","N/A","N/A"],["-DVHplot","Yes","Yes","N/A","N/A"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p11-t0","doc_id":"K223724","page_num":11,"bbox":[97.44,626.14,497.82,754.32],"n_rows":7,"n_cols":4,"columns":["BodyPart","OAR","MeanDSC\nvalues","Meanstandard\ndeviation"],"rows":[["BodyPart","OAR","MeanDSC\nvalues","Meanstandard\ndeviation"],["Head&Neck","Brain","0.98","0.01"],["","Brainstem","0.88","0.03"],["","BrachialPlexus_L","0.61","0.05"],["","BrachialPlexus_R","0.64","0.05"],["","Esophagus","0.84","0.02"],["","Eye-L","0.93","0.02"]],"caption_candidate":"samplesizeareasfollows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p12-t0","doc_id":"K223724","page_num":12,"bbox":[97.44,72.24,497.88,764.52],"n_rows":43,"n_cols":4,"columns":["","Eye-R","0.93","0.02"],"rows":[["","Eye-R","0.93","0.02"],["","InnerEar-L","0.78","0.06"],["","InnerEar-R","0.82","0.04"],["","Larynx","0.87","0.02"],["","Lens-L","0.77","0.07"],["","Lens-R","0.72","0.08"],["","Mandible","0.90","0.02"],["","MiddleEar_L","0.73","0.04"],["","MiddleEar_R","0.74","0.04"],["","OpticNerve_L","0.61","0.07"],["","OpticNerve_R","0.62","0.08"],["","OralCavity","0.90","0.03"],["","OpticChiasm","0.64","0.10"],["","Parotid-L","0.83","0.03"],["","Parotid-R","0.83","0.04"],["","PharyngealConstrictors_U","0.87","0.03"],["","PharyngealConstrictors_M","0.88","0.02"],["","PharyngealConstrictors_L","0.87","0.03"],["","Pituitary","0.74","0.14"],["","SpinalCord","0.85","0.04"],["","Submandibular_L","0.86","0.04"],["","Submandibular_R","0.87","0.03"],["","TemporalLobe_L","0.89","0.03"],["","TemporalLobe_R","0.89","0.03"],["","Thyroid","0.86","0.03"],["","TMJ_L","0.79","0.06"],["","TMJ_R","0.74","0.06"],["","Trachea","0.90","0.02"],["Thorax","Esophagus","0.80","0.05"],["","Heart","0.98","0.01"],["","Lung_L","0.99","0.00"],["","Lung_R","0.99","0.00"],["","SpinalCord","0.97","0.02"],["","Trachea","0.95","0.02"],["Abdomen","Duodenum","0.64","0.05"],["","Kidney_L","0.96","0.02"],["","Kidney_R","0.97","0.01"],["","Liver","0.95","0.02"],["","Pancreas","0.79","0.04"],["","SpinalCord","0.82","0.02"],["","Stomach","0.89","0.02"],["Pelvic-Man","Bladder","0.92","0.03"],["","BowelBag","0.89","0.04"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223724-p13-t0","doc_id":"K223724","page_num":13,"bbox":[97.44,72.24,497.88,265.44],"n_rows":12,"n_cols":4,"columns":["","FemurHead_L","0.96","0.02"],"rows":[["","FemurHead_L","0.96","0.02"],["","FemurHead_R","0.95","0.02"],["","Marrow","0.90","0.02"],["","Prostate","0.85","0.04"],["","Rectum","0.88","0.03"],["","SeminalVesicle","0.72","0.07"],["Pelvic-Female","Bladder","0.88","0.02"],["","BowelBag","0.87","0.02"],["","FemurHead_L","0.96","0.02"],["","FemurHead_R","0.95","0.02"],["","Marrow","0.89","0.02"],["","Rectum","0.77","0.04"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223726-p5-t0","doc_id":"K223726","page_num":5,"bbox":[113.64,67.68,594.0,149.28],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion Precision\n(TSX-304A/4) V10.10\nwith AiCE","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K220986","September\n12, 2022"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223726-p6-t0","doc_id":"K223726","page_num":6,"bbox":[108.73,55.28,589.4,641.76],"n_rows":40,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["D","evice Name,","","","Aquilion Precision (TSX‐","","","Aquilion Precision (TSX‐","","","",""],["","Model Number","","","304A/4) V10.14 with AiCE","","","304A/4) V10.10 with AiCE","","","",""],["","510(k) Number","","","This submission","","","K220986","","","",""],["AiCE Modifications","","","","","","","","","","",""],["• Scan Regions","","","","Abdomen and Pelvis/","","Abdomen and Pelvis/\nChest/Cardiac","","","*Added","",""],["","","","","Chest/Cardiac/","","","","","","",""],["","","","","Extremities*/Brain*/","","","","","","",""],["","","","","Inner Ear*","","","","","","",""],["","","","","","","","","","","",""],["• Magnified\nreconstruction -\nAvailable\nmagnification\nSize (D-FOV)","","","","BODY / BODY SHARP:","","BODY / BODY SHARP:\nMin. 100 mm\nLUNG:\nMin. 100 mm\nCARDIAC:\nMin. 70 mm\nMax. 500 mm","","","The minimum FOV\ndiffers depending\non the anatomical\nregion.","",""],["","","","","Min. 100 mm","","","","","","",""],["","","","","","","","","","","",""],["","","","","LUNG:","","","","","","",""],["","","","","Min. 100 mm","","","","","","",""],["","","","","","","","","","","",""],["","","","","CARDIAC:","","","","","","",""],["","","","","Min. 70 mm","","","","","","",""],["","","","","","","","","","","",""],["","","","","BONE / INNER EAR:","","","","","","",""],["","","","","Min. 50 mm","","","","","","",""],["","","","","","","","","","","",""],["","","","","BRAIN CTA:","","","","","","",""],["","","","","Min. 100 mm","","","","","","",""],["","","","","","","","","","","",""],["","","","","Max. 500 mm","","","","","","",""],["","","","","","","","","","","",""],["• Reconstruction\nprocessing\nsystem [AiCE]\n(CSAL-002A)","","","Option\n[Reconstruction Processing\nUnit required]","Option","","N/A\n[AiCE implemented with\nReconstruction Processing\nUnit (CCRS-003B)]","","","","",""],["","","","","[Reconstruction Processing","","","","","","",""],["","","","","Unit required]","","","","","","",""],["• Applicable\nanatomical\nregions","","","","• BODY and BODY SHARP","","• BODY and BODY SHARP\n(For Abdomen and\nPelvis)\n• LUNG (For Chest)\n• CARDIAC (For Cardiac)","","","*Added","",""],["","","","","(For Abdomen and","","","","","","",""],["","","","","Pelvis)","","","","","","",""],["","","","","• LUNG (For Chest)","","","","","","",""],["","","","","• CARDIAC (For Cardiac)","","","","","","",""],["","","","","• BONE (For extremities)*","","","","","","",""],["","","","","• BRAIN CTA (For brain)*","","","","","","",""],["","","","","• INNER EAR (For inner","","","","","","",""],["","","","","ear)*","","","","","","",""],["","","","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p6-t0","doc_id":"K223754","page_num":6,"bbox":[93.36,211.68,557.76,387.12],"n_rows":7,"n_cols":2,"columns":["Manufacturer","Proportion of DICOMs"],"rows":[["Manufacturer","Proportion of DICOMs"],["GE Healthcare","2%"],["AGFA","1%"],["Fujifilm Corporation","70%"],["KODAK","8%"],["Phillips Medical Systems","1%"],["Samsung Electronics","18%"]],"caption_candidate":"BraveCX device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p8-t0","doc_id":"K223754","page_num":8,"bbox":[95.79,261.24,538.29,716.16],"n_rows":7,"n_cols":9,"columns":["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],"rows":[["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],["","Trade Name","","","BraveCX","","","Lunit INSIGHT CXR Triage",""],["510(k) Number","","","NA","","","K211733","",""],["Product Code","","","QFM","","","QFM","",""],["Regulation\nNumber","","","892.2080","","","892.2080","",""],["Regulation\nName","","","Radiology","","","Radiology","",""],["Indications for\nUse","","","BraveCX is a radiological\ncomputer-assisted triage and\nnotification software that analyzes\nadult (≥18 years old) chest X-ray\nimages for the presence of pre-\nspecified suspected critical findings\n(pleural effusion and/or\npneumothorax). BraveCX uses an\nartificial intelligence algorithm to\nanalyze images for features\nsuggestive of critical findings and\nprovides case-level output available\nin the PACS/workstation for\nworklist prioritization or triage. As\na passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nBraveCX does not send a proactive","","","Lunit INSIGHT CXR Triage is\na radiological computer-\nassisted triage and notification\nsoftware that analyzes adult\nchest X-ray images for the\npresence of pre-specified\nsuspected critical findings\n(pleural effusion and/or\npneumothorax). Lunit\nINSIGHT CXR Triage uses an\nartificial intelligence algorithm\nto analyze images for features\nsuggestive of critical findings\nand provides case-level output\navailable in the\nPACS/workstation for worklist\nprioritization or triage. As a\npassive notification for","",""]],"caption_candidate":"Table 5B – Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p9-t0","doc_id":"K223754","page_num":9,"bbox":[95.79,58.44,538.29,719.76],"n_rows":7,"n_cols":9,"columns":["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],"rows":[["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],["","Trade Name","","","BraveCX","","","Lunit INSIGHT CXR Triage",""],["","","","alert directly to the appropriately\ntrained medical specialists.\nBraveCX is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\npleural effusion and/or\npneumothorax. Its results are not\nintended to be used on a stand-\nalone basis for clinical decision-\nmaking.","","","prioritization-only software\ntool within standard of care\nworkflow, Lunit INSIGHT\nCXR Triage does not send a\nproactive alert directly to the\nappropriately trained medical\nspecialists. Lunit INSIGHT\nCXR Triage is not intended to\ndirect attention to specific\nportions of an image or to\nanomalies other than pleural\neffusion and/or pneumothorax.\nIts results are not intended to\nbe used on a stand-alone basis\nfor clinical decision-making.","",""],["Notification-\nonly, parallel\nworkflow tool","","","Yes","","","Yes","",""],["User","","","Appropriately trained medical\nspecialists who are qualified to\ninterpret chest radiographs","","","Appropriately trained medical\nspecialists who are qualified to\ninterpret chest radiographs","",""],["Targeted\nclinical\ncondition,\nanatomy, and\nmodality","","","Pleural effusion, pneumothorax\nChest/Lung Frontal Chest X-ray","","","Pleural effusion, pneumothorax\nChest/Lung Frontal Chest X-\nray","",""],["Algorithm for\npre-specified\ncritical findings\ndetection","","","BraveCX is a Deep Learning\nArtificial Intelligence (AI) software\nthat was trained to detect pleural\neffusion and pneumothorax in chest\nX-Ray images. BraveCX uses a\nvendor agnostic algorithm\ncompatible with DICOM chest X-\nRay images","","","Lunit INSIGHT CXR is deep\nlearning based software that\nassists radiologists or clinicians\nin the interpretation of chest x-\nray. AI algorithm designed to\ndetect pleural effusion and\npneumothorax in chest X-ray\nimages. Lunit INSIGHT CXR\nTriage uses a vendor agnostic\nalgorithm compatible with\nDICOM chest X-ray images","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p10-t0","doc_id":"K223754","page_num":10,"bbox":[95.8,58.44,538.28,691.2],"n_rows":5,"n_cols":9,"columns":["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],"rows":[["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],["","Trade Name","","","BraveCX","","","Lunit INSIGHT CXR Triage",""],["Radiological\nimages format","","","DICOM","","","DICOM","",""],["Computational\nPlatform","","","BraveCX is supplied as a licensed\nApplication Programming Interface\n(API) that can be deployed either as\na cloud-based service, directly on\npremises, or integrated with third-\nparty systems.","","","Lunit INSIGHT CXR Triage is\ndesigned as a software module\nthat can be deployed on several\ncomputing and X-ray imaging\nplatforms such as radiological\nimaging equipment, PACS, On\nPremise or On Cloud.","",""],["Device output in\ncase of positive\ndetection","","","BraveCX automatically runs after\nimage acquisition.\nThe user may prioritize reporting\ntasks by grouping images flagged by\nBraveCX together. Results are\ndisplayed through the worklist\ninterface of PACS/workstation\nNo markup on original image.\nSecondary capture of the finding.\nUpon image acquisition from other\nradiological imaging equipment\n(e.g. X-ray systems), an on-device,\ntechnologist notification indicating\nwhich cases were flagged in the\nSecondary Capture image by Brave\nCX in PACS, is generated 15\nminutes after interpretation by the\nuser.\nThe on-device notification is\ncontextual and does not provide any\ndiagnostic information. It is not\nintended to inform any clinical\ndecision, prioritization, or action to\nthe technologist.","","","Lunit INSIGHT CXR Triage\nautomatically runs after image\nacquisition and prioritizes and\ndisplays the analysis result\nthrough the worklist interface\nof PACS/workstation.\nNo markup on original image.\nSecondary capture of the\nfinding.\nUpon image acquisition from\nother radiological imaging\nequipment (e.g. X-ray systems),\nan on-device, technologist\nnotification indicating which\ncases were flagged in the\nSecondary Capture image by\nLunit INSIGHT CXR Triage in\nPACS, is generated 15 minutes\nafter interpretation by the user.\nThe on-device notification is\ncontextual and does not provide\nany diagnostic information. It is\nnot intended to inform any\nclinical decision, prioritization,\nor action to the technologist.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p11-t0","doc_id":"K223754","page_num":11,"bbox":[95.79,58.44,538.29,627.36],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],"rows":[["","Manufacturer","","","Bering Ltd","","","Lunit Inc.",""],["","Trade Name","","","BraveCX","","","Lunit INSIGHT CXR Triage",""],["Notification\n(i.e., recipient,\ntiming and\nmeans of\nnotification)","","","Passive notification.\nImages with suspicion are flagged\nin PACS/workstation.","","","Passive notification.\nImages with suspicion are\nflagged in PACS/workstation.","",""],["Where\ngenerated\nresults (i.e.,\nDICOM files)\nare stored","","","Picture Archiving and\nCommunications (PACS) system or\nsome other local storage platform","","","PACS/Workstation","",""],["Performance\nlevel – Timing\nof notification","","","The average time taken for the\nnotification to travel from the\nBraveCX API to the point at which\nthe result is displayed in the\ndestination PACS/RIS/EPR\nworklist is 10.4 seconds.","","","The average time taken for the\nnotification to travel from the\nLunit INSIGHT CXR Triage to\nthe point at which the result is\ndisplayed in the destination\nPACS/RIS/EPR worklist is\n14.66 seconds.","",""],["Performance\nlevel –\naccuracy of\nclassification","","","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.988 (95% CI: [0.988,\n0.9887]\nSensitivity 92.62% (95% CI :\n[90.67%, 94.27%])\nSpecificity 98.11% (95% CI\n[97.33%, 98.71%])\nPneumothorax\nROC AUC > 0.95\nAUC : 0.972 (95% CI: [0.9727,\n0.9729])\nSensitivity 93.38% (95% CI:\n[92.23%, 94.40%])\nSpecificity 97.27% (95%CI:\n[96.49%-97.92%])","","","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.9686 (95% CI:\n[0.9547, 0.9824])\nSensitivity 89.86% (95% CI:\n[86.72, 93.00])\nSpecificity 93.48% (95% CI:\n[91.06, 95.91])\nPneumothorax\nROC AUC > 0.95\nAUC: 0.9630 (95% CI:\n[0.9521, 0.9739])\nSensitivity 88.92% (95% CI:\n[85.60, 92.24])\nSpecificity 90.51% (95% CI:\n[88.18, 92.83])","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p12-t0","doc_id":"K223754","page_num":12,"bbox":[93.36,532.56,557.76,706.8],"n_rows":6,"n_cols":4,"columns":["Characteristic","MIMIC (Pleural\nEffusion)","NIH (Pleural\nEffusion","CheXpert (Pleural\nEffusion)"],"rows":[["Characteristic","MIMIC (Pleural\nEffusion)","NIH (Pleural\nEffusion","CheXpert (Pleural\nEffusion)"],["Gender","","",""],["Male","54%","58%","55%"],["Female","46%","42%","45%"],["Ethnicity","","",""],["Asian","3%","N/A","12%"]],"caption_candidate":"Pleural Effusion classifier.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p13-t0","doc_id":"K223754","page_num":13,"bbox":[93.36,58.32,557.76,295.68],"n_rows":9,"n_cols":4,"columns":["Black","10%","N/A","6%"],"rows":[["Black","10%","N/A","6%"],["Hispanic","3%","N/A","4%"],["Other/Unknown","30%","N/A","25%"],["White","54%","N/A","53%"],["Age","","",""],["18-25","2%","9%","9%"],["25-35","4%","16%","8%"],["35-65","33%","63%","47%"],[">65","59%","12%","36%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p13-t1","doc_id":"K223754","page_num":13,"bbox":[86.16,375.6,557.76,707.76],"n_rows":12,"n_cols":4,"columns":["Characteristic","MIMIC\n(Pneumothorax)","NIH\n(Pneumothorax","CheXpert\n(Pneumothorax)"],"rows":[["Characteristic","MIMIC\n(Pneumothorax)","NIH\n(Pneumothorax","CheXpert\n(Pneumothorax)"],["Gender","","",""],["Male","60%","58%","53%"],["Female","40%","42%","47%"],["Ethnicity","","",""],["Asian","5%","N/A","10%"],["Black","10%","N/A","7%"],["Hispanic","3%","N/A","2%"],["Other/Unknown","5%","N/A","25%"],["White","77%","N/A","56%"],["Age","","",""],["18-25","4%","9%","8%"]],"caption_candidate":"Pneumothorax classifier.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223754-p14-t0","doc_id":"K223754","page_num":14,"bbox":[86.16,58.32,557.76,137.52],"n_rows":3,"n_cols":4,"columns":["25-35","7%","16%","7%"],"rows":[["25-35","7%","16%","7%"],["35-65","48%","63%","43%"],[">65","41%","12%","42%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223757-p6-t0","doc_id":"K223757","page_num":6,"bbox":[72.25,415.56,521.75,717.24],"n_rows":8,"n_cols":4,"columns":["","Predicate Device K203290","Subject Device K223757",""],"rows":[["","Predicate Device K203290","Subject Device K223757",""],["Information","(Bonelogic)","(Bonelogic 2.2)","Comparison"],["Classification Name","Medical image management\nand processing system","Medical image management\nand processing system","Identical"],["Service Type","Software","Software","Identical"],["Classification","21 CFR 892.2050","21 CFR 892.2050","Identical"],["Class","II","II","Identical"],["Product Code","LLZ","QIH","Identical"],["Indications for Use","Bonelogic software is intended\nto be used by specialized\nmedical practitioners to assist\nin the characterization of\nhuman anatomy with 3D\nvisualization and specific\nmeasurements. The medical\nimage modalities intended to\nbe used in the software are\ncomputed tomography (CT)\nimages, cone beam computed\ntomography (CBCT) images\nand weight-bearing cone beam\nCT (WBCT) images. The\nintended patient population is\nadults over 16 years of age.\nBonelogic software contains\nthe measurement template","Bonelogic software is to be\nused by orthopaedic healthcare\nprofessionals for diagnosis and\nsurgical planning in a hospital\nor clinic environment.\nBonelogic software provides:\nSemi-automatic segmentation\nwith manual or assisted input\nof bony structure identification\nfrom CT imaging input,\nThree-dimensional\nmathematical models of the\nanatomical structures of foot\nand ankle,\nMeasurement templates\ncontaining radiographic\nmeasures of foot and ankle,\nand tools for manually","Removal of wrist\nand hand related\nfunctionality and\naddition of an\noptional\nsemiautomatic\nsegmentation\nworkflow with\nassisted bone\nidentification\nprocess in the\nsubject device"]],"caption_candidate":"Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223757-p7-t0","doc_id":"K223757","page_num":7,"bbox":[72.28,70.44,521.72,510.72],"n_rows":8,"n_cols":4,"columns":["","Predicate Device K203290","Subject Device K223757",""],"rows":[["","Predicate Device K203290","Subject Device K223757",""],["Information","(Bonelogic)","(Bonelogic 2.2)","Comparison"],["","with a set of distance and\nangular measures. The\nmeasurements can be used for\ndiagnostic purposes. The\nthree-dimensional (3D)\nmodels are displayed and can\nbe manipulated in the\nsoftware. Together, the\ninformation from the\nmeasurements and the 3D\nvisualization can be used for\ntreatment planning in the field\nof orthopedics (foot and ankle,\nand hand and wrist). The 3D\nmodels can be outputted from\nthe software for traditional or\nadditive manufacturing. The\nphysical models generated\nbased on the 3D digital models\nare not intended for diagnostic\nuse.","obtaining linear and angular\nmeasurements,\nSurgical planning application\nfor foot and ankle using three-\ndimensional models of the\nanatomical structures and\nradiographic measures.\nThe three-dimensional models\nof the anatomical structures\ncombined with the\nmeasurements can be used for\nthe diagnosis of orthopaedic\nhealthcare conditions. The\nsurgical planning application\ncontaining the three-\ndimensional structural models\ncombined with the\nmeasurements can be used for\nthe planning of treatments and\noperations to correct\northopaedic healthcare\nconditions of foot and ankle.",""],["Input","Computed tomography\nDICOM images","Computed tomography\nDICOM Computed\ntomography","Identical"],["Image processing","Segmentation of bone\nstructures","Segmentation of bone\nstructures","Identical"],["Output","3D model of patient anatomy","3D model of patient anatomy","Identical"],["Measuring and\nplanning","Perform measurements for\npresurgical planning","Perform measurements for\npresurgical planning","Identical"],["Bone identification","Manual process","Manual and an optional\nsemiautomatic workflow with\nassisted input process\nperformed by artificial neural\nnetwork","Optional\nsemiautomatic\nbone\nidentification\nprocess in\nsubject device"]],"caption_candidate":"K233757","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p4-t0","doc_id":"K223771","page_num":4,"bbox":[226.17,467.28,519.93,585.78],"n_rows":7,"n_cols":5,"columns":["Classification Name","","21 CFR §","Product Code",""],"rows":[["Classification Name","","21 CFR §","Product Code",""],["","Primary","","",""],["System, imaging, pulsed doppler,\nultrasonic","","892.1550","IYN",""],["","Secondary","","",""],["System, imaging, pulsed echo,\nultrasonic","","892.1560","IYO",""],["Transducer, ultrasonic, diagnostic","","892.1570","ITX",""],["Automated Radiological Image\nProcessing Software","","892.2050","QIH",""]],"caption_candidate":"Common Name: Diagnostic ultrasound system and transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p5-t0","doc_id":"K223771","page_num":5,"bbox":[70.5,116.76,541.5,458.28],"n_rows":27,"n_cols":2,"columns":["","There is no change to the intended use and indications for use of the subject device as compared to the"],"rows":[["","There is no change to the intended use and indications for use of the subject device as compared to the"],["","predicates."],["",""],["","3.1 Indications for Use"],["",""],["","The Philips Lumify Diagnostic Ultrasound System is intended for diagnostic ultrasound imaging in"],["","B(2D), Color Doppler, Combined (B+Color), Pulsed Wave Doppler, and M-modes."],["",""],["","It is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications:"],["","Fetal/Obstetric, Abdominal, Pediatric, Cephalic, Urology, Gynecological, Cardiac Fetal Echo, Small"],["","Organ, Musculoskeletal, Peripheral Vessel, Carotid, Cardiac, Lung."],["",""],["","The Lumify system is a transportable ultrasound system intended for use in environments where"],["","healthcare is provided by healthcare professionals."],["",""],["","3.2 Intended Use"],["",""],["","The intended use of the product is to collect ultrasound image data that may be used by clinicians for"],["","diagnostic and procedural purposes. The product shall provide the ability for gathering clinically"],["","acceptable images and ultrasound data for the clinical presets and anatomies listed under the"],["","indications for use."],["",""],["","This product is intended to be installed, used, and operated only in accordance with safety procedures"],["","and operating instructions given in the product user information, and only for the purposes for which"],["","it was designed. However, nothing stated in the user information reduces the user’s responsibility for"],["","sound clinical judgement and best clinical procedure."],["",""]],"caption_candidate":"3. Indications for Use and Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p8-t0","doc_id":"K223771","page_num":8,"bbox":[81.2,91.8,530.87,487.11],"n_rows":14,"n_cols":9,"columns":["Standard Feature","","","","Lumify Diagnostic Ultrasound","","","Lumify Diagnostic Ultrasound",""],"rows":[["Standard Feature","","","","Lumify Diagnostic Ultrasound","","","Lumify Diagnostic Ultrasound",""],["","","","","System K223771 (Subject Device)","","","System K2030406 (Predicate Device)",""],["","Scientific Technology","","Ultrasound Imaging","","","Ultrasound Imaging","",""],["Intended Use","Intended Use","","Philips Lumify Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (2D), Pulsed\nWave, Color Doppler, Combined\n(B+Color), and M modes.","","","Philips Lumify Diagnostic Ultrasound\nSystem is intended for diagnostic\nultrasound imaging in B (2D), Pulsed\nWave, Color Doppler, Combined\n(B+Color), and M modes.","",""],["Indications for Use","","","Lumify Diagnostic Ultrasound\nSystem is indicated for diagnostic\nultrasound imaging and fluid flow\nanalysis in the following applications:\nFetal/Obstetric, Abdominal, Pediatric,\nCephalic, Urology, Gynecological,\nCardiac Fetal Echo, Small Organ,\nMusculoskeletal, Peripheral Vessel,\nCarotid, Cardiac, Lung.\nLumify is a transportable ultrasound\nsystem intended for use in\nenvironments where healthcare is\nprovided by healthcare professionals.","","","Lumify Diagnostic Ultrasound System\nis indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications:\nFetal/Obstetric, Abdominal, Pediatric,\nCephalic, Urology, Gynecological,\nCardiac Fetal Echo, Small Organ,\nMusculoskeletal, Peripheral Vessel,\nCarotid, Cardiac, Lung.\nLumify is a transportable ultrasound\nsystem intended for use in\nenvironments where healthcare is\nprovided by healthcare professionals.","",""],["","Modes of Operations","","B (2D), Pulse Wave, Color Doppler,\nCombined (B+Color), and M modes","","","B (2D), Pulse Wave, Color Doppler,\nCombined (B+Color), and M modes","",""],["","","","","","","","",""],["Transducers","Transducers","","L12-4\nS4-1\nC5-2","","","L12-4\nS4-1","",""],["","Primary Product Code","","IYN","","","IYN","",""],["","Secondary Product","","IYO, ITX, QIH","","","IYO, ITX","",""],["","Code","","","","","","",""],["Principles of Operation\n(subject merged B-lines\nFeature)","Principles of Operation","","Automatic counting of B-lines and\ndetection of merged B-lines, with\noptional manual adjustment of results\nprovided by the software.","","","Automatic counting of B-lines, with\noptional manual adjustment of results\nprovided by the software.","",""],["","(subject merged B-lines","","","","","","",""],["","Feature)","","","","","","",""]],"caption_candidate":"Lumify Diagnostic Ultrasound System with Expanded B-lines Software Feature","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p9-t0","doc_id":"K223771","page_num":9,"bbox":[90.32,570.28,445.5,609.58],"n_rows":3,"n_cols":4,"columns":["","Gender","","Male and Female"],"rows":[["","Gender","","Male and Female"],["","Age","","18 to> 89"],["","Ethnicity","","Hispanic or Latino and Not Hispanic or Latino"]],"caption_candidate":"The demographic distribution of the performance testing includes the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p10-t0","doc_id":"K223771","page_num":10,"bbox":[90.48,215.48,441.52,301.92],"n_rows":8,"n_cols":4,"columns":["","Sample size","Sensitivity","Specificity"],"rows":[["","Sample size","Sensitivity","Specificity"],["Transducer","","",""],["","(video loops)","(95% CI)","(95% CI)"],["","","",""],["All","416","0.83 (0.77, 0.88)","0.92 (0.88, 0.96)"],["C5-2","146","0.89 (0.79, 0.95)","0.96 (0.89, 0.99)"],["S4-1","150","0.81 (0.72, 0.88)","0.92 (0.80, 0.98)"],["L12-4","120","0.74 (0.57, 0.88)","0.89 (0.81, 0.95)"]],"caption_candidate":"abbreviated as CI) were as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223771-p10-t1","doc_id":"K223771","page_num":10,"bbox":[90.48,365.05,441.52,451.56],"n_rows":8,"n_cols":3,"columns":["","Sample size",""],"rows":[["","Sample size",""],["Transducer","","ICC (95% CI)"],["","(video loops)",""],["","",""],["All","416","0.91 (0.89, 0.93)"],["C5-2","146","0.94 (0.91, 0.95)"],["S4-1","150","0.87 (0.82, 0.90)"],["L12-4","120","0.91 (0.88, 0.94)"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223774-p6-t0","doc_id":"K223774","page_num":6,"bbox":[155.86,114.71,444.7,495.92],"n_rows":45,"n_cols":3,"columns":["Institution","Country # of i","m"],"rows":[["Institution","Country # of i","m"],["","",""],["Institution 17","USA","10"],["","",""],["Institution 18","USA","7"],["","",""],["Institution 19","USA","11"],["","",""],["Institution 20","USA","22"],["","",""],["Institution 21","USA","6"],["","",""],["Institution 22","USA","21"],["","",""],["Institution 23","Australia","15"],["","",""],["Institution 24","USA","10"],["","",""],["Institution 25","USA","11"],["","",""],["Institution 26","USA","10"],["","",""],["Institution 27","USA","2"],["","",""],["Institution 28","USA","1"],["","",""],["Institution 29","USA","7"],["","",""],["Institution 30","USA","6"],["","",""],["Institution 31","USA","4"],["","",""],["Institution 32","USA","1"],["","",""],["Institution 33","USA","2"],["","",""],["Institution 34","USA","2"],["","",""],["Institution 35","USA","6"],["","",""],["Institution 36","USA","14"],["","",""],["Institution 37","USA","3"],["","",""],["Equivalence","",""]],"caption_candidate":"Institution Country # of images","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223774-p14-t0","doc_id":"K223774","page_num":14,"bbox":[225.14,115.69,496.96,699.89],"n_rows":57,"n_cols":6,"columns":["Structure:","","M","IM Atlas","Contour P","rotégé"],"rows":[["Structure:","","M","IM Atlas","Contour P","rotégé"],["","","","","",""],["Glnd_Thyroid","0.47","±","0.18 0.","71 ± 0.16","(0.59)"],["","","","","",""],["Lens_L","0.22","±","0.23 0.","61 ± 0.17","(0.52)"],["","","","","",""],["Lens_R","0.22","±","0.22 0.","63 ± 0.15","(0.54)"],["","","","","",""],["Lips","0.38","±","0.14 0.","38 ± 0.14","(0.28)"],["","","","","",""],["OpticChiasm","0.04","±","0.07 0.","12 ± 0.11","(0.08)"],["","","","","",""],["OpticNrv_L","0.45","±","0.15 0.","53 ± 0.13","(0.46)"],["","","","","",""],["OpticNrv_R","0.44","±","0.14 0.","52 ± 0.12","(0.45)"],["","","","","",""],["Parotid_L","0.71","±","0.10 0.","80 ± 0.10","(0.75)"],["","","","","",""],["Parotid_R","0.71","±","0.09 0.","80 ± 0.06","(0.77)"],["","","","","",""],["Pituitary","0.38","±","0.18 0.","49 ± 0.15","(0.37)"],["","","","","",""],["SpinalCord","0.66","±","0.14 0.","63 ± 0.16","(0.57)"],["","","","","",""],["BrachialPlex_L","0.28","±","0.14 0.","37 ± 0.13","(0.25)"],["","","","","",""],["BrachialPlex_R","0.28","±","0.11 0.","36 ± 0.16","(0.23)"],["","","","","",""],["Breast_L","0.75","±","0.10 0.","74 ± 0.17","(0.65)"],["","","","","",""],["Breast_R","0.76","±","0.11 0.","77 ± 0.10","(0.71)"],["","","","","",""],["Bronchus","0.60","±","0.17 0.","66 ± 0.13","(0.56)"],["","","","","",""],["Carina","0.39","±","0.18 0.","51 ± 0.13","(0.43)"],["","","","","",""],["Cricoid","0.03","±","0.05 0.","03 ± 0.04","(-0.01)"],["","","","","",""],["Esophagus","0.49","±","0.16 0.","70 ± 0.15","(0.65)"],["","","","","",""],["Glnd_Thyroid","0.46","±","0.18 0.","67 ± 0.16","(0.57)"],["","","","","",""],["GreatVes","0.70","±","0.08 0.","74 ± 0.10","(0.65)"],["","","","","",""],["Heart","0.88","±","0.08 0.","90 ± 0.07","(0.88)"],["","","","","",""],["Humerus_Head_L","0.95","±","0.02 0.","95 ± 0.02","(0.94)"],["","","","","",""],["Humerus_Head_R","0.93","±","0.09 0.","96 ± 0.02","(0.90)"],["","","","","",""],["Kidney_L","0.74","±","0.18 0.","92 ± 0.05","(0.85)"],["","","","","",""],["Kidney_R","0.74","±","0.19 0.","91 ± 0.06","(0.84)"],["","","","","",""],["Larynx","0.45","±","0.21 0.","50 ± 0.16","(0.42)"],["","","","","",""],["Liver","0.85","±","0.11 0.","93 ± 0.06","(0.89)"]],"caption_candidate":"4.0.0 CT Model: Structure: MIM Atlas Contour ProtégéAI","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223774-p15-t0","doc_id":"K223774","page_num":15,"bbox":[119.59,115.69,499.79,699.89],"n_rows":57,"n_cols":8,"columns":["4.0.0 CT Model:","Structure:","","M","IM Atlas","Contour P","rotégé","A"],"rows":[["4.0.0 CT Model:","Structure:","","M","IM Atlas","Contour P","rotégé","A"],["","","","","","","",""],["","Lung_L","0.95","±","0.02 0.","96 ± 0.02","(0.96)","*"],["","","","","","","",""],["","Lung_R","0.95","±","0.03 0.","96 ± 0.02","(0.96)","*"],["","","","","","","",""],["","Musc_Constrict","0.41","±","0.16 0.","47 ± 0.15","(0.37)","*"],["","","","","","","",""],["","Pancreas","0.17","±","0.19 0.","45 ± 0.22","(0.32)","*"],["","","","","","","",""],["","SpinalCord","0.67","±","0.16 0.","66 ± 0.16","(0.62)","*"],["","","","","","","",""],["","Stomach","0.46","±","0.21 0.","80 ± 0.16","(0.72)","*"],["","","","","","","",""],["","Trachea","0.67","±","0.17 0.","73 ± 0.17","(0.65)","*"],["","","","","","","",""],["Abdomen","Bladder","0.72","±","0.23 0.","91 ± 0.12","(0.81)","*"],["","","","","","","",""],["","Bowel","0.46","±","0.14 0.","73 ± 0.11","(0.61)","*"],["","","","","","","",""],["","BowelBag","0.63","±","0.08 0.","68 ± 0.08","(0.62)","*"],["","","","","","","",""],["","CaudaEquina","0.62","±","0.15 0.","66 ± 0.13","(0.55)","*"],["","","","","","","",""],["","Kidney_L","0.74","±","0.17 0.","93 ± 0.03","(0.84)","*"],["","","","","","","",""],["","Kidney_R","0.75","±","0.18 0.","92 ± 0.05","(0.82)","*"],["","","","","","","",""],["","Liver","0.84","±","0.12 0.","92 ± 0.08","(0.86)","*"],["","","","","","","",""],["","SpinalCord","0.60","±","0.16 0.","63 ± 0.13","(0.55)","*"],["","","","","","","",""],["","Stomach","0.49","±","0.21 0.","81 ± 0.11","(0.70)","*"],["","","","","","","",""],["Pelvis","Bladder","0.73","±","0.22 0.","93 ± 0.11","(0.89)","*"],["","","","","","","",""],["","Bowel","0.37","±","0.15 0.","52 ± 0.19","(0.41)","*"],["","","","","","","",""],["","Colon_Sigmoid","0.20","±","0.17 0.","60 ± 0.26","(0.48)","*"],["","","","","","","",""],["","Femur_Head_L","0.90","±","0.08 0.","93 ± 0.05","(0.91)","*"],["","","","","","","",""],["","Femur_Head_R","0.90","±","0.08 0.","93 ± 0.04","(0.91)","*"],["","","","","","","",""],["","LN_Iliac","0.63","±","0.04 0.","72 ± 0.03","(0.68)","*"],["","","","","","","",""],["","PenileBulb","0.59","±","0.16 0.","63 ± 0.16","(0.58)","*"],["","","","","","","",""],["","Prostate","0.74","±","0.12 0.","85 ± 0.06","(0.82)","*"],["","","","","","","",""],["","Rectum","0.63","±","0.18 0.","83 ± 0.11","(0.79)","*"],["","","","","","","",""],["","Sacrum","0.87","±","0.01 0.","92 ± 0.00","(0.87)","*"],["","","","","","","",""],["","SeminalVes","0.38","±","0.27 0.","68 ± 0.15","(0.61)","*"],["","","","","","","",""],["SurePlan MRT","Bone","0.76","±","0.08 0.","87 ± 0.05","(0.74)","*"]],"caption_candidate":"4.0.0 CT Model: Structure: MIM Atlas Contour ProtégéAI","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223811-p4-t0","doc_id":"K223811","page_num":4,"bbox":[73.5,161.79,425.44,708.28],"n_rows":39,"n_cols":3,"columns":["Applicant:","","ImagenTechnologies,Inc."],"rows":[["Applicant:","","ImagenTechnologies,Inc."],["","","224W35thStSte500"],["","","New York, NY 10001"],["","",""],["ContactandPrimary","","RebeccaJones, Ph.D."],["Correspondent:","","VicePresident,ClinicalResearch"],["","","Headof Regulatory"],["","",""],["","","ImagenTechnologies,Inc."],["","","224W35thStSte500"],["","","New York, NY 10001"],["","","917-565-9319"],["","","rebecca.jones@imagen.ai"],["","",""],["SecondaryCorrespondent:","","AlexJ. Cadotte,Ph.D."],["","","SeniorDirector,DigitalHealth&Imaging"],["","",""],["","","MCRA"],["","","8037thStreet,NW,3rd Floor"],["","","Washington,DC 20001"],["","","202-742-3828"],["","","acadotte@mcra.com"],["","",""],["DatePrepared:","","September12,2023"],["","",""],["2. D EVICE","",""],["","",""],["","",""],["DeviceTradeName:","",""],["","L","ung-CAD"],["","",""],["DeviceCommonNameor","","MedicalImageAnalyzer"],["ClassificationName:","",""],["","",""],["Regulation:","2","1CFR 892.2070"],["","",""],["RegulatoryClass:","I","I"],["","",""],["ProductCode:","","MYN"]],"caption_candidate":"Applicant: ImagenTechnologies,Inc.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K223811-p6-t0","doc_id":"K223811","page_num":6,"bbox":[72.25,435.74,540.25,627.5],"n_rows":8,"n_cols":3,"columns":["","ProposedDevice","Predicate"],"rows":[["","ProposedDevice","Predicate"],["Number","K223811","K210666"],["Applicant","ImagenTechnologies,Inc.","ImagenTechnologies,Inc."],["DeviceName","Lung-CAD","Chest-CAD"],["ClassificationRegulation","892.2070","892.2070"],["ProductCode","MYN","MYN"],["ImageModality","X-ray","X-ray"],["StudyType","Chest","Chest"]],"caption_candidate":"Table 1: TechnologicalComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223811-p7-t0","doc_id":"K223811","page_num":7,"bbox":[72.33,72.13,540.33,462.5],"n_rows":10,"n_cols":3,"columns":["","ProposedDevice","Predicate"],"rows":[["","ProposedDevice","Predicate"],["ClinicalOutput","Identifyandmarkregionsof\ninterest(ROIs)onchest\nradiographsandlabelthebox\naroundtheROIasinterstitial\nthickening","Identifyandmarkregionsof\ninterest(ROIs)onchest\nradiographsandlabelthebox\naroundtheROIasoneofthe\nfollowing:Cardiac,\nMediastinum/Hila,Lungs,Pleura,\nBones,SoftTissues,Hardware,or\nOther"],["IntendedUsers","Physicians","Physicians"],["IntendedUserWorkflow","Deviceintendedforuseasa\nconcurrentreadingaidfor\nphysiciansinterpretingchest\nradiographs","Deviceintendedforuseasa\nconcurrentreadingaidfor\nphysiciansinterpretingchest\nradiographs"],["PatientPopulation","AdultswithChestRadiographs","AdultswithChestRadiographs"],["MachineLearning\nMethodology","SupervisedDeepLearning","SupervisedDeepLearning"],["Platform","Securecloud-basedprocessing\nanddeliveryofchestradiographs","Securecloud-basedprocessing\nanddeliveryofchestradiographs"],["ImageSource","DigitalX-ray","DigitalX-ray"],["ImageViewing","ImagedisplayedonPACSsystem","ImagedisplayedonPACSsystem"],["Privacy","HIPAACompliant","HIPAACompliant"]],"caption_candidate":"510(k) Summary Page4of8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223811-p9-t0","doc_id":"K223811","page_num":9,"bbox":[72.25,90.42,540.2,165.5],"n_rows":2,"n_cols":4,"columns":["Category","GroundTruth\nPositiven(%)","AUC","95%BootstrapCI"],"rows":[["Category","GroundTruth\nPositiven(%)","AUC","95%BootstrapCI"],["Interstitialthickening","126(2.5)","0.961","0.948,0.972"]],"caption_candidate":"Table 2: AUCoftheROCCurveforLung-CADPredictions","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223811-p9-t1","doc_id":"K223811","page_num":9,"bbox":[72.25,219.2,540.2,357.5],"n_rows":3,"n_cols":5,"columns":["Category","Sensitivity","Specificity","Positive\nPredictiveValue","Negative\nPredictiveValue"],"rows":[["Category","Sensitivity","Specificity","Positive\nPredictiveValue","Negative\nPredictiveValue"],["","95%\nWilson'sCI","95%\nWilson'sCI","95%\nWilson'sCI","95%\nWilson'sCI"],["Interstitialthickening","0.913\n(0.850,0.951)","0.866\n(0.856,0.875)","0.150\n(0.126,0.177)","0.997\n(0.995,0.999)"]],"caption_candidate":"Lung-CADPredictions","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p7-t0","doc_id":"K223830","page_num":7,"bbox":[70.88,270.11,535.36,699.46],"n_rows":3,"n_cols":4,"columns":["Catalog/\nReference\n(REF)","Model","","Model Description"],"rows":[["Catalog/\nReference\n(REF)","Model","","Model Description"],["2300","2300-01","","BK3000 ULTRASOUND SYSTEM W/O\nBATTERY\nThis configuration is primarily\nintended for Urology and General\nimaging applications."],["2300","2300-11","","BK3000 ULTRASOUND SYSTEM\nW/BATTERY\nThis configuration is primarily\nintended for Urology and General\nimaging applications."]],"caption_candidate":"Table 1: Ultrasound System 2300 available configurations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p8-t0","doc_id":"K223830","page_num":8,"bbox":[70.88,105.56,535.36,669.7],"n_rows":4,"n_cols":4,"columns":["Catalog/\nReference\n(REF)","Model","","Model Description"],"rows":[["Catalog/\nReference\n(REF)","Model","","Model Description"],["2300","2300-51","","BK5000 ULTRASOUND SYSTEM W/O\nBATTERY\nThis configuration is primarily\nintended for surgical applications."],["2300","2300-61","","BK5000 ULTRASOUND SYSTEM\nW/BATTERY\nThis configuration is primarily\nintended for surgical applications."],["2300","2300-56","","BKACTIV ULTRASOUND SYSTEM W/O\nBATTERY\nThis configuration is primarily\nintended for surgical,\nanesthesiology, urology and\ngeneral imaging applications."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p9-t0","doc_id":"K223830","page_num":9,"bbox":[70.88,105.56,535.36,347.33],"n_rows":2,"n_cols":4,"columns":["Catalog/\nReference\n(REF)","Model","","Model Description"],"rows":[["Catalog/\nReference\n(REF)","Model","","Model Description"],["2300","2300-66","","BKACTIV ULTRASOUND SYSTEM W/\nBATTERY\nThis configuration is primarily\nintended for surgical,\nanesthesiology, urology and\ngeneral imaging applications."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p10-t0","doc_id":"K223830","page_num":10,"bbox":[71.13,129.71,567.27,548.05],"n_rows":32,"n_cols":4,"columns":["Transducer","bk3000","bk5000","bkActiv"],"rows":[["Transducer","bk3000","bk5000","bkActiv"],["5C1e (9085) CURVED ARRAY TRANSDUCER","X","X","X"],["6C2 (9040) CURVED ARRAY TRANSDUCER","X","X","X"],["6C2s (9023) SMALL CURVED ARRAY TRANSDUCER","X","X","X"],["9C2 (9002) CURVED ARRAY TRANSDUCER","X","X","X"],["14L3 (9051) LINEAR ARRAY TRANSDUCER","X","X","X"],["13L4w (9011) WIDE LINEAR ARRAY TRANSDUCER","X","X","X"],["10L2w (9022) WIDE LINEAR ARRAY TRANSDUCER","X","X","X"],["18L5 (9070) SMALL GIGH-FREQUENCY LINEAR ARRAY TRANSDUCER","X","X","X"],["18L5s (9081) SMALL GIGH-FREQUENCY LINEAR ARRAY TRANSDUCER","X","X","X"],["8L2 (9032) LINEAR ARRAY TRANSDUCER","X","X","X"],["E13C2 (9029) ENDFIRE ENDOCAVITY TRANSDUCER","X","X","X"],["E14C4t (9018) TRIPLANE ENDOCAVITY TRANSDUCER","X","X","X"],["X14CL4b (9048) BIPLANE ENDOCAVITY TRANSDUCER","X","X","X"],["E10C4 (9019) ENDOCAVITY TRANSDUCER","X","X","X"],["20R3 (9052) ANORECTAL TRANSDUCER","X","X","X"],["N13C5 (9062) CURVED ARRAY TRANSDUCER","X","X","X"],["5P1 (9077) PHASED ARRAY TRANSDUCER","X","X","X"],["X18L5S (9009) HOCKEY STICK TRANSDUCER","X","X","X"],["N11C5S (9063) BURR HOLE TRANSDUCER","","X","X"],["I14C5I (9015) INTRAOPERATIVE I-SHAPE TRANSDUCER","","X","X"],["I14C5T (9016) INTRAOPERATIVE T-SHAPE TRANSDUCER","","X","X"],["I12C5B (9024) INTRAOPERATIVE BIPLANE TRANSDUCER","","X","X"],["I12C5 (9034) MINI-TRANSDUCER","","X","X"],["I12C4f (9066) LAPAROSCOPIC TRANSDUCER","","X","X"],["X12C4 (9026) DROP-IN TRANSDUCER","","X","X"],["X14L4 (9038) 3D ENDOCAVITY TRANSDUCER","","X","X"],["Rob12C4 (9096) ROBOTIC TRANSDUCER","","X","X"],["N20P6 (9007) MINIMALLY INVASIVE TRANSDUCER","","X","X"],["I13C3f (9076)\nADVANCED LAPAROSCOPIC TRANSDUCER","","X","X"],["T7P2m (9027)\nTEE TRANSDUCER","X","X","X"],["I13C3fx (9078)\nADVANCED LAPAROSCOPIC TRANSDUCER WITH TRACKING","","","X"]],"caption_candidate":"Table 2: Transducers used with Ultrasound System 2300 configurations","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p12-t0","doc_id":"K223830","page_num":12,"bbox":[73.1,150.47,739.31,574.6],"n_rows":13,"n_cols":4,"columns":["","Ultrasound System 2300","Ultrasound System 2300",""],"rows":[["","Ultrasound System 2300","Ultrasound System 2300",""],["","","",""],["Characteristic","","","Comment on"],["","Proposed device","Predicate",""],["","","","Comparison"],["","(K223830)","device",""],["","","",""],["Manufacturer","BK Medical ApS","BK Medical A(KpS2 22441)","Same"],["Common Name","Ultrasound System","Ultrasound System","Same"],["Name\n(Configuration models)","bk3000 (2300-01, 2300-11)\nbk5000 (2300-51, 2300-61)\nbkActiv (2300-56, 2300-66)","bk3000 (2300-01, 2300-11)\nbk5000 (2300-51, 2300-61)\nbkActiv (2300-56, 2300-66)","Same"],["Mode of Operation","B, M, PW, CFM, P, THI, CI, SE, CW\nCombination modes:\n2D+M, 2D+PW, 2D+C+PW,\n2D+P+PW, 2D+2D, 2D+2D\n(Biplane Imaging), 2D+(2D+C),\n2D+(2D+P), 2D+THI, 2D+SE,\n2D+CI","B, M, PW, CFM, P, THI, CI, SE, CW\nCombination modes:\n2D+M, 2D+PW, 2D+C+PW,\n2D+P+PW, 2D+2D, 2D+2D\n(Biplane Imaging), 2D+(2D+C),\n2D+(2D+P), 2D+THI, 2D+SE,\n2D+CI","Same"],["Intended Use","Intended Use:\nThe system is a diagnostic ultrasound\nimaging system used by qualified\nand trained healthcare professionals\nfor ultrasound imaging, human body\nfluid flow analysis and puncture and\nbiopsy guidance.\nIndications for Use:\nThe clinical applications and exam\ntypes include:\n• Fetal (including obstetrics)\n• Abdominal\n• Pediatric\n• Intra-operative","Intended Use:\nThe system is a diagnostic ultrasound\nimaging system used by qualified\nand trained healthcare professionals\nfor ultrasound imaging, human body\nfluid flow analysis and puncture and\nbiopsy guidance.\nIndications for Use:\nThe clinical applications and exam\ntypes include:\n• Fetal (including obstetrics)\n• Abdominal\n• Pediatric\n• Intra-operative","Summary of changes / comparison with"],["","","","predicate device\n- Due to the new software upgrade v.\ncurrently cleared clinical applications\nCardiac Adult,\nFetal (including obstetrics),\nTrans-rectal,\nTrans-vaginal,\nSmall Organ and\nPeripheral vessel\nwith transducers (9077, 9048, 9038,\n9052, 9018, 9019, 9029, 9027 and\n9032) previously activated on bk5000"]],"caption_candidate":"Table 3: Substantial Equivalence Table of the proposed device with its predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p13-t0","doc_id":"K223830","page_num":13,"bbox":[73.2,57.45,739.26,579.64],"n_rows":8,"n_cols":4,"columns":["","Ultrasound System 2300","Ultrasound System 2300",""],"rows":[["","Ultrasound System 2300","Ultrasound System 2300",""],["","","",""],["Characteristic","","","Comment on"],["","Proposed device","Predicate",""],["","","","Comparison"],["","(K223830)","device",""],["","","",""],["","• Intra-operative Neuro (also\nknown as Neurosurgery)\n• Laparoscopic\n• Small Organ (also known as\nSmall Parts)\n• Adult Cephalic (Cephalic is\nalso known as Adult Trans-\ncranial)\n• Neonatal Cephalic\n• Trans-rectal\n• Trans-vaginal\n• Musculo-skeletal (Conventional\nand Superficial)\n• Cardiac Adult\n• Trans-esophageal (Cardiac)\n• Peripheral vessel (also known\nas Peripheral Vascular)\nModes of operation:\n• 2 D (B-Mode) including\nTissue Harmonic Imaging\n• M-Mode\n• PWD Mode\n• CFM Mode (C, VFI)\n• Power Doppler\n• Contrast Imaging\n• CW Doppler\nStrain Elastography\nEnvironment:\nThe Ultrasound System 2300 is\nintended for use in the\nprofessional healthcare\nenvironment (e.g., hospitals,\nphysician offices).","• Intra-operat(iKve2 2N2e4u4r1o) ( also\nknown as Neurosurgery)\n• Laparoscopic\n• Small Organ (also known as\nSmall Parts)\n• Adult Cephalic (Cephalic is\nalso known as Adult Trans-\ncranial)\n• Neonatal Cephalic\n• Trans-rectal\n• Trans-vaginal\n• Musculo-skeletal (Conventional\nand Superficial)\n• Cardiac Adult\n• Trans-esophageal (Cardiac)\n• Peripheral vessel (also known\nas Peripheral Vascular)\nModes of operation:\n• 2 D (B-Mode) including\nTissue Harmonic Imaging\n• M-Mode\n• PWD Mode\n• CFM Mode (C, VFI)\n• Power Doppler\n• Contrast Imaging\n• CW Doppler\n• Strain Elastography\nEnvironment:\nThe Ultrasound System 2300 is\nintended for use in the\nprofessional healthcare\nenvironment (e.g., hospitals,\nphysician offices).","/ bk3000 configurations will now also\nbe enabled on bkActiv configuration."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p14-t0","doc_id":"K223830","page_num":14,"bbox":[73.16,57.45,739.28,478.12],"n_rows":9,"n_cols":4,"columns":["","Ultrasound System 2300","Ultrasound System 2300",""],"rows":[["","Ultrasound System 2300","Ultrasound System 2300",""],["","","",""],["Characteristic","","","Comment on"],["","Proposed device","Predicate",""],["","","","Comparison"],["","(K223830)","device",""],["","","",""],["","Contraindications\nThe Ultrasound System 2300 is not\nintended for ophthalmic use or any use\ncausing the acoustic beam to pass\nthrough the eye.\nThe Cardiac Adult application is not\nintended for direct use on the heart.","Contraindica(tKio2n2s2 441)\nThe Ultrasound System 2300 is not\nintended for ophthalmic use or any use\ncausing the acoustic beam to pass\nthrough the eye.\nThe Cardiac Adult application is not\nintended for direct use on the heart.",""],["Indications/Clinical\nApplications","• Abdominal\n• Intraoperative\n• Intraoperative –\nNeuro\n(Neurosurgery)\n• Pediatric\n• Musculo-skeletal\nSuperficial &\nConventional\n• Neonatal Cephalic\n• Adult Cephalic (Trans-cranial)\n• Laparoscopic\n• Small Organ (Small Parts)\n• Cardiac adult\n• Transesophageal (Cardiac)\n• Transrectal\n• Transvaginal\n• Fetal /Obstetrics\n• Peripheral Vessel (Vascular)","• Abdominal\n• Intraoperative\n• Intraoperative –\nNeuro\n(Neurosurgery)\n• Pediatric\n• Musculo-skeletal\nSuperficial &\nConventional\n• Neonatal Cephalic\n• Adult Cephalic (Trans-cranial)\n• Laparoscopic\n• Small Organ (Small Parts)\n• Cardiac adult\n• Transesophageal (Cardiac)\n• Transrectal\n• Transvaginal\n• Fetal /Obstetrics\n• Peripheral Vessel (Vascular)","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p15-t0","doc_id":"K223830","page_num":15,"bbox":[71.16,71.62,739.31,575.2],"n_rows":12,"n_cols":6,"columns":["","Ultrasound System 2300","","Ultrasound System 2300","",""],"rows":[["","Ultrasound System 2300","","Ultrasound System 2300","",""],["","","","","",""],["Characteristic","","","","","Comment on"],["","Proposed device","","Predicate device","",""],["","","","","","Comparison"],["","(K223830)","","(K222441)","",""],["","","","","",""],["Application Environment","Professional healthcare facility\nenvironment","Professional healthcare facility\nenvironment","","","Same"],["Users","Qualified Professional users","Qualified Professional users","","","Same"],["Patient Population","Adult, Pediatric","Adult, Pediatric","","","Same"],["Transducer types","Surface Contact\nIntra-operative\nLaparoscopic\nEndocavity","Surface Contact\nIntra-operative\nLaparoscopic\nEndocavity","","","Same"],["System Transducers","9002, 9007, 9009, 9011, 9015, 9016,\n9018, 9019, 9022, 9023, 9024, 9026,\n9027, 9029, 9032, 9034, 9038, 9040,\n9048, 9051, 9052, 9062, 9063, 9066,\n9070, 9076, 9077, 9081, 9085, 9096,\n9078","9002, 9007, 9009, 9011, 9015, 9016,\n9018, 9019, 9022, 9023, 9024, 9026,\n9027, 9029, 9032, 9034, 9038, 9040,\n9048, 9051, 9052, 9062, 9063, 9066,\n9070, 9076, 9077, 9081, 9085, 9096,\n9078","","","Transducers 9077, 9048, 9038, 9052,\n9018, 9019, 9029, 9027 and 9032\ncurrently available with\nbk5000/bk3000 configurations will be\nenabled on bkActiv configurations to\nsupport clinical applications Cardiac\nAdult, Fetal (including obstetrics),\nTrans-rectal, Trans-vaginal, Small\nOrgan (also known as Small Parts),\nPeripheral vessel (also known as\nPeripheral Vascular)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p16-t0","doc_id":"K223830","page_num":16,"bbox":[71.1,57.3,739.36,498.4],"n_rows":4,"n_cols":4,"columns":["Biocompatibility","The Ultrasound System does not come\nin contact with the patient.","The Ultrasound System does not come\nin contact with the patient.","Same"],"rows":[["Biocompatibility","The Ultrasound System does not come\nin contact with the patient.","The Ultrasound System does not come\nin contact with the patient.","Same"],["Hardware","Clinical display monitor (CDM):\n• 19” Optical bonded glass front.\n• Can be tilted and moved sideways.\nCart:\n• adjustable height and with 4\nlockable wheels\nKeyboard:\nTraditional keyboard with multiple\nfunctionalities / specialized controls\nor Glass touch UI\nScan engine:\n• 4 Transducer ports\n• 196 TX/RX channels\n• Tracking Interface board","Clinical display monitor (CDM):\n• 19” Optical bonded glass front.\n• Can be tilted and moved sideways.\nCart:\n• adjustable height and with 4\nlockable wheels\nKeyboard:\nTraditional keyboard with multiple\nfunctionalities / specialized controls\nor Glass touch UI\nScan engine:\n• 4 Transducer ports\n• 196 TX/RX channels\n• Tracking Interface board","Same\nNo changes to hardware since last\nclearance K222441."],["OS Software","Windows 10","Windows 10","Same"],["Associated Needle\ntracking accessories","UA1540 Tracking Control\nUnit\nUA1541 Portable EM Field\nGenerator (includes\nfield\ngenerator and a\nmounting solution)\nUA1542 Clip-on needle\nsensor\n(CIVCO)\nUA1543 Needle senor clamp\nKit (CIVCO)","UA1540 Tracking Control\nUnit\nUA1541 Portable EM Field\nGenerator (includes\nfield\ngenerator and a\nmounting solution)\nUA1542 Clip-on needle\nsensor\n(CIVCO)\nUA1543 Needle senor clamp\nKit (CIVCO)","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p18-t0","doc_id":"K223830","page_num":18,"bbox":[71.21,71.62,686.38,298.31],"n_rows":9,"n_cols":6,"columns":["","Ultrasound System 2300","","Ultrasound System 2300","",""],"rows":[["","Ultrasound System 2300","","Ultrasound System 2300","",""],["","","","","",""],["Characteristic","","","","","Comment on"],["","Proposed device","","Predicate device","",""],["","","","","","Comparison"],["","(TBD)","","(K222441)","",""],["","","","","",""],["Image features","Speckle reduction, compound\nimaging, tissue harmonic imaging\n(thi), contrast imaging (ci), trapezoid\nscanning (virtual convex) strain,\nelastography (se)","Speckle reduction, compound\nimaging, tissue harmonic imaging\n(thi), contrast imaging (ci), trapezoid\nscanning (virtual convex) strain,\nelastography (se)","","","Same"],["UI Design","-19-inch Clinical Monitor and touch\ninput device\nfor user interaction.\n-Trackball for cursor control.\n-Touchpad track pad for cursor control\n(Glass Touch UI)\n-Full configurable interaction controls\n(size/position)","-19-inch Clinical Monitor and touch\ninput device\nfor user interaction.\n-Trackball for cursor control.\n-Touchpad track pad for cursor control\n(Glass Touch UI)\n-Full configurable interaction controls\n(size/position)","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223830-p20-t0","doc_id":"K223830","page_num":20,"bbox":[120.33,189.5,520.92,422.49],"n_rows":4,"n_cols":5,"columns":["Patient Type","Training\nImages","Deep\nLearning\nValidation\nimages","Test\nimages\n(Clinical\nvalidation)","Comment"],"rows":[["Patient Type","Training\nImages","Deep\nLearning\nValidation\nimages","Test\nimages\n(Clinical\nvalidation)","Comment"],["Healthy","505","190","975",""],["Diseased","13447","1189","1461","Part of the test images\ncome from the Holland\ndataset, which only\ncontributed to the test set."],["Synthesized data","4104","48","0",""]],"caption_candidate":"• The table summarizes number of datasets used for each different purpose.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p4-t0","doc_id":"K223855","page_num":4,"bbox":[72.26,551.95,504.46,666.1],"n_rows":6,"n_cols":2,"columns":["Trade or proprietary or model name","3mensio Workstation/3mensio\nStructural Heart/3mensio Vascular"],"rows":[["Trade or proprietary or model name","3mensio Workstation/3mensio\nStructural Heart/3mensio Vascular"],["510(k) number:","K153736"],["Decision date","May 27, 2016"],["Classification product code","LLZ"],["Regulation Number","21 CFR 892.2050"],["Manufacturer","Pie Medial Imaging BV"]],"caption_candidate":"The predicate device to which substantial equivalence is claimed:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p6-t0","doc_id":"K223855","page_num":6,"bbox":[72.26,241.93,504.09,710.67],"n_rows":9,"n_cols":10,"columns":["","","Subject device","","","Predicate device","","","Comparison",""],"rows":[["","","Subject device","","","Predicate device","","","Comparison",""],["Device Name","FEops HEARTguideTM\nALPACATM","","","3mensio\nWorkstation/3mensio\nStructural\nHeart/3mensio Vascular","","","/","",""],["510(k) Number","/","","","K153736","","","/","",""],["Manufacturer","FEops NV","","","Pie Medical Imaging\nBV","","","/","",""],["Regulation Number","21 CFR 892.2050","","","21 CFR 892.2050","","","same","",""],["Device Classification\nName","Picture archiving and\ncommunications system","","","Picture archiving and\ncommunications system","","","same","",""],["Common Name","","","","3mensio Workstation","","","/","",""],["Product Code","QIH","","","LLZ","","","Similar, the subject\ndevice implements\nartificial intelligence\nincluding nonadaptive\nmachine learning\nalgorithms","",""],["Intended use","FEops HEARTguide™\nALPACA enables\nvisualization and\nmeasurement of\nstructures of the heart\nand vessels for\npreprocedural planning\nand sizing of structural\nheart interventions.","","","3mensio Workstation is\na software solution that\nis intended to provide\nCardiologists,\nRadiologists and\nClinical Specialists\nadditional information\nto aid them in reading\nand interpreting\nDICOM compliant\nmedical images of","","","Same,\nboth the subject and\npredicate device share\nthe same intended use,\nin that they enable\nvisualization of medical\nimages of the heart, and\nanalysis of structures of\nthe heart and vessels.","",""]],"caption_candidate":"dimensions in coronary arteries.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p8-t0","doc_id":"K223855","page_num":8,"bbox":[72.26,102.62,504.1,710.39],"n_rows":2,"n_cols":4,"columns":["","FEops HEARTguide™\nALPACA is not\nintended to replace the\nimplant device\ninstructions for use for\nfinal LAAO and TAVI\ndevice selection and\nplacement.","",""],"rows":[["","FEops HEARTguide™\nALPACA is not\nintended to replace the\nimplant device\ninstructions for use for\nfinal LAAO and TAVI\ndevice selection and\nplacement.","",""],["Indications for Use","FEops HEARTguide™\nALPACA enables\nvisualization and\nmeasurement of\nstructures of the heart\nand vessels for\npreprocedural planning\nand sizing of structural\nheart interventions.\nTo facilitate the above,\nFEops HEARTguide™\nALPACA provides\ngeneral functionality\nsuch as:\n• Segmentation of\ncardiovascular\nstructures\n• Visualization and\nimage reconstruction\ntechniques: 2D review,\nMPR\n• Measurement and\nannotation tools\n• Reporting tools\nFEops HEARTguide™\nALPACA also allows\nvisualization of output\ngenerated by other\nmedical device software","3mensio Workstation\nenables visualization\nand measurement of\nstructure of the heart\nand vessels for:\n- Preoperational\nplanning and\nsizing for\ncardiovascular\ninterventions\nand surgery\n- Postoperative\nevaluation\n- Support of\nclinical\ndiagnosis by\nquantifying\ndimensions in\ncoronary\narteries\n- Support of\nclinical\ndiagnosis by\nquantifying\ncalcifications\n(calcium\nscoring) in the\ncoronary\narteries\nTo facilitate the above,\nthe 3mensio\nWorkstation provides\ngeneral functionality\nsuch as:","Similar,\nBoth devices are\nindicated to be used for\npreprocedural planning\nand sizing of structural\nheart interventions.\nWhereas the subject\ndevice solely focuses on\npreprocedural planning,\nthe predicate device\nadditionally includes\nfunctionality for\npostoperative\nevaluation of structural\nheart interventions. This\ndoes not impact the\nindication for use for\npreprocedural planning.\nThe predicate device\nalso supports clinical\ndiagnosis by\nquantifying\ncalcifications and\nquantifying dimensions\nin coronary arteries.\nThis functionality is not\npresent in the subject\ndevice."]],"caption_candidate":"ALPACA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p10-t0","doc_id":"K223855","page_num":10,"bbox":[72.26,102.62,504.1,694.9],"n_rows":5,"n_cols":4,"columns":["","images (using 3D\nsurfaces).","images (volume\nrendering).",""],"rows":[["","images (using 3D\nsurfaces).","images (volume\nrendering).",""],["Landmark identification\nand measurements","Both manual and AI\nsupported functions for\nlandmark identification.","Both manual and AI\nsupported functions for\nlandmark identification.","Same"],["Scope - Structural heart\ninterventions","Transcatheter heart\ninterventions","Transcatheter heart\ninterventions","Same, both devices are\nlimited to transcatheter\ninterventions."],["Functionality for post-\nintervention evaluation","No","Yes","The predicate device\nincludes functionality\nfor post-intervention\nevaluation. This\nfunctionality is absent in\nthe subject device."],["Verification and\nValidation","Software verification\nand validation was\nperformed.\nDocumentation is\nprovided as\nrecommended by\nFDA’s Guidance for\nIndustry and FDA Staff\n“Guidance for the\nContent of Premarket\nSubmissions for\nSoftware Contained in\nMedical Devices”.\nDesign verification\nconfirmed that the\nsystem requirements\nwere implemented\ncorrectly.\nDesign validation\nestablished that the\nFEops HEARTguide\nALPACA conforms to\nthe intended use and\ndefined user needs,\ndemonstrating the safety","Verification showed\nthat the system\nrequirements – derived\nfrom the intended use\nand indications for use –\nwere implemented\ncorrectly, demonstrating\nthe effectiveness of the\ndevice.\nA validation plan for the\nfinal validation of the\nrelease build was\nexecuted on the final\nbuild.\nA test report comparing\nthe numerical results of\nthe device compared\nwith the predicate\ndevices was generated.","Same"]],"caption_candidate":"ALPACA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p11-t0","doc_id":"K223855","page_num":11,"bbox":[72.26,102.62,504.1,332.45],"n_rows":3,"n_cols":4,"columns":["","and effectiveness of the\nsubject device.","",""],"rows":[["","and effectiveness of the\nsubject device.","",""],["Cloud-based","Yes","No, 3mensio is a\ntraditional software\npackage, to be installed\non a specific computer","Different, while the\nsubject device is cloud-\nbased, the predicate\ndevice is a traditional\nsoftware package to be\ninstalled on a specific\ncomputer. FEops\nHEARTguideTM\nALPACA is subject to\ncybersecurity measures\n(see Section 16)."],["Reporting tools","FEops HEARTguide\ngenerates pdf reports","3mensio generates pdf\nreports","Same"]],"caption_candidate":"ALPACA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p12-t0","doc_id":"K223855","page_num":12,"bbox":[72.26,570.43,539.86,695.74],"n_rows":5,"n_cols":3,"columns":["","Semi-automatic output","Fully automatic output"],"rows":[["","Semi-automatic output","Fully automatic output"],["Mean of differences (%)","1.4 ± 4.6","4.1 ± 7.2"],["Confidence interval (CI) on the mean (%)","(-0.2, 2.9)","(1.6, 6.6)"],["Inferior Limit of Agreement (LoA) (%)","-7.7","-10.1"],["Superior LoA (%)","10.4","18.3"]],"caption_candidate":"following results for the semi-automatic and fully automatic outputs respectively:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p13-t0","doc_id":"K223855","page_num":13,"bbox":[72.26,102.62,539.86,152.66],"n_rows":2,"n_cols":3,"columns":["CI on inferior LoA (%)","(-10.5, -5.0)","(-14.4, -5.8)"],"rows":[["CI on inferior LoA (%)","(-10.5, -5.0)","(-14.4, -5.8)"],["CI on superior LoA (%)","(7.7, 13.2)","(14.0, 22.6)"]],"caption_candidate":"ALPACA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p13-t1","doc_id":"K223855","page_num":13,"bbox":[72.26,325.97,539.86,451.27],"n_rows":5,"n_cols":3,"columns":["","Semi-automatic output","Fully automatic output"],"rows":[["","Semi-automatic output","Fully automatic output"],["Mean dice score","0.98 ± 0.01","0.93 ± 0.04"],["Minimum Dice score","0.95","0.83"],["Maximum Dice score","0.99","0.97"],["Median Dice score","0.98","0.94"]],"caption_candidate":"ostium and the main part of the left atrial appendage.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p14-t0","doc_id":"K223855","page_num":14,"bbox":[72.26,144.38,405.19,319.73],"n_rows":7,"n_cols":2,"columns":["","Semi-automatic output"],"rows":[["","Semi-automatic output"],["Mean of differences (%)","0.5 ± 1.9"],["Confidence interval (CI) on the mean (%)","(-0.1, 1.2)"],["Inferior Limit of Agreement (LoA) (%)","-3.2"],["Superior LoA (%)","4.2"],["CI on inferior LoA (%)","(-4.3, -2.1)"],["CI on superior LoA (%)","(3.1, 5.3)"]],"caption_candidate":"provided the following results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K223855-p14-t1","doc_id":"K223855","page_num":14,"bbox":[72.26,493.03,539.86,618.34],"n_rows":5,"n_cols":3,"columns":["","Semi-automatic output","Fully automatic output"],"rows":[["","Semi-automatic output","Fully automatic output"],["Mean dice score","0.97 ± 0.01","0.96 ± 0.01"],["Minimum Dice score","0.92","0.92"],["Maximum Dice score","0.99","0.98"],["Median Dice score","0.97","0.96"]],"caption_candidate":"ascending aorta and the left ventricle.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p5-t0","doc_id":"K230020","page_num":5,"bbox":[72.0,284.52,540.0,336.48],"n_rows":4,"n_cols":2,"columns":["",". In addition, the SW architecture was changed"],"rows":[["",". In addition, the SW architecture was changed"],["to separate the image communication platform from the BriefCase SW. The new device consists of",""],["only the algorithm analysis module which can be integrated with image communication platforms that",""],["meet the BriefCase input and output requirements.",""]],"caption_candidate":"algorithm performance, due to training the subject device on a larger data set. Additional operating","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p6-t0","doc_id":"K230020","page_num":6,"bbox":[72.0,96.36,543.0,685.08],"n_rows":3,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for RibFx triage\n(K202992)","Subject Device\nAidoc Briefcase for RibFx triage"],"rows":[["","Predicate Device\nAidoc Briefcase for RibFx triage\n(K202992)","Subject Device\nAidoc Briefcase for RibFx triage"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of chest\nCTs (with or without contrast). The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage\nby flagging and communication of\nsuspect cases of three or more acute\nRib fracture (RibFx) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag\nsuspect cases on a standalone desktop\napplication in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with notifications\nfor suspect cases. Notifications include\ncompressed preview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image and\nis not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of chest\nCTs (with or without contrast) images in\nadults or transitional adolescents aged\n18 and older. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage by\nflagging and communicating suspect\ncases of three or more acute Rib\nfracture (RibFx) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected RibFx findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p7-t0","doc_id":"K230020","page_num":7,"bbox":[72.0,72.24,543.0,709.56],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase for RibFx triage\n(K202992)","Subject Device\nAidoc Briefcase for RibFx triage"],"rows":[["","Predicate Device\nAidoc Briefcase for RibFx triage\n(K202992)","Subject Device\nAidoc Briefcase for RibFx triage"],["Anatomical\nregion of\ninterest","Chest","Chest"],["Data\nacquisition\nprotocol","Chest CTs (with or without contrast)","Chest CTs (with or without contrast)"],["Notification-\nonly\n(/notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion criteria\n- Chest CTs (with or without contrast).\n- Single energy exams.\n- Scans performed with a 64 or\ngreater number of detectors.\n- Scans performed on\n(cid:68)(cid:71)(cid:88)(cid:79)(cid:87)(cid:86)(cid:18)(cid:87)(cid:85)(cid:68)(cid:81)(cid:86)(cid:76)(cid:87)(cid:76)(cid:82)(cid:81)(cid:68)(cid:79)(cid:3)(cid:68)(cid:71)(cid:88)(cid:79)(cid:87)(cid:86)(cid:3)(cid:149)(cid:3)(cid:20)(cid:27)(cid:3)(cid:92)(cid:72)(cid:68)(cid:85)(cid:86)(cid:3)\nof age.\n- Slice thickness; 0.5 - 5.0 mm axial.\nExclusion Criteria\n- All studies that are technically\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, or inadequate field of view.","Inclusion criteria\n- chest CT with or without contrast\n- Single energy exams.\n- Performed on CT scanners with 64\nor greater number of detectors\n- Scans performed on\n(cid:68)(cid:71)(cid:88)(cid:79)(cid:87)(cid:86)(cid:18)(cid:87)(cid:85)(cid:68)(cid:81)(cid:86)(cid:76)(cid:87)(cid:76)(cid:82)(cid:81)(cid:68)(cid:79)(cid:3)(cid:68)(cid:71)(cid:88)(cid:79)(cid:87)(cid:86)(cid:3)(cid:149)(cid:3)(cid:20)(cid:27)(cid:3)(cid:92)(cid:72)(cid:68)rs\nof age\n- Slice thickness; 0.5 mm to 5.0 mm\naxial slices\nExclusion Criteria\n- All studies that are technically\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, or inadequate field of view."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- AHS module (image acquisition);\n- ACS module (image processing));\n- Aidoc Worklist application for\nworkflow integration (worklist and\nnon-diagnostic Image Viewer).","- Integrated with image routing module\nvia image communication platform\n(ICP) (image acquisition).\n- Algorithm module (image\nprocessing)\n- Integrated with desktop application\nfor workflow integration (feed and\nnon-diagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p9-t0","doc_id":"K230020","page_num":9,"bbox":[72.78,99.23,516.0,281.58],"n_rows":14,"n_cols":7,"columns":["Time -to-notification","Mean","N","95% Lower","95% Upper","Median","IQR"],"rows":[["Time -to-notification","Mean","N","95% Lower","95% Upper","Median","IQR"],["","Estimate","","CL","CL","",""],["","","","","","",""],["","","","","","",""],["","(seconds)","","","","",""],["Predicate K202992","252","67","234","270","252","108"],["","","","","","",""],["Processing Time","","","","","",""],["BriefCase + Image","70.1","104","64.9","75.4","66","59"],["","","","","","",""],["Communication","","","","","",""],["Platform Time-To-","","","","","",""],["","","","","","",""],["Notification","","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p9-t1","doc_id":"K230020","page_num":9,"bbox":[130.61,489.2,481.49,536.0],"n_rows":3,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age","","65.1","","","15.5","","","20","","","66","","","90","","","308","",""],["","(Years)","","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p10-t0","doc_id":"K230020","page_num":10,"bbox":[164.32,99.27,447.18,236.56],"n_rows":6,"n_cols":18,"columns":["Ground Truth Results","","","","Gender","","","","","","","","","All","","","",""],"rows":[["Ground Truth Results","","","","Gender","","","","","","","","","All","","","",""],["","","","","Female","","","","","Male","","","","","All","","",""],["","","","","N","","","%","","N","","%","","","N","","","%"],["","Positive","","","36","","","12.1%","","61","","20.5%","","","97","","","32.6%"],["","Negative","","","104","","","34.9%","","97","","32.6%","","","201","","","67.4%"],["","All","","","140","","","47.0%","","158","","53.0%","","","298","","","100.0%"]],"caption_candidate":"Table 4. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230020-p10-t1","doc_id":"K230020","page_num":10,"bbox":[208.95,292.48,403.23,472.92],"n_rows":6,"n_cols":8,"columns":["","Manufacturer","","","N","","%",""],"rows":[["","Manufacturer","","","N","","%",""],["GE MEDICAL\nSYSTEMS","","","150","","48.7%","",""],["Philips","","","64","","20.8%","",""],["SIEMENS","","","53","","17.2%","",""],["TOSHIBA","","","41","","13.3%","",""],["","Total","","","308","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p4-t0","doc_id":"K230023","page_num":4,"bbox":[102.34,176.39,532.75,286.52],"n_rows":9,"n_cols":2,"columns":["SubmitterInformation:",""],"rows":[["SubmitterInformation:",""],["Name:","TheraPanacea SAS"],["Address:","7bisboulevardBourdon75004Paris"],["EstablishmentRegistrationNumber:","3019834893"],["Owner/OperatorNumber:","10082087"],["Phone:","+33962527819"],["Contact:","CatherineMartineau-Huynh"],["E-mail:","c.huynh@therapanacea.eu"],["DateofSummary:","28thofDecember2022"]],"caption_candidate":"withtherequirementof21CFR807.92","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p4-t1","doc_id":"K230023","page_num":4,"bbox":[102.34,344.64,532.75,393.51],"n_rows":4,"n_cols":2,"columns":["DeviceProprietaryName","NA"],"rows":[["DeviceProprietaryName","NA"],["CommonName:","ART-Plan"],["TradeName:","ART-Plan"],["ProductCode(s):","NA"]],"caption_candidate":"BelowsummarisestheDeviceClassificationinformationregardingtheART-Planv1.10.1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p4-t2","doc_id":"K230023","page_num":4,"bbox":[102.34,429.1,532.75,488.5],"n_rows":2,"n_cols":5,"columns":["Regulation\nNumber","Device","DeviceClass","Product\nCode","Classification\nPanel"],"rows":[["Regulation\nNumber","Device","DeviceClass","Product\nCode","Classification\nPanel"],["892.2050","Medicalimage\nmanagementand\nprocessingsystem","ClassII","QKB","Radiology"]],"caption_candidate":"PrimaryProductCode","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p4-t3","doc_id":"K230023","page_num":4,"bbox":[102.34,523.3,532.75,629.5],"n_rows":3,"n_cols":5,"columns":["Regulation\nNumber","Device","DeviceClass","Product\nCode","Classification\nPanel"],"rows":[["Regulation\nNumber","Device","DeviceClass","Product\nCode","Classification\nPanel"],["892.2050","Medicalimage\nmanagementand\nprocessingsystem","ClassII","LLZ","Radiology"],["892.5050","Medical\ncharged-particle\nradiationtherapy\nsystem","ClassII","MUJ","Radiology"]],"caption_candidate":"SecondaryProductCodes","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p5-t0","doc_id":"K230023","page_num":5,"bbox":[108.25,118.74,557.37,166.5],"n_rows":2,"n_cols":5,"columns":["Manufacturer","TradeName","Product\nCode","Regulation","510(k)Number"],"rows":[["Manufacturer","TradeName","Product\nCode","Regulation","510(k)Number"],["TheraPanacea\nSAS","ART-Plan","QKB","892.2050","K220813"]],"caption_candidate":"SubstantialEquivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p7-t0","doc_id":"K230023","page_num":7,"bbox":[57.69,279.72,576.33,698.76],"n_rows":7,"n_cols":4,"columns":["Characteristic","ART-Planv1.10.1withModification","ART-Planv1.10.0K220813\n(Predicate)","Equivalence"],"rows":[["Characteristic","ART-Planv1.10.1withModification","ART-Planv1.10.0K220813\n(Predicate)","Equivalence"],["DeviceName","ART-Planv1.10.1","ART-Planv1.10.0","Equivalent"],["Manufacturer","TheraPanaceaSAS","TheraPanaceaSAS","Equivalent"],["DeviceClassification","II","II","Equivalent"],["PrimaryProductCode","QKB","QKB","Equivalent"],["SecondaryProduct\nCode","LLZ,MUJ","LLZ,MUJ","Equivalent"],["IndicationsforUse","ART-Plan is indicated for cancer\npatients for whom radiation treatment\nhas been planned. It is intended to be\nused by trained medical professionals\nincluding, butnotlimitedto,radiologists,\nradiation oncologists, dosimetrists, and\nmedicalphysicists.\nART-Plan is a software application\nintended to display and visualize 3D\nmulti-modal medical image data. The\nuser may import, define, display,\ntransform and store DICOM 3.0\ncompliant datasets (including regionsof\ninterest structures). These images,\ncontours and objects can subsequently\nbe exported/distributed within the\nsystem, across computer networks\nand/or to radiation treatment planning\nsystems. Supported modalities include\nCT, PET-CT, CBCT, 4D-CT and MR\nimages.\nART-Plan supports AI-basedcontouring\non CT and MR images and offers\nsemi-automatic and manual tools for\nsegmentation.\nTo help the user assess changes in\nimage data and to obtain combined\nmulti-modal image information,\nART-Plan allows the registration of","ART-Plan is indicated for cancer\npatients for whom radiation treatment\nhas been planned. It is intended to be\nused by trained medical professionals\nincluding, butnotlimitedto,radiologists,\nradiation oncologists, dosimetrists, and\nmedicalphysicists.\nART-Plan is a software application\nintended to display and visualize 3D\nmulti-modal medical image data. The\nuser may import, define, display,\ntransform and store DICOM 3.0\ncompliant datasets (including regionsof\ninterest structures). These images,\ncontours and objects can subsequently\nbe exported/distributed within the\nsystem, across computer networks\nand/or to radiation treatment planning\nsystems. Supported modalities include\nCT, PET-CT, CBCT, 4D-CT and MR\nimages.\nART-Plan supports AI-basedcontouring\non CT and MR images and offers\nsemi-automatic and manual tools for\nsegmentation.\nTo help the user assess changes in\nimage data and to obtain combined\nmulti-modal image information,\nART-Plan allows the registration of","Equivalent"]],"caption_candidate":"characteristicsissummarisedinTable1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p8-t0","doc_id":"K230023","page_num":8,"bbox":[57.68,95.74,576.33,617.27],"n_rows":5,"n_cols":4,"columns":["Characteristic","ART-Planv1.10.1withModification","ART-Planv1.10.0K220813\n(Predicate)","Equivalence"],"rows":[["Characteristic","ART-Planv1.10.1withModification","ART-Planv1.10.0K220813\n(Predicate)","Equivalence"],["","anatomical and functional images and\ndisplay of fused and non-fused images\nto facilitate the comparison of patient\nimagedatabytheuser.\nWith ART-Plan, users are also able to\ngenerate, visualize, evaluate and\nmodifypseudo-CTfromMRIimages","anatomical and functional images and\ndisplay of fused and non-fused images\nto facilitate the comparison of patient\nimagedatabytheuser.\nWith ART-Plan, users are also able to\ngenerate, visualize, evaluate and\nmodifypseudo-CTfromMRIimages",""],["Intended\nuser/Location","It is intended to be used by trained\nmedical professionals including, but not\nlimited to, radiologists, radiation\noncologists, dosimetrists, and medical\nphysicists/Hospitals","It is intended to be used by trained\nmedical professionals including, but not\nlimited to, radiologists, radiation\noncologists, dosimetrists, and medical\nphysicists/Hospitals","Equivalent"],["Segmentationfeatures\n(Annotatemodule)","AutomaticallydelineatesOARsand\nhealthylymphnodes\nDeeplearningalgorithm.\nAutomaticsegmentationincludesthe\nfollowinglocalizations:\n*headandneck(onCTimages)\n*thorax/breast(formale/femaleandon\nCTimages)\n*abdomen(onCTimagesandMR\nimages)\n*pelvismale(onCTimagesandMR\nimages)\n*pelvisfemale(onCTimages)\n*brain(onCTimagesandMRimages)","AutomaticallydelineatesOARsand\nhealthylymphnodes\nDeeplearningalgorithm.\nAutomaticsegmentationincludesthe\nfollowinglocalizations:\n*headandneck(onCTimages)\n*thorax/breast(formale/femaleandon\nCTimages)\n*abdomen(onCTimagesandMR\nimages)\n*pelvismale(onCTimagesandMR\nimages)\n*pelvisfemale(onCTimages)\n*brain(onCTimagesandMRimages)","Equivalent-\nThecandidate\ndeviceand\npredicateare\ncapableof\nautomatically\ncontouringthe\norgan-at-risk\n(OAR)and\nhealthylymph\nnodesusing\nAI(deep\nlearning)\nalgorithm.\nThecandidate\ndevice\nincludes48\nadditional\nstructures to\nthealready\nexisting\nlocalizations"],["Bugs","Correctionof8bugs","NA","Equivalent\nThebugfixes\nintroducedin\nthecandidate\ndevicedonot\naffectthe\nsafetyor\nperformance\nofthe\npredicate\ndevice"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p9-t0","doc_id":"K230023","page_num":9,"bbox":[108.1,122.63,552.72,702.5],"n_rows":21,"n_cols":7,"columns":["Head&Neck(CT)-47structures","","","","","",""],"rows":[["Head&Neck(CT)-47structures","","","","","",""],["Brainstem","Cerebellum","Chiasma","Encephalon","Esophagus","Hypophyse","Larynx"],["LeftBrachial\nplexus","Leftcervicallymph\nnodeIB","Leftcervical\nlymphnode\nII","Leftcervical\nlymphnodeIII","Leftcervical\nlymphnode\nIVA","Leftcervical\nlymphnode\nIVB","Leftcervical\nlymphnodeV"],["Leftcervicallymph\nnodeVIIA","Leftcervicallymph\nnodeVIIB","Leftcochlea","Lefteye","Lefteyelens","Leftoptical\nnerve","Leftparotid"],["Leftsubmandible","Left\ntemporomandibula\nrjoints","Lips","Mandible","Medullar\ncanal","Mouth","Rightbrachial\nplexus"],["Rightcervical\nlymphnodeIB","Rightcervical\nlymphnodeII","Right\ncervical\nlymphnode\nIII","Rightcervical\nlymphnode\nIVA","Rightcervical\nlymphnode\nIVB","Rightcervical\nlymphnodeV","Rightcervical\nlymphnode\nVIIA"],["Rightcervical\nlymphnodeVIIB","Rightcochlea","Righteye","Righteyelens","Rightoptical\nnerve","Rightparotid","Right\nsubmandible"],["Right\ntemporomandibula\nrjoints","SpinalCord","Thyroid","Trachea","External\ncontour","",""],["Thorax/Breast(CT)-30structures","","","","","",""],["Esophagus","Heart","Larynx","Leftbrachial\nplexus","Leftbreast","Lefthumeral\nhead","LeftIMC\n(internal\nmammary\nchain)lymph\nnode"],["Leftinterpectoral\nlymphnode","Leftlung","Leftlymph\nnodeL1","Leftlymph\nnodeL2","Leftlymph\nnodeL3","Left\nsupraclavicula\nrlymphnodes","Liver"],["Medullarcanal","Rightbrachial\nplexus","Rightbreast","Righthumeral\nhead","RightIMC\n(internal\nmammary\nchain)lymph\nnode","Right\ninterpectoral\nlymphnode","Rightlung"],["Rightlymphnode\nL1","Rightlymphnode\nL2","Rightlymph\nnodeL3","Right\nsupraclavicula\nrlymphnodes","Spinalcord","Thoracicaorta","Thyroid"],["Trachea","ExternalContour","","","","",""],["PelvisMale(CT)-19structures","","","","","",""],["Analcanal","Bladder","Bowelbag","CTVn\nprostate","Leftfemoral\nhead","Leftiliac","Leftkidney"],["Liver","Medullarcanal","Penilebulb","Prostate","Rectum","Right\nfemoralhead","Rightiliac"],["Rightkidney","Seminalvesicle","Sigmoid","Spinalcord","External\ncontour","",""],["PelvisFemale(CT)-25structures","","","","","",""],["Analcanal","Bladder","Bowelbag","Common\niliacgyneco\nlymphnode","CTVt\ngyneco","Leftfemoral\nhead","Leftiliac"],["Leftiliacgyneco\nlymphnode","Leftinguinal\ngynecolymph\nnode","Leftkidney","Liver","Lomboaorti\nclymph\nnode","Medullar\ncanal","Parametrium"]],"caption_candidate":"InTable2,structuresincludedinART-Planv1.10.1arepresented.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p10-t0","doc_id":"K230023","page_num":10,"bbox":[108.08,95.5,552.72,675.53],"n_rows":20,"n_cols":7,"columns":["Presacral\ngynecolymph\nnode","Rectum","Right\nfemoral\nhead","Rightiliac","Rightiliac\ngyneco\nlymphnode","Right\ninguinal\ngyneco\nlymphnode","Rightkidney"],"rows":[["Presacral\ngynecolymph\nnode","Rectum","Right\nfemoral\nhead","Rightiliac","Rightiliac\ngyneco\nlymphnode","Right\ninguinal\ngyneco\nlymphnode","Rightkidney"],["Sigmoid","Spinalcord","Vagina","External\ncontour","","",""],["Heartsubstructures(partofthorax/breast)(CT)- 13structures","","","","","",""],["Ascendingaorta","Coronarysinus","Leftatrium","Leftmain\ncoronary\nartery","Left\nventricle","Leftventricle\nanterior","Leftventricle\napical"],["Leftventricle\ninferior","Leftventricle\nlateral","Left\nventricle\nseptal","Rightatrium","Right\nventricle","Venacava\nsuperior",""],["SBRTlung(partofthorax/breast)(CT)- 14structures","","","","","",""],["Bronchialtree","Carina","Left\nanterior\ndescending\naorta","Leftbronchia","Left\nbronchus","Leftchest\nwall","Pericardium"],["Pulmonary\narteries","Rightbronchia","Right\nbronchus","Rightchest\nwall","Spleen","Stomach","Venacava\ninferior"],["BrainT1(MR)-28structures","","","","","",""],["Anterior\ncerebellum","Chiasma","Encephalo\nn","Hypophyse","Leftcochlea","Leftcornea","Lefteyelens"],["Left\nhippocampus","Left\nhypothalamus","Left\nlacrimal\ngland","Leftoptical\nnerve","Leftretina","Left\nvestibular\nsemicircular\ncanals\n(VSCC)","Medulla\noblongata"],["Midbrain","Pons","Posterior\ncerebellum","Right\ncochlea","Right\ncornea","Righteye\nlens","Right\nhippocampu\ns"],["Right\nhypothalamus","Rightlacrimal\ngland","Right\noptical\nnerve","Rightretina","Right\nversibular\nsemicircular\ncanals\n(VSCC)","Spinalcord","External\ncontour"],["PelvisT2(male)(MR)-12structures","","","","","",""],["Analcanal","Bladder","Left\nfemoral\nhead","Leftpelvis","Penilebulb","Prostate","Rectum"],["Rightfemoral\nhead","Rightpelvis","Sacrum","Seminal\nvesicle","External\ncontour","",""],["PelvisTF(male)(MR)-19structures","","","","","",""],["Analcanal","Aorta","Bladder","Duodenum","Inferior\nvenacava","Largebowel","Leftfemoral\nhead"],["Leftkidney","Liver","Pancreas","Penilebulb","Prostate","Rectum","Right\nfemoralhead"],["Rightkidney","Seminalvesicle","Sigmoid","Stomach","External\ncontour","",""]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p17-t0","doc_id":"K230023","page_num":17,"bbox":[77.5,145.5,534.5,701.5],"n_rows":8,"n_cols":4,"columns":["Organ","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],"rows":[["Organ","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],["1. Carina","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=6.58%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["2. Lad\ncoronary","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=15.56%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["3. Left\nbronchia","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=14.75%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["4. Left\nbronchus","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=6.17%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["5. Leftchest\nwall","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=0%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["6. Pericardium","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=1.06%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["7. pulmonary","Intervariabilitycomparisonto","DICEdiff","Samplesize:33"]],"caption_candidate":"SummaryofVerificationandValidationActivities","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p18-t0","doc_id":"K230023","page_num":18,"bbox":[77.5,107.5,534.5,683.5],"n_rows":7,"n_cols":4,"columns":["arteries","experts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","inter-expert=3.61%\nPassed","whichisabovethe\nminimumdatasample\nsize"],"rows":[["arteries","experts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","inter-expert=3.61%\nPassed","whichisabovethe\nminimumdatasample\nsize"],["8. Right\nbronchia","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=22.64%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["9. Right\nbronchus","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=7.41%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["10. Right\nchestwall","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=-1.10%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["11. Spleen","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=1.08%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["12. stomach","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=2.27%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"],["13. Venacava\ninf","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=9.59%\nPassed","Samplesize:33\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p19-t0","doc_id":"K230023","page_num":19,"bbox":[77.5,107.5,534.5,704.5],"n_rows":8,"n_cols":4,"columns":["14. Bronchial\ntree","Thisstructurecorrespondstoa\nbooleanofotherstructures:carina\n+leftbronchus+rightbronchus+\nleftbronchia+rightbronchiawhich\nwhichhaveallpassedthe\nperformancetests","",""],"rows":[["14. Bronchial\ntree","Thisstructurecorrespondstoa\nbooleanofotherstructures:carina\n+leftbronchus+rightbronchus+\nleftbronchia+rightbronchiawhich\nwhichhaveallpassedthe\nperformancetests","",""],["15. Ascending\naorta","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["16. coronary\nsinus","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","diffinter-expert=3.59%\nPassed","Samplesize:20\nwhichistheminimum\ndatasamplesize"],["17. Leftatrium","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["18. Leftmain\ncoronary\nartery","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=93%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["19. Left\nventricle","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["20. Left\nventricle\nanterior","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["21. Left\nventricle\napical","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p20-t0","doc_id":"K230023","page_num":20,"bbox":[77.5,107.5,534.5,694.5],"n_rows":8,"n_cols":4,"columns":["22. Left\nventricle\ninferior","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],"rows":[["22. Left\nventricle\ninferior","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["23. Left\nventricle\nlateral","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["24. Left\nventricle\nseptal","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["25. Rightatrium","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\npassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["26. Right\nventricle","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["27. Venacava\nsup","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["28. Leftcervical\nlymphnode\nIVB","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=96.67%\nPassed","Samplesize:15\nwhichisabovethe\nminimumdatasample\nsize"],["29. Right\ncervical\nlymphnode\nIVB","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=96.67%\nPassed","Samplesize:15\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p21-t0","doc_id":"K230023","page_num":21,"bbox":[77.5,107.5,534.5,693.5],"n_rows":7,"n_cols":4,"columns":["30. Anterior\ncerebellum","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=6.47%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],"rows":[["30. Anterior\ncerebellum","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=6.47%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["31. Leftcochlea","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=19.96%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["32. Leftcornea","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=7.93%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["33. Left\nhypothalam\nus","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=4.19%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["34. Leftlacrimal\ngland","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=4.76%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["35. Leftretina","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=12.26%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["36. Leftvscc","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=-1.20%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p22-t0","doc_id":"K230023","page_num":22,"bbox":[77.5,107.5,534.5,693.5],"n_rows":7,"n_cols":4,"columns":["37. Medulla\noblangata","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=3.25%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],"rows":[["37. Medulla\noblangata","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=3.25%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["38. Midbrain","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=5.78\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["39. Pons","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=3.39%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["40. Posterior\ncerebellum","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=2.07%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["41. Right\ncochlea","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=29.22%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["42. Right\ncornea","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=4.66%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["43. Right\nhypothalam\nus","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=3.32%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p23-t0","doc_id":"K230023","page_num":23,"bbox":[77.5,107.5,534.5,515.5],"n_rows":5,"n_cols":4,"columns":["44. Right\nlacrimal\ngland","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=4.23%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],"rows":[["44. Right\nlacrimal\ngland","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=4.23%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["45. Rightretina","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=10.03%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["46. Rightvscc","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=3.08%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["47. SpinalCord","Intervariabilitycomparisonto\nexperts\n(CriterionCofperformance\ncriteria)\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=13.01%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["48. Sigmoid","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p24-t0","doc_id":"K230023","page_num":24,"bbox":[108.25,463.7,597.25,707.5],"n_rows":3,"n_cols":3,"columns":["TestName","TestDescription","Results"],"rows":[["TestName","TestDescription","Results"],["Study Protocol and\nReport Annotate\nPerformances\nSummary(v1.10.1)","The purpose of this document is to describe the testing\nprotocols and testing results for validating the performance of\nthe Annotate module. TheperformancestudyoftheART-Plan\nmodule, Annotate, evaluates the precision of the contours\ndone by the software either i) againsttheonedonebyhuman\nexperts through a direct comparison or ii) by a qualitative\nvalidationdonebyhumanexperts.\nThe objective of the tests is to demonstrate that the\nauto-segmentation algorithms (CT and MR) of the module\nAnnotate pass at least one acceptance criterion. This\ndocument includes test procedures, documentation,\nreferences, specifications, and acceptance criteria. This\ndocument is updated to take into account modificationsmade\nin ART-Plan v1.10.1 with the addition of heart substructures\nandSBRTintheCTautomaticsegmentation.","Passed"],["Study Protocol and\nReport quantitative\nvalidation of Annotate","This test demonstrates that the Annotate provides clinically\nacceptable (compared to inter-expert variability) for SBRT\nstructures. All organs that have passed the acceptance","Passed"]],"caption_candidate":"validatetheorgansaddedinv1.10.1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230023-p25-t0","doc_id":"K230023","page_num":25,"bbox":[108.33,95.72,597.33,236.5],"n_rows":3,"n_cols":3,"columns":["TestName","TestDescription","Results"],"rows":[["TestName","TestDescription","Results"],["in ART-Plan v1.10.1\nforSBRTCT.","criterion of reaching a percentage of a DSC(mean)≥ 0.8 or\nDSC(mean)≥0.54) or DSC(mean)≥mean(DSC\ninter-expert)+5% relative error (quantitative evaluation) have\nbeenreleasedinv.1.10.1.",""],["Study Protocol and\nReport Qualitative\nValidation of Annotate\nin ART-Plan V1.10.1\nfor Heart\nsubstructuresCT","This test demonstrates that the module Annotate provides\nacceptablecontoursfortheorgansevaluatedonCTimagesof\npatients. All organs that have passedtheacceptancecriterion\nof reaching a percentage of atleast85%ofAorB(qualitative\nevaluation)havebeenreleasedinv.1.10.1.","Passed"]],"caption_candidate":"For ART-Plan v1.10.1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p8-t0","doc_id":"K230039","page_num":8,"bbox":[72.24,108.02,745.42,530.4],"n_rows":4,"n_cols":5,"columns":["","to plug in multi-vendor\napplications which meet\ninterface requirements.\nuOmnispace is intended to\nbe used by trained\nprofessionals, including but\nnot limited to physicians\nand medical technicians.\nThe system is not intended\nfor the displaying of digital\nmammography images for\ndiagnosis in the U.S.","syngo.via supports\ninterpretation and\nevaluation of\nexaminations within\nhealthcare institutions,\nFor example, in\nRadiology, Nuclear\nMedicine and Cardiology\nenvironments.\nThe system is not\nintended for the\ndisplaying of digital\nmammography images\nfor diagnosis in the U.S.","",""],"rows":[["","to plug in multi-vendor\napplications which meet\ninterface requirements.\nuOmnispace is intended to\nbe used by trained\nprofessionals, including but\nnot limited to physicians\nand medical technicians.\nThe system is not intended\nfor the displaying of digital\nmammography images for\ndiagnosis in the U.S.","syngo.via supports\ninterpretation and\nevaluation of\nexaminations within\nhealthcare institutions,\nFor example, in\nRadiology, Nuclear\nMedicine and Cardiology\nenvironments.\nThe system is not\nintended for the\ndisplaying of digital\nmammography images\nfor diagnosis in the U.S.","",""],["Client-Server\nArchitecture and Multi-\nUser Access","Yes\nBased on client-server\narchitecture and supports\nmulti-user access.","Yes\nBased on client-server\narchitecture and supports\nmulti-user access.","/","Same"],["Image communication\nand storage","Yes\nCommunicate and store\nmedical images based on\nstandard communication\nprotocol DICOM.","Yes\nCommunicate and store\nmedical images based on\nstandard communication\nprotocol DICOM.","/","Same"],["Hardware /OS","Yes\nClient:\nMicrosoft Windows 7 or\nMicrosoft","Yes\nClient:\nMicrosoft Windows 7 SP1\nor Microsoft","/","Functional Substantially Equivalent\nThe client and server operating systems of\nthe proposed device are Microsoft Windows\nand Linux respectively, while those of the"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p9-t0","doc_id":"K230039","page_num":9,"bbox":[72.24,108.02,745.42,506.98],"n_rows":4,"n_cols":5,"columns":["","Windows 10 or compatible\nversions\nServer:\nLinux Core CentOS7.7 or\ncompatible versions","Windows 8.1 or Microsoft\nWindows 10\nServer:\nMicrosoft Windows Server\n2008 R2 or\nMicrosoft Windows Server\n2012 R2.\nor Microsoft Server 2016","","predicate device are Microsoft Windows and\nMicrosoft Windows Server respectively.\nThis difference doesn’t impact the safety\nand effectiveness of the subject device."],"rows":[["","Windows 10 or compatible\nversions\nServer:\nLinux Core CentOS7.7 or\ncompatible versions","Windows 8.1 or Microsoft\nWindows 10\nServer:\nMicrosoft Windows Server\n2008 R2 or\nMicrosoft Windows Server\n2012 R2.\nor Microsoft Server 2016","","predicate device are Microsoft Windows and\nMicrosoft Windows Server respectively.\nThis difference doesn’t impact the safety\nand effectiveness of the subject device."],["Workflow control","Yes\nPre-processing: Auto\nprocess images before\nloading into post-processing\napplications.\nThe client workflow\nsupports both single monitor\nand dual monitors.","Yes\nWorkflows support the\nuser in preparing images\nfor examination.\nSupports various monitor\nsetups workflow.","/","Functional Substantially Equivalent\nPre-processing is equivalent to part of the\n“preparing images for examination”, the\npredicate device also assigns the\nexamination to an application. This\ndifference doesn’t impact the safety and\neffectiveness of the subject device."],["Patient Administration","Yes\nPatient administration\ndisplays the patient data and\noffers the function of\nsearching, sorting, and\nediting of patient data and\nimage preview.","Yes\nWith simplified search\nfunctionality, clearer\nstructure of search results,\nunlimited search results,\nperiodic updates of search\nresults, image preview and\nflexible floating patient\nbrowser window.","/","Functional Substantially Equivalent\nThe proposed device does not support\nflexible floating patient browser window.\nThis difference doesn’t impact the safety\nand effectiveness of the subject device."],["Review 2D","Yes","/","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p10-t0","doc_id":"K230039","page_num":10,"bbox":[72.24,108.02,745.42,529.56],"n_rows":3,"n_cols":5,"columns":["","2D image viewing, Textual\nand graphical annotations，\ndistance, angle, ROI, image\naddition and subtraction,\nimage filter are supported.","","2D image viewing, Textual\nand graphical\nannotations，distance,\nangle, ROI, image addition\nand subtraction, image\nfilter are supported.",""],"rows":[["","2D image viewing, Textual\nand graphical annotations，\ndistance, angle, ROI, image\naddition and subtraction,\nimage filter are supported.","","2D image viewing, Textual\nand graphical\nannotations，distance,\nangle, ROI, image addition\nand subtraction, image\nfilter are supported.",""],["Review 3D","Yes\n3D image viewing, Save 3D\nimages in batches.\nSegmentation functions such\nas CT bone removal tools,\nCT/MR tissue growing tools,\nVOI, cut.","/","Yes\n3D image viewing.\nSave 3D images in\nbatches.\nSegmentation functions\nsuch as CT bone removal\ntools, CT tissue growing\ntools, VOI, cut.","Same"],["Review 3D algorithm","Yes\nVolume rendering (VR) with\nHyper Realistic Rendering\n(HRR), Multi-Planar\nReconstruction (MPR),\nMaximum Intensity\nProjection (MIP), Minimum\nIntensity Projection (MinIP),\nCurved Planar Reformation\n(CPR), Surface-shaded\nDisplay (SSD).\nAutomatic body bone\nremoval algorithm","","Yes\nVolume rendering (VR),\nMulti-Planar\nReconstruction (MPR),\nMaximum Intensity\nProjection (MIP),\nMinimum Intensity\nProjection (MinIP),\nCurved Planar\nReformation (CPR),\nSurface-shaded Display\n(SSD).\nAutomatic body bone\nremoval algorithm","Functional Substantially Equivalent\nHRR is an extension to the standard VR\nrendering algorithm to visualize the\nphotorealistic images.\nThis difference between the proposed device\nand the reference device doesn’t impact the\nsafety and effectiveness of the subject device\nas the necessary measures taken for the\nsafety and effectiveness of the proposed\ndevice."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p11-t0","doc_id":"K230039","page_num":11,"bbox":[72.24,108.02,745.42,536.52],"n_rows":4,"n_cols":5,"columns":["","Automatic head bone\nremoval algorithm","","Automatic head bone\nremoval algorithm",""],"rows":[["","Automatic head bone\nremoval algorithm","","Automatic head bone\nremoval algorithm",""],["Rib segmentation","Yes\nMachine learning based\nalgorithm","/","Yes\nThreshold based\ninteractive algorithm","Functional Substantially Equivalent\nBoth are used for rib segmentation, the\nreference device requires interaction,\nwhile the proposed device does not.\nThis difference between the proposed device\nand the reference device doesn’t impact the\nsafety and effectiveness of the subject device\nas the necessary measures taken for the\nsafety and effectiveness of the proposed\ndevice"],["Inner view","Yes\n3D virtual endoscopy view\nand extract the centerline of\nvessel, airway and colon.\nImaging algorithms:\nCT colon Inner View\nalgorithm\nCT vessel Inner View\nalgorithm\nCT lung trachea Inner View\nalgorithm\nMR vessel Inner View\nalgorithm","/","Yes\n3D virtual endoscopy view\nand extract the centerline\nof vessel, airway and\ncolon.\nImaging algorithms:\nCT colon Inner View\nalgorithm, CT vessel Inner\nView algorithm\nCT lung trachea Inner\nView algorithm","Functional Substantially Equivalent\nThe MR vessel Inner View algorithm is\nsame with CT vessel Inner View algorithm,\nthe difference of input modality does not\naffects the output.\nThis difference between the proposed device\nand the reference device doesn’t impact the\nsafety and effectiveness of the subject device\nas the necessary measures taken for the\nsafety and effectiveness of the proposed\ndevice."],["Filming","Yes","/","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p12-t0","doc_id":"K230039","page_num":12,"bbox":[72.24,108.02,745.42,434.86],"n_rows":3,"n_cols":5,"columns":["","Support to print image and\nselection of printer.","","Support to print image and\nselection of printer.",""],"rows":[["","Support to print image and\nselection of printer.","","Support to print image and\nselection of printer.",""],["Report","Yes\nSupport to create reports,\ntext editing and image\ninserting，customize report\ntemplate, exporting and\nprinting of report.","/","Yes\nSupport to create reports,\ntext editing and image\ninserting，customize\nreport template, exporting\nand printing of report.","Same"],["Archiving","Yes\nImport of DICOM images\nfrom configured network\nnodes (modalities, medical\nimaging process software,\nPACS, etc) or local and\nnetwork drives or DVD/CD.\nExport (archive) DICOM\nimages to network nodes, or\nlocal and network drives or\nDVD/CD.","Yes\nImport of DICOM data\nfrom network nodes or\nexternal media, and of\nDICOM-compliant or non\nDICOM compliant data\nfrom external media and\nWindows file system.\nExport to CD/DVD,\nWindows file system, or\nother DICOM nodes.","/","Functional Substantially Equivalent\nThe proposed product does not support to\nimport non DICOM compliant data from\nexternal media and Windows file system.\nThis difference between the proposed device\nand the reference device doesn’t impact the\nsafety and effectiveness of the subject device\nas the necessary measures taken for the\nsafety and effectiveness of the proposed\ndevice"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p14-t0","doc_id":"K230039","page_num":14,"bbox":[186.74,316.99,601.63,356.35],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Average DICE","The average dice of testing data is higher than 0.8"]],"caption_candidate":"Table 8-1. Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p14-t1","doc_id":"K230039","page_num":14,"bbox":[186.74,404.47,601.63,510.58],"n_rows":3,"n_cols":2,"columns":["Information of data","60 chest CTs"],"rows":[["Information of data","60 chest CTs"],["Sex","Male 37\nFemale 23"],["Age","[14, 35] : 5\n[36, 69] : 41\n[70, 86] : 14"]],"caption_candidate":"Table 8-2. Testing data information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230039-p15-t0","doc_id":"K230039","page_num":15,"bbox":[265.64,171.64,522.64,286.13],"n_rows":7,"n_cols":6,"columns":["","Age","","","DICE",""],"rows":[["","Age","","","DICE",""],["[14,35]","","","0.848","",""],["[36,69]","","","0.856","",""],["[70,86]","","","0.856","",""],["","Gender","","","DICE",""],["Female","","","0.856","",""],["Male","","","0.855","",""]],"caption_candidate":"Table 8-3. Subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230045-p5-t0","doc_id":"K230045","page_num":5,"bbox":[45.0,422.34,576.0,709.86],"n_rows":2,"n_cols":3,"columns":["VI. COMPARISON\nCharacteristic","OF TECHNOLOGICAL CHARACTERISTICS\nSubject Device\nHipCheck","WITH THE PREDICATE DEVICE\nPredicateDevice\nHipCheck"],"rows":[["VI. COMPARISON\nCharacteristic","OF TECHNOLOGICAL CHARACTERISTICS\nSubject Device\nHipCheck","WITH THE PREDICATE DEVICE\nPredicateDevice\nHipCheck"],["Intended\nUse/Indications for Use\nStatement","[K230045]\nHipCheck assists the surgeon to\ndetermine quantitative measurements\nfor femoroacetabular impingement\n(FAI) procedures. HipCheck provides\nstatic localization information derived\nfrom image processing of intra-\noperatively acquired static fluoroscopic\nimages, by superposition of virtual\nmeasurement tools onto those X-ray\nimages for skeletally mature patients.\nHipMap FAI Analysis is a patient-\nspecific report used to support surgeon\nor radiologist pre-operative clinical\ndecision making. HipMap\nfemoroacetabular impingement (FAI)","[K182359]\nHipCheck assists the surgeon to\ndetermine quantitative measurements\nduring femoroacetabular impingement\nprocedures.\nHipCheck provides static localization\ninformation derived from image\nprocessing of intra-operatively acquired\nX-ray images, by superposition of virtual\nmeasurement tools onto those X-ray\nimages."]],"caption_candidate":"VI. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230045-p6-t0","doc_id":"K230045","page_num":6,"bbox":[45.0,116.16,576.0,702.48],"n_rows":12,"n_cols":3,"columns":["","potential FAI, including measurements\nand visualizations that describe hip",""],"rows":[["","potential FAI, including measurements\nand visualizations that describe hip",""],["","impingement and stability.",""],["Product Code(s)","QIH","LLZ"],["Intended Patient\nPopulation","Same as predicate.","Patients undergoing arthroscopic\nsurgery."],["Surgical Approach","Same as predicate.","Arthroscopic surgery, specifically"],["Intended Users","Same as predicate.","femoroacetabular impingement.\nSurgeons and clinical staff."],["Operational\nEnvironment\nPrimary Device Function","SHaimpCeh aesc pkr:e dicate.\nLocate the femoral head and neck to\ndetermine the alpha angle using intra-\noHpiperMataipve F XA-Ir Aayn iamlyasgiess: .\nProvide three-dimensional analyses, 3D\nsurface reconstructions, and annotated","Surgical suite.\nLocate the femoral head and neck to\ndetermine the alpha angle using intra-\noperative X-ray images."],["","images to support surgeons with pre-\noperative clinical decision-making.",""],["Main System\nComponents\nUser Interface","SHaimpCeh aesc pkr:edicate.\nTHaipblMeta p FAI Analysis:","Software\nTablet."],["","General purpose computing platform\nand/or HipCheck tablet.",""],["Body Contact and Use","Same as predicate.","N/A – Device does not have any patient\ncontact."],["Sterile, Single-use\nDesign","SHaimpCeh aesc pkr:e dicate.\n- Workstation for viewing software\n- Dedicated software for image\nprocessing and display of virtual\nHmipeMasaupr eFmAIe nAtn taoloylssi s:\nInteractive HTML report for viewing on\ngeneral purpose computing platform","N /A – Device is not provided sterile or\na s a single use product.\n- Workstation for viewing software\n- Dedicated software for image\nprocessing and display of virtual\nmeasurement tools"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230045-p8-t0","doc_id":"K230045","page_num":8,"bbox":[45.0,116.16,576.0,376.56],"n_rows":5,"n_cols":3,"columns":["Femoral Head Detection\nWorkflow","Same as predicate.","- Extraction of the region of interest\n- Extended Gabor filtering\n- Binary edge detection and\nclassification\n- Circular Hough transformation\n- Feature point tracing"],"rows":[["Femoral Head Detection\nWorkflow","Same as predicate.","- Extraction of the region of interest\n- Extended Gabor filtering\n- Binary edge detection and\nclassification\n- Circular Hough transformation\n- Feature point tracing"],["","","- RANSAC circle matching\n- Target circle selection"],["Energy Source","Same as predicate.","No energy applied to the patient or\noperating staff."],["Software Level of\nConcern\nSoftware Operating\nEnvironment","SHaimpCeh aesc pkr:e dicate.\nProgramming language used is C/C++.\nThe operating system is Windows 10.\nThe hardware platform consists of a","Moderate\nProgramming language used is C/C++.\nThe operating system is Windows 8.1.\nThe hardware platform consists of a\nmicroprocessor-controlled system,"],["","microprocessor-controlled system,\nbased on a PC.","based on a PC."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230074-p2-t0","doc_id":"K230074","page_num":2,"bbox":[257.81,430.87,570.36,527.47],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb,",""],"rows":[["Jessica Lamb,",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230074-p7-t0","doc_id":"K230074","page_num":7,"bbox":[78.13,336.55,544.43,714.5],"n_rows":4,"n_cols":3,"columns":["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],"rows":[["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],["Product Code","QFM","QFM"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Intended Use/\nIndications for\nUse","Rapid Aneurysm Triage and\nNotification (ANRTN) is a\nradiological computer-assisted\ntriage and notification software\ndevice for analysis of CT images\nof the head. The device is\nintended to assist hospital\nnetworks and trained radiologists\nin workflow triage by flagging and\nprioritizing studies with suspected\nsaccular aneurysms during routine\npatient care.\nRapid ANRTN uses an artificial\nintelligence algorithm to analyze\nimages and highlight studies with\nsuspected saccular aneurysms in a\nstandalone application for study\nlist prioritization or triage in\nparallel to ongoing standard of\ncare. The device generates\ncompressed preview images that\nare meant for informational\npurposes only and not intended for","Viz ANEURYSM (Viz ANX)\nis a radiological computer-\nassisted triage and notification\nsoftware device for analysis of\nCT images of the head. The\ndevice is intended to assist\nhospital networks and trained\nradiologists in workflow triage\nby flagging and prioritizing\nstudies with suspected\naneurysms during routine\npatient care.\nViz ANEURYSM uses an\nartificial intelligence algorithm\nto analyze images and highlight\nstudies with suspected\naneurysms in a standalone\napplication for study list\nprioritization or triage in\nparallel to ongoing standard of\ncare. The device generates\ncompressed preview images\nthat are meant for informational"]],"caption_candidate":"submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230074-p8-t0","doc_id":"K230074","page_num":8,"bbox":[78.14,76.51,544.42,717.35],"n_rows":8,"n_cols":3,"columns":["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],"rows":[["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],["","diagnostic use. The device does\nnot alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nAnalyzed images are available for\nreview through the PACS, email\nand mobile application. When\nviewed the images are for\ninformational purposes only and\nnot for diagnostic use. The results\nof Rapid ANRTN, in conjunction\nwith other clinical information and\nprofessional judgment, are to be\nused to assist with\ntriage/prioritization of saccular\naneurysm cases. Radiologists who\nread the original medical images\nare responsible for the diagnostic\ndecision. Rapid ANRT is limited\nto analysis of imaging data and\nshould not be used in-lieu of full\npatient evaluation or relied upon to\nmake or confirm diagnosis.\nRapid ANRT is limited to\ndetecting saccular aneurysms at\nleast 4mm in diameter in adults.\n<inclusions and limitations\nprovided above>","purposes only and not intended\nfor diagnostic use. The device\ndoes not alter the original\nmedical image and is not\nintended to be used as a\ndiagnostic device. Analyzed\nimages are available for review\nthrough the standalone\napplication. When viewed\nthrough the standalone\napplication the images are for\ninformational purposes only\nand not for diagnostic use. The\nresults of Viz ANEURYSM, in\nconjunction with other clinical\ninformation and professional\njudgment, are to be used to\nassist with triage/prioritization\nof medical images.\nRadiologists who read the\noriginal medical images are\nresponsible for the diagnostic\ndecision. Viz ANEURYSM is\nlimited to analysis of imaging\ndata and should not be used in-\nlieu of full patient evaluation or\nrelied upon to make or confirm\ndiagnosis.\nViz ANEURYSM is limited to\ndetecting aneurysms at least\n4mm in diameter."],["Anatomical\nRegion","Head","Head"],["Independent\nStandard of Care","Yes","Yes"],["Notification/\nPrioritization","Yes","Yes"],["Identify patients\nwith pre-specified\nclinical condition","Yes","Yes"],["Clinical Condition","Aneurysm","Aneurysm"],["Intended User","Radiologist","Radiologist"]],"caption_candidate":"K230074 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230074-p9-t0","doc_id":"K230074","page_num":9,"bbox":[78.13,76.51,544.43,174.95],"n_rows":5,"n_cols":3,"columns":["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],"rows":[["Parameter","Rapid ANRTN (Subject Device)","Viz Aneurysm (Predicate Device)"],["DICOM","Yes","Yes"],["Imaging Modality","CTA","CTA"],["Alteration of Image","No","No"],["Preview Images","Non-diagnostic","Non-diagnostic"]],"caption_candidate":"K230074 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230082-p6-t0","doc_id":"K230082","page_num":6,"bbox":[72.2,104.78,547.04,584.71],"n_rows":12,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","AccuContour (K191928)","","","Auto Segmentation",""],["Indications for Use","It is used by radiation oncology\ndepartment to register\nmultimodality images and segment\n(non-contrast) CT images, to\ngenerate needed information for\ntreatment planning, treatment\nevaluation and treatment\nadaptation.","","","Auto Segmentation generates a Radiotherapy\nStructure Set (RTSS) DICOM with segmented\norgans at risk which can be used by dosimetrists,\nmedical physicists, and radiation oncologists as\ninitial contours to accelerate workflow for\nradiation therapy planning. It is the responsibility\nof the user to verify the processed output contours\nand user-defined labels for each organ at risk and\ncorrect the contours/labels as needed. Auto\nSegmentation may be used with images acquired\non CT scanners, in adult patients.","",""],["Contra-indications","None","","","Same","",""],["Patient Population","Adults only","","","Same","",""],["Algorithm","Deep Learning","","","Same","",""],["Compatible Modality","Non-contrast CT images","","","CT (contrast and non-contrast) images","",""],["OAR Segmentation\nAnatomic Regions","Head & Neck\nThorax\nAbdomen\nPelvis","","","Same","",""],["Workflow","Automated","","","Same","",""],["User Interface","Basic result preview of automatic\nsegmentation results. Manual\nsegmentation is possible.\nConfiguration menu.","","","Automated execution of the software with no user\ninteraction, other than configuration settings.\nGenerated contours are automatically transmitted\nto review workstation(s) supporting RTSS objects\nfor review and editing, as needed.","",""],["Compatible Scanner\nModels","No Limitation on scanner model,\nDICOM 3.0 compliance required","","","Same","",""],["Deployment Platform","Cloud and server-based\ndeployment","","","Server-based deployment","",""]],"caption_candidate":"510(k) Premarket Notification Submission – Auto Segmentation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230082-p8-t0","doc_id":"K230082","page_num":8,"bbox":[110.55,281.71,500.25,716.86],"n_rows":24,"n_cols":13,"columns":["OAR","","Auto Segmentation","","","","","Acceptance Criteria","","","","",""],"rows":[["OAR","","Auto Segmentation","","","","","Acceptance Criteria","","","","",""],["","","(subject device)","","","","","","","","","",""],["","","Dice Mean","","","Lower CI95","","","Type","","","Dice Mean",""],["Adrenal Left","78.68%","","","76.63%","","","Estimated","","","68.0%","",""],["Adrenal Right","72.48%","","","69.78%","","","Estimated","","","68.0%","",""],["Bladder","81.50%","","","78.33%","","","Deep learning","","","80.0%","",""],["Body","99.50%","","","99.38%","","","Atlas-based","","","98.1%","",""],["Brainstem","87.69%","","","87.15%","","","Deep learning","","","88.4%","",""],["Chiasma","43.81%","","","41.03%","","","Atlas-based","","","11.7%","",""],["Esophagus","81.69%","","","80.38%","","","Atlas-based","","","45.8%","",""],["Eye Left","91.32%","","","89.77%","","","Deep learning","","","90.1%","",""],["Eye Right","90.25%","","","88.23%","","","Deep learning","","","89.9%","",""],["Femur Left","97.65%","","","97.18%","","","Atlas-based","","","71.6%","",""],["Femur Right","97.92%","","","97.78%","","","Atlas-based","","","70.8%","",""],["Kidney Left","92.53%","","","90.30%","","","Deep learning","","","86.8%","",""],["Kidney Right","94.82%","","","93.48%","","","Deep learning","","","85.6%","",""],["Lacrimal Gland Left","59.79%","","","57.65%","","","Deep learning","","","50.0%","",""],["Lacrimal Gland Right","58.09%","","","55.81%","","","Deep learning","","","50.0%","",""],["Lens Left","76.86%","","","74.80%","","","Deep learning","","","73.3%","",""],["Lens Right","79.09%","","","77.40%","","","Deep learning","","","75.6%","",""],["Liver","94.28%","","","92.27%","","","Deep learning","","","91.1%","",""],["Lung Left","97.70%","","","97.38%","","","Deep learning","","","97.4%","",""],["Lung Right","97.99%","","","97.81%","","","Deep learning","","","97.8%","",""],["Mandible","92.70%","","","92.36%","","","Deep learning","","","94.0%","",""]],"caption_candidate":"Table 1: Summary of Auto Segmentation performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230082-p9-t0","doc_id":"K230082","page_num":9,"bbox":[110.55,104.76,500.25,530.95],"n_rows":22,"n_cols":13,"columns":["OAR","","Auto Segmentation","","","","","Acceptance Criteria","","","","",""],"rows":[["OAR","","Auto Segmentation","","","","","Acceptance Criteria","","","","",""],["","","(subject device)","","","","","","","","","",""],["","","Dice Mean","","","Lower CI95","","","Type","","","Dice Mean",""],["Optic Nerve Left","79.22%","","","77.99%","","","Deep learning","","","71.1%","",""],["Optic Nerve Right","80.20%","","","78.94%","","","Deep learning","","","71.2%","",""],["Oral Cavity","87.43%","","","86.20%","","","Deep learning","","","91.0%","",""],["Pancreas","80.34%","","","78.50%","","","Estimated","","","73.0%","",""],["Parotid Left","84.35%","","","83.27%","","","Deep learning","","","65.0%","",""],["Parotid Right","85.55%","","","84.48%","","","Deep learning","","","65.0%","",""],["Proximal Bronchial Tree\n(PBtree)","84.94%","","","83.71%","","","Atlas-based","","","54.8%","",""],["Inferior PCM (Pharyngeal\nConstrictor Muscle)","70.51%","","","68.72%","","","Estimated","","","68.0%","",""],["Middle PCM","67.09%","","","65.21%","","","Estimated","","","68.0%","",""],["Superior PCM","59.57%","","","57.85%","","","Estimated","","","50.0%","",""],["Pericardium","93.58%","","","92.00%","","","Atlas-based","","","84.4%","",""],["Pituitary","75.62%","","","74.12%","","","Deep learning","","","78.0%","",""],["Prostate","79.67%","","","77.60%","","","Atlas-based","","","52.1%","",""],["Spinal Cord","88.55%","","","87.43%","","","Deep learning","","","87.0%","",""],["Submandibular Left","86.85%","","","85.95%","","","Deep learning","","","77.0%","",""],["Submandibular Right","85.70%","","","84.79%","","","Deep learning","","","78.0%","",""],["Thyroid","85.37%","","","84.27%","","","Deep learning","","","83.0%","",""],["Trachea","91.02%","","","90.47%","","","Atlas-based","","","69.2%","",""],["Whole Brain","98.53%","","","98.46%","","","Estimated","","","93.0%","",""]],"caption_candidate":"510(k) Premarket Notification Submission – Auto Segmentation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230084-p5-t0","doc_id":"K230084","page_num":5,"bbox":[77.85,417.59,525.65,759.46],"n_rows":8,"n_cols":3,"columns":["","HERA W9 /HERA W10","HERA W9/HERA W10 (K220043)"],"rows":[["","HERA W9 /HERA W10","HERA W9/HERA W10 (K220043)"],["Feature","",""],["","(Under Review)","Primary Predicate"],["","",""],["","",""],["Manufacturer","SAMSUNG MEDISON CO.,LTD","SAMSUNG MEDISON CO.,LTD"],["Intended Use","The HERA W9/ HERA W10 Diagnostic\nUltrasound System and transducers are\nintended for diagnostic ultrasound\nimaging\nand fluid analysis of the human body.","The HERA W9/ HERA W10 Diagnostic\nUltrasound System and transducers are\nintended for diagnostic ultrasound imaging\nand fluid analysis of the human body."],["Functionality","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+\n- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for Thyroid\n- ADVR\n- 3D Imaging\n- (Volume Data Acquisition)\n- 3D Imaging presentation\n- 3D Cine/4D Cine\n- 3D Rendering MPR\n- 3D XI MSV/Oblique View\n- Volume CT","- Q Scan\n- ClearVision\n- MultiVision\n- Panoramic\n- NeedleMate+\n- AutoIMT+\n- Elastoscan+\n- E-Thyroid\n- E-Breast\n- E-Strain\n- S-Detect for Breast\n- S-Detect for Thyroid\n- ADVR\n- 3D Imaging\n- (Volume Data Acquisition)\n- 3D Imaging presentation\n- 3D Cine/4D Cine\n- 3DRendering MPR\n- 3D XI MSV/Oblique View\n- Volume CT"]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230084-p6-t0","doc_id":"K230084","page_num":6,"bbox":[77.86,85.44,525.64,666.94],"n_rows":7,"n_cols":3,"columns":["","HERA W9 /HERA W10","HERA W9/HERA W10 (K220043)"],"rows":[["","HERA W9 /HERA W10","HERA W9/HERA W10 (K220043)"],["Feature","",""],["","(Under Review)","Primary Predicate"],["","",""],["","",""],["","- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI VOCAL) XI STIC\n- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*\n- Slice A\n- HeartAssist *\n- ViewAssist","- 3D MagiCut\n- Volume Calculation\n- (VOCAL, XI VOCAL) XI STIC\n- HDVI\n- RealisticVue\n- CEUS+\n- HQ-Vision\n- MV-Flow\n- CrystalVue\n- CrystalVue Flow*\n- 5D CNS+\n- 5D Follicle\n- 5D Heart Color\n- 5D Limb Vol\n- 5D LB\n- 5D NT\n- 2D NT\n- IOTA-ADNEX\n- BiometryAssist\n- E-Cervix\n- LumiFlow\n- ShadowHDR\n- MPI+*\n- Slice A\n- HeartAssist *\n- ViewAssist"],["Transducers","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A\n- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A\n- EV2-12 (NEW)","- L3-12A\n- LA2-9A\n- LA4-18B\n- CA1-7A\n- CA2-9A\n- CA3-10A\n- CF4-9\n- E3-12A\n- EA2-11B\n- VR5-9\n- PA4-12B\n- PA3-8B\n- PM1-6A\n- CV1-8A\n- EV3-10B\n- EV2-10A\n- EA2-11AV\n- EA2-11AR\n- LA2-14A\n- PA1-5A"]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230084-p7-t0","doc_id":"K230084","page_num":7,"bbox":[104.21,435.05,518.61,592.99],"n_rows":8,"n_cols":4,"columns":["Difference","","HERA W9","HERA W10"],"rows":[["Difference","","HERA W9","HERA W10"],["Software","CrystalVue Flow","Not Supported","Supported"],["","MPI+","Not Supported","Supported"],["","HeartAssist","Not Supported","Supported"],["Hardware","Internal DVD","Not Included","Included"],["","Caster size","5\"","6\""],["","Active array probe port","3 port (default),\n4 port(option)","4 port"],["","Main monitor","21.5\"/ 23.8\" / 27\"","21.5\"/ 23\" / 23.8\" / 27\""]],"caption_candidate":"The differences between HERA W9 and HERA W10 in the subject device are as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230084-p7-t1","doc_id":"K230084","page_num":7,"bbox":[104.21,695.02,518.61,768.1],"n_rows":3,"n_cols":2,"columns":["Reference No.","Title"],"rows":[["Reference No.","Title"],["IEC 60601-1","ANSI AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and\nA2:2010 /(R)2012 Medical Electrical Equipment - Part 1: General\nRequirements for basic safety and essential performance."],["IEC 60601-1-2","IEC60601-1-2: 2020(4.1 Edition), Medical electrical equipment - Part 1-2:\nGeneral requirements for basic safety and essential performance - EMC"]],"caption_candidate":"standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230084-p8-t0","doc_id":"K230084","page_num":8,"bbox":[104.18,85.32,518.64,188.9],"n_rows":4,"n_cols":2,"columns":["IEC 60601-2-37","IEC60601-2-37:2007 + A1:2015, Particular requirements for the safety of\nultrasonic medical diagnostic and monitoring equipment"],"rows":[["IEC 60601-2-37","IEC60601-2-37:2007 + A1:2015, Particular requirements for the safety of\nultrasonic medical diagnostic and monitoring equipment"],["ISO10993-1","ISO 10993-1:2018, Biological evaluation of medical devices -- Part 1:\nEvaluation and testing within a risk management process."],["ISO14971","ISO 14971:2019, Medical devices - Application of risk management to medical\ndevices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound Equipment\nRevision 3"]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230085-p4-t0","doc_id":"K230085","page_num":4,"bbox":[73.5,162.54,425.44,708.43],"n_rows":37,"n_cols":3,"columns":["Applicant:","","ImagenTechnologies,Inc."],"rows":[["Applicant:","","ImagenTechnologies,Inc."],["","","224W35thStSte500"],["","","New York, NY 10001"],["","",""],["ContactandPrimary","","RebeccaJones, Ph.D."],["Correspondent:","","VP,ClinicalResearch"],["","","Headof Regulatory"],["","",""],["","","ImagenTechnologies,Inc."],["","","224W35thStSte500"],["","","New York, NY 10001"],["","","917-565-9319"],["","","rebecca.jones@imagen.ai"],["","",""],["SecondaryCorrespondent:","","AlexJ. Cadotte,Ph.D."],["","","SeniorDirector,DigitalHealth&Imaging"],["","",""],["","","MCRA"],["","","8037thStreet,NW,3rd Floor"],["","","Washington,DC 20001"],["","","202-742-3828"],["","","acadotte@mcra.com"],["","",""],["DatePrepared:","","September22,2023"],["","",""],["2. D EVICE","",""],["","",""],["DeviceTradeName:","L","ung-CAD"],["","",""],["DeviceCommonNameor","","MedicalImageAnalyzer"],["ClassificationName:","",""],["","",""],["Regulation:","2","1CFR 892.2070"],["","",""],["RegulatoryClass:","I","I"],["","",""],["ProductCode:","","MYN"]],"caption_candidate":"Applicant: ImagenTechnologies,Inc.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230085-p4-t1","doc_id":"K230085","page_num":4,"bbox":[67.5,555.5,489.5,714.5],"n_rows":5,"n_cols":2,"columns":["DeviceTradeName:","Lung-CAD"],"rows":[["DeviceTradeName:","Lung-CAD"],["DeviceCommonNameor\nClassificationName:","MedicalImageAnalyzer"],["Regulation:","21CFR 892.2070"],["RegulatoryClass:","II"],["ProductCode:","MYN"]],"caption_candidate":"2. D EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230085-p6-t0","doc_id":"K230085","page_num":6,"bbox":[72.25,435.74,540.25,627.5],"n_rows":8,"n_cols":3,"columns":["","ProposedDevice","Predicate"],"rows":[["","ProposedDevice","Predicate"],["Number","K230085","K210666"],["Applicant","ImagenTechnologies,Inc.","ImagenTechnologies,Inc."],["DeviceName","Lung-CAD","Chest-CAD"],["ClassificationRegulation","892.2070","892.2070"],["ProductCode","MYN","MYN"],["ImageModality","X-ray","X-ray"],["StudyType","Chest","Chest"]],"caption_candidate":"Table 1: TechnologicalComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230085-p7-t0","doc_id":"K230085","page_num":7,"bbox":[72.33,72.13,540.33,462.5],"n_rows":10,"n_cols":3,"columns":["","ProposedDevice","Predicate"],"rows":[["","ProposedDevice","Predicate"],["ClinicalOutput","Identifyandmarkregionsof\ninterest(ROIs)onchest\nradiographsandlabelthebox\naroundtheROIaslung\nhyperinflation","Identifyandmarkregionsof\ninterest(ROIs)onchest\nradiographsandlabelthebox\naroundtheROIasoneofthe\nfollowing:Cardiac,\nMediastinum/Hila,Lungs,Pleura,\nBones,SoftTissues,Hardware,or\nOther"],["IntendedUsers","Physicians","Physicians"],["IntendedUserWorkflow","Deviceintendedforuseasa\nconcurrentreadingaidfor\nphysiciansinterpretingchest\nradiographs","Deviceintendedforuseasa\nconcurrentreadingaidfor\nphysiciansinterpretingchest\nradiographs"],["PatientPopulation","AdultswithChestRadiographs","AdultswithChestRadiographs"],["MachineLearning\nMethodology","SupervisedDeepLearning","SupervisedDeepLearning"],["Platform","Securecloud-basedprocessing\nanddeliveryofchestradiographs","Securecloud-basedprocessing\nanddeliveryofchestradiographs"],["ImageSource","DigitalX-ray","DigitalX-ray"],["ImageViewing","ImagedisplayedonPACSsystem","ImagedisplayedonPACSsystem"],["Privacy","HIPAACompliant","HIPAACompliant"]],"caption_candidate":"510(k) Summary Page4of8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230085-p9-t0","doc_id":"K230085","page_num":9,"bbox":[72.25,90.42,540.2,165.5],"n_rows":2,"n_cols":4,"columns":["Category","GroundTruth\nPositiven(%)","AUC","95%BootstrapCI"],"rows":[["Category","GroundTruth\nPositiven(%)","AUC","95%BootstrapCI"],["Lunghyperinflation","266(5.3)","0.964","0.956,0.972"]],"caption_candidate":"Table 2: AUCoftheROCCurveforLung-CADPredictions","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230085-p9-t1","doc_id":"K230085","page_num":9,"bbox":[72.25,221.26,540.2,359.5],"n_rows":3,"n_cols":5,"columns":["Category","Sensitivity","Specificity","Positive\nPredictiveValue","Negative\nPredictiveValue"],"rows":[["Category","Sensitivity","Specificity","Positive\nPredictiveValue","Negative\nPredictiveValue"],["","95%\nWilson'sCI","95%\nWilson'sCI","95%\nWilson'sCI","95%\nWilson'sCI"],["Lunghyperinflation","0.898\n(0.856,0.929)","0.894\n(0.885,0.902)","0.322\n(0.289,0.357)","0.994\n(0.991,0.996)"]],"caption_candidate":"Lung-CADPredictions","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230096-p6-t0","doc_id":"K230096","page_num":6,"bbox":[52.38,325.5,555.78,510.18],"n_rows":4,"n_cols":5,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0\nwith CC-MLO\nCorrelation","Predicate\nHologic, Inc.\nGenius AI\nDetection 2.0","ScreenPoint\nMedical\nTranspara 1.7.2","Difference and\ncomments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0\nwith CC-MLO\nCorrelation","Predicate\nHologic, Inc.\nGenius AI\nDetection 2.0","ScreenPoint\nMedical\nTranspara 1.7.2","Difference and\ncomments"],["510(k) Number","pending","K221449","K221347","N/A"],["Regulation\nNumber/Name","21 CFR 892.2090 /\nRadiological Computer\nAssisted Detection and\nDiagnosis Software","Same","Same","N/A"],["Product Code","QDQ","Same","Same","N/A"]],"caption_candidate":"Summary of Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230096-p8-t0","doc_id":"K230096","page_num":8,"bbox":[52.38,72.3,555.78,658.38],"n_rows":4,"n_cols":5,"columns":["Compatible\nDBT\nSystems","Hologic Selenia\nDimensions\nHologic 3Dimensions\nSupports both models\nin the following\nmodes:\nstandard\nresolution 1-mm\nslices\nhigh resolution 1-\nmm slices (Clarity\nHD)\nhigh resolution 6-\nmm SmartSlices\n(3DQuorum)","Same","Giotto FFDM\nGeneral Electric DBT\nFujifilm DBT","The predicate\nand subject\ndevice include\nthe support of\nthe following\nmodes on the\nHologic DBT\nsystems only:\nstandard res.\n1-mm slices\nhigh res. 1-\nmm slices .\nhigh resolution\n6-mm\nSmartSlices"],"rows":[["Compatible\nDBT\nSystems","Hologic Selenia\nDimensions\nHologic 3Dimensions\nSupports both models\nin the following\nmodes:\nstandard\nresolution 1-mm\nslices\nhigh resolution 1-\nmm slices (Clarity\nHD)\nhigh resolution 6-\nmm SmartSlices\n(3DQuorum)","Same","Giotto FFDM\nGeneral Electric DBT\nFujifilm DBT","The predicate\nand subject\ndevice include\nthe support of\nthe following\nmodes on the\nHologic DBT\nsystems only:\nstandard res.\n1-mm slices\nhigh res. 1-\nmm slices .\nhigh resolution\n6-mm\nSmartSlices"],["Type of CAD\nSoftware","Radiological\ncomputer assisted\ndetection and\ndiagnostic software.","Same","Same","N/A"],["Mode of Action","Image processing\ndevice utilizing\nmachine learning to\naid in the detection,\nlocalization, and\ncharacterization of\nsoft tissue densities\n(masses, architectural\ndistortions, and\nasymmetries) and\ncalcifications in the 1-\nmm 3D DBT slices.\nFindings are co-\nregistered to 6-mm\nSmartSlices.","Same","Software that applies\nalgorithms for\nrecognition of\nsuspicious\ncalcifications and soft\ntissue lesions to\ndetect and\ncharacterize findings\nin radiological breast\nimages and provide\ninformation about\nthe presence,\nlocation, and\ncharacteristics of the\nfindings to the user.","Similar"],["Clinical\nOutput","To inform the\nprimary diagnostic\nand patient\nmanagement\ndecisions that are\nmade by the clinical\nuser.","Same","Same","N/A"]],"caption_candidate":"Genius AI Detection 2.0 CC-MLO Correlation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230096-p9-t0","doc_id":"K230096","page_num":9,"bbox":[52.38,72.3,555.78,653.58],"n_rows":7,"n_cols":5,"columns":["Patient\nPopulation","Symptomatic\nand\nasymptomatic\nwomen\nundergoing\nmammography","Same","The device is\nintended to be used\nin the population of\nwomen undergoing\nscreening\nmammography and\ndigital breast\ntomosynthesis.","Similar"],"rows":[["Patient\nPopulation","Symptomatic\nand\nasymptomatic\nwomen\nundergoing\nmammography","Same","The device is\nintended to be used\nin the population of\nwomen undergoing\nscreening\nmammography and\ndigital breast\ntomosynthesis.","Similar"],["End Users","MQSA-Qualified\nInterpreting\nPhysicians and\nRadiologists","Same","Intended users of\nTranspara® are\nphysicians qualified\nto read screening\nmammography\nexams and digital\nbreast tomosynthesis\nexams.","Similar"],["Image Source\nModalities","Digital breast\ntomosynthesis slices","Same","Same","N/A"],["Output Device","Softcopy Workstation","Same","Same","N/A"],["Deployment","Stand-alone computer","Same","Same","N/A"],["Method Of Use","Concurrent read","Same","Same","N/A"],["Visualization\nFeatures","Places mark within\nsuspicious lesion by\ndefault (Emphasize ;\nRightOn ) and reports\nconfidence of finding\nnext to each identified\nlesion in the image. CAD\ndisplay may be toggled\non/off. Option to\nautomatically zoom into\nor contour the suspicious\nregion of interest\n(PeerView ).","Same","Computer aided\ndetection (CAD)\nmarks to highlight\nlocations where the\ndevice\ndetected suspicious\ncalcifications or soft\ntissue lesions\nDecision support is\nprovided by region\nscores on a scale\nranging from 0-100,\nwith\nhigher scores\nindicating a higher\nlevel of suspicion.","Similar"]],"caption_candidate":"Genius AI Detection 2.0 CC-MLO Correlation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230112-p6-t0","doc_id":"K230112","page_num":6,"bbox":[95.98,112.46,563.84,686.3],"n_rows":58,"n_cols":4,"columns":["Characteristic","Proposed Device","Predicate Device","Comparison"],"rows":[["Characteristic","Proposed Device","Predicate Device","Comparison"],["","CAC Software","Zebra Medical Vision",""],["","","HealthCCSng",""],["","","",""],["Regulatory","","",""],["","","",""],["FDA Clearance","TBD","K210085 (9/9/2021)","-"],["","","",""],["Product Code","JAK","JAK","Same"],["","","",""],["Class","II","II","Same"],["","","",""],["Regulation","21 CFR 892.1750","21 CFR 892.1750","Same"],["","","",""],["Software","Device is software only","Device is software only","Same"],["","","",""],["Level of Concern","Moderate","Moderate","Same"],["","","",""],["General","","",""],["","","",""],["Modality","CT","CT","Same"],["","","",""],["Anatomical Site","Thoracic,Chest,Cardiac","Thoracic,Chest,Cardiac","Same"],["","","",""],["Support Input CT Scan","Low and standard dose.","Low and standard dose.","Different - Predicate is"],["","Cardiac-gated and non-","Non-cardiac-gated. Up","not labeled for use in"],["","cardiac-gated. Up to","to 3mm slice thickness.","cardiac-gated scans."],["","3mm slice thickness.","",""],["","","",""],["Image Format","DICOM","DICOM","Same"],["","","",""],["Use Environment","Hospitals and Clinics in-","Hospitals and Clinics in-","Same"],["","cluding Inpatient and","cluding Inpatient and",""],["","outpatient,andlungcan-","outpatient,andlungcan-",""],["","cer screening programs.","cer screening programs.",""],["","","",""],["Quantification","","",""],["","","",""],["Calcium Detection","Automatic","Automatic","Same"],["","","",""],["Default Threshold","130 (HU)","130 (HU)","Same"],["","","",""],["Calcium Reporting","CAC score and reference","3 category CAC risk","Different - Predicate"],["","5 category CAC risk","","does not report CAC"],["","","","scoreandcombineslower"],["","","","risk categories."],["","","",""],["Display and Outputs","","",""],["","","",""],["Outputs","DICOM Report and","DICOM Report and","Same"],["","CAC annotated DICOM","CAC annotated DICOM",""],["","images.","images.",""],["","","",""],["Alterationoforiginalim-","No","No","Same"],["age","","",""],["","","",""],["Image Viewing","Images viewed on exist-","Images viewed on exist-","Same"],["","ing viewing workstation.","ing viewing workstation.",""]],"caption_candidate":"Characteristic Proposed Device Predicate Device","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230144-p6-t0","doc_id":"K230144","page_num":6,"bbox":[72.37,92.61,540.04,701.76],"n_rows":15,"n_cols":8,"columns":["","Subject Device","","Primary Predicate","","","Secondary Predicate",""],"rows":[["","Subject Device","","Primary Predicate","","","Secondary Predicate",""],["","","","Device","","","Device",""],["510(k) Number","K230144","K210365","","","K210187","",""],["Applicant","Denti.AI","Pearl","","","Overjet","",""],["Device Name","Detect","Second Opinion","","","Dental Assist","",""],["Classification\nRegulation","892.2070 Medical Image\nAnalyzer\n892.2050 Picture Archive\nand Communication\nSystem","892.2070 Medical Image\nAnalyzer","","","892.2050 Picture Archive\nand Communication\nSystem","",""],["Product Code","MYN\nLLZ","MYN","","","LLZ","",""],["Prescription\nUse","Yes","Yes","","","Yes","",""],["Intended Users","Dentists and Dental\nSpecialists","Dental health\nprofessionals","","","Trained professionals\nincluding, but not limited\nto, dentists and dental\nhygienists","",""],["Patient\nPopulation","Adults 22 years of age\nand older with permanent\ndentition","Patients 12 years and\nolder with permanent\nteeth","","","Adults 22 years of age and\nolder","",""],["Platform","Cloud-based","Windows 7","","","Cloud-based","",""],["Imaging\nModality","Intraoral (bitewing,\nperiapical)\nExtraoral (panoramic)","Intraoral (bitewing,\nperiapical)","","","Intraoral (bitewing,\nperiapical)","",""],["Supported File\nformats","jpeg, jpg, tiff, tif, png,\nbmp, DICOM","RVG, DICOM, JPEG,\nTIFF, and PNG and\nconverts to JPEG","","","jpg, png, jfif, eop, etp, jif","",""],["Detection\nFindings","Caries and Periapical\nradiolucency","Caries, Discrepancy at\nthe margin of an existing\nrestoration, Calculus,\nPeriapical radiolucency,\nCrown (metal, including\nzirconia & non-metal),\nFilling (metal & non-\nmetal), Root canal,\nBridge and Implants.","","","N/A","",""],["Reader\nWorkflow for\nDetection","Second Reader","Second Reader","","","N/A","",""]],"caption_candidate":"Table 1: Technological Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230144-p7-t0","doc_id":"K230144","page_num":7,"bbox":[72.16,72.63,540.19,149.1],"n_rows":3,"n_cols":8,"columns":["","Subject Device","","Primary Predicate","","","Secondary Predicate",""],"rows":[["","Subject Device","","Primary Predicate","","","Secondary Predicate",""],["","","","Device","","","Device",""],["Measurements","Mesial and distal bone\nlevels associated with\neach tooth","N/A","","","Mesial and distal bone\nlevels associated with each\ntooth","",""]],"caption_candidate":"510(k) Summary - K230144 Page 4 of 6","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230144-p8-t0","doc_id":"K230144","page_num":8,"bbox":[72.4,126.74,549.05,353.16],"n_rows":17,"n_cols":2,"columns":["Endpoint","Results (95% CI)"],"rows":[["Endpoint","Results (95% CI)"],["Bitewing: CEJ-Bone: Sensitivity","98.1% (96%, 99.5%)"],["Bitewing: CEJ-Bone: Specificity","93% (88.7%, 96.7%)"],["Bitewing: CEJ-Bone: MAE","0.513 mm (0.444 mm, 0.593 mm)"],["Bitewing: CEJ-Bone/CEJ-Root Ratio: MAE","3.8% (3.3%, 4.4%)"],["",""],["Periapical: CEJ-Bone: Sensitivity","98.2% (96.2%, 99.7%)"],["Periapical: CEJ-Bone: Specificity","88.5% (82.8%, 93.4%)"],["Periapical: CEJ-Bone: MAE","0.572 mm (0.497 mm, 0.653 mm)"],["Periapical: CEJ-Root: Sensitivity","96.9% (94.2%, 99%)"],["Periapical: CEJ-Root: Specificity","92.2% (87.9%, 96%)"],["Periapical: CEJ-Root: MAE","0.735 mm (0.612 mm, 0.868 mm)"],["Periapical: CEJ-Bone/CEJ-Root Ratio: MAE","4.3% (3.7%, 4.9%)"],["",""],["Extraoral: CEJ-Bone-Root: Sensitivity","91.6% (89.6%, 93.6%)"],["Extraoral: CEJ-Bone-Root: Specificity","84.3% (70.8%, 95.8%)"],["Extraoral: CEJ-Bone/CEJ-Root Ratio: MAE","4.7% (4%, 5.5%)"]],"caption_candidate":"Table 2: Primary Study Endpoints and Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230179-p5-t0","doc_id":"K230179","page_num":5,"bbox":[76.44,127.68,538.32,184.68],"n_rows":4,"n_cols":4,"columns":["Predicate","510(k)","Device","Owner"],"rows":[["Predicate","510(k)","Device","Owner"],["Primary","K173291","6440 – MyLab9","Esaote S.p.A."],["Reference","K192157","6450 – MyLabX8","Esaote S.p.A."],["Reference","K212021","6430 – MyLabX75","Esaote S.p.A."]],"caption_candidate":"Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230179-p7-t0","doc_id":"K230179","page_num":7,"bbox":[72.24,532.5,511.56,660.48],"n_rows":6,"n_cols":3,"columns":["Main application","Districts","Invasive access"],"rows":[["Main application","Districts","Invasive access"],["","",""],["","Cardiac Adult, Cardiac Pediatric",""],["","Neonatal, Adult Cephalic, Vascular",""],["","Abdominal, Breast, Musculo-\nskeletal, Neonatal, Pediatric, Small\nOrgans (Testicles), Thyroid,\nUrological",""],["","OB/Fetal, Gynecology",""]],"caption_candidate":"Table: Intended Purpose","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230179-p8-t0","doc_id":"K230179","page_num":8,"bbox":[152.4,292.92,442.68,497.76],"n_rows":17,"n_cols":2,"columns":["Probe","Cleared via"],"rows":[["Probe","Cleared via"],["C 2-9","K192157"],["E 3-12","K192157"],["IL 4-13","K161359"],["IOT342","K161359"],["LP 4-13","K161359"],["P 2-9","K190989"],["P2 5-13","K190989"],["SB3123","K161359"],["SL3116","K161359"],["2CWL (Continous Wave Doppler)","The present submission"],["5CWL (Continous Wave Doppler)","The present submission"],["CX 1-8","The present submission"],["LX 3-15","The present submission"],["LMX 4-20","The present submission"],["PX 1-5","The present submission"],["TE 3-8","The present submission"]],"caption_candidate":"• The following probes management is added on the upgraded 6440 system:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230179-p9-t0","doc_id":"K230179","page_num":9,"bbox":[97.92,220.08,466.2,244.08],"n_rows":2,"n_cols":3,"columns":["Shape","Orientation:","Circumscribed:"],"rows":[["Shape","Orientation:","Circumscribed:"],["Success Rate > 80%","Success Rate > 90%","Success Rate > 75%"]],"caption_candidate":"BIRADS Parameters","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p5-t0","doc_id":"K230197","page_num":5,"bbox":[72.31,138.02,523.85,178.82],"n_rows":2,"n_cols":9,"columns":["","Name","","","Manufacturer","","","510(k)#",""],"rows":[["","Name","","","Manufacturer","","","510(k)#",""],["BoneMRI v1.4","","","MRIguidance B.V.","","","K221762","",""]],"caption_candidate":"5.7 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p6-t0","doc_id":"K230197","page_num":6,"bbox":[72.29,338.55,523.87,706.9],"n_rows":5,"n_cols":8,"columns":["","","Predicate Device","","","Subject Device","","Comment"],"rows":[["","","Predicate Device","","","Subject Device","","Comment"],["","","BoneMRI v1.4","","","BoneMRI","",""],["Intended Use","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI\nimages. It can be used to\nvisualize the bone structures\nin MRI images with\nenhanced contrast with\nrespect to the surrounding\nsoft tissue. It is to be used in\nthe pelvic region, which\nincludes the bony anatomy\nof the sacrum, hip bones\nand femoral heads; and the\nlumbar spine region, which\nincludes the bony anatomy\nof the vertebrae from L3 to\nS1. BoneMRI is not to be\nused for diagnosis or\nmonitoring of (primary or\nmetastatic) tumors.\nWarning: BoneMRI images\nare not intended to replace\nCT images.","","","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI\nimages. It can be used to\nvisualize the bone structures\nin MRI images with\nenhanced contrast with\nrespect to the surrounding\nsoft tissue. It is to be used in\nthe pelvic region, which\nincludes the bony anatomy\nof the sacrum, hip bones\nand femoral heads; and the\nlumbar spine region, which\nincludes the bony anatomy\nof the vertebrae from L3 to\nS1. BoneMRI is not to be\nused for diagnosis or\nmonitoring of (primary or\nmetastatic) tumors.\nWarning: BoneMRI images\nare not intended to replace\nCT images.","","","The same"],["21CFR Section","892.2050","","","892.2050","","","The same"],["Product Code","QIH","","","QIH","","","The same"]],"caption_candidate":"A. Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p7-t0","doc_id":"K230197","page_num":7,"bbox":[72.29,91.92,523.88,142.34],"n_rows":3,"n_cols":8,"columns":["","","Predicate Device","","","Subject Device","","Comment"],"rows":[["","","Predicate Device","","","Subject Device","","Comment"],["","","BoneMRI v1.4","","","BoneMRI","",""],["Target Population","Adults","","","Adults","","","The same"]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p7-t1","doc_id":"K230197","page_num":7,"bbox":[72.29,202.49,523.88,717.46],"n_rows":9,"n_cols":8,"columns":["","","Predicate Device","","","Subject Device","","Comment"],"rows":[["","","Predicate Device","","","Subject Device","","Comment"],["","","BoneMRI v1.4","","","BoneMRI","",""],["Device Nature","Software package","","","Software package","","","The same"],["Operating System","Linux","","","Linux","","","The same"],["Data input","MRI images in DICOM\nformat","","","MRI images in DICOM\nformat","","","The same"],["Data output","MRI images in DICOM\nformat","","","MRI images in DICOM\nformat","","","The same"],["Processing\nAlgorithms","MRIguidance software\nimplements an image\nenhancement algorithm\nusing convolutional neural\nnetwork. Original images are\nenhanced by running them\nthrough a cascade of filter\nbanks, where thresholding\nand scaling operations are\napplied. Separate neural\nnetwork-based filters are\nobtained to assign a\nHounsfield Unit (HU) value\nto a single volume element,\nbased on intensity and\ncontextual information. The\nparameters of the model\nwere obtained through an\nalgorithm development\npipeline.","","","MRIguidance software\nimplements an image\nenhancement algorithm\nusing convolutional neural\nnetwork. Original images are\nenhanced by running them\nthrough a cascade of filter\nbanks, where thresholding\nand scaling operations are\napplied. Separate neural\nnetwork-based filters are\nobtained to assign a\nHounsfield Unit (HU) value\nto a single volume element,\nbased on intensity and\ncontextual information. The\nparameters of the model\nwere obtained through an\nalgorithm development\npipeline.","","","The same"],["User Interface","None – enhanced images\nare viewed on existing\nPACS workstations","","","None – enhanced images\nare viewed on existing\nPACS workstations","","","The same"],["Workflow","The software operates on\nDICOM files on the file\nsystem, enhances the\nimages, and stores the\nenhanced images on the file\nsystem. The receipt of\noriginal DICOM image files\nand delivery of enhanced\nimages as DICOM files","","","The software operates on\nDICOM files on the file\nsystem, enhances the\nimages, and stores the\nenhanced images on the file\nsystem. The receipt of\noriginal DICOM image files\nand delivery of enhanced\nimages as DICOM files","","","The same"]],"caption_candidate":"B. Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p8-t0","doc_id":"K230197","page_num":8,"bbox":[72.31,91.92,523.85,173.78],"n_rows":3,"n_cols":8,"columns":["","","Predicate Device","","","Subject Device","","Comment"],"rows":[["","","Predicate Device","","","Subject Device","","Comment"],["","","BoneMRI v1.4","","","BoneMRI","",""],["","depends on other software\nsystems. Enhanced images\nco-exist with the original\nimages.","","","depends on other software\nsystems. Enhanced images\nco-exist with the original\nimages.","","",""]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230197-p8-t1","doc_id":"K230197","page_num":8,"bbox":[78.71,516.13,547.01,699.34],"n_rows":8,"n_cols":3,"columns":["Validation data demographics","",""],"rows":[["Validation data demographics","",""],["","",""],["Anatomy","Pelvic region","Lumbar spine region"],["Number of patients","101","103"],["Indications","Sacroiliitis, developmental hip\ndysplasia, avascular necrosis\nof femoral head and femoral\nacetabular impingement.","Sacroiliitis, degenerative spine\ndiseases, spondylolisthesis,\nradiculopathy, spondylosis and\nspinal fractures."],["Gender","Male: 73\nFemale: 28","Male: 49\nFemale: 54"],["Age","52 ± 21 years","55 ± 15 years"],["Data origin/Ethnicity","USA, Europe, Asia","USA, Europe, Asia"]],"caption_candidate":"The demographics of the patient population are described in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230208-p5-t0","doc_id":"K230208","page_num":5,"bbox":[72.19,355.49,539.85,710.51],"n_rows":14,"n_cols":3,"columns":["Subject Swoop® Portable MR","Subject Swoop® Portable MR Imaging","Predicate Swoop® Portable MR"],"rows":[["Subject Swoop® Portable MR","Subject Swoop® Portable MR Imaging","Predicate Swoop® Portable MR"],["Imaging System™","System™","Imaging System™ (K223247)"],["Intended Use/ Indications for\nUse:","The Swoop® Portable MR Imaging\nSystem™ is a bedside magnetic\nresonance imaging device for producing\nimages that display the internal\nstructure of the head where full\ndiagnostic examination is not clinically\npractical. When interpreted by a trained\nphysician, these images provide\ninformation that can be useful in\ndetermining a diagnosis.","Same"],["Patient Population:","Adult and pediatric patients (≥ 0 years)","Same"],["Anatomical Sites:","Head","Same"],["Environment of Use:","At the point of care in professional\nhealth care facilities such as emergency\nrooms, critical care units, hospital, or\nrehabilitation rooms.","Same"],["Energy Used and/or delivered:","Magnetic Resonance","Same"],["Magnet:","",""],["Physical Dimensions","835 mm x 630 mm x 652 mm","Same"],["Bore Opening","610 mm x 315 mm","Same"],["Weight","320 kg","Same"],["Field Strength","63.3 mT permanent magnet","Same"],["Gradient:","",""],["Strength","X: 24 mT/m, Y: 23 mT/m, Z: 39 mT/m","Same"]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230208-p6-t0","doc_id":"K230208","page_num":6,"bbox":[72.14,72.83,539.86,528.83],"n_rows":21,"n_cols":3,"columns":["Rise Time","X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms","Same"],"rows":[["Rise Time","X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms","Same"],["Slew Rate","X: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/s","Same"],["Computer Display","Hyperfine-supplied tablet","Same"],["RF Coils:","",""],["Number of Coils","1 head coil","Same"],["Coil Type","TX/RX","Same"],["Coil Geometry","Form-fitting","Same"],["Inner Dimensions (mm)","205 mm x 240 mm","Same"],["Coil Design","Linear Volume","Same"],["Patient Weight Capacity","1.6kg-200 kg","Same"],["Operation Temperature","15-30 C","Same"],["Warm Up Time","<3 minutes","Same"],["Temperature Control","No","Same"],["Humidity Control","No","Same"],["Image Reconstruction Algorithm","",""],["Noise Correction","Noise correction and line noise\nsuppression for all sequences","Same"],["T1W\n• T1-Standard\n• T1-Gray/White Contrast","Advanced Gridding","Same"],["T2W\n• T2\n• T2-Fast","Advanced Gridding","Same"],["FLAIR","Advanced Gridding","Same"],["DWI","Fast Iterative Shrinkage Thresholding\nAlgorithm (FISTA)","Conjugate Gradient"],["Image Post-Processing","• Advanced Denoising (applies to\nT1W, T2W, and FLAIR only)\n• Image orientation transform\n• Geometric distortion correction\n• Receive coil intensity correction\n• DICOM output","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230208-p7-t0","doc_id":"K230208","page_num":7,"bbox":[72.9,167.57,539.85,434.99],"n_rows":4,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Software\nVerification","Software verification testing in accordance with\nthe design requirements to ensure that the\nsoftware requirements were met.","• IEC 62304:2006\n• FDA Guidance, “Guidance for the\nContent of Premarket Submissions for\nSoftware Contained in Medical\nDevices”"],["Image\nPerformance","Testing to verify the subject device meets all\nimage quality criteria.","• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• American College of Radiology (ACR)\nPhantom Test Guidance for Use of the\nLarge MRI Phantom for the ACR MRI\nAccreditation Program\n• American College of Radiology\nstandards for named sequences"],["Software Validation","Validation to ensure the device meets user needs\nand performs as intended.","• FDA Guidance, “Guidance for the\nContent of Premarket Submissions for\nSoftware Contained in Medical\nDevices”"]],"caption_candidate":"accordance with internal requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230208-p7-t1","doc_id":"K230208","page_num":7,"bbox":[72.9,504.29,539.85,697.07],"n_rows":5,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Biocompatibility","Biocompatibility testing of patient-contacting\nmaterials.","• ISO 10993-1:2018\n• ISO 10993-5:2009\n• ISO 10993-10:2010"],["Cleaning/\nDisinfection","Cleaning and disinfection validation of patient-\ncontacting materials.","• FDA Guidance, “Reprocessing Medical\nDevices in Health Care Settings:\nValidation Methods and Labeling”\n• ISO 17664:2017\n• ASTM F3208-17"],["Safety","Electrical Safety, EMC, and Essential Performance\ntesting.","• ANSI/AAMI ES 60601-1:2005/(R)2012\n• IEC 60601-1-2:2014\n• IEC 60601-1-6:2013"],["Performance","Characterization of the Specific Absorption Rate\nfor Magnetic Resonance Imaging Systems.","• NEMA MS 8-2016"]],"caption_candidate":"modifications did not introduce a new worst-case configuration or scenario for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230209-p4-t0","doc_id":"K230209","page_num":4,"bbox":[54.28,367.17,557.74,403.85],"n_rows":2,"n_cols":9,"columns":["","Classification Description","","","21 CFR Section","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR Section","","","Product Code",""],["Automated Radiological Image Processing Software","","","21 CFR 892.2050","","","QIH, LLZ","",""]],"caption_candidate":"-Trade name: Sonix Health","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230209-p6-t0","doc_id":"K230209","page_num":6,"bbox":[36.25,94.7,751.89,555.82],"n_rows":9,"n_cols":15,"columns":["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],"rows":[["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],["Trade/Device name","","","","","","Sonix Health","","","TOMTEC-ARENA","","","V8 Diagnostic Ultrasound System","",""],["Product Code","","","","","","QIH (Subsequent Product Code: LLZ)","","","QIH (Subsequent Product Code: LLZ)","","","IYN, IYO, ITX","",""],["Regulatory Class","","","SE","","","2","","","2","","","2","",""],["Regulation Number","","","-","","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.1550, 892.1560, 892.1570","",""],["Intended use","","","SE","","","Sonix Health is intended for quantifying\nand reporting echocardiography for use by\nor on the order of a licensed physician.\nSonix Health accepts DICOM-compliant\nmedical images acquired from ultrasound\nimaging devices. Sonix Health is indicated\nfor use in adult populations.\nUltrasound images are acquired via the B\n(2D), M, Pulsed-wave Doppler, and\nContinuous-wave Doppler modes.","","","TOMTEC-ARENA software is a\nclinical software package designed for\nreview, quantification and reporting of\nstructures and function based on multi-\ndimensional digital medical data\nacquired with different modalities.\nTOMTEC ARENA is not intended to\nbe used for reading of mammography\nimages.","","","The V8 / V7 diagnostic ultrasound system and\nprobes are designed to obtain ultrasound images\nand analyze body fluids.\nThe clinical applications include: Fetal/Obstetrics,\nAbdominal, Gynecology, Intra-operative, Pediatric,\nSmall Organ, Neonatal Cephalic, Adult Cephalic,\nTrans-rectal, Trans-vaginal, Muscular-Skeletal\n(Conventional, Superficial), Urology, Cardiac\nAdult, Cardiac Pediatric, Thoracic, Trans-\nesophageal (Cardiac) and Peripheral vessel.\nIt is intended for use by, or by the order of, and\nunder the supervision of, an appropriately trained\nhealthcare professional who is qualified for direct\nuse of medical devices. It can be used in hospitals,\nprivate practices, clinics and similar care\nenvironment for clinical diagnosis of patients.\nModes of Operation: 2D mode, Color Doppler\nmode, Power Doppler (PD) mode, M mode, Pulsed\nWave (PW) Doppler mode, Continuous Wave\n(CW) Doppler mode, Tissue Doppler Imaging\n(TDI) mode, Tissue Doppler Wave (TDW) mode,\nElastoScan Mode, Combined modes, Multi-Image\nmode (Dual, Quad), 3D/4D mode.","",""],["Indications for use","","","SE","","","","","","Indications for use of TOMTEC-\nARENA TTA2 software are\nquantification and reporting of\ncardiovascular, fetal, abdominal\nstructures and function of patients with\nsuspected disease to support the\nphysician in the diagnosis","","","","",""],["Where used\n(hospital, home,\nambulance, etc.)","","","SE","","","Inside of hospitals, clinics, and physician’s\noffices.","","","Inside and outside of Hospitals,\nClinics, and Physician’s offices.","","","Inside of hospitals, clinics, and physician’s offices.","",""],["Application\ndescription","","","SE","","","Sonix Health utilizes artificial intelligence\nto automate previous manual quantification\ntasks, resulting in increased efficiency for\nusers. Our system performs view","","","IMAGE-COM is a basic module for\nreviewing and measuring digital\nmedical data. It supports routine\nworkflows for loading, analyzing and","","","The V8 / V7 are a general purpose, mobile,\nsoftware controlled, diagnostic ultrasound system.\nTheir function is to acquire ultrasound data and to\ndisplay the data as 2D mode,Color Doppler mode,","",""]],"caption_candidate":"The identified predicate devices within this submission is shown in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230209-p7-t0","doc_id":"K230209","page_num":7,"bbox":[36.27,25.92,751.87,545.74],"n_rows":4,"n_cols":15,"columns":["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],"rows":[["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],["","","","","","","classification and measurements according\nto the US ASE guidelines, and the users\ncan review and modify the results if\nnecessary.","","","saving medical studies, e.g. for the\npurpose of creating reports. IMAGE-\nCOM is where basic measurements can\nbe performed and the entry point for\nadvanced analysis modules. Study\nrelated routine measurements can be\nimported, displayed, edited and\nexported to accompanying reporting\nsystems.","","","Power Doppler (PD) mode, M mode, Pulsed Wave\n(PW) Doppler mode, Continuous Wave (CW)\nDoppler mode, Tissue Doppler Imaging (TDI)\nmode, Tissue Doppler Wave (TDW) mode,\nElastoScan Mode, Combined modes, Multi-Image\nmode(Dual, Quad), 3D/4D mode. The V8 / V7 also\ngive the operator the ability to measure anatomical\nstructures and offer analysis packages that provide\ninformation that is used to make a K223387\nTraditional 510(k) diagnosis by competent health\ncare professionals. The V8 / V7 have a real time\nacoustic output display with two basic indices, a\nmechanical index and a thermal index, which are\nboth automatically displayed.","",""],["Semi-automated\nview classification","","","SE","","","PLAX LV, A4C, A4C Zoomed LV, A2C,\nA2C zoomed LV, M-mode LA/Ao, M-\nmode LV, CW Doppler MS, CW Doppler\nMR, PW Doppler MV, CW Doppler AV,\nCW Doppler AR, CW Doppler TR, CW\nDoppler PV, CW Doppler PR, PW Doppler\nRVOT, PW Doppler LVOT, DTI MV\nannulus","","","-","","","PLAX LV, A4C, A4C Zoomed LV, A2C, A2C\nzoomed LV, M-mode LA/Ao, M-mode LV, CW\nDoppler MS, CW Doppler MR, PW Doppler MV,\nCW Doppler AV, CW Doppler AR, CW Doppler\nTR, CW Doppler PV, CW Doppler PR, PW\nDoppler RVOT, PW Doppler LVOT, DTI MV\nannulus","",""],["Semi-automated\nmeasurements","","","SE","","","IVSd (2D), IVSs (2D), LVIDd (2D),\nLVIDs (2D), LVPWd (2D), LVPWs (2D),\nLA (2D), Ao (2D), LVESV / LVEDV\n(4CH), LAV (4CH), LVESV / LVEDV\n(4CH), LVESV / LVEDV (2CH), LAV\n(2CH), LVESV / LVEDV (2CH), LA (m-\nmode), Aorta (m-mode), IVSd (m-mode),\nLVIDd (m-mode), LVPWd (m-mode),\nIVSs (m-mode), LVIIDs (m-mode),\nLVPWs (m-mode), MV Peak E Vel, MV\nPeak A Vel, MV Decel Time, e' (med), a'\n(med), s' (med), LVOT Vmax, LVOT VTI,\nRVOT Vmax, RVOT VTI, PV AccT, TR\nVmax, TR VTI, AR Vmax / PR Vmax, AR\nPHT / PR PHT, MV Vmax, MV VTI, MV,\nPHT, MR Vmax, MR VTI, AV Vmax / PV\nVmax, AV VTI / PV VTI, RVOT (2D)","","","B-Mode\n- Ao Asc diam, Ao Ann diam, Ao STJ\ndiam, Ao SV diam, IVSd, LA diam\nsystole, LVIDd, LVIDs, LVOT diam,\nLVPWd, RVDd base (RVD1), RVDd\nmid (RVD2), RVLd, RVOT diam lax,\nRVOT diam prox, TV Ann diam ant-\npost, IVSd-LVIDd-LVPWd (Same\nline)\nDOPPLER Mode\n- MV A Vel, MV E Vel, MV E/A\nSlope, (MV A Vel, MV E Vel, MV\nTime), MV Dec. Slope, (MV Dec\nTime, MV E Vel), LVOT VTI, AV\nVTI, PV VTI, TR Vmax, LV E’(l), LV\nA’(l), LV E’(s), LV A’(s), RV A’(l),\nRV E’(l), RV S’(l)","","","(PLAX LV) - Interventricular septum diameter at the\ndiastole and systole phase, LV internal diameter at\nthe diastole and systole phase, LV posterior wall\ndiameter at the diastole and systole phase, Aorta\ndiameter and LA diameter, (A4C) - LA Volume, LV\nVolume, (A4C Zoomed LV) - LV Volume, (A2C) -\nLA Volume, LV Volume, (A2C zoomed LV) - LV\nVolume, (M-mode LA/Ao) - LA diameter and Aorta\ndiameter, (M-mode / LV) - Interventricular septum\ndiameter at the diastole and systole phase, LV\ninternal diameter at the diastole and systole phase,\nLV posterior wall diameter at the diastole and systole\nphase, (CW Doppler MS) - Vmax, VTI, PHT, (CW\nDoppler MR) - Vmax, VTI, (PW Doppler MV) - E,\nA, DT, (CW Doppler AV) - Vmax, VTI, (CW\nDoppler AR) - Vmax, PHT, (CW Doppler TR) -\nVmax, VTI, (CW Doppler PV) - Vmax, VTI, (CW\nDoppler PR) - Vmax, EDV, (PW Doppler RVOT) -\nVmax, VTI, (PW Doppler LVOT) - Vmax, VTI,\n(DTI MV annulus) - S’, E’, A’","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230209-p8-t0","doc_id":"K230209","page_num":8,"bbox":[36.29,25.92,751.85,188.3],"n_rows":2,"n_cols":15,"columns":["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],"rows":[["","Description","","","Decision","","","Subject Device (K230209)","","","Predicate Device (K213544)","","","Reference Device (K220975)",""],["Semi-automation\ntechnology","","","SE","","","After the automated analysis is complete,\nusers can review and modify the results as\nneeded. The product is intended for use by,\nor on the order of a licensed physician.","","","Semi-automated adult\nechocardiography 2D and Doppler\nmeasurements are generated using and\nartificial intelligence (AI) detection\nalgorithm without user interaction.\nAfter measurement is generated, the\nuser can edit (manually adjust the\ncaliper positions), accept, or reject the\nmeasurements. The automation of\nmeasurements is constrained to the\nspecific imaging mode (2D, Doppler)\nas recommended by ASE guidelines.","","","After the analysis is complete, users can review and\nmodify the results as needed. The product is for use\nby, or on the order of a licensed physician.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p6-t0","doc_id":"K230220","page_num":6,"bbox":[110.4,129.6,526.08,743.38],"n_rows":17,"n_cols":5,"columns":["Hardware property","Proposed device\nNeuViz 128","","","Predicate device\nNeuViz 128 (K151383)"],"rows":[["Hardware property","Proposed device\nNeuViz 128","","","Predicate device\nNeuViz 128 (K151383)"],["Gantry\nAperture","720mm","","","720mm"],["Gantry\nTilt","+/-30°","","","+/-30°"],["Gantry\nScan Speed（s／360°）","0.374s、0.5s、0.6s、0.8s、\n1.0s、1.5s、2.0s","","","0.374s、0.5s、0.6s、0.8s、\n1.0s、1.5s、2.0s"],["Detector Type","Solid-state GOS ceramic","","","Solid-state GOS ceramic"],["Detector Number of\nDetector Rows","64","","","64"],["Maximum slices generated\nper rotation (multislice\ncapability)","128","","","128"],["Generator Max. Power","80kW","","","80kW"],["Generator mA Range","10mA~667mA","","","30mA~667mA"],["Generator kV Settings","80kV, 100kV, 120kV,\n140kV","","","80kV, 100kV, 120kV,\n140kV"],["Tube\nFocal Spots","0.6×1.2（small）\n1.1×1.2（large）","","","0.6×1.2（small）\n1.1×1.2（large）"],["Tube\nheat capacity","8.0MHU","","","8.0MHU"],["Couch\nType/max. moving\nlength/max. table\nloading/max. horizontal\nspeed","","standard couch(option):","","standard couch:\n205kg/160mm/s\n300kg couch (option):\n300kg/160mm/s"],["","","211kg/225mm/s","",""],["","","long couch(option):","",""],["","","211kg/310mm/s","",""],["","","300kg couch(option):","",""]],"caption_candidate":"devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p7-t0","doc_id":"K230220","page_num":7,"bbox":[110.4,106.16,526.72,184.41],"n_rows":2,"n_cols":3,"columns":["","300kg/225mm/s",""],"rows":[["","300kg/225mm/s",""],["Intelligent Positioning\nDevice\n(optional)","option for Intelligent\nPositioning feature","N/A"]],"caption_candidate":"510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p7-t1","doc_id":"K230220","page_num":7,"bbox":[110.4,220.2,526.72,731.88],"n_rows":16,"n_cols":5,"columns":["Software property\nand Feature","Proposed device\nNeuViz 128","","","Predicate device\nNeuViz 128 (K151383)"],"rows":[["Software property\nand Feature","Proposed device\nNeuViz 128","","","Predicate device\nNeuViz 128 (K151383)"],["Recon FOV","","50mm~500mm;","","50mm~500mm"],["","","Extended FOV 700mm(Optional)","",""],["Spiral Scan Range of\nPitch","0.1-2.1","0.1-2.1","","0.13-1.5"],["Reconstruction\nAlgorithm","Filtered back-projection (FBP);\nClearView;\nClearInfinity (Optional);","","","Filtered back-projection\n(FBP) ;\nClearView"],["O-Dose","Support","","","Support"],["Bolus tracking","Support","","","Support"],["SAS","Support","","","Support"],["Home","Support","","","Support"],["Film","Support","","","Support"],["Report","Support","","","Support"],["Image Review","Support","","","Support"],["MPR","Support","","","Support"],["3D","Support","","","Support"],["Virtual Endoscopy","Support","","","Support"],["Dental Analysis","Support","","","Support"]],"caption_candidate":"devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p8-t0","doc_id":"K230220","page_num":8,"bbox":[110.4,106.08,526.8,748.74],"n_rows":23,"n_cols":5,"columns":["(Optional)","","","",""],"rows":[["(Optional)","","","",""],["Vessel Analysis","Support","","","Support"],["DICOM Viewer","Support","","","Support"],["Virtual\nColonoscopy(Optional\n)","Support","","","Support"],["Brain\nPerfusion(Optional)","Support","","","Support"],["Body\nPerfusion(Optional)","Support","","","Support"],["Lung Nodule\nAnalysis(Optional)","Support","","","Support"],["Lung\nDensity(Optional)","Support","","","Support"],["Coronary\nAnalysis(Optional)","Support","","","Support"],["Cardiac Calcium\nScoring(Optional)","Support","","","Support"],["Cardiac Function\nAnalysis(Optional)","Support","","","Support"],["Cardiac\nViewer(Optional)","Support","","","Support"],["Fat Analysis(Optional)","Support","","","Support"],["CTDSA(Optional)","Support","","","Support"],["Tumor\nAssessment(Optional)","Support","","","Support"],["Real-time\nMPR(Optional)","","Support.","","N/A"],["","","Real-time MPR reconstruction is","",""],["","","a recon mode, in the clinical sca","",""],["","","nning, automatically generate sa","",""],["","","gittal or coronal MPR images ba","",""],["","","sed on the CT axial images. Red","",""],["","","uce secondary loading reconstru","",""],["","","ction time.","",""]],"caption_candidate":"510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p9-t0","doc_id":"K230220","page_num":9,"bbox":[110.4,106.2,526.8,743.5],"n_rows":47,"n_cols":5,"columns":["4D scanning(Optional)","","Support.","","N/A"],"rows":[["4D scanning(Optional)","","Support.","","N/A"],["","","It is a kind of fast spiral perfusion","",""],["","","scan.The table top of couch","",""],["","","moves back and forth repeatedly","",""],["","","in the area of interest when the","",""],["","","patient is injected with contrast","",""],["","","agent. So as to track the dynamic","",""],["","","images of contrast agent","",""],["","","changing in the same part at","",""],["","","different times.","",""],["Dual Energy Imaging\n（ Prism Imaging）\n(Optional)","","Support.","","N/A"],["","","Dual-energy imaging uses two","",""],["","","energies during one CT","",""],["","","examination, performs image","",""],["","","reconstruction of data originated","",""],["","","by the two energy separately and","",""],["","","then decomposes the two kinds","",""],["","","of images into a set of basis","",""],["","","images of pre-defined materials","",""],["","","(the decomposition parameters","",""],["","","are pre-set by the manufacturer) ,","",""],["","","according to which the next","",""],["","","process is conducted.","",""],["Prism\nViewer(Optional)","","Support","","N/A"],["","","Prism Viewer application is used","",""],["","","to view and analysis multi energy","",""],["","","images. Display a variety of","",""],["","","images with different parameters","",""],["","","and provide visual tools, to help","",""],["","","users to locate the lesion","",""],["","","accurately.","",""],["Intelligent\nPositioning(Optional)","","Support.","","N/A"],["","","The system collects and displays","",""],["","","the natural image information of","",""],["","","the human body. The system can","",""],["","","use the human body image","",""],["","","information to automatically","",""],["","","calculates the scanning position","",""],["","","according to the scanning","",""],["","","protocol and using artificial","",""],["","","intelligence","",""],["","","technology. At the same time,","",""],["","","User can also manually draw the","",""],["","","scan frame on the human","",""],["","","body Image, And Then, the","",""],["","","system calculates the scanning","",""],["","","position by the scan frame.","",""]],"caption_candidate":"510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230220-p10-t0","doc_id":"K230220","page_num":10,"bbox":[110.4,106.2,526.8,621.78],"n_rows":34,"n_cols":5,"columns":["","","According to the scanning","",""],"rows":[["","","According to the scanning","",""],["","","protocol, the system can","",""],["","","automatically adjust the couch","",""],["","","height from intelligence setting.","",""],["","","The system support patient","",""],["","","position, posture and collision","",""],["","","Detection.","",""],["Coronary Motion\nClear(Optional)","","Support.","","N/A"],["","","Coronary Motion Clear functi","",""],["","","on is used to generate imag","",""],["","","e dateset with less motion ar","",""],["","","tefact in coronary area.","",""],["Metal artifact\nremoval(Optional)","","MAR,MAR+.","","MAR"],["","","MAR/MAR+ stands for metal","",""],["","","artifact reduction. It‘s the post","",""],["","","processing algorithm that can","",""],["","","remove the artifacts caused by","",""],["","","metal or high CT value. MAR","",""],["","","method only needs image","",""],["","","data, while MAR+ method needs","",""],["","","both image data and raw data.","",""],["Arrhythmia\nHandling(Optional)","","Support.","","N/A"],["","","Recognize and ignore the ar","",""],["","","rhythmia R-peak during card","",""],["","","iac scan, and trigger the sca","",""],["","","n while normal R-peak recog","",""],["","","nized.","",""],["Auto FOV+(Optional)","","Support.","","N/A"],["","","Auto FOV is automatically mark t","",""],["","","he FOV range on the surview im","",""],["","","age based on AI technology, and","",""],["","","the FOV range can be adjusted","",""],["","","manually.Supported scan parts i","",""],["","","nclude head and lungs","",""]],"caption_candidate":"510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230223-p4-t0","doc_id":"K230223","page_num":4,"bbox":[72.32,284.76,445.34,373.82],"n_rows":5,"n_cols":4,"columns":["","Proprietary Name","","iCAC Device"],"rows":[["","Proprietary Name","","iCAC Device"],["","Classification Name","","Computed tomography x-ray system"],["","Regulation Number","","21 CFR 892.1750"],["","Product Code","","JAK"],["","Regulatory Class","","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230223-p4-t1","doc_id":"K230223","page_num":4,"bbox":[72.32,408.66,445.34,516.22],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","HealthCCSng Manufactured by Zebra Health"],"rows":[["","Proprietary Name","","HealthCCSng Manufactured by Zebra Health"],["","Premarket Notification","","K210085"],["","Classification Name","","Computed tomography x-ray system"],["","Regulation Number","","21 CFR 892.1750"],["","Product Code","","JAK"],["","Regulatory Class","","II"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230223-p8-t0","doc_id":"K230223","page_num":8,"bbox":[72.24,72.24,539.76,687.48],"n_rows":17,"n_cols":4,"columns":["Characteristic","Proposed Device: iCAC","Predicate Device:\nHealthCCSng\nManufactured by Zebra\nMedical\n(K210085)","Summary"],"rows":[["Characteristic","Proposed Device: iCAC","Predicate Device:\nHealthCCSng\nManufactured by Zebra\nMedical\n(K210085)","Summary"],["","reviewing the patient’s\nresults.","",""],["Type of\nInterpretation","Adjunctive information","Adjunctive information","Same"],["Intended User","Interpreting physicians","Interpreting physicians","Same"],["Patient population","Patients aged 30 years\nand above","Patients above the age of\n30","Similar"],["Anatomical location","Chest","Chest","Same"],["Intended location","Medical facility","Medical facility","Same"],["Rx or OTC","Rx","Rx","Same"],["Measurement scale","Agatston units","Agatston units","Same"],["Product code","JAK","JAK","Same"],["Regulation number","21 CFR §892.1750","21 CFR §892.1750","Same"],["Modality","Computed tomography\n(CT)","Computed tomography\n(CT)","Same"],["Image format","DICOM","DICOM","Same"],["Contrast","Non-contrast","Non-contrast","Same"],["Supported CT scan","Non-cardiac-gated CT\nscan","Non-cardiac-gated CT\nscan","Same"],["Slice thickness","Up to 5mm","Up to 3mm","Similar, iCAC can\nsupport a wider variety of\nscans"],["Calcification\ndetection","Automatic","Automatic","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230223-p9-t0","doc_id":"K230223","page_num":9,"bbox":[72.24,72.24,539.76,609.72],"n_rows":7,"n_cols":4,"columns":["Characteristic","Proposed Device: iCAC","Predicate Device:\nHealthCCSng\nManufactured by Zebra\nMedical\n(K210085)","Summary"],"rows":[["Characteristic","Proposed Device: iCAC","Predicate Device:\nHealthCCSng\nManufactured by Zebra\nMedical\n(K210085)","Summary"],["Default threshold of\ncalcium","130 HU (Hounsfield\nUnits)","130 HU (Hounsfield\nUnits)","Same"],["Coronary artery\ncalcification\nquantification\nmethod","CAC detection category\n(based on Agatston\nscore), exact Agatston\nscore","CAC detection category\n(based on Agatston score)","Similar, iCAC provides a\nmore precise\nrepresentation of coronary\ncalcium burden"],["Main image quality","DICOM","DICOM","Same"],["Annotation of\ndetected calcium","Yes","Yes","Same"],["Generate patient\nreport","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary\nCapture","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary\nCapture","Same"],["Report of the\ncalcium score","Yes, Coronary Calcium\nDetection Category and\nexact Agatston score\n4 categories (for detection\ncategory):\n(cid:120) 0\n(cid:120) 1-99\n(cid:120) 100-399\n(cid:120) (cid:149)(cid:23)(cid:19)(cid:19)","Yes, Coronary Calcium\nDetection Category\n3 categories:\n(cid:120) 0-99\n(cid:120) 10-399\n(cid:120) >400","Similar, iCAC provides a\nmore precise\nrepresentation of coronary\ncalcium burden by\nseparating the category 0\nfrom the other categories."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230252-p4-t0","doc_id":"K230252","page_num":4,"bbox":[72.6,166.89,362.09,542.02],"n_rows":28,"n_cols":3,"columns":["510(k) Owner Information","",""],"rows":[["510(k) Owner Information","",""],["Name:","","Orthofix US LLC"],["Address:","","3451 Plano Parkway"],["","","Lewisville, TX, USA"],["","",""],["Telephone Number:","","214-937-2176"],["Fax Number:","","214-937-3322"],["Email:","","shantaghyarian@orthofix.com"],["","",""],["Registration Number:","","2183449"],["","",""],["Contact Person:","","Shant Aghyarian"],["","",""],["Date Prepared:","","September 21, 2023"],["","",""],["Name of Device","",""],["Trade Name / Proprietary","",""],["Name:","","OFIX MIS App"],["","",""],["Common Name:","O","FIX MIS App"],["","",""],["Product Code(s):","L","LZ"],["","",""],["Classification Name:","S","ystem, Image Processing, Rad"],["","",""],["Regulatory Class:","C","lass II per 21 CFR 892.2050"],["","",""],["Predicate Devices:","N","emaris Surgimap 2.0, K14166"]],"caption_candidate":"510(k) Owner Information","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230264-p6-t0","doc_id":"K230264","page_num":6,"bbox":[72.29,270.26,579.97,570.2],"n_rows":10,"n_cols":3,"columns":["Feature","Subject Device","Predicate Device (K203182)"],"rows":[["Feature","Subject Device","Predicate Device (K203182)"],["Regulation Number","CFR 892.2050","Same"],["Product Code","LLZ","Same"],["Indications for Use","EzraFlashisanimageprocessingsoft-\nware used for image enhancement of\nMR images. It can be used to reduce\nimage noise for non-contrast 3T head\nMRI scans.","SubtleMR is an image processing soft-\nware that can be used for image en-\nhancement in MRI images. It can\nbe used to reduce image noise for\nhead, spine, neck, abdomen, pelvis,\nprostate, breast and musculoskeletal\nMRI, or increase image sharpness for\nhead MRI."],["Physical Character-\nistics","Softwarepackagethatoperatesonoff-\nthe-shelf hardware","Same"],["Computer","Linux Compatible","Same"],["DICOM Standard\nCompliance","The software processes DICOM com-\npliant image data","Same"],["Operating System","Linux","Same"],["Modalities","MRI","Same"],["User Interface","None – enhanced images are viewed\non existing PACS workstations","Same"]],"caption_candidate":"Table 1: Subject and Predicate Device Comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230264-p7-t0","doc_id":"K230264","page_num":7,"bbox":[72.26,158.48,580.0,463.5],"n_rows":2,"n_cols":3,"columns":["Image Enhancement\nAlgorithm Descrip-\ntion","EzraFlashsoftwareimplementsanim-\nage enhancement algorithm using a\nconvolutionalneuralnetwork-basedfil-\ntering. Original images are enhanced\nby running through a cascade of filter\nbanks, where thresholding and scal-\ning operations are applied. These fil-\nters result in a single machine learn-\ning model that reduces noise. The pa-\nrameters of the filters were obtained\nthrough an image-guided optimization\nprocess.","SubtleMR software implements an im-\nageenhancementalgorithmusingcon-\nvolutional neural network based filter-\ning. Original images are enhanced\nby running through a cascade of filter\nbanks, where thresholding and scaling\noperations are applied. Separate neu-\nral network based filters are obtained\nfor noise reduction and sharpness in-\ncrease. The parameters of the fil-\nters were obtained through an image-\nguided optimization process."],"rows":[["Image Enhancement\nAlgorithm Descrip-\ntion","EzraFlashsoftwareimplementsanim-\nage enhancement algorithm using a\nconvolutionalneuralnetwork-basedfil-\ntering. Original images are enhanced\nby running through a cascade of filter\nbanks, where thresholding and scal-\ning operations are applied. These fil-\nters result in a single machine learn-\ning model that reduces noise. The pa-\nrameters of the filters were obtained\nthrough an image-guided optimization\nprocess.","SubtleMR software implements an im-\nageenhancementalgorithmusingcon-\nvolutional neural network based filter-\ning. Original images are enhanced\nby running through a cascade of filter\nbanks, where thresholding and scaling\noperations are applied. Separate neu-\nral network based filters are obtained\nfor noise reduction and sharpness in-\ncrease. The parameters of the fil-\nters were obtained through an image-\nguided optimization process."],["Workflow","The software operates on DICOM files\non the file system, enhances the im-\nages, and stores the enhanced images\non the file system. The receipt of orig-\ninal DICOM image files and delivery of\nenhanced images as DICOM files de-\npends on other software systems. En-\nhanced images co-exist with the origi-\nnal images.","Same"]],"caption_candidate":"Image Enhancement EzraFlashsoftwareimplementsanim- SubtleMR software implements an im-","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230355-p4-t0","doc_id":"K230355","page_num":4,"bbox":[93.42,237.54,555.18,317.1],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Galan 3T, MRT-3020, V9.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230355-p5-t0","doc_id":"K230355","page_num":5,"bbox":[94.24,518.64,548.8,584.88],"n_rows":5,"n_cols":2,"columns":["System","Predicate Device"],"rows":[["System","Predicate Device"],["","Vantage Galan 3T, MRT-3020, V8.0 with AiCE Reconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K222387"],["Clearance Date","August 31, 2022"]],"caption_candidate":"(K222387)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230355-p7-t0","doc_id":"K230355","page_num":7,"bbox":[95.05,149.56,558.58,402.16],"n_rows":11,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Galan 3T, MRT-3020, V9.0","","","Vantage Galan 3T, MRT-3020, V8.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR (K222387)","",""],["Static field strength","3T","","","3T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i.Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii.Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p4-t0","doc_id":"K230365","page_num":4,"bbox":[72.26,189.14,535.06,508.63],"n_rows":4,"n_cols":2,"columns":["Applicant:","Sonio\n24 rue du Faubourg Saint Jacques,\n75014, Paris France"],"rows":[["Applicant:","Sonio\n24 rue du Faubourg Saint Jacques,\n75014, Paris France"],["Primary Contact Person:","Florian Akpakpa\nHead of Regulatory Affairs and Quality Assurance\nSonio\nPhone: +33 6 19 38 71 45\nEmail: florian.akpakpa@sonio.ai"],["Secondary Contact\nPerson:","Donna-Bea Tillman\nSenior Consulting\nBiologics Consulting\nPhone: +1 (410) 531-6542 - Direct\nEmail: dtillman@biologicsconsulting.com"],["Date Prepared:","July 25, 2023"]],"caption_candidate":"I.Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p4-t1","doc_id":"K230365","page_num":4,"bbox":[72.26,585.43,554.26,726.58],"n_rows":4,"n_cols":2,"columns":["Device Trade Name:","Sonio Detect"],"rows":[["Device Trade Name:","Sonio Detect"],["Classification Name:","21 CFR 892.1550 - accessory to Ultrasonic Pulsed Doppler Imaging System\n21 CFR 892.1560 - accessory to Ultrasonic Pulsed Echo Imaging System\n21 CFR 892.2050 - Medical image management and processing system"],["Regulatory Class:","Class II"],["Product Codes:","IYN (Primary)\nIYO, QIH (Secondary)"]],"caption_candidate":"II.Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p6-t0","doc_id":"K230365","page_num":6,"bbox":[75.08,166.58,525.7,417.53],"n_rows":12,"n_cols":2,"columns":["Table 1: List of views that can be automatically de\nView","tected by the software\nGestational Age of the fetus"],"rows":[["Table 1: List of views that can be automatically de\nView","tected by the software\nGestational Age of the fetus"],["Transthalamic or Cavum septum Pellucidum or Midline falx /\nTransventricular or Choroid plexus","T1 and T2/T3"],["Profile or Nuchal translucency","T1 and T2/T3"],["Crown rump length","T1"],["Sagittal spine","T2/T3"],["Abdominal circumference","T2/T3"],["Long bone","T2/T3"],["Transcerebellar view","T2/T3"],["Upper lip, nose and nostrils","T2/T3"],["Four chambers","T2/T3"],["Left ventricular outflow tract","T2/T3"],["Right ventricular outflow tract","T2/T3"]],"caption_candidate":"detected and verified by the software are detailed in the tables 1, 2 and 3 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p6-t1","doc_id":"K230365","page_num":6,"bbox":[75.08,444.31,525.7,750.1],"n_rows":5,"n_cols":2,"columns":["View","Structure"],"rows":[["View","Structure"],["Brain views and structures at T2/T3",""],["Transthalamic view\nTransventricular view\nTranscerebellar view","• Midline falx\n• Cavum septum pellucidum\n• Cerebellum"],["Heart views and structures at T2/T3",""],["Four Chambers\nThree vessels\nLVOT","• Aorta\n• Apex heart\n• Ascending aorta\n• Descending aorta\n• Interatrial septum\n• Interventricular septum\n• Left atrium\n• Left ventricle\n• Pulmonary trunk\n• Right atrium\n• Right ventricle\n• Superior vena cava"]],"caption_candidate":"Table 2:List of anatomical structures that can be automatically detected by the software","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p7-t0","doc_id":"K230365","page_num":7,"bbox":[75.5,113.18,525.7,549.79],"n_rows":8,"n_cols":2,"columns":["Quality criteria of the brain views",""],"rows":[["Quality criteria of the brain views",""],["For the transthalamic view, Sonio\nDetect automatically evaluates the\nfollowing criteria:","• Presence of the cavum septum pellucidum\n• Absence of the cerebellum\n• Brain occupies more than half of the width of the\nultrasound image"],["For the transcerebellar view, Sonio\nDetect automatically evaluates the\nfollowing criteria:","• Presence of the cerebellum\n• Presence of the cavum septum pellucidum\n• Brain occupies more than half of the width of the\nultrasound image"],["For the transventricular view, Sonio\nDetect automatically evaluates the\nfollowing criteria:","• Presence of the cavum septum pellucidum\n• Brain occupies more than half of the width of the\nultrasound image"],["Quality criteria of the heart views",""],["For the 4 chambers view, Sonio\nDetect automatically evaluates the\nfollowing criteria:","• Presence of the right ventricle\n• Presence of the left ventricle\n• Presence of the left atrium\n• Presence of the right atrium\n• Presence of the interventricular septum\n• Presence of the interauricular septum\n• Presence of the apex of the heart\n• Presence of the descending aorta"],["For the 3 vessels and 3 vessels and\ntrachea views, Sonio Detect\nautomatically evaluates the following\ncriteria:","• Presence of the pulmonary trunk\n• Presence of the ascending aorta\n• Presence of the superior vena cava"],["For the LVOT view, Sonio Detect\nautomatically evaluates the following\ncriteria:","• Presence of the left ventricle\n• Presence of the aorta\n• Presence of the right ventricle\n• Presence of the left atrium\n• Presence of the apex of the heart"]],"caption_candidate":"Table 3: List of quality criteria that can be automatically verified by the software","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p8-t0","doc_id":"K230365","page_num":8,"bbox":[72.28,445.51,539.6,714.34],"n_rows":7,"n_cols":5,"columns":["Items","","Predicate device 1: SonoLyst feature in","","Proposed device: Sonio Detect"],"rows":[["Items","","Predicate device 1: SonoLyst feature in","","Proposed device: Sonio Detect"],["","","Voluson SWIFT - K201828","",""],["Manufacturer\nname","GE Medical","","","Sonio"],["Device name","SonoLyst feature embedded in the device\nVoluson SWIFT","","","Sonio Detect"],["Regulation\nNumber","- Ultrasonic Pulsed Doppler Imaging System.\n21 CFR 892.1550, 90-IYN;\n-Ultrasonic Pulsed Echo Imaging System, 21\nCFR 892.1560, 90-IYO;\n-Diagnostic Ultrasound Transducer, 21 CFR\n892.1570, 90-ITX","","","- Accessory to Ultrasonic Pulsed Doppler\nImaging System, 21 CFR 892.1550\n- Accessory to Ultrasonic Pulsed Echo\nImaging System, 21 CFR 892.1560\n- Medical image management and processing\nsystem, 21 CFR 892.2050"],["Product codes","IYN (primary)\nIYO\nITX (secondary)","","","IYN (Primary)\nIYO, QIH (Secondary)"],["Clinical\noutcome","- Images labeled with correct view\n- Quality criteria are identified as “found”\nwhen detected and “not found” when not\ndetected","","","- Images labeled with correct view\n- Quality criteria are identified as “Verified”\nwhen detected and “Not verified” when not\ndetected"]],"caption_candidate":"Table 4: Comparison of technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230365-p9-t0","doc_id":"K230365","page_num":9,"bbox":[72.29,73.32,539.6,262.85],"n_rows":6,"n_cols":5,"columns":["Items","","Predicate device 1: SonoLyst feature in","","Proposed device: Sonio Detect"],"rows":[["Items","","Predicate device 1: SonoLyst feature in","","Proposed device: Sonio Detect"],["","","Voluson SWIFT - K201828","",""],["Intended\nUsers","General purpose radiology evaluation and\nspecialized for OB/GYN","","","Qualified and trained healthcare professional\npersonnel in a professional prenatal\nultrasound (US) imaging environment (this\nincludes sonographers, MFMs, OB/GYN,\nand Fetal surgeons)"],["Clinical\napplications","Fetal/Obstetrics","","","Fetal/Obstetrics"],["Algorithm\nMethodology","Artificial Intelligence","","","Artificial Intelligence\nLecture of biometrics\nColorimetry for 3D and Doppler"],["Platform","Embedded in the ultrasound equipment","","","Secure cloud-based and stand-alone software\ncompatible with ultrasound system from GE\nMedical, Samsung and Canon"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230370-p4-t0","doc_id":"K230370","page_num":4,"bbox":[108.31,444.77,503.69,509.47],"n_rows":3,"n_cols":9,"columns":["Device Name","Manufacturer","510(k) Number","","Regulation","","","Product",""],"rows":[["Device Name","Manufacturer","510(k) Number","","Regulation","","","Product",""],["","","","","Number","","","Code",""],["SpotLight Duo","Arineta Ltd.","K213465","892.1750","","","JAK","",""]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230370-p5-t0","doc_id":"K230370","page_num":5,"bbox":[54.05,511.45,553.59,691.18],"n_rows":2,"n_cols":4,"columns":["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],"rows":[["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],["Detector\ntechnology and\ngeometry","Fast scintillator array coupled to\nphotodiode array.\n33 (WFOV) or 23 (EFOV) configurable\nhigh resolution (HR) modules\ncomprising 192 detector rows X pitch\n0.5mm (Z direction, measured at\nscanner center).\n10(WFOV)-20 (EFOV) configurable low\nresolution (LR). EFOV includes 10\nmodules on each wing while WFOV\nincludes 10 modules on one wing.","Fast scintillator array coupled to\nphotodiode array.\n33 (WFOV) or 23 (EFOV) configurable\nhigh resolution (HR) modules\ncomprising 192 detector rows X pitch\n0.5mm (Z direction, measured at\nscanner center).\n10(WFOV)-20 (EFOV) configurable low\nresolution (LR). EFOV includes 10\nmodules on each wing while WFOV\nincludes 10 modules on one wing.","Same"]],"caption_candidate":"A table comparing the key features of the subject and predicate device is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230370-p6-t0","doc_id":"K230370","page_num":6,"bbox":[54.01,72.36,553.64,711.1],"n_rows":9,"n_cols":4,"columns":["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],"rows":[["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],["","comprising 48 detector rows X pitch\n2.0mm\nAnalog to digital conversion per channel\non the detection module.\n1D antiscatter collimator.","comprising 48 detector rows X pitch\n2.0mm\nAnalog to digital conversion per channel\non the detection module.\n1D antiscatter collimator.",""],["Data\ntransmission\nfrom rotor","Contactless transmission (capacitive\ncoupling).\nRate up to 6.25 GBit/sec","Contactless transmission (capacitive\ncoupling).\nRate up to 6.25 GBit/sec","Same"],["Power and\ncontrol\ntransmission to\nrotor","Contact less transmission","Contact less transmission","Same"],["Rotation drive","Direct drive DC motor","Direct drive DC motor","Same"],["X Ray source","2 x MCS 2093 X ray tubes by Varex\nImaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in\nX direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","2 x MCS 2093 X ray tubes by Varex\nImaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in\nX direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","Same"],["Patient table","Motorized vertical and horizontal motion\nOptional lateral motion\nCantilever carbon fiber patient cradle","Motorized vertical and horizontal motion\nOptional lateral motion\nCantilever carbon fiber patient cradle.","Same"],["Image\nreconstruction\nhardware","Multicore PC and GPU","Multicore PC and GPU","Same"],["Image\nreconstruction\nalgorithm","Modified FDK cone beam algorithm\nadapted for dual tubes geometry.\nAdaptive filter to reduce directional\nnoise in low level raw data (MBAF).\nNoise reduction algorithms:\nASIR-CV or DLIR AI based image\nreconstruction algorithm (DLIR only for\n250mm FOV and EFOV configuration).","Modified FDK cone beam algorithm\nadapted for dual tubes geometry.\nAdaptive filter to reduce directional\nnoise in low level raw data (MBAF)\nIterative reconstruction algorithm (ASIR-\nCV) to reduce image noise.\nFor WFOV configuration, adapted to\nreconstruct high resolution images\naccording to detector configuration,","Both devices\ninclude ASiR-CV,\nwhile the\nproposed device\nincludes DLIR as\nan alternative\nnoise reduction\nalgorithm. DLIR\ncan be applied to\n250mm FOV and\nEFOV\nconfiguration."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230370-p7-t0","doc_id":"K230370","page_num":7,"bbox":[54.02,72.36,553.63,712.18],"n_rows":5,"n_cols":4,"columns":["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],"rows":[["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],["","For WFOV configuration, adapted to\nreconstruct high resolution images\naccording to detector configuration,\nlower resolution images outside FOV\ncovered by high resolution detectors.\nFor extended FOV configuration,\nadapted to reconstruct high resolution\nimages up to FOV250mm, lower\nresolution images outside FOV250mm.","lower resolution images outside FOV\ncovered by high resolution detectors.\nFor extended FOV configuration,\nadapted to reconstruct high resolution\nimages up to FOV250mm, lower\nresolution images outside FOV250mm.","The SpotLight\nwith DLIR\ndemonstrates the\nproduct\nperformance\nclaims (LCD,\nNoise, High\ncontrast, Spatial\nresolution, NPS,\naccuracy and\nuniformity), as\ndid the SpotLight\nwith ASiR CV."],["Construction\nMaterials","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and\nelectronic cables components\nTable top made of carbon fiber\nreinforced resin\nCovers made pf molded polymers and\nreinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4\nand Gadolinium Oxysulfide (GOS) used\nin other legally marketed CT scanners","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and\nelectronic cables components\nTable top made of carbon fiber\nreinforced resin\nCovers made pf molded polymers and\nreinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4\nand Gadolinium Oxysulfide (GOS) used\nin other legally marketed CT scanners","Same"],["Energy sources","Walt supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes)\n72kW\nLaser alignment lights: gantry bore\nexternal lasers. <0.1mW per laser\nbeam.\nThree lead ECG trigger module,\npowered by medical grade power supply\nthrough the system PDU.","Wall supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes)\n72kW\nLaser alignment lights: gantry bore\nexternal lasers. <0.1mW per laser beam\nThree lead ECG trigger module,\npowered by medical grade power\nsupply through the system PDU","Same"],["Accessories","Head& hands and knees support\nOptional operator desk (the site may\nuse their own desk) carrying the display\nmonitor, keyboard, mouse, scan\noperation unit and optional accessories\nBarcode reader\nExternal Console UPS","Head& hands and knees support\nOptional operator desk (the site may\nuse their own desk) carrying the display\nmonitor, keyboard, mouse, scan\noperation unit and optional accessories\nBarcode reader\nExternal Console UPS","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230370-p8-t0","doc_id":"K230370","page_num":8,"bbox":[54.01,72.36,553.64,695.02],"n_rows":9,"n_cols":4,"columns":["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],"rows":[["Technological\ncharacteristics","Proposed device - SpotLight /\nSpotLight Duo (with DLIR option)","Predicate Device – SpotLight Duo\n(K213465)","Discussion"],["Software","The SpotLight is provided with software\nin three domains:\n• Console software\n• Image reconstruction software,\nincluding the DLIR algorithm\n• Embedded software","The SpotLight Duo is provided with\nsoftware in three domains:\n• Console software\n• Image reconstruction software\n• Embedded software","Substantially the\nsame: the\nsoftware principal\nblock diagram is\nthe same, where\nthe DLIR option\nis a software\nsub-system\nintegrated in the\nexisting image\nreconstruction\nchain of\nSpotLight\nDuo/CardioGrap\nhe as alternative\nto current the\nASIR-CV noise\nreduction\nalgorithm."],["Max Rotation\nspeed","250 RPM (0.24 sec per rotation)","250 RPM (0.24 sec per rotation)","Same"],["Min scan time","0.16 sec (partial), 0.24 sec (full scan) –\nFOV up to 250mm\n0.24 sec (full scan) – HR imaging at\nFOV above 250mm for asymmetric\ndetector","0.16 sec (partial), 0.24 sec (full scan) –\nFOV up to 250mm\n0.24 sec (full scan) – HR imaging at\nFOV above 250mm for asymmetric\ndetector","Same"],["Max axial\ncoverage in a\nsingle axial\nscan","140mm (280 slices x 0.5mm pitch)","140mm (280 slices x 0.5mm pitch)","Same"],["Field of View\n(FOV)","25cm - 250mm at high resolution, with\nDLIR option\nEFOV – up to 450mm with lower\nresolution outside FOV 250mm, with\nDLIR option\nWFOV - high resolution images at\nconfigurable FOV between 250mm and\n450mm","25cm - 250mm at high resolution\nEFOV – up to 450mm with lower\nresolution outside FOV 250mm\nWFOV - high resolution images at\nconfigurable FOV between 250mm and\n450mm","Same as\npredicate device,\nexcept DLIR as\noptional\nreconstruction for\n25cm and EFOV\nconfigurations"],["Max spatial\nresolution","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above\n125mm (outside FOV 250mm) covered\nby HR detectors\n7.0 lp/cm cutoff at radius above 125mm\n(outside FOV 250mm) covered by LR\ndetectors","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above\n125mm (outside FOV 250mm) covered\nby HR detectors\n7.0 lp/cm cutoff at radius above 125mm\n(outside FOV 250mm) covered by LR\ndetectors","Same"],["Bore size","60 cm","60 cm","Same"],["Max Patient\nweight","227 Kg (500 lbs)","227 Kg (500 lbs)","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230497-p4-t0","doc_id":"K230497","page_num":4,"bbox":[86.25,151.04,452.47,691.34],"n_rows":54,"n_cols":2,"columns":["510(k)Sponsor","ExoImaging"],"rows":[["510(k)Sponsor","ExoImaging"],["",""],["Address","4201BurtonDrive"],["","SantaClara,CA95054"],["",""],["CorrespondencePerson","JacquelineMurray"],["",""],["ContactInformation","jmurray@exo.inc"],["",""],["","Cell:+236838-5056"],["",""],["DatePrepared","February23,2023"],["",""],["ProposedDevice",""],["",""],["ProprietaryName","BladderAI(AIBV01)"],["",""],["CommonName","ExoBladderAI"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["PredicateDevice",""],["",""],["ProprietaryName","MEDO-Thyroid"],["",""],["PremarketNotification","K203502"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["ReferenceDevice",""],["",""],["ProprietaryName","LVivoBladder"],["",""],["PremarketNotification","K200232"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"]],"caption_candidate":"510(k)Sponsor ExoImaging","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230497-p4-t1","doc_id":"K230497","page_num":4,"bbox":[85.5,298.29,534.5,406.29],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","BladderAI(AIBV01)"],"rows":[["ProprietaryName","BladderAI(AIBV01)"],["CommonName","ExoBladderAI"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ProposedDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230497-p4-t2","doc_id":"K230497","page_num":4,"bbox":[85.5,443.27,534.5,551.27],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","MEDO-Thyroid"],"rows":[["ProprietaryName","MEDO-Thyroid"],["PremarketNotification","K203502"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"PredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230497-p4-t3","doc_id":"K230497","page_num":4,"bbox":[85.5,587.74,534.5,695.74],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","LVivoBladder"],"rows":[["ProprietaryName","LVivoBladder"],["PremarketNotification","K200232"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ReferenceDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230497-p5-t0","doc_id":"K230497","page_num":5,"bbox":[72.25,631.3,539.37,693.5],"n_rows":2,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nBladderAI(K230497)","PredicateDevice\nMEDO-Thyroid(K203502)","ReferenceDevice\nLVivoBladder(K200232)"],"rows":[["Feature/\nFunction","SubjectDevice\nBladderAI(K230497)","PredicateDevice\nMEDO-Thyroid(K203502)","ReferenceDevice\nLVivoBladder(K200232)"],["Imageinput","ComplieswithDICOM\nStandard","ComplieswithDICOM\nStandard","ComplieswithDICOM\nStandard"]],"caption_candidate":"ComparisonofTechnologicalCharacteristicswiththePredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230497-p6-t0","doc_id":"K230497","page_num":6,"bbox":[72.33,72.1,539.42,542.5],"n_rows":13,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nBladderAI(K230497)","PredicateDevice\nMEDO-Thyroid(K203502)","ReferenceDevice\nLVivoBladder(K200232)"],"rows":[["Feature/\nFunction","SubjectDevice\nBladderAI(K230497)","PredicateDevice\nMEDO-Thyroid(K203502)","ReferenceDevice\nLVivoBladder(K200232)"],["Scantype","SingleandMulti-frame\nimages","SingleandMulti-frame\nimages","Single-frameimages"],["Imagedisplay\nmode","Static","Static","Static"],["Imagenavigation\nandmanipulation\ntools","Slice-scroll,panelayout,\nreset","Slice-scroll,panelayout,\nreset","Slice-scroll,panelayout,\nreset"],["Imagereview","Yes,capableofreviewingall\nframesofmulti-frame\n(multi-slice)images","Yes,capableofreviewing\nallframesofmulti-frame\n(multi-slice)images","Yes,capableofreviewing\nimages"],["Manuallandmark\nplacement","Yes","Yes","Yes"],["Semi-automatic\nlandmark\nplacement","Yes,user-modifiable","Yes,user-modifiable","Yes,user-modifiable"],["Quantitative\nanalysis","Distance,Volume","Distance,Volume","Distance,Volume"],["Reportcreation","Yes","Yes","Yes"],["DisplayCalipers","Yes","Yes","Yes"],["Frame","TransverseandSagittal\nViews","TransverseandSagittal\nViews","TransverseandSagittal\nViews"],["OperatingSystem","Webbrowser(Google\nChrome)","Webbrowser(Google\nChrome)","Webbrowser(Google\nChrome)andAndroid"],["Algorithm","Imagesegmentationfor\nborderdetection","Imagesegmentationfor\nborderdetection","Imagesegmentationfor\nborderdetection"]],"caption_candidate":"510(k)Summary-BladderAI","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K230534-p4-t0","doc_id":"K230534","page_num":4,"bbox":[71.98,571.55,539.37,650.0],"n_rows":6,"n_cols":2,"columns":["","The diameter marking is not intended to be a final output, but serves the purpose of"],"rows":[["","The diameter marking is not intended to be a final output, but serves the purpose of"],["visualization and measurement. The original, unmarked series remains available in the PACS as",""],["well. The preview image presents an unofficial and not final measurement, and the user is instructed",""],["to review the full image and any other clinical information before making a clinical decision. The",""],["image includes a disclaimer: “Not for diagnostic use. The measurement is unofficial, not final, and",""],["must be reviewed by a radiologist.”",""]],"caption_candidate":"The BriefCase-Quantification produces a preview image annotated with the maximum axial diameter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p6-t0","doc_id":"K230534","page_num":6,"bbox":[72.35,96.34,540.2,711.15],"n_rows":2,"n_cols":4,"columns":["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],"rows":[["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],["Intended Use /\nIndications for Use","The Viz RV/LV\nSoftware device is\ndesigned to measure\nthe maximal\ndiameters of the right\nand left ventricles of\nthe heart from a\nvolumetric CTPA\nacquisition and report\nthe ratio of those\nmeasurements. Viz\nRV/LV analyzes cases\nusing an artificial\nintelligence algorithm\nto identify the location\nand measurements of\nthe ventricles. The Viz\nRV/LV software\nprovides the user with\nannotated images\nshowing ventricular\nmeasurements. Its\nresults are not\nintended to be used\non a stand-alone\nbasis for clinical\ndecision-making or\notherwise preclude\nclinical assessment of\nCTPA cases.","AI-Rad Companion\n(Cardiovascular) is\nimage processing\nsoftware that provides\nquantitative and\nqualitative analysis\nfrom previously\nacquired Computed\nTomography DICOM\nimages to support\nradiologists and\nphysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice in the\nevaluation and\nassessment of\ncardiovascular\ndiseases.\nIt provides the\nfollowing functionality:\n• Segmentation and\nvolume measurement\nof the heart\n• Quantification of the\ntotal calcium volume\nin the coronary\narteries\n• Segmentation of the\naorta\n• Measurement of\nmaximum diameters\nof the aorta at typical\nlandmarks","BriefCase-Quantificati\non is a radiological\nimage management\nand processing\nsystem software\nindicated for use in\nthe analysis of CT\nexams with contrast,\nthat include the\nabdominal aorta, in\nadults or transitional\nadolescents aged 18\nand older.\nThe device is\nintended to assist\nappropriately trained\nmedical specialists by\nproviding the user\nwith the maximum\nabdominal aortic axial\ndiameter of cases that\nincludes the\nabdominal aorta\n(M-AbdAo).\nBriefCase-Quantificati\non is indicated to\nevaluate normal and\naneurysmal\nabdominal aortas and\nis not intended to\nevaluate\npost-operative aortas.\nThe\nBriefCase-Quantificati\non results are not"]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p7-t0","doc_id":"K230534","page_num":7,"bbox":[72.35,72.35,540.2,687.16],"n_rows":4,"n_cols":4,"columns":["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],"rows":[["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],["","","• Threshold-based\nhighlighting of\nenlarged diameters\nThe software has\nbeen validated for\nnon-cardiac chest CT\ndata with filtered\nbackprojection\nreconstruction from\nSiemens\nHealthineers, GE\nHealthcare, Philips,\nand Toshiba/Canon.\nAdditionally, the\ncalcium detection\nfeature has been\nvalidated on\nnon-cardiac chest CT\ndata with iterative\nreconstruction from\nSiemens\nHealthineers.\nOnly DICOM images\nof adult patients are\nconsidered to be valid\ninput.","intended to be used\non a stand-alone\nbasis for clinical\ndecision-making or\notherwise preclude\nclinical assessment of\ncases. These\nmeasurements are\nunofficial, are not final,\nand are subject to\nchange after review\nby a radiologist. For\nfinal clinically\napproved\nmeasurements,\nplease refer to the\nofficial radiology\nreport. Clinicians are\nresponsible for\nviewing full images\nper the standard of\ncare."],["User population","Thoracic radiologists,\ngeneral radiologists,\npulmonologists,\ncardiologists, or other\nsimilar physicians","Radiologists and\nphysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice","Appropriately trained\nmedical specialists"],["Anatomical region of\ninterest","Left and right\nventricles of the heart","Heart, coronary\narteries and aorta","Abdominal aorta"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p8-t0","doc_id":"K230534","page_num":8,"bbox":[72.36,72.38,540.29,601.11],"n_rows":7,"n_cols":4,"columns":["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],"rows":[["","Predicate Device Viz\nRV/LV (K221100)","Reference Device\nAI-Rad Companion\n(Cardiovascular)\n(K183268)","Subject Device\nAidoc\nBriefCase-Quantifica\ntion of the\nAbdominal Aortic\nMeasurement\n(M-AbdAo)"],["Data acquisition\nprotocol","non-gated CTPA","non-cardiac chest CT","CT exams with\ncontrast that include\nthe abdominal aorta"],["Diameter\nMeasurement","Yes","Yes","Yes"],["Images\nformat","DICOM","DICOM","DICOM"],["Interference with\nstandard workflow","No","No","No"],["Algorithm","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images."],["Structure","- Viz RV/LV is hosted\non Viz.ai’s Backend\nServer and analyzes\napplicable CTPA\nscans.\n- The results are\nexported in DICOM\nformat are sent to a\nPACS destination for\nreview by physicians\nto assist in the\nassessment.","- AI-Rad Companion\n(Cardiovascular) is a\nsoftware only image\npost-processing\napplication.","-BriefCase-Quantificat\nion, is hosted on a\ncloud server, analyzes\napplicable CT images\nthat are acquired on\nCT scanner that are\nforwarded to\nBriefCase-Quantificati\non.\n- The results of the\nanalysis are exported\nin DICOM format, and\nare sent to a PACS\ndestination for review\nby medical specialists,\nto assist in the\nmeasurement of the\nabdominal aorta."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p9-t0","doc_id":"K230534","page_num":9,"bbox":[130.83,314.52,481.53,360.71],"n_rows":2,"n_cols":7,"columns":["","Mean","Std","Min","Median","Max","N"],"rows":[["","Mean","Std","Min","Median","Max","N"],["Age\n(Years)","66.8","14.8","25","69","90","160"]],"caption_candidate":"Table 2. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p9-t1","doc_id":"K230534","page_num":9,"bbox":[232.05,387.25,379.5,455.38],"n_rows":3,"n_cols":3,"columns":["Gender","N*","%"],"rows":[["Gender","N*","%"],["Male","94","58.8%"],["Female","64","40.0%"]],"caption_candidate":"Table 3. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230534-p9-t2","doc_id":"K230534","page_num":9,"bbox":[226.05,507.21,385.53,680.6],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["Siemens","52","32.5%"],["GE","46","28.8%"],["Philips","39","24.4%"],["Toshiba","23","14.4%"],["Total","160","100%"]],"caption_candidate":"Table 4. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230552-p4-t0","doc_id":"K230552","page_num":4,"bbox":[71.1,440.46,365.88,550.74],"n_rows":8,"n_cols":2,"columns":["Product name","Olea Sphere V3.0"],"rows":[["Product name","Olea Sphere V3.0"],["510(k) number","K152602"],["Trend name","Olea Sphere V3.0"],["Classification name","System, image processing, radiological"],["Classification panel","Radiology"],["CFR code","21 CFR 892.2050"],["Classification","Class II"],["Product code","LLZ"]],"caption_candidate":"Predicate Device: Olea Sphere V3.0 (K152602)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230552-p4-t1","doc_id":"K230552","page_num":4,"bbox":[71.1,604.38,365.88,714.66],"n_rows":8,"n_cols":2,"columns":["Product name","MR Diffusion Perfusion Mismatch V1.0"],"rows":[["Product name","MR Diffusion Perfusion Mismatch V1.0"],["510(k) number","K223502"],["Trend name","MR Diffusion Perfusion Mismatch V1.0"],["Classification name","System, image processing, radiological"],["Classification panel","Radiology"],["CFR code","21 CFR 892.2050"],["Classification","Class II"],["Product code","LLZ"]],"caption_candidate":"Reference Device: MR Diffusion Perfusion Mismatch V1.0 (K223502)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230575-p5-t0","doc_id":"K230575","page_num":5,"bbox":[85.58,391.85,551.74,499.75],"n_rows":3,"n_cols":4,"columns":["","Limbus Contour v1.7","Limbus Contour v1.1 -\nK201232","Similarities /\nDifferences"],"rows":[["","Limbus Contour v1.7","Limbus Contour v1.1 -\nK201232","Similarities /\nDifferences"],["Classification\nRegulation","892.2050 – Picture\nArchiving and\nCommunication System","892.2050 – Picture\nArchiving and\nCommunication System","Same"],["Product Code","LLZ","LLZ","Same"]],"caption_candidate":"an automatic contouring test to ensure the contours were accurate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230575-p7-t0","doc_id":"K230575","page_num":7,"bbox":[85.58,72.48,551.38,687.94],"n_rows":4,"n_cols":4,"columns":["","Limbus Contour is not\nintended for use with\ndigital\nmammography.","Limbus Contour is not\nintended for use with\ndigital mammography.","Same"],"rows":[["","Limbus Contour is not\nintended for use with\ndigital\nmammography.","Limbus Contour is not\nintended for use with\ndigital mammography.","Same"],["Intended User","Healthcare providers","Healthcare providers","Same"],["Contouring\nModes","Automatic","Automatic","Same"],["Measurements","No measurement\nfunction.","No measurement\nfunction.","Same."]],"caption_candidate":"Limbus AI K230575 Limbus Contour 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230575-p8-t0","doc_id":"K230575","page_num":8,"bbox":[85.58,72.48,551.38,635.62],"n_rows":5,"n_cols":4,"columns":["Image Fusion","No fusion support.","No fusion support.","Same"],"rows":[["Image Fusion","No fusion support.","No fusion support.","Same"],["3D image\nrendering","No image rendering\nfunction.","No image rendering\nfunction.","Same"],["Image\nModalities","CT and MR","CT and MR","Same"],["Platform","Stand-alone package\nwhich operates on\nMicrosoft\nWindows operating\nsystem operating\nsystem","Stand-alone package\nwhich operates on\nMicrosoft\nWindows operating\nsystem and MacOS\noperating system","Limbus\nContour v1.7\ndoes not\nsupport\nMacOS\noperating\nsystem"],["Environment\nof Use","Healthcare environment","Healthcare environment","Same"]],"caption_candidate":"Limbus AI K230575 Limbus Contour 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230575-p9-t0","doc_id":"K230575","page_num":9,"bbox":[85.58,72.48,551.38,732.1],"n_rows":4,"n_cols":4,"columns":["Materials","N/A – Standalone\nSoftware","N/A – Standalone\nSoftware","Same"],"rows":[["Materials","N/A – Standalone\nSoftware","N/A – Standalone\nSoftware","Same"],["Energy Source","N/A – Standalone\nSoftware","N/A – Standalone\nSoftware","Same"],["Feature\nComparison:\n• Operating\nSystem\n• Hardware\nRequirements\n• Etc.","Operating System\n• Windows 10 /\nWindows Server\n2016 and Above\nHardware Requirements\n• 2 GHz or faster multi-\ncore processor\n• 8 GB of RAM\n• For GPU versions, a\nCUDA capable\nNVIDIA GPU is\nrequired","Operating System\n• Windows 10 /\nWindows Server\n2016\n• Mac OS 10.14\nHardware Requirements\n• 2 GHz or faster multi-\ncore processor\n• 4 GB of RAM\n• For GPU versions, a\nCUDA capable\nNVIDIA GPU is\nrequired","Limbus\nContour v1.7\ndoes not\nsupport\nMacOS\noperating\nsystem.\nRAM\nrequirements\nare increased\nto 8GB in\nLimbus\nContour v1.7"],["Performance\nTesting","Two different types of\nverification testing\nwere\nconducted to verify the\nsoftware requirements:\nManual and Automated.\nAll tests passed,\ndemonstrating that the\nsoftware performance\nis in accordance with\nthe stated software\nrequirements.\nValidation testing of\nthe\nfollowing functions of the\nLimbus Contour\napplication\ndemonstrated that the","Two different types of\nverification testing were\nconducted to verify the\nsoftware requirements:\nManual and Automated.\nAll tests passed,\ndemonstrating that the\nsoftware performance is\nin accordance with the\nstated software\nrequirements.\nValidation testing of the\nfollowing functions of the\nLimbus Contour\napplication demonstrated\nthat the software meets\nuser needs and intended\nuses and to support","Same"]],"caption_candidate":"Limbus AI K230575 Limbus Contour 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230575-p10-t0","doc_id":"K230575","page_num":10,"bbox":[96.38,79.14,527.4,721.93],"n_rows":51,"n_cols":5,"columns":["","software meets user","","substantial equivalence:",""],"rows":[["","software meets user","","substantial equivalence:",""],["","needs and intended","","• Automatic",""],["","uses and to support","","Contouring –",""],["","substantial equivalence:","","Validation Test",""],["","• Automatic","","",""],["","Contouring –","","",""],["","Validation Test","","",""],["","","","",""],["Structures","A_Aorta","A","_Aorta","Limbus"],["available for","A_Aorta_I","B","ladder","Contour"],["automatic","A_Celiac","B","rain","v1.7.0"],["contouring","A_LAD","B","rainStem","contains n"],["","A_Mesenteric_S","L","N_Neck_L","structures"],["","A_Pulmonary","L","N_Neck_R","automatic"],["","Bag_Bowel","E","sophagus","contouring"],["","","","",""],["","Bag_Bowel_Extend","F","emur_Head_L",""],["","Bag_Bowel_Full","F","emur_Head_R",""],["","Bag_Bowel_S","G","lobe_L",""],["","Bladder","G","lobe_R",""],["","Bladder","H","eart",""],["","Body","G","lnd_Lacrimal_L",""],["","Bone_Hyoid","G","lnd_Lacrimal_R",""],["","Bone_Ilium","L","ens_L",""],["","Bone_Ilium_L","L","ens_R",""],["","Bone_Ilium_R","L","ung_L",""],["","Bone_Mandible","L","ung_R",""],["","Bowel","M","andible",""],["","Bowel_Extend","O","pticNrv_L",""],["","Bowel_Full","O","pticNrv_R",""],["","Bowel_S","P","arotid_L",""],["","BrachialPlex_L","P","arotid_R",""],["","BrachialPlex_R","P","rostate",""],["","BrachialPlexs","R","ectum",""],["","Brain","G","lnd_Submand_L",""],["","Brainstem","G","lnd_Submand_R",""],["","Brainstem","S","pinalCord",""],["","Breast_L","T","rachea",""],["","Breast_R","","",""],["","Breasts","","",""],["","Bronchus","","",""],["","Canal_Anal","","",""],["","CaudaEquina","","",""],["","Cavity_Oral","","",""],["","Chestwall","","",""],["","Chestwall_L","","",""],["","Chestwall_R","","",""],["","Clavicle_L","","",""],["","Clavicle_R","","",""],["","Cochlea_L","","",""],["","Cochlea_R","","",""]],"caption_candidate":"software meets user substantial equivalence:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230685-p5-t0","doc_id":"K230685","page_num":5,"bbox":[72.0,75.27,540.0,756.14],"n_rows":19,"n_cols":2,"columns":["Table of Contents",""],"rows":[["Table of Contents",""],["",""],["5.1. Submitter’s Information","3"],["",""],["5.2. Device Information","3"],["",""],["5.3. Predicate Device Information","4"],["",""],["5.4. Device Description","4"],["",""],["5.5. Indications for Use","4"],["",""],["5.6. Technological Characteristics","4"],["",""],["5.7. Discussion of differences","10"],["",""],["5.9. Conclusion","25"],["",""],["Radformation, Inc. 510(k) Submission 2 of 25",""]],"caption_candidate":"Table of Contents","well_formed":true,"extraction_settings":"text"}
{"table_id":"K230685-p6-t0","doc_id":"K230685","page_num":6,"bbox":[72.25,147.25,540.25,396.5],"n_rows":9,"n_cols":2,"columns":["Table 1 : Submitter’s Information",""],"rows":[["Table 1 : Submitter’s Information",""],["Submitter’s Name:","Kurt Sysock"],["Company:","Radformation, Inc."],["Address:","335 Madison Avenue, 4th Floor\nNew York, NY 10017"],["Contact Person:","Alan Nelson\nChief Science Officer, Radformation"],["Phone:","518-888-5727"],["Fax:","---------"],["Email:","anelson@radformation.com"],["Date of Summary Preparation","03/09/2023"]],"caption_candidate":"5.1. Submitter’s Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p6-t1","doc_id":"K230685","page_num":6,"bbox":[72.25,472.5,540.25,684.5],"n_rows":8,"n_cols":2,"columns":["Table 2 : Device Information",""],"rows":[["Table 2 : Device Information",""],["Trade Name:","AutoContour Model RADAC V3"],["Common Name:","AutoContour, AutoContouring, AutoContour Agent,\nAutoContour Cloud Server"],["Classification Name:","Class II"],["Classification:","Medical image management and processing system"],["Regulation Number:","892.2050"],["Product Code:","QKB"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2. Device Information","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K230685-p25-t1","doc_id":"K230685","page_num":25,"bbox":[108.0,562.5,517.08,605.7],"n_rows":3,"n_cols":2,"columns":["","primarily o"],"rows":[["","primarily o"],["glioblastoma and astrocytoma patients. Images were acquired on either a GE Signa",""],["HDxT (3T) or Siemens Skyra (3T) scanner and",""]],"caption_candidate":"average of 274 training image sets and 92 testing image sets and were acquired from","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p26-t0","doc_id":"K230685","page_num":26,"bbox":[57.7,126.5,558.1,270.13],"n_rows":9,"n_cols":3,"columns":["Table 7: MR Initial Testing Dataset References","",""],"rows":[["Table 7: MR Initial Testing Dataset References","",""],["ModelGroup","DataSourceID","DataCitation"],["MRBrain","MR-Renown","Shusharina,N.,&Bortfeld,T.(2021).GliomaImageSegmentationfor"],["","","Radiotherapy:RTtargets,barrierstocancerspread,andorgansatrisk[Data"],["","","set].TheCancerImagingArchive.https://doi.org/10.7937/TCIA.T905-ZQ20"],["MRPelvis","GoldAtlasPelvis","Natarajan,S.,Priester,A.,Margolis,D.,Huang,J.,&Marks,L.(2020)."],["","","ProstateMRIandUltrasoundWithPathologyandCoordinatesofTracked"],["","","Biopsy(Prostate-MRI-US-Biopsy)[Dataset].TheCancerImagingArchive"],["","","DOI:10.7937/TCIA.2020.A61IOC1A"]],"caption_candidate":"cm, and 1.5mm slice spacing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p26-t1","doc_id":"K230685","page_num":26,"bbox":[72.03,429.62,484.5,732.67],"n_rows":13,"n_cols":6,"columns":["Table 8: MR Training Data Results for AutoContour Model RADAC V3","","","","",""],"rows":[["Table 8: MR Training Data Results for AutoContour Model RADAC V3","","","","",""],["MRModels","Size","Pass\nCriteria","DSC\n(Avg)","DSCStd\nDev(Avg)","LowerBound\n95%\nConfidence\nInterval"],["Cerebellum","Medium","0.65","0.93","0.01","0.91"],["Glnd_Prostate","Medium","0.65","0.87","0.04","0.80"],["Hypothalamus","Small","0.50","0.79","0.04","0.72"],["Hypo_True","Small","0.50","0.71","0.06","0.61"],["OpticTract_L","Small","0.50","0.72","0.08","0.59"],["OpticTract_R","Small","0.50","0.72","0.08","0.59"],["Pituitary","Small","0.50","0.75","0.11","0.57"],["Prostate","Medium","0.65","0.89","0.03","0.84"],["SeminalVes","Medium","0.65","0.74","0.13","0.53"],["Eye_L","Medium","0.65","0.90","0.10","0.74"],["Eye_R","Medium","0.65","0.90","0.10","0.74"]],"caption_candidate":"0.07 for small models.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p27-t0","doc_id":"K230685","page_num":27,"bbox":[51.1,134.0,576.7,270.69],"n_rows":8,"n_cols":3,"columns":["Table 9: MR External Clinical Dataset References","",""],"rows":[["Table 9: MR External Clinical Dataset References","",""],["ModelGroup","DataSourceID","DataCitation"],["MRBrain","MR-Renown","N/A"],["MRPelvis","GoldAtlasPelvis","Nyholm, Tufve, Stina Svensson, Sebastian Andersson, Joakim Jonsson,"],["","","Maja Sohlin, Christian Gustafsson, Elisabeth Kjellén, et al. 2018. “MR"],["","","and CT Data with Multi Observer Delineations of Organs in the Pelvic"],["","","Area - Part of the Gold Atlas Project.” Medical Physics 12 (10): 3218–21."],["","","doi:10.1002/mp.12748."]],"caption_candidate":"accuracy of the models on image sets acquired that were unique to the training datasets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p27-t1","doc_id":"K230685","page_num":27,"bbox":[108.0,282.0,540.0,564.0],"n_rows":20,"n_cols":3,"columns":["For the Brain models, datasets acquired via data-use agreement from a clinical","",""],"rows":[["For the Brain models, datasets acquired via data-use agreement from a clinical","",""],["partner were acquired containing 20 MR T1 Ax post (BRAVO) image scans acquired with","",""],["a GE MR750w scanner. Images had an average slice thickness of 1.6mm, In-plane","",""],["resolution between 0.94 mm, and acquisition parameters of TR=5.98ms, TE=96.8s. Data","",""],["for testing of the MR Pelvis structure models were acquired from a publicly available","",""],["Gold Atlas Data set which contained 19 images of patients with prostate or rectal cancer.","",""],["Images were acquired on a GE DISCOVERY MR750w (Ax T2 FRFSE) with in-plane","",""],["resolution of 0.9mm, Slice thickness of 2.5mm, TR=5.988s and TE=96.8ms.","",""],["DSC values were calculated between ground truth contour data and AutoContour","",""],["structures and rated on the same DSC passing criteria as was used for the training DSC","",""],["validation. All structures passed the minimum DSC criteria for small and medium","",""],["structures with a mean","DSC of 0.74+/-0.07, 0.87+/-0.07 respectively:","Additionally, the"],["qualitative clinical appropriateness of AutoContour structures generated on these scans","",""],["was graded by clinical experts. Autocontour structures were graded on a scale from 1 to","",""],["5 where 5 refers to contour requiring no additional edits, and 1 refers to a score in which","",""],["full manual re-contour of the structure would be required. An average score >= 3 was","",""],["used to determine whether a structure model would ultimately be beneficial clinically. An","",""],["average rating of 4.4 was found across all MR structure models demonstrating that only","",""],["minor edits would be required in order to make the structure models acceptable for","",""],["clinical use.","",""]],"caption_candidate":"doi:10.1002/mp.12748.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230685-p28-t0","doc_id":"K230685","page_num":28,"bbox":[72.03,72.25,499.5,396.17],"n_rows":13,"n_cols":8,"columns":["Table 10: MR External Reviewer Results for AutoContour Model RADAC V3","","","","","","",""],"rows":[["Table 10: MR External Reviewer Results for AutoContour Model RADAC V3","","","","","","",""],["MRModels","Size","Pass\nCriteria","#External\nTestData\nSets","Average\nDSC","Average\nDSCStd.\nDev","Lower\nBound95%\nConfidence\nInterval","External\nReviewer\nAverage\nRating\n(1-5)"],["Cerebellum","Medium","0.65","20","0.93","0.01","0.91","4"],["Glnd_Prostate","Medium","0.65","18","0.87","0.04","0.80","4.3"],["Hypothalamus","Small","0.50","20","0.79","0.04","0.72","4.2"],["Hypo_True","Small","0.50","19","0.71","0.06","0.61","4.3"],["OpticTract_L","Small","0.50","20","0.72","0.08","0.59","4.4"],["OpticTract_R","Small","0.50","19","0.72","0.08","0.59","4.5"],["Pituitary","Small","0.50","19","0.75","0.11","0.57","4.2"],["Prostate","Medium","0.65","19","0.89","0.03","0.84","4.2"],["SeminalVes","Medium","0.65","19","0.74","0.13","0.53","4.2"],["Eye_L","Medium","0.65","19","0.90","0.10","0.74","4.9"],["Eye_R","Medium","0.65","20","0.90","0.10","0.74","4.9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230807-p6-t0","doc_id":"K230807","page_num":6,"bbox":[72.29,384.89,536.71,714.82],"n_rows":6,"n_cols":7,"columns":["Specification/\nAttribute","","Predicate Device","","","Proposed Device",""],"rows":[["Specification/\nAttribute","","Predicate Device","","","Proposed Device",""],["","","Deep Learning Image Reconstruction","","","Deep Learning Image",""],["","","(K213999)","","","Reconstruction",""],["Technology","DLIR uses a dedicated Deep Neural\nNetwork (DNN) which is trained on the\nCT scanner and therefore models the\npropagation of noise through the\nsystem to identify and remove the\nnoise","","","Same","",""],["System statistics -\nNoise modeling of\nthe data collection\nimaging chain\n(photon noise and\nelectronic noise)","Characterization of the photon\nstatistics as it propagates through the\npreprocessing and calibration imaging\nchain","","","Same","",""],["System statistics –\nNoise characteristics\nof the reconstructed\nimages","DLIR uses a trained DNN which models\nthe scanned object using information\nobtained from extensive phantom and\nclinical data to identify the noise\ncharacteristics and remove it","","","Same","",""]],"caption_candidate":"technological similarities and differences between the predicate device and the proposed device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230807-p7-t0","doc_id":"K230807","page_num":7,"bbox":[72.29,103.82,536.71,326.81],"n_rows":6,"n_cols":7,"columns":["Specification/\nAttribute","","Predicate Device","","","Proposed Device",""],"rows":[["Specification/\nAttribute","","Predicate Device","","","Proposed Device",""],["","","Deep Learning Image Reconstruction","","","Deep Learning Image",""],["","","(K213999)","","","Reconstruction",""],["Clinical Workflow","Select recon type and strength (Low,\nMedium, High).","","","Same","",""],["Reference\nprotocols/dose","Using the same reference protocols\nprovided on the Revolution CT/Apex\nplatform systems for ASiR-V","","","Using the same reference protocols\nprovided on the Revolution EVO,\nRevolution Maxima, Revolution\nAscend and Discovery CT750 HD\nfamily systems for ASiR-V","",""],["Deployment\nEnvironment","On CT Console","","","On CT Console\nOn GE’s Edison Platform.","",""]],"caption_candidate":"510(k) Premarket Notification Submission - DLIR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230854-p4-t0","doc_id":"K230854","page_num":4,"bbox":[88.56,362.88,523.44,461.76],"n_rows":8,"n_cols":2,"columns":["","Primary Predicate Device: SwiftMR – K220416 by AIRS Medical, Inc., Class II,"],"rows":[["","Primary Predicate Device: SwiftMR – K220416 by AIRS Medical, Inc., Class II,"],["","CFR 892.2050, classification with product code LLZ."],["",""],["IV.DEVICE DESCRIPTION",""],["","SwiftMR, is software used as a Medical Device (SaMD) consisting of a software"],["","algorithm that enhances images taken by MRI scanners. The device only"],["","processes DICOM images for the end User and is intended to be used by radiology"],["","technologists in an imaging center, clinic, or hospital."]],"caption_candidate":"III.PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230854-p5-t0","doc_id":"K230854","page_num":5,"bbox":[98.92,589.05,545.15,715.32],"n_rows":5,"n_cols":8,"columns":["Item","","Predicate Device","","","Subject Device","","Differences"],"rows":[["Item","","Predicate Device","","","Subject Device","","Differences"],["","","(SwiftMR (K220416))","","","(SwiftMR)","",""],["Physical\nCharacteristics","Software device that\noperates on off-the-\nshelf computer\nhardware","","","Same as predicate","","","No Difference"],["Computer","PC Compatible","","","Same as predicate","","","No Difference"],["DICOM\nStandard\nCompliance","The software processes\nDICOM-compliant\nimage data","","","Same as predicate","","","No Difference"]],"caption_candidate":"devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230854-p6-t0","doc_id":"K230854","page_num":6,"bbox":[98.91,91.65,545.15,586.2],"n_rows":7,"n_cols":8,"columns":["Item","","Predicate Device","","","Subject Device","","Differences"],"rows":[["Item","","Predicate Device","","","Subject Device","","Differences"],["","","(SwiftMR (K220416))","","","(SwiftMR)","",""],["Modalities","MRI","","","Same as predicate","","","No Difference"],["Image\nEnhancement\nAlgorithm\nDescription","SwiftMR implements an\nimage enhancement\nalgorithm using\nconvolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Neural\nnetwork-based filters\nthat perform noise\nreduction are obtained.\nThe parameters of the\nfilters were obtained\nthrough an image\nguided optimization\nprocess.\nSharpening filter is\nadditionally applied to\nthe deep learning\nprocessed image.","","","SwiftMR implements an\nimage enhancement\nalgorithm using\nconvolutional\nneural network-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Neural\nnetwork-based filters\nthat perform noise\nreduction and/or\nsharpening are\nobtained. The\nparameters of the filters\nwere obtained through\nan image guided\noptimization process.\nSharpening filter is\nadditionally applied to\nthe deep learning\nprocessed image.","","","The deep learning model also\nperforms sharpening function."],["Deep learning\nmodels","3 General sequence\nmodels\n1 TOF sequence model","","","1 model","","","The deep learning model is applied\nfor all types of images (including but\nnot limited to T1, T2, T2*, PD,\nFLAIR, DWI, MRA)."],["Supported body\nparts","Brain, Spine, knee,\nankle, shoulder, and hip","","","All body parts","","","It is expanded to all body parts."],["Workflow","The software operates\non DICOM files,\nenhances the images,\nand stores the\nenhanced images on\nPACS. Enhanced\nimages co-exist with the\noriginal images.","","","The software operates\non DICOM files,\nenhances the images,\nand stores the\nenhanced images on\nPACS or on MR device.\nEnhanced images co-\nexist with the original\nimages.","","","The enhanced images can also be\nsent to MR device not only to\nPACS."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p4-t0","doc_id":"K230899","page_num":4,"bbox":[108.3,350.6,522.98,524.4],"n_rows":6,"n_cols":2,"columns":["Name of Device:","qXR-PTX-PE"],"rows":[["Name of Device:","qXR-PTX-PE"],["Common or Usual Name:","Radiological Computer Assisted Prioritization Software for\nLesions"],["Classification Name:","Radiological Computer Aided Triage and Notification Software"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2080"],["Product Code:","QFM"]],"caption_candidate":"2 DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p4-t1","doc_id":"K230899","page_num":4,"bbox":[108.3,577.17,522.98,656.95],"n_rows":3,"n_cols":2,"columns":["Name of Device:","Lunit INSIGHT CXR Triage"],"rows":[["Name of Device:","Lunit INSIGHT CXR Triage"],["Manufacturer:","Lunit Inc."],["510(k) Number:","K211733"]],"caption_candidate":"3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p6-t0","doc_id":"K230899","page_num":6,"bbox":[72.04,95.15,529.47,754.48],"n_rows":12,"n_cols":8,"columns":["","","Predicate Device","","","","Subject Device",""],"rows":[["","","Predicate Device","","","","Subject Device",""],["","","Lunit INSIGHT CXR Triage","","","","qXR-PTX-PE",""],["Device Name","Lunit INSIGHT CXR Triage","","","","qXR-PTX-PE","",""],["510(k) Number","K211733","","","","","",""],["Regulation","21 CFR 892.2080","","","","21 CFR 892.2080","",""],["Regulation Description","Radiological computer aided\ntriage and notification software","","","","Radiological computer aided triage\nand notification software","",""],["Product Code","QFM","","","","QFM","",""],["Device type","Radiological Computer-Assisted\nPrioritization Software For Lesions","","","","Radiological Computer-Assisted\nPrioritization Software For Lesions","",""],["Manufacturer","Lunit Inc.","","","","Qure.ai Technologies","",""],["Intended use / Indications\nfor Use","Lunit INSIGHT CXR Triage is a\nradiological computer-assisted\ntriage and notification software\nthat analyzes adult chest X-ray\nimages for the presence of pre-\nspecified suspected critical\nfindings (pleural effusions and/or\npneumothorax). Lunit INSIGHT\nCXR Triage uses an artificial\nintelligence algorithm to analyze\nimages for features suggestive of\ncritical findings and produce case-\nlevel output available in the\nPACS/workstation for worklist\nprioritization or triage.\nAs a passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nLunight Insight CXR triage does\nnot send a proactive alert directly\nto appropriately trained medical\nspecialists. Lunit INSIGHT CXR\nTriage is not intended to direct\nattention to specific portions of\nan image. Its results are not\nintended to be used on a\nstandalone basis for clinical\ndecision-making.","","","","qXR-PTX-PE is a radiological\ncomputer-assisted triage and\nnotification software that analyzes\nadult chest X-ray images for the\npresence of pre-specified suspected\ncritical findings (pleural effusion\nand/or pneumothorax). qXR-PTX-PE\nuses an artificial intelligence\nalgorithm to analyze images for\nfeatures suggestive of critical findings\nand provides case-level output\navailable in the PACS/workstation for\nworklist prioritization or triage.\nAs a passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nqXR-PTX-PE does not send a proactive\nalert directly to the appropriately\ntrained medical specialists. qXR-PTX-\nPE is not intended to direct attention\nto specific portions of an image or to\nanomalies other than pleural effusion\nand/or pneumothorax. Its results are\nnot intended to be used on a stand-\nalone basis for clinical decision-\nmaking","",""],["Intended User","Appropriately trained medical\nspecialists who are qualified to\ninterpret chest radiographs.","","","","Radiologists, clinicians, and other\nappropriately trained medical\nspecialists qualified to read chest\nradiographs","",""],["Modality","Chest X-ray","","","","Chest X-ray","",""]],"caption_candidate":"Table 1 Comparison between qXR-PTX-PE and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p7-t0","doc_id":"K230899","page_num":7,"bbox":[72.04,72.4,529.47,764.48],"n_rows":9,"n_cols":8,"columns":["","","Predicate Device","","","","Subject Device",""],"rows":[["","","Predicate Device","","","","Subject Device",""],["","","Lunit INSIGHT CXR Triage","","","","qXR-PTX-PE",""],["Target clinical conditions","Pleural effusion, Pneumothorax\non Chest/Lung Frontal Chest X-ray","","","","Pneumothorax, Pleural effusion on\nChest/Lung Frontal Chest X-rays","",""],["Algorithm for pre-\nspecified critical findings\ndetection","AI algorithm designed to detect\npleural effusion and\npneumothorax in chest X-ray\nimages. Lunit INSIGHT CXR Triage\nuses a vendor agnostic algorithm\ncompatible with DICOM chest X-\nray images","","","","qXR-PTX-PE uses an AI algorithm to\ndetect pneumothorax and pleural\neffusion on chest X-ray images. qXR-\nPTX-PE uses a vendor agnostic\nalgorithm compatible with DICOM\nchest X-ray images","",""],["Notification only/Parallel\nworkflow","Yes","","","","Yes","",""],["Input format","DICOM","","","","DICOM","",""],["Device output in case of\npositive detection","When deployed on other\nradiological imaging equipment,\nLunit INSIGHT CXR Triage\nautomatically runs after image\nacquisition and prioritizes and\ndisplays the analysis result\nthrough the worklist interface of\nPACS/workstation.\nNo markup on original image.\nSecondary capture of the finding.\nUpon image acquisition from\nother radiological imaging\nequipment (e.g. X-ray systems),\nan on-device, technologist\nnotification indicating which cases\nwere flagged by Lunit INSIGHT\nCXR Triage in PACS, is generated.\nThe on device notification is\ncontextual and does not provide\nany diagnostic information. It is\nnot intended to inform any clinical\ndecision, prioritization, or action\nto the technologist","","","","When deployed on other radiological\nimaging equipment, qXR-PTX-PE will\nautomatically run after image\nacquisition to perform triage. It\ndisplays the analysis result through\nthe worklist interface of\nPACS/workstation.\nNo markup of the conditions will be\ndone on the original image.\nSecondary capture of the device will\nindicate the presence of findings\nsuspicious of pneumothorax or\npleural effusion.\nUpon image acquisition from other\nradiological imaging equipment (e.g.\nX-ray systems) a passive notification\nis generated.","",""],["Notification (i.e.,\nrecipient, timing and\nmeans of notification)","Passive notification. Images with\nsuspicion of pleural effusion\nand/or pneumothorax are flagged\nin PACS/workstation.","","","","Passive notification. Images with\nsuspicion of pneumothorax and/or\npleural effusion are flagged in\nPACS/workstation/DICOM viewer.","",""],["Where generated results\n(i.e., DICOM files) are\nstored","PACS/Workstation","","","","PACS/Workstation/DICOM viewer","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p8-t0","doc_id":"K230899","page_num":8,"bbox":[72.07,72.4,529.43,488.4],"n_rows":5,"n_cols":9,"columns":["","","","Predicate Device","","","","Subject Device",""],"rows":[["","","","Predicate Device","","","","Subject Device",""],["","","","Lunit INSIGHT CXR Triage","","","","qXR-PTX-PE",""],["","Performance metrics of the predicate device and qXR-PTX-PE","","","","","","",""],["Performance level –\nTiming of notification","","The average time taken for the\nnotification to travel from the\nLunit INSIGHT CXR Triage to the\npoint at which the result is\ndisplayed in the destination\nPACS/RIS/EPR worklist is 14.66\nseconds.","","","","The average time taken for the\nnotification to travel from qXR-PTX-\nPE to the point at which the result is\ndisplayed in the destination Picture\nArchiving and Communication System\n(PACS) or workstation/digital\nradiographic processing system (ex.\ndigital radiography, digital X-ray\nsystem etc.) is 10 seconds.","",""],["Performance level –\naccuracy of classification","","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.9686 (95% CI: [0.9547,\n0.9824])\nSensitivity 89.86% (95% CI: [86.72,\n93.00])\nSpecificity 93.48% (95% CI: [91.06,\n95.91])\nPneumothorax\nROC AUC > 0.95\nAUC: 0.9630 (95% CI: [0.9521,\n0.9739])\nSensitivity 88.92% (95% CI: [85.60,\n92.24]) Specificity 90.51% (95% CI:\n[88.18, 92.83])","","","","Pneumothorax\nROC AUC > 0.95\nAUC: 0.9894 (95% CI: [0.9829,\n0.9980])\nSensitivity 94.53% (95% CI: [90.42,\n97.24])\nSpecificity 96.36% (95% CI: [94.07,\n97.95])\nPleural Effusion\nROC AUC > 0.95\nAUC: 0.989 (95% CI: [0.9847, 0.9944])\nSensitivity 96.22% (95% CI: [93.62,\n97.97])\nSpecificity 94.90% (95% CI: [93.04,\n96.39])","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p9-t0","doc_id":"K230899","page_num":9,"bbox":[72.49,427.49,502.98,484.21],"n_rows":2,"n_cols":7,"columns":["AUC (95% CI)","","","Sensitivity (95% CI), TP/P","","Specificity (95% CI), TN/N",""],"rows":[["AUC (95% CI)","","","Sensitivity (95% CI), TP/P","","Specificity (95% CI), TN/N",""],["","98.94 (98.28 - 99.82)","","94.53 (90.42-97.24), 190/201","","96.36 (94.07-97.95), 397/412",""]],"caption_candidate":"Table 2 Overall Results of Accuracy Testing of qXR-PTX-PE for Pneumothorax","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K230899-p10-t0","doc_id":"K230899","page_num":10,"bbox":[72.49,231.96,504.48,288.27],"n_rows":2,"n_cols":7,"columns":["AUC (95% CI)","","","Sensitivity (95% CI), TP/P","","Specificity (95% CI), TN/N",""],"rows":[["AUC (95% CI)","","","Sensitivity (95% CI), TP/P","","Specificity (95% CI), TN/N",""],["","98.90 (98.47 - 99.44)","","96.22 (93.62-97.97), 331/344","","94.90(93.04- 96.39), 689/726",""]],"caption_candidate":"Table 3 Overall Results of Accuracy Testing of qXR-PTX-PE for Pleural Effusion","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p4-t0","doc_id":"K231001","page_num":4,"bbox":[66.07,150.32,539.5,326.82],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","DeepTekMedicalImagingPvtLtd"],"rows":[["510(k) Sponsor","DeepTekMedicalImagingPvtLtd"],["Address","3rd Floor,IdeastoImpact,PallodFarms 3\nBehindVijaySales,Baner\nPune,India,Maharashtra411405"],["Correspondence Person","RoryA. Carrillo\nRegulatoryConsultant\nCosm"],["Contact Information","Email:rory@cosmhq.com\nPhone:415-580-0916"],["Date Prepared","April07,2023"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p4-t1","doc_id":"K231001","page_num":4,"bbox":[72.0,157.19,392.85,678.83],"n_rows":49,"n_cols":2,"columns":["510(k) Sponsor","DeepTekMedicalImagingPvtLtd"],"rows":[["510(k) Sponsor","DeepTekMedicalImagingPvtLtd"],["",""],["Address","3rd Floor,IdeastoImpact,Pallod"],["",""],["","BehindVijaySales,Baner"],["",""],["","Pune,India,Maharashtra411405"],["",""],["Correspondence Person","RoryA. Carrillo"],["",""],["","RegulatoryConsultant"],["","Cosm"],["",""],["Contact Information","Email:rory@cosmhq.com"],["","Phone:415-580-0916"],["",""],["Date Prepared","April07,2023"],["",""],["2. Proposed Device",""],["",""],["ProprietaryName","DeepTekCXR Analyzerv1.0"],["",""],["Common Name","CXR Analyzer"],["",""],["ClassificationName","Medicalimageanalyzer"],["",""],["RegulationNumber","892.2070"],["",""],["RegulationName","Medicalimageanalyzer"],["",""],["Product Code","MYN"],["",""],["RegulatoryClass","II"],["",""],["3. Predicate Device",""],["",""],["ProprietaryName","Chest-CAD"],["",""],["PremarketNotification","K210666"],["",""],["ClassificationName","Medicalimageanalyzer"],["",""],["RegulationNumber","892.2070"],["",""],["RegulationName","Medicalimageanalyzer"],["",""],["Product Code","MYN"],["",""],["RegulatoryClass","II"]],"caption_candidate":"510(k) Sponsor DeepTekMedicalImagingPvtLtd","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231001-p4-t2","doc_id":"K231001","page_num":4,"bbox":[66.07,362.48,539.5,503.48],"n_rows":7,"n_cols":2,"columns":["ProprietaryName","DeepTekCXR Analyzerv1.0"],"rows":[["ProprietaryName","DeepTekCXR Analyzerv1.0"],["Common Name","CXR Analyzer"],["ClassificationName","Medicalimageanalyzer"],["RegulationNumber","892.2070"],["RegulationName","Medicalimageanalyzer"],["Product Code","MYN"],["RegulatoryClass","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p4-t3","doc_id":"K231001","page_num":4,"bbox":[66.07,538.72,539.5,679.72],"n_rows":7,"n_cols":2,"columns":["ProprietaryName","Chest-CAD"],"rows":[["ProprietaryName","Chest-CAD"],["PremarketNotification","K210666"],["ClassificationName","Medicalimageanalyzer"],["RegulationNumber","892.2070"],["RegulationName","Medicalimageanalyzer"],["Product Code","MYN"],["RegulatoryClass","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p6-t0","doc_id":"K231001","page_num":6,"bbox":[72.25,281.31,543.25,719.5],"n_rows":6,"n_cols":3,"columns":["Feature/\nFunction","Proposed Device\nDeepTekCXR Analyzer","PredicateDevice\nChest-CAD (K210666)"],"rows":[["Feature/\nFunction","Proposed Device\nDeepTekCXR Analyzer","PredicateDevice\nChest-CAD (K210666)"],["Indications for\nUse","The DeepTek CXR Analyzer V1.0 is\na computer-assisted detection\n(CADe) software device that\nanalyzes chest radiograph studies\nusing machine learning techniques\nto identify, categorize, and highlight\nsuspicious ROIs in one of the\nfollowing categories: Lungs, Pleura,\nCardiac, and Hardware. The device\nis intended for use as a concurrent\nreading aid for radiologists.\nDeepTek CXR Analyzer V1.0 is\nindicated for adults and transitional\nadolescents (18 to <22 years old but\ntreated like adults) only.","Chest-CAD isacomputer-assisted\ndetection(CADe) softwaredevicethat\nanalyzeschestradiographystudies\nusingmachinelearningtechniquesto\nidentify,categorize,andhighlight\nsuspiciousregionsof interest(ROI).\nAny suspiciousROI identifiedby\nChest-CAD isassignedtooneof the\nfollowingcategories:Cardiac,\nMediastinum/Hila,Lungs,\nPleura,Bones,SoftTissues,\nHardware,or Other.Thedeviceis\nintendedfor use as aconcurrent\nreadingaidfor physicians.\nChest-CAD isindicatedfor adults\nonly."],["Image\nModality","X-ray","X-ray"],["Study Type","Chest","Chest"],["Image Type","DICOM","DICOM"],["Clinical\nOutput","Identifyandmarkregionsof\ninterest(ROIs) on chestradiographs","Identifyandmarkregionsof interest\n(ROIs) onchestradiographs"]],"caption_candidate":"6. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p7-t0","doc_id":"K231001","page_num":7,"bbox":[72.33,88.58,543.33,480.5],"n_rows":9,"n_cols":3,"columns":["Feature/\nFunction","Proposed Device\nDeepTekCXRAnalyzer","PredicateDevice\nChest-CAD(K210666)"],"rows":[["Feature/\nFunction","Proposed Device\nDeepTekCXRAnalyzer","PredicateDevice\nChest-CAD(K210666)"],["Clinical\nFinding","Identified ROIsareassigned toone\nof thefollowing categories: Lungs,\nPleura,Cardiac,or Hardware","Identified ROIsareassigned tooneof\nthefollowing categories:Cardiac,\nMediastinum/Hila, Lungs, Pleura,\nBones,Soft Tissues,Hardware, or\nOther"],["Intended Users","Radiologists","Physicians"],["Intended User\nWorkflow","Device intendedfor useas areading\naidfor radiologists\ninterpreting chestradiographs","Device intendedfor useas areading\naidfor physiciansinterpreting chest\nradiographs"],["Patient\nPopulation","Adultswith ChestRadiographs","Adultswith ChestRadiographs"],["Algorithm\nMethodology","Artificial NeuralNetworks","Artificial NeuralNetworks"],["Platform","Secureon-premise processingand\ndeliveryof chestradiographs","Securecloud-based processing and\ndeliveryof chestradiographs"],["ImageSource","DigitalX-ray","DigitalX-ray"],["ImageViewing","Image displayedonPACSsystem","Image displayedonPACSsystem"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p9-t0","doc_id":"K231001","page_num":9,"bbox":[106.5,254.76,498.67,408.55],"n_rows":7,"n_cols":4,"columns":["","Image-LevelDetectionPerformance","",""],"rows":[["","Image-LevelDetectionPerformance","",""],["","Sensitivity[95%CI]","Specificity[95%CI]","AUROC[95%CI]"],["Lungs","0.903[0.887-0.914]","0.937[0.927-0.948]","0.971[0.968-0.976]"],["Pleura","0.924[0.902-0.932]","0.897[0.879-0.911]","0.964[0.954-0.970]"],["Cardiac","0.924[0.890-0.952]","0.930[0.925-0.941]","0.978[0.968-0.985]"],["Hardware","0.947[0.936-0.955]","0.947[0.939-0.954]","0.980[0.976-0.983]"],["Aggregate","0.926[0.917-0.933]","0.933[0.925-0.938]","0.974[0.970-0.977]"]],"caption_candidate":"TheDeepTekCXR Analyzer demonstratedthefollowing results for detection ofROIs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p10-t0","doc_id":"K231001","page_num":10,"bbox":[129.72,88.55,474.17,226.55],"n_rows":7,"n_cols":2,"columns":["ROI-LevelLocalizationPerformance",""],"rows":[["ROI-LevelLocalizationPerformance",""],["","wAFROC-FOM[95%CI]"],["Lungs","0.913[0.904-0.924]"],["Pleura","0.884[0.866-0.902]"],["Cardiac","0.952[0.941-0.966]"],["Hardware","0.954[0.948-0.963]"],["Aggregate","0.920[0.908-0.926]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p11-t0","doc_id":"K231001","page_num":11,"bbox":[92.38,237.64,501.17,413.5],"n_rows":7,"n_cols":3,"columns":["Category","wAFROC-FOM",""],"rows":[["Category","wAFROC-FOM",""],["","Unaided\n[95% CI]","Aided\n[95% CI]"],["Lungs","0.853 [0.820-0.887]","0.919[0.896-0.943]"],["Pleura","0.806 [0.763-0.850]","0.853[0.815-0.892]"],["Cardiac","0.825 [0.781-0.869]","0.886[0.842-0.930]"],["Hardware","0.919 [0.887-0.950]","0.952[0.931-0.973]"],["Aggregate","0.821 [0.791-0.852]","0.893[0.871-0.914]"]],"caption_candidate":"assessment.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231001-p12-t0","doc_id":"K231001","page_num":12,"bbox":[72.25,166.22,555.69,253.82],"n_rows":3,"n_cols":6,"columns":["Reader","Category","Sensitivity","","Specificity",""],"rows":[["Reader","Category","Sensitivity","","Specificity",""],["","","Unaided[95%CI]","Aided[95%CI]","Unaided[95%CI]","Aided[95%CI]"],["All\nreaders","Aggregate","0.810[0.699-0.902]","0.886[0.813-0.945]","0.911[0.804-0.972]","0.949[0.884-0.990]"]],"caption_candidate":"arepresented inTable 5.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231025-p4-t0","doc_id":"K231025","page_num":4,"bbox":[72.19,170.72,545.63,351.1],"n_rows":7,"n_cols":2,"columns":["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],"rows":[["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],["Address","Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.\nWest Dist.\nTaichung City 403020\nTAIWAN"],["Applicant","Joseph Chang"],["Contact Information","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["Correspondence Person","Ti-Hao Wang, MD"],["Contact Information","886-04-23213838 #168\ntihao.wang@everfortune.ai"],["Date Prepared","April 10, 2023"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231025-p4-t1","doc_id":"K231025","page_num":4,"bbox":[72.19,406.85,545.63,522.35],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM"],"rows":[["Proprietary Name","EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM"],["Common Name","EFAI ICHCT100"],["Classification Name","Radiological Computer-Assisted Triage And Notification\nSoftware"],["Regulation Number","21 CFR 892.2080"],["Regulation Name","Radiological Computer Aided Triage and Notification Software"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231025-p4-t2","doc_id":"K231025","page_num":4,"bbox":[72.19,578.02,545.63,696.52],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","CuraRad-ICH"],"rows":[["Proprietary Name","CuraRad-ICH"],["Premarket Notification","K192167"],["Classification Name","Radiological Computer-Assisted Triage And Notification\nSoftware"],["Regulation Number","21 CFR 892.2080"],["Regulation Name","Radiological Computer Aided Triage and Notification Software"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231025-p6-t0","doc_id":"K231025","page_num":6,"bbox":[72.12,229.03,526.69,719.53],"n_rows":7,"n_cols":3,"columns":["Company","Ever Fortune.AI Co., Ltd.\n(EFAI)","CuraCloud Corp."],"rows":[["Company","Ever Fortune.AI Co., Ltd.\n(EFAI)","CuraCloud Corp."],["Device Name","EFAI ICHCT","CuraRad-ICH"],["510k Number","K231025","K192167"],["Regulation No.","21CFR 892.2080","21CFR 892.2080"],["Classification","II","II"],["Product Code","QAS","QAS"],["Intended\nUse/Indication for\nUse","EFAI ICHCT is a software\nworkflow tool designed to aid in\nprioritizing the clinical\nassessment of adult non-contrast\nhead CT cases with features\nsuggestive of acute intracranial\nhemorrhage (ICH). EFAI\nICHCT analyzes cases using\ndeep learning algorithms to\nidentify suspected ICH findings.\nIt makes case-level output\navailable to a PACS/workstation\nfor worklist prioritization or\ntriage.\nEFAI ICHCT is not intended to\ndirect attention to specific\nportions of an image or to\nanomalies other than acute ICH.\nIts results are not intended to be\nused on a stand-alone basis for\nclinical decision-making nor is it\nintended to rule out hemorrhage\nor otherwise preclude clinical\nassessment of CT studies.","CuraRad-ICH is a software\nworkflow tool designed to aid\nin prioritizing the clinical\nassessment of adult\nnon-contrast head CT cases\nwith features suggestive of\nacute intracranial hemorrhage.\nCuraRad-ICH analyzes cases\nusing deep learning algorithms\nto identify suspected ICH\nfindings. It makes case-level\noutput available to a\nPACS/workstation for worklist\nprioritization or triage.\nCuraRad-ICH is not intended to\ndirect attention to specific\nportions of an image or to\nanomalies other than acute ICH.\nIts results are not intended to be\nused on a stand-alone basis for\nclinical decision-making nor is\nit intended to rule out\nhemorrhage or otherwise\npreclude clinical assessment of\nCT studies."]],"caption_candidate":"Table - Comparison with the Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231025-p7-t0","doc_id":"K231025","page_num":7,"bbox":[72.19,112.27,526.88,552.89],"n_rows":11,"n_cols":3,"columns":["Population","Adult patients indicated for\nnon-contrast head CT","Adult patients indicated for\nnon-contrast head CT"],"rows":[["Population","Adult patients indicated for\nnon-contrast head CT","Adult patients indicated for\nnon-contrast head CT"],["Intended Clinical\nEnd User","Radiologists/Trained Clinicians","Radiologists/Trained Clinicians"],["AI Used","Yes","Yes"],["Data Acquisition","Acquires medical image data\nfrom DICOM compliant\nimaging devices and modalities.","Acquires medical image data\nfrom DICOM compliant\nimaging devices and modalities."],["Input Image\nModality","Non-contrast Head CT","Non-contrast Head CT"],["Non-Diagnostic\nPreview","No","No"],["Clinical condition","Acute Intracranial Hemorrhage","Acute Intracranial Hemorrhage"],["Independent of\nstandard of care\nworkflow","Yes; No cases are removed from\nworklist","Yes; No cases are removed\nfrom worklist"],["Output","Suspected ICH (Yes or No)","Suspected ICH (Yes or No)"],["Results Receiver","PACS / Workstation","PACS / Workstation"],["Performance\nResults","Sensitivity: 0.947\n(95% CI: 0.895 - 0.974)\nSpecificity: 0.949\n(95% CI: 0.902 - 0.974)\nProcessing time: 34.96 seconds\n(95% CI: 33.89 - 36.03 seconds)","Sensitivity: 0.906\n(95% CI: 0.859 - 0.942)\nSpecificity: 0.931\n(95% CI: 0.883 - 0.964)\nProcessing time: 43 seconds\n(95% CI: 39 - 46 seconds)"]],"caption_candidate":"F.RTUNE Al","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231094-p5-t0","doc_id":"K231094","page_num":5,"bbox":[62.34,88.79,290.74,574.19],"n_rows":34,"n_cols":2,"columns":["(cid:24)(cid:20)(cid:19)(cid:11)(cid:78)(cid:12) (cid:54)(cid:88)(cid:80)(cid:80)(cid:68)","(cid:85)(cid:92)"],"rows":[["(cid:24)(cid:20)(cid:19)(cid:11)(cid:78)(cid:12) (cid:54)(cid:88)(cid:80)(cid:80)(cid:68)","(cid:85)(cid:92)"],["",""],["",""],["I. SUBMITTE","R"],["",""],["Company Name","Annalise-AIPty Ltd"],["Address","Level P,24Campbell"],["","Sydney, NSW2000"],["","Australia"],["Phone Number","+61 1800-958487"],["Contact Person","Haylee Bosshard"],["Date Prepared","July 7,2023"],["",""],["II. SUBJECT D","EVICE"],["",""],["Manufacturer Name","Annalise-AIPty Ltd"],["Device Name","Annalise Enterprise C"],["ClassificationName","Radiologicalcomputer"],["","(21CFR892.2080)"],["RegulatoryClass","II"],["Product Code","QAS"],["",""],["III. PREDICAT","E DEVICE"],["",""],["Manufacturer Name","Aidoc Medical, Ltd."],["Device Name","BriefCase"],["510(k) reference","K221314"],["ClassificationName","Radiologicalcomputer"],["","(21CFR892.2080)"],["RegulatoryClass","II"],["Product Code","QAS"],["",""],["This predicate has not b","een subject to a design"],["submission.",""]],"caption_candidate":"(cid:24)(cid:20)(cid:19)(cid:11)(cid:78)(cid:12) (cid:54)(cid:88)(cid:80)(cid:80)(cid:68)(cid:85)(cid:92)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231094-p5-t1","doc_id":"K231094","page_num":5,"bbox":[62.68,154.67,530.14,253.56],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AIPty Ltd"],"rows":[["","Company Name","","Annalise-AIPty Ltd"],["Address","Address","","Level P,24Campbell Street\nSydney, NSW2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","July 7,2023"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231094-p5-t2","doc_id":"K231094","page_num":5,"bbox":[62.68,300.65,530.14,385.74],"n_rows":5,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AIPty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AIPty Ltd"],["","Device Name","","Annalise Enterprise CTBTriage (cid:177)OH"],["ClassificationName","ClassificationName","","Radiologicalcomputer aided triage andnotificationsoftware\n(21CFR892.2080)"],["","RegulatoryClass","","II"],["","Product Code","","QAS"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231094-p5-t3","doc_id":"K231094","page_num":5,"bbox":[62.68,432.88,530.14,532.26],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Aidoc Medical, Ltd."],"rows":[["","Manufacturer Name","","Aidoc Medical, Ltd."],["","Device Name","","BriefCase"],["","510(k) reference","","K221314"],["ClassificationName","ClassificationName","","Radiologicalcomputer aided triage andnotificationsoftware\n(21CFR892.2080)"],["","RegulatoryClass","","II"],["","Product Code","","QAS"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231094-p10-t0","doc_id":"K231094","page_num":10,"bbox":[62.6,85.34,549.46,182.3],"n_rows":9,"n_cols":9,"columns":["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","Specificity % (Sp)",""],"rows":[["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","Specificity % (Sp)",""],["","","","","(95% CI)","","","(95% CI)",""],["Obstructive Hydrocephalus","(cid:148)(cid:20)(cid:17)(cid:24)(cid:80)(cid:80)","0.149943","97.3 (93.3,100.0)","","","94.0 (89.0,98.0)","",""],["","","0.185900","94.7 (89.3,98.7)","","","95.0 (90.0,99.0)","",""],["","","0.281473","92.0 (85.3,97.3)","","","97.0 (93.0,100.0)","",""],["",">1.5mm & (cid:148)(cid:24)(cid:17)(cid:19)(cid:80)(cid:80)","0.100591","97.6 (94.0,100.0)","","","95.3 (90.7,99.1)","",""],["","","0.149943","95.2 (90.5,98.8)","","","95.3 (90.7,99.1)","",""],["","","0.185900","94.0 (89.3,98.8)","","","95.3 (90.7,99.1)","",""],["","","0.281473","88.1 (81.0,94.0)","","","95.3 (90.7,99.1)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p6-t0","doc_id":"K231130","page_num":6,"bbox":[72.0,293.02,540.0,329.06],"n_rows":2,"n_cols":10,"columns":["","","Training Dataset","","","Tuning Dataset","","","Validation Dataset",""],"rows":[["","","Training Dataset","","","Tuning Dataset","","","Validation Dataset",""],["","","(n=390 samples)","","","(n=376 samples)","","","(n=163 samples)",""]],"caption_candidate":"race/ethnicity all reflect the broader U.S. population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p7-t0","doc_id":"K231130","page_num":7,"bbox":[72.36,462.84,543.96,638.04],"n_rows":8,"n_cols":3,"columns":["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std.\nDev.)"],"rows":[["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std.\nDev.)"],["Tumor Volume (n=157)","cubic centimeters (cc)","6.48 ± 12.67"],["Tumor-to-breast volume ratio (n=157)","%","0.56 ± 0.93"],["Tumor longest dimension (n=163)","centimeters (cm)","1.48 ± 1.46"],["Tumor-to-nipple distance (n=161)","centimeters (cm)","1.00 ± 1.03"],["Tumor-to-skin distance (n=163)","centimeters (cm)","0.63 ± 0.60"],["Tumor-to-chest distance (n=163)","centimeters (cm)","0.94 ± 1.34"],["Tumor center of mass (n=157)","centimeters (cm)","0.735 ± 1.26"]],"caption_candidate":"Performance data for the automated measurements is summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p8-t0","doc_id":"K231130","page_num":8,"bbox":[72.28,148.2,545.16,213.72],"n_rows":3,"n_cols":3,"columns":["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],"rows":[["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],["Tumor segmentation (n=157)","Volume Dice","0.676 ± 0.289"],["","Surface Dice","0.873 ± 0.264"]],"caption_candidate":"Results of Dice and surface Dice are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p8-t1","doc_id":"K231130","page_num":8,"bbox":[72.28,469.56,540.23,702.24],"n_rows":10,"n_cols":5,"columns":["","Predicate Device Comparison","","",""],"rows":[["","Predicate Device Comparison","","",""],["","","CADstream version 5\n(predicate)","TumorSight Viz",""],["510(k)","","K092954","TBD",""],["Manufacturer","","Merge CAD Inc.","SimBioSys Inc.",""],["Regulation Number","","892.2050","892.2050",""],["Regulation Name","","Medical image management and\nprocessing system","Medical image management and\nprocessing system",""],["Classification","","2","2",""],["Device Common Name","","Image Processing System","Image Processing System",""],["Product Code","","LLZ","QIH",""],["Functions","","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast",""]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p9-t0","doc_id":"K231130","page_num":9,"bbox":[72.24,72.24,540.24,717.12],"n_rows":4,"n_cols":3,"columns":["Intended Use","CADstream is intended to be\nused in the visualization,\nanalysis, and reporting of\nmagnetic resonance imaging\n(MRI) studies. CADstream\nsupports evaluation of dynamic\nMR data acquired during\ncontrast administration.\nCADstream performs other user\nselected processing functions\n(such as image registration,\nsubtractions, measurements, 3D\nrenderings, and reformats).\nCADstream also includes user-\nconfigurable features for\nreporting on findings in breast or\ngeneral MRI studies.\nAdditionally, CADstream assists\nusers in planning MRM guided\ninterventional procedures.\nWhen interpreted by a skilled\nphysician, this device provides\ninformation that may be used for\nscreening, diagnosis, and\ninterventional planning. Patient\nmanagement decisions should\nnot be made based solely on\ntheresults of CADstream.\nCADstream may also be used as\nan image viewer of multi-\nmodality, digital images,\nincluding ultrasound and\nmammography. CADstream is\nnot intended for primary\ninterpretation of digital\nmammography images.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast\nstudiesduring contrast\nadministration. TumorSight Viz\nperforms processing functions\n(such as image registration,\nsubtractions, measurements, 3D\nrenderings, and reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],"rows":[["Intended Use","CADstream is intended to be\nused in the visualization,\nanalysis, and reporting of\nmagnetic resonance imaging\n(MRI) studies. CADstream\nsupports evaluation of dynamic\nMR data acquired during\ncontrast administration.\nCADstream performs other user\nselected processing functions\n(such as image registration,\nsubtractions, measurements, 3D\nrenderings, and reformats).\nCADstream also includes user-\nconfigurable features for\nreporting on findings in breast or\ngeneral MRI studies.\nAdditionally, CADstream assists\nusers in planning MRM guided\ninterventional procedures.\nWhen interpreted by a skilled\nphysician, this device provides\ninformation that may be used for\nscreening, diagnosis, and\ninterventional planning. Patient\nmanagement decisions should\nnot be made based solely on\ntheresults of CADstream.\nCADstream may also be used as\nan image viewer of multi-\nmodality, digital images,\nincluding ultrasound and\nmammography. CADstream is\nnot intended for primary\ninterpretation of digital\nmammography images.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast\nstudiesduring contrast\nadministration. TumorSight Viz\nperforms processing functions\n(such as image registration,\nsubtractions, measurements, 3D\nrenderings, and reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],["Data Source (Input)","MRI","MRI"],["Output/Accessibility","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity"],["Physical Characteristics","\"-non-invasive software package\n-DICOM compatible\"","\"-non-invasive software package\n-DICOM compatible\""]],"caption_candidate":"TumorSight Viz 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p10-t0","doc_id":"K231130","page_num":10,"bbox":[72.26,72.24,540.23,512.4],"n_rows":21,"n_cols":5,"columns":["Safety","","Clinician review and assessment\nof analysis prior to use in\nplanning MRI guided\ninterventional procedures.","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning.",""],"rows":[["Safety","","Clinician review and assessment\nof analysis prior to use in\nplanning MRI guided\ninterventional procedures.","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning.",""],["","Predicate Device Feature Comparison","","",""],["Feature","","CADstream version 5\n(predicate)","TumorSight Viz",""],["Standard image viewing tools","","Yes","Yes",""],["MIPs","","Yes","Yes",""],["Reformats","","Yes","Yes",""],["Registration","","Yes","Yes",""],["Subtraction series","","Yes","Yes",""],["View 3D volume rendering","","Yes","Yes",""],["Kinetic curves","","Yes","Yes",""],["Parametric image maps","","Yes","Yes",""],["DICOM import","","Yes","Yes",""],["View finding volume","","Yes","Yes",""],["View finding location","","Yes","Yes",""],["View finding size","","Yes","Yes",""],["View kinetic curve with\nhighest uptake","","Yes","Yes",""],["View finding distance to\nnipple","","Yes","Yes",""],["View finding distance to skin","","Yes","Yes",""],["View finding distance to chest","","Yes","Yes",""],["View adjusted finding size","","Yes","No - Segmentation is not\neditable, but surgical margins\nare editable",""],["Interactive rotation of 3D\nvolume rendering","","Yes","Yes",""]],"caption_candidate":"TumorSight Viz 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p10-t1","doc_id":"K231130","page_num":10,"bbox":[72.26,662.46,535.2,717.59],"n_rows":4,"n_cols":9,"columns":["Performance\nMeasurement","N","Metric","TumorSight\nViz/CADStr\neam","","TumorSight","","CADStream\n/ Ground\nTruth","Interradiolo\ngist\nVariability"],"rows":[["Performance\nMeasurement","N","Metric","TumorSight\nViz/CADStr\neam","","TumorSight","","CADStream\n/ Ground\nTruth","Interradiolo\ngist\nVariability"],["","","","","","Viz/","","",""],["","","","","","Ground","","",""],["","","","","","Truth","","",""]],"caption_candidate":"measurements:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231130-p11-t0","doc_id":"K231130","page_num":11,"bbox":[72.39,72.52,535.31,370.44],"n_rows":6,"n_cols":7,"columns":["","","","(Mean\n± Std. Dev.)","(Mean ±\nStd. Dev.)","(Mean ±\nStd. Dev.)","(Mean\n± Std. Dev.)"],"rows":[["","","","(Mean\n± Std. Dev.)","(Mean ±\nStd. Dev.)","(Mean ±\nStd. Dev.)","(Mean\n± Std. Dev.)"],["Longest\nDimension","136","Abs.\nDistance\nError","1.48 cm\n± 1.71 cm","1.40 cm ±\n1.43 cm","1.11 cm ±\n1.52 cm","1.17 cm\n± 1.38 cm"],["Tumor to Skin","136","Abs.\nDistance\nError","0.94 cm\n± 0.69 cm","0.61 cm ±\n0.46 cm","0.49 cm ±\n0.56 cm","0.49 cm\n± 0.54 cm"],["Tumor to\nChest","136","Abs.\nDistance\nError","1.76 cm\n± 1.32 cm","0.77 cm ±\n0.90 cm","1.37 cm ±\n1.01 cm","0.79 cm\n± 1.01 cm"],["Tumor to\nNipple","134","Abs.\nDistance\nError","0.86 cm\n± 1.00 cm","0.98 cm ±\n1.06 cm","0.80 cm ±\n0.86 cm","0.82 cm\n± 0.98 cm"],["Tumor Volume","134","Abs.\nDistance\nError","9.54 cc ±\n20.89 cc","6.69 cc ±\n13.53 cc","8.09 cc ±\n17.42 cc","N/A"]],"caption_candidate":"TumorSight Viz 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231149-p4-t0","doc_id":"K231149","page_num":4,"bbox":[108.25,350.67,522.98,512.13],"n_rows":6,"n_cols":2,"columns":["Name of Device:","qXR-CTR"],"rows":[["Name of Device:","qXR-CTR"],["Common or Usual Name:","Automated radiological image processing software"],["Classification Name:","Medical image management and processing system"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2050"],["Product Code:","QIH"]],"caption_candidate":"2 DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231149-p4-t1","doc_id":"K231149","page_num":4,"bbox":[108.25,564.92,522.98,644.75],"n_rows":3,"n_cols":2,"columns":["Name of Device:","EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System"],"rows":[["Name of Device:","EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System"],["Manufacturer:","Ever Fortune.AI Co., Ltd."],["510(k) Number:","K212624"]],"caption_candidate":"3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231149-p6-t0","doc_id":"K231149","page_num":6,"bbox":[79.23,72.46,504.17,759.98],"n_rows":14,"n_cols":7,"columns":["","","Predicate Device","","","Subject Device",""],"rows":[["","","Predicate Device","","","Subject Device",""],["","","","","","",""],["","","","","","",""],["Product Code","QIH","","","QIH","",""],["Device type","Quantifying software","","","Quantifying software","",""],["Manufacturer","Ever Fortune.AI Co., Ltd.","","","Qure.ai Technologies","",""],["","","","","","",""],["Intended use /\nIndications for Use","EFAI Intelligent Cardiothoracic\nRatio Assessment System (or\niCTR) is a software for use by\nhospitals and clinics to\nautomatically assess the\ncardiothoracic ratio (CTR) of a\nchest X-ray image from the X-\nray imager subject. The iCTR is\ndesigned to measure the\nmaximal transverse diameter\nof heart and maximal inner\ntransverse diameter of\nthoracic cavity and calculate\nthe CTR of a chest X-ray image\nin posterior-anterior (PA)\nchest view using an artificial\nintelligence algorithm.\nIntended users of the\nsoftware are aimed to the\nphysicians or other licensed\npractitioners in the healthcare\ninstitutions, such as clinics,\nhospitals, healthcare facilities,\nresidential care facilities and\nlong-term care services. The\nsystem is suitable for adults\nbetween 20 - 80 years of age.\nIts results are not intended to\nbe used on a stand-alone\nbasis for clinical decision\nmaking or otherwise preclude\nclinical assessment of\ncardiothoracic ratio (CTR)\ncases.","","","qXR-CTR is a deep-learning based\nsoftware for use by hospitals and\nclinics for automated assessment of\nthe CTR on chest X-ray (CXRs) scans.\nqXR-CTR is designed to measure the\nratio of the maximal transverse\ndiameter of the heart (CD) and the\nmaximal inner transverse diameter\n(TD) of the thoracic cavity and\ncalculate the CTR value on posterior-\nanterior view chest view using an\nartificial intelligence algorithm.\nThe intended users of this device are\nphysicians or licensed practitioners in\nhealthcare institutions, such as clinics,\nhospitals, residential care facilities,\nlong-term care services, and\nhealthcare facilities.\nThe system is suitable for adults ≥ 22\nyears of age.\nThe device is used to aid the intended\nusers and results are not intended to\nbe used on a stand-alone basis for\nclinical decision making or otherwise\npreclude clinical assessment of CTR\ncases.","",""],["Algorithm for\nmeasurement of target\nstructures","AI Algorithm","","","Al Algorithm","",""],["Modality","Chest X-ray in Digital\nRadiography (DR)","","","Chest X-ray in Digital Radiography (DR)","",""],["Input","Post-anterior (PA) view chest\nX-ray image","","","Post-anterior (PA) view chest X-ray\nimage","",""],["Input format","DICOM","","","DICOM","",""],["Output Format","Reports, DICOM Secondary\nCapture series","","","Pdf report is generated, DICOM\nSecondary capture is returned to the\nPACS","",""],["Report Structure","Report will be output in the\nDICOM and JSON file format\nwhich is structured with","","","Report will be output in the DICOM\nand JSON file format which is\nstructured with following information","",""]],"caption_candidate":"K231149","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231149-p7-t0","doc_id":"K231149","page_num":7,"bbox":[79.24,72.46,504.17,633.95],"n_rows":14,"n_cols":8,"columns":["","","","Predicate Device","","","Subject Device",""],"rows":[["","","","Predicate Device","","","Subject Device",""],["","","","","","","",""],["","","following information and\nfunction tool: 1) CTR 2)\nadjustable annotation line\n(maximal inner border\ndiameter of thoracic cavity\nand maximal diameter of\nheart) 3) the trajectory of CTR\n(including chest X-ray)","","","and function tool: 1) CTR 2) annotation\nline (maximal inner border diameter of\nthoracic cavity and maximal diameter\nof heart)","",""],["Intended User","","Physicians or other licensed\npractitioners in the healthcare\ninstitutions","","","Physicians or other licensed\npractitioners in the healthcare\ninstitutions","",""],["Target Population","","20-80 years","","","≥ 22 years","",""],["Modality","","Chest X-ray in Digital\nRadiography","","","Chest X-ray in Digital Radiography","",""],["Intended Use\nEnvironment","","Healthcare institutions\n(Clinics, hospitals, healthcare\nfacilities, residential care\nfacilities and long-term care\nservices)","","","Healthcare institutions (Clinics,\nhospitals, healthcare facilities,\nresidential care facilities and long-term\ncare services)","",""],["Software device that\noperates on off the shelf\nhardware","","Yes","","","Yes","",""],["Software devices uses\nsoftware algorithms for\nimage","","Yes","","","Yes","",""],["Diameter Measurement","","Yes","","","Yes","",""],["Storage","","Saved in JSON and DICOM file\nformat text for DICOM and\nDICOM file format","","","The text report is generated with the CXR\nscan on a Structured Report (SR) format for\nPACS-based mode. For the Web-based\nmode, the user can download a PDF\nversion of the report with the same\ninformation","",""],["Software Requirement","","Ubuntu 18.04 (Web browser:\nchrome 88.0.4324.182 or\nabove)","","","Ubuntu 20.04+","",""],["","Performance metrics of the predicate device and qXR-CTR","","","","","",""],["Performance level","","RMSE:\nCardiac Diameter = 8.81 mm\nThoracic Diameter = 14.4 mm\nMean Absolute Error:\nNR","","","RMSE:\nCardiac Diameter = 7.55 mm\nThoracic Diameter = 5.43 mm\nMean Absolute Error:\n5.66 (5.0) mm\n4.04 (3.63) mm","",""]],"caption_candidate":"K231149","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231149-p8-t0","doc_id":"K231149","page_num":8,"bbox":[72.27,376.24,500.76,451.1],"n_rows":5,"n_cols":5,"columns":["Measurement","","Root Mean Squared Error (95%","","Mean Absolute Error (SD) in mm"],"rows":[["Measurement","","Root Mean Squared Error (95%","","Mean Absolute Error (SD) in mm"],["","","CI) in mm","",""],["Cardiac Diameter","7.55 (6.96, 8.38)","","","5.66 (5.0)"],["Thoracic Diameter","5.43 (4.94, 6.09)","","","4.04 (3.63)"],["CTR","0.03 (0.02, 0.03)","","","0.02 (0.02)"]],"caption_candidate":"Table 2 Overall Results of Accuracy Testing of qXR-CTR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p8-t0","doc_id":"K231157","page_num":8,"bbox":[85.56,72.24,587.52,503.88],"n_rows":4,"n_cols":4,"columns":["Subject\nDevice\nCharacteristic","Current Predicate\nDevice\nsyngo.CT Lung CAD\n(VD20) (K203258)","New Device\nsyngo.CT Lung CAD\n(VD30)","Type of Change and\nImpact to Safety & Ef-\nfectiveness"],"rows":[["Subject\nDevice\nCharacteristic","Current Predicate\nDevice\nsyngo.CT Lung CAD\n(VD20) (K203258)","New Device\nsyngo.CT Lung CAD\n(VD30)","Type of Change and\nImpact to Safety & Ef-\nfectiveness"],["Manufacturer","Siemens Healthcare\nGmbH","Siemens Healthcare\nGmbH","[Unchanged]\nNo Impact"],["Detection target","Solid and subsolid pul-\nmonary nodules in\nscreening and diagnos-\ntic chest CT acquisi-\ntions","Solid and subsolid\npulmonary nodules in\nscreening and diag-\nnostic chest CT acqui-\nsitions","[Unchanged]\nNo Impact"],["Intended Use","syngo.CT Lung CAD\nsoftware device is a\nComputer-Aided De-\ntection (CAD) tool de-\nsigned to assist radiol-\nogists in the detection\nof pulmonary nodules\nduring review of multi-\ndetector computed to-\nmography (MDCT) ex-\naminations of the\nthorax (chest). The\nsoftware is an adjunc-\ntive tool to alert the ra-\ndiologist to regions of\ninterest (ROI) that may\notherwise be\noverlooked.","syngo.CT Lung CAD\nsoftware device is a\nComputer-Aided De-\ntection (CAD) tool\ndesigned to assist ra-\ndiologists in the de-\ntection of pulmonary\nnodules during review\nof multi-detector com-\nputed tomography\n(MDCT) examina-\ntions of the thorax\n(chest). The software\nis an adjunctive tool\nto alert the radiologist\nto regions of interest\n(ROI) that may other-\nwise be overlooked.","[Unchanged]\nNo impact"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p11-t0","doc_id":"K231157","page_num":11,"bbox":[85.56,72.24,587.52,537.12],"n_rows":5,"n_cols":4,"columns":["","Voltage\n100 -140 kVp","Voltage\n100 -140 kVp","[Unchanged]\nNo impact"],"rows":[["","Voltage\n100 -140 kVp","Voltage\n100 -140 kVp","[Unchanged]\nNo impact"],["","Collimation\n1 mm or less","Collimation\n1 mm or less","[Unchanged]\nNo Impact"],["","Slice Thickness\nUp to and including\n2.5 mm with\n1.25 mm preferred","Slice Thickness\nUp to and including\n2.5 mm with\n1.25 mm preferred","[Unchanged]\nNo Impact"],["","Slice overlap\n0–50%\nNote: Reconstruction\noverlap is allowed, but\ngaps are not permitted","Slice Overlap\n0–50%\nNote: Reconstruction\noverlap is allowed,\nbut gaps are not per-\nmitted","[Unchanged]\nNo impact"],["","Kernel\nConsistent with tho-\nracic CT protocols and\nin line with patient\nsafety\nguidelines. Kernels\nwere grouped as to\ntheir profile. Typical\nkernels\nvalidated by the reader\nstudy were:\nSmooth: B, B30f,\nStandard, FC10.\nMedium: C, B45f,\nB50f, Lung, FC50,\nFC51, Bv49d_2,\nI50f_2, B60f.\nSharp: D, B70f, Bone,\nFC52 .","Kernel\nConsistent with tho-\nracic CT protocols\nand in line with pa-\ntient safety\nguidelines. Kernels\nwere grouped as to\ntheir profile. Typical\nkernels\nvalidated by the\nreader study were:\nSmooth: B, B30f,\nStandard, FC10.\nMedium: C, B45f,\nB50f, Lung, FC50,\nFC51, Bv49d_2,\nI50f_2, B60f.\nSharp: D, B70f, Bone,\nFC52.","[Unchanged]\nNo impact"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p12-t0","doc_id":"K231157","page_num":12,"bbox":[81.24,528.72,558.0,720.12],"n_rows":2,"n_cols":3,"columns":["Functional Compo-\nnent","LungCAD VD20","LungCAD VD30"],"rows":[["Functional Compo-\nnent","LungCAD VD20","LungCAD VD30"],["Preprocessing\nStandardization of\nthe input images and\nlung segmentation","(a) isotropic volume\nresampling and image\nstandardization.\n(b) lung segmentation is ac-\ncomplished using a CNN.\nInitially a coarse estimation\nof the lung is performed us-\ning a V-net process. Using\ntwo predefined bounding\nboxes left and right lungs are","(a). Isotropic volume resampling and\nimage standardization\n(b) lung segmentation is accomplished by\ncomputing masks of right upper (RUL),\nright middle (RML), right lower (RLL),\nleft upper (LUL), and left lower (LLL)\nlobes for a given CT dataset of chest. The\nsegmentation task is designed as a voxel\nlevel classification task for predicting it\nas one of the lung lobe labels or the"]],"caption_candidate":"Table 1 Summary of Differences between the Subject Device and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p13-t0","doc_id":"K231157","page_num":13,"bbox":[81.24,72.24,558.0,734.04],"n_rows":3,"n_cols":3,"columns":["","initialized. Another V-net is\nused to segment left and\nright lungs. This is followed\nby up-sampling to the origi-\nnal image resolution.","background label. The output is a proba-\nbility map indicating how likely each\nvoxel belongs to each lung lobe. The al-\ngorithm is trained on lung CT data in-\ncluding comorbidities for robustness."],"rows":[["","initialized. Another V-net is\nused to segment left and\nright lungs. This is followed\nby up-sampling to the origi-\nnal image resolution.","background label. The output is a proba-\nbility map indicating how likely each\nvoxel belongs to each lung lobe. The al-\ngorithm is trained on lung CT data in-\ncluding comorbidities for robustness."],["Candidate Genera-\ntion\nThe partitioned vol-\nume is processed us-\ning a CNN and fil-\ntered to yield a list of\ncandidates for each\nsubvolume.","(a) isotropic volume is parti-\ntioned into subvolumes\n(b) Each subvolume is fed to\na CNN to compute features\n(“response volume”). Filter-\ning and non-maximum sup-\npression yield a list of candi-\ndates for each subvolume\n(c) candidates above a cer-\ntain threshold score are\npassed to the next step.","(a) isotropic volume is partitioned into\nsubvolumes\n(b) Each subvolume is fed to a CNN to\ncompute features (“response volume”).\nFiltering and non-maximum suppression\nyield a list of candidates for each sub-\nvolume\n(c) candidates above a certain threshold\nscore are passed to the next step."],["Candidate Classifi-\ncation utilizes a\nCNN-based classifier\nto process each can-\ndidate and estimate\nthe\nlikelihood of its type\nas either “nodule” or\n“non-nodule”.","CNN is used for feature\ncomputation for each candi-\ndate.\n(a) The input image patch is\nfirstly processed by batch\nnormalization.\n(b) Three group blocks of\noperations are computed. In\neach block, a convolution,\nfollowed by a batch\nnormalization and then a\nReLU activation are used.\nResidual blocks and\nconcatenation operations are\nused for robustness\n(c) Semantic features from\nimage features are computed\nusing two fully connected\nlayers.\n(d) A soft-max function, ap-\nplied to each candidate, as-\nsigns 2 values corresponding\nto the probability of being a\nnodule or being a false posi-\ntive.","CNN is used for feature computation for\neach candidate.\n(a) The input image patch is firstly pro-\ncessed by batch normalization.\n(b) Three group blocks of operations are\ncomputed. In each block, a convolution,\nfollowed by a batch normalization and\nthen a ReLU activation are used.\nResidual blocks and concatenation\noperations are used for robustness.\n(c) Semantic features from image fea-\ntures are computed using two fully con-\nnected layers.\n(d) A soft-max function, applied to each\ncandidate, assigns 2 values correspond-\ning to the probability of being a nodule or\nbeing a false positive.\n(e) A weighted-sum of the scores from\nthis phase and the results of the prior step\nis computed. Candidates above a certain\nthreshold score are labeled as nodule can-\ndidates."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p14-t0","doc_id":"K231157","page_num":14,"bbox":[81.24,72.24,558.0,701.64],"n_rows":2,"n_cols":3,"columns":["","(e) A weighted-sum of the\nscores from this phase and\nthe results of the prior step\nis computed. Candidates\nabove a certain threshold\nscore are labeled as nodule\ncandidates.",""],"rows":[["","(e) A weighted-sum of the\nscores from this phase and\nthe results of the prior step\nis computed. Candidates\nabove a certain threshold\nscore are labeled as nodule\ncandidates.",""],["Postfiltering1","This step includes the appli-\ncation of two cascaded fil-\nters. These two filters aim at\nremoving false positives\noriginating from the colon\nand calcified protrusions (for\nexample, areas where the\nsternum meets the\nmanubrium, spine\nmalformations, osteophytes,\nand so on).\nThe first filter is a CNN-\nbased classifier that has a\nsimilar structure to that of\nthe classifier used in the\ncandidate classification step.\nThe second filter uses three\northogonal slices at the can-\ndidate location as input to\nthree CNN-based classifiers\n(one per slice). The results\nfrom the three classifiers are\nthen combined by a max-\nvoting mechanism. Any can-\ndidate deemed a false posi-\ntive by either filter is thus re-\nmoved.","This step includes the application of\nthree cascaded filters. The first one aims\nat removing false positives originating\nfrom the colon and the second one aims\nat removing false positives from calci-\nfied protrusions (for example, areas\nwhere the sternum meets the manubrium,\nspine malformations, and osteophytes,\nand so on).The third one aims at assign-\ning nodule type labels to all findings\n(solid, nonsolid, fully calcified).\nThe first filter is a CNN-based classifier\nthat has a similar structure to that of the\nclassifier in step 3.\nThe second filter uses three orthogonal\nslices at the candidate location as input to\nthree CNN-based classifiers (one per\nslice). The results from the three classifi-\ners is then combined by a max-voting\nmechanism. Any candidate deemed a\nfalse positive by either filter is thus re-\nmoved.\nThe third filter has two parts. The first\npart is a CNN-based classifier that has a\nsimilar structure to that of the classifier\nused in the candidate classification step.,\nwhich classifies findings into solid and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231157-p15-t0","doc_id":"K231157","page_num":15,"bbox":[81.24,72.24,558.0,336.6],"n_rows":2,"n_cols":3,"columns":["","","non-solid groups. The second filter is\nconstructed by using a set of hand-crafted\nrules based on features extracted from\nRaycast methods. The second filter fur-\nther labels some of the solid nodules as\n“fully calcified”. User could choose to\ndisplay findings in “solid only” mode so\nthat non-solid nodules and fully calcified\nnodules are excluded."],"rows":[["","","non-solid groups. The second filter is\nconstructed by using a set of hand-crafted\nrules based on features extracted from\nRaycast methods. The second filter fur-\nther labels some of the solid nodules as\n“fully calcified”. User could choose to\ndisplay findings in “solid only” mode so\nthat non-solid nodules and fully calcified\nnodules are excluded."],["Final Candidate\nList","The location information of\nall the nodule candidates are\ncollected into a final candi-\ndate list passed to the Host-\ning Application","The location information of all the nod-\nule candidates are collected into a final\ncandidate list passed to Hosting Applica-\ntion."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p5-t0","doc_id":"K231195","page_num":5,"bbox":[42.78,526.26,493.62,554.16],"n_rows":2,"n_cols":3,"columns":["510(k) Number","Trade Name","Manufacturer"],"rows":[["510(k) Number","Trade Name","Manufacturer"],["K193658","Viz ICH","Viz.ai, Inc."]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p10-t0","doc_id":"K231195","page_num":10,"bbox":[42.54,726.72,411.12,796.2],"n_rows":4,"n_cols":2,"columns":["ICH Subtype","Sensitivity (95% CI)"],"rows":[["ICH Subtype","Sensitivity (95% CI)"],["Intraparenchymal Hemorrhage (IPH)","96.61% (88.29-99.59)"],["Intraventricular Hemorrhage (IVH)","100.00% (59.04-100.00)"],["Subarachnoid Hemorrhage (SAH)","35.71% (12.76-64.86)"]],"caption_candidate":"and by ICH Volume (Table 6).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t0","doc_id":"K231195","page_num":11,"bbox":[42.54,120.48,411.12,165.48],"n_rows":3,"n_cols":2,"columns":["Subdural Hemorrhage (SDH)","66.67% (40.99-86.66)"],"rows":[["Subdural Hemorrhage (SDH)","66.67% (40.99-86.66)"],["Multiple Types","98.55% (92.19-99.96)"],["Table 1.",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t1","doc_id":"K231195","page_num":11,"bbox":[42.54,188.88,452.87,241.38],"n_rows":3,"n_cols":3,"columns":["Gender","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Gender","Sensitivity (95% CI)","Specificity (95% CI)"],["Male","93.18% (85.75-97.46)","91.30% (83.58-96.17)"],["Female","84.81% (74.97-91.90)","91.46% (83.20-96.50)"]],"caption_candidate":"Table 1. Summary of the performance metrics for the subsets of scans stratified by ICH Subtype.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t2","doc_id":"K231195","page_num":11,"bbox":[42.54,284.88,452.87,354.36],"n_rows":4,"n_cols":3,"columns":["Age","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Age","Sensitivity (95% CI)","Specificity (95% CI)"],["21 < Age < 50","83.33% (67.19-93.63)","88.73% (79.00-95.01)"],["50 ≤ Age < 70","92.75% (83.89-97.61)","91.25% (82.80-96.41)"],["Age ≥ 70","88.71% (78.11-95.34)","100.00% (85.18-100.00)"]],"caption_candidate":"Table 2. Summary of the performance metrics for the subsets of scans stratified by gender.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t3","doc_id":"K231195","page_num":11,"bbox":[42.54,375.36,488.28,444.84],"n_rows":4,"n_cols":3,"columns":["Slice Thickness","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Slice Thickness","Sensitivity (95% CI)","Specificity (95% CI)"],["Slice Thickness < 1.5 mm","87.50% (79.92-92.99)","94.21% (88.44-97.64)"],["1.5mm ≤ Slice Thickness < 3 mm","95.65% (78.05-99.89)","100.00% (82.35-100.00)"],["Slice Thickness ≥ 3 mm","90.62% (74.98-98.02)","76.47% (58.83-89.25)"]],"caption_candidate":"Table 3. Summary of the performance metrics for the subsets of scans stratified by age group.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t4","doc_id":"K231195","page_num":11,"bbox":[42.54,488.34,488.28,540.84],"n_rows":3,"n_cols":3,"columns":["Clinical Site","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Clinical Site","Sensitivity (95% CI)","Specificity (95% CI)"],["Boston Medical Centre","89.38% (82.18-94.39)","94.35% (88.71-97.70)"],["Other","88.89% (77.37-95.81)","84.00% (70.89-92.83)"]],"caption_candidate":"Table 4. Summary of the performance metrics for the subsets of scans stratified by slice thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231195-p11-t5","doc_id":"K231195","page_num":11,"bbox":[42.54,584.34,382.74,670.8],"n_rows":5,"n_cols":2,"columns":["Minimal Volume Threshold (ml)","Sensitivity above Threshold (95% CI)"],"rows":[["Minimal Volume Threshold (ml)","Sensitivity above Threshold (95% CI)"],["vol ≥ 0 ml","89.22% (83.50-93.49)"],["vol ≥ 0.4ml","94.59% (89.63-97.64)"],["vol ≥ 1ml","97.04% (92.59-99.19)"],["vol ≥ 5ml","99.04% (94.76-99.98)"]],"caption_candidate":"Table 5. Summary of the performance metrics for the subsets of scans stratified by referring hospital","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231281-p5-t0","doc_id":"K231281","page_num":5,"bbox":[112.72,67.68,594.0,149.28],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion Serve (TSX-\n307A/1) V1.2 with\nAiCE-i","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K222819","March 3,\n2023"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231281-p5-t1","doc_id":"K231281","page_num":5,"bbox":[112.72,526.7,580.44,725.52],"n_rows":6,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["","Device Name,","","","Aquilion Serve","","","Aquilion Serve","","","",""],["","Model Number","","","(TSX-307A/1) V1.3","","","(TSX-307A/1) V1.2 with AiCE-i","","","",""],["","510(k) Number","","","This submission","","","K222819","","","",""],["Scan modes","","","Conventional scan (Axial Scan)\nVolume, Dynamic volume scan\nDynamic scan\nHelical scan","","","Conventional scan (Axial Scan)\nVolume, Dynamic volume scan\nHelical scan","","","-Dynamic scan is a\ncontinuous scanning\nmode for a target\nregion.","",""],["Scan slice thickness","","","[Volume, Dynamic volume,\nDynamic scan]\n(80-row scan*1: 0.5 mm)\n40-row scan: 0.5 mm\n8-row scan: 0.5 mm*2\n4-row scan: 0.5, 1 and 2 mm*2","","","[Volume, Dynamic volume\nscan]\n(80-row scan*1: 0.5 mm)\n40-row scan: 0.5 mm","","","*1: Option\nDynamic volume CT\nupgrade kit (CGS-\n55A) is mandatory.\n*2: For Dynamic scan\nonly","",""]],"caption_candidate":"technological characteristics between the subject and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231281-p6-t0","doc_id":"K231281","page_num":6,"bbox":[112.52,55.22,580.45,244.62],"n_rows":7,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Comment",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Comment",""],["","Device Name,","","","Aquilion Serve","","","Aquilion Serve","","","",""],["","Model Number","","","(TSX-307A/1) V1.3","","","(TSX-307A/1) V1.2 with AiCE-i","","","",""],["","510(k) Number","","","This submission","","","K222819","","","",""],["Exposure (Dose)\nreduction mode","","","Standard\no Wedge: SilverBeam Filter","","","N/A","","","Previously cleared\nunder K213504","",""],["Dual energy system","","","Option","","","N/A","","","Previously cleared\nunder K132813","",""],["Extended field of\nview","","","Option","","","N/A","","","Reconstruction field\nup to 800 mm for\ndata acquired with\nan FOV of 500 mm,\nbecomes available.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231384-p5-t0","doc_id":"K231384","page_num":5,"bbox":[62.68,154.62,530.14,253.56],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level P, 24 Campbell Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","September 21, 2023"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231384-p5-t1","doc_id":"K231384","page_num":5,"bbox":[62.68,300.6,530.14,385.74],"n_rows":5,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CTB Triage Trauma"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231384-p5-t2","doc_id":"K231384","page_num":5,"bbox":[62.68,432.84,530.14,532.26],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Nines, Inc."],"rows":[["","Manufacturer Name","","Nines, Inc."],["","Device Name","","NinesAI"],["","510(k) reference","","K193351"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231384-p9-t0","doc_id":"K231384","page_num":9,"bbox":[64.7,519.26,547.36,583.72],"n_rows":6,"n_cols":9,"columns":["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","Specificity % (Sp)",""],"rows":[["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","Specificity % (Sp)",""],["","","","","(95% CI)","","","(95% CI)",""],["Mass Effect","≤1.5mm","0.160195","97.0 (95.3,98.4)","","","88.7 (83.5,94.0)","",""],["","","0.221484","96.6 (94.9,98.2)","","","89.5 (84.2,94.0)","",""],["",">1.5mm & ≤5.0mm","0.120944","96.8 (95.3,98.1)","","","89.3 (84.5,93.5)","",""],["","","0.160195","95.3 (93.6,97.0)","","","92.9 (88.7,96.4)","",""]],"caption_candidate":"results of the study are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p4-t0","doc_id":"K231396","page_num":4,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["K231396\nPage 3 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p5-t0","doc_id":"K231396","page_num":5,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 4 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p6-t0","doc_id":"K231396","page_num":6,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 5 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p6-t1","doc_id":"K231396","page_num":6,"bbox":[62.74,666.16,553.82,764.4],"n_rows":2,"n_cols":4,"columns":["Parameter","CEPHX","WebCeph K220903","Comparison"],"rows":[["Parameter","CEPHX","WebCeph K220903","Comparison"],["Indication for Use","CEPHX - Cephalometric Analysis\nSoftware is a software indicated\nfor use by dentists who provide\northodontic treatment for image\nanalysis, simulation, profilogram,\nVTO (Visual Treatment Objective)","WebCeph is a software\nindicated for use by dentists\nwho provide orthodontic\ntreatment for image analysis,\nsimulation, profilogram,\nVTO/STO (Visual Treatment","Different -\nHas no safety or\nsecurity impact on\nthe product. The\nSTO and age"]],"caption_candidate":"WITH THE PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p7-t0","doc_id":"K231396","page_num":7,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 6 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p7-t1","doc_id":"K231396","page_num":7,"bbox":[62.66,176.08,553.9,752.88],"n_rows":13,"n_cols":4,"columns":["Parameter","CEPHX","WebCeph K220903","Comparison"],"rows":[["Parameter","CEPHX","WebCeph K220903","Comparison"],["","and patient consultation. Results\nproduced by the software’s\ndiagnostic, treatment planning\nand simulation tools are\ndependent on the interpretation\nof trained and licensed\npractitioners or dentists. The\ndevice is only for use on patients\n14 years old and above.","Objective) and patient\nconsultation. Results produced\nby the software’s diagnostic,\ntreatment planning and\nsimulation tools are dependent\non the interpretation of trained\nand licensed practitioners or\ndentists. The device is only for\nthe use of patients above 7\nyears old.","differences are\ndetailed below."],["Platform","IBM-compatible PC or PC network","I BM-compatible PC or PC\nnetwork","Same"],["Operating\nSystem","Microsoft Window 7, 8, 10","Microsoft Window 7, 8, 10","Same"],["User Interface","Mouse, Keyboard","Mouse, Keyboard","Same"],["CPU processor type","x64-based processor or higher","x64-based processor or higher","Same"],["Image\nCommunication\nStandard","BMP, JPG, PNG","BMP, JPG, PNG","Same"],["Modality Support","X-ray or CT","X-ray or CT","Same"],["Component","Client (Internet Browser)","Client (Internet Browser)","Same"],["Database\nCompatibility","MySQL","PostgreSQL","Different -\nHas no safety,\nsecurity or\nperformance\nimpact on the\nproduct. The\ndifference is\nexplained and\ndetailed below."],["Image Measurement\ntools","Linear distance, angle","Linear distance, angle","Same"],["Image viewing","Full, side by side, thumbnail,\nZoom in / out, template.","Full, side by side, thumbnail,\nZoom in / out, template.","Same"],["Image manipulation","Brightness, contrast, flip, rotate,\nannotation, cephalometric\ntracing.","Brightness, contrast, flip, rotate,\nannotation, cephalometric\ntracing.","Same"]],"caption_candidate":"Page 6 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p8-t0","doc_id":"K231396","page_num":8,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 7 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p8-t1","doc_id":"K231396","page_num":8,"bbox":[62.67,176.08,553.89,499.2],"n_rows":7,"n_cols":4,"columns":["Parameter","CEPHX","WebCeph K220903","Comparison"],"rows":[["Parameter","CEPHX","WebCeph K220903","Comparison"],["Cephalometric\ntracing","In addition to the user-configured\nanalysis, standard orthodontic\ntracing analysis include: Downs,\nSteiner, Jarabek, McNamara,\nRicketts, Eastman, Kim, Wits.","In addition to the user-\nconfigured analysis, standard\northodontic tracing analysis\ninclude: Downs, Steiner,\nJarabek, McNamara, Ricketts,\nEastman, Kim, Wits.","Same"],["Implant module","None","None","Same"],["3D imaging capability","None","None","Same"],["Image annotation","Paint, draw, magnify, line\ndrawing, distance measure (px or\nmm), 3-point angle,\nruler(calibrate), select region\ncrop.","Paint, draw, magnify, line\ndrawing, distance measure (px\nor mm), 3-point angle,\nruler(calibrate), select region\ncrop.","Same"],["Treatment Planning,\nSimulation and follow\nup","-Translate, tip and rotate incisors,\nreposition molars, rotate\nmandible and skeletal structures -\nSuperimpose one or more growth\ntracings over original tracing.","-Translate, tip and rotate\nincisors, reposition molars,\nrotate mandible - Superimpose\none or more growth tracings\nover original tracing.","Different -\nHas no safety or\nsecurity impact on\nthe product. The\nSkeletal structure\ndifference is\nexplained and\ndetailed below."],["Supported Area","Dental, Maxilla, Mandible","Dental, Maxilla, Mandible","Same"]],"caption_candidate":"Page 7 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p9-t0","doc_id":"K231396","page_num":9,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 8 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231396-p10-t0","doc_id":"K231396","page_num":10,"bbox":[90.24,51.6,526.8,161.76],"n_rows":3,"n_cols":2,"columns":["","Date issued:\n28/01/2024"],"rows":[["","Date issued:\n28/01/2024"],["Document name: 510(k) Summary CEPHX - Cephalometric Analysis Software",""],["Page 9 of 9",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231398-p7-t0","doc_id":"K231398","page_num":7,"bbox":[66.63,72.32,545.43,212.9],"n_rows":3,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","and quantifying segmentable brain\nstructures identified on MR images.\nThe users are trained healthcare\nprofessionals who work with medical\nimaging.\nThe product is used in an office-like\nenvironment.","segmentable brain structures identified\non MR images.\nThe users are trained healthcare\nprofessionals who work with medical\nimaging.\nThe product is used in an office-like\nenvironment."],["Deployment","Cloud based","Cloud based"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p4-t0","doc_id":"K231459","page_num":4,"bbox":[77.64,162.92,404.57,754.28],"n_rows":51,"n_cols":2,"columns":["Date Prepared","07 June 2023"],"rows":[["Date Prepared","07 June 2023"],["",""],["Submitted by","Resonance Health Analysis Servic"],["",""],["","141 Burswood Rd"],["",""],["","Burswood 6100"],["",""],["","AUSTRALIA"],["",""],["Main Contact","Mitchell Wells"],["",""],["","Managing Director,"],["",""],["","Resonance Health Analysis Servic"],["",""],["","mitchellw@resonancehealth.com"],["",""],["","Tel: +61 8 9286 5300"],["",""],["","Fax: +61 8 9286 5399"],["",""],["US Contact (US Agent)","Michael van der Woude"],["",""],["","Director & GM"],["",""],["","Emergo Global Representation LL"],["",""],["","2500 Bee Cave Road, Building 1,"],["",""],["","Austin, TX 78746"],["",""],["","Phone: 512 3279997"],["",""],["","Fax : 512 3279998"],["",""],["","Email : USAgent@ul.com"],["",""],["EVICE INFORMATION",""],["",""],["Name of Device","HepaFatSmart"],["",""],["Trade/proprietary Name","HepaFatSmart (V2.0.0)"],["",""],["Classification","Class II"],["",""],["Product Code","LNH"],["",""],["CFR Section","892.1000 Magnetic Resonance D"],["",""],["Panel","Radiology"]],"caption_candidate":"07 June 2023","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231459-p4-t1","doc_id":"K231459","page_num":4,"bbox":[72.32,625.28,505.2,763.08],"n_rows":6,"n_cols":4,"columns":["","Name of Device","","HepaFatSmart"],"rows":[["","Name of Device","","HepaFatSmart"],["","Trade/proprietary Name","","HepaFatSmart (V2.0.0)"],["","Classification","","Class II"],["","Product Code","","LNH"],["","CFR Section","","892.1000 Magnetic Resonance Diagnostic Device"],["","Panel","","Radiology"]],"caption_candidate":"DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p7-t0","doc_id":"K231459","page_num":7,"bbox":[64.93,72.36,512.99,741.6],"n_rows":9,"n_cols":12,"columns":["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],["Regulatory Class","","","II","","","II","","","II","",""],["510(k) number","","","K231459","","","K201039","","","K122035","",""],["Classification Name","","","System, Nuclear\nMagnetic Resonance\nImaging, System, Image\nProcessing Radiological","","","System, Nuclear Magnetic\nResonance Imaging,\nSystem, Image Processing\nRadiological","","","System, Nuclear Magnetic\nResonance Imaging,\nSystem, Image Processing\nRadiological","",""],["CFR Section","","","892.1000","","","892.1000","","","892.1000","",""],["Product Code and\nClassification Panel","","","LNH","","","LNH","","","LNH","",""],["Device Name","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan","",""],["Trade/Common\nName","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan","",""],["Description","","","Standalone software\nplatform designed to\nautomatically analyse\nwithin seconds magnetic\nresonance imaging (MRI)\ndatasets using the\nmethod of HepaFat-Scan\nwith the liver ROI\npredicted to generate an\nestimate of the patient’s\nvolumetric liver fat\nfraction (VLFF),\nconverted into proton\ndensity fat fraction\n(PDFF) and steatosis\ngrade. No user input is\nrequired for the analysis\nthus minimising the\nimpact of human error\non obtained results.","","","Standalone software\nplatform designed to\nautomatically analyse\nwithin seconds magnetic\nresonance imaging (MRI)\ndatasets to generate an\nestimate of the patient’s\nvolumetric liver fat fraction\n(VLFF), converted into\nproton density fat fraction\n(PDFF) and steatosis grade.\nNo user input is required\nfor the analysis thus\nminimising the impact of\nhuman error on obtained\nresults.","","","Standalone software\napplication to facilitate the\nimport and visualization of\nmulti-slice, gradient-echo\nMRI data sets\nencompassing the\nabdomen, with\nfunctionality independent\nof the MRI equipment, to\nprovide objective and\nreproducible\ndetermination of the\ntriglyceride fat fraction in\nmagnetic resonance\nimages of the liver. It\nutilises magnetic\nresonance images that\nexploit the difference in\nresonance frequencies\nbetween hydrogen nuclei\nin water and triglyceride\nfat. The quantitative\ntriglyceride fat fraction is\nbased on the\nmeasurement of a\nmagnetic resonance\nparameter that reflects\nthe ratio of the proton\ndensity signal of\ntriglyceride fat to the total\nproton density signal in\nthe liver.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p8-t0","doc_id":"K231459","page_num":8,"bbox":[64.95,72.36,512.97,767.4],"n_rows":4,"n_cols":12,"columns":["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],["Technology","","","Convolutional neural\nnetworks for the\nprediction of the liver\nregion of interest (ROI).\nAlgorithmic for the\nimage quality checking\nand calculated Alpha\nconversion into VLFF,\nPDFF and Steatosis\ngrade.\nAlgorithms for the\nmeasurement and\ncalculation of Alpha\nVLFF, PDFF and Steatosis\ngrade.","","","Convolutional neural\nnetworks for the image\nanalysis.\nAlgorithmic for the image\nquality checking and Alpha\nconversion into VLFF.","","","Algorithmic, with human\ninteraction for Region of\nInterest (ROI) selection.","",""],["Intended Use","","","HepaFatSmart is\nintended for the\nquantitative\nmeasurement of\nvolumetric liver fat\nfraction (VLFF), proton\ndensity fat fraction\n(PDFF) and steatosis\ngrading.\nHepaFatSmart is an\napplication that is used\nfor the non-invasive\nevaluation of liver tissue\nby utilising magnetic\nresonance images to\nevaluate the difference\nin resonance frequencies\nbetween hydrogen\nnuclei in water and\ntriglyceride fat. The\nquantitative triglyceride\nfat fraction is based on\nthe measurement of a\nmagnetic resonance\nparameter that reflects\nthe ratio of the proton\ndensity signal of\ntriglyceride fat to the\ntotal proton density\nsignal in the liver.","","","HepaFat-AI is intended for\nquantitative measurement\nof the triglyceride fat\nfraction in magnetic\nresonance images of the\nliver, also known as\nvolumetric liver fat fraction\n(VLFF).\nIt utilises magnetic\nresonance images that\nexploit the difference in\nresonance frequencies\nbetween hydrogen nuclei\nin water and triglyceride\nfat. The quantitative\ntriglyceride fat fraction is\nbased on the\nmeasurement of a\nmagnetic resonance\nparameter that reflects the\nratio of the proton density\nsignal of triglyceride fat to\nthe total proton density\nsignal in the liver.\nWhen interpreted by a\ntrained physician, the\nresults provide information\nthat can aid in diagnosis.","","","HepaFat-Scan is a software\ndevice intended for\nquantitative measurement\nof the triglyceride fat\nfraction in magnetic\nresonance images of the\nliver. It utilises magnetic\nresonance images that\nexploit the difference in\nresonance frequencies\nbetween hydrogen nuclei\nin water and triglyceride\nfat. The quantitative\ntriglyceride fat fraction is\nbased on the\nmeasurement of a\nmagnetic resonance\nparameter that reflects\nthe ratio of the proton\ndensity signal of\ntriglyceride fat to the total\nproton density signal in\nthe liver.\nWhen interpreted by a\ntrained physician, the\nresults provide\ninformation that can aid in\ndiagnosis.","",""],["Indications","","","• Support clinical\ndiagnoses in\nindividuals with","","","HepaFat-AI is indicated to:\n• Assess the volumetric\nliver fat fraction,","","","HepaFat-Scan is a software\ndevice intended for\nquantitative measurement","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p9-t0","doc_id":"K231459","page_num":9,"bbox":[64.94,72.36,512.98,761.16],"n_rows":7,"n_cols":12,"columns":["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],["","","","confirmed or\nsuspected fatty liver\ndisease;\n• Support the\nsubsequent clinical\ndecision-making\nprocesses for patients\nunder management\nfor fatty liver related\ndisease or metabolic\nsyndromes;\nAid in the assessment\nand screening of living\ndonors for liver\ntransplant.\n• Results, when\ninterpreted by a\ntrained physician can\nbe used to support\nclinical diagnoses\nabout the status of\nliver fat content, the\nsubsequent clinical\ndecision-making\nprocesses for the\nmanagement of fatty\nliver related diseases,\nmetabolic syndromes,\nliver donor screening\nand lifestyle change.\nHepaFatSmart can be\nused to analyse the\nMRI images of patients\nof all population\nindependent of age\nand gender, with\nsuspected clinical\nconditions related to\nthe level of liver fat.","","","proton density fat\nfraction and steatosis\ngrade in individuals\nwith confirmed or\nsuspected fatty liver\ndisease;\n• Monitor liver fat\ncontent in patients\nundergoing weight loss\nmanagement;\nAid in the assessment and\nscreening of living donors\nfor liver transplant.","","","of the triglyceride fat\nfraction in magnetic\nresonance images of the\nliver. It utilises magnetic\nresonance images that\nexploit the difference in\nresonance frequencies\nbetween hydrogen nuclei\nin water and triglyceride\nfat. The quantitative\ntriglyceride fat fraction is\nbased on the\nmeasurement of a\nmagnetic resonance\nparameter that reflects\nthe ratio of the proton\ndensity signal of\ntriglyceride fat to the total\nproton density signal in\nthe liver.\nWhen interpreted by a\ntrained physician, the\nresults provide\ninformation that can aid in\ndiagnosis.","",""],["User","","","Radiologist","","","Radiologist","","","Resonance Health’s\ntrained analyst","",""],["Hosting platform","","","Cloud-based or onsite\nplatform","","","Cloud-based or onsite\nplatform","","","Resonance Health’s\ninternal server","",""],["Image-type utilized","","","Magnetic Resonance","","","Magnetic Resonance","","","Magnetic Resonance","",""],["Image format","","","DICOM","","","DICOM","","","DICOM","",""],["Data Acquisition\nmethod","","","Gradient Recalled Echo\n(GRE)","","","Gradient Recalled Echo\n(GRE)","","","Gradient Recalled Echo\n(GRE)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p10-t0","doc_id":"K231459","page_num":10,"bbox":[64.95,72.36,512.97,448.08],"n_rows":4,"n_cols":12,"columns":["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],"rows":[["","","","","HepaFatSmart","","","HepaFat-AI","","","HepaFat-Scan",""],["Anatomical Sites","","","Liver","","","Liver","","","Liver","",""],["Result report\ncontent","","","• Unique Report ID\n• Patient ID, patient\nname, and date of\nbirth for full\nidentification of the\npatient.\n• Scan date, and\nanalysis date.\n• Referrer and MRI\ncentre.\n• Results displayed:\nVLFF (%), PDFF (%)\nand Steatosis grade,\nassociated with\nconfidence intervals\nand normal range.\n• Pictures of the 2 TEs\nof the analysed slice\nand analysis liver ROI\nplaced on 1 TE.\nLiver colour map (for\nillustration purpose only,\nnot for diagnostic)","","","• Unique Report ID\n• Patient ID, patient\nname, and date of birth\nfor full identification of\nthe patient.\n• Scan date, and analysis\ndate.\n• Referrer and MRI\ncentre.\n• Results displayed: VLFF\n(%), PDFF (%) and\nSteatosis grade,\nassociated with\nconfidence intervals\nand normal range.\n• Pictures of the 3 TEs of\nthe analysed slice.\nLiver colour map (for\nillustration purpose only,\nnot for diagnostic)","","","• Unique Report ID\n• Patient ID, patient\nname, and date of\nbirth for full\nidentification of the\npatient.\n• Scan date, and analysis\ndate.\n• Referrer and MRI\ncentre.\n• Results displayed: VLFF\n(%) associated with\nconfidence intervals\nand normal range.\n• Picture of the analysed\nslice.","",""],["Result report\nformat","","","PDF (encrypted) and\nsecondary capture\n(DICOM)","","","HTML and PDF","","","PDF","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p11-t0","doc_id":"K231459","page_num":11,"bbox":[72.11,212.88,523.21,478.56],"n_rows":6,"n_cols":2,"columns":["A","B"],"rows":[["A","B"],["Figure 1. Plot A of HepaFat-Scan VLFF measured at scan 2 against HepaFat-Scan VLFF measured at scan 1 for the 42 subjects",""],["in the repeatability study. Plot B is for HepaFatSmart (41 subjects). The solid line is the line of equivalence. Note, 41 instead",""],["of 42 subjects were used in the HepaFatSmart related analysis as a single case was identified as a high iron case with the",""],["newly introduced excessive iron assessment algorithm. All the results are closely scattered around the equivalency line,",""],["indicating good performance and substantial equivalence for both the predicate HepaFat-Scan and the device HepaFatSmart,",""]],"caption_candidate":"the same analysis outcome. Briefly, the results are summarised as following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p12-t0","doc_id":"K231459","page_num":12,"bbox":[72.02,118.44,523.3,252.72],"n_rows":10,"n_cols":2,"columns":["","bias and both repeatability coefficients for the HepaFatSmart are"],"rows":[["","bias and both repeatability coefficients for the HepaFatSmart are"],["slightly better than those obtained from the repeated scans of HepaFat-Scan, indicating the",""],["performance of the HepaFatSmart is comparable (no worse) than human for the repeatability data",""],["analysed. This does not suggest yet that the HepaFatSmart is better than human analyst as the original",""],["human analysis (HepaFat-Scan) historically used two small liver ROIs rather than a single large liver",""],["ROI used in the HepaFatSmart with potentially slightly larger sampling error in the original HepaFat-",""],["Scan analysis.",""],["repeatability coefficients for the HepaFatSmart, indicating the substantial equivalence to the",""],["predicate HepaFat-Scan and a possibility that the results from HepaFatSmart and HepaFat-Scan could",""],["be interchangeable.",""]],"caption_candidate":"From the Bland Altman analysis shown in Figure 2 for both the reference standard HepaFat-Scan (plot","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p12-t1","doc_id":"K231459","page_num":12,"bbox":[72.02,400.56,523.3,651.12],"n_rows":6,"n_cols":2,"columns":["A","B"],"rows":[["A","B"],["Figure 3. Linear regression analysis of the validation study (n = 281) by comparing HepaFatSmart with the reference standard",""],["HepaFat-Scan: plot A shows the full VLFF range and plot B shows the VLFF range between 0 – 10%. The solid line is the line",""],["of equivalence. 281 datasets out of 300 passed the IQC rules. All the results are closely scattered around the equivalency",""],["line, indicating good performance and substantial equivalence for both the predicate HepaFat-Scan and the device",""],["HepaFatSmart.",""]],"caption_candidate":"size is smaller than 300 as per the IQC module in place):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p13-t0","doc_id":"K231459","page_num":13,"bbox":[72.03,72.0,523.29,179.4],"n_rows":8,"n_cols":3,"columns":["and both 95% limits for the HepaFatSmart are significantly better than those obtained from the","",""],"rows":[["and both 95% limits for the HepaFatSmart are significantly better than those obtained from the","",""],["predicate HepaFat-AI, indicating the much improved and safer performance of the HepaFatSmart,","",""],["which is as expected as the analysis outcomes are solely dependent on the liver ROI..","Despite the","Bias"],["of 0.2% is statistically significant (due to small variability), it is small and unlikely clinically significant.","",""],["Both upper and lower 95% limits are small and close to the repeatability coefficients found in the","",""],["repeatability study but significantly smaller than the predicate HepaFat-AI, indicating the new device","",""],["HepaFatSmart is substantially equivalence to the predicate HepaFat-Scan and better than the","",""],["predicate HepaFat-AI.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p13-t1","doc_id":"K231459","page_num":13,"bbox":[72.03,193.08,523.29,443.52],"n_rows":6,"n_cols":2,"columns":["A","B"],"rows":[["A","B"],["Figure 4. Bland Altman analysis of the validation study (n = 281) of the HepaFatSmart VLFF (plot A) and HepaFat-AI (plot B)",""],["by comparing with the reference standard HepaFat-Scan VLFF. For the HepaFatSmart, the Bias of 0.2% is statistically",""],["significant (due to small variability) but small and unlikely clinically significant. Both upper and lower 95% limits are small and",""],["close to the repeatability coefficients found in the repeatability study. Compared with the predicate HepaFat-AI, significant",""],["improvement is indicated by the small bias and 95% confident limits.",""]],"caption_candidate":"predicate HepaFat-AI.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231459-p13-t2","doc_id":"K231459","page_num":13,"bbox":[43.73,537.72,547.75,711.26],"n_rows":9,"n_cols":9,"columns":["","","","Bias","95% CI","Upper 95%\nLA/Repeatability","95% CI","Lower 95%\nLA/Repeatability","95% CI"],"rows":[["","","","Bias","95% CI","Upper 95%\nLA/Repeatability","95% CI","Lower 95%\nLA/Repeatability","95% CI"],["","HepaFat-Scan","","-0.2 (-0.19)","-0.5 to 0.1","1.9","1.3 to 2.5","-2.3","-1.7 to -2.9"],["","Repeatability","","","","","","",""],["","HepaFat-AI v1.2.17","","-0.2 (-0.22)","-0.8 to 0.3","3.2","2.3 to 4.2","-3.6","-2.7 to -4.6"],["","Repeatability","","","","","","",""],["","HepaFatSmart v2.0.0","","-0.1 (-0.14)","-0.4 to 0.1","1.5","1.1 to 2.0","-1.8","-1.4 to -2.4"],["","Repeatability","","","","","","",""],["HepaFat-AI v1.2.17 Limits\nof Agreement (full\nquaran�ne dataset)","","","0.4 (0.41)","0.1 to 0.7","5.4","4.9 to 6.0","-4.6","- 4.1 to -5.2"],["HepaFatSmart v2.0.0\nLimits of Agreement (full\nquaran�ne dataset)","","","0.2 (0.19)","0.1 to 0.3","1.7","1.5 to 1.8","-1.3","-1.1 to -1.4"]],"caption_candidate":"HepaFat-AI.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231470-p4-t0","doc_id":"K231470","page_num":4,"bbox":[57.0,236.47,555.1,488.78],"n_rows":4,"n_cols":2,"columns":["Applicant (Manufacturer)","Lunit Inc.\n4-8 F, 374, Gangnam-daero, Gangnam-gu,\nSeoul, 06241, Republic of Korea\nTel: + 82-70-5066-0849\nFAX: +82-2-6919-2702\nE-mail: ra_rad@lunit.io"],"rows":[["Applicant (Manufacturer)","Lunit Inc.\n4-8 F, 374, Gangnam-daero, Gangnam-gu,\nSeoul, 06241, Republic of Korea\nTel: + 82-70-5066-0849\nFAX: +82-2-6919-2702\nE-mail: ra_rad@lunit.io"],["Primary Correspondent","Harry Hyung Tak Han\nRegulatory Affairs Specialist\nEmail: hhan@lunit.io"],["Secondary Correspondent","Suhyoung Bahk\nRegulatory Affairs Specialist\nEmail: sbahk@lunit.io"],["Date Prepared","2023. 11. 03"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231470-p4-t1","doc_id":"K231470","page_num":4,"bbox":[57.0,556.8,555.1,674.45],"n_rows":5,"n_cols":2,"columns":["Name of Device","Lunit INSIGHT DBT"],"rows":[["Name of Device","Lunit INSIGHT DBT"],["Classification Name","Radiological Computer Assisted Detection/Diagnosis Software For Suspicious\nLesions For Cancer"],["Regulation","21 CFR 892.2090"],["Regulatory Class","Class II"],["Product Code","QDQ"]],"caption_candidate":"Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231470-p5-t0","doc_id":"K231470","page_num":5,"bbox":[57.0,130.65,555.1,271.56],"n_rows":6,"n_cols":2,"columns":["Name of Device","Lunit INSIGHT MMG"],"rows":[["Name of Device","Lunit INSIGHT MMG"],["Classification Name","Radiological Computer Assisted Detection/Diagnosis Software For Suspicious\nLesions For Cancer"],["Regulation","21 CFR 892.2090"],["Regulatory Class","Class II"],["Product Code","QDQ"],["Submission Number","K211678"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231470-p6-t0","doc_id":"K231470","page_num":6,"bbox":[56.99,130.7,555.08,678.55],"n_rows":12,"n_cols":9,"columns":["Item","","","Subject Device","","","Predicate Device","",""],"rows":[["Item","","","Subject Device","","","Predicate Device","",""],["","","","","Lunit INSIGHT DBT","","","Lunit INSIGHT MMG",""],["Classification Name","","","Radiological Computer Assisted\nDetection/Diagnosis Software For Suspicious\nLesions For Cancer","","","Radiological Computer Assisted\nDetection/Diagnosis Software For Suspicious\nLesions For Cancer","",""],["Regulation","","","21 CFR 892.2090","","","21 CFR 892.2090","",""],["Regulatory Class","","","Class II","","","Class II","",""],["Product Code","","","QDQ","","","QDQ","",""],["Indication for Use","","","Lunit INSIGHT DBT is a computer-assisted\ndetection and diagnosis (CADe/x) software\nintended to be used concurrently by\ninterpreting physicians to aid in the detection\nand characterization of suspected lesions for\nbreast cancer in digital breast tomosynthesis\n(DBT) exams from compatible DBT systems.\nThrough the analysis, the regions of soft\ntissue lesions and calcifications are marked\nwith an abnormality score indicating the\nlikelihood of the presence of malignancy for\neach lesion. Lunit INSIGHT DBT uses screening\nmammograms of the female population.\nLunit INSIGHT DBT is not intended as a\nreplacement for a complete interpreting\nphysician’s review or their clinical judgment\nthat takes into account other relevant\ninformation from the image or patient\nhistory.","","","Lunit INSIGHT MMG is a radiological\nComputer-Assisted Detection and Diagnosis\n(CADe/x) software device based on an\nartificial intelligence algorithm intended to aid\nin the detection, localization, and\ncharacterization of suspicious areas for breast\ncancer on mammograms from compatible\nFFDM systems. As an adjunctive tool, the\ndevice is intended to be viewed by\ninterpreting physicians after completing their\ninitial read. It is not intended as a\nreplacement for a complete physician’s\nreview or their clinical judgement that takes\ninto account other relevant information from\nthe image or patient history. The Lunit\nINSIGHT MMG uses screening mammograms\nof the female population.","",""],["","Target patient","","Women undergoing mammography","","","Women undergoing mammography","",""],["","population","","","","","","",""],["Intended user","","","Physicians interpreting screening\nmammograms","","","Physicians interpreting screening\nmammograms","",""],["Input Image Source","","","DBT","","","FFDM","",""],["Fundamental\nTechnological Basis","","","Lunit INSIGHT DBT is powered by artificial\nintelligence/machine learning-based software\nalgorithm","","","Lunit INSIGHT MMG is powered by artificial\nintelligence/machine learning-based software\nalgorithm","",""]],"caption_candidate":"5. Summary of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p8-t0","doc_id":"K231560","page_num":8,"bbox":[72.72,630.96,503.52,760.32],"n_rows":7,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Vida with syngo\nMR XA50A","K213693, cleared on February\n25, 2022","LNH\nLNI, MOS","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Lumina with\nsyngo MR XA50A","K220939, cleared April 29,\n2022","LNH\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Sola with\nsyngo MR XA51A","K221733, cleared\nSeptember 14, 2022","LNH\nLNI, MOS","Siemens Healthcare GmbH"]],"caption_candidate":"following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p9-t0","doc_id":"K231560","page_num":9,"bbox":[72.32,274.06,504.33,649.97],"n_rows":29,"n_cols":4,"columns":["","Subject Devices","Predicate Device","Reference Devices*"],"rows":[["","Subject Devices","Predicate Device","Reference Devices*"],["","","",""],["","MAGNETOM Aera,","MAGNETOM Vida with","MAGNETOM Sola with"],["","MAGNETOM Skyra,","syngo MR XA50A","syngo MR XA51A"],["","MAGNETOM Prisma,","(K213693)","(K221733)"],["Hardware","","",""],["","MAGNETOM Prismafit,","","MAGNETOM Lumina"],["","","",""],["","MAGNETOM Vida and","","with syngo MR XA50A"],["","MAGNETOM Lumina","","(K220939)"],["","with software syngo MR","",""],["","XA60A","",""],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","Yes","Yes","Yes"],["Patient Table","Yes","Yes","Yes"],["Multi-Nuclear\nOption - Supported\nNuclei","Yes","Yes","Yes"],["Computer","Yes","Yes","Yes"],["","Modified","",""],["Coils","Yes","Yes","Yes"],["","New Flex Loop Large coil for","",""],["","MAGNETOM Aera","",""],["Other HW\ncomponents","Yes","Yes","Yes"],["","Modified (Beat Sensor – for","",""],["","MAGNETOM Vida and","",""],["","MAGNETOM Lumina, Image","",""],["","calculation system – except for","",""],["","MAGNETOM Lumina)","",""]],"caption_candidate":"Summary hardware comparison table for the subject and predicate/reference device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p9-t1","doc_id":"K231560","page_num":9,"bbox":[72.32,677.8,504.33,777.48],"n_rows":10,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","",""],["Software","MAGNETOM Vida with software","MAGNETOM Vida with syngo"],["","syngo MR XA50A","MR XA31A"],["","","(K203443)"],["Sequences","",""],["","New feature as listed in the Device","Yes"],["SE-based pulse sequence types","",""],["","Description above",""],["","",""]],"caption_candidate":"Summary software comparison table for the subject and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p10-t0","doc_id":"K231560","page_num":10,"bbox":[72.43,71.32,504.94,374.76],"n_rows":33,"n_cols":3,"columns":["","New or modified pulse sequences","Yes"],"rows":[["","New or modified pulse sequences","Yes"],["GRE-based/Steady-State pulse","",""],["","as listed in the Device Description",""],["sequence types","",""],["","above",""],["","",""],["","New features as listed in the Device","Yes"],["EPI-based pulse sequence types","",""],["","Description above",""],["","",""],["Spectroscopy pulse sequence types","Yes","Yes"],["Feature and Applications","",""],["Other features and","","Yes"],["applications such as:","",""],["","New and Modified features and",""],["-Application Suites","",""],["","applications as listed in the Device",""],["-myExam Assists","",""],["","Description above",""],["-Other Imaging","",""],["","",""],["Applications","",""],["User interface and user interaction","Yes","Yes"],["Viewing and post-processing","Yes","Yes"],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["Scanning","Yes","Yes"],["","New feature","Yes"],["Reconstruction","as listed in the Device Description",""],["","above",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p11-t0","doc_id":"K231560","page_num":11,"bbox":[72.62,109.92,466.78,295.32],"n_rows":8,"n_cols":3,"columns":["","Tested Hardware or",""],"rows":[["","Tested Hardware or",""],["Performance Test","","Source/Rationale for test"],["","Software",""],["","",""],["Software verification\nand validation","New or modified software\nfeatures","Guidance for the Content of Premarket\nSubmissions for Software Contained in\nMedical Devices"],["Sample clinical images","New or modified software\nfeatures","Guidance for submission of Premarket\nNotifications for Magnetic Resonance\nDiagnostic Devices"],["Image quality\nassessment by sample\nclinical images","- new / modified pulse\nsequence types.\n- comparison images\nbetween the new / modified\nfeatures and the predicate\ndevice features",""],["Physio logging\nVerification Report","Physio logging","New Feature Introduction"]],"caption_candidate":"The following performance testing was conducted on the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p11-t1","doc_id":"K231560","page_num":11,"bbox":[72.62,349.68,503.48,428.16],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for coils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance Diagnostic\nDevices"]],"caption_candidate":"reference devices and can be reused for the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p11-t2","doc_id":"K231560","page_num":11,"bbox":[72.62,501.96,550.68,777.84],"n_rows":3,"n_cols":3,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:"],["Training and\nValidation data","• TSE: more than 25,000 slices\n• HASTE: pre-trained on the TSE dataset\nand refined with more than 10,000\nHASTE slices\n• EPI Diffusion: more than 1,000,000\nslices\nThe data covered a broad range of body\nparts, contrasts, fat suppression techniques,\norientations, and field strength.","on more than 10,000 high resolution 2D\nimages.\nThe data covered a broad range of body\nparts, contrasts, fat suppression techniques,\norientations, and field strength."],["Test Statistics and\nTest Results\nSummary","The impact of the network has been\ncharacterized by several quality metrics\nsuch as peak signal-to-noise ratio (PSNR)\nand structural similarity index (SSIM). Most\nimportantly, the performance was\nevaluated by visual comparisons to\nevaluate e.g., aliasing artifacts, image\nsharpness and denoising levels.","The impact of the network has been\ncharacterized by several quality metrics\nsuch as peak signal-to-noise ratio (PSNR),\nstructural similarity index (SSIM), and\nperceptual loss. In addition, the feature has\nbeen verified and validated by inhouse\ntests. These tests include visual rating and\nan evaluation of image sharpness by\nintensity profile comparisons of"]],"caption_candidate":"features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p12-t0","doc_id":"K231560","page_num":12,"bbox":[72.48,71.04,550.68,354.36],"n_rows":5,"n_cols":3,"columns":["","","reconstructions with and without Deep\nResolve Sharp."],"rows":[["","","reconstructions with and without Deep\nResolve Sharp."],["Equipment","1.5T and 3T MRI systems",""],["Clinical Subgroups","No clinical subgroups have been defined for the collected dataset.",""],["Demographic\nDistribution","Due to reasons of data privacy, we did not record gender, age and ethnicity during data\ncollection.",""],["Reference Standard","The acquired datasets (as described above)\nrepresent the ground truth for the training\nand validation. Input data was\nretrospectively created from the ground\ntruth by data manipulation and\naugmentation.\nThis process includes further under-\nsampling of the data by discarding k-space\nlines, lowering of the SNR level by addition\nRestricted of noise and mirroring of k-space\ndata.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation. k-space data has\nbeen cropped such that only the\ncenter part of the data was used\nas input. With this method\ncorresponding low-resolution\ndata as input and high-resolution\ndata as output / ground truth\nwere created for training and\nvalidation."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p12-t1","doc_id":"K231560","page_num":12,"bbox":[72.48,491.64,508.68,759.36],"n_rows":2,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["Deep Resolve Boost EPI Diffusion","[1] Bae SH et al., Clinical feasibility of accelerated diffusion\nweighted imaging of the abdomen with deep learning\nreconstruction: Comparison with conventional diffusion\nweighted imaging, Eur J Radiol., 154 (2022)\n[2] Lee EJ et al., Feasibility of deep learning k-space-to-image\nreconstruction for diffusion weighted imaging in patients\nwith breast cancers: Focus on image quality and reduced scan\ntime, Eur J Radiol., 157 (2022)\n[3] Afat S et al., Acquisition time reduction of diffusion-\nweighted liver imaging using deep learning image\nreconstruction. Diagn Interv Imaging, (2022).\n[4] Benkert T et al., Improved Clinical Diffusion Weighted\nImaging by Combining Deep Learning Reconstruction, Partial\nFourier, and Super Resolution, ISMRM (2022)\n[5] Kim et al., Deep Learning–Accelerated Liver Diffusion-\nWeighted Imaging - Intraindividual Comparison and\nAdditional Phantom Study of Free-Breathing and Respiratory-\nTriggering Acquisitions, Invest Radiol (2023)"]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231560-p13-t0","doc_id":"K231560","page_num":13,"bbox":[72.48,71.04,508.68,563.4],"n_rows":2,"n_cols":2,"columns":["Deep Resolve Boost HASTE","[1] Herrmann J et al., Diagnostic Confidence and\nFeasibility of a Deep Learning Accelerated HASTE Sequence of\nthe Abdomen in a Single Breath-Hold, Investigative\nRadiology, Volume 56, Number 5, May 2021.\n[2] Shanbhogue K et al. Accelerated single-shot T2-\nweighted fat-suppressed (FS) MRI of the liver with deep\nlearning-based image reconstruction: qualitative and\nquantitative comparison of image quality with conventional\nT2-weighted FS sequence. Eur Radiol. 2021 May 7.\n[3] Herrmann J et al., Development and Evaluation of\nDeep Learning-Accelerated Single-Breath-Hold Abdominal\nHASTE at 3 T Using Variable Refocusing Flip Angles. Invest\nRadiol. 2021 Apr 22.\n[4] Han S et al., Evaluation of HASTE T2 weighted image\nwith reduced echo time for detecting focal liver lesions in\npatients at risk of developing hepatocellular carcinoma. Eur J\nRadiol. 2022 Nov 1;157:110588.\n[5] Mule S et al., Fast T2-weighted liver MRI: Image\nquality and solid focal lesions conspicuity using a deep\nlearning accelerated single breath-hold HASTE fat-\nsuppressed sequence. Diagn Interv Imaging. 2022\nOct;103(10):479-485.\n[6] Ginocchio LA et al., Accelerated T2-weighted MRI of\nthe liver at 3 T using a single-shot technique with deep\nlearning-based image reconstruction: impact on the image\nquality and lesion detection. Abdom Radiol (NY). 2022 Sep 28.\n[7] Herrmann J et al., Comprehensive clinical evaluation\nof a deep learning-accelerated, single-breath-hold abdominal\nHASTE at 1.5 T and 3 T. Acad Radiol. 2022 Apr 22:S1076-\n6332(22)00195-7.\n[8] Ichinohe F. et al., Usefulness of Breath-Hold Fat-\nSuppressed T2-Weighted Images With Deep Learning–Based\nReconstruction of the Liver, Invest Radiol., 2022"],"rows":[["Deep Resolve Boost HASTE","[1] Herrmann J et al., Diagnostic Confidence and\nFeasibility of a Deep Learning Accelerated HASTE Sequence of\nthe Abdomen in a Single Breath-Hold, Investigative\nRadiology, Volume 56, Number 5, May 2021.\n[2] Shanbhogue K et al. Accelerated single-shot T2-\nweighted fat-suppressed (FS) MRI of the liver with deep\nlearning-based image reconstruction: qualitative and\nquantitative comparison of image quality with conventional\nT2-weighted FS sequence. Eur Radiol. 2021 May 7.\n[3] Herrmann J et al., Development and Evaluation of\nDeep Learning-Accelerated Single-Breath-Hold Abdominal\nHASTE at 3 T Using Variable Refocusing Flip Angles. Invest\nRadiol. 2021 Apr 22.\n[4] Han S et al., Evaluation of HASTE T2 weighted image\nwith reduced echo time for detecting focal liver lesions in\npatients at risk of developing hepatocellular carcinoma. Eur J\nRadiol. 2022 Nov 1;157:110588.\n[5] Mule S et al., Fast T2-weighted liver MRI: Image\nquality and solid focal lesions conspicuity using a deep\nlearning accelerated single breath-hold HASTE fat-\nsuppressed sequence. Diagn Interv Imaging. 2022\nOct;103(10):479-485.\n[6] Ginocchio LA et al., Accelerated T2-weighted MRI of\nthe liver at 3 T using a single-shot technique with deep\nlearning-based image reconstruction: impact on the image\nquality and lesion detection. Abdom Radiol (NY). 2022 Sep 28.\n[7] Herrmann J et al., Comprehensive clinical evaluation\nof a deep learning-accelerated, single-breath-hold abdominal\nHASTE at 1.5 T and 3 T. Acad Radiol. 2022 Apr 22:S1076-\n6332(22)00195-7.\n[8] Ichinohe F. et al., Usefulness of Breath-Hold Fat-\nSuppressed T2-Weighted Images With Deep Learning–Based\nReconstruction of the Liver, Invest Radiol., 2022"],["GRE_PC","[1] Guenthner C. et al. Ristretto MRE: A generalized multi-\nshot GRE-MRE sequence. NMR Biomed 2019; 32:e4049."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231570-p6-t0","doc_id":"K231570","page_num":6,"bbox":[56.88,212.88,532.44,348.12],"n_rows":8,"n_cols":4,"columns":["","Subject Device","Predicate Device\n(K182130)","Reference Device (K200873)"],"rows":[["","Subject Device","Predicate Device\n(K182130)","Reference Device (K200873)"],["Device Name","StrokeViewer Perfusion","iSchemaView Rapid","StrokeViewer HALO"],["Proprietary Trade\nName","StrokeViewer Perfusion","Rapid","HALO (LVO Triaging)"],["Product Classification","LLZ","LLZ","QAS"],["Classification Name","System, Image\nProcessing, Radiological","System, Image\nProcessing,\nRadiological","Radiological Computer Aided\nTriage and Notification Software"],["Classification Panel","Radiology","Radiology","Radiology"],["CFR Section","21 CFR §892.2050","21 CFR §892.2050","21 CFR §892.2080"],["Device Class","Class II","Class II","Class II"]],"caption_candidate":"2 Device Name and Classification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231570-p8-t0","doc_id":"K231570","page_num":8,"bbox":[56.88,605.04,538.44,760.68],"n_rows":5,"n_cols":5,"columns":["Date of Entry","Recognition\nNumber","Standards\nDeveloping\nOrganization","Standard\nDesignation\nNumber and Date","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","Standards\nDeveloping\nOrganization","Standard\nDesignation\nNumber and Date","Title of Standard"],["12/23/2019","5-125","ISO","14971:2019","Medical devices – Applications of risk\nmanagement to medical devices"],["07/06/2020","5-129","IEC","62366-\n1:2015+AMD1:202\n0 (Consolidated\ntext)","Medical devices Part 1: Application of\nusability engineering to medical\ndevices, including Amendment 1"],["01/14/2019","13-79","IEC","62304:2006/A1:20\n16","Medical device software – Software\nlifecycle processes (including\nAmendment 1 (2016))"],["12-19-2022","12-349","NEMA","PS 3.1 – 3.20\n2022d","Digital Imaging and Communications in\nMedicine (DICOM) Set"]],"caption_candidate":"StrokeViewer to uphold claims of safety and effectiveness of the intended purpose of the device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231570-p9-t0","doc_id":"K231570","page_num":9,"bbox":[56.88,69.24,538.44,169.2],"n_rows":3,"n_cols":5,"columns":["12/20/2021","5-134","ISO","15223-1 Fourth\nedition 2021-07","Medical devices – Symbols to be used\nwith information to be supplied by the\nmanufacturer – Part 1: General\nrequirements"],"rows":[["12/20/2021","5-134","ISO","15223-1 Fourth\nedition 2021-07","Medical devices – Symbols to be used\nwith information to be supplied by the\nmanufacturer – Part 1: General\nrequirements"],["12/19/2022","5-135","ISO","20417 First edition\n2021-04 Corrected\nversion 2021-12","Medical devices – Information to be\nsupplied by the manufacturer"],["08/21/2017","13-97","IEC","82304-1 Edition\n1.0 2016-10","Health Software – Part 1: General\nrequirements for product safety"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231570-p9-t1","doc_id":"K231570","page_num":9,"bbox":[56.88,208.44,538.44,309.48],"n_rows":5,"n_cols":2,"columns":["Standard Designation Number","Title of Standard"],"rows":[["Standard Designation Number","Title of Standard"],["ISO 13485:2016","Medical Devices—Quality Management Systems—Requirements for\nRegulatory Purposes"],["ISO/IEC 27001:2022","Information Security, Cybersecurity and privacy protection—Information\nsecurity management systems—Requirements"],["NEN 7510-1:2017+A1:2020","Health informatics—Information security management in healthcare—\nPart 1: Management System"],["NEN 7510-2:2017","Health informatics—Information security management in healthcare—\nPart 2: Controls"]],"caption_candidate":"followed:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p7-t0","doc_id":"K231587","page_num":7,"bbox":[94.09,158.84,499.54,299.16],"n_rows":8,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Vida with syngo\nMR XA50A","K213693, cleared on February\n25, 2022","LNH\nLNI, MOS","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Prisma with\nsyngo MR XA30A","K202014 cleared,\nSeptember 08, 2020","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Sola with syngo\nMR XA51A","K221733 cleared, September\n13, 2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Free.Max with\nsyngo MR XA50A","K220575 cleared, June 22,\n2022","LNH,\nLNI, MOS","Siemens Shenzhen\nMagnetic Resonance Ltd."]],"caption_candidate":"following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p7-t1","doc_id":"K231587","page_num":7,"bbox":[94.09,490.52,499.54,712.56],"n_rows":16,"n_cols":4,"columns":["Hardware","Subject Devices","Predicate Device","Reference Devices"],"rows":[["Hardware","Subject Devices","Predicate Device","Reference Devices"],["","","",""],["","MAGNETOM Cima.X","MAGNETOM Vida with","MAGNETOM Sola with"],["","with software syngo MR","syngo MR XA50A","syngo MR XA51A"],["","XA61A","(K213693)","(K221733)"],["","","","MAGNETOM Prisma with"],["","","","syngo MR XA30A"],["","","","(K202014)"],["","","","MAGNETOM Free.Max"],["","","","with syngo MR XA50A"],["","","","(K220575)"],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","New or modified features as\nlisted in the Device\nDescription above","Yes","Yes"],["Patient Table","Yes","Yes","Yes"]],"caption_candidate":"Summary hardware comparison table for the subject and predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p8-t0","doc_id":"K231587","page_num":8,"bbox":[93.96,66.9,500.43,230.4],"n_rows":12,"n_cols":4,"columns":["Multi-Nuclear\nOption - Supported\nNuclei","Yes","Yes","Yes"],"rows":[["Multi-Nuclear\nOption - Supported\nNuclei","Yes","Yes","Yes"],["Computer","Yes","Yes","Yes"],["","Modified","",""],["Coils","Yes","Yes","Yes"],["","New, based on predicate:","",""],["","Tx/Rx Knee 15, Tx/Rx Knee 15","",""],["","Flare, 4 Ch BI","",""],["","Breast coil (already introduced","",""],["","with reference system)","",""],["Other HW\ncomponents","New or modified HW","Yes","Yes"],["","components as listed in the","",""],["","Device Description above","",""]],"caption_candidate":"5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p8-t1","doc_id":"K231587","page_num":8,"bbox":[93.96,256.56,500.43,710.16],"n_rows":43,"n_cols":3,"columns":["Software","Subject Device","Predicate Device"],"rows":[["Software","Subject Device","Predicate Device"],["","",""],["","MAGNETOM Cima.X with software","MAGNETOM Vida with syngo"],["","syngo MR XA61A","MR XA50A"],["","","(K213693)"],["Sequences","",""],["SE-based pulse sequence types","New feature as listed in the Device","Yes"],["","Description above",""],["GRE-based/Steady-State pulse","New or modified pulse sequences","Yes"],["","as listed in the Device Description",""],["sequence types","",""],["","above",""],["","",""],["EPI-based pulse sequence types","New features as listed in the Device","Yes"],["","Description above",""],["Spectroscopy pulse sequence types","Yes","Yes"],["Feature and Applications","",""],["Other features and","Modified features and","Yes"],["applications such as:","",""],["-Application Suites","",""],["","applications as listed in the Device",""],["-myExam Assists","",""],["","Description above",""],["-Other Imaging","",""],["","",""],["Applications","",""],["User interface and user interaction","Yes","Yes"],["Viewing and post-processing","New or modified viewing and post-","Yes"],["","processing features as listed in the",""],["","Device Description above",""],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["Scanning","Modified and new features and","Yes"],["","applications as listed in the",""],["","Cover letter, Device Description",""],["","and Substantial Equivalence",""],["","Comparison Tables",""],["Reconstruction","New feature","Yes"],["","as listed in the Device Description",""],["","above",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"Summary software comparison table for the subject and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p9-t0","doc_id":"K231587","page_num":9,"bbox":[94.17,213.48,464.72,446.04],"n_rows":10,"n_cols":3,"columns":["","Tested Hardware or",""],"rows":[["","Tested Hardware or",""],["Performance Test","","Source/Rationale for test"],["","Software",""],["","",""],["Software verification\nand validation","New or modified software\nfeatures","Guidance for the Content of Premarket\nSubmissions for Software Contained in\nMedical Devices"],["Sample clinical images","New or modified software\nfeatures","Guidance for submission of Premarket\nNotifications for Magnetic Resonance\nDiagnostic Devices"],["Image quality\nassessment by sample\nclinical images","- new / modified pulse\nsequence types.\n- comparison images\nbetween the new / modified\nfeatures and the predicate\ndevice features",""],["Performance bench test","new and modified hardware",""],["Electrical, mechanical,\nstructural, and related\nsystem safety test","System as a whole","- AAMI / ANSI ES60601-1\n- IEC 60601-2-33"],["Electrical safety and\nelectromagnetic\ncompatibility (EMC)","System as a whole","IEC 60601-1-2"]],"caption_candidate":"The following performance testing was conducted on the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p9-t1","doc_id":"K231587","page_num":9,"bbox":[94.17,515.54,499.39,589.38],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for coils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance Diagnostic\nDevices"]],"caption_candidate":"reference devices and can be reused for the subject device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p10-t0","doc_id":"K231587","page_num":10,"bbox":[94.08,135.72,504.12,714.36],"n_rows":7,"n_cols":3,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:"],["Training and Validation data"," TSE: more than 25,000 slices\n HASTE: pre-trained on the\nTSE dataset and refined with\nmore than 10,000 HASTE\nslices\n EPI Diffusion: more than\n1,000,000 slices\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength.","on more than 10,000 high\nresolution 2D images.\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength."],["Test Statistics and Test Results\nSummary","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR) and\nstructural similarity index (SSIM).\nMost importantly, the\nperformance was evaluated by\nvisual comparisons to evaluate\ne.g., aliasing artifacts, image\nsharpness and denoising levels.","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR),\nstructural similarity index (SSIM),\nand perceptual loss. In addition,\nthe feature has been verified\nand validated by inhouse tests.\nThese tests include visual rating\nand an evaluation of image\nsharpness by intensity profile\ncomparisons of reconstructions\nwith and without Deep Resolve\nSharp."],["Equipment","1.5T and 3T MRI systems",""],["Clinical Subgroups","No clinical subgroups have been defined for the collected dataset.",""],["Demographic Distribution","Due to reasons of data privacy, we did not record gender, age and\nethnicity during data collection.",""],["Reference Standard","The acquired datasets (as\ndescribed above) represent the\nground truth for the training and\nvalidation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation and augmentation.\nThis process includes further\nunder-sampling of the data by\ndiscarding k-space lines,\nlowering of the SNR level by\naddition Restricted of noise and\nmirroring of k-space data.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation. k-space data has\nbeen cropped such that only the\ncenter part of the data was used\nas input. With this method\ncorresponding low-resolution\ndata as input and high-resolution\ndata as output / ground truth\nwere created for training and\nvalidation."]],"caption_candidate":"the AI features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p11-t0","doc_id":"K231587","page_num":11,"bbox":[94.08,144.96,504.12,733.44],"n_rows":3,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["Deep Resolve Boost EPI Diffusion","[14_1] Bae SH et al., Clinical feasibility of accelerated\ndiffusion weighted imaging of the abdomen with deep\nlearning reconstruction: Comparison with conventional\ndiffusion weighted imaging, Eur J Radiol., 154 (2022)\n[14_2] Lee EJ et al., Feasibility of deep learning k-\nspace-to-image reconstruction for diffusion weighted\nimaging in patients with breast cancers: Focus on\nimage quality and reduced scan time, Eur J Radiol., 157\n(2022)\n[14_3] Afat S et al., Acquisition time reduction of\ndiffusion-weighted liver imaging using deep learning\nimage reconstruction. Diagn Interv Imaging, (2022).\n[14_4] Benkert T et al., Improved Clinical Diffusion\nWeighted Imaging by Combining Deep Learning\nReconstruction, Partial Fourier, and Super Resolution,\nISMRM (2022)"],["Deep Resolve Boost HASTE","[14_6] Herrmann J et al., Diagnostic Confidence and\nFeasibility of a Deep Learning Accelerated HASTE\nSequence of the Abdomen in a Single Breath-Hold,\nInvestigative Radiology, Volume 56, Number 5, May\n2021.\n[14_7] Shanbhogue K et al. Accelerated single-shot T2-\nweighted fat-suppressed (FS) MRI of the liver with\ndeep learning-based image reconstruction: qualitative\nand quantitative comparison of image quality with\nconventional T2-weighted FS sequence. Eur Radiol.\n2021 May 7.\n[14_8] Herrmann J et al., Development and Evaluation\nof Deep Learning-Accelerated Single-Breath-Hold\nAbdominal HASTE at 3 T Using Variable Refocusing Flip\nAngles. Invest Radiol. 2021 Apr 22.\n[14_9] Han S et al., Evaluation of HASTE T2 weighted\nimage with reduced echo time for detecting focal liver\nlesions in patients at risk of developing hepatocellular\ncarcinoma. Eur J Radiol. 2022 Nov 1;157:110588.\n[14_10] Mule S et al., Fast T2-weighted liver MRI:\nImage quality and solid focal lesions conspicuity using\na deep learning accelerated single breath-hold HASTE\nfat-suppressed sequence. Diagn Interv Imaging. 2022\nOct;103(10):479-485.\n[14_11] Ginocchio LA et al., Accelerated T2-weighted\nMRI of the liver at 3 T using a single-shot technique\nwith deep learning-based image reconstruction:"]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231587-p12-t0","doc_id":"K231587","page_num":12,"bbox":[94.08,66.78,504.12,630.9],"n_rows":6,"n_cols":2,"columns":["","impact on the image quality and lesion detection.\nAbdom Radiol (NY). 2022 Sep 28.\n[14_12] Herrmann J et al., Comprehensive clinical\nevaluation of a deep learning-accelerated, single-\nbreath-hold abdominal HASTE at 1.5 T and 3 T. Acad\nRadiol. 2022 Apr 22:S1076-6332(22)00195-7.\n[14_13] Ichinohe F. et al., Usefulness of Breath-Hold\nFat-Suppressed T2-Weighted Images With Deep\nLearning–Based Reconstruction of the Liver, Invest\nRadiol., 2022"],"rows":[["","impact on the image quality and lesion detection.\nAbdom Radiol (NY). 2022 Sep 28.\n[14_12] Herrmann J et al., Comprehensive clinical\nevaluation of a deep learning-accelerated, single-\nbreath-hold abdominal HASTE at 1.5 T and 3 T. Acad\nRadiol. 2022 Apr 22:S1076-6332(22)00195-7.\n[14_13] Ichinohe F. et al., Usefulness of Breath-Hold\nFat-Suppressed T2-Weighted Images With Deep\nLearning–Based Reconstruction of the Liver, Invest\nRadiol., 2022"],["GRE_PC","[14_14] Guenthner C. et al. Ristretto MRE: A\ngeneralized multi-shot GRE-MRE sequence. NMR\nBiomed 2019; 32:e4049."],["Ghost reduction (DPG)","[14_24] Hoge WS, Polimeni JR. Dual-polarity GRAPPA\nfor simultaneous reconstruction and ghost correction of\necho planar imaging data. Magn Reson Med. 2016\nJul;76(1):32-44. doi: 10.1002/mrm.25839. Epub 2015"],["Fleet Reference Scan","[14_5] Polimeni JR, Bhat H, Witzel T, Benner T, Feiweier\nT, Inati SJ, Renvall V, Heberlein K, Wald LL. Reducing\nsensitivity losses due to respiration and motion in\naccelerated echo planar imaging by reordering the\nautocalibration data acquisition. Magn Reson Med.\n2016 Feb;75(2):665-79. doi: 10.1002/mrm.25628. Epub\n2015 Mar 23. PMID: 25809559; PMCID: PMC4580494."],["SAMER","[14_25] D. Polak, D N. Splitthoff, etc. Scout accelerated\nmotion estimation and reduction (SAMER). Magn\nReson Med. 2022 Jan;87(1):163-178.\n[14_26] M. Lang, A. Tabari, etc. Clinical Evaluation of\nScout Accelerated Motion Estimation and Reduction\nTechnique for 3D MR Imaging in the Inpatient and\nEmergency Department Settings. American Journal of\nNeuroradiology 2023 Jan."],["Complex Averaging","[14_22] Walsh DO, Gmitro AF, Marcellin MW. Adaptive\nreconstruction\nof phased array MR imagery. Magn Reson Med. 2000\nMay\n1;43(5):682–90.\n[14_23] Kordbacheh H, Seethamraju RT, Weiland E,\nKiefer B, Nickel MD, Chulroek T, et al. Image quality and\ndiagnostic accuracy of complex-averaged high b value\nimages in diffusion-weighted MRI of prostate cancer.\nAbdom Radiol (NY). 2019;44(6):2244–53."]],"caption_candidate":"9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p5-t0","doc_id":"K231617","page_num":5,"bbox":[72.24,86.46,500.27,784.44],"n_rows":52,"n_cols":4,"columns":["4. Legally Marketed Predicate Device","","",""],"rows":[["4. Legally Marketed Predicate Device","","",""],["","","",""],["4.1 Predicate Device","","",""],["","","",""],["Trade name:","MAGNETOM","Free.Max",""],["510(k) Number:","K220575","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device"],["","(MRDD)","",""],["Classification Panel:","Radiology","",""],["CFR Code:","21 CFR § 892",".1000",""],["Classification:","II","",""],["Product Code:","Primary: LNH","",""],["","Secondary: M","OS",""],["","","",""],["Trade name:","MAGNETOM","Free.Star",""],["510(k) Number:","K220575","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device"],["","(MRDD)","",""],["Classification Panel:","Radiology","",""],["CFR Code:","21 CFR § 892",".1000",""],["Classification:","II","",""],["Product Code:","Primary: LNH","",""],["","Secondary: M","OS",""],["","","",""],["4.2 Reference Device","","",""],["Trade name:","MAGNETOM","Sola",""],["510(k) Number:","K221733","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device"],["","(MRDD)","",""],["Classification Panel:","Radiology","",""],["CFR Code:","21 CFR § 892",".1000",""],["Classification:","II","",""],["Product Code:","Primary: LNH","",""],["","Secondary: L","NI, MOS",""],["","","",""],["Trade name:","MAGNETOM","Amira",""],["510(k) Number:","K223343","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device"],["","(MRDD)","",""],["Classification Panel:","Radiology","",""],["CFR Code:","21 CFR § 892",".1000",""],["Classification:","II","",""],["Product Code:","Primary: LNH","",""],["","Secondary: L","NI, MOS",""],["","","",""],["Trade name:","MAGNETOM","Vida",""],["510(k) Number:","K213693","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device"],["","(MRDD)","",""],["Classification Panel:","Radiology","",""],["CFR Code:","21 CFR § 892",".1000",""],["Classification:","II","",""]],"caption_candidate":"4. Legally Marketed Predicate Device","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231617-p9-t0","doc_id":"K231617","page_num":9,"bbox":[72.96,89.91,502.56,306.62],"n_rows":11,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Free.Max\nwith syngo MR XA50A","K220575,\ncleared on June 24, 2022","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["MAGNETOM Free.Star with\nsyngo MR XA50A","K220575,\ncleared on June 24, 2022","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["","FDA Clearance Number","Product",""],["Reference Device","","","Manufacturer"],["","and Date","Code",""],["","","",""],["MAGNETOM Sola with\nsyngo MR XA51A","K221733, cleared on\nSeptember 13, 2022","LNH,\nLNI,\nMOS","Siemens Healthcare GmbH"],["MAGNETOM Amira with\nsyngo MR XA50M","K223343, cleared on March\n23, 2023","LNH,\nLNI,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["MAGNETOM Vida with\nsyngo MR XA50A","K213693, cleared on\nFeburary 25, 2022","LNH,\nLNI,\nMOS","Siemens Healthcare GmbH"]],"caption_candidate":"Table 2. Predicate devices and reference devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p9-t1","doc_id":"K231617","page_num":9,"bbox":[72.96,589.47,522.88,783.3],"n_rows":11,"n_cols":5,"columns":["","Subject Devices","","Predicate Devices",""],"rows":[["","Subject Devices","","Predicate Devices",""],["","","","",""],["","MAGNETOM","MAGNETOM","MAGNETOM","MAGNETOM"],["Hardware","Free.Max with","Free.Star with","Free.Max with","Free.Star with"],["","software syngo MR","software syngo MR","Error! Reference","Error! Reference"],["","XA60A","XA60A","source not found.","source not found."],["","","","(K220575)","(K220575)"],["Magnet\nSystem","Yes, same as predicate device","","Yes",""],["RF System","Yes, same as predicate device","","Yes",""],["Transmission\ntechnique –\nRF Body Coil","Yes, same as predicate device","","Yes",""],["Gradient\nSystem","Yes, same as predicate device","","Yes",""]],"caption_candidate":"Table 3. Hardware Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p10-t0","doc_id":"K231617","page_num":10,"bbox":[72.69,71.1,522.57,247.22],"n_rows":4,"n_cols":3,"columns":["Patient Table","Yes, same as predicate device","Yes"],"rows":[["Patient Table","Yes, same as predicate device","Yes"],["Computer","Yes, modified compared to predicate\ndevice:\n-new host computer hardware\n-new MaRS hardware","Yes"],["Coils","Yes,\nnew coil compared to predicate device:\nContour Knee coil","Yes"],["Other HW\ncomponents","Yes,\nModified compared to predicate device:\n-myExam 3D Camera\nNew compared to predicate device:\n-Respiratory Sensor","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p10-t1","doc_id":"K231617","page_num":10,"bbox":[72.69,289.69,522.57,757.68],"n_rows":15,"n_cols":5,"columns":["","Subject Devices","","Predicate Devices",""],"rows":[["","Subject Devices","","Predicate Devices",""],["","","","",""],["","MAGNETOM","MAGNETOM","MAGNETOM","MAGNETOM"],["Software","Free.Max with","Free.Star with","Free.Max with","Free.Star with"],["","software syngo MR","software syngo","software syngo","syngo MR XA50A"],["","XA60A","MR XA60A","MR XA50A","(K220575)"],["","","","(K220575)",""],["Injector coupling","Yes,\nnew feature migrated from reference device\nMAGNETOM Sola with syngo MR XA51A\n(K221733)","","No",""],["Respiratory Sensor\nSupport","Yes,\nnew feature migrated from reference device\nMAGNETOM Amira with syngo MR XA50M\n(K223343)","","No",""],["myExam RT Assist","Yes,\nnew feature migrated\nfrom reference device\nMAGNETOM Sola with\nsyngo MR XA51A\n(K221733)","No","No",""],["myExam AutoPilot\nHip","Yes, new feature","","No",""],["Deep Resolve\nBoost","Yes,\nnew feature migrated from reference device\nMAGNETOM Vida with syngo MR XA50A\n(K213693)","","No",""],["Complex\nAveraging","Yes, new feature","","No",""],["HASTE_Interactive","Yes,\nnew feature migrated\nfrom reference device\nMAGNETOM Sola with\nsyngo MR XA51A\n(K221733)","No","No",""],["BEAT_Interactive","Yes,\nnew feature migrated\nfrom reference device\nMAGNETOM Sola with\nsyngo MR XA51A\n(K221733)","No","No",""]],"caption_candidate":"Table 4. Software Features Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p11-t0","doc_id":"K231617","page_num":11,"bbox":[72.55,71.1,522.54,216.56],"n_rows":4,"n_cols":4,"columns":["Needle\nIntervention AddIn","Yes,\nnew feature migrated\nfrom reference device\nMAGNETOM Sola with\nsyngo MR XA51A\n(K221733)","No","No"],"rows":[["Needle\nIntervention AddIn","Yes,\nnew feature migrated\nfrom reference device\nMAGNETOM Sola with\nsyngo MR XA51A\n(K221733)","No","No"],["Deep Resolve\nSharp","Yes, modified compared to predicate\ndevice","","Yes"],["Deep Resolve\nGain","Yes, modified compared to predicate\ndevice","","Yes"],["SMS Averaging","Yes, modified compared to predicate\ndevice","","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p11-t1","doc_id":"K231617","page_num":11,"bbox":[72.55,268.37,503.61,387.62],"n_rows":3,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Sample clinical images","New and modified software\nfeatures, pulse sequence types","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance\nDiagnostic Devices"],["Software verification and\nvalidation","New and modified software\nfeatures","Guidance for the Content of\nPremarket Submissions for\nSoftware Contained in Medical\nDevices"]],"caption_candidate":"The following performance testing was conducted on the subject devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231617-p12-t0","doc_id":"K231617","page_num":12,"bbox":[72.61,71.19,503.64,651.58],"n_rows":16,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognition","Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/\nEMC)","C1:2009/(R)2012 and\nA2:2010/(R)2012 (Consolidated\nText) Medical electrical\nequipment - Part 1: General\nrequirements for basic safety\nand essential performance (IEC\n60601-1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012","ANSI AAMI"],["19-36","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2:2014 +\nAMD1:2020","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-125","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third Edition\n2 019-12","ISO"],["5-129","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1: 2015 +\nAMD1:2020","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","IEC 62304:2006 +\nAMD1:2015","ANSI AAMI\nIEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2014)","NEMA"],["12-342","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set 03/16/2012\nRadiology","PS 3.1 - 3.20\n(2021e)","NEMA"],["2-258","Biocompati\nbility","biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process\n(Biocompatibility)","10993-1:2018","AAMI\nANSI\nISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p6-t0","doc_id":"K231631","page_num":6,"bbox":[36.0,96.36,576.0,716.76],"n_rows":2,"n_cols":4,"columns":["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],"rows":[["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],["Intended Use /\nIndications for Use","The HealthCCSng device\nis intended for use as a\nnon-invasive post-\nprocessing software to\nevaluate calcified plaques\nin the coronary arteries,\nwhich present a risk for\ncoronary artery disease.\nThe software generates an\nestimated coronary artery\ncalcium detection\ncategory. The\nHealthCCSng device\nanalyzes existing non-\ncardiac-gated CT studies\nthat include the heart of\nadult patients above the\nage of 30. The device\ngenerates a three-\ncategory output\nrepresenting the estimated\nquantity of calcium\ndetected together with\npreview axial images of the\ndetected calcium meant for\ninformational purposes\nonly. The device output will\nbe available to the\nradiologist as part of their\nstandard workflow. The\nHealthCCSng results are\nnot intended to be used on\na stand-alone basis for risk\nattribution, clinical\ndecision-making or\notherwise preclude clinical\nassessment of CT studies.","iCAC is a software device\nintended for use in\nestimating presence and\nquantity of coronary artery\ncalcium for patients aged\n30 years and above during\nroutine care. The device\nautomatically analyzes\nnon-gated, non-contrast\nchest computed\ntomography (CT) images\ncollected during routine\ncare and outputs a visual\nrepresentation of\nestimated coronary artery\ncalcium segmentation\n(intended for informational\npurposes only) and both\nexact and four-category\nquantitative estimates of\nthe patient’s coronary\nartery calcium burden in\nAgatston units.\nThe output of the subject\ndevice is made available to\nthe physician on-demand\nas part of his or her\nstandard workflow. The\ndevice-generated calcium\nscore or score group can\nbe viewed in the patient\nreport at the discretion of\nthe physician, and the\nphysician also has the\noption of viewing the\ndevice-generated calcium\nsegmentation in a","BriefCase-Quantification is a\nsoftware intended for use in\nthe analysis of non-cardiac-\ngated non-contrast CT\n(NCCT) images that include\nthe heart in adult patients\naged 30 and older.\nThe device is intended to\nassist physicians by\nproviding the user with a four-\ncategory Coronary Artery\nCalcification (CAC) of\nplaques, which present a risk\nfor coronary artery disease,\ntogether with preview axial\nimages of the detected\ncalcium meant for\ninformational purposes only.\nThe BriefCase-Quantification\nresults are not intended to be\nused on a stand-alone basis\nfor clinical decision-making or\notherwise preclude clinical\nassessment of cases.\nClinicians are responsible for\nviewing full images per the\nstandard of care."]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p7-t0","doc_id":"K231631","page_num":7,"bbox":[36.0,72.24,576.0,681.0],"n_rows":5,"n_cols":4,"columns":["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],"rows":[["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],["","","diagnostic image viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or\nthe original chest CT scan;\nboth are still available to be\nviewed and used at the\ndiscretion of the physician.\nThe device is intended to\nprovide information to the\nphysician to provide\nassistance during review of\nthe patient’s case. Results\nof the subject device are\nnot intended to be used on\na stand-alone basis and\nare solely intended to aid\nand provide information to\nthe physician. In all cases,\nfurther action taken on a\npatient should only come\nat the recommendation of\nthe physician after further\nreviewing the patient’s\nresults.",""],["User population","Radiologists","Interpreting physicians","Hospital networks and\nappropriately trained medical\nspecialists"],["Anatomical region\nof interest","Chest","Chest","Chest"],["Data acquisition\nprotocol","Non-cardiac-gated CT\nstudies that include the\nheart","Non-gated, non-contrast\nchest CT images","Non-cardiac-gated non-\ncontrast CT images that\ninclude the heart"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p8-t0","doc_id":"K231631","page_num":8,"bbox":[36.0,72.24,576.0,708.96],"n_rows":9,"n_cols":4,"columns":["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],"rows":[["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],["Calcified plaques\nevaluation","Yes","Yes","Yes"],["Interference with\nstandard workflow","No","No","No"],["Algorithm","Artificial intelligence\nalgorithm with database of\nimages.","Artificial intelligence\nalgorithm with database of\nimages.","Artificial intelligence\nalgorithm with database of\nimages."],["Slice Thickness","Up to 3.0 mm","Up to 5.0 mm","Up to 5.0 mm"],["Patient population","Patients aged 30 and older","Patients aged 30 and older","Patients aged 30 and older"],["Default threshold\nof calcium","130 HU (Hounsfield Units)","130 HU (Hounsfield Units)","130 HU (Hounsfield Units)"],["Report of the\ncalcium score -\noutput","Yes, Coronary Calcium\nDetection Category.\n3 categories:\n● 0-99\n● 10-399\n● >400","Yes, Coronary Calcium\nDetection Category and\nexact Agatston score.\n4 categories (for detection\ncategory):\n● 0\n● 1-99\n● 100-399\n● >_400","Yes, Coronary Calcium\nDetection Category: very low,\nlow, medium, and high.\n● The categories\ncomposing the output\nof the device\ncorrespond with a\nvalidated visual\nassessment\ncategorization of\nnone, mild, moderate,\nand severe in\nagreement with\ncategorized Agatston\nscores indicated in\nthe literature (very\nlow: 0; low: 1-100;\nmedium: 101-400;\nhigh: ≥400)."],["Structure","- HealthCCSng is an\nalgorithm module\nthat receives a\nnon-cardiac-gated\nCT study from the","- The iCAC Device\ntakes as an input\nnon-contrast, non-\ngated chest CT\nscans via DICOM","- BriefCase-\nQuantification, is\nhosted on a cloud\nserver, analyzes\napplicable CT images"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p9-t0","doc_id":"K231631","page_num":9,"bbox":[36.0,72.24,576.0,372.6],"n_rows":2,"n_cols":4,"columns":["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],"rows":[["","Primary Predicate\nDevice HealthCCSng\n(K210085)","Reference Device iCAC\n(K230223)","BriefCase-Quantification\nfor Coronary Artery\nCalcification (CAC)"],["","storage\napplication,\nZebra’s Imaging\nAnalytics Platform\n(IMA).\n- For each CT study\nreceived, the\nsoftware shall\nvalidate there is at\nleast one compliant\nseries in which the\nentire heart is\npresent, and\nperform an\nanalysis.","transfer from the\nclinicians imaging\ndatabase such as\nPACS or DICOM\nrouter.\n- The device uses a\ndeep learning-\nbased computer\nvision algorithm for\nits assessment.","that are acquired on\nCT scanner that are\nforwarded to\nBriefCase-\nQuantification\n- The results of the\nanalysis are exported\nin DICOM format, and\nare sent to a PACS\ndestination for review\nby medical\nspecialists, to assist\nin the evaluation of\nCAC."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p10-t0","doc_id":"K231631","page_num":10,"bbox":[130.61,232.0,481.49,297.52],"n_rows":3,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age","","67.4","","","12.8","","","30","","","69","","","90","","","432*","",""],["","(Years)","","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 2. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p10-t1","doc_id":"K231631","page_num":10,"bbox":[210.17,366.93,402.4,559.64],"n_rows":10,"n_cols":16,"columns":["Ground\nTruth\nResults","","","Gender","","","","","","","","","All","","",""],"rows":[["Ground\nTruth\nResults","","","Gender","","","","","","","","","All","","",""],["","","","Female","","","","","Male","","","","","","",""],["","","","N","","%","","","N","","%","","N","","","%"],["","Very","64","","","62%","","39","","","38%","","103","","100%",""],["","","","64","","62%","","","39","","38%","","103","","",""],["","Low","","","","","","","","","","","","","",""],["","Low","","50","","47%","","","57","","53%","","107","","","100%"],["","Medium","","47","","51%","","","45","","49%","","92","","","100%"],["","High","","54","","41%","","","77","","59%","","131","","","100%"],["","All","","215","","50%","","","218","","50%","","433","","","100%"]],"caption_candidate":"Table 3. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p10-t2","doc_id":"K231631","page_num":10,"bbox":[86.7,614.68,525.34,700.4],"n_rows":7,"n_cols":17,"columns":["","Manufacturer","","","Very Low","","","Low","","","Medium","","High","","","All",""],"rows":[["","Manufacturer","","","Very Low","","","Low","","","Medium","","High","","","All",""],["","","","","","","","","","","","","","","119 (100%)","",""],["","GE","","","30 (25%)","","","27 (23%)","","","29 (24%)","","33 (28%)","","","",""],["","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","110 (100%)","",""],["","Philips","","","20 (18%)","","","36 (33%)","","","28 (25%)","","26 (24%)","","","",""],["","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 4. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p11-t0","doc_id":"K231631","page_num":11,"bbox":[86.71,72.64,525.33,181.28],"n_rows":8,"n_cols":18,"columns":["","Manufacturer","","","Very Low","","","Low","","","Medium","","","High","","","All",""],"rows":[["","Manufacturer","","","Very Low","","","Low","","","Medium","","","High","","","All",""],["","","","","","","","","","","","","","","","52 (100%)","",""],["","Siemens","","","12 (23%)","","","13 (25%)","","","6 (12%)","","","21 (40%)","","","",""],["","","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","152 (100%)","",""],["","Toshiba","","","41 (27%)","","","31 (20%)","","","29 (19%)","","","51 (34%)","","","",""],["","","","","","","","","","","","","","","","","",""],["","Total","","","103 (24%)","","","107 (25%)","","","92 (21%)","","","131 (30%)","","","433 (100%)",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231631-p11-t1","doc_id":"K231631","page_num":11,"bbox":[72.0,382.44,540.0,421.08],"n_rows":3,"n_cols":2,"columns":["","that the results"],"rows":[["","that the results"],["are not intended to be used on a stand-alone basis for clinical decision making or otherwise preclude",""],["clinical assessment",""]],"caption_candidate":"packages with similar technological characteristics and principles of operation, incorporating deep","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231642-p6-t0","doc_id":"K231642","page_num":6,"bbox":[70.55,197.91,541.14,254.16],"n_rows":4,"n_cols":3,"columns":["• Addition of a tracer option. With Veuron-Brain-pAb3, users can select the tracer for beta amyloid.","",""],"rows":[["• Addition of a tracer option. With Veuron-Brain-pAb3, users can select the tracer for beta amyloid.","",""],["","By providing an option (reference region) for tracer, helps users identify appropriate brain regions",""],["","for analysis.",""],["","",""]],"caption_candidate":"patients.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231642-p6-t1","doc_id":"K231642","page_num":6,"bbox":[38.41,280.56,573.68,713.53],"n_rows":9,"n_cols":9,"columns":["","","","","Subject device","","","Predicate device (K213801)",""],"rows":[["","","","","Subject device","","","Predicate device (K213801)",""],["Device name","","","Veuron-Brain-pAb3","","","Veuron-Brain-pAb2","",""],["Manufacturer","","","Heuron Co., Ltd.","","","Heuron Co., Ltd.","",""],["Product code","","","LLZ","","","LLZ","",""],["Indications for use","","","The Veuron-Brain-pAb3 is software for\nthe registration, fusion, display, and\nanalysis of medical images from multiple\nmodalities including MRI and PET. The\nsoftware aids clinicians in the\nassessment and quantification of\npathologies from PET Amyloid scans of\nthe human brain. It enables anatomic\nanalysis and visualization of amyloid\nprotein concentration through the\ncalculation of standard uptake volume\nratio (SUVR) within target regions of\ninterest and comparison to those within\nthe reference regions. The software is\ndeployed via medical imaging\nworkplaces and is organized as a series\nof workflows which are specific to use\nwith radio-tracer and disease\ncombinations.","","","The Veuron-Brain-pAb2 is software\nfor the registration, fusion, display,\nand analysis of medical images from\nmultiple modalities including MRI\nand PET. The software aids\nclinicians in the assessment and\nquantification of pathologies from\nPET Amyloid scans of the human\nbrain. It enables automatic analysis\nand visualization of amyloid protein\nconcentration through the calculation\nof standard uptake volume ratio\n(SUVR) within target regions of\ninterest and comparison to those\nwithin the reference regions. The\nsoftware is deployed via medical\nimaging workplaces and is organized\nas a series of workflows which are\nspecific to use with radiotracer and\ndisease combinations.","",""],["Target anatomical site","","","Brain","","","Brain","",""],["Where used","","","Hospital","","","Hospital","",""],["Design features","","","Import DICOM data\nPerform automatic post-processing\nProvide the user confirmation\nExport the resulting data through a\nnetwork or USB","","","Import DICOM data.\nPerform automatic post-processing.\nProvide the user confirmation\nExport the resulting data through a\nnetwork or USB","",""],["Physical characteristics","","","Software package","","","Software package","",""]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231642-p7-t0","doc_id":"K231642","page_num":7,"bbox":[38.4,72.36,573.68,561.38],"n_rows":12,"n_cols":9,"columns":["","","","","Subject device","","","Predicate device (K213801)",""],"rows":[["","","","","Subject device","","","Predicate device (K213801)",""],["","","","Operates on off-the-shelf hardware\n(multiple vendors)","","","Operates on off-the-shelf hardware\n(multiple vendors)","",""],["Operating system","","","Server: Linux (Ubuntu 18.04 LTS or\nhigher)\nClient: Windows 10 or higher","","","Server: Ubuntu 16.04 LTS or higher\nClient: Windows 10, 64-bit","",""],["Standards","","","ISO 14971\nIEC 62304\nIEC 62366","","","ISO 14971\nIEC 62304\nIEC 62366","",""],["Software verification and validation","","","Tested in accordance with verification\nand validation process and planning. The\ntesting results support that all the system\nrequirements have met their acceptance\ncriteria and are adequate for its intended\nuse.","","","Tested in accordance with\nverification and validation processes\nand planning. The testing results\nsupport that all the system\nrequirements have met their\nacceptance criteria and are\nadequate for its intended use.","",""],["Compatible input data format and\nmodality","","","DICOM & NIfTI\nPET, MRI","","","DICOM & NIfTI\nPET, MRI","",""],["Input patient data","","","Manual through keyboard/mouse","","","Manual through keyboard/mouse","",""],["Output patient data","","","Picture: PNG\nReport: PNG, csv","","","Picture: PNG\nReport: csv","",""],["Study list functionality","","","Search\nImporting\nExporting","","","Search\nImporting\nExporting","",""],["Worklist","","","Yes","","","No","",""],["Tracer option","","","Yes, can select the tracer for beta amyloid\nTracer list\n 18F-Flutemetamol (FMM)\n 18F-Florbetapir (FBP)\n 18F-Florbetaben (FBB)","","","No, cannot select the tracer for beta\namyloid","",""],["Segmentation Algorithm","",""," Calculate the volume by using a\nConvolutional Neural Network\n(CNN) model.\n CNN model has trained 3D brain MR\nimages were collected from one\ndomestic institution","",""," Calculate the volume by using a\nConvolutional Neural Network\n(CNN) model.\n CNN model has trained 3D\nbrain MR images were collected\nfrom one domestic institution.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231668-p2-t0","doc_id":"K231668","page_num":2,"bbox":[257.72,457.25,570.36,554.98],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb,",""],"rows":[["Jessica Lamb,",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231668-p4-t0","doc_id":"K231668","page_num":4,"bbox":[90.0,168.24,552.24,699.0],"n_rows":18,"n_cols":2,"columns":["Submitter Information [21 CFR 807.929(a)(1)]",""],"rows":[["Submitter Information [21 CFR 807.929(a)(1)]",""],["Name","Medical Metrics, Inc."],["Address","2121 Sage Road, Suite 300\nHouston, Texas 77056"],["Phone number","+1 713 850-7500"],["Fax number","+1 713 850-7527"],["Email address","kjohnson@medicalmetrics.com"],["Establishment Registration\nNumber","Pending 510(k) clearance and marketing of device"],["Name of contact person","Kirk Johnson"],["Date prepared","07/05/2023"],["Name of the device [21 CFR 807.92(a)(2)]",""],["Trade name","Spine CAMP™ (1.1)"],["Regulation name","Medical Image Management and Processing System"],["Review panel","Radiology"],["Regulation Number","892.2050"],["Product Code","QIH"],["Legally marketed device to which\nequivalence is claimed\n[21 CFR 807.92(a)(3)]","Spine CAMP™ v1.0 (K221632)"],["Device description\n[21 CFR 807.92(a)(4)]","Spine CAMP™ is a fully-automated image processing software\ndevice. It is designed to be used with X-ray images and is\nintended to aid medical professionals in the measurement and\nassessment of spinal parameters. Spine CAMP™ is capable of\ncalculating distances, angles, linear displacements, angular\ndisplacements, and mathematical combinations of these metrics\nto characterize the morphology, alignment, and motion of the\nspine. These analysis results are presented in the form of\nreports, annotated images, and visualizations of intervertebral\nmotion to support their interpretation."],["Indications for use\n[21 CFR 807.92(a)(5)]","Spine CAMP™ is a fully-automated software that analyzes X-\nray images of the spine to produce reports that contain static\nand/or motion metrics. Spine CAMP™ can be used to obtain\nmetrics from sagittal plane radiographs of the lumbar and/or\ncervical spine and it can be used to visualize intervertebral\nmotion via an image registration method referred to as\n“stabilization.” The radiographic metrics can be used to\ncharacterize and assess spinal health in accordance with\nestablished guidance. For example, common clinical uses\ninclude assessing spinal stability, alignment, degeneration,\nfusion, motion preservation, and implant performance. The\nmetrics produced by Spine CAMP™ are intended to be used to\nsupport qualified and licensed professional healthcare\npractitioners in clinical decision-making for skeletally mature\npatients of age 18 and above."]],"caption_candidate":"510(K) SUMMARY 510(K) #K231668","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231668-p5-t0","doc_id":"K231668","page_num":5,"bbox":[90.0,126.24,552.93,710.64],"n_rows":21,"n_cols":3,"columns":["Summary of the technological characteristics of the device compared to the predicate device\n[21 CFR 807.92(a)(6)]","",""],"rows":[["Summary of the technological characteristics of the device compared to the predicate device\n[21 CFR 807.92(a)(6)]","",""],["Feature","Spine CAMP™ v1.1\n(Subject Device)","Spine CAMP™ v1.0\n(Predicate Device K221632)"],["Classification Name","Automated Radiological Image\nProcessing Software","Automated Radiological Image\nProcessing Software"],["Product Code","QIH","QIH"],["Runs on Server","Yes","Yes"],["Image Input","DICOM","DICOM"],["Anatomical Area","Spine","Spine"],["Image Processing","Vertebral body detection;\nVertebral body landmark\nspecification; Vertebral body\nregistration","Vertebral body detection; Vertebral\nbody landmark specification;\nVertebral body registration"],["Linear Measurements","Yes","Yes"],["Angular Measurements","Yes","Yes"],["2D Motion Analysis","Yes","Yes"],["Image Registration","Yes","Yes"],["Display of Image Alignment /\nStabilization","Yes","Yes"],["Clinical Reporting","Yes","Yes"],["Human Intervention for\nInterpretation","Required","Required"],["Intended User","Trained professionals","Trained professionals"],["Comparison Summary","",""],["Spine CAMP™ v1.1 is designed to utilize the same analysis methodology as the predicate device,\nSpine CAMP™ v1.0 (K221632). The types of inputs and outputs are identical between the two\ndevices. The devices are nearly identical in all respects. The primary differences are:\n Spine CAMP’s primary component, the AI Engine, was updated by retraining its AI models with\nmore imaging for improved generalization and performance. Improvements were also made to the\nAI Engine’s logic to address potential failure modes.\n Spine CAMP™ v1.1 is able to identify the femoral heads in lateral lumbar X-rays in order to\nproduce spinopelvic measurements.\n Configuration capabilities were expanded to derive outputs from the existing calculated results\nand to conditionally format report outputs according to the clinical user’s preferences.","",""],["Performance Data [21 CFR 807.92(b)]","",""],["Summary of bench tests (non-clinical) conducted for determination of substantial equivalence\n[21 CFR 807.92(b)(1)]","",""],["Software verification and validation testing was completed to demonstrate functionality of the device\nacross multiple datasets that had not been used to train any of the AI models. The same methodology\nwas utilized for the performance qualification (PQ) tests for both Spine CAMP 1.1 and its primary\ncomponent, the AI Engine v3.2, as had been previously utilized for the predicate device, Spine CAMP\nv1.0 and its primary component, the AI Engine v3.1. The software functioned as intended and all results\nobserved were as expected.\nAdditional bench testing was performed by evaluating Spine CAMP™ v1.1 performance on a large\ndataset that was previously analyzed by Spine CAMP™ v1.0. Additionally, this dataset was analyzed\nby five experienced operators using the reference device, QMA, for spinopelvic measurements that\nSpine CAMP™ v1.0 was not designed to produce. This dataset included 215 lateral cervical spine","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p6-t0","doc_id":"K231677","page_num":6,"bbox":[127.56,140.4,467.76,209.28],"n_rows":3,"n_cols":9,"columns":["","Item","","","Training Data","","","Test Data",""],"rows":[["","Item","","","Training Data","","","Test Data",""],["","","","9,422","","","","",""],["","","","7,115","","","","",""]],"caption_candidate":"- Sample Size","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p8-t0","doc_id":"K231677","page_num":8,"bbox":[72.32,102.36,769.67,514.63],"n_rows":10,"n_cols":8,"columns":["-","","","","Subject Device","","Primary Predicate Device","Reference Device"],"rows":[["-","","","","Subject Device","","Primary Predicate Device","Reference Device"],["","Manufacturer","","Edgecare Inc.","","","Verathon Inc.","Butterfly Network, Inc."],["Trade Name","","","EdgeFlow UH10","","","BladderScan® PRIME PLUS system","Auto 3D Bladder Volume Tool"],["","510(k) Number","","-","","","K172356","K200980"],["","Product Code","","IYO, ITX, QIH","","","IYO, ITX","IYO, ITX"],["Indications for Use","","","The EdgeFlow UH10 is an ultrasound\ndevice intended to be used for\nmeasuring the urine volume in the\nbladder noninvasively. It is intended\nfor use in professional healthcare\nfacilities, such as hospitals, clinics, by\nqualified and trained healthcare\nprofessionals. The EdgeFlow UH10\nsupports B-mode and harmonic\nimaging modes.","","","The BladderScan® Prime PLUS\nSystem is an ultrasound device\nintended to be used for measuring the\nurine volume in the bladder\nnoninvasively.","The Butterfly Auto 3D Bladder\nVolume Tool is a software application\npackage. It is designed to view,\nquantify and report results acquired on\nButterfly Network ultrasound systems\nfor noninvasive volume measurements\nof the bladder, to support physician\ndiagnosis. Indicated for use in adult\npopulations"],["Contraindications","","","It is contraindicated for fetal use and\nfor use on pregnant patients. And it\nshould not be used by those who are\nallergic to coupling agent and who\nhave abdomen wound and skin disease.","","","The BladderScan® Prime PLUS\nSystem is not intended for fetal use or\nfor use on pregnant patients, patients\nwith ascites, or patients with open skin\nor wounds in the suprapubic region.","The Auto 3D Bladder Volume Tool is\nnot intended for fetal or pediatric use\nor for use on pregnant patients,\npatients with ascites, or patients with\nopen skin or wounds in the suprapubic\nregion."],["","User","","Physicians/Medical Professionals","","","Physicians/Medical Professionals","Physicians/Medical Professionals"],["Target Population","","","Male\nFemale\nPediatric patients","","","Male\nFemale\nPediatric patients","Male\nFemale"],["","Anatomical Site","","Bladder","","","Bladder","Bladder"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p9-t0","doc_id":"K231677","page_num":9,"bbox":[72.32,83.33,769.68,500.82],"n_rows":20,"n_cols":6,"columns":["","Technology","","Neural network technology","Neural network technology","Neural network technology"],"rows":[["","Technology","","Neural network technology","Neural network technology","Neural network technology"],["","Sterility","","Non-sterile","Non-sterile","Non-sterile"],["Power Source","","","Battery Powered\n(Lithium-ion battery)","Battery Powered\n(Lithium-ion battery)","Battery Powered\n(Lithium-ion battery)"],["","Energy Delivered","","Ultrasound","Ultrasound","Ultrasound"],["Measurement Accuracy","","","0-100mL = ±7.5mL\n100-999 mL = ±7.5%","0-100mL = ±7.5mL\n100-999 mL = ±7.5%","0-100mL = ±7.5mL\n100-999 mL = ±7.5%"],["","Measurement Range","","0 to 999 mL","0 to 999 mL","0 to 740 mL"],["","Automatically Calculating Function","","Yes","Yes","Yes"],["","2D/3D Image","","2D","2D","3D"],["","Mode of operation","","B-mode","B-mode","B-mode"],["Transducer Type","","","Electronic Sector Scanning\n(Phased Array)","Mechanical Sector Probe","Electronic Sector Scanning\n(Phased Array)"],["","Sector Angle","","120 degrees","120 degrees","100 degrees"],["","Number of Scan Planes","","2","12","25"],["","Portable","","Yes","Yes","Yes"],["","Display","","LCD","LCD","LCD"],["","Live Scan Image","","Yes","Yes","Yes"],["","Touch Screen","","Yes","Yes","Yes"],["","Calibration","","No Calibration recommended","No Calibration recommended","No Calibration recommended"],["","Data Connections","","USB, Wireless (to PC)","USB, SD card","Wireless ( to Mobile App, Cloud)"],["Accessories","","","Cradle\nPower Adapter\nUSB Cable\nThermal Paper","Printer, battery\nbattery charger\npower cord\nmobile cart","Printer, battery\nbattery charger\npower cord\nmobile cart"],["","FDA Ultrasound Track","","Track 3","Track 1","Track 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p10-t0","doc_id":"K231677","page_num":10,"bbox":[92.25,576.72,503.06,669.78],"n_rows":3,"n_cols":9,"columns":["","No.","","","Test Items","","","Standards",""],"rows":[["","No.","","","Test Items","","","Standards",""],["1","","","General requirement for basic safety and\nessential performance","","","IEC 60601-1:2005+A1:2012","",""],["2","","","General requirement for safety –\nElectromagnetic disturbances","","","IEC 60601-1-2:2014/AMD1:2020","",""]],"caption_candidate":"standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p11-t0","doc_id":"K231677","page_num":11,"bbox":[92.25,140.34,503.06,205.98],"n_rows":3,"n_cols":9,"columns":["","No.","","","Test Items","","","Standards",""],"rows":[["","No.","","","Test Items","","","Standards",""],["1","","","Wireless Coexistence","","","• ANSI IEEE C63.27-2017","",""],["2","","","Wi-Fi Performance Test","","","• In house hold","",""]],"caption_candidate":"performed in accordance with following standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p11-t1","doc_id":"K231677","page_num":11,"bbox":[92.25,282.48,503.06,559.2],"n_rows":3,"n_cols":9,"columns":["","No.","","","Test Items","","","Standards",""],"rows":[["","No.","","","Test Items","","","Standards",""],["1","","","General requirement for safety –\nProgrammable electrical medical systems\n(PEMS)","","","• IEC 62304:2006/A1:2015\n• FDA Guidance (“Guidance for the\nContent of Premarket Submissions for\nSoftware Contained in Medical\nDevices”)\n• FDA Guidance (“Off-the-Shelf Software\nUse in Medical Devices”)","",""],["2","","","Cybersecurity Test","","","• AAMI/UL 29001-:2017\n• IEC 81001-5-1:2021\n• FDA Guidance (“Cybersecurity in\nMedical Devices: Quality System\nConsiderations and Content of Premarket\nSubmissions”)","",""]],"caption_candidate":"performed in accordance with following standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p11-t2","doc_id":"K231677","page_num":11,"bbox":[92.25,635.7,503.06,731.04],"n_rows":4,"n_cols":9,"columns":["","No.","","","Test Items","","","Standards",""],"rows":[["","No.","","","Test Items","","","Standards",""],["1","","","Acoustic Output","","","IEC 60601-2-37:2007/AMD1:2015","",""],["2","","","Measurement Accuracy of Bladder\nVolume","","","Manufacturing SOP","",""],["3","","","Deep Neural Network Performance","","","Manufacturing SOP","",""]],"caption_candidate":"characteristic properties.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231677-p12-t0","doc_id":"K231677","page_num":12,"bbox":[92.26,197.18,503.1,352.89],"n_rows":8,"n_cols":3,"columns":["Gender","Male","34 (37.78%)"],"rows":[["Gender","Male","34 (37.78%)"],["","Female","56 (62.22%)"],["Ages","Less than 19","1 (1.11%)"],["","19 or more","89 (98.89%)"],["BMI","Maximum","36.36"],["","Minimum","17.41"],["","Average","24.34"],["","Variance","10.78"]],"caption_candidate":"Demographics of the clinical trial (Total number of subjects: 90)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231683-p7-t0","doc_id":"K231683","page_num":7,"bbox":[79.99,134.76,533.05,758.76],"n_rows":20,"n_cols":5,"columns":["Technological\ncharacteristics","","inHEART MODELS\n(this submission)","inHEART MODELS\n(K220727)\nPredicate",""],"rows":[["Technological\ncharacteristics","","inHEART MODELS\n(this submission)","inHEART MODELS\n(K220727)\nPredicate",""],["","Basic imaging tools","","",""],["Processing tools","Processing tools","","",""],["Filtering tools","","Yes","Yes",""],["Reformat tools","","Yes","Yes",""],["Meshing tools","","Yes","Yes",""],["Registration tools","","Yes","Yes",""],["","Visualization tools","","",""],["2D viewer","","Yes","Yes",""],["3D viewer","","Yes","Yes",""],["Export capabilities","","Yes","Yes",""],["Reporting of results","","Yes","Yes",""],["","Advanced imaging tools","","",""],["Segmentation","","Yes\n(manually, semi-automated and\nfully automated\nsome segmentations are\nautomated using the new\nsoftware module “inHEART\nModels AI”)","Yes\n(manually and semi-\nautomated)",""],["Quantitative analysis","","Yes","Yes",""],["","Product characteristics","","",""],["Mode of operation","","Standalone and web-based\nsoftware suite","Standalone and web-based\nsoftware suite",""],["Operating system","","macOS for imaging processing\nsoftware module\nWindows or macOS for web-\nbased platform and compatible\nwith following browser: Google\nChrome, Apple Safari (for\nmacOS), Microsoft Edge (for\nWindows)","macOS for imaging\nprocessing software module\nWindows or macOS for\nweb-based platform and\ncompatible with following\nbrowser: Google Chrome,\nApple Safari (for macOS),\nMicrosoft Edge (for\nWindows)",""],["IT network","","A standard internet connection is\nneeded for the web-based\nplatform.","A standard internet\nconnection is needed for the\nweb-based platform.",""],["Input data","","DICOM compliant medical\nimages acquired from a variety of\nimaging devices including, CT,\nMR","DICOM compliant medical\nimages acquired from a\nvariety of imaging devices\nincluding, CT, MR",""]],"caption_candidate":"Table 1 Device Features and Technical Characteristic comparison matrix","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231683-p9-t0","doc_id":"K231683","page_num":9,"bbox":[40.36,318.12,572.68,566.04],"n_rows":10,"n_cols":13,"columns":["","DICE","","","ASSD","","","Volume diff. (mL)","","","Volume diff. (%)","",""],"rows":[["","DICE","","","ASSD","","","Volume diff. (mL)","","","Volume diff. (%)","",""],["","Median","Mean","StdDev","Median","Mean","StdDev","Median","Mean","StdDev","Median","Mean","StdDev"],["Aorta","0.95","0.93","0.10","0.64","0.77","0.54","3.95","4.74","4.07","5%","8%","11%"],["Left Atrium","0.95","0.95","0.02","1.16","1.24","0.61","5.97","7.84","8.98","3%","5%","6%"],["Left\nVentricle\nEndocardium","0.97","0.97","0.02","0.97","0.97","0.02","4.92","6.36","5.32","2%","3%","3%"],["LV\nEpicardium","0.97","0.97","0.01","0.71","0.76","0.30","7.22","10.10","9.96","2%","3%","2%"],["Pulmonary\nArtery Trunk","0.93","0.91","0.07","1.41","2.02","2.15","7.38","10.84","11.38","9%","14%","20%"],["Right Atrium\n& Inf. Vena\nCava","0.93","0.92","0.04","1.17","1.30","0.57","7.28","9.87","10.12","4%","6%","6%"],["Right\nVentricle\nEndocardium","0.92","0.91","0.05","1.22","1.25","0.56","9.89","14.99","14.98","7%","11%","12%"],["RV\nEpicardium","0.94","0.93","0.03","0.95","1.06","0.45","6.42","8.67","8.07","4%","4%","4%"]],"caption_candidate":"GT.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231690-p7-t0","doc_id":"K231690","page_num":7,"bbox":[47.91,235.51,564.09,711.84],"n_rows":7,"n_cols":7,"columns":["Parameter","","Subject Device","","","Predicate Device",""],"rows":[["Parameter","","Subject Device","","","Predicate Device",""],["","","iCAS -LV","","","IQQA-LIVER Software (K061696)",""],["Intended\nuse","The iCAS -LV is intended to receive multi-\nphase volume datasets of reconstructed\nstudies from PACS devices, to process\nthem and to transfer the processing output\nto the PACS in DICOM format. It is a PC-\nbased, self-contained, noninvasive image\nanalysis software application. The device\nprovides tools for visualization,\nmeasurements, segmentation, annotation,\nimages registration, processing, and\nreporting. The device is intended for use by\ntrained physicians.","","","Indications for Use (intended use): The IQQA-\nLiver is a PC-based, self-contained,\nnoninvasive image analysis software application\nfor reviewing serial multi-phase CT acquisitions\nof the liver. Combining image viewing,\nprocessing and reporting tools, the software is\ndesigned to support physicians in the\nvisualization, evaluation and reporting of liver\nand physician-identified liver lesions. The\nsoftware supports a workflow based on\nautomated image registration for viewing and\nanalyzing multi-phase volume datasets. It also\nincludes tools for interactive segmentation and\nlabeling of liver segments and vascular\nstructures. The software provides functionalities\nfor manual or interactive segmentation of\nphysician-identified lesions, and allows for\nregional volumetric analysis of such lesions in\nterms of size, shape, position and enhancement\npattern, providing information for physician's\nassessment of lesion characterization. The\nsoftware is designed for use by trained\nphysicians. Image source: DICOM","",""],["Indications\nfor use","Further, the iCAS-LV is indicated to support\nthe physicians in visualization of CT\nreconstructed images and evaluation of\nphysician-identified liver lesions. The\ncombination of the visualization, interactive\nsegmentation, measurements, automatic\nregistration, and volumetric analysis,\nsupports the physician in evaluation of the\nlesions in terms of size, shape, position and\nchanges over time. The iCAS should not be\nused in isolation for diagnosis and making\npatient management decisions.","","","","",""],["21CFR\nsection","892.2050","","","892.2050","",""],["Product\nCode","QIH","","","LLZ","",""],["Device\nnature","PC-based self-contained post processing\nSW package","","","PC-based self-contained post processing SW\npackage","",""]],"caption_candidate":"control procedures. A comparison table is presented below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231690-p8-t0","doc_id":"K231690","page_num":8,"bbox":[47.91,72.67,564.09,348.72],"n_rows":6,"n_cols":7,"columns":["Parameter","","Subject Device","","","Predicate Device",""],"rows":[["Parameter","","Subject Device","","","Predicate Device",""],["","","iCAS -LV","","","IQQA-LIVER Software (K061696)",""],["Data inputs","CT reconstructed images in DICOM format","","","CT reconstructed images in DICOM format","",""],["SW\nFunctions","The HighRAD uniquely designed SW,\nsupports a workflow, which is based on\nautomated image registration, manual or\ninteractive segmentation of physician-\nidentified liver lesions, for viewing and\nanalysing multi-phase volume datasets, It\nalso includes tools for Labeling and\nreporting.","","","Similar SW functions performed by EDDA\nunique design.","",""],["Graphical\nUser\nInterface","A graphical user interface for users to\ninteract with the software, to visualize CT\ndata, to select tools and to drive the\nworkflow","","","A graphical user interface for users to interact\nwith the software, to visualize CT data, to select\ntools and to drive the workflow","",""],["Data\noutputs","CT images in DICOM format","","","CT images in DICOM format","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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:286)(cid:448)(cid:349)(cid:272)(cid:286)(cid:367)(cid:286)(cid:400)(cid:400)(cid:3)\n(cid:69)(cid:381)(cid:3)(cid:258)(cid:282)(cid:282)(cid:349)(cid:410)(cid:349)(cid:381)(cid:374)(cid:258)(cid:367)(cid:3)\n(cid:346)(cid:258)(cid:396)(cid:282)(cid:449)(cid:258)(cid:396)(cid:286)(cid:3)(cid:396)(cid:286)(cid:395)(cid:437)(cid:349)(cid:396)(cid:286)(cid:282)(cid:3)\n(cid:69)(cid:381)(cid:3)(cid:282)(cid:349)(cid:396)(cid:286)(cid:272)(cid:410)(cid:3)(cid:437)(cid:400)(cid:286)(cid:396)(cid:3)\n(cid:349)(cid:374)(cid:410)(cid:286)(cid:396)(cid:258)(cid:272)(cid:410)(cid:349)(cid:381)(cid:374)(cid:3)\n(cid:39)(cid:258)(cid:410)(cid:286)(cid:282)(cid:853)(cid:3)(cid:89)(cid:856)(cid:94)(cid:410)(cid:258)(cid:410)(cid:349)(cid:272)(cid:853)(cid:3)(cid:258)(cid:374)(cid:282)(cid:3)\n(cid:89)(cid:856)(cid:38)(cid:396)(cid:286)(cid:286)(cid:460)(cid:286)(cid:3)\n(cid:90)(cid:286)(cid:296)(cid:286)(cid:396)(cid:286)(cid:374)(cid:272)(cid:286)(cid:3)(cid:393)(cid:396)(cid:381)(cid:410)(cid:381)(cid:272)(cid:381)(cid:367)(cid:400)(cid:3)\n(cid:393)(cid:396)(cid:381)(cid:448)(cid:349)(cid:282)(cid:286)(cid:282)(cid:3)(cid:381)(cid:374)(cid:3)(cid:410)(cid:346)(cid:286)(cid:3)\n(cid:400)(cid:455)(cid:400)(cid:410)(cid:286)(cid:373)(cid:3)\n(cid:100)(cid:396)(cid:349)(cid:336)(cid:336)(cid:286)(cid:396)(cid:400)(cid:3)(cid:336)(cid:286)(cid:374)(cid:286)(cid:396)(cid:258)(cid:410)(cid:286)(cid:282)(cid:3)\n(cid:437)(cid:410)(cid:349)(cid:367)(cid:349)(cid:460)(cid:349)(cid:374)(cid:336)(cid:3)(cid:400)(cid:381)(cid:296)(cid:410)(cid:449)(cid:258)(cid:396)(cid:286)(cid:3)\n(cid:258)(cid:367)(cid:336)(cid:381)(cid:396)(cid:349)(cid:410)(cid:346)(cid:373)(cid:3)(cid:894)(cid:87)(cid:18)(cid:4)(cid:895)(cid:3)(cid:296)(cid:381)(cid:396)(cid:3)\n(cid:286)(cid:448)(cid:258)(cid:367)(cid:437)(cid:258)(cid:410)(cid:349)(cid:381)(cid:374)(cid:3)(cid:373)(cid:381)(cid:410)(cid:349)(cid:381)(cid:374)(cid:3)(cid:381)(cid:296)(cid:3)\n(cid:349)(cid:374)(cid:410)(cid:286)(cid:396)(cid:374)(cid:258)(cid:367)(cid:3)(cid:258)(cid:374)(cid:258)(cid:410)(cid:381)(cid:373)(cid:455)(cid:3)\n(cid:448)(cid:349)(cid:400)(cid:437)(cid:258)(cid:367)(cid:349)(cid:460)(cid:286)(cid:282)(cid:3)(cid:349)(cid:374)(cid:3)(cid:410)(cid:346)(cid:286)(cid:3)(cid:87)(cid:28)(cid:100)(cid:3)\n(cid:349)(cid:373)(cid:258)(cid:336)(cid:286)(cid:3)(cid:282)(cid:258)(cid:410)(cid:258)(cid:856)(cid:3)"]],"caption_candidate":"(cid:3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231757-p7-t0","doc_id":"K231757","page_num":7,"bbox":[74.06,126.4,550.65,642.34],"n_rows":16,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["Device Name","Ez3D-i v5.5(E3)","","","Ez3D-i v5.4(E3)","",""],["510K number","-","","","K222069","",""],["Manufacturer","Ewoosoft","","","Ewoosoft","",""],["Indications for use","Ez3D-i is dental imaging software that is\nintended to provide diagnostic tools for\nmaxillofacial radiographic imaging. These\ntools are available to view and interpret a\nseries of DICOM compliant dental radiology\nimages and are meant to be used by trained\nmedical professionals such as radiologist\nand dentist.\nEz3D-i is intended for use as software to\nload, view and save DICOM images from\nCT, panorama, cephalometric and intraoral\nimaging equipment and to provide 3D\nvisualization, 2D analysis, in various MPR\n(Multi-Planar Reconstruction.) functions","","","Ez3D-i is dental imaging software that is\nintended to provide diagnostic tools for\nmaxillofacial radiographic imaging. These\ntools are available to view and interpret a\nseries of DICOM compliant dental\nradiology images and are meant to be used\nby trained medical professionals such as\nradiologist and dentist.\nEz3D-i is intended for use as software to\nload, view and save DICOM images from\nCT, panorama, cephalometric and intraoral\nimaging equipment and to provide 3D\nvisualization, 2D analysis, in various MPR\n(Multi-Planar Reconstruction.) functions","",""],["Platform","IBM-compatible PC or PC network","","","IBM-compatible PC or PC network","",""],["Operating System","Microsoft Window 10 or higher","","","Microsoft Window 10 or higher","",""],["User Interface","Mouse, Keyboard","","","Mouse, Keyboard","",""],["Image Input Sources","Images can be scanned, loaded from digital\ncameras or card readers, or imported from a\nradiographic imaging device","","","Images can be scanned, loaded from digital\ncameras or card readers, or imported from a\nradiographic imaging device","",""],["32 bit / 64 bit","64 bit","","","64 bit","",""],["Image format","DICOM","","","DICOM","",""],["Image Measurement\nTools","Length, Multi Length, Angle, Multi Angle,\nCircle, ROI/Area, Volume, Profile","","","Length, Multi Length, Angle, ROI/Area,\nVolume, Profile","",""],["Image viewing","Full, side by side, gallery, thumbnail","","","Full, side by side, gallery, thumbnail","",""],["Image manipulation","Grayscale, invert, emboss, brightness,\ncontrast, gamma, sharpen, median,\ndespeckle, hue, saturation, equalize, flip,\nmirror, masking, rotate, magnify, annotation,\ncephalometric tracing, ceph growth\nprojections, implant simulations","","","Grayscale, invert, emboss, brightness,\ncontrast, gamma, sharpen, median,\ndespeckle, hue, saturation, equalize, flip,\nmirror, masking, rotate, magnify,\nannotation, cephalometric tracing, ceph\ngrowth projections, implant simulations","",""],["3D imaging\ncapability","Ez3D-i can view, transfer and process 3D\nradiographs. Furthermore, it supports Smart\nClick, Smart Clipping, Implant Simulation\nand Canal Draw.","","","Ez3D-i can view, transfer and process 3D\nradiographs. Furthermore, it supports Smart\nClick, Smart Clipping, Implant Simulation\nand Canal Draw.","",""],["Image annotation","Text, paint, ellipse, pointer, select, draw,\nmagnify, line, rectangle, polygon, ruler,\nprotractor, smile library, smudge, brush,\nredeye reduction, select region, copy / paste","","","Text, paint, ellipse, pointer, select, draw,\nmagnify, line, rectangle, polygon, ruler,\nprotractor, smile library, smudge, brush,\nredeye reduction, select region, copy / paste","",""]],"caption_candidate":"8.1. Comparison chart of features and specifications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p6-t0","doc_id":"K231764","page_num":6,"bbox":[70.95,332.76,535.27,586.86],"n_rows":5,"n_cols":6,"columns":["","Catalog/","","Model","","Model Description"],"rows":[["","Catalog/","","Model","","Model Description"],["","Reference","","","",""],["","(REF)","","","",""],["1300","","","1300-21","","Model with rechargeable battery"],["1300","","","1300-25","","Model without rechargeable battery"]],"caption_candidate":"Table 1: Ultrasound System 1300","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p7-t0","doc_id":"K231764","page_num":7,"bbox":[70.92,129.24,473.28,552.84],"n_rows":26,"n_cols":2,"columns":["Name Description","#Reference"],"rows":[["Name Description","#Reference"],["ENDOCAVITY TRANSDUCER E10C4","9019"],["BIPLANE ENDOCAVITY TRANSDUCER E11C3b","9008"],["TRIPLANE ENDOCAVITY TRANSDUCER E14C4t","9018"],["ENDFIRE ENDOCAVITY TRANSDUCER E13C2","9029"],["BIPLANE ENDOCAVITY TRANSDUCER E14CL4b","9048"],["CURVED ARRAY TRANSDUCER 9C2","9002"],["SMALL CURVED ARRAY TRANSDUCER 6C2s","9023"],["CURVED ARRAY TRANSDUCER 6C2","9040"],["CURVED ARRAY TRANSDUCER 5C1e","9085"],["PHASED ARRAY TRANSDUCER 5P1e","9087"],["HOCKEY STICK TRANSDUCER X18L5s","9009"],["WIDE LINEAR ARRAY TRANSDUCER 13L4w","9011"],["LINEAR ARRAY TRANSDUCER 8L2","9032"],["LINEAR ARRAY TRANSDUCER 14L3","9051"],["HIGH-FREQUENCY LINEAR ARRAY TRANSDUCER\n18L5","9070"],["HIGH-FREQUENCY LINEAR ARRAY TRANSDUCER\n18L5s","9081"],["LINEAR ARRAY TRANSDUCER 14L3e","9086"],["3D ENDOCAVITY TRANSDUCER X14L4","9038"],["ANORECTAL TRANSDUCER 20R3","9052"],["I-SHAPED INTRAOPERATIVE TRANSDUCER I14C5I","9015"],["T-SHAPED INTRAOPERATIVE TRANSDUCER I14C5T","9016"],["BIPLANE INTRAOPERATIVE TRANSDUCER I12C5b","9024"],["ROBOTIC DROP-IN TRANSDUCER X12C4","9026"],["CURVED ARRAY CRANIOTOMY TRANSDUCER N13C5","9062"],["BURR HOLE TRANSDUCER N11C5s","9063"]],"caption_candidate":"Table 2: Transducers used with Ultrasound System 1300","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p9-t0","doc_id":"K231764","page_num":9,"bbox":[71.18,150.34,568.9,541.68],"n_rows":8,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["Manufacturer","BK Medical ApS","","","BK Medical ApS","","","Same"],["Common Name","Ultrasound System","","","Ultrasound System","","","Same"],["Name\n(Configuration\nmodels)","bkSpecto (1300-21,\n1300-25)","","","bkSpecto (1300-21)","","","Added:\n- bkSpecto 1300-25- a\nmodel without battery.\n- Prostate Volume Assist\n(PVA), AI software\nfeature."],["Mode of Operation","B, M, PW, CFM, P, THI,\nSE, CW\nCombination modes:\n2D+M, 2D+PW,\n2D+C+PW, 2D+P+PW,\n2D+2D, 2D+2D (Biplane\nImaging), 2D+(2D+C),\n2D+(2D+P), 2D+THI,\n2D+SE\n• 2D (B-Mode)\n(including Tissue\nHarmonic imaging)\n• M-Mode\n• Vector Flow Imaging\n(VFI)","","","B, M, PW, CFM, P, THI,\nSE, CW\nCombination modes:\n2D+M, 2D+PW,\n2D+C+PW, 2D+P+PW,\n2D+2D, 2D+2D (Biplane\nImaging), 2D+(2D+C),\n2D+(2D+P), 2D+THI,\n2D+SE\n• 2D (B-Mode)\n(including Tissue\nHarmonic imaging)\n• M-Mode\n• Vector Flow Imaging\n(VFI)","","","Same – primary predicate\nEquivalent – ref. predicate"]],"caption_candidate":"Table 3: Substantial Equivalence Table of the proposed device with its predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p10-t0","doc_id":"K231764","page_num":10,"bbox":[71.19,71.26,568.89,542.64],"n_rows":6,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["","• Strain Elastography\n• CW Doppler\n• Contrast Imaging\n• PWD Mode\n• • CFM Mode\n(Includes Color\nDoppler and\nAmplitude (Power)\nDoppler)","","","• Strain Elastography\n• CW Doppler\n• Contrast Imaging\n• PWD Mode\n• • CFM Mode\n(Includes Color\nDoppler and\nAmplitude (Power)\nDoppler)","","",""],["Intended Use","Intended Use:\nThe system is a\ndiagnostic ultrasound\nimaging system used by\nqualified and trained\nhealthcare professionals\nfor ultrasound imaging,\nhuman body fluid flow\nanalysis and puncture and\nbiopsy guidance.\nEnvironment:\nThe Ultrasound System\n1300 is intended for use\nin the professional\nhealthcare environment\n(e.g., hospitals, physician\noffices).\nContraindications:\nThe Ultrasound System\n1300 is not intended for\nophthalmic use or any use","","","Intended Use:\nThe system is a\ndiagnostic ultrasound\nimaging system used by\nqualified and trained\nhealthcare professionals\nfor ultrasound imaging,\nhuman body fluid flow\nanalysis and puncture\nand biopsy guidance.\nEnvironment:\nThe Ultrasound System\n1300 is intended for use\nin the professional\nhealthcare environment\n(e.g., hospitals, physician\noffices).\nContraindications:\nThe Ultrasound System\n1300 is not intended for\nophthalmic use or any use","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p11-t0","doc_id":"K231764","page_num":11,"bbox":[71.19,71.26,568.89,554.88],"n_rows":6,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["","causing the acoustic beam\nto pass through the eye.\nThe Cardiac Adult\napplication is not\nintended for direct use on\nthe heart.","","","causing the acoustic beam\nto pass through the eye.\nThe Cardiac Adult\napplication is not\nintended for direct use on\nthe heart.","","",""],["Indications/Clinical\nApplications","• Fetal (including\nObstetrics)\n• Abdominal\n• Pediatric1\n• Intraoperative1,2\n• Intraoperative Neuro\n(also known as\nNeurosurgery)1\n• Small Organ (Small\nParts)3\n• Adult Cephalic\n(cephalic is also known\nas Adult trans-cranial)1\n• Neonatal Cephalic1\n• Transrectal\n• Transvaginal\n• Musculoskeletal\n(Conventional)\n• Musculoskeletal\n(Superficial)\n• Cardiac Adult\n• • Peripheral Vessel\n(Peripheral\nVascular))","","","• Fetal (including\nObstetrics)\n• Abdominal\n• Pediatric1\n• Intraoperative1,2\n• Intraoperative Neuro\n(also known as\nNeurosurgery)1\n• Small Organ (Small\nParts)3\n• Adult Cephalic\n(cephalic is also known\nas Adult trans-cranial)1\n• Neonatal Cephalic1\n• Transrectal\n• Transvaginal\n• Musculoskeletal\n(Conventional)\n• Musculoskeletal\n(Superficial)\n• Cardiac Adult\n• • Peripheral Vessel\n(Peripheral\nVascular)","","","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p12-t0","doc_id":"K231764","page_num":12,"bbox":[71.17,71.26,568.91,544.92],"n_rows":11,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["Application\nEnvironment","Professional healthcare\nfacility environment","","","Professional healthcare\nfacility environment","","","Same"],["Users","Qualified Professional\nusers","","","Qualified Professional\nusers","","","Same"],["Patient Population","Adult, Pediatric","","","Adult, Pediatric","","","Same"],["Transducer types","Surface\nEndocavity\nIntraoperative","","","Surface\nEndocavity\nIntraoperative","","","Identical"],["System Transducers","9002, 9008, 9009, 9011,\n9015, 9016, 9018, 9019,\n9023, 9024, 9026, 9029,\n9032, 9038, 9040, 9048,\n9051, 9052, 9062, 9063,\n9070, 9081, 9085, 9086,\n9087","","","9002, 9008, 9009, 9011,\n9015, 9016, 9018, 9019,\n9022, 9023, 9024, 9026,\n9029, 9032, 9038, 9040,\n9048, 9051, 9052, 9062,\n9063, 9067, 9070, 9081,\n9085, 9086, 9087","","","Since 2017 the following\ntransducers have been\nterminated:9022 and 9067"],["Biocompatibility","The Ultrasound System\ndoes not come in contact\nwith the patient.","","","The Ultrasound System\ndoes not come in contact\nwith the patient.","","","Same"],["Hardware","Clinical display monitor\n(CDM):\n• 19” Optical bonded\nglass front.\n• Can be tilted and\nmoved sideways.\nCart:\n• adjustable height and\nwith 4 lockable wheels\nKeyboard:\nGlass touch UI","","","Clinical display monitor\n(CDM):\n• 19” Optical bonded\nglass front.\n• Can be tilted and\nmoved sideways.\nCart:\n• adjustable height and\nwith 4 lockable wheels\nKeyboard:\nGlass touch UI","","","Same – primary predicate\nEquivalent – ref. predicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p13-t0","doc_id":"K231764","page_num":13,"bbox":[71.18,71.26,568.9,517.92],"n_rows":8,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["","Scan engine:\n• 3 Transducer ports\n• 64 TX/RX channels","","","Scan engine:\n• 3 Transducer ports\n64 TX/RX channels","","",""],["OS Software","Windows 10","","","Windows 8.1 Industrial","","","Updated to Windows 8 OS\nto Windows 10."],["Options","- 3D Freehand\n- 3D Professional\n- DICOM Encrypted\n- Vector Flow Imaging\n(VFI)\n- Varian Interface\n- Strain Elastography\n- Needle Enhancement\n(X-shine)\n- Wi-Fi\n- bkViewer (SW running\non a mac/windows pc) –\nnot a medical device\n- Prostate Volume Assist\n(PVA)","","","- 3D Freehand\n- 3D Professional\n- DICOM Encrypted\n- Vector Flow Imaging\n(VFI)\n- Varian Interface\n- Strain Elastography\n- Needle Enhancement\n(X-shine)\n- Wi-Fi","","","- Proposed a new Prostate\nVolume Assist (PVA), AI\nsoftware feature that has\nbeen recently cleared\nunder K223830 for the\nReference Predicate device\nUltrasound System 2300.\nPVA provides a workflow\nimprovement to an existing\nprostate volume\nmeasurement and\ncalculation tool.\nIt will require the same\nbiplane/triplane transrectal\ntransducers (9008, 9018,\n9048) that are being used\nfor existing prostate\nvolume calculations and\nmeasurements."],["Image features","Speckle reduction,\ncompound imaging,\ntissue harmonic imaging\n(thi), trapezoid scanning\n(virtual convex) strain,\nelastography (se)","","","Speckle reduction,\ncompound imaging,\ntissue harmonic imaging\n(thi), trapezoid scanning\n(virtual convex) strain,\nelastography (se)","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p14-t0","doc_id":"K231764","page_num":14,"bbox":[71.19,71.26,568.89,553.32],"n_rows":6,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["UI Design","-19-inch Clinical Monitor\nand touch input device\nfor user interaction.\n-Touchpad track pad for\ncursor control (Glass\nTouch UI)\n-Full configurable\ninteraction controls\n(size/position)","","","-19-inch Clinical Monitor\nand touch input device\nfor user interaction.\n-Touchpad track pad for\ncursor control (Glass\nTouch UI)\n-Full configurable\ninteraction controls\n(size/position)","","","Same – primary predicate\nEquivalent – ref. predicate"],["Standards","ELECTROMAGNETIC\nCOMPATIBILITY\nComplies with\nrequirements for Class A\ndevices of IEC 60601-1-2\nSAFETY\nANSI/ AAMI/ES 60601-\n1,\nIEC 60601-2-37\nSOFTWARE/\nFIRMWARE\nIEC62304\nCLEANING\nVALIDATION\nAAMI TIR12, AAMI\nTIR30\nDICOM\nNEMA PS3.1-3.20\nDigital Imaging and\nCommunications in\nMedicine (DICOM)","","","ELECTROMAGNETIC\nCOMPATIBILITY\nComplies with\nrequirements for Class A\ndevices of IEC 60601-1-\n2\nSAFETY\nANSI/ AAMI/ES 60601-\n1,\nIEC 60601-2-37\nSOFTWARE/\nFIRMWARE\nIEC62304\nCLEANING\nVALIDATION\nAAMI TIR12, AAMI\nTIR30\nDICOM\nNEMA PS3.1-3.20\nDigital Imaging and","","","Same – primary predicate\nEquivalent – ref. predicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p15-t0","doc_id":"K231764","page_num":15,"bbox":[71.21,71.26,568.87,160.68],"n_rows":5,"n_cols":8,"columns":["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],"rows":[["Characteristic","","Ultrasound System 1300","","","Ultrasound System 1300","","Comment on\nComparison"],["","","","","","","",""],["","","Proposed device","","","Primary Predicate","",""],["","","(K231764)","","","(K173569)","",""],["","","","","Communications in\nMedicine (DICOM)","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231764-p17-t0","doc_id":"K231764","page_num":17,"bbox":[140.62,188.52,541.22,421.4],"n_rows":4,"n_cols":5,"columns":["Patient Type","Training\nImages","Deep\nLearning\nValidation\nimages","Test images\n(Clinical\nvalidation)","Comment"],"rows":[["Patient Type","Training\nImages","Deep\nLearning\nValidation\nimages","Test images\n(Clinical\nvalidation)","Comment"],["Healthy","505","190","975",""],["Diseased","13447","1189","1461","Includes images from\nHolland dataset that are\nonly used as Test\nimages."],["Synthesized data","4104","48","0",""]],"caption_candidate":"• The table summarizes number of datasets used for each different purpose.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231765-p6-t0","doc_id":"K231765","page_num":6,"bbox":[155.86,114.49,541.78,764.77],"n_rows":64,"n_cols":4,"columns":["Institution","Country # of","images",""],"rows":[["Institution","Country # of","images",""],["","","",""],["Institution 18","USA","7",""],["","","",""],["Institution 19","USA","27",""],["","","",""],["Institution 20","USA","27",""],["","","",""],["Institution 21","USA","6",""],["","","",""],["Institution 22","USA","41",""],["","","",""],["Institution 23","Australia","19",""],["","","",""],["Institution 24","USA","10",""],["","","",""],["Institution 25","USA","11",""],["","","",""],["Institution 26","USA","10",""],["","","",""],["Institution 27","USA","2",""],["","","",""],["Institution 28","USA","1",""],["","","",""],["Institution 29","USA","6",""],["","","",""],["Institution 30","USA","9",""],["","","",""],["Institution 31","USA","4",""],["","","",""],["Institution 32","USA","2",""],["","","",""],["Institution 33","USA","6",""],["","","",""],["Institution 34","USA","2",""],["","","",""],["Institution 35","USA","6",""],["","","",""],["Institution 36","USA","14",""],["","","",""],["Institution 37","USA","4",""],["","","",""],["Institution 38","USA","5",""],["","","",""],["Institution 39","USA","75",""],["","","",""],["Institution 40","Australia","48",""],["","","",""],["Institution 41","USA","1",""],["","","",""],["Equivalence","","",""],["","","",""],["","","","Reference"],["Subject Device:","Predicate Device:","","Predicate:"],["","","",""],["Contour ProtégéAI","Contour ProtégéAI","MIM","4.1 SEAS"],["","","",""],["(K231765)","(K223774)","[i.e.,","MIM Maes"],["","","",""],["","","","(K071964)"],["","","",""],["TBD","04/06/2023","","9/26/2007"],["","","",""],["","","","Page 3 of 19"]],"caption_candidate":"Institution Country # of images","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231765-p13-t0","doc_id":"K231765","page_num":13,"bbox":[56.48,642.8,574.13,736.9],"n_rows":5,"n_cols":11,"columns":["","","","Dice","MDA\nMIM Atlas","","MDA","","","External",""],"rows":[["","","","Dice","MDA\nMIM Atlas","","MDA","","","External",""],["4.1.0 CT","","Dice","Contour","","","Contour","","","Evaluation",""],["Model:","Structure:","MIM Atlas","ProtégéAI","","","ProtégéAI","","","Score",""],["Head and\nNeck","Bone_Mandible","0.81 ± 0.07","0.86 ± 0.07\n(0.83) *","1.00 ± 0.87","0.64 ± 0.31\n(0.93) *","","","2.86","",""],["","BrachialPlex_L","0.17 ± 0.08","0.22 ± 0.10\n(0.14) *","3.24 ± 2.62","2.82 ± 2.61\n(5.12) *","","","2.6","",""]],"caption_candidate":"Table 2: DICE, MDA and External Evaluation Score Comparison Per Structure","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231765-p14-t0","doc_id":"K231765","page_num":14,"bbox":[56.24,108.3,574.17,750.24],"n_rows":25,"n_cols":11,"columns":["","","","Dice","MDA\nMIM Atlas","","MDA","","","External",""],"rows":[["","","","Dice","MDA\nMIM Atlas","","MDA","","","External",""],["4.1.0 CT","","Dice","Contour","","","Contour","","","Evaluation",""],["Model:","Structure:","MIM Atlas","ProtégéAI","","","ProtégéAI","","","Score",""],["","BrachialPlex_R","0.15 ± 0.07","0.19 ± 0.09\n(0.11) *","3.62 ± 2.79","2.73 ± 2.38\n(5.20) *","","","2.6","",""],["","Brain","0.97 ± 0.01","0.98 ± 0.01\n(0.97) *","0.64 ± 0.37","0.52 ± 0.36\n(0.66) *","","","2.71","",""],["","Brainstem","0.78 ± 0.09","0.82 ± 0.08\n(0.78) *","1.72 ± 0.81","1.20 ± 0.65\n(1.47) *","","","2.71","",""],["","Cavity_Oral","0.75 ± 0.14","0.76 ± 0.13\n(0.68) *","3.34 ± 2.13","3.20 ± 1.93\n(4.35) *","","","2.71","",""],["","Cochlea_L","0.19 ± 0.15","0.30 ± 0.18\n(0.22) *","1.26 ± 0.85","1.17 ± 0.87\n(1.58) *","","","2.29","",""],["","Cochlea_R","0.17 ± 0.15","0.32 ± 0.20\n(0.23) *","1.12 ± 0.61","1.05 ± 0.68\n(1.37) *","","","2.29","",""],["","Eye_L","0.80 ± 0.08","0.87 ± 0.06\n(0.83) *","1.07 ± 0.60","0.65 ± 0.51\n(0.91) *","","","2.57","",""],["","Eye_R","0.80 ± 0.10","0.86 ± 0.07\n(0.82) *","1.11 ± 0.64","0.66 ± 0.48\n(0.92) *","","","2.57","",""],["","Glnd_Lacrimal_L","0.22 ± 0.17","0.40 ± 0.16\n(0.27) *","0.86 ± 0.54","0.68 ± 0.35\n(1.05) *","","","2.71","",""],["","Glnd_Lacrimal_R","0.23 ± 0.16","0.45 ± 0.14\n(0.34) *","0.73 ± 0.38","0.71 ± 0.52\n(1.09) *","","","2.71","",""],["","Glnd_Submand_L","0.57 ± 0.13","0.77 ± 0.11\n(0.69) *","1.74 ± 0.72","0.76 ± 0.32\n(1.12) *","","","3","",""],["","Glnd_Submand_R","0.56 ± 0.16","0.75 ± 0.11\n(0.65) *","1.82 ± 0.87","0.81 ± 0.34\n(1.28) *","","","3","",""],["","Glnd_Thyroid","0.47 ± 0.18","0.71 ± 0.19\n(0.57) *","2.55 ± 2.14","1.38 ± 3.18\n(3.38) *","","","2.71","",""],["","Lens_L","0.22 ± 0.23","0.61 ± 0.17\n(0.52) *","0.77 ± 0.54","0.56 ± 0.47\n(0.84) *","","","2.29","",""],["","Lens_R","0.22 ± 0.22","0.63 ± 0.16\n(0.54) *","0.81 ± 0.47","0.55 ± 0.33\n(0.78) *","","","2.29","",""],["","Lips","0.38 ± 0.14","0.37 ± 0.15\n(0.28) *","4.14 ± 2.86","5.26 ± 3.41\n(7.27)","","","2.83","",""],["","OpticChiasm","0.04 ± 0.07","0.13 ± 0.13\n(0.08) *","2.69 ± 1.87","2.46 ± 1.99\n(3.55) *","","","2","",""],["","OpticNrv_L","0.45 ± 0.15","0.53 ± 0.14\n(0.45) *","0.97 ± 0.81","0.77 ± 0.85\n(1.19) *","","","2.57","",""],["","OpticNrv_R","0.44 ± 0.14","0.52 ± 0.13\n(0.44) *","1.11 ± 1.24","0.80 ± 0.83\n(1.34) *","","","2.57","",""],["","Parotid_L","0.71 ± 0.10","0.79 ± 0.09\n(0.75) *","2.02 ± 0.95","1.30 ± 0.62\n(1.68) *","","","3","",""],["","Parotid_R","0.71 ± 0.09","0.80 ± 0.06\n(0.76) *","2.11 ± 0.76","1.26 ± 0.43\n(1.56) *","","","3","",""],["","Pituitary","0.38 ± 0.18","0.54 ± 0.15","1.07 ± 0.59","0.87 ± 0.54","","","3","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K231765-p21-t0","doc_id":"K231765","page_num":21,"bbox":[117.79,116.29,433.51,741.53],"n_rows":61,"n_cols":4,"columns":["4.1.0 CT Models:","Structure:","Relevant FOV",""],"rows":[["4.1.0 CT Models:","Structure:","Relevant FOV",""],["","","",""],["","Pancreas","54","91"],["","","",""],["","SpinalCord","100","100"],["","","",""],["","Stomach","100","100"],["","","",""],["","Trachea","99","100"],["","","",""],["","LN_Ax_L1_L","100","100"],["","","",""],["","LN_Ax_L1_R","100","100"],["","","",""],["","LN_Ax_L2_L","100","100"],["","","",""],["","LN_Ax_L2_R","100","100"],["","","",""],["","LN_Ax_L3_L","100","100"],["","","",""],["","LN_Ax_L3_R","100","100"],["","","",""],["","LN_IMN_L","100","100"],["","","",""],["","LN_IMN_R","100","100"],["","","",""],["","LN_Sclav_L","100","100"],["","","",""],["","LN_Sclav_R","100","100"],["","","",""],["Whole Body -","","",""],["Physiological Uptake","","",""],["Organs","Bladder","N/A","95"],["","","",""],["","Bone","N/A","100"],["","","",""],["","Bowel","N/A","100"],["","","",""],["","BowelBag","N/A","100"],["","","",""],["","Brain","N/A","100"],["","","",""],["","Cavity_Oral","N/A","100"],["","","",""],["","Glnd_Lacrimal_L","N/A","100"],["","","",""],["","Glnd_Lacrimal_R","N/A","100"],["","","",""],["","Glnd_Submand_L","N/A","100"],["","","",""],["","Glnd_Submand_R","N/A","100"],["","","",""],["","Heart","N/A","100"],["","","",""],["","Kidney_L","N/A","95"],["","","",""],["","Kidney_R","N/A","100"],["","","",""],["","Liver","N/A","100"],["","","",""],["","LN_Iliac","N/A","64"]],"caption_candidate":"4.1.0 CT Models: Structure: Relevant FOV Whole Body CT","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231767-p5-t0","doc_id":"K231767","page_num":5,"bbox":[62.68,154.62,530.14,253.56],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI Pty Ltd"],"rows":[["","Company Name","","Annalise-AI Pty Ltd"],["Address","Address","","Level P, 24 Campbell Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","September 21, 2023"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K231767-p5-t2","doc_id":"K231767","page_num":5,"bbox":[62.68,432.84,530.14,532.26],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI Pty Ltd"],"rows":[["","Manufacturer Name","","Annalise-AI Pty Ltd"],["","Device Name","","Annalise Enterprise CTB Triage Trauma"],["","510(k) reference","","K223240"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231767-p9-t0","doc_id":"K231767","page_num":9,"bbox":[64.69,519.26,547.37,616.26],"n_rows":9,"n_cols":11,"columns":["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","","Specificity % (Sp)","",""],"rows":[["Finding","Slice Thickness Range","Operating Point","","Sensitivity % (Se)","","","","Specificity % (Sp)","",""],["","","","","(95% CI)","","","","(95% CI)","",""],["Vasogenic Edema","≤1.5mm","0.060584","91.7 (85.0, 98.3","",")","","89.7 (83.2, 95.3","",")",""],["","","0.094076","90.0 (81.7, 96.7","",")","","90.7 (85.0, 96.3","",")",""],["","","0.145352","90.0 (81.7, 96.7","",")","","93.5 (88.8, 97.2","",")",""],["",">1.5mm & ≤5.0mm","0.060584","94.9 (89.9, 99.0","",")","","93.3 (89.7, 96.4","",")",""],["","","0.094076","93.9 (88.9, 98.0","",")","","94.3 (90.7, 97.4","",")",""],["","","0.145352","90.9 (84.8, 96.0","",")","","95.4 (92.3, 97.9","",")",""],["","","0.261255","89.9 (83.8, 94.9","",")","","97.4 (94.8, 99.5","",")",""]],"caption_candidate":"results of the study are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231772-p6-t0","doc_id":"K231772","page_num":6,"bbox":[111.64,435.31,543.92,666.46],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical equipment - Part\n1-2: General requirements for basic safety and essential performance -\nEMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["ISO10993-1","","","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3","",""]],"caption_candidate":"with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231772-p7-t0","doc_id":"K231772","page_num":7,"bbox":[125.32,219.68,526.89,298.25],"n_rows":3,"n_cols":9,"columns":["","Validation Type","","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly detected frames\n×100\nTotal number of frames with nerve","","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231772-p7-t1","doc_id":"K231772","page_num":7,"bbox":[125.32,324.17,526.89,366.17],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","90.3","","","4.8","","","88.6 to 92.0","",""],["Speed (FPS)","","","3.61","","","0.25","","","3.43 to 3.78","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K231772-p8-t1","doc_id":"K231772","page_num":8,"bbox":[125.33,466.21,526.91,505.63],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","98.69","","","0.64","","","96.31 to 100","",""],["Speed (FPS)","","","3.62","","","0.36","","","3.49 to 3.75","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals for Segmentation:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231772-p8-t2","doc_id":"K231772","page_num":8,"bbox":[125.33,531.55,526.91,610.42],"n_rows":6,"n_cols":12,"columns":["","","","","Females","","","Males","","","Total",""],"rows":[["","","","","Females","","","Males","","","Total",""],["Number of Subjects","","","8","","","3","","","11","",""],["Number of Images","","","3,041","","","795","","","3,836","",""],["Age range","","","38~71","","","32~51","","","32~71","",""],["Average age","","","45.1","","","39.7","","","43.6","",""],["Ethnicity","","","All Koreans","","","","","","","",""]],"caption_candidate":"Testing Data Information for Segmentation:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K231805-p4-t1","doc_id":"K231805","page_num":4,"bbox":[108.24,562.8,522.72,645.36],"n_rows":3,"n_cols":2,"columns":["Name of Device:","Auto Lung Nodule Detection"],"rows":[["Name of Device:","Auto Lung Nodule Detection"],["Manufacturer:","Samsung Electronics Co., Ltd"],["510(k) Number:","K201560"]],"caption_candidate":"3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231805-p6-t0","doc_id":"K231805","page_num":6,"bbox":[72.01,98.46,529.19,747.6],"n_rows":16,"n_cols":8,"columns":["","","","Predicate Device","","","Subject Device",""],"rows":[["","","","Predicate Device","","","Subject Device",""],["","","","Auto Lung Nodule Detection","","","qXR-LN",""],["Device Name","","Auto Lung Nodule Detection","","","qXR-LN","",""],["510(k) Number","","K201560","","","K231805","",""],["Regulation","","21 CFR 892.2070","","","21 CFR 892.2070","",""],["Regulation Description","","Medical Image Analyser","","","Medical Image Analyser","",""],["Product Code","","MYN","","","MYN","",""],["Device type","","Medical Image Analyser","","","Medical Image Analyser","",""],["Manufacturer","","Samsung Electronics Co., Ltd","","","Qure.ai Technologies","",""],["Intended use / Indications\nfor Use","","The Auto Lung Nodule Detection\nis computer-aided detection\nsoftware to identify and mark\nregions in relation to suspected\npulmonary nodules from 10 to 30\nmm in size. It is designed to aid\nthe physician to review the PA\nchest radiographs of adults as a\nsecond reader and be used as part\nof S-Station, which is operation\nsoftware installed on Samsung\nDigital X-ray Imaging systems.\nAuto Lung Nodule Detection\ncannot be used on the patients\nwho have lung lesions other than\nabnormal nodules.","","","The qXR-LN (qXR_Lung_nodule) is\ncomputer-aided detection software\nto identify and mark regions in\nrelation to suspected pulmonary\nnodules from 6 to 30 mm in size. The\ndevice is intended to be used in the\nincidental adult population. It is\ndesigned to aid the physician to\nreview the frontal (AP/PA) chest\nradiographs of adults acquired on\ndigital radiographic systems as a\nsecond reader and be used with any\nDICOM viewer or PACS . qXR-LN\nprovides adjunctive information only\nand is not a substitute for the original\nchest radiographic image.","",""],["Intended User","","Physicians.","","","Radiologists, emergency room\nphysicians or pulmonologists who\nregularly review chest X-rays as part\nof their daily practice.","",""],["Modality","","Chest X-ray","","","Chest X-ray","",""],["Target clinical conditions","","Lung Nodules on PAview Chest X-\nrays","","","Lung Nodules on PA/AP view Chest X-\nrays","",""],["Technology","","Machine learning","","","Deep/Machine Learning","",""],["Input format","","DICOM","","","DICOM","",""],["Output","Type","ROI marked on the duplicated\ninput image.","","","ROI marked on the duplicated input\nimage","",""]],"caption_candidate":"Table 1 Comparison between qXR-LN and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K231805-p8-t0","doc_id":"K231805","page_num":8,"bbox":[72.24,229.8,522.72,309.6],"n_rows":3,"n_cols":4,"columns":["Modality","AFROC Estimate (95% CI)","AFROC (aided-unaided)","P - Value"],"rows":[["Modality","AFROC Estimate (95% CI)","AFROC (aided-unaided)","P - Value"],["Aided","0.8095 (0.7695-0.8494)","0.07621 (0.0497 – 0.1026)","P <1×10−5"],["Unaided","0.7333 (0.6892-0.7774)","",""]],"caption_candidate":"Table 2 Performance of readers aided vs unaided by qXR-LN","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231833-p7-t0","doc_id":"K231833","page_num":7,"bbox":[120.62,186.6,509.37,530.76],"n_rows":23,"n_cols":9,"columns":["","Performance Criteria","","","Results","","","Acceptance",""],"rows":[["","Performance Criteria","","","Results","","","Acceptance",""],["","Resolution – Full Size","","","","","","",""],["Transverse Resolution FWHM @ 1 cm","","","Pass","","","≤ 4.0 mm","",""],["Transverse Resolution FWHM @ 10 cm","","","Pass","","","≤ 4.8 mm","",""],["Transverse Resolution FWHM @ 20 cm","","","Pass","","","≤ 5.2 mm","",""],["Axial Resolution FWHM @ 1 cm","","","Pass","","","≤ 4.3 mm","",""],["Axial Resolution FWHM @ 10 cm","","","Pass","","","≤ 5.4 mm","",""],["Axial Resolution FWHM @ 20 cm","","","Pass","","","≤ 5.4 mm","",""],["","","","","","","","",""],["Sensitivity @435 keV LLD","","","Pass","","","≥ 15 cps/kBq","",""],["Count Rate peak NECR","","","Pass","","","≥ 250 kcps @ ≤ 36\nkBq/cc","",""],["Count Rate peak trues","","","Pass","","","≥ 1100 kcps @ ≤ 36\nkBq/cc","",""],["Scatter Fraction at peak NECR","","","Pass","","","≤43%","",""],["Co-Registration Accuracy","","","Pass","","","≤ 5 mm","",""],["Time of Flight Resolution at 5.3kBq/cc","","","Pass","","","≤ 214 ps","",""],["","","","","","","","",""],["10mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 55.0% / ≤ 10.0%","",""],["13mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 60.0% / ≤ 9.0%","",""],["17mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 65.0% / ≤ 8.0%","",""],["22mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 70.0% / ≤ 7.0%","",""],["28mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 75.0% / ≤ 6.0%","",""],["37mm sphere (Contrast / Background Variability)","","","Pass","","","≥ 80.0% / ≤ 5.0%","",""],["Lung Residual Error","","","Pass","","","≤ 5.0%","",""]],"caption_candidate":"Maximum Ring Difference (MRD) of 85.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p6-t0","doc_id":"K231837","page_num":6,"bbox":[90.14,411.93,504.88,452.04],"n_rows":3,"n_cols":3,"columns":["510(k) Number","Trade Name","Manufacturer"],"rows":[["510(k) Number","Trade Name","Manufacturer"],["","",""],["K223042","Viz LVO","Viz AI"]],"caption_candidate":"Brainomix 360 Triage LVO is Substantially Equivalent to the following Legally Marketed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p8-t0","doc_id":"K231837","page_num":8,"bbox":[72.0,567.54,523.32,628.62],"n_rows":4,"n_cols":2,"columns":["","In-plane (axial) resolution showed a range"],"rows":[["","In-plane (axial) resolution showed a range"],["of 0.381mm to 0.72mm with a median of 0.49mm. Four different tube voltage (KvP, peak kilovoltage)",""],["values were encountered in the dataset (90KvP n=6, 100KvP, n=64; 120KvP n=137 and 140KvP, n=99).",""],["Tube current was median of 526mA [IQR: 445mA - 645mA]. With respect to contrast phase",""]],"caption_candidate":"In the CTA image dataset, the slice thickness distribution was median 0.75mm [IQR: 0.625 – 0.8] with","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p8-t1","doc_id":"K231837","page_num":8,"bbox":[72.0,628.62,523.32,673.62],"n_rows":3,"n_cols":3,"columns":["","quisition,","62 studies were Early Arterial (EA), 130 Peak Arterial (PA), 110 in Equilibrium phase (EQ),"],"rows":[["","quisition,","62 studies were Early Arterial (EA), 130 Peak Arterial (PA), 110 in Equilibrium phase (EQ),"],["3 in Peak Venous (PV), and 3 in Late Venous (LV). All the images used a standard or a soft (low-pass","",""],["filter) convolution kernel for reconstruction (e.g., STANDARD in GE MEDICAL SYSTEMS).","",""]],"caption_candidate":"Tube current was median of 526mA [IQR: 445mA - 645mA]. With respect to contrast phase during","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p10-t0","doc_id":"K231837","page_num":10,"bbox":[139.8,144.3,454.8,266.7],"n_rows":9,"n_cols":11,"columns":["","Metrics","","","Age 22-50","","","Age 50-70","","Age 70+",""],"rows":[["","Metrics","","","Age 22-50","","","Age 50-70","","Age 70+",""],["","Total N","","","57","","","132","","119",""],["","TP","","","12","","","44","","70",""],["","TN","","","39","","","75","","42",""],["","FN","","","3","","","8","","3",""],["","FP","","","3","","","5","","4",""],["","Sensitivity","","","80.0 (55.2-95.3)","","","84.6 (72.9-92.8)","","95.9 (89.2-99.1)",""],["","Specificity","","","92.9 (79.4-95.9)","","","93.8 (84.1-94.5)","","91.3 (88.7-97.5)",""],["","AUC","","","86.4 (74.0-96.7)","","","89.2 (83.4-94.2)","","94.0 (89.3-98.2)",""]],"caption_candidate":"appropriate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p10-t1","doc_id":"K231837","page_num":10,"bbox":[169.38,341.82,425.88,464.16],"n_rows":9,"n_cols":9,"columns":["","Metrics","","","Male","","","Female",""],"rows":[["","Metrics","","","Male","","","Female",""],["","Total N","","","140","","","168",""],["","TP","","","57","","","69",""],["","TN","","","72","","","84",""],["","FN","","","4","","","10",""],["","FP","","","7","","","5",""],["","Sensitivity","","","93.4 (84.9-98.2)","","","87.3 (78.6-93.6)",""],["","Specificity","","","91.1 (86.7-95.9)","","","94.4 (86.0-94.6)",""],["","AUC","","","92.3 (87.7-96.5)","","","91.3 (87.0-95.3)",""]],"caption_candidate":"appropriate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p10-t2","doc_id":"K231837","page_num":10,"bbox":[38.94,539.1,556.37,674.88],"n_rows":10,"n_cols":17,"columns":["Metrics","","","White","","","","Black/African","","Hispanic/ Latino","","","Asian/Asian\nAmerican","","","Unknown/",""],"rows":[["Metrics","","","White","","","","Black/African","","Hispanic/ Latino","","","Asian/Asian\nAmerican","","","Unknown/",""],["","","","","","","","American","","","","","","","","Refused",""],["","Total N","","","148","","","85","","","27","","7","","","40",""],["","TP","","","74","","","19","","","10","","4","","","19",""],["","TN","","","58","","","61","","","14","","3","","","19",""],["","FN","","","11","","","2","","","0","","0","","","1",""],["","FP","","","5","","","3","","","3","","0","","","1",""],["","Sensitivity","","","87.1 (78.6-93.2)","","","90.5 (72.3-98.5)","","","100.0 (77.5-100.0)","","100.0 (58.3-100.0)","","","95.0 (84.5-99.3)",""],["","Specificity","","","92.1 (83.4-93.6)","","","95.3 (87.4-98.0)","","","82.4 (72.8-97.5)","","100.0 (70.8-100.0)","","","95.0 (84.5-99.3)",""],["","AUC","","","88.9 (83.3-93.5)","","","92.9 (85.8-98.6)","","","88.5 (75.0-100.0)","","100.0 (NA*)","","","95.0 (87.5-100.0)",""]],"caption_candidate":"where appropriate. *CI could not be calculated due to lack of evidence (low N).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p11-t0","doc_id":"K231837","page_num":11,"bbox":[68.58,130.92,526.75,266.7],"n_rows":10,"n_cols":14,"columns":["Metrics","","","SIEMENS","","","","GE Medical","","Philips","Philips","Canon/ Toshiba","",""],"rows":[["Metrics","","","SIEMENS","","","","GE Medical","","Philips","Philips","Canon/ Toshiba","",""],["","","","","","","","Systems","","","","","",""],["","Total N","","","133","","","96","","","75","","4",""],["","TP","","","51","","","38","","","33","","4",""],["","TN","","","72","","","48","","","36","","0",""],["","FN","","","5","","","4","","","5","","0",""],["","FP","","","5","","","6","","","1","","0",""],["","Sensitivity","","","91.1 (81.3-97.0)","","","90.5 (78.6-97.3)","","","86.6 (73.3-95.4)","","NA",""],["","Specificity","","","93.5 (87.0-96.2)","","","88.9 (82.2-94.8)","","","97.3 (84.1-96.9)","","NA",""],["","AUC","","","92.3 (87.8-97.2)","","","89.7 (83.3-95.6)","","","92.4 (86.1-97.6)","","NA",""]],"caption_candidate":"intervals where appropriate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p11-t1","doc_id":"K231837","page_num":11,"bbox":[158.16,345.18,437.03,467.52],"n_rows":9,"n_cols":8,"columns":["","Metrics","","","MCR","","","BMC"],"rows":[["","Metrics","","","MCR","","","BMC"],["","Total N","","","129","","","179"],["","TP","","","51","","","75"],["","TN","","","70","","","86"],["","FN","","","3","","","11"],["","FP","","","5","","","7"],["","Sensitivity","","","94.4 (85.6-98.8)","","","87.2 (78.9-93.3)"],["","Specificity","","","93.3 (88.5-97.2)","","","92.5 (84.9-93.8)"],["","AUC","","","93.5 (89.0-97.7)","","","89.8 (85.2-93.8)"]],"caption_candidate":"appropriate. MCR = Mayo Clinic Rochester, BMC = Boston Medical Center.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p11-t2","doc_id":"K231837","page_num":11,"bbox":[171.54,546.0,423.66,654.9],"n_rows":8,"n_cols":8,"columns":["","Metrics","","","ICA","","MCA M1",""],"rows":[["","Metrics","","","ICA","","MCA M1",""],["","TP","","","29","","98",""],["","TN","","","156","","156",""],["","FN","","","1","","13",""],["","FP","","","14","","12",""],["","Sensitivity","","","96.6 (84.3-99.8)","","88.7 (81.3-93.5)",""],["","Specificity","","","91.8 (86.9-95.3)","","92.9 (88.2-96.2)",""],["","AUC","","","83.0 (75.0-90.3)","","90.6 (86.9-93.8)",""]],"caption_candidate":"where appropriate. ICA = intracranial carotid artery. MCA M1 = proximal segment of the middle cerebral artery.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p12-t0","doc_id":"K231837","page_num":12,"bbox":[160.38,130.92,434.88,253.26],"n_rows":9,"n_cols":9,"columns":["","Metrics","","","With Stenosis","","","Without Stenosis",""],"rows":[["","Metrics","","","With Stenosis","","","Without Stenosis",""],["","Total N","","","30","","","278",""],["","TP","","","7","","","119",""],["","TN","","","19","","","137",""],["","FN","","","3","","","11",""],["","FP","","","1","","","11",""],["","Sensitivity","","","70.0 (38.9-92.3)","","","91.5 (85.8-95.6)",""],["","Specificity","","","95.0 (71.0-96.1)","","","92.6 (88.4-94.9)",""],["","AUC","","","82.5 (66.3-96.7)","","","92.1 (88.6-95.0)",""]],"caption_candidate":"where appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p13-t0","doc_id":"K231837","page_num":13,"bbox":[72.24,430.98,523.08,756.36],"n_rows":5,"n_cols":3,"columns":["Characteristic/Parameter","Brainomix 360 Triage LVO\nProposed Device","Viz.AI Viz LVO\nPredicate Device (K223042)"],"rows":[["Characteristic/Parameter","Brainomix 360 Triage LVO\nProposed Device","Viz.AI Viz LVO\nPredicate Device (K223042)"],["Application Number","K231837","K223042"],["Product Code","QAS","QAS"],["Regulation","21 C.F.R. §892.2080","21 C.F.R. §892.2080"],["Indications for Use","Brainomix Triage LVO is a\nnotification-only, parallel\nworkflow tool for use by\nhospital networks and trained\nclinicians to identify and\ncommunicate images of\nspecific patients to a specialist,\nindependent of standard of\ncare workflow.\nBrainomix Triage LVO uses an\nartificial intelligence algorithm\nto analyze images for findings\nsuggestive of a prespecified\nclinical condition and to notify\nan appropriate medical\nspecialist of these findings in\nparallel to standard of care\nimage interpretation.","Viz LVO is a notification-only,\nparallel workflow tool for use\nby hospital networks and\ntrained clinicians to identify\nand communicate images of\nspecific patients to a specialist,\nindependent of standard of\ncare workflow.\nViz LVO uses an artificial\nintelligence algorithm to\nanalyze images for findings\nsuggestive of a prespecified\nclinical condition and to notify\nan appropriate medical\nspecialist of these findings in\nparallel to standard of care\nimage interpretation.\nIdentification of suspected"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p14-t0","doc_id":"K231837","page_num":14,"bbox":[72.24,95.22,523.08,755.82],"n_rows":3,"n_cols":3,"columns":["","Identification of suspected\nfindings is not for diagnostic\nuse beyond notification.\nSpecifically, the device\nanalyzes CT angiogram images\nof the brain acquired in the\nacute setting, and sends\nnotifications to a\nneurovascular specialist that a\nsuspected large vessel\nocclusion LVO has been\nidentified and recommends\nreview of those images.\nImages can be previewed\nthrough a mobile application.\nBrainomix Triage LVO is\nintended to analyze terminal\nICA and MCA-M1 vessels for\nLVOs.\nImages that are previewed\nthrough the mobile application\nare compressed and are for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. Notified clinicians\nare responsible for viewing\nnoncompressed images on a\ndiagnostic viewer and\nengaging in appropriate\npatient evaluation and\nrelevant discussion with a\ntreating physician before\nmaking care-related decisions\nor requests.\nBrainomix Triage LVO is limited\nto analysis of imaging data and\nshould not be used in-lieu of\nfull patient evaluation or relied\nupon to make or confirm\ndiagnosis.","findings is not for diagnostic\nuse beyond notification.\nSpecifically, the device\nanalyzes CT angiogram images\nof the brain acquired in the\nacute setting, and sends\nnotifications to a\nneurovascular specialist that a\nsuspected large vessel\nocclusion has been identified\nand recommends review of\nthose images. Images can be\npreviewed through a mobile\napplication. Viz LVO is\nintended to analyze terminal\nICA and MCA-M1 vessels for\nLVOs.\nImages that are previewed\nthrough the mobile application\nare compressed and are for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. Notified clinicians\nare responsible for viewing\nnoncompressed images on a\ndiagnostic viewer and\nengaging in appropriate\npatient evaluation and\nrelevant discussion with a\ntreating physician before\nmaking care-related decisions\nor requests.\nViz LVO is limited to analysis of\nimaging data and should not\nbe used in-lieu of full patient\nevaluation or relied upon to\nmake or confirm diagnosis."],"rows":[["","Identification of suspected\nfindings is not for diagnostic\nuse beyond notification.\nSpecifically, the device\nanalyzes CT angiogram images\nof the brain acquired in the\nacute setting, and sends\nnotifications to a\nneurovascular specialist that a\nsuspected large vessel\nocclusion LVO has been\nidentified and recommends\nreview of those images.\nImages can be previewed\nthrough a mobile application.\nBrainomix Triage LVO is\nintended to analyze terminal\nICA and MCA-M1 vessels for\nLVOs.\nImages that are previewed\nthrough the mobile application\nare compressed and are for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. Notified clinicians\nare responsible for viewing\nnoncompressed images on a\ndiagnostic viewer and\nengaging in appropriate\npatient evaluation and\nrelevant discussion with a\ntreating physician before\nmaking care-related decisions\nor requests.\nBrainomix Triage LVO is limited\nto analysis of imaging data and\nshould not be used in-lieu of\nfull patient evaluation or relied\nupon to make or confirm\ndiagnosis.","findings is not for diagnostic\nuse beyond notification.\nSpecifically, the device\nanalyzes CT angiogram images\nof the brain acquired in the\nacute setting, and sends\nnotifications to a\nneurovascular specialist that a\nsuspected large vessel\nocclusion has been identified\nand recommends review of\nthose images. Images can be\npreviewed through a mobile\napplication. Viz LVO is\nintended to analyze terminal\nICA and MCA-M1 vessels for\nLVOs.\nImages that are previewed\nthrough the mobile application\nare compressed and are for\ninformational purposes only\nand not intended for\ndiagnostic use beyond\nnotification. Notified clinicians\nare responsible for viewing\nnoncompressed images on a\ndiagnostic viewer and\nengaging in appropriate\npatient evaluation and\nrelevant discussion with a\ntreating physician before\nmaking care-related decisions\nor requests.\nViz LVO is limited to analysis of\nimaging data and should not\nbe used in-lieu of full patient\nevaluation or relied upon to\nmake or confirm diagnosis."],["Environment of use","Clinical/Hospital environment","Clinical/Hospital environment"],["Energy used and/or delivered","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231837-p15-t0","doc_id":"K231837","page_num":15,"bbox":[72.24,95.22,523.08,521.46],"n_rows":20,"n_cols":3,"columns":["Primary Users","Neurovascular Specialist","Neurovascular Specialist"],"rows":[["Primary Users","Neurovascular Specialist","Neurovascular Specialist"],["Anatomical Region","Head","Head"],["Technical Implementation","Artificial intelligence algorithm\nwith database of images","Same"],["Diagnostic application","Notification-only","Notification-only"],["Segmentation of region of\ninterest","No; the device does not mark,\nhighlight, or direct users’\nattention to a specific location\nin the original image","Internal, no image marking"],["Alteration of original image","No","No"],["Preview Images","Presentation of a preview of\nthe study for initial\ninformational purposes","Same"],["Interference with standard\nworkflow","No. Cases are not removed\nfrom worklist or deprioritized","Same"],["Notification","Mobile application and web\nuser interface","Mobile"],["Design: DICOM compliance","Yes","Yes"],["Design: Computer Platform","Standard off-the-shelf server\nor virtual server","Same"],["Design: Data acquisition","Acquires medical image data\nfrom DICOM compliant\nimaging devices and modalities","Same"],["Materials","N/A – Software only device","Same"],["Biocompatibility","N/A – Software only device","Same"],["Sterility","N/A – Software only device","Same"],["Electrical Safety","N/A – Software only device","Same"],["Mechanical Safety","N/A – Software only device","Same"],["Chemical Safety","N/A – Software only device","Same"],["Thermal Safety","N/A – Software only device","Same"],["Radiation Safety","N/A – Software only device","Same"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p4-t0","doc_id":"K231855","page_num":4,"bbox":[95.42,122.37,390.95,620.45],"n_rows":47,"n_cols":3,"columns":["5.1.","Type of Submission:","Traditional"],"rows":[["5.1.","Type of Submission:","Traditional"],["","",""],["5.2.","Date of Summary:","01/08/2024"],["","",""],["5.3.","Submitter:","Quanta Computer Inc."],["","",""],["","Address:","No. 188, Wenhua 2nd Rd"],["","",""],["","","City 33383, Taiwan (R.O."],["","",""],["","Phone:","+886-3-327-2345"],["","",""],["","Contact:","Joe Wang"],["","",""],["","","joe_wang@quantatw.com"],["","",""],["5.4.","Identification of the Device:",""],["","",""],["","Proprietary/Trade Name:","QOCA® image Smart RT"],["","",""],["","Model Number:","ZSWR901"],["","",""],["","Review Panel:","Radiology"],["","",""],["","Regulation Name:","Medical Image Managem"],["","",""],["","Regulation Number:","21 CFR 892.2050"],["","",""],["","Product Code:","QKB"],["","",""],["","Device Class:","II"],["","",""],["5.5.","Identification of the Predicat","e Device:"],["","",""],["","Predicate Device Name:","AccuContour™"],["","",""],["","Model Number:","--"],["","",""],["","510(k) Number:","K191928"],["","",""],["","Manufacturer:","Xiamen Manteia Technol"],["","",""],["","Regulation Number:","21 CFR 892.2050"],["","",""],["","Product Code:","QKB"],["","",""],["","Device Class:","II"]],"caption_candidate":"5.1. Type of Submission: Traditional","well_formed":true,"extraction_settings":"text"}
{"table_id":"K231855-p6-t0","doc_id":"K231855","page_num":6,"bbox":[87.4,298.87,524.84,716.86],"n_rows":10,"n_cols":6,"columns":["Item","Subject Device","Predicate Device","","Substantial",""],"rows":[["Item","Subject Device","Predicate Device","","Substantial",""],["","","","","Equivalence",""],["","","","","Determination",""],["510(k) Number","K231855","K191928","--","",""],["Proprietary\nName","QOCA® image Smart\nRT Contouring\nSystem","AccuContour™","--","",""],["Manufacturer","Quanta Computer Inc.","Xiamen Manteia\nTechnology LTD.","--","",""],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same","",""],["Product Code","QKB","QKB","Same","",""],["Classification","Class II","Class II","Same","",""],["Intended\nUse/Indication\nfor Use","QOCA® image Smart\nRT Contouring\nSystem is a post-\nprocessing software\nintended to\nautomatically contour\nDICOM CT imaging\ndata using deep-\nlearning-based\nalgorithms.","It is used by\nradiation oncology\ndepartment to\nregister\nmultimodality\nimages and\nsegment (non-\ncontrast) CT\nimages, to generate\nneeded information","Similar\nBoth devices utilize\nartificial\nintelligence\nalgorithms to\nautomatically\ncontour organs at\nrisk, including the\nhead and neck, as\nwell as the pelvis,","",""]],"caption_candidate":"of substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p8-t0","doc_id":"K231855","page_num":8,"bbox":[87.38,82.7,524.86,714.82],"n_rows":4,"n_cols":4,"columns":["","provide a user\ninterface for data\nvisualization. System\nsettings, user settings,\nprogress status, and\nother functionalities\nare managed via a\nweb-based interface.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","",""],"rows":[["","provide a user\ninterface for data\nvisualization. System\nsettings, user settings,\nprogress status, and\nother functionalities\nare managed via a\nweb-based interface.\nThe software is not\nintended to\nautomatically detect or\ncontour lesions. Only\nDICOM images of\nadult patients are\nconsidered to be valid\ninput.","",""],["Operating System","Windows","Windows","Same"],["Algorithm","Deep Learning","Deep Learning","Same"],["Segmentation of\nOrgan at Risk in\nthe Anatomic\nRegions","Brain stem,\nEsophagus, Mandible,\nPharyngeal,\nConstrictor Muscle\n(PCM), Spinal cord,\nThyroid, Right eye,\nLight eye, Right lens,\nLeft lens, Right optic\nnerve, Left optic\nnerve, Right parotid,\nLeft parotid,\nAnorectum, Bladder,\nBowel bag, Lumbar\nspine L5, Bilateral\nseminal vesicles,\nRight iliac, Left iliac,\nRight proximal femur,","Head and Neck,\nThorax, Abdomen,\nand Pelvis","Similar\nThe subject device\ncontains head and\nneck, and pelvis."]],"caption_candidate":"QOCA® image Smart RT Contouring System K231855","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p9-t0","doc_id":"K231855","page_num":9,"bbox":[87.38,82.7,524.86,714.34],"n_rows":3,"n_cols":4,"columns":["","Left proximal femur","",""],"rows":[["","Left proximal femur","",""],["Compatible\nModality","CT Images","Non-Contrast CT\nImages","Similar\nThe subject device\nand the predicate\ndevice are both\ncompatible only\nwith CT images for\nthe segmentation\nfeature. The\npredicate device\nclaims to handle\nonly non-contrast\nCT images, while\nthe subject device\ncan be used with\nboth contrast and\nnon-contrast CT\nimages."],["Compatible\nScanner Models","No specific\nrequirement for the\nscanner model, it is\nrecommended to use\nmulti-detector CT\n(MDCT) equipment\nwith more than 16\nslices for Radiation\nTherapy Simulation\nCT, and DICOM\ncompliance required.","No Limitation on\nscanner model,\nDICOM 3.0\ncompliance\nrequired.","Similar\nThe Subject Device\nand Predicate\nDevice are\nsubstantially\nequivalent in their\nrequirements for\nDICOM\ncompliance,\nensuring\ninteroperability and\nstandardization in\nmedical imaging\ndata. The Subject\nDevice\nrecommends a\nmulti-detector CT"]],"caption_candidate":"QOCA® image Smart RT Contouring System K231855","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p10-t0","doc_id":"K231855","page_num":10,"bbox":[87.38,82.7,524.86,714.82],"n_rows":4,"n_cols":4,"columns":["","","","scanner with more\nthan 16 slices\nspecifically for\nRadiation Therapy\nSimulation CT to\nprovide detailed\nimaging necessary\nfor accurate therapy\nplanning."],"rows":[["","","","scanner with more\nthan 16 slices\nspecifically for\nRadiation Therapy\nSimulation CT to\nprovide detailed\nimaging necessary\nfor accurate therapy\nplanning."],["Compatible\nTreatment\nPlanning System","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on\nTPS model,\nDICOM\n3.0compliance\nrequired.","Same"],["Contraindications","Adult use only.","There are no\nknown specific\nsituations that\ncontraindicate the\nuse of this device.","Similar\nThe subject device\nis designed for\nadult use, and there\nare no known\nspecific situations\nthat contraindicate\nits usage."],["Segmentation\nPerformance","The segmentation\nperformance was\nvalidated using private\ndatasets from Taiwan\nand public datasets\nwas collected from\nvarious sources,\nincluding the USA.\nThe datasets were\nobtained from major\nvendors such as GE,\nSiemens, Philips, and\nTOSHIBA. The","The segmentation\nperformance was\nvalidated using\ndatasets from\nChina and the USA\nusing three major\nvendors (GE,\nSiemens and\nPhilips). The\nsegmentation\naccuracy is\nevaluated using\nDICE similarity","Same"]],"caption_candidate":"QOCA® image Smart RT Contouring System K231855","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p13-t0","doc_id":"K231855","page_num":13,"bbox":[89.91,298.83,522.31,700.78],"n_rows":12,"n_cols":11,"columns":["Body Part","OARs","","Acceptance Criteria","","","Model Performance","","","",""],"rows":[["Body Part","OARs","","Acceptance Criteria","","","Model Performance","","","",""],["","","","(DSC)","","","DSC","","","HD95",""],["Head and\nNeck","Brain stem","0.87","","","0.942\n(±0.0215)","","","4.173\n(±20.9737)","",""],["","Esophagus","0.76","","","0.875\n(±0.0859)","","","4.694\n(±5.5237)","",""],["","Mandible","0.93","","","0.956\n(±0.0167)","","","1.413\n(±0.9036)","",""],["","Pharyngeal\nconstrictor muscle","0.70","","","0.820\n(±0.0692)","","","2.232\n(±1.3013)","",""],["","Spinal cord","0.87","","","0.931\n(±0.0282)","","","2.330\n(±3.3562)","",""],["","Thyroid","0.83","","","0.873\n(±0.1756)","","","3.249\n(±5.7852)","",""],["","Right eye","0.91","","","0.956\n(±0.0149)","","","2.038\n(±0.9599)","",""],["","Left lens","0.80","","","0.876\n(±0.1150)","","","1.526\n(±1.0436)","",""],["","Left optic nerve","0.66","","","0.805\n(±0.0849)","","","3.548\n(±3.0927)","",""],["","Right parotid","0.86","","","0.924\n(±0.0303)","","","3.825\n(±2.7730)","",""]],"caption_candidate":"The results for standalone performance testing are as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231855-p14-t0","doc_id":"K231855","page_num":14,"bbox":[89.92,82.8,522.3,375.29],"n_rows":9,"n_cols":11,"columns":["Body Part","OARs","","Acceptance Criteria","","","Model Performance","","","",""],"rows":[["Body Part","OARs","","Acceptance Criteria","","","Model Performance","","","",""],["","","","(DSC)","","","DSC","","","HD95",""],["Pelvis","Anorectum","0.70","","","0.929\n(±0.0755)","","","7.929\n(±14.2608)","",""],["","Bladder","0.82","","","0.959\n(±0.0912)","","","4.402\n(±9.7696)","",""],["","Bowel bag","0.70","","","0.944\n(±0.0338)","","","11.237\n(±8.5063)","",""],["","Lumbar spine L5","0.90","","","0.960\n(±0.0648)","","","5.985\n(±31.2018)","",""],["","Bilateral seminal\nvesicles","0.64","","","0.818\n(±0.3178)","","","3.638\n(±6.6927)","",""],["","Right iliac","0.90","","","0.985\n(±0.0111)","","","10.108\n(±51.8553)","",""],["","Right proximal\nfemur","0.90","","","0.980\n(±0.0195)","","","13.193\n(±68.4094)","",""]],"caption_candidate":"QOCA® image Smart RT Contouring System K231855","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231871-p4-t0","doc_id":"K231871","page_num":4,"bbox":[72.78,533.74,523.46,578.58],"n_rows":3,"n_cols":6,"columns":["","Manufacturer Name","","","Lunit Inc",""],"rows":[["","Manufacturer Name","","","Lunit Inc",""],["","Device Trade Name","","","Lunit INSIGHT CXR Triage",""],["","510(k) Number","","","K211733",""]],"caption_candidate":"Primary Predicate:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231871-p13-t0","doc_id":"K231871","page_num":13,"bbox":[72.94,102.22,523.42,223.42],"n_rows":4,"n_cols":4,"columns":["","Sensitivity (%)","Specificity (%)","AUC (%) (95% CI)"],"rows":[["","Sensitivity (%)","Specificity (%)","AUC (%) (95% CI)"],["Pneumothorax","94.81\n95% CI (93.90, 95.73)","97.91\n95% CI (97.00, 98.83)","97.43\n95% CI (97.12 97.74)"],["Pleural Effusion","94.39\n95% CI (93.26, 0.955)","0.9642\n95% CI(95.29, 97.54)","97.61\n95% CI (97.36, 97.86)"],["All","94.26\n95% CI (93.53, 94.99)","97.27\n95% CI (96.54, 98.00)","97.62\n95% CI (97.43 97.81)"]],"caption_candidate":"Table 2 Overall results of Accuracy testing for RADIFY® Triage","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231917-p4-t0","doc_id":"K231917","page_num":4,"bbox":[87.91,478.03,524.21,504.19],"n_rows":2,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K172346","","","sterEOS Workstation","","","June 2018","",""]],"caption_candidate":"3 LEGALLY MARKETED PREDICATE DEVICES","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231917-p6-t0","doc_id":"K231917","page_num":6,"bbox":[27.53,112.94,764.59,523.66],"n_rows":4,"n_cols":6,"columns":["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],["","","sterEOS Workstation","","",""],["","","510(k): K172346","","",""],["Indication for\nUse","The sterEOS Workstation is intended for use in the\nfields of musculoskeletal radiology and orthopedics in\nboth pediatric and adult populations as a general\ndevice for acceptance, transfer, display, storage, and\ndigital processing of 2D X-ray images of the\nmusculoskeletal system including interactive 2D\nmeasurement tools.\nWhen using 2D X-ray images obtained with the EOS\nimaging EOS system, sterEOS Workstation provides\ninteractive 3D measurement tools:\n• To aid in the analysis of scoliosis and related\ndisorders and deformities of the spine in adult\npatients as well as pediatric patients. The 3D\nmeasurement tools include interactive analysis\nbased either on identification of anatomical\nlandmarks for postural assessment, or on a model of\nbone structures derived from an a priori image data\nset from 175 patients (91 normal patients, 47\npatients with moderate idiopathic scoliosis and 37\npatients with severe idiopathic scoliosis), and dry\nisolated vertebrae data for spine modeling. The\nmodel of bone structures is not intended for use to\nassess individual vertebral abnormalities and is\nindicated only for patients 7 years and older. For\npostural assessment, a set of comparative tools is\nprovided allowing the comparison of performed\nmeasurements to reference values for patients over\n18 years old.","","","This cloud-based software is intended for\northopedic applications in both pediatric and adult\npopulations.\n2D X-ray images acquired in EOS imaging’s\nimaging systems is the foundation and resource\nto display the interactive landmarks overlayed on\nthe frontal and lateral images. These landmarks\nare available for users to assess patient-specific\nglobal alignment.\nFor additional assessment, alignment parameters\ncompared to published normative values may be\navailable.\nThis product serves as a tool to aid in the analysis\nof spinal deformities, degenerative diseases,\nlower limb alignment disorders, and deformities\nthrough precise angle and length measurements.\nIt is suitable for use with adult and pediatric\npatients aged 7 years and older.\nClinical judgment and experience are required to\nproperly use the software.","Yes, both devices are indicated for\nthe display and digital processing of\n2D X-ray images. Both devices are\nindicated for the same type of\ndisease, i.e., in the case of diseases\nthat have an impact on the patient's\nglobal alignment.\nThe information provided by both\nproducts is to be used as a\ndiagnostic aid for the user."]],"caption_candidate":"Table 5-1: Comparison for Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231917-p7-t0","doc_id":"K231917","page_num":7,"bbox":[27.5,92.54,764.62,529.54],"n_rows":7,"n_cols":6,"columns":["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],["","","sterEOS Workstation","","",""],["","","510(k): K172346","","",""],["","• To aid in the analysis of lower limbs alignment and\nrelated disorders and deformities based on angle\nand length measurements. The 3D measurement\ntools include interactive analysis based either on\nidentification of lower limb alignment landmarks or\nas for the spine, on a model of bone structures\nderived from an a priori image data set. The model\nof bone structures is not intended for use to assess\nindividual bone abnormalities. The 3D package\nincluding model-based measurements and torsion\nangles is indicated only for patients 15 years or\nolder. Only the 2D/3D ruler is indicated for\nmeasurements in patients younger than 15 years\nold.","","","",""],["Regulatory\nClass/Code","Class II\nLLZ\n(21 CFR 892.2050)","","","Class II\nQIH\n(21 CFR 892.2050)","The product code for the predicate\ndevice is LLZ. The QIH product\ncode was created after clearance of\nthe predicate device and appears to\nbe a better match for VEA Align\nthan LLZ. VEA Align employs\nmachine learning based algorithms\nthat were trained from data\ngenerated by EOS Imaging's\nimaging systems to automate the\nradiological image processing and\nanalysis."],["Device\nClassification\nName","System, Image Processing, Radiological","","","Automated Radiological Image Processing\nSoftware","Yes, both devices are classified\nunder 21 CFR 892.2050."],["Operating\nSystem","Windows","","","Windows + MAC","Yes, the subject device is\ncompatible with windows like the\npredicate device. It is also"]],"caption_candidate":"VEA Align","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231917-p8-t0","doc_id":"K231917","page_num":8,"bbox":[27.5,92.54,764.62,532.42],"n_rows":8,"n_cols":6,"columns":["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],["","","sterEOS Workstation","","",""],["","","510(k): K172346","","",""],["","","","","","compatible with the MAC operating\nsystem."],["User Population","Clinicians (radiologists, orthopedists, radiographers),\n3DServices persons, which have been trained to use\nthe application","","","Surgeons and clinical staff (physician assistants)\nthat have been trained to use the application","Yes, while the user population is\nslightly different, the inclusion of\nsurgeons and clinical staff do not\naffect device safety or\neffectiveness."],["Target\nPopulation","3D measurement tools are used on adult and\npediatric patients over 7 years of age who suffer from\nscoliosis and deformed spine pathology and for\npatients over 15 years of age with deformed lower\nlimb pathology.","","","The device is indicated only for patients 7 years\nand older.","Similar. The subject device is\ndedicated to understanding the\nglobal alignment of patients, spine\nand lower limb included. The 15-\nyear-old limitation of the predicate\ndevice was attached to workflow\ndedicated specifically to lower limbs\nonly. This workflow is not present\nin the subject device. This\ndifference does not affect device\nsafety or effectiveness."],["Software\nFunctionalities /\nModalities","Global alignment assessments","","","Global alignment assessments","Yes"],["Image\nManipulation\nFunctions","2D images display and basic manipulation (zoom,\npanning, distance, and angles measurements)","","","2D images display and basic manipulation\n(zoom, panning)","Similar. In VEA Align the user does\nnot have the possibility to make\nadditional measurements after\nreviewing the alignment provided\nby the software. The removal of\nthis function does not prevent VEA\nAlign from achieving its intended\npurpose and does not create a new\nrisk in VEA Align. The computation\nof the specific clinical parameters\nclaimed in the VEA Align User\nManual is not impacted by the\nremoval of this function. This\nfunction is not linked to the"]],"caption_candidate":"VEA Align","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231917-p9-t0","doc_id":"K231917","page_num":9,"bbox":[27.5,92.54,764.62,405.91],"n_rows":8,"n_cols":6,"columns":["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","Subject Device\nVEA Align","Substantially Equivalent?"],["","","sterEOS Workstation","","",""],["","","510(k): K172346","","",""],["","","","","","performance of VEA Align.\nConsequently, there is no impact\non the effectiveness of VEA Align."],["Measurement\nFunctions","Distances and Angles","","","Distances and Angles","Yes"],["3D Model","The 3D model is deformed manually by the user\nthrough control points up to matching accurately the\nX-ray contours. This deformation is performed by\nusing the common linear least squares estimation\nalgorithm.","","","The 3D model supports the initial placement of\nthe patient anatomic landmarks on the images\nusing a machine learning-based algorithm. It is\nnot displayed to the user and as such it is not\npart of the device outputs.","In VEA Align, the 3D model is not\nvisible to the user and the latter\ncannot interact with it. The 3D\nmodel is not part of the device\noutputs contrary to the predicate\ndevice. This difference does not\nprevent VEA Align from achieving\nits intended purpose and does not\ncreate a new risk in VEA Align.\nTherefore, this difference does not\naffect device safety or\neffectiveness."],["User Interface","Computer","","","Computer","Yes"],["Software\nEnvironment","Standalone","","","Cloud-based software","Yes, the difference regarding the\nsoftware environment does not\nintroduce new risks, or impact\nexisting risks. Therefore, this\ndifference does not affect device\nsafety or effectiveness."]],"caption_candidate":"VEA Align","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p4-t0","doc_id":"K231928","page_num":4,"bbox":[72.05,130.76,545.62,317.51],"n_rows":7,"n_cols":2,"columns":["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],"rows":[["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],["Address","Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.\nWest Dist.\nTaichung City 403020\nTAIWAN"],["Applicant","Joseph Chang"],["Contact Information","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["Correspondence Person","Ti-Hao Wang, CTO"],["Contact Information","886-04-23213838 #168\ntihao.wang@everfortune.ai"],["Date Prepared","June 28, 2023"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p4-t1","doc_id":"K231928","page_num":4,"bbox":[72.05,355.98,545.62,492.11],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","EFAI RTSuite CT HCAP-Segmentation System"],"rows":[["Proprietary Name","EFAI RTSuite CT HCAP-Segmentation System"],["Common Name","EFAI HCAPSeg"],["Classification Name","Radiological Image Processing Software For Radiation\nTherapy"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QKB"],["Regulatory Class","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p4-t2","doc_id":"K231928","page_num":4,"bbox":[72.05,530.58,545.62,677.58],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","EFAI RTSuite CT HN-Segmentation System"],"rows":[["Proprietary Name","EFAI RTSuite CT HN-Segmentation System"],["Premarket Notification","K220264"],["Classification Name","Radiological Image Processing Software For Radiation\nTherapy"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QKB"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p6-t0","doc_id":"K231928","page_num":6,"bbox":[72.42,168.93,720.56,530.73],"n_rows":8,"n_cols":5,"columns":["Characteristic","Proposed Device","Predicate Device","Reference Device- 1","Reference Device- 2"],"rows":[["Characteristic","Proposed Device","Predicate Device","Reference Device- 1","Reference Device- 2"],["Company","Ever Fortune.AI Co., Ltd.\n(EFAI)","Ever Fortune.AI Co., Ltd.\n(EFAI)","Xiamen Manteia Technology\nLTD.","Radformation, Inc."],["Device Name","EFAI HCAPSeg","EFAI HNSeg","AccuContour™","AutoContour RADAC V2"],["510k Number","K231928","K220264","K191928","K220598"],["Regulation No.","21CFR 892.2050","21CFR 892.2050","21CFR 892.2050","21CFR 892.2050"],["Classification","II","II","II","II"],["Product Code","QKB","QKB","QKB","QKB"],["Intended\nUse/Indication\nfor Use","EFAI HCAPSeg is a software\ndevice intended to assist trained\nradiation oncology\nprofessionals, including, but not\nlimited to, radiation oncologists,\nmedical physicists, and\ndosimetrists, during their\nclinical workflows of radiation\ntherapy treatment planning by\nproviding initial contours of\norgans at risk on non-contrast\nCT images. EFAI HCAPSeg is\nintended to be used on adult\npatients only.","EFAI HNSeg is a software\ndevice intended to assist trained\nradiation oncology\nprofessionals, including, but not\nlimited to, radiation oncologists,\nmedical physicists, and\ndosimetrists, during their\nclinical workflows of radiation\ntherapy treatment planning by\nproviding initial contours of\norgans at risk in the head and\nneck region on non-contrast CT\nimages. EFAI HNSeg is\nintended to be used on adult\npatients only.","It is used by radiation oncology\ndepartment to register\nmultimodality images and\nsegment (non-contrast) CT\nimages, to generate needed\ninformation for treatment\nplanning, treatment evaluation\nand treatment adaptation.","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in preparation\nfor radiation therapy treatment\nplanning."]],"caption_candidate":"Table A. Comparison with the Predicate and Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p7-t0","doc_id":"K231928","page_num":7,"bbox":[72.47,89.99,720.75,528.74],"n_rows":3,"n_cols":5,"columns":["","The contours are generated by\ndeep-learning algorithms and\nthen transferred to radiation\ntherapy treatment planning\nsystems. EFAI HCAPSeg must\nbe used in conjunction with a\nDICOM-compliant treatment\nplanning system to review and\nedit results generated. EFAI\nHCAPSeg is not intended to be\nused for decision making or to\ndetect lesions.\nEFAI HCAPSeg is an adjunct\ntool and is not intended to\nreplace a clinician's judgment\nand manual contouring of the\nnormal organs on CT. Clinicians\nmust not use the software\ngenerated output alone without\nreview as the primary\ninterpretation.","The contours are generated by\ndeep-learning algorithms and\nthen transferred to radiation\ntherapy treatment planning\nsystems. EFAI HNSeg must be\nused in conjunction with a\nDICOM-compliant treatment\nplanning system to review and\nedit results generated. EFAI\nHNSeg is not intended to be\nused for decision making or to\ndetect lesions.\nEFAI HNSeg is an adjunct tool\nand is not intended to replace a\nclinician's judgment and manual\ncontouring of the normal organs\non CT. Clinicians must not use\nthe software generated output\nalone without review as the\nprimary interpretation.","",""],"rows":[["","The contours are generated by\ndeep-learning algorithms and\nthen transferred to radiation\ntherapy treatment planning\nsystems. EFAI HCAPSeg must\nbe used in conjunction with a\nDICOM-compliant treatment\nplanning system to review and\nedit results generated. EFAI\nHCAPSeg is not intended to be\nused for decision making or to\ndetect lesions.\nEFAI HCAPSeg is an adjunct\ntool and is not intended to\nreplace a clinician's judgment\nand manual contouring of the\nnormal organs on CT. Clinicians\nmust not use the software\ngenerated output alone without\nreview as the primary\ninterpretation.","The contours are generated by\ndeep-learning algorithms and\nthen transferred to radiation\ntherapy treatment planning\nsystems. EFAI HNSeg must be\nused in conjunction with a\nDICOM-compliant treatment\nplanning system to review and\nedit results generated. EFAI\nHNSeg is not intended to be\nused for decision making or to\ndetect lesions.\nEFAI HNSeg is an adjunct tool\nand is not intended to replace a\nclinician's judgment and manual\ncontouring of the normal organs\non CT. Clinicians must not use\nthe software generated output\nalone without review as the\nprimary interpretation.","",""],["Segmentation\n(Contouring)\nTechnology","Deep learning","Deep learning","Deep learning","Deep learning"],["Operating\nSystem","Linux Ubuntu 20.04","Linux Ubuntu 20.04","Microsoft Windows","Windows based .NET front-end\napplication that also serves as\nagent Uploader supporting\nMicrosoft Windows 10 (64-bit)\nand Microsoft Windows Server\n2016.\nCloud-based Server based\nautomatic contouring"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p8-t0","doc_id":"K231928","page_num":8,"bbox":[72.44,89.99,720.75,536.99],"n_rows":5,"n_cols":5,"columns":["","","","","application compatible with\nLinux.\nWindows python-based\nautomatic contouring\napplication supporting\nMicrosoft Windows 10 (64-bit)\nand Microsoft Windows Server\n2016."],"rows":[["","","","","application compatible with\nLinux.\nWindows python-based\nautomatic contouring\napplication supporting\nMicrosoft Windows 10 (64-bit)\nand Microsoft Windows Server\n2016."],["User Population","Trained medical professionals\nincluding, but not limited to,\nradiation oncologists, medical\nphysicists, and dosimetrists.","Trained medical professionals\nincluding, but not limited to,\nradiation oncologists, medical\nphysicists, and dosimetrists.","It is used by radiation oncology\ndepartment.","Radiation treatment planners"],["Supported\nModalities","Non-contrast CT","Non-contrast CT","Segmentation Features:\nNon-Contrast CT\nRegistration Features: CT, MRI,\nPET","CT or MR input for contouring\nor registration/fusion.\nPET/CT input for\nregistration/fusion only.\nDICOM RTSTRUCT for output"],["Localization\nand Definition\nof Objects\n(ROI)","Organ-at risk of head and neck,\nchest, abdomen, and pelvis","Organ-at risk of head and neck\nregion","Organ-at-risk, including head\nand neck, thorax, abdomen and\npelvis (for both male and\nfemale)","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in preparation\nfor radiation therapy treatment\nplanning.\nCT or MR input for contouring\nof anatomical regions: Head and\nNeck, Thorax, Abdomen and\nPelvis"],["Organ-at risk\n(OAR)","A_Aorta, A_Carotid_L,\nA_Carotid_R, Bladder,\nBone_Mandible,\nBrachialPlex_L,\nBrachialPlex_R, Brain,","Brain, BrainStem, Esophagus,\nEye_L, Eye_R, Lens_L,\nLens_R, Mandible,\nOpticChiasm, OpticNerve_L,\nOpticNerve_R, OralCavity,","A_Aorta, Bladder,\nBone_Mandible,\nBrachialPlex_L,\nBrachialPlex_R, Brain,\nBrainstem, Breast_L, Breast_R,","CT Models:\nA_Aorta, A_Aorta_Asc,\nA_Aorta_Dsc, A_LAD,\nBladder, Bone_Ilium_L,\nBone_Ilium_R,"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p10-t0","doc_id":"K231928","page_num":10,"bbox":[72.45,89.99,720.75,491.24],"n_rows":4,"n_cols":5,"columns":["","V_Venacava_I, Vestibule_L,\nVestibule_R","","","LN_Neck_VIIB_L,\nLN_Neck_VIIB_R,\nLN_Pelvics, LN_Sclav_L,\nLN_Sclav_R, Liver, Lung_L,\nLung_R, Marrow_Ilium_L,\nMarrow_Ilium_R,\nMusc_Constrict, OpticChiasm,\nOpticNrv_L, OpticNrv_R,\nParotid_L, Parotid_R,\nPenileBulb, Pituitary, Prostate,\nRectum, Rib, SeminalVes,\nSpinalCanal, SpinalCord,\nStomach, Trachea,\nV_Venacava_S\nMR Models:\nOpticChiasm, OpticNrv_L,\nOpticNrv_R, Brainstem,\nHippocampus_L,\nHippocampus_R"],"rows":[["","V_Venacava_I, Vestibule_L,\nVestibule_R","","","LN_Neck_VIIB_L,\nLN_Neck_VIIB_R,\nLN_Pelvics, LN_Sclav_L,\nLN_Sclav_R, Liver, Lung_L,\nLung_R, Marrow_Ilium_L,\nMarrow_Ilium_R,\nMusc_Constrict, OpticChiasm,\nOpticNrv_L, OpticNrv_R,\nParotid_L, Parotid_R,\nPenileBulb, Pituitary, Prostate,\nRectum, Rib, SeminalVes,\nSpinalCanal, SpinalCord,\nStomach, Trachea,\nV_Venacava_S\nMR Models:\nOpticChiasm, OpticNrv_L,\nOpticNrv_R, Brainstem,\nHippocampus_L,\nHippocampus_R"],["Compatible\nTreatment\nPlanning\nSystem","No Limitation on TPS model,\nDICOM 3.0 compliance\nrequired.","No Limitation on TPS model,\nDICOM 3.0 compliance\nrequired.","No Limitation on TPS model,\nDICOM 3.0 compliance\nrequired","No Limitation"],["Automated\nWorkflow","EFAI HCAPSeg automatically\nprocesses input image data and\nsends the results as DICOM-RT\nStructure Sets to a\nuser-configurable target node.","EFAI HNSeg automatically\nprocesses input image data and\nsends the results as DICOM-RT\nStructure Sets to a\nuser-configurable target node.","AccuContour automatically\nprocesses input image data","Automatically contour, allow\nthe user to review and modify,\ngenerate DICOM-compliant\nstructure set data."],["User Interface","No","No","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p11-t0","doc_id":"K231928","page_num":11,"bbox":[72.12,424.5,538.0,715.12],"n_rows":13,"n_cols":3,"columns":["Table B. Demographic Information for Training and Test Data Sets","",""],"rows":[["Table B. Demographic Information for Training and Test Data Sets","",""],["","Training Dataset\n(n=1,410)","Testing Dataset\n(n=436)"],["Age","",""],["18 - 49 years old","95","16"],["50 - 69 years old","772","219"],["Above 70 years old","235","64"],["N/A","308","137"],["Gender","",""],["Female","563","110"],["Male","581","154"],["N/A","266","172"],["CT Manufacturer","",""],["Siemens","914","289"]],"caption_candidate":"GE Medical Systems, Philips, Toshiba.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p12-t0","doc_id":"K231928","page_num":12,"bbox":[72.19,89.62,537.97,176.62],"n_rows":4,"n_cols":3,"columns":["GE Medical Systems","436","109"],"rows":[["GE Medical Systems","436","109"],["Philips","56","35"],["Toshiba","1","2"],["N/A","3","1"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p12-t1","doc_id":"K231928","page_num":12,"bbox":[72.19,270.75,537.97,712.87],"n_rows":20,"n_cols":5,"columns":["Table C. Number of Images/Cases per OAR for Training and Testing Datasets","","","",""],"rows":[["Table C. Number of Images/Cases per OAR for Training and Testing Datasets","","","",""],["OAR","Training Dataset","","Testing Dataset",""],["","Number\nof Cases","Number\nof Images","Number\nof Cases","Number\nof Images"],["A_Aorta","1,091","77,731","119","7,030"],["A_Carotid_L","350","15,124","114","4,883"],["A_Carotid_R","347","11,883","114","4,118"],["Bladder","458","7,366","61","988"],["Bone_Mandible","667","17,013","66","1,457"],["BrachialPlex_L","474","17,909","113","3,903"],["BrachialPlex_R","473","16,978","113","3,643"],["Brain","484","22,154","66","2,894"],["Brainstem","484","11,126","66","1,403"],["Breast_L","350","14,049","76","2,832"],["Breast_R","347","14,495","75","2,727"],["Bronchus_Prox","353","7,523","113","2,315"],["Cavity_Oral","613","12,899","66","1,320"],["Cochlea_L","471","926","66","126"],["Cochlea_R","475","1,077","66","125"],["Duodenum","686","19,167","77","2,063"],["Ear_Internal_L","484","2,945","66","375"]],"caption_candidate":"datasets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p13-t0","doc_id":"K231928","page_num":13,"bbox":[72.37,89.62,538.12,720.37],"n_rows":29,"n_cols":5,"columns":["Ear_Internal_R","484","2,428","66","308"],"rows":[["Ear_Internal_R","484","2,428","66","308"],["Ear_Middle_L","484","2,162","66","277"],["Ear_Middle_R","484","2,128","66","258"],["Esophagus","1,126","61,405","114","4,844"],["Eye_L","482","6,150","66","721"],["Eye_R","484","6,182","66","727"],["FemurHeadNeck_L","462","13,358","61","1,819"],["FemurHeadNeck_R","457","13,136","61","1,802"],["Gallbladder","309","3,095","168","1,609"],["Glnd_Submand_L","604","7,233","66","808"],["Glnd_Submand_R","592","7,343","66","788"],["Glnd_Thyroid","838","14,605","114","1,956"],["Heart","716","22,271","119","3,012"],["Hippocampus_L","478","4,653","66","534"],["Hippocampus_R","475","4,432","66","463"],["IAC_L","117","326","105","176"],["IAC_R","121","333","100","148"],["Joint_TM_L","481","2,339","66","229"],["Joint_TM_R","484","2,231","66","233"],["Kidney_L","762","22,347","119","3,310"],["Kidney_R","720","20,989","119","3,407"],["Larynx","723","13,548","114","2,134"],["Lens_L","475","1,716","66","214"],["Lens_R","476","1,628","66","203"],["Liver","853","37,523","119","5,061"],["LN_Neck_IA","98","484","73","297"],["LN_Neck_IB_L","98","1,385","73","905"],["LN_Neck_IB_R","98","1,376","73","960"],["LN_Neck_II_L","98","1,936","73","1,201"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p14-t0","doc_id":"K231928","page_num":14,"bbox":[72.37,89.62,538.12,718.87],"n_rows":29,"n_cols":5,"columns":["LN_Neck_II_R","98","1,937","73","1,201"],"rows":[["LN_Neck_II_R","98","1,937","73","1,201"],["LN_Neck_III_L","98","1,083","73","817"],["LN_Neck_III_R","98","1,082","73","817"],["LN_Neck_IV_L","98","1,220","73","1,003"],["LN_Neck_IV_R","98","1,219","73","1,003"],["LN_Neck_V_L","98","2,773","73","2,227"],["LN_Neck_V_R","98","2,768","73","2,227"],["LN_Pelvics","220","9,486","177","7,872"],["Lobe_Temporal_L","481","10,045","66","1,175"],["Lobe_Temporal_R","483","10,141","66","1,185"],["Lung_L","896","50,332","119","4,261"],["Lung_R","878","49,483","119","4,263"],["OpticChiasm","479","1,793","66","279"],["OpticNrv_L","479","1,832","66","255"],["OpticNrv_R","479","2,089","66","276"],["Pancreas","757","16,684","77","1,707"],["Parotid_L","515","12,722","66","1,513"],["Parotid_R","514","12,408","66","1,501"],["PenileBulb","91","430","73","333"],["Pituitary","475","1,419","66","197"],["Prostate","205","2,887","75","1,091"],["Rectum","456","12,836","61","1,779"],["SeminalVes","206","1,534","75","613"],["Spc_Bowel","737","51,228","77","6,304"],["SpinalCanal","1,269","119,225","157","12,760"],["SpinalCord","1,407","139,337","157","13,881"],["Spleen","793","21,027","119","3,051"],["Stomach","808","25,949","119","3,758"],["Testis","128","1,301","67","801"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p15-t0","doc_id":"K231928","page_num":15,"bbox":[72.37,89.62,538.12,198.37],"n_rows":5,"n_cols":5,"columns":["Trachea","876","31,998","76","2,543"],"rows":[["Trachea","876","31,998","76","2,543"],["Uterus","163","4,087","78","1,522"],["V_Venacava_I","510","24,117","119","3,201"],["Vestibule_L","470","1,035","66","133"],["Vestibule_R","480","1,002","66","113"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p16-t0","doc_id":"K231928","page_num":16,"bbox":[71.37,90.75,540.19,299.62],"n_rows":8,"n_cols":7,"columns":["Table D. DSC Performance of EFAI HCAPSeg","","","","","",""],"rows":[["Table D. DSC Performance of EFAI HCAPSeg","","","","","",""],["","","EFAI HCAPSeg","","Comparison Device","","Statistical Result ‡"],["","","Mean DSC","SD","Mean DSC","SD","p-value"],["OARs Present in Both\nEFAI HCAPSeg and the\nComparison Device","Head & Neck","0.80","0.21","0.75","0.25","<.0001"],["","Chest","0.90","0.11","0.84","0.20","<.0001"],["","Abdomen & Pelvis","0.90","0.14","0.82","0.24","<.0001"],["OARs Unique to EFAI\nHCAPSeg","Unique OAR","0.82","0.19","-","-","<.0001"],["OAR, Organ-At-Risk; DSC, Dice Similarity Coefficient; SD, Standard Deviation.\n‡ A statistical result includes outcomes obtained from data analysis using statistical methods, encompassing the non-inferiority test for OARs\npresented in both EFAI HCAPSeg and the Comparison Device, as well as the superiority test for OARs unique to EFAI HCAPSeg. When the\np-value is <0.05, it indicates that EFAI HCAPSeg's performance is significantly non-inferior to or superior to the pre-specified performance,\nrespectively.","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p16-t1","doc_id":"K231928","page_num":16,"bbox":[71.37,371.25,540.19,612.37],"n_rows":8,"n_cols":7,"columns":["Table E. 95% HD Performance of EFAI HCAPSeg","","","","","",""],"rows":[["Table E. 95% HD Performance of EFAI HCAPSeg","","","","","",""],["","","EFAI HCAPSeg","","Comparison Device","","Statistical Result ‡"],["","","Median\n95% HD\n(mm)","Q1 - Q3\n(mm)","Median\n95% HD\n(mm)","Q1 - Q3\n(mm)","p-value"],["OARs Present in Both\nEFAI HCAPSeg and the\nComparison Device","Head & Neck","2.17","1.40 - 2.44","3.09","1.96 - 4.73","<.0001"],["","Chest","2.23","1.43 - 2.56","3.87","2.37 - 7.42","<.0001"],["","Abdomen & Pelvis","2.28","1.44 - 3.41","3.90","2.36 - 10.85","<.0001"],["OARs Unique to EFAI\nHCAPSeg","Unique OAR","2.24","1.00 - 4.69","-","-","<.0001"],["OAR, Organ-At-Risk; HD, Hausdorff Distance; Q1, First Quartile; Q3, Third Quartile.\nThe unit of measurement for the 95% HD is millimeters (mm).\n‡ A statistical result includes outcomes obtained from data analysis using statistical methods, encompassing the non-inferiority test for OARs\npresented in both EFAI HCAPSeg and the Comparison Device, as well as the superiority test for OARs unique to EFAI HCAPSeg. When the\np-value is <0.05, it indicates that EFAI HCAPSeg's performance is significantly non-inferior to or superior to the pre-specified performance,\nrespectively.","","","","","",""]],"caption_candidate":"EFAI HCAPSeg.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p17-t0","doc_id":"K231928","page_num":17,"bbox":[71.37,90.75,540.17,353.62],"n_rows":14,"n_cols":6,"columns":["Table F. DSC and 95% HD Performance of EFAI HCAPSeg across All Subgroups","","","","",""],"rows":[["Table F. DSC and 95% HD Performance of EFAI HCAPSeg across All Subgroups","","","","",""],["","","EFAI HCAPSeg","","",""],["","","Mean DSC","SD","Median\n95% HD (mm)","Q1 - Q3 (mm)"],["Gender","Female","0.83","0.23","2.28","1.40 - 3.30"],["","Male","0.85","0.17","2.23","1.39 - 3.16"],["Age Group","18 - 49 y/o","0.85","0.18","2.22","1.32 - 2.81"],["","50 - 69 y/o","0.83","0.23","2.28","1.40 - 3.38"],["","≥ 70 y/o","0.85","0.20","2.27","1.44 - 4.06"],["CT Manufacturer","GE","0.84","0.22","2.23","1.37 - 3.16"],["","Philips","0.82","0.19","2.24","1.41 - 3.15"],["","Siemens","0.89","0.15","2.29","1.42 - 3.31"],["","Others ‡","0.89","0.15","2.30","1.41 - 3.47"],["CT Slice Thickness","0.5 - 3.0 mm","0.84","0.15","2.24","1.43 - 3.13"],["","3.1 - 5.0 mm","0.83","0.23","2.20","1.33 - 3.05"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p17-t1","doc_id":"K231928","page_num":17,"bbox":[71.37,444.75,540.17,702.37],"n_rows":13,"n_cols":7,"columns":["Table G. Individual OAR performance of EFAI HCAPSeg (Proposed Device)","","","","","",""],"rows":[["Table G. Individual OAR performance of EFAI HCAPSeg (Proposed Device)","","","","","",""],["OAR","DSC Performance","","","95% HD Performance","",""],["","EFAI HCAPSeg","","Referenced\nPerformance §","EFAI HCAPSeg","","Referenced\nPerformance §"],["","Mean DSC","SD","Mean DSC","Median 95%\nHD (mm)","Q1 - Q3 (mm)","Median\n95% HD"],["A_Aorta","0.86","0.04","0.26","2.36","2.08 - 3.43","66.60"],["A_Carotid_L †","0.71","0.20","0.65","5.46","2.21 - 10.13","≤ 3.50"],["A_Carotid_R †","0.67","0.21","0.65","5.63","2.52 - 8.14","≤ 3.50"],["Bladder","0.77","0.30","0.70","4.93","3.16 - 8.54","6.22"],["Bone_Mandible","0.89","0.04","0.81","2.23","2.05 - 2.35","4.32"],["BrachialPlex_L","0.72","0.02","0.63","2.22","2.04 - 2.40","8.45"],["BrachialPlex_R","0.71","0.03","0.62","2.25","2.13 - 3.33","9.67"],["Brain","0.99","0.04","0.86","1.36","1.15 - 2.18","3.96"],["Brainstem","0.92","0.07","0.75","3.17","2.49 - 3.47","5.75"]],"caption_candidate":"Table G .","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p18-t0","doc_id":"K231928","page_num":18,"bbox":[71.62,89.62,540.37,708.37],"n_rows":33,"n_cols":7,"columns":["Breast_L","0.89","0.03","0.78","3.15","1.60 - 6.33","10.86"],"rows":[["Breast_L","0.89","0.03","0.78","3.15","1.60 - 6.33","10.86"],["Breast_R","0.89","0.03","0.78","2.38","2.14 - 4.76","11.54"],["Bronchus_Prox †","0.93","0.03","0.65","1.00","1.00 - 2.99","≤ 3.50"],["Cavity_Oral","0.92","0.12","0.78","2.28","1.35 - 4.13","7.70"],["Cochlea_L","0.65","0.26","0.45","2.11","1.35 - 2.32","3.96"],["Cochlea_R","0.70","0.21","0.51","2.09","1.33 - 2.33","3.96"],["Duodenum","0.74","0.24","0.57","6.49","2.44 - 20.81","27.41"],["Ear_Internal_L","0.85","0.08","0.71","1.48","1.24 - 2.25","3.97"],["Ear_Internal_R","0.84","0.14","0.69","1.46","1.22 - 2.24","3.97"],["Ear_Middle_L","0.83","0.16","0.67","2.15","1.37 - 2.30","4.87"],["Ear_Middle_R","0.84","0.16","0.68","1.43","1.23 - 2.19","3.97"],["Esophagus","0.84","0.08","0.71","2.50","2.08 - 7.36","6.01"],["Eye_L","0.94","0.14","0.80","1.37","1.23 - 2.21","3.95"],["Eye_R","0.92","0.19","0.79","1.33","1.16 - 2.30","3.95"],["FemurHeadNeck_L","0.95","0.15","0.82","2.21","1.37 - 2.45","4.86"],["FemurHeadNeck_R","0.92","0.14","0.76","2.30","1.42 - 3.02","5.69"],["Gallbladder †","0.81","0.31","0.65","1.00","1.00 - 2.93","≤ 3.50"],["Glnd_Submand_L","0.82","0.08","0.69","1.40","1.16 - 2.17","5.80"],["Glnd_Submand_R","0.74","0.19","0.67","1.35","1.21 - 2.10","5.83"],["Glnd_Thyroid","0.79","0.16","0.60","2.24","1.91 - 2.59","8.60"],["Heart","0.93","0.08","0.84","2.25","1.42 - 3.32","4.91"],["Hippocampus_L","0.69","0.27","0.54","1.50","1.28 - 2.29","5.13"],["Hippocampus_R","0.55","0.34","0.45","1.52","1.29 - 2.49","5.88"],["IAC_L","0.60","0.34","0.46","2.39","2.20 - 3.18","5.85"],["IAC_R","0.66","0.31","0.41","2.37","2.16 - 2.77","3.97"],["Joint_TM_L","0.63","0.28","0.50","3.06","2.36 - 3.45","4.93"],["Joint_TM_R","0.67","0.18","0.49","3.10","2.49 - 3.65","4.90"],["Kidney_L","0.93","0.17","0.78","1.36","1.21 - 2.37","4.88"],["Kidney_R","0.95","0.14","0.79","1.34","1.15 - 1.89","4.38"],["Larynx","0.83","0.11","0.66","2.44","2.18 - 3.54","6.46"],["Lens_L","0.78","0.28","0.69","2.11","1.43 - 2.26","3.96"],["Lens_R","0.80","0.31","0.70","2.20","1.44 - 2.39","3.95"],["Liver","0.95","0.02","0.86","2.02","1.31 - 2.41","4.95"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p19-t0","doc_id":"K231928","page_num":19,"bbox":[71.62,89.62,540.37,708.37],"n_rows":33,"n_cols":7,"columns":["LN_Neck_IA †","0.83","0.06","0.65","2.00","1.00 - 2.73","≤ 3.50"],"rows":[["LN_Neck_IA †","0.83","0.06","0.65","2.00","1.00 - 2.73","≤ 3.50"],["LN_Neck_IB_L †","0.90","0.03","0.65","1.87","1.10 - 2.24","≤ 3.50"],["LN_Neck_IB_R †","0.88","0.04","0.65","2.00","1.80 - 2.95","≤ 3.50"],["LN_Neck_II_L †","0.89","0.04","0.65","1.73","1.41 - 2.73","≤ 3.50"],["LN_Neck_II_R †","0.87","0.06","0.65","2.24","1.41 - 3.00","≤ 3.50"],["LN_Neck_III_L †","0.81","0.09","0.65","2.94","2.02 - 4.51","≤ 3.50"],["LN_Neck_III_R †","0.84","0.07","0.65","2.53","1.56 - 3.74","≤ 3.50"],["LN_Neck_IV_L †","0.81","0.11","0.65","3.10","2.19 - 4.16","≤ 3.50"],["LN_Neck_IV_R †","0.81","0.08","0.65","3.02","2.40 - 4.16","≤ 3.50"],["LN_Neck_V_L †","0.84","0.06","0.65","2.94","2.02 - 5.57","≤ 3.50"],["LN_Neck_V_R †","0.86","0.04","0.65","2.91","2.00 - 3.57","≤ 3.50"],["LN_Pelvics †","0.90","0.23","0.65","1.00","1.00 - 2.99","≤ 3.50"],["Lobe_Temporal_L","0.94","0.03","0.77","1.43","1.21 - 2.21","4.91"],["Lobe_Temporal_R","0.93","0.08","0.76","2.03","1.30 - 2.33","4.90"],["Lung_L","0.96","0.01","0.87","2.27","2.02 - 2.42","4.32"],["Lung_R","0.95","0.01","0.88","2.05","1.25 - 2.38","3.97"],["OpticChiasm","0.75","0.24","0.60","2.30","2.10 - 2.52","5.13"],["OpticNrv_L","0.68","0.25","0.56","2.24","1.59 - 2.36","3.97"],["OpticNrv_R","0.68","0.22","0.54","2.23","1.88 - 2.46","4.91"],["Pancreas","0.83","0.16","0.63","2.82","2.12 - 7.89","10.63"],["Parotid_L","0.87","0.14","0.74","2.08","1.38 - 2.27","6.52"],["Parotid_R","0.86","0.12","0.73","2.04","1.31 - 2.40","7.11"],["PenileBulb †","0.66","0.34","0.50","2.30","0.98 - 4.25","≤ 3.50"],["Pituitary","0.67","0.39","0.57","2.02","2.02 - 2.02","3.97"],["Prostate","0.79","0.21","0.41","2.43","2.10 - 5.10","7.36"],["Rectum","0.84","0.08","0.51","2.92","2.30 - 5.32","10.33"],["SeminalVes","0.92","0.12","0.46","2.07","1.37 - 3.57","6.04"],["Spc_Bowel","0.87","0.18","0.57","8.07","5.63 - 14.46","26.64"],["SpinalCanal","0.88","0.03","0.73","2.30","2.14 - 2.47","8.92"],["SpinalCord","0.90","0.02","0.78","2.16","1.43 - 2.37","5.84"],["Spleen","0.93","0.15","0.79","1.45","1.21 - 2.39","4.94"],["Stomach","0.85","0.12","0.80","2.89","2.22 - 7.10","5.82"],["Testis","0.82","0.29","0.31","5.46","3.16 - 22.56","40.74"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231928-p20-t0","doc_id":"K231928","page_num":20,"bbox":[72.17,89.62,540.37,183.37],"n_rows":5,"n_cols":7,"columns":["Trachea","0.91","0.03","0.79","2.30","2.08 - 2.88","5.13"],"rows":[["Trachea","0.91","0.03","0.79","2.30","2.08 - 2.88","5.13"],["Uterus †","0.78","0.29","0.80","3.85","2.91 - 12.38","≤ 3.50"],["V_Venacava_I †","0.93","0.10","0.65","1.00","1.00 - 3.01","≤ 3.50"],["Vestibule_L","0.79","0.25","0.54","1.47","1.29 - 2.25","3.96"],["Vestibule_R","0.76","0.16","0.55","2.15","1.41 - 2.31","3.97"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p5-t0","doc_id":"K231929","page_num":5,"bbox":[72.32,122.42,523.08,285.02],"n_rows":6,"n_cols":4,"columns":["","510(k) Sponsor:","","Sydney Neuroimaging Analysis Centre Pty Ltd (SNAC)"],"rows":[["","510(k) Sponsor:","","Sydney Neuroimaging Analysis Centre Pty Ltd (SNAC)"],["Address:","","","Level 1, 94 Mallett Street\nCamperdown NSW 2050\nAustralia"],["Contact Person:","","","Dr Tim (Chenyu) Wang\nDirector of Operations, Sydney Neuroimaging Analysis Centre"],["","Contact Information:","","Email: tim@snac.com.au\nPhone: + 61 2 9114 4187"],["","","",""],["","Date Prepared:","","16 Dec 2023"]],"caption_candidate":"5.1 General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p5-t1","doc_id":"K231929","page_num":5,"bbox":[72.32,319.06,523.08,504.14],"n_rows":8,"n_cols":4,"columns":["","Device Name:","","iQ-solutions™"],"rows":[["","Device Name:","","iQ-solutions™"],["","Trade Name:","","iQ-solutions™"],["","Common Name:","","Medical Image Processing Software"],["","Classification Name","","System, Image processing, Radiological"],["","Classification Panel:","","Radiology"],["","CFR Section:","","21 CFR §892.2050"],["","Device Class:","","Class II"],["","Product Code","","QIH, LLZ"]],"caption_candidate":"5.2 Device Name and Classification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p5-t2","doc_id":"K231929","page_num":5,"bbox":[72.32,538.18,523.08,746.54],"n_rows":9,"n_cols":4,"columns":["","Product Name:","","icobrain"],"rows":[["","Product Name:","","icobrain"],["","Device Trade Name:","","Icobrain"],["","510(k) Number","","K192130"],["","Clearance Date:","","December 13, 2019"],["","Manufacturer:","","icometrix NV"],["","Common Name","","Medical Image Processing Software"],["","Classification Name:","","System, Image processing, Radiological"],["","Classification Panel:","","Radiology"],["","CFR Section","","21 CFR §892.2050"]],"caption_candidate":"5.3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p6-t0","doc_id":"K231929","page_num":6,"bbox":[72.32,72.7,523.08,118.34],"n_rows":2,"n_cols":4,"columns":["","Device Class","","Class II"],"rows":[["","Device Class","","Class II"],["","Product Code","","LLZ"]],"caption_candidate":"Sydney Neuroimaging Analysis Centre Traditional 510(k) iQ-solutions™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p10-t0","doc_id":"K231929","page_num":10,"bbox":[64.83,72.34,773.62,507.12],"n_rows":6,"n_cols":8,"columns":["Characteristic","","Subject device:","","","Predicate Device:","","Summary"],"rows":[["Characteristic","","Subject device:","","","Predicate Device:","","Summary"],["","","iQ-solutions™","","","icobrain 5.0 (K192130)","",""],["","• DICOM compatible\n• Segmentation by machine learning and\ndeep learning algorithms (supervised\nsegmentation with Convolutional Neural\nNetworks)\n• Image pre-processing components\n• Measurement calculation\n• Report generation techniques","","","• Segmentation by classical machine learning\nand deep learning (supervised voxel\nclassification with Convolutional Neural\nNetworks)\n• Image pre-processing components\n• Measurement calculation\n• Report generation techniques","","",""],["Anatomical Region\nof Interest","Head","","","Head","","","Same"],["Product Input\n(Data Acquisition\nProtocol)","• Pre-contrast T1-weighted MRI scans from\nsingle or multiple time points,\n• Fluid-attenuated inversion recovery (FLAIR)\nMRI scans from single or multiple time\npoints, and\n• Post-contrast T1-weighted MRI scans from\na single time point.","","","• T1-weighted and fluid-attenuated inversion\nrecovery (FLAIR) MRI images from a single\nor multiple time points\n• Non-contrast CT (NCCT) from a single time\npoint.","","","Similar.\nBoth the subject device and the predicate\ndevice process T1 and FLAIR MRI images from\nsingle or multiple time points.\nNCCT may be used with icobrain 5.0 but not the\nsubject device; lack of this additional input\ncompatibility does not impact the safety or\nclinical function of the subject device."],["Product Output","• Multiple electronic reports with volumetric\ninformation on brain structures and white\nmatter hyperintensities (if any)\n• Automatically compares results to\nreference percentile data and to prior scans\nwhen available\n• Annotated DICOM images that can be\ndisplayed on DICOM workstations and\nPicture Archive and Communications\nSystems (PACS)","","","• Multiple electronic reports with volumetric\ninformation on brain structures and\nhyperintensities and midline shift (for NCCT\nonly)\n• Automatically compares results to a\nreference healthy population data and to\nprior scans when available\n• Annotated DICOM images that can be\ndisplayed on DICOM workstations and\nPicture Archive and Communications\nSystems (PACS)","","","Similar.\nicobrain 5.0 additionally outputs the degree of\n‘midline shift’ but this is calculated on NCCT\n(relevant to specific clinical scenarios only). As\niQ-solutions™ does not analyze NCCT, this\ndifference does not impact the safety of the\nsubject device and is not clinically significant"]],"caption_candidate":"Sydney Neuroimaging Analysis Centre Traditional 510(k) iQ-solutions™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p11-t0","doc_id":"K231929","page_num":11,"bbox":[64.87,72.34,773.59,520.92],"n_rows":3,"n_cols":8,"columns":["Characteristic","","Subject device:","","","Predicate Device:","","Summary"],"rows":[["Characteristic","","Subject device:","","","Predicate Device:","","Summary"],["","","iQ-solutions™","","","icobrain 5.0 (K192130)","",""],["Findings Covered","MR:\n• Normalized volume and volume changes of\nthe whole brain\n• Normalized volume and volume changes of\ngray matter\n• Normalized volume and volume changes of\ncortical gray matter\n• Normalized cortical volumes of cortex in\nbrain lobes (frontal, temporal, parietal and\noccipital)\n• Normalized volume and volume changes in\nthe hippocampi\n• Normalized volume and volume changes of\nthe thalamus\n• Asymmetry index of structures, including\ncortex in lobes and hippocampus\n• Unnormalized volume and volume changes\nof FLAIR white matter hyperintensities\n• Unnormalized volume and volume changes\nof T1-w white matter hyperintensities (in\npost-contrast T1-w only)","","","MR:\n• Normalized volume and volume changes of\nthe whole brain\n• Normalized volume and volume changes of\ngray matter\n• Normalized volume and volume changes of\ncortical gray matter\n• Normalized volume and volume changes of\ncortex in frontal, temporal, parietal and\noccipital lobes\n• Normalized volume and volume changes in\nthe hippocampi\n• Normalized volume and volume change of\nleft and right hippocampus\n• Asymmetry index of structures, including\ncortex in lobes and hippocampus\n• Unnormalized volume and volume changes\nof FLAIR white matter hyperintensities\n• FLAIR white matter hyperintensities in\ndifferent regions (juxtacortical,\nperiventricular, deep white matter and\ninfratentorial).\n• Unnormalized volume and volume changes\nof T1-w white matter hyperintensities and\nhypointensities\nCT:\n• Normalized volumes of the whole brain\n• Normalized volumes of the lateral\nventricles\n• Normalized volumes of basal cisterns","","","Similar.\niQ-solutions™ does not process NCCT images\nand therefore does not report findings for CT\nimages.\nFor head MRI analysis, iQ-solutions™ is similar\nto icobrain 5.0, except that the subject device\niQ-solutions™ does not report statistics related\nto regional (lobar) cortical volume change or\nT1-w image-derived hypo-intensities. iQ-\nsolutions™ additionally reports volume analysis\nof the thalamus.\nThese differences are not expected to affect\nthe safety or effectiveness of the subject\ndevice or to be clinically significant in the\nproposed intended use."]],"caption_candidate":"Sydney Neuroimaging Analysis Centre Traditional 510(k) iQ-solutions™","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p13-t0","doc_id":"K231929","page_num":13,"bbox":[72.27,454.09,518.49,607.68],"n_rows":4,"n_cols":11,"columns":["Datasets","","Diagnosis","","","Number of","","Age (mean±std)","","Number of Scans",""],"rows":[["Datasets","","Diagnosis","","","Number of","","Age (mean±std)","","Number of Scans",""],["","","(subject/scans)","","","Subjects (F/M)","","","","(Vendor:1.5T/3T)",""],["Public\nData","Healthy (1823/2225),\nDementia (336/404)","","","2159 (1146/1013)","","","18y to 95y\n(44.84±20.63)","2629, including SIEMENS\n(347/1449), Philips\n(307/208), GE (79/221)\nand others.","",""],["Private\nData","Multiple sclerosis\n(1570/5664)","","","1570 (1069/501)","","","18y to 93y\n(44.02±13.49)","5664, including SIEMENS\n(698/1052), Philips\n(243/1350), GE\n(1008/1206) and others.","",""]],"caption_candidate":"Table 3. Demographic Summary for Used Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p14-t0","doc_id":"K231929","page_num":14,"bbox":[72.25,94.67,522.71,380.52],"n_rows":14,"n_cols":10,"columns":["Analysis Modules/Datasets","","Number of Cases","","","Number of","","","Number of",""],"rows":[["Analysis Modules/Datasets","","Number of Cases","","","Number of","","","Number of",""],["","","(Train/Validation)","","","Cases (Test)","","","Subjects (All)",""],["Sequence Classification","4862","","","1207","","","2784","",""],["Brain Extraction","1843","","","458","","","1454","",""],["Scaling Factor Estimation","2986","","","527","","","3513","",""],["White matter hyperintensity Segmentation","1858","","","464","","","1026","",""],["Contrast-Enhancing Lesion Segmentation","79","","","737","","","310","",""],["Lesion Inpainting","449","","","80","","","529","",""],["Brain Tissue Segmentation","4179","","","500","","","3313","",""],["Brain Volume Change Estimation","1487","","","166","","","1648","",""],["WMH Lesion Activity","116","","","64","","","180","",""],["Cortical Lobar and Subcortical Structure\nSegmentation","Not applicable **","","","1504","","","1436","",""],["Test-ReTest Dataset","Not applicable **","","","120","","","3","",""],["Comprehensive Test Set","Not applicable **","","","81","","","81","",""]],"caption_candidate":"Table 4. Summary of Number of Cases used in Developing/Evaluating Analysis Modules","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231929-p15-t0","doc_id":"K231929","page_num":15,"bbox":[72.5,253.14,522.82,511.44],"n_rows":12,"n_cols":12,"columns":["","Analysis Modules","","","Metric Result","","","Acceptable Rate","","","Pass/Fail",""],"rows":[["","Analysis Modules","","","Metric Result","","","Acceptable Rate","","","Pass/Fail",""],["Sequence Classification","","","Accuracy = 100%","","","100%","","","Pass","",""],["Brain Extraction","","","DICE = 0.982","","","99.3%","","","Pass","",""],["Scaling Factor Estimation","","","STD = 0.0096","","","100%","","","Pass","",""],["White matter hyperintensity Segmentation","","","DICE = 0.789","","","98.8%","","","Pass","",""],["Contrast-Enhancing Lesion Segmentation","","","DICE = 0.790","","","92.1%","","","Pass","",""],["Lesion Inpainting","","","PSNR = 30.79dB","","","97.5%","","","Pass","",""],["Brain Tissue Segmentation","","","DICE = 0.972","","","100%","","","Pass","",""],["Brain Volume Change Estimation","","","R2 = 0.869","","","96.3%","","","Pass","",""],["WMH Lesion Activity","","","R2 = 0.833","","","97.5%","","","Pass","",""],["Cortical Lobar and Subcortical Structure\nSegmentation","","","R2 = 0.833","","","96.0%","","","Pass","",""],["Substructure Volume Change Estimation","","","STD = 0.0102","","","98.8%","","","Pass","",""]],"caption_candidate":"Table 5: Summary of Performances of all the Analysis Modules","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231955-p4-t0","doc_id":"K231955","page_num":4,"bbox":[72.24,86.88,524.04,482.88],"n_rows":12,"n_cols":2,"columns":["Submitter’s Name:","Carlsmed, Inc."],"rows":[["Submitter’s Name:","Carlsmed, Inc."],["Submitter’s Address:","1800 Aston Ave, Ste 100\nCarlsbad, CA 92008"],["Submitter’s Telephone:","760-766-1926"],["Contact Person:","Karen Liu, VP Quality and Regulatory\nCarlsmed, Inc.\n1800 Aston Avenue Suite 100\nCarlsbad, CA 92008\n760-766-1926\nregulatory@carlsmed.com"],["Date Summary was Prepared:","October 31, 2023"],["Trade or Proprietary Name:","aprevo® Digital Segmentation"],["Predicate Clearance Numbers\nand Name","K183105, Mimics Medical"],["Reference Device Number\nand Name","K202034 aprevo™ Intervertebral Body Fusion Device\nK201232 Limbus Contour"],["Common or Usual Name:","Medical Image Management and Processing System"],["Classification:","Class II per 21 CFR §892.2050"],["Product Code:","QIH"],["Classification Panel:","Radiology"]],"caption_candidate":"510(K) SUMMARY K231955","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231955-p5-t0","doc_id":"K231955","page_num":5,"bbox":[72.02,253.59,543.19,714.84],"n_rows":6,"n_cols":12,"columns":["","Characteristic","","","Subject Device","","","Predicate Device","","","Differences",""],"rows":[["","Characteristic","","","Subject Device","","","Predicate Device","","","Differences",""],["Name","","","aprevo® Digital\nSegmentation","","","Mimics Medical","","","","",""],["Clearance\nNumber","","","K231955","","","K183105","","","","",""],["Regulation\nNumber","","","892.2050","","","892.2050","","","Identical","",""],["Product Code","","","QIH","","","LLZ","","","Similar: both are Image\nProcessing Systems","",""],["Indications For\nUse","","","aprevo® Digital\nSegmentation software\nis intended to be used\nby trained, medically\nknowledgeable design\npersonnel to perform\ndigital image\nsegmentation of the\nspine, primarily\nlumbar anatomy. The\ndevice inputs DICOM\nimages and outputs a\n3-D model of the\nspine.","","","Mimics Medical is\nintended for use as a\nsoftware interface and\nimage segmentation system\nfor the transfer of medical\nimaging information to an\noutput file. Mimics\nMedical is also intended for\nmeasuring and treatment\nplanning.\nThe Mimics Medical\noutput can be used for the\nfabrication of physical\nreplicas of the output file\nusing traditional or additive\nmanufacturing methods.\nThe physical replica can be\nused for diagnostic\npurposes in the field of\northopaedic, maxillofacial\nand cardiovascular\napplications.\nMimics Medical should be\nused in conjunction with\nexpert clinical judgment.","","","Similar. The subject device\nhas a narrower indication for\nuse compared to the\npredicate device.","",""]],"caption_candidate":"comparison between the subject device to its predicate device, Mimics Medical (K183105)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231955-p6-t0","doc_id":"K231955","page_num":6,"bbox":[72.03,54.39,543.21,427.08],"n_rows":8,"n_cols":12,"columns":["","Characteristic","","","Subject Device","","","Predicate Device","","","Differences",""],"rows":[["","Characteristic","","","Subject Device","","","Predicate Device","","","Differences",""],["","Technical Characteristics","","","","","","","","","",""],["Compatible\nInput File\nTypes","","","DICOM","","","DICOM and standard\nimaging formats (such as\nRAW, TIFF, BMP and\njpeg format)","","","Similar. The subject device\nhas narrower input file types.","",""],["Segmentation\nFunctionality","","","Automatic Spinal\nAlgorithm","","","Manual tools, Semi-\nautomatic tools, and\nautomatic algorithms","","","Similar. Both devices\ninclude automated spine\nsegmentation tool.","",""],["User\nInteraction","","","User cannot review\nand edit segmentation\nand 3D models","","","Contains tools to review\nand edit segmentation and\n3D models","","","Similar: The output of both\ndevices can be reviewed by\nthe user. While the predicate\ndevice has a viewer to\nreview and edit\nsegmentation outputs the\nsubject device output does\nnot include any viewer but\nits outputs can be reviewed\nas part of the entire\nworkflow utilizing 3rd party\nsoftware.","",""],["3D Model\nGeneration","","","The subject device\ngenerates a 3D model","","","The predicate device\ngenerates a 3D model","","","Identical","",""],["Export Outputs","","","The subject device\ngenerates an output\nfile.","","","The predicate device\ngenerates an output file.","","","Identical","",""],["Intended User\nPopulation","","","Trained Personnel,\nKnowledgeable in\nMedicine","","","Trained personnel,\nknowledgeable in medicine","","","Identical","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231965-p11-t0","doc_id":"K231965","page_num":11,"bbox":[36.24,82.08,175.2,124.92],"n_rows":3,"n_cols":2,"columns":["Uterus","95%"],"rows":[["Uterus","95%"],["Endometrium","89%"],["Fibroids","88%"]],"caption_candidate":"Primary verification – qualitative results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231965-p11-t1","doc_id":"K231965","page_num":11,"bbox":[36.24,296.88,175.2,339.72],"n_rows":3,"n_cols":2,"columns":["Uterus","100%"],"rows":[["Uterus","100%"],["Endometrium","91%"],["Fibroids","88%"]],"caption_candidate":"Secondary evaluation – qualitative results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231965-p12-t0","doc_id":"K231965","page_num":12,"bbox":[66.6,407.64,499.44,458.4],"n_rows":4,"n_cols":3,"columns":["Anatomy","DICE when successful","DICE when failed"],"rows":[["Anatomy","DICE when successful","DICE when failed"],["Uterus","0.89 ± 0.03","n/a"],["Endometrium","0.70 ± 0.18","0.29 ± 0.27"],["Fibroids","0.70 ± 0.13","0.48 ± 0.17"]],"caption_candidate":"scores (i.e., Dice coefficient) and qualitative assessment by independent clinical experts.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231966-p4-t0","doc_id":"K231966","page_num":4,"bbox":[216.12,691.8,571.92,719.4],"n_rows":2,"n_cols":3,"columns":["The LOGIQ E10 is a full featured, track 3, general purpose diagnostic","",""],"rows":[["The LOGIQ E10 is a full featured, track 3, general purpose diagnostic","",""],["ultrasound system which consists of a mobile console approximately 585","",""]],"caption_candidate":"Ultrasound System","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231966-p5-t0","doc_id":"K231966","page_num":5,"bbox":[216.12,79.8,571.92,148.8],"n_rows":5,"n_cols":5,"columns":["mm wide (keyboard), 991 mm deep and 1300 mm high that provides","","","",""],"rows":[["mm wide (keyboard), 991 mm deep and 1300 mm high that provides","","","",""],["digital acquisition, processing and display capability. The user interface","","","",""],["includes a computer keyboard, specialized controls, 12-inch high-","","","",""],["resolution color touch screen and 23.8-inch High Contrast LED LCD","","","",""],["monitor.","","","",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231966-p7-t0","doc_id":"K231966","page_num":7,"bbox":[217.32,141.48,570.0,720.24],"n_rows":4,"n_cols":2,"columns":["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• For Longitudinal model the accuracy of\nmeasurement is expected to be higher than\n80% and for the Transverse model it is\nexpected to be higher than 70%\n• The number of individual patients’ images\nwere collected from: 30 Patients.\n• The number of samples is 60 with 30\nLongitudinal views and 30 Transverse view"],"rows":[["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• For Longitudinal model the accuracy of\nmeasurement is expected to be higher than\n80% and for the Transverse model it is\nexpected to be higher than 70%\n• The number of individual patients’ images\nwere collected from: 30 Patients.\n• The number of samples is 60 with 30\nLongitudinal views and 30 Transverse view"],["Information about clinical\nsubgroups and confounders\npresent in the dataset","• Gender: Male & Female\n• Age: range 26-81 yrs old\n• Ethnicity/Country; USA (58%) and Japan\n(42%)"],["Information about equipment\nand protocols used to collect\nimages","The datasetused for final verification was collected\nprospectively on 30 demographically\ndiverse patients at 2 sites: Japan and the USA\nexclusively with the system under consideration\nGE Logiq Fortis after the Auto Renal Measure\nAssistant function was developed using C1-6-D\nprobe in Abdomen application;"],["Information about how the\nreference standard was\nderived from the dataset (i.e.\nthe “truthing” process)","• The Validation set of 30 patient ( 60 images )\nwere loaded onto the LOGIQ validation\nsystem.\n• 2 Readers (certified sonographer/Clinician) to\nground truth the measurements: Length on the\nLongitudinal views and the Height and Width\nMeasurements on the Transverse views.\n• Board Certified Nephrologist arbitrated the\nground truth between the above two readers to\nestablish the reference standard for the dataset\n• Summary of Results:\nThe Longitudinal model for length\nmeasurements has average accuracy of 96.45\nwith 95% CI of ± 1.26% and average absolute\nerror of 0.35cm at 95% CI of ±0.12 cm.\nThe Transverse model for width\nmeasurements has average accuracy of\n92.94% with 95% CI of ± 3.02% and average\nabsolute error of 0.38cm at 95% CI of ±0.14\ncm.\nThe Transverse model for width\nmeasurements has average accuracy of\n93.13% with 95% CI of ± 3.63% and average"]],"caption_candidate":"Auto Renal Measure Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231966-p8-t0","doc_id":"K231966","page_num":8,"bbox":[217.32,201.48,569.49,692.4],"n_rows":5,"n_cols":2,"columns":["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• The overall model success rate of the Aorta,\nKidney, Liver, GB, and Pancreas view\nsuggestion is expected to be 80% or higher.\n• The number of individual patients’ images\nwere collected from: 50+ patients\n• The number of samples, if different from\nabove, and the relationship between the two:\n1100+ images"],"rows":[["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• The overall model success rate of the Aorta,\nKidney, Liver, GB, and Pancreas view\nsuggestion is expected to be 80% or higher.\n• The number of individual patients’ images\nwere collected from: 50+ patients\n• The number of samples, if different from\nabove, and the relationship between the two:\n1100+ images"],["Information about clinical\nsubgroups and confounders\npresent in the dataset","• Gender: Male & Female\n• Age: Wide range, but specific age not\ncollected\n• Ethnicity/Country; USA (77%) and Australia\n(23%)"],["Information about equipment\nand protocols used to collect\nimages","Mix of data from across three different probe\nmodels and two different Console variants. The data\ncollection protocol was standardized across all data\ncollection sites."],["Information about how the\nreference standard was\nderived from the dataset (i.e.\nthe “truthing” process)","• Before the process of data annotation, all\ninformation displayed on the device is\nremoved and performed on information\nextracted purely from Ultrasound B-mode\nimages.\n• Readers (certified sonographer/Clinician) to\nground truth the “anatomy” visible in static B-\nMode image. (Before running AI)\n• Ran AI and created confusion matrix of\nground truth vs AI predictions.\n• Calculated the accuracies of the algorithm\nagainst each class."],["Description of how\nindependence of test data\nfrom training data was\nensured","The exams used for test/training validation purpose\nare separated from the ones used during training\nprocess and there is no overlap between the two."]],"caption_candidate":"Auto Abdominal Color Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231966-p9-t0","doc_id":"K231966","page_num":9,"bbox":[217.32,103.68,570.0,608.16],"n_rows":5,"n_cols":2,"columns":["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• The overall model success rate of the\nAbdomen, Air, Breast, Carotid, Leg, MSK,\nScrotal, Thyroid and Carotid/Thyroid (Mixed)\nview suggestion is expected to be 80% or\nhigher.\n• The number of individual patients’ images\nwere collected from: 110+ patients\n• The number of samples, if different from\nabove, and the relationship between the two:\n2600+ images"],"rows":[["Summary test statistics or\nother test results including\nacceptance criteria or other\ninformation supporting the\nappropriateness of the\ncharacterized performance","• The overall model success rate of the\nAbdomen, Air, Breast, Carotid, Leg, MSK,\nScrotal, Thyroid and Carotid/Thyroid (Mixed)\nview suggestion is expected to be 80% or\nhigher.\n• The number of individual patients’ images\nwere collected from: 110+ patients\n• The number of samples, if different from\nabove, and the relationship between the two:\n2600+ images"],["Information about clinical\nsubgroups and confounders\npresent in the dataset","• Gender: Male & Female\n• Age: Wide range, but specific age not\ncollected\n• Ethnicity/Country; USA (41.2%) , Austria\n(3.8%), Australia (1.1%), Japan (41.3%), Italy\n(0.7%) and Greece (12%)."],["Information about equipment\nand protocols used to collect\nimages","Mix of data from across five different probe models\nand three different Console variants. The data\ncollection protocol was standardized across all data\ncollection sites."],["Information about how the\nreference standard was\nderived from the dataset (i.e.\nthe “truthing” process)","• Before the process of data annotation, all\ninformation displayed on the device is\nremoved and performed on information\nextracted purely from Ultrasound B-mode\nimages.\n• Readers (certified sonographer/Clinician) to\nground truth the “anatomy” visible in static B-\nMode image. (Before running AI)\n• Ran AI and created confusion matrix of\nground truth vs AI predictions.\n• Calculated the accuracies of the algorithm\nagainst each class."],["Description of how\nindependence of test data\nfrom training data was\nensured","The exams used for test/training validation purpose\nare separated from the ones used during training\nprocess and there is no overlap between the two."]],"caption_candidate":"Auto Preset Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231989-p4-t0","doc_id":"K231989","page_num":4,"bbox":[63.67,147.96,570.6,681.96],"n_rows":11,"n_cols":2,"columns":["Date:","Nov 6, 2023"],"rows":[["Date:","Nov 6, 2023"],["Submitter:","GE Medical Systems Ultrasound and Primary care Diagnostics, LLC\n9900 Innovation Dr\nWauwatosa, WI 53226"],["Manufacturer:","GE Ultrasound Korea, Ltd.\n9, Sunhwan-ro 214 beon-gil, Jungwon-gu,\nSeongnam-si, Gyeonggi-do, 13204 Republic of Korea"],["Primary Contact Person:","Bryan Behn\nRegulatory Affairs Director\nGE HealthCare\nT:(262)247-5502"],["Alternate Contact Person:","Qingmeng Chen\nRegulatory Affairs Program Manager\nGE HealthCare\nT: +86-18180590723"],["Device Trade Name:","LOGIQ E10s, LOGIQ Fortis"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550, 90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-IYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX"],["Primary Predicate Device:","K211524 LOGIQ E10s, LOGIQ Fortis Diagnostic Ultrasound System"],["Reference Device(s):","K211488 LOGIQ E10 Diagnostic Ultrasound System\nK202035 Vscan Air\nK181685 Vivid E80/ Vivid E90/ Vivid E95 R3\nK200743 Vivid E80/ Vivid E90/ Vivid E95 R4\nK170445 LOGIQ S8\nK202233 Venue Go"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231989-p7-t0","doc_id":"K231989","page_num":7,"bbox":[71.4,369.96,568.92,705.48],"n_rows":4,"n_cols":2,"columns":["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• For Longitudinal model the accuracy of measurement is expected to\nbe higher than 80% and for the Transverse model it is expected to be\nhigher than 70%\n• The number of individual patients’ images were collected from: 30\nPatients.\n• The number of samples is 60 with 30 Longitudinal views and 30\nTransverse view"],"rows":[["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• For Longitudinal model the accuracy of measurement is expected to\nbe higher than 80% and for the Transverse model it is expected to be\nhigher than 70%\n• The number of individual patients’ images were collected from: 30\nPatients.\n• The number of samples is 60 with 30 Longitudinal views and 30\nTransverse view"],["Information about clinical subgroups and\nconfounders present in the dataset","• Gender: Male & Female\n• Age: range 26-81 yrs old\n• Ethnicity/Country; USA (58%) and Japan (42%)"],["Information about equipment and protocols\nused to collect images","The datasetused for final verification was collected prospectively on 30\ndemographically\ndiverse patients at 2 sites: Japan and the USA exclusively with the system\nunder consideration\nGE Logiq Fortis after the Auto Renal Measure Assistant function was\ndeveloped using C1-6-D\nprobe in Abdomen application;"],["Information about how the reference\nstandard was derived from the dataset (i.e.\nthe “truthing” process)","• The Validation set of 30 patient ( 60 images ) were loaded onto the\nLOGIQ validation system.\n• 2 Readers (certified sonographer/Clinician) to ground truth the\nmeasurements: Length on the Longitudinal views and the Height and\nWidth Measurements on the Transverse views.\n• Board Certified Nephrologist arbitrated the ground truth between the\nabove two readers to establish the reference standard for the dataset\n• Summary of Results:"]],"caption_candidate":"• Auto Renal Measure Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231989-p8-t0","doc_id":"K231989","page_num":8,"bbox":[71.4,298.2,563.88,557.04],"n_rows":3,"n_cols":2,"columns":["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• The overall model success rate of the Aorta, Kidney, Liver, GB, and\nPancreas view suggestion is expected to be 80% or higher.\n• The number of individual patients’ images were collected from: 50+\npatients\n• The number of samples, if different from above, and the relationship\nbetween the two: 1100+ images"],"rows":[["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• The overall model success rate of the Aorta, Kidney, Liver, GB, and\nPancreas view suggestion is expected to be 80% or higher.\n• The number of individual patients’ images were collected from: 50+\npatients\n• The number of samples, if different from above, and the relationship\nbetween the two: 1100+ images"],["Information about clinical subgroups and\nconfounders present in the dataset","• Gender: Male & Female\n• Age: Wide range, but specific age not collected\n• Ethnicity/Country; USA (77%) and Australia (23%)"],["Information about equipment and protocols\nused to collect images","Mix of data from across three different probe models and two different\nConsole variants. The data collection protocol was standardized across all\ndata collection sites."]],"caption_candidate":"• Auto Abdominal Color Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K231989-p9-t0","doc_id":"K231989","page_num":9,"bbox":[71.4,390.84,568.92,711.6],"n_rows":5,"n_cols":2,"columns":["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• The overall model success rate of the Abdomen, Air, Breast, Carotid,\nLeg, MSK, Scrotal, Thyroid and Carotid/Thyroid (Mixed) view\nsuggestion is expected to be 80% or higher.\n• The number of individual patients’ images were collected from: 110+\npatients\n• The number of samples, if different from above, and the relationship\nbetween the two: 2600+ images"],"rows":[["Summary test statistics or other test results\nincluding acceptance criteria or other\ninformation supporting the appropriateness\nof the characterized performance","• The overall model success rate of the Abdomen, Air, Breast, Carotid,\nLeg, MSK, Scrotal, Thyroid and Carotid/Thyroid (Mixed) view\nsuggestion is expected to be 80% or higher.\n• The number of individual patients’ images were collected from: 110+\npatients\n• The number of samples, if different from above, and the relationship\nbetween the two: 2600+ images"],["Information about clinical subgroups and\nconfounders present in the dataset","• Gender: Male & Female\n• Age: Wide range, but specific age not collected\n• Ethnicity/Country; USA (41.2%) , Austria (3.8%), Australia (1.1%),\nJapan (41.3%), Italy (0.7%) and Greece (12%)."],["Information about equipment and protocols\nused to collect images","Mix of data from across five different probe models and three different\nConsole variants. The data collection protocol was standardized across all\ndata collection sites."],["Information about how the reference\nstandard was derived from the dataset (i.e.\nthe “truthing” process)","• Before the process of data annotation, all information displayed on\nthe device is removed and performed on information extracted purely\nfrom Ultrasound B-mode images.\n• Readers (certified sonographer/Clinician) to ground truth the\n“anatomy” visible in static B-Mode image. (Before running AI)\n• Ran AI and created confusion matrix of ground truth vs AI\npredictions.\n• Calculated the accuracies of the algorithm against each class."],["Description of how independence of test\ndata from training data was ensured","The exams used for test/training validation purpose are separated from the\nones used during training process and there is no overlap between the two."]],"caption_candidate":"• Auto Preset Assistant : Al Summary of Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232000-p9-t0","doc_id":"K232000","page_num":9,"bbox":[72.03,532.29,525.57,645.0],"n_rows":5,"n_cols":7,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","Date of\nRecognition","","Standards",""],["","","","","","Development",""],["","","","","","Organization",""],["12-349","Radiology","Digital Imaging and Communications in Medicine\n(DICOM) Set; PS 3.1 - 3.20 2022d","12/19/2022","NEMA","",""],["13-79","Software","Medical Device Software –Software Life Cycle\nProcesses; 62304:2006 (1st Edition)/A1:2016","01/14/2019","AAMI, ANSI,\nIEC","",""]],"caption_candidate":"standards listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232000-p10-t0","doc_id":"K232000","page_num":10,"bbox":[72.0,72.24,525.6,201.72],"n_rows":3,"n_cols":5,"columns":["5-125","Software/\nInformatics","Medical devices – Application of risk management to\nmedical devices; 14971 Third Edition 2019-12","12/23/2019","ISO"],"rows":[["5-125","Software/\nInformatics","Medical devices – Application of risk management to\nmedical devices; 14971 Third Edition 2019-12","12/23/2019","ISO"],["5-129","General I\n(QS/RM)","Medical devices - Part 1: Application of usability\nengineering to medical devices\n62366-1:2015+AMD1:2020","07/06/2020","AAMI, ANSI,\nIEC"],["5-134","General\n(QS/RM)","Medical devices - Symbols to be used with medical\ndevice labels, labelling, and information to be\nsupplied - Part 1: General requirements\nISO 15223-1 Fourth edition 2021-07","12/20/2021","ISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232023-p5-t0","doc_id":"K232023","page_num":5,"bbox":[75.75,147.4,344.73,710.43],"n_rows":35,"n_cols":2,"columns":["510(k) sponsor","Momentum Health"],"rows":[["510(k) sponsor","Momentum Health"],["",""],["Address","2727Rue St-Patric"],["","Montreal, QC"],["","H3K0A8"],["","Canada"],["",""],["Official Contact","EvanDimentberg"],["",""],["","Email: evan@mom"],["","Tel: (514) 794-401"],["",""],["Regulatory Contact","Joyal Shukla"],["",""],["","Email: joyal@mom"],["","Tel: (647) 467-260"],["",""],["Dateprepared","Sep 18, 2023"],["",""],["2. Subject Device",""],["",""],["Trade/ProprietaryName","Momentum Spine"],["",""],["510(k) Number","K232023"],["",""],["Classification Name","Device, Sensing,O"],["",""],["Product Code","LDK"],["",""],["Regulatory Classification","Unclassified (pre-a"],["",""],["Classification Panel","PhysicalMedicine"],["",""],["Premarket Review","Neurological and"],["","Neuromodulation"]],"caption_candidate":"510(k) sponsor Momentum HealthInc.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232023-p5-t1","doc_id":"K232023","page_num":5,"bbox":[70.79,526.52,588.5,715.52],"n_rows":7,"n_cols":2,"columns":["Trade/ProprietaryName","Momentum Spine"],"rows":[["Trade/ProprietaryName","Momentum Spine"],["510(k) Number","K232023"],["Classification Name","Device, Sensing,OpticalContour"],["Product Code","LDK"],["Regulatory Classification","Unclassified (pre-amendment)"],["Classification Panel","PhysicalMedicine"],["Premarket Review","Neurological andPhysicalMedicine Devices(OHT5)\nNeuromodulation andPhysicalMedicine Devices(DHT5B)"]],"caption_candidate":"2. Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232023-p6-t0","doc_id":"K232023","page_num":6,"bbox":[72.1,165.45,588.5,370.33],"n_rows":7,"n_cols":2,"columns":["PredicateName","Quantec Spinal Measurement System"],"rows":[["PredicateName","Quantec Spinal Measurement System"],["510(k) clearance","K923792"],["Classification Name","Device, Sensing,OpticalContour"],["Product Code","LDK"],["Regulatory Classification","Unclassified (pre-amendment)"],["Classification Panel","PhysicalMedicine"],["Premarket Review","Neurological andPhysicalMedicine Devices(OHT5)\nNeuromodulation andPhysicalMedicine Devices(DHT5B)"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p5-t0","doc_id":"K232045","page_num":5,"bbox":[70.92,74.59,541.31,757.61],"n_rows":42,"n_cols":3,"columns":["K232045 510(k) Summar","y",""],"rows":[["K232045 510(k) Summar","y",""],["","",""],["1 Submitter","",""],["","",""],["Submitted Name:","MeVis Medical Solutions AG",""],["","Caroline-Herschel-Straße 1",""],["","28359 Bremen",""],["","Germany",""],["","",""],["Establishment Name:","MeVis Medical Solutions AG",""],["","",""],["Establishment","",""],["Registration Number:","3010601176",""],["","",""],["Date Prepared:","07/10/2023",""],["","",""],["Contact Person:","Rolf Rzodeczko",""],["","Manager Regulatory Affairs",""],["","",""],["Telephone:","+49 (0)421 22495-120",""],["","",""],["Fax:","+49 (0)421 22495-999",""],["","",""],["2 Device","",""],["","",""],["Device Trade Name:","MeVis Liver Suite",""],["","",""],["Device Common Name:","MeVis Liver Suite",""],["","",""],["Regulation:","21 CFR 892.1750",""],["","",""],["Classification Name:","Computed tomography x-ray system",""],["","",""],["Product Code:","JAK",""],["","",""],["Class:","Class II",""],["","",""],["Panel:","Radiology",""],["","",""],["","MeVis Liver Suite 510(k)","– K232045"],["","001-005, Rev 1 –","09/27/2023"],["","","Page 1"]],"caption_candidate":"K232045 510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232045-p6-t0","doc_id":"K232045","page_num":6,"bbox":[70.97,96.6,531.79,146.76],"n_rows":2,"n_cols":9,"columns":["","510(k) Number","","","Primary Predicate Device","","","Product Code",""],"rows":[["","510(k) Number","","","Primary Predicate Device","","","Product Code",""],["K133643","","","syngo.CT Liver Analysis","","","JAK","",""]],"caption_candidate":"3 Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p6-t1","doc_id":"K232045","page_num":6,"bbox":[70.97,197.28,531.79,247.56],"n_rows":2,"n_cols":9,"columns":["","510(k) Number","","","Secondary Predicate Device","","","Product Code",""],"rows":[["","510(k) Number","","","Secondary Predicate Device","","","Product Code",""],["K173420","","","Radiomics App v1.0","","","LLZ","",""]],"caption_candidate":"4 Secondary Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p6-t2","doc_id":"K232045","page_num":6,"bbox":[70.97,298.08,531.79,348.24],"n_rows":2,"n_cols":9,"columns":["","510(k) Number","","","Reference Device","","","Product Code",""],"rows":[["","510(k) Number","","","Reference Device","","","Product Code",""],["K193562","","","AI-Rad Companion Organs RT","","","QKB","",""]],"caption_candidate":"5 Reference Device1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p11-t0","doc_id":"K232045","page_num":11,"bbox":[71.21,123.6,552.79,690.6],"n_rows":2,"n_cols":6,"columns":["","Device","","","Indications for Use",""],"rows":[["","Device","","","Indications for Use",""],["Subject Device\nMeVis Liver Suite","","","MeVis Liver Suite is an image analysis software and intended to be used for visualization of\nhepatic imaging studies derived from CT and MR scanning devices (image source: single- and\nmultiframe DICOM).\nMeVis Liver Suite supports physicians in their workflow for evaluating the liver, related vascular\nanatomy, and the volume of liver and liver vascular territories for treatment planning,\npreoperative evaluation of surgery strategies, and post-procedure or therapy follow-up\nassessment of the hepatic system and related vascular structures.\nMeVis Liver Suite supports image analysis for multiphase contrast enhanced CT, dynamic\ncontrast enhanced MRI, and MRCP. MeVis Liver Suite only allows import of homogenous\nimage series (i.e., image and pixel size must be constant within each series) and with\northogonal image matrix (without a gantry tilt). Images with a resolution of > 5mm slice spacing\nare not suitable for image analysis with MeVis Liver Suite.\nMeVis Liver Suite can be used for manual segmentation, user-defined manual labeling, and 3D\nvisualization of:\n• abdominal organs (i.e., liver, stomach, duodenum, spleen, kidney, gallbladder, and\npancreas).\n• liver related vascular structures (i.e., bile ducts, hepatic artery, hepatic vein, portal\nvein, and inferior vena cava)\n• lesions inside and adjacent to the liver\nThe tools for manual segmentation and 3D visualization are applicable for CT and MR imaging\nstudies.\nIn addition to the manual segmentation tools, MeVis Liver Suite provides AI based semi-\nautomatic pre-segmentation tools for liver, hepatic artery, hepatic vein, and portal vein\nrestricted to CT scans of potential living liver donors with healthy livers and intended for:\n• Liver: contrast enhanced late-venous and venous phase\n• Hepatic vein: contrast enhanced late-venous and venous phase\n• Portal vein: contrast enhanced late-venous and venous phase\n• Hepatic artery: contrast enhanced arterial phase\nUsing MeVis Liver Suite, users can evaluate the segmented objects by exploring, calculating,\nand manually correcting:\n• the volume of the segmented abdominal organs (see above)\n• the volume of the segmented lesions inside and adjacent to the liver\n• the volume of the manually defined parts of the liver\nby defining separation planes (“separation proposals”)\no\nfrom vascular territories that are derived from the user-defined labeling of the\no\nliver related vascular structures\n• 3D visualizations of user-defined (vascular) tumor margins (coloring of area - based\non user-defined margin sizes/distances - between the edges of user-defined lesions in\nrelation to the edges of user-defined vascular structures of the liver)\n• based on user provided values, calculation of liver volume to body weight ratios (i.e.,\nestimated weight for remnant or graft, body surface area, graft to recipient body\nweight ratio, graft to SLV ratio, remnant to body weight ratio).\nUsing a manual spatial registration of the images, the segmented objects (created on different\nCT phases and MRI sequences) can be visualized together.\nThe information created with MeVis Liver Suite is intended to be used only in addition to the\noriginal images, clinical data, and the real anatomical and clinical situation. Physicians make all\nfinal patient management, assessment, and treatment decisions.","",""]],"caption_candidate":"Table 1 Comparison table for indications for use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p12-t0","doc_id":"K232045","page_num":12,"bbox":[71.16,71.16,552.84,710.88],"n_rows":3,"n_cols":2,"columns":["","MeVis Liver Suite is not intended for the anatomical systems integumentary, skeletal,\nmuscular, lymphatic, respiratory, nervous, reproductive, and cardiovascular (excluding\nhepatic).\nMeVis Liver Suite does not support the following application areas: real time viewing,\ndiagnostic review, image manipulation, optimization, virtual colonoscopy, and automatic lesion\ndetection.\nMeVis Liver Suite does not utilize high-resolution displays or display drivers and should not be\nused as a replacement for a PACS workstation.\nIntended Patient Population:\nThe intended patients for MeVis Liver Suite are oncologic patients or hepatic donor/transplant\npatients. CT or MR imaging with contrast agents need to be possible for analysis of vascular\nstructures inside the liver. The age group for the intended patient population is 18 or older.\nIn addition, the semi-automatic pre-segmentation tools are restricted to CT scans of potential\nliving liver donors with healthy livers.\nIntended Part of the Body:\nImages supported for the intended medical indication include the abdominal body part with the\nliver and related vascular structures (bile ducts, hepatic artery, hepatic vein, portal vein, inferior\nvena cava).\nIntended User Profile:\nThe intended users are radiologists and surgeons.\nIntended Use Environment:\nThe use environment is expected to be in an office environment under typical office conditions\nin hospitals or medical practices.\nOperation Principle:\nThe software acts as modality for display of CT or MR imaging data, and for visualization of the\nimage analysis results on a computer system. MeVis Liver Suite does not come into direct\ncontact or indirect contact with patients or other medical devices."],"rows":[["","MeVis Liver Suite is not intended for the anatomical systems integumentary, skeletal,\nmuscular, lymphatic, respiratory, nervous, reproductive, and cardiovascular (excluding\nhepatic).\nMeVis Liver Suite does not support the following application areas: real time viewing,\ndiagnostic review, image manipulation, optimization, virtual colonoscopy, and automatic lesion\ndetection.\nMeVis Liver Suite does not utilize high-resolution displays or display drivers and should not be\nused as a replacement for a PACS workstation.\nIntended Patient Population:\nThe intended patients for MeVis Liver Suite are oncologic patients or hepatic donor/transplant\npatients. CT or MR imaging with contrast agents need to be possible for analysis of vascular\nstructures inside the liver. The age group for the intended patient population is 18 or older.\nIn addition, the semi-automatic pre-segmentation tools are restricted to CT scans of potential\nliving liver donors with healthy livers.\nIntended Part of the Body:\nImages supported for the intended medical indication include the abdominal body part with the\nliver and related vascular structures (bile ducts, hepatic artery, hepatic vein, portal vein, inferior\nvena cava).\nIntended User Profile:\nThe intended users are radiologists and surgeons.\nIntended Use Environment:\nThe use environment is expected to be in an office environment under typical office conditions\nin hospitals or medical practices.\nOperation Principle:\nThe software acts as modality for display of CT or MR imaging data, and for visualization of the\nimage analysis results on a computer system. MeVis Liver Suite does not come into direct\ncontact or indirect contact with patients or other medical devices."],["Primary Predicate\ndevice:\nSiemens syngo.\nCT Liver Analysis\n(K133643)","syngo.CT Liver Analysis is an image analysis software for CT volume data sets. It analyses the\nliver and its intrahepatic vessel structures to identify the vascular territories of sub-vessel\nsystems in the liver. These regions can be evaluated by exploring the volume of the liver and\nits vascular territories.\nUsing syngo.CT Liver Analysis, you can evaluate the liver volume and examine the vessels of\nthe liver. The following evaluation tools are provided:\n• Computation and manual correction of liver volumes\n• Computation and manual correction of tumor volumes and extent\n• Computation and manual correction of liver vessel tree structure\n• Computation of territories based on vessel branches\n• Tumor position in relation to vessels (i.e. 3D visualization of liver, tumor and vessels)\n• Manual definition of separation plane proposals\n• Computation of volume of liver parts\n• Combination of information from different CT and MR phase volumes\nsyngo.CT Liver Analysis facilitates reporting by using of appropriate reporting tools, for\nexample, volume statistics and key image creation. You can use syngo.CT Liver Analysis to\ncreate a DICOM Structured Report."],["Secondary\nPredicate device:\nRadiomics App\nv1.0 (K173420)","Microsoft Radiomics Advanced Image Contouring v1.0 (Radiomics App) is a software-only\nmedical device intended for use by trained radiation oncologists, dosimetrists and physicists to\nderive optimal organ and tumor contours for input to radiation treatment planning. Supported\nimage modalities are Computed Tomography and Magnetic Resonance. Radiomics App\nassists in the following scenarios:\nLoad, save and display of medical images and contours for treatment evaluation and treatment\nplanning."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p14-t0","doc_id":"K232045","page_num":14,"bbox":[71.16,71.16,552.84,664.08],"n_rows":7,"n_cols":4,"columns":["Software","Standalone software","Image analysis software for\nsyngo.via","Software only medical device"],"rows":[["Software","Standalone software","Image analysis software for\nsyngo.via","Software only medical device"],["OS","Windows 10 (64-bit)","syngo.via platform","Microsoft Windows"],["Supported\nModalities","DICOM CT and MR","CT and MR","CT and MR"],["Image import\nand selection","DICOM images are manually\nselected and imported into\nMeVis Liver Suite.","The user has to decide which\nanatomical structures need to\nbe evaluated and on which CT\nseries the necessary\nstructures have to be\nsegmented.","The user manually loads\nimages into the software."],["Segmentation\nof abdominal\norgans","• Liver,\n• Stomach,\n• Duodenum,\n• Spleen,\n• Kidney,\n• Gallbladder, and\n• Pancreas\nManual segmentation, user-\ndefined manual labelling, and\n3D visualization.\nFor segmenting the liver, the\nuser can trigger a semi-\nautomatic pre-segmentation\nthat creates contours of the\nliver. The created contours\ncan be manually corrected with\ninteractive contouring tools.","• Liver\nAutomatic segmentation of\nliver, interactive manual\ncorrection of the resulting\ncontour.","• No restrictions\nAssisted and automatic\ncontouring modes. Creation,\ntransformation, and\nmodification of contours."],["Segmentation\nof liver related\nvascular\nstructures","Manual segmentation, user-\ndefined manual labelling, and\n3D visualization of liver related\nvascular structures (bile ducts,\nhepatic artery, hepatic vein,\nportal vein, inferior vena cava).\nSemi-automatic pre-\nsegmentation for liver\nrelated vascular structures is\navailable: the user can click in\na user-identified vessel and\nthe software detects the\nconnected vessels. The user\ncan manually correct, add, or\ndelete detected vessels\ninteractively","Segmentation of tubular\nstructures using a semi-\nautomated segmentation of\narterial, portal venous and\nvenous vascular bile ducts\ntree.\nThe segmentation is\nperformed by setting seed\npoint into vessels entering the\nliver and the system\nautomatically starts to\nsegment the whole\nintrahepatic vascular object.\nThe user can manually add or\ndelete vessels.","n/a"],["Segmentation\nof lesions","Lesions inside and adjacent to\nthe liver\nManual segmentation, user-\ndefined manual labelling, and\n3D visualization of lesions\ninside and adjacent to the liver.","Semi-automated segmentation\nof liver lesions.\nThe user triggers automatic\nsegmentation by drawing a\nstroke across a lesion at its\nlargest extent. The user can\ncorrect the given contour of a\nlesion.","Tumors\nCreation, transformation, and\nmodification of contours.\nLocalization and definition of\nsolid tumors."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p15-t0","doc_id":"K232045","page_num":15,"bbox":[71.16,71.16,552.84,705.0],"n_rows":4,"n_cols":4,"columns":["exploring,\ncalculating,\nand manually\ncorrecting the\nvolume of\nmanually\nsegmented\nobjects of\ninterest","","",""],"rows":[["exploring,\ncalculating,\nand manually\ncorrecting the\nvolume of\nmanually\nsegmented\nobjects of\ninterest","","",""],["3D\nvisualizations\nof user-defined\n(vascular)\ntumor margins\n(coloring of\narea - based on\nuser-defined\nmargin\nsizes/distances\n- between the\nedges of user-\ndefined lesions\nin relation to\nthe edges of\nuser-defined\nvascular\nstructures of\nthe liver)","The user can manually enter\ndifferent margin values, which\nare used to create color-coded\n3D visualizations around user\ndefined lesions.","Tumor position in relation to\nvessels (i.e. 3D visualization of\nliver, tumor and vessels). The\nmargin size can be chosen\ninteractively for calculating\nsafety margin around given\ntumors.","2d distance measurement"],["Based on user\nprovided\nvalues,\ncalculation of\nliver volume to\nbody weight\nratios","The user can enter the weight\nand height of a patient. Using\nthe user-defined manually\ncreated segmentations, MeVis\nLiver Suite can calculate liver\nvolume to body weight ratios\n(i.e., estimated weight for\nremnant or graft, body surface\narea, graft to recipient body\nweight ratio, graft to SLV ratio,\nremnant to body weight ratio).","n/a","n/a"],["Spatial\nRegistration","Using a manual spatial\nregistration of the images, the\nsegmentations created on\ndifferent images (i.e. different\nCT phases and MRI\nsequences) can be visualized\ntogether. The user can\nmanually align the images in\npairs on top of each other\nusing manual rigid registration","Manual rigid registration of CT\nphase volumes -\nIn case more than one CT (or\nMR) series has been selected,\nthe series have to be manually\naligned to each other to match\nup the liver anatomy, using the\nmanual alignment tool.","Manual rigid registration."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232045-p16-t0","doc_id":"K232045","page_num":16,"bbox":[139.44,463.92,472.68,522.48],"n_rows":5,"n_cols":9,"columns":["","","","DICE","","","","95% Hausdorff",""],"rows":[["","","","DICE","","","","95% Hausdorff",""],["","","","","","","","Distance (HD)",""],["","AI-Rad Companion Organs RT (K193562)","","","Median: 0.85","","","Median: 2.0 mm",""],["MeVis Liver Suite","","","","Median: 0.98","","Median: 1.5 mm","",""],["","","","","Mean: 0.98","","","",""]],"caption_candidate":"Liver Suite and reference device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p5-t0","doc_id":"K232083","page_num":5,"bbox":[35.52,527.04,576.48,717.6],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],"rows":[["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],["Intended Use / Indications\nfor Use","The qER-Quant device is intended for\nautomatic labeling, visualization and\nquantification of segmentable brain\nstructures from a set of Non-Contrast\nhead CT (NCCT) images. The software is\nintended to automate the current manual\nprocess of identifying, labeling and\nquantifying the volume of segmentable\nbrain structures identified on NCCT\nimages.","BriefCase-Quantification of Midline Shift\n(MLS) is a radiological image\nmanagement and processing system\nsoftware intended for automatic\nmeasurement of brain midline shift in\nnon-contrast head CT (NCCT) images,\nin adults or transitional adolescents\naged 18 years and older."]],"caption_candidate":"Table 1: Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p6-t0","doc_id":"K232083","page_num":6,"bbox":[35.52,72.24,576.48,715.68],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],"rows":[["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],["","qER-Quant provides volumes from NCCT\nimages acquired at a single time point and\nprovides a table with comparative\nanalysis for two or more images that were\nacquired on the same scanner with the\nsame image acquisition protocol for the\nsame individual at multiple time points.\nThe qER-Quant software is indicated for\nuse in the analysis of the following\nstructures: Intracranial Hyperdensities,\nLateral Ventricles and Midline Shift.","The device is intended to assist\nappropriately trained medical specialists\nby providing the user with an automated\ncurrent manual process of measuring\nmidline shift.\nThe device provides midline shift\nmeasurement from NCCT images\nacquired at a single time point, and can\nadditionally provide an output with\ncomparative analysis of two or more\nimages that were acquired in the same\nindividual at multiple time points.\nThe device does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device. The\nBriefCase-Quantification results are not\nintended to be used on a stand-alone\nbasis for clinical decision-making or\notherwise preclude clinical assessment\nof cases. Clinicians are responsible for\nviewing full images per the standard of\ncare."],["Anatomical region of\ninterest","Brain","Brain"],["Target structures analyzed\non NCCT scans","Midline shift, Intracranial hyperdensities,\nand lateral ventricles","Midline shift"],["Data acquisition protocol","Non-contrast head CT (NCCT) images","Non-contrast head CT (NCCT) images"],["Midline Shift Measurement","Yes","Yes"],["Interference with standard\nworkflow","No","No"],["Time point","Single or multiple time points","Single or multiple time points"],["Output","Multiple electronic reports with volumetric\ninformation of brain structures and midline\nshift and Annotated DICOM Images","A Summary report with measurement\ninformation of midline shift and\nannotated images"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p7-t0","doc_id":"K232083","page_num":7,"bbox":[35.52,72.24,576.48,420.36],"n_rows":4,"n_cols":3,"columns":["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],"rows":[["","Predicate Device\nqER-Quant (K211222)","BriefCase-Quantification of Midline\nShift (MLS)"],["","",""],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- The qER-Quant software\ninteracts with the user’s picture\narchiving and communication\nsystem (PACS) to receive scans\nand returns the results to the\nsame destination.\n- The core processing component\nis coupled with a pre-processing\nmodule to prepare input digital\nimaging and communications in\nmedicine (DICOMs) for\nprocessing by the CNNs and a\npost-processing module to\nconvert the output into visual and\ntabular output for users.","- BriefCase-Quantification is\nhosted on a cloud server and\nanalyzes applicable CT images\nthat are acquired on CT scanner\nthat are forwarded to BriefCase-\nQuantification\n- The results of the analysis are\nexported and presented to\nmedical specialists for review ,\nto assist in the measurement of\nMLS."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p8-t0","doc_id":"K232083","page_num":8,"bbox":[130.61,390.2,481.49,451.04],"n_rows":3,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age","","64.4","","","20.2","","","18","","","68","","","90","","","228","",""],["","(Years)","","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 2: Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p8-t1","doc_id":"K232083","page_num":8,"bbox":[233.66,492.8,379.65,558.76],"n_rows":3,"n_cols":8,"columns":["Gender","","","N*","","","%",""],"rows":[["Gender","","","N*","","","%",""],["Male","","","110","","","48.3%",""],["Female","","","111","","","48.8%",""]],"caption_candidate":"Table 3: Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p8-t2","doc_id":"K232083","page_num":8,"bbox":[72.06,628.88,539.98,714.34],"n_rows":7,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["","","","47","","","20.6%","",""],["","Siemens","","","","","","",""],["","","","","","","","",""],["","","","58","","","25.4%","",""],["","GE","","","","","","",""],["","","","","","","","",""]],"caption_candidate":"Table 4: Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232083-p9-t0","doc_id":"K232083","page_num":9,"bbox":[72.07,72.64,539.96,180.69],"n_rows":8,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["","","","65","","","28.5%","",""],["","Philips","","","","","","",""],["","","","","","","","",""],["","","","58","","","25.4%","",""],["","Toshiba","","","","","","",""],["","","","","","","","",""],["","Total","","","228","","","100%",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p5-t0","doc_id":"K232096","page_num":5,"bbox":[71.06,104.3,524.26,209.18],"n_rows":7,"n_cols":2,"columns":["Device trade name","Transpara Density"],"rows":[["Device trade name","Transpara Density"],["Device","System, Image Processing, Radiological"],["Classification regulation","21 CFR 892.2050"],["Panel","Radiology"],["Device class","II"],["Product code","QIH"],["Submission type","Traditional 510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p5-t1","doc_id":"K232096","page_num":5,"bbox":[71.06,290.69,524.26,410.57],"n_rows":8,"n_cols":2,"columns":["Device trade name","Volpara Imaging Software"],"rows":[["Device trade name","Volpara Imaging Software"],["Legal Manufacturer","Volpara Health Technologies Limited"],["Device","System, Image Processing, Radiological"],["Classification regulation","21 CFR 892.2050"],["Panel","Radiology"],["Device class","II"],["Product code","LLZ"],["Clearance number","K182310"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p6-t0","doc_id":"K232096","page_num":6,"bbox":[71.02,623.14,538.66,709.66],"n_rows":2,"n_cols":4,"columns":["","Transpara Density","Predicate Device Volpara\nImaging Software\nK182310","Comments"],"rows":[["","Transpara Density","Predicate Device Volpara\nImaging Software\nK182310","Comments"],["Intended Use","Transpara Density is a\nsoftware application\nintended for use with\ndata from compatible","VolparaDensity is a\nsoftware application\nintended for use with the\nraw data from digital","Similar from the user\nperspective. Main\noutputs for the user are\nvolumetric density and"]],"caption_candidate":"device. The substantial equivalence comparison table below provides details.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p7-t0","doc_id":"K232096","page_num":7,"bbox":[71.06,71.04,538.66,697.78],"n_rows":8,"n_cols":4,"columns":["","digital mammography\nand digital breast\ntomosynthesis systems.\nTranspara Density utilizes\ndeep learning artificial\nintelligence algorithms to\nautomatically determine\nvolumetric breast density\n(VBD), breast volume,\nand an ACR BI-RADS 5th\nEdition breast density\ncategory to aid health\ncare professionals in the\nassessment of breast\ntissue composition. It is\nnot a diagnostic aid.","breast x-ray systems,\nincluding tomosynthesis.\nVolparaDensity calculates\nand quantifies\na density map and from\nthat determines\nvolumetric breast density\nas a ratio of\nfibroglandular tissue and\ntotal breast volume\nestimates. Volpara\nprovides these numerical\nvalues along with a BI-\nRADS breast density 4th\nor 5th Edition category to\naid health care\nprofessionals in the\nassessment of breast\ntissue composition.\nVolparaDensity is not an\ninterpretive or diagnostic\naid and should be used\nonly as adjunctive\ninformation when the\nfinal assessment of breast\ndensity category is made\nby an MQSA-qualified\ninterpreting\nphysician.","the BI-RADS 5th Edition\ndensity category. These\noutputs are the same."],"rows":[["","digital mammography\nand digital breast\ntomosynthesis systems.\nTranspara Density utilizes\ndeep learning artificial\nintelligence algorithms to\nautomatically determine\nvolumetric breast density\n(VBD), breast volume,\nand an ACR BI-RADS 5th\nEdition breast density\ncategory to aid health\ncare professionals in the\nassessment of breast\ntissue composition. It is\nnot a diagnostic aid.","breast x-ray systems,\nincluding tomosynthesis.\nVolparaDensity calculates\nand quantifies\na density map and from\nthat determines\nvolumetric breast density\nas a ratio of\nfibroglandular tissue and\ntotal breast volume\nestimates. Volpara\nprovides these numerical\nvalues along with a BI-\nRADS breast density 4th\nor 5th Edition category to\naid health care\nprofessionals in the\nassessment of breast\ntissue composition.\nVolparaDensity is not an\ninterpretive or diagnostic\naid and should be used\nonly as adjunctive\ninformation when the\nfinal assessment of breast\ndensity category is made\nby an MQSA-qualified\ninterpreting\nphysician.","the BI-RADS 5th Edition\ndensity category. These\noutputs are the same."],["Intended Users","Health Care Professionals","Health Care Professionals","Same"],["Image Source","Digital mammograms\nfrom mammography or\ntomosynthesis systems\n(any paddle type)","Digital mammograms\nfrom mammography or\ntomosynthesis systems,\nincluding those obtained\nusing with curved\npaddles.","Same. The subject device\nis insensitive for paddle\nshapes because it uses\nimages processed by the\nmanufacturer which are\nnot affected by paddle\nshape."],["Input image type","FOR PRESENTATION\n(processed) images for\nmammography and\nSynthetic 2D images for\nDBT","FOR PROCESSING (raw)\nimages for\nmammography and the\ncentral raw projection\nimage for DBT","The core algorithm for\ndensity computation of\nthe subject device has a\ndifferent design which\ndoes not require raw\ndata."],["Anatomical area","Breast","Breast","Same"],["Assessment Scope","","Volumetric",""],["Image Storage and Report\nGeneration","","Yes\nOutput to the console.",""],["Numeric Output","Volume of Breast\nVolumetric Breast Density","Volume of Breast\nVolumetric Breast Density","Similar, the clinically\nrelevant outputs in\npractice are the same."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p8-t0","doc_id":"K232096","page_num":8,"bbox":[71.08,71.04,538.66,366.17],"n_rows":4,"n_cols":4,"columns":["","BIRADS 5th Edition Breast\nDensity Category","BIRADS 4th or 5th Edition\nBreast Density Category\nVolume of Fibroglandular\ntissue\nAverage thickness of\ndense tissue\nMaximum thickness of\ndense tissue (and\nlocation)\nMaximum volume of\ndense tissue above any\n1cm2 square region",""],"rows":[["","BIRADS 5th Edition Breast\nDensity Category","BIRADS 4th or 5th Edition\nBreast Density Category\nVolume of Fibroglandular\ntissue\nAverage thickness of\ndense tissue\nMaximum thickness of\ndense tissue (and\nlocation)\nMaximum volume of\ndense tissue above any\n1cm2 square region",""],["Image Output","None","Density map in DICOM\nSCI format, for\nvisualization as user\nspecifies.","Density maps are not\nrequired in clinical\npractice"],["Classification","21 CFR 892.2050","21 CFR 892.2050","Same"],["Software Level of\nConcern","Moderate","Moderate","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p8-t1","doc_id":"K232096","page_num":8,"bbox":[71.08,529.03,524.24,706.42],"n_rows":6,"n_cols":9,"columns":["","Standard ID","","","Standard Title","","","FDA Recognition #",""],"rows":[["","Standard ID","","","Standard Title","","","FDA Recognition #",""],["IEC 62366-1 Edition\n1.1 2020-06","","","Medical devices - Part 1: Application of usability\nengineering to medical devices","","","5-129","",""],["ISO 14155 Third\nedition 2020-07","","","Clinical investigation of medical devices for\nhuman subjects - Good clinical practice","","","2-282","",""],["ISO 14971 Third\nEdition 2019-12","","","Medical devices - Application of risk\nmanagement to medical devices","","","5-125","",""],["IEC 62304 Edition\n1.1 2015-06\nCONSOLIDATED\nVERSION","","","Medical Device Software - Software Life Cycle\nProcesses","","","13-79","",""],["IEC 82304-1: 2016","","","Health software - Part 1: General requirements\nfor product safety","","","13-97","",""]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232096-p9-t0","doc_id":"K232096","page_num":9,"bbox":[71.06,71.04,524.26,166.1],"n_rows":2,"n_cols":3,"columns":["ISO 15223-1 Fourth\nEdition 2021-07","Medical devices - Symbols to be used with\nmedical device labels labelling and information\nto be supplied - Part 1: General requirements","5-134"],"rows":[["ISO 15223-1 Fourth\nEdition 2021-07","Medical devices - Symbols to be used with\nmedical device labels labelling and information\nto be supplied - Part 1: General requirements","5-134"],["ISO 20417 First\nedition 2021-04\nCorrected version\n2021-12","Medical devices – Information to be supplied by\nthe manufacturer","5-135"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232145-p9-t0","doc_id":"K232145","page_num":9,"bbox":[47.28,384.36,564.84,682.2],"n_rows":2,"n_cols":6,"columns":[" Fetal\n Abdominal\n Pediatric\n Small Organ\n OB/GYN\n Cardiac\n Transesophage\nal\n Intracardiac\n Transrectal\n Transvaginal\n Peripheral vessel\n Musculo-skeletal\n(conventional)\n Musculo-skeletal\n(superficial)\n Neonatal cephalic\n Adult cephalic","√\n√\n√\n√\n√\n√\n√\n--\n√\n√\n√\n√\n√\n√\n√","√\n√\n√\n√\n√\n√\n√\n--\n√\n√\n√\n√\n√\n√\n√","--\n√\n√\n--\n√\n√\n√\n√\n--\n--\n√\n--\n--\n--\n√","√\n√\n√\n√\n√\n√\n--\n--\n√\n√\n√\n√\n√\n√\n√","√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√"],"rows":[[" Fetal\n Abdominal\n Pediatric\n Small Organ\n OB/GYN\n Cardiac\n Transesophage\nal\n Intracardiac\n Transrectal\n Transvaginal\n Peripheral vessel\n Musculo-skeletal\n(conventional)\n Musculo-skeletal\n(superficial)\n Neonatal cephalic\n Adult cephalic","√\n√\n√\n√\n√\n√\n√\n--\n√\n√\n√\n√\n√\n√\n√","√\n√\n√\n√\n√\n√\n√\n--\n√\n√\n√\n√\n√\n√\n√","--\n√\n√\n--\n√\n√\n√\n√\n--\n--\n√\n--\n--\n--\n√","√\n√\n√\n√\n√\n√\n--\n--\n√\n√\n√\n√\n√\n√\n√","√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√\n√"],["Frequencies\nSupported:","√\n(1.0MHZ~1\n8MHz)","√\n(1.0MHZ~18M\nHz)","√\n(1.0MHZ~18\nMHz)","√\n(1.0MHZ~18\nMHz)","√\n(1.7MHZ~10\nMHz)"]],"caption_candidate":"Indications for Use:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232145-p10-t0","doc_id":"K232145","page_num":10,"bbox":[67.44,91.15,553.56,746.35],"n_rows":64,"n_cols":7,"columns":["","","","","","ACUSON","ACUSON"],"rows":[["","","","","","ACUSON","ACUSON"],["","","","ACUSON","","Sequoia &","SC2000"],["","","","","ACUSON","",""],["","","ACUSON","","","",""],["","","Sequoia","Sequoia","Origin","Sequoia","K# 211726"],["","","","","","",""],["tur","e / Characteristic","","Select","","Select","Predicate"],["","","This","This","This","K# 223735","device"],["","","","","Submission","",""],["","","Submission","","","",""],["","","","Submission","","Predicate",""],["","","","","","device",""],["","M","√","√","√","√","√"],["","PWD (Pulsed","√","√","√","√","√"],["","Wave Doppler)","","","","",""],["","CWD (Continuous","√","√","√","√","√"],["","Wave Doppler)","","","","",""],["","PW DTI (Doppler","√","√","√","√","√"],["","Tissue Image)","","","","",""],["","Color Doppler","√","√","√","√","√"],["","","","","","",""],["","Power Doppler","√","√","√","√","√"],["","Combined","√","√","√","√","√"],["","(BMDC)","","","","",""],["tur","es:","","","","",""],["","","","","","",""],["","Harmonic imaging","√","√","√","√","√"],["","Panoramic","√","√","√","√","√"],["","imaging","","","","",""],["","Color Panoramic","√","√","√","√","√"],["","imaging","","","","",""],["","Auto TEQ","√","√","√","√","√"],["","Cardiac Imaging","√","√","√","√","√"],["","physiological","","","","",""],["","signal display","","","","",""],["","Auto OB (eSie","√","√","√","√","√"],["","OB)","(Auto OB)","(Auto OB)","(Auto OB)","(eSie OB)","(eSie OB)"],["","Compounding","√","√","√","√","√"],["","Contrast imaging","√","√","√","√","√"],["","Clarify","√","√","√","√","√"],["","Virtual Touch -","√","√","","√","√"],["","","","","","",""],["","","","","--","",""],["","Strain","","","","",""],["","","√","","","","√"],["","","","√","√","√",""],["","","","","","",""],["","Auto Calcs (eSie","(Auto","","","(","eie Calcs"],["","","","","","",""],["","Calcs)","","(Auto Calcs)","(Auto Calcs) (e","Sie Calcs)",""],["","","Calcs)","","","",""],["","","","","","",""],["","","√","√","√","√","--"],["","","","","","",""],["","Speed of Sound","","","","",""],["","","","","","",""],["","Fusion","√","√","--","√","--"],["","Virtual Touch –","√","√","--","√","√"],["","pSWE","","","","",""],["","Virtual Touch","√","√","--","√","--"],["","Auto pSWE","","","","",""],["","","","","","",""],["AC","USON Sequoia, S","equoia Select a","nd Origin Diagn","ostic Ultrasound","System",""],["Tr","aditional 510(k)","","","","Page 6","of 15"]],"caption_candidate":"ACUSON ACUSON","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232145-p11-t0","doc_id":"K232145","page_num":11,"bbox":[67.44,91.15,560.08,746.35],"n_rows":58,"n_cols":7,"columns":["","","","","","ACUSON","ACUSON"],"rows":[["","","","","","ACUSON","ACUSON"],["","","","ACUSON","","Sequoia &","SC2000"],["","","","","ACUSON","",""],["","","ACUSON","","","",""],["","","Sequoia","Sequoia","Origin","Sequoia","K# 211726"],["","","","","","",""],["tur","e / Characteristic","","Select","","Select","Predicate"],["","","This","This","This","K# 223735","device"],["","","","","Submission","",""],["","","Submission","","","",""],["","","","Submission","","Predicate",""],["","","","","","device",""],["","Virtual Touch –","√","√","--","√","√"],["","SWE","","","","",""],["","UltraArt","√","√","√","√","--"],["","Modality Compare","√","√","√","√","--"],["","HD Zoom (Write","√","√","√","√","--"],["","Zoom)","","","","",""],["","Workflow","√","√","√","√","√"],["","Protocols","","","","",""],["","InFocus","√","√","√","√","--"],["","Flash sequencing","√","√","√","√","√"],["","Gesture control","√","√","√","√","--"],["","TeamViewer","√","√","√","√","√"],["","Motion Stabilized","√","√","√","√","√"],["","Persistence","","","","",""],["","DICOM","√","√","√","√","√"],["","DICOM SR","√","√","√","√","√"],["","Slow Flow Color","√","√","√","√","√"],["","Doppler State","","","","",""],["","Dynamic","√","√","√","√","√"],["","MultiHertz","","","","",""],["","","","","","",""],["","3D/4D Volume","√","√","--","√","√"],["","Imaging Mode","","","","",""],["","","","","","",""],["","UDFF","√","√","","√","--"],["","(Ultrasonically-","","","","",""],["","","","","","",""],["","","","","--","",""],["","Derived Fat","","","","",""],["","Fraction)","","","","",""],["","","","","","",""],["","Auto IMT","√","√","√","√","√"],["","","","","","",""],["","","√","","√","","√"],["","","","","","",""],["","Auto Doppler","","√","","√",""],["","","","","","",""],["","(eSieDoppler)","(Auto","","(Auto","","(eSieDoppler)"],["","","(","Auto Doppler)","","(eSieDoppler)",""],["","","Doppler)","","Doppler)","",""],["","Virtual workstation","√","√","√","√","--"],["","Velocity Variance","√","√","√","√","√"],["","Mapping","","","","","(Color dopper map)"],["","","","","","",""],["AC","USON Sequoia, S","equoia Select a","nd Origin Diagn","ostic Ultrasou","nd System",""],["Tr","aditional 510(k)","","","","Page","7 of 15"]],"caption_candidate":"ACUSON ACUSON","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232145-p12-t0","doc_id":"K232145","page_num":12,"bbox":[47.28,87.48,564.84,570.84],"n_rows":8,"n_cols":6,"columns":["Feature / Characteristic","ACUSON\nSequoia\nThis\nSubmission","ACUSON\nSequoia\nSelect\nThis\nSubmission","ACUSON\nOrigin\nThis\nSubmission","ACUSON\nSequoia &\nSequoia\nSelect\nK# 223735\nPredicate\ndevice","ACUSON\nSC2000\nK# 211726\nPredicate\ndevice"],"rows":[["Feature / Characteristic","ACUSON\nSequoia\nThis\nSubmission","ACUSON\nSequoia\nSelect\nThis\nSubmission","ACUSON\nOrigin\nThis\nSubmission","ACUSON\nSequoia &\nSequoia\nSelect\nK# 223735\nPredicate\ndevice","ACUSON\nSC2000\nK# 211726\nPredicate\ndevice"],[" Cardiac Volume\nImaging Feature\n AI Assist\n AI Measure\n 2D HeartAI\n 4D HeartAI\n Stress Echo\n Wide FOV","√\n√\n√\n√\n--\n√\n√","√\n√\n√\n√\n--\n√\n√","√\n√\n√\n√\n√\n√\n√","--\n--\n--\n--\n--\n--\n--","√\n--\n√\n(eSie Measure)\n√\n(Velocity\nVariance\nMapping, eSie\nLH)\n√\n(eSie LH, eSie\nLVA, eSie RH +\nGLS)\n√\n--"],["Wireless","√","√","√","√","√"],["Monitor: 23.8” Dual\nLayer High Dynamic\nRange FPD","√","√","√","√","√"],["Touch Screen: 13.3’’\nadjustable Touch\nScreen","√","√","√","√","--"],["Output Display\nStandard (Track 3)","√","√","√","√","√"],["Patient Contact\nMaterials","Tested to\nISO 10993-1","Tested to ISO\n10993-1","Tested to ISO\n10993-1","Tested to ISO\n10993-1","Tested to\nISO 10993-1"],["UL 60601-1 Certified","√","√","√","√","√"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232156-p11-t0","doc_id":"K232156","page_num":11,"bbox":[72.0,330.84,567.0,706.8],"n_rows":3,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison\nFeature","Rapid ASPECTS (K200760)","Rapid ASPECTS v3"],["Indications for Use","Rapid ASPECTS is a computer-\naided diagnosis (CADx) software\ndevice used to assist the clinician in\nthe assessment and characterization\nof brain tissue abnormalities using\nCT image data. The Software\nautomatically registers images and\nsegments and analyzes ASPECTS\nRegions of lnterest (ROIs). Rapid\nASPECTS extracts image data for\nthe ROI(s) to provide analysis and\ncomputer analytics based on\nmorphological characteristics. The\nimaging features are then\nsynthesized by an artificial\nintelligence algorithm into a single\nASPECT (Alberta Stroke Program\nEarly CT) Score.\nRapid ASPECTS is indicated for\nevaluation of patients presenting for\ndiagnostic imaging workup with\nknown MCA or ICA occlusion, for\nevaluation of extent of disease.","Rapid ASPECTS is a computer-aided\ndiagnosis (CADx) software device used\nto assist the clinician in the assessment\nand characterization of brain tissue\nabnormalities using CT image data.\nThe Software automatically registers\nimages and segments and analyzes\nASPECTS Regions of lnterest (ROIs).\nRapid ASPECTS extracts image data\nfor the ROI(s) to provide analysis and\ncomputer analytics based on\nmorphological characteristics. The\nimaging features are then synthesized\nby an artificial intelligence algorithm\ninto a single ASPECT (Alberta Stroke\nProgram Early CT) Score.\nRapid ASPECTS is indicated for\nevaluation of adult patients presenting\nfor diagnostic imaging workup, for\nevaluation of extent of disease. Extent\nof disease refers to the number of\nASPECTS regions affected which is\nreflected in the total score. This device"]],"caption_candidate":"table, as well as the Risk Benefit Analysis in the next paragraph is comparative to the predicate:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232156-p13-t0","doc_id":"K232156","page_num":13,"bbox":[72.0,75.84,567.0,272.52],"n_rows":7,"n_cols":3,"columns":["Imaging","CT","CT"],"rows":[["Imaging","CT","CT"],["Technical\nImplementation","AI/Random Forest","AI/Random Forest"],["Image Overlay","ASPECTS Atlas ROIs, highlighted\nby algorithms","ASPECTS Atlas ROIs, highlighted by\nalgorithms"],["Primary User(s)","Neuroradiologist/Clinician","Neuroradiologist/Clinician"],["Alteration of\noriginal image\ndata base","No","No"],["Alters Standard\nof Care\nWorkflow","In parallel to","In parallel to"],["Analysis\nWindow","≤ 6 hours","≤ 24 hours"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232156-p13-t1","doc_id":"K232156","page_num":13,"bbox":[72.0,310.8,539.76,703.38],"n_rows":4,"n_cols":2,"columns":["Risk Benefit Summary",""],"rows":[["Risk Benefit Summary",""],["Summary of Benefits:","This device provides a systematic, automated analysis of\nNCCT scans of the head to provide a standardized, automated\nASPECT score for Stroke workup. The clinical reader study,\nwhich included 1 expert neuroradiologist and 5 non-expert\ntypical readers demonstrated a statistically significant\nimprovement in the accuracy of the 6 readers’ scores when\nscoring was performed in conjunction with the Rapid\nASPECTS output. In a subgroup analysis, the benefit of the\nsoftware was most substantial among the non-neuroradiologist\nexpert reader which typically evaluates CT scans in\ncommunity hospitals and primary stroke centers. These non-\nexpert readers also evaluate CT scans in comprehensive\ncenters, particularly in the acute setting, when expert\nneuroradiologists are not immediately available. The software\nallows the non-expert physician to perform at the expert-like\nlevel. Use of the system did not appear to have any significant\nimpact (either positive or negative) on the score of the expert\nneuroradiologist included in the test reader group. Overall,\nthis system should provide a more consistent and timely\nbenefit of standardized reads regardless of physician and\ncenter specialty."],["Summary of the Risks","There are minimal potential risks associated with the use of\nthe device."],["","Incorrect scoring which may result in false positive\nresults and results to incorrect patient management with\npossible adverse effects such as, unnecessary additional"]],"caption_candidate":"Risk Benefit Analysis:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232156-p14-t0","doc_id":"K232156","page_num":14,"bbox":[72.0,75.84,539.76,716.82],"n_rows":8,"n_cols":2,"columns":["Risk Benefit Summary",""],"rows":[["Risk Benefit Summary",""],["","medical imaging and/or unnecessary additional\ndiagnostic workup."],["","Incorrect scoring which may result in false negative\nresults may lead to complications, including incorrect\ndiagnosis and delay in disease management."],["","The device could be misused to analyze images from an\nunintended patient population or on images acquired\nwith incompatible imaging hardware or incompatible\nimage acquisition parameters, leading to inappropriate\ndiagnostic information being displayed to the user."],["","Device failure could lead to the absence of results, delay of\nresults or incorrect results, which could likewise lead to\ninaccurate patient assessment."],["","However, based on the performance data and the\napplication of mitigating measures (general controls and\nspecial controls established for this device type), use of\nthe device is unlikely to decrease diagnostic\nperformance of the user and possible misuse of the\ndevice does not present additional risks compared with\nmisuse of other types of radiological image processing\ndevices."],["Summary of other Factors","The study was enriched to cover the range of ASPECT scores\nand scanner manufacturers and the readers in practice may not\nexperience a significant improvement in determining\nASPECTS."],["Conclusions: Do the\nprobable benefits outweigh\nthe probable risks.","Yes. The probable benefits outweigh the probable risks, given\nthe combination of required general controls and the special\ncontrols established for this device. The Special Controls\nwill sufficiently assist in managing risks associated with\nincorrect brain tissue characterization determining\nASPECT scoring, application of the device results to the\nwrong patient population, analysis of incompatible images,\nand/or device failure by ensuring proper performance and\nuse of the device.\nBy providing a systematic, automated analysis of NCCT scans\nof the head to provide a standardized, automated ASPECT\nscore for Stroke workup. The Rapid ASPECTS analytics\ncalculates morphological characteristics of brain tissue using\nthe historical training data and providing results which the\nattending physician may evaluate and modify based on other\npresenting conditions of the patient. In addition to the Rapid"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232156-p15-t0","doc_id":"K232156","page_num":15,"bbox":[72.0,75.84,539.76,313.86],"n_rows":2,"n_cols":2,"columns":["Risk Benefit Summary",""],"rows":[["Risk Benefit Summary",""],["","ASPECTS clinical module, other clinical information is easily\naccessible within the Rapid System framework such as CTA\nand CTP to inform the clinical decision-making process.\nThe clinical reader study demonstrates a statistically\nsignificant improvement of ASPECTS reads among a diverse\nsample of 6 typical readers representing multiple specialties,\nyears of practice, and practice settings.\nOverall, this system should provide a more consistent and\ntimely benefit of standardized reads regardless of physician\nand center specialty. Therefore, given the available\ninformation concerning the benefits, risks, and supporting\ndata; the probable benefits outweigh the probable risks,\ngiven the combination of required general controls and\nspecial controls established for this device."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p7-t0","doc_id":"K232231","page_num":7,"bbox":[85.38,539.58,510.07,764.88],"n_rows":11,"n_cols":8,"columns":["Feature","","","Proposed device:","","","Predicate device:",""],"rows":[["Feature","","","Proposed device:","","","Predicate device:",""],["","","","QP-Brain® (K232231)","","","NeuroQuant® (K170981)",""],["","REGULATORY DATA","","","","","",""],["Class","","II","","","II","",""],["Regulation name","","Picture Archiving and\nCommunication System","","","Medical Image management\nand processing system","",""],["Regulation number","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Classification Panel","","Radiology","","","Radiology","",""],["Product Code","","QIH, LLZ","","","LLZ","",""],["Manufacturer:","","Quibim S.L.","","","CorTechs Labs, Inc.","",""],["","INTENDED USE","","","","","",""],["Medical device description","","QP-Brain® is a medical\nimaging processing\napplication intended for\nautomatic labeling and\nvolumetric quantification of","","","NeuroQuant® is intended\nfor automatic labeling,\nvisualization and volumetric\nquantification of\nsegmentable brain","",""]],"caption_candidate":"NeuroQuant® (CorTechs Labs, Inc.)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p8-t0","doc_id":"K232231","page_num":8,"bbox":[85.37,71.2,510.07,761.04],"n_rows":9,"n_cols":8,"columns":["Feature","","","Proposed device:","","","Predicate device:",""],"rows":[["Feature","","","Proposed device:","","","Predicate device:",""],["","","","QP-Brain® (K232231)","","","NeuroQuant® (K170981)",""],["","","segmentable brain\nstructures and white matter\nhyperintensities (WMH) from\na set of adults and\nadolescents 18 and older\nMR images.","","","structures and lesions from\na set of MR images.\nIt is intended to automate\nthe manual process of\nidentifying, labeling and\nquantifying the volume of\nsegmentable brain\nstructures identified on MR\nimages.","",""],["Medical device intended\nuse environment","","Software as a Medical\nDevice, DICOM compatible\nand operate on off-the-self\nhardware (multiple vendors).","","","Software as a Medical\nDevice, DICOM compatible\nand operate on off-the-self\nhardware (multiple vendors).","",""],["Medical device intended\nuser","","The application should be\nused by clinicians with\nproper training, as a support\ntool in assessment of\nstructural MRIs.\nPatient management\ndecisions should not be\nbased solely on the results\nof the device.","","","NeuroQuant® is used by\nmedical professionals, such\nas radiologists, neurologists\nand neuroradiologists, as\nwell as by clinical\nresearchers, as a support\ntool in assessment of\nstructural MRIs.","",""],["Medical device intended\npatient population","","Adult patients and\nadolescent patients aged 18\nthrough 21 with brain MRI\nstudy. Available up to 94\nyears.","","","Adult and pediatric patients\nwith brain MRI study.\nAvailable for ages 3 to 100\nyears.","",""],["","CHARACTERISTICS","","","","","",""],["Clinical output","","Provides volumetric\nmeasurements of brain\nstructures.\n- Includes segmented\ncolor overlays and\nmorphometric\nreports.\n- Automatically\ncompares results to\nreference percentile\ndata and to prior\nscans when\navailable.\nSupports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and\nCommunications Systems.","","","Provides volumetric\nmeasurements of brain\nstructures.\n- Includes segmented\ncolor overlays and\nmorphometric\nreports.\n- Automatically\ncompares results to\nreference percentile\ndata and to prior\nscans when\navailable.\nSupports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and\nCommunications Systems.","",""],["Data source","","MRI scanner: 3D T1 MRI\nscans (for brain structures)","","","MRI scanner: 3D T1 MRI\nscans (for brain volumetry)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p9-t0","doc_id":"K232231","page_num":9,"bbox":[85.37,71.2,510.07,440.83],"n_rows":5,"n_cols":7,"columns":["Feature","","Proposed device:","","","Predicate device:",""],"rows":[["Feature","","Proposed device:","","","Predicate device:",""],["","","QP-Brain® (K232231)","","","NeuroQuant® (K170981)",""],["","and T2 FLAIR MR (for White\nMatter Hyperintensities)\nacquired with specified\nprotocols.\nQP-Brain® supports DICOM\nformat as input.","","","and T2 FLAIR MR (for White\nMatter Hyperintensities)\nacquired with specified\nprotocols.\nNeuroQuant® supports\nDICOM format as input.","",""],["Processing architecture","Automated internal pipeline\nthat performs:\n- artifact correction\n- segmentation\n- atlas-based\nparcellation\n- WMH quantification\n- volume calculation\n- report generation","","","Automated internal pipeline\nthat performs:\n- artifact correction\n- segmentation\n- atlas-based\nparcellation\n- lesion quantification\n- volume calculation\n- report generation","",""],["Safety","Automated quality control\nfunction: scan protocol\nverification.\nResults must be reviewed\nby a clinician with proper\ntraining.","","","Automated quality control\nfunctions:\n- Tissue contrast\ncheck.\n- Scan protocol\nverification.\n- Atlas alignment\ncheck.\nResults must be reviewed\nby a trained physician.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p9-t1","doc_id":"K232231","page_num":9,"bbox":[121.42,674.74,510.07,746.44],"n_rows":5,"n_cols":9,"columns":["","Region","","","DICE Score","","","Relative Volume Difference",""],"rows":[["","Region","","","DICE Score","","","Relative Volume Difference",""],["","GM","","0.983 (0.981 – 0.986)","","","2.846 (2.523 – 3.008)","",""],["","WM","","0.990 (0.988 – 0992)","","","1.643 (0.923 – 1.684)","",""],["","CSF","","0.955 (0944 – 0.965)","","","7.495 (3.950 – 7.7.18)","",""],["","ICV","","0.994 (0.994 – 0.995)","","","0.496 (0.298 – 0.694)","",""]],"caption_candidate":"QP-Brain® Brain volumetry analysis module.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p10-t0","doc_id":"K232231","page_num":10,"bbox":[85.42,148.34,510.08,233.97],"n_rows":6,"n_cols":12,"columns":["","Size","","","DICE Score","","","Absolute volume error","","","F1 score",""],"rows":[["","Size","","","DICE Score","","","Absolute volume error","","","F1 score",""],["","Low WMH","","0.506","","","0.675 mL","","","0.692","",""],["","Medium WMH","","0.636","","","2.544 mL","","","","",""],["","High WMH","","0.774","","","3.097 mL","","","","",""],["","Very High","","0.885","","","7.833 mL","","","","",""],["","WMH","","","","","","","","","",""]],"caption_candidate":"module.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232231-p10-t1","doc_id":"K232231","page_num":10,"bbox":[85.42,337.13,510.08,464.42],"n_rows":6,"n_cols":12,"columns":["","Size","","","DICE Score","","","Absolute volume error","","","F1 score",""],"rows":[["","Size","","","DICE Score","","","Absolute volume error","","","F1 score",""],["Low WMH","Low WMH","","0.406\n(0.360 – 0.450)","","","0.455 mL\n(0.317 – 0.682)","","","0.701\n(0.666 – 0.739)","",""],["Medium WMH","","","0.622\n(0.559 – 0.699)","","","2.084 mL\n(1.190 – 3.704)","","","","",""],["High WMH","","","0.748\n(0.707 – 0.790)","","","2.871 mL\n(1.311 – 4.763)","","","","",""],["","Very High","","0.806\n(0.677 – 0.923)","","","5.668 mL\n(2.853 – 15.831)","","","","",""],["","WMH","","","","","","","","","",""]],"caption_candidate":"module (confidence intervals).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p4-t0","doc_id":"K232257","page_num":4,"bbox":[72.32,250.38,539.75,278.16],"n_rows":2,"n_cols":8,"columns":["","Regulation Number","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","Regulation Name","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","","","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p4-t1","doc_id":"K232257","page_num":4,"bbox":[72.32,509.4,539.75,620.68],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Bladder AI (AIBV01)"],"rows":[["","Device Trade Name:","","Bladder AI (AIBV01)"],["","510(k) Reference:","","K230497"],["","Manufacturer Name:","","Exo Inc."],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Product Code(s):","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p4-t2","doc_id":"K232257","page_num":4,"bbox":[72.32,688.52,539.75,716.2],"n_rows":2,"n_cols":4,"columns":["","Device Trade Name:","","LVivo Software Application (LVivo Bladder)"],"rows":[["","Device Trade Name:","","LVivo Software Application (LVivo Bladder)"],["","510(k) Reference:","","K200232"]],"caption_candidate":"Reference Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p5-t0","doc_id":"K232257","page_num":5,"bbox":[72.27,72.32,539.8,155.76],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name:","","DiA Imaging Analysis Ltd"],"rows":[["","Manufacturer Name:","","DiA Imaging Analysis Ltd"],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Product Code(s):","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p5-t1","doc_id":"K232257","page_num":5,"bbox":[72.27,662.96,539.8,704.11],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducers","","C3 HD3 and PA HD3"],"rows":[["","Clarius Ultrasound Transducers","","C3 HD3 and PA HD3"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"K213436). Clarius Bladder AI is not a stand-alone software device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p7-t0","doc_id":"K232257","page_num":7,"bbox":[72.31,97.79,681.58,535.88],"n_rows":12,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Bladder AI","","Bladder AI (AIBV01)","","LVivo Software","",""],["","","","","","","Application (LVivo","",""],["","","","","","","Bladder)","",""],["","510(k) Holder/\nManufacturer","Clarius Mobile Health\nCorp.","","Exo Inc.","DiA Imaging Analysis Ltd","","","Not applicable"],["","Submission Reference","Current Submission","","K230497","K200232","","","Not applicable"],["Product Code(s)","","QIH","","QIH","QIH","","","Same as predicate device\nand reference device"],["Device Classification Name","","Automated Radiological\nImage Processing Software","","Automated Radiological\nImage Processing Software","Automated Radiological\nImage Processing Software","","","Same as predicate device\nand reference device"],["Regulation Number","","21 CFR 892.2050","","21 CFR 892.2050","21 CFR 892.2050","","","Same as predicate device\nand reference device"],["Regulation Name","","Medical Image\nManagement and\nProcessing System","","Medical Image\nManagement and\nProcessing System","Medical Image\nManagement and\nProcessing System","","","Same as predicate device\nand reference device"],["Intended Use","","Non-invasive processing of\nultrasound images using\nautomatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence/machine-\nlearning algorithms.","","Non-invasive processing of\nultrasound images using\nautomatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence/machine\nlearning algorithms.","Non-invasive processing of\nultrasound images using\nautomatic image\nsegmentation and\nmeasurement of\nanatomical structures\nutilizing artificial\nintelligence/machine\nlearning algorithms.","","","Same as predicate device\nand reference device"],["Indications for Use","","Clarius Bladder AI is\nintended for semi-\nautomatic non-invasive\nmeasurements of bladder\nvolume on ultrasound data\nacquired by the Clarius\nUltrasound Scanner (i.e.,\ncurvilinear and phased\narray scanners). The user","","Bladder AI uses machine-\nlearning techniques to aid\nin the quantification of\nbladder volume from\nultrasound images. The\ndevice is intended to be\nused on images of patients\naged two years or\nolder.","LVivo platform is intended\nfor non-invasive processing\nof ultrasound images to\ndetect, measure, and\ncalculate relevant medical\nparameters of structures\nand function of patients\nwith suspected disease.","","","The Clarius Bladder AI\nindications for use are very\nsimilar to the predicate\ndevice’s indications for use\nas both devices are\nindicated for measurement\nof bladder volume from\nultrasound image data."]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p8-t0","doc_id":"K232257","page_num":8,"bbox":[72.31,72.35,681.57,520.66],"n_rows":8,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Bladder AI","","Bladder AI (AIBV01)","","LVivo Software","",""],["","","","","","","Application (LVivo","",""],["","","","","","","Bladder)","",""],["","","shall be a healthcare\nprofessional trained and\nqualified in\nultrasound. The user shall\nretain the ultimate\nresponsibility of\nascertaining the\nmeasurements based on\nstandard practices and\nclinical judgment.","","","","","",""],["","Radiological application/\nSupported modality","Ultrasound","","Ultrasound","Ultrasound","","","Same as predicate device\nand reference device"],["Compatible Scanner\nFrequency","","C3: 2 to 6 MHz\nPA: 1 to 5 MHz","","1.3 to 9 MHz","Not available","","","The subject device’s\ncompatible scanner\nfrequency falls within the\nrange of the predicate\ndevice’s compatible\nscanner frequency"],["Principle of Operation/\nTechnology","","Ultrasound image\nprocessing software\napplication implementing\nartificial intelligence\nincluding non-adaptive\nmachine learning\nalgorithms trained with\nclinical and/or artificial\ndata intended for non-\ninvasive segmentation and\nmeasurements of\nultrasound data.","","Ultrasound image\nprocessing software\napplication implementing\nartificial intelligence\nincluding non-adaptive\nmachine learning\nalgorithms trained with\nclinical and/or artificial\ndata intended for non-\ninvasive segmentation and\nmeasurements of\nultrasound data.","Ultrasound image\nprocessing software\napplication implementing\nartificial intelligence\nincluding non-adaptive\nmachine learning\nalgorithms trained with\nclinical and/or artificial\ndata intended for non-\ninvasive segmentation and\nmeasurements of\nultrasound data.","","","Same as predicate device\nand reference device"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p9-t0","doc_id":"K232257","page_num":9,"bbox":[72.32,72.35,681.59,536.86],"n_rows":16,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Bladder AI","","Bladder AI (AIBV01)","","LVivo Software","",""],["","","","","","","Application (LVivo","",""],["","","","","","","Bladder)","",""],["Segmentation","","Yes – Segmentation of\nanatomical structures\n(bladder)","","Yes – Segmentation of\nanatomical structures\n(bladder)","Yes – Segmentation of\nanatomical structures\n(bladder)","","","Same as predicate device\nand reference device"],["Measurement","","Yes – Measurement of\nanatomical structures\n(bladder)","","Yes – Measurement of\nanatomical structures\n(bladder)","Yes – Measurement of\nanatomical structures\n(bladder)","","","Same as predicate device\nand reference device"],["Frame","","Transverse and Sagittal","","Transverse and Sagittal","Transverse and Sagittal","","","Same as predicate device\nand reference device"],["Quantitative Analysis","","Distance, Bladder Volume","","Distance, Bladder Volume","Distance, Bladder Volume","","","Same as predicate device\nand reference device"],["AI/ML Algorithm","","Image segmentation for\nborder detection, and\nbladder view classification\nusing a Deep Neural\nNetwork.","","Image segmentation for\nborder detection.","Image segmentation for\nborder detection using\nmachine learning and\nactive contour.","","","Similar to predicate device\nand reference device"],["","Automation\n(Yes or No)","Yes","","Yes","Yes","","","Same as predicate device\nand reference device"],["Display Calipers","","Yes","","Yes","Yes","","","Same as predicate device\nand reference device"],["","Manual adjustment/\nManual editing by user\ncapability\n(Yes or No)","Yes","","Yes","Yes","","","Same as predicate device\nand reference device"],["Operating System","","iOS and Android","","Web browser (Google\nChrome)","Web browser (Google\nChrome) and Android","","","Similar to predicate device"],["Anatomical Site","","Bladder","","Bladder","Bladder","","","Same as predicate device\nand reference device"],["Environment of Use","","Healthcare setting (e.g.,\nhospital, clinic)","","Healthcare setting (e.g.,\nhospital, clinic)","Healthcare setting (e.g.,\nhospital, clinic)","","","Same as predicate device\nand reference device"],["Intended Users","","Licensed healthcare\nprofessionals","","Licensed healthcare\nprofessionals","Licensed healthcare\nprofessionals","","","Same as predicate device\nand reference device"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p10-t0","doc_id":"K232257","page_num":10,"bbox":[72.3,72.35,681.55,177.34],"n_rows":5,"n_cols":8,"columns":["Criteria","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","Clarius Bladder AI","","Bladder AI (AIBV01)","","LVivo Software","",""],["","","","","","Application (LVivo","",""],["","","","","","Bladder)","",""],["Patient Population","Adults","","Adults and pediatrics (2\nyears and older)","Adults","","","Similar to the predicate\ndevice and same as the\nreference device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p11-t0","doc_id":"K232257","page_num":11,"bbox":[72.26,181.44,539.74,306.36],"n_rows":8,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["12-349","","","NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set"],["5-129","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"FDA-recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232257-p12-t0","doc_id":"K232257","page_num":12,"bbox":[72.27,385.8,539.73,440.88],"n_rows":4,"n_cols":7,"columns":["Subject Gender","","Training Dataset Number of","","","Test Dataset Number of",""],"rows":[["Subject Gender","","Training Dataset Number of","","","Test Dataset Number of",""],["","","Subjects","","","Subjects",""],["Female","353","","","12","",""],["Male","999","","","43","",""]],"caption_candidate":"Gender distribution of the subjects included in the training and test datasets are shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p8-t0","doc_id":"K232305","page_num":8,"bbox":[72.29,102.66,539.76,697.07],"n_rows":5,"n_cols":6,"columns":["","Subject Device:\nAI-Rad Companion\nBrain MR VA50A","","Predicate Device:","","Reference Device:\nicobrain (K192130)"],"rows":[["","Subject Device:\nAI-Rad Companion\nBrain MR VA50A","","Predicate Device:","","Reference Device:\nicobrain (K192130)"],["","","","AI-Rad Companion","",""],["","","","Brain MR VA40","",""],["","","","(K213706)","",""],["Indications for\nUse","AI-Rad Companion\nBrain MR is a post-\nprocessing image\nanalysis software that\nassists clinicians in\nviewing, analyzing, and\nevaluating MR brain\nimages.\nAI-Rad Companion\nBrain MR provides the\nfollowing\nfunctionalities:\n• Automatic\nsegmentation and\nquantitative analysis\nof individual brain\nstructures and\nwhite matter\nhyperintensities\n• Quantitative\ncomparison of each\nbrain structure with\nnormative data from\na healthy\npopulation\n• Presentation of\nresults for reporting\nthat includes all\nnumerical values as\nwell as visualization\nof these results","AI-Rad Companion\nBrain MR is a post-\nprocessing image\nanalysis software that\nassists clinicians in\nviewing, analyzing, and\nevaluating MR brain\nimages.\nAI-Rad Companion\nBrain MR provides the\nfollowing\nfunctionalities:\n• Automatic\nsegmentation and\nquantitative analysis\nof individual brain\nstructures and white\nmatter\nhyperintensities\n• Quantitative\ncomparison of each\nbrain structure with\nnormative data from\na healthy population\n• Presentation of\nresults for reporting\nthat includes all\nnumerical values as\nwell as visualization\nof these results","","","icobrain is intended\nfor automatic\nlabeling,\nvisualization and\nvolumetric\nquantification of\nsegmentable brain\nstructures\nfrom a set of MR or\nNCCT images. This\nsoftware is intended\nto automate the\ncurrent manual\nprocess of\nidentifying,\nlabeling and\nquantifying the\nvolume of\nsegmentable brain\nstructures identified\non MR or NCCT\nimages. icobrain\nconsists of two\ndistinct image\nprocessing pipelines:\nicobrain cross and\nicobrain long.\nicobrain cross is\nintended to provide\nvolumes from MR or\nNCCT images\nacquired at a single\ntime point. icobrain\nlong is intended to\nprovide changes in\nvolumes between two\nMR images that were\nacquired on the same\nscanner,"]],"caption_candidate":"raise different questions of the safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p9-t0","doc_id":"K232305","page_num":9,"bbox":[72.24,72.72,539.81,700.92],"n_rows":4,"n_cols":4,"columns":["","","","with the same image\nacquisition protocol\nand with same\ncontrast at two\ndifferent timepoints.\nThe results of\nicobrain cross cannot\nbe compared with the\nresults of icobrain\nlong."],"rows":[["","","","with the same image\nacquisition protocol\nand with same\ncontrast at two\ndifferent timepoints.\nThe results of\nicobrain cross cannot\nbe compared with the\nresults of icobrain\nlong."],["Brain\nMorphometry","Pre-processing\nfunctionality for\nautomatic segmentation\nand volumetry of\nMPRAGE data.","Pre-processing\nfunctionality for\nautomatic segmentation\nand volumetry of\nMPRAGE data.","Image processing for\nautomatic\nsegmentation and\nvolumetry of\nMPRAGE data."],["Brain White\nMatter\nHyperintensities\nSegmentation","AI-Rad Companion\nBrain MR White Matter\nHyperintensities\n(WMH) includes\nsegmentation and\nquantification of White\nMatter Hyperintensities\non the basis of T1-\nweighted\nMPRAGE and T2-\nweighted FLAIR\ndatasets as input.","Pre-processing\nfunctionality for\nautomatic segmentation\nand volumetry of\nMPRAGE and FLAIR\ndata.","Image processing for\nautomatic\nsegmentation and\nvolumetry of FLAIR\ndata."],["Brain White\nMatter\nHyperintensities\nQuantification","The WMH report\ncontains visualization of\nWMH (3D overlay of\nWMH map) and\nnumeric results of count\nand volume of WMH as\nper four brain regions\nperiventricular,\njuxtacortial,\ninfratentorial and deep\nwhite matter.","The WMH report\ncontains visualization of\nWMH (3D overlay of\nWMH map) and\nnumeric results of count\nand volume of WMH as\nper four brain regions\nperiventricular,\njuxtacortial,\ninfratentorial and deep\nwhite matter.","Unnormalized\nvolume and volume\nchanges of FLAIR\nwhite matter\nhyperintensities as\nper 4 brain regions"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p10-t0","doc_id":"K232305","page_num":10,"bbox":[72.24,72.72,539.81,710.04],"n_rows":5,"n_cols":4,"columns":["Follow-up","The longitudinal\nassessment of Brain MR\nimages from two\ntimepoints provides the\nrate of change of\nvolumes of brain\nstructures and the count\nand volume of new or\nenlarged WMH.","The follow-up feature is\nnot available in the\nequivalent device (AI-\nRad Companion Brain\nMR VA40)","Assessment of\nNew/Enlarging lesion\ncount"],"rows":[["Follow-up","The longitudinal\nassessment of Brain MR\nimages from two\ntimepoints provides the\nrate of change of\nvolumes of brain\nstructures and the count\nand volume of new or\nenlarged WMH.","The follow-up feature is\nnot available in the\nequivalent device (AI-\nRad Companion Brain\nMR VA40)","Assessment of\nNew/Enlarging lesion\ncount"],["Brain White\nMatter\nHyperintensities\nMap","Calculation of white\nmatter hyperintensities\nmap fused with the\nprocessed FLAIR data\nUser customizable color\nlabels for the overlay\nmap.","Calculation of white\nmatter hyperintensities\nmap fused with the\nprocessed FLAIR data\nUser customizable color\nlabels for the overlay\nmap.","Calculation of white\nmatter\nhyperintensities map\noverlaid with the\nFLAIR data"],["Brain\nMorphometry:\nQuantification","Calculation of label\nmaps (display of brain\nsegmentation) and\npartially combined label\nmaps (fused with the\nprocessed MPRAGE\ndata).","Calculation of label\nmaps (display of brain\nsegmentation) and\npartially combined label\nmaps (fused with the\nprocessed MPRAGE\ndata).","Normalized and\nunnormalized volume\nand volume changes\nof different brain\nstructures."],["Brain\nMorphometry:\nDeviation Map\nand Label map","• Deviation results\ninclude deviation map,\nwhich presents different\nbrain regions, color-\ncoded to indicate the\ndegree of deviation from\nthe average age- and\ngender-matched\nnormative volume.\n• Label results include\nthe label map, which\nshows different brain\nregions using different\ncolors.","• Deviation results\ninclude deviation map,\nwhich presents different\nbrain regions, color-\ncoded to indicate the\ndegree of deviation from\nthe average age- and\ngender-matched\nnormative volume.\n• Label results include\nthe label map, which\nshows different brain\nregions using different\ncolors.","Not available"],["Distribution &\nArchiving","Creation of an image\nseries for morphometry\nand WMH reports.\nAutomatic transfer of\ngenerated maps and","Creation of an image\nseries for morphometry\nand WMH reports.\nAutomatic transfer of\ngenerated maps and","Automatic transfer of\ngenerated image\nseries and report to a\nPACS system."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p11-t0","doc_id":"K232305","page_num":11,"bbox":[72.24,72.72,539.81,709.56],"n_rows":4,"n_cols":4,"columns":["","reports to a PACS\nsystem.","reports to a PACS\nsystem.",""],"rows":[["","reports to a PACS\nsystem.","reports to a PACS\nsystem.",""],["Architecture","Cloud-based and on-\nedge deployment in the\ninstitution premise. For\nEdge deployment, the\ndata processing is\nperformed within the\ninstitution whereas\nlogging, institution\nmanagement, and audit\nlogging are performed in\nthe cloud.","Cloud-based and on-\nedge deployment in the\ninstitution premise. For\nEdge deployment, the\ndata processing is\nperformed within the\ninstitution whereas\nlogging, institution\nmanagement, and audit\nlogging are performed in\nthe cloud.","Cloud only solution\nwith no components\ndeployed on\ncustomer premise."],["Communication","PACS (DICOM\ncompatible)","PACS (DICOM\ncompatible)","PACS (DICOM\ncompatible)"],["User interface","Configuration UI\nUser can activate or\ndeactivate the\nprocessing of brain MR\ncases in AI-Rad\nCompanion Engine.\nIf you activate AI-Rad\nCompanion Brain MR,\nthen the brain MR cases\nuploaded to AI-Rad\nCompanion Engine are\nprocessed and is\ndisplayed in the Patient\nList. You can manually\nadjust the settings\navailable in the General\nSettings screen.\nIf you deactivate AI-Rad\nCompanion Brain MR,\nthen no brain MR cases\nare processed in AI-Rad\nCompanion Engine. The\nsettings available in the\nGeneral Settings screen\nare not displayed.\nTo activate or deactivate\nAI-Rad Companion\nBrain MR, see\nConfiguring AI-Rad","Configuration UI\nUser can activate or\ndeactivate the\nprocessing of brain MR\ncases in AI-Rad\nCompanion Engine.\nIf you activate AI-Rad\nCompanion Brain MR,\nthen the brain MR cases\nuploaded to AI-Rad\nCompanion Engine are\nprocessed and is\ndisplayed in the Patient\nList. You can manually\nadjust the settings\navailable in the General\nSettings screen.\nIf you deactivate AI-Rad\nCompanion Brain MR,\nthen no brain MR cases\nare processed in AI-Rad\nCompanion Engine. The\nsettings available in the\nGeneral Settings screen\nare not displayed.\nTo activate or deactivate\nAI-Rad Companion\nBrain MR, see\nConfiguring AI-Rad","Not available"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p12-t0","doc_id":"K232305","page_num":12,"bbox":[72.24,72.72,539.81,691.66],"n_rows":3,"n_cols":4,"columns":["","Companion in the AI-\nRad Companion Engine\nInstructions for Use.\nLongitudinal (Follow-\nup) configurations and\nSupport for output in\ndifferent orientations are\nadded.\nConformation UI\nOn the Results Preview,\nuser can confirm or\ndecline the results and\nsend them to the PACS.\nAll changes are\ntemporarily saved until\nthe case is sent to the\nPACS.","Companion in the AI-\nRad Companion Engine\nInstructions for Use.\nConformation UI\nOn the Results Preview,\nuser can confirm or\ndecline the results and\nsend them to the PACS.\nAll changes are\ntemporarily saved until\nthe case is sent to the\nPACS.",""],"rows":[["","Companion in the AI-\nRad Companion Engine\nInstructions for Use.\nLongitudinal (Follow-\nup) configurations and\nSupport for output in\ndifferent orientations are\nadded.\nConformation UI\nOn the Results Preview,\nuser can confirm or\ndecline the results and\nsend them to the PACS.\nAll changes are\ntemporarily saved until\nthe case is sent to the\nPACS.","Companion in the AI-\nRad Companion Engine\nInstructions for Use.\nConformation UI\nOn the Results Preview,\nuser can confirm or\ndecline the results and\nsend them to the PACS.\nAll changes are\ntemporarily saved until\nthe case is sent to the\nPACS.",""],["Software\nrequirement/Op\nerating system","AI-Rad Companion\nBrain MR was tested on\nMicrosoft Windows 10.\nAI-Rad Companion\nBrain MR is not\nvalidated on any other\noperating system, for\nexample, MAC.\nAI-Rad Companion\nBrain MR is not\nvalidated for use with\ntouch screen or mobile\ndevices.\nAI-Rad Companion\nNotifier requires a 64-bit\nWindows Operating\nSystem (Windows 10\nrecommended). It is\nrecommended to use\nGoogle Chrome as a\npreferred web browser\nfor use with AI-Rad\nCompanion Brain MR.","AI-Rad Companion\nBrain MR was tested on\nMicrosoft Windows 10.\nAI-Rad Companion\nBrain MR is not\nvalidated on any other\noperating system, for\nexample, MAC.\nAI-Rad Companion\nBrain MR is not\nvalidated for use with\ntouch screen or mobile\ndevices.\nAI-Rad Companion\nNotifier requires a 64-bit\nWindows Operating\nSystem (Windows 10\nrecommended). It is\nrecommended to use\nGoogle Chrome as a\npreferred web browser\nfor use with AI-Rad\nCompanion Brain MR.","Not available"],["System\ndeployment","Cloud based deployment\nEdge deployment\nPlatform","Cloud based deployment\nEdge deployment\nPlatform","Cloud Only Solution"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p13-t0","doc_id":"K232305","page_num":13,"bbox":[83.37,503.96,528.61,707.28],"n_rows":6,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-129","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","IEC 62366-1\nEdition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to\nmedical devices","ISO 14971 Third\nEdition 2019-12","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","IEC 62304\nEdition 1.1\n2015-06","","","AAMI\nANSI\nIEC","",""]],"caption_candidate":"Standards (Table 2).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p14-t0","doc_id":"K232305","page_num":14,"bbox":[83.34,72.72,528.64,249.32],"n_rows":4,"n_cols":5,"columns":["","","","CONSOLIDATED\nVERSION",""],"rows":[["","","","CONSOLIDATED\nVERSION",""],["12-349","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n2021e","NEMA"],["5-134","General","Medical devices – symbols to\nbe used with information to\nbe supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","ISO\nIEC"],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","IEC"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p15-t0","doc_id":"K232305","page_num":15,"bbox":[72.27,590.32,539.78,716.34],"n_rows":4,"n_cols":6,"columns":["","Validation Type","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Acceptance Criteria",""],["Volumetric Segmentation Accuracy","","","A PCC >= 0.77 is considered as a passed case\nfor volumetric segmentation accuracy","",""],["Voxel-wise Segmentation Accuracy","","","A mean Dice score >=0.47 is considered as a\npassed case for segmentation quality","",""],["WMH Change Region-wise Segmentation\nAccuracy","","","A median F1-score >=0.69 is considered a\npassed case","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p16-t0","doc_id":"K232305","page_num":16,"bbox":[72.26,99.78,560.8,260.42],"n_rows":5,"n_cols":4,"columns":["","Volumetric\nSegmentation","Voxel-wise Segmentation","WMH Lesion-wise\nSegmentation"],"rows":[["","Volumetric\nSegmentation","Voxel-wise Segmentation","WMH Lesion-wise\nSegmentation"],["","PCC","Dice","F1-score"],["AVG","0.94","0.50","0.69"],["STD","n.a.","0.22","0.13"],["95% CI","[0.83,0.98]","[0.42,0.57]","[0.633,0.733]"]],"caption_candidate":"Summary Performance data, Standard Deviations & CIs:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232305-p16-t1","doc_id":"K232305","page_num":16,"bbox":[157.17,320.6,454.88,691.84],"n_rows":11,"n_cols":2,"columns":["","Testing Cohort"],"rows":[["","Testing Cohort"],["# Subjects","75"],["# Studies","150 (2 scans per subject)"],["# of Females","56"],["# of Males","19"],["Age Range","25-88"],["Medical Indication","MS: 60\nAlzheimer’s: 15"],["Scan Protocol","T1w MPRAGE\nT2w FLAIR"],["Field Strength","3.0T"],["Manufacturer","Siemens"],["Data Origin","UPenn: (US): 15\nADNI (US): 15\nLausanne (EU): 22\nPrague (EU): 23"]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p8-t0","doc_id":"K232322","page_num":8,"bbox":[109.95,573.13,540.03,619.98],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Terra with\nsyngo MR E12U","K183222,\ncleared February 15, 2019","LNH\nLNI, MOS","Siemens AG / Siemens\nHealthcare GmbH"]],"caption_candidate":"are substantially equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p9-t0","doc_id":"K232322","page_num":9,"bbox":[109.64,105.79,540.18,199.62],"n_rows":5,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Vida with\nsoftware syngo MR XA50A","K213693,\ncleared February 25, 2022","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Prisma with\nsoftware syngo MR XA30A","K202014,\ncleared September 8, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["syngo.via VB40A","K191040,\ncleared May 16, 2019","LLZ","Siemens Healthcare\nGmbH"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p12-t0","doc_id":"K232322","page_num":12,"bbox":[109.52,105.6,540.12,706.02],"n_rows":5,"n_cols":4,"columns":["","","","have been defined for\nthe datasets."],"rows":[["","","","have been defined for\nthe datasets."],["","Please note: due to reasons of data privacy, we did\nnot record how many individuals the datasets\nbelong to. Gender, age, and ethnicity distribution\nwere also not recorded during data collection. Due\nto the network architecture, attributes like gender,\nage and ethnicity are not relevant to the training\ndata.","","Please note: Due to\nthe network\narchitecture, attributes\nlike gender, age and\nethnicity are not\nrelevant to the training\ndata."],["Confounder","The input and output variables of the network have been derived from the\nsame dataset so that no confounders exist for the training methodology.","",""],["Reference standard","The acquired datasets\nrepresent the ground truth\nfor the training and\nvalidation. Input data was\nretrospectively created\nfrom the ground truth by\ndata manipulation and\naugmentation. This\nprocess includes further\nunder-sampling of the\ndata by discarding k-\nspace lines, lowering of\nthe SNR level by addition\nof noise and mirroring of\nk-space data.","The acquired datasets\nrepresent the ground\ntruth for the training and\nvalidation. Input data\nwas retrospectively\ncreated from the ground\ntruth by data\nmanipulation. k-space\ndata has been cropped\nsuch that only the center\npart of the data was\nused as input. With this\nmethod corresponding\nlow-resolution data as\ninput and high-resolution\ndata as output / ground\ntruth were created for\ntraining and validation.","Applying three different\nmethods for bias field\ncorrection to the data,\nhomodyne filtering, N4\nand UNICORN."],["Test statistics and\ntest results","The impact of the network\nhas been characterized\nby several quality metrics\nsuch as peak signal-to-\nnoise ratio (PSNR) and\nstructural similarity index\n(SSIM). Additionally,\nimages were inspected\nvisually to ensure that\npotential artefacts are\ndetected that are not well\ncaptured by the metrics\nlisted above.\nAfter successful passing\nof the quality metrics\ntests, work-in-progress\npackages of the network\nwere delivered and\nevaluated in clinical\nsettings with cooperation\npartners. In a total of\nseven peer-reviewed\npublications 427 patients","The impact of the\nnetwork has been\ncharacterized by several\nquality metrics such as\npeak signal-to-noise\nratio (PSNR), structural\nsimilarity index (SSIM),\nand perceptual loss. In\naddition, the feature has\nbeen verified and\nvalidated by inhouse\ntests. These tests\ninclude visual rating and\nan evaluation of image\nsharpness by intensity\nprofile comparisons of\nreconstruction with and\nwithout Deep Resolve\nSharp. Both tests show\nincreased edge\nsharpness.","Two step test\nprocedure.\n1. During training, the\ntest data set was\nused to validate\nhow the network\nperformed on\nunseen data.\n2. During system tests,\nthe standard\ndeviation was\ndetermined, and the\nRMS error was\ncalculated (against\nthe ground truth).\nThe tests show that\nDeep RxE increases\nimage homogeneity in\na reproduceable way\non the receive profile.\nImages acquired with\nDeep RxE (DL bias"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p14-t0","doc_id":"K232322","page_num":14,"bbox":[109.69,275.54,534.56,577.56],"n_rows":7,"n_cols":2,"columns":["Feature / Function","Clinical Publication"],"rows":[["Feature / Function","Clinical Publication"],["dynamic pTx for TFL\n(for MAGNETOM\nTerra.X only)","Cloos MA, Boulant N, Luong M, Ferrand G, Giacomini E, Le Bihan D,\nAmadon A. kT -points: short three-dimensional tailored RF pulses for flip-\nangle homogenization over an extended volume. Magn Reson Med. 2012\nJan;67(1):72-80. doi: 10.1002/mrm.22978. Epub 2011 May 16. PMID:\n21590724."],["","Majewski K. Simultaneous optimization of radio frequency and gradient\nwaveforms with exact Hessians and slew rate constraints applied to kT-\npoints excitation. Journal of Magnetic Resonance. 2021 May 1;\n326:106941."],["","Herrler, J, Liebig, P, Gumbrecht, R, et al. Fast online-customized\n(FOCUS) parallel transmission pulses: A combination of universal pulses\nand individual optimization. Magn Reson Med. 2021; 85: 3140-3153.\nhttps://doi.org/10.1002/mrm.28643"],["","Tanner, Mark, Giulio Gambarota, Tobias Kober, Gunnar Krueger, David\nErritzoe, José P Marques, and Rexford Newbould. 2012. ‘Fluid and White\nMatter Suppression with the MP2RAGE Sequence.’ Journal of Magnetic\nResonance Imaging: JMRI 35 (5): 1063-70.\nhttps://doi.org/10.1002/jmri.23532."],["Weight limit\nreduction for 31P/1H\nTxRx Flex Loop Coil","Parasoglou, P, et al., 3D-Mapping of Phosphocreatine Concentration in\nthe Human Calf Muscle at 7T: Comparison to 3T, Magn Reson Med.\nAuthor manuscript; available in PMC 2014 December 01, 2013\nDecember, 70(6)"],["","Hooijmans M. T., et al., Spatially localized phosphorous metabolism of\nskeletal muscle in Duchenne muscular dystrophy patients: 24±month\nfollow-up,https://doi.org/10.1371/journal.pone.0182086,August 1, 2017"]],"caption_candidate":"following features and functions.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p15-t0","doc_id":"K232322","page_num":15,"bbox":[109.72,234.18,540.08,697.98],"n_rows":13,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognitio","n Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/ EMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012\nand\nA2:2010/(R)2012\n(Consolidated Text)","ANSI AAMI"],["19-8","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2, Ed.\n4.0:2014","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33, Ed.\n3.2:2015","IEC"],["5-125","General I\n(QS/ RM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third edition\n2019-12","ISO"],["5-114","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices\n[Including CORRIGENDUM 1\n(2016)]","62366-1 Edition 1.0\n2015-02","IEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"],["2-258","Biocompati\nbility","Biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process","10993-1 Fifth\nedition 2018-08","ISO"]],"caption_candidate":"standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232322-p16-t0","doc_id":"K232322","page_num":16,"bbox":[109.55,105.6,540.3,571.08],"n_rows":11,"n_cols":5,"columns":["12-342","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20\n2021e","NEMA"],"rows":[["12-342","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20\n2021e","NEMA"],["12-188","Radiology","Determination of Signal-to-\nNoise Ratio (SNR) in Diagnostic\nMagnetic Resonance Images","MS 1:2008 (R2020)","NEMA"],["12-196","Radiology","Determination of Two-\ndimensional Geometric\nDistortion in Diagnostic\nMagnetic Resonance Images","MS 2:2008 (R2020)","NEMA"],["12-187","Radiology","Determination of Image\nUniformity in Diagnostic\nMagnetic Resonance Images","MS 3:2008 (R2020)","NEMA"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"],["12-322","Radiology","Determination of Slice\nThickness in Diagnostic\nMagnetic Resonance Imaging","MS 5:2018","NEMA"],["12-195","Radiology","Determination of Signal-to-\nNoise Ratio and Image\nUniformity for Single-Channel,\nNon-Volume Coils in Diagnostic\nMagnetic Resonance Imaging\n(MRI)","MS 6:2008 (R2014)","NEMA"],["12-315","Radiology","Characterization of the Specific\nAbsorption Rate for Magnetic\nResonance Imaging Systems","MS 8:2016","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2020)","NEMA"],["12-298","Radiology","Determination of Local Specific\nAbsorption Rate (SAR) in\nDiagnostic Magnetic Resonance\nImaging Systems","MS 10 - 2010","NEMA"],["12-306","Radiology","Quantification and Mapping of\nGeometric Distortion for Special\nApplications","MS 12 - 2016","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232331-p4-t0","doc_id":"K232331","page_num":4,"bbox":[72.5,343.5,540.5,505.5],"n_rows":6,"n_cols":2,"columns":["Proprietary name:","InVision Precision LVEF (LVEF)"],"rows":[["Proprietary name:","InVision Precision LVEF (LVEF)"],["Common name:","InVision Precision"],["Classification name:","Medical image management and processing system"],["Regulation:","21 CFR 892.2050"],["Regulatory class:","II"],["Product code:","QIH Automated Radiological Image Processing Software"]],"caption_candidate":"Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232331-p5-t0","doc_id":"K232331","page_num":5,"bbox":[90.25,497.64,522.25,680.5],"n_rows":4,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nInVision Precision","Predicate Device:\nCaption Interpretation\nAutomated Ejection\nFraction Software\nK210747"],"rows":[["Feature/\nFunction","Subject Device:\nInVision Precision","Predicate Device:\nCaption Interpretation\nAutomated Ejection\nFraction Software\nK210747"],["General Principles of Operation","",""],["Machine Learning-\nBased Algorithm","Yes","Yes"],["Operates on DICOM\nclips","Yes","Yes"]],"caption_candidate":"predicate devices is as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232331-p6-t0","doc_id":"K232331","page_num":6,"bbox":[90.33,115.44,522.33,581.5],"n_rows":12,"n_cols":3,"columns":["Feature/\nFunction","Subject Device:\nInVision Precision","Predicate Device:\nCaption Interpretation\nAutomated Ejection\nFraction Software\nK210747"],"rows":[["Feature/\nFunction","Subject Device:\nInVision Precision","Predicate Device:\nCaption Interpretation\nAutomated Ejection\nFraction Software\nK210747"],["Automation level","Semi automated","Fully automated"],["Automated View\nSelection","Yes","Yes"],["Views for EF Calculation","Single view or Biplane","Single view or Biplane"],["Automated Ejection\nFraction Calculation","Yes","Yes"],["Ejection Fraction\nreported","Numerical estimate","Numerical estimate"],["User Interface","Uses the interface of\napproved PACS system","Includes own user\ninterface"],["Quantitative feedback to\nenable clinician to\nassess EF calculation","Adjustable annotation","Confidence Metric"],["EF result shown with\nvideo clip","Yes, with adjustable\nannotation","Yes"],["User confirmation/\nrejection of result","Yes","Yes"],["Technological Characteristics","",""],["Network Architecture","Spatiotemporal Pooling","Simple Pooling"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232363-p9-t0","doc_id":"K232363","page_num":9,"bbox":[72.62,153.3,540.63,659.41],"n_rows":7,"n_cols":3,"columns":["","Predicate Device","Subject Device"],"rows":[["","Predicate Device","Subject Device"],["","qER-Quant","Viz HDS"],["Application No.","K211222","K232363"],["Product Code","QIH","QIH"],["Regulation No.","21 C.F.R. § 892.2050","21 C.F.R. § 892.2050"],["Intended Use /\nIndications for Use","The qER-Quant device is intended for\nautomatic labeling, visualization and\nquantification of segmentable brain\nstructures from a set of Non-Contrast head\nCT (NCCT) images. The software is intended\nto automate the current manual process of\nidentifying, labeling and quantifying the\nvolume of segmentable brain structures\nidentified on NCCT images.\nqER-Quant provides volumes from NCCT\nimages acquired at a single time point and\nprovides a table with comparative analysis for\ntwo or more images that were acquired on the\nsame scanner with the same image\nacquisition protocol for the same individual at\nmultiple time points.\nThe qER-Quant software is indicated for use\nin the analysis of the following structures:\nAbnormal Intracranial Hyperdensities, Lateral\nVentricles and Midline Shift.","The Viz HDS device is intended for automatic\nlabeling, visualization, and quantification of\nsegmentable brain structures from a set of\nNon-Contrast CT (NCCT) head scans. The\nsoftware is intended to automate the current\nmanual process of identifying, labeling, and\nquantifying the volume of segmentable brain\nstructures identified on NCCT images. Viz\nHDS provides volumes from NCCT scans\nacquired at a single time point. The Viz HDS\nsoftware is indicated for use in the analysis of\nthe following structures: Intracranial\nHyperdensities, Lateral Ventricles and\nMidline Shift. The device output should be\nreviewed along with patient’s original images\nby a physician."],["Anatomical Region","Head","Head"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232363-p10-t0","doc_id":"K232363","page_num":10,"bbox":[72.62,127.3,540.63,467.31],"n_rows":7,"n_cols":3,"columns":["Input images","Non-contrast CT from a single or multiple\ntime points","Non-contrast CT from a single time point"],"rows":[["Input images","Non-contrast CT from a single or multiple\ntime points","Non-contrast CT from a single time point"],["Clinical Condition","Intracranial hyperdensities, lateral ventricles\nand midline shift","Intracranial hyperdensities, lateral ventricles\nand midline shift"],["Data Acquisition","Acquires medical image data from DICOM\ncompliant imaging devices and modalities.","Acquires medical image data from DICOM\ncompliant imaging devices and modalities."],["Supported Imaging\nModality","Non-contrast CT (NCCT)","Non-contrast CT (NCCT)"],["Alteration of\nOriginal Image","No","No"],["Artificial Intelligence\nAlgorithm","Yes","Yes"],["Output","Multiple electronic reports with volumetric\ninformation of brain structures and midline\nshift AND Annotated DICOM Images","Multiple electronic reports with volumetric\ninformation of brain structures and midline\nshift AND Annotated DICOM Images"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232381-p7-t0","doc_id":"K232381","page_num":7,"bbox":[258.48,297.24,527.52,703.56],"n_rows":3,"n_cols":2,"columns":["Summary test statics\nor other test results\nincluding acceptance\ncriteria or other\ninformation\nsupporting the\nappropriateness of the\ncharacterized\nperformance","∙ The overall model success\nrate of the Abdomen, Air,\nBreast, Carotid, Leg, MSK,\nScrotal, Thyroid and\nCarotid/Thyroid(Mixed)\nview suggestion is expected\nto be 80% or higher.\n∙ The number of individual\npatient’s images were\ncollected from: 50+ patients\n∙ The number of samples, if\ndifferent from above, and\nthe relationship between the\ntwo: 330+ images"],"rows":[["Summary test statics\nor other test results\nincluding acceptance\ncriteria or other\ninformation\nsupporting the\nappropriateness of the\ncharacterized\nperformance","∙ The overall model success\nrate of the Abdomen, Air,\nBreast, Carotid, Leg, MSK,\nScrotal, Thyroid and\nCarotid/Thyroid(Mixed)\nview suggestion is expected\nto be 80% or higher.\n∙ The number of individual\npatient’s images were\ncollected from: 50+ patients\n∙ The number of samples, if\ndifferent from above, and\nthe relationship between the\ntwo: 330+ images"],["Information about\nclinical subgroups and\nconfounders present\nin the dataset","∙ Gender: Male & Female\n∙ Age: Reproductive age,\nspecific age not collected.\n∙ Ethnicity/Country;\nUSA(57%) and\nAustralia(43%)"],["Information about\nequipment and\nprotocols used to\ncollect images","Mix of data from across 4\ndifferent probe models with\nLOGIQ Totus console. The\ndata collection protocol was\nstandardized across all data"]],"caption_candidate":"- Auto preset selection:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232381-p8-t0","doc_id":"K232381","page_num":8,"bbox":[258.48,102.6,527.52,339.96],"n_rows":3,"n_cols":2,"columns":["","collection sites."],"rows":[["","collection sites."],["Information about\nhow the reference\nstandard was derived\nfrom the dataset(i.e.\nthe “truthing”\nprocess)","For the testing process, the\nresults are generated by the\nAI software and the same\nare verified as Pass or Fail\nby a certified\nsonographer/clinician. The\nresults are then aggregated\nto yield an accuracy metric\nfor the AI algorithm."],["Description of how\nindependence of test\ndata from training\ndata was ensured","The exams used for\ntest/training validation\npurpose are separated from\nthe ones used during\ntraining process and there is\nno overlap between the two."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232381-p8-t1","doc_id":"K232381","page_num":8,"bbox":[258.48,380.04,527.52,710.28],"n_rows":3,"n_cols":2,"columns":["Summary test\nstatistics or other test\nresults including\nacceptance criteria or\nother information\nsupporting the\nappropriateness of the\ncharacterized\nperformance","∙ The overall model success\nrate of the Aorta, Kidney,\nLiver, GB and Pancreas\nview suggestion is expected\nto be 80% or higher.\n∙ The number of individual\npatients’ images were\ncollected from: 40 patients.\n∙ The number of samples, if\ndifferent from above, and\nthe relationship between the\ntwo: 280+ images"],"rows":[["Summary test\nstatistics or other test\nresults including\nacceptance criteria or\nother information\nsupporting the\nappropriateness of the\ncharacterized\nperformance","∙ The overall model success\nrate of the Aorta, Kidney,\nLiver, GB and Pancreas\nview suggestion is expected\nto be 80% or higher.\n∙ The number of individual\npatients’ images were\ncollected from: 40 patients.\n∙ The number of samples, if\ndifferent from above, and\nthe relationship between the\ntwo: 280+ images"],["Information about\nclinical subgroups and\nconfounders present\nin the dataset","∙ Gender: Male & Female\n∙ Age: Reproductive age,\nspecific age not collected.\n∙ Ethnicity/country:\nUSA(35%) and\nAustralia(65%)"],["Information about\nequipment and\nprotocols used to","Mix of data from across 4\ndifferent probe models with\nLOGIQ Totus console. The"]],"caption_candidate":"- Auto Abdominal Color Assistant:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p5-t0","doc_id":"K232384","page_num":5,"bbox":[67.5,151.5,485.5,337.5],"n_rows":3,"n_cols":2,"columns":["Applicant:","VideaHealth,Inc.\n179SouthStreet,Floor5\nBoston,MA, 02111\n+1617-340-9940\nflorian@videa.ai"],"rows":[["Applicant:","VideaHealth,Inc.\n179SouthStreet,Floor5\nBoston,MA, 02111\n+1617-340-9940\nflorian@videa.ai"],["Contact&Submission\nCorrespondent:","AdamForesman\nDirectorof Quality&RegulatoryAffairs\nVideaHealth,Inc.\n+1617-340-9940\nadam@videa.ai"],["DatePrepared:","July31,2023"]],"caption_candidate":"1. S UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p5-t1","doc_id":"K232384","page_num":5,"bbox":[67.5,397.5,489.5,575.5],"n_rows":6,"n_cols":2,"columns":["DeviceTradeName:","VideaDentalAssist"],"rows":[["DeviceTradeName:","VideaDentalAssist"],["DeviceCommonName:","DentalAI System"],["ClassificationName:","MedicalImageAnalyzer"],["ClassificationRegulation\nNumber:","21CFR 892.2070"],["DeviceClass:","2"],["ProductCode:","MYN"]],"caption_candidate":"2. D EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p5-t2","doc_id":"K232384","page_num":5,"bbox":[67.5,622.5,489.5,711.5],"n_rows":3,"n_cols":2,"columns":["DeviceTradeName:","VideaCariesAssist"],"rows":[["DeviceTradeName:","VideaCariesAssist"],["DeviceCommonName:","DentalAI System"],["ClassificationName:","MedicalImageAnalyzer"]],"caption_candidate":"REDICATE EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p6-t0","doc_id":"K232384","page_num":6,"bbox":[67.5,72.5,489.5,160.5],"n_rows":3,"n_cols":2,"columns":["ClassificationRegulation\nNumber:","21CFR 892.2070"],"rows":[["ClassificationRegulation\nNumber:","21CFR 892.2070"],["Device Class:","2"],["Product Code:","MYN"]],"caption_candidate":"510(k) Summary Page2of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p7-t0","doc_id":"K232384","page_num":7,"bbox":[72.25,170.47,540.25,689.5],"n_rows":13,"n_cols":3,"columns":["Videa Dental Assist Indication","Patient Agein Scope","Radiographic Viewin\nScope"],"rows":[["Videa Dental Assist Indication","Patient Agein Scope","Radiographic Viewin\nScope"],["Caries","3years andolder","Bitewing andPeriapical"],["Attrition","3years andolder","Bitewing andPeriapical"],["Broken/Chipped","3years andolder","Bitewing andPeriapical"],["Restorative Imperfection","3years andolder","Bitewing andPeriapical"],["Pulp Stone","12years of ageand\nolderwith permanent\ndentition","Bitewing andPeriapical"],["Dens Invaginatus","3years &older","Bitewing andPeriapical"],["PeriapicalRadiolucency","22years of ageand\nolderwith permanent\ndentition","Periapicalonly"],["Furcation","22years of ageand\nolderwith permanent\ndentition","Bitewing andPeriapical"],["Calculus","3years andolder","Bitewing andPeriapical"],["WidenedPeriodontal Ligament","3years andolder","Bitewing andPeriapical"],["HistoricalTreatments: All Indications","3years andolder","All onBitewing,\nPeriapicaland\nPanoramic"],["NormalAnatomy: AllIndications","12years andolder","1.Impacted Tooth\n2.Mental Foramen\n3.MaxillaryTuberosity\nOn Bitewing,Periapical\n& Panoramic"]],"caption_candidate":"Table 1: VDAIndications ScopebyPatient Ageand ImageModality Type","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p8-t0","doc_id":"K232384","page_num":8,"bbox":[72.33,72.13,540.33,246.5],"n_rows":2,"n_cols":3,"columns":["Videa Dental Assist Indication","Patient Agein Scope","Radiographic Viewin\nScope"],"rows":[["Videa Dental Assist Indication","Patient Agein Scope","Radiographic Viewin\nScope"],["","3years andolder","All otherindicationsare\nonBitewing, Periapical\n& Panoramic except:\n1.‘Mandibular Condyle’\nVDA normalanatomy\nindicationisonly on\nPanoramicimages."]],"caption_candidate":"510(k) Summary Page4of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p10-t0","doc_id":"K232384","page_num":10,"bbox":[66.25,205.68,545.3,721.66],"n_rows":10,"n_cols":3,"columns":["","Proposed Device","PredicateDevice"],"rows":[["","Proposed Device","PredicateDevice"],["510(k) Number","TBD","K213795"],["Applicant","VideaHealth,Inc.","VideaHealth,Inc."],["Device Name","Videa DentalAssist","Videa CariesAssist"],["Classification Regulation","892.2070","892.2070"],["Product Code","MYN","MYN"],["ImageModality","X-Ray","X-Ray"],["Radiograph ViewType","Bitewing Images,Periapical\nImages,and Panoramic\nImages.\nRadiograph viewtypescopeis\nVidea DentalAssistindication\nspecific.","Bitewing Images"],["Suspect Dental Findings\nIndications","Caries: Activeand Secondary\nCariesatall penetrationdepths\nAdditionalSuspect Dental\nFindings listed intheVidea\nDental Assist’sIndicationsFor\nUse statement.","Caries: Activeand Secondary\nCariesatall penetration\ndepths."],["Historical Treatmentand\nNormal Anatomy\nIndications","Included","NotIncluded"]],"caption_candidate":"Table 2: DeviceComparisonTable","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p11-t0","doc_id":"K232384","page_num":11,"bbox":[66.33,72.13,545.31,632.33],"n_rows":8,"n_cols":3,"columns":["","Proposed Device","PredicateDevice"],"rows":[["","Proposed Device","PredicateDevice"],["Tooth Surface","For thecariesindicationonly:\nProximal, Buccal/Lingual,\nOcclusal, Root,Cervical.\nNoneof theadditionalVDA\n‘Suspect DentalFinding’\nindications arespecifictoa\ntooth surface.","Caries: Proximal,\nBuccal/Lingual, Occlusal,\nRoot, Cervical."],["Clinical Output","Message indicating if and\nhow many findings were\ndetected for each enabled\nVidea Dental Assist’s\nindication for use.\nAll Videa Dental Assist’s\nindications use a set of\ntogglable bounding boxes\naround suspected areas of\ninterest.","Message indicating if and\nhow many carious lesions\nwere detected.\nSet of togglable bounding\nboxes around suspected\nlesions."],["Patient Population","Patients ≥3yearsof age.\nPatientagerangeisVidea\nDental Assistindication\nspecific.","Adults≥22years of age"],["Intended User","Dental professionals","US licensed dentists"],["Development Technology","Supervised Deep Learning","Supervised Deep Learning"],["ImageSource","X-Ray Sensor","X-Ray Sensor"],["ImageViewing","Image Viewer","Image Viewer"]],"caption_candidate":"510(k) Summary Page7of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p13-t0","doc_id":"K232384","page_num":13,"bbox":[77.38,87.75,241.06,277.5],"n_rows":7,"n_cols":2,"columns":["Subject Age\n(Years)","Percentage"],"rows":[["Subject Age\n(Years)","Percentage"],["3- 11","13%"],["12- 21","15%"],["22- 40","19%"],["41- 60","19%"],["61and older","16%"],["Unknown","18%"]],"caption_candidate":"Table 3: Demographicbreakdown by age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p13-t1","doc_id":"K232384","page_num":13,"bbox":[77.38,353.18,241.06,467.5],"n_rows":4,"n_cols":2,"columns":["Radiographic\nView","Percentage"],"rows":[["Radiographic\nView","Percentage"],["Bitewing","45%"],["Periapical","43%"],["Panoramic","12%"]],"caption_candidate":"Table 4: Imagebreakdownby radiographic view","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p15-t0","doc_id":"K232384","page_num":15,"bbox":[77.38,141.34,241.06,330.5],"n_rows":7,"n_cols":2,"columns":["Subject Age\n(Years)","Percentage"],"rows":[["Subject Age\n(Years)","Percentage"],["3- 11","28%"],["12- 21","20%"],["22- 40","14%"],["41- 60","14%"],["61and older","8%"],["Unknown","15%"]],"caption_candidate":"Table 5: Demographicbreakdown by age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p15-t1","doc_id":"K232384","page_num":15,"bbox":[77.38,406.45,241.06,534.5],"n_rows":4,"n_cols":2,"columns":["Radiographic\nView","Percentage"],"rows":[["Radiographic\nView","Percentage"],["Bitewing","56%"],["Periapical","44%"],["Panoramic","N/A. Notin\nscope."]],"caption_candidate":"Table 6: Imagebreakdownby radiographic view","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p15-t2","doc_id":"K232384","page_num":15,"bbox":[72.25,618.21,480.25,730.5],"n_rows":3,"n_cols":2,"columns":["Videa Dental Assist\nIndication","AveragePercentageImprovementWith VDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],"rows":[["Videa Dental Assist\nIndication","AveragePercentageImprovementWith VDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],["Attrition","0.171\n(28.5%improvement;p-value3.3e-16)"],["BrokenorChipped","0.105\n(15.3%improvement;p-value1.5e-11)"]],"caption_candidate":"Table 7: ClinicalPerformance MetricsofVDA byradiographic viewtype andline type.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p16-t0","doc_id":"K232384","page_num":16,"bbox":[72.33,72.17,480.33,501.5],"n_rows":11,"n_cols":2,"columns":["Videa Dental Assist\nIndication","AveragePercentageImprovementWith VDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],"rows":[["Videa Dental Assist\nIndication","AveragePercentageImprovementWith VDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],["Calculus","0.163\n(23.0%improvement;p-valuee-12)"],["Caries","0.024\n(4.3%improvement;p-value0.0085)"],["DensInvaginatus","0.236\n(36.8%improvement;p-value1.9e-9)"],["Furcation","0.199\n(29.7%improvement;p-value0.00057)"],["PeriapicalRadiolucency","0.092\n(11.5%improvement;\np-value0.0072)"],["PulpStone","0.211\n(35.4%improvement;\np-value2.2e-16)"],["RestorativeImperfection","0.164\n(27.9%improvementp-valueof<1e-16)"],["WidenedPeriodontalLigament","0.141\n(28.4%improvement;p-valueof9.6e-13)"],["HistoricalTreatments:\nAllIndications","Notapplicable.\nNotaclinicaldiagnosticaide."],["NormalAnatomy:\nAllIndications","Notapplicable.\nNotaclinicaldiagnosticaide."]],"caption_candidate":"510(k) Summary Page12of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p17-t0","doc_id":"K232384","page_num":17,"bbox":[72.25,431.42,478.5,702.5],"n_rows":7,"n_cols":2,"columns":["VDA Suspect\nDental Finding\nIndication","AveragePercentage ImprovementWithVDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],"rows":[["VDA Suspect\nDental Finding\nIndication","AveragePercentage ImprovementWithVDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],["Attrition","0.157\n(25.9% improvement)"],["Broken/Chipped\nTooth","0.075\n(10.4% improvement)"],["Calculus","0.207\n(31.1% improvement)"],["Caries","0.031\n(5.0% improvement)"],["Dens Invaginatus","0.216\n(34.2% improvement)"],["Furcation","0.187\n29.3% improvement)"]],"caption_candidate":"AFROC ScoresOn Periapical Radiographs","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p18-t0","doc_id":"K232384","page_num":18,"bbox":[72.3,72.17,478.5,282.5],"n_rows":5,"n_cols":2,"columns":["VDA Suspect\nDental Finding\nIndication","AveragePercentage ImprovementWithVDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],"rows":[["VDA Suspect\nDental Finding\nIndication","AveragePercentage ImprovementWithVDA\n(VDA Aidedvs. UnaidedMean AFROCFOM)"],["Periapical\nRadiolucency","N/A. Seetableaboveontheoverall PRL indicationlevel\nresults. PRL isonlyapplicableonperiapical radiographsso\nthere isnosubgroupanalysistoperform."],["Pulp Stones","0.244\n(39.8% improvement)"],["Restorative\nImperfections","0.167\n(28.2% improvement)"],["WidenedPDL","0.120\n(24.4% improvement)"]],"caption_candidate":"510(k) Summary Page14of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p18-t1","doc_id":"K232384","page_num":18,"bbox":[72.3,328.73,505.5,703.5],"n_rows":8,"n_cols":3,"columns":["VDA Suspect\nDental Finding\nIndication","AveragePercentage Improvement\nWith VDA\n(VDA Aidedvs. UnaidedMean\nAFROC FOM)","Notes"],"rows":[["VDA Suspect\nDental Finding\nIndication","AveragePercentage Improvement\nWith VDA\n(VDA Aidedvs. UnaidedMean\nAFROC FOM)","Notes"],["Attrition","0.199\n(35.3% improvement)","None"],["Broken/Chipped\nTooth","0.125\n(18.4% improvement)","None"],["Calculus","0.230\n(37.0% improvement)","Calculus isonlyintendedfor\npatients12years of ageand\nolder."],["Caries","0.028\n(5.2% improvement)","None"],["Dens\nInvaginatus","0.247\n(39.3% improvement)","None"],["Furcation","N/A","Furcation isonlyintendedfor\npatients22years of ageand\nolder."],["Periapical\nRadiolucency","N/A","Periapicalradiolucencyis only\nintendedfor patients22years\nof ageand older."]],"caption_candidate":"AFROC ScoresOn PediatricPatients(Ages 3to 21Yearsof AgeUnlessOtherwise Noted)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232384-p19-t0","doc_id":"K232384","page_num":19,"bbox":[72.33,72.13,505.5,265.5],"n_rows":4,"n_cols":3,"columns":["VDA Suspect\nDental Finding\nIndication","AveragePercentage Improvement\nWith VDA\n(VDA Aidedvs. UnaidedMean\nAFROC FOM)","Notes"],"rows":[["VDA Suspect\nDental Finding\nIndication","AveragePercentage Improvement\nWith VDA\n(VDA Aidedvs. UnaidedMean\nAFROC FOM)","Notes"],["Pulp Stones","0.196\n(33.2% improvement)","Pulp Stonesindicationisonly\nintendedfor patients12years\nof ageand older."],["Restorative\nImperfections","0.231\n(39.4% improvement)","None"],["WidenedPDL","0.131\n(26.1% improvement)","None"]],"caption_candidate":"510(k) Summary Page15of15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232410-p6-t0","doc_id":"K232410","page_num":6,"bbox":[19.42,18.0,593.79,737.16],"n_rows":9,"n_cols":2,"columns":["","Intended Use/Indications for Use 21 CFR 807.92(a)(5)"],"rows":[["","Intended Use/Indications for Use 21 CFR 807.92(a)(5)"],["SmartChest is a radiological computer assisted triage and notification software that analyzes frontal chest X-ray images (Postero-Anterior\n(PA) or Antero-Posterior (AP)) of transitional adolescents (18 - 21 yo but treated like adults) and adults (≥22 yo) for the presence of\nsuspected pleural effusion and/or pneumothorax. SmartChest uses an artificial intelligence algorithm to analyze the images for features\nsuggestive of critical findings and provides case-level output available to a PACS (or other DICOM storage platforms) for worklist\nprioritization.\nAs a passive notification for prioritization-only software tool within the standard of care workflow, SmartChest does not send a proactive\nalert directly to a trained medical specialist.\nSmartChest is not intended to direct attention to a specific portion of an image. Its results are not intended to be used on a stand-alone\nbasis for clinical decision-making.",""],["","Indications for Use Comparison 21 CFR 807.92(a)(5)"],["",""],["The predicate device Indications for Use is: Lunit INSIGHT CXR Triage is a radiological computer-assisted triage and notification\nsoftware that analyzes adult chest X-ray images for the presence of pre-specified suspected critical findings (pleural effusion and/or",""],["pneumothorax). Lunit INSIGHT CXR Triage uses an artificial intelligence algorithm to analyze images for features suggestive of critical\nfindings and provides case-level output available in the PACS/workstation for worklist prioritization or triage. As a passive notification\nfor prioritization-only software tool within standard of care workflow, Lunit INSIGHT CXR Triage does not send a proactive alert directly\nto the appropriately trained medical specialists. Lunit INSIGHT CXR Triage is not intended to direct attention to specific portions of an\nimage or to anomalies other than pleural effusion and/or pneumothorax. Its results are not intended to be used on a stand-alone basis\nfor clinical decision-making.\nThe Indications for Use are similar and the Intended Use is the same.",""],["","Technological Comparison 21 CFR 807.92(a)(6)"],["",""],["The subject device (SmartChest) and the predicate device (Lunit INSIGHT CXR) are both radiological computer assisted prioritization\nnotification software. The technologies use artificial intelligence algorithms to analyze radiological images.\nThe subject and predicate devices share similar technological characteristics as follows:\n- target population, intended user and use environment, anatomical site and modality, means of notification, standalone performance\nlevel, and triage effectiveness.\nAll outputs are the same between the subject device and the primary device.\nThe only difference is related to the predicate device being able to connect to radiological imaging equipment and in parallel also\nconnecting to PACS. The subject device only connects to the PACS (or other DICOM storage platforms) and flags cases there.\nThese differences do not change or modify the risks associated with the device type nor does it raise new questions of safety or\neffectiveness.\nBoth the subject device and predicate device are only intended to passively notify the end user that a study is suspicious of the indicated\nfindings and enable them to prioritize those studies, but the end user is still required to review all images and make the find clinical\ndiagnosis.\nTNheorenfo-reC, blyin exiacmainla taionn dof /thoer d eCviclien's iincteanld eTde usset asn dS teuchmnolmogiacarl yat tr&ibu Cteso, snubcsltaunstiailo eqnusiva len2ce1 i sC suFppRo rt8ed0. 7.92(b)",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p4-t0","doc_id":"K232412","page_num":4,"bbox":[72.16,431.47,515.51,531.19],"n_rows":5,"n_cols":2,"columns":["Trade Name","LungQ v3.0.0"],"rows":[["Trade Name","LungQ v3.0.0"],["Common Use/Usual Name","Computer Tomography X-ray system"],["Product Code","JAK"],["Classification","Class II, 21 CFR 892.1750"],["Device Panel","Radiology"]],"caption_candidate":"5.2 DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p4-t1","doc_id":"K232412","page_num":4,"bbox":[72.16,582.1,515.51,622.06],"n_rows":2,"n_cols":2,"columns":["Predicate Device","LungQ v1.1.0"],"rows":[["Predicate Device","LungQ v1.1.0"],["Predicate Classification","Class II, 21 CFR 892.1750"]],"caption_candidate":"5.3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p4-t2","doc_id":"K232412","page_num":4,"bbox":[72.16,658.54,515.51,698.38],"n_rows":2,"n_cols":2,"columns":["Predicate Device","VIDA|Vision"],"rows":[["Predicate Device","VIDA|Vision"],["Predicate Classification","Class II, 21 CFR 892.1750"]],"caption_candidate":"5.4 REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p5-t0","doc_id":"K232412","page_num":5,"bbox":[72.28,355.01,539.85,709.78],"n_rows":7,"n_cols":4,"columns":["Item","LungQ v3.0.0\nThirona\n(Subject Device)","LungQ v1.1.0\nThirona\n(Predicate Device)","VIDA|vision\nVIDA Diagnostics, Inc\n(Reference Device)"],"rows":[["Item","LungQ v3.0.0\nThirona\n(Subject Device)","LungQ v1.1.0\nThirona\n(Predicate Device)","VIDA|vision\nVIDA Diagnostics, Inc\n(Reference Device)"],["510(k) Number","NA","K173821","K200990"],["Product Code","JAK","Same","Same"],["Regulation Number","21 CFR 892.1750","Same","Same"],["Device\nClassification","Class II","Same","Same"],["Common Name","Software Accessory to a\nComputed tomography x-ray\nsystem","Same","Same"],["Intended Use","The Thirona LungQ software\nprovides reproducible CT\nvalues for pulmonary tissue\nwhich is essential for\nproviding quantitative\nsupport for diagnosis and\nfollow up examination. The\nLungQ software can be used\nto support physician in the\ndiagnosis and\ndocumentation of\npulmonary tissues images\n(e.g., abnormalities) from CT\nthoracic datasets. Three-D","Same","Equivalent"]],"caption_candidate":"Table 5-1: Substantial Equivalence Comparison between Subject, Predicate and Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p6-t0","doc_id":"K232412","page_num":6,"bbox":[72.26,85.58,539.86,718.3],"n_rows":11,"n_cols":4,"columns":["","segmentation and isolation\nof sub-compartments,\nvolumetric analysis, density\nevaluations, fissure\nevaluation, and reporting\ntools are provided.","",""],"rows":[["","segmentation and isolation\nof sub-compartments,\nvolumetric analysis, density\nevaluations, fissure\nevaluation, and reporting\ntools are provided.","",""],["Modality","CT","Same","Same"],["Data Loading","DICOM","Same","Same"],["Application","Command-line interface","Same","Equivalent"],["OS","Linux","Equivalent","Equivalent"],["Segmentation","Provides 3D segmentation","Same","Same"],["","Provides Segmentation of\nthe:\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lobe\n• Right Lower Lobe\n• Pulmonary\n(sub)segments","Equivalent","Equivalent"],["","Provides Airways\nSegmentation","Same","Same"],["","User cannot manually edit\nsegmentation","Same","Equivalent"],["Lung Volume\nAnalysis Support","Ability to measure volume\nfor:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary\n(sub)segments","Equivalent","Equivalent"],["Volume Density\nAnalysis","Ability to measure volume at\nmultiple density ranges for:\n• Both Lungs","Equivalent","Equivalent"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p7-t0","doc_id":"K232412","page_num":7,"bbox":[72.28,85.58,539.86,316.97],"n_rows":4,"n_cols":4,"columns":["","• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary\n(sub)segments","",""],"rows":[["","• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary\n(sub)segments","",""],["","Ability to measure the 15th\npercentile density analysis","Same","Same"],["Fissure Analysis","Ability to perform fissure\nevaluations","Same","Same"],["Analyzed Data\nOutput","Provides a report","Same","Same"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p7-t1","doc_id":"K232412","page_num":7,"bbox":[72.28,565.39,523.64,705.34],"n_rows":4,"n_cols":4,"columns":["Identification\nNumber","Edition /\nYear","Title","Rec\nNumbe\nr"],"rows":[["Identification\nNumber","Edition /\nYear","Title","Rec\nNumbe\nr"],["AAMI TIR57","2016","Principles for medical device security—Risk management","13-83"],["ANSI AAMI\nIEC TIR 80002-\n1","2009","Medical device software - Part 1: Guidance on the\napplication of ISO 14971 to medical device software","13-34"],["ANSI NEMA\nHN 1","2019","Manufacturer Disclosure Statement for Medical Device\nSecurity","13-123"]],"caption_candidate":"Table 5-2: Standards and Guidance documents","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p8-t0","doc_id":"K232412","page_num":8,"bbox":[72.27,85.58,524.88,377.33],"n_rows":9,"n_cols":4,"columns":["IEC 62304","1.1/2015","Medical device software - Software life-cycle processes","13-79"],"rows":[["IEC 62304","1.1/2015","Medical device software - Software life-cycle processes","13-79"],["IEC 62366-1","1.1/2020","Medical devices - Application of usability engineering to\nmedical devices","5-129"],["IEC 82304-1","1.0/2016","Health software - Part 1: General requirements for\nproduct safety","13-97"],["ISO 14971","3/2019","Medical devices - Application of risk management to\nmedical devices","5-125"],["ISO 15223-1","4/2021","Medical devices — Symbols to be used with information\nto be supplied by the manufacturer — Part 1: General\nrequirements","5-117"],["ISO 20417","1/2021","Medical devices — Information to be supplied by the\nmanufacturer","5-135"],["ISO/IEC 21778","1/2017","Information technology — The JSON data interchange\nsyntax","-"],["ISO/IEC 27001","2/2013","Information technology — Security techniques —\nInformation security management systems —\nRequirements","-"],["NEMA PS 3.1 -\n3.20","2022d","Digital Imaging and Communications in Medicine\n(DICOM) Set","12-349"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p8-t1","doc_id":"K232412","page_num":8,"bbox":[72.27,420.79,524.88,709.78],"n_rows":12,"n_cols":3,"columns":["Identification\nNumber","Year","Title"],"rows":[["Identification\nNumber","Year","Title"],["FDA-1997-D-0029","2002","General Principles of Software Validation"],["FDA-2011-D-0469","2016","Applying Human Factors and Usability Engineering to Medical\nDevices"],["FDA-2011-D-0652","2014","The 510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)]"],["FDA-2014-D-0456","2018","Appropriate Use of Voluntary Consensus Standards in Premarket\nSubmissions for Medical Devices"],["FDA-2015-D-4852","2017","Design Considerations and Pre-market Submission\nRecommendations for Interoperable Medical Devices"],["FDA-2016-D-1853","2021","Unique Device Identification System: Form and Content of the\nUnique Device Identifier (UDI)"],["FDA-2018-D-1329","2019","Recommended Content and Format of Non-Clinical Bench\nPerformance Testing Information in Premarket Submissions"],["FDA-2019-D-3598","2019","Off-The-Shelf Software Use in Medical Devices"],["FDA-2021-D-0775","2023","Content of Premarket Submissions for Device Software Functions"],["FDA 2021-D-1158","2022","Cybersecurity in Medical Devices: Quality System Considerations and\nContent of Premarket Submissions"],["FDA-2023-D-1030","2023","Cybersecurity in Medical Devices: Refuse to Accept Policy for Cyber\nDevices and Related Systems Under Section 524B of the FD&C Act"]],"caption_candidate":"Table 5-3: Guidance documents","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232412-p10-t0","doc_id":"K232412","page_num":10,"bbox":[72.29,225.5,490.27,344.81],"n_rows":3,"n_cols":2,"columns":["Imaging parameters Equivalence study",""],"rows":[["Imaging parameters Equivalence study",""],["Scanner manufacture","GE MEDICAL SYSTEMS; SIEMENS; Philips"],["Scanner types","LightSpeed16; LightSpeed VCT; Sensation 64;\nDefinition; Sensation 16; Definition AS+;\nSOMATOM Definition Flash; Brilliance 64;\nLightSpeed Pro 16; Discovery CT750 HD;\nSOMATOM Definition; LightSpeed Ultra\nSOMATOM Definition AS; LightSpeed16"]],"caption_candidate":"Table 5-4: Imaging parameters equivalence study.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232431-p4-t0","doc_id":"K232431","page_num":4,"bbox":[72.26,124.46,539.86,423.65],"n_rows":5,"n_cols":2,"columns":["Submitter / Primary Contact Person","Monsuru (Kenny) Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(240) 601-3848"],"rows":[["Submitter / Primary Contact Person","Monsuru (Kenny) Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(240) 601-3848"],["Secondary Contact Person","Clayton Ginn\nRegulatory Affairs\nclayton.ginn@siemens-healthineers.com\n+1 (865) 898-2692"],["Submitter Address","Siemens Medical Solutions, Inc. USA\nMolecular Imaging\n810 Innovation Drive\nKnoxville, TN 37932\nEstablishment Registration Number: 1034973"],["Legal Manufacturer","Siemens Healthcare GmbH\nSIEMENSSTRASSE 1 -OR-\nRittigfeld 1\nFORCHHEIM Bavaria, DE 91301\nEstablishment Registration Number: 3004977335"],["Importer/Distributor","Siemens Medical Solutions USA, Inc.\n40 Liberty Boulevard\nMalvern, PA 19355\nEstablishment Registration Number: 2240869"]],"caption_candidate":"1. Identification of the Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232431-p5-t0","doc_id":"K232431","page_num":5,"bbox":[72.29,578.39,547.03,685.18],"n_rows":5,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],["","syngo.CT Brain Hemorrhage\n(SOMARIS/8 VB80)","","","syngo.CT Brain Hemorrhage\n(SOMARIS/8 VB60)","","",""],["Notification-only, parallel\nworkflow tool","Yes","","","Yes","","","Same"],["Intended User","Radiologists and clinical administrators","","","Radiologists and clinical administrators","","","Same"],["Setting","Acute Care","","","Acute Care","","","Same"]],"caption_candidate":"in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232431-p6-t0","doc_id":"K232431","page_num":6,"bbox":[72.27,73.36,547.05,444.79],"n_rows":14,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nTable"],["","syngo.CT Brain Hemorrhage\n(SOMARIS/8 VB80)","","","syngo.CT Brain Hemorrhage\n(SOMARIS/8 VB60)","","",""],["Identify patients with a\nprespecified clinical\ncondition","Yes","","","Yes","","","Same"],["Clinical condition","Intracranial hemorrhage,\nSubarachnoid hemorrhage","","","Intracranial hemorrhage","","","Extended"],["Alert to finding","Yes; flagged for review","","","Yes; flagged for review","","","Same"],["Independent of standard\nof care workflow","Yes; No cases are removed from\nworklist","","","Yes; No cases are removed from\nworklist","","","Same"],["Modality","Non-contrast CT","","","Non-contrast CT","","","Same"],["Body Part","Head","","","Head","","","Same"],["Artificial Intelligence\nalgorithm","Yes","","","Yes","","","Same"],["Training Data","29 713 cases","","","28 814 cases","","","Improved"],["Limited to analysis of\nimaging data","Yes","","","Yes","","","Same"],["Scanner Manufacturer of\nInput Data","Siemens and other vendors","","","Siemens","","","Extended"],["Output","Suspected hemorrhage / Suspected\nhemorrhage including the\nsubarachnoid space / Processing\nfinished","","","Suspected hemorrhage / Processing\nfinished","","","Extended"],["Deployment Compatibility","SOMARIS-X platform,\nsyngo.via platform","","","SOMARIS-X platform","","","Extended"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232431-p7-t0","doc_id":"K232431","page_num":7,"bbox":[72.28,381.77,539.84,653.86],"n_rows":9,"n_cols":6,"columns":["Standard","Version","Content","","FDA Recognition",""],"rows":[["Standard","Version","Content","","FDA Recognition",""],["","","","","Number",""],["","","","","(if applicable)",""],["ANSI AAMI IEC 62304",":62304:2006/A1:20\n16","Medical device software - Software life cycle processes\n[Including Amendment 1 (2016)]","13-79","",""],["NEMA PS 3.1 - 3.20\n2022d",":2022","Digital Imaging and Communications in Medicine\n(DICOM) Set","12-349","",""],["ISO 14971",":2019","Application of Risk Management to Medical Devices","5-125","",""],["IEC 62366-1","Edition 1.1 2020-06\nCONSOLIDATED\nVERSION","Medical devices - Part 1: Application of usability\nengineering to medical devices","5-129","",""],["ISO 15223-1","Fourth edition\n2021-07","Medical devices - Symbols to be used with information\nto be supplied by the manufacturer - Part 1: General\nrequirements","5-134","",""],["ISO 20417:2021","First edition 2021-\n04 Corrected\nversion 2021-12","Medical devices - Information to be supplied by the\nmanufacturer","5-135","",""]],"caption_candidate":"covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232436-p8-t0","doc_id":"K232436","page_num":8,"bbox":[76.56,141.48,526.56,719.04],"n_rows":3,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison\nFeature","Rapid ICH (K221456)","Rapid SDH"],["Indications\nfor Use","Rapid ICH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of non-enhanced\nhead CT images. The device is\nintended to assist hospital networks\nand trained radiologists in\nworkflow triage by flagging and\ncommunication of suspected\npositive findings of pathologies in\nhead CT images, namely\nIntracranial Hemorrhage (ICH).\nRapid ICH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected ICH on a standalone\ndesktop application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of Rapid ICH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","Rapid SDH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the triage and notification of\nhemispheric SDH in non-enhanced\nhead images. The device is\nintended to assist trained\nradiologists in workflow triage by\nproviding notification of suspected\nfindings of hemispheric Subdural\nHemorrhage (SDH) in head CT\nimages.\nRapid SDH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\nsuspected hemispheric SDH on a\nserver or standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected hemispheric\nSDH findings. Notifications\ninclude compressed preview\nimages, that are meant for\ninformational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage and is not intended to be\nused as a diagnostic device.\nThe results of Rapid SDH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of"]],"caption_candidate":"features are compared in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232436-p9-t0","doc_id":"K232436","page_num":9,"bbox":[76.56,75.84,526.56,689.76],"n_rows":11,"n_cols":3,"columns":["","","medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.\nNote: See limitations in IFU\nstatement above"],"rows":[["","","medical images. Notified\nclinicians are responsible for\nviewing full images per the\nstandard of care.\nNote: See limitations in IFU\nstatement above"],["Stroke/Head","Hemorrhagic Stroke/Head","Hemispheric Sub-Dural\nHemorrhage/Head"],["Removal of\ncases from\nworklist\nqueue","No","No"],["Primary\nImaging\nModalities","NCCT","NCCT"],["Technical\nImplementati\non","ML/AI/Neural Network","ML/AI/Neural Network"],["Segmentation\nof ROI","No, the device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file.","No, the device does not highlight or\ndirect a user’s attention to a specific\nlocation in the image file."],["Preview\nImages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains."],["Primary\nUser(s)","Radiologist","Radiologist"],["Alteration of\noriginal\nimage data\nbase","No","No"],["Alters\nStandard of\nCare\nWorkflow","In parallel to","In parallel to"],["Notification/\nPrioritization","Yes – PACS, Workstation","Yes – PACS, Workstation, email,\nmobile"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232436-p12-t0","doc_id":"K232436","page_num":12,"bbox":[72.0,99.71,539.25,127.34],"n_rows":4,"n_cols":6,"columns":["Slice Thickness","","N","Estimate","Lower 95%","Upper 95%\nCI"],"rows":[["Slice Thickness","","N","Estimate","Lower 95%","Upper 95%\nCI"],["","Measure","","","",""],["","","","","CI",""],["","","","","",""]],"caption_candidate":"Performance Metrics by Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232436-p12-t1","doc_id":"K232436","page_num":12,"bbox":[72.0,494.1,539.25,523.23],"n_rows":2,"n_cols":11,"columns":["Source","TP","FP","","FN","TN","Total","Measure","Estimate","95%","95%"],"rows":[["Source","TP","FP","","FN","TN","Total","Measure","Estimate","95%","95%"],["","","","","","","","","","LCI","UCI"]],"caption_candidate":"provided in those sites where enough samples are included to provide statistical relevance:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232436-p13-t0","doc_id":"K232436","page_num":13,"bbox":[72.41,75.96,538.64,105.15],"n_rows":4,"n_cols":11,"columns":["Source","TP","FP","","FN","TN","Total","Measure","","95%","95%"],"rows":[["Source","TP","FP","","FN","TN","Total","Measure","","95%","95%"],["","","","","","","","","Estimate","",""],["","","","","","","","","","LCI","UCI"],["","","","","","","","","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232440-p5-t0","doc_id":"K232440","page_num":5,"bbox":[213.75,154.13,522.38,199.67],"n_rows":3,"n_cols":2,"columns":["","It"],"rows":[["","It"],["should not be used in-lieu of full patient evaluation or solely",""],["reliedupontomakeor confirmadiagnosis.",""]],"caption_candidate":"in the measurementsof mesialanddistalbonelevelsassociated","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232440-p5-t1","doc_id":"K232440","page_num":5,"bbox":[71.37,408.12,522.38,766.5],"n_rows":7,"n_cols":4,"columns":["Feature/\nFunction","Proposed Device\nAdravisionPerioDevice","PrimaryPredicate\nOverjetDentalAssist\nK210187","Identical?"],"rows":[["Feature/\nFunction","Proposed Device\nAdravisionPerioDevice","PrimaryPredicate\nOverjetDentalAssist\nK210187","Identical?"],["Datasource","Bitewingandperiapical\nradiographs","Bitewingandperiapical\nradiographs","Yes"],["Imageinput\nsources1","Imagesimportedfromthe\nradiographicdevice,or\nfromthepractice\nmanagementsystem,or\nmanuallyuploadedintothe\nsystem","Imagesimportedfromthe\nradiographicdevice,or from\nthepracticemanagement\nsystem","No"],["Image\nformat2","DICOM, JPEG, JPG, PNG,\nTIFF,TIF, JFIF or BMP\nfile","jpg,png,jfif,eop,etp,jif","No"],["Platform3","Web-Edge,Chrome,\nFirefox,Brave,Safari","Web- Edge,Chrome,Firefox","No"],["Enduser","Dentist,dentalhygienist","Dentist,dentalhygienist","Yes"],["Patient\npopulation","Theintendedpatient\npopulationof thedeviceis","Theintendedpatient\npopulationof thedeviceis","Yes"]],"caption_candidate":"Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232440-p6-t0","doc_id":"K232440","page_num":6,"bbox":[71.56,106.52,520.5,485.5],"n_rows":8,"n_cols":4,"columns":["Feature/\nFunction","ProposedDevice\nAdravision PerioDevice","PrimaryPredicate\nOverjet DentalAssist\nK210187","Identical?"],"rows":[["Feature/\nFunction","ProposedDevice\nAdravision PerioDevice","PrimaryPredicate\nOverjet DentalAssist\nK210187","Identical?"],["","patientsliving intheUnited\nStates,who are22yearsold\nor older,that donothave\nany remainingprimary\nteeth.","patientsliving intheUnited\nStates,who are22yearsold\nor older,and thatdonot have\nany remainingprimary teeth.",""],["Operating\nsystem","Any","Any","Yes"],["User\nInterface","Mouse, keyboard,trackpad","Mouse, keyboard,trackpad","Yes"],["Patient\nDatabase\nCompatibility","SQL","SQL","Yes"],["Image\nViewing","Full, thumbnail","Full, thumbnail","Yes"],["Features\ndetected","Bone level","Bone level","Yes"],["Model output","Line segments","Line segments","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232440-p8-t0","doc_id":"K232440","page_num":8,"bbox":[72.5,122.5,522.5,197.5],"n_rows":3,"n_cols":3,"columns":["Metric","Bitewing","Periapical"],"rows":[["Metric","Bitewing","Periapical"],["Precision","91.0%","84.8%"],["Recall","94.0%","89.3%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232440-p8-t1","doc_id":"K232440","page_num":8,"bbox":[72.5,277.5,522.5,377.5],"n_rows":4,"n_cols":3,"columns":["Metric","Bitewing","Periapical"],"rows":[["Metric","Bitewing","Periapical"],["Sensitivity","90.7%","92.5%"],["Specificity","94.3%","86.8%"],["Mean AbsoluteError","0.434mm","0.504mm"]],"caption_candidate":"length measurementslabeled bythree(3) ground trutherswithinthose radiographs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p4-t0","doc_id":"K232479","page_num":4,"bbox":[84.72,546.55,514.6,594.5],"n_rows":2,"n_cols":5,"columns":["Regulation\nNumber","Device","Device\nClass","Product\nCode","Classification\nPanel"],"rows":[["Regulation\nNumber","Device","Device\nClass","Product\nCode","Classification\nPanel"],["892.5050","Medicalcharged-particle\nradiationtherapysystem","ClassII","MUJ","Radiology"]],"caption_candidate":"PrimaryProductCode:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p6-t0","doc_id":"K232479","page_num":6,"bbox":[72.06,176.36,692.33,521.77],"n_rows":7,"n_cols":7,"columns":["","GeneralInformation","","","","",""],"rows":[["","GeneralInformation","","","","",""],["Property","ProposedDevice\nART-Planv2.1.0","PrimaryPredicate\nEthos Treatment\nManagement,2.1;\nEthos Treatment\nPlanning,1.1","Referencedevice\nART-Plan\nv1.10.1","Reference\ndevice\nECLIPSE\nWITHAAA","Reference\ndevice\nEclipse Treatment\nPlanningSystem","Comment"],["Common\nName","System, Planning,\nRadiation Therapy\nTreatment","accelerator, linear,\nmedical","Radiological image\nprocessing software\nforradiationtherapy","System, Planning,\nRadiation Therapy\nTreatment","System, Planning,\nRadiation Therapy\nTreatment","Theproposeddevicesharesthesame\ncommon name ”System, Planning,\nRadiationTherapyTreatment”withthe\nprimary predicate, especially Ethos\nTreatment Planning, 1.1 (that has\n“MUJ” asaproductcodeinits510(k)\nsummary) and with some of the\nreferencedevices."],["Device\nManufactur\ner","TheraPanaceaSAS","Varian Medical\nSystems,Inc","TheraPanaceaSAS","Varian Medical\nSystems (now\nVarian Medical\nSystems,Inc)","Varian Medical\nSystems,Inc","N/A"],["510k","N/A","K212294","K230023","K041403","K102011","N/A"],["Device\nClassificatio\nn","II","II","II","II","II","The proposed device, primary\npredicate and reference devices\nhaveidenticaldeviceclassification."],["Primary\nProduct\nCode","MUJ","IYE,MUJ","QKB","MUJ","MUJ","The primary product code isMUJfor\n“System,Planning,RadiationTherapy\nTreatment” asitisasoftwareusedin\ntheplanningofradiotherapytreatment\nlike the primary predicate, especially\nEthos Treatment Planning, 1.1 (that\nhas “MUJ” as a product code in its\n510(k)summary) andsomereference\ndevices use it as their primary or\nsecondarycode"]],"caption_candidate":"GeneralComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p7-t0","doc_id":"K232479","page_num":7,"bbox":[72.1,95.65,692.5,494.27],"n_rows":4,"n_cols":7,"columns":["Secondary\nProduct\nCode","QKB,LLZ","-","LLZ,MUJ","-","LHN","Assecondaryproductcode:\n- QKB (Radiological image\nprocessing software for radiation\ntherapy)hasbeenincludedasthe\nsoftwareusesAIalgorithmsandis\nintendedforradiationtherapy.Itis\nalso the primary code of the\nreference device ART-Plan\nv1.10.1ofwhichART-Plan2.1.0is\nanupdate;\n- LLZ (System, Image Processing,\nRadiological) has been included\nas the software is used inimage\nprocessing and it is also the\nsubsequent codeofthereference\ndeviceART-Planv1.10.1ofwhich\nART-Plan2.1.0isanupdate."],"rows":[["Secondary\nProduct\nCode","QKB,LLZ","-","LLZ,MUJ","-","LHN","Assecondaryproductcode:\n- QKB (Radiological image\nprocessing software for radiation\ntherapy)hasbeenincludedasthe\nsoftwareusesAIalgorithmsandis\nintendedforradiationtherapy.Itis\nalso the primary code of the\nreference device ART-Plan\nv1.10.1ofwhichART-Plan2.1.0is\nanupdate;\n- LLZ (System, Image Processing,\nRadiological) has been included\nas the software is used inimage\nprocessing and it is also the\nsubsequent codeofthereference\ndeviceART-Planv1.10.1ofwhich\nART-Plan2.1.0isanupdate."],["Target\nPopulation","ART-Plan’s\nindicated target\npopulationiscancer\npatients for whom\nradiotherapy\ntreatment has been\nprescribed. In this\npopulation, any\npatient for whom\nrelevant modality\nimaging data is\navailable.","The patient target\ngroups are the\npatients for whom\nradiation therapyis\nindicated.","ART-Plan’s indicated\ntarget population is\ncancer patients for\nwhom radiotherapy\ntreatment has been\nprescribed. In this\npopulation,anypatient\nfor whom relevant\nmodality imaging data\nisavailable.","Notstated","Any patients with\nmalignantorbenign\ndiseases","The proposeddeviceandtheprimary\npredicate have identical target\npopulations."],["Environmen\nt","Hospital","Hospital","Hospital","Hospital","Hospital","The proposed device, primary\npredicate and reference devices\nhaveidenticaltargetenvironments."],["Intended\nUse/\nIndication\nforUse","IntendedUse\nART-Plan is a\nsoftwareintendedto\nbe used by trained\nclinicians who are\nfamiliar with\nradiation therapy,\nsuch as medical\nphysicists, medical\ndosimetrists and","IntendedUse\nEthos Treatment\nManagement is\nused to manage\nand monitor\nradiation therapy\ntreatment plans\nand sessions; it is\nintendedtobeused","IntendedUse\nART-Plan is a\nsoftware for\nmulti-modal\nvisualization,\ncontouring and\nprocessing of 3D\nimages of cancer\npatients for whom","IntendedUse\nTheVarianEclipse\ndevice is a\ntreatmentplanning\nsystem used for\ndiagnostic image\nanalysis,\ncontouring and\nsegmentation,\ngeometrical","Intendeduse\nNot availableinthe\nsummary:\nIndicationforuse\nThe Eclipse\nTreatment Planning\nSystem (Eclipse\nTPS) is used to\nplan radiotherapy","The intended use and indications\nfor use of the proposed device,\nART-Plan v2.1.0 and the primary\npredicate (especially Ethos\nTreatment Planning, 1.1) are\nsimilar as they arebothsoftwares\nintendedtobeusedintheplanning\nofradiotherapytreatment1:"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p12-t0","doc_id":"K232479","page_num":12,"bbox":[72.08,130.83,701.33,526.75],"n_rows":5,"n_cols":7,"columns":["","SystemInformation","","","","",""],"rows":[["","SystemInformation","","","","",""],["Property","ProposedDevice\nART-Planv2.1.0","PrimaryPredicate\nEthos Treatment\nManagement,2.1;\nEthos Treatment\nPlanning,1.1","Referencedevice\nART-Plan\nv1.10.1","Reference\ndevice\nECLIPSE WITH\nAAA","Referencedevice\nEclipse Treatment\nPlanningSystem","Comment"],["Method of\nUse","Standalone\nsoftwareapplication\naccessed via a\ncompliant browser\n(Chrome, Mozilla\nFirefox and Edge)\non a personal\ncomputer, tablet or\nphone (In case of\nconnection to the\nplatform with a\nscreen of a phone\noratablet,theuser\nmust choose the\noption for the\ndesktop site of his\ncommunication\ndevice. The\nplatformisoptimally\nusedwith17inches\nand up screen.\nFacilitates display\nand visualization of\ndatabyuser.","Standalonesoftware\ndevice","Standalone\nsoftware application\naccessed via a\ncompliant browser\n(Chrome or Mozilla\nFirefox) on a\npersonal computer,\ntablet or phone (In\ncase of connection\nto the platform with\nascreenofaphone\nor atablet,theuser\nmustchoosethe\noption for the\ndesktop site of his\ncommunication\ndevice.Theplatform\nis optimally used\nwith 17 inches and\nupscreen.\nFacilitates display\nand visualization of\ndatabyuser.","Computerbased\nsoftwaredevice","Computerbased\nsoftwaredevice","The proposed device andtheprimary\npredicate are both standalone\nsoftware. More details have been\nfound on the reference device\nART-Plan v1.10.1whichhas identical\nmethods of use than the proposed\ndevice. An improvement has been\nintroduced with ART-plan v2.1.0 as it\ncanbealsousedonEdgebrowser."],["Data\nVisualizatio\nn /\nGraphical\nInterface","Yes","Yes","Yes","Yes","Yes","The proposed device, the primary\npredicates and all references devices\nhaveadatavisualisationandgraphical\ninterface"],["Synthetic\nCT","Generation of CT\ndensity image\nseries out of\nmultiple MR-image\nseries and CBCT\nimages","Generation of CT\ndensityimageseries\noutofCBCTimages","Generation of CT\ndensity image\nseries out of\nmultiple MR-image\nseries","N/A","N/A","The proposed device and primary\npredicate can generate synthetic-CT\nfromCBCTimage.\nThe proposed device can generate\nsynthetic CT from CBCT and MR\nimageswhereasitisnotpossiblewith"]],"caption_candidate":"SystemInformationComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p13-t0","doc_id":"K232479","page_num":13,"bbox":[72.13,108.25,701.5,522.63],"n_rows":3,"n_cols":7,"columns":["","","","","","","theprimarypredicatetodosowithMR\nimages. This does not represent an\nadditional claim as the technological\ncharacteristics are the same and it\ndoes not raise different questions of\nsafety and effectiveness. Also, this\nfeature is covered by the reference\ndevice ART-Planv1.10.1,whichisthe\nprevious version cleared of the\nproposeddeviceART-Planv2.1.0."],"rows":[["","","","","","","theprimarypredicatetodosowithMR\nimages. This does not represent an\nadditional claim as the technological\ncharacteristics are the same and it\ndoes not raise different questions of\nsafety and effectiveness. Also, this\nfeature is covered by the reference\ndevice ART-Planv1.10.1,whichisthe\nprevious version cleared of the\nproposeddeviceART-Planv2.1.0."],["Dose\ncomputatio\nn","Dose computation\non CT and/or\nsynthetic-CT\nimages for external\nbeam irradiation\nwithphotonbeams","Dose calculation\nwith AAA dose\ncalculation model\nandAcurosXBdose\ncalculationalgorithm\non CT and / or\nsyntheticCTimages","N/A","The AAA dose\ncalculation model is\na 3D\nconvolution/superpos\nition algorithm that\nmodels primary\nphotons, photons\nscattered in the\nmedium,\ncontamination\nelectrons and\ntransport electrons\nnear tissue\nheterogeneities. The\nAAAdosecalculation\nmodel is comprised\nof two main\ncomponents, one\nbeing the\nconfiguration\nalgorithm and the\nother one the actual\ndose calculation\nalgorithm.","AcurosXB dose\ncalculationalgorithm","The proposed device, the primary\npredicateandsomereferencedevices\nECLIPSE WITH AAA and Eclipse\nTreatment Planning System can\nperformdosecomputation."],["Off-line\nadaptation\ndecision-m\naking","Assisted\nCBCT-basedoff-line\nadaptation\ndecision-making for\nsupported\nanatomies","Ethos Treatment\nManagement allows\nthe physician to do\ninitial planning,\nreview and approve\ncandidateplans,and\nmonitor ongoing\ntreatments. Support\nfor adaptive\nradiotherapy","N/A","N/A","N/A","The proposed device andtheprimary\npredicatecanassistoff-lineadaptation\ndecision-making."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p14-t0","doc_id":"K232479","page_num":14,"bbox":[72.13,108.25,701.5,525.63],"n_rows":3,"n_cols":7,"columns":["","","treatment planning\nand automated plan\ngeneration","","","",""],"rows":[["","","treatment planning\nand automated plan\ngeneration","","","",""],["Supported\nModalities","Registration:\nStaticandgatedCT,\nMR, PET (via the\nregistration of the\nCT of said PET),\n4D-CT, CBCT and\nsynthetic-CT\ngenerated from\nCBCT\nSegmentation:\nCT(injectedornot),\nMRimages,DICOM\nRTSTRUCT,\nsynthetic-CT from\nCBCT","Registration:\nCT (including\nsynthetic CT from\nCBCT), MR and\nPET\nSegmentation:\nCTandsyntheticCT\nfromCBCT","Registration:\nStaticandgatedCT\n(including 4D-CT\nand CBCT), MR,\nPET (via the\nregistration of the\nCTofsaidPET)\nSegmentation:\nCT(injectedornot),\nMRimages,DICOM\nRTSTRUCT","Segmentation:\nEclipsealsoincludes\ntools for treatment\npreparation\n(diagnostic image\nand analysis,\ncontouring and\nsegmentation) and\nplanreview.","Registration:\nCT/MR/PET Image\nRegistration\n4D image display\n(registration of time\nyes yes seriesof3D\nimages)\nSegmentation:\nGeometrical shapes,\nManual editing and\nmanipulation tools,\nAutomatic\n/semi-automatic\ntools,\nAutomatic/semi-auto\nmatic on-demand\nand post-processing\ntools for individual\norgans/structures,\nAutomatic\non-demand and\npre-processing tools\nfor multiple\norgans/structures,3D\nAutornargin, Logical\noperators","The proposed device, the primary\npredicate and most of the reference\ndevices propose both registrationand\nsegmentation on medical images of\ndifferentmodalities."],["DataExport","Distribution of\nDICOM compliant\nImages into other\nDICOM compliant\nsystems.","ARIA RadOnc\nintegration, DICOM\nRT, other image\nformats, eclipse\nscripting API\n(ESAPI) read only\naccess, eclipse\nscripting API\n(ESAPI) write\naccess, Eclipse\nautomation, Export\nfield coordinates to\nlaser system, basic","Distribution of\nDICOM compliant\nImages into other\nDICOM compliant\nsystems.","DICOM includingRT\nobjects,MDCshaper\nfiles, blocks and\ncompensator datato\nPar Scientific, plan\nand dose data to\npicker AcQSim,\nintegrated with Varis\nverification, ASCIIfile\nto laser system,\nVarian CadPlan plus\n6.0","VARiS/Vision\ndatabase integration,\nDICOMRT/3.0,other\nimage formats,\nexport field\ncoordinates to laser\nsystem","The proposed device, the primary\npredicate and reference deviceshave\nidentical data export capabilities with\nDICOMformat."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p15-t0","doc_id":"K232479","page_num":15,"bbox":[72.13,108.25,701.5,293.37],"n_rows":2,"n_cols":7,"columns":["","","RT prescription\ninformationavailable","","","",""],"rows":[["","","RT prescription\ninformationavailable","","","",""],["Compatibili\nty","Compatible with\ndata from any\nDICOM compliant\nscanners for the\napplicable\nmodalities.","ARIA RadOnc\nintegration, DICOM\nRT, other image\nformats,\nelectromagnetic\ndigitizer, eclipse\nscripting API\n(ESAPI) read only\naccess, eclipse\nscripting API\n(ESAPI) write\naccess, eclipse\nautomation, Basic\nRT prescription\ninformationavailable","Compatible with\ndata from any\nDICOM compliant\nscanners for the\napplicable\nmodalities.","DICOM includingRT\nobjects, CART\nformat, TIFF format,\nCMP format,\nConfigurable pure\npixel data,\nPortalVision MArk 1\n& 2, Varian CT\noption,\nElectromagnetic\nDigitilizer, Film\nscanner","VARIs/Vision\ndatabase integration,\nDICOMRT/3.0,other\nimage formats,\nElectromagnetic\ndigitizer,filmscanner","The proposed device, the primary\npredicate and reference deviceshave\nidenticalcompatibility(DICOMformat)"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p15-t1","doc_id":"K232479","page_num":15,"bbox":[72.13,340.4,745.5,520.42],"n_rows":4,"n_cols":7,"columns":["","","TechnicalInformation","","","",""],"rows":[["","","TechnicalInformation","","","",""],["Property","ProposedDevice\nART-Planv2.1.0","PrimaryPredicate\nEthos Treatment\nManagement,2.1;\nEthos Treatment\nPlanning,1.1","Referencedevice\nART-Plan\nv1.10.1","Reference\ndevice\nECLIPSE WITH\nAAA","Referencedevice\nEclipse Treatment\nPlanningSystem","Comment"],["Delineation\nMethod","AI","AI","AI","Notstated","Notstated","The proposed device, primary predicate and\none of the reference devices (ART-Plan\nv1.10.1)shareanAIdelineationmethod."],["Image\nregistration","Multi-modal and\nmono-modal.\nRigidanddeformable\nAutomatic and\nmanual initialization\n(landmarks, fusion\nbox,alignment).\nRegistration for the\npurposes of\nreplanning/","Registration:\nCT (including\nsynthetic CT from\nCBCT), MR and\nPET","Multi-modal and\nmono-modal.\nRigidanddeformable\nAutomatic and\nmanual initialization\n(landmarks, fusion\nbox,alignment).\nRegistration for the\npurposes of","NA","CT/MR/PET Image\nRegistration\n4D image display\n(registration of time\nyesyes\nseriesof3Dimages)","Theproposeddevice,theprimarypredicateand\nmost of the reference devices propose\nregistration of medical images of different\nmodalities."]],"caption_candidate":"TechnicalInformationComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p16-t0","doc_id":"K232479","page_num":16,"bbox":[72.13,108.25,745.5,515.37],"n_rows":3,"n_cols":7,"columns":["","recontouring and\nAI-based automatic\ncontouring.","","replanning/\nrecontouring\nand AI-based\nautomaticcontouring.","","",""],"rows":[["","recontouring and\nAI-based automatic\ncontouring.","","replanning/\nrecontouring\nand AI-based\nautomaticcontouring.","","",""],["Segmentatio\nnFeatures","Automatically\ndelineates OARs and\nhealthylymphnodes\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the following\nlocalizations:\n* head and neck (on\nCTimages)\n* thorax/breast (for\nmale/female and on\nCTimages)\n* abdomen (on CT\nimages and MR\nimages)\n* pelvis male (on CT\nimages and MR\nimages)\n*pelvisfemale(onCT\nimages)\n*brain(onCTimages\nandMRimages)","CTandsyntheticCT\nfromCBCT","Automatically\ndelineates OARsand\nhealthylymphnodes\nDeep learning\nalgorithm\nAutomatic\nsegmentation\nincludesthefollowing\nlocalizations:\n* head and neck (on\nCTimages)\n* thorax/breast (for\nmale/female and on\nCTimages)\n* abdomen (on CT\nimages and MR\nimages)\n* pelvis male (on CT\nimages and MR\nimages)\n* pelvis female (on\nCTimages)\n*brain(onCTimages\nandMRimages)","Eclipse also\nincludes tools for\ntreatment\npreparation\n(diagnostic image\nand analysis,\ncontouring and\nsegmentation) and\nplanreview.","Geometrical shapes,\nManual editing and\nmanipulation tools,\nAutomatic\n/semi-automatic\ntools,\nAutomatic/semi-auto\nmatic on-demand\nand post-processing\ntools for individual\norgans/structures,\nAutomatic\non-demand and\npre-processing tools\nfor multiple\norgans/structures,3D\nAutornargin, Logical\noperators","Theproposeddevice,theprimarypredicateand\nmost of the reference devices propose\nsegmentation on medical images of different\nmodalitiesusingAI."],["View\nManipulation\nand\nVolume\nRendering","Window and level,\npan, zoom,\ncross-hairs,slice\nnavigation.\nColorrendering,fused\nviews,galleryviews.","Window and level,\npan, zoom,\ncross-hairs, slice\nnavigation.\nColor rendering,\nfused views, gallery\nviews.","Window and level,\npan, zoom,\ncross-hairs,slice\nnavigation.\nMaximum, average\nand minimum\nintensity projection\n(MIP,AVG,MinIP),\ncolorrendering,\nmulti-planar\nreconstruction(MPR),\nfused views, gallery\nviews.","Notstated","Notstated","Theproposeddevicehasthesametoolsasthe\nprimarypredicate."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p17-t0","doc_id":"K232479","page_num":17,"bbox":[72.17,108.25,745.5,311.75],"n_rows":2,"n_cols":7,"columns":["Regions and\nVolumes\nof Interest\n(ROI)","AI Based\nautocontouring,\nRegistration based\ncontour projection\n(re-contouring),\nManual ROI\nmanipulation and\ntransformation\n(margins, booleans\noperators,\ninterpolation).","AI based\nautocontouring\nRegistration based\ncontour projection\n(re-contouring)\nManual ROI\nmanipulation and\ntransformations\n(margins, booleans\noperators,\ninterpolation).","AI Based\nautocontouring,\nRegistration based\ncontour projection\n(re-contouring),\nManual ROI\nmanipulation and\ntransformation\n(margins, booleans\noperators,\ninterpolation).","Notstated","Notstated","Both the proposed device and the primary\npredicate allow AI automatic contouring and\nmanualcontouring."],"rows":[["Regions and\nVolumes\nof Interest\n(ROI)","AI Based\nautocontouring,\nRegistration based\ncontour projection\n(re-contouring),\nManual ROI\nmanipulation and\ntransformation\n(margins, booleans\noperators,\ninterpolation).","AI based\nautocontouring\nRegistration based\ncontour projection\n(re-contouring)\nManual ROI\nmanipulation and\ntransformations\n(margins, booleans\noperators,\ninterpolation).","AI Based\nautocontouring,\nRegistration based\ncontour projection\n(re-contouring),\nManual ROI\nmanipulation and\ntransformation\n(margins, booleans\noperators,\ninterpolation).","Notstated","Notstated","Both the proposed device and the primary\npredicate allow AI automatic contouring and\nmanualcontouring."],["Region/volu\nmeof\ninterest\nmeasuremen\ntsand\nsize\nmeasuremen\nts","Intensity and\nHounsfieldunits.\nSize measurements\ninclude 2D and 3D\nmeasurements\n(number of slices,\nvolumeofastructure,\nstaticruler)","Intensity, Hounsfield\nunits, Size\nmeasurement\ninclude 2D and 3D\nmeasurements\n(number of slices,\nvolume of a\nstructure, static\nruler)","Intensity, Hounsfield\nunits and SUV\nmeasurements\nSize measurements\ninclude 2D and 3D\nmeasurements\n(number of slices,\nvolumeofastructure,\nstaticruler)","Notstated","Notstated","The proposed device offers the same kind of\nregion/volumeofinterest\nmeasurements and size measurements asthe\nprimarypredicate."]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p23-t0","doc_id":"K232479","page_num":23,"bbox":[254.33,222.52,380.3,301.14],"n_rows":4,"n_cols":3,"columns":["","Sample\nSize","%"],"rows":[["","Sample\nSize","%"],["Training","246226","78"],["Validation","69147","22"],["Total","315373","100"]],"caption_candidate":"● Auto-segmentationtool","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p23-t1","doc_id":"K232479","page_num":23,"bbox":[254.33,336.39,380.3,414.76],"n_rows":4,"n_cols":3,"columns":["","Sample\nSize","%"],"rows":[["","Sample\nSize","%"],["Training","6195","77"],["Validation","1839","23"],["Total","8034","100"]],"caption_candidate":"● Synthetic-CTfromMRimages","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p23-t2","doc_id":"K232479","page_num":23,"bbox":[254.33,449.76,380.3,528.63],"n_rows":4,"n_cols":3,"columns":["","Sample\nSize","%"],"rows":[["","Sample\nSize","%"],["Training","1467","88"],["Validation","203","12"],["Total","1670","100"]],"caption_candidate":"● Synthetic-CTfromCBCTimages","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p27-t0","doc_id":"K232479","page_num":27,"bbox":[77.38,172.22,534.63,696.5],"n_rows":8,"n_cols":4,"columns":["Organ","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],"rows":[["Organ","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],["1. Duodenum","Intervariabilitycomparisonto\nexperts\nCriterionC\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=1.32%\nPassed","Samplesize:25\nwhichisabovethe\nminimumdatasample\nsize"],["2. Largebowel","Intervariabilitycomparisonto\nexperts\nCriterionC\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=1.19%\nPassed","Samplesize:25\nwhichisabovethe\nminimumdatasample\nsize"],["3. Smallbowel","Intervariabilitycomparisonto\nexperts\nCriterionC\nMinsamplesizeforevaluation\nmethod:20","DICEdiff\ninter-expert=2.44%\nPassed","Samplesize:25\nwhichisabovethe\nminimumdatasample\nsize"],["4. Rightlacrimal\ngland","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["5. Leftlacrimal\ngland","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["6. cervicallymph\nnodesVIA","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=97%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["7. Cervicallymph","Qualitativeevaluationbyexperts","A+B=100%","Samplesize:20"]],"caption_candidate":"clearedversionofthesoftwareinv1.10.1)ispresented:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p28-t0","doc_id":"K232479","page_num":28,"bbox":[77.5,107.5,534.5,705.5],"n_rows":9,"n_cols":4,"columns":["nodesVIB","CriterionD\nMinsamplesizeforevaluation\nmethod:15","Passed","whichisabovethe\nminimumdatasample\nsize"],"rows":[["nodesVIB","CriterionD\nMinsamplesizeforevaluation\nmethod:15","Passed","whichisabovethe\nminimumdatasample\nsize"],["8. Pharyngeal\nconstrictor\nmuscle","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["9. Analcanal","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=98.68%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["10. Bladder","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=93.42%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["11. Leftfemoral\nhead","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["12. Rightfemoral\nhead","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=100%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["13. Penilebulb","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=96.05%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["14. Prostate","Qualitativeevaluationbyexperts\nCriterionD\nMinsamplesizeforevaluation\nmethod:15","A+B=92.10%\nPassed","Samplesize:38\nwhichisabovethe\nminimumdatasample\nsize"],["15. Rectum","Qualitativeevaluationbyexperts","A+B=100%","Samplesize:38"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p29-t0","doc_id":"K232479","page_num":29,"bbox":[77.42,371.16,534.58,633.5],"n_rows":4,"n_cols":4,"columns":["Clinicaluse","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],"rows":[["Clinicaluse","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],["1. tCBCT-sCT","Qualitativeevaluationbyexperts\nCriterion1D\nMinsamplesizeforevaluation\nmethod:15","Rigid:A+B%=95.56%\nDeformable:\nA+B%=97.78%\nPassed","Samplesize:45\nwhichisabovethe\nminimumdatasample\nsize"],["2. tsynthetic-CT-\nsCT","Qualitativeevaluationof\npropagatedcontoursbyexperts\nCriterion1C\nMinsamplesizeforevaluation\nmethod:17","Deformable:\nTarget:\nA+B%=94.06%\nPassed","Samplesize:30\nwhichisabovethe\nminimumdatasample\nsize"],["3. tCT-sSCT","Qualitativeevaluationbyexperts\nCriterion1D\nMinsamplesizeforevaluation\nmethod:17","rigid:A+B%=70.37%\nPassed","Samplesize:27\nwhichisabovethe\nminimumdatasample\nsize"]],"caption_candidate":"latestclearedversionofthesoftwareinv1.10.1)ispresented:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p30-t0","doc_id":"K232479","page_num":30,"bbox":[77.31,107.7,534.69,528.5],"n_rows":8,"n_cols":4,"columns":["Criteria","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],"rows":[["Criteria","Performancetest\nmethod/Acceptancecriterion","Summaryofresults","Anydifferencesto\nprotocol?"],["Synthetic-CTfromCBCT","","",""],["Gammaindex\n2%/2mm\n3%/3mm","CriteriaA&B\nMinsamplesizeforevaluation\nmethod:17","2%/2mm=98.85\n3%/3mm=99.43\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["DVHparameters\n(PTV)","CriterionC\nMinsamplesizeforevaluation\nmethod:17","DVHparameters<\n0.199%in100%ofthe\ncases\nPassed","Samplesize:20\nwhichisabovethe\nminimumdatasample\nsize"],["Doseengine","","",""],["Gammaindex\n2%/2mm\n3%/3mm","CriteriaB&C\nMinsamplesizeforevaluation\nmethod:NAinthestateoftheart","2%/2mm=97.22%\n3%/3mm=99.50%\nPassed","Samplesize:272total\nBrain:42\nH&N:70\nChest:44\nBreast:26\nPelvis90"],["DVHparameters\n(PTV)","CriteriaA\nMinsamplesizeforevaluation\nmethod:NAinthestateoftheart","DVHparameters<\n1.29%\nPassed","Samplesize:272total\nBrain:42\nH&N:70\nChest:44\nBreast:26\nPelvis90"],["DVHparameters\n(OARs)","CriteriaA\nMinsamplesizeforevaluation\nmethod:NAinthestateoftheart","DVHparameters<\n3.9%\nPassed","Samplesize:272total\nBrain:42\nH&N:70\nChest:44\nBreast:26\nPelvis90"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p31-t0","doc_id":"K232479","page_num":31,"bbox":[102.25,189.51,531.63,683.5],"n_rows":9,"n_cols":3,"columns":["TestName","TestDescription/Results","Results"],"rows":[["TestName","TestDescription/Results","Results"],["UsabilityReport\n(V2.1.0)","This document is intended to document the usability test\nresults for the ART-Plan v2.1.0 for compliance with IEC\n62366-1:2015+AMD1:2020 - Medical devices -\nApplicationofusabilityengineeringtomedicaldevices.","Passed"],["Usabilityfile-ART-USR-13\n(V2.1.0)","The ART-Plan was assessed with regards to usabilityfor\ncompliancewitheachsectionofIEC62366.","Passed"],["Usability-Testersqualification\n(V2.1.0)","This table shows that European medical physicists who\nhave participated in the evaluation have at least an\nequivalent expertise level compared to a junior US\nmedical physicist (MP), and responsibilities in the\nradiotherapyclinicalworkflowareequivalent.","N/A"],["LiteratureReviewand\nPerformanceCriteria\nExtractionReportforART-Plan\n(V2.1.0)","A literature review is performed to establish acceptance\ncriteria for performance of ART-Plan modules using\nperformance ranges observed from benchmark devices\nand alternative technologies in the literature. All\nmeasures of performance that were established in this\ndocument were supported by clinical evidence. It was\nalso demonstrated, from the clinical data, that ART-Plan\nhas a clear clinical relevance in accordance with the\nclinicalstateoftheart.","N/A"],["ART-Planperformancetesting\n-Overview\n(V1.10.1-2.1.0)","The document summarises all performance tests that\nhave been performed since the last FDA approved\nversion (1.6.1). It also shows which criteria have been\nmet in each test for all modules of ART-Plan. It\ndemonstrates that all modules of ART-Plan pass at least\none performance acceptance criterion and hence are\nclinicallyacceptableforrelease.","Passed"],["Pilotstudyforsamplesize\nestimation-literaturereview\n(V2.1.0)","The literature review was performed to estimate the\nappropriate sample size of the testing data set towards\ndemonstrating the performance of theimageregistration,\nsegmentation and synthetic-CT generation solutions on\nthe basis of the most recent and most relevant scientific\nliterature.","N/A"],["Qualitative&Quantitative\nvalidationoffusion\nperformances(V2.1.0)","The study was developed to cover the major clinical use\ncases in which fusions are used in the radiotherapy\nworkflow and split into as many sub-studies as clinical\nuse cases of fusion in radiotherapy workflow.Theresults\nshow that both types of fusion algorithms (Rigid &\nDeformable) in SmartFuse pass theperformedtests,and\nprovide valid results for further clinical use in\nradiotherapy.","Passed"],["Protocolforqualitative&\nquantitativevalidationoffusion\nperformancesfor\ntCBCT_sCT_replanning\nmodality(V2.0.0)","This study evaluated the quality of the rigid and the\ndeformable fusion algorithms of the SmartFuse module\nforreplanificationofCT-basedtreatments.","Passed"]],"caption_candidate":"softwareinv1.10.1)wasevaluatedforitssafetyandeffectivenessarepresented:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p32-t0","doc_id":"K232479","page_num":32,"bbox":[102.5,95.5,531.5,679.5],"n_rows":6,"n_cols":3,"columns":["Protocolforqualitative&\nquantitativevalidationoffusion\nperformances for\ntsynthetic-CT_sCT_replanning\nmodality(V2.1.0)","This study evaluated the quality of the rigid and the\ndeformable fusion algorithms of the SmartFuse module\nforreplanificationofCT-basedtreatments.","Passed"],"rows":[["Protocolforqualitative&\nquantitativevalidationoffusion\nperformances for\ntsynthetic-CT_sCT_replanning\nmodality(V2.1.0)","This study evaluated the quality of the rigid and the\ndeformable fusion algorithms of the SmartFuse module\nforreplanificationofCT-basedtreatments.","Passed"],["Protocolforqualitative&\nquantitativevalidationoffusion\nperformances for\ntCT_ssynthetic-CT_replanning\nmodality(V2.1.0)","This study evaluated the quality of the rigid and the\ndeformable fusion algorithms of the SmartFuse module\nforreplanificationofCT-basedtreatments.","Passed"],["StudyProtocolandReport\nAnnotate Performances\nSummary(V2.1.0)","Thepurposeofthisdocumentistodescribeallthetesting\nprotocols and testing results for validating the\nperformanceoftheAnnotatemodule.\nTo this aim, this document gathers information of all the\ndifferent testing conducted on Annotate for the CT, MR\nand synthetic-CT from CBCT autosegmentation\nalgorithmsforv2.1.0:\n● qualitative evaluation for autosegmentation\nperformance - pelvis male organs on\nsynthetic-CTfromCBCT-seesection18.13\n● autosegmentation performances against\ninter-expert variability - bowel loopstructureson\nCT -seesection18.14\n● qualitative evaluation for autosegmentation\nperformance - H&N lymph nodes (CT) - see\nsection18.15\n● Non regression testing for integration in\nART-Plan v1.11.0 (CT and MR models) - see\nsection18.7\n● Non regression testing for integration in\nART-Plan v2.1.0 (CT and MR models) - see\nsection18.16\nSince all organs added in v.2.1.0 of Annotate have\npassed at least onetestandmetatleastoneacceptance\ncriteria,allorganshavebeenreleased.","Passed"],["StudyProtocolandReport\nQualitative Validation of\nAnnotateinART-Planforpelvis\nmale organs on synthetic-CT\nfromCBCT(V2.1.0)","This test demonstrates that the module Annotate\nprovides acceptablecontoursfortheorgansevaluatedon\nsynthetic-CT from CBCT images of patients. All organs\nthat have passed the acceptance criterion of reaching a\npercentage of at least 85% of A or B (qualitative\nevaluation)havebeenreleasedinv.2.1.0.","Passed"],["Study Protocol and Report-\nAutosegmentation\nperformances against\ninter-expert variability - bowel\nloopstructures(V2.1.0)","This test demonstrates that the module Annotate\nprovides clinically acceptable (compared to inter-expert\nvariability) for bowel loops structure. All organsthathave\npassed theacceptancecriterionofreachingapercentage\nof a DSC(mean)≥ 0.8 or DSC(mean)≥0.54) or\nDSC(mean)≥mean(DSC inter-expert)+5% relative error\n(quantitativeevaluation)havebeenreleasedinv.2.1.0.","Passed"],["StudyProtocolandReport\nQualitative Validation of\nAnnotate in ART-Plan for H&N\nlymphnodes (V2.1.0)","This test demonstrates that the module Annotate\nprovides acceptablecontoursfortheorgansevaluatedon\nCT images of patients. All organs that have passed the\nacceptance criterion of reaching a percentage of at least\n85%ofAorB(qualitativeevaluation)havebeenreleased\ninv.2.1.0.","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232479-p33-t0","doc_id":"K232479","page_num":33,"bbox":[102.5,95.5,531.5,527.5],"n_rows":10,"n_cols":3,"columns":["Autosegmentationregression\ntestforintegrationinART-Plan\n(V2.1.0)","This test demonstrates equivalence between the version\nv.2.1.0 and v.2.0.0 of the auto-segmentation models for\nall structures and showsthattheupdatedmodelsprovide\nclinically acceptable contours. All organs passed the\ndefined criteria, and were hence accepted for release in\nthev.2.1.0.","Passed"],"rows":[["Autosegmentationregression\ntestforintegrationinART-Plan\n(V2.1.0)","This test demonstrates equivalence between the version\nv.2.1.0 and v.2.0.0 of the auto-segmentation models for\nall structures and showsthattheupdatedmodelsprovide\nclinically acceptable contours. All organs passed the\ndefined criteria, and were hence accepted for release in\nthev.2.1.0.","Passed"],["Studyprotocolandreport\nDose engine measurements\nvalidation (V2.1.0)","The evaluation demonstrated the dose calculation\naccuracy by carrying out measurements on a Linac and\ncomparing the results with thedoseenginegivenvarious\nmetricsandacceptancecriteria.","Passed"],["Studyprotocolandreport\nDose engine clinical validation\n(V2.1.0)","The evaluation demonstrated the non-inferiority of the\ndose engine function of the AdaptBoxmoduleintermsof\ndosimetric measures compared to other commercially\navailabledoseengines.","Passed"],["Studyprotocolandreport\nDose engine performance\nagainst reference devices\n(V2.1.0)","The evaluation demonstrated the non-inferiority of the\ndose engine function of the AdaptBoxmoduleintermsof\ndosimetricmeasurescomparedtoFDAcleareddevices.","Passed"],["Studyprotocolandreport\nClinical validation of\nsynthetic-CTs from CBCT\n(V2.1.0)","The evaluation demonstrated the non-inferiority of using\nsynthetic-CT from CBCT for treatment replanning in\nterms of dosimetric measures as compared to CT-based\ntreatment replanning. Our synthetic-CT from CBCT for\npelvis has shown to produce results that meet the\nacceptance criteria derived from clinical practice and\nliteraturereview.","Passed"],["Study protocol and report\nPerformance against Ethos\n(Varian)(V2.1.0)","The evaluation demonstrated the non-inferiority of the\nAdaptBoxmodulecomparedtoaFDAcleareddevice.","Passed"],["Studyprotocolandreport\nPerformance on US data\n(V2.1.0)","The evaluation demonstrated the equivalent\nperformancesbetweennon-USandUSpopulation.","Passed"],["StudyProtocolandReportfor\nCBCT-based synthetic-CT\nevaluation(V2.1.0)","The evaluation demonstrated the anatomical and\ngeometricalofthesynthetic-CtgeneratedfromCBCT","Passed"],["AI-powered decision making\nprocess for RT re-planning\n(V2.1.0)","This study demonstrated that AdaptBox is an effective\ntool to assist physicians and physicists in the decision\nmakingprocessforre-planning","Passed"],["SystemVerificationand\nValidationTesting(V2.1.0)","The system verification and validation testing was\nperformedtoverifythesoftwareoftheART-Plan.","Passed"]],"caption_candidate":"ART-Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232482-p6-t0","doc_id":"K232482","page_num":6,"bbox":[109.99,214.32,540.1,262.32],"n_rows":3,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Sola Fit with\nsyngo MR XA51A","K221733,\ncleared December 13, 2022","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232482-p6-t1","doc_id":"K232482","page_num":6,"bbox":[109.99,316.32,540.1,504.0],"n_rows":4,"n_cols":4,"columns":["Reference Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Aera with\nsoftware syngo MR XA30A\nPlease note: the Mobile Solution,\nas part of MAGNETOM Aera with\nsoftware syngo MR XA30A, is the\nreference device related to\nmodifications performed to fit the\nsubject device to the mobile\nenvironment.","K202014,\ncleared September 8, 2020","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"],["MAGNETOM Avanto Fit\nwith software syngo MR\nXA50A\nPlease note: reference device\nrelated to the cover","K220151,\ncleared April 1, 2022","LNH\nLNI, MOS","Siemens Healthcare\nGmbH"]],"caption_candidate":"already cleared on the following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232482-p8-t0","doc_id":"K232482","page_num":8,"bbox":[109.79,105.69,540.18,686.04],"n_rows":16,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognitio","n Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-4","General II\n(ES/ EMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-\n1:2005/(R)2012\nand A1:2012,\nC1:2009/(R)2012\nand\nA2:2010/(R)2012\n(Consolidated Text)","ANSI AAMI"],["19-8","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2, Ed.\n4.0:2014","IEC"],["12-295","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33, Ed.\n3.2:2015","IEC"],["5-125","General I\n(QS/ RM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third Edition\n2019-12","ISO"],["5-114","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices\n[Including CORRIGENDUM 1\n(2016)]","62366-1 Edition 1.0\n2015-02","IEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"],["2-258","Biocompati\nbility","Biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process","10993-1 Fifth\nedition 2018-08","ISO"],["12-342","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20\n2021e","NEMA"],["12-188","Radiology","Determination of Signal-to-\nNoise Ratio (SNR) in Diagnostic\nMagnetic Resonance Images","MS 1:2008 (R2020)","NEMA"],["12-196","Radiology","Determination of Two-\ndimensional Geometric\nDistortion in Diagnostic\nMagnetic Resonance Images","MS 2:2008 (R2020)","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232482-p9-t0","doc_id":"K232482","page_num":9,"bbox":[109.8,105.6,540.36,454.56],"n_rows":8,"n_cols":5,"columns":["12-187","Radiology","Determination of Image\nUniformity in Diagnostic\nMagnetic Resonance Images","MS 3:2008 (R2020)","NEMA"],"rows":[["12-187","Radiology","Determination of Image\nUniformity in Diagnostic\nMagnetic Resonance Images","MS 3:2008 (R2020)","NEMA"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4:2010","NEMA"],["12-322","Radiology","Determination of Slice\nThickness in Diagnostic\nMagnetic Resonance Imaging","MS 5:2018","NEMA"],["12-195","Radiology","Determination of Signal-to-\nNoise Ratio and Image\nUniformity for Single-Channel,\nNon-Volume Coils in Diagnostic\nMagnetic Resonance Imaging\n(MRI)","MS 6:2008 (R2014)","NEMA"],["12-315","Radiology","Characterization of the Specific\nAbsorption Rate for Magnetic\nResonance Imaging Systems","MS 8:2016","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2020)","NEMA"],["12-298","Radiology","Determination of Local Specific\nAbsorption Rate (SAR) in\nDiagnostic Magnetic Resonance\nImaging Systems","MS 10 - 2010","NEMA"],["12-306","Radiology","Quantification and Mapping of\nGeometric Distortion for Special\nApplications","MS 12 - 2016","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p4-t0","doc_id":"K232491","page_num":4,"bbox":[90.24,164.24,515.32,670.06],"n_rows":17,"n_cols":3,"columns":["Date Prepared:","Mar 8, 2024",""],"rows":[["Date Prepared:","Mar 8, 2024",""],["Manufacturer:","Philips Healthcare (Suzhou) Co., Ltd.\nNo. 258, Zhongyuan Road, Suzhou Industrial Park,\nSuzhou Jiangsu, CHINA, 215024\nEstablishment Registration Number: 3009529630\nAdditional Manufacturing Site:\nPhilips Medical Systems Technologies, LTD.\nAdvanced Technology Center MATAM, Building 34,\n3100202 Haifa Israel.\nEstablishment Registration Number: 9617978",""],["Primary Contact\nPerson:\nSecondary Contact\nPerson","Shiguang An\nRegulatory Affairs Engineer\nPhone: +86-0-13940106467\nE-mail: shiguang.an@philips.com\nErhong Wang\nSenior Manager Regulatory Affairs\nPhone : +86-0-13021019589\nE-mail : erhong.wang@philips.com",""],["Device Name:","CT 5300",""],["Classification:","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Regulation:","21CFR 892.1750"],["","Classification Panel:","Radiology"],["","Device Class:","Class II"],["","Primary Product Code:","JAK"],["Primary Predicate\nDevice:","Trade name:","Philips Incisive CT"],["","Manufacturer:","Philips Healthcare (Suzhou)\nCo., Ltd."],["","510(k) Clearance:","K212441"],["","Classification Regulation:","21CFR 892.1750"],["","Classification name:","Computed tomography x-ray\nsystem"],["","Classification Panel:","Radiology"],["","Device class","Class II"],["","Product Code:","JAK"]],"caption_candidate":"[As required by 21 CFR 807.92(c)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p6-t0","doc_id":"K232491","page_num":6,"bbox":[90.24,91.08,515.32,616.72],"n_rows":2,"n_cols":2,"columns":["","The CT 5300 on Trailer Kit has the same fundamental\ndesign characteristics and technologies as the current\nmarketed Philips Incisive CT on trailer (K211168 -\nNovember 22, 2021). The CT on Trailer configuration is\nidentical to the K211168 trailer configuration. The CT\nsystem should only be used in designated locations for\nuse with appropriate radiation controls and safety\nmeasures.\nIn addition to the above components and the software\noperating them, each system includes hardware and\nsoftware for data acquisition, display, manipulation, storage\nand filming as well as post-processing into views other than\nthe original axial images.\nUpgrades Kit is available to upgrade earlier Incisive CT\ninstallations to latest version."],"rows":[["","The CT 5300 on Trailer Kit has the same fundamental\ndesign characteristics and technologies as the current\nmarketed Philips Incisive CT on trailer (K211168 -\nNovember 22, 2021). The CT on Trailer configuration is\nidentical to the K211168 trailer configuration. The CT\nsystem should only be used in designated locations for\nuse with appropriate radiation controls and safety\nmeasures.\nIn addition to the above components and the software\noperating them, each system includes hardware and\nsoftware for data acquisition, display, manipulation, storage\nand filming as well as post-processing into views other than\nthe original axial images.\nUpgrades Kit is available to upgrade earlier Incisive CT\ninstallations to latest version."],["Indications for Use:","The CT 5300 is a Computed Tomography X-Ray System\nintended to produce images of the head and body by\ncomputer reconstruction of x-ray transmission data taken at\ndifferent angles and planes. These devices may include\nsignal analysis and display equipment, patient and\nequipment supports, components and accessories. The CT\n5300 is indicated for head, whole body, cardiac and\nvascular X-ray Computed Tomography applications in\npatients of all ages.\nThese scanners are intended to be used for diagnostic\nimaging and for low dose CT lung cancer screening for the\nearly detection of lung nodules that may represent cancer*.\nThe screening must be performed within the established\ninclusion criteria of programs / protocols that have been\napproved and published by either a governmental body or\nprofessional medical society.\n*Please refer to clinical literature, including the results of the\nNational Lung Screening Trial (N Engl J Med 2011;\n365:395-409) and subsequent literature, for further\ninformation."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p11-t0","doc_id":"K232491","page_num":11,"bbox":[90.24,91.08,515.32,492.34],"n_rows":2,"n_cols":2,"columns":["","design of the AI algorithm, the body joints detection\nalgorithm including CNN architecture, model parameters,\ninference pipeline, pre- and post-processing is same as\nwhat is used in the predicate Incisive CT. The original model\nwas trained using a broad dataset and performance data\nusing clinical images demonstrate the model can further\nsupport more exams (cardiac, spine, runoff).\nEvaluation/assessment of the modified Precise Position\nalgorithm, system level verification and validation activities\nhave been properly carried out to demonstrate it is as safe\nand effective as the predicate to process the newly\nintegrated exams (cardiac, spine, runoff), hence the\nmodified Precise Position in the CT 5300 is substantially\nequivalent to the predicate Incisive CT (K212441), which\nintegrates Precise Position (originally cleared in K203514).\nTherefore, the proposed device is substantially equivalent to\nthe primary currently marketed and predicate device\nPredicate Philips Incisive CT (K212441(April 27, 2022) in\nterms of safety and effectiveness."],"rows":[["","design of the AI algorithm, the body joints detection\nalgorithm including CNN architecture, model parameters,\ninference pipeline, pre- and post-processing is same as\nwhat is used in the predicate Incisive CT. The original model\nwas trained using a broad dataset and performance data\nusing clinical images demonstrate the model can further\nsupport more exams (cardiac, spine, runoff).\nEvaluation/assessment of the modified Precise Position\nalgorithm, system level verification and validation activities\nhave been properly carried out to demonstrate it is as safe\nand effective as the predicate to process the newly\nintegrated exams (cardiac, spine, runoff), hence the\nmodified Precise Position in the CT 5300 is substantially\nequivalent to the predicate Incisive CT (K212441), which\nintegrates Precise Position (originally cleared in K203514).\nTherefore, the proposed device is substantially equivalent to\nthe primary currently marketed and predicate device\nPredicate Philips Incisive CT (K212441(April 27, 2022) in\nterms of safety and effectiveness."],["Summary of Clinical\nData:","The proposed device did not require clinical study since\nsubstantial equivalence to the legally marketed predicate\ndevice was proven with the verification/validation testing,\nbench testing, retrospective clinical data, and other\nevidence as outlined"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p12-t0","doc_id":"K232491","page_num":12,"bbox":[89.11,180.02,536.86,705.69],"n_rows":12,"n_cols":11,"columns":["","Scan Characteristics Comparison","","","","","","","","",""],"rows":[["","Scan Characteristics Comparison","","","","","","","","",""],["","","","Proposed CT 5300","","","Predicate Philips","","Conclusion","Conclusion",""],["","","","device","","","Incisive CT (K212441)","","","",""],["No. of Slices","","64/128","","","64/128","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Scan Modes","","Surview\nAxial Scan\nHelical Scan","","","Surview\nAxial Scan\nHelical Scan","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Minimum Scan\nTime","","0.35 sec for 360° rotation","","","0.35 sec for 360° rotation","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Image (Spatial)\nResolution","","High resolution mode: 16\nlp/cm\nStandard resolution\nmode: 13 lp/cm","","","High resolution mode: 16\nlp/cm\nStandard resolution\nmode: 13 lp/cm","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Image Noise","","0.27% at 120 kV, 230\nmAs, 10 mm slice\nthickness","","","0.27% at 120 kV, 230\nmAs, 10 mm slice\nthickness","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Slice\nThicknesses","","Helical: 0.67mm – 5mm\nAxial: 0.625 mm –\n10.0mm","","","Helical: 0.67mm – 5mm\nAxial: 0.625 mm –\n10.0mm","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Scan Field of\nView","","Up to 500 mm","","","Up to 500 mm","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Image Matrix","","Up to 1024 * 1024","","","Up to 1024 * 1024","","","Identical.\nTherefore, substantially\nequivalent.","",""],["Display","","1920 * 1080","","","1920 * 1080","","","Identical.","",""]],"caption_candidate":"the proposed CT 5300 device and predicate Philips Incisive CT (K212441).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p13-t0","doc_id":"K232491","page_num":13,"bbox":[89.11,91.65,536.86,361.49],"n_rows":4,"n_cols":4,"columns":["","","","Therefore, substantially\nequivalent."],"rows":[["","","","Therefore, substantially\nequivalent."],["Host\nInfrastructure","Windows 10","Windows 10","Identical.\nTherefore, substantially\nequivalent."],["Communication","Compliance with DICOM","Compliance with DICOM","Identical.\nTherefore, substantially\nequivalent."],["Dose Reporting\nand\nManagement","Compliance with NEMA\nXR25, XR26, XR28 and\nXR29","Compliance with NEMA\nXR25, XR28 and XR29","Compliance with more\nNEMA standard.\nSafety and\neffectiveness are not\naffected.\nTherefore,\ndemonstrating\nsubstantial\nequivalence."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p13-t1","doc_id":"K232491","page_num":13,"bbox":[89.11,388.6,536.86,711.3],"n_rows":10,"n_cols":8,"columns":["","Software or Imaging Features Comparison","","","","","",""],"rows":[["","Software or Imaging Features Comparison","","","","","",""],["CT 5300\nFeatures\nName","","Feature description","","Same feature","","Conclusion\n(Function/ User\ninterface/\nWorkflow)",""],["","","","","cleared in","","",""],["","","","","Predicate","","",""],["","","","","Philips","","",""],["","","","","Incisive CT","","",""],["","","","","(K212441)","","",""],["2D Viewer","","In 2D Viewer mode operator can review\noriginal axial images as acquired by the\nscanner.","Yes","","","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["MPR","","Use the MPR mode to view three-plane\northogonal images. In this mode, the three\nshown planes can be easily correlated.\nThree orthogonal cut planes are shown:\n• Axial Orientation\n• Coronal Orientation\n• Sagittal Orientation","Yes","","","Identical.\nTherefore,\nsubstantially\nequivalent.",""],["3D (volume\nmode)","","The volume mode is used to display CT\nscanner data in a full volume image. It\nprovides basic tools for image editing and\ngeneration of cine movies.","Yes","","","Identical.",""]],"caption_candidate":"equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p14-t0","doc_id":"K232491","page_num":14,"bbox":[89.06,91.33,536.91,713.55],"n_rows":16,"n_cols":6,"columns":["","","","Therefore,\nsubstantially\nequivalent.","",""],"rows":[["","","","Therefore,\nsubstantially\nequivalent.","",""],["Virtual\nEndoscopy\n(Endo)","The CT Endo viewer is a review function\nthat allows you to perform a general\nflythrough of any suitable anatomical\nstructure that is filled with air or with\ncontrast material, including general vessels,\ncardiac vessels, the bronchus, and the\ncolon.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Image matrix","The Image Matrix parameter sets the\nnumber of pixels that the reconstructed\nimage will contain. Select 512, 768, or\n1024.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["O-MAR","O-MAR stands for orthopedic metal artifact\nreduction. This post processing capability\nreduces metal induced artifacts and is\ndirected for large orthopedics metals that\ncause photon starvation of the rays that\npass through the metal object.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["DoseRight\nIndex\n(DRI)","DoseRight Index (DRI) is according to the\ncurrent scan site and body size of the\npatient, the mAs suitable for the patient is\nautomatically recommended, so that the\nimage quality can meet the requirements of\nthe diagnosis, and the radiation dose of the\npatient can be reduced as far as possible.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["DOM","DOM combines angular and longitudinal\ninformation to modulate dose in three\ndimensions. Personalizes dose for each\npatient by automatically suggesting tube\ncurrent settings according to the estimated\npatient diameter in the scan region. Angular\ndose modulation varies the tube current\nduring helical scans according to changes\nin patient shape (eccentricity) and tissue\nattenuation as the tube rotates.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Precise\nPlanning","Precise Planning can automatically adjust\nthe scan range of subsequent Axial or\nHelical scan series, based on the Surview\nImage.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Oblique\nMPR","Support the adjustment of sagittal / coronal\nimage construction in the planned scanning\nphase, and finally obtain the adjusted tilted\nmultiplane image.\nOn the basis of Insert MPR, surface\nreconstruction is carried out by interpolation\nof axial image and corresponding tilted\nimage is generated.","Yes\n(It is called\n“Insert MPR” in\npredicate\ndevice)","","Revised feature,",""],["","","","","on the basis of the",""],["","","","","cleared “Insert",""],["","","","","MPR”, added the\nability for users to",""],["","","","","tilt the MPR",""],["","","","","image.",""],["","","","","Safety and",""],["","","","","effectiveness are",""],["","","","","not affected.",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p15-t0","doc_id":"K232491","page_num":15,"bbox":[89.05,91.44,536.92,707.64],"n_rows":13,"n_cols":6,"columns":["","","","","Therefore,",""],"rows":[["","","","","Therefore,",""],["","","","","substantially",""],["","","","","equivalent.",""],["OnPlan","OnPlan is a gantry operational touch panel\nlocated on both sides of the gantry. The\nOnPlan gantry controls are used to activate\nthe laser marker, controls patient table\nmovements, display patient information and\nimages, and conduct a new patient exam.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Precise\nSpine","Precise Spine application enables the\nsystem to assist the user to identify the\nlumbar disk space automatically and create\na batch based on the protocol selected.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Precise\nBrain","Precise Brain application for a series of\nbrain tissue slices that are parallel or\nvertical in the plane of the cranial CT scan.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Bolus\nTracking","The Bolus tracking function maximizes the\nefficiency of CT scans that are enhanced\nthrough the use of a contrast agent. This is\ndone by preceding the Clinical scan with\nLocator and Tracker scans.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["SAS (Spiral\nAuto Start)","This feature enables the usage of the\ninjector scan trigger.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Filming","The Filming application is used for viewing,\nrearranging, windowing and zooming\nimages prior to sending them to be printed.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Worklist","The Worklist displays patient information\nprovided by the HIS/RIS.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["MPPS","If the patient is from the Worklist and the\nMPPS function is enabled, feedback\nregarding the study status of the patient can\nbe sent to the hospital HIS/RIS.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["Reporting","The Reporting package allows you to create\ncustomized reports using pre-formatted\ntemplates.\nA template is a specially designed\nformatting document that places the\nanalytical information and images that you\nsend from an application into an organized\nreport which can be printed and saved.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent.","",""],["CCT\n(Continuous\nCT)","Continuous CT (CCT) is a scanning mode\nthat allows the physician to perform","Yes","Identical.","",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p16-t0","doc_id":"K232491","page_num":16,"bbox":[89.01,91.33,536.95,717.06],"n_rows":9,"n_cols":4,"columns":["","extended, low-dose scans while performing\na biopsy.\nThe resulting images are displayed on a\nremote monitor in the scan room, providing\nvisual feedback during the biopsy.","","Therefore,\nsubstantially\nequivalent."],"rows":[["","extended, low-dose scans while performing\na biopsy.\nThe resulting images are displayed on a\nremote monitor in the scan room, providing\nvisual feedback during the biopsy.","","Therefore,\nsubstantially\nequivalent."],["Brain\nPerfusion","Brain Perfusion is a blood flow imaging\napplication that analyzes the uptake of\ninjected contrast in order to determine\nperfusion-related information about one or\nmore regions of interest.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Dental\n(Dental\nplanning)","Dental applications are used to create true-\nsize (life size) film images of the mandible\nand maxilla for assisting oral surgeons in\nplanning implantation of prostheses. Using\na special dental planning procedure, the\nimages will be created from this scan which\ncan be input into the Dental planning\napplication.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["iDose4","iDose4 is an iterative reconstruction\ntechnique that improves image quality\nthrough artifact prevention and increased\nspatial resolution at low dose.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Helical\nRetrospectiv\n-e Tagging","Helical retrospective cardiac scanning\nenables the system to acquire a volume of\ndata while the patient’s ECG is recorded.\nThe acquired data is tagged and\nreconstructed retrospectively at any desired\nphase of the cardiac cycle.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Axial\nProspective\nGating\ncalcium\nscoring","Axial prospective gating uses an external\nECG gating system to synchronize\nindividual axial scans with the patient’s\nheartbeat. The ECG-triggered scans\nsignificantly minimize heart-motion artifacts.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Step &\nShoot","Step & Shoot Cardiac provides high quality\nCT images of the coronary arteries and\nheart anatomy at very low radiation dose\nlevels. During Step & Shoot Cardiac, X-rays\nare generated only during the cardiac phase\nof interest.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["CCS\n(Cardiac\ncalcium\nscoring)","The Cardiac Calcium Scoring application is\nused to quantify the buildup of calcium\nplaque on the walls of the patient's coronary\narteries and other relevant locations. The\npotential calcifications are highlighted by the\napplication during launch.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Precise\nimage","Precise image reconstruction is a recon\nmode where the system uses a trained\ndeep learning neural network to generate\nnoise reduction images compared with\nstandard FBP recon mode for adult\npatients only. Precise Image has not been","Yes","Same AI/ML\nimage recon\nalgorithm,\nmodified with new\nmodels to enable\nthe reconstruction"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p17-t0","doc_id":"K232491","page_num":17,"bbox":[89.01,91.33,536.95,705.18],"n_rows":4,"n_cols":4,"columns":["","validated for lung cancer screening\nindications.","","of a new organ\ntype (cardiac),\nsupport more slice\nthicknesses, a\nnew scan mode\n(high resolution\nhead), and more\nclinical scenarios\nfor body and\nhead.\nNo change to\nalgorithm\narchitecture\ncompared to\npredicate device,\ntherefore,\nsubstantially\nequivalent."],"rows":[["","validated for lung cancer screening\nindications.","","of a new organ\ntype (cardiac),\nsupport more slice\nthicknesses, a\nnew scan mode\n(high resolution\nhead), and more\nclinical scenarios\nfor body and\nhead.\nNo change to\nalgorithm\narchitecture\ncompared to\npredicate device,\ntherefore,\nsubstantially\nequivalent."],["Precise\ncardiac","Precise Cardiac is a reconstruction\ntechnique with the potential to\nprovide compensation for cardiac motion.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Precise\nposition","Precise Position is a camera-based\nworkflow designed to assist with positioning\nthe patients aged 16 years and older\nautomatically from console or OnPlan, it\ncan:\n•automatically select patient orientation.\n•automatically set vertical centering &\npositioning of the patient to the Surview\nstart and end positions.\n•support editing Surview start & end range\nand scan direction.","Yes","Same AI/ML\nalgorithm,\nmodified to\nsupport more\nexams (cardiac,\nspine, runoff).\nNo change to\nalgorithm\narchitecture\ncompared to\npredicate device,\ntherefore,\nsubstantially\nequivalent."],["Precise\nintervention","In Precise Intervention viewer there are\nseveral tools, they will help you to navigate\nthe needle safely during the intervention.","Yes","Same\ninterventional\nfeature as\npredicate device.\nTo duplicate one\nadditional\nInterventional\ncontrols panel\nfrom couch side to\na mobile cart for\nconvenience.\nThere is no\nchange to SW\nalgorithm"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p18-t0","doc_id":"K232491","page_num":18,"bbox":[89.01,91.33,536.95,707.1],"n_rows":9,"n_cols":4,"columns":["","","","compared to\npredicate device.\nTherefore,\nsubstantially\nequivalent."],"rows":[["","","","compared to\npredicate device.\nTherefore,\nsubstantially\nequivalent."],["Direct\nresults","Direct Result-With Direct Result the user is\nable to choose a desired result during scan\nplanning phase and get the result for\ndiagnosis without\nfurther intervention.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Parallel\nworkflow","The system support Parallel workflow using\nDual monitor as below:\n- main monitor: Patients, scan, service,\n\"show all\" for scan planning, Help.\n- extend monitor: Completed, viewers,\nAnalysis, recon, filming, report","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["CTC (CT\nColonoscopy)","CT Colonoscopy (CTC) application enables\nfast and easy visualization of colon scans,\nusing acquired CT images.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["VA (Vessel\nAnalysis)","Vessel Analysis (VA) offers a set of tools for\ngeneral vascular analysis. With VA the user\ncan easily remove bone, and extract\nvessels. Users also can perform\nmeasurements such as intraluminal\ndiameter, cross-sectional lumen area,\nlength.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["LNA (Lung\nNodule\nAnalysis)","The Lung Nodule Analysis (LNA)\napplication assists the radiologist with the\ndetection and quantification of pulmonary\nnodules and lesions.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["CAA\n(Cardiac\nArtery\nAnalysis)","The Coronary Artery Analysis provides\nviewing and measuring tools that allow you\nto perform dimensional and quantitative\nmeasurements of the coronary arteries to\nhelp you identify and examine the patient\nstudy for stenosis.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["CFA\n(Cardiac\nFunction\nAnalysis)","Cardiac Function Analysis (CFA) application\nis used to assess the state of the left\nventricle (LV) and to analyze functional\nheart data.","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."],["Dual Energy","Dual energy Viewer is an application for\nreview and analysis of CT dual-energy\nscans. Users need to load CT dual-\nenergy scan data which is two series\nwith similar KV. It provides registration\nfunction and can generate different","Yes","Identical.\nTherefore,\nsubstantially\nequivalent."]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232491-p19-t0","doc_id":"K232491","page_num":19,"bbox":[90.61,91.33,536.53,233.9],"n_rows":2,"n_cols":5,"columns":["","weighted KV images. Users can use the\ntools to separate materials.","","",""],"rows":[["","weighted KV images. Users can use the\ntools to separate materials.","","",""],["Substantial\nEquivalence\nConclusion:","","The CT 5300 system design, intended use, technology and principal\ntechnological components (Tube, Generator, Detector) of the proposed\ndevice are substantially equivalent to the currently marketed predicate\ndevice Philips Incisive CT (K212441 - April 27, 2021). Based on the\ninformation provided above, the proposed device with modifications does\nnot raise new questions of safety and effectiveness compared to the\ncurrently marketed predicate device Philips Incisive CT (K212441 - April\n27, 2022).","",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p8-t0","doc_id":"K232494","page_num":8,"bbox":[72.71,434.83,503.65,606.22],"n_rows":8,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Sola with syngo\nMR XA51A","K221733 on September 13,\n2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Vida with syngo\nMR XA50A","K213693 on February 25, 2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Avantofit with\nsyngo MR VE11E","K162102 on November 22,\n2016","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Skyrafit with\nsyngo MR VE11E","K162102 on November 22,\n2016","LNH,\nLNI, MOS","Siemens Healthcare GmbH"]],"caption_candidate":"equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p9-t0","doc_id":"K232494","page_num":9,"bbox":[72.32,152.83,504.37,612.78],"n_rows":33,"n_cols":4,"columns":["","Subject Devices","Predicate Device","Reference Devices"],"rows":[["","Subject Devices","Predicate Device","Reference Devices"],["","","",""],["","MAGNETOM Avantofit","MAGNETOM Vida with","MAGNETOM Avantofit"],["","MAGNETOM Skyrafit","syngo MR XA50A","MAGNETOM Skyrafit with"],["Hardware","","",""],["","with software syngo MR","(K213693)","syngo MR VE11E1"],["","","",""],["","","","(K162102)"],["","XA61A","MAGNETOM Sola with",""],["","","",""],["","","syngo MR XA51A",""],["","","(K221733)",""],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","Yes","Yes","Yes"],["Patient Table","Yes","Yes","Yes"],["Multi-Nuclear\nOption - Supported\nNuclei","Yes\nOnly for MAGNETOM Skyrafit","Yes\nOnly for MAGNETOM Vida","Yes\nOnly for MAGNETOM\nSkyrafit"],["Computer","Yes","Yes","Yes"],["","Modified compared to","",""],["","predicate device:","",""],["","- New MRAWP and MRWP","",""],["","- New MaRS hardware for","",""],["","MAGNETOM Skyrafit","",""],["Coils","Yes, new coils","Yes","Yes"],["","- Flex Loop Large (only for","",""],["","MAGNETOM Avantofit)","",""],["","- UltraFlex Large 18","",""],["","- UltraFlex Small 18","",""],["","- Contour 24/482","",""],["Other HW\ncomponents","","Yes","Yes"],["","Yes","",""],["","","",""]],"caption_candidate":"Summary hardware comparison table for the subject and predicate/reference device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p10-t0","doc_id":"K232494","page_num":10,"bbox":[72.47,71.35,505.0,479.95],"n_rows":30,"n_cols":3,"columns":["","","MAGNETOM Sola with"],"rows":[["","","MAGNETOM Sola with"],["","","syngo MR XA51A (K221733)"],["Sequences","",""],["SE-based pulse sequence types","Yes","Yes"],["","New or modified pulse sequences:","Yes"],["GRE-based/Steady-State pulse","- GRE_PC new pulse sequence",""],["sequence types","- BEAT_NAV pulse sequence re-",""],["","naming",""],["","New features:","Yes"],["EPI-based pulse sequence types","- Physiologging for EPI2D_BOLD",""],["","and EPI2D_PACE",""],["Spectroscopy pulse sequence types","Yes","Yes"],["Feature and Applications","",""],["Other features and","Modified application feature:","Yes"],["applications such as:","- myExam Angio Assist (Test Bolus",""],["-Application Suites","and Care bolus) for MAGNETOM",""],["-myExam Assists","Skyrafit",""],["-Other Imaging Applications","",""],["User interface and user interaction","Yes","Yes"],["Viewing and post-processing","Yes","Yes"],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["Scanning","Yes","Yes"],["","New feature:","Yes"],["Reconstruction","",""],["","- OpenRecon Framework",""],["","",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p10-t1","doc_id":"K232494","page_num":10,"bbox":[72.47,591.22,466.85,775.44],"n_rows":7,"n_cols":3,"columns":["","Tested Hardware or",""],"rows":[["","Tested Hardware or",""],["Performance Test","","Source/Rationale for test"],["","Software",""],["","",""],["Software verification\nand validation","New or modified software\nfeatures","Guidance for the Content of Premarket\nSubmissions for Software Contained in\nMedical Devices"],["Sample clinical images","New or modified software\nfeatures and coils","Guidance for submission of Premarket\nNotifications for Magnetic Resonance\nDiagnostic Devices"],["Image quality\nassessment by sample\nclinical images","- new / modified pulse\nsequence types.\n- comparison images\nbetween the new / modified\nfeatures and the predicate\ndevice features",""]],"caption_candidate":"The following performance testing was conducted on the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p11-t0","doc_id":"K232494","page_num":11,"bbox":[72.64,160.7,503.58,240.98],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for coils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance Diagnostic\nDevices"]],"caption_candidate":"reference devices and can be reused for the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232494-p11-t1","doc_id":"K232494","page_num":11,"bbox":[72.64,417.67,508.78,460.75],"n_rows":2,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["GRE_PC","[1] Guenthner C. et al. Ristretto MRE: A generalized multi-\nshot GRE-MRE sequence. NMR Biomed 2019; 32:e4049."]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p7-t0","doc_id":"K232496","page_num":7,"bbox":[42.6,717.0,552.84,750.73],"n_rows":2,"n_cols":7,"columns":["Characteristic/Parameter","","Brainomix 360 Triage Stroke","","","iSchemaView Rapid NCCT Stroke",""],"rows":[["Characteristic/Parameter","","Brainomix 360 Triage Stroke","","","iSchemaView Rapid NCCT Stroke",""],["","","Subject Device (K232496)","","","Predicate Device (K222884)",""]],"caption_candidate":"with the Rapid NCCT Stroke device (K222884).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p10-t0","doc_id":"K232496","page_num":10,"bbox":[42.6,759.12,503.28,790.62],"n_rows":2,"n_cols":12,"columns":["","Metrics","","","21 < Age < 50","","","50 ≤ Age < 70","","","Age ≥ 70",""],"rows":[["","Metrics","","","21 < Age < 50","","","50 ≤ Age < 70","","","Age ≥ 70",""],["","Total Positives","","","13","","","39","","","60",""]],"caption_candidate":"subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p11-t0","doc_id":"K232496","page_num":11,"bbox":[42.6,120.66,503.67,150.42],"n_rows":2,"n_cols":8,"columns":["","Sensitivity","84.62% (58.59-97.46)","","74.36% (59.09-86.41)","","61.67% (48.93-73.39)",""],"rows":[["","Sensitivity","84.62% (58.59-97.46)","","74.36% (59.09-86.41)","","61.67% (48.93-73.39)",""],["","Specificity","94.74% (77.09-99.67)","","89.09% (78.7-95.74)","","87.8% (75.07-95.75)",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p11-t1","doc_id":"K232496","page_num":11,"bbox":[42.6,172.92,503.67,234.4],"n_rows":4,"n_cols":7,"columns":["","Metrics","Female","","","Male",""],"rows":[["","Metrics","Female","","","Male",""],["","Total Positives","48","","","64",""],["","Sensitivity","75.0% (61.4-85.89)","","","64.06% (51.78-75.19)",""],["","Specificity","88.14% (77.94-94.92)","","","91.07% (81.32-96.95)",""]],"caption_candidate":"Specificity 94.74% (77.09-99.67) 89.09% (78.7-95.74) 87.8% (75.07-95.75)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p11-t2","doc_id":"K232496","page_num":11,"bbox":[42.6,256.92,503.67,332.34],"n_rows":5,"n_cols":9,"columns":["Metrics","Metrics","","Slice Thickness","","1 mm ≤ Slice Thickness\n< 3 mm","","Slice Thickness\n≥ 3 mm",""],"rows":[["Metrics","Metrics","","Slice Thickness","","1 mm ≤ Slice Thickness\n< 3 mm","","Slice Thickness\n≥ 3 mm",""],["","","","< 1 mm","","","","",""],["","Total Positives","","44","","25","","42",""],["","Sensitivity","","61.36% (46.46-74.93)","","76.0% (56.8-90.0)","","71.43% (56.52-83.7)",""],["","Specificity","","87.76% (76.29-95.19)","","96.67% (84.74-99.79)","","86.11% (71.95-95.11)",""]],"caption_candidate":"Specificity 88.14% (77.94-94.92) 91.07% (81.32-96.95)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232496-p11-t3","doc_id":"K232496","page_num":11,"bbox":[42.6,354.96,503.67,433.42],"n_rows":4,"n_cols":8,"columns":["Metrics","","SIEMENS","","GE MEDICAL SYSTEMS","Philips","",""],"rows":[["Metrics","","SIEMENS","","GE MEDICAL SYSTEMS","Philips","",""],["","Total Positives","48","","33","","27",""],["","Sensitivity","62.5% (48.25-75.4)","","69.7% (52.68-83.68)","","77.78% (59.56-90.82)",""],["","Specificity","88.24% (77.15-95.39)","","83.87% (67.93-94.24)","","96.97% (86.02-99.81)",""]],"caption_candidate":"Specificity 87.76% (76.29-95.19) 96.67% (84.74-99.79) 86.11% (71.95-95.11)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p4-t0","doc_id":"K232500","page_num":4,"bbox":[226.17,453.6,519.93,573.9],"n_rows":7,"n_cols":5,"columns":["Classification Name","","21 CFR §","Product Code",""],"rows":[["Classification Name","","21 CFR §","Product Code",""],["","Primary","","",""],["Ultrasonic pulsed doppler imaging\nsystem","","892.1550","IYN",""],["","Secondary","","",""],["Ultrasonic pulsed echo imaging\nsystem","","892.1560","IYO",""],["Diagnostic ultrasonic transducer","","892.1570","ITX",""],["Medical image management and\nprocessing system","","892.2050","QIH",""]],"caption_candidate":"Common Name: Diagnostic ultrasound system and transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p5-t0","doc_id":"K232500","page_num":5,"bbox":[70.5,138.42,541.5,530.52],"n_rows":31,"n_cols":2,"columns":["","There is no change to the intended use and indications for use of the subject device as compared to the"],"rows":[["","There is no change to the intended use and indications for use of the subject device as compared to the"],["","currently commercialized version of Lumify Diagnostic Ultrasound System, except lung indication"],["","was added through K203406 for Lumify Diagnostic Ultrasound System with B-line Detection and B-"],["","line Counting, and Pulsed Wave Doppler was added during Lumify 4.0 (Android) release through a"],["","Letter to File."],["",""],["","3.1 Indications for Use"],["",""],["","The Philips Lumify Diagnostic Ultrasound System is intended for diagnostic ultrasound imaging in"],["","B(2D), Color Doppler, Combined (B+Color), Pulsed Wave Doppler, and M-modes."],["",""],["","It is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications:"],["",""],["","Fetal/Obstetric, Abdominal, Pediatric, Cephalic, Urology, Gynecological, Cardiac Fetal Echo, Small"],["","Organ, Musculoskeletal, Peripheral Vessel, Carotid, Cardiac, Lung."],["",""],["","The Lumify system is a transportable ultrasound system intended for use in environments where"],["","healthcare is provided by healthcare professionals."],["",""],["","3.2 Intended Use"],["",""],["","The intended use of the product is to collect ultrasound image data that may be used by clinicians for"],["","diagnostic and procedural purposes. The product shall provide the ability for gathering clinically"],["","acceptable images and ultrasound data for the clinical presets and anatomies listed under the"],["","indications for use."],["",""],["","This product is intended to be installed, used, and operated only in accordance with safety procedures"],["","and operating instructions given in the product user information, and only for the purposes for which"],["","it was designed. However, nothing stated in the user information reduces the user’s responsibility for"],["","sound clinical judgement and best clinical procedure."],["",""]],"caption_candidate":"3. Indications for Use and Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p7-t0","doc_id":"K232500","page_num":7,"bbox":[72.25,258.54,539.75,724.8],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],"rows":[["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],["","","Diagnostic","","","Diagnostic","","",""],["","","Ultrasound","","","Ultrasound","","",""],["","","System K#","","","System K162549","","",""],["","","Pending","","","(Predicate","","",""],["","","(Subject Device)","","","Device)","","",""],["Regulation Number","892.1550","","","892.1550","","","892.2050","Remains unchanged\nfrom predicate\nLumify Ultrasound\nSystem"],["Device Classification\nName","System, Imaging,\nPulsed Doppler,\nUltrasonic","","","System, Imaging,\nPulsed Doppler,\nUltrasonic","","","Automated\nRadiological\nImaging Processing\nSoftware","Remains unchanged"],["Device Classification","II","","","II","","","II","Remains unchanged"],["Primary Product\nCode","IYN","","","IYN","","","QIH","Remains unchanged\nfrom predicate\nLumify Ultrasound\nSystem\nQIH is a secondary\nproduct for subject\ndevice"],["Feature Trade Name","Auto EF\nQuantification","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","LVivo EF","LVivo software\napplication has been\nincorporated in\nLumify Ultrasound\nSystem as Auto EF\nQuantification"],["Scientific Technology","Ultrasound\nImaging","","","Ultrasound\nImaging","","","Relies on\nUltrasound imaging\nto perform the\nassessment","Remains unchanged\nfor the predicate and\nsimilar for the\nreference"],["Principles of\nOperation (subject\nAuto EF\nQuantification\nFeature)","Lumify Auto EF\nQuantification is\na software only\nfeature. The core\nsystem software\narchitecture\nremains\nunchanged. This","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","The LVivo platform\nis a software system\nfor automated\nanalysis of\nultrasound\nexaminations.","With Auto EF\nQuantification feature\nthe user is offered an\nautomated\nmeasurement of\nEjection Fraction\n(EF), End Diastolic\nVolume (EDV), and"]],"caption_candidate":"predicate and reference devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p8-t0","doc_id":"K232500","page_num":8,"bbox":[72.27,91.8,539.73,716.58],"n_rows":8,"n_cols":9,"columns":["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],"rows":[["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],["","","Diagnostic","","","Diagnostic","","",""],["","","Ultrasound","","","Ultrasound","","",""],["","","System K#","","","System K162549","","",""],["","","Pending","","","(Predicate","","",""],["","","(Subject Device)","","","Device)","","",""],["","additional feature\nis added in the\nCardiac preset of\nthe Lumify\nsystem to assess\nleft ventricular\nfunction using a 4\nChamber Apical\nview of the heart.\nThis feature\nprovides\nautomated tracing\nof the Left\nVentricular (LV)\nborder and\nquantification of\nEnd Systolic\nVolume (ESV)\nand End Diastolic\nVolumes (EDV)\nas well as the\nEjection Fraction\n(EF) for LV\nassessment.","","","","","","","End Systolic Volume\n(ESV). The Lumify\nfeatures are a subset\nof the LVivo platform"],["Artificial\nIntelligence/Machine\nLearning","Auto EF\nQuantification, is\na derivative of the\npreviously\ncleared LVivoEF\nmodule\n(K210053) that\nenables\nautomated\nevaluation of end\ndiastolic volume\n(EDV), end\nsystolic volume\n(ESV) and\nEjection Fraction\n(EF) from the\nFour Chamber\n(4CH) apical\nview.","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Automated analysis\nof\nechocardiographic\nexaminations is\ndone based on\nultrasound imaging\ndata by analyzing\nalready acquired\nclip (cine\nloop). The imaging\ndata can be\nprovided in DICOM\nformat that includes\nrequired metadata\nor RGB format\ntogether with\nmetadata that is\nprovided through\nsoftware API. The\nglobal LV function\nis evaluated from\ntwo of the apical\nviews: four-\nchamber (4CH) and","The subject device\nwith the automation\nof the Auto EF\nQuantification\nfeature, the user is\nnow offered\nmeasurements\nincluding Ejection\nFraction (EF), End\nDiastolic Volume\n(EDV) and End\nSystolic Volume\n(ESV).\nThe AL/ML\nfunctionality is same\nin the subject device\nin comparison to the\nreference device."]],"caption_candidate":"Lumify Diagnostic Ultrasound System with Auto EF Quantification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p9-t0","doc_id":"K232500","page_num":9,"bbox":[72.25,91.8,539.75,700.14],"n_rows":13,"n_cols":9,"columns":["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],"rows":[["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],["","","Diagnostic","","","Diagnostic","","",""],["","","Ultrasound","","","Ultrasound","","",""],["","","System K#","","","System K162549","","",""],["","","Pending","","","(Predicate","","",""],["","","(Subject Device)","","","Device)","","",""],["","","","","","","","two-chamber (2CH)\nby calculating\nejection fraction\n(EF). The LVivo EF\nsupports global LV\nfunction evaluation\nfrom single view or\nBiplane”",""],["Automation","Yes","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Yes","Same as the reference\ndevice (DiA LVivo)"],["Manual editing by\nuser capability","Yes","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Yes","Same as the reference\ndevice (DiA LVivo)"],["Automated ED and\nES frames selection","Yes","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Yes","Same as the reference\ndevice (DiA LVivo)"],["Volume calculation\nby Simson’s method\nof discs","Yes","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Yes","Same as the reference\ndevice (DiA LVivo)"],["EF results\npresentation","Displaying full\nclip with border\ntracking. The\nresults for\nselected ED and\nES frames for\ndefault beat is\ndisplayed.","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Displaying full clip\nwith border\ntracking. And table\nwith results for each\ncycle for selected\nED & ES frames for\neach beat.","Auto EF for Lumify\ndoes not have the\ntable with results for\neach cycle. Only\nresults for ED & ES\nframes for default\nbeat is displayed."],["Algorithm","Image\nsegmentation for\nborder detection\nand tracking\nincludes\nprocessing by\nneural network","","","Not Applicable\nThis feature was\nnot available with\nthis version\n.","","","Image segmentation\nfor border detection\nand tracking\nincludes processing\nby neural network","Same as reference\ndevice"]],"caption_candidate":"Lumify Diagnostic Ultrasound System with Auto EF Quantification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p10-t0","doc_id":"K232500","page_num":10,"bbox":[72.27,91.8,539.73,317.76],"n_rows":8,"n_cols":9,"columns":["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],"rows":[["Standard Feature","","Lumify","","","Lumify","","DiA LVivo\nSoftware\nApplication\nK210053\n(Reference Device)","Comparison/\nDiscussion"],["","","Diagnostic","","","Diagnostic","","",""],["","","Ultrasound","","","Ultrasound","","",""],["","","System K#","","","System K162549","","",""],["","","Pending","","","(Predicate","","",""],["","","(Subject Device)","","","Device)","","",""],["Automated rejection\nof false results","Yes","","","Not Applicable\nThis feature was\nnot available with\nthis version","","","Yes","Same as the reference\ndevice (DiA LVivo)"],["Transducers","L12-4\nS4-1\nC5-2\nAuto EF is only\navailable on S4-1\nTransducer\n(Cardiac Phased\nArray)","","","L12-4\nS4-1\nC5-2","","","Cardiac Phased\nArray","Auto EF\nQuantification feature\nis only available on\nS4-1 transducer"]],"caption_candidate":"Lumify Diagnostic Ultrasound System with Auto EF Quantification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232500-p12-t0","doc_id":"K232500","page_num":12,"bbox":[136.09,112.5,475.91,671.94],"n_rows":14,"n_cols":5,"columns":["Variables","Values","N","%","Mean"],"rows":[["Variables","Values","N","%","Mean"],["Gender","Female","23","29","--"],["","Male","57","71","--"],["Age","19 - 92 years","80","--","64 ± 14\nyears"],["BMI","15.9-43.0","74*","--","26.4"],["LV Function","Normal or\npreserved LV\nfunction","30","37.5","--"],["","Mild LV\ndysfunction","13","16.25","--"],["","Moderate LV\ndysfunction","20","25","--"],["","Severe LV\ndysfunction","17","21.25","--"],["Population disease distribution","Coronary\nartery disease\n(CAD)","34","42","--"],["","Left\nVentricular\nHypertrophy","9","11","--"],["","Thickened\nleaflet,\nCalcified or\nprosthetic\nmitral valve","19","24","--"],["","Moderate to\nSevere Mitral\nregurgitation","7","9","--"],["","Normal LV\nFunction","11","14","--"]],"caption_candidate":"The demographic distribution of the study population includes the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p4-t0","doc_id":"K232501","page_num":4,"bbox":[90.0,148.31,456.97,712.95],"n_rows":56,"n_cols":2,"columns":["GeneralInformation",""],"rows":[["GeneralInformation",""],["",""],["510(k)Sponsor","ExoImaging"],["",""],["Address","4201BurtonDrive"],["","SantaClara,CA95054"],["",""],["CorrespondencePerson","JacquelineMurray"],["",""],["ContactInformation","jmurray@exo.inc"],["",""],["","Cell:+1236838-5056"],["",""],["DatePrepared","September21st,2023"],["",""],["ProposedDevice",""],["",""],["ProprietaryName","AIPlatform(AIP001)"],["",""],["CommonName","AIPlatform"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["PredicateDevice",""],["",""],["ProprietaryName","LVivoSoftwareApplication"],["",""],["PremarketNotification","K210053"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["ReferenceDevice",""],["",""],["ProprietaryName","LumifyDiagnosticUltrasoundSystem"],["",""],["PremarketNotification","K223771"],["",""],["ClassificationName","Ultrasonicpulseddopplerimagingsystem"],["",""],["RegulationNumber","21CFR892.1550"],["",""],["ProductCode","IYN,IYO,ITX,QIH"],["",""],["RegulatoryClass","II"]],"caption_candidate":"GeneralInformation","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232501-p4-t1","doc_id":"K232501","page_num":4,"bbox":[85.5,319.6,534.5,427.6],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","AIPlatform(AIP001)"],"rows":[["ProprietaryName","AIPlatform(AIP001)"],["CommonName","AIPlatform"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ProposedDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p4-t2","doc_id":"K232501","page_num":4,"bbox":[85.5,464.85,534.5,572.57],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","LVivoSoftwareApplication"],"rows":[["ProprietaryName","LVivoSoftwareApplication"],["PremarketNotification","K210053"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"PredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p4-t3","doc_id":"K232501","page_num":4,"bbox":[85.5,609.55,534.5,717.55],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","LumifyDiagnosticUltrasoundSystem"],"rows":[["ProprietaryName","LumifyDiagnosticUltrasoundSystem"],["PremarketNotification","K223771"],["ClassificationName","Ultrasonicpulseddopplerimagingsystem"],["RegulationNumber","21CFR892.1550"],["ProductCode","IYN,IYO,ITX,QIH"],["RegulatoryClass","II"]],"caption_candidate":"ReferenceDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p5-t0","doc_id":"K232501","page_num":5,"bbox":[63.0,132.6,539.49,203.18],"n_rows":5,"n_cols":2,"columns":["Exo AI Platform is a software as a medical device (SaMD) that helps qualified users with",""],"rows":[["Exo AI Platform is a software as a medical device (SaMD) that helps qualified users with",""],["","image-based assessment of ultrasound examinations in adult patients. It is designed to simplify"],["","workflow by helping trained healthcare providers evaluate, quantify, and generate reports for"],["","ultrasound images.Thedeviceisintendedtogenerateimagesandareportthatcanbereviewedin"],["","atypicalstandardofcaresetting."]],"caption_candidate":"DeviceDescription","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p5-t1","doc_id":"K232501","page_num":5,"bbox":[63.0,219.56,539.49,290.13],"n_rows":5,"n_cols":2,"columns":["AI Platform takes as an input imported Digital Imaging andCommunicationsinMedicine(DICOM)",""],"rows":[["AI Platform takes as an input imported Digital Imaging andCommunicationsinMedicine(DICOM)",""],["","images from ultrasound scanners of a specific range and allows users to detect, measure, and"],["","calculate relevant medical parameters of structures and function of patients with suspected"],["","disease. It provides users with a specific toolset for viewing ultrasound images of the lung and"],["","heart,placinglandmarks,andcreatingreports."]],"caption_candidate":"atypicalstandardofcaresetting.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p5-t2","doc_id":"K232501","page_num":5,"bbox":[72.1,580.42,539.49,712.5],"n_rows":3,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nExoAIPlatform","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nLumifyDiagnostic\nUltrasoundSystem\n(K223771)"],"rows":[["Feature/\nFunction","SubjectDevice\nExoAIPlatform","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nLumifyDiagnostic\nUltrasoundSystem\n(K223771)"],["Imageinput","ComplieswithDICOM\nStandard","Sameassubjectdevice","Sameassubjectdevice"],["Scantype","SingleandMulti-frame\nultrasoundimages","Sameassubjectdevice","Sameassubjectdevice"]],"caption_candidate":"ComparisonofTechnologicalCharacteristicswiththePredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p6-t0","doc_id":"K232501","page_num":6,"bbox":[72.33,93.59,539.42,702.5],"n_rows":11,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nExoAIPlatform","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nLumifyDiagnostic\nUltrasoundSystem\n(K223771)"],"rows":[["Feature/\nFunction","SubjectDevice\nExoAIPlatform","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nLumifyDiagnostic\nUltrasoundSystem\n(K223771)"],["Imagedisplay\nmode","Static","Sameassubjectdevice","Sameassubjectdevice"],["Imagenavigation\nandmanipulation\ntools","Slice-scroll,panelayout,\nreset","Sameassubjectdevice","Sameassubjectdevice"],["Imagereview","Yes,capableofreviewing\nallframesofmulti-frame\n(multi-slice)images","Sameassubjectdevice","Sameassubjectdevice"],["Principleof\nOperationand\nTechnology","Ultrasoundimage\nprocessingsoftware\nimplementingartificial\nintelligenceincluding\nnon-adaptivemachine\nlearningalgorithmstrained\nwithclinicaldataintended\nfornon-invasiveanalysisof\nultrasounddata","Sameassubjectdevice","Sameassubjectdevice"],["AIAlgorithm","DeepConvolutionalNeural\nNetworksfor\nSegmentationor\nLandmarkDetection","SameasSubject\nDevice","Sameassubjectdevice"],["Manual\nAdjustmentsor\nEditingbyUser\nAllowed","Yes","SameasSubject\nDevice","SameasSubjectDevice"],["AnatomicalSites","Heart,Lungs","Heart,Bladder","Lungs"],["EjectionFraction\nMeasurement\nViews","AP4,AP2,Bi-plane,PLAX","AP4,AP2,Bi-plane","No"],["NonCardiac\nfunctions","A-lines,B-lines","BladderVolume","B-lines"],["Reportcreation","Yes","Sameassubjectdevice","Sameassubjectdevice"]],"caption_candidate":"510(k)Summary-AIPlatform","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p8-t0","doc_id":"K232501","page_num":8,"bbox":[123.67,116.29,488.33,287.29],"n_rows":6,"n_cols":3,"columns":["Subgroup(View)","ICC(95%CI)","RMSD(95%CI)"],"rows":[["Subgroup(View)","ICC(95%CI)","RMSD(95%CI)"],["EjectionFractionParasternal\nLong-axis","0.93(0.89–0.96)","6.12(5.30–8.36)"],["EjectionFractionApicalBiplane","0.95(0.90–0.98)","4.81(3.99–7.25)"],["EjectionFractionApical(AP4)\nSinglePlane","0.92(0.88–0.95)","6.06(5.27–8.20)"],["EjectionFractionApical(AP2)\nSinglePlane","0.92(0.87–0.95)","6.25(5.33–8.82)"],["All","0.93(0.91–0.95)","5.90(5.35–7.23)"]],"caption_candidate":"Table1:SummaryofAIPlatformaccuracyandreliabilityforcardiacultrasoundimages","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232501-p8-t1","doc_id":"K232501","page_num":8,"bbox":[155.5,436.5,455.27,489.5],"n_rows":3,"n_cols":2,"columns":["","Reliability"],"rows":[["","Reliability"],["A-lines","Kappa=0.84"],["B-lines","ICC=0.97"]],"caption_candidate":"Table2:SummaryofAIPlatformreliabilityforlungultrasoundimages","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232526-p5-t0","doc_id":"K232526","page_num":5,"bbox":[87.87,390.37,420.91,540.91],"n_rows":12,"n_cols":2,"columns":["","XIDF-AWS801, Angio Workstation (Alphenix\nWorkstation), V9.3"],"rows":[["","XIDF-AWS801, Angio Workstation (Alphenix\nWorkstation), V9.3"],["Trade Proprietary Name",""],["",""],["Marketed by","Canon Medical Systems USA, Inc."],["510(k) Number","K220342"],["Clearance Date","September 27, 2022"],["","Image-intensified\nfluoroscopic x-ray system"],["Classification Name",""],["",""],["Product Code","OWB, JAA"],["Regulation Number","21 CFR 892.1650"],["Regulatory Class","Class II"]],"caption_candidate":"TABLE 1: Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p6-t0","doc_id":"K232535","page_num":6,"bbox":[72.7,413.83,503.74,528.07],"n_rows":6,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Sola with syngo\nMR XA51A","K221733 on September 13,\n2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Altea with syngo\nMR XA51A","K221733 on September 13,\n2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"]],"caption_candidate":"equivalent to the following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p7-t0","doc_id":"K232535","page_num":7,"bbox":[72.37,71.38,504.54,459.12],"n_rows":23,"n_cols":4,"columns":["","MAGNETOM Sola","MAGNETOM Sola with","MAGNETOM Altea with"],"rows":[["","MAGNETOM Sola","MAGNETOM Sola with","MAGNETOM Altea with"],["","MAGNETOM Altea","syngo MR XA51A","syngo MR XA51A"],["","with software syngo MR","(K221733)","(K221733)"],["","XA61A","",""],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","Yes","Yes","Yes"],["Patient Table","Yes","Yes","Yes"],["Multi-Nuclear\nOption - Supported\nNuclei","No","No","No"],["Computer","Yes","Yes","Yes"],["","Modified compared to","",""],["","predicate device:","",""],["","- New MRAWP and","",""],["","MRWP","",""],["","- New MaRS hardware","",""],["","for MAGNETOM Sola","",""],["Coils","Yes","Yes","Yes"],["Other HW\ncomponents","Yes","Yes","Yes"],["","Modified compared to","",""],["","predicate device:","",""],["","- myExam 3D Camera","",""],["","functionality extension","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p7-t1","doc_id":"K232535","page_num":7,"bbox":[72.37,492.41,504.54,782.28],"n_rows":22,"n_cols":3,"columns":["","Subject Devices","Predicate Device"],"rows":[["","Subject Devices","Predicate Device"],["","",""],["Software","MAGNETOM Sola","MAGNETOM Sola with syngo"],["","MAGNETOM Altea","MR XA51A"],["","with software syngo MR XA61A","(K221733)"],["Sequences","",""],["","New feature","Yes"],["SE-based pulse sequence types","- Deep Resolve Boost for",""],["","HASTE",""],["","New or modified pulse","Yes"],["","sequences:",""],["GRE-based/Steady-State pulse","",""],["","- BEAT_NAV pulse sequence",""],["sequence types","",""],["","re-naming",""],["","",""],["","- GRE_PC new pulse sequence",""],["","New features","Yes"],["","- Physiologging for EP2D_BOLD",""],["EPI-based pulse sequence types","and EP2D_PACE",""],["","- Deep Resolve Boost for",""],["","EP2D_DIFF",""]],"caption_candidate":"Summary software comparison table for the subject and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p8-t0","doc_id":"K232535","page_num":8,"bbox":[72.49,71.32,505.03,420.79],"n_rows":28,"n_cols":3,"columns":["","- Complex Averaging for",""],"rows":[["","- Complex Averaging for",""],["","EP2D_DIFF",""],["Spectroscopy pulse sequence","","Yes"],["","Yes",""],["types","",""],["","",""],["Feature and Applications","",""],["Other features and","","Yes"],["applications such as:","",""],["-Application Suites","New feature:",""],["-myExam Assists","- myExam Implant Suite",""],["-Other Imaging","",""],["Applications","",""],["User interface and user","","Yes"],["","Yes",""],["interaction","",""],["","",""],["Viewing and post-processing","Yes","Yes"],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["Scanning","Yes","Yes"],["","Modified feature:","Yes"],["Reconstruction","",""],["","- OpenRecon Framework",""],["","",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p9-t0","doc_id":"K232535","page_num":9,"bbox":[72.5,144.38,550.78,703.06],"n_rows":7,"n_cols":3,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:"],["Training and\nValidation data","• TSE: more than 25,000 slices\n• HASTE: pre-trained on the TSE dataset\nand refined with more than 10,000\nHASTE slices\n• EPI Diffusion: more than 1,000,000\nslices\nThe data covered a broad range of body\nparts, contrasts, fat suppression techniques,\norientations, and field strength.","on more than 10,000 high resolution 2D\nimages.\nThe data covered a broad range of body\nparts, contrasts, fat suppression techniques,\norientations, and field strength."],["Test Statistics and\nTest Results\nSummary","The impact of the network has been\ncharacterized by several quality metrics\nsuch as peak signal-to-noise ratio (PSNR)\nand structural similarity index (SSIM). Most\nimportantly, the performance was\nevaluated by visual comparisons to\nevaluate e.g., aliasing artifacts, image\nsharpness and denoising levels.","The impact of the network has been\ncharacterized by several quality metrics\nsuch as peak signal-to-noise ratio (PSNR),\nstructural similarity index (SSIM), and\nperceptual loss. In addition, the feature has\nbeen verified and validated by inhouse\ntests. These tests include visual rating and\nan evaluation of image sharpness by\nintensity profile comparisons of\nreconstructions with and without Deep\nResolve Sharp."],["Equipment","1.5T and 3T MRI systems",""],["Clinical Subgroups","No clinical subgroups have been defined for the collected dataset.",""],["Demographic\nDistribution","Due to reasons of data privacy, we did not record gender, age and ethnicity during data\ncollection.",""],["Reference Standard","The acquired datasets (as described above)\nrepresent the ground truth for the training\nand validation. Input data was\nretrospectively created from the ground\ntruth by data manipulation and\naugmentation.\nThis process includes further under-\nsampling of the data by discarding k-space\nlines, lowering of the SNR level by addition\nRestricted of noise and mirroring of k-space\ndata.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation. k-space data has\nbeen cropped such that only the\ncenter part of the data was used\nas input. With this method\ncorresponding low-resolution\ndata as input and high-resolution\ndata as output / ground truth\nwere created for training and\nvalidation."]],"caption_candidate":"features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p10-t0","doc_id":"K232535","page_num":10,"bbox":[72.5,159.02,508.78,764.28],"n_rows":3,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["Deep Resolve Boost EPI Diffusion","[1] Bae SH et al., Clinical feasibility of accelerated diffusion\nweighted imaging of the abdomen with deep learning\nreconstruction: Comparison with conventional diffusion\nweighted imaging, Eur J Radiol., 154 (2022)\n[2] Lee EJ et al., Feasibility of deep learning k-space-to-image\nreconstruction for diffusion weighted imaging in patients\nwith breast cancers: Focus on image quality and reduced scan\ntime, Eur J Radiol., 157 (2022)\n[3] Afat S et al., Acquisition time reduction of diffusion-\nweighted liver imaging using deep learning image\nreconstruction. Diagn Interv Imaging, (2022).\n[4] Benkert T et al., Improved Clinical Diffusion Weighted\nImaging by Combining Deep Learning Reconstruction, Partial\nFourier, and Super Resolution, ISMRM (2022)\n[5] Kim et al., Deep Learning–Accelerated Liver Diffusion-\nWeighted Imaging - Intraindividual Comparison and\nAdditional Phantom Study of Free-Breathing and Respiratory-\nTriggering Acquisitions, Invest Radiol (2023)"],["Deep Resolve Boost HASTE","[1] Herrmann J et al., Diagnostic Confidence and\nFeasibility of a Deep Learning Accelerated HASTE Sequence of\nthe Abdomen in a Single Breath-Hold, Investigative\nRadiology, Volume 56, Number 5, May 2021.\n[2] Shanbhogue K et al. Accelerated single-shot T2-\nweighted fat-suppressed (FS) MRI of the liver with deep\nlearning-based image reconstruction: qualitative and\nquantitative comparison of image quality with conventional\nT2-weighted FS sequence. Eur Radiol. 2021 May 7.\n[3] Herrmann J et al., Development and Evaluation of\nDeep Learning-Accelerated Single-Breath-Hold Abdominal\nHASTE at 3 T Using Variable Refocusing Flip Angles. Invest\nRadiol. 2021 Apr 22.\n[4] Han S et al., Evaluation of HASTE T2 weighted image\nwith reduced echo time for detecting focal liver lesions in\npatients at risk of developing hepatocellular carcinoma. Eur J\nRadiol. 2022 Nov 1;157:110588.\n[5] Mule S et al., Fast T2-weighted liver MRI: Image\nquality and solid focal lesions conspicuity using a deep\nlearning accelerated single breath-hold HASTE fat-\nsuppressed sequence. Diagn Interv Imaging. 2022\nOct;103(10):479-485.\n[6] Ginocchio LA et al., Accelerated T2-weighted MRI of\nthe liver at 3 T using a single-shot technique with deep"]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p11-t0","doc_id":"K232535","page_num":11,"bbox":[72.5,71.04,508.78,339.41],"n_rows":3,"n_cols":2,"columns":["","learning-based image reconstruction: impact on the image\nquality and lesion detection. Abdom Radiol (NY). 2022 Sep 28.\n[7] Herrmann J et al., Comprehensive clinical evaluation\nof a deep learning-accelerated, single-breath-hold abdominal\nHASTE at 1.5 T and 3 T. Acad Radiol. 2022 Apr 22:S1076-\n6332(22)00195-7.\n[8] Ichinohe F. et al., Usefulness of Breath-Hold Fat-\nSuppressed T2-Weighted Images With Deep Learning–Based\nReconstruction of the Liver, Invest Radiol., 2022"],"rows":[["","learning-based image reconstruction: impact on the image\nquality and lesion detection. Abdom Radiol (NY). 2022 Sep 28.\n[7] Herrmann J et al., Comprehensive clinical evaluation\nof a deep learning-accelerated, single-breath-hold abdominal\nHASTE at 1.5 T and 3 T. Acad Radiol. 2022 Apr 22:S1076-\n6332(22)00195-7.\n[8] Ichinohe F. et al., Usefulness of Breath-Hold Fat-\nSuppressed T2-Weighted Images With Deep Learning–Based\nReconstruction of the Liver, Invest Radiol., 2022"],["GRE_PC","[1] Guenthner C. et al. Ristretto MRE: A generalized multi-\nshot GRE-MRE sequence. NMR Biomed 2019; 32:e4049."],["Complex Averaging","[1] Walsh DO, Gmitro AF, Marcellin MW. Adaptive\nreconstruction of phased array MR imagery. Magn Reson\nMed. 2000 May 1;43(5):682–90.\n[2] Kordbacheh H, Seethamraju RT, Weiland E, Kiefer B, Nickel\nMD, Chulroek T, et al. Image quality and diagnostic accuracy\nof complex-averaged high b value images in diffusion-\nweighted MRI of prostate cancer. Abdom Radiol (NY).\n2019;44(6):2244–53"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232535-p12-t0","doc_id":"K232535","page_num":12,"bbox":[77.66,71.04,499.54,432.43],"n_rows":7,"n_cols":5,"columns":["12-295","Radiology","Medical electrical equipment - Part 2-\n33: Particular requirements for the\nbasic safety and essential performance\nof magnetic resonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],"rows":[["12-295","Radiology","Medical electrical equipment - Part 2-\n33: Particular requirements for the\nbasic safety and essential performance\nof magnetic resonance equipment for\nmedical diagnosis","60601-2-33 Ed. 3.2\nb:2015","IEC"],["5-125","General","Medical devices - Application of risk\nmanagement to medical devices","14971 Third Edition\n2019-12","ISO"],["5-114","General I\n(QS/\nRM)","Medical devices - Part 1: Application of\nusability engineering to medical devices","62366-1:2015","ANSI AAMI IEC"],["13-79","Software/\nInformatics","Medical device software - Software life\ncycle processes","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"],["12-195","Radiology","NEMA MS 6-2008 (R2014)\nDetermination of Signal-to-Noise Ratio\nand Image Uniformity for Single-\nChannel Non-Volume Coils in\nDiagnostic MR Imaging","MS 6-2008 (R2014)","NEMA"],["12-342","Radiology","Digital Imaging and Communications in\nMedicine (DICOM) Set","PS 3.1 - 3.20\n(2021e)","NEMA"],["2-258","Biocompati\nbility","Biological evaluation of medical devices\n- part 1: evaluation and testing within a\nrisk management process.\n(Biocompatibility)","10993-1 Fifth\nedition 2018-08","AAMI\nANSI\nISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p4-t0","doc_id":"K232613","page_num":4,"bbox":[72.26,163.3,456.2,415.62],"n_rows":9,"n_cols":2,"columns":["Submitter Name","Innolitics LLC"],"rows":[["Submitter Name","Innolitics LLC"],["Address","1101 West 34th St #550, Austin, TX 78705, US"],["Phone Number","+1 (512) 967-6088"],["Fax Number","N/A"],["Company Representative","Meritxell Martinez"],["Additional Company Representatives","Yujan Shrestha, MD\nEthan Ulrich\nAndrew Smith, MD, PhD\nSteven Rothenberg, MD\nJim Luker, RN, MS"],["Email","fda@innolitics.com"],["Date Summary Prepared","January 30th, 2024"],["Documentation Prepared Using","Innolitics Medtech OS Framework"]],"caption_candidate":"1.ADMINISTRATIVE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p4-t1","doc_id":"K232613","page_num":4,"bbox":[72.26,460.65,378.15,623.45],"n_rows":7,"n_cols":2,"columns":["Trade Name","CT Cardiomegaly"],"rows":[["Trade Name","CT Cardiomegaly"],["Subject Device K Number","K232613"],["Common Name","Automated Radiological Image Processing Software"],["Product Code","QIH"],["Regulation Number","892.2050"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"2.SUBJECT DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p5-t0","doc_id":"K232613","page_num":5,"bbox":[72.24,189.8,434.18,352.6],"n_rows":7,"n_cols":2,"columns":["Predicate Device Name","EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System"],"rows":[["Predicate Device Name","EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System"],["Predicate Device K Number","K212624"],["Common Name","EFAI iCTR"],["Product Code","QIH"],["Regulation Number","892.2050"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"3. PREDICATE DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p6-t0","doc_id":"K232613","page_num":6,"bbox":[72.19,629.45,539.98,718.98],"n_rows":2,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["Manufacturer","Innolitics LLC","Ever Fortune. AI Co.,\nLtd.","N/A"]],"caption_candidate":"6. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p7-t0","doc_id":"K232613","page_num":7,"bbox":[72.24,118.55,539.98,716.48],"n_rows":7,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["Regulation\nNumber","892.2050","892.2050","Same"],["Regulatory Class","Class II","Class II","Same"],["Product Code","QIH","QIH","Same"],["Regulation Name","Medical image processing\nand management system","Medical image processing\nand management system","Same"],["Device Property","SaMD","SaMD","Same"],["Intended Use/\nIndications for Use","CT Cardiomegaly is\nsoftware intended to be run\non its own or as part of\nanother medical device to\nautomatically calculate\nlinear and area based\ncardiothoracic ratio (CTR)\nfrom a CT image\ncontaining the heart.\nCT Cardiomegaly is\ndesigned to measure the\nmaximal transverse\ndiameter of heart and\nmaximal inner transverse\ndiameter of thoracic cavity\nand calculate the CTR from\nan axial CT slice\ncontaining the heart using a\nnon-adaptive machine\nlearning algorithm.\nIntended users of the\nsoftware are aimed to the\nphysicians or other\nlicensed practitioners in the\nhealthcare institutions,\nsuch as clinics, hospitals,\nhealthcare facilities,\nresidential care facilities\nand long-term care\nservices.\nThe system is suitable for\nadults and transitional\nadolescents (18 to 21 years\nold but treated as an adult).\nIts results are not intended\nto be used on a stand-alone\nbasis for clinical-decision","EFAI Intelligent\nCardiothoracic Ratio\nAssessment System (or\niCTR) is a software for use\nby hospital and clinics to\nautomatically assess the\ncardiothoracic ratio (CTR)\nof a chest X-ray image from\nthe X-ray imager subject.\nThe iCTR is designed to\nmeasure the maximal\ntransverse diameter of heart\nand maximal inner\ntransverse diameter of\nthoracic cavity and calculate\nthe CTR of a chest X-ray\nimage in posterior-anterior\n(PA) chest view using an\nartificial intelligence\nalgorithm.\nIntended users of the\nsoftware are aimed to the\nphysicians or other licensed\npractitioners in the\nhealthcare institutions, such\nas clinics, hospitals,\nhealthcare facilities,\nresidential care facilities and\nlong-term care services.\nThe system is suitable for\nadults between 20 - 80 years\nof age.\nIts results are not intended\nto be used on a stand-alone\nbasis for clinical-decision\nmaking or otherwise\npreclude clinical assessment","Both the subject (CT Cardiomegaly)\nand predicate device (iCTR) have\nidentical indications for use, with the\nexception that the subject device\nanalyzes CT images while the predicate\ndevice is limited to X-ray images.\nAnother difference between the\nindications for use for both devices is\nthat the predicate uses artificial\nintelligence algorithms using an\nunknown framework while the subject\ndevice utilizes non-adaptive machine\nlearning algorithms using the MONAI\nframework.\nHowever, these differences in\ntechnological characteristics do not\naffect safety and effectiveness of the\ndevice, and have been supported with\nverification and validation testing."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p8-t0","doc_id":"K232613","page_num":8,"bbox":[72.24,118.55,539.98,710.48],"n_rows":7,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["","making or otherwise\npreclude clinical\nassessment of any disease.","of cardiothoracic ratio\n(CTR) cases.",""],["Technical\nCharacteristics","","",""],["Input","CT image study","Post-anterior (PA) view\nchest X-ray image","The input for the predicate device is a\n2-dimensional chest X-ray image, while\nthe subject device’s input is an entire\nCT study. The subject device will select\nout of the CT study an axial slice\ncontaining the heart, if present, and\nperform measurements. The main\ndifference is that the predicate operates\non images that are post-anterior (PA)\nview chest X-ray, while the subject\ndevice’s operates on images that are\naxial CT. Nonetheless, this difference\nin imaging modality does not raise any\nnew concerns and has been verified and\nvalidated in testing."],["Output files","PDF and JSON Reports","Reports, DICOM\nSecondary Capture\nseries","The output format of the predicate\ndevice includes reports and DICOM\nsecondary capture series, while the\nsubject device’s only output format is a\nreport (in both PDF and JSON format).\nThus, the subject device’s output\nformat is a subset of the predicate’s\navailable output formats (i.e., report).\nThis lack of a feature does not raise any\nnew concerns."],["Output\nmeasurements","Linear-based CTR and\narea-based CTR","Linear-based CTR","The predicate device outputs a linear-\nbased CTR measurement while the\nsubject device outputs both linear and\narea-based CTR measurements.\nAlthough this output measurement of\narea-based CTR is not included in the\npredicate device, it does not raise\ndifferent questions of safety or\neffectiveness and has been properly\nverified and validated in testing."],["Report Structure","Report will be output in\nthe PDF and JSON\nfile format which is\nstructured with following","Report will be output in\nthe DICOM and JSON\nfile format which is\nstructured with following","Both devices produce reports that\noutput CTR and patient information.\nOne of the main differences between\nboth devices is that the predicate only"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p9-t0","doc_id":"K232613","page_num":9,"bbox":[72.22,118.55,539.98,711.48],"n_rows":4,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["","information:\n1) CTR (both linear and\narea-based)\n2) Patient information\n3) Reference value(s)","information and function\ntool:\n1) CTR\n2) adjustable annotation line\n(maximal inner border\ndiameter of thoracic cavity\nand maximal diameter of\nheart)\n3) the trajectory of CTR\n(including chest X-ray)\n4) Patient information","has one CTR output, while the subject\ndevice outputs both linear-based CTR\nand area-based CTR. This difference is\nfurther discussed in the row above.\nAdditionally, the predicate device\npresents the feature to modify the\nannotation line, which is not available\nin the subject device. However, CT\nCardiomegaly ’s indications for use\nexplicitly state that the results produced\nby the device are not intended to be\nsolely relied upon for clinical decision-\nmaking, nor do they replace the need\nfor clinical assessment of any disease.\nFurthermore, the user manual of the\ndevice contains instructions mandating\nhealthcare professionals to review the\nresults presented in the report.\nBoth devices produce reports that\ncontain relevant patient information.\nThe predicate device includes a\ntrajectory of the CTR in the report. The\nsubject device includes segmentations\nof the heart area and inner chest area.\nLastly, the subject device introduces a\nfeature to have user-specified reference\nvalue(s) stated in the report. The\nhealthcare professional is able to set\nreference value(s) linear and area-based\nCTR, based on published literature or\ntheir practice of medicine. This feature\nis not found in the predicate device, but\nhas been properly verified and\nvalidated."],["Intended Users","Physicians or other\nlicensed practitioners in\nthe healthcare\ninstitutions","Physicians or other\nlicensed practitioners in\nthe healthcare\ninstitutions","Same"],["Target Population","Adults and transitional\nadolescents (18 to 21 years\nold but treated as an adult)\"","Adults of 20-80 years old","Both devices have similar intended\ntarget populations. The subject device’s\npatient population age range has been\nsupported by appropriate performance\ntesting."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p10-t0","doc_id":"K232613","page_num":10,"bbox":[72.25,118.55,539.98,696.73],"n_rows":8,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["Location of\nanatomical\nstructures","Chest","Chest","Same"],["Imaging Modality","Computed Tomography\n(CT)","Chest X-ray in Digital\nRadiography (DR)","Although the predicate and subject\ndevice are compatible with different\nimaging modalities, this technological\ndifference does not raise new questions\nof safety or effectiveness. Additionally,\nthis difference has been properly\nsupported with verification and\nvalidation testing."],["Intended Use\nEnvironment","Healthcare institutions\n(Clinics, hospitals,\nhealthcare facilities,\nresidential care facilities\nand long-term care\nservices)","Healthcare institutions\n(Clinics, hospitals,\nhealthcare facilities,\nresidential care facilities\nand long-term care\nservices)","Same"],["Software device\nthat\noperates on off-the-\nshelf\nhardware","Yes","Yes","Same"],["Software devices\nuses\nsoftware\nalgorithms for\nimage","Yes","Yes","Same"],["Diameter\nMeasurement","Yes - Automated","Yes - Automated","Same, with the main difference that\ndiameter measurements are performed\non an axial slice of the CT series for the\nsubject device (not on chest x-ray, as\ndone for the predicate)."],["Storage","Saved in JSON and\nPDF file format","Saved in JSON and\nDICOM file format text\nfor DICOM and\nDICOM file format","Both devices store study reports in\nmachine-readable JSON format.\nThe predicate device also stores files in\nDICOM format. On the other hand, the\nsubject device also outputs reports in\nPDF format. This difference in file\nformat does not raise any new questions\nof safety or effectiveness, and is"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p11-t0","doc_id":"K232613","page_num":11,"bbox":[72.22,118.55,539.98,410.12],"n_rows":4,"n_cols":4,"columns":["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],"rows":[["Characteristic","CT Cardiomegaly","EFAI Intelligent\nCardiothoracic Ratio\n(iCTR) Assessment\nSystem (K212624)","Substantial Equivalence Discussion"],["","","","supported by verification and validation\ntesting."],["Software\nRequirement","Ubuntu 20.04.5 LTS\n(provided as a Docker\ncontainer)\nDocker 23.0.1 or above","Ubuntu 18.04\n(Web browser :\nchrome 88.0.4324.182\nor above)","Both devices have similar software\nrequirements. The subject device\nrequires a newer version of the\noperating system that runs inside a\ncontainer. The main difference is that\nthe predicate device is intended to run\non a web browser while the subject\ndevice is a command line software\nintended to be run on its own or as part\nof another medical device. This\ntechnological difference does not raise\nany new questions of safety or\neffectiveness, and is supported by\nverification and validation testing."],["Algorithm type","Machine learning based\nalgorithm (non-adaptive)","Artificial Intelligence","Same. Machine learning based\nalgorithm is a subset of artificial\nintelligence."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p12-t0","doc_id":"K232613","page_num":12,"bbox":[72.21,576.67,539.98,678.73],"n_rows":3,"n_cols":6,"columns":["Measurement","Mean Absolute\nDifference [95% CI]","Mean Difference\n[95% CI]","Mean Difference\nTarget","Standard Deviation\nof Differences","Result"],"rows":[["Measurement","Mean Absolute\nDifference [95% CI]","Mean Difference\n[95% CI]","Mean Difference\nTarget","Standard Deviation\nof Differences","Result"],["Cardiothoracic\nRatio","0.009 [0.007, 0.011]","0.0012 [-0.0008,\n0.0033]","< 0.0100","0.0172","Pass"],["Heart to Chest Area\nRatio","0.009 [0.007, 0.010]","0.0036 [0.0017,\n0.0055]","< 0.0100","0.0161","Pass"]],"caption_candidate":"Area Ratio, respectively.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p13-t0","doc_id":"K232613","page_num":13,"bbox":[72.23,214.08,521.98,282.1],"n_rows":2,"n_cols":5,"columns":["Value","Mean Difference [95%\nCI]","Mean Difference\nTarget","Standard Deviation of\nDifferences","Result"],"rows":[["Value","Mean Difference [95%\nCI]","Mean Difference\nTarget","Standard Deviation of\nDifferences","Result"],["Key Slice\nPosition","0.46 mm [-0.49, 1.41]","< 5 mm","0.49 mm","Pass"]],"caption_candidate":"Key Heart Slice Detection","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232613-p13-t1","doc_id":"K232613","page_num":13,"bbox":[72.23,308.85,289.13,378.62],"n_rows":3,"n_cols":2,"columns":["Anatomical Structure","Observed Dice [95% CI]"],"rows":[["Anatomical Structure","Observed Dice [95% CI]"],["Heart","0.95 [0.950, 0.956]"],["Inner Chest","0.98 [0.982, 0.984]"]],"caption_candidate":"Segmentation Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232661-p7-t0","doc_id":"K232661","page_num":7,"bbox":[45.03,120.36,746.97,536.16],"n_rows":8,"n_cols":4,"columns":["Measurement [units]","Description","Workflow","Application"],"rows":[["Measurement [units]","Description","Workflow","Application"],["Strain [%]","In general, myocardial strain is a measure of the deformation in\nshape and dimension of the heart muscle during the cardiac\ncycle. Mathematically Circle uses the Lagrangian strain tensor\nand measures the deformation with respect to the reference (end\ndiastole) phase. The radial, circumferential and longitudinal\nstrains are defined as the strain tensor evaluated in the radial,\ncircumferential and longitudinal directions on the appropriate SAX\nor LAX slices (in 2D), respectively.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• This measurement for the global\nmyocardium, or specific regions of\nmyocardium, can be represented over\ntime by Strain Curves.\n• Strain is also presented as an Image\nOverlay."],["Peak Strain [%]","The maximum of the strain in absolute value, over the whole\ncardiac cycle.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• This measurement, on a regional basis,\ncan be visualized and reported in Polar\nMaps.\nNote: Global peak circumferential strain\nand global peak longitudinal strain can\nbe added by the user to the clinical\nreport."],["Time to Peak Strain [ms]","Trigger time elapsed from the first phase till the phase where the\npeak strain has been reached.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Strain Rate [1/s]","Derivative of the strain with respect to time.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Strain Curves, as above."],["Peak Systolic Strain Rate\n[1/s]","The maximum of the strain rate in absolute value over all phases\nstarting from the end systole till the next diastole.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Peak Diastolic Strain Rate\n[1/s]","The maximum of the strain rate in absolute value over all phases\nstarting from the end diastole till the next systole.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Displacement\n[mm or degree]","The displacement vector represents the position of a point with\nrespect to the position of that point in the reference (end diastole)\nphase. The radial (both SAX and LAX) and longitudinal (LAX)","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal","• Strain Curves, as above.\nDisplacement is also presented as an\nImage Overlay."]],"caption_candidate":"Table 1. Measurements in the Strain Module.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232661-p8-t0","doc_id":"K232661","page_num":8,"bbox":[45.0,101.04,747.0,437.64],"n_rows":8,"n_cols":4,"columns":["","displacements are expressed in mm and the circumferential\n(SAX) displacement is presented in degree.","• LAX-Radial",""],"rows":[["","displacements are expressed in mm and the circumferential\n(SAX) displacement is presented in degree.","• LAX-Radial",""],["Peak Displacement [mm or\ndegree]","The maximum of the displacement in absolute value, over the\nwhole cardiac cycle (expressed in mm for radial and longitudinal,\nand in degree for circumferential displacements).","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Time to Peak Displacement [ms]","Trigger time elapsed from the first phase till the phase where the\npeak displacement has been reached.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Velocity [mm/s or degree/s]","Derivative of the displacement with respect to time (expressed in\nmm/s or degree/s, as appropriate). The circumferential velocity\nrepresents an angular velocity.","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Strain Curves, as above."],["Peak Systolic Velocity [mm/s or\ndegree/s]","The maximum of the velocity in absolute value over all phases\nstarting from the end diastole till the next systole (expressed in\nmm/s or degree/s, as appropriate).","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Peak Diastolic Velocity [mm/s or\ndegree/s]","The maximum of the velocity in absolute value over all phases\nstarting from the end systole till the next end diastole (expressed\nin mm/s or degree/s, as appropriate).","• SAX-Circumferential\n• SAX-Radial\n• LAX-Longitudinal\n• LAX-Radial","• Polar Maps, as above."],["Torsion [deg/cm]","The difference in rotation between the apical and basal slices\ndivided by the distance between apical and basal slices. Note that\ncircumferential displacement represents an angle.","• SAX-Circumferential","• Strain Curves, as above."],["Torsion Rate [deg/(cm*s)]","The difference in rotational velocity between apical and basal\nslices divided by the distance between the apical and basal\nslices. Note that circumferential velocity represents an angular\nvelocity.","• SAX-Circumferential","• Strain Curves, as above."]],"caption_candidate":"Strain Module 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232661-p10-t0","doc_id":"K232661","page_num":10,"bbox":[47.43,113.04,564.57,393.84],"n_rows":5,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","Strain Module","","","2D CPA MR (K120135)",""],["","","Manufactured by Circle","","","Manufactured by TomTec",""],["Intended\nUse","The Myocardial Strain Software Application is intended\nfor qualitative and quantitative evaluation of\ncardiovascular MR images in a DICOM Standard\nformat. As prerequisite, the user confirms endocardial\nand epicardial contours in a reference phase, and the\nsoftware tracks features over the cardiac cycle and\ncomputes 2D myocardial deformation and movement\n(e.g., strain, displacement, velocity).","","","2D CPA MR software is intended for quantification of\nthe myocardial deformation (strain) and movement\n(displacement / velocity) for digital magnetic\nresonance images. Possible quantification results are\nvelocity, displacement, strain, strain rate, time-to-peak\nand phase.\nPrerequisite is to draw a contour (endocard or\nendocard and epicard) in a digital magnetic resonance\nimage. Based on this manual drawn contour, the SW\ncalculates with a tracking algorithm the borders’\ndisplacement.","",""],["Indications\nfor Use","The Myocardial Strain Software Application is intended\nfor qualitative and quantitative evaluation of\ncardiovascular magnetic resonance (CMR) images. It\nprovides measurements of 2D LV myocardial function\n(displacement, velocity, strain, strain rate, time to\npeak, and torsion); these measurements are used by\nqualified medical professionals, experienced in\nexamining and evaluating CMR images, for the\npurpose of obtaining diagnostic information for\npatients with suspected heart disease as part of a\ncomprehensive diagnostic decision-making process.","","","2D Cardiac Performance Analysis is intended for\ncardiac quantification based on magnetic resonance\nimages. It provides measurements of myocardial\nfunction (displacement, velocity, strain, strain rate) that\nis used for diagnostic purposes of patients with\nsuspected heart disease.","",""]],"caption_candidate":"Table 2. Intended use and indications comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232661-p11-t0","doc_id":"K232661","page_num":11,"bbox":[47.29,113.04,564.71,475.92],"n_rows":17,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","","Strain Module","","","2D CPA MR (K120135)",""],["","","Manufactured by Circle","","","Manufactured by TomTec",""],["Device Class","II","","","II","",""],["Product Code","LLZ","","","LLZ","",""],["Regulation Name","Medical image management and\nprocessing system","","","Picture Archiving and Communications\nSystem","",""],["Regulation Number","21 CFR 892.2050","","","21 CFR 892.2050","",""],["DICOM Compliant?","Yes","","","Yes","",""],["Input Data Type","cine MR images\n(vendor independent)","","","cine MR images\n(vendor independent)","",""],["Prerequisites","Endocardial and epicardial contours in\nreference phase(s).","","","Contours (endocardial, or endocardial and\nepicardial) in a digital magnetic resonance\nimage","",""],["Myocardial deformation\nassessment technique","Feature tracking (FT)","","","Feature tracking (FT)","",""],["Comprehensive functional\nassessment of myocardial function","Yes","","","Yes","",""],["2D functional analysis of\nmyocardial deformation","Yes","","","Yes","",""],["Express parameters in their\nspatial directions (e.g.,\ncircumferential, longitudinal radial)","Yes","","","Yes","",""],["Overlay of tracked contour and\ngraphical displays for measured\nparameters","Yes","","","Yes","",""],["Myocardial Function Global and\nRegional Measurements","• Displacement\n• Velocity\n• Strain\n• Strain Rate\n• Time to Peak\n• Torsion","","","• Displacement\n• Velocity\n• Strain\n• Strain Rate\n• Time to Peak","",""],["Operating System","Microsoft Windows\nApple macOS","","","Microsoft Windows","",""]],"caption_candidate":"Table 3. Regulatory and technological features comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232698-p10-t0","doc_id":"K232698","page_num":10,"bbox":[85.58,70.46,829.8,517.44],"n_rows":12,"n_cols":4,"columns":["","NemoScan software allows for\nsurgical guide export to a validated\nmanufacturing center or to the point\nof care.\nManufacturing at the point of care\nrequires a validated process using\nCAM equipment (additive\nmanufacturing system, including\nsoftware and associated tooling) and\ncompatible material (biocompatible\nand sterilizable).\nA surgical guide may require to be\nused with accessories.","",""],"rows":[["","NemoScan software allows for\nsurgical guide export to a validated\nmanufacturing center or to the point\nof care.\nManufacturing at the point of care\nrequires a validated process using\nCAM equipment (additive\nmanufacturing system, including\nsoftware and associated tooling) and\ncompatible material (biocompatible\nand sterilizable).\nA surgical guide may require to be\nused with accessories.","",""],["Classification","21 CFR 892.2050, Class II","21 CFR 892.2050, Class II","21 CFR 892.2050, Class II"],["Product Code","QIH","LLZ","LLZ"],["Product Code\nName","System, Image Processing,\nRadiological","System, Image Processing, Radiological","System, Image Processing,\nRadiological"],["General\nDescription","Dental Surgery Planning System","Dental Surgery Planning System","Dental Surgery Planning System"],["Prescription Use","Yes","Yes","Yes"],["Core\nComponent","Stand-alone software","Stand-alone software","Stand-alone software"],["Target\npopulation","Adolescents (12-21 years of age) to\nadults (>21 years of age)","General public","Adults"],["Patient\ncondition","For edentulous, partial edentulous or\ndentition situations","For edentulous, partial edentulous or\ndentition situations","non-specific"],["Input Source","CT / CBCT scanner","CT / CBCT, DVT scanners","CT / CBCT scanner"],["Input Data\nformats","DICOM, .stl, .ply, .obj files","DICOM, .stl files","DICOM, .stl, .obj files"],["Export",".stl file format",".stl file format",".stl file format"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232698-p11-t0","doc_id":"K232698","page_num":11,"bbox":[85.58,70.46,829.2,521.64],"n_rows":9,"n_cols":4,"columns":["Printouts","Make reports of the implant\ntreatment plan.","Make reports of the implant treatment\nplan.","Make reports of the implant\ntreatment plan."],"rows":[["Printouts","Make reports of the implant\ntreatment plan.","Make reports of the implant treatment\nplan.","Make reports of the implant\ntreatment plan."],["Anatomical site","Oral-maxillofacial regions","Oral-maxillofacial regions","Oral-maxillofacial regions"],["Physical output\ndesign per\nPlanning","Yes","Yes","Yes"],["Minimum\nsystem\nrequirements","PC with specified requirements on\nhardware, operating system and\nsecurity (in user manual)","PC with specified requirements on\nhardware, operating system and security\n(in user manual)","PC with specified requirements on\nhardware, operating system and\nsecurity (in user manual)"],["Image\nregistration\n(alignment)","The scanned surface data acquired\nby the optical/intraoral scanner can\nbe aligned to the CT/CBCT\nreconstruction through a point-based\nregistration technique","The scanned surface data acquired by\nthe optical/intraoral scanner can be\naligned to the CT/CBCT reconstruction\nthrough a point-based registration\ntechnique","The scanned surface data\nacquired by the optical/intraoral\nscanner can be aligned to the\nCT/CBCT reconstruction through a\npoint-based registration technique"],["Interface\nrequirements","Desktop Application\nWeb Application","Desktop Application","Desktop Application"],["DICOM Standard\nCompliant","Yes","Yes","Yes"],["Projects\nmanagement","Project exporting/importing","Project exporting/importing","Project exporting/importing"],["Mean Features/\nTools","CAD tools to manipulate/modify/\nrender/import/export/sectioning\npatient models (teeth, upper/lower\njaws), surgical item models, areas of\ninterest. Includes:\n- Panoramic curve\n- Nerve detection\n- Virtual structures\n- Orient images to occlusal plane-\nSurgical item libraries\n- Bone density analyses, geometric\nmeasurements","CAD tools to manipulate/modify/\nrender/import/export/sectioning patient\nmodels (teeth, upper/lower jaws), surgical\nitem models, areas of interest. Includes:\n- Panoramic curve\n- Nerve detection\n- Virtual structures\n- Orient images to occlusal plane-\nSurgical item libraries\n- Bone density analyses, geometric\nmeasurements","CAD tools to manipulate/modify/\nrender/import/export/sectioning\npatient models (teeth, upper/lower\njaws), surgical item models, areas\nof interest. Includes:\n- Panoramic curve\n- Nerve detection\n- Virtual structures\n- Orient images to occlusal plane-\nSurgical item libraries\n- Bone density analyses,\ngeometric measurements"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232698-p12-t0","doc_id":"K232698","page_num":12,"bbox":[85.58,70.46,829.8,520.44],"n_rows":6,"n_cols":4,"columns":["Case\nvisualization","2D gray value images\n3D model rendering\nPanoramic mode\nMPR mode\nIndividual editing of imaging artifacts\n3D Photo in .Obj format\nAlign 3D with Photos\nImage treatment","2D gray value images\n3D model rendering\nPanoramic mode\nMPR mode\nIndividual editing of imaging artifacts","2D gray value images\n3D model rendering.\nPanoramic mode\nMPR mode\n3D Photo in .Obj format\nAlign 3D with Photos"],"rows":[["Case\nvisualization","2D gray value images\n3D model rendering\nPanoramic mode\nMPR mode\nIndividual editing of imaging artifacts\n3D Photo in .Obj format\nAlign 3D with Photos\nImage treatment","2D gray value images\n3D model rendering\nPanoramic mode\nMPR mode\nIndividual editing of imaging artifacts","2D gray value images\n3D model rendering.\nPanoramic mode\nMPR mode\n3D Photo in .Obj format\nAlign 3D with Photos"],["Measurement\ntool","Distance/Angle\nBone density measurement","Distance/Angle\nBone density measurement","Distance/Angle\nBone density measurement"],["Virtual Wax-up","Possible","Possible","Possible"],["Nerve tracing","Possible","Possible","Possible"],["Implant\nPreparation\ntools","Teeth segmentation and coordinate\nsystem;\nDICOM to STL conversion;\nMesh transformation;\nSinus segmentation;\nReorient the 3D volume;\nRoot and teeth segmentation;\nTeeth extractions;\nPanoramic curve;","Teeth segmentation and coordinate\nsystem;\nDICOM to STL conversion;\nSinus segmentation;\nReorient the 3D volume;\nRoot and teeth segmentation;\nTeeth extractions;\nPanoramic curve;","Teeth segmentation and\ncoordinate system;\nDICOM to STL conversion;\nMesh transformation;\nSinus segmentation;\nReorient the 3D volume;\nRoots segmentation and complete\nteeth fusion;\nTeeth extractions;\nPanoramic curve;"],["Implant Planning\ntools","Implant, sleeve, drill, abutment,\nanalog, and pin positioning;\nCustom Implant, Sleeve, Drill,\nAbutment, and Pin creation;\nImplant-to-implant, Implant-to-nerve\ncanal, Sleeve-to-Sleeve, and\nSleeve-to- STL surface\ndistance/collision warning;\nProsthesis wizards;","Implant, sleeve, drill, abutment, analog,\nand pin positioning;\nCustom Implant, Sleeve, Drill, Abutment,\nand Pin creation;\nImplant-to-implant, Implant-to-nerve\ncanal, Sleeve-to-Sleeve surface\ndistance/collision warning;","Implant, sleeve, drill, abutment,\nand pin positioning;\nCustom Implant, Sleeve, Drill,\nAbutment, and Pin creation;\nImplant-to-implant,\nImplant-to-nerve canal,\nSleeve-to-Sleeve, and Sleeve-to-\nSTL surface distance/collision\nwarning"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232698-p13-t0","doc_id":"K232698","page_num":13,"bbox":[85.58,70.46,829.68,516.6],"n_rows":5,"n_cols":4,"columns":["","Implant validations:","","Prosthesis wizards;\nImplant validations;"],"rows":[["","Implant validations:","","Prosthesis wizards;\nImplant validations;"],["Surgical guide\ndesign","Design the surgery guide based on\nthe implant treatment plan, such as:\n● Tooth-supported surgical\nguide design possible;\n● Gingiva-supported surgical\nguide design possible;\n● Bone-supported surgical\nguide design possible;\n● Export of surgical guide\ndesign data set possible;\n● Gingivectomy guide;\n● Offset, thickness and\nconnector setting possible;\n● Add label text in surgical\nguide;","Design the surgery guide based on the\nimplant treatment plan, such as:\n● Tooth-supported surgical guide\ndesign possible;\n● Gingiva-supported surgical guide\ndesign possible;\n● Bone-supported surgical guide\ndesign possible;\n● Gingivectomy guide;\n● Export of surgical guide design\ndata set possible;\n● Offset, wall thickness and\nconnector thickness setting\npossible.\n● Add label text in surgical guide;","Design the surgery guide based\non the implant treatment plan,\nsuch as:\n● Tooth-supported surgical\nguide design possible;\n● Gingiva-supported surgical\nguide design possible;\n● Bone-supported surgical\nguide design possible;\n● Offset, wall thickness and\nconnector thickness setting\npossible;\n● Export of surgical guide\ndesign data set possible;"],["Surgical\nprotocol design\nand creation tool","Details protocol: available per\nimplant providing detailed implant,\nsleeve and surgical protocol\ninformation together with images of\nthe planning views;\nSurgical protocol: The sequence of\nsurgical instruments to be used as\nspecified by the selected guided\nsurgery system (selected\nmanufacturers only)","Details protocol: available per implant\nproviding detailed implant, sleeve and\nsurgical protocol information together\nwith images of the planning views;\nSurgical protocol: The sequence of\nsurgical instruments to be used as\nspecified by the selected guided surgery\nsystem (selected manufacturers only)","Details protocol: available per\nimplant\nproviding detailed implant, sleeve\nand surgical protocol information\ntogether with images of the\nplanning views;\nSurgical protocol: The sequence\nof surgical instruments to be used\nas specified by the selected\nguided surgery system (selected\nmanufacturers only)"],["Other tools","Analog model, Virtual pour up and\nmodel builder.","N/A","N/A"],["Minimum\nsystem","OS - Windows 10 64-bit;\n16 GB RAM Memory minimum","OS - Windows 7, 64-bit;\n8GB RAM Memory minimum","Windows 7/8/8.1/10\n4 GB RAM Memory minimum"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232698-p14-t0","doc_id":"K232698","page_num":14,"bbox":[85.58,70.46,829.68,196.85],"n_rows":2,"n_cols":4,"columns":["hardware and\nsoftware\nrequirements","(CPU) - Intel Core i7 at 2.8GHz\nNetwork cards wired, minimum\nspeed 1 Gb./sec;\nNVidia graphics card. Minimum 2\nGB. VRAM\nHDD – 15 GB of free space","(CPU) - Intel® Core™ 2 Duo processor\nP8600\nGraphics Card and Network cards- Not\nspecified\nHDD – 128 GB of free space","16 GB RAM Memory\nrecommended\nIntel Core i7 at 2.8GHz\n5 GB free disc space or more\nInternet connection requirement"],"rows":[["hardware and\nsoftware\nrequirements","(CPU) - Intel Core i7 at 2.8GHz\nNetwork cards wired, minimum\nspeed 1 Gb./sec;\nNVidia graphics card. Minimum 2\nGB. VRAM\nHDD – 15 GB of free space","(CPU) - Intel® Core™ 2 Duo processor\nP8600\nGraphics Card and Network cards- Not\nspecified\nHDD – 128 GB of free space","16 GB RAM Memory\nrecommended\nIntel Core i7 at 2.8GHz\n5 GB free disc space or more\nInternet connection requirement"],["Payment model","Pay per use\nLicense Fee\nAnnual Fee","License Fee\nAnnual Fee","Pay per use\nLicense Fee\nAnnual Fee"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p4-t0","doc_id":"K232704","page_num":4,"bbox":[66.67,271.14,534.11,326.76],"n_rows":4,"n_cols":7,"columns":["","Regulation Number","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","Regulation Name","","","Product Code",""],["21 CFR § 892.1550","","Ultrasonic Pulsed Doppler Imaging System","","IYN","",""],["21 CFR § 892.1560","","Ultrasound Pulsed Echo Imaging System","","IYO","",""],["21 CFR § 892.1570","","Diagnostic Ultrasonic Transducer","","ITX","",""]],"caption_candidate":"Regulation Number, Name and Product Codes:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p4-t1","doc_id":"K232704","page_num":4,"bbox":[66.67,558.0,534.11,682.72],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Clarius Ultrasound Scanner"],"rows":[["","Device Trade Name:","","Clarius Ultrasound Scanner"],["","510(k) Reference:","","K213436"],["","Submitter Name:","","Clarius Mobile Health Corp."],["","Regulation Name:","","Ultrasonic Pulsed Doppler Imaging System"],["","Classification Product Code(s):","","IYN"],["","Subsequent Product Codes","","IYO, ITX"],["Regulation Number:","Regulation Number:","","21 CFR § 892.1550; 21 CFR § 892.1560; 21 CFR §\n892.1570"],["","Classification:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p5-t0","doc_id":"K232704","page_num":5,"bbox":[66.68,548.0,534.12,616.51],"n_rows":3,"n_cols":4,"columns":["","Transducer/ Scanner","","PAL HD3"],"rows":[["","Transducer/ Scanner","","PAL HD3"],["Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"],["Accessories","","","Clarius Charger HD3\nClarius Power Fan HD3"]],"caption_candidate":"The Clarius Ultrasound Scanner, subject of this 510(k) premarket notification, comprises the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p6-t0","doc_id":"K232704","page_num":6,"bbox":[66.68,176.94,548.26,713.73],"n_rows":17,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["","510(k) Holder/","","Clarius Mobile Health Corp.","","","Clarius Mobile Health Corp.","",""],["","Manufacturer","","","","","","",""],["","Submission","","Current Submission","","","K213436","",""],["","Reference","","","","","","",""],["","510(k) Track","","Track 3","","","Track 3","",""],["","Product Codes","","IYN1, IYO2, ITX3","","","IYN1, IYO2, ITX3","",""],["Regulation\nNumber","Regulation","","21 CFR 892.15501\n21 CFR 892.15602\n21 CFR 892.15703","","","21 CFR 892.15501\n21 CFR 892.15602\n21 CFR 892.15703","",""],["","Number","","","","","","",""],["Regulation Name","","","Ultrasonic Pulsed Doppler Imaging System1;\nUltrasonic Pulsed Echo Imaging System2;\nDiagnostic Ultrasonic Transducer3","","","Ultrasonic Pulsed Doppler Imaging System1;\nUltrasonic Pulsed Echo Imaging System2;\nDiagnostic Ultrasonic Transducer3","",""],["","Transducer","","PAL HD3","","","PA HD3, L15 HD3","",""],["","Model(s)","","","","","","",""],["Transducer Types","Transducer Types","","Phased Array and Linear Array\n(the phased array and linear array are\narranged side-by-side within the same\ntransducer model)","","","Phased Array, Linear Array\n(the phased array and linear array are\nrepresented in two separate transducer\nmodels)","",""],["Intended Use","","","Diagnostic ultrasound imaging or fluid flow\nanalysis of the human body","","","Diagnostic ultrasound imaging or fluid flow\nanalysis of the human body","",""],["Indications for\nUse and Clinical\nUsage","","","The Clarius Ultrasound Scanner is a software-\nbased ultrasound imaging system and\naccessories, intended for diagnostic imaging.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: ophthalmic, fetal,\nabdominal, intra-operative (non-\nneurological), pediatric, small organ, cephalic\n(adult), trans-rectal, trans-vaginal, musculo-\nskeletal (conventional, superficial), urology,\ngynecology, cardiac (adult, pediatric),\nperipheral vessel, carotid, and procedural\nguidance of needles into the body.\nThe system is a transportable ultrasound\nsystem intended for use in environments\nwhere healthcare is provided by trained\nhealthcare professionals.","","","The Clarius Ultrasound Scanner is a software-\nbased ultrasound imaging system and\naccessories, intended for diagnostic imaging.\nIt is indicated for diagnostic ultrasound\nimaging and fluid flow analysis in the\nfollowing applications: ophthalmic, fetal,\nabdominal, intra-operative (non-\nneurological), pediatric, small organ, cephalic\n(adult), trans-rectal, trans-vaginal, musculo-\nskeletal (conventional, superficial), urology,\ngynecology, cardiac (adult, pediatric),\nperipheral vessel, carotid, and procedural\nguidance of needles into the body.\nThe system is a transportable ultrasound\nsystem intended for use in environments\nwhere healthcare is provided by trained\nhealthcare professionals.","",""]],"caption_candidate":"Comparison of the Subject Device and Predicate Device for Demonstration of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p7-t0","doc_id":"K232704","page_num":7,"bbox":[66.68,72.36,548.26,714.31],"n_rows":14,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["","","","Phased Array (PAL HD3):\n• Fetal\n• Abdominal\n• Intraoperative\n• Pediatric\n• Cardiac (adult, pediatric)\nLinear Array (PAL HD3):\n• Ophthalmic\n• Abdominal\n• Intraoperative\n• Pediatric\n• Small Organ (thyroid, prostate, scrotum,\nbreast)\n• Musculoskeletal (conventional,\nsuperficial)\n• Peripheral vessel\n• Carotid\n• Needle enhance in B-Mode","","","Phased Array (PA HD3):\n• Fetal\n• Abdominal\n• Intraoperative (abdominal organs and\nvascular)\n• Pediatric\n• Cephalic (adult)\n• Cardiac (adult, pediatric)\nLinear Array (L15 HD3):\n• Ophthalmic\n• Abdominal\n• Intraoperative (abdominal organs and\nvascular)\n• Pediatric\n• Small Organ (thyroid, prostate, scrotum,\nbreast)\n• Musculoskeletal (conventional,\nsuperficial)\n• Peripheral vessel\n• Carotid\n• Needle enhance in B-Mode","",""],["Principle of\nOperation","","","Piezoelectric material in the system’s\ntransducer transmits high frequency, non-\nionizing sound waves to the designated\nregion of the body and converts the\nsubsequent echoes detected to electronic\nsignals in order to construct an image of the\ninternal structures of an anatomical field. The\nimage is sent wirelessly from the transducer\nto an external iOS or Android viewing device\non which the image can be displayed.","","","Piezoelectric material in the system’s\ntransducer transmits high frequency, non-\nionizing sound waves to the designated\nregion of the body and converts the\nsubsequent echoes detected to electronic\nsignals in order to construct an image of the\ninternal structures of an anatomical field. The\nimage is sent wirelessly from the transducer\nto an external iOS or Android viewing device\non which the image can be displayed.","",""],["Power Source","","","Internal integrated built-in (non-removable)\nlithium-ion battery","","","Internal integrated built-in (non-removable)\nlithium-ion battery","",""],["","Display","","iOS or Android mobile device","","","iOS or Android mobile device","",""],["","Wireless","","Communicates wirelessly via Wi-Fi and\nBluetooth","","","Communicates wirelessly via Wi-Fi and\nBluetooth","",""],["","Capability","","","","","","",""],["","Portability","","Portable ultrasound system","","","Portable ultrasound system","",""],["System\nComponents","System","","Transducer/scanner\nSoftware (Clarius App)\nAccessories (Charger and Power Fan)","","","Transducers/scanners\nSoftware (Clarius App)\nAccessories (Charger and Power Fan)","",""],["","Components","","","","","","",""],["Frequency","","","1-5 MHz (Phased Array) and 5-15 MHz (Linear\nArray)","","","1-5 MHz (Phased Array-PA HD3) and 5-15\nMHz (Linear Array-L15 HD3)","",""],["Modes of\nOperation","","","B-mode\nM-mode\nColor Doppler\nPower Doppler","","","B-mode\nM-mode\nColor Doppler\nPower Doppler","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p8-t0","doc_id":"K232704","page_num":8,"bbox":[66.67,72.36,548.25,300.9],"n_rows":8,"n_cols":9,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","",""],["","","","","","","","",""],["","","","","Clarius Ultrasound Scanner","","","Clarius Ultrasound Scanner",""],["","","","Pulse-Wave Doppler (PWD)\nCombined (B+M; B+CD; B+PD; B+PWD)","","","Pulse-Wave Doppler (PWD)\nCombined (B+M; B+CD; B+PD; B+PWD)","",""],["Safety Standards","","","The Clarius Ultrasound Scanner complies with\nthe following safety standards:\n60601-1\n60601-1-2\n60601-1-6\n60601-1-12\n60601-2-37","","","The Clarius Ultrasound Scanner complies with\nthe following safety standards:\n60601-1\n60601-1-2\n60601-1-6\n60601-1-12\n60601-2-37","",""],["Intended Users","","","Licensed healthcare professionals (e.g.,\ndoctors, nurses, sonographers) trained in\nultrasound use.","","","Licensed healthcare professionals (e.g.,\ndoctors, nurses, sonographers) trained in\nultrasound use.","",""],["","Environment of","","Hospital, clinic, ambulatory setting","","","Hospital, clinic, ambulatory setting","",""],["","Use","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p8-t1","doc_id":"K232704","page_num":8,"bbox":[72.01,480.72,540.08,716.52],"n_rows":11,"n_cols":4,"columns":["","Standard Designation No.","","Title of Standard"],"rows":[["","Standard Designation No.","","Title of Standard"],["","and Date","",""],["","","",""],["IEC 62304:2006 + A1:2015","","","Medical device software - Software life cycle processes"],["ISO 14971:2019","","","Medical Devices - Application of risk management to medical devices"],["","IEC 60601-1:2005 + A","","Medical electrical equipment – Part 1: General requirements for basic safety and\nessential performance"],["","2012","",""],["IEC 60601-1-2:2014","","","Medical electrical equipment – Part 1-2: General requirements for basic safety and\nessential performance – Collateral Standard: Electromagnetic Capability –\nRequirements and tests"],["IEC 60601-1-6:2010 +\nA1:2013","","","Medical electrical equipment - Part 1-6: General requirements for basic safety and\nessential performance - Collateral standard: Usability"],["IEC 60601-2-37:2015","","","Medical Electrical Equipment - Part 2-37: Particular Requirements For the basic\nsafety and essential performance of ultrasonic medical diagnostic and monitoring\nequipment"],["IEC 60601-1-12:2014","","","Medical Electrical Equipment - Part 1-12: General requirements for basic safety\nand essential performance - Collateral Standard: Requirements for medical\nelectrical equipment and medical electrical systems intended for use in the\nemergency medical services environment"]],"caption_candidate":"Scanner device family, demonstrates compliance to the following standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232704-p9-t0","doc_id":"K232704","page_num":9,"bbox":[72.0,72.24,539.76,278.88],"n_rows":8,"n_cols":2,"columns":["IEC 62133:2012","Secondary cells and batteries containing alkaline or other non-acid electrolytes -\nSafety requirements for portable sealed secondary cells, and for batteries made\nfrom them, for use in portable applications"],"rows":[["IEC 62133:2012","Secondary cells and batteries containing alkaline or other non-acid electrolytes -\nSafety requirements for portable sealed secondary cells, and for batteries made\nfrom them, for use in portable applications"],["ISO 10993-1:2018","Biological evaluation of medical devices – Part 1: Evaluation and testing within a\nrisk management process"],["ISO 15223-1:2021","Medical devices - Symbols to be used with information to be supplied by the\nmanufacturer – Part 1: General requirements"],["AIUM/NEMA UD 2-2004\n(R2009)","Acoustic Output Measurement Standard for Diagnostic Ultrasound Equipment\nRevision 3"],["IEC 62366-1:2015","Medical devices – Part 1: Application of usability engineering to medical devices"],["AIUM/NEMA UD 3-2004","NEMA Standards Publication UD 3-2004 (R2009) Standard for Real-Time Display of\nThermal and Mechanical Acoustic Output Indices on Diagnostic Ultrasound\nEquipment"],["IEC 60529:2013","Degrees of protection provided by enclosures (IP Code)"],["IEC 61157:2013","IEC 61157: Standard means for the reporting of the acoustic output of medical\ndiagnostic ultrasonic equipment"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232712-p6-t0","doc_id":"K232712","page_num":6,"bbox":[114.11,247.0,533.81,462.57],"n_rows":8,"n_cols":3,"columns":["ITEM","Proposed Device\nuMI Panorama","Predicate Device\nuMI Panorama (K223325)"],"rows":[["ITEM","Proposed Device\nuMI Panorama","Predicate Device\nuMI Panorama (K223325)"],["Patient bore size","760mm","760mm"],["PET System","Scintillator material: LYSO\nNumber of detector rings:\n• 96 (uMI Panorama 28)\n• 120 (uMI Panorama 35)\nAxial FOV:\n• 280mm (uMI Panorama 28)\n• 350mm (uMI Panorama 35)","Scintillator material: LYSO\nNumber of detector rings:\n• 96 (uMI Panorama 28)\n• 120 (uMI Panorama 35)\nAxial FOV:\n• 280mm (uMI Panorama 28)\n350mm (uMI Panorama 35)"],["CT System","uCT ATLAS Astound (K223028)","uCT ATLAS Astound (K223028)"],["Maximum table load","318kg","318kg"],["Advanced Feature","",""],["uExcel Focus","Yes","Yes"],["uKinetics","Yes","No"]],"caption_candidate":"devices is provided as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p6-t0","doc_id":"K232751","page_num":6,"bbox":[72.02,483.79,540.09,535.75],"n_rows":4,"n_cols":2,"columns":["","he SW architecture was changed"],"rows":[["","he SW architecture was changed"],["to separate the image communication platform from the BriefCase-Triage SW. The subject device",""],["consists of only the algorithm analysis module which can be integrated with image communication",""],["platforms that meet the BriefCase-Triage input and output requirements.",""]],"caption_candidate":"incorporated in software packages for use with DICOM compliant CT scanners, PACS, and radiology","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p7-t0","doc_id":"K232751","page_num":7,"bbox":[72.02,123.02,540.1,712.54],"n_rows":2,"n_cols":4,"columns":["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],"rows":[["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],["Intended Use /\nIndications for Use","Rapid PE Triage and\nNotification (PETN) is\na radiological\ncomputer aided triage\nand notification\nsoftware indicated for\nuse in the analysis of\nCTPA images. The\ndevice is intended to\nassist hospital\nnetworks and trained\nclinicians in workflow\ntriage by flagging and\ncommunication of\nsuspected positive\nfindings of central\npulmonary embolism\n(PE) pathology in\nadults. The software is\nonly intended to be\nused on single-energy\nexams.\nRapid PETN uses an\nartificial intelligence\nalgorithm to analyze\nimages and highlight\ncases with detected\nfindings on a server or\nstandalone desktop\napplication in parallel\nto the ongoing\nstandard of care image\ninterpretation. The","BriefCase is a\nradiological computer\naided triage and\nnotification software\nindicated for use in the\nanalysis of CTPA\nimages in adults or\ntransitional\nadolescents aged 18\nand older. The device\nis intended to\nassist hospital\nnetworks and\nappropriately trained\nmedical specialists in\nworkflow triage\nby flagging and\ncommunication of\nsuspected positive\nfindings of Pulmonary\nEmbolism (PE)\npathologies.\nBriefCase uses an\nartificial intelligence\nalgorithm to analyze\nimages and highlight\ncases with detected\nfindings on a\nstandalone desktop\napplication in parallel\nto the ongoing\nstandard of care\nimage interpretation.","BriefCase-Triage is a\nradiological computer-\naided triage and\nnotification software\nindicated for use in the\nanalysis of CTPA\nimages in adults or\ntransitional\nadolescents aged 18\nand older. The device\nis intended to assist\nhospital networks and\nappropriately trained\nmedical specialists in\nworkflow triage by\nflagging and\ncommunicating\nsuspected positive\ncases of Central\nPulmonary Embolism\n(Central PE).\nBriefCase-Triage uses\nan artificial intelligence\nalgorithm to analyze\nimages and highlight\ncases with detected\nfindings in parallel to\nthe ongoing standard\nof care image\ninterpretation. The\nuser is presented with\nnotifications for cases\nwith suspected Central\nPE findings.\nNotifications include"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p8-t0","doc_id":"K232751","page_num":8,"bbox":[72.02,72.24,540.1,683.5],"n_rows":2,"n_cols":4,"columns":["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],"rows":[["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],["","user is presented with\nnotifications for cases\nwith suspected\nfindings. Notifications\ninclude compressed\npreview images that\nare meant for\ninformational purposes\nonly and not intended\nfor diagnostic use\nbeyond notification.\nThe device does not\nalter the original\nmedical image and is\nnot intended to be\nused as a diagnostic\ndevice.\nThe results of Rapid\nPETN are intended to\nbe used in conjunction\nwith other patient\ninformation and based\non their professional\njudgment, to assist\nwith\ntriage/prioritization of\nmedical images.\nNotified clinicians are\nresponsible for viewing\nfull images per the\nstandard of care.\nRapid PETN is\nvalidated for use on\nGE, Siemens and\nToshiba scanners.","The user is presented\nwith notification for\ncases with suspected\nfindings. Notifications\ninclude compressed\npreview images that\nare\nmeant for informationa\nl purposes only and\nnot intended for\ndiagnostic use\nbeyond notification. T\nhe device does not\nalter the original\nmedical image and is\nnot intended to be\nused as a diagnostic\ndevice.\nThe results of\nBriefCase are\nintended to be used in\nconjunction with other\npatient information and\nbased on their\nprofessional judgment,\nto assist with\ntriage/prioritization of\nmedical images.\nNotified clinicians are\nresponsible for viewing\nfull images per the\nstandard of care.","compressed preview\nimages that are meant\nfor informational\npurposes only and not\nintended for diagnostic\nuse beyond\nnotification. The\ndevice does not alter\nthe original medical\nimage and is not\nintended to be used as\na diagnostic device.\nThe results of\nBriefCase-Triage are\nintended to be used in\nconjunction with other\npatient information and\nbased on their\nprofessional judgment,\nto assist with\ntriage/prioritization of\nmedical images.\nNotified clinicians are\nresponsible for viewing\nfull images per the\nstandard of care."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p9-t0","doc_id":"K232751","page_num":9,"bbox":[72.02,72.24,540.1,700.54],"n_rows":8,"n_cols":4,"columns":["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],"rows":[["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],["User population","Hospital networks and\ntrained clinicians","Hospital networks and\nappropriately trained\nmedical specialists","Hospital networks and\nappropriately trained\nmedical specialists"],["Anatomical region of\ninterest","Chest","Chest","Chest"],["Data acquisition\nprotocol","CTPA","CTPA","CTPA"],["Notification-only,\nparallel workflow tool","Yes","Yes","Yes"],["Interference with\nstandard workflow","No","No","No"],["Algorithm","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images."],["Structure","- The Rapid\nPETN module\noperates within\nthe integrated\nRapid Platform\nand uses the\nbasic services\nsupplied by the\nRapid Platform\nincluding\nDICOM\nprocessing, job\nmanagement,\nimaging\nmodule\nexecution and\nimaging\noutput.","- AHS module\n(image\nacquisition);\n- ACS module\n(image\nprocessing);\n- Aidoc Desktop\nApplication for\nworkflow\nintegration\n(Feed/Worklist\n(alternate\nnames) and\nnon-diagnostic\nImage\nViewer).","- Integrated with\nimage routing\nmodule via\nimage\ncommunicatio\nn platform\n(ICP) (image\nacquisition).\n- Algorithm\nmodule (image\nprocessing)\n- Integrated with\ndesktop\napplication for\nworkflow\nintegration\n(feed and non-\ndiagnostic"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p10-t0","doc_id":"K232751","page_num":10,"bbox":[72.02,72.24,540.1,203.42],"n_rows":2,"n_cols":4,"columns":["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],"rows":[["","Predicate Device\nRapid PE Triage and\nNotification (PETN)\n(K220499)","Reference Device\nBriefCase-Triage for\nPE triage\n(K222277)","Subject Device\nAidoc BriefCase-\nTriage of Central\nPulmonary\nEmbolism (Central\nPE)"],["","","","Image\nViewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p11-t0","doc_id":"K232751","page_num":11,"bbox":[121.51,652.26,490.71,699.26],"n_rows":2,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age (Years)","","","60.3","","","17.4","","","19","","","63","","","90","","","328",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p12-t0","doc_id":"K232751","page_num":12,"bbox":[72.05,99.14,540.07,233.94],"n_rows":6,"n_cols":17,"columns":["Ground\nTruth\nResults","","","","Gender","","","","","","","All","","","","",""],"rows":[["Ground\nTruth\nResults","","","","Gender","","","","","","","All","","","","",""],["","","","","Male","","","","Female","","","","All","","","",""],["","","","","N","","","%","N","%","","","N","","","%",""],["","Positive","","","65","","","19.8%","64","19.5%","","","129","","","39.3%",""],["","Negative","","","117","","","35.7%","82","25.0%","","","199","","","60.6%",""],["","All","","","182","","","55.5%","146","44.5%","","","328","","","100.0%",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232751-p12-t1","doc_id":"K232751","page_num":12,"bbox":[72.05,275.89,540.07,444.59],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["Philips","","","99","","","30.2%","",""],["GE MEDICAL SYSTEMS","","","90","","","27.4%","",""],["SIEMENS","","","78","","","23.8%","",""],["TOSHIBA","","","61","","","18.6%","",""],["","Total","","","328","","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p7-t0","doc_id":"K232765","page_num":7,"bbox":[94.09,158.84,499.54,299.16],"n_rows":8,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Vida with syngo\nMR XA50A","K213693, cleared on February\n25, 2022","LNH\nLNI, MOS","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Prisma with\nsyngo MR XA30A","K202014 cleared,\nSeptember 08, 2020","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Sola with syngo\nMR XA51A","K221733 cleared, September\n13, 2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Free.Max with\nsyngo MR XA50A","K220575 cleared, June 22,\n2022","LNH,\nLNI, MOS","Siemens Shenzhen\nMagnetic Resonance Ltd."]],"caption_candidate":"following predicate device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p7-t1","doc_id":"K232765","page_num":7,"bbox":[94.09,490.52,499.54,712.56],"n_rows":16,"n_cols":4,"columns":["Hardware","Subject Devices","Predicate Device","Reference Devices"],"rows":[["Hardware","Subject Devices","Predicate Device","Reference Devices"],["","","",""],["","MAGNETOM Cima.X Fit","MAGNETOM Vida with","MAGNETOM Sola with"],["","with software syngo MR","syngo MR XA50A","syngo MR XA51A"],["","XA61A","(K213693)","(K221733)"],["","","","MAGNETOM Prisma with"],["","","","syngo MR XA30A"],["","","","(K202014)"],["","","","MAGNETOM Free.Max"],["","","","with syngo MR XA50A"],["","","","(K220575)"],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","New or modified features as\nlisted in the Device\nDescription above","Yes","Yes"],["Patient Table","Yes","Yes","Yes"]],"caption_candidate":"Summary hardware comparison table for the subject and predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p8-t0","doc_id":"K232765","page_num":8,"bbox":[93.96,66.9,500.43,230.4],"n_rows":12,"n_cols":4,"columns":["Multi-Nuclear\nOption - Supported\nNuclei","Yes","Yes","Yes"],"rows":[["Multi-Nuclear\nOption - Supported\nNuclei","Yes","Yes","Yes"],["Computer","Yes","Yes","Yes"],["","Modified","",""],["Coils","Yes","Yes","Yes"],["","New, based on predicate:","",""],["","Tx/Rx Knee 15, Tx/Rx Knee 15","",""],["","Flare, 4 Ch BI","",""],["","Breast coil (already introduced","",""],["","with reference system)","",""],["Other HW\ncomponents","New or modified HW","Yes","Yes"],["","components as listed in the","",""],["","Device Description above","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p8-t1","doc_id":"K232765","page_num":8,"bbox":[93.96,256.56,500.43,710.16],"n_rows":43,"n_cols":3,"columns":["Software","Subject Device","Predicate Device"],"rows":[["Software","Subject Device","Predicate Device"],["","",""],["","MAGNETOM Cima.X Fit with","MAGNETOM Vida with syngo"],["","software syngo MR XA61A","MR XA50A"],["","","(K213693)"],["Sequences","",""],["SE-based pulse sequence types","New feature as listed in the Device","Yes"],["","Description above",""],["GRE-based/Steady-State pulse","New or modified pulse sequences","Yes"],["","as listed in the Device Description",""],["sequence types","",""],["","above",""],["","",""],["EPI-based pulse sequence types","New features as listed in the Device","Yes"],["","Description above",""],["Spectroscopy pulse sequence types","Yes","Yes"],["Feature and Applications","",""],["Other features and","Modified features and","Yes"],["applications such as:","",""],["-Application Suites","",""],["","applications as listed in the Device",""],["-myExam Assists","",""],["","Description above",""],["-Other Imaging","",""],["","",""],["Applications","",""],["User interface and user interaction","Yes","Yes"],["Viewing and post-processing","New or modified viewing and post-","Yes"],["","processing features as listed in the",""],["","Device Description above",""],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["Scanning","Modified and new features and","Yes"],["","applications as listed in the",""],["","Cover letter, Device Description",""],["","and Substantial Equivalence",""],["","Comparison Tables",""],["Reconstruction","New feature","Yes"],["","as listed in the Device Description",""],["","above",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"Summary software comparison table for the subject and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p9-t0","doc_id":"K232765","page_num":9,"bbox":[94.17,158.52,464.72,390.96],"n_rows":10,"n_cols":3,"columns":["","Tested Hardware or",""],"rows":[["","Tested Hardware or",""],["Performance Test","","Source/Rationale for test"],["","Software",""],["","",""],["Software verification\nand validation","New or modified software\nfeatures","Guidance for the Content of Premarket\nSubmissions for Software Contained in\nMedical Devices"],["Sample clinical images","New or modified software\nfeatures","Guidance for submission of Premarket\nNotifications for Magnetic Resonance\nDiagnostic Devices"],["Image quality\nassessment by sample\nclinical images","- new / modified pulse\nsequence types.\n- comparison images\nbetween the new / modified\nfeatures and the predicate\ndevice features",""],["Performance bench test","new and modified hardware",""],["Electrical, mechanical,\nstructural, and related\nsystem safety test","System as a whole","- AAMI / ANSI ES60601-1\n- IEC 60601-2-33"],["Electrical safety and\nelectromagnetic\ncompatibility (EMC)","System as a whole","IEC 60601-1-2"]],"caption_candidate":"The following performance testing was conducted on the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p9-t1","doc_id":"K232765","page_num":9,"bbox":[94.17,460.46,499.39,534.36],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for coils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance Diagnostic\nDevices"]],"caption_candidate":"reference devices and can be reused for the subject device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p10-t0","doc_id":"K232765","page_num":10,"bbox":[94.08,85.2,504.12,663.84],"n_rows":7,"n_cols":3,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:"],["Training and Validation data"," TSE: more than 25,000 slices\n HASTE: pre-trained on the\nTSE dataset and refined with\nmore than 10,000 HASTE\nslices\n EPI Diffusion: more than\n1,000,000 slices\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength.","on more than 10,000 high\nresolution 2D images.\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength."],["Test Statistics and Test Results\nSummary","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR) and\nstructural similarity index (SSIM).\nMost importantly, the\nperformance was evaluated by\nvisual comparisons to evaluate\ne.g., aliasing artifacts, image\nsharpness and denoising levels.","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR),\nstructural similarity index (SSIM),\nand perceptual loss. In addition,\nthe feature has been verified\nand validated by inhouse tests.\nThese tests include visual rating\nand an evaluation of image\nsharpness by intensity profile\ncomparisons of reconstructions\nwith and without Deep Resolve\nSharp."],["Equipment","1.5T and 3T MRI systems",""],["Clinical Subgroups","No clinical subgroups have been defined for the collected dataset.",""],["Demographic Distribution","Due to reasons of data privacy, we did not record gender, age and\nethnicity during data collection.",""],["Reference Standard","The acquired datasets (as\ndescribed above) represent the\nground truth for the training and\nvalidation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation and augmentation.\nThis process includes further\nunder-sampling of the data by\ndiscarding k-space lines,\nlowering of the SNR level by\naddition Restricted of noise and\nmirroring of k-space data.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation. k-space data has\nbeen cropped such that only the\ncenter part of the data was used\nas input. With this method\ncorresponding low-resolution\ndata as input and high-resolution\ndata as output / ground truth\nwere created for training and\nvalidation."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p11-t0","doc_id":"K232765","page_num":11,"bbox":[94.08,96.66,504.12,735.72],"n_rows":3,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["Deep Resolve Boost EPI Diffusion","[14_1] Bae SH et al., Clinical feasibility of accelerated\ndiffusion weighted imaging of the abdomen with deep\nlearning reconstruction: Comparison with conventional\ndiffusion weighted imaging, Eur J Radiol., 154 (2022)\n[14_2] Lee EJ et al., Feasibility of deep learning k-\nspace-to-image reconstruction for diffusion weighted\nimaging in patients with breast cancers: Focus on\nimage quality and reduced scan time, Eur J Radiol., 157\n(2022)\n[14_3] Afat S et al., Acquisition time reduction of\ndiffusion-weighted liver imaging using deep learning\nimage reconstruction. Diagn Interv Imaging, (2022).\n[14_4] Benkert T et al., Improved Clinical Diffusion\nWeighted Imaging by Combining Deep Learning\nReconstruction, Partial Fourier, and Super Resolution,\nISMRM (2022)"],["Deep Resolve Boost HASTE","[14_6] Herrmann J et al., Diagnostic Confidence and\nFeasibility of a Deep Learning Accelerated HASTE\nSequence of the Abdomen in a Single Breath-Hold,\nInvestigative Radiology, Volume 56, Number 5, May\n2021.\n[14_7] Shanbhogue K et al. Accelerated single-shot T2-\nweighted fat-suppressed (FS) MRI of the liver with\ndeep learning-based image reconstruction: qualitative\nand quantitative comparison of image quality with\nconventional T2-weighted FS sequence. Eur Radiol.\n2021 May 7.\n[14_8] Herrmann J et al., Development and Evaluation\nof Deep Learning-Accelerated Single-Breath-Hold\nAbdominal HASTE at 3 T Using Variable Refocusing Flip\nAngles. Invest Radiol. 2021 Apr 22.\n[14_9] Han S et al., Evaluation of HASTE T2 weighted\nimage with reduced echo time for detecting focal liver\nlesions in patients at risk of developing hepatocellular\ncarcinoma. Eur J Radiol. 2022 Nov 1;157:110588.\n[14_10] Mule S et al., Fast T2-weighted liver MRI:\nImage quality and solid focal lesions conspicuity using\na deep learning accelerated single breath-hold HASTE\nfat-suppressed sequence. Diagn Interv Imaging. 2022\nOct;103(10):479-485.\n[14_11] Ginocchio LA et al., Accelerated T2-weighted\nMRI of the liver at 3 T using a single-shot technique\nwith deep learning-based image reconstruction:\nimpact on the image quality and lesion detection.\nAbdom Radiol (NY). 2022 Sep 28.\n[14_12] Herrmann J et al., Comprehensive clinical\nevaluation of a deep learning-accelerated, single-"]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232765-p12-t0","doc_id":"K232765","page_num":12,"bbox":[94.08,66.78,504.12,580.32],"n_rows":6,"n_cols":2,"columns":["","breath-hold abdominal HASTE at 1.5 T and 3 T. Acad\nRadiol. 2022 Apr 22:S1076-6332(22)00195-7.\n[14_13] Ichinohe F. et al., Usefulness of Breath-Hold\nFat-Suppressed T2-Weighted Images With Deep\nLearning–Based Reconstruction of the Liver, Invest\nRadiol., 2022"],"rows":[["","breath-hold abdominal HASTE at 1.5 T and 3 T. Acad\nRadiol. 2022 Apr 22:S1076-6332(22)00195-7.\n[14_13] Ichinohe F. et al., Usefulness of Breath-Hold\nFat-Suppressed T2-Weighted Images With Deep\nLearning–Based Reconstruction of the Liver, Invest\nRadiol., 2022"],["GRE_PC","[14_14] Guenthner C. et al. Ristretto MRE: A\ngeneralized multi-shot GRE-MRE sequence. NMR\nBiomed 2019; 32:e4049."],["Ghost reduction (DPG)","[14_24] Hoge WS, Polimeni JR. Dual-polarity GRAPPA\nfor simultaneous reconstruction and ghost correction of\necho planar imaging data. Magn Reson Med. 2016\nJul;76(1):32-44. doi: 10.1002/mrm.25839. Epub 2015"],["Fleet Reference Scan","[14_5] Polimeni JR, Bhat H, Witzel T, Benner T, Feiweier\nT, Inati SJ, Renvall V, Heberlein K, Wald LL. Reducing\nsensitivity losses due to respiration and motion in\naccelerated echo planar imaging by reordering the\nautocalibration data acquisition. Magn Reson Med.\n2016 Feb;75(2):665-79. doi: 10.1002/mrm.25628. Epub\n2015 Mar 23. PMID: 25809559; PMCID: PMC4580494."],["BioMatrix Motion Sensor (SAMER)","[14_25] D. Polak, D N. Splitthoff, etc. Scout accelerated\nmotion estimation and reduction (SAMER). Magn\nReson Med. 2022 Jan;87(1):163-178.\n[14_26] M. Lang, A. Tabari, etc. Clinical Evaluation of\nScout Accelerated Motion Estimation and Reduction\nTechnique for 3D MR Imaging in the Inpatient and\nEmergency Department Settings. American Journal of\nNeuroradiology 2023 Jan."],["Complex Averaging","[14_22] Walsh DO, Gmitro AF, Marcellin MW. Adaptive\nreconstruction\nof phased array MR imagery. Magn Reson Med. 2000\nMay\n1;43(5):682–90.\n[14_23] Kordbacheh H, Seethamraju RT, Weiland E,\nKiefer B, Nickel MD, Chulroek T, et al. Image quality and\ndiagnostic accuracy of complex-averaged high b value\nimages in diffusion-weighted MRI of prostate cancer.\nAbdom Radiol (NY). 2019;44(6):2244–53."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232799-p5-t0","doc_id":"K232799","page_num":5,"bbox":[72.24,124.44,539.76,408.96],"n_rows":5,"n_cols":2,"columns":["Submitter / Primary Contact Person","Monsuru K Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(202) 856-6099"],"rows":[["Submitter / Primary Contact Person","Monsuru K Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(202) 856-6099"],["Secondary Contact Person","Clayton Ginn\nRegulatory Affairs\nclayton.ginn@siemens-healthineers.com\n+1 (865) 898-2692"],["Submitter Address","Siemens Medical Solutions, Inc. USA\nMolecular Imaging\n810 Innovation Drive\nKnoxville, TN 37932\nEstablishment Registration Number: 1034973"],["Legal Manufacturer","Siemens Healthcare GmbH\nSiemensstr 1\nD-91301 Forchheim, Germany\nEstablishment Registration Number: 3004977335"],["Importer/Distributor","Siemens Medical Solutions USA, Inc.\n40 Liberty Boulevard\nMalvern, PA 19355\nEstablishment Registration Number: 2240869"]],"caption_candidate":"1. Identification of the Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232799-p7-t0","doc_id":"K232799","page_num":7,"bbox":[72.04,185.32,539.48,704.04],"n_rows":6,"n_cols":6,"columns":["","Subject Device","","","Predicate Device",""],"rows":[["","Subject Device","","","Predicate Device",""],["","","","","",""],["","syngo.via RT Image Suite","","","syngo.via RT Image Suite",""],["","(software version: SOMARIS/8 VB80)","","","(software version SOMARIS/8 VB70)",""],["","(510(k) number: K232799)","","","(510(k) number: K220783)",""],["syngo.via RT Image Suite is a 3D and 4D image visualization,\nmulti-modality manipulation and contouring tool that helps\nthe preparation of treatments such as, but not limited to\nthose performed with radiation (for example,\nBrachytherapy, Particle Therapy, External Beam Radiation\nTherapy).\nIt provides tools to view existing contours, create, edit,\nmodify, copy contours of regions of the body, such as but\nnot limited to, skin outline, targets and organs-at-risk. It also\nprovides functionalities to create simple geometric\ntreatment plans. Contours, images and treatment plans can\nsubsequently be exported to a Treatment Planning System.\nThe software combines the following digital image\nprocessing and visualization tools:\n• Multi-modality viewing and contouring of anatomical,\nfunctional, and multi-parametric images such as but not\nlimited to CT, PET, PET/CT, MRI, Linac CBCT images\n• Multiplanar reconstruction (MPR) thin/thick, minimum\nintensity projection (MIP), volume rendering technique\n(VRT)\n• Freehand and semi-automatic contouring of regions-of-\ninterest on any orientation including oblique\n• Automated Contouring on CT images\n• Creation of contours on images supported by the\napplication without prior assignment of a planning CT\n• Manual and semi-automatic registration using rigid and\ndeformable registration\n• Supports the user in comparing, contouring, and\nadapting contours based on datasets acquired with\ndifferent imaging modalities and at different time points\n• Supports multi-modality image fusion\n• Visualization and contouring of moving tumors and\norgans\n• Management of points of interest including but not\nlimited to the isocenter\n• Creation of simple geometric treatment plans\n• Generation of a synthetic CT based on multiple pre-\ndefine MR acquisitions","","","syngo.via RT Image Suite is a 3D and 4D image visualization,\nmulti-modality manipulation and contouring tool that helps\nthe preparation of treatments such as, but not limited to\nthose performed with radiation (for example,\nBrachytherapy, Particle Therapy, External Beam Radiation\nTherapy).\nIt provides tools to view existing contours, create, edit,\nmodify, copy contours of regions of the body, such as but\nnot limited to, skin outline, targets and organs-at-risk. It also\nprovides functionalities to create simple geometric\ntreatment plans. Contours, images and treatment plans can\nsubsequently be exported to a Treatment Planning System.\nThe software combines the following digital image\nprocessing and visualization tools:\n• Multi-modality viewing and contouring of anatomical,\nfunctional, and multi-parametric images such as but not\nlimited to CT, PET, PET/CT, MRI, Linac CBCT images\n• Multiplanar reconstruction (MPR) thin/thick, minimum\nintensity projection (MIP), volume rendering technique\n(VRT)\n• Freehand and semi-automatic contouring of regions-of-\ninterest on any orientation including oblique\n• Automated Contouring on CT images\n• Creation of contours on images supported by the\napplication without prior assignment of a planning CT\n• Manual and semi-automatic registration using rigid and\ndeformable registration\n• Supports the user in comparing, contouring, and\nadapting contours based on datasets acquired with\ndifferent imaging modalities and at different time points\n• Supports multi-modality image fusion\n• Visualization and contouring of moving tumors and\norgans\n• Management of points of interest including but not\nlimited to the isocenter\n• Creation of simple geometric treatment plans\n• Generation of a synthetic CT based on multiple pre-\ndefine MR acquisitions","",""]],"caption_candidate":"6. Indications for Use Comparison to the Predicate Device","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K232808-p4-t0","doc_id":"K232808","page_num":4,"bbox":[72.49,484.08,540.42,676.62],"n_rows":7,"n_cols":3,"columns":["Classification Name(s)","Regulation Number","Product Code"],"rows":[["Classification Name(s)","Regulation Number","Product Code"],["Primary","",""],["Ultrasonic Pulsed Doppler Imaging System","21 CFR 892.1550","IYN"],["Secondary","",""],["Ultrasonic Pulsed Echo Imaging System","21 CFR 892.1560","IYO"],["Diagnostic Ultrasound Transducer","21 CFR 892.1570","ITX"],["Medical Image Management and Processing\nSystem","21 CFR 892.2050","QIH"]],"caption_candidate":"Regulation Description:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p5-t0","doc_id":"K232808","page_num":5,"bbox":[72.63,96.78,541.92,203.46],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","Butterfly iQ/iQ+ Ultrasound System"],"rows":[["Device Trade Name:","Butterfly iQ/iQ+ Ultrasound System"],["510(k) Number:","K220068"],["Submitter:","Butterfly Network, Inc."],["Classification Name:","Ultrasonic Pulsed Doppler Imaging System"],["Primary Product Code:","IYN – 21 CFR 892.1550"],["Secondary Product Code(s):","IYO – 21 CFR 892.1560\nITX – 21 CFR 892.1570\nQIH – 21 CFR 892.2050"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p6-t0","doc_id":"K232808","page_num":6,"bbox":[72.27,388.38,540.42,671.94],"n_rows":4,"n_cols":2,"columns":["IEC 60601-1 Ed. 3.2\nen: 2020","Medical Electrical Equipment – Part 1. General\nrequirements for basic safety and essential performance"],"rows":[["IEC 60601-1 Ed. 3.2\nen: 2020","Medical Electrical Equipment – Part 1. General\nrequirements for basic safety and essential performance"],["IEC 60601-1-11 Ed.\n2.1 b:2020","Medical electrical equipment - Part 1-11: General requirements\nfor basic safety and essential performance - Collateral Standard:\nRequirements for medical electrical equipment and medical\nelectrical systems used in the home healthcare environment\nCONSOLIDATED EDITION"],["IEC 60601-1-12 Ed.\n1.1 b:2020","Medical electrical equipment - Part 1-12: General requirements\nfor basic safety and essential performance - Collateral Standard:\nRequirements for medical electrical equipment and medical\nelectrical systems intended for use in the emergency medical\nservices environment CONSOLIDATED EDITION"],["IEC 60601-1-2:\n2014/AMD1:2020","Medical Electrical Equipment – Part 1-2: General requirements\nfor basic safety and essential performance – Collateral\nStandard: Electromagnetic disturbances – Requirements and\ntests"]],"caption_candidate":"methods for evaluating the safe and effective performance of the device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p7-t0","doc_id":"K232808","page_num":7,"bbox":[72.37,71.76,540.24,286.08],"n_rows":5,"n_cols":2,"columns":["IEC 60601-2-37 Ed.\n2.0 b: 2007","Medical Electrical Equipment – Part 2-37. Particular\nrequirements for the basic safety and essential performance of\nultrasonic medical diagnostic and monitoring equipment\nCONSOLIDATED EDITION"],"rows":[["IEC 60601-2-37 Ed.\n2.0 b: 2007","Medical Electrical Equipment – Part 2-37. Particular\nrequirements for the basic safety and essential performance of\nultrasonic medical diagnostic and monitoring equipment\nCONSOLIDATED EDITION"],["ISO 10993-1","Biological evaluation of medical devices — Part 1: Evaluation\nand testing within a risk management process"],["ISO 10993-5","Biological evaluation of medical devices — Part 5: Tests for in\nvitro cytotoxicity"],["ISO 10993-10","Biological evaluation of medical devices — Part 10: Tests for\nirritation and skin sensitization"],["ISO 14971:2019","Application of risk management to medical devices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p7-t1","doc_id":"K232808","page_num":7,"bbox":[104.58,361.32,540.24,397.38],"n_rows":3,"n_cols":2,"columns":["","of the subject hardware and its compatibility with the cleared Butterfly iQ App and to"],"rows":[["","of the subject hardware and its compatibility with the cleared Butterfly iQ App and to"],["its safe and effective performance. Verification and validation testing established that the",""],["meets its design requirements, intended use, and demonstrates substantial equivalence",""]],"caption_candidate":"Relevant non-clinical verification and validation testing was performed to address the","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p7-t2","doc_id":"K232808","page_num":7,"bbox":[72.37,554.94,540.24,700.65],"n_rows":3,"n_cols":4,"columns":["Model","Butterfly iQ3\nUltrasound\nSystem (Subject\nDevice)","Butterfly iQ/iQ+\nUltrasound System\n(K220068,\nPredicate Device)","Comparison"],"rows":[["Model","Butterfly iQ3\nUltrasound\nSystem (Subject\nDevice)","Butterfly iQ/iQ+\nUltrasound System\n(K220068,\nPredicate Device)","Comparison"],["Regulatory Information","","",""],["Regulation Number","892.1550","892.1550","Remains\nUnchanged"]],"caption_candidate":"subject device and the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p8-t0","doc_id":"K232808","page_num":8,"bbox":[72.45,71.61,540.28,681.73],"n_rows":28,"n_cols":8,"columns":["Device Classification\nName","","","","Ultrasonic Pulsed","","Ultrasonic Pulsed","Remains\nUnchanged"],"rows":[["Device Classification\nName","","","","Ultrasonic Pulsed","","Ultrasonic Pulsed","Remains\nUnchanged"],["","","","","Doppler Imaging","","Doppler Imaging",""],["","","","","System","","System",""],["Classification","","","Class II","Class II","Class II","Class II","Remains\nUnchanged"],["Product Codes","","","IYN\nIYO\nITX\nQIH","","IYN\nIYO\nITX\nQIH","","Remains\nUnchanged"],["Intended Use","","","","","","",""],["Intended for use by\nqualified and trained\nhealthcare professionals\nto enable diagnostic\nultrasound imaging and\nmeasurement of\nanatomical structures and\nfluids of adult and\npediatric patients.","","","✔","","✔","","Remains\nUnchanged"],["General Device Description","","","","","","",""],["Hand-held portable\ndiagnostic ultrasound\nsystem.","","","✔","","✔","","Remains\nUnchanged"],["Indications for Use","","","","","","",""],["","","","✔","","","✔","Remains\nUnchanged"],["Abdominal","","","","","","",""],["","","","","","","",""],["","","","✔","","","✔","Remains\nUnchanged"],["Cardiac","","","","","","",""],["","","","","","","",""],["","","","✔","","","✔","Remains\nUnchanged"],["Lung","","","","","","",""],["","","","","","","",""],["","","","✔","","","✔","Remains\nUnchanged"],["","Musculoskeletal","","","","","",""],["","(conventional and","","","","","",""],["","superficial)","","","","","",""],["","","","","","","",""],["","","","✔","","","✔","Remains\nUnchanged"],["","Fetal/Obstetric,","","","","","",""],["","Gynecological","","","","","",""],["","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p9-t0","doc_id":"K232808","page_num":9,"bbox":[72.57,71.86,540.4,704.95],"n_rows":48,"n_cols":6,"columns":["","","","✔","✔","Remains\nUnchanged"],"rows":[["","","","✔","✔","Remains\nUnchanged"],["Peripheral Vessel\n(including carotid, deep\nvein thrombosis, arterial\nstudies)","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Procedural Guidance","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["","Small Organs","","","",""],["","(including thyroid,","","","",""],["","scrotum, and breast)","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Urology","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Opthalmic","","","","",""],["","","","","",""],["","","","","",""],["Imaging Modes/Tools","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["M-Mode","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["B-Mode (2D)","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Color Doppler","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Pulsed Wave Doppler","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["3-D","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Harmonic Imaging","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Fetal Heart Sounds","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["B-mode + Biplane","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["","B-mode + Needle Viz","","","",""],["","Tool","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p10-t0","doc_id":"K232808","page_num":10,"bbox":[72.57,71.86,540.38,663.85],"n_rows":15,"n_cols":7,"columns":["","","","✔","✔","Remains\nUnchanged",""],"rows":[["","","","✔","✔","Remains\nUnchanged",""],["B-mode + Biplane +\nNeedle Viz Tool","","","","","",""],["","","","","","",""],["","","","✔","-","Multi-slice\ncollects and\ndisplays B-\nmode images\nfrom different\nangles\nseparately. This\nnew mode does\nnot change the\nacoustic output\nto the normal\nB-Mode or 3-D\nimage, nor\ndoes it\nintroduce any\nnew questions\nof safety and\neffectiveness.",""],["B-mode + Multi-Slice","","","","","",""],["","","","","","",""],["","","","✔","-","Sweep collects\nand\ncontinuously\ndisplays B-\nmode images\nfrom different\nangles. This\nnew mode does\nnot change the\nacoustic output\nto the normal\nB-Mode or 3-D\nimage, nor\ndoes it\nintroduce any\nnew questions\nof safety and\neffectiveness.",""],["B-mode + Sweep","","","","","",""],["","","","","","",""],["","","","","","",""],["","Transducer","","","","",""],["","","","","","",""],["","","","Single probe 2D\nPhased Array","Single probe\n2D Phased\nArray","Remains\nUnchanged",""],["Type","","","","","",""],["","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p10-t1","doc_id":"K232808","page_num":10,"bbox":[457.83,84.6,505.38,109.92],"n_rows":2,"n_cols":2,"columns":["","Remains"],"rows":[["","Remains"],["Unchange",""]],"caption_candidate":"B-mode + Biplane +","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p10-t2","doc_id":"K232808","page_num":10,"bbox":[438.89,278.28,471.52,302.52],"n_rows":2,"n_cols":2,"columns":["image,",""],"rows":[["image,",""],["","it"]],"caption_candidate":"B-Mode or 3-D","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p10-t3","doc_id":"K232808","page_num":10,"bbox":[438.89,512.64,471.52,536.88],"n_rows":2,"n_cols":2,"columns":["image,",""],"rows":[["image,",""],["","it"]],"caption_candidate":"B-Mode or 3-D","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p11-t0","doc_id":"K232808","page_num":11,"bbox":[72.57,71.86,540.38,714.85],"n_rows":36,"n_cols":4,"columns":["","1.0 - 12 MHz","1.0 - 10 MHz","Similar. The\nsubject device\nremains within the\nboundaries of the\npredicate device\nand does not\nintroduce any new\nquestions of safety\nand effectiveness."],"rows":[["","1.0 - 12 MHz","1.0 - 10 MHz","Similar. The\nsubject device\nremains within the\nboundaries of the\npredicate device\nand does not\nintroduce any new\nquestions of safety\nand effectiveness."],["Frequency","","",""],["","","",""],["","","",""],["Software Features","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Auto B-Lines Counter","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Auto Bladder Volume","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Patient Data Entry","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Patient Database\nand Storage","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Generic\nMeasurement Tools","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Analysis and\nCalculation Packages","","",""],["","","",""],["","✔","✔","Remains\nUnchanged"],["Annotations","","",""],["","","",""],["","","",""],["Other","","",""],["","","",""],["","Adult and Pediatric","Adult and Pediatric","Remains\nUnchanged"],["Target Population","","",""],["","","",""],["","Professional\nhealthcare\nfacilities (e.g.\nHospital, clinic,\nhospice, or\nmedical office),","Professional\nhealthcare facilities\n(e.g. Hospital,\nclinic, hospice, or\nmedical office),\nhome healthcare","Remains\nUnchanged"],["Device Use Settings","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p12-t0","doc_id":"K232808","page_num":12,"bbox":[72.57,71.86,540.42,709.45],"n_rows":28,"n_cols":6,"columns":["","","","home healthcare\nenvironment,\nambulances\nand/or accident\nsites, and other\nenvironments\nwhere healthcare\nis provided. Users\nmay also include\nmedical students\nworking under the\nsupervision or\nauthority of a\nphysician during\ntheir education/\ntraining.","environment,\nambulances and/or\naccident sites, and\nother environments\nwhere healthcare is\nprovided. Users\nmay also include\nmedical students\nworking under the\nsupervision or\nauthority of a\nphysician during\ntheir education/\ntraining.",""],"rows":[["","","","home healthcare\nenvironment,\nambulances\nand/or accident\nsites, and other\nenvironments\nwhere healthcare\nis provided. Users\nmay also include\nmedical students\nworking under the\nsupervision or\nauthority of a\nphysician during\ntheir education/\ntraining.","environment,\nambulances and/or\naccident sites, and\nother environments\nwhere healthcare is\nprovided. Users\nmay also include\nmedical students\nworking under the\nsupervision or\nauthority of a\nphysician during\ntheir education/\ntraining.",""],["","","","","",""],["","","","","",""],["","","","Acoustic will\nmeet\nFDA/AIUM\nguidelines","Acoustic will\nmeet\nFDA/AIUM\nguidelines","Remains\nUnchanged"],["Energy\nused/delivered\n(MI/TI)","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Portable/hand-held","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["Biocompatibility","","","","",""],["","","","","",""],["","","","Products not\nclassified as sterile","Products not\nclassified as sterile","Remains\nUnchanged"],["Sterility","","","","",""],["","","","","",""],["","","","✔","✔","Remains\nUnchanged"],["","Cleaning/Reprocessing","","","",""],["","Methods","","","",""],["","","","","",""],["","","","Meets electrical\nsafety standards\nfor a class II\nmedical device.\nGroup 1\nClass B (CISPR)","Meets electrical\nsafety standards\nfor a class II\nmedical device.\nGroup 1\nClass B (CISPR)","Remains\nUnchanged"],["Electrical safety","","","","",""],["","","","","",""],["","","","Will meet\nmechanical safety\nstandards for a\nclass II medical\ndevice","Will meet\nmechanical safety\nstandards for a\nclass II medical\ndevice","Remains\nUnchanged"],["Mechanical safety","","","","",""],["","","","","",""],["","","","COTS device\ndisplay","COTS device\ndisplay","Remains\nUnchanged"],["Display","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p12-t1","doc_id":"K232808","page_num":12,"bbox":[331.85,290.64,392.16,327.05],"n_rows":3,"n_cols":2,"columns":["Acoustic will",""],"rows":[["Acoustic will",""],["meet",""],["","/AIUM"]],"caption_candidate":"training.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p12-t2","doc_id":"K232808","page_num":12,"bbox":[331.85,618.78,406.63,657.0],"n_rows":3,"n_cols":2,"columns":["","for a"],"rows":[["","for a"],["class II medical",""],["device",""]],"caption_candidate":"mechanical safety mechanical safety Unchanged","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232808-p13-t0","doc_id":"K232808","page_num":13,"bbox":[72.52,71.86,540.31,275.11],"n_rows":15,"n_cols":5,"columns":["","","Battery","Battery","Remains\nUnchanged"],"rows":[["","","Battery","Battery","Remains\nUnchanged"],["Power requirements","","","",""],["","","","",""],["","","✔","✔","Remains\nUnchanged"],["Real-time Image","","","",""],["","","","",""],["","","✔","✔","Remains\nUnchanged"],["Frozen Image","","","",""],["","","","",""],["","","6.0 x 2.1 x 1.4","6.4 x 2.2 x 1.4","Change in size\nof probe"],["","Appx. Probe\ndimensions (L x W x\nD), inches","","",""],["","","","",""],["","","8 oz. probe only","8 oz. probe only","Remains\nUnchanged"],["Appx. Probe Weight, lbs.","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232835-p5-t0","doc_id":"K232835","page_num":5,"bbox":[113.66,67.68,594.12,149.3],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion ONE (TSX-\n306A/3) V10.12 with\nSpectral Imaging\nSystem","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K213504","June 16,\n2022"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232835-p6-t0","doc_id":"K232835","page_num":6,"bbox":[112.76,149.1,567.07,709.66],"n_rows":16,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","Device Name,","","","Aquilion ONE (TSX-308A/3) V1.4","","","Aquilion ONE (TSX-306A/3) V10.12",""],["","Model Number","","","with PIQE Reconstruction System","","","with Spectral Imaging System",""],["","510(k) Number","","","This submission","","","K213504",""],["PIQE Reconstruction\nSystem\n▪ Scan Regions\n▪ Scan Type\n▪ Intensity\n▪ Reconstruction\nimage matrix\n▪ Image thickness\n▪ Reconstruction\nInterval","","","Available\n▪ Cardiac, Abdomen and pelvis (Body)\n▪ Volume scan, Dynamic volume scan,\nHelical scan\n▪ L1 / L2 / L3\n▪ 512 x 512, 1024 x 1024\n▪ 0.5 and 1.0 mm, 2.0 mm (Helical only)\n▪ 0.25 (With option installed), 0.5, 1.0,\n2.0 mm (Helical only)","","","Available\n▪ Cardiac\n▪ Volume scan, Dynamic volume scan\n▪ MILD / STANDARD / STRONG\n▪ 512 x 512\n▪ 0.5 and 1.0 mm\n▪ 0.25 (With option installed) and 0.5\nmm","",""],["Noise reduction\nprocessing","","","▪ Adaptive Iterative Dose Reduction 3D\n(AIDR 3D)\n▪ AIDR 3D Enhanced\n▪ Advanced Intelligent Clear‐IQ Engine\n(AiCE)","","","▪ Adaptive Iterative Dose Reduction 3D\n(AIDR 3D)\n▪ AIDR 3D Enhanced\n▪ Advanced Intelligent Clear‐IQ Engine\n(AiCE)","",""],["Scan modes","","","Conventional scan (Axial Scan)\nVolume, Dynamic volume, Dynamic scan\nHelical scan","","","Conventional scan (S&S, S&V)\nVolume, Dynamic volume scan\nHelical scan","",""],["Positioning Scan","","","Single, Dual,\n3D Landmark Scan","","","Single, Dual,\nS-Helical (3D Landmark Scan)","",""],["Anatomical Landmark\nDetection","","","Available","","","Not Available","",""],["Scan (Rotation) time\n(Some may require\nadditional options)","","","Half scan: (0.15, 0.18, 0.23)\n0.24, 0.275, 0.3, 0.32, 0.35, 0.375, 0.4,\n0.45, 0.5, 0.6, 0.75, 1.0, 1.5, 2.0, 3.0 s","","","Half scan: (0.18, 0.23)\n0.275, 0.3, 0.32, 0.35, 0.375, 0.4, 0.45,\n0.5, 0.6, 0.75, 1.0, 1.5, 2.0, 3.0 s","",""],["Gantry opening\ndiameter (aperture)","","","800 mm in diameter","","","780 mm in diameter","",""],["Wedge filter types","","","Three (3) types:\nSmall, Large, SilverBeam Filter (Dose\nreduction wedge)","","","Three (3) types:\nMedium, Large, SilverBeam Filter (Dose\nreduction wedge)","",""],["Gantry internal\ncameras","","","Available","","","Not Available","",""],["Operating panel\n(Gantry monitor)","","","Operating panel\nTwo operating panels on the front","","","○iStation","",""],["Couch Speed -\nHorizontal","","","0.8 - 450 mm/s","","","0.8 - 300 mm/s","",""],["Image display matrix","","","2428 x 1230 (max.)","","","1024 x 1024 (max.)","",""]],"caption_candidate":"characteristics between the subject and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p6-t0","doc_id":"K232841","page_num":6,"bbox":[53.99,541.25,584.61,581.71],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["Axial3D Insight","Axial Medical Printing Limited","K222745"]],"caption_candidate":"Table 5-1 - Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p7-t0","doc_id":"K232841","page_num":7,"bbox":[54.16,311.0,579.83,704.86],"n_rows":11,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["Device\nManufacturer","Axial Medical Printing Limited","","","Axial Medical Printing Limited","","","N/A"],["Device Name","Axial3D Insight","","","Axial3D Insight","","","N/A"],["Device Trade or\nProprietary\nName","Axial3D Insight","","","Axial3D Insight","","","N/A"],["510(k) Number","K232841","","","K222745","","","N/A"],["Device\nRegulation\nName:","Automated Radiological Image\nProcessing Software","","","Automated Radiological image\nProcessing Software","","","Equivalent"],["Device\nRegulation\nNumber:","21 CFR 892.2050","","","21 CFR 892.2050","","","Equivalent"],["Device Product\nCode:","QIH","","","QIH","","","Equivalent"],["Device\nClassification\nFDA:","Class II","","","Class II","","","Equivalent"],["Indication for\nUse","Axial3DInsight is intended for use\nas a cloud-based service and\nimage segmentation framework\nfor the transfer of DICOM imaging\ninformation from a medical\nscanner to an output file.","","","Axial3DInsight is intended for use\nas a cloud-based service and\nimage segmentation framework\nfor the transfer of DICOM imaging\ninformation from a medical\nscanner to an output file.","","","Equivalent"]],"caption_candidate":"Table 5-2 – Predicate Device Comparison: Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p8-t0","doc_id":"K232841","page_num":8,"bbox":[54.0,89.64,579.81,718.78],"n_rows":4,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["","The Axial3DInsight output file can\nbe used for the fabrication of\nphysical replicas of the output file\nusing additive manufacturing\nmethods.\nThe output file or physical replica\ncan be used for treatment\nplanning.\nThe output file or physical replica\ncan be used for diagnostic\npurposes in the field of orthopedic\ntrauma, orthopedic, maxillofacial,\nand cardiovascular applications.\nAxial3DInsight should be used\nwith other diagnostic tools and\nexpert clinical judgment.","","","The Axial3DInsight output file can\nbe used for the fabrication of\nphysical replicas of the output file\nusing additive manufacturing\nmethods.\nThe output file or physical replica\ncan be used for treatment\nplanning.\nThe output file or physical replica\ncan be used for diagnostic\npurposes in the field of orthopedic\ntrauma, orthopedic, maxillofacial,\nand cardiovascular applications.\nAxial3DInsight should be used\nwith other diagnostic tools and\nexpert clinical judgment.","","",""],["Intended Use","Axial Medical Printing Limited’s,\nAxial3D Insight provides patient\nspecific 1:1 scale replica models,\neither as a digital file or as a 3D\nprinted physical model.\nThe digital file or 3D printed\nphysical model is intended to be\nused in conjunction with the\nDICOM images and expert\nclinical judgement. The\napplications for using the physical\n3D printed physical model as a\npresurgical planning tool are as\nfollows:\nPreoperative planning of surgical\ntreatment options including\nplanning for surgical instruments,\naiding decisions on implants, and\naiding the surgical treatment\nplan., All planning using the 3D\nreplica model should be carried\nout with the assistance of the\nDICOM images\nCommunication with the surgical\nteam to discuss the surgical\ntreatment plan in conjunction with\nDICOM images.\nCommunication with the patient\nto discuss the surgical treatment","","","Axial Medical Printing Limited’s,\nAxial3D Insight provides patient\nspecific 1:1 scale replica models,\neither as a digital file or as a 3D\nprinted physical model.\nThe digital file or 3D printed\nphysical model is intended to be\nused in conjunction with the\nDICOM images and expert\nclinical judgement. The\napplications for using the physical\n3D printed physical model as a\npresurgical planning tool are as\nfollows:\nPreoperative planning of surgical\ntreatment options including\nplanning for surgical instruments,\naiding decisions on implants, and\naiding the surgical treatment\nplan., All planning using the 3D\nreplica model should be carried\nout with the assistance of the\nDICOM images\nCommunication with the surgical\nteam to discuss the surgical\ntreatment plan in conjunction with\nDICOM images.\nCommunication with the patient\nto discuss the surgical treatment","","","Equivalent"]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p9-t0","doc_id":"K232841","page_num":9,"bbox":[54.2,89.64,580.06,447.5],"n_rows":8,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["","plan in conjunction with DICOM\nimages\nEducation tool for surgical\nplanning. The 3D printed physical\nmodel can be used for surgical\nplanning in the following\napplications: orthopedics and\ntrauma, maxillofacial, and\ncardiovascular surgery.","","","plan in conjunction with DICOM\nimages.\nEducation tool for surgical\nplanning. The 3D printed physical\nmodel can be used for surgical\nplanning in the following\napplications: orthopedics and\ntrauma, maxillofacial, and\ncardiovascular surgery.","","",""],["Method of Use","Used in conjunction with other\ndiagnostic tools and expert\nclinical judgement.","","","Used in conjunction with other\ndiagnostic tools and expert\nclinical judgement.","","","Equivalent"],["Environment","Hospital","","","Hospital","","","Equivalent"],["OTC or\nPrescription\nDevice","Prescription Use","","","Prescription Use","","","Equivalent"],["Level of\nConcern /","Moderate","","","Moderate","","","Equivalent:"],["V&V","Complies with FDA Guidance\nRequirement","","","Complies with FDA Guidance\nRequirement","","","Equivalent"]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p10-t0","doc_id":"K232841","page_num":10,"bbox":[54.12,89.64,580.3,711.1],"n_rows":8,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["Volume\nRendering","","","","","","",""],["Regions and\nVolumes of\nInterest (ROI)","Orthopedics / Trauma\nCardiovascular\nCranio- Maxillofacial","","","Orthopedics / Trauma\nCardiovascular\nCranio- Maxillofacial","","","Equivalent"],["Region/volume\nof interest\nmeasurements\nand size\nmeasurements","Yes","","","Yes","","","Equivalent"],["Region/Volume\nQuantification","Yes","","","Yes","","","Equivalent"],["Approved\nPrinters","Formlabs\n• Form 3B\nStratasys\n• J750\n• J5 Medijet\n• J850\n• Origin One\nHP\n• HP580\n• HP540","","","Formlabs\n• Form 3B\nStratasys\n• J750\n• J5 Medijet\nHP\n• HP580\n• HP540","","","Similar"],["Approved\nMaterials","Formlabs\n• Form 3B\no Standard White V4\nFLGPWH04\no Standard Draft V2\nFLDRGR02\no Standard Clear V4\nFLGPCL04\no Flexible 80A V1\nFLFL8001\nStratasys\n• J750\no Agilus,\no VeroBlackPlus,\no VeroClear,","","","Formlabs\n• Form 3B\no Standard White V4\nFLGPWH04\no Standard Draft V2\nFLDRGR02\no Standard Clear V4\nFLGPCL04\no Flexible 80A V1\nFLFL8001\nStratasys\n• J750\no Agilus,\no VeroBlackPlus,\no VeroClear,","","","Similar"]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p11-t0","doc_id":"K232841","page_num":11,"bbox":[53.92,89.64,580.27,714.7],"n_rows":3,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["","o VeroCyan,\no VeroGrey,\no VeroMagenta,\no VeroPureWhite,\no VeroYellow\n• J5 Medijet\no VeroVividTMCyan,\no VeroVividTMMagenta,\no VeroVividTMYellow,\no DraftWhite,\no MED610,\no MED615RGD,\no VeroUltraClearTM\no ElasticoTMClear\n• J850\no VeroVividTMCyan,\no VeroVividTMMagenta,\no VeroVividTMYellow,\no VeroPureWhite\no BoneMatrixTM\no GelMatrixTM\no TissueMatrixTM\no RadioMatrixTM\no Agilus30\no VeroClear\no VeroMagenta\no BlackPlus\n• Origin One\no ORIGIN DM100 by\nBASF\no ORIGIN DM200 by\nBASF\no LOCTITE 3D 3843\no LOCTITE 3D IND405\nHP\n• HP580\no Nylon PA12\n• HP540","","","o VeroCyan,\no VeroGrey,\no VeroMagenta,\no VeroPureWhite,\no VeroYellow\n• J5 Medijet\no VeroVividTMCyan,\no VeroVividTMMagenta,\no VeroVividTMYellow,\no DraftWhite,\no MED610,\no MED615RGD,\no VeroUltraClearTM\no ElasticoTMClear\nHP\n• HP580\no Nylon PA12\n• HP540\no Nylon PA12","","",""]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p12-t0","doc_id":"K232841","page_num":12,"bbox":[53.92,89.64,580.27,138.29],"n_rows":3,"n_cols":8,"columns":["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],"rows":[["Attribute","","Axial3D Insight","","","Axial3D Insight","","Comparison"],["","","(Proposed Device)","","","(Predicate Device K222745)","",""],["","o Nylon PA12","","","","","",""]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p14-t0","doc_id":"K232841","page_num":14,"bbox":[54.3,132.39,522.51,435.46],"n_rows":17,"n_cols":9,"columns":["","","","","Cardiac","","Neuro CT/CTa","Ortho CT","Trauma CT"],"rows":[["","","","","Cardiac","","Neuro CT/CTa","Ortho CT","Trauma CT"],["","","","","CT/CTa","","","",""],["","Number of","","4,838","","","4,041","10,857","19,134"],["","Images Used","","","","","","",""],["","for Validation","","","","","","",""],["","Slice Spacing","","0.4 - 0.8","","","0.44 - 1.0","0.3 - 2.0","0.2 - 2.0"],["","Range","","","","","","",""],["","(Min, Max in","","","","","","",""],["","mm)","","","","","","",""],["","Slice Spacing","","0.54","","","0.63","0.79","0.76"],["","Average","","","","","","",""],["","(in mm)","","","","","","",""],["","Pixel Size","","0.23 - 0.78","","","0.34 - 0.70","0.18 - 0.98","0.22 - 0.98"],["","Range (Min,","","","","","","",""],["","Max in mm)","","","","","","",""],["","Pixel Size","","0.46","","","0.51","0.44","0. 51"],["","Average (mm)","","","","","","",""]],"caption_candidate":"Table 5-3: Software Validation Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p14-t1","doc_id":"K232841","page_num":14,"bbox":[54.3,501.76,522.51,716.38],"n_rows":3,"n_cols":6,"columns":["","Manufacturer","","","Model",""],"rows":[["","Manufacturer","","","Model",""],["GE Medical Systems","","","Lightspeed Pro 16\nLightspeed Pro 32\nRevolution CT\nOptima CT660\nDiscovery CT750 HD","",""],["Siemens","","","SOMATOM Definition Flash\nSOMATOM Definition Edge\nSOMATOM Definition AS\nSOMATOM Definition AS+","",""]],"caption_candidate":"Table 5-4 – Imaging scanner manufactures and models used for the validation datasets","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232841-p15-t0","doc_id":"K232841","page_num":15,"bbox":[54.11,89.78,522.7,347.16],"n_rows":3,"n_cols":2,"columns":["","SOMATOM Perspective\nSOMATOM Force\nSensation 16\nAXIOM-Artis\nEmotion 16"],"rows":[["","SOMATOM Perspective\nSOMATOM Force\nSensation 16\nAXIOM-Artis\nEmotion 16"],["Phillips","IQON Spectral CT\niCT 128\niCT 256\nIngenuity Core 128\nBrilliance 62"],["Toshiba","Aquillon PRIME\nAquillon PRIME SP"]],"caption_candidate":"Special 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p7-t0","doc_id":"K232856","page_num":7,"bbox":[51.44,135.05,775.37,475.26],"n_rows":6,"n_cols":15,"columns":["Specification","","","Subject Device","","","Predicate Device","","","Comparison","","","","Impact to Safety &",""],"rows":[["Specification","","","Subject Device","","","Predicate Device","","","Comparison","","","","Impact to Safety &",""],["","","","","","","","","","","","","","Effectiveness",""],["Device name and\nversion","","","Syngo Carbon Clinicals (VA30A)","","","","Syngo Carbon Space (VA30A)","","New Product","","","NA","NA",""],["","","","","","","","K230561","","","","","","",""],["","Manufacturer","","","Siemens Healthcare GmbH","","","Siemens Healthcare GmbH","","","Same","","","NA",""],["Indications for use","","","Syngo Carbon Clinicals is intended to provide\nadvanced visualization tools to prepare and\nprocess the medical image for evaluation,\nmanipulation and communication of clinical\ndata that was acquired by the medical imaging\nmodalities (for example, CT, MR, etc.)\nThe software package is designed to support\ntechnicians and physicians in qualitative and\nquantitative measurements and in the analysis\nof clinical data that was acquired by medical\nimaging modalities.\nAn interface shall enable the connection\nbetween the Syngo Carbon Clinicals software\npackage and the interconnected software\nsolution for viewing, manipulation,\ncommunication, and storage of medical\nimages.","","","Syngo Carbon Space is a software intended to\ndisplay medical data and to support the review\nand analysis of medical images by trained\nmedical professionals.\nSyngo Carbon Space \"Diagnostic Workspace\"\nis indicated for display, rendering, post-\nprocessing of medical data (mostly medical\nimages) within healthcare institutions, for\nexample, in the field of Radiology, Nuclear\nMedicine and Cardiology.","","","The indications for use of\nSyngo Carbon Clinicals is a\nsubset of the predicate.\nSubject device is used in\nqualitative and quantitative\nmeasurements and in the\nanalysis of clinical data\nwhich is the same as the\npredicate device.\nNote: For our equivalency\ncomparison, the Syngo\nCarbon Space \"Diagnostic\nWorkspace\" shall be\nconsidered since the\nfunctionalities of Syngo\nCarbon Space \"Physician\nAccess\" is not relevant to our\nsubject device scope.\nThe Predicate device\nadditionally also is used for\ndisplay and rendering of\nmedical data.","","","None","",""]],"caption_candidate":"comparison table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p8-t0","doc_id":"K232856","page_num":8,"bbox":[51.39,67.83,775.41,340.36],"n_rows":5,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Contraindications","Syngo Carbon Clinicals is not indicated for\nmammography images for diagnosis in the\nU.S.\nSyngo Carbon Clinicals is not to be used as a\nsole basis for clinical decisions","Syngo Carbon Space \"Diagnostic Workspace\"\nis not intended for diagnosis of digital\nmammography images.\nSyngo Carbon Space \"Diagnostic Workspace\"\nis not intended to be used as a sole basis for\nclinical decisions.","Same","None","",""],["Software\narchitecture","Syngo Carbon Clinicals has architecture that\nis based on a layered pattern where the\nvarious clinical tools/functionality are\ndecomposed into modules/common tools\nwhich provide their individual functionalities.","Syngo Carbon Space is based on a\nclient-server architecture","A client server architecture is\nnot used in the subject device\ndue to the nature of the use\nof the subject device with the\ninterfacing/hosting\napplications.","None","",""],["Image\ncommunication","Syngo Carbon Clinicals relies on the\ninterfacing application for Image\ncommunication.","Standard network protocols like\nTCP/IP and standard communication\nprotocol including DICOM (2016a)\nand non-DICOM objects. Supports\ninterfacing with HL7 (v2.5 / v2.3.1 /v2.3 /\nFHIR R4).","Syngo Carbon Clinicals does\nnot have its own\ncommunication, it relies on\nthe interfacing/hosting\napplication for Image\ncommunication.","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p9-t0","doc_id":"K232856","page_num":9,"bbox":[51.42,67.83,775.39,419.88],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Image display\nalgorithms","• Rendering Tools: Cinematic Insight","• MPR: MPR, MPR Thick,\n• MPR/MPR*\n• MIP: MIP, MIP Thin\n• MinIP View\n• VRT*: Plain VRT, Adapt VRT,\n• VRT Thin, Cinematic VRT (cVRT)\n• Fused View *\n• Invert Image\n* available in in Diagnostic\nWorkspace only","Syngo Carbon Clinicals\nprovides the rendering tool:\nCinematic Insight which is\na combination of the\nAutomatic Organ\nsegmentation and the cVRT\ntechnique of image display\nwhich is available in the\npredicate device.\nThis feature uses a deep\nlearning algorithm for organ\nsegmentation (algorithm that\nwas cleared as part of the\nreference device syngo.via\nRT Image suite (K220783).\nNo changes have been made\nto this algorithm compared\nto the reference device\nThe segmented organ is then\nrendered using the cVRT\ntechnique available in the\npredicate device.","This feature does not\nimpact the safety and\neffectiveness of the\nsubject device as the\nnecessary measures are\ntaken","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p10-t0","doc_id":"K232856","page_num":10,"bbox":[51.42,67.83,775.39,410.88],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Measurement,\nEvaluation/Interpr\netation\nTools","• Oncological evaluation:\no Lesion Quantification\no Assisted Perpendicular Tool\no Lung Nodule Marker\n• Orthopaedic measurements:\no Manual calibration","• Lesion Quantification*\n• Assisted Perpendicular Tool*\n• Automatic Organ Segmentation*\n• Distance (Distance line, Distance Polyline)\n• Angle\n• 2D ROI (Circle, Freehand, Polygonal, Auto\nContour) *\n• 3D VOI (Sphere, Freehand) *\n• Pixel Lens\n• Ranges (Parallel, Radial, Radial Sliced,\nCurved, Spine) *\n• Interactive Tissue Segmentation*\n• Time Curve, Time ROI*\n• SUV Measurement*\n• Automatic Anatomy Labeling (rib, spine) *\n• Next Study/ Previous Study*\n* available in in Diagnostic Workspace only","Lung Nodule Marker tool is\nused to evaluate the lung for\nsuspected lesions across time\npoints.\nManual calibration tool is a\nsimple linear tool, where the\nuser input of measurement is\nrequired for calibration of the\nimage using a known size\ndisplay image/an object of\nknown size is available in the\nimage","This feature does not\nimpact the safety and\neffectiveness of the\nsubject device as the\nnecessary measures are\ntaken","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p12-t0","doc_id":"K232856","page_num":12,"bbox":[51.42,67.83,775.39,177.86],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["","","INDEO2, INDEO3, INDEO4,\nMPEG1, MPEG2, MPEG4, VP8,\nVP9, WMV1, WMV2, WMV3\nText Documents: CDA (XML),\nPDF","","","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p14-t0","doc_id":"K232856","page_num":14,"bbox":[51.38,67.83,775.42,500.4],"n_rows":8,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["","","Client – Mobile device\niPadOS ≥ 14, Safari web browser","","","",""],["Impact on\nImage\nAcquisition\nDevices","None\nSyngo Carbon Clinicals provides advanced\nvisualization tools to prepare and process the\nmedical images and it has no influence on the\nimage acquisition devices","None\nSyngo Carbon Space is a pure viewing\nand/or post-processing software and it\nhas no influence on the image\nacquisition devices","Same","None","",""],["CAD\nFunctionalities","None\nNo automated diagnostic\ninterpretation capabilities like CAD\nare included. All image data are to be\ninterpreted by trained personnel.","None\nNo automated diagnostic\ninterpretation capabilities like CAD\nare included. All image data are to be\ninterpreted by trained personnel.","Same","None","",""],["Clinical\ncondition the\ndevice is\nintended to\ndiagnose, treat,\nor manage","No limitation on the clinical condition\nof the patient","No limitation on the clinical condition\nof the patient","Same","None","",""],["Intended\npatient\npopulation","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","Same","None","",""],["Site of the body\nthe device is\nintended to be\nused","No limitation concerning region of\nbody or tissue type","No limitation concerning region of\nbody or tissue type","Same","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p15-t0","doc_id":"K232856","page_num":15,"bbox":[51.38,67.83,775.42,476.88],"n_rows":7,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Intended use\nenvironment","Syngo Carbon Clinicals offers a wide range\nof tools from the major clinical fields, i.e.\ngeneral radiology, oncology environments.","Syngo Carbon Space “Diagnostic\nWorkspace” is used in Radiology,\nNuclear Medicine and Cardiology\nenvironments (e.g., darkened/ shaded\nrooms).","Same","None","",""],["Intended\nuser(s)","Trained healthcare professionals","Trained healthcare professionals","Same","None","",""],["Device Type","Software application","Software application","Same","None","",""],["Cyber Security","The cybersecurity aspects for Syngo Carbon\nClinicals is handled by the interfacing/hosting\nsystem.","User access control\n• Audit Trail\n• Documentation of system security\ninformation, Network traffic &\nFirewall control\n• Support of virus / malware\nprotection\n• System Hardening (OS level and\nNetwork level)","Syngo Carbon Clinicals\napplications are running as a\npart of the interfacing device.\nThe aspects for cybersecurity\nare assessed and provided to\nthe interfacing application.","None","",""],["Hardware","Hardware is not understood as part of\nthe medical device but needs to\ncomply with the minimum\nrequirements as specified by Syngo\nCarbon Clinicals","Hardware is not understood as part of\nthe medical device but needs to\ncomply with the minimum\nrequirements as specified by Syngo\nCarbon Space","Same","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p16-t0","doc_id":"K232856","page_num":16,"bbox":[51.42,67.83,775.39,195.38],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Graphical user\ninterface","Not offered by Syngo Carbon Clinicals","Yes, with reduced color palette,\nclearer structure, and text labels on\nicons. Floating panels increases the\nuser friendliness as the user can move\nthe panels wherever they are\nconvenient with.","The subject device utilizes\nthe GUI provided by the\ninterfacing application","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p17-t0","doc_id":"K232856","page_num":17,"bbox":[51.42,67.83,775.39,446.4],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Patient\nBrowser","Not offered by Syngo Carbon Clinicals","Search, browse & open data for\ndisplay from syngo.share core &\nremote DICOM nodes\n• Search, browse & open data for\ndisplay from external XDS(-I)\nrepository) **\n• Archive functionality (upload\nmedical data to syngo.share core\nfor archive)\n• Document properties functions\n(metadata modification and\ntagging)\n• Correct & re-arrange functions\n• Restore (trigger fetch from\narchive) functions\n• Distribution, export & sharing\nfunctions\n• Inbox - access to medical data\nshared by other users **\n**available in Physician Access only","NA","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p18-t0","doc_id":"K232856","page_num":18,"bbox":[51.4,67.83,775.41,469.92],"n_rows":4,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Series\nnavigator /\nDocument\nPreview","Not offered by Syngo Carbon Clinicals","Yes, with a fast overview of the\ndisplayed and not displayed data\n(series, images) of the loaded studies,\nidentify not yet seen series/images*,\nquickly identify the relevant\nseries/images for reading, and bring\ndata (timepoints/series/images) into\ndisplay in an efficient manner\n(Drag&Drop).\nStudy / Timepoints are marked with\nindividual colors for better\nidentification.\nThe Series Navigator is called\nDocument Preview for Physician\nAccess.\n* available in in Diagnostic\nWorkspace only","NA","NA","",""],["Findings panel","Not offered by Syngo Carbon Clinicals","Findings panel collects measurements,\nannotations, and graphical objects.\nAdditionally, the user can create new\nfindings, edit findings. It also allows\ncreation of automatic findings.","The subject device utilizes\nthe findings panel provided\nby the interfacing application","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p19-t0","doc_id":"K232856","page_num":19,"bbox":[51.4,67.83,775.41,522.42],"n_rows":4,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Reporting","Not offered by Syngo Carbon Clinicals","No dedicated report creation\nfunctionality supported in Syngo\nCarbon Space.\nStructured findings can be\nautomatically transferred to external\nthird-party reporting system via FHIR\ninterface for creation of structured\nreport content [e.g. (Powerscribe [by\nNuance], SmartReports [by Smart\nReporting)]","The subject device utilizes\nthe Reporting functionality\nprovided by the interfacing\napplication","None","",""],["Image\nArchiving","Not offered by Syngo Carbon Clinicals","Diagnostic Workspace:\nSyngo Carbon Space Diagnostic\nWorkspace does not store data or\nimages.\nCreated results for a study (e.g.\nDICOM PR, SR objects) are stored in\nsyngo.share core in context of the\noriginal study. syngo.share core is\nresponsible for long term archiving of\nthe original study and created results.\nPhysician Access:\nNot applicable since Syngo Carbon\nSpace Physician Access does not\ncreate data or images that is\ntransferred/stored.","The subject device utilizes\nthe archival functionality\nprovided by the interfacing\napplication","None","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232856-p20-t0","doc_id":"K232856","page_num":20,"bbox":[51.39,67.83,775.41,336.4],"n_rows":5,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Annotation\nTool","Not offered by Syngo Carbon Clinicals","• Arrow*\n• Marker*\n• Text\n* available in in Diagnostic\nWorkspace only","The subject device utilizes\nthe annotation functionality\nprovided by the interfacing\napplication","None","",""],["Printing","Not offered by Syngo Carbon Clinicals","Diagnostic workspace:\nStructured findings can be printed on a\npaper printer.\nPhyisican Access:\nProvides printing functionality on a\npaper printer","The subject device utilizes\nthe Printing functionality\nprovided by the interfacing\napplication","None","",""],["Online help\nsystem","Yes, with search, indexing, filtering,\nlibrary function and document\ncollections","Yes, with search, indexing, filtering,\nlibrary function and document\ncollections.","Same","Nonoe","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p7-t0","doc_id":"K232899","page_num":7,"bbox":[72.3,567.56,539.75,712.14],"n_rows":5,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Reference Device",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Reference Device",""],["Device\nManufacturer","","","Siemens","","","Siemens","","","Philips Medical\nSystems MR Finland","",""],["Device Name","","","AI-Rad Companion\nOrgans RT","","","AI-Rad Companion\nOrgans RT","","","MRCAT Pelvis","",""],["","510(k) Number","","","TBD","","","K221305","","","K182888",""],["Indications for\nUse","","","AI-Rad Companion\nOrgans RT is a post-","","","AI-Rad Companion\nOrgans RT is a post-","","","MRCAT Pelvis is a\nsoftware add-on for","",""]],"caption_candidate":"raise different questions of the safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p9-t0","doc_id":"K232899","page_num":9,"bbox":[72.24,72.72,539.81,710.28],"n_rows":8,"n_cols":4,"columns":["","","adult patients are\nconsidered to be valid\ninput.",""],"rows":[["","","adult patients are\nconsidered to be valid\ninput.",""],["Algorithm","Deep Learning","Deep Learning","Machine-learning"],["Segmentation of\nOrgan at Risk in\nthe Anatomic\nRegions","CT: Head & Neck,\nThorax, Abdomen &\nPelvis\nHead & Neck lymph\nnodes\n(166 OAR)\nMR: Pelvis (9 OAR)","CT: Head & Neck,\nThorax, Abdomen &\nPelvis\nHead & Neck lymph\nnodes\n(128 OAR)","Male and female\npelvis, with soft-tissue\ncancer in the\nanatomical pelvic\nregion below L1\nvertebra, including\n(post-operative)\nprostate, rectum, anus,\nbladder and cervix"],["Compatible\nModality","CT & MR Images","CT Images","MR"],["Compatible\nScanner Models","No Limitation on\nscanner model for CT.\nSiemens Healthineers’\ndata only for MR.\nDICOM compliance\nrequired.","No Limitation on\nscanner model,\nDICOM compliance\nrequired.","Ingenia 1.5T and 3.0T\nMR-RT, Ingenia\nAmbition 1.5T MR-RT\nand Ingenia Elition\n3.0T MR-RT"],["Compatible\nTreatment\nPlanning System","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required."],["Contraindications","Adult use only","Adult use only","Adult use only"],["Target\nPopulation","AI-Rad Companion\nOrgans RT is designed\nfor use only in adult\npopulations.\nAI-Rad Companion\nOrgans RT is designed\nfor any patient for\nwhom relevant\nmodality scans are\navailable.","AI-Rad Companion\nOrgans RT is designed\nfor use only in adult\npopulations.\nAI-Rad Companion\nOrgans RT is designed\nfor any patient for\nwhom relevant\nmodality scans are\navailable. More\nspecifically, the\nsoftware is validated\non previously acquired\nCT DICOM volumes\nfor radiation therapy\ntreatment planning,\nincluding, head and","No information\npublicly available"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p10-t0","doc_id":"K232899","page_num":10,"bbox":[72.24,72.72,539.81,709.56],"n_rows":7,"n_cols":4,"columns":["","","neck, thorax, abdomen,\nand pelvis.",""],"rows":[["","","neck, thorax, abdomen,\nand pelvis.",""],["Clinical\ncondition the\ndevice is\nintended to\ndiagnose, treat or\nmanage","Limited to patients\npreviously selected for\nRadiation Therapy.","Limited to patients\npreviously selected for\nRadiation Therapy.","No information\npublicly available"],["Software\nArchitecture","AI-Rad Companion\n(Engine) architecture\nenabling the\ndeployment of AI Rad\nCompanion Organs RT\nusing Edge and in the\nCloud. The UI is\nprovided using a web-\nbased interface.","AI-Rad Companion\n(Engine) architecture\nenabling the\ndeployment of AI Rad\nCompanion Organs RT\nusing Edge and in the\nCloud. The UI is\nprovided using a web-\nbased interface.","No information\npublicly available"],["Deployment\nFeature","Edge & Cloud\nDeployment","Edge & Cloud\nDeployment","No information\npublicly available"],["Organ Templates","Creating, editing and\ndeletion of organ\ntemplates. Customize\npredefined structure\ndatabase with mapping\nto international\nnomenclature schemes.","Creating, editing and\ndeletion of organ\ntemplates. Customize\npredefined structure\ndatabase with mapping\nto international\nnomenclature schemes.","No information\npublicly available"],["Automated\nworkflow","AI-Rad Companion\nOrgans RT\nautomatically\nprocesses input image\ndata and sends the\nresults as DICOM-RT\nStructure Sets to a\nuser-configurable\ntarget node.","AI-Rad Companion\nOrgans RT\nautomatically\nprocesses input image\ndata and sends the\nresults as DICOM-RT\nStructure Sets to a\nuser-configurable\ntarget node.","Automatic contouring"],["Contour\nvisualization and\nediting feature","AI-Rad Companion\nOrgans RT provides\nbasic result preview of\nautomatic\nsegmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","AI-Rad Companion\nOrgans RT provides\nbasic result preview of\nautomatic\nsegmentation results,\nand no editing feature\nof the automatic\nsegmented contour.","No information\npublicly available"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p11-t0","doc_id":"K232899","page_num":11,"bbox":[72.24,72.72,539.81,697.19],"n_rows":5,"n_cols":4,"columns":["Segmentation\nPerformance","MR: The target\nperformance was\nvalidated using 66\ncases to validate the\noverall performance of\nthe MR contouring.\nCT: The target\nperformance was\nvalidated using 414\ncases distributed to\nthree cohorts.\nBoth: To objectively\nevaluate the target\nperformance, the DICE\ncoefficient, the\nabsolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject was equivalent\nto the overall\nperformance compared\nto the predicate,\nreference device and\ncomparable literature\n& devices.","The target performance\nwas validated using\n157 cases distributed to\ntwo cohorts. Cohort A\nis clinical routine\ntreatment planning CT\nand it is split into two\nsub-cohort and Cohort\nB is PET-CT data. To\nobjectively evaluate\nthe target performance,\nthe DICE coefficient,\nthe absolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject and reference\ndevice were equivalent\nas well as the overall\nperformance compared\nto the predicate device.","The mean and standard\ndeviation Dice\ncoefficients, along with\nthe lower 95th\npercentile confidence\nbound were calculated."],"rows":[["Segmentation\nPerformance","MR: The target\nperformance was\nvalidated using 66\ncases to validate the\noverall performance of\nthe MR contouring.\nCT: The target\nperformance was\nvalidated using 414\ncases distributed to\nthree cohorts.\nBoth: To objectively\nevaluate the target\nperformance, the DICE\ncoefficient, the\nabsolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject was equivalent\nto the overall\nperformance compared\nto the predicate,\nreference device and\ncomparable literature\n& devices.","The target performance\nwas validated using\n157 cases distributed to\ntwo cohorts. Cohort A\nis clinical routine\ntreatment planning CT\nand it is split into two\nsub-cohort and Cohort\nB is PET-CT data. To\nobjectively evaluate\nthe target performance,\nthe DICE coefficient,\nthe absolute symmetric\nsurface distance\n(ASSD) and the fail\nrate was evaluated.\nThe segmentation\nperformance of the\nsubject and reference\ndevice were equivalent\nas well as the overall\nperformance compared\nto the predicate device.","The mean and standard\ndeviation Dice\ncoefficients, along with\nthe lower 95th\npercentile confidence\nbound were calculated."],["User Interface –\nResults Preview\n(Confirmation)","Basic visualization\nfunctionality of\noriginal data and\ngenerated contours","Basic visualization\nfunctionality of\noriginal data and\ngenerated contours","No information\npublicly available"],["User Interface\nConfiguration","Configuration UI","Configuration UI","No information\npublicly available"],["Automated\nWorkflow to TPS","Results send to\nConfirmation UI &\nOptional bypassing of\nConfirmation UI to\nTPS","Results send to\nConfirmation UI &\nOptional bypassing of\nConfirmation UI to\nTPS","No information\npublicly available"],["Human Factors","Design to be used by\ntrained clinicians.","Design to be used by\ntrained clinicians.","Designed to be used by\ntrained clinicians"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p12-t0","doc_id":"K232899","page_num":12,"bbox":[83.36,306.3,528.62,668.5],"n_rows":9,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-129","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices","62366-1 Ed\n1.1 2020-06\nCV","","","IEC","",""],["5-125","General","Medical Devices –\napplication of risk\nmanagement to medical\ndevices","14971:2019-\n12","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle\nprocesses [Including\nAmendment 1 (2016)]","62304 Ed 1.1\n2015-06 CV","","","AAMI\nANSI\nIEC","",""],["12-349","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 – 3.20\n2022d","","","NEMA","",""],["5-134","General","Medical devices – symbols\nto be used with information\nto be supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","","","ISO\nIEC","",""],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","","","IEC","",""]],"caption_candidate":"following voluntary FDA recognized Consensus Standards listed in Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p14-t0","doc_id":"K232899","page_num":14,"bbox":[72.31,72.87,539.76,236.3],"n_rows":2,"n_cols":6,"columns":["","Validation Testing Subject","","","Acceptance Criteria",""],"rows":[["","Validation Testing Subject","","","Acceptance Criteria",""],["MR Contouring Organs","","","• The average segmentation accuracy (Dice\nvalue) of all subject device organs should\nbe equivalent or better than the overall\nsegmentation accuracy of the predicate\ndevice\n• The overall fail rate for each\norgan/anatomical structure is smaller than\n15%","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p14-t1","doc_id":"K232899","page_num":14,"bbox":[67.55,268.16,539.76,408.14],"n_rows":5,"n_cols":13,"columns":["","AI-Rad Companion Organs RT VA50A","","","","","","","","","","",""],"rows":[["","AI-Rad Companion Organs RT VA50A","","","","","","","","","","",""],["","(MR Contouring)","","","","","","","","","","",""],["","Dice [%]","","","","","ASSD [mm]","","","","","Fail [%]",""],["Avg","","Std","95 % CI\nBootstrap","","Avg","","Std","95 % CI\nBootstrap","","2.75","",""],["85.75","","6.48","[82.85, 87.58]","","1.25","","1.28","[0.95, 2.02]","","","",""]],"caption_candidate":"Table 3: Acceptance Criteria of AIRC Organs RT VA50","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p14-t2","doc_id":"K232899","page_num":14,"bbox":[72.31,438.28,531.01,533.14],"n_rows":4,"n_cols":9,"columns":["","","","","Dice % Average","","","95% CI",""],"rows":[["","","","","Dice % Average","","","95% CI",""],["AI-Rad Companion Organs RT VA50 – all organs","","","86","","","(83-88)","",""],["AI-Rad Companion Organs RT VA50 – common\norgans","","","82","","","(78-84)","",""],["MRCAT Pelvis (K182888) – all organs","","","77","","","(75-79)","",""]],"caption_candidate":"Table 4: Performance results of subject device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p14-t3","doc_id":"K232899","page_num":14,"bbox":[72.31,568.75,522.02,708.42],"n_rows":11,"n_cols":30,"columns":["Organ Name","","No.","","","Dice (%)","","","","","","","","","","","","","ASSD (mm)","","","","","","","","","","",""],"rows":[["Organ Name","","No.","","","Dice (%)","","","","","","","","","","","","","ASSD (mm)","","","","","","","","","","",""],["","","Study","","","AVG","","","STD","","","MED","","","95%CI","","","","AVG","","","STD","","","MED","","","95%CI","",""],["Bladder","36","","","91.32","","","6.85","","","93.48","","","(87.69","","92.87)","","0.91","","","1.82","","","0.43","","","(0.54","","2.09)",""],["Rectum","36","","","84.87","","","6.21","","","86.61","","","(82.56","","86.67)","","1.32","","","1.64","","","0.74","","","(0.97","","2.23)",""],["Anal Canal","36","","","75.78","","","7.43","","","77.43","","","(73.17","","78.04)","","1.19","","","0.65","","","1.01","","","(1.0","","1.44)",""],["Penile Bulb","36","","","82.29","","","6.89","","","82.61","","","(79.82","","84.46)","","0.55","","","0.46","","","0.41","","","(1.27","","4.77)",""],["Seminal Vesicle","36","","","66.08","","","18.65","","","72.97","","","(57.19","","71.3)","","2.06","","","3.63","","","1.1","","","(1.27","","4.77)",""],["Prostate","36","","","84.76","","","5.32","","","85.68","","","(82.59","","86.44)","","0.94","","","0.62","","","0.78","","","(0.78","","1.27)",""],["Femur Right","30","","","94.29","","","2.21","","","94.63","","","(92.94","","94.82)","","1.1","","","0.45","","","1.03","","","(0.99","","1.37)",""],["Femur Left","30","","","94.38","","","2.88","","","95.01","","","(92.68","","95.09)","","1.06","","","0.52","","","0.99","","","(0.94","","1.36)",""],["Body","30","","","98.01","","","1.88","","","98.89","","","(97.0","","98.49)","","2.12","","","1.74","","","1.2","","","(1.6","","2.88)",""]],"caption_candidate":"Table 5: Performance results of subject device compared to the reference device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p15-t0","doc_id":"K232899","page_num":15,"bbox":[72.25,119.22,545.05,311.12],"n_rows":9,"n_cols":5,"columns":["","","","T1 Dixon W","T2 W TSE"],"rows":[["","","","T1 Dixon W","T2 W TSE"],["","","","",""],["# of Datasets","","","30","36"],["Data Origin","","","USA: 15\nEU:15","USA: 25\nEU: 11"],["Age","","","22 years and older","22 years and older"],["Manufacturer","","","Siemens Healthineers","Siemens Healthineers"],["Annotated Organs","","","Body\nFemoral Head Right\nFemoral Head Left","Anal Canal, Prostate, Rectum, Penile\nBulb, Seminal Vesicle, Bladder"],["Slice Thickness","","","< 4mm","< 4mm"],["Field Strength","","","1.5T: 19\n3.0T: 11","1.5T: 14\n3.0T: 22"]],"caption_candidate":"Table 6: Detailed Performance Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p15-t1","doc_id":"K232899","page_num":15,"bbox":[72.25,345.8,545.05,536.32],"n_rows":8,"n_cols":6,"columns":["","","","T1 VIBE/Dixon W","T2 W TSE","Prostate (T2W)"],"rows":[["","","","T1 VIBE/Dixon W","T2 W TSE","Prostate (T2W)"],["","","","","",""],["# of Datasets","","","219","225","960"],["Data Origin","","","USA: 59\nEU:160","USA: 225","USA & EU"],["Age","","","22 years and older","22 years and older","62 (average)"],["Manufacturer","","","Siemens Healthineers","Siemens Healthineers","Siemens Healthineers"],["Annotated\nOrgans","","","Body\nFemoral Head Right\nFemoral Head Left","Anal Canal, Rectum,\nPenile Bulb, Seminal\nVesicle, Bladder","Prostate"],["Field\nStrength","","","1.5T: 59\n3.0T: 160","1.5T: 83\n3.0T: 142","1.5T & 3.0T"]],"caption_candidate":"Table 7: Validation Testing Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p16-t0","doc_id":"K232899","page_num":16,"bbox":[72.25,208.04,539.77,446.14],"n_rows":3,"n_cols":6,"columns":["","Validation Testing Subject","","","Acceptance Criteria",""],"rows":[["","Validation Testing Subject","","","Acceptance Criteria",""],["Organs in Predicate Device","","","• All the organs segmented in the predicate\ndevice are also segmented in the subject\ndevice\n• The average (AVG) Dice score difference\nbetween the subject and predicate device\nis smaller than 3%","",""],["New Organs for Subject Device","","","• Baseline value defined by subtracting the\nreference value using 5% error margin in\ncase of Dice and 0.1 mm in case of ASSD\n• The subject device in the selected reference\nmetric has a higher value than the defined\nbaseline value.","",""]],"caption_candidate":"smaller than 3%.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p16-t1","doc_id":"K232899","page_num":16,"bbox":[72.25,477.82,527.02,699.96],"n_rows":6,"n_cols":4,"columns":["","Dice (%)","",""],"rows":[["","Dice (%)","",""],["","Avg","Std","95% CI"],["Head & Neck","76.5","12.8","[70.9, 80.8]"],["Head & Neck lymph\nnodes","69.2","9.5","[65.7. 72.5]"],["Thorax","82.1","8.4","[79.6, 83.9]"],["Abdomen","88.3","8.3","[80.9, 92.2]"]],"caption_candidate":"Table 3: Acceptance Criteria of AIRC Organs RT VA50","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p17-t0","doc_id":"K232899","page_num":17,"bbox":[77.64,80.83,516.64,705.04],"n_rows":49,"n_cols":14,"columns":["Pelvis","","","84.","0","","","6.5","","","[80.","7, 86.7","]",""],"rows":[["Pelvis","","","84.","0","","","6.5","","","[80.","7, 86.7","]",""],["","","","","","","","","","","","","",""],["able 4: Perform","a","nce su","mmary o","f the sub","ject dev","ice CT c","ontouring","","","","","",""],["","","","","","","","","","","","","",""],["Organ Name","","","No.","Dice (%)","","","","","ASSD (m","m)","","",""],["","","","","AVG","STD","MED","95%CI","","AVG","STD","MED","95%CI",""],["Duodenum","","","76","77.3","10.4","79.7","[74.5,","79.3]","2.6","2","1.9","[2.2,","3.1]"],["Large Bowel","","","102","89.6","4.5","90.8","[88.7,","90.4]","2.1","2.6","1.4","[1.8,","2.9]"],["Sigmoid","","","74","79.9","10.6","82.2","[77.2,","82.1]","3.8","3.3","2.6","[3.1,","4.7]"],["Small Bowel","","","76","88.5","4.2","89.3","[87.4,","89.4]","1.3","0.7","1.1","[1.1,","1.5]"],["Uterus","","","25","87.8","4.2","87.8","[85.7,","89.1]","1.7","1.1","1.5","[1.4,","2.4]"],["Penile Bulb","","","30","74","9.1","75.5","[70.5,","77.0]","1.7","0.7","1.6","[1.4,","1.9]"],["Left Cochlea","","","25","74.8","16.1","77.8","[62.3,","78.6]","0.6","1.3","0.4","[0.3,","1.7]"],["Right Cochlea","","","25","79.9","4.8","81.7","[77.9,","81.7]","0.3","0.1","0.3","[0.3,","0.4]"],["Inferior Pharyng","e","al","","","","","","","","","","",""],["Constrictor Mus","c","le","30","78.2","4.8","78.6","[76.4,","79.9]","0.8","0.3","0.7","[0.7,","0.9]"],["Middle Pharyng","e","al","","","","","","","","","","",""],["Constrictor Mus","c","le","30","67.2","7.5","68.3","[64.4,","69.8]","0.9","0.3","0.8","[0.8,","1.1]"],["Superior Pharyn","g","eal","","","","","","","","","","",""],["Constrictor Mus","c","le","30","66.1","5.5","66.7","[64.1,","68.0]","0.8","0.2","0.8","[0.8,","0.9]"],["Thyroid","","","30","84.4","3.4","84.4","[83.2,","85.6]","0.7","0.2","0.7","[0.6,","0.7]"],["Pancreas","","","31","68.4","13.6","72.8","[62.9,","72.6]","3.5","2.5","2.7","[2.8,","4.6]"],["Stomach","","","31","90.7","4.2","91.6","[88.9,","92.0]","2","1.6","1.5","[1.6,","2.8]"],["Left Anterior","","","","","","","","","","","","",""],["Descending","","","","","","","","","","","","",""],["Coronary Artery","","","57","47.6","9.7","47.6","[45.1,","50.1]","4.1","3.8","2.9","[3.4,","5.4]"],["Left Atrium","","","57","86.1","4.8","86.9","[84.7,","87.2]","1.8","0.8","1.6","[1.6,","2.0]"],["Left Ventricle","","","","","","","","","","","","",""],["Endocardium","","","57","83.6","5.3","84.5","[81.9,","84.7]","2.3","0.8","2.2","[2.1,","2.5]"],["Left Ventricle","","","57","85.9","4.1","86.8","[84.8","86.9]","2.7","0.9","2.5","[2.5","2.9]"],["Right Atrium","","","57","79.5","8.8","80.9","[76.6,","81.3]","2.7","1.3","2.4","[2.4,","3.1]"],["Right Ventricle","","","57","83.4","3.4","84.2","[82.5,","84.3]","2.3","0.6","2.2","[2.2,","2.5]"],["Left Chest Wall","","","28","92.3","1.5","92.3","[91.7,","92.8]","1","0.2","0.9","[0.9,","1.1]"],["Right Chest Wal","l","","28","92.6","1.2","92.5","[92.1,","93.1]","0.9","0.2","1","[0.9,","1.0]"],["Inferior Vena Ca","v","a","27","76.2","12.6","80","[70.2,","80.1]","2","1.7","1.5","[1.6,","3.0]"],["Proximal Bronch","u","s","27","84.2","5","85.6","[81.8,","85.7]","1.1","0.4","1.1","[1.0,","1.3]"],["Pulmonary Arte","ry","","27","80","5.7","80.3","[77.4,","81.8]","2.3","0.9","2","[2.0,","2.7]"],["Spinal Canal","","","27","85.2","7.1","87.9","[81.0,","87.1]","1.3","2.2","0.7","[0.8,","2.9]"],["Superior Vena C","a","va","27","79","6.8","80.6","[76.0,","81.2]","1.5","0.8","1.3","[1.3,","1.9]"],["Trachea","","","27","88.7","4.5","89.7","[86.6,","90.1]","1","0.5","0.8","[0.8,","1.2]"],["Left Axilla Level","I","","24","81.5","5.4","82.7","[78.8,","83.3]","2.6","1.4","2","[2.2,","3.3]"],["Left Axilla Level","II","","24","79.2","6.7","80.3","[76.2,","81.6]","1.8","0.7","1.7","[1.6,","2.2]"],["Left Axilla Level","II","I","24","75.4","4.1","75.6","[73.8,","77.1]","1.5","0.4","1.5","[1.3,","1.6]"],["Left Internal","","","","","","","","","","","","",""],["Mammary","","","24","58.6","8","60.5","[55.2,","61.6]","1.9","1.4","1.3","[1.4,","2.5]"],["Left Supraclavic","ul","ar","24","79.5","8.3","81.8","[75.3,","82.2]","2","1.1","1.8","[1.7,","2.6]"],["Right Axilla Leve","l","I","24","80","7.1","82.3","[76.6,","82.4]","3","2.5","2.2","[2.3,","4.7]"],["Right Axilla Leve","l","II","24","77.6","6.9","77","[75.0,","80.4]","2","0.7","2.1","[1.7,","2.3]"],["Right Axilla Leve","l","III","24","75.9","7.6","77.4","[71.7,","78.3]","1.6","1","1.3","[1.4,","2.2]"]],"caption_candidate":"Pelvis 84.0 6.5 [80.7, 86.7]","well_formed":true,"extraction_settings":"text"}
{"table_id":"K232899-p18-t0","doc_id":"K232899","page_num":18,"bbox":[72.25,72.72,522.04,122.58],"n_rows":2,"n_cols":12,"columns":["Right Internal\nMammary","24","62.6","9.4","64.1","[56.8,","65.3]","1.6","1.4","1.1","[1.2,","2.4]"],"rows":[["Right Internal\nMammary","24","62.6","9.4","64.1","[56.8,","65.3]","1.6","1.4","1.1","[1.2,","2.4]"],["Right\nSupraclavicular","24","79.7","6.7","80.9","[76.2,","81.8]","2","0.9","1.7","[1.7,","2.5]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p18-t1","doc_id":"K232899","page_num":18,"bbox":[72.25,168.38,539.79,588.52],"n_rows":9,"n_cols":6,"columns":["","","","Cohort A","Cohort B","Cohort C"],"rows":[["","","","Cohort A","Cohort B","Cohort C"],["","","","","",""],["# of Datasets","","","73","40","301"],["# of Clinical Sites","","","3\n(Germany: 14, Brazil: 59)","4\n(Canada: 40)","25\n(NA: 165, EU: 44, Asia:\n33, SA: 19, Australia:\n28, Unknown: 12)"],["Sex","","","Male: 48\nFemale: 25","Male: 19\nFemale: 21","Male: 53\nFemale: 50\nUnknown: 198"],["Age","","","<30 : 0\n30 – 50: 0\n50 – 70: 4\n>= 70: 4\nUnknown: 110\n*unknown due to data\nminimization on\ncustomer site","<30: 0\n30 – 50: 3\n50 – 70: 25\n>70: 12",""],["Manufacturer","","","Siemens: 73","GE: 18\nPhilips: 22","Siemens: 53\nGE: 59\nPhilips: 119\nVarian: 44\nOthers: 26"],["Body Region","","","Head & Neck: 24\nThorax & Abdomen: 20\nPelvis: 29","Head & Neck: 40","Head & Neck: 50\nThorax: 81\nAbdomen: 115\nPelvis: 55"],["Slice Thickness","","","<= 1: 4\n1 – 2: 48\n2 – 3 : 20\n>3: 1","<= 1: 0\n1 – 2: 6\n2 – 3 : 31\n>3: 3","<= 1: 15\n1 – 2: 153\n2 – 3 : 118\n>3: 15"]],"caption_candidate":"Table 5: Detailed Performance evaluation of the new organs in the subject device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p18-t2","doc_id":"K232899","page_num":18,"bbox":[72.25,615.55,539.79,712.44],"n_rows":6,"n_cols":9,"columns":["","Organ Group","","","No. Training","","","No. Validation",""],"rows":[["","Organ Group","","","No. Training","","","No. Validation",""],["Cochlea","","","215","","","24","",""],["Thyroid","","","293","","","56","",""],["Constrictor Muscles","","","335","","","89","",""],["Chest Wall","","","48","","","12","",""],["LN Supraclavicular, Axilla Levels,\nInternal Mammaries","","","228","","","28","",""]],"caption_candidate":"Table 7: Validation Testing Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232899-p19-t0","doc_id":"K232899","page_num":19,"bbox":[72.24,72.72,539.81,211.04],"n_rows":8,"n_cols":3,"columns":["Duodenum, Bowels, Sigmoid","332","84"],"rows":[["Duodenum, Bowels, Sigmoid","332","84"],["Stomach","371","92"],["Pancreas","369","92"],["Pulmonary Artery, Vena Cava,\nTrachea, Spinal Canal, Proximal\nBronchus","113","34"],["Ventricles & Atriums","706","273"],["Descending Coronary Artery","252","45"],["Penile Bulb","854","213"],["Uterus","381","94"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232923-p4-t0","doc_id":"K232923","page_num":4,"bbox":[49.8,406.08,557.94,546.87],"n_rows":5,"n_cols":3,"columns":["DeviceTradename:","EthosTreatmentManagement,version3.0","EthosTreatmentPlanning,version2.0"],"rows":[["DeviceTradename:","EthosTreatmentManagement,version3.0","EthosTreatmentPlanning,version2.0"],["Commonname:","Treatmentplanandimagemanagement\napplication","Treatmentplanningsystem"],["Classificationname:","Medicalchargedparticleradiationtherapy\nsystem\n(21CFR892.5050)","Medicalchargedparticleradiationtherapy\nsystem\n(21CFR892.5050)"],["Regulatoryclass:","ClassII","ClassII"],["Productcode:","IYE","MUJ"]],"caption_candidate":"review.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232923-p5-t0","doc_id":"K232923","page_num":5,"bbox":[49.8,327.87,557.94,465.38],"n_rows":2,"n_cols":3,"columns":["IntendedUse:","EthosTreatmentManagementisusedto\nmanageandmonitorradiationtherapy\ntreatmentplansandsessions;itisintendedto\nbeusedwithatreatmentplanningsystem.\n(Sameaspredicate)","EthosTreatmentPlanningisusedtogenerate\nandmodifyradiationtherapytreatmentplans.\n(Sameaspredicate)"],"rows":[["IntendedUse:","EthosTreatmentManagementisusedto\nmanageandmonitorradiationtherapy\ntreatmentplansandsessions;itisintendedto\nbeusedwithatreatmentplanningsystem.\n(Sameaspredicate)","EthosTreatmentPlanningisusedtogenerate\nandmodifyradiationtherapytreatmentplans.\n(Sameaspredicate)"],["Indicationsfor\nUse:","EthosTreatmentManagementisindicatedfor\nuseinmanagingandmonitoringtreatment\nplansandsessions.\n(Sameaspredicate)","EthosTreatmentPlanningisindicatedforusein\ngeneratingandmodifyingradiationtherapy\ntreatmentplans.\n(Sameaspredicate)"]],"caption_candidate":"V. INTENDEDUSEANDINDICATIONSFORUSE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232923-p6-t0","doc_id":"K232923","page_num":6,"bbox":[98.93,600.1,517.87,720.53],"n_rows":2,"n_cols":2,"columns":["ValidationCharacteristic","AsappliedintheSubjectDevice:"],"rows":[["ValidationCharacteristic","AsappliedintheSubjectDevice:"],["CharacterizationofModel\nPerformance","Organsaredetectedonthepatientimageviaartificialintelligence\n(AI)segmentationmodels.Thesemodelsconsistofconvolutional\nneuralnetworks,theweightsofwhicharestatic.Theyarenot\nadaptedduringtheoperationoftheproduct.Thatmeans,the\nmodelsdonotcontinuouslylearnandthusdonotaltertheir\nbehaviorovertimebasedonuserinput."]],"caption_candidate":"ThefollowingaredetailsonthevalidationcharatseristicsfortheAImodels:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232923-p7-t0","doc_id":"K232923","page_num":7,"bbox":[99.41,73.9,521.82,720.77],"n_rows":3,"n_cols":2,"columns":["","TheAImodelsoperateonimageresolutionsthataresuitablefor\nrepresentationoftheorganstheyweretrainedfor.Patientimages\narere sampledbeforeinference(runningthedetectionnetwork).\nAfterinference,theresultinglabelmapsaresampledbackontothe\npatientimagegrid.\nContouringperformanceundergoesrigorousevaluationthrough\nverificationandvalidationprocesses.Theverificationprocessaims\ntoidentifyeligiblemodelsforsubsequentvalidation.Thisinitial\nstagereliesonquantitativemetricssuchastheDICEsimilarity\ncoefficient.TheDICEcoefficientservesasacomparisonbenchmark\nagainstreferencespublishedintheliterature,especiallywhen\nintroducingamodelforaneworgan.Incasesofmodelreplacement,\nDICEiscomputedtoensurenon regressionwithrespecttomodels\nalreadyinproduction.\nThevalidationprocessemulatestheusageoftheautocontouring\nsolutioninclinicalpractice.Experts,includingradiationoncologists,\ndosimetrists,andphysicistsfromvarioushealthcarefacilities\nworldwide,evaluatedthequalityofthecontoursacrosstestsetsto\nassesstheneedandthetypeofcontouradjustments,which\nconsequentlygivesanestimateofthetimesavedoncontouring\ntasks.Modelswereonlyconsideredeligibleforproductionifthey\nconsistentlyproducedcontoursthatneededminororno\nadjustmentsinatleast80%ofthetestcases."],"rows":[["","TheAImodelsoperateonimageresolutionsthataresuitablefor\nrepresentationoftheorganstheyweretrainedfor.Patientimages\narere sampledbeforeinference(runningthedetectionnetwork).\nAfterinference,theresultinglabelmapsaresampledbackontothe\npatientimagegrid.\nContouringperformanceundergoesrigorousevaluationthrough\nverificationandvalidationprocesses.Theverificationprocessaims\ntoidentifyeligiblemodelsforsubsequentvalidation.Thisinitial\nstagereliesonquantitativemetricssuchastheDICEsimilarity\ncoefficient.TheDICEcoefficientservesasacomparisonbenchmark\nagainstreferencespublishedintheliterature,especiallywhen\nintroducingamodelforaneworgan.Incasesofmodelreplacement,\nDICEiscomputedtoensurenon regressionwithrespecttomodels\nalreadyinproduction.\nThevalidationprocessemulatestheusageoftheautocontouring\nsolutioninclinicalpractice.Experts,includingradiationoncologists,\ndosimetrists,andphysicistsfromvarioushealthcarefacilities\nworldwide,evaluatedthequalityofthecontoursacrosstestsetsto\nassesstheneedandthetypeofcontouradjustments,which\nconsequentlygivesanestimateofthetimesavedoncontouring\ntasks.Modelswereonlyconsideredeligibleforproductionifthey\nconsistentlyproducedcontoursthatneededminororno\nadjustmentsinatleast80%ofthetestcases."],["NumberofPatientsand\nSamplesinDataset","Forthetrainingdatasets,avarietyofsubjectsandscanswereused\naccordingtothebodysiteofinterest.Theoveralltotalnumberof\ntrainingscansusedwas4769,whilethetotalfortestingscanswas\n1045.Thesescansconsistedofthefollowingbodysiteswiththe\nrespectivepatientcount(#,inclusiveoftrainingandtesting\nsubjects):fullbody(179),headandneck(1173),thorax(600),\nabdomen(527),bowel(507),andpelvis(1192)."],["Demographic,clinical\nsubgroups,andconfounding\ndetails","Thescansareobtainedfromdifferentpatientsubgroupswhichare\nprimarilycomprisedofthosewithtreatmentindicationsforcancers\n(assortedtumors,braincancer,lungcancer,breastcancer,liver\ncancer,pancreaticcancer,stomachcancer,adrenalcancer,bladder\ncancer,prostatecancer,cervicalcancer,vaginalcancer,uterus\ncancer,rectalcancer,analcancer,and/orspinalcancer).Somescans\ncamefrompost prostatectomyorpost hysterectomysourcing.\nPatientdemographicsfromalargeportionofthescansare\nanonymized,butthelargestnumberandpercentageproportionally\nofscansoriginatedfrompatientsintheUnitedStates.\nOtherconfoundingdetailsintheimagesusedtotrainandtest\nmodelswouldincludecontrastingagents,catheters,radioactive\nseeds,compressiondevices,externaldevices(tracheostomytubes),\nbreastimplants,teethimplants,and/orradiotherapymasks."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p5-t0","doc_id":"K232928","page_num":5,"bbox":[72.0,521.04,594.0,638.52],"n_rows":3,"n_cols":4,"columns":["Area of\nComparison","Subject Device-\nDeepContour","Primary-AI-Rad CAI-\nRad Companion Organs\nRT (K221305) Siemens","Reference-Contour\nProtégéAI(K223774)\nMIM Software"],"rows":[["Area of\nComparison","Subject Device-\nDeepContour","Primary-AI-Rad CAI-\nRad Companion Organs\nRT (K221305) Siemens","Reference-Contour\nProtégéAI(K223774)\nMIM Software"],["Regulation\nNumber/code","21 CFR 892.2050|QKB","22 CFR 892.2050|QKB","21 CFR 892.2050|QKB"],["Regulation Name","Medical Image Management\nAnd Processing System","Medical Image Management\nAnd Processing System","Medical Image\nManagement And\nProcessing System"]],"caption_candidate":"Table 1. Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p8-t0","doc_id":"K232928","page_num":8,"bbox":[72.0,220.2,594.0,655.8],"n_rows":7,"n_cols":4,"columns":["Algorithm","Deep Learning","Deep Learning","Machine-learning"],"rows":[["Algorithm","Deep Learning","Deep Learning","Machine-learning"],["Segmentation of\nOrgan at Risk in\nthe Anatomic\nRegions","Head & Neck, Thorax,\nAbdomen & Pelvis\n(82 OARs)","H e a d & N e ck, Thorax,\nAbdomen & Pelvis\nHead & Neck lymph\nnodes\n(108 OAR)","Head & Neck,Prostate,\nThorax, Abdomen, Lungs\n& Liver, MRT structures\n(spleen, pelvic lymph\nnodes, descending\naorta, bone)"],["Compatible\nModality","CT Images","CT Images","CT & MR"],["Compatible\nScanner Models","No Limitation on scanner\nmodel,\nDICOM compliance required.","No Limitation on scanner\nmodel,\nDICOM compliance\nrequired.","No Limitation on scanner\nmodel,\nDICOM compliance\nrequired."],["Compatible\nTreatment\nPlanning System","No Limitation on TPS model,\nDICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required.","No Limitation on TPS\nmodel, DICOM\ncompliance required."],["Contraindications","Adult use only","Adult use only","Adult use only"],["Target\nPopulation","DeepContour is designed for\nuse only in adult populations\nfor whom relevant modality\nscans , including head and\nneck, thorax, abdomen, and\npelvis, are available .","AI-Rad Companion Organs\nRT is designed for use only\nin adult populations. AI-Rad\nCompanion Organs RT is\ndesigned for any patient for\nwhom relevant modality\nscans are available. More\nspecifically, the software is\nvalidated on previously\nacquired CT DICOM\nvolumes for radiation\ntherapy treatment planning,\nincluding, head and neck,\nthorax, abdomen, and pelvis.","No public record found"]],"caption_candidate":"contours.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p9-t0","doc_id":"K232928","page_num":9,"bbox":[72.0,156.24,594.0,521.64],"n_rows":5,"n_cols":4,"columns":["Software\nArchitecture","Server-based application\nsupporting\nWindows and Local\ndeployment on Windows.","AI-Rad Companion\n(Engine) architecture\nenabling the deployment of\nAI Rad Companion Organs\nRT using Edge and in the\nCloud. The UI is provided\nusing a webbased interface.","Server-based application\nsupporting\nLinux-based OS and Local\ndeployment on Windows\nor Mac"],"rows":[["Software\nArchitecture","Server-based application\nsupporting\nWindows and Local\ndeployment on Windows.","AI-Rad Companion\n(Engine) architecture\nenabling the deployment of\nAI Rad Companion Organs\nRT using Edge and in the\nCloud. The UI is provided\nusing a webbased interface.","Server-based application\nsupporting\nLinux-based OS and Local\ndeployment on Windows\nor Mac"],["Deployment\nFeature","locally deployed or Cloud-\nbased","Edge & Cloud Deployment","Cloud-based or locally\ndeployed"],["Organ Templates","Creating, editing and deletion\nof organ templates. Customize\npredefined structure database\nwith mapping to international\nnomenclature schemes.","Creating, editing and\ndeletion of organ templates.\nCustomize predefined\nstructure database with\nmapping to international\nnomenclature schemes.","No public record found"],["Automated\nworkflow","DeepContour automatically\nprocesses input image data and\nsends the results as DICOM-\nRT Structure Sets to a user-\nconfigurable target node.","AI-Rad Companion Organs\nRT automatically processes\ninput image data and sends\nthe results as DICOM-RT\nStructure Sets to a user-\nconfigurable target node.","Automatic contouring\nworking using machine-\nlearning"],["Contour\nvisualization and\nediting feature","DeepContour provides basic\nresult preview of automatic\nsegmentation results, and\nediting feature of the\nautomatic segmented contour.","AI-Rad Companion Organs\nRT provides basic result\npreview of automatic\nsegmentation results, and no\nediting feature of the\nautomatic segmented\ncontour.","No public record found"]],"caption_candidate":"manage","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p10-t0","doc_id":"K232928","page_num":10,"bbox":[72.0,312.6,594.0,499.44],"n_rows":5,"n_cols":4,"columns":["User Interface –\nResults Preview\n(Confirmation)","Basic visualization\nfunctionality of original data\nand generated contours","Basic visualization\nfunctionality of original data\nand generated contours","Basic visualization\nfunctionality of original\ndata and generated\ncontours"],"rows":[["User Interface –\nResults Preview\n(Confirmation)","Basic visualization\nfunctionality of original data\nand generated contours","Basic visualization\nfunctionality of original data\nand generated contours","Basic visualization\nfunctionality of original\ndata and generated\ncontours"],["User Interface\nConfiguration","Configuration UI","Configuration UI","Configuration UI"],["Automated\nWorkflow to TPS","Results send to Confirmation\nUI & Optional bypassing of\nConfirmation UI to TPS","Results send to\nConfirmation UI & Optional\nbypassing of Confirmation\nUI to TPS","Results send to\nConfirmation UI &\nOptional bypassing of\nConfirmation UI to TPS"],["Human Factors","Design to be used by\ntrained clinicians.","Design to be used by\ntrained clinicians.","Design to be used by\ntrained clinicians."],["Patient Contact","None","None","None"]],"caption_candidate":"the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p11-t0","doc_id":"K232928","page_num":11,"bbox":[72.24,353.4,535.56,678.96],"n_rows":6,"n_cols":2,"columns":["# of Datasets","800"],"rows":[["# of Datasets","800"],["Data Origin","35 hospitals across China"],["Sex","Male:372\nFemale:428"],["Age","<50: 289\n50-70: 415\n>70:70\nUnknown:26 (unknown due to data minimization on customer site)"],["Body Region","Head and neck region: 200\nchest region: 200\nabdomen region: 200\npelvic region: 200"],["CT Scanner","Philips: 301\nGE: 226\nSimens: 128\nUnknown:145 (unknown due to data minimization on customer\nsite)"]],"caption_candidate":"Table 2: Training Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p12-t0","doc_id":"K232928","page_num":12,"bbox":[72.24,582.0,530.64,697.44],"n_rows":3,"n_cols":3,"columns":["# of Datasets","100","103"],"rows":[["# of Datasets","100","103"],["Data Origin","Peking Union Medical\nCollege Hospital","The 2017 lung CT segmentation\nchallenge (LCTSC): 60\nPancreas-CT (PCT): 43"],["Sex","Male: 43\nFemale: 57","Unknow:103 (unknown due to data\nminimization on customer site)"]],"caption_candidate":"Table 3: Verification Data Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p13-t0","doc_id":"K232928","page_num":13,"bbox":[72.24,72.24,530.64,301.44],"n_rows":3,"n_cols":3,"columns":["Age","<50: 31\n50-70: 46\n>70: 23","Unknown:103 (unknown due to data\nminimization on customer site)"],"rows":[["Age","<50: 31\n50-70: 46\n>70: 23","Unknown:103 (unknown due to data\nminimization on customer site)"],["Body Region","Head and neck region: 25\nchest region: 25\nabdomen region: 25\npelvic region: 25","60 thoracic CT scan: 5 segmented\norgans (left lung, right lung, heart, spinal\ncord, and esophagus)\n43 abdominal CT scan: 7 segmented\norgans (the spleen, left kidney, esophagus,\nliver, stomach, pancreas, and duodenum)"],["CT Scanner","Philips: 34\nGE: 36\nSimens: 30","Unknown 103 (unknown due to data\nminimization on customer site)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p14-t0","doc_id":"K232928","page_num":14,"bbox":[65.8,156.19,546.28,705.68],"n_rows":25,"n_cols":6,"columns":["Structure:","DeepContour","","AI-Rad CAI-Rad","","Contour ProtégéAI\n（K223774）"],"rows":[["Structure:","DeepContour","","AI-Rad CAI-Rad","","Contour ProtégéAI\n（K223774）"],["","","","Companion Organs RT","",""],["","","","（K221305）","",""],["Brain","0.98±0.01(0.97)","0.93±0.11","","","0.98 ± 0.01"],["BrainStem","0.91±0.03(0.89)","0.90±0.02","","","0.82 ± 0.09"],["Cochlea_L","0.86±0.03(0.84)","0.84±0.03","","","0.27 ± 0.17"],["Cochlea_R","0.85±0.01(0.84)","0.86±0.07","","","0.29 ± 0.18"],["Eye_L","0.89±0.02(0.88)","0.81±0.06","","","0.87 ± 0.06"],["Eye_R","0.88±0.03(0.86)","0.89±0.13","","","0.87 ± 0.06"],["Lens_L","0.89±0.02(0.88)","0.85±0.05","","","0.61 ± 0.17"],["Lens_R","0.88±0.02(0.85)","0.81±0.12","","","0.63 ± 0.15"],["Larynx","0.88±0.03(0.83)","0.84±0.08","","","0.50 ± 0.16"],["Larynx_extend","0.92±0.02(0.91)","0.90±0.11","","","None"],["Mandible","0.95±0.02(0.91)","0.91±0.07","","","0.85 ± 0.07"],["Optic_Chiasm","0.88±0.03(0.82)","0.63±0.11","","","0.12 ± 0.11"],["OpticalNerve_L","0.86±0.04(0.79)","0.66±0.06","","","0.53 ± 0.13"],["OpticalNerve_R","0.89±0.02(0.81)","0.59±0.10","","","0.52 ± 0.12"],["OralCavity","0.92±0.03(0.89)","0.82±0.09","","","0.77 ± 0.12"],["OralCavity_WithGum","0.91±0.06(0.89)","0.71±0.06","","","None"],["Parotid_L","0.88±0.05(0.82)","0.80±0.15","","","0.80 ± 0.10"],["Parotid_R","0.86±0.03(0.81)","0.81±0.04","","","0.80 ± 0.06"],["Pituitary","0.78±0.04(0.69)","0.68±0.14","","","0.49 ± 0.15"],["Temporal_Lobe_L","0.92±0.02(0.90)","0.82±0.09","","","0.68 ± 0.17"],["Temporal_Lobe_R","0.91±0.11(0.86)","0.81±0.07","","","0.79 ± 0.18"],["TMJ_L","0.85±0.02(0.83)","0.84±0.02","","","0.84± 0.06"]],"caption_candidate":"Table 5: Clinical performance comparison (Peking Union Medical College Hospital)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p15-t0","doc_id":"K232928","page_num":15,"bbox":[65.8,72.0,546.28,705.88],"n_rows":30,"n_cols":6,"columns":["TMJ_R","","","0.86±0.15(0.81)","0.85±0.15","0.83 ± 0.06"],"rows":[["TMJ_R","","","0.86±0.15(0.81)","0.85±0.15","0.83 ± 0.06"],["InternalAcousticCanal_L","","","0.76±0.02(0.71)","0.73±0.12","0.71 ± 0.17"],["InternalAcousticCanal_R","","","0.79±0.02(0.75)","0.77±0.05","0.73 ± 0.15"],["MiddleEar_L","","","0.82±0.12(0.78)","0.72±0.02","0.70 ± 0.16"],["MiddleEar_R","","","0.85±0.03(0.81)","0.80±0.13","0.77 ± 0.17"],["","TemporalLobe_withHipp","","0.89±0.08(0.85)","0.87±0.14","0.85 ± 0.18"],["","o_L","","","",""],["","TemporalLobe_withHipp","","0.90±0.05(0.86)","0.88±0.09","0.87 ± 0.06"],["","o_R","","","",""],["Submandibular_L","","","0.91±0.06(0.88)","0.81±0.11","0.75 ± 0.10"],["Submandibular_R","","","0.92±0.03(0.89)","0.72±0.16","0.74 ± 0.09"],["","PharyngealConstrictors_","","0.82±0.12(0.76)","0.77±0.13","None"],["","U","","","",""],["","PharyngealConstrictors_","","0.86±0.14(0.83)","0.76±0.11","None"],["","M","","","",""],["","PharyngealConstrictors_","","0.84±0.17(0.80)","0.74±0.07","None"],["","L","","","",""],["BrachialPlexus_L","","","0.81±0.13(0.79)","0.71±0.08","0.37 ± 0.13"],["BrachialPlexus_R","","","0.82±0.11(0.69)","0.52±0.06","0.36 ± 0.16"],["Hippocampus_L","","","0.76±0.03(0.73)","0.75 ± 0.12","0.75 ± 0.02"],["Hippocampus_R","","","0.79±0.02(0.76)","0.73 ± 0.09","0.76 ± 0.02"],["EustachianTubeBone_L","","","0.85±0.05(0.84)","0.81±0.05","0.88 ± 0.07"],["EustachianTubeBone_R","","","0.87±0.07(0.80)","0.77±0.09","0.72 ± 0.17"],["TympanicCavity_L","","","0.84±0.03(0.83)","0.80±0.13","0.75 ± 0.15"],["TympanicCavity_R","","","0.86±0.09(0.81)","0.76±0.05","0.74 ± 0.17"],["Vestibule_L","","","0.85±0.06(0.82)","0.80±0.16","0.79 ± 0.10"],["Vestibule_R","","","0.87±0.02(0.86)","0.77±0.10","0.74 ± 0.10"],["InnerEar_L","","","0.87±0.10(0.83)","0.83±0.11","0.82 ± 0.07"],["InnerEar_L","","","0.86±0.13(0.83)","0.87±0.03","0.91 ± 0.07"],["Lung_L","","","0.98±0.05(0.96)","0.92±0.16","0.96 ± 0.02"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p16-t0","doc_id":"K232928","page_num":16,"bbox":[65.8,72.0,546.28,713.85],"n_rows":27,"n_cols":4,"columns":["Lung_R","0.99±0.03(0.98)","0.95±0.08","0.96 ± 0.02"],"rows":[["Lung_R","0.99±0.03(0.98)","0.95±0.08","0.96 ± 0.02"],["Lung_All","0.98±0.14(0.97)","0.91±0.04","None"],["Heart","0.93±0.16(0.90","0.91±0.06","0.90 ± 0.07"],["Trachea","0.89±0.03(0.88)","0.89±0.03","0.73 ± 0.17"],["Esophagus","0.88±0.11(0.85)","0.78±0.07","0.70 ± 0.15"],["Breast_L","0.92±0.08(0.86)","0.82±0.05","0.74 ± 0.17"],["Breast_R","0.93±0.01(0.92)","0.83±0.04","0.77 ± 0.10"],["Aorta","0.89±0.09(0.87)","0.70 ± 0.08","0.74 ± 0.10"],["Liver","0.96±0.07(0.95)","0.86±0.17","0.93 ± 0.07"],["Kidney_L","0.92±0.03(0.91)","0.82±0.13","0.92 ± 0.05"],["Kidney_R","0.93±0.04(0.91)","0.88±0.07","0.91 ± 0.06"],["Duodenum","0.88±0.16(0.83)","0.81±.012","None"],["Pancreas","0.86±0.01(0.86)","0.87±0.03","0.45 ± 0.22"],["Smallintestine","0.89±0.12(0.85)","0.88±0.08","None"],["Bowelbag","0.93±0.16(0.88)","0.83 ± 0.08","0.68 ± 0.08"],["Bladder","0.95±0.15(0.93)","0.87 ± 0.15","0.52 ± 0.19"],["Stomach","0.86±0.01(0.86)","0.79 ± 0.21","0.81 ± 0.11"],["Femur_Head_L","0.92±0.12(0.89)","0.90±0.16","0.93 ± 0.05"],["Femur_Head_R","0.91±0.14(0.86)","0.90±0.09","0.93 ± 0.04"],["Pelvis","0.87±0.01(0.87)","0.88±0.08","0.93 ± 0.11"],["Marrow","0.85±0.13(0.84)","0.81±0.03","None"],["Sigmoid","0.82±0.02(0.81)","0.70 ± 0.17","0.60 ± 0.26"],["Rectum","0.87±0.15(0.83)","0.73 ± 0.18","0.83 ± 0.11"],["Spleen","0.91±0.01(0.90)","0.92±0.07","0.95 ± 0.03"],["SeminalVesicle","0.86±0.02(0.85)","0.78 ± 0.27","0.68 ± 0.15"],["Testis","0.87±0.03(0.84)","0.79 ± 0.16","0.63 ± 0.16"],["Prostate","0.87±0.02(0.85)","0.74 ± 0.12","0.85 ± 0.06"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p17-t0","doc_id":"K232928","page_num":17,"bbox":[65.8,73.13,546.28,275.44],"n_rows":8,"n_cols":10,"columns":["Ovid_L","","","0.85±0.03(0.82)","","","0.65±0.03","","","0.39 ± 0.17"],"rows":[["Ovid_L","","","0.85±0.03(0.82)","","","0.65±0.03","","","0.39 ± 0.17"],["Ovid_R","","","0.86±0.01(0.85)","","","0.66±0.01","","","0.43 ± 0.15"],["","Bladder-Brt","","","0.86±0.02(0.84)","","","0.82 ± 0.23","","0.91 ± 0.12"],["","SmallIntestine-Brt","","","0.87±0.04(0.85)","","0.76 ± 0.14","","","0.73 ± 0.11"],["","Rectum-Brt","","","0.86±0.03(0.84)","","0.85 ± 0.18","","","0.83 ± 0.11"],["","Sigmoid-Brt","","","0.79±0.02(0.78)","","0.70 ± 0.17","","","0.60 ± 0.26"],["","SpinalCord","","","0.93±0.01(0.92)","","0.66 ± 0.14","","","0.63 ± 0.16"],["Body","","","0.98±0.05(0.96)","","","0.97±0.03","","","None"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p17-t1","doc_id":"K232928","page_num":17,"bbox":[65.8,400.44,546.28,564.8],"n_rows":8,"n_cols":8,"columns":["Structure:","DeepContour","","AI-Rad CAI-Rad","","","Contour",""],"rows":[["Structure:","DeepContour","","AI-Rad CAI-Rad","","","Contour",""],["","","","Companion Organs RT","","","ProtégéAI",""],["","","","（K221305）","","","（K223774）",""],["SpinalCord","0.92±0.02(0.91)","0.64±0.13","","","0.62 ± 0.21","",""],["Lung L","0.97±0.15(0.96)","0.90±0.13","","","0.95 ± 0.05","",""],["Lung R","0.98±0.06(0.98)","0.93±0.11","","","0.94 ± 0.08","",""],["Heart","0.92±0.11(0.90)","0.91±0.04","","","0.90 ± 0.04","",""],["Esophagus","0.89±0.13(0.86)","0.75±0.13","","","0.68 ± 0.19","",""]],"caption_candidate":"Table 6: Clinical performance comparison (LCTSC American public datasets)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p18-t0","doc_id":"K232928","page_num":18,"bbox":[65.8,72.84,546.28,282.56],"n_rows":10,"n_cols":8,"columns":["Structure:","DeepContour","","AI-Rad CAI-Rad","","","Contour",""],"rows":[["Structure:","DeepContour","","AI-Rad CAI-Rad","","","Contour",""],["","","","Companion Organs RT","","","ProtégéAI",""],["","","","（K221305）","","","（K223774）",""],["Spleen","0.90±0.05(0.88)","0.91±0.12","","","0.89 ± 0.08","",""],["Pancreas","0.85±0.03(0.83)","0.84±0.02","","","0.43 ± 0.25","",""],["Kidney_L","0.93±0.02(0.91)","0.84±0.03","","","0.92 ± 0.17","",""],["Esophagus","0.88±0.02(0.87)","0.80±0.06","","","0.70 ± 0.06","",""],["Liver","0.97±0.03(0.97)","0.85±0.13","","","0.92 ± 0.06","",""],["Stomach","0.85±0.02(0.84)","0.80±0.05","","","0.81 ± 0.17","",""],["Duodenum","0.86±0.02(0.85)","0.82±0.12","","","None","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K232928-p18-t1","doc_id":"K232928","page_num":18,"bbox":[97.11,418.03,514.88,537.76],"n_rows":5,"n_cols":9,"columns":["","DeepContour","","","AI-Rad CAI-Rad","","","Contour ProtégéAI\n（K223774）",""],"rows":[["","DeepContour","","","AI-Rad CAI-Rad","","","Contour ProtégéAI\n（K223774）",""],["","","","","Companion Organs RT","","","",""],["","","","","（K221305）","","","",""],["","Median","95% CI\n(Bootstrap)","Median","","95% CI\n(Bootstrap)","","Median","95% CI\n(Bootstrap)"],["ASSD","0.95","[0.85,1.13]","0.96","","[0.84,1.15]","","0.95","[0.86,1.17]"]],"caption_candidate":"Table 8: Rigid and deformable registration","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233030-p7-t0","doc_id":"K233030","page_num":7,"bbox":[72.31,112.36,523.45,761.73],"n_rows":7,"n_cols":6,"columns":["","","Predicate Device\n(BoneMRI K230197)","Subject Device\n(BoneMRI)","Comment",""],"rows":[["","","Predicate Device\n(BoneMRI K230197)","Subject Device\n(BoneMRI)","Comment",""],["","Intended use","","","",""],["Intended Use","","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI images.\nIt can be used to visualize the\nbone structures in MRI\nimages with enhanced\ncontrast with respect to the\nsurrounding soft tissue.","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI images.\nIt can be used to visualize the\nbone structures in MRI\nimages with enhanced\ncontrast with respect to the\nsurrounding soft tissue.","The same",""],["21CFR Section","","829.2050","829.2050","The same",""],["Product Code","","QIH","QIH","The same",""],["Target\nPopulation","","Adults","Adolescents and Adults","Different",""],["Indications for\nUse","","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI images.\nIt can be used to visualize the\nbone structures in MRI\nimages with enhanced\ncontrast with respect to the\nsurrounding soft tissue. It is\nto be used in the pelvic\nregion, which includes the\nbony anatomy of the sacrum,\nhip bones and femoral heads;\nand the lumbar spine region,\nwhich includes the bony\nanatomy of the vertebrae\nfrom L3 to S1. BoneMRI is\nnot to be used for diagnosis\nor monitoring of (primary or\nmetastatic) tumors.\nWarning: BoneMRI images\nare not intended to replace\nCT images.","BoneMRI is an image\nprocessing software that can\nbe used for image\nenhancement in MRI images.\nIt can be used to visualize the\nbone structures in MRI\nimages with increased\ncontrast with respect to the\nsurrounding soft tissue. It is\nto be used in the pelvic\nregion, which includes the\nbony anatomy of the sacrum,\nhip bones and femoral heads;\nand the spine, which includes\nthe bony anatomy of the\ncervical, thoracic, lumbar, and\nS1 vertebrae. BoneMRI is\nindicated for use in patients\n12 years and older.\nBoneMRI is not to be used\nfor diagnosis or monitoring of\n(primary or metastatic)\ntumors. BoneMRI images are\nnot intended to replace CT\nimages in general but can be\nused to visualize 3D bone\nmorphology, tissue\nradiodensity and tissue\nradiodensity contrast.","Similar",""]],"caption_candidate":"Table 1 Predicate device comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233030-p9-t0","doc_id":"K233030","page_num":9,"bbox":[72.3,112.36,525.71,373.85],"n_rows":7,"n_cols":2,"columns":["Change","Change Description"],"rows":[["Change","Change Description"],["Software architecture","Refactor of the application workflow; introducing multi-tenancy\ncapabilities; and improving scalability of cloud deployment."],["Validation strategy","Revision of the validation strategy to support the validation of a\nmulti-vendor, multi-field strength algorithm."],["Intended patient population","The intended patient population of BoneMRI is extended to include\nadolescents. The algorithm for the application has not been\nchanged."],["Predetermined Change\nControl Plan","Addition of a Predetermined Change Control Plan to support an\niterative development approach for the machine learning models in\nthe BoneMRI application."],["Algorithm for the Spine\nregion","The algorithm for the Spine region has been re-trained. With\nadditional data for training and testing, the anatomical region of the\nalgorithm was extended to include the Cervical Spine and the\nThoracic Spine in addition to the Lumbar Spine."],["Algorithm for the Pelvic\nregion","No changes are made to the algorithm for the Pelvic region. Updates\nhave been made to improve statistical testing of the algorithm and\nto test the algorithm on additional subgroups."]],"caption_candidate":"Table 2 Summary of changes for the BoneMRI application","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233030-p9-t1","doc_id":"K233030","page_num":9,"bbox":[72.3,591.25,525.71,754.23],"n_rows":3,"n_cols":2,"columns":["Modification","Rationale"],"rows":[["Modification","Rationale"],["1. Re-training to improve ML\nmodel performance with\nadditional training data","Re-training of the ML model with additional data to increase the\nsafety and performance of the device in any of the following\ncategories:\n● Increased accuracy;\n● Increased performance for challenging cases such as rare\npathologies or artifacts;\n● Increased robustness and generalization of the model."],["2. Validation of additional\nscanner support","Validation of the ML model (either with or without additional re-\ntraining of the ML model) in order to validate an additional MRI\nvendor or field strength."]],"caption_candidate":"Table 3 Summary of changes under a Predetermined Change Control Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233030-p10-t0","doc_id":"K233030","page_num":10,"bbox":[72.46,470.46,523.07,747.73],"n_rows":20,"n_cols":9,"columns":["","","","","","","Cortical\ndelineation\nerror (mm)","Mean","Correlation\ncoefficient\nin bone"],"rows":[["","","","","","","Cortical\ndelineation\nerror (mm)","Mean","Correlation\ncoefficient\nin bone"],["","","","","","","","deviation",""],["","","","","","Data","","",""],["Subgroup","","N","Gender","Age","","","in all tissue",""],["","","","","","origin","","",""],["","","","","","","","and bone",""],["","","","","","","","",""],["","","","","","","","(HU)",""],["Total","","","75% M","","US,","< 1 mm","< 25 HU","> 0.75"],["","Pelvis","76","","53 ± 26","","","",""],["","","","25% F","","EU","","< 55 HU",""],["","","","","","","","",""],["","","","49% M","","US,","< 1 mm","< 25 HU","> 0.75"],["","Spine","117","","48 ± 23","","","",""],["","","","51% F","","EU","","< 55 HU",""],["","","","","","","","",""],["Adults","Pelvis","57","93% M\n7% F","66 ± 17","US,\nEU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Spine","94","51% M\n49% F","59 ± 16","US,\nEU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["Adolescents","Pelvis","19","21% M\n79% F","17 ± 3","US","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Spine","23","22% M\n78% F","15 ± 2","EU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"]],"caption_candidate":"<0.05.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233030-p11-t0","doc_id":"K233030","page_num":11,"bbox":[72.28,91.53,523.48,361.85],"n_rows":8,"n_cols":9,"columns":["US","Pelvis","25","24% M\n76% F","18 ± 4","US","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],"rows":[["US","Pelvis","25","24% M\n76% F","18 ± 4","US","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Spine","23","33% M\n67% F","64 ± 10","US","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["EU","Pelvis","51","100% M\n0% F","71 ± 80","EU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Spine","91","46% M\n54% F","49 ± 23","EU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["BMI","Obese","11","64% M\n36% F","51 ± 16","US,\nEU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Over-\nweight","17","60% M\n40% F","52 ± 18","US,\nEU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Healthy","18","22% M\n78% F","29 ± 22","US,\nEU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"],["","Under-\nweight","10","20% M\n80% F","17 ± 3","EU","< 1 mm","< 25 HU\n< 55 HU","> 0.75"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233080-p4-t0","doc_id":"K233080","page_num":4,"bbox":[72.36,348.6,530.52,490.44],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Nano-X AI HealthFLD device"],"rows":[["Proprietary Name","Nano-X AI HealthFLD device"],["Premarket Notification","K233080"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR §892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233080-p4-t1","doc_id":"K233080","page_num":4,"bbox":[72.36,564.36,530.52,727.08],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Predicate Device:\nNano-X AI HealthOST device"],"rows":[["Proprietary Name","Predicate Device:\nNano-X AI HealthOST device"],["Premarket Notification","K213944"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR §892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"The HealthFLD device is substantially equivalent to the following Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233080-p6-t0","doc_id":"K233080","page_num":6,"bbox":[72.81,141.3,538.42,563.21],"n_rows":2,"n_cols":3,"columns":["","Proposed Device:\nHealthFLD Device","Primary Predicate Device:\nNano-X AI Ltd. HealthOST Device\n(K213944)"],"rows":[["","Proposed Device:\nHealthFLD Device","Primary Predicate Device:\nNano-X AI Ltd. HealthOST Device\n(K213944)"],["Intended\nUse/\nIndications\nfor Use","The HealthFLD device is an image\nprocessing software that provides\nquantitative and qualitative analysis of\nthe liver from CT images to support\nclinicians in the evaluation and\nassessment of Fatty Liver. The\nHealthFLD software provides\nmeasurements of liver attenuation\n(mean HU in a region of interest).\nHealthFLD is indicated for use in non-\ncontrast and contrast CT scans, with\nany clinical indication, for patients\naged 18 up to 75. CTs must include a\nsignificant part of the liver. The\nHealthFLD device is not intended to\nprovide a diagnosis or risk assessment\nof fatty liver disease.","HealthOST is an image processing software\nthat provides qualitative and quantitative\nanalysis of the spine from CT images to\nsupport clinicians in the evaluation and\nassessment of musculoskeletal disease of the\nspine.\nThe HealthOST software provides the\nfollowing functionality:\n• Labelling of T1-L4 vertebrae\n• Measurement of height loss in each\nvertebra (T1-L4)\n• Measurement of the mean\nHounsfield Units (HU) in volume of\ninterest within vertebra (T11-L4)\nHealthOST is indicated for use in patients\naged 50 and over undergoing CT scan for\nany clinical indication, that includes at least\nfour vertebrae in the T1-L4 portion of the\nspine (for vertebral height loss) and T11-L4\n(for bone attenuation) portions of the spine.\nThe device is indicated for FBP-\nreconstructed images only"]],"caption_candidate":"K213944.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233080-p7-t0","doc_id":"K233080","page_num":7,"bbox":[72.88,102.41,537.69,682.62],"n_rows":16,"n_cols":6,"columns":["Technological\nCharacteristics","","Proposed Device:\nHealthFLD Device","Primary Predicate Device:\nNano-X AI Ltd.\nHealthOST Device\n(K213944)","Summary",""],"rows":[["Technological\nCharacteristics","","Proposed Device:\nHealthFLD Device","Primary Predicate Device:\nNano-X AI Ltd.\nHealthOST Device\n(K213944)","Summary",""],["","","","","",""],["Regulation","","","","",""],["","","","","",""],["Product Code","","JAK","JAK","Same",""],["Regulation\nNumber","","21 CFR §892.1750","21 CFR §892.1750","",""],["","","","","",""],["General","","","","",""],["","","","","",""],["Modality","","CT","CT","Same",""],["Image format","","DICOM","DICOM","Same",""],["Supported CT\nscan","","Non-contrast enhanced\nand contrast enhanced","Non-contrast enhanced and\ncontrast enhanced","Same",""],["","","","","",""],["","Analysis and Measurement","","","",""],["","","","","",""],["Detection of\ntarget organ","","Yes, detection of the liver","Yes, detection of vertebras","Similar, both devices\ndetect the target organ\nin the scan. The\ndifferences do not raise\ndifferent questions of\nsafety and\neffectiveness of the\nsubject and predicate\ndevices and evaluation\nof the device comprises\nthe same types of\nverification and\nvalidation testing",""]],"caption_candidate":"Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233080-p8-t0","doc_id":"K233080","page_num":8,"bbox":[72.88,79.37,537.68,640.62],"n_rows":6,"n_cols":6,"columns":["Segmentation of\norgan","","Deep-learning-based\nsegmentation of the Liver","Deep-learning-based\nsegmentation of vertebras","Similar, both devices\nperform segmentation\nof the target organ, in\nthe same method. The\ndifferences do not raise\ndifferent questions of\nsafety and\neffectiveness of the\nsubject and predicate\ndevices and evaluation\nof the device 5-\n6comprises the same\ntypes of verification\nand validation testing",""],"rows":[["Segmentation of\norgan","","Deep-learning-based\nsegmentation of the Liver","Deep-learning-based\nsegmentation of vertebras","Similar, both devices\nperform segmentation\nof the target organ, in\nthe same method. The\ndifferences do not raise\ndifferent questions of\nsafety and\neffectiveness of the\nsubject and predicate\ndevices and evaluation\nof the device 5-\n6comprises the same\ntypes of verification\nand validation testing",""],["Measurement\nof Hounsfield\n(HU) value","","HU measurements based\non segmentation and\nmean HU in regions of\ninterest (ROIs)\nIndication to user if\noutside reference range","HU measurements based\non segmentation and mean\nHU in volume of interest\nIndication to user if outside\nreference range","Same, both devices\nmeasure mean\nattenuation (HU) of\nselected region within\nthe organ\nRegion of interest is\nequivalent to volume\nof interest",""],["","","","","",""],["","Reporting","","","",""],["","","","","",""],["Device output","","1. Annotation of up to\nthree (3) Region of\nInterest (ROI)\n2. Liver density\nmeasured in HU","1. Vertebrae label/name\n2. Three (3) lines\nrepresenting the\nanterior, middle, and\nposterior points\nmeasures, together with\nrelative measurements\n3. % Height loss and\nrelative Genant\ncategory (20)\n4. Bone density measured\nin HU","Similar, the subject\ndevice provides the\nanalysis results as liver\nattenuation in HU,\nsame as the predicate\ndevice provides the\nbone attenuation in\nHU.",""]],"caption_candidate":"Page 5 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p4-t0","doc_id":"K233108","page_num":4,"bbox":[72.0,309.72,576.06,516.72],"n_rows":7,"n_cols":2,"columns":["Trade/Proprietary Name:","VinDr-Mammo"],"rows":[["Trade/Proprietary Name:","VinDr-Mammo"],["Common/Usual Name:","Radiological computer aided triage and notification software"],["Classification Name:","Radiological computer aided triage and notification software"],["Regulation Number:","21 CFR 892.2080"],["Product Code:","QFM, Radiological Computer-Assisted Prioritization Software\nFor Lesions"],["Device Class:","Class II"],["Classification Panel:","Radiology"]],"caption_candidate":"Device Identification:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p5-t0","doc_id":"K233108","page_num":5,"bbox":[72.54,93.12,504.24,293.64],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","CogNet QmTRIAGE"],"rows":[["Proprietary Name","CogNet QmTRIAGE"],["Premarket Notification","K220080"],["Classification Name","Radiological Computer-Assisted Prioritization Software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QFM"],["Regulatory Class","II"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p7-t0","doc_id":"K233108","page_num":7,"bbox":[72.54,319.02,539.76,699.96],"n_rows":2,"n_cols":4,"columns":["Technological\nCharacteristics","Proposed Device\nVinDr-Mammo","Predicate Device\nCogNet QmTRIAGE\n(K220080)","Summary"],"rows":[["Technological\nCharacteristics","Proposed Device\nVinDr-Mammo","Predicate Device\nCogNet QmTRIAGE\n(K220080)","Summary"],["Indication for\nUse/Intended\nUse","The VinDr-Mammo is\na passive notification\nfor prioritization-only,\nparallel-workflow\nsoftware tool used by\nMQSA qualified\ninterpreting physicians\nto prioritize patients\nwith suspicious\nfindings in the medical\ncare environment.\nVinDr-Mammo utilizes\nan artificial intelligence","The MedCognetics\n(CogNet)\nQmTRIAGETM\nsoftware is a passive\nnotification for\nprioritization-only,\nparallel-workflow\nsoftware tool used by\nMQSA qualified\ninterpreting physicians\nto prioritize patients\nwith suspicious\nfindings in the medical","Same"]],"caption_candidate":"A comparison of the technological characteristics with the predicate is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p9-t0","doc_id":"K233108","page_num":9,"bbox":[72.54,71.46,539.76,710.1],"n_rows":3,"n_cols":4,"columns":["","information beyond\ntriage and\nprioritization, does not\nremove images from\nthe interpreting\nphysician’s worklist,\nand should not be used\nin lieu of full patient\nevaluation, or relied\nupon to make or\nconfirm diagnosis.\nThe VinDr-Mammo\ndevice is intended for\nuse with complete 2D\nFFDM mammography\nexams acquired using\nvalidated FFDM\nsystems only.","QmTRIAGE device is\nlimited to the\ncategorization of\nexams, does not\nprovide any diagnostic\ninformation beyond\ntriage and\nprioritization, does not\nremove images from\nthe interpreting\nphysician’s worklist,\nand should not be used\nin lieu of full patient\nevaluation, or relied\nupon to make or\nconfirm diagnosis.\nThe QmTRIAGE\ndevice is intended for\nuse with complete 2D\nFFDM mammography\nexams acquired using\nvalidated FFDM\nsystems only.",""],"rows":[["","information beyond\ntriage and\nprioritization, does not\nremove images from\nthe interpreting\nphysician’s worklist,\nand should not be used\nin lieu of full patient\nevaluation, or relied\nupon to make or\nconfirm diagnosis.\nThe VinDr-Mammo\ndevice is intended for\nuse with complete 2D\nFFDM mammography\nexams acquired using\nvalidated FFDM\nsystems only.","QmTRIAGE device is\nlimited to the\ncategorization of\nexams, does not\nprovide any diagnostic\ninformation beyond\ntriage and\nprioritization, does not\nremove images from\nthe interpreting\nphysician’s worklist,\nand should not be used\nin lieu of full patient\nevaluation, or relied\nupon to make or\nconfirm diagnosis.\nThe QmTRIAGE\ndevice is intended for\nuse with complete 2D\nFFDM mammography\nexams acquired using\nvalidated FFDM\nsystems only.",""],["Notification-\nonly, parallel\nworkflow tool","Yes","Yes","Same"],["User","Interpreting physician","Interpreting physician","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p10-t0","doc_id":"K233108","page_num":10,"bbox":[72.54,71.46,539.76,697.56],"n_rows":8,"n_cols":4,"columns":["Alert to finding","Yes; passive\nnotification flagged for\nreview","Yes; passive\nnotification flagged for\nreview","Same"],"rows":[["Alert to finding","Yes; passive\nnotification flagged for\nreview","Yes; passive\nnotification flagged for\nreview","Same"],["Independent of\nSoC workflow","Yes; No cases are\nremoved from worklist","Yes; No cases are\nremoved from worklist","Same"],["Modality","FFDM screening\nmammograms","FFDM screening\nmammograms","Same"],["FFDM\nmanufacturers\nhave been\nvalidated","GE, Siemens, Fujifilm","Hologic","Same"],["Body part","Breast","Breast","Same"],["AI algorithm","Yes","Yes","Same"],["Limited to\nanalysis of\nimaging data","Yes","Yes","Same"],["Inclusion\nCriteria","- Standard 2D FFDM\nscreening\nmammograms\n- Biopsy proven cancer\nstudies (soft tissues and\nmicrocalcifications)\n- Biopsy-proven benign\nstudies","- Standard 2D FFDM\nscreening\nmammograms\n- Biopsy proven cancer\nstudies (soft tissues and\nmicrocalcifications)\n- BIRADS 1 and 2\nnormal/benign cases","Equivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p11-t0","doc_id":"K233108","page_num":11,"bbox":[72.54,71.46,539.76,687.6],"n_rows":3,"n_cols":4,"columns":["","- BIRADS 1 and 2\nnormal cases with 2‐\nyear follow‐up of a\nnegative diagnosis\n- Bilateral Studies with\n4 standard views (LCC,\nLMLO, RCC, RMLO)","with 2‐year follow‐up\nof a negative diagnosis\n- Female patients 22\nand older\n- Bilateral Studies with\n4 standard views (LCC,\nLMLO, RCC, RMLO)",""],"rows":[["","- BIRADS 1 and 2\nnormal cases with 2‐\nyear follow‐up of a\nnegative diagnosis\n- Bilateral Studies with\n4 standard views (LCC,\nLMLO, RCC, RMLO)","with 2‐year follow‐up\nof a negative diagnosis\n- Female patients 22\nand older\n- Bilateral Studies with\n4 standard views (LCC,\nLMLO, RCC, RMLO)",""],["Exclusion\nCriteria","-Studies that do not\ninclude all 4 views\n-Digital Breast\ntomosynthesis studies\n- 3D studies\nStudies that do not\ncomply with the\ninclusion criteria","- Digital breast\ntomosynthesis images\n- 2D synthetic views\nfrom tomosynthesis","Similar, different\ncriteria and\nscope are\nintended to limit\nto specific\nmammography\nmethods. This\ndoes not raise\nany questions\nregarding safety\nor efficacy and\nuse of\nmammography\nimages"],["Aids prompt\nidentification of\ncases with\nindicated\nfindings","Yes","Yes","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p12-t0","doc_id":"K233108","page_num":12,"bbox":[72.54,71.46,539.76,463.32],"n_rows":3,"n_cols":4,"columns":["Multiple\noperating\npoints","No Applicable","Not Applicable","Same"],"rows":[["Multiple\noperating\npoints","No Applicable","Not Applicable","Same"],["Preview Images","Presentation of\nnotification and\npreview of the study\nfor initial assessment\nnot meant for\ndiagnostic purposes.\nThe device operates in\nparallel with the\nstandard of care, which\nremains the default\noption for all cases.","The device operates in\nparallel with the\nstandard of care, which\nremains the default\noption for all cases.\nEncapsulated PDF\nstored\nwith original DICOM\nstudy and may be\ndownloaded and\nviewed as a PDF.","Equivalent"],["Where results\nare received","PACS / Workstation","PACS / Workstation","same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p13-t0","doc_id":"K233108","page_num":13,"bbox":[72.43,229.44,523.48,356.28],"n_rows":4,"n_cols":4,"columns":["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],"rows":[["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],["Sensitivity","0.889","0.849","0.926"],["Specificity","0.906","0.885","0.927"],["AUC","0.958","0.945","0.970"]],"caption_candidate":"with a two-year follow-up of a negative diagnosis. A table of results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p13-t1","doc_id":"K233108","page_num":13,"bbox":[72.43,400.26,523.48,713.28],"n_rows":12,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Characteristics","Quantity/Type"],["Number of Studies","1000"],["Number of Images","5126"],["Number of Patients","1000"],["Density A","100"],["Density B","400"],["Density C","400"],["Density D","100"],["Age (<40)","14"],["Age (40-49)","266"],["Age (50-59)","266"]],"caption_candidate":"A summary of the DDSM dataset characteristics are provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p14-t0","doc_id":"K233108","page_num":14,"bbox":[72.36,71.34,523.26,226.08],"n_rows":6,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Age (60-69)","251"],["Age (70-79)","155"],["Age (≥80)","46"],["Ethnicity","Representative of the US Population"],["Scanner Type","Unknown"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p14-t1","doc_id":"K233108","page_num":14,"bbox":[80.34,517.98,531.66,644.7],"n_rows":4,"n_cols":4,"columns":["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],"rows":[["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],["Sensitivity","0.906","0.879","0.931"],["Specificity","0.911","0.896","0.926"],["AUC","0.965","0.957","0.971"]],"caption_candidate":"ground truth. A table of results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p15-t0","doc_id":"K233108","page_num":15,"bbox":[72.4,71.34,534.21,568.74],"n_rows":19,"n_cols":2,"columns":["Characteristics","Quantity/Type"],"rows":[["Characteristics","Quantity/Type"],["Number of Studies","1864"],["Number of Images","5126"],["Number of Patients","1864"],["Density A","180"],["Density B","746"],["Density C","746"],["Density D","192"],["Age (<40)","327"],["Age (40-49)","430"],["Age (50-59)","421"],["Age (60-69)","388"],["Age (70-79)","231"],["Age (≥80)","67"],["Ethnicity","Vietnamese"],["Hologic (Selenia Dimensions 3000)","517"],["Siemens (Mammomat Inspiration)","499"],["Fujifilm (AMULET Innovality)","482"],["GE (Senographe Essential ADS)","366"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p15-t1","doc_id":"K233108","page_num":15,"bbox":[72.4,616.08,534.21,711.06],"n_rows":3,"n_cols":4,"columns":["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],"rows":[["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],["Sensitivity","0.900","0.877","0.921"],["Specificity","0.910","0.897","0.922"]],"caption_candidate":"the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p16-t0","doc_id":"K233108","page_num":16,"bbox":[72.54,170.82,534.86,297.6],"n_rows":4,"n_cols":4,"columns":["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],"rows":[["Metrics","Mean","Lower 95% CI bound","Upper 95% CI bound"],["Sensitivity","0.870","_","_"],["Specificity","0.890","_","_"],["AUC","0.957","0.936","0.973"]],"caption_candidate":"table of the predicate results is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p16-t1","doc_id":"K233108","page_num":16,"bbox":[72.54,408.42,534.86,571.44],"n_rows":5,"n_cols":3,"columns":["Breast Density","RSNA Test set","VinDr Test set"],"rows":[["Breast Density","RSNA Test set","VinDr Test set"],["A","0.964 (0.922-0.994)","1.000 (1.000-1.000)"],["B","0.967 (0.952-0.981)","0.990 (0.983-0.996)"],["C","0.946 (0.922-0.967)","0.908 (0.886-0.928)"],["D","0.949 (0.922-0.975)","0.947 (0.912-0.975)"]],"caption_candidate":"various subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p16-t2","doc_id":"K233108","page_num":16,"bbox":[72.54,594.84,534.86,689.88],"n_rows":3,"n_cols":3,"columns":["Age group","RSNA Test set","VinDr Test set"],"rows":[["Age group","RSNA Test set","VinDr Test set"],["Age (<40)","1.000 (1.000-1.000)","0.988 (0.975-0.997)"],["Age (40-49)","0.969 (0.947-0.985)","0.920 (0.894-0.943)"]],"caption_candidate":"D 0.949 (0.922-0.975) 0.947 (0.912-0.975)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p17-t0","doc_id":"K233108","page_num":17,"bbox":[72.54,71.46,534.0,379.44],"n_rows":9,"n_cols":3,"columns":["Age (50-59)","0.952 (0.915-0.983)","0.964 (0.948-0.978)"],"rows":[["Age (50-59)","0.952 (0.915-0.983)","0.964 (0.948-0.978)"],["Age (60-69)","0.941 (0.921-0.960)","0.993 (0.986-0.997)"],["Age (70-79)","0.952 (0.916-0.982)","0.974 (0.933-0.997)"],["Age (≥80)","0.928 (0.873-0.977)","0.974 (0.939-0.997)"],["Scanner model","RSNA Test set","VinDr Test set"],["Hologic","-","0.968 (0.952-0.982)"],["Siemens","-","0.999 (0.997-1.000)"],["Fujifilm","-","0.969 (0.944-0.988)"],["GE","-","0.982 (0.961-0.996)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233108-p17-t1","doc_id":"K233108","page_num":17,"bbox":[72.54,403.98,534.0,499.08],"n_rows":3,"n_cols":3,"columns":["Lesion type","RSNA Test set","VinDr Test set"],"rows":[["Lesion type","RSNA Test set","VinDr Test set"],["Mass","-","0.966 (0.951-0.979)"],["Calcification","-","0.963 (0.951-0.974)"]],"caption_candidate":"-","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233112-p6-t0","doc_id":"K233112","page_num":6,"bbox":[120.57,441.22,526.76,698.1],"n_rows":8,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","ANSI AAMI ES60601-1:2005/(R)2012 and A1:2012,\nC1:2009/(R)2012 and A2:2010 /(R)2012 Medical Electrical\nEquipment - Part 1: General Requirements for basic safety and\nessential performance.","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020(4.1 Edition), Medical electrical equipment -\nPart 1-2: General requirements for basic safety and essential\nperformance - EMC","",""],["IEC 60601-2-18","","","IEC 60601-2-18: Edition 3.0 2009-08\nMedical electrical equipment - Part 2-18: Particular requirements for\nthe basic safety and essential performance of endoscopic equipment","",""],["IEC 60601-2-37","","","IEC60601-2-37:2007 + A1:2015, Particular requirements for the\nsafety of ultrasonic medical diagnostic and monitoring equipment","",""],["ISO10993-1","","","ISO 10993-1:2018, Biological evaluation of medical devices -- Part\n1: Evaluation and testing within a risk management process.","",""],["ISO14971","","","ISO 14971:2019, Medical devices - Application of risk management\nto medical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009)\nAcoustic Output Measurement Standard for Diagnostic Ultrasound\nEquipment Revision 3","",""]],"caption_candidate":"following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233112-p8-t0","doc_id":"K233112","page_num":8,"bbox":[125.39,485.41,527.04,563.92],"n_rows":3,"n_cols":9,"columns":["","Validation Type","","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly detected frames\n×100\nTotal number of frames with nerve","","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233112-p8-t1","doc_id":"K233112","page_num":8,"bbox":[125.39,589.84,527.04,631.9],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","91.50","","","5.08","","","88.35 to 94.65","",""],["Speed (FPS)","","","3.71","","","0.06","","","3.65 to 3.78","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233112-p9-t0","doc_id":"K233112","page_num":9,"bbox":[125.37,302.03,526.76,407.12],"n_rows":8,"n_cols":12,"columns":["","","","","Females","","","Males","","","Total",""],"rows":[["","","","","Females","","","Males","","","Total",""],["Number of Subjects","","","13","","","5","","","18","",""],["Number of Images","","","1,168","","","978","","","2,146","",""],["Age range","","","32~68","","","22~50","","","22~68","",""],["Average age","","","45.7","","","35.0","","","42.7","",""],["BMI range","","","16~27.1","","","31.5","","","16~31.5","",""],["Average BMI","","","20.5","","","31.5","","","21.5","",""],["Ethnicity","","","All Koreans","","","","","","","",""]],"caption_candidate":"Testing Data Information on BMI:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p8-t0","doc_id":"K233176","page_num":8,"bbox":[72.3,108.14,769.73,438.79],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uOmnispace.MI","","","uWS-MI (K192630)","",""],["","follow-up PET, CT, MR data, with which users can\ndo image registration, lesion segmentation, and\nstatistical analysis.\nuOmnispace.MI Dynamic Analysis application is\nintended to display PET data and anatomical data\nsuch as CT or MR, and supports to do lesion\nsegmentation and output associated time activity\ncurve.\nuOmnispace.MI NeuroQ application is intended to\nanalyze the brain PET scan, give quantitative results\nof the relative activity of different brain regions, and\nmake comparison of activity of normal brain\nregions in AC database or between two studies from\nthe same patient, as well as provide analysis of\namyloid uptake levels in the brain.\nuOmnispace.MI Emory Cardiac Toolbox\napplication is intended to provide cardiac short axis\nreconstruction, browsing function. And it also\nperforms perfusion analysis, activity analysis and\ncardiac function analysis of the cardiac short axis.","","","and output associated time-activity curve.\nNeuroQ application is intended to analyze the\nbrain PET scan, give quantitative results of the\nrelative activity of 240 different brain regions, and\nmake comparison of activity of normal brain\nregions in AC database or between two studies\nfrom the same patient, as well as provide analysis\nof amyloid uptake levels in the brain.\nEmory Cardiac Toolbox application is intended to\nprovide cardiac short axis reconstruction,\nbrowsing function. And it also performs perfusion\nanalysis, activity analysis and cardiac function\nanalysis of the cardiac short axis.","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p8-t1","doc_id":"K233176","page_num":8,"bbox":[72.3,486.16,759.5,514.19],"n_rows":2,"n_cols":12,"columns":["Application","Function name","","Proposed device","","","Predicate","","","Reference","","Remark"],"rows":[["Application","Function name","","Proposed device","","","Predicate","","","Reference","","Remark"],["","","","uOmnispace.MI","","","device","","","device#2:","",""]],"caption_candidate":"Table 2 Substantial equivalent discussion for MM Fusion","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p9-t0","doc_id":"K233176","page_num":9,"bbox":[155.42,137.9,704.45,559.37],"n_rows":49,"n_cols":7,"columns":["Image Fusion","","Yes","Yes","/","Same",""],"rows":[["Image Fusion","","Yes","Yes","/","Same",""],["","","","","","",""],["Study Comparison","","Yes","Yes","/","Same",""],["","","","","","",""],["3D Visualization","","Yes","Yes","/","Same",""],["","","","","","",""],["","Manual Registration","Yes","Yes","/","Same",""],["","","","","","",""],["Registration","Dot Registration","Yes","Yes","/","Same",""],["","","","","","",""],["","Auto Registration","Yes","Yes","/","Same",""],["","","","","","",""],["Default Layout and C","ustomized Layout","Yes","Yes","/","Functional","Substantial E"],["","","","","","",""],["","","","","","Note1",""],["","","","","","",""],["Position Correction","","Yes","Yes","/","Same",""],["","","","","","",""],["","Fix threshold segmentation","Yes","Yes","/","Same",""],["","","","","","",""],["","Percentage threshold","Yes","Yes","/","Same",""],["","","","","","",""],["Lesion","","","","","",""],["","","","","","",""],["","segmentation","","","","",""],["","","","","","",""],["Segmentation","","","","","",""],["","","","","","",""],["","Adaptive threshold","Yes","Yes","/","Same",""],["","","","","","",""],["","segmentation","","","","",""],["","","","","","",""],["CT Liver Segmentatio","n","Yes","/","Yes","Same",""],["","","","","","",""],["CT Lung Segmentatio","n","Yes","/","Yes","Same",""],["","","","","","",""],["","","Yes","/","Yes","Functional","Substantially"],["Rib Labeling","","","","","",""],["","","","","","",""],["","","","","","Note 2",""],["","","","","","",""],["","","Yes","/","Yes","Functional","Substantially"],["","","","","","",""],["Spine Labeling","","","","","",""],["","","","","","Note 3",""],["","","","","","",""],["Save/Film/Report","","Yes","Yes","/","Same",""],["","","","","","",""],["","Pag","e 6 of 15","","","",""]],"caption_candidate":"MM Fusion Image Fusion Yes Yes / Same","well_formed":true,"extraction_settings":"text"}
{"table_id":"K233176-p10-t0","doc_id":"K233176","page_num":10,"bbox":[72.25,123.74,766.65,519.94],"n_rows":19,"n_cols":10,"columns":["Application","Function name","","Proposed device\nuOmnispace.MI","Predicate\ndevice\nuWS-MI\n(K192630)","Reference\ndevice#2:\nuWS-CT\n(K183170)","","Reference","","Remark"],"rows":[["Application","Function name","","Proposed device\nuOmnispace.MI","Predicate\ndevice\nuWS-MI\n(K192630)","Reference\ndevice#2:\nuWS-CT\n(K183170)","","Reference","","Remark"],["","","","","","","","device#3:","",""],["","","","","","","","syngo.via MI","",""],["","","","","","","","Workflows","",""],["","","","","","","","(K173897)","",""],["MM\nOncology","Registration","Manual Registration","Yes","Yes","/","/","","","Same"],["","","Auto Registration","Yes","Yes","/","/","","","Same"],["","One-Step Evaluation","","Yes","Yes","/","/","","","Same"],["","Lesion\nSegmentation","Fix threshold\nsegmentation","Yes","Yes","/","/","","","Same"],["","","Percentage threshold\nsegmentation","Yes","Yes","/","/","","","Same"],["","","Adaptive threshold\nsegmentation","Yes","Yes","/","/","","","Same"],["","","Lung nodule\nsegmentation","Yes","Yes","/","/","","","Same"],["","","Liver tumor\nsegmentation","Yes","Yes","/","/","","","Same"],["","","Lymph node\nsegmentation","Yes","Yes","/","/","","","Same"],["","Spread","","Yes","Yes","/","/","","","Same"],["","CT liver Segmentation","","Yes","/","Yes","/","","","Same"],["","CT lung Segmentation","","Yes","/","Yes","/","","","Same"],["","Rib Labeling","","Yes","/","Yes","/","","","Functional Substantial\nEquivalent.\nNote 4"],["","Spine Labeling","","Yes","/","Yes","/","","","Functional Substantial\nEquivalent."]],"caption_candidate":"Table 3 Substantial equivalent discussion for MM Oncology","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p11-t0","doc_id":"K233176","page_num":11,"bbox":[72.25,108.02,766.45,223.13],"n_rows":8,"n_cols":8,"columns":["","","","","","","","Note 5"],"rows":[["","","","","","","","Note 5"],["","Statistical Analysis","","Yes","Yes","/","/","Same"],["","Reference VOI","","Yes","Yes","/","/","Same"],["","Response\nAssessment","PERCIST","Yes","Yes","/","/","Same"],["","","RECIST1.0","Yes","Yes","/","/","Same"],["","","RECIST1.1","Yes","/","Yes","/","Same"],["","","Deauville Score","Yes","/","/","Yes","Same"],["","Save","","Yes","Yes","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p11-t1","doc_id":"K233176","page_num":11,"bbox":[72.25,257.33,766.45,500.26],"n_rows":15,"n_cols":10,"columns":["Application","Function name","","","Proposed device","","","Predicate device","","Remark"],"rows":[["Application","Function name","","","Proposed device","","","Predicate device","","Remark"],["","","","","uOmnispace.MI","","","uWS-MI (K192630)","",""],["Dynamic Analysis","Automatic cine","","Yes","","","Yes","","","Same"],["","ROI Drawing","","Yes","","","Yes","","","Same"],["","Data Recombination","","Yes","","","Yes","","","Same"],["","Curve Analysis","","Yes","","","Yes","","","Same"],["","Table Quantization Statistics","","Yes","","","Yes","","","Same"],["","Save","","Yes","","","Yes","","","Same"],["","Print (Filming)","","Yes","","","Yes","","","Same"],["","Registration","Manual Registration","Yes","","","Yes","","","Same"],["","","Dot Registration","Yes","","","Yes","","","Same"],["","","Auto Registration","Yes","","","Yes","","","Same"],["","Lesion\nSegmentation","Fix threshold segmentation","Yes","","","Yes","","","Same"],["","","Percentage threshold\nsegmentation","Yes","","","Yes","","","Same"],["","","Adaptive threshold\nsegmentation","Yes","","","Yes","","","Same"]],"caption_candidate":"Table 4 Substantial equivalent discussion for Dynamic Analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p14-t0","doc_id":"K233176","page_num":14,"bbox":[129.14,496.63,522.96,535.63],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Score based on gold standard","The average score of the proposed device\nresults is higher than 4 points."]],"caption_candidate":"Table 8-1. Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p14-t1","doc_id":"K233176","page_num":14,"bbox":[136.1,686.5,522.96,715.18],"n_rows":2,"n_cols":3,"columns":["Dataset","Patients Number","Samples Number"],"rows":[["Dataset","Patients Number","Samples Number"],["Testing Dataset","267","286"]],"caption_candidate":"2) Sample Size","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p15-t0","doc_id":"K233176","page_num":15,"bbox":[155.18,160.94,490.18,327.41],"n_rows":4,"n_cols":2,"columns":["Information of data","286 spine CTs"],"rows":[["Information of data","286 spine CTs"],["Gender","Male: 68\nFemale: 55\nUnknown: 163"],["Age","(10, 25]: 4\n(25, 40]: 16\n(40, 60]: 45\n(60, 75]: 47\n(75, 100]: 14\nUnknown: 160"],["Ethnicity","Asian(Chinese) data: 106\nEuropean data: 160\nThe United States data: 20"]],"caption_candidate":"Table 8-2. Testing data information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p15-t1","doc_id":"K233176","page_num":15,"bbox":[170.32,451.03,475.15,652.78],"n_rows":15,"n_cols":6,"columns":["","Age","","","Average score of the proposed device",""],"rows":[["","Age","","","Average score of the proposed device",""],["(10, 25]","","","5.000","",""],["(25, 40]","","","5.000","",""],["(40, 60]","","","5.000","",""],["(60, 75]","","","5.000","",""],["(75, 100]","","","5.000","",""],["Unknown","","","4.914","",""],["","Gender","","","Average score of the proposed device",""],["Female","","","5.000","",""],["Male","","","5.000","",""],["Unknown","","","4.913","",""],["","Ethnicity","","","Average score of the proposed device",""],["Asian(Chinese) data","","","5.000","",""],["European data","","","4.913","",""],["The United States data","","","5.000","",""]],"caption_candidate":"Table 8-3. Subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p16-t0","doc_id":"K233176","page_num":16,"bbox":[129.14,370.61,522.96,409.61],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Score based on gold standard","The average score of the proposed device\nresults is higher than 4 points."]],"caption_candidate":"Table8-4. Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p16-t1","doc_id":"K233176","page_num":16,"bbox":[136.1,556.39,522.96,582.67],"n_rows":2,"n_cols":3,"columns":["Dataset","Patients Number","Samples Number"],"rows":[["Dataset","Patients Number","Samples Number"],["Testing Dataset","156","160"]],"caption_candidate":"Table 8-5. Sample size information of testing data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p16-t2","doc_id":"K233176","page_num":16,"bbox":[209.45,670.18,436.06,707.38],"n_rows":2,"n_cols":2,"columns":["Information of data","160 CTs"],"rows":[["Information of data","160 CTs"],["Gender","Male: 110\nFemale: 39"]],"caption_candidate":"Table 8-6. Testing data information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p17-t0","doc_id":"K233176","page_num":17,"bbox":[209.45,75.12,436.06,174.38],"n_rows":3,"n_cols":2,"columns":["","Unknown: 11"],"rows":[["","Unknown: 11"],["Age","(10, 25]: 2\n(25, 40]: 14\n(40, 60]: 51\n(60, 75]: 69\n(75, 100]: 24"],["Ethnicity","Asian(Chinese) data: 80\nThe United States data: 80"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233176-p17-t1","doc_id":"K233176","page_num":17,"bbox":[177.55,280.61,467.94,451.51],"n_rows":13,"n_cols":6,"columns":["","Age","","","Average score of the proposed device",""],"rows":[["","Age","","","Average score of the proposed device",""],["(10, 25]","","","5.00","",""],["(25, 40]","","","5.00","",""],["(40, 60]","","","5.00","",""],["(60, 75]","","","5.00","",""],["(75, 100]","","","5.00","",""],["","Gender","","","Average score of the proposed device",""],["Female","","","5.00","",""],["Male","","","5.00","",""],["Unknown","","","5.00","",""],["","Ethnicity","","","Average score of the proposed device",""],["Asian(Chinese) data","","","5.00","",""],["The United States data","","","5.00","",""]],"caption_candidate":"Table 8-7. Subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p6-t0","doc_id":"K233186","page_num":6,"bbox":[106.58,108.74,546.1,339.89],"n_rows":9,"n_cols":2,"columns":["Device Classification Name","Magnetic resonance diagnostic device"],"rows":[["Device Classification Name","Magnetic resonance diagnostic device"],["510(K) Number","K230152"],["Device Name","uMR Omega"],["Manufacturer","Shanghai United Imaging Healthcare Co., Ltd."],["Regulation Number","21 CFR 892.1000"],["Classification Product Code","LNH"],["Device Classification","Class II"],["Classification Panel","Radiology"],["Intended use","The uMR Omega system is indicated for use as a\nmagnetic resonance diagnostic device (MRDD) that\nproduces sagittal, transverse, coronal, and oblique cross\nsectional images, and spectroscopic images, and that\ndisplay internal anatomical structure and/or function of\nthe head, body and extremities."]],"caption_candidate":"Reference Device #3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p6-t1","doc_id":"K233186","page_num":6,"bbox":[106.58,372.65,546.1,667.42],"n_rows":9,"n_cols":2,"columns":["Device Classification Name","Picture archiving and communication system"],"rows":[["Device Classification Name","Picture archiving and communication system"],["510(K) Number","K113456"],["Device Name","READY View"],["Manufacturer","GE Healthcare"],["Regulation Number","21 CFR 892.2050"],["Classification Product Code","LLZ"],["Device Classification","Class II"],["Classification Panel","Radiology"],["Intended use","READY View is a image analysis software that allows\nthe user to process dynamic or functional volumetric\ndata and to generate maps that display changes in image\nintensity aver time, echo time, lb-vague (Diffusion\nimaging) and frequency (Spectroscopy). The\ncombination of acquired images, reconstructed images,\ncalculated parametric images, tissue segmentation,\nannotations and measurement performed by the clinician\nallows multi-parametric analysis and may provide\nclinically relevant information for diagnosis."]],"caption_candidate":"Reference Device #4","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p10-t0","doc_id":"K233186","page_num":10,"bbox":[70.61,121.58,759.53,505.54],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uOmnispace.MR","","","uWS-MR (K192601)","",""],[""," The uOmnispace.MR Dynamic\napplication is intended to provide a general\npost-processing tool for time course\nstudies.\n The uOmnispace.MR MRS (MR\nSpectroscopy) is intended to evaluate the\nmolecule constitution and spatial\ndistribution of cell metabolism. It provides\na set of tools to view, process, and analyze\nthe complex MRS data. This application\nsupports the analysis for both SVS (Single\nVoxel Spectroscopy) and CSI (Chemical\nShift Imaging) data.\n The uOmnispace.MR MAPs\napplication is intended to provide a number\nof arithmetic and statistical functions for\nevaluating dynamic processes and images.\nThese functions are applied to the grayscale\nvalues of medical images.\n The uOmnispace.MR Breast\nEvaluation application provides the user a","",""," The Dynamic application is intended\nto provide a general post-processing\ntool for time course studies.\n MRS (MR Spectroscopy) is intended\nto evaluate the molecule constitution\nand spatial distribution of cell\nmetabolism. It provides a set of tools\nto view, process, and analyze the\ncomplex MRS data. This application\nsupports the analysis for both SVS\n(Single Voxel Spectroscopy) and CSI\n(Chemical Shift Imaging) data.\n The MAPs application is intended to\nprovide a number of arithmetic and\nstatistical functions for evaluating\ndynamic processes and images. These\nfunctions are applied to the grayscale\nvalues of medical images.\n The MR Breast Evaluation application\nprovides the user a tool to calculate","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p11-t0","doc_id":"K233186","page_num":11,"bbox":[70.61,121.58,759.53,517.54],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uOmnispace.MR","","","uWS-MR (K192601)","",""],["","tool to calculate parameter maps from\ncontrast-enhanced time-course images.\n The uOmnispace.MR Brain\nPerfusion application is intended to allow\nthe visualization of temporal variations in\nthe dynamic susceptibility time series of\nMR datasets.\n The uOmnispace.MR Vessel\nAnalysis is intended to provide a tool for\nviewing, manipulating, and evaluating MR\nvascular images.\n The uOmnispace.MR DCE analysis\nis intended to view, manipulate, and\nevaluate dynamic contrast-enhanced MRI\nimages.\n The uOmnispace.MR United Neuro\nis intended to view, manipulate, and\nevaluate MR neurological images.\n The uOmnispace.MR Cardiac\nFunction is intended to view, evaluate\nfunctional analysis of cardiac MR images.","","","parameter maps from contrast-\nenhanced time-course images.\n The Brain Perfusion application is\nintended to allow the visualization of\ntemporal variations in the dynamic\nsusceptibility time series of MR\ndatasets.\n MR Vessel Analysis is intended to\nprovide a tool for viewing,\nmanipulating, and evaluating MR\nvascular images.\n The DCE analysis is intended to view,\nmanipulate, and evaluate dynamic\ncontrast-enhanced MRI images.\n The United Neuro is intended to view,\nmanipulate, and evaluate MR\nneurological images.\n The MR Cardiac Analysis application\nis intended to be used for viewing,\npost-processing and quantitative","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p12-t0","doc_id":"K233186","page_num":12,"bbox":[71.88,121.58,759.53,206.57],"n_rows":2,"n_cols":6,"columns":["Item","","Proposed Device\nuOmnispace.MR","Predicate Device\nuWS-MR (K192601)","","Remark"],"rows":[["Item","","Proposed Device\nuOmnispace.MR","Predicate Device\nuWS-MR (K192601)","","Remark"],[""," The uOmnispace.MR Flow\nAnalysis is intended to view, evaluate flow\nanalysis of flow MR images.","","evaluation of cardiac magnetic\nresonance data.","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p12-t1","doc_id":"K233186","page_num":12,"bbox":[71.88,237.05,769.77,494.98],"n_rows":8,"n_cols":10,"columns":["Application","Function name","Proposed\ndevice\nuOmnispace.MR","Predicate\nDevice\nuWS-MR\n(K192601)","Reference\nDevice#1\nuMR\nOmega\nwith uWS-\nMR-MRS\n(K220332)","","Reference\nDevice#2\ncvi42\n(K141480)","Reference\nDevice#3\nuMR\nOmega\n(K230152)","Reference\nDevice#4\nREADY\nView\n(K113456)","Remark"],"rows":[["Application","Function name","Proposed\ndevice\nuOmnispace.MR","Predicate\nDevice\nuWS-MR\n(K192601)","Reference\nDevice#1\nuMR\nOmega\nwith uWS-\nMR-MRS\n(K220332)","","Reference\nDevice#2\ncvi42\n(K141480)","Reference\nDevice#3\nuMR\nOmega\n(K230152)","Reference\nDevice#4\nREADY\nView\n(K113456)","Remark"],["MR DCE\nAnalysis","Motion Correction","Yes","Yes","/","","/","/","/","Same"],["","Series Registration","Yes","Yes","/","","/","/","/","Same"],["","Parametric Maps","Yes","Yes","/","","/","/","/","Same"],["","ROI Analysis","Yes","Yes","/","","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","","/","/","/","Same"],["MR Brain\nPerfusion","Motion Correction","Yes","Yes","/","","/","/","/","Same"],["","Background\nRemoval","Yes","Yes","/","","/","/","/","Same"]],"caption_candidate":"Table 2 Substantial equivalent discussion for Advanced Applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p13-t0","doc_id":"K233186","page_num":13,"bbox":[72.24,121.46,769.78,524.26],"n_rows":12,"n_cols":9,"columns":["","Define Arterial\nInput Function\n(AIF)","Yes","Yes","/","/","/","/","Same"],"rows":[["","Define Arterial\nInput Function\n(AIF)","Yes","Yes","/","/","/","/","Same"],["","Parametric\nMapping\nCalculation","Yes","Yes","/","/","/","/","Same"],["","TIC Analysis","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR Breast\nEvaluation","Automatic\nSubtraction","Yes","Yes","/","/","/","/","Same"],["","Motion Correction","Yes","Yes","/","/","/","/","Same"],["","TIC Analysis","Yes","Yes","/","/","/","/","Same"],["","Background\nRemoval","Yes","Yes","/","/","/","/","Same"],["","Parameter Map\nCalculation:WO,\nWI, TTP, PEI and\nMSI","Yes","Yes","/","/","/","/","Same"],["","Parameter Map\nCalculation: SER","Yes","/","/","/","/","Yes","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR\nStitching","Automatic\nStitching","Yes","Yes","/","/","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p14-t0","doc_id":"K233186","page_num":14,"bbox":[72.24,121.46,769.78,509.38],"n_rows":14,"n_cols":9,"columns":["","Manual Stitching","Yes","Yes","/","/","/","/","Same"],"rows":[["","Manual Stitching","Yes","Yes","/","/","/","/","Same"],["","Normalization","Yes","Yes","/","/","/","/","Same"],["","Sharp/Smooth","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR Vessel\nAnalysis","Automatic\nCenterline\nExtraction","Yes","Yes","/","/","/","/","Same"],["","Vascular Stenosis\nAnalysis","Yes","Yes","/","/","/","/","Same"],["","Optimized\nVascular\nDisplaying","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR\nDynamic","Background\nRemoval","Yes","Yes","/","/","/","/","Same"],["","Motion Correction","Yes","Yes","/","/","/","/","Same"],["","TIC Analysis","Yes","Yes","/","/","/","/","Same"],["","Statistic Table","Yes","Yes","/","/","/","/","Same"],["","DCE and DSC\nAnalysis","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p15-t0","doc_id":"K233186","page_num":15,"bbox":[72.24,121.46,769.78,514.54],"n_rows":14,"n_cols":9,"columns":["MR MAPs","Background\nRemoval","Yes","Yes","/","/","/","/","Same"],"rows":[["MR MAPs","Background\nRemoval","Yes","Yes","/","/","/","/","Same"],["","T1, T2/R2,\nT2*/R2*","Yes","Yes","/","/","Yes","/","Same"],["","T1rho Calculation","Yes","/","/","/","Yes","/","Same"],["","ADC and eADC\nCalculation","Yes","Yes","/","/","/","/","Same"],["","TIC Analysis","Yes","Yes","/","/","/","/","Same"],["","Statistic Table","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR United\nNeuro","Motion Correction","Yes","Yes","/","/","/","/","Same"],["","Functional\nActivation\nCalculation","Yes","Yes","/","/","/","/","Same"],["","Diffusion\nParameter\nAnalysis","Yes","Yes","/","/","/","/","Same"],["","Adjust Display\nParameter","Yes","Yes","/","/","/","/","Same"],["","Fusion","Yes","Yes","/","/","/","/","Same"],["","Fiber Tracking","Yes","Yes","/","/","/","/","Same"],["","Time-Intensity\nCurve","Yes","Yes","/","/","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p16-t0","doc_id":"K233186","page_num":16,"bbox":[72.24,121.46,769.78,509.86],"n_rows":15,"n_cols":9,"columns":["","ROI Analysis","Yes","Yes","/","/","/","/","Same"],"rows":[["","ROI Analysis","Yes","Yes","/","/","/","/","Same"],["","MR Segmentation","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR Cardiac\nFunction","LV&RV Contour\nSegmentation","Yes","Yes","/","/","/","/","Same"],["","LAX Extent\nDefinition","Yes","Yes","/","/","/","/","Same"],["","Parameter\nCalculation","Yes","Yes","/","/","/","/","Same"],["","BSA Standardized","Yes","Yes","/","/","/","/","Same"],["","Polar Maps","Yes","Yes","/","/","/","/","Same"],["","Volume Curve","Yes","Yes","/","/","/","/","Same"],["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR Flow\nAnalysis","Contour\nSegmentation","Yes","Yes","/","Yes","/","/","Substantial\nequivalent\nNote 2"],["","Propagate Contour","Yes","Yes","/","/","/","/","Same"],["","Doppler Map","Yes","Yes","/","/","/","/","Same"],["","Parameters\nCalculation","Yes","Yes","/","/","/","/","Substantial\nequivalent\nNote 3"],["","Flow Curve","Yes","Yes","/","/","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p17-t0","doc_id":"K233186","page_num":17,"bbox":[72.24,121.46,769.78,330.79],"n_rows":6,"n_cols":9,"columns":["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],"rows":[["","Save, Filming and\nReport","Yes","Yes","/","/","/","/","Same"],["MR MRS","Single-Voxel\nSpectrum Data\nAnalysis","Yes","/","Yes","/","/","/","Same"],["","Chemical Shift\nImaging Data\nAnalysis","Yes","/","Yes","/","/","/","Same"],["","Protocol\nManagement","Yes","/","Yes","/","/","/","Same"],["","Protocol Editing","Yes","/","Yes","/","/","/","Same"],["","Save, Filming and\nReport","Yes","/","Yes","/","/","/","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p19-t0","doc_id":"K233186","page_num":19,"bbox":[129.14,422.21,522.96,516.31],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Dice","To evaluate the proposed device of automatic ventricular\nsegmentation, we compared the results with those of the\ncardiac function application of predicate device. The\nSørensen–Dice coefficient is used to evaluate consistency.\nIf dice>0.95, it is considered consistent between the two\ndevices."]],"caption_candidate":"The validation type and acceptance criteria is shown in the Table 1 below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p19-t1","doc_id":"K233186","page_num":19,"bbox":[155.18,574.15,490.18,713.62],"n_rows":3,"n_cols":2,"columns":["Information of data","114 samples from 114 different\npatients"],"rows":[["Information of data","114 samples from 114 different\npatients"],["Gender","Male: 35\nFemale:20\nUnknown: 59"],["Age","[14, 25]: 5\n(25, 40]: 12\n(40, 60]: 22\n(60, 79]: 13\nUnknown: 62"]],"caption_candidate":"Table 1 Testing data information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p20-t0","doc_id":"K233186","page_num":20,"bbox":[155.18,75.12,490.18,214.58],"n_rows":3,"n_cols":2,"columns":["Ethnicity","Europe: 50\nAsia: 53\nUSA: 11"],"rows":[["Ethnicity","Europe: 50\nAsia: 53\nUSA: 11"],["Manufacturer","UIH: 58\nGE: 2\nPhilips: 2\nSiemens: 52"],["Magnetic Field","1.5T: 23\n3.0T: 41\nUnknown: 50"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233186-p20-t1","doc_id":"K233186","page_num":20,"bbox":[206.47,270.41,438.92,598.75],"n_rows":23,"n_cols":6,"columns":["","Gender","","","Average dice",""],"rows":[["","Gender","","","Average dice",""],["Female","","","1.00","",""],["Male","","","1.00","",""],["Unknown","","","1.00","",""],["","Age","","","Average dice",""],["[14, 25]","","","1.00","",""],["(25, 40]","","","1.00","",""],["(40, 60]","","","1.00","",""],["(60, 79]","","","1.00","",""],["","Ethnicity","","","Average dice",""],["Europe","","","1.00","",""],["Asia","","","1.00","",""],["USA","","","1.00","",""],["","Manufacturer","","","Average dice",""],["UIH","","","1.00","",""],["GE","","","1.00","",""],["Philips","","","1.00","",""],["Siemens","","","1.00","",""],["","Magnetic","","Average dice","",""],["","Field","","","",""],["1.5T","","","1.00","",""],["3.0T","","","1.00","",""],["Unknown","","","1.00","",""]],"caption_candidate":"consistency between the two devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233195-p5-t0","doc_id":"K233195","page_num":5,"bbox":[106.14,112.5,544.38,254.94],"n_rows":3,"n_cols":4,"columns":["Product","Marketed by","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","510(k) Number","Clearance Date"],["Aplio i900/i800/i700 Diagnostic\nUltrasound System, Software\nV7.0 (Primary predicate)","Canon Medical\nSystems USA, Inc.","K223017","March 31, 2023"],["OLYMPUS GF TYPE UC180,\nOLYMPUS GF TYPE UCT180 EVIS\nEXERA II ULATRASOUND\nGASTROVIDEOSCOPE\n(Reference device)","Olympus Medical\nSystems\nCorporation","K093395","June 17, 2010"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p6-t0","doc_id":"K233196","page_num":6,"bbox":[72.27,228.13,545.72,664.32],"n_rows":13,"n_cols":9,"columns":["Item","","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],"rows":[["Item","","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],["","","","","(K202501)","","","Equivalence",""],["Regulatory Data","","","","","","","",""],["Regulatory\nClass","","Class II","Class II","","","Equivalent","",""],["Classification\nName","","Medical image management\nand processing system","Picture archiving and\ncommunications system","","","Equivalent1","",""],["Regulation\nNumber","","21 CFR 892.2050","21 CFR 892.2050","","","Equivalent","",""],["Product Code","","QIH","LLZ","","","Equivalent","",""],["","Use","","","","","","",""],["Target users","","Trained medical professionals","Trained medical professionals","","","Equivalent","",""],["Anatomical site","","Prostate","Prostate","","","Equivalent","",""],["Where used","","Hospital","Hospital","","","Equivalent","",""],["Workflow\nConsiderations","","• User can approve or reject\nresults\n• User can inspect and edit\nprostate segmentation\n• User can enter PSA value\nand compute PSA density\n• User can create and update\nregions of interest (ROIs)\n• User can add and update\nannotations (text) to analysis\n• User can manually set a PI-\nRADS score using a PI-RADS\ninteractive worksheet","• User can approve or reject\nresults\n• User can inspect and edit\nprostate segmentation\n• User can enter PSA value\nand compute PSA density\n• User can create and update\nregions of interest (ROIs)\n• User can add and update\nannotations (text) to analysis\n• User can manually set a PI-\nRADS score using a PI-RADS\ninteractive worksheet","","","Equivalent","",""],["","Technical characteristics","","","","","","",""]],"caption_candidate":"Substantial Equivalence Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p7-t0","doc_id":"K233196","page_num":7,"bbox":[72.26,85.93,545.74,722.4],"n_rows":7,"n_cols":8,"columns":["Item","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],"rows":[["Item","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],["","","","(K202501)","","","Equivalence",""],["Design","• Semi-automatic prostate\nsegmentation\n• Multi parametric image\nreview\n• Biparametric combination\nimage viewer\n• Basic image manipulation\ntools, Thresholding tool\n• User interface to\ncreate/update user generated\nROIs","• Semi-automatic prostate\nsegmentation\n• Multi parametric image\nreview\n• Biparametric combination\nimage viewer\n• Basic image manipulation\ntools, Thresholding tool\n• User interface to\ncreate/update user generated\nROIs","","","Equivalent","",""],["Non-clinical\nperformance","• Bench testing performed to\ntest the functionality of the\nsystem\n• This included\ncharacterization of the\nstandalone performance of\nthe prostate segmentation\nalgorithm.","• Bench testing performed to\ntest the functionality of the\nsystem\n• This included\ncharacterization of the\nstandalone performance of\nthe prostate segmentation\nalgorithm.","","","Equivalent","",""],["Clinical\nperformance","• Prostate segmentation\nalgorithm was tested in a\nclinical use context\n• i.e. as a semiautomatic\nalgorithm after correction by\ntrained clinicians.","• Prostate segmentation\nalgorithm was tested in a\nclinical use context\n• i.e. as a semiautomatic\nalgorithm after correction by\ntrained clinicians.","","","Equivalent","",""],["Standards met","• IS0 14971 – Medical devices\n–Application of risk\nmanagement to medical\ndevices\n• IEC 62304 – Medical device\nsoftware – Software life cycle\nprocesses\n• IEC 62366 – Medical\ndevices – Application of\nusability engineering to\nmedical devices","• IS0 14971 – Medical devices\n–Application of risk\nmanagement to medical\ndevices\n• IEC 62304 – Medical device\nsoftware – Software life cycle\nprocesses\n• IEC 62366 – Medical\ndevices – Application of\nusability engineering to\nmedical devices","","","Equivalent","",""],["SW verification\nand validation","• Tested in accordance with\nverification and validation\nprocesses and planning\n• The testing results support\nthat all the system\nrequirements have met their\nacceptance criteria and are\nadequate for its intended use","• Tested in accordance with\nverification and validation\nprocesses and planning\n• The testing results support\nthat all the system\nrequirements have met their\nacceptance criteria and are\nadequate for its intended use","","","Equivalent","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p8-t0","doc_id":"K233196","page_num":8,"bbox":[72.27,85.93,545.73,345.96],"n_rows":5,"n_cols":8,"columns":["Item","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],"rows":[["Item","MEDIHUB PROSTATE","","Quantib Prostate","","","Substantial",""],["","","","(K202501)","","","Equivalence",""],["Compatibility\nwith the\nenvironment\nand other\ndevices","DICOM compatible","DICOM compatible","","","Equivalent","",""],["Reported\nmeasures","Prostate gland Volume, PSA\ndensity, ROIs within the\nprostate, with for each ROI:\n• Volume\n• Average ADC value\n• PI-RADS score\n• Location","Prostate gland volume, PSA\ndensity, ROIs within the\nprostate, with for each ROI:\n• Volume\n• Average ADC value\n• PI-RADS score\n• Location","","","Equivalent","",""],["Required input","DICOM compatible data, type\nof MRI scans: T2-weighted,\nDWI, ADC, DCE","DICOM compatible data, type\nof MRI scans: T2-weighted,\nDWI, ADC, DCE","","","Equivalent","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p9-t0","doc_id":"K233196","page_num":9,"bbox":[72.3,687.32,526.2,744.81],"n_rows":6,"n_cols":5,"columns":["","","","Male, 114 (100%)",""],"rows":[["","","","Male, 114 (100%)",""],["","Gender, n(%)","","",""],["","","","",""],["","","","Mean ± SD","66.38 ± 5.33"],["Age","","","",""],["","","","Median (Min, Max)","66 (57, 78)"]],"caption_candidate":"Demographic information on subjects (N=114)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p10-t0","doc_id":"K233196","page_num":10,"bbox":[72.19,85.38,526.2,200.49],"n_rows":8,"n_cols":3,"columns":["","55~59","14 (12.3%)"],"rows":[["","55~59","14 (12.3%)"],["Age group, n (%)","",""],["","60~69","63 (55.3%)"],["","70~79","37 (32.5%)"],["","White","106 (92.9%)"],["Races","",""],["","African American","7 (6.1%)"],["","Asian","1 (0.9%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p10-t1","doc_id":"K233196","page_num":10,"bbox":[72.19,298.16,519.69,397.2],"n_rows":4,"n_cols":3,"columns":["Race","Dice Coefficient","Hausdorff Distance"],"rows":[["Race","Dice Coefficient","Hausdorff Distance"],["White","0.929\n*[0.925, 0.933]","2.173\n*[2.066, 2.280]"],["African\nAmerican","0.925\n*[0.902, 0.949]","2.085\n*[1.711, 2.459]"],["Asian","0.917\n*[nan, nan]","2.929\n*[nan, nan]"]],"caption_candidate":"comparing ground truth and the result of algorithms by race","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p10-t2","doc_id":"K233196","page_num":10,"bbox":[72.19,461.0,519.69,533.16],"n_rows":3,"n_cols":3,"columns":["Age","Dice Coefficient","Hausdorff Distance"],"rows":[["Age","Dice Coefficient","Hausdorff Distance"],["< 60","0.938\n*[0.925, 0.950]","1.871\n*[1.638, 2.103]"],["≥ 60","0.927\n*[0.923, 0.931]","2.224\n*[2.114, 2.335]"]],"caption_candidate":"comparing ground truth and the result of algorithms by age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233196-p11-t0","doc_id":"K233196","page_num":11,"bbox":[93.38,138.1,505.06,254.4],"n_rows":6,"n_cols":6,"columns":["","Properties","","","Value",""],"rows":[["","Properties","","","Value",""],["Sites","","","University of Missouri Health Care","",""],["Field Strengths","","","3T","",""],["MR Scanner Manufacturer","","","SIEMENS, Siemens HealthCare GmbH","",""],["Thickness","","","3.5mm, 5mm","",""],["Purpose of AI","","","Prostate region semi auto-segmentation","",""]],"caption_candidate":"Properties of Performance Testing Cases","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233209-p10-t0","doc_id":"K233209","page_num":10,"bbox":[36.65,114.72,752.45,526.2],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uOmnispace.CT","","","uWS-CT(K183170)","",""],["","such as: CBV, CBF, etc. in order to analyze\nfunctional blood flow information about a region of\ninterest (ROI) in brain.\n The uOmnispace.CT Heart application is\nintended to segment heart and extract coronary\nartery. It also provides analysis of vascular stenosis,\nplaque and heart function.\n The uOmnispace.CT Calcium Scoring\napplication is intended to identify calcifications and\ncalculate the calcium score.\n The uOmnispace.CT Dynamic Analysis\napplication is intended to support visualization of the\nCT datasets over time with the 3D/4D display\nmodes.\n The uOmnispace.CT Bone Structure\nAnalysis application is intended to provide\nvisualization and labels for the ribs and spine, and\nsupport batch function for intervertebral disk.\n The uOmnispace.CT Liver Evaluation\napplication is intended to provide processing and\nvisualization for liver segmentation and vessel\nextraction. It also provides a tool for the user to\nperform liver separation and residual liver segments\nevaluation.\n The uOmnispace.CT Dual Energy Analysis\nis a post-processing software package that accepts\nUIH CT images acquired using different tube\nvoltages and/or tube currents of the same anatomical\nlocation. The uOmnispace.CT Dual Energy\napplication is intended to provide information on the\nchemical composition of the scanned body materials\nand/or contrast agents. Additionally, it enables","","","information about a region of interest (ROI) in the\nbrain.\n The CT Heart application is intended to\nsegment heart and extract coronary artery. It also\nprovides analysis of vascular stenosis, plaque and\nheart function.\n The CT Calcium Scoring application is\nintended to identify calcifications and calculate the\ncalcium score.\n The CT Dynamic Analysis application is\nintended to support visualization of the CT datasets\nover time with the 3D/4D display modes.\n The CT Bone Structure Analysis application\nis intended to provide visualization and labels for the\nribs and spine, and support batch function for\nintervertebral disk.\n The CT Liver Evaluation application is\nintended to provide processing and visualization for\nliver segmentation and vessel extraction. It also\nprovides a tool for the user to perform liver\nseparation and residual liver segments evaluation.","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233209-p11-t0","doc_id":"K233209","page_num":11,"bbox":[36.65,114.72,752.45,284.69],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uOmnispace.CT","","","uWS-CT(K183170)","",""],["","images to be generated at multiple energies within\nthe available spectrum.\n The uOmnispace.CT Cardiovascular\nCombined Analysis is an image analysis software\npackage for evaluating contrast enhanced CT\nimages. The CT Cardiovascular Combined Analysis\nis intended to analyze vascular and cardiac\nstructures.It can be used in the qualitative and\nquantitative for the analysis of head-neck, abdomen,\nmulti-body part combined, TAVR (Transcatheter\nAortic Valve Replacement) CT data as input for the\nplanning of cardiovascular procedures.","","","","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233209-p12-t0","doc_id":"K233209","page_num":12,"bbox":[72.01,128.66,710.01,308.59],"n_rows":12,"n_cols":7,"columns":["Application","Function name","","Proposed device","","Predicate device:\nuWS-CT(K183170)","Remark"],"rows":[["Application","Function name","","Proposed device","","Predicate device:\nuWS-CT(K183170)","Remark"],["","","","uOmnispace.CT","","",""],["","","","","","",""],["uOmnispace.CT Lung\nDensity Analysis","Lung Segmentation","Yes","","","Yes","Same"],["","Lung Density Analysis","Yes","","","Yes","Same"],["","Lung Contour Editing","Yes","","","Yes","Same"],["","Pulmonary lobes Segmentation","Yes","","","Yes","Same"],["","Airway Segmentation","Yes","","","Yes","Same"],["","Airway Tree Extraction and Editing","Yes","","","Yes","Same"],["","Airway Contour Editing","Yes","","","Yes","Same"],["","Statistical Analysis","Yes","","","Yes","Same"],["","Save, Report, Print","Yes","","","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233209-p13-t0","doc_id":"K233209","page_num":13,"bbox":[77.4,58.1,633.26,351.31],"n_rows":24,"n_cols":6,"columns":["Shanghai United Imaging H","ealthcare Co., Ltd.","","","",""],"rows":[["Shanghai United Imaging H","ealthcare Co., Ltd.","","","",""],["Tel: +86 (21) 67076888","Fax：+86 (21) 67076889","","","",""],["www.united-imaging.com","","","","",""],["","","","","",""],["Application","Function Name","Proposed Device","Predicate","Reference Device#5","Remark"],["","","uOmnisapce.CT","Device: i","Schema View's RAPID",""],["","","","uWS-CT","（K182130）",""],["","","","(K183170)","",""],["uOmnispace.CT","Motion Correction","Yes","Yes","/","Same"],["Brain Perfusion","Arterial Detection","Yes","Yes","/","Same"],["","","","","",""],["","Parameter Map","Yes","Yes","/","Same"],["","Calculation","","","",""],["","Time-density curve","Yes","Yes","/","Same"],["","analysis","","","",""],["","Tmax","Yes","/","Yes","Functional"],["","","","","","Equivalent"],["","","","","","Note 1"],["","Ischemic penumbra","Yes","/","Yes","Functional"],["","analysis","","","","Equivalent"],["","","","","","Note 2"],["","Symmetric ROI and","Yes","Yes","/","Same"],["","ROI Template","","","",""],["","Save, Report, Print","Yes","Yes","/","Same"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K233209-p14-t0","doc_id":"K233209","page_num":14,"bbox":[79.1,114.74,714.76,339.42],"n_rows":14,"n_cols":8,"columns":["Application","Function name","Proposed device\nuOmnispace.CT","Predicate device:\nuWS-CT\n(K183170)","","Reference","","Remark"],"rows":[["Application","Function name","Proposed device\nuOmnispace.CT","Predicate device:\nuWS-CT\n(K183170)","","Reference","","Remark"],["","","","","","device#2","",""],["","","","","","UOmnispace","",""],["","","","","","(K230039)","",""],["uOmnispace.\nCT Heart","Multi-Phase Loading","Yes","Yes","/","","","Same"],["","Hyper Realistic Rendering","Yes","/","Yes","","","Same"],["","Heart Chamber Segmentation","Yes","Yes","","/","","Same"],["","Coronary Artery Extraction","Yes","Yes","/","","","Same"],["","Editing Tools","Yes","Yes","","/","","Same"],["","Centerline Extraction","Yes","Yes","","/","","Same"],["","Stenosis Analysis","Yes","Yes","","/","","Same"],["","Plaque Analysis","Yes","Yes","","/","","Same"],["","Cardiac function Assessment","Yes","Yes","/","/","","Functional Substantial\nEquivalent\nNote 3"],["","Save, Report, Print","Yes","Yes","","/","","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K233209-p28-t2","doc_id":"K233209","page_num":28,"bbox":[136.12,544.75,523.15,762.94],"n_rows":17,"n_cols":9,"columns":["","All","","","Mean Landmark Error (mm)","","","Average Score",""],"rows":[["","All","","","Mean Landmark Error (mm)","","","Average Score",""],["All data","","","0.86","","","3","",""],["Age","","","Mean Landmark Error (mm)","","","Average Score","",""],["[40, 60)","","","0.888","","","3","",""],["[60, 70)","","","0.818","","","3","",""],["[70, 80)","","","0.907","","","3","",""],["[80, 100)","","","0.845","","","3","",""],["unknown","","","0.85","","","3","",""],["","Gender","","","Mean Landmark Error (mm)","","","Average Score",""],["Female","","","0.9","","","3","",""],["Male","","","0.834","","","3","",""],["Unknown","","","0.85","","","3","",""],["Ethnicity","","","Mean Landmark Error (mm)","","","Average Score","",""],["Asia","","","0.852","","","3","",""],["U.S.","","","0.866","","","3","",""],["","US. Facility","","","Mean Landmark Error (mm)","","","Average Score",""],["U.S. Facility 1","","","0.872","","","3","",""]],"caption_candidate":"Table 8-9. Subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233211-p5-t0","doc_id":"K233211","page_num":5,"bbox":[36.31,532.42,560.56,751.69],"n_rows":9,"n_cols":12,"columns":["","Characteristic","","","Subject Device","","","Predicate Device","","","Reference Device",""],"rows":[["","Characteristic","","","Subject Device","","","Predicate Device","","","Reference Device",""],["","Device Name","","","AVIEW CAC","","","AVIEW","","","HealthCCSng",""],["Classification Name","Classification Name","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","","","Medical Image\nManagement and\nProcessing System","",""],["","Regulatory Number","","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.1750","",""],["","Product Code","","QIH, JAK","","","QIH, JAK","","","JAK","",""],["","Review Panel","","Radiology","","","Radiology","","","Radiology","",""],["","510k Number","","-","","","K214036","","","K210085","",""],["Indications for use","Indications for use","","AVIEW CAC","","","","","","","",""],["","","","AVIEW CAC provides quantitative analysis of calcified plaques in the coronary arteries\nusing non-contrast/non-gated Chest CT scans. It enables the calculation of the Agatston\nscore for coronary artery calcification, segmenting and evaluating the right coronary artery\nand left coronary artery. Also provide risk stratification based on calcium score, gender,\nand age, offering percentile-based risk categories by established guidelines. Designed for\nhealthcare professionals, including radiologists and cardiologists, AVIEW CAC supports","","","","","","","",""]],"caption_candidate":"tests, we conclude that the proposed device is substantially equivalent to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233211-p6-t0","doc_id":"K233211","page_num":6,"bbox":[36.31,84.53,560.58,747.91],"n_rows":7,"n_cols":2,"columns":["","storing, transferring, inquiring, and displaying CT data sets on-premises, facilitating\naccess through mobile devices and Chrome browsers. AVIEW CAC analyzes existing non-\ncontrast/non-gated Chest CT studies that include the heart of adult patients above the age\nof 40. Also, the device's use should be limited to CT scans acquired on General Electric\n(GE) or its subsidiaries (e.g., GE Healthcare) equipment. Use of the device with CT scans\nfrom other manufacturers has not been validated or recommended."],"rows":[["","storing, transferring, inquiring, and displaying CT data sets on-premises, facilitating\naccess through mobile devices and Chrome browsers. AVIEW CAC analyzes existing non-\ncontrast/non-gated Chest CT studies that include the heart of adult patients above the age\nof 40. Also, the device's use should be limited to CT scans acquired on General Electric\n(GE) or its subsidiaries (e.g., GE Healthcare) equipment. Use of the device with CT scans\nfrom other manufacturers has not been validated or recommended."],["","AVIEW"],["","AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets.\nThis software can be used to support the physician providing quantitative analysis of CT\nimages by image segmentation of sub-structures in the lung, lobe, airways, fissures\ncompleteness, cardiac, density evaluation, and reporting tools. AVIEW is also used to\nstore, transfer, inquire and display CT data set on-premises and as a cloud environment to\nallow users to connect by various environments such as mobile devices and Chrome\nbrowsers. Converts the sharp kernel to soft kernel for quantitative analysis of segmenting\nlow attenuation areas of the lung. Characterizing nodules in the lung in a single study or\nover the time course of several thoracic studies. Characterizations include nodule type,\nlocation of the nodule, and measurements such as size (major axis, minor axis), estimated\neffective diameter from the volume of the nodule, the volume of the nodule, Mean HU(the\naverage value of the CT pixel inside the nodule in HU), Minimum HU, Max HU,\nmass(mass calculated from the CT pixel value), and volumetric measures(Solid major;\nlength of the longest diameter measure in 3D for a solid portion of the nodule, Solid 2nd\nMajor: The size of the longest diameter of the solid part, measured in sections\nperpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling\ntime), and Lung-RADS (classification proposed to aid with findings.). The system\nautomatically performs the measurement, allowing lung nodules and measurements to be\ndisplayed and, integrate with FDA certified Mevis CAD (Computer aided detection)\n(K043617). It also provides the Agatston score, volume score, and mass score by the whole\nand each artery by segmenting four main arteries (right coronary artery, left main coronary,\nleft anterior descending, and left circumflex artery). Based on the calcium score provides\nCAC risk based on age and gender. The device is indicated for adult patients only."],["","HealthCCSng"],["","The HealthCCSng device is intended for use as a non-invasive post-processing\nsoftware to evaluate calcified plaques in the coronary arteries, which present a risk\nfor coronary artery disease. The software generates an estimated coronary artery\ncalcium detection category.\nThe HealthCCSng device analyzes existing non-cardiac-gated CT studies that\ninclude the heart of adult patients above the age of 30. The device generates a three-\ncategory output representing the estimated quantity of calcium detected together\nwith preview axial images of the detected calcium meant for informational\npurposes only. The device output will be available to the radiologist as part of their\nstandard workflow. The HealthCCSng results are not intended to be used on a\nstand-alone basis for risk attribution, clinical decision-making or otherwise\npreclude clinical assessment of CT studies"],["General Description","AVIEW CAC"],["","The AVIEW CAC is a software product that can be installed on a PC. It shows images\ntaken with the interface from various storage devices using DICOM 3.0, the digital image\nand communication standard in medicine. It also offers functions such as reading,\nmanipulation, analyzing, post-processing, saving, and sending images by using software\ntools. And is intended for use as a quantitative analysis of CT scanning. It also provides a\ncalcium score by automatically analyzing coronary arteries from the segmented arteries."]],"caption_candidate":"core:line","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233211-p9-t0","doc_id":"K233211","page_num":9,"bbox":[145.48,659.5,556.34,719.4],"n_rows":5,"n_cols":14,"columns":["","","","Ground Truth","","","","","","Predicate","","","",""],"rows":[["","","","Ground Truth","","","","","","Predicate","","","",""],["","","","ICC (95% CI)","","","p-value(>0.8)","","","ICC (95% CI)","","","p-value(>0.8)",""],["Total\n(n=150)\nI","Total","0.896(0.857,0.925)","","","<.001","","","0.939(0.916,0.956)","","","<.001","",""],["","LCA\ni----------","0.927(0.899,0.947)\nI -----+--\n----1","","","<.001\n---------+","","","0.955(0.938,0.968)\n------------","","","<.001\n-+-------","",""],["","RCA","0.840(0.778,0.884)","","","<.001","","","0.887(0.844,0.918)","","","<.001","",""]],"caption_candidate":"• Performance testing results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p5-t0","doc_id":"K233247","page_num":5,"bbox":[79.32,516.96,532.56,717.36],"n_rows":4,"n_cols":3,"columns":["Device name","Subject device\nHeuron ICH","Primary predicate device\nBriefCase (K221240)"],"rows":[["Device name","Subject device\nHeuron ICH","Primary predicate device\nBriefCase (K221240)"],["Manufacture","Heuron Co., Ltd.","Aidoc Medical, Ltd"],["Product code","QAS","QAS"],["Indications for\nUse","Heuron ICH is radiological computer-aided\ntriage and notification software designed\nfor the analysis of non-contrast head CT\nimages in adults or transitional adolescents\naged 18 and older. This device is intended\nto aid appropriately trained medical\nspecialists and hospital networks in\nstreamlining workflow by identifying and\ncommunicating suspected positive findings\nof Intracranial hemorrhage (ICH).","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of nonenhanced head\nCT images in adults or transitional\nadolescents aged 18 and older. The device\nis intended to assist hospital networks and\nappropriately trained medical specialists in\nworkflow triage by flagging and\ncommunication of suspected positive\nfindings of Intracranial hemorrhage (ICH)\npathologies."]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p6-t0","doc_id":"K233247","page_num":6,"bbox":[79.32,78.24,532.56,651.36],"n_rows":9,"n_cols":3,"columns":["","Heuron ICH employs an artificial\nintelligence algorithm to analyze non-\ncontrast CT images, flagging cases with\nidentified findings through a dedicated\napplication that operates in parallel with the\nstandard of care image interpretation\nprocess. Users receive notifications for\ncases with suspected findings, which\ninclude compressed preview images\nprovided for informational purposes only\nand are not intended for diagnostic use\nbeyond notification. Importantly, Heuron\nICH does not modify the original medical\nimages and is not intended to serve as a\ndiagnostic device.\nThe results generated by Heuron ICH are\nintended to complement other patient\ninformation and assist medical specialists in\nprioritizing and triaging medical images.\nNotified medical specialists are responsible\nfor viewing the full non-contrast CT images\nin accordance with established standard of\ncare practices.","BriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented with\nnotification for cases with suspected\nfindings. Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended\nto be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on their professional\njudgment, to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care."],"rows":[["","Heuron ICH employs an artificial\nintelligence algorithm to analyze non-\ncontrast CT images, flagging cases with\nidentified findings through a dedicated\napplication that operates in parallel with the\nstandard of care image interpretation\nprocess. Users receive notifications for\ncases with suspected findings, which\ninclude compressed preview images\nprovided for informational purposes only\nand are not intended for diagnostic use\nbeyond notification. Importantly, Heuron\nICH does not modify the original medical\nimages and is not intended to serve as a\ndiagnostic device.\nThe results generated by Heuron ICH are\nintended to complement other patient\ninformation and assist medical specialists in\nprioritizing and triaging medical images.\nNotified medical specialists are responsible\nfor viewing the full non-contrast CT images\nin accordance with established standard of\ncare practices.","BriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented with\nnotification for cases with suspected\nfindings. Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended\nto be used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on their professional\njudgment, to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care."],["Anatomical\nregion","Head","Head"],["User","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Compatible\ninput data\nformat and\nmodality","Non-enhanced CT","Non-enhanced CT"],["Image format","DICOM","DICOM"],["Technical\nImplementation","AI/ML/Neural Network","AI/ML/Neural Network"],["Directs user to\nfinding","No, the device does not highlight or direct a\nuser’s attention to a specific location in the\nimage file.","No, the device does not highlight or direct a\nuser’s attention to a specific location in the\nimage file."],["Alteration of\noriginal image\ndata","No","No"],["Notification/\nPrioritization","Yes – PACS, Workstation, email, mobile\n(Push, SMS)","Yes – PACS, Workstation, email, mobile"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p7-t0","doc_id":"K233247","page_num":7,"bbox":[108.24,329.52,539.76,549.36],"n_rows":16,"n_cols":3,"columns":["Demographic","","Total (N = 600)"],"rows":[["Demographic","","Total (N = 600)"],["Gender","Female","288 (48.0%)"],["","Male","312(52.0%)"],["Age","(cid:3409)65 years","263 (43.8%)"],["",">65 tears","337 (56.2%)"],["Race","Asian","26(4.3%)"],["","Black or African American","35 (5.8%)"],["","White","496 (82.7%)"],["","Other","28(4.7%)"],["","2 or more races","3 (0.5%)"],["","Declined","4(0.7%)"],["","Unavailable","8(1.3%)"],["Ethnicity","Hispanic","58(9.7%)"],["","Not Hispanic","526 (87.7%)"],["","Declined","2(0.3%)"],["","Unavailable","14(2.3%)"]],"caption_candidate":"Demographic information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p7-t1","doc_id":"K233247","page_num":7,"bbox":[108.24,602.76,539.76,643.92],"n_rows":3,"n_cols":4,"columns":["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],["< 2.5 mm","0.936 (0.910,0.958)","87.7 (82.9,92.0)","82.9 (77.6,87.6)"],["2.5 to 5 mm (inclusive)","0.974 (0.961,0.985)","89.1 (85.5,92.7)","95.0 (92.5,97.2)"]],"caption_candidate":"Slice thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p7-t2","doc_id":"K233247","page_num":7,"bbox":[108.24,670.8,539.76,712.08],"n_rows":3,"n_cols":4,"columns":["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],["Female","0.915 (0.878,0.947)","79.8 (72.3,86.6)","87.0 (81.7,91.7)"],["Male","0.971 (0.954,0.984)","91.1 (86.7,94.9)","88.3 (83.1,92.9)"]],"caption_candidate":"Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p8-t0","doc_id":"K233247","page_num":8,"bbox":[108.24,104.64,539.76,146.16],"n_rows":3,"n_cols":4,"columns":["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],["(cid:3409) 65 years","0.955 (0.930,0.974)","84.5 (77.7,91.3)","90.0 (85.0,94.4)"],[">65 years","0.940 (0.912,0.963)","87.4 (82.2,92.0)","85.3 (79.8,90.8)"]],"caption_candidate":"Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p8-t1","doc_id":"K233247","page_num":8,"bbox":[108.24,173.04,539.76,238.56],"n_rows":4,"n_cols":4,"columns":["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],["GE Healthcare","0.956 (0.920,0.982)","85.7 (78.0,92.3)","94.5 (89.9,98.2)"],["Siemens\n(slice thickness 2.5-5mm)*","0.982 (0.963,0.994)","93.7 (88.4, 97.9)","92.1 (87.1, 97.0)"],["Toshiba","0.978 (0.955,0.993)","82.4 (73.6,90.1)","97.3 (93.8,100.0)"]],"caption_candidate":"Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233247-p8-t2","doc_id":"K233247","page_num":8,"bbox":[108.24,284.04,539.76,325.2],"n_rows":3,"n_cols":4,"columns":["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["Subgroup","AUC (95% CI)","Sensitivity (95% CI)","Specificity (95% CI)"],["No additional findings","0.962 (0.935,0.982)","89.1 (83.6,94.5)","90.9 (86.4,94.9)"],["Any finding","0.926 (0.897,0.951)","84.4 (79.0,89.8)","83.7 (77.6,89.1)"]],"caption_candidate":"Co-existing findings or abnormalities","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233334-p5-t0","doc_id":"K233334","page_num":5,"bbox":[113.64,67.68,594.0,215.88],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Aquilion Serve (TSX-\n307A/1) V1.3\nPrimary Predicate","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K231281","September\n19, 2023"],["Aquilion Prime SP\n(TSX-303B/8) V10.2\nwith AiCE-i\nReference Predicate","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K192832","February 21,\n2020"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233334-p6-t0","doc_id":"K233334","page_num":6,"bbox":[112.02,55.05,579.58,511.99],"n_rows":17,"n_cols":8,"columns":["","Subject Device","","Primary Predicate","","","Reference Predicate",""],"rows":[["","Subject Device","","Primary Predicate","","","Reference Predicate",""],["","","","Device","","","Device",""],["Device Name,\nModel Number","Aquilion Serve SP\n(TSX-307B/1) V1.3","Aquilion Serve\n(TSX-307A/1) V1.3","Aquilion Serve","","","Aquilion Prime SP",""],["","","","","","","(TSX-303B/8) V10.2 with",""],["","","","(TSX-307A/1) V1.3","","","",""],["","","","","","","AiCE-i",""],["510(k) Number","This submission","K231281","","","K192832","",""],["X-ray generation","","","","","","",""],["Channel-direction\n(fan) angle","49.2°","49.2°","","","49.2°","",""],["Rated output","Max.72 kW\n(with Option installed)","Max. 50.4 kW","","","Max.72 kW\n(with Option installed)","",""],["X-ray tube\nvoltage","80/100/120/135 kV","80/100/120/135 kV","","","80/100/120/135 kV","",""],["X-ray tube\ncurrent*","10 - 600 mA*\n10 - 500 mA\n(* with Option installed)","10 - 420 mA","","","10 - 600 mA*\n10 - 500 mA\n(* with Option installed)","",""],["X-ray tube heat\ncapacity","7.5 MHU","5.0 MHU","","","7.5 MHU","",""],["X-ray tube cooling\nrate","Max. 1,386 kHU/min\n(16.5 kW)\nActual 1,008 kHU/min\n(12.0 kW)","Max. 864 kHU/min","","","Max. 1,386 kHU/min\n(16.5 kW)\nActual 1,008 kHU/min\n(12.0 kW)","",""],["Focal spots sizes\n– IEC 60336: 2005,\nnominal:","Small: 0.9 mm x 0.8 mm\nLarge: 1.6 mm x 1.4 mm","Small: 0.9 mm x 0.7 mm\nLarge: 1.4 mm x 1.4 mm","","","Small: 0.9 mm x 0.8 mm\nLarge: 1.6 mm x 1.4 mm","",""],["X-ray tube\ninherent filtration","1.0 mm Al equivalent or\nmore","1.0 mm Al equivalent or\nmore","","","1.0 mm Al equivalent or\nmore","",""],["X-ray generator\n(HFG)","Model: CXXG-012A","Model: CXXG-015A","","","Model: CXXG-012A","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233342-p9-t0","doc_id":"K233342","page_num":9,"bbox":[92.82,308.64,532.62,709.14],"n_rows":2,"n_cols":3,"columns":["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],"rows":[["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],["Intended Use /\nIndications for\nUse","CINA-ASPECTS is a computer-aided\ndiagnosis (CADx) software device used\nto assist the clinician in the assessment\nand characterization of brain tissue\nabnormalities using CT image data.\nThe Software automatically reorients\nimages, segments and analyzes\nASPECTS Regions of lnterest (ROIs).\nCINA-ASPECTS extracts image data\nfor the ROI(s) to provide analysis and\ncomputer analytics based on\nmorphological characteristics. The\nimaging features are then synthesized\nby an artificial intelligence algorithm\ninto a single ASPECT (Alberta Stroke\nProgram Early CT) Score.\nCINA-ASPECTS is indicated for\nevaluation of patients presenting for\ndiagnostic imaging workup with known\nMCA or ICA occlusion, for evaluation of\nextent of disease. Extent of disease\nrefers to the number of ASPECTS\nregions affected which is reflected in\nthe total score. This device provides\ninformation that may be useful in the\ncharacterization of early ischemic","Rapid ASPECTS is a computer aided\ndiagnosis (CADx) software device used\nto assist the clinician in the assessment\nand characterization of brain tissue\nabnormalities using CT image data.\nThe Software automatically registers\nimages and segments and analyzes\nASPECTS Regions of Interest (ROIs).\nRapid ASPECTS extracts image data\nfor the ROI(s) to provide analysis and\ncomputer analytics based on\nmorphological characteristics. The\nimaging features are then synthesized\nby an artificial intelligence algorithm\ninto a single ASPECT (Alberta Stroke\nProgram Early CT) Score.\nRapid ASPECTS is indicated for\nevaluation of patients presenting for\ndiagnostic imaging workup, or\nevaluation of extent of disease. Extent\nof disease refers to the number of\nASPECTS regions affected which is\nreflected in the total score. This device\nprovides information that may be useful\nin the characterization of early ischemic\nbrain tissue injury during image"]],"caption_candidate":"(ISchemaView Inc. Rapid ASPECTS)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233342-p11-t0","doc_id":"K233342","page_num":11,"bbox":[92.82,66.84,532.62,679.38],"n_rows":12,"n_cols":3,"columns":["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],"rows":[["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],["","significant noise within the\nNCCT images that make the\nscan technically inadequate.\nHemorrhagic Transformation,\nHematoma.",""],["Environment of\nuse","Clinical/Hospital environment","Clinical/Hospital environment"],["Primary Users","Neuroradiologist/Clinician","Neuroradiologist/Clinician"],["Anatomical\nregion of\ninterest","Stroke/Head","Stroke/Head"],["Standard of\nCare\nRepresentatio\nn","ASPECTS Scoring","ASPECTS Scoring"],["Data\nacquisition\nprotocol","Non-contrast head CT scans","Non-contrast head CT scans"],["Technical\nImplementatio\nn","AI/Deep Learning","ML/AI/Random Forest"],["Segmentation\nof region of\ninterest","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image"],["Image Overlay","ASPECTS regions, highlighted by\nalgorithms.","ASPECTS regions, highlighted by\nalgorithms."],["Gating\nConditions","Users must confirm ICA or MCA\nocclusion prior to accessing CINA-\nASPECTS results","Users must confirm LVO prior to\naccessing Rapid ASPECTS results"],["Alteration of\noriginal image\ndata base","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233342-p12-t0","doc_id":"K233342","page_num":12,"bbox":[92.76,66.84,532.62,155.7],"n_rows":2,"n_cols":3,"columns":["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],"rows":[["Key Feature","Subject device: CINA-ASPECTS\nSoftware","Predicate device: ISchemaView Inc.\nRapid ASPECTS Software (K200760)"],["Alters\nStandard of\nCare Workflow","In parallel to","In parallel to"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233457-p7-t0","doc_id":"K233457","page_num":7,"bbox":[55.09,209.78,737.01,536.5],"n_rows":10,"n_cols":7,"columns":["","Elements of","","Subject Device","Primary Predicate","Additional Predicate","Comparison"],"rows":[["","Elements of","","Subject Device","Primary Predicate","Additional Predicate","Comparison"],["","Comparison","","","","",""],["Device Name","","","RUS","Visible patient Suite","Synapse 3D Base Tools v6.6",""],["510#","","","K233457","K212896","K221677",""],["Manufacturer","","","Hutom","Visible Patient, SAS","FUJIFILM Corporation",""],["Classification\nName","","","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological","Same"],["Regulation\nNumber No.","","","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","Same"],["Product Code","","","QIH","LLZ","LLZ","Same"],["Classification","","","Class II","Class II","Class II","Same"],["Indications for use","","","RUS is medical imaging software that\nis intended to provide trained medical\nprofessionals with tools to aid them in\nreading, interpreting, reporting, and\ntreatment planning for patients. RUS\naccepts DICOM compliant medical\nimages acquired from iodine contrast-\nenhanced abdomen CT.\nThis product is not intended for use\nwith or for the primary diagnostic\ninterpretation of Mammography","Visible Patient Suite is medical\nimaging software that is intended to\nprovide trained medical professionals\nwith tools to aid them in reading,\ninterpreting, reporting, and treatment\nplanning for both pediatric and adult\npatients. Visible Patient Suite accepts\nDICOM compliant medical images\nacquired from a variety of imaging\ndevices, including CT, MR.\nThis product is not intended for use\nwith or for the primary diagnostic","Synapse 3D Base Tools is medical\nimaging software that is intended to\nprovide trained medical professionals\nwith tools to aid them in reading,\ninterpreting, reporting, and treatment\nplanning. Synapse 3D Base Tools\naccepts DICOM compliant medical\nimages acquired from a variety of\nimaging devices including, CT, MR,\nCR, US, NM, PT, and XA, etc. This\nproduct is not intended for use with\nor for the primary diagnostic","Same"]],"caption_candidate":"8.1.Comparison Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233457-p9-t0","doc_id":"K233457","page_num":9,"bbox":[55.09,72.35,736.94,534.75],"n_rows":20,"n_cols":15,"columns":["","Elements of","","Subject Device","","","Primary Predicate","","","Additional Predicate","","","Comparison","",""],"rows":[["","Elements of","","Subject Device","","","Primary Predicate","","","Additional Predicate","","","Comparison","",""],["","Comparison","","","","","","","","","","","","",""],["","","","","","","all final patient management\ndecisions.","","","-Imaging tools for CT images\nincluding virtual endoscopic viewing\nand dual energy image viewing.\n-Imaging tools for MR images\nincluding delayed enhancement\nimage viewing, diffusion-weighted\nMRI image viewing.","","","","",""],["Intended user","","","","Trained professionals (including","","","Trained professionals (including","","Trained medical professionals","","","Same","",""],["","","","","physicians, surgeons and technicians)","","","physicians, surgeons and technicians)","","","","","","",""],["Where used","","","Hospital","","","Hospital","","","Hospital","","","","Same",""],["Type of input data","","","CT","","","CT, MR","","","","CT, MR, CR, US, NM, PT, and XA,","","Same","",""],["","","","","","","","","","","etc","","","",""],["Data information\nprocessing","","","","Anonymization (Some Dicom Tag)","","","Anonymization (DICOM data, patient","","","Anonymization (Patient name, ID,","","Similar","",""],["","","","","Pseudonymization (Patient name, ID)","","","information)","","","study list)","","","",""],["2D viewing","","","","YES","","","YES","","","YES","","Same","",""],["Image Storing\n(DICOM SCP)","","","YES","","","YES","","","YES","","","Same","",""],["Image\nCommunication\n(DICOM SCU)","","","YES","","","YES","","","YES","","","Same","",""],["Printing (DICOM\nSCU)","","","YES","","","YES","","","YES","","","Same","",""],["Measurements (2D\nand 3D)","","","YES","","","YES","","","YES","","","Same","",""],["Reporting","","","","YES","","","YES","","","YES","","Same","",""],["Volume Rendering\nand 3D viewing","","","YES","","","YES","","","YES","","","Same","",""],["Image fusion","","","YES","","","YES","","","YES","","","Same","",""],["Surface fusion","","","","YES","","","YES","","","YES","","Same","",""],["Image subtraction\n(3D)","","","YES","","","YES","","","YES","","","Same","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233457-p10-t0","doc_id":"K233457","page_num":10,"bbox":[55.1,72.35,736.94,267.14],"n_rows":7,"n_cols":15,"columns":["","Elements of","","Subject Device","","","Primary Predicate","","","Additional Predicate","","","Comparison","",""],"rows":[["","Elements of","","Subject Device","","","Primary Predicate","","","Additional Predicate","","","Comparison","",""],["","Comparison","","","","","","","","","","","","",""],["General image\ndata management\nand\nadministration\ntools","","","YES","","","YES","","","YES","","","Same","",""],["Segmentation","","","","YES","","","YES","","","YES","","","Same",""],["Virtual\nEndoscopic\nSimulator","","","YES","","","No","","","YES","","","Same","",""],["Product\nAvailability","","","Software product","","","Software product","","","Software product","","","Same","",""],["Hardware platform","","","","Windows PC","","","Windows PC","","","Windows PC","","","Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233512-p11-t0","doc_id":"K233512","page_num":11,"bbox":[76.6,72.86,526.34,463.54],"n_rows":8,"n_cols":3,"columns":["","• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan technically\ninadequate.\n• Presence of hemorrhage","• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan technically\ninadequate.\n• Presence of hemorrhage"],"rows":[["","• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan technically\ninadequate.\n• Presence of hemorrhage","• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan technically\ninadequate.\n• Presence of hemorrhage"],["Basic PACS\nFunctions","Software package which interfaces to a\nPACS or allows viewing within the\napplication","Same"],["Computer\nPlatform","Standard off-the-shelf Hardware: On-\nPremises","Standard off-the-shelf Hardware: Hybrid (on-\npremises/cloud)"],["Software","Traditional Coding for platform","Traditional Coding for platform"],["DICOM\nCompliance","Yes","Yes"],["Functional\nOverview","Rapid is a software package that\nprovides for the visualization and study\nof changes of tissue in digital images\ncaptured by CT and MRI. Rapid\nprovides viewing and quantification.\nThe base Platform provides common\nservices to the imaging modules","Same"],["Data/Image\nTypes","Computed Tomography (CT) via\nDICOM Format","Same"],["","Magnetic Image Resonance (MRI) via\nDICOM Format","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233543-p7-t0","doc_id":"K233543","page_num":7,"bbox":[56.92,106.77,557.24,710.78],"n_rows":20,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","YSIO X.pree VA10","YSIO X.pree",""],["","","",""],["","","VA20",""],["","","",""],["Regulation\nDescription","Stationary X-Ray System","Stationary X-Ray System","Same"],["Regulation Number","892.1680","892.1680","Same"],["Classification Product\nCode","KPR","KPR","Same"],["Indications for use","YSIO X.pree is a device\nintended to visualize\nanatomical structures by\nconverting an X-ray pattern\ninto a visible image.\nYSIO X.pree enables\nradiographic exposures of\nthe whole body and may be\nused on pediatric, adult and\nbariatric patients. It can also\nbe used for emergency\napplications.\nYSIO X.pree is not for\nmammography\nexaminations.","The intended use of the device\nYSIO X.pree is to visualize\nanatomical structures of\nhuman\nbeings by converting an X-ray\npattern into a visible image.\nThe device is a digital X-ray\nsystem to generate X-ray\nimages from the whole body\nincluding the skull, chest,\nabdomen, and extremities.\nThe acquired images support\nmedical professionals to make\ndiagnostic and/or therapeutic\ndecisions.\nYSIO X.pree is not for\nmammography examinations.","Similar"],["X-Ray","","",""],["","","",""],["Generator","Polydoros R80\n65/80 kW","Polydoros R80\n65/80 kW","Same"],["X-Ray tube","OPTITOP\n150/40/80/HC-100","OPTITOP\n150/40/80/HC-100","Same"],["X-ray techniques","Radiography","Radiography","Same"],["Collimator","Digital Multileaf\nCollimator N","Digital Multileaf\nCollimator N","Same"],["Air kerma","Kerma X","Kerma X","Same"],["CARE","Combined\nApplications to\nReduce Exposure","Combined\nApplications to\nReduce Exposure","Same"],["Touch user interface\non tube suspension","touchscreen in landscape\nformat","touchscreen in landscape\nformat","Same"],["Digital Imaging","","",""],["","","",""]],"caption_candidate":"X.pree VA10)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233543-p8-t0","doc_id":"K233543","page_num":8,"bbox":[56.9,65.4,557.26,696.1],"n_rows":26,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","YSIO X.pree VA10","YSIO X.pree",""],["","","",""],["","","VA20",""],["","","",""],["Fixed detector for\ntable and wall stand","Trixell pixium 4343RC\n“Max Static”","Trixell pixium 4343RC\n“Max Static”","Same"],["Large mobile detectors","Trixell pixium\n3543EZh „MAX wi-D“","Trixell pixium\n3543EZh „MAX wi-D“","Same"],["","N/A","Trixell pixium 3543EZ3\n“X.wi-D 35”","New for YSIO\nX.pree VA20"],["","N/A","Trixell pixium 4343EZ3\n“X.wi-D 43”","New for YSIO\nX.pree VA20"],["Small mobile detector","Trixell pixium 2430EZ\n“MAX mini”","Trixell pixium 2430EZ “MAX\nmini”","Same"],["Digital imaging\nsystem","syngo XR","syngo XR","Same"],["","Operating system Windows\n10","Operating system Windows\n10","Same"],["","Operated via touch screen","Operated via touch screen","Same"],["","Image processing with\nmyExam IQ","Image processing with\nmyExam IQ","Same"],["","AI-based Auto Cropping","AI-based Auto Cropping","Same"],["","Acquisition and Image\nprocessing parameters\nselected via clinical\nprotocols","Acquisition and Image\nprocessing parameters\nselected via clinical protocols","Same"],["Other Features and Components","","",""],["","","",""],["Patient Table","Table with fixed detector\nand table with bucky","Table with fixed detector and\ntable with bucky","Same"],["","Standard tabletop and flat\ntabletop","Standard tabletop and flat\ntabletop","Same"],["Wall stand","Wall stand with fixed\ndetector and wall stand with\nbucky","Wall stand with fixed detector\nand wall stand with bucky","Same"],["Camera","Live camera for patient\npositioning and collimation","Live camera for patient\npositioning and collimation","Similar\nNew Camera\nModel, same\nfunctionality"],["AI based Automatic\ncollimation","Auto Thorax Collimation","Auto Thorax Collimation","Different.\nChanged to new\nalgorithm, Auto\nLong-Leg/Full-\nSpine collimation\nadded"],["","N/A","Auto Long-Leg/Full-Spine\ncollimation",""],["Cropping","AI-based auto cropping","AI-based auto cropping","Same"],["Wireless Remote\nControl","Yes, same type","Yes, same type","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233543-p9-t0","doc_id":"K233543","page_num":9,"bbox":[56.92,106.77,563.6,319.82],"n_rows":7,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","","",""],["","MULTIX Impact","YSIO X.pree VA20",""],["","","",""],["","","",""],["Camera","Live camera for patient\npositioning and collimation","Live camera for patient\npositioning and collimation","Same\nThe camera, used\nfor MULTIX\nImpact, is now used\nfor YSIO X.pree\nVA20"],["AI based\nAutomatic\ncollimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Same\nThe algorithm, used\nin MULTIX Impact,\nis also used for\nYSIO X.pree VA20"]],"caption_candidate":"Impact) – AI based Automatic Collimation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233543-p9-t1","doc_id":"K233543","page_num":9,"bbox":[63.67,429.58,545.48,688.12],"n_rows":7,"n_cols":2,"columns":["Standards Development",""],"rows":[["Standards Development",""],["Organization and Reference","Title of Standard"],["Number",""],["ANSI AAMI\n60601-1, 2012 Ed. 3.1","Medical Electrical Equipment - Part 1: General\nRequirements for Safety"],["IEC 60601-1-2 2014 Ed 4.1","Medical Electrical Equipment - Part 1-2: General requirements for\nbasic safety and essential performance - Collateral Standard:\nElectromagnetic disturbances - Requirements and tests"],["IEC 60601-1-3:\nEdition 2.1, 2013","Medical electrical equipment - Part 1-3: General requirements for\nbasic safety and essential performance - Collateral Standard:\nRadiation protection in diagnostic X-ray equipment"],["IEC 60601-2-28, 2017","Medical electrical equipment - Part 2-28: Particular requirements\nfor the basic safety and essential performance of X-ray tube\nassemblies for medical diagnosis"]],"caption_candidate":"Table 9: Non-clinical performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233543-p10-t0","doc_id":"K233543","page_num":10,"bbox":[63.6,65.28,545.76,380.78],"n_rows":8,"n_cols":2,"columns":["IEC 60601-2-54\n2018, Edition 1.2","Medical electrical equipment - Part 2-54: Particular requirements\nfor the basic safety and essential performance of X-ray equipment\nfor radiography and radioscopy"],"rows":[["IEC 60601-2-54\n2018, Edition 1.2","Medical electrical equipment - Part 2-54: Particular requirements\nfor the basic safety and essential performance of X-ray equipment\nfor radiography and radioscopy"],["IEC 60601-1-6\n2020 Ed 3.2","Medical electrical equipment – Part 1-6: General requirements for\nbasic safety and essential performance – Collateral standard:\nUsability"],["IEC 62366-1 2020 Ed 1.1","Medical devices – Application of usability engineering tomedical\ndevices"],["ISO 14971: 2019","Medical devices – application of risk management tomedical\ndevices"],["IEC 62304 2015, Ed.1.1","Medical device software - Software life cycle processes"],["IEC 61910-1: 2014, Ed 1.0","Medical electrical equipment - Radiation dose documentation -\nPart 1: Radiation dose structured reports for radiography and\nradioscopy"],["NEMA PS 3.1 - 3.20 2021","Digital Imaging and Communications in Medicine(DICOM) Set"],["ISO EN ISO 10993-1\nFifth edition 2018","Biological evaluation of medical devices – Part1: Evaluation and\ntesting within a risk management process"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p4-t0","doc_id":"K233568","page_num":4,"bbox":[72.29,132.0,539.81,250.7],"n_rows":5,"n_cols":4,"columns":["","510(k) Sponsor","","Ceevra, Inc."],"rows":[["","510(k) Sponsor","","Ceevra, Inc."],["Address","Address","","149 New Montgomery St, 4th Floor\nSan Francisco CA 94105"],["Correspondence Person","","","Ken Koster\nCTO, Ceevra, Inc."],["Contact Information","","","Email: kkoster@ceevra.com\nPhone: 415-305-5326"],["","Date Prepared","","December 4, 2023"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p4-t1","doc_id":"K233568","page_num":4,"bbox":[72.29,288.6,539.81,379.3],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","Ceevra Reveal 3+"],"rows":[["","Proprietary Name","","Ceevra Reveal 3+"],["","Common Name","","Reveal 3+"],["","Classification Name","","Automated Radiological Image Processing Software"],["","Regulation Number","","21 CFR 892.2050"],["","Product Code","","QIH"],["","Regulatory Class","","II"]],"caption_candidate":"2. Updated Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p4-t2","doc_id":"K233568","page_num":4,"bbox":[72.29,415.17,539.81,521.02],"n_rows":7,"n_cols":4,"columns":["","Proprietary Name","","Ceevra Reveal 3"],"rows":[["","Proprietary Name","","Ceevra Reveal 3"],["","Common Name","","Reveal 3"],["","Premarket Notification","","K222676"],["","Classification Name","","Automated Radiological Image Processing Software"],["","Regulation Number","","21 CFR 892.2050"],["","Product Code","","QIH"],["","Regulatory Class","","II"]],"caption_candidate":"3. Originally Cleared Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p5-t0","doc_id":"K233568","page_num":5,"bbox":[71.99,395.62,540.21,675.24],"n_rows":3,"n_cols":6,"columns":["","Updated Device:","","","Originally Cleared Device:",""],"rows":[["","Updated Device:","","","Originally Cleared Device:",""],["","Ceevra Reveal 3+","","","Ceevra Reveal 3 (K222676)",""],["Ceevra Reveal 3+ is intended as a medical imaging\nsystem that allows the processing, review, analysis,\ncommunication and media interchange of multi-\ndimensional digital images acquired from CT or MR\nimaging devices and that such processing may include\nthe generation of preliminary segmentations of normal\nanatomy using software that employs machine learning\nand other computer vision algorithms. It is also intended\nas software for preoperative surgical planning, and as\nsoftware for the intraoperative display of the\naforementioned multi-dimensional digital images.\nCeevra Reveal 3+ is designed for use by health care\nprofessionals and is intended to assist the clinician who\nis responsible for making all final patient management\ndecisions.\nThe machine learning algorithms in use by Ceevra\nReveal 3+ are for use only for adult patients (22 and\nover). Three-dimensional images for patients under the\nage of 22 or of unknown age will be generated without\nthe use of any machine learning algorithms.","","","Ceevra Reveal 3 is intended as a medical imaging\nsystem that allows the processing, review, analysis,\ncommunication and media interchange of multi-\ndimensional digital images acquired from CT or MR\nimaging devices and that such processing may include\nthe generation of preliminary segmentations of normal\nanatomy using software that employs machine learning\nand other computer vision algorithms. It is also intended\nas software for preoperative surgical planning, and as\nsoftware for the intraoperative display of the\naforementioned multi-dimensional digital images.\nCeevra Reveal 3 is designed for use by health care\nprofessionals and is intended to assist the clinician who\nis responsible for making all final patient management\ndecisions.\nThe machine learning algorithms in use by Ceevra\nReveal 3 are for use only for adult patients (22 and over).\nThree-dimensional images for patients under the age of\n22 or of unknown age will be generated without the use\nof any machine learning algorithms.","",""]],"caption_candidate":"Table 6.1: Comparison of Intended Use Statements","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p6-t0","doc_id":"K233568","page_num":6,"bbox":[72.18,92.05,540.04,429.36],"n_rows":15,"n_cols":9,"columns":["","Feature/","","","Updated Device:","","","Originally Cleared Device:",""],"rows":[["","Feature/","","","Updated Device:","","","Originally Cleared Device:",""],["","Function","","","Ceevra Reveal 3+","","","Ceevra Reveal 3 (K222676)",""],["Supported image Modalities","","","CT and MR","","","CT and MR","",""],["Intended users","","","Healthcare Professionals","","","Healthcare Professionals","",""],["Intended environment","","","Healthcare facilities such as\nhospitals and clinics","","","Healthcare facilities such as\nhospitals and clinics","",""],["Device Class","","","Class II","","","Class II","",""],["Image analysis features","","","Interactive manipulation and\n3D visualization","","","Interactive manipulation and\n3D visualization","",""],["Preoperative use","","","Yes","","","Yes","",""],["Intraoperative use","","","Yes","","","Yes","",""],["3D images used intraoperatively for\nreal-time guidance, navigation or\notherwise integrated with surgical\ninstruments","","","No","","","No","",""],["Segmentation work performed by","","","Internal Operators","","","Internal Operators","",""],["Built-in features for end-user to\ncompare CT/MR to device output","","","No","","","No","",""],["Quantitative measurements\ncalculated by device","","","Volume of structure,\ndiameter of structure,\ndistance between two points","","","None","",""],["Software generates semi-automated\nsegmentations of abnormal anatomy","","","No","","","No","",""],["Software generates semi-automated\nsegmentations of certain normal\nanatomy","","","Yes","","","Yes","",""]],"caption_candidate":"Table 6.2: Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233568-p6-t1","doc_id":"K233568","page_num":6,"bbox":[72.18,659.34,540.04,701.1],"n_rows":3,"n_cols":2,"columns":["","The data used in the device validation ensured"],"rows":[["","The data used in the device validation ensured"],["diversity in patient population and scanner manufacturers. Subgroup analysis was performed for patient",""],["age, patient sex, and scanner manufacturers.",""]],"caption_candidate":"at the level of the scanning institution, namely, studies sourced from a specific institution were used for","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233582-p11-t0","doc_id":"K233582","page_num":11,"bbox":[78.13,96.38,719.87,536.39],"n_rows":4,"n_cols":3,"columns":["Parameter","Rapid (K213165) – Primary Predicate","Rapid – Subject Device"],"rows":[["Parameter","Rapid (K213165) – Primary Predicate","Rapid – Subject Device"],["Product Code","LLZ, QIH","LLZ, QIH"],["Regulation","21 CFR §892.2050","21 CFR §892.2050"],["Intended Use/\nIndications for\nUse","Rapid is an image processing software package to be used\nby trained professionals, including but not limited to\nphysicians and medical technicians. The software runs on\na standard off-the-shelf computer or a virtual platform,\nsuch as VMware, and can be used to perform image\nviewing, processing and analysis of images. Data and\nimages are acquired through DICOM compliant imaging\ndevices.\nRapid provides both viewing and analysis capabilities for\nfunctional and dynamic imaging datasets acquired with CT\nPerfusion (CTP), CT Angiography (CTA), and MRI\nincluding a Diffusion Weighted MRI (DWI) Module and a\nDynamic Analysis Module (dynamic contrast-enhanced\nimaging data for MRI and CT).\nThe CT analysis includes NCCT maps showing areas of\nhypodense and hyperdense tissue.\nThe DWI Module is used to visualize local water diffusion\nproperties from the analysis of diffusion - weighted MRI\ndata.\nThe Dynamic Analysis Module is used for visualization\nand analysis of dynamic imaging data, showing properties\nof changes in contrast over time. This functionality\nincludes calculation of parameters related to tissue flow\n(perfusion) and tissue blood volume.\nRapid CT-Perfusion and Rapid MR-Perfusion can be used by\nphysicians to aid in the selection of acute stroke patients (with\nknown occlusion of the intracranial internal carotid artery or\nproximal middle cerebral artery)","Rapid is an image processing software package to be used\nby trained professionals, including but not limited to\nphysicians (medical analysis and decision making) and\nmedical technicians (administrative case processing). The\nsoftware runs on a standard off-the-shelf computer or a\nvirtual platform, such as VMware, and can be used to\nperform image viewing, processing, and analysis of\nimages. Data and images are acquired through DICOM\ncompliant imaging devices. Rapid is indicated for Adults\nonly.\nRapid provides both viewing and analysis capabilities for\nfunctional and dynamic imaging datasets acquired with\nCT, CT Perfusion (CTP), CT Angiography (CTA), C-arm\nCT Perfusion and MRI including a Diffusion Weighted\nMRI (DWI) Module and a Dynamic Analysis Module\n(dynamic contrast-enhanced imaging data for MRI,\nCT, and C-arm CT).\nRapid C-arm CT Perfusion can be used to qualitatively\nassess cerebral hemodynamics in the angiography suite.\nThe CT analysis includes NCCT maps showing areas of\nhypodense and hyperdense tissue.\nThe DWI Module is used to visualize local water\ndiffusion properties from the analysis of diffusion -\nweighted MRI data.\nThe Dynamic Analysis Module is used for visualization\nand analysis of dynamic imaging data, showing properties\nof changes in contrast over time. This functionality\nincludes calculation of parameters related to tissue flow"]],"caption_candidate":"Table 1: Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233582-p12-t0","doc_id":"K233582","page_num":12,"bbox":[78.17,76.58,719.83,532.31],"n_rows":6,"n_cols":3,"columns":["","Instructions for the use of contrast agents for this indication\ncan be found in Appendix A of the User’s Manual.\nAdditional information for safe and effective drug use is\navailable in the product-specific iodinated CT and\ngadolinium-based MR contrast drug labeling.\nIn addition to the Rapid imaging criteria, patients must meet\nthe clinical requirements for thrombectomy, as assessed by\nthe physician, and have none of the following\ncontraindications or exclusions:\n• Bolus Quality: absent or inadequate bolus.\n• Patient Motion: excessive motion leading to artifacts that\nmake the scan technically inadequate.\n• Presence of hemorrhage.","(perfusion) and tissue blood volume.\nRapid CT Perfusion and Rapid MR Perfusion can be used\nby physicians to aid in the selection of acute stroke\npatients (with known occlusion of the intracranial internal\ncarotid artery or proximal middle cerebral artery).\nInstructions for the use of contrast agents for this\nindication can be found in Appendix A of the User’s\nManual. Additional information for safe and effective\ndrug use is available in the product-specific iodinated CT\nand gadolinium-based MR contrast drug labeling.\nIn addition to the Rapid imaging criteria, patients must\nmeet the clinical requirements for thrombectomy, as\nassessed by the physician, and have none of the following\ncontraindications or exclusions:\n• Bolus Quality: absent or inadequate bolus.\n• Patient Motion: excessive motion leading to artifacts\nthat make the scan technically inadequate.\n• Presence of hemorrhage.\n• C-Arm CTP is not used in the Rapid Thrombectomy\nindication for patient selection criteria, other\nmodalities should be consulted.\nCaution\nCBV and CBT are not absolute and CBT, CBV, MTT and\nTmax are supported for qualitative interpretation of the\nperfusion maps only."],"rows":[["","Instructions for the use of contrast agents for this indication\ncan be found in Appendix A of the User’s Manual.\nAdditional information for safe and effective drug use is\navailable in the product-specific iodinated CT and\ngadolinium-based MR contrast drug labeling.\nIn addition to the Rapid imaging criteria, patients must meet\nthe clinical requirements for thrombectomy, as assessed by\nthe physician, and have none of the following\ncontraindications or exclusions:\n• Bolus Quality: absent or inadequate bolus.\n• Patient Motion: excessive motion leading to artifacts that\nmake the scan technically inadequate.\n• Presence of hemorrhage.","(perfusion) and tissue blood volume.\nRapid CT Perfusion and Rapid MR Perfusion can be used\nby physicians to aid in the selection of acute stroke\npatients (with known occlusion of the intracranial internal\ncarotid artery or proximal middle cerebral artery).\nInstructions for the use of contrast agents for this\nindication can be found in Appendix A of the User’s\nManual. Additional information for safe and effective\ndrug use is available in the product-specific iodinated CT\nand gadolinium-based MR contrast drug labeling.\nIn addition to the Rapid imaging criteria, patients must\nmeet the clinical requirements for thrombectomy, as\nassessed by the physician, and have none of the following\ncontraindications or exclusions:\n• Bolus Quality: absent or inadequate bolus.\n• Patient Motion: excessive motion leading to artifacts\nthat make the scan technically inadequate.\n• Presence of hemorrhage.\n• C-Arm CTP is not used in the Rapid Thrombectomy\nindication for patient selection criteria, other\nmodalities should be consulted.\nCaution\nCBV and CBT are not absolute and CBT, CBV, MTT and\nTmax are supported for qualitative interpretation of the\nperfusion maps only."],["","",""],["Basic PACS\nFunctions","Software package which interfaces to a PACS or allows\nviewing within the application","Same"],["Computer\nPlatform","Standard off-the-shelf Hardware: On-Premises","Standard off-the-shelf Hardware: On-Premises or Cloud\nHybrid"],["Software","Mixed Traditional and AI/ML","Same"],["DICOM\nCompliance","Yes","Same"]],"caption_candidate":"Section 11: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233582-p13-t0","doc_id":"K233582","page_num":13,"bbox":[78.11,76.58,719.89,525.95],"n_rows":25,"n_cols":3,"columns":["Functional\nOverview","Rapid is a software package that provides for the\nvisualization and study of changes of tissue in digital\nimages captured by CT and MRI. Rapid provides viewing\nand quantification.","Rapid is a software package that provides for the\nvisualization and study of changes of tissue in digital\nimages captured by CT and MRI. Rapid provides\nviewing and quantification. C-Arm CT is for\nqualitative assessment only."],"rows":[["Functional\nOverview","Rapid is a software package that provides for the\nvisualization and study of changes of tissue in digital\nimages captured by CT and MRI. Rapid provides viewing\nand quantification.","Rapid is a software package that provides for the\nvisualization and study of changes of tissue in digital\nimages captured by CT and MRI. Rapid provides\nviewing and quantification. C-Arm CT is for\nqualitative assessment only."],["Data/Image\nTypes","Computed Tomography (CT) via DICOM Format","Supported"],["","C-Arm CT via DICOM Format (not supported in\npredicate)","Qualitative Imaging"],["","Magnetic Image Resonance (MRI) via DICOM Format","Supported"],["","",""],["MRI","Diffusion Weighted Image (DWI)","Supported"],["","Dynamic Analysis tissue flow (perfusion) and tissue blood\nvolume","Supported"],["CT","CT Perfusion (CTP)","Supported"],["","CTA-large vessel density analysis","Supported"],["C-arm CT","C-arm CT Perfusion (C-arm CTP) – Not Supported","Supported via qualitative analysis"],["","",""],["Diffusion MRI","Isotropic DWI (isoDWI)","Supported"],["","ADC","Supported"],["","Trace of diffusion tensor (Trace)","Supported"],["","Fractional Anisotropy (FA) and color FA","Supported"],["Perfusion MRI\nand Perfusion\nCT","Cerebral blood flow (CBF)","Supported"],["","Cerebral blood volume (CBV)","Supported"],["","Mean transit time (MTT)","Supported"],["","Tissue residue function time to peak (Tmax)","Supported"],["Perfusion C-\narm CT","CBF – Not Supported","Supported via qualitative analysis"],["","CBV – Not Supported","Supported via qualitative analysis"],["","MTT – Not Supported","Supported via qualitative analysis"],["","Tmax – Not Supported","Supported via qualitative analysis"],["","",""],["MRI and CT","Arterial input function (AIF)Venous output function\n(VOF)","Supported"]],"caption_candidate":"Section 11: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233582-p14-t0","doc_id":"K233582","page_num":14,"bbox":[78.05,76.1,719.95,238.55],"n_rows":10,"n_cols":3,"columns":["","Time-course","Supported"],"rows":[["","Time-course","Supported"],["","Mask","Supported"],["","Region of interest (ROI) and Volumetry","Supported"],["","Volumetric comparison between 2 ROIs","Supported"],["","Motion correction","Supported"],["","Export perfusion and diffusion files to PACS and DICOM\nfile systems","Supported"],["","Acquire, transmit, process, and store medical images","Supported"],["Thrombectomy","Selection of Patients meeting criteria for thrombectomy","Supported"],["NCCT","Hyperdensity (Included)","Supported"],["","Hypodensity (Included)","Supported"]],"caption_candidate":"Section 11: 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233590-p6-t0","doc_id":"K233590","page_num":6,"bbox":[72.5,508.5,223.5,585.5],"n_rows":7,"n_cols":2,"columns":["AgeGroup,n(%)","Images/Subjects*\nN=634"],"rows":[["AgeGroup,n(%)","Images/Subjects*\nN=634"],["5-11","89"],["12-18","131"],["19-30","94"],["31-45","123"],["46-60","89"],["60+","108"]],"caption_candidate":"toothanatomy.TheDistributionofAgeRangeinthedatasetisasfollows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p5-t0","doc_id":"K233650","page_num":5,"bbox":[72.26,293.82,523.06,474.06],"n_rows":9,"n_cols":6,"columns":["","Product Name","","","Trade Name",""],"rows":[["","Product Name","","","Trade Name",""],["SOMATOM go.Up","","","SOMATOM go.Up","",""],["SOMATOM go.Now","","","SOMATOM go.Now","",""],["SOMATOM go.All","","","SOMATOM go.All","",""],["SOMATOM go.Top","","","SOMATOM go.Top","",""],["SOMATOM go.Sim","","","SOMATOM go.Sim","",""],["SOMATOM go.Open Pro","","","SOMATOM go.Open Pro","",""],["SOMATOM X.cite","","","SOMATOM X.cite","",""],["SOMATOM X.ceed","","","SOMATOM X.ceed","",""]],"caption_candidate":"Table 1: Subject Device Names","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p10-t0","doc_id":"K233650","page_num":10,"bbox":[72.27,398.04,523.05,599.04],"n_rows":6,"n_cols":6,"columns":["","Term","","","Definition",""],"rows":[["","Term","","","Definition",""],["N/A","","","The feature is not supported for the subject device","",""],["New","","","The feature is newly supported for Siemens CT Scanners and newly introduced\nwithin the subject device submission","",""],["Unmodified","","","The feature remains unchanged from that within the predicate device. The\nrelevant modification was already present within the predicate device.","",""],["Modified","","","This feature is modified from the predicate / reference devices","",""],["Enabled","","","This feature is currently supported by other cleared Siemens CT systems or\ncleared Siemens stand-alone software applications. This feature will be\nsupported for the subject device with software version SOMARIS/10 syngo CT\nVB10 and is substantially equivalent compared to the cleared version of the\nprimary/reference predicate device.","",""]],"caption_candidate":"Table 2: Overview of term definition.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p12-t0","doc_id":"K233650","page_num":12,"bbox":[72.26,420.9,523.03,753.42],"n_rows":13,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM S\ngo.Now go","OMATOM",""],["","","go.Now","","","go.Up","","","",".Up",""],["scanner","Whole body Computed Tomography\n(CT) Scanner System","","","","","","Whole body Computed Tomography\n(CT) Scanner System","","",""],["System\nConfiguration","Single Source","","","","","","Single Source","","",""],["Environment of Use","Professional Healthcare Facility","","","","","","Professional Healthcare Facility","","",""],["Generator\nMax. power (kW)","32","","","","","","32","","",""],["Detector\ntechnology","Stellar\nbased on UFC (Ultra Fast Ceramic)","","","","","","Stellar\nbased on UFC (Ultra Fast Ceramic)","","",""],["Detector\nvolume coverage\n(mm)","11.2","","","22.4","","","11.2 22","",".4",""],["Detector","16","","","32","","","16 32","","",""]],"caption_candidate":"go.Up with software version syngo CT VB10 and the primary predicate devices with software version syngo CT VA40.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p13-t0","doc_id":"K233650","page_num":13,"bbox":[72.26,95.46,523.06,764.1],"n_rows":22,"n_cols":13,"columns":["Hardware property","","","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","","","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","","","(K211373)","",""],["","","","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.Now","SOMATOM",""],["","","","","go.Now","","","go.Up","","","","go.Up",""],["physical rows","","","","","","","","","","","",""],["Detector\nSlice width (mm)","","","0.7","","","","","","0.7","","",""],["Detector\nDAS channel no.","","","768","","","","","","768","","",""],["Detector\nImage slices","","","32","","","64","","","32","","64",""],["Tube\ntechnology","","","Chronon","","","","","","Chronon","","",""],["Tube\nkV steps","","","80, 110, 130","","","","","","80, 110, 130","","",""],["Tube\nMax. current (mA)","","","400","","","","","","400","","",""],["Tube\nfocus","","","• 0.8 x 0.4 / 8°\n• 0.8 x 0.7 / 8°","","","","","","• 0.8 x 0.4 / 8°\n• 0.8 x 0.7 / 8°","","",""],["Tube\nHeat storage\ncapacity (MHU)","","","3.5","","","","","","3.5","","",""],["Tube\nCooling rate (kHU/\nmin)","","","915","","","","","","915","","",""],["Gantry\nBore size","","","70","","","","","","70","","",""],["Gantry\nScan FoV (cm)","","","50","","","","","","50","","",""],["Gantry\nExtended FoV (cm)","","","70","","","","","","70","","",""],["","Gantry","","0.5, 0.8, 1.0, 1.5","","","","","","0.8, 1.0, 1.5","","",""],["","Rot. time (sec)","","","","","","","","","","",""],["Gantry\nTilt (degree)","","","N/A","","","+/- 30°\n-30° to +28° with\noptional 307 kg","","","N/A","","+/- 30°\n-30° to +28° with\noptional 307 kg",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p14-t0","doc_id":"K233650","page_num":14,"bbox":[72.27,95.46,523.05,755.49],"n_rows":14,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.Now","SOMATOM",""],["","","go.Now","","","go.Up","","","","go.Up",""],["","","","","patient table","","","","","patient table",""],["Patient table\nType","Vector (1250\nmm),\nVario 1 (1600\nmm),\nVario RT (1600\nmm)\nwith table\nextension","","","Vario 1 (1600\nmm),\nVario 2 (2000\nmm),\nVario RT (1600\nmm)\nwith table\nextension","","","Vector (1250\nmm),\nVario 1 (1600\nmm),\nVario RT (1600\nmm)\nwith table\nextension","","Vario 1 (1600\nmm),\nVario 2 (2000\nmm),\nVario RT (1600\nmm)\nwith table\nextension",""],["Patient table\nMax. weight\ncapacity (kg)","Vector: 160\nVario 1: 227\nVario RT: 227","","","Vario 1: 227\nVario 2: 307\nVario RT: 227","","","Vector: 160\nVario 1: 227\nVario RT: 227","","Vario 1: 227\nVario 2: 307\nVario RT: 227",""],["Max. scan length\ntopogram","1680 mm with\ntable extension","","","1680 mm with\ntable extension\n2080 mm with\ntable extension","","","1680 mm with\ntable extension","","1680 mm with\ntable extension\n2080 mm with\ntable extension",""],["Max. scan length\nImage acquisition","Max. 1600 mm\nwith patient\ntable extension","","","Max. 1600 mm\nwith patient\ntable extension\nMax. 2000 mm\nwith patient\ntable extension","","","Max. 1600 mm\nwith patient\ntable extension","","Max. 1600 mm\nwith patient\ntable extension\nMax. 2000 mm\nwith patient\ntable extension",""],["Spectral filtration","Tin Filter","","","","","","Tin Filter","","",""],["High Power 80","yes","","","yes","","","yes","","yes",""],["FAST 3D Camera","option for\npatient\npositioning with\n3D Camera:\n• gantry\nmounted,\nmodified\ndesign","","","option for\npatient\npositioning with\n3D Camera:\n• ceiling\nmounted,\nmodified\ndesign\n• gantry\nmounted,\nmodified\ndesign","","","n.a.","","option for\npatient\npositioning with\n3D Camera:\n• ceiling\nmounted",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p16-t0","doc_id":"K233650","page_num":16,"bbox":[72.27,95.46,523.05,229.41],"n_rows":7,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.Now","SOMATOM",""],["","","go.Now","","","go.Up","","","","go.Up",""],["","• Scan countdown\n• Radiation on","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p16-t1","doc_id":"K233650","page_num":16,"bbox":[72.27,280.53,523.05,758.46],"n_rows":17,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.All","SOMATOM",""],["","","go.All","","","go.Top","","","","go.Top",""],["scanner","Whole body Computed Tomography\n(CT) Scanner System","","","","","","Whole body Computed Tomography\n(CT) Scanner System","","",""],["System\nConfiguration","Single Source","","","","","","Single Source","","",""],["Environment of Use","Professional Healthcare Facility","","","","","","Professional Healthcare Facility","","",""],["Generator\nMax. power (kW)","75","","","","","","75","","",""],["Detector\ntechnology","Stellar\nbased on UFC (Ultra Fast Ceramic)","","","","","","Stellar\nbased on UFC (Ultra Fast Ceramic)","","",""],["Detector\nvolume coverage\n(mm)","22.4","","","38.4","","","22.4","","38.4",""],["Detector\nphysical rows","32","","","64","","","32","","64",""],["Detector\nSlice width (mm)","0.7","","","0.6","","","0.7","","0.6",""],["Detector\nDAS channel no.","768","","","840","","","768","","840",""],["Detector\nImage slices","64","","","128","","","64","","128",""],["Tube","Athlon","","","","","","Athlon","","",""]],"caption_candidate":"go.Top with software version syngo CT VB10 and the primary predicate devices with software version syngo CT VA40.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p17-t0","doc_id":"K233650","page_num":17,"bbox":[72.25,95.46,523.06,743.7],"n_rows":19,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.All","SOMATOM",""],["","","go.All","","","go.Top","","","","go.Top",""],["technology","","","","","","","","","",""],["Tube\nkV steps","70 to 140 (in 10 kV steps)","","","","","","70 to 140 (in 10 kV steps)","","",""],["Tube\nMax. current (mA)","825","","","","","","825","","",""],["Tube\nfocus","• 1.1 x 1.2 / 8°\n• 0.8 x 0.8 / 8°","","","","","","• 1.1 x 1.2 / 8°\n• 0.8 x 0.8 / 8°","","",""],["Tube\nHeat storage\ncapacity (MHU)","7","","","","","","7","","",""],["Tube\nCooling rate (kHU/\nmin)","Up to 1700","","","","","","Up to 1700","","",""],["Gantry\nBore size","70","","","","","","70","","",""],["Gantry\nScan FoV (cm)","50","","","","","","50","","",""],["Gantry\nExtended FoV (cm)","70","","","","","","70","","",""],["Gantry\nRot. time (sec)","0.33, 0.5, 1.0","","","","","","0.33, 0.5, 1.0","","",""],["Gantry\nTilt (degree)","+/- 30°\n-30° to +28° with optional 307 kg\npatient table","","","","","","+/- 30°\n-30° to +28° with optional 307 kg\npatient table","","",""],["Patient table\nType","Vario 1 (1600 mm)\nVario 2 (2000 mm)\nVario RT (1600 mm)\nwith table extension","","","","","","Vario 1 (1600 mm)\nVario 2 (2000 mm)\nVario RT (1600 mm)\nwith table extension","","",""],["Patient table\nMax. weight\ncapacity (kg)","Vario 1: 227\nVario 2: 307\nVario RT: 227","","","","","","Vario 1: 227\nVario 2: 307\nVario RT: 227","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p20-t0","doc_id":"K233650","page_num":20,"bbox":[72.25,123.45,523.06,746.82],"n_rows":21,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.Sim","SOMATOM",""],["","","go.Sim","","","go.Open Pro","","","","go.Open Pro",""],["scanner","Whole body Computed Tomography\n(CT) Scanner System","","","","","","Whole body Computed Tomography\n(CT) Scanner System","","",""],["System\nConfiguration","Single Source","","","","","","Single Source","","",""],["Environment of Use","Professional Healthcare Facility","","","","","","Professional Healthcare Facility","","",""],["Generator\nMax. power (kW)","75","","","","","","75","","",""],["Detector\ntechnology","Stellar\nbased on UFC (Ultra Fast Ceramic)","","","","","","Stellar\nbased on UFC (Ultra Fast Ceramic)","","",""],["Detector\nvolume coverage\n(mm)","19.2","","","38.4","","","19.2","","38.4",""],["Detector\nphysical rows","32","","","64","","","32","","64",""],["Detector\nSlice width (mm)","0.6","","","0.6","","","0.6","","0.6",""],["Detector\nDAS channel no.","920","","","920","","","920","","920",""],["Detector\nImage slices","64","","","128","","","64","","128",""],["Tube\ntechnology","Athlon","","","","","","Athlon","","",""],["Tube\nkV steps","70 to 140 (in 10 kV steps)","","","","","","70 to 140 (in 10 kV steps)","","",""],["Tube\nMax. current (mA)","825","","","","","","825","","",""],["Tube\nfocus","• 1.1 x 1.2 / 7°\n• 0.8 x 0.8 / 7°","","","","","","• 1.1 x 1.2 / 7°\n• 0.8 x 0.8 / 7°","","",""],["Tube","7","","","","","","7","","",""]],"caption_candidate":"go.Open Pro with software version syngo CT VB10 and the primary predicate devices with software version syngo CT VA40.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p21-t0","doc_id":"K233650","page_num":21,"bbox":[72.25,95.46,523.06,748.14],"n_rows":19,"n_cols":11,"columns":["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware property","Subject device\nSOMATOM go. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM go. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\ngo.Sim","SOMATOM",""],["","","go.Sim","","","go.Open Pro","","","","go.Open Pro",""],["Heat storage\ncapacity (MHU)","","","","","","","","","",""],["Tube\nCooling rate (kHU/\nmin)","Up to 1700","","","","","","Up to 1700","","",""],["Gantry\nBore size","85","","","","","","85","","",""],["Gantry\nScan FoV (cm)","60","","","","","","60","","",""],["Gantry\nExtended FoV (cm)","85","","","","","","85","","",""],["Gantry\nRot. time (sec)","0.35, 0.5, 1.0","","","","","","0.35, 0.5, 1.0","","",""],["Gantry\nTilt (degree)","+/- 30\n-30° to +25° with optional 307 kg\npatient table","","","","","","+/- 30\n-30° to +25° with optional 307 kg\npatient table","","",""],["Patient table\nType","Vario 2 (2000 mm)\nVario RT (1600 mm)\nwith table extension","","","","","","Vario 2 (2000 mm)\nVario RT (1600 mm)\nwith table extension","","",""],["Patient table\nMax. weight\ncapacity (kg)","Vario 2: 307\nVario RT: 227","","","","","","Vario 2: 307\nVario RT: 227","","",""],["Max. scan length\ntopogram","1680 mm with table extension\n2080 mm with table extension","","","","","","1680 mm with table extension\n2080 mm with table extension","","",""],["Max. scan length\nImage acquisition","Max. 1600 mm with patient table\nextension\nMax. 2000 mm with patient table\nextension","","","","","","Max. 1600 mm with patient table\nextension\nMax. 2000 mm with patient table\nextension","","",""],["Spectral filtration","Tin Filter","","","Combined Tin\nFilter/Split filter","","","Tin Filter","","Combined Tin\nFilter/Split filter",""],["High Power 70/\nHigh Power 80","825 (@70 kV)\n825 (@ 80 kV)","","","","","","825 (@70 kV)\n825 (@ 80 kV)","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p23-t0","doc_id":"K233650","page_num":23,"bbox":[72.25,123.45,523.06,753.72],"n_rows":20,"n_cols":11,"columns":["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM X. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\nX.cite","SOMATOM",""],["","","X.cite","","","X.ceed","","","","X.ceed",""],["scanner","Whole body Computed Tomography\n(CT) Scanner System","","","","","","Whole body Computed Tomography\n(CT) Scanner System","","",""],["System\nConfiguration","Single Source","","","","","","Single Source","","",""],["Environment of\nUse","Professional Healthcare Facility","","","","","","Professional Healthcare Facility","","",""],["Generator\nMax. power (kW)","90 kW or 105 kW","","","105 kW or 120\nkW","","","90 kW or 105 kW","","105 kW or 120\nkW",""],["Detector\ntechnology","StellarInfinity","","","","","","StellarInfinity","","",""],["Detector\nvolume coverage","38.4 mm","","","","","","38.4 mm","","",""],["Detector\nphysical rows","64rows","","","","","","64","","",""],["Detector\nSlice width","0.6 mm","","","","","","0.6 mm","","",""],["Detector\nDAS channel no.","840","","","920","","","840","","920",""],["Detector\nImage slices","128","","","","","","128","","",""],["Tube\ntechnology","Vectron","","","","","","Vectron","","",""],["Tube\nkV steps","70–140 kV in 10 kV steps","","","","","","70–140 kV in 10 kV steps","","",""],["Tube\nMax. current","1100 mA (for 90\nkW)\n1200 mA (for 105\nkW)","","","1200 mA (for 90\nkW)\n1300 mA (for 105\nkW)","","","1100 mA (for 90\nkW)\n1200 mA (for 105\nkW)","","1200 mA (for 90\nkW)\n1300 mA (for 105\nkW)",""],["Tube\nfocus","• 0.6 x 0.7 / 8°\n• 0.8 x 1.1 / 8°","","","• 0.4 x 0.5 / 8°\n• 0.6 x 0.7 / 8°","","","• 0.6 x 0.7 / 8°\n• 0.8 x 1.1 / 8°","","• 0.4 x 0.5 / 8°\n• 0.6 x 0.7 / 8°",""]],"caption_candidate":"with software version syngo CT VB10 and the primary predicate devices with software version syngo CT VA40 (K211373).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p24-t0","doc_id":"K233650","page_num":24,"bbox":[72.26,95.46,523.06,768.9],"n_rows":16,"n_cols":11,"columns":["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM X. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\nX.cite","SOMATOM",""],["","","X.cite","","","X.ceed","","","","X.ceed",""],["","","","","• 0.8 x 1.1 / 8°","","","","","• 0.8 x 1.1 / 8°",""],["Tube\nHeat storage\ncapacity","higher than 30 MHU","","","","","","higher than 30 MHU","","",""],["Tube\nCooling rate\n(MHU/ min)","2.7 MHU / min","","","2.7 MHU / min","","","2.7 MHU / min","","2.7 MHU / min",""],["Gantry\nBore size","82","","","","","","82","","",""],["Gantry\nScan FoV (cm)","50","","","","","","50","","",""],["Gantry\nExtended FoV\n(cm)","81.5","","","","","","81.5","","",""],["Gantry\nRot. time (sec)","0.3, 0.5, 1.0","","","0,25, 0.3, 0.5, 1.0","","","0.3, 0.5, 1.0","","0,25, 0.3, 0.5, 1.0",""],["Gantry\nTilt (degree)","+/- 25\n+/-30 (only with Vitus)","","","","","","+/- 25\n+/-30 (only with Vitus)","","",""],["Patient table\nType","Vario RT (1600\nmm)\nVitus (2000 mm)\nVario 2 (2000\nmm)","","","Vario RT (1600\nmm)\nVitus (2000 mm)\nVario 2.D (2000\nmm)","","","Vario RT (1600\nmm)\nVitus (2000 mm)\nVario 2 (2000\nmm)","","Vario RT (1600\nmm)\nVitus (2000 mm)\nVario 2.D (2000\nmm)",""],["Patient table\nInstallation\noption","Regular\ninstallation\n(Vario RT, Vario 2\nand Vitus):\n474 mm\nInstallation\noption with\nextended\ndistance (Vitus):\n674 mm (474\nmm + 200 mm)","","","Regular\ninstallation\n(Vario RT, Vario 2\nand Vitus):\n474 mm\nInstallation\noption with\nextended\ndistance (Vitus):\n674 mm (474\nmm + 200 mm)","","","Regular\ninstallation\n(Vario RT, Vario 2\nand Vitus):\n474 mm","","Regular\ninstallation\n(Vario RT, Vario 2\nand Vitus):\n474 mm",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p26-t0","doc_id":"K233650","page_num":26,"bbox":[72.26,95.46,523.05,438.36],"n_rows":12,"n_cols":11,"columns":["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],"rows":[["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT VB10","","","","","","","Primary predicate device","",""],["","","","","","","","","SOMATOM X. Platform","",""],["","","","","","","","","with SOMARIS/10 syngo CT VA40","",""],["","","","","","","","","(K211373)","",""],["","","SOMATOM","","","SOMATOM","","","SOMATOM\nX.cite","SOMATOM",""],["","","X.cite","","","X.ceed","","","","X.ceed",""],["","up to 1200 mA\n(@80 kV)","","","up to 1300 mA\n(@80 kV)","","","up to 1200 mA\n(@80 kV)","","up to 1300 mA\n(@80 kV)",""],["x-ray foot switch","Option to trigger hands-free scanning","","","","","","Option to trigger hands-free scanning","","",""],["Table foot switch","Option for table patient movement","","","","","","Option for table patient movement","","",""],["i-joystick","Option for patient table movements,\nincluding an electrical connection for\nthe tablet dock which allows charging\nthe tablet when mounted.","","","","","","Option for patient table movements,\nincluding an electrical connection for\nthe tablet dock which allows charging\nthe tablet when mounted.","","",""],["Tablet dock","Option for mounting of the tablet on\nthe patient table.","","","","","","Option for mounting of the tablet on\nthe patient table.","","",""],["CARE 2D camera","Patient observation camera*\nintegrated on gantry front\n*in syngo CT VB10 the patient\nobservation camera is renamed as\nCARE 2D camera","","","","","","Patient observation camera\nintegrated on gantry front","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p28-t0","doc_id":"K233650","page_num":28,"bbox":[72.31,95.46,523.03,769.62],"n_rows":14,"n_cols":9,"columns":["Software property","","","","Subject device","","","Primary predicate device",""],"rows":[["Software property","","","","Subject device","","","Primary predicate device",""],["","","","SOMATOM go.Now\nSOMATOM go.Up\nSOMATOM go.All\nSOMATOM go.Top\nSOMATOM go.Sim\nSOMATOM go.Open Pro\nSOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10 syngo CT VB10","SOMATOM go.Now","","","SOMATOM go.Now",""],["","","","","SOMATOM go.Up","","","SOMATOM go.Up",""],["","","","","SOMATOM go.All","","","SOMATOM go.All",""],["","","","","SOMATOM go.Top","","","SOMATOM go.Top",""],["","","","","SOMATOM go.Sim","","","SOMATOM go.Sim",""],["","","","","SOMATOM go.Open Pro","","","SOMATOM go.Open Pro",""],["","","","","SOMATOM X.cite","","","SOMATOM X.cite",""],["","","","","SOMATOM X.ceed","","","SOMATOM X.ceed",""],["","","","","with SOMARIS/10 syngo CT VB10","","","with SOMARIS/10 syngo CT VA40",""],["","","","","","","","(K211373)",""],["","","","• Protocol supporting contrast\nbolus-triggered data acquisition\n• Contrast media protocols\n(including coronary CTA)\n• Pediatric Protocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy acquisition\n(TwinBeam DE and TwinSpiral\nDE)\n• Dynamic imaging (Flex 4D Spiral)\n• Protocols supporting CT\nIntervention (scan modes: i-\nsequence, i-spiral, i-Fluoro)\n• Protocols supporting Cardiac\nScanning\n• Protocols for DirectBreathhold","","","• Protocol supporting contrast\nbolus-triggered data acquisition\n• Contrast media protocols\n(including coronary CTA)\n• Pediatric Protocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy acquisition\n(TwinBeam DE and TwinSpiral\nDE)\n• Dynamic imaging (Flex 4D Spiral)\n• Protocols supporting CT\nIntervention (scan modes: i-\nsequence, i-spiral, i-Fluoro)\n• Protocols supporting Cardiac\nScanning","",""],["Advanced\nReconstruction","","","Recon&GO:\n- Spectral Recon (Dual Energy\nReconstruction from photon-\ncounting data) / including Virtual\nUnenhanced, Monoenergetic plus\n- Inline Results DE SPP (Spectral\nPost-Processing with photon-\ncounting image data)\n- Inline Anatomical ranges\n(Parallel/Radial) incl. Virtual\nUnenhanced, Monoenergetic plus\n- Inline Spine and Rib Ranges\n- Inline table and bone removal","","","Recon&GO:\n- Spectral Recon (Dual Energy\nReconstruction from photon-\ncounting data) / including Virtual\nUnenhanced, Monoenergetic plus\n- Inline Results DE SPP (Spectral\nPost-Processing with photon-\ncounting image data)","",""],["","Image viewing","","CT View&GO offers:","","","CT View&GO offers:","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p29-t0","doc_id":"K233650","page_num":29,"bbox":[72.3,95.46,523.02,767.52],"n_rows":13,"n_cols":7,"columns":["Software property","","Subject device","","","Primary predicate device",""],"rows":[["Software property","","Subject device","","","Primary predicate device",""],["","SOMATOM go.Now\nSOMATOM go.Up\nSOMATOM go.All\nSOMATOM go.Top\nSOMATOM go.Sim\nSOMATOM go.Open Pro\nSOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10 syngo CT VB10","SOMATOM go.Now","","","SOMATOM go.Now",""],["","","SOMATOM go.Up","","","SOMATOM go.Up",""],["","","SOMATOM go.All","","","SOMATOM go.All",""],["","","SOMATOM go.Top","","","SOMATOM go.Top",""],["","","SOMATOM go.Sim","","","SOMATOM go.Sim",""],["","","SOMATOM go.Open Pro","","","SOMATOM go.Open Pro",""],["","","SOMATOM X.cite","","","SOMATOM X.cite",""],["","","SOMATOM X.ceed","","","SOMATOM X.ceed",""],["","","with SOMARIS/10 syngo CT VB10","","","with SOMARIS/10 syngo CT VA40",""],["","","","","","(K211373)",""],["","- basic post-processing viewer (CT\nView&GO)\n- 2D and 3D (MPR, VRT, MIP and\nminIP)\n- Evaluation tools, Filming, Printing\n- Interactive Spectral Imaging (ISI)\n- Basic visualization tools: Endo\nView\n- Basic manipulation tools: DE ROI,\nROI HU, Average","","","- basic post-processing viewer (CT\nView&GO)\n- 2D and 3D (MPR, VRT, MIP and\nminIP)\n- Evaluation tools, Filming, Printing","",""],["Post-\nProcessing\ninterface","• Recon&GO Inline Results\nSoftware interface to post-\nprocessing algorithms which are\nunmodified when loaded onto the\nCT scanners and 510(k) cleared as\nmedical devices in their own right.\n• software interfaces for post-\nprocessing functionalities to\nprovide advanced visualization\ntools to prepare and process\nmedical images for diagnostic\npurpose.\nNote: The clearance of standalone\nAdvanced Visualization Application\nsoftware is mandatory precondition.\nThese advanced visualization tools\nare designed to support the\ntechnician & physician in the\nqualitative and quantitative\nmeasurement & analysis of clinical\ndata acquired and reconstructed by","","","• Recon&GO Inline Results\nSoftware interface to post-\nprocessing algorithms which are\nunmodified when loaded onto the\nCT scanners and 510(k) cleared as\nmedical devices in their own right.\n• software interfaces for post-\nprocessing functionalities to\nprovide advanced visualization\ntools to prepare and process\nmedical images for diagnostic\npurpose.\nNote: The clearance of standalone\nAdvanced Visualization Application\nsoftware is mandatory precondition.\nThese advanced visualization tools\nare designed to support the\ntechnician & physician in the\nqualitative and quantitative\nmeasurement & analysis of clinical\ndata acquired and reconstructed by","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p30-t0","doc_id":"K233650","page_num":30,"bbox":[72.27,95.46,523.05,744.0],"n_rows":18,"n_cols":7,"columns":["Software property","","Subject device","","","Primary predicate device",""],"rows":[["Software property","","Subject device","","","Primary predicate device",""],["","SOMATOM go.Now\nSOMATOM go.Up\nSOMATOM go.All\nSOMATOM go.Top\nSOMATOM go.Sim\nSOMATOM go.Open Pro\nSOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10 syngo CT VB10","SOMATOM go.Now","","","SOMATOM go.Now",""],["","","SOMATOM go.Up","","","SOMATOM go.Up",""],["","","SOMATOM go.All","","","SOMATOM go.All",""],["","","SOMATOM go.Top","","","SOMATOM go.Top",""],["","","SOMATOM go.Sim","","","SOMATOM go.Sim",""],["","","SOMATOM go.Open Pro","","","SOMATOM go.Open Pro",""],["","","SOMATOM X.cite","","","SOMATOM X.cite",""],["","","SOMATOM X.ceed","","","SOMATOM X.ceed",""],["","","with SOMARIS/10 syngo CT VB10","","","with SOMARIS/10 syngo CT VA40",""],["","","","","","(K211373)",""],["","Computed Tomography scanners.\nAdditional information regarding\nthe points of interface and inputs\nfor this feature is provided in\nSection 16.","","","Computed Tomography scanners.\nAdditional information regarding\nthe points of interface and inputs\nfor this feature is provided in\nSection 16.","",""],["Cybersecurity","IT Hardening","","","IT Hardening","",""],["HD FoV","HD FoV 4.0","","","HD FoV 4.0","",""],["Standard\ntechnologies","• FAST technologies\n• CARE technologies\n• GO technologies","","","• FAST technologies\n• CARE technologies\n• GO technologies","",""],["Iterative\nReconstruction\nMethods","ADMIRE*\nSAFIRE\niMAR\n*supported in SOMATOM go.All,\nSOMATOM go.Top, SOMATOM\ngo.Sim, SOMATOM go.Open Pro,\nSOMATOM X.cite and SOMATOM\nX.ceed","","","ADMIRE*\nSAFIRE\niMAR\n*supported in SOMATOM\ngo.All,SOMATOM go.Top,\nSOMATOM X.cite and SOMATOM\nX.ceed","",""],["Matrix sizes","256 x 256 pixels\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels (Precision\nMatrix)","","","256 x 256 pixels\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels (Precision\nMatrix)","",""],["DirectDensityTM","DirectDensityTM","","","DirectDensityTM","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p31-t0","doc_id":"K233650","page_num":31,"bbox":[72.3,95.46,523.02,481.17],"n_rows":13,"n_cols":7,"columns":["Software property","","Subject device","","","Primary predicate device",""],"rows":[["Software property","","Subject device","","","Primary predicate device",""],["","SOMATOM go.Now\nSOMATOM go.Up\nSOMATOM go.All\nSOMATOM go.Top\nSOMATOM go.Sim\nSOMATOM go.Open Pro\nSOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10 syngo CT VB10","SOMATOM go.Now","","","SOMATOM go.Now",""],["","","SOMATOM go.Up","","","SOMATOM go.Up",""],["","","SOMATOM go.All","","","SOMATOM go.All",""],["","","SOMATOM go.Top","","","SOMATOM go.Top",""],["","","SOMATOM go.Sim","","","SOMATOM go.Sim",""],["","","SOMATOM go.Open Pro","","","SOMATOM go.Open Pro",""],["","","SOMATOM X.cite","","","SOMATOM X.cite",""],["","","SOMATOM X.ceed","","","SOMATOM X.ceed",""],["","","with SOMARIS/10 syngo CT VB10","","","with SOMARIS/10 syngo CT VA40",""],["","","","","","(K211373)",""],["","(including relative electron density\nand relative mass density)","","","(including relative electron density\nand relative mass density)","",""],["Breath-hold\ntechnique","Respiratory Motion Management\nsupport breath hold triggered spiral\nscans with manual breath hold\ntriggered examinations.\nDirect Breathold: externally\ntriggered workflow to start a spiral\nscan by receiving a trigger signal\nfrom an external gating device.\n*Note: Direct Breathhold is not\navailable for SOMATOM go.Now","","","Respiratory Motion Management\nsupport breath hold triggered spiral\nscans with manual breath hold\ntriggered examinations.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p32-t0","doc_id":"K233650","page_num":32,"bbox":[72.3,364.8,523.02,748.8],"n_rows":3,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["FAST 3D Camera /\nFAST Integrated\nWorkflow","","","The bench test evaluates and compares the accuracy of the three sub-\nfeatures FAST Isocentering, FAST Range, and FAST Direction to the\naccuracy of the predicate device with syngo CT VA40 using the old\ncamera hardware and the then only available ceiling mount.\nThe objectives of the bench test are to demonstrate that the FAST 3D\nCamera feature of the subject device with SOMARIS/10 syngo CT VB10,\nwhere the algorithms have been optimized for a new camera hardware\nin two mounting positions, achieves comparable results as the predicate\ndevice with syngo CT VA40.\nThe FAST Isocentering accuracy of the subject device with syngo CT VB10\nis comparable to the predicate device with syngo CT VA40, regardless of\nthe camera mounting position.\nFor the FAST Range feature, the detection accuracy of all body region\nboundaries is comparable between the subject device with syngo CT\nVB10 and predicate device with syngo CT VA40. In the gantry mounting\nposition, the legs are often occluded by the torso when the patient is\nlying head-first on the table. This is not a severe limitation, as leg\nexaminations are usually performed feet-first.\nThe FAST Direction pose detection results are of comparable accuracy for\nsubject and predicate device, regardless of the camera mounting\nposition.\nOverall, the SOMARIS/10 syngo CT VB10 delivers comparable accuracy to\nthe SOMARIS/10 syngo CT VA40 predicate for the new FAST 3D Camera\nhardware, also in the new gantry position."]],"caption_candidate":"Table 10: Non-clinical performance testing (bench testing).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p33-t0","doc_id":"K233650","page_num":33,"bbox":[72.28,95.46,523.04,761.7],"n_rows":5,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["Multi-Purpose Table","","","A CT system with extended distance between CT gantry and patient table\nbase plus a mobile C-arm system were combined to evaluate the\ntechnical feasibility and possible limitations of this combination.\nThe range of possible movement for the mobile C-arm in different\npositions between CT gantry and patient table was tested and\ndocumented by measurement of angles.\nBased on the test results it can be concluded that a CT scanner, equipped\nwith a Multi-Purpose (Vitus) Patient Table, which is installed with\nenhanced distance (674 mm) to the CT gantry and offers the iCT mode\nfunctionality, provides sufficient freedom of movement for a mobile C-\narm X-ray system to be used for clinical routine without any significant\nlimitations for the myNeedle Lasers or FAST 3D Camera."],["Direct Breathhold","","","The test results showed that using the Direct Breathhold functionality, a\nspiral scan can automatically be triggered from an external respiratory\ngating device. The actual scan remains unchanged, and the object is\ncorrectly depicted in the resulting image."],["ZeeFree","","","The bench tests evaluate the performance of ZeeFree reconstruction.\nThe objectives of the tests are to demonstrate:\n• that the number of artefacts which can be attributed to a stack\nmisalignment (e.g. discontinuities in vessel structures,\nanatomical steps at air-soft-tissue interfaces, doubling of vessel\nor other anatomy) and which are often caused by incomplete\npatient breath-hold can be reduced in a “Cardiac Stack Artefact\nCorrection” (SAC) reconstruction compared to the standard\nreconstruction with otherwise matching reconstruction\nparameters.\n• that no artefacts are introduced by a SAC reconstruction.\nThe test results show:\n• If misalignment artefacts are identified in non-corrected\nstandard ECG-gated reconstructed sequence or spiral images,\nthe feature “Cardiac Stack Artefact Correction” (SAC, marketing\nname: ZeeFree) enables optional stack artefact corrected\nimages, which reduce the number of alignment artefacts.\n• The SAC reconstruction does not introduce new artefacts, which\nwere previously not present in the non-corrected standard\nreconstruction.\n• The SAC reconstruction does realize equivalent image quality in\nquantitative standard physics phantom-based measurements\n(ACR, Gammex phantom) in terms of noise, homogeneity, high-\ncontrast resolution, slice thickness and CNR compared to a non-\ncorrected standard reconstruction."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p34-t0","doc_id":"K233650","page_num":34,"bbox":[72.28,95.46,523.04,501.72],"n_rows":4,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","• The SAC reconstruction does realize equivalent image quality in\nquantitative and qualitative phantom-based measurements with\nrespect to metal objects compared to a non-corrected standard\nreconstruction.\n• The SAC algorithm can be successfully applied to phantom data if\nderived from a suitable motion phantom demonstrating its\ncorrect technical function on the tested device.\n• The SAC algorithm is independent from the physical detector\nwidth of the acquired data"],["myNeedle Guide\n(with myNeedle\nDetection)","","","Tests were performed to ensure clinical usability of the myNeedle Guide\nneedle detection algorithm. Two individual tests were performed. The\naccuracy of the automatic needle detection algorithm was tested. The\nreduction of necessary user interactions for navigating to a needle-\noriented view with and without the support of the automatic needle\ndetection algorithm was analyzed.\nIt has been shown that the algorithm was able to consistently detect\nneedle-tips over a wide variety of scans in 90.76% of cases.\nFurther, the results of this bench test clearly show that the auto needle\ndetection functionality reduces the number of interactions steps needed\nto generate a needle-aligned view in the CT Intervention SW.\nWith successful AI-based needle tip detection, no user interaction is\nneeded to achieve needle-aligned view during needle progression.\nAdditional manual adjustment (fine tuning) of the needle-aligned view is\nalways possible."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p34-t1","doc_id":"K233650","page_num":34,"bbox":[72.28,577.62,523.04,768.66],"n_rows":6,"n_cols":9,"columns":["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/19/2022","12-349","NEMA","","","PS 3.1 - 3.20 2022d","","","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set"],["07/06/2020","12-325","NEMA","","","XR 25-2019","","","Computed Tomography Dose\nCheck"],["07/06/2020","12-330","NEMA","","","XR 28-2018","","","Supplemental Requirements\nfor User Information and\nSystem Function Related to\nDose in CT"]],"caption_candidate":"Table 11: Recognized Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p35-t0","doc_id":"K233650","page_num":35,"bbox":[72.26,95.46,523.06,744.66],"n_rows":11,"n_cols":9,"columns":["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/23/2019","12-328","IEC","","","61223-3-5 Edition\n2.0 2019-09","","","Evaluation and routine testing\nin medical imaging\ndepartments - Part 3-5:\nAcceptance tests and\nconstancy tests - Imaging\nperformance of computed\ntomography X-ray equipment\n[Including: Technical\nCorrigendum 1 (2006)]"],["03/14/2011","12-226","IEC","","","61223-2-6 Second\nEdition 2006-11","","","Evaluation and routine testing\nin medical imaging\ndepartments - Part 2-6:\nConstancy tests - Imaging\nperformance of computed\ntomography X-ray equipment"],["01/14/2014","12-269","IEC","","","60601-1-3 Edition\n2.1 2013-04","","","Medical electrical equipment\n- Part 1-3: General\nrequirements for basic safety\nand essential performance –\nCollateral Standard: Radiation\nprotection in diagnostic X-ray\nequipment"],["06/27/2016","12-302","IEC","","","60601-2-44 Edition\n3.2: 2016","","","Medical electrical equipment\n- Part 2-44: Particular\nrequirements for the basic\nsafety and essential\nperformance of x-ray\nequipment for computed\ntomography"],["12/23/2019","5-125","ANSI AAMI\nISO","","","14971: 2019","","","Medical devices - Applications\nof risk management to\nmedical devices"],["","","ISO","","","14971 Third Edition\n2019-12","","","Medical devices - Application\nof risk management to\nmedical devices"],["01/14/2019","13-79","ANSI AAMI\nIEC","","","62304:2006/A1:2016","","","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1\n(2016)]"],["","","IEC","","","62304 Edition 1.1\n2015-06","","","Medical device software -\nSoftware life cycle processes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p36-t0","doc_id":"K233650","page_num":36,"bbox":[72.26,95.46,523.06,761.58],"n_rows":12,"n_cols":9,"columns":["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["","","","","","CONSOLIDATED\nVERSION","","",""],["07/09/2014","19-46","ANSI AAMI","","","ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012\n(Cons. Text) [Incl.\nAMD2:2021]","","","Medical electrical equipment\n- Part 1: General\nrequirements for basic safety\nand essential performance\n(IEC 60601-1:2005, MOD)\n[Including Amendment 2\n(2021)]"],["09/17/2018","19-36","ANSI AAMI\nIEC","","","60601-1-2:2014\n[Including AMD\n1:2021]","","","Medical electrical equipment\n- Part 1-2: General\nrequirements for basic safety\nand essential performance -\nCollateral Standard:\nElectromagnetic disturbances\n- Requirements and tests"],["","","IEC","","","60601-1-2 Edition\n4.1 2020-09\nCONSOLIDATED\nVERSION","","","Medical electrical equipment\n- Part 1-2: General\nrequirements for basic safety\nand essential performance -\nCollateral Standard:\nElectromagnetic disturbances\n- Requirements and tests"],["12/23/2016","5-129","ANSI AAMI\nIEC","","","62366-\n1:2015+AMD1:2020\n(Consolidated Text)","","","Medical devices Part 1:\nApplication of usability\nengineering to medical\ndevices, including\nAmendment 1"],["","","IEC","","","62366-1 Edition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","Medical devices - Part 1:\nApplication of usability\nengineering to medical\ndevices"],["07/09/2014","12-273","IEC","","","60825-1 Edition 2.0\n2007-03","","","Safety of laser products - Part\n1: Equipment classification,\nand requirements"],["12/21/2020","5-132","IEC","","","60601-1-6 Edition\n3.2 2020-07\nCONSOLIDATED\nVERSION","","","Medical electrical equipment\n- Part 1-6: General\nrequirements for basic safety\nand essential performance -\nCollateral standard: Usability"],["12/23/2019","12-309","IEC","","","60601-2-28 Edition\n3.0 2017-06","","","Medical electrical equipment\n- Part 2-28: Particular"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p37-t0","doc_id":"K233650","page_num":37,"bbox":[72.28,95.46,523.04,273.0],"n_rows":5,"n_cols":9,"columns":["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of\nEntry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["","","","","","","","","requirements for the basic\nsafety and essential\nperformance of X-ray tube\nassemblies for medical\ndiagnosis"],["12/20/2021","12-341","IEC","","","62563-1 Edition 1.2\n2021-07\nCONSOLIDATED\nVERSION","","","Medical electrical equipment\n- Medical image display\nsystems - Part 1: Evaluation\nmethods"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233650-p37-t1","doc_id":"K233650","page_num":37,"bbox":[72.28,316.0,523.04,584.58],"n_rows":6,"n_cols":6,"columns":["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],"rows":[["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],["","Developing","","","",""],["","Organization","","","",""],["IEC","","","60601-\n1:2005+A1:2012+A2:2020","Medical electrical\nequipment - part 1:\ngeneral requirements\nfor basic safety and\nessential performance","ANSI AAMI ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons.\nText) [Incl. AMD2:2021]"],["IEC/ISO","","","17050-1","Conformity Assessment\n– Supplier’s declaration\nof conformity – Part 1:\nGeneral requirements","Declaration of\nconformance to FDA\nrecognized consensus\nstandards."],["IEC/ISO","","","17050-2","Conformity assessment\n– Supplier’s declaration\nof conformity – Part 2:\nSupporting\ndocumentation.","General consensus\nstandards not currently\nrecognized by FDA."]],"caption_candidate":"Table 12: General Use Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p9-t0","doc_id":"K233657","page_num":9,"bbox":[72.28,205.02,523.04,299.04],"n_rows":4,"n_cols":6,"columns":["","Term","","","Definition",""],"rows":[["","Term","","","Definition",""],["New","","","The feature is newly supported for Siemens CT Scanners and the subject device","",""],["Modified","","","This feature is a modified form of a feature cleared within the predicate devices","",""],["Enabled","","","This feature is currently supported by other cleared Siemens CT systems or\ncleared Siemens stand-alone software applications.","",""]],"caption_candidate":"Table 1: Overview of term definition.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p11-t0","doc_id":"K233657","page_num":11,"bbox":[72.27,95.46,523.05,762.84],"n_rows":16,"n_cols":10,"columns":["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","SOMATOM Force\nSOMARIS/7 syngo CT VB30\n(K230421)","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT VB30",""],["","","VB10","","","VA50","","","",""],["","","","","","","","","(K230421)",""],["","","","","","(K220814)","","","",""],["","Direct Conversion\nwith “Quantum\nTechnology”","","","Direct Conversion\nwith “Quantum\nTechnology”","","","","",""],["Detector\nvolume coverage\n(mm)","2x 57.6","","","2x 57.6","","","2x 57.6","",""],["Detector\nphysical rows","2x 288","","","2x 288","","","2x 96","",""],["Detector\nslice width (mm)","0.2","","","0.2","","","0.6\n(optional: 0.4, 0.5)","",""],["Detector\nDAS channel no.","2752 (A system)\n1984 (B system)","","","2752 (A system)\n1984 (B system)","","","920 (A system)\n640 (B system)","",""],["Tube\ntechnology","VECTRON","","","VECTRON","","","VECTRON","",""],["Tube\nkV steps","70, 90, 100, 120, 140,\n150\n(150 kV only available\non the smaller tube-\ndetector system (B\nsystem) and only in\ncombination with the\nadditional Sn filter, 0.7\nmm)","","","70, 90, 100, 120, 140","","","70, 80, 90, 100, 110, 120,\n130, 140, 150","",""],["Tube\nmax. current\n(mA)","2x 1300","","","2x 1300","","","2x 1300","",""],["Tube\ntube focus (mm)","0.4 x 0.5/8°\n0.6 x 0.7/8°\n0.8 x 1.1/8°","","","0.4 x 0.5/8°\n0.6 x 0.7/8°\n0.8 x 1.1/8°","","","0.4 x 0.5/8°\n0.6 x 0.7/8°\n0.8 x 1.1/8°","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p12-t0","doc_id":"K233657","page_num":12,"bbox":[72.26,95.46,523.06,750.54],"n_rows":18,"n_cols":10,"columns":["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","SOMATOM Force\nSOMARIS/7 syngo CT VB30\n(K230421)","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT VB30",""],["","","VB10","","","VA50","","","",""],["","","","","","","","","(K230421)",""],["","","","","","(K220814)","","","",""],["","(for both tubes)","","","(for both tubes)","","","(for both tubes)","",""],["Tube\nheat capacity","higher than 30 MHU","","","higher than 30 MHU","","","Higher than 30 MHU","",""],["Gantry\nbore size (cm)","82","","","82","","","78","",""],["Gantry\nScan FoV (cm)","50","","","50","","","50","",""],["Gantry\nrotation time\n(sec)","0.25, 0.5, 1.0","","","0.25, 0.5, 1.0","","","0.25*, 0.285, 0.325*, 0.5,\n1.0\n(*optional)","",""],["Gantry\nTilt (degree)","N/A","","","N/A","","","N/A","",""],["Maximum\ntemporal\nresolution in ECG\ngated or\ntriggered\nexamination\n(ms)","mono-segment: 66\nbi-segment: 33","","","mono-segment: 66\nbi-segment: 33","","","mono-segment, standard:\n75\nmono-segment, optional:\n66\nbi-segment, standard: 38\nbi-segment, optional: 33","",""],["Maximum scan\nspeed at pitch\n(mm/s at pitch x)","737 mm/s at pitch 3.2","","","737 mm/s at pitch 3.2","","","737 mm/s at pitch 3.2","",""],["Patient Table\nType","Vario 2.D\nVitus","","","Vario 2.D\nVitus","","","PHS5\nMPT4","",""],["Max. Scan length\nTopogram (mm)","Vario 2.D: 2080\nVitus: 2080","","","Vario 2.D: 2080\nVitus: 2080","","","PHS5: 1970\nMPT4: 1970","",""],["Max. Scan length","Vario 2.D: 2000","","","Vario 2.D: 2000","","","PHS5: 1953","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p13-t0","doc_id":"K233657","page_num":13,"bbox":[72.3,95.46,523.05,737.76],"n_rows":17,"n_cols":12,"columns":["Hardware\nproperty","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Hardware\nproperty","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","","","device","","","device",""],["","","","","NAEOTOM Alpha","","","NAEOTOM Alpha","","SOMATOM Force\nSOMARIS/7 syngo CT VB30\n(K230421)","SOMATOM Force",""],["","","","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT VB30",""],["","","","","VB10","","","VA50","","","",""],["","","","","","","","","","","(K230421)",""],["","","","","","","","(K220814)","","","",""],["Image acquisition\n(mm)","","","Vitus: 2000","","","Vitus: 2000","","","MPT4: 1953","",""],["","Patient table","","Vario 2.D: 307\nVitus: 307 or 340","","","Vario 2.D: 307\nVitus: 307","","","PHS5: 227\nMPT4: 227 or 307 (with\nbariatric/trauma table top)","",""],["","Max. weight","","","","","","","","","",""],["","capacity (kg)","","","","","","","","","",""],["Patient table\nInstallation\noption","Patient table","","Regular installation\n(Vario 2.D and Vitus):\n474 mm\nInstallation option\nwith extended\ndistance (Vitus):\n674 mm (474 mm +\n200 mm)","","","Regular installation\n(Vario 2.D and Vitus):\n474 mm","","","Regular installation (PHS5\nand MPT4):\n400 mm","",""],["","Installation","","","","","","","","","",""],["","option","","","","","","","","","",""],["Spectral\nfiltration","","","Tin Filter for both\ntubes:\n0.4 mm\nadditional Tin Filter\nfor the smaller tube-\ndetector system (B\nsystem) only:\n0.7 mm","","","Tin Filter for both\ntubes:\n0.4 mm","","","Tin Filter for both tubes:\n0.6 mm","",""],["FAST 3D Camera\nfor patient\npositioning","","","option for patient\npositioning with 3D\nCamera\nceiling mounted,\nmodified design","","","option for patient\npositioning with 3D\nCamera\nceiling mounted","","","option for patient\npositioning with 3D Camera\nceiling mounted","",""],["X-ray foot switch","","","Option to trigger\nhands-free scanning","","","Option to trigger\nhands-free scanning","","","Option to trigger hands-\nfree scanning","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p14-t0","doc_id":"K233657","page_num":14,"bbox":[72.27,95.46,523.04,610.62],"n_rows":11,"n_cols":10,"columns":["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Hardware\nproperty","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","SOMATOM Force\nSOMARIS/7 syngo CT VB30\n(K230421)","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT VB30",""],["","","VB10","","","VA50","","","",""],["","","","","","","","","(K230421)",""],["","","","","","(K220814)","","","",""],["Table foot switch","Option for table\npatient movement","","","Option for table\npatient movement","","","N/A","",""],["Tablet dock for\npatient table","Option for mounting\nof the tablet on the\npatient table.","","","Option for mounting\nof the tablet on the\npatient table.","","","N/A","",""],["Interventional\nJoystick (IVJ)","Option to move the\ntable during\nmyNeedle Guide\nprocedures in the\nexamination room.\nelectrical connection\nfor the tablet dock\nwhich allows charging\nthe tablet when\nmounted.","","","Option to move the\ntable during\nmyNeedle Guide\nprocedures in the\nexamination room.\nelectrical connection\nfor the tablet dock\nwhich allows charging\nthe tablet when\nmounted.","","","i-control:\noption to operate some of\nthe CT functions including\npatient table movement as\nan alternative to the gantry\noperating panel and the\ninput units at the console.","",""],["Laser supported\nworkflow","Laser in combination\nwith FAST\nIsocentering visualize\ncoordinates for\npatient isocenter\nposition;\nmyNeedle Laser\nvisualizes a planned\nneedle path for\ninterventions","","","Laser in combination\nwith FAST\nIsocentering visualize\ncoordinates for\npatient isocenter\nposition;\nmyNeedle Laser\nvisualizes a planned\nneedle path for\ninterventions","","","Laser in combination with\nFAST Isocentering visualize\ncoordinates for patient\nisocenter position;","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p16-t0","doc_id":"K233657","page_num":16,"bbox":[72.31,95.46,523.01,768.6],"n_rows":7,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["","• Contrast media\nprotocols (including\ncoronary CTA)\n• Pediatric Protocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy\nacquisition\n• Dynamic imaging\n(Flex 4D Spiral)\n• Protocols supporting\nCT Intervention,\nCardiac Scanning,\nSpectral imaging for\nchild examination,\nSpectral imaging with\nhigh resolution\n• Protocols for\nQuantum Imaging\nmodes:\n- Quantum\n- Quantumplus\n- Quantum HD\n(previously:\nQuantum High\nresolution)\n- Quantum HD\nCardiac\n(previously High\nresolution Dual\nSource Cardiac\nmodes). In\naddition, a\nspectral image\nresults from\ndual source\n96x0.2mm ultra\nhigh-resolution\nmode can\noptionally be\nobtained","","","• Contrast media\nprotocols (including\ncoronary CTA)\n• Pediatric Protocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy\nacquisition\n• Dynamic imaging\n(Flex 4D Spiral)\n• Protocols\nsupporting CT\nIntervention,\nCardiac Scanning,\nSpectral imaging for\nchild examination,\nSpectral imaging\nwith high resolution\n• Protocols for\nQuantum Imaging\nmodes:\n- Quantum\n- Quantumplus\n- Quantum High\nresolution\n- High resolution\nDual Source\nCardiac modes","","","• Contrast media\nprotocols (including\ncoronary CTA)\n• Pediatric Protocols\n• Turbo Flash Spiral\n• Dual Source Dual\nEnergy protocols\n• Adaptive 4D Spiral\n• Protocols for\nRadiation Therapy\nPlanning\n• Dual Source Dual\nEnergy protocols for\nRadiation Therapy\nPlanning\n• Protocols for CT\nintervention,\nCardiac Scanning","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p17-t0","doc_id":"K233657","page_num":17,"bbox":[72.31,95.46,523.03,746.41],"n_rows":8,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["","- Quantumpeak\n(Quantumpeak\nmode is\nidentical to the\nDual Source\nDual Energy\nmodes at\nSOMATOM Dual\nSource Scanners\nin K230421","","","","","","","",""],["Advanced\nReconstruction","Recon&GO:\n-Spectral Recon (Dual\nEnergy Reconstruction\nfrom photon-counting\ndata) / including Virtual\nUnenhanced,\nMonoenergetic plus\n-Inline Results DE SPP\n(Spectral Post-\nProcessing with photon-\ncounting image data)\n-Inline Anatomical\nranges (Parallel/Radial)\nincl. Virtual\nUnenhanced,\nMonoenergetic plus\n(already cleared with\nthe stand-alone medical\ndevice syngo.via\n(K191040)\n-Inline Spine and Rib\nRanges (already cleared\nwith the stand-alone\nmedical device syngo.CT\nApplications (syngo.CT\nBone Reading)\nK220450))","","","Recon&GO:\n-Spectral Recon (Dual\nEnergy Reconstruction\nfrom photon-counting\ndata) / including Virtual\nUnenhanced,\nMonoenergetic plus\n-Inline Results DE SPP\n(Spectral Post-\nProcessing with\nphoton-counting image\ndata)","","","Advanced\nreconstruction tools\nsupported:\nThe syngo acquisition\nworkplace provides\nimage reconstruction\nand routine\npostprocessing.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p18-t0","doc_id":"K233657","page_num":18,"bbox":[72.3,95.46,523.03,759.96],"n_rows":14,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["","- Inline table and bone\nremoval (already\ncleared with the stand-\nalone medical device\nsyngo.CT Extended\nFunctionality (K221727))","- Inline table and bone","","","","","","",""],["","","removal (already","","","","","","",""],["","","cleared with the stand-","","","","","","",""],["","","alone medical device","","","","","","",""],["","","syngo.CT Extended","","","","","","",""],["","","Functionality (K221727))","","","","","","",""],["Image viewing","CT View&GO offers:\n- basic post-processing\nviewer (CT View&GO)\n- 2D and 3D (MPR, VRT,\nMIP and minIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive Spectral\nImaging (ISI)\n- Basic visualization\ntools: Endoscopic View\n- Basic manipulation\ntools: DE ROI, ROI HU\nThreshold, Average\n- Automated table and\nbone removal\n(already cleared with\nthe stand-alone medical\ndevice syngo.CT\nExtended Functionality\n(K221727))","","","CT View&GO offers:\n- basic post-processing\nviewer (CT View&GO)\n- 2D and 3D (MPR, VRT,\nMIP and minIP)\n- Evaluation tools,\nFilming, Printing","","","syngo Viewing offers:\n- 2D and 3D (MPR, VRT,\nMIP and minIP)\n- Evaluation tools,\nFilming, Printing","",""],["Post-Processing\ninterface","• Recon&GO Inline\nResults:\nSoftware interface to\npost-processing\nalgorithms which are\nunmodified when\nloaded onto the CT\nscanners and 510(k)","","","• Recon&GO Inline\nResults:\nSoftware interface to\npost-processing\nalgorithms which are\nunmodified when\nloaded onto the CT\nscanners and 510(k)","","","syngo.via - Wide Range\nof individual\napplications, syngo.via\nis a software solution\nintended to be used for\nviewing, manipulation,\ncommunication, and\nstorage of medical","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p19-t0","doc_id":"K233657","page_num":19,"bbox":[72.29,95.46,523.03,759.79],"n_rows":9,"n_cols":12,"columns":["Software property","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","","","device","","","device",""],["","","","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","","","VB10","","","VA50","","","VB30",""],["","","","","","","","(K220814)","","","(K230421)",""],["","","","cleared as medical\ndevices in their own\nright.\n• software interfaces\nfor post-processing\nfunctionalities to\nprovide advanced\nvisualization tools to\nprepare and process\nmedical images for\ndiagnostic purpose.\nNote: The clearance of\nstandalone Advanced\nVisualization Application\nsoftware is mandatory\nprecondition.\nThese advanced\nvisualization tools are\ndesigned to support the\ntechnician & physician\nin the qualitative and\nquantitative\nmeasurement & analysis\nof clinical data acquired\nand reconstructed by\nComputed Tomography\nscanners. Additional\ninformation regarding\nthe points of interface\nand inputs for this\nfeature is provided in\nSection 16.","","","cleared as medical\ndevices in their own\nright.\n• software interfaces\nfor post-processing\nfunctionalities to\nprovide advanced\nvisualization tools to\nprepare and process\nmedical images for\ndiagnostic purpose.\nNote: The clearance of\nstandalone Advanced\nVisualization\nApplication software is\nmandatory\nprecondition.\nThese advanced\nvisualization tools are\ndesigned to support\nthe technician &\nphysician in the\nqualitative and\nquantitative\nmeasurement &\nanalysis of clinical data\nacquired and\nreconstructed by\nComputed Tomography\nscanners. Additional\ninformation regarding\nthe points of interface\nand inputs for this\nfeature is provided in\nSection 16.","","","images. It can be used\nas a standalone device\nor together with a\nvariety of cleared and\nunmodified syngo\nbased software\noptions.","",""],["Cybersecurity","","","IT Hardening","","","IT Hardening","","","IT Hardening","",""],["","HD FoV","","supported","","","N/A","","","supported","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p20-t0","doc_id":"K233657","page_num":20,"bbox":[72.3,95.46,523.03,743.53],"n_rows":9,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["Standard\ntechnologies","• FAST technologies\n• CARE technologies\n• GO technologies\n• CARE keV","","","• FAST technologies\n• CARE technologies\n• GO technologies\n• CARE keV","","","• FAST technologies\n• CARE technologies","",""],["myExam\nCompanion –\nmyExam\nCompass/myExam\nCockpit","• myExam Compass\ncollects information\nabout the current\npatient to dynamically\nadapt the scan\nparameters or exchange\nrecon jobs according to\nthe patient's\ncharacteristics\n• myExam Cockpit\noption of displaying,\nmodifying, creating, and\ndeleting Clinical\nDecision Trees (CDTs).\nmyExam Compass\nfunctionality offers the\npossibility to\nactivate/deactivate\ndiagnostic scan ranges,\nBolus Tracking and Test\nBolus ranges. myExam\nCockpit allows to define\nthese new settings.","","","• myExam Compass\ncollects information\nabout the current\npatient to dynamically\nadapt the scan\nparameters or\nexchange recon jobs\naccording to the\npatient's characteristics\n• myExam Cockpit\noption of displaying,\nmodifying, creating,\nand deleting Clinical\nDecision Trees (CDTs).","","","N/A","",""],["Scan&GO","Scan&GO\nWith software version\nsyngo CT VB10, the\npreviously stand-alone\nScan&GO software\nfunctionality is fully\nincorporated into the\nsubject device CT\nscanner system. The","","","Scan&GO","","","N/A","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p21-t0","doc_id":"K233657","page_num":21,"bbox":[72.3,95.46,523.04,765.25],"n_rows":13,"n_cols":12,"columns":["Software property","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","","","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","","","device","","","device",""],["","","","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","","","VB10","","","VA50","","","VB30",""],["","","","","","","","(K220814)","","","(K230421)",""],["","","","","functionality remains","","","","","","",""],["","","","","unchanged.","","","","","","",""],["Reconstruction\nOptions for\nCardiac Imaging","","","• Standard\n(renamed from\n“TrueStack ‘off’” on the\nprimary predicate\ndevice)\n• TrueStack\n(renamed from\n“TrueStack ‘on’” on the\nprimary predicate\ndevice)\n• ZeeFree\nallows the\nreconstruction of\nECG-gated spiral or\nECG-triggered\nsequence data in a\ncardiac cycle-to-\ncycle border aligned\nfashion","","","• TrueStack “off”\n• TrueStack “on”","","","• TrueStack “off”\n• TrueStack “on”","",""],["Iterative\nReconstruction\nMethods","","","Quantum Iterative\nReconstruction\niMAR","","","Quantum Iterative\nReconstruction\niMAR","","","ADMIRE\nSAFIRE\niMAR","",""],["Precision Matrix","","","Precision Matrix\nresolution\nsupport image matrix\nsizes of:\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels","","","Precision Matrix\nresolution\nsupport image matrix\nsizes of:\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels","","","Precision Matrix\nresolution\nsupport image matrix\nsizes of:\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels","",""],["","Multi-Threshold","","","","","","","","N/A","",""],["","Acquisition","","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p22-t0","doc_id":"K233657","page_num":22,"bbox":[72.31,95.46,523.03,768.97],"n_rows":9,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["","• acquisition, storage,\nand reconstruction\nof projection raw\ndata of different\nenergy thresholds\n(T1, T2, T3 and T4)\n• projection raw data\nof the three higher\nenergy thresholds\n(T2, T3, and T3) can\nbe reconstructed by\noffline\nreconstruction tools\nor on the CT system","","","• acquisition, storage,\nand reconstruction\nof projection raw\ndata of different\nenergy thresholds\n(T1, T2, T3 and T4)\n• projection raw data\nof the three higher\nenergy thresholds\n(T2, T3, and T3) are\nreconstructed by\noffline\nreconstruction\ntools.","","","","",""],["myNeedle Guide","• plan the needle path\nand perform control\nscans (i-Sequence, i-\nSpiral, i-Fluoro)\n• myNeedle Detection\nalgorithm\n(modification of the\nmyNeedle Guide 3D\nsoftware)","","","• plan the needle\npath and perform\ncontrol scans (i-\nSequence, i-Spiral, i-\nFluoro)","","","N/A","",""],["FAST 3D Camera\nwith FAST\nIntegrated\nWorkflow","FAST Integrated\nWorkflow including the\nsub-features FAST\nRange, FAST\nIsocentering and FAST\nDirection\nFAST Range, FAST\nIsocentering and FAST\nDirection algorithms\noptimized with data","","","FAST Integrated\nWorkflow including the\nsub-features FAST\nRange, FAST\nIsocentering and FAST\nDirection","","","FAST Integrated\nWorkflow including the\nsub-features FAST\nRange, FAST\nIsocentering and FAST\nDirection","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p23-t0","doc_id":"K233657","page_num":23,"bbox":[72.31,95.46,523.01,246.27],"n_rows":8,"n_cols":10,"columns":["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],"rows":[["Software property","Subject device","","","","Primary predicate","","","Secondary predicate",""],["","","","","","device","","","device",""],["","","NAEOTOM Alpha","","","NAEOTOM Alpha","","","SOMATOM Force",""],["","","SOMARIS/10 syngo CT","","","SOMARIS/10 syngo CT","","","SOMARIS/7 syngo CT",""],["","","VB10","","","VA50","","","VB30",""],["","","","","","(K220814)","","","(K230421)",""],["","from the redesigned\ncamera.","from the redesigned","","","","","","",""],["","","camera.","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p24-t0","doc_id":"K233657","page_num":24,"bbox":[72.28,145.32,523.04,768.3],"n_rows":5,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["FAST 3D Camera /\nFAST Integrated\nWorkflow","","","The bench test evaluates and compares the accuracy of the three sub-\nfeatures FAST Isocentering, FAST Range, and FAST Direction to the\naccuracy of the predicate device with syngo CT VA50 using the old\ncamera hardware and the then only available ceiling mount.\nThe objectives of the bench test are to demonstrate that the FAST 3D\nCamera feature of the subject device with SOMARIS/10 syngo CT VB10,\nwhere the algorithms have been optimized for a new camera hardware\nin two mounting positions, achieves comparable results as the predicate\ndevice with syngo CT VA50.\nThe FAST Isocentering accuracy of the subject device with syngo CT VB10\nis comparable to the predicate device with syngo CT VA50, regardless of\nthe camera mounting position.\nFor the FAST Range feature, the detection accuracy of all body region\nboundaries is comparable between the subject device with syngo CT\nVB10 and predicate device with syngo CT VA50.\nThe FAST Direction pose detection results are of comparable accuracy for\nsubject and predicate device, regardless of the camera mounting\nposition.\nOverall, the SOMARIS/10 syngo CT VB10 delivers comparable accuracy to\nthe SOMARIS/10 syngo CT VA50 predicate for the new FAST 3D Camera\nhardware."],["Multi-Purpose Table","","","This document describes a hardware test in which a CT system with\nextended distance between CT gantry and patient table base plus a\nmobile C-arm system were combined to evaluate the technical feasibility\nand possible limitations of this combination.\nThe range of possible movement for the mobile C-arm in different\npositions between CT gantry and patient table was tested and\ndocumented by measurement of angles.\nBased on the test results it can be concluded that a CT scanner, equipped\nwith a Multi-Purpose (Vitus) Patient Table, which is installed with\nenhanced distance (674 mm) to the CT gantry and offers the iCT mode\nfunctionality, provides sufficient freedom of movement for a mobile C-\narm X-ray system to be used for clinical routine without any significant\nlimitations for my needle Laser or 3D Camera."],["ZeeFree","","","The bench tests evaluate the performance of ZeeFree reconstruction.\nThe objectives of the tests are to demonstrate:\n• that the number of artefacts which can be attributed to a stack\nmisalignment (e.g. discontinuities in vessel structures,\nanatomical steps at air-soft-tissue interfaces, doubling of vessel"]],"caption_candidate":"Table 6: Non-clinical performance testing (bench testing).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p25-t0","doc_id":"K233657","page_num":25,"bbox":[72.29,95.46,523.03,757.8],"n_rows":4,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","or other anatomy) and which are often caused by incomplete\npatient breath-hold can be reduced in a “Cardiac Stack Artefact\nCorrection” (SAC) reconstruction compared to the standard\nreconstruction with otherwise matching reconstruction\nparameters.\n• that no artefacts are introduced by a SAC reconstruction.\nThe test results show:\n• If misalignment artefacts are identified in non-corrected\nstandard ECG-gated reconstructed sequence or spiral images,\nthe feature “Cardiac Stack Artefact Correction” (SAC, marketing\nname: ZeeFree) enables optional stack artefact corrected\nimages, which reduce the number of alignment artefacts.\n• The SAC reconstruction does not introduce new artefacts, which\nwere previously not present in the non-corrected standard\nreconstruction.\n• The SAC reconstruction does realize equivalent image quality in\nquantitative standard physics phantom-based measurements\n(ACR, Gammex phantom) in terms of noise, homogeneity, high-\ncontrast resolution, slice thickness and CNR compared to a non-\ncorrected standard reconstruction.\n• The SAC reconstruction does realize equivalent image quality in\nquantitative and qualitative phantom-based measurements with\nrespect to metal objects compared to a non-corrected standard\nreconstruction.\n• The SAC algorithm can be successfully applied to phantom data if\nderived from a suitable motion phantom demonstrating its\ncorrect technical function on the tested device.\n• The SAC algorithm is independent from the physical detector\nwidth of the acquired data"],["myNeedle Guide\n(with myNeedle\nDetection)","","","Tests were performed to ensure clinical usability of the myNeedle Guide\nneedle detection algorithm. Two individual tests were performed. The\naccuracy of the automatic needle detection algorithm was tested. The\nreduction of necessary user interactions for navigating to a needle-\noriented view with and without the support of the automatic needle\ndetection algorithm was analyzed.\nIt has been shown that the algorithm was able to consistently detect\nneedle-tips over a wide variety of scans in 90.76% of cases.\nFurther, the results of this bench test clearly shows that the auto needle\ndetection functionality reduces the number of interactions steps needed\nto generate a needle-aligned view in the CT Intervention SW. Zero user\ninteractions are required and a needle-aligned view is displayed right\naway after a new scan, if auto needle detection is switched on in the SW"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p26-t0","doc_id":"K233657","page_num":26,"bbox":[72.27,95.46,523.05,759.3],"n_rows":6,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","configuration. Therefore, the test is already passed if only a single user\ninteraction is necessary to achieve a needle-oriented view in the manual\nworkflow."],["Quantum Spectral\nImaging","","","Tests were performed to demonstrate that:\n• T3D reconstructions in Quantumpeak mode are possible with the\nsharpest available kernels up to Qr89, Br98, etc.\n• Quantumpeak scan mode allows reconstructions of\nmonoenergetic images at energy levels from 40 to 190 keV.\nThe evaluation has been performed based on phantom studies.\nThe results showed that:\n• with T3D reconstructions from Quantumpeak scan modes, high\nresolution images with sharp kernel up to Br98 are obtained. The\nresolution is comparable to other Highresultra scan modes of the\nNAEOTOM Alpha.\n• Monoenergetic reconstructions from Quantumpeak scan modes\nare free of artifacts. Measured CT values precisely match the\nreference values.\n• The accuracy of monoenergetic reconstructions in iodine and\ncalcium inserts at the NAEOTOM Alpha is comparable or better\nthan on the secondary predicate device SOMATOM Force."],["Quantum HD Cardiac","","","Quantitative assessment in terms of image noise and a visual assessment\nof the image quality in ECG gated acquisitions between different scan\nmodes is performed: standard acquisition mode with spectral and non-\nspectral reconstruction, ultra-high resolution acquisition mode with non-\nspectral reconstruction (120x0.2 mm and 96x0.2 mm) and spectral image\nreconstruction (limited to 96x0.2 mm).\nBased on the results it can be concluded that substantial equivalence in\nimage quality is achieved by the images derived from the spectral\ncapable cardiac acquisition mode 96x0.2mm for both, the high-\nresolution UHR and the standard resolution spectral image cases,\ncompared to the single source spectral capable 120x0.2mm UHR scan\nmode."],["HD FoV","","","Tests were performed to evaluate the performance of HD FoV on\nNAEOTOM Alpha.\nFor this purpose, the HU accuracy in the extended field of view region\nwas measured based on phantom studies. The phantom diameter\naccuracy has been also evaluated.\nBased on the results it can be concluded that HD FoV enables the\nreconstruction of images while significantly improving the visualization"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p27-t0","doc_id":"K233657","page_num":27,"bbox":[72.28,95.46,523.02,181.5],"n_rows":3,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","of anatomy in the regions outside the scan field of view of 50 cm. In the\nphantom study, an HU value accuracy of about ± 40 HU was achieved\nwith skin-line accuracy of about ± 3 mm."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p27-t1","doc_id":"K233657","page_num":27,"bbox":[72.28,237.96,509.97,761.22],"n_rows":8,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/19/2022","12-349","NEMA","","","PS 3.1 - 3.20 2022d","","","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set"],["07/06/2020","12-325","NEMA","","","XR 25-2019","","","Computed\nTomography Dose\nCheck"],["07/06/2020","12-330","NEMA","","","XR 28-2018","","","Supplemental\nRequirements for\nUser Information and\nSystem Function\nRelated to Dose in CT"],["12/23/2019","12-328","IEC","","","61223-3-5 Edition\n2.0 2019-09","","","Evaluation and\nroutine testing in\nmedical imaging\ndepartments - Part 3-\n5: Acceptance tests\nand constancy tests -\nImaging performance\nof computed\ntomography X-ray\nequipment [Including:\nTechnical\nCorrigendum 1\n(2006)]"],["03/14/2011","12-226","IEC","","","61223-2-6 Second\nEdition 2006-11","","","Evaluation and\nroutine testing in\nmedical imaging\ndepartments - Part 2-\n6: Constancy tests -\nImaging performance\nof computed\ntomography X-ray\nequipment"]],"caption_candidate":"Table 7: Recognized Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p28-t0","doc_id":"K233657","page_num":28,"bbox":[72.26,95.46,509.98,765.06],"n_rows":10,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["01/14/2014","12-269","IEC","","","60601-1-3 Edition\n2.1 2013-04","","","Medical electrical\nequipment - Part 1-3:\nGeneral requirements\nfor basic safety and\nessential performance\n– Collateral Standard:\nRadiation protection\nin diagnostic X-ray\nequipment"],["06/27/2016","12-302","IEC","","","60601-2-44 Edition\n3.2: 2016","","","Medical electrical\nequipment - Part 2-\n44: Particular\nrequirements for the\nbasic safety and\nessential performance\nof x-ray equipment\nfor computed\ntomography"],["12/23/2019","5-125","ANSI AAMI\nISO","","","14971: 2019","","","Medical devices -\nApplications of risk\nmanagement to\nmedical devices"],["","","ISO","","","14971 Third Edition\n2019-12","","","Medical devices -\nApplication of risk\nmanagement to\nmedical devices"],["01/14/2019","13-79","ANSI AAMI\nIEC","","","62304:2006/A1:2016","","","Medical device\nsoftware - Software\nlife cycle processes\n[Including\nAmendment 1 (2016)]"],["","","IEC","","","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","","","Medical device\nsoftware - Software\nlife cycle processes"],["07/09/2014","19-46","ANSI AAMI","","","ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012\n(Cons. Text) [Incl.\nAMD2:2021]","","","Medical electrical\nequipment - Part 1:\nGeneral requirements\nfor basic safety and\nessential performance\n(IEC 60601-1:2005,\nMOD) [Including\nAmendment 2 (2021)]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p29-t0","doc_id":"K233657","page_num":29,"bbox":[72.27,95.46,509.97,745.08],"n_rows":9,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["09/17/2018","19-36","ANSI AAMI\nIEC","","","60601-1-2:2014\n[Including AMD\n1:2021]","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral Standard:\nElectromagnetic\ndisturbances -\nRequirements and\ntests"],["","","IEC","","","60601-1-2 Edition\n4.1 2020-09\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral Standard:\nElectromagnetic\ndisturbances -\nRequirements and\ntests"],["12/23/2016","5-129","ANSI AAMI\nIEC","","","62366-\n1:2015+AMD1:2020\n(Consolidated Text)","","","Medical devices Part\n1: Application of\nusability engineering\nto medical devices,\nincluding Amendment\n1"],["","","IEC","","","62366-1 Edition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","Medical devices - Part\n1: Application of\nusability engineering\nto medical devices"],["07/09/2014","12-273","IEC","","","60825-1 Edition 2.0\n2007-03","","","Safety of laser\nproducts - Part 1:\nEquipment\nclassification, and\nrequirements"],["12/21/2020","5-132","IEC","","","60601-1-6 Edition\n3.2 2020-07\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-6:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral standard:\nUsability"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p30-t0","doc_id":"K233657","page_num":30,"bbox":[72.29,95.46,509.95,343.14],"n_rows":5,"n_cols":8,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard\nDesignation Number\nand Date","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard\nDesignation Number\nand Date","Title of Standard"],["","","","Developing","","","",""],["","","","Organization","","","",""],["12/23/2019","12-309","IEC","","","60601-2-28 Edition\n3.0 2017-06","","Medical electrical\nequipment - Part 2-\n28: Particular\nrequirements for the\nbasic safety and\nessential performance\nof X-ray tube\nassemblies for\nmedical diagnosis"],["12/20/2021","12-341","IEC","","","62563-1 Edition 1.2\n2021-07\nCONSOLIDATED\nVERSION","","Medical electrical\nequipment - Medical\nimage display systems\n- Part 1: Evaluation\nmethods"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p30-t1","doc_id":"K233657","page_num":30,"bbox":[72.29,386.14,523.04,654.72],"n_rows":6,"n_cols":6,"columns":["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],"rows":[["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],["","Developing","","","",""],["","Organization","","","",""],["IEC","","","60601-\n1:2005+A1:2012+A2:2020","Medical electrical\nequipment - part 1:\ngeneral requirements\nfor basic safety and\nessential performance","ANSI AAMI ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons.\nText) [Incl. AMD2:2021]"],["IEC/ISO","","","17050-1","Conformity Assessment\n– Supplier’s declaration\nof conformity – Part 1:\nGeneral requirements","Declaration of\nconformance to FDA\nrecognized consensus\nstandards."],["IEC/ISO","","","17050-2","Conformity assessment\n– Supplier’s declaration\nof conformity – Part 2:\nSupporting\ndocumentation.","General consensus\nstandards not currently\nrecognized by FDA."]],"caption_candidate":"Table 8: General Use Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p30-t2","doc_id":"K233657","page_num":30,"bbox":[72.29,697.77,523.04,764.46],"n_rows":3,"n_cols":4,"columns":["","FDA Guidance Document I","ssue date",""],"rows":[["","FDA Guidance Document I","ssue date",""],["User Fees and Refunds for Premarket Notification Submissions (510(k)s 1","","0/05/2022",""],["Refuse to Accept Policy for 510(k)s 0","","4/21/2022",""]],"caption_candidate":"Table 9: FDA Guidance Document and Effective Date","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233657-p31-t0","doc_id":"K233657","page_num":31,"bbox":[72.26,95.46,523.06,394.2],"n_rows":12,"n_cols":4,"columns":["","FDA Guidance Document I","ssue date",""],"rows":[["","FDA Guidance Document I","ssue date",""],["Electronic Submission Template for Medical Device 510(k) Submissions","","10/2/2023",""],["Deciding When to Submit a 510(k) for a Change to an Existing Device","","10/25/2017",""],["The 510(k) Program: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]","","07/28/2014",""],["Content of Premarket Submissions for Device Software Functions","","06/14/2023",""],["Off-The-Shelf Software Use in Medical Devices","","09/27/2019",""],["Applying Human Factors and Usability Engineering to Medical Devices","","02/03/2016",""],["Pediatric Information for X-ray Imaging Device Premarket Notifications","","11/28/2017",""],["Cybersecurity in Medical Devices: Quality System Considerations and Content\nof Premarket Submissions","","09/27/2023",""],["Electromagnetic Compatibility (EMC) of Medical Devices","","06/06/2022",""],["Design Considerations and Pre-market Submission Recommendations for\nInteroperable Medical Devices","","09/06/2017",""],["Appropriate Use of Voluntary Consensus Standards in Premarket Submissions\nfor Medical Devices","","09/14/2018",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p5-t0","doc_id":"K233673","page_num":5,"bbox":[131.42,466.75,514.06,696.94],"n_rows":6,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],["General","","",""],["Product\nCode","LNH","LNH","Same"],["Regulation\nNo.","21 CFR 892.1000","21 CFR 892.1000","Same"],["Class","II","II","Same"],["Indications\nFor Use","The uMR Jupiter system is\nindicated for use as a\nmagnetic resonance\ndiagnostic device (MRDD)\nthat produces sagittal,\ntransverse, coronal, and\noblique cross sectional\nimages, and spectroscopic\nimages, and that display\ninternal anatomical structure","The uMR Omega system is\nindicated for use as a\nmagnetic resonance\ndiagnostic device (MRDD)\nthat produces sagittal,\ntransverse, coronal, and\noblique cross sectional\nimages, and spectroscopic\nimages, and that display\ninternal anatomical structure","Note 1"]],"caption_candidate":"Table 1 Comparison of Hardware configuration","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p6-t0","doc_id":"K233673","page_num":6,"bbox":[131.42,78.86,514.06,705.48],"n_rows":17,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],["","and/or function of the head,\nbody and extremities.\nThese images and the\nphysical parameters derived\nfrom the images when\ninterpreted by a trained\nphysician yield information\nthat may assist the diagnosis.\nContrast agents may be used\ndepending on the region of\ninterest of the scan.\nThe device is intended for\npatients > 20 kg/44 lbs.","and/or function of the head,\nbody and extremities.\nThese images and the\nphysical parameters derived\nfrom the images when\ninterpreted by a trained\nphysician yield information\nthat may assist the diagnosis.\nContrast agents may be used\ndepending on the region of\ninterest of the scan.",""],["Magnet system","","",""],["Field\nStrength","5.0 Tesla","3.0 Tesla","Note 2"],["Type of\nMagnet","Superconducting","Superconducting","Same"],["Patient-\naccessible\nbore\ndimensions","60 cm","75 cm","Note 3"],["Type of\nShielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Magnet\nHomogeneit\ny","≤ 1.3 ppm @ 50cm DSV\n≤ 0.45 ppm @ 45cm DSV\n≤ 0.19 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.015 ppm @ 20cm DSV\n≤ 0.0009 ppm @ 10cm DSV","≤ 2.30 ppm @ 50cm DSV\n≤ 0.80 ppm @ 45cm DSV\n≤ 0.38 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.02 ppm @ 20cm DSV\n≤ 0.002 ppm @ 10cm DSV","Note 4"],["Gradient system","","",""],["Max\ngradient\namplitude","120 mT/m","45 mT/m","Note 5"],["Max slew\nrate","200 T/m/s","200 T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant\nfrequencies","210.794 MHz","128.23 MHz","Note 6"],["Number of\ntransmit\nchannels","8","2","Note 7"],["Amplifier\npeak power\nper channel","8 kW","18 kW or 20 kW",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p7-t0","doc_id":"K233673","page_num":7,"bbox":[132.58,78.86,514.06,533.59],"n_rows":14,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark"],["Number of\nreceive\nchannels","96","Up to 96","Note 8"],["RF Coils","","",""],["SuperFlex\nSmall-24","Yes","SuperFlex Small-12","Note 9"],["Tx/Rx Head\nCoil -48","Yes","Head Coil -32","Note 10"],["Tx/Rx Knee\nCoil - 24","Yes","Yes","Note 11"],["SuperFlex\nBody - 24","Yes","Yes",""],["Head &\nNeck Coil -\n48","Yes","Yes",""],["Spine Coil -\n48","Yes","Yes",""],["Patient table","","",""],["Dimensions","W×H×L: 640 mm×1025\nmm× 2620 mm","W×H×L: 640 mm×880 mm×\n2620 mm","Note 12"],["Maximum\nsupported\npatient\nweight","310 kg","310 kg","Same"],["Accessories","","",""],["Vital Signal\nGating","Support\nECG/Respiratory/Pulse\nsignal triggering the scan","Support\nECG/Respiratory/Pulse\nsignal triggering the scan","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p7-t1","doc_id":"K233673","page_num":7,"bbox":[132.58,574.9,510.31,709.39],"n_rows":7,"n_cols":6,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark","",""],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Omega","Remark","",""],["Imaging Features","","","","",""],["Non-uniformity Correction","Yes","Yes","","Same",""],["Distortion Correction","Yes","Yes","","Same",""],["Image Filter","Yes","Yes","","Same",""],["SWI (Susceptibility\nWeighted Imaging)","Yes","Yes","Same","",""],["PC (2D/3D Phase Contrast)","Yes","Yes","","Same",""]],"caption_candidate":"Table 2 Comparison of the Application Software Features","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p8-t0","doc_id":"K233673","page_num":8,"bbox":[113.18,40.2,482.38,703.68],"n_rows":83,"n_cols":5,"columns":["Shangh","ai United Imaging Healthcare Co., L","td.","",""],"rows":[["Shangh","ai United Imaging Healthcare Co., L","td.","",""],["Tel: +8","6 (21) 67076888 Fax：+86 (21)","67076889","",""],["www.un","ited-imaging.com","","",""],["","","","",""],["","GETI (Gradient Echo Train","","",""],["","","","",""],["","","Yes","Yes","Same"],["","Imaging)","","",""],["","ADC (Apparent Diffusion","","",""],["","","","",""],["","","Yes","Yes","Same"],["","Coefficient)","","",""],["","FACT (Fat Analysis and","","",""],["","","Yes","Yes","Same"],["","","","",""],["","Calculation Technique)","","",""],["","PSIR (Phase Sensitive","","",""],["","","","",""],["","","Yes","Yes","Same"],["","Inversion Recovery)","","",""],["","cDWI (Computed DWI)","Yes","Yes","Same"],["","Inline T1 Mapping","Yes","Yes","Same"],["","Inline T2* Mapping","Yes","Yes","Same"],["","Inline T2 Mapping using","","",""],["","","","",""],["","","Yes","Yes","Same"],["","SEME","","",""],["","Inline T2 Mapping using","","",""],["","","","",""],["","","Yes","No","Note"],["","MASS","","",""],["","SWI+ (Susceptibility","","",""],["","","Yes","Yes","Same"],["","","","",""],["","Weighted Imaging Plus)","","",""],["","3D ASL (Arterial Spin","","",""],["","","","",""],["","","Yes","Yes","Same"],["","Labeling)","","",""],["","2D Flow (2D Flow","","",""],["","","Yes","Yes","Same"],["","","","",""],["","Quantification)","","",""],["","CEST (3D Chemical","","",""],["","Exchange Saturation","Yes","Yes","Same"],["","Transfer)","","",""],["","","","",""],["","T1rho (T1rho Quantitative","","",""],["","","Yes","Yes","Same"],["","","","",""],["","Mapping Imaging)","","",""],["","","","",""],["","FSP+ (Fast Spoiled Gradien","t","",""],["","","Yes","Yes","Same"],["","","","",""],["","Echo Plus)","","",""],["","","","",""],["","CASS (Constructive","","",""],["","","","",""],["","","Yes","No","Note"],["","Acquisition of Steady State)","","",""],["","PASS (Pair-Echo","","",""],["","","","",""],["","","Yes","No","Note"],["","Acquisition of Steady State)","","",""],["","","","",""],["","SNAP (Simultaneous Non-","","",""],["","contrast Angiography and","Yes","Yes","Same"],["","Intraplaque Hemorrhage)","","",""],["","","","",""],["","MultiBand","Yes","Yes","Same"],["","","","",""],["","Function","","",""],["","Remote Assistance","Yes","Yes","Same"],["","Spectroscopy Sequence","s","",""],["","Brain MRS","Yes","Yes","Same"],["","Liver MRS","Yes","Yes","Same"],["","Prostate MRS","Yes","Yes","Same"],["","Workflow Features","","",""],["","MoCap-Monitoring (Motio","n","",""],["","","Yes","No","Note"],["","","","",""],["","Capture Monitoring)","","",""]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K233673-p9-t0","doc_id":"K233673","page_num":9,"bbox":[134.9,78.86,510.34,140.66],"n_rows":3,"n_cols":4,"columns":["Image Reconstruction Features","","",""],"rows":[["Image Reconstruction Features","","",""],["ACS (AI-assisted\nCompressed Sensing)","Yes","Yes","Same"],["uCS (united Compressed\nSensing)","Yes","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p9-t1","doc_id":"K233673","page_num":9,"bbox":[124.34,154.94,521.14,700.2],"n_rows":12,"n_cols":2,"columns":["Note 1","The proposed device includes enhancements to the software that controls\nSpecific Absorption Rate (SAR) based on simulations for human at least 20kg.\nTherefore, it is used for patient > 20 kg/44 lbs.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 1","The proposed device includes enhancements to the software that controls\nSpecific Absorption Rate (SAR) based on simulations for human at least 20kg.\nTherefore, it is used for patient > 20 kg/44 lbs.\nThe difference did not raise new safety and effectiveness concerns."],["Note 2","The static field strength of the proposed device is different from the predicate\ndevice, but the basic imaging characteristics are consistent.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","The patient-accessible bore dimension of the proposed device is smaller than that\nof the predicate device, which satisfies the clinical applications. The difference\ndid not raise new safety and effectiveness concerns."],["Note 4","Magnet Homogeneity of the proposed device is better than that of the predicate\ndevice. Magnet homogeneity contributes to image quality. The proposed device\nwith better magnet homogeneity is benefit for image quality.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","The max gradient amplitude of the proposed device is larger than that of the\npredicate device. Peripheral nerve stimulation and cardiac stimulation was\ncontrolled according to IEC 60601-2-33.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","The difference in the resonant frequencies of the proposed device and the\npredicate device is due to the difference in field strength.\nThe difference did not raise new safety and effectiveness concerns."],["Note 7","The transmit channel number of the proposed device is more than that of the\npredicate device. More transmit channels, better B1 uniformity. The local SAR\nwas monitored to ensure patients’ safety.\nThe difference did not raise new safety and effectiveness concerns."],["Note 8","The number of receive channels of proposed device is 96. The number of receive\nchannels of predicate device is 48 or 96. The number of receive channels of\nproposed device is the same as one configuration of uMR Omega.\nThe difference did not raise new safety and effectiveness concerns."],["Note 9","The intended use of SuperFlex Small-24 is equivalent to previously cleared\nSuperFlex Small-12. The difference between them is the number of channels of\nthe receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 10","The intended use of Tx/Rx Head Coil -48 is equivalent to previously cleared\nHead Coil -32. There are two differences between them. One is that Tx/Rx Head\nCoil -48 can be used as a transmitter coil and SAR is controlled. The other one\nis that the receiver channel number of Tx/Rx Head Coil -48 is more than that of\nHead Coil -32.\nThe difference did not raise new safety and effectiveness concerns."],["Note 11","These coils were modified to adapt the frequency of the proposed device.\nThe difference did not raise new safety and effectiveness concerns."],["Note 12","The height of the patient table of the proposed device is higher than that of the\npredicate device, which can satisfy clinical application.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"Sensing)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p10-t0","doc_id":"K233673","page_num":10,"bbox":[124.34,78.86,521.14,274.01],"n_rows":4,"n_cols":2,"columns":["Note 13","MASS is substantially equivalent to GRE and acquires three different types\n(lower order SSFP_FID, SSFP_SE and higher order SSFP_FID) of echo images\nand achieves T2 mapping image by an iteration and search method.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 13","MASS is substantially equivalent to GRE and acquires three different types\n(lower order SSFP_FID, SSFP_SE and higher order SSFP_FID) of echo images\nand achieves T2 mapping image by an iteration and search method.\nThe difference did not raise new safety and effectiveness concerns."],["Note 14","CASS is substantially equivalent to BSSFP and acquires two different phase\ncycling angle images and combines them by MIP operation to reduce dark band\nartifacts.\nThe difference did not raise new safety and effectiveness concerns."],["Note 15","PASS is substantially equivalent to GRE and acquires two different type\n(SSFP_FID and SSFP_SE) of echo image and combines them to achieve hybrid\ncontrast image.\nThe difference did not raise new safety and effectiveness concerns."],["Note 16","MoCap-Monitoring is a motion monitoring module which is periodic and is\ninserted into a pulse sequence. It can realize real-time motion monitoring in\nimaging scanning and provides an alert when motion occurs.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233673-p13-t0","doc_id":"K233673","page_num":13,"bbox":[124.34,276.29,521.14,452.35],"n_rows":14,"n_cols":2,"columns":["Gender",""],"rows":[["Gender",""],["Male","15"],["Female","10"],["Age",""],["18-28","5"],["29-40","7"],[">41","13"],["Ethnicity",""],["White","4"],["Asian","21"],["Body Mass Index (BMI)",""],["Underweight (<18.5)","2"],["Healthy weight (18.5-24.9)","18"],["Overweight and obesity (>24.9)","5"]],"caption_candidate":"Table 6 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233677-p5-t0","doc_id":"K233677","page_num":5,"bbox":[84.62,344.59,545.38,434.76],"n_rows":6,"n_cols":6,"columns":["","","SOMATOM go.All","","Biograph Horizon","MI View &Go"],"rows":[["","","SOMATOM go.All","","Biograph Horizon","MI View &Go"],["","","and go.Top","","",""],["Manufacturer:","Siemens Medical Solutions USA, Inc.","","","",""],["Product Code:","JAK","","","KPS","QIH"],["Device Class:","Class II","","","",""],["510(k) Number:","K211373","","","K193178","K222172"]],"caption_candidate":"Reference Predicate Devices:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K233687-p7-t0","doc_id":"K233687","page_num":7,"bbox":[172.15,169.7,575.41,391.13],"n_rows":18,"n_cols":8,"columns":["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],"rows":[["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],["","","ECHELON SYNERGY MRI SYSTEM\n(K223426)","ECHELON Synergy V10.0","","","",""],["Standards Met","","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5, MS\n8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5,\nMS 8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","","","",""],["Type and Field Strength","","Super-conducting magnet, horizontal bore,\n1.5 Tesla","Super-conducting magnet, horizontal\nbore, 1.5 Tesla","","","",""],["Resonant Frequency","","63.86MHz","63.86MHz","","","",""],["Bore dimension","","Circle shape with diameter 70cm","Circle shape with diameter 70cm","","","",""],["Gradient Strength","","33mT/m","33mT/m","","","",""],["Slew Rate","","130 T/m/sec","130 T/m/sec","","","",""],["Rise Time","","254μsec to 33mT/m","254μsec to 33mT/m","","","",""],["","","","","","","",""],["Audible Noise (MCAN)","","","","","","",""],["Ambient","","59.9 dBA","59.9 dBA","","","",""],["Lpeak","","122.7 dBA","122.7 dBA","","","",""],["Leq","","116.5 dBA","116.5 dBA","","","",""],["Transmitter channels","","1","1","","","",""],["Peak Envelop Power","","18 kW","18 kW","","","",""],["Duty Cycle","","85% (Gating max), 10% at full power","85% (Gating max), 10% at full power","","","",""],["RF receiver channel","","32","32","","","",""]],"caption_candidate":"Table 2 Comparison: Hardware","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p7-t1","doc_id":"K233687","page_num":7,"bbox":[172.15,534.07,446.95,569.95],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"Summary is changed but there are no significant changes in technology, engineering and performance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p8-t0","doc_id":"K233687","page_num":8,"bbox":[163.82,116.78,502.3,305.38],"n_rows":13,"n_cols":3,"columns":["","PREDICATE DEVICE","SUBJECT DEVICE"],"rows":[["","PREDICATE DEVICE","SUBJECT DEVICE"],["","ECHELON SYNERGY MRI SYSTEM\n(K223426)","ECHELON Synergy V10.0"],["Transmit Coil","T/R Body","T/R Body"],["Receiver Coils","FlexFit Neuro Coil","FlexFit Neuro Coil"],["","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B"],["","Extremity Coil","Extremity Coil"],["","Hand/Wrist Coil","Hand/Wrist Coil"],["","Breast Coil\nBreast Support Kit 2","Breast Coil\nBreast Support Kit 2"],["","Micro Coil A,\nMicro Coil B","Micro Coil A,\nMicro Coil B"],["","Shoulder Coil","Shoulder Coil"],["","Spine Coil","Spine Coil"],["","Foot/Ankle Coil","Foot/Ankle Coil"],["","Flex M Coil, Flex S Coil","Flex M Coil, Flex S Coil"]],"caption_candidate":"Table 4 Comparison: RF Coils","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p8-t1","doc_id":"K233687","page_num":8,"bbox":[169.94,448.63,446.95,484.51],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p9-t0","doc_id":"K233687","page_num":9,"bbox":[102.62,120.06,580.66,564.3],"n_rows":40,"n_cols":9,"columns":["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],"rows":[["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],["","Operating System","","","None","","","No",""],["","CPU Platform","","","None","","","No",""],["","Application Software","","","Going from V9.0A to V10.0A","","","See Table 7",""],["Scan Tasks","Scan Tasks","","","Following function is updated.","","See Table 7","See Table 7",""],["","","","","- Auto Voice","","","",""],["","","","","Following positioning applications are added.","","","",""],["","","","","- AutoPose Breast, AutoPose HipJoint","","","",""],["","","","","Following positioning application is updated.","","","",""],["","","","","- AutoPose Spine","","","",""],["","","","","Following function is added.","","","",""],["","","","","- Series Save","","","",""],["","2D Processing Tasks","","","None","","","No",""],["","3D Processing Tasks","","","None","","","No",""],["","Analysis Tasks","","","None","","","No",""],["","Maintenance Tasks","","","None","","","No",""],["","Viewport Tools","","","None","","","No",""],["","Film, Archive Tools","","","None","","","No",""],["Network Tools","Network Tools","","","Following Network Tools are added.","","See Table 7","See Table 7",""],["","","","","- AutoProtocol","","","",""],["Protocol Enhancements","","","","Following function is updated.","","See Table 7","",""],["","","","","- Delayed Enhancement Imaging","","","",""],["","","","","- Navi slice positioning","","","",""],["","","","","- BeamNavi","","","",""],["","","","","Following variation of Protocol Enhancements are added in Auto Table Centering.","","","",""],["","","","","- Chest, Breast, General Abdomen, Liver/Kidney, Pelvis, WholeBody","","","",""],["","","","","Following Protocol Enhancements are added.","","","",""],["","","","","- Navigated StillShot","","","",""],["","","","","- Visual StillShot","","","",""],["","","","","- MROC","","","",""],["","","","","- IQ Retouch","","","",""],["","","","","- Exp.RAPID","","","",""],["","","","","- DWI HD","","","",""],["","","","","- DLR Clear","","","",""],["","","","","2D RADAR sequence is added to the applicable sequence of DLR Rise.","","","",""],["","","","","3D sequences and 2D RADAR are added to the applicable sequence of IterativeRAPID.","","","",""],["","","","","VASC-FSE is modified.","","","",""],["","Pulse Sequences","","","None","","","",""],["Monitoring Tools","Monitoring Tools","","","Following function is added.","","","",""],["","","","","- Synergy Vision","","","",""]],"caption_candidate":"Table 6 Comparison: Functionality","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p10-t0","doc_id":"K233687","page_num":10,"bbox":[169.94,367.61,446.95,403.37],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐Technology"],["☐Engineering","☐Materials","☐Others"]],"caption_candidate":"Application software is changed in V10.0A.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233687-p13-t0","doc_id":"K233687","page_num":13,"bbox":[158.36,511.82,525.94,582.51],"n_rows":6,"n_cols":4,"columns":["","Spine","Breast","HipJoint"],"rows":[["","Spine","Breast","HipJoint"],["Data acquisition site","FUJIFILM Healthcare Corporation and clinical site","",""],["Subject type","Healthy volunte er and patients","",""],["","177","66","65"],["Number of cases","","",""],["","","",""]],"caption_candidate":"positioning. The information on the data in the above evaluations is shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233698-p5-t0","doc_id":"K233698","page_num":5,"bbox":[72.29,621.04,539.76,702.36],"n_rows":4,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","Revolution Ascend","","","True Enhance DL",""],["","","(K213938)","","","on Revolution Ascend",""],["Patient Population","Patients of all ages","","","Same","",""]],"caption_candidate":"device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233698-p6-t0","doc_id":"K233698","page_num":6,"bbox":[72.26,120.87,539.79,539.68],"n_rows":7,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","Revolution Ascend","","","True Enhance DL",""],["","","(K213938)","","","on Revolution Ascend",""],["Clinical Workflow","The Revolution Ascend User\nInterface allows for\nmodifications of image\nreconstruction settings (FBP,\nASiR-V, and other parameters)\nbased on users desired image\ndisplay and workflow set up.","","","Same","",""],["Supported kVps","80, 100, 120, 140","","","120","",""],["Supported Recon Kernels","- Standard\n- Soft\n- Detail\n- Bone, Bone plus\n- Chest\n- Lung\n- Ultra\n- Edge, Edge plus","","","- Standard\n- Soft\n- Detail","",""],["Image Reconstruction","- Filtered back Projection\n- ASiR-V\n- Deep Learning Image\nReconstruction, DLIR\n(K230807)","","","- Filtered back Projection\n- ASiR-V","",""]],"caption_candidate":"True Enhance DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233728-p5-t0","doc_id":"K233728","page_num":5,"bbox":[72.0,153.72,539.76,611.28],"n_rows":10,"n_cols":2,"columns":["Date","January 19, 2024"],"rows":[["Date","January 19, 2024"],["Submitter","GE Healthcare (Tianjin) Company Limited\nNo. 266 Jingsan Road, Tianjin Airport Economic Area\nTianjin, P.R. China 300308"],["Primary\nContact Person","Xinyu Song\nLead Specialist, Regulatory Affairs, MR\nGE HealthCare\nPhone: +86 186 1188 4503\nE-mail: Xinyu.Song@ge.com"],["Secondary\nContact Person","Glen Sabin\nDirector - Regulatory Affairs, MR Strategy\nGE HealthCare\nPhone: 262 894-4968\nE-mail: glen.sabin@ge.com"],["Device Trade\nName","SIGNATM Champion"],["Common/Usual\nName","Magnetic Resonance Diagnostic Device"],["Classification\nNames","Magnetic Resonance Diagnostic Device per 21 CFR 892.1000"],["Product Code","LNH, LNI"],["Predicate\nDevice","SIGNATM Voyager (K192426)"],["Reference\nDevice","(1) SIGNATM Victor (K223439)\n(2) SIGNATM Hero (K213668)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233728-p7-t0","doc_id":"K233728","page_num":7,"bbox":[99.03,440.04,539.73,607.32],"n_rows":5,"n_cols":8,"columns":["Subsystem or\nComponent","","Predicate Device","","","Proposed Device","","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","","Proposed Device","","Comments"],["","","SIGNATM Voyager","","","SIGNATM Champion","",""],["","","(K192426)","","","(K233728)","",""],["Magnet","1.5T Superconducting Magnet with active\nshielding","","","","","","SIGNATM Champion uses the\nsame magnet as the\npredicate SIGNATM Voyager,\nwith a modified enclosure\ndesign."],["Gradient\nSubsystem","Water cooled gradient coil with active\ns hielding.","","","","","","SIGNATM Champion uses the\nsame gradient subsystem as\nthe predicate SIGNATM\nVoyager."]],"caption_candidate":"predicate device, as summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233728-p8-t0","doc_id":"K233728","page_num":8,"bbox":[99.02,72.36,539.74,683.64],"n_rows":8,"n_cols":8,"columns":["Subsystem or\nComponent","","Predicate Device","","","Proposed Device","","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","","Proposed Device","","Comments"],["","","SIGNATM Voyager","","","SIGNATM Champion","",""],["","","(K192426)","","","(K233728)","",""],["RF Transmit\nSubsystem","Transmit with integrated body coil and local\nT/R coil.","","","","","","SIGNATM Champion uses the\nsame integrated body coil as\nthe predicate SIGNATM\nVoyager, but other\ncomponents in the transmit\nchain are different. The\nSIGNATM Champion uses the\nIn Scan Room transmit\narchitecture found in\nReference Device 1 (SIGNATM\nVictor)."],["RF Receive\nSubsystem","Digitize-Per-Pin (DPP) receive chain\narchitecture.","","","","","","SIGNATM Champion uses the\nsame DPP architecture as\nthe predicate SIGNATM\nVoyager."],["RF Coils","Comprehensive suite of detachable coils for\nimaging all anatomies","","","","","","Coils used by SIGNATM\nChampion are also used by\nthe predicate SIGNATM\nVoyager and/or Reference\nDevice 1 (SIGNATM Victor)."],["Software\nFeatures","Comprehensive suite of software features,\npulse sequences, and image processing\napplications to support MR imaging of all\na natomies.","","","","","","Both SIGNATM Champion and\nthe predicate SIGNATM\nVoyager are fully capable MR\nsystems with a wide range of\nsoftware features. SIGNATM\nChampion includes some\nnew and enhanced features\nsuch as AIR Recon DL and\nSonic DL that were not\nincluded in the predicate\nK192426 submission. The\nSIGNATM Champion software\nfeatures are similar to those\nfound on Reference Device 2\n(SIGNATM Hero)."],["Gating\nAccessories","Respiratory,\nperipheral, and\ncardiac gating.","","","Respiratory\nperipheral and\ncardiac gating with\nwireless connection\noption.","","","In addition to SIGNATM\nVoyager’s gating solution,\nSIGNATM Champion offers an\nadditional option to use\nwireless connection."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p4-t0","doc_id":"K233731","page_num":4,"bbox":[108.24,164.76,539.76,661.68],"n_rows":7,"n_cols":2,"columns":["Date:","July 31, 2024"],"rows":[["Date:","July 31, 2024"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact Person:","Peter Uhlir\nRegulatory Affairs Program Manager\nGE HealthCare\nTel: (+36) 70-436-9317\nEmail: peter.uhlir@ge.com"],["Secondary Contact Person:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE HealthCare\nTel: 262-424-7774\nEmail: Elizabeth.Mathew@ge.com"],["Device Trade Name:","CardIQ Suite"],["Common/Usual Name:","System, X-Ray, Tomography, Computed"],["Primary Classification name:\nPrimary Regulation Number:\nPrimary Product Code:\nSecondary Product Code:\nClassification:","Computed tomography x-ray system\n21 CFR 892.1750\nJAK\nQIH\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p5-t0","doc_id":"K233731","page_num":5,"bbox":[108.24,101.16,539.76,505.92],"n_rows":2,"n_cols":2,"columns":["Primary Predicate Device\nDevice name:\nCommon/Usual Name:\nManufacturer:\n510(k) number:\nClassification Name:\nRegulation Number:\nProduct Code:\nClassification:","CardIQ Suite\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems SCS\nK213725\nComputed tomography x-ray system\n21 CFR 892.1750\nJAK\nClass II"],"rows":[["Primary Predicate Device\nDevice name:\nCommon/Usual Name:\nManufacturer:\n510(k) number:\nClassification Name:\nRegulation Number:\nProduct Code:\nClassification:","CardIQ Suite\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems SCS\nK213725\nComputed tomography x-ray system\n21 CFR 892.1750\nJAK\nClass II"],["Reference Device\nDevice name:\nCommon/Usual Name\nManufacturer:\n510(k) number:\nClassification Name:\nRegulation Number:\nProduct Code:\nClassification:","CardIQ Xpress 2.0\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems SCS\nK073138\nComputed tomography x-ray system\n21 CFR 892.1750\nJAK\nClass II"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p7-t0","doc_id":"K233731","page_num":7,"bbox":[65.44,101.34,561.56,708.36],"n_rows":8,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite (K213725)","",""],["","","",""],["Input Data for\nCalcium\nScoring","Image Requirements:\n* 120kVp\n* Gated cardiac\nacquisition\n* DFOV - 24 cm - 26 cm\n* Slice thickness ≤ 3mm\n* Non-contrast","Image Requirements:\n* 120kVp\n* Gated cardiac\nacquisition\n* DFOV - 24 cm - 35 cm\n* Slice thickness ≤ 3mm\n* Non-contrast","Substantially equivalent.\nThe only modification in the subject\ndevice comes from the DFOV limitation\nthat has been adjusted to be less\nrestrictive."],["Segmentation\nand labeling\ncalcific regions\nin the\ncoronaries","Yes,\nAutomated using deep\nlearning algorithm","Yes,\nAutomated using deep\nlearning algorithm","Identical"],["Manual\nSegmentation\nand labeling of\ncalcific regions","Yes","Yes","Identical"],["Labeling of\ncalcifications","The software provides\nthe following labels for\nthe coronary arteries\naccording to regional\nterritories.\n• LAD territory: Left\nMain Artery (LMA),\nRamus Intermedius\nBranch (RIB), Left\nAnterior Descending\n(LAD) and all Diagonal\nbranches.\n• LCX territory: Left\nCircumflex artery (LCX)\nand all Obtuse marginal\nbranches.\n• RCA territory: Right\nCoronary Artery (RCA),\nPosterior Descending\nArtery (PDA) and","The software provides\nthe following labels for\nthe coronary arteries\naccording to regional\nterritories.\n• LAD territory: Left\nMain Artery (LMA),\nRamus Intermedius\nBranch (RIB), Left\nAnterior Descending\n(LAD) and all Diagonal\nbranches.\n• LCX territory: Left\nCircumflex artery (LCX)\nand all Obtuse marginal\nbranches.\n• RCA territory: Right\nCoronary Artery (RCA),\nPosterior Descending\nArtery (PDA) and","Identical"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p8-t0","doc_id":"K233731","page_num":8,"bbox":[65.45,101.34,561.55,291.36],"n_rows":7,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite (K213725)","",""],["","","",""],["","Posterior Lateral Branch\n(PLB).","Posterior Lateral Branch\n(PLB).",""],["Computation\nof Agatston\nscore","Yes","Yes","Identical"],["Calcium Score\n– Volume\nScoring\nMethod","Yes,\nVolume and Adaptive\nVolume","Yes,\nVolume and Adaptive\nVolume","Identical"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p9-t0","doc_id":"K233731","page_num":9,"bbox":[65.48,101.34,561.52,648.48],"n_rows":5,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite (K213725)","",""],["","","",""],["Cardiac\nReview","Coronary 2D Review is\nintended to assist\nreaders in the review of\ncoronary artery imaging.\nWithin this review step,\nreaders will find tools\naligned with a 2D\ncoronary artery CTA\nreview as well as\ngeneral overview of all\nreconstructions\nacquired within a study\nsuch a multi-phase cine\nacquisitions or delayed\nenhancement imaging.\nIt provides various\nreview tools:\n* Multi oblique tools to\ngenerate chamber,\nvessel or lesion views\nin any desired\norientations\n* Cine mode to view\nmulti-phase data in\nmotion\n* 2D distance, ROI\n* Rendering\nNote: A segmented 3D\nVolume Rendering\nmodel of the heart is not\navailable.","Coronary 2D Review is\nrenamed as ‘MPR\nCardiac Review’ and has\nthe same intended\npurpose as the\npredicate device which\nis intended to assist\nreaders in the review of\ncoronary artery imaging.\nWithin this review step,\nreaders will find tools\naligned with a 2D\ncoronary artery CTA\nreview, a segmented 3D\nVolume Rendering\nmodel of the heart\n(NEW), as well as\ngeneral overview of all\nreconstructions\nacquired within a study\nsuch a multi-phase cine\nacquisitions or delayed\nenhancement imaging.\nIt provides various\nreview tools:\n* Multi oblique tools to\ngenerate chamber,\nvessel or lesion views\nin any desired\norientations\n* Cine mode to view\nmulti-phase data in\nmotion\n* 2D distance, ROI\n* Rendering","Substantially equivalent.\nThe only difference in the subject device\nis the introduction of a new deep\nlearning algorithm to automatically\nsegment heart and provide a segmented\n3D Volume Rendering model of the\nheart. The functionality to segment heart\nin 3D already exists in the reference\ndevice CardIQ Xpress 2.0 (K073138). The\nreference device uses mathematical\nmorphology operations and Hounsfield\nUnit based thresholds to segment the\nheart in 3D. In the subject device, a fully\nconvolutional neural network trained\nand validated on annotated CT images is\nused to segment the heart.\nFrom the user perspective the output of\nthe segmentation, the editing capability\nand workflow remains the same\nbetween the subject device and\nreference device. The main reason to\nincorporate the deep learning algorithm\nis to improve the workflow efficiency."]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p10-t0","doc_id":"K233731","page_num":10,"bbox":[65.46,101.34,561.54,710.28],"n_rows":6,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite (K213725)","",""],["","","",""],["Data Export","CardIQ Suite provides a\nvariety of methods for\nsharing the results with\nclinical partners.\n* Calcium Score results\nand scored images can\nbe saved as DICOM SR\nseries and networked to\nDICOM destinations for\nstructured reporting\npurposes.\n* Copy individual\nimages or the results\ntable to paste into\npersonalized\ncommunications.\n* Screen capture\nindividual images and\nresults to save data\npertinent to the patient\nfile for selective\narchiving needs.\n* Generate file for\nimporting into\ncustomized report\ntemplates or research\nfile management needs\n* Export selected Images","CardIQ Suite provides a\nvariety of methods for\nsharing the results with\nclinical partners.\n* Calcium Score results\nand scored images can\nbe saved as DICOM SR\nseries and networked to\nDICOM destinations for\nstructured reporting\npurposes.\n* Copy individual\nimages or the results\ntable to paste into\npersonalized\ncommunications.\n* Screen capture\nindividual images and\nresults to save data\npertinent to the patient\nfile for selective\narchiving needs.\n* Generate file for\nimporting into\ncustomized report\ntemplates or research\nfile management needs\n* Export selected Images","Identical"],["Coronary\nReview step","No","Yes","Substantial Equivalent\nDeep-Learning Algorithms are\nincorporated in the subject device to\nautomatically segment coronary,\nautomatically track and label coronary\ncenterline in order to improve workflow\nefficiency. The same functionalities\nalready exist in the reference device\nCardIQ Xpress 2.0 (K073138), the\ndifference is in how the functionality is"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233731-p11-t0","doc_id":"K233731","page_num":11,"bbox":[65.48,101.34,561.52,712.68],"n_rows":5,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite (K213725)","",""],["","","",""],["","","","implemented in the devices. For the\nCoronary tree segmentation, the\nreference device, CardIQ Xpress 2.0\n(K073138) utilizes signal processing\nmethods to achieve coronary\nsegmentation, whereas in the subject\ndevice a deep-learning based algorithm\nis implemented to perform the same\nfunction.\nFor the Coronary centerline tracking, the\nreference device CardIQ Xpress 2.0\nutilizes mathematical morphology,\nleveraging on hessian filters and ray\ntracing to provide the coronary\ncenterline tracking, whereas in the\nsubject device a deep-learning based\nalgorithm is implemented to perform the\nsame function. The prerequisite for this\nalgorithm is that the Coronary tree\nsegmentation must be performed.\nFor the Coronary labeling, the reference\ndevice CardIQ Xpress 2.0 utilizes a rules-\nbased algorithm, based on the\nknowledge of the anatomy of the\ncoronaries, whereas in the subject\ndevice a deep-learning based algorithm\nis implemented to perform the same\nfunction. The prerequisite for this\nalgorithm is that the Coronary tree\nsegmentation and Coronary centerline\ntracking must be performed.\nFrom the user perspective the output of\nthe coronary segmentation, tracking and\nlabeling, the editing capability for\ncoronary segmentation, tracking and\nlabeling and the workflow remains the\nsame between the subject device and\nreference device. The main reason to\nincorporate the deep learning algorithms\nis to improve the workflow efficiency."]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233749-p6-t0","doc_id":"K233749","page_num":6,"bbox":[72.31,379.75,539.83,703.44],"n_rows":3,"n_cols":7,"columns":["Subsystem","","Revolution Ascend","","","Revolution Ascend Sliding",""],"rows":[["Subsystem","","Revolution Ascend","","","Revolution Ascend Sliding",""],["","","(Predicate Device, K213938)","","","(Proposed Device)",""],["Gantry","Revolution Ascend Gantry\n- Bore size: 75cm\n- Physical Tilt\nPerformix 40 Plus X-Ray Tube\n- Supports 40 mm beamwidth\n- Liquid Metal rotor bearing\nJEDI60DC High Voltage Generator\n- Peak Power: 72 kW\n-55 kW option (software limit\non mA)\nNGX Collimator (75cm bore)\n- 40 mm max z-coverage\nMerc40H Detector\n- Backlit Diode technology\n- Chiclet Module design\n- GE low noise ASIC technology\nused for signal conversion","","","Revolution Ascend Sliding Gantry\n- Bore size: 75cm\n- Physical Tilt: Disabled\nPerformix 40 Plus X-Ray Tube\n- Supports 40 mm beam width\n- Liquid Metal rotor bearing\nJEDI60DC High Voltage Generator\n- Peak Power: 72 kW\nNGX Collimator (75cm bore)\n- 40 mm max z-coverage\nMerc40H Detector\n- Backlit Diode technology\n- Chiclet Module design\n- GE low noise ASIC technology used\nfor signal conversion","",""]],"caption_candidate":"device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233749-p7-t0","doc_id":"K233749","page_num":7,"bbox":[72.26,77.54,539.88,436.63],"n_rows":4,"n_cols":3,"columns":["Patient Support","- VT1700v Table\n- Lite Table\n- Table accessories","Patient Support equipment is stationary in\nthe horizontal axis, Gantry moves\nhorizontally with rails system."],"rows":[["Patient Support","- VT1700v Table\n- Lite Table\n- Table accessories","Patient Support equipment is stationary in\nthe horizontal axis, Gantry moves\nhorizontally with rails system."],["Horizontal\nmovement","The patient table moves horizontally\nto the gantry bore during a CT exam\nwhile the gantry is stationary","The gantry mounted on a transporter\nmoves horizontally on rails towards the\npatient who is positioned on a patient\nsupport device that is stationary. The\ntransporter uses substantial design and\nmanufacturing process as the reference\ndevice cleared in K091673."],["Reconstruction","FBP\nASIR-V (K133640)\nDLIR cleared with Revolution Ascend\n(K212067, K230807).","Same"],["Standards","IEC 60601-1 Ed. 3.1\nIEC 60601-1-2 Ed 4.0\nIEC 60601-1-3 Ed 2.1\nIEC 60601-2-28 Ed 3.0\nIEC 60601-2-44 Ed. 3.2\nIEC 61223-3-5 Ed. 2.0\nNEMA XR-25\nNEMA XR-26\nNEMA XR-28","IEC 60601-1 Ed. 3.2\nIEC 60601-1-2 Ed 4.0\nIEC 60601-1-3 Ed 2.2\nIEC 60601-2-28 Ed 3.0\nIEC 60601-2-44 Ed. 3.2\nIEC 61223-3-5 Ed. 2.0\nNEMA XR-25\nNEMA XR-26\nNEMA XR-28"]],"caption_candidate":"Revolution Ascend Sliding","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p7-t0","doc_id":"K233753","page_num":7,"bbox":[49.52,314.03,589.54,717.12],"n_rows":8,"n_cols":8,"columns":["Feature","","Subject Device","","","Predicate Device","","Comparison\nResults"],"rows":[["Feature","","Subject Device","","","Predicate Device","","Comparison\nResults"],["","","AI-Rad Companion (Pulmonary)","","","AI-Rad Companion (Pulmonary)","",""],["","","VA40","","","(K213713)","",""],["Modality","CT","","","CT","","","Identical"],["Segmentation of\nlungs","Creation of a lung segmentation\nmask by combining the\nsegmentation masks of 5 lung\nlobes.","","","Creation of a lung segmentation\nmask by combining the\nsegmentation masks of 5 lung\nlobes.","","","Identical"],["Segmentation of\nlung lobes","Computation of segmentation\nmasks of the five lung lobes (right\nupper (RUL), right middle (RML),\nright lower (RLL), left upper (LUL)\nand left lower (LLL) lobe) for a\ngiven CT data set of the chest.","","","Computation of segmentation\nmasks of the five lung lobes (right\nupper (RUL), right middle (RML),\nright lower (RLL), left upper (LUL)\nand left lower (LLL) lobe) for a\ngiven CT data set of the chest.","","","Identical"],["Parenchyma\nevaluation","The parenchyma evaluation uses\nthe lobe mask, counts all voxels per\nlobe, counts image voxels below -\n950 HU, and calculates the\npercentages of these voxels relative\nto the total number of voxels.\nAdditionally, it sums the individual\nlobe results and calculates the\npercentage for the complete lung.","","","The parenchyma evaluation uses\nthe lobe mask, counts all voxels per\nlobe, counts image voxels below -\n950 HU, and calculates the\npercentages of these voxels relative\nto the total number of voxels.\nAdditionally, it sums the individual\nlobe results and calculates the\npercentage for the complete lung.","","","Identical"],["Parenchyma\nRanges","The percentages are likewise\ndedicated to the 4 ranges. Name of\nranges and their ranges are\nconfigurable by the user.","","","The percentages are likewise\ndedicated to the 4 ranges. Name of\nranges and their ranges are\nconfigurable by the user.","","","Identical"]],"caption_candidate":"following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p8-t0","doc_id":"K233753","page_num":8,"bbox":[49.5,72.72,589.56,626.14],"n_rows":7,"n_cols":4,"columns":["Pulmonary\nDensity","AI‐based identification of areas\nwith elevated Hounsfield values.\nThreshold‐based identification of\nhighest elevated Hounsfield values\ninside these elevated regions, by a\npredefined threshold of ‐200 HU","AI‐based identification of areas\nwith elevated Hounsfield values.\nThreshold‐based identification of\nhighest elevated Hounsfield values\ninside these elevated regions, by a\npredefined threshold of ‐200 HU","Identical"],"rows":[["Pulmonary\nDensity","AI‐based identification of areas\nwith elevated Hounsfield values.\nThreshold‐based identification of\nhighest elevated Hounsfield values\ninside these elevated regions, by a\npredefined threshold of ‐200 HU","AI‐based identification of areas\nwith elevated Hounsfield values.\nThreshold‐based identification of\nhighest elevated Hounsfield values\ninside these elevated regions, by a\npredefined threshold of ‐200 HU","Identical"],["Visualization of\nsegmentation\nand parenchyma\nresults","Color overlay of MPR and VRT\nwith evaluation results","Color overlay of MPR and VRT\nwith evaluation results","Identical"],["Interface to\nLungCAD","Interface to syngo.CT LungCAD","Interface to syngo.CT LungCAD","Identical"],["Lesion\nsegmentation","Segmentation of solid and sub-solid\nlung lesions including the following\ndata:\n• Relative change of\nmaximum 2D diameter [%]\n• relative change of\nmaximum orthogonal 2D\ndiameter [%]\n• relative change of mean 2D\ndiameter [%],\n• relative change of\nmaximum 3D diameter [%]\n• Relative change of volume\n(volume doubling time [d],\nnegative growth [%])","Segmentation of lung lesions\nincluding the following data:\n• Relative change of\nmaximum 2D diameter [%]\n• relative change of\nmaximum orthogonal 2D\ndiameter [%]\n• relative change of mean 2D\ndiameter [%],\n• relative change of\nmaximum 3D diameter [%]\n• Relative change of volume\n(volume doubling time [d],\nnegative growth [%])","Enhanced –\naddition of\nsub-solid\nlesion\nsegmentation"],["Visualization of\nlesion\nsegmentation\nresults","Color overlay of MPR and VRT\nwith evaluation","Color overlay of MPR and VRT\nwith evaluation","Identical"],["Lesion follow-\nup","Correlation of segmented lung\nlesions with known priors using the\ndata from the lesion segmentation.","Correlation of segmented lung\nlesions with known priors using the\ndata from the lesion segmentation.","Identical"],["Deployment","Cloud and Edge (on-premise)\ndeployments","Cloud and Edge (on-premise)\ndeployments","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p9-t0","doc_id":"K233753","page_num":9,"bbox":[72.26,162.2,539.79,454.9],"n_rows":8,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-129","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","62366-1:\n2020-06","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to medical\ndevices","14971 Third\nEdition 2019-\n12","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","62304 Edition\n1.1 2015-06\nConsolidated","","","IEC","",""],["12-349","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n2022d","","","NEMA","",""],["5-134","Radiology","Medical devices – symbols to\nbe used with information to be\nsupplied by the manufacturer","15223-1\nFourth\nEdition 2021-\n07","","","ISO","",""]],"caption_candidate":"voluntary FDA recognized Consensus Standards listed in Table 1 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p10-t0","doc_id":"K233753","page_num":10,"bbox":[72.27,280.55,539.78,554.62],"n_rows":6,"n_cols":6,"columns":["","Validation Type","","","Target",""],"rows":[["","Validation Type","","","Target",""],["Failure Rate","","","< 1%","",""],["Accuracy for Solid & Calcified\nnodules","","","Average DICE ≥ predicate\nBias & RMSE ≤ predicate\nLoA in line with predicate LoA","",""],["Accuracy for sub-solid nodules","","","Performance was analyzed in relation to the predicate’s\nsolid nodule segmentation performance\nMedian nodule size range for sub-solid is 10mm-20mm\nLoA for 10mm-20mm ≥ 95% for all three diameter\nmetrics","",""],["DICE score","","","Average DICE score for sub-solid nodules ≥ average\nDICE for predicate solid nodules","",""],["Consistency of Subgroup results","","","Average DICE not smaller than DICE of overall cohort\nminus 1 STD\nBias of three metrics not exceed ±1 STD\nRMSE of three metrics not exceed RMSE of overall\ncohort +1 STD each","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p10-t1","doc_id":"K233753","page_num":10,"bbox":[72.27,622.9,539.78,704.82],"n_rows":2,"n_cols":6,"columns":["","Category","","","Frequency",""],"rows":[["","Category","","","Frequency",""],["Manufacturer","","","Canon/Toshiba: 18\nGE: 35\nPhilips: 15\nSiemens: 32","",""]],"caption_candidate":"Testing Data Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p11-t0","doc_id":"K233753","page_num":11,"bbox":[72.24,72.72,539.81,394.16],"n_rows":8,"n_cols":2,"columns":["Data Origin","US: 69\nGermany: 31"],"rows":[["Data Origin","US: 69\nGermany: 31"],["Dose","Low: 31\nConventional: 69"],["Contrast Enhancement","Contrasted: 47\nNative: 53"],["Slice Thickness [mm]","≤1.25: 37\n(1.25-2]: 25\n(2-3]: 38"],["Age group [years]","[21-40): 17\n[40-60): 28\n[60-70): 24\n[70-80): 21\n≥80: 10"],["Nodule type","Solid: 90\nCalcified: 12\nSub-solid: 98"],["Nodule Size Range [mm]","[3-6): 25\n[6-10): 22\n[10-20): 33\n[20-30]: 7"],["Patient Sex","Male: 47\nFemale: 53"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233753-p12-t0","doc_id":"K233753","page_num":12,"bbox":[72.29,503.51,539.76,559.6],"n_rows":3,"n_cols":8,"columns":["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],"rows":[["Predicate Device","","FDA Clearance","","","FDA Clearance","","Main Product Code"],["","","Number","","","Date","",""],["AI-Rad Companion\n(Pulmonary)","K213713","","","August 11, 2022","","","JAK"]],"caption_candidate":"(Table 5):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233788-p5-t0","doc_id":"K233788","page_num":5,"bbox":[251.29,444.49,566.0,574.84],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ*","",""]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233788-p7-t0","doc_id":"K233788","page_num":7,"bbox":[66.02,502.87,556.16,707.68],"n_rows":35,"n_cols":5,"columns":["","","Philips EPIQ Series","",""],"rows":[["","","Philips EPIQ Series","",""],["","","","Philips EPIQ Series",""],["","EPIQ Series Diagnostic","Diagnostic Ultrasound","",""],["","","","Diagnostic Ultrasound",""],["","Ultrasound System","System","",""],["","","","System",""],["","","","",""],["","","","",""],["Feature","Affiniti Series Diagnostic","Affiniti Diagnostic","","Comparison"],["","","","",""],["","Ultrasound System","Ultrasound System","",""],["","","","",""],["","","","",""],["","","","(K231190)",""],["","Proposed Devices","(K211597)","",""],["","","","Reference Device",""],["","","Predicate Devices","",""],["","","","",""],["","Class II","Class II","Class II","Identical"],["USA FDA","","","",""],["Classification","","","",""],["","","","",""],["","IYN","IYN","IYN","Identical"],["Primary Product","","","",""],["Code","","","",""],["","","","",""],["","21 CFR 892.1550","21 CFR 892.1550","21 CFR 892.1550","Identical"],["Primary","","","",""],["Regulation","","","",""],["Number","","","",""],["","","","",""],["","Smart Doppler View ID","Not applicable since the\napplication is new","Not applicable since the\napplication is new","Subject of this submission"],["Marketing Name of","","","",""],["Application","","","",""],["","","","",""]],"caption_candidate":"are substantially equivalent to the predicate devices (K211597) and reference device (K231190).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233788-p8-t0","doc_id":"K233788","page_num":8,"bbox":[66.02,67.29,556.14,669.92],"n_rows":26,"n_cols":5,"columns":["","","Philips EPIQ Series","",""],"rows":[["","","Philips EPIQ Series","",""],["","","","Philips EPIQ Series",""],["","EPIQ Series Diagnostic","Diagnostic Ultrasound","",""],["","","","Diagnostic Ultrasound",""],["","Ultrasound System","System","",""],["","","","System",""],["","","","",""],["","","","",""],["Feature","Affiniti Series Diagnostic","Affiniti Diagnostic","","Comparison"],["","","","",""],["","Ultrasound System","Ultrasound System","",""],["","","","",""],["","","","",""],["","","","(K231190)",""],["","Proposed Devices","(K211597)","",""],["","","","Reference Device",""],["","","Predicate Devices","",""],["","","","",""],["","The proposed Smart\nDoppler View ID feature is\nintended to be used Adult\nCardiology Transthoracic\nexaminations to automate\nthe navigation of the\nCalculations Package\ngroup associated with\nDoppler Measurements.\nWithout the Smart Doppler\nView ID feature, users\nmust manually navigate to\nthe desired Doppler\nCalculations Package\nGroup on the Ultrasound\nSystem to perform a\nmeasurement. The Smart\nDoppler View ID feature\nautomates this navigation\nand selects the associated\nCalculations Package\ngroup for the user based\non the provided Doppler\nSpectrum acquired by the\nuser.\nAutomated selection of\nCalculation Package\nGroups by Smart Doppler\nView ID:\n• Aortic Valve\n• Mitral Valve\n• Tricuspid Valve\n• Pulmonic Valve\n• Venous Flow\n• TDI Vel & Ratio","Manual selection by the\nuser of Calculations\nPackage group on the\nultrasound system\nassociated with\nmeasurement groups on\nthe ultrasound system.\nManual selection of\nCalculation Package\nGroups by the user:\n• Aortic Valve\n• Mitral Valve\n• Tricuspid Valve\n• Pulmonic Valve\n• Venous Flow\n• TDI Vel & Ratio","Manual selection by the\nuser of Calculations\nPackage group on the\nultrasound system\nassociated with\nmeasurement groups on\nthe ultrasound system.\nManual selection of\nCalculation Package\nGroups by the user:\n• Aortic Valve\n• Mitral Valve\n• Tricuspid Valve\n• Pulmonic Valve\n• Venous Flow\n• TDI Vel & Ratio","Subject of this submission.\nThe Smart Doppler View ID\nautomates the selection of\nCalculations Package group\non the ultrasound system\nduring Adult Cardiology\nTransthoracic examinations,\nwhere the predicate and\nreference devices require\nusers to manually navigate to\ntheir desired Calculations\nPackage group to perform\nsubsequent measurements.\nThe Smart Doppler View ID\nfeature does not perform any\nmeasurements itself and is\nonly intended to automate the\nselection of the Calculations\nPackage group associated\nwith an acquired doppler\nspectrum.\nThere is no change to the\nCalculation Package Groups\navailable to the user."],["Application","","","",""],["Description","","","",""],["","","","",""],["","After a user acquires a\ndoppler spectrum, a\nCalculations Package\ngroup is automatically\nhighlighted on the\nultrasound system display\nfor the user by Smart\nDoppler View ID. From the\nhighlighted Calculations\nPackage group, the user\nmay select a desired\nmeasurement to perform\non the image. If the user\ndisagrees with the\nhighlighted Calculations\nPackage group, they can\nmanually navigate to their\ndesired Calculations\nPackage group.","After a user acquires a\ndoppler spectrum, the user\nmust manually navigate to\nthe desired Calculations\nPackage group. From the\nmanually selected\nCalculations Package\ngroup, the user may select\na desired measurement to\nperform on the image.","After a user acquires a\ndoppler spectrum, the user\nmust manually navigate to\nthe desired Calculations\nPackage group. From the\nmanually selected\nCalculations Package\ngroup, the user may select\na desired measurement to\nperform on the image.","The only difference with Smart\nDoppler View ID is that the\nMeasurement Calculations\nPackage group is\nautomatically highlighted for\nthe user after a doppler\nspectrum is acquired. Without\nSmart Doppler View ID, users\nmust manually navigate to\ntheir desired Calculations\nPackage group.\nThere is no change to the\nuser’s functionality once the\nCalculations Package group is\nselected for them compared to\ntheir workflow without Doppler\nView ID."],["User Interface","","","",""],["Presentation","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233788-p9-t0","doc_id":"K233788","page_num":9,"bbox":[66.02,67.29,556.15,494.78],"n_rows":30,"n_cols":5,"columns":["","","Philips EPIQ Series","",""],"rows":[["","","Philips EPIQ Series","",""],["","","","Philips EPIQ Series",""],["","EPIQ Series Diagnostic","Diagnostic Ultrasound","",""],["","","","Diagnostic Ultrasound",""],["","Ultrasound System","System","",""],["","","","System",""],["","","","",""],["","","","",""],["Feature","Affiniti Series Diagnostic","Affiniti Diagnostic","","Comparison"],["","","","",""],["","Ultrasound System","Ultrasound System","",""],["","","","",""],["","","","",""],["","","","(K231190)",""],["","Proposed Devices","(K211597)","",""],["","","","Reference Device",""],["","","Predicate Devices","",""],["","","","",""],["","EPIQ:\nX5-1, X5-1c, and S5-1 are\nalready commercially\navailable and compatible\nwith the EPIQ Ultrasound\nSystem.\nAffiniti:\nS5-1, X5-1, and S4-2 are\nalready commercially\navailable and compatible\nwith the Affiniti Ultrasound\nSystem.\nNo new transducers.\nTransducer modes for\nSmart Doppler View ID:\n2D, PWD, CWD, TDI. No\nnew transducer modes.","No new transducers and no\nnew modes","The K231190 submission\nintroduced the mL26-8\ntransducer. This transducer\nis not compatible with the\nproposed Smart Doppler\nView ID feature.","No new transducers or modes\nare being introduced in this\nsubmission. All transducers\nare already available with the\nEPIQ and Affiniti Ultrasound\nSystems."],["Compatible","","","",""],["transducers","","","",""],["","","","",""],["","No measurements are\nperformed by the Smart\nDoppler View ID feature.\nAny cardiac adult TTE\nmeasurements resulting\nfrom the view selection are\nperformed either manually\nby the user or by the\ncommercially available\nAutoMeasure function\n(K211597).","Any cardiac adult TTE\nmeasurements resulting\nfrom the view selection are\nperformed either manually\nby the user or by the\ncommercially available\nAutoMeasure function\n(K211597).","Any cardiac adult TTE\nmeasurements resulting\nfrom the view selection are\nperformed either manually\nby the user or by the\ncommercially available\nAutoMeasure function\n(K211597)","No new measurements are\nbeing introduced in this\nsubmission. The subject of this\nsubmission is to provide\nworkflow enhancements using\nan artificial intelligence -\napplication."],["Measurements","","","",""],["Performed","","","",""],["","","","",""],["","Algorithm accuracy of\n97.5% (95%CI 96.3%,\n98.3%), p-value <0.0001\ncompared to the ground\ntruth","N/A – the equivalent\nfunctionality is performed\nmanually by users to select\nthe appropriate calculation\npackage group (touch\nscreen group)","N/A – the equivalent\nfunctionality is performed\nmanually by users to select\nthe appropriate calculation\npackage group (touch\nscreen group)","Subject of this submission"],["Application","","","",""],["performance","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233788-p11-t0","doc_id":"K233788","page_num":11,"bbox":[147.99,171.44,461.73,436.54],"n_rows":8,"n_cols":2,"columns":["Demographic","Result (N=400) (% (xx/N)"],"rows":[["Demographic","Result (N=400) (% (xx/N)"],["Sex\nFemale\nMale","56.3% (225/400)\n43.8% (175/400)"],["Age (years, mean ± SD (range))","61.9 ± 16.6 (18.4, 98.7)"],["Height (cm, mean ± SD (range))","169.2 ± 10.7 (125,196)"],["Weight (kg, mean ± SD (range))","84.2 ± 23.7 (40.8, 263.0)"],["BSA (m2, mean ± SD (range))","1.9 ± 0.3 (1.3, 3.4)"],["BMI (kg/m2, mean ± SD (range))","29.5 ± 7.8 (15.8,78.5)"],["Race\nWhite\nAsian\nBlack or African American\nAmerican Indian or Alaska Native\nNative Hawaiian or Other Pacific Islander\nMixed/More than one race\nOther/Unknown/Not Reported","31.3% (125/400)\n2.8% (11/400)\n53.8% (215/400)\n0.3% (1/400)\n0.8% (3/400)\n9.5% (38/400)\n1.8% (7/400)"]],"caption_candidate":"The demographic distribution of the study population includes the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233822-p6-t0","doc_id":"K233822","page_num":6,"bbox":[36.24,107.4,733.5,530.76],"n_rows":12,"n_cols":4,"columns":["","Subject Device\ni2Contour","Predicate\nNeosoma, Inc. - NS-HGlio","Comparison"],"rows":[["","Subject Device\ni2Contour","Predicate\nNeosoma, Inc. - NS-HGlio","Comparison"],["K#","","K221738",""],["Product Code","QIH","QIH",""],["CFR","21 CFR 892.2050","21 CFR 892.2050",""],["Classification","Medical image management and processing system","Medical image management and processing system",""],["Indications for Use","MRIMath i2contour is intended for the semi-automatic\nlabeling, visualization, and volumetric quantification\nof WHO grade 4 glioblastoma (GBM) from a set of\nstandard MRI images of male or female patients 18\nyears of age or older who are known to have\npathologically proven glioblastoma.\nVolumetric measurements may be compared to past\nmeasurements if available. MRIMath i2contour is not\nto be used for primary diagnosis and is not intended to\nbe the sole diagnostic metric.","NS-HGlio is intended for the semi-automatic\nlabeling, visualization, and volumetric\nquantification of high-grade brain glioma (WHO\ngrade 3 astrocytoma, WHO grade 4 astrocytoma and\nWHO grade 4 glioblastoma) from a set of standard\nMRI images of male or female patients 18 years of\nage or older who are known to have pathologically\nproven high-grade glioma.\nVolumetric measurements may be compared to past\nmeasurements if available. NS-HGlio is not to be\nused for primary diagnosis, and is intended to be\nused by qualified clinical personnel as an additional\nsource of information and is not intended to be the\nsole diagnostic metric.","Similar except the subject\ndevice is specific for\nglioblastoma (GBM)"],["Patients","Male or female patients 18 years of age or older who\nare known to have pathologically proven glioblastoma","Male or female patients 18 years of age or older who\nare known to have pathologically proven high-grade\nglioma","Similar with the subject device\nis limited to GBM"],["Type of Scans Used","MRI:\nAcquired using two different MRI sequences either in\n2D or 3D using a specified protocol: T1 post-contrast\n(T1c) or FLAIR.","MRI:\nAcquired using four different MRI sequences either\nin 2D or 3D using a specified protocol: T1, T2, T1\npost-contrast (T1c) and FLAIR.","Different"],["Intended Anatomy","Brain","Brain","Similar"],["Lesion Review","2D and 3D","2D and 3D","Similar"],["Segmentation","Semi-automatic and manual segmentation of\nglioblastoma","Semi-automatic and manual segmentation of high-\ngrade glioma","Similar"],["Quantification","Volumetric measurements of the combination of the\nenhancing and necrosis subcomponents of the T1c, and\nthe combination of edema, tumor, and necrosis\nsubcomponents in the FLAIR images of glioblastoma","Volumetric measurement of the edema, necrosis, and\nenhancing sub-components of high-grade glioma","Different"]],"caption_candidate":"Table 1 - Comparison of Subject vs. Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233822-p7-t0","doc_id":"K233822","page_num":7,"bbox":[36.24,94.74,733.5,369.06],"n_rows":10,"n_cols":4,"columns":["","Subject Device\ni2Contour","Predicate\nNeosoma, Inc. - NS-HGlio","Comparison"],"rows":[["","Subject Device\ni2Contour","Predicate\nNeosoma, Inc. - NS-HGlio","Comparison"],["Output","- Provides volumetric measurements of glioblastoma\nand the tumor + edema + necrosis subcomponents in\nFLAIR and the enhancing + necrosis subcomponents\nin T1c series\n- Includes segmentation of the tumor + edema +\nnecrosis subcomponents in FLAIR and the enhancing\n+ necrosis subcomponents in T1c series\n- Automatically compares results to prior scans when\navailable\n- Provides PDF Report of output data","- Provides volumetric measurements of glioblastoma\nand the enhancing, necrosis, and edema sub-\ncomponents\n- Includes segmentation of sub-components\n- Automatically compares results to prior scans when\navailable\n- Provides PDF Report of output data","Different"],["Image Format","DICOM","DICOM","Similar"],["Input","FLAIR or T1c Series","T1, T2, FLAIR and T1c Series","Different"],["Registration","NO","YES","Different"],["Skull Stripping","NO","YES","Different"],["Number of AIs","Two","One","Different"],["Report","YES","YES","Similar"],["Indications","Grade 4 GBM","Grade 3 astrocytoma, grade 4 astrocytoma,\ngrade 4 GBM","Different"],["Evaluation of\nAccuracy","Using three US board certified neuroradiologists with\nexpertise in measuring GBM","Using three US board certified neuroradiologists with\nexpertise in measuring high grade gliomas","Similar"]],"caption_candidate":"Page 3 of 5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p5-t0","doc_id":"K233955","page_num":5,"bbox":[72.31,257.7,539.74,340.2],"n_rows":6,"n_cols":6,"columns":["Regulation Number","Regulation Number","Regulation Name","","Primary Product",""],"rows":[["Regulation Number","Regulation Number","Regulation Name","","Primary Product",""],["","","","","Code",""],["21 CFR § 892.1550","","Ultrasonic Pulsed Doppler Imaging System","IYN","",""],["Regulation Number","Regulation Number","Regulation Name","","Secondary",""],["","","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p5-t1","doc_id":"K233955","page_num":5,"bbox":[72.31,571.4,539.74,709.6],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Sonio Detect"],"rows":[["","Device Trade Name:","","Sonio Detect"],["","510(k) Reference:","","K230365"],["","Manufacturer Name:","","Sonio"],["","Regulation Name:","","Ultrasonic Pulsed Doppler Imaging System"],["Device Classification Name:","Device Classification Name:","","Ultrasonic Pulsed Doppler Imaging System\nUltrasonic Pulsed Echo Imaging System\nMedical Image Management and Processing System"],["","Product Code(s):","","IYN; IYO; QIH"],["","Regulation Number:","","21 CFR § 892.1550; 21 CFR § 892.1560; 21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p6-t0","doc_id":"K233955","page_num":6,"bbox":[72.19,586.88,539.86,628.03],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducer","","C3 HD3"],"rows":[["","Clarius Ultrasound Transducer","","C3 HD3"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"K213436). Clarius OB AI is not a stand-alone software device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p8-t0","doc_id":"K233955","page_num":8,"bbox":[72.31,97.81,724.07,535.41],"n_rows":10,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs",""],["","","","","Clarius OB AI","","","Sonio Detect","","","from predicate device)",""],["","510(k) Holder/ Manufacturer","","Clarius Mobile Health Corp.","","","Sonio","","","Not applicable","",""],["","Submission Reference","","Current Submission","","","K230365","","","Not applicable","",""],["Product Code(s)","Product Code(s)","","IYN; QIH","","","IYN; IYO; QIH","","","The “IYN” primary product\ncode is the same as the\npredicate device and the\n“QIH” secondary product\ncode is the same as the\npredicate device.","",""],["Device Classification Name","","","Ultrasonic Pulsed Doppler Imaging\nSystem;\nMedical Image Management and\nProcessing System","","","Ultrasonic Pulsed Doppler Imaging\nSystem;\nUltrasonic Pulsed Echo Imaging System;\nMedical Image Management and\nProcessing System","","","The “Ultrasonic Pulsed\nDoppler Imaging System”\nand the “Medical Image\nManagement and\nProcessing System” device\nclassification names are\nthe same as the predicate\ndevice.","",""],["Regulation Number","","","21 CFR § 892.1550;\n21 CFR § 892.2050","","","21 CFR § 892.1550;\n21 CFR § 892.1560;\n21 CFR § 892.2050","","","The “21 CFR § 892.1550”\nregulation number and the\n“21 CFR § 892.2050”\nregulation number are the\nsame as the predicate\ndevice.","",""],["Intended Use","","","Intended for use as an assistive tool/aid\nduring the acquisition and interpretation\nof fetal ultrasound images through non-\ninvasive processing of ultrasound images\nutilizing an artificial intelligence/machine-\nlearning algorithm.","","","Intended for use as an assistive tool/aid\nduring the acquisition and interpretation\nof fetal ultrasound images through non-\ninvasive processing of ultrasound images\nutilizing an artificial intelligence/machine-\nlearning algorithm.","","","Same as predicate device.","",""],["Indications for Use","","","Clarius OB AI is intended to assist in\nmeasurements of fetal biometric\nparameters (i.e., head circumference,\nabdominal circumference, femur","","","Sonio Detect is intended to analyze fetal\nultrasound images and clips using\nmachine learning techniques to\nautomatically detect views, detect","","","Both the predicate and\nsubject device are\nindicated for analysis of\nfetal ultrasound images","",""]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p9-t0","doc_id":"K233955","page_num":9,"bbox":[72.31,72.38,724.06,520.65],"n_rows":8,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs",""],["","","","","Clarius OB AI","","","Sonio Detect","","","from predicate device)",""],["","","","length, bi-parietal diameter, crown\nrump length) on ultrasound data\nacquired by the Clarius Ultrasound\nScanner (i.e., curvilinear scanner).\nThe user shall be a healthcare\nprofessional trained and qualified in\nultrasound. The user retains the\nresponsibility of confirming the\nvalidity of the measurements based\non standard practices and clinical\njudgment. Clarius OB AI is indicated\nfor use in adult patients only.","","","anatomical structures within the views\nand verify quality criteria of the views.\nThe device is intended for use as a\nconcurrent reading aid during the\nacquisition and interpretation of fetal\nultrasound images.","","","using AI/ML techniques.\nBoth devices detect\nvarious fetal anatomies;\nthe predicate device\nprovides qualitative\ninformation to the user,\nwhereas the subject\ndevice provides semi-\nautomated quantitative\ninformation regarding\nfetal biometrics. Both the\npredicate and subject\ndevices are intended for\nuse as an adjunctive ‘tool’\nor aid by the user for the\ninterpretation of fetal\nultrasound images and are\nnot intended to replace\nclinical decision making.\nThe differences in the\nindications for use do not\nimpact the safety and\neffectiveness of the\nsubject device relative to\nthe predicate device.","",""],["","Radiological application/ Supported","","Ultrasound","","","Ultrasound","","","Same as predicate device.","",""],["","modality","","","","","","","","","",""],["","Clinical application(s)","","Obstetrics/Fetal","","","Obstetrics/Fetal","","","Same as predicate device.","",""],["Principle of Operation/ Technology","Principle of Operation/ Technology","","Ultrasound image processing software\napplication implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms trained with\nclinical and/or artificial data intended for","","","Ultrasound image processing software\napplication implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms trained with\nclinical and/or artificial data intended for","","","Same as predicate device.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p10-t0","doc_id":"K233955","page_num":10,"bbox":[72.31,72.38,724.07,387.93],"n_rows":10,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs",""],["","","","","Clarius OB AI","","","Sonio Detect","","","from predicate device)",""],["","","","non-invasive analysis (i.e., quantitative\nand/or qualitative) of ultrasound data.","","","non-invasive analysis (i.e., quantitative\nand/or qualitative) of ultrasound data.","","","","",""],["Quantitative and/or Qualitative\nAnalysis","","","Fetal biometry/measurement of fetal\nbiometric parameters (i.e., HC, AC, BPD,\nCRL, FL)","","","Detection, verification, and qualitative\nanalysis of fetal anatomical structures","","","The subject device\nperforms semi-automated\nmeasurements of fetal\nbiometrics, whereas the\npredicate device detects,\nverifies, and performs\nqualitative analysis of fetal\nanatomies.","",""],["","Algorithm Methodology","","Artificial Intelligence (AI)","","","Artificial Intelligence (AI)","","","Same as predicate device.","",""],["","Automation (Yes or No)","","Yes","","","Yes","","","Same as predicate device.","",""],["","Environment of Use","","Healthcare setting (e.g., hospital, clinic)","","","Healthcare setting (e.g., hospital, clinic)","","","Same as predicate device.","",""],["","Intended Users","","Licensed healthcare professionals","","","Licensed healthcare professionals","","","Same as predicate device.","",""],["Platform","Platform","","Embedded in the Clarius ultrasound app","","","Cloud-based and stand-alone software","","","The subject device is\nembedded in the\nultrasound app, which is\npart of the ultrasound\nsystem, whereas, the\npredicate device is cloud-\nbased, stand-alone\nsoftware.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p11-t0","doc_id":"K233955","page_num":11,"bbox":[72.26,181.44,539.74,306.36],"n_rows":8,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["12-349","","","NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set"],["5-129","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p14-t0","doc_id":"K233955","page_num":14,"bbox":[72.55,190.92,539.93,718.8],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["Modification of model\narchitecture","","Improvement and\noptimization of Clarius\nOB AI’s performance","","","Re-training of the OB AI\nmodel with new data to\noptimize its\nperformance followed\nby internal testing and\na comparison of the\noriginal OB AI model to\nthe modified OB AI\nmodel (using\nperformance metrics)\nand clinical\nperformance testing\n(verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nOB AI model with\nincreased accuracy\nand more robust\ngestational age\nestimates displayed\nto users.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization for\ndiverse cases.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of model\ntraining methods and\nparameters","","Improvement and\noptimization of Clarius\nOB AI’s performance","","","Internal testing and a\ncomparison of the\noriginal OB AI model to\nthe modified OB AI\nmodel (using","","","Improved\nperformance\nmetrics of modified\nOB AI model.","",""]],"caption_candidate":"Summary of changes to Clarius OB AI per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p15-t0","doc_id":"K233955","page_num":15,"bbox":[72.55,72.93,539.93,694.8],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","performance metrics)\nand clinical\nperformance testing\n(verification and\nvalidation).","","","Benefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization for\ndiverse cases.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of post-\nprocessing algorithms","","Improvement and\noptimization of Clarius\nOB AI’s performance\nand robustness","","","Internal testing and a\ncomparison of the\noriginal OB AI model to\nthe modified OB AI\nmodel (using\nperformance metrics)\nand clinical\nperformance testing\n(verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nOB AI model.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization for\ndiverse cases.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233955-p16-t0","doc_id":"K233955","page_num":16,"bbox":[72.55,72.93,539.93,641.04],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","","","","Internal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of data\ninput sources","","To enable use of Clarius\nOB AI on newer models\nof the 510(k)-cleared\nClarius Ultrasound\nScanner system","","","Re-training of the OB AI\nmodel to expand its use\nwith new data sources\n(i.e., new 510(k)-\ncleared models of the\nClarius Ultrasound\nScanner), internal\ntesting, and clinical\nperformance testing\n(verification and\nvalidation) to assesses\nits performance with\nthe new data input\nsources.","","","By accommodating a\nwider array of image\ngeometries and\ncharacteristics with\nthe use of new\n510(k)-cleared\nClarius scanners, the\nupdated OB AI\nmodel will be better\nequipped to handle\ndifferent models of\nthe Clarius\nUltrasound Scanner\nused in varying\nclinical scenarios.\nBenefit-Risk\nAnalysis:\nBenefits: Enhanced\ncompatibility;\nFlexibility for diverse\nclinical settings.\nRisks: Data skewing\nand concept drift.\nRisk Mitigation:\nInternal testing and\nverification datasets\nwithin the intended\npatient population\nwill ensure that data\nskewing and\nconcept drift are\nmitigated.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233968-p9-t0","doc_id":"K233968","page_num":9,"bbox":[72.29,100.14,535.51,712.92],"n_rows":40,"n_cols":7,"columns":["","","Subject device: CINA-iPE Software","","","Predicate device: BriefCase Software",""],"rows":[["","","Subject device: CINA-iPE Software","","","Predicate device: BriefCase Software",""],["","","","","","(K213886)",""],["Intended Use\n/ Indications\nfor Use","CINA-iPE is a radiological computer-\naided triage and notification software\nindicated for use in patients\nundergoing contrast-enhanced CT\nscans (not dedicated CTPA protocol)\nfor other clinical indications than\npulmonary embolism\nsuspicion, including at least a part of\nthe lung. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging and communicating\nsuspected positive findings for\nincidental Pulmonary Embolism\n(iPE). The device is indicated for\nadults and transitional adolescents\n(18 to 21 years old but treated as\nadults).\nCINA-iPE uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected incidental PE on a\nstandalone application in parallel to\nthe ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected incidental PE findings.\nThe device is not designed to detect\nPE in subsegmental arteries.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and are\nnot intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image, and it is\nnot intended to be used as a\ndiagnostic device.\nThe results of CINA-iPE\nare intended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgment to assist with\ntriage/prioritization of medical","CINA-iPE is a radiological computer-","","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\ncontrast-enhanced chest CTs (not\ndedicated CTPA protocol) in adults or\ntransitional adolescents age 18 and\nolder. The device is intended to assist\nhospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communication of\nsuspect cases of incidental Pulmonary\nEmbolism (iPE) pathologies. The device\nis intended to be used on single energy\nexams only.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag\nsuspect cases on a standalone desktop\napplication in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with notifications\nfor suspect cases. Notifications include\ncompressed preview images that are\nmeant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is\nnot intended to be used as a diagnostic\ndevice.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","",""],["","","aided triage and notification software","","","",""],["","","indicated for use in patients","","","",""],["","","undergoing contrast-enhanced CT","","","",""],["","","scans (not dedicated CTPA protocol)","","","",""],["","","for other clinical indications than","","","",""],["","","pulmonary embolism","","","",""],["","","suspicion, including at least a part of","","","",""],["","","the lung. The device is intended to","","","",""],["","","assist hospital networks and trained","","","",""],["","","radiologists in workflow triage by","","","",""],["","","flagging and communicating","","","",""],["","","suspected positive findings for","","","",""],["","","incidental Pulmonary Embolism","","","",""],["","","(iPE). The device is indicated for","","","",""],["","","adults and transitional adolescents","","","",""],["","","(18 to 21 years old but treated as","","","",""],["","","adults).","","","",""],["","","CINA-iPE uses an artificial","","","",""],["","","intelligence algorithm to analyze","","","",""],["","","images and highlight cases with","","","",""],["","","detected incidental PE on a","","","",""],["","","standalone application in parallel to","","","",""],["","","the ongoing standard of care image","","","",""],["","","interpretation. The user is presented","","","",""],["","","with notifications for cases with","","","",""],["","","suspected incidental PE findings.","","","",""],["","","The device is not designed to detect","","","",""],["","","PE in subsegmental arteries.","","","",""],["","","Notifications include compressed","","","",""],["","","preview images that are meant for","","","",""],["","","informational purposes only and are","","","",""],["","","not intended for","","","",""],["","","diagnostic use beyond notification.","","","",""],["","","The device does not alter the original","","","",""],["","","medical image, and it is","","","",""],["","","not intended to be used as a","","","",""],["","","diagnostic device.","","","",""]],"caption_candidate":"Ltd)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233968-p10-t0","doc_id":"K233968","page_num":10,"bbox":[72.25,72.36,535.55,620.28],"n_rows":14,"n_cols":7,"columns":["","","Subject device: CINA-iPE Software","","","Predicate device: BriefCase Software",""],"rows":[["","","Subject device: CINA-iPE Software","","","Predicate device: BriefCase Software",""],["","","","","","(K213886)",""],["","images. Notified clinicians are\nultimately responsible for reviewing\nfull images per the standard of care.","","","","",""],["User\npopulation","Radiologist","","","Appropriately trained medical specialists","",""],["Anatomical\nregion of\ninterest","Chest or exams including at least a\npart of the lung","","","Chest","",""],["Data\nacquisition\nprotocol","Contrast-enhanced CT scans (not\ndedicated CTPA protocol) containing\nat least a part of the lung","","","Contrast-enhanced chest CTs (but not\ndedicated CTPA protocol)","",""],["View DICOM\ndata","DICOM information about the\npatient, study and current image","","","DICOM information about the patient,\nstudy and current image","",""],["Segmentatio\nn of region of\ninterest","No; device does not mark, highlight,\nor direct users’ attention to a specific\nlocation in the original image","","","No; device does not mark, highlight, or\ndirect users’ attention to a specific\nlocation in the original image","",""],["Algorithm","Artificial intelligence algorithm with\ndatabase of images","","","Artificial intelligence algorithm with\ndatabase of images","",""],["Notification /\nPrioritization","Yes","","","Yes","",""],["Preview\nimages","Presentation of a compressed,\ngrayscale, unannotated image that is\nmarked “not for diagnostic use” is\ndisplayed as a preview function.","","","Presentation of a low-quality,\ncompressed grayscale preview image\nthat is captioned “Not for diagnostic use”.","",""],["Alteration of\noriginal\nimage","No","","","No","",""],["Removal of\ncases from\nworklist\nqueue","No. The device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","","","No. The device operates in parallel with\nthe standard of care, which remains the\ndefault option for all cases.","",""],["Structure","-iPE image processing application\n- Compatibility of use with the CINA\nPlatform device (worklist and Image\nViewer) or other medical image\ncommunications device,","","","-AHS module/Orchestrator (image\nacquisition).\n- ACS module (image processing).\n- Aidoc Worklist application for workflow\nintegration (worklist and non-diagnostic\nbasic Image Viewer).","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233977-p4-t0","doc_id":"K233977","page_num":4,"bbox":[72.02,349.73,540.1,414.53],"n_rows":3,"n_cols":3,"columns":["Classification Name","Regulation","Product Code"],"rows":[["Classification Name","Regulation","Product Code"],["Ultrasonic Pulsed Echo\nImaging System","21 CFR §892.1560","IYO"],["Diagnostic Ultrasonic\nTransducer","21 CFR §892.1570","ITX"]],"caption_candidate":"Common Name: Ultrasound elastography system","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233977-p6-t0","doc_id":"K233977","page_num":6,"bbox":[127.37,662.38,503.11,715.42],"n_rows":3,"n_cols":3,"columns":["","Parameter Fitting\nCohort (Training)","Validation Cohort"],"rows":[["","Parameter Fitting\nCohort (Training)","Validation Cohort"],["Number of patients","112","70"],["Number of Sites","4","3"]],"caption_candidate":"below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233977-p7-t0","doc_id":"K233977","page_num":7,"bbox":[127.34,75.96,503.14,141.74],"n_rows":5,"n_cols":3,"columns":["Sex (% Female)","53% Female","75.7% Female"],"rows":[["Sex (% Female)","53% Female","75.7% Female"],["Age (mean ± std)","57.4 ± 11.7","46.9 ± 13.8"],["BMI (mean ± std)","30 ± 4.4","30.9 ± 7.58"],["Race/Ethnicity (% white)","36 %","69 %"],["MRI PDFF (mean ± std)","14.2 ± 8.23","10.1 ± 9.75"]],"caption_candidate":"Model: LI-1005 Section 5 - 4","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p10-t0","doc_id":"K233998","page_num":10,"bbox":[166.34,575.95,409.75,671.38],"n_rows":5,"n_cols":3,"columns":["Feature","Lower limit (%)","Upper limit (%)"],"rows":[["Feature","Lower limit (%)","Upper limit (%)"],["SUVmax","-27.0","56.8"],["SUVmean","-20.2","38.5"],["SUVtotal","-54.1","144.5"],["Volume","-52.6","113.9"]],"caption_candidate":"Table 1: Lower and upper limits of repeatability for each imaging feature.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p11-t0","doc_id":"K233998","page_num":11,"bbox":[104.18,312.29,471.82,684.1],"n_rows":6,"n_cols":2,"columns":["Imaging Site /\nLocation","Site 1 (North Carolina, USA), n = 35\nSite 2 (Unknown State, USA) , n = 31 Site 3\n(North Carolina, USA), n = 13\nSite 4 (North Carolina, USA), n = 12\nSite 5 (Iowa, USA), n = 4\nSite 6 (North Carolina, USA), n = 3\nSite 7 (North Carolina, USA), n = 2\nSite 8 (Unknown State, USA), n = 1\nSite 9 (North Carolina, USA), n = 1\nSite 10 (Missouri, USA), n = 1"],"rows":[["Imaging Site /\nLocation","Site 1 (North Carolina, USA), n = 35\nSite 2 (Unknown State, USA) , n = 31 Site 3\n(North Carolina, USA), n = 13\nSite 4 (North Carolina, USA), n = 12\nSite 5 (Iowa, USA), n = 4\nSite 6 (North Carolina, USA), n = 3\nSite 7 (North Carolina, USA), n = 2\nSite 8 (Unknown State, USA), n = 1\nSite 9 (North Carolina, USA), n = 1\nSite 10 (Missouri, USA), n = 1"],["Cancer Type, n","Breast Cancer, n = 23\nLung Cancer, n = 20\nProstate, n = 16\nMelanoma, n = 15\nHead & Neck Cancer, n = 8\nLymphoma, n = 7\nColorectal Cancer, n = 6\nOther, n = 5\nGynecological Cancer, n = 3"],["Patient sex, n\nFemale / Male","57/46"],["Patient age, years\nMedian (range)","66 (26, 87)"],["Patient weight, kg\nMedian (range)","78.5 (43.0, 132.9)"],["Patient Race","Unreported, n = 75\nWhite, n = 25\nHispanic, n = 2\nBlack, n = 1"]],"caption_candidate":"during the scan transfer process.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p13-t0","doc_id":"K233998","page_num":13,"bbox":[30.89,125.6,545.57,710.62],"n_rows":14,"n_cols":3,"columns":["","TRAQinform IQ","Quantitative Total Extensible"],"rows":[["","TRAQinform IQ","Quantitative Total Extensible"],["Specification /","",""],["","Subject Device","Imaging (QTxI) (K173444)"],["Characteristic","",""],["","","Predicate Device"],["","",""],["","",""],["Product Code","LLZ","LLZ"],["Regulation\nNumber","892.2050","892.2050"],["Regulatory Class","II","II"],["Review Panel","Radiology","Radiology"],["Users","Trained medical professionals including, but\nnot limited to, radiologists, oncologists,\nnuclear medicine physicians, medical imaging\ntechnologists, dosimetrists and physicists.","Trained medical professionals\nincluding, but not limited to,\nradiologists, oncologists, nuclear\nmedicine physicians, medical imaging\ntechnologists, dosimetrists and\nphysicists."],["Intended Use","A software tool to aid in evaluation and\ninformation management of digital medical\nimages.","A software tool to aid in evaluation\nand information management of digital\nmedical\nimages."],["Indications for\nUse","TRAQinform IQ is a software only device that\nprovides quantitative analysis of lesions\nidentified as Regions of Interest (ROI) in\nPET/CT DICOM compliant imaging data\nacquired, interpreted, and reported on per local\npractice prior to device use.\nClinicians responsible for patient care and for\nordering TRAQinform Reports as an adjunct to\nlocally reported image interpretation do not\ninteract directly with the device. Clinicians\nresponsible for local image interpretation do\nnot interact with the device and generate their\nreporting before and independently of the\nTRAQinform Report.\nThe TRAQinform Report is generated by the\ndevice manufacturer and signed by a U.S.\nboard certified physician responsible for\nsupervising central report generation and\nqualified to practice nuclear\nradiology/medicine. The TRAQinform Report is\nfor use by trained medical professionals\nincluding but not limited to oncologists, nuclear\nradiologists/physicians, medical imaging\ntechnologists, dosimetrists, and physicists.","Quantitative Total Extensible Imaging\n(QTxI) is a software tool used to aid in\nevaluation and information management\nof digital medical images by trained\nmedical professionals including, but not\nlimited to, radiologists, oncologists,\nnuclear medicine physicians, medical\nimaging technologists, dosimetrists and\nphysicists. The medical modalities of\nthese medical images include, but are\nnot limited to, DICOM CT and PET as\nsupported by ACR/NEMA DICOM 3.0."]],"caption_candidate":"Table 3: Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p14-t0","doc_id":"K233998","page_num":14,"bbox":[29.64,83.42,545.5,597.91],"n_rows":8,"n_cols":3,"columns":["","TRAQinform IQ","Quantitative Total Extensible Imaging"],"rows":[["","TRAQinform IQ","Quantitative Total Extensible Imaging"],["Specification /","",""],["","Subject Device","(QTxI) (K173444)"],["Characteristic","",""],["","","Predicate Device"],["","",""],["","",""],["","TRAQinform IQ software contains the\nfollowing functionalities:\n• Automated matching of ROI between\npreviously performed CT and PET/CT\nDICOM 3.0 volumetric medical\nimages.\n• In order to perform automated\nmatching of ROI and quantitative\nanalysis of previously performed CT\nand PET/CT DICOM 3.0 volumetric\nmedical images, the software initially\nperforms the following functions:\n▪ Machine learning skeletal and\nanatomic structure\nsegmentation.\n▪ Threshold-based ROI\nidentification and contouring.\n• Automated quantitative analysis to\nassess previously performed CT and\nPET/CT DICOM 3.0 volumetric\nmedical images, including: change in\ntotal volume and density of each\nidentified ROI, and change in\nFludeoxyglucose F18 (FDG) tracer\nuptake of each identified ROI among\nimages.\n• Generation of images of the anatomy\ncombined with spatial and quantitative\ninformation, including computed\nclassification of quantitative FDG ROI\nchanges.","QTxI assists in the following indications:\n• Receive, store, retrieve, display\nand process digital medical\nimages\n• Create, display and print reports\nfrom those images\n• Provide medical professionals\nwith the ability to display,\nregister, and fuse medical\nimages\n• Identify Regions of Interest (ROIs)\nand perform ROI contouring\nallowing quantitative/statistical\nanalysis of full or partial body scans\n• Evaluate quantitative change in\nROIs (total or partial body;\nindividual ROI within individual) with\n3D interactive rendering of images\nwith highlighted ROIs."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p15-t0","doc_id":"K233998","page_num":15,"bbox":[29.52,91.76,545.62,668.26],"n_rows":8,"n_cols":3,"columns":["","TRAQinform IQ","Quantitative Total Extensible Imaging"],"rows":[["","TRAQinform IQ","Quantitative Total Extensible Imaging"],["Specification /","",""],["","Subject Device","(QTxI) (K173444)"],["Characteristic","",""],["","","Predicate Device"],["","",""],["","",""],["","For multi-timepoint quantitative analysis,\nrecommended use is in adult patients 22\nyears and older with partial or whole-body\nPET/CT acquired following administration\nof FDG per approved drug prescribing\ninformation and with the second FDG\nadministration separated from the first by\na period not to exceed 12 months.\nFor single-timepoint quantitative analysis,\nrecommended use is in adult patients 22\nyears and older with partial or whole-body\nPET/CT following administration of FDG,\na PSMA targeted PET drug, or a SSTR-\ntargeted PET drug per approved drug\nprescribing information.\nDiscrepancies between TRAQinform IQ\nand local PET/CT reporting have been\ninvestigated and use of TRAQinform IQ\nhas not been established for binary\npatient level progression or non-\nprogression decisions without\nmultidisciplinary review. Discrepancies\nbetween TRAQinform IQ and local\nPET/CT reporting that could impact\npatient care should therefore prompt\nconsultation with subject matter experts\n(for example, in tumor board), with a\npatient-centered focus on discrepant\nimaging regions and with blinded or\notherwise neutral adjudication regarding\ninterpretation/classification source.\nTRAQinform IQ is not intended to\ndiagnose any disease, replace the\ndiagnostic procedures for interpretation of\nCT or PET/CT images, recommend any\nspecific treatment, nor is it intended to\nreplace the skill and judgement of a\nqualified medical professional.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p16-t0","doc_id":"K233998","page_num":16,"bbox":[29.45,91.76,545.68,742.54],"n_rows":13,"n_cols":3,"columns":["","TRAQinform IQ","Quantitative Total Extensible Imaging"],"rows":[["","TRAQinform IQ","Quantitative Total Extensible Imaging"],["Specification /","",""],["","Subject Device","(QTxI) (K173444)"],["Characteristic","",""],["","","Predicate Device"],["","",""],["","",""],["Medical Modalities","CT and PET/CT images as supported by\nACR/NEMA DICOM 3.0\nRadiotracers for multiple timepoints: FDG\nRadiotracers for single timepoint: FDG,\nPSMA-targeted PET drug, or a SSTR-\ntargeted PET drug","DICOM, CT, MRI, SPECT and PET as\nsupported by ACR/NEMA DICOM 3.0\nRadiotracers: NaF PET"],["Operating System","Secure Cloud Environment with Web\nBrowser Interface","Windows 7 or Windows 10"],["Identification of\nROI","Automatic Threshold based ROI\nidentification in bone and anatomical\nstructures","Threshold based ROI identification in bone"],["Importation of\nROI contours","TRAQinform IQ allows the importation of\nphysician established contours of ROI","No importation functionality"],["Segmentation","Segmentation of bone to identify skeletal\nstructures and segmentation of\nanatomical structures to identify organs.\nSegmentation is driven by machine\nlearning algorithms.","Atlas based segmentation of bone to identify\nskeletal structures"],["Quantitative\nAnalysis","Scan-to-scan registration and ROI\nmatching allows automatic\nquantification of ROIs and assessment\nof changes/differences in ROI:\n• Changes in ROI shape\n• Single ROI splitting into multiple\nROI\n• Multiple ROI combining into a\nsingle ROI\n• ROI appearing, disappearing,\nand re- appearing across\nimages\nQuantitative analysis of functional and\nanatomical data for CT and PET/CT\nscans, including:\n• Volume of each identified\nROI on each image\n• Change in volume of each\nidentified ROI among images\n• Total volume of all identified\nROI on each image","Scan-to-scan registration and ROI matching\nallows automatic quantification of ROIs and\nassessment of changes/differences in ROI.\nQuantitative/statistical analysis of full or\npartial-body scans"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K233998-p17-t0","doc_id":"K233998","page_num":17,"bbox":[25.08,83.42,545.5,721.06],"n_rows":8,"n_cols":3,"columns":["","TRAQinform IQ","Quantitative Total Extensible Imaging"],"rows":[["","TRAQinform IQ","Quantitative Total Extensible Imaging"],["Specification /","",""],["","Subject Device","(QTxI) (K173444)"],["Characteristic","",""],["","","Predicate Device"],["","",""],["","",""],["","• Change in total volume of all\nidentified ROI on each image\n• Heterogeneity of change in volume\nof each identified ROI\nFor PET scans:\n• Tracer uptake (SUVmax,\nSUVtotal, SUVmean,\nSUVhetero) of each identified\nROI on each image\n• Change in tracer uptake\n(SUVmax, SUVtotal, SUVmean)\nof each identified ROI among\nimages\n• Total tracer uptake (SUVmax,\nSUVtotal, SUVmean, SUVhetero)\nof all identified ROI on each\nimage\n• Change in total tracer uptake\n(SUVmax, SUVtotal, SUVmean,\nSUVhetero) of all identified ROI\non each image\n• Heterogeneity of change in tracer\nuptake (SUVhetero) among\nidentified ROI\nFor CT scans:\n• Radio density (HUmax,\nHUtotal, HUmean, HUhetero)\nfor each identified ROI on\neach image\n• Changes in radio density (HUmax,\nHUtotal, HUmean) of all identified\nROI on each image\n• Change in total radio density\n(HUmax, HUtotal, HUmean,\nHUhetero) of all identified ROI on\neach image\n• Heterogeneity of change in radio\ndensity (HUhetero) among\nidentified ROI\n2D Graphical renderings of medical\nimages, including Maximum Intensity\nProjections of the PET and CT, with\noverlayed and labeled/color-coded ROI for\ninclusion in TRAQinform Reports.\n3D labeled contours for ROI, anatomic\nstructures, and skeletal structures.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p5-t0","doc_id":"K234009","page_num":5,"bbox":[81.08,443.35,499.58,520.87],"n_rows":5,"n_cols":12,"columns":["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],"rows":[["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],["","Primary Predicate Device","","","","","","","","","",""],["K183105","","","LLZ","","","Mimics Medical","","","Materialise NV","",""],["","Subsequent Predicate Device","","","","","","","","","",""],["K183489","","","LLZ","","","D2P","","","3D Systems, Inc","",""]],"caption_candidate":"Acorn 3D Software (AC-SEG-4009); Acorn 3DP Model (AC-101-XX)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p6-t0","doc_id":"K234009","page_num":6,"bbox":[72.1,117.5,477.07,266.42],"n_rows":4,"n_cols":10,"columns":["","","Automatic","","","Semi-Automatic","","","Manual",""],"rows":[["","","Automatic","","","Semi-Automatic","","","Manual",""],["Definition","Algorithmic with little or no\ndirect human control","","","A combination of\nalgorithmic and direct\nhuman control","","","Directly controlled by a\nhuman","",""],["Tool Type","Machine Learning\nalgorithm used to\nautomatically segment\nindividual vertebrae","","","Algorithmic based tools\nthat do not incorporate\nmachine learning.","","","Manual tools requiring user\ninput.","",""],["Anatomical\nLocation (s)","Spinal anatomy:\n Thoracic (T1-T12)\n Lumbar (L1-L5)","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","",""]],"caption_candidate":"intended use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p7-t0","doc_id":"K234009","page_num":7,"bbox":[72.29,415.75,557.71,719.26],"n_rows":5,"n_cols":12,"columns":["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],"rows":[["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],["","Features↓","","","(K234009)","","","(K183105)","","","(K183489)",""],["Premarket\nnotification","","","K234009","","","K183105","","","K183489","",""],["Manufacturer","","","Mighty Oak Medical","","","Materialise N.V.","","","3D Systems","",""],["Indications for Use\nStatement","","","Acorn Segmentation is intended for use as a\nsoftware interface and image segmentation\nsystem for the transfer of CT or CTA medical\nimaging information to an output file. Acorn\nSegmentation is also intended for measuring and\ntreatment planning. The Acorn Segmentation\noutput can also be used for the fabrication of\nphysical replicas of the output file using additive\nmanufacturing methods, Acorn 3DP Models. The\nphysical replica can be used for diagnostic\npurposes in the field of musculoskeletal and\ncraniomaxillofacial applications.\nAcorn Segmentation and 3DP Models should be\nused in conjunction with expert clinical judgment.","","","Mimics is intended for\nuse as a software\ninterface and image\nsegmentation system\nfor the transfer of\nmedical imaging\ninformation to an\noutput file. Mimics\nMedical is also\nintended for\nmeasuring and\ntreatment planning.\nThe Mimics Medical\noutput can be used\nfor the fabrication of\nphysical replicas of\nthe output file using\ntraditional or additive\nmanufacturing\nmethods.\nThe physical replica\ncan be used for\ndiagnostic purposes in","","","The D2P software is\nintended for use as a\nsoftware interface\nand image\nsegmentation system\nfor the transfer of\nDICOM imaging\ninformation from a\nmedical scanner to\nan output file. It is also\nintended as pre‐\noperative software for\nsurgical planning. For\nthis purpose, the\noutput file may be\nused to produce a\nphysical replica. The\nphysical replica is\nintended for\nadjunctive use along\nwith other diagnostic\ntools and expert\nclinical judgement for","",""]],"caption_candidate":"Medical, K183105).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p8-t0","doc_id":"K234009","page_num":8,"bbox":[72.28,40.92,557.73,704.02],"n_rows":9,"n_cols":12,"columns":["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],"rows":[["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],["","Features↓","","","(K234009)","","","(K183105)","","","(K183489)",""],["","","","","","","the field of\northopaedic,\nmaxillofacial and\ncardiovascular\napplications.\nMimics Medical\nshould be used in\nconjunction with\nexpert clinical\njudgment.","","","diagnosis, patient\nmanagement, and/or\ntreatment selection of\ncardiovascular,\ncraniofacial,\ngastrointestinal,\ngenitourinary,\nneurological, and/or\nmusculoskeletal\napplications.","",""],["General intended\nuse","","","Acorn Segmentation is image processing software\nthat allows the user to import, visualize and\nsegment medical images, check and correct the\nsegmentations, and create digital 3D models.","","","Mimics Medical is\nimage processing\nsoftware that allows\nthe user to import,\nvisualize and segment\nmedical images,\ncheck and correct the\nsegmentations, and\ncreate digital 3D\nmodels.","","","D2P is image\nprocessing software\nthat allows the user to\nimport, visualize and\nsegment medical\nimages, check and\ncorrect the\nsegmentations, and\ncreate digital 3D\nmodels.","",""],["Product\nClassification","","","System, Image processing, Radiological","","","System, Image\nprocessing,\nRadiological","","","System, Image\nprocessing,\nRadiological","",""],["Regulatory Class","","","Class II","","","Class II","","","Class II","",""],["Regulation\nNumber","","","892.2050","","","892.2050","","","892.2050","",""],["Product Code","","","QIH, LLZ","","","LLZ","","","LLZ","",""],["Device\nDescription","","","Acorn Segmentation is an image processing\nsoftware that allows the user to import, visualize\nand segment medical images, check and\ncorrect the segmentations, and create digital 3D\nmodels. The models can be used in Acorn\nSegmentation for measuring, treatment planning\nand producing an output file to be used for\nadditive manufacturing (3D printing). Acorn\nSegmentation is structured as a modular\npackage. This includes the following functionality:\n Importing medical images in DICOM format\n Viewing images and DICOM data\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools or fully\nautomatic algorithms\n Verifying and editing a region of interest\n Calculating a digital 3D model and editing\nthe model\n Measuring on images and 3D models\n Exporting 3D models to third-party packages\nAcorn Segmentation contains both machine\nlearning based auto-segmentation as well as\nsemi-automatic and manual segmentation tools.\nThe auto-segmentation tool is only intended to be\nused for thoracic and lumbar regions of the spine\n(T1-T12 and L1-L5). Semi-automatic and manual\nsegmentation tools are intended to be used for all\nmusculoskeletal and craniomaxillofacial\nanatomy. The following table provides a definition","","","Mimics Medical is\nimage processing\nsoftware that allows\nthe user to import,\nvisualize and segment\nmedical images,\ncheck and correct the\nsegmentations, and\ncreate digital 3D\nmodels. The models\ncan be used in Mimics\nMedical for\nmeasuring, treatment\nplanning and\nproducing an output\nfile to be used for\nadditive\nmanufacturing (3D\nprinting). Mimics\nMedical also has\nfunctionality for linking\nto third party software\npackages. Mimics\nMedical is structured\nas a modular\npackage. This includes\nthe following\nfunctionality:\n Importing\nmedical images\nin DICOM format\nand other\nformats (such as","","","The D2P software is a\nstand‐alone modular\nsoftware package\nthat provides\nadvanced\nvisualization of DICOM\nimaging data. This\nmodular package\nincludes, but is not\nlimited to the following\nfunctions:\n DICOM viewer\nand analysis\n Automated\nsegmentation\n Editing and pre‐\nprinting\n Seamless\nintegration with\n3D Systems\nprinters\n Seamless\nintegration with\n3D Systems\nsoftware\npackages\n Seamless\nintegration with\nVirtual Reality\nvisualization for\nnon‐diagnostic\nuse.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p9-t0","doc_id":"K234009","page_num":9,"bbox":[72.3,40.92,557.71,706.9],"n_rows":4,"n_cols":12,"columns":["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],"rows":[["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],["","Features↓","","","(K234009)","","","(K183105)","","","(K183489)",""],["","","","and the anatomical location(s) for each tool’s\nintended use.\nSemi-\nAutomatic Manual\nAutomatic\nA\nAlgorithmic combination\nDirectly\nwith little or of\ncontrolled\nDefinition no direct algorithmic\nby a\nhuman and direct\nhuman\ncontrol human\ncontrol\nMachine\nLearning\nAlgorithmic\nalgorithm\nbased tools Manual\nused to\nTool that do not tools\nautomat-\nType incorporate requiring\nically\nmachine user input.\nsegment\nlearning.\nindividual\nvertebrae\nMusculo-\nMusculo- skeletal &\nskeletal & craniuma-\nSpinal cranioma- xillofacial\nAnatom- anatomy: xillofacial bone:\nical  Thoracic bone:  Short\nLocation (T1-T12)  Short  Long\n(s)  Lumbar  Long  Flat\n(L1-L5)  Flat  Sesa-\n Sesamoid moid\n Irregular  Irreg-\nular\nAcorn 3DP Model is an additively manufactured\nphysical replica of the virtual 3D model\ngenerated in Acorn Segmentation. The output file\nfrom Acorn Segmentation is used to additively\nmanufacture the Acorn 3DP Model.","","","BMP, TIFF, JPG\nand raw images)\n Viewing images\nand DICOM data\n Selecting a\nregion of interest\nusing generic\nsegmentation\ntools\n Segmenting\nspecific anatomy\nusing dedicated\nsemi-automatic\ntools or fully\nautomatic\nalgorithms\n Verifying and\nediting a region\nof interest\n Calculating a\ndigital 3D model\nand editing the\nmodel\n Measuring on\nimages and 3D\nmodels\n Exporting\nimages,\nmeasurements\nand 3D models\nto third-party\npackages\n Planning\ntreatments\n(surgical cuts\netc.) on the 3D\nmodels\n Interfacing with\npackages for\nFinite Element\nAnalysis\n Creating Python\nscripts to\nautomate\nworkflows","","","","",""],["Technological\ncharacteristics","","","Acorn Segmentation is a standalone modular\nsoftware package. This module includes, but is\nnot limited to the following functions:\nImage Import\n Importing medical images in DICOM format\nImage Processing\n Processing of images with common noise-\nreduction filters\n Editing of spatial arrangement of images\nVisualization\n Viewing images and DICOM data\nSegmentation\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools","","","Mimics Medical is\nstructured as a\nmodular package.\nThis includes the\nfollowing functionality:\nImage Import\n Importing\nmedical images\nin DICOM format\nand other formats\n(such as BMP,\nTIFF, JPG and raw\nimages)\nImage Processing\n Processing of\nimages with\ncommon noise-\nreduction filters","","","D2P is structured as a\nmodular package.\nThis includes the\nfollowing functionality:\nImage Import\n Importing\nmedical images\nin DICOM format\nand other\nformats (such as\nBMP, TIFF, JPG\nand raw images)\nImage Processing\n Processing of\nimages with\ncommon noise-\nreduction filters","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p9-t1","doc_id":"K234009","page_num":9,"bbox":[161.01,93.12,354.57,352.46],"n_rows":5,"n_cols":6,"columns":["","Automatic","","Semi-","","Manual"],"rows":[["","Automatic","","Semi-","","Manual"],["","","","Automatic","",""],["Definition","Algorithmic\nwith little or\nno direct\nhuman\ncontrol","A\ncombination\nof\nalgorithmic\nand direct\nhuman\ncontrol","","","Directly\ncontrolled\nby a\nhuman"],["Tool\nType","Machine\nLearning\nalgorithm\nused to\nautomat-\nically\nsegment\nindividual\nvertebrae","Algorithmic\nbased tools\nthat do not\nincorporate\nmachine\nlearning.","","","Manual\ntools\nrequiring\nuser input."],["Anatom-\nical\nLocation\n(s)","Spinal\nanatomy:\n Thoracic\n(T1-T12)\n Lumbar\n(L1-L5)","Musculo-\nskeletal &\ncranioma-\nxillofacial\nbone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","","","Musculo-\nskeletal &\ncraniuma-\nxillofacial\nbone:\n Short\n Long\n Flat\n Sesa-\nmoid\n Irreg-\nular"]],"caption_candidate":" Viewing images","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p10-t0","doc_id":"K234009","page_num":10,"bbox":[72.31,40.92,557.69,707.86],"n_rows":3,"n_cols":12,"columns":["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],"rows":[["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],["","Features↓","","","(K234009)","","","(K183105)","","","(K183489)",""],["","",""," Segmenting specific vertebral anatomy\nusing machine-learning-based fully\nautomatic algorithms\n Verifying and editing a region of interest\nMeasurement\n Measuring on images and 3D models\nImage Export\n Exporting images and 3D models to third-\nparty packages\n3D Models\n Calculating a digital 3D model and editing\nthe model\n Smoothing a 3D model\n Importing 3D models\nTreatment Planning\n Importing of third-party STLs to visualize\nplanned interactions with anatomy as\nrepresented in DICOM images\nOther features\n Using a collection of images and masks as a\ntraining dataset for machine-learning\nsegmentation algorithm","",""," Editing of spatial\narrangement of\nimages\n Processing of\nimaging data for\nremoval of\ncommon artifacts\n(e.g. scatter)\nVisualization\n Viewing images\nand DICOM data\nSegmentation\n Selecting a\nregion of interest\nusing generic\nsegmentation\ntools\n Segmenting\nspecific anatomy\nusing dedicated\nsemi-automatic\ntools or fully\nautomatic\nalgorithms\n Verifying and\nediting a region\nof interest\nMeasurement\n Measuring on\nimages and 3D\nmodels\nImage Export\n Exporting images,\nmeasurements\nand 3D models\nto third-party\npackages\n3D Models\n Calculating a\ndigital 3D model\nand editing the\nmodel\n Wrapping a 3D\nmodel\n Smoothing a 3D\nmodel\n Importing 3D\nmodels\nTreatment Planning\n Importing of\nthird-party STLs to\nvisualize planned\ninteractions with\nanatomy as\nrepresented in\nDICOM images\n Planning\ntreatments\n(surgical cuts\netc.) on the 3D\nmodels","",""," Editing of spatial\narrangement of\nimages\nVisualization\n Viewing images\nand DICOM data\nSegmentation\n Selecting a\nregion of interest\nusing generic\nsegmentation\ntools\n Segmenting\nspecific anatomy\nusing dedicated\nsemi-automatic\ntools or fully\nautomatic deep\nlearning tools\n Verifying and\nediting a region\nof interest\nMeasurement\n Measuring on\nimages and 3D\nmodels\nImage Export\n Exporting images\nand 3D models\nto third-party\npackages\n3D Models\n Calculating a\ndigital 3D model\nand editing the\nmodel\n Smoothing a 3D\nmodel\n Importing 3D\nmodels\nTreatment Planning\n Importing of\nthird-party STLs to\nvisualize planned\ninteractions with\nanatomy as\nrepresented in\nDICOM images\n Planning\ntreatments\n(surgical cuts\netc.) on the 3D\nmodels\nOther features\nView DICOM images\nin VR without\nsegmentation","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234009-p11-t0","doc_id":"K234009","page_num":11,"bbox":[72.3,40.92,557.71,357.53],"n_rows":4,"n_cols":12,"columns":["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],"rows":[["","Device→","","","Acorn Segmentation","","","Mimics Medical","","","D2P",""],["","Features↓","","","(K234009)","","","(K183105)","","","(K183489)",""],["","","","","","","Other features\n Interfacing with\npackages for\nFinite Element\nAnalysis\n Creating Python\nscripts to\nautomate\nworkflows","","","","",""],["Physical Model","","","The Acorn Segmentation output can be used for\nthe fabrication of physical replicas of the output\nfile using additive manufacturing methods. The\nphysical replica can be used for diagnostic\npurposes in the field of musculoskeletal and\ncraniomaxillofacial applications.","","","The Mimics Medical\noutput can be used\nfor the fabrication of\nphysical replicas of\nthe output file using\ntraditional or additive\nmanufacturing\nmethods. The physical\nreplica can be used\nfor diagnostic\npurposes in the field of\northopedic,\nmaxillofacial and\ncardiovascular\napplications.","","","The D2P output file\nmay be used to\nproduce a physical\nreplica. The physical\nreplica is intended for\nadjunctive use along\nwith other diagnostic\ntools and expert\nclinical judgement for\ndiagnosis, patient\nmanagement, and/or\ntreatment selection of\ncardiovascular,\ncraniofacial,\ngastrointestinal,\ngenitourinary,\nneurological, and/or\nmusculoskeletal\napplications.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p4-t0","doc_id":"K234042","page_num":4,"bbox":[71.25,129.49,455.53,744.67],"n_rows":46,"n_cols":2,"columns":["1. General Informatio","n"],"rows":[["1. General Informatio","n"],["",""],["510(k)Sponsor","EverFortune.AICo.,Ltd."],["",""],["Address","Rm.D,8F.No.573,Sec.2TaiwanBlvd."],["","WestDist."],["","TaichungCity403020"],["","TAIWAN"],["",""],["Applicant","JosephChang"],["",""],["ContactInformation","886-04-23213838#216"],["","joseph.chang@everfortune.ai"],["",""],["CorrespondencePerson","Ti-HaoWang"],["",""],["ContactInformation","886-04-23213838#168"],["","thothwang@gmail.com"],["",""],["","tihao.wang@everfortune.ai"],["",""],["DatePrepared","October,2023"],["",""],["2. Proposed Device",""],["",""],["ProprietaryName","EFAI Bonesuite XR Bone Age Pro Assessment Syst"],["",""],["CommonName","EFAIBAPXR"],["",""],["ClassificationName","System,ImageProcessing,Radiological"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["RegulationName","MedicalImageManagementandProcessingSystem"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["3. Predicate Device",""],["",""],["ProprietaryName","MedoAria"],["",""],["PremarketNotification","K200356"],["",""],["EFAIBAPXRTraditional510(k)",""]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"text"}
{"table_id":"K234042-p4-t1","doc_id":"K234042","page_num":4,"bbox":[66.25,448.32,539.5,615.44],"n_rows":7,"n_cols":2,"columns":["ProprietaryName","EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100)"],"rows":[["ProprietaryName","EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100)"],["CommonName","EFAIBAPXR"],["ClassificationName","System,ImageProcessing,Radiological"],["RegulationNumber","21CFR892.2050"],["RegulationName","MedicalImageManagementandProcessingSystem"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p4-t2","doc_id":"K234042","page_num":4,"bbox":[66.25,662.49,539.5,710.49],"n_rows":2,"n_cols":2,"columns":["ProprietaryName","MedoAria"],"rows":[["ProprietaryName","MedoAria"],["PremarketNotification","K200356"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p5-t0","doc_id":"K234042","page_num":5,"bbox":[66.25,89.55,539.5,209.17],"n_rows":5,"n_cols":2,"columns":["ClassificationName","System,ImageProcessing,Radiological"],"rows":[["ClassificationName","System,ImageProcessing,Radiological"],["RegulationNumber","21CFR892.2050"],["RegulationName","MedicalImageManagementandProcessingSystem"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p6-t0","doc_id":"K234042","page_num":6,"bbox":[73.5,210.6,537.63,709.5],"n_rows":8,"n_cols":3,"columns":["Feature/\nFunction","ProposedDevice:\nEFAIBAPXR\n(K234042)","PredicateDevice:\nMedoAria\n(K200356)"],"rows":[["Feature/\nFunction","ProposedDevice:\nEFAIBAPXR\n(K234042)","PredicateDevice:\nMedoAria\n(K200356)"],["Intended\nUse/Indicationfor\nUse","EFAI BONESUITE XR BONE AGE\nPRO ASSESSMENT SYSTEM\n(EFAI BAPXR) is designed to view\nand quantify bone age from 2D\nPosterior Anterior (PA) view of\nleft-hand radiographs using deep\nlearning techniques to aid in the\nanalysis of bone age assessment of\npatients between 2 to 16yearsoldfor\npediatric radiologists. The results\nshould not be relied upon alone by\npediatric radiologists to make\ndiagnostic decisions. The images\nshall be with left hand andwristfully\nvisible within the field of view, and\nshall be without any major bone\ndestruction, deformity, fracture,\nexcessive motion, or other major\nartifacts.","MEDO ARIA is designed to view\nand quantify ultrasound image data\nusing machine learning techniques\nto aid trained medical professionals\nin diagnosis of developmental\ndysplasia of the hip (DDH). The\ndevice is intended to be used on\nneonates and infants, aged 0 to 12\nmonths."],["EnvironmentofUse","Healthcarefacility/Hospital","Healthcarefacility/Hospital"],["Intendeduser","Pediatricradiologist","Radiologist"],["Clinicalcondition","Boneageassessment","developmentaldysplasiaofthehip\n(DDH)"],["ImageInput","ComplieswithDICOMstandard","ComplieswithDICOMstandard"],["ScanType","X-ray","2Dand3DUltrasound"],["BodyPart","Lefthandandwrist","Hip"]],"caption_candidate":"6. Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p7-t0","doc_id":"K234042","page_num":7,"bbox":[73.5,89.5,537.5,403.5],"n_rows":8,"n_cols":3,"columns":["Imagedisplaymode","Static","Static"],"rows":[["Imagedisplaymode","Static","Static"],["ArtificialIntelligence\nAlgorithm","Yes","Yes"],["Imagenavigationand\nmanipulation\ntools","No","Adjustimagebrightnessand\ncontrast,slice-scroll,pane\nlayout,reset"],["2Dimagereview","No","Yes,capableofreviewingall\nframesofmulti-frame\n(multi-slice)image"],["Manuallandmark\nplacement","No","Yes"],["Semi-automatic\nlandmark\nplacement","No","Yes,user-modifiable"],["Quantitativeanalysis","Boneageassessment(years)","● Angle(alphaangle)\n● Distanceratio(coverage)"],["Reportcreation","No","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234042-p10-t0","doc_id":"K234042","page_num":10,"bbox":[72.0,103.44,512.14,667.75],"n_rows":57,"n_cols":3,"columns":["","Intercept(95%CI)","Slope(95%CI)"],"rows":[["","Intercept(95%CI)","Slope(95%CI)"],["Gender","",""],["Female","0.01(-0.07,0.09)","0.99(0.98,1.00)"],["Male","-0.14(-0.23,-0.04)","1.00(0.99,1.01)"],["Age","",""],["","",""],["Pre-puberty","0.03(-0.07,0.13)","0.98(0.96,0.99)"],["","",""],["Early&Mid-puberty","-0.06(-0.25,0.13)","0.99(0.98,1.01)"],["","",""],["Late-puberty","-1.10(-1.46,-0.74)","1.07(1.04,1.09)"],["","",""],["RaceorEthnicity","",""],["","",""],["White","-0.05(-0.14,0.04)","0.99(0.99,1.00)"],["","",""],["Hispanic","0.05(-0.12,0.22)","0.98(0.97,1.00)"],["","",""],["BlackorAfrican","-0.17(-0.55,0.20)","1.01(0.98,1.04)"],["","",""],["Asian","-0.12(-0.28,0.04)","0.99(0.98,1.01)"],["","",""],["Multiple","-0.19(-0.36,-0.01)","1.00(0.98,1.02)"],["","",""],["OtherRacesorEthnicities","-0.07(-0.31,0.17)","0.99(0.97,1.01)"],["","",""],["ClinicalOrganization","",""],["","",""],["OrgA","0.12(-0.13,0.37)","0.97(0.94,1.01)"],["","",""],["OrgB","-0.24(-0.69,0.21)","1.01(0.97,1.05)"],["","",""],["OrgC","-0.11(-0.24,0.02)","0.99(0.98,1.00)"],["","",""],["OrgD","-0.07(-0.15,0.01)","1.00(0.99,1.01)"],["","",""],["X-rayManufacturer","",""],["","",""],["SamsungElectronics","-0.17(-0.33,-0.01)","1.00(0.99,1.01)"],["","",""],["CarestreamHealth","-0.03(-0.16,0.10)","0.99(0.98,1.00)"],["","",""],["Kodak","-0.17(-0.28,-0.07)","1.01(1.00,1.02)"],["","",""],["GEHealthcare","0.01(-0.23,0.25)","0.99(0.96,1.01)"],["","",""],["Siemens","0.05(-0.10,0.20)","1.00(0.99,1.02)"],["","",""],["KonicaMinolta","0.12(-0.10,0.35)","0.97(0.94,1.00)"],["","",""],["OtherManufacturers","0.05(-0.29,0.39)","0.99(0.96,1.02)"],["","",""],["CaseswithRadiologicFindings","-0.03(-0.14,0.08)","0.99(0.98,1.01)"],["","",""],["CaseswithImageQualityFindings","-0.04(-0.19,0.11)","1.00(0.98,1.01)"],["","",""],["Pre-puberty:femaleages[2-7)&maleages[2-9).","",""]],"caption_candidate":"Table.SubgroupingAnalysisResultsofEFAIBAPXR","well_formed":true,"extraction_settings":"text"}
{"table_id":"K234068-p4-t0","doc_id":"K234068","page_num":4,"bbox":[72.28,492.15,523.23,523.15],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate Trade Name (Primary Predicate is listed first)","Product Code"],"rows":[["Predicate #","Predicate Trade Name (Primary Predicate is listed first)","Product Code"],["K232479","ART-Plan","MUJ"]],"caption_candidate":"Legally Marketed Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234141-p6-t0","doc_id":"K234141","page_num":6,"bbox":[72.48,96.12,507.48,513.72],"n_rows":16,"n_cols":2,"columns":["Characteristic","Percent positive\nor\naverage and\nstandard deviation"],"rows":[["Characteristic","Percent positive\nor\naverage and\nstandard deviation"],["Age (years)","67±16.73"],["Sex (Female)","39.6%"],["Body mass index (BMI)","15 to 49 (mean 6±18)"],["POCUS device (not high-end cardiac ultrasound system)","25.9%"],["Bedside ultrasound exam (outside of the echo lab)","23.8%"],["Dyslipidemia (lipid disorder)","6.7%"],["Diabetes Mellitus (DM)","15.2%"],["Obstructive lung disease","2.9%"],["Myocardial infarction (MI past \\ recent)","7.4%"],["Heart failure (HF) or cardiomyopathy (CMP)","5.8%"],["Renal dysfunction including chronic kidney disease (CKD)","10.0%"],["Hypertension","41.9%"],["Ischemic heart disease (IHD including past angioplasty or cardiac\nsurgery)","17.5%"],["CVA or TIA","8%"],["Cardiac valve disease (any valve and of any severity)","40.7%"]],"caption_candidate":"Clinical characteristics of the AISAP CARIDO V1.0 training data set","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234141-p9-t0","doc_id":"K234141","page_num":9,"bbox":[72.48,167.52,482.04,375.0],"n_rows":13,"n_cols":2,"columns":["Characteristic","Percent positive\nor\naverage and\nstandard deviation"],"rows":[["Characteristic","Percent positive\nor\naverage and\nstandard deviation"],["Age (years)","68±16.39"],["Sex (Female)","36.8%"],["Body mass index (BMI)","26.69±4.97"],["Dyslipidemia (lipid disorder)","59%"],["Diabetes Mellitus (DM)","29.3%"],["Obstructive lung disease","5.6%"],["Myocardial infarction (MI past \\ recent)","27%"],["Heart failure (HF) or cardiomyopathy (CMP)","37%"],["Renal dysfunction including chronic kidney disease (CKD)","21.2%"],["Hypertension","62%"],["CVA or TIA","12.7%"],["Cardiac valve disease (any valve and of any severity)","55.9%"]],"caption_candidate":"Clinical characteristics of the clinical study data set","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234141-p11-t0","doc_id":"K234141","page_num":11,"bbox":[49.32,563.04,562.78,587.28],"n_rows":2,"n_cols":5,"columns":["TR","Kappa","0.881 (0.871,0.892)","0.765 (0.747,0.783)","0.116"],"rows":[["TR","Kappa","0.881 (0.871,0.892)","0.765 (0.747,0.783)","0.116"],["","Accuracy","75.3% (73.6%,77.0%)","64.1% (62.2%,65.9%)","11.2%"]],"caption_candidate":"Accuracy 73.6% (71.9%,75.2%) 61.6% (59.8%,63.4%) 12.0%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234141-p11-t1","doc_id":"K234141","page_num":11,"bbox":[49.32,611.4,562.78,635.65],"n_rows":2,"n_cols":5,"columns":["AS","Kappa","0.850 (0.834,0.864)","0.792 (0.773,0.809)","0.058"],"rows":[["AS","Kappa","0.850 (0.834,0.864)","0.792 (0.773,0.809)","0.058"],["","Accuracy","74.7% (73.0%,76.3%)","69.8% (68.1%,71.6%)","4.9%"]],"caption_candidate":"Accuracy 80.6% (79.1%,82.1%) 71.7% (70.0%,73.3%) 8.9%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p7-t0","doc_id":"K234154","page_num":7,"bbox":[106.46,383.78,538.86,714.46],"n_rows":15,"n_cols":4,"columns":["ITEM","Proposed Device\nuPMR 790","Predicate Device\nuPMR 790(K222540)","Remark"],"rows":[["ITEM","Proposed Device\nuPMR 790","Predicate Device\nuPMR 790(K222540)","Remark"],["Magnet system","","",""],["Field Strength","3.0 Tesla","3.0 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible\nbore dimensions","60 cm","60 cm","Same"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Magnet\nHomogeneity","≤ 2.400 ppm @ 50 cm DSV\n≤ 0.800 ppm @ 45cm DSV\n≤ 0.390 ppm @ 40 cm DSV\n≤ 0.110 ppm @ 30 cm DSV\n≤ 0.038 ppm @ 20 cm DSV\n≤ 0.020 ppm @ 10 cm DSV","≤ 2.400 ppm @ 50 cm DSV\n≤ 0.800 ppm @ 45cm DSV\n≤ 0.390 ppm @ 40 cm DSV\n≤ 0.110 ppm @ 30 cm DSV\n≤ 0.038 ppm @ 20 cm DSV\n≤ 0.020 ppm @ 10 cm DSV","Same"],["Gradient system","","",""],["Max gradient\namplitude","45 mT/m","45 mT/m","Same"],["Max slew rate","200 T/m/s","200 T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant\nfrequencies","128.23 MHz","128.23 MHz","Same"],["Number of transmit\nchannels","2","2","Same"]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p8-t0","doc_id":"K234154","page_num":8,"bbox":[106.46,78.78,538.86,694.96],"n_rows":29,"n_cols":4,"columns":["Number of receive\nchannels","48","48","Same"],"rows":[["Number of receive\nchannels","48","48","Same"],["Amplifier peak\npower per channel","18 kW","18 kW","Same"],["RF Coils","","",""],["Volume Transmit\nCoil","Yes","Yes","Same"],["Head & Neck Coil -\n24","Yes","Yes","Same"],["Body Array Coil -\n12","Yes","Yes","Same"],["Breast Coil - 10","Yes","Yes","Same"],["Flex Coil Large - 8","Yes","Yes","Same"],["Flex Coil Small - 8","Yes","Yes","Same"],["Knee Coil - 12","Yes","Yes","Same"],["Lower Extremity\nCoil - 36","Yes","Yes","Same"],["Shoulder Coil - 12","Yes","Yes","Same"],["Small Loop Coil","Yes","Yes","Same"],["Spine Coil - 32","Yes","Yes","Same"],["Wrist Coil - 12","Yes","Yes","Same"],["Head Coil - 32","Yes","Yes","Same"],["Foot & Ankle Coil -\n24","Yes","Yes","Same"],["Cardiac Coil - 24","Yes","Yes","Same"],["Temporomandibular\nJoint Coil - 4","Yes","Yes","Same"],["Carotid Coil - 8","Yes","Yes","Same"],["Infant Coil - 24","Yes","Yes","Same"],["Patient table","","",""],["Dimensions","W×H×L: 640 mm×890\nmm× 2620 mm","W×H×L: 640 mm×890 mm\n× 2620 mm","Same"],["Maximum supported\npatient weight","250 kg","250 kg","Same"],["Accessories","","",""],["Vital Signal Gating","Wireless UIH Gating Unit\nREF 453564324621\nECG module Ref\n989803163121\nSpO2 module Ref\n989803163111\n(alternative)","Wireless UIH Gating Unit\nREF 453564324621\nECG module Ref\n989803163121\nSpO2 module Ref\n989803163111\n(alternative)","Same"],["","uVWMERP\nuMVRX\n(alternative)","uVWMERP\nuMVRX\n(alternative)",""],["PET","","",""],["Resolution","1 cm: FWMH≤3.2 mm\n10 cm: FWHM≤3.6 mm\n20 cm: FWHM≤4.8 mm","1 cm: FWMH≤3.2 mm\n10 cm: FWHM≤3.6 mm\n20cm: FWHM≤4.8 mm","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p9-t0","doc_id":"K234154","page_num":9,"bbox":[106.53,78.78,538.8,564.82],"n_rows":14,"n_cols":4,"columns":["Sensitivity","0 cm: ≥14 cps/kBq\n10 cm: ≥14 cps/kBq","0 cm: ≥14 cps/kBq\n10 cm: ≥14 cps/kBq","Same"],"rows":[["Sensitivity","0 cm: ≥14 cps/kBq\n10 cm: ≥14 cps/kBq","0 cm: ≥14 cps/kBq\n10 cm: ≥14 cps/kBq","Same"],["Scatter fraction,\ncount losses and\nrandoms\nmeasurement","NECR peak:≥110 kcps\nTrue peak: ≥300 kcps\nScatter Fraction: ≤0.46","NECR peak:≥110 kcps\nTrue peak: ≥300 kcps\nScatter Fraction: ≤0.46","Same"],["Accuracy","maximum value of the bias at\nor below necr peak activity\nvalue:≤10%","maximum value of the bias at\nor below necr peak activity\nvalue:≤10%","Same"],["Image quality","Contrast Recovery coefficient:\n10 mm: ≥45.0%\n13 mm: ≥55.0%\n17 mm: ≥55.0%\n22 mm: ≥65.0%\n28 mm: ≥65.0%\n37 mm: ≥70.0%\nNoise:\n10 mm: ≤9.0%\n13 mm: ≤8.0%\n17 mm: ≤7.0%\n22 mm: ≤7.0%\n28 mm: ≤7.0%\n37 mm: ≤7.0%\nRelative lung error:≤10%","Contrast Recovery coefficient:\n10 mm: ≥45.0%\n13 mm: ≥55.0%\n17 mm: ≥65.0%\n22 mm: ≥65.0%\n28 mm: ≥65.0%\n37 mm: ≥70.0%\nNoise:\n10 mm: ≤9.0%\n13 mm: ≤8.0%\n17 mm: ≤7.0%\n22 mm: ≤7.0%\n28 mm: ≤7.0%\n37 mm: ≤7.0%\nRelative lung error:≤10%","Note 1"],["Time of Fly(TOF)\nresolution","≤560 ps","≤560 ps","Same"],["MR Image Processing Features","","",""],["CASS","Yes","No","Note 2"],["PASS","Yes","No","Note 3"],["HYPER Iterative","Yes","Yes","Note 4"],["Workflow Features","","",""],["EasyScan","Yes","Yes","Note 5"],["QGuard-Imaging","Yes","No","Note 6"],["EasyCrop","Yes","No","Note 7"],["Mocap-Monitoring","Yes","No","Note 8"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p9-t1","doc_id":"K234154","page_num":9,"bbox":[106.53,592.9,538.8,715.73],"n_rows":8,"n_cols":6,"columns":["ITEM","Proposed Device\nuPMR 790","uMR Omega(K220332)","Remark","",""],"rows":[["ITEM","Proposed Device\nuPMR 790","uMR Omega(K220332)","Remark","",""],["SuperFlex Body - 24","Yes","Yes","","Same",""],["SuperFlex Large - 12","Yes","Yes","","Same",""],["SuperFlex Small - 12","Yes","Yes","","Same",""],["MR Image Processing Features","","","","",""],["2D Flow","Yes","Yes","","Same",""],["DeepRecon","Yes","Yes","","Same",""],["Inline T2 Mapping","Yes","Yes","","Same",""]],"caption_candidate":"Table 2 Comparison to Reference device#1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p10-t0","doc_id":"K234154","page_num":10,"bbox":[106.64,78.78,538.74,278.97],"n_rows":14,"n_cols":6,"columns":["Spectroscopy Features","","","","",""],"rows":[["Spectroscopy Features","","","","",""],["Liver Spectroscopy","Yes","Yes","","Same",""],["Breast Spectroscopy","Yes","Yes","","Same",""],["MR Image Reconstruction Features","","","","",""],["ACS","Yes","Yes","","Same",""],["Function","","","","",""],["MR conditional implant\nmode","Yes","Yes","Same","",""],["ITEM","Proposed Device\nuPMR 790","uMR Omega(K230152)","Remark","",""],["MR Image Processing Features","","","","",""],["4D Flow","Yes","Yes","","Same",""],["SNAP","Yes","Yes","","Same",""],["CEST","Yes","Yes","","Same",""],["T1rho","Yes","Yes","","Same",""],["FSP+","Yes","Yes","","Same",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p10-t1","doc_id":"K234154","page_num":10,"bbox":[106.64,307.1,538.74,348.69],"n_rows":2,"n_cols":6,"columns":["ITEM","Proposed Device\nuPMR 790","Reference Device#2\nHYPER AiR(K210001)","Remark","",""],"rows":[["ITEM","Proposed Device\nuPMR 790","Reference Device#2\nHYPER AiR(K210001)","Remark","",""],["HYPER DPR","Yes","Yes","","Same",""]],"caption_candidate":"Table 3 Comparison to Reference device#2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p10-t2","doc_id":"K234154","page_num":10,"bbox":[106.64,376.82,538.74,419.36],"n_rows":2,"n_cols":6,"columns":["ITEM","Proposed Device\nuPMR 790","Reference Device#3\nuMI 550(K193241)","Remark","",""],"rows":[["ITEM","Proposed Device\nuPMR 790","Reference Device#3\nuMI 550(K193241)","Remark","",""],["Digital Gating","Yes","Yes","","Same",""]],"caption_candidate":"Table 4 Comparison to Reference device#3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p10-t3","doc_id":"K234154","page_num":10,"bbox":[106.64,433.7,538.74,695.5],"n_rows":7,"n_cols":2,"columns":["Note 1","The contrast recovery coefficient of 17mm spheres is updated from 55% to 65%, while\nhistorical test data shows the test results can meet 65% requirement.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 1","The contrast recovery coefficient of 17mm spheres is updated from 55% to 65%, while\nhistorical test data shows the test results can meet 65% requirement.\nThe difference did not raise new safety and effectiveness concerns."],["Note 2","CASS is substantially equivalent to BSSFP and acquires two different phase cycling angle\nimages and combine them by MIP operation to reduce dark band artifact.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","PASS is substantially equivalent to GRE and acquires two different type (SSFP_FID and\nSSFP_SE) echoes image and combine them to achieve hybrid contrast image."],["Note 4","In this submission, the noise control term was changed from total variation regularization\nto smoothed total variation regularization.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","EasyScan of the proposed device supports more body part than that of the predicate\ndevice. In this submission, shoulder and abdomen are included.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","QGuard-Imaging is expected for automatic monitoring of MR images for motion artifacts\nand providing real-time prompts to assist technicians in image quality control.\nThe difference did not raise new safety and effectiveness concerns."],["Note 7","EasyCrop is a function that enables automatic cropping of vascular images scanned with\nthe TOF_3D protocol to simplify the workflow, which allows users to obtain interference-\nfree vascular MIP images and automatically rotated MIP images with different angles"]],"caption_candidate":"Digital Gating Yes Yes Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K234154-p11-t0","doc_id":"K234154","page_num":11,"bbox":[106.64,78.78,538.8,165.02],"n_rows":2,"n_cols":2,"columns":["","when the scan is completed and images are generated. After enabling the EasyCrop\nfunction, the original images of TOF_3D will still be saved.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["","when the scan is completed and images are generated. After enabling the EasyCrop\nfunction, the original images of TOF_3D will still be saved.\nThe difference did not raise new safety and effectiveness concerns."],["Note 8","MoCap-Monitoring is a motion monitoring module which is periodic and is inserted into\na pulse sequence. It can realize real-time motion monitoring in imaging scanning and\nprovides an alert when motion occurs.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p5-t0","doc_id":"K240003","page_num":5,"bbox":[66.55,519.91,521.15,676.66],"n_rows":14,"n_cols":5,"columns":["Specification","Proposed","Predicate Device:","Reference","Reference"],"rows":[["Specification","Proposed","Predicate Device:","Reference","Reference"],["","Device:","Overjet Caries","Device:","Device:"],["","Velmeni For","","Denti.AI","Second"],["","","Assist","",""],["","","","Detect",""],["","Dentists","K222746","","Opinion"],["","","","K230144",""],["","(V4D)","","","K210365"],["","","","",""],["","","","",""],["","","","",""],["Manufacturer","Velmeni Inc.","Overjet Inc.","Denti.AI\nTechnology Inc.","Pearl Inc."],["Classification","892.2070","892.2070","892.2070","892.2070"],["Product\nCode","MYN","MYN","MYN","MYN"]],"caption_candidate":"Table 1. Comparison of the Proposed Device, Predicate Device and Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p6-t0","doc_id":"K240003","page_num":6,"bbox":[66.55,67.38,521.15,710.14],"n_rows":15,"n_cols":5,"columns":["Specification","Proposed","Predicate Device:","Reference","Reference"],"rows":[["Specification","Proposed","Predicate Device:","Reference","Reference"],["","Device:","Overjet Caries","Device:","Device:"],["","Velmeni For","","Denti.AI","Second"],["","","Assist","",""],["","","","Detect",""],["","Dentists","K222746","","Opinion"],["","","","K230144",""],["","(V4D)","","","K210365"],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["Image\nModality","Radiograph","Radiograph","Radiograph","Radiograph"],["Intended\nUse","To aid in clinical\ndetection of\npathologic and/or\nnon-pathological\ndental features in\nradiographs of\npermanent teeth","To aid in clinical\ndetection of\npathologic\nand/or non-\npathological\ndental features\nin radiographs of\npermanent teeth","To aid in clinical\ndetection of\npathologic and/or\nnon-pathological\ndental features in\nradiographs of\npermanent teeth","To aid in clinical\ndetection of\npathologic and/or\nnon-pathological\ndental features in\nradiographs of\npermanent teeth"],["Indications","Velmeni for\nDentists (V4D) is\na concurrent-read,\ncomputer-assisted\ndetection software\nintended to assist\ndentist in the\nclinical detection\nof dental caries,\nfillings/\nrestorations, fixed\nprostheses, and\nimplants in digital\nbitewing,\nperiapical, and\npanoramic\nradiographs of\npermanent teeth\nin patients 15\nyears of age or\nolder. This device\nprovides\nadditional\ninformation for\ndentists in\nexamining\nradiographs of\npatients’ teeth.\nThis device is not\nintended as a\nreplacement for a\ncomplete\nexamination by\nthe dentist or their\nclinical judgment\nthat considers\nother relevant","The Overjet\nCaries Assist\n(OCA) is a\nradiological,\nautomated,\nconcurrent read,\ncomputer-\nassisted\ndetection\nsoftware intended\nto aid in the\ndetection and\nsegmentation of\ncaries on\nbitewing and\nperiapical\nradiographs. The\ndevice provides\nadditional\ninformation for\nthe dentist to use\nin their diagnosis\nof tooth surface\nsuspected of\nbeing carious.\nThe device is not\nintended as a\nreplacement for\ncomplete\ndentist’s review\nor their clinical\njudgment that\ntakes into\naccount other\nrelevant\ninformation from\nthe image,","Denti.AI Detect is\na Computer-\nAssisted\nDetection (CADe)\nsoftware device\nintended to be\nused by dental\nprofessionals,\ncomprising\ndentists and\ndental specialists,\nwhile reading\nextraoral and\nintraoral 2D\ndental\nradiographs. The\ndevice aims to\nassist in\ndetecting and\nhighlighting\nuncategorized\nregions of\ninterest (ROIs)\nwithin the teeth\narea, which\ninclude caries\nand periapical\nradiolucency, as\na second reader.\nThe device is\nalso intended to\naid in the\nmeasurements of\nmesial and distal\nbone levels\nassociated with\neach tooth. The\ndevice is aimed","Second\nOpinion® is a\ncomputer aided\ndetection\n(\"CADe”)\nsoftware to\nidentify and mark\nregions in\nrelation to\nsuspected dental\nfindings which\ninclude Caries,\nDiscrepancy at\nthe margin of an\nexisting\nrestoration,\nCalculus,\nPeriapical\nradiolucency,\nCrown (metal,\nincluding zirconia\n& non-metal),\nFilling (metal &\nnon- metal), Root\ncanal, Bridge,\nand Implants. It\nis designed to aid\ndental health\nprofessionals to\nreview bitewing\nand periapical\nradiographs of\npermanent teeth\nin patients 12\nyears of age or\nolder as a"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p7-t0","doc_id":"K240003","page_num":7,"bbox":[66.53,80.66,521.07,676.66],"n_rows":20,"n_cols":5,"columns":["Specification","Propos","Predicate Device:","Reference","Reference"],"rows":[["Specification","Propos","Predicate Device:","Reference","Reference"],["","ed","Overjet Caries","Device:","Device:"],["","Device:","","Denti.AI","Second"],["","","Assist","",""],["","Velmeni","","Detect",""],["","","K222746","","Opinion"],["","","","K230144",""],["","For","","","K210365"],["","","","",""],["","","","",""],["","Dentists","","",""],["","","","",""],["","(V4D)","","",""],["","information from\nthe image,\npatient history,\nor actual in vivo\nclinical\nassessment.\nFinal diagnosis\nand patient\ntreatment plans\nare the\nresponsibility of\nthe dentist.","patient history,\nand actual in vivo\nclinical\nassessment.","to be used with\nimages from the\npatients of 22\nyears age and\nolder without\nremaining\nprimary\ndentition. The\ndevice is not\nintended to\nreplace a\ncomplete\nclinician's review\nor clinical\njudgment that\nconsiders other\nrelevant\ninformation from\nthe image or\npatient history.","second reader."],["Intended\nBody Part","Dental/teeth","Dental/teeth","Dental/teeth","Dental/teeth"],["End User","Licensed\nDental\nProfessional","Dentist","Dental\nProfessional","Dental Clinicians"],["Patient Population","Patients requiring\ndental services,\nall sexes, at least\n15 years of age,\nand with\npermanent\ndentition","Patients requiring\ndental services,\nall sexes, at least\n12 years of age,\nand with\npermanent\ndentition","Patients\nrequiring dental\nservices, all\nsexes, at least\n22 years of age\nor older","Patients\nrequiring dental\nservices, all\nsexes, at least\n12 years of age\nor older"],["Prescriptio n\nor OTC","Prescription Use","Prescription Use","Prescription\nUse","Prescription Use"],["Reader\nWorkflow","Concurrent Read","Concurrent Read","Second Read","Second Read"],["Image\nSource","JPG, JPEG, PNG\nor DCM, DEX,\nand RVG","JPG, PNG, EOP,\nJIF, DICOM","JPEG, JPG,\nTIFF, TIF,\nPNG, BMP,\nDICOM","RVG, DICOM,\nJPEG, TIFF,\nPNG"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p8-t0","doc_id":"K240003","page_num":8,"bbox":[66.5,67.2,521.14,434.11],"n_rows":7,"n_cols":5,"columns":["Cloud\nHosted\nSoftware","Yes","Yes","Yes","Yes"],"rows":[["Cloud\nHosted\nSoftware","Yes","Yes","Yes","Yes"],["Data Input","Digital\nintraoral files\nof bitewing\nand periapical\nradiographs\nand digital\nextraoral files\nof panoramic\nradiograph","Digital files of\nbitewing and\nperiapical\nradiographs","Intraoral (bitewing\nand periapical)\nExtraoral\n(panoramic)","Digital intraoral\nfiles of bitewing\nand periapical\nradiographs"],["Model","Machine\nLearning","Machine\nLearning","Machine Learning","Machine\nLearning"],["Tooth Numbering","Yes","Yes","Unknown","Unknown"],["Detection","Caries,\nrestorations,\nfixed\nprostheses,\nand implants","Caries","Caries and\nperiapical\nradiolucency","Caries, margin\ndiscrepancy-MD,\ncalculus,\nperiapical\nradiolucency-PR,\ncrown, bridges,\nimplants, root\ncanals, and\nfillings"],["Segmentation","Yes","Yes","Regions of Interest\n(ROIs)","No"],["Bounding Boxes","Yes","Unknown","Unknown","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p10-t0","doc_id":"K240003","page_num":10,"bbox":[67.45,247.91,535.55,283.13],"n_rows":3,"n_cols":4,"columns":["Caries","","",""],"rows":[["Caries","","",""],["View","","Lesion-Level Sensitivity( 95% CI1 )",""],["Bitewing Views","","72.8% (68.0%, 77.4%)",""]],"caption_candidate":"Table 2, Lesion-Level Sensitivity for Caries","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p11-t0","doc_id":"K240003","page_num":11,"bbox":[66.5,67.44,562.3,428.83],"n_rows":15,"n_cols":4,"columns":["False Positives Per Image Mean (95% CI1)","","",""],"rows":[["False Positives Per Image Mean (95% CI1)","","",""],["Caries","0.24 [0.19, 0.29]","0.27 [0.22, 0.32]","0.33 [0.28, 0.38]"],["Fixed Prosthesis","0.03 [0.01, 0.05]","0.01 [0.00, 0.02]","0.06 [0.04, 0.08]"],["Implant","0.00 [0.00, 0.01]","0.00 [NA, NA]","0.01 [0.00, 0.02]"],["Restoration","0.15 [0.11, 0.19]","0.10 [0.07, 0.13]","0.62 [0.54, 0.70]"],["Case-level Specificity3 ( 95% CI1 )","","",""],["Caries","88.0% [84.4%, 91.2%]","84.7% [81.4%, 87.9%]","96.8% [94.6%, 98.6%]"],["Fixed Prosthesis","98.2% [96.4%, 99.7%]","99.7% [99.2%, 100.0%]","97.7%[96.0%, 99.2%]"],["Implant","100.0%[NA, NA]","100.0% [NA, NA]","100.0% [NA, NA]"],["Restoration","93.3% [89.1%, 96.9%]","95.1%[92.8%, 97.2%]","83.3% [75.0%, 90.6%]"],["DICE Score Mean (95% CI1)","","",""],["Caries","81.96% (80.81%, 83.10%)","82.77% (81.41%, 84.13%)","77.07% ( 76.25%, 77.89%)"],["Fixed Prosthesis","97.09% (96.84%, 97.33%)","96.23% (95.78%, 96.69%)","91.47% (91.24%, 91.71%)"],["Implant","94.20% (92.44%, 95.97%)","95.47% (94.60%, 96.34%)","88.67% (87.22%, 90.11%)"],["Restoration","90.45% (90.06%, 90.84%)","81% ( 88.97%, 90.64%)","81.49% (81.19%, 81.78%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p12-t0","doc_id":"K240003","page_num":12,"bbox":[60.25,403.97,564.33,700.18],"n_rows":19,"n_cols":11,"columns":["Assessment","Measure","","Results","","","","","","",""],"rows":[["Assessment","Measure","","Results","","","","","","",""],["","","","Aided (95% CI)","","","Unaided (95% CI)","","","Difference (95% CI)",""],["Bitewing","","","","","","","","","",""],["Caries","Lesion-Level Sensitivity","80.3%","","","67.5%","","","12.8% (9.9%, 15.9%)","",""],["","Mean FPs per Image","0.18","","","0.18","","","0.00 (-0.03, 0.03)","",""],["","Case-level Sensitivity","69.5%","","","51.5%","","","18.1% (13.7%, 22.5%)","",""],["","Case-level Specificity","85.7%","","","88.5%","","","-2.8% (-6.0%, 0.3%)","",""],["Fixed Prosthesis","Lesion-Level Sensitivity","95.7%","","","90.2%","","","5.5% (3.6%, 7.6%)","",""],["","Mean FPs per Image","0.04","","","0.13","","","-0.08 (-0.11, -0.05)","",""],["","Case-level Sensitivity","89.6%","","","82.7%","","","6.8% (3.0%, 10.6%)","",""],["","Case-level Specificity","97.9%","","","98.7%","","","-0.8% (-2.7%, 0.8%)","",""],["Implant","Lesion-Level Sensitivity","93.2%","","","61.3%","","","32.0% (21.4%, 41.3%)","",""],["","Mean FPs per Image","0.00","","","0.00","","","0.00 (-0.01, 0.00)","",""],["","Case-level Sensitivity","91.1%","","","59.2%","","","31.8% (21.2%, 42.9%)","",""],["","Case-level Specificity","100.0%","","","99.9%","","","0.1% (0.0%, 0.2%)","",""],["Restoration","Lesion-Level Sensitivity","90.8%","","","74.1%","","","16.7% (14.3%, 19.2%)","",""],["","Mean FPs per Image","0.15","","","0.29","","","-0.14 (-0.18, -0.09)","",""],["","Case-level Sensitivity","77.8%","","","52.7%","","","25.1% (21.3%, 29.1%)","",""],["","Case-level Specificity","92.5%","","","94.0%","","","-1.4% (-5.6%, 2.5%)","",""]],"caption_candidate":"Table 5 Sensitivity and Specificity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240003-p13-t0","doc_id":"K240003","page_num":13,"bbox":[60.24,67.38,564.33,626.5],"n_rows":36,"n_cols":11,"columns":["Assessment","Measure","","Results","","","","","","",""],"rows":[["Assessment","Measure","","Results","","","","","","",""],["","","","Aided (95% CI)","","","Unaided (95% CI)","","","Difference (95% CI)",""],["Periapical1","","","","","","","","","",""],["Caries","Lesion-Level Sensitivity","73.4%","","","48.7%","","","24.8% (19.8%, 29.8%)","",""],["","Mean FPs per Image","0.19","","","0.08","","","0.11 (0.08, 0.14)","",""],["","Case-level Sensitivity","59.0%","","","33.6%","","","25.5% (19.6%, 31.3%)","",""],["","Case-level Specificity","84.2%","","","94.5%","","","-10.3% (-13.0%, -7.6%)","",""],["Fixed Prosthesis","Lesion-Level Sensitivity","91.1%","","","80.0%","","","11.1% (8.0%, 14.5%)","",""],["","Mean FPs per Image","0.01","","","0.04","","","-0.02 (-0.03, -0.01)","",""],["","Case-level Sensitivity","82.7%","","","67.1%","","","15.7% (10.6%, 20.9%)","",""],["","Case-level Specificity","99.7%","","","99.5%","","","0.2% (-0.2%, 0.6%)","",""],["Implant","Lesion-Level Sensitivity","95.9%","","","79.5%","","","16.4% (12.7%, 20.3%)","",""],["","Mean FPs per Image","0.00","","","0.01","","","-0.01 (-0.01, 0.00)","",""],["","Case-level Sensitivity","93.8%","","","77.5%","","","16.3% (12.2%,21.0%)","",""],["","Case-level Specificity","99.9%","","","100.0%","","","-0.1% (-0.4%, 0.0%)","",""],["Restoration","Lesion-Level Sensitivity","90.6%","","","80.3%","","","10.3% (8.2%, 12.4%)","",""],["","Mean FPs per Image","0.07","","","0.05","","","-0.02 (0.00, 0.03)","",""],["","Case-level Sensitivity","83.9%","","","69.4%","","","14.5% (11.2%, 17.7%)","",""],["","Case-level Specificity","94.9%","","","97.6%","","","-2.7% (-4.9%, -0.8%)","",""],["Panoramic","","","","","","","","","",""],["Caries","Lesion-Level Sensitivity","27.2%","","","15.1%","","","6.5% (4.5%, 8.6%)","",""],["","Mean FPs per Image","0.21","","","0.30","","","-0.09 (-0.13, -0.06)","",""],["","Case-level Sensitivity","11.5%","","","8.5%","","","3.0% (0.6%, 5.5%)","",""],["","Case-level Specificity","95.1%","","","94.6%","","","0.5% (-1.7%, 2.4%)","",""],["Fixed Prosthesis","Lesion-Level Sensitivity","88.8%","","","80.5%","","","8.2% (6.1%, 10.3%)","",""],["","Mean FPs per Image","0.07","","","0.18","","","-0.10 (-0.13, -0.07)","",""],["","Case-level Sensitivity","70.5%","","","67.0%","","","3.5% (0.5%, 6.3%)","",""],["","Case-level Specificity","97.6%","","","99.0%","","","-1.4% (-2.8%, -0.1%)","",""],["Implant","Lesion-Level Sensitivity","88.3%","","","79.6%","","","8.7% (0.2%, 15.9%)","",""],["","Mean FPs per Image","0.01","","","0.01","","","0.00 (-0.01, 0.01)","",""],["","Case-level Sensitivity","77.1%","","","77.1%","","","0.0% (-10.4%, 10.0%)","",""],["","Case-level Specificity","100.0%","","","100.0%","","","0.0% (NA, NA)","",""],["Restoration","Lesion-Level Sensitivity","73.0%","","","57.4%","","","15.6% (14.3%, 16.9%)","",""],["","Mean FPs per Image","0.73","","","1.02","","","-0.29 (-0.37, -0.22)","",""],["","Case-level Sensitivity","26.7%","","","19.6%","","","7.1% (4.8%, 9.5%)","",""],["","Case-level Specificity","85.8%","","","96.2%","","","-10.4% (-16.5%, -4.8%)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240036-p5-t0","doc_id":"K240036","page_num":5,"bbox":[77.52,256.28,523.01,358.6],"n_rows":7,"n_cols":4,"columns":["","Trade Name","","PIUR tUS Infinity"],"rows":[["","Trade Name","","PIUR tUS Infinity"],["","Common Name","","PIUR tUS Infinity"],["","Classification Name","","Picture Archiving and Communications System"],["","Regulation","","21 CFR 892.2050"],["","Product Code","","QIH"],["","Regulatory Classification:","","Class II"],["","Device Panel:","","Radiology (OHT8)"]],"caption_candidate":"Table 2: Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240036-p5-t1","doc_id":"K240036","page_num":5,"bbox":[77.52,424.68,472.49,453.24],"n_rows":2,"n_cols":9,"columns":["","Predicate Device","","","Manufacturer","","","FDA 510(k)",""],"rows":[["","Predicate Device","","","Manufacturer","","","FDA 510(k)",""],["AmCAD-UT","","","AmCad BioMed Corporation","","","K203555","",""]],"caption_candidate":"Table 3: Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240036-p9-t0","doc_id":"K240036","page_num":9,"bbox":[72.08,247.56,535.53,691.05],"n_rows":6,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K203555)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K203555)",""],["","Product Name","","PIUR tUS Infinity","","","AmCAD-UT","",""],["","Manufacturer","","PIUR Imaging GmbH","","","AmCad BioMed Corporation","",""],["","Product Code /","","QIH / 21CFR 892.2050","","","QIH / 21CFR 892.2050","",""],["","Regulation","","","","","","",""],["Indications for\nUse","","","PIUR tUS Infinity is a computer-aided\ndetection device intended to assist and\nsupport the medical professionals in the\ndiagnostic workflow of thyroid and\nthyroid nodules acquired from FDA-\ncleared ultrasound systems, including\nimage documentation, analysis, and\nreporting. The device supports the\nphysician with additional information\nduring image review, including\nquantification and visualization of\nsonographic characteristics of thyroid\nnodules.\nPIUR tUS Infinity may be used on any\nadult patient aged 22 and older,\nindependent of gender, linguistic and\ncultural background, or health status,\nunless any of the contraindications\napply.\nPIUR tUS Infinity device is not\nintended for body contact (including\nskin, mucosal membrane, breached or\ncompromised surfaces, blood path\nindirect, tissues, bones, dentin, or\ncirculation blood).","","","AmCAD-UT is a Windows-based\ncomputer-aided detection (CADe)\ndevice intended to assist the medical\nprofessionals in analyzing thyroid\nultrasound images, acquired from\nFDA-cleared ultrasound systems.\nThe region of interest (ROI) of a\nuser-selected thyroid nodule is\ndefined by users or suggested by an\nAl contouring algorithm. After the\ninitial review of the ultrasound\nimages by the physicians, the device\nfurther provides detailed information\nwith quantification and visualization\nof sonographic characteristics of\nthyroid nodules. The device is\nintended for use on ultrasound\nimages of discrete thyroid nodules\nlarger than Icm, for which a biopsy\nrecommendation is required.","",""]],"caption_candidate":"Table 4: Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240036-p10-t0","doc_id":"K240036","page_num":10,"bbox":[72.08,81.36,535.54,713.61],"n_rows":14,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K203555)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K203555)",""],["Functional\nCapability of\nImage Processing","","","The device performs 2D to 3D\nreconstruction to generate volumetric\ndata of a thyroid. User-selected\ncomputer vision and machine learning\nalgorithm suggested volumes of thyroid\nlobe and nodules are visualized to be\nconfirmed by user. The system provides\na user interface for the user to manually\nselect sonographic characteristics of\neach nodule (hyperechoic foci,\nechogenicity, texture, margin,\norientation and anechoic areas) from\nwhich an ACR TI-RADS score will be\ncomputed.","","","AmCAD-UT analyzes the user-\ndefined or AI-suggested regions of\ninterest (ROI) of a user-selected\nthyroid nodule for detection and\nquantification of sonographic\ncharacteristics (hyperechoic foci,\nechogenicity, texture, margin,\norientation and anechoic areas). The\ndevice further provides detailed\ninformation with visualization of\nsonographic characteristics of\nthyroid nodules.","",""],["Reading\nParadigm","","","Device provides quantification and\nvisualization of sonographic\ncharacteristics based on 3D volumetric\ndata. Results provide proposals to be\nreviewed and confirmed by physicians.","","","AmCAD-UT is to provide\nquantification and visualization of\nsonographic characteristics after\nphysicians’ initial review of the\nimages.","",""],["Output Generated\nby the CAD\nDevice","","","The device can export volumetric data,\nannotated screenshots and reports.\nReport can contain both sides of the\npatient and includes all relevant\ndiagnostic information.","","","The image can be annotated with the\ndetected sonographic characteristics\nand be recorded by the device. The\nsoftware also automatically\ngenerates reports given the user\npreference inputs in the analysis\nprocess.","",""],["","Type of Film to be","","Digital ultrasound videoclip (cineloop)","","","Digital ultrasound image","",""],["","Processed by the","","","","","","",""],["","CAD Device","","","","","","",""],["Software Design","","","Based on computer vision, machine\nlearning, pattern recognition and\nquantification method.","","","Based on AI, Statistical Pattern\nRecognition and Quantification\nmethod","",""],["Ground Truth\nEstablishment","","","The ground truth to be established for\nperformance studies of the device are\nannotated data sets labeled by medical\nspecialists.","","","The ground truth to be established\nfor performance studies of the device\nis the ROI labeled by a panel of\nspecialists.","",""],["","Platform","","Windows-based","","","Same","",""],["","Operating System","","Standard PC or review station","","","Same","",""],["","Clinical","","Thyroid Lesions","","","Thyroid cancers","",""],["","Application","","","","","","",""],["","Image Type","","Ultrasound volume image","","","Ultrasound Image","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240036-p11-t0","doc_id":"K240036","page_num":11,"bbox":[72.08,81.36,535.54,549.78],"n_rows":17,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K203555)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K203555)",""],["Image Format","","","DICOM format:\nSecondary Capture Image Storage -\n1.2.840.10008.5.1.4.1.1.7\nMulti-frame Grayscale Byte Secondary\nCapture Image Storage -\n1.2.840.10008.5.1.4.1.1.7.2\nMulti-frame True Color Secondary\nCapture Image Storage -\n1.2.840.10008.5.1.4.1.1.7.4\nRefer to: DICOM-Conformance\nStatement-PIUR tUS Infinity","","","DICOM3.0, Bitmap, JPEG","",""],["","ROI","","Yes","","","Yes","",""],["","Quantification","","","","","","",""],["","Automatically","","Yes","","","Same","",""],["","Generating","","","","","","",""],["","Report","","","","","","",""],["","Performance","","Results from standalone performance\ntesting of machine learning algorithm\nsuggested ROIs of user-selected\nnodules","","","Results from standalone performance\ntesting of AI suggested ROI’s of\nuser-selected nodules","",""],["","Testing Data to","","","","","","",""],["","Support SE","","","","","","",""],["","Determination","","","","","","",""],["Device\nComponents","","","Infinity Box\nInfinity Sensor\nInfinity Software","","","N/A – Predicate is a software only\ndevice (SaMD)","",""],["","DICOM","","Yes","","","Same","",""],["","Compliance","","","","","","",""],["Data Acquisition","","","Acquires medical image data from\nDICOM compliant Ultrasound imaging\ndevices","","","Same","",""],["","Data / Image","","Ultrasound image via DICOM format","","","Same","",""],["","Types","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240094-p4-t0","doc_id":"K240094","page_num":4,"bbox":[99.36,473.11,414.48,756.12],"n_rows":22,"n_cols":2,"columns":["Company name:","Augmedit B.V."],"rows":[["Company name:","Augmedit B.V."],["",""],["Company owner:","Mrs. Claartje Ypma"],["",""],["Function:","CEO"],["",""],["Address:","Galerij 15, 1411 LH Na"],["",""],["Telephone:","+31 617 1010 94"],["",""],["Name of contact person:","Mr. Bryan Bhoelai"],["",""],["","Affairs &"],["Function:","Regulatory"],["","Manager"],["",""],["",""],["Email:","bryan@augmedit.com"],["",""],["Summary date:","September 10, 2024"],["",""],["Page 1 of","10"]],"caption_candidate":"Company name: Augmedit B.V.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240094-p7-t0","doc_id":"K240094","page_num":7,"bbox":[72.24,78.24,546.96,713.28],"n_rows":10,"n_cols":4,"columns":["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],"rows":[["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],["Device name","LumiNE US","VSI Holomedicine","N/A"],["510(k) number","K240094","K213215","N/A"],["Manufacturer","Augmedit B.V.","apoQlar GmbH","N/A"],["Medical specialty","Radiology","Radiology","Identical"],["CFR Reference","21 CFR 892.2050","21 CFR 892.2050","Identical"],["Device classification\nname","Medical Image management\nand Processing System","Medical Image management\nand Processing System","Identical"],["Common name","Automated Radiological\nImage Processing Software","Radiological Image Processing\nSystem","Substantially equivalent,\nthe subject device has a\nmore specific common\nname because of the\npresence of nonadaptive\nmachine learning\nalgorithms."],["Product code","QIH","LLZ","Substantially equivalent,\nthe subject device has a\nmore specific product code\nbecause of the presence of\nnonadaptive machine\nlearning algorithms."],["Intended use/\nIndications for use","The LumiNE US software is\nintended for the\nvisualization of medical\nimages to provide insights in\nanatomy and pathology in\npreparation of surgical\ntreatment. As such, the\nsoftware allows for the\nconversion of 2D patient\nimaging into 3D models, and\nfor the visualization of 2D\nand 3D patient imaging\nincluding Augmented Reality.\nWhen accessing the LumiNE\nUS software from a wireless\nhead-mounted display (HMD)\nor PC monitor, images\nviewed are for informational\npurposes only and not\nintended for diagnostic use.\nThe LumiNE US software is\nintended for use by a\n(neuro)surgeon,\n(neuro)surgical resident or a\nmedical professional that is\nqualified by a hospital to\nprepare medical imaging for\nsurgeons. For the conversion\nof medical imaging into 3D\nmodels, Magnetic Resonance\nImaging (MRI) and/or\nComputed Tomography (CT)\nimaging of adult patients are\nrequired. The LumiNE US\nsoftware is intended to be\nused for visualization in\npreparation of surgery, and\nnot for diagnostic use.\nTherefore, segmentation and\nvisualization of pathology\ncan only be used for\npreviously known and pre-\ndiagnosed conditions.\nLumiNE US can only be used\nfor contrast-enhanced T1 MR\nscans (semi-automatic\nsegmentation of known","VSI HoloMedicine® is a\nsoftware device for displaying\ndigital medical images\nacquired from CT, Angio CT,\nMRI, CBCT, PET, and SPECT\nsources. It is intended to\nvisualize 3D imaging\nholograms of the patient for\npre-operative planning outside\nand/or inside the surgical\nroom.\nWhen accessing VSI\nHoloMedicine® from a wireless\nhead-mounted display (HMD)\nor PC monitor, images viewed\nare for informational purposes\nonly and not intended for\ndiagnostic use. VSI\nHoloMedicine® is indicated for\nuse by qualified healthcare\nprofessionals including\nsurgeons, radiologists,\nphysicians, and technologists.","Substantially equivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240094-p8-t0","doc_id":"K240094","page_num":8,"bbox":[72.24,78.24,546.96,714.24],"n_rows":8,"n_cols":4,"columns":["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],"rows":[["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],["","tumor, skin, brain, and\nventricles), or for CT scans\n(threshold-based\nsegmentation).\nThe LumiNE US MRI T1\ntumor segmentation\nfunction can only be used in\ncase of a single intracranial\ncontrast enhancing tumor,\ndiagnosed by a\nneuroradiologist or a\nneurosurgeon, with a\nminimal volume of 2.0 cc (0.1\nin3) and a minimal diameter\nin any direction of 15 mm\n(0.6 inch), and a maximum\nvolume of 100cc (6.1 in3)\nand a maximal diameter in\nany direction of 75 mm (3.0\ninch).","",""],["Prescription use","Yes","Yes","Identical"],["Patient population","The device specifically\nfocuses on visualization of\nmedical images and\npreparation of surgical\ntreatment, for patients at\nthe age of 22 or older","The device is a software\nwhich allows for viewing of\nDICOM data. Therefore, its\nintended use is without any\nrestrictions regarding patient\npopulation","Different, but no impact on\nsafety and effectiveness."],["Main system\ncomponents","• Cloud based storage of\npatient data (including\nanonymizer) and viewer\n• Microsoft HoloLens 2\n• Browser based\n(universal) mobile device\nviewer","• Cloud based storage for\npatient data\n• Microsoft HoloLens 2\n• Streaming hardware hub\nto connect image\nmodalities directly to\nMicrosoft HoloLens 2\n• Anonymizer (for video’s)","Substantially equivalent"],["Imaging modality","• MRI\n• CT","• CT\n• angio CT\n• MRI\n• CBCT\n• PET CT\n• SPECT CT","Substantially equivalent,\nthe subject device uses MRI\nand CT imaging data, while\nthe predicate device allows\nto use a broader range of\nimaging modalities. Thus,\nthe predicate device allows\nto view more data types in\nthe HoloLens."],["Data Type Supported","• DICOM\n• 3D formats: STL GLTF\n• PDF\n• JPEG\n• PNG","• DICOM\n• 3D formats: OBJ, STL\n• PDF\n• JPEG\n• PNG\n• MP4","Substantially equivalent,\nboth the subject device as\nwell as the predicate device\nsupport DICOM imaging as\nwell as 3D format types.\nThe predicate device\nadditionally supports data\ntypes which allow video\nstreaming."],["","• 3D view in web browser","• General manipulation in\nHoloLens (grab, move,","Substantially equivalent:"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240094-p9-t0","doc_id":"K240094","page_num":9,"bbox":[72.24,78.24,546.96,692.64],"n_rows":7,"n_cols":4,"columns":["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],"rows":[["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],["Image\nview/manipulation","• Fusion of 3D objects\nwith source image data\n(web browser and\nMicrosoft HoloLens 2)\n• General manipulation in\nHoloLens (grab, move,\nzoom, hide, change color\netc.)\n• Surgical preparation\ntools which allow\nmarkings on 3D models\nin Microsoft HoloLens 2\n• Sharing (remote and co-\nlocated)","zoom, hide, change color\netc.)\n• Surgical Preparation Tools\n(draw, measure, etc).\n• Sharing (remote, but not\nco-located).","• Both the predicate\ndevice and Lumi enable\nmarking on 3D models\nin HMD for planning\npurposes.\n• Lumi allows for saving\nrevisions on 3D models\n(both web and\nMicrosoft HoloLens 2)\n• Lumi allows validation\nof 3D models."],["Communication\nbetween headset and\ncomputer","• Web browser (computer)\nand Microsoft HoloLens\n2 connect to cloud\nenvironment.\n• Wireless encrypted\nconnection with\nMicrosoft HoloLens 2.","• Web browser (computer)\nand Microsoft HoloLens 2\nconnect to cloud\nenvironment.\n• Wireless encrypted\nconnection with Microsoft\nHoloLens 2. Hardware to\nstream data from image\nacquisition system directly\nto Microsoft HoloLens 2.","Substantially equivalent,\nVSI uses additional\nhardware to connect to\nimage acquisition systems.\nCommunication for both\nthe subject as well as the\npredicate device is wireless,\nand data encrypted."],["MPR viewing","Yes, for CT, MRI","This viewing feature enables\nthe display of CT, MRI, CBCT,\nAngio CT, PET CT and SPECT CT\nimages into axial, coronal and\nsagittal orientations","Substantially equivalent for\nCT and MRI."],["3D Volume rendered\nviewing","• 3D volume rendering in\nweb browser.\n• Option to create manual\nsegmentation to\nvisualize results in\nMicrosoft HoloLens 2.","3D perspective views of CT,\nMRI, CBCT, Angio CT, PET CT\nand SPECT CT images sets that\nhave been transformed into\nvolumes. It also provides\npresets to enable users to alter\nthe visualization parameters\nof the 3D views to highlight\nfeatures.","Different, but no impact on\nsafety and effectiveness.\nBoth the subject as well as\npredicate device present 2D\nimaging information in 3D,\nhowever, the predicate\ndevice does not include\nimage segmentation\nfunctionality."],["Surgical planning","Creating and saving of 3D\nmodels and marks thereon\non HMD for planning\npurposes.","Saving and loading\nconfigurations of medical\nimages, marks, and 3D models\non HMD.\nAbility to save and load\ncombinations and\narrangement of objects\ndisplayed in the 3D space on\nHoloLens for planning\npurposes.\nPossibility to create\nannotation like drawings.","Substantially equivalent"],["Transmission modes","Web browser (computer) and\nMicrosoft HoloLens 2 connect\nvia wireless encrypted","Web browser (computer) and\nMicrosoft HoloLens 2 connect\nvia wireless encrypted","Substantially equivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240094-p10-t0","doc_id":"K240094","page_num":10,"bbox":[72.24,78.24,546.96,398.4],"n_rows":3,"n_cols":4,"columns":["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],"rows":[["Device\ncharacteristics","Subject device","Predicate device","Comparison analysis"],["","connection to cloud\nenvironment.","connection to cloud\nenvironment.",""],["Verification and\nvalidation","Software verification and\nvalidation was performed\nand demonstrates that the\nLumiNE US software\nperforms as intended in the\nspecified use conditions.\nDocumentation is provided\nas recommended by FDA’s\nGuidance for Industry and\nFDA Staff ‘Content of\nPremarket Submissions for\nDevice Software Functions’.\nIn addition, non-clinical\ntesting was performed to\nevaluate the performance of\nthe semi-automated\nsegmentation algorithm\nagainst manual\nsegmentation data.\nVisual quality testing on\nsoftware using the Microsoft\nHoloLens 2 Head-Mounted\nDisplay has been performed.\nNon-clinical and clinical data\ndemonstrate that the\nLumiNE US software is as\nsafe, as effective, and\nperforms as well as the\nlegally marketed device\npredicate.","Visual quality testing on\nsoftware using the Microsoft\nHoloLens Headset has been\nperformed.\nNon-clinical and clinical data\ndemonstrate that VSI\nHolomedicine is as safe, as\neffective, and performs as well\nas the legally marketed device\npredicate. Software\nverification and validation\ndemonstrate that the VSI\nHolomedicine should perform\nas intended in the specified\nuse conditions.","Substantially equivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240172-p5-t0","doc_id":"K240172","page_num":5,"bbox":[72.29,569.21,539.84,709.66],"n_rows":9,"n_cols":8,"columns":["Characteristic","","Proposed Device","","","Predicate Device","","Significant Differences"],"rows":[["Characteristic","","Proposed Device","","","Predicate Device","","Significant Differences"],["","","Genesis Software","","","Genesis Software","",""],["","","Innovations","","","Innovations","",""],["","","Preview Shoulder","","","Preview Shoulder","",""],["","","(K240172)","","","(K210556)","",""],["Product Code","QIH","","","QIH","","","N/A"],["Regulation\nNumber","21 CFR 892.2050","","","21 CFR 892.2050","","","N/A"],["Intended Use","Preoperative planning\nsoftware for surgery","","","Preoperative planning\nsoftware for surgery","","","N/A"],["Indications for\nuse","The Preview Shoulder\nsoftware is intended to be","","","The Preview Shoulder\nsoftware is intended to be","","","N/A"]],"caption_candidate":"the predicate device as noted in the following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240172-p6-t0","doc_id":"K240172","page_num":6,"bbox":[72.26,72.24,539.86,696.82],"n_rows":7,"n_cols":4,"columns":["","used as a tool for\northopedic surgeons to\ndevelop pre-operative\nshoulder plans based on\na patient CT imaging\nstudy.\nThe import process allows\nthe user to select a\nDICOM CT scan series\nfrom any location that the\nuser’s computer sees as\nan available file source.\n3D digital representations\nof various implant models\nare available in the\nplanning software.\nPreview Shoulder allows\nthe user to digitally\nperform the surgical\nplanning by showing a\nrepresentation of the\npatient’s shoulder\nanatomy as a 3D model\nand allows the surgeon to\nplace the implant in the\npatient’s anatomy.\nThe software allows the\nsurgeon to generate a\nreport, detailing the output\nof the planning activity.\nExperience in usage and\na clinical assessment are\nnecessary for a proper\nuse of the software. It is\nto be used for adult\npatients only and should\nnot be used for diagnostic\npurposes.","used as a tool for\northopedic surgeons to\ndevelop pre-operative\nshoulder plans based on\na patient CT imaging\nstudy.\nThe import process allows\nthe user to select a\nDICOM CT scan series\nfrom any location that the\nuser’s computer sees as\nan available file source.\n3D digital representations\nof various implant models\nare available in the\nplanning software.\nPreview Shoulder allows\nthe user to digitally\nperform the surgical\nplanning by showing a\nrepresentation of the\npatient’s shoulder\nanatomy as a 3D model\nand allows the surgeon to\nplace the implant in the\npatient’s anatomy.\nThe software allows the\nsurgeon to generate a\nreport, detailing the output\nof the planning activity.\nExperience in usage and\na clinical assessment are\nnecessary for a proper\nuse of the software. It is\nto be used for adult\npatients only and should\nnot be used for diagnostic\npurposes.",""],"rows":[["","used as a tool for\northopedic surgeons to\ndevelop pre-operative\nshoulder plans based on\na patient CT imaging\nstudy.\nThe import process allows\nthe user to select a\nDICOM CT scan series\nfrom any location that the\nuser’s computer sees as\nan available file source.\n3D digital representations\nof various implant models\nare available in the\nplanning software.\nPreview Shoulder allows\nthe user to digitally\nperform the surgical\nplanning by showing a\nrepresentation of the\npatient’s shoulder\nanatomy as a 3D model\nand allows the surgeon to\nplace the implant in the\npatient’s anatomy.\nThe software allows the\nsurgeon to generate a\nreport, detailing the output\nof the planning activity.\nExperience in usage and\na clinical assessment are\nnecessary for a proper\nuse of the software. It is\nto be used for adult\npatients only and should\nnot be used for diagnostic\npurposes.","used as a tool for\northopedic surgeons to\ndevelop pre-operative\nshoulder plans based on\na patient CT imaging\nstudy.\nThe import process allows\nthe user to select a\nDICOM CT scan series\nfrom any location that the\nuser’s computer sees as\nan available file source.\n3D digital representations\nof various implant models\nare available in the\nplanning software.\nPreview Shoulder allows\nthe user to digitally\nperform the surgical\nplanning by showing a\nrepresentation of the\npatient’s shoulder\nanatomy as a 3D model\nand allows the surgeon to\nplace the implant in the\npatient’s anatomy.\nThe software allows the\nsurgeon to generate a\nreport, detailing the output\nof the planning activity.\nExperience in usage and\na clinical assessment are\nnecessary for a proper\nuse of the software. It is\nto be used for adult\npatients only and should\nnot be used for diagnostic\npurposes.",""],["Subspecialties","Preview Shoulder allows\nthe surgeon to perform\nthe pre-surgical planning\nfor the following\nsubspeciality:\nUpper Limb: Total\nShoulder Replacement","Preview Shoulder allows\nthe surgeon to perform\nthe pre-surgical planning\nfor the following\nsubspeciality:\nUpper Limb: Total\nShoulder Replacement","N/A"],["Type of Use","Prescription Only","Prescription Only","N/A"],["Patient\nPopulation","Adults","Adults","N/A"],["End User","Surgeons","Surgeons","N/A"],["Computer","Personal Computer or\nWorkstation","Personal Computer or\nWorkstation","N/A"],["Operating\nSystem","Windows or MacOS","Windows or MacOS","N/A"]],"caption_candidate":"K240172","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240172-p7-t0","doc_id":"K240172","page_num":7,"bbox":[72.26,72.24,539.86,697.78],"n_rows":9,"n_cols":4,"columns":["Device\nAvailability","The software is installed\nand started from the\nuser’s computer.","The software is installed\nand started from the\nuser’s computer.","N/A"],"rows":[["Device\nAvailability","The software is installed\nand started from the\nuser’s computer.","The software is installed\nand started from the\nuser’s computer.","N/A"],["Images source","Receives medical images\nfrom various sources\nlocally available to the\nuser’s computer.\nPreview Shoulder does\nnot communicate directly\nto a PACS system.","Receives medical images\nfrom various sources\nlocally available to the\nuser’s computer.\nPreview Shoulder does\nnot communicate directly\nto a PACS system.","N/A"],["Data\nprocessing","The software processes\nthe CT image, which\nallows the implant to be\noverlapped/ placed in\nboth the original scan\nimages and/or the 3D\nmodel reconstruction of\nthe bone for surgical\nplanning.","The software processes\nthe CT image, which\nallows the implant to be\noverlapped/ placed in\nboth the original scan\nimages and/or the 3D\nmodel reconstruction of\nthe bone for surgical\nplanning.","Similar\nPost-processing algorithm\nis added to further refine\nthe 3D mesh quality.\nAlgorithm is added to\ncalculate humerus-side\nfeatures used for implant\nselection, placement, and\npre-surgical planning."],["Digital overlap\nof\nprosthetic\nmaterial","The software allows the\nimplant rendering to be\noverlapped/placed in the\n3D model reconstruction\nof the bone that results\nfrom the processed CT\nimage(s).\nThe software facilitates\nthe placement and\nrendering of scapula and\nhumerus implants for\nanatomic partial or total\nshoulder arthroplasty and\nreverse total shoulder\narthroplasty.","The software allows the\nimplant rendering to be\noverlapped/placed in the\n3D model reconstruction\nof the bone that results\nfrom the processed CT\nimage(s).\nThe software facilitates\nthe placement and\nrendering of scapula\nimplants for anatomic\npartial or total shoulder\narthroplasty and reverse\ntotal shoulder\narthroplasty.","Similar\nHumerus implants are\nadded to implant planning\nlibrary."],["Interactive\nmodel\npositioning","Yes","Yes","N/A"],["Interactive\nmodel\ndimensioning","Yes","Yes","N/A"],["Model rotation","Yes","Yes","N/A"],["Support for\ndigital\nprosthetic\nmaterials\nprovided by\nthe\nmanufacturers","Yes","Yes","N/A"],["Automatic\nCalibration","No","No","N/A"]],"caption_candidate":"K240172","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240172-p8-t0","doc_id":"K240172","page_num":8,"bbox":[72.26,72.24,539.86,247.22],"n_rows":5,"n_cols":4,"columns":["Pre-surgical\nplanning","Yes","Yes","N/A"],"rows":[["Pre-surgical\nplanning","Yes","Yes","N/A"],["Contact with\nthe patient","No","No","N/A"],["Control of life\nsupporting\ndevices","No","No","N/A"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","N/A"],["Ability to add\nadditional\nmodules when\navailable","Yes","Yes","N/A"]],"caption_candidate":"K240172","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240238-p5-t0","doc_id":"K240238","page_num":5,"bbox":[93.44,237.56,527.1,317.15],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Fortian / Orian 1.5T, MRT-1550, V9.0 with AiCE\nReconstruction Processing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240238-p6-t0","doc_id":"K240238","page_num":6,"bbox":[90.26,547.63,554.14,619.78],"n_rows":5,"n_cols":3,"columns":["System","Predicate Device","Reference Device"],"rows":[["System","Predicate Device","Reference Device"],["","Vantage Fortian/Orian 1.5T, MRT-1550, V8.0 with\nAiCE Reconstruction Processing Unit for MR","Vantage Galan 3T, MRT-1550, V9.0 with AiCE\nReconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc.","Canon Medical Systems USA, Inc."],["510(k) Number","K222968","K230355"],["Clearance Date","October 25, 2022","August 30, 2023"]],"caption_candidate":"(K230355)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240238-p8-t0","doc_id":"K240238","page_num":8,"bbox":[95.08,353.09,558.68,617.98],"n_rows":12,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Fortian/Orian 1.5T,","","","Vantage Fortian/Orian 1.5T,","",""],["","","MRT-1550, V9.0","","","MRT-1550, V8.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR","",""],["Static field strength","1.5T","","","1.5T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240290-p5-t0","doc_id":"K240290","page_num":5,"bbox":[36.5,130.5,559.5,686.5],"n_rows":20,"n_cols":2,"columns":["DateSummary Prepared:","2024-08-20"],"rows":[["DateSummary Prepared:","2024-08-20"],["Contact Details",""],["Applicant Name:","Subtle Medical,Inc."],["Applicant Address:","883SantaCruz Ave,Suite205\nMenlo Park, CA94025UnitedStates"],["Applicant Contact:","Ms.RonnyElor"],["Applicant ContactTelephone:","(925) 324-8467"],["Applicant ContactEmail:","ronny@subtlemedical.com"],["Correspondent Name:","EnzymeCorporation"],["Correspondent Address:","611GatewayBlvd, Ste120\nSouth SanFrancisco,CA 94080 UnitedStates"],["Correspondent Contact:","Mr.Jared Seehafer"],["Correspondent ContactTelephone:","(415) 638-9554"],["Correspondent ContactEmail:","jared@enzyme.com"],["Device Name",""],["Device TradeName:","AiMIFY (1.x)"],["Common Name:","Medicalimagemanagementand processingsystem"],["Classification Name:","System, ImageProcessing, Radiological"],["Regulation Number:","892.2050"],["Product Code:","LLZ"],["Device Class:","ClassII"],["Legally MarketedPredicate\nDevice:","Predicate #:K223623\nPredicate TradeName: SubtleMR\nPredicate Manufacturer:Subtle Medical"]],"caption_candidate":"Table 1.ContactDetails &Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240290-p7-t0","doc_id":"K240290","page_num":7,"bbox":[72.5,153.5,576.5,709.5],"n_rows":10,"n_cols":3,"columns":["Topic","PredicateDevice","SubjectDevice"],"rows":[["Topic","PredicateDevice","SubjectDevice"],["Physical\nCharacteristics","Softwarepackagethatoperatesonoff-the-shelf\nhardware","Same"],["DICOM\nStandard\nCompliance","ThesoftwareprocessesDICOMcompliant\nimagedata","Same"],["Operating\nSystem","Linux","Same"],["Modalities","MRI","Same"],["UserInterface","None–enhancedimagesareviewedon\nexistingPACSworkstations","Same"],["Workflow","ThesoftwareoperatesonDICOMfilesonthe\nfilesystem,enhancestheimages,andstores\ntheenhancedimagesonthefilesystem.The\nreceiptoforiginalDICOMimagefilesand\ndeliveryofenhancedimagesasDICOMfiles\ndependsonothersoftwaresystems.Enhanced\nimagesco-existwiththeoriginalimages.","Same"],["Algorithm","SubtleMRimplementsanimageenhancement\nalgorithmusingconvolutionalneuralnetwork\nbasedfiltering.Originalimagesareenhanced\nbyrunningthroughacascadeoffilterbanks,\nwherethresholdingandscalingoperationsare\napplied.Separateneuralnetworkbasedfilters\nareobtainedfornoisereductionandsharpness\nincrease.Theparametersofthefilterswere\nobtainedthroughanimage-guided\noptimizationprocess.","AiMIFYimplementsanimage\nenhancementalgorithmusing\nconvolutionalneuralnetworkbased\nfiltering.Themodelperformsnon-linear\nscalingofthecontrastuptakebetweenthe\npre-andpost-contrastimagestoimprove\nthevisualizationoftheareasinthebrain\nthathaveabsorbedthecontrastmaterial."],["Inputs","SubtleMRprocessesasingleinputimage(with\nlowSNRorlowresolution)andoutputsa\nsingleimagewithhigherSNRorresolution.","AiMIFYprocessestwoinputimages(T1\npre-contrastandT1post-contrast)and\noutputsasingleimagewithahigher\nrelativeCNR."],["Processing","SubtleMRprocessestheinputimagesliceby\nsliceina2DfashionusingaResNETstyle\nneuralnetwork.","AiMIFYprocessestheinputimageina\n2.5DfashionusingaUNetstyleneural\nnetwork."]],"caption_candidate":"Table 2.Summary ofTechnological CharacteristicsComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240291-p4-t0","doc_id":"K240291","page_num":4,"bbox":[72.0,129.49,493.28,751.83],"n_rows":53,"n_cols":2,"columns":["1. General Informatio","n"],"rows":[["1. General Informatio","n"],["",""],["510(k)Sponsor","EverFortune.AICo.,Ltd."],["",""],["Address","Rm.D,8F.No.573,Sec.2TaiwanBlvd."],["","WestDist."],["","TaichungCity403020"],["","TAIWAN"],["",""],["Applicant","JosephChang"],["",""],["ContactInformation","886-04-23213838#216"],["","joseph.chang@everfortune.ai"],["",""],["CorrespondencePerson","Ti-HaoWang"],["",""],["ContactInformation","886-04-23213838#168"],["","thothwang@gmail.com"],["",""],["","tihao.wang@everfortune.ai"],["",""],["DatePrepared","January,2024"],["",""],["2. Proposed Device",""],["",""],["ProprietaryName","EFAI CARDIOSUITE CTA ACUTE AORTIC SYN"],["","ASSESSMENTSYSTEM"],["",""],["CommonName","EFAIAASCTA"],["",""],["ClassificationName","Radiologicalcomputeraidedtriageandnotificationsoftware"],["",""],["RegulationNumber","21CFR892.2080"],["",""],["ProductCode","QAS"],["",""],["RegulatoryClass","II"],["",""],["3. Predicate Device",""],["",""],["ProprietaryName","BriefCase"],["",""],["PremarketNotification","K222329"],["",""],["ClassificationName","Radiologicalcomputeraidedtriageandnotificationsoftware"],["",""],["RegulationNumber","21CFR892.2080"],["",""],["ProductCode","QAS"],["",""],["RegulatoryClass","II"],["",""],["EFAIAASCTATraditional510(k)",""]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240291-p4-t1","doc_id":"K240291","page_num":4,"bbox":[66.07,398.39,539.5,509.39],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME\nASSESSMENTSYSTEM"],"rows":[["ProprietaryName","EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME\nASSESSMENTSYSTEM"],["CommonName","EFAIAASCTA"],["ClassificationName","Radiologicalcomputeraidedtriageandnotificationsoftware"],["RegulationNumber","21CFR892.2080"],["ProductCode","QAS"],["RegulatoryClass","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240291-p4-t2","doc_id":"K240291","page_num":4,"bbox":[66.07,556.45,539.5,655.45],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","BriefCase"],"rows":[["ProprietaryName","BriefCase"],["PremarketNotification","K222329"],["ClassificationName","Radiologicalcomputeraidedtriageandnotificationsoftware"],["RegulationNumber","21CFR892.2080"],["ProductCode","QAS"],["RegulatoryClass","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240291-p5-t0","doc_id":"K240291","page_num":5,"bbox":[73.5,640.84,537.63,730.5],"n_rows":2,"n_cols":3,"columns":["Feature/\nFunction","ProposedDevice:\nEFAIAASCTA\n(K240291)","PredicateDevice:\nBriefCase\n(K222329)"],"rows":[["Feature/\nFunction","ProposedDevice:\nEFAIAASCTA\n(K240291)","PredicateDevice:\nBriefCase\n(K222329)"],["Intended\nUse/Indication\nforUse","EFAI CARDIOSUITE CTA\nACUTE AORTIC SYNDROME\nASSESSMENT SYSTEM (EFAI","BriefCase is a radiological\ncomputer-aided triage and notification\nsoftware indicated for use in the analysis"]],"caption_candidate":"6. Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240291-p6-t0","doc_id":"K240291","page_num":6,"bbox":[73.5,89.5,537.5,726.5],"n_rows":7,"n_cols":3,"columns":["","AASCTA) is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of chest or\nchest-abdomen CTA in adults aged\n22 and older. The device is\nintended to assisthospitalnetworks\nand appropriately trained medical\nspecialists in workflow triage by\nflagging and communicating\nsuspected positive cases of aortic\ndissection(AD)oraorticintramural\nhematoma(IMH)pathology.\nEFAI AASCTA uses an artificial\nintelligence algorithm to identify\nsuspected findings. It makes\ncase-level output available to a\nPACS/workstation for worklist\nprioritization or triage. EFAI\nAASCTA is not intended to direct\nattention to specific portions or\nanomalies of an image. Its results\nare not intended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it intended\nto rule out AAS or otherwise\npreclude clinical assessment of\ncomputed tomographyangiography\ncases.","of CT exams with contrast (CTA and CT\nwith contrast) that include the chest in\nadults or transitional adolescents aged 18\nand older. Thedeviceisintendedtoassist\nhospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communicating\nsuspected positive cases of aortic\ndissection (AD) pathology. BriefCase\nuses an artificial intelligencealgorithmto\nanalyze images and highlight cases with\ndetected findings on a standalone\napplication in parallel to the ongoing\nstandard ofcareimageinterpretation.The\nuser is presented with notifications for\ncases with suspected findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device doesnotalterthe\noriginal medical image and is not\nintended to be used as a diagnostic\ndevice. The results of BriefCase are\nintended to be used in conjunction with\nother patient information and based on\nthe user's professional judgment, toassist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images per\nthestandardofcare."],"rows":[["","AASCTA) is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of chest or\nchest-abdomen CTA in adults aged\n22 and older. The device is\nintended to assisthospitalnetworks\nand appropriately trained medical\nspecialists in workflow triage by\nflagging and communicating\nsuspected positive cases of aortic\ndissection(AD)oraorticintramural\nhematoma(IMH)pathology.\nEFAI AASCTA uses an artificial\nintelligence algorithm to identify\nsuspected findings. It makes\ncase-level output available to a\nPACS/workstation for worklist\nprioritization or triage. EFAI\nAASCTA is not intended to direct\nattention to specific portions or\nanomalies of an image. Its results\nare not intended to be used on a\nstand-alone basis for clinical\ndecision-making nor is it intended\nto rule out AAS or otherwise\npreclude clinical assessment of\ncomputed tomographyangiography\ncases.","of CT exams with contrast (CTA and CT\nwith contrast) that include the chest in\nadults or transitional adolescents aged 18\nand older. Thedeviceisintendedtoassist\nhospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communicating\nsuspected positive cases of aortic\ndissection (AD) pathology. BriefCase\nuses an artificial intelligencealgorithmto\nanalyze images and highlight cases with\ndetected findings on a standalone\napplication in parallel to the ongoing\nstandard ofcareimageinterpretation.The\nuser is presented with notifications for\ncases with suspected findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device doesnotalterthe\noriginal medical image and is not\nintended to be used as a diagnostic\ndevice. The results of BriefCase are\nintended to be used in conjunction with\nother patient information and based on\nthe user's professional judgment, toassist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images per\nthestandardofcare."],["Userpopulation","Hospital networks and\nappropriately trained medical\nspecialists","Hospital networks and appropriately\ntrainedmedicalspecialists"],["Anatomical\nregionofinterest","Chestandthoracoabdominal","Chest,abdomenandthoracoabdominal"],["Dataacquisition\nprotocol","chestorchest-abdomenCTA","CT exams with contrast (CTA and CT\nwithcontrast)thatincludethechest"],["Notification-only\n(notification\nalerts),parallel\nworkflowtool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interferencewith\nstandard\nworkflow","No","No"]],"caption_candidate":"---.- F9RTUNE.AI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p7-t0","doc_id":"K240294","page_num":7,"bbox":[52.42,67.92,774.41,497.02],"n_rows":6,"n_cols":15,"columns":["Specification","","","Subject Device","","","Predicate Device","","","Comparison","","","","Impact to Safety &",""],"rows":[["Specification","","","Subject Device","","","Predicate Device","","","Comparison","","","","Impact to Safety &",""],["","","","","","","","","","","","","","Effectiveness",""],["","Device name","","","Syngo Carbon Enterprise Access","","","Syngo Carbon Space VA30A","","","New version of the","","NA","NA",""],["","and version","","","VA40A","","","(K230561)","","","product","","","",""],["","Manufacturer","","","Siemens Healthcare GmbH","","","Siemens Healthcare GmbH","","","Same","","","NA",""],["Indications for\nuse","","","Syngo Carbon Enterprise Access is\nindicated for display and rendering of\nmedical data within healthcare\ninstitutions.","","","Syngo Carbon Space is a software\nintended to display medical data and to\nsupport the review and analysis of\nmedical images by trained medical\nprofessionals.\nSyngo Carbon Space \"Diagnostic\nWorkspace\" is indicated for display,\nrendering, post-processing of medical\ndata (mostly medical images) within\nhealthcare institutions, for example, in\nthe field of Radiology, Nuclear\nMedicine and Cardiology.\nSyngo Carbon Space \"Physician\nAccess\" is indicated for display and\nrendering of medical data within\nhealthcare institutions.","","","Same","","","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p8-t0","doc_id":"K240294","page_num":8,"bbox":[52.36,67.92,774.45,497.62],"n_rows":5,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Contraindicatio\nns","Syngo Carbon Enterprise Access is\nnot intended for the diagnosis of\ndigital mammography images and\ndigital pathology reading.\nSyngo Carbon Enterprise Access is\nnot intended to be used for diagnostic\npurpose on mobile devices in the\nUnited States of America (USA).\nSyngo Carbon Enterprise Access is\nnot intended to be used as a sole basis\nfor clinical decisions.","Syngo Carbon Space \"Diagnostic\nWorkspace\" is not intended for\ndiagnosis of digital mammography\nimages.\nSyngo Carbon Space \"Diagnostic\nWorkspace\" is not intended to be used\nas a sole basis for clinical decisions.\nSyngo Carbon Space \"Physician\nAccess\" is not intended for diagnosis\nof digital mammography images.\nSyngo Carbon Space \"Physician\nAccess\" is not intended to be used for\ndiagnostic purpose on mobile devices\nin the United States of America\n(USA).\nSyngo Carbon Space \"Physician\nAccess\" is not intended to be used as\na sole basis for clinical decisions.","Same","NA","",""],["Software\narchitecture","Syngo Carbon Enterprise Access is\nbased on a client-server architecture","Syngo Carbon Space is based on a\nclient-server architecture","Same","NA","",""],["Image\ncommunication","Standard network protocols like\nTCP/IP and standard communication\nprotocol including DICOM (2016a)\nand non-DICOM objects.","Standard network protocols like\nTCP/IP and standard communication\nprotocol including DICOM (2016a)\nand non-DICOM objects. Supports\ninterfacing with HL7 (v2.5 / v2.3.1 /\nv2.3 / FHIR R4).","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p9-t0","doc_id":"K240294","page_num":9,"bbox":[52.39,67.92,774.43,253.37],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Image display\nalgorithms","• MPR: MPR\n• MIP: MIP,\n• MinIP View\n• AVG\n• MED\n• Invert Image","• MPR: MPR, MPR Thick,\nMPR/MPR*\n• MIP: MIP, MIP Thin\n• MinIP View\n• VRT*: Plain VRT, Adapt VRT,\nVRT Thin, Cinematic VRT\n• Fused View *\n• Invert Image\n* available in in Diagnostic\nWorkspace only","The additional AVG\nand MED are non\nAI/ML Algorithms","This differences\nbetween the\npredicate device and\nthe subject device\ndoesn’t impact the\nsafety and\neffectiveness of the\nsubject device as the\nnecessary measures\ntaken","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p10-t0","doc_id":"K240294","page_num":10,"bbox":[52.39,67.92,774.43,485.38],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Measurement,\nEvaluation/Inte\nrpretation\nTools","• Distance (Distance line)\n• Pixel Lens\n• Angle\n• Elipse Annotation\n• Polygon\n• Freehand\n• Capture","• Distance (Distance line, Distance\nPolyline)\n• Angle and Angle on stack*\n• 2D ROI (Circle, Freehand,\nPolygonal, Auto Contour) *\n• 3D VOI (Sphere, Freehand) *\n• Pixel Lens\n• Ranges (Parallel, Radial, Radial\nSliced, Curved, Spine) *\n• Lesion Quantification*\n• Assisted Perpendicular Tool*\n• Automatic Organ Segmentation*\n• Interactive Tissue Segmentation*\n• Time Curve, Time ROI*\n• SUV Measurement*\n• Automatic Anatomy Labeling\n(rib, spine) *\n• Next Study/Previous\nStudy/Nearline study*\n• Change Geometry*\n• Snapshot\n• CT Lung Change*\n• MR General Reading*\n• Alpha Blending*\n* Available in in Diagnostic\nWorkspace only","The tool set in the\nsubject device is\nenhanced.","This differences\nbetween the\npredicate device and\nthe subject device\ndoesn’t impact the\nsafety and\neffectiveness of the\nsubject device as the\nnecessary measures\ntaken","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p11-t0","doc_id":"K240294","page_num":11,"bbox":[56.88,37.54,492.23,559.28],"n_rows":37,"n_cols":6,"columns":["","","©S","iem","ens Healthcare Gmb","H, 2024"],"rows":[["","","©S","iem","ens Healthcare Gmb","H, 2024"],["","","","","",""],["","","","","",""],["Supported D","ICO","M image object display: D","ICO","M image object di","splay:"],["","","","","",""],["objects","•","CR Image","•","CR Image",""],["for display","•","CT Image","•","CT Image",""],["","•","DX Image","•","DX Image",""],["","•","ES Image","•","ES Image",""],["","•","GM Image","•","GM Image",""],["","•","MG Image","•","MG Image",""],["","•","MR Image","•","MR Image",""],["","•","NM Image","•","NM Image",""],["","•","PET Image","•","PET Image",""],["","•","OP/OPT Image","•","OP/OPT Image",""],["","•","RF Image","•","RF Image",""],["","•","RT IMAGE","•","RT IMAGE",""],["","•","SM (WSI)","•","SM (WSI)",""],["","•","XA Image","•","XA Image",""],["","•","US Image","•","US Image",""],["","•","Secondary capture objects","•","Secondary capture","objects"],["","","","","",""],["D","ICO","M non-image object display: D","ICO","M non-image obje","ct disp"],["","•","ECG","•","ECG",""],["","•","Encapsulated PDF","•","Encapsulated PDF",""],["","•","PR","•","PR",""],["","","","","",""],["N","on-","DICOM file display: N","on-","DICOM file displa","y:"],["","•","Images: BMP, GIF, JPEG","•","Images: BMP, GIF",", JPEG"],["","","(JFIF), JPEG 2000, JPEG-LE,","","(JFIF), JPEG 2000,","JPEG-"],["","","JPEG-LS, PCX, PNG, PNM,","","JPEG-LS, PCX, PN","G, PN"],["","","TIFF, WBMP","","TIFF, WBMP",""],["","•","Video: FLV, H.264, H.265,","•","Video: FLV, H.264",", H.26"],["","","INDEO2, INDEO3, INDEO4,","","INDEO2, INDEO3",", INDE"],["","","MPEG1, MPEG2, MPEG4,","","MPEG1, MPEG2,","MPEG"],["","","","","",""],["Page -8","","","","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240294-p12-t0","doc_id":"K240294","page_num":12,"bbox":[52.39,67.92,774.43,152.42],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["","VP8, VP9, WMV1, WMV2,\nWMV3\nText Documents: CDA (XML), PDF","VP8, VP9, WMV1, WMV2,\nWMV3\n• Text Documents: CDA (XML),\nPDF","","","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p12-t1","doc_id":"K240294","page_num":12,"bbox":[169.92,96.75,402.9,152.13],"n_rows":6,"n_cols":2,"columns":["VP8, VP9, WMV1, WMV2,","VP8, V"],"rows":[["VP8, VP9, WMV1, WMV2,","VP8, V"],["WMV3","WMV3"],["",""],["•\nDocuments: CDA (XML), PDF","Text Do"],["",""],["","PDF"]],"caption_candidate":"Effectiveness","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240294-p14-t0","doc_id":"K240294","page_num":14,"bbox":[52.34,67.92,774.46,471.58],"n_rows":8,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["","","Client – Mobile device\niPadOS ≥ 14, Safari web browser","","","",""],["Impact on\nImage\nAcquisition\nDevices","None\nSyngo Carbon Enterprise Access is a\npure viewing software and it has no\ninfluence on the image acquisition\ndevices.","None\nSyngo Carbon Space is a pure\nviewing and/or post-processing\nsoftware and it has no influence on\nthe image acquisition devices.","Same","NA","",""],["CAD\nFunctionalities","None\nNo automated diagnostic\ninterpretation capabilities like CAD\nare included. All image data are to be\ninterpreted by trained personnel.","None\nNo automated diagnostic\ninterpretation capabilities like CAD\nare included. All image data are to be\ninterpreted by trained personnel.","Same","NA","",""],["Clinical\ncondition the\ndevice is\nintended to\ndiagnose, treat,\nor manage","No limitation on the clinical condition\nof the patient.","No limitation on the clinical condition\nof the patient.","Same","NA","",""],["Intended\npatient\npopulation","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","Same","NA","",""],["Site of the body\nthe device is\nintended to be\nused","No limitation concerning region of\nbody or tissue type","No limitation concerning region of\nbody or tissue type","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p15-t0","doc_id":"K240294","page_num":15,"bbox":[52.35,67.92,774.46,494.5],"n_rows":7,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Intended use\nenvironment","Syngo Carbon Enterprise Access is\nused in departmental environments\nwithin healthcare institutions.\nFor reading images certified monitors\nare required (e.g., medical diagnostic\ndisplays).","Syngo Carbon Space “Diagnostic\nWorkspace” is used in Radiology,\nNuclear Medicine and Cardiology\nenvironments (e.g., darkened/ shaded\nrooms).\nSyngo Carbon Space \"Physician\nAccess\" is used in departmental\nenvironments within healthcare\ninstitutions.\nFor reading images certified monitors\nare required (e.g., medical diagnostic\ndisplays).","Same","NA","",""],["Intended\nuser(s)","Trained healthcare professionals","Trained healthcare professionals","Same","NA","",""],["Device Type","Software application","Software application","Same","NA","",""],["Software\narchitecture","Syngo Carbon Enterprise Access is\nbased on a client-server architecture","Syngo Carbon Space is based on a\nclient-server architecture","Same","NA","",""],["Software self-\ntest / checks","N/A – this is a browser based\napplication","Client installation is prevented\nautomatically in case if the system\ndoesn’t have the recommended\noperating system. Also during the\nlaunch of the client every time, the\ncompatibility to the server version is\nchecked and request to\nupdate/upgrade to client in case of\nmismatch.","NA","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p16-t0","doc_id":"K240294","page_num":16,"bbox":[52.36,67.92,774.45,383.71],"n_rows":5,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Cyber Security","• User access control\n• Audit Trail\n• Documentation of system\nsecurity information, Network\ntraffic & Firewall control\n• Support of virus / malware\nprotection\n• System Hardening (OS level and\nNetwork level)","• User access control\n• Audit Trail\n• Documentation of system\nsecurity information, Network\ntraffic & Firewall control\n• Support of virus / malware\nprotection\n• System Hardening (OS level and\nNetwork level)","Same","NA","",""],["Hardware","Hardware is not understood as part of\nthe medical device but needs to\ncomply with the minimum\nrequirements as specified by Syngo\nCarbon Enterprise Access","Hardware is not understood as part of\nthe medical device but needs to\ncomply with the minimum\nrequirements as specified by Syngo\nCarbon Space.","Same","NA","",""],["Graphical user\ninterface","Yes, with reduced color palette,\nclearer structure, and text labels on\nicons. Floating panels increases the\nuser friendliness as the user can move\nthe panels wherever they are\nconvenient with.","Yes, with reduced color palette,\nclearer structure, and text labels on\nicons. Floating panels increases the\nuser friendliness as the user can move\nthe panels wherever they are\nconvenient with.","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p17-t0","doc_id":"K240294","page_num":17,"bbox":[52.39,67.92,774.43,393.07],"n_rows":3,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Patient\nBrowser","• Search, browse & open data for\ndisplay from syngo.share core &\nremote DICOM nodes\n• Search, browse & open data for\ndisplay from external XDS(-I)\nrepository)\n• Archive functionality (upload\nmedical data to syngo.share core\nfor archive)\n• Document properties functions\n(metadata modification and\ntagging)\n• Correct & re-arrange functions\n• Restore (trigger fetch from\narchive) functions\n• Distribution, export & sharing\nfunctions\n• Inbox - access to medical data\nshared by other users","• Search, browse & open data for\ndisplay from syngo.share core &\nremote DICOM nodes\n• Search, browse & open data for\ndisplay from external XDS(-I)\nrepository) **\n• Archive functionality (upload\nmedical data to syngo.share core\nfor archive)\n• Document properties functions\n(metadata modification and\ntagging)\n• Correct & re-arrange functions\n• Restore (trigger fetch from\narchive) functions\n• Distribution, export & sharing\nfunctions\n• Inbox - access to medical data\nshared by other users **\n**available in Physician Access only","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p18-t0","doc_id":"K240294","page_num":18,"bbox":[52.37,67.92,774.45,441.91],"n_rows":4,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Series\nnavigator /\nDocument\nPreview","Yes, with a fast overview of the\ndisplayed and not displayed data\n(series, images) of the loaded studies,\nquickly identify the relevant\nseries/images for reading, and bring\ndata (timepoints/series/images) into\ndisplay in an efficient manner\n(Drag&Drop).\nStudy / Timepoints are marked with\nindividual colors for better\nidentification.","Yes, with a fast overview of the\ndisplayed and not displayed data\n(series, images) of the loaded studies,\nidentify not yet seen series/images*,\nquickly identify the relevant\nseries/images for reading, and bring\ndata (timepoints/series/images) into\ndisplay in an efficient manner\n(Drag&Drop).\nStudy / Timepoints are marked with\nindividual colors for better\nidentification.\nThe Series Navigator is called\nDocument Preview for Physician\nAccess.\n* available in in Diagnostic\nWorkspace only","Same","NA","",""],["Findings panel","Findings panel collects\nmeasurements, annotations, and\ngraphical objects. Additionally, the\nuser can create new findings, edit\nfindings. It also allows creation of\nautomatic findings.","Findings panel collects\nmeasurements, annotations, and\ngraphical objects. Additionally, the\nuser can create new findings, edit\nfindings. It also allows creation of\nautomatic findings.","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p19-t0","doc_id":"K240294","page_num":19,"bbox":[52.37,67.92,774.45,497.14],"n_rows":4,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Reporting","No dedicated report creation\nfunctionality supported in Syngo\nCarbon Enterprise Access","No dedicated report creation\nfunctionality supported in Syngo\nCarbon Space.\nStructured findings can be\nautomatically transferred to external\nthird-party reporting system via FHIR\ninterface for creation of structured\nreport content [e.g. (Powerscribe [by\nNuance], SmartReports [by Smart\nReporting)]","Same","NA","",""],["Image\nArchiving","Not applicable since Syngo Carbon\nEnterprise Access does not create data\nor images that is transferred/stored.","Diagnostic Workspace:\nSyngo Carbon Space Diagnostic\nWorkspace does not store data or\nimages.\nCreated results for a study (e.g.\nDICOM PR, SR objects) are stored in\nsyngo.share core in context of the\noriginal study. syngo.share core is\nresponsible for long term archiving of\nthe original study and created results.\nPhysician Access:\nNot applicable since Syngo Carbon\nSpace Physician Access does not\ncreate data or images that is\ntransferred/stored.","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p20-t0","doc_id":"K240294","page_num":20,"bbox":[52.37,67.92,774.45,496.3],"n_rows":4,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Patient Jacket","Provides access to patient history –\nother studies of patient stored in\nremote DICOM nodes. Also provides\na study content preview along with\naccess to nearline studies and prior\nRIS reports","Provides access to patient history –\nother studies of patient stored in\nsyngo.share core or\nremote DICOM nodes. Also provides\na study content preview Along with\naccess to nearline studies and prior\nRIS reports","Same","NA","",""],["Optimization &\npreparation/\nSpatial\nOperation tools","• Image Preview\n• Zoom/Pan\n• Synch, Align\n• Windowing\n• Flip (Horizontal, Vertical)\n• Blow-up\n• Scroll\n• Movie\n• Magnifier","• Image Preview\n• Zoom/Pan\n• Fit to Segment*, Fit to\nAcquisition Size*\n• Synch, Align\n• Windowing\n• Rotate (2D image or 3D\nVolume*)\n• Flip (Horizontal, Vertical)\n• Shutters On/Off*\n• Blow-up\n• Scroll\n• Movie\n• Clipping*\n• Punching and Masking*\n• Magnifier\n* available in in Diagnostic\nWorkspace only","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240294-p21-t0","doc_id":"K240294","page_num":21,"bbox":[52.36,67.92,774.45,482.98],"n_rows":5,"n_cols":7,"columns":["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],"rows":[["Specification","Subject Device","Predicate Device","Comparison","","Impact to Safety &",""],["","","","","","Effectiveness",""],["Annotation\nTool","• Text","• Arrow*\n• Marker*\n• Text\n* available in in Diagnostic\nWorkspace only","Same","NA","",""],["Printing","Provides printing functionality on a\npaper printer.","Diagnostic workspace:\nProvides printing functionality with\nable to review, modify the images\nalong with selecting the print sheet\nformat exposing then the DICOM\nprinter.\nAlso, able to monitor the printing\nstatus and retry a printing task, if\nneeded.\nNote\n• DICOM printer must be configured as DICOM\nnodes\n• Grayscale & color printing is supported\nPhyisican Access:\nProvides printing functionality on a\npaper printer.","Same","NA","",""],["Online help\nsystem","Yes, with search, indexing, filtering,\nlibrary function and document\ncollections.","Yes, with search, indexing, filtering,\nlibrary function and document\ncollections.","Same","NA","",""]],"caption_candidate":"©Siemens Healthcare GmbH, 2024","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p5-t0","doc_id":"K240301","page_num":5,"bbox":[91.92,281.78,520.18,434.92],"n_rows":8,"n_cols":7,"columns":["","","Current","","","",""],"rows":[["","","Current","","","",""],["","","FFDM","DBT","2DSM","DBT+FFDM","DBT+2DSM"],["No\nPrior","/","Supported","Unsupported","Unsupported","Supported","Supported"],["Prior","FFDM","Unsupported","Unsupported","Unsupported","Supported","Unsupported"],["","DBT","Unsupported","Unsupported","Unsupported","Unsupported","Unsupported"],["","2DSM","Unsupported","Unsupported","Unsupported","Unsupported","Unsupported"],["","DBT +\nFFDM","Unsupported","Unsupported","Unsupported","Unsupported","Unsupported"],["","DBT +\n2DSM","Unsupported","Unsupported","Unsupported","Unsupported","Supported"]],"caption_candidate":"supported combinations:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p6-t0","doc_id":"K240301","page_num":6,"bbox":[71.1,228.74,538.68,720.6],"n_rows":5,"n_cols":3,"columns":["","Predicate device (MammoScreen 2)","Subject device (MammoScreen 3)"],"rows":[["","Predicate device (MammoScreen 2)","Subject device (MammoScreen 3)"],["Manufacturer","Therapixel","Therapixel"],["Regulation number","892.2090","892.2090"],["Product Code","QDQ","QDQ"],["Intended Use","MammoScreen 2 is a concurrent\nreading and reporting aid for\nphysicians interpreting screening\nmammograms. It is intended for use\nwith compatible full-field digital\nmammography and digital breast\ntomosynthesis systems.\nOutput of the device includes marks\nof findings on mammograms along\nwith their type and level of suspicion\nscores. The level of suspicion score is\nexpressed at the finding level, for\neach breast, and overall for the\nmammogram.","MammoScreen 3 is a concurrent\nreading and reporting aid for\nphysicians interpreting screening\nmammograms. It is intended for use\nwith compatible full-field digital\nmammography and digital breast\ntomosynthesis systems. The device\ncan also use compatible prior\nexaminations in the analysis.\nOutput of the device includes\ngraphical marks of findings as soft-\ntissue lesions or calcifications on\nmammograms along with their level of\nsuspicion scores. The lesion type is\ncharacterized as mass/asymmetry,\ndistortion, or calcifications for each\ndetected finding. The level of\nsuspicion score is expressed at the\nfinding level, for each breast, and\noverall for the mammogram.\nThe location of findings, including\nquadrant, depth, and distance from the\nnipple, is also provided. This\nadjunctive information is intended to\nassist interpreting physicians during\nreporting.\nPatient management decisions should\nnot be made solely based on the\nanalysis by MammoScreen 3."]],"caption_candidate":"Summary of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p7-t0","doc_id":"K240301","page_num":7,"bbox":[71.08,71.1,539.77,170.42],"n_rows":5,"n_cols":3,"columns":["","Predicate device (MammoScreen 2)","Subject device (MammoScreen 3)"],"rows":[["","Predicate device (MammoScreen 2)","Subject device (MammoScreen 3)"],["Intended user\npopulation","Physicians qualified to read\nmammograms.","Physicians qualified to read\nmammograms."],["Intended patient\npopulation","Women undergoing mammography.","Women undergoing mammography."],["Anatomical Location","Breast","Breast"],["Design","Software-only device","Software-only device"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p7-t1","doc_id":"K240301","page_num":7,"bbox":[71.08,515.2,539.77,681.04],"n_rows":4,"n_cols":3,"columns":["Technological\ncharacteristic","Predicate device\n(MammoScreen 2)","Subject device\n(MammoScreen 3)"],"rows":[["Technological\ncharacteristic","Predicate device\n(MammoScreen 2)","Subject device\n(MammoScreen 3)"],["Type of artificial\nintelligence","MammoScreen 2 is powered by\nartificial intelligence/machine\nlearning-based software algorithm","Same."],["Level of suspicion","MammoScreen 2 outputs a level of\nsuspicion at the finding, breast and\ncase level.","Same."],["Lesion type","For each detected finding\nMammoScreen 2 classifies them as\nsoft tissue lesion or calcifications.","For each detected finding\nMammoScreen 3 classifies them as\nmass/asymmetry, distortion or\ncalcifications."]],"caption_candidate":"questions of safety and effectiveness than the previous version.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p8-t0","doc_id":"K240301","page_num":8,"bbox":[71.1,71.1,540.96,195.5],"n_rows":3,"n_cols":3,"columns":["Technological\ncharacteristic","Predicate device\n(MammoScreen 2)","Subject device\n(MammoScreen 3)"],"rows":[["Technological\ncharacteristic","Predicate device\n(MammoScreen 2)","Subject device\n(MammoScreen 3)"],["Localization","MammoScreen 2 doesn’t provide a\nlocalization.","For each finding MammoScreen 3\nprovides a quadrant, a depth and a\ndistance to the nipple."],["Inputs","FFMD or DBT","FFDM or 2DSM & DBT or FFDM\n& DBT, with an optional prior\n(FFDM or 2DSM & DBT) expect\nfor the former."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p10-t0","doc_id":"K240301","page_num":10,"bbox":[170.18,140.48,489.16,404.6],"n_rows":7,"n_cols":2,"columns":["Cancer status","Normal/benign: 77%\nMalignant: 23%"],"rows":[["Cancer status","Normal/benign: 77%\nMalignant: 23%"],["Breast density","A: 10%\nB: 44%\nC: 31%\nD: 15%"],["Age (years old)","Minimum: 32\nMaximum: 93\nMean: 58\n25th percentile: 49\n75th percentile: 65"],["Race","White: 37%\nBlack: 16%\nAsian: 18%\nAmerican Indian / Alaska native: 0.8%\nNative Hawaiian / Pacific islander: 0.2%\nUnspecified: 28%"],["Imaging modality","DBT (inc. FFDM or 2DSM): 64%\nFFDM: 36%"],["Modality manufacturer","Hologic: 100%"],["Exam dates (range)","2005 – 2023"]],"caption_candidate":"information about the test population is provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p11-t0","doc_id":"K240301","page_num":11,"bbox":[97.5,94.26,704.06,576.24],"n_rows":44,"n_cols":13,"columns":["Overall","","1,053","6,420","0.927","(0.911,","0.942)","0.912","(0.895,","0.928)","0.727","(0.715,","0.740)"],"rows":[["Overall","","1,053","6,420","0.927","(0.911,","0.942)","0.912","(0.895,","0.928)","0.727","(0.715,","0.740)"],["","A","71","658","0.953","(0.924,","0.976)","0.958","(0.901,","1.000)","0.739","(0.701,","0.778)"],["","B","489","2,682","0.933","(0.922,","0.945)","0.933","(0.910,","0.954)","0.690","(0.670,","0.709)"],["y density","","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","C","415","1,822","0.921","(0.905,","0.936)","0.896","(0.867,","0.925)","0.727","(0.702,","0.750)"],["","D","77","1,005","0.891","(0.846,","0.929)","0.816","(0.727,","0.896)","0.815","(0.787,","0.841)"],["","White","211","2,780","0.901","(0.876,","0.924)","0.857","(0.806,","0.900)","0.709","(0.689,","0.729)"],["","Black","77","1,085","0.897","(0.862,","0.929)","0.896","(0.831,","0.961)","0.680","(0.650,","0.708)"],["","Asian","41","1,406","0.899","(0.849,","0.940)","0.854","(0.732,","0.951)","0.763","(0.736,","0.789)"],["By race","","","","","","","","","","","",""],["Ameri","can Indian or Alaska","","","","","","","","","","",""],["Native","/ Native Hawaiian or","3","76","0.886","(0.701,","1.000)","0.663","(0.000,","1.000)","0.672","(0.556,","0.784)"],["oth","er Pacific Islander","","","","","","","","","","",""],["","US 1","75","2,616","0.862","(0.814,","0.905)","0.772","(0.667,","0.867)","0.752","(0.732,","0.771)"],["y source","US 2","717","915","0.951","(0.941,","0.961)","0.935","(0.917,","0.952)","0.787","(0.757,","0.817)"],["","US 3","261","2,889","0.908","(0.888,","0.925)","0.889","(0.851,","0.927)","0.689","(0.670,","0.709)"],["","≤ 50 years old","273","3,879","0.912","(0.894,","0.929)","0.879","(0.839,","0.916)","0.720","(0.704,","0.736)"],["By age","50 < age ≤ 65","397","1,630","0.942","(0.929,","0.954)","0.932","(0.907,","0.957)","0.756","(0.732,","0.780)"],["","> 65","382","911","0.921","(0.902,","0.938)","0.914","(0.885,","0.942)","0.705","(0.669,","0.740)"],["","Mass","180","6,420","0.945","(0.927,","0.961)","0.939","(0.902,","0.973)","0.727","(0.715,","0.740)"],["","Calcifications","271","6,420","0.926","(0.909,","0.942)","0.912","(0.878,","0.941)","0.727","(0.715,","0.740)"],["lesion type","Asymmetries","117","6,420","0.884","(0.854,","0.911)","0.835","(0.768,","0.897)","0.727","(0.715,","0.740)"],["Fo","cal asymmetries","262","6,420","0.921","(0.901,","0.938)","0.902","(0.861,","0.936)","0.727","(0.715,","0.740)"],["","Distortions","223","6,420","0.945","(0.929,","0.960)","0.938","(0.906,","0.969)","0.727","(0.715,","0.740)"],["","≤ 20 mm","380","6,420","0.905","(0.887,","0.922)","0.887","(0.852,","0.924)","0.727","(0.715,","0.740)"],["lesion size 20","≤ size ≤ 30 mm","355","6,420","0.933","(0.915,","0.948)","0.916","(0.881,","0.946)","0.727","(0.715,","0.740)"],["",">30 mm","318","6,420","0.959","(0.947,","0.971)","0.959","(0.934,","0.983)","0.727","(0.715,","0.740)"],["By lesion","BI–RADS 4","525","6,420","0.924","(0.910,","0.936)","0.910","(0.884,","0.935)","0.727","(0.715,","0.740)"],["severity","BI–RADS 5","178","6,420","0.972","(0.960,","0.982)","0.983","(0.961,","1.000)","0.727","(0.715,","0.740)"],["y current","FFDM","886","4,303","0.908","(0.896,","0.919)","0.915","(0.895,","0.933)","0.632","(0.615,","0.647)"],["image","DBT + FFDM","823","3,744","0.929","(0.919,","0.939)","0.925","(0.905,","0.942)","0.710","(0.694,","0.725)"],["mbination","DBT + 2DSM","161","2,114","0.904","(0.878,","0.927)","0.858","(0.806,","0.903)","0.762","(0.739,","0.785)"],["","FFDM","782","4,216","0.926","(0.916,","0.936)","0.901","(0.880,","0.921)","0.761","(0.746,","0.776)"],["prior image","DBT + FFDM","534","1833","0.930","(0.918,","0.942)","0.907","(0.882,","0.930)","0.775","(0.755,","0.795)"],["mbination","DBT + 2DSM","80","921","0.903","(0.861,","0.937)","0.838","(0.750,","0.912)","0.767","(0.735,","0.797)"],["","No prior","1,037","6,211","0.925","(0.915,","0.933)","0.933","(0.918,","0.948)","0.667","(0.653,","0.681)"],["current & Current","FFDM – Prior FFDM","679","2,135","0.905","(0.891,","0.920)","0.908","(0.887,","0.929)","0.664","(0.643,","0.683)"],["ior image Cur","rent DBT+FFDM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","630","1,717","0.932","(0.920,","0.943)","0.914","(0.894,","0.935)","0.767","(0.746,","0.788)"],["mbination","Prior FFDM","","","","","","","","","","",""],["","","","","","","","","","","","",""],[") submission Mamm","oScreen 3","","","","","Page 8 of","13","","","","",""]],"caption_candidate":"positive cases negative cases (95% CI) (95% CI) (95% CI)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240301-p12-t0","doc_id":"K240301","page_num":12,"bbox":[155.21,94.26,704.04,576.24],"n_rows":35,"n_cols":13,"columns":["Current DBT+","FFDM","","","","","","","","","","",""],"rows":[["Current DBT+","FFDM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","482","1,586","0.928","(0.913,","0.941)","0.906","(0.880,","0.932)","0.771","(0.750,","0.791)"],["Prior DBT+F","FDM","","","","","","","","","","",""],["Current DBT+","FFDM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","13","3","0.945","(0.769,","1.000)","1.000","(1.000,","1.000)","0.663","(0.000,","1.000)"],["Prior DBT+2","DSM","","","","","","","","","","",""],["Current DBT+","2DSM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","120","1,196","0.908","(0.875,","0.936)","0.875","(0.817,","0.933)","0.764","(0.737,","0.789)"],["Prior FFD","M","","","","","","","","","","",""],["Current DBT+","2DSM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","75","164","0.939","(0.905,","0.967)","0.935","(0.867,","0.987)","0.755","(0.680,","0.823)"],["Prior DBT+F","FDM","","","","","","","","","","",""],["Current DBT+","2DSM","","","","","","","","","","",""],["","","65","878","0.890","(0.844,","0.931)","0.817","(0.723,","0.908)","0.770","(0.738,","0.799)"],["","","","","","","","","","","","",""],["Prior DBT+2","DSM","","","","","","","","","","",""],["Current FFDM –","No prior","878","4,167","0.899","(0.887,","0.911)","0.911","(0.892,","0.930)","0.611","(0.594,","0.628)"],["Current DBT+","FFDM","","","","","","","","","","",""],["","","807","3,606","0.927","(0.917,","0.937)","0.941","(0.924,","0.957)","0.659","(0.642,","0.676)"],["","","","","","","","","","","","",""],["No prior","","","","","","","","","","","",""],["Current DBT+","2DSM","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","158","2,040","0.902","(0.874,","0.928)","0.893","(0.842,","0.943)","0.689","(0.665,","0.712)"],["No prior","","","","","","","","","","","",""],["6 months ≤ prior <","18 months","237","1,866","0.913","(0.893,","0.932)","0.869","(0.823,","0.912)","0.774","(0.755,","0.793)"],["","","","","","","","","","","","",""],["18 ≤ prior < 30","months","436","1,735","0.931","(0.916,","0.944)","0.917","(0.889,","0.942)","0.752","(0.728,","0.777)"],["30 months ≤ prior <","60 months","177","628","0.935","(0.912,","0.955)","0.910","(0.865,","0.949)","0.754","(0.718,","0.789)"],["","","","","","","","","","","","",""],["MammoScreen 3","","","","","","Page 9 of 1","3","","","","",""]],"caption_candidate":"positive cases negative cases (95% CI) (95% CI) (95% CI)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240301-p13-t0","doc_id":"K240301","page_num":13,"bbox":[71.16,120.9,540.96,179.24],"n_rows":5,"n_cols":4,"columns":["","Counts","PPA (95% CI)","NPA (95% CI)"],"rows":[["","Counts","PPA (95% CI)","NPA (95% CI)"],["Overall","1,039","0.784, (0.758, 0.811)","0.893, (0.880, 0.906)"],["Mass/asymmetry","548","0.868, (0.838, 0.894)","0.783, (0.752, 0.815)"],["Distortion","221","0.544, (0.475, 0.611)","0.947, (0.932, 0.962)"],["Calcifications","270","0.941, (0.911, 0.967)","0.950, (0.934, 0.964)"]],"caption_candidate":"Results are summarized in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p13-t1","doc_id":"K240301","page_num":13,"bbox":[71.16,509.08,540.96,579.16],"n_rows":6,"n_cols":4,"columns":["","Counts","PPA (95% CI)","NPA (95% CI)"],"rows":[["","Counts","PPA (95% CI)","NPA (95% CI)"],["Overall","736","0.765 (0.726, 0.810)","0.963 (0.951, 0.965)"],["Inner / Medial","149","0.866 (0.812, 0.919)","0.978 (0.966, 0.988)"],["Central","179","0.782 (0.715, 0.844)","0.925 (0.903, 0.943)"],["Outer / Lateral","372","0.884 (0.852, 0.914)","0.953 (0.929, 0.973)"],["Retroareolar","36","0.528 (0.361, 0.667)","0.994 (0.987, 0.999)"]],"caption_candidate":"CC quadrant:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p14-t0","doc_id":"K240301","page_num":14,"bbox":[71.16,293.9,540.96,363.92],"n_rows":6,"n_cols":4,"columns":["","Counts","PPA (95% CI)","NPA (95% CI)"],"rows":[["","Counts","PPA (95% CI)","NPA (95% CI)"],["Overall","749","0.471 (0.425, 0.523)","0.889 (0.878, 0.902)"],["Lower / Inferior","130","0.623 (0.538, 0.708)","0.861 (0.835, 0.884)"],["Central","151","0.351 (0.272, 0.430)","0.766 (0.731, 0.796)"],["Upper / Superior","428","0.458 (0.300, 0.600)","0.941 (0.910, 0.966)"],["Retroareolar","40","0.450 (0.300, 0.575)","0.990 (0.983, 0.997)"]],"caption_candidate":"MLO quadrant:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p15-t0","doc_id":"K240301","page_num":15,"bbox":[71.16,71.16,540.96,129.48],"n_rows":5,"n_cols":4,"columns":["","Counts","PPA (95% CI)","NPA (95% CI)"],"rows":[["","Counts","PPA (95% CI)","NPA (95% CI)"],["Overall","775","0.617 (0.587, 0.644)","0.943 (0.932, 0.953)"],["Posterior","346","0.907 (0.873, 0.936)","0.891 (0.865, 0.918)"],["Middle","355","0.852 (0.814, 0.887)","0.904 (0.879, 0.931)"],["Anterior","74","0.699 (0.595, 0.797)","0.992 (0.984, 0.997)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240301-p15-t1","doc_id":"K240301","page_num":15,"bbox":[119.66,72.74,520.04,756.24],"n_rows":9,"n_cols":8,"columns":["","Counts","PP","A (95%","CI)","NP","A (95%","CI)"],"rows":[["","Counts","PP","A (95%","CI)","NP","A (95%","CI)"],["Overall","775","0.617","(0.587,","0.644)","0.943","(0.932,","0.953)"],["Posterior","346","0.907","(0.873,","0.936)","0.891","(0.865,","0.918)"],["Middle","355","0.852","(0.814,","0.887)","0.904","(0.879,","0.931)"],["Anterior","74","0.699","(0.595,","0.797)","0.992","(0.984,","0.997)"],["","","","","","","",""],["confusion matrix:","","","","","","",""],["","","","","","","",""],["mission MammoScreen 3","","","","","","Pag","e 12 o"]],"caption_candidate":"Counts PPA (95% CI) NPA (95% CI)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240353-p4-t0","doc_id":"K240353","page_num":4,"bbox":[36.24,68.88,567.0,234.96],"n_rows":10,"n_cols":2,"columns":["Submitter’s Name:","SK Inc."],"rows":[["Submitter’s Name:","SK Inc."],["Submitter’s Address:","SK U-Tower, 9 Seongnam-daero, Bundang-gu, Seongnam-si, Gyeonggi-do, 13558\nRepublic of Korea"],["Submitter’s Telephone:","+82-2-6400-0114"],["Contact Person:","Hannah Taggart, MS\nEmpirical Technologies\n1-719-457-1152\nhtaggart@empiricaltech.com"],["Date Summary was Prepared:","June 25, 2024"],["Trade or Proprietary Name:","Hyper Insight - ICH"],["Device Classification Name:","Radiological Computer-Assisted Triage And Notification Software"],["Classification & Regulation #:","Class II per 21 CFR §892.2080"],["Product Code:","QAS"],["Classification Panel:","Radiology"]],"caption_candidate":"K240353 510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p5-t0","doc_id":"K240353","page_num":5,"bbox":[36.24,251.04,571.97,278.52],"n_rows":2,"n_cols":5,"columns":["510k Number","Trade or Proprietary or Model Name","Manufacturer","Product Code","Predicate Type"],"rows":[["510k Number","Trade or Proprietary or Model Name","Manufacturer","Product Code","Predicate Type"],["K193658","Viz ICH","Viz.ai, Inc.","QAS","Primary"]],"caption_candidate":"• Performance Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p5-t1","doc_id":"K240353","page_num":5,"bbox":[36.24,303.72,571.97,742.14],"n_rows":7,"n_cols":3,"columns":["","Subject Name\n(Subject Device)","Viz.ai, Inc. Viz ICH\n(K193658)"],"rows":[["","Subject Name\n(Subject Device)","Viz.ai, Inc. Viz ICH\n(K193658)"],["Indications for Use","Hyper Insight - ICH is a notification-only workflo\nw tool for trained clinicians to identify patients' br\nain CT images and share them with medical speci\nalists in parallel with standard patient care workflo\nw. Hyper Insight - ICH uses deep learning-based\nAI algorithms to analyze images to find suspected\nintracranial hemorrhage and notifies and shares the\nfindings to medical specialists. Identification of im\nages with suspected intracranial hemorrhage is for\nnotification purposes only, not diagnostic purposes.\nIn particular, this medical device analyzes non-cont\nrast brain CT images, and if a suspected intracrani\nal hemorrhage is identified, it sends a notification\nto medical specialists, who are advised to review t\nhese images. Images may be previewed through th\ne mobile app but are for informational purposes o\nnly and are not intended to be used for diagnostic\npurposes other than notifications and previews. T\nhe medical specialist who received the notification\nis responsible for reading the image in a diagnosti\nc viewer.\nHyper Insight - ICH is limited to the purpose of\nanalysis of image data and should not be used as\na substitute for a full patient assessment or relied\nupon to make or confirm a diagnosis.","Viz ICH is a notification-only, parallel workflow tool f\nor use by hospital networks and trained clinicians to id\nentify and communicate images of specific patients to a\nspecialist, independent of standard of care workflow.\nViz ICH uses an artificial intelligence algorithm to anal\nyze images for findings suggestive of a prespecified cli\nnical condition and to notify an appropriate medical spe\ncialist of these findings in parallel to standard of care i\nmage interpretation. Identification of suspected findings\nis not for diagnostic use beyond notification. Specificall\ny, the device analyzes non-contrast CT images of the b\nrain acquired in the acute setting and sends notification\ns to a neurovascular or neurosurgical specialist that a s\nuspected intracranial hemorrhage has been identified and\nrecommends review of those images. Images can be p\nreviewed through a mobile application. Images that are\npreviewed through the mobile application may be comp\nressed and are for informational purposes only and not\nintended for diagnostic use beyond notification. Notified\nclinicians are responsible for viewing non-compressed i\nmages on a diagnostic viewer and engaging in appropri\nate patient evaluation and relevant discussion with a tre\nating physician before making care-related decisions or\nrequests. Viz ICH is limited to analysis of imaging dat\na and should not be used in-lieu of full patient evaluati\non or relied upon to make or confirm diagnosis. Viz I\nCH is contraindicated for analyzing non-contrast CT sca\nns that are acquired on scanners from manufacturers ot\nher than General Electric (GE) or its subsidiaries (i.e.\nGE Healthcare). This contraindication applies to NCCT\nscans that conform to all applicable Patient Inclusion C\nriteria, are of adequate technical image quality, and wo\nuld otherwise be expected to be analyzed by the device\nfor a suspected ICH."],["Product Code","QAS","QAS"],["Environment of use","Clinical/Hospital Environment","Clinical/Hospital Environment"],["Intended Clinical\nEnd User","Radiologist, emergency medicine physicians, neuros\nurgeons, neurologist","Radiologist, emergency medicine physicians, neurosurgeo\nns, neurologist"],["Anatomical Region","Head","Head"],["Clinical Condition","Acute Intercranial Hemorrhage (ICH)","Intercranial Hemorrhage (ICH)"]],"caption_candidate":"Predicate Device Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p6-t0","doc_id":"K240353","page_num":6,"bbox":[36.35,36.24,572.43,326.16],"n_rows":15,"n_cols":3,"columns":["","Subject Name\n(Subject Device)","Viz.ai, Inc. Viz ICH\n(K193658)"],"rows":[["","Subject Name\n(Subject Device)","Viz.ai, Inc. Viz ICH\n(K193658)"],["Independent of\nstandard of care\nworkflow","Yes, No cases are removed from worklist","Yes"],["AI Used","Yes","Yes"],["Input Image\nModality","Non-Contrast Head CT","Non-Contrast Head CT"],["Alteration of Image","No","No"],["DICOM Compatible","Yes","Yes"],["Transfer, store, and\nprocess DICOM im\nages","Yes","Yes"],["Data Acquisition","Acquires medical image data from DICOM compli\nant imaging devices and modalities.","Acquires medical image data from DICOM compliant i\nmaging devices and modalities."],["Results of Image\nAnalysis","Internal, no image marking","Internal, no image marking"],["Preview Images","Initial assessment; non-diagnostic","Initial assessment; non-diagnostic"],["View DICOM Data","DICOM Information about the patient, study and c\nurrent image.","DICOM Information about the patient, study and curren\nt image."],["Image viewing and\nmanipulation\n(window,pan,zoom)","Yes","Yes"],["Output","AI findings (Suspected ICH or Case Processed)","Suspected ICH (Yes or No)"],["Clinical SoC\nWorkflow","In parallel to","In parallel to"],["Results Receiver","PACS/Workstation","PACS/Workstation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p6-t1","doc_id":"K240353","page_num":6,"bbox":[36.35,362.04,572.43,480.24],"n_rows":5,"n_cols":3,"columns":["Performance","Subject Device","K193658"],"rows":[["Performance","Subject Device","K193658"],["Sensitivity (%)\n95% Confidence Interval","95.45\n[91.55, 97.90]","93\n[87, 97]"],["Specificity (%)\n95% Confidence Interval","98.47\n[95.59, 99.68]","90\n[84, 94]"],["AUC of ROC","0.9864\n[0.9738, 0.9989]","0.96"],["Average time to alerting a\nspecialist","16.39±5.46 seconds","0.49±0.15 minutes"]],"caption_candidate":"Overall Performance Data Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p6-t2","doc_id":"K240353","page_num":6,"bbox":[36.35,506.96,572.43,621.72],"n_rows":6,"n_cols":13,"columns":["Age Range (years)","Subject Device","","","","","","K193658","","","","",""],"rows":[["Age Range (years)","Subject Device","","","","","","K193658","","","","",""],["","","Sensitivity","","","Specificity","","","Sensitivity","","","Specificity",""],["","","[95 Cl]","","","[95% Cl]","","","[95 Cl]","","","[95% Cl]",""],["<50","95.35\n[84.19, 99.43]","","","96.94\n[91.31, 99.36]","","","0.89\n[0.52, 1.0]","","","0.95\n[0.76, 1.0]","",""],["50 - 70","97.92\n[88.93, 99.95]","","","100.00\n[94.04, 100.00]","","","0.92\n[0.82, 0.97]","","","0.9\n[0.8, 0.96]","",""],[">70","94.39\n[88.19, 97.91]","","","100.00\n[90.75, 100.00]","","","0.94\n[0.84, 0.99]","","","0.88\n[0.76, 0.95]","",""]],"caption_candidate":"Age Subgroup Performance Data Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p7-t0","doc_id":"K240353","page_num":7,"bbox":[36.74,50.15,574.88,134.04],"n_rows":5,"n_cols":13,"columns":["Gender","","Subject Device","","","","","","K193658","","","",""],"rows":[["Gender","","Subject Device","","","","","","K193658","","","",""],["","","Sensitivity","","","Specificity","","","Sensitivity","","","Specificity",""],["","","[95% Cl]","","","[95% Cl]","","","[95% Cl]","","","[95% Cl]",""],["Male","97.25\n[92.17, 99.43]","","","100.00\n[95.55, 100.00]","","","0.9\n[0.8, 0.96]","","","0.9\n[0.8, 0.96]","",""],["Female","93.26\n[85.90, 97.49]","","","97.39\n[92.57, 99.46]","","","0.95\n[0.86, 0.99]","","","0.89\n[0.8, 0.95]","",""]],"caption_candidate":"Gender Subgroup Performance Data Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p7-t1","doc_id":"K240353","page_num":7,"bbox":[36.74,168.83,574.88,327.96],"n_rows":9,"n_cols":7,"columns":["ICH Subtype","","Subject Device","","","K193658",""],"rows":[["ICH Subtype","","Subject Device","","","K193658",""],["","","Sensitivity","","","Sensitivity",""],["","","[95% CI]","","","[95% CI]",""],["Intraparenchymal Hemorrhage\n(IPH)","97.30\n[90.58, 99.67]","","","0.98\n[0.91, 1.0]","",""],["Intraventricular Hemorrhage (I\nVH)","97.67\n[87.71, 99.94]","","","1.00\n[0.74, 1.0]","",""],["Subarachnoid Hemorrhage (SA\nH)","97.65\n[91.76, 99.71]","","","0.60\n[0.26, 0.88]","",""],["Subdural Hemorrhage (SDH)","94.69\n[88.80, 98.03]","","","0.85\n[0.62, 0.97]","",""],["Extradural Hemorrhage (EDH)","100.00\n[80.49, 100.00]","","","N/A","",""],["SDH or EDH","97.30\n[90.58, 99.67]","","","0.85\n[0.62, 0.97]","",""]],"caption_candidate":"ICH Subtype Performance Data Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p7-t2","doc_id":"K240353","page_num":7,"bbox":[36.74,362.75,574.88,437.16],"n_rows":5,"n_cols":13,"columns":["Slice Thickness","","Subject Device","","","","","","K193658","","","",""],"rows":[["Slice Thickness","","Subject Device","","","","","","K193658","","","",""],["","","Sensitivity","","","Specificity","","","Sensitivity","","","Specificity",""],["","","[95% CI]","","","[95% CI]","","","[95% CI]","","","[95% CI]",""],["2.5mm <= Slice Thickness <\n3.5mm","96.67\n[88.47, 99.59]","","","94.00\n[83.45, 98.75]","","","0.93\n[0.85, 0.98]","","","0.92\n[0.83, 0.97]","",""],["3.5mm <= Slice Thickness <\n= 5.0mm","94.78\n[89.53, 97.87]","","","100.00\n[97.45, 100.00]","","","0.92\n[0.81, 0.98]","","","0.88\n[0.77, 0.95]","",""]],"caption_candidate":"Slice Thickness Subgroup Performance Data Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p8-t0","doc_id":"K240353","page_num":8,"bbox":[125.42,156.56,486.7,201.24],"n_rows":2,"n_cols":3,"columns":["","Subject Device","K193658"],"rows":[["","Subject Device","K193658"],["Average time to\nnotification","16.39 ± 5.46 seconds\n(0.27 ± 0.091 minutes)","0.49 ± 0.15 minutes"]],"caption_candidate":"clinical workflow.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p8-t1","doc_id":"K240353","page_num":8,"bbox":[125.42,248.01,486.7,596.04],"n_rows":15,"n_cols":5,"columns":["","Performance Stratified by Clinical Site","","",""],"rows":[["","Performance Stratified by Clinical Site","","",""],["Clinical Site","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["Clinical Site 1","","100.00\n[59.04, 100.00]","100.00\n[59.04, 100.00]",""],["Clinical Site 2","","92.86\n[66.13, 99.82]","50.00\n[1.26, 98.74]",""],["Clinical Site 3","","100.00\n[2.50, 100.00]","-\n[-, -]",""],["Clinical Site 4","","100.00\n[15.81, 100.00]","90.00\n[55.50, 99.75]",""],["Clinical Site 5","","100.00\n[59.04, 100.00]","94.12\n[71.31, 99.85]",""],["Clinical Site 6","","100.00\n[2.50, 100.00]","-\n[-, -]",""],["Clinical Site 7","","100.00\n[47.82, 100.00)","100.00\n[15.81, 100.00]",""],["Clinical Site 8","","100.00\n[2.50, 100.00]","100.00\n[2.50, 100.00]",""],["Clinical Site 9","","100.00\n[69.15, 100.00]","100.00\n[59.04, 100.00]",""],["Clinical Site 10","","83.33\n[35.88, 99.58]","100.00\n[39.76, 100.00]",""],["Clinical Site 11","","92.59\n[75.71, 99.09]","100.00\n[94.72, 100.00]",""],["Clinical Site 12","","92.00\n[80.77, 97.78]","100.00\n[92.75, 100.00]",""],["Clinical Site 13","","98.51\n[91.96, 99.96]","100.00\n[88.06, 100.00]",""]],"caption_candidate":"As part of a secondary analysis, the company stratified the device performance by various confounding variables:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p8-t2","doc_id":"K240353","page_num":8,"bbox":[125.42,610.8,486.7,724.8],"n_rows":5,"n_cols":5,"columns":["","Performance Stratified by Age","","",""],"rows":[["","Performance Stratified by Age","","",""],["Age Range (ye\nars)","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["≤50","","95.35\n[84.19, 99.43]","96.94\n[91.31, 99.36]",""],["50 - 70","","97.92\n[88.93, 99.95]","100.00\n[94.04, 100.00]",""],["≥70","","94.39\n[88.19, 97.91]","100.00\n[90.75, 100.00]",""]],"caption_candidate":"[91.96, 99.96] [88.06, 100.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p9-t0","doc_id":"K240353","page_num":9,"bbox":[125.42,36.36,486.69,109.92],"n_rows":4,"n_cols":5,"columns":["","Performance Stratified by Gender","","",""],"rows":[["","Performance Stratified by Gender","","",""],["Gender","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["Male","","97.25\n[92.17, 99.43]","100.00\n[95.55, 100.00]",""],["Female","","93.26\n[85.90, 97.49]","97.39\n[92.57, 99.46]",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p9-t1","doc_id":"K240353","page_num":9,"bbox":[125.42,124.08,486.69,367.08],"n_rows":9,"n_cols":5,"columns":["","Performance Stratified by Race","","",""],"rows":[["","Performance Stratified by Race","","",""],["Race","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["American\nIndian or\nAlaskan Native","","100.00\n[2.50, 100.00]","-\n[-, -]",""],["Asian","","100.00\n[59.04, 100.00]","100.00\n[29.24, 100.00]",""],["Black or\nAfrican\nAmerican","","100.00\n[85.18, 100.00]","100.00\n[90.00, 100.00]",""],["Native\nHawaiian or\nOther Pacific\nIslander","","100.00\n[15.81, 100.00]","-\n[-, -]",""],["White","","95.21\n[90.37, 98.05]","97.79\n[93.69, 99.54]",""],["Two or more\nraces","","-\n[-, -]","-\n[-, -]",""],["Unknown","","89.47\n[66.86, 98.70]","100.00\n[84.56, 100.00]",""]],"caption_candidate":"[85.90, 97.49] [92.57, 99.46]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p9-t2","doc_id":"K240353","page_num":9,"bbox":[125.42,381.3,486.69,520.2],"n_rows":7,"n_cols":4,"columns":["","Performance Stratified by ICH Subtype","",""],"rows":[["","Performance Stratified by ICH Subtype","",""],["ICH Subtype","","Sensitivity [95% CI]",""],["Intraparenchymal Hemorrhage (IPH)","","97.30\n[90.58, 99.67]",""],["Intraventricular Hemorrhage (IVH)","","97.67\n[87.71, 99.94]",""],["Subarachnoid Hemorrhage (SAH)","","97.65\n[91.76, 99.71]",""],["Subdural Hemorrhage (SDH)","","94.69\n[88.80, 98.03]",""],["Epidural Hemorrhage (EDH)","","100.00\n[80.49, 100.00]",""]],"caption_candidate":"[66.86, 98.70] [84.56, 100.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p9-t3","doc_id":"K240353","page_num":9,"bbox":[125.42,534.48,486.69,630.84],"n_rows":5,"n_cols":5,"columns":["","Performance Stratified by Slice Thickness","","",""],"rows":[["","Performance Stratified by Slice Thickness","","",""],["Slice Thickness","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["0.5 mm ≤ slice thickness < 2.5 mm","","100.00\n[39.76, 100.00]","100.00\n[29.24, 100.00]",""],["2.5 mm ≤ slice thickness < 3.5 mm","","96.67\n[88.47, 99.59]","94.00\n[83.45, 98.75]",""],["3.5 mm ≤ slice thickness ≤ 5.0 mm","","94.78\n[89.53, 97.87]","100.00\n[97.45, 100.00]",""]],"caption_candidate":"[80.49, 100.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240353-p9-t4","doc_id":"K240353","page_num":9,"bbox":[125.42,645.12,486.69,740.34],"n_rows":5,"n_cols":5,"columns":["","Performance Stratified by CT scanner’s manufacturer","","",""],"rows":[["","Performance Stratified by CT scanner’s manufacturer","","",""],["CT scanner’s manufacturer","","Sensitivity [95% Cl]","Specificity [95% Cl]",""],["Canon Medical Systems","","100.00\n[66.37, 100.00]","-\n[-, -]",""],["GE MEDICAL SYSTEMS","","96.77\n[83.30, 99.92]","90.91\n[70.84, 98.88]",""],["Philips","","92.50\n[79.61, 98.43]","98.88\n[93.90, 99.97]",""]],"caption_candidate":"[89.53, 97.87] [97.45, 100.00]","well_formed":true,"extraction_settings":"lines"}
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(cid:18)(cid:35)(cid:26)(cid:25)(cid:29)(cid:24)(cid:22)(cid:37)(cid:26)(cid:1) (cid:19)(cid:38)(cid:32)(cid:32)(cid:22)(cid:35)(cid:40)(cid:1)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240398-p5-t0","doc_id":"K240398","page_num":5,"bbox":[107.08,426.53,375.65,564.67],"n_rows":7,"n_cols":6,"columns":["","Device Name","","","Software Version number",""],"rows":[["","Device Name","","","Software Version number",""],["RayStation","","","2024A SP3","",""],["RayPlan","","","2024A SP3","",""],["RayStation","","","2024A","",""],["RayPlan","","","2024A","",""],["RayStation","","","2023B","",""],["RayPlan","","","2023B","",""]],"caption_candidate":"Device Trade Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p7-t0","doc_id":"K240398","page_num":7,"bbox":[71.08,122.42,524.25,760.18],"n_rows":11,"n_cols":9,"columns":["","Feature","","","Description","","","Present in RayPlan",""],"rows":[["","Feature","","","Description","","","Present in RayPlan",""],["3D visualization","","","Displays the patient geometry and structures in three\ndimensions, with the possibility to rotate the patient\nimage. If available, the dose distribution and beam\nmodifiers are shown as well.","","","Yes","",""],["Adaptive\nreplanning","","","The process of replanning the treatment for a patient,\nbased on information about e.g. patient geometry,\nbiology and dose delivery acquired during treatment.","","","No","",""],["Beam\ncommissioning","","","Modeling of the radiation beam using a limited set of\nmeasurements on the clinical beam for commissioning\ntreatment machines to make them available for\ntreatment planning.","","","Yes","",""],["Beam design","","","Definition of beam orientations, apertures and various\nbeam modifiers in order to manually create a treatment\nplan.","","","Yes","",""],["Beam set-up","","","Manual or automatic definition of isocenter, selection of\ntreatment unit from the set of commissioned treatment\nmachines, and specification of gantry/couch/collimator\nangles.","","","Yes","",""],["Beam’s eye\nview","","","Displays the beam’s eye view of the patient structures,\nfluence and beam modifier settings for any beam.","","","Yes","",""],["Brachy planning","","","Tools for planning of HDR brachytherapy treatments.\nIncludes channel reconstruction and optimization and\nediting of dwell times.","","","Yes","",""],["CyberKnife\nplanning","","","CyberKnife planning is completely integrated in\nRayStation. This includes optimization of high quality\ntreatment plans collimated with MLC, fixed cones or iris\ncones, as well as support for all CyberKnife Synchrony\ntechniques for target tracking and real time motion\nsynchronization.","","","Yes","",""],["Deformable\nregistration","","","Establishing a point-to-point mapping between two\nimages using a deformation model. Used for mapping of\ndose and structures between images.","","","No","",""],["DICOM RT\nexport","","","Export of images, structure set, plan, and dose according\nto the DICOM RT standard.","","","Yes","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p8-t0","doc_id":"K240398","page_num":8,"bbox":[71.06,122.3,524.26,717.7],"n_rows":6,"n_cols":3,"columns":["DICOM RT\nimport","Import of images, structure set, plan, and dose according\nto the DICOM RT standard.","Yes"],"rows":[["DICOM RT\nimport","Import of images, structure set, plan, and dose according\nto the DICOM RT standard.","Yes"],["Dose calculation\nelectrons","For electron beams RayStation calculates dose by the\nMonte Carlo technique. The electron beam phase space\nis generated in run time by sampling from a phase space\nmodel where the electrons are created at the secondary\nscattering foil. Electron transport towards the patient\nand energy transport and scoring in the patient is done\nusing the Monte Carlo algorithm.","Yes"],["Dose calculation\nphotons","For photon beams RayStation calculates dose by the\npoint kernel superposition method (a.k.a. Collapsed\nCone) or a Monte Carlo algorithm for radiation transport\n(8.1 onwards). The incident energy fluence is modeled as\na superposition of a primary energy fluence and a scatter\nenergy fluence. The dose contribution from\ncontamination electrons is calculated by a pencil beam\nalgorithm.","Yes"],["Dose calculation\nproton","For proton beams RayStation uses either the pencil\nbeam algorithm with the Fermi-Eyges formalism, or a\nMonte Carlo algorithm for radiation transport (6.0\nonwards). For passive beams the beam model accounts\nfor the collimator and compensator block. For scanning\nbeams the beam model accounts for the spot phase\nspace including effects of air-scatter and beam paths\nthrough magnetic deflection elements. The user defined\nblock aperture is taken into account in spot selection and\noptimization. In addition to this the relative biological\neffect (RBE) of proton beams is taken into account,\nresulting in a photon equivalent dose (8.1 onwards).","No"],["Dose calculation\nbrachy","For brachy plans RayStation calculates dose based on the\nTG43 formalism.","Yes"],["Dose display\n(2D)","Displays the patient geometry with structures\nsuperimposed on the image data together with the dose\ndistribution in transversal, sagittal, and coronal\ndirections.","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p9-t0","doc_id":"K240398","page_num":9,"bbox":[71.06,122.3,524.26,757.3],"n_rows":7,"n_cols":3,"columns":["Dose tracking","Dose tracking scenarios including deformable\nregistration of one CT or CBCT to another and\nsubsequent deformation and accumulation of dose.","No"],"rows":[["Dose tracking","Dose tracking scenarios including deformable\nregistration of one CT or CBCT to another and\nsubsequent deformation and accumulation of dose.","No"],["Eye planning","Tools for specifying a highly detailed geometrical model\nof the eye based on measurements from ultrasound and\nsurgery. Support for positioning of tantalum clips. Import\nand visualization of fundus images. Creation and dose\ncomputation of proton plans with gaze angle based\ntreatment directions","No"],["Fallback\nplanning","Automatic generation of fallback plans using alternative\ntreatment machines and treatment techniques. User-\ndefined protocols specifies the setup of the fallback\nplans which are automatically generated from the\nprotocols and optimized using dose mimicking functions.","No"],["Image\nconversion","Conversion of CBCT images to synthetic CT images that\ncan be used for more accurate dose calculations.","No"],["Inverse planning","The user can define optimization settings such as\noptimization tolerance and maximum number of\niterations as well as segmentation settings on the\nmultileaf collimator and the Pencil Beam Scanning spot\npattern. An interface for controlling the optimization\nprocess is provided and the progress of optimization is\ndisplayed in a view. The system generates control points\nfor step-and shoot MLC plans, Sliding Window plans\n(DMLC), rotational plans (VMAT), 3DCRT plans, Wave Arc\nplans, TomoTherapy plans (6.1 onwards), proton, Pencil\nBeam Scanning plans, using the defined optimization\nproblem. The inverse planning can be carried out either\nthrough a conventional inverse approach or by using\nmulti-criteria optimization (photons and protons only).","Yes, but not for\nWave Arc plans or\nproton planning."],["LET evaluation","Computation and evaluation of dose-averaged linear\nenergy transfer for proton plans. LET is an additional\nphysical quantity that can be used to assess the\nradiobiological effect of the proton radiation.","No"],["LET\noptimization","Possibility to include optimization functions on the dose-\naveraged linear energy transfer in addition to the dose\nfor proton PBS.","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p10-t0","doc_id":"K240398","page_num":10,"bbox":[71.06,122.3,524.26,766.78],"n_rows":8,"n_cols":3,"columns":["Machine\ndatabase","Microsoft SQL database for storage of beam model\nparameters, machine constraints and dose curves with\ndosimetric data for treatment units.","Yes"],"rows":[["Machine\ndatabase","Microsoft SQL database for storage of beam model\nparameters, machine constraints and dose curves with\ndosimetric data for treatment units.","Yes"],["MR based\nplanning","Allowing MR-images as planning images and base dose\ncomputation on material override ROIs.","Yes"],["Optimization\nfunctions","The optimization functions are specified in terms of\nobjectives and constraints to form the optimization\nproblem that is solved by the optimization engine.","Yes"],["Patient\nanatomy\nmodeling","Manual and semi-automatic segmentation tools for\ncontouring ROIs slice by slice together with semi-\nautomated generation of the patient outline ROI.\nThe model-based segmentation technique allows for\nsemi-automatic delineation of structures by matching 3D\nshape models of the structures to new image data.\nWith atlas-based segmentation, the user can define\ntemplates consisting of already segmented image data\nand use this template for segmentation of new patient\nimages.\nWith deep learning segmentation, the user can use\ntrained deep learning models for automatic\nsegmentation of new patient images. (The model\ntraining is performed offline on clinical CT and structure\ndata.)","Yes, but not for\natlas based\nsegmentation or\ndeep learning\nsegmentation."],["Patient\ndatabase","Microsoft SQL database for storage of all patient and\nplan data. Not for long term storage.","Yes"],["Plan Explorer","The system computes a large set of plans according to\ngiven rules and the user is provided with tools to select\ngood plans from these.","No"],["Proton arc\nplanning","Generation of rotational proton arc plans. Support for\ndiscrete PBS arcs.","No"],["Quality\nassurance\npreparation","Tools for transferring the clinical plan to a phantom and\nrecalculate dose. The output is the dose distribution in\nDICOM format or a 2D dose plane and a QA report.\nPredicted EPID response is retrieved by photon dose\ncomputation in a specially designed phantom.","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p11-t0","doc_id":"K240398","page_num":11,"bbox":[71.06,122.3,524.26,751.18],"n_rows":9,"n_cols":3,"columns":["RBE dose\nhandling","RBE (Relative Biological Effectiveness) models can be\ndefined and commissioned. For proton treatments (8.1\nonwards), the user can select whether to look at RBE-\ncorrected dose or physical dose. Dose summation is only\npossible for photon doses and RBE-corrected proton\ndoses.","No"],"rows":[["RBE dose\nhandling","RBE (Relative Biological Effectiveness) models can be\ndefined and commissioned. For proton treatments (8.1\nonwards), the user can select whether to look at RBE-\ncorrected dose or physical dose. Dose summation is only\npossible for photon doses and RBE-corrected proton\ndoses.","No"],["Robust\nevaluation","Tools used to answer questions of how the dose\ndistribution would appear if the patient setup at the\ntime of treatment does not fully correspond to the\nplanning CT. A model of patient uncertainties such as CT\ninaccuracy and setup errors is used to compute a set of\nscenario doses for evaluation.\nUp to version 8.1 the support was limited to\ncomputation of one scenario at a time in Plan Evaluation.","No"],["Robust\noptimization","Optimization where a model of patient uncertainties\nsuch as CT inaccuracy, setup errors or organ motion is\nused during the optimization.","No"],["Scripting","Scripting gives programmatic access to functionality,\nexcluding user risk mitigations. Through scripting, the\nclinic specific procedures can be automated. The\noperating system and other applications can be\naccessed.","No"],["Supported\ntreatment\npositions","HFS, FFS, HFP, FFP","Yes"],["","Decubitus left/right","Yes"],["","Seated position (for proton)","No"],["System integrity\ntools","Hardware based license, preventing unauthorized\nuseable copies to be made. Checksum control of binary\nfiles to prevent tampering. Data in the patient and\nmachine databases only available for users with\nadministrator rights.","Yes"],["TomoTherapy\nplanning","Planning for TomoTherapy machines is completely\nintegrated in RayStation. Also provides tools for\nselection of targets and imaging angles for the\nTomoTherapy machine to use for target tracking during\ndelivery.","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p12-t0","doc_id":"K240398","page_num":12,"bbox":[71.06,122.3,524.26,492.91],"n_rows":7,"n_cols":3,"columns":["","Supported techniques: TH = TomoHelical, TD =\nTomoDirect",""],"rows":[["","Supported techniques: TH = TomoHelical, TD =\nTomoDirect",""],["Treatment\nadaptation","A general concept where the treatment plan is adapted\nduring the course of treatment. Tools available today\ninclude deformable dose accumulation, CBCT dose\ncalculation and replanning scenarios.","No"],["Treatment plan\napproval","Approval of the preferred treatment plan and referenced\nROIs by authorized medical staff. Once a treatment plan\nis approved, it is locked for any further modification.","Yes"],["Treatment plan\ncreation","Treatment plan creation with specification of plan\nproperties such as number of fractions and delivery\ntechnique.","Yes"],["Treatment plan\nevaluation","Evaluation of a single plan. Comparison of dose\ndistributions and DVH curves of two or three plans.","Yes"],["Undo/redo and\nauto recovery","The undo stack is saved to the database, enabling\nrecovery of RayStation after crash. The user may redo all\nor selected changes at reopen of patient after crash.","Yes"],["Virtual\nSimulation","Setup of isocenter, beam arrangements and basic\naperture design. Export to laser systems for patient\nmarking.","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p13-t0","doc_id":"K240398","page_num":13,"bbox":[70.85,486.81,535.52,741.94],"n_rows":8,"n_cols":5,"columns":["Item","","Compared to","","Comment"],"rows":[["Item","","Compared to","","Comment"],["","","RayStation 12A","",""],["Hardware platform","Substantially Equivalent","","","RayStation 2024A SP3, 2024A, 2023B and 12A all use\nstandard office PCs as hardware platform."],["Operating system","Substantially Equivalent","","","RayStation 2024A SP3, 2024A, 2023B and 12A all use\nWindows 10 Professional (or higher) and Windows Server\n2012 R2 (or higher). See RayStation 2024A System\nEnvironment Guidelines for details."],["Target population","Substantially Equivalent","","","RayStation 2024A SP3, 2024A, 2023B and 12A are intended\nfor the same target population and anatomical sites; persons\nthat have been prescribed an external beam radiation\ntherapy or chemotherapy treatment."],["Anatomical sites","Substantially Equivalent","","",""],["Human factors","Substantially Equivalent","","","In terms of human factors, the systems are considered\nequivalent. Minor updates only. The user interfaces use the\nsame framework with the same controls and views."],["Standards met","Substantially Equivalent","","","RayStation 2024A SP3, 2024A, 2023B and 12A all comply\nwith the IEC 61217, IEC 62083, IEC 62304, IEC 62366-1 and\nISO 14971."]],"caption_candidate":"General features comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p14-t0","doc_id":"K240398","page_num":14,"bbox":[70.85,122.44,535.52,377.45],"n_rows":7,"n_cols":5,"columns":["Item","","Compared to","","Comment"],"rows":[["Item","","Compared to","","Comment"],["","","RayStation 12A","",""],["Image types","Substantially Equivalent","","","RayStation 2024A SP3, 2024A, 2023B and 12A all support CT,\nPET and MR images for identifying patient organs and\ncontouring."],["Reporting aspects","Substantially Equivalent","","","When evaluating and approving treatment plans, all\nnecessary data is presented to the user and available in print\nin all systems."],["Image storing","Substantially Equivalent","","","None of the systems are intended for long term storage of\nimages or other patient data."],["Network / remote\nconnections and\ncapabilities","Substantially Equivalent","","","All systems are capable of network transfer of patient data\nusing the DICOM protocol. RayStation 2024A SP3, 2024A,\n2023B and 12A are designed for desktop use and for remote\naccess using standard virtualization techniques. Remote\nconnection to the system is verified in detail and equivalent\nto local connection."],["Cybersecurity","Substantially Equivalent","","","No architectural changes or major new features that affect\ncyber security."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p14-t1","doc_id":"K240398","page_num":14,"bbox":[49.68,538.69,574.04,769.06],"n_rows":7,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["Dose compensation point\ncomputation for Tomo\nSynchrony","A new way of computing the dose compensation point was added\nsince the previously exported position was suboptimal. The point\nis calculated by taking the center of the volume formed of the\ndose voxels with dose above 90% of the max dose.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["RayStation does not\npopulate\nDoseCompensationPoint\ncorrectly for TomoMotion\nplans","Related to the item above. The DICOM export was updated so\nthat the dose compensation point coordinates in IDMS are\npopulated with the correct coordinates (as defined in the related\nitem above).","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of"]],"caption_candidate":"compared with predicate device, RayStation 12A is presented in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p15-t0","doc_id":"K240398","page_num":15,"bbox":[49.65,122.6,574.06,756.58],"n_rows":8,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","","safety or\neffectiveness"],["Most distal energy layer\nmissing causing ripples in\ndose distribution for box\ntarget in water phantom","Ripples sometimes occurred in the distal edge of Pencil Beam\nScanning dose distributions for box targets in water phantoms in\ncombination with some dose grid setups.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Improved replanning","The improvement to adaptive replanning is to remove dialog\noptions to simplify the workflow and to allow the user to select\nwhether to include background dose or not.\nAdaptive replanning allows the user to adapt the treatment to a\nchanging patient geometry. Reasons for when a patient is\nselected for replanning can vary between treatment protocols.\nReplanning should be performed when the plan is no longer\nsuitable for treatment and when it has become necessary to\nadapt the plan to the new circumstances.\nThe prerequisite for adaptive replanning in RayStation is an\napproved treatment plan. The approved treatment plan that is\nselected for adaptation is called the base plan. The new adapted\nplan will be a copy of the base plan. In previous versions of\nRayStation there was a separate dialog for creation and editing of\nadapted plans. The New/Edit adapted plan dialog displayed all\nplan parameters copied from the base plan, and the parameters\n(such as treatment machine) were editable.\nTo simplify the plan adaptation workflow with less options, and to\nsimplify the code design, the Create adaptive plan dialog in the\nnew version of RayStation only provides some basic plan\nparameters such as plan name and selection of planning image\nset. If the user wants to change other parameters, the plan can be\nedited using the regular Edit plan dialog after creation.\nAlso, with previous versions of RayStation, adapted plans were\nalways made taking background dose into account. Either the\naccumulated delivered dose for previous fractions (computed in\nthe Dose tracking module) or the planned dose for a number of\nfractions. The background dose was considered when optimizing\nthe adapted plan on the new image set.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p16-t0","doc_id":"K240398","page_num":16,"bbox":[49.62,122.6,574.08,770.74],"n_rows":9,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","The new RayStation version makes it possible also to create\nadapted plans without taking any background dose into account.\nThis change allows a quick and simple replanning workflow where\na base plan is quickly adapted to the daily patient geometry.",""],["Improved dose tracking","The Dose tracking module in RayStation is used to evaluate the\nactual delivered dose to the patient to evaluate daily changes as\nwell as to evaluate trends as the treatment progresses. With\nprevious versions of RayStation it has been possible to do dose\ntracking for one selected treatment plan. For each fraction it was\npossible to import and to compute dose for the plan selected for\ndose tracking on the treatment time image of the patient. When\nconsidered needed a new plan, based on the original plan but\nadapted to a new image of the patient, could be made and be\nused as basis for subsequent dose tracking.\nWith the new version it is possible to select which treatment plan\nor beam set to use for dose tracking per fraction, to be able to\nfully simulate the actual treatment. In several scenarios you treat\nwith different plans on different fractions, e.g. based on bladder\nfilling. With the new version it is also possible to add and remove\nfractions to the treatment course.\nThis limited change in RayStation makes the dose tracking\nfunctionality more useful since they can be used in more\ntreatment scenarios.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Delete ROI contours in all\nslices except every n:th","This change increases usability when the user manipulates patient\nimage contours.\nWhen editing existing region of interests (ROIs) it sometimes is\nefficient to delete contours on certain image slices and to let\nRayStation's interpolation algorithm create new contours on\nthose slices. In previous versions of RayStation the user could\ndelete a complete ROI geometry or one contour at a time.\nWith the new version of RayStation, contours in several slices for\nthe selected ROI can be deleted, keeping contours in e.g. every\n2nd, 3rd or 5th slice. Optionally, it is possible to define a limited\nrange of image slices within which to do this.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Allow voxelwise min/max\ndoses if scenario group\ncontains a single image set\nScripting access to\nvoxelwise min/max dose","This change enables an evaluation criterion for more scenarios\nand brings scripting closer to what is already enabled for the user\nthrough the device graphical user interface.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p17-t0","doc_id":"K240398","page_num":17,"bbox":[49.65,122.6,574.06,770.02],"n_rows":8,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["distributions in robust\nevaluation","Possibility to compute voxelwise min/max doses as long as all\nscenarios are on a single image set. The image set is no longer\nrestricted to being the nominal image.\nScripting access to the clinical goal results with respect to the\nvoxelwise min/max distributions for a scenario group. Scripting\naccess to the actual voxelwise min/max dose distribution. These\ncould not be accessed using scripting in previous versions.","safety or\neffectiveness"],["Various DICOM\nimprovements","Two new treatment machine settings for export have been added\nin machine modeling to improve integration with Varian’s Aria\nsystem.\n1) Possibility to configure if jaws shall be exported as\nASYMX/ASYMY or X/Y. X/Y is set in the exported file (instead of\nASYMX/ASYMY) for machines that have this setting and all\nsegments in all beams are symmetrical.\n2) Setting that will remove MLC settings from export for cone\nplans, if all MLC positions are “withdrawn”.\nThe machine settings have been added for DICOM plans exported\nfrom RayStation to comply with Varian’s Aria system.\nAdded the possibility to define the default DICOM export target.\nThis is useful to make the folder that is most often used for\nexport, the folder selected by default.\nA new machine configuration for omitting pixel intensity\nrelationship attributes in the export has been added for enhanced\ncompatibility with other systems. In RayStation 11B, the attributes\n(0028, 1040) Pixel Intensity Relationship and (0028, 1041) Pixel\nIntensity Relationship Sign were added to the export of RT\nImages. The value ‘OTHER’ for Pixel Intensity Relationship Sign has\nrecently been added to the DICOM standard and hence some\nolder systems cannot handle that value. This new option makes it\npossible to exclude the attributes at export, when Pixel Intensity\nRelationship Sign = ‘OTHER’.\nAdded possibility to select if option “Delete original DICOM files\nafter import” shall be default. This is useful to have the original\nDICOM files deleted by default after import.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Point-dose optimization in\nbrachy plans","Change to increase usability by allowing the user to work with\noptimization objectives and constraints for points of interest\n(POI)s in a way similar to what was already available for regions of\ninterest (ROI)s.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p18-t0","doc_id":"K240398","page_num":18,"bbox":[49.6,122.6,574.09,758.14],"n_rows":10,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","It is now possible to add objectives and constraints on POIs. The\nsupported function types are Min dose, Max dose and Target\ndose. Otherwise, the functions work similar to ROI functions.\nIn this way it is possible to perform planning without delineating\ntargets and OARs.",""],["Electron Monte Carlo dose\nengine improvements","Minor improvements to the new electron Monte Carlo dose\nengine version (introduced in RayStation 12A). The user\nnoticeable updates are multi-GPU support and support for\ndifferent shapes of collimator tips.\nMulti-GPU: For performance reasons, the user can select to\ndistribute the computation on multiple GPUs if the computer\nrunning RayStation has more than one GPU card. Distributing the\ncomputation on multiple GPUs will make it faster. The computed\ndose is identical between one or multiple GPUs and thus accuracy\nis not affected.\nDifferent tip shapes: The user can specify in the machine model if\nthe shape of the MLC and jaw tips should be focused or rounded.\nPreviously, focused tips were always used. The selected tip shape\nis used during dose computation, giving a more accurate\ndescription of the physical machine.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Linac machine parameter\nimprovements","The changes are done to achieve more exact simulation in\nRayStation of how MLC leaves and jaws are positioned in the\nmachine during delivery.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Automated field in field\nplanning","The new Auto field-in-field tool is used to create a field-in-field\nplan based on the primary prescription and a primary field that is\neither defined by a target plus a user defined margin or by the\nfirst segment in each beam. The algorithm starts with a primary\nfield and subfields are added iteratively to irradiate low dose\nregions. The tool automatically:\n- creates subfields based on low dose regions\n- adjusts segment weights\n- computes final dose and scales to prescription\nThe tool automates a workflow that previously has been possible\nto do manually.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Segment weight\noptimization using photon\nMonte Carlo added","Optimizing with respect to only segment weights, called Segment\nMU in the RayStation user interface, were previously only\navailable for one of the two clinical photon dose engines in\nRayStation, the Collapsed Cone dose engine. Now segment weight","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p19-t0","doc_id":"K240398","page_num":19,"bbox":[49.62,122.6,574.08,770.74],"n_rows":9,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","optimization is possible also when using photon Monte Carlo, the\nother clinical photon dose engine in RayStation.\nIn the RayStation user interface, it’s possible to select to optimize\nwith respect to Segment shapes and/or Segment MU. In 12A\nhowever, it was not allowed to start Segment MU only\noptimization with photon Monte Carlo selected. With photon\nMonte Carlo selected in 12A, it was only possible to optimize\nSegment shapes individually or Segment shapes together with\nSegment MU. With Collapsed Cone selected, it was possible in\n12A to optimize Segment shapes individually, Segment MU\nindividually or Segment shapes together with Segment MU.\nIn 2023B all options are available with photon Monte Carlo\nselected as well.\nThis change makes it possible to utilize the more accurate Monte\nCarlo dose engine in more planning scenarios.","safety or\neffectiveness"],["Photon Monte Carlo dose\nengine: Improved positron\nhandling","The photon Monte Carlo dose engine has been improved with\nrespect to positron physics. For external beam treatment\nenergies, the difference in computed dose is small, but\nremodeling of photon and electron Monte Carlo machine models\nis required. The most noticeable change in computed dose before\nremodeling is the output for larger field sizes for photon Monte\nCarlo. There are no changes to the RayStation user interface.\nThis change further improves the accuracy of computed photon\nMonte Carlo dose.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Improvements to\nconformity of broad beams\nwhen using compensator\nsmearing/gradient","For proton broad beam techniques, manual editing of the\ncompensator shape is sometimes done to optimize the dose\ndistribution. Clinics reported that for some plans where smearing\nwas applied after manual compensator editing, the modulation\ngot insufficient to cover the proximal edge of the target. For\nproton broad beam techniques, \"Compute beam SOBP\" (spread\nout Bragg peak) now traces through the actual shape of the\ncompensator and proton wedge (if present).\nThis change makes it easier to get a good conformance to the\ntarget after manually editing the compensator or applying\nsmearing and gradient tools.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["LET optimization","Linear energy transfer (LET) is a quantity that, in combination with\nthe dose, provides information about the biological effect of the\nradiation. Typically, in risk organs you want to avoid high LET in\ncombination with high dose. High LET with low dose is more","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p20-t0","doc_id":"K240398","page_num":20,"bbox":[49.62,122.6,574.08,770.74],"n_rows":9,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","acceptable. Areas of the body that receive high dose and high LET\ncan experience more cell death, which is desirable in the tumor,\nbut harmful to normal tissue.\nThe new version of RayStation supports optimization on dose-\naveraged linear energy transfer (LETd) for protons. This can be\nused to lower LET in risk organs, which could reduce potential side\neffects of radiotherapy. Possibility to add Max LETd and Min LETd\noptimization functions in addition to standard dose optimization\nfunctions has been added.","safety or\neffectiveness"],["Evaluation on converted\nCBCT images for protons","This is a change to enable users to visualize proton dose on CBCT\nimages for evaluation only. The images cannot be used for\nplanning and the dose cannot be used clinically.\nIt is possible to compute an evaluation dose on converted CBCT\nimages for protons. It is not possible to use such an image for\nplanning. The conversion algorithms themselves are the same as\nthose already clinically available for photons.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Support for discrete proton\narcs","PBS Arc is a new treatment technique in RayStation. However,\nsince the arc plans are exported as regular PBS plans, with many\nfields per plan instead of many segments per field, this is an\nadministrative change.\nRayStation 2023B includes optimization of discrete PBS arc plans\nwhere the gantry is stationary during dose delivery, as opposed to\ndynamic arc plans where the gantry moves during delivery.\nDiscrete PBS arc optimization involves:\n- Many gantry angles per beam, where multiple energy layers are\ndelivered per gantry\nangle.\n- Easy setup including air gap computation for collision avoidance.\n- Iterative reduction of energy layers during optimization to\nreduce delivery time.\nPBS arc plans must be converted into regular PBS plans with many\nbeams, to be available for export out of RayStation.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Separate clinical goals per\nbeam set and plan","This change increases usability for evaluation of clinical goals.\nIt is now possible to specify which dose to evaluate a specific\nclinical goal on.\nClinical goals are clearly grouped by plan and beam set in the\nGUI.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p21-t0","doc_id":"K240398","page_num":21,"bbox":[49.6,122.6,574.09,758.14],"n_rows":10,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","In previous versions all clinical goals are evaluated on the\ncurrently selected dose (plan dose/beam set dose/beam\ndose/etc).",""],["Support and fixation\nstructures per beam set","This change increases usability by not forcing all beam sets to\nhave the same couch and fixation device settings.\nThis is to support the possibility to use different couches and\ndifferent fixation devices for different beam sets. (E.g. changing\ntreatment machine often means changing to a different kind of\ncouch.)\nOnly selected fixation and support ROIs will be included in dose\ncomputation.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["One-click creation of\nsynthetic CT","This change increases usability for creation of synthetic CT.\nIn previous versions, to create a sCT using the CBCT correction\nalgorithm or the virtual CT algorithm, the user had to provide a\npre-created deformable registration between refCT and CBCT as\nwell as a pre created Field of View (FOV) ROI on the CBCT. Also –\nan external was required on the CBCT. The new functionality\nallows sCT to be created from two rigidly registered refCT and\nCBCT.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Modality of sCT shall be CT","This change increases the usability when handling CBCT images.\nThe user can now freely choose the imaging system of a\nconverted CBCT image. Converted CBCT images fetch their HU-to-\nmass density table from their imaging system rather than from\nthe imaging system of the reference CT image. As a result, the\nmodality of such images will correspond to that of the chosen\nimaging system which in most cases will be CT instead of CBCT.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Various GUI improvements\nthroughout the system","- Adjusted treatment delivery information in Patient data\nmanagement module\n- ROI/POI lists initially sorted alphabetically\n- Sorting on sub-columns for some tables\n- Reduced size of aperture shapes toolbar\n- Show beam parts, Volume rendering settings and DRR settings\ndialogs are now non-modal\n- Improved performance of “Copy to all” of Visualization settings\nin ROI/POI details\n- Image conversion histogram updated to follow the color scheme\nin the fusion view\n- Show segment number in BEV\n- Possibility to translate also plan reports and the Report Designer","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p22-t0","doc_id":"K240398","page_num":22,"bbox":[49.62,122.6,574.08,757.3],"n_rows":9,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["Various workflow\nimprovements","These are changes for increased usability.\n- Creating structures from template now have the option to\nautomatically update derived ROIs.\n- Option to replace existing clinical goals when applying template.\n- Option to replace existing optimization functions when applying\ntemplate.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Various general system\nimprovements","These are changes for increased usability.\n- Treat and Protect settings are now scriptable for all modalities.\nNotably for protons and electrons.\n- Possibility to copy objectives and constraints\n- Function values are no longer automatically computed after final\ndose\n- Relative dose value has been added to Dose cloud visualization\n- Faster saving of patient data\n- Faster Bragg Peak rendering\n- For DICOM data where a filter has been applied the Transfer\nSyntax Implicit VR Little Endian will always be used","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Material view refactoring","This change increases usability of the material visualization view.\nMake the material visualization view less error prone and possible\nto use with beam set specific support/fixation ROIs. This will lead\nto limitations in the current functionality; no material view will be\nshown when there is no computed dose, and the material\nvisualization view will only be shown for beam set and beam\ndoses. One extension to the current functionality is made;\nmaterial will be visualized for Bolus ROIs for beams with the Bolus\nROI assigned.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Updated DRR UID handling","This is an administrative change for handling unique identifiers\n(UIDs).\nIn the 2024A RayStation/RayCare releases, a joint goal is to be\nable to deliver treatment plans using Varian TrueBeam machines.\nIn that interface, information about the RT Images/ Digitally\nReconstructed Radiographs (DRRs) that will be used for delivery\nneeds to be provided. To avoid incorrect RT Images being used at\npatient positioning, RayStation needs to produce deterministic\nUIDs for exported RT Images. The logic to generate DRRs has\npreviously been spread out and duplicated in various places in\nRayStation. Now the modelling of DRRs will be centralized in the\nRayStation domain model which will both solve the immediate","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p23-t0","doc_id":"K240398","page_num":23,"bbox":[49.58,122.6,574.1,758.86],"n_rows":11,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","issues and decrease the risk of introducing future problems when\nthe DRR generation is updated.",""],["Dose rate for setup beams","This is a change to fulfill an administrative interface requirement\nsince a dose rate for a setup beam does not have any function.\nPossibility to set a dose rate for RayStation setup beams when\nusing a Linac treatment machine.\nThe dose rate for setup beams is defined per Linac treatment\nmachine in RayPhysics.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Display brachy channel\nnumbers in 3D view","This is a change to increase usability.\nIt shall be possible to display channel numbers in the 3D view.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Improved shape\nconversion","This is a change to increase performance and accuracy of a\ncalculation. The specifications are the same and there is no design\nchange.\nNew algorithm for converting triangle mesh ROIs to voxel ROIs.\nImproves accuracy of the conversions at first and last slice of ROI\nand improves performance for cases with a lot of mesh ROIs.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["General patient modeling\nimprovements","These are changes to increase the usability of patient modeling\nworkflows.\n- ROIs grouping by body site in DLS dialog\n- Possibility to create ellipsoid ROIs\n- Default names for MBS ROIs now follow the TG263 standard\n- Improved non-uniform expansion/contraction of ROIs\n- Delete multiple contours (keeping every n:th) now works in all\nview directions\n- Possibility to add colors for ROIs in RayMachine","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Image registration\nimprovements","This change improves the visualization of the image registration\nworkspace.\nThe ‘Deformation grid’ in the Deformable registration module\nview now shows image set in the same direction as the reference\nimage set for easier comparison.\n- The floating view in the Image registration module has been\nupdated and improved. It now works like it did in RayStation 11A\nand earlier versions. Position, Direction","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p24-t0","doc_id":"K240398","page_num":24,"bbox":[49.65,122.6,574.06,770.02],"n_rows":8,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","(transversal/sagittal/coronal), Patient direction letters, Imaging\nsystem name and Slice number are again displayed in the floating\nview.",""],["Improved Varian TrueBeam\nintegration","This is an administrative change to fulfill interface requirements\nfrom other devices.\nThe new RayStation version supports indicating export of plans\nwith high MU values as High-Dose Technique Type plans. The\nversion also includes improved Dose Reference Description\nhandling.\nIn RayPhysics, it is possible to define MU thresholds for different\ntreatment techniques. The thresholds are defined per treatment\nmachine. When exporting a treatment plan, the DICOM tag (300A,\n00C7) in the RTPlan is set to SRS for beams where MU exceeds the\nthreshold.\nThe population of the DICOM attributes Prescription Description\nand Dose Reference Description has been updated. Previously,\ndefault values were used to populate these attributes. For the\nDose Reference Description, it is now possible to select between\nfour different default modes for populating the values. This\nsetting can be configured per machine. It is also possible to set\nuser defined overrides for both attributes.\nThese options are added to reduce the need to manually edit the\nproperties after importing a plan into other systems.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Improved sliding window\nVMAT sequencing","Control points are key elements in defining the delivery of a\nbeam. They specify how the beam parameters change over the\ncourse of the treatment delivery. A beam typically contains\nmultiple control points to describe the beam’s modulation and\nmovement. One important attribute of a control point is the\ngantry angle.\nIt was found that for VMAT beams, the way RayStation used\ndecimal distances between control points could lead to treatment\nplans that could not be delivered by the treatment machine (e.g.\nbecause they violated machine constraints such as maximum\ngantry speed) since the gantry angles had to be rounded to fewer\ndecimals when the plan was exported to DICOM.\nIn the new version the sliding window VMAT sequencing\nalgorithm has been modified to create control points with a","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p25-t0","doc_id":"K240398","page_num":25,"bbox":[49.6,122.6,574.09,758.14],"n_rows":10,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","gantry spacing of exactly 2 degrees, as opposed to a gantry\nspacing of maximum 2 degrees. This change ensures that the\ncreated VMAT beams are deliverable on the treatment machine.",""],["Varian Halcyon in EPID\nvalidation","This change enables the previously existing functionality to be\nused for one additional electronic portal imaging device (EPID).\nThe EPID QA functionality has now also been validated for Varian\nHalcyon.\nEPID measurements using a Varian Halcyon LINAC have been\nadded to the EPID QA validation. All validation measurements\npass the acceptance criteria, and the license for EPID QA can be\nmade available also for Varian Halcyon users.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Possibility to use\nbackground proton dose\ncomputed on converted\nCBCT","With this change, a proton dose computed on a converted CBCT\nimage set can also be used as background dose in optimization\nand in adapted plans.\nWith the previous version, it was possible to compute evaluation\ndose on converted CBCT images for protons. The image\nconversion algorithms are the same as those already clinically\navailable for photons.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Higher dose grid resolution\nfor proton PBS","In RayStation the dose grid defines the volume where dose is to\nbe computed. The finer resolution the dose grid has, the more\naccurate is the computed dose. (The dose takes longer to\ncalculate with a finer dose grid, and more data is created, so there\nare trade-offs between high resolution and performance.)\nPrevious versions of RayStation had support for a dose grid\nresolution down to 1x1x1 mm.\nFor treatments of small areas, it can be beneficial to be able to\nuse very fine dose grids. Treatments of eye cancer is one such\nexample. To better support these kinds of treatments RayStation\nnow supports dose grid resolutions down to 0.5 mm when using\nthe proton PBS Monte Carlo and Pencil Beam dose engines. This\nincludes support for computing curves at this high resolution in\nRayPhysics, as well as for computing proton curves at non-\nuniform resolution in RayPhysics.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Upgrade of CUDA","CUDA (Compute Unified Device Architecture) is a parallel\ncomputing platform and API developed by NVIDIA, enabling\ndevelopers to leverage NVIDIA GPUs (Graphics Processing Units)\nfor general-purpose processing. It enhances performance by\nallowing the execution of thousands of parallel threads. CUDA is\nused in several algorithms in RayStation that utilize the GPU, e.g.,\nin dose engines and algorithms for deformable registration.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p26-t0","doc_id":"K240398","page_num":26,"bbox":[49.65,122.6,574.06,493.51],"n_rows":8,"n_cols":3,"columns":["Added/updated function in","Description of the RayStation function","Compared to"],"rows":[["Added/updated function in","Description of the RayStation function","Compared to"],["RayStation 2024A SP3,","","RayStation 12A"],["2024A and 2023B","","K222312"],["compared with predicate","",""],["device, RayStation 12A.","",""],["","The platform used for GPU computations in RayStation (CUDA)\nhas been upgraded to version 12.2 to support new hardware\nenvironments and compiler versions. The platform upgrade does\nnot affect the use of GPU calculations withing the treatment\nplanning workflow.",""],["FSN/recall corrections","• RES 91867/FSN 109886: DICOM export from the Virtual\nSimulation module\n• RES 94153/FSN 130646 Remove template material 'Silicon\n[Si]'\n• RES 94388/FSN 133261: Incorrect early exit in SSD\n• RES 96156/FSN 148655: Density perturbation in\nPerturbed dose and Robust eval gives a lower range\nperturbation","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"],["Minor bug fixes","Fixed minor performance issues, such as crashes and low speed,\nto bring product to its initial specifications.","Substantially\nEquivalent. The\nfeature does not raise\ndifferent questions of\nsafety or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p27-t0","doc_id":"K240398","page_num":27,"bbox":[71.09,233.3,538.65,424.73],"n_rows":7,"n_cols":9,"columns":["","Standard No.","","","Standard Title","","","Recognition no.",""],"rows":[["","Standard No.","","","Standard Title","","","Recognition no.",""],["IEC 61217","","","Radiotherapy equipment - Coordinates movements\nand scales","","","12-267","",""],["IEC 62304","","","Medical device software - Software life cycle\nprocesses","","","13-79","",""],["IEC 62366-1","","","Medical devices - Part 1: Application of usability\nengineering to medical devices","","","5-129","",""],["ISO 14971","","","Medical devices - Application of risk management to\nmedical devices","","","5-125","",""],["IEC 62083","","","Medical electrical equipment - Requirements for the\nsafety of radiotherapy treatment planning systems","","","12-217","",""],["IEC 81001-5-1","","","Health software and health IT systems safety\neffectiveness and security - Part 5-1: Security -\nActivities in the product life cycle","","","13-122","",""]],"caption_candidate":"Standards applied:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240398-p31-t0","doc_id":"K240398","page_num":31,"bbox":[42.63,122.6,567.04,622.99],"n_rows":10,"n_cols":3,"columns":["Added/updated","Verification and validation data used to demonstrate","Substantially equivalent?"],"rows":[["Added/updated","Verification and validation data used to demonstrate","Substantially equivalent?"],["function in RayStation","substantial equivalence",""],["2024A SP3, 2024A and","",""],["2023B compared to","",""],["predicate device,","",""],["RayStation 12A.","",""],["Electron Monte Carlo\ndose engine\nimprovements","Dose engine validation, comparing calculated doses with\nmeasured doses obtained from clinics, doses computed in\nindependent, well-established TPS, doses computed with\nearlier versions of RayStation, and doses computed in\nBEAMnrc/egs++ with Gamma evaluation criteria.","Yes. The successful\nvalidation of this\nfeature demonstrates\nthat the device is as\nsafe and effective as\nthe predicate device."],["Segment weight\noptimization using\nphoton Monte Carlo\nadded","System-level performance of the optimization method\nproposed in the subject device was compared with the\npredicate through resulting plan dose and dose statistics for\nauto breast planning, SMLC, and VMAT plans.","Yes. The successful\nvalidation of this\nfeature demonstrates\nthat the device is as\nsafe and effective as\nthe predicate device."],["Photon Monte Carlo dose\nengine: Improved\npositron handling","Dose engine validation with Gamma evaluation criteria. After\nrecommissioning of the beam model, the dose differences\nbetween photon Monte Carlo computed doses in RayStation\n12A and RayStation 2024A are negligible. The dose engine\nvalidation shows the same level of accuracy as before after\nremodeling.","Yes. The successful\nvalidation of this\nfeature demonstrates\nthat the device is as\nsafe and effective as\nthe predicate device."],["Evaluation on converted\nCBCT images for protons","Test cases consist of CBCTs from the MedPhoton imaging ring\non a Mevion S250i system, as well as the on-board CBCT\nsystems on a Varian ProBeam and an IBA P1.\nTest cases cover validation of 3D dose computed on both the\nCorrected CBCT and Virtual CT. For each case, a ground truth\nCT image has been prepared to serve as ground truth.\nTest criteria:\nGamma 2%/2mm pass rate above 90% for proton MC/PB dose\ncomputation\nGamma 3%/3mm pass rate above 95% for proton MC/PB dose\ncomputation","Yes. The successful\nvalidation of this\nfeature demonstrates\nthat the device is as\nsafe and effective as\nthe predicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p4-t0","doc_id":"K240406","page_num":4,"bbox":[72.5,164.5,534.5,387.5],"n_rows":3,"n_cols":2,"columns":["Applicant:","Sonio\n17RueduFaubourgMontmartre,\n75009,ParisFrance"],"rows":[["Applicant:","Sonio\n17RueduFaubourgMontmartre,\n75009,ParisFrance"],["PrimaryContact Person:","FlorianAkpakpa\nHeadof RegulatoryAffairsandQualityAssurance\nSonio\nPhone:+336 1938 7145\nEmail:florian.akpakpa@sonio.ai"],["Date Prepared:","February9th,2024"]],"caption_candidate":"I. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p4-t1","doc_id":"K240406","page_num":4,"bbox":[72.5,464.5,534.5,606.5],"n_rows":4,"n_cols":2,"columns":["DeviceTradeName:","SonioDetect"],"rows":[["DeviceTradeName:","SonioDetect"],["ClassificationName:","21CFR892.1550-accessorytoUltrasonicPulsedDopplerImagingSystem\n21CFR892.1560-accessorytoUltrasonicPulsedEchoImagingSystem\n21CFR892.2050-MedicalImageManagementandProcessingSystem"],["RegulatoryClass:","ClassII"],["ProductCode:","IYN(primary)\nIYO,QIH(Secondary)"]],"caption_candidate":"II. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p6-t0","doc_id":"K240406","page_num":6,"bbox":[72.25,143.73,523.5,564.5],"n_rows":3,"n_cols":2,"columns":["Trimester","View"],"rows":[["Trimester","View"],["FirstTrimester","1. Transthalamic or Cavum septum pellucidum or Midline\nfalx/Transventricularor ChoroidPlexus\n2. Profile/Nuchaltranslucency\n3. 4Chambers\n4. Abdominalcircumference\n5. Hand\n6. Foot\n7. Crown RumpLength"],["Second and Third\ntrimester","1. Transthalamic or Cavum septum pellucidum or Midline\nfalx/Transventricularor ChoroidPlexus\n2. Transcerebellarview\n3. Profile\n4. LipsandNose\n5. Orbits\n6. 4Chambers\n7. LVOT\n8. RVOT\n9. 3vessels/3vessels andtrachea\n10. SagittalSpine\n11. Abdominalcircumference\n12. AxialBladder\n13. AxialKidneys\n14. Longbone\n15. Hand\n16. Foot\n17. Externalgenitalia(femaleandmale)\n18. Placentainsertion"]],"caption_candidate":"Table1: Listof views pertrimesterthat canbeautomaticallydetectedby Sonio Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p7-t0","doc_id":"K240406","page_num":7,"bbox":[73.12,47.05,518.25,759.2],"n_rows":81,"n_cols":4,"columns":["Sonio","","",""],"rows":[["Sonio","","",""],["510(k) Premarket","NotificationSubmission","",""],["","","",""],["Table2: Listof a","natomicalstructures that canbeautom","aticallydetecte","dby Sonio"],["Detect","","",""],["","","",""],["","","First","Second/Third"],["","","",""],["Viewname","Structures to be detected","",""],["","","TrimesterT1","TrimesterT2/T3"],["","","",""],["Brainviews & st","ructures","",""],["","","",""],["","Thalamionthetransthalamicview","-","X"],["","","",""],["","Cavumseptumpellucidum","-","X"],["","","",""],["Transthalamic","Pillarsof thefornix","-","X"],["","","",""],["view","","",""],["Transventricular","Sylvianfissure","-","X"],["view","Ventricle","-","X"],["Transcerebellar","","",""],["","","",""],["view","ChoroidPlexus","-","X"],["","","",""],["","CisternaMagna","-","X"],["","","",""],["","Cerebellum","-","X"],["","","",""],["Thoraxand Hea","rtviews & structures","",""],["","","",""],["","Adrenalgland","-","X"],["","","",""],["","Apex of theheart","-","X"],["","","",""],["","Descendingaorta","-","X"],["","","",""],["","Interatrialseptum","-","X"],["","","",""],["","Interventricularseptum","X","X"],["","","",""],["","Kidneys","-","X"],["","","",""],["","Leftatrium","X","X"],["","","",""],["","Leftventricle","X","X"],["","","",""],["4chambers","","",""],["3vessels","Mitralvalve","-","X"],["","","",""],["3vessels and","Pulmonaryvein","-","X"],["trachea","","",""],["RVOT","Rightatrium","X","X"],["","","",""],["LVOT","Rightventricle","X","X"],["Abdominal","","",""],["","Stomach","X","X"],["","","",""],["circumference","","",""],["Axialviewof","Superiorvenacava","-","X"],["thekidneys","Tricuspidvalve","-","X"],["","","",""],["","Umbilicalvein","-","X"],["","","",""],["","Ascendingaortaon LVOT View","-","X"],["","","",""],["","Ascending aortaon RVOT or 3vessels","",""],["","","",""],["","","-","X"],["","view","",""],["","","",""],["","Pulmonary artery trunk on 3 vessels","",""],["","","",""],["","","-","X"],["","View","",""],["","","",""],["","Pulmonary artery with visible","",""],["","","",""],["","","-","X"],["","bifurcation","",""]],"caption_candidate":"Sonio","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240406-p8-t0","doc_id":"K240406","page_num":8,"bbox":[72.2,74.23,523.5,450.5],"n_rows":19,"n_cols":4,"columns":["Viewname","Structures to be detected","First\nTrimesterT1","Second/Third\nTrimesterT2/T3"],"rows":[["Viewname","Structures to be detected","First\nTrimesterT1","Second/Third\nTrimesterT2/T3"],["CRL/NT/Profile/Corpuscallosumviews & structures","","",""],["CRL\nNT\nProfile\nCorpus\nCallosum","Nasalbone","X","X"],["","Diencephalon","X","-"],["","FourthventricleonNT view","X","-"],["","Nuchaltranslucency","X","-"],["","Palate","X","X"],["","Corpus Callosum","-","X"],["","Liquidspaceunderthechin","X","-"],["","Midbraintectum","-","X"],["","Vermis","-","X"],["","Choroidplexusonsagittalplane","-","X"],["","CisternamagnaonNT view","X","-"],["","BrainstemonNT view","X","-"],["Placentaview& structures","","",""],["Placenta\ninsertion","Cervix","-","X"],["","Maternalbladder","-","X"],["","Internalcervicalos","-","X"],["","Placenta","-","X"]],"caption_candidate":"510(k) PremarketNotificationSubmission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p9-t0","doc_id":"K240406","page_num":9,"bbox":[72.0,47.05,522.51,761.15],"n_rows":69,"n_cols":5,"columns":["S","onio","","",""],"rows":[["S","onio","","",""],["5","10(k) PremarketN","otificationSubmission","",""],["","","","",""],["T","able3: Listof qu","alitycriteriathat canbeautomaticallyverif","iedby Sonio","Detect"],["","","","",""],["","Viewname","Qualitycriteria","First","Second/Third"],["","","","trimester","Trimester"],["","","","T1","T2/T3"],["","","","",""],["","","Qualitycriteriaof the brainviews","",""],["","","","",""],["","","Presence of the cavum septum pellucidum","",""],["","","or of thepillarsof thefornix","-","X"],["","","","",""],["","","Presenceof thecavumseptumpellucidum","-","X"],["","","","",""],["","Transthalamic","","",""],["","view","Presenceof theSylvianfissure","-","X"],["","","","",""],["","","Absenceof thecerebellum","-","X"],["","","","",""],["","","Presenceof thethalami","-","X"],["","","","",""],["","","Presenceof theventricle","-","X"],["","","","",""],["","Transventricular","Absenceof thethalami","-","X"],["","view","","",""],["","","Presenceof thecavumseptumpellucidum","-","X"],["","","","",""],["","","Presenceof thecerebellum","-","X"],["","","","",""],["","","","",""],["","Transcerebellar","Presenceof thecisternaMagna","-","X"],["","view","","",""],["","","Presenceof thecavumseptumpellucidum","-","X"],["","","","",""],["","","Qualitycriteriaof the thorax and heart","views",""],["","","","",""],["","","Presenceof theLeftventricle","X","X"],["","","","",""],["","","Presenceof theRightventricle","X","X"],["","","","",""],["","","Presenceof theLeftatrium","X","X"],["","","","",""],["","","Presenceof theRightatrium","X","X"],["","","","",""],["","","Presenceof theinterventricularseptum","X","X"],["","4chambers","","",""],["","","","",""],["","","Presenceor theinteratrialseptum","-","X"],["","view","","",""],["","","","",""],["","","Presenceof theapexof theheart","-","X"],["","","","",""],["","","Presenceof themitralvalve","-","X"],["","","","",""],["","","Presenceof thetricuspidvalve","-","X"],["","","","",""],["","","Presenceof thedescendingaorta","-","X"],["","","","",""],["","","Presenceof atleastonepulmonaryvein","-","X"],["","","","",""],["","","","",""],["","3vessels and3","Presenceof thePulmonaryartery","-","X"],["","","","",""],["","","","",""],["","vessels and","Presenceof theascendingaorta","-","X"],["","","","",""],["","tracheaviews","Presenceof thesuperiorvenacava","-","X"]],"caption_candidate":"Sonio","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240406-p10-t0","doc_id":"K240406","page_num":10,"bbox":[71.37,74.23,528.63,766.5],"n_rows":29,"n_cols":4,"columns":["Viewname","Qualitycriteria","First\ntrimester\nT1","Second/Third\nTrimester\nT2/T3"],"rows":[["Viewname","Qualitycriteria","First\ntrimester\nT1","Second/Third\nTrimester\nT2/T3"],["LVOT view","Presenceof theLeftventricle","-","X"],["","Presenceof theLeftatrium","-","X"],["","Presenceof theascendingaorta","-","X"],["","Presenceof theapexof theheart","-","X"],["","Presenceof therightventricle","-","X"],["","Presenceof theinterventricularseptum","-","X"],["RVOT view","Presence of the pulmonary artery with\nvisiblebifurcation","-","X"],["","Presenceof therightventricle","-","X"],["","Presenceof theascendingaorta","-","X"],["Abdominal\ncircumference\nview","Presenceof thestomach","X","X"],["","Presenceof atleastoneadrenalgland","-","X"],["","Presenceof thedescendingaorta","-","X"],["","Presenceof theumbilicalvein","-","X"],["","Absenceof thekidneys","-","X"],["Axial view of\nthetwokidneys","Presenceof twokidneys","-","X"],["","Absenceof thestomach","-","X"],["Qualitycriteriaof CRL/NT/Profile/Corpuscallosumviews","","",""],["Nuchal\nTranslucency\nview","Presenceof thenasalbone","X","-"],["","Presenceof thenuchaltranslucency","X","-"],["","Presenceof thecisternamagna","X","-"],["","Presenceof thefourthventricle","X","-"],["","Presenceof theDiencephalon","X","-"],["","Presenceof thebrainstem","X","-"],["","Presenceof thepalate","X","-"],["","Presenceof liquidspaceunderthechin","X","-"],["CRLview","Presenceof thenasalbone","X","-"],["","Presenceof liquidspaceunderthechin","X","-"],["","Presenceof thepalate","X","-"]],"caption_candidate":"510(k) PremarketNotificationSubmission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p11-t0","doc_id":"K240406","page_num":11,"bbox":[71.67,74.23,528.63,356.5],"n_rows":11,"n_cols":4,"columns":["Viewname","Qualitycriteria","First\ntrimester\nT1","Second/Third\nTrimester\nT2/T3"],"rows":[["Viewname","Qualitycriteria","First\ntrimester\nT1","Second/Third\nTrimester\nT2/T3"],["Profileview","Presenceof thepalate","-","X"],["","Presenceof thenasalbone","-","X"],["Corpus\nCallosumview","Presenceof thecorpus callosum","-","X"],["","Presence of the plexus choroid (third\nventricle)","-","X"],["","Presenceof themidbraintectum","-","X"],["","Presenceof thevermis","-","X"],["Qualitycriteriaof Placentaview","","",""],["Placenta\ninsertion","Presenceof theinternalcervicalos","-","X"],["","Presenceof thecervix","-","X"],["","Presenceof thematernalbladder","-","X"]],"caption_candidate":"510(k) PremarketNotificationSubmission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p11-t1","doc_id":"K240406","page_num":11,"bbox":[71.67,413.52,519.25,564.5],"n_rows":5,"n_cols":4,"columns":["Viewname","Characteristics","Firsttrimester\nT1","Second/Third\nTrimesterT2/T3"],"rows":[["Viewname","Characteristics","Firsttrimester\nT1","Second/Third\nTrimesterT2/T3"],["Genitaliaview","Male","-","X"],["","Female","-","X"],["Placentalocation","Anterior","-","X"],["","Posterior","-","X"]],"caption_candidate":"Table4: Listof characteristicsthat canbe automaticallyverifiedby Sonio Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p12-t0","doc_id":"K240406","page_num":12,"bbox":[72.25,313.67,539.37,724.5],"n_rows":8,"n_cols":3,"columns":["Items","Predicatedevice:SonioDetect-\nK230365","Proposeddevice:SonioDetectv2"],"rows":[["Items","Predicatedevice:SonioDetect-\nK230365","Proposeddevice:SonioDetectv2"],["Manufacture\nrname","Sonio","Sonio"],["Devicename","SonioDetect","SonioDetect"],["Regulation\nNumber","21CFR892.1550-accessoryto\nUltrasonicPulsedDopplerImaging\nSystem\n21CFR892.1560-accessoryto\nUltrasonicPulsedEchoImagingSystem\n21CFR892.2050-MedicalImage\nManagementandProcessingSystem","21CFR892.1550-accessoryto\nUltrasonicPulsedDopplerImaging\nSystem\n21CFR892.1560-accessoryto\nUltrasonicPulsedEchoImagingSystem\n21CFR892.2050-MedicalImage\nManagementandProcessingSystem"],["Productcode","IYN(primary)\nIYO,QIH(Secondary)","IYN(primary)\nIYO,QIH(Secondary)"],["Features","-SonioDetectautomaticallydetects\nviews\n-SonioDetectautomaticallydetects\nanatomicalstructureswithinthe\nsupportedviews\n-SonioDetectautomaticallyverifiesthe\nqualitycriteriaofthesupportedviewsby\ncheckingwhethertheyconformto\nstandardizedqualitycriteria.","-SonioDetectautomaticallydetects\nviews\n-SonioDetectautomaticallydetects\nanatomicalstructureswithinthe\nsupportedviews\n-SonioDetectautomaticallyverifiesthe\nqualitycriteriaandcharacteristicsofthe\nsupportedviews."],["Algorithm\nMethodology","ArtificialIntelligence\nLectureofbiometrics\nColorimetryfor3DandDoppler","ArtificialIntelligence\nLectureofbiometrics\nColorimetryfor3DandDoppler"],["Platform","Securecloud-basedandstand-alone\nsoftwarecompatiblewithultrasound\nsystemfromGEMedical,Samsungand\nCanon","Securecloud-basedandstand-alone\nsoftwarecompatiblewithultrasound\nsystemfromGEMedical,Samsung,\nCanonandPhilips"]],"caption_candidate":"Table5: Comparison of technologicalcharacteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p14-t0","doc_id":"K240406","page_num":14,"bbox":[72.25,198.53,549.67,757.5],"n_rows":11,"n_cols":5,"columns":["Items (fetalultrasound views,\nanatomicalstructures and\ncharacteristicsautomatically\ndetected)","Sensitivity","","Specificity",""],"rows":[["Items (fetalultrasound views,\nanatomicalstructures and\ncharacteristicsautomatically\ndetected)","Sensitivity","","Specificity",""],["","Point\nEstimate","WilsonCI\n(95%)","Point\nEstimate","WilsonCI\n(95%)"],["Automaticdetectionof 3D fetal\nultrasoundimages","0.892","(0.836-0.931)","-","-"],["Automaticdetectionof Doppler\nfetalultrasoundimages","0.973","(0.937-0.988)","-","-"],["Automaticdetectionof fetal\nultrasoundviews throughreadingof\nannotationsonimages","0.913","(0.852-0.951)","-","-"],["Automaticdetectionof 7T1fetal\nultrasoundimages","0.914","(0.906-0.921)","-","-"],["Automaticdetectionof 18T2/T3\nfetalultrasoundimages","0.937","(0.933-0.940)","-","-"],["Automaticdetectionof 8fetalbrain\nanatomicalstructuresontheviews\n“Transthalamic”,\n“Transventricular”,\n“Transcerebellar”atT2/T3","0.934","(0.925-0.943)","0.949","(0.942-0.955)"],["Automaticdetectionof 6fetal\nthoraxandheartanatomical\nstructuresontheviews “Four\nchambers”,“LVOT”, “RVOT”,\n“Threevessels or Threevessels and\ntrachea”,“Abdominal\nCircumference”,“Axialviewof the\nkidneys”atT1","0.861","(0.841-0.878)","0.938","(0.926-0.948)"],["Automaticdetectionof 21fetal\nthoraxandheartanatomical\nstructuresontheviews “Four\nchambers”,“LVOT”, “RVOT”,\n“Threevessels or Threevessels and\ntrachea”,“Abdominal\nCircumference”,“Axialviewof the\nkidneys”atT2/T3","0.919","(0.913-0.924)","0.976","(0.974-0.978)"],["Automaticdetectionof 4fetal\nplacentaanatomicalstructureson\ntheviews “Placentainsertion”,\n“Placentalocation”atT2/T3","0.967","(0.955-0.975)","0.856","(0.838-0.871)"]],"caption_candidate":"Table6: results of the standalone performancetesting","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240406-p15-t0","doc_id":"K240406","page_num":15,"bbox":[72.33,74.21,549.63,465.5],"n_rows":8,"n_cols":5,"columns":["Items (fetalultrasound views,\nanatomicalstructures and\ncharacteristicsautomatically\ndetected)","Sensitivity","","Specificity",""],"rows":[["Items (fetalultrasound views,\nanatomicalstructures and\ncharacteristicsautomatically\ndetected)","Sensitivity","","Specificity",""],["","Point\nEstimate","WilsonCI\n(95%)","Point\nEstimate","WilsonCI\n(95%)"],["Automaticdetectionof 8fetal\nCRL/NT/Profileanatomical\nstructuresontheviews “Crown\nRumpLength”,“Nuchal\nTranslucency”,“Profile”atT1","0.898","(0.885-0.910)","0.862","(0.845-0.878)"],["Automaticdetectionof 6fetal\nCRL/NT/Profileanatomical\nstructuresontheviews “Crown\nRumpLength”,“Nuchal\nTranslucency”,“Profile”atT2/T3","0.893","(0.879-0.906)","0.956","(0.949-0.962)"],["Automaticdetectionof theAnterior\nplacentalocationfor theviews\n“Placentainsertion”,“Placenta\nlocation”atT2/T3","0.959","(0.918-0.980)","0.966","(0.924-0.986)"],["Automaticdetectionof thePosterior\nplacentalocationfor theviews\n“Placentainsertion”,“Placenta\nlocation”atT2/T3","0.966","(0.924-0.986)","0.959","(0.918-0.980)"],["Automaticdetectionof the“Female\nsex”for fetalsex for theview\n“ExternalGenitalia”","0.977","(0.942-0.991)","0.987","(0.963-0.996)"],["Automaticdetectionof the“Male\nsex”for fetalsex for theview\n“ExternalGenitalia”","0.987","(0.963-0.996)","0.977","(0.942-0.991)"]],"caption_candidate":"510(k) PremarketNotificationSubmission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p10-t0","doc_id":"K240411","page_num":10,"bbox":[57.63,122.4,732.33,519.96],"n_rows":4,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["Device\nClassification\nName","","","Medical image management and processing\nsystem","","","Picture Archiving and Communications\nSystem","","","The FDA has changed\nits regulatory\nclassification of PACS\n(Picture Archiving and\nCommunication\nSystems), referring to it\nnow as MIMPS\n(medical image\nmanagement and\nprocessing systems) as\npart of amended\nregulatory\nclassification changes\nmade for radiology-\nspecific software."],["Product Code","","","QIH, LLZ","","","LLZ","","","Both LLZ and QIH are\nproduct code of\nMedical image\nmanagement and"]],"caption_candidate":"Table 1 Comparison of general information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p11-t0","doc_id":"K240411","page_num":11,"bbox":[57.62,82.36,732.34,508.44],"n_rows":7,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["","","","","","","","","","processing system, the\ndifference between\nthem is use different\nalgorithms."],["Regulation\nNumber","","","21 CFR 892.2050","","","21 CFR 892.2050","","","Same"],["Device Class","","","II","","","II","","","Same"],["Classification\nPanel","","","Radiology","","","Radiology","","","Same"],["Advanced\nApplication","","","Yes","","","Yes","","","The predicated device\nincludes more\napplications, which is\ndiscussed in the\nfollowing sections, than\nthe proposed device.\nThis difference will not\nimpact the safety and\neffectiveness of the"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p12-t0","doc_id":"K240411","page_num":12,"bbox":[57.63,82.36,732.33,513.12],"n_rows":4,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["","","","","","","","","","device."],["Intended Use","","","uAI Portal is a software solution intended to\nbe used for viewing, manipulation,\ncommunication, and storage of medical\nimages. It supports interpretation and\nevaluation of examinations within healthcare\ninstitutions. It has the following additional\nindications:\n The Lower Extremity Vessel Analysis is\nintended to provide a tool for viewing,\nmanipulating, and evaluating CTA\nimages of lower extremities.\n The Head and Neck Vessel Analysis is\nintended to provide a tool for viewing,\nmanipulating, and evaluating imaging\ndatasets acquired with head and neck\nCTA.","","","uWS-CT is a software solution intended to be\nused for viewing, manipulation,\ncommunication, and storage of medical\nimages. It supports interpretation and\nevaluation of examinations within healthcare\ninstitutions. It has the following additional\nindications:\n The CT Oncology application is intended\nto support fast-tracking routine\ndiagnostic oncology, staging, and follow-\nup, by providing a tool for the user to\nperform the segmentation and volumetric\nevaluation of suspicious lesions in lung\nor liver.\n The CT Colon Analysis application is\nintended to provide the user a tool to","","","The intended use is\ndecreased. The\npredicated device\nincludes more\napplications, which is\ndiscussed in the\nfollowing sections, than\nthe proposed device.\nThis difference will not\nimpact the safety and\neffectiveness of the\ndevice."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p13-t0","doc_id":"K240411","page_num":13,"bbox":[57.64,82.36,732.32,514.92],"n_rows":3,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["","",""," The Coronary Analysis is intended to\nprovide a tool for viewing,\nmanipulating, and evaluating imaging\ndatasets acquired with CCTA.\n The Pulmonary Artery Analysis is\nintended to provide a tool for viewing,\nmanipulating, and evaluating imaging\ndatasets acquired with CTPA.\n The Aorta Analysis is intended to\nprovide a tool for viewing,\nmanipulating, and evaluating imaging\ndatasets acquired with aorta CTA.","","","enable easy visualization and efficient\nevaluation of CT volume data sets of the\ncolon.\n The CT Dental application is intended to\nprovide the user a tool to reconstruct\npanoramic and paraxial views of jaw.\n The CT Lung Nodule application is\nintended to provide the user a tool for the\nreview and analysis of thoracic CT\nimages, providing quantitative and\ncharacterizing information about nodules\nin the lung in a single study, or over the\ntime course of several thoracic studies.\n The CT Vessel Analysis application is\nintended to provide a tool for viewing,\nmanipulating, and evaluating CT\nvascular images. The Inner view\napplication is intended to perform a","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p14-t0","doc_id":"K240411","page_num":14,"bbox":[57.64,82.36,732.32,514.92],"n_rows":3,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["","","","","","","virtual camera view through hollow\nstructures (cavities), such as vessels.\n The CT Lung Density Analysis\napplication is intended to segment\npulmonary, lobes, and airway, providing\nthe user quantitative parameters,\nstructure information to evaluate the lung\nand airway.\n The CT Brain Perfusion application is\nintended to calculate the parameters such\nas: CBV, CBF, etc. in order to analyze\nfunctional blood flow information about\na region of interest (ROI) in the brain.\nThe CT Heart application is intended to\nsegment heart and extract coronary\nartery. It also provides analysis of\nvascular stenosis, plaque and heart\nfunction.","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p15-t0","doc_id":"K240411","page_num":15,"bbox":[57.64,82.36,732.32,520.92],"n_rows":3,"n_cols":10,"columns":["","Item","","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["","Item","","","Proposed Device","","","Predicate Device","","Remark"],["","","","","uAI Portal","","","uWS-CT(K183170)","",""],["","","","","",""," The CT Calcium Scoring application is\nintended to identify calcifications and\ncalculate the calcium score. The CT\nDynamic Analysis application is intended\nto provide visualization of the CT\ndatasets over time with the 3D/4D\ndisplay modes.\n The CT Bone Structure Analysis\napplication is intended to provide\nvisualization and labels for the ribs and\nspine, and support batch function for\nintervertebral disk.\n The CT Liver Evaluation application is\nintended to provide processing and\nvisualization for liver segmentation and\nvessel extraction. It also provides a tool\nfor the user to perform liver separation\nand residual liver segments evaluation.","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p16-t0","doc_id":"K240411","page_num":16,"bbox":[75.26,132.44,714.59,502.56],"n_rows":13,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nLower Extremity\nVessel Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nLower Extremity\nVessel Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["Lower\nExtremity\nVessel Analysis","Image Browsing","Yes","Yes","","","Same"],["","Image Editing","Yes","Yes","","","Same"],["","Vessel Segmentation","Yes","Yes","","","Same"],["","Bone Segmentation","Yes","Yes","","","Same"],["","Centerline Extraction","Yes","Yes","","","Same"],["","ROI","Yes","Yes","","","Same"],["","Measurement","Yes","Yes","","","Same"],["","Stenosis Measurement","Yes","Yes","","","Same"]],"caption_candidate":"Table 2 SE Discussion for different Advanced Applications","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p17-t0","doc_id":"K240411","page_num":17,"bbox":[75.28,82.37,714.57,288.24],"n_rows":8,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nLower Extremity\nVessel Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nLower Extremity\nVessel Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["","Print","Yes","Yes","","","Same"],["","Archive","Yes","Yes","","","Same"],["","User Configuration","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p17-t1","doc_id":"K240411","page_num":17,"bbox":[75.28,339.84,714.57,512.76],"n_rows":7,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nHead and Neck\nVessel Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nHead and Neck\nVessel Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["Head and Neck\nVessel Analysis","Image Browsing","Yes","Yes","","","Same"],["","Image Editing","Yes","Yes","","","Same"]],"caption_candidate":"User Configuration Yes Yes Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p18-t0","doc_id":"K240411","page_num":18,"bbox":[75.26,82.37,714.59,451.44],"n_rows":12,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nHead and Neck\nVessel Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nHead and Neck\nVessel Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["","Vessel\nSegmentation","Yes","Yes","","","Same"],["","Bone Segmentation","Yes","Yes","","","Same"],["","Centerline\nExtraction","Yes","Yes","","","Same"],["","Measurement","Yes","Yes","","","Same"],["","Print","Yes","Yes","","","Same"],["","Archive","Yes","Yes","","","Same"],["","User Configuration","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p19-t0","doc_id":"K240411","page_num":19,"bbox":[75.26,122.4,714.59,491.4],"n_rows":12,"n_cols":9,"columns":["Application","Function name","","Proposed device","","","Predicate device","","Remark"],"rows":[["Application","Function name","","Proposed device","","","Predicate device","","Remark"],["","","","uAI Portal","","","uWS-","",""],["","","","","","","CT(K183170)","",""],["","","","Coronary","","","","",""],["","","","Analysis","","","CT Heart","",""],["Coronary Analysis","Image Browsing","Yes","","","Yes","","","Same"],["","Image Editing","Yes","","","Yes","","","Same"],["","Heart Segmentation","Yes","","","Yes","","","Same"],["","Vessel\nSegmentation","Yes","","","Yes","","","Same"],["","Centerline\nExtraction","Yes","","","Yes","","","Same"],["","Measurement","Yes","","","Yes","","","Same"],["","Stenosis\nMeasurement","Yes","","","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p20-t0","doc_id":"K240411","page_num":20,"bbox":[81.36,93.58,542.71,510.8],"n_rows":37,"n_cols":5,"columns":["Application","Function name","Proposed device","Predicate device","Remark"],"rows":[["Application","Function name","Proposed device","Predicate device","Remark"],["","","","",""],["","","uAI Portal","uWS-",""],["","","","",""],["","","","",""],["","","","CT(K183170)",""],["","","Coronary","",""],["","","","",""],["","","Analysis","CT Heart",""],["","","","",""],["","Print","Yes","Yes","Same"],["","","","",""],["","Archive","Yes","Yes","Same"],["","","","",""],["","User Configuration","Yes","Yes","Same"],["","","","",""],["Application","Function name","Proposed device","Predicate device","Remark"],["","","","",""],["","","uAI Portal","uWS-",""],["","","","",""],["","","","",""],["","","","CT(K183170)",""],["","","Pulmonary","",""],["","","","",""],["","","Artery Analysis","CT Vessel",""],["","","","",""],["","","","Analysis",""],["","","","",""],["Pulmonary Artery","Image Browsing","Yes","Yes","Same"],["","","","",""],["Analysis","","","",""],["","","","",""],["","Image Editing","Yes","Yes","Same"],["","","","",""],["","","","",""],["","","","","The CT"],["","Segmentation","Yes","Yes",""]],"caption_candidate":"Application Function name Proposed device Predicate device Remark","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240411-p21-t0","doc_id":"K240411","page_num":21,"bbox":[75.26,82.37,714.58,463.08],"n_rows":10,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nPulmonary\nArtery Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nPulmonary\nArtery Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["","","","","","","uWS-CT (K183170) provide vessel\nsegmentation results with organs. The uAI\nPortal Pulmonary Artery Analysis offer\nsegmentation results of vessels. For the\nevaluation of vessel, the difference in\nsegmentation between the predicate device\nand proposed device will not impact the\nsafety and effectiveness of the device"],["","Measurement","Yes","Yes","","","Same"],["","Print","Yes","Yes","","","Same"],["","Archive","Yes","Yes","","","Same"],["","User Configuration","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p22-t0","doc_id":"K240411","page_num":22,"bbox":[75.26,112.4,714.58,507.84],"n_rows":10,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nAorta Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nAorta Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["Aorta Analysis","Image Browsing","Yes","Yes","","","Same"],["","Segmentation","Yes","Yes","","","Organ segmentation results have slight\ndifference due to the different applied\nalgorithm of the predicate device and\nproposed device. For the evaluation of\nvessel, those other segmentation difference\nbetween the predicate device and proposed\ndevice will not impact the safety and\neffectiveness of the device"],["","Centerline\nExtraction","Yes","Yes","","","Same"],["","Measurement","Yes","Yes","","","Same"],["","Lumen Diameter","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p23-t0","doc_id":"K240411","page_num":23,"bbox":[75.27,82.37,714.58,313.56],"n_rows":9,"n_cols":7,"columns":["Application","Function name","Proposed device\nuAI Portal\nAorta Analysis","","Predicate device","","Remark"],"rows":[["Application","Function name","Proposed device\nuAI Portal\nAorta Analysis","","Predicate device","","Remark"],["","","","","uWS-","",""],["","","","","CT(K183170)","",""],["","","","","CT Vessel","",""],["","","","","Analysis","",""],["","Measurement","","","","",""],["","Print","Yes","Yes","","","Same"],["","Archive","Yes","Yes","","","Same"],["","User Configuration","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p25-t0","doc_id":"K240411","page_num":25,"bbox":[121.32,265.08,528.72,474.36],"n_rows":13,"n_cols":3,"columns":["Demographic information","","Quantity/Years"],"rows":[["Demographic information","","Quantity/Years"],["Gender","Female","73"],["","Male","77"],["Age","Median","66Y"],["","Min","19Y"],["","Max","91Y"],["Equipment","SIEMENS","55"],["","GE","85"],["","TOSHIBA","10"],["Artifacts","With artifacts","33"],["","Without artifacts","117"],["Anatomical\nvariation","With anatomical variation","30"],["","Without anatomical variation","120"]],"caption_candidate":"was as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p25-t1","doc_id":"K240411","page_num":25,"bbox":[105.84,559.68,544.2,695.28],"n_rows":5,"n_cols":4,"columns":["Validation\nType","Application","Algorithm","Acceptance\nCriteria"],"rows":[["Validation\nType","Application","Algorithm","Acceptance\nCriteria"],["Dice, DICE is\ndefined as\nfollows:\n,\nwhere G is","Coronary Artery","Vessels\nsegmentation","0.85"],["","","Heart\nsegmentation","0.90"],["","Head and Neck\nVessel","Head vessel\nsegmentation","0.85"],["","","Neck vessel","0.90"]],"caption_candidate":"acceptance criteria is shown below：","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p26-t0","doc_id":"K240411","page_num":26,"bbox":[105.84,67.2,544.2,244.8],"n_rows":6,"n_cols":4,"columns":["the ground\ntruth, and P is\nthe\nsegmentation\nresult.","","segmentation",""],"rows":[["the ground\ntruth, and P is\nthe\nsegmentation\nresult.","","segmentation",""],["","Aorta","Trunk\nsegmentation","0.90"],["","","Branches\nsegmentation","0.80"],["","Pulmonary\nArtery","Arteries\nsegmentation","0.85"],["","","Veins\nsegmentation","0.85"],["","Lower\nExtremity\nArtery","Arteries\nsegmentation","0.80"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p26-t1","doc_id":"K240411","page_num":26,"bbox":[131.04,441.12,519.0,615.96],"n_rows":10,"n_cols":3,"columns":["Application","Algorithm","Average\nDice"],"rows":[["Application","Algorithm","Average\nDice"],["Coronary Artery","Vessels segmentation","0.920"],["","Heart segmentation","0.980"],["Head and Neck Vessel","Head vessel segmentation","0.902"],["","Neck vessel segmentation","0.967"],["Aorta","Trunk segmentation","0.946"],["","Branches segmentation","0.846"],["Pulmonary Artery","Arteries segmentation","0.953"],["","Veins segmentation","0.933"],["Lower Extremity Artery","Arteries segmentation","0.892"]],"caption_candidate":"of Dice coefficient were shown in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p27-t0","doc_id":"K240411","page_num":27,"bbox":[126.25,67.38,523.74,582.48],"n_rows":32,"n_cols":3,"columns":["Algorithm","Gender","Average dice"],"rows":[["Algorithm","Gender","Average dice"],["Vessels\nsegmentation","Female","0.912"],["","Male","0.924"],["","Age","Average dice"],["","＜40","0.915"],["","40~60","0.920"],["","＞60","0.923"],["","Manufacturer","Average dice"],["","GE","0.921"],["","SIEMENS","0.919"],["","Artifacts","Average dice"],["","With artifacts","0.929"],["","Without artifacts","0.919"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.909"],["","Without anatomical variation","0.922"],["Heart\nsegmentation","Gender","Average dice"],["","Female","0.983"],["","Male","0.978"],["","Age","Average dice"],["","＜40","0.987"],["","40~60","0.979"],["","＞60","0.979"],["","Manufacturer","Average dice"],["","GE","0.977"],["","SIEMENS","0.983"],["","Artifacts","Average dice"],["","With artifacts","0.983"],["","Without artifacts","0.979"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.977"],["","Without anatomical variation","0.980"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p27-t1","doc_id":"K240411","page_num":27,"bbox":[126.25,618.36,523.74,698.76],"n_rows":5,"n_cols":3,"columns":["Algorithm","Gender","Average dice"],"rows":[["Algorithm","Gender","Average dice"],["Head vessel\nsegmentation","Female","0.902"],["","Male","0.902"],["","Age","Average dice"],["","＜40","0.905"]],"caption_candidate":"Head and Neck Vessel Application","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p28-t0","doc_id":"K240411","page_num":28,"bbox":[126.25,67.2,523.75,534.96],"n_rows":29,"n_cols":3,"columns":["","40~60","0.903"],"rows":[["","40~60","0.903"],["","＞60","0.901"],["","Manufacturer","Average dice"],["","GE","0.899"],["","SIEMENS","0.904"],["","TOSHIBA","0.910"],["","Artifacts","Average dice"],["","With artifacts","0.902"],["","Without artifacts","0.902"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.899"],["","Without anatomical variation","0.905"],["Neck vessel\nsegmentation","Gender","Average dice"],["","Female","0.966"],["","Male","0.968"],["","Age","Average dice"],["","＜40","0.959"],["","40~60","0.968"],["","＞60","0.968"],["","Manufacturer","Average dice"],["","GE","0.966"],["","SIEMENS","0.972"],["","TOSHIBA","0.967"],["","Artifacts","Average dice"],["","With artifacts","0.968"],["","Without artifacts","0.966"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.968"],["","Without anatomical variation","0.966"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p28-t1","doc_id":"K240411","page_num":28,"bbox":[126.25,553.2,523.75,698.04],"n_rows":9,"n_cols":3,"columns":["Algorithm","Gender","Average dice"],"rows":[["Algorithm","Gender","Average dice"],["Trunk\nsegmentation","Female","0.941"],["","Male","0.950"],["","Age","Average dice"],["","＜40","0.949"],["","40~60","0.942"],["","＞60","0.947"],["","Manufacturer","Average dice"],["","GE","0.940"]],"caption_candidate":"Aorta Application","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p29-t0","doc_id":"K240411","page_num":29,"bbox":[126.25,67.2,523.75,469.68],"n_rows":25,"n_cols":3,"columns":["","SIEMENS","0.955"],"rows":[["","SIEMENS","0.955"],["","TOSHIBA","0.948"],["","Artifacts","Average dice"],["","With artifacts","0.940"],["","Without artifacts","0.947"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.949"],["","Without anatomical variation","0.945"],["Branches\nsegmentation","Gender","Average dice"],["","Female","0.832"],["","Male","0.856"],["","Age","Average dice"],["","＜40","0.829"],["","40~60","0.837"],["","＞60","0.850"],["","Manufacturer","Average dice"],["","GE","0.853"],["","SIEMENS","0.830"],["","TOSHIBA","0.858"],["","Artifacts","Average dice"],["","With artifacts","0.822"],["","Without artifacts","0.850"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.856"],["","Without anatomical variation","0.842"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p29-t1","doc_id":"K240411","page_num":29,"bbox":[126.25,505.68,523.75,698.76],"n_rows":12,"n_cols":3,"columns":["Algorithm","Gender","Average dice"],"rows":[["Algorithm","Gender","Average dice"],["Arteries\nsegmentation","Female","0.955"],["","Male","0.951"],["","Age","Average dice"],["","＜40","0.946"],["","40~60","0.946"],["","＞60","0.957"],["","Manufacturer","Average dice"],["","GE","0.956"],["","SIEMENS","0.947"],["","Artifacts","Average dice"],["","With artifacts","0.960"]],"caption_candidate":"Pulmonary Artery Application","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p30-t0","doc_id":"K240411","page_num":30,"bbox":[125.53,67.2,524.45,340.92],"n_rows":17,"n_cols":3,"columns":["","Without artifacts","0.953"],"rows":[["","Without artifacts","0.953"],["","Anatomical variation","Average dice"],["","With anatomical variation","-"],["","Without anatomical variation","0.953"],["Veins\nsegmentation","Gender","Average dice"],["","Female","0.936"],["","Male","0.930"],["","Age","Average dice"],["","＜40","0.944"],["","40~60","0.926"],["","＞60","0.936"],["","Manufacturer","Average dice"],["","GE","0.939"],["","SIEMENS","0.924"],["","Artifacts","Average dice"],["","With artifacts","0.931"],["","Without artifacts","0.933"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240411-p30-t1","doc_id":"K240411","page_num":30,"bbox":[125.53,376.92,524.45,634.32],"n_rows":16,"n_cols":3,"columns":["Algorithm","Gender","Average dice"],"rows":[["Algorithm","Gender","Average dice"],["Arteries\nsegmentation","Female","0.880"],["","Male","0.910"],["","Age","Average dice"],["","40~60","0.881"],["","＞60","0.896"],["","Manufacturer","Average dice"],["","GE","0.878"],["","SIEMENS","0.907"],["","TOSHIBA","0.895"],["","Artifacts","Average dice"],["","With artifacts","0.906"],["","Without artifacts","0.890"],["","Anatomical variation","Average dice"],["","With anatomical variation","0.897"],["","Without anatomical variation","0.892"]],"caption_candidate":"Lower Extremity Artery Application","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240417-p6-t0","doc_id":"K240417","page_num":6,"bbox":[72.0,243.6,535.56,695.52],"n_rows":7,"n_cols":3,"columns":["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],"rows":[["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],["Manufacturer","iCAD, Inc.","iCAD, Inc."],["Classification\nName","Radiological Computer Assisted\nDetection and Diagnosis Software","Radiological Computer Assisted\nDetection and Diagnosis Software"],["Regulation\nNumber","21 CFR 892.2090","21 CFR 892.2090"],["Product Code","QDQ","QDQ"],["Intended Use /\nIndication for Use","ProFound AI® V3.0 is a computer-\nassisted detection and diagnosis\n(CAD) software device intended to be\nused concurrently by interpreting\nphysicians while reading digital\nbreast tomosynthesis (DBT) exams\nfrom compatible DBT systems. The\nsystem detects soft tissue densities\n(masses, architectural distortions and\nasymmetries) and calcifications in the\n3D DBT slices. The detections and\nCertainty of Finding and Case Scores\nassist interpreting physicians in\nidentifying soft tissue densities and\ncalcifications that may be confirmed\nor dismissed by the interpreting\nPhysician.","ProFound Detection V4.0 is a\ncomputer-assisted detection and\ndiagnosis (CAD) software device\nintended to be used concurrently by\ninterpreting physicians while reading\ndigital breast tomosynthesis (DBT)\nexams from compatible DBT systems.\nThe system detects soft tissue densities\n(masses, architectural distortions and\nasymmetries) and calcifications in the\n3D DBT slices. The detections and\nCertainty of Finding and Case Scores\nassist interpreting physicians in\nidentifying soft tissue densities and\ncalcifications that may be confirmed or\ndismissed by the interpreting\nPhysician."],["End User","Radiologists","Radiologists"]],"caption_candidate":"Comparison with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240417-p7-t0","doc_id":"K240417","page_num":7,"bbox":[72.0,79.8,535.56,696.48],"n_rows":7,"n_cols":3,"columns":["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],"rows":[["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],["Patient\nPopulation","Symptomatic and asymptomatic\nwomen undergoing mammography.","Symptomatic and asymptomatic\nwomen undergoing mammography."],["Mode of Action","Image processing device intended to\naid in the detection, localization, and\ncharacterization of soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in the 3D DBT slices.","Image processing device intended to\naid in the detection, localization, and\ncharacterization of soft tissue densities\n(masses, architectural distortions and\nasymmetries) and calcifications in the\n3D DBT slices."],["Image Source\nModalities","Digital breast tomosynthesis slices","Digital breast tomosynthesis slices"],["Output Device","Softcopy Workstation","Softcopy Workstation"],["Supported Digital\nBreast\nTomosynthesis\nSystems","• Hologic Selenia\nDimensions/3Dimensions\n• Hologic 3Dimentions (Clarity HD)\n• GE Senographe Essential with\nSenoClaire\n• GE Senographe Pristina\n• Siemens Mammomat Inspiration\nboth Standard and Empire\nReconstruction\n• Siemens Mammomat Revelation\nboth Standard and Empire\nReconstruction","• Hologic Selenia\nDimensions/3Dimensions"],["Certainty of\nFinding and Case\nScores","• Represented on a 0% to 100%\nscale\n• Certainty of Finding relative score\nassigned to each detected region\n• Case Score assigned to each case\n(regardless of the number of\ndetected regions)","• Represented on a 0% to 100% scale\n• Certainty of Finding relative score\nassigned to each detected region\n• Case Score assigned to each case\n(regardless of the number of\ndetected regions)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240417-p8-t0","doc_id":"K240417","page_num":8,"bbox":[72.0,79.8,535.56,408.6],"n_rows":6,"n_cols":3,"columns":["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],"rows":[["","Predicate Device\nProFound AI V3.0\nK203822","Subject Device\nProFound Detection V4.0\nK240417"],["View Processing\nComponent\nArchitecture","Implements view processing in three\nsteps.","Implements view processing in two\nsteps."],["Processing of\nPrior Exams","Not included","Included"],["CAD Output\nDisplay","Marks displayed on the current exam.","Marks displayed on the current exam."],["Maximum Marks\nPer View","Unlimited","Three"],["Inclusion of PCCP","N/A","Included\nThe PCCP in the subject device\nincludes proposed modifications\nrelated to extending supported DBT\nimage acquisition systems."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240417-p9-t0","doc_id":"K240417","page_num":9,"bbox":[72.0,354.6,535.56,506.88],"n_rows":4,"n_cols":4,"columns":["","Sensitivity","Specificity","AUC"],"rows":[["","Sensitivity","Specificity","AUC"],["ProFound Detection\nV4.0 using priors","0.9004 (0.8633-0.9374)","0.6205 (0.5846-0.6565)","0.8753 (0.8475-0.9032)"],["ProFound Detection\nV4.0","0.9004 (0.8633-0.9374)","0.5863 (0.5498-0.6228)","0.8714 (0.8423-0.9007)"],["Predicate\n(ProFound AI V3.0)","0.8725 (0.8312-0.9138)","0.5278 (0.4909-0.5648)","0.8230 (0.7878-0.8570)"]],"caption_candidate":"below on the same independent data set:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240417-p10-t0","doc_id":"K240417","page_num":10,"bbox":[72.0,136.32,540.72,391.8],"n_rows":7,"n_cols":2,"columns":["Cancer status","Malignant: 26%\nNormal/benign: 74%"],"rows":[["Cancer status","Malignant: 26%\nNormal/benign: 74%"],["Breast Density","Fatty: 65%\nDense: 35%"],["Age (years old)","Minimum: 35\nMaximum: 90\nMean: 63\n25th percentile: 55\n75th percentile: 71"],["Race/Ethnicity","White, non-Hispanic: 59%\nBlack, non-Hispanic: 10%\nAsian or Pacific Islander, non-Hispanic:10%\nAmerican Indian or Alaska Native, non-Hispanic: 0.3%\nOther or Multiracial, non-Hispanic: 8%\nHispanic: 12%"],["Imaging Modality","DBT: 100%"],["Modality Manufacturer","Hologic: 100%"],["Exam Dates (range)","2018 - 2022"]],"caption_candidate":"test population is provided in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p6-t0","doc_id":"K240465","page_num":6,"bbox":[58.53,88.2,544.37,648.9],"n_rows":8,"n_cols":8,"columns":["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],"rows":[["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],["","","O-arm O2 Imaging System","","","O-arm O2 Imaging","",""],["","","4.3.0 Software","","","System 4.2.0 Software","",""],["Classification","Class II","","","Class II","","","Identical"],["Product Code","OWB, OXO and JAA","","","OWB, OXO and JAA","","","Identical"],["Indications for Use","The O-arm™ O2 Imaging\nSystem is a mobile x-ray\nsystem designed for 2D and\n3D imaging for adult and\npediatric patients weighing\n60lbs or greater and having\nan abdominal thickness\ngreater than 16cm and is\nintended to be used where a\nphysician benefits from 2D\nand 3D information of\nanatomic structures and\nobjects with high x-ray\nattenuation such as bony\nanatomy and metallic objects.\nThe O-arm™ O2 Imaging\nSystem is compatible with\ncertain Image Guided\nSurgery Systems.","","","The O-arm™ O2\nImaging System is a\nmobile x-ray system\ndesigned for 2D and 3D\nimaging for adult and\npediatric patients\nweighing 60lbs or greater\nand having an abdominal\nthickness greater than\n16cm and is intended to\nbe used where a\nphysician benefits from\n2D and 3D information\nof anatomic structures\nand objects with high x-\nray attenuation such as\nbony anatomy and\nmetallic objects.\nThe O-arm™ O2\nImaging System is\ncompatible with certain\nImage Guided Surgery\nSystems.","","","Identical"],["Cone Beam CT","The O-arm™ O2 Imaging\nSystem is a mobile cone-\nbeam x-ray system with\nisocentric motion options. It\nallows 3D image\nreconstruction using a 360-\ndegree rotation of the x-ray\nsource and detector within\nclosed gantry.","","","The O-arm™ O2 Imaging\nSystem is a mobile cone-\nbeam x-ray system with\nisocentric motion options.\nIt allows 3D image\nreconstruction using a\n360-degree rotation of the\nx-ray source and detector\nwithin closed gantry.","","","Identical"],["Detector Technology","40 x 30 cm (RoHS\ncompliant, Flat-Panel\nDetector using a CsI\nscintillation)","","","40 x 30 cm (RoHS\ncompliant, Flat-Panel\nDetector using a CsI\nscintillation)","","","Identical"]],"caption_candidate":"Comparison of the Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p7-t0","doc_id":"K240465","page_num":7,"bbox":[58.52,72.36,544.42,664.14],"n_rows":12,"n_cols":8,"columns":["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],"rows":[["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],["","","O-arm O2 Imaging System","","","O-arm O2 Imaging","",""],["","","4.3.0 Software","","","System 4.2.0 Software","",""],["Generator Technology","32 kW, RoHS compliant\ngenerator with improved\nelectrical interface.","","","32 kW, RoHS compliant\ngenerator with improved\nelectrical interface.","","","Identical"],["2D Imaging","2D Fluoroscopic","","","2D Fluoroscopic","","","Identical"],["2D Imaging","Automatically stitched 2D\nRadiographic (Long Film)","","","Automatically stitched 2D\nRadiographic (Long Film)","","","Identical"],["3D Imaging (20 cm\nFOV)","Full Fan (20cm FOV) scan\nacquisition","","","Full Fan (20cm FOV)\nscan acquisition","","","Identical"],["3D Imaging Protocols\n(20 cm FOV)","Available presets:\n1. Standard 3D\n2. HD3D (High Definition)\n3. Enhanced Cranial\n4. Low Dose 3D\n5. SpineSmart Dose","","","Available presets:\n1. Standard 3D\n2. HD3D (High\nDefinition)\n3. Enhanced Cranial\n4. Low Dose 3D","","","Added new preset called\nSpineSmart Dose (See below for\ndetails) in our subject device"],["3D Imaging (40 cm\nFOV)","Half-fan single scan\nacquisition","","","Half-fan single scan\nacquisition","","","Identical"],["3D Imaging Protocols\n(40 cm FOV)","Available presets:\n1. HD3D (high definition)\nequivalent to 750\nprojections","","","Available presets:\n1. HD3D (high\ndefinition) equivalent to\n750 projections","","","Identical"],["System Software","Version 4.3.0","","","Version 4.2.0","","","Equivalent, with the addition of\n4.3.0 features (KCMAR, SSD\nand 3DLS) described in\nSection 3 Device Description."],["Known Component\nMetal Artifact\nReduction\n(“KCMAR”)/Medtronic\nArtifact Reduction\n(MAR)/ Medtronic\nImplant Resolution\n(MIR)","The Medtronic Implant\nResolution System feature\nprovides enhanced\nvisualization of supported\nMedtronic implants by\nreducing artifacts\ngenerated by imaging\nhardware, such as screws\nand spinal implants, and\nenhancing hardware\nvisibility.","","","The current system is\nused for imaging\nscrews and implants,\nhowever, it does not\nhave the feature to\nreduce artifacts\ngenerated by imaging\nhardware, such as\nscrews and spinal\nimplants.","","","A dded Feature:\nKnown-Component Metal\nArtifact Reduction (KCMAR)\nis a specialized algorithm,\nwhich suppresses this metal\nartifact on pedicle screws using\nthe “known” geometry of those\nscrews."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p8-t0","doc_id":"K240465","page_num":8,"bbox":[58.56,72.36,544.27,644.7],"n_rows":5,"n_cols":8,"columns":["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],"rows":[["Feature/ Attribute","","Subject Device","","","Predicate","","Discussion"],["","","O-arm O2 Imaging System","","","O-arm O2 Imaging","",""],["","","4.3.0 Software","","","System 4.2.0 Software","",""],["3D Long Scan\nProtocol","3D Long Scan\nThe 3D Long Scan feature\nprovides functionality to\nspecify start and end\npositions for acquiring two\nto three (depending on\nlength) auto-registered 3D\nscans in combination with\nthe IGS system. The\nmaximum achievable length\nfor a 3D Long scan is\napproximately 43.8 cm\n(17.24 in).The minimum\nscan length for a 3D Long\nScan is approximately 19.2\ncm (7.6 in).","","","2D Long Film\nThe 2D Long Film mode\nprovides functionality for\nacquiring an\nintraoperative linear X-\nray scan. In this mode,\nthe O-arm™ O2 Imaging\nSystem scans while the\ngantry moves left/right\nalong the z-axis during\nacquisition between the\npositions stored in\nmemory presets 1 and 2.\nWhen the saved memory\npresets are stored at the\nextremes of the z-axis,\nthe maximum length and\nwidth of a 2D Long Film\nimage is 47 cm by 20 cm\nat isocenter.","","","Added Feature:\n3D Long Scan is the combination\nof automatic registration with\nnavigation systems (e.g.,\nMedtronic StealthStation), lateral\naccess to the patient, and a\nnavigated three-dimensional scan\nof 15-43cm of the patient’s spine.\n2D Long Film was validated\nand FDA-cleared previously."],["SpineSmart Dose\n(SSD)","SpineSmart Dose\nSSD mode is designed to\nprovide an additional\npreset setting for standard\n3D acquisitions with a\nlower overall dose\nreduction of around 70%\nfrom the standard\nacquisition protocols, for\nspinal applications. The\nrotor spins at 30° per\nsecond, acquires images\nat 30 frames per second,\nand captures\napproximately 100\nprojections.","","","Normal dose\nIn 3D acquisition\nmodes, the O-arm™ O2\nsystem IAS creates a\nseries of pulsed x-ray\nexposures throughout a\ncomplete 360-degree\nrotation of the gantry\nrotor. The rotor spins at\n30° per second,\nacquires images at 30\nframes per second and\ncaptures approximately\n391 projections.","","","Added Feature:\nSpine Smart Dose feature\nleverages Machine Learning\ntechnology with existing O-\narm™ images to achieve\nreduction in dose on the O-\narm™ O2 Imaging System. It\nis an algorithm designed to\nreduce the noise of 3D\nreconstructions acquired from\nfewer acquisitions so that\nclinically viable 3D images can\nbe produced using fewer\nprojections."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p9-t0","doc_id":"K240465","page_num":9,"bbox":[76.44,530.16,521.76,662.16],"n_rows":2,"n_cols":3,"columns":["Testing","Testing Methodology / Parameters","Overall Results"],"rows":[["Testing","Testing Methodology / Parameters","Overall Results"],["Spine Smart\nDose Clinical\nEquivalence\nDesign\nValidation","The Spine Smart Dose (SSD) feature uses a\nsparse image acquisition, an FDK\nreconstruction and a machine learning\ndenoising algorithm to provide images of\nthe spine at significantly lower dose\n(around 70% lower dose to patient). In a\nblinded review by board-certified\nneuroradiologist involving 100 clinical","This clinical and cadaver image pair\nvalidation study demonstrated that the\nclinical value of the O-arm O2 4.3 SSD\nimages is clinically equivalent when\ncompared to corresponding images from the\nPredicate Device (O-arm O2 4.2.0 Imaging\nSystem) under the specified indications."]],"caption_candidate":"Performance Testing Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p10-t0","doc_id":"K240465","page_num":10,"bbox":[76.44,72.24,521.76,656.64],"n_rows":5,"n_cols":3,"columns":["","image pairs, O-arm™ O2 Imaging System\n4.3.0 SSD images were deemed clinically\nequivalent to O-arm™ O2 Imaging System\n4.2.x Standard and Predicate High-\nDefinition modes. The dose of the SSD\nimages reviewed in this study were\napproximately ¼ the dose of the\ncorresponding Standard images.",""],"rows":[["","image pairs, O-arm™ O2 Imaging System\n4.3.0 SSD images were deemed clinically\nequivalent to O-arm™ O2 Imaging System\n4.2.x Standard and Predicate High-\nDefinition modes. The dose of the SSD\nimages reviewed in this study were\napproximately ¼ the dose of the\ncorresponding Standard images.",""],["Spine Smart\nDose Bench\nTesting","Phantom testing was performed on Spine\nSmart Dose feature to verify the system\nlevel requirements for Image Quality (3D\nLine pair, Contrast, MTF, Uniformity and\nGeometric accuracy) and Navigational\naccuracy in terms of millimeters.","All the bench testing demonstrated Spine\nSmart Dose met all the system level\nrequirements."],["KCMAR\nClinical\nEquivalence\nDesign\nValidation","The 3D O-arm acquisitions reconstructed\nusing the predicate device without KCMAR\nfeature and the same acquisitions\nreconstructed using the subject device with\nKCMAR feature were compared for their\nclinical equivalence. Board-certified\nradiologists provided clinical utility scores\n(1-5 scale) for the 40 image pairs from four\ncadavers acquired using Standard 3D\nimaging mode. The cadavers were of small,\nmedium, large, and extra-large habitus.\nIn the subsequent study, board-certified\nradiologists provided clinical utility scores\nfor the 33 image pairs from two cadavers\nacquired using other 3D imaging modes\n(Low Dose, HD, and SSD). The cadavers\nwere of small and extra-large habitus.","This cadaver image pair validation study\ndemonstrated that the clinical value of the\nKCMAR image with the O-arm O2 Imaging\nSystem version 4.3.0 is statistically better\nwhen compared to corresponding images\nfrom the Predicate Device (O-arm O2\nImaging System version 4.2.0) under the\nspecified indications."],["KCMAR\nBench Testing","Phantom studies were used to qualitatively\ncompare the metal artifact reduction\nbetween non-KCMAR and KCMAR\nprocessed images with supported\nMedtronic implants. In addition, phantom\nstudies were conducted to quantitatively\nassess the accuracy of the implant location\nin millimeters and degrees.","All the bench testing demonstrated\nKCMAR met all the system level\nrequirements."],["3D Long Scan\nClinical\nUtility\nValidation","Board-certified radiologists provided\nclinical utility scores (1-5 scale) for\nStandard, Standard 3DLS, and SSD 3DLS\nacquisitions of three cadavers. The\ncadavers were of small, medium, and extra-","This cadaver clinical utility study\ndemonstrated that the clinical utility of the\nStandard 3DLS and SSD 3DLS with the O-\narm O2 Imaging System version 4.3.0 is\nstatistically equivalent when compared to"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240465-p11-t0","doc_id":"K240465","page_num":11,"bbox":[76.44,72.24,521.76,471.0],"n_rows":4,"n_cols":3,"columns":["","large habitus, and two of the cadavers were\ninstrumented with pedicle screw hardware.\nPaired statistical equivalence testing of the\nclinical utility scores was performed\nbetween (1) the Standard (predicate) and\nStandard 3DLS mode, and (2) the Standard\n(predicate) and SSD 3DLS mode. Each test\nwas performed on 45 paired samples.","the corresponding Standard acquisition\nmode that is available in the predicate\nsystem (version 4.2.0)."],"rows":[["","large habitus, and two of the cadavers were\ninstrumented with pedicle screw hardware.\nPaired statistical equivalence testing of the\nclinical utility scores was performed\nbetween (1) the Standard (predicate) and\nStandard 3DLS mode, and (2) the Standard\n(predicate) and SSD 3DLS mode. Each test\nwas performed on 45 paired samples.","the corresponding Standard acquisition\nmode that is available in the predicate\nsystem (version 4.2.0)."],["3D Long Scan\nBench Testing","Phantom testing was performed on the 3D\nLong Scan feature to verify the system\nlevel requirements for Image Quality (3D\nLine pair, Contrast, MTF and Geometric\naccuracy) and Navigational accuracy in\nterms of millimeters.","All the bench testing demonstrated 3D Long\nScan met all the system level requirements."],["Usability","Usability for the 3DLS, SSD, and KCMAR\nfeatures was assessed in multiple formative\nevaluations and tested in two summative\nvalidations with the clinically relevant users\nin simulated use environments. Summative\nvalidation of critical tasks and new\nworkflows for 3DLS and SSD was\nconducted with surgeons, spine\nrepresentatives, and radiation technologists.\nSummative validation of KCMAR critical\ntasks and new workflows was conducted\nwith surgeons and spine representatives.","The 3DLS, SSD, and KCMAR features\npassed summative validation. Results of the\nsummative validations provided objective\nevidence the O-arm O2 Imaging System\nwith 4.3.0 software is safe and effective for\nthe intended users, uses, and use\nenvironments."],["Dosimetry","Dosimetry studies were used to confirm the\ndose accuracy (kV, mA, CTDI and DLP)\nfor the new acquisition features including\nthe Spine Smart Dose and 3D Long Scan.","All the dosimetry testing passed the system\nlevel requirements."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240516-p6-t0","doc_id":"K240516","page_num":6,"bbox":[101.67,209.9,533.97,492.19],"n_rows":8,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical equipment - Part\n1-2: General requirements for basic safety and essential performance -\nEMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -\nPart 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems","",""],["ISO10993-1","","","AAMI / ANSI / ISO 10993-1:2018/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3","",""]],"caption_candidate":"following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240516-p9-t0","doc_id":"K240516","page_num":9,"bbox":[66.62,510.55,561.57,573.79],"n_rows":5,"n_cols":2,"columns":["[ The validation for SonoSync ]",""],"rows":[["[ The validation for SonoSync ]",""],["","Pre-determined criteria were utilized in validation tests to assess whether remote viewing and reviewing"],["","with SonoSync matched the performance of local ultrasound systems."],["","Labeling materials is provided to inform users about the necessary specifications for safely and effectively"],["","conducting remote diagnostic reviews and viewing."]],"caption_candidate":"training process, and there is no overlap among the three.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240540-p6-t0","doc_id":"K240540","page_num":6,"bbox":[68.66,517.99,543.58,715.66],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K230152)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K230152)","Remark"],["Indications For\nUse","The uMR Omega system is\nindicated for use as a magnetic\nresonance diagnostic device\n(MRDD) that produces sagittal,\ntransverse, coronal, and oblique\ncross sectional images, and\nspectroscopic images, and that\ndisplay internal anatomical structure\nand/or function of the head, body\nand extremities.\nThese images and the physical\nparameters derived from the images\nwhen interpreted by a trained\nphysician yield information that","The uMR Omega system is\nindicated for use as a magnetic\nresonance diagnostic device\n(MRDD) that produces sagittal,\ntransverse, coronal, and oblique\ncross sectional images, and\nspectroscopic images, and that\ndisplay internal anatomical structure\nand/or function of the head, body\nand extremities.\nThese images and the physical\nparameters derived from the images\nwhen interpreted by a trained\nphysician yield information that","Same"]],"caption_candidate":"Table 1 Comparison of Modification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240540-p7-t0","doc_id":"K240540","page_num":7,"bbox":[68.66,85.34,543.58,205.34],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K230152)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K230152)","Remark"],["","may assist the diagnosis. Contrast\nagents may be used depending on\nthe region of interest of the scan.","may assist the diagnosis. Contrast\nagents may be used depending on\nthe region of interest of the scan.",""],["Breast Coil - 24","Yes","No","Note 1"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240540-p7-t1","doc_id":"K240540","page_num":7,"bbox":[64.34,445.87,547.78,708.22],"n_rows":5,"n_cols":4,"columns":["Item","Verification/Validation\nMethod(s)","Acceptance Criteria","Summary of Results"],"rows":[["Item","Verification/Validation\nMethod(s)","Acceptance Criteria","Summary of Results"],["Surface heating","Perform test according to\nNEMA MS 14","The maximum temperature\nof all temperature probes\nshall not exceed 41℃.","Pass"],["General\nelectrical/mechanical\nsafety","Perform test according to\nANSI/AAMI ES60601-1","Conform with\nANSI/AAMI ES60601-1","Pass"],["SNR and Uniformity","Perform test according to\nNEMA MS 1, NEMA MS\n3, NEMA MS 6 and\nNEMA MS 9","SNR and Uniformity shall\nfulfill the design\nspecification.","Pass"],["Biocompatibility","Biocompatibility\nevaluation in agreement\nwith recommendations in\nUse of International\nStandard ISO 10993-1,\n\"Biological evaluation of\nmedical devices - Part 1:\nEvaluation and testing","Materials of construction\nand manufacturing\nmaterials exempt from\ntesting according to the\nBiocompatibility guidance\n(Attachment G), the\n510(k) numbers for\ndevices where these","All the materials of\npatient-contacting\ncomponents for the Breast\nCoil - 24 are identical to\nuMR Omega which was\ncleared in K230152 in\nformulation, processing,\nsterilization, and"]],"caption_candidate":"the substantial determination.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240540-p8-t0","doc_id":"K240540","page_num":8,"bbox":[64.34,85.34,547.78,289.25],"n_rows":3,"n_cols":4,"columns":["","within a risk management\nprocess\"","materials have been\npreviously approved, or\nfull biocompatibility report\n(assessment of\nsensitization, irritation and\ncytotoxicity risks) for\ncomponents that have\ndirect contact with the\npatient.","geometry, and no other\nchemicals have been\nadded (e.g., plasticizers,\nfillers, additives, cleaning\nagents, mold release\nagents)."],"rows":[["","within a risk management\nprocess\"","materials have been\npreviously approved, or\nfull biocompatibility report\n(assessment of\nsensitization, irritation and\ncytotoxicity risks) for\ncomponents that have\ndirect contact with the\npatient.","geometry, and no other\nchemicals have been\nadded (e.g., plasticizers,\nfillers, additives, cleaning\nagents, mold release\nagents)."],["EMC-immunity,\nelectrostatic discharge","Perform test according to\nIEC 60601-1-2 and IEC\n60601-4-2","Conform with IEC 60601-\n1-2 and IEC 60601-4-2","Pass"],["Clinical image quality","Evaluate the image\ngenerated by Breast Coil-\n24 with the same method\nas the predicate device","Image quality is sufficient\nfor diagnostic use.","The U.S. Board Certified\nradiologist approves that\nimage quality is sufficient\nfor diagnostic use."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240554-p7-t0","doc_id":"K240554","page_num":7,"bbox":[37.34,104.18,574.77,717.22],"n_rows":14,"n_cols":5,"columns":["Item","Subject Device:","Primary Predicate:","Secondary Predicate:","Reference Device:"],"rows":[["Item","Subject Device:","Primary Predicate:","Secondary Predicate:","Reference Device:"],["","InferRead Lung CT.AI","InferRead Lung CT.AI","Lung Nodule","ClearRead CT(K221612)"],["","","(K192880)","Assessment and",""],["","","","Comparison Option",""],["","","","(LNA)(K162484)",""],["Indications for\nUse","InferRead Lung CT.AI is\ncomprised of computer\nassisted reading tools\ndesigned to aid the\nradiologist in the detection\nof pulmonary nodules ≥\n4mm during the review of\nCT examinations of the\nchest on an asymptomatic\npopulation ≥ 55 years old.\nInferRead Lung CT.AI\nrequires that both lungs be\nin the field of view.\nInferRead Lung CT.AI\nprovides adjunctive\ninformation and is not\nintended to be used without\nthe original CT series.","InferRead Lung CT.AI is\ncomprised of computer\nassisted reading tools\ndesigned to aid the\nradiologist in the detection\nof pulmonary nodules\nduring the review of CT\nexaminations of the chest\non an asymptomatic\npopulation. InferRead\nLung CT.AI requires that\nboth lungs be in the field of\nview. InferRead Lung\nCT.AI provides adjunctive\ninformation and is not\nintended to be used without\nthe original CT series.","The Lung Nodule\nAssessment and\nComparison Option is\nintended for use as a\ndiagnostic patient-imaging\ntool. It is intended for the\nreview and analysis of\nthoracic CT images,\nproviding quantitative and\ncharacterizing information\nabout nodules in the lung\nin a single study, or over\nthe time course of several\nthoracic studies.\nCharacterizations include\ndiameter, volume and\nvolume over time. The\nsystem automatically\nperforms the\nmeasurements, allowing\nlung nodules and\nmeasurements to be\ndisplayed.","ClearRead CT is comprised\nof computer-assisted\nreading tools designed to\naid the radiologist in the\ndetection and\ncharacterization of\npulmonary nodules during\nthe review of screening and\nsurveillance (low-dose) CT\nexaminations of the chest\non a non-oncological\npatient population.\nClearRead CT requires\nboth lungs be in the field of\nview and is not intended\nfor monitoring patients\nundergoing therapy for\nlung cancer or limited field\nof view CT scans.\nClearRead CT provides\nadjunctive information and\nis not intended to be used\nwithout the original CT\nseries."],["Product Code","OEB, QIH","OEB, LLZ","LLZ, JAK","OEB, LLZ"],["User Access\nPoint","Post Processing\nApplication","Post Processing\nApplication","Post Processing\nApplication","Post Processing\nApplication"],["Image Input","DICOM","DICOM","DICOM","DICOM"],["Type of Scans","CT","CT","CT","CT"],["Anatomical\nRegion","Chest","Chest","Chest","Chest"],["Automatically\nLocate and\nIdentify Lung\nNodules","Yes","Yes","Yes","Yes"],["Modifies the\nOriginal CT\nscan","No","No","No","No"],["Automatic\ncalculation of\nmeasurements","The maximum axial plane\nlongest diameter and\nshortest diameter, the mean","The maximum and axial\nplane longest diameter,\nmean diameter and volume","Short axis- longest\ndiameter perpendicular to\nthe long axis on the","Volume, maximum,\nminimum, average axial\nplane diameters"]],"caption_candidate":"Detailed Comparison of the Subject and Predicate/Reference Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240554-p8-t0","doc_id":"K240554","page_num":8,"bbox":[37.32,71.28,574.8,325.01],"n_rows":5,"n_cols":5,"columns":["for each\nsegmented\nnodule","diameter, volume, mean\ndensities information are\nprovided.","information are provided.","slice(mm)\nLong Axis- Longest\ndiameter on an axial slice\n(mm)\nAverage\\ Max 3D \\\nEffective diameter (mm)\nVolume(mm3)\nMean densities (HU)",""],"rows":[["for each\nsegmented\nnodule","diameter, volume, mean\ndensities information are\nprovided.","information are provided.","slice(mm)\nLong Axis- Longest\ndiameter on an axial slice\n(mm)\nAverage\\ Max 3D \\\nEffective diameter (mm)\nVolume(mm3)\nMean densities (HU)",""],["Temporal\nComparison\n(Nodule\nMatching)","Yes, automatic","No","Yes, Semi-Automatic","Yes, Fully Automatic"],["Segmentation\nof lungs and\nlung lobes","Yes","No","Yes","Yes"],["Nodule\nlocation","Yes","No","No","Yes"],["Reporting\nresults","Yes","No","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p5-t0","doc_id":"K240582","page_num":5,"bbox":[85.48,663.32,509.67,701.52],"n_rows":3,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K231917","","","VEA Align (primary predicate)","","","January 2024","",""],["K172346","","","sterEOS (secondary predicate)","","","June 2018","",""]],"caption_candidate":"3.1 VEA Align","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p6-t0","doc_id":"K240582","page_num":6,"bbox":[85.5,152.76,509.65,178.2],"n_rows":2,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K232086","","","spineEOS","","","October 2023","",""]],"caption_candidate":"3.2 spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p8-t0","doc_id":"K240582","page_num":8,"bbox":[76.3,110.95,765.47,519.96],"n_rows":3,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["Indication for Use","This cloud-based software is\nintended for orthopedic\napplications in both pediatric\nand adult populations.\n2D X-ray images acquired in\nEOS imaging’s imaging systems\nis the foundation and resource\nto display the interactive\nlandmarks overlayed on the\nfrontal and lateral images.\nThese landmarks are available\nfor users to assess patient-\nspecific global alignment.\nFor additional assessment,\nalignment parameters compared\nto published normative values\nmay be available.\nThis product serves as a tool to\naid in the analysis of spinal\ndeformities, degenerative\ndiseases, lower limb alignment\ndisorders, and deformities\nthrough precise angle and\nlength measurements. It is\nsuitable for use with adult and\npediatric patients aged 7 years\nand older.","","","The sterEOS Workstation is\nintended for use in the fields of\nmusculoskeletal radiology and\northopedics in both pediatric and\nadult populations as a general\ndevice for acceptance, transfer,\ndisplay, storage, and digital\nprocessing of 2D X-ray images\nof the musculoskeletal system\nincluding interactive 2D\nmeasurement tools.\nWhen using 2D X-ray images\nobtained with the EOS imaging\nEOS system, sterEOS\nWorkstation provides interactive\n3D measurement tools:\n To aid in the analysis of\nscoliosis and related disorders\nand deformities of the spine in\nadult patients as well as\npediatric patients. The 3D\nmeasurement tools include\ninteractive analysis based\neither on identification of\nanatomical landmarks for\npostural assessment, or on a\nmodel of bone structures\nderived from an a priori image\ndata set from 175 patients (91\nnormal patients, 47 patients","","","This cloud-based software is\nintended for orthopedic\napplications in both pediatric\nand adult populations.\n2D X-ray images acquired in\nEOS imaging’s imaging systems\nis the foundation and resource\nto display the interactive\nlandmarks overlayed on the\nfrontal and lateral images.\nThese landmarks are available\nfor users to assess patient-\nspecific global alignment.\nFor additional assessment,\nalignment parameters compared\nto published normative values\nmay be available.\nThis product serves as a tool to\naid in the analysis of spinal\ndeformities and degenerative\ndiseases, and lower limb\nalignment disorders and\ndeformities through precise\nangle and length\nmeasurements. It is suitable for\nuse with adult and pediatric\npatients aged 7 years and older.","YES\nSame as VEA Align."]],"caption_candidate":"Table 1: Summary of Predicate and Subject VEA Align Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p9-t0","doc_id":"K240582","page_num":9,"bbox":[76.3,90.07,765.47,520.32],"n_rows":3,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["","Clinical judgment and\nexperience are required to\nproperly use the software.","","","with moderate idiopathic\nscoliosis and 37 patients with\nsevere idiopathic scoliosis),\nand dry isolated vertebrae\ndata for spine modeling. The\nmodel of bone structures is\nnot intended for use to assess\nindividual vertebral\nabnormalities and is indicated\nonly for patients 7 years and\nolder. For postural\nassessment, a set of\ncomparative tools is provided\nallowing the comparison of\nperformed measurements to\nreference values for patients\nover 18 years old.\n To aid in the analysis of lower\nlimbs alignment and related\ndisorders and deformities\nbased on angle and length\nmeasurements. The 3D\nmeasurement tools include\ninteractive analysis based\neither on identification of lower\nlimb alignment landmarks or\nas for the spine, on a model of\nbone structures derived from\nan a priori image data set.\nThe model of bone structures\nis not intended for use to\nassess individual bone","","","Clinical judgment and\nexperience are required to\nproperly use the software.",""]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p10-t0","doc_id":"K240582","page_num":10,"bbox":[76.29,90.07,765.49,517.44],"n_rows":4,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["","","","","abnormalities. The 3D\npackage including model-\nbased measurements and\ntorsion angles is indicated\nonly for patients 15 years or\nolder. Only the 2D/3D ruler is\nindicated for measurements in\npatients younger than 15\nyears old.","","","",""],["Contraindications","VEA Align is contraindicated for\ncases with vertebrae with severe\ncongenital deformities (e.g.,\nhemivertebrae, spina bifida, etc.)\nand supernumerary/missing\nvertebrae.","","","The 3D spine modeling software\ndoes not allow modeling of\nvertebrae with severe congenital\ndeformities (e.g. hemivertebrae,\nspina bifida, etc.). The modeling\nof a spine that has a vertebrae\nwith a congenital deformity may\nbe generated leaving out the\nvertebrae with the congenital\ndeformity.\nThe 3D models delivered by the\nsterEOS software can only be\nused for diagnostic purposes\nwith the corresponding 2D\nimages. They are designed to\ndisplay the spatial relationship\nbetween anatomical structures\nand are unable to highlight local\nbone alterations such as:\n bones with significant\nchanges in geometry following\nsurgical intervention,","","","VEA Align is contraindicated for\ncases with vertebrae with severe\ncongenital deformities (e.g.,\nhemivertebrae, spina bifida, etc.)\nand supernumerary/missing\nvertebrae.","YES\nSame as VEA Align."]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p11-t0","doc_id":"K240582","page_num":11,"bbox":[76.29,90.07,765.49,492.9],"n_rows":4,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["","","",""," fractures,\n osteophytes,\n fibrocartilage calluses.\nThe lower limb 3D model is\nbased on an adult type and, as a\nresult, is not suited to pediatric\nlower limb 3D reconstruction.\n3D modeling can become\ninaccurate and even impossible\nwhen anatomical structures\ncannot be identified as such in\nthe following cases:\n prostheses or instruments\nmasking or replacing\nanatomical markers,\n certain pathological conditions\nthat alter the bone\ncomposition, such as\nosteoporosis,\n impossibility to differentiate\nthe internal condyle from the\nexternal condyle or the\ninternal tibial plate from the\nexternal tibial plate.","","","",""],["Regulatory\nClass/Code","Class II\nQIH\n(21 CFR 892.2050)","","","Class II\nLLZ\n(21 CFR 892.2050)","","","Class II\nQIH\n(21 CFR 892.2050)","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p12-t0","doc_id":"K240582","page_num":12,"bbox":[76.27,90.07,765.51,513.6],"n_rows":9,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["Device Classification\nName","Automated Radiological Image\nProcessing Software","","","System, Image Processing,\nRadiological","","","Automated Radiological Image\nProcessing Software","YES,\nSame as VEA Align."],["Operating System","Windows + MAC","","","Windows","","","Windows + MAC","YES"],["User Population","VEA Align is designed for\nsurgeons and clinical staff, such\nas physician assistants, who\nhave been trained to use the\napplication.","","","Clinicians (radiologists,\northopedists, radiographers), 3D\nServices persons, which have\nbeen trained to use the\napplication.","","","VEA Align Alignment\nAssessment mode is designed\nfor surgeons and clinical staff,\nsuch as physician assistants,\nwho have been trained to use\nthe application.\nVEA Align 3D mode is designed\nfor 3D Services team members.","YES\nAlignment Assessment\nmode is equivalent to\npredicate VEA Align and\n3D Mode is equivalent to\npredicate sterEOS (3D\nServices users)."],["Target Population","The device is indicated only for\npatients 7 years and older.","","","3D measurement tools are used\non adult and pediatric patients\nover 7 years of age who suffer\nfrom scoliosis and deformed\nspine pathology and for patients\nover 15 years of age with\ndeformed lower limb pathology.","","","The device is indicated only for\npatients 7 years and older.","YES\nSame as VEA Align."],["Software\nFunctionalities /\nModalities","Global alignment assessments","","","Global alignment assessments","","","Global alignment assessments","YES"],["","Includes landmarks associated\nwith vertebral endplates needed\nto calculate coronal and sagittal\nclinical parameters. These\nlandmarks are adjustable by the\nuser.","","","Includes landmarks associated\nwith vertebral endplates needed\nto calculate coronal and sagittal\nclinical parameters. These\nlandmarks are adjustable by the\nuser.","","","Includes landmarks associated\nwith vertebral endplates needed\nto calculate coronal and sagittal\nclinical parameters. These\nlandmarks are adjustable by the\nuser.","YES"],["","Includes landmarks associated\nwith the pelvis and lower limbs\nneeded to calculate coronal and\nsagittal clinical parameters.","","","Includes landmarks associated\nwith the pelvis and lower limbs\nneeded to calculate coronal and\nsagittal clinical parameters.","","","Includes landmarks associated\nwith the pelvis and lower limbs\nneeded to calculate coronal and\nsagittal clinical parameters.","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p13-t0","doc_id":"K240582","page_num":13,"bbox":[76.27,90.07,765.51,521.34],"n_rows":12,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["","These landmarks are adjustable\nby the user.","","","These landmarks are adjustable\nby the user.","","","These landmarks are adjustable\nby the user.",""],["","Provides normative values used\nto assess patients’ global\nalignment","","","Provides normative values used\nto assess patients’ global\nalignment","","","Provides normative values used\nto assess patients’ global\nalignment","YES"],["","Provides color-coded clinical\nparameters to display variance\nfrom the defined normative\nvalues","","","Provides color-coded clinical\nparameters to display variance\nfrom the defined normative\nvalues","","","Provides color-coded clinical\nparameters to display variance\nfrom the defined normative\nvalues","YES"],["Image Manipulation\nFunctions","2D images display and basic\nmanipulation (zoom, panning)","","","","2D images display and basic","","2D images display and basic\nmanipulation (zoom, panning)","YES\nSame as VEA Align."],["","","","","","manipulation (zoom, panning,","","",""],["","","","","","distance, and angles","","",""],["","","","","","measurements)","","",""],["Measurement\nFunctions","Distances and Angles","","","Distances and Angles","","","Distances and Angles","YES"],["Algorithms","Patient-specific clinical\nparameters and calculations\nbased on published literature.","","","Patient-specific clinical\nparameters and calculations\nbased on published literature.","","","Patient-specific clinical\nparameters and calculations\nbased on published literature.","YES"],["3D Reconstruction\nModel","Alignment mode: The 3D model\nsupports the initial placement of\nthe patient anatomic landmarks\non the images using a machine\nlearning-based algorithm. It is\nnot displayed to the user and as\nsuch it is not part of the device\noutputs.","","","The 3D model is deformed\nmanually by the user through\ncontrol points up to matching\naccurately the X-ray contours.","","","Alignment mode: The 3D model\nsupports the initial placement of\nthe patient anatomic landmarks\non the images using a machine\nlearning-based algorithm. It is\nnot displayed to the user and as\nsuch it is not part of the mode\noutputs.\n3D mode: The 3D reconstruction\nmodel is initialized by an AI\nalgorithm and then deformed\nmanually by the user through\ncontrol points up to matching","YES\nAlignment Assessment\nmode is equivalent to\npredicate VEA Align. In\nthe 3D mode, the 3D\nreconstruction model is\nan output of the device\nas for the secondary\npredicate, sterEOS. The\ndifference between the\nsecondary predicate\nsterEOS and the subject"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p14-t0","doc_id":"K240582","page_num":14,"bbox":[76.27,90.07,765.51,524.76],"n_rows":8,"n_cols":9,"columns":["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Secondary Predicate","","Subject VEA Align","Substantially\nEquivalent?"],["","","VEA Align (K231917)","","","sterEOS (K172346)","","",""],["","","","","","","","accurately the X-ray contours.\nThe 3D reconstruction model is\nan output of the 3D mode.","VEA Align is the\nautomatic initialization\nusing an AI algorithm for\nVEA Align 3D model\nreconstruction\ngeneration. This\ndifference allows the user\nto gain time\nduringmanual\nadjustment. This\ndifference does not\nprevent VEA Align from\nachieving its intended\npurpose and does not\ncreate a new risk in VEA\nAlign. Therefore, this\ndifference does not affect\ndevice safety or\neffectiveness."],["User Interface","Computer","","","Computer","","","Computer","YES"],["Obtaining an image","Transferred from other devices","","","Transferred from other devices","","","Transferred from other devices","YES"],["Software\nEnvironment","Cloud-based software","","","Standalone","","","Cloud-based software","YES\nSame as VEA Align."],["Human Intervention\nfor interpretation and\nmanipulation of\nimages","Required","","","Required","","","Required","YES"],["Control of life-saving\ndevices","None","","","None","","","None","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p17-t0","doc_id":"K240582","page_num":17,"bbox":[70.77,90.06,770.92,503.16],"n_rows":11,"n_cols":8,"columns":["Characteristic","","Predicate Device","","","Subject Device","","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","","Subject Device","","Substantially Equivalent?"],["","","spineEOS (K232086)","","","spineEOS","",""],["","Preoperative: allow user to consult the\npreoperative state of the patient\nPlanning: allow user to define patient specific\nsurgical strategy\nRod: allow user to define the design of rods","","","representation and associated landmarks and\nprovide feedback on corrective adjustments.\nPreoperative: allow user to consult the\npreoperative state of the patient\nPlanning: allow user to define patient specific\nsurgical strategy\nRod: allow user to define the design of rods","","","spineEOS to conform with the\ntype of input data"],["Tools Available for\nPlanning","Segmental Alignment\nInterbody Implant\nOsteotomy\nSpondylolisthesis\nRod Curvature Management","","","Segmental Alignment\nInterbody Implant\nOsteotomy\nSpondylolisthesis\nRod Curvature Management","","","YES"],["Software\nFunctionalities /\nModalities","Obtains an image and 3D model transferred\nfrom other devices","","","Obtains an image and 3D model transferred\nfrom other devices","","","YES"],["","Provides normative values used to follow the\nimpact of the planning on the patient\nalignment","","","Provides normative values used to follow the\nimpact of the planning on the patient\nalignment","","","YES"],["","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues","","","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues","","","YES"],["","Requires human intervention for\ninterpretation and manipulation of images","","","Requires human intervention for\ninterpretation and manipulation of images","","","YES"],["Image Manipulation\nFunctions","2D images and 3D model display and basic\nmanipulation (zoom, panning, and angles\nmeasurements, plumbline, and possibility to\nadd comments on the image)","","","2D images and 3D spine display and basic\nmanipulation (zoom, panning, angles\nmeasurements, plumbline, and possibility to\nadd comments on the image)","","","YES\nThe wording referring to the\nrepresentation of the spine in 3D\ndiffers from the predicate to more\nprecisely describe the spine\nrepresentation. However, it\nremains the same between the\npredicate and the subject\nspineEOS."],["Measurement\nFunctions","Distances and Angles","","","Distances and Angles","","","YES."],["User Interface","Computer","","","Computer","","","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240582-p18-t0","doc_id":"K240582","page_num":18,"bbox":[70.79,90.06,770.9,326.64],"n_rows":5,"n_cols":8,"columns":["Characteristic","","Predicate Device","","","Subject Device","","Substantially Equivalent?"],"rows":[["Characteristic","","Predicate Device","","","Subject Device","","Substantially Equivalent?"],["","","spineEOS (K232086)","","","spineEOS","",""],["Software\nEnvironment","Cloud-based software","","","Cloud-based software","","","YES"],["Clinical Parameters\nComputation","Pelvic Tilt (PT)\nSacral Slope (SS)\nPelvic Incidence (PI)\nPelvic Obliquity (PO)\nPelvic Axial Rotation\nSagittal Vertical Axis (SVA)\nC7-CSL\nPI-LL\nT1 Pelvic Angle (TPA)\nCobb Angle\nKyphosis/Lordosis Angle\nKnee Flexion/Extension Angle\nLordosis Percentage Distributions\nSpondylolisthesis grade (i.e., Slippage\npercentage)","","","Pelvic Tilt (PT)\nSacral Slope (SS)\nPelvic Incidence (PI)\nPelvic Obliquity (PO)\nSagittal Vertical Axis (SVA)\nC7-CSL\nPI-LL\nT1 Pelvic Angle (TPA)\nCobb Angle\nKyphosis/Lordosis Angle\nKnee Flexion/Extension Angle\nLordosis Percentage Distributions\nSpondylolisthesis grade (i.e., Slippage\npercentage)","","","YES\nPelvic Axial Rotation has been\nremoved from the subject device.\nCotyle Axis allows determination of\nthe patient frame in which clinical\nparameters are computed. Pelvic\nAxial Rotation is computed based\non Cotyle Axis. So, in the patient\nframe the value is always 0 for this\nparameter."],["Control of Life-\nSaving Devices","None","","","None","","","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240612-p9-t0","doc_id":"K240612","page_num":9,"bbox":[71.1,84.96,524.22,719.46],"n_rows":6,"n_cols":3,"columns":["","Subject device: CINA-VCF\nSoftware","Predicate device: BriefCase Software\n(K222692)"],"rows":[["","Subject device: CINA-VCF\nSoftware","Predicate device: BriefCase Software\n(K222692)"],["Intended Use\n/ Indications\nfor Use","CINA-VCF is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in patients aged 50 years and\nover undergoing non-enhanced or\ncontrast-enhanced CT scans which\ninclude the chest and/or abdomen.\nThe device is intended to assist\nhospital networks and\nappropriately trained medical\nspecialists within the standard-of-\ncare bone health setting in\nworkflow triage by flagging and\ncommunication of suspected\npositive cases of Vertebral\nCompression Fractures (VCF)\nfindings.\nCINA-VCF uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\napplication in parallel to the\nongoing standard of care image\ninterpretation. The device does not\nalter the original medical image,\nand it is not intended to be used as\na diagnostic device.\nThe results of CINA-VCF are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare ultimately responsible for\nreviewing full images per the\nstandard of care.","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of chest and\nabdominal CT images. The device is\nintended to assist hospital networks and\nappropriately trained medical specialists\nwithin the standard-of-care bone health\nsetting in workflow triage by flagging and\ncommunication of suspected positive\ncases of Vertebral Compression Fractures\n(VCFx) findings.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a\nstandalone application in parallel to the\nongoing standard of care image\ninterpretation. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnosis device.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User\npopulation","Trained medical specialists within\nstandard-of-care bone health\nsettings","Hospital networks and appropriately\ntrained medical specialists within the\nstandard of-care bone health setting"],["Anatomical\nregion of\ninterest","Chest and/or abdomen.","Chest and abdomen"],["Data\nacquisition\nprotocol","Non-enhanced / contrast-\nenhanced CT scans of the chest\nand/or abdomen.","Chest and abdominal CT scans"],["Passive\nnotification-","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240612-p10-t0","doc_id":"K240612","page_num":10,"bbox":[71.1,71.1,524.22,422.22],"n_rows":8,"n_cols":3,"columns":["","Subject device: CINA-VCF\nSoftware","Predicate device: BriefCase Software\n(K222692)"],"rows":[["","Subject device: CINA-VCF\nSoftware","Predicate device: BriefCase Software\n(K222692)"],["only, parallel\nworkflow tool","",""],["Interference\nwith standard\nworkflow","No","No"],["Algorithm","Artificial intelligence algorithm","Artificial intelligence algorithm"],["Preview\nimages","Presentation of compressed,\ngrayscale, unannotated images\nthat is marked “not for diagnostic\nuse”","Presentation of compressed, low-quality,\ngrayscale, unannotated image that is\ncaptioned “not for diagnostic use”"],["Alteration of\noriginal\nimage","No","No"],["Removal of\ncases from\nworklist\nqueue","No. The device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","No. The device operates in parallel with\nthe standard of care, which remains the\ndefault option for all cases."],["Structure","-VCF image processing application\n- Compatibility of use with the CINA\nPlatform device (worklist and\nImage Viewer) or other medical\nimage communications device","- AHS module (orchestrator, image\nacquisition);\n- ACS module (image processing);\n- Aidoc Desktop application for workflow\nintegration (feed and non-diagnostic\nImage Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p6-t0","doc_id":"K240631","page_num":6,"bbox":[111.64,527.08,543.93,681.28],"n_rows":5,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical equipment - Part\n1-2: General requirements for basic safety and essential performance -\nEMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -","",""]],"caption_candidate":"recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p7-t0","doc_id":"K240631","page_num":7,"bbox":[111.62,78.24,543.96,206.78],"n_rows":4,"n_cols":2,"columns":["","Part 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems"],"rows":[["","Part 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems"],["ISO10993-1","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess"],["ISO14971","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p7-t1","doc_id":"K240631","page_num":7,"bbox":[125.39,309.23,527.04,387.74],"n_rows":3,"n_cols":8,"columns":["","Validation Type","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly detected frames\n×100\nTotal number of frames with nerve","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p7-t2","doc_id":"K240631","page_num":7,"bbox":[125.39,413.68,527.04,455.74],"n_rows":3,"n_cols":11,"columns":["","Validation Type","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","90.3","","","4.88","","","87.28 to 93.33","",""],["Speed (FPS)","","3.66","","","0.25","","","3.51 to 3.82","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p8-t0","doc_id":"K240631","page_num":8,"bbox":[125.39,369.99,527.04,451.42],"n_rows":3,"n_cols":9,"columns":["","Validation Type","","","Definition","","","Acceptance Criteria",""],"rows":[["","Validation Type","","","Definition","","","Acceptance Criteria",""],["Accuracy (%)","","","Number of correctly segmented frames\nTotal number of frames with nerve\n×100","","","≥ 80%","",""],["Speed (FPS)","","","1000\nAverage latency time of each frame (msec)","","","≥ 2 FPS","",""]],"caption_candidate":"Acceptance Criteria for Segmentation:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240631-p8-t1","doc_id":"K240631","page_num":8,"bbox":[125.39,477.31,527.04,516.82],"n_rows":3,"n_cols":12,"columns":["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],"rows":[["","Validation Type","","","Average","","","Standard Deviation","","","95% CI",""],["Accuracy (%)","","","98.42","","","3.99","","","97.13 to 99.71","",""],["Speed (FPS)","","","3.64","","","0.40","","","3.48 to 3.80","",""]],"caption_candidate":"Summary Performance data, Standard Deviations & Confidence Intervals for Segmentation:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240642-p7-t0","doc_id":"K240642","page_num":7,"bbox":[188.96,72.48,512.61,318.26],"n_rows":13,"n_cols":9,"columns":["","","","","Subject Device","","","Primary Predicate Device",""],"rows":[["","","","","Subject Device","","","Primary Predicate Device",""],["","Manufacturer","","","Disior Ltd","","","Disior Ltd",""],["Trade Name","Trade Name","","","SMART Bun-Yo-Matic","","Bonelogic","",""],["","","","","CT","","","",""],["","510(k)","","Subject Device","","","K223757","",""],["Input","Input","","Computed tomography\nDICOM Computed\ntomography","","","Computed tomography\nDICOM Computed\ntomography","",""],["","Image","","Segmentation of bone\nstructures","","","Segmentation of bone\nstructures","",""],["","Processing","","","","","","",""],["Output","Output","","Automated case report of\nthe 3D model of patient\nanatomy, surgical\ninstrument parameters, and\nvisualization of implant","","","3D model of patient anatomy\nand case report of the 3D\nmodel patient anatomy","",""],["","Measuring","","Perform measurements for\npresurgical planning","","","Perform measurements for\npresurgical planning","",""],["","and Planning","","","","","","",""],["User\nInterface","User","","Graphical user interface\n(GUI) to a web application\nused with a standard web\nbrowser.","","","Graphical user interface\n(GUI) that is standalone\napplication based.","",""],["","Interface","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240645-p5-t0","doc_id":"K240645","page_num":5,"bbox":[52.81,430.23,542.48,469.63],"n_rows":2,"n_cols":9,"columns":["","Classification Description","","","21 CFR Section","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR Section","","","Product Code",""],["Automated Radiological Image Processing Software","","","21 CFR 892.2050","","","QIH, LLZ","",""]],"caption_candidate":"-Trade name: Sonix Health","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240645-p7-t0","doc_id":"K240645","page_num":7,"bbox":[52.78,135.65,535.23,721.05],"n_rows":10,"n_cols":12,"columns":["","Description","","","Decision","","","Subject Device (K240645)","","","Predicate Device (K230209)",""],"rows":[["","Description","","","Decision","","","Subject Device (K240645)","","","Predicate Device (K230209)",""],["Trade/Device name","","","","","","Sonix Health","","","Sonix Health","",""],["Product Code","","","","","","QIH (Subsequent Product Code: LLZ)","","","QIH (Subsequent Product Code: LLZ)","",""],["Regulatory Class","","","SE","","","2","","","2","",""],["Regulation Number","","","-","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Intended use","","","SE","","","Same","","","Sonix Health is intended for\nquantifying and reporting\nechocardiography for use by or on the\norder of a licensed physician. Sonix\nHealth accepts DICOM-compliant\nmedical images acquired from\nultrasound imaging devices. Sonix\nHealth is indicated for use in adult\npopulations.\nUltrasound images are acquired via the\nB (2D), M, Pulsed-wave Doppler, and\nContinuous-wave Doppler modes.","",""],["Indications for use","","","SE","","","","","","","",""],["Where used\n(hospital, home,\nambulance, etc.)","","","SE","","","Same","","","Inside of hospitals, clinics, and\nphysician’s offices.","",""],["Application\ndescription","","","SE","","","Same","","","Sonix Health utilizes artificial\nintelligence to automate previous\nmanual quantification tasks, resulting\nin increased efficiency for users. Our\nsystem performs view classification\nand measurements according to the US\nASE guidelines, and the users can\nreview and modify the results if\nnecessary.","",""],["Semi-automated\nview classification","","","SE","","","PLAX LV, PLAX zoomed AV, PLAX\nzoomed MV, PLAX zoomed AV&MV,\nPLAX zoomed Aorta, A4C, A4C zoomed\nLV, A4C RV-focused, A2C, A2C zoomed\nLV, A3C, A3C zoomed LV, A5C, PSAX\nlevel of great vessels, PSAX level of MV,\nPSAX level of papillary muscles, PSAX\nlevel of apex, SC4C, SC long axis IVC, M-\nmode LA/Ao, M-mode LV, M-mode\nTAPSE, CW Doppler MS, CW Doppler\nMR, PW Doppler MV, CW Doppler AV in\nparasternal, CW Doppler AV, CW Doppler\nAR, CW Doppler TR, CW Doppler PV,\nCW Doppler PR, PW Doppler RVOT, PW\nDoppler LVOT, Mitral annulus TDI septal,\nMitral annulus TDI lateral, Tricuspid\nannulus TDI lateral","","","PLAX LV, A4C, A4C Zoomed LV,\nA2C, A2C zoomed LV, M-mode\nLA/Ao, M-mode LV, CW Doppler\nMS, CW Doppler MR, PW Doppler\nMV, CW Doppler AV, CW Doppler\nAR, CW Doppler TR, CW Doppler\nPV, CW Doppler PR, PW Doppler\nRVOT, PW Doppler LVOT, DTI MV\nannulus","",""]],"caption_candidate":"The identified predicate device within this submission is shown in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240645-p8-t0","doc_id":"K240645","page_num":8,"bbox":[52.8,106.07,535.21,589.91],"n_rows":3,"n_cols":12,"columns":["","Description","","","Decision","","","Subject Device (K240645)","","","Predicate Device (K230209)",""],"rows":[["","Description","","","Decision","","","Subject Device (K240645)","","","Predicate Device (K230209)",""],["Semi-automated\nmeasurements","","","SE","","","[B-Mode]\nIVSd (2D), IVSs (2D), LVIDd (2D),\nLVIDs (2D), LVPWd (2D), LVPWs (2D),\nAo (2D), LA (2D), RVOT (2D), LVOT\n(2D), EF(Teich) (2D), RWT (2D),\nLAESV A4C, LVESV A4C, LVEDV\nA4C, LVGLS / LVSLS A4C, LARS A4C,\nLACtS A4C, LVEF MOD A4C, SV MOD\nA4C, RVEDA A4C, RVESA A4C, RVD1\nA4C, RVD2 A4C, RVD3 A4C, RVFWS\nA4C, RV FAC A4C, LVESV A2C,\nLVEDV A2C, LAESV A2C, LVGLS/\nLVSLS A2C, LVEF MOD A2C, LVGLS /\nLVSLS A3C\n[M-Mode]\nLAd (M), LAs (M), Aod (M), Aos (M),\nIVSd (M), IVSs (M), LVIDd (M), LVIDs\n(M), LVPWd (M), LVPWs (M), EF(Teich)\n(M), RWT(Teich) (M), SV(Teich) (M),\nLVEDV(Teich) (M), LVESV(Teich) (M),\nLVd Mass(ASE) (M), %FS (M), RV\nTAPSE (M)\n[Doppler]\nMS Vmax, MS VTI, MS PHT, MR Vmax,\nMR VTI, MV Peak E Vel, MV Peak A\nVel, MV DecT, AV Vmax, AV VTI, PV\nVmax, PV VTI, AR Vmax, AR PHT, PR\nVmax, PR EDV, TR Vmax, TR VTI,\nRVOT Vmax, RVOT VTI, RVOT AccT,\nLVOT Vmax, LVOT VTI, E' Sept, A' Sept,\nS' Sept, E' Lat, A' Lat, S' Lat(Mitral), S' Lat\n(Tricuspid)","","","IVSd (2D), IVSs (2D), LVIDd (2D),\nLVIDs (2D), LVPWd (2D), LVPWs\n(2D), LA (2D), Ao (2D), LVESV /\nLVEDV (4CH), LAV (4CH), LVESV /\nLVEDV (4CH), LVESV / LVEDV\n(2CH), LAV (2CH), LVESV / LVEDV\n(2CH), LA (mmode), Aorta (m-mode),\nIVSd (m-mode), LVIDd (m-mode),\nLVPWd (m-mode), IVSs (m-mode),\nLVIIDs (m-mode), LVPWs (m-mode),\nMV Peak E Vel, MV Peak A Vel, MV\nDecel Time, e' (med), a' (med), s'\n(med), LVOT Vmax, LVOT VTI,\nRVOT Vmax, RVOT VTI, PV AccT,\nTR Vmax, TR VTI, AR Vmax / PR\nVmax, AR PHT / PR PHT, MV Vmax,\nMV VTI, MV, PHT, MR Vmax, MR\nVTI, AV Vmax / PV Vmax, AV VTI /\nPV VTI, RVOT (2D)","",""],["Semi-automation\ntechnology","","","SE","","","Same","","","After the automated analysis is\ncomplete, users can review and modify\nthe results as needed. The product is\nintended for use by, or on the order of a\nlicensed physician.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240680-p7-t0","doc_id":"K240680","page_num":7,"bbox":[51.24,135.08,533.36,761.58],"n_rows":50,"n_cols":12,"columns":["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],"rows":[["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],["","Trade Name","","","CDM Insights","","","AI-Rad Companion Brain MR","","","OnQ Neuro",""],["510(k) Submitter\n[Number]","","","Oxford Brain Diagnostics\nLtd","","","Siemens Healthcare GmBh","","","CorTechs Labs, Inc","",""],["510(k) Number","","","K240680","","","K213706","","","K210831","",""],["Indications for\nUse","","","","CDM Insights is a post-","","AI-Rad Companion Brain MR\nis a post- processing image\nanalysis software that\nassists clinicians in viewing,\nanalyzing, and evaluating\nMR brain images.\nAI-Rad Companion Brain MR\nprovides the following\nfunctionalities:\n· Automatic segmentation\nand quantitative analysis of\nindividual brain structures\nand white matter\nhyperintensities\n· Quantitative comparison of\neach brain structure with\nnormative data from a\nhealthy population\n· Presentation of results for\nreporting that includes all\nnumerical values as well as\nvisualization of these results","","","OnQ Neuro is a fully automated\npost-processing medical device\nsoftware intended for analyzing\nand evaluating neurological MR\nimage data.\nOnQ Neuro is intended to provide\nautomatic segmentation,\nquantification, and reporting of\nderived image metrics. OnQ\nNeuro is additionally intended to\nprovide automatic fusion of\nderived parametric maps with\nanatomical MRI data. OnQ Neuro\nis intended for use on brain\ntumors, which are\nknown/confirmed to be\npathologically diagnosed cancer.\nOnQ Neuro is intended for\ncomparison of derived image\nmetrics from multiple time-\npoints.\nThe physician retains the ultimate\nresponsibility for making the final\ndiagnosis and treatment decision.","",""],["","","","","processing image analysis","","","","","","",""],["","","","","software that assists","","","","","","",""],["","","","","trained healthcare","","","","","","",""],["","","","","practitioners in viewing,","","","","","","",""],["","","","","analyzing, and evaluating","","","","","","",""],["","","","","MR brain images of adults","","","","","","",""],["","","","","> 45 years of age.","","","","","","",""],["","","","","","","","","","","",""],["","","","","CDM Insights provides the","","","","","","",""],["","","","","following functionalities:","","","","","","",""],["","","","","- Automated","","","","","","",""],["","","","","segmentation and","","","","","","",""],["","","","","quantitative analysis of","","","","","","",""],["","","","","individual brain structures","","","","","","",""],["","","","","and white matter","","","","","","",""],["","","","","hyperintensities","","","","","","",""],["","","","","- Quantitative comparison","","","","","","",""],["","","","","of brain structures and","","","","","","",""],["","","","","derived values with","","","","","","",""],["","","","","normative data from a","","","","","","",""],["","","","","healthy population","","","","","","",""],["","","","","- Presentation of results","","","","","","",""],["","","","","for reporting that includes","","","","","","",""],["","","","","numerical values as well as","","","","","","",""],["","","","","visualization of these","","","","","","",""],["","","","","results","","","","","","",""],["Intended Users","","","","The device is intended for","","","The device is intended for","","Radiologists, Oncologists","",""],["","","","","healthcare practitioners","","","healthcare professionals","","","",""],["","","","","familiar with the post-","","","familiar with the post","","","",""],["","","","","processing of magnetic","","","processing of magnetic","","","",""],["","","","","resonance images","","","resonance images","","","",""],["","Technological","","Software","Software","","Software","Software","","Software","",""],["","Principle","","","","","","","","","",""],["Device\nDescription","Device","","","CDM Insights is automated","","","AI-Rad Companion Brain MR","","","OnQ Neuro is a fully automated\npost-processing medical device\nsoftware that is used by\nradiologists, oncologists, and\nother clinicians to assist with\nanalysis and interpretation of\nneurological MR images. It\naccepts DICOM images using\nsupported protocols and\nperforms 1) automatic\nsegmentation and volumetric\nquantification of brain tumors,",""],["","Description","","","post-processing medical","","","VA40 is an enhancement to","","","",""],["","","","","device software that is","","","the predicate, AI-Rad","","","",""],["","","","","used by radiologists,","","","Companion Brain MR VA20","","","",""],["","","","","neurologists, and other","","","(K193290). Just as in the","","","",""],["","","","","trained healthcare","","","predicate, AI-Rad Companion","","","",""],["","","","","practitioners familiar with","","","Brain MR addresses the","","","",""],["","","","","the post-processing of","","","automatic quantification and","","","",""],["","","","","magnetic resonance","","","visual assessment of the","","","",""],["","","","","images. It accepts DICOM","","","volumetric properties of","","","",""],["","","","","images using supported","","","various brain structures based","","","",""],["","","","","protocols and performs:","","","on T1 MPRAGE datasets. In AI-","","","",""]],"caption_candidate":"510(k) Summary for CDM Insights [K240680]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240680-p8-t0","doc_id":"K240680","page_num":8,"bbox":[51.26,109.9,533.34,746.65],"n_rows":52,"n_cols":12,"columns":["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],"rows":[["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],["","Trade Name","","","CDM Insights","","","AI-Rad Companion Brain MR","","","OnQ Neuro",""],["","","","automatic segmentation\nand quantification of brain\nstructures and lesions,\nautomatic post-acquisition\nanalysis of diffusion-\nweighted magnetic\nresonance imaging (DWI)\ndata, and comparison of\nderived image metrics\nfrom multiple time-points.\nThe values for a given\npatient are compared\nagainst age-matched\npercentile data from a\npopulation of healthy\nreference subjects. White\nmatter hyperintensities\ncan be visualized and\nquantified by volume.\nOutput of the software\nprovides numerical values\nand derived data as graphs\nand anatomical images\nwith graphical color\noverlays.\nCDM Insights output is\nprovided in standard\nDICOM format as a\nDICOM-encapsulated PDF\nreport.","automatic segmentation","","","Rad Companion Brain MR","","","which are known/confirmed to\nbe pathologically diagnosed\ncancer, 2) automatic post-\nacquisition analysis of diffusion-\nweighted magnetic resonance\nimaging (DWI) data and\noptional automated fusion of\nderived image data with\nanatomical MR images, and 3)\ncomparison of derived image\nmetrics from multiple time-\npoints.\nOutput of the software\nprovides values as numerical\nvolumes, and images of derived\ndata as grayscale intensity\nmaps and as graphical color\noverlays on top of the\nanatomical image. OnQ Neuro\noutput is provided in standard\nDICOM format as image series\nand reports that can be\ndisplayed on most third-party\ncommercial DICOM\nworkstations",""],["","","","","and quantification of brain","","","VA40, the quantification and","","","",""],["","","","","structures and lesions,","","","visual assessment extends to","","","",""],["","","","","automatic post-acquisition","","","white matter hyperintensities","","","",""],["","","","","analysis of diffusion-","","","on the basis of T1 MPRAGE","","","",""],["","","","","weighted magnetic","","","and T2 weighted FLAIR","","","",""],["","","","","resonance imaging (DWI)","","","datasets. These datasets are","","","",""],["","","","","data, and comparison of","","","acquired as part of a typical","","","",""],["","","","","derived image metrics","","","head MR acquisition. The","","","",""],["","","","","from multiple time-points.","","","results are directly archived in","","","",""],["","","","","The values for a given","","","PACS as this is the standard","","","",""],["","","","","patient are compared","","","location for reading by","","","",""],["","","","","against age-matched","","","radiologist. From a predefined","","","",""],["","","","","percentile data from a","","","list of 30 structures (e.g.","","","",""],["","","","","population of healthy","","","Hippocampus, Left Frontal","","","",""],["","","","","reference subjects. White","","","Grey Matter, etc.), volumetric","","","",""],["","","","","matter hyperintensities","","","properties are calculated as","","","",""],["","","","","can be visualized and","","","absolute and normalized","","","",""],["","","","","quantified by volume.","","","volumes with respect to the","","","",""],["","","","","Output of the software","","","total intercranial volume. The","","","",""],["","","","","provides numerical values","","","normalized values for a given","","","",""],["","","","","and derived data as graphs","","","patient are compared against","","","",""],["","","","","and anatomical images","","","age-matched mean and","","","",""],["","","","","with graphical color","","","standard deviations obtained","","","",""],["","","","","overlays.","","","from a population of healthy","","","",""],["","","","","CDM Insights output is","","","reference subjects.","","","",""],["","","","","provided in standard","","","The white matter","","","",""],["","","","","DICOM format as a","","","hyperintensities can be","","","",""],["","","","","DICOM-encapsulated PDF","","","visualized as a 3D overlay map","","","",""],["","","","","report.","","","and the quantification in","","","",""],["","","","","","","","count and volume as per 4","","","",""],["","","","","","","","brain regions in the report.","","","",""],["","","","","","","","As an update to the previously","","","",""],["","","","","","","","cleared device, the following","","","",""],["","","","","","","","modifications have been","","","",""],["","","","","","","","made:","","","",""],["","","","","","","","1. Modified Intended","","","",""],["","","","","","","","Use Statement","","","",""],["","","","","","","","2. Addition of white","","","",""],["","","","","","","","matter hyperintensities","","","",""],["","","","","","","","overlay map, count and","","","",""],["","","","","","","","volume as per 4 brain regions","","","",""],["","","","","","","","3. Enhanced DICOM","","","",""],["","","","","","","","Structured Report (DICOM SR)","","","",""],["","","","","","","","4. Updated deployment","","","",""],["","","","","","","","structure","","","",""],["Brain\nMorphometry\nSegmentation","","","","Pre-processing","","","Pre-processing functionality","","Software performs automatic\nsegmentation","",""],["","","","","functionality for automatic","","","for automatic segmentation","","","",""],["","","","","segmentation and","","","and volumetry of MPRAGE","","","",""],["","","","","volumetry of T1-weighted","","","data.","","","",""]],"caption_candidate":"510(k) Summary for CDM Insights [K240680]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240680-p9-t0","doc_id":"K240680","page_num":9,"bbox":[51.24,109.9,533.36,761.84],"n_rows":53,"n_cols":12,"columns":["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],"rows":[["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],["","Trade Name","","","CDM Insights","","","AI-Rad Companion Brain MR","","","OnQ Neuro",""],["","","","","MRI data, e.g. MPRAGE or","","","","","","",""],["","","","","similar acquisition data.","","","","","","",""],["Brain\nMorphometry\nQuantification","","","","Calculation of label maps","","Calculation of label maps\n(display of brain\nsegmentation) and partially\ncombined label maps (fused\nwith the processed MPRAGE\ndata).","","","Software performs automatic\nquantification","",""],["","","","","(display of brain","","","","","","",""],["","","","","segmentation) and","","","","","","",""],["","","","","partially combined label","","","","","","",""],["","","","","maps (fused with the","","","","","","",""],["","","","","processed T1-weighted","","","","","","",""],["","","","","MRI data, e.g. MPRAGE or","","","","","","",""],["","","","","similar acquisition.","","","","","","",""],["Brain\nMorphometry:\nDeviation Map","","","","Calculation of deviation","","Calculation of deviation map\n(representation of brain\nstatus in relation to\nreference data) and partially\ncombined deviation maps\n(fused with the processed\nMPRAGE data) User\ncustomizable color labels for\nthe overlay map","","","Unknown","",""],["","","","","map (representation of","","","","","","",""],["","","","","brain status in relation to","","","","","","",""],["","","","","reference data) and","","","","","","",""],["","","","","partially combined","","","","","","",""],["","","","","deviation maps (fused","","","","","","",""],["","","","","with the processed T1-","","","","","","",""],["","","","","weighted MRI data, e.g.","","","","","","",""],["","","","","MPRAGE or similar","","","","","","",""],["","","","","acquisition)","","","","","","",""],["Diffusion Analysis","","","","Yes, using a single-","","No","","","Yes, using single and multi-\ncompartment diffusion models.","",""],["","","","","compartment diffusion","","","","","","",""],["","","","","model.","","","","","","",""],["","Support","","","Yes, performs comparison","","No","","","Yes, performs comparison of\nderived image metrics from\nmultiple time points.","",""],["","Longitudinal","","","of derived image metrics","","","","","","",""],["","Analysis","","","from multiple time points","","","","","","",""],["Brain White\nMatter\nHyperintensities\nSegmentation","Brain White","","","Pre-processing","","Pre-processing functionality\nfor automatic segmentation\nand volumetry of MPRAGE\nand FLAIR data.","","","Information on White Matter\nHyperintensities is not provided.","",""],["","Matter","","","functionality for automatic","","","","","","",""],["","Hyperintensities","","","segmentation and","","","","","","",""],["","Segmentation","","","volumetry of T1-weighted","","","","","","",""],["","","","","data, that includes","","","","","","",""],["","","","","MPRAGE or similar","","","","","","",""],["","","","","acquisition, and FLAIR","","","","","","",""],["","","","","data. (volumetry of white","","","","","","",""],["","","","","matter hypointensities if","","","","","","",""],["","","","","FLAIR data is not available)","","","","","","",""],["Brain White\nMatter\nHyperintensities\nQuantification","","","","Calculation of white","","Calculation of white matter\nhyperintensities count and\nvolume as per 4 brain\nregions.","","","Information on White Matter\nHyperintensities is not provided.","",""],["","","","","matter hyperintensities","","","","","","",""],["","","","","volume (white matter","","","","","","",""],["","","","","hypointensities volume if","","","","","","",""],["","","","","FLAIR data is not","","","","","","",""],["","","","","available).","","","","","","",""],["Brain White\nMatter\nHyperintensities\nMap","","","","Calculation of white","","Calculation of white matter\nhyperintensities map fused\nwith the processed FLAIR\ndata User customizable\ncolor labels for the overlay\nmap.","","","Information on White Matter\nHyperintensities is not provided.","",""],["","","","","matter hyperintensities","","","","","","",""],["","","","","map fused with the","","","","","","",""],["","","","","processed FLAIR data (or","","","","","","",""],["","","","","white matter","","","","","","",""],["","","","","hypointensities map fused","","","","","","",""],["","","","","with the processed T1-","","","","","","",""],["","","","","weighted data). Color","","","","","","",""],["","","","","labels for the overlay map.","","","","","","",""]],"caption_candidate":"510(k) Summary for CDM Insights [K240680]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240680-p10-t0","doc_id":"K240680","page_num":10,"bbox":[51.24,109.9,533.36,432.3],"n_rows":26,"n_cols":12,"columns":["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],"rows":[["","","","","New Device","","","Predicate Device","","","Additional Predicate Device",""],["","Trade Name","","","CDM Insights","","","AI-Rad Companion Brain MR","","","OnQ Neuro",""],["Distribution &\nArchiving","Distribution &","","Creation of an image\nseries for a report.\nAutomatic transfer of\nreport to a PACS system.","Creation of an image","","","Creation of an image series","","The software is configured at\ninstallation to receive input\nDICOM files from a network\nlocation, and output DICOM to a\nnetwork destination.","",""],["","Archiving","","","series for a report.","","","for a morphometry report.","","","",""],["","","","","Automatic transfer of","","","Automatic transfer of","","","",""],["","","","","report to a PACS system.","","","generated maps and","","","",""],["","","","","","","","morphometry report to a","","","",""],["","","","","","","","PACS system.","","","",""],["User Interface\nConfirmation","","","No User Interface (UI)","","","Confirmation UI with basic\nvisualization functionality","Confirmation UI with basic","","","The software is designed without",""],["","","","","","","","visualization functionality","","","the need for a user interface after",""],["","","","","","","","","","","installation",""],["User Interface\nConfiguration","","","No User Interface (UI)","","","Configuration UI","","","","The software is designed without",""],["","","","","","","","","","","the need for a user interface after",""],["","","","","","","","","","","installation",""],["Architecture","","","Cloud solution","","","","Cloud solution and Edge","","","Cloud solution or within a",""],["","","","","","","","components deployed on","","","hospital’s IT infrastructure on a",""],["","","","","","","","customer premise.","","","server or PC-based workstation",""],["Report Type","","","DICOM-encapsulated PDF\nreport","","","","DICOM structured report","","Standard DICOM format as image\nseries and reports","",""],["","","","","","","","representation of a natural","","","",""],["","","","","","","","language report","","","",""],["","Physical","","CDM Insights is a medical\ndevice software package","","","","AI-Rad Companion Brain MR","","The OnQ Neuro is a stand-alone\nmedical device software package","",""],["","Characteristics","","","","","","VA40 is a medical device","","","",""],["","","","","","","","software package","","","",""],["","Installation","","","Cloud","","","Server","","","Cloud or Server",""],["Data Source","Data Source","","","DICOM images using","","","DICOM images using","","","DICOM images using supported",""],["","","","","supported protocols","","","supported protocols","","","protocols",""]],"caption_candidate":"510(k) Summary for CDM Insights [K240680]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p5-t0","doc_id":"K240697","page_num":5,"bbox":[79.99,121.26,539.38,612.29],"n_rows":37,"n_cols":2,"columns":["1.","ADMINISTRATIVE INFORMATION"],"rows":[["1.","ADMINISTRATIVE INFORMATION"],["",""],["","DateofPreparation:September5,2024"],["","Preparedby: SadafMonajemi,PhD.Co-founderandDirector"],["","Manufacturer: See-ModeTechnologiesPte.Ltd."],["","32CarpenterStreet#03-01"],["","Singapore059911"],["","SINGAPORE"],["","Email:sadaf@see-mode.com"],["","Tel:+61415952782"],["","www.see-mode.com"],["",""],["","OfficialContact: Dr.SadafMonajemi,PhD,Co-founderandDirector"],["","See-ModeTechnologies"],["","32CarpenterStreet#03-01"],["","Singapore059911"],["","SINGAPORE"],["","Email:sadaf@see-mode.com"],["","www.see-mode.com"],["",""],["2.","DEVICE NAME AND CLASSIFICATION"],["",""],["","Trade/ProprietaryName:See-ModeAugmentedReportingTool,Thyroid"],["","(SMART-T)"],["","RegulationNumber:21CFR892.2090"],["",""],["","RegulationName:Radiologicalcomputer-assisteddetectionanddiagnosissoftware"],["",""],["","ClassificationName:System,ImageProcessing,Radiological"],["",""],["","ReviewPanel:Radiology"],["",""],["","RegulatoryClass: ClassII"],["",""],["","ProductCode:QDQ/QIH"],["",""],["3.","INTENDED USE"]],"caption_candidate":"1. ADMINISTRATIVE INFORMATION","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240697-p7-t0","doc_id":"K240697","page_num":7,"bbox":[36.7,499.57,544.5,705.29],"n_rows":4,"n_cols":4,"columns":["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],"rows":[["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],["Administrativeinformation","","",""],["Regulation","21CFR892.2090\nRadiological\ncomputer-assisteddetection\nanddiagnosissoftwarefor\nlesionssuspiciousforcancer","21CFR892.2090\nRadiological\ncomputer-assisteddetection\nanddiagnosissoftwarefor\nlesionssuspiciousforcancer","21CFR892.2060\nRadiological\ncomputer-assisteddiagnostic\nsoftwareforlesions\nsuspiciousofcancer"],["Regulatory\nClass","ClassII","ClassII","ClassII"]],"caption_candidate":"Device, Predicate Device, and Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p8-t0","doc_id":"K240697","page_num":8,"bbox":[36.68,89.9,544.5,709.12],"n_rows":5,"n_cols":4,"columns":["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],"rows":[["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],["Product\nCode","QDQ,QIH","QDQ,LLZ","POK,QIH"],["510(k)\nNumber","K240697","K210670","K212616"],["IntendedUse","","",""],["Indications\nforUse","See-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)isastand-alone\nreportingsoftwaretoassist\ntrainedmedical\nprofessionalsinanalyzing\nthyroidultrasoundimages\nofadult(>=22yearsold)\npatientswhohavebeen\nreferredforanultrasound\nexamination.\nOutputofthedevice\nincludesregionsofinterest\n(ROIs)placedonthethyroid\nultrasoundimagesassisting\nhealthcareprofessionalsto\nlocalizenodulesinthyroid\nstudies.Thedevicealso\noutputsultrasonographic\nlexicon-baseddescriptors\nbasedonACRTI-RADS.The\nsoftwaregeneratesareport\nbasedontheimageanalysis\nresultstobereviewedand\napprovedbyaqualified\nclinicianafterperforming\nqualitycontrol.\nSMART-Tmayalsobeused\nasastructuredreporting\nsoftwareforfurther\nultrasoundstudies.The\nsoftwareincludestoolsfor\nreadingmeasurementsand","BU-CADisasoftware\napplicationindicatedtoassist\ntrainedinterpreting\nphysiciansinanalyzingthe\nbreastultrasoundimagesof\npatientswithsofttissue\nbreastlesionssuspiciousfor\nbreastcancerwhoarebeing\nreferredforfurtherdiagnostic\nultrasoundexamination.\nOutputofthedeviceincludes\nregionsofinterest(ROIs)and\nlesioncontoursplacedon\nbreastultrasoundimages\nassistingphysicianstoidentify\nsuspicioussofttissuelesions\nfromuptotwoorthogonal\nviewsofasinglelesion,and\nregion-basedanalysisof\nlesionmalignancyuponthe\nphysician’squery.The\nregion-basedanalysis\nindicatesthescoreoflesion\ncharacteristics(SLC),and\ncorrespondingBI-RADS\ncategoriesinuser-selected\nROIsorROIsautomatically\nidentifiedbythesoftware.In\naddition,BU-CADalso\nautomaticallyclassifieslesion\nshape,orientation,margin,\nechopattern,andposterior\nfeaturesaccordingtoBI-RADS\ndescriptors.","KoiosDSisanartificial\nintelligence(AI)/machine\nlearning(ML)-based\ncomputer-aideddiagnosis\n(CADx)softwaredevice\nintendedforuseasan\nadjuncttodiagnostic\nultrasoundexaminationsof\nlesionsornodules\nsuspiciousforbreastor\nthyroidcancer.\nKoiosDSallowstheuserto\nselectorconfirmregionsof\ninterest(ROIs)withinan\nimagerepresentingasingle\nlesionornoduletobe\nanalyzed.Thesoftwarethen\nautomaticallycharacterizes\ntheselectedimagedatato\ngenerateanAI/ML-derived\ncancerriskassessmentand\nselectsapplicable\nlexicon-baseddescriptors\ndesignedtoimproveoverall\ndiagnosticaccuracyaswell\nasreduceinterpreting\nphysicianvariability.\nKoiosDSmayalsobeusedas\nanimageviewerof\nmulti-modalitydigital\nimages,includingultrasound\nandmammography.The\nsoftwareincludestoolsthat"]],"caption_candidate":"See-Mode AugmentedReporting Tool,Thyroid","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p9-t0","doc_id":"K240697","page_num":9,"bbox":[36.69,89.9,544.5,621.25],"n_rows":6,"n_cols":4,"columns":["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],"rows":[["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],["","annotationsfromtheimages\nthatcanbeusedfor\ngeneratingastructured\nreport.\nPatientmanagement\ndecisionsshouldnotbe\nmadesolelyonthebasisof\nanalysisbySee-Mode\nAugmentedReportingTool,\nThyroid.","BU-CADmayalsobeusedas\nanimageviewerof\nmulti-modalitydigitalimages,\nincludingultrasoundand\nmammography.Thesoftware\nincludestoolsthatallowusers\ntoadjust,measureand\ndocumentimages,andoutput\nintoastructuredreport(SR).\nPatientmanagementdecisions\nshouldnotbemadesolelyon\nthebasisofanalysisby\nBU-CAD.","allowuserstoadjust,\nmeasureanddocument\nimages,andoutputintoa\nstructuredreport.\nKoiosDSsoftwareis\ndesignedtoassisttrained\ninterpretingphysiciansin\nanalyzingthebreast\nultrasoundimagesofadult\n(>=22years)female\npatientswithsofttissue\nbreastlesionsand/or\nthyroidultrasoundsofall\nadult(>=22years)patients\nwiththyroidnodules\nsuspiciousforcancer.When\nutilizedbyaninterpreting\nphysicianwhohas\ncompletedtheprescribed\ntraining,thisdeviceprovides\ninformationthatmaybe\nusefulinrecommending\nappropriateclinical\nmanagement."],["Intended\nPopulation","Patientswiththyroid\nnodules\nwhoarebeingreferred\nforultrasoundscan\n(Prescriptiononly)","Patientswithsoft\ntissuebreastlesions\nwhoarebeingreferred\nforultrasound\ninterpreting\n(Prescriptiononly)","Patientswiththyroidnodules\nsuspiciousforcancer\n(Prescriptiononly)"],["Image\nSource","Ultrasoundimages","Ultrasoundimages","Ultrasoundimages"],["Rxonly?","Yes","Yes","Yes"],["TechnologicalCharacteristics","","",""]],"caption_candidate":"See-Mode AugmentedReporting Tool,Thyroid","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p10-t0","doc_id":"K240697","page_num":10,"bbox":[36.67,89.9,544.5,701.37],"n_rows":4,"n_cols":4,"columns":["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],"rows":[["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],["Application\nDescription","Thesubjectdeviceisa\nstand-alone,web-based\nimageprocessingand\nreportingsoftwarefor\nlocalization,characterization\nandreportingofthyroid\nultrasoundimages.\nThesoftwareanalyzes\nthyroidultrasoundimages\nandusesmachinelearning\nalgorithmstoextractspecific\ninformation.Thealgorithms\ncanidentifyandlocalize\nsuspicioussofttissue\nnodulesandalsogenerate\nlexicon-baseddescriptors,\nwhichareclassified\naccordingtoACRTI-RADS\n(composition,echogenicity,\nshape,margin,andechogenic\nfoci)withacalculated\nTI-RADScategoryaccording\ntotheACRTI-RADSchart.\nThesoftwarethengenerates\nareportbasedontheimage\nanalysisresultstobe\nreviewedandapprovedbya\nqualifiedclinicianafter\nperformingqualitycontrol.\nAnyinformationwithinthis\nreportcanbechangedand\nmodifiedbytheclinicianif\nneededduringquality\ncontrolandbeforefinalizing\nthereport.","BU-CADisasoftwaresystem\ndesignedtoassistusersin\nanalyzingbreastultrasound\nimagesincludingidentification\nofregionssuspiciousforbreast\ncancerandassessmentoftheir\nmalignancy.BU-CADconsists\nofaviewer,alesion\nidentificationmodule,anda\nlesionanalysismodule.\nThelesionidentification\nmoduleidentifiesregionsof\ninterest(automatedROIs)ofa\nsinglesuspicioussofttissue\nlesioninuptotwoorthogonal\nviewsofbreastultrasound\nimagesforassistingusersin\ndetectingsofttissuelesions.\nAdditionally,thelesion\nidentificationmodule\ngeneratesanROIandalesion\ncontouroneachbreast\nultrasoundimage.\nThelesionanalysismodule\nanalyzesgivenROIsofabreast\nlesiononultrasoundimages,\nandgeneratesascoreoflesion\ncharacteristics(SLC)interms\nofmalignancyorbenignityofa\nlesion,BI-RADScategory,and\nBI-RADSdescriptors.","KoiosDSisa\ncomputer-aideddiagnosis\n(CADx)softwaredevice\nintendedforuseasan\nadjuncttodiagnostic\nultrasoundexaminationsof\nlesionsornodules\nsuspiciousforbreastor\nthyroidcancer.\nKoiosDSallowstheuserto\nselectorconfirmregionsof\ninterest(ROIs)withinan\nimagerepresentingasingle\nlesionornoduletobe\nanalyzed.KoiosDSsoftware\ncontainsfunctionalityfor\nautomaticallyclassifying\nthyroidnodulessuspicious\nforcancer.\nThesystemgeneratesan\noutputalignedtoeitherthe\nTI-RADSorATAclassification\nguidelines.Thesystem\nautomaticallygenerates\nuser-modifiablethyroid\nnoduledescriptors\n(Composition,Echogenicity,\nShape,Margin,Echogenic\nFoci)andadirect,\nimage-derivedcancerrisk\nassessmentthatistranslated\nintoanoptional\nlexicon-specific(TI-RADSor\nATA)modifier."],["Anatomical\nLocation","Thyroid","Breast","ThyroidandBreast"],["Input","Medicalimages\nprovidedinaDICOM\nformat","Medicalimages\nprovidedinaDICOM\nformat","Medicalimages\nprovidedinaDICOM\nformat"]],"caption_candidate":"See-Mode AugmentedReporting Tool,Thyroid","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p11-t0","doc_id":"K240697","page_num":11,"bbox":[36.69,89.9,544.5,710.75],"n_rows":6,"n_cols":4,"columns":["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],"rows":[["","SubjectDevice\nSee-ModeAugmented\nReportingTool,Thyroid\n(SMART-T)\n(K240697)","PredicateDevice\nBU-CAD(K210670)","ReferenceDevice\nKoiosDS(K212616)"],["Output","ROIsplacedonthyroid\nnodules\nTI-RADSlexicondescriptors\nTI-RADScategoryaccording\ntotheACRTI-RADSchart","ROIsandlesion\ncontoursplacedon\nsuspicioussoft\ntissuelesion\nBI-RADSlexicondescriptors\nAregion-basedscore\noflesionmalignancy\nBI-RADScategory","Thyroid\nTI-RADSlexicondescriptors\nbasedonuser-selectedROIs\nTI-RADScategoryaccording\ntotheACRTI-RADSchart\nAdirect,deep-learning\nderivedcancerrisk\nassessmentthatistranslated\nintoanoptional\nlexicon-specificmodifier.\nThesoftware’sdirect,\nnon-descriptor-basedcancer\nriskassessmentispresented\nastheKoios“AIAdapter”that\ncanbeusedinconjunction\nwiththeACRTI-RADSorATA\nguidelinesfornodulerisk\nstratification\nBreast\nCategoricalandcontinuous\noutputs(confidencelevel\nindicator)thatalignto\nBI-RADScategories\nAutoclassificationof\nBI-RADSlexicondescriptors\n(shapeandorientation)"],["Operating\nPlatform","Client-servertechnology.","Client-servertechnology","Client-servertechnology"],["Image\nFormat","DICOM","DICOM","DICOM"],["2Dviewing\ncapabilities","Yes","Yes","Yes"],["Image\nstorageand\nreport\ngeneration","Yes","Yes","Yes"]],"caption_candidate":"See-Mode AugmentedReporting Tool,Thyroid","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p16-t0","doc_id":"K240697","page_num":16,"bbox":[72.25,295.73,529.0,364.5],"n_rows":2,"n_cols":4,"columns":["IOU\nCriteria","AverageAidedAUC\n(95%CI)","AverageUnaidedAUC\n(95%CI)","Standalone\n(95%CI)"],"rows":[["IOU\nCriteria","AverageAidedAUC\n(95%CI)","AverageUnaidedAUC\n(95%CI)","Standalone\n(95%CI)"],["IOU>0.5","0.758(0.711,0.803)","0.736(0.693,0.780)","0.703(0.642,0.762)"]],"caption_candidate":"negative.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p16-t1","doc_id":"K240697","page_num":16,"bbox":[72.25,511.4,529.0,626.5],"n_rows":3,"n_cols":4,"columns":["Analysis","AverageReaderAUC(95%CI)","",""],"rows":[["Analysis","AverageReaderAUC(95%CI)","",""],["","Aided","Unaided","Difference\n(Aided–Unaided)"],["AURLOC\nIOU>0.5\nIOU>0.6\nIOU>0.7\nIOU>0.8","0.758(0.711,0.803)\n0.734(0.682,0.781)\n0.686(0.629,0.740)\n0.593(0.529,0.658)","0.736(0.693,0.780)\n0.682(0.632,0.730)\n0.548(0.490,0.610)\n0.356(0.293,0.423)","0.022(-0.012,0.056)\n0.052(0.008,0.093)\n0.138(0.082,0.195)\n0.237(0.168,0.307)"]],"caption_candidate":"improvereaders’performance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p17-t0","doc_id":"K240697","page_num":17,"bbox":[72.25,138.53,519.25,226.5],"n_rows":2,"n_cols":4,"columns":["","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],"rows":[["","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],["Localisation\nAccuracy","95.6%(94.1,97.0)","93.6%(92.1,95.0)","95.1%"]],"caption_candidate":"dividedbythetotalnumberofcases.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p17-t1","doc_id":"K240697","page_num":17,"bbox":[60.25,471.4,528.25,664.5],"n_rows":6,"n_cols":4,"columns":["TI-RADDescriptor","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],"rows":[["TI-RADDescriptor","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],["Composition","84.9%(82.2,87.5)","80.4%(77.3,83.4)","86.7%"],["Echogenicity","77.4%(74.4,80.3)","70.0%(67.0,72.8)","68.2%"],["Shape","90.8%(88.2,93.1)","86.4%(83.7,88.8)","93.4%"],["Margin","73.5%(70.2,76.7)","57.3%(53.3,61.2)","58.4%"],["EchogenicFoci","75.2%(71.9,78.5)","71.1%(67.1,74.9)","70.3%"]],"caption_candidate":"themostyearsofexperience).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240697-p18-t0","doc_id":"K240697","page_num":18,"bbox":[72.25,467.56,528.25,688.5],"n_rows":7,"n_cols":4,"columns":["TI-RADS","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],"rows":[["TI-RADS","AverageAided\n(95%CI)","AverageUnaided\n(95%CI)","Standalone(95%\nCI)"],["Overall","60.0%(56.8,63.3)","51.1%(47.8,54.5)","63.8(60.0,67.7)"],["TR-1","59.0%(42.3,74.9)","52.9%(37.3,68.3)","61.9(40.0,82.6)"],["TR-2","38.1%(31.1,45.6)","31.2%(24.6,38.1)","41.1(31.7,50.4)"],["TR-3","68.9%(62.6,74.9)","58.8%(52.2,65.4)","71.7(64.9,78.3)"],["TR-4","61.4%(56.5,66.3)","52.1%(47.2,57.0)","65.5(59.1,71.6)"],["TR-5","71.3%(61.8,80.5)","62.0%(52.2,71.5)","77.0(66.1,87.3)"]],"caption_candidate":"agreementisthencalculatedastheaverageoverallthereaders.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240712-p5-t0","doc_id":"K240712","page_num":5,"bbox":[48.51,336.61,506.69,470.11],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","icobrain aria"],"rows":[["Device Trade Name:","icobrain aria"],["Regulation Number","21 CFR 892.2090"],["Regulation Name","Radiological Computer Assisted Detection And Diagnosis Software"],["Regulatory Class","Class II"],["Product Code:","QBS"],["Classification Panel:","Radiology"]],"caption_candidate":"2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240712-p5-t1","doc_id":"K240712","page_num":5,"bbox":[48.51,499.66,506.69,677.66],"n_rows":8,"n_cols":2,"columns":["Device","OsteoDetect"],"rows":[["Device","OsteoDetect"],["De Novo Number","DEN180005"],["Manufacturer","Imagen Technologies"],["Regulation Number","21 CFR 892.2090"],["Regulation Name","Radiological Computer Assisted Detection And Diagnosis Software"],["Regulatory Class","Class II"],["Product Code:","QBS"],["Classification Panel:","Radiology"]],"caption_candidate":"3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240712-p13-t0","doc_id":"K240712","page_num":13,"bbox":[48.45,229.31,546.78,644.06],"n_rows":15,"n_cols":8,"columns":["Table: Primary endpoint results for ARIA detection performance. Results are reported for assisted, unassisted and\nstandalone software. Effect size is defined as the difference between assisted and unassisted AUC, and the p-value\ncorresponds to the hypothesis test on the AUC difference.","","","","","","",""],"rows":[["Table: Primary endpoint results for ARIA detection performance. Results are reported for assisted, unassisted and\nstandalone software. Effect size is defined as the difference between assisted and unassisted AUC, and the p-value\ncorresponds to the hypothesis test on the AUC difference.","","","","","","",""],["","type","without:with\ncondition\nratio","effect size\n[95% CI]","assisted","unassisted","p-value\n(MRMC U\nstatistic\ntest)","software\nstandalone"],["ARIA detection performance","","","","","","",""],["no ARIA-E vs. (mild,\nmoderate or severe)\nARIA-E","AUC","76:123\ncases","0.051\n[0.020, 0.083]","0.873","0.822","0.001","0.838"],["","sensitivity","","","0.865","0.709","","0.943"],["","specificity","","","0.830","0.917","","0.671"],["no ARIA-H vs. (mild,\nmoderate or severe)\nARIA-H","AUC","79:120\ncases","0.044\n[0.017, 0.070]","0.825","0.781","0.001","0.811"],["","sensitivity","","","0.790","0.687","","0.867"],["","specificity","","","0.803","0.828","","0.658"],["no ARIA-H\nmicrohemorrhages\nvs. (mild, moderate or\nsevere) ARIA-\nH microhemorrhages","AUC","117:82\ncases","0.029\n[0.002, 0.055]","0.808","0.779","0.032","0.802"],["","sensitivity","","","0.796","0.693","","0.890"],["","specificity","","","0.767","0.831","","0.624"],["no ARIA-H superficial\nsiderosis vs. (mild,\nmoderate or severe)\nARIA-H superficial\nsiderosis","AUC","121:78\ncases","0.063\n[0.023, 0.102]","0.784","0.721","0.003","0.816"],["","sensitivity","","","0.599","0.497","","0.667"],["","specificity","","","0.956","0.927","","0.950"]],"caption_candidate":"types, except for a specificity of 76.7% for the detection of (mild) ARIA-H microhemorrhages.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240712-p14-t0","doc_id":"K240712","page_num":14,"bbox":[48.38,290.51,546.9,743.98],"n_rows":2,"n_cols":2,"columns":["Summary of the\nbenefits","The clinical performance assessment multiple-reader multiple-case (MRMC) study demonstrated a\nstatistically significant improvement in reader performance in detecting ARIA-E and ARIA-H in the intended\npatient population, as measured by the co-primary endpoints of the difference in Area Under the Curve for\nassisted radiological reading with icobrain aria as compared to the same task without icobrain\naria according to clinical standard of care:\nARIA-E detection: AUC - AUC = 0.873 - 0.822 = 0.051 (two sided 95% confidence interval [0.020,\nassisted unassisted\n0.083])\nARIA-H detection: AUC - AUC = 0.825 - 0.781= 0.044 (two sided 95% confidence interval\nassisted unassisted\n[0.017, 0.070]).\nThe MRMC study also demonstrated that mean sensitivity increased significantly from 70.9% (unassisted)\nto 86.5% (assisted) for ARIA-E detection, and from 68.7% to 79.0% for ARIA-H detection, while the device-\nassisted specificity remained above 80% for the detection of both ARIA types.\nLarge diagnostic gains included an increase in assisted versus unassisted performance for mild ARIA-E and\nmild ARIA-H detection (AUC - AUC = 0.071 for ARIA-E and AUC - AUC = 0.042 for\nassisted unassisted assisted unassisted\nARIA-H), notably a much higher sensitivity, at no downside in performance for the easier tasks of detecting\nmoderate-or-severe ARIA-E and ARIA-H. Earlier detection of subtle ARIA findings will allow earlier\nintervention and mitigate ARIA progression through appropriate decisions on dosing continuation or\nsuspension.\nThe inter-reader variability in ARIA severity determination was also significantly lower for assisted versus\nunassisted reads (Kendall's coefficient of concordance of 0.720 for unassisted and 0.809 for assisted ARIA-E\nseverity assessments, and of 0.656 for unassisted and 0.799 for assisted ARIA-H severity assessments), and\nreaders were on average faster (median unassisted reading 2:34min; median assisted reading 2:21min) when\nperforming assisted reading with icobrain aria."],"rows":[["Summary of the\nbenefits","The clinical performance assessment multiple-reader multiple-case (MRMC) study demonstrated a\nstatistically significant improvement in reader performance in detecting ARIA-E and ARIA-H in the intended\npatient population, as measured by the co-primary endpoints of the difference in Area Under the Curve for\nassisted radiological reading with icobrain aria as compared to the same task without icobrain\naria according to clinical standard of care:\nARIA-E detection: AUC - AUC = 0.873 - 0.822 = 0.051 (two sided 95% confidence interval [0.020,\nassisted unassisted\n0.083])\nARIA-H detection: AUC - AUC = 0.825 - 0.781= 0.044 (two sided 95% confidence interval\nassisted unassisted\n[0.017, 0.070]).\nThe MRMC study also demonstrated that mean sensitivity increased significantly from 70.9% (unassisted)\nto 86.5% (assisted) for ARIA-E detection, and from 68.7% to 79.0% for ARIA-H detection, while the device-\nassisted specificity remained above 80% for the detection of both ARIA types.\nLarge diagnostic gains included an increase in assisted versus unassisted performance for mild ARIA-E and\nmild ARIA-H detection (AUC - AUC = 0.071 for ARIA-E and AUC - AUC = 0.042 for\nassisted unassisted assisted unassisted\nARIA-H), notably a much higher sensitivity, at no downside in performance for the easier tasks of detecting\nmoderate-or-severe ARIA-E and ARIA-H. Earlier detection of subtle ARIA findings will allow earlier\nintervention and mitigate ARIA progression through appropriate decisions on dosing continuation or\nsuspension.\nThe inter-reader variability in ARIA severity determination was also significantly lower for assisted versus\nunassisted reads (Kendall's coefficient of concordance of 0.720 for unassisted and 0.809 for assisted ARIA-E\nseverity assessments, and of 0.656 for unassisted and 0.799 for assisted ARIA-H severity assessments), and\nreaders were on average faster (median unassisted reading 2:34min; median assisted reading 2:21min) when\nperforming assisted reading with icobrain aria."],["Summary of the\nrisks","There are potential risks associated with use of the device, including:\n• The device could provide false positive results (i.e., falsely detecting ARIA-E if there is no ARIA-E, false\ndetecting ARIA-H if there is no ARIA-H), which could contribute to the radiologist using this information\nto make a false positive diagnosis (i.e., diagnosing ARIA-E when there is no ARIA-E, diagnosing ARIA-H\nwhen there is no ARIA-H, overestimating mild ARIA-E or mild ARIA-H as moderate-or-severe ARIA-E or\nARIA-H, respectively). Such a false positive diagnosis can result in unnecessary additional MRI follow-up,\nunnecessary suspension of amyloid beta-directed antibody treatment, delay in treatment (if false\npositive findings correspond to symptoms caused by some other condition), HCP/patient concern,\ninconvenience, discomfort from additional MRI, delay to potential benefit due to suspension of the\namyloid beta-directed antibody treatment, ...\n• The device could provide false negative results (i.e., not detecting actual ARIA-E or ARIA-H findings),\nwhich could contribute to the radiologist using this information to make a false negative diagnosis (e.g.,\nnot diagnosing ARIA-E when there is ARIA-E, not diagnosing ARIA-H when there is ARIA-H,\nunderestimating moderate-or-severe ARIA-E or ARIA-H as mild ARIA-E or ARIA-H, respectively). A false\nnegative diagnosis could lead to delayed diagnosis, delayed suspension of treatment when necessary,\nsymptoms exacerbating, no follow-up MRI, ...\n• The device could be misused to analyze brain images from other patient populations or incompatible\nimage acquisition parameters, leading to inappropriate information regarding the presence/location of\nimaging abnormalities provided to the end user.\n• The device could fail and lead to absence of results, delay of results, or incorrect results, which can lead\nto delayed or inaccurate patient diagnosis."]],"caption_candidate":"conducted for icobrain aria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240736-p6-t0","doc_id":"K240736","page_num":6,"bbox":[197.28,408.36,520.88,630.69],"n_rows":11,"n_cols":9,"columns":["","","","","Subject Device","","","Primary Predicate Device",""],"rows":[["","","","","Subject Device","","","Primary Predicate Device",""],["","Manufacturer","","","Disior Ltd","","","Disior Ltd",""],["Trade Name","Trade Name","","","SMART Bun-Yo-Matic","","Bonelogic","",""],["","","","","X-Ray","","","",""],["","510(k)","","Subject Device","","","K223757","",""],["Input","Input","","Weight-bearing plain film\nX-Rays from sagittal and\ntransverse views","","","Computed tomography\nDICOM Computed\ntomography","",""],["Output","","","Automated case report of\nthe 3D axes of patient\nanatomy, surgical\ninstrument parameters, and\nvisualization of implant","","","3D model of patient anatomy,\nautomated case report","",""],["","Measuring","","Perform measurements for\npresurgical planning","","","Perform measurements for\npresurgical planning","",""],["","and Planning","","","","","","",""],["User\nInterface","User","","Graphical user interface\n(GUI) to a web application\nused with a standard web\nbrowser.","","","Graphical user interface\n(GUI) that is standalone\napplication based.","",""],["","Interface","","","","","","",""]],"caption_candidate":"safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240740-p4-t0","doc_id":"K240740","page_num":4,"bbox":[72.24,369.18,522.77,456.72],"n_rows":6,"n_cols":4,"columns":["Name of Device:","qCT LN Quant","",""],"rows":[["Name of Device:","qCT LN Quant","",""],["Common or Usual Name:","","Medical Image Management and Processing System",""],["Classification Name:","Automated Radiological Image Processing Software","",""],["Regulatory Class:","Class II","",""],["Regulation Number:","21 CFR 892.2050","",""],["Product Code:","QIH","",""]],"caption_candidate":"2 SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240740-p4-t1","doc_id":"K240740","page_num":4,"bbox":[72.24,508.14,522.77,603.3],"n_rows":6,"n_cols":2,"columns":["Name of Device:","Ninesmeasure"],"rows":[["Name of Device:","Ninesmeasure"],["Manufacturer:","Nines, Inc."],["510(k) Number:","K202990"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2050"],["Product Code:","LLZ"]],"caption_candidate":"3 PREDICATE DEVICES","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240740-p4-t2","doc_id":"K240740","page_num":4,"bbox":[72.24,630.54,522.77,723.72],"n_rows":6,"n_cols":2,"columns":["Name of Device:","Lung Nodule Assessment and Comparison Option (LNA)"],"rows":[["Name of Device:","Lung Nodule Assessment and Comparison Option (LNA)"],["Manufacturer:","Philips Medical Systems Nederland B.V."],["510(k) Number:","K162484"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2050; 21 CFR 892.1750"],["Product Code","LLZ, JAK"]],"caption_candidate":"Product Code: LLZ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240740-p10-t0","doc_id":"K240740","page_num":10,"bbox":[72.31,521.7,529.8,639.06],"n_rows":4,"n_cols":3,"columns":["Measurements","Median Absolute\nNormalized Error %","95% Confidence\nInterval"],"rows":[["Measurements","Median Absolute\nNormalized Error %","95% Confidence\nInterval"],["Short Axis Diameter","14.3","13.95 - 16.67"],["Long Axis Diameter","11.1","9.52 - 12.50"],["Volume","20.7","17.29 - 22.41"]],"caption_candidate":"Table 2 Standalone Performance Testing Results for qCT LN Quant","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240740-p10-t1","doc_id":"K240740","page_num":10,"bbox":[72.31,707.94,523.02,765.72],"n_rows":4,"n_cols":2,"columns":["","Both"],"rows":[["","Both"],["the subject and predicate devices are medical image analyzers intended to read chest CT scans to",""],["quantitatively characterize user identified lung nodules. The algorithms function similarly and with the",""],["same purpose of quantitative characterization of lung nodules",""]],"caption_candidate":"The comparison in Table 1 as well as the software & performance testing presented above","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240744-p6-t0","doc_id":"K240744","page_num":6,"bbox":[58.08,666.34,554.14,715.66],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K222755)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K222755)","Remark"],["Indications\nFor Use","The uMR 680 system is indicated\nfor use as a magnetic resonance","The uMR 680 system is indicated\nfor use as a magnetic resonance","Same"]],"caption_candidate":"Table 1 Comparison to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240744-p7-t0","doc_id":"K240744","page_num":7,"bbox":[57.96,85.34,554.26,437.11],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K222755)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K222755)","Remark"],["","diagnostic device (MRDD) that\nproduces sagittal, transverse,\ncoronal, and oblique cross\nsectional images, and\nspectroscopic images, and that\ndisplay internal anatomical\nstructure and/or function of the\nhead, body and extremities.\nThese images and the physical\nparameters derived from the\nimages when interpreted by a\ntrained physician yield\ninformation that may assist the\ndiagnosis. Contrast agents may be\nused depending on the region of\ninterest of the scan.","diagnostic device (MRDD) that\nproduces sagittal, transverse,\ncoronal, and oblique cross sectional\nimages, and spectroscopic images,\nand that display internal anatomical\nstructure and/or function of the\nhead, body and extremities.\nThese images and the physical\nparameters derived from the images\nwhen interpreted by a trained\nphysician yield information that\nmay assist the diagnosis. Contrast\nagents may be used depending on\nthe region of interest of the scan.",""],["Breast\nCoil - 24","Yes","No","The intended use of\nBreast coil -24 is\nequivalent to previously\ncleared Breast Coil-10.\nThe difference between\nthem is the number of\nchannels of the receiver\ncoil.\nThe difference did not\nraise new safety and\neffectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240744-p7-t1","doc_id":"K240744","page_num":7,"bbox":[57.96,465.19,554.26,504.07],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR Omega (K230152)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR Omega (K230152)","Remark"],["MRE","Yes","Yes","Same"]],"caption_candidate":"Table 2 Comparison to Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240744-p8-t0","doc_id":"K240744","page_num":8,"bbox":[57.36,85.34,554.86,702.46],"n_rows":11,"n_cols":4,"columns":["Breast Coil - 24","","",""],"rows":[["Breast Coil - 24","","",""],["Surface heating","Perform test according to\nNEMA MS 14","The maximum temperature\nof all temperature probes\nshall not exceed 41℃.","Pass"],["General\nelectrical/mechanical\nsafety","Perform test according to\nANSI/AAMI ES60601-1","Conform with ANSI/AAMI\nES60601-1","Pass"],["SNR and Uniformity","Perform test according to\nNEMA MS 1, NEMA MS 3,\nNEMA MS 6 and NEMA MS 9","SNR and Uniformity shall\nfulfill with the design\nspecification.","Pass"],["Biocompatibility","Biocompatibility evaluation in\nagreement with\nrecommendations in Use of\nInternational Standard ISO\n10993-1, \"Biological evaluation\nof medical devices - Part 1:\nEvaluation and testing within a\nrisk management process\"","Materials of construction\nand manufacturing\nmaterials exempt from\ntesting according to the\nBiocompatibility guidance\n(Attachment G), the 510(k)\nnumbers for devices where\nthese materials have been\npreviously approved, or full\nbiocompatibility report\n(assessment of\nsensitization, irritation and\ncytotoxicity risks) for\ncomponents that have direct\ncontact with the patient.","All the materials of\npatient-\ncontacting components for\nthe Breast Coil - 24 are\nidentical to uMR Omega\nwhich was cleared in\nK230152 in formulation,\nprocessing, sterilization,\nand geometry, and no\nother chemicals have been\nadded (e.g., plasticizers,\nfillers, additives, cleaning\nagents, mold release\nagents)."],["EMC-immunity,\nelectrostatic\ndischarge","Perform test according to IEC\n60601-1-2 and IEC 60601-4-2","Conform with IEC 60601-\n1-2 and IEC 60601-4-2","Pass"],["Clinical image\nquality","Evaluate the image generated by\nBreast Coil-24 with the same\nmethod as the predicate device","Image quality is sufficient\nfor diagnostic use.","The U.S. Board Certified\nradiologist approves that\nimage quality is sufficient\nfor diagnostic use."],["MRE/ epi_se_mre","","",""],["General\nelectrical/mechanical\nsafety","Perform test according to\nANSI/AAMI ES60601-1","Conform with ANSI/AAMI\nES60601-1","Pass"],["EMC","Perform test according to IEC\n60601-1-2 and IEC 60601-4-2","Conform with IEC 60601-\n1-2 and IEC 60601-4-2","Pass"],["Performance","Perform a phantom and\nvolunteer test under the\nproposed device with MRE","Bias of accuracy,\nrepeatability,\nreproducibility and\nparameter sensitivity shall\nfulfill with the design\nspecification.","Pass"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240769-p5-t0","doc_id":"K240769","page_num":5,"bbox":[90.07,83.9,521.95,681.22],"n_rows":27,"n_cols":5,"columns":["#","Features/ Characteristics","Submitted Device","Predicate Device",""],"rows":[["#","Features/ Characteristics","Submitted Device","Predicate Device",""],["","","","K222970",""],["","","","",""],["","","LVivo IQS","LVivo IQS",""],["","","","",""],["1","Indication for Use","Same","LVivo platform is\nintended for non-\ninvasive processing\nof ultrasound\nimages to detect,\nmeasure, and\ncalculate relevant\nmedical parameters of\nstructures and\nfunction of patients\nwith suspected\ndisease. In addition, it\nprovides Quality Index\nScore Feedback.","LVivo platform is"],["","","","","intended for non-"],["","","","","invasive processing"],["","","","","of ultrasound"],["","","","","images to detect,"],["","","","","measure, and"],["","","","","calculate relevant"],["","","","","medical parameters of"],["","","","","structures and"],["","","","","function of patients"],["","","","","with suspected"],["","","","","disease. In addition, it"],["","","","","provides Quality Index"],["2","Product Code","Same","QIH",""],["3","LVivo IQS Module","LVivo IQS for LV from 4-\nChamber View\nLVivo IQS for RV from 4-\nChamber View","LVivo IQS for LV from 4-\nChamber View",""],["4","Operating System","Same","Ram: 8 GB\nWindows 10 or higher\nProcessor: Intel core i3\ncompatible or higher",""],["5","Automated IQS","Same","Yes",""],["6","Algorithm","AI based","AI Based",""],["7","Grading system ranges","Same","0-60% poor (red),\n60-80 % medium (orange)\n80-100 % good (green)",""],["8","I/O support through API","yes","yes",""],["9","User group","same","same",""],["10","510(k) #","K240769","K222970",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240769-p6-t0","doc_id":"K240769","page_num":6,"bbox":[208.13,526.87,542.4,609.7],"n_rows":3,"n_cols":2,"columns":["End point number","Results"],"rows":[["End point number","Results"],["a.","In 85% of the patients with image quality 3-5\nby visual estimation it was possible to obtain\nat least “Medium” quality score by LVivo IQS"],["b.","92% of the above saved clips were clinically\ninterpretable"]],"caption_candidate":"summarized in Table-1:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240773-p4-t0","doc_id":"K240773","page_num":4,"bbox":[108.26,459.91,523.2,572.5],"n_rows":8,"n_cols":2,"columns":["510(K) Number","K223639"],"rows":[["510(K) Number","K223639"],["Trade Name","VisAble.IO"],["Manufacturer","TechsoMed Medical Technologies. LTD."],["Device Name","VisAble.IO"],["Regulation Number","892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Regulatory Class","Class II"],["Primary Product Code","QTZ, QIH, LLZ"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240773-p6-t0","doc_id":"K240773","page_num":6,"bbox":[73.38,627.04,540.08,719.52],"n_rows":4,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","VisAble.IO (Ver 1.4)","","","VisAble.IO (Ver 1.0)",""],["510(k) number","","","","K223639","",""],["Classification","Class II 892.2050 QTZ, QIH,\nLLZ","","","Class II 892.2050 QTZ, QIH,\nLLZ","",""]],"caption_candidate":"SUBSTANTIAL EQUIVALENCE COMPARISON TABLE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240773-p7-t0","doc_id":"K240773","page_num":7,"bbox":[73.34,72.36,540.12,757.92],"n_rows":6,"n_cols":3,"columns":["","undergo ablation treatment\n(including patients with soft\ntissue lesions)","undergo ablation treatment\n(including patients with soft\ntissue lesions)"],"rows":[["","undergo ablation treatment\n(including patients with soft\ntissue lesions)","undergo ablation treatment\n(including patients with soft\ntissue lesions)"],["Indications for Use","VisAble.IO is a Computed\nTomography (CT) and\nMagnetic Resonance (MR)\nimage processing software\npackage available for use with\nliver ablation procedures.\nVisAble.IO is controlled by the\nuser via a user interface.\nVisAble.IO imports images\nfrom CT and MR scanners and\nfacility PACS systems for\ndisplay and processing during\nliver ablation procedures.\nVisAble.IO is used to assist\nphysicians in planning ablation\nprocedures, including\nidentifying ablation targets and\nvirtual ablation needle\nplacement. VisAble.IO is used\nto assist physicians in\nconfirming ablation zones.\nThe software is not intended\nfor diagnosis. The software is\nnot intended to predict ablation\nvolumes or predict ablation\nsuccess.","VisAble.IO is a Computed\nTomography (CT) image\nprocessing software package\navailable for use with liver\nablation procedures.\nVisAble.IO is controlled by the\nuser via a user interface.\nVisAble.IO is controlled by the\nuser via a user interface.\nVisAble.IO imports images from\nCT and MR scanners and facility\nPACS systems for display and\nprocessing during liver ablation\nprocedures.\nVisAble.IO is used to assist\nphysicians in planning ablation\nprocedures, including identifying\nablation targets and\nvirtual ablation needle\nplacement. VisAble.IO is used to\nassist physicians in confirming\nablation zones.\nThe software is not intended for\ndiagnosis. The software is not\nintended to predict ablation\nvolumes or predict ablation\nsuccess."],["User Population","Qualified trained physicians","Qualified trained physicians"],["Where used","The application’s use\nenvironment is the Operation\nRoom and the hospital\nhealthcare environment such\nas interventional radiology\ncontrol room","The application’s use\nenvironment is the Operation\nRoom and the hospital\nhealthcare environment such as\ninterventional radiology control\nroom"],["Energy Used","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","None – software only application.\nThe software application does\nnot deliver or depend on energy\ndelivered to or from patients"],["Technological\nCharacteristics","VisAble.IO is a stand-alone\nsoftware application with tools\nand features designed to assist\nusers in planning liver ablation\nprocedures as well as tools for\ntreatment confirmation. The\nuse environment the device is\nthe Operating Room and the","VisAble.IO is a stand-alone\nsoftware application with tools\nand features designed to assist\nusers in planning liver ablation\nprocedures as well as tools for\ntreatment confirmation. The use\nenvironment the device is the\nOperating Room and the hospital"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240773-p8-t0","doc_id":"K240773","page_num":8,"bbox":[73.34,72.36,540.12,687.7],"n_rows":6,"n_cols":3,"columns":["","hospital healthcare\nenvironment such as\ninterventional radiology control\nroom. VisAble.IO has five\ndistinct workflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument Placement\n(Needle Planning)\n• Ablation Zone\nSegmentation\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-Interventional\nImages; Quantitative\nAnalysis)","healthcare environment such as\ninterventional radiology control\nroom. VisAble.IO has five distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument Placement\n(Needle Planning)\n• Ablation Zone\nSegmentation\n• Treatment Confirmation\n(Registration of Pre- and\nPost-Interventional\nImages; Quantitative\nAnalysis)"],"rows":[["","hospital healthcare\nenvironment such as\ninterventional radiology control\nroom. VisAble.IO has five\ndistinct workflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument Placement\n(Needle Planning)\n• Ablation Zone\nSegmentation\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-Interventional\nImages; Quantitative\nAnalysis)","healthcare environment such as\ninterventional radiology control\nroom. VisAble.IO has five distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument Placement\n(Needle Planning)\n• Ablation Zone\nSegmentation\n• Treatment Confirmation\n(Registration of Pre- and\nPost-Interventional\nImages; Quantitative\nAnalysis)"],["Design: Supported\nmodalities","CT, MR","CT"],["Design: Data Visualization","Window and level, pan, zoom,\ncross- hairs, slice navigation","Window and level, pan, zoom,\ncross- hairs, slice navigation"],["Design; Image\nSegmentation","Tools for segmenting 3D VOIs,\nincluding target tissues,\nablation zones, vessels and\nliver.","Tools for segmenting 3D VOIs,\nincluding target tissues, ablation\nzones, vessels and liver."],["Design: Image registration","Registration of multiple images\nand imaging modalities into a\nsingle view.","Registration of multiple images\nand imaging modalities into a\nsingle view."],["Design: Ablation zone\nconfirmation","Registration of the planning\nscan, containing the identified\ntarget tissue, with the\nconfirmation scan showing the\nablation zone. The delineated\ntarget tissue on the planning\nscan is then projected onto the\nconfirmation scan and overlaid\nonto the delineated ablation\nzone segmentation. This helps\nthe user in analysing if the\nablation zone covers the target\ntissue with the desired amount\nof margin.","Registration of the planning\nscan, containing the identified\ntarget tissue, with the\nconfirmation scan showing the\nablation zone. The delineated\ntarget tissue on the planning\nscan is then projected onto the\nconfirmation scan and overlaid\nonto the delineated ablation\nzone segmentation. This helps\nthe user in analysing if the\nablation zone covers the target\ntissue with the desired amount\nof margin."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240773-p10-t0","doc_id":"K240773","page_num":10,"bbox":[72.27,150.02,567.11,733.68],"n_rows":14,"n_cols":14,"columns":["Algorithm","N","Gender","","Mean","","","N per","","MR /CT Brand","","Performance","","Performance"],"rows":[["Algorithm","N","Gender","","Mean","","","N per","","MR /CT Brand","","Performance","","Performance"],["","","","","Age","","","Region","","","","Goal","",""],["CT Processing","","","","","","","","","","","","",""],["Liver\nSegmentation","50","M: 52%\nF: 48%","60.6","","","US: 32\nOUS: 18","","","GE Medical\nSystems,\nSiemens","Mean DICE =0.92","","","Mean DICE =0.98"],["Ablation Target\nSegmentation","59","M: 54%\nF: 46%","60.0","","","US: 30\nOUS: 29","","","GE Medical\nSystems,\nSiemens, Philips","Mean DICE = 0.70","","","Mean DICE = 0.82"],["Ablation Zone\nSegmentation","59","M:64% F:\n36%","66.0","","","US: 30\nOUS: 29","","","GE Medical\nSystems,\nSiemens","Mean DICE = 0.70","","","Mean DICE = 0.88"],["Liver Vessels\nSegmentation","100","M: 52%\nF: 48%","58.5","","","US: 72\nOUS: 28","","","GE Medical\nSystems,\nSiemens","Mean DICE = 0.70","","","Mean DICE = 0.72"],["MR Processing","","","","","","","","","","","","",""],["Liver\nSegmentation","25","M: 76%\nF: 24%","70.4","","","US: 25","","","GE Medical\nSystems, Philips,\nSiemens","Mean DICE = 0.92","","","Mean DICE = 0.93"],["Ablation Target\nSegmentation","50","M: 70%\nF: 30%","69","","","US: 46\nOUS: 4","","","GE Medical\nSystems, Philips,\nSiemens","Mean DICE = 0.70","","","Mean DICE = 0.76"],["Image Registration","","","","","","","","","","","","",""],["","","","","","","","","","","","","",""],["Pre-ablation CT to\nPost Ablation CT\nImage Registration","46","M: 59%\nF: 41%","63.3","","","US: 13\nOUS: 33","","","GE Medical\nSystems,\nSiemens,\nPhilips","MCD*= 6.06 mm","","","MCD*=4.09 mm"],["Pre-ablation MR to\nPost-ablation CT\nImage Registration","25","M: 56%\nF: 28%\nOther:\n16%","68.4","","","US: 25","","","MR: GE Medical\nSystems, Philips,\nSiemens\nCT: GE Medical\nSystems, Philips,\nSiemens,\nToshiba","MCD* = 6.06 mm","","","MCD* = 4.72 mm"]],"caption_candidate":"The following table provides a summary of the validation results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p5-t0","doc_id":"K240791","page_num":5,"bbox":[62.01,199.04,318.29,560.88],"n_rows":24,"n_cols":2,"columns":["DATE:","September 9, 2024"],"rows":[["DATE:","September 9, 2024"],["",""],["SUBMITTER:","Adas3D Medical S.L."],["","Rambla Catalunya 53, 4-"],["","08036 Barcelona"],["","Barcelona"],["","Spain"],["",""],["CONTACT:","Antoni Riu"],["","+34 93 328 3964"],["","antoni.riu@adas3d.com"],["",""],["DEVICE TRADE NAME:","ADAS 3D"],["",""],["COMMON NAME:","Radiological Image Proc"],["",""],["CLASSIFICATION NAME:","Radiological Image Proc"],["",""],["PRODUCT CODE:","Primary product code: Q"],["","Secondary product code"],["",""],["REGULATION DESCRIPTION:","Picture archiving and co"],["",""],["PREDICATE DEVICE:","ADAS 3D (K230803)"]],"caption_candidate":"September 9, 2024","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240791-p8-t0","doc_id":"K240791","page_num":8,"bbox":[56.93,236.08,538.29,783.6],"n_rows":12,"n_cols":9,"columns":["Elements of\nComparison","","","","Subject Device","","","Predicate Device",""],"rows":[["Elements of\nComparison","","","","Subject Device","","","Predicate Device",""],["","","","","ADAS 3D","","","ADAS 3D",""],["","","","","(Adas3D Medical S.L.)","","","(K230803)",""],["","Regulatory","","","","","","",""],["","data","","","","","","",""],["Regulatory\nClass","","","Class II","","","Class II","",""],["Classification\nname","","","Radiological Image processing system","","","Radiological Image processing system","",""],["Regulation\nNumber","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Product Code","","","QIH, LLZ","","","LLZ","",""],["510(k) Number","","","K240791","","","K230803","",""],["","Use","","","","","","",""],["Indications for\nUse","","","ADAS 3D is indicated for use in clinical settings\nto support the visualization and analysis of MR\nand CT images of the heart for use on\nindividual patients with cardiovascular\ndisease.\nADAS 3D is indicated for patients with\nmyocardial scar produced by ischemic or non-\nischemic heart disease. ADAS 3D processes MR\nand CT images. The quality and the resolution\nof the medical images determines the\naccuracy of the data produced by ADAS 3D.\nADAS 3D is indicated to be used only by\nqualified medical professionals (cardiologists,\nelectrophysiologists, radiologists or trained\ntechnicians) for the calculation, quantification\nand visualization of cardiac images and\nintended to be used for pre-planning and\nduring electrophysiology procedures. The data","","","Same","",""]],"caption_candidate":"modifications of the subject device to the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p9-t0","doc_id":"K240791","page_num":9,"bbox":[56.92,133.91,538.29,746.76],"n_rows":5,"n_cols":7,"columns":["Elements of\nComparison","","Subject Device","","","Predicate Device",""],"rows":[["Elements of\nComparison","","Subject Device","","","Predicate Device",""],["","","ADAS 3D","","","ADAS 3D",""],["","","(Adas3D Medical S.L.)","","","(K230803)",""],["","produced by ADAS 3D must not be used as an\nirrefutable basis or a source of medical advice\nfor clinical diagnosis or patient treatment. The\ndata produced by ADAS 3D is intended to be\nused to support qualified medical\nprofessionals for clinical decision making.\nThe clinical significance of using ADAS 3D to\nidentify arrhythmia substrates for the\ntreatment of cardiac arrhythmias (e.g.,\nventricular tachycardia) or risk stratification\nhas not been established.","","","","",""],["Device\nDescription\n(Including\nFunctional and\nTechnological\nCharacteristics)","ADAS 3D is a stand-alone software tool\ndesigned for post-processing cardiovascular\nenhanced Magnetic Resonance (MR) images\nand Computed Tomography Angiography\n(CTA) images that are formatted in the Digital\nImaging and Communication in Medicine\n(DICOM) standard. ADAS 3D software aids in\nthe non-invasive calculation, quantification\nand visualization of cardiac imaging data to\nsupport a comprehensive diagnostic decision-\nmaking process for understanding\ncardiovascular disease.\nADAS 3D exports information to multiple\nindustry standard file formats suitable for\ndocumentation and information sharing\npurposes. The 3D data is exported into\nindustry standard file formats supported by\ncatheter navigation systems.\nADAS 3D analyses the enhancement of\nmyocardial fibrosis from DICOM MR images to\nsupport:","","","ADAS 3D is a stand-alone software tool designed\nfor post-processing cardiovascular enhanced\nMagnetic Resonance (MR) images and\nComputed Tomography Angiography (CTA)\nimages that are formatted in the Digital Imaging\nand Communication in Medicine (DICOM)\nstandard. ADAS 3D software aids in the non-\ninvasive calculation, quantification and\nvisualization of cardiac imaging data to support\na comprehensive diagnostic decision-making\nprocess for understanding cardiovascular\ndisease.\nADAS 3D exports information to multiple\nindustry standard file formats suitable for\ndocumentation and information sharing\npurposes. The 3D data is exported into industry\nstandard file formats supported by catheter\nnavigation systems.\nADAS 3D analyses the enhancement of\nmyocardial fibrosis from DICOM MR images to\nsupport:","",""]],"caption_candidate":"510(k) Summary K240791","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p10-t0","doc_id":"K240791","page_num":10,"bbox":[56.93,133.91,538.29,792.6],"n_rows":4,"n_cols":7,"columns":["Elements of\nComparison","","Subject Device","","","Predicate Device",""],"rows":[["Elements of\nComparison","","Subject Device","","","Predicate Device",""],["","","ADAS 3D","","","ADAS 3D",""],["","","(Adas3D Medical S.L.)","","","(K230803)",""],["","● Visualization of the distribution of the\nenhancement in a three-dimensional\n(3D) chamber of the heart.\n● Quantification of the total volume of\nthe enhancement within the Left\nVentricle (LV) and the visualization of\nthe enhancement area in multiple\nlayers through the cardiac structure.\n● Calculation, quantification and\nvisualization of corridors of\nintermediate signal intensity\nenhancement in the LV.\n● Quantification and visualization of\nthe total area and distribution of the\nenhancement within the left Atrium\n(LA).\nAdditionally, ADAS 3D imports DICOM CTA\nimages to support:\n● Quantification of LV wall thickness.\n● Identification and Visualization of\nother 3D anatomical structures.\n● Quantification and visualization of LA\nwall thickness.\n● Quantification and visualization of\ndistances from the LA epicardium to\nother 3D anatomical structures.\nAdditionally, ADAS 3D imports DICOM\nMagnetic Resonance Angiography (MRA)\nimages to support:\n● Identification and Visualization of\nother 3D anatomical structures.","","","● Visualization of the distribution of the\nenhancement in a three-dimensional\n(3D) chamber of the heart.\n● Quantification of the total volume of\nthe enhancement within the Left\nVentricle (LV) and the visualization of\nthe enhancement area in multiple\nlayers through the cardiac structure.\n● Calculation, quantification and\nvisualization of corridors of\nintermediate signal intensity\nenhancement in the LV.\n● Quantification and visualization of the\ntotal area and distribution of the\nenhancement within the left Atrium\n(LA).\nAdditionally, ADAS 3D imports DICOM CTA\nimages to support:\n● Quantification of LV wall thickness.\n● Identification and Visualization of\nother 3D anatomical structures.\n● Quantification and visualization of LA\nwall thickness.\n● Quantification and visualization of\ndistances from the LA epicardium to\nother 3D anatomical structures.\nAdditionally, ADAS 3D imports DICOM Magnetic\nResonance Angiography (MRA) images to\nsupport:\n● Identification and Visualization of\nother 3D anatomical structures.\nIt is designed to be used by qualified medical\nprofessionals (cardiologists, radiologists or","",""]],"caption_candidate":"510(k) Summary K240791","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p11-t0","doc_id":"K240791","page_num":11,"bbox":[56.93,133.91,538.29,582.48],"n_rows":4,"n_cols":7,"columns":["Elements of\nComparison","","Subject Device","","","Predicate Device",""],"rows":[["Elements of\nComparison","","Subject Device","","","Predicate Device",""],["","","ADAS 3D","","","ADAS 3D",""],["","","(Adas3D Medical S.L.)","","","(K230803)",""],["","Additionally, ADAS 3D uses the following\nmachine-learning-based features:\n● Standard Initialization of the LV, LA,\nand Aorta from CTA\n● Standard Initialization of the\nCoronary Arteries from CTA\n● Standard Initialization of the LA from\nCTA\n● Standard Initialization of the LV from\n2D LGE-MRI and Automatic Slice\nAlignment\n● Standard Initialization of the LV from\n3D LGE-MRI\n● Standard Initialization of the LA from\n3D LGE-MRI\nIt is designed to be used by qualified medical\nprofessionals (cardiologists, radiologists or\ntrained technicians) experienced in examining\nand evaluating cardiovascular MR and CTA\nimages as part of the comprehensive\ndiagnostic decision-making process.","","","trained technicians) experienced in examining\nand evaluating cardiovascular MR and CTA\nimages as part of the comprehensive diagnostic\ndecision-making process.","",""]],"caption_candidate":"510(k) Summary K240791","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p12-t0","doc_id":"K240791","page_num":12,"bbox":[56.92,152.37,538.29,507.12],"n_rows":6,"n_cols":6,"columns":["Feature","Subject Device\nADAS 3D\n(Adas3D Medical S.L.)","","Predicate Device","","Comparison"],"rows":[["Feature","Subject Device\nADAS 3D\n(Adas3D Medical S.L.)","","Predicate Device","","Comparison"],["","","","ADAS 3D","",""],["","","","(Adas3D Medical S.L.)","",""],["","","","(K230803)","",""],["Supported\nOperating\nSystems","Linux RHEL 8, Windows 11 and\nWindows 10","Windows 10","","","Added support for\nLinux RHEL 8 and\nWindows 11"],["Initial\nIdentification\nof structures","Semi-automatic using Machine\nLearning technique:\n● Left Chambers from CTA\n● Left Ventricle from 2D DE-MRI\n● Coronaries from CTA\n● Left Ventricle from 3D DE-MRI\n● Left Atrium from 3D DE-MRI\n● Left Atrium Wall Thickness\nfrom CTA","Semi-automatic using Machine\nLearning technique:\n● Left Chambers from CTA\n● Left Ventricle from 2D DE-MRI\n● Coronaries from CTA\nManual:\n● Left Ventricle from 3D DE-MRI\n● Left Atrium from 3D DE-MRI\n● Left Atrium Wall Thickness from\nCTA","","","Added three new\nsemi-automatic\nsegmentations using\nMachine Learning\ntechnique.\nImproved the already\nexisting three semi-\nautomatic\nsegmentations."]],"caption_candidate":"5 Changes from the predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p13-t0","doc_id":"K240791","page_num":13,"bbox":[57.11,239.04,529.2,559.44],"n_rows":7,"n_cols":3,"columns":["Machine learning feature","Number of\nDICOM images","Scanner manufacturers"],"rows":[["Machine learning feature","Number of\nDICOM images","Scanner manufacturers"],["Standard Initialization of\nthe Left Chambers and\nAorta from CTA","111","GE (62%), Toshiba (35%), Philips (3%)"],["Standard Initialization of\nthe Coronaries from CTA","231","Toshiba (48%), Siemens (37%), GE (14%) and Philips\n(1%)."],["Standard Initialization the\nLA from CTA","136","GE (65%), Toshiba (32%) and Philips (3%)"],["Standard Initialization LV\nfrom 2D DE-MRI","126","Siemens (91%), GE (6%), Phillips (3%)"],["Standard Initialization of\nthe LV from 3D DE-MRI","110","Siemens (99%), GE (1%)"],["Standard Initialization of\nthe LA from 3D DE-MRI","82","GE (51%), Philips (49%)"]],"caption_candidate":"The details of the training dataset for each machine learning feature are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p13-t1","doc_id":"K240791","page_num":13,"bbox":[57.11,711.72,549.84,793.44],"n_rows":2,"n_cols":4,"columns":["Machine learning\nfeature","Number\nof cases","Data sources","Scanner manufacturers"],"rows":[["Machine learning\nfeature","Number\nof cases","Data sources","Scanner manufacturers"],["Standard Initialization\nof the Left Chambers","100","US (62%) and","US: SIEMENS (61%), Toshiba (32%) and GE (7%)"]],"caption_candidate":"development, including training. The details of each testing dataset are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p14-t0","doc_id":"K240791","page_num":14,"bbox":[57.1,134.04,549.84,553.08],"n_rows":7,"n_cols":4,"columns":["and Aorta from CTA","","OUS (38%)","OUS: SIEMENS (47%), Toshiba (26%), Canon (13%), GE\n(11%) and Philips (3%)"],"rows":[["and Aorta from CTA","","OUS (38%)","OUS: SIEMENS (47%), Toshiba (26%), Canon (13%), GE\n(11%) and Philips (3%)"],["Standard Initialization\nof the Coronaries from\nCTA","100","US (64%) and\nOUS (36%)","US: SIEMENS (64%), Toshiba (26%), GE (8%) and\nPhillips (2)\nOUS: SIEMENS (47%), Toshiba (28%), Canon (14%), GE\n(8%) and Philips (3%)"],["Standard Initialization\nthe LA from CTA","100","US (65%) and\nOUS (35%)","US: SIEMENS (58%), Toshiba (34%) and GE (8%)\nOUS: SIEMENS (53%), Toshiba (30%), Canon (11%), GE\n(3%) and Philips (3%)"],["Automatic Slice\nAlignment for LV from\n2D DE-MRI","70","US (52%) and\nOUS (48%)","US: SIEMENS (72%), Philips (25%) and GE (3%)\nOUS: Philips (58%), SIEMENS (18%) and GE (24%)"],["Standard Initialization\nof the LV from 2D DE-\nMRI","100","US (52%) and\nOUS (48%)","US: SIEMENS (71%), Philips (23%) and GE (6%)\nOUS: Philips (50%), SIEMENS (19%) and GE (31%)"],["Standard Initialization\nof the LV from 3D DE-\nMRI","100","US (69%) and\nOUS (31%)","US: SIEMENS (62%), Philips (32%) and GE (6%)\nOUS: SIEMENS (49%), Philips (45%), Toshiba (3%) and\nGE (3%)"],["Standard Initialization\nof the LA from 3D DE-\nMRI","95","US (60%) and\nOUS (35%)","US: Philips (50%), SIEMENS (45%) and GE (5%)\nOUS: SIEMENS (71%), Philips (26%) and GE (3%)"]],"caption_candidate":"510(k) Summary K240791","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p15-t0","doc_id":"K240791","page_num":15,"bbox":[56.88,305.52,533.64,797.64],"n_rows":22,"n_cols":8,"columns":["Machine Learning\nfeature","Target\nstructure","Metric","Mean","Lower\nCI95","Higher\nCI95","Threshold","Meets\nacceptance\ncriteria"],"rows":[["Machine Learning\nfeature","Target\nstructure","Metric","Mean","Lower\nCI95","Higher\nCI95","Threshold","Meets\nacceptance\ncriteria"],["Standard\nInitialization of\nthe Left\nChambers and\nAorta from CTA","LV","DC","0.93","0.92","0.94","0.84","yes"],["","LV","MSD","1.29","1.03","1.56","2.23","yes"],["","LA","DC","0.94","0.94","0.95","0.84","yes"],["","LA","MSD","1.06","0.95","1.17","2.23","yes"],["","AO","DC","0.94","0.94","0.95","0.84","yes"],["","AO","MSD","0.93","0.51","1.34","2.23","yes"],["","LAA","DC","0.84","0.83","0.85","0.76","yes"],["","LAA","MSD","1.01","0.91","1.1","2.23","yes"],["Standard\nInitialization of\nthe Coronary\nArteries from\nCTA","LCA","DC","0.82","0.80","0.84","0.78","yes"],["","LCA","HD","7.71","6.05","9.37","10.86","yes"],["","RCA","DC","0.82","0.80","0.83","0.78","yes"],["","RCA","HD","6.61","5.24","7.97","10.86","yes"],["Standard\nInitialization of\nthe LA from CTA","LA ENDO","MSD","0.37","0.32","0.41","0.32","no"],["","LA EPI","MSD","0.56","0.51","0.61","0.76","yes"],["","LA","CA","56.09","53.56","58.63","43.90","yes"],["","LA","CD1","38.32","36.37","40.28","49.00","yes"],["","LA","CD2","5.58","4.73","6.44","12.10","yes"],["Automatic Slice\nAlignment for LV\nfrom 2D LGE-MRI","LV","MDS","2.39","2.22","2.55","6.23","yes"],["Standard\nInitialization of","LV ENDO","DC","0.90","0.90","0.91","0.85","yes"],["","LV ENDO","APD","2.01","1.89","2.13","2.10","no"],["","LV ENDO","HD","9.72","9.04","10.40","13.25","yes"]],"caption_candidate":"are highlighted in bold.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240791-p16-t0","doc_id":"K240791","page_num":16,"bbox":[56.88,133.8,533.64,333.48],"n_rows":10,"n_cols":8,"columns":["the LV from 2D\nLGE-MRI","LV EPI","DC","0.93","0.93","0.94","0.89","yes"],"rows":[["the LV from 2D\nLGE-MRI","LV EPI","DC","0.93","0.93","0.94","0.89","yes"],["","LV EPI","APD","2.06","1.95","2.17","1.93","no"],["","LV EPI","HD","9.81","9.11","10.51","13.25","yes"],["Standard\nInitialization of\nthe LV from 3D\nLGE-MRI","LV ENDO","DC","0.88","0.87","0.88","0.79","yes"],["","LV ENDO","HD","2.40","2.15","2.64","27.32","yes"],["","LV EPI","DC","0.91","0.90","0.92","0.78","yes"],["","LV EPI","HD","9.57","8.81","10.33","27.32","yes"],["Standard\nInitialization of\nthe LA from 3D\nLGE-MRI","LA","DC","0.90","0.89","0.91","0.86","yes"],["","LA","MSD","1.62","1.45","1.78","1.39","no"],["","LA","HD","12.36","11.17","13.55","16.50","yes"]],"caption_candidate":"510(k) Summary K240791","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p8-t0","doc_id":"K240793","page_num":8,"bbox":[65.78,72.48,576.58,713.14],"n_rows":13,"n_cols":4,"columns":["Comparison of Technology Characteristics with Predicate Device","","",""],"rows":[["Comparison of Technology Characteristics with Predicate Device","","",""],["","Predicate Device","Subject Device","Remarks Discussion"],["","Columbo\n(K220497)","MSKai",""],["Intended User","· Radiologist\n· Neurosurgeons and\nOrtho/Spine Surgeons","· Radiologist\n· Neurosurgeons and\nOrtho/Spine Surgeons","Largely Similar"],["Intended Patient\nPopulation","Not subject to restrictions\nother than above the age of\n18, not pregnant, without\npostoperative complication,\nscoliosis, tumors, infections,\nfractures","Not subject to restrictions\nother than above the age of\n18, not pregnant, without\npostoperative complication,\ntumors, infections, complex\nhardware",""],["Supported Body\nPart","Lumbar Spine","Lumbar Spine","· Similar to Predicate\nDevice and Reference\nDevice 2\n· Different from Reference\nDevice 1"],["Segmentation","Yes, Segmentation and\nQuantitative Analysis","Yes, Segmentation and\nQuantitative Analysis","Same"],["Measurement","Yes, Quantitative comparison\nof structure with normative\ndata or user set thresholds","Yes, Quantitative comparison\nof structure with normative\ndata.","Same"],["Reporting","Yes, Exploration of results\nwith the findings for further\nreporting.","Yes, Exploration of results\nwith the findings for further\nreporting.","Same. Reports\nradiologists of\nphysicians evaluate,\nauthorized and modify\nreports"],["SaMD","Yes","Yes","Same"],["Algorithm","Deep Convolutional Image to\nImage Neural Network","Mask Region-based\nConvolutional Neural Network","Similar"],["Supported\nModality","MR","MR","Same as Predicate\ndevice, similar to\nreference devices."],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p9-t0","doc_id":"K240793","page_num":9,"bbox":[65.78,72.48,576.58,619.18],"n_rows":12,"n_cols":4,"columns":["Comparison of Technology Characteristics with Reference Device (1)","","",""],"rows":[["Comparison of Technology Characteristics with Reference Device (1)","","",""],["","Predicate Device","Subject Device","Remarks Discussion"],["","AI-Rad Companion Brain MR\n(K193290)","MSKai",""],["Intended User","· Radiologist","· Radiologist\n· Neurosurgeons and\nOrtho/Spine Surgeons","Largely Similar"],["Intended Patient\nPopulation","Patient population above the\nage of 22 years old.","Not subject to restrictions\nother than above the age of\n18, not pregnant, without\npostoperative complication,\ntumors, infections, complex\nhardware","Largely Similar"],["Supported Body\nPart","Brain","Lumbar Spine","· Similar to Predicate\nDevice and Reference\nDevice 2\n· Different from Reference\nDevice 1"],["Segmentation","Yes, Segmentation and\nQuantitative Analysis","Yes, Segmentation and\nQuantitative Analysis","Same"],["Measurement","Yes, Quantitative comparison\nof structure with normative\ndata or user set thresholds.","Yes, Quantitative comparison\nof structure with normative\ndata.","Same."],["Reporting","Yes, Exploration of results\nwith the findings for further\nreporting.","Yes, Exploration of results\nwith the findings for further\nreporting.","Same. Reports\nradiologists of\nphysicians evaluate,\nauthorized and modify\nreports"],["SaMD","Yes","Yes","Same"],["Algorithm","Unclear","Mask Region-based\nConvolutional Neural Network","Similar"],["Supported\nModality","CT","MR","Same as Predicate\ndevice, similar to\nreference devices."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p10-t0","doc_id":"K240793","page_num":10,"bbox":[65.78,72.48,576.58,664.78],"n_rows":12,"n_cols":4,"columns":["Comparison of Technology Characteristics with Reference Device (2)","","",""],"rows":[["Comparison of Technology Characteristics with Reference Device (2)","","",""],["","Predicate Device","Subject Device","Remarks Discussion"],["","AI-Rad Companion\nMusculoskeletal\n(K193267)","MSKai",""],["Intended User","· Radiologist\n· Primary Care Physicians\n· Specialty/Urgent Care\nPhysicians","· Radiologist\n· Neurosurgeons and\nOrtho/Spine Surgeons","Largely Similar"],["Intended Patient\nPopulation","Not subject to restrictions\nother than above the age of\n22.","Not subject to restrictions\nother than above the age of\n18, not pregnant, without\npostoperative complication,\ntumors, infections, complex\nhardware","Largely Similar"],["Supported Body\nPart","Thorax and Thoracic Spine","Lumbar Spine","· Similar to Predicate\nDevice and Reference\nDevice 2\n· Different from Reference\nDevice 1"],["Segmentation","Yes, Segmentation and\nQuantitative Analysis","Yes, Segmentation and\nQuantitative Analysis","Same"],["Measurement","Yes, Quantitative comparison\nof structure with normative\ndata or user set thresholds","Yes, Quantitative comparison\nof structure with normative\ndata.","Same."],["Reporting","Yes, Exploration of results\nwith the findings for further\nreporting.","Yes, Exploration of results\nwith the findings for further\nreporting.","Same. Reports\nradiologists of\nphysicians evaluate,\nauthorized and modify\nreports"],["SaMD","Yes","Yes","Same"],["Algorithm","3D Image to Image Network","Mask Region-based\nConvolutional Neural Network","Similar"],["Supported\nModality","CT","MR","Same as Predicate\ndevice, similar to\nreference devices."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p11-t0","doc_id":"K240793","page_num":11,"bbox":[72.26,293.09,527.74,447.19],"n_rows":6,"n_cols":2,"columns":["Recognition\n#","Standard"],"rows":[["Recognition\n#","Standard"],["13-79","IEC 62304:2006/AMD 1:2015 Medical device software — Software life cycle processes\n— Amendment 1"],["5-125","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["5-129","IEC 62366-1:2015+AMD1:2020 Medical devices — Part 1: Application of usability\nengineering to medical devices"],["5-117","ISO 15223-1:2016 Medical devices — Symbols to be used with medical device labels,\nlabelling and information to be supplied — Part 1: General requirements"],["12-300","NEMA PS 3.1 - 3.20 (2016) Digital Imaging and Communications in Medicine (DICOM)\nSet"]],"caption_candidate":"Consensus Standards listed in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p13-t0","doc_id":"K240793","page_num":13,"bbox":[149.54,101.54,462.58,330.53],"n_rows":12,"n_cols":3,"columns":["","Number of\nSubjects","Percent\nTotal"],"rows":[["","Number of\nSubjects","Percent\nTotal"],["Total Number of Subjects","238","100.0%"],["Gender-Male","125","52.5%"],["Gender-Female","113","47.5%"],["Age-18 through 21","51","21.4%"],["Age-22 through 50","132","55.4%"],["Age-51 and above","55","23.2%"],["Racial-Caucasian","146","61.3%"],["Racial-Black/African\nAmerican","55","23.1%"],["Racial-Hispanic","28","11.7%"],["Racial-American Indian","3","1.2%"],["Racial-Other","6","2.5%"]],"caption_candidate":"Participant Demographics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p13-t1","doc_id":"K240793","page_num":13,"bbox":[130.46,416.33,481.54,508.15],"n_rows":5,"n_cols":3,"columns":["Manufacturer","Number of MRI\nExams Collected","Percent total"],"rows":[["Manufacturer","Number of MRI\nExams Collected","Percent total"],["GE (1.5 & 3.0T)","116","48.7%"],["Philips (1.5 & 3.0T)","80","33.6%"],["Siemens (1.5 & 3.0T)","42","17.6%"],["Total","238","100.0%"]],"caption_candidate":"Image Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p14-t0","doc_id":"K240793","page_num":14,"bbox":[111.98,198.38,500.14,611.07],"n_rows":18,"n_cols":5,"columns":["Anatomy\nSegmentation","View","Mean Dice\nCoefficient\n(MDC)","95%\nConfidence\nInterval (CI)","MDC\nLimit"],"rows":[["Anatomy\nSegmentation","View","Mean Dice\nCoefficient\n(MDC)","95%\nConfidence\nInterval (CI)","MDC\nLimit"],["Vertebral Body\n(L1)","Sagittal","0.968","0.92-0.98","0.8"],["Vertebral Body\n(L2)","Sagittal","0.977","0.93-0.98","0.8"],["Vertebral Body\n(L3)","Sagittal","0.981","0.94-0.99","0.8"],["Vertebral Body\n(L4)","Sagittal","0.963","0.92-0.98","0.8"],["Vertebral Body\n(L5)","Sagittal","0.985","0.91-0.98","0.8"],["Vertebral Body\n(S1)","Sagittal","0.945","0.93-0.99","0.8"],["L5/S1 Disc","Sagittal","0.993","0.91-0.99","0.8"],["L4/L5 Disc","Sagittal","0.991","0.93-0.99","0.8"],["L3/L4 Disc","Sagittal","0.992","0.93-0.99","0.8"],["L2/L3 Disc","Sagittal","0.989","0.91-0.99","0.8"],["L1/L2 Disc","Sagittal","0.986","0.94-0.99","0.8"],["Cord Canal","Sagittal","0.983","0.93-0.99","0.8"],["Axial Disc","Axial","0.984","0.89-0.97","0.8"],["Vertebral Body","Axial","0.991","0.93-0.99","0.8"],["Dural Sac","Axial","0.978","0.90-0.98","0.8"],["Nerve Root","Axial","0.952","0.90-0.95","0.8"],["Posterior Arch","Axial","0.911","0.90-0.96","0.8"]],"caption_candidate":"Mean Dice Coefficient Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p15-t0","doc_id":"K240793","page_num":15,"bbox":[72.26,101.54,492.34,679.18],"n_rows":15,"n_cols":5,"columns":["Structural\nMeasurements","View","Mean\nAbsolute\nError (MAE)","95%\nConfidence\ninterval","MAE\nLimit"],"rows":[["Structural\nMeasurements","View","Mean\nAbsolute\nError (MAE)","95%\nConfidence\ninterval","MAE\nLimit"],["Protruding Disc\nMaterial (L5/S1)","Sagittal","1.19mm","1.11 -\n1.68mm","2mm"],["Protruding Disc\nMaterial (L4/L5)","Sagittal","1.22mm","1.12 -\n1.71mm","2mm"],["Protruding Disc\nMaterial (L3/L4)","Sagittal","1.23mm","1.14 -\n1.65mm","2mm"],["Protruding Disc\nMaterial (L2/L3)","Sagittal","1.19mm","1.07 -\n1.61mm","2mm"],["Protruding Disc\nMaterial (L1/L2)","Sagittal","1.21mm","1.11 -\n1.63mm","2mm"],["Intervertebral\nAngle (L5/S1)","Sagittal","2.6o","1.58 - 2.45o","6o"],["Intervertebral\nAngle (L4/L5)","Sagittal","2.7o","1.61 - 2.59o","6o"],["Intervertebral\nAngle (L3/L4)","Sagittal","2.7o","1.57 - 2.54o","6o"],["Intervertebral\nAngle (L2/L3)","Sagittal","2.9o","1.64 - 2.62o","6o"],["Intervertebral\nAngle (L1/L2)","Sagittal","2.4o","1.66 - 2.48o","6o"],["Vertebral Body\nHeight (Anterior)\n(L1)","Sagittal","0.66mm","0.62 -\n0.91mm","2mm"],["Vertebral Body\nHeight (Anterior)\n(L2)","Sagittal","0.68mm","0.61 -\n0.88mm","2mm"],["Vertebral Body\nHeight (Anterior)\n(L3)","Sagittal","0.69mm","0.61 -\n0.93mm","2mm"],["Vertebral Body\nHeight (Anterior)\n(L4)","Sagittal","0.64mm","0.58 -\n0.91mm","2mm"]],"caption_candidate":"Maximum Mean Absolute Error Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p16-t0","doc_id":"K240793","page_num":16,"bbox":[72.26,72.24,492.34,689.86],"n_rows":14,"n_cols":5,"columns":["Vertebral Body\nHeight (Anterior)\n(L5)","Sagittal","0.67mm","0.61 -\n0.91mm","2mm"],"rows":[["Vertebral Body\nHeight (Anterior)\n(L5)","Sagittal","0.67mm","0.61 -\n0.91mm","2mm"],["Vertebral Body\nHeight (Midline)\n(L1)","Sagittal","0.94mm","0.62 -\n0.87mm","2mm"],["Vertebral Body\nHeight (Midline)\n(L2)","Sagittal","0.93mm","0.54 -\n1.03mm","2mm"],["Vertebral Body\nHeight (Midline)\n(L3)","Sagittal","0.96mm","0.61 -\n0.1.01mm","2mm"],["Vertebral Body\nHeight (Midline)\n(L4)","Sagittal","0.97mm","0.57 -\n1.13mm","2mm"],["Vertebral Body\nHeight (Midline)\n(L5)","Sagittal","0.94mm","0.57 -\n0.99mm","2mm"],["Vertebral Body\nHeight\n(Posterior) (L1)","Sagittal","0.92mm","0.67 -\n0.99mm","2mm"],["Vertebral Body\nHeight\n(Posterior) (L2)","Sagittal","0.93mm","0.61 -\n1.01mm","2mm"],["Vertebral Body\nHeight\n(Posterior) (L3)","Sagittal","0.91mm","0.68 -\n0.99mm","2mm"],["Vertebral Body\nHeight\n(Posterior) (L4)","Sagittal","0.92mm","0.71 -\n1.06mm","2mm"],["Vertebral Body\nHeight\n(Posterior) (L5)","Sagittal","0.93mm","0.68 -\n1.09mm","2mm"],["Disc Height\n(Anterior)\n(L5/S1)","Sagittal","0.91mm","0.67 -\n0.99mm","2mm"],["Disc Height\n(Anterior) (L4/L5)","Sagittal","0.90mm","0.57 -\n1.06mm","2mm"],["Disc Height\n(Anterior) (L3/L4)","Sagittal","0.87mm","0.62 -\n1.03mm","2mm"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p17-t0","doc_id":"K240793","page_num":17,"bbox":[72.26,72.24,492.34,709.9],"n_rows":18,"n_cols":5,"columns":["Disc Height\n(Anterior) (L2/L3)","Sagittal","0.89mm","0.78 -\n1.06mm","2mm"],"rows":[["Disc Height\n(Anterior) (L2/L3)","Sagittal","0.89mm","0.78 -\n1.06mm","2mm"],["Disc Height\n(Anterior) (L1/L2)","Sagittal","0.93mm","0.71 -\n1.23mm","2mm"],["Disc Height\n(Midline) (L5/S1)","Sagittal","0.93mm","0.73 -\n1.12mm","2mm"],["Disc Height\n(Midline) (L4/L5)","Sagittal","0.90mm","0.68 -\n1.01mm","2mm"],["Disc Height\n(Midline) (L3/L4)","Sagittal","0.89mm","0.71 -\n1.13mm","2mm"],["Disc Height\n(Midline) (L2/L3)","Sagittal","0.91mm","0.64 -\n1.03mm","2mm"],["Disc Height\n(Midline) (L1/L2)","Sagittal","0.92mm","0.69 -\n1.11mm","2mm"],["Disc Height\n(Posterior)\n(L5/S1)","Sagittal","0.87mm","0.58 -\n1.03mm","2mm"],["Disc Height\n(Posterior)\n(L4/L5)","Sagittal","0.93mm","0.67 -\n0.99mm","2mm"],["Disc Height\n(Posterior)\n(L3/L4)","Sagittal","0.87mm","0.66 -\n1.07mm","2mm"],["Disc Height\n(Posterior)\n(L2/L3)","Sagittal","0.93mm","0.72 -\n1.21mm","2mm"],["Disc Height\n(Posterior)\n(L1/L2)","Sagittal","0.89mm","0.58 -\n0.91mm","2mm"],["Anterio-Lithesis\n(L5/S1)","Sagittal","1.04mm","0.81 -\n1.43mm","2mm"],["Anterio-Lithesis\n(L4/L5)","Sagittal","1.02mm","0.77 -\n1.52mm","2mm"],["Anterio-Lithesis\n(L3/L4)","Sagittal","1.05mm","0.88 -\n1.61mm","2mm"],["Anterio-\nLithesis(L2/L3)","Sagittal","1.07mm","0.84 -\n1.43mm","2mm"],["Anterio-Lithesis\n(L1/L2)","Sagittal","1.02mm","0.79 -\n1.33mm","2mm"],["Retro-Lithesis\n(L5/S1)","Sagittal","1.07mm","0.82 -\n1.51mm","2mm"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240793-p18-t0","doc_id":"K240793","page_num":18,"bbox":[72.26,72.24,492.34,279.05],"n_rows":7,"n_cols":5,"columns":["Retro-Lithesis\n(L4/L5)","Sagittal","1.049mm","0.78 -\n1.42mm","2mm"],"rows":[["Retro-Lithesis\n(L4/L5)","Sagittal","1.049mm","0.78 -\n1.42mm","2mm"],["Retro-Lithesis\n(L3/L4)","Sagittal","1.01mm","0.81 -\n1.29mm","2mm"],["Retro-Lithesis\n(L2/L3)","Sagittal","1.05mm","0.77 -\n1.34mm","2mm"],["Retro-Lithesis\n(L1/L2)","Sagittal","1.08mm","0.83 -\n1.27mm","2mm"],["Lordotic Angle","Sagittal","2.99o","2.01 - 3.62o","6o"],["Protruding Disc\nMaterial","Axial","0.97 mm","0.72 -\n1.42mm","2mm"],["Dural Sac\nDiameter","Axial","1.3 mm","0.87 -\n1.39mm","2mm"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p5-t0","doc_id":"K240845","page_num":5,"bbox":[70.85,171.68,524.46,804.95],"n_rows":23,"n_cols":3,"columns":["1.","Submitter","3"],"rows":[["1.","Submitter","3"],["","",""],["2.","Device identification","3"],["","",""],["3.","Predicate device","3"],["","",""],["4.","Device description","3"],["","",""],["5.","Intended use/Indication for use","4"],["","",""],["6.","Substantial equivalence Discussion","5"],["","",""],["7.","Performance data","8"],["","",""],["a.","Software verification and validation testing","8"],["","",""],["b.","Bench Testing","8"],["","",""],["c.","Clinical data","14"],["","",""],["8.","CONCLUSION","15"],["","",""],["","Page","2/15"]],"caption_candidate":"1. Submitter 3","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240845-p6-t0","doc_id":"K240845","page_num":6,"bbox":[70.73,162.56,526.5,322.43],"n_rows":2,"n_cols":2,"columns":["Submitter","AZmed SAS\n6 rue Léonard de Vinci\n53000 Laval, France\nPhone: +33 6 43 31 51 38"],"rows":[["Submitter","AZmed SAS\n6 rue Léonard de Vinci\n53000 Laval, France\nPhone: +33 6 43 31 51 38"],["Contact personn","Christelle BAILLE\nHead of QARA\n6 rue Léonard de Vinci\n53000 Laval, France\nPhone: +33 6 43 31 51 38\nMail: christelle@azmed.co"]],"caption_candidate":"Submitted date: 2024-07-15","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p6-t1","doc_id":"K240845","page_num":6,"bbox":[65.55,377.37,541.3,468.5],"n_rows":2,"n_cols":6,"columns":["Name of\nthe Device","Common\nor Usual\nName","Regulatory\nsection","Classification","Product\nCode","Panel"],"rows":[["Name of\nthe Device","Common\nor Usual\nName","Regulatory\nsection","Classification","Product\nCode","Panel"],["Rayvolve","Rayvolve","21 CFR\n892.2090","Class II","QBS","90\n(Radiology)"]],"caption_candidate":"2. Device identification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p6-t2","doc_id":"K240845","page_num":6,"bbox":[65.55,537.78,517.67,611.5],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Product Name","510K Number"],"rows":[["Manufacturer","Product Name","510K Number"],["AZmed","Rayvolve","K220164"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p8-t0","doc_id":"K240845","page_num":8,"bbox":[70.67,273.11,553.3,769.5],"n_rows":12,"n_cols":4,"columns":["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],["Device Name","Rayvolve","Rayvolve","Same"],["Manufacturer","AZmed SAS","AZmed SAS","Same"],["510 (k) #","K220164","K240845","N/A"],["Regulation\nNumber","21 CFR 892.2090","21 CFR 892.2090","Same"],["Class","II","II","Same"],["Product Code","QBS","QBS","Same"],["Device Panel","Radiology","Radiology","Same"],["Level of\nConcern","Moderate","Moderate","Same"],["Intended use /\nIndications for\nuse","Rayvolve is a\ncomputer-assisted\ndetection and diagnosis\n(CAD) software device to\nassist radiologists and\nemergency physicians in\ndetecting fractures during\nthe review of radiographs\nof the musculoskeletal\nsystem.","Rayvolve is a\ncomputer-assisted\ndetection and diagnosis\n(CAD) software device to\nassist radiologists and\nemergency physicians in\ndetecting fractures during\nthe review of radiographs\nof the musculoskeletal\nsystem.","Same"],["Intended user","Radiologists and\nemergency physicians","Radiologists and\nemergency physicians","Same"],["Intended patient\npopulation","Adult ≥ 22 years old","Adult and pediatric\npopulation","The subject\ndevice is\nindicated for"]],"caption_candidate":"vice and the cited predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p9-t0","doc_id":"K240845","page_num":9,"bbox":[70.62,108.21,553.37,762.5],"n_rows":11,"n_cols":4,"columns":["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],["","","","pediatric\n(≥ 2 years) as\nwell as adult\npatients."],["Image modality","X-Ray","X-Ray","Same"],["Anatomic Areas\nof Interest","Ankle\nClavicle\nElbow\nForearm\nHip\nHumerus\nKnee\nPelvis\nShoulder\nTibia/fibula\nWrist\nHand\nFoot","Ankle\nClavicle\nElbow\nForearm\nHip\nHumerus\nKnee\nPelvis\nShoulder\nTibia/fibula\nWrist\nHand\nFoot","Same"],["Clinical findings","Fractures","Fractures","Same"],["Machine\nlearning\ntechnology","Supervised Deep\nlearning","Supervised Deep\nlearning","Same"],["Image source","DICOM node (e.g,\nimaging device,\nintermediate, DICOM\nnode, PACS system, etc)","DICOM node (e.g,\nimaging device,\nintermediate, DICOM\nnode, PACS system, etc)","Same"],["Image viewing","PACS system\nImage annotations\ntoggled on or of","PACS system\nImage annotations\ntoggled on or of","Same"],["Privacy","HIPAA Compliant","HIPAA Compliant","Same"],["Platform","On-premise, on cloud,\nsecure local processing\nand delivery of DICOM\nimages (eg:PACS)","On-premise, on cloud,\nsecure local processing\nand delivery of DICOM\nimages (eg:PACS)","Same"],["Electromagnetic\ncompatibility\nand electrical\nsafety","N/A, Rayvolve is a\nstandalone software and\nis not subject to","N/A, Rayvolve is a\nstandalone software and\nis not subject to","Same"]],"caption_candidate":"'•\"J i, AZ MED","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p10-t0","doc_id":"K240845","page_num":10,"bbox":[70.62,108.21,553.37,481.5],"n_rows":5,"n_cols":4,"columns":["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison to\npredicate device","Rayvolve - Predicate\n(K220164)","Rayvolve - Subject\ndevice 510(k) file","Comparison to\nthe predicate"],["","electromagnetic testing.\nTherefore no\nelectromagnetic\ncompatibility and\nelectrical safety is\nrequired.","electromagnetic testing.\nTherefore no\nelectromagnetic\ncompatibility and\nelectrical safety is\nrequired.",""],["Magnetic\nresonance","N/A, Rayvolve is a\nstandalone software and\nis not subject to magnetic\nresonance. Therefore no\nmagnetic testing is\nrequired.","N/A, Rayvolve is a\nstandalone software and\nis not subject to magnetic\nresonance. Therefore no\nmagnetic testing is\nrequired.","Same"],["Animal and/or\nCadever Testing","N/A, Rayvolve is a\nstandalone software","N/A, Rayvolve is a\nstandalone software","Same"],["Biocompatibility","N/A, Rayvolve is a\nstandalone software with\nno direct or indirect\npatient or user contacting\ncomponents. Therefore\nno biocompatibility is\nrequired.","N/A, Rayvolve is a\nstandalone software with\nno direct or indirect\npatient or user contacting\ncomponents. Therefore\nno biocompatibility is\nrequired.","Same"]],"caption_candidate":"'•\"J i, AZ MED","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p12-t0","doc_id":"K240845","page_num":12,"bbox":[101.11,147.65,492.86,211.5],"n_rows":2,"n_cols":2,"columns":["","AUC (Bootstrapped CI)"],"rows":[["","AUC (Bootstrapped CI)"],["All","0.9399\n(0.9330; 0.9470)"]],"caption_candidate":"with high level performances :","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p12-t1","doc_id":"K240845","page_num":12,"bbox":[101.11,260.38,492.86,611.5],"n_rows":14,"n_cols":2,"columns":["Anatomic Area","AUC (Bootstrapped CI)"],"rows":[["Anatomic Area","AUC (Bootstrapped CI)"],["Ankle","0.9489 (0.9257; 0.9694)"],["Clavicle","0.9263 (0.8846; 0.9645)"],["Elbow","0.9308 (0.8932; 0.9629)"],["Foreram","0.936 (0.9012; 0.9666)"],["Humerus","0.9568 (0.9268; 0.9818)"],["Hip","0.947 (0.922; 0.9681)"],["Knee","0.9624 (0.9472; 0.9756)"],["Pelvis","0.9263 (0.8947; 0.9559)"],["Shoulder","0.9372 (0.9037; 0.9664)"],["Tibia/Fibula","0.9616 (0.9362; 0.9824)"],["Wrist","0.9484 (0.9258; 0.9688)"],["Hand","0.9485 (0.9306; 0.9654)"],["Foot","0.9404 (0.9211; 0.9581)"]],"caption_candidate":"Rayvolve performance on all radiographs","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p13-t0","doc_id":"K240845","page_num":13,"bbox":[116.55,108.25,477.42,357.5],"n_rows":6,"n_cols":2,"columns":["Ethnicity","AUC (Bootstrapped CI)"],"rows":[["Ethnicity","AUC (Bootstrapped CI)"],["Caucasian","0.944 (0.9331; 0.9548)"],["Hispanic","0.948 (0.9362; 0.9589)"],["African-American","0.9542 (0.9335; 0.9724)"],["Asian","0.9272 (0.8932; 0.9588)"],["Others","0.9308 (0.9087; 0.9503)"]],"caption_candidate":"'•\"J i, AZ MED","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p14-t0","doc_id":"K240845","page_num":14,"bbox":[65.53,163.41,518.55,228.5],"n_rows":2,"n_cols":2,"columns":["","AUC (Bootstrapped CI)"],"rows":[["","AUC (Bootstrapped CI)"],["All","0.98607\n(0.98104; 0.99058)"]],"caption_candidate":"subgroups:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p14-t1","doc_id":"K240845","page_num":14,"bbox":[65.53,256.68,518.55,607.5],"n_rows":14,"n_cols":2,"columns":["Anatomic Area","AUC (Bootstrapped CI)"],"rows":[["Anatomic Area","AUC (Bootstrapped CI)"],["Ankle","0.99137 (0.98374; 0.99727)"],["Clavicle","0.97806 (0.94626; 0.99761)"],["Elbow","0.9964 (0.99059; 1.0)"],["Forearm","0.9953 (0.98909; 0.99937)"],["Humerus","0.9955 (0.98960; 0.99943)"],["Hip","0.95821 (0.93239; 0.98014)"],["Knee","0.97742 (0.95084; 0.99592)"],["Pelvis","0.97676 (0.95241; 0.99638)"],["Shoulder","0.97814 (0.94147; 0.99958)"],["Tibia/Fibula","0.98285 (0.95925; 0.9978)"],["Wrist","0.99567 (0.99126; 0.99897)"],["Hand","0.99552 (0.99074; 0.99898)"],["Foot","0.99162 (0.98238; 0.99823)"]],"caption_candidate":"Rayvolve performance on all radiographs","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p15-t0","doc_id":"K240845","page_num":15,"bbox":[65.55,463.41,561.4,760.5],"n_rows":8,"n_cols":3,"columns":["I\nAnatomic\nArea","AUC\n(Bootstrapped CI)",""],"rows":[["I\nAnatomic\nArea","AUC\n(Bootstrapped CI)",""],["","Predicate","Re-trained"],["'\nAnkle","0.99137 (0.98374; 0.99727)","0.99732 (0.98969; 1)"],["Clavicle","0.97806 (0.94626; 0.99761)","0.98393 (0.95118; 0.99949)"],["Elbow","0.9964 (0.99059; 1.0)","0.99441 (0.98761; 0.99701)"],["Foreram","0.9953 (0.98909; 0.99937)","0.9943 (0.98809; 0.99737)\n-"],["Humerus","0.9955 (0.98960; 0.99943)","0.99351 (0.98662; 0.99644)"],["Hip","0.95821 (0.93239; 0.98014)","0.95725 (0.93236; 0.97918)"]],"caption_candidate":"compared to the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240845-p16-t0","doc_id":"K240845","page_num":16,"bbox":[65.53,108.25,561.42,468.5],"n_rows":10,"n_cols":3,"columns":["Anatomic\nArea","AUC\n(Bootstrapped CI)",""],"rows":[["Anatomic\nArea","AUC\n(Bootstrapped CI)",""],["","Predicate","Re-trained"],["Knee","0.97742 (0.95084; 0.99592)","0.9784 (0.95182; 0.9969)"],["Pelvis","0.97676 (0.95241; 0.99638)","0.97774 (0.95339; 0.99836)"],["Shoulder","0.97814 (0.94147; 0.99958)","0.98303 (0.94542; 1)"],["Tibia/Fibula","0.98285 (0.95925; 0.9978)","0.98776 (0.96512; 0.99872)"],["Wrist","0.99567 (0.99126; 0.99897)","0.99567 (0.99126; 0.99797)"],["Hand","0.99552 (0.99074; 0.99898)","0.99452 (0.98875; 0.99698)"],["Foot","0.99162 (0.98238; 0.99823)","0.99757 (0.98735; 1)"],["Total","0.98607 (0.98104; 0.99058)","0.98781 (0.98247; 0.99048)"]],"caption_candidate":"'•\"J i, AZ MED","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p5-t0","doc_id":"K240850","page_num":5,"bbox":[251.37,470.71,566.1,601.18],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ*","",""]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p8-t0","doc_id":"K240850","page_num":8,"bbox":[35.29,169.32,560.21,689.0],"n_rows":21,"n_cols":6,"columns":["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],"rows":[["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],["","","EPIQ Series Diagnostic","","",""],["","Ultrasound System","","","Application",""],["","","Ultrasound System","","",""],["Feature","Features: SVS and","","K212466","Feature: LVivo SG","Comparison"],["","","K233788","","",""],["","SWM","","Reference Device","K161382",""],["","","Predicate Device","","",""],["","Proposed Device","","","Reference Device",""],["","","","","",""],["","Abdominal, Cardiac\nAdult, Cardiac other\n(Fetal), Cardiac\nPediatric, Cerebral\nVascular, Cephalic\n(Adult), Cephalic\n(Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative\n(Vascular),\nIntraoperative\n(Cardiac), intra-luminal,\nintra-cardiac echo,\nMusculoskeletal\n(Conventional),\nMusculoskeletal\n(Superficial),\nOphthalmic, Other:\nUrology, Pediatric,\nPeripheral Vessel,\nSmall Organ (Breast,\nThyroid, Testicle),\nTransesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","Abdominal, Cardiac\nAdult, Cardiac other\n(Fetal), Cardiac\nPediatric, Cerebral\nVascular, Cephalic\n(Adult), Cephalic\n(Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative\n(Vascular),\nIntraoperative\n(Cardiac), intra-luminal,\nintra-cardiac echo,\nMusculoskeletal\n(Conventional),\nMusculoskeletal\n(Superficial),\nOphthalmic, Other:\nUrology, Pediatric,\nPeripheral Vessel,\nSmall Organ (Breast,\nThyroid, Testicle),\nTransesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected disease.","LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected disease.","Identical to predicate"],["Indications for","","","","",""],["Use","","","","",""],["","","","","",""],["","Trained healthcare\nprofessionals\nIntended for\nsonographers,\nphysicians, and\nbiomedical engineers\nwho operate and\nmaintain your product.\nBefore use of the\nsystem and user\ninformation, the user\nmust be familiar with\nultrasound techniques.\nSonography training\nand clinical procedures\nare not included in the\nUser Manual or with the\nEPIQ Series Diagnostic\nUltrasound System.","Trained healthcare\nprofessionals\nIntended for\nsonographers,\nphysicians, and\nbiomedical engineers\nwho operate and\nmaintain your product.\nBefore use of the\nsystem and user\ninformation, the user\nmust be familiar with\nultrasound techniques.\nSonography training\nand clinical procedures\nare not included in the\nUser Manual or with the\nEPIQ Series Diagnostic\nUltrasound System.","Trained healthcare\nprofessionals","Trained healthcare\nprofessionals","Identical to predicate"],["Intended Users","","","","",""],["","","","","",""],["","Clinics, hospitals, and\nclinical point-of-care for\ndiagnosis of patients.","Clinics, hospitals, and\nclinical point-of-care for\ndiagnosis of patients.","Professional healthcare\nenvironments","Professional healthcare\nenvironments","Identical to predicate"],["Intended User","","","","",""],["Environment","","","","",""],["","","","","",""]],"caption_candidate":"Table 1: Comparison to Predicate - EPIQ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p9-t0","doc_id":"K240850","page_num":9,"bbox":[35.31,67.3,560.24,708.68],"n_rows":55,"n_cols":6,"columns":["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],"rows":[["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],["","","EPIQ Series Diagnostic","","",""],["","Ultrasound System","","","Application",""],["","","Ultrasound System","","",""],["Feature","Features: SVS and","","K212466","Feature: LVivo SG","Comparison"],["","","K233788","","",""],["","SWM","","Reference Device","K161382",""],["","","Predicate Device","","",""],["","Proposed Device","","","Reference Device",""],["","","","","",""],["","Class II","Class II","Class II","Class II","Identical to predicate"],["USA FDA","","","","",""],["Classification","","","","",""],["","","","","",""],["","IYN","IYN","QIH","LLZ","Identical to predicate"],["Primary","","","","",""],["Product Code","","","","",""],["","","","","",""],["","System, Imaging,\nPulsed Doppler,\nUltrasonic","System, Imaging,\nPulsed Doppler,\nUltrasonic","Automated Radiological\nImage\nProcessing Software","Medical image\nmanagement and\nprocessing system.","Identical to predicate"],["Primary","","","","",""],["Regulation","","","","",""],["Name","","","","",""],["","","","","",""],["","21 CFR 892.1550","21 CFR 892.1550","21 CFR 892.2050","21 CFR 892.2050","Identical to predicate"],["Primary","","","","",""],["Regulation","","","","",""],["Number","","","","",""],["","","","","",""],["","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","N/A","N/A","Identical to predicate"],["Secondary","","","","",""],["Product Codes","","","","",""],["","","","","",""],["","Diagnostic ultrasonic\ntransducer\nUltrasonic pulsed echo\nimaging\nsystem\nDiagnostic\nintravascular catheter\nAutomated Radiological\nImage\nProcessing Software","Diagnostic ultrasonic\ntransducer\nUltrasonic pulsed echo\nimaging\nsystem\nDiagnostic\nintravascular catheter\nAutomated Radiological\nImage\nProcessing Software","N/A","N/A","Identical to predicate"],["Secondary","","","","",""],["Regulation","","","","",""],["Name","","","","",""],["","","","","",""],["","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","N/A","N/A","Identical to predicate"],["Secondary","","","","",""],["Regulation","","","","",""],["Number","","","","",""],["","","","","",""],["Reusable-","Yes","Yes","No, software-only","No, software-only","Identical to predicate"],["Systems and","","","","",""],["Transducers","","","","",""],["","Limited (≤ 24 hours)","Limited (≤ 24 hours)","N/A, software-only","N/A, software-only","Identical to predicate"],["Duration of use","","","","",""],["","","","","",""],["","Track 3","Track 3","N/A, software-only","N/A, software-only","Identical to predicate"],["Device Track","","","","",""],["","","","","",""],["","Smart View Select is an\nautomated software\nfeature that assists the\nuser in selection of\nimages for analysis\nwith the existing Philips\nAutoStrain LV or 2D\nAuto LV application in\nAdult Echo\nTransthoracic (TTE)\nexamination.\nThe SWM software\nautomatically evaluates\nthe segmental\n(regional) function of\nthe left ventricle (LV)\nfrom adult TTE echo\nexaminations.\nNote: Per FDA\nGuidance Technical","The predicate EPIQ\nSeries Diagnostic\nUltrasound System\ndoes not currently have\na dedicated software\napplication containing\nthe functionality\nintroduced in the\nsubject submission for\n(1) automatic selection\nof 4CH,2CH, and 3CH\nviews for left ventricle\n(LV) analysis or (2)\n(semi-) automated\nsegmental wall motion\nevaluation of the left\nventricle (LV).","The LVivoSeamless\nsoftware is a\nstandalone application\nthat extends the LVivo\nPlatform and runs\noffline on a server. The\nsystem accepts echo\nexamination that are\nsent from the US\ndevice using DICOM\ncommunication. The\nexaminations contain\nclips in DICOM format.\nThe LVivoSeamless\nscans the entire\nexamination and\nselects automatically\n4CH,2CH and 3CH\nviews for EF and GLS\nevaluation and runs the\nLVivoEF and the\nLVivoStrain. The","The LVivoSG is a\ndecision support\nsystem (software) for\nautomated segmental\nwall motion evaluation\nof the left ventricle (LV).\nThe LVivoSG is based\non a proprietary\nalgorithm for LV\nregional motion\nparameters calculation\nand wall motion\nclassification.\nThe LVivoSG uses the\nLVivo platform to detect\nthe LV inner borders\n(endocard) from which\nthe wall motion\nparameters are\ncalculated. As part of\nthe LVivoSG\ndevelopment, the LVivo","The subject EPIQ Series\nDiagnostic Ultrasound\nSystem integrates the LVivo\nSeamless algorithm of the\nK212466 reference device\nas “Smart View Select” and\nthe LVivo SWM module of\nthe LVivo SG K161382\nreference device as\n“Segmental Wall Motion”.\nMinor changes have been\nmade to the reference\nLVivo Seamless and LVivo\nSG software applications in\nthe subject SVS and SWM\napplications, as described\nbelow."],["Application","","","","",""],["Description","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p10-t0","doc_id":"K240850","page_num":10,"bbox":[35.32,67.3,560.22,713.72],"n_rows":31,"n_cols":6,"columns":["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],"rows":[["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],["","","EPIQ Series Diagnostic","","",""],["","Ultrasound System","","","Application",""],["","","Ultrasound System","","",""],["Feature","Features: SVS and","","K212466","Feature: LVivo SG","Comparison"],["","","K233788","","",""],["","SWM","","Reference Device","K161382",""],["","","Predicate Device","","",""],["","Proposed Device","","","Reference Device",""],["","","","","",""],["","Performance\nAssessment of\nQuantitative Imaging in\nRadiological Device\nPremarket\nSubmissions, the SWM\nsoftware is a semi-\nautomated quantitative\nimaging algorithm, as\nusers are generally\nexpected to review and\nconcur with the\ninitialization and\ngenerated results. The\nusers can also edit\nalgorithm generated\nsegmental wall motion\nscores for individual\nsegments based on\ntheir clinical expertise.","","results are sent back\nusing DICOM\ncommunication to the\nPACS server and\nbecome part of the\nstudy. The clinician that\nreviews the\nexaminations at the\nPACS workstation will\nbe able view the output\nof the LVivoEF and\nLVivoStrain as part of\nthe study review.","platform supports also\nedge detection and\ntracking in additional\nplane, the apical long\n(3CH). The LVivoSG\nprovides fully\nautomated\nmeasurements of the\nregional left ventricular\nsystolic function from\nthree apical views the\nfour chamber (4CH),\ntwo chamber (2CH)\nand long (3CH).",""],["","LVivo Seamless AI\nneural network","Not applicable – does\nnot contain functionality\nfor optimal triplet\nselection","LVivo Seamless AI\nneural network","Not applicable – does\nnot contain functionality\nfor optimal triplet\nselection","The subject SVS software\napplication utilizes the\nidentical, unchanged deep\nneural network for view\nidentification and optimal\ntriplet (A4C, A2C, and A3C)\nselection for subsequent LV\nanalysis"],["Deep Neural","","","","",""],["Network utilized","","","","",""],["for optimal","","","","",""],["triplet selection","","","","",""],["","","","","",""],["","Yes – the subject SVS\nsoftware application\nuses an additional\nheuristic logic step, after\nthe deep neural network\nidentifies the views and\ndetermines a list of 3 clip\ncombinations (triplets),\nto preferentially select\ntriplets of shallower scan\ndepths, provided the\ndepth exceeds 10cm\nand the variation of\ndepths of each clips is\n1cm or less","Not applicable – does\nnot contain functionality\nfor optimal triplet\nselection","Not applicable – scan\ndepth is not considered\nin the selection of the\noptimal triplets for the\nuser","Not applicable – does\nnot contain functionality\nfor optimal triplet\nselection","The subject SVS software\napplication adds an\nadditional heuristic logic\nstep for preferentially\nselecting certain scan\ndepths from the reference\nLVivo Seamless. The\nNeural Network of the\nreference device is\nunchanged, as described\nabove. Performance testing\nhas demonstrated very\nstrong correlation between\nthe LV analysis outputs\n(EF, GLS) from clips\nselected by the subject SVS\nsoftware application and\nclips manually selected by\nclinical users. Therefore,\nthe additional heuristic logic\nstep of the subject SVS\nsoftware does not raise new\nor different questions of\nsafety or effectiveness in\ncomparison to the reference\ndevice K212466."],["Scan depth","","","","",""],["considered for","","","","",""],["optimal triplet","","","","",""],["selection?","","","","",""],["","","","","",""],["","Primary – from K161382\nSecondary – from\ncleared AutoStrain LV\n(K190913)","Not applicable – does\nnot contain functionality\nfor segmental wall\nmotion","Not applicable – this\napplication does not\ncontain functionality for\nsegmental wall motion","From K161382","Subject device\npreferentially utilizes\nidentical border initialization\nalgorithm as reference\ndevice K161382.\nIf the reference device’s\nalgorithm is unsuccessful in\nthe subject SWM, it will use"],["Border","","","","",""],["initialization","","","","",""],["algorithm(s)","","","","",""],["utilized for","","","","",""],["segmental wall","","","","",""],["motion","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p11-t0","doc_id":"K240850","page_num":11,"bbox":[35.28,67.3,560.2,519.53],"n_rows":15,"n_cols":6,"columns":["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],"rows":[["","EPIQ Series Diagnostic","","LVivo Seamless","LVivo Software",""],["","","EPIQ Series Diagnostic","","",""],["","Ultrasound System","","","Application",""],["","","Ultrasound System","","",""],["Feature","Features: SVS and","","K212466","Feature: LVivo SG","Comparison"],["","","K233788","","",""],["","SWM","","Reference Device","K161382",""],["","","Predicate Device","","",""],["","Proposed Device","","","Reference Device",""],["","","","","",""],["","","","","","the border initialization of\nthe cleared AutoStrain LV\n(K190913) as a back-up.\nPerformance testing has\ndemonstrated very strong\ncorrelation between the\nSWM scoring of the subject\nsoftware application\ncompared to the scoring of\nthe reference device on the\nsame clips. Therefore, there\nare no new or increased\nrisks for the use of the\nAutoStrain LV border\ninitialization in the subject\nSWM software application\nas a back-up."],["","Users manually edit\nscores using a drop-\ndown selection","Not applicable – does\nnot contain functionality\nfor segmental wall\nmotion","Not applicable – this\napplication does not\ncontain functionality for\nsegmental wall motion","Users must manually\nedit the borders to\nattempt to edit scores","In the cleared LVivo SG,\nusers must manually adjust\nthe chamber borders to\ninfluence the SWM scores.\nIn the subject SWM on\nVM11, users may manually\nselect different SWM scores\nfor each segment using a\ndrop-down menu. Any\nscores which are manually\nchanged from those\ncalculated by the software\napplication will be indicated\nby an asterisk (*). This\nchange in editing does not\nintroduce new risks\nbecause it is providing a\nsimpler way for the user to\nedit their segmental wall\nmotion score(s) – instead of\nhaving to edit the border\ncontours to influence the\nSWM score as on the\ncleared LVivo SG, user can\ndirectly edit each segment’s\nscore with the drop-down."],["SWM scoring","","","","",""],["adjustment","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p12-t0","doc_id":"K240850","page_num":12,"bbox":[35.31,87.83,561.79,709.14],"n_rows":42,"n_cols":5,"columns":["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],"rows":[["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],["","Ultrasound System","Ultrasound System","Feature: LVivo SG",""],["Feature","Feature: SWM","K233788","K161382","Comparison"],["","Proposed Device","Predicate Device","Reference Device",""],["","Abdominal, Cardiac Adult,\nCardiac Other (Fetal), Cardiac\nPediatric, Cerebral Vascular,\nCephalic (Adult),\nCephalic (Neonatal),\nFetal/Obstetric, Gynecological,\nIntraoperative (Vascular),\nIntraoperative (Cardiac),\nMusculoskeletal (Conventional),\nMusculoskeletal (Superficial),\nOther: Urology, Pediatric,\nPeripheral Vessel,\nSmall Organ (Breast, Thyroid,\nTesticle), Transesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","Abdominal, Cardiac Adult,\nCardiac Other (Fetal), Cardiac\nPediatric, Cerebral Vascular,\nCephalic (Adult),\nCephalic (Neonatal),\nFetal/Obstetric, Gynecological,\nIntraoperative (Vascular),\nIntraoperative (Cardiac),\nMusculoskeletal (Conventional),\nMusculoskeletal (Superficial),\nOther: Urology, Pediatric,\nPeripheral Vessel,\nSmall Organ (Breast, Thyroid,\nTesticle), Transesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","LVivo platform is intended for\nnon-invasive processing of\nultrasound images to detect,\nmeasure, and calculate relevant\nmedical parameters of\nstructures and function of\npatients with suspected\ndisease.","Identical to predicate"],["Indications for","","","",""],["Use","","","",""],["","","","",""],["","Trained healthcare\nprofessionals\nIntended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the Affiniti Series\nDiagnostic Ultrasound System.","Trained healthcare\nprofessionals\nIntended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the Affiniti Series\nDiagnostic Ultrasound System.","Trained healthcare\nprofessionals","Identical to predicate"],["Intended Users","","","",""],["","","","",""],["","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Professional healthcare\nenvironments","Identical to predicate"],["Intended User","","","",""],["Environment","","","",""],["","","","",""],["","Class II","Class II","Class II","Identical to predicate"],["USA FDA","","","",""],["Classification","","","",""],["","","","",""],["","IYN","IYN","LLZ","Identical to predicate"],["Primary","","","",""],["Product Code","","","",""],["","","","",""],["","System, Imaging, Pulsed\nDoppler, Ultrasonic","System, Imaging, Pulsed\nDoppler, Ultrasonic","Medical image management\nand processing system.","Identical to predicate"],["Primary","","","",""],["Regulation","","","",""],["Name","","","",""],["","","","",""],["","21 CFR 892.1550","21 CFR 892.1550","21 CFR 892.2050","Identical to predicate"],["Primary","","","",""],["Regulation","","","",""],["Number","","","",""],["","","","",""],["","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","N/A","Identical to predicate"],["Secondary","","","",""],["Product Codes","","","",""],["","","","",""],["","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular\ncatheter","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular\ncatheter","N/A","Identical to predicate"],["Secondary","","","",""],["Regulation","","","",""],["Name","","","",""],["","","","",""]],"caption_candidate":"Table 2: Comparison to Predicate - Affiniti","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p13-t0","doc_id":"K240850","page_num":13,"bbox":[35.31,67.48,561.78,708.79],"n_rows":31,"n_cols":5,"columns":["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],"rows":[["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],["","Ultrasound System","Ultrasound System","Feature: LVivo SG",""],["Feature","Feature: SWM","K233788","K161382","Comparison"],["","Proposed Device","Predicate Device","Reference Device",""],["","Automated Radiological Image\nProcessing Software","Automated Radiological Image\nProcessing Software","",""],["","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","N/A","Identical to predicate"],["Secondary","","","",""],["Regulation","","","",""],["Number","","","",""],["","","","",""],["Reusable-","Yes","Yes","No, software-only","Identical to predicate"],["Systems and","","","",""],["Transducers","","","",""],["","Limited (≤ 24 hours)","Limited (≤ 24 hours)","N/A, software-only","Identical to predicate"],["Duration of use","","","",""],["","","","",""],["","Track 3","Track 3","N/A, software-only","Identical to predicate"],["Device Track","","","",""],["","","","",""],["","The SWM software\nautomatically evaluates the\nsegmental (regional) function of\nthe left ventricle (LV) from adult\nTTE echo examinations.\nNote: Per FDA Guidance\nTechnical Performance\nAssessment of Quantitative\nImaging in Radiological Device\nPremarket Submissions, the\nSWM software is a semi-\nautomated quantitative imaging\nalgorithm, as users are\ngenerally expected to review\nand concur with the initialization\nand generated results. The\nusers can also edit algorithm\ngenerated segmental wall\nmotion scores for individual\nsegments based on their clinical\nexpertise.","The predicate Affiniti Series\nDiagnostic Ultrasound System\ndoes not currently have a\ndedicated software application\ncontaining the functionality\nintroduced in the subject\nsubmission for (semi-)\nautomated segmental wall\nmotion evaluation of the left\nventricle (LV).","The LVivoSG is a decision\nsupport system (software) for\nautomated segmental wall\nmotion evaluation of the left\nventricle (LV). The LVivoSG is\nbased on a proprietary\nalgorithm for LV regional motion\nparameters calculation and wall\nmotion classification.\nThe LVivoSG uses the LVivo\nplatform to detect the LV inner\nborders (endocard) from which\nthe wall motion parameters are\ncalculated. As part of the\nLVivoSG development, the\nLVivo platform supports also\nedge detection and tracking in\nadditional plane, the apical long\n(3CH). The LVivoSG provides\nfully automated measurements\nof the regional left ventricular\nsystolic function from three\napical views the four chamber\n(4CH), two chamber (2CH) and\nlong (3CH).","The subject Affiniti Series\nDiagnostic Ultrasound\nSystem integrates the LVivo\nSWM module of the LVivo\nSG K161382 reference\ndevice as “Segmental Wall\nMotion”. The subject SWM\nsoftware application utilizes\nthe border initialization of\nthe cleared AutoStrain LV\nsoftware in the event that\nthe border initialization\nalgorithm from LVivo SG is\nunsuccessful. Otherwise,\nthere is no difference\nbetween the subject SWM\nsoftware application and the\nreference LVivo SG’s SWM\nmodule and no changes\nhave been made to its\nalgorithms."],["Application","","","",""],["Description","","","",""],["","","","",""],["","Primary – from K161382\nSecondary – from cleared\nAutoStrain LV (K190913)","Not applicable – does not\ncontain functionality for\nsegmental wall motion","From K161382","Subject device\npreferentially utilizes\nidentical border initialization\nalgorithm as reference\ndevice K161382.\nIf the reference device’s\nalgorithm is unsuccessful in\nthe subject SWM, it will use\nthe border initialization of\nthe cleared AutoStrain LV\n(K190913) as a back-up.\nPerformance testing has\ndemonstrated very strong\ncorrelation between the\nSWM scoring of the subject\nsoftware application\ncompared to the scoring of\nthe reference device on the\nsame clips. Therefore, there\nare no new or increased\nrisks for the use of the\nAutoStrain LV border\ninitialization in the subject"],["Border","","","",""],["initialization","","","",""],["algorithm(s)","","","",""],["utilized for","","","",""],["segmental wall","","","",""],["motion","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240850-p14-t0","doc_id":"K240850","page_num":14,"bbox":[35.28,67.48,561.73,387.27],"n_rows":9,"n_cols":5,"columns":["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],"rows":[["","Affiniti Series Diagnostic","Affiniti Series Diagnostic","LVivo Software Application",""],["","Ultrasound System","Ultrasound System","Feature: LVivo SG",""],["Feature","Feature: SWM","K233788","K161382","Comparison"],["","Proposed Device","Predicate Device","Reference Device",""],["","","","","SWM software application\nas a back-up."],["","Users manually edit scores\nusing a drop-down selection","Not applicable – does not\ncontain functionality for\nsegmental wall motion","Users must manually edit the\nborders to attempt to edit scores","In the cleared LVivo SG,\nusers must manually adjust\nthe chamber borders to\ninfluence the SWM scores.\nIn the subject SWM on\nVM11, users may manually\nselect different SWM scores\nfor each segment using a\ndrop-down menu. Any\nscores which are manually\nchanged from those\ncalculated by the software\napplication will be indicated\nby an asterisk (*). This\nchange in editing does not\nintroduce new risks\nbecause it is providing a\nsimpler way for the user to\nedit their segmental wall\nmotion score(s) – instead of\nhaving to edit the border\ncontours to influence the\nSWM score as on the\ncleared LVivo SG, user can\ndirectly edit each segment’s\nscore with the drop-down."],["SWM scoring","","","",""],["adjustment","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p4-t0","doc_id":"K240926","page_num":4,"bbox":[89.57,638.51,514.32,664.5],"n_rows":2,"n_cols":3,"columns":["510(k)","Product Name","Clearance Date"],"rows":[["510(k)","Product Name","Clearance Date"],["K222767","PeekMed web","December 2022"]],"caption_candidate":"3.1 PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p7-t0","doc_id":"K240926","page_num":7,"bbox":[68.87,143.89,743.96,486.5],"n_rows":6,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Product Code","LLZ, QIH","LLZ, QIH","Yes","---"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Yes","---"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","---"],["Intended use","PeekMed web is a system\ndesigned to help healthcare\nprofessionals carry out\npre-operative planning for several\nsurgical procedures, based on\ntheir imported patients’ imaging\nstudies. Experience in usage and\na clinical assessment is necessary\nfor the proper use of the system in\nthe revision and approval of the\noutput of the planning. The\nmulti-platform system works with a\ndatabase of digital representations\nrelated to surgical materials\nsupplied by their manufacturers.","PeekMed web is a system\ndesigned to help healthcare\nprofessionals carry out\npre-operative planning for several\nsurgical procedures, based on\ntheir imported patients’ imaging\nstudies. Experience in usage and\na clinical assessment is necessary\nfor the proper use of the system in\nthe revision and approval of the\noutput of the planning. The\nmulti-platform system works with a\ndatabase of digital representations\nrelated to surgical materials\nsupplied by their manufacturers.","Yes","---"],["Indications for","This medical device consists of a","This medical device consists of a","Yes","---"]],"caption_candidate":"Table 1: Summary of Predicate and Subject Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p8-t0","doc_id":"K240926","page_num":8,"bbox":[68.84,119.27,743.97,490.54],"n_rows":4,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["use","decision support tool for qualified\nhealthcare professionals to quickly\nand efficiently perform the\npre-operative planning for several\nsurgical procedures, using medical\nimaging with the additional\ncapability of planning the 2D or 3D\nenvironment. The system is\ndesigned for the medical\nspecialties within surgery and no\nspecific use environment is\nmandatory, whereas the typical\nuse environment is a room with a\ncomputer. The patient target group\nis adult patients who have an\ninjury or disability diagnosed\npreviously. There are no other\nconsiderations for the intended\npatient population.","decision support tool for qualified\nhealthcare professionals to quickly\nand efficiently perform the\npre-operative planning for several\nsurgical procedures, using medical\nimaging with the additional\ncapability of planning the 2D or 3D\nenvironment. The system is\ndesigned for the medical\nspecialties within surgery and no\nspecific use environment is\nmandatory, whereas the typical\nuse environment is a room with a\ncomputer. The patient target group\nis adult patients who have an\ninjury or disability diagnosed\npreviously. There are no other\nconsiderations for the intended\npatient population.","",""],["Contraindications","No contraindications specific to\nthis device.","No contraindications specific to\nthis device.","Yes","---"],["Clinical purpose","PeekMed web allows the surgeon\nto perform orthopedic pre-surgical\nplanning efficiently in the","PeekMed web allows the surgeon\nto perform orthopedic pre-surgical\nplanning efficiently in the","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p9-t0","doc_id":"K240926","page_num":9,"bbox":[68.84,119.27,743.97,477.5],"n_rows":4,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","musculoskeletal system (e.g., Hip\nprocedures, Knee procedures)","musculoskeletal system (e.g., Hip\nprocedures, Knee procedures)","",""],["Anatomical\nregions","PeekMed web allows the surgeon\nto perform the pre-surgical\nplanning efficiently in the following\nanatomical regions:\n- Hip\n- Knee\n- Upper limb","PeekMed web allows the surgeon\nto perform the pre-surgical\nplanning efficiently in the following\nanatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes\nThe subject\ndevice also\nallows the\nplanning of\northopedic\nsurgery in the\nfoot region.","The subject device allows for the surgery\nplanning on one more anatomical region\n(foot), this does not constitute a new\nintended purpose nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and release processes are\nexactly the same between the devices.\nThe new variants of the ML model for foot\nare considered in this Traditional 510(k)\nand were developed according to what is\ndefined for each ML model development\nand validation according to their intended\nrequirements and performance.\nThis change improves the medical device\nin a way that the user can benefit from the\nexisting features on one more anatomical\nregion. This change does not interfere\nwith or create an effect on other\nanatomical regions covered by the device."],["Patient Population","Adults","Adults","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p10-t0","doc_id":"K240926","page_num":10,"bbox":[68.9,119.27,743.97,485.5],"n_rows":8,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["End users","Healthcare Professionals","Healthcare Professionals","Yes","---"],["Device availability","Software is cloud-based (not\ninstallable) and can be displayed\non any personal device or\nworkstation that can run on a web\nbrowser","Software is cloud-based (not\ninstallable) and can be displayed\non any personal device or\nworkstation that can run on a web\nbrowser","Yes","---"],["Software\nArchitecture","Distributed system (cloud-based).\nThis distributed system is a\ncombination of software modules\nplaced on servers that are able to\ncommunicate with each other.","Distributed system (cloud-based).\nThis distributed system is a\ncombination of software modules\nplaced on servers that are able to\ncommunicate with each other.","Yes","---"],["Workflow","The workflow is as follows: Import\ncase images, configure images,\nidentify the case, pre-surgical\nplanning, and export the case. The\nworkflow chart is in Annex 2.","The workflow is as follows: Import\ncase images, configure images,\nidentify the case, pre-surgical\nplanning, and export the case. The\nworkflow chart is in Annex 2.","Yes","---"],["Internet\nconnection","Required","Required","Yes","---"],["Images source","Receives medical images from\nvarious sources","Receives medical images from\nvarious sources","Yes","---"],["Data processing","The software processes data to\nprovide an overlap and","The software processes data to\nprovide an overlap and","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p11-t0","doc_id":"K240926","page_num":11,"bbox":[68.9,119.27,743.97,495.5],"n_rows":10,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","dimensioning of digital\nrepresentations of the prosthetic\nmaterial","dimensioning of digital\nrepresentations of the prosthetic\nmaterial","",""],["Digital overlap of\ntemplates","Allows the overlap of models and\nthe intersection of the models","Allows the overlap of models and\nthe intersection of the models","Yes","---"],["Interactive model\npositioning","Yes","Yes","Yes","---"],["Interactive model\ndimensioning","Yes","Yes","Yes","---"],["Model rotation","Yes","Yes","Yes","---"],["Support for digital\nprosthetic\nmaterials\nprovided by the\nmanufacturers","Yes","Yes","Yes","---"],["Pre-surgical\nplanning","Yes","Yes","Yes","---"],["Type of\npre-surgical\nplanning","Automatic or Manual","Automatic or Manual","Yes","---"],["Contact with the\npatient","No","No","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p12-t0","doc_id":"K240926","page_num":12,"bbox":[68.9,119.27,743.97,482.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Control of life\nsupporting\ndevices","No","No","Yes","---"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","Yes","---"],["Ability to add\nadditional\nmodules when\navailable","Yes","Yes","Yes","---"],["Automatic bone\nsegmentation","Yes","Yes","Yes\nThe updated\nML model\nvariants were\ncompared\nagainst the\nacceptance\ncriteria and,\ntherefore\nconfirmed to\nbe an\nimprovement","The subject device includes new and\nupdated ML model variants for the\npurpose of bone segmentation. These ML\nmodel variants were developed and\nvalidated using the same methods and\nacceptance criteria and deemed as\nCompliant. The updated model variants\nwere also compared against the\nacceptance criteria, therefore confirmed to\nbe an improvement over the last ML\nmodel variants versions."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240926-p13-t0","doc_id":"K240926","page_num":13,"bbox":[68.9,119.27,743.97,492.0],"n_rows":4,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K222767","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","","","over the last\nML model\nvariants\nversions.",""],["Configuration\nWindows for\nOblique Planes\nfunctionality","Yes","Yes","","---"],["Type of\nlandmarking","Automatic or Manual","Automatic or Manual","Yes\nThe updated\nML model\nvariants were\ncompared\nagainst the\nacceptance\ncriteria and,\ntherefore\nconfirmed to\nbe an\nimprovement\nover the last\nML model\nvariants\nversions.","The subject device includes new and\nupdated ML model variants for the\npurpose of landmarking. These ML model\nvariants were developed and validated\nusing the same methods and acceptance\ncriteria and deemed as Compliant. The\nupdated model variants were also\ncompared against the acceptance criteria,\ntherefore confirmed to be an improvement\nover the last ML model variants versions."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240942-p9-t0","doc_id":"K240942","page_num":9,"bbox":[71.04,636.12,517.32,762.12],"n_rows":2,"n_cols":3,"columns":["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],"rows":[["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],["Intended Use\n/ Indications\nfor Use","CINA-CSpine is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of cervical\nspine CT images.","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of cervical spine CT\nimages.\nThe device is intended to assist hospital\nnetworks and trained radiologists in\nworkflow triage by flagging and"]],"caption_candidate":"Comparison of key features between CINA-CSpine and predicate device (Aidoc Medical Ltd)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240942-p10-t0","doc_id":"K240942","page_num":10,"bbox":[71.04,71.04,517.32,767.4],"n_rows":4,"n_cols":3,"columns":["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],"rows":[["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],["","The device is intended to assist\nhospital networks and\nappropriately trained physician\nspecialists by flagging and\ncommunication of suspected\npositive findings compatible with\nacute cervical spine fractures\nincluding non-displaced fracture\nlines and/or displaced fracture\nfragments.\nCINA-CSpine uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\napplication in parallel to the\nongoing standard of care image\ninterpretation. The device is not\ndesigned to detect vertebral\ncompression fractures.\nThe user is presented with\nnotifications for cases with\nsuspected findings. Notifications\ninclude compressed preview\nimages that are meant for\ninformational purposes only, and\nare not intended for diagnostic\nuse beyond notification.\nThe device does not alter the\noriginal medical image, and it is\nnot intended to be used as a\ndiagnostic device.\nThe results of CINA-CSpine are\nintended to be used in\nconjunction with other patient\ninformation and based on\nprofessional judgment to assist\nwith triage/prioritization of\nmedical images.\nNotified clinicians are ultimately\nresponsible for reviewing full\nimages per the standard of care.","communication of suspected positive\nfindings of linear lucencies in the cervical\nspine bone in patterns compatible with\nfractures.\nBriefCase uses an artificial intelligence\nalgorithm to analyse images and highlight\ncases with detected findings on a\nstandalone desktop application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected\nfindings.\nNotifications include compressed preview\nimages that are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation an based on their professional\njudgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["User\npopulation","Trained physician specialist","Radiologist"],["Anatomical\nregion of\ninterest","Cervical Spine","Cervical Spine"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240942-p11-t0","doc_id":"K240942","page_num":11,"bbox":[71.04,71.04,517.32,534.36],"n_rows":10,"n_cols":3,"columns":["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],"rows":[["","Subject device: CINA-CSpine\nSoftware","Predicate device: BriefCase for CSF\nTriage Software (K190896)"],["Data\nacquisition\nprotocol","Non-contrast cervical spine CT\nscans","Non-contrast cervical spine CT scans"],["View DICOM\ndata","DICOM information about the\npatient, study and current image","DICOM information about the patient,\nstudy and current image"],["Segmentation\nof region of\ninterest","No; device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the\noriginal image","No; device does not mark, highlight, or\ndirect users’ attention to a specific location\nin the original image"],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm with\ndatabase of images"],["Notification /\nPrioritization","Yes","Yes"],["Preview\nimages","Presentation of a compressed,\ngrayscale, unannotated image\nthat is marked “not for diagnostic\nuse”.","Presentation of a small, compressed,\nblack\nand white preview image that is labeled\n“Not for diagnostic use”."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist\nqueue","No. The device operates in\nparallel with the standard of care,\nwhich remains the default option\nfor all cases.","No. The device operates in parallel with\nthe standard of care, which remains the\ndefault option for all cases."],["Structure","-CSpine image processing\napplication\n- Compatibility of use with the\nCINA Platform (worklist and\nImage Viewer) or other medical\nimage communications device.","- AHS module (orchestrator, image\nacquisition)\n- ACS module (image processing).\n- Aidoc Worklist application for workflow\nintegration (worklist and non-diagnostic\nbasic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240943-p6-t0","doc_id":"K240943","page_num":6,"bbox":[67.8,277.32,567.12,712.8],"n_rows":19,"n_cols":3,"columns":["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],"rows":[["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],["Indications for Use","The LungVision System is intended to enable\nusers to segment previously acquired 3D CT\ndatasets and overlay and register these 3D\nsegmented data sets with fluoroscopic live X-\nray images of the same anatomy in order to\nsupport catheter/device navigation during\npulmonary procedures.","The LungVision System is intended to enable\nusers to segment previously acquired 3D CT\ndatasets and overlay and register these 3D\nsegmented data sets with fluoroscopic live X-\nray images of the same anatomy in order to\nsupport catheter/device navigation during\npulmonary procedures."],["Classification","Automated radiological image processing\nsoftware\nQIH, CFR 892.2050\nPicture archiving and communications system\nLLZ, CFR 892.2050","Picture archiving and communications system\nLLZ, CFR 892.2050"],["Target anatomy","Lungs","Lungs"],["Anatomy access","Bronchial airways","Bronchial airways"],["Windows OS","Windows 10","Windows 10"],["Medical imaging\nsoftware","Yes","Yes"],["General Image 2D/3D\nreview","Yes","Yes"],["3D rendering view","Yes","Yes"],["Multi-modality\nSupport","Yes","Yes"],["Image registration","Yes","Yes"],["Multi-planar\nreformatting (MPR)","Yes","Yes"],["DICOM import","Yes","Yes"],["Fluoroscopic video","Yes","Yes"],["Standard Image\nviewing tools","Yes","Yes"],["Segmentation tool","Yes","Yes"],["Video capture","Yes","Yes"],["Live Image overlays","Yes","Yes"],["Import prior plans","Yes","Yes"]],"caption_candidate":"Table 1 compares the subject device to the predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240943-p7-t0","doc_id":"K240943","page_num":7,"bbox":[67.79,73.08,567.14,143.52],"n_rows":3,"n_cols":3,"columns":["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],"rows":[["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],["Point\nmarking/ tagging","Yes","Yes"],["Navigation type","Visual","Visual"]],"caption_candidate":"30-Aug-24","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240943-p7-t1","doc_id":"K240943","page_num":7,"bbox":[67.79,156.72,567.14,275.16],"n_rows":7,"n_cols":3,"columns":["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],"rows":[["Feature","Proposed Device\nLungVision","Primary Predicate\nK183593\nBody Vision LungVision"],["Modifications","",""],["Virtual bronchoscopy","Yes","Yes"],["C-Arm based CT","Yes","Yes"],["Multi-view set-up","Yes","Yes"],["Real-time\ncompensation","N/A","Yes"],["3D Guidance","Yes","Yes"]],"caption_candidate":"Navigation type Visual Visual","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240944-p5-t0","doc_id":"K240944","page_num":5,"bbox":[71.71,258.76,539.38,704.52],"n_rows":21,"n_cols":3,"columns":["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],"rows":[["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],["Specifica(on","",""],["","System","System (K232760)"],["","",""],["Intended Use/ Indica-ons for Use:","The Swoop Portable MR Imaging System\nis a portable, ultra-low field magne-c\nresonance imaging device for producing\nimages that display the internal\nstructure of the head where full\ndiagnos-c examina-on is not clinically\nprac-cal. When interpreted by a trained\nphysician, these images provide\ninforma-on that can be useful in\ndetermining a diagnosis.","Same"],["Pa-ent Popula-on:","Adult and pediatric pa-ents (≥ 0 years)","Same"],["Anatomical Sites:","Head","Same"],["Environment of Use:","At the point of care in professional\nhealth care facili-es such as emergency\nrooms, intensive/cri-cal care units,\nhospitals, outpa-ent, or rehabilita-on\ncenters.","Same"],["Energy Used and/or delivered:","Magne-c Resonance","Same"],["Magnet:","",""],["Physical Dimensions","835 mm x 630 mm x 652 mm","Same"],["Bore Opening","610 mm x 315 mm","Same"],["Weight","320 kg","Same"],["Field Strength","63.3 mT permanent magnet","Same"],["Gradient:","",""],["Strength","X: 24 mT/m, Y: 23 mT/m, Z: 39 mT/m","Same"],["Rise Time","X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms","Same"],["Slew Rate","X: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/s","Same"],["Computer Display","Hyperfine-supplied tablet","Same"],["RF Coils:","",""],["Number of Coils","1 head coil","Same"]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240944-p6-t0","doc_id":"K240944","page_num":6,"bbox":[71.78,72.36,539.39,437.4],"n_rows":16,"n_cols":3,"columns":["Coil Type","TX/RX","Same"],"rows":[["Coil Type","TX/RX","Same"],["Coil Geometry","Form-fiang","Same"],["Inner Dimensions (mm)","205 mm x 240 mm","Same"],["Coil Design","Linear Volume","Same"],["Pa-ent Weight Capacity","1.6kg-200 kg","Same"],["Opera-on Temperature","15-30 C","Same"],["Warm Up Time","<3 minutes","Same"],["Temperature Control","No","Same"],["Humidity Control","No","Same"],["Image Reconstruc-on Algorithm:","",""],["Noise Correc-on","Noise correc-on and line noise\nsuppression for all sequences","Same"],["T1W\n• T1-Standard\n• T1-Gray/White Contrast","Advanced Gridding","Same"],["T2W\n• T2\n• T2-Fast","Advanced Gridding","Same"],["FLAIR","Advanced Gridding","Same"],["DWI","Fast Itera-ve Shrinkage Thresholding\nAlgorithm (FISTA)","Same"],["Image Post-Processing","• Advanced Denoising\n• Image orienta-on transform\n• Geometric distor-on correc-on\n• Receive coil intensity correc-on\n• DICOM output","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240944-p6-t1","doc_id":"K240944","page_num":6,"bbox":[71.78,613.38,539.39,679.56],"n_rows":2,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Software\nVerification","Software verification testing in accordance with\nthe design requirements to ensure that the\nsoftware requirements were met.","• IEC 62304:2015\n• FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"]],"caption_candidate":"requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240944-p7-t0","doc_id":"K240944","page_num":7,"bbox":[72.4,72.36,539.39,310.92],"n_rows":3,"n_cols":3,"columns":["Image\nPerformance","Testing to verify the subject device meets all\nimage quality criteria.","• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• American College of Radiology (ACR)\nPhantom Test Guidance for Use of the\nLarge MRI Phantom for the ACR MRI\nAccreditation Program\n• American College of Radiology\nstandards for named sequences"],"rows":[["Image\nPerformance","Testing to verify the subject device meets all\nimage quality criteria.","• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• American College of Radiology (ACR)\nPhantom Test Guidance for Use of the\nLarge MRI Phantom for the ACR MRI\nAccreditation Program\n• American College of Radiology\nstandards for named sequences"],["Cybersecurity","Testing to verify cybersecurity controls and\nmanagement.","FDA Guidance, “Cybersecurity in\nMedical Devices: Quality System\nConsidera-ons and Content of\nPremarket Submissions”"],["Software Validation","Validation to ensure the subject device meets user\nneeds and performs as intended.","FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240944-p7-t1","doc_id":"K240944","page_num":7,"bbox":[72.4,380.22,539.39,573.0],"n_rows":5,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Biocompatibility","Biocompatibility testing of patient-contacting\nmaterials.","• ISO 10993-1:2018\n• ISO 10993-5:2009\n• ISO 10993-10:2010"],["Cleaning/\nDisinfection","Cleaning and disinfection validation of patient-\ncontacting materials.","• FDA Guidance, “Reprocessing Medical\nDevices in Health Care Settings:\nValidation Methods and Labeling”\n• ISO 17664:2017\n• ASTM F3208-17"],["Safety","Electrical Safety, EMC, and Essential Performance\ntesting.","• ANSI/AAMI ES 60601-1:2005/(R)2012\n• IEC 60601-1-2:2014\n• IEC 60601-1-6:2013"],["Performance","Characterization of the Specific Absorption Rate\nfor Magnetic Resonance Imaging Systems.","• NEMA MS 8-2016"]],"caption_candidate":"modifications did not introduce a new worst-case configuration or scenario for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p5-t0","doc_id":"K240953","page_num":5,"bbox":[90.0,148.31,486.53,701.71],"n_rows":55,"n_cols":2,"columns":["GeneralInformation",""],"rows":[["GeneralInformation",""],["",""],["510(k)Sponsor","ExoImaging"],["",""],["Address","4201BurtonDrive"],["",""],["","SantaClara,CA95054"],["",""],["CorrespondencePerson","JacquelineMurray"],["",""],["ContactInformation","jmurray@exo.inc"],["",""],["","Cell:+1236838-5056"],["",""],["DatePrepared","April08,2024"],["",""],["ProposedDevice",""],["",""],["ProprietaryName","AIPlatform2.0(AIP002)"],["",""],["CommonName","AIPlatform2.0"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["PredicateDevice",""],["",""],["ProprietaryName","LVivoIQS"],["",""],["PremarketNotification","K222970"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["ReferenceDevice1",""],["",""],["ProprietaryName","CaptionGuidance"],["",""],["PremarketNotification","DEN190040"],["",""],["ClassificationName","ImageAcquisitionAnd/OrOptimizationGuidedbyArtificial"],["",""],["","Intelligence"],["",""],["RegulationNumber","21CFR892.2100"]],"caption_candidate":"GeneralInformation","well_formed":true,"extraction_settings":"text"}
{"table_id":"K240953-p5-t1","doc_id":"K240953","page_num":5,"bbox":[85.5,327.33,534.5,435.33],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","AIPlatform2.0(AIP002)"],"rows":[["ProprietaryName","AIPlatform2.0(AIP002)"],["CommonName","AIPlatform2.0"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ProposedDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p5-t2","doc_id":"K240953","page_num":5,"bbox":[85.5,474.69,534.5,582.69],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","LVivoIQS"],"rows":[["ProprietaryName","LVivoIQS"],["PremarketNotification","K222970"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"PredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p5-t3","doc_id":"K240953","page_num":5,"bbox":[85.5,622.56,534.5,706.56],"n_rows":4,"n_cols":2,"columns":["ProprietaryName","CaptionGuidance"],"rows":[["ProprietaryName","CaptionGuidance"],["PremarketNotification","DEN190040"],["ClassificationName","ImageAcquisitionAnd/OrOptimizationGuidedbyArtificial\nIntelligence"],["RegulationNumber","21CFR892.2100"]],"caption_candidate":"ReferenceDevice1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p6-t0","doc_id":"K240953","page_num":6,"bbox":[85.5,93.56,534.5,129.56],"n_rows":2,"n_cols":2,"columns":["ProductCode","QJU"],"rows":[["ProductCode","QJU"],["RegulatoryClass","II"]],"caption_candidate":"510(k)Summary-AIPlatform2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p6-t1","doc_id":"K240953","page_num":6,"bbox":[85.5,179.43,534.5,287.43],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","AIPlatform"],"rows":[["ProprietaryName","AIPlatform"],["PremarketNotification","K232501"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ReferenceDevice2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p7-t0","doc_id":"K240953","page_num":7,"bbox":[74.08,384.49,540.25,680.5],"n_rows":3,"n_cols":5,"columns":["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],"rows":[["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],["Scantype","Singleand\nMulti-frame\nultrasoundimages","Sameassubject\ndevice","Sameassubject\ndevice","Sameassubject\ndevice"],["Principleof\nOperationand\nTechnology","Ultrasoundimage\nprocessingsoftware\nimplementing\nartificialintelligence,\nincluding\nnon-adaptive\nmachinelearning\nalgorithmstrained\nwithclinicaldata\nintendedfor\nnon-invasiveanalysis\nofultrasounddata","Sameassubject\ndevice","Sameassubject\ndevice","Sameassubject\ndevice"]],"caption_candidate":"ComparisonofTechnologicalCharacteristicswiththePredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p8-t0","doc_id":"K240953","page_num":8,"bbox":[74.53,93.6,540.33,662.5],"n_rows":7,"n_cols":5,"columns":["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],"rows":[["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],["AIAlgorithm","DeepConvolutional\nNeuralNetworksfor\nSegmentation,\nLandmarkDetection\nandClassification","Sameassubject\ndevice","Sameassubject\ndevice","Sameassubject\ndevice"],["Anatomical\nSites","Heart,Lungs","Heart,Bladder","Heart","Heart,Lungs"],["Cardiac\nMeasurements","LVEF\nIVCMinimum\ndiameteron\ninspirationand\nMaximumdiameter\nonexpiration\nMyocardiumwall\nthickness\n(Interventricular\nSeptumand\nPosteriorwall)from\nPlaxview","LVEF,GLS\nRVsizeand\nfunction:Fractional\nAreaChange\n(FAC),FreeWall\nStrain(FWS),\nTricuspidannular\nplanesystolic\nexcursion(TAPSE)","No","LVEF"],["NonCardiacAI\nmodules","Absence/presenceof\nA-lines\nB-linescount","BladderVolume","No","Absence/presence\nofA-lines\nB-linescount"],["Realtime\nfeedbackon\nquality","Yes","Sameassubject\ndevice","Sameassubject\ndevice","No"],["Retrospectively\nrecordingof\nDiagnostic\nqualityclip","Yes","No","Sameassubject\nDevice","No"]],"caption_candidate":"510(k)Summary-AIPlatform2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p9-t0","doc_id":"K240953","page_num":9,"bbox":[74.08,93.6,540.33,281.5],"n_rows":2,"n_cols":5,"columns":["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],"rows":[["Feature/\nFunction","SubjectDevice\nExoAIPlatform2.0","PredicateDevice:\nLVivoIQS\n(K222970)","ReferenceDevice\n1:\nCaptionGuidance\n(DEN190040)","ReferenceDevice\n2:\nAIPlatform\n(K232501)"],["AImodulesare\nanaccessoryto\ncompatible\ngeneral\npurpose\ndiagnostic\nultrasound\nsystems","Yes","Sameassubject\ndevice","Sameassubject\ndevice","No"]],"caption_candidate":"510(k)Summary-AIPlatform2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p10-t0","doc_id":"K240953","page_num":10,"bbox":[106.42,118.21,505.5,276.5],"n_rows":5,"n_cols":3,"columns":["","Measurement","ICC(95%CI)"],"rows":[["","Measurement","ICC(95%CI)"],["LVWallthickness","InterVentricularSeptum(IVSd)","0.93(0.89–0.96)"],["","PosteriorWall(PWd)","0.94(0.89–0.97)"],["Inferiorvenacava(IVC)","IVCDmin","0.93(0.90–0.95)"],["","IVCDmax","0.94(0.90–0.96)"]],"caption_candidate":"Table1:SummaryofAIPlatformperformanceforleftventriclewallthicknessandIVCmeasurement","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240953-p11-t0","doc_id":"K240953","page_num":11,"bbox":[71.37,217.55,540.63,711.5],"n_rows":3,"n_cols":4,"columns":["Modification","Rationale","TestingMethods","ImpactAssessment"],"rows":[["Modification","Rationale","TestingMethods","ImpactAssessment"],["(A)Modification\ntoarchitecture,\npre/post\nprocessing","TheAImodelsin\nAIPlatform2.0\nmaybemodified\ninafocusedand\nboundmanner,to\nimproveaccuracy,\nefficiency,and\nadaptabilitywhile\nmaintainingthe\nsafetyandefficacy\nofthedevice.","Substantialequivalence\ninperformancematrices\nascomparedtotheAI\nPlatform2.0.\nNon-inferioritymarginsin\nalignmentwithFDA\nrecommendationswillbe\nusedtoensurethenew\ndeviceremainssafeand\neffectivewithoutany\nsuchchangecompared\nwiththeoriginaldevice\nandthelastmodified\nversionofthedevice.","Improvedaccuracyand/orefficiencymetricsfor\nAImodelperformance.\nBenefit-RiskAnalysis:\nBenefit:Enhancedperformance;Improved\nefficiencyandscalability.\nRisk:Reductioninclinicalperformance\nRiskMitigation:\nTherisksofoverfittingandgeneralizabilityare\nmitigatedbyconductingcross-validation,data\naugmentation,andhyperparametertuningin\ninternaltrainingprocedures.\nThefinalvalidationisperformedusing\nnon-inferiorityanalysisaccordingtothe\nestablishedclinicalprotocoltoensurebaseline\nperformanceismaintainedandimprovements\narerealizedbeforemodificationsarecommitted\nandreleased."],["(B)Introduction\nofnewtraining\ndata","Thetraining\ndatasetoftheAI\nmodelsmaybe\naugmentedwitha\nbroaderandmore\ndiverserangeof\nimagingdatato\nenhancemodel\nrobustness,\nreducebias,\nimprove\ngeneralizability,\nandrespond\neffectivelyto\nreal-world\nfeedback.","Substantialequivalence\ninperformancematrices\nascomparedtotheAI\nPlatform2.0.\nNon-inferioritymarginsin\nalignmentwithFDA\nrecommendationswillbe\nusedtoensurethenew\ndeviceremainssafeand\neffectivewithoutany\nsuchchangecompared\nwiththeoriginaldevice\nandthelastmodified\nversionofthedevice","ImprovedmodelgeneralizabilityforAImodel\noutputsdisplayedtousers.\nBenefit-RiskAnalysis:\nBenefit:Improvedmodelrobustness,reduced\nbias,enhancedgeneralizability,andresponding\ntorealworldfeedback.\nRisk:Reductioninclinicalperformance\nRiskMitigation:\nTherisksofoverfittingandgeneralizabilityare\nmitigatedbyconductingcross-validation,data\naugmentation,andhyperparametertuningin\ninternaltrainingprocedures.\nThefinalvalidationisperformedusing\nnon-inferiorityanalysisaccordingtothe\nestablishedclinicalprotocoltoensurebaseline"]],"caption_candidate":"impactassessment,arepresentedinthetablebelow:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p5-t0","doc_id":"K240980","page_num":5,"bbox":[251.39,458.77,566.19,589.17],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ","",""]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p7-t0","doc_id":"K240980","page_num":7,"bbox":[35.42,194.92,576.62,684.21],"n_rows":18,"n_cols":6,"columns":["","","","TOMTEC-ARENA","QLAB Advanced",""],"rows":[["","","","TOMTEC-ARENA","QLAB Advanced",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","","",""],["","","","Feature: 4D CARDIO-","Quantification Software",""],["","Ultrasound System","Ultrasound System","","",""],["Feature","","","VIEW","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto TV","K233788","","",""],["","","","K213544","K200974",""],["","Proposed Device","Predicate Device","","",""],["","","","Reference Device","Reference Device",""],["","","","","",""],["","Abdominal, Cardiac\nAdult, Cardiac other\n(Fetal), Cardiac\nPediatric, Cerebral\nVascular, Cephalic\n(Adult), Cephalic\n(Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative\n(Vascular),\nIntraoperative (Cardiac),\nintra-luminal, intra-\ncardiac echo,\nMusculoskeletal\n(Conventional),\nMusculoskeletal\n(Superficial),\nOphthalmic, Other:\nUrology, Pediatric,\nPeripheral Vessel, Small\nOrgan (Breast, Thyroid,\nTesticle),\nTransesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","Abdominal, Cardiac\nAdult, Cardiac other\n(Fetal), Cardiac\nPediatric, Cerebral\nVascular, Cephalic\n(Adult), Cephalic\n(Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative\n(Vascular),\nIntraoperative (Cardiac),\nintra-luminal, intra-\ncardiac echo,\nMusculoskeletal\n(Conventional),\nMusculoskeletal\n(Superficial),\nOphthalmic, Other:\nUrology, Pediatric,\nPeripheral Vessel, Small\nOrgan (Breast, Thyroid,\nTesticle),\nTransesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","Quantification and\nreporting of\ncardiovascular, fetal,\nand abdominal\nstructures and functions\nof patients with\nsuspected disease to\nsupport the physician in\nthe diagnosis.","QLAB Quantification software\nis a software application\npackage. It is designed to view\nand quantify image data\nacquired on Philips ultrasound\nsystems","Identical to predicate"],["Indications for","","","","",""],["Use","","","","",""],["","","","","",""],["","Trained healthcare\nprofessionals\nIntended for\nsonographers,\nphysicians, and\nbiomedical engineers\nwho operate and\nmaintain your product.\nBefore use of the\nsystem and user\ninformation, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are\nnot included in the User\nManual or with the EPIQ\nSeries Diagnostic\nUltrasound System.","Trained healthcare\nprofessionals\nIntended for\nsonographers,\nphysicians, and\nbiomedical engineers\nwho operate and\nmaintain your product.\nBefore use of the\nsystem and user\ninformation, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are\nnot included in the User\nManual or with the EPIQ\nSeries Diagnostic\nUltrasound System.","Licensed medical\npractitioners or assistant\nmedical technicians","Trained healthcare\nprofessionals","Identical to predicate"],["Intended","","","","",""],["Users","","","","",""],["","","","","",""]],"caption_candidate":"Table 1: Comparison to Predicate for introduction of 3D Auto TV onto EPIQ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p8-t0","doc_id":"K240980","page_num":8,"bbox":[35.42,67.38,576.68,712.71],"n_rows":30,"n_cols":6,"columns":["","","","TOMTEC-ARENA","QLAB Advanced",""],"rows":[["","","","TOMTEC-ARENA","QLAB Advanced",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","","",""],["","","","Feature: 4D CARDIO-","Quantification Software",""],["","Ultrasound System","Ultrasound System","","",""],["Feature","","","VIEW","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto TV","K233788","","",""],["","","","K213544","K200974",""],["","Proposed Device","Predicate Device","","",""],["","","","Reference Device","Reference Device",""],["","","","","",""],["","Clinics, hospitals, and\nclinical point-of-care for\ndiagnosis of patients.","Clinics, hospitals, and\nclinical point-of-care for\ndiagnosis of patients.","Inside and outside of\nHospitals, Clinics, and\nPhysician’s offices","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Identical to predicate"],["Intended User","","","","",""],["Environment","","","","",""],["","","","","",""],["","Class II","Class II","Class II","Class II","Identical to predicate"],["USA FDA","","","","",""],["Classification","","","","",""],["","","","","",""],["","IYN","IYN","QIH","QIH","Identical to predicate"],["Primary","","","","",""],["Product Code","","","","",""],["","","","","",""],["","The 3D Auto TV\nsoftware solution is\nintended for use with the\nPhilips EPIQ Diagnostic\nUltrasound Systems.\nThe software enables\nsemi-automated\nquantification of the\ntricuspid valve. At a high\nlevel, this is\naccomplished through\nautomatically derived\nmeasurements from a\nsegmented model of the\ntricuspid valve annulus\nformed by the software\nthrough model-based\nsegmentation of the\nacquired ultrasound\nimages.","The predicate EPIQ\nSeries Diagnostic\nUltrasound System does\nnot currently have a\ndedicated software\napplication for\nquantification of the\ntricuspid valve annulus.\nThe subject of this\nsubmission is to\nintroduce the 3D Auto\nTV software onto the\npredicate device.","4D CARDIO-VIEW is an\nadvanced analysis tool\nfor 3D/4D\nechocardiography data.\nAnatomical structure\nvisualization, volume\nmeasurements (LV\nand/or generic), and\nspecified or manual\nmeasurements are\npossible for cardiac\nstructures including, but\nnot limited to, the\ntricuspid valve. Various\ntools are available for\nrendering that display 2-\nand 3-dimensional\nmorphology and\nfunction for defined\nstructures.","3D Auto MV is a semi-\nautomated software\napplication intended for the\nanalysis of Mitral Valve (MV)\nanatomy and function. This\napplication generates models\nof anatomical structures of\ninterest such as the MV\nannulus, leaflets, and the\nclosure line, which allows for\nquantification of pre- and post-\noperative valvular function and\na comparison of morphology.","Similar to the reference\ndevice features.\nThe functionality and\nworkflow of the 3D Auto\nTV software is very\nsimilar to the 3D Auto\nMV tool, where\nmeasurement\nparameters are derived\nfrom models of the\nmitral valve (in the case\nof 3D Auto MV) and\ntricuspid valve (in the\ncase of 3D Auto TV).\nManual measurements\nare also able to be\nperformed on both\nsoftware applications.\nComparing 3D Auto TV\nto 4D CARDIO-VIEW,\nboth software have\nfunctionality for\nquantifying the tricuspid\nvalve. The proposed 3D\nAuto TV allows for semi-\nautomated\nquantification, where the\nreference device is fully\nmanual. As we\ndemonstrate high\nagreement in the\nmeasurement outputs\non the same patients\nwhen quantified using\nthe proposed 3D Auto\nTV software and the\nreference 4D CARDIO-\nVIEW application, there\nare no new questions\nraised of safety or\neffectiveness."],["Application","","","","",""],["Description","","","","",""],["","","","","",""],["","3D surface model is\ncreated semi-\nautomatically using\nmachine learning\nalgorithm without user\ninteraction. User is able\nto edit, accept, or reject\nthe initial landmark\nproposals of the mitral","No standard tricuspid\nvalve (TV) quantification\nparameters included as\npart of the system.","3D surface model is\ncreated based on user\ndefined anatomical\nlandmarks. User is able\nto edit the contour of the\nsurface model before\nproceeding with the\nworkflow.","3D surface model is created\nsemi-automatically using\nmachine learning algorithm\nwithout user interaction. User\nis able to edit, accept, or reject\nthe initial landmark proposals\nof the mitral valve anatomical\nlocations.","Subject device uses\nidentical method for\ncontour generation as\nthe reference device\nK200974. The only\ndifference is the\nalgorithm is trained on\ntricuspid valve images,\nwhere the reference"],["Contour","","","","",""],["Generation","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p9-t0","doc_id":"K240980","page_num":9,"bbox":[35.4,67.38,576.62,630.93],"n_rows":15,"n_cols":6,"columns":["","","","TOMTEC-ARENA","QLAB Advanced",""],"rows":[["","","","TOMTEC-ARENA","QLAB Advanced",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","","",""],["","","","Feature: 4D CARDIO-","Quantification Software",""],["","Ultrasound System","Ultrasound System","","",""],["Feature","","","VIEW","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto TV","K233788","","",""],["","","","K213544","K200974",""],["","Proposed Device","Predicate Device","","",""],["","","","Reference Device","Reference Device",""],["","","","","",""],["","valve anatomical\nlocations.","","","","device was trained using\nmitral valve images."],["","Semi-auto annulus\nresults\n• TV Ann Perimeter\n(3D)\n• TV Ann Perimeter\n(2D)\n• TV Ann Max Diam\n(2D)\n• TV Ann Min Diam\n(2D)\n• TV Ann Perimeter\nDerived Diam (2D)\n• TV Ann Height (3D)\n• TV Ann Area (2D)\nManual device results\n• TV Ann AP Diam (2D)\n• TV Ann SL Diam (2D)\n• Subvalvular 5 Plane\nSL Diam\n• Subvalvular 5 Plane\nAP Diam\n• Supravalvular C-\nShaped Perimeter\n• Supravalvular AV -\nAoCenter Diam","No standard tricuspid\nvalve (TV) quantification\nparameters included as\npart of the system.","TAVR results\n• Ann-Ost left diam\n• Ann-Ost right diam\n• Annulus Area\n• Annulus dmin\n• Annulus dmax\n• Ao Ring diam\n• Ao SV diam\n• Ao STJ diam\nVolume results (not\nrelated to TV\nquantification)\n• EDV\n• EF\n• ESV\n• GenVol\n• Mass\n• SV","Standard MV Parameters\n• AP Diameter (cm)\n• AL-PM Diameter (cm)\n• Sphericity Index (AP / AL-\nPM)\n• Intertrigonal Distance (cm)\n• Commissural Diameter (cm)\n• D-Shaped Annulus\nPerimeter (cm)\n• Annulus Height (cm)\n• Non-planar Angle (degrees)\n• Tenting Volume (cm3)\n• Coaptation Depth (mm)\n• Tenting Area (cm2)\n• Angle AAo-AP (degrees)\n• Maximum Prolapse Height\n(mm)\n• Maximum Open Coaptation\nGap (mm)\n• Maximum Open Coaptation\nWidth (mm)\n• Anterior Leaflet Area (cm2)\n• Posterior Leaflet Area (cm2)\n• Distal Anterior Leaflet Angle\n(degrees)\n• Posterior Leaflet Angle\n(degrees)\n• Anterior Leaflet Length (cm)\n• Posterior Leaflet Length\n(cm)\n• C-Shaped Annulus (cm)\n2D MV Parameters\n• D-Shaped Annulus Area\n(cm2)\n• Annulus Area (cm2)\n• Anterior Closure Line\nLength (cm)\n• Posterior Closure Line\nLength (cm)\n3D MV Parameters\n• Saddle Shaped Annulus\nArea (cm2)\n• Saddle Shaped Annulus\nPerimeter (cm)\n• Total Open Coaptation Area\n(cm2)\n• Anterior Closure Line\nLength (cm)\n• Posterior Closure Line\nLength (cm)","Similar. The proposed\n3D Auto TV software\nallows very similar semi-\nautomated\nmeasurements as the\nreference software\napplication 3D Auto MV,\nonly applied to the\ntricuspid valve.\nThe proposed 3D Auto\nTV software adds\nadditional TV annulus\nand device\nmeasurements from\nthose available in 4D\nCARDIO-VIEW to\nfurther define the\ntricuspid valve anatomy.\nBoth the proposed 3D\nAuto TV and the\nreference 4D CARDIO-\nVIEW software allow\nmanual, free-form\nmeasurements of the\ntricuspid valve."],["Measurement","","","","",""],["s Performed","","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p10-t0","doc_id":"K240980","page_num":10,"bbox":[35.42,90.37,584.47,708.7],"n_rows":33,"n_cols":5,"columns":["","","","QLAB Advanced Quantification",""],"rows":[["","","","QLAB Advanced Quantification",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","",""],["","","","Software",""],["","Ultrasound System","Ultrasound System","",""],["Feature","","","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto CFQ","K233788","",""],["","","","K200974",""],["","Proposed Device","Predicate Device","",""],["","","","Reference Device",""],["","","","",""],["","Abdominal, Cardiac Adult,\nCardiac other (Fetal), Cardiac\nPediatric, Cerebral Vascular,\nCephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative\n(Vascular), Intraoperative\n(Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Ophthalmic, Other:\nUrology, Pediatric, Peripheral\nVessel, Small Organ (Breast,\nThyroid, Testicle),\nTransesophageal (Cardiac),\nTransrectal, Transvaginal, Lung.","Abdominal, Cardiac Adult,\nCardiac other (Fetal), Cardiac\nPediatric, Cerebral Vascular,\nCephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative\n(Vascular), Intraoperative\n(Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal\n(Conventional), Musculoskeletal\n(Superficial), Ophthalmic, Other:\nUrology, Pediatric, Peripheral\nVessel, Small Organ (Breast,\nThyroid, Testicle),\nTransesophageal (Cardiac),\nTransrectal, Transvaginal, Lung.","QLAB Quantification software is a\nsoftware application package. It\nis designed to view and quantify\nimage data acquired on Philips\nultrasound systems","Identical to predicate"],["Indications for","","","",""],["Use","","","",""],["","","","",""],["","Trained healthcare professionals\nIntended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the EPIQ Series Diagnostic\nUltrasound System.","Trained healthcare professionals\nIntended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the EPIQ Series Diagnostic\nUltrasound System.","Trained healthcare professionals","Identical"],["Intended Users","","","",""],["","","","",""],["","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Identical"],["Intended User","","","",""],["Environment","","","",""],["","","","",""],["","Class II","Class II","Class II","Identical"],["USA FDA","","","",""],["Classification","","","",""],["","","","",""],["","IYN","IYN","QIH","Identical to predicate"],["Primary Product","","","",""],["Code","","","",""],["","","","",""],["","3D Auto CFQ is a new semi-\nautomated quantification software\nwhich will be introduced on the\nEPIQ Ultrasound Systems from\nsoftware version VM11.0. The\napplication provides semi-\nautomated quantification of Mitral\nRegurgitation (MR) volume and\npeak flow rate by analyzing 3D\ncolor flow images acquired during\ntransesophageal\nechocardiography (TEE)\nexaminations.","The Proximal Isovelocity Surface\nArea (PISA) methodology can be\nused currently on the predicate\ndevice to quantify valvular\nregurgitation. The technique\nutilizes 2D/Color and Doppler\nimages to allow the user to make\nsimple, manual measurements in\na cascading fashion to allow\ncalculation of peak flow rate and\nvolumetric regurgitation.","3D Auto MV is a semi-automated\nsoftware application intended for\nthe analysis of Mitral Valve (MV)\nanatomy and function. This\napplication generates models of\nanatomical structures of interest\nsuch as the MV annulus, leaflets,\nand the closure line, which allows\nfor quantification of pre- and post-\noperative valvular function and a\ncomparison of morphology.","Similar. The predicate device\nfacilitates the quantification of\nmitral regurgitation volume\nand peak flow rate through a\ngroup of measurements which\nare performed in a cascading\nfashion manually by the user\naccording to the Proximal\nIsovelocity Surface Area\n(PISA) methodology. The\nproposed 3D Auto CFQ\nsoftware application allows\nthe users to quantify the same\nmeasurements for mitral\nregurgitation volume and peak\nflow rate but in a semi-\nautomated workflow."],["Application","","","",""],["Description","","","",""],["","","","",""]],"caption_candidate":"Table 2: Comparison to Predicate for introduction of 3D Auto CFQ onto EPIQ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p11-t0","doc_id":"K240980","page_num":11,"bbox":[35.42,67.37,584.45,713.45],"n_rows":21,"n_cols":5,"columns":["","","","QLAB Advanced Quantification",""],"rows":[["","","","QLAB Advanced Quantification",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","",""],["","","","Software",""],["","Ultrasound System","Ultrasound System","",""],["Feature","","","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto CFQ","K233788","",""],["","","","K200974",""],["","Proposed Device","Predicate Device","",""],["","","","Reference Device",""],["","","","",""],["","","","","The reference device does not\ncontain functionality for\nquantification of mitral\nregurgitation."],["","3D surface model is created\nsemi-automatically using\nmachine learning algorithm\nwithout user interaction. User is\nable to edit, accept, or reject the\ninitial landmark proposals of the\nmitral valve anatomical locations.","No standard contour generation\ntechnology for the mitral valve,\noutside of 3D Auto MV, included\nas part of the system.","3D surface model is created\nsemi-automatically using\nmachine learning algorithm\nwithout user interaction. User is\nable to edit, accept, or reject the\ninitial landmark proposals of the\nmitral valve anatomical locations.","Subject device uses identical\nmethod for contour generation\nas the reference device\nK200974"],["Contour","","","",""],["Generation","","","",""],["","","","",""],["","The 3D Auto CFQ algorithm\nquantifies mitral regurgitation\nvolume and flow rate from\nacquired 3D color flow images.\nThe greyscale information from\nthese images is used to generate\na 3D model of the mitral valve,\nwhich is used as an input along\nwith the 3D color data into the 3D\nAuto CFQ flow algorithm. The 3D\nAuto CFQ algorithm uses a fluid\ndynamic model of an\nincompressible fluid (blood)\ntraveling through an irregular-\nshaped (i.e., nonround) orifice. In\nits initial step, the algorithm\ngenerates a hypothetical model\nof true blood flow velocities in the\nproximal convergence zone\nbased on all measured Doppler\nvelocities and the underlying fluid\ndynamics model. The true\nvelocity model is then converted\ninto the corresponding apparent\nDoppler velocity model\n(“synthetic apparent velocities”)\nusing ultrasound physics\n(projection along the axial\ndimension). These synthetic\nvelocities are subsequently\ncompared to the acquired\nvelocities in the Color Flow (CF)\ndata set. Based on the outcome\nof this comparison, the model is\nupdated and reiterated to get\nthe best fit between the acquired\nvelocities and the generated\nmodel. 3D Auto CFQ determines\nthe resulting regurgitant flow rate\nfor this frame. This process is\nrepeated for each frame included\nin the analysis, which in most\ncases includes the entire systolic\ncycle. In each frame, the size and\nshape of the\nregurgitant orifice is not assumed\nbut is generated by this iterative\nloop between the model and the\nCF data.","The PISA methodology uses\nsequential acquisitions and\nmanual measurements, which\nare manually performed by the\nuser:\n• MR Alias Velocity (from the\n2D/Color)\n• MR Radius (from the 2D/Color)\n• MR Vmax (from the continuous\nwave doppler)\n• MR VTI (from the continuous\nwave doppler)\nThe outputs of these\nmeasurements go into the\nequations for the derived\nmeasurements including:\n• Mitral Regurgitant (MR) Flow\nRate\n• MR Effective Regurgitant\nOrifice (ERO)\n• MR Volume","N/A – does not contain\ntechnology for mitral regurgitation\nquantification","Similar. The predicate device\nutilizes the PISA methodology\nfor quantifying MR volume\nand flow rate. This\nmethodology utilizes\nsequential measurements\nperformed by the user and is\nbased on assumptions\nincluding there being a single,\nround, constant flow orifice\nduring the entire systole.\n3D Auto CFQ operates using\n3D color to address the spatial\ncomplexities seen in mitral\nregurgitation and was\ndeveloped to evaluate the\nregurgitant flow at every frame\nin systole, where the PISA\nmethodology only assesses\none frame during systole and\nassumes this frame applies\nacross systole.\nThe proposed 3D Auto CFQ\nsoftware application allows\nthe users to quantify the same\nmeasurements for mitral\nregurgitation volume and peak\nflow rate as PISA. The\ndynamic flow algorithm is the\nnew technology introduced in\nthis submission. Everything\nleading up to the calculations\nby the dynamic flow model are\nexisting and cleared, including\nthe transducer and imaging\nmodes (X8-2t transducer; 3D\nZoom, Full Volume 3D, or Live\n3D; K163120), and software\nfor mitral valve model\ngeneration (reference device\nK200974). The dynamic flow\nmodel of the 3D Auto CFQ\nsoftware application uses\nthese as inputs to arrive at the\noutputs of mitral regurgitation\nvolume and peak flow rate.\nThese outputs are the same\nas in the predicate, only the\nmethod to arrive at the"],["Quantification","","","",""],["Technology for","","","",""],["Mitral","","","",""],["Regurgitation","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p12-t0","doc_id":"K240980","page_num":12,"bbox":[35.41,67.37,584.45,715.95],"n_rows":19,"n_cols":5,"columns":["","","","QLAB Advanced Quantification",""],"rows":[["","","","QLAB Advanced Quantification",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","",""],["","","","Software",""],["","Ultrasound System","Ultrasound System","",""],["Feature","","","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto CFQ","K233788","",""],["","","","K200974",""],["","Proposed Device","Predicate Device","",""],["","","","Reference Device",""],["","","","",""],["","","","","measurements differs in the\nsubject device."],["","3D9-3V, C5-1, C8-5, C9-2, C10-\n3V, C10-4ec, D2cwc, D2tcd,\nD5cwc, eL18-4, eL18-4 EMT,\nL12-3, L12-3 ERGO, L12-5 50,\nL15-7io, L18-5, mC7-2, mC12-3,\nmL26-8, S5-1, S7-3t, S8-3, S8-3t,\nS9-2, S12-4, V6-2, V9-2, VL12-5,\nX5-1, X5-1c, X6-1, X7-2, X7-2t,\nX8-2t, X11-4t, XL14-3\nThe 3D Auto CFQ software\napplication can analyze\ntransesophageal\nechocardiography (TEE) images\nacquired by the cleared X8-2t\ntransducer (K163120), which is\nalready commercially available\nand compatible with the EPIQ\nUltrasound System.","3D9-3V, C5-1, C8-5, C9-2, C10-\n3V, C10-4ec, D2cwc, D2tcd,\nD5cwc, eL18-4, eL18-4 EMT,\nL12-3, L12-3 ERGO, L12-5 50,\nL15-7io, L18-5, mC7-2, mC12-3,\nmL26-8, S5-1, S7-3t, S8-3, S8-3t,\nS9-2, S12-4, V6-2, V9-2, VL12-5,\nX5-1, X5-1c, X6-1, X7-2, X7-2t,\nX8-2t, X11-4t, XL14-3","The 3D Auto MV software\napplication is compatible with the\nfollowing transducers: X7-2t, X8-\n2t, X11-4t","Identical. There are no new\ntransducers introduced in this\n510(k).\nThe 3D Auto CFQ software\napplication can analyze\ntransesophageal\nechocardiography (TEE)\nimages acquired by the\ncleared X8-2t transducer\n(K163120), which is already\ncommercially available and\ncompatible with the EPIQ\nUltrasound System.\nThere are no impacts to the\nindications for use or intended\nuse of the X8-2t transducer\nwhen used for the purposes of\nacquiring images for analysis\nby the 3D Auto CFQ software\napplication. The 3D Auto CFQ\nsoftware application requires\nimages to be acquired in\neither 3D Zoom, Full Volume\n3D, or Live 3D imaging\nmodes. There are no changes\nto these existing transducer\nimaging modes."],["Compatible","","","",""],["transducers","","","",""],["","","","",""],["","Semi-automated measurements\nperformed by the 3D Auto CFQ\nsoftware application:\nMitral regurgitation (MR) volume\n[mL];\nPeak flow rate [mL/s]","Derived measurements which the\nuser can obtain through the PISA\nmethodology include:\nMitral regurgitation (MR) volume\n[mL];\nPeak flow rate [mL/s]","Standard MV Parameters\n• AP Diameter (cm)\n• AL-PM Diameter (cm)\n• Sphericity Index (AP / AL-PM)\n• Intertrigonal Distance (cm)\n• Commissural Diameter (cm)\n• D-Shaped Annulus Perimeter\n(cm)\n• Annulus Height (cm)\n• Non-planar Angle (degrees)\n• Tenting Volume (cm3)\n• Coaptation Depth (mm)\n• Tenting Area (cm2)\n• Angle AAo-AP (degrees)\n• Maximum Prolapse Height\n(mm)\n• Maximum Open Coaptation\nGap (mm)\n• Maximum Open Coaptation\nWidth (mm)\n• Anterior Leaflet Area (cm2)\n• Posterior Leaflet Area (cm2)\n• Distal Anterior Leaflet Angle\n(degrees)\n• Posterior Leaflet Angle\n(degrees)\n• Anterior Leaflet Length (cm)\n• Posterior Leaflet Length (cm)\n• C-Shaped Annulus (cm)\n2D MV Parameters","Similar. The measurements\nperformed by the proposed\n3D Auto CFQ software\napplication can also be\nobtained by a user on the\npredicate device.\nSubstantiation of the\nperformance of the 3D Auto\nCFQ software’s regurgitant\nvolume output was performed\nby comparison to cardiac\nmagnetic resonance imaging\n(CMR) images with\nacceptance criteria of\nagreement within the limits of\nagreement. While the PISA\nmethodology is a widely\naccepted method for mitral\nregurgitation quantification\nand is a recommended\nmethod by the American\nSociety of Echocardiography,\nthe outputs from 3D Auto CFQ\nwere compared to those from\nCMR (as opposed to PISA) as\nthe former is considered a\ngold standard for mitral\nregurgitation quantification.\nAcceptance criteria for 3D\nAuto CFQ was based on"],["Measurements","","","",""],["Performed","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K240980-p13-t0","doc_id":"K240980","page_num":13,"bbox":[35.38,67.37,584.42,289.08],"n_rows":11,"n_cols":5,"columns":["","","","QLAB Advanced Quantification",""],"rows":[["","","","QLAB Advanced Quantification",""],["","EPIQ Series Diagnostic","EPIQ Series Diagnostic","",""],["","","","Software",""],["","Ultrasound System","Ultrasound System","",""],["Feature","","","Feature: 3D Auto MV","Comparison"],["","Feature: 3D Auto CFQ","K233788","",""],["","","","K200974",""],["","Proposed Device","Predicate Device","",""],["","","","Reference Device",""],["","","","",""],["","","","• D-Shaped Annulus Area (cm2)\n• Annulus Area (cm2)\n• Anterior Closure Line Length\n(cm)\n• Posterior Closure Line Length\n(cm)\n3D MV Parameters\n• Saddle Shaped Annulus Area\n(cm2)\n• Saddle Shaped Annulus\nPerimeter (cm)\n• Total Open Coaptation Area\n(cm2)\n• Anterior Closure Line Length\n(cm)\n• Posterior Closure Line Length\n(cm)","agreement with CMR being\nwithin predefined maximum\nlimits of agreement.\nIn addition to regurgitant\nvolume, the peak flow rate\noutput of 3D Auto CFQ was\nvalidated in comparison to\nmanual PISA method, where\nthe correlation was very high.\nThe reference device\nK200974 facilitates\nanatomical measurements of\nthe mitral valve from the\ngenerated model of the mitral\nvalve but does not perform\nmeasurements for quantifying\nmitral regurgitation."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p5-t0","doc_id":"K241029","page_num":5,"bbox":[89.35,574.61,538.68,706.03],"n_rows":3,"n_cols":4,"columns":["Transducer / Scanner","","","Clarius Ultrasound Scanner, model C3 HD3\n(K213436)"],"rows":[["Transducer / Scanner","","","Clarius Ultrasound Scanner, model C3 HD3\n(K213436)"],["","Software","","SpineUs™ computer application"],["Tracking system","","","Motive Software\nOptiTrack Cameras\nSpineUs™ Active LED Markers\nPower over Ethernet (PoE) switch"]],"caption_candidate":"The SpineUs™ system comprises the following:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p7-t0","doc_id":"K241029","page_num":7,"bbox":[85.2,69.24,540.12,698.76],"n_rows":7,"n_cols":3,"columns":["","","Phased Array\nIntracavity"],"rows":[["","","Phased Array\nIntracavity"],["Intended Use","Diagnostic ultrasound imaging of the spinal\nregion of the human body","Diagnostic ultrasound imaging and fluid flow\nanalysis of the human body"],["Indications for\nUse and Clinical\nUsage","The SpineUs™ system is a software-based,\ntracked, ultrasound imaging system and\naccessories, intended for diagnostic imaging. It\nis indicated for diagnostic ultrasound imaging in\nthe following applications: musculoskeletal\n(conventional, superficial). The system is\nintended for use by trained chiropractors and\nradiologists in a hospital or medical clinic.\nThe SpineUs™ system is intended for assisting\ntrained chiropractors and radiologists in\nacquiring, viewing, and measuring ultrasound\nimages of the spine in both clinic and hospital\nsettings. The SpineUs™ system is intended to\nbe used as an adjunct to conventional imaging\nmethod that allows trained chiropractors and\nradiologists to measure spine-related anatomical\ncomponents on images (e.g., intervertebral\nangles and spine curvature). The system also\nallows the review and management of patient\nmeasurement data. Clinical judgment of\nanatomy and experience are required to properly\nuse the SpineUs™ system.\nPatient management decisions should not be\nmade based solely on the results of the\nSpineUs™ computer application. The user shall\nretain the ultimate responsibility of ascertaining\nthe measurements based on standard practices\nand clinical judgement.","LOGIQ E10 is intended for use by a qualified\nphysician in a hospital or medical clinic, for\nultrasound evaluation of:\n• Fetal / Obstetrics\n• Abdominal (including Renal,\nGynecology/Pelvic)\n• Pediatric\n• Small Organ (Breast, Testes,\nThyroid)\n• Neonatal Cephalic\n• Adult Cephalic\n• Cardiac (Adult and Pediatric)\n• Peripheral Vascular\n• Musculoskeletal Conventional and\nSuperficial\n• Urology (including Prostate)\n• Transrectal\n• Transvaginal\n• Transesophageal and Intraoperative\n(Abdominal and Vascular)"],["Tracking\ntechnology","3D Optical tracking using GPS-like technology","2D/3D GPS tracking using GPS-like\ntechnology."],["Artificial\nintelligence (AI)\ntechnology","AI-based segmentation of vertebral bone tissue\nin ultrasound image frames.","AI-based tools such as Breast Assistant and\nAuto Lesion Segmentation powered by Koios\nDS™, Auto Doppler Assistant, and OB\nMeasurement Assistant."],["Display","Consumer PC, provided by Verdure Imaging,\nInc.","Mobile console approximately 585 mm wide\n(keyboard), 991 mm deep and 1300 mm high\nthat provides digital acquisition, processing, and\ndisplay capability. The user interface includes a\ncomputer keyboard, specialized controls, 12-\ninch-high resolution color touch screen and\n23.8-inch High Contrast LED LCD monitor"],["Modes of\nOperation","B-mode","B, M, PW Doppler, CW Doppler, Color\nDoppler, Color M Doppler, Power Doppler,\nHarmonic Imaging, Coded Pulse, 3D/4D\nImaging mode, Elastography, Shear Wave\nElastography, Attenuation Imaging and\nCombined modes: B/M, B/Color, B/PWD,\nB/Color/PWD, B/Power/PWD"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p9-t0","doc_id":"K241029","page_num":9,"bbox":[79.25,433.38,533.51,656.25],"n_rows":12,"n_cols":7,"columns":["","Demographic","","","","Development Data",""],"rows":[["","Demographic","","","","Development Data",""],["Gender","","Male (%)","","55.5%","",""],["","","Female (%)","","42.2%","",""],["","","Unknown (%)","","2.3%","",""],["Age","","Mean (years)","","51.2","",""],["","","St. Dev. (years)","","16.6","",""],["Body Mass Index","","Mean (kg/m2)","","27.3","",""],["","","St. Dev. (kg/m2)","","6.5","",""],["Ethnicity","","Caucasian or White (%)","","60.0%","",""],["","","African American or Black (%)","","37.7%","",""],["","","Hispanic / Latino (%)","","0.0%","",""],["","","Other (%)","","2.3%","",""]],"caption_candidate":"age range, body mass index, and ethnicity.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p10-t0","doc_id":"K241029","page_num":10,"bbox":[79.19,233.76,538.67,547.08],"n_rows":21,"n_cols":3,"columns":["Non-Clinical and Clinical Performance Testing Dataset (n = 31)","",""],"rows":[["Non-Clinical and Clinical Performance Testing Dataset (n = 31)","",""],["","Mean (Years)","SD (Years)"],["Age","23.5","16.2"],["","Count","%"],["Sex","",""],["Male","13","41.9"],["Female","18","58.1"],["Body Mass Index","",""],["< 18.5","8","25.8"],["18.5 - 24.5","11","35.5"],["> 24.9","12","38.7"],["Ethnicity","",""],["Caucasian or White","8","25.8"],["African American or Black","11","35.5"],["Hispanic","4","12.9"],["Asian","5","16.1"],["Other","3","9.7"],["Spinal Curvature","",""],["< 20°","20","64.5"],["20° – 40°","7","22.6"],["> 40°","4","12.9"]],"caption_candidate":"separate annotator. These annotations were used as the ground truth for the pixel-based metrics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p10-t1","doc_id":"K241029","page_num":10,"bbox":[79.19,603.54,538.67,719.11],"n_rows":3,"n_cols":12,"columns":["","Name","","","Description","","","Success Criteria","","","Results",""],"rows":[["","Name","","","Description","","","Success Criteria","","","Results",""],["Average\nPercentage of\nTransverse\nProcesses\nIdentified*","","","The number of transverse processes\ncorrectly identified relative to the\ntotal real number of transverse\nprocesses present in the 3D\nreconstruction of the spine","","","> 80 %","","","100.0% [100.0% -\n100.0%]","",""],["Average\nInference\nTime","","","The average time required to process\na single 2D ultrasound image frame\nwith the evaluated Segmentation AI","","","> 25 frames per\nsecond","","","140.05 frames per\nsecond","",""]],"caption_candidate":"Segmentation AI Summary of Non-Clinical Endpoints, Success Criteria, and Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p11-t0","doc_id":"K241029","page_num":11,"bbox":[79.22,69.24,539.21,252.6],"n_rows":2,"n_cols":4,"columns":["","model","",""],"rows":[["","model","",""],["Pixel-Based\nMetrics","Various pixel-based metrics which are\nused to identify relative performance\nof individual image segmentations\n(Sensitivity, Specificity, Precision,\nDice Coefficient, Balanced Accuracy,\n95th Percentile Hausdorff Distance)","N/A","Sensitivity: 41.80%.\nSpecificity: 99.19%.\nPrecision: 38.70%.\nDice Coefficient:\n0.4019.\nBalanced accuracy:\n70.49%.\n95th %ile HD: 12.91\nmm."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p11-t1","doc_id":"K241029","page_num":11,"bbox":[79.22,329.1,539.21,644.04],"n_rows":24,"n_cols":6,"columns":["Patient Subgroup","","Number of Patients","","Percentage of transverse",""],"rows":[["Patient Subgroup","","Number of Patients","","Percentage of transverse",""],["","","","","processes identified (%)",""],["All Patients","","31","100.0 [100.0 – 100.0] %","",""],["","Gender","","","",""],["Male","","13","100.0 [100.0 – 100.0] %","",""],["Female","","18","100.0 [100.0 – 100.0] %","",""],["","Age","","","",""],["<18","","19 [13.1 ± 2.2]","100.0 [100.0 – 100.0] %","",""],["19-50","","7 [29.0 ± 7.3]","100.0 [100.0 – 100.0] %","",""],[">50","","5 [55.6 ± 3.9]","100.0 [100.0 – 100.0] %","",""],["","Body Mass Index","","","",""],["<18.5","","8 [16.7 ± 1.3]","100.0 [100.0 – 100.0] %","",""],["18.5-24.9","","11 [21.4 ± 1.4]","100.0 [100.0 – 100.0] %","",""],[">25.0","","12 [28.7 ± 2.4]","100.0 [100.0 – 100.0] %","",""],["","Ethnicity","","","",""],["Caucasian or White","","8","100.0 [100.0 – 100.0] %","",""],["African American or Black","","11","100.0 [100.0 – 100.0] %","",""],["Hispanic","","4","100.0 [100.0 – 100.0] %","",""],["Asian","","5","100.0 [100.0 – 100.0] %","",""],["Other","","3","100.0 [100.0 – 100.0] %","",""],["","Spinal Curvature","","","",""],["< 20°","","20","100.0 [100.0 – 100.0] %","",""],["20° – 40°","","7","100.0 [100.0 – 100.0] %","",""],["> 40°","","4","100.0 [100.0 – 100.0] %","",""]],"caption_candidate":"in the below table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p12-t0","doc_id":"K241029","page_num":12,"bbox":[79.24,107.24,546.71,482.4],"n_rows":23,"n_cols":9,"columns":["Patient Subgroup","","","Number of Patients","","","Average error (mm, 95% CI)","",""],"rows":[["Patient Subgroup","","","Number of Patients","","","Average error (mm, 95% CI)","",""],["All Patients","","","31","","","2.81 (2.36, 3.25)","",""],["","Sex","","","","","","",""],["Male","","","13","","","2.45 (1.99 - 2.92)","",""],["Female","","","18","","","3.06 (2.35 - 3.76)","",""],["","Age","","","","","","",""],["<18","","","19 [13.1 ± 2.2]","","","3.00 (1.80 - 3.18)","",""],["19-50","","","7 [29.0 ± 7.3]","","","2.49 (1.81 - 3.18)","",""],[">50","","","5 [55.6 ± 3.9]","","","2.54 (1.83 - 3.24)","",""],["","Body Mass Index","","","","","","",""],["<18.5","","","8 [16.7 ± 1.3]","","","2.87 (1.76 - 3.98)","",""],["18.5-24.9","","","11 [21.4 ± 1.4]","","","3.04 (1.94 - 4.13)","",""],[">25.0","","","12 [28.7 ± 2.4]","","","2.55 (1.47 - 3.64)","",""],["","Ethnicity","","","","","","",""],["Caucasian or White","","","8","","","2.59 (1.97 - 3.21)","",""],["African American or Black","","","11","","","3.15 (2.11 - 4.20)","",""],["Hispanic","","","4","","","2.50 (1.81 - 3.19)","",""],["Asian","","","5","","","2.65 (1.80 - 3.49)","",""],["Other","","","3","","","2.82 (1.58 - 4.07)","",""],["","Spinal Curvature","","","","","","",""],["< 20°","","","20","","","2.34 (1.96, 2.71)","",""],["20° – 40°","","","7","","","2.57 (1.83, 3.31)","",""],["> 40°","","","4","","","5.57 (3.52, 7.62)","",""]],"caption_candidate":"shown in the table below for each patient subgroup.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p12-t1","doc_id":"K241029","page_num":12,"bbox":[96.42,640.68,504.69,718.11],"n_rows":4,"n_cols":2,"columns":["Standard","Title of Standard"],"rows":[["Standard","Title of Standard"],["",""],["IEC 60601-1","Medical electrical equipment – Part 1: General requirements for basic\nsafety and essential performance"],["IEC 60601-1-2","Medical electrical equipment – Part 1-2: General requirements for basic\nsafety and essential performance – Collateral Standard: Electromagnetic\nCompatibility – Requirements and tests"]],"caption_candidate":"standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241029-p13-t0","doc_id":"K241029","page_num":13,"bbox":[96.61,69.24,504.72,169.92],"n_rows":4,"n_cols":2,"columns":["IEC 60601-2-37","Medical electrical equipment – Part 2-37: Particular requirements for the\nbasic safety and essential performance of ultrasonic medical diagnostic and\nmonitoring equipment"],"rows":[["IEC 60601-2-37","Medical electrical equipment – Part 2-37: Particular requirements for the\nbasic safety and essential performance of ultrasonic medical diagnostic and\nmonitoring equipment"],["ISO 10993-1","Biological evaluation of medical devices – Part 1: Evaluation and testing\nwithin a risk management process"],["ISO 14971","Medical Devices – Application of Risk Management to Medical Devices"],["NEMA PS 3.1 – 3.20","Digital Imaging and Communications in Medicine (DICOM) Set"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241038-p6-t0","doc_id":"K241038","page_num":6,"bbox":[15.38,132.84,596.51,466.2],"n_rows":10,"n_cols":3,"columns":["Measurement [units]","Description","Display"],"rows":[["Measurement [units]","Description","Display"],["End Diastolic Volume (EDV) [mL]","LV/RV cavity volume at the phase defined as the ED.","• On Screen Data Panel\n• CT Function Report"],["End Systolic Volume (ESV) [mL]","LV/RV blood volume at the phase defined as the ES.","• On Screen Data Panel\n• CT Function Report"],["Stroke Volume (SV) [mL]","The volume of blood pumped out of the LV/RV during\neach cardiac contraction; represented by the\ndifferences of EDV and ESV.","• On Screen Data Panel\n• CT Function Report"],["Ejection Fraction (EF) [%]","Percentage of the total amount of blood in the LV/RV\nthat is pumped out in each cardiac cycle; calculated\nby dividing the SV by EDV.","• On Screen Data Panel\n• CT Function Report"],["Cardiac Output (CO) [L/min]","The amount of blood pumped by the heart in a\nminute; calculated by multiplying the SV and heart\nrate.","• On Screen Data Panel\n• CT Function Report"],["Cardiac Index (CI) [L/min/m2]","An indexed hemodynamic parameter that relates the\nCO in one minute to body-surface area (calculated\nfrom gender, height, and weight); obtained by dividing\nthe CO by BSA.","• On Screen Data Panel\n• CT Function Report"],["End Diastolic Mass (EDM)* [g]","LV myocardial mass at the phase defined as the ED;\ncalculated by multiplying the myocardial volume in ED\nphase with myocardial density (1.05 g/mL).","• On Screen Data Panel\n• CT Function Report"],["End Systolic Mass (ESM)* [g]","LV myocardial mass at the phase defined as the ES;\ncalculated by multiplying the myocardial volume in ES\nphase with myocardial density (1.05 g/mL).","• CT Function Report"],["End Diastolic and End Systolic Mass\n(EDESM)* [g]","Mean LV myocardial mass; calculated as the average\nof the LV EDM and LV ESM.","• CT Function Report"]],"caption_candidate":"Note that measurement may also be indexed to patient BSA or height.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241038-p8-t0","doc_id":"K241038","page_num":8,"bbox":[23.07,114.12,768.93,279.96],"n_rows":5,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","CT Function Module (K241038)","","","Vitrea CT Multi-Chamber CFA (K141302)",""],["","","Manufactured by Circle","","","Manufactured by Vital Images",""],["Intended Use","The Cardiac CT Function Software Application is intended for qualitative and\nquantitative evaluation of cardiovascular CT images in a DICOM Standard\nformat, to calculate and display cardiac function metrics (e.g., end diastolic\nvolume, end systolic volume, stroke volume, ejection fraction, cardiac output,\ncardiac index, and LV myocardial mass).","","","The Vitrea CT Multi-Chamber CFA option is intended to be used with CT studies\nof the heart to assist cardiologists and radiologists in assessing function when\nproducing a cardiac evaluation. The CT Multi-Chamber CFA option includes\nsemi-automatic heart segmentation including three chambers (left ventricle, right\nventricle, and left atrium) segmentation, including identification of long axis and\nmitral valve boundaries across multiple phases; calculation of global metrics,\nincluding end diastolic volume, end systolic volume, stroke volume, ejection\nfraction, cardiac output, cardiac index, stroke index, and myocardial mass; and\ncalculation of regional metrics; including wall motion, percentage of wall\nthickening, regional ejection fraction, and polar plots.","",""],["Indications for Use","The Cardiac CT Function Software Application is indicated to be used with\nmulti-phase, multi-slice cardiovascular CT angiography images to assist\nqualified medical professionals in assessing and evaluating cardiac function.\nCT Function includes manual and semi-automatic heart segmentation of 2\nchambers (LV and RV) and calculation of cardiac function metrics including\nend diastolic volume, end systolic volume, stroke volume, ejection fraction,\ncardiac output, cardiac index, and LV myocardial mass.","","","","",""]],"caption_candidate":"Table 2. Intended use and indications comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241038-p9-t0","doc_id":"K241038","page_num":9,"bbox":[23.89,114.12,768.11,535.08],"n_rows":14,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","","CT Function Module (K241038)","","","Vitrea CT Multi-Chamber CFA (K141302)",""],["","","Manufactured by Circle","","","Manufactured by Vital Images",""],["Device Class","II","","","II","",""],["Product Code(s)","QIH, LLZ","","","LLZ","",""],["Regulation Name","Medical image management and processing system","","","Picture Archiving and Communications System","",""],["Regulation Number","21 CFR 892.2050","","","21 CFR 892.2050","",""],["DICOM Compliant?","Yes","","","Yes","",""],["Input Data Type","Multi-phase, multi-slice cardiac CT angiography images\n(vendor independent)","","","Multi-phase, multi-slice cardiac CT angiography images","",""],["Multi-chamber semi-automatic\nsegmentation","Semi-automatic determination of epicardial and endocardial contours, via\nsegmentation of the LV cavity, LV myocardium, and RV cavity in the ED and\nES phases using Machine Learning techniques.","","","Semi-automatic determination of epicardial and endocardial\ncontours, via segmentation of LV chamber and myocardium, RV\nchamber, and LA chamber.","",""],["Tools","• Provides manual contour editing tools if adjustments are needed\n• Default views automatically aligned to contours to aid typical image\nreview process\n• Report","","","• Provides image editing tools if adjustments are needed\n• Visualization presets and automated steps for typical image\nreview procedures\n• Report","",""],["Views","• 2D image viewing with real-time Window/Level, Zoom, and Pan\n• 3D and Multi-Planar Reformatting (MPR) view\n• Automatic industry standard oblique views of the heart (SAX, 2\nchamber, and 4 chamber)\n• Volume Rendering\n• Phase Navigator\n• Review Heart in Motion","","","• 2D image viewing with real-time Window/Level, Zoom, and Pan\n• 3D and Multi-Planar Reformatting (MPR) view\n• Maximum Intensity Projection\n• Automatic industry standard Oblique views of the heart\n• Volume Rendering\n• Phase Navigator\n• Review Heart in Motion","",""],["Identification of cardiac phases\nand landmarks in loaded DICOM\ndatasets","• Automatic determination of ED and ES phases by volume\n• Manually select/correct ED\n• Manually select/correct ES\n• Automatically identifies/orients to long axis view across multiple phases\n• Automatically identifies/orients basal cut plane close to the mitral valve","","","• Automatic determination of ED and ES phases by volume\n• Provides ability to select Diastolic phase\n• Provides ability to select Systolic phase\n• Automatically identifies the long axis across multiple phases\n• Automatically identifies the plane of the Mitral valve","",""],["Automated calculation and\ndisplay of cardiac parameters","• End Diastolic Volume (EDV)\n• End Systolic Volume (ESV)\n• Stroke Volume (SV)\n• Ejection Fraction (EF)\n• Cardiac Output (CO)\n• Myocardial Mass (EDM, ESM, EDESM) [in the LV Only]","","","• End Diastolic Volume (EDV)\n• End Systolic Volume (ESV)\n• Stroke Volume (SV)\n• Stroke Index (SI)\n• Ejection Fraction (EF)\n• Cardiac Output (CO)","",""]],"caption_candidate":"Table 3. Regulatory and technological features comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241038-p10-t0","doc_id":"K241038","page_num":10,"bbox":[23.91,102.0,768.09,300.36],"n_rows":5,"n_cols":7,"columns":["Feature","","Subject Device","","","Predicate Device",""],"rows":[["Feature","","Subject Device","","","Predicate Device",""],["","","CT Function Module (K241038)","","","Vitrea CT Multi-Chamber CFA (K141302)",""],["","","Manufactured by Circle","","","Manufactured by Vital Images",""],["","• Cardiac Index (CI)","","","• Myocardial Mass\n• Wall Motion\n• Percent Wall Thickening\n• Myocardial Volume (MV)\n• Myocardial Index\n• Myocardial Mass Index\n• Regional Ejection Fraction (EF)\n• Outputs a Polar Map\n• Time/Volume Graph\n• Cardiac Index (CI)\n• Regurgitation Fraction\n• Cyclic Volume Change\n• Reservoir Volume","",""],["Operating System","Microsoft Windows\nApple macOS","","","Microsoft Windows","",""]],"caption_candidate":"CT Function Module 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241079-p7-t0","doc_id":"K241079","page_num":7,"bbox":[99.36,396.36,531.72,668.52],"n_rows":6,"n_cols":4,"columns":["","Proposed device\nuCT 780 with uWS-CT-Dual\nEnergy Analysis","Predict device\nuCT 760/780 with uWS-\nCT-Dual Energy Analysis\n(K230162)","Discussion"],"rows":[["","Proposed device\nuCT 780 with uWS-CT-Dual\nEnergy Analysis","Predict device\nuCT 760/780 with uWS-\nCT-Dual Energy Analysis\n(K230162)","Discussion"],["DELTA\n(Deep\nRecon)","AI-based deep learning\nreconstruction algorithm.","AI-based deep learning\nreconstruction algorithm.","Same"],["Applicable\nBody Parts","head, chest, abdomen, cardiac and\nvascular CT applications for adults","head, chest, abdomen,\ncardiac and vascular CT\napplications for adults","Same"],["User\nInterface","5 noise reduction levels.","4 noise reduction levels.","The user interface\nincreased the choice for the\nnoise reduction level. This\nwill not introduce safety or\neffectiveness issues."],["Dataset Size","The new dataset was increased to\n127 cases compared with the\noriginal dataset.","Original Dataset","Dataset was increased .to\nimprove robustness of the\nalgorithm. The difference\nwill not introduce safety or\neffectiveness issues."],["Clinical\nworkflow","Select recon type and strength\n(noise index level).","Select recon type and\nstrength (noise index level).","Same"]],"caption_candidate":"between the proposed and predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241079-p8-t0","doc_id":"K241079","page_num":8,"bbox":[99.36,81.96,531.72,327.24],"n_rows":2,"n_cols":4,"columns":["Phantom test"," Phantom test for dose\nreduction, LCD, noise and\nspatial resolution improving\ntest.\n Basic IQ performance test\nincluding HU value on water\nphantom, thickness section\ntest.\n Additional HU value test on\ntissue-mimicking phantom,\nnoise spectrum power test."," Phantom test for dose\nreduction, LCD, noise\nand spatial resolution\nimproving test.\n Basic IQ performance\ntest including HU value\non water phantom,\nthickness section test.","Adding more phantom\ntests, including HU value\ntest on tissue-mimicking\nphantom and noise\nspectrum power test to give\na more comprehensive tests\nresults. The difference will\nnot introduce safety and\neffectiveness issues."],"rows":[["Phantom test"," Phantom test for dose\nreduction, LCD, noise and\nspatial resolution improving\ntest.\n Basic IQ performance test\nincluding HU value on water\nphantom, thickness section\ntest.\n Additional HU value test on\ntissue-mimicking phantom,\nnoise spectrum power test."," Phantom test for dose\nreduction, LCD, noise\nand spatial resolution\nimproving test.\n Basic IQ performance\ntest including HU value\non water phantom,\nthickness section test.","Adding more phantom\ntests, including HU value\ntest on tissue-mimicking\nphantom and noise\nspectrum power test to give\na more comprehensive tests\nresults. The difference will\nnot introduce safety and\neffectiveness issues."],["Conclusion","DELTA is able to generate CT\nimages at lower dose in the low\ndose simulation validation and\ngenerate equivalent or better\nimage quality compared with FBP\nin the clinical scenarios of real\nscan under a variety of dose levels.","DELTA is able to generate\nCT images with lower image\nnoise and improve low\ncontrast detectability and\nalso to reduce the dose\nrequired for diagnostic CT\nimaging.","Substantially Equivalent.\nThe function of DELTA is\noptimized in the proposed\ndevice, which improved the\nalgorithm framework. The\ndifference will not\nintroduce safety and\neffectiveness issues."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241079-p10-t0","doc_id":"K241079","page_num":10,"bbox":[138.36,164.16,518.88,384.72],"n_rows":5,"n_cols":5,"columns":["Body Part","Number","Age","Sex","Dose Distribution"],"rows":[["Body Part","Number","Age","Sex","Dose Distribution"],["Head","15","27-82","6 male\n9 female","≥70%: 10\n30%-70%: 3\n<30%: 2"],["Chest","15","46-81","9 male\n6 female","≥70%: 3\n30%-70%: 6\n<30%: 6"],["Abdomen","15","30-87","10 male\n5 female","≥70%: 5\n30%-70% 5\n<30% 5"],["Cardiac","15","29-75","7 male\n8 female","≥70%: 7\n30%-70% 8\n<30% 0"]],"caption_candidate":"The distribution of validation and test data was shown below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241098-p4-t0","doc_id":"K241098","page_num":4,"bbox":[100.8,142.81,400.97,659.7],"n_rows":43,"n_cols":4,"columns":["1. S","ubmitter","",""],"rows":[["1. S","ubmitter","",""],["","","",""],["","Name:","","CorTechs Labs, Inc"],["","","",""],["","Address:","","5060 Shoreham Place, St"],["","","",""],["","","","San Diego, CA 92122"],["","","",""],["","Contact Person:","","Kora Marinkovic"],["","","",""],["","Telephone Number:","","(858) 459-9700"],["","","",""],["","Fax Number:","","(858) 459-9705"],["","","",""],["","E-mail:","","koram@cortechslabs.com"],["","","",""],["","Date Prepared:","","8/21/2024"],["","","",""],["2. D","evice","",""],["","","",""],["","Device Trade Name:","N","euroQuant"],["","","",""],["","Common Name:","M","edical Image Processing S"],["","","",""],["","Classification Name:","S","ystem, Image Processing,"],["","","",""],["","Regulation Number:","21","CFR 892.2050"],["","","",""],["","Regulation Description:","M","edical image management"],["","","",""],["","Product Code:","Q","IH, LLZ"],["","","",""],["","Classification Panel:","R","adiology"],["","","",""],["3. P","redicate Device","",""],["","","",""],["","Device:","N","euroQuant"],["","","",""],["","510(k) Number","K","170981"],["","","",""],["","Manufacturer","C","orTechs Labs, Inc"],["","","",""],["","Product Code:","LL","Z"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241098-p4-t1","doc_id":"K241098","page_num":4,"bbox":[119.04,184.8,525.12,334.56],"n_rows":7,"n_cols":2,"columns":["Name:","CorTechs Labs, Inc"],"rows":[["Name:","CorTechs Labs, Inc"],["Address:","5060 Shoreham Place, Ste 240\nSan Diego, CA 92122"],["Contact Person:","Kora Marinkovic"],["Telephone Number:","(858) 459-9700"],["Fax Number:","(858) 459-9705"],["E-mail:","koram@cortechslabs.com"],["Date Prepared:","8/21/2024"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241098-p4-t2","doc_id":"K241098","page_num":4,"bbox":[119.04,393.36,525.12,527.28],"n_rows":7,"n_cols":2,"columns":["Device Trade Name:","NeuroQuant"],"rows":[["Device Trade Name:","NeuroQuant"],["Common Name:","Medical Image Processing Software"],["Classification Name:","System, Image Processing, Radiological"],["Regulation Number:","21 CFR 892.2050"],["Regulation Description:","Medical image management and processing system"],["Product Code:","QIH, LLZ"],["Classification Panel:","Radiology"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241098-p4-t3","doc_id":"K241098","page_num":4,"bbox":[119.04,586.32,525.12,662.88],"n_rows":4,"n_cols":2,"columns":["Device:","NeuroQuant"],"rows":[["Device:","NeuroQuant"],["510(k) Number","K170981"],["Manufacturer","CorTechs Labs, Inc"],["Product Code:","LLZ"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241098-p6-t0","doc_id":"K241098","page_num":6,"bbox":[87.36,117.96,564.2,704.64],"n_rows":12,"n_cols":3,"columns":["Device Name","NeuroQuant (Predicate, K170981)","NeuroQuant (Current Submission)"],"rows":[["Device Name","NeuroQuant (Predicate, K170981)","NeuroQuant (Current Submission)"],["","",""],["Classification","Class II","Class II"],["Product Code","LLZ","QIH, LLZ"],["Indications for\nUse","Automatic labeling, visualization and volumetric\nquantification of segmentable brain structures\nand lesions from a set of MR images.\nVolumetric data may be compared to reference\npercentile data","Automatic labeling, visualization and volumetric\nquantification of segmentable brain structures\nand lesions from a set of MR images. Volumetric\ndata may be compared to reference percentile\ndata"],["Design and\nIncorporated\nTechnology","• Automated measurement of brain tissue\nvolumes and structures and lesions\n• Automatic segmentation and quantification of\nbrain structures using a dynamic probabilistic\nneuroanatomical atlas, with age and gender\nspecificity, based on the MR image intensity","• Automated measurement of brain tissue\nvolumes and structures and lesions\n• Automatic segmentation and quantification of\nbrain structures and lesions using a dynamic\nprobabilistic neuroanatomical atlas, with age\nand gender specificity, based on the MR image\nintensity and static deep-learning technologies"],["Physical\ncharacteristics","• Software package\n• Operates on off-the-shelf hardware (multiple\nvendors)","• Software package\n• Operates on off-the-shelf hardware (multiple\nvendors)"],["Operating\nSystem","Supports Linux, Mac OS X and Windows.","Supports Linux, Mac OS X and Windows."],["Processing\nArchitecture","Automated internal pipeline that performs:\n-artifact correction\n-segmentation\n-lesion quantification\n-volume calculation\n-report generation","Automated internal pipeline that performs:\n-artifact correction\n-segmentation\n-lesion quantification\n-volume calculation\n-report generation"],["Data Source","• MRI scanner: 3D T1 and T2 FLAIR MRI scans\nacquired with specified protocols\n• NeuroQuant Supports DICOM format as input","• MRI scanner: 3D T1 and T2 FLAIR and T2*\nGRE / SWI MRI scans acquired with specified\nprotocols\n• NeuroQuant Supports DICOM format as input"],["Output","• Provides volumetric measurements of brain\nstructures and lesions\n• Includes segmented color overlays and\nmorphometric reports\n• Automatically compares results to reference\npercentile data and to prior scans when\navailable\n• Supports DICOM format as output of results\nthat can be displayed on DICOM workstations\nand Picture Archive and Communications\nSystems","• Provides volumetric measurements of brain\nstructures and lesions\n• Includes segmented color overlays and\nmorphometric reports\n• Automatically compares results to reference\npercentile data and to prior scans when\navailable\n• Supports DICOM format as output of results\nthat can be displayed on DICOM workstations\nand Picture Archive and Communications\nSystems"],["Safety","Automated quality control functions:\n-Tissue contrast check\n-Scan protocol verification\n-Atlas alignment check\nResults must be reviewed by a trained physician","Automated quality control functions:\n-Tissue contrast check\n-Scan protocol verification\n-Atlas alignment check\nResults must be reviewed by a trained physician"]],"caption_candidate":"Summary Comparison Table for the device and predicate device (K170981):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p8-t0","doc_id":"K241108","page_num":8,"bbox":[67.26,87.36,535.02,588.3],"n_rows":11,"n_cols":3,"columns":["","Predicate Device\nCoLumbo (K220497)","Subject Device\nRAI"],"rows":[["","Predicate Device\nCoLumbo (K220497)","Subject Device\nRAI"],["Intended User","Radiologist and neuro- and spine-\nsurgeons","Radiologist and neuro- and spine-\nsurgeons"],["Intended Patient\nPopulation","Patients aged 18 years or older,\nundergoing clinical lumbar spine MR\nexams.\nCoLumbo does not support DICOM\nimages of patients that are pregnant,\nundergo MRI scan with contrast media,\nor have post-operational complications,\nscoliosis, tumors, infections, fractures.","Patients aged 18 years or older,\nundergoing clinical lumbar spine MR\nexams.\nRAI does not support DICOM images\nof patients that are pregnant, undergo\nMRI scan with contrast media, or have\npost-operational complications,\nscoliosis, tumors, infections, fractures."],["Supported Body\nPart","Lumbar spine","Lumbar spine"],["Segmentation","Software automatically generates\nsegmentations of anatomical features of\ninterest","Software automatically generates\nsegmentations of anatomical features of\ninterest"],["Measurement","Software automatically generates\nmeasurements of interest","Software automatically generates\nmeasurements of interest"],["Threshold-Based\nOut-of-Range\nMeasurements","Software automatically highlights and\nreports out-of-range measurements\nbased on predetermined thresholds","Software does not automatically\nhighlight or report any out-of-range\nmeasurements"],["Reporting","Exportation of measurement results to a\nwritten report for user's review, revise\nand approval","Exportation of measurement results in\nboth a DICOM Structured Report and\na .docx file for users to review and to\nuse full or partial list of software-\ngenerated measurements to prepare\ntheir own radiology report."],["SaMD","Yes","Yes"],["Algorithm","Deep Convolutional Image-to-Image\nNeural Network","Convolutional Neural Network"],["Supported\nModality","MR","MR"]],"caption_candidate":"Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p9-t0","doc_id":"K241108","page_num":9,"bbox":[81.25,211.52,551.32,412.14],"n_rows":7,"n_cols":4,"columns":["","Recognition","","Standard"],"rows":[["","Recognition","","Standard"],["","#","",""],["13-79","","","IEC 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION, Medical device software\n— Software life cycle processes"],["5-125","","","ISO 14971 Third Edition 2019-12, Medical devices — Application of risk management\nto medical devices"],["5-129","","","IEC 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION, Medical devices —\nPart 1: Application of usability engineering to medical devices"],["5-134","","","ISO 15223-1 Fourth edition 2021-07, Medical devices – Symbols to be used with\ninformation to be supplied by the manufacturer – Part 1: General requirements"],["12-349","","","NEMA PS 3.1 – 3.20 2022d, Digital Imaging and Communications in Medicine\n(DICOM) Set"]],"caption_candidate":"Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p10-t0","doc_id":"K241108","page_num":10,"bbox":[85.02,155.4,495.7,485.28],"n_rows":11,"n_cols":3,"columns":["","Number of subjects","Percent of total"],"rows":[["","Number of subjects","Percent of total"],["Total number of subjects","200","100%"],["Gender, Male","92","46%"],["Gender, Female","108","54%"],["Age, 18 - 21","43","21.5%"],["Age, 22 - 50","89","44.5%"],["Age, 51 - 100","68","34%"],["Racial, Caucasian","107","53.5%"],["Racial, Black/African American","16","8%"],["Racial, Hispanic","58","29%"],["Racial, Asian or other","19","9.5%"]],"caption_candidate":"Study Subjects","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p10-t1","doc_id":"K241108","page_num":10,"bbox":[85.02,542.04,495.7,733.92],"n_rows":5,"n_cols":5,"columns":["Manufacturer","Model name","Tesla","Number of\nMRIs","Percent"],"rows":[["Manufacturer","Model name","Tesla","Number of\nMRIs","Percent"],["GE Medical\nSystems","GENESIS SIGNA","1.5","5","2.5%"],["","SIGNA Creator","1.5","1","0.5%"],["","SIGNA EXCITE","1.5","10","5%"],["","Signa HDxt","1.5","21","10.5%"]],"caption_candidate":"The 200 MR studies were acquired on MRI imaging systems made by five (5) manufacturers.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p11-t0","doc_id":"K241108","page_num":11,"bbox":[85.02,67.38,495.0,401.22],"n_rows":9,"n_cols":5,"columns":["Philips","Prodiva CS","1.5","5","2.5%"],"rows":[["Philips","Prodiva CS","1.5","5","2.5%"],["Philips Medical\nSystems","Achieva","1.5","1","0.5%"],["","Ingenia","1.5","11","5.5%"],["","Panorama 0.23 T\nPower","0.23","21","10.5%"],["SIEMENS","Espree","1.5","25","12.5%"],["","MAGNETOM Altea","1.5","21","10.5%"],["","Skyra","3","21","10.5%"],["","Symphony","1.5","7","3.5%"],["TOSHIBA MEC","MRT200PP2","1.5","51","25.5%"]],"caption_candidate":"RAI 510(k) Premarket Notification Remedy Logic Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p11-t1","doc_id":"K241108","page_num":11,"bbox":[121.02,665.1,486.3,736.08],"n_rows":3,"n_cols":2,"columns":["Measurement","MAE limit"],"rows":[["Measurement","MAE limit"],["Dural Sac Area (Axial)","20 mm2"],["Spinal Canal Area (Axial)","30 mm2"]],"caption_candidate":"limit) for each measurement listed below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p12-t0","doc_id":"K241108","page_num":12,"bbox":[124.24,67.5,486.3,114.84],"n_rows":2,"n_cols":2,"columns":["Lordotic Angle (Sagittal)","6 °"],"rows":[["Lordotic Angle (Sagittal)","6 °"],["Vertebral Body Slippage (Sagittal)","2 mm"]],"caption_candidate":"RAI 510(k) Premarket Notification Remedy Logic Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p12-t1","doc_id":"K241108","page_num":12,"bbox":[124.24,178.38,490.5,405.66],"n_rows":15,"n_cols":2,"columns":["Anatomical structure","MDC limit"],"rows":[["Anatomical structure","MDC limit"],["Artery (Axial)","0.8"],["Disc (Axial)","0.7"],["Disc (Sagittal)","0.7"],["Disc Material Outside IV Space (Axial)","0.7"],["Dural Sac (Axial)","0.8"],["Kidney (Axial)","0.8"],["Ligamentum Flavum (Axial)","0.7"],["Muscle (Axial)","0.8"],["Sacrum (Sagittal)","0.8"],["Spinal Canal (Axial)","0.8"],["Spinal Canal (Sagittal)","0.8"],["Vein (Axial)","0.8"],["Vertebral Arch (Axial)","0.8"],["Vertebral Body (Sagittal)","0.8"]],"caption_candidate":"limit (MDC Limit) for each segmentation listed below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p12-t2","doc_id":"K241108","page_num":12,"bbox":[124.24,468.9,490.5,730.74],"n_rows":10,"n_cols":2,"columns":["Measurement","MAE limit"],"rows":[["Measurement","MAE limit"],["Anterior Disc Height (Sagittal)","2 mm"],["Anterior Vertebral Body Height (Sagittal)","2 mm"],["Dural Sac Anterior-Posterior Diameter\n(Axial)","2 mm"],["Dural Sac Transverse Diameter (Axial)","2 mm"],["Middle Disc Height (Sagittal)","2 mm"],["Middle Vertebral Body Height (Sagittal)","2 mm"],["Posterior Disc Height (Sagittal)","2 mm"],["Posterior Vertebral Body Height (Sagittal)","2 mm"],["Spinal Canal Anterior-Posterior Diameter\n(Axial)","2 mm"]],"caption_candidate":"each measurement listed below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p13-t0","doc_id":"K241108","page_num":13,"bbox":[87.12,129.3,528.0,317.52],"n_rows":5,"n_cols":6,"columns":["Measurement","Mean Absolute\nError (MAE)","95% Confidence\nInterval\nLower Bound","95%\nConfidence\nInterval\nUpper Bound","MAE\nLimit","Success"],"rows":[["Measurement","Mean Absolute\nError (MAE)","95% Confidence\nInterval\nLower Bound","95%\nConfidence\nInterval\nUpper Bound","MAE\nLimit","Success"],["Dural Sac Area\n(Axial)","17.2 mm2","16.5 mm2","17.9 mm2","20 mm2","Yes"],["Spinal Canal\nArea (Axial)","23.3 mm2","22.3 mm2","24.3 mm2","30 mm2","Yes"],["Lordotic Angle\n(Sagittal)","3.4 °","2,9 °","3,9 °","6 °","Yes"],["Vertebral Body\nSlippage\n(Sagittal)","0.6 mm","0,5 mm","0,8 mm","2 mm","Yes"]],"caption_candidate":"Primary Endpoints Results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p13-t1","doc_id":"K241108","page_num":13,"bbox":[87.12,355.56,528.0,734.7],"n_rows":14,"n_cols":6,"columns":["Anatomical\nStructure\nSegmentation","Mean Dice\nCoefficient (MDC)","95% Confidence\nInterval\nLower Bound","95% Confidence\nInterval\nUpper Bound","MDC\nLimit","Success"],"rows":[["Anatomical\nStructure\nSegmentation","Mean Dice\nCoefficient (MDC)","95% Confidence\nInterval\nLower Bound","95% Confidence\nInterval\nUpper Bound","MDC\nLimit","Success"],["Artery (Axial)","0.866","0.861","0.871","0.8","Yes"],["Disc (Axial)","0.806","0.796","0.815","0.7","Yes"],["Disc (Sagittal)","0.914","0.910","0.918","0.7","Yes"],["Disc Material\nOutside IV\nSpace (Axial)","0.803","0.793","0.812","0.7","Yes"],["Dural Sac\n(Axial)","0.926","0.924","0.929","0.8","Yes"],["Kidney (Axial)","0.879","0.872","0.886","0.8","Yes"],["Ligamentum\nFlavum (Axial)","0.740","0.736","0.744","0.7","Yes"],["Muscle (Axial)","0.946","0.945","0.947","0.8","Yes"],["Sacrum\n(Sagittal)","0.925","0.923","0.928","0.8","Yes"],["Spinal Canal\n(Axial)","0.942","0.941","0.944","0.8","Yes"],["Spinal Canal\n(Sagittal)","0.871","0.865","0.877","0.8","Yes"],["Vein (Axial)","0.821","0.815","0.827","0.8","Yes"],["Vertebral Arch","0.846","0.843","0.850","0.8","Yes"]],"caption_candidate":"Secondary Endpoints Results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p14-t0","doc_id":"K241108","page_num":14,"bbox":[85.29,67.38,530.19,117.96],"n_rows":2,"n_cols":6,"columns":["(Axial)","","","","",""],"rows":[["(Axial)","","","","",""],["Vertebral Body\n(Sagittal)","0.900","0.894","0.905","0.8","Yes"]],"caption_candidate":"RAI 510(k) Premarket Notification Remedy Logic Inc.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241108-p14-t1","doc_id":"K241108","page_num":14,"bbox":[85.29,137.28,530.19,644.94],"n_rows":11,"n_cols":6,"columns":["Measurement","Mean Absolute\nError (MAE)","95% confidence\ninterval\nLower bound","95% confidence\ninterval\nUpper bound","MAE\nlimit","Success"],"rows":[["Measurement","Mean Absolute\nError (MAE)","95% confidence\ninterval\nLower bound","95% confidence\ninterval\nUpper bound","MAE\nlimit","Success"],["Anterior Disc\nHeight (Sagittal)","1.3 mm","1.18 mm","1.32 mm","2 mm","Yes"],["Anterior\nVertebral Body\nHeight (Sagittal)","1.6 mm","1.48 mm","1.81 mm","2 mm","Yes"],["Dural Sac\nAnterior-\nPosterior\nDiameter\n(Axial)","1.49 mm","1.46 mm","1.52 mm","2 mm","Yes"],["Dural Sac\nTransverse\nDiameter\n(Axial)","1.15 mm","1.09 mm","1.22 mm","2 mm","Yes"],["Middle Disc\nHeight (Sagittal)","1 mm","0.95 mm","1.04 mm","2 mm","Yes"],["Middle\nVertebral Body\nHeight (Sagittal)","1.3 mm","1.21 mm","1.33 mm","2 mm","Yes"],["Posterior Disc\nHeight (Sagittal)","1 mm","0.95 mm","1.07 mm","2 mm","Yes"],["Posterior\nVertebral Body\nHeight (Sagittal)","1.6 mm","1.44 mm","1.72 mm","2 mm","Yes"],["Spinal Canal\nAnterior-\nPosterior\nDiameter\n(Axial)","0.81 mm","1.78 mm","0.83 mm","2 mm","Yes"],["Spinal Canal\nTransverse\nDiameter\n(Axial)","1.74 mm","1.64 mm","1.85 mm","2 mm","Yes"]],"caption_candidate":"(Sagittal) 0.900 0.894 0.905 0.8 Yes","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241112-p6-t0","doc_id":"K241112","page_num":6,"bbox":[72.4,92.46,539.6,718.56],"n_rows":6,"n_cols":5,"columns":["","","Predicate Device:","","Subject Device:\nBriefCase-Quantification"],"rows":[["","","Predicate Device:","","Subject Device:\nBriefCase-Quantification"],["","","BriefCase-Quantification","",""],["","","(K230534)","",""],["Indications for Use/ Intended Use","BriefCase-Quantification is a\nradiological image\nmanagement and\nprocessing system software\nindicated for use in the\nanalysis of CT exams with\ncontrast, that include the\nabdominal aorta, in adults or\ntransitional adolescents\naged 18 and older.\nThe device is intended to\nassist appropriately trained\nmedical specialists by\nproviding the user with the\nmaximum abdominal aortic\naxial diameter measurement\nof cases that include the\nabdominal aorta (M-AbdAo).\nBriefCase-Quantification is\nindicated to evaluate normal\nand aneurysmal abdominal\naortas and is not intended to\nevaluate post-operative\naortas.\nThe BriefCase-\nQuantification results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making or\notherwise preclude clinical\nassessment of cases. These\nmeasurements are\nunofficial, are not final, and\nare subject to change after\nreview by a radiologist. For\nfinal clinically approved\nmeasurements, please refer\nto the official radiology\nreport. Clinicians are\nresponsible for viewing full\nimages per the standard of\ncare.","","","BriefCase-Quantification is a\nradiological image\nmanagement and\nprocessing system software\nindicated for use in the\nanalysis of CT exams with\ncontrast, that include the\nabdominal aorta, in adults or\ntransitional adolescents\naged 18 and older.\nThe device is intended to\nassist appropriately trained\nmedical specialists by\nproviding the user with the\nmaximum abdominal aortic\ndiameter measurement of\ncases that include the\nabdominal aorta (M-AbdAo).\nBriefCase-Quantification is\nindicated to evaluate normal\nand aneurysmal abdominal\naortas and is not intended to\nevaluate post-operative\naortas.\nThe BriefCase-\nQuantification results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making or\notherwise preclude clinical\nassessment of cases. These\nmeasurements are\nunofficial, are not final, and\nare subject to change after\nreview by a radiologist. For\nfinal clinically approved\nmeasurements, please refer\nto the official radiology\nreport. Clinicians are\nresponsible for viewing full\nimages per the standard of\ncare."],["User Population","Appropriately trained\nmedical specialists.","","","Appropriately trained\nmedical specialists."],["Anatomical region of interest","","","",""]],"caption_candidate":"Table 1: Comparison between Predicate and Subject Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241112-p7-t0","doc_id":"K241112","page_num":7,"bbox":[72.38,72.54,539.62,659.36],"n_rows":12,"n_cols":5,"columns":["","","Predicate Device:","","Subject Device:\nBriefCase-Quantification"],"rows":[["","","Predicate Device:","","Subject Device:\nBriefCase-Quantification"],["","","BriefCase-Quantification","",""],["","","(K230534)","",""],["Data acquisition protocol","CT exams with contrast that\ninclude the abdominal aorta","","","CT exams with contrast that\ninclude the abdominal aorta"],["Diameter Measurement","Yes","","","Yes"],["Measurement Method","Axial","","","Orthogonal"],["Images Format","DICOM","","","DICOM"],["Interference with\nstandard workflow","No","","","No"],["Preview images","Presentation of a\ncompressed, grayscale\npreview image that is\ncaptioned “Not for diagnostic\nuse”.","","","Presentation of a\ncompressed, grayscale\npreview image that is\ncaptioned “Not for diagnostic\nuse”."],["Output","Maximum abdominal aortic\ndiameter with preview image\nthat contains the\nmeasurement and key slice\nwith the long and short axis\nof the aorta in the slice with\nthe maximum measurement.","","","Maximum abdominal aortic\ndiameter with preview image\nthat contains the\nmeasurement and key slice\nwith the long and short axis\nof the aorta in the\nreformatted slice composed\nof the plane that is\northogonal to the blood flow\nand not on the original axial\nslice."],["Algorithm","Artificial intelligence\nalgorithm with database of\nimages","","","Artificial intelligence\nalgorithm with database of\nimages"],["Structure","- BriefCase-Quantification is\nhosted on a cloud server,\nanalyzes applicable CT\nimages that are forwarded to\nBriefCase-Quantification.\n- The results of the analysis\nare exported in DICOM\nformat, and are sent to a\nPACS destination for review\nby medical specialists, to\nassist in the measurement of\nthe abdominal aorta.","","","- BriefCase-Quantification is\nhosted on a cloud server,\nanalyzes applicable CT\nimages that are forwarded to\nBriefCase-Quantification.\n- The results of the analysis\nare exported in DICOM\nformat, and are sent to a\nPACS destination for review\nby medical specialists, to\nassist in the measurement of\nthe abdominal aorta."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241112-p8-t0","doc_id":"K241112","page_num":8,"bbox":[130.63,433.44,481.42,484.83],"n_rows":5,"n_cols":21,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","","N",""],["","","","62.8","","","19.6","","","18.0","","","67.5","","","90.0","","","","",""],["","Age","","","","","","","","","","","","","","","","","162","",""],["","(Years)","","","","","","","","","","","","","","","","","","",""],["","","","","","","","","","","","","","","","","","","","",""]],"caption_candidate":"Table 2. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241112-p8-t1","doc_id":"K241112","page_num":8,"bbox":[232.15,513.48,379.78,594.1],"n_rows":7,"n_cols":9,"columns":["","Gender","","","N*","","","%",""],"rows":[["","Gender","","","N*","","","%",""],["","","","76","","","46.9%","",""],["","Male","","","","","","",""],["","","","","","","","",""],["","","","86","","","53.1%","",""],["","Female","","","","","","",""],["","","","","","","","",""]],"caption_candidate":"Table 3. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241112-p9-t0","doc_id":"K241112","page_num":9,"bbox":[232.47,85.56,379.42,246.96],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["Philips","","","43","","","26.5%","",""],["Canon","","","41","","","25.3%","",""],["Siemens","","","39","","","24.1%","",""],["GE","","","39","","","24.1%","",""],["","Total","","","162","","","100%",""]],"caption_candidate":"Table 4. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241121-p4-t0","doc_id":"K241121","page_num":4,"bbox":[72.36,123.88,540.47,280.52],"n_rows":10,"n_cols":4,"columns":["","Applicant Name","","Microstructure Imaging, Inc."],"rows":[["","Applicant Name","","Microstructure Imaging, Inc."],["Applicant Address","Applicant Address","","370 Jay St, 7th Floor\nBrooklyn NY 11201 United States"],["","Applicant Contact","","Gregory Lemberskiy, PhD"],["","Applicant Contact Email","","gregory.lemberskiy@micsi.com"],["","Correspondent Name","","Enzyme Corporation"],["Correspondent Address","Correspondent Address","","611 Gateway Blvd, Suite 120\nSouth San Francisco CA 94080 United States"],["","Correspondent Contact Telephone","","(415)579-1152"],["","Correspondent Contact","","Michelle Rubin-Onur, PhD"],["","Correspondent Contact Email","","mrubinonur@enzyme.com"],["","Date","","July 16, 2024"]],"caption_candidate":"Contact Details 21 CFR 807.92(a)(1)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241121-p4-t1","doc_id":"K241121","page_num":4,"bbox":[72.36,306.43,540.47,372.04],"n_rows":5,"n_cols":4,"columns":["","Device Trade Name","","MICSI-RMT"],"rows":[["","Device Trade Name","","MICSI-RMT"],["","Common Name","","Medical image management and processing system"],["","Classification Name","","System, Image Processing, Radiological"],["","Regulation Number","","892.2050"],["","Product Code(s)","","LLZ"]],"caption_candidate":"Device Name 21 CFR 807.92(a)(2)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241121-p4-t2","doc_id":"K241121","page_num":4,"bbox":[72.36,398.02,540.47,424.12],"n_rows":2,"n_cols":9,"columns":["","Predicate #","","","Predicate Trade Name","","","Product Code",""],"rows":[["","Predicate #","","","Predicate Trade Name","","","Product Code",""],["K191688","","","SubtleMR","","","LLZ","",""]],"caption_candidate":"Legally Marketed Predicate Device 21 CFR 807.92(a)(3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p7-t0","doc_id":"K241166","page_num":7,"bbox":[72.27,225.68,724.08,527.22],"n_rows":10,"n_cols":7,"columns":["ITEM","Proposed Device\nuCT 550","Predicate Device (K200016)\nuCT 530, uCT 550","","Reference Device #1","","Discussion of\nDifferences"],"rows":[["ITEM","Proposed Device\nuCT 550","Predicate Device (K200016)\nuCT 530, uCT 550","","Reference Device #1","","Discussion of\nDifferences"],["","","","","(K230162)","",""],["","","","","uCT 760 with uWS-","",""],["","","","","CT-Dual Energy","",""],["","","","","Analysis,","",""],["","","","","uCT 780 with uWS-","",""],["","","","","CT-Dual Energy","",""],["","","","","Analysis","",""],["Gantry"," Rotation speed: up to\n0.5s/rotation;\n 70cm bore"," Rotation speed: up to\n0.5s/rotation;\n 70cm bore","--","","","Same"],["Detector"," 22mm Detector\n Material: Solid-state GOS\n 40 rows,\n 864 channels/row\n Size of detector element in Z-\nplane: 0.55mm"," 22mm Detector\n Material: Solid-state GOS\n 40 rows,\n 864 channels/row\n Size of detector element in Z-\nplane: 0.55mm","--","","","Same"]],"caption_candidate":"reference device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p8-t0","doc_id":"K241166","page_num":8,"bbox":[72.24,111.98,724.12,512.28],"n_rows":7,"n_cols":5,"columns":["X-ray Tube"," 70, 80, 100, 120, 140 kV\n mA range: 10 mA-420 mA\n Anode heat capacity: 5.3MHU\n Maximum anode heat\ndissipation:\n9.6kW(815kHU/min)\n Focal spot size:\n0.5mm × 1.0mm\n1.0mm × 1.0mm"," 70, 80, 100, 120, 140 kV\n mA range: 10 mA-420 mA\n Anode heat capacity: 5.3MHU\n Maximum anode heat\ndissipation:\n9.6kW(815kHU/min)\n Focal spot size:\n0.5mm × 1.0mm\n1.0mm × 1.0mm","--","Same"],"rows":[["X-ray Tube"," 70, 80, 100, 120, 140 kV\n mA range: 10 mA-420 mA\n Anode heat capacity: 5.3MHU\n Maximum anode heat\ndissipation:\n9.6kW(815kHU/min)\n Focal spot size:\n0.5mm × 1.0mm\n1.0mm × 1.0mm"," 70, 80, 100, 120, 140 kV\n mA range: 10 mA-420 mA\n Anode heat capacity: 5.3MHU\n Maximum anode heat\ndissipation:\n9.6kW(815kHU/min)\n Focal spot size:\n0.5mm × 1.0mm\n1.0mm × 1.0mm","--","Same"],["High Voltage Generator"," 50kW Power\n 70, 80, 100, 120, 140 kV"," 50kW Power\n 70, 80, 100, 120, 140 kV","--","Same"],["Patient Table"," Maximum load capacity\n205kg"," Maximum load capacity\n205kg","--","Same"],["Maximum Slices\nGenerated per Rotation","80 for uCT 550","40 for uCT 530\n80 for uCT 550","--","Same"],["Reconstruction Field of\nView","40-500mm\n40-700mm with extended FOV","40-500mm\n40-600mm with extended FOV","--","Substantially\nEquivalent,\nThe difference will\nnot raise safety and\neffectiveness\nconcerns."],["Application Features","","","",""],["KARL 3D","Yes","Yes","--","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p9-t0","doc_id":"K241166","page_num":9,"bbox":[72.24,111.98,724.12,523.56],"n_rows":10,"n_cols":5,"columns":["Metal Artifact Correction\n(MAC)","Yes","Yes","--","Same"],"rows":[["Metal Artifact Correction\n(MAC)","Yes","Yes","--","Same"],["Auto ALARA mA","Yes","--","Yes","Same"],["Auto ALARA kVp","Yes","--","Yes","Same"],["Organ-Based Auto\nALARA mA","Yes","--","Yes","Same"],["DELTA (Deep Recon)","Yes\nIt is an AI-based deep learning\nalgorithm to effectively reduce\nimage noise, enhance high-contrast\nspatial resolution, improve low-\ncontrast detectability, and\ncorrespondingly decrease the dose\nrequired for diagnostic CT images.","--","Yes","Substantial\nEquivalent\nNote 1"],["CardioXphase","Yes","--","Yes","Same"],["Online MPR","Yes","--","Yes","Same"],["EasyRange","Yes\nIt is an AI-based deep learning\nalgorithm to automatically\nrecommend the scan range.","--","Yes","Substantial\nEquivalent\nNote 2"],["uAI Vision","Yes","--","Yes","Same"],["Motion Freeze","Yes","--","--","Substantial\nEquivalent\nNote 3"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p10-t0","doc_id":"K241166","page_num":10,"bbox":[72.25,111.98,724.1,286.4],"n_rows":5,"n_cols":5,"columns":["","It is an AI-based deep learning\nalgorithm to reduce the artifacts\ncaused by head motion.","","",""],"rows":[["","It is an AI-based deep learning\nalgorithm to reduce the artifacts\ncaused by head motion.","","",""],["Injector Linkage","Yes","--","Yes","Same"],["CT-guided Intervention","Yes","--","Yes","Same"],["Low Dose CT Lung\nCancer Screening\nProtocol (LDCTLCS)","Yes","--","Yes","Same"],["Remote Assistance","Yes","--","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p10-t1","doc_id":"K241166","page_num":10,"bbox":[72.25,350.02,724.1,518.64],"n_rows":7,"n_cols":6,"columns":["","Proposed device\nuCT 550","","Reference device","","Discussion"],"rows":[["","Proposed device\nuCT 550","","Reference device","","Discussion"],["","","","uCT 760/780 with uWS-CT-","",""],["","","","Dual Energy Analysis","",""],["","","","(K230162)","",""],["Technology","AI-based deep learning algorithm","AI-based deep learning algorithm","","","Same"],["Applicable Body Parts","Head, chest, abdomen and vascular\nCT applications for adults","Head, chest, abdomen, cardiac\nand vascular CT applications for\nadults","","","The proposed device does not support\ncardiac. This difference will not introduce\nsafety and effectiveness issues."],["User Interface","5 noise reduction levels","4 noise reduction levels","","","Increased noise reduction. This difference\nwill not introduce safety and effectiveness\nissues."]],"caption_candidate":"Compared with DELTA (Deep Recon) algorithm cleared by K230162, detailed discussion about the difference are as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p11-t0","doc_id":"K241166","page_num":11,"bbox":[72.24,111.98,724.12,390.4],"n_rows":4,"n_cols":4,"columns":["Dataset Size","The dataset was increased to 127\ncases compared with the original\ndataset.","Original Dataset","Dataset was increased to improve algorithm\nrobustness. This difference will not\nintroduce safety and effectiveness issues."],"rows":[["Dataset Size","The dataset was increased to 127\ncases compared with the original\ndataset.","Original Dataset","Dataset was increased to improve algorithm\nrobustness. This difference will not\nintroduce safety and effectiveness issues."],["Clinical workflow","Select recon type, strength (noise\nindex level)","Select recon type and strength\n(noise index level)","Same"],["Bench test","Bench test for dose reduction,\nLCD, noise reduction and spatial\nresolution improving test. Basic IQ\nperformance test including HU\nvalue on water phantom, thickness\nsection test.","Bench test for dose reduction,\nLCD, noise reduction and spatial\nresolution improving test. Basic\nIQ performance test including HU\nvalue on water phantom,\nthickness section test.","Same"],["Conclusion","DELTA supplies diagnostic image\nquality at lower dose in the low\ndose simulation validation and\nequivalent or better image quality\ncompared with FBP in the\nevaluation of clinical cases covering a\nvariety of dose level.","DELTA is able to generate CT\nimages with lower image noise\nand improved low contrast\ndetectability, also reduce the dose\nrequired for diagnostic CT\nimaging.","Substantially Equivalent\nThe function of DELTA has been\noptimized in the uCT 550. The difference\nwill not raise new safety and effectiveness\nconcerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241166-p13-t0","doc_id":"K241166","page_num":13,"bbox":[138.38,593.8,540.0,712.78],"n_rows":3,"n_cols":5,"columns":["Body Part","Number","Age","Sex","Dose Distribution"],"rows":[["Body Part","Number","Age","Sex","Dose Distribution"],["Head","15","19-79","8 male\n7 female","≥70%: 13\n30%-70%: 2\n≤30%: 0"],["Chest","14","29-78","9 male\n5 female","≥70%: 2\n30%-70%: 4\n≤30%: 8"]],"caption_candidate":"validation and test data was shown below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241200-p8-t0","doc_id":"K241200","page_num":8,"bbox":[53.16,59.87,788.8,528.07],"n_rows":5,"n_cols":10,"columns":["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],"rows":[["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],["","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","","",""],["","","","for Qualified Arineta Systems","","","(K230370) CT X-ray System (with DLIR option)","","",""],["","Indications for Use","","","","","","","",""],["Indications for use","Indications for use","The SpotLight / SpotLight Duo is intended to produce cross-\nsectional images of the body by computer reconstruction of\nX-ray transmission projection data taken at different angles.\nThe system has the capability to image cardiovascular and\nthoracic anatomies, including the heart, in a single rotation.\nThe system may acquire data using Axial, Cine and Cardiac\nscan techniques from patients of all ages (DLIR is limited for\npatient use above the age of 2 years). These images may be\nobtained either with or without contrast. This device may\ninclude signal analysis and display equipment, patient and\nequipment supports, components and accessories.\nThis device may include data and image processing to\nproduce images in a variety of trans-axial and reformatted\nplanes.\nThe system is indicated for x-ray Computed Tomography\nimaging of cardiovascular and thoracic anatomies that fit in\nthe scan field-of-view.\nThe Low Dose CT Lung Cancer Screening Option for\nSpotLight / SpotLight Duo is indicated for using low dose CT\nfor lung cancer screening. The screening must be conducted\nwith the established program criteria and protocols (for\nmedium and large patients) that have been approved and\npublished by a governmental body or a professional medical\nsociety. Information from professional societies related to\nlung cancer screening can be found but is not limited to:\nAmerican College of Radiology® (ACR) – resources and\ntechnical specification; accreditation American Association of\nPhysicists in Medicine (AAPM) – Lung Cancer Screening\nProtocols; radiation management. Please refer to clinical\nliterature, including the results of the National Lung\nScreening Trial (N Engl J Med 2011; 365:395-409) and\nsubsequent literature, for further information.\nThe DLIR and ASIR-CV options are not compatible with the\nLow Dose Lung Cancer Screening option.\nThe device output is useful for diagnosis of disease or\nabnormality and for planning of therapy procedures.","","","The SpotLight / SpotLight Duo (with DLIR option) is intended\nto produce cross-sectional images of the body by computer\nreconstruction of x-ray transmission projection data taken at\ndifferent angles. The system has the capability to image\ncardiovascular and thoracic anatomies, including the heart,\nin a single rotation. The system may acquire data using\nAxial, Cine, and Cardiac scan techniques from patients of all\nages (DLIR is limited for patient use above the age of 2\nyears). These images may be obtained either with or without\ncontrast. This device may include signal analysis and display\nequipment, patient and equipment supports, components\nand accessories.\nThis device may include data and image processing to\nproduce images in a variety of trans-axial and reformatted\nplanes.\nThe system is indicated for X-ray Computed Tomography\nimaging of cardiovascular and thoracic anatomies that fit in\nthe scan field of view.\nThe device output is useful for diagnosis of disease or\nabnormality and for planning of therapy procedures.","","","The indications for use are\nsimilar, with the same\nindications for the entire\ndevice, except for minor\ndifferences; the indications\nfor use for the proposed\nSpotLight/SpotLight Duo\ndevices include Low Dose\nLung Cancer Screening\nOption with additional\nreferences to ACR and\nAAPM guidelines, and\nspecific DLIR and ASIR-CV\nlimitation for that option. LCS\nindication for use does not\nconstitute a new intended\nuse for the CT.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241200-p9-t0","doc_id":"K241200","page_num":9,"bbox":[53.16,59.87,788.83,535.51],"n_rows":13,"n_cols":11,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","","",""],["","","","","for Qualified Arineta Systems","","","(K230370) CT X-ray System (with DLIR option)","","",""],["","Technological Characteristics","","","","","","","","",""],["Detector technology\nand geometry","Detector technology","","Fast scintillator array coupled to photodiode array.\n33 (WFOV) or 23 (EFOV) configurable high resolution (HR)\nmodules comprising 192 detector rows X pitch 0.5mm (Z\ndirection, measured at scanner center).\n10 (WFOV) or 20 (EFOV) configurable low resolution (LR).\nEFOV includes 10 modules on each wing while WFOV\nincludes 10 modules on one wing. comprising 48 detector\nrows X pitch 2.0mm\nAnalog to digital conversion per channel on the detection\nmodule.\n1D antiscatter collimator.","","","Fast scintillator array coupled to photodiode array.\n33 (WFOV) or 23 (EFOV) configurable high resolution (HR)\nmodules comprising 192 detector rows X pitch 0.5mm (Z\ndirection, measured at scanner center).\n10 (WFOV)-20 (EFOV) configurable low resolution (LR).\nEFOV includes 10 modules on each wing while WFOV\nincludes 10 modules on one wing. comprising 48 detector\nrows X pitch 2.0mm\nAnalog to digital conversion per channel on the detection\nmodule.\n1D antiscatter collimator.","","","Same",""],["","and geometry","","","","","","","","",""],["","Data transmission","","Contactless transmission (capacitive coupling). Rate up to\n6.25 GBit/sec","","","Contactless transmission (capacitive coupling). Rate up to\n6.25 GBit/sec","","","Same",""],["","from rotor","","","","","","","","",""],["","Power and control","","Brush contact slipring","","","Brush contact slipring","","","Same",""],["","transmission to rotor","","","","","","","","",""],["","Rotation drive","","Direct drive DC motor","","","Direct drive DC motor","","","Same",""],["X Ray source","X Ray source","","2 x MCS 2093 X ray tubes by Varex Imaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in X direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","","","2 x MCS 2093 X ray tubes by Varex Imaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in X direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","","","Same",""],["Patient table","","","Motorized vertical and horizontal motion.\nOptional lateral motion\nCantilever carbon fiber patient cradle.","","","Motorized vertical and horizontal motion.\nOptional lateral motion.\nCantilever carbon fiber patient cradle.","","","Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241200-p10-t0","doc_id":"K241200","page_num":10,"bbox":[53.16,59.87,788.84,522.78],"n_rows":9,"n_cols":10,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","",""],["","","","","for Qualified Arineta Systems","","","(K230370) CT X-ray System (with DLIR option)","",""],["","Image reconstruction","","Multicore PC and GPU","","","Multicore PC and GPU","","","Same"],["","hardware","","","","","","","",""],["Image reconstruction\nalgorithm","Image reconstruction","","Modified FDK cone beam algorithm adapted for dual tubes\ngeometry.\nAdaptive filter to reduce directional noise in low level raw\ndata (MBAF).\nNon-local means algorithm MBAF2 (optional).\nFor WFOV configuration, adapted to reconstruct high\nresolution images according to detector configuration, lower\nresolution images outside FOV covered by high resolution\ndetectors.\nFor extended FOV configuration, adapted to reconstruct high\nresolution images up to FOV250mm, lower resolution\nimages outside FOV250mm.","","","Modified FDK cone beam algorithm adapted for dual tubes\ngeometry.\nAdaptive filter to reduce directional noise in low level raw\ndata (MBAF).\nNon-local means algorithm MBAF2 (optional).\nFor WFOV configuration, adapted to reconstruct high\nresolution images according to detector configuration, lower\nresolution images outside FOV covered by high resolution\ndetectors.\nFor extended FOV configuration, adapted to reconstruct high\nresolution images up to FOV250mm, lower resolution\nimages outside FOV250mm.\nASIR-CV or DLIR AI based image reconstruction algorithm.","","","Substantially the same\nreconstruction technology,\nexcept the ASIR-CV and AI-\nbased DLIR image\nreconstruction algorithms.\nThe proposed LD LCS\noption is not compatible with\nDLIR and ASIR-CV.\nThe LD LCS option is\navailable with or without\nMBAF2."],["","algorithm","","","","","","","",""],["Construction Materials","","","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and electronic cables\ncomponents\nTable top made of carbon fiber reinforced resin\nCovers made pf molded polymers and reinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4 and Gadolinium\nOxysulfide (GOS) used in other legally marketed CT\nscanners","","","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and electronic cable\ncomponents\nTable top made of carbon fiber reinforced resin\nCovers made pf molded polymers and reinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4 and Gadolinium\nOxysulfide (GOS) used in other legally marketed CT\nscanners","","","Same"],["Energy sources","","","Wall supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes) 72kW","","","Wall supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes) 72kW","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241200-p11-t0","doc_id":"K241200","page_num":11,"bbox":[53.16,59.87,788.85,509.57],"n_rows":13,"n_cols":10,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","",""],["","","","","for Qualified Arineta Systems","","","(K230370) CT X-ray System (with DLIR option)","",""],["","","","Laser alignment lights: gantry bore external lasers. <0.1mW\nper laser beam\nThree lead ECG trigger module, powered by medical grade\npower supply through the system PDU","","","Laser alignment lights: gantry bore external lasers. <0.1mW\nper laser beam\nThree lead ECG trigger module, powered by medical grade\npower supply through the system PDU","","",""],["Software","","","Provided with software in three domains:\n• Console software\n• Image reconstruction software\n• Embedded software","","","Provided with software in three domains:\n• Console software\n• Image reconstruction software\n• Embedded software","","","Substantially the same, with\nminor changes in the added\nLD LCS protocols (for\nmedium and large patients)\nper AAPM guidelines."],["","Max Rotation speed","","250 RPM (0.24 sec per rotation)","","","250 RPM (0.24 sec per rotation)","","","Same"],["Min scan time","Min scan time","","0.16 sec (partial), 0.24 sec (full scan) – FOV up to 250mm\n0.24 sec (full scan) – HR imaging at FOV above 250mm for\nasymmetric detector","","","0.16 sec (partial), 0.24 sec (full scan) – FOV up to 250mm\n0.24 sec (full scan) – HR imaging at FOV above 250mm for\nasymmetric detector","","","Same"],["","Max axial coverage in","","140mm (280 slices x 0.5mm pitch)","","","140mm (280 slices x 0.5mm pitch)","","","Same"],["","a single axial scan","","","","","","","",""],["Field of View (FOV)","Field of View (FOV)","","25cm - 250mm at high resolution\nWFOV - High resolution images at configurable FOV\nbetween 250mm and 450mm\nEFOV – Lower resolution in the FOV between HR coverage\nand 450mm","","","25cm - 250mm at high resolution\nWFOV - High resolution images at configurable FOV\nbetween 250mm and 450mm\nEFOV – Lower resolution in the FOV between HR coverage\nand 450mm","","","Same"],["Max spatial resolution","","","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by HR detectors\n7.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by LR detectors","","","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by HR detectors\n7.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by LR detectors","","","Same"],["","Bore size","","60 cm","","","60 cm","","","Same"],["","Max Patient weight","","227 Kg (500 lbs)","","","227 Kg (500 lbs)","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241200-p12-t0","doc_id":"K241200","page_num":12,"bbox":[53.14,59.87,788.81,438.31],"n_rows":6,"n_cols":10,"columns":["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],"rows":[["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],["","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","","",""],["","","","for Qualified Arineta Systems","","","(K230370) CT X-ray System (with DLIR option)","","",""],["Add on parts and\naccessories","","Operator console table\nNG2000 Table slickers\nBar code reader\nUninterruptible Power Supply\nHead& hands and knees support","","","Operator console table\nNG2000 Table slickers\nBar code reader\nUninterruptible Power Supply\nHead& hands and knees support","","","Same",""],["","Image Quality Metrics","","","","","","","",""],["CT number accuracy - In a low signal situation such as with LD LCS, the CT number measured in a nodule may be compromised. In LCS, the CT number may be a reference against\npotentially calcified nodules.\nCT number uniformity - In a low signal situation such as LD LCS, maintaining sufficient CT number uniformity throughout the lung and various structures is important for more robust\ndetectability of nodules. Uniformity is needed to maintain CT number separation between structures.\nImage noise (standard deviation) - As dose is reduced, background noise in the image increases. If this noise becomes too large, nodule detectability and sizing measurement may\nbe compromised.\nModulation Transfer Function (MTF) - MTF is a measure of the high contrast spatial resolution performance of the system. Nodules in the lung are high contrast objects and therefore,\nMTF should be preserved at lower dose conditions.\nVisual Resolution/Image Artifacts - This relates to the evaluation of images to assess their visual resolution using high contrast bar patterns and evaluation of the degree of artifacts\n(e.g., low signal streaks, beam hardening). These tests are relevant because of the high contrast detection task of relatively small objects for this application. Streak or beam\nhardening may obscure pathology and affect CT number accuracy.\nNoise Power Spectrum (NPS) - Similar to standard deviation of noise, changes in noise texture may result in nodule detection becoming more challenging especially if there is a\nsignificant shift in the frequency of the noise, and/or an increase in amplitude of the NPS plot.\nSlice Thickness - The ability to produce slice thicknesses (FWHM of the slice sensitivity profile) that are close to the nominal slice thickness is important in defining clear edges and\nboundaries of the nodule and in nodule sizing.\nContrast to Noise (CNR) - Sufficient CNR is needed to detect solid and non-solid nodules in the lung. This metric is similar to SNR but accounts for the contrast between an object\nand the background. Arineta believes this is the primary figure of metric to evaluate nodule detectability.\nThe image quality metrics were used for evaluation to determine substantial equivalence. Each metric is provided with a description of the impact/relevance of the metric for LCS. All\nIQ metrics used for both the proposed and the predicate device are the same.","","","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241211-p6-t0","doc_id":"K241211","page_num":6,"bbox":[71.08,131.64,540.81,720.12],"n_rows":7,"n_cols":4,"columns":["","Predicate Device","Subject Device","Remark/Discussion"],"rows":[["","Predicate Device","Subject Device","Remark/Discussion"],["","CoLumbo","CoLumbo",""],["","Version 2","Version 3",""],["","(K193290)","",""],["Regulation","892.2050","892.2050","Same"],["Product Code","QIH","QIH","Same"],["Indications for\nUse","CoLumbo is an image post-\nprocessing and measurement\nsoftware tool that provides\nquantitative spine\nmeasurements from\npreviously-acquired DICOM\nlumbar spine Magnetic\nResonance (MR) images for\nusers’ review, analysis, and\ninterpretation. It provides the\nfollowing functionality to\nassist users in visualizing,\nmeasuring and documenting\nout-of-range measurements:\n• Feature segmentation;\n• Feature measurement;\n• Threshold-based labeling\nof out-of-range\nmeasurement; and\n• Export of measurement\nresults to a written report\nfor user’s review, revise\nand approval.\nCoLumbo does not produce or\nrecommend any type of\nmedical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify features\nin lumbar MR images and\ncompile a report. The user is\nresponsible for\nconfirming/modifying settings,\nreviewing and verifying the\nsoftware-generated\nmeasurements, inspecting out-","CoLumbo is an image post-\nprocessing and measurement\nsoftware tool that provides\nquantitative spine\nmeasurements from\npreviously-acquired DICOM\nlumbar spine Magnetic\nResonance (MR) images for\nusers’ review, analysis, and\ninterpretation. It provides the\nfollowing functionality to\nassist users in visualizing,\nmeasuring and documenting\nout-of-range measurements:\n• Feature segmentation;\n• Feature measurement;\n• Threshold-based labeling\nof out-of-range\nmeasurement; and\n• Export of measurement\nresults to a written report\nfor user’s review, revise\nand approval.\nCoLumbo does not produce\nor recommend any type of\nmedical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify features\nin lumbar MR images and\ncompile a report. The user is\nresponsible for\nconfirming/modifying\nsettings, reviewing and\nverifying the software-\ngenerated measurements,\ninspecting out-of-range\nmeasurements, and approving\ndraft report content using","Highly similar\nIndications for use\nare the same with the\nlist of\ncontraindications\nchanged."]],"caption_candidate":"Table 1 – Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241211-p7-t0","doc_id":"K241211","page_num":7,"bbox":[71.08,71.22,540.82,681.24],"n_rows":10,"n_cols":4,"columns":["","Predicate Device","Subject Device","Remark/Discussion"],"rows":[["","Predicate Device","Subject Device","Remark/Discussion"],["","CoLumbo","CoLumbo",""],["","Version 2","Version 3",""],["","(K193290)","",""],["","of-range measurements, and\napproving draft report content\nusing their medical judgment\nand discretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM images of MRI\nacquired from lumbar spine\nexams of patients aged 18 and\nabove are considered to be\nvalid input. CoLumbo does not\nsupport DICOM images of\npatients that are pregnant,\nundergo MRI scan with\ncontrast media, or have post-\noperational complications,\nscoliosis, tumors, infections,\nfractures.","their medical judgment and\ndiscretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM images of MRI\nacquired from lumbar spine\nexams of patients aged 18\nand above are considered to\nbe valid input. CoLumbo\ndoes not support DICOM\nimages of patients that are\npregnant, undergo MRI scan\nwith contrast media, or have\npost-operational\ncomplications, tumors,\ninfections.",""],["Intended User","Radiologist and neuro- and\nspine-surgeons","Radiologist and neuro- and\nspine-surgeons","Same"],["Intended Patient\nPopulation","The intended patient\npopulation is not subject to\nany restrictions.\nAutomation support requires\nimages of patients of 18 years\nand older, not pregnant,\nwithout post-operational\ncomplications, scoliosis,\ntumors, infections, fractures.","The intended patient\npopulation is not subject to\nany restrictions.\nAutomation support requires\nimages of patients of 18 years\nand older, not pregnant,\nwithout post-operational\ncomplications, tumors,\ninfections.","Highly similar"],["Supported Body\nPart","Lumbar Spine","Lumbar Spine","Same"],["Segmentation","Yes\nSegmentation and\nquantitative analysis","Yes\nSegmentation and\nquantitative analysis","Same"],["Measurement","Yes\nQuantitative comparison of\nstructure with normative data\nor user-set thresholds","Yes\nQuantitative comparison of\nstructure with normative data\nor user-set thresholds","Same"]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241211-p8-t0","doc_id":"K241211","page_num":8,"bbox":[71.08,71.22,540.81,698.76],"n_rows":10,"n_cols":4,"columns":["","Predicate Device","Subject Device","Remark/Discussion"],"rows":[["","Predicate Device","Subject Device","Remark/Discussion"],["","CoLumbo","CoLumbo",""],["","Version 2","Version 3",""],["","(K193290)","",""],["Threshold-Based\nOut-of-Range\nMeasurements","Yes\nQuantitative comparison of\nstructure with normative data\nor user-set thresholds","Yes\nQuantitative comparison of\nstructure with normative data\nor user-set thresholds","Same"],["Reporting","Yes","Yes","Same"],["SaMD","Yes","Yes","Same"],["Algorithm","Deep Convolutional\nImage-to-Image Neural\nNetwork","Deep Convolutional\nImage-to-Image Neural\nNetwork","Same"],["Supported\nModality","MR","MR","Same"],["Supported\nMeasurements","• Focal disk material outside\nVB projection and its\nmigration – descending\nand ascending;\n• Disk outside VB\nprojection;\n• Dural sac cross-sectional\narea;\n• Nerve root deviation;\n• Vertebral body height;\n• Disk height;\n• Lordotic angle;\n• Spondylolisthesis\nslippage;","• Focal disk material outside\nVB projection;\n• Descending (caudal) and\nascending (cranial) disk\nmaterial outside of the\nintervertebral space;\n• Disk outside VB\nprojection;\n• Dural sac cross-sectional\narea;\n• Nerve root deviation;\n• Vertebral body height;\n• Disk height;\n• Lordotic angle;\n• Spondylolisthesis\nslippage;\n• Аngle of lateral spinal\ncurvature;\n• Facet joint diameter;\n• Posterior epidural fat size;\n• Muscle fat infiltration\npercentage;\n• Foramen diameter;\n• Lateral recess diameter;\n• Dural sac anterior-\nposterior diameter;\n• Spinal canal diameter;\n• Disk Material Outside of\nEndplate Margins Size;","Highly similar\nThe Subject Device\nsupports several\nmore measurements."]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241211-p9-t0","doc_id":"K241211","page_num":9,"bbox":[71.13,71.22,540.78,207.48],"n_rows":5,"n_cols":4,"columns":["","Predicate Device","Subject Device","Remark/Discussion"],"rows":[["","Predicate Device","Subject Device","Remark/Discussion"],["","CoLumbo","CoLumbo",""],["","Version 2","Version 3",""],["","(K193290)","",""],["","","• Ligament Flavum\nThickness;\n• Vertebral Body Zone with\nChanged Intensity Size.\n• Vertebral Body Width\nDifference AP Size.",""]],"caption_candidate":"CoLumbo 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241211-p9-t1","doc_id":"K241211","page_num":9,"bbox":[92.48,536.16,549.92,705.0],"n_rows":6,"n_cols":2,"columns":["Recognition","Standard"],"rows":[["Recognition","Standard"],["#",""],["13-79","IEC 62304:2006/AMD 1:2015 Medical device software — Software life cycle\nprocesses — Amendment 1"],["13-97","IEC 82304-1:2016 Health software — Part 1: General requirements for product safety"],["5-125","ISO 14971:2019 Medical devices — Application of risk management to medical\ndevices"],["5-129","IEC 62366-1:2015+AMD1:2020 Medical devices — Part 1: Application of usability\nengineering to medical devices"]],"caption_candidate":"Table 2 - Voluntary Conformance Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241222-p8-t0","doc_id":"K241222","page_num":8,"bbox":[66.3,347.35,545.83,772.92],"n_rows":9,"n_cols":10,"columns":["Feature/Characteristic","","","Predicate Device","","","Subject Device","","Comparison",""],"rows":[["Feature/Characteristic","","","Predicate Device","","","Subject Device","","Comparison",""],["","","","Ventripoint Medical","","","Ventripoint Medical","","",""],["","","","System Plus (VMS+)","","","System Plus (VMS+)","","",""],["","","","3.0 (K191493)","","","4.0","","",""],["Indications for Use","","The VMS+ is an\nadjunct to existing\nultrasound imaging\nsystems and is\nintended to record,\nanalyze, store and\nretrieve digital\nultrasound images for\ncomputerized 3-\ndimensional image\nprocessing.\nThe VMS+ is\nindicated for use\nwhere Left Ventricle\n(LV), Right Ventricle\n(RV), Left Atrium\n(LA), and Right\nAtrium (RA) volumes\nand ejection fractions\nare warranted or\ndesired.","","","The VMS+ is an\nadjunct to existing\nultrasound imaging\nsystems and is\nintended to record,\nanalyze, store and\nretrieve digital\nultrasound images for\ncomputerized 3-\ndimensional image\nprocessing.\nThe VMS+ is indicated\nfor use where Left\nVentricle (LV), Right\nVentricle (RV), Left\nAtrium (LA), and Right\nAtrium (RA) volumes\nand ejection fractions\nare warranted or\ndesired.","","","Same",""],["","Technological Characteristics","","","","","","","",""],["Software based\nanalysis tool","","Yes","","","Yes","","","Same",""],["Knowledge-Based\nReconstruction\nAlgorithm","","Yes","","","Yes","","","Same",""],["3D Visualization","","Generates a 3D\nsurface model of the\n4 chambers and","","","Generates a 3D\nsurface model of the 4\nchambers and","","","Same",""]],"caption_candidate":"same as the predicate with acceptable results.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241222-p9-t0","doc_id":"K241222","page_num":9,"bbox":[66.29,94.43,545.84,757.68],"n_rows":8,"n_cols":8,"columns":["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],"rows":[["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],["","","Ventripoint Medical","","","Ventripoint Medical","",""],["","","System Plus (VMS+)","","","System Plus (VMS+)","",""],["","","3.0 (K191493)","","","4.0","",""],["","accompanying\nvolume\nmeasurement.","","","accompanying volume\nmeasurement.","","",""],["Measurements","End-systolic volumes\n(EDV, ESV), Ejection\nFractions (EF), Stroke\nVolumes and Cardiac\nOutputs","","","End-systolic volumes\n(EDV, ESV), Ejection\nFractions (EF), Stroke\nVolumes and Cardiac\nOutputs.","","","Same"],["Acquisition Workflow","Executing on a\ncomputer, processes\ndata acquired by the\nsensor system in\nconjunction with the\noutput from the\nultrasound\nequipment, to enable\ntracking of anatomic\nlandmark points from\nthe 2D images and\nconversion of those\npoints into 3D data\npoints.","","","Executing on a\ncomputer, processes\ndata acquired by the\nsensor system in\nconjunction with the\noutput from the\nultrasound equipment,\nto enable tracking of\nanatomic landmark\npoints from the 2D\nimages and conversion\nof those points into 3D\ndata points.","","","Same"],["Points placement","Requires placement\nof anatomic\nlandmarks on the 2D\nimages. On-screen\nguide is provided to\nuser for point\nplacement first\nguesses. User must\nmanually adjust first\nguess point\nplacements as\nrequired.\nLandmarks are then\nused to build an\naccurate 3D\nconstructed shape\nmesh (defined by\nvertices, edges, and\nfaces).","","","Requires placement of\nanatomic landmarks on\nthe 2D images. On-\nscreen guide is\nprovided to user for\npoint placement first\nguesses. Alternatively,\nautomated point\nplacement first guesses\ncan be generated via a\nbutton press. User\nmust manually adjust\nfirst guess point\nplacements as\nrequired.\nLandmarks are then\nused to build an\naccurate 3D\nconstructed shape\nmesh (defined by\nvertices, edges, and\nfaces).","","","VMS+ 4.0 is equivalent\nto VMS+ 3.0. The\nautomated control point\nfirst guess placement is\nadded to improve user\nworkflow efficiency.\nUsers must still\nmodify/confirm control\npoint placement after\nan automated first\nguess.\nInternal user validation\nof the final location of\ncontrol points using the\non-screen guide versus\nautomated first\nguesses was assessed.\nAdditionally, verification\ntests were performed\nagainst doctors’ point\nplacement.\nThus, the difference\ndoes not raise different\nquestions of safety and\neffectiveness."]],"caption_candidate":"Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241222-p10-t0","doc_id":"K241222","page_num":10,"bbox":[66.29,94.43,545.83,627.58],"n_rows":7,"n_cols":8,"columns":["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],"rows":[["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],["","","Ventripoint Medical","","","Ventripoint Medical","",""],["","","System Plus (VMS+)","","","System Plus (VMS+)","",""],["","","3.0 (K191493)","","","4.0","",""],["Location of KBR\ncatalogue","Knowledge-based\nreconstruction located\nlocally on the system,\nwhich accepts the 3D\ndata points generated\nthrough the use of the\nposition sensor\nsystem and provides\nthe computation\nengine for generating\na 3D surface\nconstruction of the\nfour chambers and\naccompanying\nvolume measurement\nand ejection fractions\nof the four chambers\nof the four chambers\nof the heart, either at\nend-diastolic and/or\nend-systolic.","","","Knowledge-based\nreconstruction located\nlocally on the system,\nwhich accepts the 3D\ndata points generated\nthrough the use of the\nposition sensor system\nand provides the\ncomputation engine for\ngenerating a 3D\nsurface construction of\nthe four chambers and\naccompanying volume\nmeasurement and\nejection fractions of the\nfour chambers of the\nfour chambers of the\nheart, either at end-\ndiastolic and/or end-\nsystolic.","","","Same"],["Software application\ntypes","Console (system) and\nWorkstation\n(standalone)","","","Console (system) and\nWorkstation\n(standalone)","","","Same"],["Hardware data\nacquisition system","Touchscreen for\nimage capture, a\nvideo-input connector\nto receive image data\nfrom an ultrasound\nmachine, off-the-shelf\nreal-time video\ncapture card to\nreceive image data\nfrom an ultrasound\nmachine, and 3D\npositional tracking\nsystem to receive\nposition and\norientation\ninformation.","","","Touchscreen for image\ncapture, a video-input\nconnector to receive\nimage data from an\nultrasound machine,\noff-the-shelf real-time\nvideo capture card to\nreceive image data\nfrom an ultrasound\nmachine, and 3D\npositional tracking\nsystem to receive\nposition and orientation\ninformation.","","","Same"]],"caption_candidate":"Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241222-p11-t0","doc_id":"K241222","page_num":11,"bbox":[66.28,94.43,545.84,724.54],"n_rows":10,"n_cols":8,"columns":["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],"rows":[["Feature/Characteristic","","Predicate Device","","","Subject Device","","Comparison"],["","","Ventripoint Medical","","","Ventripoint Medical","",""],["","","System Plus (VMS+)","","","System Plus (VMS+)","",""],["","","3.0 (K191493)","","","4.0","",""],["3D tracking/positional\nsystem","Magnetic-based; free-\nhand scanning;\nconsisting of\nmechanical arm,\ntransmitter,\nultrasound transducer\nsensor, and\nassociated\nelectronics.","","","Magnet-free; free-hand\nscanning; consisting of\nultrasound transducer\nsensor,\ntransmitter/sensor on\npatient, and associated\nelectronics.","","","VMS+ 4.0 is equivalent\nto VMS+ 3.0 with the\nonly difference being\nthat the magnet has\nbeen removed from\ntransmitter/sensor as\nan improvement. The\nway in which the device\noperates remains the\nsame; both systems\nare free-hand scanning.\nIn addition, the\nperformance of the new\ndevice is the same as\nthe predicate device.\nThus, the difference\ndoes not raise different\nquestions of safety and\neffectiveness."],["Patient contacting\ncomponents","Surface device; intact\nskin; A-limited (<24h)","","","Surface device; intact\nskin; A-limited (<24h)","","","Same"],["3D Echo and MRI\nfunctionality","Can import 3D echo\nand MRI studies for\nvolumetric analysis.","","","Can import 3D echo and\nMRI studies for\nvolumetric analysis.","","","Same"],["Software controls","The software\ncomponents are\nresponsible for\nproviding the user\nwith controls for\nmanaging the\nhardware operation,\ncapturing ultrasound\nimages, marking up\nimages with key\nanatomical features,\ninvoking the\nreconstruction\nalgorithm, displaying\nthe resulting\nconstruction and\ngenerating the\ncorresponding report.","","","The software\ncomponents are\nresponsible for\nproviding the user with\ncontrols for managing\nthe hardware operation,\ncapturing ultrasound\nimages, marking up\nimages with key\nanatomical features,\ninvoking the\nreconstruction\nalgorithm, displaying\nthe resulting\nconstruction and\ngenerating the\ncorresponding report.","","","Same"],["Power requirements","Power requirements:\nAC :100V- 240V,\nFrequenzy:50-60Hz","","","Power requirements:\nAC :100V- 240V,\nFrequenzy:50-60Hz","","","Same"],["Image data format","Original VMS+ and\nDICOM format","","","Original VMS+ and\nDICOM format","","","Same"]],"caption_candidate":"Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241242-p5-t0","doc_id":"K241242","page_num":5,"bbox":[108.24,142.68,539.76,719.52],"n_rows":11,"n_cols":2,"columns":["Date:","May 1, 2024"],"rows":[["Date:","May 1, 2024"],["Submitter:","GE Medical Systems, LLC\n3200 N. Grandview Blvd.\nWaukesha, WI 53188"],["Primary Contact:","Brian R. Zielski\nSr. Lead Specialist, Regulatory Affairs - MR\nPhone: 262-227-3596\nEmail: brian.zielski@gehealthcare.com"],["Secondary Contact:","Andrew Menden\nDirector, Regulatory Affairs - MR\nPhone: 262-308-5719\nEmail: andrew.menden@gehealthcare.com"],["Device Trade Name:","SIGNA MAGNUS"],["Common / Usual Name:","Magnetic Resonance Diagnostic Device"],["Classification Name:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH, LNI"],["Predicate Device(s):","SIGNA Premier (K193282)"],["Reference Device(s):","SIGNA Champion (K233728)"],["Device Description:","SIGNA MAGNUS is a 3.0T high-performance magnetic\nresonance imaging system designed to support imaging\nof the head, neck, TMJ and limited cervical spine. The\nsystem supports scanning in axial, coronal, sagittal,\noblique, and double oblique planes using a variety of\npulse sequences, imaging techniques, acceleration\nmethods, and reconstruction algorithms. The system can\nbe delivered as a new system installation, or as an\nupgrade to existing compatible whole-body 3.0T MR\nsystems from GE HealthCare."]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241242-p6-t0","doc_id":"K241242","page_num":6,"bbox":[108.24,86.4,539.76,703.68],"n_rows":4,"n_cols":2,"columns":["","Key aspects of the system design:\n• An asymmetrically designed, head-only gradient coil\nthat achieves up to 300 mT/m peak gradient\namplitude and 750 T/m/s peak slew rate.\n• A graduated patient bore size, starting at 74 cm at\nthe entry down to 37 cm at isocenter.\n• Uses the same magnet as a conventional whole-\nbody 3.0T system, with integral active shielding and a\nzero boil-off cryostat.\n• Can be installed as a new system or upgraded from\nan existing compatible whole-body 3.0T MR system.\n• A dockable mobile patient table.\n• Oscillating Diffusion ENcoding (ODEN) - a spectral\ndiffusion technique that uses a sinusoidal diffusion\ngradient waveform."],"rows":[["","Key aspects of the system design:\n• An asymmetrically designed, head-only gradient coil\nthat achieves up to 300 mT/m peak gradient\namplitude and 750 T/m/s peak slew rate.\n• A graduated patient bore size, starting at 74 cm at\nthe entry down to 37 cm at isocenter.\n• Uses the same magnet as a conventional whole-\nbody 3.0T system, with integral active shielding and a\nzero boil-off cryostat.\n• Can be installed as a new system or upgraded from\nan existing compatible whole-body 3.0T MR system.\n• A dockable mobile patient table.\n• Oscillating Diffusion ENcoding (ODEN) - a spectral\ndiffusion technique that uses a sinusoidal diffusion\ngradient waveform."],["Indications for Use:","SIGNA MAGNUS system is a head-only magnetic\nresonance scanner designed to support high resolution,\nhigh signal-to-noise ratio, diffusion-weighted imaging,\nand short scan times. SIGNA MAGNUS is indicated for use\nas a diagnostic imaging device to produce axial, sagittal,\ncoronal, and oblique images, spectroscopic images,\nparametric maps, and/or spectra, dynamic images of the\nstructures and/or functions of the head, neck, TMJ, and\nlimited cervical spine on patients 6 years of age and\nolder. Depending on the region of interest being imaged,\ncontrast agents may be used.\nThe images produced by SIGNA MAGNUS reflect the\nspatial distribution or molecular environment of nuclei\nexhibiting magnetic resonance. These images and/or\nspectra, when interpreted by a trained physician, yield\ninformation that may assist in diagnosis."],["Technology:","SIGNA MAGNUS employs the same functional scientific\ntechnology as its predicate device."],["Comparison of Indications\nfor Use:","SIGNA MAGNUS and the predicate device’s Indications\nfor Use are substantially equivalent. While the predicate\nis intended for all anatomies, SIGNA MAGNUS is intended\nfor only the head, neck, TMJ, and cervical spine."]],"caption_candidate":"Attachment 15 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241242-p7-t0","doc_id":"K241242","page_num":7,"bbox":[108.24,86.4,539.76,705.24],"n_rows":2,"n_cols":2,"columns":["","As such, GE HealthCare considers that SIGNA MAGNUS\nhas the same intended use as the predicate device in\naccordance with the FDA’s guidance document “The\n510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)]”, dated 28 July 2014."],"rows":[["","As such, GE HealthCare considers that SIGNA MAGNUS\nhas the same intended use as the predicate device in\naccordance with the FDA’s guidance document “The\n510(k) Program: Evaluating Substantial Equivalence in\nPremarket Notifications [510(k)]”, dated 28 July 2014."],["Comparison of\nTechnological\nCharacteristics:","Overall, SIGNA MAGNUS employs the same fundamental\nscientific technology as the predicate device.\nSystem Design: Both SIGNA MAGNUS and the predicate\ndevice include the 3.0 T magnet, RF transmit\narchitecture, RF receive chain and software application\nsuite. However, the most notable technological\ndifference between the SIGNA™ MAGNUS and the\npredicate device are:\n• Gradient System: The SIGNA MAGNUS can deliver\na peak gradient amplitude of 300 mT/m and peak\ngradient slew rate of 750 T/m/s compared to the\npredicate’s peak gradient amplitude of 80 mT/m\nand peak gradient slew rate of 200 T/m/s. PNS\nand CS thresholds are also significantly different\nbetween the two systems, allowing more\nperformance to be used on the SIGNA MAGNUS\nsystem.\n• Applications: The SIGNA MAGNUS uses the SIGNA\nWorks suite of applications with the addition of\nOscillating Diffusion ENcoding (ODEN) - a spectral\ndiffusion technique that uses a sinusoidal\ndiffusion gradient waveform. ODEN is not offered\non the predicate device.\n• Field-of-View (FOV): The SIGNA MAGNUS FOV\n(26cm x 26 cm x 26cm) is intended for head, neck,\nTMJ, and limited cervical spine scanning. As such,\na smaller maximum imaging FOV is specified\ncompared to the predicate device with an FOV of\n50cm x 50cm x 50cm.\n• Bore Size: Unlike the straight cylindrical patient\nbore of the predicate device, the SIGNA MAGNUS"]],"caption_candidate":"Attachment 15 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241242-p8-t0","doc_id":"K241242","page_num":8,"bbox":[108.24,86.4,539.76,718.56],"n_rows":2,"n_cols":2,"columns":["","system has a stepped progressively narrowing\npatient bore. The widest part at the patient bore\nentry accommodates the arms and torso. It has a\n74 cm inner diameter. The patient bore diameter\nat the shoulders is narrowed to 54 cm. At the\nhead, the SIGNA MAGNUS patient bore diameter\nis 37 cm compared to 70 cm for the predicate\ndevice.\n• Receive Channels: The SIGNA MAGNUS has 64\nindependent RF channels to account for the\nimaged anatomies of head, neck, TMJ, and limited\ncervical spine, compared to 146 for the predicate\ndevice which is used for whole-body imaging.\n• Max RF Power Output: The SIGNA MAGNUS has\n7.5 kW peak total maximum RF power output\ncompared to 30 kW for the predicate device.\nOperating Principles: SIGNA MAGNUS functions using\nthe same operating principles as the predicate device.\nMaterials: SIGNA MAGNUS and the predicate device\nboth use the same materials.\nSafety and Performance Testing: Both SIGNA MAGNUS\nand the predicate device comply with the same safety\nand performance testing (see Determination of\nSubstantial Equivalence, below).\nThese technological differences do not raise any\nquestions regarding safety and effectiveness. Both\ndevices must address questions of whether they provide\nan adequate level of image quality appropriate for\ndiagnostic use. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the image quality performance\nof SIGNA MAGNUS compared to the predicate device."],"rows":[["","system has a stepped progressively narrowing\npatient bore. The widest part at the patient bore\nentry accommodates the arms and torso. It has a\n74 cm inner diameter. The patient bore diameter\nat the shoulders is narrowed to 54 cm. At the\nhead, the SIGNA MAGNUS patient bore diameter\nis 37 cm compared to 70 cm for the predicate\ndevice.\n• Receive Channels: The SIGNA MAGNUS has 64\nindependent RF channels to account for the\nimaged anatomies of head, neck, TMJ, and limited\ncervical spine, compared to 146 for the predicate\ndevice which is used for whole-body imaging.\n• Max RF Power Output: The SIGNA MAGNUS has\n7.5 kW peak total maximum RF power output\ncompared to 30 kW for the predicate device.\nOperating Principles: SIGNA MAGNUS functions using\nthe same operating principles as the predicate device.\nMaterials: SIGNA MAGNUS and the predicate device\nboth use the same materials.\nSafety and Performance Testing: Both SIGNA MAGNUS\nand the predicate device comply with the same safety\nand performance testing (see Determination of\nSubstantial Equivalence, below).\nThese technological differences do not raise any\nquestions regarding safety and effectiveness. Both\ndevices must address questions of whether they provide\nan adequate level of image quality appropriate for\ndiagnostic use. The performance data described in this\nsubmission include results of both bench testing and\nclinical testing that show the image quality performance\nof SIGNA MAGNUS compared to the predicate device."],["Determination of\nSubstantial Equivalence:","Summary of Non-Clinical Tests:\nSIGNA MAGNUS and the predicate device were subject to\nsimilar risk management testing to demonstrate\nsubstantial equivalence of safety and performance."]],"caption_candidate":"Attachment 15 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241242-p10-t0","doc_id":"K241242","page_num":10,"bbox":[108.24,86.4,539.76,336.48],"n_rows":2,"n_cols":2,"columns":["","October 10, 2023. The image quality of SIGNA MAGNUS\nis substantially equivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are\ncomparable to the claimed predicate device. SIGNA\nMAGNUS employs equivalent technology to the claimed\npredicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended.\nTherefore, SIGNA MAGNUS is substantially equivalent to\nthe predicate device to which it has been compared."],"rows":[["","October 10, 2023. The image quality of SIGNA MAGNUS\nis substantially equivalent to that of the predicate device.\nSubstantial Equivalence Conclusion:\nThe indications for use of the proposed device are\ncomparable to the claimed predicate device. SIGNA\nMAGNUS employs equivalent technology to the claimed\npredicate device.\nAdditionally, the results from the above non-clinical tests\ndemonstrate that the device performs as intended.\nTherefore, SIGNA MAGNUS is substantially equivalent to\nthe predicate device to which it has been compared."],["Conclusion:","In conclusion, GE Healthcare considers SIGNA MAGNUS\nto be at least as safe and effective, and its performance is\nsubstantially equivalent to the predicate device."]],"caption_candidate":"Attachment 15 – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241245-p5-t0","doc_id":"K241245","page_num":5,"bbox":[45.67,103.74,519.82,251.92],"n_rows":5,"n_cols":2,"columns":["Company","Echo IQ Ltd"],"rows":[["Company","Echo IQ Ltd"],["Address","Suite 2.114, Level 1, 477 Pitt Street\nSydney NSW 2000\nAustralia"],["Phone","+61 (02) 9159 3719"],["Contact Person","Dane Brescacin"],["Date Prepared","October 2, 2024"]],"caption_candidate":"1. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241245-p5-t1","doc_id":"K241245","page_num":5,"bbox":[51.24,107.73,246.11,530.18],"n_rows":34,"n_cols":2,"columns":["Company","Echo IQ Ltd"],"rows":[["Company","Echo IQ Ltd"],["",""],["Address","Suite 2.114,"],["",""],["","Sydney NSW"],["",""],["","Australia"],["",""],["Phone","+61 (02) 915"],["",""],["Contact Person","Dane Bresca"],["",""],["Date Prepared","October 2, 2"],["",""],[". SUBJECT DEVIC","E"],["",""],["Device Name","EchoSolv AS"],["",""],["Classification Name","Radiological"],["","Lesions Sus"],["",""],["Regulation","21 CFR 892."],["",""],["Regulatory Class","Class II"],["",""],["Product Code","POK"],["",""],[". PREDICATE DEV","ICE"],["",""],["Device Name","EchoGo Pro"],["",""],["Manufacturer","Ultromics Li"],["",""],["510(k) Number","K201555"]],"caption_candidate":"Company Echo IQ Ltd","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241245-p5-t2","doc_id":"K241245","page_num":5,"bbox":[45.67,291.69,519.82,424.25],"n_rows":5,"n_cols":2,"columns":["Device Name","EchoSolv AS"],"rows":[["Device Name","EchoSolv AS"],["Classification Name","Radiological Computer-Assisted Diagnostic Software (CADx) for\nLesions Suspicious for Cancer"],["Regulation","21 CFR 892.2060"],["Regulatory Class","Class II"],["Product Code","POK"]],"caption_candidate":"2. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241245-p5-t3","doc_id":"K241245","page_num":5,"bbox":[45.67,463.99,519.82,540.31],"n_rows":3,"n_cols":2,"columns":["Device Name","EchoGo Pro"],"rows":[["Device Name","EchoGo Pro"],["Manufacturer","Ultromics Limited"],["510(k) Number","K201555"]],"caption_candidate":"3. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241245-p8-t0","doc_id":"K241245","page_num":8,"bbox":[45.61,579.43,555.81,794.62],"n_rows":14,"n_cols":4,"columns":["Subgroups","Variations","N","AUROC (95% CI)"],"rows":[["Subgroups","Variations","N","AUROC (95% CI)"],["Age","18-65 years","1295","0.954 (0.941 - 0.966)"],["","≥65 years","4973","0.942 (0.936 - 0.948)"],["Sex","Male","3172","0.945 (0.937 - 0.952)"],["","Female","3095","0.954 (0.947 - 0.961)"],["Race","White","4927","0.949 (0.943 - 0.954)"],["","Black","343","0.953 (0.924 - 0.977)"],["","Asian","114","0.970 (0.938 - 0.992)"],["","Hispanic","156","0.965 (0.937 - 0.986)"],["","Other","727","0.921 (0.901 - 0.937)"],["LVEF","<30%","421","0.914 (0.883 - 0.941)"],["","≥30 to <50%","929","0.939 (0.925 - 0.953)"],["","≥50%","4887","0.950 (0.945 - 0.956)"],["BMI","18-25 kg/m2","1866","0.952 (0.943 - 0.961)"]],"caption_candidate":"EchoSolv AS performed consistently across all subgroups, refer to the results in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241245-p9-t0","doc_id":"K241245","page_num":9,"bbox":[45.6,65.16,555.82,141.5],"n_rows":5,"n_cols":4,"columns":["",">25 to 30 kg/m2","2075","0.951 (0.942 - 0.959)"],"rows":[["",">25 to 30 kg/m2","2075","0.951 (0.942 - 0.959)"],["",">30 to 35 kg/m2","1121","0.936 (0.922 - 0.949)"],["",">35 kg/m2","888","0.947 (0.932 - 0.960)"],["Inputs","Minimum inputs","6,268","0.931 (0.925 - 0.937)"],["","All available inputs","6,268","0.948 (0.942 - 0.952)"]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241280-p5-t0","doc_id":"K241280","page_num":5,"bbox":[72.62,391.51,552.65,693.89],"n_rows":10,"n_cols":4,"columns":["Trade Name:","","",""],"rows":[["Trade Name:","","",""],["Common Name:","","",""],["","","Class II",""],["Classification:","","",""],["","","21 CFR 892.2050",""],["Regulation\nNumber:","","",""],["","","QIH - Automated Radiological Image Processing Software\nLLZ - System, Image Processing, Radiological",""],["Product Code:","","",""],["Review Panel:","","Radiology",""],["Predicate Devices:","","Primary Predicate:\nManufacturer: CorticoMetrics, LLC\nTrade Name: THINQ\n510(k) Number: K192051\nProduct Code: LLZ","Secondary Predicate:\nManufacturer: AMRA Medical AB\nTrade Name: AMRA Profiler\n510(k) Number: K211983\nProduct Code: LNH"]],"caption_candidate":"Prepared","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241329-p4-t0","doc_id":"K241329","page_num":4,"bbox":[72.5,130.5,540.5,711.5],"n_rows":21,"n_cols":2,"columns":["DateSummary Prepared:","2024-07-09"],"rows":[["DateSummary Prepared:","2024-07-09"],["Contact Details",""],["Applicant Name:","Subtle Medical,Inc."],["Applicant Address:","883SantaCruz Ave,Suite205\nMenlo Park, CA94025UnitedStates"],["Applicant Contact:","Ms.RonnyElor"],["Applicant ContactTelephone:","(650) 397-8709"],["Applicant ContactEmail:","ronny@subtlemedical.com"],["Correspondent Name:","EnzymeCorporation"],["Correspondent Address:","611GatewayBlvd, Ste120\nSouth SanFrancisco,CA 94080 UnitedStates"],["Correspondent Contact:","Mr.Jared Seehafer"],["Correspondent ContactTelephone:","(415) 638-9554"],["Correspondent ContactEmail:","jared@enzyme.com"],["Device Name",""],["Device TradeName:","SubtleSYNTH (1.x)"],["Common Name:","Medicalimagemanagementand processingsystem"],["Classification Name:","AutomatedRadiological Image ProcessingSoftware"],["Regulation Number:","892.2050"],["Product Code:","QIH"],["Additional Product Codes:","LNH"],["Device Class:","ClassII"],["Legally MarketedPredicate\nDevice:","Predicate #:K201616\nPredicate TradeName: SyMRI\nPredicate Manufacturer:SyntheticMR AB"]],"caption_candidate":"Table 1.ContactDetails &Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p7-t0","doc_id":"K241331","page_num":7,"bbox":[72.28,362.49,327.37,717.98],"n_rows":16,"n_cols":6,"columns":["","Structure Name","","","Structure Type",""],"rows":[["","Structure Name","","","Structure Type",""],["Adductor brevis","","","Muscle","",""],["Adductor longus","","","Muscle","",""],["Adductor magnus","","","Muscle","",""],["Biceps femoris (long head)","","","Muscle","",""],["Biceps femoris (short head)","","","Muscle","",""],["Fibulari**","","","Muscle","",""],["Flexor Digitorum Longus","","","Muscle","",""],["Flexor Hallucis Longus","","","Muscle","",""],["Gastrocnemius (lateral head)","","","Muscle","",""],["Gastrocnemius (medial\nhead)","","","Muscle","",""],["Gemelli*","","","Muscle","",""],["Gluteus maximus","","","Muscle","",""],["Gluteus medius","","","Muscle","",""],["Gluteus minimus","","","Muscle","",""],["Gracilis","","","Muscle","",""]],"caption_candidate":"extensor hallucis longus, and fibularis tertius.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p8-t0","doc_id":"K241331","page_num":8,"bbox":[72.28,72.28,327.38,603.95],"n_rows":25,"n_cols":2,"columns":["Iliacus","Muscle"],"rows":[["Iliacus","Muscle"],["Obturator externus","Muscle"],["Obturator internus","Muscle"],["Pectineus","Muscle"],["Phalangeal extensors***","Muscle"],["Piriformis","Muscle"],["Popliteus","Muscle"],["Psoas major","Muscle"],["Quadratus femoris","Muscle"],["Quadratus lumborum","Muscle"],["Rectus femoris","Muscle"],["Sartorius","Muscle"],["Semimembranosus","Muscle"],["Semitendinosus","Muscle"],["Soleus","Muscle"],["Tensor fasciae latae","Muscle"],["Tibialis anterior","Muscle"],["Tibialis Posterior","Muscle"],["Vastus intermedius","Muscle"],["Vastus lateralis","Muscle"],["Vastus medialis","Muscle"],["Pelvis","Bone"],["Femur","Bone"],["Tibia","Bone"],["Fibula","Bone"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p9-t0","doc_id":"K241331","page_num":9,"bbox":[72.29,431.5,539.96,719.48],"n_rows":7,"n_cols":5,"columns":["Topic","","AMRA Profiler (510k Number:","","MuscleView"],"rows":[["Topic","","AMRA Profiler (510k Number:","","MuscleView"],["","","K173749)","",""],["Physical\nCharacteristics","A service that is provided with a\ncloud-based service using an\nautomated image-analysis pipeline\n(with manual quality control for scan\npreprocessing and label quality\ncontrol)","","","Software package that operates on a\nvirtual machine within off-the-shelf\nhardware"],["Computer","Not applicable","","","PC Compatible"],["DICOM\nStandard\nCompliance","The service processes DICOM\ncompliant image data in accordance\nwith a required MRI protocol.","","","The software processes DICOM\ncompliant image data"],["Modalities","MRI","","","MRI"],["MRI\nParameters of\nImportance","Collected Series: 3D Dixon water and\nfat phase.\nRegion of Interest: Lower extremity,\nUpper body as well\nSupported Field Strength:","","","The same except that we support a\nlarger variability in scan properties\nand coverage"]],"caption_candidate":"Table 2. Summary of technological characteristic comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p10-t0","doc_id":"K241331","page_num":10,"bbox":[72.27,72.28,539.98,485.15],"n_rows":6,"n_cols":3,"columns":["","Direction of Capture: Axial\nSupported In-Plane Resolution:\nSupported Slice Spacing:\nNote: Rigid conformity to MRI\nprotocol is needed.",""],"rows":[["","Direction of Capture: Axial\nSupported In-Plane Resolution:\nSupported Slice Spacing:\nNote: Rigid conformity to MRI\nprotocol is needed.",""],["User Interface","Concierge Service. Data is provided\nand analyzed, and results returned","The software is designed for use on\na workstation with a web-based user\ninterface. Functionalities are largely\nthe same."],["Segmentation\nStructures","12 individual muscles and 6 muscle\ngroups across the lower and upper\nextremity and liver","Eighty (8 bones, 72 muscles)\nindividual structures on both the left\nand right side for the lower extremity\nfocused region."],["Segmentation\nMetrics","Muscle Volume, Fat Fraction","Structure volume, muscle fat\ninfiltration, and derived metrics\nincluding asymmetry, muscle length,\nand cross-sectional area"],["Overall\nSegmentation\nMethod","Labeled muscle segmentations\nautomatically generated using non-\nrigid image registration to atlases\nutilizing 2D analysis techniques","AI segmentation model-based\napproach using a library of expert\ncontours for training, MuscleView\nuses a machine learning-based\nmethod to train CNNs from expert\ncontours to perform segmentation on\nthe target images to generate\ncontours"],["Support of\nManual Editing\nby customer","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p11-t0","doc_id":"K241331","page_num":11,"bbox":[72.84,368.76,547.91,710.91],"n_rows":16,"n_cols":4,"columns":["Factor","Groups","Training data","Validation data"],"rows":[["Factor","Groups","Training data","Validation data"],["Number of unique scans","n/a","1658","148"],["Number of unique subjects","n/a","1294","148"],["Gender","Male (%)","1192*","102"],["","Female (%)","374*","46"],["Age*","Mean","29","31.7"],["","Standard Deviation","13.4","15.5"],["Ethnicity\n(based on regional\ndemographics)","% Non-Hispanic White","52","52"],["","% Hispanic/Latino","18","18"],["","% Black/African American","14","14"],["","% Asian","10","10"],["","% Australian","2","2"],["","% American Indian /\nAlaska Native","<1","<1"],["","% Native Hawaiian /\nPacific Islander","<1","<1"],["","% Australian Aboriginal","<1","<1"],["","% Other","2","2"]],"caption_candidate":"were not available for some scans.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241331-p12-t0","doc_id":"K241331","page_num":12,"bbox":[72.83,72.84,547.93,166.49],"n_rows":5,"n_cols":4,"columns":["MRI Manufacturer","Siemens","680","74"],"rows":[["MRI Manufacturer","Siemens","680","74"],["","GE Medical Systems","435","28"],["","Philips Medical Systems","82","29"],["","Canon","1","4"],["","Other (Toshiba) or\nUnknown","460","13"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241350-p6-t0","doc_id":"K241350","page_num":6,"bbox":[72.05,613.44,525.55,711.0],"n_rows":4,"n_cols":7,"columns":["Specification","","Predicate Device 1","","","Proposed Device",""],"rows":[["Specification","","Predicate Device 1","","","Proposed Device",""],["","","Xeleris V Processing and Review","","","Clarify DL",""],["","","System (K221680)","","","on Xeleris V",""],["Technology","OSEM-based Iterative Image\nReconstruction","","","OSEM-based Iterative Image\nReconstruction with integrated deep\nlearning model trained to reduce noise","",""]],"caption_candidate":"feature / technological differences between the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241350-p7-t0","doc_id":"K241350","page_num":7,"bbox":[72.05,113.16,525.55,222.6],"n_rows":4,"n_cols":7,"columns":["Specification","","Predicate Device 2","","","Proposed Device",""],"rows":[["Specification","","Predicate Device 2","","","Proposed Device",""],["","","StarGuide (K221680)","","","Clarify DL",""],["","","including Smart Console","","","on StarGuide’s Smart Console",""],["Technology","OSEM-based and BSREM-based\nIterative Image Reconstruction","","","OSEM-based and BSREM-based Iterative\nImage Reconstruction with integrated deep\nlearning model trained to reduce noise","",""]],"caption_candidate":"510(k) Premarket Notification Submission for Clarify DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p5-t0","doc_id":"K241380","page_num":5,"bbox":[72.34,173.78,539.86,403.89],"n_rows":4,"n_cols":4,"columns":["Owner","","","Diagnoly\n60 Avenue Rockefeller\n69008 Lyon, France\n+33(0)4.78.76.85.75"],"rows":[["Owner","","","Diagnoly\n60 Avenue Rockefeller\n69008 Lyon, France\n+33(0)4.78.76.85.75"],["Primary contact\nperson","","","Ivan Voznyuk\nChief Executive Officer\nDiagnoly\nPhone: +33(0)6.95.87.04.55\nEmail: ivan@diagnoly.com"],["Secondary contact\nperson","","","Nima Akhlaghi\nAssociate Director, Digital Health Regulatory Affairs\nMCRA, LLC\nPhone: 202.742.3889\nEmail: nakhlaghi@mcra.com"],["","Date prepared","","2024-08-30"]],"caption_candidate":"1 510(k) owner","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p5-t1","doc_id":"K241380","page_num":5,"bbox":[72.34,462.99,539.86,597.27],"n_rows":4,"n_cols":4,"columns":["","Trade Name","","FETOLY-HEART"],"rows":[["","Trade Name","","FETOLY-HEART"],["Classification name","Classification name","","Accessory to Ultrasonic Pulsed Doppler Imaging System, 21 CFR 892.1550\nAccessory to Ultrasonic Pulsed Echo Imaging System, 21 CFR 892.1560\nMedical image management and processing system, 21 CFR 892.2050"],["","Class","","II"],["Product code","Product code","","IYN (Primary)\nIYO, QIH (secondary)"]],"caption_candidate":"2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p6-t0","doc_id":"K241380","page_num":6,"bbox":[72.49,562.45,567.52,707.1],"n_rows":12,"n_cols":3,"columns":["Heart views","Quality criteria within the views",""],"rows":[["Heart views","Quality criteria within the views",""],["","(A1) Sp","Spine"],["","(A2) lRb","Left rib"],["","(A3) rRb","Right rib"],["","(A4) Ao","Descending aorta"],["","(A5) VC","Inferior vena cava"],["","(A6) St","Stomach"],["(A) ABD","",""],["Abdomen view","(A7) Uv","Umbilical vein"],["(n = 8)","(A8) Ap","Thorax apex"],["","",""],["","(B1) Sp","Spine"]],"caption_candidate":"4.1 Definition of a complete examination","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p7-t0","doc_id":"K241380","page_num":7,"bbox":[72.45,102.3,567.52,704.79],"n_rows":62,"n_cols":3,"columns":["","(B2) lRb","Left rib"],"rows":[["","(B2) lRb","Left rib"],["","(B3) rRb","Right rib"],["","(B4) Ao","Descending aorta"],["","(B5) lPV","Left pulmonary vein"],["","(B6) rPV","Right pulmonary vein"],["","(B7) LA","Left atrium"],["","(B8) RA","Right atrium"],["(B) 4CH","(B9) FOP","Foramen Ovale flap (Vieussens valve)"],["Four chamber view","(B10) FO","Open Foramen Ovale"],["(n = 19)","",""],["","(B11) MV","Mitral valve"],["","",""],["","(B12) TV","Tricuspid valve"],["","(B13) bCr","Connection between crux and atrial septum (vestibular septum)"],["","(B14) Cr","Atrioventricular valve offset in crux"],["","(B15) tCr","Connection between interventricular septum and crux"],["","(B16) IVS","Interventricular septum"],["","(B17) LV","Left ventricle"],["","(B18) RV","Right ventricle"],["","(B19) Str","Sternum"],["","",""],["","(C1) LA","Left atrium"],["","",""],["","",""],["","(C2) aAo","Proximal ascending aorta"],["","",""],["","",""],["","(C3) SV","Semilunar valves"],["","",""],["","",""],["","(C4) LV","Left ventricle"],["","",""],["","",""],["","(C5) IVS","Interventricular septum"],["(C) LVOT","",""],["","",""],["Left Ventricular Outflow Tract view","",""],["","(C6) RV","Right ventricle"],["(n = 6)","",""],["","",""],["","(D1) dAo","Descending aorta"],["","(D2) Tr","Trachea / bronchi"],["","(D3) lPA","Left pulmonary artery"],["","(D4) Du","Ductus arteriosus"],["","(D5) rPA","Right pulmonary artery"],["","(D6) Or","Origin of pulmonary arteries"],["(D) RVOT","(D7) S","Septum between pulmonary artery trunk and ascending aorta"],["Right Ventricular Outflow Tract view","(D8) aAo","Ascending aorta"],["(n = 10)","(D9) SVC","Superior vena cava"],["","(D10) PA","Pulmonary trunk"],["","(E1) Sp","Spine"],["","(E2) Tr","Trachea"],["","(E3) ES","Side space on the left of ductus / pulmonary artery"],["","(E4) PA","Main pulmonary artery"],["","(E5) Du","Ductus (Ductal arch)"],["","(E6) aAo","Ascending aorta"],["(E) 3VX","(E7) aAr","Aortic arch"],["Three vessels view","",""],["","(E8) SVC","Superior vena cava"],["(n = 9)","",""],["","(E9) Th","Thymus / sternum"],["","",""]],"caption_candidate":"510(k) Summary — K241380","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p9-t0","doc_id":"K241380","page_num":9,"bbox":[72.43,154.7,539.69,698.14],"n_rows":12,"n_cols":9,"columns":["Aspect","","Predicate device:\nSonio Detect\n(Cardiac Features)\nK240406","","Reference device:","","Proposed device:\nFETOLY-HEART","Comparison between\nProposed and\nPredicate device",""],"rows":[["Aspect","","Predicate device:\nSonio Detect\n(Cardiac Features)\nK240406","","Reference device:","","Proposed device:\nFETOLY-HEART","Comparison between\nProposed and\nPredicate device",""],["","","","","Voluson Expert","","","",""],["","","","","18/20/22 (Cardiac-","","","",""],["","","","","related SonolystLive","","","",""],["","","","","Feature)","","","",""],["","","","","K220358","","","",""],["","General","","","","","","",""],["Manufacturer\nname","","Sonio","GE Healthcare","","","Diagnoly","NA",""],["Device name","","Cardiac-related\nfeatures in Sonio\nDetect","Cardiac-related\nSonolystLive in the\nVoluson Expert\n18/20/22","","","FETOLY-HEART","NA",""],["Product\ncode(s)","","IYN (Primary)\nIYO, QIH (secondary)","IYN (Primary)\nIYO, ITX (Secondary)","","","IYN (Primary)\nIYO, QIH (secondary)","Substantially\nequivalent\nPrimary codes are the\nsame for all devices",""],["Regulation\nnumber","","- Accessory to\nUltrasonic Pulsed\nDoppler Imaging\nSystem, 21 CFR\n892.1550\n- Accessory to\nUltrasonic Pulsed\nEcho Imaging System,\n21 CFR 892.1560","- Ultrasonic Pulsed\nDoppler Imaging\nSystem, 21 CFR\n892.1550\n- Ultrasonic Pulsed\nEcho Imaging System,\n21 CFR 892.1560\n- Diagnostic\nUltrasound\nTransducer, 21 CFR\n892.1570, 90-ITX","","","- Accessory to\nUltrasonic Pulsed\nDoppler Imaging\nSystem, 21 CFR\n892.1550\n- Accessory to\nUltrasonic Pulsed\nEcho Imaging System,\n21 CFR 892.1560\n- Medical image\nmanagement and\nprocessing system,\n21 CFR 892.2050","Substantially\nequivalent\nAll devices are class II\ndevices subject to\n510(k) regulatory\npathway.",""],["Brief\ndescription","","The predicate device\nis a software that\naims at helping\nsonographers,\nOB/GYNs, MFMs and\nFetal surgeons (all\nthree designated as\nhealthcare\nprofessionals i.e.\nHCP) to perform their\nroutine fetal heart\nultrasound","The reference device\nis a software that\naims at helping\nsonographers,\nOB/GYNs, MFMs and\nFetal surgeons (all\nthree designated as\nhealthcare\nprofessionals i.e.\nHCP) to perform their\nroutine fetal heart\nultrasound","","","FETOLY-HEART is a\nsoftware that aims at\nhelping\nsonographers,\nOB/GYNs, MFMs and\nFetal surgeons (all\nthree designated as\nhealthcare\nprofessionals i.e.\nHCPs) to perform\ntheir routine fetal\nheart ultrasound","Substantially\nequivalent\nThe subject device\nand the predicate\ndevices have the\nsame objective.",""]],"caption_candidate":"compared to the predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p10-t0","doc_id":"K241380","page_num":10,"bbox":[72.38,127.7,539.74,709.78],"n_rows":4,"n_cols":5,"columns":["Indications for\nuse","The predicate device\nis intended to analyze\nfetal ultrasound\nimages and clips\nusing machine\nlearning techniques\nto automatically\ndetect heart views,\ndetect anatomical\nstructures within the\nviews and verify\nquality criteria of the\nviews.\nThe device is\nintended for use as a\nconcurrent reading\naid during the\nacquisition and\ninterpretation of fetal\nultrasound images.","The device is a\ngeneral purpose\nultrasound system\nintended for use by\nqualified and trained\nhealthcare\nprofessionals.","FETOLY-HEART is\nintended to analyse\nfetal ultrasound\nimages and clips\nusing machine\nlearning techniques\nto automatically\ndetect heart views\nand quality criteria\nwithin the views. The\ndevice is intended for\nuse as a concurrent\nreading aid during\nthe acquisition and\ninterpretation of fetal\nultrasound images.\nFETOLY-HEART is\nindicated for use\nduring routine fetal\nheart examination of\n2nd and 3rd\ntrimester pregnancy\n(gestational age:\nfrom 17 to 40 weeks).","Substantially\nequivalent\nIndications for Use\nare the same\nbetween predicate\nand subject devices."],"rows":[["Indications for\nuse","The predicate device\nis intended to analyze\nfetal ultrasound\nimages and clips\nusing machine\nlearning techniques\nto automatically\ndetect heart views,\ndetect anatomical\nstructures within the\nviews and verify\nquality criteria of the\nviews.\nThe device is\nintended for use as a\nconcurrent reading\naid during the\nacquisition and\ninterpretation of fetal\nultrasound images.","The device is a\ngeneral purpose\nultrasound system\nintended for use by\nqualified and trained\nhealthcare\nprofessionals.","FETOLY-HEART is\nintended to analyse\nfetal ultrasound\nimages and clips\nusing machine\nlearning techniques\nto automatically\ndetect heart views\nand quality criteria\nwithin the views. The\ndevice is intended for\nuse as a concurrent\nreading aid during\nthe acquisition and\ninterpretation of fetal\nultrasound images.\nFETOLY-HEART is\nindicated for use\nduring routine fetal\nheart examination of\n2nd and 3rd\ntrimester pregnancy\n(gestational age:\nfrom 17 to 40 weeks).","Substantially\nequivalent\nIndications for Use\nare the same\nbetween predicate\nand subject devices."],["Targeted\npopulation","Pregnant women\nduring the 2nd and\n3rd trimester of\npregnancy","Pregnant women\nduring the 2nd\ntrimester of\npregnancy","Pregnant women\nduring the 2nd and\n3rd trimester of\npregnancy","Substantially\nequivalent\nSubject device has\nthe same intended\npatient population\nthan the predicate\ndevices."],["Clinical\noutcome","- Images labeled with\ncorrect fetal heart\nview","- Images labeled\nwith correct fetal\nheart view","- Images labeled with\ncorrect fetal heart\nview for patient cases","Substantially\nequivalent\nPerformance testing\nhas successfully\nvalidated the clinical\noutcomes"],["","- Quality criteria\nidentified as\n“Verified” when\ndetected and “Not\nverified” when not\ndetected","- Quality criteria\nidentified as “Found”\nwhen detected and\n“Not found” when\nnot detected","- Quality criteria\nidentified as\n“Verified” when\ndetected and “Not","Substantially\nequivalent\nIn the subject device,\nquality criteria\nbounding box\nlocalization can be"]],"caption_candidate":"time. time. time.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p11-t0","doc_id":"K241380","page_num":11,"bbox":[72.41,243.02,539.71,698.38],"n_rows":5,"n_cols":7,"columns":["Intended user","","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Substantially\nequivalent\nSubject device has\nthe same intended\nusers as the predicate\ndevices.",""],"rows":[["Intended user","","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Substantially\nequivalent\nSubject device has\nthe same intended\nusers as the predicate\ndevices.",""],["Clinical\napplications","","Fetal/Obstetrics","Fetal/Obstetrics","Fetal/Obstetrics","Substantially\nequivalent\nClinical application is\nthe same for subject\nand predicate\ndevices.",""],["Inclusion of a\nPCCP","","N/A","N/A","Included","Different\nThe PCCP in the\nsubject device\nincludes proposed\nmodifications related\nto modifying model\ntraining\nhyperparameters,\nadditional retraining\nwith new training and\nvalidation datasets\ncollected, and\naddition/removal of\nheart quality criteria.",""],["","Functionality 1: completeness overview","","","","",""],["Automatically\ndetect views","","Detection of 4ch, 3vx,\nLVOT, RVOT and Abd\nviews (complete\nimplementation of\nISUOG\nrecommendations)","Detection of 4ch, 3vx,\nLVOT, RVOT and Abd\nviews (complete\nimplementation of\nISUOG\nrecommendations)","Detection of 4ch, 3vx,\nLVOT, RVOT and Abd\nviews (complete\nimplementation of\nISUOG\nrecommendations)","Substantially\nequivalent\nThe subject device\nincludes the\ndetection of the same\nviews than the\npredicate device.",""]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p12-t0","doc_id":"K241380","page_num":12,"bbox":[72.44,286.55,539.69,711.82],"n_rows":5,"n_cols":7,"columns":["","Functionality 2: completeness illustration","","","","",""],"rows":[["","Functionality 2: completeness illustration","","","","",""],["Automatically\nselects views","","NA","Automatic suggestion\nof views from a\nsequence of images.","Automatic extraction\nof views from a\nsequence of images.","Substantially\nequivalent\nThis image selection\nfunctionality is a\nfeature absent in the\npredicate device but\npresent in the\nreference device.\nSoftware testing has\nbeen performed to\nvalidate its use and\ndoes not introduce\nnew questions of\nsafety and\neffectiveness.",""],["","Technical characteristics","","","","",""],["Data input","","Accepts images and\nimage sequences\nfrom ultrasound\nmachines","Accepts images and\nimage sequences\nfrom ultrasound\nmachines","Accepts images and\nimage sequences\nfrom ultrasound\nmachines","Substantially\nequivalent\nThe input data is the\nsame for the subject\ndevice and the\npredicate and\nreference devices.",""],["Algorithm\nMethodology","","Artificial Intelligence:\nUtilizes computer\nvision algorithms to\nanalyze ultrasound\nimages and provides\nvisualization of\ndetected landmarks\nand views","Artificial Intelligence:\nUtilizes computer\nvision algorithms to\nanalyze ultrasound\nimages and provides\nvisualization of\ndetected landmarks\nand views","Artificial Intelligence:\nUtilizes computer\nvision algorithms to\nanalyze ultrasound\nimages and provides\nvisualization of\ndetected landmarks\nand views","Substantially\nequivalent\nThe subject device\nand the primary\npredicate device use\nboth artificial\nintelligence.",""]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p13-t0","doc_id":"K241380","page_num":13,"bbox":[72.38,273.65,539.74,541.51],"n_rows":2,"n_cols":5,"columns":["Ultrasound\nMachine\ncompatibility","Compatible with\nultrasound system\nfrom GE Medical,\nSamsung, Canon and\nPhilips","NA","Compatible with\nultrasound system\nfrom GE Medical,\nSamsung and Canon","Substantially\nequivalent\nThis compatibility has\nbeen tested and\nvalidated as part of\ndevice\ngeneralizability in the\nperformance testing\nstudy."],"rows":[["Ultrasound\nMachine\ncompatibility","Compatible with\nultrasound system\nfrom GE Medical,\nSamsung, Canon and\nPhilips","NA","Compatible with\nultrasound system\nfrom GE Medical,\nSamsung and Canon","Substantially\nequivalent\nThis compatibility has\nbeen tested and\nvalidated as part of\ndevice\ngeneralizability in the\nperformance testing\nstudy."],["User\ninteraction","The user can interact\nwith the software to\noverride the\nsoftware’s outputs.\nThe user has the\nability to review and\nedit/override the\nmatching at any time\nduring or at the end\nof the exam.","NA","The user can interact\nwith the software to\noverride the\nsoftware’s outputs.\nThe user has the\nability to review and\nedit/override the\nmatching at any time\nduring or at the end\nof the exam.","Substantially\nequivalent\nUser interactions are\nthe same between\nprimary predicate\nand subject devices."]],"caption_candidate":"concerns.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p14-t0","doc_id":"K241380","page_num":14,"bbox":[72.47,385.01,540.13,710.26],"n_rows":4,"n_cols":4,"columns":["Modification","Rationale","Testing Methods","Impact Assessment"],"rows":[["Modification","Rationale","Testing Methods","Impact Assessment"],["","","",""],["Modification of\ntraining and/or\nvalidation datasets","Increase or recovery (in\ncase of data drift) of\nFETOLY-HEART’s\nperformance.","Re-training of the FETOLY-\nHEART model with new\ndata to optimize its\nperformance followed by\ninternal testing and a\ncomparison of the initial\nmodel to the modified\nmodel using performance\nmetrics on the test\ndataset.","Increased performance metrics of the\nmodified model for view or quality\ncriteria detection.\nBenefits: Increase or recovery of\nperformance; generalization for\ndiverse cases.\nRisks: Performance decrease\n(overfitting, unintended bias).\nRisk mitigation: The modified model\nwill be tested for superiority on the\nperformance study test dataset which\nwill contain new unseen data."],["Modification of\nmodel training\nhyperparameters","Improvement and\noptimization of FETOLY-\nHEART’s performance","Re-training of the FETOLY-\nHEART model with new\nparameters to optimize its\nperformance followed by\ninternal testing and a\ncomparison of the initial\nmodel to the modified\nmodel using performance","Increased performance metrics of the\nmodified model for view or quality\ncriteria detection.\nBenefits: Increased performance;\ngeneralization for diverse cases.\nRisks: Performance decrease\n(overfitting, unintended bias)."]],"caption_candidate":"Summary of changes to FETOLY-HEART per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p15-t0","doc_id":"K241380","page_num":15,"bbox":[72.46,662.6,539.77,717.22],"n_rows":6,"n_cols":7,"columns":["","Sensitivity","","","Specificity","",""],"rows":[["","Sensitivity","","","Specificity","",""],["Fetal heart view","","Point","Bootstrap CI","","Point","Bootstrap CI"],["","N(positive)","","","N(negative)","",""],["","","estimate","(95%)","","estimate","(95%)"],["","","","","","",""],["Abdomen view","428","0.976","(0.960,0.990)","1860","0.998","(0.996,1.000)"]],"caption_candidate":"tables below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p16-t0","doc_id":"K241380","page_num":16,"bbox":[72.52,102.14,539.59,200.18],"n_rows":5,"n_cols":7,"columns":["Four chamber view","391","0.987","(0.974,0.997)","1897","1.00","(1.000,1.000)"],"rows":[["Four chamber view","391","0.987","(0.974,0.997)","1897","1.00","(1.000,1.000)"],["Left ventricular outflow\ntract view","360","0.983","(0.969,0.994)","1928","0.999","(0.998,1.000)"],["Right ventricular outflow\ntract view","313","0.987","(0.974,0.996)","1975","0.998","(0.996,1.000)"],["Three vessels view","316","0.981","(0.965,0.993)","1972","0.998","(0.997,1.000)"],["Other view","480","0.985","(0.972,0.995)","1808","0.983","(0.977,0.989)"]],"caption_candidate":"510(k) Summary — K241380","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p16-t1","doc_id":"K241380","page_num":16,"bbox":[72.52,243.13,539.59,696.58],"n_rows":30,"n_cols":11,"columns":["","","Sensitivity","","","Specificity","","","mIoU","",""],"rows":[["","","Sensitivity","","","Specificity","","","mIoU","",""],["Quality criterion","","","Point","Bootstrap CI","","Point","Bootstrap CI","Point","Bootstrap CI",""],["","","N","","","N","","","","",""],["","","","estimate","(95%)","","estimate","(95%)","estimate","(95%)",""],["","","","","","","","","","",""],["Abdomen view","","","","","","","","","",""],["Spine","","417","0.966","(0.949,0.981)","1871","0.995","(0.992,0.998)","0.739","(0.728,0.750)",""],["Left rib","","401","0.903","(0.873,0.933)","1887","0.997","(0.995,0.999)","0.651","(0.631,0.673)",""],["Right rib","","388","0.910","(0.882,0.940)","1900","0.997","(0.994,0.999)","0.624","(0.602,0.643)",""],["Descending aorta","","417","0.947","(0.925,0.969)","1871","0.998","(0.996,0.999)","0.528","(0.515,0.542)",""],["Inferior vena cava","","363","0.915","(0.884,0.941)","1925","0.992","(0.988,0.996)","0.512","(0.496,0.528)",""],["Stomach","","414","0.976","(0.961,0.988)","1874","0.995","(0.992,0.998)","0.734","(0.720,0.746)",""],["Umbilical vein","","345","0.962","(0.942,0.980)","1943","0.991","(0.987,0.994)","0.676","(0.660,0.693)",""],["Thorax apex","","397","0.919","(0.893,0.944)","1891","0.993","(0.989,0.997)","0.571","(0.549,0.592)",""],["","Four chamber view","","","","","","","","",""],["Spine","","339","0.965","(0.944,0.982)","1949","0.999","(0.997,1.000)","0.768","(0.754,0.779)",""],["Left rib","","308","0.945","(0.917,0.970)","1980","0.996","(0.993,0.999)","0.744","(0.726,0.764)",""],["Right rib","","309","0.958","(0.934,0.980)","1979","0.996","(0.993,0.998)","0.749","(0.730,0.768)",""],["Descending aorta","","361","0.981","(0.965,0.994)","1927","0.996","(0.994,0.999)","0.646","(0.632,0.659)",""],["Left pulmonary vein","","127","0.921","(0.871,0.965)","2161","0.998","(0.995,1.000)","0.628","(0.601,0.653)",""],["Right pulmonary vein","","198","0.904","(0.860,0.943)","2090","0.996","(0.993,0.999)","0.601","(0.578,0.623)",""],["Left atrium","","387","0.990","(0.979,0.997)","1901","0.998","(0.996,1.000)","0.759","(0.747,0.771)",""],["Right atrium","","391","0.987","(0.975,0.997)","1897","1.00","(1.000,1.000)","0.774","(0.763,0.786)",""],["Foramen ovale flap","","113","0.929","(0.883,0.971)","2175","1.00","(0.999,1.000)","0.530","(0.505,0.561)",""],["Open Foramen Ovale","","348","0.951","(0.928,0.972)","1940","0.996","(0.993,0.999)","0.616","(0.598,0.634)",""],["Mitral valve","","207","0.908","(0.866,0.948)","2081","0.998","(0.995,1.000)","0.676","(0.654,0.695)",""],["Tricuspid valve","","243","0.959","(0.931,0.983)","2045","0.995","(0.992,0.998)","0.718","(0.701,0.735)",""],["Connection between\ncrux and atrial septum","","299","0.943","(0.915,0.969)","1989","0.990","(0.986,0.994)","0.587","(0.567,0.603)",""],["Atrioventricular valve\noffset in crux","","115","0.939","(0.897,0.980)","2173","0.992","(0.988,0.995)","0.648","(0.623,0.673)",""],["Connection between\ninterventricular\nseptum and crux","","177","0.910","(0.868,0.951)","2111","0.996","(0.993,0.999)","0.565","(0.544,0.585)",""]],"caption_candidate":"Other view 480 0.985 (0.972,0.995) 1808 0.983 (0.977,0.989)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p17-t0","doc_id":"K241380","page_num":17,"bbox":[77.42,105.47,531.37,745.27],"n_rows":92,"n_cols":8,"columns":["Interventricular","","","","","","",""],"rows":[["Interventricular","","","","","","",""],["","216 0.917","(0.877,0.949)","2072","0.996","(0.993,0.999)","0.71","(0.689,0.728)"],["","","","","","","",""],["septum","","","","","","",""],["","","","","","","",""],["Left ventricle","389 0.987","(0.975,0.997)","1899","1.00","(1.000,1.000)","0.748","(0.734,0.761)"],["","","","","","","",""],["Right ventricle","387 0.990","(0.979,0.997)","1901","0.999","(0.997,1.000)","0.758","(0.746,0.770)"],["","","","","","","",""],["Sternum","322 0.972","(0.952,0.988)","1966","0.991","(0.986,0.995)","0.681","(0.661,0.700)"],["","","","","","","",""],["eft ventricular outflow t","ract view","","","","","",""],["","","","","","","",""],["Left atrium","356 0.98","(0.966,0.992)","1932","0.997","(0.995,0.999)","0.656","(0.633,0.676)"],["","","","","","","",""],["Proximal ascending","","","","","","",""],["","","","","","","",""],["","360 0.983","(0.969,0.994)","1928","0.999","(0.998,1.000)","0.716","(0.702,0.730)"],["aorta","","","","","","",""],["","","","","","","",""],["Semilunar valves","165 0.909","(0.866,0.950)","2123","0.998","(0.995,1.000)","0.527","(0.503,0.552)"],["","","","","","","",""],["Left ventricle","358 0.978","(0.961,0.992)","1930","0.999","(0.998,1.000)","0.745","(0.732,0.758)"],["","","","","","","",""],["Interventricular","","","","","","",""],["","","","","","","",""],["","199 0.925","(0.888,0.959)","2089","0.995","(0.992,0.998)","0.663","(0.638,0.690)"],["septum","","","","","","",""],["","","","","","","",""],["Right ventricle","358 0.980","(0.964,0.992)","1930","0.999","(0.997,1.000)","0.698","(0.675,0.719)"],["","","","","","","",""],["ight ventricular outflow","tract view","","","","","",""],["","","","","","","",""],["Descending aorta","294 0.949","(0.924,0.971)","1994","0.997","(0.994,0.999)","0.617","(0.595,0.638)"],["","","","","","","",""],["Trachea / bronchi","180 0.922","(0.882,0.960)","2108","0.990","(0.985,0.994)","0.520","(0.491,0.548)"],["","","","","","","",""],["Left pulmonary artery","125 0.960","(0.921,0.992)","2163","0.995","(0.992,0.998)","0.615","(0.582,0.646)"],["","","","","","","",""],["Ductus arteriosus","177 0.944","(0.907,0.974)","2111","0.997","(0.995,0.999)","0.631","(0.606,0.656)"],["","","","","","","",""],["Right pulmonary","","","","","","",""],["","","","","","","",""],["","302 0.980","(0.965,0.994)","1986","0.994","(0.991,0.997)","0.654","(0.633,0.675)"],["artery","","","","","","",""],["","","","","","","",""],["Origin of pulmonary","","","","","","",""],["","258 0.922","(0.889,0.953)","2030","0.997","(0.994,0.999)","0.589","(0.568,0.610)"],["","","","","","","",""],["arteries","","","","","","",""],["","","","","","","",""],["Septum between","","","","","","",""],["pulmonary artery","","","","","","",""],["","218 0.945","(0.911,0.973)","2070","0.993","(0.989,0.996)","0.692","(0.672,0.710)"],["","","","","","","",""],["trunk and ascending","","","","","","",""],["aorta","","","","","","",""],["","","","","","","",""],["Ascending aorta","312 0.974","(0.957,0.990)","1976","0.998","(0.996,1.000)","0.633","(0.613,0.650)"],["","","","","","","",""],["Superior vena cava","218 0.940","(0.910,0.971)","2070","0.994","(0.991,0.998)","0.577","(0.549,0.603)"],["","","","","","","",""],["Pulmonary trunk","312 0.971","(0.952,0.990)","1976","0.999","(0.998,1.000)","0.760","(0.744,0.775)"],["","","","","","","",""],["hree vessels views","","","","","","",""],["","","","","","","",""],["Spine","276 0.953","(0.929,0.975)","2012","0.998","(0.996,1.000)","0.792","(0.779,0.805)"],["","","","","","","",""],["Trachea","206 0.932","(0.899,0.964)","2082","0.997","(0.994,0.999)","0.539","(0.517,0.562)"],["","","","","","","",""],["Side space on the left","","","","","","",""],["","","","","","","",""],["","270 0.933","(0.901,0.961)","2018","0.991","(0.987,0.995)","0.784","(0.767,0.800)"],["of ductus","","","","","","",""],["","","","","","","",""],["Main pulmonary","","","","","","",""],["","","","","","","",""],["","169 0.947","(0.910,0.976)","2119","0.999","(0.998,1.000)","0.733","(0.708,0.755)"],["artery","","","","","","",""],["","","","","","","",""],["Ductus","141 0.972","(0.944,0.993)","2147","0.998","(0.996,1.000)","0.749","(0.724,0.771)"],["","","","","","","",""],["Ascending aorta","181 0.978","(0.954,0.995)","2107","0.999","(0.997,1.000)","0.621","(0.599,0.643)"],["","","","","","","",""],["Aortic arch","133 0.97","(0.942,0.993)","2155","0.997","(0.995,0.999)","0.724","(0.699,0.747)"],["","","","","","","",""],["Superior vena cava","303 0.964","(0.942,0.983)","1985","0.996","(0.994,0.999)","0.528","(0.508,0.547)"],["","","","","","","",""],["Thymus/sternum","212 0.915","(0.876,0.953)","2076","0.998","(0.995,1.000)","0.716","(0.693,0.737)"],["","","","","","","",""],["Document number: 300-TEMP-","17 version 01","","","","","","Page 13 / 1"],["Application date: 2023-11-30","","","","","","",""]],"caption_candidate":"Interventricular","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241380-p18-t0","doc_id":"K241380","page_num":18,"bbox":[72.59,210.68,540.57,706.72],"n_rows":38,"n_cols":4,"columns":["","","Number of cases","Number of images"],"rows":[["","","Number of cases","Number of images"],["Subgroup","","",""],["","","(total=480)","(total=2,288)"],["","Center 1","99 (20.6%)","505 (22.1%)"],["","Center 2","63 (13.1%)","248 (10.8%)"],["","Center 3","84 (17.5%)","378 (16.5%)"],["Center","Center 4","55 (11.5%)","264 (11.5%)"],["","Center 5","54 (11.2%)","275 (12.0%)"],["","Center 6","55 (11.5%)","265 (11.6%)"],["","Center 7","70 (14.6%)","353 (15.4%)"],["","US","234 (48.8%)","1157 (50.6%)"],["Territory","","",""],["","EU","246 (51.2%)","1131 (49.4%)"],["","","",""],["","2nd trimester","233 (48.5%)","1189 (52.0%)"],["Gestational age","3rd trimester","243 (50.6%)","1075 (47.0%)"],["","Unknown","4 (0.8%)","24 (1.0%)"],["","< 20 years","27 (5.6%)","128 (5.6%)"],["","[20-29] years","214 (44.6%)","1020 (44.6%)"],["Maternal age","[30-39] years","194 (40.4%)","901 (39.4%)"],["","≥40 years","26 (5.4%)","127 (5.6%)"],["","Unknown","19 (4.0%)","112 (4.9%)"],["","<18.5 kg/m2","20 (4.2%)","99 (4.3%)"],["","[18.5;24.9] kg/m2","137 (28.5%)","661 (28.9%)"],["BMI","[25;29.9] kg/m2","108 (22.5%)","491 (21.5%)"],["","≥30 kg/m2","157 (32.7%)","712 (31.1%)"],["","Unknown","58 (12.1%)","325 (14.2%)"],["","General Electric","163 (34.0%)","781 (34.1%)"],["Scanner manufacturer","Samsung","297 (61.9%)","1405 (61.4%)"],["","Canon","20 (4.2%)","102 (4.5%)"],["","Abnormal","32 (6.7%)","179 (7.8%)"],["Fetus cardiac normality","","",""],["","Normal","448 (93.3%)","2109 (92.2%)"],["","","",""],["","Bad","-","708 (30.9%)"],["Image digital quality","Average","-","815 (35.6%)"],["","Good","-","765 (33.4%)"],["Image type","Full exam video frame","-","145 (6.3%)"]],"caption_candidate":"The subgroups distribution is summarized in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241380-p19-t0","doc_id":"K241380","page_num":19,"bbox":[72.57,102.36,540.58,204.88],"n_rows":7,"n_cols":4,"columns":["","Cardiac clip frame","-","771 (33.7%)"],"rows":[["","Cardiac clip frame","-","771 (33.7%)"],["","Full exam still image","-","1372 (60.0%)"],["","Asian and Pacific Islander","23 (4.8%)","107 (4.7%)"],["","Black","125 (26.0%)","607 (26.5%)"],["Race and ethnicity","Hispanic","43 (9.0%)","209 (9.1%)"],["","White","277 (57.7%)","1295 (56.6%)"],["","Unknown","12 (2.5%)","70 (3.1%)"]],"caption_candidate":"510(k) Summary — K241380","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p7-t0","doc_id":"K241429","page_num":7,"bbox":[175.75,166.7,575.54,378.91],"n_rows":18,"n_cols":8,"columns":["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],"rows":[["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],["","","ECHELON Synergy V10.0 (K233687)","ECHELON Synergy MRI System","","","",""],["Standards Met","","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5, MS\n8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5,\nMS 8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","","","",""],["Type and Field\nStrength","","Super-conducting magnet, horizontal bore,\n1.5 Tesla","Super-conducting magnet, horizontal\nbore, 1.5 Tesla","","","",""],["Resonant Frequency","","63.86MHz","63.86MHz","","","",""],["Bore dimension","","Circle shape with diameter 70cm","Circle shape with diameter 70cm","","","",""],["Gradient Strength","","33mT/m","33mT/m","","","",""],["Slew Rate","","130 T/m/sec","130 T/m/sec","","","",""],["Rise Time","","254μsec to 33mT/m","254μsec to 33mT/m","","","",""],["","","","","","","",""],["Audible Noise (MCAN)","","","","","","",""],["Ambient","","59.9 dBA","59.9 dBA","","","",""],["Lpeak","","122.7 dBA","122.7 dBA","","","",""],["Leq","","116.5 dBA","116.5 dBA","","","",""],["Transmitter channels","","1","1","","","",""],["Peak Envelop Power","","18 kW","18 kW","","","",""],["Duty Cycle","","85% (Gating max), 10% at full power","85% (Gating max), 10% at full power","","","",""],["RF receiver channel","","32","32","","","",""]],"caption_candidate":"Table 2 Comparison: Hardware","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p7-t1","doc_id":"K241429","page_num":7,"bbox":[175.75,521.98,445.66,557.86],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p8-t0","doc_id":"K241429","page_num":8,"bbox":[168.02,113.78,498.7,309.1],"n_rows":13,"n_cols":3,"columns":["","PREDICATE DEVICE","SUBJECT DEVICE"],"rows":[["","PREDICATE DEVICE","SUBJECT DEVICE"],["","ECHELON Synergy V10.0 (K233687)","ECHELON Synergy MRI System"],["Transmit Coil","T/R Body","T/R Body"],["Receiver Coils","FlexFit Neuro Coil","FlexFit Neuro Coil"],["","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B"],["","Extremity Coil","Extremity Coil"],["","Hand/Wrist Coil","Hand/Wrist Coil"],["","Breast Coil\nBreast Support Kit 2","Breast Coil\nBreast Support Kit 2\nBreast Coil 17\nBreast Support Holder"],["","Micro Coil A,\nMicro Coil B","Micro Coil A,\nMicro Coil B"],["","Shoulder Coil","Shoulder Coil"],["","Spine Coil","Spine Coil"],["","Foot/Ankle Coil","Foot/Ankle Coil"],["","Flex M Coil, Flex S Coil","Flex M Coil, Flex S Coil"]],"caption_candidate":"Table 4 Comparison: RF Coils","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p8-t1","doc_id":"K241429","page_num":8,"bbox":[175.01,452.35,445.66,488.11],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p9-t0","doc_id":"K241429","page_num":9,"bbox":[107.93,114.06,576.01,306.0],"n_rows":15,"n_cols":9,"columns":["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],"rows":[["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],["","Operating System","","","None","","","No",""],["","CPU Platform","","","None","","","No",""],["","Application Software","","","None","","","No",""],["Scan Tasks","","","","None","","","No",""],["","2D Processing Tasks","","","None","","","No",""],["","3D Processing Tasks","","","None","","","No",""],["","Analysis Tasks","","","None","","","No",""],["","Maintenance Tasks","","","None","","","No",""],["","Viewport Tools","","","None","","","No",""],["","Film, Archive Tools","","","None","","","No",""],["","Network Tools","","","None","","","No",""],["","Protocol Enhancements","","","None","","","No",""],["","Pulse Sequences","","","None","","","",""],["","Monitoring Tools","","","None","","","",""]],"caption_candidate":"Table 6 Comparison: Functionality","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241429-p9-t1","doc_id":"K241429","page_num":9,"bbox":[175.01,457.39,445.66,493.15],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241430-p7-t0","doc_id":"K241430","page_num":7,"bbox":[72.5,566.5,569.5,709.5],"n_rows":4,"n_cols":3,"columns":["Characteristic","SubjectDevice:\niCardio.aiEchoMeasure","PredicateDevice:\nLibby™Echo:Prio"],"rows":[["Characteristic","SubjectDevice:\niCardio.aiEchoMeasure","PredicateDevice:\nLibby™Echo:Prio"],["Regulation","21CFR892.2050","21CFR892.2050"],["ProductCode","QIH","QIH"],["IntendedUse","Identical","Quantificationofcardiovascular\nfunctionfromanechocardiogram"]],"caption_candidate":"Thefollowingtableshowsasummaryofthesimilaritiesanddifferences:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241430-p8-t0","doc_id":"K241430","page_num":8,"bbox":[72.5,120.5,569.5,716.5],"n_rows":9,"n_cols":3,"columns":["Indicationsforuse","iCardio.aiEchoMeasureis\nsoftwarethatisusedtoprocess\npreviouslyacquired\nDICOM-compliantcardiac\nultrasoundimages,andtomake\nmeasurementsontheseimages\ninordertoprovideautomated\nestimationofseveralcardiac\nmeasurements.Thedata\nproducedbythissoftwareis\nintendedtobeusedtosupport\nqualifiedcardiologists,\nsonographers,orotherlicensed\nprofessionalhealthcare\npractitionersforclinical\ndecision-making.\niCardio.aiEchoMeasureis\nindicatedforuseinadult\npatients.","LibbyEcho:Prioissoftwarethat\nisusedtoprocesspreviously\nacquiredDICOM-compliant\ncardiacultrasoundimages,andto\nmakemeasurementsonthese\nimagesinordertoprovide\nautomatedestimationofseveral\ncardiacmeasurements.Thedata\nproducedbythissoftwareis\nintendedtobeusedtosupport\nqualifiedcardiologists,\nsonographers,orotherlicensed\nprofessionalhealthcare\npractitionersforclinical\ndecision-making.\nLibbyEcho:Prioisindicatedfor\nuseinadultpatients."],"rows":[["Indicationsforuse","iCardio.aiEchoMeasureis\nsoftwarethatisusedtoprocess\npreviouslyacquired\nDICOM-compliantcardiac\nultrasoundimages,andtomake\nmeasurementsontheseimages\ninordertoprovideautomated\nestimationofseveralcardiac\nmeasurements.Thedata\nproducedbythissoftwareis\nintendedtobeusedtosupport\nqualifiedcardiologists,\nsonographers,orotherlicensed\nprofessionalhealthcare\npractitionersforclinical\ndecision-making.\niCardio.aiEchoMeasureis\nindicatedforuseinadult\npatients.","LibbyEcho:Prioissoftwarethat\nisusedtoprocesspreviously\nacquiredDICOM-compliant\ncardiacultrasoundimages,andto\nmakemeasurementsonthese\nimagesinordertoprovide\nautomatedestimationofseveral\ncardiacmeasurements.Thedata\nproducedbythissoftwareis\nintendedtobeusedtosupport\nqualifiedcardiologists,\nsonographers,orotherlicensed\nprofessionalhealthcare\npractitionersforclinical\ndecision-making.\nLibbyEcho:Prioisindicatedfor\nuseinadultpatients."],["AnatomicalSite","Identical","CardiovascularStructures"],["Modality","Identical","Ultrasound"],["IntendedUsers","Identical","Accreditedechocardiographers\nandsonographers"],["IntendedPatient\nPopulation","Identical","Adults"],["HardwareComponent?","No","No"],["Machinelearning-based\nalgorithm","Yes","Yes"],["OperatesonDICOMclips","Yes","Yes"],["Echocardiogramimages","Yes","Yes"]],"caption_candidate":"Traditional510kSummary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241430-p9-t0","doc_id":"K241430","page_num":9,"bbox":[72.5,120.5,569.5,554.5],"n_rows":7,"n_cols":3,"columns":["ondevicereport","",""],"rows":[["ondevicereport","",""],["Auto-viewclassification","Yes","Yes"],["Image-qualityChecks","Yes","NoInformation"],["Measurements","1. LeftVentricularVolume(A2C,\nA4C,andBiplane;Systoleand\nDiastole)\n2. LeftVentricularDiameter\n(SystoleandDiastole)\n3. RightVentricularDiameter\n4. PosteriorWallThickness\n5. AorticAnnulusDiameter\n6. LeftVentricularOutflowTract\nDiameter\n7. SinusofValsalvaDiameter\n8. Sinotubular JunctionDiameter\n9. LeftAtriumDimension\n10. InterventricularSeptal\nThickness","1. EjectionFraction\n2. LeftVentricleVolume(A2C,A4C,\nBiplane;SystoleandDiastole)"],["Contours/Keypoints\noverlaidon\nechocardiogramimages","Yes","Yes"],["Userconfirmation/\nrejectionofresult","Yes","Yes"],["Manualeditingof\nautomatedresultbyuser","No","Yes"]],"caption_candidate":"Traditional510kSummary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241439-p7-t0","doc_id":"K241439","page_num":7,"bbox":[66.61,72.32,534.17,707.82],"n_rows":9,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["Device Name","VUNO Med-Chest X-ray Triage/\nVUNO Med-CXR Link Triage","qXR-PTX-PE"],["510(k) Number","K241439","K230899"],["Regulation","21 CFR 892.2080","21 CFR 892.2080"],["Regulation\nDescription","Radiological computer aided triage\nand notification software","Radiological computer aided triage\nand notification software"],["Product Code","QFM","QFM"],["Device Type","Radiological Computer-Assisted\nPrioritization Software For Lesions","Radiological Computer-Assisted\nPrioritization Software For Lesions"],["Manufacturer","VUNO Inc.","Qure.ai Technologies"],["Intended use/\nIndications for\nUse","VUNO Med-Chest X-ray\nTriage/VUNO Med-CXR Link\nTriage is a radiological computer-\nassisted triage and notification\nsoftware that analyzes adult chest X-\nray images for the presence of pre-\nspecified suspected critical findings\n(pleural effusion and/or\npneumothorax).\nVUNO Med-Chest X-ray\nTriage/VUNO Med-CXR Link\nTriage uses an artificial intelligence\nalgorithm to analyze images for\nfeatures suggestive of critical\nfindings and provides case-level\noutput available in the\nPACS/workstation for worklist\nprioritization or triage.\nAs a passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nVUNO Med-Chest X-ray\nTriage/VUNO Med-CXR Link\nTriage does not send a proactive\nalert directly to the appropriately\ntrained medical specialists. VUNO\nMed-Chest X-ray Triage/VUNO\nMed-CXR Link Triage is not\nintended to direct attention to\nspecific portions of an image or to\nanomalies other than pleural\neffusion and/or pneumothorax. Its\nresults are not intended to be used\non a stand-alone basis for clinical","qXR-PTX-PE is a radiological\ncomputer-assisted triage and\nnotification software that analyzes\nadult chest X-ray images for the\npresence of pre-specified suspected\ncritical findings (pleural effusion\nand/or pneumothorax).\nqXR-PTX-PE uses an artificial\nintelligence algorithm to analyze\nimages for features suggestive of\ncritical findings and provides case-\nlevel output available in the\nPACS/workstation for worklist\nprioritization or triage.\nAs a passive notification for\nprioritization-only software tool\nwithin standard of care workflow,\nqXR-PTX-PE does not send a\nproactive alert directly to the\nappropriately trained medical\nspecialists. qXR-PTXPE is not\nintended to direct attention to\nspecific portions of an image or to\nanomalies other than pleural\neffusion and/or pneumothorax. Its\nresults are not intended to be used\non a standalone basis for clinical\ndecision-making."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241439-p8-t0","doc_id":"K241439","page_num":8,"bbox":[66.61,72.32,534.17,708.3],"n_rows":10,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["","decision-making.",""],["Intended User","Trained radiologists and healthcare\nprofessionals","Radiologists, clinicians, and other\nappropriately trained medical\nspecialists qualified to read chest\nradiographs"],["Modality","Chest X-ray","Chest X-ray"],["Target Clinical\nConditions","Pneumothorax, Pleural effusion on\nChest/Lung Frontal Chest X-rays","Pneumothorax, Pleural effusion on\nChest/Lung Frontal Chest X-rays"],["Algorithm for\npre-specified\ncritical findings\ndetection","VUNO Med-Chest X-ray Triage/\nVUNO Med-CXR Link Triage uses\nan AI algorithm to detect\npneumothorax and pleural effusion\non chest X-ray images.\nVUNO Med-Chest X-ray Triage/\nVUNO Med-CXR Link Triage uses\na vendor agnostic algorithm\ncompatible with DICOM chest X-\nray images.","qXR-PTX-PE uses an AI algorithm\nto detect pneumothorax and pleural\neffusion on chest X-ray images.\nqXR-PTX-PE uses a vendor\nagnostic algorithm compatible with\nDICOM\nchest X-ray images."],["Notification\nonly/\nParallel\nworkflow","Yes","Yes"],["Input format","DICOM, JPG, PNG","DICOM"],["Device output in\ncase of positive\ndetection","When deployed on other\nradiological imaging equipment,\nVUNO Med-Chest X-ray\nTriage/VUNO Med-CXR Link\nTriage will automatically run after\nimage acquisition to perform triage.\nIt displays the analysis result\nthrough the worklist interface of\nPACS/workstation.\nNo markup of the conditions will be\ndone on the original image.\nSecondary capture of the device will\nindicate the presence of findings\nsuspicious of pneumothorax or\npleural effusion.\nUpon image acquisition from other\nradiological imaging equipment\n(e.g. X-ray systems) a passive\nnotification is generated.","When deployed on other\nradiological imaging equipment,\nqXR-PTX-PE will automatically run\nafter image acquisition to perform\ntriage. It displays the analysis result\nthrough the worklist interface of\nPACS/workstation.\nNo markup of the conditions will be\ndone on the original image.\nSecondary capture of the device will\nindicate the presence of findings\nsuspicious of pneumothorax or\npleural effusion.\nUpon image acquisition from other\nradiological imaging equipment\n(e.g. X-ray systems) a passive\nnotification is generated."],["Notification\n(i.e., recipient,","Passive notification. Images with\nsuspicion of pneumothorax and/or","Passive notification. Images with\nsuspicion of pneumothorax and/or"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241439-p9-t0","doc_id":"K241439","page_num":9,"bbox":[66.62,72.32,534.16,595.42],"n_rows":5,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["timing and\nmeans of\nnotification)","pleural effusion are flagged in\nPACS/workstation/DICOM viewer.","pleural effusion are flagged in\nPACS/workstation/DICOM viewer."],["Where\ngenerated\nresults(i.e.,\nDICOM files)\nare stored","PACS/Workstation/DICOM viewer","PACS/Workstation/DICOM viewer"],["Performance\nlevel\n- Timing of\nnotification","The average time taken for the\nnotification to travel from VUNO\nMed-Chest X-ray Triage/VUNO\nMed-CXR Link Triage to the point\nat which the result is displayed in\nthe destination Picture Archiving\nand Communication System(PACS)\nor workstation/digital radiographic\nprocessing system (ex. digital\nradiography, digital X-ray system\netc.) is below 10 seconds.","The average time taken for the\nnotification to travel from qXR-\nPTX-PE to the point at which the\nresult is displayed in the destination\nPicture Archiving and\nCommunication System(PACS) or\nworkstation/digital radiographic\nprocessing system (ex. digital\nradiography, digital X-ray system\netc.) is 10 seconds."],["Performance\nlevel\n- Accuracy of\nclassification","Pneumothorax\nROC AUC > 0.95\nAUC: 0.9883 (95% CI: [0.9815,\n0.9939])\nSensitivity 95.45 % (95% CI:\n[92.01, 97.71])\nSpecificity 96.41% (95% CI: [94.32,\n97.90])\nPleural Effusion\nROC AUC > 0.95\nAUC: 0.9900 (95% CI: [0.9863,\n0.9932])\nSensitivity 96.53% (95% CI: [94.24,\n98.09])\nSpecificity 95.11% (95% CI: [93.37,\n96.50])","Pneumothorax\nROC AUC > 0.95\nAUC: 0.9894 (95% CI: [0.9829,\n0.9980])\nSensitivity 94.53% (95% CI: [90.42,\n97.24])\nSpecificity 96.36% (95% CI: [94.07,\n97.95])\nPleural Effusion\nROC AUC > 0.95\nAUC: 0.989 (95% CI: [0.9847,\n0.9944])\nSensitivity 96.22% (95% CI: [93.62,\n97.97])\nSpecificity 94.90% (95% CI: [93.04,\n96.39])"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241439-p13-t0","doc_id":"K241439","page_num":13,"bbox":[93.35,72.36,534.12,109.38],"n_rows":2,"n_cols":9,"columns":["","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],"rows":[["","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],["98.83 (98.15 - 99.39)","","","95.45 (92.01 - 97.71)","","","96.41 (94.32 - 97.90)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241439-p13-t1","doc_id":"K241439","page_num":13,"bbox":[93.35,461.86,534.12,498.34],"n_rows":2,"n_cols":9,"columns":["","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],"rows":[["","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],["99.00 (98.63 - 99.32)","","","96.53 (94.24 - 98.09)","","","95.11 (93.37 - 96.50)","",""]],"caption_candidate":"97.97) and specificity 94.90 (93.04-96.39).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p4-t0","doc_id":"K241440","page_num":4,"bbox":[72.51,409.5,531.1,509.27],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Nano-X AI HealthCCSng device"],"rows":[["Proprietary Name","Nano-X AI HealthCCSng device"],["Premarket Notification","K241440"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR §892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Modified Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p4-t1","doc_id":"K241440","page_num":4,"bbox":[72.51,558.17,531.1,681.42],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Cleared Device:\nNano-X AI HealthCCSng device"],"rows":[["Proprietary Name","Cleared Device:\nNano-X AI HealthCCSng device"],["Premarket Notification","K210085"],["Classification Name","Computed tomography x-ray system."],["Regulation Number","21 CFR §892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"The HealthCCSng V2.0 device is substantially equivalent to the following cleared Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p7-t0","doc_id":"K241440","page_num":7,"bbox":[72.91,382.62,539.35,708.59],"n_rows":2,"n_cols":3,"columns":["","Modified Device:\nHealthCCSng Device","Cleared Device:\nNano-X AI Ltd. HealthCCSng Device\n(K210085)"],"rows":[["","Modified Device:\nHealthCCSng Device","Cleared Device:\nNano-X AI Ltd. HealthCCSng Device\n(K210085)"],["Intended\nUse/\nIndications\nfor Use","The HealthCCSng device is intended\nfor use as a non-invasive post-\nprocessing software to evaluate\ncalcified plaques in the coronary\narteries, which present a risk for\ncoronary artery disease.\nThe HealthCCSng device analyzes\nroutine non-gated, non-contrast CT\nstudies that include the entire heart of\nadult patients of age 30-85.\nThe device generates an exact calcium\nscore and a four coronary artery\ncalcium detection category output\nrepresenting the estimated quantity of\ncalcium detected together with\npreview axial images of the detected","The HealthCCSng device is\nintended for use as a non-\ninvasive post-processing\nsoftware to evaluate calcified\nplaques in the coronary arteries,\nwhich present a risk for coronary\nartery disease. The software\ngenerates an estimated coronary\nartery calcium detection\ncategory.\nThe HealthCCSng device analyzes\nexisting non-cardiac-gated CT studies\nthat include the heart of adult patients\nabove the age of 30.\nThe device generates a three-category\noutput representing the estimated"]],"caption_candidate":"HealthCCSng cleared device K210085.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p8-t0","doc_id":"K241440","page_num":8,"bbox":[72.98,377.15,539.33,713.11],"n_rows":12,"n_cols":5,"columns":["Technological\nCharacteristics","Modified Device:\nHealthCCSng Device","Cleared Device:\nNano-X AI Ltd. HealthCCSng\nDevice (K210085)","","Summary"],"rows":[["Technological\nCharacteristics","Modified Device:\nHealthCCSng Device","Cleared Device:\nNano-X AI Ltd. HealthCCSng\nDevice (K210085)","","Summary"],["","","","",""],["Regulation","","","",""],["","","","",""],["Product Code","JAK","JAK","Same",""],["Regulation\nNumber","21 CFR §892.1750","21 CFR §892.1750","",""],["","","","",""],["General","","","",""],["","","","",""],["Modality","Computed tomography (CT)","Computed tomography (CT)","Same",""],["Image format","DICOM","DICOM","Same",""],["Supported CT\nscan","Non-contrast CT scan","Non-cardiac-gated CT scan","Similar. The\ninclusion criteria\nare the same: in",""]],"caption_candidate":"Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p9-t0","doc_id":"K241440","page_num":9,"bbox":[72.95,78.39,539.31,687.52],"n_rows":7,"n_cols":6,"columns":["","","","","both devices\nalgorithm is\nintended to run on\nnon-contrast non-\ngated CT scans.",""],"rows":[["","","","","both devices\nalgorithm is\nintended to run on\nnon-contrast non-\ngated CT scans.",""],["Slice thickness","","Up to 5.1 mm","Up to 3.1 mm","Similar, the\nmodified\nHealthCCSng\nsupports all the\nslice thickness\nrange as in the\ncleared device and\nin addition can\nsupport a wider\nvariety of scans.\nThe expansion of\nthe slice thickness\nrange was\nvalidated and\nperformnance was\nfound similar to\nthe cleared device.",""],["Intended users","","Radiologists, Interpretive\nClinicians","Radiologists, Interpretive\nClinicians","Same",""],["Intended\npopulation","","Patients aged 30-85 years","Patients aged 30 years and\nabove","Similar, both\nmodified and\ncleared devices\nare intended for\nadult population\nat the age of 30\nand older; the\nmodified device\nhas an upper limit\nas part of product\nscope focus on\nrelevant\npopulation.",""],["","","","","",""],["","Analysis and Measurement","","","",""],["","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p10-t0","doc_id":"K241440","page_num":10,"bbox":[72.92,78.56,539.31,717.36],"n_rows":10,"n_cols":4,"columns":["Detection of\ntarget organ","Yes, detection of the heart","Yes, detection of the heart","Same"],"rows":[["Detection of\ntarget organ","Yes, detection of the heart","Yes, detection of the heart","Same"],["Segmentation of\norgan","Deep-learning-based\nsegmentation of the heart","Deep-learning-based\nsegmentation of the heart","Same"],["Calcification\ndetection","Automatic","Automatic","Same"],["Default threshold\nof calcium","130 HU (Hounsfield Units)","130 HU (Hounsfield Units)","Same"],["Coronary artery\ncalcification\nquantification\nmethod","Coronary Calcium\nDetection Category and\nexact detected calcium\nscore on side bar","Coronary Calcium Detection\nCategory Detected and\ncalcium score mark on side\nbar","Similar, both\ndevices provide\ncalcium category;\nboth the cleared\ndevice and the\nmodified device\nmark the calcium\nscore on a side\nbar; the modified\ndevice also\nprovides the\ndetected calcium\nscore number as\nan output, which\nwas validated and\nwas found similar\nto the cleared\ndevice."],["","","",""],["Reporting","","",""],["","","",""],["Annotation of\ndetected calcium","Yes","Yes","Same"],["Generate patient\nreport","Optional to add the results to\nthe report, DICOM\nSecondary Capture, Insight\nUI application","DICOM Secondary Capture,\nInsight UI application","Similar, the\nmodified device\nalso enables the\noption to add the"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p11-t0","doc_id":"K241440","page_num":11,"bbox":[72.91,78.56,539.35,427.73],"n_rows":2,"n_cols":4,"columns":["","","","results to the\nradiology report."],"rows":[["","","","results to the\nradiology report."],["Device output","1) Estimated Coronary\nCalcium Detection,\nbased on the\nmeasurement of calcium\ndeposits in the coronary\narteries, precise score is\nindicated besides the\narrow on the side scale\nbar.\n2) A corresponding\nEstimated Coronary\nCalcium Detection\nCategory, based on the\nEstimated Coronary\nCalcium measurements\n4 categories:\n0 – Zero Calcium\n1-99 – Low\n100-399 – Medium\n≥400 - High","1) Estimated Coronary\nCalcium Detection, based\non the measurement of\ncalcium deposits in the\ncoronary arteries, score is\npresented as an arrow on\nthe side scale bar.\n2) A corresponding\nEstimated Coronary\nCalcium Detection\nCategory, based on the\nEstimated Coronary\nCalcium measurements\n3 categories:\n0-99 – Low\n100-399 – Medium\n400 - High","Similar, both\ndevices provide\ncalcium category;\nThe modified\nHealthCCSng\ndevice provides a\nmore precise\nrepresentation of\ncoronary calcium\nscore, and\nseparating the\ncategory 0 from\nthe other from the\n‘low’ category."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241440-p13-t0","doc_id":"K241440","page_num":13,"bbox":[72.87,93.63,548.83,297.23],"n_rows":12,"n_cols":11,"columns":["","HealthCCSng CAC Category [HU] Non-Gated","","","","","","","","",""],"rows":[["","HealthCCSng CAC Category [HU] Non-Gated","","","","","","","","",""],["","","","","","","","","","Total",""],["","0","","1-99","","100-399","","400+","","",""],["","","","","","","","","","",""],["","N","%","N","%","N","%","N","%","N","%"],["HealthCCSng CAC","","","","","","","","","",""],["Category [HU] Gated","","","","","","","","","",""],["0","16","88.89%","1","5.56%","1","5.56%",".",".","18","100.00%"],["1-99","12","44.44%","13","48.15%","2","7.41%",".",".","27","100.00%"],["100-399",".",".","8","36.36%","12","54.55%","2","9.09%","22","100.00%"],["400+",".",".",".",".","6","18.18%","27","81.82%","33","100.00%"],["Total","28","28.00%","22","22.00%","21","21.00%","29","29.00%","100","100.00%"]],"caption_candidate":"Table 1: Categorical Agreement","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241480-p5-t0","doc_id":"K241480","page_num":5,"bbox":[18.5,17.28,595.25,555.12],"n_rows":23,"n_cols":5,"columns":["510(k)#: K241480","","510(k) Summary","","Prepared on: 2024-09-26"],"rows":[["510(k)#: K241480","","510(k) Summary","","Prepared on: 2024-09-26"],["","","","",""],["","","","",""],["Contact Details","","","","21 CFR 807.92(a)(1)"],["","","","",""],["","","","",""],["","JLK, Inc.","","",""],["","JLK Tower, 5, Teheran-ro 33-gil Gangnam-gu Seoul n/a 06141 Korea,\nSouth","","",""],["","(+82)1038507933","","",""],["","Dr. Kim Dongmin","","",""],["","dmkim@jlkgroup.com","","",""],["","","Hogan Lovells","",""],["","","Columbia Square 555 Thirteenth Street NW Washington D/C 20004\nUnited States","",""],["","","(+1)2026373638","",""],["","","Mr. Smith John","",""],["","","john.smith@hoganlovells.com","",""],["Device Name","","","21 CFR 807.92(a)(2)",""],["","","","",""],["","JBS-LVO","","",""],["","Radiological computer aided triage and notification software","","",""],["","Radiological Computer-Assisted Triage And Notification Software","","",""],["","892.2080","","",""],["","QAS","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241480-p5-t1","doc_id":"K241480","page_num":5,"bbox":[18.5,605.88,595.25,684.28],"n_rows":4,"n_cols":4,"columns":["K223042","Viz LVO","","QAS"],"rows":[["K223042","Viz LVO","","QAS"],["K221248","Rapid LVO","","QAS"],["Device Description Summary","","21 CFR 807.92(a)(4)",""],["","","",""]],"caption_candidate":"Predicate # Predicate Trade Name (Primary Predicate is listed first) Product Code","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p5-t0","doc_id":"K241490","page_num":5,"bbox":[72.82,164.28,539.62,347.49],"n_rows":12,"n_cols":2,"columns":["","Paciuksenkatu 29, 6th floor"],"rows":[["","Paciuksenkatu 29, 6th floor"],["","00270 Helsinki, Finland"],["","Tel: +358 (0) 40 721 3783"],["","info@mvision.ai"],["Establishment",""],["Registration Number: 3022745617",""],["Contact Person: Kalpana Jha",""],["","VP of Regulatory and Market Strategy"],["","kalpana.jha@mvision.ai"],["","Tel: +358 44 9214 354"],["",""],["Subject Device",""]],"caption_candidate":"Company Name and Address: MVision AI Oy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p5-t1","doc_id":"K241490","page_num":5,"bbox":[72.82,359.91,539.62,501.94],"n_rows":8,"n_cols":2,"columns":["Device Trade Name:","Contour+(MVision Al Segmentation)"],"rows":[["Device Trade Name:","Contour+(MVision Al Segmentation)"],["Common Name:","Medical Image Segmentation Software"],["Device Classification Name:","Radiological Image Processing Software For Radiation Therapy"],["Product Code:","QKB"],["Device Class:","Class II"],["Review Panel:","Radiology"],["Regulation Description:","Medical Image Management And Processing System"],["Regulation Number:","21 CFR §892.2050"]],"caption_candidate":"Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p5-t2","doc_id":"K241490","page_num":5,"bbox":[72.82,546.77,539.62,599.05],"n_rows":3,"n_cols":2,"columns":["Device Name:","MVision Al Segmentation"],"rows":[["Device Name:","MVision Al Segmentation"],["510(k) Number:","K212915"],["Manufacturer:","MVision AI Oy"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p7-t0","doc_id":"K241490","page_num":7,"bbox":[73.68,65.51,484.69,720.7],"n_rows":81,"n_cols":3,"columns":["T7","LN_Breast_L4_L/R","LN_Neck_XB_L/R"],"rows":[["T7","LN_Breast_L4_L/R","LN_Neck_XB_L/R"],["","",""],["T8","LN_IMN_IC4_L/R","Larynx_SG"],["","",""],["T9","LN_IMN_L/R","Lens_L/R"],["","",""],["","LN_Intpect_L/R","Lips"],["","",""],["","LN_RTOG_IMN_L/R","Lung_L/R"],["","",""],["","Lung_L/R","Musc_Constrict"],["","",""],["","SpinalCanal","OpticChiasm"],["","",""],["","SpinalCord","OpticChiasm_cnv"],["","",""],["","Spleen","OpticNrv_L/R"],["","",""],["","Stomach","OpticNrv_cnv_L/R"],["","",""],["","Trachea","Parotid_L/R"],["","",""],["","V_Venacava_I","Pituitary"],["","",""],["","V_Venacava_S","SpinalCanal"],["","",""],["","Ventricle_L/R","SpinalCord"],["","",""],["","Wire","Trachea"],["","",""],["CT Lung and Abdomen","CT Female Pelvis","CT Male Pelvis"],["","",""],["A_Aorta","A_Aorta","A_Aorta"],["","",""],["A_Aorta_v2","Bag_Bowel","Bag_Bowel"],["","",""],["A_LAD","Bladder","Bladder"],["","",""],["A_Pulm","Body","Body"],["","",""],["Atrium_L/R","Bone_Pelvic","Bone_Pelvic"],["","",""],["Bag_Bowel","Bowel_Large","Bowel_Large"],["","",""],["Body","Bowel_Small","Bowel_Small"],["","",""],["Bones","CTV_Central","CaudaEquina"],["","",""],["Bowel_Large","CTV_Param","Duodenum"],["","",""],["Bowel_Small","CTV_Pelvis","Femur_Head_L/R"],["","",""],["BrachialPlex_L/R","Duodenum","Femur_Implant_L/R"],["","",""],["Bronchus_Prox","Femur_Head_L/R","Femur_L/R"],["","",""],["Chestwall_L/R","Femur_Implant_L/R","Kidney_L/R"],["","",""],["Duodenum","Femur_L/R","L4_VB"],["","",""],["Esophagus","Kidney_L/R","L5_VB"],["","",""],["Heart","L4_VB","Liver"],["","",""],["Heart+A_Pulm","L5_VB","LN_Inguinal_L/R"],["","",""],["Humerus_Head_L/R","Liver","LN_NRG"],["","",""],["Humerus_L/R","LN_Gyn_RTOG","LN_Pivotal"],["","",""],["Kidney_L/R","LN_Inguinal_L/R","LN_RTOG"],["","",""],["Liver","LN_PAN","Markers"],["","",""],["Lung_L/R","LN_PAN_Long","Musc_Coccygeus_L/R"],["","",""],["Pancreas","LN_Pivotal","Musc_Iliacus_L/R"],["","",""],["SpinalCanal","LN_RTOG","Musc_Obt_Int_L/R"],["","",""],["SpinalCord","Musc_Coccygeus_L/R","Musc_Pirifor_L/R"]],"caption_candidate":"T7 LN_Breast_L4_L/R LN_Neck_XB_L/R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241490-p8-t0","doc_id":"K241490","page_num":8,"bbox":[72.18,62.22,540.18,720.9],"n_rows":40,"n_cols":3,"columns":["Spleen","Musc_Iliacus_L/R","Musc_Psoas_Maj_L/R"],"rows":[["Spleen","Musc_Iliacus_L/R","Musc_Psoas_Maj_L/R"],["Stomach","Musc_Obt_Int_L/R","Pancreas"],["Trachea","Musc_Pirifor_L/R","PenileBulb"],["Trachea_Prox","Musc_Psoas_Maj_L/R","Prostate"],["V_Venacava_I","Pancreas","RectoSigmoid"],["V_Venacava_S","RectoSigmoid","Rectum"],["Ventricle_L/R","Rectum","Sacrum"],["","Sacrum","SeminalVes"],["","SpinalCanal","SpinalCanal"],["","SpinalCord","SpinalCord"],["","Spleen","Spleen"],["","Stomach","Stomach"],["","UteroCervix","V_Venacava_I"],["","V_Venacava_I","Vessels_L/R"],["","Vagina","Vessels_Long_L/R"],["","Vessels_L/R",""],["","Vessels_Long_L/R",""],["","",""],["CT Brain","MR Brain","MR T2 Male Pelvis"],["A_Carotid_L/R","Amygdala_L/R","Bladder"],["Body","Body","BladderTrigone"],["Brain","Brain","PenileBulb"],["Brainstem","Brainstem","Prostate"],["Cochlea_L/R","Cerebellum","Rectum"],["Eye_Ant_L/R","CorpusCallosum","SeminalVes"],["Eye_L/R","Eye_L/R","Spacer"],["Eye_Post_L/R","Glnd_Lacrimal_L/R",""],["Fossa_Pituitary","Hippocampus_L/R",""],["Glnd_Lacrimal_L/R","Hypothalamus",""],["Lens_L/R","MedullaOblongata",""],["OpticChiasm","Midbrain",""],["OpticChiasm_cnv","OpticChiasm",""],["OpticNrv_cnv_L/R","OpticChiasm_cnv",""],["OpticNrv_L/R","OpticNrv_cnv_L/R",""],["Parotid_L/R","OpticNrv_L/R",""],["Pituitary","OpticTract_cnv_L/R",""],["SpinalCanal","OpticTract_L/R",""],["SpinalCord","Pituitary",""],["","Pons",""],["","Thalamus_L/R",""]],"caption_candidate":"510(k) Summary – K241490","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p9-t0","doc_id":"K241490","page_num":9,"bbox":[72.27,420.44,539.72,720.18],"n_rows":16,"n_cols":4,"columns":["","MVision AI Segmentation (K212915)","Contour+ (MVision Al Segmentation)","Comparison"],"rows":[["","MVision AI Segmentation (K212915)","Contour+ (MVision Al Segmentation)","Comparison"],["esU\nrof\nsnoitacidnI","MVisionAI Segmentation is a software\nsystem for image analysis algorithms to be\nused in radiation therapy treatment\nplanning workflows. The system includes\nprocessing tools for automatic contouring\nof CT images using machine learning\nbased algorithms. The produced\nsegmentation templates for regions of\ninterest must be transferred to appropriate\nimage visualization systems as an initial\ntemplate for a medical professional to\nvisualize, review, modify and approve\nprior to further use in clinical workflows.\nThe system creates initial contours of pre-\ndefined structures of common anatomical\nsites, i.e. Head and Neck, Brain, Breast,\nLung and Abdomen, Male Pelvis, and\nFemale Pelvis in adult patients.\nMVision AI Segmentation is not intended\nto detect lesions or tumors. The device is\nnot intended for use with real-time\nadaptive planning workflows.","Contour+ (MVision Al Segmentation) is\na software system for image analysis\nalgorithms to be used in radiation therapy\ntreatment planning workflows. The\nsystem includes processing tools for\nautomatic contouring of CT and MR\nimages using machine learning based\nalgorithms. The produced segmentation\ntemplates for regions of interest must be\ntransferred to appropriate image\nvisualization systems as an initial\ntemplate for a medical professional to\nvisualize, review, modify and approve\nprior to further use in clinical workflows.\nThe system creates initial contours of\npre-defined structures of common\nanatomical sites, i.e., Head and Neck,\nBrain, Breast, Lung and Abdomen, Male\nPelvis, and Female Pelvis.\nContour+ (MVision Al Segmentation) is\nnot intended to detect lesions or tumors.\nThe device is not intended for use with\nreal-time adaptive planning workflows.","Same intended use."],["","","","The only difference"],["","","","is the inclusion of"],["","","","processing tools for"],["","","","automatic contouring"],["","","","of MR images, in"],["","","","addition to CT"],["","","","images –this is a"],["","","","change in"],["","","","technological"],["","","","characteristics that"],["","","","does not affect the"],["","","","intended use of the"],["","","","device."],["","","",""]],"caption_candidate":"The following table outlines the similarities and differences between the two software versions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241490-p10-t0","doc_id":"K241490","page_num":10,"bbox":[72.21,63.08,539.99,717.06],"n_rows":20,"n_cols":4,"columns":["","MVision AI Segmentation (K212915)","Contour+ (MVision Al Segmentation)","Comparison"],"rows":[["","MVision AI Segmentation (K212915)","Contour+ (MVision Al Segmentation)","Comparison"],["dednetnI\nsresU","Designed to be used by clinicians trained\nin radiation therapy workflows.","Designed to be used by clinicians trained\nin radiation therapy workflows.","Same."],["","","",""],["tneitaP\nnoitalupoP\ntegraT","Patients who have been prescribed\nradiation therapy.","Patients who have been prescribed\nradiation therapy.","Same"],["","","",""],["tnemyolpeD tnemnorivnE","Cloud based software Application\nLocal (on customer premises)\ninstallation in healthcare provider's IT\nnetwork / server","Cloud based software Application\nLocal (on customer premises)\ninstallation in healthcare provider's IT\nnetwork / server","Same"],["","","",""],["gnitarepO mroftalP","Ubuntu","Ubuntu\nWindows","Contour+ may also"],["","","","run in a Windows"],["","","","operating platform"],["","","",""],["/\nsnoitacinummoC\ngnikrowteN","DICOM image and structure set data\ntransfers\nTCP/IP, SCP, and HTTP (Local)\nTCP/IP, SCP, and HTTPS (Cloud)","DICOM image and structure set data\ntransfers\nTCP/IP, SCP, and HTTP (Local)\nTCP/IP, SCP, and HTTPS (Cloud)","Minor changes:\nAdded API script to\nsend scans directly\nfrom the Varian\nEclipse Treatment\nPlanning System;"],["","","","Provided read-only"],["","","","Import/Export UI to"],["","","","upload/download"],["","","","DICOM data via a"],["","","","web browser"],["seitiladom\ngnigamI","CT","CT\nMR","Added support for\nautomatic contouring\nof MR images"],["noitatnemgeS\nsmhtirogla","Machine learning-based contouring\nusing deep learning-based models\nDoes not support segmentation based\non atlas-based techniques","Machine learning-based contouring\nusing deep learning-based models\nDoes not support segmentation based\non atlas-based techniques","Same algorithms;\nUpdated certain\nCT segmentation\nmodels; Added 1 CT\nand 2 MR models"],["desab\ngniruotnoc-er\nnoitartsigeR","No","No","Same"]],"caption_candidate":"510(k) Summary – K241490","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241496-p5-t0","doc_id":"K241496","page_num":5,"bbox":[101.66,212.57,535.32,292.13],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH(Per 21CFR§892.1000)"],["Trade ProprietaryName:","Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction\nProcessing Unit for MR"],["ModelNumber:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICENAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241496-p6-t0","doc_id":"K241496","page_num":6,"bbox":[75.5,120.62,487.21,680.98],"n_rows":58,"n_cols":3,"columns":["5.","MANUFACTURINGSITE",""],"rows":[["5.","MANUFACTURINGSITE",""],["","",""],["","Canon MedicalSystemsCorporation",""],["","",""],["","1385Shimoishigami",""],["","",""],["","Otawara-shi,Tochigi324-8550,Japan",""],["","",""],["6.","ESTABLISHMENTREGISTRATION",""],["","",""],["","9614698",""],["","",""],["7.","DATEPREPARED",""],["","",""],["","May 24, 2024",""],["","",""],["8.","DEVICENAME",""],["","",""],["","VantageGalan3T,MRT-3020,V10.0 with AiCE Reconstruction Processing Unit","for MR"],["","",""],["9.","TRADENAME",""],["","",""],["","VantageGalan3T,MRT-3020,V10.0 with AiCE Reconstruction Processing Unit","for MR"],["","",""],["10.","CLASSIFICATION NAME",""],["","",""],["","MagneticResonanceDiagnosticDevice(MRDD)",""],["","",""],["11.","CLASSIFICATION PANEL",""],["","",""],["","Radiology",""],["","",""],["12.","DEVICECLASSIFICATION",""],["","",""],["","ClassII(per21CFR892.1000,MagneticResonanceDiagnosticDevice)",""],["","",""],["13.","PRODUCT CODE",""],["","",""],["","90-LNH",""],["","",""],["4. P","REDICATEDEVICE",""],["","",""],["P","redicateDevice:Vantage Galan 3T, MRT-3020, V9.0 with AiCE Reconstruction","Processing"],["(","K230355)",""],["","",""],["","Predicate Device",""],["","System Vantage Galan 3T, MRT-3020, V9.0 with AiCE",""],["","Reconstruction Processing Unit for MR",""],["","Marketed By Canon Medical Systems USA, Inc.",""],["","510(k) Number K230355",""],["","Clearance Date August30, 2023",""],["","",""],["15.","REASON FORSUBMISSION",""],["","",""],["","Modificationof acleared device",""],["","",""],["16.","SUBMISSION TYPE",""],["","Traditional510(k) Premarket Notification",""]],"caption_candidate":"5. MANUFACTURINGSITE","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241496-p6-t1","doc_id":"K241496","page_num":6,"bbox":[90.26,534.55,365.11,606.7],"n_rows":5,"n_cols":2,"columns":["System","Predicate Device"],"rows":[["System","Predicate Device"],["","Vantage Galan 3T, MRT-3020, V9.0 with AiCE\nReconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K230355"],["Clearance Date","August30, 2023"]],"caption_candidate":"(K230355)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241496-p7-t0","doc_id":"K241496","page_num":7,"bbox":[95.1,600.84,558.65,692.14],"n_rows":7,"n_cols":8,"columns":["Item","","Subject Device:","","","PredicateDevice:","","Notes"],"rows":[["Item","","Subject Device:","","","PredicateDevice:","","Notes"],["","","Vantage Galan 3T, MRT-3020,","","","Vantage Galan 3T, MRT-3020,","",""],["","","V10.0","","","V9.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR(K230355)","",""],["Static field strength","3T","","","3T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"]],"caption_candidate":"19. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241496-p8-t0","doc_id":"K241496","page_num":8,"bbox":[95.08,84.4,558.67,319.25],"n_rows":10,"n_cols":8,"columns":["Item","","Subject Device:","","","PredicateDevice:","","Notes"],"rows":[["Item","","Subject Device:","","","PredicateDevice:","","Notes"],["","","Vantage Galan 3T, MRT-3020,","","","Vantage Galan 3T, MRT-3020,","",""],["","","V10.0","","","V9.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR(K230355)","",""],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241543-p9-t0","doc_id":"K241543","page_num":9,"bbox":[61.6,62.52,514.95,239.78],"n_rows":2,"n_cols":4,"columns":["Test\nperformed","Samplesize\n(numberof\nCT scans)","Acceptancecriteria","Performanceresults"],"rows":[["Test\nperformed","Samplesize\n(numberof\nCT scans)","Acceptancecriteria","Performanceresults"],["Liver\nsegmentation\nmask","450","1)Mean Dice(cid:116) 0.95\n2) 95% CI lower bound\nofDicescores (cid:116) 0.90\n3) 95% CI upper bound\nofHD95 score (cid:100) 4.0","1)Dicescore:\n+Mean 1std: 0.9649 0.0195\n+ 95% CIDice: 0. 9649 [0.9631,\n0.9667]\n2)HD95:\n+Mean 1std: 1.70611.5800\n+95%CI: 1.7061 [1.5595,\n1.8526]"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241543-p9-t1","doc_id":"K241543","page_num":9,"bbox":[61.6,367.61,543.39,470.95],"n_rows":2,"n_cols":4,"columns":["Testperformed","Samplesize(number\nof CT scans)","Acceptancecriteria","Performanceresults"],"rows":[["Testperformed","Samplesize(number\nof CT scans)","Acceptancecriteria","Performanceresults"],["liver volume\nmeasurement","450","95% CI upper bound of\nVolumeError(cid:100) 5%","NVE:\nMean1std:2.7269%\n3.1928 %\n95%CI:[2.4308 %\n, 3.0230 %]"]],"caption_candidate":"The results of the liver volume measurement are provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241561-p9-t0","doc_id":"K241561","page_num":9,"bbox":[79.46,161.9,532.66,385.61],"n_rows":5,"n_cols":2,"columns":["Total number of studies","108,775"],"rows":[["Total number of studies","108,775"],["Density distribution","A: 12.79%\nB: 34.58%\nC: 42.94%\nD: 9.38%\nUnknown (excluded): 0.31%"],["Patient ages","First quartile (Q1): 47.0\nMean: 56.0\nThird quartile (Q3): 64.0"],["Patient Race / Ethnicity","White: 49.13%\nAsian: 7.63%\nBlack or african american: 0.43%\nnative hawaiian or pacific islander: 0.09%\nUnknown: 42.72%"],["Manufacturer","Hologic: 61.63%\nGE: 38.37%"]],"caption_candidate":"A detailed description of the training data is available in the Table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241561-p10-t0","doc_id":"K241561","page_num":10,"bbox":[72.26,267.05,560.86,479.83],"n_rows":3,"n_cols":11,"columns":["Sources","Origins","Patients","Studies","Images","Manufacturer\n(images)","Modalities\n(images)","Breast\nDensities\n(studies)","Study\nDates","Patient\nAges\n(y/o)","Patient Races"],"rows":[["Sources","Origins","Patients","Studies","Images","Manufacturer\n(images)","Modalities\n(images)","Breast\nDensities\n(studies)","Study\nDates","Patient\nAges\n(y/o)","Patient Races"],["FR_1: 437\n(47.40%)\nUS_1: 249\n(27.01%)\nUS_2: 228\n(24.73%)\nUS_3: 8\n(0.87%)","USA: 485\n(52.60%)\nFRA: 437\n(47.40%)","unknown: 478\n(51.84%)\nbenign: 426\n(46.20%)\nmalignant: 14\n(1.52%)\nundetermined: 4\n(0.43%)","unknown: 478\n(51.84%)\nbenign: 426\n(46.20%)\nmalignant: 14\n(1.52%)\nundetermined: 4\n(0.43%)","benign: 2,446\n(57.23%)\nunknown: 1,774\n(41.51%)\nmalignant: 39\n(0.91%)\nundetermined:\n15 (0.35%)","hologic: 4,274\n(100.00%)","FFDM: 3,053\n(71.43%)\n2DSM: 1,221\n(28.57%)","C: 366\n(39.70%)\nB: 353\n(38.29%)\nD: 106\n(11.50%)\nA: 97\n(10.52%)","min:\n2015-\n05-22\nmax:\n2023-\n02-15","min: 40\nq25:\n52.0\nmean:\n59.7\nq75:\n67.0\nmax: 90","unknown: 451\n(48.92%)\nwhite: 273\n(29.61%)\nasian: 102\n(11.06%)\nblack or african\namerican: 88\n(9.54%)\namerican indian or\nalaska native: 4\n(0.43%)\nnative hawaiian or\npacific islander: 4\n(0.43%)"],["922","922","922","922","4,274","4,274","4,274","922","","","922"]],"caption_candidate":"2DSM were considered. Details of the dataset are reported in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241561-p21-t0","doc_id":"K241561","page_num":21,"bbox":[72.26,196.46,540.1,709.66],"n_rows":4,"n_cols":4,"columns":["","Modification 1:\nSupport of GE\nmammograms (no\nre-training\nrequired)","Modification 2:\nSupport of Siemens\nMammograms (re-\ntraining required)","Modification 3:\nPre-training of\nbackbone using\nUnsupervised\nMachine Learning\n(as opposed to\nSupervised\nMachine Learning)"],"rows":[["","Modification 1:\nSupport of GE\nmammograms (no\nre-training\nrequired)","Modification 2:\nSupport of Siemens\nMammograms (re-\ntraining required)","Modification 3:\nPre-training of\nbackbone using\nUnsupervised\nMachine Learning\n(as opposed to\nSupervised\nMachine Learning)"],["Data used for\ndevelopment and\nmodifications,\nrepresenting the\ntarget population","No new data\ncollection is foreseen\nfor this change.","Siemens, FFDM\nSiemens, 2DSM","No new data\ncollection is foreseen\nfor this change."],["Comprehensive testing\nfor planned changes","Agreement testing\nagainst the visual\nassessment of 5\nradiologists on GE\nmammograms.","Agreement testing\nagainst the visual\nassessment of 5\nradiologists on\nHologic\nmammograms.\nAgreement testing\nagainst the visual\nassessment of 5\nradiologists on\nSiemens\nmammograms.","Agreement testing\nagainst the visual\nassessment of 5\nradiologists on\nHologic and new\nmanufacturer(s)\nmammograms."],["Acceptance criteria\nof the updated device","Quadratic kappa on\nGE mammograms\nsuperior to 0.85.\nLinear kappa,\naccuracy, and\ndensity bins (A, B, C\nand D) on GE","Quadratic kappa on\nSiemens and\nHologic\nmammograms\nsuperior to 0.85\nLinear kappa,\naccuracy, and density","Quadratic kappa on\nHologic\nmammograms\nsuperior to 0.85.\nLinear kappa,\naccuracy, and density\nbins (A, B, C and D)"]],"caption_candidate":"development/modification and testing, and the monitoring methodology.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241561-p22-t0","doc_id":"K241561","page_num":22,"bbox":[72.26,80.78,540.1,378.17],"n_rows":3,"n_cols":4,"columns":["","mammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms.","bins (A, B, C and D)\non Siemens and\nHologic\nmammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms.","on Hologic\nmammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms."],"rows":[["","mammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms.","bins (A, B, C and D)\non Siemens and\nHologic\nmammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms.","on Hologic\nmammograms non-\ninferior to the\ncomparator device\n(K241561) on\nHologic\nmammograms."],["Characterization of\nthe device before and\nafter implementation\nof changes","The device will be accessible to more centers, and thus to more\nwoman. Prevents obsolescence of MammoScreen BD.\nBetter representation of breast tissue diversity leading to higher\noverall performances and a better generalization on unseen data.","",""],["Monitoring, detection,\nand response to\ndeviations in device\nperformance.","Therapixel monitors customer sites. The distribution of breast density\nassessment obtained is determined on a representative screening\ndistribution, which serves as a Reference Distribution. Device\nmonitoring compares breast density assessment in real conditions to\nthe reference distribution and alerts of any deviations. The\ninvestigation can result in a field-safety notice, a Medical Device\nReport.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241582-p6-t0","doc_id":"K241582","page_num":6,"bbox":[106.14,112.5,544.38,167.28],"n_rows":2,"n_cols":4,"columns":["Product","Marketed by","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","510(k) Number","Clearance Date"],["Aplio i900/i800/i700 Diagnostic\nUltrasound System, Software\nV7.0","Canon Medical\nSystems USA, Inc.","K223017","March 31, 2023"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241582-p8-t0","doc_id":"K241582","page_num":8,"bbox":[100.74,434.76,539.76,734.64],"n_rows":3,"n_cols":2,"columns":["Demographic distribution","This study included representative images\nfrom 50 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 20-98 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 16.4-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, mildly\nabnormal, moderately abnormal, and\nseverely abnormal categories of left\nventricle ejection fraction equivalently\nrepresented"],"rows":[["Demographic distribution","This study included representative images\nfrom 50 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 20-98 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 16.4-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, mildly\nabnormal, moderately abnormal, and\nseverely abnormal categories of left\nventricle ejection fraction equivalently\nrepresented"],["Data collection","Images from 239 demographically diverse\npatients acquired over a two-month period at\na U.S. clinical site."],["Truthing Method","A licensed sonographer selected\nrepresentative images for each of the four\nevaluated chamber views (A4C/A3C/A2C/SAX)"]],"caption_candidate":"Validation data details:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241582-p9-t0","doc_id":"K241582","page_num":9,"bbox":[100.74,449.22,539.76,735.66],"n_rows":3,"n_cols":2,"columns":["Demographic distribution","This study included images from 50 patients\nselected from among previously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 20-98 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 16.4-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, mildly\nabnormal, moderately abnormal, and\nseverely abnormal categories of left\nventricle ejection fraction equivalently\nrepresented"],"rows":[["Demographic distribution","This study included images from 50 patients\nselected from among previously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 20-98 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 16.4-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, mildly\nabnormal, moderately abnormal, and\nseverely abnormal categories of left\nventricle ejection fraction equivalently\nrepresented"],["Data collection","Images from 239 demographically diverse\npatients acquired over a two-month period at\na U.S. clinical site."],["Truthing Method","Ground truth was established by the median\nof manual measurement results taken by\nthree licensed sonographers using the"]],"caption_candidate":"Validation data details:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241582-p10-t0","doc_id":"K241582","page_num":10,"bbox":[100.74,422.34,539.76,708.78],"n_rows":3,"n_cols":2,"columns":["Demographic distribution","This study included representative images\nfrom 45 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nknown males and females*\n• Age: Ranging from 36-89 years old*\n• Ethnicity (Country): USA\n• BMI: ranging from 18.8-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, low severity,\nand high severity categories of LVOT\nvelocity time integral range\nequivalently represented"],"rows":[["Demographic distribution","This study included representative images\nfrom 45 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nknown males and females*\n• Age: Ranging from 36-89 years old*\n• Ethnicity (Country): USA\n• BMI: ranging from 18.8-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, low severity,\nand high severity categories of LVOT\nvelocity time integral range\nequivalently represented"],["Data collection","Images from 239 demographically diverse\npatients acquired over a two-month period at\na U.S. clinical site."],["Truthing Method","Ground truth was established by the median\nof manual LVOT measurement results taken by\nthree licensed sonographers"]],"caption_candidate":"Validation data details:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241582-p11-t0","doc_id":"K241582","page_num":11,"bbox":[100.74,381.06,539.76,667.5],"n_rows":3,"n_cols":2,"columns":["Demographic distribution","This study included representative images\nfrom 45 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nknown males and females*\n• Age: Ranging from 36-89 years old*\n• Ethnicity (Country): USA\n• BMI: ranging from 18.8-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, low severity,\nand high severity categories of AV\nvelocity time integral range\nequivalently represented"],"rows":[["Demographic distribution","This study included representative images\nfrom 45 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nknown males and females*\n• Age: Ranging from 36-89 years old*\n• Ethnicity (Country): USA\n• BMI: ranging from 18.8-71.6 kg/m2,\nequally distributed across\nunderweight or healthy, overweight,\nand obese categories\n• Disease severity: normal, low severity,\nand high severity categories of AV\nvelocity time integral range\nequivalently represented"],["Data collection","Images from 239 demographically diverse\npatients acquired over a two-month period at\na U.S. clinical site."],["Truthing Method","Ground truth was established by the median\nof manual AV measurement results taken by\nthree licensed sonographers"]],"caption_candidate":"Validation data details:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241585-p8-t0","doc_id":"K241585","page_num":8,"bbox":[116.1,79.5,534.3,279.54],"n_rows":11,"n_cols":3,"columns":["AIIR","Yes","Yes"],"rows":[["AIIR","Yes","Yes"],["HYPER Iterative","Yes","No"],["uExcel DPR","Yes","No"],["RMC","Yes","No"],["uKinetics","Yes","No"],["AIEFOV","Yes","No"],["Motion Management\n(MM)","Yes","No"],["CT-less AC","Yes","No"],["Retrospective\nRespiratory-gated\nScan","Yes","No"],["uExcel Unity","Yes","No"],["uExcel iQC","Yes","No"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241593-p5-t0","doc_id":"K241593","page_num":5,"bbox":[71.18,161.5,524.26,269.76],"n_rows":2,"n_cols":2,"columns":["Submitter","GLEAMER SAS\n47bis, rue des Vinaigriers\n75010, Paris 10, FRANCE"],"rows":[["Submitter","GLEAMER SAS\n47bis, rue des Vinaigriers\n75010, Paris 10, FRANCE"],["Primary Contact\nPerson","Antoine Tournier\nChief Compliance Officer\nTel: 0033 6 15 81 23 45\nEmail: antoine.tournier@gleamer.ai\nAlternate email: qara@gleamer.ai"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241593-p5-t1","doc_id":"K241593","page_num":5,"bbox":[71.18,318.01,524.26,401.37],"n_rows":6,"n_cols":4,"columns":["","Trade Name","","BoneMetrics (US)"],"rows":[["","Trade Name","","BoneMetrics (US)"],["","510(k) reference","","K241593"],["","Common Name","","Automated Radiological Image Processing Software"],["","Regulation","","21 CFR 892.2050"],["","Product Code","","QIH"],["","Classification","","Class II"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241593-p5-t2","doc_id":"K241593","page_num":5,"bbox":[71.18,449.67,524.26,477.35],"n_rows":2,"n_cols":4,"columns":["","Predicate Device","","IB Lab LAMA"],"rows":[["","Predicate Device","","IB Lab LAMA"],["","510(k) Reference","","K223646"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241593-p12-t0","doc_id":"K241593","page_num":12,"bbox":[71.18,499.27,524.22,600.65],"n_rows":7,"n_cols":14,"columns":["Endpoint","","","Metric","","Mean","","","Lower","","","Upper","","Acceptance criteria"],"rows":[["Endpoint","","","Metric","","Mean","","","Lower","","","Upper","","Acceptance criteria"],["","","","","","(95% CI)","","","Bound","","","Bound","",""],["","Cobb angle with the","","Mean Absolute\nError (°)","2.56","","","2.0","2.0","","3.28","3.28","","Upper bound of the MAE\n95% CI < 6.34°"],["","largest curvature","","","","","","","","","","","",""],["","n = 212","","","","","","","","","","","",""],["Minor Cobb angle\nn = 189","Minor Cobb angle","","Mean Absolute\nError (°)","2.78","","","2.29","","","3.33","","","Upper bound of the MAE\n95% CI < 6.34°"],["","n = 189","","","","","","","","","","","",""]],"caption_candidate":"(MAE) and an acceptance criteria.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241593-p13-t0","doc_id":"K241593","page_num":13,"bbox":[71.14,136.46,524.24,475.01],"n_rows":9,"n_cols":9,"columns":["Population","Endpoint","Metric","","Mean","","Lower\nBound","Upper\nBound","Acceptance\ncriteria"],"rows":[["Population","Endpoint","Metric","","Mean","","Lower\nBound","Upper\nBound","Acceptance\ncriteria"],["","","","","(95%","","","",""],["","","","","CI)","","","",""],["Adults","Cobb angle with\nthe largest\ncurvature\n(n=100)","Mean\nAbsolute\nError (°)","3.31","","","2.21","4.87","Upper bound of the\nMAE 95% CI < 6.34°"],["","Minor Cobb\nangle\n(n=90)","Mean\nAbsolute\nError (°)","2.91","","","2.29","3.68","Upper bound of the\nMAE 95% CI < 6.34°"],["Children","Cobb angle with\nthe largest\ncurvature\n(n=32)","Mean\nAbsolute\nError (°)","1.34","","","0.88","1.86","Upper bound of the\nMAE 95% CI < 6.34°"],["","Minor Cobb\nangle\n(n=18)","Mean\nAbsolute\nError (°)","1.95","","","1.01","3.21","Upper bound of the\nMAE 95% CI < 6.34°"],["Adolescent","Cobb angle with\nthe largest\ncurvature\n(n=80)","Mean\nAbsolute\nError (°)","2.11","","","1.71","2.56","Upper bound of the\nMAE 95% CI < 6.34°"],["","Minor Cobb\nangle\n(n=81)","Mean\nAbsolute\nError (°)","2.83","","","1.96","3.85","Upper bound of the\nMAE 95% CI < 6.34°"]],"caption_candidate":"and children and pediatrics population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241596-p6-t0","doc_id":"K241596","page_num":6,"bbox":[120.18,600.9,527.7,707.1],"n_rows":3,"n_cols":3,"columns":["ITEM","Proposed Device\nuMI Panvivo","Predicate Device\nuMI 780 (K172143)"],"rows":[["ITEM","Proposed Device\nuMI Panvivo","Predicate Device\nuMI 780 (K172143)"],["Patient bore size","700mm","700mm"],["PET System","Scintillator material: LYSO\nNumber of detector rings: 100\nAxial FOV: 295 mm","Scintillator material: LYSO\nNumber of detector rings: 112\nAxial FOV: 300 mm"]],"caption_candidate":"devices is provided as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p5-t0","doc_id":"K241620","page_num":5,"bbox":[71.11,170.86,524.26,295.32],"n_rows":2,"n_cols":2,"columns":["Submitter","GLEAMER SAS\n47bis, rue des Vinaigriers\n75010, Paris 10, FRANCE"],"rows":[["Submitter","GLEAMER SAS\n47bis, rue des Vinaigriers\n75010, Paris 10, FRANCE"],["Primary Contact\nPerson","Antoine Tournier\nChief Compliance Officer\nTel: 0033 6 15 81 23 45\nEmail: antoine.tournier@gleamer.ai\nAlternate email: qara@gleamer.ai"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p5-t1","doc_id":"K241620","page_num":5,"bbox":[71.11,333.85,524.26,445.31],"n_rows":7,"n_cols":4,"columns":["","Trade Name","","ChestView US"],"rows":[["","Trade Name","","ChestView US"],["","510(k) reference","","K241620"],["","Common Name","","Medical Image Analyzer"],["","Classification Name","","Medical Image Analyzer"],["","Regulation","","21 CFR 892.2070"],["","Product Code","","MYN"],["","Classification","","Class II"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p5-t2","doc_id":"K241620","page_num":5,"bbox":[71.11,483.87,524.26,515.59],"n_rows":2,"n_cols":4,"columns":["","Predicate Device","","Aorta-CAD"],"rows":[["","Predicate Device","","Aorta-CAD"],["","510(k) Reference","","K213353"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p10-t0","doc_id":"K241620","page_num":10,"bbox":[71.3,71.26,541.06,413.06],"n_rows":29,"n_cols":6,"columns":["","","","Radiologists/emergency medicine physicians","Physicians",""],"rows":[["","","","Radiologists/emergency medicine physicians","Physicians",""],["Intended Users","","","","",""],["","","","","",""],["","","","Device intended for use as a concurrent reading aid for\nusers interpreting chest radiographs","Same",""],["","Intended User","","","",""],["","Workflow","","","",""],["","","","","",""],["","","","Adults with Chest Radiographs","Same",""],["","Patient","","","",""],["","population","","","",""],["","","","","",""],["","","","","",""],["","Technological Information","","","",""],["","","","","",""],["","","","Supervised Deep learning","Same",""],["","Machine","","","",""],["","Learning","","","",""],["","Methodology","","","",""],["","","","","",""],["","","","Secure cloud-based processing and delivery of chest\nradiographs","Same",""],["","Deployment","","","",""],["","Platform","","","",""],["","","","","",""],["","","","Digital X-ray","Same",""],["Image Source","","","","",""],["","","","","",""],["","","","Image displayed on PACS system","Same",""],["Image Viewing","","","","",""],["","","","","",""]],"caption_candidate":"GLEAMER – ChestView US","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p11-t0","doc_id":"K241620","page_num":11,"bbox":[71.06,316.97,539.69,389.07],"n_rows":5,"n_cols":10,"columns":["","ROIs","","AUC","","","","95% Bootstrap CI","",""],"rows":[["","ROIs","","AUC","","","","95% Bootstrap CI","",""],["","NODULE","","","0.93","","","","[0.921; 0.938]",""],["","MEDIASTINUM/HILA ABNORMALITY","","","0.922","","","","[0.91; 0.934]",""],["","CONSOLIDATION","","","0.952","","","","[0.947; 0.957]",""],["","PLEURAL SPACE ABNORMALITY","","","0.973","","","","[0.97; 0.975]",""]],"caption_candidate":"Table 2: AUC of the ROC Curve for ChestView US Model Predictions by ROI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241620-p11-t1","doc_id":"K241620","page_num":11,"bbox":[71.06,433.39,539.69,619.62],"n_rows":11,"n_cols":13,"columns":["ROIs","","","","Specificity/Sensitivity","","","","","","","",""],"rows":[["ROIs","","","","Specificity/Sensitivity","","","","","","","",""],["","","","","High-sensitivity operating point","","","","","High-specificity operating point\n(FINDINGS)","","",""],["","","","","(POSSIBLE FINDINGS)","","","","","","","",""],["","","","","Specificity – 95%","","","Sensitivity – 95%","","Specificity – 95%\nBootstrap CI","","","Sensitivity – 95%\nBootstrap CI"],["","","","","Bootstrap CI","","","Bootstrap CI","","","","",""],["NODULE","","","0.956 [0.948; 0.963]","","","0.829 [0.801; 0.86]","","","0.994 [0.99; 0.996]","","0.482 [0.455; 0.518]",""],["","MEDIASTINUM/HILA","","0.975 [0.971; 0.98]","","","0.793 [0.739; 0.832]","","","0.992 [0.99; 0.994]","","0.535 [0.475; 0.592]",""],["","ABNORMALITY","","","","","","","","","","",""],["CONSOLIDATION","","","0.946 [0.938; 0.952]","","","0.853 [0.822; 0.879]","","","0.985 [0.981; 0.989]","","0.61 [0.583; 0.643]",""],["","PLEURAL SPACE","","0.965 [0.958; 0.971]","","","0.892 [0.87; 0.911]","","","0.975 [0.97; 0.981]","","0.87 [0.85; 0.896]",""],["","ABNORMALITY","","","","","","","","","","",""]],"caption_candidate":"level on the standalone dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p4-t0","doc_id":"K241659","page_num":4,"bbox":[251.4,492.27,566.18,598.7],"n_rows":6,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""],["","Secondary","","","","","","",""],["Medical image management and\nprocessing system","","","892.2050","","","LLZ","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""]],"caption_candidate":"Common Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p7-t0","doc_id":"K241659","page_num":7,"bbox":[74.59,131.17,722.21,530.95],"n_rows":8,"n_cols":11,"columns":["Feature","","Ultrasound Workspace","","","TOMTEC-ARENA","","","EPIQ Series Diagnostic","","Comparison"],"rows":[["Feature","","Ultrasound Workspace","","","TOMTEC-ARENA","","","EPIQ Series Diagnostic","","Comparison"],["","","Version 6.0 (UWS6.0)","","","TTA2.50","","","Ultrasound System","",""],["","","","","","","","","","",""],["","","Proposed Device","","","Predicate Device","","","Reference Device","",""],["K-number","Not available","","","K213544","","","K240850","","","Subject of this submission\nis UWS6.0"],["Intended Use","The product is a clinical\nsoftware package\ndesigned for review,\nquantification and\nreporting of structures and\nfunction based on multi-\ndimensional digital\nmedical data acquired with\ndifferent modalities. The\nproduct is not intended to\nbe used for reading of\nmammography images.","","","TOMTEC-ARENA\nsoftware is a clinical\nsoftware package\ndesigned for review,\nquantification and\nreporting of structures and\nfunction based on multi-\ndimensional digital\nmedical data acquired with\ndifferent\nmodalities.TOMTEC-\nARENA is not intended to\nbe used for reading of\nmammography images.","","","Abdominal, Cardiac Adult,\nCardiac other (Fetal),\nCardiac Pediatric,\nCerebral Vascular,\nCephalic (Adult), Cephalic\n(Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative (Vascular),\nIntraoperative (Cardiac),\nintra-luminal, intra-cardiac\necho, Musculoskeletal\n(Conventional),\nMusculoskeletal\n(Superficial), Ophthalmic,\nOther: Urology, Pediatric,\nPeripheral Vessel, Small\nOrgan (Breast, Thyroid,\nTesticle),\nTransesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung.","","","Intended Use/Indications\nfor use of predicate and\nsubject device are\nidentical (unchanged) -\nexcept of the product\nname (bolded).\nIntended Use/Indications\nfor use of reference device\nand subject device are\nsimilar and considered\nequivalent (specifically if\ncompared for the clinical\nuse case/workflow of the\nsubject feature)."],["Indications for Use","Indications for use of the\nproduct are quantification\nand reporting of\ncardiovascular, fetal, and\nabdominal structures and\nfunction of patients with\nsuspected disease to\nsupport the physician\nin the diagnosis.","","","Indications for use of\nTOMTEC-ARENA TTA2\nsoftware are quantification\nand reporting of\ncardiovascular, fetal,\nabdominal structures and\nfunction of patients with\nsuspected disease to\nsupport the physicians in\nthe diagnosis","","","","","",""],["Intended Users","The product is intended\nto be used only by","","","TOMTEC-ARENA\nsoftware is intended to be","","","The product is intended to\nbe used only by licensed","","","Identical for predicate and\nsubject device -except of"]],"caption_candidate":"Table 1: Comparison to Predicate and Reference Device for introduction of SWM onto UWS6.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p11-t0","doc_id":"K241659","page_num":11,"bbox":[42.67,142.66,742.91,512.92],"n_rows":13,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["K-number","Not available","K213544","Subject of this submission is UWS6.0"],["","","",""],["","3D Auto TV software enables semi-\nautomated quantification of the tricuspid valve\nduring transesophageal echocardiography\n(TEE) and transthoracic echocardiography\n(TTE) examinations. It applies artificial\nintelligence for model based segmentation. At\na high level, this is accomplished through\nautomatically derived measurements from a\nsegmented model of the tricuspid valve\nannulus formed by the software through\nmodel-based segmentation of the acquired\nultrasound images.","3D Auto MV (formerly named 4D MV-\nASSESSMENT) is a semi-automated\nsoftware application intended for the analysis\nof Mitral Valve (MV) anatomy and function.\nThis application generates models of\nanatomical structures of interest such as the\nMV annulus, leaflets, and the closure line,\nwhich allows for quantification of pre- and\npost-operative valvular function and a\ncomparison of morphology.\n4D CARDIO-VIEW is an advanced analysis\ntool for 3D/4D echocardiography data.\nAnatomical structure visualization, volume\nmeasurements (LV and/or generic), and\nspecified or manual measurements are\npossible for cardiac structures including, but\nnot limited to, the tricuspid valve. Various\ntools are available for rendering that display\n2- and 3-dimensional morphology and\nfunction for defined structures.","Similar to the predicate device features.\nThe functionality and workflow of the 3D Auto\nTV software is very similar to the 3D Auto\nMV tool, where measurement parameters are\nderived from models of the mitral valve (in the\ncase of 3D Auto MV) and tricuspid valve (in\nthe case of 3D Auto TV). Manual\nmeasurements are also able to be performed\non both software applications.\nComparing 3D Auto TV to 4D CARDIO-\nVIEW, both software have functionality for\nquantifying the tricuspid valve. The proposed\n3D Auto TV allows semi-automated\nquantification, where the reference device is\nfully manual. As we demonstrate high\nagreement in the measurement outputs on\nthe same patients when quantified using the\nproposed 3D Auto TV software and the\nreference 4D CARDIO-VIEW application\n(REF #4), there are no new questions raised\nof safety or effectiveness.\nThe subject of this submission is introduction\nof semi-automated quantification via 3D Auto\nTV of UWS6.0."],["Application","","",""],["Description","","",""],["3D Auto TV","","",""],["","","",""]],"caption_candidate":"For Indications for Use, Intended Use, Product Code Information, Classification please refer to Table 1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p12-t0","doc_id":"K241659","page_num":12,"bbox":[42.67,108.1,742.91,531.7],"n_rows":14,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["","3D surface model is created semi-\nautomatically using machine learning\nalgorithm without user interaction. User is\nable to edit, accept, or reject the initial\nlandmark proposals of the tricuspid valve\nanatomical locations.","3D Auto MV: 3D surface model is created\nsemi-automatically using machine learning\nalgorithm without user interaction. User is\nable to edit, accept, or reject the initial\nlandmark proposals of the mitral valve\nanatomical locations.\n4D CARDIO-VIEW: 3D surface model is\ncreated based on user defined anatomical\nlandmarks. User is able to edit the contour of\nthe surface model before proceeding with the\nworkflow.","Subject device uses identical method for\ncontour generation as the 3D Auto MV\napplication of the predicate device. The only\ndifference is the algorithm is trained on\ntricuspid valve images, where the predicate\ndevice was trained using mitral valve images"],["Contour","","",""],["Generation","","",""],["","","",""],["","Semi-auto annulus results\n• TV Ann Perimeter (3D)\n• TV Ann Perimeter (2D)\n• TV Ann Max Diam (2D)\n• TV Ann Min Diam (2D)\n• TV Ann Perimeter Derived Diam (2D)\n• TV Ann Height (3D)\n• TV Ann Area (2D)\nManual device results\n• TV Ann AP Diam (2D)\n• TV Ann SL Diam (2D)\n• Subvalvular 5 Plane SL Diam\n• Subvalvular 5 Plane AP Diam\n• Supravalvular C-Shaped Perimeter\n• Supravalvular AV - AoCenter Diam","3D Auto MV:\nStandard MV Parameters\n• AP Diameter (cm)\n• AL-PM Diameter (cm)\n• Sphericity Index (AP / AL-PM)\n• Intertrigonal Distance (cm)\n• Commissural Diameter (cm)\n• D-Shaped Annulus Perimeter (cm)\n• Annulus Height (cm)\n• Non-planar Angle (degrees)\n• Tenting Volume (cm3)\n• Coaptation Depth (mm)\n• Tenting Area (cm2)\n• Angle AAo-AP (degrees)\n• Maximum Prolapse Height (mm)\n• Maximum Open Coaptation Gap (mm)\n• Maximum Open Coaptation Width (mm)\n• Anterior Leaflet Area (cm2)\n• Posterior Leaflet Area (cm2)\n• Distal Anterior Leaflet Angle (degrees)\n• Posterior Leaflet Angle (degrees)\n• Anterior Leaflet Length (cm)\n• Posterior Leaflet Length (cm)","Similar. The proposed 3D Auto TV software\nenables a subset of very similar semi-\nautomated measurements as the predicated\nsoftware application 3D Auto MV, only for the\ntricuspid annulus.\nThe proposed 3D Auto TV software adds\nadditional TV annulus and device\nmeasurements from those available in 4D\nCARDIO-VIEW to further define the tricuspid\nvalve anatomy.\nBoth the proposed 3D Auto TV and the\npredicate 4D CARDIO-VIEW software allow\nmanual, free-form measurements of the\nvalve."],["Measurements","","",""],["Performed","","",""],["","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p13-t0","doc_id":"K241659","page_num":13,"bbox":[42.63,108.1,742.89,463.67],"n_rows":7,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["","","• C-Shaped Annulus (cm)\n2D MV Parameters\n• D-Shaped Annulus Area (cm2)\n• Annulus Area (cm2)\n• Anterior Closure Line Length (cm)\n• Posterior Closure Line Length (cm)\n3D MV Parameters\n• Saddle Shaped Annulus Area (cm2)\n• Saddle Shaped Annulus Perimeter (cm)\n• Total Open Coaptation Area (cm2)\n• Anterior Closure Line Length (cm)\n• Posterior Closure Line Length (cm)\n4D CARDIO-VIEW:\nTAVR results\n• Ann-Ost left diam\n• Ann-Ost right diam\n• Annulus Area\n• Annulus dmin\n• Annulus dmax\n• Ao Ring diam\n• Ao SV diam\n• Ao STJ diam\nVolume results (not related to TV\nquantification)\n• EDV\n• EF\n• ESV\n• GenVol\n• Mass\n• SV",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p14-t0","doc_id":"K241659","page_num":14,"bbox":[42.67,183.44,742.93,530.95],"n_rows":17,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["K-number","Not available","K213544","Subject of this submission is UWS6.0"],["","","",""],["","The 3D Auto CFQ is a new artificial\nintelligence software which will be introduced\non the Ultrasound Workspace Software\nsystem starting with Version 6.0. The\napplication provides semi-automated\nquantification of Mitral Regurgitation (MR)\nvolume and peak flow rate based on 3D color\nflow images acquired during\ntransesophageal echocardiography (TEE)\nexaminations.","The Proximal Isovelocity Surface Area (PISA)\nmethodology can be used currently on the\npredicate device to quantify valvular\nregurgitation. The technique utilizes 2D/Color\nand Doppler images to allow the user to make\nsimple, manual measurements in a cascading\nfashion to allow calculation of peak flow rate\nand volumetric regurgitation.\n3D Auto MV is a semi-automated software\napplication intended for the analysis of Mitral\nValve (MV) anatomy and function. This\napplication generates models of anatomical\nstructures of interest such as the MV annulus,\nleaflets, and the closure line, which allows for\nquantification of pre- and post-operative\nvalvular function and a comparison of\nmorphology.","Similar. The predicate device facilitates the\nquantification of mitral regurgitation volume\nand peak flow rate through a group of\nmeasurements which are performed in a\ncascading fashion manually by the user\naccording to the Proximal Isovelocity Surface\nArea (PISA) methodology. The proposed 3D\nAuto CFQ software application allows the\nusers to quantify the same measurements for\nmitral regurgitation volume and peak flow rate\nbut in a semi-automated workflow.\n3D Auto MV feature of the predicate does not\ncontain functionality for quantification of mitral\nregurgitation."],["Application","","",""],["Description","","",""],["3D Auto CFQ","","",""],["","","",""],["","3D surface model is created semi-\nautomatically using machine learning\nalgorithm without user interaction. User is\nable to edit, accept, or reject the initial\nlandmark proposals of the mitral valve\nanatomical locations.","PISA: No standard contour generation\ntechnology for the mitral valve, outside of 3D\nAuto MV, included as part of the system.\n3D Auto MV: 3D surface model is created\nsemi-automatically using machine learning","Subject device uses identical method for\ncontour generation as the 3D Auto MV\nfeature of the predicate device."],["Contour","","",""],["Generation","","",""],["","","",""]],"caption_candidate":"For Indications for Use, Intended Use, Product Code Information, Classification please refer to Table 1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p15-t0","doc_id":"K241659","page_num":15,"bbox":[42.67,108.1,742.91,523.7],"n_rows":13,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["","","algorithm without user interaction. User is able\nto edit, accept, or reject the initial landmark\nproposals of the mitral valve anatomical\nlocations.",""],["","The 3D Auto CFQ algorithm quantifies mitral\nregurgitation volume and flow rate from\nacquired 3D color flow images. The greyscale\ninformation from these images is used to\ngenerate a 3D model of the mitral valve,\nwhich is used as an input along with the 3D\ncolor data into the 3D Auto CFQ flow\nalgorithm. The 3D Auto CFQ algorithm uses a\nfluid dynamic model of an incompressible\nfluid (blood) traveling through an irregular-\nshaped (i.e., nonround) orifice. In its initial\nstep, the algorithm generates a hypothetical\nmodel of true blood flow velocities in the\nproximal convergence zone based on all\nmeasured Doppler velocities and the\nunderlying fluid dynamics model. The true\nvelocity model is then converted into the\ncorresponding apparent Doppler velocity\nmodel (“synthetic apparent velocities”) using\nultrasound physics (projection along the axial\ndimension). These synthetic velocities are\nsubsequently compared to the acquired\nvelocities in the Color Flow (CF) data set.\nBased on the outcome of this comparison,\nthe model is updated and reiterated to get\nthe best fit between the acquired velocities\nand the generated model. 3D Auto CFQ\ndetermines the resulting regurgitant flow rate","PISA:\nThe PISA methodology uses sequential\nacquisitions and manual measurements,\nwhich are manually performed by the user:\n- MR Alias Velocity (from the 2D/Color)\n- MR Radius (from the 2D/Color)\n- MR Vmax (from the continuous wave\ndoppler)\n- MR VTI (from the continuous wave\ndoppler)\nThe outputs of these measurements go into\nthe equations for the derived measurements\nincluding:\n- Mitral Regurgitant (MR) Flow Rate\n- MR Effective Regurgitant Orifice (ERO)\n- MR Volume\n3D Auto MV:\nN/A – does not contain technology for mitral\nregurgitation quantification","Similar. The PISA methodology of the\npredicate device – used for quantifying MR\nvolume and flow rate - utilizes sequential\nmeasurements performed by the user and is\nbased on assumptions including there being\na single, round, constant flow orifice during\nthe entire systole.\n3D Auto CFQ operates using 3D color to\naddress the spatial complexities seen in\nmitral regurgitation and was developed to\nevaluate the regurgitant flow at every frame in\nsystole, where the PISA methodology only\nassesses one frame during systole and\nassumes this frame applies across systole.\nThe proposed 3D Auto CFQ software\napplication allows the users to quantify the\nsame measurements for mitral regurgitation\nvolume and peak flow rate as PISA. The\ndynamic flow algorithm is the new technology\nintroduced in this submission. Mitral valve\nmodel generation is identical to the 3D Auto\nMV feature of the predicate device. The\ndynamic flow model of the 3D Auto CFQ\nsoftware application uses this as input to\narrive at the outputs of mitral regurgitation\nvolume and peak flow rate. These outputs are"],["Quantification","","",""],["Technology for","","",""],["Mitral","","",""],["Regurgitation","","",""],["","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p16-t0","doc_id":"K241659","page_num":16,"bbox":[42.65,108.1,742.91,528.2],"n_rows":11,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["","for this frame. This process is repeated for\neach frame included in the analysis, which in\nmost cases includes the entire systolic cycle.\nIn each frame, the size and shape of the\nregurgitant orifice is not assumed but is\ngenerated by this iterative loop between the\nmodel and the CF data.","","the same as in the predicate, only the method\nto arrive at the measurements differs in the\nsubject device."],["","Semi-automated measurements performed\nby the 3D Auto CFQ software application:\nMitral regurgitation (MR) volume [mL];\nPeak flow rate [mL/s]","PISA:\nDerived measurements which the user can\nobtain through the PISA methodology include:\nMitral regurgitation (MR) volume [mL];\nPeak flow rate [mL/s]\n3D Auto MV:\nStandard MV Parameters\n• AP Diameter (cm)\n• AL-PM Diameter (cm)\n• Sphericity Index (AP / AL-PM)\n• Intertrigonal Distance (cm)\n• Commissural Diameter (cm)\n• D-Shaped Annulus Perimeter (cm)\n• Annulus Height (cm)\n• Non-planar Angle (degrees)\n• Tenting Volume (cm3)\n• Coaptation Depth (mm)\n• Tenting Area (cm2)\n• Angle AAo-AP (degrees)\n• Maximum Prolapse Height (mm)\n• Maximum Open Coaptation Gap (mm)\n• Maximum Open Coaptation Width (mm)\n• Anterior Leaflet Area (cm2)\n• Posterior Leaflet Area (cm2)\n• Distal Anterior Leaflet Angle (degrees)\n• Posterior Leaflet Angle (degrees)\n• Anterior Leaflet Length (cm)\n• Posterior Leaflet Length (cm)","Similar. The measurements performed by the\nproposed 3D Auto CFQ software application\ncan also be obtained by a user on the\npredicate device using the PISA\nmethodology.\nSubstantiation of the performance of the 3D\nAuto CFQ software’s regurgitant volume\noutput was performed by comparison to\ncardiac magnetic imaging with (CMR) images\nwith acceptance criteria of agreement within\nthe limits of agreement. While the PISA\nmethodology is a widely accepted method for\nmitral regurgitation quantification and is a\nrecommended method by the American\nSociety of Echocardiography, the outputs\nfrom 3D Auto CFQ were compared to those\nfrom CMR (as opposed to PISA) as the\nformer is considered a gold standard for\nmitral regurgitation quantification.\nAcceptance criteria for 3D Auto CFQ was\nbased on agreement with CMR being within\npredefined maximum limits of agreement."],["Measurements","","",""],["Performed","","",""],["","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p17-t0","doc_id":"K241659","page_num":17,"bbox":[42.63,108.1,742.89,281.59],"n_rows":7,"n_cols":4,"columns":["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],"rows":[["","Ultrasound Workspace Version 6.0","TOMTEC-ARENA",""],["","(UWS6.0)","TTA2.50 - K213544",""],["Feature","","","Comparison"],["","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["","","• C-Shaped Annulus (cm)\n2D MV Parameters\n• D-Shaped Annulus Area (cm2)\n• Annulus Area (cm2)\n• Anterior Closure Line Length (cm)\n• Posterior Closure Line Length (cm)\n3D MV Parameters\n• Saddle Shaped Annulus Area (cm2)\n• Saddle Shaped Annulus Perimeter (cm)\n• Total Open Coaptation Area (cm2)\n• Anterior Closure Line Length (cm)\n• Posterior Closure Line Length (cm)","In addition to regurgitant volume, the peak\nflow rate output of 3D Auto CFQ was\nvalidated in comparison to manual PISA\nmethod, where the correlation was very high.\n3D Auto MV feature of the predicate device\nfacilitates anatomical measurements of the\nmitral valve from the generated model of the\nmitral valve but does not perform\nmeasurements for quantifying mitral\nregurgitation."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241659-p18-t0","doc_id":"K241659","page_num":18,"bbox":[74.58,142.67,722.2,489.68],"n_rows":7,"n_cols":11,"columns":["Feature","","Ultrasound Workspace","","","TOMTEC-ARENA","","","EPIQ Series Diagnostic","","Comparison"],"rows":[["Feature","","Ultrasound Workspace","","","TOMTEC-ARENA","","","EPIQ Series Diagnostic","","Comparison"],["","","Version 6.0 (UWS6.0)","","","TTA2.50","","","Ultrasound System","",""],["","","","","","","","","","",""],["","","Proposed Device","","","Predicate Device","","","Reference Device","",""],["K-number","Not available","","","K213544","","","K202216","","","Subject of this submission\nis UWS6.0"],["Transducer Clinical\nApplication / cleared\ncompatibility","VeriSight ICE / Pro ICE\n(Proposed Transducer)\nTEE (transesophageal)\ntransducer.\nIntended for intracardiac\nand intra-luminal\nvisualization of cardiac and\ngreat vessel anatomy and\nphysiology as well as\nvisualization of other\ndevices in the heart. The\nVeriSight ICE catheter\nprovides 2D ultrasound\nimaging capabilities, while\nthe VeriSight Pro ICE\ncatheter provides 2D\nand/or 3D ultrasound\nimaging capabilities.","","","N/A, compatibility to\nVeriSight ICE / Pro ICE\nhas not been shown.","","","VeriSight ICE / Pro ICE\nwas introduced on EPIQ\nvia K202216.\nTEE (transesophageal)\ntransducer.\nIntended for intracardiac\nand intra-luminal\nvisualization of cardiac and\ngreat vessel anatomy and\nphysiology as well as\nvisualization of other\ndevices in the heart. The\nVeriSight ICE catheter\nprovides 2D ultrasound\nimaging capabilities, while\nthe VeriSight Pro ICE\ncatheter provides 2D\nand/or 3D ultrasound\nimaging capabilities.","","","Identical to reference\ndevice."],["Data Compatibility","Compatibility to UWS6.0 is\nsubject of this submission.","","","N/A, for TTA2\ncompatibility for VeriSight\nICE / Pro ICE has not\nbeen shown.","","","VeriSight ICE / Pro ICE\nwas introduced on EPIQ\nvia K202216.","","","Identical to reference\ndevice."]],"caption_candidate":"Table 4: Comparison to Predicate and Reference Device for Compatibility to VeriSight ICE / Pro ICE Probe on UWS6.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241665-p5-t0","doc_id":"K241665","page_num":5,"bbox":[77.47,575.88,545.45,699.42],"n_rows":6,"n_cols":2,"columns":["Predicate DeviceInformation",""],"rows":[["Predicate DeviceInformation",""],["Device Name","Omni Legend"],["Manufacturer","GE Medical Systems Israel, Functional Imaging"],["510(k) number","K221932"],["Regulation number","21CFR 892.1200 and 21CFR892.1750"],["Product Code","KPS and JAK"]],"caption_candidate":"Product Code KPS and JAK","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241665-p6-t0","doc_id":"K241665","page_num":6,"bbox":[77.98,103.8,545.21,227.34],"n_rows":6,"n_cols":2,"columns":["ReferenceDeviceInformation",""],"rows":[["ReferenceDeviceInformation",""],["Device Name","Precision DL"],["Manufacturer","GE Medical Systems Israel, Functional Imaging"],["510(k) number","K223212"],["Regulation Number","21CFR 892.1200"],["Product Code","KPS"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241665-p6-t1","doc_id":"K241665","page_num":6,"bbox":[77.98,246.24,545.21,383.58],"n_rows":6,"n_cols":2,"columns":["ReferenceDeviceInformation",""],"rows":[["ReferenceDeviceInformation",""],["Device Name","Discovery MI"],["Manufacturer","GE Medical System, L.L.C."],["510(k) number","K161574"],["Regulation number","21CFR 892.1200 and 21CFR 892.1750"],["Product Code","KPS and JAK"]],"caption_candidate":"Product Code KPS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241665-p8-t0","doc_id":"K241665","page_num":8,"bbox":[72.29,372.51,539.8,642.9],"n_rows":8,"n_cols":9,"columns":["","Specification/","","","Predicate Device:","","","Proposed Device:",""],"rows":[["","Specification/","","","Predicate Device:","","","Proposed Device:",""],["","Attribute","","","Omni Legend(K221932)","","","Omni Legend",""],["PET Gantry","","","Multiple detector ring configurations\n(16, 32cm axial FOV).70 cm bore.","","","Multiple detector ring configurations\n(16,21,32cm axial FOV).70 cm bore","",""],["Detector Unit","","","SiPM-based light sensor with ASIC","","","SiPM-based light sensor with ASIC","",""],["","","","BGO scintillator crystals","","","BGO scintillator crystals","",""],["CT System","","","Revolution Maxima (K192686)","","","Revolution Maxima(K192686)","",""],["Image Reconstruction\n/ Processing","","","Iterative Image Reconstruction,\nincluding Precision DL (K223212)","","","Iterative Image Reconstruction,\nincluding Precision DL (K223212).\nPET DigitalGating (DDG) also known\nas MotionFree (K180318)\nEnhanced AC option","",""],["Standards\nConformance","","","IEC 60601-1 and applicable Collateral\nand Particular Standards.","","","IEC 60601-1 and applicable Collateral\nand Particular Standards.","",""]],"caption_candidate":"differences between the predicate and proposed devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241671-p6-t0","doc_id":"K241671","page_num":6,"bbox":[21.52,618.31,598.8,763.02],"n_rows":4,"n_cols":2,"columns":["K230179",""],"rows":[["K230179",""],["","Device Description Summary 21 CFR 807.92(a)(4)"],["",""],["6450 Ultrasound System is a general-purpose diagnostic ultrasound system, based on a mainframe platform that can be easily moved\nthanks to four swivelling wheels.\naudible to the human ear) for the visualization of deep structures of the body by recording the reflections or echoes of ultrasonic pulses",""]],"caption_candidate":"K192157 6450 MyLabX8 IYN","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241671-p7-t0","doc_id":"K241671","page_num":7,"bbox":[19.71,18.98,598.8,761.8],"n_rows":10,"n_cols":3,"columns":["directed into the tissues and of the Doppler effect, i.e. the frequency-shifted ultrasound reflections produced by moving targetsI (nutseurnalalyl Use\nred blood cells) in the bloodstream, to determine both direction and velocity of blood flow in the target organs.\nThe primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both PW and\nCW), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes. 6450 Ultrasound System also\nmanages Elastosonography (ElaXto, QElaXto, QElaXto 2D), 3D/4D and CnTI.\nSeveral types of probes are used to cover different needs in terms of geometrical shape and frequency range.\n6450 Ultrasound System can drive Phased Array, Convex Array, Linear Array, Doppler probes and Volumetric probes (Bi-Scan probes).\nThe control panel is equipped with a pull-out Qwerty alphanumeric keyboard that allows data entry. The touchscreen has an emulation\nof the Qwerty keyboard that allows data entry and has additional controls and mode-depending keys, integrated in the touchscreen.\n6450 Ultrasound System is equipped with wireless capability.\n6450 Ultrasound System will be available on the market in two models with the following commercial names: MyLabE80, MyLabE85.\nThe difference between MyLabE80 and MyLabE85 models is only in the licenses configuration.\nFor both models, there is the ETC (Easy To Clean) version, having a keyboard with special controls and material, compatible with\ndisinfection procedures.\n6450 Ultrasound System, defined herein, introduces new features and accessories listed below:\n1. XStrain LA: XStrain allows clinicians to quantify endocardial velocities of contraction and relaxation and local deformation of the heart\n(Strain/Strain rate). XStrain LA is an advanced processing package for the Left Atrium analysis.\n2. New probe: IHX 6-25\n6450 Ultrasound System employs the same fundamental technological characteristics as its predicate device cleared via K192157.","","sI (nutseurnalalyl Use"],"rows":[["directed into the tissues and of the Doppler effect, i.e. the frequency-shifted ultrasound reflections produced by moving targetsI (nutseurnalalyl Use\nred blood cells) in the bloodstream, to determine both direction and velocity of blood flow in the target organs.\nThe primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both PW and\nCW), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes. 6450 Ultrasound System also\nmanages Elastosonography (ElaXto, QElaXto, QElaXto 2D), 3D/4D and CnTI.\nSeveral types of probes are used to cover different needs in terms of geometrical shape and frequency range.\n6450 Ultrasound System can drive Phased Array, Convex Array, Linear Array, Doppler probes and Volumetric probes (Bi-Scan probes).\nThe control panel is equipped with a pull-out Qwerty alphanumeric keyboard that allows data entry. The touchscreen has an emulation\nof the Qwerty keyboard that allows data entry and has additional controls and mode-depending keys, integrated in the touchscreen.\n6450 Ultrasound System is equipped with wireless capability.\n6450 Ultrasound System will be available on the market in two models with the following commercial names: MyLabE80, MyLabE85.\nThe difference between MyLabE80 and MyLabE85 models is only in the licenses configuration.\nFor both models, there is the ETC (Easy To Clean) version, having a keyboard with special controls and material, compatible with\ndisinfection procedures.\n6450 Ultrasound System, defined herein, introduces new features and accessories listed below:\n1. XStrain LA: XStrain allows clinicians to quantify endocardial velocities of contraction and relaxation and local deformation of the heart\n(Strain/Strain rate). XStrain LA is an advanced processing package for the Left Atrium analysis.\n2. New probe: IHX 6-25\n6450 Ultrasound System employs the same fundamental technological characteristics as its predicate device cleared via K192157.","","sI (nutseurnalalyl Use"],["","Intended Use/Indications for Use 21 CFR 807.92(a)(5)",""],["","",""],["The multifunctional ultrasound scanner is used to collect, display and analyze ultrasound images during ultrasound imaging procedures\nin combination with supported echographic probes.\nMain application: Districts: Invasive access:\nCardiac Cardiac Adult, Cardiac Pediatric Transesophageal\nVascular Neonatal, Adult Cephalic, Vascular Not applicable\nGeneral Imaging Abdominal, Breast, Musculoskeletal, Intraoperative (Abdominal),\nNeonatal, Pediatric, Small Organs Laparoscopic, Transrectal\n(Testicles), Thyroid, Urological\nWomen Health OB/Fetal, Gynecology Transrectal, Transvaginal\nVirtual Navigator option supports a radiological clinical ultrasound examination (first modality) by providing additional image\ninformation from a second imaging modality. As second imaging modality it is intended any image coming from CT, MR, US, PET, XA and\nNM.\nThe second modality provides additional security in assessing the morphology of the real time ultrasound image.\nThe primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both Pulsed\nWave (PW) and Continuous Wave (CW)), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes,\nElastosonography, 3D/4D and CnTI.\nThe ultrasound scanner is suitable to be installed in professional healthcare facility environment and is designed for ultrasound\npractitioners.","",""],["","Indications for Use Comparison 21 CFR 807.92(a)(5)",""],["","",""],["The indications for use of the 6450 Ultrasound System are the same as those of predicate device, cleared via K192157.","",""],["","Technological Comparison 21 CFR 807.92(a)(6)",""],["","",""],["The new version of Esaote 6450 Ultrasound System is substantially equivalent to the predicate device 6450 Ultrasound System (cleared","",""]],"caption_candidate":"directed into the tissues and of the Doppler effect, i.e. the frequency-shifted ultrasound reflections produced by moving targetsI (nutseurnalalyl Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241684-p7-t0","doc_id":"K241684","page_num":7,"bbox":[72.63,130.2,539.37,708.5],"n_rows":8,"n_cols":2,"columns":["PCCPDetails","Description"],"rows":[["PCCPDetails","Description"],["ModificationOverview","Improveperformancebyreducingfalsepositive\nandfalsenegativeoutputsbasedonpost-market\nandreal-worlddata. Specifically,improvements\nresultingfromre-trainingtheMLmodelwithnew\ndata."],["Rationale","Aimstoenhanceclinicalutilitybyimprovingthe\ndevice’saccuracy,ensuringreliabledatafor\nprecisecharting,andsupportinghigh-quality\npatientcareanddocumentation."],["PerformanceEvaluationActivity","Identicaltotheacceptancecriteriaandstandalone\nstudyprotocolforthepre-modifiedversionofthe\ndeviceclearedinK233590.Primaryendpoints\nwillbethemainacceptancecriteria,other\nendpointsandadditionalanalyseswillbe\nconductedandreviewedforanymajordropin\nperformance.\nIfaspecificmodificationfailsperformance\nevaluation,failure(s)willbedocumented,andthe\nmodificationwillnotbeimplemented."],["Implementation","Themodificationwillbeimplementedmanually\n(non-automatic)acrossalldevicesonthemarket\ninauniformmanner(globaladaptation)."],["ImpactonIndications/IntendedUse","Themodificationwillnotaffecttheindicationsor\nintendeduseoftheOverjetChartingAssist\ndevice,asclearedunderK233590."],["Release","ThePCCPdoesnotincludeanyprovisionsfor\nimplementationofadaptivealgorithmsthatwill\ncontinuouslylearninthefield.Inaccordancewith\nthePCCP,allalgorithmmodificationswillbe\ntrained,tuned,andlockedpriortoreleaseofthe\nsoftwaretothefield."],["InstructionsforUse","AprocedureforupdatingInstructionsforUse\nupdateshasbeenestablishedinordertoinform\nusersaboutalgorithmchangesimplementedunder\nthisFDA-authorizedPCCP,includingasummary"]],"caption_candidate":"PCCPandmodificationprotocoldescriptionisprovidedinthetablebelow:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241696-p6-t0","doc_id":"K241696","page_num":6,"bbox":[72.24,612.6,535.56,715.8],"n_rows":4,"n_cols":4,"columns":["Feature","Subject Device","Predicate Device","Comparison"],"rows":[["Feature","Subject Device","Predicate Device","Comparison"],["510(k) Number","K241696","K192109","N/A"],["Name","Ortho AI","IB Lab’s KOALA\nSoftware","N/A"],["Classification\nName and\nProduct Code","System, Image\nProcessing,\nRadiological (QIH)","System, Image\nProcessing,\nRadiological (LLZ)","Same"]],"caption_candidate":"Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241696-p7-t0","doc_id":"K241696","page_num":7,"bbox":[72.24,72.24,535.56,708.72],"n_rows":8,"n_cols":4,"columns":["Runs on Server","Yes","Yes","Same"],"rows":[["Runs on Server","Yes","Yes","Same"],["Image input","JPEG, PNG, BMP,\nDICOM","DICOM compliant\nimages collected in other\ndevices in either digitally\ncomputed (CR) or\ndirectly digital (DX)\nformats.","Similar. The subject\ndevice is validated to\nadditionally analyze other\nstandard image formats\nand does not raise new\nquestions about safety or\neffectiveness."],["Imaging\nprocessing","Landmark detection, user\ncan edit landmark","Knee detection;\nLandmark detection;\nJoint space detection","Same"],["Anatomical\nArea","Knee, Hip, Lumbar Spine","Leg","Similar. The subject\ndevice is intended to be\nused on the knee, hip, and\nlumbar spine while the\npredicate device is only\nfor the leg. This\ndifference in specific\nanatomic locations does\nnot raise new types of\nquestions for safety or\neffectiveness."],["Measurement","Length and angle","Length and angle","Same"],["Way of\nMeasurement","Semi-automatic (AI\ndriven)","Automatic (AI driven)","Similar. The subject\ndevice requires the user\nto review and edit the\ndevice output as\nnecessary while the\npredicate device does not\nas a fully automatic\ndevice."],["Intended User","Trained Professional","Trained Professional","Same"],["Indications for\nUse","Ortho AI is an image-\nprocessing software\nindicated to assist in\nmaking measurements for\na total hip arthroplasty,\ntotal knee arthroplasty,\nand lumbar spine fusion\nsurgery.\nIt is intended to assist in\nthe measurement of x-ray\nimages by measuring\nlengths, angles and\nposition of implants\nrelative to the bone\nstructures of interest,\nprovided that the points\nof interest can be","IB Lab KOALA is a\nradiological fully-\nautomated image\nprocessing software\ndevice of either computed\n(CR) or directly digital\n(DX)images intended to\naid medical professionals\nin the measurement of\nminimum joint space\nwidth; the assessment of\nthe presence or absence\nof sclerosis, joint space\nnarrowing, and\nosteophytes based\nOARSI criteria for these\nparameters; and the\npresence or absence of","The subject device\nperforms measurements\nof lengths and angles on\nhip, knee, and lumbar\nspine images. The\npredicate device performs\nlength and angle\nmeasurements on leg\nimages. This difference in\nspecific anatomic\nlocations does not raise\nnew questions for safety\nor effectiveness and\ntherefore does not induce\nchanges in the intended\nuse"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p5-t0","doc_id":"K241719","page_num":5,"bbox":[72.5,654.5,540.5,702.5],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application Number"],"rows":[["Manufacturer","Device Name","Application Number"],["Viz.ai, Inc.","Viz ICH","K210209"]],"caption_candidate":"Predicate Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p7-t0","doc_id":"K241719","page_num":7,"bbox":[66.5,362.5,516.5,718.5],"n_rows":2,"n_cols":3,"columns":["Parameter","Subject Device\nNeuroICH","Predicate Device\nViz ICH"],"rows":[["Parameter","Subject Device\nNeuroICH","Predicate Device\nViz ICH"],["Indications of\nuse","NeuroICH is a notification-only,\nparallel workflow tool for use by\nhospital networks and trained\nclinicians to identify and\ncommunicate images of\nsuspected ICH patients to a\nspecialist, independent of\nstandard of care workflow.\nThe device uses an artificial\nintelligence algorithm to analyze\nnon-contrast CT images of the\nhead acquired in the acute setting\nfor findings suggestive of\nintracranial hemorrhage (ICH) in\nparallel to the ongoing standard of\ncare image interpretation and\nnotify an appropriate clinician of\nthese findings. Notifications\ninclude non-diagnostic preview\nimages that are meant for\ninformational purposes only. The\ndevice does not alter or remove\nthe original medical image and is\nnot intended to be used as a\ndiagnostic device. Images can be","Viz ICH is a notification-only,\nparallel workflow tool for use by\nhospital networks and trained\nclinicians to identify and\ncommunicate images of specific\npatients to a specialist, independent\nof standard of care workflow.\nViz ICH uses an artificial\nintelligence algorithm to analyze\nimages for findings suggestive of a\nprespecified clinical condition and\nto notify an appropriate medical\nspecialist of these findings in\nparallel to standard of care for\nimage interpretation. Identification\nof suspected findings is not for\ndiagnostic use beyond notification.\nSpecifically, the device analyzes\nnon-contrast CT images of the brain\nacquired in the acute setting, and\nsends notifications to a\nneurovascular or neurosurgical\nspecialist that a suspected\nintracranial hemorrhage has been\nidentified and recommends review"]],"caption_candidate":"A table comparing the key features of the subject and predicate device is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p8-t0","doc_id":"K241719","page_num":8,"bbox":[66.5,72.5,516.5,709.5],"n_rows":7,"n_cols":3,"columns":["","previewed through a mobile\napplication.\nNotified clinicians are responsible\nfor viewing high quality images on\na diagnostic viewer per the\nstandard of care and engaging in\nappropriate patient evaluation in\nconjunction with other patient\ninformation before making\ncare-related decisions. NeuroICH\nis limited to analysis of imaging\ndata and should not be used\nin-lieu of full patient evaluation or\nrelied upon to make or confirm\ndiagnosis.","of those images. Images can be\npreviewed through a mobile\napplication.\nImages that are previewed through\nthe mobile application may be\ncompressed and are for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. Notified clinicians are\nresponsible for viewing\nnon-compressed images on a\ndiagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making\ncare-related decisions or requests.\nViz ICH is limited to analysis of\nimaging data and should not be\nused in-lieu of full patient evaluation\nor relied upon to make or confirm\ndiagnosis."],"rows":[["","previewed through a mobile\napplication.\nNotified clinicians are responsible\nfor viewing high quality images on\na diagnostic viewer per the\nstandard of care and engaging in\nappropriate patient evaluation in\nconjunction with other patient\ninformation before making\ncare-related decisions. NeuroICH\nis limited to analysis of imaging\ndata and should not be used\nin-lieu of full patient evaluation or\nrelied upon to make or confirm\ndiagnosis.","of those images. Images can be\npreviewed through a mobile\napplication.\nImages that are previewed through\nthe mobile application may be\ncompressed and are for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. Notified clinicians are\nresponsible for viewing\nnon-compressed images on a\ndiagnostic viewer and engaging in\nappropriate patient evaluation and\nrelevant discussion with a treating\nphysician before making\ncare-related decisions or requests.\nViz ICH is limited to analysis of\nimaging data and should not be\nused in-lieu of full patient evaluation\nor relied upon to make or confirm\ndiagnosis."],["Device\ncomponents","1. Image forwarding module\nconfigured on site machine at\nhospital end for transferring\nDICOM studies.\n2. Image analysis software\nalgorithm hosted on AWS cloud\nmanaged by NEUROCAREAI.\n3. Mobile application software\nmodule for review of notification\nand non-diagnostic images.\n4. Admin panel as web application\nfor registration and management\nof systems, sites and clinicians\naccounts.","1. Image analysis software\nalgorithm hosted on Viz.ai’s\nservers.\n2. Mobile application software\nmodule for review of notification\nand non-diagnostic images."],["Anatomical\nregion of\ninterest","Head","Head"],["Diagnostic\napplication","Notification only","Notification only"],["Intended user","Neurovascular or Neurosurgical\nSpecialist","Neurovascular or Neurosurgical\nSpecialist"],["Data\nacquisition","Acquires medical image data from\nDICOM compliant imaging\ndevices and modalities.","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities."],["Data\nacquisition\nprotocol","Non contrast CT scan of the head","Non contrast CT scan of the head"]],"caption_candidate":"NEUROCAREAIINC. NeuroICH510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p9-t0","doc_id":"K241719","page_num":9,"bbox":[66.5,72.5,516.5,421.5],"n_rows":10,"n_cols":3,"columns":["DICOM\ncompatible","Yes","Yes"],"rows":[["DICOM\ncompatible","Yes","Yes"],["View DICOM\ndata","DICOM Information about the\npatient, study, and current image","DICOM Information about the\npatient, study and current image"],["Segmentation\nof the region\nof interest","No; the device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the\noriginal image.","No; the device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the original\nimage."],["Al used","Yes","Yes"],["Notification","Yes","Yes"],["Preview\nimages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option for all cases."],["Alteration of\noriginal image","No","No"],["Removal of\ncases from\nworklist queue","No","No"],["Abnormalities\ntriaged","ICH","ICH"],["Preview\nimage\ninformation","Preview images returned to the\nMobile application for view.","Preview images returned to the\nMobile application for view."]],"caption_candidate":"NEUROCAREAIINC. NeuroICH510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p10-t0","doc_id":"K241719","page_num":10,"bbox":[90.75,534.37,512.28,706.91],"n_rows":13,"n_cols":3,"columns":["AgeRange(Years)","Sensitivity[95%CI]","Specificity[95%CI]"],"rows":[["AgeRange(Years)","Sensitivity[95%CI]","Specificity[95%CI]"],["","",""],["22to50","94.87%(83.08%-98.43%)","89.86%(80.48%-94.93%)"],["","",""],["50to70","95.83%(86.02%-98.72%)","92.05%(84.46%-96.04%)"],["","",""],["70+","93.75%(83.13%-97.73%)","95.24%(88.39%-98.06%)"],["","",""],["D","evicePerformancebyGender",""],["","",""],["Gender","Sensitivity[95%CI]","Specificity[95%CI]"],["","",""],["Male","93.07%(86.37%-96.55%)","90.91%(84.74%-94.30%)"]],"caption_candidate":"AgeRange(Years) Sensitivity[95%CI] Specificity[95%CI]","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241719-p11-t0","doc_id":"K241719","page_num":11,"bbox":[90.75,79.5,514.51,657.62],"n_rows":39,"n_cols":3,"columns":["Female","100% (90%-99.93%)","96.92%(89.48%-99.05%)"],"rows":[["Female","100% (90%-99.93%)","96.92%(89.48%-99.05%)"],["","",""],["Devic","ePerformancebySliceThickne","ss"],["","",""],["SliceThickness","Sensitivity[95%CI]","Specificity[95%CI]"],["","",""],["2mm≤SliceThickness<3","96.15%(81.03%-99.09%)","98%(89.55%-99.52%)"],["mm","",""],["","",""],["3mm≤SliceThickness≤5","94.50%(88.51%-97.40%)","91.10%(86.20%-94.35%)"],["mm","",""],["","",""],["Dev","icePerformancebyICHSub-TY","pe"],["","",""],["ICHSub-Type","Sensitivity[95%","CI]"],["","",""],["SubduralHemorrhage","91.89%(83.40%","-96.16%)"],["","",""],["IntraparenchymalHemorrhage","98.25%(90.76%","-99.58%)"],["","",""],["SubarachnoidHemorrhage","100%(93.40%-","99.95%)"],["","",""],["IntraventricularHemorrhage","96.43%(82.24%","-99.15%)"],["","",""],["EpiduralHemorrhage","100%(71.51%-","99.77%)"],["","",""],["DeviceP","erformancebyScannerManufa","cturer"],["","",""],["ScannerManufacturer","Sensitivity[95%CI]","Specificity[95%CI]"],["","",""],["GEMedicalSystems","94.44%(81.81%-98.30%)","95.60%(91.57%-97.73%)"],["","",""],["Siemens","94.25%(87.24%-97.46%)","84.62%(72.41%-91.93%0"],["","",""],["Philips","100%(63.06%-99.68%)","100%(29.24%-99.16%)"],["","",""],["SiemensHealthineers","N/A","75%(28.36%-94.73%)"],["","",""],["TOSHIBA","100%(54.07%-99.58%)","0%(1.26%-84.19%)"]],"caption_candidate":"Female 100% (90%-99.93%) 96.92%(89.48%-99.05%)","well_formed":true,"extraction_settings":"text"}
{"table_id":"K241719-p11-t1","doc_id":"K241719","page_num":11,"bbox":[85.5,120.65,538.4,234.5],"n_rows":4,"n_cols":3,"columns":["DevicePerformancebySliceThickness","",""],"rows":[["DevicePerformancebySliceThickness","",""],["SliceThickness","Sensitivity[95%CI]","Specificity[95%CI]"],["2mm≤SliceThickness<3\nmm","96.15%(81.03%-99.09%)","98%(89.55%-99.52%)"],["3mm≤SliceThickness≤5\nmm","94.50%(88.51%-97.40%)","91.10%(86.20%-94.35%)"]],"caption_candidate":"Female 100% (90%-99.93%) 96.92%(89.48%-99.05%)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p11-t2","doc_id":"K241719","page_num":11,"bbox":[85.5,260.67,538.4,420.5],"n_rows":7,"n_cols":2,"columns":["DevicePerformancebyICHSub-TYpe",""],"rows":[["DevicePerformancebyICHSub-TYpe",""],["ICHSub-Type","Sensitivity[95%CI]"],["SubduralHemorrhage","91.89%(83.40%-96.16%)"],["IntraparenchymalHemorrhage","98.25%(90.76%-99.58%)"],["SubarachnoidHemorrhage","100%(93.40%-99.95%)"],["IntraventricularHemorrhage","96.43%(82.24%-99.15%)"],["EpiduralHemorrhage","100%(71.51%-99.77%)"]],"caption_candidate":"mm","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p12-t0","doc_id":"K241719","page_num":12,"bbox":[71.33,72.25,539.33,702.5],"n_rows":17,"n_cols":4,"columns":["DevicePerformancebyCTScannerMake/Model","","",""],"rows":[["DevicePerformancebyCTScannerMake/Model","","",""],["Scanner\nManufactur\ner","ScannerModel","Sensitivity[95%CI]","Specificity[95%CI]"],["GEMedical\nSystems","OptimaCT660","66.67%(19.41%-93.24%)","95.10%(90.24%-97.57%)"],["","RevolutionCT","100%(87.66%-99.91%)","50%(9.43%-90.57%)"],["","RevolutionEVO","83.33%(42.13%-96.33%)","100%(88.43%-99.92%)"],["","DiscoveryRT","N/A","100%(29.24%-99.16%)"],["","Discovery690","N/A","100%(54.07%-99.58%)"],["","LightSpeedPro16","N/A","100%(15.81%-98.74%)"],["Siemens","SOMATOMDrive","100%(29.24%-99.16%)","100%(73.54%-99.79%)"],["","SOMATOM\nPerspective","90%(58.72%-97.72%)","88.89%(55.50%-97.48%)"],["","SOMATOMDefinition\nAS","100%(92.13%-99.94%)","77.78%(44.39%-93.33%)"],["","SOMATOMDefinition\nAS+","100%(82.35%-99.87%)","75%(46.19%-90.91%)"],["","SOMATOMgo.Up","50%(9.43%-90.57%)","100%(39.76%-99.37%)"],["","Perspective","70%(39.03%-89.07%)","80%(35.88%-95.67%)"],["","SOMATOMDefinition\nEdge","100%(15.81%-98.74%)","N/A"],["","SOMATOMgo.Top","N/A","33%(6.76%-80.59%)"],["","BiographHorizon","N/A","100%(15.81%-98.74%0"]],"caption_candidate":"NEUROCAREAIINC. NeuroICH510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p13-t0","doc_id":"K241719","page_num":13,"bbox":[72.0,72.5,539.0,311.5],"n_rows":7,"n_cols":4,"columns":["Philips","Brilliance16","100%(59.04%-99.64%)","100%(29.24%-99.16%)"],"rows":[["Philips","Brilliance16","100%(59.04%-99.64%)","100%(29.24%-99.16%)"],["","IncisiveCT","100%(15.81%-98.74%)","N/A"],["Siemens\nHealthineers","SOMATOMgo.UP","N/A","50%(9.43%-90.57%)"],["","SOMATOMgo.Top","N/A","100%(29.24%-99.16%)"],["TOSHIBA","Aquilion","100%(29.24%-99.16%)","N/A"],["","AquilionONE","100%(29.24%-99.16%)","NA"],["","AquilionPRIME","100%(15.81%-98.74%)","0%(1.26%-84.19%)"]],"caption_candidate":"NEUROCAREAIINC. NeuroICH510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p13-t1","doc_id":"K241719","page_num":13,"bbox":[85.5,347.52,539.0,507.5],"n_rows":5,"n_cols":3,"columns":["DevicePerformancebyICHVolume","",""],"rows":[["DevicePerformancebyICHVolume","",""],["MinimalVolumeThreshold\n(mL)","SensitivityAboveThreshold\n[95%CI]","SensitivityBelow/Equal\nThreshold[95%CI]"],["1","100%(91.96%-99.94%)","92.86%(68.05%-98.34%)"],["5","100%(87.23%-99.91%)","96.77%(83.78%-99.23%)"],["10","100%(83.89%-99.88%)","97.30%(86.19%-99.36%)"]],"caption_candidate":"AquilionPRIME 100%(15.81%-98.74%) 0%(1.26%-84.19%)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p13-t2","doc_id":"K241719","page_num":13,"bbox":[72.0,533.41,539.0,715.5],"n_rows":6,"n_cols":4,"columns":["DevicePerformancebyScannerReconstructionMethod","","",""],"rows":[["DevicePerformancebyScannerReconstructionMethod","","",""],["Scanner\nManufacturer","Reconstruction\nMethod","Sensitivity[95%CI]","Specificity[95%CI]"],["GEMedicalSystems","STANDARD","93.94%(80.32%-98.14%)","95.60%(91.57%-97.73%)"],["","SOFT","100%(39.76%-99.37%)","N/A"],["Siemens","J37f,3","100%(29.24%-99.16%)","100%(73.54%-99.79%)"],["","J30s,2","84%(65.13%-93.45%)","88.24%(65.29%-96.42%)"]],"caption_candidate":"10 100%(83.89%-99.88%) 97.30%(86.19%-99.36%)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p14-t0","doc_id":"K241719","page_num":14,"bbox":[72.06,72.5,539.6,585.5],"n_rows":15,"n_cols":4,"columns":["","H31f","100%(88.06%-99.91%)","66.67%(19.41%-93.24%)"],"rows":[["","H31f","100%(88.06%-99.91%)","66.67%(19.41%-93.24%)"],["","J37f,2","100%(76.84%-99.82%)","50.00%(%18.41%-\n81.59%)"],["","Hr40f,3","50%(9.43%-90.57%)","80.00%(35.88%-95.67%)"],["","Hf38s","100%(15.81%-98.74%)","N/A"],["","H30s","100%(63.06%-99.68%)","100%(63.06%-99.68%)"],["","J37s,2","100%(47.82%-99.49%)","0%(0.84%-70.76%)"],["","Hc40f,2","100%(29.24%-99.16%)","N/A"],["","J30s,1","100%(29.24%-99.16%)","N/A"],["","Hr38s","N/A","100%(15.81%-98.74%)"],["","H30f","100%(15.81%-98.74%)","N/A"],["Philips","U,B","100%(63.06%-99.68%)","100%(29.24%-99.16%)"],["Siemens\nHealthineers","Hr40f,3","N/A","75%(28.36%-94.73%)"],["TOSHIBA","FC68","100%(29.24%-99.16%)","0%(1.26%-84.19%)"],["","FC26","100%(29.24%-99.16%)","N/A"],["","FC23","100%(15.81%-98.74%)","N/A"]],"caption_candidate":"NEUROCAREAIINC. NeuroICH510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241719-p15-t0","doc_id":"K241719","page_num":15,"bbox":[85.5,223.64,538.08,303.5],"n_rows":3,"n_cols":3,"columns":["DevicePerformancebyTime","",""],"rows":[["DevicePerformancebyTime","",""],["Parameter","NeuroICHTimewith\nStandardDeviation","VizICHTimewithStandard\nDeviation"],["TimetoNotification(TTN)","0.37±0.20minutes","0.49±0.08minutes"]],"caption_candidate":"workflow early with notifications from the NeuroICH software.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241725-p5-t0","doc_id":"K241725","page_num":5,"bbox":[127.75,167.82,517.15,448.22],"n_rows":5,"n_cols":2,"columns":["510(k) Owner","Better Diagnostics AI Corp."],"rows":[["510(k) Owner","Better Diagnostics AI Corp."],["Address","29 Alcott Way Avon CT, 06001\nUSA"],["Correspondence person","Raj Zaveri\nQuality and Regulatory Consultant"],["Contact information","Email: rajzaveri10@gmail.com\nPhone: +91 8369438297"],["Date prepared","M arch 23, 2024"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p5-t0","doc_id":"K241727","page_num":5,"bbox":[72.0,453.85,539.56,505.76],"n_rows":4,"n_cols":2,"columns":["",". In addition, the SW architecture"],"rows":[["",". In addition, the SW architecture"],["was changed to separate the image communication platform from the Briefcase-Triage SW. The",""],["subject device consists of only the algorithm analysis module which can be integrated with image",""],["communication platforms that meet the Briefcase-Triage input and output requirements.",""]],"caption_candidate":"algorithm performance, due to training the subject device on a larger data set and additional","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p6-t0","doc_id":"K241727","page_num":6,"bbox":[72.37,135.37,556.87,713.62],"n_rows":2,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],"rows":[["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],["Intended Use /\nIndications for\nUse","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nCTPA images in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage\nby flagging and communication of\nsuspected positive findings of\nPulmonary Embolism (PE)\npathologies.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected PE findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for","Briefcase-Triage is a radiological\ncomputer- aided triage and notification\nsoftware indicated for use in the analysis\nof CTPA images, in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communicating suspected\npositive cases of Pulmonary Embolism\n(PE) pathologies.\nBriefcase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected findings\nin parallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases with\nsuspected findings. Notifications include\ncompressed preview images that are\nmeant for informational purposes only,\nand not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of Briefcase-Triage are\nintended to be used in conjunction with\nother patient information and based on\ntheir professional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p7-t0","doc_id":"K241727","page_num":7,"bbox":[72.37,72.37,556.87,717.37],"n_rows":9,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],"rows":[["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],["","viewing full images per the standard of\ncare.",""],["User\npopulation","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of\ninterest","Chest","Chest"],["Data\nacquisition\nprotocol","CTPA","CTPA"],["Notification-onl\ny (/notification\nalerts), parallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion criteria\n● CTPA protocols.\n● Single Energy or Dual Energy\nexams\n● Performed on CT scanners with\n64 or greater number of detectors\n● Scans performed on\nadults/transitional adults ≥ 18\nyears of age\n● Slice thickness; 0.5 mm to 3.0 mm\naxial slices","Inclusion criteria\n● CTPA protocols.\n● Single Energy or Dual Energy exams\n● Performed on CT scanners with 64\nor greater number of detectors\n● Scans performed on\nadults/transitional adults ≥ 18 years\nof age\n● Slice thickness; 0.5 mm to 3.0 mm\naxial slices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p7-t1","doc_id":"K241727","page_num":7,"bbox":[78.0,553.51,136.94,607.24],"n_rows":4,"n_cols":2,"columns":["","for"],"rows":[["","for"],["clinical",""],["performance",""],["testing",""]],"caption_candidate":"Exclusion ● CTPA protocols. ● CTPA protocols.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p8-t0","doc_id":"K241727","page_num":8,"bbox":[72.37,72.37,556.87,377.62],"n_rows":4,"n_cols":3,"columns":["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],"rows":[["","Predicate Device\nAidoc Briefcase-Triage for PE\n(K222277)","Subject Device\nAidoc Briefcase-Triage for PE"],["","Exclusion Criteria\n● All studies that are technically\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, sub-optimal bolus timing\nor an inadequate field of view.","Exclusion Criteria\n● All studies that are technically\ninadequate, including studies with\nmotion artifacts, severe metal\nartifacts, sub-optimal bolus timing\nor an inadequate field of view."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for\nworkflow integration\n(Feed/Worklist (alternate names)\nand non-diagnostic Image\nViewer).","- Integrated with image routing module via\nimage communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and\nnon-diagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p9-t0","doc_id":"K241727","page_num":9,"bbox":[72.09,349.72,515.93,553.72],"n_rows":3,"n_cols":7,"columns":["Time -to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],"rows":[["Time -to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],["Predicate K222277\nProcessing Time","78.0","499","73.6","82.3","64.5","53.2"],["Briefcase-Triage +\nImage\nCommunication\nPlatform\nTime-To-Notification","26.42","499","25.3","27.54","23.81","14.74"]],"caption_candidate":"Table 2. Time-to- notification comparison for Briefcase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p10-t0","doc_id":"K241727","page_num":10,"bbox":[130.62,99.19,481.62,161.44],"n_rows":2,"n_cols":7,"columns":["","Mean","Std","Min","Median","Max","N"],"rows":[["","Mean","Std","Min","Median","Max","N"],["Age\n(Years)","62.1","17.3","18","64","90","499"]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p10-t1","doc_id":"K241727","page_num":10,"bbox":[164.32,186.26,447.06,323.4],"n_rows":6,"n_cols":7,"columns":["Ground Truth\nResults","Gender","","","","All",""],"rows":[["Ground Truth\nResults","Gender","","","","All",""],["","Female","","Male","","",""],["","N","%","N","%","N","%"],["Positive","100","20.0%","113","22.6%","213","42.6%"],["Negative","154","30.8%","127","25.4%","281","56.2%"],["All","254","50.8%","240","48.0%","494","98.8%"]],"caption_candidate":"Table 4. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241727-p10-t2","doc_id":"K241727","page_num":10,"bbox":[208.62,393.48,402.87,563.73],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["SIEMENS","201","40.3%"],["GE","100","20.0%"],["Canon","99","19.8%"],["Philips","99","19.8%"],["Total","499","100%"]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p6-t0","doc_id":"K241770","page_num":6,"bbox":[72.07,511.86,539.57,739.3],"n_rows":4,"n_cols":7,"columns":["","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)"],"rows":[["","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)"],["","TransparaTM","","","ProstatIDTM","",""],["","K181704","","","K212783","",""],["The ScreenPoint Transpara™\nsystem is intended for use as a\nconcurrent reading aid for\nphysicians interpreting screening\nmammograms, to identify\nregions suspicious for breast\ncancer and assess their\nlikelihood of malignancy.\nOutput of the device includes\nmarks placed on suspicious soft\ntissue lesions and suspicious\ncalcifications; region-based\nscores, displayed upon the\nphysician’s query, indicating the","","","ProstatlD™ is a radiological\ncomputer assisted detection\n(CADe) and diagnostic (CADx)\nsoftware device for use in a\nhealthcare facility or hospital to\nassist trained radiologists in the\ndetection, assessment and\ncharacterization of prostate\nabnormalities, including cancer\nlesions using MR image data","","","Prostate MR AI is a plug-in\nRadiological Computer Assisted\nDetection and Diagnosis\nSoftware device intended to be\nused\n• with a separate hosting\napplication\n• as a concurrent reading aid\nto assist radiologists in the\ninterpretation of a prostate\nMRI examination acquired"]],"caption_candidate":"Indications for Use Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p8-t0","doc_id":"K241770","page_num":8,"bbox":[22.51,570.34,594.07,730.18],"n_rows":8,"n_cols":11,"columns":["Attribute","","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis",""],"rows":[["Attribute","","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis",""],["","","","TransparaTM","","","ProstatIDTM","","","",""],["","","","K181704","","","K212783","","","",""],["","General Information","","","","","","","","",""],["Regulation\nnumber","","§ 892.2090 Radiological\nComputer Assisted Detection\nand Diagnosis Software","","","§ 892.2090 Radiological\nComputer Assisted Detection and\nDiagnosis Software","","","§ 892.2090 Radiological\nComputer Assisted Detection\nand Diagnosis Software","Identical",""],["Classification","","Class II","","","Class II","","","Class II","Identical",""],["Product Code","","QDQ","","","QDQ","","","QDQ","Identical",""],["","Clinical Characteristics","","","","","","","","",""]],"caption_candidate":"THE PREDICATE DEVICES","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p9-t0","doc_id":"K241770","page_num":9,"bbox":[22.46,78.94,594.1,691.54],"n_rows":9,"n_cols":9,"columns":["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],"rows":[["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],["","","TransparaTM","","","ProstatIDTM","","",""],["","","K181704","","","K212783","","",""],["Intended Use\n(short)","A concurrent reading aid for\nphysicians interpreting\nscreening FFDM acquired with\ncompatible mammography\nsystems, to identify findings and\nassess their level of suspicion.","","","A concurrent reading aid for\nphysicians interpreting prostate\nMRI exams of patients presented\nfor high-risk screening or\ndiagnostic imaging, to identify\nregions suspicious for prostate\ncancer and assess their likelihood\nof malignancy.","","","A concurrent reading aid for\nphysicians interpreting prostate\nMRI examinations acquired\naccording to the PI-RADS\nstandard, to identify findings and\nassess their level of suspicion.","Equivalent –\nJustified in\nSection V."],["Intended\npatient\npopulation","Women undergoing screening\nmammography","","","Population of biological males\nwith a prostate gland undergoing\nscreening or clinical MRI exams.\nThis includes biological males of\nall ages with clinical indicators\nsuggestive of possible prostate\ncancer or with family history of\nprostate cancer.","","","Adult men (40 years and older)\nwith suspected prostate cancer\nundergoing prostate MRI\nwithout prior treatment of the\nprostate gland (treatment-naïve).","Equivalent –\nImages\ncaptured from\ndifferent\npatient\npopulations\nare\nstandardized\nto be\nprocessible by\nCAD devices."],["Anatomical\nregion of\ninterest","Breast","","","Prostate gland","","","Prostate gland","Equivalent –\nImages\ncaptured from\ndifferent\nanatomical\nregions are\nstandardized\nto be\nprocessible by\nCAD devices."],["Intended\nUsers","physicians qualified to read\nscreening mammograms","","","Physicians qualified to read and\ninterpret prostate MRI exams\nconsistent with ACR\nrecommendations in the context\nof PI-RADS v2","","","Radiologists qualified to read\nprostate MRI","Equivalent –\n– Users are\nqualified to\nread radiology\nimages using\nCAD devices"],["Mode of\naction","Software that applies algorithms\nfor recognition of suspicious\ncalcifications and soft tissue\nlesions to detect and\ncharacterize findings in\nradiological breast images and\nprovide information about the\npresence, location, and\ncharacteristics of the findings to\nthe user.","","","Software that applies algorithms\nfor recognition of suspicious\ntissue regions in Prostate MR\nimages to provide information\nabout the presence, location, and\nlevel of suspicion of the findings.","","","Software that applies algorithms\nfor recognition of suspicious\ntissue regions in Prostate MR\nimages to provide information\nabout the presence, location, and\nlevel of suspicion of the\nfindings.","Equivalent –\nBoth predicate\nand subject\ndevices use\nalgorithms to\ndetect findings\nand provide\ndiagnosis."],["Medthod of\nUse","Concurrent","","","Concurrent","","","Concurrent","Identical"]],"caption_candidate":"Prostate MR AI (VA10A) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p10-t0","doc_id":"K241770","page_num":10,"bbox":[22.48,78.94,594.1,648.22],"n_rows":11,"n_cols":11,"columns":["Attribute","","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis",""],"rows":[["Attribute","","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis",""],["","","","TransparaTM","","","ProstatIDTM","","","",""],["","","","K181704","","","K212783","","","",""],["Visualization\nFeatures","","Computer aided detection\n(CAD) marks to highlight\nlocations where the device\ndetected suspicious\ncalcifications or soft tissue\nlesions. Decision support is\nprovided by region scores on a\nscale ranging from 0-100, with\nhigher scores indicating a higher\nlevel of suspicion.","","","ProstatID does not include a\nstandalone graphical user\ninterface. Rather, ProstatID\noutputs are in DICOM format and\nmay be viewed on DICOM-\ncompliant image viewers.","","","Prostate MR AI does not include\na standalone graphical user\ninterface. Rather, it is a plug-in\ndevice that is intended to be used\nwith a separate hosting\napplication that allows the user\nto view the original case, as well\nas confirm, reject, edit, or add\nlesions, their contours and\nScores.","Equivalent –\nThe difference\nbetween\npredicate and\nsubject\ndevices is\njustified by\nusing the\nreference\ndevice which\nalso does not\nhave UI while\nit retains the\nsame level of\nsafety and\neffectiveness.",""],["","Technical Characteristics","","","","","","","","",""],["Design","","Software only device","","","Software only device","","","Software only device","Identical",""],["Automatic\nSegmentation","","Yes","","","Yes","","","Yes","Identical",""],["Algorithm","","Artificial intelligence algorithm\ntrained with large datasets of\nbiopsy proven examples of\nbreast cancer, benign lesions\nand normal tissue.","","","Neural network trained on a\ndatabase of reference normal\ntissues and abnormalities with\nknown ground truth.","","","Artificial intelligence algorithm\ntrained on a database of prostate\nMR image series acquired\naccording to the PI-RADS\nstandard (non-contrast T2W and\nDWI image series), and\ncorresponding radiological\nand/or biopsy findings.","Identical – all\ntrained AI\nalgorithms",""],["Alteration\noriginal\nimage","","No","","","No","","","No","Identical",""],["Data\nacquisition\nprotocol","","Screening mammograms","","","Prostate MRI image series","","","Prostate MRI image series\nacquired according to the PI-\nRADS standard","Equivalent –\nAcquired\nimages are\nqualified for\nCAD device\nprocessing",""],["Input","","Medical images provided in a\nDICOM format","","","Medical images provided in a\nDICOM format","","","Medical images provided in a\nDICOM format","Equivalent –\nDevices all\nuse\nstandardized\nimage types.",""]],"caption_candidate":"Prostate MR AI (VA10A) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p11-t0","doc_id":"K241770","page_num":11,"bbox":[22.51,78.94,594.07,504.07],"n_rows":4,"n_cols":9,"columns":["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],"rows":[["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],["","","TransparaTM","","","ProstatIDTM","","",""],["","","K181704","","","K212783","","",""],["Output","• Marks placed on suspicious\nsoft tissue lesions and\nsuspicious calcifications\n• Region-based scores\nindicating the likelihood that\ncancer is present\n• Overall score indicating the\nlikelihoood that cancer is\npresent on the mammogram","","","• Marks locations suspicious\nof lesions\n• Provides region scores with\nhigher scores indicating a\nhigher level of suspicion\n• Provides single exam score\nthat synthesizes features","","","• Automatically segments the\ncontours of the prostate gland\n• Automatically segments the\nparts of the prostate that belong\nto the periheral zone (PZ) and\nthat do not belong to the\nperipheral zone (non-PZ),\nrespectively\n• Calculation of a “Suspicion\nMap” that indicates lesions\nsuspicious for cancer\n• For each detected lesion:\no Lesion contours\no Rating of severity (“Score”)\non a scale from 3 to 5 (in\nsteps of 1). Score is\ngenerated by an algorithm\ntrained on the correlation of\nprostate MRI with PI-RADS\nscores provided by\nradiologists and results of\nlesion-targeted biopsy.\no A “Level of Suspicion”\n(LoS) on a scale from 60 to\n100 (in steps of 1) as a fine\ngranular measure of the\nalgorithm's suspicion for the\npresence of a significant\nlesion, based on training on\nPI-RADS scores provided by\nradiologists and results of\nlesion-targeted biopsy","Equivalent –\nas far as the\ndifferent\nbody regions\nallow. PZ vs.\nnon-PZ is\nprostate\nspecific and\nis relevant for\nPI-RADS\nevaluation.\nInstead of\nmarks for\nsuspicious\nlocations in\nthe image, the\nsubject\ndevice\nprovides\nlesion\ncontours and\na “suspicion\nmap”."]],"caption_candidate":"Prostate MR AI (VA10A) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p12-t0","doc_id":"K241770","page_num":12,"bbox":[22.49,78.94,594.09,553.39],"n_rows":5,"n_cols":9,"columns":["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],"rows":[["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],["","","TransparaTM","","","ProstatIDTM","","",""],["","","K181704","","","K212783","","",""],["Score","Finding level:\nContinuous score 1-100\nindicating the level of suspicion\nof malignancy (from low\nsuspicion to high suspicion).\nBreast level:\nNone\nExam level:\n10-point scale score indicative\nof higher frequency of cancer\npositive","","","Finding level:\nScores on a continuous scale\nfrom 0 to 1 that accompany the\noverlay markings of suspicious\nlocations\nCase level:\nSuggested level of suspicion\n(LoS) or overall PI-RADS exam\nscore","","","Finding level:\nRating of severity (“Score”) on a\nscale from 3 to 5 (in steps of 1).\nThe Score is generated by an\nalgorithm trained on the\ncorrelation of prostate MRI with\nPI-RADS scores provided by\nradiologists and results of lesion-\ntargeted biopsy\nA “Level of Suspicion” (LoS) on\na scale from 60 to 100 (in steps\nof 1) as a more granular measure\nof the algorithm's suspicion for\nthe presence of a significant\nlesion, based on training on PI-\nRADS scores provided by\nradiologists and results of lesion-\ntargeted biopsy\nProstate level (= Exam Level):\nLoS derived from Finding Level\nresults as maximum LoS over all\nfindings (on a scale of 60-100 in\nsteps of 1), or (in the absence of\nfindings) as maximum of\ninternal Suspicion Map over\nprostate segmentation (on a scale\nof 1-59 in steps of 1)","Equivalent –\nThe\ndifferences\nbetween\npredicate and\nsubject\ndevices can be\njustified by\nusing the\nreference\ndevice which\napply\ncontinuous\nfinding scale\nand share the\nsame PI-\nRADS LoS\nexam score."],["Finding\ndiscovery","Findings are by-default\ndisplayed when score is equal or\nhigher than 5.\nUpon user request for findings\nof score equal or less than 4.","","","Findings are added to post-\nprocessed T2W image in DICOM\nformat as a colorized translucent\noverlay to highlight locations, as\noverlay scores on a continuous\nscale from 0 to 1, and as a\nsuggested LoS or overall PI-\nRADS exam score.","","","Upon activation of the plug-in,\nfindings are displayed in the\nhosting workflow as\nsegmentations on the T2W\nimage series with corresponding\nratings by Scores (value range:\n3-5), and as an overall exam\nScore.","Equivalent –\nFinding\nresults of both\npredicate and\nsubject\ndevices can be\ndisplayed."]],"caption_candidate":"Prostate MR AI (VA10A) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241770-p13-t0","doc_id":"K241770","page_num":13,"bbox":[22.51,78.94,594.07,683.86],"n_rows":4,"n_cols":9,"columns":["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],"rows":[["Attribute","","Predicate Device","","","Reference Device","","Subject Device\nProstate MR AI (VA10A)","Equivalency\nAnalysis"],["","","TransparaTM","","","ProstatIDTM","","",""],["","","K181704","","","K212783","","",""],["Performance","Reader study with 6720 reads:\n• fully crossed multi-reader,\nmulti-case design\n• 240 cases\n• 14 radiologists\nCase-level ROC:\n• radiologists’ AUC unaided =\n0.866\n• radiologists’ AUC aided =\n0.886\n• mean difference: +0.020,\n95% C.I. [0.010, 0.030]","","","Reader study with 2700 reads:\n• 150 cases were read by 9\ntrained physicians in two\nseparate reads – first without\nProstatID, and second with\nProstatID.\nCase-level ROC for discriminating\nGleason Score ≥ 7 in those 130 out\nof the 150 cases that had biopsy\nresults:\n• radiologists’ AUC unaided =\n0.629\n• radiologists’ AUC unaided =\n0.671\n• mean difference: +0.042,\n95% C.I. [0.005, 0.080]\nLesion-level wAFROC:\n• radiologists’ AUC unaided =\n0.387\n• radiologists’ AUC aided =\n0.430\n• mean difference: +0.043,\n95% C.I. [0.003, 0.083]","","","Reader study with 4080 reads:\n• split-plot multi-reader, multi-\ncase design\n(comprising 2 fully crossed\nmulti-reader, multi-case splits)\n• 2× 170 = 340 cases from 2\nconsecutively acquired cohorts\n• 2× 6 = 12 radiologists\n• Two analysis scenarios:\na) all cases, all readers\nb) only cases with biopsy, or a\nnegative MRI and ≥12\nmonths negative follow-up\nby PSA or MRI (exclusion\nof 34 cases), and only case-\nreader pairs in which\nreaders were not involved\nin prostate MRI reading at\nthe institution providing the\ncase during the time of data\ncollection (exclusion of\n459 case-reader pairs)\nCase-level ROC for\ndiscriminating Gleason Score ≥ 6:\n• radiologists’ AUC (unaided) =\na) 0.676; b) 0.658\n• radiologists’ AUC (aided) =\na) 0.701; b) 0.695\n• mean difference:\na) +0.025,\n95% C.I. [0.001, 0.049]\nb) +0.037,\n95% C.I. [0.011, 0.063]\nLesion-level wAFROC:\n• radiologists’ AUC unaided =\na) 0.734; b) 0.772\n• radiologists’ AUC aided =\na) 0.769; b) 0.834\n• mean difference:\na) +0.035,\n95% C.I. [0.002, 0.068]\nb) +0.030,\n95% C.I. [0.008, 0.052]","Equivalent –\nThe difference\nbetween the\npredicate and\nsubject\ndevices can be\njustified by\ncomparing\nwith the\nperformance\nof the\nreference\ndevice. Reader\nstudies of both\nreference and\nsubject\ndevices used\nsimilar\nstatistically\nmeaningful\ncase numbers,\nqualified\nreaders,\nacceptance\ncriteria and\nyielded\ncomparable\nstudy results."]],"caption_candidate":"Prostate MR AI (VA10A) Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p6-t0","doc_id":"K241831","page_num":6,"bbox":[70.5,104.5,523.5,208.5],"n_rows":7,"n_cols":2,"columns":["Devicetradename","Transpara2.1.0"],"rows":[["Devicetradename","Transpara2.1.0"],["Device","RadiologicalComputerAssistedDetectionandDiagnosis\nSoftware"],["Classificationregulation","21CFR892.2090"],["Panel","Radiology"],["Deviceclass","II"],["Productcode","QDQ"],["Submissiontype","Traditional510(k)"]],"caption_candidate":"2. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p6-t1","doc_id":"K241831","page_num":6,"bbox":[70.5,290.5,523.5,407.5],"n_rows":8,"n_cols":2,"columns":["Devicetradename","Transpara1.7.2"],"rows":[["Devicetradename","Transpara1.7.2"],["LegalManufacturer","ScreenPointMedicalB.V."],["Device","RadiologicalComputerAssistedDetectionandDiagnosis\nSoftware"],["Classificationregulation","21CFR892.2090"],["Panel","Radiology"],["Deviceclass","II"],["Productcode","QDQ"],["Clearancenumber","K221347"]],"caption_candidate":"3. Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p8-t0","doc_id":"K241831","page_num":8,"bbox":[70.67,514.64,540.43,707.5],"n_rows":6,"n_cols":4,"columns":["StandardID","Year/\nEdition","StandardTitle","FDA\nRecognition#"],"rows":[["StandardID","Year/\nEdition","StandardTitle","FDA\nRecognition#"],["IEC62366-1","Edition1.1\n2020-06","Medicaldevices-Part1:Applicationofusability\nengineeringtomedicaldevices","5-129"],["ISO20417","Firstedition\n2021-04\nCorrected\nversion\n2021-12","Medicaldevices–Informationtobesuppliedbythe\nmanufacturer","5-135"],["ISO14971","Third\nEdition\n2019-12","MedicalDevices-ApplicationOfRiskManagementTo\nMedicalDevices","5-125"],["IEC62304","Edition1.1\n2015-06","MedicalDeviceSoftware-SoftwareLifeCycle\nProcesses","13-79"],["IEC82304-1","Edition1.0\n2016-10","Healthsoftware-Part1:Generalrequirementsfor\nproductsafety","13-97"]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p9-t0","doc_id":"K241831","page_num":9,"bbox":[70.62,132.66,540.45,538.5],"n_rows":17,"n_cols":3,"columns":["ID","Year","Title"],"rows":[["ID","Year","Title"],["FDA-1997-D-\n0029","2002","GeneralPrinciplesofSoftwareValidation"],["FDA-2011-D-\n0652","2014","The510(k)Program:EvaluatingSubstantialEquivalencein\nPremarketNotifications[510(k)]"],["FDA-2015-D-\n5105","2016","PostmarketManagementofCybersecurityinMedicalDevices"],["FDA-2011-D-\n0469","2016","ApplyingHumanFactorsandUsabilityEngineeringtoMedical\nDevices"],["FDA-2015-D-\n4852","2017","DesignConsiderationsandPre-marketSubmission\nRecommendationsforInteroperableMedicalDevices"],["FDA-2014-D-\n0456","2018","AppropriateUseofVoluntaryConsensusStandardsinPremarket\nSubmissionsforMedicalDevices"],["FDA-2018-D-\n1329","2019","RecommendedContentandFormatofNon-ClinicalBenchPerformance\nTestingInformationinPremarketSubmissions"],["FDA-2016-D-\n1853","2021","UniqueDeviceIdentificationSystem:FormandContentofthe\nUniqueDeviceIdentifier(UDI)"],["FDA-2009-D-\n0593","2022","Computer-AssistedDetectionDevicesAppliedtoRadiologyImagesand\nRadiologyDeviceData-PremarketNotification[510(k)]Submissions"],["FDA-2009-D-\n0503","2022","ClinicalPerformanceAssessment:Considerationsfor\nComputer-AssistedDetectionDevicesAppliedtoRadiologyImagesand\nRadiologyDeviceDatainPremarketNotification(510(k))Submissions"],["FDA-2019-D-\n1470","2022","TechnicalPerformanceAssessmentofQuantitativeImagingin\nRadiologicalDevicePremarketSubmissions"],["FDA\n2021-D-1158","2023","CybersecurityinMedicalDevices:QualitySystemConsiderationsand\nContentofPremarketSubmissions"],["FDA-2021-D-\n0775","2023","ContentofPremarketSubmissionsforDeviceSoftwareFunctions"],["FDA-2019-D-\n3598","2023","Off-The-ShelfSoftwareUseinMedicalDevices"],["FDA-2023-D-\n1030","2023","CybersecurityinMedicalDevices:RefusetoAcceptPolicyforCyber\nDevicesandRelatedSystemsUnderSection524BoftheFD&CAct"],["FDA-2021-D-\n0872","2023","ElectronicSubmissionTemplateforMedicalDevice510(k)Submissions"]],"caption_candidate":"The following guidance documents were used to support this submission:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p10-t0","doc_id":"K241831","page_num":10,"bbox":[70.67,412.67,340.3,473.5],"n_rows":4,"n_cols":5,"columns":["","NumberofExams","Normal","Benign","Cancer"],"rows":[["","NumberofExams","Normal","Benign","Cancer"],["FFD\nM","5.730","4,830","150","750"],["DBT","4,477","3,757","120","600"],["Total","10,207","8,587","270","1,350"]],"caption_candidate":"Table1:Datausedforevaluationofstand-aloneperformance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p10-t1","doc_id":"K241831","page_num":10,"bbox":[70.67,609.51,503.55,672.5],"n_rows":3,"n_cols":5,"columns":["","Sensitivityfor\nSensitiveMode\n(70%specificity)","Sensitivityfor\nSpecificMode\n(80%specificity)","Sensitivityfor\nElevatedRisk\n(97%specificity)","Exam-basedAUC"],"rows":[["","Sensitivityfor\nSensitiveMode\n(70%specificity)","Sensitivityfor\nSpecificMode\n(80%specificity)","Sensitivityfor\nElevatedRisk\n(97%specificity)","Exam-basedAUC"],["FFDM","97.4%(96.3-98.5)","95.2%(93.7-96.7)","80.8%(78.0-83.6)","0.960(0.953-0.966)"],["DBT","96.9%(95.5-98.3)","95.1%(93.3-96.8)","78.4%(75.1-81.7)","0.955(0.947-0.963)"]],"caption_candidate":"Table2:Resultsoverallstand-aloneperformanceTranspara–SensitivityandAreaundertheROCCurve(AUC)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p11-t0","doc_id":"K241831","page_num":11,"bbox":[70.67,149.79,540.43,477.5],"n_rows":23,"n_cols":5,"columns":["TestDescription","Subgroup","TotalNumberofExams\n(FFDM/DBTpooled)","Non-can\ncer","Cancer"],"rows":[["TestDescription","Subgroup","TotalNumberofExams\n(FFDM/DBTpooled)","Non-can\ncer","Cancer"],["Ethnicity","WhiteNon-Hispanic","529","728","89"],["","WhiteHispanic","324","255","69"],["","Black","351","253","37"],["","Turkish","189","149","27"],["","Asian","601","544","57"],["","Other","360","203","108"],["AgeGroups","Above50yearsold","13024","11523","1498"],["","Below50yearsold","2845","2637","208"],["LesionSize","Mass<20mm","705","0","705"],["","Mass20-50mm","573","0","573"],["","Mass>50mm","120","0","120"],["RadiologicalLesion\nSubtypes","Mass","917","0","917"],["","CalcificationGroups","541","0","541"],["","Architectural\nDistortion","663","0","663"],["","Asymmetries","52","0","52"],["HistologySubtypes","ILC","129","0","129"],["","IDC","432","0","432"],["","DCIS","183","0","183"],["Screeningvs\nDiagnostic(DBT)","Screening","824","679","145"],["","Diagnostic","3,931","3,454","477"],["BreastDensity","LowDensity(BIRADS\nA+B)","5,154","4,582","572"],["","HighDensity\n(BIRADSC+D)","4,982","4,263","719"]],"caption_candidate":"any deviations in specific sub-groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p11-t1","doc_id":"K241831","page_num":11,"bbox":[70.67,587.63,340.3,650.5],"n_rows":4,"n_cols":5,"columns":["","NumberofExams","Normal","Benign","Cancer"],"rows":[["","NumberofExams","Normal","Benign","Cancer"],["FFD\nM","4,266","3,742","53","471"],["DBT","1,458","1,256","30","172"],["Total","5,724","4,998","83","643"]],"caption_candidate":"overview is presented in table 4.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p12-t0","doc_id":"K241831","page_num":12,"bbox":[70.67,108.46,540.42,253.5],"n_rows":6,"n_cols":5,"columns":["","Sensitivityfor\nSensitiveMode\n(70%specificity)","Sensitivityfor\nSpecificMode\n(80%specificity)","Sensitivityfor\nElevatedRisk\n(97%specificity)","Exam-basedAUC"],"rows":[["","Sensitivityfor\nSensitiveMode\n(70%specificity)","Sensitivityfor\nSpecificMode\n(80%specificity)","Sensitivityfor\nElevatedRisk\n(97%specificity)","Exam-basedAUC"],["FFDMwithout\nTA","95.7%(93.7-\n97.6)","94.5%(92.3-\n96.7)","78.9%(75.0-\n82.8)","0.954(0.941-\n0.965)"],["FFDMwithTA","95.7%(93.7-\n97.6)","95.4%(93.4-\n97.4)","82.7%(79.1-\n86.4)","0.958(0.946-\n0.969)"],["","","","",""],["DBTwithoutTA","94.6%(91.2-\n98.0)","91.0%(86.7-\n95.4)","67.1%(59.9-\n74.2)","0.935(0.915-\n0.953)"],["DBTwithTA","94.6%(91.2-\n98.0)","91.0%(86.7-\n95.4)","74.9%(68.3-\n81.4)","0.941(0.921-\n0.958)"]],"caption_candidate":"are demonstrated in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p12-t1","doc_id":"K241831","page_num":12,"bbox":[70.67,349.82,540.42,567.5],"n_rows":14,"n_cols":5,"columns":["TestDescription","Subgroup","Total Number of Exams\n(FFDM/DBTpooled)","Non-can\ncer","Cancer"],"rows":[["TestDescription","Subgroup","Total Number of Exams\n(FFDM/DBTpooled)","Non-can\ncer","Cancer"],["PriorTimeIntervals","0.9-1.5years","3,152","2,731","421"],["","1.5-6years","2,489","2,267","222"],["AgeGroups","Under50yearsold","909","876","33"],["","Between50-65\nyearsold","2,796","2,532","264"],["","Above65yearsold","1,375","1,173","202"],["SinglevsMulti-prior","Singleprior","1,526","1,306","220"],["","Multipriors","1,526","1,306","220"],["BreastDensity","LowDensity\n(BIRADSA+B)","2,915","2,573","342"],["","HighDensity\n(BIRADSC+D)","2,728","2,425","303"],["ModalityofPriorTypefor\nDBTcurrent","FFDM","533","519","14"],["","Synthetic","927","761","166"],["ManufacturerType","SingleManufacturer","3,213","2,852","361"],["","CrossManufacturer","1,053","943","110"]],"caption_candidate":"show any deviations in specific sub-groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p13-t0","doc_id":"K241831","page_num":13,"bbox":[70.67,170.52,336.4,221.5],"n_rows":3,"n_cols":3,"columns":["","Standalone",""],"rows":[["","Standalone",""],["","FFDM","DBT"],["Compatible\nmanufacturers","Hologic,GE,Philips,\nSiemens,andFujifilm","Hologic,Siemens,GE\nandFujifilm"]],"caption_candidate":"Table7CompatibleManufacturersforstandaloneimageprocessing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241831-p13-t1","doc_id":"K241831","page_num":13,"bbox":[70.67,310.38,327.43,375.5],"n_rows":5,"n_cols":2,"columns":["Current","Prior"],"rows":[["Current","Prior"],["SiemensFFDM","HologicFFDM,SiemensFFDM"],["GEFFDM","HologicFFDM,GEFFDM"],["HologicFFDM","HologicFFDM,SiemensFFDM,GEFFDM"],["HologicDBT+SM","HologicDBT+SM,HologicFFDM"]],"caption_candidate":"Table8CompatibleManufacturerfortemporalcomparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p6-t0","doc_id":"K241837","page_num":6,"bbox":[85.28,313.18,554.53,731.5],"n_rows":4,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["Classification\nRegulation","892.2050–Medicalimage\nmanagementandprocessing\nsystem","892.2050–Medicalimage\nmanagementandprocessing\nsystem","Same"],["ProductCode","QKB","LLZ","Similar;Both\nproductcodes\nrefertothe\nsameCFR\n892.2050-\nMedicalimage\nmanagement\nand\nprocessing\nsystem"],["Indicationsfor\nUse","LimbusContourisasoftwareonly\nmedicaldeviceintended foruse\nbytrainedradiation oncologists,\ndosimetristsand physiciststo\nderiveoptimal contoursforinput\ntoradiation treatmentplanning.\nSupportedimagemodalities are\nComputedTomography and\nMagneticResonance.The Limbus\nContourSoftware assistsinthe\nfollowing\nscenarios:\n•Operatesinconjunctionwith\nradiationtreatmentplanning\nsystemsorDICOMviewing\nsystemstoload,save,and display\nmedicalimagesand contoursfor\ntreatment\nevaluationandtreatmentplanning.\n•Creation,transformation,and\nmodificationofcontoursfor","LimbusContourisasoftwareonly\nmedicaldeviceintended foruse\nbytrainedradiation oncologists,\ndosimetristsand physiciststo\nderiveoptimal contoursforinputto\nradiation treatmentplanning.\nSupportedimagemodalities are\nComputedTomography and\nMagneticResonance.The Limbus\nContourSoftware assistsinthe\nfollowing\nscenarios:\n•Operatesinconjunctionwith\nradiationtreatmentplanning\nsystemsorDICOMviewing\nsystemstoload,save,and display\nmedicalimagesand contoursfor\ntreatment\nevaluationandtreatmentplanning.\n•Creation,transformation,and\nmodificationofcontoursfor","Same"]],"caption_candidate":"automatic contouring test to ensure the contours were accurate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p7-t0","doc_id":"K241837","page_num":7,"bbox":[85.35,72.1,554.52,728.5],"n_rows":10,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["","applicationsincluding,butnot\nlimitedto:transferringcontoursto\nradiotherapytreatmentplanning\nsystems, aidingadaptivetherapy\nand archivingcontoursforpatient\nfollow-up.\n•Localizationanddefinitionof\nhealthyanatomicalStructures.\nLimbusContourisnot\nintendedforusewithdigital\nmammography.","applicationsincluding,butnot\nlimitedto:transferringcontoursto\nradiotherapytreatmentplanning\nsystems, aidingadaptivetherapy\nand archivingcontoursforpatient\nfollow-up.\n•Localizationanddefinitionof\nhealthyanatomicalStructures.\nLimbusContourisnot\nintendedforusewithdigital\nmammography.",""],["IntendedUser","Healthcareproviders","Healthcareproviders","Same"],["Machine\nLearning\nAlgorithm","Lockedalgorithm;DeepLearning\nmodel","Lockedalgorithm;DeepLearning\nmodel","Same"],["Contouring\nModes","Automatic","Automatic","Same"],["Supported\nImage\nModalities","CT;MR","CT;MR","Same"],["Compatible\nScannerModels","NoLimitationonscannermodel,\nDICOM3.0compliancerequired.","NoLimitationonscannermodel,\nDICOMcompliancerequired.","Same"],["Compatible\nTreatment\nPlanning\nSystem","NoLimitationonTPSmodel","NoLimitationonTPSmodel","Same"],["Result\nVisualization","LimbusContourhasnodata\nvisualization.Dataprocessingis\nautomatedanddoesnotrequireuser\ninteraction.Acontrolinterfaceis\nprovidedforsystemadministration\nandconfigurationonly.\nVisualizationsoftwaremustbeused\ntofacilitatethereviewandeditofthe\ngeneratedcontours.","LimbusContourhasnodata\nvisualization.Dataprocessingis\nautomatedanddoesnotrequireuser\ninteraction.Acontrolinterfaceis\nprovidedforsystemadministration\nandconfigurationonly.\nVisualizationsoftwaremustbeused\ntofacilitatethereviewandeditofthe\ngeneratedcontours.","Same"],["Structures\nAvailablefor\nContouring","CTStructures\n● A_Aorta\n● A_Aorta_l\n● A_Celiac\n● A_LAD\n● A_Mesenteric_S\n● A_Pulmonary\n● Bag_Bowel\n● Bag_Bowel_Extend\n● Bag_Bowel_Full\n● Bag_Bowel_S\n● Bladder\n● Body\n● Bone_Hyoid","CTStructures\n● A_Aorta\n● A_Aorta_Base\n● A_Aorta_I\n● A_Celiac\n● A_LAD\n● A_Mesenteric_S\n● A_Pulmonary\n● Atrium_L\n● Atrium_R\n● Bowel_Bag\n● Bowel_Bag_Extend\n● Bowel_Bag_Full\n● Bowel_Bag_Superior","Similar;The\nsubjectdevice\naddsnew\nstructuresfor\nexisting\nsupported\nimage\nmodalities\n(CT/MR)"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p8-t0","doc_id":"K241837","page_num":8,"bbox":[85.35,72.1,554.52,725.5],"n_rows":2,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["","● Bone_Ilium_L\n● Bone_Ilium_R\n● Bone_Ilium\n● Bone_Mandible\n● Bowel\n● Bowel_Extend\n● Bowel_Full\n● Bowel_S\n● BrachialPlex_L\n● BrachialPlex_R\n● BrachialPlexs\n● Brain\n● Brainstem\n● Breast_L\n● Breast_R\n● Breasts\n● Bronchus\n● Canal_Anal\n● CaudaEquina\n● Cavity_Oral\n● Chestwall_L\n● Chestwall_R\n● Chestwalls\n● Clavicle_L\n● Clavicle_R\n● Cochlea_L\n● Cochlea_R\n● Colon_Sigmoid\n● Cornea_L\n● Cornea_R\n● Duodenum\n● Esophagus\n● Eye_L\n● Eye_R\n● Eyes\n● Femur_Head_L\n● Femur_Head_R\n● Femur_Heads\n● Gallbladder\n● Glnd_Lacrimal_L\n● Glnd_Lacrimal_R\n● Glnd_Submand_L\n● Glnd_Submand_R\n● Glnd_Thyroid\n● GreatVes\n● Heart\n● Hippocampus_L\n● Hippocampus_R\n● Humerus_L\n● Humerus_R\n● Kidney_L\n● Kidney_R\n● Kidneys\n● Larynx\n● Lens_L\n● Lens_R\n● Lips\n● Liver\n● LN_Ax_Sclav_L","● Bowel\n● Bowel_Extend\n● Bowel_Full\n● Bowel_Superior\n● Bladder\n● Body\n● Body+Mask\n● Bone_Hyoid\n● Bone_Ilium_L\n● Bone_Ilium_R\n● Bone_Ilium\n● Bone_Ischium_L\n● Bone_Ischium_R\n● Bone_Mandible\n● Bone_Pelvic\n● BoneMarrow_Pelvic\n● BrachialPlex_L\n● BrachialPlex_R\n● BrachialPlexs\n● Brain\n● Brainstem\n● Breast_Implant_L\n● Breast_Implant_R\n● Breast_L\n● Breast_R\n● Breasts\n● Bronchus\n● Canal_Anal\n● Carina\n● CaudaEquina\n● Cavity_Oral\n● Cerebellum\n● Chestwall_L\n● Chestwall_R\n● Chestwall\n● Clavicle_L\n● Clavicle_R\n● Cochlea_L\n● Cochlea_R\n● Colon_Sigmoid\n● Cornea_L\n● Cornea_R\n● Duodenum\n● Esophagus\n● Eye_L\n● Eye_R\n● Eyes\n● Femur_Head_L\n● Femur_Head_R\n● Femur_Heads\n● Gallbladder\n● Glnd_Lacrimal_L\n● Glnd_Lacrimal_R\n● Glnd_Submand_L\n● Glnd_Submand_R\n● Glnd_Thyroid\n● GreatVes\n● Heart\n● Heart+A_Pulm",""]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p9-t0","doc_id":"K241837","page_num":9,"bbox":[85.35,72.1,554.52,725.5],"n_rows":2,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["","● LN_Ax_Sclav_R\n● LN_Ax_L1_L\n● LN_Ax_L1_R\n● LN_Ax_L2_L\n● LN_Ax_L2_R\n● LN_Ax_L3_L\n● LN_Ax_L3_R\n● LN_Sclav_L\n● LN_Sclav_R\n● LN_IMN_L\n● LN_IMN_R\n● LN_Neck_L\n● LN_Neck_R\n● LN_Neck_234_L\n● LN_Neck_234_R\n● LN_Neck_2347AB_L\n● LN_Neck_2347AB_R\n● LN_Neck_IA\n● LN_Neck_IA6\n● LN_Neck_IB_L\n● LN_Neck_IB_R\n● LN_Neck_II_L\n● LN_Neck_II_R\n● LN_Neck_III_L\n● LN_Neck_III_R\n● LN_Neck_IV_L\n● LN_Neck_IV_R\n● LN_Neck_V_L\n● LN_Neck_V_R\n● LN_Neck_VI\n● LN_Neck_VIIAB_L\n● LN_Neck_VIIAB_R\n● LN_Pelvis\n● Lung_L\n● Lung_R\n● Lungs\n● Musc_Constrict\n● Musc_PecMinor_L\n● Musc_PecMinor_R\n● Musc_Sclmast_L\n● Musc_Sclmast_R\n● OpticChiasm\n● OpticNrv_L\n● OpticNrv_R\n● Pancreas\n● Parotid_L\n● Parotid_R\n● PelvisVessels\n● PenileBulb\n● Pituitary\n● Prostate\n● Prostate+SeminalVes\n● PubicSymphys\n● Rectum\n● Retina_L\n● Retina_R\n● Ribs_L\n● Ribs_R\n● Ribs","● Hippocampus_L\n● Hippocampus_R\n● Humerus_L\n● Humerus_R\n● InternalAuditoryCanal_L\n● InternalAuditoryCanal_R\n● Kidney_L\n● Kidney_R\n● Kidneys\n● Larynx\n● Lens_L\n● Lens_R\n● Lips\n● Liver\n● Lung_L\n● Lung_R\n● Lungs\n● Mesorectum\n● Musc_Constrict\n● Musc_PecMinor_L\n● Musc_PecMinor_R\n● Musc_Sclmast_L\n● Musc_Sclmast_R\n● Optics\n● OpticChiasm\n● OpticNrv_L\n● OpticNrv_R\n● Pancreas\n● Parotid_L\n● Parotid_R\n● PelvisVessels\n● PenileBulb\n● Pericardium\n● Pericardium+A_Pulm\n● Pituitary\n● Prostate\n● Prostate+SeminalVes\n● ProstateBed\n● PubicSymphys\n● Rectum\n● Retina_L\n● Retina_R\n● Ribs_L\n● Ribs_R\n● Ribs\n● Sacrum\n● SeminalVes\n● Skin\n● SpinalCanal\n● SpinalCord\n● Spleen\n● Sternum\n● Stomach\n● Trachea\n● Uterus+Cervix\n● V_Venacava_I\n● V_Venacava_S\n● Vagina\n● VB_C1",""]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p10-t0","doc_id":"K241837","page_num":10,"bbox":[85.35,72.1,554.52,725.5],"n_rows":2,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["","● Sacrum\n● SeminalVes\n● Skin\n● SpinalCanal\n● SpinalCord\n● Spleen\n● Sternum\n● Stomach\n● Trachea\n● Uterus_Cervix\n● V_Venacava_I\n● V_Venacava_S\n● Vagina\n● Ventricle_L\nMRStructures\n● Brainstem\n● Cornea_L\n● Cornea_R\n● Eye_L\n● Eye_R\n● Hippocampus_L\n● Hippocampus_R\n● Optics\n● PenileBulb\n● Prostate\n● Retina_L\n● Retina_R\n● SeminalVes","● VB_C2\n● VB_C3\n● VB_C4\n● VB_C5\n● VB_C6\n● VB_C7\n● VB_L1\n● VB_L2\n● VB_L3\n● VB_L4\n● VB_L5\n● VB_T01\n● VB_T02\n● VB_T03\n● VB_T04\n● VB_T05\n● VB_T06\n● VB_T07\n● VB_T08\n● VB_T09\n● VB_T10\n● VB_T11\n● VB_T12\n● VBs\n● Ventricle_L\n● Ventricle_R\n● Bladder_HDR\n● Bowel_HDR\n● Canal_Anal_HDR\n● Colon_Sigmoid_HDR\n● Rectum_HDR\n● Urethra_HDR\n● Bladder_CBCT\n● Femur_Head_L_CBCT\n● Femur_Head_R_CBCT\n● LN_Pelvics_CBCT\n● Prostate_CBCT\n● Rectum_CBCT\n● SeminalVes_CBCT\nMRStructures\n● Bladder\n● Brainstem\n● Cornea_L\n● Cornea_R\n● Eye_L\n● Eye_R\n● Femur_Head_L\n● Femur_Head_R\n● Hippocampus_L\n● Hippocampus_R\n● Optics\n● PenileBulb\n● PubicSymphys\n● Prostate\n● Rectum\n● Retina_L\n● Retina_R\n● Sacrum",""]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p12-t0","doc_id":"K241837","page_num":12,"bbox":[85.35,72.1,554.52,716.5],"n_rows":3,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["","mostoftheanatomicalstructures\nexamined,theDiceScores(DSC)\nbetweenLimbusContourandexpert\ncontourswerenotsignificantly\ndifferentfromtheinter-observer\nexpertvariabilitybaselines.\nTheinvestigationbyWong,Huang,\nWellsetal.,2021evaluated\nimplementationofLimbusContour\nprospectivelyattwoCanadian\ninstitutions.LimbusContourwas\nusedtogenerateOARandCTVsfor\nallpatientsundergoingRTfora\ncentralnervoussystem(CNS),head\nandneck(H&N),orprostatecancer.\nAutomaticcontoursweregenerated\nonapproximately551eligiblecases.\n203surveyswerecollectedon27\nCNS,54H&N,and93prostateRT\nplans,resultinginanoverallsurvey\ncompliancerateof32%.The\nmajorityofOARautomaticcontours\nrequiredminimaleditssubjectively\n(meaneditingscore ≤ 2)and\nobjectively(meanDSCand95%HD\nwas ≥ 0.90and ≤ 2.0mm,\nrespectively).\nOverall,thousandsoftotalstructures\nwereanalyzedacrossall\ninvestigationscoveringallsupported\nanatomicalsitestoprovidea\nsubstantialsampleofdeviceoutputs\ntodrawconclusionsthatanatomical\nstructurecontouroutputsoffergood\ngeometricalignmentwithexpert\ncontours,requireminimalediting,\nandsignificantlyreducethetime\nneededforcontouring.","oftheanatomicalstructures\nexamined,theDiceScores(DSC)\nbetweenLimbusContourandexpert\ncontourswerenotsignificantly\ndifferentfromtheinter-observer\nexpertvariabilitybaselines.\nTheinvestigationbyWong,Huang,\nWellsetal.,2021evaluated\nimplementationofLimbusContour\nprospectivelyattwoCanadian\ninstitutions.LimbusContourwas\nusedtogenerateOARandCTVsfor\nallpatientsundergoingRTfora\ncentralnervoussystem(CNS),head\nandneck(H&N),orprostatecancer.\nAutomaticcontoursweregenerated\nonapproximately551eligiblecases.\n203surveyswerecollectedon27\nCNS,54H&N,and93prostateRT\nplans,resultinginanoverallsurvey\ncompliancerateof32%.Themajority\nofOARautomaticcontoursrequired\nminimaleditssubjectively(mean\neditingscore ≤ 2)andobjectively\n(meanDSCand95%HDwas ≥ 0.90\nand ≤ 2.0mm,respectively).\nOverall,thousandsoftotalstructures\nwereanalyzedacrossall\ninvestigationscoveringallsupported\nanatomicalsitestoprovidea\nsubstantialsampleofdeviceoutputs\ntodrawconclusionsthatanatomical\nstructurecontouroutputsoffergood\ngeometricalignmentwithexpert\ncontours,requireminimalediting,\nandsignificantlyreducethetime\nneededforcontouring.",""],["Computer\nPlatform&\nOperating\nSystem","OperatingSystem •Windows10/\nWindows Server2016andAbove\nHardwareRequirements •2GHzor\nfastermulticore processor •8GBof\nRAM •ForGPUversions,a CUDA\ncapableNVIDIA GPUisrequired","OperatingSystem •Windows10/\nWindows Server2016andAbove\nHardwareRequirements •2GHzor\nfastermulticore processor •16GB\nofRAM •ForGPUversions,a\nCUDAcapableNVIDIA GPUis\nrequired","Similar;\nLimbus\nContourv1.8.0\nrequires16GB\nofRAM\ninsteadof8\nGBtosupport\nadded\nstructuresfor\nautomatic\ncontouring"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p13-t0","doc_id":"K241837","page_num":13,"bbox":[85.35,72.1,554.52,241.5],"n_rows":4,"n_cols":4,"columns":["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],"rows":[["Item","LimbusContourv1.8","LimbusContourv1.7-K230575","Similarities/\nDifferences"],["Cloud-based\ndeployment","No","No","Same"],["Locally\ndeployed(or\ninstalled)","Yes","Yes","Same"],["DataTransfer","ExportedLimbusContourDICOM\nRT-StructureSetfilesareimported\nintotheTreatmentPlanningSystem\norDICOMViewerthrough\ninteractionswiththeFileSystem","ExportedLimbusContourDICOM\nRT-StructureSetfilesareimported\nintotheTreatmentPlanningSystem\norDICOMViewerthrough\ninteractionswiththeFileSystem","Same"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p14-t0","doc_id":"K241837","page_num":14,"bbox":[85.5,475.5,555.5,728.5],"n_rows":15,"n_cols":5,"columns":["Structure","Modality","Bodysite","Numberoftrainingscans","Numberofvalidationscans"],"rows":[["Structure","Modality","Bodysite","Numberoftrainingscans","Numberofvalidationscans"],["Canal_Anal","CT","Pelvis","1084","50"],["Canal_Anal(Female)","CT","Pelvis","383","43"],["Canal_Anal_HDR","CT","Pelvis","466","49"],["Canal_Anal_HDR","MRI","Pelvis","304","34"],["A_Aorta","CT","Thorax","715","50"],["A_Aorta_Base","CT","Thorax","331","37"],["A_Aorta_I","CT","Abdomen","352","40"],["Applicator_Cylinder(beta)","CT","Pelvis","217","24"],["Applicator_Ring(beta)","CT","Pelvis","163","19"],["Bladder","CT","Pelvis","1105","50"],["Bladder_CBCT","CT","Pelvis","356","39"],["Bladder(Female)","CT","Pelvis","378","43"],["Bladder_HDR","CT","Pelvis","712","49"],["Bladder_HDR","MRI","Pelvis","303","34"]],"caption_candidate":"training.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p15-t0","doc_id":"K241837","page_num":15,"bbox":[85.5,72.5,555.5,721.5],"n_rows":39,"n_cols":5,"columns":["Bowel","CT","Pelvis","697","50"],"rows":[["Bowel","CT","Pelvis","697","50"],["Bowel_Extend","CT","Pelvis","697","50"],["Bowel_Extend(Female)","CT","Pelvis","697","50"],["Bowel(Female)","CT","Pelvis","697","50"],["Bowel_Full","CT","Pelvis","697","50"],["Bowel_Full(Female)","CT","Pelvis","697","50"],["Bowel_HDR","CT","Pelvis","682","50"],["Bowel_HDR","MRI","Pelvis","305","36"],["Bowel_Superior","CT","Abdomen","453","50"],["Bladder","MRI","Pelvis","579","50"],["Bowel_Bag","CT","Pelvis","697","50"],["Bowel_Bag_Extend","CT","Pelvis","697","50"],["Bowel_Bag_Extend(Female)","CT","Pelvis","697","50"],["Bowel_Bag(Female)","CT","Pelvis","697","50"],["Bowel_Bag_Full","CT","Pelvis","697","50"],["Bowel_Bag_Full(Female)","CT","Pelvis","697","50"],["Bowel_Bag_Superior","CT","Abdomen","453","50"],["Brain","CT","HeadNeck","452","47"],["Brainstem","CT","HeadNeck","614","50"],["Brainstem","MRI","HeadNeck","241","27"],["Breasts","CT","Thorax","660","50"],["Breast_L","CT","Thorax","660","50"],["Wire_Breast_L(beta)","CT","Thorax","660","50"],["Breast_R","CT","Thorax","660","50"],["Wire_Breast_R(beta)","CT","Thorax","660","50"],["LN_Ax_Sclav_L","CT","Thorax","343","39"],["LN_Ax_Sclav_R","CT","Thorax","343","39"],["LN_Ax_L1_L","CT","Thorax","343","39"],["LN_Ax_L1_R","CT","Thorax","343","39"],["LN_Ax_L2_L","CT","Thorax","343","39"],["LN_Ax_L2_R","CT","Thorax","343","39"],["LN_Ax_L3_L","CT","Thorax","343","39"],["LN_Ax_L3_R","CT","Thorax","343","39"],["LN_Sclav_L","CT","Thorax","343","39"],["LN_Sclav_R","CT","Thorax","343","39"],["A_Celiac","CT","Thorax","435","44"],["Carina","CT","Thorax","865","50"],["CaudaEquina","CT","Pelvis","663","50"],["Cerebellum","CT","HeadNeck","135","16"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p16-t0","doc_id":"K241837","page_num":16,"bbox":[85.5,72.5,555.5,732.5],"n_rows":40,"n_cols":5,"columns":["Chestwall","CT","Thorax","223","25"],"rows":[["Chestwall","CT","Thorax","223","25"],["Chestwall_L","CT","Thorax","223","25"],["CW2cm_L","CT","Thorax","223","25"],["Chestwall_R","CT","Thorax","223","25"],["CW2cm_R","CT","Thorax","223","25"],["OpticChiasm","CT","HeadNeck","1254","140"],["Clavicle_L","CT","HeadNeck","104","12"],["Clavicle_R","CT","HeadNeck","104","12"],["Cochlea_L","CT","HeadNeck","248","29"],["Cochlea_R","CT","HeadNeck","248","29"],["Musc_Constrict","CT","HeadNeck","186","21"],["Cornea_L","CT","HeadNeck","729","50"],["Cornea_L","MRI","HeadNeck","199","23"],["Cornea_R","CT","HeadNeck","729","50"],["Cornea_R","MRI","HeadNeck","199","23"],["Bone_Ilium","CT","Pelvis","214","24"],["Bone_Ilium_L","CT","Pelvis","214","24"],["Bone_Ilium_R","CT","Pelvis","214","24"],["LN_Neck_L","CT","HeadNeck","374","42"],["LN_Neck_R","CT","HeadNeck","374","42"],["LN_Neck_IA","CT","HeadNeck","112","13"],["LN_Neck_IA6","CT","HeadNeck","112","13"],["LN_Neck_VI","CT","HeadNeck","112","13"],["LN_Neck_234_L","CT","HeadNeck","672","50"],["LN_Neck_234_R","CT","HeadNeck","672","50"],["LN_Neck_2347AB_L","CT","HeadNeck","672","50"],["LN_Neck_2347AB_R","CT","HeadNeck","672","50"],["LN_Neck_IB_L","CT","HeadNeck","672","50"],["LN_Neck_IB_R","CT","HeadNeck","672","50"],["LN_Neck_II_L","CT","HeadNeck","672","50"],["LN_Neck_II_R","CT","HeadNeck","672","50"],["LN_Neck_III_L","CT","HeadNeck","672","50"],["LN_Neck_III_R","CT","HeadNeck","672","50"],["LN_Neck_IV_L","CT","HeadNeck","672","50"],["LN_Neck_IV_R","CT","HeadNeck","672","50"],["LN_Neck_V_L","CT","HeadNeck","672","50"],["LN_Neck_V_R","CT","HeadNeck","672","50"],["LN_Neck_VIIA_L","CT","HeadNeck","672","50"],["LN_Neck_VIIA_R","CT","HeadNeck","672","50"],["LN_Neck_VIIAB_L","CT","HeadNeck","672","50"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241837-p17-t0","doc_id":"K241837","page_num":17,"bbox":[85.5,72.5,555.5,723.5],"n_rows":38,"n_cols":5,"columns":["LN_Neck_VIIAB_R","CT","HeadNeck","672","50"],"rows":[["LN_Neck_VIIAB_R","CT","HeadNeck","672","50"],["LN_Neck_VIIB_L","CT","HeadNeck","672","50"],["LN_Neck_VIIB_R","CT","HeadNeck","672","50"],["Mesorectum","CT","Pelvis","302","33"],["Duodenum","CT","Abdomen","382","37"],["Esophagus","CT","Thorax","1643","50"],["ESTRO_LN_IMN_L","CT","Thorax","409","45"],["ESTRO_LN_IMN_R","CT","Thorax","409","45"],["ESTRO_LN_IMN_L_Expand","CT","Thorax","409","45"],["ESTRO_LN_IMN_R_Expand","CT","Thorax","409","45"],["ESTRO_LN_Ax_IP_L","CT","Thorax","395","44"],["ESTRO_LN_Ax_IP_R","CT","Thorax","395","44"],["ESTRO_LN_Ax_L1_L","CT","Thorax","395","44"],["ESTRO_LN_Ax_L1_R","CT","Thorax","395","44"],["ESTRO_LN_Ax_L2+IP_Fill_L","CT","Thorax","395","44"],["ESTRO_LN_Ax_L2+IP_Fill_R","CT","Thorax","395","44"],["ESTRO_LN_Ax_L2_L","CT","Thorax","404","45"],["ESTRO_LN_Ax_L2_R","CT","Thorax","404","45"],["ESTRO_LN_Ax_L3_L","CT","Thorax","404","45"],["ESTRO_LN_Ax_L3_R","CT","Thorax","404","45"],["ESTRO_LN_Sclav_L","CT","Thorax","409","45"],["ESTRO_LN_Sclav_R","CT","Thorax","409","45"],["Eyes","CT","HeadNeck","729","50"],["Femur_Heads","CT","Pelvis","511","50"],["Femur_Head_L","CT","Pelvis","511","50"],["Femur_Head_L_CBCT","CT","Pelvis","139","17"],["Femur_Head_L","MRI","Pelvis","67","8"],["Femur_Head_R","CT","Pelvis","511","50"],["Femur_Head_R_CBCT","CT","Pelvis","139","17"],["Femur_Head_R","MRI","Pelvis","67","8"],["Gallbladder","CT","Abdomen","539","50"],["Eye_L","CT","HeadNeck","729","50"],["Eye_L","MRI","HeadNeck","199","23"],["Eye_R","CT","HeadNeck","729","50"],["Eye_R","MRI","HeadNeck","199","23"],["GreatVes","CT","Thorax","715","50"],["Heart","CT","Thorax","1000","50"],["Heart+A_Pulm","CT","Thorax","33","4"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K241837-p25-t0","doc_id":"K241837","page_num":25,"bbox":[85.35,72.06,555.31,725.37],"n_rows":36,"n_cols":7,"columns":["Structure","Limbus\nMeanDSC","Limbus\nDSCStd\nDev","Number\nofScans","LimbusDSC\nlower95%conf\nedge","TestDSC\nThreshold","Result"],"rows":[["Structure","Limbus\nMeanDSC","Limbus\nDSCStd\nDev","Number\nofScans","LimbusDSC\nlower95%conf\nedge","TestDSC\nThreshold","Result"],["Colon_Sigmoid_HDR","0.753036","0.15966944","10","0.6388233","0.47","Passed"],["Cornea_L","0.96183182","0.06990272","11","0.91415686","0.489","Passed"],["Cornea_L","0.913718","0.03513108","10","0.88858848","0.489","Passed"],["Cornea_R","0.96934727","0.05299966","11","0.93320051","0.498","Passed"],["Cornea_R","0.927223","0.02302511","10","0.91075297","0.498","Passed"],["Duodenum","0.828433","0.18461132","10","0.69637919","0.649","Passed"],["ESTRO_LN_Ax_IP_L","0.984552","0.0225043","10","0.96845451","0.79","Passed"],["ESTRO_LN_Ax_IP_R","0.988801","0.01830441","10","0.97570773","0.796","Passed"],["ESTRO_LN_Ax_L1_L","0.997122","0.00681545","10","0.99224686","0.66","Passed"],["ESTRO_LN_Ax_L1_R","0.967503","0.01693458","10","0.95538957","0.66","Passed"],["ESTRO_LN_Ax_L2+IP_Fill_L","0.992986","0.01314147","10","0.98358582","0.73","Passed"],["ESTRO_LN_Ax_L2+IP_Fill_\nR","0.994206","0.01093726","10","0.9863825","0.73","Passed"],["ESTRO_LN_Ax_L2_L","0.995192","0.01077199","10","0.98748672","0.73","Passed"],["ESTRO_LN_Ax_L2_R","0.997352","0.00448639","10","0.99414286","0.73","Passed"],["ESTRO_LN_Ax_L3_L","0.993382","0.00884358","10","0.98705612","0.51","Passed"],["ESTRO_LN_Ax_L3_R","0.992149","0.01468854","10","0.98164218","0.51","Passed"],["ESTRO_LN_IMN_L","0.980597","0.02745317","10","0.96095955","0.39","Passed"],["ESTRO_LN_IMN_L_Expand","0.982079","0.05662552","10","0.94157436","0.39","Passed"],["ESTRO_LN_IMN_R","0.974402","0.04214952","10","0.94425214","0.39","Passed"],["ESTRO_LN_IMN_R_Expand","0.977852","0.06968747","10","0.92800405","0.39","Passed"],["ESTRO_LN_Sclav_L","0.97586","0.03136266","10","0.95342606","0.7","Passed"],["ESTRO_LN_Sclav_R","0.98735","0.02268151","10","0.97112575","0.7","Passed"],["Esophagus","0.83741083","0.02651585","12","0.82009643","0.67","Passed"],["Eye_L","0.93511824","0.03324782","17","0.91687796","0.894","Passed"],["Eye_L","0.950337","0.01463563","10","0.93986803","0.847","Passed"],["Eye_R","0.94191706","0.03257919","17","0.92404361","0.902","Passed"],["Eye_R","0.939666","0.03581356","10","0.9140483","0.849","Passed"],["Femur_Head_L","0.961299","0.00888921","10","0.95494049","0.93","Passed"],["Femur_Head_L","0.938162","0.04781144","10","0.90396214","0.77","Passed"],["Femur_Head_L_CBCT","0.977939","0.01378171","10","0.96808085","0.88","Passed"],["Femur_Head_R","0.961381","0.01105991","10","0.95346976","0.937","Passed"],["Femur_Head_R","0.948586","0.02852155","10","0.92818433","0.77","Passed"],["Femur_Head_R_CBCT","0.989667","0.01081208","10","0.98193304","0.88","Passed"],["Gallbladder","0.946422","0.05882969","10","0.9043407","0.809","Passed"],["Glnd_Lacrimal_L","0.76574538","0.0785035","13","0.71649497","0.489","Passed"]],"caption_candidate":"LimbusAI LimbusContour510(k)Submission","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K241891-p5-t0","doc_id":"K241891","page_num":5,"bbox":[72.29,579.0,517.45,609.18],"n_rows":2,"n_cols":9,"columns":["","510(k) Number","","","Device/Manufacturer","","","Predicate/Reference",""],"rows":[["","510(k) Number","","","Device/Manufacturer","","","Predicate/Reference",""],["DEN220040","","","Fibresolve / Imvaria, Inc","","","Predicate","",""]],"caption_candidate":"ScreenDx is substantially equivalent to the following predicate:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K241891-p13-t0","doc_id":"K241891","page_num":13,"bbox":[72.48,78.6,464.76,380.94],"n_rows":12,"n_cols":4,"columns":["CT Scan Technical Characteristics","","",""],"rows":[["CT Scan Technical Characteristics","","",""],["","","Full Dataset",""],["","","%","n"],["CT Manufacturer","Siemens","46.8","1413"],["-","Philips","13.7","414"],["-","GE","26.0","785"],["-","Toshiba","7.1","214"],["-","Other*","0.2","6"],["Slice Thickness (mm)","≤1.5","32.9","995"],["-",">1.5, <3","48.3","1459"],["-","3-4","8.5","258"],["-","5","10.1","305"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p14-t0","doc_id":"K241891","page_num":14,"bbox":[72.48,195.84,540.48,422.7],"n_rows":9,"n_cols":2,"columns":["Pivotal Study Performance",""],"rows":[["Pivotal Study Performance",""],["-","Performance"],["Sensitivity","91.4% [CI: 89.0-93.3%]"],["Specificity","95.2% [CI: 94.3-96.1%]"],["LR+","19.1 [CI: 18.3-20.0]"],["LR-","0.091 [CI: 0.085-0.098]"],["OR","210.7 [CI: 152.0-291.9]"],["PPV","85.1% [CI: 82.3-87.6%]"],["","97.4% [CI: 96.6-98.0%]"]],"caption_candidate":"observed to be 91.4% (89.0 - 93.3%) and specificity was observed to be 95.2% (CI: 94.3 - 96.1%).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p15-t0","doc_id":"K241891","page_num":15,"bbox":[72.71,122.58,539.29,309.48],"n_rows":5,"n_cols":5,"columns":["Device performance in smoking cohorts","","","",""],"rows":[["Device performance in smoking cohorts","","","",""],["Group","n","Disease\nPrevalence","Sensitivity","Specificity"],["Positive smoking\nhistory","1811","23.3%","91.9% [CI: 89.0-\n94.4%]","94.2% [CI: 92.8-\n95.3%]"],["Negative smoking\nhistory","262","57.3%","87.3% [CI: 80.9-\n92.2%]","91.1% [CI: 84.2-\n95.6%]"],["Unknown smoking\nhistory","945","12.9%","94.3 [CI: 88.9-\n97.7%]","97.6% [CI: 96.3-\n98.5%]"]],"caption_candidate":"diseases. Results were analyzed within smoking subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p15-t1","doc_id":"K241891","page_num":15,"bbox":[72.71,325.47,539.29,490.42],"n_rows":6,"n_cols":5,"columns":["Device Performance by CT Slice Thickness","","","",""],"rows":[["Device Performance by CT Slice Thickness","","","",""],["Group","N","Disease\nPrevalence","Sensitivity","Specificity"],["<=1.5 mm","995","56.8%","94.7% [CI: 92.5-\n96.4%]","86.7% [CI: 83.4-\n90.0%]"],[">1.5, <3 mm","1459","2.7%","90.% [CI: 76.3-\n97.2%]","97.7% [CI: 96.7-\n98.4%]"],["3-4 mm","258","7.0%","72.2% [CI: 46.5-\n90.3%]","95.0% [CI: 91.4-\n97.4%]"],["5 mm","305","22.6%","70.0% [CI: 57.3-\n80.1%]","95.8% [CI: 92.3-\n97.9%]"]],"caption_candidate":"history 97.7%] 98.5%]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p15-t2","doc_id":"K241891","page_num":15,"bbox":[72.71,506.73,539.29,641.92],"n_rows":5,"n_cols":5,"columns":["Device Performance by CT Type","","","",""],"rows":[["Device Performance by CT Type","","","",""],["Group","N","Disease\nPrevalence","Sensitivity","Specificity"],["HRCT","854","37.6%","84.7% [CI: 80.3-\n88.4%]","87.8% [CI: 84.7-\n90.5%]"],["LDCT","999","1.0%","60.0% [CI: 26.2-\n87.8%]","96.8% [CI: 95.5-\n97.8%]"],["Routine CT","1165","31.2%","98.1% [CI: 96.1-\n99.2%]","98.3% [CI: 97.1-\n99.0%]"]],"caption_candidate":"80.1%] 97.9%]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p16-t0","doc_id":"K241891","page_num":16,"bbox":[72.48,195.84,323.7,554.94],"n_rows":14,"n_cols":2,"columns":["Additional Validation Study Performance",""],"rows":[["Additional Validation Study Performance",""],["Study Results",""],["","(n=2482)"],["Age (years)","Q1: 49, Q3: 63"],["Sex (% Female)","50%"],["CT Scanner Manufacturer",""],["GE","870 (35%)"],["Siemens","1486 (60%)"],["Philips","126 (5%)"],["Disease Presence/Absence",""],["Positive","39 (1.6%)"],["Negative","2443 (98.4%)"],["Device Sensitivity","87% [CI: 85.8-88.5%]"],["Device Specificity","98% [CI: 97.5-98.5%]"]],"caption_candidate":"the study were assessed to determine whether the device was able to identify positive cases.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241891-p18-t0","doc_id":"K241891","page_num":18,"bbox":[72.48,78.6,539.52,710.52],"n_rows":3,"n_cols":4,"columns":["Modification","Rationale","Testing Methods","Impact Assessment"],"rows":[["Modification","Rationale","Testing Methods","Impact Assessment"],["Update model\narchitecture or\ntraining data","With additional real-\nworld data and\nongoing assessments\nof real-world\nperformance of the\nmodel, re-training a\nnew model allows for\npotential\nimprovements in\ngeneralizability which\nprovides greater\nclinical value.","Substantial\nequivalence as\ncompared to the\nprior version.\nStatistical\nassessments\nfollowing same\nstandards used in\noriginal device\nclearance.","Revised\ngeneralizability or\naccuracy metrics for\nthe system.\nBenefit-Risk Analysis:\nBenefit: Enhanced\nperformance;\ngeneralizability.\nRisk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."],["Updated model\nthreshold selection","With additional real-\nworld data and\nongoing assessments\nof real-world\nperformance of the\nmodel, a change in\noptimized threshold\ntargeting may\nprovide a better\nbalance of sensitivity\nand specificity for the\nappropriate\npopulations.","Substantial\nequivalence as\ncompared to the\nprior version.\nStatistical\nassessments\nfollowing same\nstandards used in\noriginal device\nclearance.","Revised relative\nperformance of\nsensitivity,\nspecificity, PPV, and\nNPV for real-world\nuse.\nBenefit-Risk Analysis:\nBenefit: Enhanced\nperformance;\ngeneralizability.\nRisk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241922-p6-t0","doc_id":"K241922","page_num":6,"bbox":[72.32,185.23,756.55,519.45],"n_rows":4,"n_cols":10,"columns":["-","","Subject Device","","","Primary Device","","","Reference Device",""],"rows":[["-","","Subject Device","","","Primary Device","","","Reference Device",""],["","","Myomics","","","Myomics Q (K211432)","","","cvi42 Auto (K213998)",""],["","","Manufactured by Phantomics","","","Manufactured by Phantomics","","","Manufactured by Circle",""],["Indication\nfor use","Myomics is intended to be used for viewing, post-\nprocessing, qualitative and quantitative evaluation\nof cardiovascular magnetic resonance (MR)\nimages in a Digital Imaging and Communications\nin Medicine (DICOM) standard format.\nIt enables a set of tools to assist physicians in\nqualitative assessment of cardiac images and\nquantitative measurements of the heart and\nadjacent vessels; and to view the presence or\nabsence of physician-identified lesion in blood\nvessels.\nThe target population for manual workflows of\nMyomics is not restricted; however, semi-\nautomated machine learning algorithms of\nMyomics are intended for an adult population.\nThe software comprises various analysis modules,\nincluding AI-powered algorithms, for a\ncomprehensive evaluation of MR images.\nMyomics is used for cardiac images acquired\nfrom a 3.0 T MR scanner.","","","Myomics Q is intended to be used for viewing,\npost-processing and analysis of cardiac magnetic\nresonance (MR) images in a Digital Imaging and\nCommunications in Medicine (DICOM) Standard\nformat. It enables:\n- Importing cardiac MR images in DICOM format.\n- Supporting clinical diagnostics by analysis of\ncardiac MR images using display functionality such\nas panning, windowing, zooming through\nseries/slices of the images.\n- Supporting clinical diagnostics analysis of the\nheart in cardiac MR images and signal intensity.\n- Software package is designed to support the\nphysician-to-physician compliance assessment,\ndocument and follow up heart disease by cardiac\nMRI.\nIt shall be used by qualified medical professionals,\nexperienced in examining and evaluating\ncardiovascular MR images, for the purpose of\nobtaining diagnostic information as part of a\ncomprehensive diagnostic decision-making process.\nThis device is a software application that can be\nused as a stand-alone product or in a network\nenvironment.","","","cvi42 Auto is intended to be used for\nviewing, post-processing, qualitative and\nquantitative evaluation of cardiovascular\nmagnetic resonance (MR) and computed\ntomography (CT) images in a Digital Imaging\nand Communications in Medicine (DICOM)\nStandard format.\nIt enables a set of tools to assist physicians in\nqualitative assessment of cardiac images and\nquantitative measurements of the heart and\nadjacent vessels; perform calcium scoring;\nand to confirm the presence or absence of\nphysician-identified lesion in blood vessels.\nThe target population for cvi42 Auto’s\nmanual workflows is not restricted; however,\ncvi42 Auto’s semi-automated machine\nlearning algorithms are intended for an adult\npopulation.\ncvi42 Auto shall be used only for cardiac\nimages acquired from an MR or CT scanner.\nIt shall be used by qualified medical\nprofessionals, experienced in examining and\nevaluating cardiovascular MR or CT images,","",""]],"caption_candidate":"Table 1. Comparison to the predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241922-p7-t0","doc_id":"K241922","page_num":7,"bbox":[72.32,87.4,756.55,203.13],"n_rows":4,"n_cols":10,"columns":["-","","Subject Device","","","Primary Device","","","Reference Device",""],"rows":[["-","","Subject Device","","","Primary Device","","","Reference Device",""],["","","Myomics","","","Myomics Q (K211432)","","","cvi42 Auto (K213998)",""],["","","Manufactured by Phantomics","","","Manufactured by Phantomics","","","Manufactured by Circle",""],["","Myomics shall be used only for cardiac images\nacquired from an MR scanner. It shall be used by\nqualified medical professionals, experienced in\nexamining and evaluating cardiovascular MR\nimages, for the purpose of obtaining diagnostic\ninformation as part of a comprehensive diagnostic\ndecision-making process.","","","The target population for the device is not\nrestricted, however the image acquisition by a\ncardiac MR scanner may limit the use of the device\nfor certain sectors or the public.","","","for the purpose of obtaining diagnostic\ninformation as part of a comprehensive\ndiagnostic decision-making process.","",""]],"caption_candidate":"Myomics 510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241922-p7-t1","doc_id":"K241922","page_num":7,"bbox":[72.32,245.98,756.55,367.17],"n_rows":8,"n_cols":12,"columns":["","-","","","Subject Device","","","Primary Device","","","Reference Device",""],"rows":[["","-","","","Subject Device","","","Primary Device","","","Reference Device",""],["","Device Name","","","Myomics","","","Myomics Q","","","cvi42 Auto Imaging Software Application",""],["","510(k) Number","","","-","","","K211432","","","K213998",""],["Manufacturer","","","Phantomics Inc.","","","Phantomics Inc.","","","Circle Cardiovascular Imaging Inc.","",""],["Regulation Number","","","21CFR892.2050","","","21CFR892.2050","","","21CFR892.2050","",""],["Regulation Name","","","Picture Archiving and Communication\nSystem","","","Picture Archiving and Communication\nSystem","","","Picture Archiving and Communication\nSystem","",""],["Classification","","","Class II","","","Class II","","","Class II","",""],["Product Code","","","QIH","","","LLZ","","","QIH","",""]],"caption_candidate":"Table 2. General comparison to the predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241922-p8-t0","doc_id":"K241922","page_num":8,"bbox":[85.4,98.83,769.67,433.15],"n_rows":24,"n_cols":12,"columns":["-","","","","Subject Device","","","Primary Device","","","Reference Device",""],"rows":[["-","","","","Subject Device","","","Primary Device","","","Reference Device",""],["","","","","Myomics","","","Myomics Q (K211432)","","","cvi42 Auto (K213998)",""],["","","","","Manufactured by Phantomics","","","Manufactured by Phantomics","","","Manufactured by Circle",""],["Imaging Modalities","","","MR","","","MR","","","MR and CT","",""],["Imaging Type","","","Cardiovascular","","","Cardiovascular","","","Cardiovascular","",""],["","DICOM Compliant","","Yes","","","Yes","","","Yes","",""],["","Networking","","","","","","","","","",""],["","Import and Display","","Yes","","","Yes","","","Yes","",""],["","MR images","","","","","","","","","",""],["","Images can be","","Yes","","","Yes","","","Yes","",""],["","displayed by study","","","","","","","","","",""],["","and series","","","","","","","","","",""],["","Segmentation of","","Yes (Endocardium and epicardium contour\nsegmentation)","","","Yes (Endocardium and epicardium contour\nsegmentation)","","","Yes (Endocardium and epicardium contour\nsegmentation)","",""],["","regions of interest","","","","","","","","","",""],["","Store images","","Yes (File Format: dcm, json, nii, csv)","","","Yes (File Format: dcm, json, nii, csv)","","","Yes (File Format: PDF, XML)","",""],["","Machine Learning","","Yes (Semi-automatic segmentation)","","","No","","","Yes (Semi-automatic segmentation)","",""],["","Based Algorithm","","","","","","","","","",""],["Quantitative\nAssessment of\nCardiac Function","","","Yes (Manual segmentation, and semi-\nautomatic segmentation using Machine\nLearning technique of four heart chambers in\nshort-axis views)","","","Yes (Manual segmentation)","","","Yes (Manual segmentation, and semi-\nautomatic segmentation using Machine\nLearning technique of four heart chambers in\nlong and short-axis views)","",""],["","Operating System","","Microsoft Windows","","","Microsoft Windows","","","Mac OS and Microsoft Windows","",""],["","Software","","IEC 62304:2006+A1:2015","","","IEC 62304:2006+A1:2015","","","IEC 62304:2006+A1:2015","",""],["","Development","","","","","","","","","",""],["","Standard","","","","","","","","","",""],["","Risk Management","","ISO 14971:2019","","","ISO 14971:2007","","","ISO 14971:2019","",""],["","Standard","","","","","","","","","",""]],"caption_candidate":"Table 3. Feature comparison table of Myomics with the predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241922-p9-t0","doc_id":"K241922","page_num":9,"bbox":[72.25,405.38,523.07,513.24],"n_rows":9,"n_cols":5,"columns":["AI Module No.","Data Group (AI Model Name)","Training","Validation","Test"],"rows":[["AI Module No.","Data Group (AI Model Name)","Training","Validation","Test"],["AIM-01","Native T1 Map Myocardium Segmentation","594 cases","42 cases","92 cases"],["AIM-02","Post T1 Map Myocardium Segmentation","498 cases","41 cases","91 cases"],["AIM-03","T2 Map Myocardium Segmentation","586 cases","59 cases","109 cases"],["AIM-04","CINE Myocardium Segmentation","640 cases","40 cases","90 cases"],["AIM-05","LGE PSIR Myocardium Segmentation","491 cases","27 cases","77 cases"],["AIM-06","CINE RV Myocardium Segmentation","437 cases","142 cases","192 cases"],["AIM-07","LGE Magnitude Myocardium Segmentation","477 cases","27 cases","77 cases"],["SUM","","3723 cases","378 cases","728 cases"]],"caption_candidate":"Table 4. AI Module Description in Myomics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241923-p5-t0","doc_id":"K241923","page_num":5,"bbox":[66.05,151.89,539.62,351.39],"n_rows":7,"n_cols":2,"columns":["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],"rows":[["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],["Address","8F., No.360, Sec. 1, Jingmao Rd.,\nBeitun Dist.,\nTaichung City 406040,\nTaiwan"],["Applicant","Joseph Chang"],["Contact Information","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["Correspondence Person","Ti-Hao Wang"],["Contact Information","886-04-23213838 #168\nthothwang@gmail.com\ntihao.wang@everfortune.ai"],["Date Prepared","November, 2024"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241923-p5-t1","doc_id":"K241923","page_num":5,"bbox":[66.05,398.46,539.62,509.46],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","EFAI NEUROSUITE CT MIDLINE SHIFT ASSESSMENT\nSYSTEM (MLS-CT-100)"],"rows":[["Proprietary Name","EFAI NEUROSUITE CT MIDLINE SHIFT ASSESSMENT\nSYSTEM (MLS-CT-100)"],["Common Name","EFAI MLSCT"],["Classification Name","Radiological computer-assisted triage and notification software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241923-p7-t0","doc_id":"K241923","page_num":7,"bbox":[73.87,89.62,538.12,726.37],"n_rows":6,"n_cols":3,"columns":["","prioritizing the clinical assessment of\nnon-contrast head CT cases with\nfeatures suggestive of midline shift\n(MLS) in individuals aged 18 years\nand above. EFAI MLSCT analyzes\ncases using deep learning algorithms\nto identify suspected MLS findings. It\nmakes case-level output available to a\nPACS/workstation for worklist\nprioritization or triage.\nEFAI MLSCT is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\nMLS. Its results are not intended to be\nused on a stand-alone basis for clinical\ndecision-making nor is it intended to\nrule out MLS or otherwise preclude\nclinical assessment of CT studies.","The device is intended to assist\nhospital networks and trained medical\nspecialists in workflow triage by\nflagging the following suspected\npositive findings of pathologies in\nhead CT images: intracranial\nhemorrhage, mass effect, midline\nshift and cranial fracture.\nqER uses an artificial intelligence\nalgorithm to analyze images on a\nstandalone cloud-based application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings.\nNotifications include non-diagnostic\npreview images that are meant for\ninformational purposes only. The\ndevice does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of the device are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],"rows":[["","prioritizing the clinical assessment of\nnon-contrast head CT cases with\nfeatures suggestive of midline shift\n(MLS) in individuals aged 18 years\nand above. EFAI MLSCT analyzes\ncases using deep learning algorithms\nto identify suspected MLS findings. It\nmakes case-level output available to a\nPACS/workstation for worklist\nprioritization or triage.\nEFAI MLSCT is not intended to direct\nattention to specific portions of an\nimage or to anomalies other than\nMLS. Its results are not intended to be\nused on a stand-alone basis for clinical\ndecision-making nor is it intended to\nrule out MLS or otherwise preclude\nclinical assessment of CT studies.","The device is intended to assist\nhospital networks and trained medical\nspecialists in workflow triage by\nflagging the following suspected\npositive findings of pathologies in\nhead CT images: intracranial\nhemorrhage, mass effect, midline\nshift and cranial fracture.\nqER uses an artificial intelligence\nalgorithm to analyze images on a\nstandalone cloud-based application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings.\nNotifications include non-diagnostic\npreview images that are meant for\ninformational purposes only. The\ndevice does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of the device are intended\nto be used in conjunction with other\npatient information and based on\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare."],["Classification/\nProduct Code","21 CFR 892.2080/QAS","21 CFR 892.2080/QAS"],["Anatomical\nregion of interest","Head","Head"],["Data acquisition\nprotocol","Non contrast CT scan of the head","Non contrast CT scan of the head"],["Segmentation of\nregion of interest","No; device does not mark, highlight,\nor direct users’ attention to a\nspecific location in the original\nimage.","No; device does not mark, highlight,\nor direct users’ attention to a\nspecific location in the original\nimage."],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p5-t0","doc_id":"K241949","page_num":5,"bbox":[121.94,583.78,554.02,658.66],"n_rows":4,"n_cols":3,"columns":["","CFR Number","Product Code"],"rows":[["","CFR Number","Product Code"],["Ultrasonic Pulsed Doppler Imaging System (Primary)","892.1550","90-IYN"],["Ultrasonic Pulsed Echo Imaging System","892.1560","90-IYO"],["Diagnostic Ultrasound Transducer","892.1570","90-ITX"]],"caption_candidate":"Regulatory Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p5-t1","doc_id":"K241949","page_num":5,"bbox":[121.94,667.06,554.02,704.14],"n_rows":2,"n_cols":2,"columns":["Classification Panel:","Radiology"],"rows":[["Classification Panel:","Radiology"],["Device Classification:","II"]],"caption_candidate":"Diagnostic Ultrasound Transducer 892.1570 90-ITX","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p6-t0","doc_id":"K241949","page_num":6,"bbox":[111.5,553.39,554.38,664.66],"n_rows":4,"n_cols":4,"columns":["Type","Device","510 (k) Number","Manufacturer"],"rows":[["Type","Device","510 (k) Number","Manufacturer"],["1)Primary Predicate\nDevice","P60 Series Digital Color\nDoppler Ultrasound System","K171000","SonoScape Medical Corp."],["2)Reference Device","S90 Exp Series Digital Color\nDoppler Ultrasound System","K222596","SonoScape Medical Corp."],["3)Reference Device","P20 Elite Series Digital Color\nDoppler Ultrasound System","K221140","SonoScape Medical Corp."]],"caption_candidate":"4. Identification of Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p7-t0","doc_id":"K241949","page_num":7,"bbox":[115.58,412.97,540.82,710.86],"n_rows":3,"n_cols":2,"columns":["Equipment used to\ncollect images","The data set were acquired with P60/S60 series Digital Color Doppler\nUltrasound System and probes in order to secure diversity of the data set:\nMix of data from retrospective data collection and prospective data collection\nin clinical practice."],"rows":[["Equipment used to\ncollect images","The data set were acquired with P60/S60 series Digital Color Doppler\nUltrasound System and probes in order to secure diversity of the data set:\nMix of data from retrospective data collection and prospective data collection\nin clinical practice."],["Reference standard","The ground truths drawn by five OB/GYN experts with more than 3 years’\nexperience were cross-checked by the two experts with more than 20 years’\nexperience and were re-checked by other four experts with more than 30\nyears’ experience.\nAny images that do not meet the inclusion/exclusion criteria were excluded\nfrom the set of images."],["Test Set","The test set used to test the standalone performance of S-FetusAI are\nindependent of the training data set and tuning data set, which have been\ncollected at three hospitals in China and meet the characteristics of\nindependence, representativeness, uniformity of distribution, etc., and strive\nto include all possible scenarios in the clinic as far as possible.\nS-Fetus-Recognition:\nThe number of test set is more than 200 images for each standard section;\ntotal 3717 images for 14 standard sections.\nS-Fetus-Measure:"]],"caption_candidate":"1) Standalone Performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p8-t0","doc_id":"K241949","page_num":8,"bbox":[115.58,85.34,540.82,180.38],"n_rows":3,"n_cols":2,"columns":["","The number of test set is more than 250 for each standard section; total 2929\nimage for 9 standard sections."],"rows":[["","The number of test set is more than 250 for each standard section; total 2929\nimage for 9 standard sections."],["Acceptance Criteria","The accuracy of the S-Fetus-Recognition is not less than 85%.\nThe accuracy of the S-fetus-Measure is not less than 80%."],["Test Results","The accuracy of the S-Fetus-Recognition is 90.01%.\nThe accuracy of the S-fetus-Measure is 85%."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241949-p8-t1","doc_id":"K241949","page_num":8,"bbox":[115.58,227.66,540.82,651.46],"n_rows":5,"n_cols":2,"columns":["Research Device","P60 Exp Digital Color Doppler Ultrasound System with S-FetusAI\n& VC6-2 Probe"],"rows":[["Research Device","P60 Exp Digital Color Doppler Ultrasound System with S-FetusAI\n& VC6-2 Probe"],["Research Group","Trial group: Automatic recognition and measurement of the S-FetusAI\nfunction of the Research Device;\nContrast group: Manual recognition and measurement of the investigators\n(physicians with more than 3 years of specialized training in obstetric\nultrasound examination; total 7 investigators).\nThe section recognition results and precision of Sp of Trial group and\nContrast group were evaluated by the 2 Readers from the independent\nevaluation group, which consists of three qualified professionals (senior\nexperts who had been involved in prenatal ultrasound examination)."],["Sample Size","158 cases"],["Clinical\nPerformance\nEvaluation &\nAcceptance Criteria","1.Identification Precision of the 14 Standard Sections (Primary Evaluation\nIndicator)\nNon-inferiority design is used.\nIf the lower limit of the 95% CI for the difference of Identification Precision\nis greater than -10%, then the Identification Precision of the Standard Section\nof S-FetusAI function is considered non-inferior to manual recognition.\n2. Measurement Error of Growth Parameters (Secondary Evaluation\nIndicator)\n1)The relative errors of measurement for the 11 Growth Parameters;\n2)The precision of Sp (spinal cord cone end positioning)."],["Conclusion","According to the clinical trial results, we can deduce that the recognition\nprecision of the standard sections of S-FetusAI was not inferior to that of\nthe manual scan, S-FetusAI has a good consistency with the manual\nmeasurement and the Sp (spinal cone end positioning) precision was\nbasically equal between the trial group and control group."]],"caption_candidate":"2) Clinical Performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241971-p8-t0","doc_id":"K241971","page_num":8,"bbox":[111.63,336.41,543.93,618.7],"n_rows":8,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012\nand A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -\nPart 1: General requirements for basic safety and essential performance\n(IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical equipment - Part\n1-2: General requirements for basic safety and essential performance -\nEMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -\nPart 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems","",""],["ISO10993-1","","","AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of\nmedical devices – Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices","",""],["NEMA UD 2-2004","","","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3","",""]],"caption_candidate":"ultrasound system and its applications comply with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241971-p10-t0","doc_id":"K241971","page_num":10,"bbox":[86.34,518.05,525.78,554.95],"n_rows":3,"n_cols":8,"columns":["","1st trimester","","","","","",""],"rows":[["","1st trimester","","","","","",""],["Label","","Fluid","Fetus","Umbilical-cord","Placenta","Uterus",""],["Acceptance Rate (%)","","98%","96%","80%","86%","89%",""]],"caption_candidate":"Acceptance rate for each label - qualitative results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241971-p10-t1","doc_id":"K241971","page_num":10,"bbox":[86.34,569.86,525.78,609.82],"n_rows":3,"n_cols":10,"columns":["","2nd/3rd trimester","","","","","","","",""],"rows":[["","2nd/3rd trimester","","","","","","","",""],["Label","","Fluid","Head","Body","Limbs","Umbilical-cord","Placenta","Uterus",""],["Acceptance rate (%)","","92%","94%","84%","83%","82%","85%","87%",""]],"caption_candidate":"Acceptance Rate (%) 98% 96% 80% 86% 89%","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241971-p10-t2","doc_id":"K241971","page_num":10,"bbox":[86.34,636.94,525.78,684.34],"n_rows":3,"n_cols":8,"columns":["","1st trimester","","","","","",""],"rows":[["","1st trimester","","","","","",""],["Label","","Fluid","Fetus","Umbilical-cord","Placenta","Uterus",""],["Mean DSC\nfor accepted cases","","0.96","0.91","0.68","0.74","0.93",""]],"caption_candidate":"The mean DSC for the accepted and rejected cases - quantitative results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241971-p11-t0","doc_id":"K241971","page_num":11,"bbox":[86.38,112.85,525.68,196.34],"n_rows":4,"n_cols":10,"columns":["","2nd/3rd trimester","","","","","","","",""],"rows":[["","2nd/3rd trimester","","","","","","","",""],["Label","","Fluid","Head","Body","Umbilical-cord","Limbs","Placenta","Uterus",""],["Mean DSC\nfor accepted\ncases","","0.78","0.94","0.68","0.67","0.66","0.75","0.80",""],["Mean DSC\nfor rejected cases","","0.25","0.46","0.29","0.38","0.39","0.32","0.30",""]],"caption_candidate":"for rejected cases","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241982-p5-t0","doc_id":"K241982","page_num":5,"bbox":[72.5,326.5,540.5,450.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name","DeepFoqus (DeepFoqus-Accelerate)"],"rows":[["Device Trade Name","DeepFoqus (DeepFoqus-Accelerate)"],["Common Name","Medical image management and processing system"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","892.2050"],["Product Code(s)","QIH"]],"caption_candidate":"2.0 Device Name 21 CFR 807.92(a)(2)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241982-p5-t1","doc_id":"K241982","page_num":5,"bbox":[72.5,487.5,540.5,536.5],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate Trade Name (Primary Predicate is listed first)","Product Code"],"rows":[["Predicate #","Predicate Trade Name (Primary Predicate is listed first)","Product Code"],["K210999","SwiftMR","LLZ"]],"caption_candidate":"3.0 Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241984-p7-t0","doc_id":"K241984","page_num":7,"bbox":[58.49,89.54,564.64,691.44],"n_rows":7,"n_cols":8,"columns":["Characteristics","","","Subject Device:","","","Predicate Device:",""],"rows":[["Characteristics","","","Subject Device:","","","Predicate Device:",""],["","Characteristics","","Hi-Imaging 4TAVR","","","3mensio Workstation (K153736)",""],["","Regulatory Information","","","","","",""],["Classification","","21 CFR§892.2050 “Medical image management and\nprocessing systems”","","","21 CFR§892.2050 “Medical image\nmanagement and processing systems”","",""],["Product Code","","QIH (Automated Radiological Image Processing\nSoftware)","","","LLZ (System, Image Processing,\nRadiological)","",""],["Intended Use","","Hi-D Imaging 4TAVR software is intended to\nvisualize, analyze, and report anatomical structures of\nthe full heart of the patient. Full heart comprises the\ncomponents of the heart and vessels, including aorta,\nleft ventricle, left atrium, myocardium, right ventricle,\nand pulmonary artery. The intended use is to support\ntrained healthcare professionals (cardiologists,\nradiologists, and clinical specialists) before the cardiac\noperations, such as transcatheter aortic valve\nreplacement (TAVR), in reading and interpreting\nmedical DICOM images of the heart and vessels, and\nby measuring clinically relevant pre-procedural\nplanning parameters (diameters, lengths, perimeters,\nareas). The software itself is not intended to be a\ndecision-making tool by itself.","","","3mensio Workstation is a software solution\nthat is intended to provide Cardiologists,\nRadiologists and Clinical Specialists\nadditional information to aid them in reading\nand interpreting DICOM compliant medical\nimages of structures of the heart and vessels.\n3mensio Structural Heart enables the user to:\n(cid:120) Visualize and measure (diameters,\nlengths, areas, volumes, angles)\nstructures of the heart and vessels\n(cid:120) Quantify calcium (volume, density)\n3mensio Vascular enables the user to:\n(cid:120) Visualize and assess stenosis,\naneurisms and vascular structures\n(cid:120) Measure the dimensions of vessels\n(diameters, lengths, areas, volumes,\nangles)","",""],["Indications for\nUse","","Hi-D Imaging 4TAVR is a software as a medical\ndevice (SaMD) intended to support trained healthcare\nprofessionals (cardiologists, radiologists, clinical\nspecialists) with the assessment of the cardiovascular\nanatomy and visualization and measurement of\nstructures of the heart and vessels, including the aortic\nvalve, and with pre-operational planning and sizing for\ntranscatheter aortic valve replacement (TAVR)\nprocedures by providing:\n- Automatic segmentation of the full heart and vessels\n- 3D and 2D rendering of DICOM images\n- Automatic centerline detection\n- Automatic detection of the LVOT (left ventricular\noutflow tract), aortic, sinus, sinotubular junction\n(STJ), ascending aorta and descending aorta planes\n- Automatic multiplanar reconstruction (MPR) based\non the centerline\n- Measurement and visualization tools\n- Manual measurement option for the user\n- Automatic S-curve extraction\n- Automatic report generation\nHi-D Imaging 4TAVR software is indicated for\npatients with tricuspid aortic stenosis who are eligible\nfor TAVR operations and without any prior aortic\nvalve implants.","","","3mensio Workstation enables visualization\nand measurement of structures of the heart\nand vessels for:\n• Pre-operational planning and sizing for\ncardiovascular interventions and surgery\n• Postoperative evaluation\n• Support of clinical diagnosis by quantifying\ndimensions in coronary arteries\n• Support of clinical diagnosis by quantifying\ncalcifications (calcium scoring) in the\ncoronary arteries\nTo facilitate the above, the 3mensio\nWorkstation provides general functionality\nsuch as:\n• Segmentation of cardiovascular structures\n• Automatic and manual center lumen line\ndetection\n• Visualization and image reconstruction\ntechniques: 2D review, Volume Rendering,\nMPR, Curved MPR, Stretched CMPR,\nSlabbing, MIP, AIP, MinIP\n• Measurement and annotation tools\n• Reporting tools","",""]],"caption_candidate":"Table 1: Summary of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241984-p8-t0","doc_id":"K241984","page_num":8,"bbox":[58.49,75.74,564.64,704.04],"n_rows":7,"n_cols":8,"columns":["Characteristics","","","Subject Device:","","","Predicate Device:",""],"rows":[["Characteristics","","","Subject Device:","","","Predicate Device:",""],["","Characteristics","","Hi-Imaging 4TAVR","","","3mensio Workstation (K153736)",""],["","Technological Characteristics","","","","","",""],["Input Data\nType","","CT data in DICOM format (vendor independent)","","","CT data in DICOM format (vendor\nindependent)","",""],["Image\nFunctionality","","(cid:120) Importing (Single and batch imports)\n(cid:120) Encryption\n(cid:120) History of processed images","","","(cid:120) Exporting\n(cid:120) Deleting\n(cid:120) Anonymizing (no automatic deletion of\noriginal patient data)\n(cid:120) Search","",""],["Centerline\nExtraction","","(cid:120) Automatic Centerline extraction for the entire aortic\nsegment.\n(cid:120) Automatic anatomical profiling of MPR planes\nalong the aortic centerline.","","","(cid:120) Realign orthogonal MPRs\n(cid:120) Segmentation toolset:\n- Automatic segmentation of the\nascending aorta\n- Automatic centerline (center lumen\nline)\n- Manual centerline\n- Centerline editing\n(cid:120) Undo/redo operations\n(cid:120) Volume sculpting","",""],["Image\nAssessments","","(cid:120) Automatic segmentation and anatomical\nmeasurements of heart components\n(cid:120) Automatic anatomical measurements for pre-\noperational TAVR planning.\n(cid:120) Automatic detection of TAVR anatomical\nlandmarks.\n(cid:120) TAVR sizing (IFU based TAVR sizing chart).\n(cid:120) C-Arm angulation calculation (S-curve).","","","X-Ray Image Assessments:\n(cid:120) Linear (length and diameter), angular and\nROI measurements\n(cid:120) Volume measurements\n(cid:120) C-Arm angulation calculation\n(cid:120) Text and arrow annotations\n(cid:120) Calcium scoring for assessment of\ncalcium in the aortic root\n(cid:120) Calcium scoring for assessment of\ncalcium in the coronary arteries\n(cid:120) Segmentation and analysis of coronary\nartery tree centerline\nIntravascular ultrasound (IVUS) / optical\ncoherence tomography (OCT) Image\nAssessments:\n(cid:120) Orthogonal, oblique, double oblique,\ncurved, cross-curved, stretched MPR\nrendering\n(cid:120) MIP, AveIP, MinIP and color volume\nslabs\n(cid:120) MIP volume rendering\n(cid:120) Color volume rendering\n(cid:120) Grayscale volume rendering\n(cid:120) 2D slice review and stack comparison\n(cid:120) 4D cine\n(cid:120) Interactive VOI clipping\n(cid:120) Multi-tissue color and opacity control\n(cid:120) Active presets/User-defined presets","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K241984-p9-t0","doc_id":"K241984","page_num":9,"bbox":[58.51,75.74,564.55,195.72],"n_rows":3,"n_cols":7,"columns":["Characteristics","","Subject Device:","","","Predicate Device:",""],"rows":[["Characteristics","","Subject Device:","","","Predicate Device:",""],["","","Hi-Imaging 4TAVR","","","3mensio Workstation (K153736)",""],["Results Output","(cid:120) 2D, 3D visuals with centerline\n(cid:120) Downloadable 3D meshes of the heart\ncompartments\n(cid:120) Planes of interest visualized in 3D\n(cid:120) Summary\n(cid:120) Report generation, downloadable in PDF format\n(cid:120) IFU based TAVR sizing chart","","","(cid:120) Printout\n(cid:120) Session state\n(cid:120) PDF format\n(cid:120) DICOM PDF report","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242020-p7-t0","doc_id":"K242020","page_num":7,"bbox":[72.36,168.33,539.73,690.81],"n_rows":36,"n_cols":4,"columns":["","","EPIQ Series Diagnostic",""],"rows":[["","","EPIQ Series Diagnostic",""],["","EPIQ Series Diagnostic","",""],["","","Ultrasound System",""],["","Ultrasound System","",""],["","","",""],["","","",""],["","","Affiniti Diagnostic Ultrasound",""],["Feature","Affiniti Series Diagnostic","","Comparison"],["","","System",""],["","Ultrasound System","",""],["","","",""],["","","",""],["","","(K240850)",""],["","Proposed Devices","",""],["","","Predicate Device",""],["","","",""],["","Class II","Class II","Identical"],["USA FDA","","",""],["Classification","","",""],["","","",""],["","IYN","IYN","Identical"],["Primary Product","","",""],["Code","","",""],["","","",""],["","21 CFR 892.1550","21 CFR 892.1550","Identical"],["Primary Regulation","","",""],["Number","","",""],["","","",""],["","Auto ElastQ","ElastQ","Subject of this\nsubmission"],["Marketing Name of","","",""],["Application","","",""],["","","",""],["","The Auto ElastQ software feature\nis intended to assist the user in\nmaking liver stiffness\nmeasurements using 2D-SWE\nthrough recommended particular\nframes and ROI positions to the\nuser.\nThe system software will select up\nto three frames that are assessed\nto be the most stable and present\nthese to the user. The circle ROI\nwill be launched in the locations\nthat are identified to be\nhomogenous and temporally\nstable.","The ElastQ feature (“manual\nworkflow”) is a tool for measuring\nthe stiffness of the target organ\n(liver) which requires the user to\nreview a loop of elastography\nimages displayed on the system\nand uses the trackball to cine to\nthe frame(s) that are visually\nperceived to be the most stable.\nThe circle ROI is then launched in\nthe center of the shear wave\nimaging box, and the user\nmanually positions the ROI within\nthe box in a location that appears\nto be homogenous and\nrepresentative of the tissue in the\nentire box.","Subject of this\nsubmission\nThe difference between\nthe predicate and the\nsubject device is:\nThe proposed Auto\nElastQ feature\nrecommends particular\nframes and ROI locations\nthat are assessed to be\nmost stable homogenous\nto the user.\nThe predicate device\nrequires users to review\na loop of elastography\nimages and then use the\ntrackball to cine to the\nframes that are visually\nperceived to be the most\nstable. Then the user\nmust manually positions\nthe ROI in a location that\nappears to be most\nstable and homogenous."],["Application","","",""],["Description","","",""],["","","",""]],"caption_candidate":"substantially equivalent to the predicate devices (K240850).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242020-p8-t0","doc_id":"K242020","page_num":8,"bbox":[72.35,72.33,539.72,673.53],"n_rows":32,"n_cols":4,"columns":["","","EPIQ Series Diagnostic",""],"rows":[["","","EPIQ Series Diagnostic",""],["","EPIQ Series Diagnostic","",""],["","","Ultrasound System",""],["","Ultrasound System","",""],["","","",""],["","","",""],["","","Affiniti Diagnostic Ultrasound",""],["Feature","Affiniti Series Diagnostic","","Comparison"],["","","System",""],["","Ultrasound System","",""],["","","",""],["","","",""],["","","(K240850)",""],["","Proposed Devices","",""],["","","Predicate Device",""],["","","",""],["","The Auto ElastQ workflow\nanalyzes the frames present in\nthe cineloop buffer. The system\nsoftware will automatically cine to\nthree frames that are assessed to\nbe the most stable and present\nthese to the user. The\nmeasurement ROI will\nautomatically launch and be\nplaced on locations identified to\nbe homogeneous and temporally\nstable.\nEven though the Auto ElastQ\nfeature will suggest a particular\nROI placement, the user must\ninspect the results and ensure\nthat it meets intended clinical use.\nOtherwise, the user can make\nadjustments to what the feature\nproposes, by either selecting a\ndifferent frame or a different ROI\nposition.","In the current released software\n(“manual workflow”), the user\nreviews a loop of elastography\nimages displayed on the system\ndisplay and then uses the\ntrackball to cine to the frame(s)\nthat are visually perceived to be\nthe most stable. The circle ROI is\nthen launched in the center of the\nshear wave imaging box, and the\nuser manually positions the ROI\nwithin the box in a location that\nappears to be homogeneous and\nrepresentative of the tissue in the\nentire box.","Subject of this\nsubmission\nThe proposed Auto\nElastQ will provide a\nrecommendation to the\nuser where the predicate\ndevice requires the user\nto navigate the system\nmanually."],["User Interface","","",""],["Presentation","","",""],["","","",""],["","Auto ElastQ Feature:\nC5-1","ElastQ Feature:\nC5-1","Identical, no new\ntransducers or modes\nare being introduced in\nthis submission."],["Compatible","","",""],["transducers","","",""],["","","",""],["","The Auto ElastQ feature\ncalculates stiffness\nmeasurements based on selected\nframes and ROI positions\nrecommended to the user or\nbased on user adjustments to\nwhat the feature recommended.","The ElastQ feature calculates\nstiffness measurements based on\nthe manually selected frames and\nROI positions.","No new measurements\nare being introduced in\nthis submission. The\nsubject of this\nsubmission is to provide\nworkflow enhancements."],["Measurements","","",""],["Performed","","",""],["","","",""],["","A retrospective data analysis\nstudy was conducted to evaluate\nthe performance of the Auto\nElastQ software compared to\nmanual measurements performed\nby expert readers.\nThe results demonstrated high\nagreement of Auto ElastQ\nalgorithm-generated\nmeasurements, based on\nstatistical analysis, with manual\nelastography measurements.","N/A – the equivalent functionality\nis performed manually by the\nusers to select the most\nappropriate frames and ROI\npositions.","Subject of this\nsubmission"],["Application","","",""],["performance","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242054-p4-t0","doc_id":"K242054","page_num":4,"bbox":[35.12,21.85,567.28,93.97],"n_rows":3,"n_cols":5,"columns":["","","Special 510(k) Premarket Notification","","Page 1 of 3"],"rows":[["","","Special 510(k) Premarket Notification","","Page 1 of 3"],["","","OptimMRI (v2) - K242054","",""],["","510(k) Summary","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242054-p5-t0","doc_id":"K242054","page_num":5,"bbox":[35.12,21.85,567.28,93.97],"n_rows":3,"n_cols":5,"columns":["","","Special 510(k) Premarket Notification","","Page 2 of 3"],"rows":[["","","Special 510(k) Premarket Notification","","Page 2 of 3"],["","","OptimMRI (v2) - K242054","",""],["","510(k) Summary","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242054-p6-t0","doc_id":"K242054","page_num":6,"bbox":[35.12,21.85,567.28,93.97],"n_rows":3,"n_cols":5,"columns":["","","Special 510(k) Premarket Notification","","Page 3 of 3"],"rows":[["","","Special 510(k) Premarket Notification","","Page 3 of 3"],["","","OptimMRI (v2) - K242054","",""],["","510(k) Summary","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242062-p5-t0","doc_id":"K242062","page_num":5,"bbox":[20.66,344.76,591.07,420.87],"n_rows":3,"n_cols":3,"columns":["","","mike@hardianhealth.com"],"rows":[["","","mike@hardianhealth.com"],["Device Name 21 CFR 807.92(a)(2)","",""],["","1CMR Pro",""]],"caption_candidate":"Correspondent Contact Mr. Michael Pogose","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242062-p5-t1","doc_id":"K242062","page_num":5,"bbox":[20.66,513.96,591.07,564.48],"n_rows":2,"n_cols":2,"columns":["","QIH, LLZ"],"rows":[["","QIH, LLZ"],["Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)",""]],"caption_candidate":"Regulation Number 892.2050","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p7-t0","doc_id":"K242123","page_num":7,"bbox":[72.49,299.77,444.35,378.01],"n_rows":5,"n_cols":4,"columns":["Metric Name","Value","Criteria","Pass/Fail"],"rows":[["Metric Name","Value","Criteria","Pass/Fail"],["Left-MAE","6.444","<10","Pass"],["Left-MAE-STD","9.269","<15","Pass"],["Right-MAE","5.611","<10","Pass"],["Right-MAE-STD","8.610","<15","Pass"]],"caption_candidate":"criteria, which is summarized below in Table 1.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p7-t1","doc_id":"K242123","page_num":7,"bbox":[72.49,485.36,518.55,558.48],"n_rows":5,"n_cols":5,"columns":["Device","","","Left MAE (%)","Right MAE (%)"],"rows":[["Device","","","Left MAE (%)","Right MAE (%)"],["","Device","","",""],["","Predicate device with NO-CNN (n=18)","","7.333","6.889"],["","Proposed device with CNN (n=18)","","3.000","6.278"],["","Difference between devices","","4.333 > 0","0.611 > 0"]],"caption_candidate":"metrics are summarized in Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p8-t0","doc_id":"K242123","page_num":8,"bbox":[72.0,461.76,504.0,503.52],"n_rows":3,"n_cols":6,"columns":["","Metrics","","","All Cases (N=308)",""],"rows":[["","Metrics","","","All Cases (N=308)",""],["","Vessels DSC","","","0.955 (0.953, 0.957)",""],["","Parenchyma DSC","","","0.999 (0.999, 1.000)",""]],"caption_candidate":"Table 3. Summary performance metrics from full sample of 308 patients, with 95% confidence intervals where appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p8-t1","doc_id":"K242123","page_num":8,"bbox":[72.0,618.42,523.32,673.62],"n_rows":4,"n_cols":12,"columns":["","Metrics","","","Age 22-50","","","Age 50-70","","","Age 70+",""],"rows":[["","Metrics","","","Age 22-50","","","Age 50-70","","","Age 70+",""],["","Total N","","","57","","","132","","","119",""],["","Vessels DSC","","","0.958 (0.953, 0.962)","","","0.959 (0.957, 0.962)","","","0.949 (0.946, 0.953)",""],["","Parenchyma DSC","","","0.999 (0.999, 1.000)","","","0.999 (0.999, 1.000)","","","0.999 (0.999, 1.000)",""]],"caption_candidate":"appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p8-t2","doc_id":"K242123","page_num":8,"bbox":[72.0,726.6,421.75,768.36],"n_rows":3,"n_cols":9,"columns":["","Metrics","","","Male","","","Female",""],"rows":[["","Metrics","","","Male","","","Female",""],["","Total N","","","140","","","168",""],["","Vessels DSC","","","0.952 (0.949, 0.955)","","","0.958 (0.955, 0.960)",""]],"caption_candidate":"appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p9-t0","doc_id":"K242123","page_num":9,"bbox":[63.78,161.34,530.88,250.94],"n_rows":7,"n_cols":18,"columns":["Metrics","","","White","","","","Black/African","","","Hispanic/","","","Asian/Asian","","","Unknown/",""],"rows":[["Metrics","","","White","","","","Black/African","","","Hispanic/","","","Asian/Asian","","","Unknown/",""],["","","","","","","","American","","","Latino","","","American","","","Refused",""],["","Total N","","","148","","","85","","","27","","","7","","","40",""],["Vessels DSC","Vessels DSC","","","0.954 (0.951,","","","0.957 (0.953,","","","0.957 (0.949,","","","0.958 (0.948,","","","0.955 (0.951,",""],["","","","","0.956)","","","0.961)","","","0.964)","","","0.967)","","","0.959)",""],["","Parenchyma","","","0.999 (0.999,","","","0.999 (0.999,","","","0.999 (0.999,","","","0.999 (0.999,","","","0.999 (0.999,",""],["","DSC","","","1.000)","","","1.000)","","","1.000)","","","1.000)","","","1.000)",""]],"caption_candidate":"where appropriate. *CI could not be calculated due to lack of evidence (low N).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p9-t1","doc_id":"K242123","page_num":9,"bbox":[71.33,304.92,421.56,360.12],"n_rows":4,"n_cols":9,"columns":["","Metrics","","","MCR","","","BMC",""],"rows":[["","Metrics","","","MCR","","","BMC",""],["","Total N","","","129","","","179",""],["","Vessels DSC","","","0.952 (0.949, 0.956)","","","0.957 (0.955, 0.959)",""],["","Parenchyma DSC","","","0.999 (0.999, 1.000)","","","0.999 (0.999, 1.000)",""]],"caption_candidate":"appropriate. MCR = Mayo Clinic Rochester, BMC = Boston Medical Center.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p9-t2","doc_id":"K242123","page_num":9,"bbox":[71.33,413.1,530.88,505.81],"n_rows":7,"n_cols":15,"columns":["Metrics","","","SIEMENS","","","","GE Medical","","Philips","","","Canon/ Toshiba","",""],"rows":[["Metrics","","","SIEMENS","","","","GE Medical","","Philips","","","Canon/ Toshiba","",""],["","","","","","","","Systems","","","","","","",""],["","Total N","","","133","","","96","","","75","","","4",""],["Vessels DSC","Vessels DSC","","0.953 (0.95, 0.956)","0.953 (0.95, 0.956)","","0.954 (0.95, 0.957)","0.954 (0.95, 0.957)","","","0.961 (0.958,","","0.964 (0.947, 0.981)","0.964 (0.947, 0.981)",""],["","","","","","","","","","","0.964)","","","",""],["","Parenchyma","","0.999 (0.999, 1.000)","","","0.999 (0.999, 1.000)","","","","0.999 (0.999,","","0.999 (0.999, 1.000)","",""],["","DSC","","","","","","","","","1.000)","","","",""]],"caption_candidate":"intervals where appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p9-t3","doc_id":"K242123","page_num":9,"bbox":[71.33,559.08,421.56,614.28],"n_rows":4,"n_cols":9,"columns":["","Metrics","","","With Stenosis","","","Without Stenosis",""],"rows":[["","Metrics","","","With Stenosis","","","Without Stenosis",""],["","Total N","","","30","","","278",""],["","Vessels DSC","","","0.957 (0.952, 0.962)","","","0.955 (0.953, 0.957)",""],["","Parenchyma DSC","","","0.999 (0.999, 1.000)","","","0.999 (0.999, 1.000)",""]],"caption_candidate":"confidence intervals where appropriate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p11-t0","doc_id":"K242123","page_num":11,"bbox":[43.65,386.95,550.65,766.02],"n_rows":7,"n_cols":10,"columns":["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],"rows":[["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],["","","Brainomix 360 e-CTA","","","Brainomix 360 e-CTA","","","iSchemaView Rapid",""],["","","(K242123)","","","(K192692)","","","(K233582)",""],["510(k) Number","K242123","","","K192692","","","K233582","",""],["Product Code","LLZ, QIH","","","LLZ","","","LLZ, QIH","",""],["Regulation\nNumber","21 CFR §892.2050","","","21 CFR §892.2050","","","21 CFR §892.2050","",""],["Intended\nUse/Indications\nfor Use","Brainomix 360 e-CTA is an\nimage processing software\npackage to be used by trained\nprofessionals, including, but\nnot limited to physicians and\nmedical technicians. The\nsoftware runs on standard “off\nthe-shelf” hardware (physical\nor virtualized) and can be used\nto perform image viewing,\nprocessing, and analysis of\nimages. Data and images are\nacquired through DICOM\ncompliant imaging devices.\nBrainomix 360 e-CTA provides\nviewing and analysis\ncapabilities for imaging\ndatasets acquired with CTA (CT\nAngiography).","","","Brainomix 360 e-CTA is an\nimage processing software\npackage to be used by trained\nprofessionals, including, but\nnot limited to physicians and\nmedical technicians. The\nsoftware runs on standard “off\nthe-shelf” hardware (physical\nor virtualized) and can be used\nto perform image viewing,\nprocessing, and analysis of\nimages. Data and images are\nacquired through DICOM\ncompliant imaging devices.\nBrainomix 360 e-CTA provides\nviewing and analysis\ncapabilities for imaging\ndatasets acquired with CTA (CT\nAngiography).","","","Rapid is an image processing\nsoftware package to be used by\ntrained professionals, including\nbut not limited to physicians\n(medical analysis and decision\nmaking) and medical\ntechnicians (administrative case\nprocessing). The software runs\non a standard off-the-shelf\ncomputer or a virtual platform,\nsuch as VMware, and can be\nused to perform image viewing,\nprocessing, and analysis of\nimages. Data and images are\nacquired through DICOM\ncompliant imaging devices.\nRapid is indicated for use in\nAdults only. Rapid provides both\nviewing and analysis capabilities\nfor functional and dynamic\nimaging datasets acquired with\nCT, CT Perfusion (CTP), CT\nAngiography (CTA), C-arm CT","",""]],"caption_candidate":"A table comparing the key features of the proposed and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p12-t0","doc_id":"K242123","page_num":12,"bbox":[43.69,95.59,550.61,734.46],"n_rows":4,"n_cols":10,"columns":["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],"rows":[["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],["","","Brainomix 360 e-CTA","","","Brainomix 360 e-CTA","","","iSchemaView Rapid",""],["","","(K242123)","","","(K192692)","","","(K233582)",""],["","Brainomix 360 e-CTA is not\nintended for mobile diagnostic\nuse.\nBrainomix 360 e-CTA vessel\ndensity asymmetry ratio\napplies only to the MCA region.","","","Brainomix 360 e-CTA is not\nintended for mobile diagnostic\nuse.","","","Perfusion and MRI including a\nDiffusion Weighted MRI (DWI)\nModule and a Dynamic Analysis\nModule (dynamic contrast-\nenhanced imaging data for MRI,\nCT, and C-arm CT). Rapid C-arm\nCT Perfusion can be used to\nqualitatively assess cerebral\nhemodynamics in the\nangiography suite. The CT\nanalysis includes NCCT maps\nshowing areas of hypodense\nand hyperdense tissue. The DWI\nModule is used to visualize local\nwater diffusion properties from\nthe analysis of diffusion -\nweighted MRI data. The\nDynamic Analysis Module is\nused for visualization and\nanalysis of dynamic imaging\ndata, showing properties of\nchanges in contrast over time.\nThis functionality includes\ncalculation of parameters\nrelated to tissue flow\n(perfusion) and tissue blood\nvolume. Rapid CT Perfusion and\nRapid MR Perfusion can be used\nby physicians to aid in the\nselection of acute stroke\npatients (with known occlusion\nof the intracranial internal\ncarotid artery or proximal\nmiddle cerebral artery).\nInstructions for the use of\ncontrast agents for this\nindication can be found in\nAppendix A of the User’s\nManual. Additional information\nfor safe and effective drug use is\navailable in the product-specific\niodinated CT and gadolinium-\nbased MR contrast drug\nlabeling. In addition to the\nRapid imaging criteria, patients\nmust meet the clinical\nrequirements for\nthrombectomy, as assessed by\nthe physician, and have none of","",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p13-t0","doc_id":"K242123","page_num":13,"bbox":[43.64,95.59,550.66,760.74],"n_rows":11,"n_cols":10,"columns":["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],"rows":[["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],["","","Brainomix 360 e-CTA","","","Brainomix 360 e-CTA","","","iSchemaView Rapid",""],["","","(K242123)","","","(K192692)","","","(K233582)",""],["","","","","","","","the following contraindications\nor exclusions:\n• Bolus Quality: absent or\ninadequate bolus.\n• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan\ntechnically inadequate.\n• Presence of hemorrhage.\n• C-Arm CTP is not to be\nused in the Rapid\nThrombectomy indication\nfor patient selection\ncriteria, other modalities\nshould be consulted.\nCautions:\nC-Arm CTP provides qualitative\ndata only, review other\nmodalities prior to diagnosis.\nCBV and CBT are not absolute\nand CBT, CBV, MTT and Tmax\nare supported for qualitative\ninterpretation of the perfusion\nmaps only.","",""],["Environment of\nuse","Clinical/Hospital environment","","","Same","","","Same","",""],["Energy used\nand/or delivered","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","","","Same","","","Same","",""],["Primary Users","Radiologist/Clinician","","","Same","","","Same","",""],["Design:\nSupported\nModalities for\nimage processing\nand visualization","CTA only","","","CTA only","","","CT [NCCT, CT, CTA, C-arm\nCT(CBCT)] or MR (MR, MRA)","",""],["MIP Views\naccessible","Maximum intensity projections\n(MIPs) of the vascular system\nin axial, coronal, left and right\nhemisphere sagittal, and\nposterior views","","","Maximum intensity projections\n(MIPs) of the vascular system\nin axial, coronal and left and\nright hemisphere sagittal views","","","Maximum intensity projections\n(MIPs) of the vascular system in\naxial, coronal, left and right\nhemisphere sagittal.","",""],["Technical\nImplementation","Mixed Traditional and AI/ML","","","Traditional","","","Mixed Traditional and AI/ML","",""],["Image Overlay","Vessel Density with visual\nrepresentation (3D-colored\noverlay)","","","No","","","Vessel Density with visual\nrepresentation (2D-colored\noverlay)","",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242123-p14-t0","doc_id":"K242123","page_num":14,"bbox":[43.63,95.59,550.67,557.1],"n_rows":17,"n_cols":10,"columns":["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],"rows":[["Characteristics/\nParameter","","Proposed Device","","","Primary Predicate Device","","","Secondary Predicate Device",""],["","","Brainomix 360 e-CTA","","","Brainomix 360 e-CTA","","","iSchemaView Rapid",""],["","","(K242123)","","","(K192692)","","","(K233582)",""],["Design: PACS\nfunctionality","View, process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and listing","","","Same","","","Same","",""],["Design: DICOM\ncompliance","Yes","","","Yes","","","Yes","",""],["Design: Computer\nPlatform","Standard off-the-shelf server or\nvirtual server","","","Same","","","Same","",""],["Design: Data\nacquisition","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities","","","Same","","","Same","",""],["Additional tools","Arterial input function\n(AIF)Venous output function\n(VOF) – CTA","","","Same","","","Same","",""],["Functional\noverview","Brainomix 360 e-CTA is a\nsoftware package that provides\nfor the study of changes of\ntissue in digital images\ncaptured by CTA. Brainomix\n360 e-CTA provides viewing\nand quantification for CTA\nimages.","","","Same","","","RAPID is a software package\nthat provides for the\nvisualization and study of\nchanges of tissue in digital\nimages captured by CT and MRI.\nRAPID provides viewing and\nquantification.","",""],["Materials","N/A – Software only device","","","Same","","","Same","",""],["Biocompatibility","N/A – Software only device","","","Same","","","Same","",""],["Sterility","N/A – Software only device","","","Same","","","Same","",""],["Electrical Safety","N/A – Software only device","","","Same","","","Same","",""],["Mechanical Safety","N/A – Software only device","","","Same","","","Same","",""],["Chemical Safety","N/A – Software only device","","","Same","","","Same","",""],["Thermal Safety","N/A – Software only device","","","Same","","","Same","",""],["Radiation Safety","N/A – Software only device","","","Same","","","Same","",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p12-t0","doc_id":"K242130","page_num":12,"bbox":[115.94,137.3,597.4,695.99],"n_rows":36,"n_cols":9,"columns":["Product","","","","Koios DS 3.0","","","Koios DS 3.6",""],"rows":[["Product","","","","Koios DS 3.0","","","Koios DS 3.6",""],["","","","","(K212616)","","","(subject device)",""],["","Physical","","","Software Package","","","Software Package",""],["","Characteristics","","","Operates on off-the-shelf hardware","","","Operates on off-the-shelf hardware",""],["","Storage","","","Storage not supported","","","Storage not supported",""],["","Image Input","","","DICOM","","","DICOM",""],["Characteristics","Characteristics","","","Decision support device used to assist","","","Decision support device used to assist in",""],["","","","","in the assessment and","","","the assessment and characterization of",""],["","","","","characterization of breast lesions and","","","breast lesions and thyroid nodules using US",""],["","","","","thyroid nodules using US image data.","","","image data.",""],["Intended\nUse/Indications\nfor Use","","","","Koios Decision Support (DS) is an","","","Koios Decision Support (DS) is an artificial",""],["","","","","artificial intelligence (AI)/machine","","","intelligence (AI)/machine learning (ML)-",""],["","","","","learning (ML)-based computer-aided","","","based computer-aided diagnosis (CADx)",""],["","","","","diagnosis (CADx) software device","","","software device intended for use as an",""],["","","","","intended for use as an adjunct to","","","adjunct to diagnostic ultrasound",""],["","","","","diagnostic ultrasound examinations of","","","examinations of lesions or nodules",""],["","","","","lesions or nodules suspicious for","","","suspicious for breast or thyroid cancer.",""],["","","","","breast or thyroid cancer.","","","",""],["","","","","","","","Koios DS allows the user to select or",""],["","","","","Koios DS allows the user to select or","","","confirm regions of interest (ROIs) within an",""],["","","","","confirm regions of interest (ROIs)","","","image representing a single lesion or",""],["","","","","within an image representing a single","","","nodule to be analyzed. The software then",""],["","","","","lesion or nodule to be analyzed. The","","","automatically characterizes the selected",""],["","","","","software then automatically","","","image data to generate an AI/ML-derived",""],["","","","","characterizes the selected image data","","","cancer risk assessment and selects",""],["","","","","to generate an AI/ML-derived cancer","","","applicable lexicon-based descriptors",""],["","","","","risk assessment and selects applicable","","","designed to improve overall diagnostic",""],["","","","","lexicon-based descriptors designed to","","","accuracy as well as reduce interpreting",""],["","","","","improve overall diagnostic accuracy","","","physician variability.",""],["","","","","as well as reduce interpreting","","","",""],["","","","","physician variability.","","","Koios DS software may also be used as an",""],["","","","","","","","image viewer of multi-modality digital",""],["","","","","Koios DS software may also be used","","","images, including ultrasound and",""],["","","","","as an image viewer of multi-modality","","","mammography. The software includes",""],["","","","","digital images, including ultrasound","","","tools that allow users to adjust, measure",""],["","","","","and mammography. The software","","","and document images, and output into a",""]],"caption_candidate":"6.Substantial Equivalence Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p13-t0","doc_id":"K242130","page_num":13,"bbox":[115.94,108.37,597.4,696.53],"n_rows":38,"n_cols":7,"columns":["","","includes tools that allow users to","","structured report.\nKoios DS software is designed to assist\ntrained interpreting physicians in analyzing\nthe breast ultrasound images of adult (>=\n22 years) female patients with soft tissue\nbreast lesions and/or thyroid ultrasounds\nof all adult (>= 22 years) patients with\nthyroid nodules suspicious for cancer.\nWhen utilized by an interpreting physician\nwho has completed the prescribed\ntraining, this device provides information\nthat may be useful in recommending\nappropriate clinical management.","",""],"rows":[["","","includes tools that allow users to","","structured report.\nKoios DS software is designed to assist\ntrained interpreting physicians in analyzing\nthe breast ultrasound images of adult (>=\n22 years) female patients with soft tissue\nbreast lesions and/or thyroid ultrasounds\nof all adult (>= 22 years) patients with\nthyroid nodules suspicious for cancer.\nWhen utilized by an interpreting physician\nwho has completed the prescribed\ntraining, this device provides information\nthat may be useful in recommending\nappropriate clinical management.","",""],["","","adjust, measure and document","","","",""],["","","images, and output into a structured","","","",""],["","","report.","","","",""],["","","","","","",""],["","","Koios DS software is designed to","","","",""],["","","assist trained interpreting physicians","","","",""],["","","in analyzing the breast ultrasound","","","",""],["","","images of adult (>= 22 years) female","","","",""],["","","patients with soft tissue breast lesions","","","",""],["","","and/or thyroid ultrasounds of all adult","","","",""],["","","(>= 22 years) patients with thyroid","","","",""],["","","nodules suspicious for cancer. When","","","",""],["","","utilized by an interpreting physician","","","",""],["","","who has completed the prescribed","","","",""],["","","training, this device provides","","","",""],["","","information that may be useful in","","","",""],["","","recommending appropriate clinical","","","",""],["","","management.","","","",""],["","","","","","",""],["Target Population\n(subset of above\nfor comparison\npurposes)","","Koios DS software is designed to","","Koios DS software is designed to assist\ntrained interpreting physicians in analyzing\nthe breast ultrasound images of adult (>=\n22 years) female patients with soft tissue\nbreast lesions and/or thyroid ultrasounds\nof all adult (>= 22 years) patients with\nthyroid nodules suspicious for cancer.","",""],["","","assist trained interpreting physicians","","","",""],["","","in analyzing the breast ultrasound","","","",""],["","","images of adult (>= 22 years) female","","","",""],["","","patients with soft tissue breast lesions","","","",""],["","","and/or thyroid ultrasounds of all adult","","","",""],["","","(>= 22 years) patients with thyroid","","","",""],["","","nodules suspicious for cancer.","","","",""],["Limitations for\nUse\n(subset of above\nfor comparison\npurposes)","","Limitations:","","","Limitations:",""],["","","•Patient management decisions","","","•Patient management decisions should",""],["","","should not be made solely on the","","","not be made solely on the results of the",""],["","","results of the Koios DS analysis.","","","Koios DS analysis.",""],["","","•Koios DS software is not to be used","","","•Koios DS software is not to be used for",""],["","","for the evaluation of normal tissue,","","","the evaluation of normal tissue, on sites of",""],["","","on sites of post-surgical excision, or","","","post-surgical excision, or images with",""],["","","images with doppler, elastography, or","","","doppler, elastography, or other overlays",""],["","","other overlays present in them.","","","present in them.",""],["","","•Koios DS software is not intended","","","•Koios DS software is not intended for use",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p14-t0","doc_id":"K242130","page_num":14,"bbox":[115.94,108.37,597.4,698.03],"n_rows":38,"n_cols":9,"columns":["","","","","for use on portable handheld devices","","on portable handheld devices (e.g.\nsmartphones or tablets) or as a primary\ndiagnostic viewer of mammography\nimages.\n•The software does not predict the\npresence of the thyroid nodule margin\ndescriptor, extra-thyroidal extension. In\nthe event that this condition is present, the\nuser may select this category manually\nfrom the margin descriptor list.","",""],"rows":[["","","","","for use on portable handheld devices","","on portable handheld devices (e.g.\nsmartphones or tablets) or as a primary\ndiagnostic viewer of mammography\nimages.\n•The software does not predict the\npresence of the thyroid nodule margin\ndescriptor, extra-thyroidal extension. In\nthe event that this condition is present, the\nuser may select this category manually\nfrom the margin descriptor list.","",""],["","","","","(e.g. smartphones or tablets) or as a","","","",""],["","","","","primary diagnostic viewer of","","","",""],["","","","","mammography images.","","","",""],["","","","","•The software does not predict the","","","",""],["","","","","presence of the thyroid nodule","","","",""],["","","","","margin descriptor, extra-thyroidal","","","",""],["","","","","extension. In the event that this","","","",""],["","","","","condition is present, the user may","","","",""],["","","","","select this category manually from the","","","",""],["","","","","margin descriptor list.","","","",""],["","Modality Used for","","","Breast Ultrasound Data","","","Breast Ultrasound Data",""],["","Analysis","","","Thyroid Ultrasound Data","","","Thyroid Ultrasound Data",""],["Input","Input","","","Medical images provided in a DICOM","","","Medical images provided in a DICOM",""],["","","","","format","","","format",""],["ROI\nRequirements","","","","Breast","","Breast\nThe software requires a user to select up to\ntwo ROIs, from up to two orthogonal\nviews, that represent a single lesion to be\nselected and processed.\nThyroid\nTwo ROIs that represent a single lesion to\nbe selected and processed are required for\nanalysis.\nThe first ROI is drawn on the transverse\nview of the nodule. The second is drawn on\nthe longitudinal view.","Breast",""],["","","","","The software requires a user to select","","","The software requires a user to select up to",""],["","","","","up to two ROIs, from up to two","","","two ROIs, from up to two orthogonal",""],["","","","","orthogonal views, that represent a","","","views, that represent a single lesion to be",""],["","","","","single lesion to be selected and","","","selected and processed.",""],["","","","","processed.","","","",""],["","","","","","","","Thyroid",""],["","","","","Thyroid","","","Two ROIs that represent a single lesion to",""],["","","","","Two ROIs that represent a single","","","be selected and processed are required for",""],["","","","","lesion to be selected and processed","","","analysis.",""],["","","","","are required for analysis.","","","",""],["","","","","","","","The first ROI is drawn on the transverse",""],["","","","","The first ROI is drawn on the","","","view of the nodule. The second is drawn on",""],["","","","","transverse view of the nodule. The","","","the longitudinal view.",""],["","","","","second is drawn on the longitudinal","","","",""],["","","","","view.","","","",""],["Output (Breast)","","","","Koios defined categorical and","","Koios defined categorical and continuous\noutputs (confidence level indicator) that\nalign to BI-RADS, U1-U5, and auto-\nclassified shape and orientation.","",""],["","","","","continuous outputs (confidence level","","","",""],["","","","","indicator) that align to BI-RADS, U1-","","","",""],["","","","","U5, and auto-classified shape and","","","",""],["","","","","orientation.","","","",""],["Output (Thyroid)","","","","Koios DS software automatically","","","Koios DS software automatically classifies",""],["","","","","classifies thyroid nodules suspicious","","","thyroid nodules suspicious for cancer",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p15-t0","doc_id":"K242130","page_num":15,"bbox":[115.94,108.37,597.4,403.11],"n_rows":19,"n_cols":7,"columns":["","","","","for cancer based on image data","","based on image data generating an output\naligned to either the TI-RADS or ATA\nclassification guidelines. The system\nautomatically generates user-modifiable\nnodule descriptors (Composition,\nEchogenicity, Shape, Margin, Echogenic\nFoci) and a direct, image-derived cancer\nrisk assessment that is translated into an\noptional lexicon-specific modifier."],"rows":[["","","","","for cancer based on image data","","based on image data generating an output\naligned to either the TI-RADS or ATA\nclassification guidelines. The system\nautomatically generates user-modifiable\nnodule descriptors (Composition,\nEchogenicity, Shape, Margin, Echogenic\nFoci) and a direct, image-derived cancer\nrisk assessment that is translated into an\noptional lexicon-specific modifier."],["","","","","generating an output aligned to either","",""],["","","","","the TI-RADS or ATA classification","",""],["","","","","guidelines. The system automatically","",""],["","","","","generates user-modifiable nodule","",""],["","","","","descriptors (Composition,","",""],["","","","","Echogenicity, Shape, Margin,","",""],["","","","","Echogenic Foci) and a direct, image-","",""],["","","","","derived cancer risk assessment that is","",""],["","","","","translated into an optional lexicon-","",""],["","","","","specific modifier.","",""],["","Comparative","","Metric: AUC\nCases: 900\nReaders: 15","Metric: AUC","","Metric: AUC\nCases: 900\nReaders: 15"],["","Clinical","","","Cases: 900","",""],["","Performance","","","Readers: 15","",""],["","Testing (Breast)","","","","",""],["","Comparative","","Metric: AUC\nCases: 650\nReaders: 15","","","Metric: AUC\nCases: 650\nReaders: 15"],["","Clinical","","","","",""],["","Performance","","","","",""],["","Testing (Thyroid)","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p16-t0","doc_id":"K242130","page_num":16,"bbox":[102.98,466.75,535.06,700.54],"n_rows":3,"n_cols":3,"columns":["","Koios DS 3.0 K212616","Koios DS 3.6 K242130"],"rows":[["","Koios DS 3.0 K212616","Koios DS 3.6 K242130"],["Diagnostic Engine","Breast (v 1.1.0)\nThyroid (v2.2.0)","Breast (v. 3.0.0)\nThyroid (v. 2.2.0)"],["Workflow Enhancements","Breast Smart Click\nBreast Smart Calipers\nThyroid Smart Calipers","Breast Smart Click\nBreast Smart Calipers\nThyroid Smart Click\nThyroid Smart Calipers\nImage Registration and\nMatching"]],"caption_candidate":"Technological Characteristics Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p21-t0","doc_id":"K242130","page_num":21,"bbox":[102.98,108.66,656.37,334.85],"n_rows":3,"n_cols":3,"columns":["5.Single Image vs Orthogonal\nImage Pair","Single Image: 0.914 [0.910 -\n0.918]\nOrthogonal Pair: 0.929 [0.913,\n0.945]","Single Image: 0.932 [+/- 0.003]"],"rows":[["5.Single Image vs Orthogonal\nImage Pair","Single Image: 0.914 [0.910 -\n0.918]\nOrthogonal Pair: 0.929 [0.913,\n0.945]","Single Image: 0.932 [+/- 0.003]"],["6.Assessment of Categorical\nAgreement – Shape\n(prior results continue to apply)","0.738 [0.679, 0.797]",""],["7.Assessment of Categorical\nAgreement – Orientation\n(prior results continue to apply)","0.744 [0.675, 0.813]",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p22-t0","doc_id":"K242130","page_num":22,"bbox":[102.98,108.66,656.37,514.4],"n_rows":2,"n_cols":3,"columns":["8.Operating Point","PLR:\nSystem= 2.52 [2.26, 2.79]\nNLR:\nSystem=0.04 [0.02, 0.07]\nPPV:\nSystem= 0.70 [0.67, 0.73]\nNPV:\nSystem= 0.96 [0.94, 0.98]","PLR:\nSystem= 2.661 [2.338, 2.984]\nNLR:\nSystem= 0.039 [0.013, 0.064]\nPPV:\nSystem= 0.708 [0.672, 0.743]\nNPV:\nSystem= 0.966 [0.944, 0.988]"],"rows":[["8.Operating Point","PLR:\nSystem= 2.52 [2.26, 2.79]\nNLR:\nSystem=0.04 [0.02, 0.07]\nPPV:\nSystem= 0.70 [0.67, 0.73]\nNPV:\nSystem= 0.96 [0.94, 0.98]","PLR:\nSystem= 2.661 [2.338, 2.984]\nNLR:\nSystem= 0.039 [0.013, 0.064]\nPPV:\nSystem= 0.708 [0.672, 0.743]\nNPV:\nSystem= 0.966 [0.944, 0.988]"],["9.Data Set Drift Analysis -\nMalignancy Risk Classifier AUC","ROCAUC = 0.930 [0.914, 0.946]","ROCAUC = 0.949 [0.936, 0.962]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p29-t0","doc_id":"K242130","page_num":29,"bbox":[48.96,72.53,517.77,718.52],"n_rows":5,"n_cols":2,"columns":["1: No Match Rate","No Match Rate = 0.32%"],"rows":[["1: No Match Rate","No Match Rate = 0.32%"],["2: Match Time","Average Time for Study Preprocessing: 2.39 +/- 0.48\nseconds\nAverage Time for Image Matching: 0.22 +/- 0.12\nseconds\nNote: The average study size which was processed in\nthis experiment was 53 +/- 11 images. The measured\ndurations scale roughly linearly with study size."],["3: End-to-End Breast Engine Performance","AUC = 0.946\nSensitivity = 0.975\nSpecificity = 0.637"],["4: End-to-End Thyroid Engine Performance","AUC = 0.801\nSensitivity = 0.670\nSpecificity = 0.603"],["5: Breast Image Matching Outcomes","Successful Match:\nCount: 2018\nFraction: 0.995\nNo Match:\nCount: 10\nFraction: 0.005\nIncorrect Match:"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p30-t0","doc_id":"K242130","page_num":30,"bbox":[48.96,72.53,517.77,694.76],"n_rows":4,"n_cols":2,"columns":["","Count: 0\nFraction: 0.000\nIncorrect Image:\nCount: 0\nFraction: 0.000"],"rows":[["","Count: 0\nFraction: 0.000\nIncorrect Image:\nCount: 0\nFraction: 0.000"],["6: Breast Image Matching DICE Coefficient","DICE = 0.995 =/- 0.005"],["7: Thyroid Image Matching Outcomes","Successful Match:\nCount: 1288\nFraction: 1.000\nNo Match:\nCount: 0\nFraction: 0.000\nIncorrect Match:\nCount: 0\nFraction: 0.000\nIncorrect Image:\nCount: 0\nFraction: 0.000"],["8: Thyroid Image Matching DICE Coefficient","DICE = 0.996 =/- 0.004"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p33-t0","doc_id":"K242130","page_num":33,"bbox":[71.62,134.15,480.26,473.98],"n_rows":34,"n_cols":18,"columns":["Reader\nID","","","Board\nCertification/\nSpecialty","","","","Breast","","Years of\nExperience –\nMammography\nand/or Breast\nUltrasound","","","Academic\nInstitution\nAffiliation\n(Yes/No)","","","MQSA\nQualified\nInterpreting\nPhysician","",""],"rows":[["Reader\nID","","","Board\nCertification/\nSpecialty","","","","Breast","","Years of\nExperience –\nMammography\nand/or Breast\nUltrasound","","","Academic\nInstitution\nAffiliation\n(Yes/No)","","","MQSA\nQualified\nInterpreting\nPhysician","",""],["","","","","","","","Fellowship","","","","","","","","","",""],["","","","","","","","Trained","","","","","","","","","",""],["","","","","","","","and/or","","","","","","","","","",""],["","","","","","","","Dedicated","","","","","","","","","",""],["","","","","","","","Breast Imager","","","","","","","","","",""],["1","","","","Diagnostic","","No","","","13 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["2","","","","Diagnostic","","No","","","4 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["3","","","","Diagnostic","","Yes","","","7 years","","","Yes","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["4","","","","Breast","","No","","","0 years","","","No","","","No","",""],["","","","","Surgeon","","","","","","","","","","","","",""],["","5","","","OB/GYN","","","No","","","20 years","","","No","","","No",""],["6","","","","Diagnostic","","No","","","13 years","","","Yes","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["7","","","","Diagnostic","","No","","","3 years","","","Yes","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["","8","","","OB/GYN","","","No","","","0 years","","","No","","","No",""],["9","","","","Diagnostic","","Yes","","","15 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["10","","","","Diagnostic","","No","","","13 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["11","","","","Diagnostic","","Yes","","","30 years","","","No","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["12","","","","Diagnostic","","Yes","","","10 years","","","Yes","","","Yes","",""],["","","","","Radiology","","","","","","","","","","","","",""],["13","","","","Diagnostic","","No","","","0 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["14","","","","Interventional","","No","","","4 years","","","No","","","No","",""],["","","","","Radiology","","","","","","","","","","","","",""],["15","","","","Breast","","No","","","25 years","","","Yes","","","No","",""],["","","","","Surgeon","","","","","","","","","","","","",""]],"caption_candidate":"Reader Background","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p37-t0","doc_id":"K242130","page_num":37,"bbox":[52.36,404.42,348.18,707.88],"n_rows":19,"n_cols":3,"columns":["Reader","","Experience (post-"],"rows":[["Reader","","Experience (post-"],["","Reader Category",""],["ID","","residency)"],["","",""],["R1","Domestic Endocrinologist (End)","< 10 years"],["R2","Domestic Radiologist (Rad)","≥ 20 years"],["R3","Domestic Rad","≥ 20 years"],["R4","Domestic Rad","≥ 10 and < 20 years"],["R5","Domestic Rad","≥ 10 and < 20 years"],["R6","Domestic Rad","≥ 10 and < 20"],["R7","Domestic Rad","≥ 20 years"],["R8","Domestic Rad","< 10 years"],["R9","Domestic Rad","≥ 20 years"],["R10","Domestic Rad","≥ 20 years"],["R11","Domestic End","< 10 years"],["R12","European Rad","≥ 20 years"],["R13","European Rad","≥ 20 years"],["R14","European End","≥ 20 years"],["R15","European End","≥ 20 years"]],"caption_candidate":"Reader Experience","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p42-t0","doc_id":"K242130","page_num":42,"bbox":[26.88,72.48,525.7,711.1],"n_rows":8,"n_cols":3,"columns":["FNA","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(US readers, US data)","+0.053 [0.026, 0.080] (sensitivity)\n+0.180 [0.161, 0.198] (specificity)"],"rows":[["FNA","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(US readers, US data)","+0.053 [0.026, 0.080] (sensitivity)\n+0.180 [0.161, 0.198] (specificity)"],["","Change in average Sensitivity and\nSpecificity of Follow-up with Koios DS\n(EU readers, EU data)","+0.060 [-0.009, 0.129] (sensitivity)\n+0.296 [0.238, 0.354] (specificity)"],["Secondary Analysis 3","Change in average AUC with Koios DS\n(EU Readers, EU Data)","+0.079 [0.024, 0.134] (parametric)\n+0.066 [0.014, 0.118] (non-parametric)"],["Secondary Analysis 4","Inter-Reader Variability measuring the\nassociation of TI-RADS points assigned\nwith and without decision support\nDifference (Relative Change %)","40.7% (all readers, all data)\n37.4% (US readers, US data)\n49.7% (EU Readers, EU Data)"],["Secondary Analysis 5","Impact on Interpretation Time","-23.6% (all readers, all data)\n-22.7% (US readers, US data)\n-32.4% (EU Readers, EU Data)"],["Secondary Analysis 6","Change in average AUC with Koios DS\ndescriptor classifiers only (without AI\nAdapter) (parametric)","+0.022 [0.005, 0.039]\n(all readers, all data)\n+0.017 [-0.007, 0.041]\n(US readers, US data)\n+0.010 [-0.051, 0.071]\n(EU Readers, EU Data)"],["","Change in average AUC with Koios DS\ndescriptor classifiers only (without AI\nAdapter) (non-parametric)","+0.019 [0.001, 0.037]\n(all readers, all data)\n+0.015 [-0.010, 0.039]\n(US readers, US data)\n+0.004 [-0.054, 0.062]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of FNA with Koios DS\ndescriptor classifiers only (without AI\nAdapter)","Sensitivity:\n+0.052 [0.022, 0.081]\n(all readers, all data)\n+0.026 [-0.014, 0.066]\n(US readers, US data)\n+0.109 [-0.004, 0.221]\n(EU Readers, EU Data)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p43-t0","doc_id":"K242130","page_num":43,"bbox":[26.88,72.48,525.7,709.9],"n_rows":3,"n_cols":3,"columns":["","","Specificity\n-0.009 [-0.024, 0.006]\n(all readers, all data)\n-0.001 [-0.022, 0.019]\n(US readers, US data)\n-0.032 [-0.095, 0.031]\n(EU Readers, EU Data)"],"rows":[["","","Specificity\n-0.009 [-0.024, 0.006]\n(all readers, all data)\n-0.001 [-0.022, 0.019]\n(US readers, US data)\n-0.032 [-0.095, 0.031]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of Follow-up with Koios DS\ndescriptor classifiers only (without AI\nAdapter) – excluding cases\nrecommended for FNA","Sensitivity\n0.079 [0.031, 0.128]\n(all readers, all data)\n0.072 [0.008, 0.135]\n(US readers, US data)\n0.133 [-0.068, 0.334]\n(EU Readers, EU Data)\nSpecificity\n0.015 [-0.010, 0.040]\n(all readers, all data)\n0.012 [-0.021, 0.045]\n(US readers, US data)\n0.010 [-0.093, 0.113]\n(EU Readers, EU Data)"],["","Change in average sensitivity and\nspecificity of Follow-up with Koios DS\ndescriptor classifiers only (without AI\nAdapter) – including cases\nrecommended for FNA","Sensitivity\n+0.047 [0.026, 0.067]\n(all readers, all data)\n+0.037 [0.009, 0.065]\n(US readers, US data)\n+0.067 [0.000, 0.134]\n(EU Readers, EU Data)\nSpecificity\n+0.000 [-0.013, 0.012]\n(all readers, all data)\n+0.003 [-0.014, 0.019]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242130-p44-t0","doc_id":"K242130","page_num":44,"bbox":[21.48,194.54,502.51,610.42],"n_rows":7,"n_cols":4,"columns":["","All Readers, All Data","US Readers, US Data","EU Readers, EU Data"],"rows":[["","All Readers, All Data","US Readers, US Data","EU Readers, EU Data"],["Change in average Sensitivity/Specificity of FNA","","",""],["TI-RADS categorization\nw/AI Adapter + size\ncriteria","+0.084 [0.054, 0.113]\n(sensitivity)\n+0.140 [0.125, 0.155]\n(specificity)","+0.058 [0.017, 0.098]\n(sensitivity)\n+0.130 [0.110, 0.151]\n(specificity)","+0.125 [0.014, 0.237]\n(sensitivity)\n+0.171 [0.109, 0.233]\n(specificity)"],["TI-RADS categorization +\nsize criteria","+0.052 [0.022, 0.081]\n(sensitivity)\n-0.009 [-0.024, 0.006]\n(specificity)","+0.026 [-0.014, 0.066]\n(sensitivity)\n-0.001 [-0.022, 0.019]\n(specificity)","+0.109 [-0.004, 0.221]\n(sensitivity)\n-0.032 [-0.095, 0.031]\n(specificity)"],["Change in average Sensitivity/Specificity of Follow-up","","",""],["TI-RADS categorization\nw/AI Adapter + size\ncriteria","+0.060 [0.040, 0.080]\n(sensitivity)\n+0.206 [0.192, 0.219]\n(specificity)","+0.053 [0.026, 0.080]\n(sensitivity)\n+0.180 [0.161, 0.198]\n(specificity)","+0.060 [-0.009, 0.129]\n(sensitivity)\n+0.296 [0.238, 0.354]\n(specificity)"],["TI-RADS categorization +\nsize criteria","+0.047 [0.026, 0.067]\n(sensitivity)\n+0.000 [-0.013, 0.012]\n(specificity)","+0.037 [0.009, 0.065]\n(sensitivity)\n+0.003 [-0.014, 0.019]\n(specificity)","+0.067 [0.000, 0.134]\n(sensitivity)\n-0.012 [-0.065, 0.041]\n(specificity)"]],"caption_candidate":"Summary of System Clinical Performance Using TI-RADS RSS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p7-t0","doc_id":"K242166","page_num":7,"bbox":[72.26,123.14,523.18,338.93],"n_rows":6,"n_cols":2,"columns":["Measurement","Results"],"rows":[["Measurement","Results"],["Distance\nmeasurement","Distance between two points in mm"],["(Open) spline","Distance over a non-straight trajectory in mm"],["Closed spline","Area in mm², perimeter, area derived diameter, perimeter\nderived diameter, min diameter and max diameter all in mm"],["Angle","Angle in degrees"],["Hounsfield probe (3D\nMarker)","The HU (Hounsfield unit) of the underlying pixel"]],"caption_candidate":"is within 5% of the true value.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p8-t0","doc_id":"K242166","page_num":8,"bbox":[22.33,268.73,582.46,557.47],"n_rows":9,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["Device name","TribusConnect","","","RemotEye Viewer","","","TruPlan Computed\nTomography (CT)\nImaging Software","",""],["Device manufacturer","TribusMed BV","","","NeoLogica s.r.l.","","","Circle Cardiovascular\nImaging Inc.","",""],["510(k) number","K242166","","","K141061","","","K222593","",""],["Regulation name","Medical image\nmanagement and\nprocessing system","","","Picture archiving and\ncommunications system","","","Medical image\nmanagement and\nprocessing system","",""],["Regulation Number","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["Product code","QIH","","","LLZ","","","QIH, LLZ","",""],["Regulatory Class","II","","","II","","","II","",""]],"caption_candidate":"Device comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p9-t0","doc_id":"K242166","page_num":9,"bbox":[22.37,72.36,582.41,548.47],"n_rows":3,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["Intended use","TribusConnect is a cloud-\nbased DICOM viewer\ndesigned for medical\nprofessionals to securely\naccess, review,\nmanipulate, measure and\nvisualize DICOM images.\nThe software is intended\nto be used by trained\nhealthcare professionals,\nincluding but not limited\nto radiologists,\nphysicians, nurses, and\ntechnicians.","","","The RemotEye Viewer\nsoftware product is\nintended to be used as a\nfunctional, web based\nmedical image viewer to\ndownload, review,\ninterpret, manipulate,\nvisualize and print\nmedical multi-modality\nimage data in DICOM\nformat also stored in\nremote locations with\nrespect to the viewing\nsite. When interpreted by\na trained physician, the\nmedical images\ndisplayed by RemotEye\nViewer can be used as an\nelement for diagnosis.\nTypical users of\nRemotEye Viewer are\ntrained professionals,\nincluding but not limited\nto radiologists,\nphysicians, nurses and\ntechnicians.","","","TruPlan enables\nvisualization and\nmeasurement of\nstructures of the heart\nand vessels for:\n- Pre-procedural\nplanning and sizing for\nthe left atrial appendage\nclosure (LAAC)\nprocedure\n- Post-procedural\nevaluation for the LAAC\nprocedure","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p10-t0","doc_id":"K242166","page_num":10,"bbox":[22.37,72.36,582.41,769.06],"n_rows":3,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["Indications for use","TribusConnect is a\nmedical image\nmanagement and\nprocessing device which\nfacilitates remote viewing\non different locations of\nCT images stored in\nDICOM format, allowing\nhealthcare professionals\nto access, review,\nmanipulate, measure and\nvisualize\nsimulated patient data\nfrom different sources.\nTribusConnect is suitable\nfor, but not limited to, pre-\nprocedural planning of\ncardiac interventions and\npost procedural analysis\nof cardiac interventions.\nTo facilitate the above,\nTribusConnect uses CT\nDICOM data to output\nvolume renderings, ML-\nbased heart\nsegmentation, a\nsimulated fluoroscopy\nview, endo views, MIP and\nMPR views.\nMeasurements can only\nbe performed on MPR\nviews.\nTribusConnect is not\nintended for diagnostic\nuse on mobile displays.\nTribusConnect is not\nintended to serve as the","","","The RemotEye Viewer\nsoftware product is\nintended to be used as a\nfunctional, web based\nmedical image viewer to\ndownload, review,\ninterpret, manipulate,\nvisualize and print\nmedical multi-modality\nimage data in DICOM\nformat also stored in\nremote locations with\nrespect to the viewing\nsite. When interpreted by\na trained physician, the\nmedical images\ndisplayed by RemotEye\nViewer can be used as an\nelement for diagnosis.\nTypical users of\nRemotEye Viewer are\ntrained professionals,\nincluding but not limited\nto radiologists,\nphysicians, nurses and\ntechnicians.","","","TruPlan enables\nvisualization and\nmeasurement of\nstructures of the heart\nand vessels for:\n- Pre-procedural\nplanning and sizing for\nthe left atrial appendage\nclosure (LAAC)\nprocedure\n- Post-procedural\nevaluation for the LAAC\nprocedure","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p11-t0","doc_id":"K242166","page_num":11,"bbox":[22.35,72.36,582.44,721.54],"n_rows":5,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["","primary archive for\nmedical imaging data.\nTribusConnect is an\nadjunct tool and is not\nintended to replace a\nphysician’s own review on\nthe images.\nThe intended patient\npopulation is comprised\nof adult patients (22 years\nof age and older)","","","","","","","",""],["Patient population","The intended patient\npopulation is comprised\nof adult patients (22 years\nof age and older)","","","No limitations in 510(k) or\nIFU\nSimilar, The fact that a\nportion of the population\nis not within the scope of\nTribusConnect does not\nintroduce new risks.","","","TruPlan’s intended\npatient population is\ncomprised of adult\npatients.\nSame","",""],["Input data","CT (In DICOM format)","","","Multi modality DICOM\ncompliant (Including CT)\nSimilar, more supported\nmodalities","","","CT (In DICOM format)\nSame","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p12-t0","doc_id":"K242166","page_num":12,"bbox":[22.34,72.36,582.45,753.58],"n_rows":6,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["Patient study\nmanagement","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search","","","• Study/series previewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search\nSame","","","• Study/series\npreviewing\n• Exporting\n• Deleting\n• Anonymizing\n• Search\nSame","",""],["Measurement\nfunctionality","• Distance (length,\ndiameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity","","","Advanced distance, area,\nangle and density\nmeasurement tools\n(including SUV for PET\nimages), plus several\ngraphical annotation\ntools.\nMeasurement of CTR\n(Cardio-Thoracic Ratio)\nalso supported.\nSame","","","• Distance (length,\ndiameter,\nperimeter)\n• Area\n• Angle\n• Signal intensity\n• Coordinates\nSame","",""],["Visualization/rendering","• 2D\n• 3D\n• 4D\n• MPR\n• Annotations\n• Segmented 3D volume","","","• 2D\n• 3D\n• MPR / MIP / MinIP /AvgIP\n• Annotations\nSimilar. No information\ncould be found whether\n4D is supported, since 4D\nas implemented in\nTribusConnect and\nTruPlan is a sequence of\n3D images played in a\nmovie, this will not\nintroduce a new risk","","","• 2D\n• 3D\n• 4D\n• MPR\n• MIP\n• Annotations\n• Segmented 3D volume\nSame","",""],["Segmentations","ML based segmentation\nof all heart chambers,\naorta, pulmonary trunk\nand vena cava","","","No segmentation","","","ML based segmentation\nleft atrium, left ventricle,\nleft atrial appendage\nand the aorta. (Left","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p13-t0","doc_id":"K242166","page_num":13,"bbox":[22.34,72.36,582.45,753.58],"n_rows":6,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["","","","","","","","heart)\nManual sculpting\nSimilar, The same\nunderlying technique is\nused the algorithm in\nTribusConnect is trained\nto identify more\nstructures, this does not\nintroduce new risks.\nAbsence of the sculpting\nfeature does not\nintroduce new risks.","",""],["Left atrial appendage\nlocalization","Semi-Automated\nLocalization of LAA\nappendage","","","No such functionality","","","Localization of LAA\nappendage\nSimilar, since\nTribusConnect does not\nautomatically suggest\nmeasurements like\nTruPlan, no new risks are\nintroduced.","",""],["Session saving","Analysis is stored in a\n“Saved session”","","","DICOM presentation\nstates and Key note\nimages\nSimilar, the saved\nsessions in\nTribusConnect also\ncontain information\nabout the orientation of\nthe MPR planes and\nvolumes, this does not\nintroduce new risks","","","Analysis is saved in a\nsaved session.\nSame","",""],["Collaboration","Shared sessions","","","Cloud-based peer-to-\npeer image sharing\nfunctionalities.","","","Sessions are saved on a\ncentral location and\navailable for other users.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242166-p14-t0","doc_id":"K242166","page_num":14,"bbox":[22.34,72.36,582.45,719.62],"n_rows":6,"n_cols":10,"columns":["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],"rows":[["","","TribusConnect","","","RemotEye Viewer","","","TruPlan",""],["","","(Subject device)","","","(Primary Predicate)","","","(Secondary Predicate)",""],["","","","","Same","","","Similar, work can be\nshared via a saved\nsession, but no “live”\nimage sharing, this does\nnot introduce new risks","",""],["Upload of data","File system based upload\nof DICOM files.","","","DICOM protocol and\nimport from disk\nSame","","","Supports DICOM\nconnectivity and file-\nsystem based upload of\nimage data.\nSame","",""],["Storage of data","Cloud","","","Cloud\nSame","","","Laptop, on-premise\nserver\nSimilar, an on-premise\nserver is not necessarily\naccessible via the\ninternet, the risks\nintroduced by the cloud\ncomponent are handled\nin the cyber security risk\nassessment and\ndeemed acceptable","",""],["Technical environment","Cloud based zero\nfootprint viewer, users\ncan access the viewer\nthrough a standard web\nbrowser on their\ndesktops, laptops, or\nmobile devices.","","","RemotEye Viewer is\ncompatible with\nWindows, Mac OS X and\nLinux clients.\nSimilar, TribusConnect is\nsupported on more\ndevices, the possible\nrisks introduced by this\nare evaluated as part of\nthe risk management\nactivities and deemed\nacceptable","","","Windows/Apple based\ndesktop/laptop\napplication.\nSimilar, TribusConnect\nis supported on more\ndevices and cloud\nbased, the possible risks\nintroduced by this are\nevaluated as part of the\nrisk management\nactivities and deemed\nacceptable","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p8-t0","doc_id":"K242168","page_num":8,"bbox":[216.92,137.7,553.36,692.1],"n_rows":2,"n_cols":7,"columns":["","","MHD","","","Anal Sphincter",""],"rows":[["","","MHD","","","Anal Sphincter",""],["Summary\ntest\nStatistics","","","","","",""]],"caption_candidate":"MHD (valsava manoeuver detection) and Anal sphincter:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p12-t0","doc_id":"K242168","page_num":12,"bbox":[217.0,82.14,553.35,379.73],"n_rows":2,"n_cols":3,"columns":["","","independent reviewers, with\nat least two being US\nCertified sonographers, with\nextensive clinical experience."],"rows":[["","","independent reviewers, with\nat least two being US\nCertified sonographers, with\nextensive clinical experience."],["Independ\nence of\nTest data","To ensure separation of\ntrain and test data,\nfollowing steps were\nundertaken:\nPost model development,\nwe acquired consecutive\ndata from previously\nunseen sites to test the\nrobustness of the algorithm\non new data distributions.\nWe also collected\nconsecutive data\n(separately) from sites that\nhad contributed to the\ntrain pool as well.","To ensure separation of train\nand test data, following steps\nwere undertaken:\nPost model development, we\nacquired data from\npreviously unseen (in train\npool) systems as well as\nnew/unseen sites to test the\nrobustness of the algorithm\non new data distributions."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p12-t1","doc_id":"K242168","page_num":12,"bbox":[217.0,422.97,553.35,707.14],"n_rows":2,"n_cols":4,"columns":["","","SonoAVC Follicle 2.0",""],"rows":[["","","SonoAVC Follicle 2.0",""],["Summary test\nStatistics","","",""]],"caption_candidate":"AI Testing Summary for updated feature SonoAVC Follicle 2.0:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p13-t0","doc_id":"K242168","page_num":13,"bbox":[217.0,82.24,553.38,609.28],"n_rows":3,"n_cols":2,"columns":["","For various confounders the individual accuracy\nnumbers are as follows:\nProbe wise distribution:\nRIC5-9 – 94.6%\nRIC10 – 93,6%\nRIC6-12 – 90.6%\nGeographical distribution:\nGermany – 92.2%\nIndia – 95.1%\nSpain – 94.7%\nU.K. – 95.5%"],"rows":[["","For various confounders the individual accuracy\nnumbers are as follows:\nProbe wise distribution:\nRIC5-9 – 94.6%\nRIC10 – 93,6%\nRIC6-12 – 90.6%\nGeographical distribution:\nGermany – 92.2%\nIndia – 95.1%\nSpain – 94.7%\nU.K. – 95.5%"],["",""],["Confounders","The test cohort consists of multiple sets – Set 1 is\nacquired together with the train data set and\nremaining sets (2-5) are acquired post model\ndevelopment.\nFor set 1 – the size distribution of follicles (measured\nas the largest 3D diameter) is detailed below:\n3-5 mm: 31%\n5-10 mm: 40%\n10-15 mm: 21%\n>15 mm: 8%\nThe above is in line with the clinical prevalence of the\nfollicle sizes.\nThe above, together with data from diverse probes and\ndifferent sites ensure sufficient diversity is captured in\nterms of acquisition settings, image quality as well as\npatient demographics.\nThe performance matrix for the various size ranges\nfor follicles is as follows.\nSize Range Dice\n(mm) Coefficient\n3-5 0.937619\n5-10 0.946289\n10-15 0.962315\n>15 0.93206"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p13-t1","doc_id":"K242168","page_num":13,"bbox":[328.18,514.0,455.48,595.7],"n_rows":6,"n_cols":6,"columns":["","Size Range","","Dice\nCoefficient","",""],"rows":[["","Size Range","","Dice\nCoefficient","",""],["","(mm)","","","",""],["","3-5","","","0.937619",""],["","5-10","","","0.946289",""],["","10-15","","","0.962315",""],["",">15","","","0.93206",""]],"caption_candidate":"for follicles is as follows.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p14-t0","doc_id":"K242168","page_num":14,"bbox":[216.94,81.83,553.38,670.63],"n_rows":2,"n_cols":2,"columns":["Data Collection","Data is provided by external clinical partners who de-\nidentified the data before sharing it with us. Original\ndata is collected in the form of 3D volumes in *.vol1 or\n*.4dv2 data formats. This preserves the flexibility to re-\nprocess data to our needs retrospectively during scan\nconversion3.\nTrain Data Distribution:\nTotal Volumes: 249\n- Distribution by Systems: Voluson E8 (20),\nVoluson E10 (131), Voluson P8 (29), Voluson\nS10 (48), Voluson S8 (21)\n- Distribution by Probes: RIC5-9A-RS (98), RIC5-\n9-D (149), RIC6-12-D (2)\n- Distribution by Countries: India (62), Germany\n(29), United Kingdom (29), Spain (103)\nTest Data Distribution\nTotal Datasets: 138\nTotal follicle count across all volumes: 2708\n- Distribution by Systems: Voluson E22 (63), E10\n(32), Voluson E8 (20), Voluson P8 (8), Voluson\nS10 (12), Voluson S8 (3)\n- Distribution by Probes: RIC5-9 (84), RIC10 (37),\nRIC6-12 (17)\n- Distribution by Countries: Germany (54), India\n(11), Spain (43), United Kingdom (7); USA (23)"],"rows":[["Data Collection","Data is provided by external clinical partners who de-\nidentified the data before sharing it with us. Original\ndata is collected in the form of 3D volumes in *.vol1 or\n*.4dv2 data formats. This preserves the flexibility to re-\nprocess data to our needs retrospectively during scan\nconversion3.\nTrain Data Distribution:\nTotal Volumes: 249\n- Distribution by Systems: Voluson E8 (20),\nVoluson E10 (131), Voluson P8 (29), Voluson\nS10 (48), Voluson S8 (21)\n- Distribution by Probes: RIC5-9A-RS (98), RIC5-\n9-D (149), RIC6-12-D (2)\n- Distribution by Countries: India (62), Germany\n(29), United Kingdom (29), Spain (103)\nTest Data Distribution\nTotal Datasets: 138\nTotal follicle count across all volumes: 2708\n- Distribution by Systems: Voluson E22 (63), E10\n(32), Voluson E8 (20), Voluson P8 (8), Voluson\nS10 (12), Voluson S8 (3)\n- Distribution by Probes: RIC5-9 (84), RIC10 (37),\nRIC6-12 (17)\n- Distribution by Countries: Germany (54), India\n(11), Spain (43), United Kingdom (7); USA (23)"],["Truthing process\nfor training dataset","To ensure correct and reliable “truthing” process of the\ntraining data we followed a two-step approach.\nIn the 1st step, a detailed curation protocol (developed\nby clinical experts) was shared with the curators, and\nthey were trained and instructed to follow the same.\nAs an automated quality control step, we confirm the\navailability of all the required masks/markings in each\nof the curated views. Missing masks or inconsistent\nlabels are reported back to the curators and the\ndatasets not used for training/development until all\nmasks are available and consistently labelled.\nIn addition, during and after the data curation process,\na arbitrator reviews all the datasets and curations from\neach curator’s completed data pool for their clinical\naccuracy. In case that any inconsistencies are detected,\nan optimal curation strategy is discussed and\ncommunicated back to the entire curation team.\n,"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p15-t0","doc_id":"K242168","page_num":15,"bbox":[217.0,82.24,553.35,427.69],"n_rows":2,"n_cols":2,"columns":["Truthing process\nfortest data","For Evaluation pool:\nThe evaluation was based on interpretation of the AI\noutput by reviewing clinicians. The evaluation was\nconducted by three independent reviewers, with at\nleast two being US Certified sonographers, with\nextensive clinical experience."],"rows":[["Truthing process\nfortest data","For Evaluation pool:\nThe evaluation was based on interpretation of the AI\noutput by reviewing clinicians. The evaluation was\nconducted by three independent reviewers, with at\nleast two being US Certified sonographers, with\nextensive clinical experience."],["Independence of\nTest data","To ensure separation of train and test data, following\nsteps were undertaken:\n1. Post acquiring the data at the start of the\nmodel development – the entire data pool\nwas split into train / validation and test\ndatasets ensuring that there is uniqueness in\nthe patient representation in each set – i.e. a\nsingle patient is present only in one of the\nthree groups. Also, it was attempted that\nthere is a representation of as many\ngeographical sites as possible in both the test\nand train pool. Beyond these two constraints,\nthe data was split randomly.\n2. Post model development, we acquired\nconsecutive data from previously unseen (in\ntrain pool) systems as well as new/unseen\nprobe to test the robustness of the algorithm\non new data distributions."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p15-t1","doc_id":"K242168","page_num":15,"bbox":[217.0,497.94,553.35,712.82],"n_rows":2,"n_cols":4,"columns":["","","2nd Trimester SonoLyst/SonolysLive",""],"rows":[["","","2nd Trimester SonoLyst/SonolysLive",""],["Summary test\nStatistics","","",""]],"caption_candidate":"SonoLyst/SonoLystlive","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p16-t0","doc_id":"K242168","page_num":16,"bbox":[216.96,82.14,553.38,684.73],"n_rows":3,"n_cols":2,"columns":["Confounders","In order to demonstrate the generalization\nperformance of the algorithm, the quantitative\nevaluation is performed for two subgroups: a data set\ncontaining of a variety of ultrasound systems and data\nformats against a data set containing the target\nplatform. For both subgroups the acceptance criteria\na re met."],"rows":[["Confounders","In order to demonstrate the generalization\nperformance of the algorithm, the quantitative\nevaluation is performed for two subgroups: a data set\ncontaining of a variety of ultrasound systems and data\nformats against a data set containing the target\nplatform. For both subgroups the acceptance criteria\na re met."],["Data Collection","- Systems: GEHC Voluson V730, E6, E8, E10,\nSiemens S2000 and Hitachi Aloka\n- Formats: Still images were obtained in DICOM\n& JPEG format, cine loops in RAW data\nformat.\n- Countries: UK, Austria, India and USA\n- Total number of images: 2.2M\n- Total number of cine loops: 3595"],["Truthing process\nfor training\ndatasets","To ensure the quality of the curated data for\nverification, the following strategy is employed:\nemployed\n1. The images were curated (sorted and graded)\nby a single sonographer\n2. The images were sorted and graded by\nScanNav AutoCapture Second Trimester.\nThis process resulted in some images being\nreclassified during sorting.\n3. Where they differed from the ground truth,\nthe sorted images from step 2 were reviewed\nby a 5-sonographer review panel, in order to\ndetermine the sorting accuracy of the system.\nThe sorting process resulted in some images\nbeing reclassified based upon the majority\nview of the panel.\n4. Where they differed from the ground truth,\nthe graded images from step 1 were reviewed\nby a 5-sonographer review panel, in order to\ndetermine the grading accuracy of the system"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p17-t0","doc_id":"K242168","page_num":17,"bbox":[217.0,82.24,553.36,235.69],"n_rows":2,"n_cols":2,"columns":["Truthing process\nfor Test datasets","For Evaluation pool:\nThe evaluation was based on interpretation of the AI\noutput by reviewing clinicians. The evaluation was\nconducted by three independent reviewers, with at\nleast two being US Certified sonographers, with\nextensive clinical experience."],"rows":[["Truthing process\nfor Test datasets","For Evaluation pool:\nThe evaluation was based on interpretation of the AI\noutput by reviewing clinicians. The evaluation was\nconducted by three independent reviewers, with at\nleast two being US Certified sonographers, with\nextensive clinical experience."],["Independence of\nTest data","All training data is independent from the test data at a\npatient level."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p17-t1","doc_id":"K242168","page_num":17,"bbox":[217.0,305.94,553.36,718.43],"n_rows":3,"n_cols":4,"columns":["","","1st Trimester SonoLyst/SonolysLive",""],"rows":[["","","1st Trimester SonoLyst/SonolysLive",""],["Summary test\nStatistics","• Data used for both training and validation has\nbeen collected across multiple geographical\nsites using different systems to represent the\nvariations in target population.\n• The verification for the SonoLyst 1st Trim IR&X\nfeature is based on computing confusion\nmatrices for the sorting (SonoLyst IR) and\ngrading (SonoLyst X) features\n• The verification of the SonoLystLive 1st Trim\nTrimester features is based on the average\nagreement between a sonographer panel and\nthe output of the algorithm regarding Traffic\nlight quality (green/amber/none)\n• The verification of the SonoBiometry CRL\nfeature is based on the acceptability rate for\nthe placement of CRL callipers\n• The average success rate of SonoLyst 1st\nTrimester IR, X and SonoBiometry CRL and\noverall traffic light accuracy is 80% or higher\n•","",""],["Confounders","For SonoLyst 1st Trimester the following confounder is\nused: the algorithmic performance is tested on two\nsub data sets: 1) data acquired with transabdominal\nprobes 2) data acquired with transvaginal probes. By\nchoosing transabdominal vs transvaginal probes as\nconfounder for the data analysis, the robustness of the\nalgorithm against the influence of the abdominal wall,\nthe transducer geometry and frequency is evaluated.\nFor both subgroups the acceptance criteria are met.\nThis demonstrates the generalization performance of\nt he algorithm.","",""]],"caption_candidate":"SonoLyst/Sonolystlive","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242168-p18-t0","doc_id":"K242168","page_num":18,"bbox":[216.95,81.83,553.38,642.48],"n_rows":3,"n_cols":2,"columns":["Data Collection","- Systems: GE Voluson V730, P8, S6/S8, E6, E8,\nE10, Expert 22, Philips Epiq 7G\n- Formats: Still images were obtained in DICOM\n& JPEG format, cine loops in RAW data\nformat.\n- Countries: UK, Austria, India and USA\n- For training 122,711 labelled source images\nfrom 35,861 patients\n- For testing the following number of images\nwere used:\nSonoLyst 1st Trim IR: 5271\nSonoLyst 1st Trim X: 2400\nSonoLyst 1st Trim Live: 6000\nSonoBiometry CRL: 110"],"rows":[["Data Collection","- Systems: GE Voluson V730, P8, S6/S8, E6, E8,\nE10, Expert 22, Philips Epiq 7G\n- Formats: Still images were obtained in DICOM\n& JPEG format, cine loops in RAW data\nformat.\n- Countries: UK, Austria, India and USA\n- For training 122,711 labelled source images\nfrom 35,861 patients\n- For testing the following number of images\nwere used:\nSonoLyst 1st Trim IR: 5271\nSonoLyst 1st Trim X: 2400\nSonoLyst 1st Trim Live: 6000\nSonoBiometry CRL: 110"],["Truthing process\nfor test datasets","To ensure the quality of the curated data for\nverification, the following strategy is employed:\nemployed\n1. The images were curated (sorted and graded)\nby a single sonographer\n2. The images were sorted and graded by\nScanNav AutoCapture First Trimester.\nThis process resulted in some images\nbeing reclassified during sorting.\n3. Where they differed from the ground truth,\nthe sorted images from step 2 were\nreviewed by a 5-sonographer review\npanel, in order to determine the sorting\naccuracy of the system.\nThe sorting process resulted in some images\nbeing reclassified based upon the majority\nview of the panel.\n4. Where they differed from the ground truth,\nthe graded images from step 1 were\nreviewed by a 5-sonographer review\npanel, in order to determine the grading\naccuracy of the system."],["Independence of\nTest data","All training data is independent from the test data at a\npatient level.\nA statistically significant subset of the test data is\nindependent from the training data at a site level, with\nno test data collected at the site being used in training."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p9-t0","doc_id":"K242171","page_num":9,"bbox":[71.57,202.72,532.67,764.5],"n_rows":14,"n_cols":4,"columns":["Study Type (Anatomic\nArea of Interest)","Radiographic View(s)\nSupported","Findings","Patient Population"],"rows":[["Study Type (Anatomic\nArea of Interest)","Radiographic View(s)\nSupported","Findings","Patient Population"],["Ankle","Frontal, Lateral, Oblique","Fracture","Adults, Infants, Children, Adolescents"],["Foot","Frontal, Lateral, Oblique","Fracture","Adults, Infants, Children, Adolescents"],["Knee","Frontal, Lateral, Oblique","Fracture","Adults, Infants, Children, Adolescents"],["Leg (includes\nTibia/Fibula)","Frontal, Lateral","Fracture","Adults, Infants, Children, Adolescents"],["Femur","Frontal, Lateral","Fracture","Adults"],["Wrist","Frontal, Lateral, Oblique","Fracture","Adults, Children, Adolescents"],["Hand/Finger","Frontal, Lateral, Oblique","Fracture","Adults, Infants, Children, Adolescents"],["Elbow","Frontal, Lateral, Oblique","Fracture","Adults, Children, Adolescents"],["","Lateral","Elbow Joint\nEffusion","Adults, Children, Adolescents"],["Forearm","Frontal, Lateral","Fracture","Adults, Infants, Children, Adolescents"],["","Lateral","Elbow Joint\nEffusion","Adults, Children, Adolescents"],["Arm (includes Humerus)","Frontal, Lateral","Fracture","Adults, Neonates, Infants, Children,\nAdolescents"],["","Lateral","Elbow Joint\nEffusion","Adults, Children, Adolescents"]],"caption_candidate":"the review of commonly acquired radiographs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p10-t0","doc_id":"K242171","page_num":10,"bbox":[72.09,80.82,532.62,314.75],"n_rows":6,"n_cols":4,"columns":["Study Type (Anatomic\nArea of Interest)","Radiographic View(s)\nSupported","Findings","Patient Population"],"rows":[["Study Type (Anatomic\nArea of Interest)","Radiographic View(s)\nSupported","Findings","Patient Population"],["Shoulder","Frontal, Lateral","Fracture","Adults, Infants, Children, Adolescents"],["Clavicle","Frontal","Fracture","Adults, Children, Adolescents,\nNeonates, Infants"],["Pelvis","Frontal","Fracture","Adults, Infants, Children, Adolescents"],["Hip","Frontal, Lateral","Fracture","Adults, Infants, Children, Adolescents"],["Thorax (includes ribs)","Frontal, Lateral, Ribs\nseries","Fracture","Adults"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p12-t0","doc_id":"K242171","page_num":12,"bbox":[70.79,511.74,524.59,739.88],"n_rows":9,"n_cols":4,"columns":["Substantial Equivalence Table","","",""],"rows":[["Substantial Equivalence Table","","",""],["","Proposed Device\nTechCare Trauma","Predicate Device\nBone View","Similarities &\nDifferences"],["Number","K242171","K222176","NA"],["Applicant","Milvue","Gleamer","NA"],["Device Name","TechCare Trauma","BoneView 1.1-US","NA"],["Classification\nRegulation","21 CFR 892.2090","21 CFR 892.2090","Same"],["Product\nCode","QBS","QBS","Same"],["Device\nClassification","Radiological computer assisted\ndetection/diagnosis software for\nfracture Class II","Radiological computer assisted\ndetection/diagnosis software for\nfracture Class II","Same"],["Image\nModality","2D Xray Images","2D Xray Images","Same"]],"caption_candidate":"elements:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p13-t0","doc_id":"K242171","page_num":13,"bbox":[70.73,80.82,524.57,770.22],"n_rows":2,"n_cols":4,"columns":["Intended\nUse","TechCare Trauma is intended to\nanalyze 2D X ray radiographs using\nmachine learning techniques to aid in\nthe detection, localization, and\ncharacterization of fractures and/or\nelbow joint effusion during the\nreview of commonly acquired\nradiographs.","BoneView is intended to aid in the\ndetection,\nlocalization, and characterization of\nfractures on\nacquired medical images","Same"],"rows":[["Intended\nUse","TechCare Trauma is intended to\nanalyze 2D X ray radiographs using\nmachine learning techniques to aid in\nthe detection, localization, and\ncharacterization of fractures and/or\nelbow joint effusion during the\nreview of commonly acquired\nradiographs.","BoneView is intended to aid in the\ndetection,\nlocalization, and characterization of\nfractures on\nacquired medical images","Same"],["Anatomic\nAreas of\nInterest","Fracture, for Adults (greater than 21\nyears of age) and\nInfants/Children/Adolescents\n(between 28 days of age\nand 21 years of age):\nAnkle\nFoot\nKnee\nLeg\nHand/Finger\nForearm\nArm\nShoulder\nClavicle\nPelvis\nHip\nFracture, for Adults (greater than 21\nyears of age) and\nChildren/Adolescents (between 2\nyears of age\nand 21 years of age):\nWrist\nFracture, for Adults only (greater\nthan 21 years of age):\nFemur\nThorax (includes ribs)\nFracture, for neonates (from 0 to 28\ndays of age):\nArm (includes Humerus)\nClavicle\nElbow Joint Effusion, for Adults\n(greater than 21 years of age) and\nChildren/Adolescents (between 2\nyears of age\nand 21 years of age):\nElbow (lateral)\nForearm (lateral)","Fracture :\nAdults (greater than 21 years of age)\nand\nChildren/Adolescents (between 2\nyears of age\nand 21 years of age):\nAnkle\nFoot\nKnee\nTibia/Fibula\nWrist\nHand\nElbow\nForearm\nHumerus\nShoulder\nClavicle\nAdults (greater than 21 years of age)\nonly:\nPelvis\nHip\nFemur\nRibs\nThoracic Spine\nLumbosacral Spine","Similar"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p14-t0","doc_id":"K242171","page_num":14,"bbox":[70.81,80.82,524.59,732.62],"n_rows":8,"n_cols":4,"columns":["","Arm, includes Humerus (lateral)","",""],"rows":[["","Arm, includes Humerus (lateral)","",""],["Clinical\nFindings","Fracture and Elbow Joint Effusion\n(EJE)","Fracture","Similar with the\naddition of Elbow\nJoint Effusions for\nTechCare Trauma"],["Intended\nUser","The intended users of TechCare\nTrauma are clinicians with the\nauthority to diagnose fractures\nand/or elbow joint effusions in\nvarious settings including primary\ncare (e. g., family practice, internal\nmedicine), emergency medicine,\nurgent care, and specialty care (e. g.\northopedics), as well as radiologists\nwho review radiographs across\nsettings.","The intended users of BoneView are\nclinicians with the authority to\ndiagnose fractures in various settings\nincluding primary care (e. g., family\npractice, internal medicine),\nemergency medicine, urgent care, and\nspecialty care (e. g. orthopedics), as\nwell as radiologists who review\nradiographs across settings.","Same"],["Patient\nPopulation","For Fracture : Neonates and infants\n(from birth to less than 2 years),\nchildren and adolescents (aged 2 to\nless than 22 years) and adults (aged\n22 years and over).\nFor EJE: Children and adolescents\n(aged 2 to less than 22 years) and\nadults (aged 22 years and over).","Adults (greater than 21 years of age)\nand Children/Adolescents (between 2\nyears of age and 21 years of age)","Similar with the\naddition of\nneonates and\ninfants (from\nbirth to less than\n2 years) for\nTechCare Trauma"],["Machine\nLearning\nMethodolog\ny","Supervised Deep Learning","Supervised Deep Learning","Same"],["Image\nsource","DICOM node (e.g., imaging device,\nintermediate DICOM node, PACS\nsystem, etc.)","DICOM node (e.g., imaging device,\nintermediate DICOM node, PACS\nsystem, etc.)","Same"],["Image\nViewing","PACS system\nImage annotations made on copy of\noriginal\nimage or image annotations toggled\non/off","PACS system\nImage annotations made on copy of\noriginal\nimage or image annotations toggled\non/off","Same"],["Deployment\nPlatform","Deployment on-premise or on cloud\nand\nconnection to several computing\nplatforms and\nX-ray imaging platforms such as X-ray\nradiographic systems, or PACS","Deployment on-premise or on cloud\nand\nconnection to several computing\nplatforms and\nX-ray imaging platforms such as X-ray\nradiographic systems, or PACS","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p17-t0","doc_id":"K242171","page_num":17,"bbox":[76.1,138.18,488.6,735.89],"n_rows":48,"n_cols":10,"columns":["mage-level ROC-A","UC Summary for TechCa","re Trauma","","","","","","",""],"rows":[["mage-level ROC-A","UC Summary for TechCa","re Trauma","","","","","","",""],["","","","","","","","","",""],["Popul","ation (Nb of images)","","Imag","e-leve","l R","OC-","AU","C [95%","CI]"],["","","","","","","","","",""],["Fracture - Adult (41","09)","","","0.962","[0.9","57","- 0",".967]",""],["","","","","","","","","",""],["Fracture - Pediatric","(2872)","","","0.962","[0.9","55","- 0",".969]",""],["","","","","","","","","",""],["EJE - Adult (280)","","","","0.965","[0.9","36","- 0",".986]",""],["","","","","","","","","",""],["EJE - Pediatric (483",")","","","0.976","[0.9","63","- 0",".986]",""],["","","","","","","","","",""],["mage-level ROC-A","UC Summary for fractur","e detectio","n","","","","","",""],["","","","","","","","","",""],["Category (Nb","of images Adu","lt ROC-AUC","[95% CI]","","Ped","iatr","ic","ROC-AU","C [95%"],["adult/ped","iatric)","","","","","","","",""],["","","","","","","","","",""],["","By","Anatomical","Regions","","","","","",""],["","","","","","","","","",""],["Ankle (293 / 283)","0",".941 [0.913;","0.965]","","","0.9","48","[0.916;","0.976]"],["","","","","","","","","",""],["Arm (197 / 183)","0",".981 [0.962;","0.996]","","","0.9","88","[0.978;","0.996]"],["","","","","","","","","",""],["Clavicle (210 / 171)","0",".998 [0.993;","1.000]","","","0.9","85","[0.965;","1.000]"],["","","","","","","","","",""],["Elbow (364 / 326)","0",".933 [0.899;","0.960]","","","0.9","42","[0.911;","0.970]"],["","","","","","","","","",""],["Femur (244 / NA)","0",".968 [0.945;","0.988]","","","","","NA",""],["","","","","","","","","",""],["Foot (298 / 299)","0",".972 [0.955;","0.988]","","","0.9","64","[0.937;","0.985]"],["","","","","","","","","",""],["Forearm (197 / 195",") 0",".969 [0.946;","0.988]","","","0.9","98","[0.995;","1.000]"],["","","","","","","","","",""],["Hand/Fingers (284","/ 281) 0",".951 [0.923;","0.976]","","","0.9","34","[0.899;","0.964]"],["","","","","","","","","",""],["Hip/Pelvis (221 - pe","diatric)","","","","","0.8","93","[0.849;","0.931]"],["- Hip (327 -","adult) 0",".945 [0.898;","0.979]","","","","","",""],["- Pelvis (163","- adult) 0",".955 [0.923;","0.979]","","","","","",""],["","","","","","","","","",""],["Knee (284 / 189)","0",".947 [0.921;","0.969]","","","0.9","48","[0.891;","0.990]"],["","","","","","","","","",""],["Leg (216 / 226)","0",".979 [0.957;","0.995]","","","0.9","59","[0.930;","0.983]"],["","","","","","","","","",""],["Shoulder (324 / 23","8) 0",".962 [0.940;","0.980]","","","0.9","91","[0.981;","0.998]"],["","","","","","","","","",""],["Thorax/Rib (414 / N","A) 0",".939 [0.912;","0.961]","","","","","NA",""],["","","","","","","","","",""],["Wrist (264 / 260)","0",".946 [0.920;","0.974]","","","0.9","73","[0.952;","0.990]"]],"caption_candidate":"Image-level ROC-AUC Summary for TechCare Trauma","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242171-p17-t1","doc_id":"K242171","page_num":17,"bbox":[70.71,153.29,523.41,270.5],"n_rows":5,"n_cols":2,"columns":["Population (Nb of images)","Image-level ROC-AUC [95% CI]"],"rows":[["Population (Nb of images)","Image-level ROC-AUC [95% CI]"],["Fracture - Adult (4109)","0.962 [0.957 - 0.967]"],["Fracture - Pediatric (2872)","0.962 [0.955 - 0.969]"],["EJE - Adult (280)","0.965 [0.936 - 0.986]"],["EJE - Pediatric (483)","0.976 [0.963 - 0.986]"]],"caption_candidate":"Image-level ROC-AUC Summary for TechCare Trauma","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p18-t0","doc_id":"K242171","page_num":18,"bbox":[70.78,80.5,523.18,743.5],"n_rows":26,"n_cols":3,"columns":["Female (2556 / 1090)","0.962 [0.955; 0.969]","0.964 [0.952; 0.975]"],"rows":[["Female (2556 / 1090)","0.962 [0.955; 0.969]","0.964 [0.952; 0.975]"],["Male (1553 / 1766)","0.962 [0.953; 0.970]","0.961 [0.952; 0.970]"],["By Image View","",""],["Frontal (1874 / 1530)","0.971 [0.964; 0.978]","0.966 [0.955; 0.975]"],["Lateral (1161 / 805)","0.955 [0.942; 0.965]","0.961 [0.946; 0.972]"],["Oblique (771 / 297)","0.946 [0.932; 0.962]","0.965 [0.944; 0.983]"],["By Age","",""],["22 to <65 years (2205)","0.972 [0.965; 0.977]","NA"],["≥ 65 years (1904)","0.950 [0.940; 0.959]","NA"],["<2 years (96)","NA","0.948 [0.888; 0.992]"],["2 to <12 years (998)","NA","0.971 [0.960; 0.981]"],["12 to <18 years (1218)","NA","0.955 [0.943; 0.967]"],["18 to <22 years (560)","NA","0.965 [0.949; 0.979]"],["By Imaging Hardware Manufacturer","",""],["Konica Minolta (2617 / 709)","0.952 [0.944; 0.959]","0.956 [0.941; 0.969]"],["Siemens (1107 / 657)","0.974 [0.963; 0.984]","0.953 [0.935; 0.969]"],["Samsung (136 / 257)","0.978 [0.948; 1.000]","0.944 [0.912; 0.971]"],["Agfa (NA / 889)","NA","0.972 [0.957; 0.985]"],["Carestream (NA / 59)","NA","1.000 [1.000; 1.000]"],["Philips (NA / 81)","NA","0.933 [0.870; 0.981]"],["RamSoft (NA / 69)","NA","0.996 [0.982; 1.000]"],["Fujifilm (67 / NA)","0.993 [0.969; 1.000]","NA"],["Other (181 / 148)","0.962 [0.931; 0.986]","0.969 [0.943; 0.988]"],["By Particular Groups","",""],["Displaced (3434 / 2066)","0.970 [0.964; 0.975]","0.969 [0.960; 0.977]"],["Non-Displaced (2581 / 2224)","0.951 [0.939; 0.962]","0.958 [0.949; 0.968]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p19-t0","doc_id":"K242171","page_num":19,"bbox":[63.42,152.74,530.55,198.5],"n_rows":2,"n_cols":5,"columns":["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],"rows":[["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],["All","0.906 [0.891; 0.919]","0.900 [0.887; 0.912]","0.940 [0.928; 0.951]","0.845 [0.830; 0.859]"]],"caption_candidate":"Image-level Sensitivity and Specificity for Fracture detection - Adult population (N = 4109)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p19-t1","doc_id":"K242171","page_num":19,"bbox":[63.42,246.44,530.55,292.5],"n_rows":2,"n_cols":5,"columns":["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],"rows":[["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],["All","0.821 [0.719; 0.893]","0.980 [0.949; 0.993]","0.859 [0.764; 0.923]","0.955 [0.917; 0.978]"]],"caption_candidate":"Image-level Sensitivity and Specificity for EJE detection - Adult population (N = 280)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p19-t2","doc_id":"K242171","page_num":19,"bbox":[63.42,340.14,530.55,385.5],"n_rows":2,"n_cols":5,"columns":["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],"rows":[["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],["All","0.900 [0.882; 0.916]","0.927 [0.913; 0.938]","0.930 [0.914; 0.943]","0.875 [0.859; 0.891]"]],"caption_candidate":"Image-level Sensitivity and Specificity for Fracture detection – Pediatric population (N = 2872)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242171-p19-t3","doc_id":"K242171","page_num":19,"bbox":[63.42,433.67,530.55,479.5],"n_rows":2,"n_cols":5,"columns":["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],"rows":[["","Se (High Sp)","Sp (High Sp)","Se (High Se)","Sp (High Se)"],["All","0.669 [0.587; 0.744]","0.977 [0.954; 0.989]","0.901 [0.839; 0.941]","0.933 [0.901; 0.955]"]],"caption_candidate":"Image-level Sensitivity and Specificity for EJE detection – Pediatric population (N = 483)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242188-p7-t0","doc_id":"K242188","page_num":7,"bbox":[72.26,77.66,508.66,695.26],"n_rows":4,"n_cols":3,"columns":["","informational purposes only) and\nboth exact and four-category\nquantitative estimates of the\npatient’s coronary artery calcium\nburden in Agatston units.\nThe output of the subject device\nis made available to the\nphysician on-demand as part of\nhis or her standard workflow.\nThe device generated calcium\nscore or score group can be\nviewed in the patient report at\nthe discretion of the physician,\nand the physician also has the\noption of viewing the device-\ngenerated calcium segmentation\nin a diagnostic image viewer.\nThe subject device output in no\nway replaces the original patient\nreport or the original chest CT\nscan; both are still available to be\nviewed and used at the discretion\nof the physician.\nThe device is intended to provide\ninformation to the physician to\nprovide assistance during review\nof the patient’s case. Results of\nthe subject device are not\nintended to be used on a stand-\nalone basis and are solely\nintended to aid and provide\ninformation to the physician. In\nall cases, further action taken on\na patient should only come at the\nrecommendation of the physician\nafter further reviewing the\npatient’s results.","coronary arteries: the right\ncoronary artery (RCA), the left\nmain artery (LM), the left anterior\ndescending artery (LAD), and the\nleft circumflex artery (LCX). The\nsoftware calculates the Agatston\nscore as the sum for each artery\nwhile also providing the total\nacross all coronary arteries. The\ntotal Agatston score is calibrated\nto 3.0mm slice thickness and is\nused to derive a CAC category and\nthe arterial age. The provided\nsegmentations are for illustrative\npurposes only and are not intended\nfor diagnostic use.\nClearRead CT CAC provides\nadjunctive information and is not\nintended to be used without\nclinical expert review."],"rows":[["","informational purposes only) and\nboth exact and four-category\nquantitative estimates of the\npatient’s coronary artery calcium\nburden in Agatston units.\nThe output of the subject device\nis made available to the\nphysician on-demand as part of\nhis or her standard workflow.\nThe device generated calcium\nscore or score group can be\nviewed in the patient report at\nthe discretion of the physician,\nand the physician also has the\noption of viewing the device-\ngenerated calcium segmentation\nin a diagnostic image viewer.\nThe subject device output in no\nway replaces the original patient\nreport or the original chest CT\nscan; both are still available to be\nviewed and used at the discretion\nof the physician.\nThe device is intended to provide\ninformation to the physician to\nprovide assistance during review\nof the patient’s case. Results of\nthe subject device are not\nintended to be used on a stand-\nalone basis and are solely\nintended to aid and provide\ninformation to the physician. In\nall cases, further action taken on\na patient should only come at the\nrecommendation of the physician\nafter further reviewing the\npatient’s results.","coronary arteries: the right\ncoronary artery (RCA), the left\nmain artery (LM), the left anterior\ndescending artery (LAD), and the\nleft circumflex artery (LCX). The\nsoftware calculates the Agatston\nscore as the sum for each artery\nwhile also providing the total\nacross all coronary arteries. The\ntotal Agatston score is calibrated\nto 3.0mm slice thickness and is\nused to derive a CAC category and\nthe arterial age. The provided\nsegmentations are for illustrative\npurposes only and are not intended\nfor diagnostic use.\nClearRead CT CAC provides\nadjunctive information and is not\nintended to be used without\nclinical expert review."],["Intended User","Radiologists","Radiologists"],["Modality","Routine, non-contrast, non-gated\nchest CT Series","Non-contrast, non-gated, standard,\nor low-dose chest CT scans"],["Anatomical\nRegion","Chest","Chest"]],"caption_candidate":"ClearRead™ CT CAC","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242188-p8-t0","doc_id":"K242188","page_num":8,"bbox":[77.66,37.75,501.72,679.49],"n_rows":54,"n_cols":4,"columns":["raditional 510(k",") Premarket Notification","Riverain","Technologies"],"rows":[["raditional 510(k",") Premarket Notification","Riverain","Technologies"],["learRead™ CT","CAC","",""],["","","",""],["Clinical","Coronary Artery Calcification","Coronary Artery Cal","cification"],["Condition","","",""],["","","",""],["Quantification","Yes","Yes",""],["of Calcium","","",""],["Burden","","",""],["","","",""],["Segmentation","Yes","Yes",""],["of Calcium","","",""],["","","",""],["Number of","4","4",""],["Detection","","",""],["Categories","","",""],["","","",""],["Calculation of","Yes","Yes",""],["Exact Calcium","","",""],["Score","","",""],["","","",""],["Type of","Adjunctive","Adjunctive",""],["Information","","",""],["","","",""],["Intended","Medical Facility","Medical Facility",""],["location","","",""],["","","",""],["Prescriptive","Yes","Yes",""],["Use","","",""],["","","",""],["Measurement","Agatston Units","Agatston Units",""],["Scale","","",""],["","","",""],["Image Format","DICOM","DICOM",""],["","","",""],["Slice","Up to 5mm","Up to 3mm",""],["Thickness","","",""],["","","",""],["Calcification","Automatic","Automatic",""],["Detection","","",""],["","","",""],["Default","130 HU (Hounsfield Units)","130 HU (Hounsfield","Units)"],["Threshold of","","",""],["Calcium","","",""],["","","",""],["Coronary","CAC detection category (based","CAC detection categ","ory and"],["Artery","on Agatston score), exact","arterial age based on","the measured"],["Calcification","Agatston score.","Agatston score.",""],["Quantification","","",""],["Method","","",""],["","","",""],["Annotation of","Yes","Yes",""],["Detected","","",""],["Calcium","","",""]],"caption_candidate":"Traditional 510(k) Premarket Notification Riverain Technologies","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242188-p9-t0","doc_id":"K242188","page_num":9,"bbox":[72.26,77.66,508.66,251.93],"n_rows":2,"n_cols":3,"columns":["Generate\nPatient Report","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","Optional to copy result to\nclipboard, insert in report, DICOM\nSecondary Capture"],"rows":[["Generate\nPatient Report","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","Optional to copy result to\nclipboard, insert in report, DICOM\nSecondary Capture"],["Report of the\nCalcium Score","Yes, Coronary Calcium\nDetection Category and exact\nAgatston score 4 categories (for\ndetection category):\n• 0\n• 1-99\n• 100-399\n• 400 +","Yes, Coronary Calcium Detection\nCategory and measured Agatston\nscore 4 categories (for detection\ncategory):\n• 0\n• 1-99\n• 100-399\n• 400 +"]],"caption_candidate":"ClearRead™ CT CAC","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p7-t0","doc_id":"K242203","page_num":7,"bbox":[72.56,96.48,540.34,718.8],"n_rows":12,"n_cols":4,"columns":["","Predicate Device","Reference Device AI-","Subject Device"],"rows":[["","Predicate Device","Reference Device AI-","Subject Device"],["","","",""],["","BriefCase-","Rad Companion","Aidoc BriefCase-"],["","Quantification of the","(Cardiovascular)",""],["","","","Quantification of"],["","Abdominal Aortic","(K222360)",""],["","","","Aortic Measurement"],["","Measurement (M-","","(M-Aorta)"],["","AbdAo) (K241112)","",""],["","","",""],["","","",""],["Intended Use /\nIndications for Use","BriefCase-\nQuantification is a\nradiological image\nmanagement and\nprocessing system\nsoftware indicated for\nuse in the analysis of\nCT exams with\ncontrast, that include\nthe abdominal aorta, in\nadults or transitional\nadolescents aged 18\nand older.\nThe device is intended\nto assist appropriately\ntrained medical\nspecialists by\nproviding the user with\nthe maximum\nabdominal aortic axial\ndiameter of cases that\nincludes the\nabdominal aorta (M-\nAbdAo). BriefCase-\nQuantification is\nindicated to evaluate\nnormal and\naneurysmal abdominal\naortas and is not\nintended to evaluate\npost-operative aortas.\nThe BriefCase-\nQuantification results\nare not intended to be","AI-Rad Companion\n(Cardiovascular) is\nimage processing\nsoftware that provides\nquantitative\nand qualitative\nanalysis from\npreviously\nacquired Computed\nTomography DICOM\nimages to support\nradiologists and\nphysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice in the\nevaluation and\nassessment of\ncardiovascular\ndiseases.\nIt provides the\nfollowing functionality:\n- Segmentation and\nvolume measurement\nof the heart\n- Quantification of the\ntotal calcium volume in\nthe coronary arteries\n- Segmentation of the\naorta\n- Measurement of\nmaximum diameters of\nthe aorta at typical\nlandmarks","BriefCase-\nQuantification is a\nradiological image\nmanagement and\nprocessing system\nsoftware indicated for\nuse in the analysis of\ncontrast-enhanced CT\nexams that include the\naorta in adults or\ntransitional\nadolescents aged 18\nand older.\nBriefCase-\nQuantification of Aortic\nMeasurement (M-\nAorta) is intended to\nassist hospital\nnetworks\nand appropriately\ntrained\nmedical specialists by\nproviding the user with\naortic diameter\nmeasurements across\nthe aorta. BriefCase-\nQuantification is\nindicated to evaluate\nnormal and\naneurysmal aortas and\nis not intended to\nevaluate post-\noperative aortas."]],"caption_candidate":"Table 1. Key feature comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p8-t0","doc_id":"K242203","page_num":8,"bbox":[72.56,71.4,540.34,710.16],"n_rows":12,"n_cols":4,"columns":["","Predicate Device","Reference Device AI-","Subject Device"],"rows":[["","Predicate Device","Reference Device AI-","Subject Device"],["","","",""],["","BriefCase-","Rad Companion","Aidoc BriefCase-"],["","Quantification of the","(Cardiovascular)",""],["","","","Quantification of"],["","Abdominal Aortic","(K222360)",""],["","","","Aortic Measurement"],["","Measurement (M-","","(M-Aorta)"],["","AbdAo) (K241112)","",""],["","","",""],["","","",""],["","used on a stand-alone\nbasis for clinical\ndecision-making or\notherwise preclude\nclinical assessment of\ncases.\nThese measurements\nare unofficial, are not\nfinal, and are subject to\nchange after review by\na radiologist. For final\nclinically approved\nmeasurements, please\nrefer to the official\nradiology report.\nClinicians are\nresponsible for viewing\nfull images per the\nstandard of care.","- Threshold-based\nhighlighting of\nenlarged diameters\nThe software has been\nvalidated for non-\ncardiac chest CT data\nwith filtered\nbackprojection\nreconstruction from\nSiemens Healthineers,\nGE Healthcare,\nPhilips, and\nToshiba/Canon.\nAdditionally, the\ncalcium detection\nfeature has been\nvalidated on non-\ncardiac chest CT data\nwith iterative\nreconstruction from\nSiemens Healthineers.\nOnly DICOM images\nof adult patients are\nconsidered to be valid\ninput.","The device provides\nthe following\nassessmnets:\n● Aortic\nmeasurements\nat 10\nanatomical\nlandmarks;\n● Maximum\naortic diameter\nof the\nabdominal\naorta,\ndescending\naorta and\nascending\naorta.\nThe BriefCase-\nQuantification results\nare not intended to be\nused on a stand-alone\nbasis for clinical\ndecision-making or\notherwise preclude\nclinical assessment of\ncases.\nThese measurements\nare unofficial, are not\nfinal, and are subject to\nchange after review by\na radiologist. For final\nclinically approved\nmeasurements, please\nrefer to the official\nradiology report.\nClinicians are\nresponsible for viewing"]],"caption_candidate":"4","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p9-t0","doc_id":"K242203","page_num":9,"bbox":[72.5,71.4,540.42,717.36],"n_rows":20,"n_cols":4,"columns":["","Predicate Device","Reference Device AI-","Subject Device"],"rows":[["","Predicate Device","Reference Device AI-","Subject Device"],["","","",""],["","BriefCase-","Rad Companion","Aidoc BriefCase-"],["","Quantification of the","(Cardiovascular)",""],["","","","Quantification of"],["","Abdominal Aortic","(K222360)",""],["","","","Aortic Measurement"],["","Measurement (M-","","(M-Aorta)"],["","AbdAo) (K241112)","",""],["","","",""],["","","",""],["","","","full images per the\nstandard of care."],["User population","Appropriately trained\nmedical specialists","Radiologists and\nphysicians from\nemergency medicine,\nspecialty care, urgent\ncare, and general\npractice","Hospital networks and\nappropriately trained\nmedical specialists"],["Anatomical region of\ninterest","Abdominal aorta","Heart, coronary\narteries and aorta","Aorta"],["Data acquisition\nprotocol","CT exams with\ncontrast that include\nthe abdominal aorta","non-cardiac chest CT","contrast-enhanced CT\nexams that include the\naorta"],["Diameter\nMeasurement","Yes","Yes","Yes"],["Images\nformat","DICOM","DICOM","DICOM"],["Interference with\nstandard workflow","No","No","No"],["Algorithm","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images.","Artificial intelligence\nalgorithm with\ndatabase of images."],["Structure","-BriefCase-\nQuantification,\nis hosted on a cloud\nserver, analyzes\napplicable CT images\nthat are acquired on\nCT scanner that are\nforwarded to\nBriefCase-\nQuantification.","- The system remains\nhosted in the teamplay\ndigital health platform\nand remains driven by\nthe AI-Rad Companion\nEngine.\n- The edge\ndeployment the\nprocessing of clinical","- BriefCase-\nQuantification is\nhosted on a cloud\nserver, analyzes\napplicable CT images\nthat are forwarded to\nBriefCase-\nQuantification.\n- The results of the\nanalysis are exported"]],"caption_candidate":"5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p10-t0","doc_id":"K242203","page_num":10,"bbox":[72.56,71.4,540.34,331.32],"n_rows":12,"n_cols":4,"columns":["","Predicate Device","Reference Device AI-","Subject Device"],"rows":[["","Predicate Device","Reference Device AI-","Subject Device"],["","","",""],["","BriefCase-","Rad Companion","Aidoc BriefCase-"],["","Quantification of the","(Cardiovascular)",""],["","","","Quantification of"],["","Abdominal Aortic","(K222360)",""],["","","","Aortic Measurement"],["","Measurement (M-","","(M-Aorta)"],["","AbdAo) (K241112)","",""],["","","",""],["","","",""],["","- The results of the\nanalysis are exported\nin DICOM format, and\nare sent to a PACS\ndestination for review\nby medical specialists,\nto assist in the\nmeasurement of the\nabdominal aorta.","data and the\ngeneration of\nresults are performed\nwithin the customer\nenvironment.\n- This system remains\nfully connected to the\ncloud for monitoring\nand maintenance of\nthe system from a\nremote setup.","in DICOM format, and\nare sent to a PACS\ndestination for review\nby medical specialists,\nto assist in the\nmeasurement of the\nabdominal aorta."]],"caption_candidate":"6","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p11-t0","doc_id":"K242203","page_num":11,"bbox":[225.2,183.48,386.7,269.2],"n_rows":3,"n_cols":3,"columns":["Gender","N*","%"],"rows":[["Gender","N*","%"],["Male","106","50%"],["Female","106","50%"]],"caption_candidate":"Table 3. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242203-p11-t1","doc_id":"K242203","page_num":11,"bbox":[225.2,295.56,386.7,467.56],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["Siemens","58","27.4%"],["GE","49","23.1%"],["Philips","50","23.6%"],["Toshiba","55","25.9%"],["Total","212","100%"]],"caption_candidate":"Table 4. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242215-p7-t0","doc_id":"K242215","page_num":7,"bbox":[72.24,125.24,542.75,706.62],"n_rows":11,"n_cols":4,"columns":["","Subject Device","Primary predicate Device","Reference Device"],"rows":[["","Subject Device","Primary predicate Device","Reference Device"],["Device name","Neurophet AQUA V3.1","Neurophet AQUA v2.1","NeuroQuant® v2.2"],["510(k)","K242215","K220437","K170981"],["Manufacturer","NEUROPHET, Inc.","NEUROPHET, Inc.","CorTechs Labs, Inc"],["Product Code","QIH, LLZ","LLZ","LLZ"],["Indications for\nUse","Neurophet AQUA is\nintended for automatic\nlabeling, visualization and\nvolumetric quantification of\nsegmentable brain\nstructures and lesions from\na set of MR images.\nVolumetric data may be\ncompared to reference\npercentile data.","Neurophet AQUA is\nintended for Automatic\nlabeling, visualization and\nvolumetric quantification of\nsegmentable brain\nstructures from a set of MR\nimages. Volumetric data\nmay be compared to\nreference percentile data.","NeuroQuant is intended\nfor automatic labeling,\nvisualization and\nvolumetric quantification\nof segmentable brain\nstructures and lesions from\na set of MR images.\nVolumetric data may be\ncompared to reference\npercentile data."],["Target\nAnatomical\nSites","Brain","Brain","Brain"],["Design and\nIncorporated\nTechnology","•Automated measurement\nof brain tissue volumes,\nstructures, and lesions\n▪Automatic segmentation\nand quantification of brain\nstructures using deep\nlearning","•Automated measurement of\nbrain tissue volumes and\nstructures\n▪Automatic segmentation\nand quantification of brain\nstructures using deep\nlearning","•Automated measurement of\nbrain tissue volumes and\nstructures and lesions\n•Automatic segmentation\nand quantification of brain\nstructures using a dynamic\nprobabilistic neuroanatomical\natlas, with age and gender\nspecificity, based on the MR\nimage intensity"],["Physical\ncharacteristics","•Software package\n•Operates on off-the-\nshelf hardware (multiple\nvendors)","•Software package\n•Operates on off-the-shelf\nhardware (multiple\nvendors)","•Software package\n•Operates on off-the-shelf\nhardware (multiple\nvendors)"],["Operating\nSystem","Windows","Windows","Supports Linux, Mac OS\nX and Windows."],["Processing\nArchitecture","Automated internal\npipeline that performs:\n-segmentation\n-volume calculation\n-lesion quantification\n-report generation","Automated internal pipeline\nthat performs:\n-segmentation\n-volume calculation\n-report generation","Automated internal\npipeline that performs:\n-artifact correction\n-segmentation\n-lesion quantification\n-volume calculation\n-report generation"]],"caption_candidate":"Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242215-p8-t0","doc_id":"K242215","page_num":8,"bbox":[72.24,72.24,542.76,491.2],"n_rows":3,"n_cols":4,"columns":["Data Source","•MRI scanner: 3D T1\nand FLAIR MRI scans\nacquired with specified\nprotocols\n•Supports DICOM\nformat as input","•MRI scanner: 3D T1 scans\nacquired with specified\nprotocols\n• Supports DICOM format\nas input","•MRI scanner: 3D T1 and\nFLAIR MRI scans\nacquired with specified\nprotocols\n•Supports DICOM format\nas input"],"rows":[["Data Source","•MRI scanner: 3D T1\nand FLAIR MRI scans\nacquired with specified\nprotocols\n•Supports DICOM\nformat as input","•MRI scanner: 3D T1 scans\nacquired with specified\nprotocols\n• Supports DICOM format\nas input","•MRI scanner: 3D T1 and\nFLAIR MRI scans\nacquired with specified\nprotocols\n•Supports DICOM format\nas input"],["Output","▪Provides volumetric\nmeasurements of brain\nstructures and lesions\n▪Includes segmented\ncolor overlays and\nmorphometric reports\n▪Automatically\ncompares results to\nreference percentile data\nand to prior scans when\navailable\n▪Supports DICOM\nformat as output of\nresults that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and\nCommunications\nSystems","▪Provides volumetric\nmeasurements of brain\nstructures\n▪Includes segmented color\noverlays and\nmorphometric reports\n▪Automatically compares\nresults to reference\npercentile data and to prior\nscans when available\n▪Supports DICOM format\nas output of results that can\nbe displayed on DICOM\nworkstations and Picture\nArchive and\nCommunications Systems","▪Provides volumetric\nmeasurements of brain\nstructures and lesions\n▪Includes segmented color\noverlays and\nmorphometric reports\n▪Automatically compares\nresults to reference\npercentile data and to prior\nscans when available\n▪Supports DICOM format\nas output of results that\ncan be displayed on\nDICOM workstations and\nPicture Archive and\nCommunications Systems"],["Safety","•Automated quality\ncontrol functions\n-Image artifact check\n-Scan protocol\nverification\n•Results must be\nreviewed by a trained\nphysician","•Automated quality control\nfunctions\n-Tissue contrast check\n-Scan protocol verification\n• Results must be reviewed\nby a trained physician","•Automated quality\ncontrol functions\n-Tissue contrast check\n-Scan protocol\nverification\n-Atlas alignment check\n•Results must be reviewed\nby a trained physician"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242240-p7-t0","doc_id":"K242240","page_num":7,"bbox":[82.1,138.85,515.5,719.05],"n_rows":24,"n_cols":3,"columns":["Parameter","CaRi-Plaque","Autoplaque 3.0 (K212758)"],"rows":[["Parameter","CaRi-Plaque","Autoplaque 3.0 (K212758)"],["","Subject Device","Predicate Device"],["Computer Operating System","Client-side Google Chrome\napplication","Windows / Mac OS"],["Stand-alone software","Yes","Same"],["DICOM Compliance","DICOM 3","Same"],["2D Imaging","Review of coronary vessels in 2D\nMPR, curved MPR, and\nstraightened view.","Same"],["2D Measurement","2D measurement tools of vessel\ndiameter and contour","Same"],["3D Imaging","Review of structures in 3D","Same"],["Maximum intensity projection (MIP)","N/A; this visualization method is\nnot necessary analyzing the\npresence and extent of coronary\nplaque and luminal stenosis","MIP with interactive control"],["Multiplanar reformatting (MPR)","MPR with oblique slicing.\nVariable slab thickness is not\nnecessary analyzing the\npresence and extent of coronary\nplaque and luminal stenosis","MPR with oblique slicing and\nvariable slab thickness"],["Quantitative Measurements","",""],["Diameter stenosis: Maximum diameter\nstenosis, with respect to proximal and\ndistal references","Yes","Same"],["Total Plaque Volume","Yes","Same"],["Calcified Plaque Volume","Yes","Same"],["NCP volume: noncalcified plaque\nvolume","Yes","Same"],["LD-NCP volume: low-density\nnoncalcified plaque volume","Yes","Same"],["Vessel Volume","No. This is calculated but not\nreported as a device output.","Yes"],["NCP burden: noncalcified plaque\nvolume / analyzed vessel volume","No","Yes"],["LD-NCP burden: low-density\nnoncalcified plaque volume / analyzed\nvessel volume","No","Yes"],["CP burden: calcified plaque\nvolume/analyzed vessel volume","No","Yes"],["Total plaque burden: total plaque\nvolume/analyzed vessel volume","Yes","Same"],["Plaque composition NCP: noncalcified\nplaque composition (NCP volume /\ntotal plaque volume)","No","Yes"],["Plaque composition CP: calcified\nplaque composition (CP volume / total\nplaque volume)","No","Yes"],["Plaque composition LDNCP: low-\ndensity noncalcified plaque","No","Yes"]],"caption_candidate":"Table 1. Technology Comparison to Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242240-p8-t0","doc_id":"K242240","page_num":8,"bbox":[82.11,122.05,515.48,520.57],"n_rows":13,"n_cols":3,"columns":["Parameter","CaRi-Plaque","Autoplaque 3.0 (K212758)"],"rows":[["Parameter","CaRi-Plaque","Autoplaque 3.0 (K212758)"],["","Subject Device","Predicate Device"],["composition (LD-NCP volume / NCP\nvolume)","",""],["QCAD: Maximum diameter stenosis","Yes, refers to a single reference\nsite","Yes, refers to proximal and distal\nreferences"],["Remodeling index: ratio of maximum\nvessel area / proximal and distal\nreferences","Yes","Same"],["Area stenosis: maximum area stenosis,\nwith respect to proximal and distal\nreferences","Yes","Same"],["Plaque length: diseased vessel length","No. This is calculated but not\nreported as a device output.","Yes"],["Contrast density difference: maximum\ndifference in contrast density over\nlesion with respect to proximal","No; not used as a common\nreference standard","Yes"],["MLD: minimal luminal dimeter over\nlesion","No. This is calculated but not\nreported as a device output.","Yes"],["MLA: minimum luminal area over\nlesion","No","Yes"],["Vessel profile: area, maximum\ndiameter, minimum diameter\nmeasured from selected vessel cross\nsection","Yes","Same"],["Lumen profile: area, maximum\ndiameter, minimum diameter\nmeasured from selected lumen cross\nsection","Yes","Same"],["Vessel, plaque, and lumen\nsegmentation","Yes- semi-automatic (threshold-\nbased segmentation with full\noption to edit); output\ndemonstrated to meet pre-\ndetermined acceptance criteria\nin clinical performance study","Yes- semi-automatic (deep\nlearning based with full option to\nedit)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p5-t0","doc_id":"K242270","page_num":5,"bbox":[56.85,182.42,538.42,275.54],"n_rows":4,"n_cols":2,"columns":["Company Name:","Orthofix S.r.l."],"rows":[["Company Name:","Orthofix S.r.l."],["Address","Via Delle Nazioni, 9\n37012 Bussolengo (VR) - Italy"],["Telephone","+39 045 6719000"],["Fax","+39 045 6719380"]],"caption_candidate":"Submitter information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p5-t1","doc_id":"K242270","page_num":5,"bbox":[56.85,616.15,538.42,644.11],"n_rows":2,"n_cols":3,"columns":["Primary Predicate","510(k) Number","Manufacturer"],"rows":[["Primary Predicate","510(k) Number","Manufacturer"],["OrthoNextTM Platform System","K202519","Orthofix S.r.l."]],"caption_candidate":"Primary Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p5-t2","doc_id":"K242270","page_num":5,"bbox":[56.85,699.82,538.42,741.1],"n_rows":2,"n_cols":3,"columns":["Reference Device","510(k) Number","Manufacturer"],"rows":[["Reference Device","510(k) Number","Manufacturer"],["Orthofix TrueLok Hexapod System (TL-\nHEX) V2.0","K170650","Orthofix S.r.l."]],"caption_candidate":"Reference device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p6-t0","doc_id":"K242270","page_num":6,"bbox":[56.88,98.66,538.42,478.75],"n_rows":3,"n_cols":2,"columns":["Device description","The subject OrthoNext™ Platform System is a web-based modular software system,\nindicated for assisting healthcare professionals in planning of orthopedic surgery and\ntreatment both preoperatively and postoperatively, including deformity analysis and\ncorrection with several Orthofix products.\nThe subject software system is intended for use by Healthcare Professionals (HCP),\nwith full awareness of the appropriate orthopedic procedures, in the operating theatre\nonly.\nThe subject software functions are intended to inform the HCP on orthopedic\nprocedure treatment planning when the Orthofix external or internal fixation systems\nare used. These functions are evidence-based tools that support HCP when\nconsidering treatment digital planning options for a patient. The software functions\ndo not treat a patient or determine a patient’s treatment.\nThe software enables the HCP to import radiological images, display 2D views (frontal\nand lateral) of the radiological images, overlay the positioning of the template and\nsimulate the treatment plan option, and to generate parameters and/or\nmeasurements to be verified or adjusted by the HCP based on their clinical judgment."],"rows":[["Device description","The subject OrthoNext™ Platform System is a web-based modular software system,\nindicated for assisting healthcare professionals in planning of orthopedic surgery and\ntreatment both preoperatively and postoperatively, including deformity analysis and\ncorrection with several Orthofix products.\nThe subject software system is intended for use by Healthcare Professionals (HCP),\nwith full awareness of the appropriate orthopedic procedures, in the operating theatre\nonly.\nThe subject software functions are intended to inform the HCP on orthopedic\nprocedure treatment planning when the Orthofix external or internal fixation systems\nare used. These functions are evidence-based tools that support HCP when\nconsidering treatment digital planning options for a patient. The software functions\ndo not treat a patient or determine a patient’s treatment.\nThe software enables the HCP to import radiological images, display 2D views (frontal\nand lateral) of the radiological images, overlay the positioning of the template and\nsimulate the treatment plan option, and to generate parameters and/or\nmeasurements to be verified or adjusted by the HCP based on their clinical judgment."],["Indications for use","The OrthoNext™ Platform System is indicated for assisting healthcare professionals in\npreoperative planning of orthopedic surgery and post-operative planning of\northopedic treatment. The device allows for overlaying of Orthofix Product templates\non radiological images, and includes tools for performing measurements on the image\nand for positioning the template. Clinical judgments and experience are required to\nproperly use the software."],["Comparison of\nTechnological\nCharacteristics with the\nPredicate Device","The following table provides a comparison of technological characteristics of the\nsubject and the primary predicate device. Any differences have been demonstrated to\nnot raise different questions of safety and effectiveness by virtue of objective\nevidence."]],"caption_candidate":"Page 2 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p7-t0","doc_id":"K242270","page_num":7,"bbox":[62.67,85.56,532.87,723.34],"n_rows":8,"n_cols":6,"columns":["Technological Characteristics","","Subject Device\nOrthoNext™ Platform System","","Primary Predicate Device",""],"rows":[["Technological Characteristics","","Subject Device\nOrthoNext™ Platform System","","Primary Predicate Device",""],["","","","","OrthoNext™ Platform System",""],["","","","","(K202519)",""],["1.","Indications for use","The OrthoNext™ Platform system is\nindicated for assisting healthcare\nprofessionals in preoperative planning\nof orthopedic surgery and post-\noperative planning of orthopedic\ntreatment. The device allows for\noverlaying of Orthofix Product\ntemplates on radiological images, and\nincludes tools for performing\nmeasurements on the image and for\npositioning the template. Clinical\njudgments and experience are\nrequired to properly use the software.","The OrthoNext™ Platform system is\nindicated for assisting healthcare\nprofessionals in preoperative\nplanning of orthopedic surgery. The\ndevice allows for overlaying of\nOrthofix Product templates on\nradiological images, and includes\ntools for performing measurements\non the image and for positioning the\ntemplate. Clinical judgments and\nexperience are required to properly\nuse the software.\nThe OrthoNext™ Platform system is\nnot to be used for mammography.","",""],["","Assessment: The subject indications for use include “post-operative planning of orthopedic treatment”, a\nfeature already included in the scope of the reference device, without substantially changing the intended\nuse of the device, which remains intended for assisting healthcare professionals in orthopedic procedure\n(surgery and treatment) planning. The difference in the type of treatment planning does not constitute a\nnew intended use. The statement “The OrthoNext™ Platform system is not to be used for mammography”\nincluded in the original Indications for Use of the primary predicate device was not incorporated in the\nIndications for Use of the subject device because it was specifically addressed in a dedicated section of the\nInstructions for Use; as the primary predicate device, the subject device is not to be used for\nmammography.\nEquivalent - no significant new questions have been raised.","","","",""],["2.","Population to be treated","OrthoNext™ Platform System does\nnot directly interact with patients.\nSoftware planning functionalities are\napplicable to patients that need pre-\noperative orthopedic surgery planning\nor post-operative orthopedic\ntreatment planning.","OrthoNext™ Platform System does\nnot directly interact with patients.\nSoftware planning functionalities are\napplicable to patients that need pre-\noperative orthopedic surgery\nplanning.","",""],["","Assessment: in comparison to the predicate device, the subject patient population explicitly includes\npatients needing postoperative orthopedic treatment planning, as in the reference device. The population\nthat undergoes postoperative treatment is the same (or a subgroup) of the population needing\npreoperative planning, thus it can be considered already included in the patient population of the primary\npredicate device.\nEquivalent - no significant new questions have been raised.","","","",""],["3.","Principle of Operation","Principle of operation:\n• Importation medical images format\n(x-ray images)\n• Processing tools\n• Measurements and parameters\nanalysis tools\n• Surgical planning tools\n• Enable software modules\n(preoperative and postoperative) for\noverlaying template for simulation.","Principle of operation:\n• Importation medical images format\n(x-ray images)\n• Processing tools\n• Measurements and parameters\nanalysis tools\n• Surgical planning tools\n• Enable software modules\n(preoperative and postoperative) for\noverlaying template for simulation.","",""]],"caption_candidate":"Page 3 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p8-t0","doc_id":"K242270","page_num":8,"bbox":[62.65,71.44,532.9,649.87],"n_rows":9,"n_cols":4,"columns":["","Assessment: The subject device has the same principle of operation of the primary predicate. Equivalent -\nno significant new questions have been raised.","",""],"rows":[["","Assessment: The subject device has the same principle of operation of the primary predicate. Equivalent -\nno significant new questions have been raised.","",""],["4.","Configuration and mode\nof access","Web-based: login is possible through\naccess to a website by username and\npassword licensed by the\nmanufacturer.\nThe device is not incorporated into IT-\nNetworks.","Web-based: login is possible through\naccess to a website by username and\npassword licensed by the\nmanufacturer.\nThe device is not incorporated into\nIT-Networks."],["","Assessment: The configuration and mode of access of the subject device is the same as the predicate\ndevice.\nEquivalent - no significant new questions have been raised.","",""],["5.","Supported devices","PC/Mac/Tablet","PC/Mac"],["","Assessment: the main supported platforms are PC/Mac, as the primary predicate device. The subject\ndevice is also validated for use on a tablet: since the software is web-based, access is allowed via a login to\nthe same web portal, independently from the platform used.\nEquivalent - no significant new questions have been raised.","",""],["6.","Operating Systems","Windows (Microsoft) - Minimum\nWindows 10; macOS (Apple) -\nMinimum macOS Big Sur (version 11);\niPad (Apple) - Minimum 15.8","Windows (Microsoft) - Minimum\nWindows 10; macOS (Apple) -\nMinimum macOS Big Sur (version 11)"],["","Assessment: the supported operating systems are the same (Windows, macOS) in comparison to the\nprimary predicate. The subject device is also validated for use on a tablet, thus also a dedicated operating\nsystem is included.\nEquivalent - no significant new questions have been raised.","",""],["7.","Supported browsers","• Google Chrome v120 or higher\n(Windows)\n• Microsoft Edge v121 or higher\n(Windows)\n• Firefox v122 or higher (Windows)\n• Safari 17.2 or higher (macOS)\n• Mobile Safari 15.8 or higher (iPadOS)\n- Web Graphics Library (WebGL)\nenabled\nNOTE: Web Graphics Library (WebGL)\navailability and minimum screen\nresolution are checked at login time in\norder to provide access to the SW.","• Google Chrome Browser Version 83\nor higher (Windows)\n• Microsoft Edge Version 44 or\nhigher (Windows)\n• Mozilla Firefox Version 77 or higher\n(Windows)\n• Safari Version 13 or higher (macOS)\n- Web Graphics Library (WebGL)\nenabled\nNOTE: Web Graphics Library\n(WebGL) availability and minimum\nscreen resolution are checked at\nlogin time in order to provide access\nto the SW."],["","Assessment: The supported browsers are the same in comparison with the primary predicate, with updated\nversions. The subject device is also validated for use on a tablet, thus also a dedicated browser is included.\nEquivalent - no significant new questions have been raised.","",""]],"caption_candidate":"Page 4 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p9-t0","doc_id":"K242270","page_num":9,"bbox":[62.65,71.52,532.9,281.21],"n_rows":4,"n_cols":4,"columns":["8.","System requirements","Computer System Requirements\nDisplay Settings: Screen Resolution of\n1280 x 768 pixels or higher.\nInternet Connection:\nMinimum required internet\nconnectivity speed of 512 kbps\nRecommended internet connectivity\nspeed of 3 mbps or higher","Computer System Requirements\nDisplay Settings: Screen Resolution\nof 1280 x 768 pixels or higher.\nInternet Connection:\nMinimum required internet\nconnectivity speed of 512 kbps\nRecommended internet connectivity\nspeed of 3 mbps or higher"],"rows":[["8.","System requirements","Computer System Requirements\nDisplay Settings: Screen Resolution of\n1280 x 768 pixels or higher.\nInternet Connection:\nMinimum required internet\nconnectivity speed of 512 kbps\nRecommended internet connectivity\nspeed of 3 mbps or higher","Computer System Requirements\nDisplay Settings: Screen Resolution\nof 1280 x 768 pixels or higher.\nInternet Connection:\nMinimum required internet\nconnectivity speed of 512 kbps\nRecommended internet connectivity\nspeed of 3 mbps or higher"],["","Assessment: The subject device system requirements are identical to the primary predicate device.\nEquivalent - no significant new questions have been raised.","",""],["9.","Image input","Can receive digital images in .png or\n.jpg format","Can receive digital images in .png or\n.jpg format"],["","Assessment: Subject device image input management is identical to the primary predicate device.\nEquivalent - no significant new questions have been raised.","",""]],"caption_candidate":"Page 5 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p11-t0","doc_id":"K242270","page_num":11,"bbox":[216.53,157.76,502.14,188.66],"n_rows":2,"n_cols":3,"columns":["N° of Samples","Mean value [0-255]","Median Vaue [0-255]"],"rows":[["N° of Samples","Mean value [0-255]","Median Vaue [0-255]"],["24000","190","193"]],"caption_candidate":"intensities produced the following results (0 = black; 255 = white).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p11-t1","doc_id":"K242270","page_num":11,"bbox":[262.85,299.87,455.77,409.61],"n_rows":7,"n_cols":2,"columns":["Statistic","Value"],"rows":[["Statistic","Value"],["Mean Diameter [px]","70"],["Median Diameter [px]","71"],["Mean Area [px2]","4105"],["Median Area [px2]","3959"],["Mean Brightness","190"],["Median Brightness","193"]],"caption_candidate":"Training Set, Sample size = 24000.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p11-t2","doc_id":"K242270","page_num":11,"bbox":[262.85,447.47,455.77,588.79],"n_rows":9,"n_cols":2,"columns":["Statistic","Value"],"rows":[["Statistic","Value"],["Mean Diameter [px]","40.37"],["Median Diameter [px]","42.23"],["Diameter Std. Deviation [px]","11.16"],["Mean Area [px2]","1377.48"],["Median Area [px2]","1400.69"],["Area Std. Deviation [px2]","692.44"],["Mean Brightness","192"],["Median Brightness","194"]],"caption_candidate":"marker","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p11-t3","doc_id":"K242270","page_num":11,"bbox":[262.85,626.65,455.77,720.7],"n_rows":6,"n_cols":2,"columns":["Candidate Model – Threshold Value = 0.96",""],"rows":[["Candidate Model – Threshold Value = 0.96",""],["Precision","1"],["Accuracy","0.8"],["TPR/Recall","0.75"],["FPR","0"],["F1 Score","0.86"]],"caption_candidate":"Performance Testing Summary:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p12-t0","doc_id":"K242270","page_num":12,"bbox":[185.95,108.38,532.83,149.06],"n_rows":3,"n_cols":15,"columns":["","Intersection","","","Center MAE","","","Center MAPE","","","Radius MAE","","","Radius MAPE",""],"rows":[["","Intersection","","","Center MAE","","","Center MAPE","","","Radius MAE","","","Radius MAPE",""],["","over Union (%)","","","(px)","","","(%)","","","(px)","","","(%)",""],["79","","","4.83","","","0.38","","","1.29","","","3","",""]],"caption_candidate":"truth values of the Test Set:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242270-p13-t0","doc_id":"K242270","page_num":13,"bbox":[56.88,71.04,538.42,271.46],"n_rows":2,"n_cols":2,"columns":["","Software usability activities have been conducted at the same time, asking surgeons\nto perform some specified tasks, answer to some questions in written form, navigate\nthrough the software and inviting them to describe ease of use or concerns regarding\ntasks they are invited to perform. Feedback has been collected in written form\ntogether with the answers rating and was analyzed in the Summative Usability Report.\nGiven the overall analysis, Orthofix concluded that the design verification and\nvalidation results are acceptable, and that the usability test gave objective evidence\nthat the device usability requirements are met as far as safety of the user interface of\nthe subject OrthoNext™ Platform System is concerned."],"rows":[["","Software usability activities have been conducted at the same time, asking surgeons\nto perform some specified tasks, answer to some questions in written form, navigate\nthrough the software and inviting them to describe ease of use or concerns regarding\ntasks they are invited to perform. Feedback has been collected in written form\ntogether with the answers rating and was analyzed in the Summative Usability Report.\nGiven the overall analysis, Orthofix concluded that the design verification and\nvalidation results are acceptable, and that the usability test gave objective evidence\nthat the device usability requirements are met as far as safety of the user interface of\nthe subject OrthoNext™ Platform System is concerned."],["Conclusions","Based upon: intended use, conditions of use, patient population, basic software\ndesign, operating principle, and non-clinical performance data, the subject\nOrthoNext™ Platform System has been shown to be substantially equivalent to the\nlegally marketed primary predicate device (K202519)."]],"caption_candidate":"Page 9 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242275-p9-t0","doc_id":"K242275","page_num":9,"bbox":[72.2,221.44,539.69,486.78],"n_rows":9,"n_cols":6,"columns":["Recognition\nNumber","Designation Number and\nEdition/Date","Title","","Standards",""],"rows":[["Recognition\nNumber","Designation Number and\nEdition/Date","Title","","Standards",""],["","","","","Development",""],["","","","","Organization",""],["12-349","PS 3.1 - 3.20 2022d","Digital Imaging and Communications in\nMedicine (DICOM) Set","NEMA","",""],["13-79","62304 Edition 1.1 2015-06\nCONSOLIDATED VERSION","Medical Device Software –Software Life\nCycle Processes","AAMI, ANSI, IEC","",""],["5-125","14971 Third Edition 2019-12","Medical devices – Application of risk\nmanagement to medical devices","ISO","",""],["5-129","62366-1 Edition 1.1 2020-06\nCONSOLIDATED VERSION","Medical devices - Part 1: Application of\nusability engineering to medical devices","AAMI, ANSI, IEC","",""],["5-134","15223-1 Fourth edition 2021-07","Medical devices - Symbols to be used with\nmedical device labels, labelling, and\ninformation to be supplied - Part 1: General\nrequirements","ISO","",""],["5-135","20417 First edition 2021-04\nCorrected version 2021-12","Medical devices – Information to be\nsupplied by the manufacturer","ISO","",""]],"caption_candidate":"FDA Recognized Consensus standards listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p8-t0","doc_id":"K242292","page_num":8,"bbox":[59.96,122.28,730.0,518.34],"n_rows":8,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["Device Classification Name","Radiological Computer Aided\nTriage And Notification Software","Radiological Computer Aided\nTriage And Notification Software","","","Same"],["Product Code","QAS","QAS","","","Same"],["Regulation Number","21 CFR 892.2080","21 CFR 892.2080","","","Same"],["Device Class","II","II","","","Same"],["Classification Panel","Radiology","Radiology","","","Same"],["Intended Use/Indications for\nUse","uAI Easy Triage ICH is a\nradiological computer-assisted\ntriage and notification software\ndevice indicated for analysis of\nnon-enhanced head CT images.\nThe device is intended to assist\nhospital networks and trained\nradiologists in workflow triage by","Cina is a radiological computer\naided triage and notification\nsoftware indicated for use in the\nanalysis of (1) non-enhanced head\nCT images and (2) CT\nangiography of the head.\nThe device is intended to assist","","","Compared to predicate device, the\nproposed device provides one\napplications for ICH while the\npredicate device CINA (K221716)\nprovides two applications for ICH\nand LVO.\nuAI Easy Triage ICH and the\npredicate device CINA(K221716)\nhave the same intended use"]],"caption_candidate":"Table 1 Substantial Equivalence Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p9-t0","doc_id":"K242292","page_num":9,"bbox":[59.99,82.22,729.98,510.96],"n_rows":3,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["","flagging and prioritizing studies\nwith suspected positive findings of\nIntracranial Hemorrhage (ICH).","hospital networks and trained\nradiologists in workflow triage by\nflagging and communicating\nsuspected positive findings of (1)\nhead CT images for Intracranial\nHemorrhage (ICH) and (2) head\nCT angiography for large vessel\nocclusion (LVO) of the anterior\ncirculation (distal ICA, MCA-M1\nor proximal MCA-M2).\nCina uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected (1)\nICH or (2) LVO on a standalone\nWeb application in parallel to the\nongoing standard of care image\ninterpretation. The user is\npresented with notifications for\ncases with suspected ICH or LVO","","","and\\indications for use in terms of\nfinding suspected intracranial\nhemorrhage in non-enhanced head\nCT, flagging suspected cases, and\nindicating the case to the attention of\nthe clinician."]],"caption_candidate":"K242292","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p10-t0","doc_id":"K242292","page_num":10,"bbox":[59.99,82.22,729.98,504.0],"n_rows":3,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["","","findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only, and\nare not intended for diagnostic use\nbeyond notification. The device\ndoes not alter the original medical\nimage, and it is not intended to be\nused as a diagnostic device.\nThe results of Cina are intended to\nbe used in conjunction with other\npatient information and based on\nprofessional judgement to assist\nwith triage/prioritization of\nmedical images. Notified\nclinicians are ultimately\nresponsible for reviewing full\nimages per the standard of care.","","",""]],"caption_candidate":"K242292","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p11-t0","doc_id":"K242292","page_num":11,"bbox":[59.96,82.22,730.0,518.28],"n_rows":7,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["User population","Radiologist","Radiologist","","","Same"],["Anatomical region of interest","Head","Head","","","Same"],["Data acquisition protocol","Non-contrast CT scan of the head","Non-contrast CT scan of the head\nor neck and CT angiogram images\nof the brain","","","Compared to predicate device, the\nproposed device supports non-\ncontrast head CT data for ICH\napplication while the predicate device\nsupport non-contrast head CT data for\nICH application or neck and brain CT\nangiogram data for LVO application.\nThe difference between the proposed\ndevice and the predicate device will\nnot impact the safety and\neffectiveness of the subject device."],["View DICOM data","DICOM information about the\npatient, study and current image","DICOM information about the\npatient, study and current image","","","Same"],["Segmentation of region of\ninterest","No; device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the","No; device does not mark,\nhighlight, or direct users’ attention\nto a specific location in the","","","Same"]],"caption_candidate":"K242292","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p12-t0","doc_id":"K242292","page_num":12,"bbox":[59.96,82.22,730.0,516.9],"n_rows":8,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["","original image","original image","","",""],["Algorithm","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm\nwith database of images","","","Same"],["Notification /\nPrioritization","Yes","Yes","","","Same"],["Preview\nimages","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","Presentation of a preview of the\nstudy for initial assessment not\nmeant for diagnostic purposes.\nThe device operates in parallel\nwith the standard of care, which\nremains the default option for all\ncases.","","","Same"],["Alteration of\noriginal image","No","No","","","Same"],["Removal of","No","No","","","Same"]],"caption_candidate":"K242292","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p13-t0","doc_id":"K242292","page_num":13,"bbox":[59.98,82.22,729.99,340.44],"n_rows":4,"n_cols":6,"columns":["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],"rows":[["Item","Proposed Device\nuAI Easy Triage ICH","","Predicate Device","","Remark"],["","","","CINA（K221716）","",""],["cases from\nworklist queue","","","","",""],["Structure","- ICH image processing\napplications\n- uAI Easy Triage Platform,\nincluding Alert Icon, Patient\nManagement, and Image Viewer.","- LVO and ICH image processing\napplications\n- Cina Platform (worklist and\nImage Viewer)","","","Compared to predicate device, the\nproposed device have same software\nstructure and add an alert icon\nmodule to pop-up the suspected\npositive findings of ICH. The\ndifference between the proposed\ndevice and the predicate device will\nnot impact the safety and\neffectiveness of the subject device."]],"caption_candidate":"K242292","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242292-p15-t0","doc_id":"K242292","page_num":15,"bbox":[127.08,380.22,494.52,584.22],"n_rows":17,"n_cols":3,"columns":["Subgroup","Breakdown","Sample Size"],"rows":[["Subgroup","Breakdown","Sample Size"],["Gender","Male","49%"],["","Female","51%"],["Age Ranges (Years)","18-45","17%"],["","45-65","36%"],["","65+","47%"],["Race Group","White","63%"],["","Black","18%"],["","others","19%"],["Equipment","GE","17%"],["","Philips","21%"],["","Siemens","62%"],["ICH Subtypes","Intraparenchymal Hemorrhage (IPH)","30%"],["","Intraventricular Hemorrhage (IVH)","17%"],["","Subarachnoid Hemorrhage (SAH)","24%"],["","Subdural Hemorrhage (SDH)","22%"],["","Extradural Hemorrhage (EDH)","0.3%"]],"caption_candidate":"Table 2 Clinical testing data subgroup information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242295-p5-t0","doc_id":"K242295","page_num":5,"bbox":[73.4,262.16,437.68,348.39],"n_rows":9,"n_cols":2,"columns":["Proprietary Name","Bunkerhill BMD"],"rows":[["Proprietary Name","Bunkerhill BMD"],["",""],["Classification Name","Bone Densitometer"],["",""],["Regulation Number","21 CFR 892.1170"],["",""],["Product Code","KGI"],["",""],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242295-p5-t1","doc_id":"K242295","page_num":5,"bbox":[73.4,378.45,437.68,504.35],"n_rows":12,"n_cols":2,"columns":["Proprietary Name","ABMD software"],"rows":[["Proprietary Name","ABMD software"],["",""],["Premarket","K213760"],["Notification",""],["Classification Name","Bone Densitometer"],["",""],["Regulation Number","21 CFR 892.1170"],["",""],["Product Code","KGI"],["",""],["Regulatory Class","II"],["",""]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242295-p6-t0","doc_id":"K242295","page_num":6,"bbox":[92.67,507.08,523.61,680.64],"n_rows":8,"n_cols":4,"columns":["","Proposed","Predicate","Summary"],"rows":[["","Proposed","Predicate","Summary"],["","Device:","Device: ABMD",""],["","Bunkerhill","SW(K213760)",""],["","BMD","",""],["Product code","KGI","KGI","Same"],["Regulation\nnumber","21 CFR §892.1170","21 CFR §892.1170","Same"],["Modality","Computed\ntomography (CT)","Computed\ntomography (CT)","Same"],["Image format","DICOM","DICOM","Same"]],"caption_candidate":"below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242295-p7-t0","doc_id":"K242295","page_num":7,"bbox":[92.66,68.62,523.64,171.21],"n_rows":2,"n_cols":4,"columns":["Device provides\nestimates of bone\nmineral density,\nT- scores and Z-\nscores","Yes","Yes","Similar, subject\ndevice provides a\nsubset of predicate\ndevice outputs i.e.\nonly T- score group."],"rows":[["Device provides\nestimates of bone\nmineral density,\nT- scores and Z-\nscores","Yes","Yes","Similar, subject\ndevice provides a\nsubset of predicate\ndevice outputs i.e.\nonly T- score group."],["User","Healthcare provider","Healthcare Provider","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242295-p7-t1","doc_id":"K242295","page_num":7,"bbox":[92.66,186.23,533.86,567.33],"n_rows":7,"n_cols":4,"columns":["","Proposed Device:","Predicate Device:","Summary"],"rows":[["","Proposed Device:","Predicate Device:","Summary"],["","Bunkerhill BMD","ABMD SW(K213760)",""],["Retrospective\nmeasurements\nfrom CT scans","CT scan images can\nbe selected and\ninputted to the\nsoftware","CT scan images can be\nselected and inputted to\nthe software.","Same"],["Automatic\naveraging\nHounsfield Units","Software\nautomatically\nmeasures and\naverages Hounsfield\nunits in the regions of\ninterest of spinal\nbones.","Software automatically\nmeasures and averages\nHounsfield units in the\ntrabecular region of the\nspinal bones.","Same"],["Main image\nquality","DICOM","DICOM","Same"],["Calibration","Software outputs\ncalibrated BMD\nscore.","Software outputs\ncalibrated BMD score.","Same"],["Generate patient\nreport","Optional to copy\nresult to clipboard,\ninsert in report,\nDICOM Secondary\nCapture","Optional to copy result\nto clipboard, insert in\nreport, DICOM\nSecondary Capture","Same"]],"caption_candidate":"User Healthcare provider Healthcare Provider Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242300-p7-t0","doc_id":"K242300","page_num":7,"bbox":[72.01,486.04,467.08,698.82],"n_rows":7,"n_cols":6,"columns":["","Designation","","Title","Standards\nDevelopment\nOrganization","Recognition\nNumber"],"rows":[["","Designation","","Title","Standards\nDevelopment\nOrganization","Recognition\nNumber"],["","Number and","","","",""],["","Edition/Dat","","","",""],["","e","","","",""],["PS 3.1 - 3.20\n2023e","","","Digital Imaging and Communications in Medicine\n(DICOM) Set","NEMA","12-349"],["62304\nEdition 1.1\n2015-06\nCONSOLIDA\nTED\nVERSION","","","Medical Device Software –Software Life Cycle\nProcesses","AAMI, ANSI,\nIEC","13-79"],["14971 Third\nEdition\n2019-12","","","Medical devices – Application of risk management to\nmedical devices","ISO","5-125"]],"caption_candidate":"listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242300-p8-t0","doc_id":"K242300","page_num":8,"bbox":[72.0,72.18,467.1,295.62],"n_rows":3,"n_cols":4,"columns":["62366-1\nEdition 1.1\n2020-06\nCONSOLIDA\nTED\nVERSION","Medical devices - Part 1: Application of usability\nengineering to medical devices","AAMI, ANSI,\nIEC","5-129"],"rows":[["62366-1\nEdition 1.1\n2020-06\nCONSOLIDA\nTED\nVERSION","Medical devices - Part 1: Application of usability\nengineering to medical devices","AAMI, ANSI,\nIEC","5-129"],["15223-1\nFourth\nedition\n2021-07","Medical devices -Symbols to be used with medical\ndevice labels, labelling, and information to be\nsupplied - Part 1: General requirements","ISO","5-134"],["20417 First\nedition\n2021-04\nCorrected\nversion\n2021-12","Medical devices – Information to be supplied by the\nmanufacturer","ISO","5-135"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242334-p7-t0","doc_id":"K242334","page_num":7,"bbox":[72.28,245.89,595.94,681.16],"n_rows":6,"n_cols":4,"columns":["Comparison of\nTechnological\nCharacteristics","Subject Device Ezra Flash","Primary Predicate\n(K230264)","Secondary Predicate\n(K203182)"],"rows":[["Comparison of\nTechnological\nCharacteristics","Subject Device Ezra Flash","Primary Predicate\n(K230264)","Secondary Predicate\n(K203182)"],["Trade Name:","EzraFlash","EzraFlash","SubtleMR"],["Regulation\nNumber:","21 CFR 892.2050","Same","Same"],["Product Code","QIH","LLZ","LLZ"],["Indications for\nUse","Ezra Flash is an image pro-\ncessing software used for im-\nage enhancement of MR im-\nages. It can be used to\nreduce image noise in im-\nages acquired as part of non-\ncontrast MRI exams on 1.5-\nTesla and 3-Tesla Siemens\nand GE scanners for patients\n> 18 years of age:\n• Sagittal T1, Axial\nT2 and Axial Flair\nsequences within the\nhead region\n• Axial T2, Coronal T2\nwithin the Abdomen\nregion\n• Sagittal T2, Axial T2,\nCoronal T2 within the\nPelvis region","Ezra Flash is an image pro-\ncessing software used for im-\nage enhancement of MR im-\nages. It can be used to\nreduce image noise in im-\nages acquired as part of non-\ncontrast MRI exams on 3-\nTesla Siemens and GE scan-\nners for Sagittal T1, Axial\nT2 and Axial Flair sequences\nwithintheheadregionforpa-\ntients > 18 years of age.","SubtleMR is an image pro-\ncessing software that can be\nused for image enhancement\nin MRI images. It can\nbe used to reduce image\nnoise for head, spine, neck,\nabdomen, pelvis, prostate,\nbreast and musculoskeletal\nMRI, or increase image\nsharpness for head MRI."],["Physical Char-\nacteristics","Software package that op-\nerates on off-the-shelf hard-\nware.","Same","Same"]],"caption_candidate":"characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242334-p8-t0","doc_id":"K242334","page_num":8,"bbox":[72.29,158.51,595.93,544.07],"n_rows":6,"n_cols":4,"columns":["Computer","Linux Compatible","Same","Same"],"rows":[["Computer","Linux Compatible","Same","Same"],["DICOM Stan-\ndard Compli-\nance","The software processes DI-\nCOM compliant image data","Same","Same"],["Operating Sys-\ntem","Linux","Same","Same"],["Modalities","MRI","Same","Same"],["User Interface","None – enhanced images\nare viewed on existing PACS\nworkstations","Same","Same"],["Image Enhance-\nment Algorithm\nDescription","Ezra Flash software imple-\nments an image enhance-\nment algorithm using a con-\nvolutional neural network-\nbased filtering. Original im-\nages are enhanced by run-\nning through a cascade of\nfilter banks, where thresh-\nolding and scaling operations\nare applied. These filters\nresult in a single machine-\nlearning model that reduces\nnoise. A dedicated machine-\nlearningmodelisusedforthe\nhead and body. The pa-\nrameters of the filters were\nobtained through an image-\nguided optimization process.","Ezra Flash software imple-\nments an image enhance-\nment algorithm using a con-\nvolutional neural network-\nbased filtering. Original im-\nages are enhanced by run-\nning through a cascade of\nfilter banks, where thresh-\nolding and scaling operations\nare applied. These filters\nresult in a single machine-\nlearning model that reduces\nnoise. The parameters of the\nfilters were obtained through\nan image-guided optimiza-\ntion process.","SubtleMR software imple-\nments an image enhance-\nment algorithm using con-\nvolutional neural network-\nbased filtering. Original im-\nages are enhanced by run-\nning through a cascade of\nfilter banks, where thresh-\nolding and scaling operations\nare applied. Separate neural\nnetwork-based filters are ob-\ntainedfornoisereductionand\nsharpness increase. The pa-\nrameters of the filters were\nobtained through an image-\nguided optimization process."]],"caption_candidate":"Linux Compatible Same Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242338-p5-t0","doc_id":"K242338","page_num":5,"bbox":[89.83,175.77,522.0,300.8],"n_rows":15,"n_cols":4,"columns":["","","","Cleerly, Inc."],"rows":[["","","","Cleerly, Inc."],["","Submitter","",""],["","","",""],["","","","Amit Relia, Vice President, Regulatory and Quality Affairs"],["","Contact Person","",""],["","","",""],["","","","1099 18th St Suite 2860, Denver CO 80202"],["","Address","",""],["","","",""],["","","","(949)701-6918"],["","Phone","",""],["","","",""],["","","","Amit.Relia@cleerlyhealth.com"],["","Email","",""],["","","",""]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242338-p5-t1","doc_id":"K242338","page_num":5,"bbox":[89.83,360.03,522.0,503.43],"n_rows":18,"n_cols":4,"columns":["","","","Cleerly LABS (v2.0)"],"rows":[["","","","Cleerly LABS (v2.0)"],["","Trade Name","",""],["","","",""],["","","","Automated radiological image processing software"],["","Common Name","",""],["","","",""],["","","","Medical image management and processing system."],["","Classification Name","",""],["","","",""],["","","","Class II, § 892.2050"],["","Product Classification","",""],["","","",""],["","","","QIH"],["","Primary Product Code","",""],["","","",""],["","","","LLZ"],["","Subsequent Product Code","",""],["","","",""]],"caption_candidate":"2. Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242338-p5-t2","doc_id":"K242338","page_num":5,"bbox":[89.83,562.71,522.0,706.1],"n_rows":18,"n_cols":4,"columns":["","","","Cleerly LABS (v2.0)"],"rows":[["","","","Cleerly LABS (v2.0)"],["","Trade Name","",""],["","","",""],["","","","System, Image Processing, Radiological"],["","Common Name","",""],["","","",""],["","","","Medical image management and processing system."],["","Classification Name","",""],["","","",""],["","","","Class II, § 892.2050"],["","Product Classification","",""],["","","",""],["","","","LLZ"],["","Product Code","",""],["","","",""],["","","","K202280"],["","Submission Number","",""],["","","",""]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p5-t0","doc_id":"K242342","page_num":5,"bbox":[67.5,125.5,485.5,296.5],"n_rows":7,"n_cols":2,"columns":["Applicant:","BrightHeart\n7-11boulevardHaussmann\nParis75009,France"],"rows":[["Applicant:","BrightHeart\n7-11boulevardHaussmann\nParis75009,France"],["",""],["Contact:","ChristopheGardella\nChiefTechnicalOfficer\nTel.+003669650566\nEmail.christophe@brightheart.fr"],["",""],["SubmissionCorrespondent:","ChristopheGardella"],["",""],["DatePrepared:","October21, 2024"]],"caption_candidate":"UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p5-t1","doc_id":"K242342","page_num":5,"bbox":[67.5,343.5,489.5,443.5],"n_rows":5,"n_cols":2,"columns":["DeviceTradeName:","FetalEchoScan"],"rows":[["DeviceTradeName:","FetalEchoScan"],["DeviceCommonName:","Medicalimageanalyzer"],["ClassificationName","Radiologicalcomputer-assisteddiagnosticsoftwarefor\nlesionssuspiciousfor cancer21CFR 892.2060"],["RegulatoryClass:","ClassII"],["ProductCode:","POK"]],"caption_candidate":"EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p6-t0","doc_id":"K242342","page_num":6,"bbox":[66.25,659.5,545.37,710.5],"n_rows":2,"n_cols":3,"columns":["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],"rows":[["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],["510(k)Number","TBD","K201555"]],"caption_candidate":"Table 1. TechnologicalComparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p7-t0","doc_id":"K242342","page_num":7,"bbox":[66.33,72.13,545.42,660.5],"n_rows":10,"n_cols":3,"columns":["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],"rows":[["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],["Applicant","BrightHeart","UltromicsLtd."],["ClassificationRegulation","892.2060","892.2060"],["ProductCode","POK","POK"],["DeviceType","SaMD","SaMD"],["Softwarealgorithm","MachineLearningModel","MachineLearningModel"],["ImagingModality","FetalUltrasound","AdultStressEchocardiography"],["ModelInputs","Fetalultrasoundstudycontaining\nthefollowingviews:4chamber,left\nventricularoutflowtract,right\nventricularoutflowtract","Electrocardiogramwithapical2\nchamber,4chamberandparasternal\nshortaxis(SAX)views."],["Modelmethod","Suspiciousradiographicfindings\ncategorizedinto2groups:\n● “classification”featuresare\nbasedontheidentificationof\nmorphologicalfeatureswithin\nthevideoclip.\n● “measurement”featuresare\nbasedonthedetectionand\nsegmentationofkeyanatomic\npoints","Thesoftwareautomaticallyregisters\nimages,andsegmentsandanalyses\nselectedregionsofinterest(ROI).\nGeometricparametersarecalculated\nfromtheapprovedcontoursandare\nfedintoafixedclassificationmodel\nthathasbeenpreviouslytrainedon\ndatasetswithknownoutcomes.The\noutputofthemodelgeneratesa\nreportwhichcontainsacategorical\nassessmentastowhetherthedata\nareconsistentwithsignificantCAD\nornot."],["Modeltrainedtoidentify","Identifiablesuspiciousradiographic\nfindingsofthefetalheart\n● overridingartery\n● septaldefectatthecardiaccrux\n● abnormalrelationshipofthe\noutflowtracts\n● enlargedcardiothoracicratio\n● rightventriculartoleft\nventricularsizediscrepancy\n● tricuspidvalvetomitralvalve\nannularsizediscrepancy\n● pulmonaryvalvetoaorticvalve\nannularsizediscrepancy\n● cardiacaxisdeviation","Coronaryarterydisease"]],"caption_candidate":"510(k)Summary Page3of8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p8-t0","doc_id":"K242342","page_num":8,"bbox":[66.33,72.13,545.42,206.5],"n_rows":2,"n_cols":3,"columns":["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],"rows":[["","SubjectDevice\nFetalEchoScan","PredicateDevice\nEchoGoProv1.0.2"],["ModelOutput","Foreachframethesoftware\nevaluateswhetherthefindingsare:\npresent,absent,orinconclusive.\nA“recordsummarytable”displays\nasummaryofresultsforeachvideo\nclip.An“examsummarytable”\ndisplaysasummaryoftheresultsfor\ntheoverallstudy.","Categoricalassessmentasto\nwhetherthedataaresuggestiveofa\nhigherorlowerpossibilityof\nsignificantcoronaryarterydisease\nornot"]],"caption_candidate":"510(k)Summary Page4of8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p10-t0","doc_id":"K242342","page_num":10,"bbox":[87.72,72.17,523.5,386.38],"n_rows":11,"n_cols":5,"columns":["","InconclusiveExams\nCountedasNegative","","InconclusiveExams\nCountedasPositive",""],"rows":[["","InconclusiveExams\nCountedasNegative","","InconclusiveExams\nCountedasPositive",""],["","Sensitivity\n(Worst-Case)","Specificity\n(Best-Case)","Sensitivity\n(Best-Case)","Specificity\n(Worst-Case)"],["Anysuspiciousfindings","0.977(0.954;\n0.989)","0.977(0.961;\n0.987)","0.987(0.967;\n0.995)","0.963(0.944;\n0.976)"],["Overridingartery","0.894(0.820;\n0.940)","0.989(0.977;\n0.995)","0.942(0.880;\n0.973)","0.979(0.963;\n0.988)"],["Cardiac crux septal\ndefect","0.905(0.823;\n0.951)","0.995(0.985;\n0.998)","0.917(0.838;\n0.959)","0.989(0.977;\n0.995)"],["Abn.OTrelationship","0.869(0.781;\n0.925)","0.991(0.979;\n0.996)","0.952(0.884;\n0.981)","0.989(0.977;\n0.995)"],["EnlargedCTR","0.955(0.876;\n0.985)","1.000(0.993;\n1.000)","0.955(0.876;\n0.985)","1.000(0.993;\n1.000)"],["Cardiacaxisdeviation","0.945(0.851;\n0.981)","1.000(0.993;\n1.000)","0.945(0.851;\n0.981)","1.000(0.993;\n1.000)"],["PV/AVsizediscrepancy","0.954(0.914;\n0.975)","0.989(0.977;\n0.995)","0.954(0.914;\n0.975)","0.989(0.977;\n0.995)"],["RV/LVsizediscrepancy","0.950(0.900;\n0.975)","1.000(0.993;\n1.000)","0.950(0.900;\n0.975)","1.000(0.993;\n1.000)"],["TV/MVsize\ndiscrepancy","0.943(0.896;\n0.970)","1.000(0.993;\n1.000)","0.943(0.896;\n0.970)","1.000(0.993;\n1.000)"]],"caption_candidate":"510(k)Summary Page6of8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242342-p11-t0","doc_id":"K242342","page_num":11,"bbox":[66.72,430.36,544.5,617.66],"n_rows":11,"n_cols":5,"columns":["","Aided","Unaided","AidedminusUnaided",""],"rows":[["","Aided","Unaided","AidedminusUnaided",""],["","ModelEstimateAUC\n(95%CI)","ModelEstimateAUC\n(95%CI)","ModelEstimateDifference\n(95%CI)","DBM-OR\np-value"],["Anysuspiciousfindings","0.974(0.957;0.990)\n0.953(0.916;0.990)\n0.971(0.943;0.999)\n0.972(0.953;0.992)\n0.960(0.930;0.989)\n0.967(0.932;1.000)\n0.979(0.962;0.997)\n0.991(0.983;0.999)\n0.964(0.938;0.990)","0.825(0.741;0.908)\n0.803(0.719;0.888)\n0.857(0.782;0.933)\n0.832(0.738;0.927)\n0.746(0.666;0.826)\n0.786(0.704;0.867)\n0.839(0.756;0.921)\n0.868(0.801;0.936)\n0.850(0.779;0.921)","0.149(0.066;0.232) 0.002\n0.150(0.063;0.237) 0.002\n0.114(0.042;0.186) 0.004\n0.140(0.048;0.232) 0.005\n0.214(0.131;0.297) <0.001\n0.181(0.106;0.256) <0.001\n0.140(0.060;0.221) 0.002\n0.123(0.055;0.190) 0.001\n0.114(0.048;0.179) 0.002",""],["Overridingartery","","","",""],["Cardiaccruxseptaldefect","","","",""],["Abn.OTrelationship","","","",""],["EnlargedCTR","","","",""],["Cardiacaxisdeviation","","","",""],["PV/AVsizediscrepancy","","","",""],["RV/LVsizediscrepancy","","","",""],["TV/MVsizediscrepancy","","","",""]],"caption_candidate":"butpossiblypositivetootherfindings.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p5-t0","doc_id":"K242359","page_num":5,"bbox":[90.0,136.71,456.97,704.93],"n_rows":56,"n_cols":2,"columns":["GeneralInformation",""],"rows":[["GeneralInformation",""],["",""],["510(k)Sponsor","ExoInc."],["",""],["Address","4201BurtonDrive"],["","SantaClara,CA95054"],["",""],["CorrespondencePerson","JacquelineMurray"],["",""],["ContactInformation","jmurray@exo.inc"],["",""],["","Cell:+1236-838-5056"],["",""],["DatePrepared","August8,2024"],["",""],["ProposedDevice",""],["",""],["ProprietaryName","StrainAI(SAI001)"],["",""],["CommonName","StrainAI"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["PredicateDevice",""],["",""],["ProprietaryName","LVivoSoftwareApplication"],["",""],["PremarketNotification","K210053"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"],["",""],["ReferenceDevice",""],["",""],["ProprietaryName","Us2.v2"],["",""],["PremarketNotification","K233676"],["",""],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["",""],["RegulationNumber","21CFR892.2050"],["",""],["ProductCode","QIH"],["",""],["RegulatoryClass","II"]],"caption_candidate":"GeneralInformation","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242359-p5-t1","doc_id":"K242359","page_num":5,"bbox":[85.5,309.69,534.5,417.69],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","StrainAI(SAI001)"],"rows":[["ProprietaryName","StrainAI(SAI001)"],["CommonName","StrainAI"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ProposedDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p5-t2","doc_id":"K242359","page_num":5,"bbox":[85.5,455.91,534.5,563.62],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","LVivoSoftwareApplication"],"rows":[["ProprietaryName","LVivoSoftwareApplication"],["PremarketNotification","K210053"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"PredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p5-t3","doc_id":"K242359","page_num":5,"bbox":[85.5,601.54,534.5,709.54],"n_rows":6,"n_cols":2,"columns":["ProprietaryName","Us2.v2"],"rows":[["ProprietaryName","Us2.v2"],["PremarketNotification","K233676"],["ClassificationName","AutomatedRadiologicalImageProcessingSoftware"],["RegulationNumber","21CFR892.2050"],["ProductCode","QIH"],["RegulatoryClass","II"]],"caption_candidate":"ReferenceDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p6-t0","doc_id":"K242359","page_num":6,"bbox":[72.07,437.87,539.66,698.5],"n_rows":4,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nStrainAI","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nUs2.v2(K233676)"],"rows":[["Feature/\nFunction","SubjectDevice\nStrainAI","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nUs2.v2(K233676)"],["Physical\nCharacteristic","Softwarepackagethat\noperatesutilizing\noff-the-shelfhardware","Sameassubjectdevice","Sameassubjectdevice"],["Scantype","Multi-frameultrasound\nimages","Sameassubjectdevice","Sameassubjectdevice"],["Principleof\nOperationand\nTechnology","Ultrasoundimage\nprocessingsoftware\nimplementingartificial\nintelligenceincluding\nnon-adaptivemachine\nlearningalgorithmstrained\nwithclinicaldataintended\nfornon-invasiveanalysisof\nultrasounddata","Sameassubjectdevice","Sameassubjectdevice"]],"caption_candidate":"ComparisonofTechnologicalCharacteristicswiththePredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p7-t0","doc_id":"K242359","page_num":7,"bbox":[72.06,93.59,539.64,299.5],"n_rows":4,"n_cols":4,"columns":["Feature/\nFunction","SubjectDevice\nStrainAI","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nUs2.v2(K233676)"],"rows":[["Feature/\nFunction","SubjectDevice\nStrainAI","PredicateDevice\nLVivoSoftwareApplication\n(K210053)","ReferenceDevice\nUs2.v2(K233676)"],["AIAlgorithm","DeepConvolutionalNeural\nNetworksfor\nSegmentationor\nLandmarkDetection","SameasSubject\nDevice","Sameassubjectdevice"],["AnatomicalSites","Heart","Heart,Bladder","Sameassubjectdevice"],["GLScalculation","Yes","SameasSubject\nDevice","SameasSubjectDevice"]],"caption_candidate":"510(k)Summary-StrainAI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242359-p8-t0","doc_id":"K242359","page_num":8,"bbox":[72.13,169.65,540.17,215.5],"n_rows":2,"n_cols":3,"columns":["Measurement","ICC(95%CI)","RMSD(95%CI)"],"rows":[["Measurement","ICC(95%CI)","RMSD(95%CI)"],["GlobalLongitudinalStrain(GLS)","0.95(0.91–0.97)","2.76(2.44–3.17)"]],"caption_candidate":"Table1:SummaryofStrainAIaccuracyandreliabilityforcardiacultrasoundimages","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p5-t0","doc_id":"K242362","page_num":5,"bbox":[72.24,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 1 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p5-t1","doc_id":"K242362","page_num":5,"bbox":[72.24,398.45,315.41,587.86],"n_rows":8,"n_cols":2,"columns":["Item","Description"],"rows":[["Item","Description"],["Device Name","Lightning Viewer"],["Manufacturer","Nexsys Electronics Inc. dba Medweb"],["Product Code","LLZ"],["Regulation Number","892.2050"],["Regulation Name","System, Image Processing, Radiological"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"2.DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p5-t2","doc_id":"K242362","page_num":5,"bbox":[72.24,633.94,315.41,704.98],"n_rows":3,"n_cols":2,"columns":["Item","Description"],"rows":[["Item","Description"],["Device Name","OmegaAI Image Viewer"],["Manufacturer","RamSoft Inc."]],"caption_candidate":"3.PREDICATE DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p6-t0","doc_id":"K242362","page_num":6,"bbox":[72.21,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 2 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p6-t1","doc_id":"K242362","page_num":6,"bbox":[72.21,117.38,315.41,283.13],"n_rows":7,"n_cols":2,"columns":["Item","Description"],"rows":[["Item","Description"],["510(k) Number","K222476"],["Product Code","LLZ"],["Regulation Number","892.2050"],["Regulation Name","System, Image Processing, Radiological"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"Effective Date: 2024-12-20 Page 2 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p7-t0","doc_id":"K242362","page_num":7,"bbox":[72.02,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 3 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p8-t0","doc_id":"K242362","page_num":8,"bbox":[72.02,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 4 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p9-t0","doc_id":"K242362","page_num":9,"bbox":[72.18,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 5 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p9-t1","doc_id":"K242362","page_num":9,"bbox":[72.18,437.11,539.86,688.18],"n_rows":4,"n_cols":4,"columns":["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],"rows":[["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],["Intended Use","Lightning Viewer is\nintended for diagnostic\npurposes and to be used\nas a review tool.","The OmegaAI Image Viewer\nis intended for diagnostic\npurposes and to be used as a\nreview tool.","Same"],["Mammographic\nUse","Lossy image\ncompression should not\nbe used for primary\nreading in\nmammography.","Lossy image\ncompression should not be\nused for primary reading in\nmammography.","Same"],["Image\nManipulation\nFeatures","Adjustment Tools:\nWindow level, rotate,\nflip, pan, stack scroll, and\nzoom.\nMarkup Tools:\nAnnotate, angle, cobb\nangle, probe, Mark ROI,\nand measurement.","Adjustment Tools:\nWindow level, rotate, flip,\npan, stack scroll, and zoom.\nMarkup Tools:\nAnnotate, angle, cobb angle,\nprobe, Mark ROI, and\nmeasurement.","Same"]],"caption_candidate":"8.2. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p10-t0","doc_id":"K242362","page_num":10,"bbox":[72.2,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 6 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p10-t1","doc_id":"K242362","page_num":10,"bbox":[72.2,117.38,539.86,711.46],"n_rows":6,"n_cols":4,"columns":["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],"rows":[["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],["Specialized\nTools","Spine labeling;\nMammography tools","Unknown.","The subject device has specialized tools for\nspecific use cases, such as spine labeling\nand mammography tools. These tools fall\nunder the same general intended use to\nreview and navigate diagnostic images and\naiding users in visualizing a region of\ninterest. Thus, the inclusion of these\nspecialized tools do not raise any new\nquestions of safety and effectiveness."],["Support\nModalities","Supports the following\nimage modalities\nCR/DR/XR, CT, FL, MR,\nMG, NM, US/US Echo,\nPET and VL.","View all image modalities,\nincluding CR, CT, DX, MR,\nMG, NM, US, PET, RG, SC,\nVL, XA, PET, and Film\nDigitizer.","Both devices support a wide range of image\nmodalities, including CR, CT, MR, MG,\nNM, US, PET, and VL. The predicate\ndevice supports additional modalities like\nDX, RG, SC, XA, and Film Digitizer. This\ndifference does not raise any new questions\nof safety or effectiveness. The additional\nmodalities supported by the predicate device\ndo not impact the safety or effectiveness of\nLightning Viewer for its intended use cases."],["Architecture","A web-based software\nsolution that displays\nimages and reports from a\nPACS through a zero-\nfootprint application\naccessible via a web\nbrowser, requiring no\ninstallation.","Server-based software\nsolution that displays images\nand reports from a PACS\nusing a zero-footprint\napplication (browser).\nNo installation is needed.","Both devices are zero-footprint and require\nno installation. The subject device is web-\nbased, while the predicate device is server-\nbased. The architectural difference does not\nimpact the core functionality, safety, or\neffectiveness of either device. Both\narchitectures are commonly used in medical\nimaging and have established safety and\nperformance profiles."],["Technology","Use of various\ntechnology standards like\nDICOM, DICOMweb,\nWADO, Rest, HL7.","Use of various technology\nstandards (LDAP, SSO,\nHTTPS, HTML, HL-7\nIntegration web services,\netc.)","Both devices utilize industry-standard\ntechnologies for communication and data\nexchange (DICOM, HL7). Each device uses\na different set of additional technologies to\nsupport its architecture and features (e.g.,\nweb-based vs. server-based). These\ndifferences do not impact the safety or\neffectiveness of the devices. The different\ntechnologies used by the devices are all\nindustry-standard and well-established for\ntheir respective purposes (security,\ncommunication, data exchange)."],["Support\nPlatforms,\nDevices","Supports major browsers\nlike Chrome and Safari.","Supports major desktop (for\ndiagnostic purposes) and\nmobile platforms (for non-\ndiagnostic purposes; can be\nused as a review tool) such as\nMicrosoft Edge, Chrome,","The predicate device supports a wider range\nof platforms, including desktop and mobile\noperating systems. Lightning Viewer is\ndesigned as a web-based application and\nrelies on the browser's capabilities for\ncompatibility and rendering. This difference"]],"caption_candidate":"Effective Date: 2024-12-20 Page 6 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p11-t0","doc_id":"K242362","page_num":11,"bbox":[72.14,36.24,544.3,102.02],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary","DOC-0031\nRev C"],"rows":[["","510(k) Summary","DOC-0031\nRev C"],["","Effective Date: 2024-12-20","Page 7 of 7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242362-p11-t1","doc_id":"K242362","page_num":11,"bbox":[72.14,117.38,539.86,169.94],"n_rows":2,"n_cols":4,"columns":["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],"rows":[["Feature","Lightning Viewer","OmegaAI Image Viewer","Comments"],["","","Safari, Apple iOS, Android,\nWindows and Mac devices.","does not raise new questions of safety or\neffectiveness."]],"caption_candidate":"Effective Date: 2024-12-20 Page 7 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242403-p7-t0","doc_id":"K242403","page_num":7,"bbox":[113.66,67.68,603.12,284.09],"n_rows":3,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product Code","510(k)\nNumber","Clearance\nDate"],["Primary\nPredicate Device\nAquilion ONE (TSX-\n308A/3) V1.4 with\nPIQE Reconstruction\nSystem","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K232835","April 2, 2024"],["Reference\nPredicate Device\nAquilion ONE (TSX-\n306A/3) V10.12 with\nSpectral Imaging\nSystem","Canon\nMedical\nSystems, USA","21 CFR\n§892.1750","Computed\nTomography\nX-ray System","JAK:\nSystem, X-ray,\nTomography,\nComputed","K213504","June 16, 2022"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242403-p8-t0","doc_id":"K242403","page_num":8,"bbox":[112.82,269.97,571.6,583.99],"n_rows":10,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","Device Name,","","Aquilion ONE (TSX-308A/3) V1.5","Aquilion ONE (TSX-308A/3) V1.5","","","Aquilion ONE (TSX-308A/3) V1.4",""],["","Model Number","","","","","","with PIQE Reconstruction System",""],["","510(k) Number","","","This submission","","","K232835",""],["PIQE Reconstruction\nSystem (CRRS-001A)\n▪ Scan Regions\n▪ Scan Type","","","Available\n▪ Cardiac, Lung, Abdomen and pelvis\n(Body)\n▪ Volume scan, Dynamic volume scan,\nHelical scan","","","Available\n▪ Cardiac, Abdomen and pelvis (Body)\n▪ Volume scan, Dynamic volume scan,\nHelical scan","",""],["3D Landmark Scan","","","Available X-ray tube voltage: 120kV","","","Available X-ray tube voltage: 120/135kV","",""],["Spectral Imaging\nSystem (CSDE-004A)","","","Option:\nBODY, LUNG, BONE and CARDIAC\n(Cardiac previously cleared under\nK213504)","","","Option:\nBODY, LUNG and BONE","",""],["Motion Correction\nAdvanced Patient\nMotion Correction\n(APMC)\nCLEAR Motion\n(CSCM-001A)","","","Available\nAvailable","","","Available\nNot Available","",""],["Connect Assistance\n(COCA-001A)","","","Available\n(Previously cleared under K213504)","","","Not Available","",""],["Area Finder\n(CGAP-003A)","","","Available\n(Previously cleared under K213504)","","","Not Available","",""]],"caption_candidate":"and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p5-t0","doc_id":"K242437","page_num":5,"bbox":[72.24,407.12,330.9,546.92],"n_rows":6,"n_cols":2,"columns":["Trade Name","Smile Dx®"],"rows":[["Trade Name","Smile Dx®"],["Common Name","Computer-Assisted Detection Device"],["Classification Name","Medical Image Analyzer"],["Primary Product Code","MYN"],["Primary Regulation Number","21 CFR 892.2070"],["Secondary Product Code","LLZ"]],"caption_candidate":"2.DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p5-t1","doc_id":"K242437","page_num":5,"bbox":[72.24,591.95,272.46,638.45],"n_rows":2,"n_cols":2,"columns":["Predicate Device Name","Overjet Caries Assist"],"rows":[["Predicate Device Name","Overjet Caries Assist"],["Predicate Device K Number","K212519"]],"caption_candidate":"3.PRIMARY PREDICATE DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p6-t0","doc_id":"K242437","page_num":6,"bbox":[72.12,120.8,273.13,190.55],"n_rows":3,"n_cols":2,"columns":["Predicate Device K Number","K210365"],"rows":[["Predicate Device K Number","K210365"],["Predicate Device Name","Overjet Dental Assist"],["Predicate Device K Number","K210187"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p7-t0","doc_id":"K242437","page_num":7,"bbox":[72.19,368.12,539.98,716.73],"n_rows":6,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["Manufacturer","Cube Click, Inc.","Overjet, Inc.","Pearl Inc.","Overjet, Inc.","N/A"],["Regulation\nNumber","892.2070","892.2070","892.2070","892.2050","Smile Dx® falls\nunder the same\nregulation\n(892.2070) as\nprimary predicate\n(Overjet Caries\nAssist)."],["Regulation\nName","Medical image\nanalyzer","Medical image\nanalyzer","Medical image\nanalyzer","Picture archiving\nand\ncommunications\nsystem","Smile Dx® falls\nunder the same\nregulation\n(892.2070) as\npredicate (Overjet\nCaries Assist)."],["Regulatory\nClass","Class II","Class II","Class II","Class II","Same"],["Product Code","MYN; LLZ","MYN","MYN","LLZ","Smile Dx® has the\nsame primary\nproduct MYN as\npredicate (Overjet\nCaries Assist) and\nreference device"]],"caption_candidate":"For technological characteristics comparison, the following table is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p8-t0","doc_id":"K242437","page_num":8,"bbox":[72.15,120.8,539.98,718.23],"n_rows":4,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","","","","","(Second Opinion).\nAdditionally, Smile\nDx®’s secondary\nproduct code LLZ is\nthe same as reference\ndevice (Overjet\nDental Assist). Thus,\nthe subject device\nhas the same product\ncodes as the\nidentified predicate\nand reference\ndevices."],["Device\nProperty","SaMD/CADe","SaMD/CADe","SaMD/CADe","SaMD","Same"],["Indications for\nUse","Smile Dx® is a\ncomputer-assisted\ndetection (CADe)\nsoftware designed\nto aid dentists in\nthe review of\ndigital files of\nbitewing and\nperiapical\nradiographs of\npermanent teeth.\nIt is intended to\naid in the\ndetection and\nsegmentation of\nsuspected dental\nfindings which\ninclude: caries,\nperiapical\nradiolucencies\n(PARL),\nrestorations, and\ndental anatomy.\nSmile Dx® is\nalso intended to\naid dentists in the\nmeasurement (in\nmillimeter and\npercentage\nmeasurements) of\nmesial and distal\nbone levels\nassociated with","The Overjet\nCaries Assist\n(OCA) is a\nradiological,\nautomated,\nconcurrent read,\ncomputer-\nassisted detection\nsoftware\nintended to aid in\nthe detection and\nsegmentation of\ncaries on\nbitewing\nradiographs. The\ndevice provides\nadditional\ninformation for\nthe dentist to use\nin their diagnosis\nof a tooth surface\nsuspected of\nbeing carious.\nThe device is not\nintended as a\nreplacement for a\ncomplete\ndentist's review\nor their clinical\njudgment that\ntakes into\naccount other\nrelevant","Second Opinion®\nis a computer\naided detection\n(\"CADe\")\nsoftware to\nidentify and mark\nregions in relation\nto suspected dental\nfindings which\ninclude Caries,\nDiscrepancy at the\nmargin of an\nexisting\nrestoration,\nCalculus,\nPeriapical\nradiolucency,\nCrown (metal,\nincluding zirconia\n& non-metal),\nFilling (metal &\nnon-metal), Root\ncanal, Bridge and\nImplants.\nIt is designed to\naid dental health\nprofessionals to\nreview bitewing\nand periapical\nradiographs of\npermanent teeth in\npatients 12 years","Overjet Dental\nAssist is a\nradiological semi-\nautomated image\nprocessing\nsoftware device\nintended to aid\ndental\nprofessionals in\nthe measurements\nof mesial and\ndistal bone levels\nassociated with\neach tooth from\nbitewing and\nperiapical\nradiographs.\nIt should not be\nused in-lieu of full\npatient evaluation\nor solely relied\nupon to make or\nconfirm a\ndiagnosis. The\nsystem is to be\nused by trained\nprofessionals\nincluding, but not\nlimited to, dentists\nand dental\nhygienists.\nIntended Patient\nPopulation:","Smile Dx® has\nsimilar indications\nfor use to predicate\nK212519 for\ndetecting caries,\nreference device\nK210365 for\ndetecting PARLs,\nand reference device\nK210187 for\nmeasurement of bone\nlevels. Thus, the\nsubject device\ncombines the\nindications for use of\nthe three identified\npredicate and\nreference devices.\nAll three devices\nshare the same\nintended use to\nidentify suspected\nareas of interest in\nintra-oral\nradiographs."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p9-t0","doc_id":"K242437","page_num":9,"bbox":[72.12,120.8,539.98,716.48],"n_rows":3,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","each tooth.\nThe device is not\nintended as a\nreplacement for a\ncomplete dentist's\nreview or their\nclinical judgment\nthat takes into\naccount other\nrelevant\ninformation from\nthe image, patient\nhistory, and\nactual in vivo\nclinical\nassessment.\nSmile Dx®\nsupports both\ndigital and\nphosphor sensors.","information from\nthe image,\npatient history,\nand actual in\nvivo clinical\nassessment.","of age or older as a\nsecond reader.","The intended\npatient population\nof the device is\npatients living in\nthe United States,\nwho are 22 years\nold or older, and\nthat do not have\nany remaining\nprimary teeth.\nOverjet has not\nevaluated the\nperformance of\nthe device on\nprimary dentition.",""],["Detections\nand/or\nmeasurements","• Normal\nanatomy\n• Caries\n• Periapical\nradiolucencies\n• Bone level\nmeasurements\n(mesial and\ndistal)\n• Restorations","Caries","Caries, Margin\ndiscrepancy,\nCalculus,\nPeriapical\nradiolucencies,\nRestorations","Bone level\nmeasurements\n(mesial and distal)","Smile Dx® detects\ncaries similar to\npredicate Overjet\nCaries Assist\nK212519.\nSmile Dx® also\ndetects PARLs and\nrestorations, similar\nto reference device\nSecond Opinion\nK210365. Second\nOpinion also detects\nother features such as\nmargin discrepancy\nand calculus,\nhowever, these are\nnot supported by\nsubject device. The\nabsence of these\nfeatures in Smile\nDx® does not create\na new intended use.\nSmile Dx® also\nmeasures mesial and\ndistal bone levels,\nsame as reference\ndevice Overjet"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p10-t0","doc_id":"K242437","page_num":10,"bbox":[72.2,120.8,539.98,712.73],"n_rows":7,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","","","","","Dental Assist\nK210187."],["Intended User","Dentists","Dentists","Dentists","Dental\nprofessionals\nincluding, but not\nlimited to, dentists\nand dental\nhygienists.","Smile Dx® is\nintended for use by\nlicensed dentists,\nsame as all of the\nidentified predicate\nand reference\ndevices. The\nreference device\nOverjet Dental Assist\nis also intended for\nuse by other dental\nprofessionals, such\nas dental hygienists.\nHowever, use of\nSmile Dx® has been\nlimited to use by\nlicensed dentists\nonly."],["Patient\nPopulation","Patients requiring\ndental services,\nall sexes, at least\n22 years of age,\nand with\npermanent\ndentition.","Patients\nrequiring dental\nservices,\nall sexes, at least\n18 years of age,\nand with\npermanent\ndentition.","Patients requiring\ndental services,\nall sexes, at least\n12 years of age,\nand with\npermanent\ndentition.","Patients requiring\ndental services,\nall sexes, at least\n22 years of age,\nand with\npermanent\ndentition.","The intended patient\npopulation for Smile\nDx® is limited to\npatients with\npermanent dentition\nwho are at least 22\nyears of age. This is\nidentical to the\nreference device\nSecond Opinion.\nThis intended patient\npopulation age has\nbeen supported by\nuse of representative\npatient data in\ntesting."],["Rx or OTC","Rx-only","Rx-only","Rx-only","Rx-only","Same"],["Technical\nCharacteristics","","","","",""],["Platform","Web - Edge,\nChrome, FireFox,\nSafari","Web - Edge,\nChrome, Firefox","Local computer\napplication\n(Cloud-based\ninstallation)","Web - Edge,\nChrome, Firefox","The subject device is\na web-based\napplication, similar\nto Overjet Caries\nAssist and Overjet"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p11-t0","doc_id":"K242437","page_num":11,"bbox":[72.2,120.8,539.98,712.73],"n_rows":7,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","","","","","Dental Assist. It is\ncompatible with\nsimilar browsers and\nis also compatible\nwith Safari, which is\na commonly used\nbrowser."],["OS","Any","Any","Windows 7 or\nhigher","Any","The subject device is\ncompatible with any\noperating system,\nsame as predicate\nOverjet Caries Assist\nand reference device\nOverjet Dental\nAssist."],["User Interface","Mouse,\nKeyboard,\nTrackpad","Mouse,\nKeyboard,\nTrackpad","Mouse, Keyboard","Mouse, Keyboard,\nTrackpad","Same"],["Image\nModality","Radiograph","Radiograph","Radiograph","Radiograph","Same"],["Radiograph\nType","Bitewing and\nperiapical","Bitewing and\nperiapical","Bitewing and\nperiapical","Bitewing and\nperiapical","Same"],["Image Input\nSources","Images imported\nfrom local\ncomputer, from a\nrange of\nmanufacturers","Images imported\nfrom the\nradiographic\ndevice, or from\nthe practice\nmanagement\nsystem, from\nCarestream or\nSchick sensors","Radiography\ndevices from a\nrange of\nmanufacturers","Images imported\nfrom the\nradiographic\ndevice, or from\nthe practice\nmanagement\nsystem","Images are manually\nimported from the\ndentist user’s local\ncomputer into Smile\nDx®. The subject\ndevice does not\nconnect to practice\nmanagement systems\nlike Overjet Caries\nAssist and Overjet\nDental Assist.\nHowever, this\ndifference does not\nraise any new\nquestions of safety\nand effectiveness.\nAdditionally, Smile\nDx® is compatible\nwith images from a\nrange of radiography\ndevice"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p13-t0","doc_id":"K242437","page_num":13,"bbox":[72.17,120.8,539.98,719.98],"n_rows":5,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","user interface.\nThe dentist can\nadjust image\nsettings, display\nand hide the\npresented\nannotations.","display, hide,\ncreate and edit\nthe annotations\npresented.","displays it within\nits user interface.\nDetected features\nare highlighted\nwith color-coded\nboundary boxes\noverlaid on the\noriginal\nradiograph.","","device exclusively\nuploads images from\nthe local computer.\nSimilarly, users of\nSmile Dx® are\nrequired to manually\nupload images to the\nsoftware, whereas\nthe reference device\nSecond Opinion\nautomatically\nuploads images.\nNevertheless, these\ntechnological\ndifferences do not\nraise new questions\nof safety and\neffectiveness. The\nabsence of these\nfeatures in the\nsubject device does\nnot impede its ability\nto fulfill its intended\nuse."],["Algorithm","Utilizes computer\nvision machine\nlearning\nalgorithm(s).","Utilizes\ncomputer vision\nmachine learning\nalgorithm(s).","Utilizes computer\nvision\nneural network\nalgorithms,\ndeveloped from\nopen-source\nmodels using\nsupervised\nmachine learning\ntechniques.","Utilizes computer\nvision techniques.","Same. Smile Dx®\nutilizes computer\nvision techniques,\nspecifically, machine\nlearning algorithms\nto detect suspected\nfindings, same as the\nidentified predicate\nand reference\ndevices."],["Output","Suspected\nfindings (i.e.,\ncaries, PARLs)\nand\nmeasurements\n(bone levels) are\noverlaid on the\noriginal\nradiograph","Caries detection\nand segmentation\non radiograph\nresulting in\noutline of\nsuspected caries","Detected features\n(e.g., caries,\nPARLs) are\nhighlighted with\ncolor-coded\nboundary boxes\noverlaid on the\noriginal radiograph","Bone-level\nannotations on\nradiograph","The output of Smile\nDx® is similar to the\noutputs of all of the\nidentified predicate\nand reference\ndevices, as they all\noverlay the findings\non the original\nradiograph."],["Marker\nType/Size","Contour\nsegmentations for\ncaries and\nperiapical","Presents\nsuspected carious\nlesions as\nsegmented","Color-coded\nbounding boxes /\nFixed","Color-coded lines\nfor bone levels","The subject device\nhas similar marker\ntypes to its predicate\nand reference"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p14-t0","doc_id":"K242437","page_num":14,"bbox":[72.17,120.8,539.98,719.98],"n_rows":5,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","radiolucencies.\nColor-coded lines\nfor bone levels","polygons\noutlining the\nprediction","","","devices.\nFor suspected caries,\nthe subject device\ncreates a contour of\nthe suspected caries,\nsimilar to the\npredicate (Overjet\nCaries Assist).\nFor periapical\nradiolucencies, the\nsubject device\ncreates countours.\nThis is different to\nreference device’s\n(Second Opinion)\nbounding boxes. The\nperformance and\naccuracy of the\nsegmentations has\nbeen supported with\nappropriate\nperformance testing.\nFor bone levels, the\nsubject device\noutputs color-coded\nlines depending on\nthe level of measured\nboneloss, similar to\nreference device\nOverjet Dental\nAssist."],["Image\nMeasurement","Linear distance","N/A","N/A","Linear distance","Smile Dx® is similar\nto reference device\nOverjet Dental Assist\nin that it creates a\nlinear distance for\nmeasured bone\nlevels."],["Image Viewing","Full, Thumbnail","Full, Thumbnail","Full, Thumbnail","Full, Thumbnail","Same"],["Image\nManipulation","Image adjustment\ntools (e.g.,\nbrightness,\ncontrast, opacity,","Annotations","Image adjustment\ntools (e.g.,\nbrightness,","Annotation (line)","Smile Dx® has\nsimilar image\nadjustment tools as\nreference devie\nSecond Opinion"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p15-t0","doc_id":"K242437","page_num":15,"bbox":[72.12,120.8,539.98,716.48],"n_rows":3,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","rotation prior to\nupload)","","contrast, zoom,\ninvert, rotate)","","(e.g., contrast and\nbrightness). Smile\nDx® introduces a\nnew tool (i.e.,\nopacity adjustment),\nhowever, this does\nnot raise any new\nquestions of safety\nand effectiveness and\nis a common image\nadjustment tool.\nSmile Dx® lacks\nsome of the features\nfound in the\npredicate and\nreference devices\n(e.g., zoom, invert,\nand manual\nannotation tools).\nHowever, these tools\nare not needed to\naccomplish the\nintended use of the\ndevice and do not\nraise new questions\nof safety and\neffectiveness."],["Performance\nTesting","• Standalone\nperformance\nstudy for\npathologic feature\n(i.e., caries and\nperiapical\nradiolucency)\ndetection, non-\npathologic feature\ndetection (i.e.,\nnormal anatomy\nand restorations)\nand bone level\nmeasurement\nperformance.\n• Multiple-\nReader,\nMultiple-Case\n(MRMC) study\nfor pathologic\ndental features","• Standalone\nstudy for\npathologic\nfeature detection\nperformance.\n• Multiple-\nReader,\nMultiple-Case\n(MRMC) study\nfor pathologic\ndental features\n• Analysis\nincluded:\n• Sensitivity and\nspecificity\nevaluations\n• Dice coefficient\nanalysis","• Standalone study\nfor\npathological\nand non-\npathologic\nfeature detection\nperformance.\n• Multiple-Reader,\nMultiple-Case\n(MRMC) study for\npathologic dental\nfeatures\n• Analysis\nincluded:\n• wAFROC-FOM\nanalysis for\nprimary endpoints\n•Determination of\nthe changes in\nsensitivity and\nchange in number","• Bench testing\nevaluated\nprecision and\nrecall against\nlabeled keypoints\nwithin\nradiographs.\n• Retrospective\nclinical\nperformance\ntesting that\ncompared\nadjudicated\nmeasurements\nagainst Overjet\nDental Assist’s\npredicted\nmeasurements.\nAnalysis included","Smile Dx®\nunderwent similar\nevaluations as\npredicate and\nreference devices,\nfollowing\nrecommendations in\n2022 FDA Guidance\n“Computer-Assisted\nDetection Devices\nApplied to Radiology\nImages and\nRadiology Device\nData - Premarket\nNotification [510(k)]\nSubmissions”."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p16-t0","doc_id":"K242437","page_num":16,"bbox":[72.17,120.8,539.98,268.83],"n_rows":2,"n_cols":6,"columns":["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],"rows":[["Characteristic","Smile Dx®","Predicate\nDevice: Overjet\nCaries Assist\n(K212519)","Reference Device:\nSecond Opinion\n(K210365)","Reference\nDevice: Overjet\nDental Assist\n(K210187)","Comparison"],["","• Analysis\nincluded:\n• wAFROC\nanalysis for\nprimary endpoint\n• Sensitivity and\nspecificity\nevaluations","","of false positive\ndental pathologies\nof a given type per\nimage (FPPI)","sensitivity and\nspecificity.",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p17-t0","doc_id":"K242437","page_num":17,"bbox":[72.19,155.3,539.98,235.83],"n_rows":3,"n_cols":4,"columns":["Radiograph\nType","Bone Level Detection -\nSensitivity","Bone Level Detection -\nSpecificity","Bone Loss Measurement (Mean Absolute\nError [95% CI]"],"rows":[["Radiograph\nType","Bone Level Detection -\nSensitivity","Bone Level Detection -\nSpecificity","Bone Loss Measurement (Mean Absolute\nError [95% CI]"],["Bitewing","95.5% [94.3%, 96.7%]","94.0% [91.1%, 96.6%]","0.30 mm [0.29mm, 0.32mm]"],["Periapical","87.3% [85.4%, 89.2%]","92.1% [89.9%, 94.1%]","2.6% [2.4%, 2.8%]"]],"caption_candidate":"a test dataset of 352 cases collected from multiple U.S. sites. The test results were as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p17-t1","doc_id":"K242437","page_num":17,"bbox":[72.19,297.35,522.23,378.12],"n_rows":3,"n_cols":5,"columns":["Non-pathologic Region","Dice","Sensitivity\n(Pixel-level)","Sensitivity\n(Contour-level)","Specificity\n(Contour-level)"],"rows":[["Non-pathologic Region","Dice","Sensitivity\n(Pixel-level)","Sensitivity\n(Contour-level)","Specificity\n(Contour-level)"],["Normal Anatomy","0.84 [0.83, 0.85]","86.1% [85.4%, 86.8%]","95.2% [94.5%, 96%]","93.5% [91.6%, 95.8%]"],["Restorations","0.87 [0.85, 0.90]","83.1% [80.3%, 86.4%]","90.9% [88.2%, 93.9%]","99.6% [99.3%, 99.8%]"]],"caption_candidate":"test dataset of 200 cases collected from different U.S. sites. The test results were as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242437-p18-t0","doc_id":"K242437","page_num":18,"bbox":[72.12,184.8,309.88,255.33],"n_rows":3,"n_cols":5,"columns":["","𝜽\n𝒄𝒐𝒏𝒕𝒓𝒐𝒍","𝜽\n𝑪𝑨𝑫","𝜟𝜽 [95% CI]","p-value"],"rows":[["","𝜽\n𝒄𝒐𝒏𝒕𝒓𝒐𝒍","𝜽\n𝑪𝑨𝑫","𝜟𝜽 [95% CI]","p-value"],["Caries","0.781","0.908","+0.127 [0.081, 0.172]","< 0.001"],["PARLs","0.849","0.947","+0.098 [0.061, 0.135]","< 0.001"]],"caption_candidate":"specificity, thereby meeting the acceptance criteria for effective detection of caries and PARLs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242444-p7-t0","doc_id":"K242444","page_num":7,"bbox":[104.21,298.31,518.62,437.69],"n_rows":7,"n_cols":4,"columns":["Difference","","HERA W9","HERA W10"],"rows":[["Difference","","HERA W9","HERA W10"],["Software","CrystalVue Flow","Not Supported","Supported"],["","MPI+","Not Supported","Supported"],["Hardware","Caster size","5\"","6\""],["","Active array probe port","3 port (default),\n4 port(option)","4 port"],["","Control panel moving","Rotate","Swivel"],["","Main monitor","21.5\"/ 23.8\" / 27\"","21.5\"/ 23\" / 23.8\" / 27\""]],"caption_candidate":"The differences between HERA W9 and HERA W10 in the subject device are as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242444-p7-t1","doc_id":"K242444","page_num":7,"bbox":[119.8,539.71,518.62,757.66],"n_rows":6,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012,\nC1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text)\nMedical electrical equipment - Part 1: General requirements for\nbasic safety and essential performance (IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical\nequipment - Part 1-2: General requirements for basic safety and\nessential performance - EMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment –\nPart 2-37: Particular requirements for the basic safety and essential\nperformance of ultrasonic medical diagnostic and monitoring\nequipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical\nequipment - Part 4-2: Guidance and interpretation -\nElectromagnetic immunity: performance of medical electrical\nequipment and medical electrical systems","",""],["ISO10993-1","","","AAMI / ANSI / ISO 10993-1:2018/(R)2013, Biological evaluation","",""]],"caption_candidate":"standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242444-p8-t0","doc_id":"K242444","page_num":8,"bbox":[119.78,85.32,518.64,162.74],"n_rows":3,"n_cols":2,"columns":["","of medical devices – Part 1: Evaluation and testing within a risk\nmanagement process"],"rows":[["","of medical devices – Part 1: Evaluation and testing within a risk\nmanagement process"],["ISO14971","ISO 14971:2019, Medical devices - Application of risk\nmanagement to medical devices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement\nStandard for Diagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"HERA W9/ HERA W10 Diagnostic Ultrasound Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242444-p12-t0","doc_id":"K242444","page_num":12,"bbox":[84.74,286.61,525.12,362.57],"n_rows":6,"n_cols":2,"columns":["[ The validation for SonoSync ]",""],"rows":[["[ The validation for SonoSync ]",""],["",""],["","Pre-determined criteria were utilized in validation tests to assess whether remote viewing and"],["","reviewing with SonoSync matched the performance of local ultrasound systems."],["","Labeling materials is provided to inform users about the necessary specifications for safely and"],["","effectively conducting remote diagnostic reviews and viewing."]],"caption_candidate":"the ones during training process and there is no overlap between the three.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242461-p7-t0","doc_id":"K242461","page_num":7,"bbox":[85.07,368.44,528.68,645.72],"n_rows":3,"n_cols":3,"columns":["Predicate Device (K182643) -\nSegmentation Software Application as\npart of IRIS 1.0 System","","Subject Device\nIRISeg"],"rows":[["Predicate Device (K182643) -\nSegmentation Software Application as\npart of IRIS 1.0 System","","Subject Device\nIRISeg"],["Intended use for providing tools for image analysis\nand segmentation of kidney CT images.\nThe IRIS 1.0 System is intended as a medical\nimaging system that allows the processing, review,\nanalysis, communication, and media interchange\nof multi-dimensional digital images acquired from\nCT imaging devices. It is also intended as software\nfor preoperative surgical planning, and as\nsoftware for the intraoperative display of the\naforementioned multi-dimensional digital images.\nThe IRIS 1.0 System Is designed for use by health\ncare professionals and is intended to assist the\nclinician who is responsible for making all final\npatient management decisions.","","SAME intended use."],["","","DIFFERENCE in Indications for use:\nThe machine learning enabled kidney CT\nauto-segmentation tool is intended for use\nfor adult patients with contrast-enhanced,\naxial kidney CT images with slice thickness\n3mm or less.\nIRISeg is intended for use by qualified\nprofessionals."]],"caption_candidate":"Comparison of Indications for Use and intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242461-p8-t0","doc_id":"K242461","page_num":8,"bbox":[85.78,87.4,526.31,717.96],"n_rows":16,"n_cols":7,"columns":["Description","","Predicate Device (K182643) -","","","Subject Device",""],"rows":[["Description","","Predicate Device (K182643) -","","","Subject Device",""],["","","IRISeg as part of IRIS 1.0 System","","","IRISeg",""],["Regulation Number","21 CFR §892.2050","","","21 CFR §892.2050","",""],["Classification","Class II","","","Class II","",""],["Product Code","Primary: LLZ","","","Primary: QIH; Associate: LLZ","",""],["Prescription use","Rx only","","","Rx only","",""],["Host Hardware\nCompatibility","General-purpose computer\nhardware","","","General-purpose computer\nhardware","",""],["Intended population","Adult patients","","","Adult patients","",""],["Intended Users","Healthcare Professionals","","","Qualified Professionals","",""],["Intended Clinical\nDecision Support","The output file can be used to\nrender a 3D model for\npreoperative surgical planning\nand intraoperative display.\nThe output file is meant for\nvisual, non-diagnostic use and\nshall be reviewed by clinicians\nwho are responsible for all final\npatient management decisions.","","","Equivalent to the predicate\ndevice","",""],["Principles of Operations\n/ Workflow","Manual segmentation alone\nAuto-segmentation followed by\nmanual segmentation.","","","Equivalent to the predicate\ndevice","",""],["User interface /\nEnvironment","Graphical user interface design.\nOffice setting (Segmentation\nSoftware Application running on\na general-purpose computer)","","","Equivalent to the predicate\ndevice","",""],["Supported Input","DICOM-Compliant CT scans\nAxial views, contrast enhanced","","","Equivalent to the predicate\ndevice","",""],["Supported Output","Segmentation files that can be\nused to render a 3D model for\npreoperative surgical planning\nand intraoperative display","","","Equivalent to the predicate\ndevice","",""],["Supported Segmentation\nStructures","5 Kidney CT structures:\nParenchyma, Artery, Vein,\nCollecting System and Mass","","","Equivalent to the predicate\ndevice","",""],["ML Auto-Segmentation\nStructures","5 Kidney CT structures:\nParenchyma, Artery, Vein,\nCollecting System and Mass","","","4 Kidney CT structures:\nParenchyma, Artery, Vein and\nCollecting System","",""]],"caption_candidate":"Comparison of Device Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242461-p9-t0","doc_id":"K242461","page_num":9,"bbox":[86.16,65.92,526.3,226.56],"n_rows":5,"n_cols":7,"columns":["Description","","Predicate Device (K182643) -","","","Subject Device",""],"rows":[["Description","","Predicate Device (K182643) -","","","Subject Device",""],["","","IRISeg as part of IRIS 1.0 System","","","IRISeg",""],["Manual Tools","Various segmentation and\nselection tools for manual\nsegmentation.","","","Equivalent to the predicate\ndevice","",""],["2D and 3D Visualization\nFeatures","Volume rendering, 3D model\nvisualization, 2D slice\nvisualization.","","","Equivalent to the predicate\ndevice","",""],["Segmentation Support\nFeatures","Metadata viewing","","","Equivalent to the predicate\ndevice","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242461-p10-t0","doc_id":"K242461","page_num":10,"bbox":[72.42,289.92,514.99,339.56],"n_rows":4,"n_cols":9,"columns":["Test Case","","","Artery DSC","Parenchyma DSC","Vein DSC","","Collecting System",""],"rows":[["Test Case","","","Artery DSC","Parenchyma DSC","Vein DSC","","Collecting System",""],["","","","","","","","MDA",""],["","Overall Testing","","[0.87, 0.90]","[0.95, 0.97]","[0.87, 0.89]","[1.3, 1.9]","",""],["","(N=81)","","","","","","",""]],"caption_candidate":"test dataset are summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242467-p7-t0","doc_id":"K242467","page_num":7,"bbox":[67.62,604.45,539.64,719.13],"n_rows":4,"n_cols":4,"columns":["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],"rows":[["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],["FDA Clearance","DEN220040","TBD","--"],["Clearance Date","01/12/2024","TBD","--"],["Product Code","QWO","QWO","Same"]],"caption_candidate":"the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242467-p8-t0","doc_id":"K242467","page_num":8,"bbox":[67.62,90.28,539.64,715.13],"n_rows":6,"n_cols":4,"columns":["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],"rows":[["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],["Class","II","II","Same"],["Regulation","892.2085","892.2085","Same"],["Software","Device is software only","Device is software only","Same"],["Software\nDocumentation\nLevel","Moderate","Basic","Documentation is similar\nand differences are due to\nupdated FDA guidance."],["Indications for\nUse","Fibresolve is a software‐only device\nthat receives and analyzes lung\ncomputed tomography (CT) imaging\ndata in order to provide a diagnostic\nsubtype classification in suspected\ncases of interstitial lung disease\n(ILD). The device supplements the\nstandard-of‐care workflow by\nproviding a qualitative, diagnostic\nclassification output of imaging\nfindings based on machine learning\npattern recognition, in order to\nprovide adjunctive information as\npart of a referral pathway to an\nappropriate Multidisciplinary\nDiscussion (MDD) or as part of an\nMDD. Specifically, the tool is used\nto serve as an adjunct in the\ndiagnosis of idiopathic pulmonary\nfibrosis (IPF) prior to invasive\ntesting. The results of Fibresolve are\nintended to be used only by\nclinicians qualified in the care of\nlung disease, specifically in caring\nfor patients with ILD, in conjunction\nwith the patient’s clinical history,\nsymptoms, and other diagnostic\ntests, as well as the clinician’s\nprofessional judgment.\nThe input to Fibresolve is a DICOM‐\ncompliant lung CT scan. Clinical\ncase eligibility includes the\nfollowing criteria:\nAge > 22 years old.\nPulmonary symptoms suggestive of\npossible ILD including IPF.","Imbio IQ-UIP is a computer-aided\nsoftware indicated for use in\npassively notifying specialists\nassociated with interstitial lung\ndisease (ILD) centers of\nradiological findings suggestive of\nradiological usual interstitial\npneumonia (UIP) in non-contrast,\nchest CT scans of adults. Imbio IQ-\nUIP uses an artificial intelligence\nalgorithm to analyze images and\nidentify positive findings on a\nworklist application separate from\nand in parallel to the standard of\ncare radiological image\ninterpretation. Identification of\npositive findings include summary\nreports with a clinical guideline\nreference for the definition of UIP\npattern that are meant for\ninformational purposes only. The\ndevice does not alter the original\nmedical image and is not intended\nto be used as a diagnostic device.\nThe results of Imbio IQ-UIP are\nused to notify specialists at an ILD\ncenter of radiological findings that\nmay be consistent with UIP. These\nspecialists are qualified clinicians\nexperienced in evaluating chest\nCTs for ILD. Input images originate\nfrom within the same hospital\nnetwork associated with the ILD\ncenter. The results of Imbio IQ-UIP\nare intended to be used in\nconjunction with additional patient\ninformation and based on the\nuser's professional judgment, to\nassist with the review of medical","Similarities\n• Referral software for\nfindings suggestive of\na pre-specified\nclinical fibrotic lung\ncondition\n• Uses artificial\nintelligence to\nanalyze chest/lung CT\nimages\n• Used by clinicians\nqualified in the care\nof lung disease\n• Operates in parallel to\nstandard of care\nworkflow\n• Provide qualitative\ndiagnostic subtype\nclassification for\ncases suspected of\ninterstitial lung\ndisease\n• Limited to analysis of\nimaging data and\nshould not be used\nin-lieu of full patient\nevaluation or relied\nupon to make or\nconfirm diagnosis"]],"caption_candidate":"510(k) Summary – IQ UIP","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242467-p9-t0","doc_id":"K242467","page_num":9,"bbox":[67.62,90.28,539.63,690.14],"n_rows":8,"n_cols":4,"columns":["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],"rows":[["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],["","","images. Notified clinicians are\nresponsible for viewing full image\nseries and making final clinical\ndeterminations.","Differences:\n• IQ-UIP reports\nviewable on\ndedicated worklist\napplication separate\nfrom standard-of-\ncare."],["Technical\nMethod","The device supports referral of\nfindings related to fibrotic lung\ndiseases using machine learning,\nartificial intelligence or other\nimage analysis algorithms.","The device supports referral of\nfindings related to fibrotic lung\ndiseases using machine\nlearning, artificial intelligence or\nother image analysis algorithms.","Same"],["Target Area","The device operates on\nradiological images of the\nhuman body.","The device operates on\nradiological images of the\nhuman body.","Same"],["Anatomical Site","Lung/Chest","Lung/Chest","Same"],["Intended User\nPopulation","Clinicians qualified in care of lung\ndisease","Clinicians qualified in care of lung\ndisease","Same"],["Patient\nPopulation","Adults > 22 years old and with\npulmonary symptoms suggestive of\npossible ILD including IPF.","Adults > 22 years old","Similarities:\n• Adults > 22 years old\nDifferences:\n• Fibresolve’s patient\npopulation is limited\nto those adults with\npulmonary symptoms\nsuggestive of possible\nILD including IPF.\n• IQ-UIP patient\npopulation would\ninclude the same\npatient population as\nthose indicated for\nFibresolve but may\nalso include others\nwho have undergone a\nchest CT for other\nsymptoms."],["Communication\nwith Patient","Does not communicate images\nto patients.","Does not communicate images\nto patients.","Same"]],"caption_candidate":"510(k) Summary – IQ UIP","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242467-p10-t0","doc_id":"K242467","page_num":10,"bbox":[67.62,90.28,539.64,223.99],"n_rows":3,"n_cols":4,"columns":["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],"rows":[["Characteristic","Predicate: Fibresolve\n(DEN220040)","Proposed: IQ-UIP","Similarities or\nDifferences"],["Alteration of\noriginal image","No","No","Same"],["Viewing","Unknown","Referral report viewable on\ndedicated worklist application\naccessible by the intended users.","IQ-UIP reports viewable on\ndedicated worklist\napplication separate from\nstandard-of-care."]],"caption_candidate":"510(k) Summary – IQ UIP","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242467-p11-t0","doc_id":"K242467","page_num":11,"bbox":[72.46,120.47,543.07,628.32],"n_rows":25,"n_cols":3,"columns":["Data Bin","Datasets","Percentage of Total (%)"],"rows":[["Data Bin","Datasets","Percentage of Total (%)"],["","",""],["Gender","",""],["","",""],["Male","437","54.4%"],["Female","300","37.3%"],["N/A","67","8.3%"],["Age (years)","",""],["","",""],["<50","89","11.1%"],["≥50 AND <60","150","18.7%"],["≥60 AND <70","257","32.0%"],["≥70 AND <80","215","26.7%"],["≥80","46","5.7%"],["N/A","47","5.8%"],["Race/Ethnicity","",""],["","",""],["White","302","37.6%"],["African-American","27","3.4%"],["Asian","21","2.6%"],["Hispanic","2","0.2%"],["American Indian or Alaska Native","2","0.2%"],["Native Hawaiian or Other Pacific Islander","1","0.1%"],["Other","1","0.1%"],["N/A","448","55.7%"]],"caption_candidate":"Demographic data are presented in the following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p5-t0","doc_id":"K242488","page_num":5,"bbox":[72.0,107.13,396.39,664.99],"n_rows":57,"n_cols":3,"columns":["Company Name:","Omega Medical Imaging, LLC",""],"rows":[["Company Name:","Omega Medical Imaging, LLC",""],["","",""],["Address:","3400 St. Johns Parkway, Suite","1020,"],["","",""],["Telephone No:","407-323-9400",""],["","",""],["Registration No:","1052701",""],["","",""],["Contact person:","Matthew Anderson, Director RA","/QA"],["","",""],["Date Prepared:","06/04/2024",""],["","",""],["Device (trade) name:","Soteria E-View",""],["","",""],["Common/usual name:","Fluoroscopic/Radiographic X-ra","y sys"],["","",""],["Classification Name:","Image-intensified Fluoroscopic","X-ray"],["","",""],["Classification Panel:","Radiology",""],["","",""],["CFR section:","892.1650",""],["","",""],["Device Class:","Class II",""],["","",""],["Primary Product code:","JAA",""],["","",""],["Secondary product code:","OWB",""],["","",""],["","Predicate Device K21","233"],["","",""],["Company Name:","Omega Medical Imaging, LLC",""],["","",""],["Address:","3400 St. Johns Parkway, Suite","1020,"],["","",""],["Telephone No:","407-323-9400",""],["","",""],["Registration No:","1052701",""],["","",""],["Contact person:","John Newman",""],["","",""],["Date Prepared:","08/19/2021",""],["","",""],["Device (trade) name:","Soteria.AI",""],["","",""],["Common/usual name:","Fluoroscopic/Radiographic X-ra","y sys"],["","",""],["Classification Name:","Image-intensified Fluoroscopic","X-ray"],["","",""],["Classification Panel:","Radiology",""],["","",""],["CFR section:","892.1650",""],["","",""],["Device Class:","Class II",""],["","",""],["Primary Product code:","JAA",""],["","",""],["Secondary Product code:","OWB",""]],"caption_candidate":"Company Name: Omega Medical Imaging, LLC","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242488-p9-t0","doc_id":"K242488","page_num":9,"bbox":[54.08,79.62,544.48,325.18],"n_rows":23,"n_cols":9,"columns":["","Indications for use comparison:","","","","","","",""],"rows":[["","Indications for use comparison:","","","","","","",""],["","510(k)","","K212336 (Predicate Device)\nSoteria.AI, Model AI-100","","","K242488 (This Submission)\nSoteria E-View, Model GI-100","K242488 (This Submission)",""],["","Number and","","","","","","Soteria E-View, Model GI-100",""],["","Device Name","","","","","","",""],["Intended Use","Intended Use","","The Omega Medical Imaging, LLC AI-100,\nSoteria.AI (SSXI) systems with FluoroShield / CA-\n100S device to provide an automated Region of\ninterest that reduces exposure to the patient and\noperator. The System is intended for use in\nRadiographic/fluoroscopic applications, including\ncardiac, vascular, general\nradiographic/fluoroscopic diagnostic, and\ninterventional x-ray imaging for General and\nPediatric Populations.","","","","The Omega Medical Imaging, LLC GI-100,",""],["","","","","","","","Soteria E-View (SSXI) systems with",""],["","","","","","","","FluoroShield / CA-100S device to provide an",""],["","","","","","","","automated Region of interest that reduces",""],["","","","","","","","exposure to the patient and operator. The",""],["","","","","","","","System is intended for use in",""],["","","","","","","","Radiographic/fluoroscopic applications, including",""],["","","","","","","","gastrointestinal, ERCP, general",""],["","","","","","","","radiographic/fluoroscopic diagnostic, and",""],["","","","","","","","interventional x-ray imaging for General and",""],["","","","","","","","Pediatric Populations.",""],["","","","","","","","",""],["","Classification","","Image-intensified Fluoroscopic X-ray system","","","Image-intensified Fluoroscopic X-ray system","Image-intensified Fluoroscopic X-ray system",""],["","Name:","","","","","","",""],["","CFR","","892.1650","","","892.1650","",""],["","Regulation #:","","","","","","",""],["","Device Class","","","Class II","","","Class II",""],["","Classification","","JAA, OWB","JAA, OWB","","JAA, OWB","JAA, OWB",""],["","Product Code:","","","","","","",""]],"caption_candidate":"Comparison with Predicate Devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p9-t1","doc_id":"K242488","page_num":9,"bbox":[113.68,393.05,539.54,726.18],"n_rows":16,"n_cols":7,"columns":["","1. Flat Panel Detectors","","","","",""],"rows":[["","1. Flat Panel Detectors","","","","",""],["","","","510(k) Cleared (Predicate","","This Submission Soteria E-View",""],["","","","Device) K212336","","",""],["","","","","","",""],["Detector Name:","","Teledyne Dalsa Xineos-3030HS","","","Varex Azure 3131Z CXP Detector",""],["1.1 Receptor Type","","CMOS","","","IGZO (indium gallium zinc oxide)",""],["1.2 Conversion Screen","","Cesium Iodide","","","Cesium Iodide",""],["1.3 Pixel Area – Active","","29.6 cm x 29.6 cm","","","30.7 cm x 30.7 cm",""],["1.4 Pixel Matrix – Active","","1952 x 1952","","","2048 x 2048",""],["1.5 Pixel Pitch","","151.8 µm","","","150 μm",""],["1.6 Limiting Resolution","","3.15 lp/mm","","","3.3 lp/mm",""],["1.7 MTF, X-ray","","58% @ (1.0 lp/mm at RQA5 1x1)","","","60% @ (1.0 lp/mm)",""],["1.8 Energy Range","","40 - 125 kV","","","40-125 kV",""],["1.9 Fill Factor","","83%","","","66%",""],["1.10 Dynamic Range","","77dB","","","65 dB",""],["1.9 A/D Conversion","","16-bits","","","16-bits",""]],"caption_candidate":"Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p11-t0","doc_id":"K242488","page_num":11,"bbox":[113.67,57.84,539.8,699.96],"n_rows":28,"n_cols":5,"columns":["3.13 DICOM Storage","","Yes","Yes",""],"rows":[["3.13 DICOM Storage","","Yes","Yes",""],["3.14 DICOM Storage to\nDVD/CD","","With Embedded Viewer","With Embedded Viewer",""],["","4. Reference Monitor Identifiers [Review Station]","","",""],["4.1 Patient Name","","Yes","Yes",""],["4.2 Patient I.D.","","Yes","Yes",""],["4.3 Date","","No","No",""],["4.4 Time","","No","No",""],["4.5 Window/Level","","No","No",""],["4.6 Hospital Name","","No","No",""],["4.7 Physician Name","","Yes","Yes",""],["4.8 Study I.D.","","Yes","Yes",""],["4.9 Series/Image","","Yes","Yes",""],["4.10 Acquisition Mode","","Yes","Yes",""],["4.11 Image Orientation","","Yes","Yes",""],["4.12 Radiation","","No","No",""],["I4.13 Image I.D.","","Yes","Yes",""],["","5. Live Monitor Identifiers [Image Area]","","",""],["5.1 Patient Name","","Yes","Yes",""],["5.2 Patient I.D.","","Yes","Yes",""],["5.3 Date","","Yes","Yes",""],["5.4 Time","","Yes","Yes",""],["5.5 Window/Level","","No","No",""],["5.6 Hospital Name","","Yes","Yes",""],["5.7 Physician Name","","No","No",""],["5.8 Study I.D.","","Yes","Yes",""],["5.9 Series/Image","","Only Image Number","Only Image Number",""],["5.10 Image Orientation","","Yes","Yes",""],["5.11 Radiation Symbol","","Radiation symbol during Live","Radiation symbol during Live",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p12-t0","doc_id":"K242488","page_num":12,"bbox":[113.68,57.84,539.79,700.56],"n_rows":22,"n_cols":5,"columns":["5.12 Image I.D.","","e.g., FL LIH, FL Loops, Spot\nReplay, or Cine Replay","e.g., FL LIH, FL Loops, Spot\nReplay, or Cine Replay",""],"rows":[["5.12 Image I.D.","","e.g., FL LIH, FL Loops, Spot\nReplay, or Cine Replay","e.g., FL LIH, FL Loops, Spot\nReplay, or Cine Replay",""],["5.13 Detector Status","","Ready/Not Ready","Ready/Not Ready",""],["5.14 Magnification Mode","","Normal, MAG 1, MAG 2","Normal, MAG 1, MAG 2",""],["5.15 Loop Replay","","Play, Forward, Reverse, Play,\n& Pause","Play, Forward, Reverse, Play, &\nPause",""],["","GUI [Graphic User Interface on Reference Monitor]","","",""],["","Patient/Exam Entry","","",""],["5.16 Directory","","Opens ‘Patient Directory’\nscreen","Opens ‘Patient Directory’\nscreen",""],["5.17 New","","Opens ‘Patient Data Entry’\nscreen","Opens ‘Patient Data Entry’\nscreen",""],["5.18 Close","","Closes active patient","Closes active patient",""],["","Acquisition","","",""],["5.19 NR Hi / NR Lo","","Selects Noise Reduction Level","Selects Noise Reduction Level",""],["5.20 L -> R","","Live to Reference (monitor)\ntransfer","Live to Reference (monitor)\ntransfer",""],["5.21 Fluoro Pulse Rates:","","Pulse Rates: [14 f/s default,\n7.5, & 3.75 f/s]","Pulse Rates: [12.5 f/s default,\n6, & 3 f/s]",""],["Note: Image Orientation available for Acquisition Mode [from Review]","","","",""],["","Review","","",""],["5.22 Edge\n[enhancement]","","Increments from 1 - 5","Increments from 1 - 5",""],["5.23 Win./Lev.","","Window/Level adjustment","Window/Level adjustment",""],["5.24 Split","","Invokes 4 on 1 image display,\nNo","Invokes 4 on 1 image display,\nNo",""],["5.25 Reference – Live","","Toggles image between the\nReference and Live monitors","Toggles image between the\nReference and Live monitors",""],["5.26 Zoom","","Up to 2X zoom with panning","Up to 2X zoom with panning",""],["5.27 Polarity","","Video white on black or black\non white","Video white on black or black\non white",""],["5.28 Collimate","","Invokes electronic shutters","Invokes electronic shutters",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p13-t0","doc_id":"K242488","page_num":13,"bbox":[113.68,57.84,539.79,703.68],"n_rows":22,"n_cols":7,"columns":["5.29 R [image\norientation]","","Toggles thru 1 of 4 positions","","","Toggles thru 1 of 4 positions",""],"rows":[["5.29 R [image\norientation]","","Toggles thru 1 of 4 positions","","","Toggles thru 1 of 4 positions",""],["","Additional Functions","","","","",""],["5.30 Send","","Opens ‘DICOM server node\nselection’","","","Opens ‘DICOM server node\nselection’",""],["5.31 Print","","Sends image to a Windows®\ncompatible printer (No)","","","Sends image to a Windows®\ncompatible printer (No)",""],["5.32 Save","","Saves current image to Hard\nDrive","","","Saves current image to Hard\nDrive",""],["5.33Text","","Invokes the Annotation and\nMeasurement function","","","Invokes the Annotation and\nMeasurement function",""],["","C-Arm & Operator Controls","","","","",""],["C-ARM Specifications:","","","510(k) Cleared (Predicate","","This Submission Soteria E-View.AI",""],["","","","Device) K212336","","",""],["C-Angulation","","Head ± 110° ± 2°,\nSide ± 45° ± 2°,","","","± 90°, ± 2°",""],["C-Roll","","Head ± 45° ± 2°,\nSide ± 90° ± 2°,","","","+ 90°, ± 2°, -75°, ± 2°",""],["Iso-Rotation","","± 90°, ± 2°","","","No",""],["Collimator - Longitude","","Opens to full field, closes fully","","","Opens to full field, closes fully",""],["Collimator –\nLatitude","","Opens to full field, closes fully","","","Opens to full field, closes fully",""],["Cardio Filter –\nOpen Close","","Opens to full field, closes fully\n(vascular), closes to mid field\n(lung)","","","No Filter",""],["Cardio Filter –\nRotate","","Rotates cardio filter(s) 360°","","","No Filter",""],["Variable SID","","13”, ± 1”","","","13”, ± 1”",""],["","Operator Controls","","","","",""],["Fluoro Enable","","Enables/disables Fluoro function","","","Enables/disables Fluoro function",""],["Fluoro Timer Reset","","Resets 5-minute alarm on high\nvoltage generator","","","Resets 5-minute alarm on high\nvoltage generator",""],["Emergency Stop","","Disables motion actuators and\nhigh voltage generator","","","Disables motion actuators and\nhigh voltage generator",""],["Magnification mode","","Selects field sizes: Normal, Mag\n1, and Mag 2","","","Selects field sizes: Normal, Mag 1,\nand Mag 2",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p14-t0","doc_id":"K242488","page_num":14,"bbox":[113.68,57.84,539.79,711.06],"n_rows":26,"n_cols":5,"columns":["Controls select","","Requests active control is 2\ncontrollers are installed","Requests active control is 2\ncontrollers are installed",""],"rows":[["Controls select","","Requests active control is 2\ncontrollers are installed","Requests active control is 2\ncontrollers are installed",""],["5th Axis Rotate","","± 90°, ± 2°","No",""],["Cardio filter select","","Lung or vascular","No",""],["DAP meter reset","","Resets DAP meter outputs to 0","Resets DAP meter outputs to 0",""],["Pediatric Filter Select","","Selects none, 0.1, 0.2, or 0.3 mm\nCu filters","No",""],["Parking Control","","Controls parking actuator","No",""],["Fluoro","","Enables X-ray fluoro","Enables X-ray fluoro",""],["Fluoro loops","","Enables X-ray fluoro loops","Enables X-ray fluoro loops",""],["Cine","","Enables X-ray cine mode","No",""],["","Miscellaneous Functions:","","",""],["System Digital Display","","Miscellaneous System Status","Miscellaneous System Status",""],["Collision Sensing on FPD","","Bump stop.","Bump stop.",""],["","Collimator Functions:","","",""],["Collimator: Maximum Size\nand Tracking","","Yes","Yes",""],["Collimator: Minimum Size","","Yes","Yes",""],["","X-Ray Specifications","","",""],["Half Value Layer","","Minimum value = 3.6 mm Al\nequiv. @ 100 kV\nMaximum value = 4.0 mm Al\nEquiv. @ 100 kV","Minimum value = 3.6 mm Al\nequiv. @ 100 kV\nMaximum value = 4.0 mm Al\nEquiv. @ 100 kV",""],["Tabletop Aluminum\nEquivalence","","Rejection Limit: 2.00 mm Al max.","Rejection Limit: 1.6 mm Al max.",""],["Dose Calibration: Maximum\nInput Dose Rate","","80 to 85 mGy/minute","80 to 85 mGy/minute",""],["Dose Calibration: Max Input\nDose Rate","","2.3 to 2.9 µR/frame","2.3 to 2.9 µR/frame",""],["Dose Calibration: Flat Panel\nInput Dose rate","","0.8 µGy/sec.","0.8 µGy/sec.",""],["Generator Function: Pulsed\nFluoro Function","","Yes","Yes",""],["Generator Function: ABC\nFunction","","Yes","Yes",""],["Image Quality: Resolution","","Up to 3.15 lp/mm","Up to 3.15 lp/mm",""],["Last Image Hold","","Yes","Yes",""],["","Patient Table Specifications:","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242488-p15-t0","doc_id":"K242488","page_num":15,"bbox":[113.68,57.84,539.79,713.16],"n_rows":24,"n_cols":8,"columns":["Table Specifications:","","","510(k) Cleared (Predicate\nDevice) K212336","","","This Submission Soteria E-View",""],"rows":[["Table Specifications:","","","510(k) Cleared (Predicate\nDevice) K212336","","","This Submission Soteria E-View",""],["Table Lock Manual Disable\nControls","","","Unlocks table rotate, latitude\nand longitude.","","","No",""],["Table Trendelenburg","","","± 15°, ± 1°","","","± 12°, ± 1°",""],["Table height","","","33” to 45”","","","Same",""],["Table cradle (LAO/RAO)","","","± 15°, ± 1°","","","± 12°, ± 1°",""],["Table Rotation","","","0° to 90°","","","No",""],["","X-RAY TUBE Specifications:","","","","","",""],["X-RAY Tube\nSpecifications:","","","510(k) Cleared (Predicate\nDevice) K212336","","","This Submission Soteria E-View",""],["Tube Model:","","","G-2090","","","G-1092",""],["Heat Exchanger","","","HE-280","","","HE-100",""],["Focal Spot sizes","","","0.6 - 1.0 mm","","","0.6 – 1.2mm",""],["Heat Unit rating","","","2.0 MHU","","","1.0 MHU",""],["Housing Model:","","","B-240H","","","B-160",""],["","High Voltage Generator","","","","","",""],["","H.V. Generator","","","510(k) Cleared (Predicate","","This Submission Soteria E-View",""],["","Specifications:","","","Device) K212336","","",""],["Model:","","","EMD Technologies EPS High\nVoltage Generator series","","","EMD Technologies EPS High\nVoltage Generator series",""],["Mains Input Power:","","","480 Vac +/- 10% 50/60 Hz (3\nphases)","","","480 Vac +/- 10% 50/60 Hz (3\nphases)",""],["kV range:","","","40 kV - 125 kV","","","40 kV - 125 kV",""],["mA range:","","","Min: 5mA to Max: 1000mA","","","Min: 5mA to Max: 1000mA",""],["","CA-100S / FluoroShield","","","","","",""],["ROI: ‘ON’ ,’OFF’,\n‘ERROR’, or\n‘BYPASS’","","","Yes","","","Yes",""],["‘AUTO’ or\n‘MANUAL’ ROI","","","Yes","","","Yes",""],["‘HIGH’ or ‘LOW’\nreduction","","","Yes","","","Yes",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242500-p5-t0","doc_id":"K242500","page_num":5,"bbox":[105.05,151.48,309.19,620.72],"n_rows":39,"n_cols":2,"columns":["mary of 510(k) is being","submitted in accordance"],"rows":[["mary of 510(k) is being","submitted in accordance"],["",""],["er",""],["",""],["Name:","LARALAB GmbH"],["",""],["Address:","Herzog-Heinrich-Str.13, 8"],["",""],["Contact Person:","Julian Bernard"],["",""],["Phone Number:","+49 152 28821761"],["",""],["Email Address:","julian.bernard@laralab.de"],["",""],["ion Date","March 19, 2025"],["",""],["nformation",""],["",""],["Trade Name:","LARALAB"],["",""],["Common Name:","LARALAB"],["",""],["Classification:","Medical image managem"],["",""],["Regulation Number:","21 CFR § 892.2050"],["",""],["Product Code:","QIH"],["",""],["Device Class:","Class II"],["",""],["510(k) Number:","K242500"],["",""],["e Device",""],["",""],["Device Name:","3mensio Workstation"],["",""],["510(k) Number:","K153736"],["",""],["Manufacturer:","Pie Medical Imaging B.V."]],"caption_candidate":"This summary of 510(k) is being submitted in accordance with the requirements of 21 CFR 807.92.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242500-p6-t0","doc_id":"K242500","page_num":6,"bbox":[65.17,641.95,520.38,736.09],"n_rows":3,"n_cols":4,"columns":["","Subject Device","Predicate Device","Comparison"],"rows":[["","Subject Device","Predicate Device","Comparison"],["Device","LARALAB","3mensio Workstation","/"],["Product Code","QIH","LLZ","Similar, the subject\ndevice implements\nartificial intelligence\nincluding nonadaptive"]],"caption_candidate":"assessing coronary arteries.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242500-p7-t0","doc_id":"K242500","page_num":7,"bbox":[65.17,105.8,520.38,736.09],"n_rows":5,"n_cols":4,"columns":["","","","machine learning\nalgorithms."],"rows":[["","","","machine learning\nalgorithms."],["Classification","Medical image management and\nprocessing system","Medical image management and\nprocessing system","Same."],["Regulation Number","21 CFR § 892.2050","21 CFR § 892.2050","Same."],["Intended Use","LARALAB is a software application that\nis intended to provide cardiologists,\nradiologists, heart surgeons and\nhealthcare professionals additional\ninformation to aid them in reading and\ninterpreting DICOM compliant medical\nimages of structures of the heart and\nvessels.\nLARALAB enables the user to make:\n- Visualizations, assessments\nand measurements (e.g.,\ndiameters, lengths, areas,\nvolumes, angles) of\nstructures of the heart and\nvessels, including such\nvascular structures relevant\nas access routes in the\ncontext of cardiovascular\nprocedures.","3mensio Workstation is a software\nsolution that is intended to provide\ncardiologists, radiologists and clinical\nspecialists additional information to\naid them in reading and interpreting\nDICOM compliant medical images of\nstructures of the heart and vessels.\n3mensio Structural Heart enables the\nuser to:\n- Visualize and measure\n(diameters, lengths, areas,\nvolumes, angles) structures\nof the heart and vessels\n- Quantify calcium (volume,\ndensity)\n3mensio Vascular enables the\nuser to:\n- Visualize and assess\nstenosis, aneurysms and\nvascular structures\n- Measure the dimensions\nof vessels (diameters,\nlengths, areas, volumes,\nangles)","While minor textual\ndifferences exist, the\nintended uses of the two\ndevices are otherwise the\nsame."],["Indications for Use","The LARALAB software enables\nvisualization, assessment and\nmeasurement of cardiovascular\nstructures for:\n- Preprocedural planning and\nsizing for cardiovascular\ninterventions and surgery\n- Postprocedural image\nreview\nTo facilitate the above, LARALAB\nprovides general functionality such as:\n- Automatic segmentation of\ncardiovascular structures\nand other objects of interest\n(calcifications)\n- Automatic measurements\n- Manual measurement and\nadjustment tools\n- Visualization and image","3mensio Workstation enables\nvisualization and measurement of\nstructures of the heart and vessels\nfor:\n- Pre-operational planning\nand sizing for\ncardiovascular\ninterventions and surgery\n- Postoperative evaluation\n- Support of clinical\ndiagnosis by quantifying\ndimensions in coronary\narteries\n- Support of clinical\ndiagnosis by quantifying\ncalcified plaques (calcium\nscoring) in the coronary\narteries\nTo facilitate the above, the 3mensio\nWorkstation provides general\nfunctionality such as:\n- Segmentation of\ncardiovascular structures\n- Automatic and manual\ncenterline detection\n- Visualization and image\nreconstruction\ntechniques: 2D review,\nVolume Rendering, MPR,","Substantially the same.\nBoth devices are indicated\nfor use in preprocedural\nplanning and\npostprocedural\nassessment of structural\nheart interventions.\nThe predicate device also\nsupports clinical diagnosis\nby quantifying\ncalcifications and\nquantifying dimensions in\ncoronary arteries. In order\nto provide these functions,\nthe predicate device\nsupports a wider range of\nviewing functionality (e.g.,\nvolume rendering and\nother general visualization\nand image reconstruction\ntechniques) than the\nsubject device.\nThe additional quantifying\nfunction for the evaluation\nof calcifications and\ncoronary artery\ndimensions and additional\ngeneral visualization and\nimage reconstruction\ntechniques are not"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242500-p8-t0","doc_id":"K242500","page_num":8,"bbox":[65.17,105.8,520.38,736.09],"n_rows":5,"n_cols":4,"columns":["","reconstruction techniques:\nMultiplanar Reconstruction\n(MPR), Surface rendering, 4D\nviews\n- Reporting tools","Curved MPR, Stretched\nCMRP, Slabbing, MWP,\nALP, MiniP\n- Measurement and\nannotation tools\n- Reporting tools","necessary for the subject\ndevice to perform as\nintended and not including\nthose functions does not\nimpact the performance of\nthe subject device or the\nability to use the subject\ndevice as intended."],"rows":[["","reconstruction techniques:\nMultiplanar Reconstruction\n(MPR), Surface rendering, 4D\nviews\n- Reporting tools","Curved MPR, Stretched\nCMRP, Slabbing, MWP,\nALP, MiniP\n- Measurement and\nannotation tools\n- Reporting tools","necessary for the subject\ndevice to perform as\nintended and not including\nthose functions does not\nimpact the performance of\nthe subject device or the\nability to use the subject\ndevice as intended."],["Software Access","Cloud based. The LARALAB software\nincludes cloud-based and related\ncybersecurity functionality for cloud-\nbased devices, including:\n- User authentication\n- Data encryption\n(HTTPS/SSL) in transit and at\nrest\n- Encrypted data storage\n- Third party cloud services\ncompliant with security\nstandards","Traditional client install. 3mensio is a\ntraditional software package, to be\ninstalled on a specific computer.","Although the subject\ndevice is cloud-based and\nthe predicate device is a\ntraditional software\npackage that needs to be\ninstalled on a specific\ncomputer, this difference\nin application access does\nnot impact the intended\nuse or the performance of\nthe device, which remain\nsubstantially equivalent.\nAny risks related to\naccessing the application\nin the cloud that do not\nexist for a specific\ncomputer installation are\nfully mitigated by the\ncybersecurity functionality\nof the subject device.\nTherefore, these minor\ndifferences do not raise\ndifferent questions of\nsafety or effectiveness."],["Import of patient\ndata","- Upload from local device","- Import from local device\n- Import from PACS","Both devices offer similar\nimport/upload functions.\nThe limited difference is\ndue to the cloud-based\nnature of the subject\ndevice, which requires that\npatient data be uploaded,\nas opposed to directly\nimporting data from a\nPACS system, into the local\npredicate device."],["DICOM Support","- CT data in DICOM format\n(vendor independent)\n- Upload DICOM files","- CT data in DICOM format\n(vendor independent)\n- Import DICOM files\n- DICOM compliance for\nCT, Ultrasound images","Similar. Predicate device\noffer additional\nfunctionality for ultrasound\nimages."],["Data privacy","- Data de-identification before\nupload (Protected Health\nInformation (PHI) can\ncompletely be removed and\ndoes not leave the client or\nhospital)","- Data de-identification","Data privacy is effectively\nthe same between the\nsubject and predicate\ndevices. For both devices\npatient data is de-\nidentified and no protected\nhealth information leaves\nthe facility (either because\nit is removed before the\ndata is uploaded, as in the\nsubject device, or because"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242500-p9-t0","doc_id":"K242500","page_num":9,"bbox":[65.17,105.8,520.38,736.09],"n_rows":5,"n_cols":4,"columns":["","","","the data remains on site, as\nin the predicate device)."],"rows":[["","","","the data remains on site, as\nin the predicate device)."],["Data management\nfunctionality","- Study list overview\n- Deleting\n- Search\n- Sorting\n- Export","- Study list overview\n- Deleting\n- Search\n- Sorting\n- Export","Same."],["Automatic analyses","Automatic processing generating:\n- Volumetric segmentations of\ncardiovascular structures\nbased on deterministic Deep\nLearning algorithms\n- Measurements (e.g. splines,\ndistances, angulation,\nvolumes)\n- Assessments containing\nAutomatic Pre-calculated\nviews","Automatic segmentation toolset:\n- Automatic segmentations\n- Automatic centerline","Both devices include\nautomated segmentation\nfunctionality and both\ndevices include the option\nfor the physician to review\nthe segmentation. There\nare slight differences\nbetween the underlying\nautomatic analysis\nconcepts between the\ndevices. Specifically, the\nsubject device provides\nthe user with pre-\ncalculated\nsegmentations/measurem\nents/assessments, which\nthe user can\nreview/adjust/approve.\nAlternatively, the predicate\ndevice includes automated\nand manual steps.\nHowever, in both cases,\nthe type of information\noutputted by the device is\nidentical."],["Image Assessment\nTools","- Length measurement\n- Spline/diameter\nmeasurement\n- Angle Measurement\n- Volume measurements\n- Zoom / Pan / Rotation /\nWindowing tools\n- Markers / Annotation tool\n- C-arm angulation calculation","- Length measurement\n- Spline/diameter\nmeasurement\n- Angle measurement\n- Volume measurements\n- Zoom / Pan / Rotation /\nWindowing tools\n- Markers / Annotation tool\n- C-Arm angulation\ncalculation\nAdditional tools for vascular\nassessment:\n- Calcium scoring for\nassessment of calcium in\nthe aortic root\n- Calcium scoring for\nassessment of calcium in\nthe coronary arteries\n- Segmentation and analysis\nof coronary artery tree\ncenterline","Similar. Predicate device\noffers additional\nfunctionality for coronary\nartery assessment."],["Visualizations","2D\n- Multiplanar Reconstruction\n(MPR)\n- Coloured overlays (of\nsegmented objects)","2D\n- Multiplanar\nReconstruction (MPR)\n- Maximum intensity\nprojection (MIP)","Similar. Predicate device\noffers additional\nfunctionality for image\nassessment."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242500-p10-t0","doc_id":"K242500","page_num":10,"bbox":[65.17,105.8,520.38,301.1],"n_rows":3,"n_cols":4,"columns":["","3D\n- Surface rendering","- Minimum-intensity\nprojection (MinIP)\n- AveIP\n- Curved (CPR) cross-\ncurved, stretched Planar\nReformation\n3D\n- MIP volume rendering\n- Color volume rendering\n- Grayscale volume\nrendering",""],"rows":[["","3D\n- Surface rendering","- Minimum-intensity\nprojection (MinIP)\n- AveIP\n- Curved (CPR) cross-\ncurved, stretched Planar\nReformation\n3D\n- MIP volume rendering\n- Color volume rendering\n- Grayscale volume\nrendering",""],["Storage and Export\nof Results","- Session state\n- Report in PDF format","- Session state\n- Report in PDF format","Same."],["System Outputs","- Case Planning results, incl.:\n- Measurements\n- Screenshots\n- Assessments","- Case Planning results, incl.:\n- Measurements\n- Screenshots\n- Assessments","Same."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242511-p7-t0","doc_id":"K242511","page_num":7,"bbox":[111.65,597.28,543.92,687.22],"n_rows":3,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 & A1:2012 C1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons. Text) [Incl. AMD2:2021] Medical electrical\nequipment - Part 1: General requirements for basic safety and essential\nperformance (IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2:2014 [Including AMD 1:2021] , Medical electrical\nequipment - Part 1-2: General requirements for basic safety and essential","",""]],"caption_candidate":"ultrasound system and its applications comply with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242511-p8-t0","doc_id":"K242511","page_num":8,"bbox":[111.62,78.24,543.96,258.38],"n_rows":6,"n_cols":2,"columns":["","performance - EMC"],"rows":[["","performance - EMC"],["IEC 60601-2-37","IEC 60601-2-37 Edition 2.1 2015, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment"],["IEC 60601-4-2","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -\nPart 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems"],["ISO10993-1","AAMI / ANSI / ISO 10993-1:2018, Biological evaluation of medical\ndevices – Part 1: Evaluation and testing within a risk management process"],["ISO14971","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242522-p7-t0","doc_id":"K242522","page_num":7,"bbox":[61.7,455.6,547.7,610.78],"n_rows":6,"n_cols":4,"columns":["","Subject Device\nSecond Opinion CC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK222746"],"rows":[["","Subject Device\nSecond Opinion CC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK222746"],["Manufacturer","Pearl Inc.","Pearl Inc.","Overjet, Inc."],["Classification","892.2070","892.2070","892.2070"],["Product Code","MYN","MYN","MYN"],["Image\nModality","Radiograph","Radiograph","Radiograph"],["Intended Use","Dental CADe to aid in\ndental radiograph review\nby HCP","Dental CADe to aid in dental\nradiograph review by HCP","Dental CADe to aid in dental\nradiograph review by HCP"]],"caption_candidate":"Table 1: Comparison of Second Opinion CC with the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242522-p8-t0","doc_id":"K242522","page_num":8,"bbox":[61.65,312.8,547.65,585.74],"n_rows":5,"n_cols":4,"columns":["","Subject Device\nSecond Opinion CC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK222746"],"rows":[["","Subject Device\nSecond Opinion CC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK222746"],["","","radiographs of permanent teeth\nin patients 12 years of age or\nolder as a second reader.","from the image, patient history, or\nactual in vivo clinical assessment."],["Intended\nbody part","Dental","Dental","Dental"],["Technology","Utilizes computer vision\nneural network algorithms,\ndeveloped from\nopen-source models using\nsupervised machine\nlearning techniques","Utilizes computer vision neural\nnetwork algorithms, developed\nfrom open-source models\nusing supervised machine\nlearning techniques","Automated, concurrent-read,\nCADe software that utilizes\nmachine learning"],["Device\nDescription","Detection of caries using\npolygons.","Detection of radiological dental\nfindings: 5 restorations\n(crowns, bridges, implants, root\ncanals, fillings), 4 pathologies\n(caries, margin discrepancy,\ncalculus, periapical\nradiolucency) using bounding\nboxes.","Detection and segmentation of\ncaries using polygons."]],"caption_candidate":"bitewing and periapical account other relevant information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242522-p11-t0","doc_id":"K242522","page_num":11,"bbox":[61.63,95.5,534.37,243.5],"n_rows":11,"n_cols":2,"columns":["Total\nN=500",""],"rows":[["Total\nN=500",""],["Overall status, n (%)",""],["Healthy","288 (57.6)"],["Containing Caries","212 (42.4)"],["Number of lesions on abnormal images",""],["Total, n","356"],["Mean (SD)","1.7 (1.23)"],["Median (range)","1.0 (1, 9)"],["Lesion size on abnormal images (percent of image pixels)",""],["Mean (SD)","1.5 (1.95)"],["Median (range)","0.6 (0,11)"]],"caption_candidate":"Table 2 - Summary of image characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p7-t0","doc_id":"K242551","page_num":7,"bbox":[72.07,120.97,540.05,389.21],"n_rows":4,"n_cols":6,"columns":["","Subject Device","","","Predicate Device",""],"rows":[["","Subject Device","","","Predicate Device",""],["","syngo Dynamics VA41D","","","syngo Dynamics VA40F",""],["","K242551","","","K222428",""],["syngo Dynamics is a multimodality, vendor\nagnostic Cardiology image and information\nsystem intended for medical image management\nand processing that provides capabilities relating\nto the review and digital processing of medical\nimages.\nsyngo Dynamics supports clinicians by providing\npost image processing functions for image\nmanipulation, and/or quantification that are\nintended for use in the interpretation and analysis\nof medical images for disease detection,\ndiagnosis, and/or patient management within the\nhealthcare institution’s network.\nsyngo Dynamics is not intended to be used for\ndisplay or diagnosis of digital mammography\nimages in the U.S.","","","syngo Dynamics is a multimodality, vendor\nagnostic Cardiology image and information\nsystem intended for medical image management\nand processing that provides capabilities relating\nto the review and digital processing of medical\nimages.\nsyngo Dynamics supports clinicians by providing\npost image processing functions for image\nmanipulation, and/or quantification that are\nintended for use in the interpretation and analysis\nof medical images for disease detection,\ndiagnosis, and/or patient management within the\nhealthcare institution’s network.\nsyngo Dynamics is not intended to be used for\ndisplaying or diagnosis of digital mammography\nimages in the U.S.","",""]],"caption_candidate":"Indications for Use Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p8-t0","doc_id":"K242551","page_num":8,"bbox":[72.28,95.76,539.84,696.94],"n_rows":8,"n_cols":8,"columns":["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],["","","syngo Dynamics VA41D","","","syngo Dynamics VA40F","",""],["","","K242551","","","K222428","",""],["Architecture","Client-server","","","Client-server","","","Identical"],["Supported\nmodalities","• US\n• XA\n• DX\n• CT\n• MR\n• SC\n• NM\n• PT\n• ECG","","","• US\n• XA\n• DX\n• CT\n• MR\n• SC\n• NM\n• PT\n• ECG","","","Identical"],["Supported\ndeployment","• Standalone medical\ndevice including a\nDICOM Server\n• Integrated model within\nan Electronic Health\nRecord (EHR) System\nwith a DICOM Archive\n• Multimodality\nCardiovascular\n(MMCV) deployment\nwith native support of\n2D/3D CT/MR image\ntypes","","","• Standalone medical\ndevice including a\nDICOM Server\n• Integrated model within\nan Electronic Health\nRecord (EHR) System\nwith a DICOM Archive\n• Multimodality\nCardiovascular\n(MMCV) deployment\nwith native support of\n2D/3D CT/MR image\ntypes","","","Identical"],["Image\nCommunication","Within the network, the\nfollowing communication\nprotocols are used:\n• TCP/IP: for\ncommunication and\ntransport\n• DICOM and HL7 at\napplication level\n• HTTP for\ncommunication and\ntransport of images,\nMP4s and thumbnails","","","Within the network, the\nfollowing communication\nprotocols are used:\n• TCP/IP for\ncommunication and\ntransport\n• DICOM and HL7 at\napplication level\n• HTTP(S) for\ncommunication and\ntransport of images,\nMP4s and thumbnails","","","Identical"],["Image Data\nCompression","Lossless compression with\ncompression factor 2 to 3\nand lossy compression\n(JPEG and MP4) with\nhigher compression rate.","","","Lossless compression with\ncompression factor 2 to 3\nand lossy compression\n(JPEG and MP4) with\nhigher compression rate.","","","Identical"]],"caption_candidate":"Traditional 510(k) K242551","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p9-t0","doc_id":"K242551","page_num":9,"bbox":[72.29,85.92,539.84,642.58],"n_rows":7,"n_cols":8,"columns":["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],["","","syngo Dynamics VA41D","","","syngo Dynamics VA40F","",""],["","","K242551","","","K222428","",""],["Imaging\nAlgorithms","• Window/Leveling\n• Edge Enhancement\n• Digital Subtraction\n• Multiplanar\nreconstruction (MPR)\n• Maximum and\nMinimum Intensity\nProjection (MIP/MinIP)\n• Volume Rendering\nTechnique (VRT)\n• Gamma Correction\n• Manual and semi-\nautomated calculation\nfor left ventricular\nejection fraction (Auto\nEF, updated)","","","• Window/Leveling\n• Edge Enhancement\n• Digital Subtraction\n• Multiplanar\nreconstruction (MPR)\n• Maximum and\nMinimum Intensity\nProjection (MIP/MinIP)\n• Volume Rendering\nTechnique (VRT)\n• Gamma Correction\n• Manual and semi-\nautomated calculation\nfor left ventricular\nejection fraction (Auto\nEF)","","","Enhanced. Rationale is\nprovided below this\ntable."],["Quantitative\nalgorithms","• Pixel Size Evaluation\n• Distance line\n• Angle\n• volume","","","• Pixel Size Evaluation\n• Distance line\n• Angle\n• Volume","","","Identical"],["Decision\nSupport","Ability to interface with a\nthird-party rules engine\n(BizTalk), where rules are\nconfigured by the end\ncustomer to determine\nclinical relevance of\nselected observations.\nCustomers identify and\nstore selected patient data.\nOrchestrations provide a\ntrigger to pull in previously\nstored relevant data for a\ngiven study.","","","Ability to interface with a\nthird-party rules engine\n(BizTalk), where rules are\nconfigured by the end\ncustomer to determine\nclinical relevance of\nselected observations.\nCustomers identify and\nstore selected patient data.\nOrchestrations provide a\ntrigger to pull in previously\nstored relevant data for a\ngiven study.","","","Identical"],["Reporting","• Customizable DICOM\nStructured Reporting\n• Collaborative reporting\n• Web reporting","","","• Customizable DICOM\nStructured Reporting\n• Collaborative reporting\n• Remote reporting","","","Identical"]],"caption_candidate":"Traditional 510(k) K242551","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p10-t0","doc_id":"K242551","page_num":10,"bbox":[72.28,85.92,539.84,675.94],"n_rows":8,"n_cols":8,"columns":["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],["","","syngo Dynamics VA41D","","","syngo Dynamics VA40F","",""],["","","K242551","","","K222428","",""],["Access\nstrategies for\nimaging and\nreporting","• Workplace (thick\nclient)- access for\nreading and reporting.\n• Remote Workplace\n(MP4 image display\nwith access to full\nDICOM image for\nUS/XA and full\nDICOM image for\nCT/MR) – access for\nreading and reporting\n• WebViewer – (Web\nClient with MP4 Image\ndisplay) – Access for\nreview only","","","• Workplace (thick\nclient) – access for\nreading and reporting.\n• Remote Workplace\n(MP4 image display\nwith access to full\nDICOM image for\nUS/XA and full\nDICOM image for\nCT/MR) – access for\nreading and reporting.\n• WebViewer- (Web\nClient with MP4 Image\ndisplay) – Access for\nreview only","","","Identical"],["Mobile Device\nSupport","Yes –Through the Common\nLogin and Web Viewer,\nimages can be viewed on\nmobile devices,\nWebViewer, supports iOS\nand Android devices, but\nare non-diagnostic use.","","","Yes –Through the Common\nLogin and Web Viewer,\nimages can be viewed on\nmobile devices,\nWebViewer, supports iOS\nand Android devices, but\nare non-diagnostic use.","","","Identical"],["Long Term\nArchive","Provide long term archive\nand retrieve of DICOM\nstudies to/from either VNA\n(Vendor Neutral Archive)\nor HSM (Hierarchical\nStorage Management)\narchiving Systems.","","","Provide long term archive\nand retrieve of DICOM\nstudies to/from either VNA\n(Vendor Neutral Archive)\nor HSM (Hierarchical\nStorage Management)\narchiving Systems.","","","Identical"],["Hardware","Software-only option for\nserver Workstation:\nsoftware only (HW is not\npart of the medical device,\nbut needs to meet\nrecommended requirements\nas specified by syngo\nDynamics)","","","Software-only option for\nserver Workstation:\nsoftware only (HW is not\npart of the medical device,\nbut needs to meet\nrecommended requirements\nas specified by syngo\nDynamics)","","","Identical"],["Virtualization","Provides virtualization of\nserver and client machines","","","Provides virtualization of\nserver and client machines","","","Identical"]],"caption_candidate":"Traditional 510(k) K242551","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p11-t0","doc_id":"K242551","page_num":11,"bbox":[72.3,85.92,539.82,593.5],"n_rows":5,"n_cols":8,"columns":["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],"rows":[["Attribute","","Subject Device","","","Predicate Device","","Equivalency\nAnalysis"],["","","syngo Dynamics VA41D","","","syngo Dynamics VA40F","",""],["","","K242551","","","K222428","",""],["Operating\nsystem","Server:\nMicrosoft Windows server\n2016 Standard edition (64\nbit)\nMicrosoft Windows Server\n2019 Standard Edition (64\nBit)\nClient Software: Microsoft\nWindows 10 x64 version\n1803 or greater\nPortal Website Host:\nMicrosoft Windows Server\n2016 Standard edition (64-\nbit), Microsoft Windows\nServer 2019 Standard\nedition (64-bit)","","","Server:\nMicrosoft Windows server\n2016 Standard edition (64\nbit)\nMicrosoft Windows Server\n2019 Standard Edition (64\nBit)\nClient Software: Microsoft\nWindows 10 x64 version\n1803 or greater\nPortal Website Host:\nMicrosoft Windows Server\n2016 Standard edition (64-\nbit), Microsoft Windows\nServer 2019 Standard\nedition (64-bit)","","","Identical"],["Deployment\nstrategy","• The use of syngo\nDynamics VA41D\nserver/workplace in the\ncontext of\ncardiovascular\nconfiguration.\n• EHR/EHS Integrated\nconfiguration with\nsyngo Dynamics server.\n• Multi-modality\ncardiovascular\nconfiguration with\nnative/syngo server and\nsyngo Dynamics\nworkplace with\nnative/syngo\ncomponents.","","","• The use of syngo\nDynamics VA40F\nserver/workplace in the\ncontext of\ncardiovascular\nconfiguration.\n• EHR/EHS Integrated\nconfiguration with\nsyngo Dynamics server.\n• Multi-modality\ncardiovascular\nconfiguration with\nnative/syngo server and\nsyngo Dynamics\nworkplace with\nnative/syngo\ncomponents.","","","Identical"]],"caption_candidate":"Traditional 510(k) K242551","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242551-p14-t0","doc_id":"K242551","page_num":14,"bbox":[77.66,98.54,557.86,358.49],"n_rows":4,"n_cols":3,"columns":["Planned Modifications","Test Methods and Validation\nActivities","Communication to users, as needed"],"rows":[["Planned Modifications","Test Methods and Validation\nActivities","Communication to users, as needed"],["Modification Group #1:\nRe-training Auto EF ML-\nDSF with additional data","Performance testing will be\nrepeated using the same test\nmethods and acceptance criteria\nas that used in syngo Dynamics\nVA41D.","Labeling will be updated in accordance\nwith the authorized PCCP to provide\nusers with current information regarding\nthe device’s re-training process and\nperformance capabilities"],["Modification Group #2:\nOptimizations of the Auto\nEF ML-DSF core\nalgorithms","Performance testing will be\nrepeated using the same test\nmethods and acceptance criteria\nas that used in syngo Dynamics\nVA41D.","Labeling will be updated in accordance\nwith the authorized PCCP to provide\nusers with current information regarding\nthe device’s re-training process and\nperformance capabilities"],["Modification Group #3:\nAuto EF ML-DSF with\ncontrast support","Performance testing will be\nrepeated using the same test\nmethods and acceptance criteria\nas that used in syngo Dynamics\nVA41D. Performance testing\nwill be expanded to include\ncontrast cases.","Labeling will be updated in accordance\nwith the authorized PCCP to provide\nusers with current information regarding\nthe device’s capabilities with expanded\ninput images including contrast."]],"caption_candidate":"Summary Predetermined Modifications for Auto EF","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p7-t0","doc_id":"K242594","page_num":7,"bbox":[76.6,160.16,535.64,649.9],"n_rows":12,"n_cols":6,"columns":["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],"rows":[["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],["","","","","(Biometry Assist feature",""],["","","","","in the V8 ultrasound",""],["","","","","system)",""],["510(k)\nNumber","K242594","K230365","K223387","",""],["Applicant","DeepEcho","Sonio","Samsung Medison Co.","",""],["Device Name","DEEPECHO","Sonio Detect","Biometry Assist feature in\nthe V8 ultrasound system","",""],["Classification\nRegulation","892.1550 - Accessory to\nUltrasonic Pulsed\nDoppler Imaging\nSystem\n892.1560 - Accessory to\nUltrasonic Pulsed Echo\nImaging System\n892.2050 - Medical\nImage Management and\nProcessing System","892.1550 - Accessory to\nUltrasonic Pulsed Doppler\nImaging System\n892.1560 - Accessory to\nUltrasonic Pulsed Echo\nImaging System\n892.2050 - Medical Image\nManagement and\nProcessing System","892.1550 - Ultrasonic\nPulsed Doppler Imaging\nSystem\n892.1560 - Ultrasonic\nPulsed Echo Imaging\nSystem\n892.1570 - Diagnostic\nUltrasound Transducer","",""],["Product\nCode","IYN (Primary), IYO,\nQIH (Secondary)","IYN (Primary), IYO, QIH\n(Secondary)","IYN, IYO, ITX","",""],["Intended\nUsers","Qualified and trained\nhealthcare professionals\nincluding radiologists,\nobstetricians,\nsonographers,\nOB/GYNs, maternal\nand fetal medicine\nspecialists (MFM\nspecialists), and fetal\nsurgeons","Qualified and trained\nhealthcare professionals in\na professional prenatal\nultrasound imaging\nenvironment, including\nsonographers, MFMs,\nOB/GYNs, and fetal\nsurgeons","Appropriately trained\nhealthcare professionals\nqualified for direct use of\nmedical devices","",""],["Patient\nPopulation","Pregnant patients aged\n18 years and older,\nfrom 14 to 41 weeks of\ngestation","Pregnant patients across\nTrimester 1, Trimester 2,\nand Trimester 3, from 11\nweeks to 37 weeks of\ngestation","Females of reproductive\nage","",""],["Imaging\nModality","Ultrasound","Ultrasound","Ultrasound","",""]],"caption_candidate":"Table 1: Comparator Table for Subject and Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p8-t0","doc_id":"K242594","page_num":8,"bbox":[76.6,72.54,535.63,681.82],"n_rows":9,"n_cols":6,"columns":["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],"rows":[["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],["","","","","(Biometry Assist feature",""],["","","","","in the V8 ultrasound",""],["","","","","system)",""],["Views\nDetected","Cephalic view,\nAbdominal view,\nFemoral view","Transthalamic view,\nTransventricular view,\nTranscerebellar view, Four\nchambers, Profile or\nNuchal translucency,\nCrown rump length,\nSagittal spine, Abdominal\ncircumference, Long bone,\nUpper lip, nose, and\nnostrils, Left ventricular\noutflow tract, Right\nventricular outflow tract","8 views recommended by\nthe ISUOG and AIUM for\nbiometric measurements\nand heart assessment.","",""],["Measurement\nComputation","Femur Length (FL),\nAbdominal\ncircumference (AC),\nAmniotic Fluid\nPocket’s Depth, Head\ncircumference (HC),\nBiparietal Diameter\n(BPD) Estimated Fetal\nWeight (EFW),\nEstimated Gestational\nAge (EGA)","None","Length measurement (FL,\nBPD)\nEllipse measurement (AC,\nHC)\nNuchal Translucency","",""],["Findings","Images labeled with\ncorrect views, caliper\nplacement suggestion\nand measurement for\ncircumference and\ndistance for metrics\nsuch as HC, BPD, FL,\nAC, and examination\nreports","Images labeled with\ncorrect views, quality\ncriteria identified as\n\"Verified\" when detected\nand \"Not verified\" when\nnot detected","Images labeled with correct\nview\nCaliper placement\nsuggestion and\nmeasurement for\ncircumference, distance and\nNuchal Translucency\nEditable examination report\naccessible on the console","",""],["Clinical\nApplications","Fetal/Obstetrics","Fetal/Obstetrics","Fetal/Obstetrics","",""],["Real-Time\nAssistance","Provides real-time\nidentification of views\nand suggestions for\ncaliper placement.","Primarily focused on\nverifying the quality\ncriteria of detected views,\nensuring that all required\nviews are captured\naccording to standardized\nprotocols","Available on the Samsung\nV8 for automated view\nrecognition and\nmeasurement.","",""]],"caption_candidate":"510(k) Summary – K242594","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p9-t0","doc_id":"K242594","page_num":9,"bbox":[76.62,72.54,535.61,264.41],"n_rows":6,"n_cols":6,"columns":["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],"rows":[["Category","Proposed Device\n(DEEPECHO)","Primary Predicate\nDevice (Sonio Detect)","","Reference Device",""],["","","","","(Biometry Assist feature",""],["","","","","in the V8 ultrasound",""],["","","","","system)",""],["Algorithm\nMethodology","Artificial Intelligence\nfor biometric\nmeasurement\ncomputations","Artificial Intelligence for\nlecture of biometrics and\ncolorimetry for 3D and\nDoppler","Deep learning-based\nrecognition algorithm","",""],["Platform and\nAccessibility","Cloud-based standalone\nsoftware accessible\nfrom various devices,\noffering flexibility and\nease of integration into\ndifferent clinical\nenvironments","A SaaS solution with edge\nsoftware requiring\ninstallation on a server\nconnected to the\nultrasound machine","Embedded in the ultrasound\nequipment.","",""]],"caption_candidate":"510(k) Summary – K242594","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p11-t0","doc_id":"K242594","page_num":11,"bbox":[98.9,406.85,513.12,579.91],"n_rows":6,"n_cols":6,"columns":["Variable","N","Intercept","","Slope",""],"rows":[["Variable","N","Intercept","","Slope",""],["","","Point Estimate","95% CI","Point Estimate","95% CI"],["Femur Length","431","0.003","(-0.020, 0.025)","0.969","(0.966, 0.973)"],["Head Circumference","858","-.360","(-0.462, -.0258)","1.026","(1.022, 1.031)"],["Abdominal Circumference","499","-.017","(-0.101, 0.065)","1.017","(1.013, 1.021)"],["Biparietal Diameter","858","-.165","(-0.203, -0.125)","1.020","(1.015, 1.025)"]],"caption_candidate":"Table 2: Primary Endpoints #1 - #4 Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p12-t0","doc_id":"K242594","page_num":12,"bbox":[126.38,92.42,485.62,293.42],"n_rows":8,"n_cols":4,"columns":["Endpoint of Interest","","Statistics",""],"rows":[["Endpoint of Interest","","Statistics",""],["","","n/N","Point Estimate\n(95% CI)*"],["Abdominal View","Sensitivity","442/508","86.9% (83.8% - 89.7%)"],["","Specificity","7107/7340","96.8% (96.4% - 97.2%)"],["Cephalic View","Sensitivity","992/1010","98.2% (97.4% - 99%)"],["","Specificity","6482/6838","94.8% (94.2% - 95.3%)"],["Femoral View","Sensitivity","415/452","91.8% (89% - 94.2%)"],["","Specificity","7204/7396","97.4% (97% - 97.8%)"]],"caption_candidate":"Table 3: Primary Endpoints #5 and #6 Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p12-t1","doc_id":"K242594","page_num":12,"bbox":[71.06,661.45,541.22,715.36],"n_rows":3,"n_cols":4,"columns":["Anatomica\nl View","Measureme\nnt","<= 28 weeks",""],"rows":[["Anatomica\nl View","Measureme\nnt","<= 28 weeks",""],["","","","> 28 weeks"],["Abdominal","Sensitivity","180/220 (81.8%) [0.761 - 0.867]","221/233 (94.8%) [0.912 - 0.973]"]],"caption_candidate":"View","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p13-t0","doc_id":"K242594","page_num":13,"bbox":[46.08,38.69,556.7,634.31],"n_rows":48,"n_cols":11,"columns":["","","","","510(k) Sum","mary –","K242594","","","",""],"rows":[["","","","","510(k) Sum","mary –","K242594","","","",""],["","","","","","","","","","",""],["","Anatomica","","Measureme","","","","","","",""],["","l View","","nt","<= 28","weeks","","> 28 wee","ks","",""],["","","","","","","","","","",""],["","","","Specificity","4576/4698 (9","7.4%) [0.969","- 2123/2","227 (95.3","%) [0",".944 -",""],["","","","","0.9","78]","","0.962]","","",""],["","","","","","","","","","",""],["","Cephalic","","Sensitivity","564/580 (97.2%",") [0.956 - 0.9","84] 367/369","(99.5%) [0",".981","- 0.999]",""],["","","","","","","","","","",""],["","","","Specificity","4093/4338 (94.4","%) [0.936 - 0",".95] 1995/2","091 (95.4","%) [0",".944 -",""],["","","","","","","","0.963]","","",""],["","","","","","","","","","",""],["","Femoral","","Sensitivity","174/197 (88.3%",") [0.83 - 0.9","25] 199/206","(96.6%) [0",".931","- 0.986]",""],["","","","","","","","","","",""],["","","","Specificity","4580/4721 (97%",") [0.965 - 0.","975] 2211/2","254 (98.1","%) [0",".974 -",""],["","","","","","","","0.986]","","",""],["","","","","","","","","","",""],["","Table 5:","V","iew Identifica","tion Primary End","point by BMI","Subgroups and","Per Anato","mical","View",""],["","","","","","","","","","",""],["An","atomical","","Measurem","","","","","","",""],["","View","","ent","18.5 - 25","25 - 30","30 - 35","35 - 40","","> 40",""],["","","","","","","","","","",""],["Abdo","minal","S","ensitivity 3","9/48 (81.3%) 44/","46 (95.7%)","17/17 (100%)","6/7 (85.7","%)","3/4 (75","%)"],["","","","","[0.674 -","[0.852 -","[0.805 - 1]","[0.421","-","[0.194","-"],["","","","","0.911]","0.995]","","0.996]","","0.994]",""],["","","","","","","","","","",""],["","","S","pecificity","903/926","514/532","166/171","80/83 (96.","4%)","43/45 (95.","6"],["","","","","(97.5%)","(96.6%)","(97.1%)","[0.898","-","[0.849","-"],["","","","","[0.963 - [0.","947 - 0.98]","[0.933 - 0.99]","0.992]","","0.995]",""],["","","","","0.984]","","","","","",""],["","","","","","","","","","",""],["Ceph","alic","S","ensitivity","132/133 86/","87 (98.9%)","23/23 (100%)","13/14 (92.","9%)","7/7 (100","%)"],["","","","","(99.2%) [","0.938 - 1]","[0.852 - 1]","[0.661","-","[0.59 -","1]"],["","","","","[0.959 - 1]","","","0.998]","","",""],["","","","","","","","","","",""],["","","S","pecificity","807/841","475/491","156/165","73/76 (96.","1%)","40/42 (95.","2"],["","","","","(96%) [0.944","(96.7%)","(94.5%)","[0.889","-","[0.838","-"],["","","","","- 0.972]","[0.948 -","[0.899 -","0.992]","","0.994]",""],["","","","","","0.981]","0.975]","","","",""],["","","","","","","","","","",""],["Femo","ral","S","ensitivity 3","2/34 (94.1%) 34","/34 (100%)","12/12 (100%)","5/5 (100","%)","4/4 (100","%)"],["","","","","[0.803 - [","0.897 - 1]","[0.735 - 1]","[0.478 -","1]","[0.398 -","1]"],["","","","","0.993]","","","","","",""],["","","","","","","","","","",""],["","","S","pecificity","914/940","535/544","174/176","83/85 (97.","6%)","45/45 (10","0%"],["","","","(","97.2%) [0.96","(98.3%)","(98.9%) [0.96","[0.918","-","[0.921 -","1]"],["","","","","- 0.982]","[0.969 -","- 0.999]","0.997]","","",""]],"caption_candidate":"510(k) Summary – K242594","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242594-p13-t1","doc_id":"K242594","page_num":13,"bbox":[70.91,72.51,541.07,248.31],"n_rows":10,"n_cols":4,"columns":["Anatomica","Measureme\nnt","<= 28 weeks",""],"rows":[["Anatomica","Measureme\nnt","<= 28 weeks",""],["l View","","","> 28 weeks"],["","Specificity","4576/4698 (97.4%) [0.969 -\n0.978]","2123/2227 (95.3%) [0.944 -"],["","","","0.962]"],["Cephalic","Sensitivity","564/580 (97.2%) [0.956 - 0.984]","367/369 (99.5%) [0.981 - 0.999]"],["","Specificity","4093/4338 (94.4%) [0.936 - 0.95]","1995/2091 (95.4%) [0.944 -"],["","","","0.963]"],["Femoral","Sensitivity","174/197 (88.3%) [0.83 - 0.925]","199/206 (96.6%) [0.931 - 0.986]"],["","Specificity","4580/4721 (97%) [0.965 - 0.975]","2211/2254 (98.1%) [0.974 -"],["","","","0.986]"]],"caption_candidate":"510(k) Summary – K242594","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242594-p14-t0","doc_id":"K242594","page_num":14,"bbox":[25.8,106.53,585.72,426.52],"n_rows":20,"n_cols":6,"columns":["Anatomical View","Measurement","Butterfly","Clarius","General","Philips Medical\nSystems"],"rows":[["Anatomical View","Measurement","Butterfly","Clarius","General","Philips Medical\nSystems"],["","","","","Electric",""],["Abdominal","Sensitivity","28/42 (66.7%)\n[0.505 - 0.804]","8/9 (88.9%)\n[0.518 - 0.997]","252/295","154/162\n(95.1%) [0.905 -\n0.978]"],["","","","","(85.4%) [0.809 -",""],["","","","","0.892]",""],["","Specificity","77/77 (100%)\n[0.953 - 1]","155/167\n(92.8%) [0.878 -\n0.962]","5484/5628","1386/1463\n(94.7%) [0.935 -\n0.958]"],["","","","","(97.4%) [0.97 -",""],["","","","","0.978]",""],["Cephalic","Sensitivity","37/37 (100%)\n[0.905 - 1]","13/13 (100%)\n[0.753 - 1]","630/635","312/325 (96%)\n[0.933 - 0.979]"],["","","","","(99.2%) [0.982 -",""],["","","","","0.997]",""],["","Specificity","82/82 (100%)\n[0.956 - 1]","141/163\n(86.5%) [0.803 -\n0.913]","5088/5288","1166/1300\n(89.7%) [0.879 -\n0.913]"],["","","","","(96.2%) [0.957 -",""],["","","","","0.967]",""],["Femoral","Sensitivity","33/40 (82.5%)\n[0.672 - 0.927]","8/11 (72.7%)\n[0.39 - 0.94]","207/216","167/185\n(90.3%) [0.851 -\n0.941]"],["","","","","(95.8%) [0.922 -",""],["","","","","0.981]",""],["","Specificity","79/79 (100%)\n[0.954 - 1]","152/165\n(92.1%) [0.869 -\n0.957]","5590/5707","1378/1440\n(95.7%) [0.945 -\n0.967]"],["","","","","(97.9%) [0.975 -",""],["","","","","0.983]",""]],"caption_candidate":"View","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242600-p7-t0","doc_id":"K242600","page_num":7,"bbox":[61.7,446.75,547.7,601.9],"n_rows":6,"n_cols":4,"columns":["","SubjectDevice\nSecondOpinionPC","PrimaryPredicate\nSecondOpinion\nK210365","SecondaryPredicate\nOverjet\nK231678"],"rows":[["","SubjectDevice\nSecondOpinionPC","PrimaryPredicate\nSecondOpinion\nK210365","SecondaryPredicate\nOverjet\nK231678"],["Manufacturer","PearlInc.","PearlInc.","Overjet,Inc."],["Classification","892.2070","892.2070","892.2070"],["ProductCode","MYN","MYN","MYN"],["Image\nModalit\ny","Radiograph","Radiograph","Radiograph"],["IntendedUse","DentalCADetoaidindental\nradiographreviewbyHCP","DentalCADetoaidindental\nradiographreviewbyHCP","DentalCADetoaidindental\nradiographreviewbyHCP"]],"caption_candidate":"Table 1: Comparison of Second Opinion PC with the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242600-p8-t0","doc_id":"K242600","page_num":8,"bbox":[61.5,91.5,547.5,547.5],"n_rows":4,"n_cols":4,"columns":["FullIFU","Second Opinion PC is a\ncomputer aided detection\n(\"CADe”) software to aid\ndentists in the detection of\nperiapical radiolucencies\nby drawing bounding\npolygons to highlight the\nsuspected region of\ninterest.\nIt is designed to aid dental\nhealth professionals to\nreview periapical\nradiographs of permanent\nteeth in patients 12 years\nof age or older as a second\nreader.","SecondOpinionisacomputer\naideddetection(\"CADe”)\nsoftwaretoidentifyandmark\nregionsinrelationtosuspected\ndentalfindingswhichinclude\nCaries,Discrepancyatthe\nmarginofanexisting\nrestoration,Calculus,Periapical\nradiolucency,Crown(metal,\nincludingzirconia&non-metal),\nFilling(metal&non-metal),\nRootcanal,Bridgeand\nImplants.\nItisdesignedtoaiddental\nhealthprofessionalstoreview\nbitewingandperiapical\nradiographsofpermanentteeth\ninpatients12yearsofageor\nolderasasecondreader.","OverjetPeriapicalRadiolucency\n(PARL)Assistisaradiological,\nautomated,concurrentread\ncomputer-assisteddetection\nsoftwareintendedtoaidinthe\ndetectionofperiapicalradiolucencies\nonpermanentteethcapturedon\nperiapicalradiographs.Thedevice\nprovidesadditionalaidforthedentist\ntouseintheiridentificationof\nperiapicalradiolucency.Thedevice\nisnotintendedasareplacementfor\nacompletedentist’sreviewortheir\nclinicaljudgmentthatconsidersother\nrelevantinformationfromtheimage\norpatienthistory.Thesystemisto\nbeusedbyprofessionallytrained\nandlicenseddentists.\nTheOverjetPeriapicalRadiolucency\nAssistsoftwareisindicatedforuse\nonpatients12yearsofageorolder."],"rows":[["FullIFU","Second Opinion PC is a\ncomputer aided detection\n(\"CADe”) software to aid\ndentists in the detection of\nperiapical radiolucencies\nby drawing bounding\npolygons to highlight the\nsuspected region of\ninterest.\nIt is designed to aid dental\nhealth professionals to\nreview periapical\nradiographs of permanent\nteeth in patients 12 years\nof age or older as a second\nreader.","SecondOpinionisacomputer\naideddetection(\"CADe”)\nsoftwaretoidentifyandmark\nregionsinrelationtosuspected\ndentalfindingswhichinclude\nCaries,Discrepancyatthe\nmarginofanexisting\nrestoration,Calculus,Periapical\nradiolucency,Crown(metal,\nincludingzirconia&non-metal),\nFilling(metal&non-metal),\nRootcanal,Bridgeand\nImplants.\nItisdesignedtoaiddental\nhealthprofessionalstoreview\nbitewingandperiapical\nradiographsofpermanentteeth\ninpatients12yearsofageor\nolderasasecondreader.","OverjetPeriapicalRadiolucency\n(PARL)Assistisaradiological,\nautomated,concurrentread\ncomputer-assisteddetection\nsoftwareintendedtoaidinthe\ndetectionofperiapicalradiolucencies\nonpermanentteethcapturedon\nperiapicalradiographs.Thedevice\nprovidesadditionalaidforthedentist\ntouseintheiridentificationof\nperiapicalradiolucency.Thedevice\nisnotintendedasareplacementfor\nacompletedentist’sreviewortheir\nclinicaljudgmentthatconsidersother\nrelevantinformationfromtheimage\norpatienthistory.Thesystemisto\nbeusedbyprofessionallytrained\nandlicenseddentists.\nTheOverjetPeriapicalRadiolucency\nAssistsoftwareisindicatedforuse\nonpatients12yearsofageorolder."],["Intended\nbodypart","Dental","Dental","Dental"],["Technology","Utilizescomputervision\nneuralnetworkalgorithms,\ndevelopedfrom\nopen-sourcemodelsusing\nsupervisedmachine\nlearningtechniques","Utilizescomputervisionneural\nnetworkalgorithms,developed\nfromopen-sourcemodels\nusingsupervisedmachine\nlearningtechniques","Automated,concurrent-read,\nCADesoftwarethatutilizes\nmachinelearning"],["Device\nDescription","Detectionofperiapical\nradiolucenciesusing\npolygons.","Detectionofradiologicaldental\nfindings:5restorations\n(crowns,bridges,implants,root\ncanals,fillings),4pathologies\n(caries,margindiscrepancy,\ncalculus,periapical\nradiolucency)usingbounding\nboxes.","Detectionandsegmentationof\nperiapicalradiolucenciesusing\npolygons."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242600-p10-t0","doc_id":"K242600","page_num":10,"bbox":[61.63,532.56,534.37,692.5],"n_rows":12,"n_cols":2,"columns":["Total\nN=500",""],"rows":[["Total\nN=500",""],["Overallstatus,n(%)",""],["Normal","380(76.0)"],["Abnormal","120(24.0)"],["Numberoflesionsonabnormalimages",""],["Total,n","151"],["Mean(SD)","1.3(0.46)"],["Median(range)","1.0(1,3)"],["Lesionsizeonabnormalimages(percentofimagepixels)",""],["Mean(SD)","2.8(3.02)"],["Median(range)","1.7(0,17)"],["Sourcetable:S_IMG_ALL.rtf",""]],"caption_candidate":"Table 2 - Summary of image characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p5-t0","doc_id":"K242607","page_num":5,"bbox":[43.29,401.77,552.48,499.06],"n_rows":6,"n_cols":2,"columns":["Trade Name","ScanDiags Ortho L-Spine MR-Q"],"rows":[["Trade Name","ScanDiags Ortho L-Spine MR-Q"],["Common Name","Ortho L-Spine MR-Q"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"],["Regulatory Class","Class II"]],"caption_candidate":"2.1 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p5-t1","doc_id":"K242607","page_num":5,"bbox":[43.29,547.6,552.48,645.01],"n_rows":6,"n_cols":2,"columns":["Trade Name","CoLumbo"],"rows":[["Trade Name","CoLumbo"],["510(k) Submitter/Holder","Smart Soft Healthcare AD"],["510(k) Number","K220497"],["Classification Name","Medical image management and processing system"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"]],"caption_candidate":"2.2 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p7-t0","doc_id":"K242607","page_num":7,"bbox":[43.01,315.83,552.39,763.8],"n_rows":14,"n_cols":3,"columns":["","Subject Device:","Predicate Device:"],"rows":[["","Subject Device:","Predicate Device:"],["","",""],["","ScanDiags Ortho L-Spine MR-Q","CoLumbo"],["","",""],["510(k) number","TBD","K220497"],["Applicant","ScanDiags AG","Smart Soft Healthcare AD"],["Device Name","ScanDiags Ortho L-Spine MR-Q","CoLumbo"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050"],["Product Code","QIH","QIH"],["Class","II","II"],["Image Modality","Radiological images: MRI\n(Standardized images used as input)","Radiological images: MRI\n(Standardized images used as input)"],["Study Type\n(anatomical area\nof interest)","Lumbar spine","Lumbar spine"],["Segmentation\nand quantitative\nanalysis","• Lumbar spine vertebral body\narea\n• Lumbar spine intervertebral disc\narea\n• Foraminal area segmentation\n• Spinal canal area\nFor all segmented areas the area in mm2\nis calculated","• Vertebral body area\n• Intervertebral disc area\n• Foraminal stenosis clearance size\n• Dural sac area and stenotic ratio"],["Measurements","• Vertebral body heights (anterior,\nmiddle, posterior)\n• Vertebral body derived\nmeasurements:\no Height ratios","• Vertebral body height (anterior,\nmiddle, posterior)\n• Disc height (anterior, middle,\nposterior)\n• Spinal canal anteroposterior\ndiameter"]],"caption_candidate":"Spine MR-Q) to the predicate device (CoLumbo, K220497).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p8-t0","doc_id":"K242607","page_num":8,"bbox":[42.96,81.14,552.48,763.68],"n_rows":9,"n_cols":3,"columns":["","o Angle\no Biconcave height losses\n• Intervertebral disc heights\n(anterior, middle, posterior)\n• Spinal canal anteroposterior and\nmediolateral diameters",""],"rows":[["","o Angle\no Biconcave height losses\n• Intervertebral disc heights\n(anterior, middle, posterior)\n• Spinal canal anteroposterior and\nmediolateral diameters",""],["Provided output","Report:\nA Measurement Result PDF-report sent\nback to the PACS, which is reviewed,\nrevised and approved by radiologist and\ncontains cropped versions of the original\nMRI images, with an overlay on top of the\ncropped images to highlight the\nsegmented anatomic structures and\napplied measurements and tables\ndisplaying quantitative data of the\nanatomic areas of interest.","Report:\nExport of measurement results to a written\nreport for user's review, revise and\napproval."],["Human\nIntervention for\nInterpretation","Required","Required"],["Privacy","The ScanDiags Ortho L-Spine MR-Q\nSoftware is HIPAA Compliant by\npreventing unauthorized access (only\nauthenticated and authorized users can\naccess DICOM data and preliminary\nMeasurement Results in built-in\nScanDiags DICOM Viewer), encrypting\ndata in transfer (both DICOM-TLS, SSL\ncertificates in use). The DICOM data\ntransferred to and processed by\nScanDiags Ortho L-Spine MR-Q Software\nonly temporarily stores the data until it is\neither approved or rejected by the\nintended user. The vulnerability\nassessment and penetration testing\ndemonstrates satisfactory security\nperformance.","Smart Soft Healthcare conforms to the\ncybersecurity requirements by\nimplementing a process of\npreventing unauthorized access,\nmodifications, misuse or denial of use, or\nthe unauthorized use of\ninformation that is stored, accessed or\ntransferred from a medical device to an\nexternal recipient. The\nvulnerability assessment and penetration\ntesting demonstrates satisfactory security\nperformance."],["SaMD","Yes","Yes"],["Supported\nModality","MR","MR"],["Patient\nPopulation","Adult ≥ 22 years of age","Patients aged ≥ 18 are considered to be\nvalid input."],["Intended User","Clinicians","Clinicians"],["Machine\nLearning\nMethodology","Supervised Deep Convolutional Neural\nNetwork (DCNN), both for classification\n(image-to-class) to and segmentation\n(image-to-image) model architectures","Deep Convolutional Image-to-Image\nNeural Network"]],"caption_candidate":"Page 4 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p10-t0","doc_id":"K242607","page_num":10,"bbox":[43.13,200.1,552.3,441.67],"n_rows":15,"n_cols":3,"columns":["Mean intraclass correlation coefficient (ICC) of measurements (heights, diameters and areas) for","",""],"rows":[["Mean intraclass correlation coefficient (ICC) of measurements (heights, diameters and areas) for","",""],["lumbar vertebrae, discs, neuroforamina and the thecal sac.","",""],["Body Region","Measurement","ICC [95% CI]"],["Vertebra","Area","0.95 [0.94 - 0.96]"],["","Anterior Height","0.85 [0.30 - 0.94]"],["","Middle Height","0.91 [0.63 - 0.96]"],["","Posterior Height","0.89 [0.87 - 0.91]"],["Neuroforamen","Area","0.90 [0.86 - 0.93]"],["Intervertebral Disc","Area","0.92 [0.87 - 0.94]"],["","Anterior Height","0.78 [0.73 - 0.82]"],["","Middle Height","0.85 [0.18 - 0.95]"],["","Posterior Height","0.74 [0.68 - 0.78]"],["Thecal Sac","Area","0.94 [0.91 - 0.96]"],["","Anteroposterior Diameter","0.92 [0.90 - 0.94]"],["","Mediolateral Diameter","0.86 [0.83 - 0.88]"]],"caption_candidate":"The device successfully passed the primary ICC acceptance criteria across all structures.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p10-t1","doc_id":"K242607","page_num":10,"bbox":[43.13,511.07,552.3,629.5],"n_rows":8,"n_cols":2,"columns":["Table 8: Mean DICE scores for lumbar vertebrae, discs, neuroforamina and the thecal sac.",""],"rows":[["Table 8: Mean DICE scores for lumbar vertebrae, discs, neuroforamina and the thecal sac.",""],["","Measurement"],["",""],["","DICE [95% CI]"],["Vertebra","0.95 [0.95 - 0.96]"],["Neuroforamen","0.86 [0.85 - 0.86]"],["Intervertebral Disc","0.89 [0.89 - 0.90]"],["Thecal Sac","0.89 [0.89 - 0.90]"]],"caption_candidate":"The device successfully passes the secondary DICE acceptance criteria across all structures.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p10-t2","doc_id":"K242607","page_num":10,"bbox":[43.13,698.9,552.3,760.08],"n_rows":4,"n_cols":3,"columns":["Table 9: Mean absolute error (MAE) of measurements (heights, diameters and areas) for lumbar","",""],"rows":[["Table 9: Mean absolute error (MAE) of measurements (heights, diameters and areas) for lumbar","",""],["vertebrae, discs, neuroforamina and the thecal sac.","",""],["Body Region","Measurement","MAE"],["Vertebra","Anterior Height [mm]","1.17"]],"caption_candidate":"The device successfully passes the co-secondary MAE acceptance criteria across all structures.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242607-p11-t0","doc_id":"K242607","page_num":11,"bbox":[42.96,81.14,552.48,195.98],"n_rows":7,"n_cols":3,"columns":["","Middle Height [mm]","0.86"],"rows":[["","Middle Height [mm]","0.86"],["","Posterior Height [mm]","0.79"],["Intervertebral Disc","Anterior Height [mm]","1.1"],["","Middle Height [mm]","1.19"],["","Posterior Height [mm]","0.96"],["Thecal Sac","Anteroposterior Diameter [mm]","0.81"],["","Mediolateral Diameter [mm]","1.26"]],"caption_candidate":"Page 7 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242624-p13-t0","doc_id":"K242624","page_num":13,"bbox":[92.6,433.15,750.2,518.91],"n_rows":5,"n_cols":9,"columns":["Application","Function name","","Proposed device","","","Predicate Device","","Remark"],"rows":[["Application","Function name","","Proposed device","","","Predicate Device","","Remark"],["","","","uOmnispace.CT","","","uOmnispace.CT (K233209)","",""],["Lung Density Analysis","Lung Segmentation","Yes","","","Yes","","","Functional Substantially\nEquivalent (Note 1)"],["","Lung Density Analysis","Yes","","","Yes","","","Same"],["","Lung Contour Editing","Yes","","","Yes","","","Same"]],"caption_candidate":"body parts.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242624-p14-t0","doc_id":"K242624","page_num":14,"bbox":[92.59,81.06,750.22,210.3],"n_rows":8,"n_cols":9,"columns":["Application","Function name","","Proposed device","","","Predicate Device","","Remark"],"rows":[["Application","Function name","","Proposed device","","","Predicate Device","","Remark"],["","","","uOmnispace.CT","","","uOmnispace.CT (K233209)","",""],["","Pulmonary lobes Segmentation","Yes","","","Yes","","","Same"],["","Airway Segmentation","Yes","","","Yes","","","Functional Substantially\nEquivalent (Note 1)"],["","Airway Tree Extraction and Editing","Yes","","","Yes","","","Same"],["","Airway Contour Editing","Yes","","","Yes","","","Same"],["","Statistical Analysis","Yes","","","Yes","","","Same"],["","Save, Report, Print","Yes","","","Yes","","","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K242624-p30-t1","doc_id":"K242624","page_num":30,"bbox":[105.5,208.94,524.72,422.7],"n_rows":12,"n_cols":6,"columns":["","","Liver","Hepatic artery","Hepatic portal","Hepatic vein"],"rows":[["","","Liver","Hepatic artery","Hepatic portal","Hepatic vein"],["Subgroup","Distribution","segmentati","segmentation","vein segmentation","segmentation"],["","","on","","",""],["Sex","F","0.981","0.928","0.932","0.924"],["","M","0.98","0.926","0.93","0.918"],["","unknown","0.981","0.926","0.936","0.91"],["Age","[12,22)","0.978","0.921","0.925","0.906"],["","[22,60)","0.982","0.93","0.934","0.929"],["",">=60","0.98","0.926","0.933","0.928"],["","unknown","0.981","0.926","0.936","0.91"],["Anatomical\nvariation","With anatomical\nvariation","0.981","0.927","0.933","0.915"],["","Without\nanatomical\nvariation","0.98","0.925","0.932","0.919"]],"caption_candidate":"generality across different subgroups:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242652-p5-t0","doc_id":"K242652","page_num":5,"bbox":[56.66,239.52,554.5,515.52],"n_rows":4,"n_cols":2,"columns":["ApplicantInformation","LunitInc.\n4-8F,374,Gangnam-daero,Gangnam-gu,\nSeoul,06241,RepublicofKorea\nTel:+82-2-2138-0827\nFAX:+82-2-6919-2702"],"rows":[["ApplicantInformation","LunitInc.\n4-8F,374,Gangnam-daero,Gangnam-gu,\nSeoul,06241,RepublicofKorea\nTel:+82-2-2138-0827\nFAX:+82-2-6919-2702"],["PrimaryCorrespondent","SuhyoungBahk\nSr.RegulatoryAffairsSpecialist\nEmail:sbahk@lunit.io"],["SecondaryCorrespondent(s)","HyungtakHarryHan\nSr.RegulatoryAffairsSpecialist\nEmail:hhan@lunit.io\nSuminChung\nSr.RegulatoryAffairsSpecialist\nEmail:sumin.chung@lunit.io"],["DatePrepared","Aug30,2024"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242652-p5-t1","doc_id":"K242652","page_num":5,"bbox":[56.66,583.61,554.5,701.86],"n_rows":5,"n_cols":2,"columns":["NameofDevice","LunitINSIGHTDBTv1.1"],"rows":[["NameofDevice","LunitINSIGHTDBTv1.1"],["ClassificationName","Radiological Computer Assisted Detection/Diagnosis Software For Suspicious\nLesionsForCancer"],["Regulation","21CFR892.2090"],["RegulatoryClass","ClassII"],["ProductCode","QDQ"]],"caption_candidate":"SubjectDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242652-p6-t0","doc_id":"K242652","page_num":6,"bbox":[56.67,156.38,555.5,320.88],"n_rows":7,"n_cols":2,"columns":["NameofDevice","LunitINSIGHTDBT(v1.0)"],"rows":[["NameofDevice","LunitINSIGHTDBT(v1.0)"],["510(k)number","K231470"],["Manufacturer","LunitInc."],["ClassificationName","Radiological Computer Assisted Detection/Diagnosis Software For Suspicious\nLesionsForCancer"],["Regulation","21CFR892.2090"],["RegulatoryClass","ClassII"],["ProductCode","QDQ"]],"caption_candidate":"PredicateDevice","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242652-p7-t0","doc_id":"K242652","page_num":7,"bbox":[56.68,178.69,556.3,706.25],"n_rows":11,"n_cols":3,"columns":["Item","ModifiedDevice","UnmodifiedDevice"],"rows":[["Item","ModifiedDevice","UnmodifiedDevice"],["","LunitINSIGHTDBTv1.1","LunitINSIGHTDBT(v1.0)"],["ClassificationName","RadiologicalComputerAssisted\nDetection/DiagnosisSoftwareForSuspicious\nLesionsForCancer","RadiologicalComputerAssisted\nDetection/DiagnosisSoftwareForSuspicious\nLesionsForCancer"],["Regulation","21CFR892.2090","21CFR892.2090"],["RegulatoryClass","ClassII","ClassII"],["ProductCode","QDQ","QDQ"],["IndicationforUse","LunitINSIGHTDBTisacomputer-assisted\ndetectionanddiagnosis(CADe/x)software\nintendedtobeusedconcurrentlyby\ninterpretingphysicianstoaidinthedetection\nandcharacterizationofsuspectedlesionsfor\nbreastcancerindigitalbreasttomosynthesis\n(DBT)examsfromcompatibleDBTsystems.\nThroughtheanalysis,theregionsofsoft\ntissuelesionsandcalcificationsaremarked\nwithanabnormalityscoreindicatingthe\nlikelihoodofthepresenceofmalignancyfor\neachlesion.LunitINSIGHTDBTusesscreening\nmammogramsofthefemalepopulation.\nLunitINSIGHTDBTisnotintendedasa\nreplacementforacompleteinterpreting\nphysician’sreviewortheirclinicaljudgment\nthattakesintoaccountotherrelevant\ninformationfromtheimageorpatienthistory.","LunitINSIGHTDBTisacomputer-assisted\ndetectionanddiagnosis(CADe/x)software\nintendedtobeusedconcurrentlyby\ninterpretingphysicianstoaidinthedetection\nandcharacterizationofsuspectedlesionsfor\nbreastcancerindigitalbreasttomosynthesis\n(DBT)examsfromcompatibleDBTsystems.\nThroughtheanalysis,theregionsofsoft\ntissuelesionsandcalcificationsaremarked\nwithanabnormalityscoreindicatingthe\nlikelihoodofthepresenceofmalignancyfor\neachlesion.LunitINSIGHTDBTusesscreening\nmammogramsofthefemalepopulation.\nLunitINSIGHTDBTisnotintendedasa\nreplacementforacompleteinterpreting\nphysician’sreviewortheirclinicaljudgment\nthattakesintoaccountotherrelevant\ninformationfromtheimageorpatienthistory."],["Targetpatient\npopulation","Womenundergoingmammography","Womenundergoingmammography"],["Intendeduser","Physiciansinterpretingscreening\nmammograms","Physiciansinterpretingscreening\nmammograms"],["InputImageSource","DBT","DBT"],["Fundamental\nTechnologicalBasis","LunitINSIGHTDBTispoweredbyartificial\nintelligence/machinelearning-basedsoftware\nalgorithm","LunitINSIGHTDBTispoweredbyartificial\nintelligence/machinelearning-basedsoftware\nalgorithm"]],"caption_candidate":"5. SummaryofSubstantialEquivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p7-t0","doc_id":"K242683","page_num":7,"bbox":[85.23,186.83,509.97,769.2],"n_rows":11,"n_cols":10,"columns":["Feature","","","Proposed device:","","","Predicate device:","","Comments",""],"rows":[["Feature","","","Proposed device:","","","Predicate device:","","Comments",""],["","","","QP-Prostate® CAD","","","ProstatIDTM (K212783)","","",""],["","REGULATORY DATA","","","","","","","",""],["Class","","II","","","II","","","N/A",""],["Regulation name","","Radiological Computer\nAssisted\nDetection/Diagnosis\nSoftware","","","Radiological Computer\nAssisted\nDetection/Diagnosis\nSoftware","","","N/A",""],["Regulation number","","21 CFR 892.2090","","","21 CFR 892.2090","","","N/A",""],["Classification Panel","","Radiology","","","Radiology","","","N/A",""],["Product Code","","QDQ","","","QDQ","","","N/A",""],["Applicant","","Quibim S.L.","","","ScanMed, LLC.","","","N/A",""],["","Indications for Use","","","","","","","",""],["Medical device\ndescription","","QP-Prostate® CAD is a\nComputed Aided\nDetection and\nDiagnosis\n(CADe/CADx) image\nprocessing software\nthat automatically\ndetects and identifies\nsuspected lesions in the\nprostate gland based\non bi-parametric\nprostate MRI. The\nsoftware is intended to\nbe used as a\nconcurrent read by\nclinicians with proper\ntraining in a clinical\nsetting as an aid for\ninterpreting prostate\nMRI studies. The\nresults can be\ndisplayed in a variety of\nDICOM outputs,\nincluding identified\nsuspected regions of\nabnormalities marked\nas an overlay onto\nsource MR images. The\noutput can be displayed\non third-party DICOM\nworkstations and\nPicture Archive and\nCommunication\nSystems (PACS).\nPatient management","","","ProstatIDTM is a\nradiological computer\nassisted detection\n(CADe) and diagnostic\n(CADx) software device\nfor use in a healthcare\nfacility or hospital to\nassist trained\nradiologists in the\ndetection, assessment,\nand characterization of\nprostate abnormalities,\nincluding cancer lesions\nusing MR image data\nwith the following\nindications for use.\nProstatID analyzes T2W,\nDWI and ADC MRI data.\nProstatID does not\ninclude DCE images in\nits analysis.\nProstatID software is\nintended for use as a\nconcurrent reading aid\nfor physicians\ninterpreting\nprostate MRI exams of\npatients presented for\nhigh-risk screening or\ndiagnostic imaging, from\ncompatible MRI\nsystems, to identify\nregions suspicious for\nprostate cancer and\nassess their likelihood of\nmalignancy.\nOutputs of the device\ninclude the volume of the\nprostate and locations,\nas well as the extent of\nsuspect lesions, with","","","Substantially\nequivalent. Minor\ndifferences in outputs,\nexist, but both devices\nare CADe/x devices\nthat characterize\nprostate abnormalities\non MR image data.\nThe differences do not\nraise different\nquestions of safety\nand effectiveness.",""]],"caption_candidate":"predicate device ProstatIDTM (Bot Image, Inc.)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p8-t0","doc_id":"K242683","page_num":8,"bbox":[85.23,71.15,509.97,724.08],"n_rows":4,"n_cols":8,"columns":["Feature","","Proposed device:","","","Predicate device:","","Comments"],"rows":[["Feature","","Proposed device:","","","Predicate device:","","Comments"],["","","QP-Prostate® CAD","","","ProstatIDTM (K212783)","",""],["","decisions should not be\nbased solely on the\nresults of QP-Prostate®\nCAD.","","","index scores indicating\nthe likelihood that cancer\nis present, as well as an\nexam score by way of\nPI-RADS interpretation\nsuggestion. \"Extent of\nsuspect lesions\" refers to\nboth the assessment of\nthe boundary of a\nparticular abnormality,\nas well as identification\nof multiple abnormalities.\nIn cases where multiple\nabnormalities are\npresent, ProstatlD can\nbe used to assess each\nabnormality\nindependently.\nOutputs of this device\nshould be interpreted\nwith all available MR\ndata consistent with\nACR clinical\nrecommendations\n(e.g., dynamic contract\nenhanced images if\navailable) in context of\nPI-RADs v2, and in\nconjunction with bi-\nparametric\nMRI acquired with either\nsurface or endorectal\nMRI accessory coils\nfrom compatible MRI\nsystems. Analysis by\nProstatlD\nis not intended as a\nreplacement for\ninterpreting prostate\nabnormalities using MR\nimage data consistent\nwith clinical\nrecommendations\n(including DCE); nor\nshould patient\nmanagement decisions\nbe made solely on the\nbasis of ProstatlD.","","",""],["Intended user\npopulation","QP-Prostate® CAD is\nintended to be used by\nphysicians with proper\ntraining, including\nradiologists, urologists\nand any physician\nqualified to read and\ninterpret prostate MRI\nconsistent with ACR\nrecommendations in the\ncontext of PI-RADS.","","","Intended users of\nProstatlD are physicians\nqualified to read and\ninterpret prostate MRI\nexams consistent with\nACR recommendations\nin the context of PI-\nRADS v2.","","","Substantially\nequivalent."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p9-t0","doc_id":"K242683","page_num":9,"bbox":[85.23,71.15,509.97,767.52],"n_rows":9,"n_cols":10,"columns":["Feature","","","Proposed device:","","","Predicate device:","","Comments",""],"rows":[["Feature","","","Proposed device:","","","Predicate device:","","Comments",""],["","","","QP-Prostate® CAD","","","ProstatIDTM (K212783)","","",""],["Intended patient\npopulation","","Patients above 40\nyears with prostate MR\nimaging.","","","The device is intended to\nbe used in the\npopulation of biological\nadult males with a\nprostate gland\nundergoing screening or\nclinical MRI exams. This\nincludes biological males\nwith clinical indicators\nsuggestive of possible\nprostate cancer or\nwith family history of\nprostate cancer.","","","Substantially\nequivalent.",""],["","CHARACTERISTICS","","","","","","","",""],["Clinical finding","","Identification of location\nof suspicious lesions,\nwith two suspicion\nlevels of clinically\nsignificant prostate\ncancer, moderate or\nhigh","","","Extent and location of\nidentified suspected\nlesions, assigned to a\nlevel of suspicion (0-1).\nA suggested level of\nsuspicion or overall PI-\nRADS exam score.","","","Substantially\nequivalent. While\nminor differences exist\nin that QP-Prostate\nprovides two suspicion\nlevels, while ProstatID\nassigns a level of\nsuspicion on a scale of\n0-1, the intended use\nof the devices remain\nthe same.\nFurthermore, the\nsafety and\neffectiveness of QP-\nProstate are supported\nthrough performance\nassessments and do\nnot raise different\nquestions of safety\nand effectiveness.",""],["DICOM compatibility","","DICOM-in DICOM-out","","","DICOM-in DICOM-out","","","Same",""],["Input for analysis","","T2W and DWI series,\nDCE is not included for\nanalysis","","","T2W, DWI and ADC MRI\ndata, DCE is not\nincluded for analysis","","","Substantially similar.\nWhile QP-Prostate\ntakes a subset of the\ninput data used in the\npredicate device. This\ndifference does not\nraise different\nquestions of safety\nand effectiveness.",""],["Algorithm methodology","","Neural Networks and\nMachine Learning","","","Random Forest","","","AI-based, safety and\neffectiveness are\nsupported\nthrough performance\nassessments.",""],["Safety","","The software is\nintended to be used as\na concurrent read by\nclinicians with proper\ntraining in a clinical\nsetting as an aid for\ninterpreting prostate\nMRI studies. Patient\nmanagement decisions\nshould not be based\nsolely on the results of\nQP-Prostate® CAD.","","","ProstatID software is\nintended for use as a\nconcurrent reading aid.\nAnalysis by ProstatlD is\nnot intended as a\nreplacement for\ninterpreting prostate\nabnormalities using MR\nimage data consistent\nwith clinical\nrecommendations\n(including DCE); nor","","","Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p10-t0","doc_id":"K242683","page_num":10,"bbox":[85.25,71.15,509.95,153.84],"n_rows":3,"n_cols":8,"columns":["Feature","","Proposed device:","","","Predicate device:","","Comments"],"rows":[["Feature","","Proposed device:","","","Predicate device:","","Comments"],["","","QP-Prostate® CAD","","","ProstatIDTM (K212783)","",""],["","","","","should patient\nmanagement decisions\nbe made solely on the\nbasis of ProstatlD.","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p11-t0","doc_id":"K242683","page_num":11,"bbox":[130.96,443.88,464.16,609.28],"n_rows":11,"n_cols":6,"columns":["","Metric (lesion level)","","","Result",""],"rows":[["","Metric (lesion level)","","","Result",""],["AUC-ROC","AUC-ROC","","0.732\n(95% CI: 0.668-0.791)","",""],["","Sensitivity","","0.677\n(95% CI: 0.593-0.761)","",""],["","(high suspicion marker)","","","",""],["","False Positive Rate per Case","","0.417\n(95% CI: 0.313-0.522)","",""],["","(high suspicion marker, any biopsy source)","","","",""],["","Sensitivity","","0.795\n(95% CI: 0.722-0.861)","",""],["","(high and moderate suspicion markers)","","","",""],["","False Positive Rate per Case","","0.855\n(95% CI: 0.709-0.996)","",""],["","(high and moderate suspicion markers, any","","","",""],["","biopsy source)","","","",""]],"caption_candidate":"Table 2: Summary of the standalone performance testing for QP-Prostate® CAD.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242683-p12-t0","doc_id":"K242683","page_num":12,"bbox":[159.68,357.0,435.81,469.87],"n_rows":4,"n_cols":6,"columns":["","Metric","","","Result",""],"rows":[["","Metric","","","Result",""],["AUC\nunaided","AUC\nunaided","","0.849\n(95% CI: 0.814-0.884)","",""],["AUC\naided","","","0.868\n(95% CI: 0.834-0.902)","",""],["DAUC (AUC - AUC )\naided unaided","","","0.019\n(95% CI: 0.001-0.038)\np-value: 0.039","",""]],"caption_candidate":"CAD.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p5-t0","doc_id":"K242729","page_num":5,"bbox":[72.25,147.25,540.25,396.5],"n_rows":9,"n_cols":2,"columns":["Table 1 : Submitter’s Information",""],"rows":[["Table 1 : Submitter’s Information",""],["Submitter’s Name:","Kurt Sysock"],["Company:","Radformation, Inc."],["Address:","261 Madison Avenue, 9th Floor\nNew York, NY 10016"],["Contact Person:","Alan Nelson\nChief Technology Officer, Radformation"],["Phone:","518-888-5727"],["Fax:","---------"],["Email:","anelson@radformation.com"],["Date of Summary Preparation","09/05/2024"]],"caption_candidate":"5.1. Submitter’s Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p5-t1","doc_id":"K242729","page_num":5,"bbox":[72.25,472.5,540.25,684.5],"n_rows":8,"n_cols":2,"columns":["Table 2 : Device Information",""],"rows":[["Table 2 : Device Information",""],["Trade Name:","AutoContour Model RADAC V4"],["Common Name:","AutoContour, AutoContouring, AutoContour Agent,\nAutoContour Cloud Server"],["Classification Name:","Class II"],["Classification:","Medical image management and processing system"],["Regulation Number:","892.2050"],["Product Code:","QKB"],["Classification Panel:","Radiology"]],"caption_candidate":"5.2. Device Information","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K242729-p26-t0","doc_id":"K242729","page_num":26,"bbox":[52.5,72.25,496.5,698.37],"n_rows":25,"n_cols":8,"columns":["Rib05_L","Medium","0.65","37","0.85","0.14","0.610838085","4.5"],"rows":[["Rib05_L","Medium","0.65","37","0.85","0.14","0.610838085","4.5"],["Rib05_R","Medium","0.65","33","0.88","0.02","0.83649353","4.6"],["Rib06_L","Medium","0.65","40","0.86","0.08","0.724382375","4.5"],["Rib06_R","Medium","0.65","40","0.86","0.12","0.662757125","4.6"],["Rib07_L","Medium","0.65","40","0.85","0.14","0.625797495","4.6"],["Rib07_R","Medium","0.65","40","0.86","0.14","0.624501425","4.7"],["Rib08_L","Medium","0.65","40","0.85","0.14","0.62039746","4.5"],["Rib08_R","Medium","0.65","40","0.85","0.14","0.619059365","4.6"],["Rib09_L","Medium","0.65","40","0.84","0.14","0.608365215","4.7"],["Rib09_R","Medium","0.65","40","0.82","0.20","0.496094935","4.5"],["Rib10_L","Medium","0.65","40","0.82","0.19","0.505475645","4.7"],["Rib10_R","Medium","0.65","40","0.795","0.23","0.41650505","4.8"],["Rib11_L","Medium","0.65","39","0.79","0.19","0.473883335","4.8"],["Rib11_R","Medium","0.65","39","0.79","0.23","0.405756435","4.7"],["Rib12_L","Small","0.5","29","0.77","0.14","0.539397945","4.7"],["Rib12_R","Small","0.5","28","0.81","0.10","0.6521935","4.9"],["SacralPlex_L","Medium","0.65","61","0.71","0.07","0.59617898","4.75"],["SacralPlex_R","Medium","0.65","41","0.73","0.05","0.6399795","4.75"],["V_Brachioceph_L","Medium","0.65","40","0.81","0.15","0.56550252","4.8"],["V_Brachioceph_R","Small","0.5","40","0.86","0.06","0.754842185","4.7"],["V_Jugular_L","Medium","0.65","82","0.77","0.12","0.565053955","4.35"],["V_Jugular_R","Medium","0.65","82","0.78","0.20","0.62129336","4.35"],["V_Venacava_S\n(Update)","Medium","0.65","39","0.91","0.04","0.84602356","4.4"],["Ventricle_L","Medium","0.65","20","0.99","0.004","0.98438629","4.6"],["Ventricle_R","Medium","0.65","20","0.97","0.01","0.953399715","4.7"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p27-t0","doc_id":"K242729","page_num":27,"bbox":[108.0,117.0,529.56,160.2],"n_rows":3,"n_cols":2,"columns":["","primarily of glioblastoma and astrocytoma patients."],"rows":[["","primarily of glioblastoma and astrocytoma patients."],["Images were acquired on either a GE Signa HDxT (3T) or Siemens Skyra (3T) scanner",""],["and",""]],"caption_candidate":"45 testing image sets and were acquired from the Cancer Imaging Archive GLIS-RT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p27-t1","doc_id":"K242729","page_num":27,"bbox":[57.71,251.57,558.07,460.5],"n_rows":13,"n_cols":3,"columns":["Table 7: MR Initial Testing Dataset References","",""],"rows":[["Table 7: MR Initial Testing Dataset References","",""],["ModelGroup","DataSourceID","DataCitation"],["MRBrain","MR-Renown","Shusharina,N.,&Bortfeld,T.(2021).GliomaImageSegmentationfor"],["","","Radiotherapy:RTtargets,barrierstocancerspread,andorgansatrisk[Data"],["","","set].TheCancerImagingArchive.https://doi.org/10.7937/TCIA.T905-ZQ20"],["MRPelvis","Prostate-MRI-U\nS-Biopsy","Natarajan,S.,Priester,A.,Margolis,D.,Huang,J.,&Marks,L.(2020)."],["","","ProstateMRIandUltrasoundWithPathologyandCoordinatesofTracked"],["","","Biopsy(Prostate-MRI-US-Biopsy)[Dataset].TheCancerImagingArchive"],["","","DOI:10.7937/TCIA.2020.A61IOC1A"],["MRPelvis_2","NYP","N/A-Testingdatawassharedby1institution"],["MRPelvis_3","ProstateX","Litjens,G.,Debats,O.,Barentsz,J.,Karssemeijer,N.,&Huisman,H.(2017)."],["","","SPIE-AAPMPROSTATExChallengeData(Version2)[dataset].TheCancer"],["","","ImagingArchive.https://doi.org/10.7937/K9TCIA.2017.MURS5CL"]],"caption_candidate":"open source datasets, and one institution within the United States.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p27-t2","doc_id":"K242729","page_num":27,"bbox":[108.0,560.25,539.03,603.45],"n_rows":3,"n_cols":2,"columns":["","For MR Structure"],"rows":[["","For MR Structure"],["models, a mean training DSC of 0.96+/-0.03 was found for large models, 0.84+/-0.07 for",""],["medium models, 0.74+/- 0.09 for small models.",""]],"caption_candidate":"(NRG/RTOG) guidelines as appropriate by three clinically experienced experts","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p27-t3","doc_id":"K242729","page_num":27,"bbox":[72.17,620.38,483.91,719.5],"n_rows":3,"n_cols":6,"columns":["Table 8: MR Training Data Results for AutoContour Model RADAC V4","","","","",""],"rows":[["Table 8: MR Training Data Results for AutoContour Model RADAC V4","","","","",""],["MRModels","Size","Pass\nCriteria","DSC\n(Avg)","DSCStd\nDev(Avg)","LowerBound\n95%\nConfidence\nInterval"],["A_Pud_Int_L","Small","0.5","0.69","0.08","0.5584"]],"caption_candidate":"medium models, 0.74+/- 0.09 for small models.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p28-t0","doc_id":"K242729","page_num":28,"bbox":[72.25,72.5,484.5,393.5],"n_rows":17,"n_cols":6,"columns":["A_Pud_Int_R","Small","0.5","0.69","0.08","0.5584"],"rows":[["A_Pud_Int_R","Small","0.5","0.69","0.08","0.5584"],["Bladder","Large","0.8","0.92","0.07","0.80485"],["Bladder_Trigone","Small","0.5","0.72","0.05","0.63775"],["Brain","Large","0.8","0.97","0","0.97"],["Colon_Sigmoid","Medium","0.65","0.72","0.18","0.4239"],["External_Pelvis","Large","0.8","0.99","0.01","0.97355"],["Femur_L","Medium","0.65","0.93","0.03","0.88065"],["Femur_R","Medium","0.65","0.93","0.03","0.88065"],["Lens_L","Small","0.5","0.82","0.09","0.67195"],["Lens_R","Small","0.5","0.82","0.09","0.67195"],["NVB_L","Small","0.5","0.61","0.08","0.4784"],["NVB_R","Small","0.5","0.61","0.08","0.4784"],["PenileBulb","Small","0.5","0.79","0.12","0.5926"],["Rectal_Spacer","Medium","0.65","0.84","0.12","0.6426"],["Rectum","Medium","0.65","0.88","0.1","0.7155"],["SpinalCord_Cerv","Small","0.5","0.82","0.06","0.7213"],["Urethra","Medium","0.65","0.68","0.09","0.53195"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p28-t1","doc_id":"K242729","page_num":28,"bbox":[51.07,456.5,574.91,684.69],"n_rows":14,"n_cols":3,"columns":["Table 9: MR External Clinical Dataset References","",""],"rows":[["Table 9: MR External Clinical Dataset References","",""],["ModelGroup","DataSourceID","DataCitation"],["MRBrain","MR-Renown","N/A"],["MRPelvis","GoldAtlasPelvis","Nyholm, Tufve, Stina Svensson, Sebastian Andersson, Joakim Jonsson,\nMaja Sohlin, Christian Gustafsson, Elisabeth Kjellén, et al. 2018. “MR\nand CT Data with Multi Observer Delineations of Organs in the Pelvic"],["","","Maja Sohlin, Christian Gustafsson, Elisabeth Kjellén, et al. 2018. “MR"],["","","and CT Data with Multi Observer Delineations of Organs in the Pelvic"],["","","Area - Part of the Gold Atlas Project.” Medical Physics 12 (10): 3218–21."],["","","doi:10.1002/mp.12748."],["MRPelvis_2","SynthRad","ThummererA,vanderBijlE,GalaponJrA,VerhoeffJJ,LangendijkJA,BothS,"],["","","vandenBergCAT,MasperoM.2023.SynthRAD2023GrandChallengedataset:"],["","","GeneratingsyntheticCTforradiotherapy.MedicalPhysics,50(7),4664-4674."],["","","https://doi.org/10.1002/mp.16529"],["MRLinac\nPelvis","MRLinac","N/A-Testingdatawassharedby2institutionsutilizingMRLinacsforimage"],["","","acquisitions."]],"caption_candidate":"accuracy of the models on image sets acquired that were unique to the training datasets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p29-t0","doc_id":"K242729","page_num":29,"bbox":[108.0,72.0,540.0,314.0],"n_rows":17,"n_cols":6,"columns":["resolution between 0.94 mm, and acquisition parameters of TR=5.98ms, TE=96.8s. Data","","","","",""],"rows":[["resolution between 0.94 mm, and acquisition parameters of TR=5.98ms, TE=96.8s. Data","","","","",""],["for testing of the MR Pelvis structure models were acquired from 2 publicly available","","","","",""],["datasets, which contained images of patients with prostate or rectal cancer, as well as 1","","","","",""],["dataset shared from 2 institutions utilizing an MR Linac.","","","Various scanner models and","",""],["acquisition settings were used.","","","","",""],["DSC values were calculated between ground truth contour data and AutoContour","","","","",""],["structures and rated on the same DSC passing criteria as was used for the training DSC","","","","",""],["validation. All structures passed the minimum DSC criteria for small, medium, and large","","","","",""],["structures with a mean","DSC of 0.61+/-0.14, 0.84+/-0.09, 0.80+/-.09 respectively:","","","",""],["Additionally, the qualitative clinical appropriateness of AutoContour structures generated","","","","",""],["on these scans was graded by clinical experts. Autocontour structures were graded on a","","","","",""],["scale from 1 to 5 where 5 refers to contour requiring no additional edits, and 1 refers to a","","","","",""],["score in which full manual re-contour of the structure would be required. An average","","","","",""],["score >= 3 was used to determine whether a structure model would ultimately be","","","","",""],["beneficial clinically. An average rating of 4.6 was found across all MR structure models","","","","",""],["demonstrating that only minor edits would be required in order to make the structure","","","","",""],["models acceptable for clinical use.","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p29-t1","doc_id":"K242729","page_num":29,"bbox":[55.5,372.25,499.16,735.62],"n_rows":16,"n_cols":8,"columns":["Table 10: MR External Reviewer Results for AutoContour Model RADAC V4","","","","","","",""],"rows":[["Table 10: MR External Reviewer Results for AutoContour Model RADAC V4","","","","","","",""],["MRModels","Size","Pas\ns\nCrite\nria","#\nExternal\nTest\nData\nSets","Average\nDSC","Average\nDSCStd.\nDev","Lower\nBound95%\nConfidence\nInterval","External\nReviewer\nAverage\nRating\n(1-5)"],["A_Pud_Int_L","Small","0.5","45","0.57","0.11","0.39913191","4.9"],["A_Pud_Int_R","Small","0.5","45","0.58","0.10","0.47111123","4.9"],["Bladder","Large","0.8","45","0.93","0.06","0.824646915","4.8"],["Bladder_Trigone","Medium","0.5","45","0.59","0.13","0.379483905","4.6"],["Brain","Large","0.8","20","0.97","0.01","0.959101725","4.6"],["Colon_Sigmoid","Medium","0.65","45","0.74","0.21","0.406063225","4.5"],["External_Pelvis","Large","0.8","6","0.99","0.001","0.98960849","5"],["Femur_L","Medium","0.65","44","0.94","0.02","0.90950333","4.6"],["Femur_R","Medium","0.65","45","0.95","0.01","0.921129565","4.5"],["Glnd_Prostate(Update)","Medium","0.65","45","0.83","0.07","0.71662536","4.8"],["Lens_L","Small","0.5","18","0.72","0.14","0.487633895","4.6"],["Lens_R","Small","0.5","19","0.63","0.21","0.268851055","4.6"],["NVB_L","Small","0.5","45","0.54","0.12","0.34080495","4.2"],["NVB_R","Small","0.5","45","0.50","0.12","0.305008105","4.2"]],"caption_candidate":"models acceptable for clinical use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242729-p30-t0","doc_id":"K242729","page_num":30,"bbox":[55.5,72.25,499.5,203.37],"n_rows":7,"n_cols":8,"columns":["PenileBulb","Small","0.5","45","0.71","0.18","0.40456992","4.8"],"rows":[["PenileBulb","Small","0.5","45","0.71","0.18","0.40456992","4.8"],["Prostate(Update)","Medium","0.65","45","0.86","0.04","0.7887511","4.8"],["Rectal_Spacer","Small","0.5","5","0.51",".22","0.1481","3.9"],["Rectum","Medium","0.65","45","0.84","0.07","0.721510645","4.5"],["SeminalVes(Update)","Medium","0.65","45","0.69","0.16","0.43922276","4.6"],["SpinalCord_Cerv","Small","0.5","18","0.837","0.08","0.704194545","4.6"],["Urethra","Small","0.5","26","0.56","0.13","0.35090269","4.9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p8-t0","doc_id":"K242745","page_num":8,"bbox":[72.3,433.48,539.7,707.22],"n_rows":5,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["Device\nManufacturer","","","Siemens","","","Siemens","",""],["Device Name","","","AI-Rad Companion Organs RT","","","AI-Rad Companion Organs RT","",""],["510(k) Number","","","K242745","","","K232899","",""],["Indications for\nUse","","","AI-Rad Companion Organs RT is\na post-processing software\nintended to automatically contour\nDICOM CT and MR pre-defined\nstructures using deep-learning-\nbased algorithms.\nContours that are generated by AI-\nRad Companion Organs RT may\nbe used as input for clinical\nworkflows including external\nbeam radiation therapy treatment","","","AI-Rad Companion Organs RT is\na post-processing software\nintended to automatically contour\nDICOM CT and MR pre-defined\nstructures using deep-learning-\nbased algorithms.\nContours that are generated by AI-\nRad Companion Organs RT may\nbe used as input for clinical\nworkflows including external\nbeam radiation therapy treatment","",""]],"caption_candidate":"raise different questions of the safety and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p9-t0","doc_id":"K242745","page_num":9,"bbox":[72.24,72.72,539.76,693.66],"n_rows":8,"n_cols":3,"columns":["","planning. AI-Rad Companion\nOrgans RT must be used in\nconjunction with appropriate\nsoftware such as Treatment\nPlanning Systems and Interactive\nContouring applications, to\nreview, edit, and accept contours\ngenerated by AI-Rad Companion\nOrgans RT.\nThe outputs of AI-Rad Companion\nOrgans RT are intended to be used\nby trained medical professionals.\nThe software is not intended to\nautomatically detect or contour\nlesions","planning. AI-Rad Companion\nOrgans RT must be used in\nconjunction with appropriate\nsoftware such as Treatment\nPlanning Systems and Interactive\nContouring applications, to\nreview, edit, and accept contours\ngenerated by AI-Rad Companion\nOrgans RT.\nThe outputs of AI-Rad Companion\nOrgans RT are intended to be used\nby trained medical professionals.\nThe software is not intended to\nautomatically detect or contour\nlesions"],"rows":[["","planning. AI-Rad Companion\nOrgans RT must be used in\nconjunction with appropriate\nsoftware such as Treatment\nPlanning Systems and Interactive\nContouring applications, to\nreview, edit, and accept contours\ngenerated by AI-Rad Companion\nOrgans RT.\nThe outputs of AI-Rad Companion\nOrgans RT are intended to be used\nby trained medical professionals.\nThe software is not intended to\nautomatically detect or contour\nlesions","planning. AI-Rad Companion\nOrgans RT must be used in\nconjunction with appropriate\nsoftware such as Treatment\nPlanning Systems and Interactive\nContouring applications, to\nreview, edit, and accept contours\ngenerated by AI-Rad Companion\nOrgans RT.\nThe outputs of AI-Rad Companion\nOrgans RT are intended to be used\nby trained medical professionals.\nThe software is not intended to\nautomatically detect or contour\nlesions"],["Algorithm","Deep Learning","Deep Learning"],["Segmentation of\nOrgan at Risk in the\nAnatomic Regions","CT: Head & Neck, Thorax,\nAbdomen & Pelvis\nHead & Neck lymph nodes\n(203 OAR)\nMR: Pelvis (9 OAR)","CT: Head & Neck, Thorax,\nAbdomen & Pelvis\nHead & Neck lymph nodes\n(166 OAR)\nMR: Pelvis (9 OAR)"],["Compatible\nModality","CT & MR Images","CT & MR Images"],["Compatible\nScanner Models","No Limitation on scanner model\nfor CT. Siemens Healthineers’\ndata only for MR. DICOM\ncompliance required.","No Limitation on scanner model\nfor CT. Siemens Healthineers’\ndata only for MR. DICOM\ncompliance required."],["Compatible\nTreatment Planning\nSystem","No Limitation on TPS model,\nDICOM compliance required.","No Limitation on TPS model,\nDICOM compliance required."],["Contraindications","Adult use only","Adult use only"],["Target Population","AI-Rad Companion Organs RT is\ndesigned for use only in adult\npopulations.\nAI-Rad Companion Organs RT is\ndesigned for any patient for whom\nrelevant modality scans are\navailable.","AI-Rad Companion Organs RT is\ndesigned for use only in adult\npopulations.\nAI-Rad Companion Organs RT is\ndesigned for any patient for whom\nrelevant modality scans are\navailable."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p10-t0","doc_id":"K242745","page_num":10,"bbox":[72.24,72.72,539.76,709.5],"n_rows":7,"n_cols":3,"columns":["Clinical condition\nthe device is\nintended to\ndiagnose, treat or\nmanage","Limited to patients previously\nselected for Radiation Therapy.","Limited to patients previously\nselected for Radiation Therapy."],"rows":[["Clinical condition\nthe device is\nintended to\ndiagnose, treat or\nmanage","Limited to patients previously\nselected for Radiation Therapy.","Limited to patients previously\nselected for Radiation Therapy."],["Software\nArchitecture","AI-Rad Companion (Engine)\narchitecture enabling the\ndeployment of AI Rad Companion\nOrgans RT using Edge and in the\nCloud. The UI is provided using a\nweb-based interface.","AI-Rad Companion (Engine)\narchitecture enabling the\ndeployment of AI Rad Companion\nOrgans RT using Edge and in the\nCloud. The UI is provided using a\nweb-based interface."],["Deployment\nFeature","Edge & Cloud Deployment","Edge & Cloud Deployment"],["Organ Templates","Creating, editing and deletion of\norgan templates. Customize\npredefined structure database with\nmapping to international\nnomenclature schemes.","Creating, editing and deletion of\norgan templates. Customize\npredefined structure database with\nmapping to international\nnomenclature schemes."],["Automated\nworkflow","AI-Rad Companion Organs RT\nautomatically processes input\nimage data and sends the results as\nDICOM-RT Structure Sets to a\nuser-configurable target node.","AI-Rad Companion Organs RT\nautomatically processes input\nimage data and sends the results as\nDICOM-RT Structure Sets to a\nuser-configurable target node."],["Contour\nvisualization and\nediting feature","AI-Rad Companion Organs RT\nprovides basic result preview of\nautomatic segmentation results,\nand no editing feature of the\nautomatic segmented contour.","AI-Rad Companion Organs RT\nprovides basic result preview of\nautomatic segmentation results,\nand no editing feature of the\nautomatic segmented contour."],["Segmentation\nPerformance","MR: The algorithm is unchanged\nfrom the predicate and is separate\nfrom the CT algorithm therefore\nthe performance is unchanged\nfrom the predicate.\nCT: The target performance was\nvalidated using 579 cases\ndistributed to four cohorts.\nBoth: To objectively evaluate the\ntarget performance, the DICE\ncoefficient, the absolute symmetric\nsurface distance (ASSD) and the\nfail rate was evaluated. The","MR: The target performance was\nvalidated using 66 cases to\nvalidate the overall performance of\nthe MR contouring.\nCT: The target performance was\nvalidated using 414 cases\ndistributed to three cohorts.\nBoth: To objectively evaluate the\ntarget performance, the DICE\ncoefficient, the absolute symmetric\nsurface distance (ASSD) and the\nfail rate was evaluated. The\nsegmentation performance of the"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p11-t0","doc_id":"K242745","page_num":11,"bbox":[72.24,72.72,539.76,324.54],"n_rows":5,"n_cols":3,"columns":["","segmentation performance of the\nsubject was equivalent to the\noverall performance compared to\nthe predicate, reference device and\ncomparable literature & devices.","subject was equivalent to the\noverall performance compared to\nthe predicate, reference device and\ncomparable literature & devices."],"rows":[["","segmentation performance of the\nsubject was equivalent to the\noverall performance compared to\nthe predicate, reference device and\ncomparable literature & devices.","subject was equivalent to the\noverall performance compared to\nthe predicate, reference device and\ncomparable literature & devices."],["User Interface –\nResults Preview\n(Confirmation)","Basic visualization functionality of\noriginal data and generated\ncontours","Basic visualization functionality of\noriginal data and generated\ncontours"],["User Interface\nConfiguration","Configuration UI","Configuration UI"],["Automated\nWorkflow to TPS","Results send to Confirmation UI &\nOptional bypassing of\nConfirmation UI to TPS","Results send to Confirmation UI &\nOptional bypassing of\nConfirmation UI to TPS"],["Human Factors","Design to be used by trained\nclinicians.","Design to be used by trained\nclinicians."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p11-t1","doc_id":"K242745","page_num":11,"bbox":[83.38,585.46,528.57,711.06],"n_rows":5,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-129","General","Medical Devices –\nApplication of usability\nengineering to medical\ndevices","62366-1 Ed\n1.1 2020-06\nCV","","","IEC","",""],["5-125","General","Medical Devices –\napplication of risk","14971:2019-\n12","","","ISO","",""]],"caption_candidate":"FDA recognized Consensus Standards listed in Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p12-t0","doc_id":"K242745","page_num":12,"bbox":[83.34,72.72,528.6,393.66],"n_rows":7,"n_cols":5,"columns":["","","management to medical\ndevices","",""],"rows":[["","","management to medical\ndevices","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle\nprocesses [Including\nAmendment 1 (2016)]","62304 Ed 1.1\n2015-06 CV","AAMI\nANSI\nIEC"],["12-352","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 – 3.20\n2023e","NEMA"],["5-134","General","Medical devices – symbols\nto be used with information\nto be supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","ISO\nIEC"],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","IEC"],["13-122","Software/\nInformatics","Health software and Health\nIT system safety\neffectiveness and security","81001-5-1\nEdition 1.0\n2021-12","IEC"],["5-135","General","Medical devices –\nInformation to be supplied\nby the manufacturer","20417 First\nedition 2021-\n04","ISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p13-t0","doc_id":"K242745","page_num":13,"bbox":[72.29,559.26,539.71,690.96],"n_rows":2,"n_cols":6,"columns":["","Validation Testing Subject","","","Acceptance Criteria",""],"rows":[["","Validation Testing Subject","","","Acceptance Criteria",""],["Organs in Predicate Device","","","• All the organs segmented in the predicate\ndevice are also segmented in the subject\ndevice\n• The average (AVG) Dice score difference\nbetween the subject and predicate device\nis smaller than 3%","",""]],"caption_candidate":"smaller than 3%.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p14-t0","doc_id":"K242745","page_num":14,"bbox":[72.24,157.92,525.83,448.74],"n_rows":8,"n_cols":4,"columns":["","Dice (%)","",""],"rows":[["","Dice (%)","",""],["","Avg","Std","95% CI"],["Head & Neck","76.1","14.3","[75.1, 77.2]"],["Head & Neck lymph\nnodes","69.3","13.9","[68.7, 70.0]"],["Thorax","76.9","15.8","[76.2, 77.6]"],["Abdomen","87.3","10.1","[86.3, 88.2]"],["Pelvis","85.7","9.6","[85.0, 86.5]"],["Cardiac","75.6","15.1","[74.1, 77.1]"]],"caption_candidate":"Table 3: Acceptance Criteria of AIRC Organs RT VA50","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p14-t1","doc_id":"K242745","page_num":14,"bbox":[72.24,478.86,525.83,719.76],"n_rows":16,"n_cols":10,"columns":["Organ Name","NO.","Dice (%)","","","","ASSD (mm)","","",""],"rows":[["Organ Name","NO.","Dice (%)","","","","ASSD (mm)","","",""],["","","AVG","STD","MED","95%CI","AVG","STD","MED","95%CI"],["Left Breast","30","90.4","3.8","91","[89, 91.8]","2.4","2.2","1.8","[1.5, 3.2]"],["Right Breast","30","90.2","3.7","90.8","[88.8, 91.5]","1.9","0.7","1.8","[1.7, 2.2]"],["Bowel Bag","33","95","3.6","96.5","[93.7, 96.3]","1.9","1.5","1.4","[1.4, 2.5]"],["Left Pelvic Bone","30","93.4","1.6","93.8","[92.8, 94]","0.6","0.2","0.5","[0.5, 0.6]"],["Right Pelvic Bone","30","93.9","1.3","94","[93.4, 94.4]","0.5","0.1","0.5","[0.4, 0.6]"],["Pituitary","30","75.8","7.4","77","[73.1, 78.6]","0.7","0.3","0.6","[0.5, 0.8]"],["Sacrum","30","90.7","4","91.9","[89.2, 92.2]","0.8","0.6","0.6","[0.5, 1]"],["Brainstem","30","88.4","2.5","88.8","[87.5, 89.3]","1","0.3","0.9","[0.9, 1.1]"],["Glottis","30","68","8.7","70.9","[64.8, 71.3]","1.2","0.4","1.1","[1.1, 1.4]"],["Supraglottic Larynx","30","80","5.9","81","[77.8, 82.20]","0.8","0.3","0.7","[0.7, 0.9]"],["Esophagus","30","85.6","4.2","86","[84, 87.2]","0.6","0.3","0.6","[0.5, 0.7]"],["Left Lacrimal Gland","30","72.1","7.3","71.3","[69.4, 74.9]","0.8","0.3","0.8","[0.7, 0.9]"],["Right Lacrimal Gland","30","69.9","12.4","73.6","[65.3, 74.6]","0.9","0.7","0.8","[0.7, 1.2]"],["Left Femur Head","30","95.2","1.1","95.2","[94.8, 95.6]","0.5","0.2","0.5","[0.5, 0.6]"]],"caption_candidate":"Table 3: Performance summary of the subject device CT contouring","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p15-t0","doc_id":"K242745","page_num":15,"bbox":[77.64,74.93,507.5,699.95],"n_rows":69,"n_cols":15,"columns":["Right Femur Hea","d","","30","94.9","1.3","","95.1","[94.5,","95.4]","0.6","0.2","0.5","[0.5,","0.6]"],"rows":[["Right Femur Hea","d","","30","94.9","1.3","","95.1","[94.5,","95.4]","0.6","0.2","0.5","[0.5,","0.6]"],["","","","","","","","","","","","","","",""],["Left Humeral Hea","d","","30","94.2","2.1","","94.8","[93.4,","94.9]","0.7","0.3","0.6","[0.6,","0.8]"],["","","","","","","","","","","","","","",""],["Right Humeral H","ead","","30","94.6","3.2","","95.4","[93.4,","95.8]","0.7","0.5","0.5","[0.5,","0.9]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","10L","31","52.9","9.7","","55.1","[49.4,","56.5]","1.2","0.6","1.1","[1, 1.","5]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","10R","31","50.2","9.5","","50.6","[46.7,","53.7]","1.4","0.6","1.2","[1.1,","1.6]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","1L","31","70.7","10","","73","[67, 7","4.4]","2.4","1.2","1.9","[1.9,","2.8]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","1R","31","66","12.8","","67.9","[61.3,","70.7]","2.4","0.9","2.3","[2.1,","2.8]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","2L","31","67.6","7.6","","68.6","[64.8,","70.5]","1.4","0.4","1.3","[1.2,","1.5]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","2R","31","55.5","13.6","","56.9","[50.6,","60.5]","2.3","1.5","2","[1.7,","2.8]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","3A","31","75.6","6.3","","77.6","[73.3,","77.9]","1.6","0.4","1.5","[1.5,","1.8]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","3P","31","65.9","6","","66.5","[63.7,","68.1]","1.6","0.6","1.5","[1.4,","1.8]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","4L","31","65.7","8.4","","67.2","[62.6,","68.8]","1.4","0.7","1.1","[1.1,","1.7]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","4R","31","72.8","8","","74.6","[69.9,","75.7]","1.7","0.7","1.6","[1.4,","1.9]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","5","31","61","14.8","","65.7","[55.5,","66.4]","1.8","0.8","1.6","[1.5,","2.1]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","6","31","58.8","14.8","","62.5","[53.4,","64.2]","2","1.1","1.6","[1.6,","2.4]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","7","31","59","7.6","","61.3","[56.2,","61.8]","1.9","0.8","1.7","[1.6,","2.2]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","8","31","65.8","8","","67.9","[62.9,","68.8]","2","0.9","1.7","[1.7,","2.4]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","9L","31","38.3","21.1","","42.9","[30.6,","46.1]","5.3","4.4","3.7","[3.7,","6.9]"],["","","","","","","","","","","","","","",""],["MEDIASTINAL","LN","9R","29","38.8","15.6","","38.5","[32.9,","44.7]","3.7","2","3.5","[2.9,","4.4]"],["","","","","","","","","","","","","","",""],["able 4: Detail","ed P","erformance ev","aluatio","n of the","new org","a","ns in th","e su","bject dev","ice","","","",""],["","","","","","","","","","","","","","",""],["","","","","","Test","C","ohort","","","","","","",""],["","","","","","","","","","","","","","",""],["","","# Patients","","24","4","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","(Data origin)","","So","uth/Nort","h","Ameri","ca: 1","63","","","","",""],["","","","","","","","","","","","","","",""],["","","","","EU",": 70","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","As","ia: 6","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","Au","stralia:","3","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","Un","known:","2","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","Gender","","F:","111","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","M:","100","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","Un","known:","3","3","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","GE",": 29","","","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","Phi","lips: 33","","","","","","","","",""],["","","Manufacturer","","","","","","","","","","","",""],["","","","","Sie","mens: 1","5","8","","","","","","",""],["","","","","","","","","","","","","","",""],["","","","","Ot","her/Unk","n","own: 2","4","","","","","",""],["","","","","","","","","","","","","","",""],["","","Slice Thicknes","s","<=","1: 10","","","","","","","","",""]],"caption_candidate":"Right Femur Head 30 94.9 1.3 95.1 [94.5, 95.4] 0.6 0.2 0.5 [0.5, 0.6]","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242745-p16-t0","doc_id":"K242745","page_num":16,"bbox":[72.4,166.05,539.6,512.1],"n_rows":13,"n_cols":11,"columns":["Cohort","","A","","","","","","","","B"],"rows":[["Cohort","","A","","","","","","","","B"],["","","A.1","","","A.2","","","A.3","",""],["# Patients","73","","","40","","","301","","","165"],["# Of clinical\nsites\n(Data origin)","3\nGermany: 14\nBrazil: 59","","","4\nCanada: 40","","","12+\nSouth/North America:\n184\nEU: 44","","","20+"],["","","","","","","","","","","South/North\nAmerica: 100"],["","","","","","","","","","","EU: 51"],["","","","","","","","Asia: 33\nAustralia: 28\nUnknown: 12","","","Asia: 6"],["","","","","","","","","","","Australia: 3"],["","","","","","","","","","","Unknown: 5"],["Body Region","Head & Neck: 24\nThorax &\nAbdomen: 20\nPelvis: 29","","","Head & Neck:\n40","","","Head & Neck: 50\nThorax: 81\nAbdomen: 115\nPelvis: 55","","","Head & Neck: 40"],["","","","","","","","","","","Thorax: 69"],["","","","","","","","","","","Abdomen: 25"],["","","","","","","","","","","Pelvis: 31"]],"caption_candidate":"Table 5: Validation Testing Data Information for new OARs","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p16-t1","doc_id":"K242745","page_num":16,"bbox":[72.4,539.34,539.6,710.16],"n_rows":13,"n_cols":9,"columns":["","Organ Group","","","No. of Training","","","No. of Validation",""],"rows":[["","Organ Group","","","No. of Training","","","No. of Validation",""],["Lacrimal Glands Left","","","247","","","62","",""],["Lacrimal Glands Right","","","","","","","",""],["Pituitary Gland","","","247","","","62","",""],["Humeral Head Left","","","207","","","52","",""],["Humeral Head Right","","","","","","","",""],["Bowel Bag","","","544","","","25","",""],["Pelvic Bone Left","","","160","","","40","",""],["Pelvic Bone Right","","","","","","","",""],["Sacrum","","","160","","","40","",""],["Mediastinal LN I Left","","","136","","","34","",""],["Mediastinal LN 1 Right","","","","","","","",""],["Mediastinal LN II Left","","","","","","","",""]],"caption_candidate":"Table 5: Validation Testing Data Information based on Cohort","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242745-p17-t0","doc_id":"K242745","page_num":17,"bbox":[72.24,72.72,539.76,348.36],"n_rows":20,"n_cols":3,"columns":["Mediastinal LN II Right","",""],"rows":[["Mediastinal LN II Right","",""],["Mediastinal LN III Anterior","",""],["Mediastinal LN III Posterior","",""],["Mediastinal LN IV Left","",""],["Mediastinal LN IV Right","",""],["Mediastinal LN V","",""],["Mediastinal LN VI","",""],["Mediastinal LN VII","",""],["Mediastinal LN VIII","",""],["Mediastinal LN IX Left","",""],["Mediastinal LN IX Right","",""],["Mediastinal LN X Left","",""],["Mediastinal LN X Right","",""],["Femoral Head Left","160","40"],["Femoral Head Right","",""],["Brainstem","247","62"],["Esophagus","247","62"],["Breast Left\nBreast Right","172","44"],["Supraglottic Larynx","247","62"],["Glottis","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p7-t0","doc_id":"K242748","page_num":7,"bbox":[72.25,356.82,539.75,703.2],"n_rows":7,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["Device Name","Oncospace","Oncospace","Identical"],["510(k) Owner","Oncospace, Inc.","Oncospace, Inc.",""],["510(k) Number","--","K222803",""],["Product Code","MUJ","MUJ","Identical"],["Product Name","System, Planning, Radiation\nTherapy Treatment","System, Planning, Radiation\nTherapy Treatment","Identical"],["Intended Use","Oncospace is used to configure\nand review radiotherapy treatment\nplans for a patient with malignant\nor benign disease in the head and\nneck, thoracic, abdominal, and\npelvic regions. It allows for set up\nof radiotherapy treatment\nprotocols, association of a\npotential treatment plan with the\nprotocol(s), submission of a dose\nprescription and achievable\ndosimetric goals to a treatment\nplanning system, and review of\nthe treatment plan. It is intended\nfor use by qualified, trained\nradiation therapy professionals\n(such as medical physicists,\noncologists, and dosimetrists).","Oncospace is used to configure\nand review radiotherapy treatment\nplans for a patient with malignant\nor benign disease in the prostate,\nhead, and neck regions. It allows\nfor set up of radiotherapy\ntreatment protocols, association of\na potential treatment plan with the\nprotocol(s), submission of a dose\nprescription and achievable\ndosimetric goals to a treatment\nplanning system, and review of\nthe treatment plan. It is intended\nfor use by qualified, trained\nradiation therapy professionals\n(such as medical physicists,\noncologists, and dosimetrists).\nThis device is for prescription use\nby order of a physician.","Substantially\nEquivalent\nAdded thoracic\nand abdominal\nregions, added\ngynecological\nsites to expand\nthe prostate\nreference to the\npelvic region."]],"caption_candidate":"Note: The subject device algorithms, and any future algorithm updates, are locked prior to clinical use.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p8-t0","doc_id":"K242748","page_num":8,"bbox":[72.25,101.4,539.75,692.88],"n_rows":13,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["","This device is for prescription use\nby order of a physician.","",""],["Operating\nSystem","Windows/Web-browser","Windows/Web-browser","Identical"],["Platform","Client-Server (Clinic-provided\nclient machines, cloud Windows\nservers controlled by Oncospace)","Client-Server (Clinic-provided\nclient machines, cloud Windows\nservers controlled by Oncospace)","Identical"],["DICOM-RT\nCompliant","Yes","Yes","Identical"],["Full Treatment\nPlanning System","No","No","Identical"],["Connected to or\nControlling of\nRadiation\nDelivery Devices","No","No","Identical"],["Typical Users","Medical professionals, including\nbut not limited to, radiation\noncologists, medical physicists or\nphysicians.","Medical professionals, including\nbut not limited to, radiation\noncologists, medical physicists or\nphysicians.","Identical"],["Patient\nPopulation","There are no demographic,\nregional, or cultural limitations\nfor patients. It is up to the user to\ndetermine if the system can be\nused for a patient.","There are no demographic,\nregional, or cultural limitations\nfor patients. It is up to the user to\ndetermine if the system can be\nused for a patient.","Identical"],["Body Regions","Head and neck\nThoracic\nAbdominal\nPelvic\nThe thoracic, abdominal, and\ngynecological regions have been\nadded using the same machine\nlearning methods as in the\npredicate device.","Head and neck\nProstate","New:\nGynecologic,\nthoracic, and\nabdominal organs\nIdentical: Head\nand neck, prostate"],["Environment","The system can be used in a\nhospital environment or in a\ndoctor’s office.","The system can be used in a\nhospital environment or in a\ndoctor’s office.","Identical"],["JPEG image\nsupport","Yes","Yes","Identical"],["Import\nTreatment Plans","Yes. Import existing plans from\nthird-party systems to compare\ndose objectives against templates.","Yes. Import existing plans from\nthird-party systems to compare\ndose objectives against templates.","Identical"]],"caption_candidate":"Page 4 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p9-t0","doc_id":"K242748","page_num":9,"bbox":[72.25,101.4,539.75,656.34],"n_rows":11,"n_cols":4,"columns":["Element","Subject","Predicate","Conclusion"],"rows":[["Element","Subject","Predicate","Conclusion"],["“Template”\nTreatment Plans","Yes. Factory-default plans with\ndose goals exist and users can\nconfigure a dose template.","Yes. Factory-default plans with\ndose goals exist and users can\nconfigure a dose template.","Identical"],["Automatic Initial\nTumor Selection","Yes. Regions of interest are\nmatched as the study is opened in\nthe device. Users can adjust or\nmatch to more available regions\nof interest.","Yes. Regions of interest are\nmatched as the study is opened in\nthe device. Users can adjust or\nmatch to more available regions\nof interest.","Identical"],["Dose Objective\nComparison","Yes. Comparisons can be done\nbetween more than one selected\ntreatment plan. Dose is based on\ncalculated dose and curated, gold-\nstandard treatment plans.","Yes. Comparisons can be done\nbetween more than one selected\ntreatment plan. Dose is based on\ncalculated dose and curated, gold-\nstandard treatment plans.","Identical"],["Image Viewer\nCapabilities","Yes. Display, pan, zoom, scroll,\nwindowing, viewport layout.","Yes. Display, pan, zoom, scroll,\nwindowing, viewport layout.","Identical"],["Calculate and\nDisplay Isodose\nLines","Yes","Yes","Identical"],["Calculate and\nDisplay Dose\nVolume\nHistograms","Yes","Yes","Identical"],["Compare Dose\nfrom Multiple\nPlans","Yes","Yes","Identical"],["Dose\nSummation/\nTreatment-Over-\nTime Data","Yes","Yes","Identical"],["Plan Review","Yes. Contains features for review\nof isodose lines, review of DVHs,\ndose comparison and dose\nsummation.","Yes. Contains features for review\nof isodose lines, review of DVHs,\ndose comparison and dose\nsummation.","Identical"],["Export Plan\nInformation","Yes. Can export the selected plan\nfor review and setup by a\ndosimetrist.\nOncospace does not export a final\nplan, it will not export to a record-\nand-verify system.","Yes. Can export the selected plan\nfor review and setup by a\ndosimetrist.\nOncospace does not export a final\nplan, it will not export to a record-\nand-verify system.","Identical"]],"caption_candidate":"Page 5 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p10-t0","doc_id":"K242748","page_num":10,"bbox":[72.48,455.64,540.48,703.26],"n_rows":2,"n_cols":4,"columns":["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],"rows":[["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],["Head and\nNeck","1145 treatment plans for patients\nwho received radiation therapy for\nHNC at Johns Hopkins University\nbetween 2008-2019.\nPlans were required to exhibit 90%\ntarget coverage.\n10% of the plans were single-\ntarget and 90% were SIB (19% 2-\ntarget, 51% 3-target, 20% 4-\ntarget).\n96% of plans had a total\nprescribed dose >= 60 Gy, 4% had\na total prescribed dose < 60 Gy.","Dataset A: 265 patients who\nreceived radiation therapy\nfor HNC at Institution_2.\nPlans were required to\nexhibit 90% target coverage.\n11% of the plans were\nsingle-target and 89% were\nSIB (3% 2-target, 41% 3-\ntarget, 45% 4-target). 98% of\nplans had a total prescribed\ndose >= 60 Gy, 2% had a\ntotal prescribed dose < 60\nGy.","18 patients who received\nradiation therapy for HNC at\nJHU between 2021-2022. This\nincluded plans with 1-4 target\ndose levels, 10 to 48 fractions,\nin a variety of anatomical\nlocations: lip, larynx, base of\ntongue, parotid, nasopharynx,\nscalp, neck, etc. HN was\nclinically validated in a previous\n510k submission."]],"caption_candidate":"medical record such that technique information could not be linked.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p11-t0","doc_id":"K242748","page_num":11,"bbox":[72.48,101.64,540.48,686.1],"n_rows":4,"n_cols":4,"columns":["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],"rows":[["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],["","The dataset contained 35% IMRT,\n27% VMAT, 15% tomotherapy, 2%\n3D conformal, and 22%\nunspecified plans.","Dataset B: 27 patients who\nreceived radiation therapy\nfor HNC at Institution_3.\nPlans were required to\nexhibit 90% target coverage.\nAll plans had 3 targets and\ntotal prescribed dose >= 60\nGy.",""],["Thoracic","1623 treatment plans (1437 lung\nand 186 esophagus) for patients\nwho received radiation therapy for\nthoracic cancer at Johns Hopkins\nUniversity between 2008-2019.\nPlans were required to exhibit 92%\ntarget coverage.\n82% of plans had a total\nprescribed dose >= 45 Gy, 18%\nhad a total prescribed dose < 45\nGy.\n57% of plans had conventional\nfractionation (dose per fraction\n<2.3Gy) and 43% were hypo-\nfractionated plans.","","20 patients (14 lung and 6\nesophagus) who received\nradiation therapy at JHU\nbetween 2021-2024. This\nincluded targets in multiple\nlocations within the lungs and\nesophagus, including single-\ntarget, SIB, and multi-phase\ncourses, treated with\nconventional- and hypo-\nfractionation, and SBRT."],["Abdominal","712 treatment plans for patients\nwho received radiation therapy for\npancreatic cancer at Johns\nHopkins University between 2008-\n2019, and 69 treatment plans\nfrom patients who received\nradiation therapy for liver cancer\nat Montefiore Einstein\nComprehensive Cancer Center.\nPlans were required to exhibit 85%\ntarget coverage.\n3% of plans had conventional\nfractionation (dose per fraction","","17 patients (11 pancreas and 6\nliver) who received radiation\ntherapy for at JHU between\n2021-2024. This included\nsingle-target and SIB courses,\ntreated with conventional- and\nhypo-fractionation and SBRT."]],"caption_candidate":"Page 7 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242748-p12-t0","doc_id":"K242748","page_num":12,"bbox":[72.48,101.64,540.48,468.54],"n_rows":3,"n_cols":4,"columns":["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],"rows":[["Anatomical\nLocation","Development (Training/Tuning)\nand Internal Performance Testing\nDataset (randomly split 80/20)","External Performance Test\nDataset(s)","Clinical Validation Dataset"],["","<2.3Gy) and 97% were hypo-\nfractionated plans.","",""],["Pelvis","1785 treatment plans (1662\nprostate and 123 gynecological)\nfor patients who received\nradiation therapy for pelvic cancer\nat Johns Hopkins University\nbetween 2008-2019.\nPlans were required to exhibit 94%\ntarget coverage.\n98% of plans had conventional\nfractionation (dose per fraction\n<2.3Gy) and 2% were hypo-\nfractionated plans.\n37% of plans had at least one\nphase with a nodal PTV, and 63%\ndid not.\nThe Prostate dataset used in the\nPelvis model contained 15% IMRT,\n46% VMAT, 14% tomotherapy,\nand 25% unspecified plans.","40 patients who received\nradiation therapy for\nprostate cancer at\nInstitution_3. Plans were\nrequired to exhibit 94%\ntarget coverage. All plans\nhad conventional\nfractionation.","17 patients (12 prostate and 5\ngynecological) who received\nradiation therapy at JHU\nbetween 2021-2024. This\nincluded single-target and SIB\ncourses, treated with\nconventional- and hypo-\nfractionation and SBRT.\nProstate was clinically validated\nin previous 510k submission."]],"caption_candidate":"Page 8 of 10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242781-p8-t0","doc_id":"K242781","page_num":8,"bbox":[33.25,122.82,578.75,708.84],"n_rows":14,"n_cols":9,"columns":["","Measurement [units]","","","Description","","","Application",""],"rows":[["","Measurement [units]","","","Description","","","Application",""],["Distance [mm]","","","Length between two points, for both\ncurved lines (splines) and straight lines,\nincluding the diameter (including min,\nmax, average) resulting from closed\nsplines and depth","","","Diameter & depth of cardiovascular\nstructures of interest","",""],["Perimeter [mm]","","","The perimeter of a contour (closed spline)","","","Perimeter of cardiovascular structures of\ninterest","",""],["Area [cm2]","","","The area within contour(s)","","","Area of cardiovascular structures of interest","",""],["Signal intensity [HU]\n(modality CT) / Intensity\n[unitless] (modality MR)","","","Modality CT: Hounsfield value (in\nHounsfield Units, HU) of the underlying\npixels\nModality MR: Intensity / shade of grey\n(high, intermediate, low) of underlying\npixels","","","Intensity of pixels in cardiovascular\nstructures of interest","",""],["Volume [mm3 or mL]","","","The volume within contour(s)","","","Volume of cardiovascular structures of\ninterest","",""],["Coordinates [mm, mm, mm]","","","Location in the x-, y-, and z-planes of a\npoint","","","Coordinates of points of interest on a 3D\nrendering, for export purposes","",""],["Mass [g]","","","The mass within contour(s)","","","Mass of cardiovascular structures of interest","",""],["Displacement [mm or\ndegree]","","","The displacement vector represents the\nposition of a point with respect to the\nposition of that point in the reference (end\ndiastole) phase.","","","Strain within cardiovascular structures of\ninterest (e.g., myocardium)","",""],["Agatston Score [HU]","","","Industry-standard measure for coronary\ncalcium based on volume and intensity of\ncalcified plaque","","","For assessing overall calcified plaque\nburden in coronary arteries.","",""],["Angle [degrees]","","","The angle of an object/structure of\ninterest","","","Angle between two lines of interest","",""],["Stenosis [%]","","","The narrowing of a vessel in area or\ndiameter compared to a normal reference\nlocation","","","For measuring an abnormal narrowing in an\nartery","",""],["Velocity [mL/min or cm/s]","","","The velocity of moving objects within\ncontour(s)","","","Velocity within cardiovascular structures of\ninterest (e.g., blood flow)","",""],["Strain [%]","","","Strain is a measure of the deformation in\nshape and dimension of the heart muscle\nduring the cardiac cycle.","","","Strain within cardiovascular structures of\ninterest (e.g., myocardium)","",""]],"caption_candidate":"Table 1. Measurements in cvi42.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242781-p9-t0","doc_id":"K242781","page_num":9,"bbox":[33.24,101.04,578.76,711.84],"n_rows":12,"n_cols":3,"columns":["Strain Rate [1/s]","Derivative of strain with respect to time","Strain within cardiovascular structures of\ninterest, as above"],"rows":[["Strain Rate [1/s]","Derivative of strain with respect to time","Strain within cardiovascular structures of\ninterest, as above"],["Time to Peak [ms]","Trigger time elapsed from the first phase\ntill the phase where the peak strain has\nbeen reached.","Strain within cardiovascular structures of\ninterest, as above"],["Torsion [degree/cm]","The difference in rotation between the\napical and basal slices divided by the\napical and basal slices. Note\ncircumferential displacement represents\nan angle.","Strain within cardiovascular structures of\ninterest, as above"],["End Diastolic Volume [mL]","LV/RV cavity volume at the phase\ndefined as the ED","Calculated clinical data for LV/RV"],["End Systolic Volume [mL]","LV/RV cavity volume at the phase\ndefined as the ES","Calculated clinical data for LV/RV"],["Stroke Volume [mL]","Stroke volume is the volume of blood\npumped out of the LV/RV during each\ncardiac contraction and is represented by\nthe difference of EDV and ESV.","Calculated clinical data for LV/RV"],["Ejection Fraction [%]","Ejection fraction is measured as a\npercentage of the total amount of blood in\nLV/RV that is pumped out with each\ncardiac cycle. It is calculated by dividing\nthe SV by EDV.","Calculated clinical data for LV/RV"],["Cardiac Output [L/min]","Cardiac output is the amount of blood\npumped by the heart in a minute and is\ncalculated by multiplying the SV with\nheart rate per minute.","Calculated clinical data for LV/RV"],["Cardiac Index [L/min/m2]","Cardiac index is a hemodynamic\nparameter that relates the CO from LV in\none minute to BSA and is obtained by\ndividing the CO by BSA.","Calculated clinical data for LV"],["End Diastolic Mass [g]","LV myocardial mass at the phase defined\nas the ED and is calculated by multiplying\nthe myocardial volume in ED phase with\nmyocardial density (1.05 g/ml).","Calculated clinical data for LV"],["End Systolic Mass [g]","LV myocardial mass at the phase defined\nas the ES and is calculated by multiplying\nthe myocardial volume in ES phase with\nmyocardial density (1.05 g/ml).","Calculated clinical data for LV"],["Body Surface Area [m2]","The total surface area of the body","Surface area of the patient body used in\nmedical indicators or assessments"]],"caption_candidate":"cvi42 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242781-p12-t0","doc_id":"K242781","page_num":12,"bbox":[9.44,113.07,998.6,427.76],"n_rows":31,"n_cols":4,"columns":["","","Subject Device",""],"rows":[["","","Subject Device",""],["","","cvi42 Software Application (K242781)",""],["","","Manufactured by Circle",""],["Intended Use","","cvi42 is intended to be used by qualified medical professionals for viewing, post-processing and quantitative evaluation of cardiovascular magnetic resonance (MR) images and cardiovascular computed tomography (CT) images in a Digital Imaging",""],["","","and Communications in Medicine Standard format, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process",""],["Indications for Use","","cvi42 is intended to be used for viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine",""],["","","(DICOM) Standard format.",""],["","","",""],["","","It enables:",""],["","","• Importing cardiac MR & CT Images in DICOM format.",""],["","","• Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including",""],["","","multiplanar reconstructions of the images.",""],["","","• Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass.",""],["","","• Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images.",""],["","","• Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis).",""],["","","• Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion).",""],["","","• Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and",""],["","","quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves.",""],["","","• Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume",""],["","","rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation,",""],["","","stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the physician in confirming the presence or absence of physician identified lesion in blood",""],["","","vessels and evaluation, documentation and follow up of any such lesions.",""],["","","",""],["","","cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process.",""],["","","cvi42 is a software application that can be used as a stand-alone product or in a networked environment.",""],["","","",""],["","","The target population for cvi42 and its manual workflows is not restricted; however, cvi42’s semi-automated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image",""],["","","acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.",""],["","","",""],["","","cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner.",""],["","","",""]],"caption_candidate":"Table 2. Subject Device Intended Use / Indications for Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242781-p13-t0","doc_id":"K242781","page_num":13,"bbox":[9.44,113.07,998.6,537.5],"n_rows":46,"n_cols":19,"columns":["","","Primary Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate",""],"rows":[["","","Primary Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate",""],["","","cmr42 (K082628)","","","ct42 (K111373)","","","cvi42 (K141480)","","","cvi42 Auto (K213998)","","","Strain (K232661)","","","CT Function (K241038)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["Intended Use","Viewing, post-processing,\nqualitative and quantitative\nevaluation of cardiovascular MR\nimages in DICOM format.","Viewing, post-processing,","","Viewing, post-processing, qualitative\nand quantitative evaluation of\ncardiovascular CT images in DICOM\nformat.","Viewing, post-processing, qualitative","","Viewing, post-processing, qualitative\nand quantitative evaluation of blood\nvessels and cardiovascular MR and\nCT images in DICOM format.","Viewing, post-processing, qualitative","","Viewing, post-processing, qualitative\nand quantitative evaluation of blood\nvessels and cardiovascular MR and\nCT images in DICOM format.","Viewing, post-processing, qualitative","","","The Myocardial Strain Software","","The Cardiac CT Function Software\nApplication is intended for qualitative\nand quantitative evaluation of\ncardiovascular CT images in a DICOM\nStandard format, to calculate and\ndisplay cardiac function metrics (e.g.,\nend diastolic volume, end systolic\nvolume, stroke volume, ejection fraction,\ncardiac output, cardiac index, and LV\nmyocardial mass).","The Cardiac CT Function Software",""],["","","qualitative and quantitative","","","and quantitative evaluation of","","","and quantitative evaluation of blood","","","and quantitative evaluation of blood","","","Application is intended for qualitative","","","Application is intended for qualitative",""],["","","evaluation of cardiovascular MR","","","cardiovascular CT images in DICOM","","","vessels and cardiovascular MR and","","","vessels and cardiovascular MR and","","","and quantitative evaluation of","","","and quantitative evaluation of",""],["","","images in DICOM format.","","","format.","","","CT images in DICOM format.","","","CT images in DICOM format.","","","cardiovascular MR images in a","","","cardiovascular CT images in a DICOM",""],["","","","","","","","","","","","","","","DICOM Standard format. As","","","Standard format, to calculate and",""],["","","","","","","","","","","","","","","perquisite, the user confirms","","","display cardiac function metrics (e.g.,",""],["","","","","","","","","","","","","","","endocardial and epicardial contours in","","","end diastolic volume, end systolic",""],["","","","","","","","","","","","","","","a reference phase, and the software","","","volume, stroke volume, ejection fraction,",""],["","","","","","","","","","","","","","","tracks features over the cardiac cycle","","","cardiac output, cardiac index, and LV",""],["","","","","","","","","","","","","","","and computed 2D myocardial","","","myocardial mass).",""],["","","","","","","","","","","","","","","deformation and movement (e.g.,","","","",""],["","","","","","","","","","","","","","","strain, displacement, velocity).","","","",""],["Indications for Use","","cmr42 is intended to be used for","","ct42 is intended to be used for viewing,\npost-processing and quantitative\nevaluation of cardiovascular computed\ntomography (CT) images in a Digital\nImaging and Communications in\nMedicine (DICOM) Standard format.\nIt enables:\n• Importing Cardiac CT Images in\nDICOM format\n• Supporting clinical diagnostics by\nqualitative analysis of the cardiac CT\nimages using display functionality\nsuch as panning, windowing,\nzooming, navigation through\nseries/slices and phases, 3D\nreconstruction of images including\nmulti-lanner reconstructions of the\nimages.\n• Supporting clinical diagnostics by\nquantitative measurement of the heart\nand adjacent vessels in cardiac CT\nimages, specifically distance, area,\nvolume and mass\n• Supporting clinical diagnostics by\nusing area and volume measurements\nfor measuring LV function and derived\nparameters cardiac output and cardiac\nindex in long axis and short axis\ncardiac CT images.","","","","cvi42 vascular analysis add-on is an","","","cvi42 Auto is intended to be used for","","The Myocardial Strain Software\nApplication is intended for qualitative\nand quantitative evaluation of\ncardiovascular magnetic resonance\n(CMR) images. It provides\nmeasurements of 2D LV myocardial\nfunction (displacement, velocity,\nstrain, strain rate, time to peak, and\ntorsion); these measurements are\nused by qualified medical\nprofessionals, experiences in\nexamining and evaluating CMR\nimages, for the purpose of obtaining\ndiagnostic information for patients with\nsuspected heart disease as part of a\ncomprehensive diagnostic decision-\nmaking process.","The Myocardial Strain Software","","The Cardiac CT Function Software\nApplication is indicated to be use with\nmulti-phase, multi-slice cardiovascular\nCT angiography images to assist\nqualified medical professionals in\nassessing and evaluating cardiac\nfunction. CT Function includes manual\nand semi-automatic heart segmentation\nof 2 chambers (LV and RV) and\ncalculation of cardiac function metrics\nincluding end diastolic volume, end\nsystolic volume, stroke volume, ejection\nfraction, cardiac output, cardiac index,\nand LV myocardial mass.","",""],["","","viewing, post-processing and","","","","","","image analysis software package add-","","","viewing, post-processing, qualitative","","","Application is intended for qualitative","","","",""],["","","quantitative evaluation of","","","","","","on for evaluating CT and MR images","","","and quantitative evaluation of","","","and quantitative evaluation of","","","",""],["","","cardiovascular magnetic resonance","","","","","","of blood vessels. 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{"table_id":"K242781-p14-t0","doc_id":"K242781","page_num":14,"bbox":[9.44,101.16,998.6,423.93],"n_rows":35,"n_cols":19,"columns":["","","Primary Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate",""],"rows":[["","","Primary Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate","","","Predicate",""],["","","cmr42 (K082628)","","","ct42 (K111373)","","","cvi42 (K141480)","","","cvi42 Auto (K213998)","","","Strain (K232661)","","","CT Function (K241038)",""],["","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle","","","Manufactured by Circle",""],["","It shall be used by qualified medical\nprofessionals, experienced in\nexamining and evaluating\ncardiovascular MR images, for the\npurpose of obtaining diagnostic\ninformation as part of a\ncomprehensive diagnostic decision-\nmaking process. cmr42 is a 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{"table_id":"K242781-p15-t0","doc_id":"K242781","page_num":15,"bbox":[8.14,113.07,999.86,534.85],"n_rows":45,"n_cols":24,"columns":["Feature","","","","Subject Device","","Primary Predicate\ncmr42 (K082628)\nManufactured by Circle","","","Predicate\nct42 (K111373)\nManufactured by Circle","","","Predicate\ncvi42 (K141480)\nManufactured by Circle","","","Predicate\ncvi42 Auto (K213998)\nManufactured by Circle","","","Predicate\nStrain (K232661)\nManufactured by Circle","","","Predicate\nCT Function (K241038)\nManufactured by Circle","",""],"rows":[["Feature","","","","Subject Device","","Primary Predicate\ncmr42 (K082628)\nManufactured by Circle","","","Predicate\nct42 (K111373)\nManufactured by Circle","","","Predicate\ncvi42 (K141480)\nManufactured by Circle","","","Predicate\ncvi42 Auto (K213998)\nManufactured by Circle","","","Predicate\nStrain (K232661)\nManufactured by Circle","","","Predicate\nCT Function (K241038)\nManufactured by Circle","",""],["","","","","cvi42 Software 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{"table_id":"K242781-p16-t0","doc_id":"K242781","page_num":16,"bbox":[8.14,101.16,999.86,334.41],"n_rows":23,"n_cols":22,"columns":["Feature","","Subject Device","","Primary Predicate\ncmr42 (K082628)\nManufactured by Circle","","","Predicate\nct42 (K111373)\nManufactured by Circle","","","Predicate\ncvi42 (K141480)\nManufactured by Circle","","","Predicate\ncvi42 Auto (K213998)\nManufactured by Circle","","","Predicate\nStrain (K232661)\nManufactured by Circle","","","Predicate\nCT Function (K241038)\nManufactured by Circle","",""],"rows":[["Feature","","Subject Device","","Primary Predicate\ncmr42 (K082628)\nManufactured by Circle","","","Predicate\nct42 (K111373)\nManufactured by Circle","","","Predicate\ncvi42 (K141480)\nManufactured by Circle","","","Predicate\ncvi42 Auto (K213998)\nManufactured by Circle","","","Predicate\nStrain (K232661)\nManufactured by Circle","","","Predicate\nCT Function (K241038)\nManufactured by Circle","",""],["","","cvi42 Software Application","","","","","","","","","","","","","","","","","","",""],["","","(K242781)","","","","","","","","","","","","","","","","","","",""],["","","Manufactured by Circle","","","","","","","","","","","","","","","","","","",""],["","","Cardiac Index (CI)","","","","","","","","","","","","","","","","","","",""],["","","End Diastolic Mass (EDM)","","","","","","","","","","","","","","","","","","",""],["","","End Systolic Mass (ESM)","","","","","","","","","","","","","","","","","","",""],["","","Body Surface Area (BSA)","","","","","","","","","","","","","","","","","","",""],["Quantitative assessment of\ncardiac function","Manual segmentation, and\nsemi-automatic segmentation\nusing Machine Learning\ntechnique of four heart\nchambers in long and short-\naxis views","Manual segmentation, and","","Manual segmentation of four\nheart chambers in long and\nshort-axis views","","","Manual segmentation, and\nsemi-automatic segmentation\nof four heart chambers in short-\naxis views","","","Manual segmentation, and\nsemi-automatic segmentation\nof four heart chambers in long\nand short-axis views","","","Manual segmentation, and\nsemi-automatic segmentation\nusing Machine Learning\ntechnique of four heart\nchambers in long and short-\naxis views","","","Manual segmentation, 2D\nfunctional analysis of\nmyocardial deformation","","","Semi-automatic determination\nof epicardial and endocardial\ncontours, via segmentation of\nthe LV cavity, LV myocardium,\nand RV cavity and the ED and\nES phases using Machine\nLearning Techniques","",""],["","","semi-automatic segmentation","","","","","","","","","","","","","","","","","","",""],["","","using Machine Learning","","","","","","","","","","","","","","","","","","",""],["","","technique of four heart","","","","","","","","","","","","","","","","","","",""],["","","chambers in long and short-","","","","","","","","","","","","","","","","","","",""],["","","axis views","","","","","","","","","","","","","","","","","","",""],["Assessment of cardiac blood flow","","Quantification of blood flow","","","Quantification of blood flow","","N/A","","","N/A","","","N/A","","","N/A","","","N/A","",""],["","","using MR velocity encoded","","","using MR velocity encoded","","","","","","","","","","","","","","","",""],["","","images.","","","images.","","","","","","","","","","","","","","","",""],["Centerline placement in coronary\nvessels","","Manual and semi-automatic","","Manual","Manual","","Manual and semi-automatic","","","Manual and semi-automatic","","","Manual and semi-automatic\nusing Machine Learning\ntechnique","","","No","","","No","",""],["","","using Machine Learning","","","","","","","","","","","","","","","","","","",""],["","","technique","","","","","","","","","","","","","","","","","","",""],["Calcium Scoring","Yes, using ML methodology","Yes, using ML methodology","","No","","","Yes, using non-ML\nmethodology","","","No","","","Yes, using ML methodology","","","No","","","No","",""],["Workstation operating system","","masOS,","","","macOS,","","","macOS,","","","macOS,","","","macOS,","","","macOS,","","","macOS,",""],["","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows","","","Microsoft Windows",""]],"caption_candidate":"cvi42 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p5-t0","doc_id":"K242800","page_num":5,"bbox":[111.52,397.01,598.32,656.98],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","5000 Compact Series Ultrasound Systems\nAuto Measure"],"rows":[["Proprietary Name","5000 Compact Series Ultrasound Systems\nAuto Measure"],["Common Name","Diagnostic Ultrasound System and Transducers"],["Regulation Description","Classification Description 21 CFR § Product Code\nPrimary\nSystem, imaging, pulsed doppler,\n892.1550 IYN\nultrasonic\nSecondary\nSystem, imaging, pulsed echo,\n892.1560 IYO\nultrasonic\nTransducer, ultrasonic, diagnostic 892.1570 ITX\nAutomated Radiological Image\n892.2050 QIH\nProcessing Software"],["Device Class","Class II"],["Review Panel","Radiology"],["Predicate Device","K222648 5000 Compact Series Diagnostic Ultrasound Systems"],["Reference Device","K211597 Philips Affiniti Series Diagnostic Ultrasound System VM 9.0"]],"caption_candidate":"II. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p5-t1","doc_id":"K242800","page_num":5,"bbox":[251.85,446.95,566.58,565.7],"n_rows":7,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p8-t0","doc_id":"K242800","page_num":8,"bbox":[42.86,155.41,756.54,535.51],"n_rows":13,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["","Abdominal,\nCardiac Adult,\nCardiac Pediatric,\nCarotid,\nCerebral Vascular,\nCephalic (Adult),\nCephalic (Neonatal),\nFetal Echo,\nFetal/Obstetric,\nGynecological,\nIntraoperative (Vascular),\nLung,\nMusculoskeletal (Conventional),\nMusculoskeletal (Superficial),\nOphthalmic,\nPediatric,\nPeripheral Vessel,\nSmall Parts\nTransesophageal (Cardiac),\nTransrectal,\nTransvaginal, and\nUrology.","Abdominal,\nCardiac Adult,\nCardiac Pediatric,\nCarotid,\nCerebral Vascular,\nCephalic (Adult),\nCephalic (Neonatal),\nFetal Echo,\nFetal/Obstetric,\nGynecological,\nIntraoperative (Vascular),\nLung,\nMusculoskeletal (Conventional),\nMusculoskeletal (Superficial),\nOphthalmic,\nPediatric,\nPeripheral Vessel,\nSmall Organ (Breast, Thyroid,\nTesticle),\nTransesophageal (Cardiac),\nTransrectal,\nTransvaginal, and\nUrology.","Abdominal,\nCardiac Adult,\nCardiac Other (Fetal),\nCardiac Pediatric,\nCerebral Vascular,\nCephalic (Adult),\nCephalic (Neonatal),\nFetal/Obstetric,\nGynecological,\nIntraoperative (Vascular),\nIntraoperative (Cardiac),\nMusculoskeletal (Conventional),\nMusculoskeletal (Superficial),\nOther:\nUrology,\nPediatric,\nPeripheral Vessel,\nSmall Organ (Breast, Thyroid,\nTesticle),\nTransesophageal (Cardiac),\nTransrectal,\nTransvaginal,\nLung","Identical to Predicate\nSmall Parts and Small Organs are\nsame. To align with terminology in\nCompact 5000 Systema and User\nManual,\nUpdated to Small Parts"],["Indications","","","",""],["for Use","","","",""],["","","","",""],["","Trained healthcare professionals\nIntended for sonographers,","Trained healthcare professionals\nIntended for sonographers,","Trained healthcare professionals\nIntended for sonographers,","Identical to Predicate"],["Intended","","","",""],["Users","","","",""],["","","","",""]],"caption_candidate":"devices are substantially equivalent to the predicate devices K222648 & Reference Device K211597","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p9-t0","doc_id":"K242800","page_num":9,"bbox":[42.86,67.33,756.57,542.95],"n_rows":26,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["","physicians, and biomedical\nengineers who operate and\nmaintain your product.\nTrained healthcare Professional\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the 5000 Compact Series\nUltrasound Systems.","physicians, and biomedical\nengineers who operate and\nmaintain your product.\nTrained healthcare Professional\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the 5000 Compact Series\nUltrasound Systems.","physicians, and biomedical\nengineers who operate and\nmaintain your product.\nTrained healthcare Professional\nBefore use of the system and user\ninformation, the user must be\nfamiliar with ultrasound techniques.\nSonography training and clinical\nprocedures are not included in the\nUser Manual or with the Affiniti\nSeries Diagnostic Ultrasound\nSystem.",""],["","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical point-\nof-care for diagnosis of patients.","Identical to Predicate"],["Intended User","","","",""],["Environment","","","",""],["","","","",""],["","Class II","Class II","Class II","Identical to Predicate"],["USA FDA","","","",""],["Classification","","","",""],["","","","",""],["","IYN","IYN","IYN","Identical to Predicate"],["Primary","","","",""],["Product Code","","","",""],["","","","",""],["Primary","21 CFR 892.1550","21 CFR 892.1550","21 CFR 892.1550","Identical to Predicate"],["Regulation","","","",""],["Number","","","",""],["","ITX\nIYO\nQIH","ITX\nIYO","ITX\nIYO\nQIH","Identical to Predicate"],["Secondary","","","",""],["Product","","","",""],["Codes","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p10-t0","doc_id":"K242800","page_num":10,"bbox":[42.87,67.33,756.57,526.39],"n_rows":25,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["","System, imaging, pulsed echo,\nultrasonic\nTransducer, ultrasonic,\ndiagnostic\nAutomated Radiological Image\nProcessing Software","System, imaging, pulsed echo,\nultrasonic\nTransducer, ultrasonic,\ndiagnostic\nAutomated Radiological Image\nProcessing Software","System, imaging, pulsed echo,\nultrasonic\nTransducer, ultrasonic, diagnostic\nAutomated Radiological Image\nProcessing Software","Identical to Predicate"],["Secondary","","","",""],["Regulation","","","",""],["Name","","","",""],["","","","",""],["Secondary","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 892.2050","Identical to Predicate"],["Regulation","","","",""],["Number","","","",""],["","VM","VM","VM","Identical to Predicate"],["Software","","","",""],["Platform","","","",""],["","","","",""],["","2","Not available","1","Difference No.1\nThe detectors for a subset of\nmeasurements available with\nthe Auto Measure feature have\nundergone additional training\nsince the original release of\nthe feature on Affiniti Series\nUltrasound SystemVM9.0.\nArchitecture of all detectors,\ntraining procedure and all\nacceptance criteria for the\nadditional training data are\nidentical to Auto Measure\nVersion 1"],["Auto Measure","","","",""],["Software","","","",""],["Version","","","",""],["","","","",""],["","Yes","Yes","Yes","Identical to Predicate"],["Reusable","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p11-t0","doc_id":"K242800","page_num":11,"bbox":[42.86,67.33,756.54,538.15],"n_rows":13,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical to Predicate"],["Duration of","","","",""],["use","","","",""],["","","","",""],["","Auto Measure is an optional\nsoftware feature on the 5000\nCompact Series\nUltrasound System that\nprovides the end user with\nsemiautomated adult\nechocardiography 2D and\nDoppler measurements through\nan AI-algorithm, training via\nmachine-learning techniques. It is\nintended to be used with an Adult\nCardiology Transthoracic\ntransducer and acquisitions that\ninclude an ECG\nThese measurements are\nroutinely collected during a\ntransthoracic ECG, per The\nAmerican Society of Echo\ncardiography (ASE)\nrecommendations\n2D modes include the following:\nIVSd\nLVIDd\nLVPWd\nLVIDs\nAsc Ao Diam\nLVOT Diam\nAo Sinus Diam","The healthcare professional\nperforms 2D and Doppler\nmeasurements during a\ntransthoracic echocardiogram\nby Manually positioning the\ncalipers on the ultrasound’s\nsystem waveform or image.\n2D modes include the following:\nIVSd\nLVIDd\nLVPWd\nLVIDs\nAsc Ao Diam\nLVOT Diam","Auto Measure is an optional\nsoftware feature on the Affiniti\nSeries\nDiagnostic Ultrasound System that\nprovides the end user with\nsemiautomated adult\nechocardiography 2D and Doppler\nmeasurements through an AI-\nalgorithm, training via machine-\nlearning techniques. It is intended\nto be used with an Adult Cardiology\nTransthoracic transducer and\nacquisitions that include an ECG.\nThese measurements are routinely\ncollected during a transthoracic\nECG, per The American Society of\nEcho\ncardiography (ASE)\nrecommendations\n2D modes include the following:\nIVSd\nLVIDd","Difference No.2\nAuto Measure is being included in\nthe subject submission with 5000\nCompact Series Ultrasound\nSystems"],["Application","","","",""],["Description","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p12-t0","doc_id":"K242800","page_num":12,"bbox":[42.86,67.33,756.54,540.3],"n_rows":10,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["","Ao STJ Diam\nRV Base, RV Mid, RV Length\nTV Annulus\nDoppler modes include the\nfollowing:\nMV Peak E Vel, MV Peak A Vel\nMV Inflow (MV Dec Time, MV\nPeak E Vel, MV Peak A Vel)\nLVOT VTI, LVOT Vmax\nAV VTI, AV Vmax\nPV VTI, PV Vmax\nTR Vmax\nLat E’ Vel, Lat A’ Vel\nLat Vel (Lat E’ Vel, Lat A’ Vel)\nMed E’ Vel, Med A’ Vel\nMed Vel (Med E’ Vel, Med A’ Vel)\nRV S Vel","Ao Sinus Diam\nAo STJ Diam\nRV Base, RV Mid, RV Length\nTV Annulus\nDoppler modes include the\nfollowing:\nMV Peak E Vel, MV Peak A Vel\nMV Inflow (MV Dec Time, MV\nPeak E Vel, MV Peak A Vel)\nLVOT VTI, LVOT Vmax\nAV VTI, AV Vmax\nPV VTI, PV Vmax\nTR Vmax\nLat E’ Vel, Lat A’ Vel\nLat Vel (Lat E’ Vel, Lat A’ Vel)\nMed E’ Vel, Med A’ Vel\nMed Vel (Med E’ Vel, Med A’ Vel)\nRV S Vel","LVPWd\nLVIDs\nAsc Ao Diam\nLVOT Diam\nAo Sinus Diam\nAo STJ Diam\nRV Base, RV Mid, RV Length\nTV Annulus\nDoppler modes include the\nfollowing:\nMV Peak E Vel, MV Peak A Vel\nMV Inflow (MV Dec Time, MV\nPeak E Vel, MV Peak A Vel)\nLVOT VTI, LVOT Vmax\nAV VTI, AV Vmax\nPV VTI, PV Vmax\nTR Vmax\nLat E’ Vel, Lat A’ Vel\nLat Vel (Lat E’ Vel, Lat A’ Vel)\nMed E’ Vel, Med A’ Vel\nMed Vel (Med E’ Vel, Med A’ Vel)\nRV S Vel",""],["Compatible","S5-1 and S4-2","S5-1 and S4-2","S5-1 and S4-2 ,x5-1, x5-1c","Identical to Predicate"],["transducers","","","",""],["for Auto","","","",""],["Measure","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p13-t0","doc_id":"K242800","page_num":13,"bbox":[42.86,67.33,756.54,386.33],"n_rows":12,"n_cols":5,"columns":["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],"rows":[["","5000 Compact Series","5000 Compact Series","Affiniti Diagnostic Ultrasound",""],["","Ultrasound Systems with Auto","Ultrasound Systems","System VM9.0",""],["Feature","Measure Version 2","(K 222648 )","(K211597)","Comparison"],["","","Primary predicate device","Reference Device",""],["","","","",""],["Version2","","","",""],["","","","",""],["","User selects an adult\nechocardiography 2D or Doppler\nmeasurement to perform then the\ncaliper positions are initialized\nbased on the output of the AI\ndetection algorithm.\nThe user can edit, accept, or\nreject the measurements.\nAlternately The healthcare\nprofessional performs 2D and\nDoppler measurements during a\ntransthoracic echocardiogram by\nManually positioning the calipers\non the ultrasound’s system\nwaveform or image.","T he healthcare professional\np erforms 2D and Doppler\nm easurements during a\nt ransthoracic echocardiogram by\nM anually positioning the calipers\non the ultrasound’s system\nw aveform or image.","User selects an adult\nechocardiography 2D or Doppler\nmeasurement to perform then the\ncaliper positions are initialized\nbased on the output of the AI\ndetection algorithm.\nThe user can edit, accept, or reject\nthe measurements.\nAlternately The healthcare\nprofessional performs 2D and\nDoppler measurements during a\ntransthoracic echocardiogram by\nManually positioning the calipers\non the ultrasound’s system\nwaveform or image.","Difference No.2\nAuto Measure is being included in\nthe subject submission with 5000\nCompact Series Ultrasound\nSystems"],["User","","","",""],["Interface","","","",""],["Presentation","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p18-t0","doc_id":"K242800","page_num":18,"bbox":[80.9,122.42,735.77,516.22],"n_rows":16,"n_cols":6,"columns":["Parameter","Detector","N","Z score (A.","Measured Limits of Agreement (LoA)","Checked Limits"],"rows":[["Parameter","Detector","N","Z score (A.","Measured Limits of Agreement (LoA)","Checked Limits"],["","","(Sample","Carkeet)","(detector prediction vs manual ground","of Agreement"],["","","Size)","","truth) \"","(LoAs)"],["","","","","",""],["Ao Sinus\nDiameter","DETECTOR_ID_BMOD\nE_AO_AOSV","308","2.1320","[-11.0022%, 11.2816%]","[-35.0%, 35.0%]"],["Ao STJ\nDiameter","DETECTOR_ID_BMOD\nE_AO_AOSTJ","301","2.1342","[-11.4181%, 13.1139%]","[-35.0%, 35.0%]"],["Asc Ao\nDiameter","DETECTOR_ID_BMOD\nE_AO_AOASC","204","2.1769","[-14.7794%, 15.9598%]","[-35.0%, 35.0%]"],["IVSd","DETECTOR_ID_BMOD\nE_LV_LVDISTANCE_S\nAME_LINE","305","2.1330","[-33.2114%, 28.1632%]","[-35.0%, 35.0%]"],["LVIDd","DETECTOR_ID_BMOD\nE_LV_LVDISTANCE_S\nAME_LINE","457","2.0984","[-14.1564%, 12.4223%]","[-35.0%, 35.0%]"],["LVIDs","DETECTOR_ID_BMOD\nE_LV_LVID_ES","469","2.0965","[-23.4752%, 26.0242%]","[-35.0%, 35.0%]"],["LVOT\nDiameter","DETECTOR_ID_BMOD\nE_LV_LVOT","453","2.0991","[-17.729%, 16.1588%]","[-35.0%, 35.0%]"],["LVPWd","DETECTOR_ID_BMOD\nE_LV_LVDISTANCE_S\nAME_LINE","305","2.1330","[-33.1364%, 29.9544%]","[-35.0%, 35.0%]"],["RV Base","DETECTOR_ID_BMOD\nE_RV_RVD_BASE","302","2.1339","[-16.1373%, 25.9079%]","[-35.0%, 35.0%]"],["RV Mid","DETECTOR_ID_BMOD\nE_RV_RVD_MID","243","2.1564","[-25.0913%, 30.2573%]","[-35.0%, 35.0%]"],["RV Length","DETECTOR_ID_BMOD\nE_RV_RVL","117","2.2599","[-14.6089%, 13.3871%]","[-35.0%, 35.0%]"],["TV Annulus","DETECTOR_ID_BMOD\nE_RV_TVANN","53","2.4511","[-19.3628%, 18.0347%]","[-35.0%, 35.0%]"]],"caption_candidate":"Detector performance results of Auto Measure detectors","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p19-t0","doc_id":"K242800","page_num":19,"bbox":[81.01,67.22,735.82,247.37],"n_rows":6,"n_cols":6,"columns":["MV Decel.\nTime","DETECTOR_ID_DOPPL\nER_MV_DECEL_E_DU\nRATION","136","2.2343","[-23.5717%, 22.8591%]","[-25.0%, 25.0%]"],"rows":[["MV Decel.\nTime","DETECTOR_ID_DOPPL\nER_MV_DECEL_E_DU\nRATION","136","2.2343","[-23.5717%, 22.8591%]","[-25.0%, 25.0%]"],["MV Peak A\nVel","DETECTOR_ID_DOPPL\nER_MV_VMAX_A_VE\nLOCITY","229","2.1631","[-12.3694%, 15.2363%]","[-24.0%, 24.0%]"],["MV Peak E\nVel","DETECTOR_ID_DOPPL\nER_MV_VMAX_E_VEL OCITY","136","2.2343","[ -9.2081%, 9.1223%]","[-24.0%, 24.0%]"],["AV VTI","DETECTOR_ID_DOPPL\nER_AV_VTI","247","2.1546","[-21.5393%, 19.8925%]","[-22.0%, 22.0%]"],["LVOT VTI","DETECTOR_ID_DOPPL\nER_LVOT_VTI","234","2.1607","[-17.267%, 17.2093%]","[-22.0%, 22.0%]"],["PV VTI","DETECTOR_ID_DOPPL\nER_PV_VTI","66","2.3864","[-20.6140%, 21.0567%]","[-22.0%, 22.0%]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242800-p19-t1","doc_id":"K242800","page_num":19,"bbox":[96.84,305.93,724.9,470.5],"n_rows":5,"n_cols":2,"columns":["Age","52.4 ± 15.5 years"],"rows":[["Age","52.4 ± 15.5 years"],["Gender","• Male: 49.6 %\n• Female: 50.4 %"],["Ethnicity","• Asian: 30.2 %\n• Black: 26.4 %\n• White: 36.2\n• Other: 7.3 %"],["Body Surface Area","1.9 m² ± 0.2 m²"],["Weight","76.8 kg ± 17.0 kg"]],"caption_candidate":"studies. The available data per detector are listed in column 3 above. Demographic distribution for all validation studies is as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p5-t0","doc_id":"K242807","page_num":5,"bbox":[72.38,328.5,540.38,472.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name","HeartFocus (v.1.1.1)"],"rows":[["Device Trade Name","HeartFocus (v.1.1.1)"],["Common Name","Radiological acquisition and/or optimization\nguidance system"],["Classification Name","Image Acquisition And/Or Optimization\nGuided By Artificial Intelligence"],["Regulation Number","892.2100"],["Product Code","QJU"]],"caption_candidate":"Secondary Contact Email bertrand.moal@deski.ai","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p8-t0","doc_id":"K242807","page_num":8,"bbox":[72.1,516.72,534.33,711.26],"n_rows":4,"n_cols":4,"columns":["Parameter","Caption Guidance\n(DEN 190040)","Proposed HeartFocus","Conclusion"],"rows":[["Parameter","Caption Guidance\n(DEN 190040)","Proposed HeartFocus","Conclusion"],["Classification\nName","Image Acquisition and/Or\nOptimization Guided by\nArtificial Intelligence","Image Acquisition and/Or\nOptimization Guided by\nArtificial Intelligence","Same"],["Product Code","QJU","QJU","Same"],["Intended Use","The Caption Guidance\nsoftware is intended to\nassist medical\nprofessionals in the","The HeartFocus software\nis intended to assist\nhealthcare professionals in\nthe acquisition of cardiac","Same"]],"caption_candidate":"Table 1: Predicate table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p9-t0","doc_id":"K242807","page_num":9,"bbox":[72.1,115.59,534.5,712.59],"n_rows":4,"n_cols":4,"columns":["","acquisition of cardiac\nultrasound images. Caption\nGuidance software is an\naccessory to compatible\ngeneral purpose diagnostic\nultrasound systems.","ultrasound images. The\nHeartFocus software is an\naccessory to compatible\ngeneral purpose\ndiagnostic ultrasound\nsystems.",""],"rows":[["","acquisition of cardiac\nultrasound images. Caption\nGuidance software is an\naccessory to compatible\ngeneral purpose diagnostic\nultrasound systems.","ultrasound images. The\nHeartFocus software is an\naccessory to compatible\ngeneral purpose\ndiagnostic ultrasound\nsystems.",""],["Indications for use","The Caption Guidance\nsoftware is indicated for\nuse in two-dimensional\ntransthoracic\nechocardiography\n(2D-TTE) for adult patients,\nspecifically in the\nacquisition of the following\nstandard views:\nParasternal Long-Axis\n(PLAX), Parasternal\nShort-Axis at the Aortic\nValve (PSAX-AV),\nParasternal Short-Axis at\nthe Mitral Valve\n(PSAX-MV), Parasternal\nShort-Axis at the Papillary\nMuscle (PSAX-PM), Apical\n4-Chamber (AP4), Apical\n5-Chamber (AP5), Apical\n2-Chamber (AP2), Apical\n3-Chamber (AP3),\nSubcostal 4-Chamber\n(SubC4), and Subcostal\nInferior Vena Cava\n(SC-IVC).","The HeartFocus software\nis indicated for use in\ntwo-dimensional\ntransthoracic\nechocardiography\n(2DTTE) for adult patients,\nspecifically in the\nacquisition of the following\nstandard views:\nParasternal Long-Axis\n(PLAX), Parasternal\nShort-Axis at the Aortic\nValve\n(PSAX-AV), Parasternal\nShort-Axis at the Mitral\nValve (PSAX-MV),\nParasternal Short-Axis at\nthe\nPapillary Muscles\n(PSAX-PM), Apical\n4-Chamber (A4C), Apical\n5-Chamber (A5C), Apical\n2-\nChamber (A2C), Apical\n3-Chamber (A3C),\nSubcostal 4-Chamber\n(SC-4C), and Subcostal\nInferior\nVena Cava (SC-IVC).","Same\n*A4C, A5C, A2C,\nA3C, SC-4C are\nthe American\nSociety of\nEchocardiography\nAcronyms:\nGuidelines for\nPerforming a\nComprehensive\nTransthoracic\nEchocardiographic\nExamination in\nAdults:\nRecommendations\nfrom the American\nSociety of\nEchocardiography\n(asecho.org)"],["Intended User","Medical professionals\n(including expert\nsonographers)","Medical professionals\n(including expert\nsonographers)","Same"],["Compatible\nUltrasound\nSystem and Probe","The uSmart 2300t Plus\nultrasound system with the\n2300t-compatible Terason\n4v2A linear phased array\nprobe","Clarius Scanner PAHD3\n(wireless), PAHD, PAL,\nand Clarius Ultrasound\nScanner Software","Substantially\nEquivalent: Both\nthe predicate\ndevices and the\nproposed device\nfunction as a"]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p11-t0","doc_id":"K242807","page_num":11,"bbox":[72.08,115.59,534.5,712.59],"n_rows":5,"n_cols":4,"columns":["","","","direct the user to a\nprobe position that\nwill enable\nacquisition of a\ndiagnostic quality\nclip. Hence, this\ndifference does not\nraise new\nquestions of safety\nand/or\neffectiveness."],"rows":[["","","","direct the user to a\nprobe position that\nwill enable\nacquisition of a\ndiagnostic quality\nclip. Hence, this\ndifference does not\nraise new\nquestions of safety\nand/or\neffectiveness."],["Real Time\nFeedback on\nImage Quality","Quality Meter: real-time\nfeedback from the Quality\nMeter advises the user on\nthe expected diagnostic\nquality of the resulting clip,\nsuch that the user can\nmake decisions to further\noptimize the quality, for\nexample by following the\nprescriptive guidance\nfeature","HeartFocus algorithm\nprovides analysis of the\ndiagnostic-quality of the\nimage and indicates to the\nuser when the current\nframe is diagnostic-quality\nto hold the position for a\nrecording\nFurther, a score on the\nexpected diagnostic\nquality of the Auto-Record\nand Best-Effort-Record\nclips is indicated such that\nthe user can\nmake decisions to further\noptimize the quality","Substantially\nEquivalent"],["Manual Image\nRecording","Manual recording","Manual recording if\nprompted by the user","Same"],["Automatic Capture\nof Clips and\nPredicted\nDiagnostic Quality","Auto-Capture: The Caption\nGuidance Auto-Capture\nfeature triggers an\nautomatic capture of a clip\nwhen the quality is\npredicted to be diagnostic,\nemulating the way in which\na sonographer knows\nwhen an image is\nof sufficient quality to be\ndiagnostic and records it.","Auto-Record: automates\nthe capture of\ndiagnostic-quality\nrecordings, emulating how\na sonographer\nknows when an image is\nof sufficient quality to be\ndiagnostic and records it.","Substantially\nEquivalent"],["Retrospectively\nRecording of\nHighest Quality\nClip","Save Best Clip: This\nfeature continually\nassesses clip quality while\nthe user is scanning and, if\nthe user is not able to\nobtain a clip sufficient for","Best-Effort-Record: this\nfeature stores the clip that\nhas been evaluated as\nhaving the best expected\ndiagnostic quality during\nan exam for a given\nreference view. If the user","Substantially\nEquivalent"]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p12-t0","doc_id":"K242807","page_num":12,"bbox":[72.13,115.59,534.5,298.59],"n_rows":3,"n_cols":4,"columns":["","Auto-Capture, the software\nallows the user to\nretrospectively record the\nhighest quality clip\nobtained so far, mimicking\nthe choice a sonographer\nmight make when\nrecording an exam.","does not manage to\nperform an auto-record for\nthe reference view, the\nBest-Effort-Record clip is\nproposed to the user.",""],"rows":[["","Auto-Capture, the software\nallows the user to\nretrospectively record the\nhighest quality clip\nobtained so far, mimicking\nthe choice a sonographer\nmight make when\nrecording an exam.","does not manage to\nperform an auto-record for\nthe reference view, the\nBest-Effort-Record clip is\nproposed to the user.",""],["Deep Learning\nBased Algorithm","Yes","Yes","Same"],["Machine Learning\n– Based Algorithm","Yes","Yes","Same"]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p14-t0","doc_id":"K242807","page_num":14,"bbox":[72.25,210.55,536.58,546.5],"n_rows":4,"n_cols":5,"columns":["Feature","AI/ML\nAlgorithm","Objective","Endpoint","Success Criteria"],"rows":[["Feature","AI/ML\nAlgorithm","Objective","Endpoint","Success Criteria"],["Diagnostic-\nquality\nview\ndetection","View\nClassification","Ability to classify\nultrasound\nimages with\nsimilar accuracy\nas experts","Cohen’s kappa\nscore between the\nmodel’s predictions\nand the ground\ntruth labels made by\nexperts (by frame)","Lower bound of the\n95% confidence\ninterval of the Cohen’s\nkappa score > 0.6\n(substantial\nagreement) for the 10\nreference view"],["Live\nguidance","Guidance","Ability to provide\nsuccessful\nguidance cues\non ultrasound\nframes","Positive predictive\nvalue of successful\nguidance cues (by\nframe)","Lower bound of the\n95% confidence\ninterval of the positive\npredictive value > 0.8\nfor the 10 reference\nviews"],["Auto\nrecord","View\nClassification\n+ Recording","Ability to save\nhigh-quality\nrecords\naccording to\nexperts","Positive predictive\nvalue of high-quality\nrecords among\nauto-records (by\nclip)","Lower bound of the\n95% confidence\ninterval of the positive\npredictive value > 0.6\nand point estimate of\nthe positive predictive\nvalue > 0.8 for the 10\nreference views"]],"caption_candidate":"Table 2: Primary objectives, endpoints, and success criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p17-t0","doc_id":"K242807","page_num":17,"bbox":[86.38,631.6,522.25,715.5],"n_rows":3,"n_cols":2,"columns":["Endpoint","Percent of diagnostic quality\n% [95% Wilson CI*]"],"rows":[["Endpoint","Percent of diagnostic quality\n% [95% Wilson CI*]"],["Qualitative Visual Assessment of LV Size","100 [98.4;100]"],["Qualitative Visual Assessment of LV Function","100 [98.4;100]"]],"caption_candidate":"Table 3: Primary endpoint results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p18-t0","doc_id":"K242807","page_num":18,"bbox":[86.5,115.5,524.33,176.69],"n_rows":2,"n_cols":2,"columns":["Qualitative Visual Assessment of RV Size","100 [98.4;100]"],"rows":[["Qualitative Visual Assessment of RV Size","100 [98.4;100]"],["Qualitative Visual Assessment of Non-Trivial\nPericardial Effusion","100 [98.4;100]"]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p18-t1","doc_id":"K242807","page_num":18,"bbox":[83.37,532.8,524.33,706.5],"n_rows":6,"n_cols":2,"columns":["Endpoint","Percent of diagnostic quality\n% [95% Wilson CI*]"],"rows":[["Endpoint","Percent of diagnostic quality\n% [95% Wilson CI*]"],["Qualitative Visual Assessment of RV Function","99.6 [97.7;99.9]"],["Qualitative Visual Assessment of LA Size","100 [98.4;100]"],["Qualitative Visual Assessment of RA Size","98.8 [96.4;99.6]"],["Qualitative Visual Assessment of Segmental\nKinetics of the LV","95.4 [92.0;97.4]"],["Qualitative Visual Assessment of AV","98.8 [96.4;99.6]"]],"caption_candidate":"Table 4: Secondary endpoint results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p19-t0","doc_id":"K242807","page_num":19,"bbox":[83.5,115.5,525.5,187.5],"n_rows":3,"n_cols":2,"columns":["Qualitative Visual Assessment of MV","100 [98.4;100]"],"rows":[["Qualitative Visual Assessment of MV","100 [98.4;100]"],["Qualitative Visual Assessment of TV","95.4 [92.0;97.4]"],["Qualitative Visual Assessment of IVC Size","78.3 [72.7;83.1]"]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p20-t0","doc_id":"K242807","page_num":20,"bbox":[116.37,138.39,483.25,415.5],"n_rows":11,"n_cols":2,"columns":["View","Percent of diagnostic quality\n% [95% Wilson CI*]"],"rows":[["View","Percent of diagnostic quality\n% [95% Wilson CI*]"],["PLAX","97.5 [94.7;98.8]"],["PSAX-AV","89.2 [84.6;92.5]"],["PSAX-MV","90.8 [86.5;93.9]"],["PSAX-PM","97.1 [94.1;98.6]"],["A4C","96.2 [93.0;98.0]"],["A5C","93.3 [89.4;95.9]"],["A2C","82.5 [77.2;86.8]"],["A3C","90.0 [85.6;93.2]"],["SC-4C","89.2 [84.6;92.5]"],["SC-IVC","77.5 [71.8;82.3]"]],"caption_candidate":"Table 5: Study results: diagnostic-quality clips","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p22-t0","doc_id":"K242807","page_num":22,"bbox":[72.13,116.0,540.5,377.0],"n_rows":8,"n_cols":3,"columns":["Table 6: Rationale and testing for each modification","",""],"rows":[["Table 6: Rationale and testing for each modification","",""],["Modification","Rationale","Testing"],["M1 - Retraining of the\ncore algorithms","Enhance the performance of the\nAI models in the perspective of\nextending the use of the ML-DS\nwith new ultrasound systems","Execute AI performance on\nthe reference test set and\nsystem-level validation tests"],["M2 - Extend the use of\nthe ML-DSF with new\nultrasound systems","Enable support for a broader\nrange of ultrasound systems","Execute AI performance tests\non new system test set and\nsystem-level validation test"],["M3 - Extend the use of\nthe ML-DSF with new\noperating systems","Enable support for a broader\nrange of devices","Execute system-level\nvalidation test"],["","",""],["Table 7 describes the requirements for the ultrasound systems that can be cleared through the","",""],["PCCP (M1+M2).","",""]],"caption_candidate":"DESKi HeartFocus 510(k) Summary Apr 4, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p22-t1","doc_id":"K242807","page_num":22,"bbox":[72.13,395.46,531.3,682.5],"n_rows":4,"n_cols":2,"columns":["Requirement","Description"],"rows":[["Requirement","Description"],["FDA-cleared ultrasound system\ncompatible with HeartFocus’ intended\nuse","● Ultrasound system shall be FDA-cleared\n● Validated for cardiac use\n● Validated for use on adults"],["Integration features","● Technical integration shall allow HeartFocus\nto access live ultrasound stream\n● Compatible for an integration on\nHeartFocus’ operating systems"],["Minimal specifications","● The ultrasound system shall provide an\nimage stream at a minimum of 15 frames\nper second.\n● Center or nominal frequency within 2–5\nMHz, suitable for adult transthoracic\nechocardiography\n● At least 30 cm depth, to allow full\nvisualization of adult cardiac structures\n● 2D B-mode imaging (grayscale)\n● Cone-shaped field of view with an opening\nangle of at least 80 degrees"]],"caption_candidate":"Table 7: Ultrasound system requirements","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242807-p23-t0","doc_id":"K242807","page_num":23,"bbox":[72.03,381.35,539.36,717.5],"n_rows":4,"n_cols":5,"columns":["Feature","AI/ML\nAlgorithm","Objective","Endpoint","Success Criteria"],"rows":[["Feature","AI/ML\nAlgorithm","Objective","Endpoint","Success Criteria"],["Diagnostic-\nquality\nview\ndetection","View\nClassification","Ability to classify\nultrasound\nimages with\nsimilar accuracy\nas experts","Cohen’s kappa\nscore between the\nmodel’s predictions\nand the ground\ntruth labels made by\nexperts (by frame)","Lower bound of the\n95% confidence\ninterval of the Cohen’s\nkappa score > 0.6\n(substantial\nagreement) for the 10\nreference view"],["Live\nguidance","Guidance","Ability to provide\nsuccessful\nguidance cues\non ultrasound\nframes","Positive predictive\nvalue of successful\nguidance cues (by\nframe)","Lower bound of the\n95% confidence\ninterval of the positive\npredictive value > 0.8\nfor the 10 reference\nviews"],["Auto\nrecord","View\nClassification\n+ Recording","Ability to save\nhigh-quality\nrecords\naccording to\nexperts","Positive predictive\nvalue of high-quality\nrecords among\nauto-records (by\nclip)","Lower bound of the\n95% confidence\ninterval of the positive\npredictive value > 0.6\nand point estimate of\nthe positive predictive\nvalue > 0.8 for the 10\nreference views"]],"caption_candidate":"Table 8: Primary objectives, endpoints, and success criteria for M1+M2 modifications.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242821-p5-t0","doc_id":"K242821","page_num":5,"bbox":[72.0,129.49,354.94,751.83],"n_rows":53,"n_cols":2,"columns":["1. General Informatio","n"],"rows":[["1. General Informatio","n"],["",""],["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],["",""],["Address","8F., No.360, Sec. 1, Jingmao"],["","Beitun Dist.,"],["","Taichung City 406040,"],["","Taiwan"],["",""],["Applicant","Joseph Chang"],["",""],["Contact Information","886-04-23213838 #216"],["","joseph.chang@everfortune.ai"],["",""],["Correspondence Person","Ti-Hao Wang"],["",""],["Contact Information","886-04-23213838 #168"],["","thothwang@gmail.com"],["",""],["","tihao.wang@everfortune.ai"],["",""],["Date Prepared","January, 2025"],["",""],["2. Proposed Device",""],["",""],["Proprietary Name","EFAI CHESTSUITE XR M"],["","SYSTEM (ETT-XR-100)"],["",""],["Common Name","EFAI ETTXR"],["",""],["Classification Name","Radiological computer-assist"],["",""],["Regulation Number","21 CFR 892.2080"],["",""],["Product Code","QAS"],["",""],["Regulatory Class","II"],["",""],["3. Predicate Device",""],["",""],["Proprietary Name","Briefcase"],["",""],["Premarket Notification","K221330"],["",""],["Classification Name","Radiological computer-assist"],["",""],["Regulation Number","21 CFR 892.2080"],["",""],["Product Code","QAS"],["",""],["Regulatory Class","II"],["",""],["EFAI ETTXR Traditional 510(k)",""]],"caption_candidate":"1.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242821-p5-t1","doc_id":"K242821","page_num":5,"bbox":[66.05,151.89,539.62,351.39],"n_rows":7,"n_cols":2,"columns":["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],"rows":[["510(k) Sponsor","Ever Fortune.AI Co., Ltd."],["Address","8F., No.360, Sec. 1, Jingmao Rd.,\nBeitun Dist.,\nTaichung City 406040,\nTaiwan"],["Applicant","Joseph Chang"],["Contact Information","886-04-23213838 #216\njoseph.chang@everfortune.ai"],["Correspondence Person","Ti-Hao Wang"],["Contact Information","886-04-23213838 #168\nthothwang@gmail.com\ntihao.wang@everfortune.ai"],["Date Prepared","January, 2025"]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242821-p5-t2","doc_id":"K242821","page_num":5,"bbox":[66.05,398.46,539.62,509.46],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","EFAI CHESTSUITE XR MALPOSITIONED ETT ASSESSMENT\nSYSTEM (ETT-XR-100)"],"rows":[["Proprietary Name","EFAI CHESTSUITE XR MALPOSITIONED ETT ASSESSMENT\nSYSTEM (ETT-XR-100)"],["Common Name","EFAI ETTXR"],["Classification Name","Radiological computer-assisted triage and notification software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242821-p5-t3","doc_id":"K242821","page_num":5,"bbox":[66.05,556.26,539.62,655.63],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Briefcase"],"rows":[["Proprietary Name","Briefcase"],["Premarket Notification","K221330"],["Classification Name","Radiological computer-assisted triage and notification software"],["Regulation Number","21 CFR 892.2080"],["Product Code","QAS"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242821-p7-t0","doc_id":"K242821","page_num":7,"bbox":[73.69,127.9,537.94,723.37],"n_rows":2,"n_cols":3,"columns":["Feature/\nFunction","Proposed Device:\nEFAI ETTXR","Predicate Device:\nBriefCase\n(K221330)"],"rows":[["Feature/\nFunction","Proposed Device:\nEFAI ETTXR","Predicate Device:\nBriefCase\n(K221330)"],["Intended\nUse/Indication\nfor Use","EFAI CHESTSUITE XR\nMALPOSITIONED ETT\nASSESSMENT SYSTEM (EFAI\nETTXR) is a radiological\ncomputer-aided triage and notification\nsoftware indicated for use in the\nanalysis of chest X-ray (CXR) images\nin adults. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage by\nflagging and communicating\nsuspected positive cases of vertically\nmalpositioned endotracheal tube\n(ETT) in relation to the carina.\nFindings are flagged when the ETT\ndistal tip is assessed as being more\nthan 7 cm above the carina, less than 3\ncm above the carina, or when it is\nbelow the carina (i.e in the right or left\nmainstem bronchus). The device\nassesses solely the vertical position of\nthe ETT distal tip relative to the\ncarina, does not factor patient\npositioning, and cannot detect\nesophageal intubation. The device is\ntested in the single lumen\nendotracheal tube, while it may trigger\na false prioritization alert in the case\nof properly positioned double lumen\nETT.\nEFAI ETTXR analyzes cases using\ndeep learning algorithms to identify\nsuspected malpositioned ETT\nfindings. It makes case-level output\navailable to a PACS/workstation for\nworklist prioritization or triage. EFAI\nETTXR is not intended to direct\nattention to specific portions of an\nimage or to anomalies of an image. Its\nresults are not intended to be used on a\nstand-alone basis for clinical","BriefCase is a radiological\ncomputeraided triage and notification\nsoftware indicated for use in the\nanalysis of frontal chest X-ray (CXR)\nimages in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage\nby flagging and communicating\nsuspected positive cases of vertically\nmalpositioned endotracheal tube\n(ETT) in relation to the carina.\nFindings are flagged when the ETT\ndistal tip is assessed as being more\nthan 5 cm above the carina, less than 2\ncm above the carina, or when it is\nbelow the carina (i.e in the right or left\nmainstem bronchus).\nThe device assesses solely the vertical\nposition of the ETT distal tip relative\nto the carina, does not factor patient\npositioning, and cannot detect\nesophageal intubation. The device\ndoes not provide results when the\ncarina is not well-visualized on the\nx-ray image. The device does not\ndiscriminate types of ETTs, as such a\nproperly positioned double lumen ETT\nmay trigger a false prioritization alert.\nBriefCase uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected findings on a standalone\napplication in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with\nnotifications for cases with suspected\nfindings. Notifications include\ncompressed preview images that are"]],"caption_candidate":"6. Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242821-p8-t0","doc_id":"K242821","page_num":8,"bbox":[73.87,89.62,538.12,700.87],"n_rows":7,"n_cols":3,"columns":["","decision-making nor is it intended to\nrule out malpositioned ETT or\notherwise preclude clinical assessment\nof chest radiographs.","meant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on the\nuser’s professional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care."],"rows":[["","decision-making nor is it intended to\nrule out malpositioned ETT or\notherwise preclude clinical assessment\nof chest radiographs.","meant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on the\nuser’s professional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images\nper the standard of care."],["User population","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomical\nregion of\ninterest","Chest","Chest"],["Data\nacquisition\nprotocol","Chest X-ray (AP view)","Frontal Chest X-ray (CXR)"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\nWorklist or deprioritized.","No. No cases are removed from\ndesktop app or deprioritized"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242822-p5-t0","doc_id":"K242822","page_num":5,"bbox":[65.47,457.27,576.41,538.63],"n_rows":3,"n_cols":16,"columns":["","Device Trade","","","Regulation","","Common name","","Device","","","Product","","","Classification",""],"rows":[["","Device Trade","","","Regulation","","Common name","","Device","","","Product","","","Classification",""],["","Name","","","Number","","","","Class","","","Code(s)","","","Name",""],["ART-Plan+\n(v3.0.0)","","","892.5050","","","Medical charged-particle\nradiation therapy system","Class II","","","MUJ\nAssociated\nProduct\nCode(s):\nQKB, LLZ","","","System,\nPlanning,\nRadiation\nTherapy\nTreatment","",""]],"caption_candidate":"Device Name:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242822-p5-t1","doc_id":"K242822","page_num":5,"bbox":[108.26,594.34,526.9,652.9],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate trade name\n(primary predicate is listed\nfirst)","Product code"],"rows":[["Predicate #","Predicate trade name\n(primary predicate is listed\nfirst)","Product code"],["K222728","Radiation Planning Assistant\n(RPA)","MUJ"]],"caption_candidate":"Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242822-p6-t0","doc_id":"K242822","page_num":6,"bbox":[108.26,139.7,526.9,194.3],"n_rows":3,"n_cols":3,"columns":["Reference device #","Reference device trade\nname","Product code"],"rows":[["Reference device #","Reference device trade\nname","Product code"],["K213628","VBrain","QKB"],["K234068","ART-Plan","MUJ"]],"caption_candidate":"Legally marketed reference devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242822-p8-t0","doc_id":"K242822","page_num":8,"bbox":[108.5,224.24,532.96,527.97],"n_rows":11,"n_cols":8,"columns":["Technical Information","","","","","","",""],"rows":[["Technical Information","","","","","","",""],["Property","","","Proposed Device\nART-Plan v3.0.0","","Primary Predicate","","Comment"],["","","","","","Radiation Planning","",""],["","","","","","System (RPA)","",""],["","","","","","","",""],["Delineation\nMethod","","","AI","AI","","","The proposed device and primary\npredicate share an AI delineation\nmethod."],["Segmentation\nFeatures","","","Automatically delineates\nOARs and lymph nodes and\ntargets.\nDeep learning algorithm.\nAutomatic segmentation\nincludes the following\nlocalizations:\n* head and neck (on CT)\n* thorax/breast (for\nmale/female and on CT)\n* abdomen (on CT images\nand MR images)\n* pelvis male (on CT and\nMR)\n* pelvis female (on CT\nimages)\n* brain (on CT images and\nMR images)","The RPA provides\nautocontouring for a range\nof structures","","","The proposed device proposes\nsegmentation on the same\nlocalizations with the same medical\nimages of different modalities using AI."],["","Regions and","","AI Based autocontouring","AI Based autocontouring,","","","The proposed device and the primary\npredicate allow AI automatic\ncontouring."],["","Volumes","","","","","",""],["","of Interest","","","","","",""],["","(ROI)","","","","","",""]],"caption_candidate":"additional claim for the proposed device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p6-t0","doc_id":"K242837","page_num":6,"bbox":[72.0,420.6,540.0,472.56],"n_rows":4,"n_cols":2,"columns":["","In addition, the SW architecture was changed to separate the image"],"rows":[["","In addition, the SW architecture was changed to separate the image"],["communication platform from the BriefCase-Triage SW. The subject device consists of only the",""],["algorithm analysis module which can be integrated with image communication platforms that meet the",""],["BriefCase-Triage input and output requirements.",""]],"caption_candidate":"BriefCase-Triage for CSF (K203508) are identical in most aspects and differ mostly with respect to","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p7-t0","doc_id":"K242837","page_num":7,"bbox":[59.67,96.48,539.13,688.68],"n_rows":5,"n_cols":5,"columns":["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],"rows":[["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],["","","","Aidoc BriefCase-Triage for CSF",""],["","","","(K203508)",""],["Intended\nUse /\nIndications\nfor Use","BriefCase-Triage is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the\nanalysis of CT scans that include the\ncervical spine, in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of linear\nlucencies in the cervical spine bone in\npatterns compatible with fractures.\nBriefCase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected\nfindings in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with notifications\nfor cases with suspected findings.\nNotifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter\nthe original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase-Triage are\nintended to be used in conjunction with\nother patient information and based on\ntheir professional judgment, to assist\nwith triage/prioritization of medical\nimages. Notified clinicians are\nresponsible for viewing full images per\nthe standard of care.","BriefCase is a radiological computer aided\ntriage and notification software indicated\nfor use in the analysis of cervical spine CT\nimages. The device is intended to assist\nhospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communication of\nsuspected positive findings of linear\nlucencies in the cervical spine bone in\npatterns compatible with fractures.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with detected findings on a\nstandalone desktop application in parallel\nto the ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended\nto be used as a diagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other patient\ninformation and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","",""],["User\npopulation","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists","",""]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p8-t0","doc_id":"K242837","page_num":8,"bbox":[59.65,72.36,539.15,698.88],"n_rows":11,"n_cols":5,"columns":["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],"rows":[["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],["","","","Aidoc BriefCase-Triage for CSF",""],["","","","(K203508)",""],["Anatomical\nregion of\ninterest","Cervical Spine","Cervical Spine","",""],["Data\nacquisition\nprotocol","CT with or without contrast that includes\nthe cervical spine","Non-contrast cervical spine CT scan","",""],["Notification-\nonly\n(/notification\nalerts),\nparallel\nworkflow\ntool","Yes","Yes","",""],["Images\nformat","DICOM","DICOM","",""],["Interference\nwith\nstandard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized","",""],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion Criteria:\n● CT with or without contrast that\nincludes the cervical spine\n(bone and standard kernel)\n● Scans performed on\nadults/transitional adults ≥ 18\nyears of age.\n● Slice thickness: 0.3 mm - 5.0\nmm\nExclusion Criteria\n● All studies that have an\ninadequate field of view","Inclusion Criteria:\n● Non-enhanced cervical spine CT\n(bone kernel only).\n● Scans performed on\nadults/transitional adults ≥ 18\nyears of age.\n● Scans performed on CT scanners\nwith 64 or greater number of\ndetectors.\n● Slice thickness: 0.625 mm - 2.5\nmm axial or 2-3 mm sagittal or 2-3\nmm. coronal reconstructions with\nbone kernel.\nExclusion Criteria\n● All scans that are technically\ninadequate, including motion\nartifacts, severe metal artifacts, or\nan inadequate field of view.","",""],["Additional\nOperating\nPoints","4 Additional Operating Points","N/A","",""],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p8-t1","doc_id":"K242837","page_num":8,"bbox":[65.4,394.8,124.92,446.76],"n_rows":4,"n_cols":2,"columns":["","for"],"rows":[["","for"],["clinical",""],["performance",""],["testing",""]],"caption_candidate":"Exclusion ● CT with or without contrast that ● Non-enhanced cervical spine CT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p9-t0","doc_id":"K242837","page_num":9,"bbox":[59.69,72.36,539.11,234.36],"n_rows":4,"n_cols":5,"columns":["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],"rows":[["","Subject Device\nAidoc BriefCase-Triage for CSF","","Predicate Device",""],["","","","Aidoc BriefCase-Triage for CSF",""],["","","","(K203508)",""],["Structure","- Integrated with image routing module\nvia image communication platform (ICP)\n(image acquisition).\n- Algorithm module (image\nprocessing)\n- Integrated with desktop application\nfor workflow integration (feed and\nnon-diagnostic Image Viewer).","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for\nworkflow integration (Feed/Worklist\n(alternate names) and non-diagnostic\nImage Viewer).","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p10-t0","doc_id":"K242837","page_num":10,"bbox":[113.2,169.52,498.6,365.45],"n_rows":17,"n_cols":6,"columns":["Time -to-","Mean","N","95% Lower","95% Upper","Median"],"rows":[["Time -to-","Mean","N","95% Lower","95% Upper","Median"],["","","","","",""],["Notification","Estimate","","CL","CL",""],["","","","","",""],["","(seconds)","","","",""],["Predicate K203508","234","48","228","246","234"],["","","","","",""],["","","","","",""],["Processing Time","","","","",""],["BriefCase-Triage +","15.1","202","14.1","16.2","13.4"],["","","","","",""],["","","","","",""],["Image","","","","",""],["Communication","","","","",""],["","","","","",""],["Platform Time-To-","","","","",""],["Notification","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p11-t0","doc_id":"K242837","page_num":11,"bbox":[130.64,112.8,481.44,153.42],"n_rows":3,"n_cols":20,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","N",""],["","Age","","62.0","","","19.6","","","18.0","","","65.0","","","90.0","","","487",""],["","(Years)","","","","","","","","","","","","","","","","","487",""]],"caption_candidate":"Table 4. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p11-t1","doc_id":"K242837","page_num":11,"bbox":[172.14,216.94,437.65,339.66],"n_rows":6,"n_cols":18,"columns":["Ground\nTruth\nResults","","","","Gender","","","","","","","","","","All","","",""],"rows":[["Ground\nTruth\nResults","","","","Gender","","","","","","","","","","All","","",""],["","","","","Female","","","","","Male","","","","","","All","",""],["","","","","N","","","%","","N","","","%","","","N","","%"],["","Positive","","","80","","","16.4%","","108","","","22.2%","","","188","","38.6%"],["","Negative","","","160","","","32.9%","","122","","","25.1%","","","282","","57.9%"],["","All","","","240","","","49.3%","","230","","","47.2%","","","487*","","100%"]],"caption_candidate":"Table 5. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242837-p11-t2","doc_id":"K242837","page_num":11,"bbox":[208.95,396.84,402.78,559.44],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["GE MEDICAL\nSYSTEMS","","","150","","","30.8%","",""],["SIEMENS","","","132","","","27.1%","",""],["TOSHIBA","","","122","","","25.1%","",""],["Philips","","","83","","","17.0%","",""],["","Total","","","487","","","100%",""]],"caption_candidate":"Table 6. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242838-p5-t0","doc_id":"K242838","page_num":5,"bbox":[51.12,439.8,555.24,567.36],"n_rows":5,"n_cols":2,"columns":["Device Trade Name","QuickRad"],"rows":[["Device Trade Name","QuickRad"],["Regulation Name/ Device Common Name","Medical image management and processing system"],["Regulation Number","21 CFR 892.2050"],["Device Class","Class 2"],["Product Code","LLZ"]],"caption_candidate":"II. DEVICE DETAILS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242838-p5-t1","doc_id":"K242838","page_num":5,"bbox":[51.12,615.24,555.24,788.4],"n_rows":6,"n_cols":2,"columns":["Device Trade Name","Augmento"],"rows":[["Device Trade Name","Augmento"],["Device Manufacturer Name","DEEPTEK MEDICAL IMAGING PRIVATE LIMITED"],["510(k) Number","K222781"],["Regulation Number","21 CFR 892.2050"],["Device Class","Class 2"],["Product Code","LLZ"]],"caption_candidate":"III. PREDICATE DEVICE DETAILS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242838-p8-t0","doc_id":"K242838","page_num":8,"bbox":[32.04,67.44,563.64,805.56],"n_rows":10,"n_cols":5,"columns":["","","physicians, radiologists, nurses,\nand medical technicians.","certified medical practitioners,\nincluding physicians, radiologists,\nand medical technicians.",""],"rows":[["","","physicians, radiologists, nurses,\nand medical technicians.","certified medical practitioners,\nincluding physicians, radiologists,\nand medical technicians.",""],["9.","Prescription or\nOTC","Prescription","Prescription","Same"],["Specifications","","","",""],["10.","Modalities","Various Image sources","Various image sources","Same"],["11.","Web browser\nsoftware","Google Chrome, Mozilla, and\nEdge","Google Chrome, Mozilla, Edge,","Same"],["12.","Resolution","32-bit Color Display &\n1920x1080","32-bit Color Display &\n1920x1080","Same"],["13.","Image Storage","Yes","Yes","Same"],["14.","Software\nenvironment","OS: Windows 10","OS: Windows 11","Same"],["Functions","","","",""],["15.","Main\nFunctions","• Log In\n• Worklist – Search Filter\n• Worklist – Open image\n• Work list- study List\n• Worklist – Report\n• Worklist – Series\n• Viewer – View exam\n• Viewer – Control View\nwindow\n• Viewer – view mode (real\nresolution)\n• Viewer – View mode\n(Highlight)\n• Viewer – Stacking\n• Viewer – Changing the layout\n• Viewer – Comparative study\n• Viewer – Preset filter\n• Viewer - Zoom\n• Viewer – Panning\n• Viewer - Invert Image\n• Viewer – Viewing mode\n(Normal/ Image/ Stack/\nCustom/ Annotation)\n• Viewer – Comparative study\n• Viewer – Rotation\n• MIP/MPR Reconstruction\n• Viewer – Reference line\n• Viewer – Sharpening","• Log In\n• Worklist – Search Filter\n• Worklist – Open image\n• Work list- study List\n• Worklist – Report\n• Worklist – Series\n• Viewer – View exam\n• Viewer – Thumbnail view of the\nseries\n• Viewer–Changing the layout\n• Viewer–Comparative study\n• Viewer – Preset filter\n• Viewer - Zoom\n• Viewer – Panning\n• Viewer - Invert Image\n• Viewer – Viewing mode\n(Normal/Stack/ Custom/ Annotation/\nsynchronized screening)\n• Viewer – Comparative study\n• Viewer – Rotation\n• Viewer- MIP/MPR Reconstruction\n• Viewer – Reference line\n• Viewer–Measurement- rectangular,\nellipse, angle/cobb angle\n• Viewer – Cine/movie mode\n• Viewer- Overlaying/ Hide or display\noverlay\n• Viewer- Magnify\n• Viewer- Probe/HU","Similar1"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242838-p9-t0","doc_id":"K242838","page_num":9,"bbox":[32.04,67.44,563.64,321.0],"n_rows":4,"n_cols":5,"columns":["","","• Viewer – Measure\n• Viewer – Inverting image color\n• Viewer – Cine\n• Viewer- Overlaying.","• Viewer- crop",""],"rows":[["","","• Viewer – Measure\n• Viewer – Inverting image color\n• Viewer – Cine\n• Viewer- Overlaying.","• Viewer- crop",""],["16.","3D Cursor","Yes","Yes","Same"],["17.","Optional\nIntegration of\nFDA-cleared\n3rd party AI\nmodels","Yes","Yes","Same"],["18.","Operation feature","Web environment-based\nPACS.\nViewing and handling DICOM\nmedical images. Review and\nreport study located on a\nserver.","Web environment-based\nPACS.\nViewing and handling DICOM\nmedical images. Review, modify,\nand approve the study located in a\nserver.","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242919-p7-t0","doc_id":"K242919","page_num":7,"bbox":[40.84,114.76,813.68,518.56],"n_rows":10,"n_cols":9,"columns":["Specification","Subject Device","","Primary Predicate Device","","","Secondary Predicate Device","","Comparison"],"rows":[["Specification","Subject Device","","Primary Predicate Device","","","Secondary Predicate Device","","Comparison"],["","","","K221592","","","K161201","",""],["Device Name","V5med Lung AI","AVIEW Lung Nodule CAD","","","ClearRead CTTM","","","N/A"],["Classification Name","Medical Image Management and\nProcessing System","Medical Image Management and\nProcessing System","","","Medical image management and\nprocessing system","","","Same"],["Device Class","Class II","Class II","","","Class II","","","Same"],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050","","","21 CFR 892.2050","","","Same"],["Product Code","OEB/LLZ","OEB/LLZ","","","OEB/LLZ","","","Same"],["Review Panel","Radiology","Radiology","","","Radiology","","","Same"],["510(k) Number","K242919","K221592","","","K161201","","","N/A"],["Indications for Use","V5med Lung AI is a Computer-Aided\nDetection (CAD) software designed to\nassist radiologists in detecting\npulmonary nodules (with diameter of\n4-30 mm) during CT examinations of\nthe chest for asymptomatic\npopulations. This software provides\nadjunctive information to alert\nradiologists to regions of interest with\nsuspected lung nodules that may\notherwise be overlooked. It can be\nused in a concurrent read mode, where\nthe AI analysis results are displayed\nalongside the original CT images\nduring both the initial review and any\nsubsequent reviews by the radiologist.\nV5med Lung AI does not replace the\nradiologist’s critical judgment or\ndiagnostic processes and should not\nbe used in isolation from the original\nCT series.","AVIEW Lung Nodule CAD is a\nComputer-Aided Detection (CAD)\nsoftware designed to assist\nradiologists in the detection of\npulmonary nodules (with diameter 3-\n20 mm) during the review of\nCT examinations of the chest for\nasymptomatic populations. AVIEW\nLung Nodule CAD provides\nadjunctive information to alert the\nradiologists to regions of interest\nwith suspected lung nodules that may\notherwise be overlooked. AVIEW\nLung Nodule CAD may be used as a\nsecond reader after the radiologist\nhas completed their initial read. The\nalgorithm has been validated using\nnon-contrast CT images, the majority\nof which were acquired on Siemens\nSOMATOM CT series scanners;\ntherefore, limiting device use to use\nwith Siemens SOMATOM CT series\nis recommended.","","","ClearRead CT™ is comprised of\ncomputer assisted reading tools\ndesigned to aid the radiologist in the\ndetection of pulmonary nodules\nduring review of CT examinations of\nthe chest on an asymptomatic\npopulation. The ClearRead CT\nrequires both lungs be in the field of\nview. ClearRead CT provides\nadjunctive information and is not\nintended to be used without the\noriginal CT series.","","","V5med Lung AI and AVIEW Lung\nNodule CAD (predicate device) are\nboth Computer-Aided Detection (CAD)\nsoftware designed to assist radiologists\nin detecting pulmonary nodules during\nCT examinations of the chest for\nasymptomatic populations. Both\nprovide adjunctive information to alert\nradiologists to regions of interest with\nsuspected lung nodules that may\notherwise be overlooked.\nHowever, V5med Lung AI supports a\nbroader nodule diameter range (4-30\nmm), compared to AVIEW's range of\n3-20 mm, making it similar to\nClearRead CT™, which also covers\nnodules from 5-20 mm. Additionally,\nV5med Lung AI does not restrict the\nuse to non-contrast images, unlike\nAVIEW, aligning it more closely with\nClearRead CT™. Furthermore, V5med\nLung AI does not limit the scanner\nsource, while AVIEW is validated"]],"caption_candidate":"Functional Specification Comparison Table for the V5med Lung AI and AVIEW Lung Nodule CAD (K221592):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242919-p8-t0","doc_id":"K242919","page_num":8,"bbox":[40.86,82.82,813.66,517.72],"n_rows":3,"n_cols":5,"columns":["","","","","primarily with Siemens SOMATOM\nCT series scanners, making V5med\nLung AI more flexible like ClearRead\nCT™. These differences do not impact\nthe safety and effectiveness of V5med\nLung AI."],"rows":[["","","","","primarily with Siemens SOMATOM\nCT series scanners, making V5med\nLung AI more flexible like ClearRead\nCT™. These differences do not impact\nthe safety and effectiveness of V5med\nLung AI."],["General Description","The V5med Lung AI is a software\nproduct designed to detect nodules in\nthe lungs. The detection model is\ntrained using a Deep Convolutional\nNeural Network (CNN) based\nalgorithm, enabling automatic\ndetection of lung nodules ranging\nfrom 4 to 30 mm in chest CT images.\nThe system integrates algorithm logic\nand database on the same server,\nensuring simplicity and ease of\nmaintenance. It accepts chest CT\nimages from a Picture Archiving and\nCommunication System (PACS),\nRadiological Information System\n(RIS), or directly from a CT scanner,\nanalyzes the images, and provides\noutput annotations regarding lung\nnodules.","The AVIEW Lung Nodule CAD is a\nsoftware product that detects nodules\nin the lung. The lung\nnodule detection model was trained\nby Deep Convolution Neural\nNetwork (CNN) based algorithm\nfrom the chest CT image. Automatic\ndetection of lung nodules of 3 to\n20mm in chest CT images.\nBy complying with DICOM\nstandards, this product can be linked\nwith the Picture Archiving and\nCommunication System (PACS) and\nprovides a separate user interface to\nprovide functions such as analyzing,\nidentifying, storing, and transmitting\nquantified values related to lung\nnodules. The CAD’s results could be\ndisplayed after the user’s first read,\nand the user could select or de-select\nthe mark provided by the CAD. The\ndevice’s performance was validated\nwith SIEMENS’ SOMATOM series\nmanufacturing. The device is\nintended to be used with a cleared\nAVIEW platform.","ClearRead CT is a dedicated post-\nprocessing application that\ngenerates a secondary vessel\nsuppressed Lung CT series with\nCADe marks and associated region\ndescriptors intended to aid the\nradiologist in the detection of\npulmonary nodules.","V5med Lung AI and AVIEW Lung\nNodule CAD both utilize Deep\nConvolutional Neural Network (CNN)\nbased algorithms for lung nodule\ndetection in chest CT images. However,\nV5med Lung AI supports a broader\nnodule detection range of 4 to 30 mm,\ncompared to AVIEW’s 3 to 20 mm,\nmaking it similar to ClearRead CT™,\nwhich also covers nodules from 5 - 20\nmm.Unlike AVIEW, which is\nvalidated with SIEMENS’ SOMATOM\nseries and intended to be used with a\ncleared AVIEW platform, V5med Lung\nAI does not restrict the scanner source\nor the use of non-contrast images,\naligning it more closely with ClearRead\nCT™ in terms of flexibility. These\ndifferences do not impact the safety and\neffectiveness of V5med Lung AI."],["Detection target(s)","Pulmonary nodules in\nscreening and diagnostic chest CT\nacquisitions.","Pulmonary nodules in\nnon-contrast chest CT\nacquisitions","Pulmonary nodules in\nchest CT acquisitions.","The detection targets of V5med Lung\nAI are similar to the detection targets of\nthe predicate devices."]],"caption_candidate":"V5med Lung AI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242919-p9-t0","doc_id":"K242919","page_num":9,"bbox":[40.82,82.82,813.7,465.58],"n_rows":10,"n_cols":5,"columns":["Nodule Characteristics","Diameter:\n• Pulmonary nodules 4 – 30 mm\nLocations:\n• Full range: central, peripheral","Diameter:\n• Pulmonary nodules 3 – 20 mm\nLocations:\n• Full range: central, peripheral\nContours:\n• Round, irregular","Diameter:\n• Pulmonary nodules 5 – 20 mm","Diameter:\n• The diameter range of V5med\nLung AI is similar to the\npredicate devices\nLocations:\n• Same as primary predicate"],"rows":[["Nodule Characteristics","Diameter:\n• Pulmonary nodules 4 – 30 mm\nLocations:\n• Full range: central, peripheral","Diameter:\n• Pulmonary nodules 3 – 20 mm\nLocations:\n• Full range: central, peripheral\nContours:\n• Round, irregular","Diameter:\n• Pulmonary nodules 5 – 20 mm","Diameter:\n• The diameter range of V5med\nLung AI is similar to the\npredicate devices\nLocations:\n• Same as primary predicate"],["Nodule Marking","A bounding box is provided around\nnodules","A bounding box is provided around\nnodules","A bounding box is provided around\nnodules","Same"],["Automatically locate\nand identify lung\nnodules","Yes","Yes","Yes","Same"],["Modifies the Original\nCT scan","No","No","Yes","Same as AVIEW Lung Nodule CAD."],["Image format","DICOM","DICOM","DICOM","Same"],["Hosting Platform","-","AVIEW","-","No specific hosting platform. Same as\ncleared ClearRead CT."],["Hosting Application","-","AVIEW LCS","-","No specific hosting application. Same\nas cleared ClearRead CT."],["Outputs","DICOM GSPS (Grayscale Softcopy\nPresentation State)","DICOM GSPS (Grayscale Softcopy\nPresentation State)\nXML (Coordinate of detected\nnodules)\nAble to view results\non AVIEW, AVIEW\nLCS viewer page","DICOM GSPS (Grayscale Softcopy\nPresentation State)","Similar to AVIEW Lung Nodule CAD\nbut lacks XML output and specific\nviewer capabilities of AVIEW.\nThe outputs of V5med Lung AI are\nsimilar to the outputs of the predicate\ndevices."],["Type of Scans","CT","CT","CT","Same"],["CT Scanners","Multi-vendor and multi-detector\nCT (MDCT) scanners\n(Siemens, GE, Philips, and\nToshiba)","Siemens SOMATOM CT\nScanners","Not Provided","V5med Lung AI does not restrict the\nbrand or specifications of the scanner,\nsame as ClearRead CT."]],"caption_candidate":"V5med Lung AI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242919-p11-t0","doc_id":"K242919","page_num":11,"bbox":[71.94,623.52,482.94,679.02],"n_rows":3,"n_cols":4,"columns":["","Unaided","Aided","Difference (95%CI)"],"rows":[["","Unaided","Aided","Difference (95%CI)"],["AUC","0.734","0.830","0.0959 (0.0586, 0.1332)"],["Reading Times (s)","113.0","115.9","-17.1 (-26.7, -9.0)"]],"caption_candidate":"concerns, it demonstrates substantial equivalence to the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p7-t0","doc_id":"K242925","page_num":7,"bbox":[66.86,275.6,553.18,581.62],"n_rows":3,"n_cols":4,"columns":["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],"rows":[["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],["","","Segmentation (K230082)",""],["Intended Use","MR Contour DL is intended\nto be used as a workflow\ntool for initial anatomy\nsegmentation of organs at\nrisk on MR images as an aid\nin radiation therapy\nplanning after user\nconfirmation.","Auto Segmentation is\nintended to be used as a\nworkflow tool for initial\nanatomy segmentation of\norgans at risk on CT images\nas an aid in radiation\ntherapy planning after\nuser confirmation.","Both the proposed device and the\npredicate device are intended to be\nused as a workflow tool for initial\nanatomy segmentation of organs at risk\nas an aid in radiation therapy planning\nafter user confirmation. The proposed\ndevice is intended for post-processing\nMR images, whereas the predicate is\nintended for post-processing of CT\nimages. All features and performance of\nthe proposed device have been verified\nand validated per GE HealthCare’s\nquality system. No safety and\neffectiveness issues were raised. In\naddition, the performance testing\nconducted on MR Contour DL\nsuccessfully demonstrate the devices\nperformance, particularly the anatomy\nsegmentation of organs at risk on MR\nimages. The intended use of the\nproposed device falls within the general\nintended use of the predicate device\nand do not create a new Intended Use."]],"caption_candidate":"Table 1: Comparison of Intended Use between Proposed Device and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p7-t1","doc_id":"K242925","page_num":7,"bbox":[66.86,615.52,553.18,739.45],"n_rows":3,"n_cols":4,"columns":["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],"rows":[["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],["","","Segmentation (K230082)",""],["Indications\nfor Use","MR Contour DL generates a\nRadiotherapy Structure Set\n(RTSS) DICOM with\nsegmented organs at risk\nwhich can be used by\ntrained medical\nprofessionals. It is intended\nto aid in radiation therapy","Auto Segmentation\ngenerates a Radiotherapy\nStructure Set (RTSS)\nDICOM with segmented\norgans at risk which can\nbe used by dosimetrists,\nmedical physicists, and\nradiation oncologists as","Substantially Equivalent – Both the\nproposed device and the predicate\ndevice are indicated to generate a\nRadiotherapy Structure Set (RTSS)\nDICOM with segmented organs at risk.\nBoth the proposed device and the\npredicate device are:\n• Used by trained medical"]],"caption_candidate":"Table 2: Comparison of Indications for Use between Proposed Device and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p8-t0","doc_id":"K242925","page_num":8,"bbox":[66.85,94.38,553.23,535.78],"n_rows":3,"n_cols":4,"columns":["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],"rows":[["Items","Proposed MR Contour DL","Predicate: Auto","Comparison"],["","","Segmentation (K230082)",""],["","planning by generating\ninitial contours to\naccelerate workflow for\nradiation therapy planning.\nIt is the responsibility of\nthe user to verify the\nprocessed output contours\nand user-defined labels for\neach organ at risk and\ncorrect the contours/labels\nas needed. MR Contour DL\nis intended to be used with\nimages acquired on MR\nscanners, in adult patients.","initial contours to\naccelerate workflow for\nradiation therapy\nplanning. It is the\nresponsibility of the user\nto verify the processed\noutput contours and user-\ndefined labels for each\norgan at risk and correct\nthe contours/labels as\nneeded. Auto\nSegmentation may be\nused with images acquired\non CT scanners, in adult\npatients.","professionals, including the\nprofessions listed by the\npredicate device.\n• Intended to aid in radiation\ntherapy planning by generating\ninitial contours to accelerate\nworkflow for radiation therapy\nplanning.\n• Declare that it is the\nresponsibility of the user to\nverify the processed output\ncontours and user-defined\nlabels for each organ at risk and\nto correct the contours/labels\nas needed.\nMR Contour DL is intended to be used\nwith images acquired on MR scanners in\nadult patients while the predicate\ndevice is intended to be used on images\nacquired on CT scanners in adult\npatients.\nAll features and performance of the\nproposed device have been verified and\nvalidated per GEHC’s quality system. No\nsafety and effectiveness issues were\nraised. Additionally, the testing\nperformed on MR Contour DL\ndemonstrates the devices performance,\nparticularly the anatomy segmentation\nof organs at risk on MR images. The\nindications for use for the proposed\ndevice is substantially equivalent to that\nof the predicate."]],"caption_candidate":"510(k) Premarket Notification Submission – MR Contour DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p8-t1","doc_id":"K242925","page_num":8,"bbox":[66.85,592.36,553.23,696.04],"n_rows":6,"n_cols":6,"columns":["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],"rows":[["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],["","Contour DL","Auto","AutoContour","Contour",""],["","","Segmentation","Model RADAC","ProtégéAI",""],["","","(K230082)","V2 (K220598)","(K213976)",""],["Product\nCode","QKB","QKB","QKB","QKB","Identical"],["Patient\nPopulation","Adult only","Adult only","Adult only","Adult only","Identical"]],"caption_candidate":"devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p9-t0","doc_id":"K242925","page_num":9,"bbox":[66.81,94.38,553.29,730.32],"n_rows":10,"n_cols":6,"columns":["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],"rows":[["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],["","Contour DL","Auto","AutoContour","Contour",""],["","","Segmentation","Model RADAC","ProtégéAI",""],["","","(K230082)","V2 (K220598)","(K213976)",""],["Intended\nUsers","Radiologists,\nRadiation\noncologists,\nDosimetrists,\nand Medical\nPhysicists","Radiation\nOncologists,\nDosimetrists,\nand Medical\nPhysicists","Medical\nProfessionals\nwho do\nradiation\ntherapy\ntreatment\nplanning","Trained\nMedical\nProfessionals","Substantially Equivalent – both the\nproposed device and the predicate\ndevice are intended for trained\nmedical professionals in the\nradiation oncology field"],["Algorithm","Deep Learning","Deep Learning","Machine\nLearning/Dee\np Learning","Machine\nLearning","Substantially Equivalent – both the\nproposed device and the predicate\ndevice contain deep learning auto\nsegmentation algorithms"],["Compatible\nModality","MR images","CT images","CT images and\nMR images","CT images and\nMR images","Substantially Equivalent – While the\npredicate device is only intended to\nsegment CT Images, both reference\ndevices are intended to segment\nboth CT and MR images. Reference 1\nuses DICOM-compliant image data\n(CT or MR) to automatically contour\nvarious structures of interest for RT\nplanning. Reference device 2 is\nintended to assist in the automated\nprocessing of digital medical images\nof modalities CT and MR to create\ncontours using machine learning\nalgorithms. The proposed device\naligns with the performance of\ncommercially available products on\nthe market, specifically Reference\nDevices 1 and 2."],["OAR\nSegmentati\non\nAnatomic\nRegions","Head/neck\nPelvis","Head/neck\nThorax\nAbdomen\nPelvis","Head/neck\nThorax\nAbdomen\npelvis","Head/neck\nProstate\nThorax\nAbdomen\nLungs and\nLiver","Substantially Equivalent – Both the\npredicate and proposed device cover\nthe Head/neck and Pelvis regions."],["Workflow","Automated","Automated","Manual and\nAutomated","Automated","Identical"],["User\nInterface","Automated\nexecution of\nthe software\nwith no user\ninteraction,\nother than\nconfiguration\nsettings.\nGenerated","Automated\nexecution of\nthe software\nwith no user\ninteraction,\nother than\nconfiguration\nsettings.\nGenerated","Contains both\nan automated\nprocessing\ncomponent,\nData\nVisualization,\nand Graphical\nUser Interface","Designed for\nuse in the\nprocessing of\nmedical\nimages and\noperates on\nWindows,\nMac, and\nLinux","Identical"]],"caption_candidate":"510(k) Premarket Notification Submission – MR Contour DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p10-t0","doc_id":"K242925","page_num":10,"bbox":[66.83,94.38,553.27,630.76],"n_rows":7,"n_cols":6,"columns":["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],"rows":[["Items","Proposed MR","Predicate:","Reference 1:","Reference 2:","Comparison"],["","Contour DL","Auto","AutoContour","Contour",""],["","","Segmentation","Model RADAC","ProtégéAI",""],["","","(K230082)","V2 (K220598)","(K213976)",""],["","contours are\nautomatically\ntransmitted to\nreview\nworkstation(s)\nsupporting\nRTSS objects\nfor review and\nediting, as\nneeded.","contours are\nautomatically\ntransmitted to\nreview\nworkstation(s)\nsupporting\nRTSS objects\nfor review and\nediting, as\nneeded.","","computer\nsystems.\nDeployed on a\nremote server\nusing the\nMIMcloud\nservice for\ndata\nmanagement\nand transfer;\nor locally on\nthe\nworkstation or\nserver running\nMIM software.",""],["Compatible\nScanner\nModels","Compatible\non MR\nScanners,\nDICOM\ncompliance\nrequired.","No limitation\non scanner\nmodel,\nDICOM\ncompliance\nrequired.","No limitation\non scanner\nmodel,\nDICOM\ncompliance\nrequired","No limitation\non scanner\nmodel,\nDICOM\ncompliance\nrequired","Substantially Equivalent – The\nproposed device is compatible with\nMR scanner models and DICOM\ncompliance is required. The\nproposed device has only been\ntested on GEHC data. If a non-GEHC\nMR image is sent to MR Contour DL,\na notice message will display after\ncontouring.\nThe predicate device has no\nlimitation on scanner models and\nDICOM compliance is also required.\nThis difference does not raise any\nnew safety or effectiveness\nconcerns."],["Deployment\nPlatform","Server-based\ndeployment","Server-based\ndeployment","Cloud and\nserver-based\ndeployment","Cloud-based\ndeployment\nand locally\ndeployed (or\ninstalled)","Identical – Both the proposed\ndevice and the predicate device\nare deployed on Edison HealthLink\n(EHL), GE Healthcare’s\ncomputational platform providing\nhosting infrastructure and services."]],"caption_candidate":"510(k) Premarket Notification Submission – MR Contour DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242925-p13-t0","doc_id":"K242925","page_num":13,"bbox":[40.62,135.72,571.44,673.05],"n_rows":39,"n_cols":9,"columns":["","","Ground-truth","","","","","Reader-study",""],"rows":[["","","Ground-truth","","","","","Reader-study",""],["Organ","Anatomy\nregion","Number\nof cases","DSC\nAcceptance\ncriteria","DSC\nMEAN","HD95\nMEAN","HD95 value\ncompared\nto predicate\ndevice","Number\nof cases","Likert\nscore\nMEAN"],["bladder","pelvis","53","80%","92.4%","4.7","Improved","40","3.7"],["bowel-bag","pelvis","40","80%","90.3%","13.3","N/A","40","3.3"],["brainstem","head/neck","50","65%","94.3%","2.1","Improved","30","4.0"],["chiasm","head/neck","50","50%","72.7%","2.5","Improved","30","3.5"],["eye-L","head/neck","50","65%","95.5%","1.4","Improved","30","4.3"],["eye-R","head/neck","50","65%","95.4%","1.4","Improved","30","4.3"],["femoral-head-L","pelvis","53","80%","93.7%","4.5","Not-Improved","40","4.2"],["femoral-head-R","pelvis","51","80%","93.5%","5.3","Not-Improved","40","4.1"],["head-body","head/neck","50","80%","99.3%","1.6","Improved","30","3.8"],["inner-ear-L","head/neck","50","50%","88.4%","1.4","N/A","30","4.5"],["inner-ear-R","head/neck","50","50%","88.3%","1.3","N/A","30","4.4"],["lacrimal-L","head/neck","50","50%","67.4%","4.2","Equivalent","30","4.0"],["lacrimal-R","head/neck","50","50%","65.6%","4.4","Equivalent","30","4.0"],["larynx-G","head/neck","49","50%","67.1%","3.9","N/A","30","3.5"],["larynx-SG","head/neck","50","65%","85.3%","4.9","N/A","30","3.8"],["lens-L","head/neck","50","50%","86.7%","1.2","Improved","30","4.4"],["lens-R","head/neck","50","50%","86.1%","1.3","Improved","30","4.5"],["mandible","head/neck","50","65%","89.8%","2.8","Equivalent","30","3.6"],["optic-nerve-L","head/neck","50","50%","73.4%","2.9","Equivalent","30","3.7"],["optic-nerve-R","head/neck","50","50%","72.3%","2.6","Improved","30","3.7"],["oral-cavity","head/neck","50","65%","92.5%","3.7","Improved","30","3.7"],["parotid-L","head/neck","50","65%","85.9%","4.9","Improved","30","3.8"],["parotid-R","head/neck","50","65%","84.6%","6.0","Improved","30","3.7"],["PCM-inf","head/neck","44","50%","53.6%","7.0","Not-Improved","30","3.5"],["PCM-mid","head/neck","50","50%","60.1%","6.1","Equivalent","30","3.8"],["PCM-sup","head/neck","50","50%","57.6%","6.8","Improved","30","3.4"],["pelvis-body","pelvis","50","80%","97.5%","10.0","Not-Improved","40","4.1"],["penile-bulb","pelvis","39","50%","67.5%","7.3","N/A","30","3.3"],["pituitary","head/neck","50","50%","73.7%","2.5","Equivalent","30","3.6"],["prostate","pelvis","43","65%","83.0%","5.6","Equivalent","30","3.0"],["rectum","pelvis","53","65%","79.6%","19.8","N/A","40","3.6"],["seminal-vesicles","pelvis","43","65%","69.2%","7.3","N/A","30","3.3"],["spinal-cord","head/neck","50","65%","90.3%","2.2","Improved","30","4.1"],["submandibular-L","head/neck","49","65%","86.4%","3.4","Equivalent","30","3.9"],["submandibular-R","head/neck","49","65%","85.4%","3.3","Equivalent","30","3.9"],["urethra","pelvis","43","50%","35.8%","9.5","N/A","30","3.4"],["whole-brain","head/neck","50","80%","98.8%","1.8","Improved","30","3.7"]],"caption_candidate":"Distance).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p5-t0","doc_id":"K242994","page_num":5,"bbox":[86.24,373.16,523.08,548.35],"n_rows":7,"n_cols":2,"columns":["510(k) Number","K242994"],"rows":[["510(k) Number","K242994"],["Trade/Device/Model Name","OncoStudio / OS-01"],["Device Classification Name","Medical Image Management and Processing System"],["Regulation Number","21 CFR 892.2050"],["Classification Product Code","QKB"],["Device Class","Class II"],["510(k) Review Panel","Radiology"]],"caption_candidate":"3. Trade Name, Common Name, Classification [21 CFR 807.92(a)(2)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p6-t0","doc_id":"K242994","page_num":6,"bbox":[86.24,166.16,523.08,341.35],"n_rows":7,"n_cols":2,"columns":["510(k) Number","K230685"],"rows":[["510(k) Number","K230685"],["Trade/Device/Model Name","AutoContour Model RADAC V3"],["Device Classification Name","Medical Image Management And Processing System"],["Regulation Number","21 CFR 892.2050"],["Classification Product Code","QKB"],["Device Class","Class II"],["510(k) Review Panel","Radiology"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p6-t1","doc_id":"K242994","page_num":6,"bbox":[86.24,381.48,523.08,556.75],"n_rows":7,"n_cols":2,"columns":["510(k) Number","K232899"],"rows":[["510(k) Number","K232899"],["Trade/Device/Model Name","AI-Rad Companion Organs RT"],["Device Classification Name","Medical Image Management And Processing System"],["Regulation Number","21 CFR 892.2050"],["Classification Product Code","QKB"],["Device Class","Class II"],["510(k) Review Panel","Radiology"]],"caption_candidate":"Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p8-t0","doc_id":"K242994","page_num":8,"bbox":[50.99,219.72,542.02,762.05],"n_rows":18,"n_cols":11,"columns":["","","Subject Device","","","Predicate Device","","","Reference Device1","","SE\nNote"],"rows":[["","","Subject Device","","","Predicate Device","","","Reference Device1","","SE\nNote"],["Item","OncoStudio","","","","AutoContour Model RADAC","","","AI-Rad Companion","",""],["","","","","","V3","","","Organs RT","",""],["","Medical Image Management\nAnd Processing System","","","Medical Image\nManagement And\nProcessing System","","","Medical Image\nManagement And\nProcessing System","","","-"],["Regulation","","","","","","","","","",""],["Name","","","","","","","","","",""],["","","","","","","","","","",""],["Regulation","21 CFR 892.2050","","","21 CFR 892.2050","","","21 CFR 892.2050","","","-"],["Number","","","","","","","","","",""],["Product","QKB","","","QKB","","","QKB","","","-"],["Code","","","","","","","","","",""],["Class","II","","","II","","","II","","","-"],["510k","K242994","","","K230685","","","K232899","","","-"],["Number","","","","","","","","","",""],["","OncoStudio provides deep-\nlearning-based automatic\ncontouring to organs at risk\nin DICOM-RT format from CT\nimages. This software could\nbe used as an initial\ncontouring for the clinicians\nto be confirmed by the\nradiation oncology\ndepartment for treatment\nplanning or other professions\nwhere a segmented mask of\norgans is needed.\n• Deep learning\ncontouring from Head &\nNeck, Thorax, Abdomen,\nand Pelvis\n• Generates DICOM-RT\nstructure of contoured\nobjects\n• Manual Contouring\n• Receive, transmit, store,","","","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in\npreparation for radiation\ntherapy treatment\nplanning","","","AI-Rad Companion\nOrgans RT is a post-\nprocessing software\nintended to\nautomatically\ncontour DICOM CT\nand MR predefined\nstructures using\ndeep-leaming-based\nalgorithms. Contours\nthat are generated\nby AI-Rad\nCompanion Organs\nRT may be used as\ninput for clinical\nworkflows including\nexternal beam\nradiation therapy\ntreatment planning.\nAI-Rad Companion\nOrgans RT must be\nused in conjunction\nwith appropriate","","","Same"],["Indication","","","","","","","","","",""],["for Use","","","","","","","","","",""],["","","","","","","","","","",""]],"caption_candidate":"[Table 1. Comparison of Proposed Device to Predicate Device and Reference Device]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p9-t0","doc_id":"K242994","page_num":9,"bbox":[50.98,85.6,542.04,761.73],"n_rows":6,"n_cols":7,"columns":["","retrieve, display, and process\nmedical images and DICOM\nobjects","","","","software such as\nTreatment Planning\nSystems and\nInteractive\nContouring\napplications, to\nreview, edit, and\naccept contours\ngenerated by AI-Rad\nCompanion Organs\nRT. The output of AI-\nRad Companion\nOrgans RT are\nintended to be used\nby trained medical\nprofessionals. The\nsoftware is not\nintended to\nautomatically detect\nor contour lesions.",""],"rows":[["","retrieve, display, and process\nmedical images and DICOM\nobjects","","","","software such as\nTreatment Planning\nSystems and\nInteractive\nContouring\napplications, to\nreview, edit, and\naccept contours\ngenerated by AI-Rad\nCompanion Organs\nRT. The output of AI-\nRad Companion\nOrgans RT are\nintended to be used\nby trained medical\nprofessionals. The\nsoftware is not\nintended to\nautomatically detect\nor contour lesions.",""],["","• A_Aorta\n• A_Carotid_L\n• A_Carotid_R\n• A_Coronary_R\n• A_Iliac_L\n• A_Iliac_R\n• A_LAD\n• A_Subclavian_L\n• A_Subclavian_R\n• Anus\n• Atrium_L\n• Atrium_R\n• Autochthon_L\n• Autochthon_R\n• Bag_Bowel\n• Bladder\n• Bone_Mandible\n• Bowel_Large\n• Bowel_Small\n• BrachialPlex_L\n• BrachialPlex_R\n• Brachiocephalic_Trunk\n• Brain\n• Brainstem\n• Breast_L\n• Breast_R","• LN_Sclav_L_RTOG\n• LN_Sclav_R_ESTRO\n• LN_Sclav_R_RTOG\n• Larynx\n• Lens_L\n• Lens_R\n• Liver\n• Lobe_Temporal_L\n• Lobe_Temporal_R\n• Lung_L\n• Lung_LLL\n• Lung_LUL\n• Lung_R\n• Lung_RLL\n• Lung_RML\n• Lung_RUL\n• OpticChiasm\n• OpticNrv_L\n• OpticNrv_R\n• Pancreas\n• Parotid_L\n• Parotid_R\n• Pharynx\n• Pituitary\n• Prostate\n• Rectum","• A_Aorta\n• A_Aorta_Asc\n• A_Aorta_Dsc\n• A_LAD\n• A_Pulmonary\n• Bladder\n• Bladder_F\n• Bone_Ilium_L\n• Bone_Ilium_R\n• Bone_Mandible\n• Bone_Pelvic\n• Bone_Skull\n• Bone_Sternum\n• Bowel\n• Bowel_Bag\n• Bowel_Large\n• Bowel_Small\n• BrachialPlex_L\n• BrachialPlex_R\n• Brain\n• Brainstem\n• Breast_L\n• Breast_R\n• Bronchus\n• BuccalMucosa\n• Carina","• LN_Ax_L\n• LN_Ax_L1_L\n• LN_Ax_L1_R\n• LN_Ax_L2_L\n• LN_Ax_L2_L3_L\n• LN_Ax_L2_L3_R\n• LN_Ax_L2_R\n• LN_Ax_L3_L\n• LN_Ax_L3_R\n• LN_Ax_R\n• LN_IMN_L\n• LN_IMN_R\n• LN_IMN_RC_L\n• LN_IMN_RC_R\n• LN_Inguinofem_L\n• LN_Inguinofem_R\n• LN_Neck_IA\n• LN_Neck_IB-V_L\n• LN_Neck_IB-V_R\n• LN_Neck_II_L\n• LN_Neck_II_R\n• LN_Neck_II-IV_L\n• LN_Neck_II-IV_R\n• LN_Neck_II-V_L\n• LN_Neck_II-V_R\n• LN_Neck_III_L","(166 OARs)\nFull list of OAR is not provided","Differ\nent"],["Regions of","","","","","",""],["Interest(R","","","","","",""],["OIs)","","","","","",""],["","","","","","",""]],"caption_candidate":"K242994","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p10-t0","doc_id":"K242994","page_num":10,"bbox":[101.4,93.28,379.79,757.12],"n_rows":98,"n_cols":7,"columns":["•","Bronchus_L","•","Rib01_L","• CaudaEquina","•","LN_Neck_III_R"],"rows":[["•","Bronchus_L","•","Rib01_L","• CaudaEquina","•","LN_Neck_III_R"],["","","","","","",""],["•","Bronchus_R","•","Rib01_R","• Cavity_Oral","•","LN_Neck_IV_L"],["","","","","","",""],["•","CaudaEquina","•","Rib02_L","• Cavity_Oral_Ext","•","LN_Neck_IV_R"],["","","","","","",""],["•","Cavity_Oral","•","Rib02_R","• Chestwall_L","•","LN_Neck_V_L"],["","","","","","",""],["•","Clavicle_L","•","Rib03_L","• Chestwall_OAR","•","LN_Neck_V_R"],["","","","","","",""],["•","Clavicle_R","•","Rib03_R","• Chestwall_R","•","LN_Neck_VIA"],["","","","","","",""],["•","Cochlea_L","•","Rib04_L","• Chestwall_RC_L","•","LN_Neck_VIIA_L"],["","","","","","",""],["•","Cochlea_R","•","Rib04_R","• Chestwall_RC_R","•","LN_Neck_VIIA_R"],["","","","","","",""],["•","Colon","•","Rib05_L","• Cochlea_L","•","LN_Neck_VIIB_L"],["","","","","","",""],["•","Kidney_Cortex_L","•","Rib05_R","• Cochlea_R","•","LN_Neck_VIIB_R"],["","","","","","",""],["•","Kidney_Cortex_R","•","Rib06_L","• Colon_Sigmoid","•","LN_Paraaortic"],["","","","","","",""],["•","Costal_Cartilages","•","Rib06_R","• Cornea_L","•","LN_Pelvics"],["","","","","","",""],["•","Duodenum","•","Rib07_L","• Cornea_R","•","LN_Pelvic_NRG"],["","","","","","",""],["•","Esophagus","•","Rib07_R","• Duodenum","•","LN_Sclav_L"],["","","","","","",""],["•","Eye_L","•","Rib08_L","• Ear_Internal_L","•","LN_Sclav_R"],["","","","","","",""],["•","Eye_R","•","Rib08_R","• Ear_Internal_R","•","LN_Sclav_RADCOMP_L"],["","","","","","",""],["•","Femur_Head_L","•","Rib09_L","• Esophagus","•","LN_Sclav_RADCOMP_R"],["","","","","","",""],["•","Femur_Head_R","•","Rib09_R","• External","•","Lobe_Temporal_L"],["","","","","","",""],["•","Femur_L","•","Rib10_L","• Eye_L","•","Lobe_Temporal_R"],["","","","","","",""],["•","Femur_R","•","Rib10_R","• Eye_R","•","Lung_L"],["","","","","","",""],["•","Gallbladder","•","Rib11_L","• Femur_Head_L","•","Lung_R"],["","","","","","",""],["•","Glnd_Adrenal_L","•","Rib11_R","• Femur_Head_R","•","Macula_L"],["","","","","","",""],["•","Glnd_Adrenal_R","•","Rib12_L","• Femur_L","•","Macula_R"],["","","","","","",""],["•","Glnd_Submand_L","•","Rib12_R","• Femur_R","•","Marrow_Ilium_L"],["","","","","","",""],["•","Glnd_Submand_R","•","Sacrum","• Femur_RTOG_L","•","Marrow_Ilium_R"],["","","","","","",""],["•","Glnd_Thyroid","•","Scapula_L","• Femur_RTOG_R","•","Musc_Constrict"],["","","","","","",""],["•","Gluteus_Maximus_L","•","Scapula_R","• GallBladder","•","Nipple_L"],["","","","","","",""],["•","Gluteus_Maximus_R","•","Colon_Sigmoid","• Genitals_F","•","Nipple_R"],["","","","","","",""],["•","Gluteus_Medius_L","•","Skull","• Genitals_M","•","OpticChiasm"],["","","","","","",""],["•","Gluteus_Medius_R","•","SpinalCord","• Glnd_Lacrimal_L","•","OpticNrv_L"],["","","","","","",""],["•","Gluteus_Minimus_L","•","Spleen","• Glnd_Lacrimal_R","•","OpticNrv_R"],["","","","","","",""],["•","Gluteus_Minimus_R","•","Sternum","• Glnd_Submand_L","•","Pancreas"],["","","","","","",""],["•","Heart","•","Stomach","•","•","Parotid_L"],["","","","","","",""],["","","","","Glnd_Submand_R","",""],["•","Hip_L","•","Trachea","","•","Parotid_R"],["","","","","","",""],["","","","","• Glnd_Thyroid","",""],["•","Hip_R","•","VB_C1","","•","PenileBulb"],["","","","","","",""],["","","","","• HDR_Cylinder","",""],["•","Hippocampus_L","•","VB_C2","","•","Pericardium"],["","","","","","",""],["","","","","• Heart","",""],["•","Hippocampus_R","•","VB_C3","","•","Pituitary"],["","","","","","",""],["","","","","• Hippocampus_L","",""],["•","Humerus_L","•","VB_C4","","•","Prostate"],["","","","","","",""],["","","","","• Hippocampus_R","",""],["•","Humerus_R","•","VB_C5","","•","Rectum"],["","","","","","",""],["","","","","• Humerus_L","",""],["•","Iliopsoas_L","•","VB_C6","","•","Rectum_F"],["","","","","","",""],["","","","","• Humerus_R","",""],["•","Iliopsoas_R","•","VB_C7","","•","Retina_L"],["","","","","","",""],["","","","","• Kidney_L","",""],["•","Joint_TM_L","•","VB_L1","","•","Retina_R"],["","","","","","",""],["","","","","• Kidney_R","",""],["•","Joint_TM_R","•","VB_L2","","•","Rib"],["","","","","","",""],["","","","","• Kidney_Outer_L","",""],["•","Kidney_L","•","VB_L3","","•","Rib_L"]],"caption_candidate":"• Bronchus_L • Rib01_L • CaudaEquina • LN_Neck_III_R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K242994-p11-t0","doc_id":"K242994","page_num":11,"bbox":[50.91,85.56,542.04,763.37],"n_rows":5,"n_cols":7,"columns":["","• Kidney_R\n• LN_Ax_L1_L\n• LN_Ax_L1_R\n• LN_Ax_L2_L\n• LN_Ax_L2_R\n• LN_Ax_L3_L\n• LN_Ax_L3_R\n• LN_IMN_L\n• LN_IMN_R\n• LN_Neck_IA\n• LN_Neck_IB_L\n• LN_Neck_IB_R\n• LN_Neck_III_L\n• LN_Neck_III_R\n• LN_Neck_II_L\n• LN_Neck_II_R\n• LN_Neck_IVA_L\n• LN_Neck_IVA_R\n• LN_Neck_IVB_L\n• LN_Neck_IVB_R\n• LN_Neck_VA_L\n• LN_Neck_VA_R\n• LN_Neck_VBC_L\n• LN_Neck_VBC_R\n• LN_Sclav_L_ESTRO","• VB_L4\n• VB_L5\n• VB_S1\n• VB_T01\n• VB_T02\n• VB_T03\n• VB_T04\n• VB_T05\n• VB_T06\n• VB_T07\n• VB_T08\n• VB_T09\n• VB_T10\n• VB_T11\n• VB_T12\n• V_Brachioceph_L\n• V_Brachioceph_R\n• V_Iliac_L\n• V_Iliac_R\n• V_Portal_And_Splenic\n• V_Pulmonary\n• V_Venacava_I\n• V_Venacava_S\n• Ventricle_L\n• Ventricle_R","• Kidney_Outer_R\n• Larynx\n• Larynx_Glottic\n• Larynx_NRG\n• Larynx_SG\n• Lens_L\n• Lens_R\n• Lips\n• Liver","• Rib_R\n• SeminalVes\n• SpinalCanal\n• SpinalCord\n• Spleen\n• Stomach\n• Trachea\n• UteroCervix\n• V_Venacava_I\n• V_Venacava_S\n• VB\n• VB_C1\n• VB_C2\n• VB_C3\n• VB_C4\n• VB_C5\n• VB_C6\n• VB_C7\n• VB_L1\n• VB_L2\n• VB_L3\n• VB_L4\n• VB_L5\n• VB_T01\n• VB_T02\n• VB_T03\n• VB_T04\n• VB_T05\n• VB_T06\n• VB_T07\n• VB_T08\n• VB_T09\n• VB_T10\n• VB_T11\n• VB_T12","",""],"rows":[["","• Kidney_R\n• LN_Ax_L1_L\n• LN_Ax_L1_R\n• LN_Ax_L2_L\n• LN_Ax_L2_R\n• LN_Ax_L3_L\n• LN_Ax_L3_R\n• LN_IMN_L\n• LN_IMN_R\n• LN_Neck_IA\n• LN_Neck_IB_L\n• LN_Neck_IB_R\n• LN_Neck_III_L\n• LN_Neck_III_R\n• LN_Neck_II_L\n• LN_Neck_II_R\n• LN_Neck_IVA_L\n• LN_Neck_IVA_R\n• LN_Neck_IVB_L\n• LN_Neck_IVB_R\n• LN_Neck_VA_L\n• LN_Neck_VA_R\n• LN_Neck_VBC_L\n• LN_Neck_VBC_R\n• LN_Sclav_L_ESTRO","• VB_L4\n• VB_L5\n• VB_S1\n• VB_T01\n• VB_T02\n• VB_T03\n• VB_T04\n• VB_T05\n• VB_T06\n• VB_T07\n• VB_T08\n• VB_T09\n• VB_T10\n• VB_T11\n• VB_T12\n• V_Brachioceph_L\n• V_Brachioceph_R\n• V_Iliac_L\n• V_Iliac_R\n• V_Portal_And_Splenic\n• V_Pulmonary\n• V_Venacava_I\n• V_Venacava_S\n• Ventricle_L\n• Ventricle_R","• Kidney_Outer_R\n• Larynx\n• Larynx_Glottic\n• Larynx_NRG\n• Larynx_SG\n• Lens_L\n• Lens_R\n• Lips\n• Liver","• Rib_R\n• SeminalVes\n• SpinalCanal\n• SpinalCord\n• Spleen\n• Stomach\n• Trachea\n• UteroCervix\n• V_Venacava_I\n• V_Venacava_S\n• VB\n• VB_C1\n• VB_C2\n• VB_C3\n• VB_C4\n• VB_C5\n• VB_C6\n• VB_C7\n• VB_L1\n• VB_L2\n• VB_L3\n• VB_L4\n• VB_L5\n• VB_T01\n• VB_T02\n• VB_T03\n• VB_T04\n• VB_T05\n• VB_T06\n• VB_T07\n• VB_T08\n• VB_T09\n• VB_T10\n• VB_T11\n• VB_T12","",""],["","Local deployment on\nWindows","","Windows based .NET\nfront-end application that\nalso serves as agent\nUploader supporting\nMicrosoft Windows 10 (64-\nbit) and Microsoft\nWindows Server 2016.\nCloud-based Server based\nautomatic contouring\napplication compatible","","Edge & Cloud\nDeployment","Differ\nent"],["Operating","","","","","",""],["System","","","","","",""],["","","","","","",""]],"caption_candidate":"K242994","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K242994-p12-t0","doc_id":"K242994","page_num":12,"bbox":[50.99,85.6,542.04,767.57],"n_rows":20,"n_cols":5,"columns":["","","with Linux. Windows\npython-based automatic\ncontouring application\nsupporting Microsoft\nWindows 10 (64-bit) and\nMicrosoft Windows Server\n2016.","",""],"rows":[["","","with Linux. Windows\npython-based automatic\ncontouring application\nsupporting Microsoft\nWindows 10 (64-bit) and\nMicrosoft Windows Server\n2016.","",""],["Image","DICOM","DICOM","DICOM","Same"],["Format","","","",""],["","1) Deep learning contouring\nfrom Head & Neck, Thorax,\nAbdomen, and Pelvis\n2) Generates DICOM-RT\nstructure of contoured\nobjects\n3) Manual Contouring\n4) Receive, transmit, store,\nretrieve, display, and process\nmedical images and DICOM\nobjects","1) Automatically contour\nvarious structures of\ninterest for radiation\ntherapy treatment\nplanning\n2) Allow the user to review\nand modify the resulting\ncontours\n3) Generate DICOM-\ncompliant structure set\ndata the can be imported\ninto a radiation therapy\ntreatment planning system","CT or MR series of\nimages serve as\ninput for AI-Rad\nCompanion Organs\nRT and are acquired\nas part of a typical\nscanner acquisition.\nOnce processed by\nthe AI algorithms,\ngenerated contours\nin DICOM-RTSTRUCT\nformat are reviewed\nin a confirmation\nwindow, allowing\nclinical user to\nconfirm or reject the\ncontours before\nsending to the target\nsystem. Optionally,\nthe user may select\nto directly transfer\nthe contours to a\nconfigurable DICOM\nnode","Same"],["General","","","",""],["Functions","","","",""],["","","","",""],["Algorithm","Deep Learning","Deep Learning","Deep Learning","Same"],["","CT Images. DICOM\nRTSTRUCT for output","CT or MR input for\ncontouring or\nregistration/fusion. PET/CT\ninput for\nregistration/fusion only.\nDICOM RTSTRUCT for\noutput","CT & MR Images","Equiv\nalent"],["Compatibl","","","",""],["e Modality","","","",""],["","","","",""],["","Head & Neck, Thorax,\nAbdomen, Pelvis","Head and Neck, Thorax,\nAbdomen, Pelvis","Head & Neck,\nThorax, Abdomen &\nPelvis Head & Neck\nlymph nodes","Same"],["Segmentat","","","",""],["ion of","","","",""],["Organ","","","",""],["","","","",""],["","Automatically processes input\nimage data contour organs","Automatically contour\nvarious structures of","AI-Rad Companion\nOrgans RT","Same"],["Workflow","","","",""],["","","","",""]],"caption_candidate":"K242994","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p5-t0","doc_id":"K243005","page_num":5,"bbox":[72.0,36.24,539.76,71.04],"n_rows":2,"n_cols":3,"columns":["","FDA 510(k) Summary",""],"rows":[["","FDA 510(k) Summary",""],["","","Rev. 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p6-t0","doc_id":"K243005","page_num":6,"bbox":[72.0,36.24,539.76,71.04],"n_rows":2,"n_cols":3,"columns":["","FDA 510(k) Summary",""],"rows":[["","FDA 510(k) Summary",""],["","","Rev. 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p7-t0","doc_id":"K243005","page_num":7,"bbox":[72.0,36.24,538.32,71.04],"n_rows":2,"n_cols":3,"columns":["","FDA 510(k) Summary",""],"rows":[["","FDA 510(k) Summary",""],["","","Rev. 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p7-t1","doc_id":"K243005","page_num":7,"bbox":[79.2,99.24,538.32,675.24],"n_rows":24,"n_cols":3,"columns":["Feature","SUBJECT:\nAudaxCeph Cephalogram\nAnalysis Software","PREDICATE:\nCephX Cephalometric Analysis\nSoftware"],"rows":[["Feature","SUBJECT:\nAudaxCeph Cephalogram\nAnalysis Software","PREDICATE:\nCephX Cephalometric Analysis\nSoftware"],["510(k) Number","","K231396"],["Intended Use","Designed for use by\nspecialized dental practices\nfor storing and presenting\npatient images and assisting\nin treatment planning.\nResults produced by the\nsoftware's treatment planning\ntools are dependent on the\ninterpretation of trained and\nlicensed practitioners.","Indicated for use by dentists who\nprovide orthodontic treatment for\nimage analysis, simulation,\nprofilogram, VTO (Visual\nTreatment Objective), and patient\nconsultation. Results produced by\nthe software’s diagnostic,\ntreatment planning and simulation\ntools are dependent on the\ninterpretation of trained and\nlicensed practitioners or dentists.\nThe device is only for use on\npatients 14 years old and above."],["Product Code","QIH","QIH"],["Type of Use (Rx /OTC)","Rx","Rx"],["User","Orthodontic, oral maxillofacial\nsurgery, and dental-specialty\npractices.","Orthodontic, oral maxillofacial\nsurgery, and dental-specialty\npractices."],["Platform","IBM-compatible PC or PC\nnetwork","IBM-compatible PC or PC\nnetwork"],["Processor","x64-based processor or\nhigher","x64-based processor or higher"],["Software Access","Local PC hosted or cloud\nhosted","Cloud-hosted"],["Materials, Additives, &\nFinishing Agents","N/A, software-only device","N/A, software-only device"],["Energy Delivery","N/A, software-only device","N/A, software-only device"],["Anatomical Area","Dental, Maxilla, Mandible","Dental, Maxilla, Mandible"],["Device Features","",""],["2D Image Acquisition/Digitizing\n(radiological/image capture\ninterface/controls)","No","No"],["2D Automatic Tracing\nw/Clinician Review","Yes","Yes"],["2D Image Measurements","Yes","Yes"],["2D Image Superimposition","Yes","Yes"],["2D Growth Forecast","Yes","Yes"],["2D Treatment Simulation","Yes","Yes"],["2D Custom Analysis Editor","Yes","Yes"],["2D Orthognathic Surgical\nPlanning","No","No"],["Implant Module","No","No"],["3D Image Capability","No","No"],["Landmarks","60","21"]],"caption_candidate":"Table 1: Comparison of Subject Device with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p8-t0","doc_id":"K243005","page_num":8,"bbox":[72.0,36.24,539.76,71.04],"n_rows":2,"n_cols":3,"columns":["","FDA 510(k) Summary",""],"rows":[["","FDA 510(k) Summary",""],["","","Rev. 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p8-t1","doc_id":"K243005","page_num":8,"bbox":[78.0,582.12,532.56,692.16],"n_rows":4,"n_cols":3,"columns":["Standard","Title","FDA Recognition #"],"rows":[["Standard","Title","FDA Recognition #"],["IEC 62304 ed. 1.1","Medical device software - Software life\ncycle processes","13-79"],["IEC 62366-1 ed 1.1","Medical devices - Part 1: Application of\nusability engineering to medical devices","5-129"],["ISO 14971:2019","Medical devices - Application of risk\nmanagement to medical devices","5-125"]],"caption_candidate":"Table 2: Non-Clinical Testing Standards & Guidance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p9-t0","doc_id":"K243005","page_num":9,"bbox":[72.0,36.24,539.76,71.04],"n_rows":2,"n_cols":3,"columns":["","FDA 510(k) Summary",""],"rows":[["","FDA 510(k) Summary",""],["","","Rev. 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p9-t1","doc_id":"K243005","page_num":9,"bbox":[78.0,85.32,532.56,214.44],"n_rows":4,"n_cols":3,"columns":["Standard","Title","FDA Recognition #"],"rows":[["Standard","Title","FDA Recognition #"],["IEC TR 80002-1 ed. 1.0","Medical device software - Part 1: Guidance\non the application of ISO 14971 to medical\ndevice software","13-34"],["FDA Guidance\n(09-27-2023)","Cybersecurity in Medical Devices: Quality\nSystem Considerations and Content of\nPremarket Submissions","Docket:\nFDA-2021-D-1158"],["AAMI TIR57:2016","Principles for medical device security - Risk\nmanagement.","13-83"]],"caption_candidate":"Rev. 3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243005-p9-t2","doc_id":"K243005","page_num":9,"bbox":[114.23,363.62,465.01,415.57],"n_rows":3,"n_cols":4,"columns":["Parameter","","Acceptance Criteria","Conclusion"],"rows":[["Parameter","","Acceptance Criteria","Conclusion"],["MRE (mm)","Lateral","≤ 1.5","PASS"],["","Frontal (PA)","≤ 2.5","PASS"]],"caption_candidate":"Table 3: Automatic Landmark Detection Accuracy Study Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243038-p8-t0","doc_id":"K243038","page_num":8,"bbox":[72.37,71.49,544.2,708.24],"n_rows":34,"n_cols":4,"columns":["Predicate Device & Reference Device Comparison","","",""],"rows":[["Predicate Device & Reference Device Comparison","","",""],["Topic","Proposed Device","Predicate Device","Reference Device"],["","","",""],["Manufacturer","Artrya Ltd.","Circle Cardiovascular","TeraRecon, Inc."],["","","Imaging Inc.",""],["Model Name","Salix Central","cvi42 Auto Imaging","iNtuition-Structural Heart"],["","","Software Application","Module"],["510(k) Number","Subject Device: TBD","K213998","K191585"],["","Salix Central is intended to\ncomplement standard care\nas an adjunctive tool and is\nnot intended as a\nreplacement to a medical\nprofessional’s\ncomprehensive diagnostic\ndecision-making process.\nThe software’s semi-\nautomated features are\nintended for an adult\npopulation and should only\nbe used by qualified\nmedical professionals\nexperienced in examining\nand evaluating cardiac CT\nimages.","The target population for\ncvi42 Auto’s manual\nworkflows is not\nrestricted; however, Salix\nCentral’s semi-automated\nmachine learning\nalgorithms are intended\nfor an adult population.\ncvi42 Auto shall be used\nonly for cardiac images\nacquired from an MR or\nCT scanner. It shall be\nused by qualified medical\nprofessionals,\nexperienced in examining\nand evaluating\ncardiovascular MR or CT\nimages, for the purpose of\nobtaining diagnostic\ninformation as part of a\ncomprehensive diagnostic\ndecision-making process.","tools and features that\nfacilitate: - Automatic and\nmanual centerline\ndetection. - Segmentation\nof cardiovascular\nstructures"],["","","",""],["Device Class","II","II","II"],["","","",""],["Device","QIH","LLZ, QIH","LLZ"],["Classification","","",""],["Intended Users","Cardiologists, Radiologists\nand Clinical Specialists","Qualified Medical\nProfessionals","Cardiologists,\nRadiologists and Clinical\nSpecialists"],["","","",""],["Operating","Client-Server Google\nChrome Application","macOS, Microsoft\nWindows","Microsoft Windows"],["Platform","","",""],["DICOM","Yes; DICOM 3.0 or higher","Yes","Yes"],["Compliant","","",""],["Image","CT","MR and CT","CT, MR, Nuc, PET, Angio,\nUS/Echo, SPECT"],["Acquisition","","",""],["Secured","Yes","Yes","Yes"],["Network Server","","",""],["Integration","","",""],["Store Images","Yes","Yes","Yes"],["2D Imaging","Yes","Yes","Yes"],["3D Imaging","Yes","Yes","Yes"],["Multiplanar","Yes","Yes","Yes"],["Reformat","","",""],["(MPR)","","",""],["Study Analysis","Panning\nWindowing\nZooming","Panning\nWindowing\nZooming","Yes"],["– Navigation","","",""],["Tools","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243038-p9-t0","doc_id":"K243038","page_num":9,"bbox":[72.37,71.49,544.18,367.88],"n_rows":21,"n_cols":4,"columns":["Predicate Device & Reference Device Comparison","","",""],"rows":[["Predicate Device & Reference Device Comparison","","",""],["Topic","Proposed Device","Predicate Device","Reference Device"],["","","",""],["Manufacturer","Artrya Ltd.","Circle Cardiovascular","TeraRecon, Inc."],["","","Imaging Inc.",""],["Model Name","Salix Central","cvi42 Auto Imaging","iNtuition-Structural Heart"],["","","Software Application","Module"],["510(k) Number","Subject Device: TBD","K213998","K191585"],["","Series, slices, and phases","Series, slices, and phases",""],["Study Analysis","Centerline\nWall\nSignal Intensity Overlay","Yes","Yes"],["– Visualization","","",""],["and Editing","","",""],["Measurements","Distance\nDiameter\nArea\nHounsfield Unit (HU)\nLumen % diameter\nreduction","Distance\nPerimeter\nArea\nHounsfield Unit (HU)\nVolume","Yes"],["","","",""],["Centerline","Manual and semi-automatic\n/ user-editable","Manual and semi-\nautomatic using Machine\nLearning technique","Semi-automatic"],["Extraction and","","",""],["Wall","","",""],["Segmentation","","",""],["Calcium","Yes","Yes","Yes"],["Scoring","","",""],["Reporting","Yes","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243038-p10-t0","doc_id":"K243038","page_num":10,"bbox":[60.62,231.04,555.4,371.94],"n_rows":7,"n_cols":9,"columns":["Salix Central Output","Statistic","","Estimate","","","Acceptance","","Result"],"rows":[["Salix Central Output","Statistic","","Estimate","","","Acceptance","","Result"],["","","","[95% CI]","","","Criteria","",""],["Calcium Scoring","Pearson Correlation","0.958\n[0.947, 0.966]","","","0.90","","","Pass"],["Centerline Extraction","True Placement\nPercentage","90.4%\n[88.5%, 92.2%]","","","78%","","","Pass"],["Vessel Labelling","F1 Score","78.4%\n[96.1%, 80.5%]","","","70%","","","Pass"],["Lumen Wall Segmentation","Dice Score","0.8996\n(0.8938, 0.9055)","","","0.80","","","Pass"],["Vessel Wall Segmentation","Dice Score","0.9016\n(0.8962, 0.9070)","","","0.80","","","Pass"]],"caption_candidate":"Salix Central performance exceeded all the pre-defined acceptance criteria for all validation tests.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243065-p6-t0","doc_id":"K243065","page_num":6,"bbox":[90.36,381.24,557.64,651.0],"n_rows":5,"n_cols":3,"columns":["Modification","K201992 PCCP","Subject PCCP"],"rows":[["Modification","K201992 PCCP","Subject PCCP"],["Real-Time Guidance\nfor Additional 2D TTE\nViews","Added cardiac views to standard\nechocardiography views, focusing\non various anatomical regions\n(e.g., PLAX, PSAX, Apical,\nSubcostal, Suprasternal).","Expands the list of views in previously\nauthorized PCCP by adding additional\nstandard cardiac subset views. These\nadditional cardiac ultrasound views are\nfocused on enhanced diagnostic imaging and\ncoverage of specific anatomical regions."],["Labeling compatibility\nof new compatible\nultrasound systems\nand UI Enhancement","Ensured software compatibility\nwith ultrasound systems of similar\nscreen sizes.","Builds on compatibility with additional UI/UX\nimprovements, incl. support for various screen\nsizes such as mobile platforms."],["Non-expert Validation","Not included.","Adds standalone test protocol to enable\nvalidation of modified device performance by\nthe intended user groups, ensuring\nequivalency to the original device based on\npredefined clinical endpoints."],["Human Factors Test","Not included.","Introduces Human Factors Testing to evaluate\nuser interactions and ensure critical tasks\nremain unaffected by UI/UX modifications."]],"caption_candidate":"PCCP of this submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243065-p7-t0","doc_id":"K243065","page_num":7,"bbox":[90.26,337.08,562.54,713.52],"n_rows":5,"n_cols":9,"columns":["","Modification","","","Rationale","","","Testing Methods",""],"rows":[["","Modification","","","Rationale","","","Testing Methods",""],["Retraining/optimization/\nmodification of core algorithm(s)","","","These changes enhance model\nrobustness, reduce bias, improve\ngeneralizability, and enable\nCaption Health to respond\neffectively real-world feedback.","","","Repeating verification tests and\nthe system level validation test to\nensure the pre-defined acceptance\ncriteria are met.","",""],["Real-time guidance for additional\n2D TTE views: This modification\nexpands the list of views by adding\nadditional cardiac subset views","","","These changes enhance the\nsystem’s diagnostic capabilities by\nproviding more focused, specific\nviews that assist expert clinicians\nin making more accurate cardiac\nassessments, improving overall\nusability.","","","Repeating verification tests and\ntwo system level validation tests\nincluding usability testing to\nensure the pre-defined acceptance\ncriteria are met for the additional\nviews.","",""],["Optimization of the core\nalgorithm(s) implementation in\nthe software such as optimization\nof algorithm thresholds, averaging\nlogic, transfer functions,\nfrequency, and refresh rate","","","These optimizations improve the\nperformance of the algorithm,\nmaking it more efficient and\naccurate without changing its\nfundamental functionality, ensure\nconsistency across different\ndevices and enhance the usability\nof the device","","","Repeating relevant verification\ntest(s) and the system level\nvalidation test to ensure the pre-\ndefined acceptance criteria are\nmet.","",""],["Addition of new types of\nprescriptive guidance for existing\nviews such as patient positioning\nand breathing guidance, guidance","","","These changes provide additional\nreal-time feedback to users\nenhances system’s utility and user\nexperience in obtaining diagnostic","","","Repeating relevant verification\ntests and two system level\nvalidation tests including usability","",""]],"caption_candidate":"A summary of these software modifications, rationale and test methods are presented in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p7-t0","doc_id":"K243122","page_num":7,"bbox":[88.7,572.11,520.9,714.58],"n_rows":6,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],["Magnet system","","",""],["Field Strength","3.0 Tesla","3.0 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible bore\ndimensions","75 cm","75 cm","Same"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p8-t0","doc_id":"K243122","page_num":8,"bbox":[88.7,78.84,520.9,709.18],"n_rows":37,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],["Magnet Homogeneity","2.30 ppm @ 50cm DSV\n0.80 ppm @ 45cm DSV\n0.38 ppm @ 40cm DSV\n0.08 ppm @ 30cm DSV\n0.02 ppm @ 20cm DSV\n0.002 ppm @ 10cm DSV","2.30 ppm @ 50cm DSV\n0.80 ppm @ 45cm DSV\n0.38 ppm @ 40cm DSV\n0.08 ppm @ 30cm DSV\n0.02 ppm @ 20cm DSV\n0.002 ppm @ 10cm DSV","Same"],["Gradient system","","",""],["Max gradient\namplitude","45 mT/m","45 mT/m","Same"],["Max slew rate","200 T/m/s","200 T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant frequencies","128.23 MHz","128.23 MHz","Same"],["Number of transmit\nchannels","2","2","Same"],["Number of receive\nchannels","Up to 96","Up to 96","Same"],["Amplifier peak power\nper channel","uXD2181: 18 kW\nuXD2201: 20 kW","uXD2181: 18 kW\nuXD2201: 20 kW","Same"],["RF Coils","","",""],["Volume Transmit Coil","Yes","Yes","Same"],["Head & Neck Coil -24","Yes","Yes","Same"],["Body Array Coil - 12","Yes","Yes","Same"],["Breast Coil - 10","Yes","Yes","Same"],["Flex Coil Large - 8","Yes","Yes","Same"],["Flex Coil Small - 8","Yes","Yes","Same"],["Knee Coil - 12","Yes","Yes","Same"],["Lower Extremity Coil\n- 36","Yes","Yes","Same"],["Shoulder Coil - 12","Yes","Yes","Same"],["Small Loop Coil","Yes","Yes","Same"],["Spine Coil - 32","Yes","Yes","Same"],["Wrist Coil - 12","Yes","Yes","Same"],["Cardiac Coil - 24","Yes","Yes","Same"],["Temporomandibular\nJoint Coil - 4","Yes","Yes","Same"],["Foot & Ankle Coil - 24","Yes","Yes","Same"],["Head Coil - 32","Yes","Yes","Same"],["Head Coil - 12","Yes","Yes","Same"],["Carotid Coil - 8","Yes","Yes","Same"],["Infant Coil - 24","Yes","Yes","Same"],["Body Array Coil - 24","Yes","Yes","Same"],["Head & Neck Coil - 48","Yes","Yes","Same"],["Spine Coil - 48","Yes","Yes","Same"],["Head Coil - 64","Yes","Yes","Same"],["SuperFlex Body - 24","Yes","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p9-t0","doc_id":"K243122","page_num":9,"bbox":[88.7,78.84,520.9,709.54],"n_rows":26,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],["SuperFlex Large - 12","Yes","Yes","Same"],["SuperFlex Small - 12","Yes","Yes","Same"],["Tx/Rx Knee Coil - 24","Yes","Yes","Same"],["SuperFlex Body Wide\n- 24","Yes","Yes","Same"],["Breast Coil-24","Yes","Yes","Same"],["Breast Coil - 12","Yes","No","Note 1"],["Head Coil - 16","Yes","No","Note 2"],["Tx/Rx Head Coil","Yes","No","Note 3"],["Patient table","","",""],["Dimensions","Patient Table:\nwidth 640mm, height\n880mm, length 2620mm\nDetachable Table:\nwidth 810mm, height\n880mm, length 2505mm","Patient Table:\nwidth 640mm, height\n880mm, length 2620mm\nDetachable Table:\nwidth 826mm, height\n880mm, length 2578mm","Note 4"],["Maximum supported\npatient weight","Patient Table:\n310 kg\nDetachable Table:\n310kg","Patient Table:\n310 kg\nDetachable Table:\n310kg","Same"],["Accessories","","",""],["Vital Signal Gating","Wireless UIH Gating Unit\nREF 453564324621\nECG module Ref\n989803163121\nSpO2 module Ref\n989803163111\n(alternative)","Wireless UIH Gating Unit\nREF 453564324621\nECG module Ref\n989803163121\nSpO2 module Ref\n989803163111\n(alternative)","Same"],["","ECG, Rrespiration and\npulse module\nuVWMERP\nWireless gating trigger unit\nuMVRX\n(alternative)","ECG, Rrespiration and\npulse module\nuVWMERP\nWireless gating trigger unit\nuMVRX\n(alternative)","Same"],["","Respiration module\nmmw101\n(optional)","Respiration module\nmmw100\n(optional)","Note 5"],["Image Processing","","",""],["Inline ECV","Yes","No","Note 6"],["Inline MOCO","Yes","No","Note 7"],["MTP","Yes","No","Note 8"],["Workflow","","",""],["TI Scout","Yes","No","Note 9"],["Breast Biopsy","Yes","No","Note 10"],["uVision","Yes","Yes","Note 11"],["EasyScan","Yes","Yes","Note 12"],["Image Reconstruction","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p10-t0","doc_id":"K243122","page_num":10,"bbox":[88.7,78.84,520.9,128.18],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Predicate Device\nuMR Omega (K240540,\nK230152, K220332)","Remark"],["SparkCo","Yes","No","Note 13"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p10-t1","doc_id":"K243122","page_num":10,"bbox":[88.7,156.26,520.9,228.62],"n_rows":4,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Reference Device#1\nuWS-MR (K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Reference Device#1\nuWS-MR (K220332)","Remark"],["Image Processing","","",""],["Inline Cardiac function","Yes","Yes","Note 14"],["Inline MRS","Yes","Yes","Note 15"]],"caption_candidate":"Table 2 Comparison to Reference device#1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p10-t2","doc_id":"K243122","page_num":10,"bbox":[88.7,256.7,520.9,372.41],"n_rows":6,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Omega","Reference Device#2\nuPMR 790 (K234154)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Omega","Reference Device#2\nuPMR 790 (K234154)","Remark"],["Workflow","","",""],["EasyCrop","Yes","Yes","Note 16"],["ImageGuard","Yes","Yes","Same"],["Mocap(also named\nMoCap-Monitoring)","Yes","Yes","Same"],["EasyFACT(also named\nInline FACT)","Yes","Yes","Same"]],"caption_candidate":"Table 3 Comparison to Reference device#2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p10-t3","doc_id":"K243122","page_num":10,"bbox":[88.7,386.69,520.9,695.98],"n_rows":7,"n_cols":2,"columns":["Note 1","The intended use of Breast Coil - 12 is essentially identical to previously cleared Breast\nCoil - 10. There are two differences between Breast Coil – 12 and Breast Coil – 10. One\nis that Breast Coil - 12 can be used with Biopsy Configuration to provide breast biopsy\nfunction. The other one is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 1","The intended use of Breast Coil - 12 is essentially identical to previously cleared Breast\nCoil - 10. There are two differences between Breast Coil – 12 and Breast Coil – 10. One\nis that Breast Coil - 12 can be used with Biopsy Configuration to provide breast biopsy\nfunction. The other one is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 2","The intended use of Head Coil - 16 is equivalent to previously cleared Head Coil - 32.\nThe only difference between them is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","The intended use of Tx/Rx Head Coil is essentially identical to previously cleared Head\nCoil - 12. There are two differences between Tx/Rx Head Coil and Head Coil – 12. One\nis that Tx/Rx Head Coil is of a 16 Legs High-Pass Birdcage used for transmitter coil. The\nother one is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 4","The dimensions of detachable table were changed from width 826mm, height 880mm,\nlength 2578mm to width 810mm, height 880mm, length 2505mm.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","The model name of mmw component was changed from mmw100 to mmw101.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","Inline ECV aims to calculate the pixel-wise ECV (extracellular volume fraction) images\nfrom the native and post T1 mapping.\nThe difference did not raise new safety and effectiveness concerns."],["Note 7","Inline MOCO is a function that perform motion correction on MR images, which can\nreduce the motion caused by physiological factors such as breathing and heart beat in\nthe images.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"Inline FACT)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p11-t0","doc_id":"K243122","page_num":11,"bbox":[88.7,78.84,520.9,483.91],"n_rows":9,"n_cols":2,"columns":["Note 8","MTP is substantially equivalent to GRE and acquires two flip angles and multi-echo\nimages with one scan, and then uses specific image processing to attain multi-parametric\nimages.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 8","MTP is substantially equivalent to GRE and acquires two flip angles and multi-echo\nimages with one scan, and then uses specific image processing to attain multi-parametric\nimages.\nThe difference did not raise new safety and effectiveness concerns."],["Note 9","TI Scout automatically selects the TI frame which has the darkest ventricular\nmyocardium of the TI Scout image, allowing users to achieve the best inversion time\n(TI) and simplifying the workflow which needed the TI.\nThe difference did not raise new safety and effectiveness concerns."],["Note 10","Breast Biopsy is a workflow that can provide biopsy instruction for technicians based\non the hardware and lesion parameters, the instruction include the biopsy grid\ncoordinate, needle block cell and needle depth.\nThe difference did not raise new safety and effectiveness concerns."],["Note 11","During this submission, Body Part Recognition function was included in uVision, which\nallows assist patient positioning by performing image recognition on human natural\nimages through a 3D camera during the positioning stage.\nThe difference did not raise new safety and effectiveness concerns."],["Note 12","EasyScan of the proposed device supports more body parts than that of the predicate\ndevice. In this submission, breast and pelvis and hip and ankle and thorax are included.\nThe difference did not raise new safety and effectiveness concerns."],["Note 13","SparkCo is an algorithm that can detect and correct spark artifacts (a specific occurring\nMRI artifact that is caused by electromagnetic interference (EMI)) in MRI images.\nThe difference did not raise new safety and effectiveness concerns."],["Note 14","During this submission, inline ED/ES Phases Recognition for Real Time Cine was\nincluded in Inline Cardiac function, which allows automatically rearrange the cardiac\nimages into an aligned cardiac cycle.\nThe difference did not raise new safety and effectiveness concerns."],["Note 15","Inline MRS of the proposed device are the same as the predicate device. The difference\nis that the algorithms of Inline MRS are shifted from the post-processing workstation to\ninline console.\nThe difference did not raise new safety and effectiveness concerns."],["Note 16","EasyCrop of the proposed device supports more body parts than that of the predicate\ndevice. In this submission, head and carotid and renal are included.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p14-t0","doc_id":"K243122","page_num":14,"bbox":[90.73,348.58,519.0,592.51],"n_rows":17,"n_cols":2,"columns":["Subjects' Characteristics\n(N=15)","N(%)"],"rows":[["Subjects' Characteristics\n(N=15)","N(%)"],["Gender, N(%)",""],["Male","9(60%)"],["Female","6(40%)"],["Age, N(%): Min=18, Max=59, Avg.=30.8, Std.=9.88",""],["18-29","2(20%)"],["30-44","8(53.3%)"],["45-64","4(26.7%)"],[">=65","0(0.0%)"],["Ethnicity, N(%)",""],["White","N.A."],["Asian","15(100%)"],["Body Mass Index (BMI), N(%): Min=17.0, Max=53.5, Avg.=24.0, Std.=7.05",""],["Underweight (<18.5)","2(13.3%)"],["Healthy weight (18.5-24.9)","10(66.7%)"],["Overweight (25.0-29.9)","3(20%)"],["Obesity (>=30.0)","0(0.0%)"]],"caption_candidate":"Table 4. The demographic distribution of real-world spark testing dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p15-t0","doc_id":"K243122","page_num":15,"bbox":[90.26,110.54,519.46,236.3],"n_rows":10,"n_cols":2,"columns":["Body Parts","Number of cases"],"rows":[["Body Parts","Number of cases"],["Head","21"],["C-spine","5"],["Shoulder","1"],["Wrist","1"],["Thorax","2"],["Abdomen","8"],["L-spine","2"],["Pelvis","19"],["Total","59"]],"caption_candidate":"testing dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p15-t1","doc_id":"K243122","page_num":15,"bbox":[90.26,331.97,519.46,571.15],"n_rows":3,"n_cols":4,"columns":["Test parts","Test Methods","Accept criteria","Test Results"],"rows":[["Test parts","Test Methods","Accept criteria","Test Results"],["Test on the\nspark\ndetection\naccuracy","Based on the real-world\ntesting dataset, calculating\nthe detection accuracy by\ncomparing the spark\ndetection results with the\nground-truth.","The average detection\naccuracy need be larger\nthan 90%","The average detection\naccuracy is 94%."],["Test on the\nspark\ncorrection\nperformance","Based on the simulated spark\ntesting dataset, calculating\nthe PSNR(Peak signal-to-\nnoise ratio) of the spark-\ncorrected images and original\nspark images\nBased on the real-world\nspark dataset, evaluating the\nimage quality improvement\nbetween the spark-corrected\nimages and spark images by\none experienced evaluator.","The average PSNR of\nspark-corrected images\nneed to be higher than\nthe spark images.\nSpark artifacts need to\nbe reduced or corrected\nafter enable the\nSparkCo.","The average PSNR of\nspark-corrected images\nis 1.6 higher than the\nspark images.\nThe images with spark\nartifacts were\nsuccessfully corrected\nafter enable the\nSparkCo."]],"caption_candidate":"Table 6 The test methods and test results of SparkCo","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p16-t0","doc_id":"K243122","page_num":16,"bbox":[90.34,228.5,519.35,422.69],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Passing rate","To verify the effectiveness of the algorithm, the subjective evaluation\nmethod was used. The segmentation result of each case was obtained with\nthe algorithm, and the segmentation mask was evaluated with the following\ncriteria. The test pass criteria was: no failure cases, satisfaction rate\nS/(S+A+F) exceeding 95%.\nThe criteria is as follows:\nSatisfied (S): the segmentation myocardial boundary adheres to the\n\nmyocardial boundary and blood pool ROI is within the blood pool excluding\nthe papillary muscles.\nAcceptable (A): These are small missing or redundant areas in the\n\nmyocardial segmentation but not obviously and the blood pool ROI is within\nthe blood pool excluding the papillary muscles.\nFail (F): The myocardial mask does not adhere to the myocardial\n\nboundary or the blood pool ROI is not within the blood pool, or the blood\npool ROI contains papillary muscles."]],"caption_candidate":"Table 7 Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p16-t1","doc_id":"K243122","page_num":16,"bbox":[90.34,534.84,519.35,708.16],"n_rows":7,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male 20\nFemale 8",""],["Age",""],["<18 1\n18-28 4\n29-40 1\n> 41 22",""],["Protocol",""],["post_t1map_sax 28\nnative_t1map_sax 28",""],["BMI (kg/m(2))",""]],"caption_candidate":"Table 8 Distribution of Patient dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p17-t0","doc_id":"K243122","page_num":17,"bbox":[90.34,78.84,519.36,194.66],"n_rows":4,"n_cols":2,"columns":["<18.5 0\n[18.5, 25) 7\n>=25 15\nUnknown 6",""],"rows":[["<18.5 0\n[18.5, 25) 7\n>=25 15\nUnknown 6",""],["Magnetic field strength (T)",""],["1.5 13\n3 15",""],["Ethnicity",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p17-t1","doc_id":"K243122","page_num":17,"bbox":[90.34,224.21,519.36,281.81],"n_rows":2,"n_cols":2,"columns":["Healthy",""],"rows":[["Healthy",""],["Negative 19\nPostive 4\nUnknown 5",""]],"caption_candidate":"USA 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243122-p17-t2","doc_id":"K243122","page_num":17,"bbox":[90.34,377.67,519.36,707.5],"n_rows":16,"n_cols":5,"columns":["","","","Total Failure","Total satisfaction"],"rows":[["","","","Total Failure","Total satisfaction"],["Gender","Satisfied (S)","Acceptable (A)","",""],["","","","Rate","Rate"],["","","","",""],["Male\nFemale","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Age","","","",""],["18-28\n29-40\n> 41","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"],["Protocol","","","",""],["post_t1map_sax\nnative_t1map_sax","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["BMI (kg/m(2))","","","",""],["<18.5\n[18.5, 25)\n>=25\nUnknown","100%\n100%\n100%\n100%","0%\n0%\n0%\n0%","0%\n0%\n0%\n0%","100%\n100%\n100%\n100%"],["Magnetic field strength (T)","","","",""],["1.5\n3","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Ethnicity","","","",""],["Asia\nUSA","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Healthy","","","",""]],"caption_candidate":"Table 9 Segmentation algorithm subgroup analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243145-p5-t0","doc_id":"K243145","page_num":5,"bbox":[72.24,124.44,539.81,408.98],"n_rows":5,"n_cols":2,"columns":["Submitter / Primary Contact Person","Kenny M Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(202) 856-6099"],"rows":[["Submitter / Primary Contact Person","Kenny M Bello\nRegulatory Affairs\nmonsuru.bello@siemens-healthineers.com\n+1(202) 856-6099"],["Secondary Contact Person","Clayton Ginn\nRegulatory Affairs\nclayton.ginn@siemens-healthineers.com\n+1 (865) 898-2692"],["Submitter Address","Siemens Medical Solutions, Inc. USA\nMolecular Imaging\n810 Innovation Drive\nKnoxville, TN 37932\nEstablishment Registration Number: 1034973"],["Legal Manufacturer","Siemens Healthineers AG\nSiemensstr 1\nD-91301 Forchheim, Germany\nEstablishment Registration Number: 3004977335"],["Importer/Distributor","Siemens Medical Solutions USA, Inc.\n40 Liberty Boulevard\nMalvern, PA 19355\nEstablishment Registration Number: 2240869"]],"caption_candidate":"1. Identification of the Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243145-p6-t0","doc_id":"K243145","page_num":6,"bbox":[72.04,419.6,539.52,659.2],"n_rows":5,"n_cols":6,"columns":["","Subject Device","","","Predicate Device",""],"rows":[["","Subject Device","","","Predicate Device",""],["","","","","",""],["","syngo.CT LVO Detection","","","syngo.CT Brain Hemorrhage",""],["","(SOMARIS/8 VB80)","","","(SOMARIS/8 VB80)",""],["syngo.CT LVO Detection is a radiological post-\nprocessing application for the analysis of CT\nangiography (CTA) head images. syngo.CT LVO\nDetection supports computer-aided triage, and it\naddresses vascular abortions in the CTA of the\nbrain, commonly referred to as large vessel\nocclusion (LVO), in the ICA, M1, and M2 segment.\nThe output for triage is intended for\ninformational purposes only. It is not intended\nfor diagnostic use and does not alter the original\nmedical image.","","","syngo.CT Brain Hemorrhage is designed to assist\nthe radiologist in prioritizing cases of suspected\nintracranial hemorrhage, also in the\nsubarachnoid space, on non-contrast CT\nexaminations of the head. It makes case-level\noutput available to a CT scanner or other PACS\nsystem for worklist prioritization.\nThe output is intended for informational\npurposes only and is not intended for diagnostic\nuse. The device does not alter the original\nmedical image and is not intended to be used as\na standalone diagnostic device.","",""]],"caption_candidate":"6. Indications for Use Comparison to the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243145-p7-t0","doc_id":"K243145","page_num":7,"bbox":[78.14,185.17,539.57,572.14],"n_rows":30,"n_cols":4,"columns":["","Subject Device","Predicate Device",""],"rows":[["","Subject Device","Predicate Device",""],["Feature","syngo.CT LVO Detection\n(SOMARIS/8 VB80)\n(K243145)","syngo.CT Brain Hemorrhage","Comparison"],["","","(SOMARIS/8 VB80)",""],["","","(K232431)",""],["Notification-only, parallel","Yes","Yes","Same"],["workflow tool","","",""],["Intended User","Radiologists and clinical\nadministrators","Radiologists and clinical\nadministrators","Same"],["","","",""],["Setting","Acute Care","Acute Care","Same"],["","","",""],["Identify patients with a","Yes","Yes","Same"],["prespecified clinical condition","","",""],["Clinical condition","Suspected Stroke/LVO","Suspected Stroke/Brain\nHemorrhage","Same"],["","","",""],["Alert to finding","Yes; flagged for review","Yes; flagged for review","Same"],["","","",""],["Primary Imaging Modalities","CT","CT","Same"],["","","",""],["Body Part","Head","Head","Same"],["","","",""],["Artificial Intelligence algorithm","Yes","Yes","Same"],["","","",""],["Limited to analysis of imaging data","Yes","Yes","Same"],["","","",""],["Scanner Manufacturer of Input","Siemens and other vendors","Siemens and other vendors","Same"],["Data","","",""],["Output","Suspected LVO/\nProcessing finished","Suspected hemorrhage/\nProcessing finished","Similar"],["","","",""],["Deployment Compatibility","syngo.via platform","syngo.via platform,\nSOMARIS-10 platform","Similar"],["","","",""]],"caption_candidate":"table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243145-p8-t0","doc_id":"K243145","page_num":8,"bbox":[72.26,535.95,539.79,717.84],"n_rows":7,"n_cols":6,"columns":["Standard","Version","Content","","FDA Recognition",""],"rows":[["Standard","Version","Content","","FDA Recognition",""],["","","","","Number",""],["","","","","(if applicable)",""],["IEC 62304","62306 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","Medical device software - Software life cycle processes","13-79","",""],["NEMA PS 3.1 - 3.20\n2022d",":2022","Digital Imaging and Communications in Medicine\n(DICOM) Set","12-349","",""],["ISO 14971","Third Edition 2019-\n12","Application of Risk Management to Medical Devices","5-125","",""],["IEC 62366-1","Edition 1.1 2020-06\nCONSOLIDATED\nVERSION","Medical devices - Part 1: Application of usability\nengineering to medical devices","5-129","",""]],"caption_candidate":"standards listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243145-p9-t0","doc_id":"K243145","page_num":9,"bbox":[72.27,72.89,539.78,188.9],"n_rows":5,"n_cols":6,"columns":["Standard","Version","Content","","FDA Recognition",""],"rows":[["Standard","Version","Content","","FDA Recognition",""],["","","","","Number",""],["","","","","(if applicable)",""],["ISO 15223-1","Fourth edition\n2021-07","Medical devices - Symbols to be used with information\nto be supplied by the manufacturer - Part 1: General\nrequirements","5-134","",""],["ISO 20417:2021","First edition 2021-\n04 Corrected\nversion 2021-12","Medical devices - Information to be supplied by the\nmanufacturer","5-135","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243158-p7-t0","doc_id":"K243158","page_num":7,"bbox":[31.5,96.36,576.06,671.5],"n_rows":4,"n_cols":4,"columns":["","Subject Device\nTeraRecon Aorta.CT\nK243158","Predicate Device\nAutoSeg-H\nK220039","Comparison"],"rows":[["","Subject Device\nTeraRecon Aorta.CT\nK243158","Predicate Device\nAutoSeg-H\nK220039","Comparison"],["Indications\nfor Use","TeraRecon Aorta.CT is\nintended to provide an\nautomatic 3D segmentation\nand label anatomical\nlandmarks of the Aorta. The\nresults of TeraRecon\nAorta.CT are intended to be\nused in conjunction with\nother patient information by\ntrained professionals who\nare responsible for making\nany patient management\ndecision per the standard of\ncare. TeraRecon Aorta.CT\nis a software as a medical\ndevice (SaMD) deployed as\na containerized application.\nThe device inputs are CT\nAngiography with contrast\nDICOM images. The device\noutputs are DICOM result\nfiles which may be viewed\nutilizing DICOM-compliant\nsystems. The device does\nnot alter the original input\ndata and does not provide a\ndiagnosis.\nTeraRecon Aorta.CT is\nindicated to generate results\nfrom aortic CT Angiography\nscans taken of adult\npatients except patients with\npre-existing aortic device,\nbicuspid aortic valve\nanomaly, aortic dissection,\naortic rupture, and\nabdominal metallic devices.\nThe device is not specific to\nany gender, ethnic group, or\nclinical condition.","AutoSeg-H is medical\nimaging software that is\nintended to provide trained\nmedical professionals with\ntools to aid them in reading,\ninterpreting, reporting, and\ntreatment planning.\nAutoSeg-H accepts DICOM\ncompliant medical images\nacquired from imaging\ndevice (Computed\nTomography).\nAutoSeg-H provides the\ntools for specific analysis\napplications which provide\ncustom UI, targeted\nmeasurements and\nreporting functions\nincluding:\n- Coronary Artery Analysis\nfor CT coronary\narteriography images: which\nis intended for the\nqualitative and quantitative\nanalysis of coronary\narteries.\n- Valve Analysis: which is\nintended for automatic\nextraction of the heart and\naorta regions, automatic\ndetection of the contour of\nthe aorta and valves,\nmeasurement of the vicinity\nof the valves.\n- 4-Chamber Analysis:\nwhich is intended for\nautomatic extraction of the\nleft atrium, left ventricle,\nright atrium, and right\nventricle from CT.","Differences:\nThe subject device does not include\nfunctionality to provide professionals with\ntools to read, interpret, report or treatment\nplan.\nThe predicate device provides analysis tools\nfor coronary artery analysis and 4-chamber\nanalysis that the subject device does not\nprovide.\nThe predicate device provides measurements\nof the vicinity of the cardiac valves which the\nsubject device does not provide.\nThe subject device includes landmarks of the\naorta that the predicate device does not.\nThe subject device indicates that it is not for\nuse on images of adult patients with pre-\nexisting aortic device, bicuspid aortic valve\nanomaly, aortic dissection, aortic rupture, and\nabdominal metallic devices. The predicate\ndevice does not mention similar non use\nscenarios.\nSimilarities:\nThe subject and predicate devices are both\nindicated for use with Computed Tomography\n(CT) DICOM images.\nThe subject and predicate devices are both\nindicated for use on images of adult patients.\nThe subject and predicate devices both\nprovide segmentation results.\nSummary:\nThe noted differences do not render the\nsubject device NSE because the identified\ndifferences do not raise different safety and\neffectiveness questions. The similarities show\nthat similar device output is provided based\non the same technology utilized in the\ndevices."],["Modality","Computed Tomography\n(CT)","Computed Tomography\n(CT)","Same"],["Algorithm\nTechnology","Supervised deep learning-\nbased algorithms","Deep learning-based\nalgorithms","Same"]],"caption_candidate":"Technological Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243158-p8-t0","doc_id":"K243158","page_num":8,"bbox":[31.5,72.24,576.06,339.26],"n_rows":3,"n_cols":4,"columns":["","Subject Device\nTeraRecon Aorta.CT\nK243158","Predicate Device\nAutoSeg-H\nK220039","Comparison"],"rows":[["","Subject Device\nTeraRecon Aorta.CT\nK243158","Predicate Device\nAutoSeg-H\nK220039","Comparison"],["Device\nOutputs","DICOM Seg and DICOM\nCoF","Results in form of 2D\nImages, 3D Images,\nInformation and Results","Differences:\nThe predicate device outputs measurement\nresults that are not available in the subject\ndevice.\nSimilarities:\nBoth the subject and predicate devices\noutput results following the DICOM\nstandard.\nSummary:\nThe noted differences do not render the\nsubject device NSE because the identified\ndifferences do not raise different safety and\neffectiveness questions. The similarities\nshow that similar device output is provided\nbased on the same technology utilized in\nthe devices."],["Installation\nMethods","Application installed on a\ncomputer","Application installed on a\ncomputer","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p7-t0","doc_id":"K243189","page_num":7,"bbox":[71.83,279.28,540.73,315.49],"n_rows":3,"n_cols":4,"columns":["","Training Dataset","Tuning Dataset","Validation Dataset"],"rows":[["","Training Dataset","Tuning Dataset","Validation Dataset"],["","(n=676 samples)","(n=240 samples)","(n=217 samples)"],["","","",""]],"caption_candidate":"race/ethnicity all reflect the broader U.S. population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p8-t0","doc_id":"K243189","page_num":8,"bbox":[73.15,462.03,544.85,636.82],"n_rows":8,"n_cols":3,"columns":["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std. Dev.)"],"rows":[["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std. Dev.)"],["Tumor Volume (n=184)","cubic centimeters (cc)","5.22 ± 15.58"],["Tumor-to-breast volume ratio (n=184)","%","0.51 ± 1.48"],["Tumor longest dimension (n=202)","centimeters (cm)","1.60 ± 1.93"],["Tumor-to-nipple distance (n=200)","centimeters (cm)","1.20 ± 1.37"],["Tumor-to-skin distance (n=202)","centimeters (cm)","0.63 ± 0.61"],["Tumor-to-chest distance (n=202)","centimeters (cm)","0.91 ± 1.14"],["Tumor center of mass (n=184)","centimeters (cm)","0.72 ± 1.42"]],"caption_candidate":"Performance data for the automated measurements is summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p9-t0","doc_id":"K243189","page_num":9,"bbox":[72.82,147.17,546.11,212.71],"n_rows":3,"n_cols":3,"columns":["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],"rows":[["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],["Tumor segmentation (n=184)","Volumetric Dice","0.75 ± 0.24"],["","Surface Dice","0.88 ± 0.24"]],"caption_candidate":"Results of Dice and surface Dice are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p9-t1","doc_id":"K243189","page_num":9,"bbox":[72.82,468.52,540.96,700.98],"n_rows":10,"n_cols":3,"columns":["Predicate Device Comparison","",""],"rows":[["Predicate Device Comparison","",""],["","Predicate Device","TumorSight Viz"],["510(k)","K231130","K243189"],["Manufacturer","SimBioSys, Inc.","SimBioSys, Inc."],["Regulation Number","892.2050","892.2050"],["Regulation Name","Medical image management and\nprocessing system","Medical image management and\nprocessing system"],["Classification","2","2"],["Device Common Name","Image Processing System","Image Processing System"],["Product Code","QIH","QIH"],["Functions","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p10-t0","doc_id":"K243189","page_num":10,"bbox":[72.77,71.28,540.98,529.67],"n_rows":5,"n_cols":3,"columns":["Intended Use","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],"rows":[["Intended Use","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],["Data Source (Input)","MRI","MRI"],["Output/Accessibility","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity"],["Physical Characteristics","\"-non-invasive software package\n-DICOM compatible\"","\"-non-invasive software package\n-DICOM compatible\""],["Safety","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning.","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p11-t0","doc_id":"K243189","page_num":11,"bbox":[72.79,71.4,540.97,497.9],"n_rows":22,"n_cols":3,"columns":["Predicate Device Feature Comparison","",""],"rows":[["Predicate Device Feature Comparison","",""],["Feature","Predicate Device","TumorSight Viz"],["Standard image viewing tools","Yes","Yes"],["MIPs","Yes","Yes"],["Reformats","Yes","Yes"],["Registration","Yes","Yes"],["Subtraction series","Yes","Yes"],["View 3D volume rendering","Yes","Yes"],["Kinetic curves","Yes","Yes"],["Parametric image maps","Yes","Yes"],["Manual DICOM import","Yes","Yes"],["Automated DICOM image\nimport","No","Yes"],["Updated segmentation model","No","Yes"],["View finding volume","Yes","Yes"],["View finding location","Yes","Yes"],["View finding size","Yes","Yes"],["View kinetic curve with\nhighest uptake","Yes","Yes"],["View finding distance to\nnipple","Yes","Yes"],["View finding distance to skin","Yes","Yes"],["View finding distance to chest","Yes","Yes"],["View adjusted finding size","No - Segmentation is not\neditable, but surgical margins\nare editable","No - Segmentation is not\neditable, but surgical margins\nare editable"],["Interactive rotation of 3D\nvolume rendering","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243189-p12-t0","doc_id":"K243189","page_num":12,"bbox":[73.19,71.59,536.81,424.74],"n_rows":12,"n_cols":7,"columns":["Performance","N","Metric","Predicate/","TumorSight","Predicate/","Inter-"],"rows":[["Performance","N","Metric","Predicate/","TumorSight","Predicate/","Inter-"],["Measurement","","","TumorSight","Viz/","Ground","radiologist"],["","","","Viz","Ground","Truth","Variability"],["","","","","Truth","",""],["","","","(Mean","(Mean ±","(Mean ±","(Mean"],["","","","± Std. Dev.)","Std. Dev.)","Std. Dev.)","± Std. Dev.)"],["","","","","","",""],["Longest\nDimension","197","Abs.\nDistance\nError","1.33 cm ± 1.80\ncm","1.59 cm ± 1.93\ncm","1.27 cm ± 1.34\ncm","1.30 cm ± 1.34\ncm"],["Tumor to Skin","197","Abs.\nDistance\nError","0.24 cm ± 0.39\ncm","0.61 cm ± 0.60\ncm","0.55 cm ± 0.48\ncm","0.51 cm ± 0.48\ncm"],["Tumor to\nChest","197","Abs.\nDistance\nError","0.64 cm ± 1.13\ncm","0.89 cm ± 1.12\ncm","0.69 cm ± 0.88\ncm","0.97 cm ± 1.16\ncm"],["Tumor to\nNipple","195","Abs.\nDistance\nError","0.89 cm ± 1.03\ncm","1.15 cm ± 1.30\ncm","1.01 cm ± 1.23\ncm","1.03 cm ± 1.30\ncm"],["Tumor Volume","197","Abs.\nVolume\nError","4.42 cc ± 11.03\ncc","5.22 cc ± 15.58\ncc","6.50 cc ± 21.40\ncc","NA"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p5-t0","doc_id":"K243229","page_num":5,"bbox":[72.84,280.64,445.7,381.44],"n_rows":10,"n_cols":2,"columns":["Proprietary Name","Bunkerhill AVC"],"rows":[["Proprietary Name","Bunkerhill AVC"],["",""],["Classification Name","Computed tomography x-ray system"],["",""],["Regulation Number","21 CFR 892.1750"],["",""],["Product Code","JAK"],["",""],["","II"],["Regulatory Class",""]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p6-t0","doc_id":"K243229","page_num":6,"bbox":[72.72,484.32,540.24,700.56],"n_rows":2,"n_cols":3,"columns":["","Proposed Device: Bunkerhill AVC","Predicate Device: iCAC Device\n(K230223)"],"rows":[["","Proposed Device: Bunkerhill AVC","Predicate Device: iCAC Device\n(K230223)"],["Intended use /\nIndications for\nuse","Bunkerhill AVC is a software device\nintended for use in detecting presence\nand estimating quantity of aortic valve\ncalcification for adult patients aged 40\nyears and above. The device\nautomatically analyzes non-gated, non-\ncontrast chest computed tomography\n(CT) images collected during clinical\ncare and outputs the region of interest\n(intended for informational purposes\nonly) and quantification of detected\ncalcium.","iCAC is a software device intended for\nuse in estimating presence and quantity\nof coronary artery calcium for patients\naged 30 years and above during routine\ncare. The device automatically analyzes\nnon-gated, non-contrast chest computed\ntomography (CT) images collected\nduring routine care and outputs a visual\nrepresentation of estimated coronary\nartery calcium segmentation (intended\nfor informational purposes only) and\nboth exact and four-category quantitative\nestimates of the patient’s coronary artery\ncalcium burden in Agatston units."]],"caption_candidate":"A table comparing the intended use of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p7-t0","doc_id":"K243229","page_num":7,"bbox":[72.72,70.32,540.24,479.28],"n_rows":2,"n_cols":3,"columns":["","Proposed Device: Bunkerhill AVC","Predicate Device: iCAC Device\n(K230223)"],"rows":[["","Proposed Device: Bunkerhill AVC","Predicate Device: iCAC Device\n(K230223)"],["","The output of the subject device is made\navailable to the physician on-demand as\npart of his or her standard workflow. The\ndevice-generated quantification can be\nviewed in the patient report at the\ndiscretion of the physician, and the\nphysician also has the option of viewing\nthe device-generated calcium region of\ninterest in a diagnostic image viewer.\nThe subject device output in no way\nreplaces the original patient report or the\noriginal non-gated, non-contrast CT\nscan; both are still available to be viewed\nand used at the discretion of the\nphysician.\nThe device is intended to provide\ninformation to the physician to provide\nassistance during review of the patient’s\ncase. Results of the subject device are\nnot intended to be used on a stand-alone\nbasis and are solely intended to aid and\nprovide information to the physician. In\nall cases, further action taken on a patient\nshould only come at the recommendation\nof the physician after further reviewing\nthe patient’s results.","The output of the subject device is made\navailable to the physician on-demand as\npart of his or her standard workflow. The\ndevice generated calcium score or score\ngroup can be viewed in the patient report\nat the discretion of the physician, and the\nphysician also has the option of viewing\nthe device-generated calcium\nsegmentation in a diagnostic image\nviewer. The subject device output in no\nway replaces the original patient report\nor the original chest CT scan; both are\nstill available to be viewed and used at\nthe discretion of the physician.\nThe device is intended to provide\ninformation to the physician to provide\nassistance during review of the patient’s\ncase. Results of the subject device are\nnot intended to be used on a stand-alone\nbasis and are solely intended to aid and\nprovide information to the physician. In\nall cases, further action taken on a\npatient should only come at the\nrecommendation of the physician after\nfurther reviewing the patient’s results."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p8-t0","doc_id":"K243229","page_num":8,"bbox":[72.72,229.92,540.24,714.24],"n_rows":12,"n_cols":4,"columns":["","Proposed Device:\nBunkerhill AVC","Predicate Device: iCAC\nDevice (K230223)","Summary"],"rows":[["","Proposed Device:\nBunkerhill AVC","Predicate Device: iCAC\nDevice (K230223)","Summary"],["Product code","JAK","JAK","Same"],["Regulation number","21 CFR §892.1750","21 CFR §892.1750","Same"],["Modality","Computed tomography\n(CT)","Computed tomography\n(CT)","Same"],["Image format","DICOM","DICOM","Same"],["Contrast","Non-contrast","Non-contrast","Same"],["Supported CT scan","Non-cardiac-gated CT\nscan","Non-cardiac-gated CT scan","Same"],["Slice thickness","Up to 5 mm","Up to 5 mm","Same"],["Calcification\ndetection","Automatic","Automatic","Same"],["Main image quality","DICOM","DICOM","Same"],["Annotation of\ndetected calcium","Yes","Yes","Same"],["Visual\nOutput\nformat","Visual output in the form\na Circular Region of\nInterest (ROI) around\ndetected calcification\n(intended for\ninformational purposes\nonly). The estimated\nvisual output can be\nviewed by the physician\nin a","Outputs a visual\nrepresentation of\nestimated coronary\nartery calcium\nsegmentation\n(intended for\ninformational\npurposes only). The","Predicate device shows\nestimated segmentation\nas one of the device\noutputs whereas subject\ndevice shows a ROI, not\nsegmentation."]],"caption_candidate":"calcification.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p9-t0","doc_id":"K243229","page_num":9,"bbox":[72.72,88.32,540.24,472.08],"n_rows":2,"n_cols":4,"columns":["","diagnostic image viewer.\nThe physician’s standard\nmethod for viewing\nunaltered chest CT scans\nin PACS will remain\navailable to them even if\nthe subject device is\nbeing used. However, the\nphysician will also have\nan option to view the\nvisual output estimated\nby the subject device as a\nseparate series within\nPACS.","estimated calcium\nsegmentation can be\nviewed by the\nphysician in a\ndiagnostic image\nviewer. The\nphysician’s standard\nmethod for viewing\nunaltered chest CT\nscans in PACS will\nremain available to\nthem even if the\nsubject device is being\nused.\nHowever, the\nphysician will also\nhave an option to view\nthe calcium\nsegmentation\nestimated by the\nsubject device as a\nseparate series within\nPACS.","Both are for information\nonly."],"rows":[["","diagnostic image viewer.\nThe physician’s standard\nmethod for viewing\nunaltered chest CT scans\nin PACS will remain\navailable to them even if\nthe subject device is\nbeing used. However, the\nphysician will also have\nan option to view the\nvisual output estimated\nby the subject device as a\nseparate series within\nPACS.","estimated calcium\nsegmentation can be\nviewed by the\nphysician in a\ndiagnostic image\nviewer. The\nphysician’s standard\nmethod for viewing\nunaltered chest CT\nscans in PACS will\nremain available to\nthem even if the\nsubject device is being\nused.\nHowever, the\nphysician will also\nhave an option to view\nthe calcium\nsegmentation\nestimated by the\nsubject device as a\nseparate series within\nPACS.","Both are for information\nonly."],["Generate patient\nreport","Optional to copy result\nto clipboard, insert in\nreport, DICOM\nSecondary Capture","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243229-p10-t0","doc_id":"K243229","page_num":10,"bbox":[72.72,63.36,540.24,485.04],"n_rows":8,"n_cols":4,"columns":["Report of the\ncalcium score","Yes, estimated\nAgatston-equivalent\nscore and binary\noutput\n(presence/absence)","Yes, Coronary Calcium\nDetection Category and\nestimated Agatston score\n4 detection categories","iCAC provides\nestimation of coronary\ncalcium burden\nwhereas subject device\nprovides estimation of\ncalcification on aortic\nvalve."],"rows":[["Report of the\ncalcium score","Yes, estimated\nAgatston-equivalent\nscore and binary\noutput\n(presence/absence)","Yes, Coronary Calcium\nDetection Category and\nestimated Agatston score\n4 detection categories","iCAC provides\nestimation of coronary\ncalcium burden\nwhereas subject device\nprovides estimation of\ncalcification on aortic\nvalve."],["Type of\nInterpretation","Adjunctive information","Adjunctive information","Same"],["Intended User","Qualified medical\nprofessionals such as\ncardiologists or\nradiologists","Interpreting physicians","Similar"],["Patient population","Patients aged 40 years\nand above","Patients above the age of 30","Similar"],["Anatomical\nlocation","Chest","Chest","Same"],["Intended location","Medical facility","Medical facility","Same"],["Rx or OTC","Rx","Rx","Same"],["Measurement scale","Agatston-equivalent units","Agatston-equivalent units","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243230-p8-t0","doc_id":"K243230","page_num":8,"bbox":[54.7,86.42,456.7,713.42],"n_rows":9,"n_cols":4,"columns":["","Subject Device\nSecond Opinion®\nBLE","Primary Predicate\nOverjet Dental\nAssist\nK210187","Reference Device\nVidea Perio Assist\nK223296"],"rows":[["","Subject Device\nSecond Opinion®\nBLE","Primary Predicate\nOverjet Dental\nAssist\nK210187","Reference Device\nVidea Perio Assist\nK223296"],["Manufacturer","Pearl Inc.","Overjet, Inc.","VideaHealth, Inc."],["Classification","892.2050","892.2050","892.2050"],["Product Code","QIH","LLZ","QIH"],["Class","Class II","Class II","Class II"],["Image Modality","Radiograph","Radiograph","Radiograph"],["Intended Use","Dental automated\nimage processing\nsoftware device to aid\nin bone level\nmeasurement dental\nradiograph review by\nHCP","Dental automated\nimage processing\nsoftware device to aid\nin bone level\nmeasurement dental\nradiograph review by\nHCP","Dental automated\nimage processing\nsoftware device to aid\nin bone level\nmeasurement dental\nradiograph review by\nHCP"],["Full IFU","Second Opinion®\nBLE is a radiological\nautomated image\nprocessing software\ndevice intended to\nidentify and display\nbone level\nmeasurements in\nbitewing and\nperiapical\nradiographs. It should\nnot be used in lieu of\nfull patient evaluation\nor solely relied upon\nto make or confirm a\ndiagnosis.\nIt is designed to aid\ndental health\nprofessionals to\nreview bitewing and\nperiapical radiographs\nof permanent teeth in\npatients 12 years of\nage or older as a\nconcurrent and\nsecond reader.","Overjet Dental Assist\nis a radiological\nsemi-automated\nimage processing\nsoftware device\nintended to aid dental\nprofessionals in the\nmeasurements of\nmesial and distal bone\nlevels associated with\neach tooth from\nbitewing and\nperiapical\nradiographs. It should\nnot be used in lieu of\nfull patient evaluation\nor solely relied upon\nto make or confirm a\ndiagnosis. The system\nis to be used by\ntrained professionals\nincluding, but not\nlimited to, dentists and\ndental hygienists.","Videa Perio Assist is\na radiological\nsemi-automated\nimage processing\nsoftware device\nintended to aid dental\nprofessionals in the\nmeasurements and\nvisualization of mesial\nand distal bone levels\nassociated with each\ntooth from bitewing\nand periapical\nradiographs.\nMeasurements are\nmade available as\nlinear distances or\nrelative percentages.\nIt should not be used\nin-lieu of full patient\nevaluation or solely\nrelied upon to make or\nconfirm a diagnosis.\nThe system is to be\nused by trained\nprofessionals\nincluding, but not\nlimited to, dentists and\ndental hygienists."],["Intended body part","Dental","Dental","Dental"]],"caption_candidate":"K243230","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243230-p9-t0","doc_id":"K243230","page_num":9,"bbox":[54.65,86.42,456.65,243.22],"n_rows":2,"n_cols":4,"columns":["Technology","Utilizes computer\nvision neural\nnetwork\nalgorithms,\ndeveloped from\nopen-source\nmodels using\nsupervised\nmachine learning\ntechniques","Utilizes computer\nvision neural\nnetwork algorithms,\ndeveloped from\nopen-source\nmodels using\nsupervised\nmachine learning\ntechniques","Utilizes computer\nvision neural network\nalgorithms, developed\nfrom open-source\nmodels using\nsupervised machine\nlearning techniques"],"rows":[["Technology","Utilizes computer\nvision neural\nnetwork\nalgorithms,\ndeveloped from\nopen-source\nmodels using\nsupervised\nmachine learning\ntechniques","Utilizes computer\nvision neural\nnetwork algorithms,\ndeveloped from\nopen-source\nmodels using\nsupervised\nmachine learning\ntechniques","Utilizes computer\nvision neural network\nalgorithms, developed\nfrom open-source\nmodels using\nsupervised machine\nlearning techniques"],["Device Description","Detection & display of\nlinear bone level\nmeasurements","Detection & display of\nlinear bone level\nmeasurements","Detection & display\nof linear bone level\nmeasurements"]],"caption_candidate":"K243230","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243230-p10-t0","doc_id":"K243230","page_num":10,"bbox":[195.5,414.5,419.5,585.5],"n_rows":7,"n_cols":2,"columns":["Subject Age","Count (%)"],"rows":[["Subject Age","Count (%)"],["<30","63 (15.9)"],["30-<40","54 (13.6)"],["40-<50","79 (19.9)"],["50-<60","71 (17.9)"],["60-<70","73 (18.4)"],["70+","56 (14.1)"]],"caption_candidate":"The demographics of the data set was as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243230-p10-t1","doc_id":"K243230","page_num":10,"bbox":[195.5,628.5,427.5,728.5],"n_rows":4,"n_cols":2,"columns":["Gender","Count (%)"],"rows":[["Gender","Count (%)"],["Female","160 (40.4)"],["Male","190 (48.0)"],["Other","44 (11.1)"]],"caption_candidate":"70+ 56 (14.1)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243230-p11-t0","doc_id":"K243230","page_num":11,"bbox":[72.5,329.5,558.75,404.5],"n_rows":3,"n_cols":3,"columns":["Metric","Bitewing","Periapical"],"rows":[["Metric","Bitewing","Periapical"],["Precision","87%","87%"],["Recall","91%","87%"]],"caption_candidate":"both precision & recall for bitewing and periapical images.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243234-p7-t0","doc_id":"K243234","page_num":7,"bbox":[61.7,475.44,547.7,630.65],"n_rows":6,"n_cols":4,"columns":["","Subject Device\nSecond Opinion PC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK231678"],"rows":[["","Subject Device\nSecond Opinion PC","Primary Predicate\nSecond Opinion\nK210365","Secondary Predicate\nOverjet\nK231678"],["Manufacturer","Pearl Inc.","Pearl Inc.","Overjet, Inc."],["Classification","892.2070","892.2070","892.2070"],["Product Code","MYN","MYN","MYN"],["Image\nModality","Radiograph","Radiograph","Radiograph"],["Intended Use","Dental CADe to aid in\ndental radiograph review\nby HCP","Dental CADe to aid in dental\nradiograph review by HCP","Dental CADe to aid in dental\nradiograph review by HCP"]],"caption_candidate":"Table 1: Comparison of Second Opinion CS with the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243234-p8-t0","doc_id":"K243234","page_num":8,"bbox":[61.67,91.5,547.67,510.9],"n_rows":4,"n_cols":4,"columns":["Full IFU","Second Opinion® CS is a\ncomputer aided detection\n(\"CADe”) software to aid in\nthe detection and\nsegmentation of caries in\nperiapical radiographs.\nIt is designed to aid dental\nhealth professionals to review\nperiapical radiographs of\npermanent teeth in patients\n12 years of age or older as a\nsecond reader.","Second Opinion® is a computer\naided detection (\"CADe”) software\nto identify and mark regions in\nrelation to suspected dental\nfindings which include Caries,\nDiscrepancy at the margin of an\nexisting restoration, Calculus,\nPeriapical radiolucency, Crown\n(metal, including zirconia &\nnon-metal), Filling (metal &\nnon-metal), Root canal, Bridge,\nand Implants.\nIt is designed to aid dental health\nprofessionals to review bitewing\nand periapical radiographs of\npermanent teeth in patients 12\nyears of age or older as a second\nreader.","Overjet Caries Assist (OCA) is a\nradiological, automated,\nconcurrent-read, computer-assisted\ndetection (CADe) software intended\nto aid in the detection and\nsegmentation of caries on bitewing\nand periapical radiographs. The\ndevice provides additional\ninformation for the dentist to use in\ntheir diagnosis of a tooth surface\nsuspected of being carious. The\ndevice is not intended as a\nreplacement for a complete dentist’s\nreview or their clinical judgment that\ntakes into account other relevant\ninformation from the image, patient\nhistory, or actual in vivo clinical\nassessment."],"rows":[["Full IFU","Second Opinion® CS is a\ncomputer aided detection\n(\"CADe”) software to aid in\nthe detection and\nsegmentation of caries in\nperiapical radiographs.\nIt is designed to aid dental\nhealth professionals to review\nperiapical radiographs of\npermanent teeth in patients\n12 years of age or older as a\nsecond reader.","Second Opinion® is a computer\naided detection (\"CADe”) software\nto identify and mark regions in\nrelation to suspected dental\nfindings which include Caries,\nDiscrepancy at the margin of an\nexisting restoration, Calculus,\nPeriapical radiolucency, Crown\n(metal, including zirconia &\nnon-metal), Filling (metal &\nnon-metal), Root canal, Bridge,\nand Implants.\nIt is designed to aid dental health\nprofessionals to review bitewing\nand periapical radiographs of\npermanent teeth in patients 12\nyears of age or older as a second\nreader.","Overjet Caries Assist (OCA) is a\nradiological, automated,\nconcurrent-read, computer-assisted\ndetection (CADe) software intended\nto aid in the detection and\nsegmentation of caries on bitewing\nand periapical radiographs. The\ndevice provides additional\ninformation for the dentist to use in\ntheir diagnosis of a tooth surface\nsuspected of being carious. The\ndevice is not intended as a\nreplacement for a complete dentist’s\nreview or their clinical judgment that\ntakes into account other relevant\ninformation from the image, patient\nhistory, or actual in vivo clinical\nassessment."],["Intended\nbody part","Dental","Dental","Dental"],["Technology","Utilizes computer vision\nneural network algorithms,\ndeveloped from\nopen-source models using\nsupervised machine\nlearning techniques","Utilizes computer vision neural\nnetwork algorithms, developed\nfrom open-source models\nusing supervised machine\nlearning techniques","Automated, concurrent-read,\nCADe software that utilizes\nmachine learning"],["Device\nDescription","Detection and\nsegmentation of caries.","Detection of radiological dental\nfindings: 5 restorations\n(crowns, bridges, implants, root\ncanals, fillings), 4 pathologies\n(caries, margin discrepancy,\ncalculus, periapical\nradiolucency) using bounding\nboxes.","Detection and segmentation of\ncaries."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p5-t0","doc_id":"K243239","page_num":5,"bbox":[85.5,315.59,534.5,423.59],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Lung AI (LAI001)"],"rows":[["Proprietary Name","Lung AI (LAI001)"],["Common Name","Lung AI"],["Classification Name","Medical Image Analyzer"],["Regulation Number","21 CFR 892.2070"],["Product Code","MYN"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p5-t1","doc_id":"K243239","page_num":5,"bbox":[85.5,461.77,534.5,569.52],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Lung-CAD"],"rows":[["Proprietary Name","Lung-CAD"],["Premarket Notification","K230085"],["Classification Name","Medical Image Analyzer"],["Regulation Number","21 CFR 892.2070"],["Product Code","MYN"],["Regulatory Class","II"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p7-t0","doc_id":"K243239","page_num":7,"bbox":[78.25,253.8,538.5,658.5],"n_rows":8,"n_cols":3,"columns":["Feature/ Function","Subject Device:\nLung AI","Predicate Device\nLung-CAD by Imagen Technologies\n(K230085)"],"rows":[["Feature/ Function","Subject Device:\nLung AI","Predicate Device\nLung-CAD by Imagen Technologies\n(K230085)"],["Image Modality","Ultrasound","Digital X-ray"],["Study Type","Chest","Chest"],["Scan type","Multi-frame ultrasound images","Digital X-ray images"],["Clinical Output","Identify and mark regions of\ninterest (ROIs) on lung\nUltrasound","Identify and mark regions of\ninterest (ROIs) on chest\nradiographs and label the box\naround the ROI as lung\nhyperinflation"],["Intended User Workflow","Device is intended for use as a\nconcurrent reading aid for\ntrained healthcare\nprofessionals qualified in\ninterpreting lung ultrasounds","Device intended for use as a\nconcurrent reading aid for\nphysicians interpreting chest\nradiographs"],["Patient Population","Adults","Adults"],["Principle of Operation and\nTechnology","Artificial intelligence, including\nnon-adaptive machine learning\nalgorithms trained with clinical\ndata","Artificial intelligence"]],"caption_candidate":"Comparison of Technological Characteristics with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p8-t0","doc_id":"K243239","page_num":8,"bbox":[78.5,93.5,538.5,209.5],"n_rows":2,"n_cols":3,"columns":["AI Algorithm","Supervised Deep Learning\nincluding Deep Convolutional\nNeural Networks for\nSegmentation, Landmark\nDetection and Classification","Supervised Deep Learning"],"rows":[["AI Algorithm","Supervised Deep Learning\nincluding Deep Convolutional\nNeural Networks for\nSegmentation, Landmark\nDetection and Classification","Supervised Deep Learning"],["Intended Users","Trained healthcare professionals","Physicians"]],"caption_candidate":"510(k) Summary - Lung AI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p9-t0","doc_id":"K243239","page_num":9,"bbox":[195.25,358.24,417.25,466.5],"n_rows":5,"n_cols":2,"columns":["Lung Finding","Detection Performance Metric"],"rows":[["Lung Finding","Detection Performance Metric"],["Pleural Effusion","Se = 0.97 (95% CI 0.94 – 0.99)"],["","Sp = 0.91 (95% CI 0.87 – 0.96)"],["Consolidation /\nAtelectasis","Se = 0.97 (95% CI 0.94 – 0.99)"],["","Sp = 0.94 (95% CI 0.90 – 0.98)"]],"caption_candidate":"Table 1. Summary of Lung AI performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243239-p9-t1","doc_id":"K243239","page_num":9,"bbox":[195.25,580.35,417.25,688.5],"n_rows":5,"n_cols":2,"columns":["Lung Finding","Localization Performance Metric"],"rows":[["Lung Finding","Localization Performance Metric"],["Pleural Effusion","Se = 0.85 (95% CI 0.80 – 0.89)"],["","Sp = 0.91 (95% CI 0.87 – 0.96)"],["Consolidation /\nAtelectasis","Se = 0.86 (95% CI 0.81 – 0.90)"],["","Sp = 0.94 (95% CI 0.90 – 0.98)"]],"caption_candidate":"Table 2. Summary of Lung AI localization performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p5-t0","doc_id":"K243250","page_num":5,"bbox":[72.02,114.41,540.17,661.28],"n_rows":20,"n_cols":2,"columns":["Date Summary Prepared:","2025-02-10"],"rows":[["Date Summary Prepared:","2025-02-10"],["Contact Details:",""],["Applicant Name:","Subtle Medical, Inc."],["Applicant Address:","883 Santa Cruz Ave, Suite 205\nMenlo Park, CA 94025 United States"],["Applicant Contact:","Ms. Ronny Elor"],["Applicant Contact Telephone:","(925) 324-8467"],["Applicant Contact Email:","ronny@subtlemedical.com"],["Correspondent Name:","Enzyme Corporation"],["Correspondent Address:","611 Gateway Blvd, Ste 120\nSouth San Francisco, CA 94080 United States"],["Correspondent Contact:","Mr. Jared Seehafer"],["Correspondent Contact Telephone:","(415) 638-9554"],["Correspondent Contact Email:","jared@enzyme.com"],["Device Name:",""],["Device Trade Name:","SubtleHD (1.x)"],["Common Name:","Medical image management and processing system"],["Classification Name:","System, Image Processing, Radiological"],["Regulation Number:","892.2050"],["Product Code:","QIH"],["Device Class:","Class II"],["Legally Marketed Predicate Devices:","Primary Predicate #: K230854\nPredicate Trade Name: SwiftMR\nPredicate Manufacturer: AIRS Medical Inc.\nSecondary Predicate #: K223623\nPredicate Trade Name: SubtleMR\nPredicate Manufacturer: Subtle Medical, Inc."]],"caption_candidate":"Table 1. Contact Details and Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p7-t0","doc_id":"K243250","page_num":7,"bbox":[72.25,98.46,537.25,688.5],"n_rows":11,"n_cols":5,"columns":["Comparison","SubtleHD\n(Subject Device)","SwiftMR\n(Primary\nPredicate\nDevice)\n(K230854)","SubtleMR\n(Secondary\nPredicate\nDevice)\n(K223623)","Noted\nDifferences"],"rows":[["Comparison","SubtleHD\n(Subject Device)","SwiftMR\n(Primary\nPredicate\nDevice)\n(K230854)","SubtleMR\n(Secondary\nPredicate\nDevice)\n(K223623)","Noted\nDifferences"],["Workflow","The software operates\non DICOM files,\nenhances the images,\nand sends the\nenhanced images to\nany desired destination\nwith an AE Title (e.g.,\nPACS, MR device,\nworkstation, and\nmore). Enhanced\nimages coexist with\nthe original images.","The software operates\non DICOM files,\nenhances the images,\nand stores the\nenhanced images on\nPACS or on a MR\ndevice. Enhanced\nimages coexist with\nthe original images.","The software operates\non DICOM files on the\nfile system, enhances\nthe images, and stores\nthe enhanced images\non the file system. The\nreceipt of original\nDICOM image files\nand delivery of\nenhanced images as\nDICOM files depends\non other software\nsystems.","SubtleHD can send\nenhanced images to\nany destination as long\nas it is associated with\nan IP and AE Title.\nSubtleMR by default is\nintended to send\nenhanced images to\nPACS, but can be\nconfigured to other\ndestinations. SwiftMR\ncan send enhanced\nimages to PACS or an\nMR Device.\nSubstantially\nEquivalent."],["Product Code","QIH","LLZ","LLZ","Substantially\nEquivalent."],["Physical\nCharacteristics","Software package\nOperates on a virtual\nmachine","Same","Same","Same"],["Intended User","Radiologists","Same","Same","Same"],["Intended Location","Medical facility\n(hospitals, clinics,\nimaging center, etc.)","Same","Same","Same"],["Modalities","MRI","Same","Same","Same"],["Operating System /\nComputer","Linux Compatible; PC\nor Mac","PC Compatible","Same","SubtleHD and\nSubtleMR are PC or\nMac, while SwiftMR is\nonly PC. Substantially\nEquivalent."],["Rx or OTC","Rx","Same","Same","Same"],["User Interface","None","Same","Same","Same"],["DICOM\nStandard Compliance","The software\nprocesses\nDICOM-compliant\nimage data.","Same","Same","Same"]],"caption_candidate":"Table 2. Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p8-t0","doc_id":"K243250","page_num":8,"bbox":[72.33,72.08,537.33,703.5],"n_rows":6,"n_cols":5,"columns":["Comparison","SubtleHD\n(Subject Device)","SwiftMR\n(Primary\nPredicate\nDevice)\n(K230854)","SubtleMR\n(Secondary\nPredicate\nDevice)\n(K223623)","Noted\nDifferences"],"rows":[["Comparison","SubtleHD\n(Subject Device)","SwiftMR\n(Primary\nPredicate\nDevice)\n(K230854)","SubtleMR\n(Secondary\nPredicate\nDevice)\n(K223623)","Noted\nDifferences"],["Image Enhancement\nAlgorithm Description","SubtleHD software\nimplements an image\nenhancement\nalgorithm using a\nconvolutional neural\nnetwork based filtering.\nOriginal images are\nenhanced by running\nthrough a cascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. A single\nneural network is\ntrained for adaptive\nnoise reduction and\nsharpness increase.\nThe parameters within\nthe neural network\nwere obtained through\nan image-guided\noptimization process.\nAdditional nonlocal\nmean based denoising\nand unsharp masking\nbased sharpening\nfilters are applied to\nthe deep learning\nprocessed image.","SwiftMR implements\nan image\nenhancement\nalgorithm using\nconvolutional neural\nnetwork-based\nfiltering. Original\nimages are enhanced\nby running through a\ncascade of filter banks,\nwhere thresholding\nand scaling operations\nare applied. Neural\nnetwork-based filters\nthat perform noise\nreduction and/or\nsharpening are\nobtained. The\nparameters of the\nfilters were obtained\nthrough an\nimage-guided\noptimization process.\nSharpening filter is\nadditionally applied to\nthe deep learning\nprocessed image.","SubtleMR software\nimplements an image\nenhancement\nalgorithm using\nconvolutional neural\nnetwork based filtering.\nOriginal images are\nenhanced by running\nthrough a cascade of\nfilter banks, where\nthresholding and\nscaling operations are\napplied. Separate\nneural network based\nfilters are obtained for\nnoise reduction and\nsharpness increase.\nThe parameters of the\nfilters were obtained\nthrough an\nimage-guided\noptimization process.","Substantially\nEquivalent."],["Model Architecture","Single SRE/DNE\nmodel with filters/\npre/post-processing.","DNE is a model; SRE\nis achieved via multiple\nfilters","SRE is a model, DNE\nis a model, with filters/\npre/post-processing","Deep-learning\nalgorithm and\nprocessing steps for\nnoise reduction and\nsharpness\nenhancement.\nSubstantially\nEquivalent."],["Function","Combined SRE and\nDNE for all anatomies.","Combined SRE and\nDNE, can turn either\noff as an option.","Separate, DNE head,\nspine, neck, abdomen,\npelvis, prostate,\nbreast, and\nmusculoskeletal, SRE\nhead only.","Substantially\nEquivalent."],["Enhancement levels","Optional high\ndenoising level and\noptional high\nsharpening level.","Denoising level from\nlevel 0 to level 8,\nSharpness level from\nlevel 0 to level 5.","No levels (single level).","SubtleHD and SwiftMR\nare substantially\nequivalent. SubtleMR\nhas a single SRE and\nDNE option."],["Performance Validation","Endpoints and\nacceptance criteria\nusing retrospective\nclinical images for both\nnoise reduction and\nsharpness increase\nfunctions.","Same","Same","Same"]],"caption_candidate":"Subtle Medical Inc. - 510(k) – SubtleHD – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p11-t0","doc_id":"K243250","page_num":11,"bbox":[72.25,283.57,537.25,524.5],"n_rows":10,"n_cols":4,"columns":["Test Set","Study Test","Result (mean ± std dev)","T-Test P-Value"],"rows":[["Test Set","Study Test","Result (mean ± std dev)","T-Test P-Value"],["Paired Test Set\n(Unaligned SOC as\nthe Reference)","L1 Loss","9.993% ± 92.487%","0.189"],["","SSIM","0.0115 ± 0.0403","0.001"],["","PSNR","-0.307 dB ± 2.863 dB","0.150"],["Paired Test Set\n(Unaligned\nSubtleHD-enhanced\nSOC as the\nReference)","L1 Loss","-6.908% ± 22.422%","0.022"],["","SSIM","0.0210 ± 0.0448","<0.0001"],["","PSNR","0.583 dB ± 2.754 dB","<0.0001"],["Aligned Test Set","L1 Loss","-38.837% ± 15.469%","<0.0001"],["","SSIM","0.0367 ± 0.0219","<0.0001"],["","PSNR","3.844 dB ± 2.172 dB","<0.0001"]],"caption_candidate":"Table 3. Standalone Image Quality Metric Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p12-t0","doc_id":"K243250","page_num":12,"bbox":[72.25,402.58,537.25,717.5],"n_rows":9,"n_cols":5,"columns":["Endpoint","Acceptance Criteria","SubtleHD\nMode","Result","Conclusion"],"rows":[["Endpoint","Acceptance Criteria","SubtleHD\nMode","Result","Conclusion"],["Denoising (SNR)\nPrimary Endpoint","SNR shall improve by at least 40% in\nhomogenous ROI regions for at least 90%\nof the dataset.","Default","PASS","SubtleHD performs\ndenoising, in terms of\nimproved SNR, MRI images."],["","SNR shall improve by at least 40% in\nhomogenous ROI regions for at least 95%\nof the dataset.","High\nDenoising","PASS",""],["Sharpness\n(Image Intensity\nChange) Primary\nEndpoint","Slope in a line ROI is increased for at least\n90% of the dataset.","Default","PASS","SubtleHD sharpens, in terms\nof improvement in visibility of\nthe edge at a tissue interface\nby image intensity slope\nmeasure, MRI images."],["","Slope in a line ROI is increased for at least\n95% of the dataset.","High\nSharpening","PASS",""],["Sharpness\n(Image Intensity\nChange for\nBrains)\nSecondary\nEndpoint","Thickness, in terms of FWHM in a line ROI,\nis reduced for at least 90% of the dataset.","Default","PASS","SubtleHD sharpens, in terms\nof improvement in visibility of\nan anatomical structure by\nimage intensity FWHM\nmeasure, MRI images."],["","Thickness, in terms of FWHM in a line ROI,\nis reduced for at least 95% of the dataset.","High\nSharpening","PASS",""],["Sharpness and\nOver Smoothing\n(Gradient\nEntropy) Primary\nEndpoint","At least 90% of cases demonstrate a lower\ngradient entropy value after SubtleHD\nprocessing.","Default","PASS","SubtleHD does not result in\nover-smoothed images, in\nterms of improvement in\ngradient entropy."],["","At least 95% of cases demonstrate a lower\ngradient entropy value after SubtleHD\nprocessing.","High\nSharpening","PASS",""]],"caption_candidate":"Table 4. Performance Validation Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p13-t0","doc_id":"K243250","page_num":13,"bbox":[72.14,72.08,539.11,163.5],"n_rows":2,"n_cols":5,"columns":["Endpoint","Acceptance Criteria","SubtleHD\nMode","Result","Conclusion"],"rows":[["Endpoint","Acceptance Criteria","SubtleHD\nMode","Result","Conclusion"],["","There is a statistically significant\nimprovement in gradient entropy when\ncomparing the original and SubtleHD\nenhanced images across the performance\ndataset per a two-sided paired t-test.","Default and\nHigh\nSharpening","PASS",""]],"caption_candidate":"Subtle Medical Inc. - 510(k) – SubtleHD – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p13-t1","doc_id":"K243250","page_num":13,"bbox":[72.14,358.86,517.5,618.5],"n_rows":4,"n_cols":5,"columns":["Endpoint","Endpoint\nDescription","Acceptance Criteria","Result","Conclusion"],"rows":[["Endpoint","Endpoint\nDescription","Acceptance Criteria","Result","Conclusion"],["Denoising\n(Primary\nEndpoint)","Signal-to-Noise Ratio","Statistically significantly\nbetter with p-value < 0.05\nor not statistically\nsignificantly different in a\nWilcoxon signed rank test","PASS","SubtleHD performs\ndenoising, in terms of\nimproved SNR, for MRI\nImages."],["","Overall Image Quality\n/ Diagnostic\nConfidence","Statistically significantly\nbetter with p-value < 0.05\nor not statistically\nsignificantly different in a\nWilcoxon signed rank test","PASS",""],["Sharpness\n(Primary\nEndpoint)","Visibility of Small\nStructures","Statistically significantly\nbetter with p-value < 0.05\nor not statistically\nsignificantly different in a\nWilcoxon signed rank test","PASS","SubtleHD performs\nsharpening and does not\nover-smoooth images, in\nterms of improved visibility\nof small structures, for MRI\nimages."]],"caption_candidate":"Table 5. Reader Study Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243250-p14-t0","doc_id":"K243250","page_num":14,"bbox":[72.33,72.08,517.5,233.5],"n_rows":2,"n_cols":5,"columns":["Endpoint","Endpoint\nDescription","Acceptance Criteria","Result","Conclusion"],"rows":[["Endpoint","Endpoint\nDescription","Acceptance Criteria","Result","Conclusion"],["Artifacts\n(Secondary\nEndpoint)","Artifact Introduction","SubtleHD-enhanced\nimages do not contain\nartifacts that could impact\ndiagnosis or b) both input\nand SubtleHD-enhanced\nimages are deemed to\ncontain artifacts that could\nimpact diagnosis.","PASS","SubtleHD does not introduce\nartifacts into MRI images."]],"caption_candidate":"Subtle Medical Inc. - 510(k) – SubtleHD – 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243292-p5-t0","doc_id":"K243292","page_num":5,"bbox":[95.73,393.01,518.74,542.32],"n_rows":5,"n_cols":2,"columns":["510(k) Sponsor","Avatar Medical"],"rows":[["510(k) Sponsor","Avatar Medical"],["Address","11 rue de Lourmel\n75015 Paris France"],["Correspondence Person","FRANCOIS Adeline\nVP QARA and Clinical Affairs"],["Contact Information","Email: adeline@avatarmedical.ai"],["Date of Submission","October 2024"]],"caption_candidate":"Table 2A – Submission correspondent","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243292-p6-t0","doc_id":"K243292","page_num":6,"bbox":[114.05,36.15,500.41,137.64],"n_rows":4,"n_cols":2,"columns":["Product Code:","QIH, automated radiological image processing software"],"rows":[["Product Code:","QIH, automated radiological image processing software"],["Subsequent Product\nCode:","LLZ, system, image processing, radiological"],["Regulatory Class","II"],["Classification Panel","Radiology"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243292-p6-t1","doc_id":"K243292","page_num":6,"bbox":[114.05,212.98,500.41,411.5],"n_rows":9,"n_cols":2,"columns":["Trade name","FX SPS"],"rows":[["Trade name","FX SPS"],["Common Name","Planning software for Total Shoulder Arthroplasty"],["Premarket Notification","K213922"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","LLZ"],["Regulatory Class","II"],["Classification Panel","Radiology"]],"caption_candidate":"Table 2C – Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243292-p7-t0","doc_id":"K243292","page_num":7,"bbox":[67.22,92.16,547.24,710.14],"n_rows":15,"n_cols":3,"columns":["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],"rows":[["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],["Intended Users","Healthcare Professionals","Healthcare Professionals"],["Intended Environment","Healthcare facilities such as hospitals and clinics","Healthcare facilities such as hospitals\nand clinics"],["Device Class","Class II","Class II"],["Type of software","Web-based software","Web-based software"],["Use time","Pre-operatively","Pre-operatively"],["Imaging used","CT-scan images","CT-scan images"],["Type of implants planned","Anatomical and reverse shoulder implants","Anatomical and reverse shoulder\nimplants"],["Manual/Automatic\nsegmentation","Manual segmentation performed.","Automatic segmentation performed."],["User profiles","User profiles define the authorized actions for the\nuser.","User profiles define the authorized\nactions for the user."],["Case management","List of cases","List of cases"],["Tools","Milling tool","Milling tool (called reaming)"],["Patient Information Display","Patient last name\nPatient first name\nPatient sex\nPatient birthdate\nShoulder side\nSurgery date","Patient last name\nPatient first name\nPatient sex\nPatient birthdate\nPatient age\nPatient height\nPatient weight\nShoulder side\nSurgery date"],["Bone representation","3D and 2D representation of the humerus and the\nscapula","3D and 2D representation of the humerus\nand the scapula."],["2D DICOM Viewer","2D DICOM view\nAxial views are displayed in 2D DICOM Viewer\ninterfaces.","The 2D DICOM Viewer Interface displays\n2D DICOM images\nAxial and coronal views are displayed in\ntwo separate 2D DICOM Viewer\ninterfaces."]],"caption_candidate":"Table 2D: Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243292-p8-t0","doc_id":"K243292","page_num":8,"bbox":[67.22,36.15,547.24,444.59],"n_rows":6,"n_cols":3,"columns":["3D Viewer","3D reconstruction in an interactive viewing interface","3D reconstruction in an interactive\nviewing interface with soft tissues (Pre-\nPosition Interface only)"],"rows":[["3D Viewer","3D reconstruction in an interactive viewing interface","3D reconstruction in an interactive\nviewing interface with soft tissues (Pre-\nPosition Interface only)"],["Planning step","Case details,\nSegmentation,\nGlenoid","Create plan,\nValidate Segmentations,\nPre-position with the validation of\nShoulder Landmarks,\nImplant,\nGlenoid/humerus,\nPost position,\nSurgical planning Report"],["Landmarks / Measurements","Manual measurements performed:\nShoulder Measurements, scapula neck length,\nposterior subluxation, glenoid reaming depth.","Pre-positioning or Semi-automatic\nmeasurements performed:\nShoulder Measurements, baseplate\nSeating, posterior subluxation, glenoid\nreaming depth."],["Implant Initial Placement","Manual initial placement performed.","Pre-positioning or Semi-automatic initial\nplacement performed."],["Planning report","Planning report comprising preoperative and planned\nparameters.","Planning report comprising patient\ninformation, implant and measurement\npre and Post position, with 8 images to\nillustrate the chosen implant\nconfiguration."],["Recommandations","Does not include any predictions and\nrecommendations.","Does not include any predictions and\nrecommendations."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243294-p11-t0","doc_id":"K243294","page_num":11,"bbox":[72.34,179.66,490.15,307.62],"n_rows":8,"n_cols":12,"columns":["","Metric Name","","","Value","","","Criteria","","","Pass/Fail",""],"rows":[["","Metric Name","","","Value","","","Criteria","","","Pass/Fail",""],["","Absolute Bias (upper","","7.61","","","<12","","","Pass","",""],["","95% CI)","","","","","","","","","",""],["Standard deviation\n(upper 95% CI)","Standard deviation","","1.99","","","<19","","","Pass","",""],["","(upper 95% CI)","","","","","","","","","",""],["","Pearson’s","","0.993","","",">0.86","","","Pass","",""],["","correlation – r","","","","","","","","","",""],["","(lower 95% CI)","","","","","","","","","",""]],"caption_candidate":"volumetric values (mL) by Brainomix 360 e-ASPECTS. This is summarized in Table 1 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243294-p14-t0","doc_id":"K243294","page_num":14,"bbox":[72.42,462.91,532.75,763.18],"n_rows":7,"n_cols":10,"columns":["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],"rows":[["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],["","Parameter","","","Brainomix 360 e-ASPECTS","","","Brainomix 360 e-ASPECTS","",""],["","","","","(K243294)","","","(K221564)","",""],["510(k) Number","","","K243294","","","K221564","","","K232156"],["Product Code","","","POK","","","POK","","","POK"],["Regulation Number","","","21 CFR §892.2060","","","21 CFR §892.2060","","","21 CFR §892.2060"],["Intended\nUse/Indications for\nUse","","","Brainomix 360 e-ASPECTS is a\ncomputer-aided diagnosis\n(CADx) software device used\nto assist the clinician in the\nassessment and\ncharacterization of brain\ntissue abnormalities using CT\nimage data.\nThe software automatically\nregisters images and uses an\natlas to segment and analyze\nASPECTS regions. Brainomix\n360 e-ASPECTS extracts image\ndata from individual voxels in\nthe image to provide analysis\nand computer analytics and\nrelates the analysis to the\natlas defined ASPECTS regions.","","","Brainomix 360 e-ASPECTS is a\ncomputer-aided diagnosis\n(CADx) software device used\nto assist the clinician in the\nassessment and\ncharacterization of brain\ntissue abnormalities using CT\nimage data.\nThe software automatically\nregisters images and uses an\nAtlas to segment and analyze\nASPECTS regions. Brainomix\n360 e-ASPECTS extracts image\ndata from individual voxels in\nthe image to provide analysis\nand computer analytics and\nrelates the analysis to the\natlas defined ASPECTS regions.","","","Rapid ASPECTS is a computer-\naided diagnosis (CADx)\nsoftware device used to assist\nthe clinician in the assessment\nand characterization of brain\ntissue abnormalities using CT\nimage data.\nThe Software automatically\nregisters images and segments\nand analyzes ASPECTS Regions\nof Interest (ROls). Rapid\nASPECTS extracts image data\nfor the ROI(s) to provide\nanalysis and computer\nanalytics based on\nmorphological characteristics.\nThe imaging features are then\nsynthesized by an artificial"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243294-p15-t0","doc_id":"K243294","page_num":15,"bbox":[72.46,93.5,532.71,769.18],"n_rows":4,"n_cols":10,"columns":["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],"rows":[["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],["","Parameter","","","Brainomix 360 e-ASPECTS","","","Brainomix 360 e-ASPECTS","",""],["","","","","(K243294)","","","(K221564)","",""],["","","","The imaging features are then\nsynthesized by an artificial\nintelligence algorithm into a\nsingle ASPECTS (Alberta Stroke\nProgram Early CT) score.\nBrainomix 360 e-ASPECTS is\nindicated for evaluation of\npatients presenting for\ndiagnostic imaging workup for\nevaluation of extent of\ndisease. Extent of disease\nrefers to the number of\nASPECTS regions affected\nwhich is reflected in the total\nscore. Brainomix 360 e-\nASPECTS provides information\nthat may be useful in the\ncharacterization of ischemic\nbrain tissue injury during\nimage interpretation (within\n24 hours from time last known\nwell).\nBrainomix 360 e-ASPECTS\nprovides a comparative\nanalysis to the ASPECTS\nstandard of care radiologist\nassessment by providing\nhighlighted ASPECTS regions\nand an automated editable\nASPECTS score for clinician\nreview. Brainomix 360 e-\nASPECTS additionally provides\na visualization of the voxels\ncontributing to and excluded\nfrom the automated ASPECTS\nscore and a calculation of the\nvoxel volume contributing to\nASPECTS score.\nLimitations:\n1. Brainomix 360 e-ASPECTS is\nnot intended for primary\ninterpretation of CT images. It\nis used to assist physician\nevaluation.\n2. The ASPECTS score should\nbe only used for ischemic\nstroke patients following the\nstandard of care.\n3. Brainomix 360 e-ASPECTS\nhas only been validated and is","","","The imaging features are then\nsynthesized by an artificial\nintelligence algorithm into a\nsingle ASPECTS (Alberta Stroke\nProgram Early CT) Score.\nBrainomix 360 e-ASPECTS is\nindicated for evaluation of\npatients presenting for\ndiagnostic imaging workup\nwith known MCA or ICA\nocclusion, for evaluation of\nextent of disease. Extent of\ndisease refers to the number\nof ASPECTS regions affected\nwhich is reflected in the total\nscore. Brainomix 360 e-\nASPECTS provides information\nthat may be useful in the\ncharacterization of ischemic\nbrain tissue injury during\nimage interpretation (within 6\nhours from time last known\nwell).\nBrainomix 360 e-ASPECTS\nprovides a comparative\nanalysis to the ASPECTS\nstandard of care radiologist\nassessment by providing\nhighlighted ASPECTS regions\nand an automated editable\nASPECTS score for clinician\nreview. Brainomix 360 e-\nASPECTS additionally provides\na visualization of the voxels\ncontributing to the automated\nASPECTS score and the voxels\nexcluded from the automated\nASPECTS score.\nLimitations:\n1. Brainomix 360 e-ASPECTS is\nnot intended for primary\ninterpretation of CT images. It\nis used to assist physician\nevaluation.\n2. Brainomix 360 e-ASPECTS\nhas been validated in patients\nwith known MCA or ICA\nocclusion prior to ASPECTS\nscoring.","","","intelligence algorithm into a\nsingle ASPECT (Alberta Stroke\nProgram Early CT) Score.\nRapid ASPECTS is indicated for\nevaluation of adult patients\npresenting for diagnostic\nimaging workup, for\nevaluation of extent of\ndisease. Extent of disease\nrefers to the number of\nASPECTS regions affected\nwhich is reflected in the total\nscore. This device provides\ninformation that may be\nuseful in the characterization\nof early ischemic brain tissue\ninjury for ischemic stroke\npatient (typically, < 24 hours\nsince last known well) during\nimage interpretation following\nthe standard of care. Rapid\nASPECTS provides a\ncomparative analysis to the\nASPECTS standard of care\nradiologist assessment using\nthe ASPECTS atlas definitions\nand atlas display including\nhighlighted ROls and\nnumerical scoring. Rapid\nASPECTS presents the original\nand annotated images for\nconcurrent reads.\nLimitations:\n1. The ASPECTS score should\nbe only used for ischemic\nstroke patients following the\nstandard of care.\n2. Rapid ASPECTS is an adjunct\ntool and is not intended to\nreplace a clinicians review of\nthe original imaging or their\nclinical judgement.\n3. Physicians should not use\nthe CAD generated output as\nthe primary interpretation\nwithout their concurrence.\nContraindications/Exclusions/\nCautions:"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243294-p16-t0","doc_id":"K243294","page_num":16,"bbox":[72.42,93.5,532.74,761.26],"n_rows":6,"n_cols":10,"columns":["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],"rows":[["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],["","Parameter","","","Brainomix 360 e-ASPECTS","","","Brainomix 360 e-ASPECTS","",""],["","","","","(K243294)","","","(K221564)","",""],["","","","intended to be used in patient\npopulations aged over 21\nyears.\n4. Brainomix 360 e-ASPECTS is\nnot intended for mobile\ndiagnostic use. Images viewed\non a mobile platform are\ncompressed preview images\nand not for diagnostic\ninterpretation.\n5. Brainomix 360 e-ASPECTS\nhas been validated and is\nintended to be used on\nSiemens Somatom Definition\nscanners.\nContraindications/\nExclusions/Cautions:\n• Patient motion: Excessive\npatient motion leading to\nartifacts that make the scan\ntechnically inadequate\n• Hemorrhagic\nTransformation, Hematoma","","","3. Brainomix 360 e-ASPECTS is\nnot suitable for use on brain\nscans displaying neurological\npathologies other than acute\nstroke, such as tumors or\nabscesses, hemorrhagic\ntransformation and\nhematoma.\n4. Use of Brainomix 360 e-\nASPECTS Module in clinical\nsettings other than brain\nischemia within 6 hours from\ntime last known well, caused\nby known ICA or MCA\nocclusions has not been\ntested.\n5. Brainomix 360 e-ASPECTS\nhas been validated and is\nintended to be used on\nSiemens Somatom Definition\nscanners.\n6. Brainomix 360 e-ASPECTS\nhas only been validated and is\nintended to be used in patient\npopulations aged over 21\nyears.\n7. Brainomix 360 e-ASPECTS is\nnot intended for mobile\ndiagnostic use. Images viewed\non a mobile platform are\ncompressed preview images\nand not for diagnostic\ninterpretation.\nContraindications/\nExclusions/Cautions:\n• Patient motion: Excessive\npatient motion leading to\nartifacts that make the scan\ntechnically inadequate\n• Hemorrhagic\nTransformation, Hematoma","","","• Patient Motion: excessive\nmotion leading to artifacts\nthat make the scan\ntechnically inadequate.\n• Hemorrhagic\nTransformation,\nHematoma\n• Very thin or no Ventricles"],["Environment of use","","","Clinical/Hospital environment","","","Clinical/Hospital environment","","","Clinical/Hospital environment"],["Energy used and/or\ndelivered","","","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","","","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","","","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243294-p17-t0","doc_id":"K243294","page_num":17,"bbox":[72.39,93.5,532.77,650.74],"n_rows":23,"n_cols":10,"columns":["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],"rows":[["","Characteristics/","","","Proposed Device","","","Predicate Device","","Reference Device\nRapid ASPECTS (v3)\n(K232156)"],["","Parameter","","","Brainomix 360 e-ASPECTS","","","Brainomix 360 e-ASPECTS","",""],["","","","","(K243294)","","","(K221564)","",""],["Primary Users","","","Neuroradiologist/Clinician","","","Neuroradiologist/Clinician","","","Neuroradiologist/Clinician"],["Clinical Application\n/Anatomical region","","","Stroke/Head","","","Stroke/Head","","","Stroke/Head"],["Standard of Care","","","ASPECTS Scoring","","","ASPECTS Scoring","","","ASPECTS Scoring"],["Design: Modalities\nfor image processing\nand visualization","","","CT","","","CT","","","CT"],["Technical\nImplementation","","","ML/AI/Random Forest","","","ML/AI/Random Forest","","","ML/AI/Random Forest"],["Image Overlay","","","ASPECTS regions, highlighted\nby algorithms. Voxel-wise\nanalysis visualized as a heat\nmap.","","","ASPECTS regions, highlighted\nby algorithms. Voxel-wise\nanalysis visualized as a heat\nmap.","","","ASPECTS Atlas ROIs,\nhighlighted by algorithms"],["Gating Conditions","","","None","","","Users must confirm ICA or\nMCA occlusion prior to\naccessing Brainomix 360 e-\nASPECTS results.","","","None"],["Design: PACS\nfunctionality","","","View process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and\nlisting.","","","View process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and\nlisting.","","","View process and analyze\nmedical images. Performs\nstandard PACS functions with\nrespect to querying and\nlisting."],["Design: DICOM\ncompliance","","","Yes","","","Yes","","","Yes"],["Design: Computer\nPlatform","","","Standard off-the-shelf server\nor virtual server","","","Standard off-the-shelf server\nor virtual server","","","Standard off-the-shelf server\nor virtual server"],["Design: Data\nacquisition","","","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities","","","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities","","","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities"],["Alters Standard of\nCare Workflow","","","In parallel to","","","In parallel to","","","In parallel to"],["Materials","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Biocompatibility","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Sterility","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Electrical Safety","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Mechanical Safety","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Chemical Safety","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Thermal Safety","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"],["Radiation Safety","","","N/A – Software only device","","","N/A – Software only device","","","N/A – Software only device"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243331-p8-t0","doc_id":"K243331","page_num":8,"bbox":[228.68,430.36,571.98,481.3],"n_rows":3,"n_cols":4,"columns":["Measurement","Bland Altman: Mean,\n(LOA) (% points)","Data Range (%\npoints)","Pearson’s\nCorrelation (r)"],"rows":[["Measurement","Bland Altman: Mean,\n(LOA) (% points)","Data Range (%\npoints)","Pearson’s\nCorrelation (r)"],["Biplane EF","1.22, (-8.49, 10.93)","8.8 – 73.6","0.95"],["GLS","-1.27 (-5.16, 2.62)","-3.35 - -25.41","0.92"]],"caption_candidate":"provided for 139 exams (84%) in which the system correctly identified 4, 2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243335-p5-t0","doc_id":"K243335","page_num":5,"bbox":[93.42,237.5,527.02,317.06],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction\nProcessing Unit for MR"],["Model Number:","MRT-3020"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243335-p6-t0","doc_id":"K243335","page_num":6,"bbox":[90.24,518.74,365.02,590.8],"n_rows":5,"n_cols":2,"columns":["System","Predicate Device"],"rows":[["System","Predicate Device"],["","Vantage Galan 3T, MRT-3020, V10.0 with AiCE\nReconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K241496"],["Clearance Date","August 20, 2024"]],"caption_candidate":"(K241496)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243335-p7-t0","doc_id":"K243335","page_num":7,"bbox":[90.24,149.48,365.32,221.6],"n_rows":5,"n_cols":2,"columns":["System","Reference Device"],"rows":[["System","Reference Device"],["","Vantage Galan 3T, MRT-3020, V9.0 with AiCE\nReconstruction Processing Unit for MR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K230355"],["Clearance Date","August 30, 2023"]],"caption_candidate":"(K230355)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243335-p7-t1","doc_id":"K243335","page_num":7,"bbox":[95.04,629.5,558.49,703.68],"n_rows":6,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Galan 3T, MRT-3020,","","","Vantage Galan 3T, MRT-3020,","",""],["","","V10.0","","","V10.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR (K241496)","",""],["Static field strength","3T","","","3T","","","Same"]],"caption_candidate":"20. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243335-p8-t0","doc_id":"K243335","page_num":8,"bbox":[95.0,84.36,558.52,336.44],"n_rows":11,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Galan 3T, MRT-3020,","","","Vantage Galan 3T, MRT-3020,","",""],["","","V10.0","","","V10.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR (K241496)","",""],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243341-p6-t0","doc_id":"K243341","page_num":6,"bbox":[53.64,107.76,539.58,703.86],"n_rows":5,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],["Regulation\nNumber/Name","21 CFR 892.2090/\nRadiological Computer Assisted\nDetection and Diagnosis Software","Same","N/A"],["Product Code","QDQ","Same","N/A"],["Classification\nDescription","A radiological computer assisted\ndetection and diagnostic software for\nsuspected lesions is an image\nprocessing device intended to aid in\nthe detection, localization, and\ncharacterization of lesions suspicious\nfor cancer on acquired medical images\n(e.g., mammography, MR, CT,\nultrasound, radiography). The device\ndetects, identifies and characterizes\nlesions suspicious for cancer based on\nfeatures or information extracted\nfrom the images, and may provide\ninformation about the presence,\nlocation, and characteristics of the\nlesion to the user. Primary diagnostic\nand patient management decisions\nare made by the clinical user.","Same","N/A"],["Indications for Use","Genius AI Detection 2.0 is a computer-\naided detection and diagnosis\n(CADe/CADx) software device\nintended to be used with compatible\ndigital breast tomosynthesis (DBT)\nsystems to identify and mark regions\nof interest including soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in DBT exams from\ncompatible DBT systems and provide\nconfidence scores that offer\nassessment for Certainty of Findings\nand a Case Score. The device intends\nto aid in the interpretation of digital\nbreast tomosynthesis exams in a\nconcurrent fashion, where the\ninterpreting physician confirms or","Same","N/A"]],"caption_candidate":"Summary of Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243341-p7-t0","doc_id":"K243341","page_num":7,"bbox":[53.64,78.78,539.58,713.22],"n_rows":14,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],["","dismisses the findings during the\nreading of the exam.","",""],["Compatible DBT\nSystems","Envision Mammography Platform\nSupports the following modes:\n• High resolution 1-mm slices\n(Clarity HD)\n• High resolution 6-mm smart\nslices (3DQuorum)","Hologic Selenia Dimensions\nHologic 3Dimensions\nSupports both models in the\nfollowing modes:\n• Standard\nresolution 1-mm slices\n• High resolution\n1-mm slices (Clarity\nHD)\n• High resolution\n6-mm smart slices\n(3DQuorum)","The Envision\nMammography\nPlatform\nsupports High\nresolution slices;\nstandard\nresolution is not\navailable."],["Type of CAD\nSoftware","Radiological computer assisted\ndetection and diagnostic software","Same","N/A"],["Mode of Action","Image processing device utilizing\nmachine learning to aid in the\ndetection, localization, and\ncharacterization of soft tissue\ndensities (masses, architectural\ndistortions and asymmetries) and\ncalcifications in the 1-mm 3D DBT\nslices. Findings are co-registered to 6-\nmm SmartSlices.","Same","N/A"],["Clinical Output","To inform the primary diagnostic and\npatient management decisions that\nare made by the clinical user.","Same","N/A"],["Patient Population","Symptomatic and asymptomatic\nwomen undergoing mammography.","Same","N/A"],["End Users","MQSA- Qualified Interpreting\nPhysicians and Radiologists","Same","N/A"],["Image Source\nModalities","Digital Breast Tomosynthesis Slices","Same","N/A"],["Output Device","Softcopy Workstation","Same","N/A"],["Deployment","Stand-alone computer","Same","N/A"],["Method of Use","Concurrent reading","Same","N/A"],["Supported Views","CC and MLO","Same","N/A"],["Visualization\nFeatures","Places mark within suspicious lesion\nby default (Emphasize ™; RightOn™)","Same","N/A"]],"caption_candidate":"Genius AI Detection 2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243341-p8-t0","doc_id":"K243341","page_num":8,"bbox":[53.64,78.78,539.58,214.5],"n_rows":2,"n_cols":4,"columns":["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],"rows":[["Features and\nCharacteristics","Subject Device\nHologic, Inc.\nGenius AI Detection 2.0","Predicate Device\nHologic, Inc.\nGenius AI Detection\n2.0 (K221449)","Difference and\nComments"],["","and reports confidence of finding next\nto each identified lesion in the image.\nCAD display may be toggled on/off.\nOption to automatically zoom into or\ncontour the suspicious region of\ninterest (PeerView™).","",""]],"caption_candidate":"Genius AI Detection 2.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243350-p8-t0","doc_id":"K243350","page_num":8,"bbox":[72.0,417.9,562.56,713.7],"n_rows":21,"n_cols":5,"columns":["Product Name","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)"],"rows":[["Product Name","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)"],["Regula'on","","21 CFR 892.2050; Medical image","","21 CFR 892.2050; Medical image\nmanagement and processing system"],["","","management and processing system","",""],["Product Code","","QIH","","LLZ, QIH"],["Intended\nUse/\nIndica'ons for\nUse\nStatement","","Rapid Neuro3D (RN3D) is an image","","Rapid is an image processing soOware\npackage to be used by trained professionals,\nincluding but not limited to physicians\n(medical analysis and decision making) and\nmedical technicians (administra've case\nprocessing). The soOware runs on a standard\noff-the-shelf computer or a virtual pla`orm,\nsuch as VMware, and can be used to perform\nimage viewing, processing, and analysis of\nimages. Data and images are acquired\nthrough DICOM compliant imaging devices.\nRapid is indicated for Adults only.\nRapid provides both viewing and analysis\ncapabili'es for func'onal and dynamic\nimaging datasets acquired with CT, CT\nPerfusion (CTP), CT Angiography (CTA), C-arm\nCT Perfusion and MRI including a Diffusion"],["","","analysis soOware for imaging datasets","",""],["","","acquired with conven'onal CT","",""],["","","Angiography (CTA) from the aor'c arch to","",""],["","","the vertex of the head). The module","",""],["","","removes bone, 'ssue, and venous","",""],["","","vessels, providing a 3D and 2D","",""],["","","visualiza'on of the neurovasculature","",""],["","","supplying arterial blood to the brain.","",""],["","","Outputs of the device include 3D","",""],["","","rota'onal maximum intensity projec'ons","",""],["","","(MIPS), volume renders (VR), along with","",""],["","","the curved planar reforma'on (CPR) of","",""],["","","the isolated leO and right internal caro'd","",""],["","","and vertebral arteries.","",""],["","","Rapid Neuro3D is designed to support","",""],["","","the physician in confirming the presence","",""]],"caption_candidate":"software is substantially equivalent.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243350-p9-t0","doc_id":"K243350","page_num":9,"bbox":[72.0,75.9,562.56,705.06],"n_rows":45,"n_cols":5,"columns":["Product Name","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)"],"rows":[["Product Name","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)"],["o","","or absence of physician-iden'fied lesions","","Weighted MRI (DWI) Module and a Dynamic\nAnalysis Module (dynamic contrast-enhanced\nimaging data for MRI, CT, and C-arm CT).\nRapid C-arm CT Perfusion can be used to\nqualita'vely assess cerebral hemodynamics in\nthe angiography suite.\nThe CT analysis includes NCCT maps showing\nareas of hypodense and hyperdense 'ssue.\nThe DWI Module is used to visualize local\nwater\ndiffusion proper'es from the analysis of\ndiffusion -weighted MRI data.\nThe Dynamic Analysis Module is used for\nvisualiza'on and analysis of dynamic imaging\ndata, showing proper'es of changes in\ncontrast over 'me. This func'onality includes\ncalcula'on of parameters related to 'ssue\nflow (perfusion) and 'ssue blood volume.\nRapid CT Perfusion and Rapid MR Perfusion\ncan be used by physicians to aid in the\nselec'on of acute stroke pa'ents (with\nknown occlusion of the intracranial internal\ncaro'd artery or proximal middle cerebral\nartery).\nInstruc'ons for the use of contrast agents for\nthis indica'on can be found in Appendix A of\nthe User’s Manual. Addi'onal informa'on for\nsafe and effec've drug use is available in the\nproduct-specific iodinated CT and gadolinium-\nbased MR contrast drug labeling.\nIn addi'on to the Rapid imaging criteria,\npa'ents must meet the clinical requirements\nfor thrombectomy, as assessed by the\nphysician, and have none of the following\ncontraindica'ons or exclusions:\n• Bolus Quality: absent or inadequate bolus.\n• Pa'ent Mo'on: excessive mo'on leading to\nar'facts that make the scan technically\ninadequate."],["","","and evalua'on, documenta'on, and","",""],["","","follow-up of any such lesion and","",""],["","","treatment planning.","",""],["","","Its results are not intended to be used on","",""],["","","a stand-alone basis for clinical decision-","",""],["","","making or otherwise preclude clinical","",""],["","","assessment.","",""],["","","RN3D is indicated for adults.","",""],["","","Precau'ons/Exclusions:","",""],["","","Series containing excessive pa'ent","",""],["","","mo'on or metal implants may impact","",""],["","","module output quality.","",""],["","","","",""],["","","The RN3D module will not process series","",""],["","","that meet the following module exclusion","",""],["","","criteria:","",""],["","","• Series containing inadequate contrast","",""],["","","agent (<0.3 mL of right-hemisphere","",""],["","","intracranial arterial contrast media or","",""],["","","<0.3 mL of leO-hemisphere","",""],["","","intracranial arterial contrast media,","",""],["","","above 120 HU)","",""],["","","• Series acquired w/cone-beam CT","",""],["","","scanners (c-arm CT)","",""],["","","• Series that are non-axial","",""],["","","• Series with a non-supine pa'ent","",""],["","","posi'on","",""],["","","• Series containing missing or","",""],["","","improperly ordered slices (e.g., as a","",""],["","","result of manual correc'on by an","",""],["","","imaging technician)","",""],["","","• CTA datasets with:","",""],["","","1) in-plane X and Y FOV < 160mm or","",""],["","","> 400mm.","",""],["","","2) Z FOV (cranio-caudal transverse","",""],["","","anatomical coverage) < 90 mm.","",""],["","","3) in-plane pixel spacing (X & Y","",""],["","","resolu'on) < 0.2 mm or > 1.0 mm.","",""],["","","4) Z slice spacing of < 0.2 mm or >","",""],["","","1.25 mm.","",""],["","","5) slice thickness > 1.5mm.","",""],["","","6) data acquired at x-ray tube voltage","",""],["","","< 70kVp or > 150kVp.","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243350-p10-t0","doc_id":"K243350","page_num":10,"bbox":[72.01,75.9,562.55,674.85],"n_rows":22,"n_cols":7,"columns":["Product Name","","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)",""],"rows":[["Product Name","","","Rapid Neuro3D (Subject Device)","","Rapid (including Rapid CTA) (K233582)",""],["","","","","","• Presence of hemorrhage.\n• C-Arm CTP is not used in the Rapid\nThrombectomy\nindica'on for pa'ent selec'on criteria, other\nmodali'es should be consulted.\nCau'on\nCBV and CBT are not absolute and CBT, CBV,\nMTT and Tmax are supported for qualita've\ninterpreta'on of the perfusion maps only.",""],["Intended\nUsers","","","Radiologists, neurovascular and","","Medical imaging professionals who analyze\n'ssue using CT or MRI images",""],["","","","neurosurgical specialists, such as","","",""],["","","","vascular neurosurgeons, neuro-","","",""],["","","","interven'onal specialists, ED physicians,","","",""],["","","","or users with similar training.","","",""],["","Technological CharacterisDcs","","","","",""],["Func'onality","","","SoOware package (SaMD) which","","SoOware package (SaMD) which interfaces to\na PACS/Viewer or allows viewing within the\napplica'on.",""],["","","","interfaces to a PACS/Viewer or allows","","",""],["","","","viewing within the applica'on.","","",""],["Computer\nPla`orm","","Standard off-the-shelf Hardware: On-\nPremises or Cloud Hybrid","Standard off-the-shelf Hardware: On-","","Standard off-the-shelf Hardware: On-\nPremises or Cloud\nHybrid",""],["","","","Premises or Cloud Hybrid","","",""],["Technical\nImplementatio\nn","","AI/ML","","","Mixed - Tradi'onal Coding and AI/ML",""],["Input DICOM\nImaging\nModality","","CTA","","","CT, CTP, CTA, C-arm CT, MRI, NCCT",""],["Imaging Type","","","Neurological (aor'c arch to the vertex","","Neurological",""],["","","","of the head)","","",""],["SoOware\nOutputs","","• 2D/3D vessel visualiza'on (Thins, MIPS,\nVR, CPR)\n• Automated segmenta'on and removal\nof obstruc've bones and/or vessels","• 2D/3D vessel visualiza'on (Thins, MIPS,","","• Digital image processing, visualiza'on, and\nanalysis tools (various detailed in IFU above,\nincluding 'ssue flow (perfusion), 'ssue blood\nvolume, etc.)\nSpecifically for Rapid CTA:\n• 2D/3D vessel visualiza'on (MIPS, colored\noverlay indica'ng reduc'on of vessel density)\n• Automated segmenta'on and removal of\nobstruc've bones and/or vessels",""],["","","","VR, CPR)","","",""],["","","","• Automated segmenta'on and removal","","",""],["","","","of obstruc've bones and/or vessels","","",""],["","","","","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p5-t0","doc_id":"K243363","page_num":5,"bbox":[72.24,525.84,523.08,552.12],"n_rows":2,"n_cols":4,"columns":["Manufacturer","Predicate Trade Name","Application No.","Product Code"],"rows":[["Manufacturer","Predicate Trade Name","Application No.","Product Code"],["Viz.ai, Inc.","Viz ICH","K193658","QAS"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p7-t0","doc_id":"K243363","page_num":7,"bbox":[72.32,580.71,523.04,738.81],"n_rows":10,"n_cols":9,"columns":["","","","","Viz ICH","","","JLK-ICH",""],"rows":[["","","","","Viz ICH","","","JLK-ICH",""],["","Image Analysis","","","","","","",""],["","Supported Imaging","","Non-contrast CT (NCCT)","","","Non-contrast CT (NCCT)","",""],["","Modality","","","","","","",""],["","Alteration of Original","","No","","","No","",""],["","Image Database","","","","","","",""],["","Results of Image","","Internal, no image marking","","","Internal, no image marking","",""],["","Analysis","","","","","","",""],["","Image Viewing Functionality","","","","","","",""],["Preview Images","","","Initial assessment, non-\ndiagnostic purposes","","","Initial assessment, non-\ndiagnostic purposes","",""]],"caption_candidate":"device, the previously cleared Viz ICH. Thus, JLK-ICH is substantially equivalent.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p8-t0","doc_id":"K243363","page_num":8,"bbox":[72.32,85.35,523.07,388.74],"n_rows":17,"n_cols":6,"columns":["View DICOM Data","","","DICOM Information about the\npatient, study and current\nimage.","DICOM Information about the\npatient, study and current\nimage.",""],"rows":[["View DICOM Data","","","DICOM Information about the\npatient, study and current\nimage.","DICOM Information about the\npatient, study and current\nimage.",""],["","Image viewing and any","","Yes","Yes",""],["","manipulation (window,","","","",""],["","pan, level, zoom)","","","",""],["Segmentation of region\nof interest","","","No; device does not mark,\nhighlight, or direct users'\nattention to a specific location in\nthe original image.","No; device does not mark,\nhighlight, or direct users'\nattention to a specific location in\nthe original image.",""],["","Technological Characteristics","","","",""],["","Compatibility with the","","DICOM Compatible","DICOM Compatible",""],["","environment and other","","","",""],["","devices","","","",""],["","Transfer, store, and","","Yes","Yes",""],["","process DICOM images","","","",""],["","Technical","","Artificial intelligence algorithm\nwith database of images","Artificial intelligence algorithm\nwith database of images",""],["","Implementation","","","",""],["","Interference with","","No. Cases are not removed\nfrom worklist or deprioritized.","No. Cases are not removed\nfrom worklist or deprioritized.",""],["","standard workflow","","","",""],["Data acquisition","","","Acquires medical image data\nfrom DICOM-compliant imaging\ndevices and modalities","Acquires medical image data\nfrom DICOM-compliant imaging\ndevices and modalities",""],["","Time to Notification","","0.49±0.15 minutes","0.19 ±0.04 minutes",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p9-t0","doc_id":"K243363","page_num":9,"bbox":[72.28,573.36,523.04,665.88],"n_rows":5,"n_cols":6,"columns":["","Performance Metrics Overview for Patients Categorized by Age","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Age","","","",""],["","Age Range\n(Years)","N","Sensitivity [95% CI]","Specificity [95% CI]",""],["<50","","74","0.94 [0.86, 1.00]","0.97 [0.91, 1.00]",""],["50-70","","146","0.95 [0.89, 1.00]","1.0 [1.00, 1.00]",""],["70<","","156","1.0 [1.00, 1.00]","0.96 [0.90, 1.00]",""]],"caption_candidate":"various confounding variables:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p9-t1","doc_id":"K243363","page_num":9,"bbox":[72.28,683.25,523.04,768.0],"n_rows":5,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Gender","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Gender","","","","","","","",""],["","Gender","N","","","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Male","","188","","0.98 [0.95, 1.00]","","","0.97 [0.92, 1.00]","",""],["Female","","187","","0.97 [0.92, 1.00]","","","0.99 [0.97, 1.00]","",""],["Unknown","","1","","1.0 [1.00, 1.00]","","","-","",""]],"caption_candidate":"70< 156 1.0 [1.00, 1.00] 0.96 [0.90, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p10-t0","doc_id":"K243363","page_num":10,"bbox":[72.27,85.98,523.05,204.36],"n_rows":7,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Race-Ethnicity","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Race-Ethnicity","","","","","","","",""],["","Race-Ethnicity","N","","","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Non-Hispanic White","","263","","0.99 [0.97, 1.00]","","","0.97 [0.94, 1.00]","",""],["Hispanic or Latino","","35","","1.0 [1.00, 1.00]","","","1.0 [1.00, 1.00]","",""],["Black or African American","","60","","0.9 [0.76, 1.00]","","","0.97 [0.92, 1.00]","",""],["Asian & Pacific Islander","","8","","0.83 [0.50, 1.00]","","","1.0 [0.00, 1.00]","",""],["Unknown / Refused","","10","","1.0 [0.00, 1.00]","","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p10-t1","doc_id":"K243363","page_num":10,"bbox":[72.27,223.14,523.05,325.2],"n_rows":6,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Scanner Manufacturer","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Scanner Manufacturer","","","","","","","",""],["","Manufacturer","N","","","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["General Electric","","118","","0.96 [0.90, 1.00]","","","0.98 [0.95, 1.00]","",""],["Siemens","","161","","0.98 [0.95, 1.00]","","","0.97 [0.93, 1.00]","",""],["Philips","","77","","0.97 [0.90, 1.00]","","","0.98 [0.93, 1.00]","",""],["Toshiba / Canon","","20","","1.0 [1.00, 1.00]","","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Unknown / Refused 10 1.0 [0.00, 1.00] 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p10-t2","doc_id":"K243363","page_num":10,"bbox":[72.27,345.06,523.05,420.0],"n_rows":5,"n_cols":9,"columns":["","Performance Metrics Overview for Patients Categorized by Slice Thickness","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Slice Thickness","","","","","","",""],["Slice Thickness","","N","","Sensitivity","","","Specificity",""],["","","","","[95% CI]","","","[95% CI]",""],["2.5mm≤Slice thickness <3.5mm","","62","1.0 [0.00, 1.00]","","","1.0 [1.00, 1.00]","",""],["3.5mm≤Slice thickness ≤5mm","","314","0.97 [0.95, 0.99]","","","0.97 [0.94, 0.99]","",""]],"caption_candidate":"Toshiba / Canon 20 1.0 [1.00, 1.00] 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p10-t3","doc_id":"K243363","page_num":10,"bbox":[72.27,439.86,523.05,592.2],"n_rows":9,"n_cols":9,"columns":["","Performance Metrics Overview for Patients Categorized by ICH Subtype","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by ICH Subtype","","","","","","",""],["","ICH Subtype","","","N","","","Sensitivity [95% CI]",""],["Intraparenchymal Hemorrhage (IPH)","","","36","","","1.0 [1.00, 1.00]","",""],["Intraventricular Hemorrhage (IVH)","","","12","","","0.92 [0.75, 1.00]","",""],["Subarachnoid Hemorrhage (SAH)","","","32","","","0.97 [0.91, 1.00]","",""],["Subdural Hemorrhage (SDH)","","","22","","","0.95 [0.86, 1.00]","",""],["Epidural Hemorrhage (EDH)","","","3","","","0.67 [0.00, 1.00]","",""],["SDH or EDH*","","","15","","","1.0 [1.00, 1.00]","",""],["Multiple","","","68","","","0.99 [0.96, 1.00]","",""]],"caption_candidate":"3.5mm≤Slice thickness ≤5mm 314 0.97 [0.95, 0.99] 0.97 [0.94, 0.99]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p10-t4","doc_id":"K243363","page_num":10,"bbox":[72.27,639.33,523.05,743.64],"n_rows":6,"n_cols":9,"columns":["","Performance Metrics Overview for Patients Categorized by ICH Volume","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by ICH Volume","","","","","","",""],["","Volume (mL)","","","N","","","Sensitivity [95% CI]",""],["Volume < 1","","","20","","","0.8 [0.60, 0.95]","",""],["1 ≤ Volume < 5","","","33","","","1.0 [1.00, 1.00]","",""],["5 ≤ Volume < 10","","","28","","","1.0 [1.00, 1.00]","",""],["Volume ≥ 10","","","107","","","0.99 [0.97, 1.00]","",""]],"caption_candidate":"or an epidural hematoma.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243363-p11-t0","doc_id":"K243363","page_num":11,"bbox":[72.27,126.96,523.05,207.36],"n_rows":3,"n_cols":15,"columns":["","NCCT-to-notification","","","Mean Estimate","","","95% Lower CI","","","95% Upper CI","","","Median",""],"rows":[["","NCCT-to-notification","","","Mean Estimate","","","95% Lower CI","","","95% Upper CI","","","Median",""],["K193658, Viz ICH","","","0.49","","","0.47","","","0.51","","","n/a","",""],["JLK-ICH","","","0.19","","","0.186","","","0.197","","","0.20","",""]],"caption_candidate":"positive cases was also evaluated.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p7-t0","doc_id":"K243376","page_num":7,"bbox":[72.27,177.65,702.9,527.52],"n_rows":7,"n_cols":4,"columns":["ITEM","Proposed Device: uAngio AVIVA CX","Predicate Device: Azurion R2.1(K200917)","Remark"],"rows":[["ITEM","Proposed Device: uAngio AVIVA CX","Predicate Device: Azurion R2.1(K200917)","Remark"],["Classification Name","Image-intensified fluoroscopic x-ray\nsystem","Image-intensified fluoroscopic x-ray system","Same"],["Classification Regulation","21 CFR, Part 892.1650","21 CFR, Part 892.1650","Same"],["Classification Panel","Radiology","Radiology","Same"],["Device Class","II","II","Same"],["Product Code","OWB, JAA","OWB, JAA","Same"],["Indications for Use","The system is used to perform image\nguidance in diagnostic, intervention and\nsurgical procedures.\nProcedures that can be performed with the\nsystem include cardiac angiography,\nneuro-angiography, vascular and non-\nvascular angiography, rotational\nangiography and whole body\nradiographic/fluoroscopic procedures.","The Azurion series (within the limits of the\nused operating room table) is intended for use\nto perform:\n• Image guidance in diagnostic, interventional,\nand minimally invasive surgery procedures for\nthe following clinical application areas:\nvascular, non-vascular, cardiovascular, and\nneuro procedures.\n•Cardiac imaging applications including\ndiagnostics, interventional and minimally\ninvasive surgery procedures.\nAdditionally:\n•The Azurion series can be used in a hybrid\noperating room.\n•The Azurion series contains a number of\nfeatures to support a flexible and patient-centric","Note1"]],"caption_candidate":"as below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p8-t0","doc_id":"K243376","page_num":8,"bbox":[72.24,108.02,702.94,508.78],"n_rows":20,"n_cols":4,"columns":["","","procedural workflow.\nPatient Population:\nAll human patients of all ages. Patient weight is\nlimited to the specification of the patient table.",""],"rows":[["","","procedural workflow.\nPatient Population:\nAll human patients of all ages. Patient weight is\nlimited to the specification of the patient table.",""],["Specifications","","",""],["Generator","","",""],["Max. generator power","100 KW","100 KW","Same"],["Max. current","1000 mA at 100 kV","1000 mA at 100 kV","Same"],["X-ray tube","","",""],["Focal spot","0.4mm, 0.6mm, 1.0mm","0.4mm, 0.7mm","Note2"],["Continuous anode input\npower","3500W","3500W","Same"],["Flat panel detector-config.1","","",""],["Max. field of view","48 cm diagonal","48 cm diagonal","Same"],["Pixel pitch","154 μm","154 μm","Same"],["DQE (at 0lp/mm)","77%","77%","Same"],["Flat panel detector-config.2","","",""],["Max. field of view","48 cm diagonal","48 cm diagonal","Same"],["Pixel pitch","150 μm","154 μm","Note3"],["DQE (at 0lp/mm)","77%","77%","Same"],["Collimator","YES","YES","Same"],["Removable anti-scatter\ngrid","YES","YES","Same"],["Stand","","",""],["longitudinal movement","Max. 6350 mm","Max. 6350 mm","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p9-t0","doc_id":"K243376","page_num":9,"bbox":[72.24,108.02,702.94,523.08],"n_rows":20,"n_cols":4,"columns":["lateral movement range","Max. 2360 mm","Max. 2360 mm","Same"],"rows":[["lateral movement range","Max. 2360 mm","Max. 2360 mm","Same"],["L-arm rotation","±135°","±135°","Same"],["Patient table - config.1 Floating table","","",""],["max. table load","340 kg","325 kg","Note4"],["max. patient weight","280 kg + 600 N for CPR\nCPR can be done in any position of the\ntable top","250 kg + 500 N for CPR.\nCPR can be done in any position of the table\ntop","Note5"],["Pivot","±180°","- 90°/+180° or -180°/+90°","Note6"],["Patient table - config.2 Multi-tilt table","","",""],["max. table load","380 kg","325 kg","Note7"],["max. patient weight","280 kg + 600 N for CPR","250 kg + 500 N for CPR.","Note8"],["Pivot","±180°","-90°/+180° or -180°/90°","Note9"],["tilt","+15°，-20°","±16.5°","Note10"],["cradle","±15°","±15°","Same"],["Image acquisition protocol","","",""],["Fluoroscopy","YES","YES","Same"],["Roadmap","YES","YES","Same"],["Dynamic DR","YES","YES","Same"],["2D DSA","YES","YES","Same"],["Singleshot","YES","YES","Same"],["Cine","YES","YES","Same"],["Bolus Chase and Bolus\nChase Reconstruction","YES","YES","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p10-t0","doc_id":"K243376","page_num":10,"bbox":[72.32,108.02,702.85,281.09],"n_rows":7,"n_cols":4,"columns":["Protocol for Pediatric","YES","YES","Same"],"rows":[["Protocol for Pediatric","YES","YES","Same"],["Software function","","",""],["Camera-assisted\nrecognition (uSpace)","YES","NO","Note11"],["Voice control (uLingo)","YES","NO","Note12"],["Safety","","",""],["basic safety and essential\nperformance","ANSI/AAMI ES60601-1:2005/A2:2021","IEC 60601-1, 2nd Ed.\n+ Amendment No. 1\n+ Amendment No. 2 + Corrigendum","Same"],["Electro Magnetic\nCompatibility","ANSI/AAMI/IEC 60601-1-\n2:2014/A1:2021","IEC 60601-1-2, ed.2.1","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p10-t1","doc_id":"K243376","page_num":10,"bbox":[72.32,308.03,702.85,420.66],"n_rows":11,"n_cols":4,"columns":["ITEM","Proposed Device: uAngio AVIVA CX","Reference Device: SmartCT R1.0(K201583)","Remark"],"rows":[["ITEM","Proposed Device: uAngio AVIVA CX","Reference Device: SmartCT R1.0(K201583)","Remark"],["3D rotational","","",""],["","YES","YES","Same"],["angiography","","",""],["","","",""],["Cone Beam CT (CBCT)","YES","YES","Same"],["High-resolution Cone","","",""],["","YES","YES","Same"],["Beam CT","","",""],["","","",""],["3D Roadmap","YES","YES","Same"]],"caption_candidate":"Compatibility 2:2014/A1:2021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p10-t2","doc_id":"K243376","page_num":10,"bbox":[72.32,462.24,709.76,523.18],"n_rows":4,"n_cols":2,"columns":["Justification",""],"rows":[["Justification",""],["","In general, both products are used to perform image guidance in diagnostic, interventional, and surgery procedures, and"],["Note1","are suitable for all human patients of all ages. The description differences between the two products do not affect safety"],["","and effectiveness."]],"caption_candidate":"3D Roadmap YES YES Same","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p11-t0","doc_id":"K243376","page_num":11,"bbox":[72.18,108.59,709.71,526.81],"n_rows":46,"n_cols":2,"columns":["","uAngio AVIVA CX has one more focal spot than the predicate device. Even if one focal filament fails, the others remain"],"rows":[["","uAngio AVIVA CX has one more focal spot than the predicate device. Even if one focal filament fails, the others remain"],["Note2","operational, and the drive circuits for all three focal filaments are independent. The difference does not introduce safety"],["","and effectiveness issues."],["","The smaller the pixel pitch, the greater the capability to capture fine structures, which means the ability to identify"],["Note3",""],["","smaller lesions and tissues. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.1 Floating table) of the proposed device has a higher weight capacity, meeting the needs of more"],["Note4",""],["","clinical scenarios. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.1 Floating table) of the proposed device has a higher patient weight capacity, enabling it to serve"],["Note5",""],["","a broader patient population. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.1 Floating table) of the proposed device has a larger rotation range, meeting the needs of more"],["Note6",""],["","clinical scenarios. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.2 Multi-tilt table) of the proposed device has a higher weight capacity, meeting the needs of"],["Note7",""],["","more clinical scenarios. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.2 Multi-tilt table) of the proposed device has a higher patient weight capacity, enabling it to"],["Note8",""],["","serve a broader patient population. The difference does not introduce safety and effectiveness issues."],["",""],["","The patient table (config.2 Multi-tilt table) of the proposed device has a larger rotation range, meeting the needs of more"],["Note9",""],["","clinical scenarios. The difference does not introduce safety and effectiveness issues."],["",""],["",""],["","The patient table (config.2 Multi-tilt table) of the proposed device has a broader total tilt range than that of the predicate"],["Note10",""],["","device. The difference does not introduce safety and effectiveness issues."],["",""],["",""],["","uSpace uses multi-view cameras with machine learning methods and includes the following features:"],["","1. uSpace Auto Positioning: it allows users to send a specific body part of the patient to the system and automatically"],["","position it by long-pressing a button. 2. uSpace VeraCT: it allows users to skip the process of conventional AP and lateral"],["","positioning and Test Run during the VeraCT acquisition, and get to the acquisition start point only by long-pressing one"],["Note11","button.3. uSpace Auto SID: adjust the SID within a certain range to make it closer to the patient's surface. 4. uSpace Auto"],["","Parameter: reduce the process of parameters setting based on the patient's actual body thickness. 5. uSpace Iso Tracking:"],["","adjust the table height to align the patient’s isocenter with the C-arm isocenter."],["","System motion is initiated only by the user's continuous triggering and the system is equipped with hardware-based"],["","collision prevention features to ensure safety. The difference does not introduce safety and effectiveness issues."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p12-t0","doc_id":"K243376","page_num":12,"bbox":[72.18,108.59,709.62,178.95],"n_rows":5,"n_cols":2,"columns":["","uLingo is based on a machine learning method and it allows the system to be controlled via user's voice command, such"],"rows":[["","uLingo is based on a machine learning method and it allows the system to be controlled via user's voice command, such"],["","as protocol selection, image browsing, motion control, and tool utilization, to enhance the system's usability. uLingo will"],["Note12","not directly trigger radiation or motion. The system provides voice confirmation/feedback for the functions related to"],["","radiation and motion, for example motion lock/unlock, radiation lock/unlock, protocol selection, motion control, etc. The"],["","difference does not affect safety and effectiveness."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p13-t0","doc_id":"K243376","page_num":13,"bbox":[126.02,529.63,537.48,696.22],"n_rows":2,"n_cols":2,"columns":["Feature","Bench Testing Performed"],"rows":[["Feature","Bench Testing Performed"],["Cone Beam\nCT","The bench tests evaluate the performance of CBCT.\nThe objectives of the tests are to demonstrate:\ni. C-arm positioning accuracy;\nii. Imaging performance of CBCT (including in-plane uniformity,\nspatial resolution, reconstruction section thickness, noise, contrast\nto noise ratio, artifact analyses) can meet the requirements.\niii. Radiation dose can meet the requirements.\nThe geometric phantom, Catphan700 phantom, chest phantom,\nhead phantom, CTDI dosimetry phantom, body phantom and head\nphantom are used in the tests above.\nThe test results show:"]],"caption_candidate":"effective integration into the system:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p14-t0","doc_id":"K243376","page_num":14,"bbox":[126.02,86.18,537.48,698.98],"n_rows":4,"n_cols":2,"columns":["","- The position error of the C-arm is acceptable and the position is\nrepeatable.\n- The imaging performance of CBCT fulfills the requirements.\n- CTDI of CBCT protocols fulfills the requirement.\nNote: CBCT images are not for quantitative use."],"rows":[["","- The position error of the C-arm is acceptable and the position is\nrepeatable.\n- The imaging performance of CBCT fulfills the requirements.\n- CTDI of CBCT protocols fulfills the requirement.\nNote: CBCT images are not for quantitative use."],["Fusion","The tests evaluate the performance of the Image Registration\nAlgorithm.\nThe objectives of the tests are to demonstrate:\n- The accuracy of the Image Registration Algorithm can meet the\nrequirement of mean target registration error (mTRE) less than\nthe pixel diagonal distance.\nThe test results show:\n- Using DSA mask to regist with DSA mask, CBCT, CT, CTA,\nand MR for testing image registration. Each group has three sets\nof test data.\n- All the mTREs of the test cases are smaller than the voxel\ndiagonal distance, which can achieve sub-pixel accuracy\nregistration. Image Registration Algorithm is able to meet the\nverification criteria, the verification result is passed."],["DSA","The tests evaluate the performance of the DSA Algorithm.\nThe objectives of the tests are to demonstrate:\nDynamic range meets the submillimeter vessel simulation\ncomponent is visible across all copper step wedges of the\nsubtracted image.\nContrast sensitivity meets the low millimeter vascular simulation\ncomponent should be visible in a copper step wedge of sufficient\nthickness in the subtraction image.\nThe test results show:\nUsing digital subtraction angiography phantom with\ncompensation test step wedge to test subtracted image of\nDSA，four typical groups（Body，Head，Vascular，\nPediatric） are tested ,each group applying two sets of test data.\nFrom the testing results, submillimeter sized blood vessels can be\nseen in all copper step wedges, and the thickness of blood vessels\nvisible in sufficiently thick copper step wedges meets the\nrequirements."],["3D Roadmap","The tests evaluate the performance of Neuro Registration\nAlgorithm.\nThe objectives of the tests are to demonstrate:\n- The accuracy of neuro registration can meet a precision of at\nleast 1 mm.\nThe test results show:\n- Using 3D DSA mask to register with an FL image for testing\nneuro registration. It has eight sets of test data in the group."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243376-p15-t0","doc_id":"K243376","page_num":15,"bbox":[126.02,86.18,537.48,709.3],"n_rows":4,"n_cols":2,"columns":["","- The registration results of neuro registration algorithm is that the\nmTRE is less than 1mm. The neuro registration was able to meet\na precision of at least 1 mm, the verification was passed."],"rows":[["","- The registration results of neuro registration algorithm is that the\nmTRE is less than 1mm. The neuro registration was able to meet\na precision of at least 1 mm, the verification was passed."],["uChase","The tests evaluate the performance of the Stitching Algorithm.\nThe objectives of the tests are to demonstrate:\n- The accuracy of the Image Registration Algorithm in Stitching\ncan meet the requirement of mean target registration error\n(mTRE) less than the pixel diagonal distance.\n- The stitching results meet the clinical needs, with an average\nscore from clinical specialists higher than 2.\nThe test results show:\n- All the mTREs of the test cases are smaller than the pixel\ndiagonal distance, and the average score of stitching results is\n2.95, which is higher than 2.The Stitching Algorithm was able to\nmeet the verification criteria and the verification of the algorithm\nwas passed."],["uSpace","The tests evaluate the performance of uSpace futures.\nThe objectives of the tests are to demonstrate:\n- Test the performance of the human key point detection accuracy.\n- Test the performance of the collision detection rate.\n- The performance of the auto SID meets the distance\nmaintenance accuracy. And the adjustment of SID meets the\nrequirements of radiation safety and image quality.\nThe test results show:\n- Human key point detection achieves the required accuracy for\nnot deviating from the range of the acquisition field of view.\n- Collision detection achieves the specified detection rate.\n- Auto SID adjustment achieves the required accuracy for\nmaintaining a distance from detector to the patient during C-arm\nrotation or patient table lifting.\nPrimary protective barrier, Field limitation and Air kerma rates\nwere tested within the allowable adjustment range of the system.\nThe radiation safety test results of the uAngio AVIVA CX under\ndifferent SID.\nThe image quality evaluation was tested through the clinical\nevaluation and objective physical characteristics. According to the\nacceptable criteria in the regulations, the image quality test results\nof the uAngio AVIVA CX under different SID meet the\nrequirements."],["uLingo","The tests evaluate the performance of the uLingo algorithm.\nThe objectives of the tests are to demonstrate:\n- Test the performance of wake-up algorithm.\n- Test the performance of voice commands recognition\nalgorithm."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243378-p6-t0","doc_id":"K243378","page_num":6,"bbox":[78.14,248.78,544.42,695.87],"n_rows":10,"n_cols":3,"columns":["Parameter","Rapid RV/LV (K223396)\nPredicate Device","Rapid MLS – (K243378)"],"rows":[["Parameter","Rapid RV/LV (K223396)\nPredicate Device","Rapid MLS – (K243378)"],["Product Code","QIH","QIH"],["Regulation","21 CFR §892.2050","21 CFR §892.2050"],["Intended Use/\nIndications for\nUse","The Rapid RV/LV software device\nis designed to measure the maximal\ndiameters of the right and left\nventricles of the heart from a\nvolumetric CTPA acquisition and\nreport the ratio of those\nmeasurements. Rapid RV/LV\nanalyzes cases using machine\nlearning algorithms to identify\nlocations and measurements of the\nventricles. The Rapid RV/LV\ndevice provides the user with\nannotated images showing\nventricular measurements. Its\nresults are not intended to be used\non a stand-alone basis for clinical\ndecision-making or otherwise\npreclude clinical assessment of\nCTPA cases.","The Rapid MLS software device is\ndesigned to measure the midline\nshift of the brain from a NCCT\nacquisition and report the\nmeasurements. Rapid MLS analyzes\ncases using machine learning\nalgorithms to identify locations and\nmeasurements of the expected brain\nmidline and any shift which may\nhave occurred. The Rapid MLS\ndevice provides the user with\nannotated images showing\nmeasurements. Its results are not\nintended to be used on a stand-alone\nbasis for clinical decision-making or\notherwise preclude clinical\nassessment of NCCT cases."],["Input Data\nRequirements","Non-gated, CT Pulmonary\nAngiography images","Non-Contrast CT images"],["DICOM Compliance","Yes, using CTPA","Yes, using NCCT"],["Measurements","Heart RV, LV diameter","Brain midline measures"],["SW","AI ML","AI ML"],["Interface","Command Line","Command Line"],["Outputs","Reports, DICOM Secondary\nCapture Series","Reports, DICOM Secondary\nCapture Series"]],"caption_candidate":"the Rapid MLS software device that is the subject of this Traditional 510(k) submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p8-t0","doc_id":"K243397","page_num":8,"bbox":[88.7,222.98,520.9,708.46],"n_rows":22,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],["General","","",""],["Magnet system","","",""],["Field Strength","1.5 Tesla","1.5 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible bore\ndimensions","70cm","70cm","Same"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Magnet Homogeneity","1.40ppm @ 50cm DSV\n0.90ppm @ 45cm DSV\n0.45ppm @ 40cm DSV\n0.190ppm @ 30cm DSV\n0.120ppm @ 20cm DSV\n0.040ppm @ 10cm DSV","1.40ppm @ 50cm DSV\n0.90ppm @ 45cm DSV\n0.45ppm @ 40cm DSV\n0.190ppm @ 30cm DSV\n0.120ppm @ 20cm DSV\n0.040ppm @ 10cm DSV","Same"],["Gradient system","","",""],["Max gradient\namplitude","45mT/m","45mT/m","Same"],["Max slew rate","200T/m/s","200T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant frequencies","63.87 MHz","63.87 MHz","Same"],["Number of transmit\nchannels","1","1","Same"],["Number of receive\nchannels","Up to 96","Up to 96","Same"],["Amplifier peak power\nper channel","18 kW","18 kW","Same"],["RF Coils","","",""],["Head & Neck Coil -24","Yes","Yes","Same"],["Spine Coil - 32","Yes","Yes","Same"],["Body Array Coil - 12","Yes","Yes","Same"]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p9-t0","doc_id":"K243397","page_num":9,"bbox":[88.7,78.84,520.9,707.62],"n_rows":28,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],["Body Array Coil - 24","Yes","Yes","Same"],["Breast Coil - 10","Yes","Yes","Same"],["Knee Coil - 12","Yes","Yes","Same"],["Lower Extremity Coil\n- 24","Yes","Yes","Same"],["Shoulder Coil - 12","Yes","Yes","Same"],["Small Loop Coil","Yes","Yes","Same"],["Wrist Coil - 12","Yes","Yes","Same"],["Cardiac Coil - 24","Yes","Yes","Same"],["Foot & Ankle Coil -\n24","Yes","Yes","Same"],["Temporomandibular\nJoint Coil - 4","Yes","Yes","Same"],["Carotid Coil - 8","Yes","Yes","Same"],["Flex Coil Large - 8","Yes","Yes","Same"],["Flex Coil Small - 8","Yes","Yes","Same"],["Infant Coil-24","Yes","Yes","Same"],["SuperFlex Large - 12","Yes","Yes","Same"],["SuperFlex Small - 12","Yes","Yes","Same"],["SuperFlex Body - 24","Yes","Yes","Same"],["Breast Coil-24","Yes","Yes","Same"],["Breast Coil 12","Yes","No","Note 1"],["Head Coil 16","Yes","No","Note 2"],["Patient table","","",""],["Dimensions","Patient Table:\nwidth 640 mm, height\n880 mm, length 2620\nmm","Patient Table:\nwidth 640 mm, height\n880 mm, length 2620\nmm","Same"],["","Detachable Table:\nwidth 826 mm, height\n880 mm, length 2578\nmm","Detachable Table:\nwidth 810 mm, height\n880 mm, length 2505\nmm","Note 3"],["Maximum supported\npatient weight","Patient Table:\n250 kg","Patient Table:\n250 kg","Same"],["","Detachable Table:\n310 kg","Detachable Table:\n310 kg","Same"],["Accessories","","",""],["Vital Signal Gating","/","Wireless UIH Gating\nUnit REF\n453564324621\nECG module Ref\n989803163121\nSpO2 module Ref\n989803163111(alternati\nve)","Note 4"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p10-t0","doc_id":"K243397","page_num":10,"bbox":[88.7,78.84,520.9,323.69],"n_rows":14,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K240744)","Remark"],["","uVWMERP\nuMVRX\n(alternative)","uVWMERP\nuMVRX\n(alternative)","Same"],["","mmw100 (optional)","mmw100 (optional)","Same"],["Image Processing","","",""],["Inline ECV","Yes","No","Note 5"],["Inline MOCO","Yes","No","Note 6"],["MTP","Yes","No","Note 7"],["Workflow","","",""],["TI Scout","Yes","No","Note 8"],["Breast Biopsy","Yes","No","Note 9"],["Auto Bolus tracker","Yes","No","Note 10"],["EasyScan","Yes","Yes","Note 11"],["Image Reconstruction","","",""],["SparkCo","Yes","No","Note 12"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p10-t1","doc_id":"K243397","page_num":10,"bbox":[88.7,351.77,520.9,424.13],"n_rows":4,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Reference Device#1\nuWS-MR (K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Reference Device#1\nuWS-MR (K220332)","Remark"],["Image Processing","","",""],["Inline Cardiac function","Yes","Yes","Note 13"],["Inline MRS","Yes","Yes","Note 14"]],"caption_candidate":"Table 2 Comparison to Reference device#1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p10-t2","doc_id":"K243397","page_num":10,"bbox":[88.7,452.23,520.9,668.62],"n_rows":14,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Reference Device#2\nuPMR 790 (K234154)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Reference Device#2\nuPMR 790 (K234154)","Remark"],["Workflow","","",""],["EasyCrop","Yes","Yes","Note 15"],["ImageGuard","Yes","Yes","Same"],["Mocap (also named\nMoCap-Monitoring)","Yes","Yes","Same"],["EasyFACT (also\nnamed Inline FACT)","Yes","Yes","Same"],["Image Processing","","",""],["4D Flow","Yes","Yes","Same"],["SNAP","Yes","Yes","Same"],["CEST","Yes","Yes","Same"],["T1rho","Yes","Yes","Same"],["FSP+","Yes","Yes","Same"],["CASS","Yes","Yes","Same"],["PASS","Yes","Yes","Same"]],"caption_candidate":"Table 3 Comparison to Reference device#2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p11-t0","doc_id":"K243397","page_num":11,"bbox":[88.7,106.46,520.9,156.26],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Reference Device#3\nuMR Omega (K230152)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Reference Device#3\nuMR Omega (K230152)","Remark"],["ACS","Yes","Yes","Same"],["uVision","Yes","Yes","Note 16"]],"caption_candidate":"Table 4 Comparison to Reference device#3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p11-t1","doc_id":"K243397","page_num":11,"bbox":[88.7,170.54,520.9,701.86],"n_rows":12,"n_cols":2,"columns":["Note 1","The intended use of Breast Coil - 12 is essentially identical to previously cleared\nBreast Coil - 10. There are two differences between Breast Coil – 12 and Breast Coil –\n10. One is that Breast Coil - 12 can be used with Biopsy Configuration to provide\nbreast biopsy function. The other one is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 1","The intended use of Breast Coil - 12 is essentially identical to previously cleared\nBreast Coil - 10. There are two differences between Breast Coil – 12 and Breast Coil –\n10. One is that Breast Coil - 12 can be used with Biopsy Configuration to provide\nbreast biopsy function. The other one is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 2","The intended use of Head Coil - 16 is equivalent to Head Coil – 12 previously cleared\nvia K200024. The only difference between them is the number of channels of the\nreceiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","The dimensions of detachable table were changed from width 826mm, height 880mm,\nlength 2578mm to width 810mm, height 880mm, length 2505mm.\nThe difference did not raise new safety and effectiveness concerns."],["Note 4","One alterative wireless VSM was removed from the proposed device.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","Inline ECV aims to calculate the pixel-wise ECV (extracellular volume fraction) images\nfrom the native and post T1 mapping.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","Inline MOCO is a function that perform motion correction on MR images, which can\nreduce the motion caused by physiological factors such as breathing and heart beat in\nthe images.\nThe difference did not raise new safety and effectiveness concerns."],["Note 7","MTP is substantially equivalent to GRE and acquires two flip angles and multi-echo\nimages with one scan, and then uses specific image processing to attain multi-\nparametric images.\nThe difference did not raise new safety and effectiveness concerns."],["Note 8","TI Scout automatically selects the TI frame which has the darkest ventricular\nmyocardium of the TI Scout image, allowing users to achieve the best inversion time\n(TI) and simplifying the workflow which needed the TI.\nThe difference did not raise new safety and effectiveness concerns."],["Note 9","Breast Biopsy is a workflow that can provide biopsy instruction for technicians based\non the hardware and lesion parameters, the instruction include the biopsy grid\ncoordinate, needle block cell and needle depth.\nThe difference did not raise new safety and effectiveness concerns."],["Note 10","Auto Bolus tracker is a feature that automatically recognizes the time when the contrast\nagent reaches the target position and triggers the scan.\nThe difference did not raise new safety and effectiveness concerns."],["Note 11","EasyScan of the proposed device supports more body parts than that of the predicate\ndevice. In this submission, breast and pelvis and hip and ankle and thorax are\nincluded.\nThe difference did not raise new safety and effectiveness concerns."],["Note 12","SparkCo is an algorithm that can detect and correct spark artifacts (a specific occurring\nMRI artifact that is caused by electromagnetic interference (EMI)) in MRI images.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"uVision Yes Yes Note 16","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p12-t0","doc_id":"K243397","page_num":12,"bbox":[88.7,78.84,520.9,274.73],"n_rows":4,"n_cols":2,"columns":["Note 13","During this submission, inline ED/ES Phases Recognition was included in Inline\nCardiac function, which allows automatically rearrange the cardiac images into an\naligned cardiac cycle.\nThe difference did not raise new safety and effectiveness concerns."],"rows":[["Note 13","During this submission, inline ED/ES Phases Recognition was included in Inline\nCardiac function, which allows automatically rearrange the cardiac images into an\naligned cardiac cycle.\nThe difference did not raise new safety and effectiveness concerns."],["Note 14","Inline MRS of the proposed device are the same as the predicate device. The\ndifference is that the algorithms of Inline MRS are shifted from the post-processing\nworkstation to inline console.\nThe difference did not raise new safety and effectiveness concerns."],["Note 15","EasyCrop of the proposed device supports more body parts than that of the predicate\ndevice. In this submission, head and carotid and renal are included.\nThe difference did not raise new safety and effectiveness concerns."],["Note 16","uVision of the reference device just supports Hand Gesture Recognition. During this\nsubmission, Body Part Recognition function was included in uVision, which allows\nassist patient positioning by performing image recognition on human natural images\nthrough a 3D camera during the positioning stage.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p15-t0","doc_id":"K243397","page_num":15,"bbox":[90.63,201.55,519.06,446.47],"n_rows":18,"n_cols":2,"columns":["Subjects' Characteristics\n(N=35)","N(%)"],"rows":[["Subjects' Characteristics\n(N=35)","N(%)"],["Gender, N(%)",""],["Male","23(65.7%)"],["Female","12(34.3%)"],["Age, N(%): Min=18, Max=68, Avg.=34.2, Std.=10.83",""],["18-29","4(11.4%)"],["30-44","12(34.3%)"],["45-64","10(28.6%)"],[">=65","9(25.7%)"],["Ethnicity, N(%)",""],["White","9(25.7%)"],["Asian","21(60%)"],["Black","5(14.3%)"],["Body Mass Index (BMI), N(%): Min=16.0, Max=53.5, Avg.=23.3, Std.=9.57",""],["Underweight (<18.5)","6(17.1%)"],["Healthy weight (18.5-24.9)","14(40%)"],["Overweight (25.0-29.9)","10(28.6%)"],["Obesity (>=30.0)","5(14.3%)"]],"caption_candidate":"Table 5 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p15-t1","doc_id":"K243397","page_num":15,"bbox":[90.63,597.31,519.06,695.02],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["AI Module\nVerification Test","The performance of AI was\nevaluated by comparing\nthe input error and output\nerror with respect of\nNRMSE. If the NRMSE of\nthe AI output is less than\nthe NRMSE of input, the","The ratio of error:\nNRMSE(output)/\nNRMSE(input) is\nalways less than\n1.","Pass"]],"caption_candidate":"Table 6 The performance evaluation report criteria of ACS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p16-t0","doc_id":"K243397","page_num":16,"bbox":[90.26,78.84,519.46,576.91],"n_rows":6,"n_cols":4,"columns":["","performance of AI is\nconsidered to be validated.","",""],"rows":[["","performance of AI is\nconsidered to be validated.","",""],["Image SNR","Calculating SNR for both\nACS and CS images under\nthe same acceleration\nfactors and protocol\nparameters","ACS has higher\nSNR than CS.","Pass"],["Image\nResolution","Calculating the resolution\nvalue in elliptic ROI using\nthe (standard deviation\n(SD) / mean value(S)) for\nboth ACS and CS images\nunder the same\nacceleration factors and\nprotocol parameters","ACS has higher\n(standard\ndeviation (SD) /\nmean value(S))\nvalues than CS.","Pass"],["Image\nContrast","Comparing the ROI signal\nintensities between images\nacquired with fully\nsampled and ACS images\nunder the same\nacceleration factors with\ndifferent TI values","Bland-Altman\nanalysis of image\nintensities\nacquired using\nfully sampled and\nACS was shown\nwith less than 1%\nbias and all\nsample points\nfalls in the 95%\nconfidence\ninterval.","Pass"],["Image Uniformity","Images of the phantom\nwere acquired with fully\nsampled and ACS protocol\nrespectively. Method used\nhere for data analysis is\naccording to NEMA MS 6-\n2008(R2004)","ACS achieved\nsignificantly\nsame image\nuniformities as\nfully sampled\nimage","Pass"],["Structure\nMeasurement","Dimensions of selected\nsmall structures were\nidentified and measured on\nACS images as well as on\nfully sampled images.","Measurements\ndifferences on\nACS and fully\nsampled images\nof same structures\nunder 5% is\nacceptable.","Pass"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p17-t0","doc_id":"K243397","page_num":17,"bbox":[90.17,555.53,519.45,715.54],"n_rows":13,"n_cols":5,"columns":["","","","N(%)",""],"rows":[["","","","N(%)",""],["","Subjects' Characteristics","","",""],["","(N=15)","","",""],["","Gender, N(%)","","",""],["Male","","","9(60%)",""],["Female","","","6(40%)",""],["","Age, N(%): Min=18, Max=59, Avg.=30.8, Std.=9.88","","",""],["18-29","","","2(20%)",""],["30-44","","","8(53.3%)",""],["45-64","","","4(26.7%)",""],[">=65","","","0(0.0%)",""],["","Ethnicity, N(%)","","",""],["White","","","N.A.",""]],"caption_candidate":"Table 7 The demographic distribution of real-world spark testing dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p18-t0","doc_id":"K243397","page_num":18,"bbox":[90.23,91.1,519.45,162.38],"n_rows":5,"n_cols":4,"columns":["","Body Mass Index (BMI), N(%): Min=17.0, Max=53.5, Avg.=24.0, Std.=7.05","",""],"rows":[["","Body Mass Index (BMI), N(%): Min=17.0, Max=53.5, Avg.=24.0, Std.=7.05","",""],["Underweight (<18.5)","","2(13.3%)",""],["Healthy weight (18.5-24.9)","","10(66.7%)",""],["Overweight (25.0-29.9)","","3(20%)",""],["Obesity (>=30.0)","","0(0.0%)",""]],"caption_candidate":"Asian 15(100%)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p18-t1","doc_id":"K243397","page_num":18,"bbox":[90.23,321.65,519.45,447.43],"n_rows":10,"n_cols":2,"columns":["Body Parts","Number of cases"],"rows":[["Body Parts","Number of cases"],["Head","21"],["C-spine","5"],["Shoulder","1"],["Wrist","1"],["Thorax","2"],["Abdomen","8"],["L-spine","2"],["Pelvis","19"],["Total","59"]],"caption_candidate":"testing dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p18-t2","doc_id":"K243397","page_num":18,"bbox":[90.23,543.07,519.45,709.78],"n_rows":3,"n_cols":4,"columns":["Test parts","Test Methods","Accept criteria","Test Results"],"rows":[["Test parts","Test Methods","Accept criteria","Test Results"],["Test on the\nspark\ndetection\naccuracy","Based on the real-world\ntesting dataset, calculating\nthe detection accuracy by\ncomparing the spark\ndetection results with the\nground-truth.","The average detection\naccuracy need be larger\nthan 90%","The average detection\naccuracy is 94%."],["Test on the\nspark\ncorrection\nperformance","Based on the simulated spark\ntesting dataset, calculating\nthe PSNR (Peak signal-to-\nnoise ratio) of the spark-\ncorrected images and original\nspark images","The average PSNR of\nspark-corrected images\nneed to be higher than\nthe spark images.\nSpark artifacts need to\nbe reduced or corrected","The average PSNR of\nspark-corrected images\nis 1.6 higher than the\nspark images.\nThe images with spark\nartifacts were"]],"caption_candidate":"Table 9 The test methods and test results of SparkCo","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p19-t0","doc_id":"K243397","page_num":19,"bbox":[90.32,277.85,519.39,327.17],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["The error between the phase indices calculated\nby the algorithm for the ED and ES of test data\nand the gold standard phase indices.","The average error does not exceed 1 frame."]],"caption_candidate":"Table 10 Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p19-t1","doc_id":"K243397","page_num":19,"bbox":[90.32,414.98,519.39,645.87],"n_rows":7,"n_cols":3,"columns":["Gender","Number of people","Number of cases"],"rows":[["Gender","Number of people","Number of cases"],["Male 36\nFemale 10\nUnknown 10","","72\n13\n10"],["Age","",""],["[20,30) 15\n[30,40) 9\n[40,50) 14\n[50,60) 5\n>=60 3\nUnknown 10","","20\n23\n22\n17\n3\n10"],["Field strength","",""],["1.5T 10\n3.0T 36\nUnknown 10","","19\n66\n10"],["Disease conditions","",""]],"caption_candidate":"Table 11 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p20-t0","doc_id":"K243397","page_num":20,"bbox":[90.32,93.36,519.38,165.38],"n_rows":2,"n_cols":2,"columns":["Ethnicity",""],"rows":[["Ethnicity",""],["Asian 22\nWhite 16\nBlack 8\nUnknown 10","60\n16\n9\n10"]],"caption_candidate":"ARV 1 1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p20-t1","doc_id":"K243397","page_num":20,"bbox":[90.32,270.87,519.38,656.14],"n_rows":13,"n_cols":3,"columns":["","","Average of frame index"],"rows":[["","","Average of frame index"],["Gender","Case Number",""],["","","differences"],["","",""],["Male 72\nFemale 13\nUnknown 10","","0.12\n0.14\n0.14"],["Age","",""],["[20,30) 20\n[30,40) 23\n[40,50) 22\n[50,60) 17\n>=60 3\nUnknown 10","","0.13\n0.10\n0.16\n0.10\n0.16\n0.14"],["Field strength","",""],["1.5T 19\n3.0T 66\nUnknown 10","","0.13\n0.12\n0.14"],["Disease conditions","",""],["NOR 85\nMINF 2\nDCM 2\nHCM 5\nARV 1","","0.12\n0.15\n0.13\n0.15\n0.14"],["Ethnicity","",""],["Asian 60\nWhite 16\nBlack 9\nUnknown 10","","0.11\n0.19\n0.13\n0.14"]],"caption_candidate":"Table 12 Subgroup analysis of results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p21-t0","doc_id":"K243397","page_num":21,"bbox":[90.33,204.38,519.37,398.57],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Passing rate","To verify the effectiveness of the algorithm, the subjective evaluation\nmethod was used. The segmentation result of each case was obtained with\nthe algorithm, and the segmentation mask was evaluated with the following\ncriteria. The test pass criteria was: no failure cases, satisfaction rate\nS/(S+A+F) exceeding 95%.\nThe criteria is as follows:\nSatisfied (S): the segmentation myocardial boundary adheres to the\n\nmyocardial boundary and blood pool ROI is within the blood pool\nexcluding the papillary muscles.\nAcceptable (A): These are small missing or redundant areas in the\n\nmyocardial segmentation but not obviously and the blood pool ROI is\nwithin the blood pool excluding the papillary muscles.\nFail (F): The myocardial mask does not adhere to the myocardial\n\nboundary or the blood pool ROI is not within the blood pool, or the\nblood pool ROI contains papillary muscles."]],"caption_candidate":"Table 23 Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p21-t1","doc_id":"K243397","page_num":21,"bbox":[90.33,474.7,519.37,706.42],"n_rows":8,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male 20\nFemale 8",""],["Age",""],["<18 1\n18-28 4\n29-40 1\n> 41 22",""],["Protocol",""],["post_t1map_sax 28\nnative_t1map_sax 28",""],["BMI (kg/m(2))",""],["<18.5 0\n[18.5, 25) 7\n>=25 15\nUnknown 6",""]],"caption_candidate":"Table 14 Distribution of Patient dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p22-t0","doc_id":"K243397","page_num":22,"bbox":[90.34,79.23,519.35,224.3],"n_rows":6,"n_cols":2,"columns":["Magnetic field strength (T)",""],"rows":[["Magnetic field strength (T)",""],["1.5 13\n3 15",""],["Ethnicity",""],["Asian 17\nWhite 11",""],["Healthy",""],["Negative 19\nPostive 4\nUnknown 5",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p22-t1","doc_id":"K243397","page_num":22,"bbox":[90.34,298.11,519.35,671.14],"n_rows":17,"n_cols":5,"columns":["","","","Total Failure","Total satisfaction"],"rows":[["","","","Total Failure","Total satisfaction"],["Gender","Satisfied (S)","Acceptable (A)","",""],["","","","Rate","Rate"],["","","","",""],["Male\nFemale","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Age","","","",""],["18-28\n29-40\n> 41","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"],["Protocol","","","",""],["post_t1map_sax\nnative_t1map_sax","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["BMI (kg/m(2))","","","",""],["<18.5\n[18.5, 25)\n>=25\nUnknown","100%\n100%\n100%\n100%","0%\n0%\n0%\n0%","0%\n0%\n0%\n0%","100%\n100%\n100%\n100%"],["Magnetic field strength (T)","","","",""],["1.5\n3","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Ethnicity","","","",""],["Asian\nWhite","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Healthy","","","",""],["Negative\nPostive\nUnknown","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"]],"caption_candidate":"Table 15 Segmentation algorithm subgroup analysis","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p23-t0","doc_id":"K243397","page_num":23,"bbox":[90.26,206.42,519.46,243.74],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Dice","The average Dice coefficient of the left ventricular myocardium after\nmotion correction is greater than 0.87."]],"caption_candidate":"Table 16 Validation type and acceptance criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p23-t1","doc_id":"K243397","page_num":23,"bbox":[90.26,349.13,519.46,374.21],"n_rows":2,"n_cols":3,"columns":["Dataset","Patients Number","Cases Number"],"rows":[["Dataset","Patients Number","Cases Number"],["Testing Data","60","105"]],"caption_candidate":"Table 17 Sample size information of testing data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p23-t2","doc_id":"K243397","page_num":23,"bbox":[90.26,574.87,519.46,713.26],"n_rows":11,"n_cols":3,"columns":["Subgroup","Details of each subgroup","Number of cases"],"rows":[["Subgroup","Details of each subgroup","Number of cases"],["Age","<22","3"],["","[22, 40)","17"],["","[40, 60)","38"],["","[60, 90)","47"],["Gender","Female","26"],["","Male","79"],["Ethnicity","Asian","74"],["","White","31"],["BMI (kg/m(2))","< 18.5","1"],["","[18.5, 25)","23"]],"caption_candidate":"Table 18 Cardiac perfusion images subgroup information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p24-t0","doc_id":"K243397","page_num":24,"bbox":[90.26,78.84,519.46,166.82],"n_rows":7,"n_cols":3,"columns":["",">=25","37"],"rows":[["",">=25","37"],["","Unknown","44"],["Magnetic field\nstrength (T)","1.5","40"],["","3.0","65"],["Disease conditions","Positive","49"],["","Negative","16"],["","Unknown","40"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p24-t1","doc_id":"K243397","page_num":24,"bbox":[90.26,256.34,519.46,281.57],"n_rows":2,"n_cols":3,"columns":["Dataset","Patients Number","Cases Number"],"rows":[["Dataset","Patients Number","Cases Number"],["Testing Data","33","182"]],"caption_candidate":"Table 19 Sample size information of testing data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p24-t2","doc_id":"K243397","page_num":24,"bbox":[90.26,482.23,519.46,708.58],"n_rows":18,"n_cols":3,"columns":["Subgroup","Details of each subgroup","Samples Number"],"rows":[["Subgroup","Details of each subgroup","Samples Number"],["Age","<22","34"],["","[22, 40)","110"],["","[40, 60)","34"],["","[60, 90)","4"],["Gender","Female","58"],["","Male","124"],["Ethnicity","Asian","89"],["","White","64"],["","Black","26"],["","Hispanic","3"],["BMI (kg/m(2))","< 18.5","21"],["","[18.5, 25)","79"],["",">=25","76"],["","Unknown","6"],["Magnetic field\nstrength (T)","1.5","50"],["","3.0","132"],["Disease conditions","Positive","3"]],"caption_candidate":"Table 20 Cardiac dark blood images subgroup information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p25-t0","doc_id":"K243397","page_num":25,"bbox":[90.29,78.84,519.42,103.94],"n_rows":2,"n_cols":3,"columns":["","Negative","35"],"rows":[["","Negative","35"],["","Unknown","144"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p25-t1","doc_id":"K243397","page_num":25,"bbox":[90.29,255.02,519.42,544.15],"n_rows":23,"n_cols":6,"columns":["","Age","","","Average Dice after motion correction",""],"rows":[["","Age","","","Average Dice after motion correction",""],["<22","","","0.92","",""],["[22, 40)","","","0.93","",""],["[40, 60)","","","0.92","",""],["[60, 90)","","","0.92","",""],["","Gender","","","Average Dice after motion correction",""],["Female","","","0.92","",""],["Male","","","0.92","",""],["","Ethnicity","","","Average Dice after motion correction",""],["Asian","","","0.92","",""],["White","","","0.91","",""],["","BMI (kg/m(2))","","","Average Dice after motion correction",""],["< 18.5","","","0.95","",""],["[18.5, 25)","","","0.93","",""],[">=25","","","0.91","",""],["Unknown","","","0.93","",""],["","Magnetic field strength (T)","","","Average Dice after motion correction",""],["1.5","","","0.92","",""],["3.0","","","0.93","",""],["","Disease conditions","","","Average Dice after motion correction",""],["Positive","","","0.93","",""],["Negative","","","0.92","",""],["Unknown","","","0.91","",""]],"caption_candidate":"Table 21 Cardiac perfusion images subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243397-p26-t0","doc_id":"K243397","page_num":26,"bbox":[90.29,106.58,519.42,420.77],"n_rows":25,"n_cols":6,"columns":["","Age","","","Average Dice after motion correction",""],"rows":[["","Age","","","Average Dice after motion correction",""],["<22","","","0.96","",""],["[22, 40)","","","0.96","",""],["[40, 60)","","","0.96","",""],["[60, 90)","","","0.95","",""],["","Gender","","","Average Dice after motion correction",""],["Female","","","0.96","",""],["Male","","","0.96","",""],["","Ethnicity","","","Average Dice after motion correction",""],["Asian","","","0.96","",""],["White","","","0.95","",""],["Black","","","0.95","",""],["Hispanic","","","0.96","",""],["","BMI (kg/m(2))","","","Average Dice after motion correction",""],["< 18.5","","","0.96","",""],["[18.5, 25)","","","0.96","",""],[">=25","","","0.96","",""],["Unknown","","","0.98","",""],["","Magnetic field strength (T)","","","Average Dice after motion correction",""],["1.5","","","0.96","",""],["3.0","","","0.96","",""],["","Disease conditions","","","Average Dice after motion correction",""],["Positive","","","0.97","",""],["Negative","","","0.96","",""],["Unknown","","","0.96","",""]],"caption_candidate":"Table 22 Cardiac dark blood images subgroup performance test","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243446-p5-t0","doc_id":"K243446","page_num":5,"bbox":[72.24,153.48,539.76,618.84],"n_rows":6,"n_cols":2,"columns":["Date:","January 24, 2025"],"rows":[["Date:","January 24, 2025"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283, rue de la Minière\n78530 Buc, France"],["Primary Contact:","Ning WEN\nRegulatory Affairs Program Manager\nGE HealthCare, (GE Medical Systems SCS)\nTel: +33 6 2324 6023\nEmail: ning.wen@gehealthcare.com"],["Secondary Contact","Michelle Huettner\nRegulatory Affairs Director\nTel: +1 901 558 8035\nEmail: michelle.huettner@gehealthcare.com"],["Device Trade Name:\nCommon/Usual Name:\nRegulation Number:\nPrimary Product Code:\nSecondary Product Code:\nRegulatory Class:","3DXR\n3DXR, with CleaRecon DL option\n21CFR 892.1650, Image-intensified fluoroscopic x-ray system\nOWB\nQIH\nClass II"],["Predicate Device:\nDevice Name:\nManufacturer:\n510(k) number:\nRegulation Number:\nProduct Code:\nRegulatory Class:","3DXR\nGE Medical Systems SCS\nK181403\n21CFR 892.1650, Image-intensified fluoroscopic x-ray system\nOWB\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243446-p7-t0","doc_id":"K243446","page_num":7,"bbox":[72.25,258.59,539.75,717.72],"n_rows":18,"n_cols":7,"columns":["Specification","","Predicate Device:","","","Proposed Device:",""],"rows":[["Specification","","Predicate Device:","","","Proposed Device:",""],["","","3DXR [K181403]","","","3DXR",""],["Indications for Use","Identical","","","Identical","",""],["Patient Population","No limitations on the patient\npopulation","","","Same, except for CleaRecon DL\noption which is validated for adult\npopulation only","",""],["3D Reconstruction","Yes","","","Yes","",""],["CleaRecon DL","No, streak artifacts reduction by\nIodine Streaks Reduction only","","","Yes, streak artifacts removal\npowered by DL-based algorithm","",""],["3DStent","No, 3D reconstruction of moving\nobject with the compensation of\nthe respiratory motion","","","Yes, 3D reconstruction of coronary\nstent with the compensation of the\nrespiratory and cardiac motion","",""],["Imaging Purposes","No, read multiple acquisition\nsystem DICOM tags to identify\nthe clinical protocol","","","Yes, read acquisition system 3D\npreset in Imaging Purposes DICOM\ntag","",""],["Motion Freeze","Identical","","","Identical","",""],["Metal Artifact Reduction","Identical","","","Identical","",""],["Active Tracker Detection","Identical","","","Identical","",""],["Iodine Streaks Reduction","Identical","","","Identical","",""],["Scatter Reduction","Yes","","","Yes","",""],["Extended Range","Identical","","","Identical","",""],["CT Format","Identical","","","Identical","",""],["Image Filters","Yes","","","Yes","",""],["3D Volume Size selection","Identical","","","Identical","",""],["3D Sub Volume selection","Yes","","","Yes","",""]],"caption_candidate":"between the predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p6-t0","doc_id":"K243523","page_num":6,"bbox":[71.14,153.03,524.24,250.08],"n_rows":4,"n_cols":6,"columns":["","Product name","","","Trade name",""],"rows":[["","Product name","","","Trade name",""],["NAEOTOM Alpha","","","NAEOTOM Alpha.Peak\nNAEOTOM Alpha","",""],["NAEOTOM Alpha.Pro","","","NAEOTOM Alpha.Pro","",""],["NAEOTOM Alpha.Prime","","","NAEOTOM Alpha.Prime","",""]],"caption_candidate":"II. Device Name and Classification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p11-t0","doc_id":"K243523","page_num":11,"bbox":[71.13,248.34,524.24,429.48],"n_rows":5,"n_cols":6,"columns":["","Term","","","Definition",""],"rows":[["","Term","","","Definition",""],["New","","","The feature is newly supported for Siemens CT scanners and the subject device","",""],["Modified","","","This feature is a modified form of a feature cleared within the primary and/or\nsecondary predicate devices","",""],["Enabled","","","This feature is currently supported by other cleared Siemens CT systems or\ncleared Siemens stand-alone software applications. This feature will be\nsupported for the subject device with software version SOMARIS/10 syngo CT\nVB20 and is substantially equivalent compared to the cleared version of the\nprimary/secondary predicate device.","",""],["n.a.","","","The feature is not supported by the subject device or by the primary and/or\nsecondary predicate device.","",""]],"caption_candidate":"Table 1: Overview of term definition.","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K243523-p13-t0","doc_id":"K243523","page_num":13,"bbox":[70.88,92.52,529.59,588.78],"n_rows":17,"n_cols":12,"columns":["","Technological\nproperty","HW/\nSW\nchange","","Subject devices","","","","","Predicate devices","",""],"rows":[["","Technological\nproperty","HW/\nSW\nchange","","Subject devices","","","","","Predicate devices","",""],["","","","Dual Source","Dual Source","","","Single\nsource","Dual Source","Dual Source","Single\nsource",""],["","","","NAEOTOM\nAlpha\nsyngo CT\nVB20","","NAEOTOM\nAlpha.Pro\nsyngo CT\nVB20","NAEOTOM\nAlpha.Prime\nsyngo CT\nVB20","","","NAEOTOM","SOMATOM\nX.ceed\nsyngo CT\nVB10\n(K233650)",""],["","","","","","","","","","Alpha","",""],["","","","","","","","","","syngo CT","",""],["","","","","","","","","","VB10","",""],["","","","","","","","","","(K233657)","",""],["","- RT planning","","","","","","","","","",""],["8.","Oncology Exchange","SW","new","","new","new","","n.a.","","n.a.",""],["9.","DirectSetupNotes","SW","enabled3","","enabled3","enabled3","","n.a.","","cleared",""],["10.","FAST 3D Camera/\nFAST Integrated\nWorkflow","SW/\nHW","modified4","","modified4","modified4","","cleared","","cleared",""],["11.","Flex 4D Spiral","SW","modified4","","modified4","modified4","","cleared","","cleared",""],["12.","FAST Planning","SW","modified4","","modified4","modified4","","cleared","","cleared",""],["13.","CARE Moodlight","HW","enabled5","","enabled5","enabled5","","n.a.","","n.a.",""],["14.","Eco Power Mode","HW/\nSW","new","","new","new","","n.a.","","n.a.",""],["15.","Power Shaver","SW/\nHW","n.a.","","n.a.","new","","n.a.","","n.a.",""],["16.","myExam\nCompanion –\nmyExam\nCompass/\nmyExam Cockpit","SW","modified4","","modified4","modified4","","cleared","","cleared",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p15-t0","doc_id":"K243523","page_num":15,"bbox":[71.13,92.52,524.25,771.18],"n_rows":23,"n_cols":12,"columns":["Hardware\nproperty","","","","Subject device","","","","Primary predicate S\ndevice d","","econdary predicate",""],"rows":[["Hardware\nproperty","","","","Subject device","","","","Primary predicate S\ndevice d","","econdary predicate",""],["","","","","","","","","","","evice",""],["","","","","(Dual source NAEOTOM CT systems)","","","","","","",""],["","","","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","NAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha S\nSOMARIS/10 syngo S\nCT VB10 C\n(K233657) (","OMATOM X.ceed",""],["","","","","","","Alpha.Pro","","","","",""],["","","","","SOMARIS/10 syngo","","","","","","OMARIS/10 syngo",""],["","","","","CT VB20","","SOMARIS/10 syngo","","","","T VB10",""],["","","","","","","CT VB20","","","","",""],["","","","","","","","","","","K233650)",""],["","","","with myNeedle\nLaser:","","with myNeedle\nLaser:","","","with myNeedle\nLaser:","","",""],["System\nconfiguration","","","Dual Source","","Dual Source","","","Dual Source S","","ingle Source",""],["Environment\nof Use","","","Professional\nHealthcare Facility","","Professional\nHealthcare Facility","","","Professional P\nHealthcare Facility H","","rofessional\nealthcare Facility",""],["Generator\nmax. power\n(kW)","","","2x 120","","2x 120","","","2x 120 1","","05 or 120",""],["Detector\ntechnology","","","QuantaMax\ndirect conversion\nwith “Quantum\nTechnology”","","QuantaMax\ndirect conversion\nwith “Quantum\nTechnology”","","","QuantaMax S\ndirect conversion U\nwith “Quantum C\nTechnology”","","tellarInfinity\nFC (Ultra Fast\neramic)",""],["","Detector","","2x 57.6","","2x 38.4","","","2x 57.6 3","","8.4",""],["","volume","","","","","","","","","",""],["","coverage","","","","","","","","","",""],["","(mm)","","","","","","","","","",""],["","Detector","","2x 288","","2x 192","","","2x 288 6","","4",""],["","physical rows","","","","","","","","","",""],["Detector\nslice width\n(mm)","","","0.2","","0.2","","","0.2 0","",".6",""],["Detector\nDAS channel\nno.","","","2752 (A system)\n1984 (B system)","","2752 (A system)\n1984 (B system)","","","2752 (A system) 9\n1984 (B system)","","20",""],["Tube","","","VECTRON","","VECTRON","","","VECTRON V","","ECTRON",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K243523-p20-t0","doc_id":"K243523","page_num":20,"bbox":[71.15,92.52,524.21,270.51],"n_rows":10,"n_cols":10,"columns":["Hardware\nproperty","","Subject device","","","","Primary predicate S\ndevice d","","econdary predicate",""],"rows":[["Hardware\nproperty","","Subject device","","","","Primary predicate S\ndevice d","","econdary predicate",""],["","","","","","","","","evice",""],["","","(Dual source NAEOTOM CT systems)","","","","","","",""],["","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","NAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha S\nSOMARIS/10 syngo S\nCT VB10 C\n(K233657) (K","OMATOM X.ceed",""],["","","","","Alpha.Pro","","","","",""],["","","SOMARIS/10 syngo","","","","","","OMARIS/10 syngo",""],["","","CT VB20","","SOMARIS/10 syngo","","","","T VB10",""],["","","","","CT VB20","","","","",""],["","","","","","","","","233650)",""],["","respiratory gating\nsystems\n• Open Online\nInterface","","respiratory gating\nsystems\n• Open Online\nInterface","","","","","respiratory gating\nsystems",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p21-t0","doc_id":"K243523","page_num":21,"bbox":[71.12,92.52,524.25,739.5],"n_rows":16,"n_cols":9,"columns":["Hardware\nproperty","Subject device","","","","Primary predicate\ndevice","","Secondary predicate",""],"rows":[["Hardware\nproperty","Subject device","","","","Primary predicate\ndevice","","Secondary predicate",""],["","","","","","","","device",""],["","","NAEOTOM Alpha.Prime","","","NAEOTOM Alpha\nSOMARIS/10 syngo CT\nVB10\n(K233657)","","SOMATOM X.ceed",""],["","","SOMARIS/10 syngo CT","","","","","SOMARIS/10 syngo CT",""],["","","VB20","","","","","VB10",""],["","","","","","","","(K233650)",""],["System\nconfiguration","Single Source","","","Dual Source","","Single Source","",""],["Environment of\nUse","Professional Healthcare\nFacility","","","Professional Healthcare\nFacility","","Professional Healthcare\nFacility","",""],["Generator\nmax. power (kW)","105 or 120","","","2x 120","","105 or 120","",""],["Detector\ntechnology","QuantaMax\nDirect Conversion with\n“Quantum Technology”","","","QuantaMax\nDirect Conversion with\n“Quantum Technology”","","UFC\n(Ultra Fast Ceramic)","",""],["Detector\nvolume coverage\n(mm)","57.6","","","2x 57.6","","38.4","",""],["Detector\nphysical rows","288","","","2x 288","","64","",""],["Detector\nslice width (mm)","0.2","","","0.2","","0.6","",""],["Detector\nDAS channel no.","2752","","","2752 (A system)\n1984 (B system)","","920","",""],["Tube\ntechnology","VECTRON","","","VECTRON","","VECTRON","",""],["Tube\nkV steps","70, 90, 100, 120, 140","","","70, 90, 100, 120, 140,\n150\n(150 kV only available\non the smaller tube-\ndetector system (B\nsystem) and only in\ncombination with the","","70, 80, 90, 100, 110,\n120, 130, 140, 150","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K243523-p27-t0","doc_id":"K243523","page_num":27,"bbox":[71.17,92.52,524.2,769.05],"n_rows":12,"n_cols":11,"columns":["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],"rows":[["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],["","","","","","","","","","predicate device",""],["","","(Dual Source)","","","(Single Source)","","","","",""],["","NAEOTOM Alpha\nNAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","","NAEOTOM\nAlpha.Prime\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB10\n(K233657) (","SOMATOM X.ceed",""],["","","","","","Alpha.Prime","","","","",""],["","","NAEOTOM","","","","","","","",""],["","","Alpha.Pro","","","","","","","",""],["","","","","","","","","","SOMARIS/10 syngo",""],["","","SOMARIS/10 syngo","","","SOMARIS/10 syngo","","","","CT VB10",""],["","","CT VB20","","","CT VB20","","","","",""],["","","","","","","","","","K233650)",""],["Protocols","Support of:\n• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash\nSpiral\n• Dual Energy\nacquisition\n• Protocols\nsupporting CT\nIntervention,\nCardiac\nScanning,\nSpectral imaging\nfor child\nexamination,\nSpectral imaging\nwith high\nresolution\n• Protocols for\nQuantum\nImaging modes:\n- Quantum\n- Quantump\nlus\n- Quantum\nHD\n- Quantum\nHD Cardiac\n- Quantump\neak\n• Dynamic\nimaging (Flex 4D","","","Support of:\n• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash\nSpiral\n• Dual Energy\nacquisition\n• Protocols\nsupporting CT\nIntervention,\nCardiac\nScanning,\nSpectral imaging\nfor child\nexamination,\nSpectral imaging\nwith high\nresolution\n• Protocols for\nQuantum\nImaging modes:\n- Quantum\n- Quantump\nlus\n- Quantum\nHD\n- Quantum\nHD Cardiac\n• Dynamic\nimaging (Flex 4D","","","Support of:\n• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash\nSpiral\n• Dual Energy\nacquisition\n• Protocols\nsupporting CT\nIntervention,\nCardiac\nScanning,\nSpectral imaging\nfor child\nexamination,\nSpectral imaging\nwith high\nresolution\n• Protocols for\nQuantum\nImaging modes:\n- Quantum\n- Quantump\nlus\n- Quantum\nHD\n- Quantum\nHD Cardiac\n- Quantump\neak\n• Dynamic\nimaging (Flex 4D","","Support of:\n• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash\nSpiral\n• Dual Energy\nacquisition\n(TwinBeam DE\nand TwinSpiral\nDE)\n• Protocols\nsupporting CT\nIntervention,\nCardiac\nScanning",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p28-t0","doc_id":"K243523","page_num":28,"bbox":[71.16,92.52,524.22,748.62],"n_rows":13,"n_cols":11,"columns":["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],"rows":[["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],["","","","","","","","","","predicate device",""],["","","(Dual Source)","","","(Single Source)","","","","",""],["","NAEOTOM Alpha\nNAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","","NAEOTOM\nAlpha.Prime\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB10\n(K233657) (","SOMATOM X.ceed",""],["","","","","","Alpha.Prime","","","","",""],["","","NAEOTOM","","","","","","","",""],["","","Alpha.Pro","","","","","","","",""],["","","","","","","","","","SOMARIS/10 syngo",""],["","","SOMARIS/10 syngo","","","SOMARIS/10 syngo","","","","CT VB10",""],["","","CT VB20","","","CT VB20","","","","",""],["","","","","","","","","","K233650)",""],["","Spiral with\nseparation\nfactor driven\nscan range)\n• Protocols for\nRadiation\nTherapy\nPlanning\nsupport patient\nmarking\n• Protocols for\nDirectBreathhol\nd\n• Protocols for\nFAST 4D\n• Protocols that\nallow scanning\nwith support of\nan external\nrespiratory\ngating system\n(Anzai, Varian\nRGSC, Open\ninterface, Open\nOnline\nInterface)","","","Spiral with\nseparation\nfactor driven\nscan range)\n• Protocols for\nRadiation\nTherapy\nPlanning\nsupport patient\nmarking\n• Protocols for\nDirectBreathhol\nd\n• Protocols for\nFAST 4D\n• Protocols that\nallow scanning\nwith support of\nan external\nrespiratory\ngating system\n(Anzai, Varian\nRGSC, Open\ninterface, Open\nOnline\nInterface)","","","Spiral with cycle\ntime driven scan\nrange)","","• Dynamic\nimaging (Flex 4D\nSpiral Flex 4D\nSpiral with cycle\ntime driven scan\nrange)\n• Protocols for\nRadiation\nTherapy\nPlanning\nsupport patient\nmarking\n• Protocols for\nDirectBreathhol\nd\n• Protocols for\nFAST 4D\n• Protocols that\nallow scanning\nwith support of\nan external\nrespiratory\ngating system\n(ANZAI, Varian\nRGSC, Open\ninterface)",""],["Advanced\nReconstruction","Recon&GO:\n- Spectral Recon\n- Inline Results – DE\nSPP\n- Inline Results –\nAnatomical ranges\n(Parallel/Radial)\nincl. Virtual\nUnenhanced,\nMonoenergetic plus\n- Inline Results –\nSpine and Rib\nRanges","","","Recon&GO:\n- Spectral Recon\n- Inline Results – DE\nSPP\n- Inline Results –\nAnatomical ranges\n(Parallel/Radial)\nincl. Virtual\nUnenhanced,\nMonoenergetic plus\n- Inline Results –\nSpine and Rib\nRanges","","","Recon&GO:\n- Spectral Recon -\n- Inline Results – DE -\nSPP\n- Inline Results – -\nAnatomical ranges\n(Parallel/Radial) (\nincl. Virtual i\nUnenhanced,\nMonoenergetic plus\n- Inline Results – -\nSpine and Rib\nRanges","","Recon&GO:\nSpectral Recon\nInline Results – DE\nSPP\nInline Results –\nAnatomical ranges\nParallel/Radial)\nncl. Virtual\nUnenhanced,\nMonoenergetic plus\nInline Results –\nSpine and Rib\nRanges",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p29-t0","doc_id":"K243523","page_num":29,"bbox":[71.15,92.52,524.22,758.55],"n_rows":14,"n_cols":11,"columns":["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],"rows":[["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],["","","","","","","","","","predicate device",""],["","","(Dual Source)","","","(Single Source)","","","","",""],["","NAEOTOM Alpha\nNAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","","NAEOTOM\nAlpha.Prime\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB10\n(K233657)","SOMATOM X.ceed",""],["","","","","","Alpha.Prime","","","","",""],["","","NAEOTOM","","","","","","","",""],["","","Alpha.Pro","","","","","","","",""],["","","","","","","","","","SOMARIS/10 syngo",""],["","","SOMARIS/10 syngo","","","SOMARIS/10 syngo","","","","CT VB10",""],["","","CT VB20","","","CT VB20","","","","",""],["","","","","","","","","","(K233650)",""],["","- Inline Results –\ntable and bone\nremoval","","","- Inline Results –\ntable and bone\nremoval","","","- Inline Results –\ntable and bone\nremoval","","- Inline Results –\ntable and bone\nremoval",""],["Image viewing","CT View&GO:\n- basic post-\nprocessing viewer\n(CT View&GO)\n- 2D and 3D (MPR,\nVRT, MIP and\nminIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive\nSpectral Imaging\n(ISI)\n- Basic visualization\ntools: Endo View\n- Basic\nmanipulation tools:\nDE ROI, ROI HU\nThreshold, Average\n- Automated table\nand bone removal","","","CT View&GO:\n- basic post-\nprocessing viewer\n(CT View&GO)\n- 2D and 3D (MPR,\nVRT, MIP and\nminIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive\nSpectral Imaging\n(ISI)\n- Basic visualization\ntools: Endo View\n- Basic\nmanipulation tools:\nDE ROI, ROI HU\nThreshold, Average\n- Automated table\nand bone removal","","","CT View&GO:\n- basic post-\nprocessing viewer\n(CT View&GO)\n- 2D and 3D (MPR,\nVRT, MIP and\nminIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive\nSpectral Imaging\n(ISI)\n- Basic visualization\ntools: Endo View\n- Basic\nmanipulation tools:\nDE ROI, ROI HU\nThreshold, Average\n- Automated table\nand bone removal","","CT View&GO:\n- basic post-\nprocessing viewer\n(CT View&GO)\n- 2D and 3D (MPR,\nVRT, MIP and\nminIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive\nSpectral Imaging\n(ISI)\n- Basic visualization\ntools: Endo View\n- Basic\nmanipulation tools:\nDE ROI, ROI HU\nThreshold, Average\n- Automated table\nand bone removal",""],["Post-Processing\ninterface","• Recon&GO\nInline Results:\nSoftware interface\nto post-processing\nalgorithms which\nare unmodified\nwhen loaded onto\nthe CT scanners and\n510(k) cleared as\nmedical devices,\nInline Results – RT-\nPlanning introduced","","","• Recon&GO\nInline Results:\nSoftware interface\nto post-processing\nalgorithms which\nare unmodified\nwhen loaded onto\nthe CT scanners and\n510(k) cleared as\nmedical devices,\nInline Results – RT-\nPlanning introduced","","","• Recon&GO\nInline Results:\nSoftware interface\nto post-processing\nalgorithms which\nare unmodified\nwhen loaded onto\nthe CT scanners and\n510(k) cleared as\nmedical devices\ni\ni","","• Recon&GO\nInline Results:\nSoftware interface\nto post-processing\nalgorithms which\nare unmodified\nwhen loaded onto\nthe CT scanners and\n510(k) cleared as\nmedical devices,\nncluding the\nnterface Inline\nResults – RT-\nPlanning",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p30-t0","doc_id":"K243523","page_num":30,"bbox":[71.17,92.52,524.2,771.1],"n_rows":12,"n_cols":11,"columns":["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],"rows":[["Software\nproperty","","Subject device","","","Subject device","","Primary predicate\ndevice","","Secondary",""],["","","","","","","","","","predicate device",""],["","","(Dual Source)","","","(Single Source)","","","","",""],["","NAEOTOM Alpha\nNAEOTOM\nAlpha.Pro\nSOMARIS/10 syngo\nCT VB20","NAEOTOM Alpha","","NAEOTOM\nAlpha.Prime\nSOMARIS/10 syngo\nCT VB20","NAEOTOM","","","NAEOTOM Alpha\nSOMARIS/10 syngo\nCT VB10\n(K233657) (","SOMATOM X.ceed",""],["","","","","","Alpha.Prime","","","","",""],["","","NAEOTOM","","","","","","","",""],["","","Alpha.Pro","","","","","","","",""],["","","","","","","","","","SOMARIS/10 syngo",""],["","","SOMARIS/10 syngo","","","SOMARIS/10 syngo","","","","CT VB10",""],["","","CT VB20","","","CT VB20","","","","",""],["","","","","","","","","","K233650)",""],["","• CT View&GO\nplug-in\ninterface:\ndesigned for\nstandalone plug-ins\nwhich are\nrepresented by the\ncleared medical\ndevice by its own\ncalled syngo.CT\nExtended\nFunctionality,\nplug-in CT\nView&GO –\nSim&GO introduced\n• CT View&GO\nsoftware\ninterface for\nAdvanced\nVisualization\nApps:\nSoftware interfaces\nfor post-processing\nfunctionalities to\nprovide advanced\nvisualization tools\nto prepare and\nprocess medical\nimages for\ndiagnostic purpose.\nNote: The clearance\nof standalone\nAdvanced\nVisualization\nApplication\nsoftware is\nmandatory\nprecondition.","","","• CT View&GO\nplug-in\ninterface:\ndesigned for\nstandalone plug-ins\nwhich are\nrepresented by the\ncleared medical\ndevice by its own\ncalled syngo.CT\nExtended\nFunctionality,\nplug-in CT\nView&GO –\nSim&GO introduced\n• CT View&GO\nsoftware\ninterface for\nAdvanced\nVisualization\nApps:\nSoftware interfaces\nfor post-processing\nfunctionalities to\nprovide advanced\nvisualization tools\nto prepare and\nprocess medical\nimages for\ndiagnostic purpose.\nNote: The clearance\nof standalone\nAdvanced\nVisualization\nApplication\nsoftware is\nmandatory\nprecondition.","","","• CT View&GO\nplug-in\ninterface:\ndesigned for\nstandalone plug-ins\nwhich are\nrepresented by the r\ncleared medical\ndevice by its own\ncalled syngo.CT\nExtended\nFunctionality\ni\ni\n• CT View&GO\nsoftware\ninterface for\nAdvanced\nVisualization\nApps:\nSoftware interfaces\nfor post-processing f\nfunctionalities to f\nprovide advanced\nvisualization tools\nto prepare and t\nprocess medical\nimages for i\ndiagnostic purpose.\nNote: The clearance\nof standalone\nAdvanced\nVisualization\nApplication\nsoftware is\nmandatory\nprecondition.\nThese advanced\nvisualization tools","","• CT View&GO\nplug-in\ninterface:\ndesigned for\nstandalone plug-ins\nwhich are\nepresented by the\ncleared medical\ndevice by its own\ncalled syngo.CT\nExtended\nFunctionality,\nncluding the plug-\nn CT View&GO –\nSim&GO\n• CT View&GO\nsoftware\ninterface for\nAdvanced\nVisualization\nApps:\nSoftware interfaces\nor post-processing\nunctionalities to\nprovide advanced\nvisualization tools\no prepare and\nprocess medical\nmages for\ndiagnostic purpose.\nNote: The clearance\nof standalone\nAdvanced\nVisualization\nApplication\nsoftware is\nmandatory\nprecondition.\nThese advanced\nvisualization tools",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p34-t0","doc_id":"K243523","page_num":34,"bbox":[71.14,375.27,524.24,760.44],"n_rows":5,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed for new and modified features"],"rows":[["","Feature/Non-clinical","","Bench Testing performed for new and modified features"],["","supportive testing","",""],["Direct i4D","","","The target of the bench test is to perform a respiratory sequence scan\nusing a dynamic phantom where at every planned position of the scan\nrange at least one complete breathing cycle is acquired.\nObjective of the test is to compare a conventional respiratory 4DCT scan\n(spiral scan) with the breathing pattern of a thorax phantom and the\nresult of Direct i4D with the same breathing pattern.\nThe test results show that with Direct i4D it is possible to acquire data for\na full breathing cycle at every position of the patient even if the\nrespiratory rate changes during the data acquisition. Compared to the\nconventional 4DCT scan mode interpolation artifacts (which occur\nbecause not for every position a complete breathing cycle could be\nacquired) can successfully be avoided with Direct i4D."],["DirectBreathhold","","","The test results show that using the Direct Breathhold functionality, a\nspiral scan can automatically be triggered from an external respiratory\ngating device. The actual scan remains unchanged, and the object is\ncorrectly depicted in the resulting image."],["Recon&GO – RT\nplanning","","","The bench test underpins the possibility that with the introduction of the\nRTP scan protocols in the subject devices NAEOTOM CT scanner systems\nwith syngo CT VB20, time and imaging dose can be saved, since each RTP\nscan range allows for spectral post-processing to provide task-specific\nimages for an end-to-end radiotherapy workflow and thus no additional\nscan range with Single Energy is needed."]],"caption_candidate":"Table 6: Non-clinical performance testing (bench testing).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p35-t0","doc_id":"K243523","page_num":35,"bbox":[71.13,92.52,524.25,753.96],"n_rows":7,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed for new and modified features"],"rows":[["","Feature/Non-clinical","","Bench Testing performed for new and modified features"],["","supportive testing","",""],["FAST 3D Camera/\nFAST Integrated\nWorkflow","","","The FAST 3D camera sub-features FAST Isocentering, FAST Range, and\nFAST Direction have been optimized using additional data from adults\nand adolescence patients. The bench test evaluates and compares the\naccuracy of the three sub-features in software version syngo CT VB20 to\nthe accuracy of the predicate devices with syngo CT VB10.\nThe objectives of the bench tests are to demonstrate that the FAST 3D\ncamera achieves comparable or better results for both, adults and\nadolescents, as the predicate device for adults.\nOverall, the subject devices with syngo CT VB20 delivers comparable or\nimproved accuracy to the predicate devices with syngo CT VB10\npredicate device for adults and extends the support to adolescents."],["Flex 4D Spiral","","","The performed bench test report describes the technical background of\nFlex 4D Spiral and its functionalities with NAEOTOM CT scanners,\ndemonstrate the proper function of those, and assess the image quality\nof Flex 4D Spiral."],["FAST Planning","","","The purpose of the test is to provide a clear reporting on the applied\nalgorithm, its product development, validation, and verification on\npatient data, which enable the claims.\nObjective of the test is to assess the fraction (percentage) of ranges\ncalculated by the FAST Planning algorithm that are correct and can be\napplied without change. Additionally, calculation time was measured to\ncheck whether it meets interactive requirements.\nThe test results show that the editing actions for the scanner technician\ncan be reduced to a minimum and that the calculation time is fast\nenough for interactive speed during scanning. For more than 90% of the\nranges no editing action was necessary to cover standard ranges. For\nmore than 95%, the speed of the algorithm was sufficient."],["Low-Dose Lung Cancer\nScreening –\nNAEOTOM Alpha.Pro","","","The bench test provides a comparison of technical parameters specific to\nLow-Dose Lung Cancer Screening of the predicate and subject devices,\nfollowing the established concept of our previous 510(k) submissions.\nIt can be concluded that the subject and predicate devices are\nsubstantially equivalent for the task of Low-Dose Lung Cancer Screening\nsince the bench test results showed comparable technical parameters."],["Low-Dose Lung Cancer\nScreening –\nNAEOTOM\nAlpha.Prime","","","The bench test provides a comparison of technical parameters specific to\nLow-Dose Lung Cancer Screening of the predicate and subject devices,\nfollowing the established concept of our previous 510(k) submissions.\nIt can be concluded that the subject and predicate devices are\nsubstantially equivalent for the task of Low-Dose Lung Cancer Screening\nsince the bench test results showed comparable technical parameters."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p36-t0","doc_id":"K243523","page_num":36,"bbox":[71.13,161.79,524.25,772.14],"n_rows":9,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/19/2022","12-349","NEMA","","","PS 3.1 - 3.20 2022d","","","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set"],["07/06/2020","12-325","NEMA","","","XR 25-2019","","","Computed\nTomography Dose\nCheck"],["07/06/2020","12-330","NEMA","","","XR 28-2018","","","Supplemental\nRequirements for User\nInformation and\nSystem Function\nRelated to Dose in CT"],["12/23/2019","12-328","IEC","","","61223-3-5 Edition 2.0\n2019-09","","","Evaluation and routine\ntesting in medical\nimaging departments -\nPart 3-5: Acceptance\ntests and constancy\ntests - Imaging\nperformance of\ncomputed tomography\nX-ray equipment\n[Including: Technical\nCorrigendum 1 (2006)]"],["03/14/2011","12-226","IEC","","","61223-2-6 Second\nEdition 2006-11","","","Evaluation and routine\ntesting in medical\nimaging departments -\nPart 2-6: Constancy\ntests - Imaging\nperformance of\ncomputed tomography\nX-ray equipment"],["01/14/2014","12-269","IEC","","","60601-1-3 Edition 2.1\n2013-04","","","Medical electrical\nequipment - Part 1-3:\nGeneral requirements\nfor basic safety and\nessential performance\n– Collateral Standard:\nRadiation protection in\ndiagnostic X-ray\nequipment"]],"caption_candidate":"Table 7: Recognized Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p37-t0","doc_id":"K243523","page_num":37,"bbox":[71.12,92.52,524.25,762.06],"n_rows":10,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["06/27/2016","12-302","IEC","","","60601-2-44 Edition\n3.2: 2016","","","Medical electrical\nequipment - Part 2-44:\nParticular\nrequirements for the\nbasic safety and\nessential performance\nof x-ray equipment for\ncomputed tomography"],["12/23/2019","5-125","ANSI AAMI\nISO","","","14971: 2019","","","Medical devices -\nApplications of risk\nmanagement to\nmedical devices"],["","","ISO","","","14971 Third Edition\n2019-12","","","Medical devices -\nApplication of risk\nmanagement to\nmedical devices"],["01/14/2019","13-79","ANSI AAMI\nIEC","","","62304:2006/A1:2016","","","Medical device\nsoftware - Software\nlife cycle processes\n[Including Amendment\n1 (2016)]"],["","","IEC","","","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","","","Medical device\nsoftware - Software\nlife cycle processes"],["07/09/2014","19-46","ANSI AAMI","","","ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012\n(Cons. Text) [Incl.\nAMD2:2021]","","","Medical electrical\nequipment - Part 1:\nGeneral requirements\nfor basic safety and\nessential performance\n(IEC 60601-1:2005,\nMOD) [Including\nAmendment 2 (2021)]"],["09/17/2018","19-36","ANSI AAMI\nIEC","","","60601-1-2:2014\n[Including AMD\n1:2021]","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral Standard:\nElectromagnetic\ndisturbances -\nRequirements and\ntests"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p38-t0","doc_id":"K243523","page_num":38,"bbox":[71.12,92.52,524.25,759.06],"n_rows":10,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["","","IEC","","","60601-1-2 Edition 4.1\n2020-09\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral Standard:\nElectromagnetic\ndisturbances -\nRequirements and\ntests"],["12/23/2016","5-129","ANSI AAMI\nIEC","","","62366-\n1:2015+AMD1:2020\n(Consolidated Text)","","","Medical devices Part 1:\nApplication of usability\nengineering to medical\ndevices, including\nAmendment 1"],["","","IEC","","","62366-1 Edition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","Medical devices - Part\n1: Application of\nusability engineering\nto medical devices"],["07/09/2014","12-273","IEC","","","60825-1 Edition 2.0\n2007-03","","","Safety of laser\nproducts - Part 1:\nEquipment\nclassification, and\nrequirements"],["12/21/2020","5-132","IEC","","","60601-1-6 Edition 3.2\n2020-07\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-6:\nGeneral requirements\nfor basic safety and\nessential performance\n- Collateral standard:\nUsability"],["12/23/2019","12-309","IEC","","","60601-2-28 Edition\n3.0 2017-06","","","Medical electrical\nequipment - Part 2-28:\nParticular\nrequirements for the\nbasic safety and\nessential performance\nof X-ray tube\nassemblies for medical\ndiagnosis"],["12/20/2021","12-341","IEC","","","62563-1 Edition 1.2\n2021-07","","","Medical electrical\nequipment - Medical\nimage display systems"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p39-t0","doc_id":"K243523","page_num":39,"bbox":[71.13,212.58,524.24,481.14],"n_rows":6,"n_cols":6,"columns":["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],"rows":[["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard Used"],["","Developing","","","",""],["","Organization","","","",""],["IEC","","","60601-\n1:2005+A1:2012+A2:2020","Medical electrical\nequipment - part 1:\ngeneral requirements\nfor basic safety and\nessential performance","ANSI AAMI ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons.\nText) [Incl. AMD2:2021]"],["IEC/ISO","","","17050-1","Conformity Assessment\n– Supplier’s declaration\nof conformity – Part 1:\nGeneral requirements","Declaration of\nconformance to FDA\nrecognized consensus\nstandards."],["IEC/ISO","","","17050-2","Conformity assessment\n– Supplier’s declaration\nof conformity – Part 2:\nSupporting\ndocumentation.","General consensus\nstandards not currently\nrecognized by FDA."]],"caption_candidate":"Table 8: General Use Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p39-t1","doc_id":"K243523","page_num":39,"bbox":[71.13,524.19,524.24,743.76],"n_rows":10,"n_cols":4,"columns":["","FDA Guidance Document I","ssue date",""],"rows":[["","FDA Guidance Document I","ssue date",""],["User Fees and Refunds for Premarket Notification Submissions (510(k)s","","10/05/2022",""],["Refuse to Accept Policy for 510(k)s","","04/21/2022",""],["Electronic Submission Template for Medical Device 510(k) Submissions","","10/2/2023",""],["Deciding When to Submit a 510(k) for a Change to an Existing Device","","10/25/2017",""],["The 510(k) Program: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]","","07/28/2014",""],["Content of Premarket Submissions for Device Software Functions","","06/14/2023",""],["Off-The-Shelf Software Use in Medical Devices","","09/27/2019",""],["Applying Human Factors and Usability Engineering to Medical Devices","","02/03/2016",""],["Pediatric Information for X-ray Imaging Device Premarket Notifications","","11/28/2017",""]],"caption_candidate":"Table 9: FDA Guidance Document and Effective Date","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243523-p40-t0","doc_id":"K243523","page_num":40,"bbox":[71.13,92.52,524.24,238.32],"n_rows":5,"n_cols":4,"columns":["","FDA Guidance Document I","ssue date",""],"rows":[["","FDA Guidance Document I","ssue date",""],["Cybersecurity in Medical Devices: Quality System Considerations and Content 0\nof Premarket Submissions","","9/27/2023",""],["Electromagnetic Compatibility (EMC) of Medical Devices 0","","6/06/2022",""],["Design Considerations and Pre-market Submission Recommendations for 0\nInteroperable Medical Devices","","9/06/2017",""],["Appropriate Use of Voluntary Consensus Standards in Premarket Submissions 0\nfor Medical Devices","","9/14/2018",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p7-t0","doc_id":"K243547","page_num":7,"bbox":[103.1,152.3,542.4,370.61],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega (K243122)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega (K243122)","Remark"],["indication\ns for use","The uMR Ultra system is indicated\nfor use as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse,\ncoronal, and oblique cross sectional\nimages, and spectroscopic images,\nand that display internal anatomical\nstructure and/or function of the\nhead, body and extremities.\nThese images and the physical\nparameters derived from the images\nwhen interpreted by a trained\nphysician yield information that\nmay assist the diagnosis. Contrast\nagents may be used depending on\nthe region of interest of the scan.","The uMR Omega system is indicated\nfor use as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse, coronal,\nand oblique cross sectional images,\nand spectroscopic images, and that\ndisplay internal anatomical structure\nand/or function of the head, body and\nextremities.\nThese images and the physical\nparameters derived from the images\nwhen interpreted by a trained\nphysician yield information that may\nassist the diagnosis. Contrast agents\nmay be used depending on the region\nof interest of the scan.","Same"]],"caption_candidate":"Table 1 Comparison of Indication for Use to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p7-t1","doc_id":"K243547","page_num":7,"bbox":[103.1,397.01,542.4,696.94],"n_rows":8,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark"],"rows":[["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark"],["General","","",""],["Magnet system","","",""],["Field Strength","3.0 Tesla","3.0 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible bore\ndimensions","70 cm","75 cm","Note 1"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Magnet Homogeneity","≤ 2.30 ppm @ 50cm DSV\n≤ 0.80 ppm @ 45cm DSV\n≤ 0.38 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.02 ppm @ 20cm DSV\n≤ 0.002 ppm @ 10cm DSV","≤ 2.30 ppm @ 50cm DSV\n≤ 0.80 ppm @ 45cm DSV\n≤ 0.38 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.02 ppm @ 20cm DSV\n≤ 0.002 ppm @ 10cm DSV","Same"]],"caption_candidate":"Table 2 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p8-t0","doc_id":"K243547","page_num":8,"bbox":[103.1,78.84,542.4,713.74],"n_rows":26,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark"],"rows":[["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark"],["Gradient system","","",""],["Max gradient amplitude","100 mT/m","45 mT/m","Note 2"],["Max slew rate","200 T/m/s","200 T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant frequencies","128.23 MHz","128.23 MHz","Same"],["Number of transmit\nchannels","2","2","Same"],["Amplifier peak power\nper channel","Option 1: 20 kW","Option 1: 18 kW\nOption 2: 20 kW","Note 3"],["Maximum number of\nreceive channels","192","96","Note 4"],["RF Coils","","",""],["Volume Transmit Coil","Yes","Yes","Same"],["Breast Coil - 12","Yes","Yes","Same"],["Breast Coil - 24","Yes","Yes","Same"],["SuperFlex Large - 12","Yes","Yes","Same"],["UHD SuperFlex Large -\n24","Yes","No","Note 5"],["SuperFlex Small - 12","Yes","Yes","Same"],["UHD SuperFlex Small -\n24","Yes","No","Note 6"],["SuperFlex Body - 24","Yes","Yes","Same"],["SuperFlex Whole Body\n- 48","Yes","No","Note 7"],["Head Coil - 16","Yes","Yes","Same"],["Head & Neck Coil - 24","Yes","Yes","Same"],["Head & Neck Coil - 48","Yes","Yes","Same"],["UHD SuperFlex Free -\n24","Yes","No","Note 8"],["Infant Coil - 24","Yes","Yes","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p9-t0","doc_id":"K243547","page_num":9,"bbox":[108.5,40.2,535.88,697.06],"n_rows":57,"n_cols":5,"columns":["","Shanghai United Imaging Health","care Co., Ltd.","",""],"rows":[["","Shanghai United Imaging Health","care Co., Ltd.","",""],["","Tel: +86 (21) 67076888 Fax","：+86 (21) 67076889","",""],["","www.united-imaging.com","","",""],["","","","",""],["","","Proposed Device","Predicate Device",""],["","ITEM","","","Remark"],["","","uMR Ultra","uMR Omega",""],["","","","",""],["S","mall Loop Coil","Yes","Yes","Same"],["","","","",""],["","Wrist Coil - 12","Yes","Yes","Same"],["","","","",""],["","Wrist Coil - 24","Yes","No","Note 9"],["","","","",""],["T","x/Rx Head Coil","Yes","Yes","Same"],["","","","",""],["S","houlder Coil - 12","Yes","Yes","Same"],["","","","",""],["S","houlder Coil - 24","Yes","No","Note 10"],["","","","",""],["S","pine Coil - 48","Yes","Yes","Same"],["","","","",""],["T","x/Rx Knee Coil - 24","Yes","Yes","Same"],["","","","",""],["F","oot & Ankle Coil - 24","Yes","Yes","Same"],["","","","",""],["C","arotid Coil - 8","Yes","Yes","Same"],["","","","",""],["T","emporomandibular","","",""],["","","Yes","Yes","Same"],["J","oint Coil - 4","","",""],["","","","",""],["P","atient table","","",""],["","","","",""],["","Maximum supported","","",""],["","","310 kg","310 kg","Same"],["p","atient weight","","",""],["","","","",""],["A","ccessories","","",""],["","","","",""],["","","ECG, Respiration and pulse","ECG, Respiration and pulse",""],["V","ital Signal Gating","","","Same"],["","","module","module",""],["","","","",""],["T","ilt Support","Yes","No","Note 11"],["","","","",""],["P","ositioning Couch-top","Yes","No","Note 12"],["","","","",""],["C","oil Support","Yes","No","Note 13"],["","","","",""],["P","atient Bore Projector","Yes","No","Note 14"],["","","","",""],["u","Vision","","",""],["","","","",""],["B","ody Part","","",""],["","","Yes","No","Note 15"],["R","ecognization","","",""]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243547-p10-t0","doc_id":"K243547","page_num":10,"bbox":[103.1,78.84,542.35,711.53],"n_rows":29,"n_cols":6,"columns":["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark","",""],"rows":[["ITEM","Proposed Device\nuMR Ultra","Predicate Device\nuMR Omega","Remark","",""],["Hand Gesture\nRecognization","Yes","Yes","Same","",""],["Safety","","","","",""],["Electrical Safety","Comply with ES 60601-1","Comply with ES 60601-1","Same","",""],["EMC","Comply with IEC 60601-1-2","Comply with IEC 60601-1-2","Same","",""],["Max SAR for Transmit\nCoil","Comply with IEC 60601-2-\n33","Comply with IEC 60601-2-33","Same","",""],["Max dB/dt","Comply with IEC 60601-2-\n33","Comply with IEC 60601-2-33","Same","",""],["Biocompatibility","Comply with ISO 10993-5\nand ISO 10993-10","Comply with ISO 10993-5 and\nISO 10993-10","Same","",""],["Surface Heating","NEMA MS 14","NEMA MS 14","Same","",""],["Imaging Features","","","","",""],["4D CEMRA","Yes","Yes","","Same",""],["4D NCEMRA","Yes","Yes","","Same",""],["ARMS","Yes","Yes","","Same",""],["ARMS DWI","Yes","Yes","","Same",""],["3D ASL","Yes","Yes","","Same",""],["Multi-PLD ASL","Yes","Yes","","Same",""],["bFAST","Yes","Yes","","Same",""],["BOLD","Yes","Yes","","Same",""],["Brain Perfusion","Yes","Yes","","Same",""],["cDWI","Yes","Yes","","Same",""],["CEST","Yes","Yes","Same","",""],["DB SWI","Yes","Yes","Same","",""],["DCE","Yes","Yes","Same","",""],["DTI","Yes","Yes","","Same",""],["Multiband","Yes","Yes","","Same",""],["FACT","Yes","Yes","","Same",""],["4D Flow","Yes","Yes","","Same",""],["2D Flow","Yes","Yes","","Same",""],["FSE DWI","Yes","Yes","","Same",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p11-t0","doc_id":"K243547","page_num":11,"bbox":[108.5,40.2,535.88,702.7],"n_rows":71,"n_cols":5,"columns":["","Shanghai United Imaging Health","care Co., Ltd.","",""],"rows":[["","Shanghai United Imaging Health","care Co., Ltd.","",""],["","Tel: +86 (21) 67076888 Fax","：+86 (21) 67076889","",""],["","www.united-imaging.com","","",""],["","","","",""],["","","Proposed Device","Predicate Device",""],["","ITEM","","","Remark"],["","","uMR Ultra","uMR Omega",""],["","","","",""],["F","SP+","Yes","Yes","Same"],["","","","",""],["","MARS+","Yes","Yes","Same"],["","","","",""],["","MATRIX","Yes","Yes","Same"],["","","","",""],["","MicroView","Yes","Yes","Same"],["","","","",""],["","MQD","Yes","No","Note 16"],["","","","",""],["3","D MRCP","Yes","Yes","Same"],["","","","",""],["","MRE","Yes","Yes","Same"],["","","","",""],["R","espiratory Navigator","Yes","Yes","Same"],["","","","",""],["N","CEMRA","Yes","Yes","Same"],["","","","",""],["S","NAP","Yes","Yes","Same"],["","","","",""],["S","WI","Yes","Yes","Same"],["","","","",""],["S","WI+","Yes","Yes","Same"],["","","","",""],["T","1rho","Yes","Yes","Same"],["","","","",""],["t","FAST","Yes","Yes","Same"],["","","","",""],["T","RASS","Yes","Yes","Same"],["","","","",""],["u","CS","Yes","Yes","Same"],["","","","",""],["u","CSR","Yes","Yes","Same"],["","","","",""],["u","FreeR","Yes","Yes","Same"],["","","","",""],["u","SWIFT","Yes","Yes","Same"],["","","","",""],["U","TE","Yes","Yes","Same"],["","","","",""],["","WFI","Yes","Yes","Same"],["","","","",""],["Q","Scan","Yes","Yes","Same"],["","","","",""],["","Myocardial Perfusion","","",""],["","","Yes","Yes","Same"],["I","maging","","",""],["","","","",""],["C","ardiac Function","","",""],["","","Yes","Yes","Same"],["I","maging","","",""],["","","","",""],["","Myocardial Tagging","","",""],["","","Yes","Yes","Same"],["I","maging","","",""],["","","","",""],["","Myocardial Mapping","","",""],["","","Yes","Yes","Same"],["I","maging","","",""],["","","","",""],["","MRCA","Yes","Yes","Same"],["","","","",""],["S","ilicone-Only Imaging","Yes","Yes","Same"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243547-p12-t0","doc_id":"K243547","page_num":12,"bbox":[108.5,40.2,535.88,692.08],"n_rows":69,"n_cols":5,"columns":["","Shanghai United Imaging Health","care Co., Ltd.","",""],"rows":[["","Shanghai United Imaging Health","care Co., Ltd.","",""],["","Tel: +86 (21) 67076888 Fax","：+86 (21) 67076889","",""],["","www.united-imaging.com","","",""],["","","","",""],["","","Proposed Device","Predicate Device",""],["","ITEM","","","Remark"],["","","uMR Ultra","uMR Omega",""],["","","","",""],["I","nline MOCO","Yes","Yes","Same"],["","","","",""],["I","nline ECV","Yes","Yes","Same"],["","","","",""],["","Workflow","","",""],["","","","",""],["E","asyScan","Yes","Yes","Same"],["","","","",""],["","MoCap","Yes","Yes","Same"],["","","","",""],["E","asyBolus","Yes","No","Note 17"],["","","","",""],["A","uto Bolus Tracker","Yes","No","Note 18"],["","","","",""],["B","reast Biopsy","Yes","Yes","Same"],["","","","",""],["I","nline CEST","Yes","No","Note 19"],["","","","",""],["T","I Scout","Yes","Yes","Same"],["","","","",""],["E","asyFACT","Yes","Yes","Same"],["","","","",""],["E","asyCrop","Yes","Yes","Same"],["","","","",""],["I","mage Reconstruction","","",""],["","","","",""],["A","CS","Yes","Yes","Same"],["","","","",""],["D","eepRecon","Yes","Yes","Same"],["","","","",""],["t-","ACS","Yes","No","Note 20"],["","","","",""],["A","iCo","Yes","No","Note 21"],["","","","",""],["S","parkCo","Yes","Yes","Same"],["","","","",""],["I","nline Maps","Yes","Yes","Same"],["","","","",""],["S","pectroscopy","","",""],["","","","",""],["C","SI MRS Head","Yes","Yes","Same"],["","","","",""],["C","SI MRS Prostate","Yes","Yes","Same"],["","","","",""],["S","VS MRS Head","Yes","Yes","Same"],["","","","",""],["S","VS MRS Breast","Yes","Yes","Same"],["","","","",""],["S","VS MRS Liver","Yes","Yes","Same"],["","","","",""],["S","VS MRS Prostate","Yes","Yes","Same"],["","","","",""],["O","ther Functions","","",""],["","","","",""],["E","asyRegister","Yes","No","Note 22"],["","","","",""],["I","mplant Safety Mode","Yes","Yes","Same"],["","","","",""],["u","Remote Assistant","Yes","Yes","Same"],["","","","",""],["N","ote 1 The patient-acc","essible bore dimension of the p","roposed device is smaller than t","hat of the"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243547-p13-t0","doc_id":"K243547","page_num":13,"bbox":[103.1,78.84,542.4,679.66],"n_rows":14,"n_cols":2,"columns":["","The difference did not raise new safety and effectiveness concerns."],"rows":[["","The difference did not raise new safety and effectiveness concerns."],["Note 2","The max gradient amplitude of the proposed device is larger than that of the predicate\ndevice. Peripheral nerve stimulation and cardiac stimulation was controlled according to\nIEC 60601-2-33.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","The amplifier peak power per channel of the proposed device is the same as one\nconfiguration of the predicate device.\nThe difference did not raise new safety and effectiveness concerns."],["Note 4","The number of receive channels of the proposed device is more than that of the predicate\ndevice.\nThe difference did not raise new safety and effectiveness concerns."],["Note 5","The intended use of UHD SuperFlex Large - 24 is equivalent to previously cleared\nSuperFlex SuperFlex Large - 12. The only difference between them is the number of\nchannels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 6","The intended use of UHD SuperFlex Small - 24 is equivalent to previously cleared\nSuperFlex SuperFlex Small - 12. The only difference between them is the number of\nchannels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 7","The intended use of SuperFlex Whole Body - 48 is equivalent to previously cleared\nSuperFlex Body - 24. The only difference between them is the number of channels of the\nreceiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 8","The intended use of UHD SuperFlex Free - 24 is identical to previously cleared Head &\nNeck Coil - 48 (except imaging of head). The difference between them is the number of\nchannels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 9","The intended use of Wrist Coil - 24 is equivalent to previously cleared Wrist Coil - 12. The\nonly difference between them is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 10","The intended use of Shoulder Coil - 24 is equivalent to previously cleared Shoulder Coil -\n12. The only difference between them is the number of channels of the receiver coil.\nThe difference did not raise new safety and effectiveness concerns."],["Note 11","Compared to the predicate device, the proposed device added Tilt Support, which is used\nto support Head & Neck Coil scanning.\nThe new component did not raise new safety and effectiveness concerns."],["Note 12","Compared to the predicate device, the proposed device added Positioning Couch-top.\nPositioning Couch-top has load-bearing and deformation requirements. It is determined\naccording to clinical needs and product characteristics.\nThe new component did not raise new safety and effectiveness concerns."],["Note 13","Compared to the predicate device, the proposed device added Coil Support. Coil Support\ncan achieve the purpose of being as close as possible but not in contact with the human\nbody through the adjustment mechanism. The internal space and adjustment range can\nadapt to different body types of people.\nThe new component did not raise new safety and effectiveness concerns."],["Note 14","Compared to the predicate device, the proposed device added Patient Bore Projector, which\nprojects the video into the bore for patients to watch during scanning to improve patient\ncomfort.\nThe new function did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p14-t0","doc_id":"K243547","page_num":14,"bbox":[103.1,78.84,542.4,469.27],"n_rows":8,"n_cols":2,"columns":["Note 15","Compared to the predicate device, the proposed device added Body Part Recognization\nfunction in uVision, which allows assist patient positioning by performing image\nrecognition on human natural images through a 3D camera during the positioning stage.\nThe new function did not raise new safety and effectiveness concerns."],"rows":[["Note 15","Compared to the predicate device, the proposed device added Body Part Recognization\nfunction in uVision, which allows assist patient positioning by performing image\nrecognition on human natural images through a 3D camera during the positioning stage.\nThe new function did not raise new safety and effectiveness concerns."],["Note 16","MQD is substantially equivalent to GRE without RF Spoiling and use varyling flip angle\nand/or repetition time to acquire T1 mapping and T2 mapping images.\nThe new function did not raise new safety and effectiveness concerns."],["Note 17","EasyBolus is a workflow feature that combines the EasyScan function and the\nAutoBolusTracer function, capable of automatically locating the Bolus protocol and its\nROI (Region of Interest), and observing changes in signal values within the ROI to\nautomatically trigger the next protocol. The positioning can also be adjusted manually by\nuser. If the user is not satisfied with the timing of the trigger, manual triggering is also\npossible. The user panel also supports user configuration for manual triggering.\nThe new function did not raise new safety and effectiveness concerns."],["Note 18","Auto Bolus Tracker is a feature that automatically recognizes the time when the contrast\nagent reaches the target position and triggers the scan.\nThe new function did not raise new safety and effectiveness concerns."],["Note 19","Inline CEST aims to calculate the images of Z-spectrum curve and MTRasym curve from\nthe data in ROI from S0, Ssat and B0Map.\nThe new function did not raise new safety and effectiveness concerns."],["Note 20","t-ACS (temporal AI-assisted Compressed Sensing) is a dynamic magnetic resonance\nimaging technique which combines traditional Compressed Sensing algorithm with deep\nlearning priors. It outputs multi-phase images.\nThe new function did not raise new safety and effectiveness concerns."],["Note 21","AiCo (AI-based Motion Correction) is a k-space based technique to suppress motion\nartifacts. After enabling the AiCo function, the original images will still be saved.\nThe new function did not raise new safety and effectiveness concerns."],["Note 22","EasyRegister is a function that automatic estimates patient’s height and weight and patient\nposition by performing regression on human natural images through a 3D camera during\nthe positioning stage. Based on the captured feature and estimated pose of the patient on\nthe table.\nThe new function did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p14-t1","doc_id":"K243547","page_num":14,"bbox":[103.1,510.55,542.4,696.94],"n_rows":8,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Ultra","Reference Device#1\nuWS-MR (K220332)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Ultra","Reference Device#1\nuWS-MR (K220332)","Remark"],["Image Processing","","",""],["Inline Cardiac\nFunction","Yes","Yes","Note 23"],["Inline MRS","Yes","Yes","Same"],["Inline CPR","Yes","Yes","Same"],["Inline BOLD","Yes","Yes","Same"],["Inline DTI","Yes","Yes","Same"],["Inline Perfusion","Yes","Yes","Same"]],"caption_candidate":"Table 2 Comparison to reference device#1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p15-t0","doc_id":"K243547","page_num":15,"bbox":[104.84,78.84,542.4,245.06],"n_rows":4,"n_cols":5,"columns":["ITEM","","Proposed Device\nuMR Ultra","Reference Device#1\nuWS-MR (K220332)","Remark"],"rows":[["ITEM","","Proposed Device\nuMR Ultra","Reference Device#1\nuWS-MR (K220332)","Remark"],["Workflow","","","",""],["Inline Stitching","","Yes","Yes","Same"],["Note 23","In this submission, inline ED/ES phase recognition was included in the inline cardiac\nfunction module.\nCardiac MR cine imaging captures multi-slice data with varying end-systolic (ES) and\nend-diastolic (ED) phases in the absence of triggering signals (e.g., ECG). The inline\nED/ES recognition algorithm automatically identifies these phases per slice, enabling\ncross-slice cardiac cycle alignment for functional analysis.\nThe difference did not raise new safety and effectiveness concerns.","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p15-t1","doc_id":"K243547","page_num":15,"bbox":[104.84,286.37,538.8,380.21],"n_rows":4,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Ultra","Reference Device#2\nuPMR 790 (K234154)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Ultra","Reference Device#2\nuPMR 790 (K234154)","Remark"],["Workflow","","",""],["PASS","Yes","Yes","Same"],["ImageGuard","Yes","Yes","Same"]],"caption_candidate":"Table 3 Comparison to reference device#2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p18-t0","doc_id":"K243547","page_num":18,"bbox":[108.02,285.17,537.48,486.31],"n_rows":16,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=25)"],"rows":[["Subjects' Characteristics","Total(N=25)"],["Gender","Number"],["Male","15"],["Female","10"],["Age",""],["18-28","5"],["29-40","7"],[">41","13"],["Ethnicity",""],["White","4"],["Asian","16"],["Black","5"],["Body Mass Index (BMI)",""],["Underweight (<18.5)","2"],["Healthy weight (18.5-24.9)","18"],["Overweight and obesity (>24.9)","5"]],"caption_candidate":"groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p18-t1","doc_id":"K243547","page_num":18,"bbox":[108.02,613.75,537.48,711.46],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["AI Module\nVerification Test","The performance of AI was\nevaluated by comparing the\ninput error and output error\nwith respect of NRMSE. If\nthe NRMSE of the AI\noutput is less than the\nNRMSE of input, the","The ratio of error:\nNRMSE(output)/\nNRMSE(input) is\nalways less than\n1.","Pass"]],"caption_candidate":"corresponding testing results can be found in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p19-t0","doc_id":"K243547","page_num":19,"bbox":[108.02,78.84,537.48,589.03],"n_rows":6,"n_cols":4,"columns":["","performance of AI is\nconsidered to be validated.","",""],"rows":[["","performance of AI is\nconsidered to be validated.","",""],["Image SNR","Calculating SNR for both\nACS and CS images under\nthe same acceleration\nfactors and protocol\nparameters","ACS has higher\nSNR than CS.","Pass"],["Image\nResolution","Calculating the resolution\nvalue in elliptic ROI within\na line-pair test object using\nthe (standard deviation\n(SD) / mean value(S)) for\nboth ACS and CS images\nunder the same\nacceleration factors and\nprotocol parameters","ACS has higher\n(standard\ndeviation (SD) /\nmean value(S))\nvalues than CS.","Pass"],["Image\nContrast","Comparing the ROI signal\nintensities between images\nacquired with fully\nsampled and ACS images\nunder the same\nacceleration factors with\ndifferent TI values","Bland-Altman\nanalysis of image\nintensities\nacquired using\nfully sampled and\nACS was shown\nwith less than 1%\nbias and all\nsample points\nfalls in the 95%\nconfidence\ninterval.","Pass"],["Image Uniformity","Images of the phantom\nwere acquired with fully\nsampled and ACS protocol\nrespectively. Method used\nhere for data analysis is\naccording to NEMA MS 6-\n2008(R2004)","ACS achieved\nsignificantly same\nimage\nuniformities as\nfully sampled\nimage","Pass"],["Structure\nMeasurement","Dimensions of selected\nsmall structures were\nidentified and measured on\nACS images as well as on\nfully sampled images.","Measurements\ndifferences on\nACS and fully\nsampled images\nof same structures\nunder 5% is\nacceptable.","Pass"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p20-t0","doc_id":"K243547","page_num":20,"bbox":[108.1,507.88,537.36,709.09],"n_rows":14,"n_cols":6,"columns":["","Subjects' Characteristics","","","Total(N=25)",""],"rows":[["","Subjects' Characteristics","","","Total(N=25)",""],["","Gender","","","Number",""],["","Male","","","16",""],["","Female","","","9",""],["","Age","","","",""],["","18-28","","","10",""],["","29-50","","","12",""],["",">50","","","3",""],["","Ethnicity","","","",""],["","White","","","10",""],["","Asian","","","10",""],["","Black","","","5",""],["","Body Mass Index (BMI)","","","",""],["","< 18.5","","","10",""]],"caption_candidate":"ethnicity, and BMI groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p21-t0","doc_id":"K243547","page_num":21,"bbox":[108.02,282.05,537.48,456.79],"n_rows":6,"n_cols":4,"columns":["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],"rows":[["Evaluation\nItem","Acceptance Criteria","Test Result","Results"],["Image SNR","DeepRecon images achieve higher SNR\ncompared to NADR images","NADR: 343.63","PASS"],["","","DeepRecon: 496.15",""],["Image\nuniformity","Uniformity difference between\nDeepRecon images and NADR images\nunder 5%","0.07%","PASS"],["Image contrast","Intensity difference between DeepRecon\nimages and NADR images under 5%","0.2%","PASS"],["Structure\nmeasurement","Measurements on NADR and DeepRecon\nimages of same structures, measurement\ndifference under 5%","0%","PASS"]],"caption_candidate":"testing and the corresponding testing results can be found in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p22-t0","doc_id":"K243547","page_num":22,"bbox":[108.02,364.49,537.48,585.79],"n_rows":15,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=116)"],"rows":[["Subjects' Characteristics","Total(N=116)"],["Gender","Number"],["Male","68"],["Female","48"],["Age",""],["<29","43"],["29-40","25"],["> 41","48"],["Magnetic field strength (T)",""],["1.5","24"],["3","92"],["Ethnicity",""],["Black","31"],["White","56"],["Asian","29"]],"caption_candidate":"ankle, breast, thorax)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p24-t0","doc_id":"K243547","page_num":24,"bbox":[108.02,364.49,537.48,581.95],"n_rows":15,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=60)"],"rows":[["Subjects' Characteristics","Total(N=60)"],["Gender","Number"],["Male","41"],["Female","19"],["Age",""],["18-28","25"],["29-40","15"],["> =41","20"],["Ethnicity",""],["White","24"],["Black","9"],["Asian","27"],["BMI",""],["<= 24.9","37"],["> 24.9","23"]],"caption_candidate":"various genders, age groups, ethnicities and BMI groups as shown in the tables below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p24-t1","doc_id":"K243547","page_num":24,"bbox":[108.02,598.27,537.48,707.86],"n_rows":5,"n_cols":3,"columns":["Body part /Phantom","Dynamic MRI scan applications","Number of cases"],"rows":[["Body part /Phantom","Dynamic MRI scan applications","Number of cases"],["HEAD","Type I: Non-periodic physiological movement","136"],["SPINE","Type I: Non-periodic physiological movement","132"],["HIP","Type I: Non-periodic physiological movement","106"],["CARDIAC","Type II: Cardiac periodic movement","25"]],"caption_candidate":"> 24.9 23","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p25-t0","doc_id":"K243547","page_num":25,"bbox":[108.02,78.84,537.48,232.1],"n_rows":7,"n_cols":3,"columns":["KNEE","Type I: Non-periodic physiological movement","131"],"rows":[["KNEE","Type I: Non-periodic physiological movement","131"],["ABDOMEN","Type III: Contrast enhancement","186"],["","Type I: Non-periodic physiological movement","94"],["PELVIS","Type III: Contrast enhancement","52"],["","Type I: Non-periodic physiological movement","149"],["ANKLE","Type I: Non-periodic physiological movement","94"],["PHANTOM","Type I: Non-periodic physiological movement","68"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p26-t0","doc_id":"K243547","page_num":26,"bbox":[108.02,314.81,537.48,666.94],"n_rows":28,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=24)"],"rows":[["Subjects' Characteristics","Total(N=24)"],["Gender","Number"],["Male","12"],["Female","12"],["Age",""],["18-28","8"],["29-40","11"],[">41","5"],["Body Mass Index (BMI)",""],["Under and healthy weight (<24.9)","10"],["Overweight and obesity (>24.9)","14"],["Ethnicity",""],["White","7"],["Black","5"],["Asian","12"],["Body parts","Number of Cases"],["Head","20"],["Neck","23"],["Shoulder","23"],["Spine","28"],["Thorax","12"],["Abdomen","14"],["Cardiac","9"],["Pelvis","27"],["Hip","15"],["Knee","16"],["Ankle","18"],["Upper Extremity","13"]],"caption_candidate":"with and without fat saturation. The demographic distribution was listed in table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p28-t0","doc_id":"K243547","page_num":28,"bbox":[107.95,78.72,537.48,303.29],"n_rows":17,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=15)"],"rows":[["Subjects' Characteristics","Total(N=15)"],["Gender","Number"],["Male","9"],["Female","6"],["Age",""],["18-29","2"],["30-44","8"],["45-64","4"],[">=65","0"],["Ethnicity",""],["White","N.A."],["Asian","15"],["Body Mass Index (BMI)",""],["Underweight (<18.5)","2"],["Healthy weight (18.5-24.9)","10"],["Overweight (25.0-29.9)","3"],["Obesity (>=30.0)","0"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p28-t1","doc_id":"K243547","page_num":28,"bbox":[107.95,414.89,537.48,540.67],"n_rows":10,"n_cols":2,"columns":["Body Parts","Number of cases"],"rows":[["Body Parts","Number of cases"],["Head","21"],["C-spine","5"],["Shoulder","1"],["Wrist","1"],["Thorax","2"],["Abdomen","8"],["L-spine","2"],["Pelvis","19"],["Total","59"]],"caption_candidate":"human ethnicity.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p28-t2","doc_id":"K243547","page_num":28,"bbox":[107.95,604.51,537.48,698.26],"n_rows":2,"n_cols":4,"columns":["Test parts","Test Methods","Accept criteria","Test Results"],"rows":[["Test parts","Test Methods","Accept criteria","Test Results"],["Test on the\nspark\ndetection\naccuracy","Based on the real-world\ntesting dataset, calculating\nthe detection accuracy by\ncomparing the spark\ndetection results with the\nground-truth.","The average detection\naccuracy need be larger\nthan 90%","The average detection\naccuracy is 94%."]],"caption_candidate":"and spark correction effectiveness, as the following Table 6 shows.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p30-t0","doc_id":"K243547","page_num":30,"bbox":[108.02,78.84,537.48,300.05],"n_rows":15,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=80)"],"rows":[["Subjects' Characteristics","Total(N=80)"],["Gender","Number"],["Male","45"],["Female","35"],["Age",""],["≤25","14"],["26-50","47"],["≥51","19"],["Magnetic field strength (T)",""],["1.5","31"],["3","49"],["Ethnicity",""],["White","35"],["Black","21"],["Asian","24"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p31-t0","doc_id":"K243547","page_num":31,"bbox":[108.02,332.69,537.48,553.99],"n_rows":15,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=65)"],"rows":[["Subjects' Characteristics","Total(N=65)"],["Gender","Number"],["Male","37"],["Female","28"],["Age",""],["<29","23"],["29-40","9"],["＞40","33"],["Magnetic field strength (T)",""],["1.5T","18"],["3.0T","47"],["Ethnicity",""],["Asian","12"],["Black","19"],["White","34"]],"caption_candidate":"groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p32-t0","doc_id":"K243547","page_num":32,"bbox":[108.02,332.69,537.48,430.37],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Passing Rate","Satisfied and Acceptable ratio (S+A)/(S+A+F) exceeds 95%.\nSatisfied (S): Five ROIs are placed within the liver parenchyma, avoiding the\nliver borders and vascular structures.\nAcceptable (A): Fewer than five ROIs are placed within the liver\nparenchyma, avoiding the liver borders and vascular structures.\nFailure (F): ROIs are positioned on liver borders or vascular structures, or no\nROIs are placed."]],"caption_candidate":"The validation type and acceptance criteria is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p32-t1","doc_id":"K243547","page_num":32,"bbox":[108.02,510.19,537.48,701.98],"n_rows":13,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=25)"],"rows":[["Subjects' Characteristics","Total(N=25)"],["Gender","Number"],["Male","20"],["Female","5"],["Age",""],["<30","6"],["[30,40)","7"],["[40,50)","6"],["[50,60)","3"],["[60,70)","2"],[">=70","1"],["Weight (kg)",""],["<80","14"]],"caption_candidate":"total of 25 cases from 25 volunteers were used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p33-t0","doc_id":"K243547","page_num":33,"bbox":[108.02,78.84,537.48,167.3],"n_rows":6,"n_cols":2,"columns":["[80, 90)","4"],"rows":[["[80, 90)","4"],[">=90","7"],["Ethnicity",""],["Asian","11"],["White","9"],["Black","5"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p33-t1","doc_id":"K243547","page_num":33,"bbox":[108.02,263.09,537.48,523.63],"n_rows":8,"n_cols":5,"columns":["Gender","Satisfied (S)","Acceptable (A)","Failure (F)","Satisfied and Acceptable Ratio"],"rows":[["Gender","Satisfied (S)","Acceptable (A)","Failure (F)","Satisfied and Acceptable Ratio"],["Male\nFemale","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Age","","","",""],["<30\n[30,40)\n[40,50)\n[50,60)\n[60,70)\n>=70","100%\n100%\n100%\n100%\n100%\n100%","0%\n0%\n0%\n0%\n0%\n0%","0%\n0%\n0%\n0%\n0%\n0%","100%\n100%\n100%\n100%\n100%\n100%"],["Weight (kg)","","","",""],["<80\n[80, 90)\n>=90","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"],["Ethnicity","","","",""],["Asian\nWhite\nBlack","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"]],"caption_candidate":"generalization in different subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p34-t0","doc_id":"K243547","page_num":34,"bbox":[108.02,94.7,537.48,144.02],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Error between TI frame output\nby algorithm and gold\nstandard","The average frame difference between the frame of auto-calculated\nTI and the gold standard frame is less than or equal to 1 frame, and\nthe maximum frame difference is less than or equal to 2 frames."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p34-t1","doc_id":"K243547","page_num":34,"bbox":[108.02,223.82,537.48,548.35],"n_rows":22,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=27)"],"rows":[["Subjects' Characteristics","Total(N=27)"],["Gender","Number"],["Male","18"],["Female","9"],["Age",""],["<18","1"],["18-28","4"],["29-40","7"],["> 41","15"],["Protocol",""],["TIscout_sax","27"],["BMI (kg/m(2))",""],["<18.5","1"],["[18.5, 25)","10"],[">=25","11"],["Unknown","5"],["Magnetic field strength (T)",""],["1.5","18"],["3","9"],["Ethnicity",""],["Asian","19"],["White","8"]],"caption_candidate":"table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p34-t2","doc_id":"K243547","page_num":34,"bbox":[108.02,628.3,537.48,700.78],"n_rows":4,"n_cols":4,"columns":["Gender","Number","Average frame difference","maximum frame\ndifference"],"rows":[["Gender","Number","Average frame difference","maximum frame\ndifference"],["Male","18","0.38","2"],["Female","9","0.44","1"],["Age","","",""]],"caption_candidate":"Scout algorithm performs as expected in different subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p35-t0","doc_id":"K243547","page_num":35,"bbox":[108.02,78.84,537.48,329.57],"n_rows":17,"n_cols":4,"columns":["<18","1","0","0"],"rows":[["<18","1","0","0"],["18-28","4","0.25","1"],["29-40","7","0.57","2"],["> 41","15","0.33","1"],["Protocol","","",""],["TIscout_sax","27","0.37","2"],["BMI (kg/m(2))","","",""],["<18.5","1","0","0"],["[18.5, 25)","10","0.7","2"],[">=25","11","0.27","1"],["Unknown","5","0","0"],["Magnetic field strength (T)","","",""],["1.5","18","0.39","2"],["3","9","0.33","1"],["Ethnicity","","",""],["Asian","19","0.47","2"],["White","8","0.125","1"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p35-t1","doc_id":"K243547","page_num":35,"bbox":[108.02,520.51,537.48,557.83],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Dice","The average Dice coefficient of the left ventricular myocardium after\nmotion correction is greater than 0.87."]],"caption_candidate":"The validation type and acceptance criteria is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p35-t2","doc_id":"K243547","page_num":35,"bbox":[108.02,637.66,537.48,662.74],"n_rows":2,"n_cols":3,"columns":["Dataset","Patients Number","Cases Number"],"rows":[["Dataset","Patients Number","Cases Number"],["Testing Data","60","105"]],"caption_candidate":"Sample Size:","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K243547-p37-t1","doc_id":"K243547","page_num":37,"bbox":[108.07,457.87,537.41,709.18],"n_rows":20,"n_cols":6,"columns":["","Age","","","Average Dice after motion correction",""],"rows":[["","Age","","","Average Dice after motion correction",""],["","<22","","","0.92",""],["","[22, 40)","","","0.93",""],["","[40, 60)","","","0.92",""],["","[60, 90)","","","0.92",""],["","Gender","","","Average Dice after motion correction",""],["","Female","","","0.92",""],["","Male","","","0.92",""],["","Ethnicity","","","Average Dice after motion correction",""],["","Asian","","","0.93",""],["","White","","","0.91",""],["","BMI (kg/m(2))","","","Average Dice after motion correction",""],["","< 18.5","","","0.95",""],["","[18.5, 25)","","","0.93",""],["",">=25","","","0.91",""],["","Unknown","","","0.93",""],["","Magnetic field strength (T)","","","Average Dice after motion correction",""],["","1.5","","","0.92",""],["","3.0","","","0.93",""],["","Disease conditions","","","Average Dice after motion correction",""]],"caption_candidate":"subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p38-t0","doc_id":"K243547","page_num":38,"bbox":[108.05,78.96,537.43,116.42],"n_rows":3,"n_cols":6,"columns":["","Positive","","","0.93",""],"rows":[["","Positive","","","0.93",""],["","Negative","","","0.92",""],["","Unknown","","","0.91",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K243547-p39-t0","doc_id":"K243547","page_num":39,"bbox":[108.02,301.01,537.48,350.33],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["The error between the phase indices calculated\nby the algorithm for the ED and ES of test data\nand the gold standard phase indices.","The average error does not exceed 1 frame."]],"caption_candidate":"The validation type and acceptance criteria is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p39-t1","doc_id":"K243547","page_num":39,"bbox":[108.02,430.13,537.48,710.5],"n_rows":19,"n_cols":3,"columns":["Gender","Number of people","Number of cases"],"rows":[["Gender","Number of people","Number of cases"],["Male","36","72"],["Female","10","13"],["Unknown","10","10"],["Age","",""],["[20,30)","15","20"],["[30,40)","9","23"],["[40,50)","14","22"],["[50,60)","5","17"],[">=60","3","3"],["Unknown","10","10"],["Field strength","",""],["1.5T","10","19"],["3.0T","36","66"],["Unknown","10","10"],["Disease conditions","",""],["NOR","46","85"],["MINF","2","2"],["DCM","2","2"]],"caption_candidate":"table below. A total of 95 cases from 56 volunteers were used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p40-t0","doc_id":"K243547","page_num":40,"bbox":[108.02,78.84,537.48,167.3],"n_rows":6,"n_cols":3,"columns":["HCM","5","5"],"rows":[["HCM","5","5"],["ARV","1","1"],["Ethnicity","",""],["Asian","22","60"],["White","26","26"],["Black","8","9"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p40-t1","doc_id":"K243547","page_num":40,"bbox":[108.02,278.93,537.48,657.58],"n_rows":25,"n_cols":3,"columns":["Gender","Case Number","Average of frame index\ndifferences"],"rows":[["Gender","Case Number","Average of frame index\ndifferences"],["Male","72","0.12"],["Female","13","0.14"],["Unknown","10","0.14"],["Age","",""],["[20,30)","20","0.13"],["[30,40)","23","0.10"],["[40,50)","22","0.16"],["[50,60)","17","0.10"],[">=60","3","0.16"],["Unknown","10","0.14"],["Field strength","",""],["1.5T","19","0.13"],["3.0T","66","0.12"],["Unknown","10","0.14"],["Disease conditions","",""],["NOR","85","0.12"],["MINF","2","0.15"],["DCM","2","0.13"],["HCM","5","0.15"],["ARV","1","0.14"],["Ethnicity","",""],["Asian","60","0.11"],["White","26","0.33"],["Black","9","0.13"]],"caption_candidate":"good generalization in different subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p41-t0","doc_id":"K243547","page_num":41,"bbox":[108.02,205.1,537.48,399.29],"n_rows":2,"n_cols":2,"columns":["Validation Type","Acceptance Criteria"],"rows":[["Validation Type","Acceptance Criteria"],["Passing rate","To verify the effectiveness of the algorithm, the subjective evaluation\nmethod was used. The segmentation result of each case was obtained with\nthe algorithm, and the segmentation mask was evaluated with the following\ncriteria. The test pass criteria was: no failure cases, satisfaction rate\nS/(S+A+F) exceeding 95%.\nThe criteria are as follows:\nSatisfied (S): the segmentation myocardial boundary adheres to the\n\nmyocardial boundary and blood pool ROI is within the blood pool\nexcluding the papillary muscles.\nAcceptable (A): These are small missing or redundant areas in the\n\nmyocardial segmentation but not obviously and the blood pool ROI is\nwithin the blood pool excluding the papillary muscles.\nFail (F): The myocardial mask does not adhere to the myocardial\n\nboundary or the blood pool ROI is not within the blood pool, or the\nblood pool ROI contains papillary muscles."]],"caption_candidate":"The validation type and acceptance criteria is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p41-t1","doc_id":"K243547","page_num":41,"bbox":[108.02,490.99,537.48,712.3],"n_rows":15,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=28)"],"rows":[["Subjects' Characteristics","Total(N=28)"],["Gender","Number"],["Male","20"],["Female","8"],["Age",""],["<18","1"],["18-28","4"],["29-40","1"],["> 41","22"],["Protocol",""],["post_t1map_sax","28"],["native_t1map_sax","28"],["BMI (kg/m(2))",""],["<18.5","0"],["[18.5, 25)","7"]],"caption_candidate":"table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p42-t0","doc_id":"K243547","page_num":42,"bbox":[108.02,78.84,537.48,255.86],"n_rows":12,"n_cols":2,"columns":[">=25","15"],"rows":[[">=25","15"],["Unknown","6"],["Magnetic field strength (T)",""],["1.5","13"],["3","15"],["Ethnicity",""],["Asian","17"],["White","11"],["Healthy",""],["Negative","19"],["Postive","4"],["Unknown","5"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p42-t1","doc_id":"K243547","page_num":42,"bbox":[108.02,333.65,537.48,706.78],"n_rows":14,"n_cols":5,"columns":["Gender","Satisfied (S)","Acceptable (A)","Total Failure\nRate","Total satisfaction\nRate"],"rows":[["Gender","Satisfied (S)","Acceptable (A)","Total Failure\nRate","Total satisfaction\nRate"],["Male\nFemale","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Age","","","",""],["18-28\n29-40\n> 41","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"],["Protocol","","","",""],["post_t1map_sax\nnative_t1map_sax","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["BMI (kg/m(2))","","","",""],["<18.5\n[18.5, 25)\n>=25\nUnknown","100%\n100%\n100%\n100%","0%\n0%\n0%\n0%","0%\n0%\n0%\n0%","100%\n100%\n100%\n100%"],["Magnetic field strength (T)","","","",""],["1.5\n3","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Ethnicity","","","",""],["Asian\nWhite","100%\n100%","0%\n0%","0%\n0%","100%\n100%"],["Healthy","","","",""],["Negative\nPositive\nUnknown","100%\n100%\n100%","0%\n0%\n0%","0%\n0%\n0%","100%\n100%\n100%"]],"caption_candidate":"segmentation algorithm performs as expected in different subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p44-t0","doc_id":"K243547","page_num":44,"bbox":[108.02,391.49,537.48,420.29],"n_rows":2,"n_cols":4,"columns":["Algorithm","PH5","PH15","MEAN_H"],"rows":[["Algorithm","PH5","PH15","MEAN_H"],["Human height estimation","92.4%","100%","31.53mm"]],"caption_candidate":"The performance of the height estimation algorithm is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p45-t0","doc_id":"K243547","page_num":45,"bbox":[108.02,423.17,537.48,451.99],"n_rows":2,"n_cols":4,"columns":["Algorithm","PW10","PW20","MEAN_H"],"rows":[["Algorithm","PW10","PW20","MEAN_H"],["Human weight estimation","68.64%","90.68%","6.18kg"]],"caption_candidate":"The performance of the height estimation algorithm is shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243547-p46-t0","doc_id":"K243547","page_num":46,"bbox":[108.02,380.33,537.48,586.87],"n_rows":14,"n_cols":2,"columns":["Subjects' Characteristics","Total(N=20)"],"rows":[["Subjects' Characteristics","Total(N=20)"],["Gender","Number"],["Male","12"],["Female","8"],["Age",""],["<60","11"],[">60","9"],["Protocol",""],["neck_easy_scout","20"],["BolusTracker_cor","20"],["Magnetic field strength (T)",""],["3.0","20"],["Ethnicity",""],["Asia","20"]],"caption_candidate":"The EasyBolus has undergone performance testing on 20 subjects","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243548-p8-t0","doc_id":"K243548","page_num":8,"bbox":[77.64,177.72,124.56,245.4],"n_rows":5,"n_cols":2,"columns":["","for"],"rows":[["","for"],["clinical",""],["performa",""],["nce",""],["testing",""]],"caption_candidate":"Exclusion ● CT images with or without ● Chest CT with or without contrast","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243548-p10-t0","doc_id":"K243548","page_num":10,"bbox":[113.19,100.04,498.6,302.09],"n_rows":16,"n_cols":6,"columns":["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],"rows":[["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],["","","","","",""],["","Estimate","","CL","CL",""],["","","","","",""],["","(seconds)","","","",""],["Predicate K230020","70.1","104","64.9","75.4","66"],["","","","","",""],["","","","","",""],["Processing Time","","","","",""],["BriefCase-Triage +","41.4","104","40.4","42.5","39.5"],["","","","","",""],["Image","","","","",""],["Communication","","","","",""],["Platform Time-To-","","","","",""],["","","","","",""],["Notification","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243548-p11-t0","doc_id":"K243548","page_num":11,"bbox":[230.01,558.63,382.12,714.56],"n_rows":11,"n_cols":7,"columns":["Thickness\n(mm)","","N","","%","",""],"rows":[["Thickness\n(mm)","","N","","%","",""],["","","56","","18.2%","",""],["0.5-1","","","","","",""],["","","","","","",""],["","","151","","49.0%","",""],["1-2","","","","","",""],["","","","","","",""],["","","101","","32.8%","",""],["2-5","","","","","",""],["","","","","","",""],["Total","","308","","","100%",""]],"caption_candidate":"Table 6. Frequency Distribution of slice thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243548-p12-t0","doc_id":"K243548","page_num":12,"bbox":[72.48,277.08,540.48,469.2],"n_rows":5,"n_cols":3,"columns":["Operating Points","Sensitivity % (95% CI)","Specificity % (95% CI)"],"rows":[["Operating Points","Sensitivity % (95% CI)","Specificity % (95% CI)"],["AOP1","98.1% (95% CI: 93.2%-\n99.8%)","90.2% (95% CI: 85.3%-\n93.9%)"],["AOP2","97.12% (95% CI: 91.8%-\n99.4%)","92.16% (95% CI: 87.6%-\n95.5%)"],["AOP3","92.3% (95% CI: 85.4%-\n96.6%)","95.1% (95% CI: 91.2%-\n97.6%)"],["AOP4","Sensitivity was 88.5% (95%\nCI: 80.7%-93.9%)","95.1% (95% CI: 91.2%-\n97.6%)"]],"caption_candidate":"Table 7. Additional Operating Points","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p5-t0","doc_id":"K243611","page_num":5,"bbox":[72.26,525.91,523.18,552.19],"n_rows":2,"n_cols":4,"columns":["Manufacturer","Predicate Trade Name","Application No.","Product Code"],"rows":[["Manufacturer","Predicate Trade Name","Application No.","Product Code"],["Viz.ai, Inc.","Viz SDH","K220439","QAS"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p8-t0","doc_id":"K243611","page_num":8,"bbox":[72.34,86.07,520.05,637.45],"n_rows":29,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["Device Name","","","JLK-SDH","","","Viz SDH","",""],["","510(k) Number","","K243611","","","K220439","",""],["","Regulation Number","","21 C.F.R. § 892.2080","","","21 C.F.R. § 892.2080","",""],["","Product Code","","QAS","","","QAS","",""],["","Intended User","","Radiologist","","","Neurovascular Specialist","",""],["","Anatomical Region","","Head","","","Head","",""],["Region of Interest","","","Hemispheric Subdural\nHemorrhage","","","Hemispheric Subdural\nHemorrhage","",""],["","Indicated Imaging","","Non-contrast CT (NCCT)","","","Non-contrast CT (NCCT)","",""],["","Modality","","","","","","",""],["Alteration of Original\nImage Database","Alteration of Original","","No","","","No","",""],["","Diagnostic Application","","Notification-only","","","Notification-only","",""],["","Algorithm","","Artificial Intelligence / Machine\nLearning","","","Artificial Intelligence / Machine\nLearning.","",""],["","Implementation","","","","","","",""],["","Results of Image","","Internal, no image marking","","","Internal, no image marking","",""],["","Analysis","","","","","","",""],["Segmentation of region\nof interest","","","No; device does not mark,\nhighlight, or direct users'\nattention to a specific location in\nthe original image.","","","No; device does not mark,\nhighlight, or direct users'\nattention to a specific location\nin the original image.","",""],["","Relationship to standard","","In Parallel / Concurrently","","","In Parallel / Concurrently","",""],["","of care workflow","","","","","","",""],["","Compatibility with the","","DICOM Compatible","","","DICOM Compatible","",""],["","environment and other","","","","","","",""],["","devices","","","","","","",""],["","Technical","","Artificial intelligence algorithm\nwith database of images","","","Artificial intelligence algorithm\nwith database of images","",""],["","Implementation","","","","","","",""],["Preview Images","","","Initial assessment; non-\ndiagnostic purposes\nPresentation of preview of the\nstudy for initial informational\npurposes","","","Initial assessment; non-\ndiagnostic purposes\nPresentation of preview of the\nstudy for initial informational\npurposes","",""],["","Interference with","","No. Cases are not removed\nfrom worklist or deprioritized.","","","No. Cases are not removed\nfrom worklist or deprioritized.","",""],["","standard workflow","","","","","","",""],["Data acquisition","","","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities","","","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities","",""],["","Time to Notification","","0.19 ±0.05 minutes","","","1.15±0.57 minutes","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t0","doc_id":"K243611","page_num":10,"bbox":[72.3,127.04,523.14,195.14],"n_rows":4,"n_cols":8,"columns":["Performance Metrics Overview for Patients Categorized by States (i.e. Clinical Site)","","","","","","",""],"rows":[["Performance Metrics Overview for Patients Categorized by States (i.e. Clinical Site)","","","","","","",""],["","Clinical Site","N","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Region 001","","422","0.97 [0.93, 0.99]","","0.99 [0.98, 1.00]","",""],["Region 002","","138","0.98 [0.94, 1.00]","","0.9 [0.83, 0.96]","",""]],"caption_candidate":"various confounding variables:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t1","doc_id":"K243611","page_num":10,"bbox":[72.3,230.9,523.14,323.33],"n_rows":5,"n_cols":6,"columns":["","Performance Metrics Overview for Patients Categorized by Age","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Age","","","",""],["","Age Range\n(Years)","N","Sensitivity [95% CI]","Specificity [95% CI]",""],["<50","","84","0.94 [0.80, 1.00]","0.99 [0.95, 1.00]",""],["50-70","","220","0.96 [0.89, 1.00]","0.98 [0.95, 0.99]",""],["70<","","256","0.98 [0.95, 1.00]","0.97 [0.93, 0.99]",""]],"caption_candidate":"Region 002: Northeast – New York / Midwest – Missouri, Iowa, Wisconsin, Illinois, Ohio","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t2","doc_id":"K243611","page_num":10,"bbox":[72.3,340.61,523.14,408.41],"n_rows":4,"n_cols":8,"columns":["Performance Metrics Overview for Patients Categorized by Gender","","","","","","",""],"rows":[["Performance Metrics Overview for Patients Categorized by Gender","","","","","","",""],["","Gender","N","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Male","","283","0.99 [0.97, 1.00]","","0.96 [0.93, 0.98]","",""],["Female","","277","0.95 [0.89, 0.99]","","0.99 [0.97, 1.00]","",""]],"caption_candidate":"70< 256 0.98 [0.95, 1.00] 0.97 [0.93, 0.99]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t3","doc_id":"K243611","page_num":10,"bbox":[72.3,421.94,523.14,540.31],"n_rows":7,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Race-Ethnicity","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Race-Ethnicity","","","","","","","",""],["","Race-Ethnicity","N","","","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Non-Hispanic White","","424","","0.97 [0.93, 0.99]","","","0.99 [0.97, 1.00]","",""],["Hispanic or Latino","","51","","1.0 [1.00, 1.00]","","","0.97 [0.89, 1.00]","",""],["Black or African American","","67","","0.96 [0.86, 1.00]","","","0.9 [0.81, 0.98]","",""],["Asian & Pacific Islander","","9","","1.0 [1.00, 1.00]","","","1.0 [0.00, 1.00]","",""],["Unknown / Refused","","9","","-","","","0.89 [0.67, 1.00]","",""]],"caption_candidate":"Female 277 0.95 [0.89, 0.99] 0.99 [0.97, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t4","doc_id":"K243611","page_num":10,"bbox":[72.3,554.08,523.14,656.26],"n_rows":6,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Scanner Manufacturer","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Scanner Manufacturer","","","","","","","",""],["","Manufacturer","N","","","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["General Electric","","124","","0.98 [0.93, 1.00]","","","0.89 [0.82, 0.96]","",""],["Siemens","","340","","0.95 [0.90, 0.99]","","","0.99 [0.98, 1.00]","",""],["Philips","","70","","1.0 [1.00, 1.00]","","","1.0 [1.00, 1.00]","",""],["Toshiba / Canon","","26","","1.0 [1.00, 1.00]","","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Unknown / Refused 9 - 0.89 [0.67, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p10-t5","doc_id":"K243611","page_num":10,"bbox":[72.3,670.03,523.14,754.42],"n_rows":5,"n_cols":9,"columns":["","Performance Metrics Overview for Patients Categorized by SDH Type","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by SDH Type","","","","","","",""],["","SDH type","","","N","","","Sensitivity [95% CI]",""],["Acute","","","96","","","0.95 [0.90, 0.99]","",""],["Chronic","","","25","","","1.0 [1.00, 1.00]","",""],["Both (Acute & Chronic)","","","53","","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Toshiba / Canon 26 1.0 [1.00, 1.00] 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t0","doc_id":"K243611","page_num":11,"bbox":[72.3,85.98,523.14,159.86],"n_rows":4,"n_cols":7,"columns":["","Performance Metrics Overview for Patients Categorized by SDH with Other Hemorrhage","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by SDH with Other Hemorrhage","","","","",""],["","SDH and other Hemorrhage","N","","","Sensitivity [95% CI]",""],["Subdural Hemorrhage Only","","95","","0.99 [0.97, 1.00]","",""],["Subdural Hemorrhage and Other\nHemorrhage Present","","79","","0.95 [0.90, 0.99]","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t1","doc_id":"K243611","page_num":11,"bbox":[72.3,172.52,523.14,276.89],"n_rows":6,"n_cols":7,"columns":["","Performance Metrics Overview for Patients Categorized by SDH Location","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by SDH Location","","","","",""],["","SDH Location","N","","","Sensitivity [95% CI]",""],["Convexity","","84","","0.96 [0.92, 1.00]","",""],["Falx","","12","","0.83 [0.58, 1.00]","",""],["Tentorium","","2","","1.0 [1.00, 1.00]","",""],["Multi","","76","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Hemorrhage Present","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t2","doc_id":"K243611","page_num":11,"bbox":[72.3,305.63,523.14,407.69],"n_rows":6,"n_cols":10,"columns":["","Performance Metrics Overview for Patients Categorized by Slice Thickness","","","","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Slice Thickness","","","","","","","",""],["","Slice Thickness","","","N","Sensitivity [95% CI]","","","Specificity [95% CI]",""],["Slice thickness<2.5mm","","","1","","-","","1.0 [1.00, 1.00]","",""],["2.5mm≤Slice thickness <3.5mm","","","73","","1.0 [1.00, 1.00]","","0.94 [0.88, 0.99]","",""],["3.5mm≤Slice thickness ≤5mm","","","485","","0.97 [0.94, 0.99]","","0.98 [0.96, 0.99]","",""],["Slice thickness>5mm","","","1","","1.0 [1.00, 1.00]","","-","",""]],"caption_candidate":"Multi 76 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t3","doc_id":"K243611","page_num":11,"bbox":[72.3,436.46,523.14,540.79],"n_rows":6,"n_cols":7,"columns":["","Performance Metrics Overview for Patients Categorized by SDH Thickness","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by SDH Thickness","","","","",""],["","SDH Thickness","N","","","Sensitivity [95% CI]",""],["Thickness < 3mm","","15","","0.67 [0.40, 0.87]","",""],["3mm ≤ Thickness < 6mm","","36","","1.0 [1.00, 1.00]","",""],["6mm ≤ Thickness < 10mm","","45","","1.0 [1.00, 1.00]","",""],["Thickness ≥ 10mm","","78","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Slice thickness>5mm 1 1.0 [1.00, 1.00] -","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t4","doc_id":"K243611","page_num":11,"bbox":[72.3,569.56,523.14,673.9],"n_rows":6,"n_cols":7,"columns":["","Performance Metrics Overview for Patients Categorized by SDH Volume","","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by SDH Volume","","","","",""],["","Volume (mL)","N","","","Sensitivity [95% CI]",""],["Volume < 1","","42","","0.88 [0.79, 0.98]","",""],["1 ≤ Volume < 5","","51","","1.0 [1.00, 1.00]","",""],["5 ≤ Volume < 10","","16","","1.0 [1.00, 1.00]","",""],["Volume ≥ 10","","65","","1.0 [1.00, 1.00]","",""]],"caption_candidate":"Thickness ≥ 10mm 78 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243611-p11-t5","doc_id":"K243611","page_num":11,"bbox":[72.3,702.7,523.14,755.38],"n_rows":3,"n_cols":6,"columns":["","Performance Metrics Overview for Patients Categorized by Metal Artifacts","","","",""],"rows":[["","Performance Metrics Overview for Patients Categorized by Metal Artifacts","","","",""],["Metallic artifact","","N","Sensitivity [95% CI]","Specificity [95% CI]",""],["Metallic artifact (+)","","122","1.0 [1.00, 1.00]","0.91 [0.85, 0.97]",""]],"caption_candidate":"Volume ≥ 10 65 1.0 [1.00, 1.00]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243614-p5-t0","doc_id":"K243614","page_num":5,"bbox":[72.26,189.14,535.06,383.93],"n_rows":3,"n_cols":2,"columns":["Applicant:","Sonio\n147 Rue d’Aboukir,\n75002, Paris France"],"rows":[["Applicant:","Sonio\n147 Rue d’Aboukir,\n75002, Paris France"],["Primary Contact Person:","Florian Akpakpa\nDirector Regulatory Affairs and Quality Assurance\nSonio\nPhone: +33 6 19 38 71 45\nEmail: florian.akpakpa@sonio.ai"],["Date Prepared:","February 19, 2025"]],"caption_candidate":"I.Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243614-p5-t1","doc_id":"K243614","page_num":5,"bbox":[72.26,460.63,535.06,586.87],"n_rows":4,"n_cols":2,"columns":["Device Trade\nName:","Sonio Suspect"],"rows":[["Device Trade\nName:","Sonio Suspect"],["Classification\nName:","21 CFR 892.2060 - Radiological computer-assisted diagnostic\nsoftware for lesions suspicious of cancer"],["Regulatory Class:","Class II"],["Product Code:","POK (primary)"]],"caption_candidate":"II.Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243614-p7-t0","doc_id":"K243614","page_num":7,"bbox":[58.09,166.34,539.54,470.23],"n_rows":12,"n_cols":4,"columns":["Fetal","","",""],"rows":[["Fetal","","",""],["","Abnormal Finding","View","GA"],["Anatomy","","",""],["","","",""],["Chest","Absence or unusual size of at least one of the 3\nvessels","3 vessels","T2/T3"],["","Malposition of the great vessels","LVOT/RVOT","T2/T3"],["","Disequilibrium OR absence of at least one of the\ntwo ventricles","4 chambers","T1/T2/T3"],["","Thoracic situs inversus","",""],["Abdominal","Abdominal situs inversus","Abdominal\ncircumference","T1/T2/T3"],["","Non-visibility of a single stomach bubble OR\nabnormally big stomach","",""],["Cephalic","Absence of the cavum septum pellucidum","Transthalamic view","T2/T3"],["","Absence of the Corpus Callosum","Corpus callosum\nview*","T2/T3"]],"caption_candidate":"Anatomy and Gestational Age (GA)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p9-t0","doc_id":"K243617","page_num":9,"bbox":[90.28,169.22,553.07,584.35],"n_rows":9,"n_cols":9,"columns":["Software\nfunctions","Subject devices","","Predicate","","","Reference","","Discussion"],"rows":[["Software\nfunctions","Subject devices","","Predicate","","","Reference","","Discussion"],["","","","device","","","device #1","",""],["","","","(K231482)","","","(K230162)","",""],["CardioBoost","Yes\nIt is an image reconstruction method\nfor cardiac scanning based on deep\nlearning technology.","--","","","DELTA","","","Substantial\nEquivalent\nNote 1"],["AIIR","Yes\nIt is an image reconstruction method\nthat combines a modal-based iterative\nreconstruction and deep learning\ntechnology.","Yes","","","--","","","Substantial\nEquivalent\nNote 2"],["CardioXpha\nse","Yes\nIt can recommend the optimal phase\nfor cardiac reconstruction, which is\nbased on deep learning technology.","Yes","","","--","","","Substantial\nEquivalent\nNote 3"],["Motion\nFreeze","Yes\nIt is an intelligent function based\non deep learning to reduce the\nartifacts caused by head motion.","--","","","--","","","Substantial\nEquivalent\nNote 4"],["Ultra EFOV","Yes\nIt can extend reconstruction FOV to\nbore size using deep learning\ntechnique.","EFOV","","","EFOV","","","Substantial\nEquivalent\nNote 5"],["CardioCapt\nure","Yes\nIt is a motion correction function for\ncardiac scanning to reduce coronary\nmotion artifact, which is based on\ndeep learning technology.\nOnly uCT ATLAS Optimize this\nfunction","Yes\nBoth uCT\nATLAS and\nuCT ATLAS\nAstound have\nthis function","","","--","","","Substantial\nEquivalent\nNote 6"]],"caption_candidate":"predicate/reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p9-t1","doc_id":"K243617","page_num":9,"bbox":[90.28,607.75,553.07,713.98],"n_rows":3,"n_cols":2,"columns":["Justification",""],"rows":[["Justification",""],["Note ID","Justification"],["Note 1","Compared to the reference device (K230162), CardioBoost in subject devices is an\nimage reconstruction method for cardiac. The difference in the subject devices is datasets\naugmentation and deep learning network optimization in order to improve the overall\nperformance for cardiac images reconstruction\nFrom the user perspective, the workflow remains the same between the subject device\nand reference device."]],"caption_candidate":"function","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p10-t0","doc_id":"K243617","page_num":10,"bbox":[90.26,77.64,552.48,421.73],"n_rows":5,"n_cols":2,"columns":["Note 2","For uCT ATLAS:\nCompared to the predicate device (K231482), the differences in the subject device are\ndatasets augmentation and deep learning network optimization to enable reconstruction\nfor head.\nFor uCT ATLAS Astound:\nCompared to the predicate device (K231482), the difference in the subject device is deep\nlearning network optimization to improve the overall performance.\nFrom the user perspective, the workflow remains the same between the subject devices\nand predicate devices."],"rows":[["Note 2","For uCT ATLAS:\nCompared to the predicate device (K231482), the differences in the subject device are\ndatasets augmentation and deep learning network optimization to enable reconstruction\nfor head.\nFor uCT ATLAS Astound:\nCompared to the predicate device (K231482), the difference in the subject device is deep\nlearning network optimization to improve the overall performance.\nFrom the user perspective, the workflow remains the same between the subject devices\nand predicate devices."],["Note 3","Compared to the predicate devices (K231482), the difference in the subject device is the\nintroduction of a new deep learning based coronaries detection algorithm to improve the\nperformance of CardioXphase. The functionality to select the best phase flowchart\nalready exists in the predicate devices CardioXphase (K231482).\nFrom the user perspective, the workflow remains the same between the subject devices\nand reference devices"],["Note 4","The function of Motion Freeze is an image reconstruction algorithm which intend to\ncorrect the patient head motion, this will not raise new safety and effectiveness concerns."],["Note 5","Compared to the predicate devices (K231482), the difference in the subject devices is\nthat Ultra EFOV introduces a deep learning network to improve HU accuracy in the area\nof extended FOV.\nFrom the user perspective, the workflow remains the same between the subject devices\nand reference devices."],["Note 6","CardioCapture in this submission is only optimized for uCT ATLAS.\nCompared to the predicate device(K231482), the difference in the subject device is the\nintroduction of the deep learning module.\nFrom the user perspective, the workflow remains the same between the subject device\nand predicate device. ."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p11-t0","doc_id":"K243617","page_num":11,"bbox":[90.38,77.76,519.28,707.4],"n_rows":44,"n_cols":6,"columns":["","Software functions","","","Bench test",""],"rows":[["","Software functions","","","Bench test",""],["CardioBoost","CardioBoost","","","The bench test for CardioBoost was performed to evaluate the",""],["","","","","subject devices IQ with CardioBoost.",""],["","","","","",""],["","","","","IQ evaluation includes:",""],["","","","","·General IQ Performance testing of metrics identified in IEC",""],["","","","","61223-3-5 to study overall performance in a standardized and",""],["","","","","referenceable manner. General IQ tests include CT HU number",""],["","","","","test and thickness section test.",""],["","","","","·A low contrast detectability (LCD) test was performed under",""],["","","","","the guidance of CTIQ White Paper to evaluate the LCD",""],["","","","","enhancement, dose reduction and noise reduction.",""],["","","","","·A high contrast spatial resolution test was performed under",""],["","","","","the guidance of AAPM's report .",""],["","","","","",""],["","","","","The test result shows that:",""],["","","","","·CardioBoost passed the basic general IQ test which satisfied",""],["","","","","the requirement of IEC 61223-3-5.",""],["","","","","·CardioBoost showed better LCD comparing with FBP at",""],["","","","","same scanning dose and can reduce scanning dose comparing",""],["","","","","with FBP at same LCD.",""],["","","","","·CardioBoost showed better noise comparing with FBP.",""],["","","","","·CardioBoost showed better spatial resolution comparing with",""],["","","","","FBP at same scanning dose.",""],["AIIR","","","","The bench test for AIIR was performed to evaluate the subject",""],["","","","","devices IQ with AIIR.",""],["","","","","",""],["","","","","IQ evaluation includes:",""],["","","","","·General IQ Performance testing of metrics identified in IEC",""],["","","","","61223-3-5 to study overall performance in a standardized and",""],["","","","","referenceable manner. General IQ tests include CT HU number",""],["","","","","test and thickness section test.",""],["","","","","·A low contrast detectability (LCD) test was performed under",""],["","","","","the guidance of CTIQ White Paper to evaluate the LCD",""],["","","","","enhancement, dose reduction and noise reduction.",""],["","","","","·A high contrast spatial resolution test was performed under",""],["","","","","the guidance of AAPM's report.",""],["","","","","",""],["","","","","The test results show that:",""],["","","","","·AIIR passed the basic general IQ test which satisfied the",""],["","","","","requirement of IEC 61223-3-5.",""],["","","","","·AIIR showed better LCD comparing with FBP at same",""],["","","","","scanning dose and can reduce scanning dose comparing with",""],["","","","","FBP at same LCD.",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p12-t0","doc_id":"K243617","page_num":12,"bbox":[90.33,77.78,519.36,428.07],"n_rows":25,"n_cols":4,"columns":["","","·AIIR showed better noise comparing with FBP.",""],"rows":[["","","·AIIR showed better noise comparing with FBP.",""],["","","·AIIR showed better spatial resolution comparing with FBP at",""],["","","same scanning dose.",""],["CardioXphase","","The bench test for CardioXphase was performed to evaluate the",""],["","","extraction accuracy of new AI module in heart and coronary",""],["","","artery structure. Other modules are same as the function cleared",""],["","","in K231482.",""],["","","The quantitative assessment metrics for the heart mask and",""],["","","coronary artery mask extracted by the new AI module and the",""],["","","annotated results are calculated: Dice Similarity Coefficient",""],["","","(DICE), Precision, and Recall.",""],["","","The test results show that all indicators have met the",""],["","","verification criteria and have passed the verification.",""],["Motion Freeze","","The bench test for Motion Freeze was performed to evaluate the",""],["","","effectiveness on reducing head motion artifacts, by comparing",""],["","","the artifacts on images with- and without- Motion Freeze,",""],["","","The test results show that Motion Freeze can reduce head",""],["","","motion artifacts.",""],["Ultra EFOV","","The bench test for Ultra EFOV was performed to evaluate the",""],["","","effectiveness on improving CT value accuracy, by comparing",""],["","","the CT value of images with EFOV and the CT value of",""],["","","images with Ultra EFOV.",""],["","","The test results show that Ultra EFOV can improve the CT",""],["","","number, in cases where the scanned object exceeds the CT field",""],["","","of scan-FOV.",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p12-t1","doc_id":"K243617","page_num":12,"bbox":[90.33,442.51,519.36,692.38],"n_rows":3,"n_cols":2,"columns":["Software functions","Reader study"],"rows":[["Software functions","Reader study"],["CardioBoost","The clinical images reconstructed with CardioBoost and KARL\n3D respectively were shown to the readers to perform a five-\npoint scale evaluation of both image sets on the several image\nquality aspects, including noise level, structure fidelity, image\nquality and clinical features.\nThe results confirmed that CardioBoost images are sufficient\nfor diagnosis and the image quality of CardioBoost is equal or\nbetter than the image quality of KARL 3D over all of the\nevaluation aspects."],["AIIR","The clinical images reconstructed with AIIR and FBP\nrespectively were shown to the readers to perform a five-point\nscale evaluation of both image sets on the several image quality\naspects, including noise level, streaking artifact reduction and\nimage structure fidelity.\nThe results confirmed that AIIR images are sufficient for\ndiagnose and the image quality of AIIR is equal or better than\nthe image quality of FBP over all of the evaluation aspects."]],"caption_candidate":"of scan-FOV.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243617-p13-t0","doc_id":"K243617","page_num":13,"bbox":[90.26,77.64,519.46,415.73],"n_rows":3,"n_cols":2,"columns":["Motion Freeze","The clinical images reconstructed with Motion Freeze were\nshown to the readers to perform a 5-point scale evaluation of\nboth image sets on the image quality aspects, including artifact\ncorrection effect and clinical diagnostic benefit of the images.\nThe results confirmed that Motion Freeze is helpful for both\nartifact suppression and clinical diagnosis."],"rows":[["Motion Freeze","The clinical images reconstructed with Motion Freeze were\nshown to the readers to perform a 5-point scale evaluation of\nboth image sets on the image quality aspects, including artifact\ncorrection effect and clinical diagnostic benefit of the images.\nThe results confirmed that Motion Freeze is helpful for both\nartifact suppression and clinical diagnosis."],["Ultra EFOV","The clinical images with Ultra EFOV and EFOV respectively\nwere shown to the readers to perform a 5-point scale evaluation\nof both image sets on the image quality aspects, including\nimage artifacts and homogeneity of same tissue.\nThe results confirm that the images with Ultra EFOV can\nimprove the accuracy of image CT numbers, in cases where the\nscanned object exceeds the CT field of view."],["CardioCapture","AI motion correction is a new module integrated as a part of\nCardioCapture in uCT ATLAS. Other modules are same as the\nfunction cleared in K231482.\nThe reader evaluation is based on the CardioCapture function\nwith AIMC enabled. The evaluation aspects include:\n·Contours are clear and continuous\n·Motion artifacts of coronary arteries are tolerable\n·Number of diagnostic coronaries reaches at least 50% of the\ntotal number of coronary artery segments\nThe results conclude the effectiveness of CardioCapture\nfunction for reducing cardiac motion artifacts as expected."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p5-t0","doc_id":"K243633","page_num":5,"bbox":[69.24,157.08,522.84,503.64],"n_rows":14,"n_cols":3,"columns":["General Information","",""],"rows":[["General Information","",""],["Manufacturer","Brainlab AG; Olof-Palme Str.9; 81829, Munich, Germany",""],["Establishment Registration","8043933",""],["Trade Name","Brainlab Elements (7.0);\nBrainlab Elements Image Fusion (5.0);\nBrainlab Elements Image Fusion Angio (1.0);\nBrainlab Elements Contouring (5.0);\nBrainlab Elements Fibertracking (3.0);\nBrainlab Elements BOLD MRI Mapping (1.0)",""],["Classification Name","Automated Radiological Image Processing Software",""],["Product Code","QIH; JAK; LLZ",""],["Regulation Number","892.2050",""],["Regulatory Class","II",""],["Panel","Radiology",""],["Predicate Device","K223106; Brainlab Elements 6.0",""],["Reference Device","K212397; StealthStation S8 Cranial v2.0",""],["Contact Information","",""],["Primary Contact","","Alternate Contact"],["Sadwini Suresh\nQM Consultant\nPhone: +49 89 99 15 68 0\nEmail: regulatory.affairs@brainlab.com","","Chiara Cunico\nSenior Manager Regulatory Affairs\nPhone: +49 89 99 15 68 0\nEmail: chiara.cunico@brainlab.com"]],"caption_candidate":"June 11, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p7-t0","doc_id":"K243633","page_num":7,"bbox":[72.27,345.0,560.97,554.28],"n_rows":5,"n_cols":4,"columns":["","Predicate","","Name"],"rows":[["","Predicate","","Name"],["","Number","",""],["Subject\nDevice","","","Brainlab Elements, Brainlab Elements Contouring (5.0), Brainlab Elements Fibertracking (3.0), Brainlab\nElements Image Fusion (5.0), Brainlab Elements Image Fusion Angio (1.0), Brainlab Elements BOLD\nMRI Mapping (1.0)"],["Predicate\ndevice\n(K223106)","","","Brainlab Elements, Brainlab Elements Contouring (4.5), Brainlab Elements Fibertracking (2.0), Brainlab\nElements Image Fusion (4.5), Brainlab Elements Image Fusion Angio (1.0), Brainlab Elements BOLD\nMRI Mapping (1.0)"],["Reference\ndevice\n(K212397)","","","StealthStation S8 Cranial v2.0"]],"caption_candidate":"3. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p7-t1","doc_id":"K243633","page_num":7,"bbox":[72.27,607.08,560.97,690.36],"n_rows":3,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Fusion 4.5 (K223106))","","","Fusion 5.0)",""],["Indications for\nuse","","","Brainlab Elements Image Fusion is an\napplication for the co-registration of image\ndata within medical procedures by using rigid\nand deformable registration methods. It is","","","Brainlab Elements Image Fusion is an application\nfor the co-registration of image data within\nmedical procedures by using rigid and deformable\nregistration methods. It is intended to align","",""]],"caption_candidate":"Image Fusion 5.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p8-t0","doc_id":"K243633","page_num":8,"bbox":[72.26,73.38,560.98,701.76],"n_rows":7,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Fusion 4.5 (K223106))","","","Fusion 5.0)",""],["","","","intended to align anatomical structures\nbetween data sets.\nThe device itself does not have clinical\nindications.","","","anatomical structures between data sets. It is not\nintended for diagnostic purposes.\nBrainlab Elements Image Fusion is indicated for\nplanning of cranial and extracranial surgical\ntreatments and preplanning of cranial and\nextracranial radiotherapy treatments.","",""],["Operator profile","","","The intended users are medical professionals.\nTypical users are:\n- Image Guided Surgery (IGS):\nNeurosurgeons, Ear-Nose-Throat (ENT)\nsurgeons and Cranio-Maxillofacial (CMF)\nsurgeons including their assistants\nRadiotherapy (RT): medical professionals who\nperform radiation treatment planning (medical\nphysicists, radiation oncologists, dosimetrists,\nphysicians, etc.)","","","The intended users are medical professionals.\nTypical users are:\n- Image Guided Surgery (IGS): Surgeons\ntrained in the areas of neurosurgery, spine\nand trauma surgery, ear-nose-throat (ENT)\nsurgery and craniomaxillofacial (CMF) surgery\nincluding their assistants.\nRadiotherapy (RT): medical professionals who\nperform radiation treatment planning (medical\nphysicists, radiation oncologists, dosimetrists,\nphysicians, etc.).","",""],["Patient\npopulation","","","In general, there are no demographic, regional\nor cultural limitations for patients. It is up to the\nuser to decide if the system shall be used to\nassist a certain procedure.","","","There are no demographic, regional or cultural\nlimitations for patients.","",""],["Conditions of\nuse","","","The system shall be used in a hospital office\nenvironment or rooms appropriate for surgical\ninterventions or radiotherapy planning.","","","The system shall be used in a hospital office\nenvironment or rooms appropriate for surgical\ninterventions or radiotherapy planning.","",""],["Computer\nhardware\nrequirements","","","Brainlab Elements can be used on hardware\nthat fulfills the defined minimum requirements:\n- Operating System: Windows 8.1 64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X compatible\n- Display Resolution: 1920 x 1080 (Full HD)","","","All platforms which fulfill the minimum\nrequirements:\nIGS Workstation:\n- Operating system: Windows 10\n- minimum 4 physical cores\n- RAM: 8 GB\n- Graphics: DirectX 12 compatible\n- Display resolution: 1920 x 1080 (Full HD)\nIGS Server / Virtual Machine\n- Operating System: Windows Server 2016\n- RAM 16GB\nRT Workstation:\n- Operating System: Windows 10\n- minimum 6 physical cores\n- RAM: 48GB\n- Graphics card: DirectX 12\n- Display resolution: 1920 x 1080 (Full HD)\nRT Server / Virtual Machine\n- Operating System: Windows Server 2016\n- minimum 12 physical cores","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p9-t0","doc_id":"K243633","page_num":9,"bbox":[72.25,73.38,560.99,690.6],"n_rows":11,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Fusion 4.5 (K223106))","","","Fusion 5.0)",""],["","","","","","","- RAM: 64GB (+16GB per additional user)","",""],["Operating\nsystem","","","- Windows Server 2012 R2 / 2016 / 2019\n- Windows 8.1\nWindows 10","","","- Windows Server 2016\n- Windows Server 2019\n- Windows Server 2022\n- Windows 10","",""],["Input Devices","","","Touch and mouse/keyboard control Touch and\nmouse/keyboard control","","","Touch and mouse/keyboard control Touch and\nmouse/keyboard control","",""],["Image Data Sets\nFormat","","","DICOM 3D imaging Modalities, e.g. CT/XT,\nMRI, NM/PET, OT, are supported for automatic\nfusion.\nOther modalities are supported for manual\nfusion (alignment)","","","DICOM 3D imaging Modalities, e.g. CT/XT, MRI,\nNM/PET, OT, are supported for automatic fusion.\nOther modalities are supported for manual fusion\n(alignment)","",""],["Rigid co-\nregistration,\nrigid image\nfusion","","","Automatic rigid co-registration (rigid fusion) of\n3D DICOM image data: CT (incl. low-dose CT),\nMR, OT (e.g. Perfusion), MR-DTI, MR-BOLD,\nNM/PET, US (ultrasound).\nManual rigid co-registration (rigid fusion) of\nother (unknown) 3D DICOM image data.","","","Automatic rigid co-registration (rigid fusion) of 3D\nDICOM image data: CT (incl. low-dose CT), MR,\nOT (e.g. Perfusion), MR-DWI, MR-BOLD, NM/PET,\nUS (ultrasound).\nManual rigid co-registration (rigid fusion) of other\n(unknown) 3D DICOM image data.","",""],["Application View\nLayout and\nViews","","","GUI Technology: HTML\nSingle view layout:\n- Axial view is displayed by default\n- The user is able to switch to coronal and\nsagittal views\n- A toolbar is available on the right side to\naccess the data selection, fusion tools and\nverification tools\n- In the header, the user is able to approve or\nreject the fusion result","","","GUI Technology: HTML\nSingle view layout:\n- Axial view is displayed by default\n- The user is able to switch to coronal and sagittal\nviews\n- A toolbar is available on the right side to access\nthe data selection, fusion tools and verification\ntools\n- In the header, the user is able to approve or\nreject the fusion result","",""],["Region of\nInterest","","","The co-registration can be restricted to a\nspecific region of interest of the datasets by\nmeans of a box.","","","The co-registration can be restricted to a specific\nregion of interest of the datasets by means of a\nbox and an ellipsoid.","",""],["Rigid co-\nregistration,\nrigid image\nfusion","","","Automatic rigid co-registration (rigid fusion) of\n3D DICOM image data: CT (incl. low-dose CT),\nMR, OT (e.g. Perfusion), MR-DTI, MR-BOLD,\nNM/PET, US (ultrasound).\nManual rigid co-registration (rigid fusion) of\nother (unknown) 3D DICOM image data.","","","Automatic rigid co-registration (rigid fusion) of 3D\nDICOM image data: CT (incl. low-dose CT), MR,\nOT (e.g. Perfusion), MR-DWI, MR-BOLD, NM/PET,\nUS (ultrasound).\nManual rigid co-registration (rigid fusion) of other\n(unknown) 3D DICOM image data.","",""],["Deformable\nRegistration /\nElastic Image\nFusion:\nDistortion","","","Distortion Correction for cranial image data:\nCT-MR, MR-MR (incl. DTI)","","","Distortion Correction for cranial image data: CT-\nMR, MR-MR (incl. DTI)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p10-t0","doc_id":"K243633","page_num":10,"bbox":[72.25,73.38,560.99,702.0],"n_rows":9,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Fusion 4.5 (K223106))","","","Fusion 5.0)",""],["Correction\nCranial","","","","","","","",""],["Deformable\nRegistration /\nElastic Image\nFusion:\nCurvature\nCorrection Spine","","","Curvature Correction for spinal image data:\nCT-CT, CT-MR (incl. low-dose CT scanner)","","","Curvature Correction for spinal image data: CT-\nCT, CT-MR (incl. low-dose CT scanner)","",""],["Deformable\nRegistration /\nElastic Image\nFusion: Virtual\niMRI Cranial","","","Calculation of a brain shift (“virtual iMRI”)\nsimulation, based on intra-operative CT or MR\nimage data, offering a simulation of pre-\noperative planning data within an intra-\noperative situation.\nThe intra-operative resection cavity is grayed\nout in the simulation result.\nWith the acceptance of a Virtual iMRI\nsimulation, the original variant of an image set\nand existing co-registrations are removed from\nthe current data selection","","","Calculation of a brain shift (“virtual iMRI”)\nsimulation, based on intra-operative CT, MR, or\nUS image data, offering a simulation of pre-\noperative planning data within an intra-operative\nsituation.\nThe intra-operative resection cavity is blacked out\nin the simulation result.\nAutomatic scrolling is activated as soon as a\nsimulation result is available.\nWith the acceptance of a Virtual iMRI simulation,\nthe original variant of an image set and existing\nco-registrations are kept in the current data\nselection","",""],["Verification\nTools: Spy\nGlass","","","A spy glass superimposes the first image set in\na frame over the second image set.","","","A spy glass superimposes the first image set in a\nframe over the second image set.","",""],["Verification\nTools: Blending","","","Blending allows to view structures in two\nimage sets at the same time by using\ncomplimentary colors to distinguish both image\nsets.","","","Blending allows to view structures in two image\nsets at the same time by using complimentary\ncolors to distinguish both image sets.","",""],["Verification\nTools: Spy\nGlass for\nDeformable Co-\nRegistrations","","","For deformable registrations the spy glass\nfeature is combined with a heatmap and a\ndeformation grid, highlighting areas where the\ndeformed image set has been (locally)\nmodified and giving a global impression about\nthe deformation","","","For deformable registrations the spy glass feature\nis combined with a heatmap and a deformation\ngrid, highlighting areas where the deformed image\nset has been (locally) modified and giving a global\nimpression about the deformation","",""],["Verification\nTools: Blending\nfor deformable\nco-registrations","","","For deformable registrations the blending\nfeature is combined with a deformation grid,\nwhich gives a global impression about the\ndeformation while its colored grid lines\nhighlight areas where the deformed image set\nhas been (locally) modified.","","","For deformable registrations the blending feature\nis combined with a deformation grid, which gives a\nglobal impression about the deformation while its\ncolored grid lines highlight areas where the\ndeformed image set has been (locally) modified.\nFor Virtual iMRI with Ultrasound, the weather\nradar, a specific type of blending with distinct\ncolors, has been implemented.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p11-t0","doc_id":"K243633","page_num":11,"bbox":[72.27,73.38,560.97,143.4],"n_rows":3,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Fusion 4.5 (K223106))","","","Fusion 5.0)",""],["Contrast\nClearance\nAnalysis","","","Calculation of treatment response assessment\nmaps for the analysis of contrast agent\nclearance.","","","Calculation of treatment response assessment\nmaps for the analysis of contrast agent clearance","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p11-t1","doc_id":"K243633","page_num":11,"bbox":[72.27,195.96,560.97,705.12],"n_rows":5,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Angio 1.0.2 (K223106))","","","Fusion Angio 1.0.2)",""],["Indications for\nuse","","","Brainlab Elements Image Fusion Angio is a\nsoftware application that is intended to be used\nfor the co-registration of cerebrovascular\nimage data.\nThe device itself does not have clinical\nindications.","","","Brainlab Elements Image Fusion Angio is a\nsoftware application that is intended to be used for\nthe co-registration of cerebrovascular image data.\nIt is not intended for diagnostic purposes. Brainlab\nElements Image Fusion Angio is indicated for\nplanning of cranial surgical treatments and\npreplanning of cranial radiotherapy treatments.","",""],["Operator profile","","","The intended users are medical professionals.\nTypical users are:\n- Image Guided Surgery (IGS):\nNeurosurgeons, Ear-Nose-Throat (ENT)\nsurgeons and Cranio-Maxillofacial (CMF)\nsurgeons including their assistants\nRadiotherapy (RT): medical professionals who\nperform radiation treatment planning (medical\nphysicists, radiation oncologists, dosimetrists,\nphysicians, etc.)","","","The intended users are medical professionals.\nTypical users are:\n- Image Guided Surgery (IGS): Surgeons\ntrained in the areas of neurosurgery including\ntheir assistants.\nRadiotherapy (RT): medical professionals who\nperform radiation treatment planning (medical\nphysicists, radiation oncologists, dosimetrists,\nphysicians, etc.).","",""],["Computer\nhardware\nrequirements","","","Brainlab Elements can be used on hardware\nthat fulfills the defined minimum requirements:\n- Operating System: Windows 8.1 64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X compatible\nDisplay Resolution: 1920 x 1080 (Full HD)","","","All platforms which fulfill the minimum\nrequirements:\nIGS Workstation:\n- Operating system: Windows 10\n- minimum 4 physical cores\n- RAM: 8 GB\n- Graphics: DirectX 12 compatible\n- Display resolution: 1920 x 1080 (Full HD)\nIGS Server / Virtual Machine\n- Operating System: Windows Server 2016\n- RAM 16GB\nRT Workstation:\n- Operating System: Windows 10\n- minimum 6 physical cores","",""]],"caption_candidate":"Image Fusion Angio 1.0.2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p12-t0","doc_id":"K243633","page_num":12,"bbox":[72.27,73.38,560.95,209.52],"n_rows":3,"n_cols":9,"columns":["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],"rows":[["","Topic/","","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements Image",""],["","Feature","","","Elements Image Angio 1.0.2 (K223106))","","","Fusion Angio 1.0.2)",""],["","","","","","","- RAM: 48GB\n- Graphics card: DirectX 12\n- Display resolution: 1920 x 1080 (Full HD)\nRT Server / Virtual Machine\n- Operating System: Windows Server 2016\n- minimum 12 physical cores\n- RAM: 64GB (+16GB per additional user)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p12-t1","doc_id":"K243633","page_num":12,"bbox":[72.27,288.11,539.74,688.2],"n_rows":6,"n_cols":6,"columns":["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],["","","","","Contouring 5.0)",""],["Indications for use","Brainlab Elements Contouring provides\nan interface with tools and views to\noutline, refine, combine and manipulate\nstructures in patient image data. The\ngenerated 3D structures are not intended\nto create physical replicas used for\ndiagnostic purposes.\nThe device itself does not have clinical\nindications","","Brainlab Elements Contouring provides an\ninterface with tools and views to outline, refine,\ncombine and manipulate structures in patient\nimage data. It is not intended for diagnostic\npurposes.Brainlab Elements Contouring is\nindicated for planning of cranial and\nextracranial surgical treatments and\npreplanning of cranial and extracranial\nradiotherapy treatments.","",""],["Patient population","In general, there are no demographic,\nregional or cultural limitations for\npatients. It is up to the user to decide if\nthe system shall be used to assist a\ncertain procedure.","","There are no demographic, regional or cultural\nlimitations for patients.","",""],["Conditions of use","The system shall be used in a hospital\noffice environment or rooms appropriate\nfor surgical interventions or radiotherapy\nplanning.","","The system shall be used in a hospital office\nenvironment or rooms appropriate for surgical\ninterventions or radiotherapy planning.","",""],["Operator profile","The intended users are medical\nprofessionals. Typical users are:\n- Image Guided Surgery (IGS):\nNeurosurgeons, Ear-Nose-Throat\n(ENT) surgeons and Cranio-\nMaxillofacial (CMF) surgeons\nincluding their assistants\nRadiotherapy (RT): medical professionals\nwho perform radiation treatment planning","","The intended users are medical professionals.\nTypical users are:\n- Image Guided Surgery (IGS): Surgeons\ntrained in the areas of neurosurgery, spine\nand trauma surgery, ear-nose-throat\n(ENT) surgery and craniomaxillofacial\n(CMF) surgery including their assistants.\nRadiotherapy (RT): medical professionals who\nperform radiation treatment planning (medical","",""]],"caption_candidate":"Contouring 5.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p13-t0","doc_id":"K243633","page_num":13,"bbox":[72.26,73.36,539.74,698.04],"n_rows":7,"n_cols":6,"columns":["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],["","","","","Contouring 5.0)",""],["","(medical physicists, radiation oncologists,\ndosimetrists, physicians, etc.)","","physicists, radiation oncologists, dosimetrists,\nphysicians, etc.).","",""],["Computer hardware\nrequirements","Brainlab Elements can be used on\nhardware that fulfills the defined\nminimum requirements:\n- Operating System: Windows 8.1 64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X compatible\n- Display Resolution: 1920 x 1080 (Full\nHD)","","IGS Workstation:\n- Operating system: Windows 10\n- minimum 4 physical cores\n- RAM: 8 GB\n- Graphics: DirectX 12 compatible\n- Display resolution: 1920 x 1080 (Full HD) IGS\nServer / Virtual Machine:\n- Operating System: Windows Server 2016\n- RAM 16GB\nRT Workstation:\n- Operating System: Windows 10\n- minimum 6 physical cores\n- RAM: 48GB\n- Graphics card: DirectX 12\n- Display resolution: 1920 x 1080 (Full HD) RT\nServer / Virtual Machine:\n- Operating System: Windows Server 2016\n- minimum 12 physical cores\n- RAM: 64GB (+16GB per additional user)\nIf Anatomical Patient Model 1.1 (APM 1.1) shall\nbe used, the following minimum requirements\nhave to\nbe fulfilled:\n- CPU: 12 (virtual) cores\n- RAM: 24 GB\nIf the Cranial Tumor Segmentation feature of\nContouring shall be supported, the following\nGPU\nrequirements have to be fulfilled:\n- GPU vRAM: 8GB\n- GPU driver: ≥ 472.5* (*cuda 11.8 tool kit\ncompatibility)\n- CUDA compute capability: > 5.2","",""],["Operating system","- Windows Server 2012 R2 / 2016 / 2019\n- Windows 8.1\n- Windows 10","","- Windows Server 2016\n- Windows Server 2019\n- Windows Server 2022\n- Windows 10","",""],["Input Devices","Touch and mouse/keyboard control","","Touch and mouse/keyboard control","",""],["Automatic\nSegmentation:\nCranial Tumors","Not available","","Cranial tumors are auto-segmented as 3D\nobjects in image sets with supported modality","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p14-t0","doc_id":"K243633","page_num":14,"bbox":[72.25,73.36,539.75,685.8],"n_rows":9,"n_cols":6,"columns":["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],["","","","","Contouring 5.0)",""],["","","","(MR-t1 contrast enhanced) by means of a\nmachine learning algorithm.\nSimilar to other anatomical structures the user\ncan review, adjust or reject the tumor object.","",""],["Automatic\nSegmentation:\nAnatomical objects","The application automatically creates\nsegmentation objects by using an atlas-\nbased automatic segmentation of the\nbrain.\nWorkflow-relevant segmentation objects\nare\ncreated automatically or, if required by a\nworkflow, on a single button click.","","The application automatically creates\nsegmentation objects by using an atlas-based\nautomatic segmentation of the\nbrain.\nWorkflow-relevant segmentation objects are\ncreated automatically or, if required by a\nworkflow, on a single button click.\nIn addition auto-segmented objects can\noptionally also be retrieved via the Anatomical\nPatient Model 1.1 by means of a setting.","",""],["Landmark Support","The application can display annotations.\nAnnotations cannot be changed or\nremoved.","","The application can be used to display, define\nand edit annotations and registration markers.","",""],["Visualization:\nBlending Mode","Not available","","The application can be used to display two\nfused images within one view. A slider is\navailable to blend from one image to another.","",""],["Abnormity Detection","If an anomaly is detected, the application\nautomatically focuses the views on this\nanomaly.\nAnomaly detection is either the result of\nthe\natlas-based automatic segmentation of\nthe\nbrain or, on platforms with appropriate\nGPUs, the result of a machine learning\nalgorithm. The GPU requirements are\nlisted\nin the UniversalAtlasPerformer Test Plan\nML Abnormity Detection.","","If an anomaly is detected, the application\nautomatically focuses the views on this\nanomaly.\nAnomaly detection is either the result of the\natlas-based automatic segmentation of the\nbrain or, on platforms with appropriate\nGPUs, the result of a machine learning\nalgorithm. The GPU requirements are listed\nin the UniversalAtlasPerformer Test Plan\nML Abnormity Detection.","",""],["Automatic\nSegmentation:\nAnatomical objects\n– Segmentation\nTemplates","The application also offers the possibility\nto\ndefine customized segmentation\ntemplates.","","The application also offers the possibility to\ndefine customized segmentation templates.","",""],["Automatic\nSegmentation –\nResection Cavity","Not available","","A resection cavity object can be segmented\nautomatically based on ultrasound image data.\nSimilar to other anatomical or tumor objects,\nthe user can review, adjust or reject the\nresection cavity object.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p15-t0","doc_id":"K243633","page_num":15,"bbox":[72.25,73.36,539.75,699.12],"n_rows":9,"n_cols":6,"columns":["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],["","","","","Contouring 5.0)",""],["Manual Creation\nand Refinement of\nObjects","The application provides tools for manual\ncreation and refinement of segmentation\nobjects:\n- SmartShaper\n- Brush 3D / Erase 3D\n- Brush 2D / Erase 2D\n- Smart Brush","","The application provides tools for manual\ncreation and refinement of segmentation\nobjects:\n- SmartShaper\n- Brush 3D / Erase 3D\n- Brush 2D / Erase 2D\n- Smart Brush","",""],["Multi-Modal\nDrawing","SmartBrush can be used for multi-modal\ndrawing, i.e. two images are used for\ndrawing in a multi-modal view layout.","","SmartBrush can be used for multi-modal\ndrawing, i.e. two images are used for drawing\nin the newly introduced blending view when\nBlending Mode is active.","",""],["Manual Creation of\nObjects: Threshold\nSegmentation","The application provides a Threshold\nSegmentation tool to create objects.\nThreshold Segmentation supports MR,\nCT, PET, US and Contrast Clearance\nAnalysis (CCA) data.\nThe size of a geometric ROI during\nThreshold Segmentation can be adjusted.","","The application provides a Threshold\nSegmentation tool to create objects.\nThreshold Segmentation supports MR, CT,\nPET, US, Contrast Clearance Analysis (CCA)\nand RGB data.\nThe size of a geometric ROI during Threshold\nSegmentation can be adjusted and it can be\nrotated.","",""],["Object Manipulation","The application provides tools for the\nmanipulation of objects:\n- Copy\n- Margins\n- Smoothing\n- Mirroring\n- Shifting and Rotation\n- Splitting\n- Automatic Object Fitting","","The application provides tools for the\nmanipulation of objects:\n- Copy\n- Margins\n- Smoothing\n- Mirroring\n- Shifting and Rotation\n- Splitting\n- Automatic Object Fitting","",""],["Logical Operations","The application provides tools for logical\noperations on objects:\n- Union\n- Subtract\n- Intersect","","The application provides tools for logical\noperations on objects:\n- Union\n- Subtract\n- Intersect","",""],["Object Review","The application provides functionality to\ncontrol the review state of objects. In\ncase\nof leaving the application with\nunreviewed\nsemi-automatically or automatically\ncreated\nobjects, a message is displayed.","","The application provides functionality to\ncontrol the review state of objects. In case\nof leaving the application with unreviewed\nsemi-automatically or automatically created\nobjects, a message is displayed.","",""],["Volumetric Report","It is possible to create a printable report\nfor\nan object in a platform independent file","","It is possible to create a printable report for\nan object in a platform independent file\nformat, giving information about the object's\nvolume, its diameter according to the","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p16-t0","doc_id":"K243633","page_num":16,"bbox":[72.27,73.36,539.73,525.12],"n_rows":5,"n_cols":6,"columns":["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","Primary Predicate Device (Brainlab\nElements Contouring 4.5 (K223106))","","","Subject Device (Brainlab Elements",""],["","","","","Contouring 5.0)",""],["","format, giving information about the\nobject's\nvolume, its diameter according to the\nMacdonald criteria and its response\nevaluation criteria (RECIST).\nIf multiple objects are selected and a\nvolumetric report is created, it contains\ninformation about all objects.","","Macdonald criteria and its response\nevaluation criteria (RECIST).\nIf multiple objects are selected and a\nvolumetric report is created, it contains\ninformation about all objects.","",""],["Drawing Tools for\nthe Spine SRS Use\nCase","The application calculates a clinical\ntarget\nvolume (CTV) and a cropped organ at risk\n(OAR) object based on a manually\noutlined\nGross Tumor (GTV).\nCTV and OAR objects can be created\nupon\nbutton click, based on a guideline\npublished\nby Cox et al. (2012) when adding a GTV\noutline.\nIn a user session, multiple combinations\nof\nGTV, CTV and OAR can be created.","","The application calculates a clinical target\nvolume (CTV) and a cropped organ at risk\n(OAR) object based on a manually outlined\nGross Tumor (GTV).\nCTV and OAR objects can be created upon\nbutton click, based on a guideline published\nby Cox et al. (2012) when adding a GTV\noutline.\nIn a user session, multiple combinations of\nGTV, CTV and OAR can be created.","",""],["Drawing Tools for\nthe Angio Use Case","The application offers outlining features\nfor\ncerebrovascular diseases. These features\nshall be supported by utilization of\nangiographic image data (i. e. 2D DSA)\nand\nprojective fusions written by Image\nFusion\nAngio.","","The application offers outlining features for\ncerebrovascular diseases. These features\nshall be supported by utilization of\nangiographic image data (i. e. 2D DSA) and\nprojective fusions written by Image Fusion\nAngio.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p16-t1","doc_id":"K243633","page_num":16,"bbox":[72.27,577.67,539.73,698.4],"n_rows":3,"n_cols":7,"columns":["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],["","","Elements Fibertracking 2.0 (K223106))","","","Fibertracking 3.0)",""],["Indications for use","Brainlab Elements Fibertracking is an\napplication for the processing and\nvisualization of cranial white matter tracts\nbased on Diffusion Tensor Imaging (DTI)\ndata for use in treatment planning\nprocedures.","","","Brainlab Elements Fibertracking is an\napplication for the processing and\nvisualization of cranial white matter tracts\nbased on diffusion weighted imaging\n(DWI) data for use in treatment planning\nprocedures. It is not intended for diagnostic\npurposes. Brainlab Elements Fibertracking","",""]],"caption_candidate":"Fibertracking 3.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p17-t0","doc_id":"K243633","page_num":17,"bbox":[72.26,73.36,539.74,698.52],"n_rows":8,"n_cols":7,"columns":["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],["","","Elements Fibertracking 2.0 (K223106))","","","Fibertracking 3.0)",""],["","The device itself does not have clinical\nindications.","","","is indicated for planning of cranial surgical\ntreatments and preplanning of cranial\nradiotherapy treatments.","",""],["Operator profile","The intended users are medical\nprofessionals. Typical users are:\n- Image Guided Surgery (IGS):\nNeurosurgeons, Ear-Nose-Throat\n(ENT) surgeons and Cranio-\nMaxillofacial (CMF) surgeons including\ntheir assistants\nRadiotherapy (RT): medical professionals\nwho perform radiation treatment planning\n(medical physicists, radiation oncologists,\ndosimetrists, physicians, etc.)","","","The intended users are medical\nprofessionals. Typical users are:\n- Image Guided Surgery (IGS): Surgeons\ntrained in the areas of neurosurgery\nincluding their assistants.\nRadiotherapy (RT): medical professionals\nwho perform radiation treatment planning\n(medical physicists, radiation oncologists,\ndosimetrists, physicians, etc.).","",""],["Patient population","In general, there are no demographic,\nregional or cultural limitations for patients.\nIt is up to the user to decide if the system\nshall be used to assist a certain procedure.","","","There are no demographic, regional or\ncultural limitations for patients.","",""],["Conditions of use","The system shall be used in a hospital\noffice environment or rooms appropriate\nfor surgical interventions or radiotherapy\nplanning.","","","The system shall be used in a hospital\noffice environment or rooms appropriate\nfor surgical interventions or radiotherapy\nplanning.","",""],["Computer hardware\nrequirements","Brainlab Elements can be used on\nhardware that fulfills the defined minimum\nrequirements:\n- Operating System: Windows 8.1 64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X compatible\n- Display Resolution: 1920 x 1080 (Full HD)","","","IGS Workstation:\n- Operating system: Windows 10\n- minimum 4 physical cores\n- RAM: 8 GB\n- Graphics: DirectX 12 compatible\n- Display resolution: 1920 x 1080 (Full HD)\nIGS Server / Virtual Machine:\n- Operating System: Windows Server 2016\n- RAM 16GB\nRT Workstation:\n- Operating System: Windows 10\n- minimum 6 physical cores\n- RAM: 48GB\n- Graphics card: DirectX 12\n- Display resolution: 1920 x 1080 (Full HD)\nRT Server / Virtual Machine:\n- Operating System: Windows Server 2016\n- minimum 12 physical cores\n- RAM: 64GB (+16GB per additional user)","",""],["Operating system","- Windows Server 2012 R2 / 2016 / 2019\n- Windows 8.1\n- Windows 10","","","- Windows Server 2016\n- Windows Server 2019\n- Windows Server 2022\n- Windows 10","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p18-t0","doc_id":"K243633","page_num":18,"bbox":[72.26,73.36,539.74,698.04],"n_rows":7,"n_cols":7,"columns":["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],["","","Elements Fibertracking 2.0 (K223106))","","","Fibertracking 3.0)",""],["","","","","","",""],["Preprocessing","Automatic DTI Preprocessing (by using\ncomponent DTI Preprocessing Performer\n2.0):\n Eddy Current Correction,\n Motion Correction,\n B-Vector Realignment,\n Denoising,\n Regularization","","","Automatic DWI Preprocessing (by using\ncomponent DWI Performer 3.0):\n Eddy Current Correction,\n Motion Correction,\n B-Vector Realignment,\n Denoising,\n Regularization\n Creation of ODF field for HARDI data","",""],["Define seed regions\nof interest","Application offers the following possibilities\nto define seed ROIs for Fibertracking (ROI\nbased Fibertracking):\n Manual 3D Object (as include or exclude\nROI)\n Existing 3D Object(s), e.g. by using ROI\ntemplates\n “Interactive Tracking” to use a dynamic\nROI to generate fiber bundles on the fly","","","Application offers the following possibilities\nto define seed ROIs for Fibertracking (ROI\nbased Fibertracking):\n Manual 3D Object (as include or exclude\nROI)\n Existing 3D Object(s), e.g. by using ROI\ntemplates\n “Interactive Tracking” to use a dynamic\nROI to generate fiber bundles on the fly","",""],["Algorithm\nconfiguration","Application offers three sliders to influence\nthe algorithm’s stopping criteria:\n Minimum FA Threshold (default: 0.2)\n Minimum Length (default: 80 mm)\n Maximum Angulation (default: 20°)\nSee also topic “Toolarea”.","","","Application offers sliders to influence the\nalgorithm’s stopping criteria:\nDeterministic tracking using DTI:\n Refinement (remove outliers, default:\n10%)\n Minimum FA Threshold (default: 0.2)\n Maximum Angulation (default: 20°)\nProbabilistic tracking using CSD:\n Refinement (remove outliers, default:\n10%)\n Amplitude (default: 0.1)\n Maximum Angulation (default: 20°)","",""],["Fibertracking\nalgorithm","• Deterministic Tracking Algorithm\nbased on Combined Single/Dual\nTensor Tracking\nCreate 3D Objects from Fiber bundles","","","• Deterministic Tracking Algorithm\nbased on Combined Single/Dual\nTensor Tracking\n• Probabilistic tracking algorithm\n• Constrained Spherical Deconvolution\ntracking\nCreate 3D Objects from Fiber bundles\nReference Device K212397\nStealthStation S8 Cranial v2.0:\nStealthStation S8 Cranial v2.0 offers a","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p19-t0","doc_id":"K243633","page_num":19,"bbox":[72.27,73.36,539.73,449.64],"n_rows":4,"n_cols":7,"columns":["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],"rows":[["Topic/ Feature","","Primary Predicate Device (Brainlab","","","Subject Device (Brainlab Elements",""],["","","Elements Fibertracking 2.0 (K223106))","","","Fibertracking 3.0)",""],["","","","","similar algorithm like the new probabilistic\nCSD tracking algorithm introduced with\nFibertracking 3.0.","",""],["User Interface: Tool\nArea, description"," Fiber bundles are accessible via toggle\ncontrol and manageable via In-App\nDataSelection.\n ROIs are accessible in sidebar for\ndrag&drop to fiber bundle.\n ROI-Brush accessible via toolarea.\n Other ROIs directly accessible via\nSidebar.\n Parameter sliders area accessible in\ntoolarea.\n “Refresh” accessible via toolarea.\n “Erase” accessible via toolarea\n “Objects Exclude” via Sidebar","",""," Fiber bundles are accessible and\nmanageable in sidebar control\n ROIs are accessible in sidebar for\ndrag&drop to fiber bundle and selectable\nfor editing.\n ROI-Brush accessible via toolarea.\n Other ROIs directly accessible via\nSidebar.\n Parameter sliders area accessible in\ntoolarea.\n “Refresh” accessible via sidebar.\n “Erase” accessible via toolarea.\n “Objects Exclude” via Sidebar\n Algorithm (DTI or CSD) can be selected\nin toolarea\n Measurement of coordinates and FA\nvalues available via toolarea","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p19-t1","doc_id":"K243633","page_num":19,"bbox":[72.27,502.18,539.73,702.84],"n_rows":5,"n_cols":5,"columns":["Topic/ Feature","","Primary Predicate Device","","Subject Device (Brainlab Elements\nBOLD MRI Mapping 1.0)"],"rows":[["Topic/ Feature","","Primary Predicate Device","","Subject Device (Brainlab Elements\nBOLD MRI Mapping 1.0)"],["","","(Brainlab Elements BOLD MRI","",""],["","","Mapping (K223106))","",""],["Indications for use","Brainlab Elements BOLD MRI\nMapping provides tools to analyze\nblood oxygen level dependent data\n(BOLD MRI Data) to visualize the\nactivation signal and correlation\nbetween brain areas.\nThe device itself does not have\nclinical indications","","","Brainlab Elements BOLD MRI\nMapping provides tools to analyze\nblood oxygen level dependent data\n(BOLD MRI Data) to visualize the\nactivation signal. It is not intended\nfor diagnostic purposes.\nBrainlab Elements BOLD MRI\nMapping is indicated for planning of\ncranial surgical treatments."],["Operator profile","The intended users are medical\nprofessionals. Typical users are:","","","The intended users are medical\nprofessionals. Typical users are:"]],"caption_candidate":"BOLD MRI Mapping 1.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p20-t0","doc_id":"K243633","page_num":20,"bbox":[72.27,73.34,539.73,472.2],"n_rows":6,"n_cols":5,"columns":["Topic/ Feature","","Primary Predicate Device","","Subject Device (Brainlab Elements\nBOLD MRI Mapping 1.0)"],"rows":[["Topic/ Feature","","Primary Predicate Device","","Subject Device (Brainlab Elements\nBOLD MRI Mapping 1.0)"],["","","(Brainlab Elements BOLD MRI","",""],["","","Mapping (K223106))","",""],["","- Image Guided Surgery (IGS):\nNeurosurgeons, Ear-Nose-\nThroat (ENT) surgeons and\nCranioMaxillofacial (CMF)\nsurgeons including their\nassistants\nRadiotherapy (RT): medical\nprofessionals who perform radiation\ntreatment planning (medical\nphysicists, radiation oncologists,\ndosimetrists, physicians, etc.)","","","Image Guided Surgery (IGS):\nSurgeons trained in the area of\nneurosurgery including their\nassistants"],["Computer hardware requirements","Brainlab Elements can be used on\nhardware that fulfills the defined\nminimum requirements:\n- Operating System: Windows 8.1\n64bit\n- Minimum 4 logical cores\n- Minimum RAM: 6 GB\n- Graphics: Direct X compatible\nDisplay Resolution: 1920 x 1080\n(Full HD)","","","IGS Workstation:\n- Operating system: Windows 10\n- minimum 4 physical cores\n- RAM: 8 GB\n- Graphics: DirectX 12 compatible\n- Display resolution: 1920 x 1080\n(Full HD)\nIGS Server / Virtual Machine:\n- Operating System: Windows\nServer 2016\n- RAM 16GB"],["Operating system","- Windows Server 2012 R2 /\n2016 / 2019\n- Windows 8.1\nWindows 10","","","- Windows Server 2016\n- Windows Server 2019\n- Windows Server 2022\nWindows 10"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p22-t0","doc_id":"K243633","page_num":22,"bbox":[131.07,635.76,480.93,700.44],"n_rows":4,"n_cols":12,"columns":["","Diagnostic","","","Mean","","","Mean","","","Mean",""],"rows":[["","Diagnostic","","","Mean","","","Mean","","","Mean",""],["","Characteristics","","","Dice","","","Precision","","","Recall",""],["All","","","0.75","","","0.86","","","0.85","",""],["Metastases to the CNS","","","0.74","","","0.85","","","0.84","",""]],"caption_candidate":"Table 1 Summary of test statistics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243633-p23-t0","doc_id":"K243633","page_num":23,"bbox":[131.04,73.2,480.96,125.52],"n_rows":3,"n_cols":4,"columns":["Meningiomas","0.76","0.89","0.90"],"rows":[["Meningiomas","0.76","0.89","0.90"],["Cranial and paraspinal nerve tumors","0.89","0.97","0.97"],["Gliomas and glio-/neuronal tumors","0.81","0.95","0.85"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243647-p5-t0","doc_id":"K243647","page_num":5,"bbox":[21.95,18.25,591.42,97.74],"n_rows":3,"n_cols":2,"columns":["510(k) Summary\n510(k) #: K243647 Prepared on: 2025-06-23",""],"rows":[["510(k) Summary\n510(k) #: K243647 Prepared on: 2025-06-23",""],["Contact Details 21 CFR 807.92(a)(1)",""],["","FUJIFILM Healthcare Americas Corporation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243647-p5-t1","doc_id":"K243647","page_num":5,"bbox":[21.95,190.0,591.42,266.18],"n_rows":3,"n_cols":2,"columns":["","hcusregulatoryaffairs@fujifilm.com"],"rows":[["","hcusregulatoryaffairs@fujifilm.com"],["Device Name 21 CFR 807.92(a)(2)",""],["","Synapse PACS (7.5)"]],"caption_candidate":"Applicant Contact Ms. Kulkarni Chaitrali","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243647-p5-t2","doc_id":"K243647","page_num":5,"bbox":[21.95,359.2,591.42,409.89],"n_rows":2,"n_cols":2,"columns":["","QIH"],"rows":[["","QIH"],["Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)",""]],"caption_candidate":"Regulation Number 892.2050","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243647-p5-t3","doc_id":"K243647","page_num":5,"bbox":[21.95,464.1,591.42,764.44],"n_rows":5,"n_cols":2,"columns":["K221677","LLZ"],"rows":[["K221677","LLZ"],["Device Description Summary 21 CFR 807.92(a)(4)",""],["The Synapse PACS is an enterprise-wide medical information and image management software that runs on standard “off-the-shelf” PC\nhardware and Software (OS, browser). Synapse is intended for communication, storage, display, manipulation, measurement, printing,\nand processing of images and information acquired from various medical imaging and information systems. As a Software as a Medical\nDevice (SaMD), Synapse PACS performs these purposes without being part of a hardware medical device.",""],["Intended Use/Indications for Use 21 CFR 807.92(a)(5)",""],["FUJIFILM Synapse PACS Software is intended for use as a web-based application on an off-the shelf PC which meets or exceeds\nminimum specifications and is networked with a FUJIFILM Synapse PACS server.\nThe FUJIFILM Synapse PACS Software can process medical images from DICOM compliant modalities and non-DICOM sources.\nFUJIFILM Synapse PACS Software provides toolsets for:\n• Performing measurements on DICOM images\n• Regional segmentation\n• Importing and presenting data from modalities (DICOM and non-DICOM),\n• Solving clinical calculations\n• Creating and distributing structured reports",""]],"caption_candidate":"K190232 Synapse PACS LLZ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243647-p6-t0","doc_id":"K243647","page_num":6,"bbox":[19.73,18.5,593.58,762.1],"n_rows":7,"n_cols":2,"columns":["FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation\non displays appropriate to the medical task being performed. It enables the display, comparison, fusion, and volume rendering of studies\nto aid in reading, interpreting, reporting, and treatment planning.\nTypical users are radiologists, cardiologists, technologists, sonographers, technicians, nurses, and clinicians.\nMIP, MPR Fusion, and volume rendering are not intended for mammography use. FUJIFILM Synapse PACS Software can be used to\nprocess FUJIFILM’s DICOM MG “For Processing” images and also for the display, manipulation, and interpretation of lossless compressed\nor non-compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA-\ncleared, DICOM compatible displays for mammography.",""],"rows":[["FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation\non displays appropriate to the medical task being performed. It enables the display, comparison, fusion, and volume rendering of studies\nto aid in reading, interpreting, reporting, and treatment planning.\nTypical users are radiologists, cardiologists, technologists, sonographers, technicians, nurses, and clinicians.\nMIP, MPR Fusion, and volume rendering are not intended for mammography use. FUJIFILM Synapse PACS Software can be used to\nprocess FUJIFILM’s DICOM MG “For Processing” images and also for the display, manipulation, and interpretation of lossless compressed\nor non-compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA-\ncleared, DICOM compatible displays for mammography.",""],["","Indications for Use Comparison 21 CFR 807.92(a)(5)"],["There are no differences in the indication for use between the subject device and the primary predicate device.",""],["","Technological Comparison 21 CFR 807.92(a)(6)"],["The differences between the features in the subject device and the primary predicate device are Volume Rendering Techniques, 3D\nTools, Bone Removal, and 2-Point VOI. Although the primary predicate device does not have the features listed, the reference device\nhave the same features. Because the predicate device and reference device contain the same features, the addition of the features in\nversion 7.5 do not affect the safety or efficacy of the subject device.",""],["","Non-Clinical and/or Clinical Tests Summary & Conclusions 21 CFR 807.92(b)"],["Non-clinical testing result:\nThe differences between the features in the subject device and the primary predicate device are Volume Rendering Techniques\nincluding 3D Tools, 2-Point Volume of Interest (VOI), and Bone Removal.\nThe key addition to Synapse PACS 7.5.0 is the ability to perform volume rendering and 3D volume viewing for CT and MR.\nThe algorithm is already cleared and marketed for Synapse 3D (K221677, reference device). The volume rendering algorithms were\nintegrated unchanged into Synapse PACS 7.5.0 (subject device).\nThe 2-point VOI performs is a semi-automatic segmentation of a lesion in CT and MRI images using the line drawn by the user on the\nlesion. The algorithm implemented is the same as already cleared and marketed algorithms for Synapse 3D (K221677, reference device).\nIn Synapse3D, it is called Tumor Boundary Segmentation algorithm. The algorithm has been integrated into Synapse PACS unchanged\ncompared to Synapse 3D. Comparison with Synapse 3D (K221677, reference device) provides the same results in Synapse PACS 7.5.0\n(subject device).\nBone Removal is a tool that enhances the visibility of vessels in 3D rendered images by masking out bone regions. The tool is based on\nan AI algorithm cleared and marketed for Synapse 3D (K221677, reference device). It was improved for Synapse PACS 7.5.0. Comparison\nwith Synapse 3D (K221677, reference device) showed that the improved algorithm does not affect the safety or efficacy of Synapse PACS\n7.5.0 (subject device). Please refer to the Performance Bench Testing for testing with the improved algorithm.\nPerformance Testing Summary\nA. Summary test statistics and acceptance criteria:\nDice Similarity Coefficient (DSC) and 95% Hausdorff Distance (HD) were used as primary and secondary endpoints to validate the\nperformance of bone extraction algorithm. A pre-defined acceptance threshold of 0.951 was used for DSC. For 95% HD, we pre-define\nacceptance range 0.98 mm – 7.31 mm. The thresholds are determined after reviewing existing bone removal models in the literature.\nThe mean observed dice overlap coefficient and 95% HD with 95% confidence intervals were 0.959 [0.955 – 0.963] and 1.367 mm [1.170\nmm – 1.563 mm], respectively, exceeding the predefined acceptance thresholds.\nAcross the subgroups— region, sex, age band, vendor, slice-thickness bin, body region, contrast—Dice values remained tightly clustered\nbetween 0.94 and 0.97 and 95 % HD never exceeded 2.57 mm. The 5 mm cohort shows a slightly lower Dice (0.942) because thick slices\ncompress bone detail into fewer voxels, so tiny absolute deviations inflate the overlap metric; the boundary error remains modest (HD =\n2.6 mm), confirming clinically acceptable performance.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p5-t0","doc_id":"K243651","page_num":5,"bbox":[108.26,164.78,539.81,661.72],"n_rows":7,"n_cols":2,"columns":["Date:","November 26, 2024"],"rows":[["Date:","November 26, 2024"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact Person:","Peter Uhlir\nRegulatory Affairs Program Manager\nGE HealthCare\nTel: (+36) 70-436-9317\nEmail: peter.uhlir@gehealthcare.com"],["Secondary Contact Person:","Camille Vidal\nSenior Director Regulatory Affairs – Digital, AW & SEI\nGE HealthCare\nTel: 240-280-5356\nEmail: Camille.Vidal@gehealthcare.com"],["Device Trade Name:","VersaViewer"],["Common/Usual Name:","System, Image Processing, Radiological"],["Primary Classification Name:\nPrimary Regulation Number:\nPrimary Product Code:\nSecondary Product Code:\nClassification:","Medical image management and processing system\n21 CFR 892.2050\nLLZ\nQIH\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p6-t0","doc_id":"K243651","page_num":6,"bbox":[108.26,101.22,539.81,496.96],"n_rows":2,"n_cols":2,"columns":["Primary Predicate Device\nDevice name:\nCommon/Usual Name:\nManufacturer:\n510(k) number:\nClassification Name:\nRegulation Number:\nProduct Code:\nClassification:","Volume Viewer Plus\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems SCS\nK041521\nComputed tomography X-Ray System\n21 CFR 892.1750\nJAK\nClass II"],"rows":[["Primary Predicate Device\nDevice name:\nCommon/Usual Name:\nManufacturer:\n510(k) number:\nClassification Name:\nRegulation Number:\nProduct Code:\nClassification:","Volume Viewer Plus\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems SCS\nK041521\nComputed tomography X-Ray System\n21 CFR 892.1750\nJAK\nClass II"],["Reference Device\nDevice name:\nCommon/Usual Name:\nManufacturer:\n510(k) number:\nRegulation Number /\nClassification Name /\nProduct Code:\nClassification:","Spectral Bone Marrow\nSystem, X-Ray, Tomography, Computed\nGE Medical Systems, LLC\nK223514\n21 CFR 892.1750 / Computed tomography X-ray system / JAK\n21 CFR 892.2050 / Automated Radiological Image Processing\nSoftware / QIH\nClass II"]],"caption_candidate":"510(k) Premarket Notification Submission - VersaViewer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p8-t0","doc_id":"K243651","page_num":8,"bbox":[108.06,117.85,554.58,659.26],"n_rows":6,"n_cols":4,"columns":["Specification","Primary Predicate Device:","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate Device:","Subject Device:","Comparison"],["","Volume Viewer Plus","VersaViewer",""],["","(K041521)","",""],["Targeted\nanatomy and\nimaging\nmodality","All anatomies\nCT, MR, PET, NM, XACT\nDICOM images","All anatomies\nCT, MR, PET, NM, XACT,\nSCPT, US, CR, DX, RF,\nXA, MR PJN, CT GSI, MG\nand breast\ntomosynthesis (for\npresentation only).","Substantially equivalent.\nThe Image Support of proposed\ndevice is adapted and compatible\nwith acquisition images evolution.\nThe image support has been\nsuccessfully verified and\nvalidated. No safety and\neffectiveness issues are raised by\nthe expanded scope of modality\ncoverage.\nVersaViewer is not intended for\nthe displaying of digital\nmammography images for\ndiagnosis."],["Images\nRendering\nTypes","Axial / Coronal / Sagittal\nOblique / 3D / Volume\nRendering / MIP / minIP /\nAverage Rendering / Surface\nRendering","Axial / Coronal /\nSagittal\nOblique / 3D / Volume\nRendering / MIP /\nminIP and Average\nRendering","Substantially Equivalent\nBoth the predicate and proposed\ndevices include the Axial /\nCoronal / Sagittal and Oblique /\n3D / Volume Rendering / MIP /\nminIP and Average Rendering\ntypes."],["Images\nmanipulation","The following image\nmanipulations are available:\n(cid:120) Magnification\n(cid:120) Roam/pan\n(cid:120) ww/wl and , ww/wl\npresets\n(cid:120) simple oblique\n(cid:120) link / unlink series.","Usual image\nmanipulations are\naccessible directly from\nactive annotations in\nviewports, through\nmouse actions or icons\nin the toolbar:\n(cid:120) Zoom in / zoom\nout\n(cid:120) Roam / pan\n(cid:120) WW/WL manual\nadjustments and\npresets panel\n(cid:120) Multi oblique\ntool: displays\nthree adjustable\nobliques planes\n(cid:120) Link / unlink\nseries","Substantially Equivalent\nAll the functionalities existed in\nVolume Viewer Plus except the\nmulti-oblique tool.\nThis tool is like simple oblique\nmode, available in Volume Viewer\nPlus. It has been added in the\nsubject device, creating 3\northogonal obliques views.\nThis function facilitates user’s\nreview but doesn’t add or remove\nany information."]],"caption_candidate":"510(k) Premarket Notification Submission - VersaViewer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p9-t0","doc_id":"K243651","page_num":9,"bbox":[108.07,101.41,554.57,635.62],"n_rows":5,"n_cols":4,"columns":["Specification","Primary Predicate Device:","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate Device:","Subject Device:","Comparison"],["","Volume Viewer Plus","VersaViewer",""],["","(K041521)","",""],["Set of\nsegmentation\ntools","Not available","Yes\nSegmentation tools\nallow to create or edit\nfindings on 2D and 3D\nviews in axial, coronal\nor sagittal standard\norientation.\n(cid:120) Smart Brush\nautomatically\nadapts brush\nshape to the\nimage density /\nsignal.\n(cid:120) Threshold Brush\nselects values\nwithin a given\nthreshold, with\nthe possibility to\nadd a factor to\nsmooth contour\nedges.","Substantially Equivalent\nBrush is a new segmentation-\nbased measurement, but its\nresult can be obtained by\ncombination of existing functions\nalready presented in the\npredicate device. It improves and\noptimizes the workflow.\nThis function has already cleared\nin GEHC legacy device, BreView\n(K233714)."],["Export","DICOM Secondary Capture\nexport","It provides a variety of\nmethods for sharing\nthe results with clinical\npartners.\n(cid:120) Export images\nand findings can\nbe saved as SCPT\nseries and\nnetworked to\nDICOM\ndestinations for\nstructured\nreporting\npurposes.\n(cid:120) Copy images and\nfindings to paste\ninto personalized\ncommunications.","Substantially Equivalent\nBoth the predicate and subject\ndevice have capabilities to export\nthe information displayed in the\napplication."]],"caption_candidate":"510(k) Premarket Notification Submission - VersaViewer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p10-t0","doc_id":"K243651","page_num":10,"bbox":[108.09,116.05,554.57,578.74],"n_rows":5,"n_cols":4,"columns":["Specification","Reference Device:","Subject Device:","Comparison"],"rows":[["Specification","Reference Device:","Subject Device:","Comparison"],["One View","Spectral Bone Marrow","VersaViewer",""],["","(K223514)","",""],["Clinical\nWorkflow","Automated","Automated","Substantially Equivalent\nIn the subject device, a fully\nautomated workflow generates\nthe desired images (colored MD\nimages of the segmented bone\nregion overlaid on the\nmonochromatic base or Virtual\nUnenhanced images) as\nsecondary capture DICOM objects\nand networks them to the\npreconfigured DICOM\ndestinations (e.g. PACS) for the\nuser to review. Similar workflow\nalready exists in reference device,\nSpectral Bone Marrow (K223514).\nThis change in the subject device\ngreatly improves the overall\nefficiency of the review workflow."],["Segmentation\ntechnology","Deep Learning based\nsegmentation (bone)","Deep Learning based\nsegmentation (lung,\nliver, bone, aorta, heart\nand body (entire body))","Substantially equivalent\nThe One View feature includes CT\nMulti Organ segmentation that\nprovides a fully automatic\nsegmentation based on deep-\nlearning model for six body parts\nas lung, liver, bone, aorta, heart\nand body (entire body), each with\nits own distinctive contrast\nparameters:\nThe deep learning algorithm\nemployed in the subject device\nhave been successfully verified\nand validated, through\ncomparison to legacy\nsegmentation algorithms."]],"caption_candidate":"510(k) Premarket Notification Submission - VersaViewer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243651-p11-t0","doc_id":"K243651","page_num":11,"bbox":[108.12,101.41,554.54,404.9],"n_rows":4,"n_cols":4,"columns":["Specification","Reference Device:","Subject Device:","Comparison"],"rows":[["Specification","Reference Device:","Subject Device:","Comparison"],["One View","Spectral Bone Marrow","VersaViewer",""],["","(K223514)","",""],["Algorithm\nOutput","Spectral contrast parameters\n(Base keV in greyscale,\nMaterial density image\noverlay of Water (HAP) in\ncolor), utilized visualize bone\nmarrow.","Spectral contrast\nparameters (keV, MD\noverlay in greyscale or\ncolor), utilized to create\norgan contrast.","Substantially Equivalent\nOne View option of VersaViewer\nadjusts the imaging parameters\nof several body parts\nautomatically and displays them\nin one image.\nIn the reference device, Spectral\nBone Marrow (K223514) the\nfused image of colored material\ndensity (MD) images (e.g water\n(HAP)) of the segmented bone\nregion overlaid onto the base\nmonochromatic spectral CT\nimages or Virtual Unenhanced\nimages, as secondary capture\nDICOM series.\nIn the subject device same\nalgorithm output is use but it is\napplied for other six body parts as\nlung, liver, bone, aorta, heart and\nbody (entire body),"]],"caption_candidate":"510(k) Premarket Notification Submission - VersaViewer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p5-t0","doc_id":"K243667","page_num":5,"bbox":[72.24,600.24,539.76,697.2],"n_rows":6,"n_cols":3,"columns":["","Sonic DL Cine","Sonic DL 3D"],"rows":[["","Sonic DL Cine","Sonic DL 3D"],["Pulse Sequence Compatibility","FIESTA Cine","Fast Spin Echo (3D FSE)\nGradient Echo (3D GRE)"],["Anatomic Coverage","Cardiac","All anatomies"],["Field Strength Compatibility","1.5T, 3.0T","1.5T, 3.0T, 7.0T"],["Contrast Compatibility","Yes","Yes"],["Maximum Acceleration","12","Up to 12"]],"caption_candidate":"MR system software and activated through purchasable software option keys.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p7-t0","doc_id":"K243667","page_num":7,"bbox":[72.24,496.8,302.64,554.16],"n_rows":5,"n_cols":3,"columns":["Whole Brain Volume (mL)","",""],"rows":[["Whole Brain Volume (mL)","",""],["","Mean Diff","95% CI"],["Fully sampled vs ARC 2x1x1.2","1.1","[-4.4, 6.5]"],["Fully sampled vs Sonic DL 4","1.4","[-2.4, 5.3]"],["Fully sampled vs Sonic DL 12","6.8","[-4.9, 18.6]"]],"caption_candidate":"differences between methods.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p7-t1","doc_id":"K243667","page_num":7,"bbox":[313.68,496.8,530.4,554.16],"n_rows":5,"n_cols":3,"columns":["Cerebral White Matter Volume (mL)","",""],"rows":[["Cerebral White Matter Volume (mL)","",""],["","Mean Diff","95% CI"],["Fully sampled vs ARC 2x1x1.2","-1.5","[-4.4, 1.5]"],["Fully sampled vs Sonic DL 4","-2.0","[-5.2, 1.3]"],["Fully sampled vs Sonic DL 12","-2.3","[-10.1, 5.5]"]],"caption_candidate":"differences between methods.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p7-t2","doc_id":"K243667","page_num":7,"bbox":[72.24,558.24,302.64,615.72],"n_rows":5,"n_cols":3,"columns":["Cortical Gray Matter Volume (mL)","",""],"rows":[["Cortical Gray Matter Volume (mL)","",""],["","Mean Diff","95% CI"],["Fully sampled vs ARC 2x1x1.2","3.0","[1.2, 4.9]"],["Fully sampled vs Sonic DL 4","3.2","[0.7, 5.6]"],["Fully sampled vs Sonic DL 12","9.1","[2.1, 16.0]"]],"caption_candidate":"Fully sampled v s Sonic DL 12 6. 8 [-4.9, 18.6] F ully sampled vs Sonic DL 12 -2.3 [ -10.1, 5.5]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p7-t3","doc_id":"K243667","page_num":7,"bbox":[313.68,558.24,530.4,615.72],"n_rows":5,"n_cols":3,"columns":["Ventricle Total Volume (mL)","",""],"rows":[["Ventricle Total Volume (mL)","",""],["","Mean Diff","95% CI"],["Fully sampled vs ARC 2x1x1.2","-0.1","[-0.3, 0.2]"],["Fully sampled vs Sonic DL 4","-0.1","[-0.4, 0.1]"],["Fully sampled vs Sonic DL 12","-0.2","[-0.8, 0.4]"]],"caption_candidate":"Fully sampled v s Sonic DL 12 6. 8 [-4.9, 18.6] F ully sampled vs Sonic DL 12 -2.3 [ -10.1, 5.5]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p7-t4","doc_id":"K243667","page_num":7,"bbox":[72.24,619.8,302.64,677.28],"n_rows":5,"n_cols":3,"columns":["HOC Average Occupancy","",""],"rows":[["HOC Average Occupancy","",""],["","Mean Diff","95% CI"],["Fully sampled vs ARC 2x1x1.2","0.004","[-0.007, 0.014]"],["Fully sampled vs Sonic DL 4","0.007","[-0.009, 0.023]"],["Fully sampled vs Sonic DL 12","0.014","[-0.018, 0.046]"]],"caption_candidate":"Fully sampled v s Sonic DL 12 9. 1 [2.1, 1 6.0] F ully sampled vs Sonic DL 12 -0.2 [-0.8, 0.4]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p8-t0","doc_id":"K243667","page_num":8,"bbox":[110.4,172.32,501.72,418.08],"n_rows":8,"n_cols":2,"columns":["Number of image series evaluated:","120"],"rows":[["Number of image series evaluated:","120"],["Number of unique subjects:\nPatients:\nHealthy Volunteers:","54\n48\n6"],["Sites contributing data:\nUnited States:\nOutside of United States:","7\n4\n3"],["Gender of subjects\nMale:\nFemale:","26\n28"],["Age range of subjects:","11-80 years"],["Pathology:","Subjects from clinical sites included examples\nof various pathologies representing a mixture\nof small, large, focal, diffuse, hyper- and hypo-\nintense lesions"],["Contrast:","Contrast agents were used in a subset of the\ndata, as clinically indicated"],["Equipment Used:","GE HealthCare 1.5T, 3.0T, and 7.0T MR Systems"]],"caption_candidate":"extremities as summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243667-p10-t0","doc_id":"K243667","page_num":10,"bbox":[72.24,77.4,539.76,201.72],"n_rows":8,"n_cols":5,"columns":["Anatomy","Maximum\nAcceleration\nTested","Recommended Default Acceleration Range","",""],"rows":[["Anatomy","Maximum\nAcceleration\nTested","Recommended Default Acceleration Range","",""],["","","1.5T","3.0T","7.0T"],["Brain","12","4 – 6","6 – 8","8 – 10"],["Spine","12","4 – 6","6 – 8","-"],["Musculoskeletal","12","4 – 6","8 – 10","8 – 10"],["Abdomen","12","4 – 6","8 – 10","-"],["Pelvis","12","4 – 6","6 – 8","-"],["Breast","10","4 – 6","6 – 8","-"]],"caption_candidate":"Traditional 510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p5-t0","doc_id":"K243672","page_num":5,"bbox":[108.24,164.76,539.64,639.24],"n_rows":7,"n_cols":2,"columns":["Date:","May 16, 2025"],"rows":[["Date:","May 16, 2025"],["Submitter:","GE Medical Systems SCS\nEstablishment Registration Number - 9611343\n283 rue de la Miniere\n78530 Buc, France"],["Primary Contact Person:","Mireille Haddad\nRegulatory Affairs Program Manager\nGE HealthCare\nEmail: mireillehaddad@gehealthcare.com"],["Secondary Contact Person:","Elizabeth Mathew\nSenior Regulatory Affairs Manager\nGE HealthCare\nTel: 262-424-7774\nEmail: elizabeth.mathew@gehealthcare.com"],["Device Trade Name:","CardIQ Suite"],["Common/Usual Name:","System, X-Ray, Tomography, Computed"],["Primary Classification Name:\nPrimary Regulation Number:\nPrimary Product Code:\nSecondary Product Code:\nClassification:","Computed Tomography X-Ray System\n21 CFR 892.1750\nJAK\nQIH\nClass II"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p6-t0","doc_id":"K243672","page_num":6,"bbox":[113.64,110.36,302.22,300.87],"n_rows":17,"n_cols":2,"columns":["Primary Predicate Device",""],"rows":[["Primary Predicate Device",""],["",""],["Device name:","CardIQ Sui"],["",""],["Common/Usual Name:","System, X-"],["",""],["Manufacturer:","GE Medica"],["",""],["510(k) number:","K233731"],["",""],["Classification Name:","Computed"],["",""],["Regulation Number:","21 CFR 89"],["",""],["Product Code:","JAK"],["",""],["Classification:","Class II"]],"caption_candidate":"Primary Predicate Device","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243672-p7-t0","doc_id":"K243672","page_num":7,"bbox":[113.64,56.71,422.09,502.79],"n_rows":35,"n_cols":3,"columns":["10(k) Premarket Notifica","tion Submission-CardIQ","Suite"],"rows":[["10(k) Premarket Notifica","tion Submission-CardIQ","Suite"],["","",""],["Reference Device","",""],["","",""],["Device name:","CardIQ Xpress 2.0",""],["","",""],["Common/Usual Name:","System, X-Ray, Tomography, C","omput"],["","",""],["Manufacturer:","GE Medical Systems SCS",""],["","",""],["510(k) number:","K073138",""],["","",""],["Classification Name:","Computed tomography X-Ray","System"],["","",""],["Regulation Number:","21 CFR 892.1750",""],["","",""],["Product Code:","JAK",""],["","",""],["Classification:","Class II",""],["","",""],["Device name:","SmartScore 4.0",""],["","",""],["Common/Usual Name:","System, X-Ray, Tomography, C","omput"],["","",""],["Manufacturer:","GE Medical Systems SCS",""],["","",""],["510(k) number:","K020929",""],["","",""],["Classification Name:","Computed tomography X-Ray","System"],["","",""],["Regulation Number:","21 CFR 892.1750",""],["","",""],["Product Code:","JAK",""],["","",""],["Classification:","Class II",""]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243672-p9-t0","doc_id":"K243672","page_num":9,"bbox":[108.06,401.52,578.22,680.52],"n_rows":7,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite","",""],["","","",""],["","(K233731)","",""],["Input Data for\nCalcium Scoring","Image Requirements:\n• 120kVp\n• Gated cardiac\nacquisition\n• DFOV - 24 cm -\n35 cm\n• Slice thickness ≤\n3mm\n• Non-contrast","Image Requirements:\n• 120kVp\n• Gated cardiac\nacquisition\n• DFOV - 24 cm -\n35 cm\n• Slice thickness ≤\n3mm\n• Non-contrast","Identical"],["Segmentation\nand labeling\ncalcific regions\nin the\ncoronaries","Yes","Yes","Identical"]],"caption_candidate":"the predicate devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p10-t0","doc_id":"K243672","page_num":10,"bbox":[108.04,101.34,578.24,665.88],"n_rows":9,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite","",""],["","","",""],["","(K233731)","",""],["Manual\nSegmentation\nand labeling of\ncalcific regions","Yes","Yes","Identical"],["Computation of\ncalcium score -\nAgatson Score &\nVolume Scoring\nmethods","Yes","Yes","Identical"],["Percentile guide","No","Yes","Substantially Equivalent\nIn the subject device, the calcium\nscore is used as input to a percentile\nguide in order to be able to compare\nthe patient's calcium score with a\nsimilar population of individuals.\nThough the percentile guide\nfunctionality does not exist in the\npredicate device, this functionality\nalready exists in the reference\ndevice, SmartScore 4.0 (K020929)."],["Cardiac Review","Yes","Yes","Identical\nMPR Cardiac Review is intended to\nassist readers in the review of\ncoronary artery imaging. Within this\nreview step, readers will find tools\naligned with a 2D coronary artery CTA\nreview, a segmented 3D Volume\nRendering model of the heart, as well\nas general overview of all\nreconstructions acquired within a\nstudy such a multi-phase cine\nacquisitions or delayed enhancement\nimaging."]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p11-t0","doc_id":"K243672","page_num":11,"bbox":[108.05,101.34,578.23,695.76],"n_rows":8,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite","",""],["","","",""],["","(K233731)","",""],["Heart\nSegmentation","Yes (Contrast-enhanced\ncardiac exams)","Yes (Contrast-\nenhanced and non-\ncontrast cardiac\nexams)","Substantial Equivalent\nThe predicate device already\nsegments the heart for contrast-\nenhanced exams and the same\nalgorithm exists in the subject device\nwith no changes. The subject device\nhas been updated to add another\ndeep learning algorithm to segment\nnon-contrasted heart exams. The\nnew deep learning algorithm for\nheart segmentation of non-\ncontrasted exams uses the same\nmodel as the previous existing heart\nsegmentation algorithm for\ncontrasted exams, however now the\ninput is changed, and the model is\ntrained and tested with the non-\ncontrasted exams."],["Heart fat\nestimate","No","Yes","Substantial Equivalent\nIn the subject device, a predefined\nHU threshold of -200 to 30 is\napplied to the ROI and is\nautomatically generated on the\nsegmented heart which provides\nthe visualization of the heart fat\nestimate. The estimated volume of\nthe heart fat is calculated for the\ndesignated CACS phase selected. In\nthe reference device, CardIQ Xpress\n2.0, the same functionality can be\nperformed using semi-automatic\nsegmentation tools."],["Coronary\nReview -\nCoronary\nSegmentation","Yes","Yes","Identical"]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p12-t0","doc_id":"K243672","page_num":12,"bbox":[108.06,101.34,578.22,680.4],"n_rows":7,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite","",""],["","","",""],["","(K233731)","",""],["Coronary\nReview -\nCoronary\nTracking","Coronary Centerline\nTracking is available","Coronary Centerline\nTracking is available,\nincludes lumen\nsegmentation.","Substantially equivalent\nThe functionality of coronary\ncenterline tracking already exists in\nthe predicate device CardIQ Suite.\nIn the subject device, a new post-\nprocessing step is added to the\ncoronary centerline tracking\nalgorithm to generate a new output:\nthe coronary lumen segmentation.\nThe lumen segmentation was already\navailable in the reference device\nCardIQ Xpress 2.0. The post-\nprocessing lumen segmentation\nadded in the subject device uses the\nsame image processing\nmethodology, based on pixel\nintensity, that was used in CardIQ\nXpress 2.0.\nAdditionally, the Deep learning\nalgorithm for coronary tracking in\nthe subject device has been updated\nby retraining to a finer resolution for\nmore precision and incorporates\nsome post-processing steps to refine\nthe centerline and tracking at vessel\nostia, aorta, and vessel bifurcations."],["Coronary\nReview -\nCoronary\nLabeling","Yes","Yes","Substantially equivalent\nThe functionality of coronary\ncenterline labelling already exists in\nthe predicate device.\nThe algorithm coronary labelling has\nbeen improved to increase the\nperformance but uses a similar\napproach as the one in the predicate\ndevice."]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243672-p13-t0","doc_id":"K243672","page_num":13,"bbox":[108.06,101.34,578.22,499.8],"n_rows":7,"n_cols":4,"columns":["Specification","Primary Predicate","Subject Device:","Comparison"],"rows":[["Specification","Primary Predicate","Subject Device:","Comparison"],["","Device:","CardIQ Suite",""],["","CardIQ Suite","",""],["","","",""],["","(K233731)","",""],["Lumen diameter\nQuantification\nand minimum\ndiameter\ncomputations\nEstimate\n(Narrowing\nHighlights)","No","Yes","Substantial Equivalent\nThe lumen diameter quantification\nis calculated using a new non-deep\nlearning algorithm and displayed as\na lumen minimum diameter profile\ngraph. This profile is equivalent to\nthe minimum diameter lumen\nprofile available in the reference\ndevice, CardIQ Xpress 2.0\n(K073138).\nA local reduction in minimum\ndiameter in the lumen profile is\ncolor coded based on a signal\nprocessing algorithm."],["Vascular\nMeasurement\nTool","No","Yes","Substantial Equivalent\nThe computational method and\nuser workflow for vascular\nmeasurements in the subject\ndevice, is identical to the reference\ndevice, CardIQ Xpress 2.0\n(K073138)."]],"caption_candidate":"510(k) Premarket Notification Submission-CardIQ Suite","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p7-t0","doc_id":"K243679","page_num":7,"bbox":[72.26,92.06,544.68,669.34],"n_rows":11,"n_cols":3,"columns":["","Predicate device (MammoScreen 3)","Subject device (MammoScreen 4)"],"rows":[["","Predicate device (MammoScreen 3)","Subject device (MammoScreen 4)"],["Manufacturer","Therapixel","Therapixel"],["Regulation number","892.2090","892.2090"],["Product Code","QDQ","QDQ"],["Intended Use","MammoScreen 3 is a concurrent\nreading and reporting aid for\nphysicians interpreting screening\nmammograms. It is intended for use\nwith compatible full-field digital\nmammography and digital breast\ntomosynthesis systems. The device\ncan also use compatible prior\nexaminations in the analysis.\nOutput of the device includes graphical\nmarks of findings as soft-tissue lesions\nor calcifications on mammograms\nalong with their level of suspicion\nscores. The lesion type is characterized\nas mass/asymmetry, distortion, or\ncalcifications for each detected finding.\nThe level of suspicion score is\nexpressed at the finding level, for each\nbreast, and overall for the\nmammogram.\nThe location of findings, including\nquadrant, depth, and distance from the\nnipple, is also provided. This\nadjunctive information is intended to\nassist interpreting physicians during\nreporting.\nPatient management decisions should\nnot be made solely based on the\nanalysis by MammoScreen 3.","MammoScreen® 4 is a concurrent\nreading and reporting aid for physicians\ninterpreting mammograms. It is\nintended for use with compatible full-\nfield digital mammography and digital\nbreast tomosynthesis. The device can\nalso use compatible prior examinations\nin the analysis.\nOutput of the device includes graphical\nmarks of findings as soft-tissue lesions or\ncalcifications on mammograms along\nwith their level of suspicion scores. The\nlesion type is characterized as\nmass/asymmetry, distortion, or\ncalcifications for each detected finding.\nThe level of suspicion score is expressed\nat the finding level, for each breast, and\noverall for the mammogram.\nThe location of findings, including\nquadrant, depth, and distance from the\nnipple, is also provided. This adjunctive\ninformation is intended to assist\ninterpreting physicians during reporting.\nPatient management decisions should\nnot be made solely based on the analysis\nby MammoScreen 4."],["Intended user\npopulation","Physicians qualified to read\nmammograms.","Physicians qualified to read\nmammograms."],["Intended patient\npopulation","Women undergoing mammography.","Women undergoing mammography."],["Anatomical Location","Breast","Breast"],["Design","Software-only device","Software-only device"],["Type of artificial\nintelligence","MammoScreen 3 is powered by\nartificial intelligence/machine\nlearning-based software algorithm","Same."],["Level of suspicion","MammoScreen 3 outputs a level of\nsuspicion at the finding, breast and\ncase level.","Same."]],"caption_candidate":"Predicate device comparison:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p8-t0","doc_id":"K243679","page_num":8,"bbox":[72.26,72.24,544.68,286.37],"n_rows":6,"n_cols":3,"columns":["","Predicate device (MammoScreen 3)","Subject device (MammoScreen 4)"],"rows":[["","Predicate device (MammoScreen 3)","Subject device (MammoScreen 4)"],["Lesion type","For each detected finding\nMammoScreen 3 classifies them as\nmass/asymmetry, distortion or\ncalcifications.","Same."],["Localization","For each finding MammoScreen 3\nprovides a quadrant, a depth and a\ndistance to the nipple.","Same."],["Inputs","FFDM or 2DSM & DBT or FFDM & DBT,\nwith an optional prior (FFDM or 2DSM\n& DBT) expect for the former.","Same."],["Support of Hologic\nEnvision system","Not included.","Included."],["Inclusion of PCCP","Not Included.","Included.\nThe PCCP in the subject device includes\nproposed modifications related to\nextending supported image acquisition\nsystems."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p9-t0","doc_id":"K243679","page_num":9,"bbox":[72.26,208.94,539.88,665.98],"n_rows":10,"n_cols":2,"columns":["Statistics tests for primary objective","Non-inferiority in standalone cancer detection performance\ncompared to the previous version of MammoScreen"],"rows":[["Statistics tests for primary objective","Non-inferiority in standalone cancer detection performance\ncompared to the previous version of MammoScreen"],["Primary endpoint","• AUC at the mammogram level MS4: 0.894 (0.870, 0.919),\nMS2: 0.867 (0.839, 0.896), Δ: 0.027 (0.002, 0.052),\np<0.0001\n• AUC at the breast level: MS4: 0.919 (0.897, 0.941), MS2:\n0.895 (0.871, 0.920), Δ: 0.023 (0.002, 0.045), p<0.0001\n• AUC LROC at the finding level: MS4: 0.891 (0.862,\n0.921), MS2: 0.837 (0.797, 0.877), Δ: 0.055 (0.032,\n0.077), p<0.0001"],["Acceptance criteria","Positive lower bound of the 95% CI of the difference in\nendpoints between the version under evaluation\n(MammoScreen 4 on Envision) and the reference version\n(MammoScreen 2 on Dimension)"],["Number of included patients","1,475"],["Number of included studies","2,950 (each patient underwent a DBT acquisition with two Hologic\nmammography systems)"],["Age distribution","Age <= 50: 446\n50 < Age <= 65: 642\n65 > Age: 372"],["Race and Ethnicity distribution","Asian: 16\nWhite: 1180\nBlack: 94\nOther (including American Indian, Alaska Native, Native Hawaiian\nor Other Pacific Islander): 14\nHispanic: 88\nNot Hispanic: 1136"],["Considered subgroups","Density, Lesion type (mass/asymmetries, calcifications, distortion),\nAge, Lesion size, Lesion severity, Race, Ethnicity, Data\nprovenance, Reference standard for negative cases."],["Truthing process","Positive cases: biopsy-proven presence of cancer.\nBenign cases: cases confirmed by biopsy result and cases\nconfirmed by imaging follow-up.\nNegative cases: verified by imaging follow-up."],["Independence of test data from training\ndata","Data sources are separated into the training/tuning group and the\ntest group. Sources in the training/tuning group may only be used\nfor model training and tuning. Sources in the test group may only\nbe used for external validation of the model’s performances on"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p10-t0","doc_id":"K243679","page_num":10,"bbox":[72.26,529.87,539.88,686.86],"n_rows":4,"n_cols":2,"columns":["Modification #1 summary","Support of GE mammograms (no re-training required)"],"rows":[["Modification #1 summary","Support of GE mammograms (no re-training required)"],["Modification #2 summary","Support of a new mammography manufacturer other than Hologic\nand GE (re-training required) – this modification may also include\nthe support of GE mammograms in case Modification #1 does not\nconclude to the non-inferiority on GE mammograms compared to\nHologic"],["Statistics tests for primary\nobjective","Non-inferiority of device standalone performance on mammograms\nof the manufacturer under evaluation compared to Hologic\nmammograms"],["Primary endpoints","AUC at the mammogram, breast and finding level (AUC LROC)"]],"caption_candidate":"The table below lists and describes the anticipated modifications:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p11-t0","doc_id":"K243679","page_num":11,"bbox":[72.26,72.24,539.88,240.74],"n_rows":3,"n_cols":2,"columns":["Acceptance criteria","• Modification #1: See Table 1.\n• Modification #2: See Table 1 (unpaired comparisons) and Table 2\n(paired comparisons)."],"rows":[["Acceptance criteria","• Modification #1: See Table 1.\n• Modification #2: See Table 1 (unpaired comparisons) and Table 2\n(paired comparisons)."],["Validation activities","Upon demonstration of the non-inferiority through the\nstandalone performance testing, changes will be documented in a\nminor release amending:\n- The Algorithm test protocol and results documents\n- The User Guide\n- The device label"],["Communication plan","Upcoming updates are communicated to users through advisory notices\nsent by email at least 2 weeks before deployment. Users may choose to\nopt-out the update during the 2-week notice period."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p11-t1","doc_id":"K243679","page_num":11,"bbox":[72.26,281.33,539.88,554.59],"n_rows":7,"n_cols":7,"columns":["","Primary endpoints","","","Acceptance criteria proposed for\nPCCP","",""],"rows":[["","Primary endpoints","","","Acceptance criteria proposed for\nPCCP","",""],["","AUC ROC\n(exam\nlevel)","AUC ROC\n(breast\nlevel)","AUC LROC\n(finding\nlevel)","Exam level","Breast level","Finding\nlevel"],["MammoScreen\n(K192854) on\nHologic FFDM only","0.89\n(0.87, 0.91)","0.91\n(0.89, 0.92)","0.88\n(0.86, 0.90)","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02"],["MammoScreen 2\n(K211541) on\nHologic DBT + FFDM","0.89\n(0.87, 0.91)","0.92\n(0.90, 0.93)","0.88\n(0.86, 0.90)","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02"],["MammoScreen 2\n(K211541) on\nHologic DBT + 2DSM","0.89\n(0.87, 0.91)","0.92\n(0.90, 0.93)","0.88\n(0.86, 0.90)","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02"],["MammoScreen 3\n(K240301) on\nHologic DBT + FFDM\nwith FFDM priors","0.93\n(0.91, 0.94)","0.95\n(0.93, 0.97)","0.93\n(0.91, 0.95)","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02","LB 95% CI\ndiff ≥ -0.02"],["MammoScreen 3\n(K240301) on\nHologic DBT + 2DSM\nwith DBT + 2DSM\npriors","0.89\n(0.84, 0.93)","0.92\n(0.88, 0.96)","0.87\n(0.83, 0.94)","LB 95% CI\ndiff ≥ -0.05","LB 95% CI\ndiff ≥ -0.04","LB 95% CI\ndiff ≥ -0.04"]],"caption_candidate":"Table 1: Primary endpoints and acceptance criteria for unpaired comparisons.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p11-t2","doc_id":"K243679","page_num":11,"bbox":[72.26,595.15,539.88,654.82],"n_rows":2,"n_cols":7,"columns":["","Primary endpoints","","","Acceptance criteria proposed for\nPCCP","",""],"rows":[["","Primary endpoints","","","Acceptance criteria proposed for\nPCCP","",""],["","AUC ROC\n(exam\nlevel)","AUC ROC\n(breast\nlevel)","AUC LROC\n(finding\nlevel)","Exam level","Breast level","Finding\nlevel"]],"caption_candidate":"Table 2: Primary endpoints and acceptance criteria for paired comparisons.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243679-p12-t0","doc_id":"K243679","page_num":12,"bbox":[72.26,72.24,539.88,285.89],"n_rows":5,"n_cols":7,"columns":["MammoScreen\n(K192854) on\nHologic FFDM only","0.89\n(0.87, 0.91)","0.91\n(0.89, 0.92)","0.88\n(0.86, 0.90)","LB 95%CI\n≥0.84","LB 95%CI\n≥0.86","LB 95%CI\n≥0.83"],"rows":[["MammoScreen\n(K192854) on\nHologic FFDM only","0.89\n(0.87, 0.91)","0.91\n(0.89, 0.92)","0.88\n(0.86, 0.90)","LB 95%CI\n≥0.84","LB 95%CI\n≥0.86","LB 95%CI\n≥0.83"],["MammoScreen 2\n(K211541) on\nHologic DBT + FFDM","0.89\n(0.87, 0.91)","0.92\n(0.90, 0.93)","0.88\n(0.86, 0.90)","LB 95%CI\n≥0.84","LB 95%CI\n≥0.87","LB 95%CI\n≥0.83"],["MammoScreen 2\n(K211541) on\nHologic DBT + 2DSM","0.89\n(0.87, 0.91)","0.92\n(0.90, 0.93)","0.88\n(0.86, 0.90)","LB 95%CI\n≥0.84","LB 95%CI\n≥0.87","LB 95%CI\n≥0.83"],["MammoScreen 3\n(K240301) on\nHologic DBT + FFDM\nwith FFDM priors","0.93\n(0.91, 0.94)","0.95\n(0.93, 0.97)","0.93\n(0.91, 0.95)","LB 95%CI\n≥0.88","LB 95%CI\n≥0.9","LB 95%CI\n≥0.88"],["MammoScreen 3\n(K240301) on\nHologic DBT + 2DSM\nwith DBT + 2DSM\npriors","0.89\n(0.84, 0.93)","0.92\n(0.88, 0.96)","0.87\n(0.83, 0.94)","LB 95%CI\n≥0.84","LB 95%CI\n≥0.87","LB 95%CI\n≥0.83"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243684-p5-t0","doc_id":"K243684","page_num":5,"bbox":[67.5,118.5,485.5,288.5],"n_rows":7,"n_cols":2,"columns":["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],"rows":[["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],["",""],["Contact:","Christophe Gardella\nChief Technical Officer\nTel. +0033686543950\nEmail. christophe@brightheart.fr"],["",""],["Submission Correspondent:","Christophe Gardella"],["",""],["Date Prepared:","May 5, 2025"]],"caption_candidate":"UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243684-p5-t1","doc_id":"K243684","page_num":5,"bbox":[67.5,335.5,489.5,436.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name:","BrightHeart View Classifier"],"rows":[["Device Trade Name:","BrightHeart View Classifier"],["Device Common Name:","Fetal ultrasound view classifier"],["Classification Name","21 CFR §892.2050, Medical image management and\nprocessing system"],["Product Code(s):","QIH"],["Regulatory Class:","Class II"]],"caption_candidate":"EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243684-p6-t0","doc_id":"K243684","page_num":6,"bbox":[66.25,365.65,546.25,642.5],"n_rows":7,"n_cols":4,"columns":["","Subject Device\nBrightHeart View\nClassifier","Predicate Device\nSonix Health","Reference Device\nHeartAssist feature in\nthe Samsung V8\nDiagnostic\nUltrasound System,\nV7 Diagnostic\nUltrasound System."],"rows":[["","Subject Device\nBrightHeart View\nClassifier","Predicate Device\nSonix Health","Reference Device\nHeartAssist feature in\nthe Samsung V8\nDiagnostic\nUltrasound System,\nV7 Diagnostic\nUltrasound System."],["510(k) Number","TBD","K230209","K223387"],["Applicant","BrightHeart","Ontact Health","Samsung"],["Classification\nRegulation","21 CFR §892.2050","21 CFR §892.2050","21 CFR §892.2150\n21 CFR §892.1560\n21 CFR §892.1570"],["Product Code","QIH","QIH, LLZ","IYN, IYO, ITX"],["Device Type","SaMD","SaMD","SaMD"],["Software algorithm","Machine Learning\nModel","Machine Learning\nModel","Machine Learning\nModel"]],"caption_candidate":"Technological Comparison:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243684-p7-t0","doc_id":"K243684","page_num":7,"bbox":[66.33,72.1,546.33,555.5],"n_rows":7,"n_cols":4,"columns":["","Subject Device\nBrightHeart View\nClassifier","Predicate Device\nSonix Health","Reference Device\nHeartAssist feature in\nthe Samsung V8\nDiagnostic\nUltrasound System,\nV7 Diagnostic\nUltrasound System."],"rows":[["","Subject Device\nBrightHeart View\nClassifier","Predicate Device\nSonix Health","Reference Device\nHeartAssist feature in\nthe Samsung V8\nDiagnostic\nUltrasound System,\nV7 Diagnostic\nUltrasound System."],["Imaging Modality","Fetal Ultrasound","Adult\nEchocardiography","The Samsung V8 and\nV7 are general\npurpose, mobile,\nsoftware controlled,\ndiagnostic ultrasound\nsystems, including\nfetal ultrasound."],["Model Inputs","Ultrasound images\nand video clips","Ultrasound images\nand video clips","Ultrasound images"],["Model method","Neural networks","Neural networks","Neural networks"],["Model trained to\nidentify","Classification of\nultrasound images\ninto standard views of\nfetal heart.","Classification of\nultrasound images\ninto standard views of\nadult heart,\ndetermination cardiac\nmeasurements.","Classification of\nultrasound images\ninto standard views of\nfetal heart scanning,\nand detection of\ncalipers used for\nmeasurements"],["Model Output","Identifies standard\nviews of the heart and\nabdomen in images\nand video clips.","Identifies standard\nviews of the heart in\nimages and video\nclips, detection of\ncardiac\nmeasurements.","Identifies standard\nviews of the heart and\nabdomen in images"],["PCCP","Included","Not included","Not included"]],"caption_candidate":"510(k) Summary - K243684 Page 3 of 9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p7-t0","doc_id":"K243685","page_num":7,"bbox":[72.27,100.69,539.87,709.06],"n_rows":16,"n_cols":7,"columns":["","","Predicate device","","","Subject device",""],"rows":[["","","Predicate device","","","Subject device",""],["","","(MammoScreen BD – K241561)","","","(MammoScreen BD – K243685)",""],["Manufacturer","Therapixel","","","Therapixel","",""],["Regulation number","892.2050","","","892.2050","",""],["Product Code","QIH","","","QIH","",""],["Medical Class Device","Class II","","","Class II","",""],["Intended Use","MammoScreen® BD is a software\napplication intended for use with\ncompatible full-field digital\nmammography and digital breast\ntomosynthesis systems.\nMammoScreen BD evaluates the\nbreast tissue composition to provide an\nACR BI-RADS 5th Edition breast\ndensity category. The device is\nintended to be used in the population of\nasymptomatic women undergoing\nscreening mammography who are at\nleast 40 years old.\nMammoScreen BD only produces\nadjunctive information to aid\ninterpreting physicians in the\nassessment of breast tissue\ncomposition. It is not a diagnostic\nsoftware.\nPatient management decisions should\nnot be made solely based on analysis\nby MammoScreen BD.","","","MammoScreen® BD is a software\napplication intended for use with\ncompatible full-field digital\nmammography and digital breast\ntomosynthesis systems.\nMammoScreen BD evaluates the\nbreast tissue composition to provide an\nACR BI-RADS 5th Edition breast\ndensity category. The device is\nintended to be used in the population of\nasymptomatic women undergoing\nscreening mammography who are at\nleast 40 years old.\nMammoScreen BD only produces\nadjunctive information to aid\ninterpreting physicians in the\nassessment of breast tissue\ncomposition. It is not a diagnostic\nsoftware.\nPatient management decisions should\nnot be made solely based on analysis\nby MammoScreen BD.","",""],["Intended patient population","Asymptomatic women undergoing\nmammography","","","Asymptomatic women undergoing\nmammography","",""],["Intended user population","Interpreting physicians","","","Interpreting physicians","",""],["Anatomical Location","Breast","","","Breast","",""],["Design","Software-only device","","","Software-only device","",""],["Type of artificial\nintelligence","Supervised Machine Learning","","","Supervised Machine Learning","",""],["Input","Compatible full-field digital\nmammography and digital breast\ntomosynthesis systems (using\nSynthetic 2D (2DSM)) for Hologic.","","","Compatible full-field digital\nmammography and digital breast\ntomosynthesis systems (using\nSynthetic 2D (2DSM)) for Hologic\nand GE.","",""],["Output","Breast density assessment based on\nACR BIRADS 5th edition category at\nthe mammogram level.","","","Breast density assessment based on\nACR BIRADS 5th edition category at\nthe mammogram level.","",""],["Support of Hologic Envision\nsystem and GE\nmammograms","Not included","","","Included","",""],["Inclusion of PCCP","Predetermined Change Control Plan\n(PCCP) including:","","","Predetermined Change Control Plan\n(PCCP) including:","",""]],"caption_candidate":"Predicate device comparison:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p9-t0","doc_id":"K243685","page_num":9,"bbox":[72.26,147.98,539.88,323.09],"n_rows":5,"n_cols":2,"columns":["Total number of studies","108,775"],"rows":[["Total number of studies","108,775"],["Density distribution","A: 12.79%\nB: 34.58%\nC: 42.94%\nD: 9.38%\nUnknown (excluded): 0.31%"],["Patient ages","First quartile (Q1): 47.0 Mean: 56.0 Third quartile (Q3):\n64.0"],["Patient Race / Ethnicity","White: 49.13%\nAsian: 7.63%\nBlack or African American: 0.43%\nNative Hawaiian or Pacific Islander: 0.09%\nUnknown: 42.72%"],["Manufacturer","Hologic: 61.63%\nGE: 38.37%"]],"caption_candidate":"the Table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p11-t0","doc_id":"K243685","page_num":11,"bbox":[72.77,122.74,539.98,711.4],"n_rows":12,"n_cols":4,"columns":["","Hologic","Hologic Envision","GE"],"rows":[["","Hologic","Hologic Envision","GE"],["Statistics tests\nfor primary\nobjective","Superiority in standalone performance for density assignment of MammoScreen BD compared\nto a pre-determined reference value (Kappa = 0.85).\nreference","",""],["Primary\nendpoint","No change from previous\nclearance. Quadratically\nweighted Cohen’s kappa\nbetween the density\nassessment of\nMammoScreen BD and\nthe established ground\ntruth.\nKappa quadratic = 89.03\n[95% CI: 87.43 – 90.56]","Quadratically weighted\nCohen’s kappa between the\ndensity assessment of\nMammoScreen BD and the\nestablished ground truth.\nKappa quadratic = 89.54\n[95% CI: 86.88 – 91.69]","Quadratically weighted Cohen’s\nkappa between the density\nassessment of MammoScreen BD\nand the established ground truth.\nKappa quadratic = 93.19 [95% CI:\n90.50 – 94.92]"],["Acceptance\ncriteria","The one-sided p-value for the test H0: Kappa ≤ 0.85 is less than the significance level (α=0.05)\nand the lower bound of the 95% confidence interval for Kappa > 0.85 indicating that the\nobserved weighted Kappa is statistically significantly greater than 0.85.","",""],["Number of\nincluded\npatients","922","500","376"],["Number of\nincluded\nstudies","1,155","500","490"],["Age\ndistribution","Range: [40 – 90]\nFirst quartile (Q1): 50.0\nMean: 58.5\nThird quartile (Q3 : 66.0\n• Age < 55: 570\n• 55 ≤ Age < 65: 308\n• Age ≥ 65: 269","Range: [36 – 86]\nFirst quartile (Q1): 48.0\nMean: 56.0\nThird quartile (Q3): 65.0\n• Age < 55: 234\n• 55 ≤ Age < 65: 130\n• Age ≥ 65: 136","Range: [31 -86]\nFirst quartile (Q1) : 47.0\nMean : 57.2\nThird quartile (Q3): 67.0\n• Age < 55: 234\n• 55 ≤ Age < 65: 130\n• Age ≥ 65: 136"],["Race and\nEthnicity\ndistribution","White: 273\nAsian: 102\nBlack or African\nAmerican: 88\nAmerican indian or\nalaska native: 4\nNative hawaiian or\npacific islander: 4","Asian: 6\nWhite: 401\nBlack or African\nAmerican: 40\nHispanic: 23\nNot Hispanic: 388","Asian: 48\nWhite: 48\nBlack: 41\nOther (including American Indian,\nAlaska Native, Native Hawaiian or\nOther Pacific Islander): 83\nHispanic: 88"],["Considered\nsubgroups","Age","",""],["","Age < 55: A(53), B(182),\nC(239), D(96)\n55 ≤ Age < 65: A(26),\nB(115), C(129), D(38)\nAge ≥ 65: A(34), B(138),\nC(83), D(14)","Age < 55: A(21), B(73),\nC(103), D(37)\n55 ≤ Age < 65: A(14), B(59),\nC(52), D(4)\nAge ≥ 65: A(15), B(68),\nC(45), D(8)","Age < 55: A(9), B(44), C(118),\nD(37)\n55 ≤ Age < 65: A(15), B(73),\nC(41), D(9)\nAge ≥ 65: A(18), B(83), C(41),\nD(4)"],["","Race","",""],["","Asian: A(2), B(52), C(61),\nD(17)\nWhite: A(59), B(176),\nC(137), D(34)","Asian: A(0), B(2), C(2), D(2)\nWhite: A(42), B(163),\nC(159), D(37)","Asian: A(1), B(31), C(28), D(8)\nWhite: A(11), B(17), C(21), D(7)\nBlack: A(8), B(21), C(16), D(3)\nOther: A(9), B(59), C(48), D(10)"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p12-t0","doc_id":"K243685","page_num":12,"bbox":[72.66,80.99,539.94,406.88],"n_rows":7,"n_cols":4,"columns":["","Black: A(20), B(32),\nC(34), D(9)\nOther: A(1), B(3), C(4),\nD(0)","Black: A(3), B(16), C(18),\nD(3)\nHispanic: A(1), B(8), C(12),\nD(2)\nNot Hispanic: A(39), B(160),\nC(148), D(41)","Hispanic: A(5), B(13), C(11), D(3)"],"rows":[["","Black: A(20), B(32),\nC(34), D(9)\nOther: A(1), B(3), C(4),\nD(0)","Black: A(3), B(16), C(18),\nD(3)\nHispanic: A(1), B(8), C(12),\nD(2)\nNot Hispanic: A(39), B(160),\nC(148), D(41)","Hispanic: A(5), B(13), C(11), D(3)"],["","Data provenance","",""],["","USA: A(85), B(269),\nC(241), D(63)\nEU: A(28), B(169),\nC(214), D(86)","USA: A(50), B(200), C(200),\nD(50)","USA: A(38), B(155), C(139),\nD(31)\nEU: A(4), B(45), C(61), D(19)"],["","Breast thickness","",""],["","Thick. < 50: A(7), B(80),\nC(145), D(87)\n50 ≤ Thick. < 70: A(43),\nB(272), C(252), D(58)\nThick. ≥ 70: A(63), B(86),\nC(58), D(4)","Thick. < 50: A(4), B(25),\nC(47), D(28)\n50 ≤ Thick. < 70: A(25),\nB(104), C(115), D(20)\nThick. ≥ 70: A(21), B(71),\nC(38), D(2)","Thick. < 50: A(33), B(135),\nC(142), D(46)\n50 ≤ Thick. < 70: A(4), B(51),\nC(49), D(3)\nThick. ≥ 70: A(5), B(14), C(9),\nD(1)"],["Truthing\nprocess","The reference standard for breast density value was established by majority rule among the\nassessment of 5 breast radiologists with at least 10 years of experience in breast imaging\ninterpretation.","",""],["Independence\nof test data\nfrom training\ndata","Data sources are separated into the training/tuning group and the test group. Sources in the\ntraining/tuning group may only be used for model training and tuning. Sources in the test group\nmay only be used for external validation of the model’s performances on unseen data (i.e., from\nsources entirely left out during training and tuning).\nData used for the standalone performance testing only belongs to the test group.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p12-t1","doc_id":"K243685","page_num":12,"bbox":[72.66,557.35,539.94,711.34],"n_rows":3,"n_cols":3,"columns":["","Modification #1\nSupport of Siemens Mammograms\n(retraining required)","Modification #2\nPre-training of backbone using\nUnsupervised Machine Learning (as\nopposed to Supervised Machine\nLearning)"],"rows":[["","Modification #1\nSupport of Siemens Mammograms\n(retraining required)","Modification #2\nPre-training of backbone using\nUnsupervised Machine Learning (as\nopposed to Supervised Machine\nLearning)"],["Data used for\ndevelopment and\nmodifications,\nrepresenting the\ntarget population","Siemens, FFDM\nSiemens, 2DSM.","No new data collection is foreseen for this\nchange."],["Statistics tests for\nprimary\nobjective","Superiority in standalone performance for density assignment of MammoScreen BD\ncompared to a pre-determined reference value (Kappa = 0.85).\nreference",""]],"caption_candidate":"anticipated modifications.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243685-p13-t0","doc_id":"K243685","page_num":13,"bbox":[72.26,80.77,539.88,462.91],"n_rows":6,"n_cols":2,"columns":["Primary\nendpoints","Quadratically weighted Cohen’s kappa between the density assessment of\nMammoScreen and the established ground truth"],"rows":[["Primary\nendpoints","Quadratically weighted Cohen’s kappa between the density assessment of\nMammoScreen and the established ground truth"],["Acceptance\ncriteria","Lower bound of the 95% confidence interval > 0.85"],["Validation\nactivities","Upon demonstration of the superiority through the standalone performance testing,\nchanges will be documented in a minor release amending:\n• The Algorithm test protocol and results documents\n• The Device Label, including the User Guide"],["Communication\nplan","Upcoming updates are communicated through advisory notices sent by email at least\n2 weeks before deployment. Advisory notices contain:\n• The new version identification,\n• A summary of the change,\n• The schedule for the application of the change,\n• Statement that the Support team will contact the customer and/or user for\nacceptance, training or scheduling of the change, if necessary,\n• A link to access the updated User Guide, where the changes mentioned are\nreflected.\nUsers may decide to opt out of the update during the 2-week notice period.\nMammoScreen BD does not have its own user interface. The new labelling for\nMammoScreen BD will be available on the compatible third-party software once the\nupdate is activated."],["Characterization\nof the device\nbefore and after\nimplementation\nof changes","The device will be accessible to more centers, and thus to more woman. Prevents\nobsolescence of MammoScreen BD. Better representation of breast tissue diversity\nleading to higher overall performances and a better generalization on unseen data."],["Monitoring,\ndetection, and\nresponse to\ndeviations in\ndevice\nperformance","Therapixel monitors customer sites. The distribution of breast density assessment\nobtained is determined on a representative screening distribution, which serves as a\nReference Distribution. Device monitoring compares breast density assessment in\nreal conditions to the reference distribution and alerts of any deviations. The\ninvestigation can result in a field-safety notice, a Medical Device Report."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243702-p7-t0","doc_id":"K243702","page_num":7,"bbox":[111.64,534.61,543.92,688.78],"n_rows":5,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 & A1:2012 C1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons. Text) [Incl. AMD2:2021] Medical electrical\nequipment - Part 1: General requirements for basic safety and essential\nperformance (IEC 60601-1:2005, MOD)","",""],["IEC 60601-1-2","","","IEC60601-1-2:2014 [Including AMD 1:2021] , Medical electrical\nequipment - Part 1-2: General requirements for basic safety and essential\nperformance - EMC","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.1 2015, Medical electrical equipment – Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -","",""]],"caption_candidate":"with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243702-p8-t0","doc_id":"K243702","page_num":8,"bbox":[111.62,92.42,543.94,208.22],"n_rows":4,"n_cols":2,"columns":["","Part 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems"],"rows":[["","Part 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems"],["ISO10993-1","AAMI / ANSI / ISO 10993-1:2018, Biological evaluation of medical\ndevices – Part 1: Evaluation and testing within a risk management process"],["ISO14971","ISO 14971:2019, Medical devices - Application of risk management to\nmedical devices"],["NEMA UD 2-2004","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for\nDiagnostic Ultrasound Equipment Revision 3"]],"caption_candidate":"SAMSUNG MEDISON CO., LTD. Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p8-t0","doc_id":"K243762","page_num":8,"bbox":[70.47,94.39,532.78,713.26],"n_rows":22,"n_cols":6,"columns":["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],"rows":[["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],["","","","Base","",""],["","","","Tools(V6.6)","",""],["","","","(K221677)","",""],["","","","(Primary","",""],["","","","predicate","",""],["","","","device)","",""],["Classification\nName","System,\nImage\nProcessing,\nRadiological","System,\nImage\nProcessing,\nRadiological","","","Same"],["Regulatory\nNumber","892.2050","892.2050","","","Same"],["Product Code","QIH, LLZ","LLZ","","","Same"],["Classification","Class II","Class II","","","Same"],["Review Panel","Radiology","Radiology","","","Same"],["Decision Date","-","November 10,\n2022","","","Predicate device is\ncleared"],["2D Viewing","Yes","Yes","","","Same"],["Image Storing\n(DICOM SCP)","Yes","Yes","","","Same"],["Image\nCommunication\n(DICOM SCU)","Yes","Yes","","","Same"],["DICOM\nInterface\n(SCP/SCU)","Yes","Yes","","","Same"],["Printing\n(DICOM SCU)","Yes","Yes","","","Same"],["Measurements\n(2D and 3D)","Yes","Yes","","","Same"],["Annotations -\nStandardized and\nFree Text","Yes","Yes","","","Same"],["Reporting","Yes","Yes","","","Same"],["Cine","Yes","Yes","","","Same"]],"caption_candidate":"Table 1 Device Features and Technical Characteristics Comparison Matrix","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p9-t0","doc_id":"K243762","page_num":9,"bbox":[70.47,72.16,532.77,715.78],"n_rows":15,"n_cols":6,"columns":["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],"rows":[["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],["","","","Base","",""],["","","","Tools(V6.6)","",""],["","","","(K221677)","",""],["","","","(Primary","",""],["","","","predicate","",""],["","","","device)","",""],["Volume\nRendering and\n3D Viewing","Yes","Yes","","","Same"],["MPR\n・ orthogonal /\noblique /\ncurved\nMulti-Planar\nReconstructio\nns (MPR),\n・ Sector and\nrectangular\nshape MPR\nimage\nviewing\n・ MPR for\ndental images\n・ Multiple MPR\nimages along\nan object\n(Slicer)","Yes","Yes","","","Same"],["Maximum,\nAverage,\nMinimum\nIntensity\nProjection","Yes","Yes","","","Same"],["4D viewing","Yes","Yes","","","Same"],["Image fusion","Yes","Yes","","","Same"],["Surface\nrendering","Yes","Yes","","","Same"],["Image\nsubtraction (3D)","Yes","Yes","","","Same"],["Time-density\ndistribution","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p10-t0","doc_id":"K243762","page_num":10,"bbox":[70.47,72.16,532.78,718.06],"n_rows":19,"n_cols":6,"columns":["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],"rows":[["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],["","","","Base","",""],["","","","Tools(V6.6)","",""],["","","","(K221677)","",""],["","","","(Primary","",""],["","","","predicate","",""],["","","","device)","",""],["General image\ndata management\nand\nadministration\ntools","Yes","Yes","","","Same"],["Segmentation","Yes","Yes","","","Some new segmentation\napplications are added\nand implemented using\nthe same deep learning\nmethod called as “Fully\nConvolutional\nNetwork”."],["Path definition","Yes","Yes","","","Same"],["Boundary\ndetection","Yes","Yes","","","Same"],["CT PET fusion","Yes","Yes","","","Same"],["ADC image\nviewing (MRI)","Yes","Yes","","","Same"],["Virtual\nEndoscopic\nSimulator","Yes","Yes","","","Same"],["Diffusion-weight\ned MRI Data\nAnalysis","Yes","Yes","","","Same"],["Delayed\nEnhancement\nImage Viewing","Yes","Yes","","","Same"],["Dual Energy\nimage viewing","Yes","Yes","","","Same"],["PixelShine","Yes","Yes","","","Same"],["Pancreas\nAnalysis","Yes","No","","","Added new feature.\nNote: The new feature"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p11-t0","doc_id":"K243762","page_num":11,"bbox":[70.48,72.16,532.77,718.9],"n_rows":10,"n_cols":6,"columns":["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],"rows":[["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],["","","","Base","",""],["","","","Tools(V6.6)","",""],["","","","(K221677)","",""],["","","","(Primary","",""],["","","","predicate","",""],["","","","device)","",""],["","","","","","Pancreas Analysis is the\nsimilar to Contour\nProtégéAI (“Reference\nDevice”), which was\ncleared by CDRH via\nK213976 on\n02/03/2022. This added\nnew feature does not\nraise different questions\nof safety and\neffectiveness."],["Rectal Analysis","Yes","No","","","Added new feature.\nNote: The new feature\nRectal Analysis is the\nsimilar to Contour\nProtégéAI (“Reference\nDevice”), which was\ncleared by CDRH via\nK213976 on\n02/03/2022. This added\nnew feature does not\nraise different questions\nof safety and\neffectiveness."],["Segmentation\nViewer","Yes","No","","","Added new feature.\nNote: The new feature\nSegmentation Tools is\nthe similar to Contour\nProtégéAI (“Reference\nDevice”), which was\ncleared by CDRH via\nK213976 on\n02/03/2022. This added\nnew feature does not"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p12-t0","doc_id":"K243762","page_num":12,"bbox":[70.47,72.16,532.77,693.7],"n_rows":12,"n_cols":6,"columns":["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],"rows":[["Device\nParameters","Synapse 3D\nBase Tools\n(V7.0) (This\nsubmission)","","Synapse 3D","","Comparison"],["","","","Base","",""],["","","","Tools(V6.6)","",""],["","","","(K221677)","",""],["","","","(Primary","",""],["","","","predicate","",""],["","","","device)","",""],["","","","","","raise different questions\nof safety and\neffectiveness."],["Post-reconstructi\non request","Yes","No","","","Added new feature.\nNote:\nThe new feature\nPost-reconstruction\nrequest is the same as\nthe feature available on\nthe SCENARIA View\n(“Reference Device”),\nwhich was cleared by\nCDRH via K190841 on\n09/13/2019. This added\nnew feature does not\nraise different questions\nof safety and\neffectiveness."],["Spatial\nreproduction\ndisplay","Yes","No","","","Added new feature.\nNote:\nThe purpose of this\nfunction is the\nvisualization of organs,\netc. Therefore, this\nadded feature does not\nraise different questions\nof safety and\neffectiveness."],["Product\nAvailability","Software\nProduct","Software\nProduct","","","Same"],["Hardware\nPlatform","Windows PC","Windows PC","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p14-t0","doc_id":"K243762","page_num":14,"bbox":[114.63,217.7,490.29,317.57],"n_rows":6,"n_cols":6,"columns":["","Region","","","Number of cases",""],"rows":[["","Region","","","Number of cases",""],["US_East","","","295","",""],["US_Midwest","","","175","",""],["US_Southeast","","","185","",""],["US_Southwest","","","73","",""],["US_Nouthwest","","","4","",""]],"caption_candidate":"regions for the performance testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p14-t1","doc_id":"K243762","page_num":14,"bbox":[114.63,366.65,490.29,709.54],"n_rows":5,"n_cols":9,"columns":["","Items","","","Subitems","","","Number of cases",""],"rows":[["","Items","","","Subitems","","","Number of cases",""],["Total 1086","","","","","","","",""],["Sex Men 672\nWomen 414","","","","","","","",""],["Age 22-34 years old 23\n35-64 years old 484\n65-120 years old 579\nManufacturer SIEMENS 507\nGE 288\nPHILIPS 260\nCANON(TOSHIBA) 22\nFUJIFILM(HITACHI) 9","","","","","","","",""],["SliceThickness 0.0-0.99mm 86\n1.0-1.24mm 134\n1.25-1.49mm 49\n1.5-1.99mm 6\n2.0-2.49mm 91\n2.5-2.99mm 56\n3.0-3.99mm 450\n4.0-4.99mm 121\n≽5.0 93","","","","","","","",""]],"caption_candidate":"following table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p15-t0","doc_id":"K243762","page_num":15,"bbox":[114.39,137.3,517.65,719.26],"n_rows":34,"n_cols":5,"columns":["","","Number","","DICE (Average)"],"rows":[["","","Number","","DICE (Average)"],["","","of cases","",""],["Duodenum (CT)","30 0.85","","",""],["Stomach (CT)","30 0.96","","",""],["Lung section (Left S1S2) (CT)","30 0.92","","",""],["Lung section (Left S3) (CT)","30 0.88","","",""],["Lung section (Left S4) (CT)","30 0.75","","",""],["Lung section (Left S5) (CT)","30 0.81","","",""],["Lung section (Left S6) (CT)","30 0.9","","",""],["Lung section (Left S8) (CT)","30 0.85","","",""],["Lung section (Left S9) (CT)","30 0.73","","",""],["Lung section (Left S10) (CT)","30 0.87","","",""],["Lung section (Right S1) (CT)","30 0.89","","",""],["Lung section (Right S2) (CT)","30 0.89","","",""],["Lung section (Right S3) (CT)","30 0.91","","",""],["Lung section (Right S4) (CT)","30 0.88","","",""],["Lung section (Right S5) (CT)","30 0.85","","",""],["Lung section (Right S6) (CT)","30 0.9","","",""],["Lung section (Right S7) (CT)","30 0.8","","",""],["Lung section (Right S8) (CT)","30 0.84","","",""],["Lung section (Right S9) (CT)","30 0.71","","",""],["Lung section (Right S10) (CT)","30 0.83","","",""],["Pancreas section (Body) (CT)","29 0.91","","",""],["Pancreas section (Head) (CT)","29 0.95","","",""],["Pancreas section (Tail) (CT)","29 0.99","","",""],["Spleen (CT)","35 0.95","","",""],["Pancreas duct (CT)","29 0.74","","",""],["Pancreas (CT)","30 0.86","","",""],["ROI (CT)*","29 0.85","","",""],["Liver section (S1) (CT)","31 0.99","","",""],["Liver section (S2) (CT)","31 0.99","","",""],["Liver section (S3) (CT)","31 0.97","","",""],["Liver section (S4) (CT)","31 0.97","","",""],["Liver section (S5) (CT)","31 0.92","","",""]],"caption_candidate":"follows.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p16-t0","doc_id":"K243762","page_num":16,"bbox":[114.39,72.48,517.65,295.49],"n_rows":13,"n_cols":2,"columns":["Liver section (S6) (CT)","31 0.94"],"rows":[["Liver section (S6) (CT)","31 0.94"],["Liver section (S7) (CT)","31 0.98"],["Liver section (S8) (CT)","31 0.97"],["Gall bladder (CT)","37 0.92"],["Bronchus (CT)","30 0.87"],["Lung lobe (Left Lower) (CT)","30 0.99"],["Lung lobe (Left Upper) (CT)","30 0.99"],["Lung lobe (Right Lower) (CT)","30 0.99"],["Lung lobe (Right Middle) (CT)","30 0.97"],["Lung lobe (Right Upper) (CT)","30 0.99"],["Pulmonary Arteries (CT)","30 0.83"],["Pulmonary Veins (CT)","30 0.85"],["Pancreas vessel (CT)","30 0.9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243762-p16-t1","doc_id":"K243762","page_num":16,"bbox":[114.39,312.84,517.65,705.22],"n_rows":22,"n_cols":5,"columns":["","","Number of","","DICE (Average)"],"rows":[["","","Number of","","DICE (Average)"],["","","cases","",""],["Prostate (MRI)","30 0.9","","",""],["Rectal ROI (tumor) (MRI)*","27 0.75","","",""],["Ureter (T2) (MRI)","33 0.63","","",""],["Bladder (MRI)","35 0.93","","",""],["Pelvis (MRI)","34 0.94","","",""],["Seminal vesicle (MRI)","32 0.7","","",""],["Ureter (T1Dynamic) (MRI)","33 0.76","","",""],["Prostate tumor (DWI) (MRI)*","36 0.65","","",""],["Prostate tumor (T2) (MRI)*","39 0.6","","",""],["Kidney tumor (MRI)*","31 0.88","","",""],["Left Kidney (MRI)","31 0.97","","",""],["Right Kidney (MRI)","31 0.98","","",""],["ROI (MRI)*","133 0.72","","",""],["Rectal muscularis propria\n(MRI)","32 0.91","","",""],["Mesorectum (MRI)","32 0.9","","",""],["Pelvic vessel (Artery) (MRI)","30 0.81","","",""],["Pelvic vessel (Vein) (MRI)","30 0.8","","",""],["Kidney vessel (Artery) (MRI)","32 0.92","","",""],["Kidney vessel (Vein) (MRI)","32 0.86","","",""],["Pelvic nerve (MRI)","30 0.7","","",""]],"caption_candidate":"Pancreas vessel (CT) 30 0.9","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243769-p7-t0","doc_id":"K243769","page_num":7,"bbox":[72.04,303.89,522.95,731.16],"n_rows":12,"n_cols":5,"columns":["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],"rows":[["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],["","EQUIVALENCE","","",""],["","COMPARISON TABLE","","",""],["Regulation","","","892.1600 – Angiographic\nX-ray System","892.1600 – Angiographic\nX-ray System"],["Product Code","","","QHA (Class 2) – X-ray\nAngiographic Imaging\nBased Coronary Vascular\nSimulation Software","QHA (Class 2) – X-ray\nAngiographic Imaging\nBased Coronary Vascular\nSimulation Software"],["Associated Product Code","","","LLZ","LLZ"],["Image modality","","","XA","XA"],["Input format","","","DICOM","DICOM"],["Patient study browser\n(used to select the patient\nstudy of interest)","","","Yes","Yes"],["Import study from PACS","","","Yes","Yes"],["Automated series loading","","","Yes","Yes"],["Interactive image handling\n(incl. windowing, zooming,\npanning, filtering, window-\nlevel)","","","Yes","Yes"]],"caption_candidate":"predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243769-p8-t0","doc_id":"K243769","page_num":8,"bbox":[72.03,85.88,522.95,695.86],"n_rows":14,"n_cols":5,"columns":["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],"rows":[["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],["","EQUIVALENCE","","",""],["","COMPARISON TABLE","","",""],["Cine loop review with\ncontrols for speed, and\nframe-by-frame review.","","","Yes","Yes"],["ECG display\n(used for ECG signal display\nin synchrony with the review\nof the XA images)","","","Yes","Yes"],["ISO center calibration\n(provided by the\nmanufacturer of the X-ray\nacquisition equipment)","","","Yes","Yes"],["Possibility to edit or delete an\nexisting analysis","","","Yes","Yes"],["Multiple analyses possible on\na single image","","","Yes","Yes"],["Report facility","","","Yes","Yes"],["Export results to PACS","","","Yes","Yes"],["Audit Trail","","","Yes","Yes"],["Guided workflow supporting\nstep-by-step analysis","","","Yes","Yes"],["Selection of the angiographic\nseries to be used in the\nanalysis","","","Selection is now\nsupported by an AI/ML\nmodel and manual\ncorrection","Only supported manual\nselection"],["Selection of the\ndetermination of the start\nand end points of the vessel\nto be analyzed","","","Selection is now\nsupported by an AI/ML\nmodel and manual\ncorrection","Only supported manual\nselection"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243769-p9-t0","doc_id":"K243769","page_num":9,"bbox":[72.06,85.88,522.93,416.71],"n_rows":5,"n_cols":5,"columns":["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],"rows":[["","SUBSTANTIAL","","SUBJECT DEVICE:\nQFR (K243769)","PREDICATE DEVICE:\nQANGIO XA 3D (K182611)"],["","EQUIVALENCE","","",""],["","COMPARISON TABLE","","",""],["Determination of the ED\nframe within the series to be\nused","","","Selection is now\nsupported by a\ncombination of an AI/ML\nmodel and an analytical\nalgorithm using the ECG\ndata and manual\ncorrection","Only supported manual\nselection"],["Determination of start and\nend frame for flow velocity\ncalculation","","","Automatic determination\nof the start and end\nframe is now supported\nby an analytical\nalgorithm based on\ntraditional image\nprocessing techniques or\nmanual indication","Only supported manual\nindication of the start and\nend frame"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243779-p6-t0","doc_id":"K243779","page_num":6,"bbox":[72.86,395.0,540.62,681.73],"n_rows":4,"n_cols":3,"columns":["","Proposed Device: Bunkerhill AAQ","Predicate Device: Briefcase"],"rows":[["","Proposed Device: Bunkerhill AAQ","Predicate Device: Briefcase"],["","Algorithm","Quantification (K230534)"],["","",""],["Intended use /\nIndications for\nuse","Bunkerhill AAQ is a radiological image\nprocessing system software indicated for\nuse in the analysis of CT exams with or\nwithout contrast, that include the L1 – L5\nregion of the abdominal aorta, in adults\naged 22 and older.\nThe device is intended to assist\nappropriately trained medical specialists\nby providing the user with the maximum\naxial abdominal aortic diameter\nmeasurement of cases that include the\nabdominal aorta. Bunkerhill AAQ is\nindicated to evaluate normal and\naneurysmal abdominal aortas and is not\nintended to evaluate post- operative\naortas.","BriefCase-Quantification is a\nradiological image management and\nprocessing system software indicated for\nuse in the analysis of CT exams with\ncontrast, that include the abdominal\naorta, in adults or transitional\nadolescents aged 18 and older.\nThe device is intended to assist\nappropriately trained medical specialists\nby providing the user with the maximum\nabdominal aortic axial diameter\nmeasurement of cases that include the\nabdominal aorta (M-AbdAo) BriefCase-\nQuantification is indicated to evaluate\nnormal and aneurysmal abdominal aortas\nand is not intended to evaluate post-\noperative aortas."]],"caption_candidate":"A table comparing the intended use of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243779-p7-t0","doc_id":"K243779","page_num":7,"bbox":[72.86,71.4,540.62,300.85],"n_rows":4,"n_cols":3,"columns":["","Proposed Device: Bunkerhill AAQ","Predicate Device: Briefcase"],"rows":[["","Proposed Device: Bunkerhill AAQ","Predicate Device: Briefcase"],["","Algorithm","Quantification (K230534)"],["","",""],["","The Bunkerhill AAQ results are not\nintended to be used on a stand-alone basis\nfor clinical decision-making or otherwise\npreclude clinical assessment of cases.\nThese measurements are unofficial, are\nnot final, and are subject to change after\nreview by a qualified interpreting\nphysician. For final clinically approved\nmeasurements, please refer to the official\nradiology report. Clinicians are\nresponsible for viewing full images per\nthe standard of care.","The BriefCase-Quantification results are\nnot intended to be used on a stand-alone\nbasis for clinical decision-making or\notherwise preclude clinical assessment of\ncases. These measurements are\nunofficial, are not final, and are subject\nto change after review by a radiologist.\nFor final clinically approved\nmeasurements, please refer to the official\nradiology report. Clinicians are\nresponsible for viewing full images per\nthe standard of care."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243779-p8-t0","doc_id":"K243779","page_num":8,"bbox":[72.8,71.4,540.46,580.42],"n_rows":13,"n_cols":4,"columns":["","Proposed Device:","Predicate Device:","Summary"],"rows":[["","Proposed Device:","Predicate Device:","Summary"],["","Bunkerhill AAQ","Briefcase Quantification",""],["","Algorithm","(K230534)",""],["","","",""],["Product code","QIH","QIH","Same"],["Regulation number","21 CFR §892. 2050","21 CFR §892. 2050","Same"],["Modality","Computed tomography\n(CT)","Computed tomography\n(CT)","Same"],["Image format","DICOM","DICOM","Same"],["Supported CT scan","CT exams with or\nwithout contrast that\ninclude the abdominal\naorta","CT exams with\ncontrast that include\nthe abdominal aorta","Similar"],["Diameter\nmeasurement","Yes","Yes","Same"],["Algorithm","Artificial intelligence\nalgorithm with database\nof images.","Artificial intelligence\nalgorithm with database of\nimages.","Same"],["Interference with\nstandard workflow","No","No","Same"],["Output","Output can be optionally\nor on-demand be\ninserted into the\nradiology report;\nproduces a preview\nimage annotated with\nthe maximum axial\ndiameter measurement.\nThe original, unmarked\nseries remains available\nin the PACS as\nwell.","Produces a preview image\nannotated with the\nmaximum axial diameter\nmeasurement. The original,\nunmarked series remains\navailable in the PACS as\nwell.","Similar"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243779-p9-t0","doc_id":"K243779","page_num":9,"bbox":[72.8,71.4,540.45,592.2],"n_rows":12,"n_cols":4,"columns":["","Proposed Device:","Predicate Device:","Summary"],"rows":[["","Proposed Device:","Predicate Device:","Summary"],["","Bunkerhill AAQ","Briefcase Quantification",""],["","Algorithm","(K230534)",""],["","","",""],["Structure","-Bunkerhill AAQ, is\nhosted on a cloud server,\nanalyzes applicable CT\nimages that are acquired\non CT scanner that are\nforwarded to Bunkerhill\nAAQ.\n- The results of the\nanalysis are exported\nin DICOM format, and\nare sent to a PACS\ndestination for review\nby medical specialists,\nto assist in the","-BriefCase-Quantificat\nion, is hosted on a\ncloud server, analyzes\napplicable CT images\nthat are acquired on\nCT scanner that are\nforwarded to\nBriefCase-Quantificati\non.\n- The results of the\nanalysis are exported\nin DICOM format, and\nare sent to a PACS\ndestination for review","Same"],["","measurement of the\nabdominal aorta.","by medical specialists,\nto assist in the\nmeasurement of the\nabdominal aorta.",""],["Type of\nInterpretation","Adjunctive information","Adjunctive information","Same"],["Intended User","Appropriately trained\nmedical specialists","Appropriately trained\nmedical specialists","Same"],["Patient population","Patients aged 18 years\nand above","Patients above the age of 18","Same"],["Anatomical\nlocation","Abdominal aorta","Abdominal aorta","Same"],["Intended location","Medical facility","Medical facility","Same"],["Rx or OTC","Rx","Rx","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p6-t0","doc_id":"K243793","page_num":6,"bbox":[248.0,486.96,566.2,617.27],"n_rows":8,"n_cols":4,"columns":["","Classification Description","21 CFR §","Product Code"],"rows":[["","Classification Description","21 CFR §","Product Code"],["","Primary","",""],["","System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],["","Secondary","",""],["","System, imaging, pulsed echo,\nultrasonic","892.1560","IYO"],["","Transducer, ultrasonic, diagnostic","892.1570","ITX"],["","Medical image management and\nprocessing system","892.2050","QIH"],["","Diagnostic Intravascular Catheter","870.1200","OBJ*"]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p10-t0","doc_id":"K243793","page_num":10,"bbox":[35.32,89.52,767.12,511.53],"n_rows":31,"n_cols":4,"columns":["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],"rows":[["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],["Feature","Feature: R-Trigger","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","","",""],["","Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac\nPediatric, Cerebral Vascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative\n(Vascular), Intraoperative (Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Ophthalmic, Other: Urology,\nPediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,\nTesticle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.","Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac\nPediatric, Cerebral Vascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative\n(Vascular), Intraoperative (Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Ophthalmic, Other: Urology,\nPediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,\nTesticle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.","Identical to predicate"],["","","",""],["","","",""],["","","",""],["Indications for Use","","",""],["","","",""],["","Trained healthcare professionals\nIntended for sonographers, physicians, and biomedical\nengineers who operate and maintain your product.\nBefore use of the system and user information, the user\nmust be familiar with ultrasound techniques. Sonography\ntraining and clinical procedures are not included in the User\nManual or with the EPIQ Series Diagnostic Ultrasound\nSystem.","Trained healthcare professionals\nIntended for sonographers, physicians, and biomedical\nengineers who operate and maintain your product.\nBefore use of the system and user information, the user\nmust be familiar with ultrasound techniques. Sonography\ntraining and clinical procedures are not included in the User\nManual or with the EPIQ Series Diagnostic Ultrasound\nSystem.","Identical to predicate"],["","","",""],["","","",""],["","","",""],["Intended Users","","",""],["","","",""],["Intended User","Clinics, hospitals, and clinical point-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical point-of-care for diagnosis of\npatients.","Identical to predicate"],["Environment","","",""],["","","",""],["USA FDA","Class II","Class II","Identical to predicate"],["Classification","","",""],["","","",""],["Primary Product","IYN","IYN","Identical to predicate"],["Code","","",""],["","","",""],["Primary Regulation","System, Imaging, Pulsed Doppler, Ultrasonic","System, Imaging, Pulsed Doppler, Ultrasonic","Identical to predicate"],["Name","","",""],["","","",""],["Primary Regulation","21 CFR 892.1550","21 CFR 892.1550","Identical to predicate"],["Number","","",""],["","","",""]],"caption_candidate":"Table 1: Comparison to Predicate for introduction of R-Trigger onto EPIQ","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p11-t0","doc_id":"K243793","page_num":11,"bbox":[35.32,66.48,767.12,502.05],"n_rows":33,"n_cols":4,"columns":["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],"rows":[["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],["Feature","Feature: R-Trigger","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","","",""],["Secondary Product","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","Identical to predicate"],["Codes","","",""],["","","",""],["","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Identical to predicate"],["Secondary","","",""],["Regulation Name","","",""],["","","",""],["Secondary","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","Identical to predicate"],["Regulation Number","","",""],["","","",""],["Reusable- Systems","Yes","Yes","Identical to predicate"],["and Transducers","","",""],["","","",""],["Duration of use","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical to predicate"],["","","",""],["Device Track","Track 3","Track 3","Identical to predicate"],["","","",""],["","The R-Trigger AI software feature on Philips EPIQ and\nAffiniti Ultrasound System is intended to support detection\nof R-wave peak (R-trigger) as an input to AutoStrain and\nAutoMeasure applications, as well as other cardiac clinical\napplications. The R-trigger algorithm is planned to be\nimplemented as workflow enhancement to the AutoStrain\n(previously cleared by FDA; K190913) and AutoMeasure\n(previously cleared by FDA; K211597) applications on EPIQ\nand Affiniti Ultrasound Systems in the VM13 software\nrelease.","The EPIQ ultrasound systems currently detects R-Trigger\nevents by processing a patient’s ECG signal using the on-\ncart physio board.","Similar. In the subject device, the R-Trigger algorithm will\nprovide an additional method of determining R-Trigger\nevents for a patient’s acquired ultrasound clip.\nCurrently, the Ultrasound System requires an ECG signal,\nwhich is processed by the on-cart physio board, to detect R-\nTrigger events in the cardiac cycle. These detected events\nare used as input into various cardiac clinical applications.\nIn the subject device, the R-Trigger algorithm will serve as a\nback-up for R-Trigger event detection.\nDetecting events from the ECG signal on the system will still\nbe the preferred method. In case the ECG signal is not\nusable or not available, the new R-Trigger algorithm will\ndetect the events.\nFrom a user perspective, their only difference is that they\nwill be able to use certain cardiac clinical applications on\nacquired clips which do not have a usable ECG signal in the\nsubject device. Otherwise, there are not able changes\nvisible to the user as both methods work in the background."],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["Application","","",""],["Description","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p12-t0","doc_id":"K243793","page_num":12,"bbox":[35.32,101.04,767.12,523.05],"n_rows":31,"n_cols":4,"columns":["","Affiniti Series Diagnostic Ultrasound System","Affiniti Series Diagnostic Ultrasound System",""],"rows":[["","Affiniti Series Diagnostic Ultrasound System","Affiniti Series Diagnostic Ultrasound System",""],["Feature","Feature: R-Trigger","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","","",""],["","Abdominal, Cardiac Adult, Cardiac Other (Fetal), Cardiac\nPediatric, Cerebral Vascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative\n(Vascular), Intraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal (Superficial), Other: Urology,\nPediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,\nTesticle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.","Abdominal, Cardiac Adult, Cardiac Other (Fetal), Cardiac\nPediatric, Cerebral Vascular, Cephalic (Adult), Cephalic\n(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative\n(Vascular), Intraoperative (Cardiac), Musculoskeletal\n(Conventional), Musculoskeletal (Superficial), Other:\nUrology, Pediatric, Peripheral Vessel, Small Organ (Breast,\nThyroid, Testicle), Transesophageal (Cardiac), Transrectal,\nTransvaginal, Lung.","Identical to predicate"],["","","",""],["","","",""],["","","",""],["Indications for Use","","",""],["","","",""],["","Trained healthcare professionals\nIntended for sonographers, physicians, and biomedical\nengineers who operate and maintain your product.\nBefore use of the system and user information, the user\nmust be familiar with ultrasound techniques. Sonography\ntraining and clinical procedures are not included in the User\nManual or with the EPIQ Series Diagnostic Ultrasound\nSystem.","Trained healthcare professionals\nIntended for sonographers, physicians, and biomedical\nengineers who operate and maintain your product.\nBefore use of the system and user information, the user\nmust be familiar with ultrasound techniques. Sonography\ntraining and clinical procedures are not included in the User\nManual or with the EPIQ Series Diagnostic Ultrasound\nSystem.","Identical to predicate"],["","","",""],["","","",""],["","","",""],["Intended Users","","",""],["","","",""],["Intended User","Clinics, hospitals, and clinical point-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical point-of-care for diagnosis of\npatients.","Identical to predicate"],["Environment","","",""],["","","",""],["USA FDA","Class II","Class II","Identical to predicate"],["Classification","","",""],["","","",""],["Primary Product","IYN","IYN","Identical to predicate"],["Code","","",""],["","","",""],["Primary Regulation","System, Imaging, Pulsed Doppler, Ultrasonic","System, Imaging, Pulsed Doppler, Ultrasonic","Identical to predicate"],["Name","","",""],["","","",""],["Primary Regulation","21 CFR 892.1550","21 CFR 892.1550","Identical to predicate"],["Number","","",""],["","","",""]],"caption_candidate":"Table 2: Comparison to Predicate for introduction of R-Trigger onto Affiniti","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p13-t0","doc_id":"K243793","page_num":13,"bbox":[35.32,66.48,767.12,493.04],"n_rows":33,"n_cols":4,"columns":["","Affiniti Series Diagnostic Ultrasound System","Affiniti Series Diagnostic Ultrasound System",""],"rows":[["","Affiniti Series Diagnostic Ultrasound System","Affiniti Series Diagnostic Ultrasound System",""],["Feature","Feature: R-Trigger","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","","",""],["Secondary Product","ITX\nIYO\nQIH","ITX\nIYO\nQIH","Identical to predicate"],["Codes","","",""],["","","",""],["","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nAutomated Radiological Image\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nAutomated Radiological Image\nProcessing Software","Identical to predicate"],["Secondary","","",""],["Regulation Name","","",""],["","","",""],["Secondary","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 892.2050","Identical to predicate"],["Regulation Number","","",""],["","","",""],["Reusable- Systems","Yes","Yes","Identical to predicate"],["and Transducers","","",""],["","","",""],["Duration of use","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical to predicate"],["","","",""],["Device Track","Track 3","Track 3","Identical to predicate"],["","","",""],["","The R-Trigger AI software feature on Philips EPIQ and\nAffiniti Ultrasound System is intended to support detection\nof R-wave peak (R-trigger) as an input to AutoStrain and\nAutoMeasure applications, as well as other cardiac clinical\napplications. The R-trigger algorithm is planned to be\nimplemented as workflow enhancement to the AutoStrain\n(previously cleared by FDA; K190913) and AutoMeasure\n(previously cleared by FDA; K211597) applications on EPIQ\nand Affiniti Ultrasound Systems in the VM13 software\nrelease.","The Affiniti ultrasound systems currently detects R-Trigger\nevents by processing a patient’s ECG signal using the on-\ncart physio board.","Similar. In the subject device, the R-Trigger algorithm will\nprovide an additional method of determining R-Trigger\nevents for a patient’s acquired ultrasound clip.\nCurrently, the Ultrasound System requires an ECG signal,\nwhich is processed by the on-cart physio board, to detect R-\nTrigger events in the cardiac cycle. These detected events\nare used as input into various cardiac clinical applications.\nIn the subject device, the R-Trigger algorithm will serve as a\nback-up for R-Trigger event detection.\nDetecting events from the ECG signal on the system will still\nbe the preferred method. In case the ECG signal is not\nusable or not available, the new R-Trigger algorithm will\ndetect the events.\nFrom a user perspective, their only difference is that they\nwill be able to use certain cardiac clinical applications on\nacquired clips which do not have a usable ECG signal in the\nsubject device. Otherwise, there are not able changes\nvisible to the user as both methods work in the background."],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["Application","","",""],["Description","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p14-t0","doc_id":"K243793","page_num":14,"bbox":[144.63,595.62,432.29,705.96],"n_rows":8,"n_cols":2,"columns":["","Subjects"],"rows":[["","Subjects"],["",""],["","(mean ± SD (n) (min, max) or % (n/N) )"],["Age (years)","59.00±16.66 (3964);(18.00;100.00)"],["Gender",""],["Male","48.56% (1925/3964)"],["Female","51.44% (2039/3964)"],["Race",""]],"caption_candidate":"Table 1: AutoMeasure Subjects’ Demographics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p15-t0","doc_id":"K243793","page_num":15,"bbox":[144.62,66.36,432.33,170.04],"n_rows":6,"n_cols":2,"columns":["Asian","2.70% (107/3964)"],"rows":[["Asian","2.70% (107/3964)"],["Black or African\nAmerican","45.18% (1791/3964)"],["White","30.25% (1199/3964)"],["Other/Mixed","21.85% (866/3964)"],["Unknown","0.03% (1/3964)"],["BMI (kg/ m2)","28.85±7.06 (3964);(12.40;63.60)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p15-t1","doc_id":"K243793","page_num":15,"bbox":[144.62,208.68,432.33,406.92],"n_rows":13,"n_cols":2,"columns":["","Subjects"],"rows":[["","Subjects"],["",""],["","(mean ± SD (n) (min, max) or % (n/N) )"],["Age (years)","48.87±18.60 (82) (20.00, 86.00)"],["Gender",""],["Male","45.12% (37/82)"],["Female","54.88% (45/82)"],["Race",""],["Asian","24.39% (20/82)"],["Black or African\nAmerican","7.32% (6/82)"],["White","36.59% (30/82)"],["Other/Mixed","31.71% (26/82)"],["BMI (kg/ m2)","24.37±3.47 (82) (16.40, 33.80)"]],"caption_candidate":"Table 2: AutoStrain Subjects’ Demographics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p15-t2","doc_id":"K243793","page_num":15,"bbox":[144.62,445.68,432.33,643.92],"n_rows":13,"n_cols":2,"columns":["","Subjects"],"rows":[["","Subjects"],["",""],["","(mean ± SD (n) (min, max) or % (n/N) )"],["Age (years)","58.51±17.00 (1894); (18.00;100.00)"],["Gender",""],["Male","47.31% (896/1894)"],["Female","52.69% (998/1894)"],["Race",""],["Asian","3.27% (62/1894)"],["Black or African\nAmerican","42.77% (810/1894)"],["White","31.36% (594/1894)"],["Other/Mixed","22.60% (428/1894)"],["BMI (kg/ m2)","28.51±6.81(1894); (12.40;69.50)"]],"caption_candidate":"Table 3: R-trigger Time Stamp Subjects’ Demographics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p16-t0","doc_id":"K243793","page_num":16,"bbox":[44.54,156.36,568.05,702.48],"n_rows":22,"n_cols":7,"columns":["","Order of","","","","Measurement",""],"rows":[["","Order of","","","","Measurement",""],["","","Outcomes","","","","Acceptance"],["Endpoint","Hypothesis","","Lower LoA (95% CI)","Upper LoA (95% CI)","Type",""],["","","Comparison","","","","Criteria"],["","Testing","","","","",""],["","","","","","",""],["","","","","","",""],["Endpoint 1:\nR-trigger","1","R-wave peak time\nstamp","-58.06ms\n(-59.34, -56.78)","69.69ms\n(68.41, 70.97)","Time Stamp","[-99.5ms,\n99.5ms]"],["Endpoint 3:\nAutoStrain*","N/A","EF","-6.64%\n(-7.60%, -5.68%)","6.52%\n(5.56%, 7.49%)","EF","[20%, 20%]"],["","N/A","GLS","-5.25%\n(-5.72%, -4.79%)","4.63%\n(4.16%, 5.10%)","GLS","[7%, 7%]"],["Endpoint 2:\nAutoMeasure","4","MV E Vel","-12.00 %\n(-13.17%, -10.84 %)","12.98 %\n(11.81 %, 14.14%)","Pw/cw Doppler\nvelocity","[-25%, 25%]"],["","5","LVIDd","-9.33 %\n(-9.84%, -8.81 %)","9.33 %\n(8.82 %, 9.85%)","Distance","[-30%, 30%]"],["","6","RVLd","-8.60 %\n(-9.57 %, -7.62 %)","5.35 %\n(4.38 %, 6.33%)","Distance","[-30%, 30%]"],["","7","TR VTI","-12.26 %\n(-15.15 %, -9.37 %)","17.44 %\n(14.54 %, 20.33%)","Pw/cw Doppler\nVTI","[-29%, 29%]"],["","8","PV VTI","-13.73 %\n(-15.87 %, -11.59 %)","17.91 %\n(15.78 %, 20.05%)","Pw/cw Doppler\nVTI","[-29%, 29%]"],["","9","LA Diameter a.p.\n(PLAX)","-8.05 %\n(-9.41 %, -6.70 %)","9.39 %\n(8.03 %, 10.74%)","Distance","[-30%, 30%]"],["","10","MV A Vel","-15.95 %\n(-17.44 %, -14.47 %)","14.69 %\n(13.20 %, 16.17%)","Pw/cw Doppler\nvelocity","[-25%, 25%]"],["","11","Ao SV diam","-7.60 %\n(-8.42 %, -6.77 %)","9.30 %\n(8.47 %, 10.12%)","Distance","[-30%, 30%]"],["","12","LVOT diam","-9.84 %\n(-10.51 %, -9.16 %)","9.55 %\n(8.87 %, 10.22%)","Distance","[-30%, 30%]"],["","13","LVOT VTI","-10.97 %\n(-12.66 %, -9.28 %)","14.41 %\n(12.72 %, 16.09%)","Pw/cw Doppler\nVTI","[-29%, 29%]"],["","14","AoR Diam(2D) = Ao\nAnnlus diam","-13.02 %\n(-14.60 %, -11.44 %)","13.00 %\n(11.42 %, 14.58%)","Distance","[-30%, 30%]"],["","15","RV S'(l)","-16.11 %\n(-17.59 %, -14.63 %)","17.97 %\n(16.49 %, 19.45%)","TDI velocity","[-28%, 28%]"]],"caption_candidate":"Table 4: Relative Bland-Altman Analysis for R-trigger AI-based workflow vs Ground Truth","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p17-t0","doc_id":"K243793","page_num":17,"bbox":[44.54,66.48,568.06,714.12],"n_rows":25,"n_cols":7,"columns":["","Order of","","","","Measurement",""],"rows":[["","Order of","","","","Measurement",""],["","","Outcomes","","","","Acceptance"],["Endpoint","Hypothesis","","Lower LoA (95% CI)","Upper LoA (95% CI)","Type",""],["","","Comparison","","","","Criteria"],["","Testing","","","","",""],["","","","","","",""],["","","","","","",""],["","16","LV A'(s)","-15.85 %\n(-18.53 %, -13.17 %)","17.53 %\n(14.85 %, 20.22%)","TDI velocity","[-28%, 28%]"],["","17","TR Vmax","-9.66 %\n(-11.95 %, -7.38 %)","13.83 %\n(11.54 %, 16.12%)","Pw/cw Doppler\nvelocity","[-25%, 25%]"],["","18","AV VTI","-12.85 %\n(-14.06 %, -11.64 %)","14.77 %\n(13.56 %, 15.98%)","Pw/cw Doppler\nVTI","[-29%, 29%]"],["","19","Ao Asc diam","-9.63 %\n(-10.49 %, -8.76 %)","10.64 %\n(9.77 %, 11.50%)","Distance","[-30%, 30%]"],["","20","TAPSE","-19.65 %\n(-22.85 %, -16.44 %)","18.23 %\n(15.02 %, 21.43%)","Distance\n(TAPSE/MAPSE)","[-34%, 34%]"],["","21","Ao STJ diam","-7.61 %\n(-8.26 %, -6.95 %)","8.83 %\n(8.17 %, 9.49%)","Distance","[-30%, 30%]"],["","22","RA Volume (A4Cs)","-27.08 %\n(-29.52 %, -24.63 %)","32.89 %\n(30.45 %, 35.33%)","Volume Contour","[-46%, 46%]"],["","23","LA Vol (A2Cs)","-21.72 %\n(-23.61 %, -19.82 %)","20.47 %\n(18.58 %, 22.37%)","Volume Contour","[-46%, 46%]"],["","24","LA Vol (A4Cs)","-23.80 %\n(-25.88 %, -21.73 %)","21.51 %\n(19.44 %, 23.58%)","Volume Contour","[-46%, 46%]"],["","25","LV A'(l)","-17.60 %\n(-20.15 %, -15.06 %)","21.44 %\n(18.90 %, 23.98%)","TDI velocity","[-28%, 28%]"],["","26","LV E'(s)","-19.45 %\n(-21.25 %, -17.65 %)","20.89 %\n(19.08 %, 22.69%)","TDI velocity","[-28%, 28%]"],["","27","LV E'(l)","-19.21 %\n(-21.04 %, -17.37 %)","21.62 %\n(19.78 %, 23.45%)","TDI velocity","[-28%, 28%]"],["","28","LVPWd","-14.13 %\n(-14.89 %, -13.36 %)","13.59 %\n(12.82 %, 14.35%)","Distance Short","[-40%, 40%]"],["","29","MV Dec. Time","-24.95 %\n(-26.87 %, -23.03 %)","23.62 %\n(21.70 %, 25.54%)","Doppler Time\nInterval","[-35%, 35%]"],["","30","IVSd","-15.82 %\n(-16.65 %, -15.00 %)","14.21 %\n(13.38 %, 15.04%)","Distance Short","[-40%, 40%]"],["","31","TV Ann diam ant-post","-14.91 %\n(-17.46 %, -12.37 %)","14.74 %\n(12.20 %, 17.29%)","Distance","[-30%, 30%]"],["","32","LVIDs","-13.31 %\n(-14.27 %, -12.34 %)","12.98 %\n(12.02 %, 13.95%)","Distance","[-30%, 30%]"],["","33","RVDd base (RVD1)","-12.60 %\n(-13.27 %, -11.92 %)","12.68 %\n(12.00 %, 13.36%)","Distance","[-30%, 30%]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p18-t0","doc_id":"K243793","page_num":18,"bbox":[44.6,66.48,567.98,172.32],"n_rows":9,"n_cols":7,"columns":["","Order of","","","","Measurement",""],"rows":[["","Order of","","","","Measurement",""],["","","Outcomes","","","","Acceptance"],["Endpoint","Hypothesis","","Lower LoA (95% CI)","Upper LoA (95% CI)","Type",""],["","","Comparison","","","","Criteria"],["","Testing","","","","",""],["","","","","","",""],["","","","","","",""],["","34","RVDd mid (RVD2)","-20.45 %\n(-21.80 %, -19.11 %)","16.86 %\n(15.51 %, 18.21%)","Distance","[-30%, 30%]"],["","35","MR VTI","-14.36 %\n(-15.90 %, -12.82 %)","17.04 %\n(15.50 %, 18.58%)","Pw/cw Doppler\nVTI","[-29%, 29%]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p18-t1","doc_id":"K243793","page_num":18,"bbox":[106.61,225.96,507.74,279.48],"n_rows":7,"n_cols":4,"columns":["Order of","","Pearson's correlation",""],"rows":[["Order of","","Pearson's correlation",""],["Hypothesis","Outcomes Comparison","","Acceptance Criteria"],["","","coefficient (r) (95% CI)",""],["Testing","","",""],["","","",""],["2","EF","0.892 (0.853,0.922)","LCB >0.8"],["3","GLS","0.992 (0.990,0.994)","LCB >0.8"]],"caption_candidate":"Table 5: Pearson’s Correlation for R-trigger AI-based workflow vs ground Truth","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243793-p19-t0","doc_id":"K243793","page_num":19,"bbox":[67.2,86.88,754.68,416.16],"n_rows":6,"n_cols":7,"columns":["Age\n[years]","2D ALAX\nmean std\n[ms] [ms] N","2D PLAX\nmean std\n[ms] [ms] N","CWD\nmean std\n[ms] [ms] N","PWD\nmean std\n[ms] [ms] N","TDI\nmean std\n[ms] [ms] N","Mmode\nmean std\n[ms] [ms] N"],"rows":[["Age\n[years]","2D ALAX\nmean std\n[ms] [ms] N","2D PLAX\nmean std\n[ms] [ms] N","CWD\nmean std\n[ms] [ms] N","PWD\nmean std\n[ms] [ms] N","TDI\nmean std\n[ms] [ms] N","Mmode\nmean std\n[ms] [ms] N"],["< 30\n[30, 40)\n[40, 50)\n[50, 60)\n[60, 70)\n[70, 80)\n>= 80","22,3608 29,7713 464\n15,5169 27,0963 590\n18,7653 42,5653 534\n14,7195 34,6072 816\n19,0654 32,6803 946\n20,1622 33,3848 962\n18,0821 50,1052 266","20,4984 29,4916 276\n21,4149 33,2061 452\n12,1518 29,6201 442\n14,7519 28,2333 522\n21,1265 32,6609 786\n18,4896 33,6052 520\n9,7551 41,2727 248","-3,2113 21,604 770\n-6,3028 26,6602 1116\n-4,4 28,6318 1656\n-3,2839 37,7419 1770\n-3,0363 29,7499 2346\n-4,6104 32,7933 2030\n3,206 28,1476 760","-5,9128 22,2969 522\n0,1642 23,4811 888\n-4,0744 21,9616 1046\n-0,8162 31,5805 1188\n-3,9253 42,291 1110\n-3,5902 33,4302 1252\n12,4942 42,5802 306","2,4613 22,485 708\n1,1274 26,0283 912\n5,3757 32,6808 992\n5,6068 36,7938 1240\n4,6591 38,8012 1546\n11,6894 32,1315 1534\n21,6097 40,9872 472","0,1614 23,7552 60\n-8,6466 24,2302 62\n-6,1834 13,7949 82\n-8,4599 25,889 118\n8,0672 40,9966 118\n-\n10,0727 35,7687 138\n10,9446 21,0323 18"],["Total 4578 3246 10448 6312 7404 596","","","","","",""],["BMI\n[kg/m²]","2D ALAX\nmean std\n[ms] [ms] N","2D PLAX\nmean std\n[ms] [ms] N","CWD\nmean std\n[ms] [ms] N","PWD\nmean std\n[ms] [ms] N","TDI\nmean std\n[ms] [ms] N","Mmode\nmean std\n[ms] [ms] N"],["< 18.5\n[18.5,\n25.0)\n[25.0,\n30.0)\n[30.0,\n35.0)\n[35.0,\n40.0)\n>= 40.0","19,5505 28,3718 210\n18,0509 35,7453 1608\n20,3118 32,0369 1410\n15,5626 34,5971 744\n15,7476 38,8853 442\n21,3035 44,2133 164","18,7511 29,4978 148\n19,8614 36,0952 1038\n18,4808 32,469 930\n15,4517 32,3496 592\n14,4673 25,3248 374\n11,6543 25,0333 164","-6,0925 25,9067 430\n-4,0071 29,1289 3714\n-2,3525 27,6045 2718\n-0,9768 31,9309 1900\n-4,5722 36,7892 1148\n-\n10,5029 40,7001 538","-0,3086 23,7911 194\n-3,3768 28,6633 2404\n0,4405 31,5529 1714\n-1,3386 24,6602 1004\n-5,1252 35,0944 624\n-3,3229 58,5367 372","-3,2873 27,7559 192\n4,6081 36,3333 2778\n9,7347 32,522 2196\n8,0421 34,47 1170\n7,2621 31,0496 742\n6,2726 31,0726 326","-\n49,2954 28,5332 12\n-8,5554 38,4066 230\n2,7052 26,8123 170\n-5,0901 23,6583 60\n-5,0401 12,8211 80\n12,1638 16,8775 44"],["Total 4578 3246 10448 6312 7404 596","","","","","",""]],"caption_candidate":"Table 7: Performance results of the different age – and BMI groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243794-p6-t0","doc_id":"K243794","page_num":6,"bbox":[251.32,480.84,566.0,611.16],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Medical image management and\nprocessing system","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ","",""]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243794-p7-t0","doc_id":"K243794","page_num":7,"bbox":[251.32,67.32,566.0,197.64],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Medical image management and\nprocessing system","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243794-p15-t0","doc_id":"K243794","page_num":15,"bbox":[142.35,608.88,430.03,707.64],"n_rows":7,"n_cols":2,"columns":["","Subjects"],"rows":[["","Subjects"],["","(mean ± SD (n) (min, max) or % (n/N) )"],["Age (years)","59.00±16.66 (3964);(18.00;100.00)"],["Gender",""],["Male","48.56% (1925/3964)"],["Female","51.44% (2039/3964)"],["Race",""]],"caption_candidate":"The subjects whose TTE clips were used in the study were:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243794-p16-t0","doc_id":"K243794","page_num":16,"bbox":[142.32,67.2,430.08,162.48],"n_rows":6,"n_cols":2,"columns":["Asian","2.70% (107/3964)"],"rows":[["Asian","2.70% (107/3964)"],["Black or African American","45.18% (1791/3964)"],["White","30.25% (1199/3964)"],["Other/Mixed","21.85% (866/3964)"],["Unknown","0.03% (1/3964)"],["BMI (kg/ m2)","28.85±7.06 (3964);(12.40;63.60)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p6-t0","doc_id":"K243808","page_num":6,"bbox":[70.85,134.4,524.43,296.43],"n_rows":19,"n_cols":3,"columns":["1.","Submitter","3"],"rows":[["1.","Submitter","3"],["","",""],["2.","Device identification","3"],["","",""],["3.","Predicate device","3"],["","",""],["4.","Device description","4"],["","",""],["5.","Intended use/Indication for use","5"],["","",""],["6.","Substantial equivalence Discussion","5"],["","",""],["7.","Performance data summary","11"],["","",""],["a.","Software verification and validation testing","11"],["","",""],["b.","Bench Testing","12"],["","",""],["8.","CONCLUSION","13"]],"caption_candidate":"1. Submitter 3","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243808-p7-t0","doc_id":"K243808","page_num":7,"bbox":[70.73,125.42,526.5,284.79],"n_rows":2,"n_cols":2,"columns":["Submitter","AZmed\n10 Rue d’Uzès\n75002 Paris, France\nPhone: +33 6 72 19 04 19"],"rows":[["Submitter","AZmed\n10 Rue d’Uzès\n75002 Paris, France\nPhone: +33 6 72 19 04 19"],["Contact person","Anthony JOSEPH\nQARA Associate\n10 Rue d’Uzès\n75002 Paris, France\nPhone: +33 6 72 19 04 19\nMail: anthony@azmed.co"]],"caption_candidate":"Submitted date: 2025-02-17","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p7-t1","doc_id":"K243808","page_num":7,"bbox":[65.55,340.13,541.3,445.5],"n_rows":2,"n_cols":6,"columns":["Name of\nthe Device","Common\nor Usual\nName","Regulatory\nsection","Classification","Product\nCode","Panel"],"rows":[["Name of\nthe Device","Common\nor Usual\nName","Regulatory\nsection","Classification","Product\nCode","Panel"],["Rayvolve\nPTX-PE","Rayvolve","21 CFR\n892.2080","Class II","QFM","90\n(Radiology)"]],"caption_candidate":"2. Device identification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p7-t2","doc_id":"K243808","page_num":7,"bbox":[65.55,514.42,517.67,594.5],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Product Name","510K Number"],"rows":[["Manufacturer","Product Name","510K Number"],["Lunit, Inc.","Lunit INSIGHT CXR\nTriage","K211733"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p9-t0","doc_id":"K243808","page_num":9,"bbox":[70.67,375.49,568.3,766.5],"n_rows":10,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["Device Name","Lunit INSIGHT CXR Triage","Rayvolve","N/A"],["Manufacturer","Lunit, Inc.","AZmed","N/A"],["510 (k) #","K211733","K243808","N/A"],["Regulation\nNumber","21 CFR 892.2080","21 CFR 892.2080","Same"],["Class","II","II","Same"],["Product Code","QFM","QFM","Same"],["Device Panel","Radiology","Radiology","Same"],["Level of\nConcern","Moderate","Moderate","Same"],["Intended use\n/ Indications\nfor use","Lunit INSIGHT CXR Triage\nis a radiological\ncomputer-assisted triage\nand notification software\nthat analyzes adult chest\nX-ray images for the\npresence of pre-specified\nsuspected critical findings","Rayvolve PTX-PE is a\nradiological\ncomputer-assisted triage\nand notification software\nthat analyzes chest x-ray\nimages (Postero-Anterior\n(PA) or Antero-Posterior\n(AP)) of patients 18 years","Equivalent,\nslight precision\non the\nintended\npatient\npopulation (see\nthe line\n‘intended"]],"caption_candidate":"of operation vice and the cited predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p10-t0","doc_id":"K243808","page_num":10,"bbox":[70.62,127.75,568.37,765.5],"n_rows":4,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["","(pleural effusion and/or\npneumothorax). Lunit\nINSIGHT CXR Triage uses\nan artificial intelligence\nalgorithm to analyze images\nfor features suggestive of\ncritical findings and provides\ncase-level output available\nin the PACS/workstation for\nworklist prioritization or\ntriage. As a passive\nnotification for\nprioritization-only software\ntool within standard of care\nworkflow, Lunit INSIGHT\nCXR Triage does not send\na proactive alert directly to\nthe appropriately trained\nmedical specialists. Lunit\nINSIGHT CXR Triage is not\nintended to direct attention\nto specific portions of an\nimage. Its results are not\nintended to be used on a\nstand-alone basis for clinical\ndecision-making.","of age or older for the\npresence of pre-specified\nsuspected critical findings\n(pleural effusion and/or\npneumothorax).\nRayvolve PTX-PE uses an\nartificial intelligence\nalgorithm to analyze the\nimages for features\nsuggestive of critical\nfindings and provides\nstudy-level output available\nin DICOM Node Servers\nfor worklist prioritization or\ntriage.\nAs a passive notification for\nprioritization-only software\ntool within the standard of\ncare workflow, Rayvolve\nPTX-PE does not send a\nproactive alert directly to a\ntrained medical specialist.\nRayvolve PTX-PE is not\nintended to direct attention\nto specific portions of an\nimage. Its results are not\nintended to be used on a\nstand-alone basis for\nclinical decision-making.","patient\npopulation for\nthe\njustification)\nand for other\nDICOM\nstorage\nplatforms the\nsubject device.\nOther DICOM\nstorage\nplatforms are\nequivalent to\nPACS.\nNone of those\nprecisions\nraise new\nquestions of\nsafety or\neffectiveness"],["Intended user","Appropriately trained\nmedical specialists who are\nqualified to interpret chest\nradiographs","Healthcare professionals","Equivalent.\nHealthcare\nprofessionals\nare qualified to\ninterpret chest\nradiographs"],["Intended\npatient\npopulation","Adults","18 years of age or older","Equivalent:\nOur dataset\ncontains\nimages for\npatients of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p11-t0","doc_id":"K243808","page_num":11,"bbox":[70.62,127.75,568.37,769.5],"n_rows":5,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["","","","18-21 years\nold.\nThe\nperformance\nresults (see\nAppendix 25)\nshows that the\nperformances\nof Rayvolve\nPTX-PE for\npatients\nbetween 18\nand 21 years\nold are\nequivalent to\nthe results\nobtained for\npatients older\nthan 21 years\nold. So, it\ndoesn’t raise\nnew questions\nof safety or\neffectiveness,\nand maintain\nthe same level\nof performance\nthan the\npredicated\ndevice"],["Targeted\nclinical\ncondition and\nanatomy","Pleural effusion,\npneumothorax\nChest/Lung","Pleural effusion,\npneumothorax\nChest/Lung","Same"],["Radiological\nimages\nformat","DICOM","DICOM","Same"],["Image\nmodality","Frontal chest X-ray","Postero-Anterior (PA) or\nAntero-Posterior (AP)\nchest X-ray","Equivalent.\nInclusion of the\norientation of\nthe image"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p12-t0","doc_id":"K243808","page_num":12,"bbox":[70.62,127.75,568.37,757.5],"n_rows":4,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["","","","acquisition, but\nthe\nperformance\ntesting (see\nappendix 25)\nhas\ndemonstrated\nthat Rayvolve\nPTX-PE\nachieves\nequivalent\naccuracy on\nboth AP and\nPA views, so\nconsidering\nboth views\ndoesn’t raise\nnew questions\nof safety or\neffectiveness,\nand maintain\nthe same level\nof performance\nthan the\npredicated\ndevice"],["Algorithm for\npre-specified\ncritical\nfindings\ndetection","AI algorithm designed to\ndetect pleural effusion and\npneumothorax in chest\nX-ray images.\nLunit INSIGHT CXR Triage\nuses a vendor agnostic\nalgorithm compatible with\nDICOM chest X-ray images.","AI algorithm designed to\ndetect pleural effusion and\npneumothorax in chest\nX-ray images.\nRayvolve PTX-PE uses a\nvendor agnostic algorithm\ncompatible with DICOM\nchest X-ray images.","Same"],["Where\ngenerated\nresults are\nstored","PACS/Workstation","PACS/Workstation","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p13-t0","doc_id":"K243808","page_num":13,"bbox":[70.62,127.75,568.37,759.5],"n_rows":3,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["Computationa\nl platform","Lunit INSIGHT CXR Triage\nis designed as a software\nmodule that can be\ndeployed on several\ncomputing and X-ray\nimaging platforms such as\nradiological imaging\nequipment, PACS, On\nPremise or On Cloud.","Rayvolve PTX-PE is\ndesigned as a software\nmodule that can be\ndeployed on several\ncomputing and X-ray\nimaging platforms such as\nradiological imaging\nequipment, PACS, On\nPremise or On Cloud.","Same"],["Device output\nin case of\npositive\ndetection","When deployed on other\nradiological imaging\nequipment Lunit INSIGHT\nCXR Triage automatically\nruns after image acquisition\nand prioritizes and displays\nthe analysis result through\nthe worklist interface of\nPACS/workstation.\nNo markup on original\nimage. Secondary capture\nof the finding.\nUpon image acquisition\nfrom other radiological\nimaging equipment (e.g.\nX-ray systems), an\non-device, tehcnologist\nnotification indicating which\ncases were flagged by Lunit\nINSIGHT CXR Triage in\nPACS, is generated 15\nminutes after interpretation\nby the user.\nThe on device notification is\ncontextual and does not\nprovide any diagnostic","When deployed on other\nradiological imaging\nequipment Rayvolve\nPTX-PE automatically\nruns after image\nacquisition and prioritizes\nand displays the analysis\nresult through the worklist\ninterface of\nPACS/workstation.\nNo markup on the original\nimage. Secondary capture\nof the device will indicate\nthe presence of findings\nsuspicious of\npneumothorax or pleural\neffusion.\nUpon image acquisition\nfrom other radiological\nimaging equipment (e.g,\nX-ray systems), a passive\nnotification indicating which\nstudies were flagged by\nRayvolve PTX-PE is\ngenerated.\nThe notification is","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p14-t0","doc_id":"K243808","page_num":14,"bbox":[70.62,127.75,568.37,763.5],"n_rows":5,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["","information. It is not\nintended to inform any\nclinical decision,\nprioritization, or action to the\ntechnologist.","contextual and does not\nprovide any diagnostic\ninformation. It is not\nintended to inform any\nclinical decision,\nprioritization, or action.",""],["Notification\n(i.e., recipient\ntiming and\nmeans of\nnotification)","Passive notification.\nImages with suspicion of\npleural effusion and/or\npneumothorax are flagged\nin PACS/workstation","Passive notification.\nImages with suspicion of\npneumothorax and/or\npleural effusion are flagged\nin\nPACS/workstation/DICOM\nviewer.","Equivalent:\nDICOM\nviewers are the\nsoftware that\nallow to open\nthe Dicom files\non the\nworkstations, it\ndoesn’t raise\nnew questions\nof safety or\neffectiveness"],["Performance\nlevel - Timing\nof notification","The average time taken by\nthe device to analyze the\nstudy and send a\nnotification to the worklist is\n20,76 seconds for pleural\neffusion and 20.45 seconds\nfor pneumothorax","The average time taken by\nthe device to analyze the\nstudy and send a\nnotification to the worklist is\n19.56 seconds for pleural\neffusion and 19.43\nseconds for pneumothorax","Equivalent\nThe\nperformance\nresults of the\nsubject device\nare slightly\nbetter than the\nresults for the\npredicate\ndevice, so it\ndoesn’t raise\nnew questions\nof safety or\neffectiveness."],["Performance\nlevel -\naccuracy of\nclassification","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.9686 (95% CI:\n[0.9547,0.9824])\nSensitivity 89.86% (95% CI:\n[86.72, 93.00])","Pleural Effusion\nROC AUC > 0.95\nAUC: 0.9830 (95% CI:\n[0.9778, 0.9880])\nSensitivity 0.9134 (95% CI:\n[0.8874, 0.9339])","Equivalent\nThe\nperformance\nresults of the\nsubject device\nare slightly\nbetter than the"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243808-p15-t0","doc_id":"K243808","page_num":15,"bbox":[70.62,127.75,568.37,363.5],"n_rows":2,"n_cols":4,"columns":["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],"rows":[["Comparison\nto predicate\ndevice","Lunit INSIGHT CXR Triage\n- Predicate (K220164)","Rayvolve PTX-PE -\nSubject device 510(k) file","Comparison to\nthe predicate"],["","Specificity 93.48% (95% CI:\n[91.06, 95.91])\nPneumothorax\nROC AUC > 0.95\nAUC: 0.9630 (95% CI:\n[0.9521,0.9739])\nSensitivity 88.92% (95% CI:\n[85.60,92.24])\nSpecificity 90.51% (95% CI:\n[88.18,92.83])","Specificity 0.9448 (95% CI:\n[0.9239, 0.9339])\nPneumothorax\nROC AUC > 0.95\nAUC: 0.9857 (95% CI:\n[0.9809,0.9901])\nSensitivity 0.9379 (95% CI:\n[0.9127,0.9561])\nSpecificity 0.9178 (95% CI:\n[0.8911,0.9561])","results for the\npredicate\ndevice, so it\ndoesn’t raise\nnew questions\nof safety or\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243810-p5-t0","doc_id":"K243810","page_num":5,"bbox":[89.81,181.62,522.38,702.99],"n_rows":10,"n_cols":10,"columns":["1.(a)","Submitter\nAddress:","Brainlab Ltd.\n35 Efal Street\nPetach-Tikva, Israel 4951132","","","","","","",""],"rows":[["1.(a)","Submitter\nAddress:","Brainlab Ltd.\n35 Efal Street\nPetach-Tikva, Israel 4951132","","","","","","",""],["1.(b)","Manufacturer\nAddress:\nMfg. Phone:\nContact Person:\nDate:","Brainlab Ltd\n35 Efal Street\nPetach-Tikva, Israel 4951132\nTel.: +972-3-929-0929\nVeronika Kravtsov, RA Manager\nMay 8, 2025","","","","","","",""],["2.","Device &\nClassification:\nName:","Radiological Image Processing System –\nclassified as Class 2 QIH and LLZ\nRegulation Number 21 CFR 892.2050\nTraumaCad Neo (1.1)","","","","","","",""],["3.","Predicate Devices:","TraumaCad Neo (K231498)\nPeekMed Web (V1) (K222767)","","","","","","",""],["4.","Description:","TraumaCad Neo 1.1 allows surgeons to evaluate digital images\nwhile performing various pre-operative surgical planning and\nevaluation of images. This software application enables\nsurgeons to plan operations on screen, execute measurements,\nand facilitates a film-less orthopedic practice. TraumaCad Neo\n1.1 also allows post-operative review and assessment of X-ray\nimages obtained after the surgical procedure, with a feature for\nautomatic surgery outcome analysis of postoperative total hip\narthroplasty images. The program features an extensive\nregularly updated library of digital templates from leading\nmanufacturers. TraumaCad Neo supports DICOM and is\ncommunicating with Quentry®, a proprietary web-based cloud\nservice from Brainlab and with other healthcare data platforms,\nsuch as PACS solutions. It is through these healthcare data\nplatforms, where the medical staff can upload images to plan\ntheir expected results prior to the procedure to create a smooth\nsurgical workflow from start to finish.","","","","","","",""],["5.","Indications for\nUse:","","TraumaCad Neo is indicated for assisting healthcare","","","","","",""],["","","","professionals to analyze orthopedic conditions and to plan","","","","","",""],["","","","orthopedic procedures by overlaying on relevant radiological","","","","","",""],["","","","images visual information such as measurements and","","","","","",""],["","","","prosthesis templates. Clinical judgment and experience are","","","","","",""]],"caption_candidate":"Pursuant to CFR 807.92, the following 510(k) Summary is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243810-p6-t0","doc_id":"K243810","page_num":6,"bbox":[89.37,96.61,522.75,260.88],"n_rows":6,"n_cols":9,"columns":["","","","required to properly use the software. The software is no","","","t","",""],"rows":[["","","","required to properly use the software. The software is no","","","t","",""],["","","","intended for primary radiological image interpretation or","","","","",""],["","","","radiological appraisal. Device is not intended for use on mobile","","","","",""],["","","","phones.","","","","",""],["","","","","","","","",""],["6.","Comparison of\nTechnological\nCharacteristics:","With respect to technology and intended use, TraumaCad Neo\n1.1 is substantially equivalent to its predicate devices. Based\nupon the outcomes from the Risk Analysis and Performance\nTesting Evaluation, Brainlab Ltd. believes that the modification\nof TraumaCad Neo 1.0 (predicate device) which allows it to\nbecome TraumaCad Neo 1.1 does not raise additional safety or\nefficacy concerns. The following comparison tables depict the\nchanges.","","","","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243810-p8-t0","doc_id":"K243810","page_num":8,"bbox":[98.73,114.41,426.96,453.81],"n_rows":31,"n_cols":3,"columns":["","Submitted Device:","Predicate D"],"rows":[["","Submitted Device:","Predicate D"],["","",""],["Features/ Characteristics","TraumaCad Neo 1.1","TraumaCad"],["","",""],["Template support from","Yes","Yes"],["manufacturers","",""],["","",""],["Permits Template","Yes","Yes"],["Rotation","",""],["","",""],["Pre-Operative Planning","Yes","Yes"],["","",""],["Post Operative Review","Yes","Yes"],["","",""],["Patient Contacting","No","No"],["","",""],["Control of Life","No","No"],["Sustaining Devices","",""],["","",""],["Healthcare professional","Yes","Yes"],["intervention for","",""],["interpretation of images","",""],["","",""],["Software Delivery","Web and locally","Web"],["","",""],["Post Operative","Automatically (AI) for","Manually for"],["Landmark Placement","Hip images, manually","modules"],["","for other anatomies",""],["","modules",""],["","",""],["510(k) #","Pending","K231498"]],"caption_candidate":"Submitted Device: Predicate Device:","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243831-p6-t0","doc_id":"K243831","page_num":6,"bbox":[92.34,136.12,518.98,757.14],"n_rows":23,"n_cols":3,"columns":["1.","Submitter","3"],"rows":[["1.","Submitter","3"],["","",""],["2.","Device identification","3"],["","",""],["3.","Predicate device","3"],["","",""],["4.","Device description","4"],["","",""],["5.","Intended use/Indication for use","4"],["","",""],["6.","Substantial equivalence Discussion","4"],["","",""],["7.","Performance data","5"],["","",""],["a.","Software verification and validation testing","5"],["","",""],["b.","Bench Testing","5"],["","",""],["c.","Clinical data","5"],["","",""],["8.","CONCLUSION","7"],["","",""],["","","Page2/9"]],"caption_candidate":"1. Submitter 3","well_formed":true,"extraction_settings":"text"}
{"table_id":"K243831-p7-t0","doc_id":"K243831","page_num":7,"bbox":[92.17,130.35,519.71,288.38],"n_rows":2,"n_cols":2,"columns":["Submitter","AZmedSAS\n10rued’Uzès\n75002Paris\nPhone:+33643315138"],"rows":[["Submitter","AZmedSAS\n10rued’Uzès\n75002Paris\nPhone:+33643315138"],["Contactpersonn","ChristelleBAILLE\nHeadofQARA\n10rued’Uzès\n75002Paris\nPhone:+33643315138\nMail:christelle@azmed.co"]],"caption_candidate":"Submitted date: 2025-03-24","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243831-p7-t1","doc_id":"K243831","page_num":7,"bbox":[87.35,340.22,534.85,416.22],"n_rows":2,"n_cols":6,"columns":["Nameofthe\nDevice","Commonor\nUsualName","Regulatory\nsection","Classification","Product\nCode","Panel"],"rows":[["Nameofthe\nDevice","Commonor\nUsualName","Regulatory\nsection","Classification","Product\nCode","Panel"],["RayvolveLN","Rayvolve","21CFR\n892.2070","ClassII","MYN","90(Radiology)"]],"caption_candidate":"2. Device identification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243831-p7-t2","doc_id":"K243831","page_num":7,"bbox":[87.35,481.84,519.71,555.43],"n_rows":2,"n_cols":4,"columns":["Manufacturer","BrandName","CommercialName","510KNumber"],"rows":[["Manufacturer","BrandName","CommercialName","510KNumber"],["Samsung\nElectronics Co.,\nLtd.","Auto Lung Nodule\nDetection","Auto Lung Nodule\nDetection","K201560"]],"caption_candidate":"follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243831-p8-t0","doc_id":"K243831","page_num":8,"bbox":[92.17,521.69,519.92,723.81],"n_rows":6,"n_cols":3,"columns":["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],"rows":[["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],["Device Name","Auto Lung Nodule\nDetection","Rayvolve"],["Manufacturer","Samsung Electronics Co.,\nLtd.","AZmed SAS"],["510 (k) #","K201560","K243831"],["Regulation Number","21 CFR 892.2070","21 CFR 892.2070"],["Class","II","II"]],"caption_candidate":"the cited predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243831-p9-t0","doc_id":"K243831","page_num":9,"bbox":[92.12,79.33,519.94,721.92],"n_rows":11,"n_cols":3,"columns":["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],"rows":[["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],["Regulation Description","Medical Image Analyser","Medical Image Analyser"],["Product Code","MYN","MYN"],["Device Panel","Radiology","Radiology"],["Level of Concern","Moderate","Moderate"],["Intended use /\nIndications for use","The Auto Lung Nodule\nDetection is\ncomputer-aided detection\nsoftware to identify and\nmark regions in relation to\nsuspected pulmonary\nnodules from 10 to 30 mm\nin size. It is designed to\naid the physician to review\nthe PA chest radiographs\nof adults as a second\nreader and be used as\npart of S-Station, which is\noperation software\ninstalled on Samsung\nDigital X-ray Imaging\nsystems. Auto Lung\nNodule Detection cannot\nbe used on the patients\nwho have lung lesions\nother than abnormal\nnodules.","Rayvolve LN is a\ncomputer-aided detection\nsoftware device to assist\nradiologists to identify and\nmark regions in relation to\nsuspected pulmonary\nnodules from 6 to 30mm\nsize. It is designed to aid\nradiologists in reviewing\nthe frontal (AP/PA) chest\nradiographs of patients of\n18 years of age or older,\nacquired on digital\nradiographic systems as a\nsecond reader and be\nused with any DICOM\nNode server. Rayvolve LN\nprovides adjunctive\ninformation only and is not\na substitute for the original\nchest radiographic image."],["Target population","Physician","Radiologists"],["Intended User Workflow","Device intended as a\nsecond-reader for\nphysicians interpreting\nchest radiographs","Device intended as a\nsecond-reader for\nphysicians interpreting\nchest radiographs"],["Intended patient\npopulation","Adult population","Patients 18 years of age\nor older"],["Image modality","X-ray","X-ray"],["Anatomical site","Chest","Chest"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243831-p10-t0","doc_id":"K243831","page_num":10,"bbox":[92.12,79.33,519.94,386.12],"n_rows":8,"n_cols":3,"columns":["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],"rows":[["Comparison to\npredicate device","Predicate - Auto Lung\nNodule Detection\n(K201560)","Rayvolve LN - Subject\ndevice 510(k) file"],["","",""],["Clinical findings","Lung Nodules on PAview\nChest X-rays","Lung Nodules on PA/AP\nview Chest X-rays"],["Machine learning\ntechnology","Machine learning","Supervised Deep learning"],["Input format","DICOM","DICOM"],["Output","ROI marked on the\nduplicated input\nimage","ROI marked on the\nduplicated input\nimage"],["Biocompatibility /\nelectromagnetic /\nmagnetic resonance /\nElectrical/mechanical /\nchemical / thermal /\nradiation/ steriliy safety","N/A, the device is a\nstandalone software/","N/A, the device is a\nstandalone software/"],["Reader workflow","Second reader workflow","Second reader workflow"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p5-t0","doc_id":"K243853","page_num":5,"bbox":[72.32,244.32,539.75,272.04],"n_rows":2,"n_cols":8,"columns":["","Regulation Number","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","Regulation Name","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","","","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p5-t1","doc_id":"K243853","page_num":5,"bbox":[72.32,503.36,539.75,614.56],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Clarius Bladder AI"],"rows":[["","Device Trade Name:","","Clarius Bladder AI"],["","510(k) Reference:","","K232257"],["","Manufacturer Name:","","Clarius Mobile Health Corp."],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Primary Product Code:","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p5-t2","doc_id":"K243853","page_num":5,"bbox":[72.32,655.52,539.75,711.04],"n_rows":4,"n_cols":4,"columns":["","Device Trade Name:","","AI-Rad Companion Prostate MR"],"rows":[["","Device Trade Name:","","AI-Rad Companion Prostate MR"],["","510(k) Reference:","","K193283"],["","Manufacturer Name:","","Siemens Medical Solutions USA Inc."],["","Regulation Name:","","Medical Image Management and Processing System"]],"caption_candidate":"Reference Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p6-t0","doc_id":"K243853","page_num":6,"bbox":[72.26,72.32,539.91,127.84],"n_rows":4,"n_cols":4,"columns":["","Device Classification Name:","","Automated Radiological Image Processing Software"],"rows":[["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Primary Product Code:","","QIH"],["","Regulation Number:","","21 CFR § 892.2050;"],["","Regulatory Class:","","Class II"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p6-t1","doc_id":"K243853","page_num":6,"bbox":[72.26,614.24,539.91,655.39],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducers","","C3 HD3; EC7 HD3"],"rows":[["","Clarius Ultrasound Transducers","","C3 HD3; EC7 HD3"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"K213436). Clarius Prostate AI is not a stand-alone software device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p8-t0","doc_id":"K243853","page_num":8,"bbox":[72.31,97.79,719.75,535.9],"n_rows":11,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Prostate AI","","Clarius Bladder AI","","AI-Rad Companion Prostate","",""],["","","","","","","MR","",""],["510(k) Holder/ Manufacturer","","Clarius Mobile Health Corp.","","Clarius Mobile Health Corp.","Siemens Medical Solutions\nUSA Inc.","","","Not applicable"],["","Submission Reference","Current Submission","","K232257","K193283","","","Not applicable"],["","Primary Product Code","QIH","","QIH","QIH","","","Same as predicate device."],["Device Classification Name","","Automated Radiological\nImage Processing Software","","Automated Radiological\nImage Processing Software","Automated Radiological\nImage Processing Software","","","Same as predicate device."],["Regulation Name","","Medical Image Management\nand Processing System","","Medical Image Management\nand Processing System","Medical Image Management\nand Processing System","","","Same as predicate device."],["","Regulation Number","21 CFR § 892.2050","","21 CFR § 892.2050","21 CFR § 892.2050","","","Same as predicate device."],["Intended Use","","Intended for use as an\nassistive tool during the\nacquisition and\ninterpretation of ultrasound\nimages utilizing an artificial\nintelligence/machine-\nlearning algorithm for\nsegmentation and\nmeasurement of anatomical\nstructures.","","Non-invasive processing of\nultrasound images using\nautomatic image\nsegmentation and\nmeasurement of anatomical\nstructures utilizing artificial\nintelligence/ machine\nlearning algorithms.","Non-invasive processing of\nMR images using automatic\nimage segmentation and\nmeasurement of anatomical\nstructures utilizing artificial\nintelligence algorithms.","","","Same as predicate device."],["Indications for Use","","Clarius Prostate AI is\nintended for semi-automatic\nmeasurements of prostate\nvolume on ultrasound data\nacquired by the Clarius\nUltrasound Scanner (i.e.,\ncurvilinear and endo-cavitary\nscanners). The user shall be\na healthcare professional\ntrained and qualified in\nultrasound. The user retains\nthe responsibility of","","Clarius Bladder AI is\nintended for semi-automatic\nnon-invasive measurements\nof bladder volume on\nultrasound data acquired by\nthe Clarius Ultrasound\nScanner (i.e., curvilinear and\nphased array scanners). The\nuser shall be a healthcare\nprofessional trained and\nqualified in ultrasound. The\nuser shall retain the ultimate","AI-Rad Companion Prostate\nMR is a post-processing\nimage analysis software that\nassists clinicians in viewing,\nmanipulating, analyzing and\nevaluating MR prostate\nimages for biopsy support.\nAI-Rad Companion Prostate\nMR provides the following\nfunctionalities:","","","Both the predicate and\nsubject device are indicated\nfor semi-automated\nmeasurements of ultrasound\nimage data using AI/ML-\nbased technology. Both\ndevices detect the\nanatomical structure,\nperform segmentation,\nperform measurements of\nthe structure, and perform\nmeasurement of the"]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p9-t0","doc_id":"K243853","page_num":9,"bbox":[72.31,72.35,719.74,532.9],"n_rows":7,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Prostate AI","","Clarius Bladder AI","","AI-Rad Companion Prostate","",""],["","","","","","","MR","",""],["","","confirming the validity of the\nmeasurements based on\nstandard practices and\nclinical judgment. Clarius\nProstate AI is intended for\nuse in adult male patients\nonly.","","responsibility of ascertaining\nthe measurements based on\nstandard practices and\nclinical judgment.","• Automatic segmentation\nand quantitative analysis of\nthe prostate gland\n• Manual annotation of\nrelevant findings\n• Presentation and export of\nresults for further processing\nand reporting","","","structure’s volume. Both the\npredicate and subject\ndevices are intended for use\nas an adjunctive ‘tool’ or aid\nby the user for the\ninterpretation of ultrasound\nimages and are not intended\nto replace clinical decision\nmaking. The minor\ndifferences in the indications\nfor use do not impact the\nsafety and effectiveness of\nthe subject device relative to\nthe predicate device."],["","Radiological application/\nSupported modality","Ultrasound","","Ultrasound","Magnetic Resonance (MR)","","","Same as predicate device."],["Principle of Operation/\nTechnology","","Ultrasound image processing\nsoftware application\nimplementing artificial\nintelligence utilizing non-\nadaptive machine learning\nalgorithms trained with\nclinical and/or artificial data\nintended for segmentation\nand measurements of\nultrasound data.","","Ultrasound image processing\nsoftware application\nimplementing artificial\nintelligence including non-\nadaptive machine learning\nalgorithms trained with\nclinical and/or artificial\ndata intended for non-\ninvasive segmentation and\nmeasurements of ultrasound\ndata.","Radiological (MR) image\nprocessing software\nimplementing artificial\nintelligence including non-\nadaptive machine learning\nalgorithms trained with\nclinical and/or artificial data\nintended for automated\nsegmentation of the\nprostate gland with the\npossibility of manual\nadjustment and annotation.","","","Same as predicate device."],["Quantitative and/or\nQualitative Analysis","","Distance; Prostate Volume","","Distance; Bladder Volume","Distance; Prostate Volume","","","Equivalent to the predicate\ndevice. The subject device\nperforms semi-automated\nmeasurements of the\nprostate gland and prostate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p10-t0","doc_id":"K243853","page_num":10,"bbox":[72.32,72.35,719.75,535.42],"n_rows":12,"n_cols":9,"columns":["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],"rows":[["Criteria","","SUBJECT DEVICE","","PREDICATE DEVICE","REFERENCE DEVICE","","","RATIONALE\n(if subject device differs\nfrom predicate device)"],["","","Clarius Prostate AI","","Clarius Bladder AI","","AI-Rad Companion Prostate","",""],["","","","","","","MR","",""],["","","","","","","","","volume, whereas the\npredicate device performs\nsemi-automated\nmeasurements of the\nbladder and bladder volume."],["Segmentation","","Yes – Segmentation of\nanatomical structures\n(prostate)","","Yes – Segmentation of\nanatomical structures\n(bladder)","Yes – Segmentation of\nanatomical structures\n(prostate)","","","Equivalent to the predicate\ndevice. The only difference is\nthe anatomical structure\n(prostate gland vs. bladder)."],["Measurement","","Yes – Measurement of\nanatomical structures\n(prostate)","","Yes – Measurement of\nanatomical structures\n(bladder)","Yes – Measurement of\nanatomical structures\n(prostate)","","","Equivalent to the predicate\ndevice. The only difference is\nthe anatomical structure\n(prostate gland vs. bladder)."],["Algorithm Methodology","","Artificial Intelligence\n(AI)/Machine Learning (ML)\nImage segmentation for\nborder detection, and\nprostate view classification\nusing a Deep Neural\nNetwork.","","Artificial Intelligence\n(AI)/Machine Learning (ML)\nImage segmentation for\nborder detection, and\nbladder view classification\nusing a Deep Neural\nNetwork.","Artificial Intelligence\n(AI)/Machine Learning (ML)\nImage segmentation of the\nprostate gland with the\npossibility of manual\nadjustment and annotation.","","","Same as predicate device."],["","Automation\n(Yes or No)","Yes","","Yes","Yes","","","Same as predicate device."],["","Manual adjustment/Manual\nediting capability\n(Yes or No)","Yes","","Yes","Yes","","","Same as predicate device."],["Environment of Use","","Healthcare setting (e.g.,\nhospital, clinic)","","Healthcare setting (e.g.,\nhospital, clinic)","Healthcare setting (e.g.,\nhospital, clinic)","","","Same as predicate device."],["Anatomical Site","","Prostate gland","","Bladder","Prostate gland","","","Equivalent to predicate\ndevice; same as reference\ndevice."],["Intended Users","","Licensed healthcare\nprofessionals","","Licensed healthcare\nprofessionals","Licensed healthcare\nprofessionals","","","Same as predicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p12-t0","doc_id":"K243853","page_num":12,"bbox":[72.26,181.44,539.74,306.36],"n_rows":8,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["12-349","","","NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set"],["5-129","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"FDA-recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p15-t0","doc_id":"K243853","page_num":15,"bbox":[72.58,310.32,539.9,716.4],"n_rows":2,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["Modification of data\ninput sources (Clarius\nprobes)","","To add data from\ncurrent Clarius scanners\nand future 510(K)\ncleared scanners to the\nClarius Prostate AI\nmodel so the model can\nbe deployed on more\nscanners.","","","Re-training of the\nProstate AI model to\nexpand its use with\nadditional data sources\n(i.e., 510(k)-cleared\nmodels of the Clarius\nUltrasound Scanner),\ninternal testing, and\nclinical performance\ntesting (verification and\nvalidation) to assesses\nits performance with\nthe new data input\nsources.","","","By accommodating a\nwider array of image\ngeometries and\ncharacteristics with\nthe use of additional\n510(k)-cleared\nClarius scanners, the\nupdated Prostate AI\nmodel will be better\nequipped to handle\ndifferent transducer\nmodels of the\nClarius Ultrasound\nScanner used in\nvarying clinical\nscenarios.\nBenefit-Risk\nAnalysis:\nBenefits: Enhanced\ncompatibility;\nFlexibility for diverse\nclinical settings.\nRisks: Data skewing\nand concept drift.\nRisk Mitigation:\nInternal testing and\nverification datasets","",""]],"caption_candidate":"Summary of planned modifications to Clarius Prostate AI per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p16-t0","doc_id":"K243853","page_num":16,"bbox":[72.53,72.93,539.95,709.2],"n_rows":4,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","","","","within the intended\npatient population\nwill ensure that data\nskewing and\nconcept drift are\nmitigated.","",""],["Modification to the filter\ncounts","","Improvement and\noptimization of Clarius\nProstate AI’s\nperformance","","","Re-training of the\nProstate AI model to\noptimize its\nperformance followed\nby internal testing and\na comparison of the\noriginal Prostate AI\nmodel to the modified\nProstate AI model\n(using performance\nmetrics) followed with\nclinical performance\ntesting (verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nProstate AI model\nwith increased\naccuracy and more\nrobust prostate\nvolume\nmeasurements\ndisplayed to users.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of model\nparameter (initial\nlearning rate)","","Improvement and\noptimization of Clarius\nProstate AI’s\nperformance","","","Re-training of the\nProstate AI model to\noptimize its\nperformance followed\nby internal testing and\na comparison of the\noriginal Prostate AI\nmodel to the modified","","","Improved\nperformance\nmetrics of modified\nProstate AI model.\nBenefit-Risk\nAnalysis:","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243853-p17-t0","doc_id":"K243853","page_num":17,"bbox":[72.58,72.93,539.9,344.64],"n_rows":2,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","Prostate AI model\n(using performance\nmetrics) and clinical\nperformance testing\n(verification and\nvalidation).","","","Benefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p6-t0","doc_id":"K243859","page_num":6,"bbox":[72.26,346.85,539.86,444.43],"n_rows":7,"n_cols":2,"columns":["Trade Name","PRAEVAorta®2"],"rows":[["Trade Name","PRAEVAorta®2"],["Subject Device K Number","K243859"],["Common Name","Automated radiological image processing software"],["Product Code","QIH"],["Regulation Number","21CFR 892.2050"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"2. SUBJECT DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p6-t1","doc_id":"K243859","page_num":6,"bbox":[72.26,495.79,539.86,593.38],"n_rows":7,"n_cols":2,"columns":["Predicate Device Name","CT Cardiomegaly"],"rows":[["Predicate Device Name","CT Cardiomegaly"],["Predicate Device K Number","K232613"],["Common Name","Automated Radiological Image Processing Software"],["Product Code","QIH"],["Regulation Number","892.2050"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"3. PREDICATE DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p8-t0","doc_id":"K243859","page_num":8,"bbox":[64.96,145.3,539.84,698.02],"n_rows":7,"n_cols":4,"columns":["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],"rows":[["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],["Regulatory number","21 CFR 892.2050","21 CFR 892.2050","Same"],["Regulatory class","Class II","Class II","Same"],["Product code","QIH","QIH","Same"],["Device property","SaMD","SaMD","Same"],["Indication for use","PRAEVAorta®2 is a software\nintended to be run on its own or\nas part of another medical\ndevice to automatically\ncalculate maximum diameters\nof anatomical zones from a\nDICOM CT image containing\nblood vessels\nPRAEVAorta2 is designed to\nmeasure the maximal\ntransverse diameter of vessel\nand determine the maximal\ngeneral diameter using a non-\nadaptative machine learning\nalgorithm\nIntended users of the software\nare aimed to the clinical\nspecialist, physicians or other\nlicensed practitioners in\nhealthcare institutions, such as\nclinics, hospitals, healthcare\nfacilities, residential care\nfacilities and long-term care\nservices. Any results obtained\nfrom the software by an\nintended user other than a\nphysician must be validated by\nthe physician responsible of the\npatient. The system is suitable\nfor adults. Its results are not\nintended to be used on a\nstandalone basis for clinical\ndecision making or otherwise\npreclude clinical assessment of\nany disease","CT Cardiomegaly is software\nintended to be run on its own\nor as part of another medical\ndevice to automatically\ncalculate linear and area\nbased cardiothoracic ration\n(CTR) from a CT image\ncontaining the heart. CT\nCardiomegaly is designed to\nmeasure the maximal\ntransverse diameter of heart\nand maximal inner transverse\ndiameter of thoracic cavity\nand calculate the CTR from an\naxial CT slice containing the\nheart using a non-adaptative\nmachine learning algorithm.\nIntended users of the\nsoftware are aimed to the\nphysicians or other licensed\npractitioners in the\nhealthcare institutions, such\nas clinics, hospitals,\nhealthcare facilities,\nresidential care facilities and\nlong-term care services. The\nsystem is suitable for adults\nand transitional adolescents\n(18 to 21 years old but\ntreated as an adult). Its\nresults are not intended to be\nused on a stand-alone basis\nfor clinical decision making or\notherwise preclude clinical\nassessment of any disease.","Equivalent\nIndication for use of the\ntwo devices are analyzing\nCT scan images.\nBoth the subject device\nand the primary predicate\nare using non adaptative\nmachine learning\nalgorithms. An observed\ndifference between the\nsubject device and the\npredicate is the anatomical\nzone analyzed in CT scan.\nThe primary predicate is\nassessing the heart while\nthe subject device is\nassessing arteries .\nHowever, these\ndifferences in\ntechnological\ncharacteristics do not\naffect safety and\neffectiveness of the device\nand have been supported\nwith verification and\nvalidation testing."],["Input","CT scan images","CT scan images","Same"]],"caption_candidate":"6. COMPARAISON OF TECHNOLOGICAL CHARACTERISTICS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p9-t0","doc_id":"K243859","page_num":9,"bbox":[64.97,119.86,539.83,701.14],"n_rows":4,"n_cols":4,"columns":["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],"rows":[["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],["Output files","- PDF, JSON and DICOM SC\nreport\n- DICOM GSPS","- PDF and JSON report","Equivalent\nThe subject device\nproposed the same storage\nformat as the primary\npredicate.\nHowever, it is also\nproposing two additional\nformats, “DICOM SC\nreport” and “DICOM GSPS”\nThis difference in\ntechnological\ncharacteristics does not\naffect safety and\neffectiveness of the device\nand has been supported\nwith verification and\nvalidation testing."],["Output measurements","- Maximal transverse\ndiameter of vessels (aorta\nand iliac arteries)\n- Linear measurements\n(diameters)\n- Various visualization\ntechniques: 2D/3D","- Linear and area based\ncardiothoracic ratio\n- Maximal transverse\ndiameter of the heart\n- Maximal inner\ntransverse diameter of\nthoracic cavity","Equivalent to the\npredicate.\nThe subject device is\nrealizing the similar\nmeasurements as the\nprimary device.\nThe main difference\nbetween the primary\npredicate and the subject\ndevice is the body part\nassessed.\nHowever, these\ndifferences in\ntechnological\ncharacteristics do not\naffect safety and\neffectiveness of the device\nand have been supported\nwith verification and\nvalidation testing."],["Report Structure","Report will be output in the PDF\nand JSON file, and DICOM SC\nreport which is structured with\nfollowing information:\n- Maximum orthogonal\ndiameter of\nanatomical zones\n- Patient information\n- Reference value(s)","Report will be output in the\nPDF and JSON\nfile format which is\nstructured with following\ninformation:\n- CTR (both linear\nand area-based)\n- Patient information\n- Reference value(s)","Equivalent\nBoth devices generate a\nreports with a final output\n(Maximal Orthogonal\ndiameter or CTR), which is\nused to support medical\ndiagnosis for a specific\nclinical condition and\nincludes patient\ninformation."]],"caption_candidate":"Traditional 510(k) premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p10-t0","doc_id":"K243859","page_num":10,"bbox":[64.96,119.86,539.84,706.42],"n_rows":7,"n_cols":4,"columns":["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],"rows":[["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],["Intended users","- Physicians or other\nlicensed practitioners in\nhealthcare institutions\n- Clinical specialists with\nresults validated by a\nphysician","Physician or other licensed\npractitioners in the\nhealthcare institutions","Equivalent\nThe subject device is also\nintended to be used by\nclinical specialist, the\nresults being validated by\nthe doctor in charge."],["Target population","- Adults","Adults and transitional\nadolescents (18 to 21 years\nold but treated as an adult)","Equivalent.\nThe subject device is more\nrestrictive as\nthe primary predicate.\nThese differences in\ntechnological\ncharacteristics do not\naffect safety and\neffectiveness of the device\nhave been\nsupported with verification\nand validation\ntesting."],["Location of anatomical\nstructures","- Thoraco-abdominal-pelvis","Chest","The primary predicate is\nmore restrictive\nas the new device.\nHowever these\ndifferences are supported\nwith a\nperformance bench test."],["Imaging modality","- Computed Tomography\n(CT)","Computed Tomography (CT)","Same"],["Intended use\nenvironment","- Healthcare institutions\n(clinics, hospitals,\nhealthcare facilities,\nresidential care facilities\nand long-term care\nservices)\n- Healthcare company\nrealizing sizing assessment\nof vessels)","Healthcare institutions\n(clinics, hospitals, healthcare\nfacilities, residential care\nfacilities and long-term care\nservices)","The subject device is\nusable by healthcare\ncompany realizing sizing\nassessment\nvessels while the primary\npredicate is not.\nHowever, these\ndifferences in\ntechnological\ncharacteristics do not\naffect\nthe safety and\neffectiveness of the device\nand have been supported\nwith verification\nand validation testing"],["Software device that\noperatures on off-the-\nshelf hardware","Yes","Yes","Same"]],"caption_candidate":"Traditional 510(k) premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243859-p11-t0","doc_id":"K243859","page_num":11,"bbox":[64.96,119.86,539.85,682.66],"n_rows":8,"n_cols":4,"columns":["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],"rows":[["","NEW DEVICE\nPRAEVAorta® 2\nNurea","PRIMARY PREDICATE\nCT Cardiomegaly\nInnolitics\nK232613","Substantially Equivalent"],["Software device uses\nsoftware algorithms for\nimage","Yes","Yes","Same"],["Diameter measurement","Yes, automated","Yes, automated","Same"],["Storage","Saved in PDF, JSON and DICOM\nSC format, DICOM GSPS","Saved in JSON and PDF file\nformat","The subject device\nproposed the same\nstorage format as the\nprimary predicate\nand one format in common\nwith the\nsecondary predicate.\nHowever, it is also\nproposing an additional\nformat “DICOM\nGSPS”.\nThis difference in\ntechnological\ncharacteristics does not\naffect safety and\neffectiveness of the device\nand have been\nsupported with verification\nand validation\ntesting"],["Software requirement","- Ubuntu\n- Docker","- Ubuntu 20.04.5 LTS\n(provided as a docker\ncontainer)\n- Docker 23.0.1 or above","Equivalent"],["Algorithm type","Machine learning based\nalgorithm (non-adaptative)","- Machine learning based\nalgorithm (non-\nadaptative)","Same"],["Input of patient data","Command line interface (API)","Command line interface (API)","Same"],["Image assessment","- Linear (diameters)\nmeasurements\n- Automatic segmentation\nand quantitative analysis\n- Segmentation and analysis\nor aortic and iliac arteries","- Linear (diameter, ratio)\n- Area based ratio\n- Automatic segmentation\nand measurements","Equivalent.\nThe subject device is more\nrestrictive than\nthe predicate.\nThis difference in\ntechnological\ncharacteristics do not\naffect safety and\neffectiveness of the device\nand have been\nsupported with verification\nand validation\ntesting"]],"caption_candidate":"Traditional 510(k) premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243862-p8-t0","doc_id":"K243862","page_num":8,"bbox":[105.86,72.24,506.14,252.6],"n_rows":3,"n_cols":5,"columns":["Segmental wall\nmotion evaluation","","","Yes. Based on the\nsame machine\nlearning algorithm,\nmultiple rocessing\nsteps were added\nand the calculated\nfeatures revised","Yes. Based on a machine\nlearning algorithm."],"rows":[["Segmental wall\nmotion evaluation","","","Yes. Based on the\nsame machine\nlearning algorithm,\nmultiple rocessing\nsteps were added\nand the calculated\nfeatures revised","Yes. Based on a machine\nlearning algorithm."],["Operating System","","","Same","Windows/Linux(With\nAndroid option for LVivo EF"],["","510(k) #","","Pending","K240553"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243862-p9-t0","doc_id":"K243862","page_num":9,"bbox":[194.66,355.28,569.76,466.78],"n_rows":3,"n_cols":5,"columns":["ICC","","","",""],"rows":[["ICC","","","",""],["","GT vs LVivo\nSWM","Expert 1 vs\nExpert 2","Expert 1 vs\nExpert 3","Expert 2 vs\nExpert 3"],["WMSI","0.8 5","0.6 4","0.7 4","0.81"]],"caption_candidate":"provided in the ground truth from all three experts were included. The comparison for","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243862-p10-t0","doc_id":"K243862","page_num":10,"bbox":[227.0,72.24,454.9,185.78],"n_rows":5,"n_cols":2,"columns":["Specificity","82%"],"rows":[["Specificity","82%"],["Sensitivity","82%"],["Accuracy","82%"],["Correlation","0.856"],["n","78"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243863-p5-t0","doc_id":"K243863","page_num":5,"bbox":[73.5,197.5,541.5,456.5],"n_rows":11,"n_cols":2,"columns":["Submitter Name","Roche Molecular Systems, Inc."],"rows":[["Submitter Name","Roche Molecular Systems, Inc."],["Address","2881 Scott Blvd\nSanta Clara, CA 95050 USA"],["Contact","Aarti Shukla\nRegulatory Affairs Manager, RIS\nPhone: (408) 705-7215\nFax: (925) 225-0207\naarti.shukla@roche.com"],["Date Prepared","December 16, 2024"],["Proprietary Name","Automated Total Metabolic Tumor Volume (aTMTV)"],["Common Name","Opulus™ Lymphoma Precision"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Regulatory Class","II"],["Product Codes","QIH, Automated Radiological Image Processing Software"],["Predicate Device","NS-HGlio, K221738"]],"caption_candidate":"with the requirements of 21 CFR 807.92.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243863-p7-t0","doc_id":"K243863","page_num":7,"bbox":[76.25,95.13,550.25,452.5],"n_rows":9,"n_cols":3,"columns":["Feature/function","Opulus™ Lymphoma Precision\n(subject device)","NS-HGlio\n(predicate device)"],"rows":[["Feature/function","Opulus™ Lymphoma Precision\n(subject device)","NS-HGlio\n(predicate device)"],["Model Type","Artificial Intelligence Machine Learning\n(AI/ML) Algorithm","Artificial Intelligence Machine Learning\n(AI/ML) Algorithm"],["Patient population","Patients already pathologically diagnosed\nwith FDG-avid lymphomas","Patients already pathologically diagnosed to\nhave brain tumors"],["Input","Standard DICOM format - PET with the\nassociated attenuation correction CT","Standard DICOM format - four different\nMRI sequences"],["Output","Report and image overlay","Report and image overlay"],["Segmentation","Segments disease related tracer uptake in\nFDG-avid lymphomas","Segments disease related contrast\nuptake and FLAIR image intensity\nchanges in high-grade gliomas (HGG)"],["Visualization","Overlay of segmentation mask on input\nPET/CT images","Overlay of segmentation mask on input MRI\nimages"],["Quantification","Volumetric measurements derived from\nsegmented lymphoma disease burden","Volumetric measurements derived\nfrom segmented HGG disease burden"],["Ground truth\nEstablishment","Reference standard (ground truth) was\nestablished using three US board certified\nradiologists/nuclear medicine physicians\nwith expertise in identifying and\nsegmenting FDG-avid lymphoma related\nuptake","Reference standard (ground truth) was\nestablished using three board certified\nneuroradiologists with expertise in\nidentifying and segmenting high grade\ngliomas"]],"caption_candidate":"3. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243863-p8-t0","doc_id":"K243863","page_num":8,"bbox":[116.5,151.7,513.37,529.5],"n_rows":15,"n_cols":2,"columns":["Patient Characteristic","Percentage (%)"],"rows":[["Patient Characteristic","Percentage (%)"],["Gender",""],["Female","34.6%"],["Male","65.4%"],["Ethnicity",""],["Hispanic Or Latino","1.6%"],["Not Hispanic Or Latino","96.2%"],["Not Reported","1.6%"],["Unknown","0.5%"],["Age groups",""],["<40 y","11.0%"],["40-49 y","11.5%"],["50-59 y","17.0%"],["60-69 y","28.0%"],[">=70 y","32.4%"]],"caption_candidate":"validation dataset was not available to the algorithm developers during the algorithm training.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243884-p7-t0","doc_id":"K243884","page_num":7,"bbox":[28.41,620.19,559.95,739.32],"n_rows":5,"n_cols":4,"columns":["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],"rows":[["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],["","Subject Device (SD):","Predicate Device (PD):",""],["","TAVIPILOT","Philips HeartNavigator 2.0",""],["","","",""],["General\ninformation","Product codes: OWB, QIH\nClassification name: Image-intensified\nfluoroscopic x-ray system\nClassification regulation: 21 CFR\n892.1650\nFDA Clearance: K243884","Product code: OWB, LLZ\nClassification name: Image-intensified\nfluoroscopic x-ray system\nClassification regulation: 21 CFR\n892.1650\nFDA Clearance: K140138","Similar to PD:\nPredicate device is legally\nmarketed."]],"caption_candidate":"COMPARISON OF TECHNOLOGICAL FEATURES TO PREDICATE DEVICE (SE TABLE):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243884-p8-t0","doc_id":"K243884","page_num":8,"bbox":[28.39,72.35,559.99,773.4],"n_rows":7,"n_cols":4,"columns":["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],"rows":[["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],["","Subject Device (SD):","Predicate Device (PD):",""],["","TAVIPILOT","Philips HeartNavigator 2.0",""],["","","",""],["Intended Use\n(IU) including\nIndications for\nUse (IFU)","TAVIPILOT is an intra-operative software\nwhich provides real-time fluoroscopy\ndetection, tracking and marking of the\nNon-Coronary Cusp and the prosthetic\nvalve, to allow optimal guidance for\nprecise positioning of the prosthetic\nvalve, according to the planning phase,\nfor TAVI/TAVR (transcatheter aortic valve\nimplantation/replacement) procedures.\nThe guidance provided by TAVIPILOT is\nnot intended to substitute the cardiac\nsurgeon’s or the interventional\ncardiologist’s judgment and analysis of\nthe patient’s condition.\nThe device is only intended for adults\n(i.e., 21 years and older).\nContra-indications:\n- Patients who have already undergone a\nTAVI/TAVR or SAVR (surgical aortic valve\nreplacement)\n- Patients diagnosed with aortic\ninsufficiency\n- Patients for whom the main access for\nthe TAVI/TAVR catheter is not femoral\n- Patients who have a non-tricuspid\nnative valve\n- Patients who have a permanent\nPacemaker implant or temporary\nPacemaker within 2 cm from the aortic\nroot, other than the pacing guidewire\n- Patients who have thoracic surgical\nimplants\n-Patients who are not adults","HeartNavigator is a tool to assist the\nuser with the treatment of structural\nheart disease using minimal invasive\ninterventional techniques. In addition\nto the conventional live fluoroscopy it\nprovides the user with tools to plan\nand guide the procedure using 3D\nimage data.","Similar to PD:\nSD does not assist the user with\nprocedure planning.\nSD provides support for a\nspecific structural heart\ndisease treatment procedure,\nnamely TAVI/TAVR."],["","The TAVIPILOT software tool is intended\nto be used in combination with FDA\ncleared X-ray systems to assist cardiac\nsurgeons and interventional\ncardiologists with the treatment of\nstructural heart diseases using minimal\ninvasive interventional techniques for\nwhich TAVI/TAVR is indicated.","The HeartNavigator software tool is\nintended to be used in combination\nwith the primary predicate device\nAllura X-ray system (K130638) to assist\ncardiac surgeons and interventional\ncardiologists with the treatment of\nstructural heart diseases using\nminimal invasive interventional\ntechniques.","Similar to PD:\nBoth devices are intended to\nassist cardiac surgeons and\ninterventional cardiologists\nwith the treatment of structural\nheart diseases using FDA\ncleared X-Ray C-arm systems\nand minimal invasive\ninterventional techniques.\nSD provides support for a\nspecific structural heart\ndisease treatment procedure,\nnamely TAVI/TAVR."],["","In addition to conventional live\nfluoroscopy TAVIPILOT provides the user\nwith tools to guide the procedure using a\n2D projection of the aortic root-related\nlandmarks and transcatheter aortic\nvalve overlayed on the 2D X-ray image\ndata from the FDA cleared X-ray systems","In addition to conventional live\nfluoroscopy HeartNavigator provides\nthe user with tools to plan (by use of\npreviously acquired DICOM cardiac CT\npatient data) and guide the procedure\nusing a 2D projection of the aortic root-\nrelated landmarks obtained during\nplanning, on X-ray image data from the\nAllura X-ray system.","Similar to PD:\nBoth PD and SD use 2D\noverlay on the fluoroscopic\nimage for guidance.\nSD does not assist the user\nwith procedure planning in\nthe planning phase"]],"caption_candidate":"K243884 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243884-p9-t0","doc_id":"K243884","page_num":9,"bbox":[28.37,72.35,560.01,775.86],"n_rows":12,"n_cols":4,"columns":["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],"rows":[["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],["","Subject Device (SD):","Predicate Device (PD):",""],["","TAVIPILOT","Philips HeartNavigator 2.0",""],["","","",""],["","During Live phase the SD offers\nanatomical detection and tracking of the\naortic root-related landmarks and\ntranscatheter aortic valve which is\noverlayed in 2D on the 2D fluoroscopy x-\nray image data using trained AI/ML\nmodel.","During live phase the PD converts the\n3D CT-data to a 2D projection of the\naortic root-related landmarks, which is\noverlayed on the 2D fluoroscopy x-ray\nimage.","Different in technology:\nBoth PD and SD offer\nanatomical detection, tracking\nand marking of the aortic\nroot. Both PD and SD use 2D\noverlay on the fluoroscopic\nimage for guidance. SD uses a\ntrained AI/ML model"],["","TAVIPILOT does not change or influence\nthe TAVI procedure","HeartNavigator 2.0 does not change or\ninfluence the TAVI procedure","Same as PD"],["Patients, Users &\nEnvironment","Patient Population:\nTAVIPILOT is suitable for patients with\nstructural heart diseases who are\nconsidered appropriate for treatment\nwith a TAVI/TAVR procedure.","Patient Population:\nHeartNavigator 2.0 is suitable for\npatients with structural heart diseases\nthat have a medical condition for\nwhich the treatment with minimal\ninvasive interventional techniques\nusing fluoroscopy is considered\nsuitable.","Same as PD\nSD is specifically suitable for\npatients with structural heart\ndiseases for which TAVI/TAVR is\nindicated."],["","Intended users:\nThe user is a clinical specialist who is\nfully skilled and qualified to perform the\nTAVI/TAVR procedure and is responsible\nfor sound clinical judgement and for\napplying the best clinical procedure","Intended users:\nThe user is a clinical specialist who is\nfully skilled and qualified to perform\nthe structural heart disease procedure\nand is responsible for sound clinical\njudgement and for applying the best\nclinical procedure.","Same as PD\nSD’s intended users are skilled\nand qualified to perform a\nspecific structural heart\ndisease procedure, namely\nTAVI/TAVR."],["","General safety and effectiveness:\nTo facilitate safe and efficacious\noperation of the system by a trained\nhealthcare professional, instructions for\nuse are provided as part of the labelling,\nas well as training at system handover.","General safety and effectiveness:\nTo facilitate safe and efficacious\noperation of the system by a trained\nhealthcare professional, instructions\nfor use are provided as part of the\nlabelling, as well as training at system\nhandover.","Same as PD"],["","Clinical environment:\nTAVIPILOT is intended to be used in the\ncontrol room and in the examination\nroom of an interventional suite and/or\nhybrid operating room.","Clinical environment:\nHeartNavigator is intended to be used\nin the control room and in the\nexamination room of an interventional\nsuite and/or hybrid operating room.","Same as PD"],["","Computer (PC) environment\n• Windows operating system\n• Video capture for receiving C-arm X-\nray fluoroscopic images\n• Output to LDM (Large Display\nMonitor)","Computer (PC) environment\n• Windows operating system\n• Video capture for receiving C-arm X-\nray fluoroscopic images\n• Output to LDM (Large Display\nMonitor)","Same as PD"],["Principle of\nOperation and\nTechnology","The main operating principle of\nTAVIPLIOT consists of the following SW\nworkflow:\n1. Preparing for Live task\n2. Live Task","The main operating principle of\nHeartNavigator consists of the\nfollowing SW workflow:\n1. Planning segmentation task\n2. Planning measurement task\n3. Planning viewing task\n4. Planning registration task\n5. Preparing for Live task\n6. Live Task","Similar to PD:\nThe intended use of the SD is\nnot to assists the user with TAVI\nprocedure planning, therefore\nsteps 1-4 of the PD steps are\nnot relevant for the SD."]],"caption_candidate":"K243884 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243884-p10-t0","doc_id":"K243884","page_num":10,"bbox":[28.39,72.35,560.0,498.34],"n_rows":9,"n_cols":4,"columns":["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],"rows":[["Product/\nFeature","","","Substantial Equivalence (SE)\nand Comments"],["","Subject Device (SD):","Predicate Device (PD):",""],["","TAVIPILOT","Philips HeartNavigator 2.0",""],["","","",""],["TAVIPILOT SW\nWorkflow –\nPreparing for Live\nTask","Valve type, valve size and positioning are\nselected by the user in the preparing for\nlive tasks","Valve type, size and positioning are\nselected by the user in the preparing\nfor live tasks.","Same as PD\nBoth SD and PD requires valve\ntype, size and positioning input\nby the user."],["","Live task – reception of fluoroscopic\ndata\nReception of live fluoroscopic stream\nfrom an FDA-cleared X-Ray system","Live task – reception of fluoroscopic\ndata\nReception of live fluoroscopic stream\nfrom the Allura X-ray system (K130638)","Similar to PD\nBoth devices receives live\nfluoroscopic images from a\ncleared X-ray system"],["","Live task – displaying raw fluoroscopic\ndata\nDuring Live Task the TAVIPILOT is\ndisplayed in addition to the original raw\nfluoroscopic data (image), on the large\nmonitor as a separate fluoroscopic\nimage with the overlayed guidance\ninformation","Live task – displaying raw\nfluoroscopic data\nDuring Live Task the HeartNavigator\n2.0 is displayed in addition to the\noriginal raw fluoroscopic data (image),\non the large monitor as a separate\nfluoroscopic image with the overlayed\nguidance information","Same as PD:\nBoth SD and PD keep an\noriginal raw fluoroscopic image\nflow and provide their guidance\non a separate flow"],["","Live tasks - Aortic root-related\nlandmarks:\nUpon detection, the aortic root-related\nlandmarks are displayed to the user by\noverlaying a 2D landmark on the 2D live\nx-ray images.","Live tasks - Aortic root-related\nlandmarks:\nUpon detection, the aortic root-related\nlandmarks are displayed to the user by\noverlaying a 2D landmark (NCC, LCC\nand RCC) on the live 2D x-ray images.","Similar to PD:\nBoth systems display 2D\nlandmarks on the live 2D\nfluoroscopic stream for\nmarking of the NCC.\nSD only displays NCC as a dot,\nPD displays NCC, LCC and RCC\nas a circle"],["","Live tasks – Transcatheter Aortic Valve\n(TAV):\nUpon detection, the TAV is displayed to\nthe user by overlaying a 2D on the live 2D\nx-ray images.","Live tasks – Transcatheter Aortic\nValve (TAV):\nThe TAV is displayed to the user by\noverlaying a 2D landmark (2D valve\noverlay) on the live 2D x-ray images.","Similar to PD:\nBoth systems displays 2D\nlandmarks on the live 2D\nfluoroscopic stream for\nmarking of the TAV.\nSD displays TAV as line overlay,\nPD displays TAV as multiple line\noverlay"]],"caption_candidate":"K243884 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243893-p7-t0","doc_id":"K243893","page_num":7,"bbox":[61.48,550.78,413.88,701.56],"n_rows":6,"n_cols":3,"columns":["","Subject Device\nSecond Opinion® Pediatric","Primary Predicate\nSecond Opinion\nK210365"],"rows":[["","Subject Device\nSecond Opinion® Pediatric","Primary Predicate\nSecond Opinion\nK210365"],["Manufacturer","Pearl Inc.","Pearl Inc."],["Classification","892.2070","892.2070"],["Product Code","MYN","MYN"],["Image\nModality","Radiograph","Radiograph"],["Intended Use","Dental CADe to aid in dental\nradiograph review by HCP","Dental CADe to aid in dental\nradiograph review by HCP"]],"caption_candidate":"Table 1: Comparison of Second Opinion® Pediatric with the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243893-p8-t0","doc_id":"K243893","page_num":8,"bbox":[61.48,86.5,413.81,412.2],"n_rows":4,"n_cols":3,"columns":["Full IFU","Second Opinion® Pediatric is a\ncomputer aided detection\n(\"CADe”) software to aid in the\ndetection of caries in bitewing\nand periapical radiographs.\nThe intended patient population\nof the device is patients aged 4\nyears and older that have\nprimary or permanent teeth\n(primary or mixed dentition) and\nare indicated for dental\nradiographs.","Second Opinion® is a computer\naided detection (“CADe”) software\nto identify and mark regions in\nrelation to suspected dental\nfindings which include Caries,\nDiscrepancy at the margin of an\nexisting restoration, Calculus,\nPeriapical radiolucency, Crown\n(metal, including zirconia &\nnon-metal), Filling (metal &\nnon-metal), Root canal, Bridge and\nImplants.\nIt is designed to aid dental health\nprofessionals to review bitewing\nand periapical radiographs of\npermanent teeth in patients 12\nyears of age or older as a second\nreader."],"rows":[["Full IFU","Second Opinion® Pediatric is a\ncomputer aided detection\n(\"CADe”) software to aid in the\ndetection of caries in bitewing\nand periapical radiographs.\nThe intended patient population\nof the device is patients aged 4\nyears and older that have\nprimary or permanent teeth\n(primary or mixed dentition) and\nare indicated for dental\nradiographs.","Second Opinion® is a computer\naided detection (“CADe”) software\nto identify and mark regions in\nrelation to suspected dental\nfindings which include Caries,\nDiscrepancy at the margin of an\nexisting restoration, Calculus,\nPeriapical radiolucency, Crown\n(metal, including zirconia &\nnon-metal), Filling (metal &\nnon-metal), Root canal, Bridge and\nImplants.\nIt is designed to aid dental health\nprofessionals to review bitewing\nand periapical radiographs of\npermanent teeth in patients 12\nyears of age or older as a second\nreader."],["Intended body\npart","Dental","Dental"],["Technology","Automated, CADe software that\nutilizes machine learning","Automated, CADe software that\nutilizes machine learning"],["Device\nDescription","Detection & display of caries\nlesions in intraoral radiographs","Detection and display of anatomy\nand pathologies in intraoral\nradiographs"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243933-p5-t0","doc_id":"K243933","page_num":5,"bbox":[72.3,136.59,539.79,305.54],"n_rows":15,"n_cols":4,"columns":["","","","Ceevra, Inc."],"rows":[["","","","Ceevra, Inc."],["","510(k) Sponsor","",""],["","","",""],["","","","149 New Montgomery St, 4th Floor\nSan Francisco CA 94105"],["Address","","",""],["","","",""],["","","","Ken Koster\nCTO, Ceevra, Inc."],["Correspondence Person","","",""],["","","",""],["","","","Email: kkoster@ceevra.com\nPhone: 415-305-5326"],["Contact Information","","",""],["","","",""],["","","","March 2, 2025"],["","Date Prepared","",""],["","","",""]],"caption_candidate":"1. General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243933-p5-t1","doc_id":"K243933","page_num":5,"bbox":[72.3,343.17,539.79,493.89],"n_rows":18,"n_cols":4,"columns":["","","","Ceevra Reveal 3+"],"rows":[["","","","Ceevra Reveal 3+"],["","Proprietary Name","",""],["","","",""],["","","","Reveal 3+"],["","Common Name","",""],["","","",""],["","","","Automated Radiological Image Processing Software"],["","Classification Name","",""],["","","",""],["","","","21 CFR 892.2050"],["","Regulation Number","",""],["","","",""],["","","","QIH"],["","Product Code","",""],["","","",""],["","","","II"],["","Regulatory Class","",""],["","","",""]],"caption_candidate":"2. Updated Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243933-p5-t2","doc_id":"K243933","page_num":5,"bbox":[72.3,529.76,539.79,655.34],"n_rows":15,"n_cols":4,"columns":["","","","Ceevra Reveal 3+"],"rows":[["","","","Ceevra Reveal 3+"],["","Proprietary Name","",""],["","","",""],["","","","Reveal 3+"],["","Common Name","",""],["","","",""],["","","","K233568"],["","Premarket Notification","",""],["","","",""],["","","","Automated Radiological Image Processing Software"],["","Classification Name","",""],["","","",""],["","","","21 CFR 892.2050"],["","Regulation Number","",""],["","","",""]],"caption_candidate":"3. Originally Cleared Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243933-p6-t0","doc_id":"K243933","page_num":6,"bbox":[72.2,76.95,539.95,127.1],"n_rows":6,"n_cols":4,"columns":["","","","QIH"],"rows":[["","","","QIH"],["","Product Code","",""],["","","",""],["","","","II"],["","Regulatory Class","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243933-p9-t0","doc_id":"K243933","page_num":9,"bbox":[71.5,105.72,540.5,147.48],"n_rows":3,"n_cols":2,"columns":["","The data used in the device validation"],"rows":[["","The data used in the device validation"],["ensured diversity in patient population and scanner manufacturers. Subgroup analysis was performed for",""],["patient age, patient sex, and scanner manufacturers.",""]],"caption_candidate":"were enforced at the level of the scanning institution, namely, studies sourced from a specific institution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243989-p8-t0","doc_id":"K243989","page_num":8,"bbox":[61.47,142.8,555.67,588.44],"n_rows":10,"n_cols":3,"columns":["","Subject Device\nSecond Opinion® 3D","Primary Predicate\nRelu Creator\nK233925"],"rows":[["","Subject Device\nSecond Opinion® 3D","Primary Predicate\nRelu Creator\nK233925"],["Manufacturer","Pearl Inc.","Relu BV"],["Classification","892.2050","892.2050"],["Product Code","QIH","QIH"],["Image\nModality","Radiograph","Radiograph"],["Intended Use","Dental automated image processing\nsoftware device to aid in reviewing CBCT\nradiograph by HCP","Dental automated image processing software device to aid\nin reviewing CBCT, IOS and FS medical images by HCP"],["Full IFU","Second Opinion® 3D is a radiological\nautomated image processing software\ndevice intended to identify and mark\nclinically relevant anatomy in dental\nCBCT radiographs; specifically Dentition,\nMaxilla, Mandible, Inferior Alveolar Canal\nand Mental Foramen (IAN), Maxillary\nSinus, Nasal space, and airway. It should\nnot be used in lieu of full patient\nevaluation or solely relied upon to make\nor confirm a diagnosis.\nIt is designed to aid health professionals\nto review CBCT radiographs of patients\n12 years of age or older as a concurrent\nand second reader.","Relu Creator is a software program for the management,\ntransfer, and analysis of dental and craniomaxillofacial\nimage information, and can be used to provide design input\nfor dental solutions. It displays and enhances digital images\nfrom various sources to support the\ndiagnostic process and treatment planning. It stores and\nprovides these images within the system or across computer\nsystems at different locations."],["Intended body\npart","Dental","Dental"],["Technology","Utilizes computer vision neural network\nalgorithms, developed from open-source\nmodels using supervised machine\nlearning techniques","Utilizes computer vision neural network algorithms,\ndeveloped from open-source models using supervised\nmachine learning techniques"],["Device\nDescription","3D modelling of patient anatomy","3D modelling of patient anatomy"]],"caption_candidate":"Table 1: Comparison of Second Opinion® 3D with the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K243989-p10-t0","doc_id":"K243989","page_num":10,"bbox":[54.7,278.74,518.74,466.76],"n_rows":8,"n_cols":6,"columns":["AnatomyID","Anatomy Name","Mean (95% CI)","Median [Min., Max.]","Std.dev.","one-sample t-test (p_value)"],"rows":[["AnatomyID","Anatomy Name","Mean (95% CI)","Median [Min., Max.]","Std.dev.","one-sample t-test (p_value)"],["1","Dentition","0.86 (0.83, 0.89)","0.88 [0.55, 0.93]","0.08","<0.000001"],["2","Maxillary Complex","0.91 (0.91, 0.92)","0.92 [0.72, 0.94]","0.03","<0.000001"],["3","Mandible","0.97 (0.97, 0.97)","0.97 [0.94, 0.98]","0.01","<0.000001"],["4","IAN Canal","0.76 (0.74, 0.78)","0.78 [0.4, 0.88]","0.09","<0.000001"],["5","Maxillary Sinus","0.97 (0.97, 0.98)","0.98 [0.73, 0.99]","0.03","<0.000001"],["6","Nasal Space","0.9 (0.89, 0.91)","0.91 [0.72, 0.96]","0.04","<0.000001"],["7","Airway","0.95 (0.94, 0.96)","0.96 [0.58, 0.98]","0.04","<0.000001"]],"caption_candidate":"statistical analysis can be observed:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K244002-p6-t0","doc_id":"K244002","page_num":6,"bbox":[29.28,237.6,582.72,711.36],"n_rows":7,"n_cols":4,"columns":["","Subject Device","Predicate Device","Reference Device"],"rows":[["","Subject Device","Predicate Device","Reference Device"],["Device Name","AngioWaveNet","ClariCT.AI K212074\nClariPi USA Inc.","Canon XIDF-AWS801,\nAngio Workstation\n(Alphenix Workstation),\nV9.5 K232526 Canon\nMedical Systems"],["Product Code","Primary QIH. Secondary OWB","LLZ","OWB, JAA"],["Regulation","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.1650"],["Indications for Use","AngioWaveNet is indicated for use\nby qualified physicians or under\ntheir supervision to aid in the\nanalysis and interpretation of X-ray\ncoronary angiographic cines.\nAngioWaveNet is intended for use\nin adults during X-ray coronary\nangiographic imaging procedures as\na clinically useful complement to\nthe viewing of standard\nangiographic cines acquired during\ndiagnostic coronary angiography\nprocedures. AngioWaveNet\nsoftware is intended for use to\nenhance the visibility of blood\nvessels, vascular structures, and\nrelated anatomical features within\nangiographic images, which may be\nclinically useful to the treating\nphysician","ClariCT.AI, is a\nsoftware device\nintended for networking,\ncommunication\nprocessing and\nenhancement of CT images\nin DICOM format\nregardless of the\nmanufacturer of CT\nscanner or model.","The Angio Workstation (XIDF-\nAWS801) is used in\ncombination with an\ninterventional\nangiography system\n(Alphenix series systems,\nInfinix-i series systems and\nINFX series systems) to provide\n2D and 3D imaging of selective\ncatheter angiography\nprocedures for the whole body\n(includes heart, chest,\nabdomen, brain and extremity).\nWhen XIDF-AWS801 is\ncombined with Dose Tracking\nSystem (DTS), DTS is used with\nselective catheter angiography\nprocedures for the heart, chest,\nabdomen, pelvis and brain."],["Intended User","Interventional cardiologists and\nrelated specialists","Radiologists and\nspecialists","Interventional cardiologists\nand related specialists"],["Modality\nSupport","Fluoroscopic angiography","CT","Fluoroscopic angiography"]],"caption_candidate":"7.Substantial Equivalence Chart:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K244002-p7-t0","doc_id":"K244002","page_num":7,"bbox":[29.28,29.28,582.72,302.76],"n_rows":5,"n_cols":4,"columns":["","Subject Device","Predicate Device","Reference Device"],"rows":[["","Subject Device","Predicate Device","Reference Device"],["System\nCompatibility","All X-ray\nangiography\nsystems exporting\nto XA DICOM\nmodality","All CT Scanners","Canon\nAlphenix series systems\nInfinix-i series systems\nINFX series systems"],["Image\nprocessing\nMethod","Pre-trained deep-learning models","Pre-trained deep learning\nmodels","Pre-trained deep-learning\nmodels"],["Supported\nImage Format","DICOM\n● 512x512 8 or 16 bits\n● 1024x1024 8 or 16 bits","DICOM\n512x512x8 bits","DICOM\n512x512x8 bits"],["Components\nand Hardware\nRequirements","On-site client:\nIntel Quad Core i7-\n4770 3.4GHz minimum\n● 32GB Ram\n● Windows 10 or 11\nProfessional","Windows Operating System,\nPC Hardware,\nCUDA supported\ngraphics card or\nequivalent","PC Hardware with GPU"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250005-p7-t0","doc_id":"K250005","page_num":7,"bbox":[77.73,86.9,539.86,705.19],"n_rows":7,"n_cols":6,"columns":["","","","Subject Device","Equivalent Device","Equivalent Device"],"rows":[["","","","Subject Device","Equivalent Device","Equivalent Device"],["","Device name","","Clever One v1.0","EzDent-i v3.4","Ez3D-i v5.5"],["","510K number","","-","K241114","K231757"],["","Manufacturer","","Ewoosoft","Ewoosoft","Ewoosoft"],["Indications for\nuse","Indications for","","Clever One is dental\nimaging software that\nis intended to provide\ntools for supporting\ndiagnosis and\ntreatment.\nThese tools enable\nend users to view and\ninterpret a series of\nDICOM compliant\nmedical images and\nare intended for use\nby trained medical\nprofessionals. Clever\nOne allows users to\nload, view, and save\nDICOM images from\nCT, panoramic,\ncephalometric,\nintraoral, and other\nimaging equipment. It\nalso provides\nfunctionalities such as\n2D viewing, 2D\nanalysis, 3D\nvisualization, 3D\nanalysis.","EzDent-i is dental\nimaging software that\nis intended to provide\ndiagnostic tools for\nmaxillofacial\nradiographic imaging.\nThese tools are\navailable to view and\ninterpret a series of\nDICOM compliant\ndental radiology\nimages and are meant\nto be used by trained\nmedical professionals\nsuch as radiologist\nand dentist.\nEzDent-i is intended\nfor use as software to\nacquire, view and save\n2D image files, load\nDICOM project files\nfrom panorama,\ncephalometric, and\nintra-oral imaging\nequipment.","Ez3D-i is dental\nimaging software that\nis intended to provide\ndiagnostic tools for\nmaxillofacial\nradiographic imaging.\nThese tools are\navailable to view and\ninterpret a series of\nDICOM compliant\ndental radiology\nimages and are meant\nto be used by trained\nmedical professionals\nsuch as radiologist\nand dentist. Ez3D-i is\nintended for use as\nsoftware to load, view\nand save DICOM\nimages from CT,\npanorama,\ncephalometric and\nintraoral imaging\nequipment and to\nprovide 3D\nvisualization, 2D\nanalysis, in various\nMPR (Multi-Planar\nReconstruction)\nfunctions."],["","use","","","",""],["Technology/Princ\niple of Operation","","","Clever One is a dental\nimaging software\ndesigned to acquire,\nprocess, view, edit,\nand analyze medical\nimages for supporting\ndiagnostic and\npreoperative planning","EzDent-i is a device\nthat provides various\nfeatures to acquire,\ntransfer, edit, display,\nstore, and perform\ndigital processing of\nmedical images.\nEzDent-i is a patient &","Ez3D-i v5.5 is 3D\nviewing software for\ndental CT images in\nDICOM format with a\nhost of useful\nfunctions including\nMPR, 2-dimensional\nanalysis and 3-"]],"caption_candidate":"9. Substantial Equivalence:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250005-p9-t0","doc_id":"K250005","page_num":9,"bbox":[77.74,72.27,539.86,707.23],"n_rows":15,"n_cols":6,"columns":["","","","The software\ninterfaces with dental\nimaging equipment,\nsuch as CT,\npanoramic,\ncephalometric, and\nintraoral X-ray\nsystems, as well as\nintraoral cameras, for\nimage acquisition. It is\ndesigned for use in\nnetwork\nenvironments,\nallowing users to\nupload and download\nclinical diagnostic\nimages and patient\ndata for enhanced\ncollaboration and\nefficient patient\nmanagement.","",""],"rows":[["","","","The software\ninterfaces with dental\nimaging equipment,\nsuch as CT,\npanoramic,\ncephalometric, and\nintraoral X-ray\nsystems, as well as\nintraoral cameras, for\nimage acquisition. It is\ndesigned for use in\nnetwork\nenvironments,\nallowing users to\nupload and download\nclinical diagnostic\nimages and patient\ndata for enhanced\ncollaboration and\nefficient patient\nmanagement.","",""],["Platform","","","IBM-compatible PC or\nPC network","IBM-compatible PC or\nPC network","IBM-compatible PC or\nPC network"],["","Operating","","Microsoft Window 10\nor higher","Microsoft Windows\n10,11","Microsoft Window 10\nor higher"],["","System","","","",""],["","User Interface","","Mouse, Keyboard","Mouse, Keyboard","Mouse, Keyboard"],["Image Input\nSources","Image Input","","Images can be\nscanned, loaded from\ndigital cameras or\ncard readers, or\nimported from a\nradiographic imaging\ndevice","Images can be\nscanned, loaded from\ndigital cameras or\ncard readers, or\nimported from a\nradiographic imaging\ndevice","Images can be\nscanned, loaded from\ndigital cameras or\ncard readers, or\nimported from a\nradiographic imaging\ndevice"],["","Sources","","","",""],["","32 bit / 64 bit","","64 bit","32 / 64 bit","64 bit"],["","Image format","","DICOM","DICOM","DICOM"],["","Patient Database","","SQL","SQL","SQL"],["","Compatibility","","","",""],["Includes Image\nMeasurement\ntools","Includes Image","","Length, Multi Length,\nAngle, Multi Angle,\nCircle, ROI/Area,\nVolume, Profile","Linear distance, angle","Length, Multi Length,\nAngle, Multi Angle,\nCircle, ROI/Area,\nVolume, Profile"],["","Measurement","","","",""],["","tools","","","",""],["Image viewing","","","Full, side by side,\ngallery, thumbnail","Full, side by side,\ngallery, thumbnail","Full, side by side,\ngallery, thumbnail"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250005-p10-t0","doc_id":"K250005","page_num":10,"bbox":[77.74,72.29,539.86,690.55],"n_rows":9,"n_cols":6,"columns":["Image\nmanipulation","","","Grayscale, invert,\nemboss, brightness,\ncontrast, gamma,\nsharpen, median,\ndespeckle, hue,\nsaturation, equalize,\nflip, mirror, masking,\nrotate, magnify,\nannotation,\ncephalometric tracing,\nceph growth,\nprojections, implant\nsimulations, film view,\nzooming, whitening,\nnerve canal tracing,\nmemo","Brightness, contrast,\nsharpness, inverse,\nfilm view, rotate,\nzooming, whitening,\nnerve canal tracing,\nmemo","Grayscale, invert,\nemboss, brightness,\ncontrast, gamma,\nsharpen, median,\ndespeckle, hue,\nsaturation, equalize,\nflip, mirror, masking,\nrotate, magnify,\nannotation,\ncephalometric tracing,\nceph growth,\nprojections, implant\nsimulations"],"rows":[["Image\nmanipulation","","","Grayscale, invert,\nemboss, brightness,\ncontrast, gamma,\nsharpen, median,\ndespeckle, hue,\nsaturation, equalize,\nflip, mirror, masking,\nrotate, magnify,\nannotation,\ncephalometric tracing,\nceph growth,\nprojections, implant\nsimulations, film view,\nzooming, whitening,\nnerve canal tracing,\nmemo","Brightness, contrast,\nsharpness, inverse,\nfilm view, rotate,\nzooming, whitening,\nnerve canal tracing,\nmemo","Grayscale, invert,\nemboss, brightness,\ncontrast, gamma,\nsharpen, median,\ndespeckle, hue,\nsaturation, equalize,\nflip, mirror, masking,\nrotate, magnify,\nannotation,\ncephalometric tracing,\nceph growth,\nprojections, implant\nsimulations"],["Implant module","","","Generic implant\nlibraries","Generic implant\nlibraries","Generic implant\nlibraries"],["3D imaging\ncapability","","","Clever One can view,\ntransfer and process\n3D radiographs.\nFurthermore, it\nsupports Smart Click,\nSmart Clipping,\nImplant Simulation\nand Canal Draw.","Includes interface to\n3D imaging software,\nEz3D-i. EzDent-i\nimaging software does\nnot view, transfer or\nprocess 3D\nradiographs.","Ez3D-I can view,\ntransfer and process\n3D radiographs.\nFurthermore, it\nsupports Smart Click,\nSmart Clipping,\nImplant Simulation\nand Canal Draw."],["Image annotation","","","Test, paint, ellipse,\npointer, select, draw,\nmagnify, line,\nrectangle, polygon,\nruler, protractor,\nsmile library, smudge,\nbrush, redeye\nreduction, select\nregion, copy / paste","Text, paint, ellipse,\npointer, select, draw,\nmagnify, line,\nrectangle, polygon,\nruler, protractor,\nsmile library, smudge,\nbrush, redeye\nreduction, select\nregion, copy / paste","Test, paint, ellipse,\npointer, select, draw,\nmagnify, line,\nrectangle, polygon,\nruler, protractor,\nsmile library, smudge,\nbrush, redeye\nreduction, select\nregion, copy / paste"],["","Distribution of","","USB, EzUpdater","EzUpdater","USB, EzUpdater"],["","Installation File","","","",""],["","for Upgrade","","","",""],["Customer\nSupport","Customer","","Manufacturer\nwebsite, phone\nnumber, and e-mail\ninformation provided.","Manufacturer\nwebsite, phone\nnumber, and e-mail\ninformation provided.","Manufacturer\nwebsite, phone\nnumber, and e-mail\ninformation provided."],["","Support","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250005-p11-t0","doc_id":"K250005","page_num":11,"bbox":[77.74,72.29,539.86,279.38],"n_rows":6,"n_cols":6,"columns":["Dose Information\nDisplay","","","File information, Dose\nindicator (if\napplicable)","File information, Dose\nindicator (if\napplicable)","File information, Dose\nindicator (if\napplicable)"],"rows":[["Dose Information\nDisplay","","","File information, Dose\nindicator (if\napplicable)","File information, Dose\nindicator (if\napplicable)","File information, Dose\nindicator (if\napplicable)"],["","Report","","Create, open, view,\nedit, delete","Create, open, view,\nedit, delete","Create, open, view,\nedit, delete"],["","Management","","","",""],["","Pre-integrated","","Clever Dent, Weclever","Clever Dent, Weclever","Clever Dent, Weclever"],["","PMS","","","",""],["Send E-mail","Send E-mail","","Send e-mail,\nattachment, compress\nto zip file, signature,\nconvert report to,\nconverted image to,\npatient information\nanonymization","Send e-mail,\nattachment, compress\nto zip file, signature,\nconvert report to,\nconverted image to,\npatient information\nanonymization","Send e-mail,\nattachment, compress\nto zip file, signature,\nconvert report to,\nconverted image to,\npatient information\nanonymization"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250023-p3-t0","doc_id":"K250023","page_num":3,"bbox":[257.72,168.62,570.36,265.22],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250023-p7-t0","doc_id":"K250023","page_num":7,"bbox":[156.46,482.12,567.93,738.15],"n_rows":10,"n_cols":10,"columns":["","","","Subject Device","","","","Primary Predicate","","Additional Predicate"],"rows":[["","","","Subject Device","","","","Primary Predicate","","Additional Predicate"],["","","","","","","","Device","","Device"],["","Manufacturer","","","Disior Ltd","","","Disior Ltd","","Disior Ltd"],["Trade Name","Trade Name","","SMART PCFD","","","","SMART Bun-Yo-Matic","",""],["","","","","","","","","","Bonelogic"],["","","","","","","","CT","",""],["","","","","","","","","",""],["","510(k)","","Subject Device","","","K240642","","","K223757"],["Indications\nfor Use","Indications","","SMART PCFD software\nincludes AI-powered\nalgorithms and is\nintended to be used to\nsupport orthopedic\nhealthcare professionals\nin the diagnosis and\nsurgical planning of\nProgressive Collapsing\nFoot Deformity (PCFD)\nin a hospital or clinic\nenvironment. The\nmedical image modality\nintended to be used in\nthe software is weight-\nbearing CT (WBCT).","","","SMART Bun-Yo-Matic CT\nsoftware is to be used by\northopaedic healthcare\nprofessionals for diagnosis\nand surgical planning in a\nhospital or clinic\nenvironment. The medical\nimaging type intended to be\nused as the input of the\nsoftware is Computed\nTomography (CT).\nSMART Bun-Yo-Matic CT\nsoftware provides:\n• Visualization report of\nthe three-dimensional","","","Bonelogic software is to\nbe used by orthopaedic\nhealthcare professionals\nfor diagnosis and surgical\nplanning in a hospital or\nclinic environment.\nBonelogic software\nprovides:\n• Semi-automatic\nsegmentation with\nmanual or assisted\ninput of bony\nstructure\nidentification from\nCT imaging input,"],["","for Use","","","","","","","",""]],"caption_candidate":"image processing, measuring and planning capabilities, and user interface.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250023-p9-t0","doc_id":"K250023","page_num":9,"bbox":[156.46,50.07,568.08,340.53],"n_rows":9,"n_cols":6,"columns":["","","","surgical instrument\nparameters combined\nwith the measurements is\nintended to be used to\nsupport orthopedic\nhealthcare professionals\nin surgical planning of\nPCFD.","",""],"rows":[["","","","surgical instrument\nparameters combined\nwith the measurements is\nintended to be used to\nsupport orthopedic\nhealthcare professionals\nin surgical planning of\nPCFD.","",""],["Input","","","Weight Bearing CT\nDICOM Computed\ntomography","Computed tomography\nDICOM Computed\ntomography","Computed tomography\nDICOM Computed\ntomography"],["","Image","","Segmentation of bone\nstructures","Segmentation of bone\nstructures","Segmentation of bone\nstructures"],["","Processing","","","",""],["Output","Output","","Automated case report of\nthe 3D model of patient\nanatomy, surgical\ninstrument parameters,\nand visualization of\nimplant","Automated case report of\nthe 3D model of patient\nanatomy, surgical\ninstrument parameters, and\nvisualization of implant","3D model of patient\nanatomy and case report\nof the 3D model patient\nanatomy"],["","Measuring","","Perform measurements\nfor presurgical planning","Perform measurements for\npresurgical planning","Perform measurements for\npresurgical planning"],["","and Planning","","","",""],["User\nInterface","User","","Graphical user interface\n(GUI) to a web\napplication used with a\nstandard web browser.","Graphical user interface\n(GUI) to a web application\nused with a standard web\nbrowser.","Graphical user interface\n(GUI) built on the Unity\ndevelopment engine."],["","Interface","","","",""]],"caption_candidate":"K250023","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p7-t0","doc_id":"K250035","page_num":7,"bbox":[70.5,283.51,541.5,714.63],"n_rows":9,"n_cols":4,"columns":["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],"rows":[["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],["Clearance\nDate","TBD","November 8, 2023","N/A"],["Operating\nPlatform","Server-based application\nsupporting:\n• Linux-based OS\n• Local deployment on\nWindows or Mac","Server-based application\nsupporting:\n• Linux-based OS\n• Local deployment on\nWindows or Mac","No change"],["Modalities","CT and MR","CT and MR","No change"],["Atlas-based\nSegmentation","No","No","No change"],["Automatically\ncontour\nimaging data\nusing\nmachine-\nlearning","Yes","Yes","No change"],["Cloud-based\nDeployment","Yes","Yes","No change"],["Local\nDeployment\nor Installation","Yes","Yes","No change"],["Neural","(1.0.0 models)","(1.0.0 models)","The subject device contains"]],"caption_candidate":"Table 1 – Comparison to Predicate Device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p8-t0","doc_id":"K250035","page_num":8,"bbox":[70.5,119.76,541.5,718.41],"n_rows":2,"n_cols":4,"columns":["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],"rows":[["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],["Network\nModels\nIncluded","• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Liver CT\n• Prostate MR\n(1.1.0 model)\n• Prostate MR\n(2.0.0 models)\n• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Abdomen CT\n• Lungs and Liver CT\n(3.1.0 models)*\n• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Abdomen CT\n• Lungs and Liver CT\n• MRT Additional Structures\nCT\n(4.0.0 models)\n• Head and Neck CT\n• Thorax CT\n• Abdomen CT\n• Pelvis CT\n• SurePlan MRT CT\n(4.1.0 models)\n• Head and Neck CT\n• Thorax CT\n• Whole Body –\nPhysiological\n• Uptake Organs CT\n(4.2.0 models)","• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Liver CT\n• Prostate MR\n(1.1.0 model)\n• Prostate MR\n(2.0.0 models)\n• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Abdomen CT\n• Lungs and Liver CT\n(3.1.0 models)*\n• Head and Neck CT\n• Prostate CT\n• Thorax CT\n• Abdomen CT\n• Lungs and Liver CT\n• MRT Additional Structures\nCT\n(4.0.0 models)\n• Head and Neck CT\n• Thorax CT\n• Abdomen CT\n• Pelvis CT\n• SurePlan MRT CT\n(4.1.0 models)\n• Head and Neck CT\n• Thorax CT\n• Whole Body –\nPhysiological\n• Uptake Organs CT","one new neural network\nmodel and three updated\nneural network models\ncompared to the predicate.\nThese 4 models were all\ntrained on the same\narchitecture as the\npredicate without any\nchanges. These 4 models\ncover all the existing\nstructures for contouring\nand additional, new\nstructures, which are\ndenoted in bold font.\nThese 4 models were all\ntested according to the\nsame procedures and\nacceptance criteria as the\npredicate. No unexpected\nresults were observed. The\nchanges do not raise new\nquestions for safety and\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p9-t0","doc_id":"K250035","page_num":9,"bbox":[70.5,119.76,541.5,710.29],"n_rows":2,"n_cols":4,"columns":["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],"rows":[["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],["","• Thorax CT\n- LN_IMN_L\n- LN_IMN_R\n- LN_Sclav_L\n- LN_Sclav_R\n- LN_Ax_L1_L\n- LN_Ax_L1_R\n- LN_Ax_L2_L\n- LN_Ax_L2_R\n- LN_Ax_L3_L\n- LN_Ax_L3_R\n- BrachialPlex_L***\n- BrachialPlex_R***\n- Breast_L***\n- Breast_R***\n- Breast_L_RTOG**\n- Breast_R_RTOG**\n- Bronchus\n- Carina\n- Cricoid\n- Esophagus\n- Glnd_Thyroid\n- GreatVes***\n- Heart***\n- Humerus_Head_L\n- Humerus_Head_R\n- Kidney_L\n- Kidney_R\n- Larynx***\n- Liver\n- Lung_L\n- Lung_R\n- Musc_Constrict\n- Pancreas\n- SpinalCord\n- Stomach***\n- Trachea\n- Ribs**\n- Chestwall_L**\n- Chestwall_R**\n- A_Asc_Aorta**\n- A_LAD**\n• Abdomen CT\n- Bladder\n- Bowel***","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p10-t0","doc_id":"K250035","page_num":10,"bbox":[71.25,119.76,541.5,649.93],"n_rows":5,"n_cols":4,"columns":["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],"rows":[["ITEM","Subject Device:\nContour ProtégéAI+\n(K250035)","Predicate Device:\nContour ProtégéAI\n(K231765)","Substantial Equivalence\nDiscussion"],["","- Bowel Bag***\n- Cauda Equina\n- Left Kidney\n- Right Kidney\n- Liver\n- Spinal Cord\n- Stomach***\n• Female Pelvis CT**\n- Bowel Bag**\n- Bowel**\n- LN Pelvics**\n- Bladder**\n- Uterocervix**\n- Colon Sigmoid**\n- Cauda Equina**\n- Sacral Plexus**\n- Sacrum**\n- Rectum**\n- Femur Head L**\n- Femur Head R**\n• SurePlan MRT CT\n- Bone***\n- Glnd_Lacrimal_L\n- Glnd_Lacrimal_R\n- Glnd_Submand_L\n- Glnd_Submand_R\n- Glnd_Thyroid\n- Kidney_L (Kidney_L w/o\nRenal Pelvis)\n- Kidney_R (Kidney_R\nw/o Renal Pelvis)\n- Liver\n- Lung_L\n- Lung_R\n- Parotid_L\n- Parotid_R\n- Spleen","",""],["* The 3.1.0 models share the same training images and architecture as the 3.0.0 models. Some errors and style","","",""],["inconsistencies in the training segmentations were corrected before re-training, resulting in the 3.1.0 models.","","",""],["** Indicates new contour/mode","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p13-t0","doc_id":"K250035","page_num":13,"bbox":[72.17,143.61,534.25,697.22],"n_rows":16,"n_cols":7,"columns":["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],"rows":[["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],["Thorax","BrachialPlex_L","0.30 ± 0.14","0.41 ± 0.15\n(0.28) *","3.01 ±\n1.19","2.89 ± 1.07\n(3.94) *","2.43"],["","BrachialPlex_R","0.31 ± 0.12","0.39 ± 0.15\n(0.26) *","3.08 ±\n1.54","3.11 ± 1.38\n(4.55) *","2.43"],["","Breast_L","0.74 ± 0.11","0.79 ± 0.07\n(0.73) *","5.73 ±\n3.10","5.00 ± 2.53\n(6.98) *","2.38"],["","Breast_R","0.76 ± 0.12","0.80 ± 0.11\n(0.71) *","5.03 ±\n2.72","4.49 ± 2.02\n(6.24) *","2.57"],["","Breast_L_RTO\nG","0.74 ± 0.11","0.77 ± 0.11\n(0.69) *","5.73 ±\n3.10","5.47 ± 3.72\n(7.87)","2.5"],["","Breast_R_RTO\nG","0.76 ± 0.12","0.77 ± 0.15\n(0.67) *","5.03 ±\n2.72","5.10 ± 3.17\n(7.24)","2.5"],["","Bronchus","0.57 ± 0.19","0.62 ± 0.14\n(0.50) **","2.69 ±\n2.22","1.86 ± 0.90\n(3.19) *","2.63"],["","Carina","0.37 ± 0.18","0.50 ± 0.12\n(0.41) *","2.67 ±\n2.65","1.93 ± 0.83\n(3.07) *","2.43"],["","Cricoid","0.02 ± 0.04","0.06 ± 0.05\n(0.02) *","4.77 ±\n1.53","5.01 ± 1.40\n(6.27) *","2.86"],["","Esophagus","0.47 ± 0.17","0.69 ± 0.16\n(0.63) *","2.73 ±\n2.19","1.08 ± 1.53\n(1.71) *","2.5"],["","Glnd_Thyroid","0.46 ± 0.18","0.66 ± 0.18\n(0.53) *","2.84 ±\n1.90","1.68 ± 1.44\n(2.86) *","2.86"],["","GreatVes","0.64 ± 0.17","0.70 ± 0.16\n(0.53) **","4.59 ±\n1.99","3.44 ± 1.99\n(5.46) *","2.63"],["","Heart","0.88 ± 0.08","0.90 ± 0.07\n(0.87) *","3.05 ±\n2.03","2.49 ± 1.84\n(3.08) *","2.63"],["","Humerus_Hea\nd_L","0.60 ± 0.24","0.62 ± 0.24\n(0.42) **","0.38 ±\n0.23","0.33 ± 0.22\n(0.52) *","3"],["","Humerus_Hea\nd_R","0.57 ± 0.22","0.60 ± 0.22\n(0.41) **","0.78 ±\n2.00","0.33 ± 0.35\n(1.60) *","3"]],"caption_candidate":"Table 2 – Dice, MDA, and external evaluation results.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p14-t0","doc_id":"K250035","page_num":14,"bbox":[72.25,119.78,534.33,704.18],"n_rows":18,"n_cols":7,"columns":["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],"rows":[["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],["","Kidney_L","0.73 ± 0.19","0.90 ± 0.09\n(0.83) *","3.75 ±\n2.66","1.32 ± 1.13\n(2.27) *","2.75"],["","Kidney_R","0.73 ± 0.19","0.89 ± 0.09\n(0.83) *","3.97 ±\n2.60","1.41 ± 1.06\n(2.34) *","2.75"],["","Larynx","0.47 ± 0.19","0.59 ± 0.14\n(0.51) *","3.42 ±\n1.32","2.87 ± 1.34\n(3.51) *","2.63"],["","Liver","0.84 ± 0.12","0.90 ± 0.13\n(0.85) *","5.06 ±\n4.18","3.56 ± 9.12\n(6.39) *","2.71"],["","Lung_L","0.95 ± 0.02","0.96 ± 0.02\n(0.96) *","1.12 ±\n0.46","0.79 ± 0.40\n(0.94) *","2.75"],["","Lung_R","0.95 ± 0.03","0.97 ± 0.03\n(0.96) *","1.36 ±\n0.67","0.85 ± 0.48\n(1.04) *","2.75"],["","Musc_Constrict","0.40 ± 0.17","0.50 ± 0.17\n(0.39) *","2.00 ±\n1.79","1.67 ± 1.55\n(2.71) *","3"],["","Pancreas","0.17 ± 0.17","0.47 ± 0.21\n(0.36) *","16.43 ±\n16.42","6.80 ± 8.89\n(14.66) **","2.17"],["","SpinalCord","0.66 ± 0.16","0.64 ± 0.17\n(0.59) *","1.29 ±\n0.91","1.28 ± 0.72\n(1.50) *","2.5"],["","Stomach","0.46 ± 0.22","0.73 ± 0.21\n(0.64) *","12.56 ±\n13.48","6.89 ± 20.57\n(14.36) **","2.13"],["","Trachea","0.68 ± 0.15","0.74 ± 0.17\n(0.66) *","1.43 ±\n0.65","1.12 ± 0.64\n(1.46) *","2.63"],["","A_LAD","0.07 ± 0.09","0.32 ± 0.12\n(0.22) *","8.77 ±\n10.69","3.43 ± 4.46\n(11.41) **","2.67"],["","A_Aorta_Asc","0.72 ± 0.16","0.83 ± 0.17\n(0.68) **","2.90 ±\n2.16","1.11 ± 0.60\n(2.64) *","2.14"],["","Rib","0.25 ± 0.09","0.28 ± 0.11\n(0.21) *","35.64 ±\n12.65","39.04 ± 14.62\n(49.68) **","2.63"],["","Chestwall_L","0.40 ± 0.16","0.39 ± 0.17\n(0.19) **","4.35 ±\n1.12","4.44 ± 1.24\n(5.87) *","2.43"],["","Chestwall_R","0.45 ± 0.18","0.42 ± 0.18\n(0.22) **","4.66 ±\n1.65","4.69 ± 1.56\n(6.51) *","2.43"],["","LN_Ax_L1_L","0.59 ± 0.09","0.63 ± 0.10\n(0.75) *","2.76 ±\n0.89","2.25 ± 0.80\n(3.32) *","2.67"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p15-t0","doc_id":"K250035","page_num":15,"bbox":[72.2,119.78,534.33,704.18],"n_rows":18,"n_cols":7,"columns":["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],"rows":[["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],["","LN_Ax_L1_R","0.52 ± 0.12","0.58 ± 0.13\n(0.69) *","3.46 ±\n1.04","2.90 ± 1.52\n(4.09) *","2.67"],["","LN_Ax_L2_L","0.57 ± 0.16","0.64 ± 0.13\n(0.77) **","2.57 ±\n1.25","1.93 ± 0.88\n(2.88) *","2.67"],["","LN_Ax_L2_R","0.53 ± 0.20","0.60 ± 0.18\n(0.73) **","2.91 ±\n1.29","2.44 ± 1.26\n(3.31) *","2.67"],["","LN_Ax_L3_L","0.55 ± 0.17","0.62 ± 0.19\n(0.76) **","2.21 ±\n1.11","1.90 ± 1.26\n(2.87) *","2.67"],["","LN_Ax_L3_R","0.46 ± 0.16","0.52 ± 0.17\n(0.65) *","3.30 ±\n1.95","2.74 ± 1.73\n(4.24) *","2.67"],["","LN_IMN_L","0.17 ± 0.11","0.41 ± 0.17\n(0.59) *","4.75 ±\n3.26","1.82 ± 0.85\n(5.05) **","3"],["","LN_IMN_R","0.23 ± 0.16","0.48 ± 0.20\n(0.63) *","3.36 ±\n1.95","1.69 ± 1.38\n(3.09) *","3"],["","LN_Sclav_L","0.58 ± 0.15","0.66 ± 0.13\n(0.79) *","2.84 ±\n1.94","2.49 ± 1.70\n(4.18) *","2"],["","LN_Sclav_R","0.48 ± 0.09","0.55 ± 0.09\n(0.64) *","2.97 ±\n0.75","2.67 ± 0.90\n(3.56) *","2.33"],["Abdomen","Bladder","0.72 ± 0.23","0.92 ± 0.16\n(0.81) *","3.97 ±\n3.00","0.78 ± 0.73\n(1.93) *","2.6"],["","Bowel","0.34 ± 0.14","0.52 ± 0.19\n(0.37) *","9.26 ±\n3.49","5.05 ± 3.17\n(8.13) **","2.5"],["","BowelBag","0.30 ± 0.09","0.36 ± 0.11\n(0.29) *","14.13 ±\n3.62","10.08 ± 3.36\n(12.50) *","2.89"],["","CaudaEquina","0.62 ± 0.15","0.69 ± 0.13\n(0.59) *","1.17 ±\n0.51","0.95 ± 0.53\n(1.33) *","2.6"],["","Kidney_L","0.74 ± 0.17","0.94 ± 0.03\n(0.85) *","3.86 ±\n2.48","0.82 ± 0.41\n(2.12) *","2.9"],["","Kidney_R","0.75 ± 0.18","0.92 ± 0.07\n(0.83) *","3.97 ±\n3.35","0.96 ± 0.62\n(2.74) *","2.9"],["","Liver","0.84 ± 0.12","0.93 ± 0.08\n(0.86) *","5.23 ±\n3.65","2.01 ± 2.14\n(3.85) *","2.8"],["","SpinalCord","0.60 ± 0.16","0.65 ± 0.14\n(0.56) *","1.13 ±\n0.60","0.83 ± 0.32\n(1.10) *","2.9"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p16-t0","doc_id":"K250035","page_num":16,"bbox":[72.17,119.78,534.33,716.18],"n_rows":18,"n_cols":7,"columns":["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],"rows":[["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],["","Stomach","0.49 ± 0.21","0.82 ± 0.11\n(0.72) *","11.56 ±\n14.68","2.68 ± 2.02\n(9.37) **","2.5"],["Female\nPelvis","Bladder","0.61 ± 0.18","0.91 ± 0.06\n(0.83) *","5.53 ±\n3.76","1.04 ± 0.94\n(2.66) *","2.75"],["","Bag_Bowel","0.45 ± 0.17","0.52 ± 0.20\n(0.36) **","8.89 ±\n2.79","6.89 ± 2.25\n(9.06) *","2.63"],["","Bowel","0.34 ± 0.10","0.55 ± 0.19\n(0.42) *","8.81 ±\n3.05","4.84 ± 3.03\n(7.44) *","2.75"],["","Colon_Sigmoid","0.05 ± 0.05","0.47 ± 0.24\n(0.36) *","20.55 ±\n12.23","14.72 ± 15.14\n(23.56) **","2.5"],["","Femur_Head_\nL","0.86 ± 0.07","0.91 ± 0.08\n(0.84) *","1.43 ±\n0.78","0.95 ± 1.03\n(1.75) *","2.75"],["","Femur_Head_\nR","0.87 ± 0.05","0.92 ± 0.02\n(0.89) *","1.22 ±\n0.59","0.69 ± 0.28\n(1.09) *","2.75"],["","UteroCervix","0.16 ± 0.16","0.65 ± 0.27\n(0.47) *","10.65 ±\n5.73","4.39 ± 13.21\n(13.49) **","2"],["","LN_Pelvics","0.64 ± 0.05","0.74 ± 0.06\n(0.69) *","4.37 ±\n1.11","4.12 ± 1.52\n(5.28) *","2.75"],["","Rectum","0.38 ± 0.16","0.75 ± 0.12\n(0.67) *","6.30 ±\n3.30","1.52 ± 1.66\n(3.04) *","2.63"],["","SacralPlex","0.02 ± 0.01","0.03 ± 0.01\n(0.02) *","13.03 ±\n1.73","12.81 ± 1.86\n(14.38) *","2.5"],["","Sacrum","0.84 ± 0.02","0.89 ± 0.01\n(0.87) *","1.58 ±\n0.32","1.09 ± 0.17\n(1.31) *","3"],["","CaudaEquina","0.65 ± 0.11","0.66 ± 0.11\n(0.58) *","1.19 ±\n0.58","0.94 ± 0.59\n(1.39) *","2.57"],["SurePlan\nMRT","Bone","0.76 ± 0.08","0.83 ± 0.05\n(0.71) *","4.77 ±\n1.97","4.57 ± 3.35\n(9.50) **","3"],["","Glnd_Lacrimal\n_L","0.23 ± 0.17","0.30 ± 0.21\n(0.16) *","1.99 ±\n0.86","1.26 ± 0.57\n(1.96) *","2.67"],["","Glnd_Lacrimal\n_R","0.23 ± 0.16","0.36 ± 0.23\n(0.22) *","1.53 ±\n0.80","1.18 ± 0.87\n(1.97) *","2.67"],["","Glnd_Subman","0.58 ± 0.12","0.67 ± 0.29","2.19 ±","1.00 ± 0.35","3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p17-t0","doc_id":"K250035","page_num":17,"bbox":[72.25,119.78,534.33,507.56],"n_rows":12,"n_cols":7,"columns":["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],"rows":[["4.2.0 CT\nModel","Structure","Dice MIM\nAtlas","Dice\nContour\nProtégéAI","MDA\nMIM\nAtlas","MDA\nContour\nProtégéAI","External\nEvaluation\nScore"],["","d_L","","(0.52) *","0.76","(1.45) *",""],["","Glnd_Subman\nd_R","0.56 ± 0.16","0.66 ± 0.31\n(0.48) *","2.41 ±\n1.14","0.97 ± 0.33\n(1.68) *","3"],["","Glnd_Thyroid","0.47 ± 0.19","0.75 ± 0.12\n(0.63) **","2.98 ±\n1.95","1.29 ± 1.20\n(2.46) *","2.67"],["","Kidney_L","0.72 ± 0.18","0.91 ± 0.04\n(0.82) *","4.08 ±\n2.52","1.56 ± 0.61\n(2.89) *","3"],["","Kidney_R","0.76 ± 0.17","0.91 ± 0.03\n(0.82) *","3.87 ±\n3.14","1.45 ± 0.63\n(3.12) *","3"],["","Liver","0.85 ± 0.12","0.93 ± 0.07\n(0.88) *","4.82 ±\n3.51","1.79 ± 1.50\n(3.25) *","2.67"],["","Lung_L","0.94 ± 0.03","0.96 ± 0.04\n(0.93) *","1.42 ±\n0.51","0.90 ± 0.49\n(1.32) *","3"],["","Lung_R","0.94 ± 0.04","0.96 ± 0.05\n(0.92) *","1.66 ±\n0.75","1.07 ± 0.86\n(1.75) *","3"],["","Parotid_L","0.71 ± 0.09","0.81 ± 0.05\n(0.78) *","2.17 ±\n0.77","1.42 ± 0.40\n(1.73) *","3"],["","Parotid_R","0.71 ± 0.09","0.82 ± 0.05\n(0.78) *","2.17 ±\n0.73","1.34 ± 0.48\n(1.67) *","3"],["","Spleen","0.72 ± 0.10","0.95 ± 0.02\n(0.87) *","4.38 ±\n1.87","0.62 ± 0.45\n(2.08) *","2.67"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p18-t0","doc_id":"K250035","page_num":18,"bbox":[72.11,143.59,540.13,274.25],"n_rows":5,"n_cols":3,"columns":["4.2.0 CT Models","MIM Atlas","Contour ProtégéAI"],"rows":[["4.2.0 CT Models","MIM Atlas","Contour ProtégéAI"],["Thorax","220.33 ± 232.42","181.44 ± 219.43 (200.79) *"],["Abdomen","354.53 ± 386.05","238.05 ± 309.40 (312.07) *"],["Female Pelvis","433.24 ± 392.19","314.13 ± 349.77 (383.86) *"],["SurePlan MRT","216.52 ± 207.87","133.01 ± 160.23 (167.60) *"]],"caption_candidate":"Table 3 – 4.2.0 CT Models cumulative APL.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p18-t1","doc_id":"K250035","page_num":18,"bbox":[72.11,333.35,540.13,703.66],"n_rows":16,"n_cols":4,"columns":["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],"rows":[["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],["Thorax","BrachialPlex_L","100","100"],["","BrachialPlex_R","100","100"],["","Breast_L","100","100"],["","Breast_R","100","100"],["","Breast_L_RTOG","100","100"],["","Breast_R_RTOG","100","100"],["","Bronchus","100","100"],["","Carina","99","100"],["","Cricoid","91","100"],["","Esophagus","99","100"],["","Glnd_Thyroid","100","77"],["","GreatVes","100","91"],["","Heart","100","100"],["","Humerus_Head_L","100","100"],["","Humerus_Head_R","100","100"]],"caption_candidate":"Table 4 – 4.2.0 CT Models localization accuracy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p19-t0","doc_id":"K250035","page_num":19,"bbox":[72.25,119.76,540.33,715.41],"n_rows":26,"n_cols":4,"columns":["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],"rows":[["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],["","Kidney_L","100","95"],["","Kidney_R","100","100"],["","Larynx","100","100"],["","Liver","99","95"],["","Lung_L","100","100"],["","Lung_R","100","100"],["","Musc_Constrict","100","91"],["","Pancreas","96","95"],["","SpinalCord","100","100"],["","Stomach","97","100"],["","Trachea","99","100"],["","A_LAD","100","86"],["","A_Aorta_Asc","96","100"],["","Rib","100","86"],["","Chestwall_L","100","100"],["","Chestwall_R","100","100"],["","LN_Ax_L1_L","100","100"],["","LN_Ax_L1_R","100","100"],["","LN_Ax_L2_L","100","100"],["","LN_Ax_L2_R","100","100"],["","LN_Ax_L3_L","100","100"],["","LN_Ax_L3_R","100","100"],["","LN_IMN_L","100","100"],["","LN_IMN_R","100","100"],["","LN_Sclav_L","100","100"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p20-t0","doc_id":"K250035","page_num":20,"bbox":[72.14,119.76,540.33,715.41],"n_rows":26,"n_cols":4,"columns":["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],"rows":[["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],["","LN_Sclav_R","100","100"],["Abdomen","Bladder","98","95"],["","Bowel","100","100"],["","BowelBag","100","100"],["","CaudaEquina","100","100"],["","Kidney_L","100","91"],["","Kidney_R","100","100"],["","Liver","100","100"],["","SpinalCord","100","100"],["","Stomach","100","100"],["Female Pelvis","Bladder","100","100"],["","Bag_Bowel","100","100"],["","Bowel","100","100"],["","Colon_Sigmoid","93","86"],["","Femur_Head_L","100","100"],["","Femur_Head_R","100","95"],["","UteroCervix","97","100"],["","LN_Pelvics","100","100"],["","Rectum","100","100"],["","SacralPlex","100","100"],["","Sacrum","100","100"],["","CaudaEquina","100","100"],["SurePlan MRT","Bone","*","100"],["","Glnd_Lacrimal_L","*","100"],["","Glnd_Lacrimal_R","*","95"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250035-p21-t0","doc_id":"K250035","page_num":21,"bbox":[72.25,119.76,540.33,400.41],"n_rows":12,"n_cols":4,"columns":["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],"rows":[["4.2.0 CT Models","Structure","Relevant FOV","Whole Body CT"],["","Glnd_Submand_L","*","95"],["","Glnd_Submand_R","*","100"],["","Glnd_Thyroid","*","82"],["","Kidney_L","*","91"],["","Kidney_R","*","95"],["","Liver","*","100"],["","Lung_L","*","100"],["","Lung_R","*","100"],["","Parotid_L","*","100"],["","Parotid_R","*","100"],["","Spleen","*","100"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250042-p8-t0","doc_id":"K250042","page_num":8,"bbox":[68.87,150.0,742.62,492.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Product Code","QIH, LLZ","LLZ, QIH","Yes","---"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Yes","---"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","---"],["Intended\nuse/Indications for\nuse","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the\nsystem in the revision and approval of the\noutput of the planning. The multi-platform\nsystem works with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using\nmedical imaging with the additional","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of","Yes","---"]],"caption_candidate":"Table 1: Summary of Predicate and Subject Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250042-p9-t0","doc_id":"K250042","page_num":9,"bbox":[68.84,112.4,742.71,495.5],"n_rows":6,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","capability of planning the 2D or 3D\nenvironment. The system is designed for\nthe medical specialties within surgery and\nno specific use environment is mandatory,\nwhereas the typical use environment is a\nroom with a computer. The patient target\ngroup is adult patients who have an injury\nor disability diagnosed previously. There\nare no other considerations for the\nintended patient population.","planning the 2D or 3D environment. The\nsystem is designed for the medical\nspecialties within surgery and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","",""],["Contraindications","No contraindications specific to this\ndevice.","No contraindications specific to this device.","Yes","---"],["Clinical purpose","PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","Yes","---"],["Anatomical regions","PeekMed web allows the surgeon to\nperform the pre-surgical planning\nefficiently in the following anatomical\nregions:\n- Hip\n- Knee\n- Upper limb\n- Foot","PeekMed web allows the surgeon to\nperform the pre-surgical planning efficiently\nin the following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes","—"],["Patient Population","Adults","Adults","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250042-p10-t0","doc_id":"K250042","page_num":10,"bbox":[68.9,112.4,742.71,486.5],"n_rows":11,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["End users","Healthcare Professionals","Healthcare Professionals","Yes","---"],["Device availability","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Yes","---"],["Software\nArchitecture","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Yes","---"],["Workflow","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export\nthe case.","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","Yes","---"],["Internet connection","Required","Required","Yes","---"],["Images source","Receives medical images from various\nsources","Receives medical images from various\nsources","Yes","---"],["Data processing","The software processes data to provide\nan overlap and dimensioning of digital\nrepresentations of the prosthetic material","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","Yes","---"],["Digital overlap of\ntemplates","Allows the overlap of models and the\nintersection of the models","Allows the overlap of models and the\nintersection of the models","Yes","---"],["Interactive model\npositioning","Yes","Yes","Yes","---"],["Interactive model","Yes","Yes","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250042-p11-t0","doc_id":"K250042","page_num":11,"bbox":[68.9,112.4,742.71,486.5],"n_rows":11,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["dimensioning","","","",""],["Model rotation","Yes","Yes","Yes","---"],["Support for digital\nprosthetic\nmaterials provided\nby the\nmanufacturers","Yes","Yes","Yes","---"],["Pre-surgical\nplanning","Yes","Yes","Yes","---"],["Type of\npre-surgical\nplanning","Automatic or Manual","Automatic or Manual","Yes","---"],["Contact with the\npatient","No","No","Yes","---"],["Control of life\nsupporting devices","No","No","Yes","---"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","Yes","---"],["Ability to add\nadditional modules\nwhen available","Yes","Yes","Yes","---"],["Automatic bone","Yes","Yes","Yes","The subject device includes new ML"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250042-p12-t0","doc_id":"K250042","page_num":12,"bbox":[68.9,112.4,742.71,432.75],"n_rows":3,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K240926","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["segmentation","- Hip (X-ray and CT scan)\n- Knee (X-ray and CT scan)\n- Upper limb (CT scan)\n- Foot (CT scan)","- Hip (X-ray and CT scan)\n- Knee (X-ray and CT scan)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","","model variants for segmentation.\nBoth devices allow the planning for\nfoot region with CT scans but the\nsubject device also allows with X-ray\nimages.\nThis does not constitute an intended\npurpose update nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices."],["Type of\nlandmarking","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray and CT scan)\n- Upper limb (CT scan)\n- Foot (CT scan)","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray and CT scan)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes","The subject device includes new ML\nmodel variants for landmarking.\nBoth devices allow the planning for\nfoot region with CT scans but the\nsubject device also allows with X-ray\nimages.\nThis does not constitute an intended\npurpose update nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p5-t0","doc_id":"K250064","page_num":5,"bbox":[72.3,182.5,539.75,344.5],"n_rows":3,"n_cols":2,"columns":["Company Name and Address","MVision AI Oy\nPaciuksenkatu 29, 6th floor\n00270 Helsinki, Finland\nTel: +358 040 5489229\nWebsite: www.mvision.ai"],"rows":[["Company Name and Address","MVision AI Oy\nPaciuksenkatu 29, 6th floor\n00270 Helsinki, Finland\nTel: +358 040 5489229\nWebsite: www.mvision.ai"],["Contact Person","Kalpana Jha\nVP of Regulatory and Market Strategy\nkalpana.jha@mvision.ai\nTel: +358 44 9214 354"],["Establishment Registration Number","3022745617"]],"caption_candidate":"Submitter's Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p5-t1","doc_id":"K250064","page_num":5,"bbox":[72.3,385.45,539.75,533.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name","Dose+"],"rows":[["Device Trade Name","Dose+"],["Device Classification Name","System, Planning, Radiation Therapy Treatment"],["Product Code","MUJ"],["Regulation","Medical charged-particle radiation therapy system\n(21 CFR 892.5050)"],["Device Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p5-t2","doc_id":"K250064","page_num":5,"bbox":[72.3,574.56,539.75,640.5],"n_rows":3,"n_cols":2,"columns":["Device Name","Oncospace"],"rows":[["Device Name","Oncospace"],["510(k) Number","K222803"],["Manufacturer","Oncospace, Inc."]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p7-t0","doc_id":"K250064","page_num":7,"bbox":[72.25,236.81,539.37,698.5],"n_rows":4,"n_cols":4,"columns":["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],"rows":[["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],["Product Code","MUJ","MUJ","Same"],["Device Classification","System, Planning, Radiation\nTherapy Treatment","System, Planning,\nRadiation Therapy\nTreatment","Same"],["Intended Use /\nIndication for Use","Dose+ is a software-only medical\ndevice intended for use by qualified,\ntrained radiation therapy\nprofessionals (including but not\nlimited to medical physicists,\nradiation oncologists, and medical\ndosimetrists).The device is intended\nfor male patients with localized\nprostate cancer or prostate cancer\nwith pelvic lymph node involvement\nwho are undergoing external beam\nradiation therapy treatment. The\nsoftware uses machine\nlearning-based algorithms to\nautomatically produce 3D dose\ndistributions from patient-specific\nanatomical geometry and target\ndose prescription.\nThe predicted dose distribution\noutput is required to be transferred\nto a radiotherapy treatment\nplanning system (TPS) or reviewed\nby any DICOM-RT compliant\nsoftware prior to further use in\nclinical workflows. Dose+ is\nintended to provide additional\ninformation during the treatment\nplanning process facilitating the\ncreation and review of a treatment\nplan.","Oncospace is used to\nconfigure and review\nradiotherapy treatment\nplans for a patient with\nmalignant or benign\ndisease in the prostate,\nhead, and neck regions.\nIt allows for the set up of\nradiotherapy treatment\nprotocols, association of\na potential treatment plan\nwith the protocol(s),\nsubmission of a dose\nprescription and\nachievable dosimetric\ngoals to a treatment\nplanning system, and\nreview of the treatment\nplan. It is intended for use\nby qualified, trained\nradiation therapy\nprofessionals (such as\nmedical physicists,\noncologists, and\ndosimetrists). This device\nis for prescription use by\norder of a physician.","Both devices provide\ndosimetric guidance for\nexternal beam\nradiotherapy treatment\nplanning."]],"caption_candidate":"predicate device that support the claim of substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p8-t0","doc_id":"K250064","page_num":8,"bbox":[72.33,72.1,539.42,689.5],"n_rows":11,"n_cols":4,"columns":["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],"rows":[["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],["","Dose+ is not intended to be used\nfor disease diagnosis and treatment\ndecision purposes in clinical\nworkflows.","",""],["Typical Users","Radiation therapy professionals,\nincluding medical physicists,\noncologists, and dosimetrists","Radiation therapy\nprofessionals, including\nmedical physicists,\noncologists, and\ndosimetrists","Same"],["Patient Population","Patients with malignant or benign\ndisease in the prostate undergoing\nexternal beam radiation therapy","Patients with malignant or\nbenign disease in the\nprostate, head, and neck\nregions undergoing\nexternal beam radiation\ntherapy","The subject device is not\nindicated for head and\nneck treatments"],["Platform","Client-Server Architecture\n(Clinic-provided client machines or\ncloud servers controlled by the\nmanufacturer)","Client-Server Architecture\n(Clinic-provided client\nmachines or cloud\nWindows servers\ncontrolled by the\nmanufacturer)","Same architecture;\nDifferent only in the\noperating system of the\ncloud servers"],["Operating System (OS)","Windows Client,\nLinux Server","Windows (Client and\nServer)","Different only in the OS of\nthe cloud servers"],["DICOM-RT Compliant","Yes","Yes","Same"],["Full Treatment Planning\nSystem","No","No","Same"],["Connected to or\nControlling of Radiation\nDelivery Devices","No","No","Same"],["Input Data","A patient’s CT images, RT Structure\nsets and target dose prescription in\nROI names","A patient’s CT images,\nRT Structure sets and\ntarget dose in treatment\nprotocols or user\nspecified","Same patient-specific\ndata. Input explicitly\nprovided to Dose+, while\nthe predicate device\nrequires user input or the\ncreation of protocol\ntemplates."],["Processing and Device\nOutput","Processes input using locked\nmachine learning (ML) models\ntrained on patient-specific\nanatomical geometry to generate\nthe predicted 3D dose distribution","Processes treatment plan\ndata using locked\nmachine learning (ML)\nmodels trained on\npatient-specific\nanatomical geometry to\npredict achievable\ndosimetric goals/\nobjectives for OARs","Same processing\nfundamentals but\ndifferent ML models\n(complete 3D dose\nprediction vs. dosimetric\nobjectives prediction for\nOARs)."]],"caption_candidate":"510(k) Summary – Dose+","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250064-p9-t0","doc_id":"K250064","page_num":9,"bbox":[72.33,72.1,539.42,270.5],"n_rows":3,"n_cols":4,"columns":["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],"rows":[["Device\nCharacteristic","Subject Device (Dose+)","Predicate Device\n(Oncospace, K222803)","Comparison"],["Output Format","Exports DICOM RT Dose objects\nwith complete 3D dose distribution\nthat may be reviewed using a\nthird-party DICOM-RT compliant\nsoftware or that may be directly\ntransferred to a radiotherapy\ntreatment planning system (TPS)\nfor review prior to further use in\nclinical workflows","Exports dosimetric goals/\nobjectives in different\nspecific formats for\nreview in a treatment\nplanning system (TPS)\nprior to further use in\nclinical workflows","Different output formats\nbut both devices provide\ndosimetric information to\nassist with plan\noptimization during\ntreatment planning."],["Plan Review\nFunctionality","Does not include treatment plan\nreview features.","Contains integrated\nfeatures and GUI for\ntreatment plan review,\nincluding DVH\nvisualization","Different.\nDose+ relies on existing\nthird party TPS review\nfunctionality."]],"caption_candidate":"510(k) Summary – Dose+","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250087-p10-t0","doc_id":"K250087","page_num":10,"bbox":[89.58,585.6,256.98,670.56],"n_rows":3,"n_cols":2,"columns":["BMI","Success Rate"],"rows":[["BMI","Success Rate"],["Overweight\n>25","92%"],["Normal\n<25","95%"]],"caption_candidate":"with known BMI:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250177-p8-t0","doc_id":"K250177","page_num":8,"bbox":[72.36,375.82,539.73,704.97],"n_rows":26,"n_cols":4,"columns":["","EPIQ and Affiniti Series","EPIQ and Affiniti Series",""],"rows":[["","EPIQ and Affiniti Series","EPIQ and Affiniti Series",""],["","Diagnostic Ultrasound System","Diagnostic Ultrasound System",""],["Feature","","","Comparison"],["","","(K242020)",""],["","","",""],["","Proposed Device","Predicate Device",""],["","Class II","Class II","Identical"],["USA FDA","","",""],["Classification","","",""],["","","",""],["","IYN","IYN","Identical"],["Primary Product","","",""],["Code","","",""],["","","",""],["","21 CFR 892.1550","21 CFR 892.1550","Identical"],["Primary Regulation","","",""],["Number","","",""],["","","",""],["","Remote Software Management","Remote Software Management","Subject of this\nsubmission"],["Marketing Name of","","",""],["Application","","",""],["","","",""],["","Remote Software Management\nprovides capabilities to remotely\nupgrade to major software\nreleases on EPIQ and Affiniti.\nRSM is capable of deploying the\nfollowing packages onto the\nsystem:\nOS Packages\nDevice Drivers\nPrinter Drivers","The Remote Software\nManagement feature allows\nremote update capabilities, such\nas bug fixes and patches. System\nupgrades are performed by Field\nService Engineer","The proposed RSM will\nprovide the patch\nupgrade, major releases,\nAutomatic and scheduled\ndownloads of the\nsoftware where the\npredicated RSM had only\nthe bug fixed and patch\nupgrades. The subject of\nthis submission is to\nprovide upgrades with\nthe full RSM."],["Application","","",""],["Description","","",""],["","","",""]],"caption_candidate":"substantially equivalent to the predicate devices (K242020).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250177-p9-t0","doc_id":"K250177","page_num":9,"bbox":[72.33,72.34,539.71,478.41],"n_rows":15,"n_cols":4,"columns":["","EPIQ and Affiniti Series","EPIQ and Affiniti Series",""],"rows":[["","EPIQ and Affiniti Series","EPIQ and Affiniti Series",""],["","Diagnostic Ultrasound System","Diagnostic Ultrasound System",""],["Feature","","","Comparison"],["","","(K242020)",""],["","","",""],["","Proposed Device","Predicate Device",""],["","BIOS/UEFI Version\nApplication Packages\nService Application Packages\nAutomatic backup/restore of\nexisting system settings\nAlong with the above\nfunctionalities, it also supports\nAutomatic and Scheduled\nsoftware downloads/installation.","",""],["","The system must be connected to\nthe Philips Remote Server. The\nuser can go into Philips Support\nConnect and navigate the\ndownload and installation process\nfor system updates and upgrades.\nAdditionally, Remote Software\nManagement supports automatic\nand scheduled software\ndownloads and installations.","The system must be connected to\nthe Philips Remote Server. The\nuser can go into Philips Support\nConnect and navigate the\ndownload and installation process\nfor system updates only.","The proposed RSM will\nprovide an automatic,\nScheduled download to\nthe user where the\npredicate device requires\nthe user to connect\nPhilips Support and\nnavigate\nsystem manually. There\nis no change to the\nuser’s functionality with\nfull RSM feature."],["User Interface","","",""],["Presentation","","",""],["","","",""],["","Remote Service Engineer\nperforms verification post\ninstallation, verify all settings and\ncustomizations are retained.\nInstallation is verified through the\nPhilips Remote Service portal.","Field service engineer performs\nfull upgrade activities.","Subject of this\nSubmission.\nVerification and\nValidation Testing has\nbeen conducted on the\nRSM feature to support\nthe Application\nperformance is\nequivalent to the\npredicate device."],["Application","","",""],["performance","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250221-p10-t0","doc_id":"K250221","page_num":10,"bbox":[23.09,84.54,768.91,529.8],"n_rows":5,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","StrokeSENS ASPECTS","","","Brainomix 360 e-ASPECTS (K221564)",""],["","","","","","",""],["","","Manufactured by Circle Cardiovascular Imaging Inc.","","","Manufactured by Brainomix Limited",""],["Indications for\nUse/Intended use","StrokeSENS ASPECTS is a computer-aided diagnosis (CADx) software device\nused to assist the clinician in the assessment and characterization of brain\ntissue abnormalities using CT image data.\nThe Software automatically registers images and uses an Atlas to segment and\nanalyze ASPECTS Regions. StrokeSENS ASPECTS extracts image data from\nindividual voxels in the image to provide analysis and computer analytics and\nrelates the analysis to the atlas defined ASPECTS regions. The imaging\nfeatures are then synthesized by an artificial intelligence algorithm into a single\nASPECT (Alberta Stroke Program Early CT) Score.\nStrokeSENS ASPECTS is indicated for evaluation of patients presenting for\ndiagnostic imaging workup with known MCA or ICA occlusion, for evaluation of\nextent of disease. Extent of disease refers to the number of ASPECTS regions\naffected which is reflected in the total score. StrokeSENS ASPECTS provides\ninformation that may be useful in the characterization of ischemic brain tissue\ninjury during image interpretation (within 12 hours from time last known well).\nStrokeSENS ASPECTS provides a comparative analysis to the ASPECTS\nstandard of care radiologist assessment by providing highlighted ASPECTS\nregions and an automated editable ASPECTS score for clinician review.\nStrokeSENS ASPECTS presents the original and annotated images for\nconcurrent reads. StrokeSENS ASPECTS additionally provides a visualization\nof the voxels contributing to the automated ASPECTS score.\nLimitations:\n1. StrokeSENS ASPECTS is not intended for primary interpretation of\nCT images. It is used to assist physician evaluation.\n2. StrokeSENS ASPECTS has been validated in patients with known\nMCA or ICA occlusion prior to ASPECTS scoring.\n3. Use of StrokeSENS ASPECTS in clinical settings other than brain\nischemia within 12 hours from time last known well, caused by known\nICA or MCA occlusions, has not been tested.\n4. StrokeSENS ASPECTS has only been validated and is intended to be\nused in patient populations aged over 21.","","","Brainomix 360 e-ASPECTS is a computer-aided diagnosis (CADx) software\ndevice used to assist the clinician in the assessment and characterization of\nbrain tissue abnormalities using CT image data.\nThe software automatically registers images and uses an Atlas segment to\nanalyze ASPECTS regions. Brainomix 360 e-aspects extracts image data from\nindividual voxels in the image to provide analysis and computer analytics and\nrelates the analysis to the atlas defined ASPECTS regions. The imaging\nfeatures are then synthesized by an artificial intelligence algorithm into a single\nASPECTS (Alberta Stroke Program Early CT) Score.\nBrainomix 360 e-ASPECTS is indicated for evaluation of patients presenting for\ndiagnostic imaging workup with known MCA or ICA occlusion, for evaluation of\nextent of disease. Extent of disease refers to the number of ASPECTS regions\naffected which is reflected in the total score. Brainomix 360 e-ASPECTS\nprovides information that may be useful in the characterization of ischemic\nbrain tissue injury during image interpretation (within 6 hours from time last\nknown well).\nBrainomix 360 e-ASPECTS provides a comparative analysis to the ASPECTS\nstandard of care radiologist assessment by providing highlighted ASPECTS\nregions and an automated editable ASPECTS score for clinician review.\nBrainomix 360 e-ASPECTS additionally provides a visualization of the voxels\ncontributing to the automated ASPECTS score and the voxels excluded from\nthe automated ASPECTS score.\nLimitations:\n1. Brainomix 360 e-ASPECTS is not intended for primary interpretation\nof CT images. It is used to assist physician evaluation.\n2. Brainomix 360 e-ASPECTS has ben validated in patients with known\nMCA or ICA occlusion prior to ASPECTS scoring.\n3. Brainomix 360 e-ASPECTS is not suitable for use on brain scans\ndisplaying neurological pathologies other than acute stroke, such as\ntumours or abscesses, haemorrhagic transformation and hematoma.\n4. Use of Brainomix 360 e-ASPECTS Module in clinical settings other\nthan brain ischemia within 6 hours from time last known well, caused\nby known ICA or MCA occlusions has not been tested.","",""]],"caption_candidate":"Table 1. Indications comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250221-p11-t0","doc_id":"K250221","page_num":11,"bbox":[23.09,72.36,768.91,264.72],"n_rows":5,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","StrokeSENS ASPECTS","","","Brainomix 360 e-ASPECTS (K221564)",""],["","","","","","",""],["","","Manufactured by Circle Cardiovascular Imaging Inc.","","","Manufactured by Brainomix Limited",""],["","Contraindications:\n• StrokeSENS ASPECTS is contraindicated for use on brain scans\ndisplaying neurological pathologies other than acute ischemic stroke, such\nas tumours or abscesses, haemorrhagic transformation and hematoma.\nCautions:\n• Patient motion: Excessive patient motion leading to artifacts that make the\nscan technically inadequate.","","","5. Brainomix 360 e-ASPECTS has only been validated and is intended\nto be used in patient populations aged over 21.\n6. Brainomix 360 e-ASPECTS has been validated and is intended to be\nused on Siemens Somatom Definition scanners.\n7. Brainomix 360 e-ASPECTS is not intended for mobile diagnostic use.\nImages viewed on a mobile platform are compressed preview images\nand not for diagnostic interpretation.\nContraindications/Exclusions/Cautions:\n• Patient motion: Excessive patient motion leading to artifacts that make\nthe scan technically inadequate.\n• Haemorrhagic Transformation, Hematoma.","",""]],"caption_candidate":"StrokeSENS ASPECTS 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250221-p12-t0","doc_id":"K250221","page_num":12,"bbox":[23.89,84.54,768.11,398.04],"n_rows":19,"n_cols":5,"columns":["Feature","","Subject Device","","Predicate Device\nBrainomix 360 e-ASPECTS (K221564)\nManufactured by Brainomix Limited"],"rows":[["Feature","","Subject Device","","Predicate Device\nBrainomix 360 e-ASPECTS (K221564)\nManufactured by Brainomix Limited"],["","","StrokeSENS ASPECTS","",""],["","","","",""],["","","","",""],["","","Manufactured by Circle Cardiovascular Imaging Inc.","",""],["Device Class","II","","","II"],["Product Code(s)","POK","","","POK"],["Regulation Name","Radiological computer-assisted diagnostic software for lesions\nsuspicious of cancer.","","","Radiological computer-assisted diagnostic software for lesions\nsuspicious of cancer."],["Regulation Number","21 CFR 892.2060","","","21 CFR 892.2060"],["DICOM Compliant?","Yes","","","Yes"],["Input Data Type","Non-contrast head CT scans","","","Non-contrast head CT scans"],["Clinical Application/Anatomic al\nRegion","Stroke/Head","","","Stroke/Head"],["Standard of Care\nRepresentation","ASPECT Scoring","","","ASPECT Scoring"],["Alteration of original image data\nbase","No","","","No"],["Alters Standard of Care\nWorkflow","In parallel to","","","In parallel to"],["Technical Implementation","ML/AI (Deep Learning)","","","ML/AI (Random Forest)"],["Design: Computer Platform","Standard off-the-shelf server or virtual server","","","Standard off-the-shelf server or virtual server"],["Image Overlay","ASPECTS regions, highlighted by algorithms.\nVoxel-wise analysis visualized as a heat map.","","","ASPECTS regions, highlighted by algorithms.\nVoxel-wise analysis visualized as a heat map."],["Gating Conditions","Users must confirm ICA or MCA occlusion prior to accessing ASPECTS\nresults","","","Users must confirm ICA or MCA occlusion prior to accessing ASPECTS\nresults"]],"caption_candidate":"Table 2. Regulatory and technological features comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p5-t0","doc_id":"K250226","page_num":5,"bbox":[72.31,244.32,539.75,272.04],"n_rows":2,"n_cols":8,"columns":["","Regulation Number","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","Regulation Name","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","","","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p5-t1","doc_id":"K250226","page_num":5,"bbox":[72.31,503.36,539.75,614.56],"n_rows":8,"n_cols":4,"columns":["","Device Trade Name:","","Clarius AI"],"rows":[["","Device Trade Name:","","Clarius AI"],["","510(k) Reference:","","K222406"],["","Manufacturer Name:","","Clarius Mobile Health Corp."],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Primary Product Code:","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p6-t0","doc_id":"K250226","page_num":6,"bbox":[72.17,470.84,540.05,511.99],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducers","","L7 HD3; L15 HD3; L20 HD3"],"rows":[["","Clarius Ultrasound Transducers","","L7 HD3; L15 HD3; L20 HD3"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"cleared in K213436). Clarius Median Nerve AI is not a stand-alone software device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p8-t0","doc_id":"K250226","page_num":8,"bbox":[72.32,97.81,674.39,535.89],"n_rows":11,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs from",""],["","Device Trade Name","","","Clarius Median Nerve AI","","","Clarius AI","","","predicate device)",""],["","510(k) Holder/ Manufacturer","","Clarius Mobile Health Corp.","","","Clarius Mobile Health Corp.","","","Same as predicate device.","",""],["","Submission Reference","","Current Submission","","","K222406","","","Not applicable","",""],["","Primary Product Code","","QIH","","","QIH","","","Same as predicate device.","",""],["Device Classification Name","Device Classification Name","","Automated Radiological\nImage Processing Software","","","Automated Radiological\nImage Processing Software","","","Same as predicate device.","",""],["Regulation Name","","","Medical Image Management and\nProcessing System","","","Medical Image Management and\nProcessing System","","","Same as predicate device.","",""],["","Regulation Number","","21 CFR § 892.2050","","","21 CFR § 892.2050","","","Same as predicate device.","",""],["Intended Use","Intended Use","","Intended for use as an assistive\ntool during the acquisition and\ninterpretation of ultrasound\nimages utilizing an artificial\nintelligence/machine-learning\nalgorithm for segmentation and\nmeasurement of anatomical\nstructures.","","","Non-invasive processing of\nultrasound images using\nautomatic image segmentation\nand measurement of anatomical\nstructures utilizing artificial\nintelligence/ machine learning\nalgorithms.","","","Same as predicate device.","",""],["Indications for Use","","","Clarius Median Nerve AI is\nintended for segmentation\nand semi-automatic non-\ninvasive measurements of the\nmedian nerve cross-sectional\narea on ultrasound data\nacquired by the Clarius\nUltrasound Scanner (i.e.,\nlinear array scanners). The\nuser shall be a healthcare\nprofessional trained and\nqualified in ultrasound. The\nuser retains the responsibility\nof confirming the validity of\nthe measurements based on\nstandard practices and clinical","","","Clarius AI is intended to semi-\nautomatically place calipers for\nnon-invasive measurements of\nmusculoskeletal structures (e.g.,\nAchilles’ tendon, plantar fascia,\npatellar tendon) on ultrasound\ndata acquired by the Clarius\nUltrasound Scanner (i.e., L7 and\nL15). The user shall be a\nhealthcare professional trained\nand qualified in MSK\n(musculoskeletal) ultrasound. The\nuser shall retain the ultimate\nresponsibility of ascertaining the\nmeasurements based on standard\npractices and clinical judgment.","","","Both the predicate device and\nsubject device are indicated for\nsemi-automated measurements\nof anatomical (musculoskeletal)\nstructures on ultrasound image\ndata acquired by the Clarius\nUltrasound Scanner using AI/ML-\nbased technology. Both devices\ndetect the anatomical structure,\nperform segmentation, and\nperform measurements of the\nstructure. Both the predicate and\nsubject devices are intended for\nuse as an adjunctive ‘tool’ or aid\nby the user for the segmentation\nand anatomical measurements of","",""]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p9-t0","doc_id":"K250226","page_num":9,"bbox":[72.32,72.38,674.39,533.85],"n_rows":11,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs from",""],["","Device Trade Name","","","Clarius Median Nerve AI","","","Clarius AI","","","predicate device)",""],["","","","judgment. Clarius Median\nNerve Al is indicated for use\nin adult patients only.","","","","","","ultrasound images and are not\nintended to replace clinical\ndecision-making. The minor\ndifferences in the indications for\nuse do not impact the safety and\neffectiveness of the subject\ndevice relative to the predicate\ndevice.","",""],["","Radiological application/","","Ultrasound","","","Ultrasound","","","Same as predicate device.","",""],["","Supported modality","","","","","","","","","",""],["Principle of Operation/\nTechnology","Principle of Operation/","","Ultrasound image processing\nsoftware implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms\ntrained with clinical and/or\nartificial data intended for\nsegmentation and measurements\nof ultrasound data.","","","Ultrasound image processing\nsoftware implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms\ntrained with clinical and/or\nartificial data intended for\nsegmentation and measurements\nof ultrasound data.","","","Same as predicate device.","",""],["","Technology","","","","","","","","","",""],["Quantitative and/or Qualitative\nAnalysis","","","Median nerve cross-sectional area\nmeasurement","","","Tendon thickness measurement","","","Equivalent to the predicate\ndevice. The subject device\nperforms semi-automated\nmeasurements of the median\nnerve cross-sectional area,\nwhereas the predicate device\nperforms semi-automated\nmeasurements of tendon\nthickness.","",""],["Segmentation","","","Yes – Segmentation of anatomical\nstructures (median nerve)","","","Yes – Segmentation of anatomical\nstructures (tendons)","","","Equivalent to the predicate\ndevice. The only difference is the\nanatomical structure (median\nnerve vs. tendons).","",""],["Measurement","","","Yes – Measurement of anatomical\nstructures (median nerve cross-\nsectional area)","","","Yes – Measurement of anatomical\nstructures (tendon thickness of","","","Equivalent to the predicate\ndevice. The only difference is the","",""]],"caption_candidate":"K250226","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p10-t0","doc_id":"K250226","page_num":10,"bbox":[72.32,72.38,674.39,462.68],"n_rows":16,"n_cols":12,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","","RATIONALE",""],["","","","","","","","","","","(if subject device differs from",""],["","Device Trade Name","","","Clarius Median Nerve AI","","","Clarius AI","","","predicate device)",""],["","","","","","","the Achilles’ tendon, plantar\nfascia, patellar tendon)","","","anatomical structure (median\nnerve vs. tendons).","",""],["Algorithm Methodology","","","Artificial Intelligence (AI)/Machine\nLearning (ML)\nImage segmentation for border\ndetection, and median nerve view\nclassification using a Deep Neural\nNetwork.","","","Artificial Intelligence (AI)/Machine\nLearning (ML)\nImage segmentation for border\ndetection, and tendon view\nclassification using a Deep Neural\nNetwork.","","","Same as predicate device.","",""],["","Automation","","Yes","","","Yes","","","Same as predicate device.","",""],["","(Yes or No)","","","","","","","","","",""],["","Manual adjustment/Manual","","Yes","","","Yes","","","Same as predicate device.","",""],["","editing capability","","","","","","","","","",""],["","(Yes or No)","","","","","","","","","",""],["Environment of Use","Environment of Use","","Healthcare setting (e.g., hospital,\nclinic)","","","Healthcare setting (e.g., hospital,\nclinic)","","","Same as predicate device.","",""],["Anatomical Site","","","Wrist, forearm","","","Foot, ankle, knee","","","The difference in anatomical site\ndoes not impact the safety and\neffectiveness of the subject\ndevice relative to the predicate\ndevice.","",""],["","Intended Users","","Licensed healthcare professionals","","","Licensed healthcare professionals","","","Same as predicate device.","",""],["","Patient Population","","Adults","","","Adults","","","Same as reference device.","",""],["","Operating System Compatibility","","iOS and Android","","","iOS and Android","","","Same as predicate device.","",""],["Platform","Platform","","Embedded in the Clarius\nultrasound app for use with the\nClarius Ultrasound Scanner\nsystem","","","Embedded in the Clarius\nultrasound app for use with the\nClarius Ultrasound Scanner\nsystem","","","Same as predicate device.","",""]],"caption_candidate":"K250226","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p11-t0","doc_id":"K250226","page_num":11,"bbox":[72.26,181.44,539.74,306.36],"n_rows":8,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["12-349","","","NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set"],["5-129","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"following FDA-recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p13-t0","doc_id":"K250226","page_num":13,"bbox":[72.38,318.84,325.79,570.72],"n_rows":16,"n_cols":5,"columns":["","Table 1: Geographic Data","","",""],"rows":[["","Table 1: Geographic Data","","",""],["","Location","","Number of Images",""],["United States","","130","",""],["Brazil","","13","",""],["Canada","","10","",""],["Australia","","9","",""],["Belgium","","4","",""],["unknown","","4","",""],["Germany","","3","",""],["United Kingdom","","3","",""],["South Africa","","2","",""],["Dominican Republic","","1","",""],["Philippines","","1","",""],["Poland","","1","",""],["The Netherlands","","1","",""],["Total","","182","",""]],"caption_candidate":"subjects. The geographic distribution of data collected is shown in Table 1:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p14-t0","doc_id":"K250226","page_num":14,"bbox":[72.48,308.76,539.64,385.68],"n_rows":3,"n_cols":10,"columns":["","Table 2: Non-Inferiority Test Result Summary for Clinical Performance of Clarius Median Nerve AI","","","","","","","",""],"rows":[["","Table 2: Non-Inferiority Test Result Summary for Clinical Performance of Clarius Median Nerve AI","","","","","","","",""],["","","","p-value","","","Equivalence Margin","","Mean Difference",""],["Clarius Median Nerve AI\nvs Human Experts","","6.497e-47 (97.5% CI: -inf,\n0.3285)","","","3 mm2","","-0.065 mm 2","",""]],"caption_candidate":"The non-inferiority performance testing summary is shown in Table 2:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p14-t1","doc_id":"K250226","page_num":14,"bbox":[72.48,444.96,437.6,570.84],"n_rows":8,"n_cols":2,"columns":["Table 3: Jaccard Scores of Segmentation masks",""],"rows":[["Table 3: Jaccard Scores of Segmentation masks",""],["Comparison","Jaccard Score"],["Reviewer 1 vs Clarius Median Nerve AI","0.62 [95%CI: 0.62, 0.68]"],["Reviewer 2 vs Clarius Median Nerve AI","0.71 [95%CI: 0.69, 0.74]"],["Reviewer 3 vs Clarius Median Nerve AI","0.68 [95%CI: 0.65, 0.71]"],["Reviewer 1 vs Reviewer 2","0.76 [95%CI: 0.74, 0.78]"],["Reviewer 1 vs Reviewer 3","0.72 [95%CI: 0.70, 0.75]"],["Reviewer 2 vs Reviewer 3","0.77 [95%CI: 0.75, 0.79]"]],"caption_candidate":"results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p15-t0","doc_id":"K250226","page_num":15,"bbox":[72.58,631.17,539.9,714.96],"n_rows":2,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["Modification of training\nhyperparameters (initial\nlearning rate, width\nmultiplier, dropout rate)","","Improvement and\noptimization of Clarius\nMedian Nerve AI’s\nperformance","","","Re-training of the\nMedian Nerve AI model\nwith modified\nhyperparameters to\noptimize its performance","","","Improved\nperformance\nmetrics of modified\nMedian Nerve AI\nmodel with","",""]],"caption_candidate":"Summary of planned modifications to Clarius Median Nerve AI per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p16-t0","doc_id":"K250226","page_num":16,"bbox":[72.55,72.93,539.93,708.24],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","followed by internal\ntesting and a comparison\nof the original Median\nNerve AI model to the\nmodified Median Nerve\nAI model (using\nperformance metrics)\nfollowed with clinical\nperformance testing\n(verification and\nvalidation).","","","increased accuracy\nand more robust\nmeasurements\ndisplayed to users.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of post-\nprocessing algorithms\n(adjustments to\nmeasurement validity\nthresholds)","","Improvement and\noptimization of Clarius\nMedian Nerve AI’s\nperformance and\nrobustness","","","Internal testing and a\ncomparison of the\noriginal Median Nerve AI\nmodel to the modified\nMedian Nerve AI model\n(using performance\nmetrics) and clinical\nperformance testing\n(verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nMedian Nerve AI\nmodel.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and","",""]],"caption_candidate":"K250226","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250226-p17-t0","doc_id":"K250226","page_num":17,"bbox":[72.55,72.93,539.93,708.24],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","","","","dropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of data\ninput sources (Clarius\nprobes)","","To add data from\ncurrent Clarius\nscanners and future\n510(k) cleared\nscanners to the Clarius\nMedian Nerve AI\nmodel so the model\ncan be deployed on\nmore scanners.","","","Re-training of the\nMedian Nerve AI model\nto expand its use with\nadditional data input\nsources (i.e., 510(k)-\ncleared models of the\nClarius Ultrasound\nScanner), internal\ntesting, and clinical\nperformance testing\n(verification and\nvalidation) to assesses its\nperformance with the\nnew data input sources.","","","By accommodating a\nwider array of image\ngeometries and\ncharacteristics with\nthe use of new\n510(k)-cleared\nClarius ultrasound\nscanners, the\nupdated Median\nNerve AI model will\nbe better equipped\nto handle different\ntransducer models\nof the Clarius\nUltrasound Scanner\nused in varying\nclinical scenarios.\nBenefit-Risk\nAnalysis:\nBenefits: Enhanced\ncompatibility;\nFlexibility for diverse\nclinical settings.\nRisks: Data skewing\nand concept drift.\nRisk Mitigation:\nInternal testing and\nverification datasets\nwithin the intended\npatient population\nwill ensure that data\nskewing and\nconcept drift are\nmitigated.","",""]],"caption_candidate":"K250226","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p5-t0","doc_id":"K250236","page_num":5,"bbox":[72.03,224.58,287.63,652.95],"n_rows":37,"n_cols":2,"columns":["510(K) SUBMITTER",""],"rows":[["510(K) SUBMITTER",""],["",""],["Company Name:","Hyperfine, Inc."],["",""],["Company Address:","351 New Whitfield St"],["",""],["","Guilford, CT 06437"],["",""],["CONTACT",""],["",""],["Name:","Christine Kupchick"],["",""],["Telephone:","(203) 343-3404"],["",""],["Email:","ckupchick@hyperfine.io"],["",""],["Date Prepared:","May 22, 2025"],["",""],["DEVICE IDENTIFICATION",""],["",""],["Trade Name:","Swoop® Portable MR Im"],["",""],["Common Name:","Magnetic Resonance Im"],["",""],["Regulation Number:","21 CFR 892.1000"],["",""],["Classification Name:","System, Nuclear Magne"],["",""],["Product Code:","LNH; MOS"],["",""],["Regulatory Class:","Class II"],["",""],["PREDICATE DEVICE INFORMA","TION"],["",""],["The subject Swoop Port","able MR Imaging System"],["",""],["System (K240944).",""]],"caption_candidate":"510( )S","well_formed":true,"extraction_settings":"text"}
{"table_id":"K250236-p6-t0","doc_id":"K250236","page_num":6,"bbox":[72.64,424.79,540.08,708.37],"n_rows":8,"n_cols":8,"columns":["Specification","","","Subject Swoop Portable MR Imaging","","","Predicate Swoop Portable MR Imaging",""],"rows":[["Specification","","","Subject Swoop Portable MR Imaging","","","Predicate Swoop Portable MR Imaging",""],["","","","System (V2)","","","System (V1) (K240944)",""],["","INTENDED USE","","","","","",""],["Intended Use/ Indications\nfor Use","","The Swoop Portable MR Imaging\nSystem is a portable, ultra-low field\nmagnetic resonance imaging device for\nproducing images that display the\ninternal structure of the head where\nfull diagnostic examination is not\nclinically practical. When interpreted\nby a trained physician, these images\nprovide information that can be useful\nin determining a diagnosis.","","","Same","",""],["Patient Population","","Adult and pediatric patients (≥ 0 years)","","","","Same",""],["Anatomical Sites","","Head","","","","Same",""],["Environment of Use","","At the point of care in professional\nhealth care facilities such as\nemergency rooms, intensive/critical\ncare units, hospitals, outpatient, or\nrehabilitation centers.","","","Same","",""],["Energy Used and/or\ndelivered","","Magnetic Resonance","","","Same","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p7-t0","doc_id":"K250236","page_num":7,"bbox":[72.64,72.78,540.07,622.08],"n_rows":39,"n_cols":9,"columns":["","MAGNET","","","","","","",""],"rows":[["","MAGNET","","","","","","",""],["Field strength","","","64.9 mT (nominal)","","","","63.3 ± 2.0 mT",""],["Type","","","Permanent magnet","","","","Same",""],["Patient accessible bore size","","","36.0 in. width, 13.4 in. height","","","","24.0 in. width, 12.4 in. height",""],["Magnet weight","","","712 lbs.","","","","705 lbs.",""],["","GRADIENT SYSTEM","","","","","","",""],["Maximum gradient\namplitude","","","X: 33.9 mT/m\nY: 33.2 mT/m\nZ: 66.2 mT/m","","","","X: 24.3 mT/m",""],["","","","","","","","Y: 22.9 mT/m",""],["","","","","","","","Z: 38.5 mT/m",""],["Rise time (zero to max)","","","X: 1.8 ms\nY: 1.8 ms\nZ: 5.1 ms","","","","X: 2.1 ms",""],["","","","","","","","Y: 2.0 ms",""],["","","","","","","","Z: 3.8 ms",""],["Slew rate","","","X: 18.8 T/m/s\nY: 18.4 T/m/s\nZ: 13.0 T/m/s","","","","X: 24 T/m/s",""],["","","","","","","","Y: 22 T/m/s",""],["","","","","","","","Z: 21 T/m/s",""],["","RF COIL","","","","","","",""],["Type","","","Transmit/receive","","","","Same",""],["Transmit coil design","","","Linear","","","","Same",""],["","OTHER","","","","","","",""],["Patient weight capacity","","","1.6kg-200 kg","","","Same","",""],["Operation temperature","","","15-30 C","","","Same","",""],["Warm up time","","","<3 minutes","","","Same","",""],["Temperature control","","","No","","","","Same",""],["Humidity control","","","No","","","Same","",""],["SEQUENCES & IMAGE PROCESSING","","","","","","","",""],["T1W sequences","","","• T1 (Standard), T1 (Gray/White)\n• Advanced Gridding reconstruction","","","","• Same",""],["","","","","","","","• Same",""],["T2W sequences","","","• T2, T2 (Fast)\n• Advanced Gridding reconstruction","","","","• Same",""],["","","","","","","","• Same",""],["FLAIR sequences","","","• FLAIR, FLAIR (Fast)\n• Advanced Gridding reconstruction","","","","• FLAIR only",""],["","","","","","","","• Same",""],["DWI/ADC sequences","","","• DWI/ADC, DWI/ADC (Fast)\n• Advanced Gridding + FISTA","","","","• DWI/ADC only",""],["","","","","","","","• FISTA only",""],["Image post-processing\n(All Sequences)","","","• Advanced Denoising\n• Image orientation transform\n• Geometric distortion correction\n• Receive coil intensity correction\n• Advanced Interpolation\n• DICOM output","","","","• Same",""],["","","","","","","","• Same",""],["","","","","","","","• Same",""],["","","","","","","","• Same",""],["","","","","","","","• n/a",""],["","","","","","","","• Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p8-t0","doc_id":"K250236","page_num":8,"bbox":[72.63,136.48,536.87,707.38],"n_rows":5,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Verification","","","Verification testing in accordance with the\ndesign requirements.","","","• IEC 62304:2015\n• FDA Guidance, “Content of\nPremarket Submissions for Device\nSoftware Functions”\n• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• NEMA MS 8-2016\n• American College of Radiology\n(ACR) Phantom Test Guidance for\nUse of the Large MRI Phantom for\nthe ACR MRI Accreditation Program\n• American College of Radiology\nstandards for named sequences\n• FDA Guidance, “Cybersecurity in\nMedical Devices: Quality System\nConsiderations and Content of\nPremarket Submissions”","",""],["Validation","","","Validation to ensure the subject device meets\nuser needs and performs as intended.","","","• FDA Guidance, “Content of\nPremarket Submissions for Device\nSoftware Functions”\n• FDA Guidance, “Applying Human\nFactors and Usability Engineering to\nMedical Devices\n• IEC 62366-1:2015+AMD1:2020","",""],["Biocompatibility","","","Biocompatibility evaluation of patient-\ncontacting materials.","","","• ISO 10993-1:2018\n• ISO 10993-5:2009\n• ISO 10993-10:2021\n• ISO 10993-23:2021","",""],["Reprocessing","","","Cleaning and disinfection evaluation of patient-\ncontacting materials.","","","• FDA Guidance, “Reprocessing\nMedical Devices in Health Care\nSettings: Validation Methods and\nLabeling”\n• ISO 17664:2021\n• ASTM F3208-20\n• AAMI TIR12:2020\n• ANSI/AAMI ST98:2022","",""]],"caption_candidate":"standards to support substantial equivalence to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p9-t0","doc_id":"K250236","page_num":9,"bbox":[72.64,72.71,536.87,148.71],"n_rows":2,"n_cols":9,"columns":["","Test","","","Test Description","","","Applicable Standard(s)",""],"rows":[["","Test","","","Test Description","","","Applicable Standard(s)",""],["Safety","","","Electrical Safety, EMC, and Essential\nPerformance testing.","","","• IEC 60601-1:2005 Ed.3+A1; A2\n• IEC 60601-1-2:2014 Ed.4+A1\n• IEC 60601-1-6:2010 Ed.3+A1; A2\n• IEC 60601-2-33:2015 Ed. 3.2","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p10-t0","doc_id":"K250236","page_num":10,"bbox":[72.42,95.9,476.08,355.75],"n_rows":15,"n_cols":5,"columns":["Model/Sequence group: T1, T2, FLAIR","","","",""],"rows":[["Model/Sequence group: T1, T2, FLAIR","","","",""],["Patients","","40","",""],["Images","","111","",""],["","Demographics","","",""],["Gender","","Female","38%",""],["","","Male","55%",""],["","","Unknown","7%",""],["Age","","18-35","5%",""],["","","35-60","28%",""],["","","60+","62%",""],["","","2+*","5%",""],["Ethnicity Data","","Not Recorded","",""],["Number of sites","","4","",""],["Equipment Type","","Swoop v2†","",""],["Pathology","","Atrophy, Cerebellar Infarct, Chronic Infarct, Demyelinating diseases, Embolic\nInfarct, Hydrocephalus, Infarct, Intracerebral Hemorrhage, Intraparenchymal\nHemorrhage, Lesion, M1 Occlusion, Mass Effect, Seizure, Stroke, Subdural\nHemorrhage, Traumatic Brain Injury, Tumor, White Matter Disease, White\nMatter Lesion","",""]],"caption_candidate":"Dataset and Sample Size per Model:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p10-t1","doc_id":"K250236","page_num":10,"bbox":[72.42,387.75,476.08,635.33],"n_rows":15,"n_cols":5,"columns":["Model/Sequence group: DWI","","","",""],"rows":[["Model/Sequence group: DWI","","","",""],["# of patient","","29","",""],["# Images","","94","",""],["","Demographics","","",""],["Gender\nAge","","Female","35%",""],["","","Male","55%",""],["","","Unknown","10%",""],["","","18-35","7%",""],["","","35-60","21%",""],["","","60+","65%",""],["","","2+*","7%",""],["Ethnicity Data","","Not Recorded","",""],["Number of sites","","4","",""],["Equipment Type","","Swoop v2","",""],["Pathology","","Atrophy, Cerebella Infarct, Chronic Infarct, Demyelinating Diseases, Embolic\nInfarct, Infarct, Intracerebral Hemorrhage, Intraparenchymal Hemorrhage,\nLesion, M1 Occlusion, Mass Effect, Stroke, Subdural Hemorrhage, Traumatic\nBrain Injury, Tumor, White Matter Disease","",""]],"caption_candidate":"† Contained Swoop Mk1.9 (<1%)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p11-t0","doc_id":"K250236","page_num":11,"bbox":[72.41,377.75,476.07,616.08],"n_rows":15,"n_cols":5,"columns":["Patients","","15","",""],"rows":[["Patients","","15","",""],["Images","","46","",""],["Pathologies","","58","",""],["ROIs","","464","",""],["","Demographics and other Variability","","",""],["Gender","","Female","28%",""],["","","Male","70%",""],["","","Unknown","2%",""],["Age","","35-60","28%",""],["","","60+","70%",""],["","","2+*","2%",""],["Ethnicity Data","","Not Recorded","",""],["Number of sites","","2","",""],["Equipment","","Swoop v2","",""],["Pathology","","Atrophy, Demyelinating diseases, Embolic Infarct, Infarct, Intracereberal\nHemorrhage, Intraparenchymal Hemorrhage, Lesion, Resection, Stroke,\nThrombectomy, Tumor, White Matter Disease, White Matter Hyperintensity,\nWhite Matter Lesion","",""]],"caption_candidate":"criteria are described below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250236-p12-t0","doc_id":"K250236","page_num":12,"bbox":[72.41,349.73,476.07,602.33],"n_rows":14,"n_cols":5,"columns":["Patients","","32","",""],"rows":[["Patients","","32","",""],["Images","","167","",""],["","Demographics and other Variability","","",""],["Gender","","Female","28%",""],["","","Male","70%",""],["","","Unknown","2%",""],["Age","","18-35","1%",""],["","","35-60","25%",""],["","","60+","35%",""],["","","2+*","39%",""],["Ethnicity Data","","Not Recorded","",""],["Number of sites","","3","",""],["Equipment","","Swoop v2","",""],["Pathology","","Included pathology: Atrophy, Chronic Infarct, Demyelinating diseases, Embolic\nInfarct, Hemorrhage, Hydrocephalus, Infarct, Intracereberal Hemorrhage,\nIntraparenchymal Hemorrhage, Lesion, M1 Occlusion, Mass Effect, Stroke,\nSubdural Hemorrhage, Traumatic Brain Injury, Tumor, White Matter Disease","",""]],"caption_candidate":"each sequence-available image orientation (axial, sagittal, coronal) were used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250237-p7-t0","doc_id":"K250237","page_num":7,"bbox":[65.49,179.24,726.57,532.55],"n_rows":6,"n_cols":6,"columns":["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],"rows":[["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],["","","","Visible Patient Suite","",""],["","","","(K212896)","",""],["Product Code","QIH","LLZ","","",""],["Classification","Class II","Class II","","",""],["Indications for Use","InferOperate Suite is medical imaging\nsoftware that is intended to provide trained\nmedical professionals with tools to aid them\nin reading, interpreting, reporting, and\ntreatment planning for patients, including both\npreoperative surgical planning and\nintraoperative image display. InferOperate\nSuite accepts DICOM compliant medical\nimages acquired from a variety of imaging\ndevices.\nThis product is not intended for use with or\nfor the primary diagnostic interpretation of\nMammography images.\nIt provides several categories of tools. It\nincludes basic imaging tools for general\nimages, including 2D viewing, volume\nrendering and 3D volume viewing, orthogonal\nMulti-Planar Reconstructions (MPR), surface\nrendering, measurements, surgical planning,\nreporting, storing, general image management","Visible Patient Suite is medical\nimaging software that is intended to\nprovide trained medical professionals\nwith tools to aid them in reading,\ninterpreting, reporting. and treatment\nplanning for both pediatric and adult\npatients. Visible Patient Suite accepts\nDICOM compliant medical images\nacquired from a variety of imaging\ndevices, including CT, MR.\nThis product is not intended for use\nwith or for the primary diagnostic\ninterpretation of Mammography\nimages.\nThe software provides several\ncategories of tools. It includes basic\nimaging tools for general images,\nincluding 2D viewing, volume\nrendering and 3D volume viewing.\northogonal Multi-Planar","","","Same"]],"caption_candidate":"Detailed Comparison of the Subject and Predicate Devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250237-p8-t0","doc_id":"K250237","page_num":8,"bbox":[65.48,72.36,726.58,529.66],"n_rows":8,"n_cols":6,"columns":["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],"rows":[["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],["","","","Visible Patient Suite","",""],["","","","(K212896)","",""],["","and administration tools, etc.\nIt includes a basic image processing workflow\nand a custom UI to segment anatomical\nstructures. The processing may include the\ngeneration of preliminary segmentations of\nanatomy using software that employs machine\nlearning and other computer vision\nalgorithms, as well as interactive\nsegmentation tools, etc.\nInferOperate Suite is designed for use by\ntrained professionals and is intended to assist\nthe clinician who is responsible for making all\nfinal patient management decisions.\nInferOperate Suite utilizes machine learning-\nbased algorithms for adult patients\nundergoing CT chest, abdominal, or pelvic\nscans. For image data of other anatomical\nregions or modalities, patients under 21 years\nof age, or patients with unknown age, we\nprovide non-ML software functions, such as\nSTL viewer.","Reconstructions (MPR), image fusion,\nsurface rendering. measurements,\nreporting, storing, general image\nmanagement and administration tools,\netc.\nIt includes a basic image processing\nworkflow and a custom UI to segment\nanatomical structures, which are visible\nin the image data (bones, organs,\nvascular/airway structures. etc.),\nincluding interactive segmentation\ntools, basic image filters, etc.\nIt also includes detection and labeling\ntools of organ segments (liver, lungs\nand kidneys), including path definition\nthrough vascular/airway, approximation\nof vascular/airway territories from\ntubular structures and interactive\nlabeling.\nThe software is designed to be used by\ntrained professionals (including\nphysicians, surgeons and technicians)\nand is intended to assist the clinician\nwho is solely responsible for making all\nfinal patient management decisions.","","",""],["Intended User","Trained professionals","Trained professionals","","","Same"],["Image Input","DICOM","DICOM","","","Same"],["2D viewing","Yes","Yes","","","Same"],["3D volume viewing","Yes","Yes","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250237-p9-t0","doc_id":"K250237","page_num":9,"bbox":[65.47,72.36,726.59,429.16],"n_rows":15,"n_cols":6,"columns":["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],"rows":[["Item","Subject Device:\nInferOperate Suite","","Primary Predicate:","","Comparison"],["","","","Visible Patient Suite","",""],["","","","(K212896)","",""],["Orthogonal Multi-\nPlanar\nReconstructions\n(MPR)","Yes","Yes","","","Same"],["Surface rendering","Yes","Yes","","","Same"],["Measurements","Yes","Yes","","","Same"],["Surgical planning","Yes","Yes","","","Same"],["Anatomical Region","Thorax, abdomen, pelvis, etc.","Thorax, abdomen, pelvis, etc.","","","Same"],["Preoperative viewing\nof 3D images","Yes","Yes","","","Same"],["Intraoperative\nviewing of 3D images","Yes","Yes","","","Same"],["Storing","Yes","Yes","","","Same"],["General image data\nmanagement and\nadministration tools","Yes","Yes","","","Same"],["Segmentation","Yes","Yes","","","Same"],["Product\nAvailability","Software product","Software product","","","Same"],["Modifies the Original\nDICOM data","No","No","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250237-p10-t0","doc_id":"K250237","page_num":10,"bbox":[69.24,542.62,542.82,707.1],"n_rows":6,"n_cols":9,"columns":["No.","Model","N","Dice","","","HD95","",""],"rows":[["No.","Model","N","Dice","","","HD95","",""],["","","","Mean","95%CI","Target","Mean","95%CI","Target"],["1","Bronchus","70","0.87","0.85-0.88","0.79","2.33","2.07-2.59","3.5"],["2","Pulmonary artery","70","0.87","0.86-0.88","0.76","3.35","2.79-3.90","5.55"],["","Pulmonary vein","","0.85","0.84-0.86","0.77","3.19","2.96-3.42","5.55"],["3","Pulmonary lobe","70","0.98","0.97-0.98","0.88","2.63","2.34-2.91","4.15"]],"caption_candidate":"Distance (HD95) (mm) is summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250237-p11-t0","doc_id":"K250237","page_num":11,"bbox":[69.24,72.24,542.82,581.74],"n_rows":20,"n_cols":9,"columns":["","Pulmonary segment","","0.88","0.88-0.89","0.79","3.42","3.13-3.70","4.15"],"rows":[["","Pulmonary segment","","0.88","0.88-0.89","0.79","3.42","3.13-3.70","4.15"],["4","Liver","61","0.98","0.98-0.98","0.87","2.15","2.09-2.22","4.95"],["5","Hepatic segment\n(Couinaud's method)","61","0.91","0.89-0.94","0.80","2.54","2.18-2.89","4.95"],["","Hepatic segment (Vascular\nmethod)","61","0.91","0.89-0.94","0.80","3.52","2.90-4.14","4.95"],["6","Hepatic artery","61","0.89","0.88-0.91","0.80","2.36","1.98-2.74","5.55"],["7","Hepatic vein","61","0.91","0.90-0.91","0.80","1.86","1.75-1.98","5.55"],["","Portal vein","61","0.86","0.85-0.86","0.80","2.24","1.65-2.82","5.55"],["8","Portal vein segment","61","0.85","0.83-0.86","0.75","3.46","2.74-4.18","5.55"],["9","Gallbladder","56","0.94","0.93-0.96","0.78","2.19","1.74-2.63","3.5"],["10","Common hepatic-bile duct","61","0.83","0.79-0.88","0.73","3.54","2.05-5.03","5.55"],["11","Pancreas","61","0.97","0.95-0.98","0.7","2.49","1.23-3.75","10.63"],["12","Spleen","59","0.97","0.96-0.97","0.84","2.79","1.64-3.94","4.94"],["13","Kidney","57","0.98","0.98-0.98","0.85","1.79","1.63-2.09","4.86"],["","Bladder","17","0.98","0.97-0.99","0.80","2.33","0.00-5.33","6.22"],["14","Renal vein","57","0.86","0.85-0.87","0.80","3.03","2.01-4.13","5.55"],["15","Renal artery","57","0.85","0.85-0.86","0.80","2.24","2.08-2.76","5.55"],["16","Upper urinary tract","57","0.84","0.82-0.85","0.70","2.81","2.39-3.53","5.55"],["17","Adrenal gland","57","0.85","0.82-0.87","0.70","2.69","1.98-3.70","10.63"],["18","Bone","30","0.97","0.97-0.98","0.80","0.83","0.69-0.97","5.75"],["19","Skin","30","0.97","0.97-0.98","0.90","0.40","0.32-0.48","10.00"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p7-t0","doc_id":"K250246","page_num":7,"bbox":[88.7,409.37,520.9,682.54],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],["General","","",""],["indications for use","The uMR Jupiter system is\nindicated for use as a\nmagnetic resonance\ndiagnostic device (MRDD)\nthat produces sagittal,\ntransverse, coronal, and\noblique cross sectional\nimages, and spectroscopic\nimages, and that display\ninternal anatomical structure\nand/or function of the head,\nbody and extremities.","The uMR Jupiter system is\nindicated for use as a\nmagnetic resonance\ndiagnostic device (MRDD)\nthat produces sagittal,\ntransverse, coronal, and\noblique cross sectional\nimages, and spectroscopic\nimages, and that display\ninternal anatomical structure\nand/or function of the head,\nbody and extremities.","Same"]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p8-t0","doc_id":"K250246","page_num":8,"bbox":[88.7,78.84,520.9,715.9],"n_rows":15,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],["","These images and the\nphysical parameters derived\nfrom the images when\ninterpreted by a trained\nphysician yield information\nthat may assist the diagnosis.\nContrast agents may be used\ndepending on the region of\ninterest of the scan.\nThe device is intended for\npatients > 20 kg/44 lbs.","These images and the\nphysical parameters derived\nfrom the images when\ninterpreted by a trained\nphysician yield information\nthat may assist the diagnosis.\nContrast agents may be used\ndepending on the region of\ninterest of the scan.\nThe device is intended for\npatients > 20 kg/44 lbs.",""],["Magnet system","","",""],["Field Strength","5.0 Tesla","5.0 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible bore\ndimensions","60 cm","60 cm","Same"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Magnet Homogeneity","≤ 1.3 ppm @ 50cm DSV\n≤ 0.45 ppm @ 45cm DSV\n≤ 0.19 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.015 ppm @ 20cm DSV\n≤ 0.0009 ppm @ 10cm DSV","≤ 1.3 ppm @ 50cm DSV\n≤ 0.45 ppm @ 45cm DSV\n≤ 0.19 ppm @ 40cm DSV\n≤ 0.08 ppm @ 30cm DSV\n≤ 0.015 ppm @ 20cm DSV\n≤ 0.0009 ppm @ 10cm DSV","Same"],["Gradient system","","",""],["Max gradient\namplitude","120 mT/m","120 mT/m","Same"],["Max slew rate","200 T/m/s","200 T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant frequencies","210.794 MHz","210.794 MHz","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p9-t0","doc_id":"K250246","page_num":9,"bbox":[88.7,78.84,520.9,673.42],"n_rows":22,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Predicate Device\nuMR Jupiter (K233673)","Remark"],["Number of transmit\nchannels","8","8","Same"],["Amplifier peak power\nper channel","8 kW","8 kW","Same"],["Number of receive\nchannels","96","96","Same"],["RF Coils","","",""],["Volume Transmit Coil","Yes","Yes","Same"],["SuperFlex Small-24","Yes","Yes","Same"],["Tx/Rx Head Coil -48","Yes","Yes","Same"],["Tx/Rx Knee Coil - 24","Yes","Yes","Same"],["SuperFlex Body - 24","Yes","Yes","Same"],["Head & Neck Coil - 48","Yes","Yes","Same"],["Spine Coil - 48","Yes","Yes","Same"],["SuperFlex Large - 24","Yes","No","Note 1"],["Patient table","","",""],["Dimensions","640 mm×1025 mm×2620\nmm","640 mm×1025 mm×2620\nmm","Same"],["Maximum supported\npatient weight","310 kg","310 kg","Same"],["Accessories","","",""],["Vital Signal Gating","Support\nECG/Respiratory/Pulse\nsignal triggering the scan","Support\nECG/Respiratory/Pulse\nsignal triggering the scan","Same"],["Function","","",""],["t-ACS","Yes","No","Note 2"],["EasyFACT","Yes","No","Note 3"],["tFAST","Yes","No","Note 4"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p10-t0","doc_id":"K250246","page_num":10,"bbox":[88.7,78.84,520.9,364.61],"n_rows":4,"n_cols":2,"columns":["Note 1","The intended use of SuperFlex Large-24 is similar to previously cleared SuperFlex Small-\n24. There are two differences between them. One is that the size of SuperFlex Large-24\nis bigger than SuperFlex Small-24. Another is the applied body parts."],"rows":[["Note 1","The intended use of SuperFlex Large-24 is similar to previously cleared SuperFlex Small-\n24. There are two differences between them. One is that the size of SuperFlex Large-24\nis bigger than SuperFlex Small-24. Another is the applied body parts."],["Note 2","t-ACS (temporal AI-assisted Compressed Sensing) is a dynamic magnetic resonance\nimaging technique which combines traditional Compressed Sensing algorithm with deep\nlearning priors. It outputs multi-phase images.\nThe difference did not raise new safety and effectiveness concerns."],["Note 3","Easy FACT is a function which based on the FACT sequence, automatically places the\nROI (Regions of Interest) of 5 suitable locations on the liver and performs numerical\nstatistics of quantitative values (FF and R2*), including mean, maximum, minimum and\nother information, and outputs online reporting.\nThe difference did not raise new safety and effectiveness concerns."],["Note 4","tFAST further accelerates acquisition in time dimension on the basis of FAST\n(Framework for Acceleration STrategy) parallel acceleration technology to improve\nscanning speed. Suitable for dynamic imaging:\nIt can be used for real-time cardiac imaging and perfusion imaging.\nThe difference did not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p10-t1","doc_id":"K250246","page_num":10,"bbox":[88.7,392.69,520.9,559.75],"n_rows":8,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Reference Device#1\nuPMR 790 (K234154)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Reference Device#1\nuPMR 790 (K234154)","Remark"],["RF Coils","","",""],["Foot & Ankle Coil - 24","Yes","Yes","Same"],["Function","","",""],["EasyScan","Yes","Yes","Same"],["EasyCrop","Yes","Yes","Same"],["DeepRecon","Yes","Yes","Same"],["WFI","Yes","Yes","Same"]],"caption_candidate":"Table 2 Comparison to reference device#1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p10-t2","doc_id":"K250246","page_num":10,"bbox":[88.7,587.83,520.9,661.78],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR Jupiter","Reference Device#2\nuMR Omega (K240540)","Remark"],"rows":[["ITEM","Proposed Device\nuMR Jupiter","Reference Device#2\nuMR Omega (K240540)","Remark"],["Function","","",""],["QScan","Yes","Yes","Same"]],"caption_candidate":"Table 3 Comparison to reference device#2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p13-t0","doc_id":"K250246","page_num":13,"bbox":[104.97,527.47,500.55,669.46],"n_rows":7,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male\nFemale","12\n47"],["Age",""],["18-29\n30-44\n45-64","10\n29\n20"],["Ethnicity",""],["Asian","59"],["Body Mass Index (BMI)",""]],"caption_candidate":"covers UIH MRI systems with various magnetic field strengths (1.5T, 3T, and 5T).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p14-t0","doc_id":"K250246","page_num":14,"bbox":[104.96,264.53,500.67,480.55],"n_rows":8,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male\nFemale","17\n11"],["Age",""],["18-29\n30-44\n45-64","15\n9\n4"],["Ethnicity",""],["White\nAsian","2\n26"],["Body Mass Index (BMI)",""],["<18.5\n18.5-24.9\n25.0-29.9\n≥30.0","1\n21\n4\n2"]],"caption_candidate":"datasets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p16-t0","doc_id":"K250246","page_num":16,"bbox":[107.1,189.98,502.61,419.09],"n_rows":10,"n_cols":6,"columns":["","Gender","","","Number",""],"rows":[["","Gender","","","Number",""],["Male\nFemale","","","21\n14","",""],["","Age","","","",""],["18-28\n29-40\n>41","","","10\n15\n10","",""],["","Body Mass Index (BMI)","","","",""],["<24.9\n>24.9","","","23\n12","",""],["","Ethnicity","","","",""],["White","","","14","",""],["Black","","","4","",""],["Asian","","","17","",""]],"caption_candidate":"age groups and BMI groups as shown in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p16-t1","doc_id":"K250246","page_num":16,"bbox":[107.1,435.41,502.61,693.94],"n_rows":9,"n_cols":3,"columns":["Body part /\nPhantom","Dynamic MRI scan applications","Number of\ncases"],"rows":[["Body part /\nPhantom","Dynamic MRI scan applications","Number of\ncases"],["HEAD","Type I: Non-periodic physiological\nmovement","168"],["SPINE","Type I: Non-periodic physiological\nmovement","94"],["HIP","Type I: Non-periodic physiological\nmovement","64"],["KNEE","Type I: Non-periodic physiological\nmovement","94"],["ABDOMEN","Type II: Contrast enhancement","108"],["","Type I: Non-periodic physiological\nmovement","30"],["PELVIS","Type II: Contrast enhancement","28"],["","Type I: Non-periodic physiological\nmovement","98"]],"caption_candidate":"Asian 17","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p17-t0","doc_id":"K250246","page_num":17,"bbox":[109.1,78.84,500.61,143.3],"n_rows":2,"n_cols":3,"columns":["ANKLE","Type I: Non-periodic physiological\nmovement","100"],"rows":[["ANKLE","Type I: Non-periodic physiological\nmovement","100"],["PHANTOM","Type I: Non-periodic physiological\nmovement","36"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p17-t1","doc_id":"K250246","page_num":17,"bbox":[104.38,588.31,505.34,702.46],"n_rows":8,"n_cols":6,"columns":["","Gender","","","Number",""],"rows":[["","Gender","","","Number",""],["","Male","","","10",""],["","Female","","","10",""],["","Age","","","",""],["","18-28","","","5",""],["","29-50","","","9",""],["",">50","","","6",""],["","Ethnicity","","","",""]],"caption_candidate":"BMI groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p18-t0","doc_id":"K250246","page_num":18,"bbox":[104.38,79.08,505.34,164.54],"n_rows":6,"n_cols":5,"columns":["","White","","5",""],"rows":[["","White","","5",""],["","Asian","","15",""],["","Body Mass Index (BMI)","","",""],["","< 18.5","","2",""],["","18.5-24.9","","13",""],["","> 24.9","","5",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p18-t1","doc_id":"K250246","page_num":18,"bbox":[108.71,655.18,501.01,714.64],"n_rows":3,"n_cols":5,"columns":["","Age","","Number",""],"rows":[["","Age","","Number",""],["22- 40\n40- 60","","","1\n4",""],["","Gender","","",""]],"caption_candidate":"The subgroup information of EasyFACT images in testing data is summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p19-t0","doc_id":"K250246","page_num":19,"bbox":[107.98,78.84,501.73,168.62],"n_rows":5,"n_cols":6,"columns":["Female\nMale","","","2\n3","",""],"rows":[["Female\nMale","","","2\n3","",""],["","Magnetic field strength (T)","","","",""],["5.0T","","","5","",""],["","Ethnicity","","","",""],["Asia","","","5","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p19-t1","doc_id":"K250246","page_num":19,"bbox":[107.98,500.53,501.73,646.9],"n_rows":8,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male\nFemale","7\n1"],["Age",""],["18-40\n> 41","3\n5"],["Magnetic field strength (T)",""],["5","8"],["Ethnicity",""],["Asia","8"]],"caption_candidate":"demographic distributions covering various genders, age groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250246-p20-t0","doc_id":"K250246","page_num":20,"bbox":[108.0,475.83,501.72,636.82],"n_rows":9,"n_cols":2,"columns":["Gender","Number"],"rows":[["Gender","Number"],["Male\nFemale","7\n3"],["Age",""],["<60\n≥60","6\n4"],["Magnetic field strength (T)",""],["3.0T","5"],["5.0T","5"],["Ethnicity",""],["Asia","10"]],"caption_candidate":"various genders, age groups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p5-t0","doc_id":"K250248","page_num":5,"bbox":[72.0,474.78,540.0,526.68],"n_rows":4,"n_cols":2,"columns":["","In addition, the SW architecture was changed to separate the image communication"],"rows":[["","In addition, the SW architecture was changed to separate the image communication"],["platform from the Briefcase-Triage SW. The subject device consists of only the algorithm analysis",""],["module which can be integrated with image communication platforms that meet the Briefcase-Triage",""],["input and output requirements.",""]],"caption_candidate":"Triage for iPE (K213886) are identical in most aspects and differ mostly with respect to their algorithm","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p6-t0","doc_id":"K250248","page_num":6,"bbox":[45.33,148.2,566.62,718.2],"n_rows":5,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","Aidoc Briefcase-Triage for iPE","","","Aidoc Briefcase-Triage for iPE (K213886)",""],["Intended Use\n/ Indications\nfor Use","BriefCase-Triage is a radiological computer\naided triage and notification software\nindicated for use in the analysis of contrast-\nenhanced images that include the lungs in\nadults or transitional adolescents age 18\nand older. The device is intended to assist\nhospital networks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspect\ncases of incidental Pulmonary Embolism\n(iPE) pathologies.\nBriefCase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected findings\nin parallel to the ongoing standard of care\nimage interpretation. The user is presented\nwith notifications for suspect cases.\nNotifications include compressed preview\nimages that are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original medical\nimage and is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase-Triage are\nintended to be used in conjunction with\nother patient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","","","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of contrast-enhanced chest\nCTs (not dedicated CTPA protocol) in adults or\ntransitional adolescents age 18 and older. The\ndevice is intended to assist hospital networks\nand appropriately trained medical specialists in\nworkflow triage by flagging and communication\nof suspect cases of incidental Pulmonary\nEmbolism (iPE) pathologies. The device is\nintended to be used on single-energy exams\nonly.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag suspect\ncases on a standalone desktop application in\nparallel to the ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for suspect cases. Notifications\ninclude compressed preview images that are\nmeant for informational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on their professional\njudgment, to assist with triage/prioritization of\nmedical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care.","",""],["User\npopulation","Hospital networks and appropriately trained\nmedical specialists","","","Hospital networks and appropriately trained\nmedical specialists","",""],["Anatomical\nregion of\ninterest","Lungs","","","Chest","",""]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p7-t0","doc_id":"K250248","page_num":7,"bbox":[45.32,72.36,566.63,714.3],"n_rows":11,"n_cols":7,"columns":["","","Subject Device","","","Predicate Device",""],"rows":[["","","Subject Device","","","Predicate Device",""],["","","Aidoc Briefcase-Triage for iPE","","","Aidoc Briefcase-Triage for iPE (K213886)",""],["Data\nacquisition\nprotocol","Contrast-enhanced images that include the\nlungs","Contrast-enhanced images that include the","","Contrast enhanced chest CTs (not dedicated\nCTPA protocol)","Contrast enhanced chest CTs (not dedicated",""],["","","lungs","","","CTPA protocol)",""],["Notification-\nonly\n(/notification\nalerts),\nparallel\nworkflow tool","Yes","","","Yes","",""],["Images\nformat","DICOM","","","DICOM","",""],["Interference\nwith standard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","","","No. No cases are removed from\ndesktop app or deprioritized","",""],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion Criteria\n● Contrast-enhanced images that\ninclude the lungs\n● Single and dual energy exams\n● Scans performed on adults/\ntransitional adolescents ≥ 18 years\nof age.\n● Slice thickness; 0.5 - 5.0 mm axial.\nExclusion Criteria\n● All studies that have an inadequate\nfield of view.","","","Inclusion Criteria:\n● Contrast-enhanced chest CTs\n(not dedicated CTPA protocol\n● Single energy exams\n● Scans performed with a 64-\nslice or greater number of\ndetectors\n● Scans performed on\nadults/transitional adults ≥ 18\nyears of age\n● Slice thickness; 0.5 - 3.0 mm\naxial\nExclusion Criteria\n● All studies that are technically\ninadequate, including studies\nwith motion artifacts, severe\nmetal artifacts, or inadequate\nfield of view","",""],["Additional\nOperating\nPoints","4 Additional Operating Points","","","N/A","",""],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","","","Artificial intelligence algorithm with database of\nimages.","",""],["Structure","- Integrated with image routing module via\nimage communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and non-\ndiagnostic Image Viewer).","","","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for workflow\nintegration (Feed/Worklist (alternate\nnames) and non-diagnostic Image\nViewer).","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p7-t1","doc_id":"K250248","page_num":7,"bbox":[51.06,314.04,109.98,366.0],"n_rows":4,"n_cols":2,"columns":["","for"],"rows":[["","for"],["clinical",""],["performance",""],["testing",""]],"caption_candidate":"Exclusion ● Contrast-enhanced images that ● Contrast-enhanced chest CTs","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p8-t0","doc_id":"K250248","page_num":8,"bbox":[72.74,602.78,504.4,711.1],"n_rows":12,"n_cols":6,"columns":["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],"rows":[["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],["","","","","",""],["","Estimate","","CL","CL",""],["","","","","",""],["","(seconds)","","","",""],["Predicate K213886 Processing","282","63","264","306","300"],["Time","","","","",""],["Briefcase-Triage + Image","40.2","243","36.9","43.5","37.5"],["","","","","",""],["Communication Platform Time-","","","","",""],["","","","","",""],["To-Notification","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for Briefcase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p9-t0","doc_id":"K250248","page_num":9,"bbox":[130.6,251.91,481.36,292.5],"n_rows":3,"n_cols":20,"columns":["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","N",""],"rows":[["","","","","Mean","","","Std","","","Min","","","Median","","","Max","","N",""],["","Age","","61.7","","","17.2","","","18","","","63","","","90","","","498",""],["","(Years)","","","","","","","","","","","","","","","","","498",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p9-t1","doc_id":"K250248","page_num":9,"bbox":[172.2,343.84,437.58,427.1],"n_rows":6,"n_cols":15,"columns":["","Ground\nTruth\nResults","Gender","","","","","","","","","","","",""],"rows":[["","Ground\nTruth\nResults","Gender","","","","","","","","","","","",""],["","","Female","","","","Male","","","","","All","","",""],["","","N","","%","","N","","","%","","N","","","%"],["","Positive","113","","23","126","","","25.7","","","239","","48.7",""],["","Negative","140","","28.5","112","","","22.8","","","252","","51.3",""],["","All","253","","51.5","238","","","48.5","","","491","","100",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250248-p9-t2","doc_id":"K250248","page_num":9,"bbox":[188.67,497.85,423.26,622.92],"n_rows":6,"n_cols":8,"columns":["","Manufacturer","","","N","","%",""],"rows":[["","Manufacturer","","","N","","%",""],["GE MEDICAL SYSTEMS","","","139","","27.9%","",""],["Philips","","","97","","19.5%","",""],["SIEMENS","","","164","","32.9%","",""],["TOSHIBA","","","98","","19.7%","",""],["","Total","","","498","","100%",""]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p5-t0","doc_id":"K250290","page_num":5,"bbox":[72.25,637.23,522.25,671.5],"n_rows":2,"n_cols":3,"columns":["510(k)","Product Name","Clearance Date"],"rows":[["510(k)","Product Name","Clearance Date"],["K240926","PeekMed web","December 2024"]],"caption_candidate":"3.1. Peekmed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p8-t0","doc_id":"K250290","page_num":8,"bbox":[35.37,158.9,805.5,495.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["Product Code","LLZ, QIH","LLZ, QIH","Yes","–"],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050","Yes","–"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","–"],["Intended Use","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.","SurgiTwin is a web-based platform\ndesigned to help healthcare\nprofessionals carry out pre-operative\nplanning for knee reconstruction\nprocedures, based on their patients'\nimported imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the\nsystem in the revision and approval of\nthe output of the planning.\nThe system works with a database of\ndigital representations related to surgical\nmaterials supplied by their\nmanufacturers. SurgiTwin generates a\nPDF report as an output. End users of\nthe generated SurgiTwin reports are\ntrained healthcare professionals.\nSurgiTwin does not provide a diagnosis\nor surgical recommendation.","Yes\nSee\njustification","The last three sentences have been\nadded for clarification but do not alter the\nintended use compared to the predicate."]],"caption_candidate":"Table 1: Summary of predicate and subject device characteristics and rationale for substantial equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p9-t0","doc_id":"K250290","page_num":9,"bbox":[35.42,115.37,805.5,355.5],"n_rows":2,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["Indications for Use","This medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of\nplanning the 2D or 3D environment. The\nsystem is designed for the medical\nspecialties within surgery and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","This medical device consists of a\ndecision support tool for qualified\nhealthcare professionals to quickly and\nefficiently perform the pre-operative\nplanning for total knee arthroplasty\nprocedures, using medical imaging with\nthe additional capability of planning the\n2D or 3D environment. The system is\ndesigned for medical specialties within\nsurgery and no specific use environment\nis mandatory. The typical use\nenvironment is a room with a computer.\nThe intended patient group is patients\nover 22 years old identified to require\nknee reconstruction surgery without any\nexisting material in the operated lower\nlimb.","Yes\nSee\njustification","SurgiTwin allows the surgeon to perform\nthe pre-surgical planning efficiently in the\nknee, while the predicate allows planning\nin the hip, knee, upper limb, and foot. The\nanatomical region and surgical procedure\ncovered in SurgiTwin are included in its\npredicate. Comparison of the indications\nfor use therefore supports substantial\nequivalence."]],"caption_candidate":"SurgiTwin","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p10-t0","doc_id":"K250290","page_num":10,"bbox":[35.42,115.37,805.5,504.5],"n_rows":4,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["Contraindications","No contraindications specific to this device.","SurgiTwin is contraindicated as follows:\n- Patients under 22 years of age\n- Presence of orthopedic\nhardware in the joint to be\noperated\n- Pathological anomaly in the limb\nto be operated including fracture,\ntumor, or significant bone loss\n- Patients with severe limb\ndeformities\n- Contraindications for each\nimplant as given by the implant\nmanufacturer","Yes\nSee\njustification","Contraindications are added as a\nprecautionary measure to enhance user\nawareness and ensure safe and\nappropriate use of the device within its\nintended population. They do not indicate\na fundamental difference in SurgiTwin’s\ntechnological characteristics, intended\nuse, or performance compared to the\npredicate."],["Clinical Purpose","PeekMed web allows the surgeon to\nefficiently perform orthopedic pre-surgical\nplanning in the musculoskeletal system","SurgiTwin allows the surgeon to\nefficiently perform orthopedic\npre-surgical planning in the knee","Yes\nSee\njustification","SurgiTwin allows the surgeon to perform\nthe pre-surgical planning efficiently in the\nknee, while PeekMed® web allows\nplanning in the hip, knee, upper limb, and\nfoot. The anatomical region and surgical\nprocedure covered in SurgiTwin are\nincluded in its predicate. Comparison of\nthe general purpose therefore supports\nsubstantial equivalence."],["Anatomical Regions","PeekMed web allows the surgeon to\nperform the pre-surgical planning in the\nfollowing anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","SurgiTwin allows the surgeon to\nefficiently perform orthopedic\npre-surgical planning in the knee","Yes\nSee\njustification","See justification above."]],"caption_candidate":"SurgiTwin","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p11-t0","doc_id":"K250290","page_num":11,"bbox":[35.42,115.37,805.5,495.5],"n_rows":11,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["Patient Population","Adults","Adults","Yes",""],["End Users","Healthcare Professionals","Healthcare Professionals","Yes","–"],["Device Availability","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Yes","–"],["Software Architecture","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each\nother.","Yes","–"],["Workflow","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export\nthe case.","Yes","–"],["Internet Connection","Required","Required","Yes",""],["Image Source","Receives medical images from various\nsources","Receives medical images from various\nsources","Yes","–"],["Data Processing","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","The software processes data to provide\nan overlap and dimensioning of digital\nrepresentations of the prosthetic material","Yes","–"],["Digital overlap of\ntemplates","Allows the overlap of models and the\nintersection of the models","Allows the overlap of models and the\nintersection of the models","Yes","–"],["Interactive model\npositioning","Yes","Yes","Yes","–"]],"caption_candidate":"SurgiTwin","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p12-t0","doc_id":"K250290","page_num":12,"bbox":[35.42,115.37,805.5,504.5],"n_rows":12,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["Interactive model\ndimensioning","Yes","Yes","Yes","–"],["Model Rotation","Yes","Yes","Yes","–"],["Support for digital\nprosthetic materials\nprovided by the\nmanufacturers","Yes","Yes","Yes","–"],["Contact with the patient","No","No","Yes","–"],["Control of life supporting\ndevices","No","No","Yes","–"],["Human intervention for\nimage interpretation","Yes","Yes","Yes","–"],["Tools for surgical\nsimulation and planning","Yes","Yes","Yes","–"],["Preoperative annotation\nand analysis","Yes","Yes","Yes","–"],["Provides values\nfor measurement","Yes, including distance and angle\nmeasurement","Yes, including distance and angle\nmeasurement","Yes","–"],["Automatic bone\nsegmentation","Yes","Yes","Yes","–"],["Machine learning\nmodels for image\nsegmentation","Yes","Yes","Yes","–"]],"caption_candidate":"SurgiTwin","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p13-t0","doc_id":"K250290","page_num":13,"bbox":[35.42,115.37,805.5,286.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","Peekmed web\nK240926","SurgiTwin\nSubject Device\nK250290","Substantially\nEquivalent?","Justification and rationale"],["MPR View","Yes","Yes","Yes","–"],["Automatic placement of\nanatomical landmarks","Yes","Yes","Yes","–"],["Approval of anatomical\nlandmarks by user","Yes","Yes","","-"],["Modification of\nanatomical landmarks","Yes","No","Yes\nSee\njustification","See discussion of technological\ndifferences below."]],"caption_candidate":"SurgiTwin","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250290-p15-t0","doc_id":"K250290","page_num":15,"bbox":[95.38,495.22,522.63,581.5],"n_rows":5,"n_cols":2,"columns":["Metric","Acceptance Criteria"],"rows":[["Metric","Acceptance Criteria"],["Mean DSC","> 0.95"],["Mean voxel based AHD","< 1.0mm"],["5th percentile of the DSC","> 0.9"],["95th percentile of the boundary based HD 95","< 2.5mm"]],"caption_candidate":"table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250328-p5-t0","doc_id":"K250328","page_num":5,"bbox":[72.0,160.19,328.78,627.31],"n_rows":35,"n_cols":3,"columns":["1.","SUBMITTER’S NAME",""],"rows":[["1.","SUBMITTER’S NAME",""],["","Fumiaki Teshima",""],["","Sr. Manager, Quality Assurance Dept.",""],["","Quality, Safety and Regulation Center",""],["","Canon Medical Systems Corporation",""],["","1385 Shimoishigami",""],["","Otawara-shi, Tochigi-ken, Japan 324-8550",""],["","",""],["2.","ESTABLISHMENT REGISTRATION",""],["","9614698",""],["","",""],["3.","OFFICIAL CORRESPONDENT/CONTACT PERS","ON"],["","Yoshiaki Cook",""],["","Sr. Manager, Regulatory Affairs",""],["","Canon Medical Systems USA, Inc.",""],["","2441 Michelle Drive",""],["","Tustin, CA 92780",""],["","ycook@us.medical.canon",""],["","+1 (657) 270-5595",""],["","",""],["4.","DATE PREPARED",""],["","February 05, 2025",""],["","",""],["5.","DEVICE NAME/TRADE NAME",""],["","UltraExtend NX CUW-U001S V2.0 Ultrasound","Image"],["","",""],["6.","COMMON NAME",""],["","Radiological Image Processing System",""],["","",""],["7.","DEVICE CLASSIFICATION",""],["","Class II",""],["","Medical Image Management and Processing","System"],["","Subsequent Product Codes:",""],["","Ultrasonic Pulsed Doppler Imaging System –","Product"],["","Ultrasonic Pulsed Echo Imaging System – Pro","duct Co"]],"caption_candidate":"1. SUB","well_formed":true,"extraction_settings":"text"}
{"table_id":"K250328-p6-t0","doc_id":"K250328","page_num":6,"bbox":[96.0,112.5,586.5,288.6],"n_rows":3,"n_cols":5,"columns":["Product","Marketed by","Regulation Number\n& Classification\nProduct Code","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","Regulation Number\n& Classification\nProduct Code","510(k) Number","Clearance Date"],["UltraExtend FX, Ultrasound\nWorkstation Package, V2.02\n(Primary predicate device)","Canon Medical\nSystems USA,\nInc.","892.2050\nLLZ","K121076","10/09/2012"],["Aplio i900/i800/i700\nDiagnostic Ultrasound\nSystem, Software Version\n7.0\n(Reference device)","Canon Medical\nSystems USA,\nInc.","892.1550\nIYN","K223017","03/31/2023"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250330-p6-t0","doc_id":"K250330","page_num":6,"bbox":[54.26,550.99,541.16,769.18],"n_rows":8,"n_cols":9,"columns":["","Subject Device","Primary predicate device","","Secondary predicate","","","Comparison",""],"rows":[["","Subject Device","Primary predicate device","","Secondary predicate","","","Comparison",""],["","","","","device","","","",""],["Device Name","3mensio Workstation","3mensio Workstation","TOMTEC","","","/","",""],["510(k) Number","K250330","K153736","K213544","","","/","",""],["Product Code","QIH, LLZ","LLZ","LLZ, QIH","","","Similar, the subject device\nimplements AI/ML\nalgorithms","",""],["Classification","Medical image\nmanagement and\nprocessing system","Medical image\nmanagement and\nprocessing system","Medical image\nmanagement and\nprocessing system","","","Same","",""],["Regulation Number","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","","","Same","",""],["Intended Use","Standalone diagnostic\nbioimaging software is\nintended to measure and\nvisualize cardiovascular\nstructures.","3mensio Workstation is a\nsoftware solution that is\nintended to provide\nCardiologists, Radiologists\nand Clinical Specialists\nadditional information to\naid them in reading and\ninterpreting DICOM\ncompliant medical images\nof structures of the heart\nand vessels.","TOMTEC-ARENA software\nis a clinical software\npackage designed for\nreview, quantification and\nreporting of structures and\nfunction based\non multi-dimensional\ndigital medical data\nacquired with different\nmodalities. TOMTEC-\nARENA is not intended to","","","Same, both the subject\ndevice and primary\npredicate device generally\nshare the intended use to\nenable visualization and\nmeasurement of\ncardiovascular structures.","",""]],"caption_candidate":"below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250330-p7-t0","doc_id":"K250330","page_num":7,"bbox":[54.24,72.24,541.18,762.94],"n_rows":3,"n_cols":5,"columns":["","","3mensio Structural Heart\nenables the user to:\n• Visualize and measure\n(diameters, lengths,\nareas, volumes, angles)\nstructures of the heart\nand vessels\n• Quantify calcium\n(volume, density)\n3mensio Vascular enables\nthe user to:\n• Visualize and assess\nstenosis, aneurysms and\nvascular structures\n• Measure the dimensions\nof vessels (diameters,\nlengths, areas, volumes,\nangles)","be used for reading of\nmammography images.",""],"rows":[["","","3mensio Structural Heart\nenables the user to:\n• Visualize and measure\n(diameters, lengths,\nareas, volumes, angles)\nstructures of the heart\nand vessels\n• Quantify calcium\n(volume, density)\n3mensio Vascular enables\nthe user to:\n• Visualize and assess\nstenosis, aneurysms and\nvascular structures\n• Measure the dimensions\nof vessels (diameters,\nlengths, areas, volumes,\nangles)","be used for reading of\nmammography images.",""],["Indications for Use","Standalone software for\nmedical image analysis\nintended for advanced\nvisualization and\nquantitative analysis for\ndiagnostics in the field of\ncardiology or radiology by\nmeans of enabling\nvisualization and\nmeasurement of the heart\nand vessels for:\n• Pre-operational planning\nand sizing for\ncardiovascular\ninterventions and\nsurgery\n• Postoperative evaluation\n• Support of clinical\ndiagnosis by quantifying\ndimensions of coronary\narteries\n• Support of clinical\ndiagnosis by quantifying\ncalcifications (calcium\nscoring)\nTo facilitate the above, the\n3mensio Workstation\nprovides general\nfunctionality such as:\n• Segmentation of\ncardiovascular structures\n• Automatic and manual\ncenterline detection\n• Visualization and image\nreconstruction\ntechniques: 2D review,\nVolume Rendering, MPR,\nCurved MPR, Stretched\nCMPR, Slabbing, MIP,\nAIP, MinIP\n• Measurement and\nannotation tools\n• Reporting tools","3mensio Workstation\nenables visualization and\nmeasurement of\nstructures of the heart and\nvessels for:\n• Pre-operational planning\nand sizing for\ncardiovascular\ninterventions and\nsurgery\n• Postoperative evaluation\n• Support of clinical\ndiagnosis by quantifying\ndimensions in coronary\narteries\nTo facilitate the above, the\n3mensio Workstation\nprovides general\nfunctionality such as:\n• Segmentation of\ncardiovascular structures\n• Automatic and manual\ncenterline detection\n• Visualization and image\nreconstruction\ntechniques: 2D review,\nVolume Rendering, MPR,\nCurved MPR, Stretched\nCMPR, Slabbing, MIP,\nAIP, MinI\n• Measurement and\nannotation too\n• Reporting tools","Indications for use of\nTomTec-Arena TTA2\nsoftware are quantification\nand reporting of\ncardiovascular, fetal,\nabdominal structures and\nfunction of patients with\nsuspected disease to\nsupport the physician in\nthe diagnosis.","Same for the subject device\nand primary predicate\ndevice. Additionally, the\nsubject device includes\nfunctionality for calcium\nquantification in in other\ncardiovascular structures\nthen only coronary arteries.\nFor the secondary predicate\ndevice, only quantification\nand reporting of\ncardiovascular structures is\napplicable for this\ncomparison. Other\nanatomical structures are\nnot relevant for the\ncomparison."],["Anatomical Site","Segmentation,\nquantification, review, and\nreporting of cardiovascular\nstructures","Segmentation,\nquantification, review, and\nreporting of cardiovascular\nstructures","Segmentation,\nquantification, review, and\nreporting of\ncardiovascular, fetal and\nabdominal structures.","Same for the subject device\nand primary predicate\ndevice. For the secondary\npredicate device, only\nquantification and reporting"]],"caption_candidate":"510(k) Summary – K250330 3mensio Workstation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250330-p8-t0","doc_id":"K250330","page_num":8,"bbox":[54.24,72.24,541.18,751.06],"n_rows":8,"n_cols":5,"columns":["","","","","of cardiovascular structures\nis applicable for this\ncomparison. Other\nanatomical structures are\nnot relevant for the\ncomparison."],"rows":[["","","","","of cardiovascular structures\nis applicable for this\ncomparison. Other\nanatomical structures are\nnot relevant for the\ncomparison."],["Design","Software as a medical\ndevice: standalone and\nweb-based (on-premise\nand in the cloud)","Software as a medical\ndevice (standalone)","Software as a medical\ndevice (standalone)","The subject device can be\ndeployed either standalone\nor web-based (on-premise\nand in the cloud) but this\ndifference does not impact\nthe intended use,\nindications for use, safety\nand performance of the\ndevice. Any risks related to\nweb-based availability (both\non-premise and in the\ncloud) are mitigated by\ncybersecurity measures."],["Data Import and Type","• Vendor independent\n• CT data in DICOM format\n• X-Ray data in DICOM\nformat\n• Ultrasound data (2D and\n3D) in DICOM format","• Vendor independent\n• CT data in DICOM format\n• X-Ray data in DICOM\nformat\n• Ultrasound data (2D) in\nDICOM format","• Vendor independent\n• Ultrasound data (2D and\n3D) in DICOM format","Same, the subject device\nincludes data types of both\npredicate device combined."],["Data Management","• Study list overview\n• Deleting\n• Exporting\n• Anonymizing\n• Search","• Study list overview\n• Deleting\n• Exporting\n• Anonymizing\n• Search","Note: features not\nmentioned since they are\nnot relevant for this\ncomparison.","Same, the subject device\nand primary predicate\ndevice use the same types\nof data management\nfunctionality."],["Image Processing and\nContour Definition","• Realign orthogonal\nMPR’s\n• Segmentation toolset:\n- Automatic\nsegmentation (both AI\nand non-AI)\n- Manual segmentation\n- Automatic centerline\n- Manual centerline\n- Growing centerline\n- Centerline editing\n• Volume sculpting","• Realign orthogonal\nMPR’s\n• Segmentation toolset:\n- Automatic\nsegmentation (non-AI)\n- Manual segmentation\n- Automatic centerline\n- Manual centerline\n- Growing centerline\n- Centerline editing\nVolume sculpting","Note: features not\nmentioned since they are\nnot relevant for this\ncomparison.","Both the subject and\nprimary predicate device\ninclude automated and\nmanual segmentation\nfunctionality and both\ndevices include the option\nfor the physician to review\nand edit the segmentation.\nThe segmentation toolset in\nthe subject device\nadditionally includes ML\nfeatures."],["Image Assessment","• Linear (length and\ndiameter), area and\nangle measurements\n• Volume measurements\n• C-arm angulation\ncalculation\n• Text, arrow and 3D\nannotations\n• Calcium scoring\n• Valve assessment","• Linear (length and\ndiameter), area and\nangle measurements\n• Volume measurements\n• C-arm angulation\ncalculation\n• Text, arrow and 3D\nannotations\n• Calcium scoring\n• Valve assessment","• Linear (length and\ndiameter), area and\nangle measurements\n• Volume measurements\n• Text, arrow and 3D\nannotations","Same, the subject device\nand primary predicate\ndevice use the same image\nassessment functionality.\nAlso the secondary\npredicate device uses\nrelevant image assessment\ntypes for analysis of 3D\nultrasound images."],["Image Display","• Orthogonal, oblique,\ndouble-oblique, curved,\ncross-curved, stretched\nMPR, curved MPR views\n• MIP, AIP, MinIP and color\nvolume slabs\n• Volume rendering\n• 2D slice review and stack\ncomparison\n• 4D cine\n• Multi-tissue color and\nopacity control\n• Virtual device displays","• Orthogonal, oblique,\ndouble-oblique, curved,\ncross-curved, stretched\nMPR, curved MPR views\n• MIP, AIP, MinIP and color\nvolume slabs\n• Volume rendering\n• 2D slice review and stack\ncomparison\n• 4D cine\n• Multi-tissue color and\nopacity control\nVirtual device displays","• Oblique, double-oblique\nviews\n• Volume rendering\n• 4D cine","Same, both the subject\ndevice and primary\npredicate device use the\nsame types of image display.\nThe secondary predicate\ndevice uses relevant image\ndisplay features for analysis\nof 3D ultrasound images."],["Storage and Export of\nResults","Session states\nPDF reports","Session states\nPDF reports","Not relevant for\ncomparison.","Same."]],"caption_candidate":"510(k) Summary – K250330 3mensio Workstation","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250337-p7-t0","doc_id":"K250337","page_num":7,"bbox":[72.36,570.48,546.96,710.04],"n_rows":2,"n_cols":2,"columns":["Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart Module\n(K191585)"],"rows":[["Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart Module\n(K191585)"],["The AiORTA - Plan tool is an image analysis software\ntool. It provides visualization and measurements\nbased on 3D reconstruction, computed from\ncardiovascular CTA scans. The device is intended to\nprovide adjunct information to a licensed healthcare\npractitioner (HCP) in addition to clinical data and other\ninputs, as a measurement tool used in assessment of\naortic aneurysm, pre-operative evaluation, planning\nand sizing for cardiovascular intervention and surgery,","iNtuition-Structural Heart Module is a software solution\nthat is intended to assist Cardiologists, Radiologists and\nClinical Specialists with the visualization and\nmeasurements of structures of the heart and vessels.\niNtuition-Structural Heart Module enables the user to:\n• Visualize and measure (diameters, lengths,\nangles, areas and volumes) structures of the\nheart and vessels for pre-operative planning"]],"caption_candidate":"Table 1: Indications for Use Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250337-p8-t0","doc_id":"K250337","page_num":8,"bbox":[72.36,479.64,545.76,712.08],"n_rows":10,"n_cols":3,"columns":["Device Characteristic","Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart\nModule (K191585)"],"rows":[["Device Characteristic","Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart\nModule (K191585)"],["Manufacturer","ViTAA Medical Solutions Inc.","TeraRecon Inc."],["Classification","21 CFR 892.2050","21 CFR 892.2050"],["Product code","QIH","LLZ"],["Intended end-user","Healthcare Practitioner","Healthcare Practitioner"],["Anatomical scope","Abdominal aorta","Aorta, aortic valves, mitral valve, pulmonic\nvalve, atria and atrial appendages, and\nventricles"],["Image source","Cardiovascular CTA scans","CT, MR, Nuc, PET, Angio, US/Echo, SPECT\nscans"],["Operating system","Microsoft Windows","Microsoft Windows"],["System configuration","Web application","Server or workstation"],["Analysis workflow","Semi-automatic analysis pipeline\nrequiring input from ViTAA Analysts.","Fully automated analysis performed in real-\ntime within the software."]],"caption_candidate":"Table 2: Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250337-p9-t0","doc_id":"K250337","page_num":9,"bbox":[72.36,72.36,545.64,433.32],"n_rows":7,"n_cols":3,"columns":["Device Characteristic","Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart\nModule (K191585)"],"rows":[["Device Characteristic","Subject Device: AiORTA - Plan","Predicate Device: iNtuition-Structural Heart\nModule (K191585)"],["Vessel Geometry\nMeasurement Tools","Provides tools for measuring vessel\ngeometry, including diameters, lengths,\nand volumes.","Provides tools for measuring vessel geometry,\nincluding diameters, lengths, volumes, areas,\nand angles."],["Segmentation","Semi-automatic segmentation using\nautomasking algorithm. End-users\n(clinicians) able to review and modify\nsegmentations as needed.","Automatic and manual segmentation\navailable within the software, with end-users\n(clinicians) able to edit and adjust\nsegmentations as needed."],["Centerline detection","Automatic centerline detection within\nthe analysis pipeline.","Both automatic and manual centerline\ndetection are offered, with the ability to edit\nand refine the centerline by the end-user."],["Change in Geometric\nAnalysis","Reports automated measurements\ndescribing changes between two\nstudies.","Not available"],["Storage of results","-Report in PDF format\n-Viewports: Session state","-Structured reporting with xml, text, xls\noutput\n-Word and html report\n-DICOM SC\n-Workflow scenes: restore saved state"],["Viewpoint controls","-General controls (lock viewpoints,\nswitch to single/quad view, etc.)\n-2D CT image controls (pan, window,\nlevel, etc.)\n-3D map controls (rotate, pan, zoom)","Identical to or\nmore extensive than subject device"]],"caption_candidate":"Class II SaMD Premarket Notification 510(k): AiORTA - Plan","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250337-p11-t0","doc_id":"K250337","page_num":11,"bbox":[107.4,402.0,538.2,500.28],"n_rows":4,"n_cols":3,"columns":["","Expert-expert MPAD","Device-expert MPAD"],"rows":[["","Expert-expert MPAD","Device-expert MPAD"],["Length: renal to left iliac bifurcation","7.1mm","6.9mm"],["Length: renal to right iliac bifurcation","10.4mm","9.6mm"],["Diameter: wall right iliac","2.7mm","2.5mm"]],"caption_candidate":"acceptability of the device’s measurements.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250354-p5-t0","doc_id":"K250354","page_num":5,"bbox":[72.5,542.5,492.5,586.5],"n_rows":2,"n_cols":3,"columns":["Manufacturer","Device Name","Application No."],"rows":[["Manufacturer","Device Name","Application No."],["Viz.ai, Inc.","Viz HDS","K232363"]],"caption_candidate":"Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250354-p8-t0","doc_id":"K250354","page_num":8,"bbox":[72.5,433.5,540.5,594.5],"n_rows":6,"n_cols":3,"columns":["Substantial Equivance Table","",""],"rows":[["Substantial Equivance Table","",""],["","Predicate Device","Subject Device"],["","Viz HDS","Viz Subdural+"],["Application No.","K232363","K250354"],["Product Code","QIH","QIH"],["Regulation No.","21 C.F.R. § 892.2050","21 C.F.R. § 892.2050"]],"caption_candidate":"can retrieve by looking at the original NCCT.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250354-p9-t0","doc_id":"K250354","page_num":9,"bbox":[72.5,137.5,540.5,708.5],"n_rows":7,"n_cols":3,"columns":["Intended Use /\nIndications for\nUse","The Viz HDS device is intended for\nautomatic labeling, visualization, and\nquantification of segmentable brain\nstructures from a set of Non-Contrast\nCT (NCCT) head scans. The software\nis intended to automate the current\nmanual process of identifying, labeling,\nand quantifying the volume of\nsegmentable brain structures identified\non NCCT images. Viz HDS provides\nvolumes from NCCT scans acquired at\na single time point. The Viz HDS\nsoftware is indicated for use in the\nanalysis of the following structures:\nIntracranial Hyperdensities, Lateral\nVentricles and Midline Shift. The device\noutput should be reviewed along with\npatient’s original images by a physician.","The Viz Subdural+ (Subdural Plus)\ndevice is intended for automatic\nlabeling, visualization and\nquantification of collections in the\nsubdural space from a set of\nNon-Contrast Head CT (NCCT)\nimages. The software is intended to\nautomate the current manual process\nof identifying, labeling and quantifying\nthe volume of collections in the\nsubdural space identified on NCCT\nimages. Viz Subdural+ provides\nvolumes from NCCT images acquired\nat a single time point.\nThe Viz Subdural+ software is\nintended for labeling subdural\ncollections and reporting the\ngrayscale value of the collection,\nwidest width of the subdural\ncollection, and midline shift. The\ndevice output should be reviewed\nalong with the patient’s original\nimages by a physician qualified to\ninterpret brain CT images."],"rows":[["Intended Use /\nIndications for\nUse","The Viz HDS device is intended for\nautomatic labeling, visualization, and\nquantification of segmentable brain\nstructures from a set of Non-Contrast\nCT (NCCT) head scans. The software\nis intended to automate the current\nmanual process of identifying, labeling,\nand quantifying the volume of\nsegmentable brain structures identified\non NCCT images. Viz HDS provides\nvolumes from NCCT scans acquired at\na single time point. The Viz HDS\nsoftware is indicated for use in the\nanalysis of the following structures:\nIntracranial Hyperdensities, Lateral\nVentricles and Midline Shift. The device\noutput should be reviewed along with\npatient’s original images by a physician.","The Viz Subdural+ (Subdural Plus)\ndevice is intended for automatic\nlabeling, visualization and\nquantification of collections in the\nsubdural space from a set of\nNon-Contrast Head CT (NCCT)\nimages. The software is intended to\nautomate the current manual process\nof identifying, labeling and quantifying\nthe volume of collections in the\nsubdural space identified on NCCT\nimages. Viz Subdural+ provides\nvolumes from NCCT images acquired\nat a single time point.\nThe Viz Subdural+ software is\nintended for labeling subdural\ncollections and reporting the\ngrayscale value of the collection,\nwidest width of the subdural\ncollection, and midline shift. The\ndevice output should be reviewed\nalong with the patient’s original\nimages by a physician qualified to\ninterpret brain CT images."],["Anatomical\nRegion","Head","Head"],["Independent\nStandard of Care\nWorkflow","Yes","Yes"],["Input images","Non-contrast CT from a single time\npoint","Non-contrast CT from a single time\npoint"],["Measured\nStructures /\nConditions","Intracranial hyperdensities, lateral\nventricles and midline shift","Subdural collections and midline shift"],["Measurands","Intracranial hyperdensities volume;\nlateral ventricles volume;\nmidline shift","Subdural collections volume;\nSubdural collections widest width;\nmidline shift"],["Data Acquisition","Acquires medical image data from\nDICOM compliant imaging devices and\nmodalities.","Acquires medical image data from\nDICOM compliant imaging devices\nand modalities."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250354-p10-t0","doc_id":"K250354","page_num":10,"bbox":[72.0,137.5,540.5,312.5],"n_rows":4,"n_cols":3,"columns":["Supported\nImaging Modality","Non-contrast CT (NCCT)","Non-contrast CT (NCCT)"],"rows":[["Supported\nImaging Modality","Non-contrast CT (NCCT)","Non-contrast CT (NCCT)"],["Alteration of\nOriginal Image","No","No"],["Artificial\nIntelligence\nAlgorithm","Yes","Yes"],["Output","Multiple electronic reports with\nmeasurements quantifying brain\nstructures and midline shift;\nannotated DICOM Images.","Multiple electronic reports with\nmeasurements quantifying subdural\ncollections and midline shift;\nannotated DICOM Images."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250354-p10-t1","doc_id":"K250354","page_num":10,"bbox":[72.0,462.5,540.5,661.5],"n_rows":5,"n_cols":5,"columns":["Metric","Mean Absolute Error (MAE)","","","DICE Score"],"rows":[["Metric","Mean Absolute Error (MAE)","","","DICE Score"],["","Mean (95%\nConfidence\nInterval)","Standard\nDeviation","Median (10th -\n90th Percentile)","Mean (95%\nConfidence\nInterval)"],["Subdural Collection Volume\n(N=203)","7.53 (5.60, 9.45)","13.91","2.70 (0.0 - 22.22)","73% (68% -\n77%)"],["Subdural Collection\nMaximum (Widest)\nThickness\n(N=203)","1.77 (1.24, 2.30)","3.84","0.43 (0.0 - 5.37)","N/A"],["Midline Shift\n(N=151)","1.1 (0.94,1.27)","1.03","0.8 (0.17 - 2.37)","N/A"]],"caption_candidate":"NCCT imaging assessment after presenting to one of the participating sites.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250367-p7-t0","doc_id":"K250367","page_num":7,"bbox":[71.24,131.84,540.76,711.7],"n_rows":9,"n_cols":5,"columns":["","Predicate Device","Reference Device","Subject Device","Remark/"],"rows":[["","Predicate Device","Reference Device","Subject Device","Remark/"],["","(K241211)","(K231668)","","Discussion"],["Device Name","CoLumbo","Spine CAMP™ (1.1)","CoLumboX","n/a"],["Manufacturer","Smart Soft Healthcare","Medical Metrics, Inc.","Smart Soft Healthcare","n/a"],["Classification\nPanel","Radiology","Radiology","Radiology","Same"],["CFR Section","21 CFR 892.2050\n(Medical image\nmanagement and processing\nsystem)\nQIH","21 CFR 892.2050\n(Medical image\nmanagement and processing\nsystem)\nQIH","Proposed:\n21 CFR 892.2050\n(Medical image\nmanagement and processing\nsystem)\nQIH","Same"],["Device Class","Class II","Class II","Class II","Same"],["Intended Use","Intended to assist the\nradiologist, spine- and\nneuro-surgeon in\nperforming routine\nevaluations of lumbar spine\nMRI exams and producing\na report of findings\nsummarizing the results of\nthe evaluation.","Spine CAMP™ is a fully-\nautomated image\nprocessing software device.\nIt is designed to be used\nwith X-ray images and is\nintended to aid medical\nprofessionals in the\nmeasurement and\nassessment of spinal\nparameters. Spine CAMP™\nis capable of calculating\ndistances, angles, linear\ndisplacements, angular\ndisplacements, and\nmathematical combinations\nof these metrics to\ncharacterize the\nmorphology, alignment, and\nmotion of the spine. These\nanalysis results are\npresented in the form of\nreports, annotated images,\nand visualizations of\nintervertebral motion to\nsupport their interpretation.","Intended to assist the\nradiologist, spine- and\nneuro-surgeon in\nperforming routine\nevaluations of lumbar spine\nx-ray images.","Similar"],["Indications for\nUse","CoLumbo is an image post-\nprocessing and\nmeasurement software tool\nthat provides quantitative\nspine measurements from\npreviously-acquired\nDICOM lumbar spine\nMagnetic Resonance (MR)\nimages for users’ review,\nanalysis, and interpretation.\nIt provides the following","Spine CAMP™ is a fully-\nautomated software that\nanalyzes Xray images of the\nspine to produce reports\nthat contain static and/or\nmotion metrics. Spine\nCAMP™ can be used to\nobtain metrics from sagittal\nplane radiographs of the\nlumbar and/or cervical\nspine and it can be used to","CoLumboX is an image\npost-processing and\nmeasurement software tool\nthat provides quantitative\nspine measurements from\npreviously-acquired\nDICOM lumbar spine x-ray\nimages for users’ review,\nanalysis, and interpretation.\nIt provides the following\nfunctionality to assist users","Similar"]],"caption_candidate":"Table 1 – Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250367-p8-t0","doc_id":"K250367","page_num":8,"bbox":[71.18,71.16,540.82,717.58],"n_rows":3,"n_cols":5,"columns":["","functionality to assist users\nin visualizing, measuring\nand documenting out-of-\nrange measurements:\n•Feature segmentation;\n•Feature measurement;\n•Threshold-based labeling\nof out-of-range\nmeasurement; and\n•Export of measurement\nresults to a written report\nfor user’s review, revise\nand approval.\nCoLumbo does not produce\nor recommend any type of\nmedical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify\nfeatures in lumbar MR\nimages and compile a\nreport. The user is\nresponsible for\nconfirming/modifying\nsettings, reviewing and\nverifying the software-\ngenerated measurements,\ninspecting out-of-range\nmeasurements, and\napproving draft report\ncontent using their medical\njudgment and discretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM images of\nMRI acquired from lumbar\nspine exams of patients\naged 18 and above are\nconsidered to be valid\ninput. CoLumbo does not\nsupport DICOM images of\npatients that are pregnant,\nundergo MRI scan with\ncontrast media, or have\npost-operative\ncomplications, tumors,\ninfections.","visualize intervertebral\nmotion via an image\nregistration method referred\nto as “stabilization.” The\nradiographic metrics can be\nused to characterize and\nassess spinal health in\naccordance with established\nguidance. For example,\ncommon clinical uses\ninclude assessing spinal\nstability, alignment,\ndegeneration, fusion,\nmotion preservation, and\nimplant performance. The\nmetrics produced by Spine\nCAMP™ are intended to be\nused to support qualified\nand licensed professional\nhealthcare practitioners in\nclinical decision-making for\nskeletally mature patients of\nage 18 and above.","in visualizing, measuring\nand documenting\nmeasurements:\n•Feature segmentation;\n•Feature measurement;\n•Threshold-based labeling\nof out-of-range\nmeasurement; and\n•Export of measurement\nresults.\nCoLumboX does not\nproduce or recommend any\ntype of medical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify\nfeatures in lumbar x-ray\nimages and potentially\ncompile a report. The user\nis responsible for\nconfirming/modifying\nsettings, reviewing the\nsoftware-generated\nmeasurements, and utilizing\nCoLumboX output using\ntheir medical judgment and\ndiscretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM x-ray images\nof patients aged 18 and\nolder are considered to be\nvalid input. CoLumboX\ndoes not support DICOM\nimages of patients who are\npregnant or those\nwith post-operative\ncomplications, tumors, or\ninfections.",""],"rows":[["","functionality to assist users\nin visualizing, measuring\nand documenting out-of-\nrange measurements:\n•Feature segmentation;\n•Feature measurement;\n•Threshold-based labeling\nof out-of-range\nmeasurement; and\n•Export of measurement\nresults to a written report\nfor user’s review, revise\nand approval.\nCoLumbo does not produce\nor recommend any type of\nmedical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify\nfeatures in lumbar MR\nimages and compile a\nreport. The user is\nresponsible for\nconfirming/modifying\nsettings, reviewing and\nverifying the software-\ngenerated measurements,\ninspecting out-of-range\nmeasurements, and\napproving draft report\ncontent using their medical\njudgment and discretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM images of\nMRI acquired from lumbar\nspine exams of patients\naged 18 and above are\nconsidered to be valid\ninput. CoLumbo does not\nsupport DICOM images of\npatients that are pregnant,\nundergo MRI scan with\ncontrast media, or have\npost-operative\ncomplications, tumors,\ninfections.","visualize intervertebral\nmotion via an image\nregistration method referred\nto as “stabilization.” The\nradiographic metrics can be\nused to characterize and\nassess spinal health in\naccordance with established\nguidance. For example,\ncommon clinical uses\ninclude assessing spinal\nstability, alignment,\ndegeneration, fusion,\nmotion preservation, and\nimplant performance. The\nmetrics produced by Spine\nCAMP™ are intended to be\nused to support qualified\nand licensed professional\nhealthcare practitioners in\nclinical decision-making for\nskeletally mature patients of\nage 18 and above.","in visualizing, measuring\nand documenting\nmeasurements:\n•Feature segmentation;\n•Feature measurement;\n•Threshold-based labeling\nof out-of-range\nmeasurement; and\n•Export of measurement\nresults.\nCoLumboX does not\nproduce or recommend any\ntype of medical diagnosis or\ntreatment. Instead, it simply\nhelps users to more easily\nidentify and classify\nfeatures in lumbar x-ray\nimages and potentially\ncompile a report. The user\nis responsible for\nconfirming/modifying\nsettings, reviewing the\nsoftware-generated\nmeasurements, and utilizing\nCoLumboX output using\ntheir medical judgment and\ndiscretion.\nThe device is intended to be\nused only by hospitals and\nother medical institutions.\nOnly DICOM x-ray images\nof patients aged 18 and\nolder are considered to be\nvalid input. CoLumboX\ndoes not support DICOM\nimages of patients who are\npregnant or those\nwith post-operative\ncomplications, tumors, or\ninfections.",""],["Intended User","Radiologist & neuro- and\nspine-surgeons","Trained professionals","Radiologist & neuro- and\nspine-surgeons","Same"],["Intended\nPatient\nPopulation","The intended patient\npopulation is not subject to\nany restrictions.\nAutomation support\nrequires images of patients\nof 18 years and older, not","Skeletally mature patients\nof age 18 and above","Skeletally mature patients\nof age 18 and older that are\nnot pregnant and do not\nhave post-operative\ncomplications, tumors,\ninfections.","Highly\nSimilar"]],"caption_candidate":"CoLumboX 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250367-p9-t0","doc_id":"K250367","page_num":9,"bbox":[71.18,71.16,540.82,223.7],"n_rows":4,"n_cols":5,"columns":["","pregnant, without post-\noperative complications,\ntumors, infections.","","",""],"rows":[["","pregnant, without post-\noperative complications,\ntumors, infections.","","",""],["Supported\nBody Part","Lumbar spine","Lumbar and/or cervical\nspine","Lumbar spine","Same"],["Threshold-\nBased Out-of-\nRange\nMeasurements","Yes","Yes","Yes","Same"],["Supported\nModality","MR","X-ray","X-ray","Same with\nreference\ndevice"]],"caption_candidate":"CoLumboX 510(k) Premarket Notification Smart Soft Healthcare","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p5-t0","doc_id":"K250369","page_num":5,"bbox":[72.32,619.54,539.68,675.36],"n_rows":2,"n_cols":3,"columns":["Name","Manufacturer","510(k)#"],"rows":[["Name","Manufacturer","510(k)#"],["Axial3D Insight","Axial Medical Printing Limited","K232841"]],"caption_candidate":"Table 5 - Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p6-t0","doc_id":"K250369","page_num":6,"bbox":[72.27,472.11,540.21,713.58],"n_rows":11,"n_cols":4,"columns":["","Axial3D Insight","Axial3D Insight (Predicate",""],"rows":[["","Axial3D Insight","Axial3D Insight (Predicate",""],["Attribute","","","Comparison"],["","(Proposed Device)","Device)",""],["","","",""],["Device Manufacturer","Axial Medical Printing Limited","Axial Medical Printing Limited","N/A"],["Device Name","Axial3D Insight","Axial3D Insight","N/A"],["Device Trade or\nProprietary Name","Axial3D Insight","Axial3D Insight","N/A"],["510(k) Number","K250369","K232841","N/A"],["Device Regulation\nName","Automated Radiological Image\nProcessing Software","Automated Radiological Image\nProcessing Software","Equivalent"],["Device Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Equivalent"],["Device Product\nCode","QIH","QIH","Equivalent"]],"caption_candidate":"Table 2 – Predicate Device Comparison: Intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p7-t0","doc_id":"K250369","page_num":7,"bbox":[72.29,98.89,540.19,714.3],"n_rows":7,"n_cols":4,"columns":["","Axial3D Insight","Axial3D Insight (Predicate",""],"rows":[["","Axial3D Insight","Axial3D Insight (Predicate",""],["Attribute","","","Comparison"],["","(Proposed Device)","Device)",""],["","","",""],["Device\nClassification FDA","Class II","Class II","Equivalent"],["Indication for Use","Axial3D Insight is intended for\nuse as a cloud-based service and\nimage segmentation framework\nfor the transfer of DICOM\nimaging information from a\nmedical scanner to an output file.\nThe Axial3D Insight output file\ncan be used for fabrication of\nphysical replicas of the output file\nusing additive manufacturing\nmethods.\nThe output file or physical replica\ncan be used for treatment\nplanning.\nThe output file or physical replica\ncan be used for diagnostic\npurposes in the field of trauma,\northopedic, maxillofacial, and\ncardiovascular applications.\nAxial3D Insight should be used in\nconjunction with other diagnostic\ntools and expert clinical\njudgement.","Axial3D Insight is intended for use\nas a cloud-based service and\nimage segmentation framework for\nthe transfer of DICOM imaging\ni nformation from a medical scanner\nto an output file.\nThe Axial3D Insight output file can\nbe used for fabrication of physical\nreplicas of the output file using\nadditive manufacturing methods.\nThe output file or physical replica\ncan be used for treatment\nplanning.\nThe output file or physical replica\ncan be used for diagnostic\npurposes in the field of trauma,\northopedic, maxillofacial, and\ncardiovascular applications.\nAxial3D Insight should be used in\nconjunction with other diagnostic\ntools and expert clinical judgement.","Equivalent"],["Intended Use","Axial Medical Printing Limited,\nAxial3D Insight provides patient-\nspecific 1:1 scale replica models,\neither as a digital file or as a 3D\nprinted physical model.\nThe digital file or 3D printed\nphysical model is intended to be\nused in conjunction with the\nDICOM images and expert\nclinical judgement. The\napplications for using the\nphysical 3D printed model as a\npresurgical planning tool are as\nfollows:\nPreoperative planning of surgical\ntreatment options including\nplanning for surgical instruments,\naiding decisions on implants, and\naiding the surgical treatment\nplan., All planning using the 3D\nreplica model should be carried\nout with the assistance of the\nDICOM images","Axial Medical Printing Limited,\nAxial3D Insight provides patient-\nspecific 1:1 scale replica models,\neither as a digital file or as a 3D\nprinted physical model.\nThe digital file or 3D printed\nphysical model is intended to be\nused in conjunction with the\nDICOM images and expert clinical\njudgement. The applications for\nusing the physical 3D printed\nmodel as a presurgical planning\ntool are as follows:\nPreoperative planning of surgical\ntreatment options including\nplanning for surgical instruments,\naiding decisions on implants, and\naiding the surgical treatment plan.,\nAll planning using the 3D replica\nmodel should be carried out with\nthe assistance of the DICOM\nimages\nCommunication with the surgical\nteam to discuss the surgical","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p8-t0","doc_id":"K250369","page_num":8,"bbox":[72.28,98.89,540.2,501.42],"n_rows":10,"n_cols":4,"columns":["","Axial3D Insight","Axial3D Insight (Predicate",""],"rows":[["","Axial3D Insight","Axial3D Insight (Predicate",""],["Attribute","","","Comparison"],["","(Proposed Device)","Device)",""],["","","",""],["","Communication with the surgical\nteam to discuss the surgical\ntreatment plan in conjunction with\nDICOM images\nCommunication with the patient\nto discuss the surgical treatment\nplan in conjunction with DICOM\nimages\nEducation tool for surgical\nplanning.\nThe 3D printed physical model\ncan be used for surgical planning\nin the following applications:\northopedics, trauma,\nmaxillofacial, and cardiac\nsurgery.","treatment plan in conjunction with\nDICOM images\nCommunication with the patient to\ndiscuss the surgical treatment plan\nin conjunction with DICOM images\nEducation tool for surgical\nplanning.\nThe 3D printed physical model can\nbe used for surgical planning in the\nfollowing applications:\northopedics, trauma, maxillofacial,\nand cardiac surgery.",""],["Method of Use","Used in conjunction with other\ndiagnostic tools and expert\nclinical judgment.","Used in conjunction with other\ndiagnostic tools and expert clinical\njudgment.","Equivalent"],["Use Environment","Hospital","Hospital","Equivalent"],["OTC or Prescription\nDevice","Prescription Use","Prescription Use","Equivalent"],["V&V","Complies with FDA Guidance\nRequirement","Complies with FDA Guidance\nRequirement","Equivalent"],["PCCP","Will have access to approved\nPCCP","Will have access to approved\nPCCP","Different – the premise\nof this 510k is to have\nthe PCCP approved"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p9-t0","doc_id":"K250369","page_num":9,"bbox":[72.27,98.89,540.21,512.58],"n_rows":11,"n_cols":4,"columns":["","Axial3D Insight","Axial3D Insight (Predicate",""],"rows":[["","Axial3D Insight","Axial3D Insight (Predicate",""],["Attribute","","","Comparison"],["","(Proposed Device)","Device)",""],["","","",""],["Supported\nModalities","CT and CTA","CT and CTA","Equivalent"],["Image\nregistration","Yes","Yes","Equivalent"],["Segmentation\nFeatures","A combination of automated\ntools with smart editing tools","A combination of automated\ntools with smart editing tools","Equivalent"],["View\nManipulation and\nVolume\nRendering","Yes","Yes","Equivalent"],["Regions and\nVolumes of\nInterest (ROI)","Orthopedics / Trauma\nCardiovascular\nCranio- Maxillofacial","Orthopedics / Trauma\nCardiovascular\nCranio- Maxillofacial","Equivalent"],["Region/volume of\ninterest\nmeasurements\nand size\nmeasurements","Yes","Yes","Equivalent"],["Region/Volume\nQuantification","Yes","Yes","Equivalent"]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p10-t0","doc_id":"K250369","page_num":10,"bbox":[72.32,494.19,540.22,669.56],"n_rows":15,"n_cols":7,"columns":["","","","Cardiac CT/CTa","Neuro CT/CTa","Ortho CT","Trauma CT"],"rows":[["","","","Cardiac CT/CTa","Neuro CT/CTa","Ortho CT","Trauma CT"],["","","","","","",""],["","Number of","","4,838","4,041","10,857","19,134"],["","Images Used for","","","","",""],["","Validation","","","","",""],["","Slice Spacing","","0.4 - 0.8","0.44 - 1.0","0.3 - 2.0","0.2 - 2.0"],["","Range","","","","",""],["","(Min, Max in mm)","","","","",""],["","Slice Spacing","","0.54","0.63","0.79","0.76"],["","Average","","","","",""],["","(in mm)","","","","",""],["","Pixel Size Range","","0.23 - 0.78","0.34 - 0.70","0.18 - 0.98","0.22 - 0.98"],["","(Min, Max in mm)","","","","",""],["","Pixel Size","","0.46","0.51","0.44","0. 51"],["","Average (mm)","","","","",""]],"caption_candidate":"Table 4: Software Validation Data","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p11-t0","doc_id":"K250369","page_num":11,"bbox":[72.51,98.93,540.46,356.58],"n_rows":5,"n_cols":6,"columns":["","Manufacturer","","","Model",""],"rows":[["","Manufacturer","","","Model",""],["GE Medical Systems","","","Lightspeed Pro 16\nLightspeed Pro 32\nRevolution CT\nOptima CT660\nDiscovery CT750 HD","",""],["Siemens","","","SOMATOM Definition Flash\nSOMATOM Definition Edge\nSOMATOM Definition AS\nSOMATOM Definition AS+\nSOMATOM Perspective\nSOMATOM Force\nSensation 16\nAXIOM-Artis\nEmotion 16","",""],["Phillips","","","IQON Spectral CT\niCT 128\niCT 256\nIngenuity Core 128\nBrilliance 62","",""],["Toshiba","","","Aquillon PRIME\nAquillon PRIME SP","",""]],"caption_candidate":"Traditional 510(k) Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250369-p12-t0","doc_id":"K250369","page_num":12,"bbox":[72.05,266.24,539.53,683.22],"n_rows":6,"n_cols":4,"columns":["ID","Summary","Trigger for Retrain","Timeframe"],"rows":[["ID","Summary","Trigger for Retrain","Timeframe"],["MOD_ML_001","Increasing Volume of\nTraining, Tuning and\nTesting data","Newly available or identified\nsource(s) of data representing\nthe original intended use\npopulation","Reviewed periodically\nevery 6 months"],["MOD_ML_002","Semantic Sub-Labeling","Internal R&D activities\ndemonstrating benefits from\nintroducing semantic sub-\nlabelling that increase the\neffectiveness of AxialML output\nas utilized by Axial3D internal\nengineers","Within 18 months"],["MOD_ML_003","Introduction of New\nAssistive Labeling","Internal R&D activities\ndemonstrating performance\nbenefits from introducing\nassistive labels that increases\nthe effectiveness of AxialML\noutput as utilized by Axial3D\ninternal engineers","Reviewed periodically\nevery 6 months"],["MOD_ML_004","Model Parameter and\nHyperparameter Tuning","Internal R&D activities\ndemonstrating performance\nbenefits from parameter and\nhyperparameter tuning that\nincreases the effectiveness of\nAxialML output as utilized by\nAxial3D internal engineers","Reviewed periodically\nevery 12 months"],["MOD_ML_005","Performance Increasing\nLibrary Updates","Newly available library or\ndependency updates, of\ncomponent utilized in the\noriginal device that increases\nthe effectiveness of AxialML\noutput as utilized by Axial3D\ninternal engineers","Reviewed periodically\nevery 6 months"]],"caption_candidate":"Table 5: Potential Modifications List","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p5-t0","doc_id":"K250370","page_num":5,"bbox":[71.15,251.64,581.51,332.4],"n_rows":5,"n_cols":2,"columns":["Device Trade Name","SCENARIA View Phase 5.0"],"rows":[["Device Trade Name","SCENARIA View Phase 5.0"],["Common Name","Computed tomography x-ray system"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","892.1750"],["Product Code","JAK"]],"caption_candidate":"Subject Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p5-t1","doc_id":"K250370","page_num":5,"bbox":[71.15,370.68,581.51,467.52],"n_rows":6,"n_cols":2,"columns":["Predicate Device Trade Name","SCENARIA View 4.2"],"rows":[["Predicate Device Trade Name","SCENARIA View 4.2"],["510(k) Number","K231574"],["Common Name","Computed tomography x-ray system"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","892.1750"],["Product Code","JAK"]],"caption_candidate":"Predicate Device Name","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p7-t0","doc_id":"K250370","page_num":7,"bbox":[71.16,128.16,581.52,581.88],"n_rows":17,"n_cols":5,"columns":["Systems","Subject Device\nSCENARIA View Phase 5.0","Predicate Device\nSCENARIA View 4.2 (K231574)","","Discussion of Difference"],"rows":[["Systems","Subject Device\nSCENARIA View Phase 5.0","Predicate Device\nSCENARIA View 4.2 (K231574)","","Discussion of Difference"],["Gantry","There are no differences between the two systems.","","","--"],["Detector","There are no differences between the two systems.","","","--"],["X-ray Tube","There are no differences between the two systems.","","","--"],["X-ray Generator","There are no differences between the two systems.","","","--"],["Patient Table","Types of maximum load capacity:\n250kg, 300kg","Types of maximum load capacity:\n250kg","","Different specifications do not\nconstitute a new intended use.\nThere are no significant\nchanges in technological\ncharacteristics. For safety, this\nitem is controlled and tested\naccording to same regulations\nand/or standards as the\npredicate device."],["Operator’s\nconsole","There are no differences between the two systems.","","","--"],["Scanning","There are no differences between the two systems.","","","--"],["Reconstruction","There are no differences between the two systems.","","","--"],["Performance","There are no differences between the two systems.","","","--"],["Dose Controls","There are no differences between the two systems.","","","--"],["Dose Display","There are no differences between the two systems.","","","--"],["Features\nThere are the following differences between the two systems.","","","",""],["AutoPose","Yes","","--","Note 1"],["RemoteRecon","Yes","","--","Note 2"],["Motion corrected\nreconstruction","Supported body parts:\nHeart (Cardio Still Shot),\nChest (Body Still Shot)","","Supported body part:\nHeart (Cardio Still Shot)","Note 3"],["AutoPositioning","Supported body parts:\nHead, Chest, Head and Neck,\nNeck, C-spine, Heart, Chest-\nAbdomen, Chest-Upper Abdomen,\nAbdomen-Pelvis, Abdomen, Pelvis,\nT-spine, L-spine, T-L-spine","","Supported body parts:\nHead, Chest","Note 4"]],"caption_candidate":"characteristics.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p11-t0","doc_id":"K250370","page_num":11,"bbox":[125.48,71.29,529.2,125.5],"n_rows":3,"n_cols":7,"columns":["","Region","","Head","Neck","Chest","Heart"],"rows":[["","Region","","Head","Neck","Chest","Heart"],["","Number of cases","","50","50","52","54"],["","Collection site","","Clinical sites in the USA","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p11-t1","doc_id":"K250370","page_num":11,"bbox":[125.48,142.05,529.2,196.28],"n_rows":3,"n_cols":5,"columns":["","Region","","Abdomen","Abdomen-Pelvis"],"rows":[["","Region","","Abdomen","Abdomen-Pelvis"],["","Number of cases","","52","52"],["","Collection site","","Clinical sites in the USA",""]],"caption_candidate":"Collection site Clinical sites in the USA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p11-t2","doc_id":"K250370","page_num":11,"bbox":[125.48,212.67,529.2,277.56],"n_rows":3,"n_cols":5,"columns":["Region","","","Chest-Abdomen","Chest-Upper\nAbdomen"],"rows":[["Region","","","Chest-Abdomen","Chest-Upper\nAbdomen"],["","Number of cases","","50",""],["","Collection site","","Clinical sites in the USA",""]],"caption_candidate":"Collection site Clinical sites in the USA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250370-p11-t3","doc_id":"K250370","page_num":11,"bbox":[125.48,294.02,529.2,358.92],"n_rows":3,"n_cols":7,"columns":["Region","","","C-Spine","T-\nSpine","L-\nSpine","T-L-\nSpine"],"rows":[["Region","","","C-Spine","T-\nSpine","L-\nSpine","T-L-\nSpine"],["","Number of cases","","50","50","50","24"],["","Collection site","","Clinical sites in the USA","","",""]],"caption_candidate":"Collection site Clinical sites in the USA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250379-p5-t0","doc_id":"K250379","page_num":5,"bbox":[108.24,115.56,539.76,582.48],"n_rows":11,"n_cols":2,"columns":["Date:","24 February 2025"],"rows":[["Date:","24 February 2025"],["Submitter:","GE Medical Systems, LLC\n3200 N Grandview Blvd. Waukesha, WI USA 53188"],["Distributor:","GE Medical Systems, LLC\n3200 N Grandview BLVD. Waukesha, WI USA 53188"],["Primary Contact\nPerson:","Glen Sabin\nDirector, Regulatory Affairs\nGE HealthCare\nPhone: 262- 5216848\nE-mail: glen.sabin@gehealthcare.com"],["Secondary\nContact Person:","Huande Li\nManager, Regulatory Affairs, MR\nPhone: 86-18101131237\nE-mail: huande.li@gehealthcare.com"],["Device Trade\nName:","SIGNA Prime Elite"],["Common/Usual\nName:","Magnetic Resonance Diagnostic Device"],["Classification\nNames:","Magnetic Resonance Diagnostic Device per 21 CFR\n892.1000"],["Product Code:","LNH, LNI"],["Predicate\nDevice(s):","SIGNA Victor (K223439)"],["Reference\nDevice(s):","SIGNA Champion (K233728)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250379-p7-t0","doc_id":"K250379","page_num":7,"bbox":[108.24,72.24,539.76,467.88],"n_rows":7,"n_cols":4,"columns":["Subsystem or\ncomponent","Predicate Device\nSIGNA Victor","Proposed Device\nSIGNA Prime Elite","Comments"],"rows":[["Subsystem or\ncomponent","Predicate Device\nSIGNA Victor","Proposed Device\nSIGNA Prime Elite","Comments"],["Magnet","1.5T Superconducting Magnet with\nactive shielding.","","SIGNA Prime Elite\nuses a magnet\nequivalent to that of the\npredicate SIGNA\nVictor."],["Gradient\nsubsystem","Water cooled gradient coil with active\nshielding","","SIGNA Prime Elite\nuses an equivalent\ngradient subsystem as\nthe predicate SIGNA\nVictor."],["RF transmit\nsubsystem","Transmit with integrated body coil and\nlocal T/R coil.","","SIGNA Prime Elite\nuses an equivalent RF\ntransmit subsystem as\nthe predicate SIGNA\nVictor."],["RF receive\nsubsystem","Digitize-Per-Pin (DPP) receive chain\narchitecture.","","SIGNA Prime Elite\nuses the identical DPP\narchitecture as\nthe predicate SIGNA\nVictor."],["RF coils","Comprehensive suite of detachable coils\nfor imaging all anatomies","","Coils used by SIGNA\nPrime Elite are\nidentical with those\nused by the predicate\nSIGNA Victor."],["Software\nfeatures","Comprehensive suite of software\nfeatures, pulse sequences, and image\nprocessing applications to support MR\nimaging of all anatomies.","","SIGNA Prime Elite\nuses equivalent\nsoftware with SIGNA\nChampion."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250416-p9-t0","doc_id":"K250416","page_num":9,"bbox":[72.24,302.16,539.76,709.2],"n_rows":12,"n_cols":5,"columns":["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],["510K Number","N/A","K210831","K232231","-"],["Manufacturer","Galileo CDS Inc","CorTechs Labs, Inc.","Quibim S.L.","-"],["Classification","Class II","Class II","Class II","Same"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","Same"],["Regulation\nDescription","Medical image\nmanagement and\nprocessing system.","Medical image\nmanagement and\nprocessing system.","Medical image\nmanagement and\nprocessing system.","Same"],["Classification\nName","Automated\nRadiological Image\nProcessing Software","Automated Radiological\nImage Processing\nSoftware","Automated Radiological\nImage Processing\nSoftware","Same"],["Product code","QIH, LLZ","QIH","QIH, LLZ","Same"],["","","","",""],["Intended Use","MR imaging data\npost processing\nsoftware","MR imaging data post\nprocessing software","MR imaging data post\nprocessing software","Same"],["Type of Imaging\nScan","MRI","MRI","MRI","Same"],["Intended Body\nPart","Brain","Brain","Brain","Same"]],"caption_candidate":"5.5. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250416-p10-t0","doc_id":"K250416","page_num":10,"bbox":[72.24,72.24,539.76,719.28],"n_rows":4,"n_cols":5,"columns":["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],["Indications for\nUse","GBrain MRI is a\npost processing\nmedical device\nsoftware intended\nfor analyzing and\nquantitatively\nreporting signal\nhyperintensities in\nthe brain on FLAIR\nMR images in the\ncontext of diagnostic\nradiology.\nGBrain MRI is\nintended to provide\nautomatic\nsegmentation,\nquantification, and\nreporting of derived\nimage metrics. It is\nnot intended for the\ndetection or specific\ndiagnosis of any\ndisease nor for the\ndetection of signal\nhyperintensities.\nGBrain MRI should\nnot be used in-lieu of\na full evaluation of\nthe patient’s MRI\nscans. The physician\nretains the ultimate\nresponsibility for\nmaking the final\npatient management\nand treatment\ndecisions.","OnQ Neuro is a fully\nautomated post\nprocessing medical\ndevice software\nintended for analyzing\nand evaluating\nneurological MR image\ndata.\nOnQ Neuro is intended\nto provide automatic\nsegmentation,\nquantification, and\nreporting of derived\nimage metrics.\nOnQ Neuro is\nadditionally intended to\nprovide automatic\nfusion of derived\nparametric maps with\nanatomical MRI data.\nOnQ Neuro is intended\nfor use on brain tumors,\nwhich are\nknown/confirmed to be\npathologically\ndiagnosed cancer.\nOnQ Neuro is intended\nfor comparison of\nderived image metrics\nfrom multiple time\npoints.\nThe physician retains\nthe ultimate\nresponsibility for\nmaking the final\ndiagnosis and treatment\ndecision.","QP-Brain® is a medical\nimaging processing\napplication intended for\nautomatic labeling and\nvolumetric quantification\nof segmentable brain\nstructures and white\nmatter hyperintensities\n(WMH) from a set of\nadults and adolescents 18\nand older MR images.\nVolumetric\nmeasurements may be\ncompared to reference\npercentile data. The\napplication is used by\nclinicians with proper\ntraining, as a support tool\nin assessment of\nstructural MRIs. Patient\nmanagement decisions\nshould not be based\nsolely on the results of\nthe device.","The indications for use\nare similar to the\npredicate devices. The\nsubject device analyzes\nsignal hyperintensities\nregardless of location\nsimilar to the primary\npredicate and also\ndetects hyperintensities\nin white matter similar\nto the secondary\npredicate. As with the\nsecondary predicate,\nthe subject device has a\ngeneral indication and\nis not specific to a\nparticular disease or\ncondition."],["Environment for\nuse","Hospital, Clinic,\nImaging Center,\nMedical Offices","Hospital, Clinic,\nImaging Center,\nMedical Offices","Hospital, Clinic, Imaging\nCenter, Medical Offices","Same"],["Intended Patient\nPopulation","Adult patients aged\n21\nand above with a\nbrain MRI study.","Patients with brain\ntumors, which are\nknown/confirmed to be","Adult patients and\nadolescent patients aged\n18\nthrough 21 with brain\nMRI","Similar to secondary\npredicate and the\nmajority of the primary\npredicate’s population."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250416-p11-t0","doc_id":"K250416","page_num":11,"bbox":[72.24,72.24,539.76,707.52],"n_rows":8,"n_cols":5,"columns":["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],["","","pathologically\ndiagnosed cancer.","study. Available up to 94\nyears.",""],["Intended User","Radiologists,\nImaging\nProfessionals, and\nother Clinicians\nworking with\nradiological images.\nThe application\nshould be\nused as a support\ntool in assessment of\nstructural MRIs.\nPatient management\ndecisions should not\nbe based solely on\nthe results of the\ndevice.","Radiologists, and\nOncologists","The application should\nbe\nused by clinicians with\nproper training, as a\nsupport\ntool in assessment of\nstructural MRIs. Patient\nmanagement decisions\nshould not be based\nsolely on the results of\nthe device.",""],["","","","",""],["Design and\nIncorporated\nTechnology","Automated\nsegmentation using\ndeep learning\nfollowed by volume\ncalculations, and\nreport generation.\nResults displayed on\nPACS.","Automated\nsegmentation using deep\nlearning followed by\nvolume calculations.\nResults displayed on\nPACS.","Automated segmentation\nusing deep learning\nfollowed by volume\ncalculations, and report\ngeneration.\nResults displayed on\nPACS.","Same"],["Physical\nCharacteristics","Software package-\nOperates on off-the-\nshelf hardware\n(multiple vendors).","Software package-\nOperates on multiple\nplatforms","Software package-\nOperates on on off-the-\nshelf hardware (multiple\nvendors).","Same"],["Data Source","Supports DICOM\nformat as input from\nthe MRI scanner or\nthe PACS.","Supports DICOM\nformat as input from the\nMRI scanner.","Supports DICOM format\nas input from the MRI\nscanner.","Same with the addition\nof input from the\nPACS."],["Output","Provides volumetric\nmeasurements of\nregions with\nhyperintense signal\non T2w FLAIR\nimages.\nIncludes segmented\ncolor overlays and","Provides volumetric\nmeasurements of\ndifferent regions of\nbrain tumors including\nbut not restricted to\nregions with\nhyperintense signal on\nT2w FLAIR images.\nIncludes segmented","Provides volumetric\nmeasurements of\ndifferent brain structures\non T1 MR images, as\nwell as of White Matter\nHyperintensities on T2w\nFLAIR images.\nIncludes segmented color\noverlays and volumetric","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250416-p12-t0","doc_id":"K250416","page_num":12,"bbox":[72.24,72.24,539.76,341.04],"n_rows":5,"n_cols":5,"columns":["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Primary Predicate\nOnQ Neuro (K210831)","Secondary Predicate\nQP-Brain (K232231)","Comments on\nSubstantial\nEquivalence"],["","volumetric reports","color overlays and\nvolumetric reports","reports",""],["Reporting","Results displayed in\ntext and graphical\nformats","Results displayed in\ntabular and graphical\nformats","Results displayed in\ntabular and graphical\nformats",""],["DICOM\nCommunication","Yes","Yes","Yes","Same"],["Safety","Automated quality\ncontrol function:\nscan protocol\nverification.\nResults must be\nreviewed\nby a clinician with\nproper\ntraining.","Display/measurement\ndata can be viewed,\naccepted, or rejected by\na physician.","Automated quality\ncontrol function: scan\nprotocol verification.\nResults must be reviewed\nby a clinician with proper\ntraining.","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p5-t0","doc_id":"K250427","page_num":5,"bbox":[111.46,175.03,529.54,345.82],"n_rows":6,"n_cols":2,"columns":["Company Name:","Taiwan Medical Imaging Co., Ltd."],"rows":[["Company Name:","Taiwan Medical Imaging Co., Ltd."],["Address:","3F., No. 1, Fuxing 4th Rd., Qianzhen Dist.,\nKaohsiung City 806611\nTaiwan"],["Contact Person:","Bo-Ru Lin"],["Phone:","+886-2-25555835"],["Email:","boru.lin@ailabs.tw"],["Date Prepared","February 14, 2025"]],"caption_candidate":"1 Submitter Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p5-t1","doc_id":"K250427","page_num":5,"bbox":[111.46,393.24,529.54,555.62],"n_rows":7,"n_cols":2,"columns":["Trade Name:","TAIMedImg DeepMets"],"rows":[["Trade Name:","TAIMedImg DeepMets"],["Common Name:","DeepMets"],["Classification Name","Radiological Image Processing Software for Radiation Therapy"],["Regulation Description","Medical Image Management and Processing System"],["Product Code","QKB, QIH"],["Regulation Number","21 CFR 892.2050"],["Device Class","Class II"]],"caption_candidate":"2 Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p5-t2","doc_id":"K250427","page_num":5,"bbox":[111.46,597.12,529.54,689.81],"n_rows":4,"n_cols":2,"columns":["Device Name:","VBrain"],"rows":[["Device Name:","VBrain"],["510(k) Number:","K203235"],["Manufacturer:","Vysioneer Inc."],["Product Code:","QKB"]],"caption_candidate":"3 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p8-t0","doc_id":"K250427","page_num":8,"bbox":[90.5,72.48,515.86,745.66],"n_rows":3,"n_cols":3,"columns":["","contour images and offers automated\nsegmentation for Gross Tumor\nVolume (GTV) contours of brain\nmetastases. The software is an\nadjunctive tool and not intended for\nreplacing the users’ current standard\npractice of manual contouring\nprocess. All automatic output\ngenerated by the software shall be\nthoroughly reviewed by a trained\nmedical professional prior to\ndelivering any therapy or treatment.\nThe physician retains the ultimate\nresponsibility for making the final\ndiagnosis and treatment decision.\nTAIMedImg DeepMets is intended\nto be used by medical professionals\ntrained in the use of the device.\nOnly DICOM images of adult\npatients are considered valid input.\nDeepMets does not support DICOM\nimages of patients that have one of\nthe following exclusions:\n(i) presence of prior craniotomy, (ii)\npatients with clinical imaging\ndiagnosis of brain tumors other than\nBM, (iii) Images with patient motion:\nexcessive motion leading to artifacts\nthat make the scan technically\ninadequate.\nMedical professionals must finalize\n(confirm or modify) the contours\ngenerated by TAIMedImg\nDeepMets, as necessary, using an\nexternal platform available at the\nfacility that supports DICOM-RT\nviewing/editing functions, such as\nimage visualization software and\ntreatment planning system.","diagnosis. VBrain is intended only\nfor generating Gross Tumor Volume\n(GTV) contours of brain metastases,\nmeningiomas, and acoustic neuromas\non axial T1 contrast-enhanced MRI\nimages; It is not intended to be used\nwith images of other brain tumors.\nThe user must know the tumor type\nwhen they use VBrain. VBrain is\nintended to be used on adult patients\nonly.\nMedical professionals must finalize\n(confirm or modify) the contours\ngenerated by VBrain, as necessary,\nusing an external platform available\nat the facility that supports DICOM-\nRT viewing/editing functions, such\nas image visualization software and\ntreatment planning system."],"rows":[["","contour images and offers automated\nsegmentation for Gross Tumor\nVolume (GTV) contours of brain\nmetastases. The software is an\nadjunctive tool and not intended for\nreplacing the users’ current standard\npractice of manual contouring\nprocess. All automatic output\ngenerated by the software shall be\nthoroughly reviewed by a trained\nmedical professional prior to\ndelivering any therapy or treatment.\nThe physician retains the ultimate\nresponsibility for making the final\ndiagnosis and treatment decision.\nTAIMedImg DeepMets is intended\nto be used by medical professionals\ntrained in the use of the device.\nOnly DICOM images of adult\npatients are considered valid input.\nDeepMets does not support DICOM\nimages of patients that have one of\nthe following exclusions:\n(i) presence of prior craniotomy, (ii)\npatients with clinical imaging\ndiagnosis of brain tumors other than\nBM, (iii) Images with patient motion:\nexcessive motion leading to artifacts\nthat make the scan technically\ninadequate.\nMedical professionals must finalize\n(confirm or modify) the contours\ngenerated by TAIMedImg\nDeepMets, as necessary, using an\nexternal platform available at the\nfacility that supports DICOM-RT\nviewing/editing functions, such as\nimage visualization software and\ntreatment planning system.","diagnosis. VBrain is intended only\nfor generating Gross Tumor Volume\n(GTV) contours of brain metastases,\nmeningiomas, and acoustic neuromas\non axial T1 contrast-enhanced MRI\nimages; It is not intended to be used\nwith images of other brain tumors.\nThe user must know the tumor type\nwhen they use VBrain. VBrain is\nintended to be used on adult patients\nonly.\nMedical professionals must finalize\n(confirm or modify) the contours\ngenerated by VBrain, as necessary,\nusing an external platform available\nat the facility that supports DICOM-\nRT viewing/editing functions, such\nas image visualization software and\ntreatment planning system."],["Operating\nSystem","Linux","Linux"],["User\nPopulation","The software is only used by trained\nmedical professionals.","Trained medical professionals\nincluding, but not limited to,\nradiologists, oncologists, physicians,"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p9-t0","doc_id":"K250427","page_num":9,"bbox":[90.5,72.48,515.86,709.78],"n_rows":9,"n_cols":3,"columns":["","","medical technologists, dosimetrists,\nand physicists."],"rows":[["","","medical technologists, dosimetrists,\nand physicists."],["Patient\nPopulation","Adult patients with known primary\ncancer (outside brain) and brain\nmetastasis scheduled for radiation\ntherapy.","Adult patients with known\n(diagnosed) brain metastases,\nmeningiomas, or acoustic neuromas\nscheduled for radiation therapy."],["Anatomical\nSite","Brain","Brain"],["Supported\nModalities","Axial T1-weighted contrast-\nenhanced (T1WI+C) brain magnetic\nresonance (MR) images","Axial T1 contrast-enhanced MRI\nimages"],["Localization\nand Definition\nof Objects","Known (imaging diagnosed) brain\nmetastases with a diameter of ≥ 10\nmm","Qualified brain tumors - brain\nmetastases, meningiomas, and\nacoustic neuromas"],["Performance\nTesting","A performance evaluation of\nTAIMedImg DeepMets for brain\nmetastasis segmentation is\nproceeded, the clinical testing dataset\ncomprised 158 cases from 16 MRI\nscan sources in US. Five metrics are\ncalculated and evaluated: (1) lesion-\nwise sensitivity, (2) false positive\nrate, (3) Dice Similarity Coefficient,\n(4) Hausdorff distance and (5)\ncentroid distance between DeepMets’\nsegmentation and clinicians’\nsegmentation.","VBrain AI software for brain tumor\ncontouring (segmentation)\nperformance test data sets consisted\nof 116 cases acquired from 4\ndifferent institutions (3 US and 1\nnon-US). Five metrics are evaluated:\n(1) lesion-wise sensitivity, (2) false-\npositive rate, (3) lesion-wise Dice\ncoefficient, (4) average Hausdorff\ndistance, and (5) average centroid\ndistance between VBrain’s\nsegmentation and clinicians’\nsegmentation."],["Segmentation\n(Contouring)\nTechnology","Deep learning","Deep learning"],["Design: Data\nVisualization/\nGraphical\nUser Interface","No","No"],["Design:\nManual\nediting feature","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p10-t0","doc_id":"K250427","page_num":10,"bbox":[90.5,72.48,515.86,152.78],"n_rows":2,"n_cols":3,"columns":["Alteration of\nOriginal\nImages","No","No"],"rows":[["Alteration of\nOriginal\nImages","No","No"],["Data Export","DICOM-RT","DICOM-RT"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250427-p11-t0","doc_id":"K250427","page_num":11,"bbox":[103.85,410.17,504.8,634.06],"n_rows":6,"n_cols":5,"columns":["Metric","Mean","95%CI","Acceptance\nCriteria","Source"],"rows":[["Metric","Mean","95%CI","Acceptance\nCriteria","Source"],["Lesion-Wise Sensitivity\n(Se) (%)","89.97","(86.51, 93.43)","> 80","Deep\nlearning"],["False-Positive Rate (FPR)\n(FPs/case)","0.354","(0.215, 0.481)","< 0.5","Deep\nlearning"],["Dice Similarity Coefficient\n(DSC)","0.70","(0.67, 0.72)","≥ 0.65","Estimated"],["Hausdorff Distance (HD)\n(mm)","6.66","(5.86, 7.41)","≤ 8.0","Estimated"],["Centroid Distance (CD)\n(mm)","1.75","(1.33, 2.11)","≤ 2.0","Estimated"]],"caption_candidate":"Table B: Summary of DeepMets performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p6-t0","doc_id":"K250436","page_num":6,"bbox":[70.86,73.26,432.82,764.04],"n_rows":48,"n_cols":5,"columns":["Classification:","II","","",""],"rows":[["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["4. Legally Marketed Pred","icate and Ref","erence Device","",""],["4.1. Predicate Device","","","",""],["","","","",""],["Trade name:","MAGNETOM","Sola","",""],["510(k) Number:","K232535","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["4.2. Reference Device","","","",""],["Trade name:","MAGNETOM","Cima.X","",""],["510(k) Number:","K231587","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","MAGNETOM","Free.Max","",""],["510(k) Number:","K231617","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: M","OS","",""],["","","","",""],["Trade name:","MAGNETOM","Amira","",""],["510(k) Number:","K223343","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","syngo.via VB4","0A","",""],["510(k) Number:","K191040","","",""],["Classification Name:","Picture Archi","ving and Communic","ations","System"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR §892",".2050","",""]],"caption_candidate":"Classification: II","well_formed":true,"extraction_settings":"text"}
{"table_id":"K250436-p8-t0","doc_id":"K250436","page_num":8,"bbox":[72.48,121.02,516.3,445.84],"n_rows":5,"n_cols":3,"columns":["Hardware","New Hardware","- New Magnet\n- New Gradient Coil\n- New RF System\n- New Local Coils\n- New Patient Tables\n- New Computer Systems"],"rows":[["Hardware","New Hardware","- New Magnet\n- New Gradient Coil\n- New RF System\n- New Local Coils\n- New Patient Tables\n- New Computer Systems"],["","",""],["Software","New Features\nand\nApplications","- AutoMate Cardiac\n- Quick Protocols\n- BLADE with SMS acceleration for non-diffusion\nimaging\n- Deep Resolve Swift Brain\n- Fast GRE Reference Scan\n- Ghost reduction\n- Fleet Reference Scan\n- SMS Averaging\n- Select&GO extension\n- myExam Spine Autopilot\n- New Startup-Timer"],["","",""],["","Modified\nFeatures and\nApplications","- Improvements for Pulse Sequence Type SPACE\n- Improved Gradient ECO Mode Settings\n- Inline Image Filter switchable for users"]],"caption_candidate":"to the predicate device MAGNETOM Sola with software syngo MR XA61A (K232535):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p9-t0","doc_id":"K250436","page_num":9,"bbox":[72.7,139.62,502.8,392.06],"n_rows":11,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Sola with\nsyngo MR XA61A","K232535, cleared on\nDecember 22, 2023","LNH,\nLNI,\nMOS","Siemens Healthcare\nGmbH"],["","FDA Clearance Number","Product",""],["Reference Device","","","Manufacturer"],["","and Date","Code",""],["","","",""],["MAGNETOM Cima.X with\nsyngo MR XA61A","K231587, cleared on\nDecember 18, 2023","LNH,\nLNI,\nMOS","Siemens Healthcare\nGmbH"],["MAGNETOM Free.Max\nwith syngo MR XA60A","K231617, cleared on\nNovember 09, 2023","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["MAGNETOM Amira with\nsyngo MR XA50M","K223343, cleared on\nMarch 28, 2023","LNH,\nLNI,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["syngo.via VB40A","K191040, cleared on May\n16, 2019","LLZ","Siemens Healthcare\nGmbH"]],"caption_candidate":"following reference devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p9-t1","doc_id":"K250436","page_num":9,"bbox":[72.7,656.42,502.8,730.62],"n_rows":5,"n_cols":3,"columns":["","Tested Hardware or",""],"rows":[["","Tested Hardware or",""],["Performance Test","","Source/Rationale for test"],["","Software",""],["","",""],["Sample clinical images","Coils, new and modified\nsoftware features, pulse\nsequence types","Guidance for Submission of\nPremarket Notifications for"]],"caption_candidate":"The following performance testing was conducted on the subject devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p10-t0","doc_id":"K250436","page_num":10,"bbox":[72.48,401.54,505.08,770.7],"n_rows":3,"n_cols":4,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:","Deep Resolve Swift Brain:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:","Deep Resolve Swift Brain:"],["Training and\nValidation\ndata","• TSE: more than\n25,000 slices\n• HASTE: pre-trained\non the TSE dataset\nand refined with\nmore than 10,000\nHASTE slices\n• EPI Diffusion: more\nthan 1,000,000\nslices\nThe data covered a\nbroad range of body\nparts, contrasts, fat\nsuppression\ntechniques,\norientations, and field\nstrength.","on more than 10,000\nhigh resolution 2D\nimages.\nThe data covered a\nbroad range of body\nparts, contrasts, fat\nsuppression techniques,\norientations, and field\nstrength.","29,740 2D slices:\n• Training: 20,076 slices\n• 1.5T Validation: 3,616 slices;\n3T Validation: 6,048 slices"],["Test Statistics\nand Test\nResults\nSummary","The impact of the\nnetwork has been\ncharacterized by\nseveral quality metrics\nsuch as peak signal-to-\nnoise ratio (PSNR) and\nstructural similarity\nindex (SSIM). Most","The impact of the\nnetwork has been\ncharacterized by several\nquality metrics such as\npeak signal-to-noise\nratio (PSNR), structural\nsimilarity index (SSIM),\nand perceptual loss. In","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR),\nstructural similarity index (SSIM)\nand normalized mean squared\nerror (NMSE). Additionally,\nimages were inspected visually"]],"caption_candidate":"features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p11-t0","doc_id":"K250436","page_num":11,"bbox":[72.48,71.1,506.73,580.0],"n_rows":5,"n_cols":4,"columns":["","importantly, the\nperformance was\nevaluated by visual\ncomparisons to\nevaluate e.g., aliasing\nartifacts, image\nsharpness and\ndenoising levels.","addition, the feature\nhas been verified and\nvalidated by inhouse\ntests. These tests\ninclude visual rating and\nan evaluation of image\nsharpness by intensity\nprofile comparisons of\nreconstructions with\nand without Deep\nResolve Sharp.","to ensure that potential artefacts\nare detected that are not well\ncaptured by the metrics listed\nabove.\nAfter successful passing of the\nquality metrics tests, work-in-\nprogress packages of the\nnetwork were delivered and\nevaluated in clinical settings with\ncollaboration partners."],"rows":[["","importantly, the\nperformance was\nevaluated by visual\ncomparisons to\nevaluate e.g., aliasing\nartifacts, image\nsharpness and\ndenoising levels.","addition, the feature\nhas been verified and\nvalidated by inhouse\ntests. These tests\ninclude visual rating and\nan evaluation of image\nsharpness by intensity\nprofile comparisons of\nreconstructions with\nand without Deep\nResolve Sharp.","to ensure that potential artefacts\nare detected that are not well\ncaptured by the metrics listed\nabove.\nAfter successful passing of the\nquality metrics tests, work-in-\nprogress packages of the\nnetwork were delivered and\nevaluated in clinical settings with\ncollaboration partners."],["Equipment","1.5T and 3T MRI systems","",""],["Clinical\nSubgroups","No clinical subgroups have been defined for the collected dataset.","",""],["Demographic\nDistribution","Due to reasons of data privacy, we did not record gender, age and ethnicity during\ndata collection.","",""],["Reference\nStandard","The acquired datasets\n(as described above)\nrepresent the ground\ntruth for the training\nand validation. Input\ndata was\nretrospectively created\nfrom the ground truth\nby data manipulation\nand augmentation.\nThis process includes\nfurther under-sampling\nof the data by\ndiscarding k-space\nlines, lowering of the\nSNR level by addition\nRestricted of noise and\nmirroring of k-space\ndata.","The acquired datasets\nrepresent the ground\ntruth for the training\nand validation. Input\ndata was\nretrospectively created\nfrom the ground truth\nby data manipulation. k-\nspace data has been\ncropped such that only\nthe center part of the\ndata was used as input.\nWith this method\ncorresponding low-\nresolution\ndata as input and high-\nresolution data as\noutput / ground truth\nwere created for\ntraining and validation.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation and augmentation.\nThis process includes further\nunder-sampling of the data by\ndiscarding k-space lines, lowering\nof the SNR level by addition of\nGaussian noise to k-space data\nand uniformly-random cropping\nof the training data along the\nreadout direction."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p12-t0","doc_id":"K250436","page_num":12,"bbox":[72.48,71.15,508.68,745.68],"n_rows":4,"n_cols":2,"columns":["Deep Resolve\nSwift Brain","[1] Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: Sensitivity\nencoding for fast MRI. Magn Reson Med. 1999;42:952-962.\n[2] Demir et al., Optimization of Magnetization Transfer Contrast for EPI FLAIR Brain\nImaging, Magn Reson Med. 2022;87:2380-2387. DOI: 10.1002/mrm.29141\n[3] Yu S, Park B, Jeong J. Deep iterative down-up CNN for image denoising. In: Proc.\nIEEE Conf. Comput. Vis. Pattern Recognit.; 2019:9.\n[4] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D. Σ-net:\nSystematic evaluation of iterative deep neural networks for fast parallel MR image\nreconstruction. ArXiv191209278 Cs Eess. December 2019.\nhttp://arxiv.org/abs/1912.09278. Accessed January 9, 2020.\n[5] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D. Systematic\nevaluation of iterative deep neural networks for fast parallel MRI reconstruction\nwith sensitivity‐weighted coil combination. Magn. Reson. Med. 2021;86(4):1859-\n1872. doi:10.1002/mrm.28827\n[6] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: From error\nvisibility to structural similarity. IEEE Trans Image Process. 2004;13(4):600-612.\ndoi:10.1109/TIP.2003.819861\n[7] Clifford et al., An artificial intelligence-accelerated 2-minute multi-shot echo\nplanar imaging protocol for comprehensive high-quality clinical brain imaging,\nMagn Reson Med. 2022;87:2453–2463, DOI: 10.1002/mrm.29117\n[8] Zbontar J, Knoll F, Sriram A, et al. fastMRI: An open dataset and benchmarks for\naccelerated MRI. arXiv:181108839 [physics, stat]. December 2019.\nhttp://arxiv.org/abs/1811.08839. Accessed March 5, 2020.\n[9] Altmann et al., Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and\nMulti-shot EPI, Acad Radiol, Volume 30, Issue 12, P2988-2998, December 2023,\nDOI: https://doi.org/10.1016/j.acra.2023.04.019\n[10] Altmann et al., Ultrafast Brain MRI with Deep Learning Reconstruction for\nSuspected Acute Ischemic Stroke, Radiology 2024; 310(2):e231938,\nhttps://doi.org/10.1148/radiol.231938"],"rows":[["Deep Resolve\nSwift Brain","[1] Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: Sensitivity\nencoding for fast MRI. Magn Reson Med. 1999;42:952-962.\n[2] Demir et al., Optimization of Magnetization Transfer Contrast for EPI FLAIR Brain\nImaging, Magn Reson Med. 2022;87:2380-2387. DOI: 10.1002/mrm.29141\n[3] Yu S, Park B, Jeong J. Deep iterative down-up CNN for image denoising. In: Proc.\nIEEE Conf. Comput. Vis. Pattern Recognit.; 2019:9.\n[4] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D. Σ-net:\nSystematic evaluation of iterative deep neural networks for fast parallel MR image\nreconstruction. ArXiv191209278 Cs Eess. December 2019.\nhttp://arxiv.org/abs/1912.09278. Accessed January 9, 2020.\n[5] Hammernik K, Schlemper J, Qin C, Duan J, Summers RM, Rueckert D. Systematic\nevaluation of iterative deep neural networks for fast parallel MRI reconstruction\nwith sensitivity‐weighted coil combination. Magn. Reson. Med. 2021;86(4):1859-\n1872. doi:10.1002/mrm.28827\n[6] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: From error\nvisibility to structural similarity. IEEE Trans Image Process. 2004;13(4):600-612.\ndoi:10.1109/TIP.2003.819861\n[7] Clifford et al., An artificial intelligence-accelerated 2-minute multi-shot echo\nplanar imaging protocol for comprehensive high-quality clinical brain imaging,\nMagn Reson Med. 2022;87:2453–2463, DOI: 10.1002/mrm.29117\n[8] Zbontar J, Knoll F, Sriram A, et al. fastMRI: An open dataset and benchmarks for\naccelerated MRI. arXiv:181108839 [physics, stat]. December 2019.\nhttp://arxiv.org/abs/1811.08839. Accessed March 5, 2020.\n[9] Altmann et al., Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and\nMulti-shot EPI, Acad Radiol, Volume 30, Issue 12, P2988-2998, December 2023,\nDOI: https://doi.org/10.1016/j.acra.2023.04.019\n[10] Altmann et al., Ultrafast Brain MRI with Deep Learning Reconstruction for\nSuspected Acute Ischemic Stroke, Radiology 2024; 310(2):e231938,\nhttps://doi.org/10.1148/radiol.231938"],["","[11] Xie Y, Yang Q, Xie G, Pang J, Fan Z, Li D: Improved black-blood imaging using\nDANTE-SPACE for simultaneous carotid and intracranial vessel wall evaluation,\nMagn Reson Med, 2016 Jun, 75(6):2286-94. doi: 10.1002/mrm.25785. Epub 2015\nJul 8. PMID: 26152900; PMCID: PMC4706507\n[12] Li L, Miller KL, Jezzard P: DANTE-prepared pulse trains: a novel approach to\nmotion-sensitized and motion-suppressed quantitative magnetic resonance\nimaging, Magn Reson Med, 2012 Nov, 68(5):1423-38. doi: 10.1002/mrm.24142.\nEpub 2012 Jan 13. PMID: 22246917\n[13] Tagawa H, Fushimi Y, Funaki T, Nakajima S, Sakata A, Okuchi S, Hinoda T, Grinstead\nJ, Ahn S, Hidaka Y, Yoshida K, Miyamoto S, Nakamoto Y: Vessel wall MRI in\nmoyamoya disease: arterial wall enhancement varies depending on age, arteries,\nand disease progression, Eur Radiol, 2023 Oct 5, doi: 10.1007/s00330-023-10251-\n9. Epub ahead of print. PMID: 37798407"],["SPACE\nImprovement","[14] Wang X, Greer JS, Dimitrov IE, Pezeshk P, Chhabra A, Madhuranthakam AJ:\nFrequency Offset Corrected Inversion Pulse for B0 and B1 Insensitive Fat\nSuppression at 3T: Application to MR Neurography of Brachial Plexus, J Magn\nReson Imaging, 2018 Oct 48(4):1104-1111. doi: 10.1002/jmri.26021. Epub 2018\nSep 15. PMID: 30218576"],["","[15] Mugler JP 3rd: Optimized three-dimensional fast-spin-echo MRI, J Magn Reson\nImaging, 2014 Apr 39(4):745-67. doi: 10.1002/jmri.24542. Epub 2014 Jan 8. PMID:\n24399498."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p14-t0","doc_id":"K250436","page_num":14,"bbox":[77.8,71.2,515.06,775.2],"n_rows":13,"n_cols":5,"columns":["","","","Reference","Standards"],"rows":[["","","","Reference","Standards"],["Recognition","","","",""],["","Product Area","Title of Standard","Number and","Development"],["Number","","","",""],["","","","date","Organization"],["","","","",""],["19-46","General II\n(ES/EMC)","Medical electrical\nequipment - part 1:\ngeneral requirements\nfor basic safety and\nessential performance","ES60601-1:2005\n/(R)2012 &\nA1:2012,\nC1:2009/(R)2012\n&A2:2010/(R)2012\n(Cons. Text)\n[Incl.AMD2:2021]","ANSI AAMI"],["19-36","General","Medical electrical\nequipment - Part 1-2:\nGeneral requirements\nfor basic safety and\nessential performance -\nCollateral Standard:\nElectromagnetic\ndisturbances -\nRequirements and tests","60601-1-2\nEdition 4.1:2020-\n09","IEC"],["12-295","Radiology","Medical electrical\nequipment - Part 2-33:\nParticular requirements\nfor the basic safety and\nessential performance\nof magnetic resonance\nequipment for medical\ndiagnosis","60601-2-33 Ed.\n3.2 b:2015","IEC"],["5-125","General","Medical devices -\nApplication of risk\nmanagement to medical\ndevices","14971 Third\nEdition 2019-12","ISO"],["5-129","General I (QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical\ndevices","62366-1: 2015 +\nAMD1:2020","ANSI AAMI IEC"],["13-79","Software/\nInformatics","Medical device software\n- Software life cycle\nprocesses","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","IEC"],["12-232","Radiology","Acoustic Noise\nMeasurement\nProcedure for\nDiagnosing Magnetic","MS 4-2010","NEMA"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250436-p15-t0","doc_id":"K250436","page_num":15,"bbox":[77.64,71.1,515.28,342.68],"n_rows":4,"n_cols":5,"columns":["","","Resonance Imaging\nDevices","",""],"rows":[["","","Resonance Imaging\nDevices","",""],["12-288","Radiology","Standards Publication\nCharacterization of\nPhased Array Coils for\nDiagnostic Magnetic\nResonance Images","MS 9-2008\n(R2020)","NEMA"],["12-352","Radiology","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set","PS 3.1 - 3.20\n2023e","NEMA"],["2-258","Biocompatibility","Biological evaluation of\nmedical devices - part 1:\nevaluation and testing\nwithin a risk\nmanagement process.\n(Biocompatibility)","10993-1 Fifth\nedition 2018-08","ISO"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p5-t0","doc_id":"K250440","page_num":5,"bbox":[69.24,153.96,522.84,410.88],"n_rows":14,"n_cols":3,"columns":["General Information","",""],"rows":[["General Information","",""],["Manufacturer","Brainlab AG; Olof-Palme Str.9; 81829, Munich, Germany",""],["Establishment Registration","8043933",""],["Trade Name","RT Elements 4.5",""],["Classification Name","System, planning, radiation therapy treatment",""],["Product Code","MUJ; QIH",""],["Regulation Number","892.5050",""],["Regulatory Class","II",""],["Panel","Radiology",""],["Predicate Device","RT Elements (4.0); K223279",""],["Reference Device","Contouring 5.0 (part of Brainlab Elements 7.0 – K243633)",""],["Contact Information","",""],["Primary Contact","","Alternate Contact"],["Sadwini Suresh\nQM Consultant\nPhone: +49 89 99 15 68 0\nEmail: regulatory.affairs@brainlab.com","","Chiara Cunico\nSenior Manager Regulatory Affairs\nPhone: +49 89 99 15 68 0\nEmail: chiara.cunico@brainlab.com"]],"caption_candidate":"June 17, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p6-t0","doc_id":"K250440","page_num":6,"bbox":[79.33,102.69,532.67,571.8],"n_rows":10,"n_cols":5,"columns":["","Software","","Description",""],"rows":[["","Software","","Description",""],["Multiple Brain Mets SRS\n4.5","","","Multiple Brain Mets SRS provides optimized planning and display for\ncranial multi-metastases radiation treatment planning.",""],["Cranial SRS 4.5","","","Cranial SRS provides optimized planning and display for cranial\nradiation treatment planning.",""],["Spine SRS 4.5","","","Spine SRS provides optimized planning and display for spine\nmetastases.",""],["Cranial SRS w/ Cones 4.5","","","Cranial SRS w/ Cones provides planning and display for functional\ndiseases (e.g. trigeminal neuralgia) or cranial lesion radiation\ntreatment.",""],["RT Contouring 4.5","","","RT Contouring contains features to outline, refine, combine and\nmanipulate structures in patient image data for planning of cranial\nand extracranial radiotherapy treatments. The Cranial Tumor\nSegmentation feature uses AI/Ml. The algorithm was trained on MRI\nimage data with contrast-enhancing tumors from multiple clinical\nsites, including a wide variety of scanner models and patient\ncharacteristics.",""],["RT QA 4.5","","","RT QA contains features for patient specific quality assurance. Use\nRT QA to recalculate patient treatment plans on a phantom to verify\nthat the patient treatment plan fulfills the planning requirements.",""],["Dose Review 4.5","","","Dose Review contains features for review of isodose lines, review of\nDVHs, dose comparison and dose summation.",""],["Brain Mets Retreatment\nReview 4.5","","","Retreatment Review allows the preparation and analysis of the next\ntreatment by providing a 3D visualization of all previously treated and\nnew metastases and review options for the summed dose of previous\ntreatment plans.",""],["Physics Administration\n7.5","","","The Physics Administration is a tool that allows to administer\nmeasured beam data and machine profiles for RT Elements software.\nThe Software can be used to define and edit Hounsfield to electron\ndensity conversion tables.",""]],"caption_candidate":"The device consists of the following software modules:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p7-t0","doc_id":"K250440","page_num":7,"bbox":[72.31,74.2,539.69,698.49],"n_rows":4,"n_cols":3,"columns":["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],"rows":[["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],["Indications For Use","The device is intended for\nradiation treatment planning for\nuse in stereotactic, conformal,\ncomputer planned, Linac based\nradiation treatment and indicated\nfor cranial, head and neck and\nextracranial lesions.","The device is intended for radiation\ntreatment planning for use in\nstereotactic, conformal, computer\nplanned, Linac based radiation\ntreatment and indicated for cranial,\nhead and neck and extracranial lesions."],["Applications/Elements\nincluded","• Multiple Brain Mets SRS\n• Cranial SRS\n• Spine SRS\n• Cranial SRS w/ Cones\n• RT QA – Recalculation\n• RT QA – Patient Specific\nQA\n• RT QA – Beam Model\nVerification\n• Dose Review\n• Brain Mets Retreatment\nReview\n• Physics Administration\n• Phantom Definition\n• Tissue Model","• Multiple Brain Mets SRS\n• Cranial SRS\n• Spine SRS\n• Cranial SRS w/ Cones\n• RT QA – Recalculation\n• RT QA – Patient Specific QA\n• RT QA – Beam Model\nVerification\n• Dose Review\n• Brain Mets Retreatment Review\n• Physics Administration\n• Phantom Definition\n• Tissue Model\n• SmartBrush (RT; RT Spine;\nAngio)\n• Object Management"],["Operating Principle","The device is composed by\nsoftware only and can be\ncontrolled via mouse and\nkeyboard. The software is\ndisplayed on a computer screen.\nThe input of the Brainlab RT\nElements are co-registered\nDICOM image sets with\nsegmented objects.\nThe output is a DICOM RT dose\nplan for further processing and\nfinally to control the radiation\ndelivery to a patient using a linear\naccelerator.","The device is composed by software\nonly and can be controlled via mouse\nand keyboard. The software is\ndisplayed on a computer screen.\nBased on co-registered DICOM image\nsets, the software can create 3D\nstructures or objects which are further\nused for the creation of RT dose plans.\nThe output is a DICOM RT dose plan for\nfurther processing and finally to control\nthe radiation delivery to a patient using\na linear accelerator."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p8-t0","doc_id":"K250440","page_num":8,"bbox":[72.31,74.2,539.69,642.69],"n_rows":6,"n_cols":7,"columns":["Topic/ Feature","","Predicate Device","","","Subject Device",""],"rows":[["Topic/ Feature","","Predicate Device","","","Subject Device",""],["","","(RT Elements 4.0 - K223279)","","","(RT Elements 4.5)",""],["Display Resolution","• 1920 x 1200 (WUXGA)\n• 2560 x 1440 (WQHD)\n• 3840 x 2048 (4K)","","","• 1920 x 1080 (FHD)\n• 1920 x 1200 (WUXGA)\n• 2560 x 1440 (WQHD)\n• 3840 x 2048 (4K)","",""],["Supported Operating\nSystems","• Windows 10 1507\n• Windows 10 1607\n• Windows 10 1809\n• Windows 10 21H2\n• Windows Server 2012 R2\n64-bit\n• Windows Server 2016\n• Windows Server 2019\n• Windows Server 2022","","","• Windows 10 1607\n• Windows 10 1809\n• Windows 10 v 21H2\n• Windows Server 2016\n• Windows Server 2019\n• Windows Server 2022","",""],["Data Input","• DICOM Images\n• DICOM Segmentation\n• DICOM Registration\n• DICOM Key Object\nSelection Document\n• DICOM Raw (Brainlab\nLoad/Save)\n• DICOM RT Dose\n• DICOM RT Structure Set\n• Machine Profiles\n• HuToEd-Tables","","","• DICOM Images\n• DICOM Segmentation\n• DICOM Registration\n• DICOM Key Object Selection\nDocument\n• DICOM Raw (Brainlab\nLoad/Save)\n• DICOM RT Dose\n• DICOM RT Structure Set\n• Machine Profiles\n• HuToEd-Tables","",""],["Intended User Profile","The intended users are medical\nprofessionals who perform\nradiation treatment planning\n(medical physicists, radiation\noncologists, dosimetrists,\nphysicians, etc.).","","","The intended users are medical\nprofessionals who perform radiation\ntreatment planning (medical physicists,\nradiation oncologists, dosimetrists,\nphysicians, etc.).","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p9-t0","doc_id":"K250440","page_num":9,"bbox":[72.31,74.2,539.69,481.41],"n_rows":7,"n_cols":5,"columns":["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","","","Subject Device\n(RT Elements 4.5)"],"rows":[["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","","","Subject Device\n(RT Elements 4.5)"],["Data Output","• DICOM Images\n• DICOM RT Struct\n• DICOM RT Plan\n• DICOM Key Object\nSelection Document\n• DICOM RT Dose\n• DICOM Raw (Brainlab\nLoad/Save)\n• DICOM Segmentation\n• DICOM Registrations\n• PDF Report\n• ASCII Dose Export","","","• DICOM Images\n• DICOM RT Struct\n• DICOM RT Plan\n• DICOM Key Object Selection\nDocument\n• DICOM RT Dose\n• DICOM Raw (Brainlab\nLoad/Save)\n• DICOM Segmentations\n• DICOM Registrations\n• PDF Report\n• ASCII Dose Export\n• csv files"],["Supported Collimators","• Multileaf Collimators\n• Circular Conical\nCollimators","","","• Multileaf Collimators\n• Circular Conical Collimators"],["GUI Technology","","• HTML5 (only RT","","• HTML5\n• WPF (only Physics\nAdministration)"],["","","Preparation & RT","",""],["","","Analysis)","",""],["","","• WPF","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p10-t0","doc_id":"K250440","page_num":10,"bbox":[72.31,74.2,539.69,634.76],"n_rows":3,"n_cols":3,"columns":["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],"rows":[["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],["Supported Image\nModalities","• CT\n• MRI\n• PET","• CT\n• MRI\n• PET\nFurthermore, it is possible to load the\noutput of the Contrast Clearance\nElement which is labeled as OT (other)\nImage set.\nBackground: The Contrast Clearance\nAnalysis calculation compares two 3D\nMRI data sets with injected contrast\nagents that were taken 60 to 105\nminutes apart (early and late scans).\nWhen comparing the two 3D MRI data\nsets, Contrast Clearance Analysis\nperforms a voxel-by-voxel subtraction\nof the early MR images from the late\nMR images resulting in a high-\nresolution color-coded Treatment\nResponse Assessment Map (TRAM).\nThis map provides effective separation\nbetween regions of contrast\naccumulation (positive value in red),\nand regions of contrast clearance\n(negative values in blue). Red regions\nshow contrast accumulation , i.e. non-\ntumor regions and predominantly vessel\nnecrosis. Dark blue regions show\nefficient contrast clearance, i.e.\npredominantly morphologically active\ntumor regions."],["Dose Calculation\nAlgorithm","• Pencil Beam Algorithm\n• Monte Carlo Algorithm\n• Circular Cone Algorithm","• Pencil Beam (PB) Algorithm\n• Monte Carlo (MC) Algorithm\n• Circular Cone Algorithm"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p11-t0","doc_id":"K250440","page_num":11,"bbox":[72.31,74.2,539.69,678.12],"n_rows":4,"n_cols":3,"columns":["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],"rows":[["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],["Performance\nCharacteristics","Pencil Beam/Monte Carlo:\nbetter than 3%\nCircular Cone:\n1%/1mm","Pencil Beam/Monte Carlo:\nbetter than 3%\nCircular Cone:\n1%/1mm"],["Object Changes","In the planning applications it is\npossible to add and remove\nreview objects to/from a\ntreatment plan.\nIn general object property\nchanges are not possible during\ntreatment planning.","Review objects can be added/removed\nin all planning applications as well as\nDose Planning.\nPTV (Planning Target Volume) , OAR\n(Organ At Risk) and other objects’\nproperties can be changed for\ntreatment plans (e.g., name, color and\ncomment). The optimization result\nremains valid after the change."],["Separation of\noptimization and final\ndose calculation","The final dose calculation was\nautomatically performed at the\nend of the optimization.","The user can trigger the final dose\ncalculation separately from the plan\noptimization (VMAT (Volumetric\nModulated Arc Therapy)):\n→ Possible to optimize a plan using\nPB or MC first and then trigger\nfinal dose calculation using fine\nMC parameters\n→ MC coarse and MC fine dose is\ncached of the current state and\nthe MC dose of the last\noptimization result to enable the\nuser to easily revert to the last\nplan state\n→ The fine and coarse MC\nparameters visualized in the\ndropdown can be defined in the\nClinical Protocol. The spatial\nresolution and grid size used\nduring a MC based optimization\ncan only be changed in the\nClinical Protocol"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p12-t0","doc_id":"K250440","page_num":12,"bbox":[72.31,74.2,539.69,604.77],"n_rows":3,"n_cols":3,"columns":["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],"rows":[["Topic/ Feature","Predicate Device\n(RT Elements 4.0 - K223279)","Subject Device\n(RT Elements 4.5)"],["Interface to Art-Plan\n(by TheraPanacea) for\nextracranial workflows","Not part of the Predicate Device.","For the following extracranial workflows\nan interface to the cloud based 3rd party\ncontouring system “Art-Plan” by\nTheraPanacea (TPC) was introduced.\nArt-Plan provides an auto-segmentation\nof extracranial structures which are\nloaded into Object Management.\nTherefore, Art-Plan Connect (part of\nArt-Plan) is installed on the same HW as\nthe RT Elements and works as a\ncommunication gateway between the\nmain Art Plan cloud service and the RT\nElements."],["APM (Anatomical\nPatient Model)","Not part of the Predicate Device.","Component of the RT Elements with a\ngRPC API, which serves as an\nalgorithmic backend for medical image\ndata processing. The API can readily be\nused by client applications to have\naccess to functionalities for automatic\nprocessing of 2D and 3D medical image\ndata (e.g. segmentations, landmarks).\nTo provide its functionality the APM\nservice also includes interfaces to other\ncomponents of the Universal Patient\nModel device like\nUniversalAtlasPerformer and\nUATransferPerformer. Additional\nfunctionality is also implemented\ndirectly in the APM service (like cranial\ntumor segmentations).\nThe component is used by RT\nContouring."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p15-t0","doc_id":"K250440","page_num":15,"bbox":[75.77,568.18,536.13,681.24],"n_rows":5,"n_cols":13,"columns":["Diagnostic\nCharacteristics","Mean\nDice","","95%","","Mean\nPrecision","","95%","","Mean\nRecall","","95%",""],"rows":[["Diagnostic\nCharacteristics","Mean\nDice","","95%","","Mean\nPrecision","","95%","","Mean\nRecall","","95%",""],["","","","Confidence","","","","Confidence","","","","Confidence",""],["","","","Interval","","","","Interval","","","","Interval",""],["All","0.75","[0.74;\n0.76]","","","0.86","[0.85;\n0.88]","","","0.85","[0.83;\n0.87]","",""],["Metastases to the\nCNS","0.74","[0.73;\n0.75]","","","0.85","[0.83;\n0.87]","","","0.84","[0.82;\n0.86]","",""]],"caption_candidate":"Table 1 Summary of test statistics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250440-p16-t0","doc_id":"K250440","page_num":16,"bbox":[75.72,73.2,536.16,193.08],"n_rows":3,"n_cols":7,"columns":["Meningiomas","0.76","[0.73;\n0.79]","0.89","0.84; 0.94]","0.90","[0.85;\n0.94]"],"rows":[["Meningiomas","0.76","[0.73;\n0.79]","0.89","0.84; 0.94]","0.90","[0.85;\n0.94]"],["Cranial and\nparaspinal nerve\ntumors","0.89","[0.88;\n0.90]","0.97","[0.93; 1.0]","0.97","[0.93; 1.0]"],["Gliomas and glio-\n/neuronal tumors","0.81","[0.76;\n0.86]","0.95","[0.88; 1.0]","0.85","[0.74;\n0.94]"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p12-t0","doc_id":"K250443","page_num":12,"bbox":[72.71,659.98,503.65,734.62],"n_rows":4,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Avanto Fit (1.5T)\nwith syngo MR XA50A","K220151, cleared on April 01,\n2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Skyra Fit (3T)\nwith syngo MR XA50A","K220589, cleared on May 13,\n2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"]],"caption_candidate":"following devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p13-t0","doc_id":"K250443","page_num":13,"bbox":[72.47,71.04,503.99,271.73],"n_rows":9,"n_cols":4,"columns":["MAGNETOM Sola Fit2 (1.5T)\nwith syngo MR XA51A","K221733, cleared on September\n13, 2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],"rows":[["MAGNETOM Sola Fit2 (1.5T)\nwith syngo MR XA51A","K221733, cleared on September\n13, 2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Viato.Mobile\n(1.5T) with syngo MR XA51A","K240608, cleared on March 29,\n2024","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["syngo.via VB40A","K191040, cleared on May 16,\n2019","LLZ","Siemens Healthcare GmbH"],["Reference Device","FDA Clearance Number and","Product","Manufacturer"],["","Date","Code",""],["MAGNETOM Cima.X with\nsyngo MR XA61A","K231587, cleared on December\n18, 2023","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Sola with syngo\nMR XA61A","K232535, cleared on December\n22, 2023","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Vida\nwith syngo MR XA50A,","K213693, cleared Feb 25,2022","LNH,\nLNI, MOS","Siemens Healthcare GmbH"],["MAGNETOM Aera with syngo\nMR VE11","K153343, cleared on April 15,\n2016","LNH,\nLNI, MOS","Siemens Healthcare GmbH"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p13-t1","doc_id":"K250443","page_num":13,"bbox":[72.47,489.84,503.99,726.1],"n_rows":18,"n_cols":4,"columns":["","Subject Devices","Predicate Devices","Reference Devices"],"rows":[["","Subject Devices","Predicate Devices","Reference Devices"],["","","",""],["","MAGNETOM Avanto Fit,","MAGNETOM Avanto Fit","MAGNETOM Cima.X"],["","MAGNETOM Skyra Fit,","with syngo MR XA50A","(K231587) with syngo MR"],["","MAGNETOM Sola Fit, and","(K220151), MAGNETOM","XA61A; MAGNETOM Sola"],["","MAGNETOM Viato.Mobile, all","Skyra Fit with syngo MR","(K232535) with syngo MR"],["Hardware","with software syngo MR","XA50A (K220589),","XA61A; MAGNETOM Vida"],["","XA70A","MAGNETOM Sola Fit with","(K213693) with syngo MR"],["","","syngo MR XA51A","XA50A, (K203443)"],["","","(K221733), and","MAGNETOM Aera with"],["","","MAGNETOM Viato.Mobile","syngo MR VE11"],["","","with syngo MR XA51A",""],["","","(K240608)",""],["Magnet System","Yes","Yes","Yes"],["RF System","Yes","Yes","Yes"],["Transmission\ntechnique","Yes","Yes","Yes"],["Gradient System","Yes","Yes","Yes"],["Patient Table","Yes","Yes","Yes"]],"caption_candidate":"Summary hardware comparison table for the subject and predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p14-t0","doc_id":"K250443","page_num":14,"bbox":[72.44,71.16,504.84,232.87],"n_rows":11,"n_cols":4,"columns":["Multi-Nuclear\nOption - Supported\nNuclei","No","No","No\n(Yes for MAGNETOM\nCima.X)"],"rows":[["Multi-Nuclear\nOption - Supported\nNuclei","No","No","No\n(Yes for MAGNETOM\nCima.X)"],["Computer","Y es","Yes","Yes"],["Coils","Yes","Yes","Yes"],["","New for MAGNETOM Avanto","",""],["","Fit, based on predicate: BM","",""],["","Head/Neck 20","",""],["Other HW\ncomponents","Yes","Yes","Yes"],["","3D camera, cushions modified","",""],["","compared to the respective","",""],["","subject device (see Device","",""],["","Description)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p14-t1","doc_id":"K250443","page_num":14,"bbox":[72.44,260.73,504.84,766.18],"n_rows":51,"n_cols":3,"columns":["","Subject Devices","Predicate Devices"],"rows":[["","Subject Devices","Predicate Devices"],["","",""],["","MAGNETOM Avanto Fit,","MAGNETOM Avanto Fit with"],["","MAGNETOM Skyra Fit, MAGNETOM","syngo MR XA50A (K220151),"],["","Sola Fit, and MAGNETOM","MAGNETOM Skyra Fit with"],["Software","Viato.Mobile, all with software","syngo MR XA50A (K220589),"],["","syngo MR XA70A","MAGNETOM Sola Fit with"],["","","syngo MR XA51A (K221733),"],["","","and MAGNETOM Viato.Mobile"],["","","with syngo MR XA51A"],["","","(K240608)"],["Sequences","",""],["","New feature as listed in the Device","Yes"],["SE-based pulse sequence types","",""],["","Description above",""],["","",""],["","New or modified pulse sequences","Yes"],["GRE-based/Steady-State pulse","",""],["","as listed in the Device Description",""],["sequence types","",""],["","above",""],["","",""],["","New features as listed in the Device","Yes"],["EPI-based pulse sequence types","",""],["","Description above",""],["","",""],["Spectroscopy pulse sequence types","Yes","Yes"],["Feature and Applications","",""],["Other features and","","Yes"],["applications such as:","",""],["","Modified features and",""],["-Application Suites","",""],["","applications as listed in the Device",""],["-myExam Assists","",""],["","Description above",""],["-Other Imaging","",""],["","",""],["Applications","",""],["User interface and user interaction","Yes","Yes"],["","New or modified viewing and post-","Yes"],["Viewing and post-processing","processing features as listed in the",""],["","Device Description above",""],["Workflow and software utilization","Yes","Yes"],["Patient Management","Yes","Yes"],["Scan Modes and Pulse Sequences","Yes","Yes"],["","Modified and new features and","Yes"],["","applications as listed in the",""],["Scanning","Cover letter, Device Description",""],["","and Substantial Equivalence",""],["","Comparison Tables",""],["Reconstruction","New feature","Yes"]],"caption_candidate":"Summary software comparison table for the subject and predicate devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p15-t0","doc_id":"K250443","page_num":15,"bbox":[72.59,71.32,504.32,122.3],"n_rows":4,"n_cols":3,"columns":["","as listed in the Device Description",""],"rows":[["","as listed in the Device Description",""],["","above",""],["Image Display","Yes","Yes"],["File/Data Management","Yes","Yes"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p15-t1","doc_id":"K250443","page_num":15,"bbox":[72.59,506.59,504.32,585.1],"n_rows":2,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Performance bench test","- SNR and image uniformity\nmeasurements for coils\n- Heating measurements for coils","Guidance for Submission of\nPremarket Notifications for\nMagnetic Resonance Diagnostic\nDevices"]],"caption_candidate":"reference devices and can be reused for the subject device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p16-t0","doc_id":"K250443","page_num":16,"bbox":[72.5,90.62,508.78,703.3],"n_rows":7,"n_cols":3,"columns":["","Deep Resolve Boost:","Deep Resolve Sharp:"],"rows":[["","Deep Resolve Boost:","Deep Resolve Sharp:"],["Training and Validation data","• TSE: more than 25,000 slices\n• HASTE: pre-trained on the\nTSE dataset and refined with\nmore than 10,000 HASTE\nslices\n• EPI Diffusion: more than\n1,000,000 slices\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength.","on more than 10,000 high\nresolution 2D images.\nThe data covered a broad range\nof body parts, contrasts, fat\nsuppression techniques,\norientations, and field strength."],["Test Statistics and Test Results\nSummary","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR) and\nstructural similarity index (SSIM).\nMost importantly, the\nperformance was evaluated by\nvisual comparisons to evaluate\ne.g., aliasing artifacts, image\nsharpness and denoising levels.","The impact of the network has\nbeen characterized by several\nquality metrics such as peak\nsignal-to-noise ratio (PSNR),\nstructural similarity index (SSIM),\nand perceptual loss. In addition,\nthe feature has been verified\nand validated by inhouse tests.\nThese tests include visual rating\nand an evaluation of image\nsharpness by intensity profile\ncomparisons of reconstructions\nwith and without Deep Resolve\nSharp."],["Equipment","1.5T and 3T MRI systems",""],["Clinical Subgroups","No clinical subgroups have been defined for the collected dataset.",""],["Demographic Distribution","Due to reasons of data privacy, we did not record gender, age and\nethnicity during data collection.",""],["Reference Standard","The acquired datasets (as\ndescribed above) represent the\nground truth for the training and\nvalidation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation and augmentation.\nThis process includes further\nunder-sampling of the data by\ndiscarding k-space lines,\nlowering of the SNR level by\naddition Restricted of noise and\nmirroring of k-space data.","The acquired datasets represent\nthe ground truth for the training\nand validation. Input data was\nretrospectively created from the\nground truth by data\nmanipulation. k-space data has\nbeen cropped such that only the\ncenter part of the data was used\nas input. With this method\ncorresponding low-resolution\ndata as input and high-resolution\ndata as output / ground truth\nwere created for training and\nvalidation."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p17-t0","doc_id":"K250443","page_num":17,"bbox":[72.5,102.86,508.78,780.36],"n_rows":7,"n_cols":2,"columns":["Feature","Publications"],"rows":[["Feature","Publications"],["GRE_PC","[13_1] Christian Guenthner, Sweta Sethi, Marian\nTroelstra, Ristretto MRE: A generalized multi‐shot GRE‐\nMRE sequence NMR Biomed 2019 32:e4049"],["3D Whole Heart","[13_2] Henningsson M, Koken P, Stehning C et al.:\nWhole-heart coronary MR angiography with 2D self-\nnavigated image reconstruction Magn Reson\nMed, 2012, 67:437–45\n[13_3] Prieto C, Doneva M, Usman M et al.: Highly\nefficient respiratory motion compensated free-\nbreathing coronary MRA using golden-step Cartesian\nacquisition, J Magn Reson Imaging, 2015 41:738–46\n[13_4] Correia T, Ginami G, Cruz G, et al.: Optimized\nrespiratory-resolved motion compensated 3D Cartesian\ncoronary MR angiography, Magn Reson Med, 2018\n80:2618–2629\n[13_5] Chefd’hotel C, Hermosillo G, Faugeras O Flows\nof diffeomorphisms for multimodal image registration.\nProc. IEEE International Symposium on Biomedical\nImaging 2002 753–756\n[13_6] Batchelor PG, Atkinson D, Irarrazaval P, et al.:\nMatrix Description of General Motion Correction\nApplied to Multishot Images, Magn Reson Med 2005\n54:1273–1280\n[13_7] Zeilinger MG, Kunze K-P, Munoz C et al.: Non-\nrigid motion-corrected free-breathing 3D myocardial\nDixon LGE imaging in a clinical setting, Eur Radiol 2022\n32:4340-4351"],["SPACE Improvement: high bandwidth\nIR pulse","[13_8] Wang X, Greer JS, Dimitrov IE, Pezeshk P,\nChhabra A, Madhuranthakam AJ: Frequency Offset\nCorrected Inversion Pulse for B0 and B1 Insensitive Fat\nSuppression at 3T: Application to MR Neurography of\nBrachial Plexus, J Magn Reson Imaging, 2018 Oct\n48(4):1104-1111. doi: 10.1002/jmri.26021. Epub 2018\nSep 15. PMID: 30218576"],["SPACE Improvement: increase\ngradient spoiling","[13_9] Mugler JP 3rd: Optimized three-dimensional fast-\nspin-echo MRI, J Magn Reson Imaging, 2014 Apr\n39(4):745-67. doi: 10.1002/jmri.24542. Epub 2014 Jan\n8. PMID: 24399498."],["Deep Resolve Gain","[13_10] Kellman P. et al Image Reconstruction in SNR\nUnits: A General Method for SNR Measurement MRM,\n2005 54:1439\n[13_11] Blu T. et al: The SURE-LET approach to image\ndenoising, IEEE Transactions on Image Processing, 2007\n6(11):2778-86"],["HASTE diffusion","[13_12] Ilıca AT, Hıdır Y, Bulakbaşı N, Satar B, Güvenç I,\nArslan HH, Imre N. HASTE diffusionweighted MRI for the\nreliable detection of cholesteatoma. Diagn Interv"]],"caption_candidate":"of the following features and functions:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250443-p18-t0","doc_id":"K250443","page_num":18,"bbox":[72.5,71.04,508.78,774.84],"n_rows":3,"n_cols":2,"columns":["","Radiol. 2012 Mar-Apr 18(2):153 -8. doi: 10.4261/1 305-\n3825.DIR. 4246- 11.3. Epub 2011 Sep 29. PMID:\n21960134"],"rows":[["","Radiol. 2012 Mar-Apr 18(2):153 -8. doi: 10.4261/1 305-\n3825.DIR. 4246- 11.3. Epub 2011 Sep 29. PMID:\n21960134"],["AutoMate Cardiac","[13_13] J. a. Y. S. S. a. S. M. Wetzl, \"AI‐based Single‐Click\nCardiac MRI Exam: Initial Clinical Experience and\nEvaluation in 44 Patients,\" in ISMRM & ISMRT Annual\nMeeting & Exhibition, 2023.\n[13_14] S. S. a. P. E. a. S. M. a. F. C. a. C. T. a. S. P. a. F. J.\nL. a. T. C. a. W. J. a. M. A. Yoon, \"Automated Cardiac\nResting Phase Detection Targeted on the Right\nCoronary Artery,\" Machine Learning for Biomedical\nImaging, vol. 2, pp. 1‐26, 2023.\n[13_15] S. S. a. S. M. a. R. M. a. C. T. a. S. P. a. E. T. a. T.\nC. a. W. R. Yoon, \"Validation of a deep learning based\nautomated myocardial inversion time selection for late\ngadolinium enhancement imaging in a prospective\nstudy,\" in ISMRM & ISMRT Annual Meeting &\nExhibition, 2021.\n[13_16] R. a. K. T. a. S. Y. a. Y. Y. a. S. Y. S. a. W. J. a. S.\nM. a. K. T. Ogawa, \"Neural network‐‐based fully\nautomated cardiac resting phase detection algorithm\ncompared with manual detection in patients,\" Acta\nRadiologica Open, vol. 11, no. 10, p.\n20584601221137772, 2022.\n[13_17] S. a. W. J. a. S. M. a. B. M. a. Y. S. S. a. G. C. a. B.\nR. McDermott, \"AIbased Cardiac Scan Automation: A\nProspective Comparison of Highly Automated Scan\nWorkflows in 32 Patients,\" in Society for Cardiovascular\nMagnetic Resonance, 2024.\n[13_18] S. a. A. M. a. J. A. a. S. R. B. a. Z. T. a. K. M. a. S.\nJ. a. T. E. a. C. E. a. S. C. Bohnen, \"Cardiovascular\nmagnetic resonance imaging in the prospective,\npopulation‐based, Hamburg City Health cohort study:\nobjectives and design,\" Journal of Cardiovascular\nMagnetic Resonance, vol. 20, pp. 1‐11, 2018.\n[13_19] T. a. G. P. a. H. T. a. U. T. a. C. S. a. K. M. a. T. S.\na. L. Y. a. M. M. C. a. S. F. Pezel, \"Vasodilatation stress\ncardiovascular magnetic resonance imaging: Feasibility,\nworkflow and safety in a large prospective registry of\nmore than 35,000 patients,\" Archives of Cardiovascular\nDiseases, vol. 114, pp. 490‐503, 2021.\n[13_20] G. a. P. A. U. a. K. K. P. a. N. R. a. H. R. a. W. J. a.\nY. S. S. a. S. M. a. N. B. L. a. P. C. a. o. Wood, \"Automated\ndetection of cardiac rest period for trigger delay\ncalculation for image‐based navigator coronary\nmagnetic resonance angiography,\" Journal of\nCardiovascular"],["Ghost reduction","[13_21] W Scott Hoge, Jonathan R Polimeni: Dual-\npolarity GRAPPA for simultaneous reconstruction and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250484-p5-t0","doc_id":"K250484","page_num":5,"bbox":[77.52,274.28,523.01,376.6],"n_rows":7,"n_cols":4,"columns":["","Trade Name","","PIUR tUS inside"],"rows":[["","Trade Name","","PIUR tUS inside"],["","Common Name","","PIUR tUS inside"],["","Classification Name","","Picture Archiving and Communications System"],["","Regulation","","21 CFR 892.2050"],["","Product Code","","QIH"],["","Regulatory Classification:","","Class II"],["","Device Panel:","","Radiology (OHT8)"]],"caption_candidate":"Table 2: Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250484-p5-t1","doc_id":"K250484","page_num":5,"bbox":[77.52,442.68,472.49,471.24],"n_rows":2,"n_cols":9,"columns":["","Predicate Device","","","Manufacturer","","","FDA 510(k)",""],"rows":[["","Predicate Device","","","Manufacturer","","","FDA 510(k)",""],["PIUR tUS Infinity","","","PIUR Imaging GmbH","","","K240036","",""]],"caption_candidate":"Table 3: Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250484-p9-t0","doc_id":"K250484","page_num":9,"bbox":[72.08,239.76,535.53,697.29],"n_rows":6,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K240036)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K240036)",""],["","Product Name","","PIUR tUS inside","","","PIUR tUS Infinity","",""],["","Manufacturer","","PIUR Imaging GmbH","","","PIUR Imaging GmbH","",""],["","Product Code /","","QIH / 21CFR 892.2050","","","QIH / 21CFR 892.2050","",""],["","Regulation","","","","","","",""],["Indications for\nUse","","","PIUR tUS inside is a computer-aided\ndetection device intended to assist and\nsupport the medical professionals in the\ndiagnostic workflow of thyroid and\nthyroid nodules acquired from FDA-\ncleared ultrasound systems, including\nimage documentation, analysis, and\nreporting. The device supports the\nphysician with additional information\nduring image review, including\nquantification and visualization of\nsonographic characteristics of thyroid\nnodules.\nPIUR tUS inside may be used on any\nadult patient aged 22 and older,\nindependent of gender, age, linguistic\nand cultural background, or health\nstatus, unless any of the\ncontraindications apply.\nPIUR tUS inside device is not intended\nfor body contact (including skin,\nmucosal membrane, breached or\ncompromised surfaces, blood path\nindirect, tissues, bones, dentin, or\ncirculation blood).","","","PIUR tUS Infinity is a computer-\naided detection device intended to\nassist and support the medical\nprofessionals in the diagnostic\nworkflow of thyroid and thyroid\nnodules acquired from FDA-cleared\nultrasound systems, including image\ndocumentation, analysis, and\nreporting. The device supports the\nphysician with additional\ninformation during image review,\nincluding quantification and\nvisualization of sonographic\ncharacteristics of thyroid nodules.\nPIUR tUS Infinity may be used on\nany adult patient aged 22 and older,\nindependent of gender, age,\nlinguistic and cultural background,\nor health status, unless any of the\ncontraindications apply.\nPIUR tUS Infinity device is not\nintended for body contact (including\nskin, mucosal membrane, breached\nor compromised surfaces, blood path\nindirect, tissues, bones, dentin, or\ncirculation blood).","",""]],"caption_candidate":"Table 4: Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250484-p10-t0","doc_id":"K250484","page_num":10,"bbox":[72.08,99.36,535.54,697.29],"n_rows":14,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K240036)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K240036)",""],["Functional\nCapability of\nImage Processing","","","The device performs 2D to 3D\nreconstruction to generate volumetric\ndata of a thyroid. User-selected\ncomputer vision and machine learning\nalgorithm suggested volumes of thyroid\nlobe and nodules are visualized to be\nconfirmed by user. Based on that\nsegmentation, quantification of nodules\nfor sonographic characteristics\n(hyperechoic foci, echogenicity, texture,\nmargin, orientation and anechoic areas)\nis being performed and visualized.","","","Same","",""],["Image Retrieval\nInterface","","","Direct access to the image stream\nthrough the software interface run\ndirectly on the compatible ultrasound\nscanner","","","Infinity Box transfers digital image\nfrom 3rd Party ultrasound system to\nthe software through WiFi\nconnection","",""],["Reading\nParadigm","","","Device provides quantification and\nvisualization of sonographic\ncharacteristics based on 3D volumetric\ndata. Results provide proposals to be\nreviewed and confirmed by physicians.","","","Same","",""],["","ACR TI-RADS","","Manual approach whereby user\nclassifies 5 ACR TI-RADS parameters","","","Same","",""],["","Classification","","","","","","",""],["Output Generated\nby the Device","","","The device can export volumetric data,\nannotated screenshots and reports.\nReport can contain both sides of the\npatient and includes all relevant\ndiagnostic information.","","","Same","",""],["","Type of Film to be","","Digital ultrasound videoclip (cineloop)","","","Same","",""],["","Processed by the","","","","","","",""],["","Device","","","","","","",""],["Software Design","","","Based on computer vision, machine\nlearning, pattern recognition and\nquantification method.","","","Same","",""],["Ground Truth\nEstablishment","","","The ground truth to be established for\nperformance studies of the device are\nannotated data sets labeled by medical\nspecialists.","","","Same","",""],["","Platform","","Windows-based","","","Same","",""],["","Operating System","","Ultrasound System","","","Standard PC or review station","",""]],"caption_candidate":"PIUR tUS inside","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250484-p11-t0","doc_id":"K250484","page_num":11,"bbox":[72.08,99.36,535.54,641.19],"n_rows":20,"n_cols":9,"columns":["","Description","","","Subject Device","","","Predicate Device (K240036)",""],"rows":[["","Description","","","Subject Device","","","Predicate Device (K240036)",""],["","Clinical","","Thyroid Lesions","","","Same","",""],["","Application","","","","","","",""],["","Image Type","","Ultrasound volume image","","","Same","",""],["Image Format","","","DICOM format:\nSecondary Capture Image Storage -\n1.2.840.10008.5.1.4.1.1.7\nMulti-frame Grayscale Byte Secondary\nCapture Image Storage -\n1.2.840.10008.5.1.4.1.1.7.2\nMulti-frame True Color Secondary\nCapture Image Storage -\n1.2.840.10008.5.1.4.1.1.7.4\nRefer to: DICOM-Conformance\nStatement-PIUR tUS inside System","","","Same","",""],["","ROI","","Yes","","","Same","",""],["","Quantification","","","","","","",""],["","Automatically","","Yes","","","Same","",""],["","Generating","","","","","","",""],["","Report","","","","","","",""],["","Performance","","Results from standalone performance\ntesting of machine learning algorithm\nsuggested ROIs of user-selected\nnodules","","","Same","",""],["","Testing Data to","","","","","","",""],["","Support SE","","","","","","",""],["","Determination","","","","","","",""],["Device\nComponents","","","PIUR Sensor\nPIUR Bracket\ninside Software","","","Infinity Box\nPIUR Sensor\nPIUR Bracket\nInfinity Software","",""],["","DICOM","","Yes","","","Same","",""],["","Compliance","","","","","","",""],["Data Acquisition","","","Acquire medical image data from\nDICOM compliant Ultrasound imaging\ndevice","","","Same","",""],["","Data / Image","","Ultrasound image via DICOM format","","","Same","",""],["","Types","","","","","","",""]],"caption_candidate":"PIUR tUS inside","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p8-t0","doc_id":"K250525","page_num":8,"bbox":[61.73,91.1,558.27,687.3],"n_rows":10,"n_cols":4,"columns":["","Subject Device\nSecond Opinion®\nPanoramic","Primary Predicate\nDenti.AI Detect\nK230144","Secondary Predicate\nSecond Opinion®\nK210365"],"rows":[["","Subject Device\nSecond Opinion®\nPanoramic","Primary Predicate\nDenti.AI Detect\nK230144","Secondary Predicate\nSecond Opinion®\nK210365"],["Manufacturer","Pearl Inc.","Denti.AI Technology, Inc.","Pearl Inc."],["Classification","892.2070","892.2070","892.2070"],["Product Code","MYN","MYN","MYN"],["Image\nModality","Radiograph","Radiograph","Radiograph"],["Intended Use","Dental CADe to aid with the\ndetection of regions of interest in\npanoramic\nradiograph review by HCP","Dental CADe to aid with the\ndetection of regions of interest in\ndental radiograph review by HCP","Dental CADe to aid in dental\nradiograph review by HCP"],["Full IFU","Second Opinion®\nPanoramic is a radiological\nautomated image\nprocessing software device\nintended to identify and\nmark regions, in panoramic\nradiographs, in relation to\nsuspected dental findings\nwhich include: Caries,\nPeriapical radiolucency, and\nImpacted third molars.\nIt is designed to aid dental\nhealth professionals to\nreview panoramic\nradiographs of permanent\nteeth in patients 16 years of\nage or older as both a\nconcurrent and second\nreader.","Denti.AI Detect is a\nComputer-Assisted Detection\n(CADe) software device intended to\nbe used by dental professionals,\ncomprising dentists and dental\nspecialists, while reading extraoral\nand intraoral 2D dental\nradiographs.\nThe device aims to assist in\ndetecting and highlighting\nuncategorized regions of interest\n(ROIs)within the teeth area, which\ninclude caries and periapical\nradiolucency, as a second reader.\nThe device is also intended to aid in\nthe measurements of mesial and\ndistal bone levels associated with\neach tooth.\nThe device is aimed to be used with\nimages from the patients of 22\nyears age and older without\nremaining primary dentition. The\ndevice is not intended to replace a\ncomplete clinician's review or\nclinical judgment that considers\nother relevant information from the\nimage or patient history.","Second Opinion® is a computer\naided detection (“CADe”) software\nto identify and mark regions in\nrelation to suspected dental\nfindings which include Caries,\nDiscrepancy at the margin of an\nexisting restoration, Calculus,\nPeriapical radiolucency, Crown\n(metal, including zirconia &\nnon-metal), Filling (metal &\nnon-metal), Root canal, Bridge and\nImplants.\nIt is designed to aid dental health\nprofessionals to review bitewing\nand periapical radiographs of\npermanent teeth in patients 12\nyears of age or older as a second\nreader."],["Intended body\npart","Dental","Dental","Dental"],["Technology","Automated, CADe software that\nutilizes machine learning","Automated, CADe software that\nutilizes machine learning","Automated, CADe software that\nutilizes machine learning"],["Device\nDescription","Detection and display of\nanatomy and pathologies in\nextraoral radiographs","Detection and display of anatomy\nand pathologies in intraoral and\nextraoral radiographs","Detection and display of anatomy\nand pathologies in intraoral\nradiographs"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p10-t0","doc_id":"K250525","page_num":10,"bbox":[75.5,672.5,446.5,732.5],"n_rows":3,"n_cols":4,"columns":["Region/Geo","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],"rows":[["Region/Geo","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],["Northwest","95","102","96"],["Northeast","99","101","117"]],"caption_candidate":"Table 2 Geographic distribution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p11-t0","doc_id":"K250525","page_num":11,"bbox":[75.75,91.5,447.5,141.5],"n_rows":3,"n_cols":4,"columns":["South","73","93","95"],"rows":[["South","73","93","95"],["West","60","88","89"],["Midwest","93","112","114"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p11-t1","doc_id":"K250525","page_num":11,"bbox":[75.75,208.5,447.5,292.5],"n_rows":4,"n_cols":4,"columns":["Gender","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],"rows":[["Gender","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],["Female","186","231","234"],["Male","191","226","225"],["Unknown","43","39","52"]],"caption_candidate":"Table 3 Gender distribution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p11-t2","doc_id":"K250525","page_num":11,"bbox":[75.75,382.5,459.5,458.5],"n_rows":4,"n_cols":4,"columns":["Age Group","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],"rows":[["Age Group","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],[">16 - 34 years","178","157","208"],["35 - 64 years","156","208","203"],[">= 65 years","86","131","100"]],"caption_candidate":"Table 4 Age distribution","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p11-t3","doc_id":"K250525","page_num":11,"bbox":[75.75,560.5,447.5,713.5],"n_rows":8,"n_cols":4,"columns":["","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],"rows":[["","Impacted Teeth\nN=420","Periapical Radiolucency\nN=496","Caries\nN=511"],["Overall status, n (%)","","",""],["Normal","225 (53.6)","294 (59.3)","292 (57.1)"],["Abnormal","195 (46.4)","202 (40.7)","219 (42.9)"],["Number of dental features on\nabnormal images","","",""],["Total, n","459","309","654"],["Mean (SD)","2.35 (1.1)","1.53 (1.1)","2.99 (3.3)"],["Median (range)","2 (1, 4)","1 (1, 11)","2 (1, 25)"]],"caption_candidate":"Table 6 Summary of Image characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250525-p12-t0","doc_id":"K250525","page_num":12,"bbox":[76.5,91.5,446.5,157.5],"n_rows":3,"n_cols":4,"columns":["Dental feature size on\nabnormal images (percent of\nimage pixels)","","",""],"rows":[["Dental feature size on\nabnormal images (percent of\nimage pixels)","","",""],["Mean (SD)","0.83 (0.22)","0.09 (0.1)","0.06 (0.07)"],["Median (range)","0.8 (0.23, 1.59)","0.05 (0.0, 0.83)","0.03 (0.0, 0.42)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p6-t0","doc_id":"K250650","page_num":6,"bbox":[72.29,216.71,523.15,317.93],"n_rows":6,"n_cols":6,"columns":["Patient Size\n(AAPM group)","Weight (Kg)","CTDI (mGy)","","SpotLight /",""],"rows":[["Patient Size\n(AAPM group)","Weight (Kg)","CTDI (mGy)","","SpotLight /",""],["","","","","SpotLight Duo -",""],["","","","","Indication for Use",""],["Small","50-70 Kg","0.25-2.8 mGy","Proposed Device","",""],["Medium","70-90 Kg","0.5-4.3 mGy","K241200","",""],["Large","90-120 Kg","1.0-5.6 mGy","K241200","",""]],"caption_candidate":"size groups, as detailed in the following table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p8-t0","doc_id":"K250650","page_num":8,"bbox":[53.16,59.87,788.8,533.82],"n_rows":7,"n_cols":10,"columns":["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],"rows":[["","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],["","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","","",""],["","","","for the SpotLight / SpotLight Duo System","","","(K241200) CT X-ray System with Low Dose Lung Cancer","","",""],["","","","(Whole LCS population indication-","","","Screening (LD LCS) Option","","",""],["","","","small, medium, and large patient groups)","","","(LCS medium and large patient groups indication)","","",""],["","Indications for Use","","","","","","","",""],["Indications for use","Indications for use","The SpotLight / SpotLight Duo is intended to produce cross-\nsectional images of the body by computer reconstruction of\nX-ray transmission projection data taken at different angles.\nThe system has the capability to image cardiovascular and\nthoracic anatomies, including the heart, in a single rotation.\nThe system may acquire data using Axial, Cine and Cardiac\nscan techniques from patients of all ages (DLIR is limited for\npatient use above the age of 2 years). These images may be\nobtained either with or without contrast. This device may\ninclude signal analysis and display equipment, patient and\nequipment supports, components and accessories.\nThis device may include data and image processing to\nproduce images in a variety of trans-axial and reformatted\nplanes.\nThe system is indicated for x-ray Computed Tomography\nimaging of cardiovascular and thoracic anatomies that fit in\nthe scan field-of-view.\nThe Low Dose CT Lung Cancer Screening Option for\nSpotLight / SpotLight Duo is indicated for using low dose CT\nfor lung cancer screening. The screening must be conducted\nwith the established program criteria and protocols that have\nbeen approved and published by a governmental body or a\nprofessional medical society. Information from professional\nsocieties related to lung cancer screening can be found but\nis not limited to: American College of Radiology® (ACR) –\nresources and technical specification; accreditation American\nAssociation of Physicists in Medicine (AAPM) – Lung Cancer\nScreening Protocols; radiation management. Please refer to\nclinical literature, including the results of the National Lung\nScreening Trial (N Engl J Med 2011; 365:395-409) and\nsubsequent literature, for further information.\nThe DLIR and ASIR-CV options are not compatible with the\nLow Dose Lung Cancer Screening option.\nThe device output is useful for diagnosis of disease or\nabnormality and for planning of therapy procedures.","","","The SpotLight / SpotLight Duo is intended to produce cross-\nsectional images of the body by computer reconstruction of\nX-ray transmission projection data taken at different angles.\nThe system has the capability to image cardiovascular and\nthoracic anatomies, including the heart, in a single rotation.\nThe system may acquire data using Axial, Cine and Cardiac\nscan techniques from patients of all ages (DLIR is limited for\npatient use above the age of 2 years). These images may be\nobtained either with or without contrast. This device may\ninclude signal analysis and display equipment, patient and\nequipment supports, components and accessories.\nThis device may include data and image processing to\nproduce images in a variety of trans-axial and reformatted\nplanes.\nThe system is indicated for x-ray Computed Tomography\nimaging of cardiovascular and thoracic anatomies that fit in\nthe scan field-of-view.\nThe Low Dose CT Lung Cancer Screening Option for\nSpotLight / SpotLight Duo is indicated for using low dose CT\nfor lung cancer screening. The screening must be conducted\nwith the established program criteria and protocols (for\nmedium and large patients) that have been approved and\npublished by a governmental body or a professional medical\nsociety. Information from professional societies related to\nlung cancer screening can be found but is not limited to:\nAmerican College of Radiology® (ACR) – resources and\ntechnical specification; accreditation American Association of\nPhysicists in Medicine (AAPM) – Lung Cancer Screening\nProtocols; radiation management. Please refer to clinical\nliterature, including the results of the National Lung\nScreening Trial (N Engl J Med 2011; 365:395-409) and\nsubsequent literature, for further information.\nThe DLIR and ASIR-CV options are not compatible with the\nLow Dose Lung Cancer Screening option.\nThe device output is useful for diagnosis of disease or\nabnormality and for planning of therapy procedures.","","","The indications for use are\nsimilar except for minor\ndifferences. The indications\nfor use for the proposed\nSpotLight/SpotLight Duo\ndevices include the whole\nLow Dose Lung Cancer\nScreening Option with\nadditional small patient\nprotocols per AAPM\nguidelines (50-70kg, <2.8\nmGy).\nThe indication for use does\nnot constitute a new\nintended use for the CT.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p9-t0","doc_id":"K250650","page_num":9,"bbox":[53.16,59.87,788.83,517.15],"n_rows":14,"n_cols":11,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion",""],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","","",""],["","","","","for the SpotLight / SpotLight Duo System","","","(K241200) CT X-ray System with Low Dose Lung Cancer","","",""],["","","","","(Whole LCS population indication-","","","Screening (LD LCS) Option","","",""],["","","","","small, medium, and large patient groups)","","","(LCS medium and large patient groups indication)","","",""],["","Technological Characteristics","","","","","","","","",""],["Detector technology\nand geometry","Detector technology","","Fast scintillator array coupled to photodiode array.\n33 (WFOV) or 23 (EFOV) configurable high resolution (HR)\nmodules comprising 192 detector rows X pitch 0.5mm (Z\ndirection, measured at scanner center).\n10 (WFOV) or 20 (EFOV) configurable low resolution (LR).\nEFOV includes 10 modules on each wing while WFOV\nincludes 10 modules on one wing. comprising 48 detector\nrows X pitch 2.0mm\nAnalog to digital conversion per channel on the detection\nmodule.\n1D antiscatter collimator.","","","Fast scintillator array coupled to photodiode array.\n33 (WFOV) or 23 (EFOV) configurable high resolution (HR)\nmodules comprising 192 detector rows X pitch 0.5mm (Z\ndirection, measured at scanner center).\n10 (WFOV)-20 (EFOV) configurable low resolution (LR).\nEFOV includes 10 modules on each wing while WFOV\nincludes 10 modules on one wing. comprising 48 detector\nrows X pitch 2.0mm\nAnalog to digital conversion per channel on the detection\nmodule.\n1D antiscatter collimator.","","","Same",""],["","and geometry","","","","","","","","",""],["Data transmission\nfrom rotor","","","Contactless transmission (capacitive coupling). Rate up to\n6.25 GBit/sec","","","Contactless transmission (capacitive coupling). Rate up to\n6.25 GBit/sec","","","Same",""],["","Power and control","","Brush contact slipring","","","Brush contact slipring","","","Same",""],["","transmission to rotor","","","","","","","","",""],["","Rotation drive","","Direct drive DC motor","","","Direct drive DC motor","","","Same",""],["X Ray source","X Ray source","","2 x MCS 2093 X ray tubes by Varex Imaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in X direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","","","2 x MCS 2093 X ray tubes by Varex Imaging Corp.\nSingle ended grounded rotating anode\nAnode angle 13 degrees\n1.0 MHU anode heat capacity\nGrid controlled focal spot modulation in X direction\nSmall and large focal spots\nMax kVp: 140 kV\nMax power: 72 KW","","","Same",""],["Patient table","","","Motorized vertical and horizontal motion.\nOptional lateral motion\nCantilever carbon fiber patient cradle.","","","Motorized vertical and horizontal motion.\nOptional lateral motion.\nCantilever carbon fiber patient cradle.","","","Same",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p10-t0","doc_id":"K250650","page_num":10,"bbox":[53.16,59.87,788.84,515.82],"n_rows":11,"n_cols":10,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","",""],["","","","","for the SpotLight / SpotLight Duo System","","","(K241200) CT X-ray System with Low Dose Lung Cancer","",""],["","","","","(Whole LCS population indication-","","","Screening (LD LCS) Option","",""],["","","","","small, medium, and large patient groups)","","","(LCS medium and large patient groups indication)","",""],["","Image reconstruction","","Multicore PC and GPU","","","Multicore PC and GPU","","","Same"],["","hardware","","","","","","","",""],["Image reconstruction\nalgorithm","Image reconstruction","","Modified FDK cone beam algorithm adapted for dual tubes\ngeometry.\nAdaptive filter to reduce directional noise in low level raw\ndata (MBAF).\nNon-local means algorithm MBAF2 (optional).\nFor WFOV configuration, adapted to reconstruct high\nresolution images according to detector configuration, lower\nresolution images outside FOV covered by high resolution\ndetectors.\nFor extended FOV configuration, adapted to reconstruct high\nresolution images up to FOV250mm, lower resolution\nimages outside FOV250mm.","","","Modified FDK cone beam algorithm adapted for dual tubes\ngeometry.\nAdaptive filter to reduce directional noise in low level raw\ndata (MBAF).\nNon-local means algorithm MBAF2 (optional).\nFor WFOV configuration, adapted to reconstruct high\nresolution images according to detector configuration, lower\nresolution images outside FOV covered by high resolution\ndetectors.\nFor extended FOV configuration, adapted to reconstruct high\nresolution images up to FOV250mm, lower resolution\nimages outside FOV250mm.","","","Same"],["","algorithm","","","","","","","",""],["Construction Materials","","","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and electronic cables\ncomponents\nTable top made of carbon fiber reinforced resin\nCovers made pf molded polymers and reinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4 and Gadolinium\nOxysulfide (GOS) used in other legally marketed CT\nscanners","","","Metal parts (mostly steel and aluminum)\nLead and tungsten for X-ray shielding\nPCB, electronic components and electronic cable\ncomponents\nTable top made of carbon fiber reinforced resin\nCovers made pf molded polymers and reinforced resins\nOil in X-ray tubes cooling systems\nDetector scintillators made of CdWO4 and Gadolinium\nOxysulfide (GOS) used in other legally marketed CT\nscanners","","","Same"],["Energy sources","","","Wall supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes) 72kW","","","Wall supply 380 to 480 V 3 phase\nMax power demand 115 kVA\nMax X ray power (total for two tubes) 72kW","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p11-t0","doc_id":"K250650","page_num":11,"bbox":[53.16,59.87,788.85,495.04],"n_rows":15,"n_cols":10,"columns":["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],"rows":[["","","","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],["","","","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","",""],["","","","","for the SpotLight / SpotLight Duo System","","","(K241200) CT X-ray System with Low Dose Lung Cancer","",""],["","","","","(Whole LCS population indication-","","","Screening (LD LCS) Option","",""],["","","","","small, medium, and large patient groups)","","","(LCS medium and large patient groups indication)","",""],["","","","Laser alignment lights: gantry bore external lasers. <0.1mW\nper laser beam\nThree lead ECG trigger module, powered by medical grade\npower supply through the system PDU","","","Laser alignment lights: gantry bore external lasers. <0.1mW\nper laser beam\nThree lead ECG trigger module, powered by medical grade\npower supply through the system PDU","","",""],["Software","","","Provided with software in three domains:\n• Console software\n• Image reconstruction software\n• Embedded software","","","Provided with software in three domains:\n• Console software\n• Image reconstruction software\n• Embedded software","","","Same"],["Max Rotation speed","","","250 RPM (0.24 sec per rotation)","","","250 RPM (0.24 sec per rotation)","","","Same"],["Min scan time","","","0.16 sec (partial), 0.24 sec (full scan) – FOV up to 250mm\n0.24 sec (full scan) – HR imaging at FOV above 250mm for\nasymmetric detector","","","0.16 sec (partial), 0.24 sec (full scan) – FOV up to 250mm\n0.24 sec (full scan) – HR imaging at FOV above 250mm for\nasymmetric detector","","","Same"],["","Max axial coverage in","","140mm (280 slices x 0.5mm pitch)","","","140mm (280 slices x 0.5mm pitch)","","","Same"],["","a single axial scan","","","","","","","",""],["Field of View (FOV)","Field of View (FOV)","","25cm - 250mm at high resolution\nWFOV - High resolution images at configurable FOV\nbetween 250mm and 450mm\nEFOV – Lower resolution in the FOV between HR coverage\nand 450mm","","","25cm - 250mm at high resolution\nWFOV - High resolution images at configurable FOV\nbetween 250mm and 450mm\nEFOV – Lower resolution in the FOV between HR coverage\nand 450mm","","","Same"],["Max spatial resolution","","","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by HR detectors\n7.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by LR detectors","","","17.5 lp/cm cutoff at center\n10.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by HR detectors\n7.0 lp/cm cutoff at radius above 125mm (outside FOV\n250mm) covered by LR detectors","","","Same"],["","Bore size","","60 cm","","","60 cm","","","Same"],["","Max Patient weight","","227 Kg (500 lbs)","","","227 Kg (500 lbs)","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250650-p12-t0","doc_id":"K250650","page_num":12,"bbox":[53.16,59.87,788.81,200.54],"n_rows":6,"n_cols":8,"columns":["","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],"rows":[["","","Proposed devices –","","","Primary Predicate devices –","","Discussion"],["","","Low Dose CT Lung Cancer Screening (LD LCS) Option","","","The Cleared Arineta’s SpotLight / SpotLight Duo","",""],["","","for the SpotLight / SpotLight Duo System","","","(K241200) CT X-ray System with Low Dose Lung Cancer","",""],["","","(Whole LCS population indication-","","","Screening (LD LCS) Option","",""],["","","small, medium, and large patient groups)","","","(LCS medium and large patient groups indication)","",""],["Add on parts and\naccessories","Operator console table\nNG2000 Table slickers\nBar code reader\nUninterruptible Power Supply\nHead& hands and knees support","","","Operator console table\nNG2000 Table slickers\nBar code reader\nUninterruptible Power Supply\nHead& hands and knees support","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p8-t0","doc_id":"K250660","page_num":8,"bbox":[55.77,112.11,556.03,773.1],"n_rows":13,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos Agile Max","LUMINOS Q.namix T",""],["","","",""],["","","",""],["Regulation\nDescription","System, x-ray, fluoroscopic,\nimage-intensified, Solid State\nX-ray imager","System, x-ray, fluoroscopic,\nimage-intensified, Solid State\nX-ray imager","Same"],["Regulation\nNumber","892.1650","892.1650","Same"],["Classification\nProduct Code","JAA, OWB","JAA, OWB","Same"],["Indications for\nuse","Luminos Agile Max is a\ndevice intended to visualize\nanatomical structures by\nconverting an X-ray pattern\ninto a visible image. The\nsystem has medical\napplications ranging from\ngastrointestinal examinations\nto cranial, skeletal, thoracic\nand lung exposures as well as\nexaminations of the urogenital\ntract. The unit may also be\nused in emergency\napplications, lymphography,\nendoscopy, myelography,\nvenography, arthrography,\ninterventional radiology,\ndigital angiography and digital\nsubtraction angiography\n(DSA). The system may be\nused on pediatric, adult and\nbariatric patients.\nLuminos Agile Max is not for\nmammography examinations.","LUMINOS Q.namix T and\nLUMINOS Q.namix R are\ndevices intended to visualize\nanatomical structures by\nconverting an X-ray pattern\ninto a visible image. It is a\nmultifunctional, general R/F\nsystem, suitable for routine\nradiography and fluoroscopy\nexaminations, including\ngastrointestinal- and urogenital\nexaminations and specialist\nareas like arthrography,\nangiography and pediatrics.\nLUMINOS Q.namix T and\nLUMINOS Q.namix R are\nnot intended to be used for\nmammography examinations.","Similar"],["X-Ray","","",""],["","","",""],["Generator","Polydoros F80\n65/80 kW","Polydoros RFX\n65/80 kW","Changed, new State of\nthe Art Generator"],["X-Ray tube","OPTITOP\n150/40/80/HC-100","OPTITOP\n150/40/80/HC-100","Same"],["X-ray techniques","Radiography, Pulsed\nfluoroscopy, DSA and series\nexposure","Radiography, Pulsed\nfluoroscopy and series\nexposure","Changed, DSA\nfunction is not\navailable at\nLUMINOS"]],"caption_candidate":"(Luminos Agile Max K173639)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p9-t0","doc_id":"K250660","page_num":9,"bbox":[55.76,61.5,556.05,755.1],"n_rows":26,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos Agile Max","LUMINOS Q.namix T",""],["","","",""],["","","",""],["","","","Q.namix T"],["Collimator","Digital Multileaf\nCollimator N","Digital Multileaf\nCollimator RFU","Changed, new\ncollimator"],["Air kerma","Kerma X","Kerma X","Same"],["CARE","Combined\nApplications to\nReduce Exposure","Combined\nApplications to\nReduce Exposure","Same"],["Touch user\ninterface on tube\nsuspension","touchscreen in portrait format","touchscreen in landscape\nformat","Changed, same touch\nuser interface as for\nreference device\nYSIO X.pree is used"],["Controls at\nDigital Imaging\nTower (DIT)","hardware buttons","Two touch user interfaces at\nleft and right side, replacing\nmost of the hardware buttons","Changed, new touch\nuser interface"],["Digital Imaging","","",""],["","","",""],["Fluoro Detector\nin DIT","Trixel pixium 4343F-4\n“Max Dynamic”","Trixel pixium 4343F-5\n“X.fluoro”","Changed, new version\nof the Fluoro detector"],["Fixed detector for\nwall stand","Trixell pixium 4343RCE\n“Max Static”","Trixell pixium 4343RCE\n“Max Static”","Same"],["Large mobile\ndetectors","Trixell pixium\n3543EZh „MAX wi-D“","Trixell pixium\n3543EZh „MAX wi-D“","Same"],["","N/A","Trixell pixium 3543EZ3\n“X.wi-D 35”","New, Same as for\nreference device\nYSIO X.pree."],["","N/A","Trixell pixium 4343EZ3\n“X.wi-D 43”","New, Same as for\nreference device\nYSIO X.pree."],["Small mobile\ndetector","Trixell pixium 2430EZ “MAX\nmini”","Trixell pixium 2430EZ “MAX\nmini”","Same"],["","N/A","Trixell pixium 2430EZ3\n“X.wi-D 24”","New for LUMINOS\nQ.namix T"],["Digital imaging\nsystem","Fluorospot Compact","Fluorospot Compact Plus","Changed"],["","Operating system Windows 10","Operating system Windows 10","Same"],["","Operated via mouse and\nkeyboard","Operated via touch screen","Changed"],["","Image processing with\nDiamond View Plus","Image processing with\nmyExam IQ","Slightly different,\nbased on same\nprocessing\nsoftware. Same as for\nreference device\nYSIO X.pree."],["","N/A","AI-based Auto Cropping","New, Same as for\nreference device\nYSIO X.pree."],["","Acquisition and Image\nprocessing parameters selected\nvia Organ Programs","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Changed, same as for\nreference device\nYSIO X.pree."],["Display","19” Monitor","24” and 32” Touch Monitors","Changed, new touch\nMonitors available"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p10-t0","doc_id":"K250660","page_num":10,"bbox":[55.77,61.5,556.04,442.26],"n_rows":16,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos Agile Max","LUMINOS Q.namix T",""],["","","",""],["","","",""],["Other Features and Components","","",""],["","","",""],["Ceiling Stand\n(Second Plane)","Ysio Max Ceiling Stand","YSIO X.pree Ceiling Stand","Changed, updated\nCeiling Stand"],["Patient Table","Table with optional bucky tray","Table with optional bucky tray","Same"],["","Standard tabletop","Standard tabletop and flat\ntabletop","Changed, optional flat\ntabletop is now\navailable"],["Wall stand","Wall stand with fixed detector\nand wall stand with bucky tray","Wall stand with fixed detector\nand wall stand with bucky tray","Same"],["Camera","N/A","Live camera for patient\npositioning and collimation","New, Same as for\nreference device\nYSIO X.pree."],["AI based\nAutomatic\ncollimation","N/A","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","New, Same as for\nreference device\nYSIO X.pree."],["Cropping","Auto Cropping","AI-based Auto Cropping","Changed, same AI-\nbased cropping used\nas for reference device\nYSIO X.pree."],["Indicator Lights","N/A","Indicator Light at tube stand\n(YSIO X.pree option)","New"],["Light below\nDigital Imaging\nTower (DIT)","N/A","available","New"],["Foot Switch","Wired Footswitch","Wired and wireless Footswitch","New wireless foot\nswitch"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p11-t0","doc_id":"K250660","page_num":11,"bbox":[67.42,103.02,567.67,763.98],"n_rows":13,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos dRF Max","LUMINOS Q.namix R",""],["","","",""],["","","",""],["Regulation\nDescription","System, x-ray, fluoroscopic,\nimage-intensified, Solid State\nX-ray imager","System, x-ray, fluoroscopic,\nimage-intensified, Solid State\nX-ray imager","Same"],["Regulation\nNumber","892.1650","892.1650","Same"],["Classification\nProduct Code","JAA, OWB","JAA, OWB","Same"],["Indications for\nuse","Luminos dRF Max is a device\nintended to visualize\nanatomical structures by\nconverting an X-ray pattern\ninto a visible image. The\nsystem has medical\napplications ranging from\ngastrointestinal examinations\nto cranial, skeletal, thoracic\nand lung exposures as well as\nexaminations of the urogenital\ntract. The unit may also be\nused in emergency\napplications, lymphography,\nendoscopy, myelography,\nvenography, arthrography,\ninterventional radiology,\ndigital angiography and digital\nsubtraction angiography\n(DSA). The system may be\nused on pediatric, adult and\nbariatric patients.\nLuminos dRF Max is not for\nmammography examinations.","LUMINOS Q.namix T and\nLUMINOS Q.namix R are\ndevices intended to visualize\nanatomical structures by\nconverting an X-ray pattern\ninto a visible image. It is a\nmultifunctional, general R/F\nsystem, suitable for routine\nradiography and fluoroscopy\nexaminations, including\ngastrointestinal- and urogenital\nexaminations and specialist\nareas like arthrography,\nangiography and pediatrics.\nLUMINOS Q.namix T and\nLUMINOS Q.namix R are\nnot intended to be used for\nmammography examinations.","Similar"],["X-Ray","","",""],["","","",""],["Generator","Polydoros F80\n65/80 kW","Polydoros RFX\n65/80 kW","Changed, new State of\nthe Art Generator"],["X-Ray tube","OPTITOP\n150/40/80/HC-100","OPTITOP\n150/40/80/HC-100","Same"],["X-ray techniques","Radiography, Pulsed\nfluoroscopy, DSA and series\nexposure","Radiography, Pulsed\nfluoroscopy and series\nexposure","Changed, DSA\nfunction is not\navailable at\nLUMINOS"]],"caption_candidate":"Device (Luminos dRF Max K173639)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p12-t0","doc_id":"K250660","page_num":12,"bbox":[67.41,61.5,567.69,767.58],"n_rows":30,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos dRF Max","LUMINOS Q.namix R",""],["","","",""],["","","",""],["","","","Q.namix R"],["Collimator","Digital Multileaf\nCollimator N","Digital Multileaf\nCollimator RFU","Changed, new\ncollimator"],["Air kerma","Kerma X","Kerma X","Same"],["CARE","Combined\nApplications to\nReduce Exposure","Combined\nApplications to\nReduce Exposure","Same"],["Touch user\ninterface on tube\nsuspension","touchscreen in portrait format","touchscreen in landscape\nformat","Changed, same touch\nuser interface as for\nreference device\nYSIO X.pree is used"],["Digital Imaging","","",""],["","","",""],["Fluoro Detector\nin table","Trixel pixium 4343F-4\n“Max Dynamic”","Trixel pixium 4343F-5\n“X.fluoro”","Changed, new version\nof the Fluoro detector"],["Fixed detector for\nwall stand","Trixell pixium 4343RCE\n“Max Static”","Trixell pixium 4343RCE\n“Max Static”","Same"],["Large mobile\ndetectors","Trixell pixium\n3543EZh „MAX wi-D“","Trixell pixium\n3543EZh „MAX wi-D“","Same"],["","N/A","Trixell pixium 3543EZ3\n“X.wi-D 35”","New, Same as for\nreference device\nYSIO X.pree."],["","N/A","Trixell pixium 4343EZ3\n“X.wi-D 43”","New, Same as for\nreference device\nYSIO X.pree."],["Small mobile\ndetector","Trixell pixium 2430EZ “MAX\nmini”","Trixell pixium 2430EZ “MAX\nmini”","Same"],["","N/A","Trixell pixium 2430EZ3\n“X.wi-D 24”","New for LUMINOS\nQ.namix R"],["Digital imaging\nsystem","Fluorospot Compact","Fluorospot Compact Plus","Changed"],["","Operating system Windows 10","Operating system Windows 10","Same"],["","Operated via mouse and\nkeyboard","Operated via touch screen","Changed"],["","Image processing with\nDiamond View Plus","Image processing with\nmyExam IQ","Slightly different,\nbased on same\nprocessing software.\nSame as for reference\ndevice YSIO X.pree."],["","N/A","AI-based Auto Cropping","New, Same as for\nreference device\nYSIO X.pree."],["","Acquisition and Image\nprocessing parameters selected\nvia Organ Programs","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Changed, same as for\nreference device\nYSIO X.pree."],["Display","19” Monitor","24” and 32” Touch Monitors","Changed, new touch\nMonitors available"],["Other Features and Components","","",""],["","","",""],["Ceiling Stand\n(Second Plane)","Ysio Max Ceiling Stand","YSIO X.pree Ceiling Stand","Changed, updated\nCeiling Stand"],["Patient Table","Table with optional bucky tray","Table with optional bucky tray","Same"],["","Standard tabletop","Standard tabletop and flat","Changed, optional flat"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p13-t0","doc_id":"K250660","page_num":13,"bbox":[65.98,61.5,569.08,355.08],"n_rows":12,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","Luminos dRF Max","LUMINOS Q.namix R",""],["","","",""],["","","",""],["","","tabletop","tabletop is now\navailable"],["Wall stand","Wall stand with fixed detector\nand wall stand with bucky tray","Wall stand with fixed detector\nand wall stand with bucky tray","Same"],["Camera","N/A","Live camera for patient\npositioning and collimation","New, Same as for\nreference device\nYSIO X.pree."],["AI based\nAutomatic\ncollimation","N/A","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","New, Same as for\nreference device\nYSIO X.pree."],["Cropping","Auto Cropping","AI-based Auto Cropping","Changed, Same AI-\nbased cropping used\nas for reference device\nYSIO X.pree."],["Indicator Lights","N/A","Indicator Light at tube stand\n(YSIO X.pree option)","New for LUMINOS\nQ.namix R"],["Mood Light","N/A","Available","New for LUMINOS\nQ.namix R"],["Foot Switch","Wired Footswitch","Wired and wireless Footswitch","New wireless foot\nswitch"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p13-t1","doc_id":"K250660","page_num":13,"bbox":[65.98,414.54,569.08,647.16],"n_rows":11,"n_cols":4,"columns":["Feature","Reference device","Subject device LUMINOS","Comment"],"rows":[["Feature","Reference device","Subject device LUMINOS","Comment"],["","YSIO X.pree","Q.namix T",""],["","","",""],["","","",""],["Camera","Live camera for patient\npositioning and collimation","Live camera for patient\npositioning and collimation","Same"],["AI based\nAutomatic\ncollimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Same"],["Cropping","AI-based Auto Cropping","AI-based Auto Cropping","Same"],["Digital imaging\nsystem","Image processing with myExam\nIQ","Image processing with\nmyExam IQ","Same"],["","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Same"],["Large mobile\ndetectors","Trixell pixium 3543EZ3 “X.wi-\nD 35”","Trixell pixium 3543EZ3 “X.wi-\nD 35”","Same"],["","Trixell pixium 4343EZ3 “X.wi-\nD 43”","Trixell pixium 4343EZ3 “X.wi-\nD 43”","Same"]],"caption_candidate":"(YSIO X.pree, K 233543)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p14-t0","doc_id":"K250660","page_num":14,"bbox":[55.76,103.5,561.99,348.18],"n_rows":11,"n_cols":4,"columns":["Feature","Reference device","Subject device LUMINOS","Comment"],"rows":[["Feature","Reference device","Subject device LUMINOS","Comment"],["","YSIO X.pree","Q.namix R",""],["","","",""],["","","",""],["Camera","Live camera for patient\npositioning and collimation","Live camera for patient\npositioning and collimation","Same"],["AI based\nAutomatic\ncollimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Auto Thorax, Auto Long-\nLeg/Full-Spine collimation","Same"],["Cropping","AI-based Auto Cropping","AI-based Auto Cropping","Same"],["Digital imaging\nsystem","Image processing with myExam\nIQ","Image processing with\nmyExam IQ","Same"],["","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Same"],["Large mobile\ndetectors","Trixell pixium 3543EZ3 “X.wi-\nD 35”","Trixell pixium 3543EZ3 “X.wi-\nD 35”","Same"],["","Trixell pixium 4343EZ3 “X.wi-\nD 43”","Trixell pixium 4343EZ3 “X.wi-\nD 43”","Same"]],"caption_candidate":"(YSIO X.pree, K 233543)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p14-t1","doc_id":"K250660","page_num":14,"bbox":[91.02,411.78,544.03,655.5],"n_rows":8,"n_cols":5,"columns":["System\nFunction","Luminos Agile","Luminos dRF","LUMINOS","LUMINOS"],"rows":[["System\nFunction","Luminos Agile","Luminos dRF","LUMINOS","LUMINOS"],["","Max (Predicate)","Max (Predicate)","Q.namix T","Q.namix R"],["Fluoroscopy\noutside of the\nExamination\nRoom","","X","","X"],["Fluoroscopy at\nthe table next to\nthe patient","X","","X",""],["Tube over the\ntable","","X","","X"],["Tube under the\ntable","X","","X",""],["Second Plane\nYSIO X.pree\n(option)","","","X","X"],["Second Plane\nYsio Max\n(option)","X","X","",""]],"caption_candidate":"Q.namix R) to Predicate Devices (Luminos dRF Max and Luminos Agile Max)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250660-p15-t0","doc_id":"K250660","page_num":15,"bbox":[62.18,153.54,544.05,703.56],"n_rows":15,"n_cols":2,"columns":["Standards Development Organization",""],"rows":[["Standards Development Organization",""],["and Reference Number","Title of Standard"],["",""],["ANSI AAMI\n60601-1, 2020 Ed. 3.2","Medical Electrical Equipment - Part 1:\nGeneral Requirements for Safety"],["IEC 60601-1-2 2020 Ed 4.1","Medical Electrical Equipment - Part 1-2: Generalrequirements for\nbasic safety and essential performance - Collateral Standard:\nElectromagnetic disturbances - Requirements and tests"],["IEC 60601-1-3:\nEdition 2.2, 2021","Medical electrical equipment - Part 1-3: General requirements for\nbasic safety and essential performance - Collateral Standard:\nRadiation protection in diagnostic X-ray equipment"],["IEC 60601-2-28, 2017","Medical electrical equipment - Part 2-28: Particular requirements\nfor the basic safety and essential performance of X-ray tube\nassemblies for medical diagnosis"],["IEC 60601-2-54\n2018, Edition 1.2","Medical electrical equipment - Part 2-54: Particular requirements\nfor the basic safety and essential performance of X-ray equipment\nfor radiography and radioscopy"],["IEC 60601-1-6\n2020 Ed 3.2","Medical electrical equipment – Part 1-6: General requirements for\nbasic safety and essential performance – Collateral standard:\nUsability"],["IEC 62366-1 2020 Ed 1.1","Medical devices – Application of usability engineering tomedical\ndevices"],["ISO 14971: 2019","Medical devices – application of risk management tomedical\ndevices"],["IEC 62304 2015, Ed.1.1","Medical device software - Software life cycle processes"],["IEC 61910-1: 2014, Ed 1.0","Medical electrical equipment - Radiation dose documentation -\nPart 1: Radiation dose structured reports for radiography and\nradioscopy"],["NEMA PS 3.1 - 3.20 2023e","Digital Imaging and Communications in Medicine(DICOM) Set"],["ISO EN ISO 10993-1\nFifth edition 2018","Biological evaluation of medical devices – Part1: Evaluation and\ntesting within a risk management process"]],"caption_candidate":"Table 8. Non-clinical performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p5-t0","doc_id":"K250662","page_num":5,"bbox":[72.65,285.62,405.58,356.9],"n_rows":5,"n_cols":4,"columns":["","Proprietary Name","","Bunkerhill MAC"],"rows":[["","Proprietary Name","","Bunkerhill MAC"],["","Classification Name","","Computed tomography x-ray system"],["","Regulation Number","","21 CFR 892.1750"],["","Product Code","","JAK"],["Regulatory Class","","","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p5-t1","doc_id":"K250662","page_num":5,"bbox":[72.65,398.29,405.58,484.67],"n_rows":6,"n_cols":4,"columns":["","Proprietary Name","","Bunkerhill AVC"],"rows":[["","Proprietary Name","","Bunkerhill AVC"],["","Premarket Notification","","K243229"],["","Classification Name","","Computed tomography x-ray system"],["","Regulation Number","","21 CFR 892.1750"],["","Product Code","","JAK"],["","Regulatory Class","","II"]],"caption_candidate":"Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p7-t0","doc_id":"K250662","page_num":7,"bbox":[23.45,72.36,588.77,713.38],"n_rows":3,"n_cols":10,"columns":["","","Proposed Device:","","","Predicate Device: Bunkerhill","","","Predicate Device: iCAC",""],"rows":[["","","Proposed Device:","","","Predicate Device: Bunkerhill","","","Predicate Device: iCAC",""],["","","Bunkerhill MAC","","","AVC (K243229)","","","(K230223)",""],["","contrast chest computed\ntomography (CT) images\ncollected during clinical care\nand outputs the region of\ninterest (intended for\ninformational purposes only)\nand quantification of detected\ncalcium.\nThe device-generated\nquantification can be viewed in\nthe patient report at the\ndiscretion of the physician, and\nthe physician also has the\noption of viewing the device-\ngenerated calcium region of\ninterest in a diagnostic image\nviewer. The subject device\noutput in no way replaces the\noriginal patient report or the\noriginal non-gated, non-\ncontrast CT scan; both are still\navailable to be viewed and used\nat the discretion of the\nphysician.\nThe device is intended to\nprovide information to the\nphysician to provide assistance\nduring review of the patient’s\ncase. Results of the subject\ndevice are not intended to be\nused on a stand-alone basis and\nare solely intended to aid and\nprovide information to the\nphysician. In all cases, further\naction taken on a patient should\nonly come at the\nrecommendation of the","","","gated, non- contrast chest\ncomputed tomography (CT)\nimages collected during\nclinical care and outputs the\nregion of interest (intended\nfor informational purposes\nonly) and quantification of\ndetected calcium.\nThe output of the subject\ndevice is made available to\nthe physician on-demand as\npart of his or her standard\nworkflow. The device-\ngenerated quantification can\nbe viewed in the patient\nreport at the discretion of the\nphysician, and the physician\nalso has the option of\nviewing the device-\ngenerated calcium region of\ninterest in a diagnostic\nimage viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or\nthe original non-gated, non-\ncontrast CT scan; both are\nstill available to be viewed\nand used at the discretion\nof the physician.\nThe device is intended to\nprovide information to the\nphysician to provide assistance\nduring review of the patient’s\ncase. Results of the subject\ndevice are not intended to be\nused on a stand- alone basis and\nare solely intended to aid and\nprovide information to the\nphysician. In all cases, further\naction taken on a patient should","","","automatically analyzes\nnon- gated, non-contrast\nchest computed\ntomography (CT) images\ncollected during routine\ncare and outputs a visual\nrepresentation of\nestimated coronary artery\ncalcium segmentation\n(intended for\ninformational purposes\nonly) and both exact and\nfour-category\nquantitative estimates of\nthe patient’s coronary\nartery calcium burden in\nAgatston units.\nThe output of the subject\ndevice is made available\nto the physician on-\ndemand as part of his or\nher standard workflow.\nThe device generated\ncalcium score or score\ngroup can be viewed in\nthe patient report at the\ndiscretion of the\nphysician, and the\nphysician also has the\noption of viewing the\ndevice- generated calcium\nsegmentation in a\ndiagnostic image viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or\nthe original chest CT\nscan; both are still\navailable to be viewed and\nused at the discretion of\nthe physician.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p8-t0","doc_id":"K250662","page_num":8,"bbox":[23.45,72.36,588.77,337.73],"n_rows":3,"n_cols":10,"columns":["","","Proposed Device:","","","Predicate Device: Bunkerhill","","","Predicate Device: iCAC",""],"rows":[["","","Proposed Device:","","","Predicate Device: Bunkerhill","","","Predicate Device: iCAC",""],["","","Bunkerhill MAC","","","AVC (K243229)","","","(K230223)",""],["","physician after further\nreviewing the patient’s results.","","","only come at the\nrecommendation of the\nphysician after further\nreviewing the patient’s results.","","","The device is intended to\nprovide information to the\nphysician to provide\nassistance during review of\nthe patient’s case. Results of\nthe subject device are not\nintended to be used on a\nstand-alone basis and are\nsolely intended to aid and\nprovide information to the\nphysician. In all cases,\nfurther action taken on a\npatient should only come at\nthe recommendation of the\nphysician after further\nreviewing the patient’s\nresults.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p9-t0","doc_id":"K250662","page_num":9,"bbox":[23.41,230.48,588.83,709.54],"n_rows":14,"n_cols":7,"columns":["","Proposed Device:\nBunkerhill MAC","","Predicate Device:","","Predicate Device: iCAC\n(K230223)","Summary"],"rows":[["","Proposed Device:\nBunkerhill MAC","","Predicate Device:","","Predicate Device: iCAC\n(K230223)","Summary"],["","","","Bunkerhill AVC","","",""],["","","","(K243229)","","",""],["Product code","JAK","JAK","","","JAK","Same"],["Regulation number","21 CFR §892.1750","21 CFR §892.1750","","","21 CFR §892.1750","Same"],["Modality","Computed tomography (CT)","Computed tomography (CT)","","","Computed tomography\n(CT)","Same"],["Image format","DICOM","DICOM","","","DICOM","Same"],["Contrast","Non-contrast","Non-contrast","","","Non-contrast","Same"],["Supported CT scan","Non-cardiac-gated CT scan","Non-cardiac-gated CT scan","","","Non-cardiac-gated CT\nscan","Same"],["Slice thickness","Up to 5 mm","Up to 5 mm","","","Up to 5 mm","Same"],["Calcification\ndetection","Automatic","Automatic","","","Automatic","Same"],["Main image quality","DICOM","DICOM","","","DICOM","Same"],["Annotation of\ndetected calcium","Yes","Yes","","","Yes","Same"],["Visual Output\nformat","Visual output in the form a\nRegion of Interest or ROI\n(intended for informational\npurposes only). The\nestimated visual output can\nbe viewed by the physician\nin a diagnostic image viewer.\nThe physician’s standard\nmethod for viewing\nunaltered chest CT scans in\nPACS will remain available\nto them even if the subject\ndevice is being used.\nHowever, the physician will\nalso have an option to view\nthe visual output estimated","Visual output in the form a\nRegion of Interest or ROI\n(intended for informational\npurposes only). The\nestimated visual output can\nbe viewed by the physician\nin a diagnostic image\nviewer. The physician’s\nstandard method for\nviewing unaltered chest CT\nscans in PACS will remain\navailable to them even if the\nsubject device is being used.\nHowever, the physician will\nalso have an option to view\nthe visual output estimated\nby the subject device as a","","","Outputs a visual\nrepresentation of\nestimated coronary artery\ncalcium segmentation\n(intended for\ninformational purposes\nonly). The estimated\ncalcium segmentation can\nbe viewed by the\nphysician in a diagnostic\nimage viewer. The\nphysician’s standard\nmethod for viewing\nunaltered chest CT scans\nin PACS will remain\navailable to them even if\nthe subject device is","Same"]],"caption_candidate":"subject and predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250662-p10-t0","doc_id":"K250662","page_num":10,"bbox":[23.41,72.36,588.82,509.11],"n_rows":13,"n_cols":7,"columns":["","Proposed Device:\nBunkerhill MAC","","Predicate Device:","","Predicate Device: iCAC\n(K230223)","Summary"],"rows":[["","Proposed Device:\nBunkerhill MAC","","Predicate Device:","","Predicate Device: iCAC\n(K230223)","Summary"],["","","","Bunkerhill AVC","","",""],["","","","(K243229)","","",""],["","by the subject device as a\nseparate series within PACS.","separate series within\nPACS.","","","being used. However, the\nphysician will also have\nan option to view the\ncalcium segmentation\nestimated by the subject\ndevice as a separate series\nwithin PACS.",""],["Generate patient\nreport","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","","","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary\nCapture","Same"],["Report of the\ncalcium score","Yes, estimated exact\nAgatston-equivalent score\nand binary output\n(presence/absence)","Yes, estimated exact\nAgatston-equivalent score\nand binary output\n(presence/absence)","","","Yes, Coronary\nCalcium Detection\nCategory and exact\nAgatston score\n4 detection categories","Same"],["Type of\nInterpretation","Adjunctive information","Adjunctive information","","","Adjunctive\ninformation","Same"],["Intended User","Qualified medical\nprofessionals such as\ncardiologists or radiologists","Qualified medical\nprofessionals such as\ncardiologists or radiologists","","","Interpreting\nphysicians","Same"],["Patient population","Patients aged 40 years and\nabove","Patients above the age of 40","","","Patients above the age of\n30","Same"],["Anatomical\nlocation","Chest (mitral annulus)","Chest (aortic valve)","","","Chest","Similar"],["Intended location","Medical facility","Medical facility","","","Medical facility","Same"],["Rx or OTC","Rx","Rx","","","Rx","Same"],["Measurement scale","Agatston-equivalent units","Agatston-equivalent units","","","Agatston units","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250670-p5-t0","doc_id":"K250670","page_num":5,"bbox":[22.68,346.18,592.79,395.86],"n_rows":3,"n_cols":2,"columns":["","mike@hardianhealth.com"],"rows":[["","mike@hardianhealth.com"],["Device Name 21 CFR 807.92(a)(2)",""],["",""]],"caption_candidate":"Correspondent Contact Mr. Michael Pogose","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250670-p5-t1","doc_id":"K250670","page_num":5,"bbox":[22.68,515.4,592.79,565.06],"n_rows":3,"n_cols":2,"columns":["","QIH"],"rows":[["","QIH"],["Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)",""],["",""]],"caption_candidate":"Regulation Number 892.2050","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250670-p5-t2","doc_id":"K250670","page_num":5,"bbox":[22.68,619.75,592.79,765.6],"n_rows":7,"n_cols":2,"columns":["K191171","QIH"],"rows":[["K191171","QIH"],["Device Description Summary 21 CFR 807.92(a)(4)",""],["",""],["in reviewing the images, making measurements and writing a report.",""],["Intended Use/Indications for Use 21 CFR 807.92(a)(5)",""],["",""],["in reviewing the images, making measurements and writing a report.",""]],"caption_candidate":"K210791 us2ai QIH","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p7-t0","doc_id":"K250685","page_num":7,"bbox":[72.48,157.2,522.48,758.16],"n_rows":5,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison Feature","Predicate Device: Rapid NCCT Stroke","Subject Device: Methinks NCCT Stroke"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["","Rapid NCCT Stroke is a radiological computer\naided triage and notification software indicated\nfor use in the analysis of (1) nonenhanced head\nCT (NCCT) images. The device is intended to\nassist hospital networks and trained clinicians in\nworkflow triage by flagging and communicating\nsuspected positive findings of (1) head CT\nimages for Intracranial\nHemorrhage (ICH) and (2) NCCT large vessel\nocclusion (LVO) of the ICA and MCA-M1.\nRapid NCCT Stroke uses an artificial\nintelligence algorithm to analyze images and\nhighlight cases with detected (1) ICH\nor (2) NCCT LVO on the Rapid server on\npremise or in the cloud in parallel to the ongoing\nstandard of care image interpretation. The user\nis presented with notifications for cases with\nsuspected ICH or LVO findings via PACS, email\nor mobile device. Notifications include\ncompressed preview images that are meant for\ninformational purposes only, and are not\nintended for diagnostic use beyond notification.\nThe device does not alter the original medical\nimage, and it is not intended to be used as a\nprimary diagnostic device. The results of Rapid\nNCCT Stroke are intended to be used in\nconjunction with other patient information and\nbased on professional judgment to assist with\ntriage/prioritization of medical images. Notified\nclinicians are ultimately responsible for\nreviewing full images per the standard of care.\nRapid NCCT Stroke is for Adults only.\nCautions:\n● All patients should get adequate care for\ntheir symptoms including CTA and/or\nother appropriate care per the standard\nclinical practice, irrespective of the device\noutput\n● The device is not intended to be a rule-out\ndevice and for cases that have been\nprocessed by the device without\nnotification for “Suspected LVO” should\nnot be viewed as indicating that LVO is\nexcluded. All cases should undergo CTA,\nper the standard stroke workup.\nLimitations:\n● Rapid NCCT Stroke does not replace the\nneed for CTA or MRA in ischemic stroke\nworkup, it provides workflow prioritization\nand notification only.","Methinks NCCT Stroke is a radiological\ncomputer aided triage and notification software\nindicated for use in the analysis of (1) non-\ncontrast head CT (NCCT) images. The device is\nintended to assist hospital networks and trained\nclinicians in workflow triage by flagging and\ncommunicating suspected positive findings of\n(1) Intracranial Hemorrhage (ICH) and (2) Large\nVessel Occlusion (LVO) of the ICA, MCA-M1\nand MCA-M2.\nMethinks NCCT Stroke uses an artificial\nintelligence algorithm to analyze images and\nhighlight cases with detected (1) ICH and (2)\nLVO in the cloud in parallel to the ongoing\nstandard of care image interpretation. The user\nis presented with notifications for cases with\nsuspected ICH or LVO findings via PACS and/or\nnotifications. Notifications include preview\nimages that are meant for informational\npurposes only, and are not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original medical\nimage, and it is not intended to be used as a\nprimary diagnostic device. The results of\nMethinks NCCT Stroke are intended to be used\nin conjunction with other patient information and\nbased on professional judgment to assist with\ntriage/prioritization of medical images. Notified\nclinicians are ultimately responsible for\nreviewing full images per the standard of care.\nMethinks NCCT Stroke is for adults only.\nCautions:\n● All patients should get adequate care for\ntheir symptoms including CTA and/or\nother appropriate care per the standard\nclinical practice, irrespective of the device\noutput.\n● The device is not intended to be a rule-out\ndevice and for cases that have been\nprocessed by the device without\nnotification for “LVO Suspected” should\nnot be viewed as indicating that LVO is\nexcluded. All cases should undergo CTA,\nper the standard stroke workup.\nLimitations:\n• The device does not replace the need\nfor CTA in ischemic stroke workup, it\nprovides workflow prioritization and\nnotification only."]],"caption_candidate":"Table 1. Substantial Equivalence Table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p8-t0","doc_id":"K250685","page_num":8,"bbox":[72.48,72.48,522.48,490.08],"n_rows":12,"n_cols":3,"columns":["","● Rapid ICH has been shown to reliably\nidentify hemorrhages of ≥ 0.4ml.\nContraindications/Exclusions\n● Patient Motion: excessive motion leading\nto artifacts that make the scan technically\ninadequate.\n● Hemorrhagic Transformation, Hematoma\n● Very thin or no Ventricles.",""],"rows":[["","● Rapid ICH has been shown to reliably\nidentify hemorrhages of ≥ 0.4ml.\nContraindications/Exclusions\n● Patient Motion: excessive motion leading\nto artifacts that make the scan technically\ninadequate.\n● Hemorrhagic Transformation, Hematoma\n● Very thin or no Ventricles.",""],["User","Trained Clinicians","Trained Physicians"],["Anatomy","Head","Head"],["Input Data","NCCT images","NCCT images"],["Technology","AI/ML/Neural Network","AI/ML/Neural Network"],["Segmentation of ROI","The device does not highlight or direct a user’s\nattention to a specific location in the image file.","The device does not highlight or direct a user’s\nattention to a specific location in the image file."],["Preview Images","Presentation of a preview of the study for initial\nassessment not meant for diagnostic purposes.\nThe device operates in parallel with the standard\nof care.","Presentation of a preview of the study for initial\nassessment not meant for diagnostic purposes.\nThe device operates in parallel with the standard\nof care."],["Annotation/Localization","Device does not mark, highlight, or direct users’\nattention to a specific location in the original\nimage.","Device does not mark, highlight, or direct users’\nattention to a specific location in the original\nimage."],["Prioritization\nNotification","Yes","Yes"],["Clinical SoC Workflow","In parallel to","In parallel to"],["Technical Pipeline","Two cascaded functions (ICH then LVO) using\nthree integrated algorithms.","Single algorithm with two different outputs (ICH\nand LVO)."],["Removal of Cases\nfrom SoC review","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p9-t0","doc_id":"K250685","page_num":9,"bbox":[72.35,331.44,522.01,437.52],"n_rows":5,"n_cols":3,"columns":["","Sensitivity (95% CI)","Specificity (95% CI)"],"rows":[["","Sensitivity (95% CI)","Specificity (95% CI)"],["Methinks NCCT-LVO","73.6% (59.7% - 84.7%)","89.1% (82.0% - 94.1%)"],["R1 + R2 (Experts)","50.0% (40.1% - 59.9%)","92.0% (87.8% - 95.1%)"],["R3 + R4 (Non-experts)","37.7% (28.5% - 47.7%)","87.4% (82.5% - 91.3%)"],["R1 + R2 + R3 + R4 (All)","43.9% (37.1% - 50.8%)","89.7% (86.6% - 92.3%)"]],"caption_candidate":"Table 2. Performance of the readers vs Methinks NCCT-LVO in the reader study.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p9-t1","doc_id":"K250685","page_num":9,"bbox":[72.35,534.72,522.01,595.44],"n_rows":3,"n_cols":4,"columns":["Parameter","Mean","95% CI Lower","95% CI Upper"],"rows":[["Parameter","Mean","95% CI Lower","95% CI Upper"],["Time to notification of NCCT-ICH (minutes)","1.43","1.36","1.50"],["Time to notification of NCCT-LVO (minutes)","1.42","1.36","1.48"]],"caption_candidate":"Table 3. Time to notification of Methinks NCCT Stroke.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p9-t2","doc_id":"K250685","page_num":9,"bbox":[72.35,709.92,522.01,750.48],"n_rows":2,"n_cols":6,"columns":["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Male","Sensitivity","76","97.4%","90.8%","99.7%"]],"caption_candidate":"Table 4. performance metrics NCCT-ICH by Gender.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p10-t0","doc_id":"K250685","page_num":10,"bbox":[72.48,72.48,523.92,173.52],"n_rows":5,"n_cols":6,"columns":["","Specificity","119","99.2%","95.4%","100.0%"],"rows":[["","Specificity","119","99.2%","95.4%","100.0%"],["Female","Sensitivity","55","90.9%","80.0%","97.0%"],["","Specificity","107","100.0%","96.6%","100.0%"],["Unspecified","Sensitivity","1","100.0%","2.5%","100.0%"],["","Specificity","0","-","-","-"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p10-t1","doc_id":"K250685","page_num":10,"bbox":[72.48,198.24,523.92,339.6],"n_rows":7,"n_cols":6,"columns":["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["< 50 years","Sensitivity","17","94.1%","71.3%","99.9%"],["","Specificity","43","97.7%","87.7%","99.9%"],["50 - 70 years","Sensitivity","53","98.1%","89.9%","100.0%"],["","Specificity","98","100.0%","96.3%","100.0%"],["> 70 years","Sensitivity","62","91.9%","82.2%","97.3%"],["","Specificity","85","100.0%","95.8%","100.0%"]],"caption_candidate":"Table 5. performance metrics NCCT-ICH by Age.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p10-t2","doc_id":"K250685","page_num":10,"bbox":[72.48,364.56,523.92,549.36],"n_rows":7,"n_cols":6,"columns":["Slice Thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Slice Thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["1mm ≤ Slice\nThickness <\n2.5mm","Sensitivity","37","97.3%","85.8%","99.9%"],["","Specificity","77","98.7%","93.0%","100.0%"],["2.5mm ≤ Slice\nThickness <\n4mm*","Sensitivity","30","83.3%","65.3%","94.4%"],["","Specificity","36","97.2%","85.5%","99.9%"],["4mm ≤ Slice\nThickness ≤\n5.5mm","Sensitivity","95","93.7%","86.8%","97.6%"],["","Specificity","149","100.0%","97.6%","100.0%"]],"caption_candidate":"Table 6. performance metrics NCCT-ICH by Slice Thickness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p10-t3","doc_id":"K250685","page_num":10,"bbox":[72.48,585.36,523.92,767.28],"n_rows":9,"n_cols":6,"columns":["Vendor Machine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Vendor Machine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Siemens","Sensitivity","83","92.8%","84.9%","97.3%"],["","Specificity","146","100.0%","97.5%","100.0%"],["General Electric*","Sensitivity","48","93.8%","85.7%","97.5%"],["","Negatives","22","100.0%","84.6%","100.0%"],["Philips","Sensitivity","47","97.9%","88.7%","99.9%"],["","Specificity","80","98.8%","93.2%","100.0%"],["Toshiba / Canon*","Sensitivity","12","100.0%","73.5%","100.0%"],["","Negatives","7","85.7%","42.1%","99.6%"]],"caption_candidate":"Table 7. performance metrics NCCT-ICH by Vendor Machine.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p11-t0","doc_id":"K250685","page_num":11,"bbox":[72.48,110.4,523.92,261.12],"n_rows":7,"n_cols":6,"columns":["Hemorrhage\nvolume","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Hemorrhage\nvolume","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Smaller than 1 ml","Sensitivity","10","80.0%","44.4%","97.5%"],["","Specificity","0","-","-","-"],["Between 1 ml and\n5 ml","Sensitivity","50","92.0%","80.8%","97.8%"],["","Specificity","0","-","-","-"],["Bigger than 5 ml","Sensitivity","95","96.8%","91.0%","99.3%"],["","Specificity","0","-","-","-"]],"caption_candidate":"Table 8. performance metrics NCCT-ICH by hemorrhage volume.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p11-t1","doc_id":"K250685","page_num":11,"bbox":[72.48,281.52,523.92,512.88],"n_rows":11,"n_cols":6,"columns":["Hemorrhage sub\ntype","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Hemorrhage sub\ntype","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Epidural\nhemorrhage*","Sensitivity","3","100.0%","29.2%","100.0%"],["","Specificity","0","-","-","-"],["Subdural\nhemorrhage*","Sensitivity","21","85.7%","63.7%","97.0%"],["","Specificity","0","-","-","-"],["Subarachnoid\nhemorrhage","Sensitivity","13","92.3%","64.0%","99.8%"],["","Specificity","0","-","-","-"],["Intraparenchymal\nhemorrhage","Sensitivity","112","97.3%","92.4%","99.4%"],["","Specificity","0","-","-","-"],["Intraventricular\nhemorrhage","Sensitivity","27","100.0%","87.2%","100.0%"],["","Specificity","0","-","-","-"]],"caption_candidate":"Table 9. performance metrics NCCT-ICH by hemorrhage sub-type.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p11-t2","doc_id":"K250685","page_num":11,"bbox":[72.48,582.48,523.92,683.52],"n_rows":5,"n_cols":6,"columns":["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Female","Sensitivity","56","76.8%","63.6%","87.0%"],["","Specificity","109","93.6%","87.2%","97.4%"],["Male","Sensitivity","54","75.9%","62.4%","86.5%"],["","Specificity","116","88.8%","81.6%","93.9%"]],"caption_candidate":"Table 10. performance metrics NCCT-LVO by Gender.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p12-t0","doc_id":"K250685","page_num":12,"bbox":[72.48,84.48,523.92,225.84],"n_rows":7,"n_cols":6,"columns":["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["< 50","Sensitivity","7","85.7%","42.1%","99.6%"],["","Specificity","38","100.0%","90.7%","100.0%"],["50 - 70","Sensitivity","43","74.4%","58.8%","86.5%"],["","Specificity","103","91.3%","84.1%","95.9%"],["> 70","Sensitivity","60","76.7%","64.0%","86.6%"],["","Specificity","84","86.9%","77.8%","93.3%"]],"caption_candidate":"Table 11. performance metrics NCCT-LVO by Age.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p12-t1","doc_id":"K250685","page_num":12,"bbox":[72.48,250.56,523.92,423.12],"n_rows":7,"n_cols":6,"columns":["Slice Thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Slice Thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["1mm ≤ Slice\nThickness <\n2.5mm","Sensitivity","25","72.0%","50.6%","87.9%"],["","Specificity","78","91.0%","82.4%","96.3%"],["2.5mm ≤ Slice\nThickness < 4mm","Sensitivity","35","77.1%","59.9%","89.6%"],["","Specificity","45","84.4%","70.5%","93.5%"],["4mm ≤ Slice\nThickness ≤\n5.5mm","Sensitivity","50","78.0%","64.0%","88.5%"],["","Specificity","102","94.1%","87.6%","97.8%"]],"caption_candidate":"Table 12. performance metrics NCCT-LVO by Slice Thickness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p12-t2","doc_id":"K250685","page_num":12,"bbox":[72.48,450.48,523.92,632.4],"n_rows":9,"n_cols":6,"columns":["Vendor Machine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Vendor Machine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Siemens","Sensitivity","36","75.0%","57.8%","87.9%"],["","Specificity","86","96.5%","90.1%","99.3%"],["General Electric","Sensitivity","19","73.7%","48.8%","90.9%"],["","Specificity","28","82.1%","63.1%","93.9%"],["Philips","Sensitivity","34","76.5%","58.8%","89.3%"],["","Specificity","82","86.6%","77.3%","93.1%"],["Toshiba / Canon","Sensitivity","21","81.0%","58.1%","94.6%"],["","Specificity","29","96.6%","82.2%","99.9%"]],"caption_candidate":"Table 13. performance metrics NCCT-LVO by Vendor Machine.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p12-t3","doc_id":"K250685","page_num":12,"bbox":[72.48,659.76,523.92,760.8],"n_rows":5,"n_cols":6,"columns":["LVO Subgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["LVO Subgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["ICA","Sensitivity","36","77.8%","60.8%","89.9%"],["","Specificity","0","-","-","-"],["MCA-M1","Sensitivity","44","88.6%","75.4%","96.2%"],["","Specificity","0","-","-","-"]],"caption_candidate":"Table 14. performance metrics NCCT-LVO by LVO subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p13-t0","doc_id":"K250685","page_num":13,"bbox":[72.48,72.48,523.42,193.68],"n_rows":6,"n_cols":6,"columns":["ICA + MCA-M1\n(as predicate)","Sensitivity","77","83.1%","72.9%","90.7%"],"rows":[["ICA + MCA-M1\n(as predicate)","Sensitivity","77","83.1%","72.9%","90.7%"],["","Specificity","0","-","-","-"],["MCA-M2","Sensitivity","25","68.0%","46.5%","85.1%"],["","Specificity","0","-","-","-"],["LVO without\nischemia","Sensitivity","33","42.4%","25.5%","60.8%"],["","Specificity","0","-","-","-"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p13-t1","doc_id":"K250685","page_num":13,"bbox":[72.48,285.84,523.42,407.04],"n_rows":6,"n_cols":2,"columns":["Output","Sensitivity (95% CI)"],"rows":[["Output","Sensitivity (95% CI)"],["Methinks NCCT-LVO","38.8% (17.3% - 64.3%)"],["Radiologist 1","33.3% (13.3% - 59.0%)"],["Radiologist 2","22.2% (6.4% - 47.6%)"],["Radiologist 3","16.6% (3.6% - 41.4%)"],["Radiologist 4","11.1% (1.4% - 34.7%)"]],"caption_candidate":"subgroup.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250685-p13-t2","doc_id":"K250685","page_num":13,"bbox":[72.48,432.0,523.42,703.68],"n_rows":13,"n_cols":6,"columns":["Non-LVO\nSubgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Non-LVO\nSubgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Tumors","Sensitivity","0","-","-","-"],["","Specificity","2","50.0%","1.3%","98.7%"],["Stenosis > 51%","Sensitivity","0","-","-","-"],["","Specificity","28","85.7%","67.3%","96.0%"],["Intracranial\nHemorrhage\n(ICH)","Sensitivity","0","-","-","-"],["","Specificity","3","100.0%","29.2%","100.0%"],["Other Acute\nIschemic Events","Sensitivity","0","-","-","-"],["","Specificity","62","79.0%","66.8%","88.3%"],["Chronic Lesions","Sensitivity","0","-","-","-"],["","Specificity","104","89.4%","81.9%","94.6%"],["No Findings\n(none of the\nabove)","Sensitivity","0","-","-","-"],["","Specificity","160","95.6%","91.2%","98.2%"]],"caption_candidate":"Table 16. performance metrics NCCT-LVO by non-LVO subgroups.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p5-t0","doc_id":"K250686","page_num":5,"bbox":[72.21,204.0,391.56,369.72],"n_rows":7,"n_cols":2,"columns":["Company Name","NeuroSpectrum Insights Corp."],"rows":[["Company Name","NeuroSpectrum Insights Corp."],["Address","376 Main St. Suite 100, Bedminster NJ 07921"],["Phone Number","908-304-4858"],["Company Representative","Andrew D. Stewart, CEO"],["Official Correspondent","James Luker, Innolitics"],["Email","JLuker@Innolitics.com"],["Date Prepared","March 2, 2025"]],"caption_candidate":"1. CONTACT INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p5-t1","doc_id":"K250686","page_num":5,"bbox":[72.21,415.8,391.56,557.88],"n_rows":6,"n_cols":2,"columns":["Trade Name","GyriCalc"],"rows":[["Trade Name","GyriCalc"],["Common Name","Neuroanatomy measuring software"],["Product Code","LLZ"],["Regulation Number","892.2050"],["Class","Class II"],["Panel","Radiology"]],"caption_candidate":"2. DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p5-t2","doc_id":"K250686","page_num":5,"bbox":[72.21,603.96,391.56,698.64],"n_rows":4,"n_cols":2,"columns":["Predicate Device Name","NeuroQuant"],"rows":[["Predicate Device Name","NeuroQuant"],["Predicate Device K Number","K170981"],["Product Code","LLZ"],["Regulation Number","892.2050"]],"caption_candidate":"3. PREDICATE DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p6-t0","doc_id":"K250686","page_num":6,"bbox":[72.12,158.4,391.56,205.8],"n_rows":2,"n_cols":2,"columns":["Class","Class II"],"rows":[["Class","Class II"],["Panel","Radiology"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p9-t0","doc_id":"K250686","page_num":9,"bbox":[72.2,228.24,539.76,686.88],"n_rows":9,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same"],["Regulation\nDescription","Medical image\nmanagement and\nprocessing system","Picture archiving and\ncommunications system","Same"],["Classification\nName","System, Image Processing,\nRadiological","System, Image Processing,\nRadiological","Same"],["Class","Class II","Class II","Same"],["Product Code","LLZ","LLZ","Same"],["Device\nDescription\nDevice type","Software medical device\n(SaMD)","Software medical device\n(SaMD)","Same- Both devices are SaMD"],["Physical\ncharacteristics","• Software package\n• Operates on off-the-shelf\nhardware (multiple\nvendors)","• Software package\n• Operates on off-the-shelf\nhardware (multiple\nvendors)","Same"],["Operating System","Client: Supports Windows\n11 or MAC OS 12\nServer: Ubuntu 23.04 LTS","Supports Linux, Mac OS X\nand Windows","Equivalent-\nBoth the subject and predicate devices\nare software devices (SaMD) which run\non industry standard computing\nhardware and Operating Systems. The\nGyriCalc device has been tested to\nconfirm that it meets it’s stated\nrequirements and performs as intended\non the stated operating system(s).\nGyriCalc does not support the Linux\nOS. This difference does not affect the\nsafety or effectiveness as compared to\nthe NeuroQuant predicate device."]],"caption_candidate":"6.1. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p10-t0","doc_id":"K250686","page_num":10,"bbox":[72.14,158.4,539.76,714.84],"n_rows":3,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["General Device\nDescription","Fully automated MR\nimaging post-processing\nmedical device software\nwhich includes:\n-automatic labeling,\nvisualization and\nvolumetric quantification\nof brain structures from a\nset of MR images and\nreturns segmented images\nand morphometric reports.\n(Morphometric\nmeasurements based on\n3D T1 MRI series)","Fully automated MR imaging\npost-processing medical\ndevice software which\nincludes:\n-automatic labeling,\nvisualization and volumetric\nquantification of brain and\nlesions from a set of MR\nimages and returns segmented\nimages and morphometric\nreports.\n(Morphometric measurements\nbased on 3D T1 MRI series)","Equivalent-\nThe primary functionality is the same\nwith the exception that the subject\nGyriCalc device does not include lesion\nlabeling or volumetric quantification of\nsuch lesions.\nAs lesion detection is not intended to be\nperformed by GyriCalc, its absence\ndoes not affect Intended Use, safety or\neffectiveness comparison of the subject\nand predicate devices.\nThe subject device measurements\ninclude volume, area and gyrification\nwhereas the predicate device provides\nonly volume measurement. The\naddition of area and gyrification\nmeasurements are considered\ntechnological characteristics which are\nsupported by clinical performance\ntesting. As the area and gyrification are\nalso measurements, they do not add a\nnew ‘intended use’ and do not affect the\nsafety and/or effectiveness of the\nsubject device as compared to the\npredicate device or raise new questions\nrelating to safety and/or effectiveness."],["Design and\nIncorporated\nTechnology","- Automated measurement\nof brain tissue structures\nfor volume, area and\ngyrification.\n- Automatic segmentation\nand\nquantification of brain\nstructures using deep\nlearning","• Automated measurement of\nbrain tissue volumes and\nstructures and lesions\n• Automatic segmentation and\nquantification of\nbrain structures using a\ndynamic probabilistic\nneuroanatomical atlas, with\nage and gender specificity,\nbased on the MR image\nintensity","Equivalent-\nThe design and technological\ncharacteristics of the subject GyriCalc\ndevice and the predicate NeuroQuant\ndevice are equivalent. Both devices are\nsoftware medical devices (SaMD) and\nutilize DICOM MRI images of the\nbrain which are automatically\nsegmented into regions and then\nperform measurements.\nThe subject device measurements\ninclude volume, area and gyrification\nwhereas the predicate device provides\nonly volume measurement. The\naddition of area and gyrification are\nconsidered technologic characteristics\nwhich are supported by clinical\nperformance testing. As the area and"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p11-t0","doc_id":"K250686","page_num":11,"bbox":[72.14,158.4,539.76,714.84],"n_rows":3,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["","","","gyrification are also measurements,\nthey do not add a new ‘intended use’\nand do not affect the safety and/or\neffectiveness of the subject device as\ncompared to the predicate device or\nraise new questions relating to safety\nand/or effectiveness.\nDifferences:\n-GyriCalc does not include lesion\nquantification functionality whereas the\nNeuroQuant predicate does. Lesion\nquantification functionality is not an\naspect of GyriCalc’s intended use and\ndoes not affect the safety or\neffectiveness as compared to the\npredicate device.\n-GyriCalc’s automated segmentation\nutilizes FreeSurfer’s robust SynthSeg\nalgorithm whereas the predicate device\nuses a dynamic probabalistic\nneuroanatomical atlas for its automated\nsegmentation functionality. GyriCalc’s\nsegmentation results have been\nvalidated using an ‘expert reader’ study.\nNote: NEUROPHET (K220437) has\nbeen added as a Reference device to\nsupport the technological characteristic\nof the use of FreeSurfer for\nsegmentation initialization. A separate\ncomparison table is provided for the\nreference device.\n- GyriCalc does not include gender\nspecificity. Gender specificity is not\nnecessary for GyriCalc to perform its its\nintended use in a safe and effective\nmanner.\nThe differences do not affect the safety\nor effectiveness as compared to the\npredicate device and are supported by\nclinical performance testing."],["Processing\nArchitecture","Automated internal\npipeline that performs:","Automated internal pipeline\nthat performs:","Equivalent -\nThe subject device and the predicate"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p12-t0","doc_id":"K250686","page_num":12,"bbox":[72.16,158.4,539.76,710.16],"n_rows":4,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["","- artifact correction\n- segmentation\n- volume calculation\n- gyrification analysis\n- report generation","- artifact correction\n- segmentation\n- lesion quantification\n- volume calculation\n- report generation","have similar processing architectures,\nwith the exception that the subject\ndevice also uses gyrification analysis\nfor measuring Local Gyrification Index\n(LGI). This additional technological\ncharacteristic (i.e., gyrification analysis)\ndoes not raise different questions of\nsafety and effectiveness. The\nfunctionality has been supported by\nperformance testing.\nAdditionally, as previously stated,\nGyriCalc does not include lesion\nquantification as it is not within the\nscope of its intended use/indications."],["Data Source","• MRI scanner: 3D T1\nMRI scans acquired with\nspecified protocols from\n1.5 and 3 Tesla MR\nimaging devices.\n• GyriCalc supports\nDICOM format as input","• MRI scanner: 3D T1 MRI\nscans acquired with\nspecified protocols\n• NeuroQuant Supports\nDICOM format as input","Equivalent\nGyriCalc performance has been\nsuccessfully tested on DICOM images\nfrom 1.5 and 3.0 Tesla MR imaging\ndevices. The available information on\nthe NeuroQuant predicate device does\nnot appear to specify the magnet\nstrength. However, the following note\nin the NeuroQuant Clinical Training\nmaterial states that “Some NeuroQuant\nparameters vary depending on scanner\nmanufacturer & field strength”. This\nsupports that NeuroQuant supports\nvarious magnet strengths."],["Output","- Provides volumetric\nmeasurements of brain\nstructures, including\ngyrification information\n- Includes segmented color\noverlays and\nmorphometric reports\n- The information is\nprovided as a .pdf report.","- Provides volumetric\nmeasurements of brain\nstructures and lesions\n- Includes segmented color\noverlays and\nmorphometric reports\n- Automatically compares\nresults to reference\npercentile data and to prior\nscans when\navailable\n- Supports DICOM format as\noutput of results that\ncan be displayed on DICOM\nworkstations and","Equivalent\nBoth the GyriCalc subject device and\nthe NeuroQuant predicate device\nprovide volumetric measurements of\nbrain structures and segmented color\noverlays and\nmorphometric reports.\nDifferences-\nThe GyriCalc device provides\ngyrification information whereas\nNeuroQuant does not.\nThis additional technological\ncharacteristic (i.e., gyrification analysis)\ndoes not raise different questions of\nsafety and effectiveness. The"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p13-t0","doc_id":"K250686","page_num":13,"bbox":[72.17,158.4,539.76,711.6],"n_rows":5,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["","","Picture Archive and\nCommunications Systems","functionality has been supported by\nperformance testing.\nGyriCalc does not compare results to\nreference\npercentile data and to prior scans. This\nfunctionality is not within the scope of\nGyriCalc’s intended use/indications as\nGyriCalc is intended for quantification\nrather than comparison at this time.\nHowever, GyriCalc does include\n‘sample values’ which are supported by\nthe data used in the performance\nvalidation testing.\nGyriCalc does not output DICOM for\ndisplay on PACS devices. GyriCalc’s\nsole output is a .pdf report which can be\nviewed on standard .pdf reading\napplications or may be printed.\nThe stated differences do not alter the\nintended use, safety or performance of\nthe GyriCalc device as compared to the\nNeuroQuant predicate device."],["Specific Device\nOutput","Provides morphometric\nmeasurements based on\n3D T1 MRI series","Provides morphometric\nmeasurements based on 3D T1\nMRI series","Same"],["MR Scan\nParameters","-Plane: Sagittal, Axial\n-Mode: –3D\n-Type: T1 weighted\n-Matrix: 256 x 256\n-Resolution: Ideally\nisotropic with a voxel size\nof 1mm x1mm x1mm\n-NEX/NSA: 1\n-Slice Thickness: 1 mm","Plane –sagittal\nMode –3D\nT1 weighted\nMatrix –192 x 192\nNEX / NSA 1\nSlice thickness –1.2 mm\nSpacing –1.2 mm\nNumber of slices –160 -170\nFOV 24 – 25.6","Equivalent-\nGyriCalc’s MR Scan parameters are\nmainly the same (equivalent) to the\nNeuroQuant predicates parameters.\nGyriCalc’s parameters are consistent\nwith optimizing the images for analysis\nby the GyriCalc software. However,\nthere are potentially minor variations\nbetween the parameters of the two\ndevices which do not alter the safety,\neffectiveness or performance of the\nGyriCalc device."],["Use Cases","For use in routine patient\ncare as a support tool for","For use in both clinical trial\nresearch and routine patient","Equivalent-\nGyriCalc does not explicitly intend the"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p15-t0","doc_id":"K250686","page_num":15,"bbox":[72.16,158.4,539.76,716.16],"n_rows":4,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["Report","GyriCalc results are\ndocumented in a pdf report\nwhich is available to the\nclinician","A report is generated\nResults are provided in a\nstandard DICOM format as\nadditional MR series that can\nbe displayed on third-party\nDICOM workstations and\nPACS.","Equivalent-\nGyriCalc’s sole output is a .pdf report\nwhich can be viewed digitally using\nstandard .pdf reading software as well\nas can be printed if desired.\nGyriCalc does not provide DICOM\nseries which can be viewed on third-\nparty DICOM workstations and PACS\nas this functionality is not required for\nGyriCalc to perform its intended use.\nThe absence of DICOM series output\ndoes not raise new questions relating to\nthe safety or effectiveness of the\nGyriCalc device."],["Cybersecurity","GyriCalc utilizes current\n‘state of the art’\ncybersecurity processes\nand controls which align\nwith FDA’s current\nguidance and\nrecommendations.","No information is publicly\navailable on cybersecurity.","Equivalent (or better)\nThe K170981 submission of\nNeuroQuant did not contain specific\ninformation related to cybersecurity. In\nrecent years, the requirements related to\ncybersecurity have greatly evolved.\nGyriCalc utilizes current ‘state of the\nart’ cybersecurity processes and\ncontrols which align with FDA’s\ncurrent guidance and recommendations."],["Performance\nTesting","GyriCalc performance was\nevaluated by comparing\nsegmentation accuracy\nwith expert manual\nsegmentations and by\nmeasuring segmentation\nreproducibility between\nsame subject scans.\nThe system yields\nreproducible results that\nare well correlated with\ncomputer-aided expert\nmanual segmentations.\nGyriCalc’s segmentation\naccuracy compared to\nexpert manual\nsegmentations of 3D T1","NeuroQuant performance was\nevaluated by comparing\nsegmentation accuracy with\nexpert\nmanual segmentations and by\nmeasuring segmentation\nreproducibility between same\nsubject scans.\nThe system yields\nreproducible results that are\nwell correlated with\ncomputer-aided expert manual\nsegmentations.\nNeuroQuant’s segmentation\naccuracy compared to expert\nmanual segmentations of 3D\nT1","Equivalent\nThe performance of GyriCalc and\nNeuroQuant was verified using\ncomparison against expert manual\nsegmentation. The results of testing\nhave confirmed equivalent\nperformance.\nGyriCalc has equivalent segmentation\naccuracy performance for the major\ncortical regions is equivalent to the\nNeuroQuant predicate.\nNote 1: GyriCalc does not perform\nsubcortical brain structures.\nNote 2: NEUROPHET (K220437) has\nbeen added as a Reference device to\nsupport the technological characteristic\nof the use of FreeSurfer for"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p16-t0","doc_id":"K250686","page_num":16,"bbox":[72.12,158.4,539.76,707.52],"n_rows":2,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["","MRI scans was evaluated\nusing Dice’s coefficient\nmetric. The results were in\nthe range of 92-99% with\nan average of 95%\nconfidence.\nVolume Measurements:\nGyriCalc’s mean\npercentage absolute\nvolume difference of the\nmajor cortical regions was\nin the range of 0.45 -12.1\n%\nArea Measurements:\nGyriCalc’s mean absolute\nsurface area error was in\nthe range of 0.33 - 12.6 %.\nGyrification\nMeasurements:\nGyriCalc’s mean absolute\ngyrification Index error\nwas in the range of 0.04 -\n0.89%.\nDescription of Subjects:\nThe imaging data was\ncollected retrospectively\nfrom a population of\nanonymized patients 2-3\nyears (24-36 months) with\ncurated clinical records.\nSafety and Effectiveness:\nThe measurements met the\npredetermined acceptance\ncriteria.\nAdverse Events:\nAs the clinical\nperformance testing was\nperformed retrospectively\non previously acquired T1\nweighted MRI scans, there\nwere no adverse events","MRI scans was evaluated\nusing Dice’s coefficient\nmetric. For major subcortical\nbrain structures\nDice’s coefficients are in the\nrange of 80-90% and for\nmajor cortical regions are in\nthe range of 75-85%. For\nlesion segmentations\nevaluated separately using 3D\nT1 and T2 FLAIR MRI scan\npairs of subjects with brain\nlesions, Dice’s coefficient\nexceeds 80%.\nBrain structure segmentation\nreproducibility of repeated 3D\nT1 MRI scans for same\nsubjects\nwas evaluated by using the\npercentage absolute volume\ndifferences. The mean\npercentage\nabsolute volume differences\nfor all major subcortical\nstructures were in the range of\n1-5%. Brain\nlesion segmentation\nreproducibility was evaluated\nseparately using 3D T1 and\nT2 FLAIR MRI\nrepeated scan pairs of subjects\nwith brain lesions. The mean\nabsolute lesion volume\ndifference\nwas less than 0.25cc, while\nthe mean percentage lesion\nabsolute volume difference\nwas less than 2.5%.","segmentation initialization. A separate\ncomparison table is provided for the\nreference device.\nVolume Measurements:\nGyriCalc performed in an equivalent\nmanner to the NeuroQuant in terms of\nvolumetric measurements. (Note:\nNeuroQuant reported on major\nsubcortical structures rather than the\nmajor cortical structures)\nThe NeuroQuant predicate device does\nnot include area or gyrification\nmeasurements. These ‘Technological\nCharacteristics’ are supported by the\nresults of the clinical performance\ntesting and do not raise new questions\nrelating to safety and/or effectiveness as\ncompared to the predicate device.\nGyriCalc does not perform lesion\nsegmentations or quantification of\nlesions as this functionality is not within\nit’s stated intended use/indications. As\nlesion functionality is not within\nGyriCalc’s intended use, the lack of\nsuch functionality does not raise new\nquestions related to safety or\neffectiveness of the GyriCalc device."]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p17-t0","doc_id":"K250686","page_num":17,"bbox":[72.2,158.4,539.76,245.76],"n_rows":3,"n_cols":4,"columns":["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NeuroQuant (K170981)\nPrimary Predicate Device","Equivalence Discussion"],["","(AEs) noted.","",""],["","","",""]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p17-t1","doc_id":"K250686","page_num":17,"bbox":[72.2,312.72,539.76,718.2],"n_rows":7,"n_cols":4,"columns":["Feature/Function","GyriCalc","NEUROPHET\n(K220437)\nReference Device","Equivalence Discussion"],"rows":[["Feature/Function","GyriCalc","NEUROPHET\n(K220437)\nReference Device","Equivalence Discussion"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same"],["Regulation\nDescription","Medical image management\nand processing system","Medical image\nmanagement and\nprocessing\nsystem","Same"],["Classification\nName","System, Image Processing,\nRadiological","System, Image\nProcessing,\nRadiological","Same"],["Class","Class II","Class II","Same"],["Product Code","LLZ","LLZ","Same"],["Indications for\nUse","GyriCalc is intended for\nautomatic labeling,\nvisualization, and\nquantification including\nvolume, surface area and\ngyrification analysis (i.e.,\ngyrification index) of\nsegmentable brain structures\nfrom a set of MR images.\nGyriCalc is intended to be\nused by qualified personnel\nand interpreted by a qualified\nclinician.","Neurophet\nAQUA is\nintended for\nAutomatic\nlabeling,\nvisualization\nand volumetric\nquantification of\nsegmentable\nbrain\nstructures from a\nset of MR\nimages.\nVolumetric\ndata may be","Equivalent -\nBoth the subject device (GyriCalc) and the\nreference device (Neurophet AQUA) are intended\nto be used for automatic labeling, visualization,\nvolumetric quantification of segmentable brain\nstructures from a set of MR images.\nThe subject device measurements include volume,\narea and gyrification whereas the reference device\nprovides only volume measurement. The addition\nof area and gyrification measurements are\nconsidered technological characteristics which are\nsupported by clinical performance testing. As the\narea and gyrification are also measurements, they\ndo not add a new ‘intended use’ and do not affect\nthe safety and/or effectiveness of the subject"]],"caption_candidate":"(For segmentation methodology)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p18-t0","doc_id":"K250686","page_num":18,"bbox":[72.16,158.4,539.76,705.0],"n_rows":4,"n_cols":4,"columns":["","GyriCalc is not intended to be\nused for visualization or\nquantification of neurologic\nlesions.\nGyriCalc is intended for\nchildren between 24 to 36\nmonths of age.","compared to\nreference\npercentile data.","device as compared to the reference device or\nraise new questions relating to safety and/or\neffectiveness.\nGyriCalc does not include a normative database\nwith which to compare brain structures to ‘normal’\npatients. This functionality is not needed as\nGyriCalc is intended for visualization and\nquantification only at this time. However,\nGyriCalc does include ‘reference values’ which\nare supported by the data used in the performance\nvalidation testing.\nFor clarity, GyriCalc has added an explicit\nstatement that the device is intended to be used by\nqualified personnel and interpreted by a qualified\nclinician. The reference Neurophet AQUA device\nIndications statement does not state this explicitly\nbut it is assumed as Neurophet AQUA is an Rx\nonly device."],"rows":[["","GyriCalc is not intended to be\nused for visualization or\nquantification of neurologic\nlesions.\nGyriCalc is intended for\nchildren between 24 to 36\nmonths of age.","compared to\nreference\npercentile data.","device as compared to the reference device or\nraise new questions relating to safety and/or\neffectiveness.\nGyriCalc does not include a normative database\nwith which to compare brain structures to ‘normal’\npatients. This functionality is not needed as\nGyriCalc is intended for visualization and\nquantification only at this time. However,\nGyriCalc does include ‘reference values’ which\nare supported by the data used in the performance\nvalidation testing.\nFor clarity, GyriCalc has added an explicit\nstatement that the device is intended to be used by\nqualified personnel and interpreted by a qualified\nclinician. The reference Neurophet AQUA device\nIndications statement does not state this explicitly\nbut it is assumed as Neurophet AQUA is an Rx\nonly device."],["Target\nAnatomical\nSites","Brain","Brain","Same"],["Data Source","- MRI scanner: 3D T1\nscans acquired with\nspecified protocols\n- Supports DICOM\nformat as input.","- MRI scanner:\n3D T1\nscans acquired\nwith\nspecified\nprotocols\n- Supports\nDICOM\nformat as input.","Same"],["Design and\nIncorporated\nTechnology","- Automated\nmeasurement of brain\ntissue volumes and\nstructures.\n- Automatic\nsegmentation and\nquantification of brain\nstructures using deep\nlearning.","- Automated\nmeasurement of\nbrain\ntissue volumes\nand\nstructures\n- Automatic\nsegmentation and\nquantification of\nbrain\nstructures using\ndeep\nlearning","Equivalent-\nBoth the subject GyriCalc and Reference\nNEUROPHET device perform segmentation based\non deep-learning methodologies whereas the\nPrimary Predicate device utilizes a technically\nsimilar ‘atlas-based’ segmentation methodology.\nGyriCalc’s segmentation accuracy compared to\nexpert manual segmentations of 3D T1\nMRI scans was evaluated using Dice’s coefficient\nmetric. The results were in the range of 92-99%\nwith an average of 95% confidence.\nThe results of the segmentation support that the\nsubject GyriCalc device is as safe and effective as\nthe reference device."]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p20-t0","doc_id":"K250686","page_num":20,"bbox":[72.2,462.24,202.68,699.0],"n_rows":10,"n_cols":2,"columns":["Patient Characteristic","Count"],"rows":[["Patient Characteristic","Count"],["Patient Sex",""],["Male","57"],["Female","25"],["Patient Age (months)",""],["24-27","18"],["27-30","24"],["30-33","16"],["33-36","24"],["Location",""]],"caption_candidate":"the device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p21-t0","doc_id":"K250686","page_num":21,"bbox":[72.22,158.4,202.68,229.44],"n_rows":3,"n_cols":2,"columns":["Patient Characteristic","Count"],"rows":[["Patient Characteristic","Count"],["U.S.","54"],["Brazil","28"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p21-t1","doc_id":"K250686","page_num":21,"bbox":[72.22,256.8,249.6,564.6],"n_rows":13,"n_cols":2,"columns":["Imaging Characteristics",""],"rows":[["Imaging Characteristics",""],["Magnetic Field Strength","Count"],["1.5 T","67"],["3.0 T","15"],["Manufacturer","Count"],["Philips","25"],["GE","56"],["SIEMENS","1"],["Voxel Spacing (mm)","Median [Range]"],["Pixel Spacing X","0.45 [0.35, 1.25]"],["Pixel Spacing Y","0.45 [0.35, 1.30]"],["Slice Thickness","3.00 [0.99, 5.00]"],["Slice Count","48 [24, 341]"]],"caption_candidate":"Brazil 28","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p21-t2","doc_id":"K250686","page_num":21,"bbox":[72.22,651.48,539.76,698.88],"n_rows":2,"n_cols":2,"columns":["Reason for MRI","Count *"],"rows":[["Reason for MRI","Count *"],["Not specified","29"]],"caption_candidate":"confounders for patients in the test dataset.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p22-t0","doc_id":"K250686","page_num":22,"bbox":[72.22,158.4,539.76,382.68],"n_rows":9,"n_cols":2,"columns":["Reason for MRI","Count *"],"rows":[["Reason for MRI","Count *"],["Seizure(s)","20"],["Developmental Delay","14"],["Episode of altered mental status","3"],["Epilepsy","2"],["Estropia","2"],["Vomiting","2"],["Weakness/Lethargy","2"],["Ataxia, exotropia, headaches, macrocephaly, microcephaly, optic nerve hypoplasia, orbital mass, spastic\nhemiparesis, nystagmus, spastic diplegia, suspected pituitary disorder","11 (1 for\neach)"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p22-t1","doc_id":"K250686","page_num":22,"bbox":[72.22,410.04,539.76,657.84],"n_rows":10,"n_cols":2,"columns":["Radiological Findings/Potential Confounders","Count *"],"rows":[["Radiological Findings/Potential Confounders","Count *"],["None/Not Specified","23"],["Seizure(s)/Epilepsy","22"],["Sinus Inflammation/Infection","19"],["Developmental Delay","14"],["Premature Birth","4"],["Diminutive Pituitary","2"],["Eye Disorder","5"],["Movement Disorder","5"],["Asymmetry of hippocampus, benign ventricular cyst, ear infection, focal cortical displasia, hyperthyroidism,\nmacrocephaly, microcephaly, neonatal infarction, orbital dermoid","9 (1 for\neach)"]],"caption_candidate":"* some patients with multiple reasons for MRI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p23-t0","doc_id":"K250686","page_num":23,"bbox":[72.16,501.6,465.24,674.4],"n_rows":4,"n_cols":4,"columns":["Structure/Region","Mean Absolute\nVolume Error","Mean Absolute\nSurface Area Error","Mean Absolute\nGyrification Index Error"],"rows":[["Structure/Region","Mean Absolute\nVolume Error","Mean Absolute\nSurface Area Error","Mean Absolute\nGyrification Index Error"],["Total Cortex\nLeft Cortex\nRight Cortex","2.14% [1.66%, 2.61%]\n2.41% [1.81%, 3.01%]\n1.88% [1.49%, 2.28%]","N/A*","N/A*"],["Superior Frontal\nLeft\nRight","0.48% [0.25%, 0.72%]\n0.59% [0.31%, 0.87%]","0.46% [0.17%, 0.76%]\n0.63% [0.21%, 1.05%]","0.04% [0.02%, 0.05%]\n0.04% [0.02%, 0.05%]"],["Middle Frontal\nLeft\nRight","0.51% [0.29%, 0.72%]\n0.45% [0.29%, 0.60%]","0.49% [0.08%, 0.91%]\n0.33% [0.16%, 0.49%]","0.05% [0.03%, 0.06%]\n0.04% [0.03%, 0.05%]"]],"caption_candidate":"specified regions of the brain are reported below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250686-p24-t0","doc_id":"K250686","page_num":24,"bbox":[72.18,158.4,465.24,423.36],"n_rows":6,"n_cols":4,"columns":["Structure/Region","Mean Absolute\nVolume Error","Mean Absolute\nSurface Area Error","Mean Absolute\nGyrification Index Error"],"rows":[["Structure/Region","Mean Absolute\nVolume Error","Mean Absolute\nSurface Area Error","Mean Absolute\nGyrification Index Error"],["Fusiform\nLeft\nRight","1.44% [0.74%, 2.14%]\n1.37% [0.66%, 2.08%]","1.40% [0.48%, 2.32%]\n1.30% [0.47%, 2.13%]","0.07% [0.05%, 0.10%]\n0.08% [0.04%, 0.12%]"],["Inferior Temporal\nLeft\nRight","1.11% [0.71%, 1.51%]\n1.05% [0.59%, 1.52%]","1.14% [0.62%, 1.67%]\n1.09% [0.56%, 1.61%]","0.12% [0.06%, 0.17%]\n0.12% [0.06%, 0.17%]"],["Inferior Parietal\nLeft\nRight","12.10% [8.44%, 15.77%]\n7.88% [5.68%, 10.07%]","12.58% [8.72%, 16.43%]\n8.42% [5.98%, 10.86%]","0.89% [0.56%, 1.22%]\n0.49% [0.32%, 0.67%]"],["Lingual\nLeft\nRight","4.92% [3.85%, 6.00%]\n4.46% [3.59%, 5.33%]","5.70% [4.11%, 7.29%]\n5.45% [4.09%, 6.80%]","0.32% [0.23%, 0.41%]\n0.49% [0.35%, 0.63%]"],["Cuneus\nLeft\nRight","10.75% [8.50%, 13.00%]\n10.18% [7.79%, 12.57%]","11.64% [8.75%, 14.54%]\n11.28% [8.51%, 14.05%]","0.48% [0.32%, 0.65%]\n0.50% [0.36%, 0.64%]"]],"caption_candidate":"(21 CFR 807.92(c))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250694-p3-t0","doc_id":"K250694","page_num":3,"bbox":[257.81,223.82,570.36,320.45],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250694-p5-t0","doc_id":"K250694","page_num":5,"bbox":[72.26,371.93,540.34,497.47],"n_rows":5,"n_cols":2,"columns":["Device Name","Scaida BrainCT-ICH"],"rows":[["Device Name","Scaida BrainCT-ICH"],["Common Name","Radiological computer aided triage and\nnotification software"],["Classification Name","Radiological Computer-Assisted Triage\nAnd Notification Software"],["Regulation Number","892.2080"],["Product Code(s)","QAS"]],"caption_candidate":"Device Name: 21 CFR 807.92 (a) (2)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250694-p5-t1","doc_id":"K250694","page_num":5,"bbox":[72.26,546.07,540.34,605.14],"n_rows":3,"n_cols":2,"columns":["Predicate #","K211179"],"rows":[["Predicate #","K211179"],["Predicate Trade Name (Primary\nPredicate is listed first)","InferRead CT Stroke.AI"],["Product Code","QAS"]],"caption_candidate":"Legally Marketed Predicate Devices: 21 CFR 807.92 (a) (3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250694-p7-t0","doc_id":"K250694","page_num":7,"bbox":[72.38,244.82,539.74,706.54],"n_rows":12,"n_cols":4,"columns":["Item","Scaida BrainCT-ICH\n(Subject device)","InferRead CT Stroke.AI\nK211179\n(Predicate device)","Comparison"],"rows":[["Item","Scaida BrainCT-ICH\n(Subject device)","InferRead CT Stroke.AI\nK211179\n(Predicate device)","Comparison"],["Intended\nuse/indications for\nuse","Radiological computer aided\nnotification software indicated\nfor use in the analysis of non-\ncontrast head CT images of\nadult patients. The device is\nintended to assist trained\nradiologists in workflow triage\nby flagging and communicating\nsuspected positive findings of\nIntracranial Hemorrhage (ICH).","Radiological computer aided\ntriage and notification\nsoftware for use in the\nanalysis of Non-Enhanced\nHead CT images. The device\nis intended to assist hospital\nnetworks and trained\nradiologists in workflow triage\nby flagging suspected\npositive findings of\nIntracranial Hemorrhage\n(ICH).","Same"],["User population","Radiologist","Radiologist","Same"],["Patient population","Adult","Adult","Same"],["Anatomical region of\ninterest","Head","Head","Same"],["Data acquisition\nprotocol","NCCT","NCCT","Same"],["Segmentation of\nregion of interest","No","No","Same"],["Algorithm","AI algorithm with database of\nimages","AI algorithm with database of\nimages","Same"],["Notification/\nprioritization","Yes","Yes, case-level indicator","Same"],["Preview images","No","Presentation of a preview of\nthe study for initial\nassessment not meant for\ndiagnostic purposes.\nThe device operates in\nparallel with the standard of\ncare, which remains the\ndefault option for all cases","Preview of\nimages is not\navailable"],["Alteration of original\nimage","No","No","Same"],["Removal of cases\nfrom worklist queue","No","No","Same"]],"caption_candidate":"as per the comparison table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250694-p8-t0","doc_id":"K250694","page_num":8,"bbox":[72.38,72.36,539.74,371.69],"n_rows":13,"n_cols":4,"columns":["Clinical standard of\ncare workflow","In parallel to","In parallel to","Same"],"rows":[["Clinical standard of\ncare workflow","In parallel to","In parallel to","Same"],["Design: DICOM\ncompliance","Yes","Yes","Same"],["Design: Computer\nPlatform","Standard off-the-shelf server or\nvirtual server","Standard off-the-shelf server\nor virtual server","Same"],["Design: Data\nacquisition","Acquires medical image data\nfrom DICOM compliant imaging\ndevices and modalities","Acquires medical image data\nfrom DICOM compliant\nimaging devices and\nmodalities","Same"],["Energy used and/or\ndelivered","None – software only\napplication. The software\napplication does not deliver or\ndepend on energy delivered to\nor from patients","None – software only\napplication. The software\napplication does not deliver\nor depend on energy\ndelivered to or from patients","Same"],["Materials","N/A – Software only device","N/A – Software only device","Same"],["Biocompatibility","N/A – Software only device","N/A – Software only device","Same"],["Sterility","N/A – Software only device","N/A – Software only device","Same"],["Electrical Safety","N/A – Software only device","N/A – Software only device","Same"],["Mechanical Safety","N/A – Software only device","N/A – Software only device","Same"],["Chemical Safety","N/A – Software only device","N/A – Software only device","Same"],["Thermal Safety","N/A – Software only device","N/A – Software only device","Same"],["Radiation Safety","N/A – Software only device","N/A – Software only device","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p7-t0","doc_id":"K250738","page_num":7,"bbox":[56.63,389.0,557.0,555.34],"n_rows":9,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","YSIO X.pree VA20","YSIO X.pree VA20",""],["","","",""],["","","Gen2",""],["","","",""],["Regulation\nDescription","Stationary X-Ray System","Stationary X-Ray System","Same"],["Regulation\nNumber","§892.1680","§892.1680","Same"],["Classification\nProduct Code","KPR","KPR","Same"],["Model Number","11107464","11574001","Changed"]],"caption_candidate":"(YSIO X.pree VA20)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p8-t0","doc_id":"K250738","page_num":8,"bbox":[56.64,59.7,556.99,710.34],"n_rows":19,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","YSIO X.pree VA20","YSIO X.pree VA20",""],["","","",""],["","","Gen2",""],["","","",""],["Indications for\nuse","The intended use of the device\nYSIO X.pree is to visualize\nanatomical structures of\nhuman beings by converting an\nX-ray pattern into a visible\nimage.\nThe device is a digital X-ray\nsystem to generate X-ray\nimages from the whole body\nincluding the skull, chest,\nabdomen, and extremities. The\nacquired images support\nmedical professionals to make\ndiagnostic and/or therapeutic\ndecisions.\nYSIO X.pree is not for\nmammography examinations.","The intended use of the device\nYSIO X.pree is to visualize\nanatomical structures of human\nbeings by converting an X-ray\npattern into a visible image.\nThe device is a digital X-ray\nsystem to generate X-ray images\nfrom the whole body\nincluding the skull, chest,\nabdomen, and extremities. The\nacquired images support\nmedical professionals to make\ndiagnostic and/or therapeutic\ndecisions.\nYSIO X.pree is not for\nmammography examinations.","Same"],["X-Ray","","",""],["","","",""],["Generator","Polydoros R\n65/80 kW","Polydoros RFX UG R\n65/80 kW","Updated state-\nof-the-art\ngenerator with\nequal performance"],["X-Ray tube","OPTITOP\n150/40/80/HC-100","OPTITOP\n150/40/80/HC-100","Same"],["X-ray techniques","Radiography","Radiography","Same"],["Collimator","Digital Multileaf\nCollimator N","Digital Multileaf\nCollimator RFU","Updated collimator\nwith\nequal performance"],["Air kerma","Kerma X","Kerma X","Same"],["CARE","Combined\nApplications to\nReduce Exposure","Combined\nApplications to\nReduce Exposure","Same"],["Touch user\ninterface on tube\nsuspension","touchscreen in landscape\nformat","touchscreen in landscape format","Same"],["Automatic\nExposure Control","Field selection via touch user\ninterface","Field selection via touch user\ninterface and virtual AEC\noverlay on the camera image","New virtual\nAEC selection"],["Digital Imaging","","",""],["","","",""],["Fixed detector for\ntable and wall\nstand","Trixell pixium 4343RC\n“Max Static”","Trixell pixium 4343RC\n“Max Static”","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p9-t0","doc_id":"K250738","page_num":9,"bbox":[56.61,59.7,557.02,667.84],"n_rows":27,"n_cols":4,"columns":["Feature","Predicate device","Subject device","Comment"],"rows":[["Feature","Predicate device","Subject device","Comment"],["","YSIO X.pree VA20","YSIO X.pree VA20",""],["","","",""],["","","Gen2",""],["","","",""],["Large mobile\ndetectors","Trixell pixium\n3543EZh „MAX wi-D“","Trixell pixium\n3543EZh „MAX wi-D“","Same"],["","Trixell pixium 3543EZ3\n“X.wi-D 35”","Trixell pixium 3543EZ3 “X.wi-\nD 35”","Same"],["","Trixell pixium 4343EZ3\n“X.wi-D 43”","Trixell pixium 4343EZ3 “X.wi-\nD 43”","Same"],["Small mobile\ndetectors","Trixell pixium 2430EZ “MAX\nmini”","Trixell pixium 2430EZ “MAX\nmini”","Same"],["","N/A","Trixell pixium 2430EZ3 “X.wi-\nD 24”","New small mobile\ndetector"],["Digital imaging\nsystem","syngo XR","syngo XR","Same"],["","Operating system Windows 10","Operating system Windows 10","Same"],["","Operated via touch screen","Operated via touch screen","Same"],["","Image processing with\nmyExam IQ","Image processing with myExam\nIQ","Same"],["","AI-based Auto Cropping","AI-based Auto Cropping","Same"],["","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Acquisition and Image\nprocessing parameters selected\nvia clinical protocols","Same"],["Other Features and Components","","",""],["","","",""],["Patient Table","Table with fixed detector and\ntable with bucky","Table with fixed detector and\ntable with bucky","Updated table\nhardware with\nequal performance"],["","Standard tabletop and flat\ntabletop","Standard tabletop and flat\ntabletop","Same"],["Wall stand","Wall stand with fixed detector\nand wall stand with bucky","Wall stand with fixed detector\nand wall stand with bucky","Updated wall stand\nhardware, new\nwireless detector\nconfigurations"],["Camera","Live camera for patient\npositioning and collimation","Live camera for patient\npositioning and collimation","Same"],["AI based\nAutomatic\ncollimation","Auto Thorax Collimation","Auto Thorax Collimation","Same"],["","Auto Long-Leg/Full-Spine\ncollimation","Auto Long-Leg/Full-Spine\ncollimation",""],["Cropping","AI-based auto-cropping","AI-based auto-cropping","Same"],["Wireless Remote\nControl","Yes, same type","Yes, same type","Same"],["Status Indicator\nLights","N/A","Status Indicator Lights at tube\nstand and wall stand","New"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p10-t0","doc_id":"K250738","page_num":10,"bbox":[62.02,123.66,543.94,697.98],"n_rows":15,"n_cols":2,"columns":["Standards Development",""],"rows":[["Standards Development",""],["Organization and Reference","Title of Standard"],["Number",""],["ANSI AAMI\n60601-1, 2020 Ed. 3.2","Medical Electrical Equipment - Part 1: General\nRequirements for Safety"],["IEC 60601-1-2 2020 Ed 4.1","Medical Electrical Equipment - Part 1-2: General requirements\nfor basic safety and essential performance - Collateral Standard:\nElectromagnetic disturbances - Requirements and tests"],["IEC 60601-1-3:\nEdition 2.2, 2021","Medical electrical equipment - Part 1-3: General requirements for\nbasic safety and essential performance - Collateral Standard:\nRadiation protection in diagnostic X-ray equipment"],["IEC 60601-2-28, 2017","Medical electrical equipment - Part 2-28: Particular requirements\nfor the basic safety and essential performance of X-ray tube\nassemblies for medical diagnosis"],["IEC 60601-2-54\n2018, Edition 1.2","Medical electrical equipment - Part 2-54: Particular requirements\nfor the basic safety and essential performance of X-ray equipment\nfor radiography and radioscopy"],["IEC 60601-1-6\n2020 Ed 3.2","Medical electrical equipment – Part 1-6: General requirements for\nbasic safety and essential performance – Collateral standard:\nUsability"],["IEC 62366-1 2020 Ed 1.1","Medical devices – Application of usability engineering tomedical\ndevices"],["ISO 14971: 2019","Medical devices – application of risk management tomedical\ndevices"],["IEC 62304 2015, Ed.1.1","Medical device software - Software life cycle processes"],["IEC 61910-1: 2014, Ed 1.0","Medical electrical equipment - Radiation dose documentation -\nPart 1: Radiation dose structured reports for radiography and\nradioscopy"],["NEMA PS 3.1 - 3.20 2023e","Digital Imaging and Communications in Medicine(DICOM) Set"],["ISO EN ISO 10993-1\nFifth edition 2018","Biological evaluation of medical devices – Part1: Evaluation and\ntesting within a risk management process"]],"caption_candidate":"Table 8: Non-clinical performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p11-t0","doc_id":"K250738","page_num":11,"bbox":[49.75,169.88,578.32,710.28],"n_rows":21,"n_cols":5,"columns":["","Pixium 3543EZ3","Pixium 2430EZ","Pixium 2430EZ3","Comparison to"],"rows":[["","Pixium 3543EZ3","Pixium 2430EZ","Pixium 2430EZ3","Comparison to"],["","(predicate","(predicate","(subject","predicate"],["","detector)","detector)","detector)",""],["Sensor Technology","Amorphous Silicon","Amorphous Silicon","Amorphous Silicon","same"],["Scintillator","Cesium Iodide (CsI)","Cesium Iodide (CsI)","Cesium Iodide (CsI)","same"],["Pixel pitch","99 µm","148 µm","99 µm","same as 3543EZ3"],["Pixel area - full IQ","345.1 mm x 424.4\nmm","284.2 mm x 225.0\nmm","229.0 mm x 284.3\nmm","similar to 2430EZ"],["Pixel matrix - full IQ","3495 x 4298 pixels","1920 x 1520 pixels","2319 x 2879 pixels","higher than for\n2430EZ"],["Pixel matrix - active","3520 x 4316 pixels","1920 x 1560 pixels","2336 x 2880 pixels","higher than for\n2430EZ"],["Maximum resolution","5 lp/mm","3.4 lp/mm","5 lp/mm","same as 3543EZ3"],["Detector dimensions\n(mm)","384.5 x 460.5 x 16.0","268.5 x 328.5 x 16.0","268.5 x 328.5 x 16.0","same as 2430EZ"],["Sensitivity (RQA5)","450/560/680 lsb/µGy\n(min/typ/max)","450/550/700 lsb/µGy\n(min/typ/max)","450/560/680 lsb/µGy\n(min/typ/max)","same as 3543EZ3"],["Maximal linear dose\nrange (RQA5)\n[µGy]","50","50","50",""],["Electronic Noise\n[lsb]","8.2","3.6","8.2",""],["DQE @ 0 lp/mm\n(2.5µGy, RQA5)\n[%]","70","70","70",""],["DQE @ 1 lp/mm\n(2.5µGy, RQA5)\n[%]","53","51","53",""],["DQE @ 2 lp/mm\n(2.5µGy, RQA5)\n[%]","45","42","45",""],["DQE @ 3 lp/mm\n(2.5µGy, RQA5)\n[%]","38","29","38",""],["DQE @ 4 lp/mm\n(2.5µGy, RQA5)\n[%]","27","n.a.","27",""],["DQE @ 5 lp/mm\n(2.5µGy, RQA5)\n[%]","14","n.a.","14",""],["MTF @ 0.5 lp/mm","84","81","84",""]],"caption_candidate":"Table 8-2: Comparison of the new detector X.wi-D24 (Pixium 2430EZ3) to the predicates detectors","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p12-t0","doc_id":"K250738","page_num":12,"bbox":[49.74,59.58,578.34,201.92],"n_rows":6,"n_cols":5,"columns":["(IEC 62220) [%]","","","",""],"rows":[["(IEC 62220) [%]","","","",""],["MTF @ 1 lp/mm\n(IEC 62220) [%]","68","63","68",""],["MTF @ 2 lp/mm\n(IEC 62220) [%]","43","35","43",""],["MTF @ 3 lp/mm\n(IEC 62220) [%]","27","19","27",""],["MTF @ 4 lp/mm\n(IEC 62220) [%]","16","n.a.","16",""],["MTF @ 5 lp/mm\n(IEC 62220) [%]","10","n.a.","10",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250738-p14-t0","doc_id":"K250738","page_num":14,"bbox":[99.96,61.15,392.93,750.87],"n_rows":7,"n_cols":2,"columns":["Radio Frequency Wireless Technology in Medical","Devices - G"],"rows":[["Radio Frequency Wireless Technology in Medical","Devices - G"],["Drug Administration Staff",""],["Document issue on August 13, 2013",""],["",""],["Medical Solutions USA, Inc.","40 Liberty Boulev"],["of 10","Malvern,PA19355"],["","USA"]],"caption_candidate":"Radio Frequency Wireless Technology in Medical Devices - Guidance for Industry and Food and","well_formed":true,"extraction_settings":"text"}
{"table_id":"K250753-p7-t0","doc_id":"K250753","page_num":7,"bbox":[60.5,156.5,559.5,705.5],"n_rows":3,"n_cols":2,"columns":["Modification Description","This modification includes re-training the model and is an update\nto the model weights (and optionally hyperparameters) based on a\ncombination of new and existing training and tuning data,\nenhancing its ability to generalize and improve performance on\nreal-world cases while maintaining the model architecture. No\nchanges are made to the deployment environment or inference\npipeline, only the trained parameters (model weights) are updated.\n● Bitewing Caries Detection Model\n● Bitewing Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\n● Periapical Caries Detection Model\n● Periapical Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\n● Panoramic Caries Detection Model\n● Panoramic Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\nRe-training will be triggered if performance or data drift metrics are\nobserved. Performance drift metrics include lesion or case level\nsensitivity, case level specificity, false positive rate per image, and\nDICE score. Data drift metrics including Population Stability Index\n(PSI) and Statistical Distribution Changes are evaluated on a\nquarterly basis."],"rows":[["Modification Description","This modification includes re-training the model and is an update\nto the model weights (and optionally hyperparameters) based on a\ncombination of new and existing training and tuning data,\nenhancing its ability to generalize and improve performance on\nreal-world cases while maintaining the model architecture. No\nchanges are made to the deployment environment or inference\npipeline, only the trained parameters (model weights) are updated.\n● Bitewing Caries Detection Model\n● Bitewing Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\n● Periapical Caries Detection Model\n● Periapical Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\n● Panoramic Caries Detection Model\n● Panoramic Fillings/restorations, Fixed Prostheses, and\nImplants Detection Model\nRe-training will be triggered if performance or data drift metrics are\nobserved. Performance drift metrics include lesion or case level\nsensitivity, case level specificity, false positive rate per image, and\nDICE score. Data drift metrics including Population Stability Index\n(PSI) and Statistical Distribution Changes are evaluated on a\nquarterly basis."],["Goal","The goal is to ensure the device remains safe and effective while\nenhancing the device diagnostic accuracy for detecting dental caries,\nrestorations, fixed prostheses, and implants."],["Testing Methods","Re-training of each Condition Detection Model with new data to\nmaintain/improve its performance will be followed by performance\ntesting and a comparison of the modified Condition Detection\nModel to the reference models i.e. most recent model version and\nthe original cleared model version (using model-specific\nperformance metrics) and verification and validation.\nThe Condition Detection modification will not change the intended\nuse/instructions for use cleared under K240003, hence, the overall\nstandalone study protocol methodology for the modifications\nimplemented under the approved PCCPs is aligned with the"]],"caption_candidate":"will not be implemented.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250753-p8-t0","doc_id":"K250753","page_num":8,"bbox":[60.5,68.5,559.5,715.5],"n_rows":3,"n_cols":2,"columns":["","predicate Velmeni for Dentists cleared under K240003. The\nmodifications do not affect the relevance of the study endpoints,\nwhich were originally chosen based on current dental practices.\nThe acceptance criteria for Sensitivity , Specificity and Average\nFalse Positives have been updated to match the lower bounds of\nconfidence interval demonstrated by the originally cleared models'\nstandalone results. The new models will be evaluated on a\ncombined test dataset with balanced ratio of historical and new\ndata for validation to avoid overfitting historical data from repeated\nuse. The new test data is fully independent on a site-level from\ntraining/tuning data, and the test dataset remains at least 50% US\ndata.\nSince the device remains unchanged from the version cleared\nunder K24003, the clinical test results under K240003 remain\napplicable and MRMC results concluded the effectiveness of the\nV4D software in assisting readers to identify more caries and\nidentify more fixed prostheses, implants, and restorations\ncorrectly."],"rows":[["","predicate Velmeni for Dentists cleared under K240003. The\nmodifications do not affect the relevance of the study endpoints,\nwhich were originally chosen based on current dental practices.\nThe acceptance criteria for Sensitivity , Specificity and Average\nFalse Positives have been updated to match the lower bounds of\nconfidence interval demonstrated by the originally cleared models'\nstandalone results. The new models will be evaluated on a\ncombined test dataset with balanced ratio of historical and new\ndata for validation to avoid overfitting historical data from repeated\nuse. The new test data is fully independent on a site-level from\ntraining/tuning data, and the test dataset remains at least 50% US\ndata.\nSince the device remains unchanged from the version cleared\nunder K24003, the clinical test results under K240003 remain\napplicable and MRMC results concluded the effectiveness of the\nV4D software in assisting readers to identify more caries and\nidentify more fixed prostheses, implants, and restorations\ncorrectly."],["Device Update Procedure","The modified model will be locked prior to the evaluation. If the\npredefined PCCP criteria is met, the device will be updated\nmanually and available globally for all the end users (global\navailability). After the release, the rollout is accompanied by an\non-screen pop-up notification with the updated device version and\nlink to User manual that covers the model changes and resulting\nperformance characteristics. The latest device version will also be\nreflected on the Support tab for future user awareness.\nAdditionally, the support tab will include a link to the updated User\nmanual reflecting the modification implemented under the\napproved PCCP and updated standalone performance results."],["Impact Assessment","These updates maintain or enhance the model's ability to\ngeneralize across different patient demographics, radiograph\nmodalities, and clinical scenarios. This ensures that the model\ncontinues to perform reliably in aiding dental practitioners in the\ndetection and localization of dental conditions lesions on bitewing,\nperiapical, and panoramic radiographs.\nBenefit-Risk Analysis:\nBenefits: Maintained or improved performance, generalization\nability, prevention of subgroup biases\nRisks: Model degradation, overfitting, misclassification,\nRisk Mitigations:\nCross-validation, early stopping, bias monitoring, training data\ncomposition, performance evaluation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p5-t0","doc_id":"K250766","page_num":5,"bbox":[71.99,126.72,267.82,708.37],"n_rows":46,"n_cols":2,"columns":["1. SUBMITTER",""],"rows":[["1. SUBMITTER",""],["",""],["Submitted by:",""],["",""],["Thirona BV",""],["",""],["Toernooiveld 300",""],["",""],["6525 EC Nijmegen",""],["",""],["the Netherlands",""],["",""],["Contact Person:",""],["",""],["Eva van Rikxoort",""],["",""],["Telephone Number: +31 6 47","14 28 38"],["",""],["Email: evavanrikxoort@thirona",".eu"],["",""],["Date Prepared: 1st October 20","25"],["",""],["DEVICE",""],["",""],["Trade Name","LungQ 4"],["",""],["Common Use/Usual","Computer"],["Name",""],["",""],["Product Code","JAK"],["",""],["Classification","Class II, 2"],["",""],["Device Panel","Radiology"],["",""],["PREDICATE DEVICE",""],["",""],["Predicate Device","LungQ v3."],["",""],["Predicate Classification","Class II, 21"],["",""],["2. REFERENCE DEVICE",""],["",""],["Reference Device","Thoracic V"],["",""],["Reference Classification","Class II, 21"]],"caption_candidate":"1. SUBMITTER","well_formed":true,"extraction_settings":"text"}
{"table_id":"K250766-p5-t1","doc_id":"K250766","page_num":5,"bbox":[72.13,433.08,515.45,544.8],"n_rows":5,"n_cols":2,"columns":["Trade Name","LungQ 4"],"rows":[["Trade Name","LungQ 4"],["Common Use/Usual\nName","Computer Tomography X-ray system"],["Product Code","JAK"],["Classification","Class II, 21 CFR 892.1750"],["Device Panel","Radiology"]],"caption_candidate":"DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p5-t2","doc_id":"K250766","page_num":5,"bbox":[72.13,595.5,515.45,634.92],"n_rows":2,"n_cols":2,"columns":["Predicate Device","LungQ v3.0.0"],"rows":[["Predicate Device","LungQ v3.0.0"],["Predicate Classification","Class II, 21 CFR 892.1750"]],"caption_candidate":"PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p5-t3","doc_id":"K250766","page_num":5,"bbox":[72.13,671.4,515.45,710.82],"n_rows":2,"n_cols":2,"columns":["Reference Device","Thoracic VCAR with GSI Pulmonary Perfusion"],"rows":[["Reference Device","Thoracic VCAR with GSI Pulmonary Perfusion"],["Reference Classification","Class II, 21CFR 892.2050"]],"caption_candidate":"2. REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p7-t0","doc_id":"K250766","page_num":7,"bbox":[72.25,105.84,692.81,536.58],"n_rows":12,"n_cols":3,"columns":["Item","LungQ 4\nThirona\n(Subject device)","LungQ v3.0.0\nThirona\n(Predicate Device)"],"rows":[["Item","LungQ 4\nThirona\n(Subject device)","LungQ v3.0.0\nThirona\n(Predicate Device)"],["510(k) Number","K250766","K232412"],["Product Code","JAK","Same"],["Regulation Number","21 CFR 892.1750","Same"],["Device Classification","Class II","Same"],["Common Name","Computed tomography x-ray system","Same"],["Indication for use","The Thirona LungQ software provides reproducible CT values for\npulmonary tissue and specified endobronchial implants which is\nessential for providing quantitative support for diagnosis, treatment\nplanning and follow up examination. The LungQ software can be used\nto support physician in the diagnosis and documentation of pulmonary\ntissues images (e.g., abnormalities) from CT thoracic datasets. Three-D\nsegmentation and isolation of sub-compartments, volumetric analysis,\ndensity evaluations, estimated chronic perfusion defect analysis,\nfissure evaluation and reporting tools are provided.","Equivalent"],["Modality","CT","Same"],["Data Loading","DICOM","Same"],["Application","Command-line interface","Same"],["Segmentation","Provides 3D segmentation","Same"],["","Provides Segmentation of the:\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe","Same"]],"caption_candidate":"Table 1: Substantial Equivalence Comparison between Subject and Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p8-t0","doc_id":"K250766","page_num":8,"bbox":[72.24,85.56,692.82,524.16],"n_rows":5,"n_cols":3,"columns":["","• Right Upper Lobe\n• Right Middle Lobe\n• Right Lower Lobe\n• Pulmonary (sub)segments",""],"rows":[["","• Right Upper Lobe\n• Right Middle Lobe\n• Right Lower Lobe\n• Pulmonary (sub)segments",""],["","Provides Segmentation of the:\nAirways","Same"],["","Provides segmentation of specified endobronchial implants","Equivalent"],["Lung Volume Analysis\nSupport","Ability to measure volume\nfor:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary (sub)segments","Same"],["Volume Density Analysis","Ability to measure volume at multiple density ranges for:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary (sub)segments","Same"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250766-p9-t0","doc_id":"K250766","page_num":9,"bbox":[72.24,85.56,692.82,349.38],"n_rows":5,"n_cols":3,"columns":["","Ability to measure the 15th percentile density analysis","Same"],"rows":[["","Ability to measure the 15th percentile density analysis","Same"],["Fissure Analysis","Ability to perform fissure evaluations","Same"],["Endobronchial implant\nanalysis","Ability to report the number of specified endobronchial implants in the\nlungs.","Equivalent"],["Estimated chronic\nperfusion defect analysis","Ability to report estimated chronic perfusion defect quantification for:\n• Both Lungs\n• Left Lung\n• Right Lung\n• Left Upper Lobe\n• Left Lower Lobe\n• Right Upper Lobe\n• Right Middle Lob\n• Right Lower Lobe\n• Pulmonary (sub)segments","Equivalent"],["Analyzed Data Output","Provides a report","Same"]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250780-p7-t0","doc_id":"K250780","page_num":7,"bbox":[45.96,121.44,802.02,504.48],"n_rows":6,"n_cols":5,"columns":["ITEM","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],"rows":[["ITEM","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],["RegulatoryInformation","","","",""],["RegulationNo.","21CFR892.2050","21CFR892.2050","21CFR892.5050","21CFR892.5050"],["ProductCode","QKB","QKB","MUJ","MUJ"],["Class","II","II","II","II"],["IndicationsofUse","Theprimaryfunctionof\nARTAssistantistofacilitate\nimageprocessingwithimage\nregistrationandsyntheticCT\n(sCT)generationinadaptive\nradiationtherapy.Thisenables\nuserstometiculouslydesignART\nplansbasedontheprocessed\nimages.","Itisusedbyradiationoncology\ndepartmenttoregister\nmulti-modalityimagesand\nsegment(non-contrast)CT\nimages,togenerateneeded\ninformationfortreatment\nplanning,treatmentevaluation\nandtreatmentadaptation.","MRIPlannerisasoftware-only\nmedicaldeviceintendedforuse\nbytrainedradiationoncologists,\ndosimetristsandphysiciststo\nprocessimagesfromMRI\nsystemsto\n1)providetheoperatorwith\ninformationoftissueproperties\nforradiationattenuation\nestimationpurposesinphoton\nexternalbeamradiotherapy\ntreatmentplanning,andto\n2)derivecontoursforinputto\nradiationtreatmentplanningby\nassistinginlocalizationand\ndefinitionofhealthyanatomical\nstructures.\nMRIPlannerisnotintendedto\nautomaticallycontourtumorsor","RayStationisasoftwaresystemfor\nradiationtherapyandmedical\noncology.Basedonuserinput,\nRayStationproposestreatment\nplans.Afteraproposedtreatment\nplanisreviewedandapprovedby\nauthorizedintendedusers,\nRayStationmayalsobeusedto\nadministertreatments.\nThesystemfunctionalitycanbe\nconfiguredbasedonuserneeds."]],"caption_candidate":"VI. COMPARISONOFTECHNOLOGICALCHARACTERISTICSWITHTHEPREDICATEDEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250780-p8-t0","doc_id":"K250780","page_num":8,"bbox":[45.96,90.24,802.02,489.36],"n_rows":7,"n_cols":5,"columns":["ITEM","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],"rows":[["ITEM","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],["","","","tumorclinicaltargetvolumes.\nMRIPlannerisindicatedfor\nradiotherapyplanningofadult\npatientsforprimaryand\nmetastaticcancersinthebrain\nandhead-neckregions,aswellas\nsofttissuecancersinthepelvic\nregion.\nMRIPlannergeneratessynthetic\nCTimagesforradiation\nattenuationestimationpurposes\nforthepelvis,brainand\nhead-neckregionsonly.MRI\nPlannergeneratesautomatically\nderivedcontoursofthebladder,\ncolonandfemoralheads,for\nprostatecancerpatientsonly.",""],["OperatingSystem","Windows","Windows","Windows","Windows"],["TechnologicalCharacteristics","","","",""],["AutoRigidRegistration\nAlgorithm","Intensitybased","Intensitybased","N/A","N/A"],["AutoDeformable\nRegistrationAlgorithm","Intensitybased","Intensitybased","N/A","N/A"],["ImageConversionAlgorithm","Deeplearning","N/A","MachineLearning","MachineLearning"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250780-p9-t0","doc_id":"K250780","page_num":9,"bbox":[45.96,90.24,801.98,414.48],"n_rows":13,"n_cols":6,"columns":["ITEM","","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],"rows":[["ITEM","","SubjectDevice","PredicateDeviceK221706","ReferenceDeviceK211841","ReferenceDeviceK220141"],["RegistrationFeature","","","","",""],["ImageRegistration","Autorigidregistrationandauto\ndeformableregistration","","Autorigidregistrationandauto\ndeformableregistration","N/A","N/A"],["CompatibleModality","Autorigidregistration:\nCT,MRI,PET\nAutodeformableregistration:\nCT,MRI,CBCT","","Autorigidregistration:\nCT,MRI,PET\nAutodeformableregistration:\nCT,MRI,CBCT","N/A","N/A"],["CompatibleScannerModels","NoLimitationonscannermodel,\nDICOM3.0compliancerequired","","NoLimitationonscannermodel,\nDICOM3.0compliancerequired","N/A","N/A"],["ImageConversionFeature","","","","",""],["ImageConversion","","GeneratessyntheticCTfrom\nbothMRandCBCT","N/A","GeneratessyntheticCTfromMR","GeneratessyntheticCTfrom\nCBCT"],["ImageEnhanceFeature","","","","",""],["CBCTImageEnhance","","YES","N/A","YES","N/A"],["ImageContouringFeature","","","","",""],["ManualContouring","YES","","YES","N/A","N/A"],["CompatibleScannerModels","NoLimitationonscannermodel,\nDICOM3.0compliancerequired","","NoLimitationonscannermodel,\nDICOM3.0compliancerequired","N/A","N/A"],["ContourQA","YES","","YES","N/A","N/A"]],"caption_candidate":"510(k)Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p6-t0","doc_id":"K250788","page_num":6,"bbox":[58.32,128.28,535.32,712.32],"n_rows":16,"n_cols":2,"columns":["Date:","August 27, 2025"],"rows":[["Date:","August 27, 2025"],["Owner/Submitter:\n21 CFR 807.92(a)(1)","GE Hualun Medical Systems Co., Ltd.\nNo.1, Yong Chang North Road, Beijing Economic Technological Development\nZone, 100176 Beijing P.R. China"],["Primary Contact\nPerson:","Kenny Ma\nManager, Regulatory Affairs, WHXR\nGE Hualun Medical Systems Co., Ltd.\nEmail: Kenny.Ma@gehealthcare.com\nContact Phone Number: +86 (181) 01130591"],["Secondary Contact\nPerson:","Christopher Paulik\nSenior Regulatory Affairs Manager\nGE HealthCare (GE Medical Systems, LLC)\nEmail: Christopher.A.Paulik@gehealthcare.com\nContact Phone Number: +1 (262) 8945415"],["Device Trade Name:\n21 CFR 801.92(a)(2)","Definium Tempo Select"],["510(k) Reference\nnumber","K250788"],["Common/Usual\nName:","Digital Radiographic System"],["Regulation Name:","Stationary X-Ray System"],["Regulation:","21 CFR 892.1680"],["Classification:","Class II"],["Product Code:","KPR"],["Subsequent Product\nCode(s):","MQB"],["Predicate Device:\n21 CFR 807.92(a)(3)","Discovery XR656 HD with VolumeRad (K191699)\n21CFR 892.1680 (KPR, MQB)\nClass II"],["Predicate Device\nManufacturer","GE Hualun Medical Systems Co., Ltd.\nNo.1, Yong Chang North Road, Beijing Economic Technological Development Zone,\n100176 Beijing P.R. China"],["Reference Device:","Definium Pace Select (K231892)\n21CFR 892.1680 (KPR, MQB)\nClass II"],["Reference Device\nManufacturer:","GE Hualun Medical Systems Co., Ltd.\nNo.1, Yong Chang North Road, Beijing Economic Technological Development Zone,\n100176 Beijing P.R. China"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p7-t0","doc_id":"K250788","page_num":7,"bbox":[44.81,630.72,565.51,745.92],"n_rows":5,"n_cols":10,"columns":["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],"rows":[["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],["","","Discovery XR656 HD","","","Definium Tempo Select","","","between Definium Tempo",""],["","","K191699","","","K250788","","","Select and Predicate",""],["Intended Use","General Purpose Digital\nRadiographic Imaging System","","","General Purpose Digital\nRadiographic Imaging System","","","Identical","",""],["Indications\nfor Use","The Discovery XR656 HD is intended\nto generate digital radiographic\nimages of the skull, spinal column,\nchest, abdomen, extremities, and","","","The Definium Tempo Select is\nintended to generate digital\nradiographic images of the skull,\nspinal column, chest, abdomen,","","","Equivalent\nThe VolumeRAD is\nremoved from the\nproposed device.","",""]],"caption_candidate":"Table 1: High-level Comparison of Subject Device to Predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p8-t0","doc_id":"K250788","page_num":8,"bbox":[44.8,79.8,565.52,732.96],"n_rows":6,"n_cols":10,"columns":["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],"rows":[["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],["","","Discovery XR656 HD","","","Definium Tempo Select","","","between Definium Tempo",""],["","","K191699","","","K250788","","","Select and Predicate",""],["","other body parts in patients of all\nages. Applications can be performed\nwith the patient sitting, standing, or\nlying in the prone or supine position\nand the system is intended for use in\nall routine radiography exams.\nOptional image pasting function\nenables the operator to stitch\nsequentially acquired radiographs\ninto a single image.\nThe Discovery XR656 HD\nincorporates AutoGrid, which is an\noptional image processing software\ninstalled as a part of the systems\nHelix image processing software.\nAutoGrid can be used in lieu of an\nanti-scatter grid to improve image\ncontrast in general radiographic\nimages by reducing the effects of\nscatter radiation.\nWhen the VolumeRAD option is\nincluded on the system, the system\ncan generate tomographic images of\nhuman anatomy including the skull,\nspinal column, chest, abdomen,\nextremities, and other body parts in\npatients of all ages.\nWhen the VolumeRAD option is used\nfor patients undergoing thoracic\nimaging, it is indicated for the\ndetection of lung nodules.\nVolumeRAD generates diagnostic\nimages of the chest that aid the\nradiologist in achieving superior\ndetectability of lung nodules versus\nposterior-anterior and left lateral\nviews of the chest, at a comparable\nradiation level.\nThe device is not intended for\nmammographic applications.","","","extremities, and other body parts in\npatients of all ages. Applications\ncan be performed with the patient\nsitting, standing, or lying in the\nprone or supine position and the\nsystem is intended for use in all\nroutine radiography exams.\nOptional image pasting function\nenables the operator to stitch\nsequentially acquired radiographs\ninto a single image.\nThe device is not intended for\nmammographic applications.","","","","",""],["Contraindicat\nions","None known.","","","None known.","","","Identical","",""],["User group","Professional Use Only","","","Professional Use Only","","","Identical","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p9-t0","doc_id":"K250788","page_num":9,"bbox":[44.77,79.8,565.55,734.28],"n_rows":15,"n_cols":10,"columns":["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],"rows":[["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],["","","Discovery XR656 HD","","","Definium Tempo Select","","","between Definium Tempo",""],["","","K191699","","","K250788","","","Select and Predicate",""],["Patient\nPopulation","All ages","","","All ages","","","Identical","",""],["System\nSoftware\nArchitecture","Distributed software architecture\n(Atlas)","","","Distributed software architecture\n(Atlas)","","","Identical","",""],["Operator I/F","One-LCD monitor, Keyboard, Mouse,\nBarcode reader","","","One-LCD monitor, Keyboard, Mouse\nand Barcode reader","","","Identical","",""],["X-Ray Tube","MX 100","","","MX 100","","","Identical","",""],["Tube head\nconsole","6” LCD touch screen console","","","12” LCD touch screen console","","","Changed\nThe same function for\nmotion control and the UI\nchanged with more exam\ninformation synced with\nmain UI.","",""],["Collimator\nand Auto FOV","Automatic","","","Automatic","","","Identical","",""],["DAP","DAP software calculation based on\nFOV and SID measured by Encoder\nafter Dose calibration","","","DAP software calculation based on\nFOV and SID measured by Encoder\nafter Dose calibration","","","Identical","",""],["Camera\nWorkflow","The depth Camera provides:\n1. Live video on main UI","","","The same depth camera provides\nworkflow improvement based on\nthe predicate:\n1. Patient size suggestion based\non camera depth\nmeasurement.\n2. Detector and ion chamber\noutline on video.\n3. Patient Snapshot during exam.\n4. FOV adjustable from video in\nMain UI.","","","New\nThis new feature provides\nadditional observation for\npatient positioning.","",""],["High Voltage\nGenerator","- 50KW or 65KW or 80kW","","","- 50KW or 65KW or 80kW","","","Equivalent\nSame function, different\nsupplier.","",""],["DICOM","DICOM 3.0","","","DICOM 3.0","","","Identical.","",""],["Cabinet","GCC-C4 cabinet as power unit for HV\ngenerator and system","","","GCC-C5 cabinet as power unit for HV\ngenerator and system","","","Equivalent.\nThe GCC-C5 is changed to\naccommodate the\ngenerator.","",""],["Detector","FlashPad HD:\n10 x 12 detector (K161942)\n14 x 17 detector (K161966)\n17 x 17 detector (K181526)","","","FlashPad Select:\n17x17 detector (K210314)","","","Equivalent\nThe proposed device only\nuses the listed equivalent\n17 x 17 detector which is\nidentical to the reference\nproduct Definium Pace\nSelect cleared under\nK231892.","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p10-t0","doc_id":"K250788","page_num":10,"bbox":[44.78,79.8,565.54,734.76],"n_rows":13,"n_cols":10,"columns":["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],"rows":[["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],["","","Discovery XR656 HD","","","Definium Tempo Select","","","between Definium Tempo",""],["","","K191699","","","K250788","","","Select and Predicate",""],["Detector size/\nresolution","Three detector Size supported at\n100 um resolutions:\n17 x 17 inch\n14 x 17 inch\n10 x 12 inch","","","One detector Size supported at 100\num resolutions:\n17 x 17 inch","","","Identical\nRemoved 10 x 12 and 14 x\n17 detectors.","",""],["Detector\nloading","300kg (distributed loading)\n150kg (point loading)","","","300kg (distributed loading)\n150kg (point loading)","","","Identical","",""],["Detector\nWireless\nConnectivity","YES – 802.11 wireless (Personal Area\nNetwork)","","","YES – 802.11 wireless (Personal Area\nNetwork)","","","Identical","",""],["Patient Table","Elevating","","","Elevating","","","Equivalent\nThe table provides same\nfunction with minor travel\nrange and loading change","",""],["Wall stand","Motorized","","","Motorized","","","Equivalent\nMinor change on travel\nrange","",""],["Overhead\nTube\nSuspension\n( OTS)","5-axes motion controlled with Auto\nPositioning overhead tube support\n(OTS) from console position and\nlocal manual control","","","4-axes motion controlled with Auto\nPositioning overhead tube support\n(OTS) from console position and\nlocal manual control","","","Changed\nMotor and driver changed\nwith minor specification\nchange and the supplier\nchanged","",""],["Image Pasting\non Table and\nWall Stand\nMode","Image pasting can be performed at\nWall stand mode and Table mode","","","Image pasting can be performed at\nWall stand mode and Table mode.\nIndividual mA adjustable for fixed\nmode and ion chamber is\nchangeable in sub-image is\nprovided","","","Changed\nThe function of individual\nmA adjustable for fixed\nmode and ion chamber\nadjustable in sub-images is\nprovided. The registration\nand image process\nalgorithm are not changed.","",""],["Auto Grid\nOption","Yes\nVirtual grid function for DC (Digital\nCassette) mode","","","Yes\nVirtual grid function in Table, WS\n(Wall stand) and DC (Digital\nCassette) mode","","","Equivalent\nThe Auto-Grid algorithm is\nthe identical to the\npredicate device whilst\nonly DC (Digital Cassette)\nmode is used.\nIn the proposed device, we\nprovided Table, WS and DC\nmode Auto Grid which\nalgorithm is same with the\np redicate.","",""],["Auto tracking\nfor Wall Stand","Auto-tracking between Wall stand\nand tube stand vertically (OTS\ntracking WS)","","","Auto-tracking between Wall stand\nand tube stand vertically (OTS\ntracking WS and WS tracking OTS)","","","Changed\nThe tracking methods are\nsame, just added mutual\ntracking feature.","",""],["Auto tracking\nfor Table","Auto-tracking between Wall stand\nand tube stand vertically","","","Auto-tracking between Wall stand\nand tube stand vertically","","","Identical\nThe tracking method is\nsame.","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250788-p11-t0","doc_id":"K250788","page_num":11,"bbox":[44.81,79.8,565.51,415.56],"n_rows":5,"n_cols":10,"columns":["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],"rows":[["Specification","","Predicate Device","","","Proposed Device","","","Discussion of differences",""],["","","Discovery XR656 HD","","","Definium Tempo Select","","","between Definium Tempo",""],["","","K191699","","","K250788","","","Select and Predicate",""],["Auto\nPositioning","Tube can be motorized to defined\nposition via motorized 5 axis\nmotion.","","","Tube can be motorized to defined\nposition via motorized 4 axis\nmotion.\nTube can be automatically\nangulated according to the input on\ntube head console UI.","","","Equivalent\nAuto-position is simpler\nsince the column rotation\nmotorization is removed.\nThe tube angulation is\nadded, and it is a small\nfeature since it is only the\ntube rotates around its\ncenter. But the auto\npositioning method is\nequivalent.","",""],["Tissue\nEqualization","The image processing algorithm\nprovides pre-tuned and\nconfigurable thick and thin regions\nto improve contrast and visibility in\nover-penetrated and under-\npenetrated regions.","","","The image processing algorithm\nuses artificial intelligence to\ndynamically estimate thick and thin\nregions to improve contrast and\nvisibility in over-penetrated and\nunder-penetrated regions.","","","Changed\nThe algorithm is the same\nbut parameters per\nanatomy/view are\ndetermined by artificial\nintelligence to provide\nbetter consistence and\neasier user interface in the\nproposed device.","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250831-p6-t0","doc_id":"K250831","page_num":6,"bbox":[62.72,197.6,530.16,296.56],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Annalise-AI"],"rows":[["","Company Name","","Annalise-AI"],["Address","Address","","Level P, 24 Campbell Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","April 23, 2025"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250831-p6-t1","doc_id":"K250831","page_num":6,"bbox":[62.72,353.36,530.16,438.52],"n_rows":5,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI"],"rows":[["","Manufacturer Name","","Annalise-AI"],["","Device Name","","Annalise Enterprise"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM, QAS*"]],"caption_candidate":"II. SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250831-p6-t2","doc_id":"K250831","page_num":6,"bbox":[62.72,495.36,530.16,594.84],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Annalise-AI"],"rows":[["","Manufacturer Name","","Annalise-AI"],["","Device Name","","Annalise Enterprise CXR Triage Trauma"],["","510(k) reference","","K222179"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21CFR892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QFM, QAS*"]],"caption_candidate":"III. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250831-p11-t0","doc_id":"K250831","page_num":11,"bbox":[62.66,584.22,549.45,690.24],"n_rows":6,"n_cols":9,"columns":["","Finding","","","Product Code","","","AUC (95% CI)",""],"rows":[["","Finding","","","Product Code","","","AUC (95% CI)",""],["Pneumothorax","","","QFM","","","0.984 (0.976, 0.990)","",""],["Tension pneumothorax","","","QFM","","","0.989 (0.984, 0.994)","",""],["Pneumoperitoneum","","","QAS","","","0.987 (0.976, 0.994)","",""],["Pleural effusion","","","QFM","","","0.977 (0.969, 0.984)","",""],["Vertebral compression fracture","","","QFM","","","0.972 (0.960, 0.982)","",""]],"caption_candidate":"below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250831-p12-t0","doc_id":"K250831","page_num":12,"bbox":[62.79,85.41,549.33,449.4],"n_rows":27,"n_cols":4,"columns":["","","Sensitivity % (Se)","Specificity % (Sp)"],"rows":[["","","Sensitivity % (Se)","Specificity % (Sp)"],["Finding","Operating Point","",""],["","","(95% CI)","(95% CI)"],["","","",""],["Pneumothorax","0.200","97.1 (95.5,98.6)","88.2 (85.4,90.8)"],["","0.250","96.2 (94.3,98.1)","91.9 (89.5,94.1)"],["","0.300","95.0 (92.8,97.1)","94.1 (91.9,95.9)"],["","0.350","93.1 (90.7,95.5)","95.6 (93.7,97.2)"],["","0.400","90.7 (88.0,93.3)","96.7 (95.0,98.2)"],["Tension pneumothorax","0.225","96.0 (92.0,99.2)","94.0 (92.3,95.6)"],["","0.250","95.2 (91.2,98.4)","94.6 (93.1,96.2)"],["","0.300","93.6 (88.8,97.6)","95.6 (94.1,96.9)"],["","0.350","89.6 (84.0,94.4)","96.6 (95.3,97.8)"],["","0.400","87.2 (80.8,92.8)","97.5 (96.4,98.6)"],["Pneumoperitoneum","0.250","96.2 (92.4,99.0)","87.9 (83.2,92.1)"],["","0.300","94.3 (89.5,98.1)","90.5 (86.3,94.2)"],["","0.350","92.4 (86.7,97.1)","93.7 (90.0,96.8)"],["","0.400","91.4 (85.7,96.2)","95.8 (92.6,98.4)"],["","0.450","87.6 (81.0,93.3)","98.4 (96.3,100.0)"],["Pleural effusion","0.380","96.7 (95.0,98.1)","86.8 (83.6,89.5)"],["","0.425","94.4 (92.3,96.5)","89.5 (86.8,92.1)"],["","0.450","92.9 (90.7,95.0)","91.3 (88.6,93.7)"],["","0.475","89.8 (87.1,92.3)","93.7 (91.5,95.9)"],["","0.500","87.6 (84.6,90.5)","95.5 (93.5,97.0)"],["Vertebral compression fracture","0.460","93.4 (90.1,96.0)","85.8 (82.1,89.6)"],["","0.500","92.6 (89.3,95.6)","90.9 (87.7,93.7)"],["","0.550","87.1 (83.1,90.8)","94.7 (91.8,96.9)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p6-t0","doc_id":"K250886","page_num":6,"bbox":[248.15,475.32,567.54,604.82],"n_rows":8,"n_cols":4,"columns":["","Classification Description","21 CFR §","Product Code"],"rows":[["","Classification Description","21 CFR §","Product Code"],["","Primary","",""],["","System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],["","Secondary","",""],["","System, imaging, pulsed echo,\nultrasonic","892.1560","IYO"],["","Transducer, ultrasonic, diagnostic","892.1570","ITX"],["","Automated Radiological Image\nProcessing Software","892.2050","QIH"],["","Diagnostic Intravascular Catheter","870.1200","OBJ*"]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p6-t1","doc_id":"K250886","page_num":6,"bbox":[252.75,700.56,567.54,723.96],"n_rows":2,"n_cols":3,"columns":["Classification Description","21 CFR §","Product Code"],"rows":[["Classification Description","21 CFR §","Product Code"],["Primary","",""]],"caption_candidate":"Predicate Regulation Description","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p7-t0","doc_id":"K250886","page_num":7,"bbox":[254.55,61.2,569.37,167.52],"n_rows":6,"n_cols":3,"columns":["System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],"rows":[["System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],["Secondary","",""],["System, imaging, pulsed echo,\nultrasonic","892.1560","IYO"],["Transducer, ultrasonic, diagnostic","892.1570","ITX"],["Automated Radiological Image\nProcessing Software","892.2050","QIH"],["Diagnostic Intravascular Catheter","870.1200","OBJ*"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p11-t0","doc_id":"K250886","page_num":11,"bbox":[56.08,58.68,726.09,558.81],"n_rows":35,"n_cols":4,"columns":["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],"rows":[["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],["Feature","Feature: SVS v2","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["Primary Product","IYN","IYN","Identical to predicate"],["Code","","",""],["","","",""],["Primary","System, Imaging, Pulsed Doppler, Ultrasonic","System, Imaging, Pulsed Doppler, Ultrasonic","Identical to predicate"],["Regulation","","",""],["Name","","",""],["Primary","21 CFR 892.1550","21 CFR 892.1550","Identical to predicate"],["Regulation","","",""],["Number","","",""],["Secondary","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","Identical to predicate"],["Product Codes","","",""],["","","",""],["","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Identical to predicate"],["Secondary","","",""],["Regulation","","",""],["Name","","",""],["","","",""],["Secondary","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","Identical to predicate"],["Regulation","","",""],["Number","","",""],["","","",""],["Reusable-","Yes","Yes","Identical to predicate"],["Systems and","","",""],["Transducers","","",""],["Duration of use","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical to predicate"],["","Smart View Select is an automated software\nfeature that assists you in the selection of\nimages for analysis with the existing Philips\nAutoStrain LV or 2D Auto LV application in\nAdult Echo Transthoracic examination. This\nfeature automatically classifies each acquired\nimage by view and selects an appropriate set of\nimages for Left ventricle (LV) analysis. The\nclassification is based on a Deep Learning AI\ninterface engine; the selection is a non-AI","Smart View Select is an automated software\nfeature that assists you in the selection of\nimages for analysis with the existing Philips\nAutoStrain LV or 2D Auto LV application in\nAdult Echo Transthoracic examination. This\nfeature automatically classifies each acquired\nimage by view and selects an appropriate set\nof images for Left ventricle (LV) analysis. The\nclassification is based on a Deep Learning AI\ninterface engine; the selection is a non-AI","Identical to predicate"],["","","",""],["","","",""],["","","",""],["Application","","",""],["Description","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p12-t0","doc_id":"K250886","page_num":12,"bbox":[56.1,58.68,726.05,560.37],"n_rows":26,"n_cols":4,"columns":["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],"rows":[["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],["Feature","Feature: SVS v2","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","algorithm that considers the view classification\nand image depth to select the optimal set of\nimages.\nYou can launch AutoStrain LV or 2D Auto LV\nwith the set of images that have been\nautomatically selected without the need to\nreview the acquired images and manually\nselect the views.","algorithm that considers the view\nclassification and image depth to select the\noptimal set of images.\nYou can launch AutoStrain LV or 2D Auto LV\nwith the set of images that have been\nautomatically selected without the need to\nreview the acquired images and manually\nselect the views.",""],["","","",""],["","AI based neural network for optimal view\nselection","AI based neural network for optimal view\nselection","The subject SVS software\napplication utilizes a deep neural\nnetwork for view identification\nand optimal triplet (A4C, A2C, and\nA3C) selection for subsequent LV\nAnalysis. The neural network is\nutilized in a similar way as in the\npredicate device for the analysis\nstandard 2D echo examinations.\nThe neural network of the subject\ndevice was revised as described in\nattachment 002. Performance\ntesting has demonstrated very\nstrong correlation between the LV\nanalysis outputs (EF, GLS) from\nclips selected by the subject SVS\nsoftware application and clips\nmanually selected by clinical users."],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["Deep Neural","","",""],["Network","","",""],["Utilization for","","",""],["optimal triplet","","",""],["selection","","",""],["","","",""],["","Yes – the subject SVS software application\nuses an additional heuristic logic step, after the\ndeep neural network identifies the views and\ndetermines a list of 3\nclip combinations (triplets), to preferentially\nselect triplets of shallower scan depths.\nRestriction of depth on clinical images is 12-20\ncm.","Yes – the subject SVS software application\nuses an additional heuristic logic step, after\nthe deep neural network identifies the views\nand determines a list of 3 clip combinations\n(triplets), to preferentially select triplets of\nshallower scan depths, provided the depth\nexceeds 10cm and the variation of depths of\neach clips is 1cm or less.","The subject SVS software\napplication, similar to the predicate\ndevice(K240850), includes\nadditional heuristic logic step for\npreferentially selecting certain scan\ndepths. The logic was revised in the\nsubject device. Performance testing\nhas demonstrated very strong\ncorrelation between the LV analysis\noutputs (EF, GLS) from clips\nselected by the subject SVS\nsoftware application and clips\nmanually selected by clinical users.\nTherefore, the revision in the"],["","","",""],["","","",""],["","","",""],["Scan depth","","",""],["considered for","","",""],["optimal triplet","","",""],["selection?","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p13-t0","doc_id":"K250886","page_num":13,"bbox":[56.05,58.68,726.02,156.93],"n_rows":5,"n_cols":4,"columns":["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],"rows":[["","EPIQ Series Diagnostic Ultrasound System","EPIQ Series Diagnostic Ultrasound System",""],["Feature","Feature: SVS v2","K240850","Comparison"],["","Proposed Device","Predicate Device",""],["","","","additional heuristic logic step of the\nsubject SVS software does not raise\nnew or different questions of safety\nor effectiveness in comparison to\nthe predicate device K240850."],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p14-t0","doc_id":"K250886","page_num":14,"bbox":[60.74,58.68,721.29,552.34],"n_rows":37,"n_cols":4,"columns":["","Affiniti Series Diagnostic Ultrasound","EPIQ Series Diagnostic Ultrasound",""],"rows":[["","Affiniti Series Diagnostic Ultrasound","EPIQ Series Diagnostic Ultrasound",""],["","System","System",""],["Feature","","","Comparison"],["","Feature: SVS v2","K240850",""],["","","",""],["","Proposed Device","Predicate Device",""],["","Sonography training and clinical\nprocedures are not included in the\nUser Manual or with the Affiniti Series\nDiagnostic Ultrasound System.","included in the User Manual or with the\nEPIQ Series Diagnostic Ultrasound\nSystem.",""],["","","",""],["Intended User","Clinics, hospitals, and clinical point-of-\ncare for diagnosis of patients.","Clinics, hospitals, and clinical point-of-\ncare for diagnosis of patients.","Identical to predicate"],["Environment","","",""],["","","",""],["","Class II","Class II","Identical to predicate"],["USA FDA Classification","","",""],["","","",""],["","IYN","IYN","Identical to predicate"],["Primary Product Code","","",""],["","","",""],["","System, Imaging, Pulsed Doppler,\nUltrasonic","System, Imaging, Pulsed Doppler,\nUltrasonic","Identical to predicate"],["Primary Regulation Name","","",""],["","","",""],["Primary Regulation","21 CFR 892.1550","21 CFR 892.1550","Identical to predicate"],["Number","","",""],["","","",""],["Secondary Product","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","Identical to predicate"],["Codes","","",""],["","","",""],["","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular catheter\nAutomated Radiological Image\nProcessing Software","Identical to predicate"],["","","",""],["Secondary Regulation","","",""],["Name","","",""],["","","",""],["Secondary Regulation","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","Identical to predicate"],["Number","","",""],["","","",""],["Reusable- Systems and","Yes","Yes","Identical to predicate"],["Transducers","","",""],["Duration of use","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical to predicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p17-t0","doc_id":"K250886","page_num":17,"bbox":[60.78,58.68,721.22,300.93],"n_rows":16,"n_cols":4,"columns":["","Affiniti Series Diagnostic Ultrasound","EPIQ Series Diagnostic Ultrasound",""],"rows":[["","Affiniti Series Diagnostic Ultrasound","EPIQ Series Diagnostic Ultrasound",""],["","System","System",""],["Feature","","","Comparison"],["","Feature: SVS v2","K240850",""],["","","",""],["","Proposed Device","Predicate Device",""],["","Yes – the subject SVS software\napplication uses an additional\nheuristic logic step, after the deep\nneural network identifies the views\nand determines a list of 3\nclip combinations (triplets), to\npreferentially select triplets of\nshallower scan depths. Restriction of\ndepth on clinical images is 12-20 cm.","Yes – the subject SVS software\napplication uses an additional heuristic\nlogic step, after the deep neural network\nidentifies the views and determines a list\nof 3 clip combinations (triplets), to\npreferentially select triplets of shallower\nscan depths, provided the depth\nexceeds 10cm and the variation of\ndepths of each clips is 1cm or less.","The subject SVS software application,\nsimilar to the predicate\ndevice(K240850), includes additional\nheuristic logic step for preferentially\nselecting certain scan depths. The\nlogic was revised in the subject device.\nPerformance testing has demonstrated\nvery strong correlation between the LV\nanalysis outputs (EF, GLS) from clips\nselected by the subject SVS software\napplication and clips manually selected\nby clinical users. Therefore, the\nrevision in the additional heuristic logic\nstep of the subject SVS software does\nnot raise new or different questions of\nsafety or effectiveness in comparison\nto the predicate device K240850."],["","","",""],["","","",""],["","","",""],["","","",""],["","","",""],["Scan depth considered","","",""],["for optimal triplet","","",""],["selection?","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250886-p19-t0","doc_id":"K250886","page_num":19,"bbox":[126.24,57.24,477.0,735.36],"n_rows":34,"n_cols":2,"columns":["Female","46.5% (33/71)"],"rows":[["Female","46.5% (33/71)"],["Age (years, mean ± SD (range))","61.0 ± 16.4 (23.0, 89.0)"],["Height (cm, mean ± SD (range))","171.4 ± 12.1 (145.0, 198.0)"],["Weight (kg, mean ± SD (range))","87.7 ± 21.4 (47.2, 164.5)"],["BSA (m², mean ± SD (range))","2.0 ± 0.3 (1.4, 2.8)"],["BMI (kg/m², mean ± SD (range))","29.7 ± 6.7 (17.7, 57.6)"],["",""],["Race",""],["White","35.2% (25/71)"],["Asian","0.0% (0/71)"],["Black or African American","60.6% (43/71)"],["American Indian or Alaska Native","0.0% (0/71)"],["Native Hawaiian or Other Pacific Islander","0.0% (0/71)"],["Mixed/More than one race","1.4% (1/71)"],["Other/Unknown/Not Reported","2.8% (2/71)"],["",""],["LV systolic function",""],["Normal","46 (64.79%)"],["Mild","4 (5.63%"],["Moderate","10 (14.08%)"],["Severe","11 (15.49%)"],["",""],["RWMA",""],["Normal","40 (56.34%)"],["Not Reported","27 (38.03%)"],["Abnormal","4 (5.63%)"],["",""],["Known CAD","Not Reported"],["",""],["Previous reported MI Location",""],["None","71 (100.00%)"],["",""],["LV Hypertrophy",""],["No","42 (59.15%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250901-p5-t0","doc_id":"K250901","page_num":5,"bbox":[93.42,221.0,527.02,300.56],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Fortian / Orian 1.5T, MRT-1550, V10.0 with AiCE\nReconstruction Processing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250901-p6-t0","doc_id":"K250901","page_num":6,"bbox":[90.24,512.02,365.02,599.98],"n_rows":5,"n_cols":2,"columns":["System","Predicate Device"],"rows":[["System","Predicate Device"],["","Vantage Fortian/Orian 1.5T, MRT-1550, V9.0\nwith AiCE Reconstruction Processing Unit for\nMR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K240238"],["Clearance Date","April 12, 2024"]],"caption_candidate":"for MR (K240238)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250901-p7-t0","doc_id":"K250901","page_num":7,"bbox":[90.24,133.28,351.52,221.24],"n_rows":5,"n_cols":2,"columns":["System","Reference Device"],"rows":[["System","Reference Device"],["","Vantage Galan 3T, MRT-1550, V10.0 with\nAiCE Reconstruction Processing Unit for\nMR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K243335"],["Clearance Date","January 7, 2025"]],"caption_candidate":"(K243335)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250901-p8-t0","doc_id":"K250901","page_num":8,"bbox":[95.0,405.26,558.53,670.06],"n_rows":12,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Fortian/Orian 1.5T,","","","Vantage Fortian/Orian 1.5T,","",""],["","","MRT-1550, V10.0","","","MRT-1550, V9.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR","",""],["Static field strength","1.5T","","","1.5T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"20. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250914-p6-t0","doc_id":"K250914","page_num":6,"bbox":[59.5,362.33,554.18,795.84],"n_rows":31,"n_cols":9,"columns":["","","","Subject Device","","","Predicate Device (K234042)","",""],"rows":[["","","","Subject Device","","","Predicate Device (K234042)","",""],["","Device(Trade)","","MediAI-BA","","","EFAI BAPXR","",""],["","Name","","","","","","",""],["","Classification","","","Automated Radiological Image","","","Automated Radiological Image",""],["","Name","","","Processing Software","","","Processing Software",""],["Product Code","","","QIH","","","QIH","",""],["","Regulation","","21 CFR 892.2050","","","21 CFR 892.2050","",""],["","Number","","","","","","",""],["","Regulatory","","Class II","","","Class II","",""],["","Class","","","","","","",""],["Intended\nUse/Indication\nfor Use","","","","The MediAI-BA is designed to view","","EFAI BONESUITE XR BONE AGE\nPRO ASSESSMENT SYSTEM (EFAI\nBAPXR) is designed to view and\nquantify bone age from 2D Posterior\nAnterior (PA) view of left-hand\nradiographs using deep learning\ntechniques to aid in the analysis of\nbone age assessment of patients\nbetween 2 to 16 years old for pediatric\nradiologists. The results should not be\nrelied upon alone by pediatric\nradiologists to make diagnostic\ndecisions. The images shall be with\nleft hand and wrist fully visible within\nthe field of view, and\nshall be without any major bone\ndestruction, deformity, fracture,\nexcessive motion, or other major\nartifacts.","",""],["","","","","and quantify bone age from 2D","","","",""],["","","","","Posterior Anterior (PA) view of left-","","","",""],["","","","","hand radiographs using deep learning","","","",""],["","","","","techniques to aid in the analysis of","","","",""],["","","","","bone age assessment of patients","","","",""],["","","","","between 2 to 18 years old for pediatric","","","",""],["","","","","radiologists. The results should not be","","","",""],["","","","","relied upon alone by pediatric","","","",""],["","","","","radiologists to make diagnostic","","","",""],["","","","","decisions. The images shall be with","","","",""],["","","","","left hand and wrist fully visible within","","","",""],["","","","","the field of view, and shall be without","","","",""],["","","","","any major bone destruction, deformity,","","","",""],["","","","","fracture, excessive motion, or other","","","",""],["","","","","major artifacts.","","","",""],["","","","","","","","",""],["","","","","Limitations:","","","",""],["","","","","– This software is not intended for use","","","",""],["","","","","in patients with growth disorders","","","",""],["","","","","caused by congenital anomalies (e.g.,","","","",""]],"caption_candidate":" Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250914-p7-t0","doc_id":"K250914","page_num":7,"bbox":[59.5,47.26,554.18,682.3],"n_rows":45,"n_cols":7,"columns":["","","","","Down syndrome, Noonan syndrome,","",""],"rows":[["","","","","Down syndrome, Noonan syndrome,","",""],["","","","","congenital adrenal hyperplasia,","",""],["","","","","methylmalonic acidemia, skeletal","",""],["","","","","dysplasia, chronic renal disease, or","",""],["","","","","prior long-term steroid exposure), as","",""],["","","","","these conditions may cause complex","",""],["","","","","skeletal changes beyond bone","",""],["","","","","maturation.","",""],["","","","","– Images showing anatomical","",""],["","","","","variations or notable abnormalities","",""],["","","","","(e.g., bone tumors, sequelae of","",""],["","","","","fractures, or congenital deformities) in","",""],["","","","","the region required for interpretation","",""],["","","","","are excluded from the intended use.","",""],["","Environment","","Healthcare facility/Hospital","","","Healthcare facility/Hospital"],["","of Use","","","","",""],["Intended User","","","Pediatric radiologist","","","Pediatric radiologist"],["","Clinical","","Bone age assessment","","","Bone age assessment"],["","Condition","","","","",""],["Image Input","","","Complies with DICOM standard","","","Complies with DICOM standard"],["Scan Type","","","X-ray","","","X-ray"],["","Anatomical","","Left hand and wrist","","","Left hand and wrist"],["","Area","","","","",""],["","Image Display","","Static","","","Static"],["","Mode","","","","",""],["","Artificial","","Yes","","","Yes"],["","Intelligence","","","","",""],["","Algorithm","","","","",""],["","Image","","No","","","No"],["","Navigation and","","","","",""],["","Manipulation","","","","",""],["","Tools","","","","",""],["","2D Image","","No","","","No"],["","Review","","","","",""],["","Manual","","No","","","No"],["","Landmark","","","","",""],["","Placement","","","","",""],["","Semi-","","No","","","No"],["","automatic","","","","",""],["","Landmark","","","","",""],["","Placement","","","","",""],["","Quantitative","","Bone age assessment (years)","","","Bone age assessment (years)"],["","Analysis","","","","",""],["","Report","","Yes","","","No"],["","Creation","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250941-p8-t0","doc_id":"K250941","page_num":8,"bbox":[72.07,454.26,539.9,718.56],"n_rows":5,"n_cols":3,"columns":["Subsystem","Revolution Apex Elite","Revolution Vibe"],"rows":[["Subsystem","Revolution Apex Elite","Revolution Vibe"],["","(Predicate Device, K213715)","(Proposed Device)"],["Gantry"," 80 cm patient bore\n Rotation Speeds: 0.23, 0.28, 0.35,\n0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0\nseconds per rotation.","Same"],["Detector"," 160 mm Z-coverage\n 256 rows, 0.625 mm pixel pitch\n Low capacitance backlit\nphotodiode\n Gemstone Scintillator Material\n Detector Thermal System (DTS)\nwith higher RPM fans"," Up to 160 mm in Z with 320 mm SFOV; Up\nto 40 mm in Z with up to 50 mm SFOV\n 256 rows, 0.625 mm pixel pitch within 320\nmm SFOV; 64 rows, 0.625 mm pixel within\n500 mm SFOV\n Low capacitance backlit photodiode\n Gemstone Scintillator Material\n Detector Thermal System (DTS) with higher\nRPM fans"],["Reconstruction","FBP\nASIR-V (K133640)\nDLIR (K183202, K213999, K201745)\nMaxFOV 2 (K203617)","Same"]],"caption_candidate":"the predicate and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p5-t0","doc_id":"K250959","page_num":5,"bbox":[72.24,402.96,330.24,521.52],"n_rows":5,"n_cols":2,"columns":["Trade Name","BioticsAI"],"rows":[["Trade Name","BioticsAI"],["Common Name","Ultrasonic pulsed doppler imaging system"],["Classification Name","System, Imaging, Pulsed Doppler, Ultrasonic"],["Regulation Number","21 CFR 892.1550"],["Product Code(s)","IYN, IYO, QIH"]],"caption_candidate":"2. DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p5-t1","doc_id":"K250959","page_num":5,"bbox":[72.24,567.6,292.56,685.92],"n_rows":5,"n_cols":2,"columns":["Predicate Device Name","Sonio Detect"],"rows":[["Predicate Device Name","Sonio Detect"],["Manufacturer","Sonio"],["510(k) Number","K240406"],["Product Code","IYN, IYO, QIH"],["Regulation Number","21 CFR 892.1550"]],"caption_candidate":"3. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p7-t0","doc_id":"K250959","page_num":7,"bbox":[72.48,514.56,539.52,744.96],"n_rows":6,"n_cols":2,"columns":["Label","Label Criteria"],"rows":[["Label","Label Criteria"],["Head (also referred to as\n“Brain”)","One of “Transcerebellar” plane, “Transthalamic” plane, or the\n“Transventricular” plane"],["Face","One of “Median Facial Profile” plane, “Coronal Plane of Upper Lip,\nNose, and Nostrils” plane, or “Orbits, Lenses” plane"],["Thorax/Chest (Also\nreferred to as “Heart\nScreening Planes”)","One of the “Right Ventricular Outflow Tract” plane, “Three-Vessel\nView” plane, “Three-Vessel and Trachea View” plane, “Left Ventricular\nOutflow Tract” plane, or “Thorax Four-Chamber Heart View” plane"],["Abdomen","One of “Bladder Plane ”, “Kidneys Plane”, “Stomach Umbilical Plane“,\nor “Cord Insertion Plane”"],["Limbs","Do one or more of these elements exist:\n● The tibia is present\n● The fibula is present"]],"caption_candidate":"Table 1: AI-1 Outputs / High Level Anatomy Classification Label Criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p9-t0","doc_id":"K250959","page_num":9,"bbox":[72.36,158.76,539.4,725.4],"n_rows":26,"n_cols":2,"columns":["Structure","Views the Structure is found in (hence we only predict the visibility of\nstructures within these views)"],"rows":[["Structure","Views the Structure is found in (hence we only predict the visibility of\nstructures within these views)"],["Bladder","Abdomen Bladder"],["Cord Insertion","Abdomen Cord Insertion"],["Kidney","Abdomen Kidneys"],["Abdominal Aorta","Abdomen Stomach Umbilical"],["Inferior Vena Cava","Abdomen Stomach Umbilical"],["Stomach Shadow","Abdomen Stomach Umbilical"],["Floating Ribs","Abdomen Stomach Umbilical Vein"],["Umbilical Vein","Abdomen Stomach Umbilical vein"],["Ossification Center Of The\nSpine","Abdomen Stomach Umbilical, Abdomen Kidneys, Heart Screening Planes,\nThorax 4 Chamber Heart, Spine Sagittal"],["Lower Lip","Face Coronal Upper lip Nose Nostrils, Face Median Facial Profile"],["Upper Lip","Face Coronal Upper lip Nose Nostrils, Face Median Facial Profile"],["Chin","Face Median Facial Profile"],["Frontal Bone","Face Median Facial Profile"],["Maxilla","Face Median Facial Profile"],["Nasal Bone","Face Median Facial Profile"],["Skin Overlying The\nForehead","Face Median Facial Profile"],["Nose","Face Median Facial Profile, Face Coronal Upperlip Nose Nostrils"],["Orbits","Face Orbits Lenses"],["Cerebellum","Head Transcerebellar"],["Cerebral Peduncles","Head Transcerebellar"],["Cisterna Magna","Head Transcerebellar"],["Falx Cerebri","Head Transthalamic, Head Transventricular"],["Septum Pellucidum","Head Transthalamic, Head Transventricular"],["Atria","Head Transventricular"],["Choroid Plexus","Head Transventricular"]],"caption_candidate":"Table 3: AI-3 Outputs / Fetal Anatomical Structures and Regions Label Criteria","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p10-t0","doc_id":"K250959","page_num":10,"bbox":[72.36,98.52,539.4,559.08],"n_rows":22,"n_cols":2,"columns":["Lateral Ventricle Posterior\nHorn Walls","Head Transventricular"],"rows":[["Lateral Ventricle Posterior\nHorn Walls","Head Transventricular"],["Parito Occipital Sulcus","Head Transventricular"],["CSP","Head Transventricular, Head Transthalamic"],["Lateral Sulcus","Head Transventricular, Head Transthalamic"],["Thalami","Head Transventricular, Head Transthalamic"],["Aorta","Heart Screening Planes"],["LVOT","Heart Screening Planes"],["Pulmonary Artery","Heart Screening Planes"],["RVOT","Heart Screening Planes"],["Superior Vena Cava","Heart Screening Planes"],["Thymus Gland","Heart Screening Planes"],["Left Ventricle","Heart Screening Planes, Thorax 4 Chamber Heart"],["Lungs","Heart Screening Planes, Thorax 4 Chamber Heart"],["Right Atrium","Heart Screening Planes, Thorax 4 Chamber Heart"],["Right Ventricle","Heart Screening Planes, Thorax 4 Chamber Heart"],["Septum Primum","Heart Screening Planes, Thorax 4 Chamber Heart"],["Ventricular Septum","Heart Screening Planes, Thorax 4 Chamber Heart"],["Descending Aorta","Heart Screening Planes, Thorax 4 Chamber Heart"],["Left Atrium","Heart Screening Planes, Thorax 4 Chamber Heart"],["Ribs","Heart Screening Planes, Thorax 4 Chamber Heart"],["Femur","Limbs Femur"],["Skin Overlying The Spine","Spine Sagittal"]],"caption_candidate":"BioticsAI 510(k) Summary Page 6 of 12","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p11-t0","doc_id":"K250959","page_num":11,"bbox":[72.49,377.93,539.34,747.0],"n_rows":9,"n_cols":3,"columns":["Feature/Fun","",""],"rows":[["Feature/Fun","",""],["ction","Proposed Device: BioticsAI","Predicate Device: Sonio Detect (K240406 )"],["Manufacture\nName","BioticsAI, Inc.","Sonio"],["Device Name","BioticsAI","Sonio Detect"],["Regulation\nNumber","21 CFR 892.1550 - accessory to Ultrasonic Pulsed\nDoppler Imaging System\n21 CFR 892.1560 - accessory to Ultrasonic Pulsed\nEcho Imaging System\n21 CFR 892.2050 - Medical Image Management\nand Processing System","21 CFR 892.1550 - accessory to Ultrasonic\nPulsed Doppler Imaging System\n21 CFR 892.1560 - accessory to Ultrasonic\nPulsed Echo Imaging System\n21 CFR 892.2050 - Medical Image Management\nand Processing System"],["Product Code","IYN (primary)\nIYO, QIH (Secondary)","IYN (primary)\nIYO, QIH (Secondary)"],["Intended\nUsers","Qualified and trained healthcare professional\npersonnel in a professional prenatal ultrasound\n(US) imaging environment (this includes\nsonographers, MFMs, OB/GYN, and Fetal\nsurgeons)","Qualified and trained healthcare professional\npersonnel in a professional prenatal ultrasound\n(US) imaging environment (this includes\nsonographers, MFMs, OB/GYN, and Fetal\nsurgeons)"],["Features","- BioticsAI automatically detects views\n- BioticsAI automatically detects anatomical\nstructures within the supported views\n- BioticsAI provides an interface to the operator\nthat shows BioticsAI’s automatic anatomical\nfindings, allowing the operator to verify the\nquality criteria and characteristics of the supported\nviews.","- Sonio Detect automatically detects views\n- Sonio Detect automatically detects anatomical\nstructures within the supported views\n- Sonio Detect automatically verifies the quality\ncriteria and characteristics of the supported\nviews."],["Algorithm\nMethodology","Artificial Intelligence (Computer Vision)","Artificial Intelligence (Computer Vision)"]],"caption_candidate":"Table 4: Comparison of Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p12-t0","doc_id":"K250959","page_num":12,"bbox":[71.76,98.52,540.08,235.08],"n_rows":3,"n_cols":3,"columns":["Platform","Secure cloud-based software compatible with\nstandard DIMSE integration with ultrasound\nsystems from GE Medical","Secure cloud-based and stand-alone software\ncompatible with ultrasound systems from GE\nMedical, Samsung, Canon and Philips"],"rows":[["Platform","Secure cloud-based software compatible with\nstandard DIMSE integration with ultrasound\nsystems from GE Medical","Secure cloud-based and stand-alone software\ncompatible with ultrasound systems from GE\nMedical, Samsung, Canon and Philips"],["Real Time?","No","No"],["System\nCompatibility","BioticsAI requires the following:\n- Clinical support for exporting DICOM over\nDIMSE to BioticsAI’s DICOM Adapter.\n- SaaS accessibility from an internet browser\n(recommended browser: Google Chrome).","Sonio Detect requires the following:\n- Edge Software (described below) to install on\na server on the same network as the Ultrasound\nMachine;\n- SaaS accessibility from any internet browser\n(recommended browser: Google Chrome)."]],"caption_candidate":"BioticsAI 510(k) Summary Page 8 of 12","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p13-t0","doc_id":"K250959","page_num":13,"bbox":[72.4,149.76,539.6,744.96],"n_rows":6,"n_cols":5,"columns":["Items (fetal ultrasound views detected)","Sensitivity","","Specificity",""],"rows":[["Items (fetal ultrasound views detected)","Sensitivity","","Specificity",""],["","Point\nEstima\nte","Bootstrappi\nng CI\n(95%)","Point\nEstima\nte","Bootstrappi\nng CI\n(95%)"],["AI-1 High Level Anatomy:\nFetal “Abdomen” View\nDetection across any of:\n(“Bladder Plane ”,, “Kidneys Plane”, “Stomach\nUmbilical Plane“, “Cord Insertion Plane”)","0.953","(0.942,\n0.962)","0.986","(0.984,\n0.989)"],["AI-1 High Level Anatomy:\nFetal “Face” View,\nDetection across any of:\n(“Median Facial Profile Plane”, “Coronal Plane of\nUpper Lip, Nose, and Nostrils Plane”, “Orbits,\nLenses Plane”)","0.944","(0.932,\n0.956)","0.993","(0.991,\n0.994)"],["AI-1 High Level Anatomy:\nFetal “Head” Planes,\nDetection across any of:\n(“Transthalamic Plane”, “Transventricular Plane”,\n“Transcerebellar Plane”)","0.955","(0.946,\n0.964)","0.996","(0.995,\n0.997)"],["AI-1 High Level Anatomy:\nAutomatic detection of the Fetal “Limbs”\ncharacterized across, 10 potential visual elements\nDetection across any of:\n-tibia\n-fibula\n-foot\n-ankle region, “relationship between the tibia,\nfibula, and foot”\n-humerus\n-radius\n-ulna\n-wrist region, “relationship between the hand,\nradius, and ulna”\n-hand\n-femur","0.919","(0.895,\n0.943)","0.983","(0.981,\n0.985)"]],"caption_candidate":"Table 5: Results of Standalone Performance Testing for AI-1: High-Level Anatomy Classification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p14-t0","doc_id":"K250959","page_num":14,"bbox":[72.37,277.8,490.2,712.92],"n_rows":14,"n_cols":3,"columns":["Class","Sensitivity\nBootstrapping CI (95%)","Specificity\nBootstrapping CI (95%)"],"rows":[["Class","Sensitivity\nBootstrapping CI (95%)","Specificity\nBootstrapping CI (95%)"],["abdomen_bladder","0.960\n(0.940, 0.977)","0.998\n(0.997, 0.998)"],["abdomen_cord_insertion","0.965\n(0.947, 0.983)","0.998\n(0.997, 0.999)"],["abdomen_kidneys","0.953\n(0.927, 0.973)","0.998\n(0.997, 0.999)"],["abdomen_stomach_umbilical_vein","0.990\n(0.982, 0.997)","1.000\n(1.000, 1.000)"],["face_coronal_of_upperlip_nose_nostrils","0.981\n(0.968, 0.993)","0.999\n(0.999, 1.000)"],["face_median_facial_profile","1.000\n(1.000, 1.000)","0.999\n(0.998, 1.000)"],["face_orbits_lenses","0.897\n(0.863, 0.927)","0.999\n(0.999, 1.000)"],["head_transcerebellar","0.998\n(0.994, 1.000)","1.000\n(0.999, 1.000)"],["head_transthalamic","0.923\n(0.899, 0.945)","0.992\n(0.991, 0.994)"],["head_transventricular","0.975\n(0.964, 0.984)","1.000\n(1.000, 1.000)"],["limbs_femur","0.955\n(0.944, 0.966)","0.992\n(0.990, 0.994)"],["spine_sagittal","0.909\n(0.891, 0.927)","0.995\n(0.993, 0.996)"],["thorax_lungs_four_heart_chambers","0.969\n(0.954, 0.983)","0.997\n(0.996, 0.998)"]],"caption_candidate":"Classification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p15-t0","doc_id":"K250959","page_num":15,"bbox":[72.48,123.84,539.52,732.24],"n_rows":8,"n_cols":7,"columns":["Items (fetal ultrasound\nviews,\nanatomical structures\nand\ncharacteristics\nautomatically\ndetected)","Sensitivity Across\nDiagnostically\nAcceptable Images","","Sensitivity Across\nall Image Qualities","","Specificity Across\nall Image Qualities",""],"rows":[["Items (fetal ultrasound\nviews,\nanatomical structures\nand\ncharacteristics\nautomatically\ndetected)","Sensitivity Across\nDiagnostically\nAcceptable Images","","Sensitivity Across\nall Image Qualities","","Specificity Across\nall Image Qualities",""],["","Point\nEstima\nte","Bootstrapping\nCI (95%)","Point\nEstim\nate","Bootstrappi\nng CI\n(95%)","Point\nEstim\nate","Bootstrappi\nng CI\n(95%)"],["Automatic detection of 5\nHigh-Level Fetal\nAnatomy Sections\n(Abdomen, Face, Head,\nLimbs, Thorax)","-","-","0.934","(0.929, 0.94)","0.989","(0.988, 0.99)"],["Automatic detection of 13\nfetal ultrasound planes\n(Per-class Top-1\nclassification)","-","-","0.960","(0.955,\n0.964)","0.997","(0.997,\n0.998)"],["Automatic detection of 12\nfetal head\nanatomical structures on\nthe views\n“Transthalamic”,\n“Transventricular”,\n“Transcerebellar”","0.948","(0.935, 0.959)","0.881","(0.871,\n0.891)","0.991","(0.99, 0.992)"],["Automatic detection of 9\nfetal abdomen\nanatomical structures on\nthe views\n“Bladder”,\n“Kidneys”,\n“Stomach Umbilical\nVein”,\n“Cord Insertion”","0.953","(0.941, 0.964)","0.919","(0.909, 0.93)","0.983","(0.982,\n0.984)"],["Automatic detection of 9\nfetal face\nanatomical structures on\nthe views\n“Coronal Plane of Upper\nLip, Nose, and Nostriles”,\n“Median Facial Profile”,\n“Orbits, Lenses”","0.983","(0.976, 0.989)","0.958","(0.951,\n0.965)","0.991","(0.99, 0.992)"],["Automatic detection of 2\nfetal spine","0.992","(0.989, 0.996)","0.975","(0.97, 0.98)","0.927","(0.921,\n0.931)"]],"caption_candidate":"Top-1 Fetal Plane Classification”, and “AI-3: Fetal Anatomical Structure Classification”","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250959-p16-t0","doc_id":"K250959","page_num":16,"bbox":[72.48,98.64,539.52,285.12],"n_rows":2,"n_cols":7,"columns":["anatomical structures on\nthe views\n“Sagittal Spine”","","","","","",""],"rows":[["anatomical structures on\nthe views\n“Sagittal Spine”","","","","","",""],["Automatic detection of 16\nfetal thorax and heart\nanatomical structures on\nthe views\n“Four Chamber”,\n“LVOT”,\n“RVOT”,\n“3VV”,\n“3VT”","0.978","(0.969, 0.985)","0.925","(0.911,\n0.939)","0.989","(0.988, 0.99)"]],"caption_candidate":"BioticsAI 510(k) Summary Page 12 of 12","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250999-p9-t0","doc_id":"K250999","page_num":9,"bbox":[120.52,569.59,524.6,686.38],"n_rows":6,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","IEC 60601-1:2005, IEC 60601-1:2005/AMD1:2012, IEC 60601-\n1:2005/AMD2:2020","",""],["IEC 60601-1-2","","","IEC 60601-1-2:2014, IEC 60601-1-2:2014/AMD1:2020","",""],["IEC 60601-2-37","","","IEC 60601-2-37 (ed.2), am1 for use in conjunction with IEC60601-\n1 (ed.3), am1 with Corr1 and Corr2","",""],["IEC 60601-4-2","","","IEC TS 60601-4-2:2024","",""],["ISO10993-1","","","ISO 10993-1:2018, Biological evaluation of medical devices – Part 1:\nEvaluation and testing within a risk management process","",""]],"caption_candidate":"applications comply with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K250999-p10-t0","doc_id":"K250999","page_num":10,"bbox":[120.53,92.54,524.59,157.22],"n_rows":3,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["ISO14971","","","ISO 14971:2019, Medical devices - Application of risk management\nto medical devices","",""],["NEMA UD 2-\n2004","","","NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard\nfor Diagnostic Ultrasound Equipment Revision 3","",""]],"caption_candidate":"510(k) Premarket Notification – Traditional","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p6-t0","doc_id":"K251002","page_num":6,"bbox":[72.0,39.27,301.93,676.02],"n_rows":39,"n_cols":3,"columns":["510(k) Summary","",""],"rows":[["510(k) Summary","",""],["","",""],["In accordance with 21 CFR 80","","7.87(h) and 21 C"],["Dental AI device is provided b","","elow."],["","",""],["1. S UBMITTER","",""],["","",""],["Applicant:","","VideaHealth, Inc"],["","","179 South Street"],["","","Boston, MA, 021"],["","","+1 617-340-994"],["","","florian@videa.ai"],["","",""],["Contact & Submission","","Adam Foresman"],["Correspondent:","","Director of Qual"],["","","VideaHealth, Inc"],["","","+1 617-340-994"],["","","adam@videa.ai"],["","",""],["Date Prepared:","","September 17, 2"],["","",""],["2. D EVICE","",""],["","",""],["Device Trade Name:","V","idea Dental AI"],["","",""],["Device Common Name:","D","ental AI System"],["","",""],["Classification Name:","","Medical image an"],["","",""],["Classification Regulation","2","1 CFR 892.2070"],["Number:","",""],["","",""],["Device Class:","2",""],["","",""],["Product Code:","","MYN"],["","",""],["3. P REDICATE D EVI","C","E"],["","",""],["Predicate Device: K232384","","VideaHealth’s Vi"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251002-p6-t1","doc_id":"K251002","page_num":6,"bbox":[67.5,171.5,485.5,357.5],"n_rows":3,"n_cols":2,"columns":["Applicant:","VideaHealth, Inc.\n179 South Street, Floor 5\nBoston, MA, 02111\n+1 617-340-9940\nflorian@videa.ai"],"rows":[["Applicant:","VideaHealth, Inc.\n179 South Street, Floor 5\nBoston, MA, 02111\n+1 617-340-9940\nflorian@videa.ai"],["Contact & Submission\nCorrespondent:","Adam Foresman\nDirector of Quality & Regulatory Affairs\nVideaHealth, Inc.\n+1 617-340-9940\nadam@videa.ai"],["Date Prepared:","September 17, 2025"]],"caption_candidate":"1. S UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p6-t2","doc_id":"K251002","page_num":6,"bbox":[67.5,417.5,489.5,595.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","Videa Dental AI"],"rows":[["Device Trade Name:","Videa Dental AI"],["Device Common Name:","Dental AI System"],["Classification Name:","Medical image analyzer"],["Classification Regulation\nNumber:","21 CFR 892.2070"],["Device Class:","2"],["Product Code:","MYN"]],"caption_candidate":"2. D EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p7-t0","doc_id":"K251002","page_num":7,"bbox":[72.25,641.27,540.25,730.5],"n_rows":3,"n_cols":3,"columns":["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],"rows":[["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],["Caries","3 years and older","Bitewing and Periapical"],["Attrition","3 years and older","Bitewing and Periapical"]],"caption_candidate":"Table 1: VDA Indications Scope by Patient Age and Image Modality Type","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p8-t0","doc_id":"K251002","page_num":8,"bbox":[72.33,72.13,540.33,678.5],"n_rows":11,"n_cols":3,"columns":["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],"rows":[["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],["Broken/Chipped","3 years and older","Bitewing and Periapical"],["Restorative Imperfection","3 years and older","Bitewing and Periapical"],["Pulp Stone","12+ years of age and\nolder with permanent\ndentition","Bitewing and Periapical"],["Dens Invaginatus","3 years & older","Bitewing and Periapical"],["Periapical Radiolucency","22 years of age and\nolder with permanent\ndentition","Periapical only"],["Furcation","22 years of age and\nolder with permanent\ndentition","Bitewing and Periapical"],["Calculus","3 years and older","Bitewing and Periapical"],["Widened PDL","3 years and older","Bitewing and Periapical"],["Historical Treatments: All Indications","3 years and older","All on Bitewing,\nPeriapical & Panoramic\nexcept:\n1.‘Screw’ VDA\nhistorical treatment\nidentification is only on\nPanoramic images.\n2.‘Plate’ VDA historical\ntreatment indication is\nonly on Panoramic\nimages."],["Normal Anatomy: All Indications","12 years and older","1. Impacted Tooth\n2. Mental Foramen\n3. Maxillary Tuberosity\nOn Bitewing, Periapical\n& Panoramic"]],"caption_candidate":"510(k) Summary Page 3 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p9-t0","doc_id":"K251002","page_num":9,"bbox":[72.33,72.13,540.33,246.5],"n_rows":2,"n_cols":3,"columns":["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],"rows":[["Videa Dental Assist Indication","Patient Age in Scope","Radiographic View in\nScope"],["","3 years and older","All other indications are\non Bitewing, Periapical\n& Panoramic except:\n1.‘Mandibular Condyle’\nVDA normal anatomy\nindication is only on\nPanoramic images."]],"caption_candidate":"510(k) Summary Page 4 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p11-t0","doc_id":"K251002","page_num":11,"bbox":[66.25,90.61,545.29,624.6],"n_rows":11,"n_cols":3,"columns":["","Proposed Device","Proposed Device"],"rows":[["","Proposed Device","Proposed Device"],["510(k) Number","K251002","K232384"],["Applicant","VideaHealth, Inc.","VideaHealth, Inc."],["Device Name","Videa Dental AI","Videa Dental Assist"],["Classification Regulation","892.2070","892.2070"],["Product Code","MYN","MYN"],["Image Modality","X-Ray","X-Ray"],["Radiograph View Type","Bitewing Images, Periapical\nImages, and Panoramic\nImages.\nRadiograph view type scope is\nVidea Dental Assist indication\nspecific.","Bitewing Images, Periapical\nImages, and Panoramic\nImages.\nRadiograph view type scope is\nVidea Dental Assist indication\nspecific."],["Suspect Dental Findings\nIndications","Caries: Active and Secondary\nCaries at all penetration depths\nAdditional Suspect Dental\nFindings listed in the Videa\nDental Assist’s Indications For\nUse statement.","Caries: Active and Secondary\nCaries at all penetration depths\nAdditional Suspect Dental\nFindings listed in the Videa\nDental Assist’s Indications For\nUse statement."],["Historical Treatment and\nNormal Anatomy\nIndications","Included","Included"],["Tooth Surface","For the caries indication only:\nProximal, Buccal/Lingual,\nOcclusal, Root, Cervical.\nNone of the additional VDA\n‘Suspect Dental Finding’\nindications are specific to a\ntooth surface.","For the caries indication only:\nProximal, Buccal/Lingual,\nOcclusal, Root, Cervical.\nNone of the additional VDA\n‘Suspect Dental Finding’\nindications are specific to a\ntooth surface."]],"caption_candidate":"Table 2: Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p12-t0","doc_id":"K251002","page_num":12,"bbox":[66.25,72.13,545.31,661.5],"n_rows":7,"n_cols":3,"columns":["","Proposed Device","Proposed Device"],"rows":[["","Proposed Device","Proposed Device"],["Clinical Output","Message indicating if and how\nmany findings were detected\nfor each enabled Videa Dental\nAI’s indication for use.\nAll Videa Dental AI’s\nindications use a set of\ntogglable bounding boxes\naround suspected areas of\ninterest.\nThe user has the option to\ntoggle to segmentation view\n(also called isocontour view)\ninstead of bounding boxes for\ncaries and calculus.\nThe user has the option to\ntoggle between operating\npoints (high sensitivity vs.\nhigh specificity) for a caries\nand periapical radiolucency.\nThe user has the option to\ntoggle normal tooth anatomy\nsegmentations including\nenamel, pulp, crown dentin\nand root dentin on and off.","Message indicating if and how\nmany findings were detected\nfor each enabled Videa Dental\nAssist’s indication for use.\nAll Videa Dental Assist’s\nindications use a set of\ntoggleable bounding boxes\naround suspected areas of\ninterest."],["Patient Population","Patients ≥ 3 years of age.\nPatient age range is Videa\nDental Assist indication\nspecific.","Patients ≥ 3 years of age.\nPatient age range is Videa\nDental Assist indication\nspecific."],["Intended User","Dental professionals","Dental professionals"],["Development Technology","Supervised Deep Learning","Supervised Deep Learning"],["Image Source","X-Ray Sensor","X-Ray Sensor"],["Image Viewing","Image Viewer","Image Viewer"]],"caption_candidate":"510(k) Summary Page 7 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p15-t0","doc_id":"K251002","page_num":15,"bbox":[77.38,87.75,241.06,277.5],"n_rows":7,"n_cols":2,"columns":["Subject Age\n(Years)","Percentage"],"rows":[["Subject Age\n(Years)","Percentage"],["3 - 11","28%"],["12 - 21","20%"],["22 - 40","14%"],["41 - 60","14%"],["61 and older","8%"],["Unknown","15%"]],"caption_candidate":"Table 5: Demographic breakdown by age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251002-p15-t1","doc_id":"K251002","page_num":15,"bbox":[77.38,353.18,241.06,480.5],"n_rows":4,"n_cols":2,"columns":["Radiographic\nView","Percentage"],"rows":[["Radiographic\nView","Percentage"],["Bitewing","56%"],["Periapical","44%"],["Panoramic","N/A. Not in\nscope."]],"caption_candidate":"Table 6: Image breakdown by radiographic view","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251027-p7-t0","doc_id":"K251027","page_num":7,"bbox":[20.29,105.24,591.83,694.8],"n_rows":13,"n_cols":9,"columns":["","Measurement [units]","","","Description","","","Display",""],"rows":[["","Measurement [units]","","","Description","","","Display",""],["Calcified Plaque (CP)\nVolume [mm3]","","","The volume of calcified plaque (CP) in a lesion or all the lesions\nin a vessel.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Non-Calcified Plaque\n(NCP) Volume [mm3]","","","The volume of non-calcified plaque (NCP) in a lesion or all the\nlesions in a vessel.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Low-Attenuation Plaque\n(LAP) Volume [mm3]","","","The volume of low-attenuation plaque (LAP) in a lesion or all\nthe lesions in a vessel; LAP volume is also included in NCP\nvolume.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Total Plaque Volume\n[mm3]","","","The volume of total plaque including CP and NCP (with LAP) in\na lesion or all the lesions in a vessel.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Calcified Plaque (CP)\nBurden [%]","","","The burden of CP in a lesion or the whole vessel; obtained by\ndividing the CP volume by the lesion vessel wall or entire vessel\nvolume, as appropriate.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Non-Calcified Plaque\n(NCP) Burden [%]","","","The burden of NCP in a lesion or the whole vessel; obtained by\ndividing the NCP volume by the lesion vessel wall or entire\nvessel volume, as appropriate.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Low-Attenuation Plaque\n(LAP) Burden [%]","","","The burden of LAP in a lesion or the whole vessel; obtained by\ndividing the LAP volume by the lesion vessel wall or entire\nvessel volume, as appropriate.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Total Plaque Burden\n[%]","","","The burden of total plaque in a lesion or the whole vessel;\nobtained by dividing the total plaque volume by the lesion\nvessel wall or entire vessel volume, as appropriate.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Remodeling Index [no\nunit]","","","A measure of enlargement of vessel dimensions to\naccommodate plaque development compared to normal vessel\nsections; it is expressed as the ratio of the largest diameter\nacross the lesion and reference diameter (or maximum vessel\nwall cross-sectional area and reference vessel wall cross-\nsectional area).","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Diameter-Based\nStenosis [%]","","","Stenosis expressed as the percent amount of reduced lumen\ndiameter compared with reference diameter.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Area-Based Stenosis\n[%]","","","Stenosis expressed as the percent amount of reduced lumen\narea compared with reference area.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""],["Lesion Length [mm]","","","The length of the lesion.","","","• On Screen Data Panel\n• Coronaries (Plaque)\nModule Report","",""]],"caption_candidate":"Table 1. Measurements in the Coronary Plaque Module","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251027-p10-t0","doc_id":"K251027","page_num":10,"bbox":[9.85,105.24,782.15,526.68],"n_rows":18,"n_cols":9,"columns":["Feature","","Subject Device","","","Primary Predicate","","Secondary Predicate\nCleerly Labs (K190868)\nManufactured by Cleerly Inc","Comparison"],"rows":[["Feature","","Subject Device","","","Primary Predicate","","Secondary Predicate\nCleerly Labs (K190868)\nManufactured by Cleerly Inc","Comparison"],["","","Coronary Plaque Module","","","cvi42 Auto (K213998)","","",""],["","","","","","","","",""],["","","Manufactured by Circle","","","Manufactured by Circle","","",""],["","","Cardiovascular Imaging Inc.","","","Cardiovascular Imaging Inc.","","",""],["Device Class","II","","","II","","","II","Same as predicate device(s)"],["Product Code","QIH, LLZ","","","QIH, LLZ","","","LLZ","Same as primary predicate device,\nsecondary predicate uses AI/ML\nfunctionality."],["Regulation Name","Medical image management and\nprocessing system","","","Medical image management and\nprocessing system","","","Picture archiving and\ncommunications system","Same as primary predicate device,\nsecondary predicate uses AI/ML\nfunctionality."],["Regulation Number","21 CFR § 892.2050","","","21 CFR § 892.2050","","","21 CFR § 892.2050","Same as predicate device(s)"],["Computer operating system","macOS, Microsoft Windows","","","macOS, Microsoft Windows","","","Client-Server Google Chrome\nApplication","Same as primary predicate device.\nCore functionality of subject\ndevice unaffected by OS. No\nsafety or effectiveness concerns\n."],["Imaging Modalities","CT","","","MR and CT","","","CT","Same as the predicate device(s)\nwith the exception that the primary\npredicate also allows MR inputs."],["DICOM Compliant","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["Import and display CT images","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["Post process CCT images","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["Images can be displayed by\nstudy and series","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["2D Imaging","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["2D Measurement","Yes","","","Yes","","","Yes","Same as predicate device(s)"],["3D Imaging","Yes","","","Yes","","","Yes","Same as predicate device(s)"]],"caption_candidate":"Table 3. Regulatory and technological features comparison.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251027-p11-t0","doc_id":"K251027","page_num":11,"bbox":[9.85,93.12,782.15,508.32],"n_rows":9,"n_cols":5,"columns":["Multiplanar reformatting (MPR)","Yes","Yes","Yes","Same as predicate device(s)"],"rows":[["Multiplanar reformatting (MPR)","Yes","Yes","Yes","Same as predicate device(s)"],["Segmentation of Region of\nInterest","Manual and Semi-Automatic (using\nMachine Learning technique)\nSegmentation of Coronary Vessels,\nIncluding Lumen and Vessel Wall\nStructures.","Manual and Semi-Automatic (using\nMachine Learning technique)\nCenterline Generation of the\nCoronary Vessels.","Manual and Semi-Automatic (using\nMachine Learning Technique)\nSegmentation of Coronary Vessels,\nIncluding Lumen and Vessel Wall\nStructures.","Same as the predicate device(s),\nwith the exception that the primary\npredicate does not offer\nsegmentation of the lumen and\nvessel wall structures.\nThe successful passing of the\nV&V performance testing has\ndemonstrated that the addition of\nsemi-automatic segmentation of\nthe lumen and vessel wall\nstructures does not raise new\nquestions of safety."],["Plaque Thresholds","Yes","No","Yes","Both the subject device and\nsecondary predicate device\nprovide plaque thresholds."],["Measurements","","","",""],["Signal Density [HU]","Yes","Yes","Yes","Same as predicate device(s)"],["Distance Measurements\n(Vessel, Lesion, Length) [mm]","Yes","Yes","Yes","Same as predicate device(s)"],["Volumetric Plaque\nMeasurements [mm3]","- Non-Calcified Plaque (NCP)\n- Low-Attenuation Plaque (LAP)\n- Calcified Plaque (CP)\n- Total Plaque","- Calcified Plaque (CP)","- Total Vessel\n- Total Lumen\n- Non-Calcified Plaque (NCP)\n- Low-Density Non-Calcified Plaque\n(LD-NCP)\n- Calcified Plaque (CP)\n- Total Plaque","The subject device and the\nsecondary predicate display the\nsame measurements, with the\nexception of Total Vessel and\nTotal Lumen – which are\ncalculated but not reported as a\ndevice output."],["Remodeling Index","Yes","No","Yes","Same as the secondary predicate\ndevice."],["Stenosis [%]","- Diameter-Based Stenosis\n- Area-Based Stenosis","- Diameter-Based Stenosis\n- Area-Based Stenosis","- Diameter-Based Stenosis\n- Area-Based Stenosis","Same as predicate device(s)"]],"caption_candidate":"Coronary Plaque Module 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251027-p13-t0","doc_id":"K251027","page_num":13,"bbox":[139.56,196.32,472.32,348.0],"n_rows":9,"n_cols":3,"columns":["Endpoint","Results","Pass / Fail"],"rows":[["Endpoint","Results","Pass / Fail"],["Lumen Mean DSC","0.76","Pass"],["Wall Mean DSC","0.80","Pass"],["Lumen Mean HD","0.77 mm","Pass"],["Wall Mean HD","0.87 mm","Pass"],["TP PCC","0.97","Pass"],["CP PCC","0.99","Pass"],["NCP PCC","0.93","Pass"],["LAP PCC","0.74","Pass"]],"caption_candidate":"(PCC). All performance testing results met Circle’s pre-defined acceptance criteria.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p5-t0","doc_id":"K251029","page_num":5,"bbox":[94.25,252.61,543.8,436.52],"n_rows":5,"n_cols":2,"columns":["Submitter Name","Vista AI, Inc."],"rows":[["Submitter Name","Vista AI, Inc."],["Submitter Address","431 Florence Street\nSuite 100\nPalo Alto, CA 94301"],["Establishment Registration #","3011767965"],["Primary Contact","James Jochen Rogers\nFDA Regulatory Affairs, Quality Assurance, and Clinical Studies\nT: 724.713.2298\nE: jr@vista.ai"],["Submission Date","April 2, 2025"]],"caption_candidate":"Administrative Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p5-t1","doc_id":"K251029","page_num":5,"bbox":[94.25,506.98,543.8,723.3],"n_rows":9,"n_cols":2,"columns":["Trade / Proprietary Name","Vista OS, Vista AI Scan, RTHawk"],"rows":[["Trade / Proprietary Name","Vista OS, Vista AI Scan, RTHawk"],["Common Name","RTHawk"],["Product Version","RTHawk 3.3.0"],["Regulation Number","892.1000"],["Regulation Name","Magnetic resonance diagnostic device (MRDD)"],["Regulatory Class","Class II"],["Device Classification Name","System, Nuclear Magnetic Resonance Imaging"],["Classification Panel","Radiology"],["Classification Product Code","LNH"]],"caption_candidate":"Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p6-t0","doc_id":"K251029","page_num":6,"bbox":[94.07,202.63,544.33,251.2],"n_rows":2,"n_cols":4,"columns":["510(k) #","Device","510(k) Sponsor","Clearance Date"],"rows":[["510(k) #","Device","510(k) Sponsor","Clearance Date"],["K212233","RTHawk, HeartVista Cardiac Package","HeartVista, Inc.","October 5, 2021"]],"caption_candidate":"Predicate Device(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p8-t0","doc_id":"K251029","page_num":8,"bbox":[94.07,228.58,473.16,365.35],"n_rows":6,"n_cols":2,"columns":["Safety Parameter","Safety Level"],"rows":[["Safety Parameter","Safety Level"],["Magnetic Field Strength","1.5T, 3.0T"],["Operating Modes","IEC 60601-2-33 1st Level Operating Mode"],["Safety Parameter Display","SAR, dB/dt"],["Max SAR","< 4 W/kg whole-body"],["Max dB/dt","1st Level Operating Mode"]],"caption_candidate":"RTHawk operates compatible MR scanners within the safety parameters listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p9-t0","doc_id":"K251029","page_num":9,"bbox":[94.07,363.34,533.76,684.54],"n_rows":9,"n_cols":2,"columns":["Reference #","Title"],"rows":[["Reference #","Title"],["IEC 60601-2-33:2022-08\n(Ed. 4.0)","Medical electrical equipment - Part 2-33: Particular requirements\nfor the basic safety and essential performance of magnetic\nresonance equipment for medical diagnosis (radiology)"],["IEC 60601-1:2020 (Ed.\n3.2)","Medical electrical equipment - Part 1: General requirements for\nbasic safety and essential performance; Section 14 Programmable\nElectrical Medical Systems (PEMS)"],["MS1-2008","Determination of Signal-to-Noise Ratio (SNR) in Diagnostic\nMagnetic Resonance Imaging"],["MS3-2008","Determination of Image Uniformity in Diagnostic Magnetic\nResonance Images"],["MS4-2010","Acoustic Noise Measurement Procedure for Diagnostic Magnetic\nResonance Imaging Devices"],["MS8-2016","Characterization of the Specific Absorption Rate (SAR) for\nMagnetic Resonance Imaging Systems"],["NEMA PS3.1 - 3.20\n(2023e)","Digital Imaging And Communications In Medicine (DICOM) Set"],["ISO 14971:2019","Medical Devices - Application Of Risk Management To Medical\nDevices"]],"caption_candidate":"table below, as applicable to device features and components:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p13-t0","doc_id":"K251029","page_num":13,"bbox":[70.82,501.91,553.49,732.46],"n_rows":3,"n_cols":3,"columns":["Attribute","RTHawk 3.0.0, K212233","RTHawk 3.3.0: Subject Device"],"rows":[["Attribute","RTHawk 3.0.0, K212233","RTHawk 3.3.0: Subject Device"],["Device Name","RTHawk, HeartVista Cardiac Package","Vista OS, Vista AI Scan, RTHawk"],["Indications for Use","RTHawk is an accessory to 1.5T and 3.0T\nwhole-body magnetic resonance diagnostic\ndevices (MRDD or MR). It is intended to\noperate alongside, and in parallel with, the\nexisting MR console to acquire traditional,\nreal-time and accelerated images.\nThe HeartVista Cardiac Package is a collection\nof RTHawk Apps designed to acquire,\nreconstruct and display cardiovascular MR\n(CMR) images. RTHawk produces static and\ndynamic transverse, coronal, sagittal, and\noblique cross-sectional images that display the\ninternal structures and/or functions of the entire\nbody. The images produced reflect the spatial\ndistribution of nuclei exhibiting magnetic\nresonance. The magnetic resonance properties\nthat determine image appearance are proton\ndensity, spin-lattice relaxation time (T1),","Vista OS is an accessory to 1.5T and 3.0T\nwhole-body magnetic resonance diagnostic\ndevices (MRDD). It is intended to operate\nalongside, and in parallel with, the existing MR\nconsole to acquire traditional, real-time and\naccelerated images.\nVista OS software controls the MR scanner to\nacquire, reconstruct and display static and\ndynamic transverse, coronal, sagittal, and\noblique cross-sectional images that display the\ninternal structures and/or functions of the entire\nbody. The images produced reflect the spatial\ndistribution of nuclei exhibiting magnetic\nresonance. The magnetic resonance properties\nthat determine image appearance are proton\ndensity, spin-lattice relaxation time (T1),\nspin-spin relaxation time (T2) and flow. When\ninterpreted by a trained physician, these"]],"caption_candidate":"The following compares the modified device to the predicate device K212233:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p14-t0","doc_id":"K251029","page_num":14,"bbox":[70.99,146.21,553.66,735.98],"n_rows":20,"n_cols":3,"columns":["","spin-spin relaxation time (T2) and flow. When\ninterpreted by a trained physician, these\nimages provide information that may assist in\nthe determination of a diagnosis.\nRTHawk is intended for use as an accessory to\nthe following MRI systems:\nManufacturers: GE Healthcare (GEHC),\nSiemens Healthineers\nField Strengths: 1.5T and 3.0T\nGE Software Versions: 12, 15, 16, 23, 24, 25,\n26\nSiemens Software Versions: N4/VE; NX/VA","images provide information that may assist in\nthe determination of a diagnosis.\nVista OS is intended for use as an accessory to\nthe following MRI systems:\nManufacturers:: GE Healthcare (GEHC),\nSiemens Healthineers\nField Strength:: 1.5T and 3.0T\nGE Software Versions:: 12, 15, 16, 23, 24, 25,\n26, 30\nSiemens Software Versions:: N4/VE; NX/VA"],"rows":[["","spin-spin relaxation time (T2) and flow. When\ninterpreted by a trained physician, these\nimages provide information that may assist in\nthe determination of a diagnosis.\nRTHawk is intended for use as an accessory to\nthe following MRI systems:\nManufacturers: GE Healthcare (GEHC),\nSiemens Healthineers\nField Strengths: 1.5T and 3.0T\nGE Software Versions: 12, 15, 16, 23, 24, 25,\n26\nSiemens Software Versions: N4/VE; NX/VA","images provide information that may assist in\nthe determination of a diagnosis.\nVista OS is intended for use as an accessory to\nthe following MRI systems:\nManufacturers:: GE Healthcare (GEHC),\nSiemens Healthineers\nField Strength:: 1.5T and 3.0T\nGE Software Versions:: 12, 15, 16, 23, 24, 25,\n26, 30\nSiemens Software Versions:: N4/VE; NX/VA"],["Scanner\nCompatibility","GE Healthcare, Siemens Healthineers","GE Healthcare, Siemens Healthineers"],["Magnetic Field\nStrengths","1.5T, 3.0T","1.5T, 3.0T"],["Shift/Advance Table","No","No"],["Imaging Planes","Transverse, Coronal, Sagittal, Oblique,\nDouble Oblique","Transverse, Coronal, Sagittal, Oblique,\nDouble Oblique"],["Pulse Sequences","",""],["","B0 Mapping","B0 Mapping"],["","","Brain Localizer"],["","Cardiac Localizer","Cardiac Localizer"],["","Cardiac T1 Map","Cardiac T1 Map"],["","Cardiac T2 Map","Cardiac T2 Map"],["","Cardiac T2* Map Spiral","Cardiac T2* Map Spiral"],["","Cardiac T2* Map Cartesian","Cardiac T2* Map Cartesian"],["","Cartesian Shimming","Cartesian Shimming"],["","Cine Cartesian SSFP","Cine Cartesian SSFP"],["","Cine DE Cal","Cine DE Cal"],["","","Cine Flow Calibration"],["","Cine Spiral SSFP","Cine Spiral SSFP"],["","FB DE GRE Cal","FB DE GRE Cal"],["","FB DE GRE","FB DE GRE"]],"caption_candidate":"+1 650-800-7937 | info@vista.ai | vista.ai","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251029-p15-t0","doc_id":"K251029","page_num":15,"bbox":[70.99,146.21,553.66,731.75],"n_rows":25,"n_cols":3,"columns":["","FB DE SSFP","FB DE SSFP"],"rows":[["","FB DE SSFP","FB DE SSFP"],["","FB MS Tagging GRE","FB MS Tagging GRE"],["","FB Multi-Slice GRE","FB Multi-Slice GRE"],["","FB Multi-Slice SSFP","FB Multi-Slice SSFP"],["","","Frequency Scout"],["","Gated 3D MRA GRE","Gated 3D MRA GRE"],["","Gated High-Res GRE","Gated High-Res GRE"],["","Gated Double-IR FSE","Gated Double-IR FSE"],["","HART GRE","HART GRE"],["","HART SSFP","HART SSFP"],["","Multi-Slice Cine Flow","Multi-Slice Cine Flow"],["","Multi-Slice DE GRE","Multi-Slice DE GRE"],["","Multi-Slice DE SSFP","Multi-Slice DE SSFP"],["","Nav 3D DE GRE","Nav 3D DE GRE"],["","Noise Measurement","Noise Measurement"],["","","Prostate Localizer"],["","Real-Time Loc GRE","Real-Time Loc GRE"],["","Real-Time Loc SSFP","Real-Time Loc SSFP"],["","Real-Time Color PC","Real-Time Color PC"],["","Single-BH 3D DE GRE","Single-BH 3D DE GRE"],["","Stack of Spiral Cine Flow","Stack of Spiral Cine Flow"],["","Time-Course GRE","Time-Course GRE"],["","Wait","Wait"],["Remote Imaging and\nSupport","Yes","Yes"],["Automated Scan\nPlanning","Yes","Yes"]],"caption_candidate":"+1 650-800-7937 | info@vista.ai | vista.ai","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251059-p8-t0","doc_id":"K251059","page_num":8,"bbox":[87.53,135.06,739.26,515.22],"n_rows":6,"n_cols":12,"columns":["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],"rows":[["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],["Device name and\nversion","Device name and","","Syngo Carbon Clinicals (VA41)\nK251059","Syngo Carbon Clinicals (VA41)","","Syngo Carbon Clinicals (VA30)\nK232856","Syngo Carbon Clinicals (VA30)","","","New version of the",""],["","version","","","K251059","","","K232856","","","predicate device with",""],["","","","","","","","","","","added features",""],["Indications for use","","","Syngo Carbon Clinicals is intended to provide\nadvanced visualization tools to prepare and process\nthe medical image for evaluation, manipulation and\ncommunication of clinical data that was acquired by\nthe medical imaging modalities (for example, CT,\nMR, etc.)\nOrthoMatic Spine provides the means to perform\nmusculoskeletal measurements of the whole spine, in\nparticular spine curve angle measurements.\nThe TimeLens provides the means to compare a\nregion of interest between multiple time points.\nThe software package is designed to support\ntechnicians and physicians in qualitative and\nquantitative measurements and in the analysis of\nclinical data that was acquired by medical imaging\nmodalities.\nAn interface shall enable the connection between the\nSyngo Carbon Clinicals software package and the\ninterconnected software solution for viewing,\nmanipulation, communication, and storage of medical\nimages.","","","Syngo Carbon Clinicals is intended to provide\nadvanced visualization tools to prepare and process the\nmedical image for evaluation, manipulation and\ncommunication of clinical data that was acquired by\nthe medical imaging modalities (for example, CT,\nMR, etc.)\nThe software package is designed to support\ntechnicians and physicians in qualitative and\nquantitative measurements and in the analysis of\nclinical data that was acquired by medical imaging\nmodalities.\nAn interface shall enable the connection between the\nSyngo Carbon Clinicals software package and the\ninterconnected software solution for viewing,\nmanipulation, communication, and storage of medical\nimages.","","","Indications adapted to\ninclude the new features","",""],["Contraindications","","","Syngo Carbon Clinicals is not indicated for\nmammography images for diagnosis in the U.S.\nSyngo Carbon Clinicals is not to be used as a sole\nbasis for clinical decisions","","","Syngo Carbon Clinicals is not indicated for\nmammography images for diagnosis in the U.S.\nSyngo Carbon Clinicals is not to be used as a sole basis\nfor clinical decisions","","","Same","",""]],"caption_candidate":"comparison table:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251059-p9-t0","doc_id":"K251059","page_num":9,"bbox":[87.5,67.86,739.3,479.04],"n_rows":6,"n_cols":12,"columns":["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],"rows":[["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],["Software\narchitecture","","","Syngo Carbon Clinicals has architecture that is based\non a layered pattern where the various clinical\ntools/functionality are decomposed into\nmodules/common tools which provide their\nindividual functionalities.","","","Syngo Carbon Clinicals has architecture that is based\non a layered pattern where the various clinical\ntools/functionality are decomposed into\nmodules/common tools which provide their\nindividual functionalities.","","","Same","",""],["Image\ncommunication","","","Syngo Carbon Clinicals relies on the interfacing\napplication for Image communication.","","","Syngo Carbon Clinicals relies on the interfacing\napplication for Image communication.","","","Same","",""],["Image display\nalgorithms","","","• Rendering Tools: Cinematic Insight","","","• Rendering Tools: Cinematic Insight","","","Same","",""],["Measurement,\nEvaluation/Interpr\netation\nTools","","","• Oncological evaluation:\nLesion Quantification\no\nAssisted Perpendicular Tool\no\nLung Nodule Marker\no\nTime Lens\no\n• Orthopaedic measurements:\nManual calibration\no\nOrthoMatic Spine\no","","","• Oncological evaluation:\nLesion Quantification\no\nAssisted Perpendicular Tool\no\nLung Nodule Marker\no\n• Orthopaedic measurements:\nManual calibration\no","","","Time Lens tool enables\ncomparison of a region of\ninterest between multiple\ntimepoints.\nOrthoMatic Spine tool\nprovides automated\ncalculation of spine\nmeasurements in CR and\nDX images.","",""],["Supported objects\nfor display","","","DICOM image object display\n• CT Image\n• DX Image\n• CR Image","","","DICOM image object display\n• CT Image\n• DX Image\n• CR Image","","","Same","",""]],"caption_candidate":"©Siemens Healthineers AG, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251059-p10-t0","doc_id":"K251059","page_num":10,"bbox":[87.49,67.86,739.31,521.52],"n_rows":10,"n_cols":12,"columns":["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],"rows":[["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],["Operating\nsystem","","","None\nSyngo Carbon Clinicals relies on the interfacing\napplication for operating system.","","","None\nSyngo Carbon Clinicals relies on the interfacing\napplication for operating system.","","","Same","",""],["Impact on Image\nAcquisition\nDevices","","","None\nSyngo Carbon Clinicals provides advanced\nvisualization tools to prepare and process the\nmedical images and it has no influence on the image\nacquisition devices","","","None\nSyngo Carbon Clinicals provides advanced\nvisualization tools to prepare and process the medical\nimages and it has no influence on the image\nacquisition devices","","","Same","",""],["CAD\nFunctionalities","","","None\nNo automated diagnostic interpretation capabilities\nlike CAD are included. All image data are to be\ninterpreted by trained personnel.","","","None\nNo automated diagnostic interpretation capabilities\nlike CAD are included. All image data are to be\ninterpreted by trained personnel.","","","Same","",""],["Clinical condition\nthe device is\nintended to\ndiagnose, treat, or\nmanage","","","No limitation on the clinical condition\nof the patient","","","No limitation on the clinical condition\nof the patient","","","Same","",""],["Intended patient\npopulation","","","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","","","No limitation concerning the patient\npopulation (e.g., age, weight, health,\ncondition)","","","Same","",""],["Site of the body\nthe device is\nintended to be\nused","","","No limitation concerning region of\nbody or tissue type","","","No limitation concerning region of\nbody or tissue type","","","Same","",""],["Intended use\nenvironment","","","Syngo Carbon Clinicals offers a wide range of tools\nfrom the major clinical fields, i.e. general radiology,\noncology environments.","","","Syngo Carbon Clinicals offers a wide range of tools\nfrom the major clinical fields, i.e. general radiology,\noncology environments.","","","Same","",""],["Intended\nuser(s)","","","Trained healthcare professionals","","","Trained healthcare professionals","","","Same","",""],["Device Type","","","Software application","","","Software application","","","Same","",""]],"caption_candidate":"©Siemens Healthineers AG, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251059-p11-t0","doc_id":"K251059","page_num":11,"bbox":[87.5,67.86,739.3,265.02],"n_rows":7,"n_cols":12,"columns":["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],"rows":[["","Specification","","","Subject Device","","","Predicate Device","","","Comparison",""],["Cyber Security","","","The cybersecurity aspects for Syngo Carbon\nClinicals is handled by the interfacing/hosting\nsystem.","","","The cybersecurity aspects for Syngo Carbon Clinicals\nis handled by the interfacing/hosting system.","","","Same","",""],["Graphical user\ninterface","","","Not offered by Syngo Carbon Clinicals, it relies on\nthe hosting applications","","","Not offered by Syngo Carbon Clinicals, it relies on\nthe hosting applications","","","Same","",""],["Image\nArchiving","","","Not offered by Syngo Carbon Clinicals","","","Not offered by Syngo Carbon Clinicals","","","Same","",""],["Annotation\nTool","","","Not offered by Syngo Carbon Clinicals","","","Not offered by Syngo Carbon Clinicals","","","Same","",""],["Printing","","","Not offered by Syngo Carbon Clinicals","","","Not offered by Syngo Carbon Clinicals","","","Same","",""],["Online help\nsystem","","","Yes, with search, indexing, filtering, library function\nand document collections","","","Yes, with search, indexing, filtering, library function\nand document collections","","","Same","",""]],"caption_candidate":"©Siemens Healthineers AG, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p2-t0","doc_id":"K251071","page_num":2,"bbox":[257.72,472.18,570.36,513.58],"n_rows":3,"n_cols":2,"columns":["Imaging Software Team",""],"rows":[["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"]],"caption_candidate":"Assistant Director","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p4-t0","doc_id":"K251071","page_num":4,"bbox":[67.5,118.5,485.5,288.5],"n_rows":7,"n_cols":2,"columns":["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],"rows":[["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],["",""],["Contact:","Christophe Gardella\nChief Technical Officer\nTel. +0033686543950\nEmail. christophe@brightheart.fr"],["",""],["Submission Correspondent:","Christophe Gardella"],["",""],["Date Prepared:","April 7, 2025"]],"caption_candidate":"UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p4-t1","doc_id":"K251071","page_num":4,"bbox":[67.5,335.5,489.5,436.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name:","Fetal EchoScan v1.1"],"rows":[["Device Trade Name:","Fetal EchoScan v1.1"],["Device Common Name:","Medical image analyzer"],["Classification Name","Radiological computer-assisted diagnostic software for\nlesions suspicious for cancer 21 CFR 892.2060"],["Regulatory Class:","Class II"],["Product Code:","POK"]],"caption_candidate":"EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p5-t0","doc_id":"K251071","page_num":5,"bbox":[66.25,611.49,545.37,704.5],"n_rows":4,"n_cols":3,"columns":["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],"rows":[["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],["510(k) Number","TBD","K242342"],["Applicant","BrightHeart","BrightHeart"],["Classification Regulation","892.2060","892.2060"]],"caption_candidate":"Table 1. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p6-t0","doc_id":"K251071","page_num":6,"bbox":[66.33,72.13,545.42,693.5],"n_rows":9,"n_cols":3,"columns":["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],"rows":[["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],["Product Code","POK","POK"],["Device Type","SaMD","SaMD"],["Software algorithm","Machine Learning Model","Machine Learning Model"],["Imaging Modality","Fetal Ultrasound","Fetal Ultrasound"],["Model Inputs","Fetal ultrasound study containing\nthe following views: 4 chamber, left\nventricular outflow tract, right\nventricular outflow tract","Fetal ultrasound study containing\nthe following views: 4 chamber, left\nventricular outflow tract, right\nventricular outflow tract"],["Model method","Suspicious radiographic findings\ncategorized into 2 groups:\n● “classification” features are\nbased on the identification of\nmorphological features within\nthe video clip.\n● “measurement” features are\nbased on the detection and\nsegmentation of key anatomic\npoints","Suspicious radiographic findings\ncategorized into 2 groups:\n● “classification” features are\nbased on the identification of\nmorphological features within\nthe video clip.\n● “measurement” features are\nbased on the detection and\nsegmentation of key anatomic\npoints"],["Model trained to identify","Identifiable suspicious radiographic\nfindings of the fetal heart\n● overriding artery\n● septal defect at the cardiac crux\n● abnormal relationship of the\noutflow tracts\n● enlarged cardiothoracic ratio\n● right ventricular to left\nventricular size discrepancy\n● tricuspid valve to mitral valve\nannular size discrepancy\n● pulmonary valve to aortic valve\nannular size discrepancy\n● cardiac axis deviation","Identifiable suspicious radiographic\nfindings of the fetal heart\n● overriding artery\n● septal defect at the cardiac crux\n● abnormal relationship of the\noutflow tracts\n● enlarged cardiothoracic ratio\n● right ventricular to left\nventricular size discrepancy\n● tricuspid valve to mitral valve\nannular size discrepancy\n● pulmonary valve to aortic valve\nannular size discrepancy\n● cardiac axis deviation"],["Model Output","For each frame the software\nevaluates whether the findings are:\npresent, absent, or inconclusive.\nA “record summary table” displays\na summary of results for each video\nclip. An “exam summary table”\ndisplays a summary of the results for\nthe overall study.","For each frame the software\nevaluates whether the findings are:\npresent, absent, or inconclusive.\nA “record summary table” displays\na summary of results for each video\nclip. An “exam summary table”\ndisplays a summary of the results for\nthe overall study."]],"caption_candidate":"510(k) Summary Page 3 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p7-t0","doc_id":"K251071","page_num":7,"bbox":[66.33,72.13,545.42,148.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],"rows":[["","Subject Device\nFetal EchoScan v1.1","Predicate Device\nFetal EchoScan v1.0"],["Output Display","● Annotated DICOMs within the\nuser PACS viewer","● Annotated DICOMs within the\nuser PACS viewer\n● Device web interface"]],"caption_candidate":"510(k) Summary Page 4 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p9-t0","doc_id":"K251071","page_num":9,"bbox":[87.72,72.17,523.5,386.38],"n_rows":11,"n_cols":5,"columns":["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],"rows":[["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],["","Sensitivity\n(Worst-Case)","Specificity\n(Best-Case)","Sensitivity\n(Best-Case)","Specificity\n(Worst-Case)"],["Any suspicious findings","0.977 (0.954 ;\n0.989)","0.977 (0.961 ;\n0.987)","0.987 (0.967 ;\n0.995)","0.963 (0.944 ;\n0.976)"],["Overriding artery","0.894 (0.820 ;\n0.940)","0.989 (0.977 ;\n0.995)","0.942 (0.880 ;\n0.973)","0.979 (0.963 ;\n0.988)"],["Cardiac crux septal\ndefect","0.905 (0.823 ;\n0.951)","0.995 (0.985 ;\n0.998)","0.917 (0.838 ;\n0.959)","0.989 (0.977 ;\n0.995)"],["Abn. OT relationship","0.869 (0.781 ;\n0.925)","0.991 (0.979 ;\n0.996)","0.952 (0.884 ;\n0.981)","0.989 (0.977 ;\n0.995)"],["Enlarged CTR","0.955 (0.876 ;\n0.985)","1.000 (0.993 ;\n1.000)","0.955 (0.876 ;\n0.985)","1.000 (0.993 ;\n1.000)"],["Cardiac axis deviation","0.945 (0.851 ;\n0.981)","1.000 (0.993 ;\n1.000)","0.945 (0.851 ;\n0.981)","1.000 (0.993 ;\n1.000)"],["PV/AV size discrepancy","0.954 (0.914 ;\n0.975)","0.989 (0.977 ;\n0.995)","0.954 (0.914 ;\n0.975)","0.989 (0.977 ;\n0.995)"],["RV/LV size discrepancy","0.950 (0.900 ;\n0.975)","1.000 (0.993 ;\n1.000)","0.950 (0.900 ;\n0.975)","1.000 (0.993 ;\n1.000)"],["TV/MV size\ndiscrepancy","0.943 (0.896 ;\n0.970)","1.000 (0.993 ;\n1.000)","0.943 (0.896 ;\n0.970)","1.000 (0.993 ;\n1.000)"]],"caption_candidate":"510(k) Summary Page 6 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251071-p10-t0","doc_id":"K251071","page_num":10,"bbox":[66.72,508.39,544.5,695.68],"n_rows":11,"n_cols":5,"columns":["","Aided","Unaided","Aided minus Unaided",""],"rows":[["","Aided","Unaided","Aided minus Unaided",""],["","Model Estimate AUC\n(95% CI)","Model Estimate AUC\n(95% CI)","Model Estimate Difference\n(95% CI)","DBM-OR\np-value"],["Any suspicious findings","0.974 (0.957 ; 0.990)\n0.953 (0.916 ; 0.990)\n0.971 (0.943 ; 0.999)\n0.972 (0.953 ; 0.992)\n0.960 (0.930 ; 0.989)\n0.967 (0.932 ; 1.000)\n0.979 (0.962 ; 0.997)\n0.991 (0.983 ; 0.999)\n0.964 (0.938 ; 0.990)","0.825 (0.741 ; 0.908)\n0.803 (0.719 ; 0.888)\n0.857 (0.782 ; 0.933)\n0.832 (0.738 ; 0.927)\n0.746 (0.666 ; 0.826)\n0.786 (0.704 ; 0.867)\n0.839 (0.756 ; 0.921)\n0.868 (0.801 ; 0.936)\n0.850 (0.779 ; 0.921)","0.149 (0.066 ; 0.232) 0.002\n0.150 (0.063 ; 0.237) 0.002\n0.114 (0.042 ; 0.186) 0.004\n0.140 (0.048 ; 0.232) 0.005\n0.214 (0.131 ; 0.297) <0.001\n0.181 (0.106 ; 0.256) <0.001\n0.140 (0.060 ; 0.221) 0.002\n0.123 (0.055 ; 0.190) 0.001\n0.114 (0.048 ; 0.179) 0.002",""],["Overriding artery","","","",""],["Cardiac crux septal defect","","","",""],["Abn. OT relationship","","","",""],["Enlarged CTR","","","",""],["Cardiac axis deviation","","","",""],["PV/AV size discrepancy","","","",""],["RV/LV size discrepancy","","","",""],["TV/MV size discrepancy","","","",""]],"caption_candidate":"analyzed finding but possibly positive to other findings.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251072-p7-t0","doc_id":"K251072","page_num":7,"bbox":[88.5,324.12,541.5,496.74],"n_rows":13,"n_cols":2,"columns":["3. Anatomy Segmentation : This study assessed the ability of Segmentron Viewer to segment 8",""],"rows":[["3. Anatomy Segmentation : This study assessed the ability of Segmentron Viewer to segment 8",""],["anatomical structures in 56 CBCT scans. Across all anatomical structures, Segmentron",""],["demonstrated strong segmentation agreement with the reference standard. The primary",""],["endpoint was met, as the Dice Coefficients for each anatomical region exceeded their",""],["respective pre-defined PGs.",""],["",""],["4. Labeling Performance: This study aimed to validate the accuracy of labels automatically",""],["generated by the device for teeth, anatomical structures, and pulp on 40 CBCT scans from the",""],["larger validation dataset. Across all teeth, pulp, and anatomical structures in all CBCT scans,",""],["Segmentron Viewer achieved a labeling accuracy of 100%, demonstrating strong concordance",""],["between the labels automatically generated by the device and those determined by an expert",""],["radiologist.",""],["",""]],"caption_candidate":"and success on the secondary endpoints.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251072-p8-t0","doc_id":"K251072","page_num":8,"bbox":[43.79,65.87,748.22,532.81],"n_rows":42,"n_cols":12,"columns":["","Criteria","","","Subject Device: Segmentron Viewer","","","Predicate Device: Ez3D-i /E3 (K231757)","","","Comparison",""],"rows":[["","Criteria","","","Subject Device: Segmentron Viewer","","","Predicate Device: Ez3D-i /E3 (K231757)","","","Comparison",""],["","Regulation #","","21 CFR 892.2050","","","21 CFR 892.2050","","","","",""],["","Device","","","Automated radiological image processing software","","","Automated radiological image processing software","","","Same",""],["","Product Code","","","QIH","","","QIH","","","Same",""],["Intended Use/\nIndications for\nUse","Intended Use/","","Segmentron Viewer is a software product intended\nfor processing and manipulating maxillofacial\nradiographic images. Segmentron Viewer allows\nusers to perform the following functions:\n1. Viewing patient images (provides tools for image\nprocessing and viewing functions);\n2.Reading and 3D visualization of CBCT images;\n3. Generating editable 3D STL files (for educational\npurposes only).\nThe device is indicated for use by medical\nprofessionals (such as dentists and radiologists), in\npatients 14 years and older with permanent teeth.\nSegmentron Viewer is a web application. It can be\nused in a network environment.","","","Ez3D-i/E3 is dental imaging software that is intended to provide\ndiagnostic tools for maxillofacial radiographic imaging. These\ntools are available to view and interpret a series of DICOM\ncompliant dental radiology images and are meant to be used\nby trained medical professionals such as radiologist and\ndentist.\nEz3D-i/E3 is intended for use as software to load, view and\nsave DICOM images from CT, panorama, cephalometric and\nintraoral imaging equipment and to provide 3D visualization, 2D\nanalysis, in various MPR (Multi-Planar Reconstruction)\nfunctions","Ez3D-i/E3 is dental imaging software that is intended to provide","","Same intended\nuse. The minor\ndifferences in\nindications for use\ndo not raise\ndifferent questions\nof safety or\neffectiveness or\nalter the\nfundamental\nclinical purpose.","Same intended",""],["","Indications for","","","","","","diagnostic tools for maxillofacial radiographic imaging. These","","","use. The minor",""],["","Use","","","","","","tools are available to view and interpret a series of DICOM","","","differences in",""],["","","","","","","","compliant dental radiology images and are meant to be used","","","indications for use",""],["","","","","","","","by trained medical professionals such as radiologist and","","","",""],["","","","","","","","","","","do not raise",""],["","","","","","","","dentist.","","","",""],["","","","","","","","","","","different questions",""],["","","","","","","","","","","",""],["","","","","","","","","","","of safety or",""],["","","","","","","","Ez3D-i/E3 is intended for use as software to load, view and","","","",""],["","","","","","","","","","","effectiveness or",""],["","","","","","","","save DICOM images from CT, panorama, cephalometric and","","","",""],["","","","","","","","","","","alter the",""],["","","","","","","","intraoral imaging equipment and to provide 3D visualization, 2D","","","",""],["","","","","","","","","","","fundamental",""],["","","","","","","","analysis, in various MPR (Multi-Planar Reconstruction)","","","",""],["","","","","","","","functions","","","clinical purpose.",""],["Functions and\nCapabilities","","","(cid:120) View and save images from CBCT scanners\n(cid:120) Image measurement\n(cid:120) Multi-Planar Reconstruction (MPR) functions\n(cid:120) 3D image viewing and reformation\n(cid:120) Rendering functions, e.g., MPR and 3D rendering\n(visualization), 3D zoom\n(cid:120) Image segmentation\n(cid:120) Export capabilities\n(cid:120) Generates reports\n(cid:120) Manage and add objects\n(cid:120) Image manipulation (e.g., magnify, hue,\nbrightness)\n(cid:120) Image annotation\n(cid:120) Cloud-based storage","","","","(cid:120) View and save images from CT, panorama, cephalometric","","Both are AI-\nbased, software-\nonly devices\nproviding tools for\nviewing/evaluating\npre-existing\nmaxillofacial\nradiographic\nimages. The\ndifferences in\nspecific functions\ndo not raise\ndifferent\nquestions.","",""],["","","","","","","","and intraoral imaging equipment","","","",""],["","","","","","","","(cid:120) Image measurement","","","",""],["","","","","","","","(cid:120) Multi-Planar Reconstruction (MPR) functions","","","",""],["","","","","","","","(cid:120) 2D image viewing and analysis","","","",""],["","","","","","","","(cid:120) 3D image viewing and reformation (including canal","","","",""],["","","","","","","","drawing)","","","",""],["","","","","","","","(cid:120) Rendering functions, e.g., Volume Rendering, MIP, miniIP,","","","",""],["","","","","","","","X-ray, and 3D zoom","","","",""],["","","","","","","","(cid:120) Image Segmentation","","","",""],["","","","","","","","(cid:120) Transfer images","","","",""],["","","","","","","","(cid:120) Generates reports","","","",""],["","","","","","","","(cid:120) Manage and add objects, color maps, fine tuning","","","",""],["","","","","","","","(cid:120) Image manipulation (e.g., magnify, hue, brightness)","","","",""],["","","","","","","","(cid:120) Image annotation","","","",""],["","","","","","","","(cid:120) Implant simulation tools for treatment planning","","","",""],["","","","","","","","(cid:120) Bone density profiling","","","",""],["","Algorithm","","","Supervised machine learning","","","Supervised machine learning","","","Same",""],["","Image Format","","","DICOM","","","DICOM","","","Same",""],["","Configuration","","","Web application","","","Desktop application","","","Similar",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p6-t0","doc_id":"K251078","page_num":6,"bbox":[73.73,514.76,538.27,541.74],"n_rows":2,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K251747","","","VEA Align","","","August 2025","",""]],"caption_candidate":"3 LEGALLY MARKETED PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p6-t1","doc_id":"K251078","page_num":6,"bbox":[73.73,576.71,538.27,604.5],"n_rows":2,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K072847","","","APEX Software for QDR X-Ray Bone Densitometers","","","December 2007","",""]],"caption_candidate":"4 REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p8-t0","doc_id":"K251078","page_num":8,"bbox":[35.27,114.62,729.47,539.04],"n_rows":11,"n_cols":7,"columns":["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],"rows":[["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],["Manufacturer","EOS imaging","Hologic","","","EOS imaging",""],["","","","Hologic","","",""],["System","VEA Align (K251747)","","APEX Software for QDR X-","","AutoDensity",""],["","","","Ray Bone Densitometers","","",""],["","","","(K072847)","","",""],["Product Code","QIH","KGI","","","QIH","Yes, same as predicate"],["Device Classification","II","II","","","II","Yes, same as predicate"],["Device Classification\nName","Medical Image Management and\nProcessing System","Bone Densitometer","","","Medical Image Management and\nProcessing System","Yes, same as predicate"],["Regulation Number","§892.2050","§892.1170","","","§892.2050","Yes, same as predicate"],["Intended use /\nIndications","This cloud-based software is\nintended for orthopedic\napplications in both pediatric and\nadult populations.\n2D X-ray images acquired in\nEOS imaging’s imaging systems\nis the foundation and resource to\ndisplay the interactive landmarks\noverlayed on the frontal and\nlateral images.\nThese landmarks are available\nfor users to assess patient-\nspecific global alignment.\nFor additional assessment,\nalignment parameters compared\nto published normative values\nmay be available.\nThis product serves as a tool to\naid in the analysis of spinal\ndeformities and degenerative\ndiseases, and lower limb\nalignment disorders and\ndeformities through precise angle\nand length measurements. It is","The APEX for QDR X-Ray Bone\nDensitometers is indicated for\nthe estimation of bone mineral\ndensity (BMD), comparison of\nmeasured variables obtained\nfrom a given QDR scan to a\ndatabase of reference values,\nthe estimation of fracture risk,\nvertebral deformity assessment,\nbody composition analysis, and\ndiscrimination of bone from\nprosthetics using the Hologic\nQDR® X-Ray Bone\nDensitometers.\nIVA scans are intended for the\nvisualization or quantitative\nassessment of vertebral body\ndeformities. IVA also allows the\nvisualization of abdominal aortic\ncalcifications and, if present,\nclinical correlation may be\nadvised since abdominal aortic\ncalcification may be associated\nwith cardiovascular disease.","","","AutoDensity is a post-processing\nsoftware intended to estimate\nspine Bone Mineral Density\n(BMD) from EOSedge dual\nenergy images for orthopedic\npre-surgical assessment\napplications. It is an\nopportunistic tool that enables\nimmediate assessment of bone\ndensity from EOSedge images\nacquired for other purposes.\nAutoDensity is not intended to\nreplace DXA screening.\nSuspected low BMD should be\nconfirmed by a DXA exam.\nClinical judgment and experience\nare required to properly use the\nsoftware.","Yes, the subject device intended\nuse/indications for use are\nsubstantially equivalent to the\npredicate device as both devices\nintended/indicated to provide clinical\nparameters from X-ray images\nacquired by EOS imaging system\n(EOSedge) for orthopedic pre-\nsurgical assessment applications\n(alignment parameters for the\npredicate and BMD for the subject\ndevice)."]],"caption_candidate":"AutoDensity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p9-t0","doc_id":"K251078","page_num":9,"bbox":[35.27,114.62,729.46,510.3],"n_rows":10,"n_cols":7,"columns":["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],"rows":[["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],["Manufacturer","EOS imaging","Hologic","","","EOS imaging",""],["","","","Hologic","","",""],["System","VEA Align (K251747)","","APEX Software for QDR X-","","AutoDensity",""],["","","","Ray Bone Densitometers","","",""],["","","","(K072847)","","",""],["","suitable for use with adult and\npediatric patients aged 7 years\nand older.\nClinical judgment and experience\nare required to properly use the\nsoftware","","","","",""],["Contraindications","VEA Align is contraindicated for\ncases with vertebrae with severe\ncongenital deformities (e.g.,\nhemivertebrae, spina bifida, etc.).","Pregnancy and the use of\ncontrast agents within the past 7\ndays are contraindicated.","","","AutoDensity is contraindicated\nfor cases with supernumerary/\nmissing vertebrae.","Yes, the updated contraindications\ndo not change the Intended Use.\nBoth devices treat the same patient\npopulation and compute clinical\nparameters from X-ray images\nacquired by EOSedge system for\northopedic applications.\nWhile contraindications are\ndifferent, this is not critical to the\nproposed device's functionality."],["Technical\nCharacteristics","AutoDensity software runs in a\ncloud-environment.","APEX software runs on QDR X-\nRay Bone Densitometers.","","","AutoDensity software runs in a\ncloud-environment.","Yes, same as the predicate."],["","VEA Align generates spine\nlandmarks from 2D X-ray images\nacquired with EOSedge system,\nused to compute alignment\nclinical parameters.","The Hologic APEX software\ngenerates a range of reports and\nimages utilizing the DXA data\nacquired with the Hologic QDR\nsystems. It can display the DXA\nmeasurements along with a\nrepresentative color image\nmapping of bone and soft tissue.","","","AutoDensity generates bone\nmineral density information\nutilizing the dual-energy images\nacquired with the EOSedge\nsystem. It computes bone\nmineral density measurements\nfrom \"aluminum\" and \"PMMA\"\nimages:\n• Aluminum image is\nbone-equivalent\ndensity,","Yes, the subject device is\nsubstantially equivalent to the\npredicate device as they both used\nEOSedge images to compute\nclinical parameters.\nThe subject device is also\nequivalent to the reference device\nas they both enable bone mineral\nassessments to be identified from\nbone-equivalent and tissues-\nequivalent images."]],"caption_candidate":"AutoDensity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p10-t0","doc_id":"K251078","page_num":10,"bbox":[35.27,114.62,729.47,537.3],"n_rows":11,"n_cols":7,"columns":["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],"rows":[["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],["Manufacturer","EOS imaging","Hologic","","","EOS imaging",""],["","","","Hologic","","",""],["System","VEA Align (K251747)","","APEX Software for QDR X-","","AutoDensity",""],["","","","Ray Bone Densitometers","","",""],["","","","(K072847)","","",""],["","","","","","• PMMA image is soft\ntissue-equivalent\ndensity.",""],["","The software allows:\nAssessment of patient spinal\nglobal alignment.","The software allows:\n• Assessment of bone\ndensity with lumbar\nspine, double hip and\nwrist examinations.\n• Diagnosis of vertebral\nfractures using low-\ndose spinal imaging.\n• Instant quantification of\nbone quality of a lumbar\nspine examination.\nOther functionalities are available\non the system that are not\ndescribed in this comparison\ntable.","","","The software allows:\nAssessment of bone density with\nlumbar spine.","Yes, the subject device is\nsubstantially equivalent to the\nreference device as they both\nassess bone mineral density of\nlumbar spine."],["Principles of\nOperation","VEA Align workflow is divided\ninto the following steps:\n• Data Acquisition\n• Data Computation\n• Report Generation","APEX software workflow is\ndivided into the following main\nsteps:\n• Data Acquisition,\n• Data Computation,\n• Report Generation.","","","AutoDensity workflow is divided\ninto the following main steps:\n• Data Ingestion,\n• Data Computation,\n• Report Generation.","Yes, same"],["Device Input","X-ray images from EOS and\nEOSedge systems","Dual-energy X-ray images","","","Dual-energy X-ray images from\nEOSedge systems","Yes, the subject device is\nsubstantially equivalent to the\npredicate device as they both uses\nEOSedge images as input."],["Device Output","VEA Align processes data and\ngenerates:","APEX software processes data\nand generates:","","","AutoDensity processes data and\ngenerates:","Yes, the subject device is\nsubstantially equivalent to the\npredicate device as they both"]],"caption_candidate":"AutoDensity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p11-t0","doc_id":"K251078","page_num":11,"bbox":[35.27,114.62,729.46,491.52],"n_rows":10,"n_cols":7,"columns":["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],"rows":[["Specification","Predicate","Reference Device","","","Subject Device","Substantial Equivalence\nDiscussion"],["Manufacturer","EOS imaging","Hologic","","","EOS imaging",""],["","","","Hologic","","",""],["System","VEA Align (K251747)","","APEX Software for QDR X-","","AutoDensity",""],["","","","Ray Bone Densitometers","","",""],["","","","(K072847)","","",""],["","• Preview of the spine\nused to compute\nlandmarks and clinical\nparameters\n• Alignment clinical\nparameters","• Previews with vertebrae\nused for BMD\ncomputation,\n• BMD measurement.","","","• Previews with vertebrae\nused for BMD\ncomputation,\n• BMD measurements.","generate clinical parameters and\npreview of the images used to\ncompute them.\nThe subject device is also\nequivalent to the reference device\nas they both process data and\ngenerate previews and BMD\nmeasurements."],["Regions of Interest\ndetection","VEA Align computes landmarks\nassociated with vertebral centers\nand endplates needed to\ncalculate coronal and sagittal\nclinical parameters.","Region of interest detection is\ndone for at least the following\nanatomical body part:\n• Spine (lumbar\nvertebrae):\nFrontal: L1, L2,\no\nL3 and L4","","","Region of interest detection is\ndone for the following anatomical\nbody part:\n• Spine (lumbar\nvertebrae)\no Frontal: L1, L2,\nL3 and L4.","Yes, the subject device is\nsubstantially equivalent to the\nreference device as they both\nperform region of interest detection\non similar anatomical body parts."],["Provides Bone\nMineral Density\nValue","N/A","Bone Mineral Density values are\ncomputed for at least the\nfollowing anatomical body part:\n• Spine (lumbar\nvertebrae):\no Frontal: L1, L2,\nL3, L4 and\ntotal BMD","","","Bone Mineral Density values are\ncomputed for the following\nanatomical body part:\n• Spine (lumbar\nvertebrae):\no Frontal: L1, L2,\nL3, L4 and\ntotal BMD","Yes, the subject device is\nsubstantially equivalent to the\nreference device in that Bone\nMineral Density values are also\ncomputed using L1 to L4."],["Information Provided\nin the Report","Patient information\nExamination information\nLandmark detection\nAlignment clinical parameters","Patient information\nExamination information\nROI detection\nBone Mineral Density Values","","","Patient information\nExamination information\nROI detection\nBone Mineral Density Values","Yes, same"]],"caption_candidate":"AutoDensity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251078-p13-t0","doc_id":"K251078","page_num":13,"bbox":[105.84,114.54,506.1,382.74],"n_rows":18,"n_cols":3,"columns":["Type","Subgroup","Category"],"rows":[["Type","Subgroup","Category"],["Demographics*","Age","Pediatric"],["","","Adult"],["","Sex","Male"],["","","Female"],["Image Acquisition*","Field of View","Full Spine"],["","","Full Body"],["Data Collection Site","Country","US"],["","","OUS"],["Disease Conditions","Degenerative – Spine","Normal-Mild"],["","","Moderate"],["","","Severe"],["Lumbar Morphometry\n(Levels evaluated\nseparately; maximum\nangle compared to\nview-plane)","Vertebral Sagittal Angle for\nL1, L2, L3 and L4 each, and\nmaximum","Low"],["","","Medium"],["","","High"],["","Vertebral Axial Rotation\n(VAR) for L1, L2, L3 and L4\neach, and maximum","Low"],["","","Medium"],["","","High"]],"caption_candidate":"AutoDensity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251096-p8-t0","doc_id":"K251096","page_num":8,"bbox":[68.87,150.0,742.62,492.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Product Code","QIH, LLZ","QIH, LLZ","Yes","---"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Yes","---"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","---"],["Intended\nuse/Indications for\nuse","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the\nsystem in the revision and approval of the\noutput of the planning. The multi-platform\nsystem works with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using\nmedical imaging with the additional","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment is\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of","Yes","---"]],"caption_candidate":"Table 1: Summary of Predicate and Subject Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251096-p9-t0","doc_id":"K251096","page_num":9,"bbox":[68.84,112.4,742.71,489.5],"n_rows":7,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","capability of planning the 2D or 3D\nenvironment. The system is designed for\nthe medical specialties within surgery and\nno specific use environment is mandatory,\nwhereas the typical use environment is a\nroom with a computer. The patient target\ngroup is adult patients who have an injury\nor disability diagnosed previously. There\nare no other considerations for the\nintended patient population.","planning the 2D or 3D environment. The\nsystem is designed for the medical\nspecialties within surgery and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","",""],["Contraindications","No contraindications specific to this\ndevice.","No contraindications specific to this device.","Yes","---"],["Clinical purpose","PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","Yes","---"],["Anatomical regions","PeekMed web allows the surgeon to\nperform the pre-surgical planning\nefficiently in the following anatomical\nregions:\n- Hip\n- Knee\n- Upper limb\n- Foot","PeekMed web allows the surgeon to\nperform the pre-surgical planning efficiently\nin the following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes","—"],["Patient Population","Adults","Adults","Yes","---"],["End users","Healthcare Professionals","Healthcare Professionals","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251096-p10-t0","doc_id":"K251096","page_num":10,"bbox":[68.9,112.4,742.71,481.5],"n_rows":10,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Device availability","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run on a\nweb browser","Yes","---"],["Software\nArchitecture","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Yes","---"],["Workflow","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export\nthe case.","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","Yes","---"],["Internet connection","Required","Required","Yes","---"],["Images source","Receives medical images from various\nsources","Receives medical images from various\nsources","Yes","---"],["Data processing","The software processes data to provide\nan overlap and dimensioning of digital\nrepresentations of the prosthetic material","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","Yes","---"],["Digital overlap of\ntemplates","Allows the overlap of models and the\nintersection of the models","Allows the overlap of models and the\nintersection of the models","Yes","---"],["Interactive model\npositioning","Yes","Yes","Yes","---"],["Interactive model\ndimensioning","Yes","Yes","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251096-p11-t0","doc_id":"K251096","page_num":11,"bbox":[68.9,112.4,742.71,493.5],"n_rows":10,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Model rotation","Yes","Yes","Yes","---"],["Support for digital\nprosthetic\nmaterials provided\nby the\nmanufacturers","Yes","Yes","Yes","---"],["Pre-surgical\nplanning","Yes","Yes","Yes","---"],["Type of\npre-surgical\nplanning","Automatic or Manual","Automatic or Manual","Yes","---"],["Contact with the\npatient","No","No","Yes","---"],["Control of life\nsupporting devices","No","No","Yes","---"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","Yes","---"],["Ability to add\nadditional modules\nwhen available","Yes","Yes","Yes","---"],["Automatic bone\nsegmentation","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray and CT scan)","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray, CT scan, and MRI)","Yes","The subject device includes a new ML\nmodel variant for segmentation.\nBoth devices allow planning for the"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251096-p12-t0","doc_id":"K251096","page_num":12,"bbox":[68.9,112.4,742.67,326.0],"n_rows":3,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K250042","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","","knee region with X-rays and CT scans,\nbut the subject device also allows with\nMRI.\nThis does not constitute an intended\npurpose update, nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices."],["Type of\nlandmarking","Automatic or Manual\n- Hip\n- Knee\n- Upper limb\n- Foot","Automatic or Manual\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p5-t0","doc_id":"K251106","page_num":5,"bbox":[89.94,191.42,433.21,688.12],"n_rows":49,"n_cols":3,"columns":["1)","Date Prepared:","April 10, 2025"],"rows":[["1)","Date Prepared:","April 10, 2025"],["","",""],["2)","Submitter:",""],["","",""],["","Manufacturer Name:","FUJIFILM SonoSite, Inc."],["","",""],["","Address:","21919 30th Drive SE"],["","",""],["","","Bothell, WA 98021-3904"],["","",""],["","Corresponding Official:","Anoush Frankian"],["","",""],["","","Director, Regulatory Affairs"],["","",""],["","Email:","anoush.frankian@fujifilm.com"],["","",""],["","Telephone:","425-951-6824"],["","",""],["","Facsimile:","425-951-1201"],["","",""],["","Secondary Contact:","Anjana Varier"],["","",""],["","","Senior Regulatory Affairs Spec"],["","",""],["","","anjana.varier@fujifilm.com"],["","",""],["","Telephone:","425-686-6519"],["","",""],["3)","Proposed Device:",""],["","",""],["","Trade Name:","Sonosite LX and Sonosite PX"],["","",""],["","","Ultrasound Systems"],["","",""],["","Common Name:","Diagnostic System and Transd"],["","",""],["","","Accessories"],["","",""],["","Regulation Name:","Ultrasonic Pulsed Doppler Ima"],["","",""],["","Regulation Number:","21 CFR 892.1550, 892.1560. 8"],["","",""],["","","892.2050"],["","",""],["","Product Code:","IYN, IYO, ITX, QIH"],["","",""],["","Device Classification:","Class II"],["","",""],["","Classification Panel:","Radiology"]],"caption_candidate":"1) Date Prepared: April 10, 2025","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251106-p8-t0","doc_id":"K251106","page_num":8,"bbox":[73.5,101.7,541.5,716.4],"n_rows":5,"n_cols":4,"columns":["Feature","PIV Assist\nvalidated on\nSonosite LX and\nSonosite PX\nUltrasound\nSystem\n(This\nsubmission)","Sonosite LX\nUltrasound\nSystem\n(K233597)\nPredicate device","Sonosite PX\nUltrasound\nSystem\n(K213763)\nReference device"],"rows":[["Feature","PIV Assist\nvalidated on\nSonosite LX and\nSonosite PX\nUltrasound\nSystem\n(This\nsubmission)","Sonosite LX\nUltrasound\nSystem\n(K233597)\nPredicate device","Sonosite PX\nUltrasound\nSystem\n(K213763)\nReference device"],["Intended\nUse","Same as predicate and\nreference device","Diagnostic ultrasound\nimaging or fluid flow\nanalysis of the human\nbody","Diagnostic ultrasound\nimaging or fluid flow\nanalysis of the human\nbody"],["Indications\nfor Use","Same as predicate and\nreference device","Abdominal\nAdult Cephalic\nNeonatal Cephalic\nCardiac Adult\nCardiac Pediatric\nFetal – OB/GYN\nMusculo-skeletal\n(Conventional) Musculo-\nskeletal (Superficial)\nOphthalmic\nPediatric\nPeripheral vessel\nSmall Organ (breast,\nthyroid, testicle,\nprostate)\nTransrectal\nTransvaginal\nTrans-esophageal\n(cardiac)\nNeedle Guidance","Abdominal\nAdult Cephalic\nNeonatal Cephalic\nCardiac Adult\nCardiac Pediatric\nFetal – OB/GYN\nMusculo-skeletal\n(Conventional) Musculo-\nskeletal (Superficial)\nOphthalmic\nPediatric\nPeripheral vessel\nSmall Organ (breast,\nthyroid, testicle,\nprostate)\nTransrectal\nTransvaginal\nTrans-esophageal\n(cardiac)\nNeedle Guidance"],["Transducer\nTypes","Same as predicate and\nreference device","Linear Array\nCurved Linear Array\nPhased Array\nIntracavitary\nTrans-esophageal","Linear Array\nCurved Linear Array\nPhased Array\nIntracavitary\nTrans-esophageal"],["Transducer\nFrequency","Same as predicate and\nreference device","1.0-19.0 MHz","1.0-19.0 MHz"]],"caption_candidate":"Table 1: Technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p9-t0","doc_id":"K251106","page_num":9,"bbox":[73.5,71.46,541.5,705.36],"n_rows":4,"n_cols":4,"columns":["Global\nMaximum\nOutputs/\nWorst\nCase\nSetting","Same as predicate and\nreference device","Ispta.3: 607 mW/cm^2\n(L12-3)\nTI Type: TIB (P5-1) TI\nValue: 4.87 (P5-1) MI:\n1.72 (L12-3)\nIpa.3@MI Max: 793\nmW/cm^2 (L15-4)","Ispta.3: 607 mW/cm^2\n(L12-3)\nTI Type: TIB (P5-1) TI\nValue: 4.87 (P5-1) MI:\n1.72 (L12-3)\nIpa.3@MI Max: 793\nmW/cm^2 (L15-4)"],"rows":[["Global\nMaximum\nOutputs/\nWorst\nCase\nSetting","Same as predicate and\nreference device","Ispta.3: 607 mW/cm^2\n(L12-3)\nTI Type: TIB (P5-1) TI\nValue: 4.87 (P5-1) MI:\n1.72 (L12-3)\nIpa.3@MI Max: 793\nmW/cm^2 (L15-4)","Ispta.3: 607 mW/cm^2\n(L12-3)\nTI Type: TIB (P5-1) TI\nValue: 4.87 (P5-1) MI:\n1.72 (L12-3)\nIpa.3@MI Max: 793\nmW/cm^2 (L15-4)"],["Acoustic\nOutput\nDisplay &\nFDA Limits","Same as predicate and\nreference device","Display Feature for\nHigher Outputs MI\nOutput Display TI Output\nDisplay","Display Feature for\nHigher Outputs MI\nOutput Display TI Output\nDisplay"],["Modes of\nOperation","Same\nSame as predicate and\nreference device","B-mode Grayscale\nImaging\nTissue Harmonic Imaging\nM-mode\nSimultaneous M-Mode\nAnatomical M-Mode\nColor Power Doppler\nZoom\nCombination Modes\nPulsed Wave (PW)\nDoppler\nContinuous Wave (CW)\nDoppler\nSpeckle reduction\nalgorithm (formerly\nbranded as SonoHD2\nNoise Reduction)\nSonoMB/MBe Image\nCompounding\nCW Doppler\nVelocity Color Doppler\nTissue Doppler Imaging\n(TDI)","B-mode Grayscale\nImaging\nTissue Harmonic Imaging\nM-mode\nSimultaneous M-Mode\nAnatomical M-Mode\nColor Power Doppler\nZoom\nCombination Modes\nPulsed Wave (PW)\nDoppler\nContinuous Wave (CW)\nDoppler\nSpeckle reduction\nalgorithm (formerly\nbranded as SonoHD2\nNoise Reduction)\nSonoMB/MBe Image\nCompounding\nCW Doppler\nVelocity Color Doppler\nTissue Doppler Imaging\n(TDI)"],["DICOM","Same as predicate and\nreference device","DICOM 3.0\nStore, Modality Worklist,\nModality Perform\nProcedure Step (MPPS),\nStorage Commitment,","DICOM 3.0\nStore, Modality Worklist,\nModality Perform\nProcedure Step (MPPS),\nStorage Commitment,\nStructured reports,\noffline media"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p10-t0","doc_id":"K251106","page_num":10,"bbox":[73.5,71.46,541.5,722.28],"n_rows":5,"n_cols":4,"columns":["","","Structured reports,\noffline media",""],"rows":[["","","Structured reports,\noffline media",""],["#Transmit\nChannels","Same as predicate and\nreference device","128 digital channels","128 digital channels"],["#Receive\nChannels","Same as predicate and\nreference device","128 digital channels","128 digital channels"],["Patient\nContact\nMaterials","Same as predicate and\nreference device","Transducers:\nSilicone Rubber\nPolysulfone\nPolyVinylChloride (PVC)\nSilicone RTV Adhesive\nSilicone\nPolymethyl-pentene\nEpoxy Paste Adhesive\nPolyurethane\nFKM rubber\nThermoplastic\npolyurethane\nNeedle Guides: Acetal\ncopolymer Acrylonitrile-\nbutadien- styrene (ABS)","Transducers:\nSilicone Rubber\nPolysulfone\nPolyVinylChloride (PVC)\nSilicone RTV Adhesive\nSilicone\nPolymethyl-pentene\nEpoxy Paste Adhesive\nPolyurethane\nFKM rubber\nThermoplastic\npolyurethane\nNeedle Guides: Acetal\ncopolymer Acrylonitrile-\nbutadien- styrene (ABS)"],["System\nCharacteris\ntics","PIV Assist is validated\non both Sonosite PX\nand Sonosite LX\nUltrasound Systems.\nNo hardware changes\nwere made to either of\nthese devices to\ninclude PIV Assist.\nNew features\ninclude -\n• L12-3 PIV Assist\nfeature added to\nPeripheral\nIntraVenous Exam\nType\n• L19-5 PIV Assist\nfeature added to\nPeripheral IntraVenous\nand Vascular Access\nExam Types","Sonosite LX:\n21.3 “Projected\nCapacitive (PCAP) touch\nscreen interface\nStorage bin capacity: 11\nlbs. (5 kg)\nStand depth: 25.4 in.\n(64.5 cm)\nStand width: 23.0 in.\n(58.4 cm)\nHeight range: max with\nmonitor up 68 in. (172.7\ncm); min with monitor\ndown 49 in. (124.5 cm)\nWeight (system and\naccessories including\nsafe working load):\n151.68 lbs. (68.8 kg)\n2 USB 2.0 Ports","Sonosite PX:\nBeamformer 128/128\n15.6” capacitive screen\ninterface\nStorage bin capacity: 11\nlbs\nStand depth: 25.4 in\n(64.5 cm)\nStand width: 23.0 in.\n(58.4)\nHeight: 45 in. (114.3\ncm) maximum, 33 in.\n(83.8 cm) minimum\nWeight: 17.92 lbs (8.13\nkg) with the L15-4\ntransducer and battery\ninstalled\nTotal Stand weight with\nsystems and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p13-t0","doc_id":"K251106","page_num":13,"bbox":[72.48,87.06,540.84,264.68],"n_rows":3,"n_cols":3,"columns":["Reference Number","Recognition Number","Title"],"rows":[["Reference Number","Recognition Number","Title"],["IEC 62304","13-79","ANSI AAMI IEC\n62304:2006/A1:2016\nMedical device software -\nSoftware life cycle\nprocesses [Including\nAmendment 1 (2016)"],["ISO 14971","5-125","ANSI AAMI ISO 14971:2019\nMedical devices -\nApplication of risk\nmanagement to medical\ndevices"]],"caption_candidate":"Table 2: FDA Recognized standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p14-t0","doc_id":"K251106","page_num":14,"bbox":[73.02,498.52,538.3,718.16],"n_rows":4,"n_cols":6,"columns":["Demographi\nc Type","Demographic\nGroup","Detection\nPrecision (%)","Detection\nRecall (%)","Vein\nClassification\nAccuracy (%)","Artery\nClassification\nAccuracy (%)"],"rows":[["Demographi\nc Type","Demographic\nGroup","Detection\nPrecision (%)","Detection\nRecall (%)","Vein\nClassification\nAccuracy (%)","Artery\nClassification\nAccuracy (%)"],["Age Range","18-39","95.97%\n(95% CI:\n94%-98%)","97.00%\n(95% CI:\n95%-98%)","97.24%\n(95% CI:\n95%-99%)","90.00%\n(95% CI:\n82%-95%)"],["","40-65","96.85%\n(95% CI:\n95%-98%)","96.56%\n(95% CI:\n95%-98%)","96.10%\n(95% CI:\n94%-98%)","89.27%\n(95% CI:\n84%-93%)"],["","65 and over","98.45%\n(95% CI:\n97%-99%)","97.52%\n(95% CI:\n96%-98%)","95.16%\n(95% CI:\n93%-97%)","89.89%\n(95% CI:\n86%-93%)"]],"caption_candidate":"Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p15-t0","doc_id":"K251106","page_num":15,"bbox":[150.02,102.4,533.75,742.42],"n_rows":58,"n_cols":7,"columns":["","96.99%","","96.70%","","95.24%","88.11%"],"rows":[["","96.99%","","96.70%","","95.24%","88.11%"],["","(95% CI:","","(95% CI:","","(95% CI:","(95% CI:"],["","","","","","",""],["","96%-98%)","","95%-98%)","","93%-97%)","84%-92%)"],["F","","","","","",""],["","","","","","",""],["","97.65%","","97.45%","","96.77%","91.42%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","(95% CI:","(95% CI:"],["","","","","","",""],["","","","","","",""],["","96%-99%)","","96%-98%)","","95%-98%)","87%-94%)"],["","","","","","",""],["M","","","","","",""],["","","","","","",""],["","95.94%","","96.24%","9","0.38% (95%","83.19%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","CI:","(95% CI:"],["African","","","","","",""],["","","","","","",""],["","93%-98%)","","94%-98%)","","86%-94%)","75%-89%)"],["","","","","","",""],["American/Black","","","","","",""],["","","","","","",""],["","91.38%","","96.36%","9","7.30% (95%","94.12%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","CI:","(95% CI:"],["","","","","","",""],["","81%-97%)","","87%-100%)","","86%-100%)","71%-100%)"],["Asian","","","","","",""],["","","","","","",""],["","97.73%","","97.11%","","96.76%","91.25%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","(95% CI:","(95% CI:"],["","","","","","",""],["","97%-99%)","","96%-98%)","","95%-98%)","87%-94%)"],["Caucasian/White","","","","","",""],["","","","","","",""],["","97.39%","","97.39%","","98.65%","96.20%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","(95% CI:","(95% CI:"],["","","","","","",""],["","95%-99%)","","95%-99%)","","96%-100%)","89%-99%)"],["Hispanic","","","","","",""],["","","","","","",""],["","100.00%","","100.00%","","100.00%","100.00%"],["","","","","","",""],["","(95% CI:","","(95% CI:","","(95% CI:","(95% CI:"],["","","","","","",""],["","86%-100%)","","86%-100%)","","77%-100%)","69%-100%)"],["Mixed/Multiracial","","","","","",""],["","","","","","",""],["98.8","2% (95% CI:","97",".67%","95.","10% 78.13","%"],["","96%-100%)","(95","% CI: 94%-","(95","% CI: 90%- (95% C","I: 60%-"],["Native American","","99","%)","98%",") 91%)",""],["","","","","","",""],["","","","","","",""],["","","","","","","Page 11"]],"caption_candidate":"96.99% 96.70% 95.24% 88.11%","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251106-p16-t0","doc_id":"K251106","page_num":16,"bbox":[72.77,84.74,537.95,251.32],"n_rows":3,"n_cols":6,"columns":["BMI Range","Below 25","97.06%\n(95% CI:\n95%-98%)","96.35%\n(95% CI:\n94%-98%)","96.13%\n(95% CI:\n94%-98%)","92.22%\n(95% CI:\n87%-96%)"],"rows":[["BMI Range","Below 25","97.06%\n(95% CI:\n95%-98%)","96.35%\n(95% CI:\n94%-98%)","96.13%\n(95% CI:\n94%-98%)","92.22%\n(95% CI:\n87%-96%)"],["","25-29.9","98.24%\n(95% CI:\n97%-99%)","96.54%\n(95% CI:\n95%-98%)","97.05%\n(95% CI:\n95%-98%)","92.97%\n(95% CI:\n88%-96%)"],["","30 and above","96.79%\n(95% CI:\n95%-98%)","98.00%\n(95% CI:\n97%-99%)","95.19%\n(95% CI:\n93%-97%)","84.13%\n(95% CI:\n78%-89%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p16-t1","doc_id":"K251106","page_num":16,"bbox":[72.77,315.38,537.95,652.18],"n_rows":6,"n_cols":6,"columns":["Demographic\nType","Demographic\nGroup","Detection Precision\n(%)","Detection\nRecall (%)","Vein\nClassification\nAccuracy (%)","Artery Classification\nAccuracy (%)"],"rows":[["Demographic\nType","Demographic\nGroup","Detection Precision\n(%)","Detection\nRecall (%)","Vein\nClassification\nAccuracy (%)","Artery Classification\nAccuracy (%)"],["Age Range","18-39","94.00%\n(95% CI: 91.68%-\n95.83%)","93.15%\n(95% CI:\n91%-95%)","94.20%\n(95% CI:\n91%-96%)","81.10%\n(95% CI:\n73%-88%)"],["","40-65","94.95%\n(95% CI:\n93%-96%)","94.37%\n(95% CI:\n93%-96%)","94.76%\n(95% CI:\n93%-96%)","85.24%\n(95% CI:\n80%-90%)"],["","65 and over","97.01%\n(95% CI:\n96%-98%)","95.33%\n(95% CI:\n94%-97%)","94.55%\n(95% CI:\n93%-96%)","88.61%\n(95% CI:\n85%-92%)"],["Sex","F","95.05%\n(95% CI:\n94%-96%)","93.78%\n(95% CI:\n92%-95%)","93.36%\n(95% CI:\n91%-95%)","82.96%\n(95% CI:\n78%-87%)"],["","M","96.07%\n(95% CI:\n95%-97%)","95.13%\n(95% CI:\n94%-96%)","95.62%\n(95% CI:\n94%-97%)","88.89%\n(95% CI:\n85%-92%)"]],"caption_candidate":"Systems","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251106-p17-t0","doc_id":"K251106","page_num":17,"bbox":[72.9,71.34,537.22,571.5],"n_rows":9,"n_cols":6,"columns":["Ethnicity","African\nAmerican/ Black","94.40%\n(95% CI:\n91%-97%)","94.96%\n(95% CI:\n92%-97%)","91.36%\n(95% CI:\n87%-95%)","84.03%\n(95% CI:\n76%-90%)"],"rows":[["Ethnicity","African\nAmerican/ Black","94.40%\n(95% CI:\n91%-97%)","94.96%\n(95% CI:\n92%-97%)","91.36%\n(95% CI:\n87%-95%)","84.03%\n(95% CI:\n76%-90%)"],["","Asian","100%\n(95% CI:\n95%-100%)","95.71%\n(95% CI:\n88%-99%)","90.91%\n(95% CI:\n78%-97%)","85.19%\n(95% CI:\n66%-96%)"],["","Caucasian/\nWhite","95.71%\n(95% CI:\n94%-97%)","95.05%\n(95% CI:\n94%-96%)","94.77%\n(95% CI:\n93%-96%)","84.47%\n(95% CI:\n80%-88%)"],["","Hispanic","94.23%\n(95% CI:\n92%-96%)","92.52%\n(95% CI:\n90%-95%)","97.58%\n(95% CI:\n95%-99%)","94.44%\n(95% CI:\n89%-98%)"],["","Mixed/Multira\ncial","100.00%\n(95% CI:\n88%-100%)","93.75%\n(95% CI:\n79%-99%)","89.47%\n(95% CI:\n67%-99%)","84.62%\n(95% CI:\n55%-98%)"],["","Native\nAmerican","97.77%\n(95% CI:\n94%-99%)","94.09%\n(95% CI:\n90%-97%)","93.48%\n(95% CI:\n88%-97%)","80.43%\n(95% CI:\n66%-91%)"],["BMI Range","Below 25","93.98%\n(95% CI:\n92%-96%)","95.12%\n(95% CI:\n93%-97%)","93.64%\n(95% CI:\n91%-96%)","89.21%\n(95% CI:\n85%-93%)"],["","25-29.9","95.27%\n(95% CI:\n94%-97%)","93.19%\n(95% CI:\n91%-95%)","93.45%\n(95% CI:\n91%-95%)","84.51%\n(95% CI:\n79%-89%)"],["","30 and above","97.02%\n(95% CI:\n96%-98%)","95.13 %\n(95% CI:\n94%-96%)","95.85%\n(95% CI:\n94%-97%)","83.87%\n(95% CI:\n78%-89%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251110-p5-t0","doc_id":"K251110","page_num":5,"bbox":[251.16,475.45,565.97,605.86],"n_rows":8,"n_cols":3,"columns":["Classification Description","21 CFR §","Product Code"],"rows":[["Classification Description","21 CFR §","Product Code"],["Primary","",""],["System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],["Secondary","",""],["System, imaging, pulsed echo,\nultrasonic","892.1560","IYO"],["Transducer, ultrasonic, diagnostic","892.1570","ITX"],["Automated Radiological Image\nProcessing Software","892.2050","QIH"],["Diagnostic Intravascular Catheter","870.1200","OBJ*"]],"caption_candidate":"Common Name Diagnostic Ultrasound System and Transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251151-p6-t0","doc_id":"K251151","page_num":6,"bbox":[78.13,417.86,544.43,715.91],"n_rows":4,"n_cols":3,"columns":["Parameter","Rapid LVO (K200941)\nPredicate Device","Rapid CTA 360\nSubject Device"],"rows":[["Parameter","Rapid LVO (K200941)\nPredicate Device","Rapid CTA 360\nSubject Device"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Intended Use/\nIndications for\nUse","Rapid LVO is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of CTA head\nimages. The device is intended to\nassist hospital networks and trained\nradiologists in workflow triage by\nflagging and communication of\nsuspected positive ICA or MCA-M1\nLarge Vessel Occlusion (LVO)\nfindings in head CTA images.\nRapid LVO uses a software\nalgorithm to analyze images and\nhighlight cases with suspected LVO\non a server or standalone desktop\napplication in parallel to the ongoing","Rapid CTA 360 is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the analysis of CTA adult\nhead images. The device is intended\nto assist hospital networks and\ntrained clinicians in workflow triage\nby flagging and communication of\nsuspected positive Large and\nMedium Vessel Occlusion findings\nin head CTA images including the\nICA (C1-C5), MCA (M1-M3),\nACA, PCA, Basilar and Vertebral\nvascular segments.\nRapid CTA 360 uses an AI software\nalgorithm to analyze images and"]],"caption_candidate":"the Rapid CTA 360 software device that is the subject of this Traditional 510(k) submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251151-p7-t0","doc_id":"K251151","page_num":7,"bbox":[78.14,72.98,544.42,625.79],"n_rows":9,"n_cols":3,"columns":["","standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected LVO findings.\nNotifications include compressed\npreview images. These are meant for\ninformational purposes only and are\nnot intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of Rapid LVO are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","highlight cases with suspected\nocclusion on a server or standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected LVO and MVO findings.\nNotifications include compressed\npreview images. These are meant for\ninformational purposes only and are\nnot intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of Rapid CTA 360 are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care."],"rows":[["","standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected LVO findings.\nNotifications include compressed\npreview images. These are meant for\ninformational purposes only and are\nnot intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of Rapid LVO are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage /prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","highlight cases with suspected\nocclusion on a server or standalone\ndesktop application in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected LVO and MVO findings.\nNotifications include compressed\npreview images. These are meant for\ninformational purposes only and are\nnot intended for diagnostic use\nbeyond notification. The device does\nnot alter the original medical image\nand is not intended to be used as a\ndiagnostic device.\nThe results of Rapid CTA 360 are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care."],["Input Data\nRequirements","CTA","CTA"],["Patient Population","Adult","Adult"],["DICOM\nCompliance","Yes","Yes"],["User Output","Notification w/compressed\nimages","Notification w/compressed\nimages"],["SW","Traditional","AI/ML"],["Segments","ICA, MCA-M1","ICA (C1-C5), MCA (M1-M3),\nACA, PCA, Basilar and Vertebral"],["Outputs","Reports, DICOM Secondary\nCapture Series","Reports, DICOM Secondary\nCapture Series"],["Cybersecurity\nFramework","External I/Fs through Rapid\nPlatform","External I/Fs through Rapid\nPlatform"]],"caption_candidate":"iSchemaView - Traditional 510(k) Rapid CTA 360 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251153-p5-t0","doc_id":"K251153","page_num":5,"bbox":[77.66,587.4,545.14,710.88],"n_rows":6,"n_cols":4,"columns":["","Predicate Device Information","",""],"rows":[["","Predicate Device Information","",""],["Device Name","","Aurora",""],["Manufacturer","","GE Medical Systems Israel, Functional Imaging",""],["510(k) number","","K243605",""],["Regulation number","","21CFR 892.1200 and 21CFR 892.1750",""],["Product Code","","KPS and JAK",""]],"caption_candidate":"Product Code: KPS & JAK","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251153-p8-t0","doc_id":"K251153","page_num":8,"bbox":[72.26,93.42,539.8,342.66],"n_rows":6,"n_cols":9,"columns":["","Specification /","","","Predicate Device:","","","Proposed Device:",""],"rows":[["","Specification /","","","Predicate Device:","","","Proposed Device:",""],["","Attribute","","","Aurora (K243605)","","","Aurora",""],["NM System","","","Dual NaI-based detectors NM system\nfor Planar and SPECT imaging, with\n“Real-time Time Activity Curve” option\nfor Planar Dynamic Scans","","","Dual NaI-based detectors NM system for\nPlanar and SPECT imaging, with “Real-\ntime Time Activity Curve” option for\nPlanar Dynamic Scans and DL Automatic\nKidney Segmentation","",""],["CT System","","","GEHC Commercially Available\nRevolution Ascend (K213938)","","","GEHC Commercially Available Revolution\nAscend (K213938)","",""],["Patient Table","","","Dual axis table for Planar, SPECT, CT\nand SPECT / CT Imaging\nSPECT Scan Range: 200cm\nSPECT-CT Scan Range: 185 cm","","","Dual axis table for Planar, SPECT, CT and\nSPECT / CT Imaging\nSPECT Scan Range: 200cm\nSPECT-CT Scan Range: 185 cm","",""],["Standards\nConformance","","","IEC 60601-1 and applicable Collateral\nand Particular Standards.","","","IEC 60601-1 and applicable Collateral and\nParticular Standards.","",""]],"caption_candidate":"510(k) Premarket Notification Submission for Aurora","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p8-t0","doc_id":"K251167","page_num":8,"bbox":[72.25,108.12,716.01,531.24],"n_rows":12,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uDR Aurora CX","","","uDR 780i (K241068)","",""],["High Voltage Generator","","","","","","",""],["Max. Power/kW","65kW/80kW","","","65kW/80kW","","","Same"],["Max. tube\nVoltage(kV)","150kV","","","150kV","","","Same"],["Shortest exposure\ntime","1ms","","","1ms","","","Same"],["X-Ray Tube Assemble","","","","","","",""],["Focus Nominal\nValue","0.6/1.2","","","0.6/1.2","","","Same"],["Maximum peak\nvoltage","150kV","","","150kV","","","Same"],["Anode Heat Content","65kw: ≥300kHU\n80kw: ≥400kHU","","","65kw: ≥300kHU\n80kw: ≥400kHU","","","Same"],["Anode Target Angle","12°","","","12°","","","Same"],["X-ray tube assembly\nHeat content","65kw: ≥1250KHU","","","65kw: ≥1250KHU","","","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p10-t0","doc_id":"K251167","page_num":10,"bbox":[77.4,36.47,709.41,510.41],"n_rows":45,"n_cols":4,"columns":["Shanghai United Imaging Healthc","are Co., Ltd.","",""],"rows":[["Shanghai United Imaging Healthc","are Co., Ltd.","",""],["","","",""],["Tel: +86 (21) 67076888 Fa","x：+86 (21) 67076889","",""],["","","",""],["www.united-imaging.com","","",""],["","","",""],["","Proposed Device","Predicate Device",""],["Item","","","Remark"],["","uDR Aurora CX","uDR 780i (K241068)",""],["","","",""],["","100 μm","125μm",""],["","","",""],["Effective","","",""],["","","",""],["","35cm x 43cm","41.5cm x 42.6cm","Note 5"],["","","",""],["Radiographic Size","","",""],["","","",""],["Collimator","","",""],["","","",""],["Inherent filtration","1mm Al","1mm Al","Same"],["","","",""],["","without filter,","without filter,",""],["","","",""],["","0.1 mm,","0.1 mm,",""],["Copper prefilter","","","Same"],["","0.2 mm,","0.2 mm,",""],["","","",""],["","0.3 mm;","0.3 mm;",""],["","","",""],["","Live 2D Camera for patient positioning and","",""],["","","",""],["Bulit-in camera","","N/A","Note 6"],["","","",""],["","collimation","",""],["","","",""],["Elevating table","","",""],["","","",""],["Motorized vertical","","",""],["","","",""],["","≥38.2cm","≥38.2cm","Same"],["","","",""],["travel","","",""],["","","",""],["Max. patient weight","320kg","320kg","Same"]],"caption_candidate":"K251167","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251167-p11-t0","doc_id":"K251167","page_num":11,"bbox":[72.25,108.12,716.01,479.02],"n_rows":11,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uDR Aurora CX","","","uDR 780i (K241068)","",""],["Detector travel range","≥90cm","","","≥67cm","","","Note 7"],["Auto tracking for\nadjusting the table\nheight is maintained","Yes, X-ray tube follows table height adjustment;\nsource-image distance is maintained.","","","Yes, X-ray tube follows table height\nadjustment; source-image distance is\nmaintained.","","","Same"],["Auto tracking for\nlongitudinal tube\ntravel","Yes, detector follows tube movement;\ncentering maintained.","","","Yes, detector follows tube movement;\ncentering maintained.","","","Same"],["Auto tracking for\ntube rotation","Yes, detector follows tube movement;\ncentering maintained.","","","Yes, detector follows tube movement;\ncentering maintained.","","","Same"],["Software function","","","","","","",""],["uAid","Yes","","","No","","","Note8"],["Stitching","Yes","","","Yes","","","Same"],["AEC","Yes","","","Yes","","","Same"],["Safety","","","","","","",""]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p12-t0","doc_id":"K251167","page_num":12,"bbox":[72.25,108.12,716.01,463.71],"n_rows":12,"n_cols":8,"columns":["Item","","Proposed Device","","","Predicate Device","","Remark"],"rows":[["Item","","Proposed Device","","","Predicate Device","","Remark"],["","","uDR Aurora CX","","","uDR 780i (K241068)","",""],["Electrical Safety","ANSI/AAMI ES 60601-1:2005 & A1:2012 &\nA2:2021 Medical electrical equipment - Part 1:\nGeneral requirements for basic safety and\nessential performance","","","ANSI/AAMI ES 60601-1:2005 & A1:2012 &\nA2:2021 Medical electrical equipment - Part 1:\nGeneral requirements for basic safety and\nessential performance","","","Same"],["EMC","Comply with IEC 60601-1-2:2014+A1:2020","","","","Comply with IEC60601-1-2","","Same"],["Biocompatibility","Patient Contact Materials were tested and\ndemonstrated no cytotoxicity (ISO 10993-5),\nno evidence for irritation and sensitization (ISO\n10993-10).","","","","Patient Contact Materials were tested and","","Same"],["","","","","","demonstrated no cytotoxicity (ISO 10993-5),","",""],["","","","","","no evidence for irritation and sensitization (ISO","",""],["","","","","","10993-10).","",""],["Clinical Image\nEvaluation","Clinical Image Evaluation for the proposed device are provided in Section 11.5 Clinical Image Evaluation.","","","","","",""],["Standards","","","","","","",""],["DICOM","DICOM3","","","","DICOM3","","Same"],["Power Source","AC Line, Various voltages available","","","","AC Line, Various voltages available","","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p13-t0","doc_id":"K251167","page_num":13,"bbox":[56.45,128.17,709.97,500.38],"n_rows":3,"n_cols":8,"columns":["Item","","Proposed Device","","","Reference Device","","Remark"],"rows":[["Item","","Proposed Device","","","Reference Device","","Remark"],["","","uDR Aurora CX","","","MULTIX Impact C(K213700)","",""],["uVision\nFunction\n（optional）","Users can manually adjust FOV and\nstitching range on the workstation.\nTo assist the users with setting the FOV\nand stitching range, exam range is\nautomatically planned for chest and\nstitching range is automatically planned for\nWholeSpine & WholeLowerExtremity.","","","-Virtual Collimation\nManually adjust collimation size on\nimaging system by 3D camera\n-Smart Virtual Ortho:\nOrtho range set by 2D camera in the\nimage system manually\n-Auto Thorax Collimation\nExam range automatically planned for\nThorax by 3D camera with manual\nadjustment\n-Auto Full-Spine& Long-Leg\nCollimation:\nOrtho range automatically planned for\nFull-Spine &Long-Leg by 2D camera\nwith manual adjustment","","","Note 9"]],"caption_candidate":"Table2: Comparison of new features to predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p14-t0","doc_id":"K251167","page_num":14,"bbox":[56.4,128.06,710.02,497.74],"n_rows":8,"n_cols":2,"columns":["Justification",""],"rows":[["Justification",""],["Note 1","Minor grammatical changes only."],["Note 2","The larger the image matrix size, the higher the resolution, and the greater the capability to capture fine\nstructures, which means the ability to identify smaller lesions and tissues. The difference does not introduce\nsafety and effectiveness issues."],["Note 3","Effective Radiographic Size refers to the actual area size of the detector panel that can be utilized in practical\nimaging. A larger Effective Radiographic Size indicates that the detector can cover a larger range of anatomical\nareas in practical use. The difference does not introduce safety and effectiveness issues."],["Note 4","The larger the image matrix size, the higher the resolution, and the greater the capability to capture fine\nstructures, which means the ability to identify smaller lesions and tissues. The difference does not introduce\nsafety and effectiveness issues."],["Note 5","Only the different of size specification, does not affect safety and effectiveness. The 35cm x 43cm normally\nused in free exam mode which is different with 41.5cm x 42.6cm which used in the tray in table."],["Note 6","2D camera only introduced to capture optical information and support more clinical operational possibilities.,\ndoes not affect safety and effectiveness."],["Note 7","Detector travel range refers to the movement range of the tray in Table. A larger travel range indicates a larger\ncoverage on table and more operational possibilities. The difference does not introduce safety and effectiveness\nissues."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p15-t0","doc_id":"K251167","page_num":15,"bbox":[56.4,108.02,710.02,218.09],"n_rows":2,"n_cols":2,"columns":["Note 8","uAid evaluates the positioning quality of chest images with deep learning methods. It efficiently and objectively\ncategorizes images into three levels according to four criteria, to assist standardizing the management of image\nquality/technologist skills. The difference does not introduce safety and effectiveness issues."],"rows":[["Note 8","uAid evaluates the positioning quality of chest images with deep learning methods. It efficiently and objectively\ncategorizes images into three levels according to four criteria, to assist standardizing the management of image\nquality/technologist skills. The difference does not introduce safety and effectiveness issues."],["Note 9","For manually adjust collimation size and automatically planned for chest and stitching range these two functions\nare same with predicate device MULTIX Impact C, the difference is the description way, the difference does not\nintroduce safety and effectiveness issues."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p15-t1","doc_id":"K251167","page_num":15,"bbox":[77.69,473.26,721.85,525.96],"n_rows":2,"n_cols":6,"columns":["","Feature","","","Bench Testing Performed",""],"rows":[["","Feature","","","Bench Testing Performed",""],["uVision","","","Introduction","",""]],"caption_candidate":"Additional non-clinical tests are conducted for key features to ensure safe and effectiveness when integrated into the system:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p17-t0","doc_id":"K251167","page_num":17,"bbox":[274.61,163.7,713.86,215.21],"n_rows":2,"n_cols":5,"columns":["Height (m)","≤1.25","1.25~1.5","1.5~1.75","≥1.75"],"rows":[["Height (m)","≤1.25","1.25~1.5","1.5~1.75","≥1.75"],["Percentage","3%","7%","58%","32%"]],"caption_candidate":"independently)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p17-t1","doc_id":"K251167","page_num":17,"bbox":[274.61,272.69,699.94,510.87],"n_rows":8,"n_cols":5,"columns":["Date","Chest/case","Case of Non-\nCompliant Cases in\nSystem-\nAutomatically Set\nResults","Full Spine or Full\nLower Limb\nStitching/case","Case of Non-\nCompliant Cases in\nSystem-Automatically\nSet Results"],"rows":[["Date","Chest/case","Case of Non-\nCompliant Cases in\nSystem-\nAutomatically Set\nResults","Full Spine or Full\nLower Limb\nStitching/case","Case of Non-\nCompliant Cases in\nSystem-Automatically\nSet Results"],["2024.12.17","62","3","2","0"],["2024.12.18","44","3","2","0"],["2024.12.19.","35","2","5","0"],["2024.12.20","18","1","5","0"],["2024.12.21","59","2","2","0"],["2024.12.22","47","1","1","0"],["2024.12.23","63","2","3","0"]],"caption_candidate":"for chest PA、WholeSpine and WholeLowerExtremity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p18-t0","doc_id":"K251167","page_num":18,"bbox":[77.64,108.36,721.9,531.48],"n_rows":2,"n_cols":2,"columns":["","Total number of 328 14 20 0\ncases in a week\nEquipment and Protocols\nThe test data was collected, and the testing protocol included chest, Whole-spine\nstitching, Whole-Lower-extremity stitching.\nClinical Subgroups\nNo clinical subgroups and confounders have been defined for the datasets.\nTesting & Training Data Independence\nThe testing dataset was collected independently from the training dataset, with separated\nsubjects and during different time periods. Therefore, the testing data is entirely independent\nand does not share any overlap with the training data.\nSummary\nAccording to the results of the current equipment statistics, in 95% of patient positioning\nprocesses, the light field and equipment position automatically set by uVision can meet the\nclinical positioning and shooting requirements. In the remaining 5% of cases, based on the\nlight field and system position automatically set by the equipment, technicians still need to\nmake manual adjustments"],"rows":[["","Total number of 328 14 20 0\ncases in a week\nEquipment and Protocols\nThe test data was collected, and the testing protocol included chest, Whole-spine\nstitching, Whole-Lower-extremity stitching.\nClinical Subgroups\nNo clinical subgroups and confounders have been defined for the datasets.\nTesting & Training Data Independence\nThe testing dataset was collected independently from the training dataset, with separated\nsubjects and during different time periods. Therefore, the testing data is entirely independent\nand does not share any overlap with the training data.\nSummary\nAccording to the results of the current equipment statistics, in 95% of patient positioning\nprocesses, the light field and equipment position automatically set by uVision can meet the\nclinical positioning and shooting requirements. In the remaining 5% of cases, based on the\nlight field and system position automatically set by the equipment, technicians still need to\nmake manual adjustments"],["uAid","Introduction\nuAid is used for checking the quality of examination and positioning. The results can help to\nassist with departmental management functions. uAid is triggered after the acquisition of\nchest X-ray images in patients aged over 20 years, which automatically evaluates image\ncharacteristics against four criteria, namely whether there is a foreign object, whether the\nlung field is complete, whether the scapula is open, and whether the spine is located on the\ncenter line, categorizing images into one of three quality levels. The outcome of the\nevaluation is instantly accessible to radiologic technologists, reminding them to verify that\nthe image meets the image quality control. It bears emphasis that the result of image quality\ncontrol is for reference only and cannot be used as the basis for clinical diagnosis.\nAcceptance Criteria\nuAid is designed to provide an objective image evaluation method, offering hospitals a\nunified assessment tool to manage images/technicians. The accuracy of non-standard image"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p19-t0","doc_id":"K251167","page_num":19,"bbox":[274.61,358.75,691.42,517.78],"n_rows":11,"n_cols":3,"columns":["Age","Male","Female"],"rows":[["Age","Male","Female"],["20-29","310","698"],["30-39","308","744"],["40-49","298","798"],["50-59","385","801"],["60-69","320","799"],["70-79","200","472"],["80-89","97","210"],["90-99","21","46"],["No Age","97","187"],["No Age，No Gender","45",""]],"caption_candidate":" Age and gender distribution of data sets for uAid：","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251167-p20-t0","doc_id":"K251167","page_num":20,"bbox":[274.61,108.31,593.59,180.05],"n_rows":5,"n_cols":3,"columns":["","Negative","Positive"],"rows":[["","Negative","Positive"],["lung field segmentation","465","31"],["Spinal centerline segmentation","815","68"],["Shoulder blades segmentation","210","1089"],["Foreign object","1078","3080"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p6-t0","doc_id":"K251195","page_num":6,"bbox":[72.0,528.96,540.0,584.04],"n_rows":4,"n_cols":2,"columns":["","In addition, the SW architecture was changed to separate the image communication platform"],"rows":[["","In addition, the SW architecture was changed to separate the image communication platform"],["from the BriefCase-Triage SW. The subject device consists of only the algorithm analysis module which can be",""],["integrated with image communication platforms that meet the BriefCase-Triage input and output",""],["requirements.",""]],"caption_candidate":"Triage for BA (K213721) are identical in most aspects and differ mostly with respect to their algorithm","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p7-t0","doc_id":"K251195","page_num":7,"bbox":[72.0,210.72,539.16,699.84],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],["Intended\nUse /\nIndications\nfor Use","BriefCase-Triage is a radiological computer\naided triage and notification software\nindicated for use in the analysis of contrast-\nenhanced CT images that include the brain,\nin adults or transitional adolescents aged 18\nand older. The device is intended to assist\nhospital networks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspected\npositive cases of Brain Aneurysm (BA)\nfindings that are 3.0 mm or larger.\nBriefCase-Triage uses an artificial intelligence\nalgorithm to analyze images and flag suspect\ncases in parallel to the ongoing standard of\ncare image interpretation. The user is\npresented with notifications for suspect\ncases. Notifications include compressed\npreview images that are meant for\ninformational purposes only and not\nintended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase-Triage are intended\nto be used in conjunction with other patient\ninformation and based on professional\njudgment, to assist with triage/prioritization\nof medical images. Notified clinicians are","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of head CT Angio (CTA)\nimages. The device is intended to assist\nhospital networks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspected\npositive cases of Brain Aneurysm (BA) findings\nabove 5 mm size.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and flag suspect\ncases on a standalone desktop application in\nparallel to the ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for suspect cases. Notifications\ninclude compressed preview images that are\nmeant for informational purposes only and\nnot intended for diagnostic use beyond\nnotification. The device does not alter the\noriginal medical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended to be\nused in conjunction with other patient\ninformation and based on professional\njudgment, to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p8-t0","doc_id":"K251195","page_num":8,"bbox":[72.0,72.24,539.16,608.16],"n_rows":9,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],["","responsible for viewing full images per the\nstandard of care.",""],["User\npopulation","Hospital networks and appropriately trained\nmedical specialists","Hospital networks and appropriately trained\nmedical specialists"],["Threshold\nBA\nFindings","Brain Aneurysm (BA) findings that are 3.0 mm\nsize or larger","Brain Aneurysm (BA) findings above 5 mm size"],["Anatomica\nl region of\ninterest /\nOrgan","Brain","Head"],["Data\nacquisition\nprotocol","Contrast-enhanced CT images that include\nthe brain","Computed tomography angiography (CTA) of\nthe head"],["Notificatio\nn-only\n(/notificati\non alerts),\nparallel\nworkflow\ntool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interferen\nce with\nstandard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p9-t0","doc_id":"K251195","page_num":9,"bbox":[72.0,72.24,539.16,585.72],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage for BA","Predicate Device\nAidoc BriefCase-Triage for BA (K213721)"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperforman\nce testing","Inclusion criteria\n● Contrast-enhanced CT images that\ninclude the brain\n● Scans performed on\nadults/transitional adults ≥ 18 years of\nage.\n● Slice thickness; 0.5 mm – 2.5\nmm axial slices.\nExclusion Criteria\n● All studies that have an inadequate\nfield of view.","Inclusion criteria\n● computed tomography\nangiography (CTA) of the head.\n● Scans performed on\nadults/transitional adults ≥ 18 years of\nage.\n● Scans performed on CT\nscanners with 64 or greater number of\ndetectors.\n● Slice thickness; 0.5 – 2.5 mm\naxial slices.\nExclusion Criteria\n● All scans that are technically\ninadequate, including motion artifacts,\nsevere metal artifacts, or an inadequate\nfield of view."],["Additional\nOperating\nPoints","3 Additional Operating Points","N/A"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with database\nof images."],["Structure","- Integrated with image routing module via\nimage communication platform (ICP) (image\nacquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and non-\ndiagnostic Image Viewer).","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for workflow\nintegration (Feed/Worklist (alternate\nnames) and non-diagnostic Image\nViewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p10-t0","doc_id":"K251195","page_num":10,"bbox":[113.13,604.4,498.6,716.76],"n_rows":10,"n_cols":6,"columns":["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],"rows":[["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],["","Estimate","","CL","CL",""],["","","","","",""],["","","","","",""],["","(seconds)","","","",""],["Predicate K213721","","","","",""],["","","","","",""],["","252","103","234","270","252"],["","","","","",""],["Processing Time","","","","",""]],"caption_candidate":"Table 2. Time-to- notification comparison for BriefCase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p11-t0","doc_id":"K251195","page_num":11,"bbox":[113.18,72.32,498.76,214.33],"n_rows":11,"n_cols":6,"columns":["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],"rows":[["Time -to-notification","Mean","N","95% Lower","95% Upper","Median"],["","Estimate","","CL","CL",""],["","","","","",""],["","","","","",""],["","(seconds)","","","",""],["BriefCase-Triage and","44.8","241","41.4","48.2","38.2"],["","","","","",""],["Image Communication","","","","",""],["Platform Time-To-","","","","",""],["","","","","",""],["Notification","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p11-t1","doc_id":"K251195","page_num":11,"bbox":[130.64,421.8,481.44,468.03],"n_rows":2,"n_cols":20,"columns":["","","","","Mean","","Std","","","Min","","","Median","","","Max","","","N",""],"rows":[["","","","","Mean","","Std","","","Min","","","Median","","","Max","","","N",""],["","Age (Years)","","61.9","","17.7","","","18","","","65","","","98","","","544","",""]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p11-t2","doc_id":"K251195","page_num":11,"bbox":[179.32,509.55,433.04,655.72],"n_rows":6,"n_cols":11,"columns":["Ground\nTruth\nResults","","Gender","","","","","All","","",""],"rows":[["Ground\nTruth\nResults","","Gender","","","","","All","","",""],["","","Female","","","Male","","","","",""],["","","N","","%","N","%","N","","%",""],["","Positive","165","","30.3%","81","14.9%","246","","45.2%",""],["","Negative","172","","31.6%","126","23.2%","298","","54.8%",""],["","All","337","","61.9%","207","38.1%","544","","100.0%",""]],"caption_candidate":"Table 4. Frequency Distribution of Gender *","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p12-t0","doc_id":"K251195","page_num":12,"bbox":[208.95,72.88,403.16,178.44],"n_rows":6,"n_cols":9,"columns":["","Manufacturer","","","N","","","%",""],"rows":[["","Manufacturer","","","N","","","%",""],["GE MEDICAL SYSTEMS","","","243","","","44.7%","",""],["Philips","","","69","","","12.7%","",""],["SIEMENS","","","166","","","30.5%","",""],["TOSHIBA","","","66","","","12.1%","",""],["Total","","","544","","","100%","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p12-t1","doc_id":"K251195","page_num":12,"bbox":[229.85,209.79,382.5,308.24],"n_rows":5,"n_cols":9,"columns":["","Thickness","","N","","","%","",""],"rows":[["","Thickness","","N","","","%","",""],["","(mm)","","","","","","",""],["0-1","","","355","","","65.3%","",""],["1-2.5","","","189","","","34.70%","",""],["","Total","","","544","","","100%",""]],"caption_candidate":"Table 6. Frequency Distribution of slice thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p12-t2","doc_id":"K251195","page_num":12,"bbox":[214.27,340.96,397.71,423.88],"n_rows":4,"n_cols":9,"columns":["","Protocol","","","N","","","%",""],"rows":[["","Protocol","","","N","","","%",""],["CT angiogram","","","270","","","49.6%","",""],["CT w/ contrast","","","274","","","50.4%","",""],["","Total","","","544","","","100%",""]],"caption_candidate":"Table 7. Frequency Distribution of protocol","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251195-p13-t0","doc_id":"K251195","page_num":13,"bbox":[72.48,72.48,540.48,173.76],"n_rows":3,"n_cols":3,"columns":["AOP1","87.4% (95% CI: 82.6%-91.3%)","91.9% (95% CI: 88.3%-94.8%)"],"rows":[["AOP1","87.4% (95% CI: 82.6%-91.3%)","91.9% (95% CI: 88.3%-94.8%)"],["AOP2","87.0% (95% CI: 82.1%-90.9%)","92.6% (95% CI: 89.0%-95.3%)"],["AOP3","86.2% (95% CI: 81.2%-90.2%)","93.6% (95% CI: 90.2%-96.1%)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p6-t0","doc_id":"K251276","page_num":6,"bbox":[71.72,316.9,539.58,716.35],"n_rows":17,"n_cols":3,"columns":["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],"rows":[["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],["Specification","",""],["","System","System (K240944)"],["","",""],["Intended Use/ Indications for Use:","The Swoop Portable MR Imaging System\nis a portable, ultra-low field magnetic\nresonance imaging device for producing\nimages that display the internal\nstructure of the head where full\ndiagnostic examination is not clinically\npractical. When interpreted by a trained\nphysician, these images provide\ninformation that can be useful in\ndetermining a diagnosis.","Same"],["Patient Population:","Adult and pediatric patients (≥ 0 years)","Same"],["Anatomical Sites:","Head","Same"],["Environment of Use:","At the point of care in professional\nhealth care facilities such as emergency\nrooms, intensive/critical care units,\nhospitals, outpatient, or rehabilitation\ncenters.","Same"],["Energy Used and/or delivered:","Magnetic Resonance","Same"],["Magnet:","",""],["Physical Dimensions","835 mm x 630 mm x 652 mm","Same"],["Bore Opening","610 mm x 315 mm","Same"],["Weight","320 kg","Same"],["Field Strength","63.3 mT permanent magnet","Same"],["Gradient:","",""],["Strength","X: 24 mT/m, Y: 23 mT/m, Z: 39 mT/m","Same"],["Rise Time","X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms","Same"]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p7-t0","doc_id":"K251276","page_num":7,"bbox":[71.7,72.58,539.59,559.29],"n_rows":24,"n_cols":3,"columns":["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],"rows":[["","Subject Swoop Portable MR Imaging","Predicate Swoop Portable MR Imaging"],["Specification","",""],["","System","System (K240944)"],["","",""],["Slew Rate","X: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/s","Same"],["Computer Display","Hyperfine-supplied tablet","Same"],["RF Coils:","",""],["Number of Coils","1 head coil","Same"],["Coil Type","TX/RX","Same"],["Coil Geometry","Form-fitting","Same"],["Inner Dimensions (mm)","205 mm x 240 mm","Same"],["Coil Design","Linear Volume","Same"],["Patient Weight Capacity","1.6kg-200 kg","Same"],["Operation Temperature","15-30 C","Same"],["Warm Up Time","<3 minutes","Same"],["Temperature Control","No","Same"],["Humidity Control","No","Same"],["Image Processing:","",""],["Noise Correction","Noise correction and line noise\nsuppression for all sequences","Same"],["T1W\n• T1-Standard\n• T1-Gray/White Contrast","Advanced Gridding","Same"],["T2W\n• T2\n• T2-Fast","Advanced Gridding","Same"],["FLAIR","Advanced Gridding","Same"],["DWI","Advanced Gridding,\nFast Iterative Shrinkage Thresholding\nAlgorithm (FISTA)","Fast Iterative Shrinkage Thresholding\nAlgorithm (FISTA)"],["Image Post-Processing","• Advanced Denoising\n• Image orientation transform\n• Geometric distortion correction\n• Receive coil intensity correction\n• Advanced Interpolation\n• DICOM output","• Advanced Denoising\n• Image orientation transform\n• Geometric distortion correction\n• Receive coil intensity correction\n• DICOM output"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p8-t0","doc_id":"K251276","page_num":8,"bbox":[72.46,116.11,539.58,363.74],"n_rows":5,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Software\nVerification","Software verification testing in accordance with\nthe design requirements to ensure that the\nsoftware requirements were met.","• IEC 62304:2016\n• FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"],["Image Performance","Testing to verify the subject device meets all\nimage quality criteria.","• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• American College of Radiology\nstandards for named sequences"],["Cybersecurity","Testing to verify cybersecurity controls and\nmanagement.","• FDA Guidance, “Cybersecurity in\nMedical Devices: Quality System\nConsiderations and Content of\nPremarket Submissions”"],["Software\nValidation","Validation to ensure the subject device meets\nuser needs and performs as intended.","• FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"]],"caption_candidate":"requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p8-t1","doc_id":"K251276","page_num":8,"bbox":[72.46,435.21,539.58,628.07],"n_rows":5,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Biocompatibility","Biocompatibility testing of patient-contacting\nmaterials.","• ISO 10993-1:2018\n• ISO 10993-5:2009\n• ISO 10993-10:2010"],["Cleaning/\nDisinfection","Cleaning and disinfection validation of patient-\ncontacting materials.","• FDA Guidance, “Reprocessing Medical\nDevices in Health Care Settings:\nValidation Methods and Labeling”\n• ISO 17664:2017\n• ASTM F3208-17"],["Safety","Electrical Safety, EMC, and Essential Performance\ntesting.","• ANSI/AAMI ES 60601-1:2005/(R)2012\n• IEC 60601-1-2:2014\n• IEC 60601-1-6:2013"],["Performance","Characterization of the Specific Absorption Rate\nfor Magnetic Resonance Imaging Systems.","• NEMA MS 8-2016"]],"caption_candidate":"modifications did not introduce a new worst-case configuration or scenario for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t0","doc_id":"K251276","page_num":10,"bbox":[72.45,72.59,537.71,646.57],"n_rows":5,"n_cols":6,"columns":["","Model /","","#Patients","#Images","Demographics"],"rows":[["","Model /","","#Patients","#Images","Demographics"],["","Sequence","","","",""],["","Group","","","",""],["T1, T2,\nFLAIR","","","44","92","Gender\nFemale Male Unknown\n55% 30% 15%\nAge\n0-2 2-18 18-35 35-60 60+ 18+* Unknown\n16% 14% 11% 20% 23% 9% 7%\n*partially anonymized\nEthnicity data not recorded.\nNumber of sites: 9\nEquipment\nSwoop Mk1.7 Swoop Mk1.8 Swoop Mk1.9\n57% 9% 34%\nIncluded pathology: Alzheimer’s Disease, Hemorrhage, Hydrocephalus,\nHypoglycemia, Intracereberal Hemorrhage, Multiple Sclerosis, Subdural\nHemorrhage, Seizure, Traumatic Brain Injury, Treacher Collins Syndrome,\nTumor, White Matter Hyperintensity"],["DWI","","","34","65","Gender:\nFemale Male Unknown\n41% 47% 12%\nAge:\n0-2 2-18 18-35 35-60 60+ Unknown\n21% 15% 18% 23% 18% 5%\nEthnicity data not recorded.\nNumber of sites: 6\nEquipment:\nSwoop Mk1.7 Swoop Mk1.9\n73% 27%\nIncluded pathology: Alzheimer’s Disease, Hemorrhage, Hydrocephalus,\nHypoglycemia, Subdural Hemorrhage, Seizure, Traumatic Brain Injury,\nThrombosis, Treacher Collins Syndrome, White Matter Hyperintensity"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t1","doc_id":"K251276","page_num":10,"bbox":[236.34,122.3,537.71,153.3],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["55%","30%","15%"]],"caption_candidate":"T1, T2, 44 92 Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t2","doc_id":"K251276","page_num":10,"bbox":[236.34,178.3,548.23,209.33],"n_rows":2,"n_cols":8,"columns":["0-2","2-18","18-35","35-60","60+","18+*","Unknown",""],"rows":[["0-2","2-18","18-35","35-60","60+","18+*","Unknown",""],["16%","14%","11%","20%","23%","9%","7%",""]],"caption_candidate":"Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t3","doc_id":"K251276","page_num":10,"bbox":[236.34,295.35,485.45,326.35],"n_rows":2,"n_cols":3,"columns":["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],"rows":[["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],["57%","9%","34%"]],"caption_candidate":"Equipment","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t4","doc_id":"K251276","page_num":10,"bbox":[236.34,400.62,537.71,431.62],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["41%","47%","12%"]],"caption_candidate":"DWI 34 65 Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t5","doc_id":"K251276","page_num":10,"bbox":[236.34,458.9,501.95,489.9],"n_rows":2,"n_cols":6,"columns":["0-2","2-18","18-35","35-60","60+","Unknown"],"rows":[["0-2","2-18","18-35","35-60","60+","Unknown"],["21%","15%","18%","23%","18%","5%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p10-t6","doc_id":"K251276","page_num":10,"bbox":[236.34,563.67,435.26,594.7],"n_rows":2,"n_cols":2,"columns":["Swoop Mk1.7","Swoop Mk1.9"],"rows":[["Swoop Mk1.7","Swoop Mk1.9"],["73%","27%"]],"caption_candidate":"Equipment:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p11-t0","doc_id":"K251276","page_num":11,"bbox":[72.27,347.6,540.48,647.95],"n_rows":4,"n_cols":2,"columns":["Patients","43"],"rows":[["Patients","43"],["Images","95"],["ROIs","316"],["Demographics\nand other\nVariability","Gender:\nFemale Male Unknown\n62% 17% 21%\nAge:\n0-2 2-18 18-35 35-60 60+ 2+* Unknown\n8% 31% 7% 10% 31% 9% 4%\n*partially anonymized\nEthnicity data not recorded.\nNumber of sites: 8\nEquipment type:\nSwoop Mk1.7 Swoop Mk1.8 Swoop Mk1.9\n36% 18% 46%\nIncluded pathology: stroke, white matter disease, hemorrhage, tumor, hydrocephalus,\ncerebral edema, hypoxic brain injury, Alzheimer’s, Treacher-Collins syndrome, seizures,\nmultiple sclerosis, post-surgical tumor resection, and thrombectomy follow-up"]],"caption_candidate":"criteria are described below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p11-t1","doc_id":"K251276","page_num":11,"bbox":[156.08,406.87,379.65,437.9],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["62%","17%","21%"]],"caption_candidate":"Demographics Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p11-t2","doc_id":"K251276","page_num":11,"bbox":[156.08,450.65,517.23,481.65],"n_rows":2,"n_cols":7,"columns":["0-2","2-18","18-35","35-60","60+","2+*","Unknown"],"rows":[["0-2","2-18","18-35","35-60","60+","2+*","Unknown"],["8%","31%","7%","10%","31%","9%","4%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p11-t3","doc_id":"K251276","page_num":11,"bbox":[156.08,567.67,379.65,598.7],"n_rows":2,"n_cols":3,"columns":["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],"rows":[["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],["36%","18%","46%"]],"caption_candidate":"Equipment type:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p12-t0","doc_id":"K251276","page_num":12,"bbox":[72.27,394.62,539.98,706.23],"n_rows":3,"n_cols":2,"columns":["Patients","46"],"rows":[["Patients","46"],["Images","177"],["Demographics\nand other\nVariability","Gender:\nFemale Male Unknown\n31% 23% 46%\nAge:\n0-2 2-18 18-35 35-60 60+ 2+*\n6% 11% 6% 17% 39% 21%\n*partially anonymized\nEthnicity data not recorded.\nNumber of sites: 11\nEquipment type:\nSwoop Mk1.7 Swoop Mk1.8 Swoop Mk1.9\n20% 10% 70%\nIncluded pathology: Alzheimer’s Disease, Cavernous malformation, Cerebral Amyloid\nAngiopathy, Cerebral Tuberculosis, Cortical dysplasia, Edema, Empyema Evacuation,\nEthmoidectomy, Hemorrhage, Hydrocephalus, Multiple Sclerosis, Subarachnoid\nHemorrhage, Subdural Hemorrhage, Seizure, Stroke, Subdural Empyema, Thrombosis,\nTreacher Collins Syndrome, Tumor, White Matter Hyperintensity"]],"caption_candidate":"each sequence-available image orientation (axial, sagittal, coronal) were used.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p12-t1","doc_id":"K251276","page_num":12,"bbox":[156.08,438.4,534.48,469.4],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["31%","23%","46%"]],"caption_candidate":"Demographics Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p12-t2","doc_id":"K251276","page_num":12,"bbox":[156.08,482.15,477.2,513.17],"n_rows":2,"n_cols":6,"columns":["0-2","2-18","18-35","35-60","60+","2+*"],"rows":[["0-2","2-18","18-35","35-60","60+","2+*"],["6%","11%","6%","17%","39%","21%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251276-p12-t3","doc_id":"K251276","page_num":12,"bbox":[156.08,601.45,534.48,632.45],"n_rows":2,"n_cols":3,"columns":["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],"rows":[["Swoop Mk1.7","Swoop Mk1.8","Swoop Mk1.9"],["20%","10%","70%"]],"caption_candidate":"Equipment type:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p5-t0","doc_id":"K251306","page_num":5,"bbox":[72.0,93.45,507.88,711.4],"n_rows":64,"n_cols":6,"columns":["1. General Informatio","n","","","",""],"rows":[["1. General Informatio","n","","","",""],["","","","","",""],["510(k) Sponsor","Ever Fortune.AI Co., Ltd.","","","",""],["","","","","",""],["Address","8F., No.360, Sec. 1, Jingmao R","d.,","","",""],["","Beitun Dist.,","","","",""],["","Taichung City 406040,","","","",""],["","Taiwan","","","",""],["","","","","",""],["Applicant","Joseph Chang","","","",""],["","","","","",""],["Contact Information","886-04-23213838 #216","","","",""],["","joseph.chang@everfortune.ai","","","",""],["","","","","",""],["Correspondence Person","Ti-Hao Wang","","","",""],["","","","","",""],["Contact Information","886-04-23213838 #168","","","",""],["","thothwang@gmail.com","","","",""],["","","","","",""],["","tihao.wang@everfortune.ai","","","",""],["","","","","",""],["Date Prepared","January 28, 2026","","","",""],["","","","","",""],["2. Proposed Device","","","","",""],["","","","","",""],["Proprietary Name","Seg Pro V3 (RT-300)","","","",""],["","","","","",""],["Common Name","Seg Pro V3","","","",""],["","","","","",""],["Classification Name","Radiological Image Processing","Software","For","Radiation","Therapy"],["","","","","",""],["Regulation Number","21 CFR 892.2050","","","",""],["","","","","",""],["Product Code","QKB","","","",""],["","","","","",""],["Regulatory Class","II","","","",""],["","","","","",""],["3. Predicate Device","","","","",""],["","","","","",""],["Proprietary Name","EFAI RTSUITE CT HCAP-Seg","mentation","Sy","stem",""],["","","","","",""],["Premarket Notification","K231928","","","",""],["","","","","",""],["Classification Name","Radiological Image Processing","Software","For","Radiation","Therapy"],["","","","","",""],["Regulation Number","21 CFR 892.2050","","","",""],["","","","","",""],["Product Code","QKB","","","",""],["","","","","",""],["Regulatory Class","II","","","",""],["","","","","",""],["4. Reference Device","","","","",""],["","","","","",""],["Proprietary Name","AutoContour RADAC V4","","","",""],["","","","","",""],["Premarket Notification","K242729","","","",""],["","","","","",""],["Classification Name","Radiological Image Processing","Software","For","Radiation","Therapy"],["","","","","",""],["Regulation Number","21 CFR 892.2050","","","",""],["","","","","",""],["Product Code","QKB","","","",""],["","","","","",""],["Regulatory Class","II","","","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251306-p5-t1","doc_id":"K251306","page_num":5,"bbox":[66.05,349.31,539.62,447.94],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Seg Pro V3 (RT-300)"],"rows":[["Proprietary Name","Seg Pro V3 (RT-300)"],["Common Name","Seg Pro V3"],["Classification Name","Radiological Image Processing Software For Radiation Therapy"],["Regulation Number","21 CFR 892.2050"],["Product Code","QKB"],["Regulatory Class","II"]],"caption_candidate":"2. Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p5-t2","doc_id":"K251306","page_num":5,"bbox":[66.05,481.14,539.62,580.14],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","EFAI RTSUITE CT HCAP-Segmentation System"],"rows":[["Proprietary Name","EFAI RTSUITE CT HCAP-Segmentation System"],["Premarket Notification","K231928"],["Classification Name","Radiological Image Processing Software For Radiation Therapy"],["Regulation Number","21 CFR 892.2050"],["Product Code","QKB"],["Regulatory Class","II"]],"caption_candidate":"3. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p5-t3","doc_id":"K251306","page_num":5,"bbox":[66.05,613.77,539.62,712.77],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","AutoContour RADAC V4"],"rows":[["Proprietary Name","AutoContour RADAC V4"],["Premarket Notification","K242729"],["Classification Name","Radiological Image Processing Software For Radiation Therapy"],["Regulation Number","21 CFR 892.2050"],["Product Code","QKB"],["Regulatory Class","II"]],"caption_candidate":"4. Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p7-t0","doc_id":"K251306","page_num":7,"bbox":[64.31,197.27,728.06,550.5],"n_rows":8,"n_cols":5,"columns":["Feature/\nFunction","Proposed Device","Predicate Device","Reference Device","Comparison"],"rows":[["Feature/\nFunction","Proposed Device","Predicate Device","Reference Device","Comparison"],["Company","Ever Fortune.AI Co., Ltd.\n(EFAI)","Ever Fortune.AI Co., Ltd.\n(EFAI)","Radformation, Inc.","N/A"],["Device Name","Seg Pro V3","EFAI HCAPSeg","AutoContour RADAC V4","N/A"],["510k Number","K251306","K231928","K242729","N/A"],["Regulation No.","21 CFR 892.2050","21 CFR 892.2050","21 CFR 892.2050","Identical"],["Classification","II","II","II","Identical"],["Product Code","QKB","QKB","QKB","Identical"],["Intended\nUse/Indication\nfor Use","Seg Pro V3 is a software\ndevice intended to assist\ntrained radiation oncology\nprofessionals, including, but\nnot limited to, radiation\noncologists, medical\nphysicists, and dosimetrists,\nduring their clinical\nworkflows of radiation\ntherapy treatment planning\nby providing initial contours\nof organs at risk on DICOM","EFAI HCAPSeg is a\nsoftware device intended to\nassist trained radiation\noncology professionals,\nincluding, but not limited to,\nradiation oncologists,\nmedical physicists, and\ndosimetrists, during their\nclinical workflows of\nradiation therapy treatment\nplanning by providing initial\ncontours of organs at risk on","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in\npreparation for radiation\ntherapy treatment planning.","The proposed and predicate\ndevices share the same\nintended use: assisting\ntrained radiation oncology\nprofessionals in generating\ninitial contours of organs at\nrisk (OARs) for radiation\ntherapy planning. While the\nproposed device supports\nboth CT and MR images and\nthe predicate device supports\nonly CT, this difference in"]],"caption_candidate":"in the following section.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p8-t0","doc_id":"K251306","page_num":8,"bbox":[64.5,90.0,728.25,554.25],"n_rows":3,"n_cols":5,"columns":["","images. Seg Pro V3 is\nintended to be used on adult\npatients only.\nThe contours are generated\nby deep-learning algorithms\nand then transferred to\nradiation therapy treatment\nplanning systems. Seg Pro\nV3 must be used in\nconjunction with a\nDICOM-compliant treatment\nplanning system to review\nand edit results generated.\nSeg Pro V3 is not intended to\nbe used for decision making\nor to detect lesions.\nSeg Pro V3 is an adjunct tool\nand is not intended to replace\na clinician's judgment and\nmanual contouring of the\nnormal organs on DICOM\nimages. Clinicians must not\nuse the software generated\noutput alone without review\nas the primary interpretation.","non-contrast CT images.\nEFAI HCAPSeg is intended\nto be used on adult patients\nonly.\nThe contours are generated\nby deep-learning algorithms\nand then transferred to\nradiation therapy treatment\nplanning systems. EFAI\nHCAPSeg must be used in\nconjunction with a\nDICOM-compliant treatment\nplanning system to review\nand edit results generated.\nEFAI HCAPSeg is not\nintended to be used for\ndecision making or to detect\nlesions.\nEFAI HCAPSeg is an\nadjunct tool and is not\nintended to replace a\nclinician's judgment and\nmanual contouring of the\nnormal organs on CT.\nClinicians must not use the\nsoftware generated output\nalone without review as the\nprimary interpretation.","","imaging modality does not\nalter the intended use or raise\nnew questions of safety or\neffectiveness. The reference\ndevice is not included in this\ncomparison, as it is not used\nto establish substantial\nequivalence in intended use."],"rows":[["","images. Seg Pro V3 is\nintended to be used on adult\npatients only.\nThe contours are generated\nby deep-learning algorithms\nand then transferred to\nradiation therapy treatment\nplanning systems. Seg Pro\nV3 must be used in\nconjunction with a\nDICOM-compliant treatment\nplanning system to review\nand edit results generated.\nSeg Pro V3 is not intended to\nbe used for decision making\nor to detect lesions.\nSeg Pro V3 is an adjunct tool\nand is not intended to replace\na clinician's judgment and\nmanual contouring of the\nnormal organs on DICOM\nimages. Clinicians must not\nuse the software generated\noutput alone without review\nas the primary interpretation.","non-contrast CT images.\nEFAI HCAPSeg is intended\nto be used on adult patients\nonly.\nThe contours are generated\nby deep-learning algorithms\nand then transferred to\nradiation therapy treatment\nplanning systems. EFAI\nHCAPSeg must be used in\nconjunction with a\nDICOM-compliant treatment\nplanning system to review\nand edit results generated.\nEFAI HCAPSeg is not\nintended to be used for\ndecision making or to detect\nlesions.\nEFAI HCAPSeg is an\nadjunct tool and is not\nintended to replace a\nclinician's judgment and\nmanual contouring of the\nnormal organs on CT.\nClinicians must not use the\nsoftware generated output\nalone without review as the\nprimary interpretation.","","imaging modality does not\nalter the intended use or raise\nnew questions of safety or\neffectiveness. The reference\ndevice is not included in this\ncomparison, as it is not used\nto establish substantial\nequivalence in intended use."],["Segmentation\n(Contouring)\nTechnology","Deep learning","Deep learning","Deep learning","Identical"],["Operating System","Linux Ubuntu 22.04.5 LTS","Linux Ubuntu 20.04","Windows based .NET\nfront-end application that\nalso serves as agent\nUploader supporting","The proposed and predicate\ndevices are Linux-based"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p9-t0","doc_id":"K251306","page_num":9,"bbox":[64.5,90.0,728.25,555.25],"n_rows":4,"n_cols":5,"columns":["","","","Microsoft Windows 10\n(64-bit) and Microsoft\nWindows Server 2016.\nCloud-based Server based\nautomatic contouring\napplication compatible with\nLinux.\nWindows python-based\nautomatic contouring\napplication supporting\nMicrosoft Windows 10\n(64-bit) and Microsoft\nWindows Server 2016.",""],"rows":[["","","","Microsoft Windows 10\n(64-bit) and Microsoft\nWindows Server 2016.\nCloud-based Server based\nautomatic contouring\napplication compatible with\nLinux.\nWindows python-based\nautomatic contouring\napplication supporting\nMicrosoft Windows 10\n(64-bit) and Microsoft\nWindows Server 2016.",""],["User population","Trained medical\nprofessionals including, but\nnot limited to, radiation\noncologists, medical\nphysicists, and dosimetrists.","Trained medical\nprofessionals including, but\nnot limited to, radiation\noncologists, medical\nphysicists, and dosimetrists.","Radiation treatment planners","All devices are intended for\nuse by trained radiation\ntherapy professionals. User\ngroups are functionally\nequivalent."],["Supported\nModalities","CT or MR","CT","CT or MR input for\ncontouring or\nregistration/fusion. PET/CT\ninput for registration/fusion\nonly. DICOM RTSTRUCT\nfor output","The proposed device\nsupports both CT and MR\nimages, while the predicate\ndevice supports only CT. The\nreference device also\nsupports CT and MR for\ncontouring and fusion. The\nproposed device aligns with\nthe performance of\ncommercially available\nproducts on the market,\nspecifically Reference\nDevices."],["","CT models include 166\norgans-at-risk (OARs) across","CT models include 80 OARs\nacross the head-and-neck,","CT or MR input for\ncontouring of anatomical","Both the proposed and\npredicate devices cover the"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p12-t0","doc_id":"K251306","page_num":12,"bbox":[72.37,190.12,541.12,729.37],"n_rows":28,"n_cols":7,"columns":["CT OAR","Size","Pass\nCriteria","Number\nof Cases","Mean\nDSC","SD of\nMean DSC","Lower\nBound 95%\nCI"],"rows":[["CT OAR","Size","Pass\nCriteria","Number\nof Cases","Mean\nDSC","SD of\nMean DSC","Lower\nBound 95%\nCI"],["Bone_Pelvic","Large","0.80","34","0.92","0.02","0.909"],["Bone_Pelvic_L","Large","0.80","34","0.91","0.02","0.898"],["Bone_Pelvic_R","Large","0.80","34","0.91","0.03","0.904"],["Bowel","Medium","0.65","34","0.89","0.02","0.881"],["Bowel_Large","Medium","0.65","34","0.87","0.04","0.860"],["Bowel_Small","Medium","0.65","34","0.85","0.03","0.841"],["Chestwall","Large","0.80","32","0.87","0.03","0.856"],["Chestwall_L","Large","0.80","32","0.86","0.03","0.851"],["Chestwall_R","Large","0.80","32","0.87","0.03","0.860"],["Clavicle_L","Medium","0.65","32","0.85","0.08","0.824"],["Clavicle_R","Medium","0.65","32","0.85","0.06","0.828"],["Femur_L","Large","0.80","34","0.91","0.04","0.898"],["Femur_R","Large","0.80","34","0.92","0.04","0.903"],["GI_Tract","Large","0.80","34","0.92","0.02","0.913"],["Glnd_Adrenal_L","Small","0.50","34","0.71","0.08","0.687"],["Glnd_Adrenal_R","Small","0.50","34","0.73","0.09","0.695"],["Gluteus","Large","0.80","34","0.91","0.02","0.907"],["Gluteus_Max_L","Medium","0.65","34","0.89","0.03","0.885"],["Gluteus_Max_R","Medium","0.65","34","0.90","0.03","0.893"],["Gluteus_Med_L","Medium","0.65","34","0.89","0.03","0.883"],["Gluteus_Med_R","Medium","0.65","34","0.90","0.02","0.889"],["Gluteus_Min_L","Medium","0.65","34","0.87","0.03","0.864"],["Gluteus_Min_R","Medium","0.65","34","0.88","0.03","0.867"],["Humerus_L","Large","0.80","32","0.90","0.18","0.833"],["Humerus_R","Large","0.80","32","0.92","0.08","0.893"],["Iliopsoas_L","Large","0.80","34","0.92","0.02","0.914"],["Iliopsoas_R","Large","0.80","34","0.93","0.02","0.923"]],"caption_candidate":"criteria) for each OAR, are shown in the following tables.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251306-p13-t0","doc_id":"K251306","page_num":13,"bbox":[72.37,89.62,541.12,730.12],"n_rows":35,"n_cols":7,"columns":["Lung_LLL","Medium","0.65","32","0.91","0.07","0.879"],"rows":[["Lung_LLL","Medium","0.65","32","0.91","0.07","0.879"],["Lung_LUL","Medium","0.65","32","0.90","0.03","0.893"],["Lung_RLL","Medium","0.65","32","0.92","0.02","0.911"],["Lung_RML","Medium","0.65","32","0.88","0.04","0.867"],["Lung_RUL","Medium","0.65","32","0.91","0.03","0.903"],["Lungs","Large","0.80","32","0.96","0.02","0.955"],["Rib01_L","Medium","0.65","32","0.87","0.09","0.841"],["Rib01_R","Medium","0.65","32","0.89","0.06","0.869"],["Rib02_L","Medium","0.65","32","0.88","0.08","0.848"],["Rib02_R","Medium","0.65","32","0.87","0.08","0.836"],["Rib03_L","Medium","0.65","32","0.89","0.06","0.866"],["Rib03_R","Medium","0.65","32","0.86","0.08","0.829"],["Rib04_L","Medium","0.65","32","0.86","0.08","0.835"],["Rib04_R","Medium","0.65","32","0.85","0.06","0.826"],["Rib05_L","Medium","0.65","32","0.87","0.06","0.845"],["Rib05_R","Medium","0.65","32","0.89","0.05","0.870"],["Rib06_L","Medium","0.65","32","0.87","0.05","0.856"],["Rib06_R","Medium","0.65","32","0.86","0.05","0.845"],["Rib07_L","Medium","0.65","32","0.86","0.05","0.840"],["Rib07_R","Medium","0.65","32","0.86","0.06","0.834"],["Rib08_L","Medium","0.65","32","0.86","0.05","0.840"],["Rib08_R","Medium","0.65","32","0.83","0.11","0.791"],["Rib09_L","Medium","0.65","32","0.86","0.05","0.846"],["Rib09_R","Medium","0.65","32","0.86","0.07","0.832"],["Rib10_L","Medium","0.65","32","0.87","0.05","0.848"],["Rib10_R","Medium","0.65","32","0.84","0.04","0.827"],["Rib11_L","Medium","0.65","32","0.84","0.06","0.817"],["Rib11_R","Medium","0.65","32","0.82","0.05","0.804"],["Rib12_L","Medium","0.65","32","0.85","0.07","0.831"],["Rib12_R","Medium","0.65","32","0.87","0.09","0.841"],["Ribs","Large","0.80","32","0.89","0.08","0.865"],["Ribs_L","Large","0.80","32","0.89","0.17","0.826"],["Ribs_R","Large","0.80","32","0.89","0.07","0.866"],["Sacrum","Large","0.80","34","0.91","0.03","0.896"],["Scapula_L","Medium","0.65","32","0.82","0.05","0.800"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K251351-p13-t1","doc_id":"K251351","page_num":13,"bbox":[50.13,400.8,545.16,627.24],"n_rows":13,"n_cols":8,"columns":["Organ&\nStructure","NO.","Size","PassCriteria","DSCMean","DSCSTD","LowerBound\n95%CI","Average\nRating(1-5)"],"rows":[["Organ&\nStructure","NO.","Size","PassCriteria","DSCMean","DSCSTD","LowerBound\n95%CI","Average\nRating(1-5)"],["Trachea","25","Medium","0.650","0.946","0.008","0.940","4.7"],["Esophagus","30","Medium","0.650","0.901","0.054","0.866","4.6"],["Lung_L","29","Large","0.800","0.975","0.012","0.966","4.7"],["Lung_R","30","Large","0.800","0.998","0.076","0.949","4.5"],["Lung_All","30","Large","0.800","0.993","0.060","0.954","4.8"],["Heart","30","Large","0.800","0.971","0.060","0.931","4.6"],["SpinalCord","30","Medium","0.650","0.964","0.067","0.920","4.6"],["Liver","30","Large","0.800","0.978","0.064","0.936","4.5"],["Stomach","30","Large","0.800","0.915","0.039","0.889","4.5"],["A_Aorta","30","Large","0.800","0.951","0.006","0.947","4.6"],["Spleen","30","Large","0.800","0.932","0.031","0.913","4.8"],["Body","30","Large","0.800","0.998","0.001","0.997","4.9"]],"caption_candidate":"Table3:TestResultsafterRigidRegistrationforEachROI","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251355-p7-t0","doc_id":"K251355","page_num":7,"bbox":[78.15,72.34,569.96,717.6],"n_rows":8,"n_cols":6,"columns":["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],"rows":[["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],["","","","","",""],["","","","Pie Medical","",""],["","","","CAAS Workstation","",""],["","","","(K180019)","",""],["Company","SpectraWAVE\n12 Oak Park Drive\nBedford, MA 01730, USA","Pie Medical Imaging BV\nPhilipsweg 1, 6227 AJ\nMaastricht, The Netherlands","","",""],["Intended\nUse","The SpectraWAVE X1-FFR\nSoftware is a software\nproduct intended to be used\nby or under the supervision of\na cardiologist in order to aid in\nreading, co-registering, and\ninterpreting cardiovascular X-\nray images to support in\ndiagnoses and for assistance\nduring the intervention of\ncardiovascular conditions.","CAAS Workstation is a\nmodular software product\nintended to be used by or\nunder supervision of a\ncardiologist or radiologist in\norder to aid in reading, co-\nregistering and interpreting\ncardiovascular X-Ray images\nto support diagnoses and for\nassistance during intervention\nof cardiovascular conditions.","","","Identical"],["Indications\nfor Use","The SpectraWAVE X1-FFR\nSoftware features\nsegmentation of coronary\nvessels, and measurement\nand reporting tools to facilitate\nthe following use:\n• Calculate the dimensions\nof coronary vessels;\n• Quantify stenosis in\ncoronary vessels;\n• Quantify pressure drop in\ncoronary vessels;\nThe SpectraWAVE X1-FFR\nSoftware is intended to be\nused by or under the\nsupervision of a cardiologist.","CAAS Workstation features\nsegmentation of\ncardiovascular structures, 3D\nreconstruction of vessel\nsegments and catheter path\nbased on multiple\nangiographic images,\nmeasurement and reporting\ntools to facilitate the following\nuse:\n• Calculate the dimensions\nof cardiovascular\nstructures;\n• Quantify stenosis in\ncoronary and peripheral\nvessels;\n• Quantify the motion of the\nleft and right ventricular\nwall;\n• Perform density\nmeasurements;\n• Determine C-arm position\nfor optimal imaging of\ncardiovascular structures;\n• Enhance stent\nvisualization and measure\nstent dimensions;","","","The subject\ndevice indications\nare identical to a\nsubset of the\nindications\ncleared for the\npredicate device.\nIndications for the\nsubject device\nfocus on the\nassessment of\ncoronary vessels."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251355-p8-t0","doc_id":"K251355","page_num":8,"bbox":[78.14,72.34,569.97,705.96],"n_rows":10,"n_cols":6,"columns":["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],"rows":[["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],["","","","","",""],["","","","Pie Medical","",""],["","","","CAAS Workstation","",""],["","","","(K180019)","",""],["","","• Quantify pressure drop in\ncoronary vessels;\n• Co-registration of\nangiographic X-Ray\nimages with IVUS and\nOCT images.\nCAAS Workstation is\nintended to be used by or\nunder supervision of a\ncardiologist or radiologist.","","",""],["Regulation\nNumber","21 CFR 892.1600","21 CFR 892.1600","","","Identical"],["FDA\nProduct\nCode","QHA, LLZ","QHA, LLZ","","","Identical"],["Data Input","X-ray angiography in Display\nformat (vendor independent)","X-ray angiography in DICOM\nformat (vendor independent);\n• IVUS and OCT data in\nDICOM format (vendor\nindependent);\n• IVUS data as video\nstream","","","The subject\ndevice data input\ntype is similar to a\nsubset of the data\ninputs cleared for\nthe predicate\ndevice.\nThe subject\ndevice uses X-\nRay angiography\nin display format\nand does not\naccept other\nimage types."],["Image\nDisplay","• 2D X-Ray Image","• 2D X-ray image;\n• 3D reconstruction based\non 2 Xray images;\n• 2D intravascular image;\n• Longitudinal intravascular\nreconstruction","","","The subject\ndevice’s image\ndisplay outputs\nare identical to a\nsubset of the\nimage display\noutputs cleared\nfor the predicate\ndevice."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251355-p9-t0","doc_id":"K251355","page_num":9,"bbox":[78.15,72.34,569.95,603.24],"n_rows":7,"n_cols":6,"columns":["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],"rows":[["","SUBJECT DEVICE\nSpectraWAVE\nX1-FFR","","PREDICATE DEVICE","","Comparison"],["","","","","",""],["","","","Pie Medical","",""],["","","","CAAS Workstation","",""],["","","","(K180019)","",""],["","","","","","The subject\ndevice displays\n2D X-Ray Images\nand does not\ndisplay 3D\nreconstruction or\nintravascular\nformats."],["Image\nAssessment","• Automatic calibration;\n• Vessel dimensions\n(diameters, lengths);\n• Automatic and manual\nstenosis assessment;\n• Pressure drop calculation\nin coronary vessel","• Manual and automatic\ncalibration;\n• Basic length, diameter,\ndensity and angle\nmeasurements;\n• Vessels and ventricle\ndimensions (diameters,\nareas, volumes);\n• Automatic and manual\nstenosis assessment;\n• Left and right ventricular\nwall motion;\n• Left ventricular\nmyocardium dimensions;\n• Enhanced stent\nvisualization;\n• Stent dimensions;\n• Pressure drop calculation\nin coronary vessels;\n• Providing common frame\nof reference for IVUS and\nOCT data with X-ray\nangiographic data","","","The subject\ndevice’s image\nassessment\ncapabilities are\nidentical to a\nsubset of the\nimage\nassessment\ncapabilities\ncleared for the\npredicate device.\nThe subject\ndevice’s image\nassessment\nfocuses on the\nanalysis of\ncoronary vessels."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p5-t0","doc_id":"K251368","page_num":5,"bbox":[72.34,160.34,539.86,390.53],"n_rows":4,"n_cols":4,"columns":["Owner","","","Diagnoly\n2 Place de Francfort\n69003 Lyon, France\n+33(0)4.78.76.85.75"],"rows":[["Owner","","","Diagnoly\n2 Place de Francfort\n69003 Lyon, France\n+33(0)4.78.76.85.75"],["Primary contact\nperson","","","Ivan Voznyuk\nChief Executive Officer\nDiagnoly\nPhone: +33(0)6.95.87.04.55\nEmail: qara@diagnoly.com"],["Secondary contact\nperson","","","Nima Akhlaghi\nAssociate Director, Digital Health Regulatory Affairs\nMCRA, LLC\nPhone: 202.742.3889\nEmail: nakhlaghi@mcra.com"],["","Date prepared","","2025-09-11"]],"caption_candidate":"1 510(k) owner","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p5-t1","doc_id":"K251368","page_num":5,"bbox":[72.34,436.11,539.86,570.38],"n_rows":4,"n_cols":4,"columns":["","Trade Name","","FETOLY"],"rows":[["","Trade Name","","FETOLY"],["Classification name","Classification name","","Accessory to Ultrasonic Pulsed Doppler Imaging System, 21 CFR 892.1550\nAccessory to Ultrasonic Pulsed Echo Imaging System, 21 CFR 892.1560\nMedical image management and processing system, 21 CFR 892.2050"],["","Class","","II"],["Product code","Product code","","IYN (Primary)\nIYO, QIH (secondary)"]],"caption_candidate":"2 Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p7-t0","doc_id":"K251368","page_num":7,"bbox":[72.46,177.56,567.52,717.97],"n_rows":55,"n_cols":3,"columns":["Heart views","Quality criteria within the views",""],"rows":[["Heart views","Quality criteria within the views",""],["","(A1) Sp","Spine"],["","(A2) lRb","Left rib"],["","(A3) rRb","Right rib"],["","(A4) Ao","Descending aorta"],["","(A5) VC","Inferior vena cava"],["(A) ABD","",""],["","(A6) St","Stomach"],["Abdomen view","",""],["(n = 8)","(A7) Uv","Umbilical vein"],["","(A8) aA","Anterior Abdomen"],["","(B1) Sp","Spine"],["","(B2) lRb","Left rib"],["","(B3) rRb","Right rib"],["","(B4) Ao","Descending aorta"],["","(B5) lPV","Left pulmonary vein"],["","(B6) rPV","Right pulmonary vein"],["","(B7) LA","Left atrium"],["(B) 4CH","(B8) RA","Right atrium"],["Four chamber view","(B9) FOF","Septum primum (Vieussens valve or Fo-ramen Ovale Flap)"],["(n = 19)","",""],["","(B10) FO","Open Foramen Ovale"],["","",""],["","(B11) MV","Mitral valve"],["","(B12) TV","Tricuspid valve"],["","(B13) bCr","Connection between crux and atrial septum (vestibular septum)"],["","(B14) Cr","Atrioventricular valve offset in crux"],["","(B15) tCr","Connection between interventricular septum and crux"],["","(B16) IVS","Interventricular septum"],["","(B17) LV","Left ventricle"],["","(B18) RV","Right ventricle"],["","(B19) Str","Sternum"],["","",""],["","(C1) LA","Left atrium"],["","",""],["","",""],["","(C2) aAo","Proximal ascending aorta"],["","",""],["","",""],["","(C3) SV","Semilunar valves"],["","",""],["","",""],["","(C4) LV","Left ventricle"],["","",""],["","",""],["","(C5) IVS","Interventricular septum"],["(C) LVOT","",""],["","",""],["Left Ventricular Outflow Tract view","",""],["","(C6) RV","Right ventricle"],["(n = 6)","",""],["","",""],["","(D1) dAo","Descending aorta"],["","(D2) Tr","Trachea / bronchi"],["","(D3) lPA","Left pulmonary artery"]],"caption_candidate":"Ultrasound in Obstetrics and Gynecology for the foetal heart screening of 2nd and 3rd trimesters of pregnancy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p8-t0","doc_id":"K251368","page_num":8,"bbox":[72.46,102.3,567.52,322.3],"n_rows":24,"n_cols":3,"columns":["","(D4) Du","Ductus arteriosus"],"rows":[["","(D4) Du","Ductus arteriosus"],["","(D5) rPA","Right pulmonary artery"],["","(D6) Or","Origin of pulmonary arteries"],["","(D7) S","Septum between pulmonary artery trunk and ascending aorta"],["","(D8) aAo","Ascending aorta"],["","(D9) SVC","Superior vena cava"],["(D) RVOT","",""],["","",""],["Right Ventricular Outflow Tract view","",""],["","(D10) PA","Pulmonary trunk"],["(n = 10)","",""],["","",""],["","(E1) Sp","Spine"],["","(E2) Tr","Trachea"],["","(E3) ES","Side space on the left of ductus / pulmonary artery"],["","(E4) DuA","Ductal arch connected to the descending aorta"],["","(E5) Du","Ductal arch not connected to the descending aorta"],["","(E6) aAo","Ascending aorta"],["(E) 3VX","(E7) aAr","Aortic arch"],["Three vessels view","",""],["","(E8) SVC","Superior vena cava"],["(n = 9)","",""],["","(E9) Th","Thymus / sternum"],["","",""]],"caption_candidate":"K251368 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p8-t1","doc_id":"K251368","page_num":8,"bbox":[72.46,473.29,539.0,709.36],"n_rows":18,"n_cols":3,"columns":["Brain views","Quality criteria within the views",""],"rows":[["Brain views","Quality criteria within the views",""],["","(F1) aFx","Anterior Falx"],["","(F2) CSP","Cavum Septum Pellucidum"],["","(F3) For","Fornix"],["","(F4) dAV","Distal Anterior Ventricle"],["","(F5) pAV","Proximal Anterior Ventricle"],["","(F6) AC","Ambient Cisterna"],["(F) TV","(F7) Atr","Atrium"],["Transventricular view","",""],["","(F8) CP","Choroid Plexus"],["(n = 15)","",""],["","(F9) POS","Parieto Occipital Sulcus"],["","",""],["","(F10) pFx","Posterior Falx"],["","(F11) dCS","Distal Coronal suture"],["","(F12) pCS","Proximal Coronal suture"],["","(F13) SF","Sylvian Fissure"],["","(F14) Sk","Skull"]],"caption_candidate":"Ultrasound in Obstetrics and Gynecology for the foetal brain screening of 2nd and 3rd trimesters of pregnancy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p9-t0","doc_id":"K251368","page_num":9,"bbox":[72.46,102.07,539.02,558.74],"n_rows":36,"n_cols":3,"columns":["","(F15) Sep","Thalami Separation"],"rows":[["","(F15) Sep","Thalami Separation"],["","(G1) dTh","Distal Thalamus"],["","(G2) pTh","Proximal Thalamus"],["","(G3) 4V","4th Ventricle"],["","(G4) Ver","Vermis"],["","(G5) dCH","Distal Cerebellar Hemisphere"],["","(G6) pCH","Proximal Cerebellar Hemisphere"],["(G) TC","",""],["Transcerebellar view","(G7) CB","Cerebellar Border"],["(n = 8)","(G8) CM","Cisterna Magma"],["","",""],["","(H1) aFx","Anterior Falx"],["","(H2) CSP","Cavum Septum Pellicidum"],["","(H3) dAV","Distal Anterior Ventricle"],["","(H4) pAV","Proximal Anterior Ventricle"],["","(H5) dTh","Distal Thalamus"],["","(H6) pTh","Proximal Thalamus"],["(H) TT","(H7) Sep","Thalami Separation"],["Transthalamic view","",""],["","(H8) 3V","3rd Ventricle"],["(n = 12)","",""],["","(H9) dCS","Distal Coronal Suture"],["","",""],["","(H10) pCS","Proximal Coronal Suture"],["","(H11) SF","Sylvian Fissure"],["","(H12) Sk","Skull"],["","(I1) NB","Nose Bone"],["","(I2) uVer","Upper Part of Vermis"],["","(I3) lVer","Lower Part of Vermis"],["","(I4) Fas","Fastigium"],["","(I5) rgCC","Rostrum & Genu Corpus Callosum"],["","(I6) bCC","Body Corpus Callosum"],["(I) SAG","",""],["Sagittal/profile view","(I7) sCC","Splenium Corpus Callosum"],["(n = 8)","(I8) CSP","Cavum Septum Pellicidum"],["","",""]],"caption_candidate":"K251368 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p11-t0","doc_id":"K251368","page_num":11,"bbox":[72.29,102.02,540.31,633.84],"n_rows":7,"n_cols":7,"columns":["Aspect","","Predicate device:\nFETOLY-HEART\nK241380","Reference device:\nVoluson Expert\n18/20/22 (FETAL HS\nFeature)\nK220358","Proposed device: FETOLY","Comparison between\nProposed and\nPredicate device",""],"rows":[["Aspect","","Predicate device:\nFETOLY-HEART\nK241380","Reference device:\nVoluson Expert\n18/20/22 (FETAL HS\nFeature)\nK220358","Proposed device: FETOLY","Comparison between\nProposed and\nPredicate device",""],["","General","","","","",""],["Manufacturer\nname","","Diagnoly","GE Healthcare","Diagnoly","NA",""],["Device name","","FETOLY-HEART","FETAL HS in the\nVoluson Expert\n18/20/22","FETOLY","NA",""],["Product\ncode(s)","","IYN (Primary)\nIYO, QIH (secondary)","IYN (Primary)\nIYO, ITX (Secondary)","IYN (Primary)\nIYO, QIH (secondary)","Substantially\nequivalent\nPrimary codes are\nthe same for subject\nand primary\npredicate devices",""],["Regulation\nnumber","","- Accessory to Ultrasonic\nPulsed Doppler Imaging\nSystem, 21 CFR 892.1550\n- Accessory to Ultrasonic\nPulsed Echo Imaging\nSystem, 21 CFR 892.1560\n- Medical image\nmanagement and\nprocessing system, 21\nCFR 892.2050","- Ultrasonic Pulsed\nDoppler Imaging\nSystem, 21 CFR\n892.1550\n- Ultrasonic Pulsed\nEcho Imaging\nSystem, 21 CFR\n892.1560\n- Diagnostic\nUltrasound\nTransducer, 21 CFR\n892.1570, 90-ITX","- Accessory to Ultrasonic\nPulsed Doppler Imaging\nSystem, 21 CFR 892.1550\n- Accessory to Ultrasonic\nPulsed Echo Imaging System,\n21 CFR 892.1560\n- Medical image management\nand processing system, 21\nCFR 892.2050","Substantially\nequivalent\nAll devices are class II\ndevices subject to\n510(k) regulatory\npathway.",""],["Brief\ndescription","","FETOLY-HEART is a\nsoftware that aims at\nhelping sonographers,\nOB/GYNs, MFMs and\nFetal surgeons (all three\ndesignated as healthcare\nprofessionals i.e. HCPs)\nto perform their routine\nfetal heart ultrasound\nexaminations in real-\ntime.","The reference device\nis a software that\naims at helping\nsonographers,\nOB/GYNs, MFMs and\nFetal surgeons (all\nthree designated as\nhealthcare\nprofessionals i.e.\nHCP) to perform\ntheir routine fetal\nheart ultrasound\nexaminations in real-\ntime.","FETOLY is a software that\naims at helping sonographers,\nOB/GYNs, MFMs and Fetal\nsurgeons (all three\ndesignated as healthcare\nprofessionals i.e. HCPs) to\nperform their routine fetal\nheart ultrasound\nexaminations in real-time.","Substantially\nequivalent\nThe subject device\nand the predicate\ndevices have the\nsame objective.",""]],"caption_candidate":"K251368 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p12-t0","doc_id":"K251368","page_num":12,"bbox":[72.26,473.47,540.34,715.08],"n_rows":2,"n_cols":5,"columns":["Targeted\npopulation","Pregnant women during\nthe 2nd and 3rd\ntrimester of pregnancy","Pregnant women\nduring the 2nd and\n3rd trimester of\npregnancy","Pregnant women during the\n2nd and 3rd trimester of\npregnancy","Substantially\nequivalent\nSubject device has\nthe same intended\npatient population\nthan the predicate\ndevices."],"rows":[["Targeted\npopulation","Pregnant women during\nthe 2nd and 3rd\ntrimester of pregnancy","Pregnant women\nduring the 2nd and\n3rd trimester of\npregnancy","Pregnant women during the\n2nd and 3rd trimester of\npregnancy","Substantially\nequivalent\nSubject device has\nthe same intended\npatient population\nthan the predicate\ndevices."],["Clinical\noutcome","- Images labeled with\ncorrect fetal heart view\nfor patient cases\n- Quality criteria\nidentified as “Verified”\nwhen detected and “Not\nverified” when not\ndetected\n- Images labeled with the\nlocalization of quality\ncriteria","- Images labeled with\nmeasurements and\nin- and out- of-range\ndisplay","- Images labeled with correct\nfetal heart/brain view for\npatient cases\n- Quality criteria identified as\n“Verified” when detected and\n“Not verified” when not\ndetected\n- Images labeled with the\nlocalization of quality criteria\n- Images labeled with\nmeasurements and in- and\nout- of-range display","Substantially\nequivalent\nThe clinical outcome\nis the same between\npredicates and\nsubject devices.\nHowever,\nperformance testing\nhas shown that there\nis no impact on safety\nand effectiveness of\nthe inclusion in\nFETOLY of additional"]],"caption_candidate":"40 weeks).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p13-t0","doc_id":"K251368","page_num":13,"bbox":[72.28,182.92,540.32,648.48],"n_rows":5,"n_cols":7,"columns":["Intended user","","Qualified healthcare\nprofessional specialized\nin prenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional specialized in\nprenatal ultrasound imaging","Substantially\nequivalent\nSubject device has\nthe same intended\nusers as the\npredicate devices.",""],"rows":[["Intended user","","Qualified healthcare\nprofessional specialized\nin prenatal ultrasound\nimaging","Qualified healthcare\nprofessional\nspecialized in\nprenatal ultrasound\nimaging","Qualified healthcare\nprofessional specialized in\nprenatal ultrasound imaging","Substantially\nequivalent\nSubject device has\nthe same intended\nusers as the\npredicate devices.",""],["Clinical\napplications","","Fetal/Obstetrics","Fetal/Obstetrics","Fetal/Obstetrics","Substantially\nequivalent\nClinical application is\nthe same for subject\nand predicate\ndevices.",""],["Inclusion of a\nPCCP","","Yes, proposed\nmodifications related to\nmodifying model training\nhyperparameters,\nadditional retraining with\nnew training and\nvalidation datasets\ncollected, and\naddition/removal of\nheart quality criteria.","N/A","Yes, proposed modifications\nrelated to modifying model\ntraining hyperparameters,\nadditional retraining with\nnew training and validation\ndatasets collected,\naddition/removal of heart\nquality criteria, addition of\nfetal heart and brain\nbiometric measurements","Substantially\nequivalent\nSubject and predicate\ndevices both have a\nPCCP to update AI\nmodel",""],["","Functionality 1: completeness overview","","","","",""],["Automatically\ndetect views","","Detection of 4ch, 3vx,\nLVOT, RVOT and Abd\nviews (complete\nimplementation of\nISUOG\nrecommendations)","N/A","Detection of 4ch, 3vx, LVOT,\nRVOT and Abd heart views\nDetection of TV, TT, TC and\nSAG brain views\n(complete implementation of\nISUOG recommendations)","Substantially\nequivalent\nThe subject device\nincludes the\ndetection of new\nviews when\ncompared to the\npredicate device. This\nquantitative\nenhancement has\nbeen tested and does\nnot raise any new\nquestion of safety\nand effectiveness.",""]],"caption_candidate":"completeness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p14-t0","doc_id":"K251368","page_num":14,"bbox":[72.31,260.91,540.29,590.71],"n_rows":5,"n_cols":7,"columns":["","Functionality 2: completeness illustration","","","","",""],"rows":[["","Functionality 2: completeness illustration","","","","",""],["Automatically\nselects views","","Automatic extraction of\nviews from a sequence of\nimages.","N/A","Automatic extraction of views\nfrom a sequence of images.","Substantially\nequivalent\nThis image selection\nfunctionality is the\nsame than for the\npredicate device\nSoftware testing has\nbeen performed to\nvalidate its use and\ndoes not introduce\nnew questions of\nsafety and\neffectiveness.",""],["","Functionality 3: Measurement","","","","",""],["Automatically\nmeasure fetal\nanatomy","","N/A","Heart angle\nmeasurement","Heart and brain biometric\nmeasurements, including\nangles and ratios","Substantially\nequivalent\nPerformance testing\nhas shown that there\nis no impact on safety\nand effectiveness of\nthe inclusion in\nFETOLY of additional\ntypes of\nmeasurements in\ncomparison with the\nreference device.",""],["","Functionality 4: Measurement illustration","","","","",""]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p15-t0","doc_id":"K251368","page_num":15,"bbox":[72.28,232.56,540.32,704.14],"n_rows":6,"n_cols":7,"columns":["","Technical characteristics","","","","",""],"rows":[["","Technical characteristics","","","","",""],["Data input","","Accepts images and\nimage sequences from\nultrasound machines","Accepts images and\nimage sequences\nfrom ultrasound\nmachines","Accepts images and image\nsequences from ultrasound\nmachines","Substantially\nequivalent\nThe input data is the\nsame for the subject\ndevice and the\npredicate and\nreference devices.",""],["Algorithm\nMethodology","","Artificial Intelligence:\nUtilizes computer vision\nalgorithms to analyze\nultrasound images and\nprovides visualization of\ndetected landmarks and\nviews","Artificial Intelligence:\nUtilizes computer\nvision algorithms to\nanalyze ultrasound\nimages and provides\nmeasurements","Artificial Intelligence: Utilizes\ncomputer vision algorithms to\nanalyze ultrasound images\nand provides measurements","Substantially\nequivalent\nAll devices use\nartificial intelligence.",""],["Platform","","Operates as a local\nsoftware functioning\nindependently from the\nultrasound equipment.","Operates as a local\nsoftware embedded\nin the ultrasound\nequipment.","Operates as a local software\nfunctioning independently\nfrom the ultrasound\nequipment.","Substantially\nequivalent\nSubject and primary\npredicate devices use\nan edge-based\napproach",""],["Ultrasound\nMachine\ncompatibility","","Compatible with\nultrasound system from\nGE Medical, Samsung\nand Canon","NA","Compatible with ultrasound\nsystem from GE Medical,\nSamsung and Canon","Substantially\nequivalent\nThis compatibility has\nbeen tested and\nvalidated as part of\ndevice\ngeneralizability in the\nperformance testing\nstudy.",""],["User\ninteraction","","The user can interact\nwith the software to\noverride the software’s\noutputs. The user has the\nability to review and\nedit/override the\nmatching at any time\nduring or at the end of\nthe exam.","The user has the\nability to review the\nsoftware output.","The user can interact with the\nsoftware to override the\nsoftware’s outputs. The user\nhas the ability to review and\nedit/override the matching at\nany time during or at the end\nof the exam.","Substantially\nequivalent\nUser interactions are\nthe same between\nprimary predicate\nand subject devices.",""]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p16-t0","doc_id":"K251368","page_num":16,"bbox":[72.53,603.1,540.07,719.5],"n_rows":3,"n_cols":4,"columns":["Modification","Rationale","Testing Methods","Impact Assessment"],"rows":[["Modification","Rationale","Testing Methods","Impact Assessment"],["","","",""],["Modification of\ntraining and/or\nvalidation datasets","Increase or recovery (in\ncase of data drift) of\nFETOLY’s performance.","Re-training of the FETOLY\nmodel with new data to\noptimize its performance\nfollowed by internal testing\nand a comparison of the initial\nmodel to the modified model\nusing performance metrics on\nthe test dataset.","Increased performance metrics of the\nmodified model for view or quality criteria\nor subview detection.\nIncreased performance metrics of the\nmodified model for realization of\nquantitative biometric measurements."]],"caption_candidate":"Summary of changes to FETOLY per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p17-t0","doc_id":"K251368","page_num":17,"bbox":[72.26,230.9,540.34,695.38],"n_rows":2,"n_cols":4,"columns":["Modification of\nmodel training\nhyperparameters","Improvement/\noptimization,\nmaintenance or recovery\n(in case of data drift) of\nFETOLY’s performance\nMaintain alignment with\nquality criteria and\nbiometric measurements\nrecommended for fetal\nheart and brain screening\nin state-of-the-art\ninternational guidelines.","Re-training of the FETOLY\nmodel with new parameters\nto optimize its performance\nfollowed by internal testing\nand a comparison of the initial\nmodel to the modified model\nusing performance metrics on\nthe test dataset.","Increased performance metrics of the\nmodified model for view or quality criteria\nor subview detection.\nIncreased performance metrics of the\nmodified model for realization of\nquantitative biometric measurements.\nEnhanced compliance with standard\ninternational guidelines.\nBenefits: Increased , maintained or\nrecovered performance; generalization for\ndiverse cases; keeping the device relevant\nby aligning with the updated list of heart\nand brain quality criteria/measurements\nRisks: Performance decrease (overfitting,\nunintended bias).\nRisk mitigation: The modified model will\nbe tested for superiority on the\nperformance study test dataset which will\ncontain new unseen data."],"rows":[["Modification of\nmodel training\nhyperparameters","Improvement/\noptimization,\nmaintenance or recovery\n(in case of data drift) of\nFETOLY’s performance\nMaintain alignment with\nquality criteria and\nbiometric measurements\nrecommended for fetal\nheart and brain screening\nin state-of-the-art\ninternational guidelines.","Re-training of the FETOLY\nmodel with new parameters\nto optimize its performance\nfollowed by internal testing\nand a comparison of the initial\nmodel to the modified model\nusing performance metrics on\nthe test dataset.","Increased performance metrics of the\nmodified model for view or quality criteria\nor subview detection.\nIncreased performance metrics of the\nmodified model for realization of\nquantitative biometric measurements.\nEnhanced compliance with standard\ninternational guidelines.\nBenefits: Increased , maintained or\nrecovered performance; generalization for\ndiverse cases; keeping the device relevant\nby aligning with the updated list of heart\nand brain quality criteria/measurements\nRisks: Performance decrease (overfitting,\nunintended bias).\nRisk mitigation: The modified model will\nbe tested for superiority on the\nperformance study test dataset which will\ncontain new unseen data."],["Heart or brain quality\ncriteria\naddition/removal","Maintain alignment with\nquality criteria\nrecommended for fetal\nheart and brain screening\nin state-of-the-art\ninternational guidelines.","New quality criteria list will be\ncontrolled using the same\nacceptance criteria as defined\nby secondary endpoints.","Enhanced compliance with standard\ninternational guidelines.\nBenefits: Keeping the device relevant by\naligning with the updated list of heart and\nbrain quality criteria.\nRisks: Performance decrease and user\nconfusion.\nRisk mitigation: Proper performance\ntesting with no decrease in test\nperformance. This change only pertains to\nquality criteria belonging to one of the 5\nheart views or 4 brain views already\nincluded in FETOLY."]],"caption_candidate":"contain new unseen data.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p19-t0","doc_id":"K251368","page_num":19,"bbox":[72.59,278.43,497.24,706.7],"n_rows":40,"n_cols":4,"columns":["","","Number of cases","Number of images"],"rows":[["","","Number of cases","Number of images"],["Subgroup","","",""],["","","(total=750)","(total=5,554)"],["","","",""],["","Center 1 (EU)","139 (18.5%)","1162 (20.9%)"],["","Center 2 (EU)","79 (10.6%)","500 (9%)"],["","Center 3 (EU)","96 (12.8%)","739 (13.3%)"],["Center","Center 4 (US)","141 (18.8%)","1008 (18.1%)"],["","Center 5 (US)","118 (15.7%)","728 (13.1%)"],["","Center 6 (US)","102 (13.6%)","800 (14.4%)"],["","Center 7 (US)","75 (10%)","617 (11.2%)"],["","US","436 (58.1%)","3153 (56.8%)"],["Territory","","",""],["","EU","314 (41.9%)","2401 (43.2%)"],["","","",""],["","2nd trimester","392 (52.3%)","3107 (55.9%)"],["Gestational age","","",""],["","3rd trimester","358 (47.7%)","2447 (44.1%)"],["","","",""],["","< 20 years","42 (5.6%)","300 (5.4%)"],["","[20-29] years","299 (39.9%)","2135 (38.4%)"],["Maternal age","[30-39] years","324 (43.2%)","2434 (43.8%)"],["","≥40 years","41 (5.5%)","317 (5.8%)"],["","Unknown","44 (5.8%)","368 (6.6%)"],["","<18.5 kg/m2","26 (3.5%)","204 (3.7%)"],["","[18.5;24.9] kg/m2","216 (28.8%)","1617 (29.1%)"],["BMI","[25;29.9] kg/m2","183 (24.4%)","1346 (24.2%)"],["","≥30 kg/m2","240 (32%)","1669 (30.1%)"],["","Unknown","85 (11.3%)","718 (12.9%)"],["","General Electric","373 (49.7%)","2999 (54%)"],["Scanner manufacturer","Samsung","342 (45.6%)","2267 (40.1%)"],["","Canon","35 (4.7%)","288 (5.9%)"],["","Abnormal","180 (24%)","1442 (26%)"],["Fetus cardiac/cerebral normality","","",""],["","Normal","570 (76%)","4112 (74%)"],["","","",""],["","Bad","N/A","1316 (23.7%)"],["Image digital quality","Average","N/A","1446 (26%)"],["","Good","N/A","2792 (50.3%)"],["Image type","Long video","N/A","262 (4.7%)"]],"caption_candidate":"The subgroups distribution is summarized in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p20-t0","doc_id":"K251368","page_num":20,"bbox":[72.57,102.36,497.26,196.35],"n_rows":7,"n_cols":4,"columns":["","Short video","N/A","1499 (27%)"],"rows":[["","Short video","N/A","1499 (27%)"],["","Full exam still image","N/A","3793 (68.3%)"],["","Asian and Pacific Islander","30 (4%)","196 (3.5%)"],["","Black","207 (27.6%)","1522 (27.4%)"],["Race and ethnicity","Hispanic","57 (7.6%)","411 (7.4%)"],["","White","415 (55.3%)","3089 (55.6%)"],["","Unknown","41 (5.5%)","336 (6.1%)"]],"caption_candidate":"K251368 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p21-t0","doc_id":"K251368","page_num":21,"bbox":[177.46,305.96,434.58,423.81],"n_rows":9,"n_cols":6,"columns":["","Class","","","LOA (LOA CI)",""],"rows":[["","Class","","","LOA (LOA CI)",""],["","thymic-thoracic_ratio","","0.044 (0.038,0.051)","",""],["","cardiothoracic_ratio","","0.036 (0.031,0.043)","",""],["","vessels_ratio","","0.095 (0.078,0.119)","",""],["","cephalic_index","","0.03 (0.028,0.034)","",""],["","vessels_number","","0.223 (0.113,0.324)","",""],["","cardiothoracic_position","","0.048 (0.043,0.053)","",""],["","right-left_ventricular_ratio","","0.101 (0.093,0.110)","",""],["","cardiac_angle","","6.476 (5.557,7.494)","",""]],"caption_candidate":"- Realization of fetal heart and brain biometric measurements:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p21-t1","doc_id":"K251368","page_num":21,"bbox":[72.6,588.2,540.52,706.34],"n_rows":13,"n_cols":4,"columns":["","","Number of cases","Number of images"],"rows":[["","","Number of cases","Number of images"],["Subgroup","","",""],["","","(total=441)","(total=6,024)"],["","","",""],["","Center 1 (EU)","67 (15.2%)","966 (16%)"],["","Center 2 (EU)","50 (11.3%)","560 (9.4%)"],["","Center 3 (EU)","99 (22.4%)","1515 (25.1%)"],["Center","","",""],["","Center 4 (US)","53 (12%)","753 (12.5%)"],["","","",""],["","Center 5 (US)","51 (11.7%)","571 (9.5%)"],["","Center 6 (US)","121 (27.4%)","1659 (27.5%)"],["Territory","US","225 (51%)","2983 (49.5%)"]],"caption_candidate":"model’s robustness and generalizability. The subgroups distribution is summarized in the table below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251368-p22-t0","doc_id":"K251368","page_num":22,"bbox":[72.59,102.36,540.58,520.16],"n_rows":37,"n_cols":4,"columns":["","EU","216 (49%)","3041 (50.5%)"],"rows":[["","EU","216 (49%)","3041 (50.5%)"],["","2nd trimester","280 (63.5%)","3848 (63.9%)"],["Gestational age","","",""],["","3rd trimester","161 (36.5%)","2176 (36.1%)"],["","","",""],["","< 20 years","20 (4.5%)","266 (4.4%)"],["","[20-29] years","181 (41%)","2436 (40.4%)"],["Maternal age","","",""],["","[30-39] years","212 (48.1%)","2951 (49%)"],["","","",""],["","≥40 years","28 (6.4%)","371 (6.2%)"],["","<18.5 kg/m2","20 (4.5%)","279 (4.6%)"],["","[18.5;24.9] kg/m2","133 (30.2%)","1866 (31%)"],["BMI","[25;29.9] kg/m2","129 (29.3%)","1731 (28.7%)"],["","≥30 kg/m2","143 (32.4%)","1926 (32%)"],["","Unknown","16 (3.6%)","222 (3.7%)"],["","General Electric","235 (53.3%)","3383 (56.1%)"],["Scanner manufacturer","Samsung","156 (35.4%)","1925 (32%)"],["","Canon","50 (11.3%)","716 (11.9%)"],["","In-range","343 (77.8%)","4710 (78.2%)"],["Reference range adherence","","",""],["","Out-of-range","98 (22.2%)","1314 (21.8%)"],["","","",""],["","High-risk","150 (34%)","2009 (33.3%)"],["Pregnancy type","No high-risk","279 (63.3%)","3835 (63.7%)"],["","Unknown","12 (2.7%)","180 (3%)"],["","Bad","N/A","1324 (22%)"],["Image digital quality","Average","N/A","2847 (47.3%)"],["","Good","N/A","1853 (30.7%)"],["","Full exam video frame","N/A","390 (6.5%)"],["Image type","Clip frame","N/A","2290 (38%)"],["","Full exam still image","N/A","3344 (55.5%)"],["","Asian and Pacific Islander","20 (4.5%)","251 (4.2%)"],["","Black","118 (26.8%)","1611 (26.7%)"],["Race and ethnicity","Hispanic","33 (7.5%)","445 (7.4%)"],["","White","267 (60.6%)","3672 (61%)"],["","Unknown","3 (0.6%)","45 (0.7%)"]],"caption_candidate":"K251368 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251370-p6-t0","doc_id":"K251370","page_num":6,"bbox":[108.0,215.22,573.84,306.42],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],["Cartesion Prime\n(PCD-1000A/3)\nV10.15","Canon Medical\nSystems USA","21 CFR\n892.1200","Emission\nComputed\nTomography\nSystem","KPS","K231748","September\n12, 2023"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251370-p8-t0","doc_id":"K251370","page_num":8,"bbox":[107.16,108.09,530.05,246.3],"n_rows":6,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","Device Name,","","","Cartesion Prime","","","Cartesion Prime",""],["","Model Number","","","(PCD-1000A/3) V10.21","","","(PCD-1000A/3) V10.15",""],["","510(k) Number","","","This submission","","","K231748",""],["Deviceless PET\nRespiratory gating\nsystem","","","Mode Setting:\nAI","","","Mode Setting:\nNormal","",""],["AiCE-i for PET","","","Pediatric Imaging: Available\nIntensity Settings:\nSmooth, Standard, Sharp","","","Pediatric Imaging: Not Available\nIntensity Settings:\nON/OFF","",""]],"caption_candidate":"included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p8-t0","doc_id":"K251386","page_num":8,"bbox":[175.72,206.9,575.53,447.31],"n_rows":20,"n_cols":8,"columns":["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],"rows":[["","","PREDICATE DEVICE","SUBJECT DEVICE","","","",""],["","","ECHELON Synergy MRI System\n(K241429)","ECHELON Synergy","","","",""],["Standards Met","","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5, MS\n8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","NEMA: MS 1, MS 2, MS 3, MS 4, MS 5,\nMS 8, MS 14,\nIEC: 60601-1, 60601-1-2, 60601-2-33,\n62304","","","",""],["Type and Field\nStrength","","Super-conducting magnet, horizontal bore,\n1.5 Tesla","Super-conducting magnet, horizontal\nbore, 1.5 Tesla","","","",""],["Resonant Frequency","","63.86MHz","63.86MHz","","","",""],["Bore dimension","","Circle shape with diameter 70cm","Circle shape with diameter 70cm","","","",""],["Gradient Strength","","33mT/m","33mT/m","","","",""],["Slew Rate","","130 T/m/sec","130 T/m/sec","","","",""],["Rise Time","","254μsec to 33mT/m","254μsec to 33mT/m","","","",""],["","","","","","","",""],["Audible Noise (MCAN)","","","","","","",""],["Ambient","","59.9 dBA","59.9 dBA","","","",""],["Lpeak","","122.7 dBA","122.7 dBA","","","",""],["Leq","","116.5 dBA","116.5 dBA","","","",""],["Transmitter channels","","1","1","","","",""],["Peak Envelop Power","","18 kW","18 kW","","","",""],["Duty Cycle","","85% (Gating max), 10% at full power","85% (Gating max), 10% at full power","","","",""],["RF receiver channel","","32","32","","","",""],["","","Internal Type Name: EM-7","Internal Type Name: EM-7 or EM-7A","","","",""],["","","Fixed table","Fixed table or Dockable table","","","",""]],"caption_candidate":"Table 2 Comparison: Hardware","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p8-t1","doc_id":"K251386","page_num":8,"bbox":[175.72,609.7,445.63,645.46],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"These devices have changed but there are no significant changes in technology, engineering and performance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p9-t0","doc_id":"K251386","page_num":9,"bbox":[168.02,113.78,498.7,316.3],"n_rows":13,"n_cols":3,"columns":["","PREDICATE DEVICE","SUBJECT DEVICE"],"rows":[["","PREDICATE DEVICE","SUBJECT DEVICE"],["","ECHELON Synergy MRI System (K241429)","ECHELON Synergy"],["Transmit Coil","T/R Body","T/R Body"],["Receiver Coils","FlexFit Neuro Coil","FlexFit Neuro Coil"],["","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B","FlexFit Blanket Coil A,\nFlexFit Blanket Coil B"],["","Extremity Coil","Extremity Coil"],["","Hand/Wrist Coil","Hand/Wrist Coil"],["","Breast Coil\nBreast Support Kit 2\nBreast Coil 17\nBreast Support Holder","Breast Coil\nBreast Support Kit 2\nBreast Coil 17\nBreast Support Holder"],["","Micro Coil A,\nMicro Coil B","Micro Coil A,\nMicro Coil B"],["","Shoulder Coil","Shoulder Coil"],["","Spine Coil","Spine Coil,\nSpine Coil B"],["","Foot/Ankle Coil","Foot/Ankle Coil"],["","Flex M Coil, Flex S Coil","Flex M Coil, Flex S Coil"]],"caption_candidate":"Table 4 Comparison: RF Coils","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p9-t1","doc_id":"K251386","page_num":9,"bbox":[174.98,459.55,445.63,495.31],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p10-t0","doc_id":"K251386","page_num":10,"bbox":[107.93,114.06,575.99,512.1],"n_rows":34,"n_cols":9,"columns":["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],"rows":[["","ITEM","","","DIFFERENCES","","","ANALYSIS",""],["","Operating System","","","None","","","No",""],["","CPU Platform","","","None","","","No",""],["","Application Software","","","Going from V10.0A from V11.0A","","","See Table 7",""],["Scan Tasks","Scan Tasks","","","Following positioning applications are added.","","See Table 7","See Table 7",""],["","","","","- AutoPose Abdomen, AutoPose Pelvis for male, AutoPose Pelvis for female, AutoPose Cardiac","","","",""],["","","","","Following positioning applications are modified.","","","",""],["","","","","- AutoPose Knee, AutoPose Shoulder, AutoPose HipJoint","","","",""],["","2D Processing Tasks","","","None","","","No",""],["3D Processing Tasks","3D Processing Tasks","","","Following function is modified.","","See Table 7","See Table 7",""],["","","","","- Multiplanar Reformatting (MPR)","","","",""],["","Analysis Tasks","","","None","","","No",""],["","Maintenance Tasks","","","None","","","No",""],["","Viewport Tools","","","None","","","No",""],["","Film, Archive Tools","","","None","","","No",""],["Network Tools","Network Tools","","","Following function is modified.","","See Table 7","See Table 7",""],["","","","","-AutoProtocol","","","",""],["Protocol Enhancements","","","","Following Protocol Enhancements are modified.","","See Table 7","",""],["","","","","- Gating: cardiac, peripheral pulse (with multi-gate delay parameter and SSFP capability),","","","",""],["","","","","Respiratory Gating","","","",""],["","","","","- Echo Planar, Diffusion Weighted Imaging","","","",""],["","","","","- Beam Navi","","","",""],["","","","","- Enhanced PC (improvement of Cine PC)","","","",""],["","","","","- AutoExam","","","",""],["","","","","- Navigated StillShot, Visual StillShot","","","",""],["","","","","- IQ Retouch","","","",""],["","","","","Following Protocol Enhancements are enhanced.","","","",""],["","","","","- k-RAPID","","","",""],["","","","","- IP-Scan","","","",""],["Pulse Sequences","","","","Following changes are added in Pulse Sequences.","","","",""],["","","","","- 2D GE, 2D RSSG, 3D RSSG, 2D GE EPI, 2D DW EPI, 2D Soft GE","","","",""],["","","","","“DLR Symmetry” is added.","","","",""],["Monitoring Tools","","","","Following function is modified.","","","",""],["","","","","- Synergy Vision","","","",""]],"caption_candidate":"Table 6 Comparison: Functionality","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p11-t0","doc_id":"K251386","page_num":11,"bbox":[174.98,216.02,445.63,251.93],"n_rows":2,"n_cols":3,"columns":["☐ Manufacturing Process","☐ Labeling","☐ Technology"],"rows":[["☐ Manufacturing Process","☐ Labeling","☐ Technology"],["☐ Engineering","☐ Materials","☐ Others"]],"caption_candidate":"- Synergy Vision","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251386-p14-t0","doc_id":"K251386","page_num":14,"bbox":[108.18,394.01,575.73,502.63],"n_rows":6,"n_cols":14,"columns":["","","","Shoulder","Knee","HipJoint","Abdomen","","Pelvis for","","","Pelvis for","","Cardiac"],"rows":[["","","","Shoulder","Knee","HipJoint","Abdomen","","Pelvis for","","","Pelvis for","","Cardiac"],["","","","","","","","","male","","","female","",""],["","Number of cases","","60","60","65","115","60","","","68","","","126"],["Data acquisition\nsite","Data acquisition","","FUJIFILM Corp.,\nFUJIFILM Healthcare\nAmericas Corp., clinical\nsites","","FUJIFILM\nCorp.,\nclinical site","FUJIFILM Corp., FUJIFILM Healthcare Americas\nCorp., clinical site","","","","","","",""],["","site","","","","","","","","","","","",""],["","Subject Type","","Healthy volunteer and patients","","","","","","","","","",""]],"caption_candidate":"The information on the data in the single evaluations is shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251397-p7-t0","doc_id":"K251397","page_num":7,"bbox":[72.27,572.58,539.73,714.06],"n_rows":5,"n_cols":5,"columns":["","Recognition","","Standard Number and Date","Standard Name"],"rows":[["","Recognition","","Standard Number and Date","Standard Name"],["","Number","","",""],["12-295","","","IEC60601-2-33 Ed. 3.2:2010 +\nAmd 1:2013 + Amd 2:2015","Medical electrical equipment - Part 2-33: Particular\nrequirements for the basic safety and essential\nperformance of magnetic resonance equipment for\nmedical diagnosis"],["-","","","ANSI / AAMI ES60601-\n1:2005/(R)2012 and A1:2012","Medical Electrical Equipment - Part 1: General\nRequirements For Basic Safety And Essential\nPerformance (IEC 60601-1:2006, MOD)."],["19-36","","","IEC 60601-1-2:2014 [Including\nAMD 1:2021]","Medical electrical equipment - Part 1-2: General\nrequirements for basic safety and essential\nperformance - Collateral Standard: Electromagnetic"]],"caption_candidate":"demonstrates compliance with following international and FDA-recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251397-p8-t0","doc_id":"K251397","page_num":8,"bbox":[72.26,72.36,539.74,305.76],"n_rows":8,"n_cols":5,"columns":["","Recognition","","Standard Number and Date","Standard Name"],"rows":[["","Recognition","","Standard Number and Date","Standard Name"],["","Number","","",""],["","","","","disturbances - Requirements and tests [Including\nAmendment 1 (2021)]"],["5-132","","","IEC 60601-1-6 Edition 3.2 2020-\n07 CONSOLIDATED VERSION","Medical electrical equipment - Part 1-6: General\nrequirements for basic safety and essential\nperformance - Collateral standard: Usability"],["5-131","","","ANSI AAMI IEC 60601-1-8:2006\nand A1:2012 [Including AMD\n2:2021]","Medical Electrical Equipment - Part 1-8: General\nrequirements for basic safety and essential\nperformance - Collateral Standard: General\nrequirements tests and guidance for alarm systems\nin medical electrical equipment and medical\nelectrical systems [Including Amendment 2 (2021)]"],["13-79","","","ANSI AAMI IEC\n62304:2006/A1:2016","Medical device software - Software life cycle\nprocesses [Including Amendment 1 (2016)]"],["5-129","","","ANSI AAMI IEC 62366-\n1:2015+AMD1:2020\n(Consolidated Text)","Medical devices Part 1: Application of usability\nengineering to medical devices including\nAmendment 1"],["5-125","","","ANSI AAMI ISO 14971: 2019","Medical devices – Application of risk management to\nmedical devices."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251399-p5-t0","doc_id":"K251399","page_num":5,"bbox":[72.0,141.0,539.76,586.56],"n_rows":10,"n_cols":2,"columns":["Date","September 10, 2025"],"rows":[["Date","September 10, 2025"],["Submitter","GE Medical Systems, LLC\n3200 N. Grandview Blvd.\nWaukesha, WI USA 53188"],["Primary\nContact Person","Xinyu Song\nLead Specialist, Regulatory Affairs, MR\nGE HealthCare\nPhone: 86 186 1188 4503\nE-mail: Xinyu.Song@gehealthcare.com"],["Secondary\nContact Person","Glen Sabin\nDirector - Regulatory Affairs, MR Strategy\nGE HealthCare\nPhone: 262 894-4968\nE-mail: Glen.Sabin@gehealthcare.com"],["Device Trade\nName","SIGNATM Sprint"],["Common/Usual\nName","Magnetic Resonance Diagnostic Device"],["Classification\nNames","Magnetic Resonance Diagnostic Device per 21 CFR 892.1000"],["Product Code","LNH, LNI, MOS"],["Predicate\nDevice","SIGNATM Premier (K193282)"],["Reference\nDevice","(1) SIGNATM Artist (K202238)\n(2) SIGNATM Champion (K233728)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251399-p7-t0","doc_id":"K251399","page_num":7,"bbox":[72.02,403.32,539.98,703.92],"n_rows":7,"n_cols":6,"columns":["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint","Comments"],["","","SIGNATM Premier","","",""],["","","(K193282)","","",""],["Magnet","3.0T Superconducting\nMagnet with active\nshielding.","","","1.5T Superconducting\nMagnet with active\nshielding.","The magnet has same technology with\ndifferent magnet field strength, and\nminor modification on enclosure.\nIt is identical with Reference Device\nSIGNATM Artist."],["Gradient\nSubsystem","A gradient coil with water-cooled, active-shielded\ndesign.","","","","The gradient coil is modified to\nreduced DC resistance and AC\nimpedance for less cooling\nrequirements."],["RF Transmit\nSubsystem","3.0T Transmit with\nembedded body coil\nand local T/R coil.","","","1.5T Transmit with\nembedded body coil\nand local T/R coil.","The platform body coil is modified to\nreduce thermal and enhance intra-bore\nvisibility.\nThe RF Transmit Subsystem except\nbody coil is identical with Reference\nDevice SIGNATM Artist."],["RF Receive\nSubsystem","3.0T Digitize-Per-Pin\n(DPP) receive chain\narchitecture.","","","1.5T Digitize-Per-Pin\n(DPP) receive chain\narchitecture.","The RF Receive Subsystem uses the\nsame technology with different RF\nfrequency.\nIt is identical with Reference Device\nSIGNATM Artist."]],"caption_candidate":"predicate/reference devices, as summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251399-p8-t0","doc_id":"K251399","page_num":8,"bbox":[72.02,86.76,539.98,356.16],"n_rows":7,"n_cols":6,"columns":["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint","Comments"],["","","SIGNATM Premier","","",""],["","","(K193282)","","",""],["RF Coils –\ndetachable","Comprehensive suite\nof 3.0T detachable\ncoils for imaging all\nanatomies.","","","Comprehensive suite\nof 1.5T detachable\ncoils for imaging all\nanatomies.","The RF coils use same technology with\ndifferent RF frequency.\nThey are substantial equivalent with\nReference Device SIGNATM Artist’s RF\ncoils."],["RF Coil –\nembedded","AIR Posterior Array","","","1.5T AIR Posterior\nArray","The 1.5T AIR Posterior Array coil has\nthe same fundamental scientific\nprinciples and similar SNR and\nUniformity measurements within their\noperated field strength. It is\nsubstantially equivalent with SIGNA™\nPremier’s AIR PA coil."],["Software\nFeatures","Comprehensive suite of software features, pulse\nsequences, and image processing applications to\nsupport MR imaging of all anatomies.","","","","SIGNA™ Sprint uses equivalent\nsoftware with predicate and reference\ndevices."],["Gating\nAccessories","Respiratory peripheral and cardiac gating with\nwireless connection.","","","","SIGNA™ Sprint uses the identical gating\naccessories with predicate and\nreference devices."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p7-t0","doc_id":"K251406","page_num":7,"bbox":[72.5,134.5,539.5,696.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],["Intended\nUse /\nIndication\ns for Use","BriefCase-Triage is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the analysis\nof CT chest, abdomen, or chest/abdomen\nwith contrast (CTA and CT with contrast)\nin adults or transitional adolescents aged\n18 and older. The device is intended to\nassist hospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communication of\nsuspected positive findings of Aortic\nDissection (AD) pathology.\nBriefCase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases with\nsuspected findings. Notifications\ninclude compressed preview images that\nare meant for informational purposes only\nand not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of BriefCase-Triage are\nintended to be used in conjunction with\nother patient information and based on\ntheir professional judgment, to assist with\ntriage/ prioritization.","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of CT\nexams with contrast (CTA and CT with\ncontrast) that include the chest in adults\nor transitional adolescents aged 18 and\nolder. The device is intended to\nassist hospital networks and\nappropriately trained medical\nspecialists in workflow triage by flagging\nand communication of suspected\npositive findings of Aortic Dissection\n(AD) pathology.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification. The\ndevice does not alter the original\nmedical image and is not intended to be\nused as a diagnostic device.\nThe results of BriefCase are intended to\nbe used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/ prioritization."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p8-t0","doc_id":"K251406","page_num":8,"bbox":[72.5,72.5,539.5,561.5],"n_rows":7,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],["User\npopulatio\nn","Hospital networks and appropriately\ntrained medical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Anatomic\nal region\nof interest","Chest, abdomen and thoraco-abdominal","Chest, abdomen and\nthoraco-abdominal"],["Data\nacquisitio\nn protocol","CT chest, abdomen, or chest/abdomen\nexams with contrast (CTA and CT with\ncontrast)","CT exams with contrast (CTA and CT\nwith contrast) that include the chest"],["Notificatio\nn-only\n(/notificati\non alerts),\nparallel\nworkflow\ntool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interferen\nce with\nstandard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p9-t0","doc_id":"K251406","page_num":9,"bbox":[72.5,72.5,539.5,590.5],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for AD","Predicate Device\nAidoc Briefcase-Triage for AD\n(K222329)"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperforma\nnce\ntesting","Inclusion Criteria\n● Scans performed on\nadults/transitional adolescents ≥\n18 years of age.\n● CT chest, abdomen, or\nchest/abdomen exams with\ncontrast (CTA and CT with\ncontrast)\n● Slice thickness 0.5 mm - 5.0 mm\nExclusion Criteria\n● All studies that have an\ninadequate field of view","Inclusion Criteria\n● Scans performed on\nadults/transitional adolescents ≥\n18 years of age.\n● CT exams with contrast (CTA\nand CT with contrast) that\ninclude the chest\n● Slice thickness 0.5 mm - 5.0\nmm\nExclusion Criteria\n● All studies that are technically\ninadequate, such as severe\nmetal artifacts, or inadequate\nfield of view."],["Additional\nOperating\nPoints","4 Additional Operating Points","2 Additional Operating Points"],["Algorithm","Artificial intelligence algorithm with\ndatabase of images.","Artificial intelligence algorithm with\ndatabase of images."],["Structure","- Integrated with image routing module via\nimage communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and\nnon-diagnostic Image Viewer).","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for\nworkflow integration (Feed/Worklist\n(alternate names) and\nnon-diagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p9-t1","doc_id":"K251406","page_num":9,"bbox":[78.0,178.68,124.68,246.29],"n_rows":5,"n_cols":2,"columns":["","for"],"rows":[["","for"],["clinical",""],["performa",""],["nce",""],["testing",""]],"caption_candidate":"adults/transitional adolescents ≥ adults/transitional adolescents ≥","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p11-t0","doc_id":"K251406","page_num":11,"bbox":[112.5,72.07,498.67,276.25],"n_rows":3,"n_cols":6,"columns":["Time -to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median"],"rows":[["Time -to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median"],["Predicate K222329\nProcessing Time","38.0","499","35.5","40.4","31.1"],["Briefcase-Triage +\nImage\nCommunication\nPlatform\nTime-To-Notification","10.7","212","10.5","10.9","10.4"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p11-t1","doc_id":"K251406","page_num":11,"bbox":[130.5,470.09,481.5,550.31],"n_rows":2,"n_cols":7,"columns":["","Mean","Std","Min","Median","Max","N"],"rows":[["","Mean","Std","Min","Median","Max","N"],["Age\n(Years)","60.1","17.3","18","62","90","212"]],"caption_candidate":"Table 3. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p12-t0","doc_id":"K251406","page_num":12,"bbox":[169.5,96.24,442.5,287.45],"n_rows":6,"n_cols":7,"columns":["Ground\nTruth\nResults","Gender","","","","All",""],"rows":[["Ground\nTruth\nResults","Gender","","","","All",""],["","Female","","Male","","",""],["","N","%","N","%","N","%"],["Positive","73","14.3%","132","25.9%","205","40.3%"],["Negative","177","34.8%","127","25.0%","304","59.7%"],["All","250","49.1%","259","50.9%","509","100.0%"]],"caption_candidate":"Table 4. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p12-t1","doc_id":"K251406","page_num":12,"bbox":[208.5,345.17,400.92,549.73],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["GE MEDICAL\nSYSTEMS","141","27.7%"],["Philips","112","22%"],["SIEMENS","174","34.2%"],["TOSHIBA","82","16.1%"],["Total","509","100%"]],"caption_candidate":"Table 5. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251406-p13-t0","doc_id":"K251406","page_num":13,"bbox":[72.5,140.5,540.5,273.5],"n_rows":5,"n_cols":3,"columns":["Operating Points","Sensitivity % (95% CI)","Specificity % (95% CI)"],"rows":[["Operating Points","Sensitivity % (95% CI)","Specificity % (95% CI)"],["AOP1","95.6% (95% CI: 91.8%-98.0%)","88.2% (95% CI: 84.0%-91.6%)"],["AOP2","94.1% (95% CI: 90.0%-96.9%)","89.8% (95% CI: 85.8%-93.0%)"],["AOP3","89.3% (95% CI: 84.2%-93.2%)","94.7% (95% CI: 91.6%-97.0%)"],["AOP4","86.3% (95% CI: 80.9%-90.7%)","97.7% (95% CI: 95.3%-99.1%)"]],"caption_candidate":"Table 6. Additional Operating Points","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p7-t0","doc_id":"K251408","page_num":7,"bbox":[58.72,145.11,809.91,510.39],"n_rows":8,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["","510(k) number","","","TBC","","","DEN230023","","","",""],["","Legal","","Naitive Technologies Limited","","","16-Bit Inc","","","","",""],["","Manufacturer","","","","","","","","","",""],["","Device Name","","","OsteoSight™","","","Rho","","","",""],["Anatomical area of\nInterest","Anatomical area of","","Pelvis or hip","","","Lumbar spine\nThoracic spine\nChest\nPelvis\nKnee\nHand/wrist","","","Both predicate and\nsubject device are\nindicated for\nquantification of X-ray\nimages of the pelvis.","",""],["","Interest","","","","","","","","","",""],["Indications for Use","","","OsteoSight™ is a software application\nintended for use opportunistically with standard\nanteroposterior (AP) radiographs of the hip or\npelvis performed in patients aged 50 years and\nolder.. OsteoSight™ provides a notification in","","","Rho is a software application intended for\nuse opportunistically with standard frontal\nradiographs of the lumbar spine, thoracic\nspine, chest, pelvis, knee, or hand/wrist\nperformed in patients aged 50 years and","","","Equivalent intended\nuse","",""]],"caption_candidate":"Table 1. Comparison of Technological Characteristics & Intended Use to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p8-t0","doc_id":"K251408","page_num":8,"bbox":[58.72,117.51,809.92,511.74],"n_rows":6,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["","","","the form of a report to aid radiologists and/or\nphysician interpreters in identifying patients\nwith possible low bone mineral density (BMD)\nat the femoral neck to prompt a clinical\nassessment of bone health. OsteoSight™\nshould not be used to rule out low BMD.\nRadiologists and referring clinicians should\nfollow recommended practices for screening\nand assessment, regardless of the absence of\nan OsteoSight™ report.","","","older. Rho provides a notification in the form\nof a report to aid radiologists and/or\nphysician interpreters in identifying patients\nwith possible low bone mineral density\n(BMD) at L1-L4 or the femoral neck to\nprompt a clinical assessment of bone\nhealth. Rho should not be used to rule out\nlow BMD. Radiologists and referring\nclinicians should follow recommended\npractices for screening and assessment,\nregardless of the absence of Rho report.","","","","",""],["Intended User","","","Physician","","","Physician","","","Same","",""],["Target Patient\nPopulation","","","Adults ≥ 50 years who undergo an X-ray as\npart of their standard of care","","","Adults ≥ 50 years who undergo an X-ray as\npart of their standard of care","","","Same","",""],["","Device Use","","When reporting the X-ray, the radiologist or\nphysician interpreter can review the OsteoSight","","","Rho can be installed on-premise or in the\ncloud, however, it must be within your","","","Same","",""],["","environment","","","","","","","","","",""]],"caption_candidate":"United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p9-t0","doc_id":"K251408","page_num":9,"bbox":[58.72,117.51,809.91,501.45],"n_rows":3,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["","","","Report, and, if in agreement, can simply include\nthis finding in their own words. OsteoSight can\nbe installed in the cloud, via a host integration\nplatform, which may be within the existing\nsecured network of a clinical site. OsteoSight\nconsists of a number of microservices deployed\nthrough container orchestration services like\nDocker.","","","existing secured network. All traffic to and\nfrom Rho can be monitored and controlled\nby you. Rho consists of a DICOM node,\ndatabase and a number of microservices\ndeployed through container orchestration\nservices like Docker Compose and\nKubernetes.","","","","",""],["Design: Purpose","","","To opportunistically analyze standard\nanteroposterior (AP) radiographs of the hip or\npelvis performed in patients aged 50 years and\nolder.\nThe algorithm presents a binary output to\nindicate whether the patient likely has low BMD\nat the femoral neck. An OsteoSight Report is","","","To opportunistically analyze standard\nanteroposterior (AP) radiographs of the\nspine, chest, pelvis, knee, hand or wrist\nperformed in patients aged 50 years and\nolder.\nThe algorithm presents a binary output to\nindicate whether or not the patient likely has\nlow BMD at either the femoral neck or L1-","","","Same, but fewer\nanatomical regions.","",""]],"caption_candidate":"United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p10-t0","doc_id":"K251408","page_num":10,"bbox":[58.72,117.51,809.92,502.92],"n_rows":7,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["","","","generated for positive cases that can be sent\nback to the PACS for physician interpretation.\nOsteoSight provides a notification in the form of\na report to aid radiologists and/or physician\ninterpreters to identify patients with possible low\nbone mineral density (BMD) at the femoral neck\nto prompt a clinical assessment of bone health.","","","L4. A Rho Report is generated for positive\ncases that can be sent back to the PACS for\nphysician interpretation or viewed through a\nbrowser-based interface.\nRho provides a notification in the form of a\nreport to aid radiologists and/or physician\ninterpreters in identifying patients with\npossible low bone mineral density (BMD) at\nthe femoral neck to prompt a clinical\nassessment of bone health.","","","","",""],["","Machine Learning","","Supervised Machine Learning (ML)","","","Supervised Machine Learning (ML)","","","Same","",""],["","Methodology","","","","","","","","","",""],["Image source","Image source","","DICOM Source (e.g., imaging device,\nintermediate DICOM node, PACS system, etc.)","","","DICOM Source (e.g., imaging device,\nintermediate DICOM node, PACS system,\netc.)","","","Same","",""],["","Clinical output","","Results Report","","","Results Report","","","Same","",""],["","Clinical Finding","","Patients at risk of low BMD","","","Patients at risk of low BMD","","","Same","",""]],"caption_candidate":"United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p11-t0","doc_id":"K251408","page_num":11,"bbox":[58.72,117.51,809.92,506.05],"n_rows":6,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["Image viewing","Image viewing","","Result output through a report with no\nannotation of the original image","","","Result output through a report with no\nannotation of the original image","","","Same","",""],["Deployment\nenvironment","","","Results will be presented to a physician in a\nmedical setting, typically via a Picture\nArchiving and Communication System (PACS).","","","Results will be presented to a physician in\na medical setting, typically via a Picture\nArchiving and Communication System\n(PACS).","","","Same","",""],["Human factors","","","OsteoSight was developed under design\ncontrols in compliance with IEC 62366,\n‘Application of usability engineering to medical\ndevices’, and FDA guidance ‘Applying Human\nFactors and Usability Engineering to Medical\nDevices Guidance for Industry and Food and\nDrug Administration Staff’.","","","Rho was developed under design controls\nand approved based on its compliance to\nthe FD&C Act including validation of its\ninterfaces and risk controls.","","","Same","",""],["Standards met","","","OsteoSight was developed in accordance with\napplicable design standards;\nISO 14971, BS EN 62366 and IEC 62304.","","","No publicly available information.","","","/","",""],["","Materials","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""]],"caption_candidate":"United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p12-t0","doc_id":"K251408","page_num":12,"bbox":[58.72,117.51,809.93,443.77],"n_rows":11,"n_cols":12,"columns":["","","","","Subject Device","","","Predicate Device","","","Summary",""],"rows":[["","","","","Subject Device","","","Predicate Device","","","Summary",""],["","Biocompatibility","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["Compatibility with\nthe environment\nand other devices","Compatibility with","","OsteoSight processes DICOM images in a\nsoftware-only configuration and does not\nrequire physical integration with imaging\nequipment.\nOsteoSight has been validated for its intended\nuse and operational environment.","","","Rho processes DICOM images in a\nsoftware-only configuration and does not\nrequire physical integration with imaging\nequipment.","","","Same","",""],["","the environment","","","","","","","","","",""],["","and other devices","","","","","","","","","",""],["","Sterility","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["","Electrical safety","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["","Mechanical safety","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["","Chemical safety","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["","Thermal safety","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""],["","Radiation safety","","N/A – Software device only.","","","N/A – Software device only.","","","/","",""]],"caption_candidate":"United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p14-t0","doc_id":"K251408","page_num":14,"bbox":[85.15,328.5,510.17,754.62],"n_rows":10,"n_cols":6,"columns":["","Data","","","Total",""],"rows":[["","Data","","","Total",""],["Sample size","","","3082","",""],["Age (Median [IQR])\n(min-max)","","","70.0 [64.0 - 76.0]\n(50 – 98)","",""],["Sex (Female:Male:not reported)","","","2787:285:10","",""],["BMI (Mean +/- SD)\n(min-max)","","","29.3 +/- 6.6\n(15.1 – 63.8)","",""],["DXA FN BMD (Mean +/- SD)\n(min-max)","","","0.716 +/- 0.146\n(0.134 – 1.535)","",""],["Prevalence of Low BMD (%)","","","66.7%","",""],["Time Between Scans (Median [IQR]\ndays)(min-max)","","","107.5 [31.0 - 207.0]\n(0 – 365)","",""],["Race","","","Asian: 81 (2.6%); Black or African American: 171\n(5.5%); Hispanic: 574 (18.6%); Other/not known:\n855 (27.7%); White: 1401 (45.5%)","",""],["Manufacturer","","","Agfa: 2 (0.1%); Canon Inc.: 17 (0.6%); Carestream:\n77 (2.5%); Eos Imaging: 2 (0.1%); FUJIFILM: 41","",""]],"caption_candidate":"Body mass index (BMI), Dual-energy X-ray absorptiometry (DXA), bone mineral density (BMD).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p15-t0","doc_id":"K251408","page_num":15,"bbox":[71.15,321.53,531.61,458.22],"n_rows":3,"n_cols":11,"columns":["Population","N","","Specificity","","","Sensitivity","","","AUC",""],"rows":[["Population","N","","Specificity","","","Sensitivity","","","AUC",""],["","","","(95% CI)","","","(95% CI)","","","(95% CI)",""],["OsteoSight Intended Use\nPopulation","3082","0.951\n(0.936-0.963)","","","0.370\n(0.349-0.391)","","","n/a","",""]],"caption_candidate":"Table 3. Performance Characterization of OsteoSight in Intended Use Population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p16-t0","doc_id":"K251408","page_num":16,"bbox":[71.12,135.77,540.25,273.42],"n_rows":3,"n_cols":11,"columns":["Population","N","","AUC","","","Sensitivity","","","Specificity",""],"rows":[["Population","N","","AUC","","","Sensitivity","","","Specificity",""],["","","","(95% CI)","","","(95% CI)","","","(95% CI)",""],["Subset of OsteoSight\nIntended Use Population\nthat produced a result","2596","0.837\n(0.821-0.853)","","","0.441\n(0.386-0.487)","","","0.943\n(0.922-0.961)","",""]],"caption_candidate":"a result.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p16-t1","doc_id":"K251408","page_num":16,"bbox":[71.12,504.54,546.53,754.14],"n_rows":9,"n_cols":15,"columns":["","Group","","","N","","","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],"rows":[["","Group","","","N","","","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],["Sex","","","","","","","","","","","","","",""],["Females","","","2787","","","n/a","","","0.373 (0.352-0.395)","","","0.950 (0.934-0.963)","",""],["Males","","","285","","","n/a","","","0.319 (0.249-0.399)","","","0.957 (0.910-0.980)","",""],["Age group (years)","","","","","","","","","","","","","",""],["50-59","","","418","","","n/a","","","0.258 (0.201-0.324)","","","0.969 (0.938-0.985)","",""],["60-69","","","1012","","","n/a","","","0.347 (0.310-0.385)","","","0.940 (0.912-0.960)","",""],["70-79","","","1045","","","n/a","","","0.401 (0.366-0.437)","","","0.959 (0.930-0.976)","",""],["80+","","","485","","","n/a","","","0.489 (0.441-0.537)","","","0.912 (0.830-0.957)","",""]],"caption_candidate":"Use Population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p17-t0","doc_id":"K251408","page_num":17,"bbox":[71.11,102.66,546.53,536.1],"n_rows":15,"n_cols":5,"columns":["BMI (kg/m2)","","","",""],"rows":[["BMI (kg/m2)","","","",""],["18-25","352","n/a","0.508 (0.452-0.565)","0.906 (0.797-0.959)"],["25-30","464","n/a","0.442 (0.388-0.498)","0.941 (0.891-0.969)"],[">30","531","n/a","0.306 (0.253-0.365)","0.960 (0.930-0.978)"],["Race","","","",""],["Asian","81","n/a","0.353 (0.250-0.472)","0.923 (0.667-0.986)"],["Black or African\nAmerican","171","n/a","0.229 (0.133-0.365)","0.967 (0.919-0.987)"],["Hispanic","574","n/a","0.414 (0.364-0.465)","0.963 (0.928-0.981)"],["White","855","n/a","0.375 (0.335-0.416)","0.940 (0.907-0.962)"],["Other/not known","1401","n/a","0.359 (0.330-0.389)","0.949 (0.922-0.967)"],["Region","","","",""],["Midwest","425","n/a","0.283 (0.237-0.333)","0.978 (0.922-0.994)"],["Northeast","357","n/a","0.258 (0.210-0.312)","0.936 (0.859-0.972)"],["South","2146","n/a","0.409 (0.383-0.436)","0.952 (0.935-0.965)"],["West","154","n/a","0.438 (0.355-0.524)","0.885 (0.710-0.960)"]],"caption_candidate":"England, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251408-p17-t1","doc_id":"K251408","page_num":17,"bbox":[71.11,603.9,546.53,742.5],"n_rows":5,"n_cols":15,"columns":["","Group","","","N","","","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],"rows":[["","Group","","","N","","","AUC (95% CI)","","","Sensitivity (95% CI)","","","Specificity (95% CI)",""],["Sex","","","","","","","","","","","","","",""],["Females","","","2347","","","0.840 (0.823-0.856)","","","0.446 (0.390-0.501)","","","0.942 (0.921-0.960)","",""],["Males","","","239","","","0.810 (0.756-0.865)","","","0.374 (0.130-0.537)","","","0.948 (0.888-0.991)","",""],["Age group (years)","","","","","","","","","","","","","",""]],"caption_candidate":"population in which OsteoSight generated a result.","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K251455-p7-t0","doc_id":"K251455","page_num":7,"bbox":[254.64,61.28,569.46,167.8],"n_rows":6,"n_cols":3,"columns":["System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],"rows":[["System, imaging, pulsed doppler,\nultrasonic","892.1550","IYN"],["Secondary","",""],["System, imaging, pulsed echo,\nultrasonic","892.1560","IYO"],["Transducer, ultrasonic, diagnostic","892.1570","ITX"],["Automated Radiological Image\nProcessing Software","892.2050","QIH"],["Catheter, Ultrasound, Intravascular","870.1200","OBJ*"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251455-p10-t0","doc_id":"K251455","page_num":10,"bbox":[76.27,119.17,706.4,541.02],"n_rows":36,"n_cols":5,"columns":["","","","LVivo Software",""],"rows":[["","","","LVivo Software",""],["","","EPIQ & Affiniti Series Diagnostic Ultrasound","Application",""],["","EPIQ & Affiniti Series Diagnostic Ultrasound","Systems","Feature: Auto EF",""],["","System Feature: SVS v2 Contrast","K240850","K243235",""],["","","Predicate Device","Reference Device",""],["Feature","Proposed Device","","","Comparison"],["","Abdominal, Cardiac Adult, Cardiac other (Fetal),\nCardiac Pediatric, Cerebral Vascular, Cephalic\n(Adult), Cephalic (Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Ophthalmic, Other:\nUrology, Pediatric, Peripheral Vessel, Small Organ\n(Breast, Thyroid, Testicle), Transesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung","Abdominal, Cardiac Adult, Cardiac other (Fetal),\nCardiac Pediatric, Cerebral Vascular, Cephalic\n(Adult), Cephalic (Neonatal), Fetal/Obstetric,\nGynecological, Intraoperative (Vascular),\nIntraoperative (Cardiac), intra-luminal, intra-\ncardiac echo, Musculoskeletal (Conventional),\nMusculoskeletal (Superficial), Ophthalmic, Other:\nUrology, Pediatric, Peripheral Vessel, Small Organ\n(Breast, Thyroid, Testicle), Transesophageal\n(Cardiac), Transrectal,\nTransvaginal, Lung","LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected disease. In\naddition, it has the ability\nto provide Quality Score\nfeedback","No change"],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["Indications for","","","",""],["Use","","","",""],["","","","",""],["","Trained healthcare professionals\nIntended for sonographers, physicians who\noperate and maintain your product.\nBefore use of the system and user information,\nthe user must be familiar with ultrasound\ntechniques. Sonography training and clinical\nprocedures are not included in the User Manual or\nwith the EPIQ and Affiniti Series Diagnostic\nUltrasound System.","Trained healthcare professionals\nIntended for sonographers, physicians who operate\nand maintain your product.\nBefore use of the system and user information,\nthe user must be familiar with ultrasound\ntechniques. Sonography training and clinical\nprocedures are not included in the User Manual or\nwith the EPIQ and Affiniti Series Diagnostic\nUltrasound System.","Trained healthcare\nprofessionals","No change"],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["Intended","","","",""],["Users","","","",""],["","","","",""],["Intended User","Clinics, hospitals, and clinical point-of-care for\ndiagnosis of patients.","Clinics, hospitals, and clinical point-of-care for\ndiagnosis of patients.","Professional healthcare\nenvironments","No change"],["Environment","","","",""],["","","","",""],["USA FDA","Class II","Class II","Class II","No change"],["Classification","","","",""],["Primary","IYN","IYN","QIH","No change"],["Product Code","","","",""],["Primary","Ultrasonic pulsed doppler imaging\nsystem","Ultrasonic pulsed doppler imaging\nsystem","Medical image\nmanagement and\nprocessing system","No change"],["Regulation","","","",""],["Name","","","",""],["","","","",""],["Primary","21 CFR 892.1550","21 CFR 892.1550","21 CFR 892.2050","No change"],["Regulation","","","",""],["Number","","","",""]],"caption_candidate":"Affiniti Series Diagnostic Ultrasound Systems. The subject devices are substantially equivalent to the predicate devices (K240850).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251455-p11-t0","doc_id":"K251455","page_num":11,"bbox":[72.45,58.4,682.65,591.48],"n_rows":43,"n_cols":5,"columns":["","","","LVivo Software",""],"rows":[["","","","LVivo Software",""],["","","EPIQ & Affiniti Series Diagnostic Ultrasound","Application",""],["","EPIQ & Affiniti Series Diagnostic Ultrasound","Systems","Feature: Auto",""],["","System Feature: SVS v2 Contrast","K240850","EF K243235",""],["","","","Reference Device",""],["Feature","Proposed Device","Predicate Device","","Comparison"],["Secondary","ITX\nIYO\nOBJ\nQIH","ITX\nIYO\nOBJ\nQIH","N/A","No change"],["Product Codes","","","",""],["","","","",""],["Secondary","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging system\nDiagnostic intravascular catheter\nMedical image management and processing\nsystem","Diagnostic ultrasonic transducer Ultrasonic\npulsed echo imaging system Diagnostic\nintravascular catheter\nMedical image management and processing\nsystem","N/A","No change"],["Regulation","","","",""],["Name","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["Secondary","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","21 CFR 892.1570\n21 CFR 892.1560\n21 CFR 870.1200\n21 CFR 892.2050","N/A","No change"],["Regulation","","","",""],["Number","","","",""],["","","","",""],["Reusable-","Yes","Yes","No, software-feature","No change"],["Systems and","","","",""],["Transducers","","","",""],["Duration of use","Limited (≤ 24 hours)","Limited (≤ 24 hours)","N/A, software-feature","No change"],["","Smart View Select is an automated software\nfeature that assists the user in selection of images\nfor analysis with the existing Philips AutoStrain LV\nor 2D Auto LV (K240850) application in Adult Echo\nTransthoracic (TTE) examination.\nUsers can launch existing 2D Auto EF; 2D Auto EF\nAdv (submitted K251110) or AutoStrain LV; or 2D\nAuto LV (both K240850) with the set of images that\nhave been automatically selected without the need\nto review the acquired images and manually select\nthe views. Users may select 2D Auto EF Adv, to\nprocess the selected views by SVS v2 Contrast.\nSVS v2 Contrast prioritizes the contrast image pair;\nhowever, if an appropriate pair of contrast images\nis not found, then Auto EF Adv may select non-\ncontrast images. The manual approach to select\nviews is still available and\nthe user can override automatically selected\nimages from SVS v2 Contrast.","Predicate integrates the LVivo seamless\nalgorithm (K212466) to introduce Smart View\nSelect (SVS) on the EPIQ Series Diagnostic\nUltrasound System. SVS is an automated\nsoftware feature that assists the user in\nselection of optimal images for analysis with the\nexisting Pillips AutoStrain LV or 2D Auto LV\n(both K240850)\nThe LVivo contains the functionality introduced\nfor\n(1)automatic selection of 4CH,2CH, and 3CH\nviews for left ventricle (LV) analysis or (2)\n(semi- automated segmental wall motion\nevaluation of the left ventricle (LV).","LVivo platform is\nintended for non-\ninvasive processing of\nultrasound images to\ndetect, measure, and\ncalculate relevant\nmedical parameters of\nstructures and function\nof patients with\nsuspected diseases. In\naddition, it has the\nability to provide Quality\nScore feedback","The algorithm is\nrevised to include the\nselection of optimal\nimages for analysis\nwhen contrast is used\nin routine TTE exams."],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["","","","",""],["Application","","","",""],["Description","","","",""],["","","","",""],["Deep Neural","LVivo Seamless AI neural network","LVivo Seamless AI neural network\n6","LVivo Seamless AI\nneural network","No change"],["Network","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251455-p13-t0","doc_id":"K251455","page_num":13,"bbox":[25.67,284.21,569.16,335.49],"n_rows":5,"n_cols":5,"columns":["","Mean Difference ± SD","95 % CI for Mean","",""],"rows":[["","Mean Difference ± SD","95 % CI for Mean","",""],["Outcomes Comparison","(n)","Difference","Lower LoA (95% CI)","Upper LoA (95% CI)"],["EF - SVS Selected (Automated) vs EF -","0.71 ± 4.36 (46)","-0.58 , 2.01","-7.83 (-10.06, -5.60)","9.26 (7.03, 11.49)"],["Manually Selected (Ground Truth)","","","",""],["","","","",""]],"caption_candidate":"Biplane EF - Manually Selected (Ground Truth)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251455-p13-t1","doc_id":"K251455","page_num":13,"bbox":[17.94,392.41,575.96,450.92],"n_rows":5,"n_cols":8,"columns":["Outcomes Comparison","","N","","Pearson's correlation","","p-Value",""],"rows":[["Outcomes Comparison","","N","","Pearson's correlation","","p-Value",""],["Outcomes Comparison","","","","","","","p-Value"],["","","","","coefficient (r) (95% CI)","","",""],["EF–SVS Selected (Automated) vs EF–Manually Tracing","","46","0.938 (0.890, 0.965)","0.938 (0.890, 0.965)","","<.0001","<.0001"],["(Ground Truth)","","","","","","",""]],"caption_candidate":"Tracing (Ground Truth)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251455-p13-t2","doc_id":"K251455","page_num":13,"bbox":[17.94,527.91,575.96,576.22],"n_rows":4,"n_cols":5,"columns":["","Mean Difference ± SD","95 % CI for Mean","",""],"rows":[["","Mean Difference ± SD","95 % CI for Mean","",""],["Outcomes Comparison","(n)","Difference","Lower LoA (95% CI)","Upper LoA (95% CI)"],["EF - SVS Selected (Automated) vs EF -","1.22 ± 5.22 (46)","-0.33, 2.77","-9.01 (-11.67, -6.34)","11.45 (8.78, 14.11)"],["Manually Tracing (Ground Truth)","","","",""]],"caption_candidate":"(Ground Truth)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251456-p5-t0","doc_id":"K251456","page_num":5,"bbox":[67.5,118.5,485.5,288.5],"n_rows":7,"n_cols":2,"columns":["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],"rows":[["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],["",""],["Contact:","Christophe Gardella\nChief Technical Officer\nTel. +0033686543950\nEmail. christophe@brightheart.fr"],["",""],["Submission Correspondent:","Christophe Gardella"],["",""],["Date Prepared:","May 8, 2025"]],"caption_candidate":"UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251456-p5-t1","doc_id":"K251456","page_num":5,"bbox":[67.5,335.5,489.5,436.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name:","BrightHeart View Classifier"],"rows":[["Device Trade Name:","BrightHeart View Classifier"],["Device Common Name:","Fetal ultrasound view classifier"],["Classification Name","21 CFR §892.2050, Medical image management and\nprocessing system"],["Product Code(s):","QIH"],["Regulatory Class:","Class II"]],"caption_candidate":"EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251456-p6-t0","doc_id":"K251456","page_num":6,"bbox":[72.25,314.19,531.25,702.5],"n_rows":14,"n_cols":3,"columns":["","Subject device:\nBrightHeart View Classifier v1.1","Predicate device:\nBrightHeart View Classifier v1.0"],"rows":[["","Subject device:\nBrightHeart View Classifier v1.1","Predicate device:\nBrightHeart View Classifier v1.0"],["510(k) Number","-","K243684"],["Applicant","BrightHeart","BrightHeart"],["Classification\nRegulation","21 CFR §892.2050, Medical image\nmanagement and processing system","21 CFR §892.2050, Medical image\nmanagement and processing system"],["Product Code","QIH","QIH"],["Intended user","Healthcare professionals (HCP) trained and\nqualified in fetal ultrasound.","Healthcare professionals (HCP) trained and\nqualified in fetal ultrasound."],["Intended\npopulation","Pregnant women aged 18 or older,\nundergoing anatomic ultrasound\nexamination\nThe device is not intended for use in\nmultiple pregnancies.","Pregnant women aged 18 or older,\nundergoing anatomic ultrasound\nexamination\nThe device is not intended for use in\nmultiple pregnancies."],["Device Type","SaMD","SaMD"],["Imaging\nModality","Fetal Ultrasound","Fetal Ultrasound"],["Platform","Cloud-based stand-alone software","Cloud-based stand-alone software"],["Operates on\nDICOM files","Yes","Yes"],["Model Inputs","Ultrasound images and video clips","Ultrasound images and video clips"],["Model method","Neural networks","Neural networks"],["Model trained\nto identify","Classification of ultrasound images into\nstandard views of fetal heart.","Classification of ultrasound images into\nstandard views of fetal heart."]],"caption_candidate":"Technological Comparison:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251456-p7-t0","doc_id":"K251456","page_num":7,"bbox":[72.33,72.13,531.33,172.5],"n_rows":3,"n_cols":3,"columns":["","Subject device:\nBrightHeart View Classifier v1.1","Predicate device:\nBrightHeart View Classifier v1.0"],"rows":[["","Subject device:\nBrightHeart View Classifier v1.1","Predicate device:\nBrightHeart View Classifier v1.0"],["Device Output","Identifies standard views of the fetal heart\nand abdomen in images and video clips.","Identifies standard views of the fetal heart\nand abdomen in images and video clips."],["Output Display","● Annotated DICOM files within a\nDICOM viewer\n● Device web interface","● Annotated DICOM files within a\nDICOM viewer"]],"caption_candidate":"510(k) Summary Page 3 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251456-p9-t0","doc_id":"K251456","page_num":9,"bbox":[72.5,158.5,546.5,526.5],"n_rows":2,"n_cols":4,"columns":["Modification","Rationale","Testing Methods","Impact Assessment"],"rows":[["Modification","Rationale","Testing Methods","Impact Assessment"],["Modification of\ntraining and/or\nvalidation datasets to\nupdate model weights\nand detection\nthresholds","Improvements in the\nview classification\nperformance of the\ndevice.","Re-training of the\nBrightHeart View\nClassifier with new\ndata to optimize its\nperformance followed\nby performance\ntesting and a\ncomparison of the\noriginal BrightHeart\nView Classifier to\nthe modified\nBrightHeart View\nClassifier (using\nperformance metrics)\nand verification and\nvalidation.","Improved\nperformance\nmetrics of modified\nBrightHeart View\nClassifier\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization for\ndiverse cases.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nTesting data\nsequestration and\ntesting on new data\nwill ensure proper\nevaluation and\nmitigate risks of\noverfitting."]],"caption_candidate":"Summary of changes to BrightHeart View Classifier per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p5-t0","doc_id":"K251474","page_num":5,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"K251474","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p5-t1","doc_id":"K251474","page_num":5,"bbox":[70.82,418.39,520.66,519.31],"n_rows":7,"n_cols":2,"columns":["Trade Name","TransparaTM 2.1.0"],"rows":[["Trade Name","TransparaTM 2.1.0"],["Legal Manufacturer","ScreenPoint Medical B.V."],["510(k) Number","K241831"],["Device","Radiological Computer Assisted Detection/Diagnosis Software for\nLesions Suspicious for Cancer"],["Class","Class II"],["Regulation Number","21 CFR 892.2090"],["Product Code","QDQ"]],"caption_candidate":"4 Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p6-t0","doc_id":"K251474","page_num":6,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p7-t0","doc_id":"K251474","page_num":7,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p7-t1","doc_id":"K251474","page_num":7,"bbox":[70.82,248.81,524.62,764.16],"n_rows":10,"n_cols":4,"columns":["","Predicate Device\n(TransparaTM 2.1.0)","Subject Device\n(Median LCS/eyonis LCS)","Substantially Equivalent ?"],"rows":[["","Predicate Device\n(TransparaTM 2.1.0)","Subject Device\n(Median LCS/eyonis LCS)","Substantially Equivalent ?"],["Classification\nRegulation","21 CFR 892.2090\nRadiological Computer\nAssisted Detection\nAnd Diagnosis\nSoftware","SAME","Yes, identical."],["Medical Device\nClassification","Class II","SAME","Yes, identical"],["Product Code","QDQ","SAME","Yes, identical"],["Level of Concern","Moderate/Basic Level\nof Documentation","SAME","Yes, identical"],["Intended Use","A concurrent reading\naid for Physicians\ninterpreting screening\nimages, to identify\nfindings and assess\ntheir level of\nsuspicion.","SAME","Yes, identical"],["Target patient\nPopulation","Screening population","SAME","Yes, identical"],["Target user\npopulation","Interpreting physician","SAME","Yes, identical"],["Design","Software-only device\n(Viewer optional)","SAME\nNo viewer","Yes, identical"],["Score","Finding level:\nContinuous score 1-\n100 indicating the\nlevel of suspicion of\nmalignancy (from low\nsuspicion to high\nsuspicion).\nOrgan level:\nNone\nExam level:","Finding level:\nDiscreet score 1-10\naccompanied with\nmalignancy rate (from\nprobably benign to very\nsuspicious)\nOrgan level:\nNone\nExam level:\nNone","Both devices’ algorithms\nyield a continuous 100-\npoint score, intended to be\ninterpreted as likelihood of\nmalignancy. The predicate\nprovides the 100-point\nscore directly to the user,\nwhile Median LCS provides\na simplified 10-point score\nthat is monotonic with the\nlikelihood of malignancy.\nSubstantially equivalent."]],"caption_candidate":"effectiveness of the device when used as labeled.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p8-t0","doc_id":"K251474","page_num":8,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p8-t1","doc_id":"K251474","page_num":8,"bbox":[70.82,101.18,524.62,667.18],"n_rows":4,"n_cols":4,"columns":["","10-point scale score\nindicative of higher\nfrequency of cancer\npositive.","",""],"rows":[["","10-point scale score\nindicative of higher\nfrequency of cancer\npositive.","",""],["Interaction with\nfindings","Upon user request by\nclicking in a position\nof the image also\ndetected by\nTransparaTM.","Findings are by-default\ndisplayed when score is\nequal or higher to 2.","Both are implementations\nof the same intention:\nreducing the number of\nfindings the user has to\nreview. Substantially\nequivalent."],["Device output &\nuser interface","Distinguishes two\ntypes of suspicious\nfindings (calcifications\nand soft tissue\nlesions).\nThe device output\nincludes the location\nand the outline of\nfindings.\nTranspara™\nprocessing server is a\nstandalone system\nWITHOUT a user\ninterface.","Only targets one type of\nfindings (nodules,\nsolid/part-solid).\nMedian LCS result report\nincludes the localization\n(slice number), two\nsnapshots, diameters\nand volume.\nSame.","Despite some differences\nbetween the predicate\ndevice and Median LCS,\ndevice output and user\ninterface are still\ncomparable and do not\nraise new questions\nregarding safety and\neffectiveness of the device."],["Fundamental\nscientific\ntechnology","A chain of medical\nimage processing and\nmachine learning\ntechniques are\nimplemented. The\ndevice includes ‘deep\nlearning’ modules for\nrecognition of\nsuspicious lesions.\nThese modules are\ntrained with very large\ndatabases of cancer\nand normal patients\nproven by biopsy or\nfollow-up.","SAME","Yes, identical"]],"caption_candidate":"Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p9-t0","doc_id":"K251474","page_num":9,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p9-t1","doc_id":"K251474","page_num":9,"bbox":[70.82,195.14,524.62,394.49],"n_rows":8,"n_cols":4,"columns":["Standard ID","Year / Edition","Standard Title","Recognition #"],"rows":[["Standard ID","Year / Edition","Standard Title","Recognition #"],["IEC 62366-1","Edition 1.1 2020-06","Medical devices - Part 1: Application of usability\nengineering to medical devices","5-129"],["ISO 20417","First edition 2021-04\nCorrected Version 2021-12","Medical devices – Information to be supplied by\nthe manufacturer","5-135"],["ISO 14971","Third Edition 2019-12","Medical Devices - Application Of Risk\nManagement To Medical Devices","5-125"],["IEC 62304","Edition 1.1 2015-06","Medical Device Software - Software Life Cycle\nProcesses","13-79"],["IEC 82304-1","Edition 1.0 2016-10","Health software - Part 1: General requirements\nfor product safety","13-97"],["ISO 15223-1","Fourth edition 2021-07","Medical devices - Symbols to be used with\ninformation to be supplied by the manufacturer\n-Part 1: General requirements","5-134"],["NEMA PS 3.1\n–3.20 2023e","2023 edition","Digital Imaging and Communications in\nMedicine (DICOM) Set","12-352"]],"caption_candidate":"voluntary FDA recognized standards and guidelines:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p9-t2","doc_id":"K251474","page_num":9,"bbox":[70.82,421.87,543.22,735.1],"n_rows":16,"n_cols":3,"columns":["ID","Year","Title"],"rows":[["ID","Year","Title"],["FDA-1997-D-0029","2002","General Principles of Software Validation"],["FDA-2011-D-0652","2014","The 510(k) Program: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]"],["FDA-2015-D-5105","2016","Postmarket Management of Cybersecurity in Medical Devices"],["FDA-2011-D-0469","2016","Applying Human Factors and Usability Engineering to Medical Devices"],["FDA-2015-D-4852","2017","Design Considerations and Pre-market Submission\nRecommendations for Interoperable Medical Devices"],["FDA-2014-D-0456","2018","Appropriate Use of Voluntary Consensus Standards in Premarket\nSubmissions for Medical Devices"],["FDA-2018-D-1329","2019","Recommended Content and Format of Non-Clinical Bench Performance\nTesting Information in Premarket Submissions"],["FDA-2018-D-1339","2020","Multiple Function Device Products: Policy and Considerations: Guidance for\nIndustry and Food and Drug Administration"],["FDA-2016-D-1853","2021","Unique Device Identification System: Form and Content of the Unique Device\nIdentifier (UDI)"],["FDA-2019-D-1470","2022","Technical Performance Assessment of Quantitative Imaging in Radiological\nDevice Premarket Submissions"],["FDA 2021-D-1158","2023","Cybersecurity in Medical Devices: Quality System Considerations and\nContent of Premarket Submissions"],["FDA-2021-D-0775","2023","Content of Premarket Submissions for Device Software Functions"],["FDA-2019-D-3598","2023","Off-The-Shelf Software Use in Medical Devices"],["FDA-2023-D-1030","2023","Cybersecurity in Medical Devices: Refuse to Accept Policy for Cyber Devices\nand Related Systems Under Section 524B of the FD&C Act"],["FDA-2021-D-0872","2023","Electronic Submission Template for Medical Device 510(k) Submissions"]],"caption_candidate":"The following guidance documents were used to support this submission:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p10-t0","doc_id":"K251474","page_num":10,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p11-t0","doc_id":"K251474","page_num":11,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251474-p12-t0","doc_id":"K251474","page_num":12,"bbox":[56.76,22.08,529.42,87.02],"n_rows":2,"n_cols":4,"columns":["","Median Technologies","",""],"rows":[["","Median Technologies","",""],["Document Title: eyonisLCS1.1_K251474_510(k)\nSummary","","Doc #\neyonisLCS1.1_K251474_510(k)\nSummary","Version\n01"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251481-p11-t0","doc_id":"K251481","page_num":11,"bbox":[100.79,157.02,538.08,218.97],"n_rows":4,"n_cols":2,"columns":["","the users with the ability to enter"],"rows":[["","the users with the ability to enter"],["Heart Rate value into the Measurement Display Area, which can be used for specific calculations,",""],["such as cardiac output. The subject devices support heart rate measurement entry from different",""],["modes with specific labels.",""]],"caption_candidate":"Abdominal Diameter).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251483-p6-t0","doc_id":"K251483","page_num":6,"bbox":[107.42,566.73,539.74,760.08],"n_rows":7,"n_cols":6,"columns":["","Subject device","Predicate device","","Substantial",""],"rows":[["","Subject device","Predicate device","","Substantial",""],["","","","","Equivalence",""],["Device name","SwiftSight-Brain","Neurophet AQUA V3.1","-","",""],["510(k)","-","K242215","-","",""],["Manufacturer","AIRS Medical Inc.","NEUROPHET, Inc","-","",""],["Product code","QIH, LLZ","QIH, LLZ","Same","",""],["Indications for\nuse","This device is intended for\nautomatic labelling,\nvisualization and volumetric\nquantification of segmentable\nbrain structures and lesions\nfrom a set of MR images.\nVolumetric data may be","Neurophet AQUA is intended for\nautomatic labeling, visualization\nand volumetric quantification of\nsegmentable brain structures\nand lesions from a set of MR\nimages. Volumetric data may be\ncompared to reference","Same","",""]],"caption_candidate":"Comparison table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251483-p7-t0","doc_id":"K251483","page_num":7,"bbox":[107.41,85.41,539.75,749.52],"n_rows":11,"n_cols":6,"columns":["","Subject device","Predicate device","","Substantial",""],"rows":[["","Subject device","Predicate device","","Substantial",""],["","","","","Equivalence",""],["","compared to reference\npercentile data.","percentile data.","","",""],["Target\nanatomical sites","Brain","Brain","Same","",""],["Design and\nincorporated\ntechnology"," Automated measurement of\nbrain tissue volumes,\nstructures, and lesions\n Automatic segmentation and\nquantification of brain\nstructures using deep learning"," Automated measurement of\nbrain tissue volumes,\nstructures, and lesions\n Automatic segmentation and\nquantification of brain\nstructures using deep learning","Same","",""],["Physical\ncharacteristics"," Software package\n Operates on off-the shelf\nhardware (multiple vendors)"," Software package\n Operates on off-the shelf\nhardware (multiple vendors)","Same","",""],["Operation\nsystem","Windows","Windows","Same","",""],["Processing\narchitecture","Automated internal pipeline\nthat performs:\n segmentation\n volume calculation\n report generation","Automated internal pipeline\nthat performs:\n segmentation\n volume calculation\n report generation","Same","",""],["Data source"," MRI scanner: 3D T1 and FLAIR\nMRI scans acquired with\nspecified protocols\n Supports DICOM format as\ninput"," MRI scanner: 3D T1 and FLAIR\nMRI scans acquired with\nspecified protocols\n Supports DICOM format as\ninput","Same","",""],["Output"," Provides volumetric\nmeasurements of brain\nstructures and lesions\n Includes segmented color\noverlays and morphometric\nreports\n Automatically compares\nresults to reference percentile\ndata and to prior scans when\navailable\n Supports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and Communications\nSystems"," Provides volumetric\nmeasurements of brain\nstructures and lesions\n Includes segmented color\noverlays and morphometric\nreports\n Automatically compares\nresults to reference percentile\ndata and to prior scans when\navailable\n Supports DICOM format as\noutput of results that can be\ndisplayed on DICOM\nworkstations and Picture\nArchive and Communications\nSystems","Same","",""],["Safety"," Automated quality control\nfunctions"," Automated quality control\nfunctions","Substantially\nEquivalent","",""]],"caption_candidate":"www.airsmed.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251483-p8-t0","doc_id":"K251483","page_num":8,"bbox":[107.45,85.41,539.71,180.96],"n_rows":3,"n_cols":6,"columns":["","Subject device","Predicate device","","Substantial",""],"rows":[["","Subject device","Predicate device","","Substantial",""],["","","","","Equivalence",""],["","- Tissue contrast check\n- Scan protocol verification\n Results must be reviewed by a\nmedical professional","- Image artifact check\n- Scan protocol verification\n Results must be reviewed by a\ntrained physician","","",""]],"caption_candidate":"www.airsmed.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251514-p7-t0","doc_id":"K251514","page_num":7,"bbox":[45.69,250.61,566.31,700.61],"n_rows":3,"n_cols":5,"columns":["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],"rows":[["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],["Classification\nRegulation","21 CFR 892.2050, Medical\nImage Management and\nProcessing System","21 CFR 892.2050,\nMedical Image\nManagement and\nProcessing System","21 CFR 892.2050, Medical\nImage Management and\nProcessing System","Same"],["Intended\nUse/Indication\ns for Use","Overjet CBCT Assist is a\nsoftware for the analysis of\ndental and\ncraniomaxillofacial Cone\nBeam Computed\nTomography (CBCT)\nimages. The software\nutilizes artificial\nintelligence/machine\nlearning algorithms to\nprovide automated\nsegmentations,\nuser-delineated or\nautomated measurements,\nand 2D/3D visualizations.\nThese tools are intended to\nassist dental professionals\nin their review and\ninterpretation of CBCT\nimages by facilitating\nanatomical assessment and\nsupporting their diagnostic\nand treatment planning\nprocess. The device is not\nintended as a replacement\nfor a complete clinician’s\nreview or their clinical\njudgement.","Relu Creator is a\nsoftware program for the\nmanagement, transfer,\nand analysis of dental\nand craniomaxillofacial\nimage information, and\ncan be used to provide\ndesign input for dental\nsolutions. It\ndisplays and enhances\ndigital images from\nvarious sources to\nsupport the diagnostic\nprocess and\ntreatment planning. It\nstores and provides\nthese images within the\nsystem or across\ncomputer\nsystems at different\nlocations.","Planmeca Romexis is a\nmedical imaging software\nintended for use in dental and\nmedical care as a tool for\ndisplaying and visualizing\ndental and medical 2D and\n3D image files from imaging\ndevices, such as projection\nradiography and CBCT. It is\nintended for use by\nradiologists, clinicians,\nreferring physicians and other\nqualified individuals to\nretrieve, process, render,\ndiagnose, review, store, print,\nand distribute\nimages of both adult and\npediatric patients.\nPlanmeca Romexis is also a\npreoperative software used\nfor dental implant planning.\nBased on the planned implant\nposition a model of a surgical\nguide for a guided implant\nsurgery can be designed. The\ndesigned objects can be\nexported to manufacture a\nseparate physical product.","All three devices\nare intended to\nsupport the\nvisualization,\nanalysis, and\ninterpretation of\n3D CBCT data in\ndental and\ncraniomaxillofacial\napplications.\nWhile the\npredicate devices\ninclude\ndownstream\ndental solutions,\nthe subject device\nis limited to\ndiagnostic\nsupport. These\ndifferences do not\nintroduce new\nquestions of\nsafety or\neffectiveness."]],"caption_candidate":"Table 1: Comparison to Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251514-p8-t0","doc_id":"K251514","page_num":8,"bbox":[45.67,72.08,566.33,712.5],"n_rows":4,"n_cols":5,"columns":["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],"rows":[["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],["","","","Planmeca Romexis is also a\npreoperative software for\nsimulating / evaluating\nsurgical treatment options.\nPlanmeca Romexis is also\nintended to be used for\nmonitoring, recording, storing\nand displaying mandibular\njaw positions and movements\nrelative to the maxilla.\nAdditionally, Planmeca\nRomexis includes monitoring\nfeatures for Planmeca\ndevices for maintenance\npurposes. The software is\ndesigned to work as a\nstand-alone or as an\naccessory to Planmeca\nimaging and Planmeca dental\nunit products in standard PC.\nThe software is for use by\nauthorized healthcare\nprofessionals. Use of the\nsoftware for implant planning\nrequires that the user has the\nnecessary medical training in\nimplantology and surgical\ndentistry. Use of the software\nfor surgical treatment\nplanning requires that the\nuser has the necessary\nmedical training in\nmaxillofacial surgery.\nIndications of the dental\nimplants do not change with\nguided surgery compared to\nconventional surgery.",""],["Platform &\nRequirements","Web-application","Web-application\nLocal application","Standard PC hardware","The subject\ndevice is offered\nas a web\napplication only."],["Input File\nTypes","Supports CBCT-based\nDICOM files: standard\nCBCT, enhanced CBCT,\nand craniofacial 3D DICOM\nformats.","Supports a broader\nrange of image types\nused in dental\nworkflows, including\nCBCT, IOS (intraoral\nscans), and FS (facial\nscans).","2D, 3D","The subject\ndevice is focused\nexclusively on 3D\nvolumetric CBCT\ndata while the\npredicate devices\nare capable of"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251514-p9-t0","doc_id":"K251514","page_num":9,"bbox":[45.67,72.08,565.62,572.92],"n_rows":4,"n_cols":5,"columns":["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],"rows":[["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Primary Predicate\nRelu Creator (K233925)\nRelu BV","Secondary Predicate\nPlanmeca Romexis\n(K200572)\nPlanmeca Oy","Comparison"],["","","","","ingesting a\nbroader range of\nimaging\nmodalities."],["Output File\nTypes","PDF","PDF report\nCommon formats for\ndental and\ncraniomaxillofacial\ntreatment planning\napplications (STL,\nDICOM, PLY, OBJ)","PDF report","All three devices\nprovide output as\nPDF reports. The\npredicate Relu\nCreator also\nsupports export in\nstandard 3D\nplanning formats\nas compared to\nthe subject device."],["Functions and\nCapabilities","● Multi-Planar\nReconstruction Views\n● 3D Volume Rendering\n● Virtual Panoramic view\nreconstruction\n● Image enhancement and\nmanipulation (Brightness,\nContrast)\n● AI-based segmentation of\ndental and\ncraniomaxillofacial\nanatomy, as well as past\nrestorations.\n● Measurement - Distance\n(length, diameter,\nperimeter), Area, Angle,\nSignal intensity\n● Implant Site Evaluation\n● 3rd molar surgery\nplanning by generating\nlinear measurement to\nnearby critical structures\n● Supports airway\nevaluation by reporting\nminimum cross-sectional\narea","● Multi-Planar\nReconstruction Views\n● 3D Volume Rendering\n● Virtual Panoramic\nview reconstruction\n● Image enhancement\nand manipulation\n(Brightness, Contrast)\n● AI-based\nsegmentation of\ndental and\ncraniomaxillofacial\nanatomy, as well as\npast restorations.\n● Preoperative Planning\n● STL export supported\nfor general anatomical\nstructures.","● Multi-Planar Reconstruction\nViews\n● 3D Volume Rendering\n● Virtual Panoramic view\nreconstruction\n● Image enhancement and\nmanipulation (Brightness,\nContrast)\n● Segmentation of the jaws\n● Linear, angular, area and\nvolumetric measurements\n● Implant Planning\n● Preoperative software for\nsimulating / evaluating\nsurgical treatment\n● Airway volume\nmeasurement","The differences in\nspecific features\ndo not introduce\nnew questions of\nsafety or\neffectiveness."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251514-p9-t1","doc_id":"K251514","page_num":9,"bbox":[70.5,614.5,565.62,702.5],"n_rows":2,"n_cols":3,"columns":["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Reference Device\nOverjet Charting Assist\n(K241684)\nOverjet Inc."],"rows":[["Criteria","Subject Device\nOverjet CBCT Assist\nOverjet, Inc.","Reference Device\nOverjet Charting Assist\n(K241684)\nOverjet Inc."],["Classification\nRegulation","21 CFR 892.2050, Medical Image\nManagement and Processing System","21 CFR 892.2050, Medical Image Management\nand Processing System"]],"caption_candidate":"Table 2: Comparison to Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251514-p10-t0","doc_id":"K251514","page_num":10,"bbox":[70.5,72.5,563.5,388.5],"n_rows":3,"n_cols":3,"columns":["Intended\nUse/Indicatio\nns for Use","Overjet CBCT Assist is a software for the\nanalysis of dental and craniomaxillofacial\nCone Beam Computed Tomography (CBCT)\nimages. The software utilizes artificial\nintelligence/machine learning algorithms to\nprovide automated segmentations,\nuser-delineated or automated\nmeasurements, and 2D/3D visualizations.\nThese tools are intended to assist dental\nprofessionals in their review and\ninterpretation of CBCT images by facilitating\nanatomical assessment and supporting their\ndiagnostic and treatment planning process.\nThe device is not intended as a replacement\nfor a complete clinician’s review or their\nclinical judgement.","Overjet Charting Assist is a Medical Image\nManagement and Processing System (MIMPS)\nintended to detect natural dental structures\nincluding detection of tooth anatomy (enamel,\npulp), and tooth numbering, as well as dental\nstructures added through past restorative\ntreatments: implants, crowns, endodontic\ntreatment (previous root canal treatment), fillings.\nThe device is intended to assist dental\nprofessionals in producing dental charts based on\nimage analysis. The Overjet Charting Assist\ndetects these findings on bitewing (BW) and\nperiapical (PA) images for patients with primary\nand/or permanent teeth (Ages 5 and above), and\npanoramic (Pano) radiographs for patients with\nonly permanent teeth. The device is not intended\nas a replacement for a complete clinician's review\nor clinical judgment that considers other relevant\ninformation from the image or patient history."],"rows":[["Intended\nUse/Indicatio\nns for Use","Overjet CBCT Assist is a software for the\nanalysis of dental and craniomaxillofacial\nCone Beam Computed Tomography (CBCT)\nimages. The software utilizes artificial\nintelligence/machine learning algorithms to\nprovide automated segmentations,\nuser-delineated or automated\nmeasurements, and 2D/3D visualizations.\nThese tools are intended to assist dental\nprofessionals in their review and\ninterpretation of CBCT images by facilitating\nanatomical assessment and supporting their\ndiagnostic and treatment planning process.\nThe device is not intended as a replacement\nfor a complete clinician’s review or their\nclinical judgement.","Overjet Charting Assist is a Medical Image\nManagement and Processing System (MIMPS)\nintended to detect natural dental structures\nincluding detection of tooth anatomy (enamel,\npulp), and tooth numbering, as well as dental\nstructures added through past restorative\ntreatments: implants, crowns, endodontic\ntreatment (previous root canal treatment), fillings.\nThe device is intended to assist dental\nprofessionals in producing dental charts based on\nimage analysis. The Overjet Charting Assist\ndetects these findings on bitewing (BW) and\nperiapical (PA) images for patients with primary\nand/or permanent teeth (Ages 5 and above), and\npanoramic (Pano) radiographs for patients with\nonly permanent teeth. The device is not intended\nas a replacement for a complete clinician's review\nor clinical judgment that considers other relevant\ninformation from the image or patient history."],["Input Data","3D CBCT volumes (DICOM format)","2D dental radiographs"],["Technology","AI-based algorithms for the detection of\ndental and craniomaxillofacial anatomy, as\nwell as past restorations.","AI-based algorithms for the detection of natural\ndental structures and structures added through\npast restorative treatment."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p5-t0","doc_id":"K251532","page_num":5,"bbox":[109.88,474.85,528.37,552.43],"n_rows":5,"n_cols":12,"columns":["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],"rows":[["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],["","Primary Predicate Device","","","","","","","","","",""],["K234009","","","LLZ, QIH","","","Acorn 3D Software","","","Mighty Oak Medical","",""],["","Subsequent Predicate Device","","","","","","","","","",""],["K141669","","","LLZ","","","Surgimap","","","Nemaris Inc.","",""]],"caption_candidate":"Acorn Segmentation & 3DP Model","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p6-t0","doc_id":"K251532","page_num":6,"bbox":[72.1,357.17,513.07,506.2],"n_rows":4,"n_cols":10,"columns":["","","Automatic","","","Semi-Automatic","","","Manual",""],"rows":[["","","Automatic","","","Semi-Automatic","","","Manual",""],["Definition","Algorithmic with little or no\ndirect human control","","","A combination of\nalgorithmic and direct\nhuman control","","","Directly controlled by a\nhuman","",""],["Tool Type","Machine Learning algorithm\nused to automatically\nsegment individual vertebrae\nand the pelvis","","","Algorithmic based tools that\ndo not incorporate machine\nlearning.","","","Manual tools requiring user\ninput.","",""],["Anatomical\nLocation (s)","Spinal anatomy:\n Thoracic (T1-T12)\n Lumbar (L1-L5)\n Sacrum","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","",""]],"caption_candidate":"musculoskeletal anatomy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p7-t0","doc_id":"K251532","page_num":7,"bbox":[36.14,341.93,575.96,707.74],"n_rows":7,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software & 3DP Models","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],"rows":[["","Device→","","","Acorn 3D Software & 3DP Models","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],["","Features↓","","","(K251532)","","","(K234009)","","","(K141669)",""],["Trade Name","","","Acorn 3D Software(AC-SEG-4009);\nAcorn 3DP Model (AC-101-XX)","","","Acorn 3D Software (AC-SEG-4009); Acorn 3DP\nModel (AC-101-XX)","","","Surgimap","",""],["Common\nName","","","Image processing system","","","Image processing system","","","Picture Archiving and\nCommunication System (PACS)","",""],["Premarket\nnotification","","","K251532","","","K234009","","","K141669","",""],["Manufacturer","","","Mighty Oak Medical","","","Mighty Oak Medical","","","Nemaris Inc.","",""],["Indications for\nUse Statement","","","Acorn 3D Software is a modular image\nprocessing software intended for use as an\ninterface for visualization of medical images,\nsegmentation, treatment planning, and\nproduction of an output file.\nThe Acorn 3D Segmentation module is intended\nfor use as a software interface and image\nsegmentation system for the transfer of CT or\nCTA medical images to an output file. Acorn\nSegmentation is also intended for measuring\nand treatment planning. The Acorn\nSegmentation output can also be used for the\nfabrication of physical replicas of the output file\nusing additive manufacturing methods, Acorn\n3DP Models. The physical replica can be used\nfor diagnostic purposes in the field of\nmusculoskeletal and craniomaxillofacial\napplications.\nThe Acorn 3D Trajectory Automation module\nmay be used to plan pedicle screw placement\nin the spine in pediatric and adult patients.\nAcorn 3D Software and 3DP Models should be\nused in conjunction with expert clinical\njudgment.","","","Acorn Segmentation is intended for use as a\nsoftware interface and image segmentation\nsystem for the transfer of CT or CTA medical\nimages to an output file. Acorn Segmentation is\nalso intended for measuring and treatment\nplanning. The Acorn Segmentation output can\nalso be used for the fabrication of physical\nreplicas of the output file using additive\nmanufacturing methods, Acorn 3DP Models. The\nphysical replica can be used for diagnostic\npurposes in the field of musculoskeletal and\ncraniomaxillofacial applications.\nAcorn Segmentation and 3DP Models should be\nused in conjunction with expert clinical\njudgment.","","","The Surgimap software assists\nhealthcare professionals in\nviewing, storing, and measuring\nimages as well as planning\northopedic surgeries. The device\nallows service providers to\nperform generic as well as\nspecialty measurements of the\nimages, and to plan surgical\nprocedures. The device also\nincludes tools for measuring\nanatomical components for\nplacement of surgical implants,\nand offer online synchronization\nof the database with the\npossibility to share data among\nSurgimap users. Clinical judgment\nand experience are required to\nproperly use the software.","",""]],"caption_candidate":"Table 1: Comparison of devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p8-t0","doc_id":"K251532","page_num":8,"bbox":[36.14,72.36,575.96,677.5],"n_rows":10,"n_cols":18,"columns":["","Device→","","","Acorn 3D Software & 3DP Models\n(this submission)","","","","","","","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],"rows":[["","Device→","","","Acorn 3D Software & 3DP Models\n(this submission)","","","","","","","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],["","Features↓","","","","","","","","","","","","(K234009)","","","(K141669)",""],["General\nintended use","","","Acorn 3D Software is an image processing\nsoftware that allows the user to import, visualize\nand segment medical images, check and\ncorrect the segmentations, and create digital\n3D models.","","","","","","","","","Acorn Segmentation is an image processing\nsoftware that allows the user to import, visualize\nand segment medical images, check and\ncorrect the segmentations, and create digital\n3D models.","","","Surgimap is image analysis and\nsurgical planning software\nintended for use by medical\nprofessionals to view, measure,\nand annotate medical images\n(including DICOM images) for\ndiagnostic and preoperative\nplanning purposes.","",""],["Product\nClassification","","","Automated radiological image processing\nsoftware","","","","","","","","","Automated radiological image processing\nsoftware","","","Medical image management\nand processing system.","",""],["Regulatory\nClass","","","Class II","","","","","","","","","Class II","","","Class II","",""],["Classification","","","892.2050","","","","","","","","","892.2050","","","892.2050","",""],["Product Code","","","QIH, LLZ","","","","","","","","","QIH, LLZ","","","LLZ","",""],["Device\nDescription","","","Acorn 3D Software is an image processing\nsoftware that allows the user to import, visualize\nand segment medical images, check and\ncorrect the segmentations, and create digital\n3D models. The models can be used in Acorn 3D\nSoftware for measuring, treatment planning and\nproducing an output file to be used for additive\nmanufacturing (3D printing). Acorn 3D Software\nis structured as a modular package.\nThis includes the following functionality:\n Importing medical images in DICOM\nformat\n Viewing images and DICOM data\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools or fully\nautomatic algorithms\n Verifying and editing a region of interest\n Calculating a digital 3D model and\nediting the model\n Measuring on images and 3D models\n Exporting 3D models to third-party\npackages\n Planning pedicle screw placement\nThe Acorn 3D Segmentation module contains\nboth machine learning based auto\nsegmentation as well as semi-automatic and\nmanual segmentation tools. The auto-\nsegmentation tool is only intended to be used\nfor thoracic and lumbar regions of the spine (T1-\nT12 and L1-L5) and the pelvis (sacrum). Semi-\nautomatic and manual segmentation tools are\nintended to be used for all musculoskeletal\nanatomy.\nSemi- Manual\nAutomatic\nAutomatic\nAlgorithmic A\nDirectly\nwith little or combination\nnoitinifeD controlled no direct of algorithmic\nby a\nhuman and direct\nhuman\ncontrol human control","","","","","","","","","Acorn Segmentation is an image processing\nsoftware that allows the user to import, visualize\nand segment medical images, check and\ncorrect the segmentations, and create digital\n3D models. The models can be used in Acorn\nSegmentation for measuring, treatment\nplanning and producing an output file to be\nused for additive manufacturing (3D printing).\nAcorn Segmentation is structured as a modular\npackage.\nThis includes the following functionality:\n Importing medical images in DICOM\nformat\n Viewing images and DICOM data\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools or fully\nautomatic algorithms\n Verifying and editing a region of interest\n Calculating a digital 3D model and\nediting the model\n Measuring on images and 3D models\n Exporting 3D models to third-party\npackages\nThe Acorn Segmentation module contains both\nmachine learning based auto segmentation as\nwell as semi-automatic and manual\nsegmentation tools. The auto-segmentation tool\nis only intended to be used for thoracic and\nlumbar regions of the spine (T1-T12 and L1-L5)\nand the pelvis (sacrum). Semi-automatic and\nmanual segmentation tools are intended to be\nused for all musculoskeletal anatomy.\nSemi- Manual\nAutomatic\nAutomatic\nAlgorithmic A\nDirectly\nwith little or combination\nnoitinifeD controlled no direct of algorithmic\nby a\nhuman and direct\nhuman\ncontrol human control","","","Surgimap is a software\napplication intended for use by\ntrained medical professionals,\nincluding physicians, to view,\nmeasure, and annotate medical\nimages (including DICOM\nimages) for diagnostic and\nplanning purposes.\nSurgimap provides tools for\northopedic surgical planning\nsuch as templating and\nmeasuring angles, lengths, and\nother relevant anatomical data.\nThe software may also be used to\ncreate preoperative plans that\ncan be shared among\nhealthcare professionals.\nIt is intended as a planning and\nimaging tool and not for primary\nimage interpretation or as a sole\ndiagnostic device.","",""],["","","","","","","","Automatic","","Semi-\nAutomatic","","Manual","","","","","",""],["","","","","","noitinifeD","","Algorithmic\nwith little or\nno direct\nhuman\ncontrol","A\ncombination\nof algorithmic\nand direct\nhuman control","","","Directly\ncontrolled\nby a\nhuman","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p8-t1","doc_id":"K251532","page_num":8,"bbox":[297.29,596.37,442.2,668.69],"n_rows":2,"n_cols":5,"columns":["Automatic","","Semi-\nAutomatic","","Manual"],"rows":[["Automatic","","Semi-\nAutomatic","","Manual"],["Algorithmic\nwith little or\nno direct\nhuman\ncontrol","A\ncombination\nof algorithmic\nand direct\nhuman control","","","Directly\ncontrolled\nby a\nhuman"]],"caption_candidate":"anatomy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p9-t0","doc_id":"K251532","page_num":9,"bbox":[36.15,72.36,575.95,712.54],"n_rows":6,"n_cols":21,"columns":["","Device→","","","Acorn 3D Software & 3DP Models\n(this submission)","","","","","","","Acorn 3D Software & 3DP Models","","","","","","","","Surgimap",""],"rows":[["","Device→","","","Acorn 3D Software & 3DP Models\n(this submission)","","","","","","","Acorn 3D Software & 3DP Models","","","","","","","","Surgimap",""],["","Features↓","","","","","","","","","","(K234009)","","","","","","","","(K141669)",""],["","","","Machine\nLearning\nalgorithm Algorithmic\nused to based tools Manual\nautomaticall that do not tools\nepyT y segment incorporate requiring\nindividual machine user input.\nvertebrae learning.\nlooT\nand the\npelvis\nMusculoske\nletal &\n)s( Musculoskelet craniomaxil\nnoitacoL Spinal al & lofacial\nanatomy: craniomaxillof\nbone:\n Thoracic acial bone:\n Short\n(T1-T12)  Short\n Long\nlacimotanA  Lumbar  Long\n Flat\n(L1-L5)  Flat\n Sesam\n Sacrum  Sesamoid\noid\n Irregular\n Irregul\nar\nAcorn 3DP Model is an additively manufactured\nphysical replica of the virtual 3D model\ngenerated in Acorn Segmentation. The output\nfile from Acorn Segmentation is used to\nadditively manufacture the Acorn 3DP Model.\nThe Acorn 3D Trajectory Automation contains\ndedicated fully automatic algorithms for\nplanning pedicle screw trajectories. The\nalgorithms are only intended to be used for the\nthoracic and lumbar regions of the spine (T1-T12\nand L1-L5). The output file from Acorn 3D\nTrajectory Automation contains information\nrelevant to pedicle screw placement surgery,\nincluding entry points, end points, and screw\nsizes of planned screws.","","epyT\nlooT","","Machine\nLearning\nalgorithm\nused to\nautomaticall\ny segment\nindividual\nvertebrae\nand the\npelvis","Algorithmic\nbased tools\nthat do not\nincorporate\nmachine\nlearning.","Manual\ntools\nrequiring\nuser input.","Machine\nLearning\nalgorithm\nAlgorithmic\nused to\nbased tools Manual\nautomatic\nthat do not tools\nally\nincorporate requiring\nepyT segment machine user input.\nindividual\nlearning.\nvertebrae\nlooT\nand the\npelvis\nMusculoske\nletal &\n)s( Musculoskelet craniomaxil\nnoitacoL Spinal al & lofacial\nanatomy: craniomaxillof\nbone:\n Thoracic acial bone:\n Short\n(T1-T12)  Short\n Long\nlacimotanA  Lumbar  Long\n Flat\n(L1-L5)  Flat\n Sesam\n Sacrum  Sesamoid\noid\n Irregular\n Irregul\nar\nAcorn 3DP Model is an additively manufactured\nphysical replica of the virtual 3D model\ngenerated in Acorn Segmentation. The output\nfile from Acorn Segmentation is used to\nadditively manufacture the Acorn 3DP Model.","","epyT\nlooT","","Machine\nLearning\nalgorithm\nused to\nautomatic\nally\nsegment\nindividual\nvertebrae\nand the\npelvis","Algorithmic\nbased tools\nthat do not\nincorporate\nmachine\nlearning.","Manual\ntools\nrequiring\nuser input.","","","",""],["","","","","",")s(\nnoitacoL\nlacimotanA","","Spinal\nanatomy:\n Thoracic\n(T1-T12)\n Lumbar\n(L1-L5)\n Sacrum","Musculoskelet\nal &\ncraniomaxillof\nacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","Musculoske\nletal &\ncraniomaxil\nlofacial\nbone:\n Short\n Long\n Flat\n Sesam\noid\n Irregul\nar","","","","","","","","","","",""],["","","","","","","","","","","","",")s(\nnoitacoL\nlacimotanA","","Spinal\nanatomy:\n Thoracic\n(T1-T12)\n Lumbar\n(L1-L5)\n Sacrum","Musculoskelet\nal &\ncraniomaxillof\nacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","Musculoske\nletal &\ncraniomaxil\nlofacial\nbone:\n Short\n Long\n Flat\n Sesam\noid\n Irregul\nar","","","",""],["Technological\ncharacteristics","","","Acorn 3D Software is a standalone modular\nsoftware package. This software package\nincludes, but is not limited to, the following\nfunctions:\nImage import\n Importing medical images in DICOM\nformat (e.g. CT and CTA)\nImage Processing\n Processing of images with common noise-\nreduction filters\n Editing of spatial arrangement of images\nVisualization\n Viewing images and DICOM data\nSegmentation\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools\n Segmenting specific vertebral anatomy\nusing machine-learning-based fully\nautomatic algorithms\n Verifying and editing a region of interest\nMeasurement\n Measuring on images and 3D models\nData Export\n Machine-readable format (e.g. JSON and\nSTL)\n Project Files (proprietary file format specific\nto the software)","","","","","","","Acorn Segmentation is a standalone modular\nsoftware package. This module includes, but is\nnot limited to the following functions:\nImage Import\n Importing medical images in DICOM\nformat (e.g. CT and CTA)\nImage Processing\n Processing of images with common noise-\nreduction filters\n Editing of spatial arrangement of images\nVisualization\n Viewing images and DICOM data\nSegmentation\n Selecting a region of interest using generic\nsegmentation tools\n Segmenting specific anatomy using\ndedicated semi-automatic tools\n Segmenting specific vertebral anatomy\nusing machine-learning-based fully\nautomatic algorithms\n Verifying and editing a region of interest\nMeasurement\n Measuring on images and 3D models\nData Export\n Machine-readable format (e.g. STL)\n Project Files (proprietary file format specific\nto the software)","","","","","","","","Surgimap software includes the\nfollowing functions:\nImage Import\n Importing medical images in\nDICOM format (e.g. CT,\nCTA, MRI, etc.)\n Standard formats (JPEG, TIFF,\nPNG, PPT…)\nImage Processing\n Processing of images with\ncommon noise-reduction\nfilters\n Editing of spatial\narrangement of images\nVisualization\n Viewing images and DICOM\ndata\nSegmentation\n None\nMeasurement\n Measuring on images\nData Export\n Machine-readable format\n(e.g. CSV and DICOM)\n Project Files (proprietary file\nformat specific to the\nsoftware)","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251532-p10-t0","doc_id":"K251532","page_num":10,"bbox":[36.14,72.36,575.96,709.9],"n_rows":6,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software & 3DP Models","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],"rows":[["","Device→","","","Acorn 3D Software & 3DP Models","","","Acorn 3D Software & 3DP Models","","","Surgimap",""],["","Features↓","","","(this submission)","","","(K234009)","","","(K141669)",""],["","","","3D Models\n Calculating a digital 3D model and editing\nthe model\n Smoothing a 3D model\n Importing 3D models\nTreatment Planning\n Importing of third-party STLs to visualize\nplanned interactions with anatomy as\nrepresented in DICOM images\n Generic Implants\no Pedicle Screw Implant\nOther features\n Using a collection of images and masks as\na training dataset for machine-learning\nsegmentation algorithm","","","3D Models\n Calculating a digital 3D model and editing\nthe model\n Smoothing a 3D model\n Importing 3D models\nTreatment Planning\n Importing of third-party STLs to visualize\nplanned interactions with anatomy as\nrepresented in DICOM images\nOther features\n Using a collection of images and masks as\na training dataset for machine-learning\nsegmentation algorithm","",""," Standard formats (JPG, PNG,\nTIFF, PDF)\n3D Models\n None\nTreatment Planning\n Procedures\no Wedge\nOsteotomy(ex:SPO,PSO)\no Opening Osteotomy\no Resect Osteotomy\no Un-Slip (i.e. spondylolisthesis\ncorrection)\no Anatomical Marker\n Generic Implants\no Screw Implant\no Reference Line for Screw\no Interbody Spacer o\nFreehand Rod\no SA Rod\no Coronal Free hand\n Vendor Specific Implant\no Globus Medical Spacer\nTemplate\no Globus Rod\no K2M Interbody Spacer\nTemplate\no K2M BACS Patient Specific\nRod\no K2M Pre-Bent Rod Template\no K2M Screw\nOther features\n Various","",""],["Pedicle Screw\nPlanning","",""," Surgeon Inputs / Preferences\no Screw Size\no Trajectory Angle\no Tulip Position\no Breach Criteria\n Automatic Optimization\n Review against patient imaging","","","N/A","",""," Surgeon Inputs /\nPreferences\no Screw Size\no Trajectory Angle\no Entry and End Point\n Manual Optimization\n Review against patient\nimaging","",""],["Physical Model","","","The Acorn 3D Segmentation module output can\nbe used for the fabrication of physical replicas\nof the output file using additive manufacturing\nmethods. The physical replica can be used for\ndiagnostic purposes in the field of orthopedic\nand musculoskeletal applications.","","","The Acorn Segmentation output can be used for\nthe fabrication of physical replicas of the output\nfile using additive manufacturing methods. The\nphysical replica can be used for diagnostic\npurposes in the field of orthopedic and\nmusculoskeletal applications.","","","N/A","",""],["Intended User","","","The Acorn 3D Segmentation module can be\nused by biomedical engineers or personnel\nequivalent by training or experience. Their\nresults should be used in conjunction with expert\nclinical judgement.\nThe Acorn 3D Trajectory Automation module is\nintended for use by medical professionals, such\nas clinicians and surgeons, who are trained in\nspinal procedures and the interpretation of\ndiagnostic imaging.\nBe advised that the quality of medical images\ndetermines the accuracy of the 3D model in\nAcorn 3D Software. Scanning protocols are left\nto the discretion of the user; however, we\nrecommend that industry standards are\nreferenced and followed. Only images\nobtained less than six months before should be\nused for planning and/or evaluating treatment\noptions.","","","Acorn Segmentation can be used by\nbiomedical engineers or personnel equivalent\nby training or experience. Their results should be\nused in conjunction with expert clinical\njudgement.\nBe advised that the quality of medical images\ndetermines the accuracy of the 3D model in\nAcorn 3D Software. Scanning protocols are left\nto the discretion of the user; however, we\nrecommend that industry standards are\nreferenced and followed. Only images\nobtained less than six months before should be\nused for planning and/or evaluating treatment\noptions.","","","Surgimap is intended as a\ndecision support system for\npersons who have received\nappropriate medical training, and\nshould not be used as a sole\nbasis for making clinical\ndecisions pertaining to patient\ndiagnosis, care, or management.\nAll information derived from the\nsoftware must be clinically\nreviewed regarding its plausibility\nbefore use in treating patients.\nAny derivation of the application\nof medical information from the\nprogram, other than the original\ndesign or intended use thereof, is\nnot advised and considered a\nmisuse of the software product.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251533-p3-t0","doc_id":"K251533","page_num":3,"bbox":[257.72,209.29,570.36,306.62],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251533-p6-t0","doc_id":"K251533","page_num":6,"bbox":[78.11,551.21,544.22,714.91],"n_rows":11,"n_cols":3,"columns":["Parameter","Rapid SDH (K232436)\nPredicate Device","Rapid OH – Subject Device"],"rows":[["Parameter","Rapid SDH (K232436)\nPredicate Device","Rapid OH – Subject Device"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Intended Use/\nIndications for\nUse","Rapid SDH is a radiological\ncomputer aided triage and\nnotification software indicated for\nuse in the triage and notification of\nhemispheric SDH in non-enhanced\nhead images. The device is intended\nto assist trained radiologists in","Rapid OH is a radiological computer"],["","","aided triage and notification software"],["","","indicated for suspicion of Obstructive"],["","","Hydrocephalus (OH) in non-enhanced"],["","","CT head images of adult patients. The"],["","","device is intended to assist trained"],["","","clinicians in workflow prioritization"],["","",""]],"caption_candidate":"submission.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251533-p7-t0","doc_id":"K251533","page_num":7,"bbox":[78.1,76.51,543.95,714.19],"n_rows":29,"n_cols":3,"columns":["","workflow triage by providing\nnotification of suspected findings of\nhemispheric Subdural Hemorrhage\n(SDH) in head CT images.\nRapid SDH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\nsuspected hemispheric SDH on a\nserver or standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected hemispheric SDH\nfindings. Notifications include\ncompressed preview images, that\nare meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the\noriginal medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of Rapid SDH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","triage by providing notification of"],"rows":[["","workflow triage by providing\nnotification of suspected findings of\nhemispheric Subdural Hemorrhage\n(SDH) in head CT images.\nRapid SDH uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\nsuspected hemispheric SDH on a\nserver or standalone desktop\napplication in parallel to the\nongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with\nsuspected hemispheric SDH\nfindings. Notifications include\ncompressed preview images, that\nare meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the\noriginal medical image and is not\nintended to be used as a diagnostic\ndevice.\nThe results of Rapid SDH are\nintended to be used in conjunction\nwith other patient information and\nbased on professional judgment, to\nassist with triage/prioritization of\nmedical images. Notified clinicians\nare responsible for viewing full\nimages per the standard of care.","triage by providing notification of"],["","","suspected findings in head CT"],["","","images."],["","","Rapid OH uses an artificial"],["","","intelligence algorithm to analyze"],["","","images and highlight cases with"],["","","suspected OH on a server or"],["","","standalone desktop application in"],["","","parallel to the ongoing standard of"],["","","care image interpretation. The user is"],["","","presented with notifications for cases"],["","","with suspected OH"],["","","findings. Notifications include"],["","","compressed preview images, that are"],["","","meant for informational purposes only"],["","","and not intended for diagnostic use"],["","","beyond notification. The device does"],["","","not alter the original medical image"],["","","and is not intended to be used as a"],["","","diagnostic device."],["","","The results of Rapid OH are intended"],["","","to be used in conjunction with other"],["","","patient information and based"],["","","on professional judgment, to assist"],["","","with triage/prioritization of medical"],["","","images. Notified clinicians are"],["","","responsible for viewing full images"],["","","per the standard of care."],["","","Contraindications/Limitations/Excl\nusions:\n• Rapid OH is intended for use\nfor adult patients.\n• Input data image series\ncontaining excessive patient\nmotion or metal implants\nmay impact module analysis\naccuracy, robustness and\nquality.\n• Ventriculoperitoneal shunts\nare contraindicated\nExclusions:\n• Series with missing slices or\nimproperly ordered slices\n• data acquired at x-ray tube\nvoltage < 100kVp or >\n140kVp."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251533-p8-t0","doc_id":"K251533","page_num":8,"bbox":[78.11,76.49,544.33,289.33],"n_rows":8,"n_cols":3,"columns":["","","• data not representing human\nhead or head/neck\nanatomical regions"],"rows":[["","","• data not representing human\nhead or head/neck\nanatomical regions"],["Input Data\nRequirements","Non-Contrast CT images","Non-Contrast CT images"],["DICOM Compliance","Yes","Yes"],["Anatomical Focus","Head","Head"],["SW","AI ML","AI ML"],["Removal of Cases\nfrom worklist queue","No","No"],["Outputs","Notifications, Reports, DICOM\nSecondary Capture Series","Notifications, Reports, DICOM\nSecondary Capture Series"],["Notification/\nPrioritization","PACS, Workstation, email, mobile","PACS, Workstation, email, mobile"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p7-t0","doc_id":"K251590","page_num":7,"bbox":[72.48,140.4,522.72,767.28],"n_rows":12,"n_cols":3,"columns":["Substantial Equivalence Table","",""],"rows":[["Substantial Equivalence Table","",""],["Comparison Feature","Predicate Device: ContaCT","Subject Device: Methinks CTA Stroke"],["Product Code","QAS","QAS"],["Regulation","21 CFR §892.2080","21 CFR §892.2080"],["Indications for Use","ContaCT is a notification-only, parallel workflow\ntool for use by hospital networks and trained\nclinicians to identify and communicate images of\nspecific patients to a specialist, 1 independent of\nstandard of care workflow.\nContaCT uses an artificial intelligence algorithm\nto analyze images for findings suggestive of a\npre-specified clinical condition and to notify an\nappropriate medical specialist of these findings\nin parallel to standard of care image\ninterpretation. Identification of suspected\nfindings is not for diagnostic use beyond\nnotification. Specifically, the device analyzes CT\nangiogram images of the brain acquired in the\nacute setting,and sends notifications to a\nneurovascular specialist that a suspected large\nvessel occlusion has been identified and\nrecommends review of those images. Images\ncan be previewed through a mobile application.\nImages that are previewed through the mobile\napplication are compressed and are for\ninformational purposes only and not intended for\ndiagnostic use beyond notification. Notified\nclinicians are responsible for viewing non-\ncompressed images on a diagnostic viewer and\nengaging in appropriate patient evaluation and\nrelevant discussion with a treating physician\nbefore making care-related decisions or\nrequests. ContaCT is limited to analysis of\nimaging data and should not be used in-lieu of\nfull patient evaluation or relied upon to make or\nconfirm diagnosis.","Methinks CTA Stroke is a radiological computer\naided triage and notification software, parallel\nworkflow tool for use by hospital networks and\ntrained clinicians to identify and communicate\nimages of specific patients to a specialist,\nindependent of standard of care workflow.\nMethinks CTA Stroke uses an artificial\nintelligence algorithm to analyze images for\nfindings suggestive of a pre-specified clinical\ncondition and to notify an appropriate medical\nspecialist of these findings in parallel to standard\nof care image interpretation.\nIdentification of suspected findings is not for\ndiagnostic use beyond notification.\nSpecifically, the device analyzes CT angiogram\nimages of the brain acquired in the acute setting,\nand sends to PACS and/or notifications to a\nneurovascular specialist that a suspected large\nvessel occlusion has been identified and\nrecommends review of those images. Images\ncan be previewed through an image viewer.\nMethinks CTA Stroke is intended to analyze\nterminal ICA, MCA-M1 and MCA-M2 vessels for\nLVOs.\nImages that are previewed are for informational\npurposes only and not intended for diagnostic\nuse beyond notification.\nNotified clinicians are responsible for viewing\nnon-compressed images on a diagnostic viewer\nand engaging in appropriate patient evaluation\nand relevant discussion with a treating physician\nbefore making care-related decisions or\nrequests. Methinks CTA Stroke is limited to\nanalysis of imaging data and should not be used\nin-lieu of full patient evaluation or relied upon to\nmake or confirm diagnosis."],["User","Trained Clinicians","Trained Physicians"],["Anatomy","Head","Head"],["Input Data","CT Angiography images","CT Angiography images"],["Technology","Artificial intelligence/ Neural Network","AI/ML/Neural Network"],["Segmentation of ROI","The device does not highlight or direct a user’s\nattention to a specific location in the image file.","The device does not highlight or direct a user’s\nattention to a specific location in the image file."],["Preview Images","Images that are previewed are for informational\npurposes only and not intended for diagnostic\nuse beyond notification.","Images that are previewed are for informational\npurposes only and not intended for diagnostic\nuse beyond notification."],["Annotation/Localization","The device does not mark, highlight, or direct\nusers’ attention to a specific location in the","The device does not mark, highlight, or direct\nusers’ attention to a specific location in the"]],"caption_candidate":"Table 1. Substantial Equivalence Table.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p8-t0","doc_id":"K251590","page_num":8,"bbox":[72.48,72.48,522.72,198.96],"n_rows":5,"n_cols":3,"columns":["","original image.","original image."],"rows":[["","original image.","original image."],["Prioritization\nNotification","Yes","Yes"],["Clinical SoC Workflow","In parallel to","In parallel to"],["Technical Pipeline","Large Vessel Occlusion (LVO) Notification (one\noutput)","Large Vessel Occlusion (LVO) Notification (one\noutput)"],["Removal of Cases\nfrom SoC review","No","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p9-t0","doc_id":"K251590","page_num":9,"bbox":[72.88,83.76,524.48,114.72],"n_rows":2,"n_cols":4,"columns":["Parameter","Mean","95% CI Lower","95% CI Upper"],"rows":[["Parameter","Mean","95% CI Lower","95% CI Upper"],["Time to notification of CTA-LVO (minutes)","3.30","3.23","3.36"]],"caption_candidate":"Table 2. Time to notification of Methinks CTA Stroke.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p9-t1","doc_id":"K251590","page_num":9,"bbox":[72.88,223.2,524.48,361.92],"n_rows":5,"n_cols":6,"columns":["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Gender","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Male","Sensitivity","53","96.2%","87.0%","99.5%"],["","Specificity","115","92.2%","85.7%","96.4%"],["Female","Sensitivity","57","100.0%","93.7%","100.0%"],["","Specificity","111","91.0%","84.1%","95.6%"]],"caption_candidate":"Table 3. Performance metrics CTA-LVO by Gender.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p9-t2","doc_id":"K251590","page_num":9,"bbox":[72.88,388.08,524.48,585.6],"n_rows":7,"n_cols":6,"columns":["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Age","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["< 50 years","Sensitivity","8","100.0%","63.1%","100.0%"],["","Specificity","40","97.5%","86.8%","99.9%"],["50 - 70 years","Sensitivity","41","97.6%","87.1%","99.9%"],["","Specificity","106","92.5%","85.7%","96.7%"],["> 70 years","Sensitivity","61","98.4%","91.2%","100.0%"],["","Specificity","80","87.5%","78.2%","93.8%"]],"caption_candidate":"Table 4. Performance metrics CTA-LVO by Age.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p9-t3","doc_id":"K251590","page_num":9,"bbox":[72.88,612.0,524.48,729.84],"n_rows":4,"n_cols":6,"columns":["Vendor\nmachine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Vendor\nmachine","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Siemens","Sensitivity","35","97.1%","85.1%","99.9%"],["","Specificity","83","92.8%","84.9%","97.3%"],["General Electric","Sensitivity","20","100.0%","83.2%","100.0%"]],"caption_candidate":"Table 5. Performance metrics CTA-LVO by vendor machine.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p10-t0","doc_id":"K251590","page_num":10,"bbox":[72.96,72.24,524.32,219.84],"n_rows":5,"n_cols":6,"columns":["","Specificity","31","83.9%","66.3%","94.5%"],"rows":[["","Specificity","31","83.9%","66.3%","94.5%"],["Philips","Sensitivity","34","97.1%","84.7%","99.9%"],["","Specificity","82","91.5%","83.2%","96.5%"],["Toshiba /\nCanon","Sensitivity","21","100.0%","83.9%","100.0%"],["","Specificity","30","96.7%","82.8%","99.9%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p10-t1","doc_id":"K251590","page_num":10,"bbox":[77.96,78.25,511.87,730.57],"n_rows":50,"n_cols":8,"columns":["","Specificity","31","83.9%","66.3%","","94.5%",""],"rows":[["","Specificity","31","83.9%","66.3%","","94.5%",""],["","","","","","","",""],["Philips","Sensitivity","34","97.1%","84.7%","","99.9%",""],["","","","","","","",""],["","Specificity","82","91.5%","83.2%","","96.5%",""],["","","","","","","",""],["Toshiba /","Sensitivity","21","100.0%","83.9%","","100.0%",""],["Canon","","","","","","",""],["","","","","","","",""],["","Specificity","30","96.7%","82.8%","","99.9%",""],["","","","","","","",""],["","Table 6. Perf","ormance metrics","CTA-LVO by LVO","subgroup.","","",""],["","","","","","","",""],["LVO","Measure","N","Estimate","Lower 95%","CI","Upper 95%","CI"],["subgroups","","","","","","",""],["","","","","","","",""],["ICA","Sensitivity","35","100.0%","90.0%","","100.0%",""],["","","","","","","",""],["","Specificity","0","-","-","","-",""],["","","","","","","",""],["MCA-M1","Sensitivity","44","100.0%","92.0%","","100.0%",""],["","","","","","","",""],["","Specificity","0","-","-","","-",""],["","","","","","","",""],["ICA + MCA-M1","Sensitivity","76","100.0%","95.3%","","100.0%",""],["","","","","","","",""],["","Specificity","0","-","-","","-",""],["","","","","","","",""],["MCA-M2","Sensitivity","25","92.0%","74.0%","","99.0%",""],["","","","","","","",""],["","Specificity","0","-","-","","-",""],["","","","","","","",""],["","Table 7. Perf","ormance metrics","CTA-LVO by slice","thickness.","","",""],["","","","","","","",""],["Slice thickness","Measure","N","Estimate","Lower 95%","CI","Upper 95%","CI"],["","","","","","","",""],["0.3mm ≤ slice","Sensitivity","91","97.8%","92.3%","","99.7%",""],["thickness ≤","","","","","","",""],["1mm","Specificity","198","92.9%","88.4%","","96.1%",""],["","","","","","","",""],["1mm < slice","Sensitivity","19","100.0%","82.4%","","100.0%",""],["thickness ≤","","","","","","",""],["1.3mm","Specificity","28","82.1%","63.1%","","93.9%",""],["","","","","","","",""],["","Table 8. Perfor","mance metrics CT","A-LVO by non-LV","O subgroup",".","",""],["","","","","","","",""],["Non-LVO","Measure","N","Estimate","Lower 95%","CI","Upper 95%","CI"],["subgroups","","","","","","",""],["","","","","","","",""],["Tumors","Sensitivity","0","-","-","","-",""]],"caption_candidate":"Specificity","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251590-p10-t2","doc_id":"K251590","page_num":10,"bbox":[72.96,530.88,524.32,658.32],"n_rows":5,"n_cols":6,"columns":["Slice thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Slice thickness","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["0.3mm ≤ slice\nthickness ≤\n1mm","Sensitivity","91","97.8%","92.3%","99.7%"],["","Specificity","198","92.9%","88.4%","96.1%"],["1mm < slice\nthickness ≤\n1.3mm","Sensitivity","19","100.0%","82.4%","100.0%"],["","Specificity","28","82.1%","63.1%","93.9%"]],"caption_candidate":"Table 7. Performance metrics CTA-LVO by slice thickness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p10-t3","doc_id":"K251590","page_num":10,"bbox":[72.96,684.72,524.32,740.64],"n_rows":2,"n_cols":6,"columns":["Non-LVO\nsubgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],"rows":[["Non-LVO\nsubgroups","Measure","N","Estimate","Lower 95% CI","Upper 95% CI"],["Tumors","Sensitivity","0","-","-","-"]],"caption_candidate":"Table 8. Performance metrics CTA-LVO by non-LVO subgroup.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251590-p11-t0","doc_id":"K251590","page_num":11,"bbox":[72.96,72.24,523.68,352.8],"n_rows":11,"n_cols":6,"columns":["","Specificity","2","100.0%","15.8%","100.0%"],"rows":[["","Specificity","2","100.0%","15.8%","100.0%"],["Stenosis > 51%","Sensitivity","0","-","-","-"],["","Specificity","27","74.1%","53.7%","88.9%"],["Intracranial\nHemorrhage\n(ICH)","Sensitivity","0","-","-","-"],["","Specificity","3","100.0%","29.2%","100.0%"],["Other Acute\nIschemic\nEvents","Sensitivity","0","-","-","-"],["","Specificity","61","78.7%","66.3%","88.1%"],["Chronic Lesions","Sensitivity","0","-","-","-"],["","Specificity","101","86.1%","77.8%","92.2%"],["No Findings\n(none of the\nabove)","Sensitivity","0","-","-","-"],["","Specificity","162","96.3%","92.1%","98.6%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251602-p6-t0","doc_id":"K251602","page_num":6,"bbox":[89.02,287.17,421.94,451.42],"n_rows":9,"n_cols":6,"columns":["Trade Name","","","Alphenix, INFX-8000V/B, INFX-8000V/S, V9.5","",""],"rows":[["Trade Name","","","Alphenix, INFX-8000V/B, INFX-8000V/S, V9.5","",""],["","Marketed by","","","Canon Medical Systems USA, Inc.",""],["","510(k) Number","","","K233107",""],["","Clearance Date","","","August 30, 2024",""],["Common Name","","","Interventional Fluoroscopic X-ray System","",""],["Classification Name","","","Image-Intensified Fluoroscopic X-ray System","",""],["","Regulation Number","","","21 CFR 892.1650",""],["Regulation Class","","","Class II","",""],["","Product Code","","","OWB",""]],"caption_candidate":"13. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251602-p7-t0","doc_id":"K251602","page_num":7,"bbox":[83.59,322.31,529.87,486.31],"n_rows":7,"n_cols":9,"columns":["","","","","Predicate Device","","","Subject Device",""],"rows":[["","","","","Predicate Device","","","Subject Device",""],["","Device Name, Model","","","Alphenix, INFX-8000V/B,","","","Alphenix, INFX-8000V/B, INFX-8000V/S,",""],["","Number","","","INFX-8000V/S, V9.5","","","V9.6 with αEvolve Imaging",""],["","510(k) Number","","","K233107","","","This submission",""],["Software to support\nαEvolve Imaging","","","Not Available","","","Available","",""],["Stylish Design Cover\nXGSD-120H/B1 (/BU\nfor upgrade)","","","Not Available","","","Available","",""],["Deep Learning Server\nXIDF-DLS801 for\nαEvolve Imaging","","","Not Available","","","Available","",""]],"caption_candidate":"predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p4-t0","doc_id":"K251610","page_num":4,"bbox":[19.08,19.44,593.04,435.84],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK251610 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK251610 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K251610",""],["Please provide the device trade name(s).","",""],["qER-CTA (v1 .0)","",""],["Please provide your Indications for Use below.","","?"],["qER-CTA is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to\nidentify and communicate images of specific patients to a specialist, independent of the standard of care\nworkflow. qER-CTA uses a deep learning algorithm to analyze images for findings suggestive of a pre-\nspecified clinical condition and to notify an appropriate medical specialist in parallel to standard of care\nimage interpretation. Identification of suspected findings is not for diagnostic use beyond notification.\nSpecifically, the device analyses CT angiogram images of the brain acquired in the acute setting and sends\nnotifications to a neurovascular specialist that a suspected large vessel occlusion has been identified,\nrecommending review of those images. Images can be previewed through a mobile application. qER-CTA is\nintended to analyze the internal carotid artery (ICA) and M1 segment of the middle cerebral artery (MCA) for\nLVOs on CTA scans of adults (2:: 22 years of age). Images previewed through the mobile application are\ncompressed and for informational purposes only, not intended for diagnostic use beyond notification.\nNotified clinicians are responsible for viewing non-compressed images on a diagnostic viewer, conducting\nappropriate patient evaluation, and engaging in relevant discussions with the treating physician before\nmaking care-related decisions or requests. qER-CTA is limited to the analysis of imaging data and should\nnot be used as a substitute for full patient evaluation or relied upon to make or confirm a diaQnosis.","",""],["Please select the types of uses (select one or both, as [gJ Prescription Use (Part 21 CFR 801 Subpart D)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p5-t0","doc_id":"K251610","page_num":5,"bbox":[72.24,302.04,522.78,375.66],"n_rows":5,"n_cols":2,"columns":["Name of Device:","qER-CTA (v1.0)"],"rows":[["Name of Device:","qER-CTA (v1.0)"],["Classification Name:","Radiological computer-assisted triage and notification software"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2080"],["Product Code:","QAS"]],"caption_candidate":"2 SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p5-t1","doc_id":"K251610","page_num":5,"bbox":[72.24,427.08,522.78,522.24],"n_rows":6,"n_cols":2,"columns":["Name of Device:","Viz LVO"],"rows":[["Name of Device:","Viz LVO"],["Manufacturer:","Viz.ai, Inc."],["510(k) Number:","K223042"],["Regulatory Class:","Class II"],["Regulation Number:","21 CFR 892.2080"],["Product Code","QAS"]],"caption_candidate":"3 PREDICATE DEVICES","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p7-t0","doc_id":"K251610","page_num":7,"bbox":[72.26,133.89,769.72,511.86],"n_rows":9,"n_cols":9,"columns":["","","","","Primary Predicate Device","","","Subject Device",""],"rows":[["","","","","Primary Predicate Device","","","Subject Device",""],["","Device Name","","","Viz LVO","","","qER-CTA",""],["510(k) Number","","","K223042","","","K251610","",""],["Device Class","","","Class II","","","Class II","",""],["Device Classification\nName","","","Radiological computer aided triage and notification software","","","Radiological computer aided triage and notification software","",""],["Regulation Number","","","21 CFR 892.2080","","","21 CFR 892.2080","",""],["Product Code","","","QAS","","","QAS","",""],["Manufacturer","","","Viz.ai, Inc.","","","Qure.ai Technologies Pvt. Ltd.","",""],["Intended use /\nIndications for Use","","","Viz LVO is a notification-only, parallel workflow tool designed\nfor use by hospital networks and trained clinicians to identify\nand communicate images of specific patients to a specialist,\nindependent of the standard of care workflow. Viz LVO uses\nan artificial intelligence algorithm to analyze images for\nfindings suggestive of a pre-specified clinical condition and to\nnotify an appropriate medical specialist of these findings in\nparallel to standard-of-care image interpretation. The\nidentification of suspected findings is intended solely for\nnotification purposes and not for diagnostic use beyond this\nnotification. Specifically, the device analyzes CT angiogram\nimages of the brain acquired in acute settings and sends\nnotifications to a neurovascular specialist when a suspected\nlarge vessel occlusion (LVO) has been identified. It also\nrecommends a review of those images. Images can be\npreviewed through a mobile application. Viz LVO is intended\nto analyze the terminal ICA and MCA-M1 vessels for LVOs.\nImages previewed through the mobile application are","","","qER-CTA is a notification-only, parallel workflow tool for use\nby hospital networks and trained clinicians to identify and\ncommunicate images of specific patients to a specialist,\nindependent of the standard of care workflow. qER-CTA uses\na deep learning algorithm to analyse images for findings\nsuggestive of a pre-specified clinical condition and to notify an\nappropriate medical specialist in parallel to standard of care\nimage interpretation. Identification of suspected findings is\nnot for diagnostic use beyond notification. Specifically, the\ndevice analyses CT angiogram images of the brain acquired in\nthe acute setting and sends notifications to a neurovascular\nspecialist that a suspected large vessel occlusion has been\nidentified, recommending review of those images. Images can\nbe previewed through a mobile application. qER-CTA is\nintended to analyse the internal carotid artery (ICA) and M1\nsegment of the middle cerebral artery (MCA) for LVOs on CTA\nscans of adults (≥ 22 years of age). Images previewed through\nthe mobile application are compressed and for informational","",""]],"caption_candidate":"Table 1 Comparison between qER-CTA and the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p8-t0","doc_id":"K251610","page_num":8,"bbox":[72.26,72.36,769.72,500.88],"n_rows":9,"n_cols":9,"columns":["","","","","Primary Predicate Device","","","Subject Device",""],"rows":[["","","","","Primary Predicate Device","","","Subject Device",""],["","Device Name","","","Viz LVO","","","qER-CTA",""],["","","","compressed and are for informational purposes only. They\nare not intended for diagnostic use beyond notification.\nNotified clinicians are responsible for viewing non-\ncompressed images on a diagnostic viewer and engaging in\nappropriate patient evaluation and relevant discussions with\nthe treating physician before making care-related decisions or\nrequests. Viz LVO is limited to the analysis of imaging data and\nshould not be used in lieu of a full patient evaluation or relied\nupon to make or confirm a diagnosis.","","","purposes only, not intended for diagnostic use beyond\nnotification. Notified clinicians are responsible for viewing\nnon-compressed images on a diagnostic viewer, conducting\nappropriate patient evaluation, and engaging in relevant\ndiscussions with the treating physician before making care-\nrelated decisions or requests.qER-CTA is limited to the analysis\nof imaging data and should not be used as a substitute for full\npatient evaluation or relied upon to make or confirm a\ndiagnosis.","",""],["Intended User","","","Neurovascular specialists, such as vascular neurologists,\nneuro-interventional specialists, or users with similar training\nwho have been pre-authorized by their Healthcare\nOrganization or Facility.","","","Neurologists, neuroradiologists, radiologists, neuro-\ninterventional specialist, and/or other emergency\ndepartment physicians.","",""],["Modality","","","Head Computed Tomography Angiography (CTA)","","","Head Computed Tomography Angiography (CTA)","",""],["Target clinical conditions","","","Large Vessel Occlusion","","","Large Vessel Occlusion","",""],["Algorithm for pre-\nspecified critical findings\ndetection","","","Image processing algorithms for large vessel occlusion","","","Image processing algorithms for large vessel occlusion","",""],["Input format","","","DICOM","","","DICOM","",""],["Performance level –\naccuracy of classification","","","Sensitivity: 87.8% (95% CI: 81.2% - 92.5%)\nSpecificity: 89.6% ( 95% CI: 83.7% - 93.9%)\nAUC: 0.91","","","Sensitivity: 91.35% (95% CI: 87.54%-94.07%)\nSpecificity: 91.86% (95% CI: 88.18% -94.47%)\nAUC: 0.959","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p9-t0","doc_id":"K251610","page_num":9,"bbox":[72.3,72.36,769.68,130.62],"n_rows":3,"n_cols":9,"columns":["","","","","Primary Predicate Device","","","Subject Device",""],"rows":[["","","","","Primary Predicate Device","","","Subject Device",""],["","Device Name","","","Viz LVO","","","qER-CTA",""],["Mean Time to\nNotification","","","7.32 [5.51, 9.13]","","","6.36 [ 6.06, 6.66 ]","",""]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p10-t0","doc_id":"K251610","page_num":10,"bbox":[81.63,473.16,513.39,528.72],"n_rows":3,"n_cols":7,"columns":["Abnormality","","","AUC (95% CI)","Sensitivity (95% CI),\nTP/P","Specificity (95% CI),\nTN/N",""],"rows":[["Abnormality","","","AUC (95% CI)","Sensitivity (95% CI),\nTP/P","Specificity (95% CI),\nTN/N",""],["","Large Vessel","","0.959 (0.943 – 0.975)","91.35% (87.54%-94.07%)","91.86% (88.18% -\n94.47%)",""],["","Occlusion","","","","",""]],"caption_candidate":"Table 2 Standalone Performance Testing Results for qER-CTA","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p10-t1","doc_id":"K251610","page_num":10,"bbox":[72.24,583.2,401.66,713.34],"n_rows":4,"n_cols":2,"columns":["qER-CTA\n(N = 584)","Time to Notification of\nSpecialist for LVO cases (mins)"],"rows":[["qER-CTA\n(N = 584)","Time to Notification of\nSpecialist for LVO cases (mins)"],["Mean","6.36 (6.06-6.66)"],["SD","3.68"],["Median","6.89"]],"caption_candidate":"Time to Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251610-p11-t0","doc_id":"K251610","page_num":11,"bbox":[72.0,111.54,523.02,165.24],"n_rows":4,"n_cols":2,"columns":["","Both the"],"rows":[["","Both the"],["subject and predicate device are medical image analyzers intended to read head CTA scans to classify",""],["user identified large vessel occlusion. The algorithms function similarly and with the same purpose of",""],["classification of large vessel occlusion",""]],"caption_candidate":"The comparison in Table 1 as well as the software & performance testing presented above","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p5-t0","doc_id":"K251629","page_num":5,"bbox":[62.66,148.94,532.88,749.02],"n_rows":10,"n_cols":4,"columns":["","I. Submitter information","",""],"rows":[["","I. Submitter information","",""],["Submitter","","MEDICREA INTERNATIONAL S.A.S. (MEDTRONIC)\n5389 Route de Strasbourg – Vancia\nRillieux-la-Pape, 69140\nFrance\nPhone : 00 33 4 72 01 87 87",""],["Contact\nPerson","","Cécile HUMBERT\nSr Regulatory Affairs Specialist\nMEDICREA INTERNATIONAL S.A.S. (MEDTRONIC)",""],["","II. Device identification","",""],["Trade name","","UNiD™ Spine Analyzer",""],["Classification\nRegulation","","Common Name Automated radiological image processing\nsoftware\nPrimary Product Code QIH\nAssociated Product Code LLZ\nRegulation Number 21 CFR 892.2050\nRegulation Name Medical image management and processing\nsystem\nClass 2",""],["","III. Predicate and reference devices","",""],["Primary\npredicate\ndevice","","Device name UNiD™ Spine Analyzer\n510(k) information K212005, cleared on 01/12/2022\nCommon Name system, image processing, radiological\nProduct Code LLZ\nRegulation Number 21 CFR 892.2050\nRegulation Name Medical image management and processing\nsystem\nClass 2",""],["","IV. Subject device description","",""],["The UNiD™ Spine Analyzer is a web-based application developed to perform preoperative and postoperative\npatient image measurements and simulate preoperative planning steps for spine surgery. It aims to make\nmeasurements on a patient image, simulate a surgical strategy, draw patient-specific rods or choose from a\npre-selection of standard implants. The UNiD™ Spine Analyzer allows the user to:\n1. Measure radiological images using generic tools and “specialty” tools\n2. Plan and simulate aspects of surgical procedures\n3. Estimate the compensatory effects of the simulated surgical procedure on the patient’s spine\nThe planning of surgical procedures is done by Medtronic as part of the service of pre-operative planning.\nThe surgical plan may then be used to assist in designing patient-specific implants. Surgeons will have to\nvalidate the surgical plan before Medtronic manufactures any implant.\nThe UNiD™ Spine Analyzer interface is accessible in either standalone mode or connected mode.","","",""]],"caption_candidate":"Date prepared: May 28, 2025","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p6-t0","doc_id":"K251629","page_num":6,"bbox":[62.69,57.06,532.85,762.58],"n_rows":4,"n_cols":4,"columns":["","V. Intended use and indications for use","",""],"rows":[["","V. Intended use and indications for use","",""],["Intended use\n/ Indications\nfor use","","The UNiD™ Spine Analyzer is intended for assisting healthcare professionals in viewing and\nmeasuring images as well as planning orthopedic surgeries. The device allows surgeons and\nservice providers to perform generic, as well as spine related measurements on images, and\nto plan surgical procedures. The device also includes tools for measuring anatomical\ncomponents for placement of surgical implants. Clinical judgment and experience are\nrequired to properly use the software.",""],["","VI. Comparison of technological characteristics","",""],["The subject device has similar fundamental scientific technology, overall design, features, computer\nconfiguration characteristics, intended use, and indications as the predicate device. The subject device and\nthe predicate device are intended to assisting healthcare professionals in viewing and measuring images as\nwell as planning orthopedic surgeries.\nThe subject device and the predicate device are compared in the table below.\nSubject Device Predicate\nFeature/ Attribute\nUNiD™ Spine Analyzer 5.0.0 UNiD™ Spine Analyzer 4.0.0\nProduct code(s) QIH, LLZ LLZ\nRegulation number 892.2050 892.2050\nClassification 2 2\nIntended use / The UNiD™ Spine Analyzer is intended for The UNiD™ Spine Analyzer is intended for\nIndications for use assisting healthcare professionals in assisting healthcare professionals in\nviewing and measuring images as well as viewing and measuring images as well as\nplanning orthopedic surgeries. The device planning orthopedic surgeries. The device\nallows surgeons and service providers to allows surgeons and service providers to\nperform generic, as well as spine related perform generic, as well as spine related\nmeasurements on images, and to plan measurements on images, and to plan\nsurgical procedures. The device also surgical procedures. The device also\nincludes tools for measuring anatomical includes tools for measuring anatomical\ncomponents for placement of surgical components for placement of surgical\nimplants. Clinical judgment and experience implants. Clinical judgment and experience\nare required to properly use the software. are required to properly use the software.\nFundamental scientific\nStandalone software Standalone software\ntechnology\nComputer PC Compatible PC Compatible\nOperating System Windows + Mac Windows + Mac\nSupply mean Cloud-based Cloud-based\nHealth Data Host AWS AWS\nFrontend code Angular 14 & Angular JS 1.7 Angular JS 1.7\nBackend code .NET 8.0 .NET 4.8\nDatabases server SQL Server MySQL\nHuman intervention Required for interpretation and Required for interpretation and\nmanipulation of images manipulation of images\nSupported image\nJPEG; PNG; GIF JPEG; PNG; GIF\nformat\nAccess mode Standalone or connected mode Standalone or connected mode\nFeature Contains all image setting tools (contrast; Contains all image setting tools (contrast;\n- Image setting brightness; zoom in/out; flip, rotate, text brightness; zoom in/out; flip, rotate, text\noverlay, calibration) overlay, calibration; intermodal\ncalibration)\nIntermodal calibration has been removed\nas part of a bug fix.","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p7-t0","doc_id":"K251629","page_num":7,"bbox":[68.3,57.33,527.26,704.14],"n_rows":7,"n_cols":3,"columns":["Feature\n- Generic\nmeasurements\ntools","Contains all generic measurements tools\n(Line; circle; angle; measured, simulated,\nand normative values display; values color-\ncoding)\nColor-coding thresholds are reworked but\nthe operating mode is similar.","Contains all generic measurements tools\n(Line; circle; angle; measured, simulated,\nand normative values display; values color-\ncoding)"],"rows":[["Feature\n- Generic\nmeasurements\ntools","Contains all generic measurements tools\n(Line; circle; angle; measured, simulated,\nand normative values display; values color-\ncoding)\nColor-coding thresholds are reworked but\nthe operating mode is similar.","Contains all generic measurements tools\n(Line; circle; angle; measured, simulated,\nand normative values display; values color-\ncoding)"],["Feature\n- Spine\nmeasurements\ntools","Contains all spine-related measurements\ntools (Llordo; TKypho; pelvic; T1SPi; SVA;\nSA Analysis; Sagittal wizard; Coronal\nwizard; Transitional anatomy (as part of\nSagittal wizard); Cervical; Lenke\nclassification; Coronal correction factor)\nSagittal Wizard, SA Analysis, Cervical tool\nand Lenke tool are reworked for\nimprovement and adding new calculations,\nbut the operating mode remains similar.\nThe Guide Spline tool has been removed as\npart of a bug fix.","Contains all spine-related measurements\ntools (Llordo; TKypho; pelvic; T1SPi; SVA;\nSA Analysis; Sagittal wizard; Coronal\nwizard; Transitional anatomy (as part of\nSagittal wizard); Cervical; Lenke\nclassification; Guide spline; Coronal\ncorrection factor)"],["Feature\n- Surgical tools","Contains surgical tools to simulate surgical\ngestures (wedge; open; resect; spondy;\nwedge auto; open auto; resect auto)","Contains surgical tools to simulate surgical\ngestures (wedge; open; resect; spondy,\nwedge auto; open auto; resect auto)"],["Feature\n- Implants tools","Contains tools to place or draw rods,\nscrews or cages (Free Rod; cage; screw;\nscrew selection; Rod Auto; cage auto;\nscrew wizard; postop screw).\nSome tools are reworked and relabeled.\nTool functionalities have been improved,\nand bugs have been fixed, but there is no\nchange in output data of the reworked\ntools.","Contains generic implants and tools to\nplace and/or draw rods, screws or cages\n(UNiD Rod; cage; cage selection; screw;\nscrew selection; UNiD Rod Auto; cage auto;\nscrew wizard; postop screw)."],["Feature\n- Implants database","Contains commercially available interbody\ndevices.\nSome TLIF and ALIF implants have been\nremoved from the database.","Contains commercially available interbody\ndevices."],["Feature\n- AI algorithms","Degenerative; Adult Deformity; Pediatric\nDeformity\nThe Degenerative model is updated. The\nfunctionality is similar. A new application is\nadded (LIV=L5)","Degenerative; Adult Deformity; Pediatric\nDeformity"],["Features\n- UNiD™ plan export","Contains several export options (as image,\nas ZIP file or to the Medtronic HUB).\nThe export options to the Medtronic HUB\nare reworked (export default view with\ntransitional anatomy; link a rod design to a\nrod order)","Contains several export options (as image,\nas ZIP file or to the Medtronic HUB)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p8-t0","doc_id":"K251629","page_num":8,"bbox":[62.69,57.06,532.85,766.3],"n_rows":2,"n_cols":4,"columns":["","VII. Performance data","",""],"rows":[["","VII. Performance data","",""],["Nonclinical\ntests","","The following non-clinical performance data were provided in support of substantial\nequivalence:\nSoftware verification\nThe software verification is a combination of software code review, software unit test, unit\nintegration testing, and system level integration to ensure the software is developed\ncorrectly and adheres to its design specifications. Software verification was conducted on the\nUNiD™ Spine Analyzer in accordance with IEC 62304.\nSoftware validation\nThe software validation was performed through user acceptance testing to ensure the\nsoftware satisfies the specified requirements and meets the user’s needs. It was conducted\non the UNiD™ Spine Analyzer in accordance with IEC 82304-1.\nAI-enabled device software functions (AI-DSF)\nThe software incorporates AI-DSF, which give indication to the user about compensatory\nmechanisms the patient could experience after the surgery according to the planned\ninstrumentation. Depending on the type of surgery (Adult, Pediatric or Degenerative), a\nspecific predictive model is available.\nOutputs of these models are intended to be used as inputs of the software system to simulate\ncompensatory mechanisms after spinal fixation.\nThe subject device incorporates a new version of the Degenerative Predictive model\ncompared to the predicate device. This new version includes degenerative constructs with\nLower Instrumented level on L5 and predicts Lower non instrumented lordosis in these\nsituations.\nPreoperative and post operative images from 1050 patient surgery cases were collected from\ndifferent clinical sites in the US only.\nAfter the images were collected, they were then provided to and measured by highly trained\nMedtronic measurement technicians, operating within a quality-controlled environment. The\nviability of images for use is vetted by these technicians before beginning surgical planning.\nConsequently, the manufacturer of imaging equipment does not have any impact on\nperformance.\nGround truth was derived from the measured images.\nEach patient case was assigned a unique identifier and included only in either the testing or\nthe training dataset, in order to ensure the independence of both datasets.\nThe demographic characteristics for the global dataset are presented in the table below.\nTraining set (No. of Testing set (No. of Overall (No. of\nDegen model\nsubjects=776) subjects=274) subjects=1050)\nMean age, years\n62.4 (11.5) 61.0 (12.7) 62.0 (11.8)\n(sd)\nGender, N (%)\nFemale 389 (50%) 127 (46%) 516 (49%)\nMale 387 (50%) 147 (54%) 534 (51%)\nTable 2: Degenerative Model Demographics global dataset\nNon-inferiority of the subject device vs the predicate device was evaluated: one-tailed paired\nT-tests for non-inferiority were performed between the MAEs obtained with the subject",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p8-t1","doc_id":"K251629","page_num":8,"bbox":[159.62,618.07,502.54,710.62],"n_rows":3,"n_cols":4,"columns":["Degen model","Training set (No. of\nsubjects=776)","Testing set (No. of\nsubjects=274)","Overall (No. of\nsubjects=1050)"],"rows":[["Degen model","Training set (No. of\nsubjects=776)","Testing set (No. of\nsubjects=274)","Overall (No. of\nsubjects=1050)"],["Mean age, years\n(sd)","62.4 (11.5)","61.0 (12.7)","62.0 (11.8)"],["Gender, N (%)\nFemale\nMale","389 (50%)\n387 (50%)","127 (46%)\n147 (54%)","516 (49%)\n534 (51%)"]],"caption_candidate":"The demographic characteristics for the global dataset are presented in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251629-p9-t0","doc_id":"K251629","page_num":9,"bbox":[62.67,56.88,532.87,369.05],"n_rows":4,"n_cols":4,"columns":["","","device and the ones obtained with the predicate device. The acceptance criterion for these\nstatistical tests were set to alpha of 0.025, and at least 90% power.\nThe results from the degenerative predictive model performance testing met the defined\nacceptance criterion. The model showed non-inferiority compared to its predicate and is\nconsidered acceptable for use.\nCybersecurity testing\nThe cybersecurity testing was conducted on the UNiD™ Spine Analyzer in accordance with\nANSI AAMI SW96 and IEC 81001-5-1 to ensure the software integrity, confidentiality and\navailability. Activities performed as part of cybersecurity testing included: security risk\nassessment and threat modeling, vulnerability assessment, and penetration testing.\nUsability evaluation\nUsability of the UNiD™ Spine Analyzer user interface was evaluated according to IEC 62366-\n1. The purpose was to assess the software ergonomics and ensure no usability issues could\nraise significant risks in terms of safety and effectiveness.",""],"rows":[["","","device and the ones obtained with the predicate device. The acceptance criterion for these\nstatistical tests were set to alpha of 0.025, and at least 90% power.\nThe results from the degenerative predictive model performance testing met the defined\nacceptance criterion. The model showed non-inferiority compared to its predicate and is\nconsidered acceptable for use.\nCybersecurity testing\nThe cybersecurity testing was conducted on the UNiD™ Spine Analyzer in accordance with\nANSI AAMI SW96 and IEC 81001-5-1 to ensure the software integrity, confidentiality and\navailability. Activities performed as part of cybersecurity testing included: security risk\nassessment and threat modeling, vulnerability assessment, and penetration testing.\nUsability evaluation\nUsability of the UNiD™ Spine Analyzer user interface was evaluated according to IEC 62366-\n1. The purpose was to assess the software ergonomics and ensure no usability issues could\nraise significant risks in terms of safety and effectiveness.",""],["Clinical tests","","No clinical testing was used in order to support this submission.",""],["","VIII. Conclusion","",""],["Based on the information contained in this submission, the subject UNiD™ Spine Analyzer v5.0.0 device is\nsubstantially equivalent to the following predicate device:\n− Predicate 1 (Primary Predicate): UNiD™ Spine Analyzer v4.0.0 (K212005, S.E. 01/12/2022)","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251651-p9-t0","doc_id":"K251651","page_num":9,"bbox":[95.88,72.59,558.0,712.81],"n_rows":27,"n_cols":5,"columns":["","","Intended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are not\nincluded in the User Manual\nor with the EPIQ Series\nDiagnostic Ultrasound\nSystem.\nBefore use of the system and\nuser information, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are not\nincluded in the User Manual\nor with the Affiniti Series\nDiagnostic Ultrasound\nSystem.","Intended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the EPIQ Series Diagnostic\nUltrasound System.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the Affiniti Series\nDiagnostic Ultrasound System.",""],"rows":[["","","Intended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are not\nincluded in the User Manual\nor with the EPIQ Series\nDiagnostic Ultrasound\nSystem.\nBefore use of the system and\nuser information, the user\nmust be familiar with\nultrasound techniques.\nSonography training and\nclinical procedures are not\nincluded in the User Manual\nor with the Affiniti Series\nDiagnostic Ultrasound\nSystem.","Intended for sonographers,\nphysicians, and biomedical\nengineers who operate and\nmaintain your product.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the EPIQ Series Diagnostic\nUltrasound System.\nBefore use of the system and\nuser information, the user must\nbe familiar with ultrasound\ntechniques. Sonography training\nand clinical procedures are not\nincluded in the User Manual or\nwith the Affiniti Series\nDiagnostic Ultrasound System.",""],["","","","",""],["","","","",""],["","","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Clinics, hospitals, and clinical\npoint-of-care for diagnosis of\npatients.","Identical"],["Intended","","","",""],["User","","","",""],["Environment","","","",""],["","","","",""],["","","Class II","Class II","Identical"],["USA FDA","","","",""],["Classification","","","",""],["","","","",""],["","","IYN","IYN","Identical"],["Primary","","","",""],["Product","","","",""],["Code","","","",""],["","","","",""],["","","21 CFR 892.1550","21 CFR 892.1550","Identical"],["Primary","","","",""],["Regulation","","","",""],["Number","","","",""],["","","","",""],["","","ITX\nIYO\nOBJ*\nQIH\n*Applicable only to Philips\nEPIQ Series Diagnostic\nUltrasound System, per\nclearance under K202216;\nNot applicable for Philips\nAffiniti Series Diagnostic\nUltrasound System","ITX\nIYO\nOBJ*\nQIH\n*Applicable only to Philips EPIQ\nSeries Diagnostic Ultrasound\nSystem, per clearance under\nK202216; Not applicable for\nPhilips Affiniti Series Diagnostic\nUltrasound System","Identical.\nThe EMI filter is not\nassociated with\nproduct code QIH."],["Secondary","","","",""],["Product","","","",""],["Codes","","","",""],["","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251651-p10-t0","doc_id":"K251651","page_num":10,"bbox":[95.8,72.59,558.0,718.6],"n_rows":32,"n_cols":5,"columns":["","","Diagnostic ultrasonic\ntransducer\nUltrasonic pulsed echo\nimaging\nsystem\nDiagnostic intravascular\ncatheter\nAutomated Radiological\nImage\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular\ncatheter\nAutomated Radiological Image\nProcessing Software","Identical"],"rows":[["","","Diagnostic ultrasonic\ntransducer\nUltrasonic pulsed echo\nimaging\nsystem\nDiagnostic intravascular\ncatheter\nAutomated Radiological\nImage\nProcessing Software","Diagnostic ultrasonic transducer\nUltrasonic pulsed echo imaging\nsystem\nDiagnostic intravascular\ncatheter\nAutomated Radiological Image\nProcessing Software","Identical"],["Secondary","","","",""],["Regulation","","","",""],["Name","","","",""],["","","","",""],["","","21 CFR 892.1560\n21 CFR 892.1570\n21 CFR 892.2050\n21 CFR 870.1200","21 CFR 892.1560\n21 CFR 892.1570\n21 CFR 892.2050\n21 CFR 870.1200","Identical"],["Secondary","","","",""],["Regulation","","","",""],["Number","","","",""],["","","","",""],["","","Yes","Yes","Identical"],["Reusable","","","",""],["","","","",""],["","","Limited (≤ 24 hours)","Limited (≤ 24 hours)","Identical"],["Duration of","","","",""],["use","","","",""],["","","","",""],["","","Custom EMI Filter Module","-","Introduction of the\noptional spare part\nCustom EMI Filter\nModule"],["Marketing","","","",""],["Name of","","","",""],["Application","","","",""],["","","","",""],["","","Image appears clean without\nany Image artifacts potentially\ncaused by the external\nhospital environments such as\nbad non isolated grounding.","Visible imperfections or\ndistortions in an Ultrasound\nimage that are a result of\nexternal interference. These\nartifacts can be caused by\nexternal factors such as\nconductive noise induced by the\nelectrical powerline or poor\nelectrical grounding can affect\nthe overall quality of the image.","The proposed\ndevice has better &\ncleaner Image over\nPredicate Device\nwhen image\nartifacts may arise\ndue to external\nhospital\nenvironmental\nfactors, such as\npoor or non-\nisolated grounding.\nVerification and\nValidation Testing\nhas been\nconducted with\nCustom EMI Filter\non the EPIQ &\nAffiniti Systems to\nsupport\nClear Image\nwithout any Image\nartifacts."],["Image","","","",""],["Artifacts","","","",""],["","","","",""],["","","Yes","Yes","Custom EMI filter\ndoesn’t involve the\nuser interface of\nthe system"],["User","","","",""],["Interface","","","",""],["","","","",""],["","","Yes","Yes","Custom EMI filter\ndoesn’t involve the"],["Software","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251651-p11-t0","doc_id":"K251651","page_num":11,"bbox":[98.42,501.14,539.74,654.12],"n_rows":7,"n_cols":8,"columns":["Test Type","","","Description","","","Outcome",""],"rows":[["Test Type","","","Description","","","Outcome",""],["Radiated Emissions","","Evaluated emissions from the\ndevice","","","Passed","",""],["Conducted Emissions","","Assessed conducted noise on\npower lines","","","Passed","",""],["Electrostatic Discharge\n(ESD)","","Tested immunity to static\nelectricity","","","Passed","",""],["Radiated RF Immunity","","Assessed resistance to RF\nfields (420–470 MHz)","","","Passed","",""],["Voltage Interruptions","","Simulated power fluctuations","","","Passed","",""],["Proximity Field Testing","","Evaluated performance near RF\nsources","","","Passed","",""]],"caption_candidate":"Tests Conducted:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p4-t0","doc_id":"K251656","page_num":4,"bbox":[19.27,19.44,593.04,363.84],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK251656 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK251656 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K251656",""],["Please provide the device trade name(s).","",""],["Careverse CoronaryDoc (Careverse CoronaryDoc)","",""],["Please provide your Indications for Use below.","","?"],["Careverse CoronaryDoc is a web-based software application that is intended to be used by trained medical\nprofessionals as an interactive tool for viewing and analyzing cardiac computed tomography (CT) data for\ndetermining the presence and extent of coronary plaques (i.e., atherosclerosis) and stenosis in patients who\nunderwent Coronary Computed Tomography Angiography (CCTA) for evaluation of CAD or suspected\nCAD. This software post processes CT images obtained using any Computed Tomography (CT) scanner.\nThe software provides tools for the measurement and visualization of coronary arteries.\nThe software is not intended to replace the skill and judgment of a qualified medical practitioner and should\nonly be used by people who have been appropriately trained in the software's functions, capabilities and\nlimitations.","",""],["Please select the types of uses (select one or both, as ~ Prescription Use (Part 21 CFR 801 Subpart D)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p7-t0","doc_id":"K251656","page_num":7,"bbox":[108.24,179.76,550.8,756.0],"n_rows":4,"n_cols":4,"columns":["Item","Subject device, K251656","Predicate device (K202280)","Analysis"],"rows":[["Item","Subject device, K251656","Predicate device (K202280)","Analysis"],["Product Code","QIH","LLZ","Same"],["Regulation","21 CFR 892.2050","21 CFR 892.2050","Same"],["Intended\nUse/Indications\nfor Use","Careverse CoronaryDoc is a\nweb-based software application\nthat is intended to be used by\ntrained medical professionals as\nan interactive tool for viewing\nand analyzing cardiac computed\ntomography (CT) data for\ndetermining the presence and\nextent of coronary plaques (i.e.,\natherosclerosis) and stenosis in\npatients who underwent\nCoronary Computed\nTomography Angiography\n(CCTA) for evaluation of CAD\nor suspected CAD. This\nsoftware post processes CT\nimages obtained using any\nComputed Tomography (CT)\nscanner. The software provides\ntools for the measurement and\nvisualization of coronary\narteries.\nThe software is not intended to\nreplace the skill and judgment\nof a qualified medical\npractitioner and should only be\nused by people who have been\nappropriately trained in the","Cleerly Labs is a web-based\nsoftware application that is\nintended to be used by trained\nmedical professionals as an\ninteractive tool for viewing and\nanalyzing cardiac computed\ntomography (CT) data for\ndetermining the presence and\nextent of coronary plaques (i.e.,\natherosclerosis) and stenosis in\npatients who underwent\nCoronary Computed\nTomography Angiography\n(CCTA) for evaluation of CAD\nor suspected CAD. This\nsoftware post processes CT\nimages obtained using any\nComputed Tomography (CT)\nscanner. The software provides\ntools for the measurement and\nvisualization of coronary\narteries.\nThe software is not intended to\nreplace the skill and judgment\nof a qualified medical\npractitioner and should only be\nused by people who have been\nappropriately trained in the","Same"]],"caption_candidate":"6. Comparison of Technological Characteristic with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p8-t0","doc_id":"K251656","page_num":8,"bbox":[108.24,72.24,550.8,760.08],"n_rows":12,"n_cols":4,"columns":["","software’s functions,\ncapabilities and limitations.","software’s functions,\ncapabilities and limitations.\nUsers should be aware that\ncertain views make use of\ninterpolated data. This is data\nthat is created by the software\nbased on the original data set.\nInterpolated data may give the\nappearance of healthy tissue in\nsituations where pathology that\nis near or smaller than the\nscanning resolution may be\npresent.",""],"rows":[["","software’s functions,\ncapabilities and limitations.","software’s functions,\ncapabilities and limitations.\nUsers should be aware that\ncertain views make use of\ninterpolated data. This is data\nthat is created by the software\nbased on the original data set.\nInterpolated data may give the\nappearance of healthy tissue in\nsituations where pathology that\nis near or smaller than the\nscanning resolution may be\npresent.",""],["Image Input","DICOM 3.0 Compliant","DICOM 3.0 Compliant","Same"],["Image\nAcquisition","CT Images","CT Images","Same"],["Study Analysis\nTools –\nNavigation","Yes","Yes","Same"],["Study Analysis\nTools –\nEditing/\nVisualization","Yes","Yes","Same"],["2D Imaging","Yes","Yes","Same"],["3D Imaging","Yes","Yes","Same"],["Multiplanar\nReformat\n(MPR)","Yes","Yes","Same"],["Segmentation\nof Region of\nInterest","Yes","Yes","Same"],["Plaque\nComposition\nOverlay","Yes","Yes","Same"],["Hounsfield\nUnit (HU)","Yes","Yes","Same"],["Distance\nMeasurements","Yes","Yes","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p9-t0","doc_id":"K251656","page_num":9,"bbox":[108.24,72.24,550.8,217.68],"n_rows":4,"n_cols":4,"columns":["Volumetric\nMeasurements","Yes","Yes","Same"],"rows":[["Volumetric\nMeasurements","Yes","Yes","Same"],["Stenosis","Yes","Yes","Same"],["Coronary\nAnatomical\nFindings","Yes","Yes","Same"],["Coronary\nReport","Yes","Yes","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p9-t1","doc_id":"K251656","page_num":9,"bbox":[129.36,559.2,481.68,688.32],"n_rows":7,"n_cols":6,"columns":["Stenosis Grade","n","m","Agreement","Lower 95% CI","Higher 95% CI"],"rows":[["Stenosis Grade","n","m","Agreement","Lower 95% CI","Higher 95% CI"],["non-stenosis","682","675","98.97%","97.90%","99.59%"],["minor stenosis","160","146","91.25%","85.75%","95.13%"],["minimal stenosis","100","87","87.00%","78.80%","92.89%"],["moderate stenosis","94","82","87.23%","78.76%","93.23%"],["severe stenosis","86","72","83.72%","74.20%","90.80%"],["complete occlusion","34","31","91.18%","76.32%","98.14%"]],"caption_candidate":"Table 1: Stenosis Performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251656-p10-t0","doc_id":"K251656","page_num":10,"bbox":[108.24,233.76,508.32,362.88],"n_rows":7,"n_cols":3,"columns":["Output","Pearson Correlation Coefficient","Bland-Altman Agreement"],"rows":[["Output","Pearson Correlation Coefficient","Bland-Altman Agreement"],["vessel volume","98.42%","95.18%"],["lumen volume","98.52%","94.78%"],["total plaque volume","96.94%","95.91%"],["calcified plaque volume","97.92%","98.00%"],["non-calcified plaque volume","95.14%","95.24%"],["low-density non-calcified","88.42%","94.96%"]],"caption_candidate":"Table 2: Plaque Performance","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251673-p5-t0","doc_id":"K251673","page_num":5,"bbox":[108.0,471.78,544.38,520.44],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate Trade Name","Product Code"],"rows":[["Predicate #","Predicate Trade Name","Product Code"],["K211193","BD Prevue™ II Peripheral\nVascular Access System","IYO – ITX – LLZ"]],"caption_candidate":"3. Legally Marketed Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251673-p6-t0","doc_id":"K251673","page_num":6,"bbox":[72.24,367.38,526.5,497.16],"n_rows":3,"n_cols":2,"columns":["Imaging Applications","Exam Type (Adult and Pediatric)"],"rows":[["Imaging Applications","Exam Type (Adult and Pediatric)"],["Vascular","Assessment of vessels in the extremities and neck leading to or\ncoming from the heart, superficial veins in the arms and legs,\nand vessel mapping. Assessment of superficial thoracic vessels."],["Vascular Access","Guidance for PICC, CVC, dialysis catheter, port, PIV, midline,\narterial line placement, access to fistula and grafts, and general\nvein and artery access"]],"caption_candidate":"Typical examinations performed using the BD Prevue™ II System include:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251682-p7-t0","doc_id":"K251682","page_num":7,"bbox":[36.25,98.4,575.76,335.16],"n_rows":5,"n_cols":4,"columns":["Model\nMuscleView 2.0","Release Date\n05/30/2025","Anatomical Region\nFull Body","Model Function\nAssistive AI"],"rows":[["Model\nMuscleView 2.0","Release Date\n05/30/2025","Anatomical Region\nFull Body","Model Function\nAssistive AI"],["","","",""],["Model Training and Testing\nThe MuscleView 2.0 – Setting 1 model underwent supervised machine learning using a curated collection of\nretrospective MRI datasets from a diverse population (n = 1294 unique subjects). Each dataset was labeled\nthrough a consensus process by expert segmentation analysts to establish ground truth.\nThe model was tested on diverse datasets (n = 148 unique subjects) independent from the training datasets and\nblinded to ground truth segmentations. Performance results demonstrated segmentation accuracy within the\ninterobserver variability range observed among experts.","","",""],["Model Settings\nAll AI/ML inferences are performed automatically, with no configuration, calibration or exposed modifiable\nparameters. The model behavior is locked and deterministic.","","",""],["Privacy\nPatient data is kept within the user’s network and is not used to train or test future models.","","",""]],"caption_candidate":"AI/ML Model Cards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251682-p7-t1","doc_id":"K251682","page_num":7,"bbox":[36.25,385.73,582.58,464.28],"n_rows":6,"n_cols":5,"columns":["Attribute","Subject Device","Predicate Device","Reference Device","Comment"],"rows":[["Attribute","Subject Device","Predicate Device","Reference Device","Comment"],["Device Name","MuscleView 2.0","MuscleView 1.0","AMRA Profiler","n/a"],["Manufacturer","Springbok, Inc.","Springbok, Inc.","AMRA","n/a"],["510(k) Number","TBD","K241331","K211983","n/a"],["Regulation","892.1000","892.1000","892.1000","No di(cid:431)erence"],["Product Code","LNH","LNH","LNH","No di(cid:431)erence"]],"caption_candidate":"Predicate Device Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251682-p8-t0","doc_id":"K251682","page_num":8,"bbox":[36.25,73.61,582.59,728.64],"n_rows":9,"n_cols":5,"columns":["Attribute","Subject Device","Predicate Device","Reference Device","Comment"],"rows":[["Attribute","Subject Device","Predicate Device","Reference Device","Comment"],["Indications for\nUse","MuscleView is a\nmagnetic resonance\ndiagnostic software\ndevice which\nautomatically segments\nmuscle, bone, fat and\nother anatomical\nstructures from\nmagnetic resonance\nimaging. After\nsegmentation, it\nenables the generation,\ndisplay and review of\nmagnetic resonance\nimaging data. Other\nphysical parameters\nderived from the images\nmay also be produced.\nWhen interpreted by a\ntrained clinician, these\nimages and physical\nparameters may yield\ninformation that may\nassist in diagnosis.","MuscleView is intended for\nuse in adults and pediatric\npatients aged 18 years and\nolder to automatically\nsegment muscle and bone\nstructures of the lower\nextremities from magnetic\nresonance imaging using a\nmachine learning-based\napproach. Following\nsegmentation, it provides\nderived metrics including\nmuscle volume, bone\nvolume, intramuscular fat\npercentage, and left/right\nasymmetry. The software is\nintended to be used by\nphysicians trained in the\ninterpretation of MRI\nimages and serves as an\ninitial method for\nsegmenting muscle and\nbone structures from one\nor more study series.\nSegmentation results must\nbe reviewed and, if\nnecessary, edited using\nappropriate software.\nMuscleView is intended\nsolely to provide\nsegmentation and derived\nmetrics for muscle and\nbone structures and is not\nintended to directly\nsupport the diagnosis of\nany disease. This device is\nnot intended for use in\npatients with tumors in the\nlower limbs.","Indicated for use as a\nmagnetic resonance\ndiagnostic device software\napplication for non-\ninvasive fat and muscle\nevaluation, this device\nenables the generation,\ndisplay, and review of 2D\nmagnetic resonance\nmedical image data. It is\ndesigned to utilize DICOM\n3.0 compliant magnetic\nresonance image datasets\nacquired from compatible\nMR systems to display the\ninternal structure of the\nbody, including the liver.\nOther physical parameters\nderived from the images\nmay also be produced. The\nsoftware provides a\nnumber of quantification\ntools, such as Region of\nInterest (ROI) placements,\nto be used for the\nassessment of regions\nwithin an image to quantify\nliver tissue characteristics,\nincluding the\ndetermination of fat\nfraction in the liver, T2*,\nand muscle volume. These\nimages and the physical\nparameters derived from\nthem, when interpreted by\na trained clinician, yield\ninformation that may assist\nin diagnosis.","The subject device\nexpands upon the\ncapabilities of the\npredicate device by\nsupporting\nsegmentation and\nanalysis of a broader\nrange of anatomical\nregions of interest\n(ROIs), including ROIs in\nthe upper body and\ndi(cid:431)erent types of\nadipose tissue.\nFurthermore, the\nsubject device includes\na comparative function\nsimilar to that of the\nreference device,\nenabling comparison of\npatient-specific metrics\nto a virtual control\ngroup."],["Anatomy","Muscles, bones and fat\nstructures in the legs,\ntrunk and arms.","Muscles, bones and fat\nstructures in the legs.","Muscles, bones and fat\nstructures in the legs",""],["Intended Users","Trained clinicians","Trained clinicians","Trained clinicians","No di(cid:431)erence"],["Target\nPopulation","Adults and pediatric\npatients aged 18 and\nolder","Adults and pediatric\npatients aged 18 and\nolder","Adults","No di(cid:431)erence"],["Contra-\nindications","Tumors in the trunk,\narms and/or lower limbs","Tumors in the lower\nextremities","None, software only","Subject device\ncontraindications reflect\nthe expanded\nindications for use from\nthe predicate device."],["Imaging\nmodality","Magnetic Resonance\nImaging","Magnetic Resonance\nImaging","Magnetic Resonance\nImaging","No di(cid:431)erence"],["MRI Scanners","GE, Siemens, Philips","GE, Siemens, Philips","GE, Siemens, Philips","No di(cid:431)erence"],["MR Field\nStrength","1.5T, 3.0T","1.5T, 3.0T","1.5T, 3.0T","No di(cid:431)erence"]],"caption_candidate":"A better view of health","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251682-p10-t0","doc_id":"K251682","page_num":10,"bbox":[36.26,200.47,576.29,560.51],"n_rows":23,"n_cols":18,"columns":["Factor","","","Groups","","","","AI Setting 1","","","","","","AI Setting 2 & 3","","","",""],"rows":[["Factor","","","Groups","","","","AI Setting 1","","","","","","AI Setting 2 & 3","","","",""],["","","","","","","","(Lower Extremity)","","","","","","(Upper extremity and Adipose Tissue)","","","",""],["","","","","","","","Training data","","","Validation data","","","Training data","","","Validation data",""],["Number of unique scans","","","n/a","","","1658","","","148","","","392","","","171","",""],["","Number of unique subjects","","","n/a","","","1294","","","148","","","209","","","171",""],["Gender","","","Male","","","1192*","","","102","","","230*","","","96*","",""],["","","","Female","","","374*","","","46","","","156*","","","74*","",""],["Age*","","","","Mean","","","29","","","31.7","","","41.8","","","39.3",""],["","","","","Standard Deviation","","","13.4","","","15.5","","","19.4","","","17.7",""],["Ethnicity\n(based on regional\ndemographics)","","","% Non-Hispanic White","","","52","","","52","","","50","","","50","",""],["","","","% Hispanic/Latino","","","18","","","18","","","17","","","15","",""],["","","","% Black/African American","","","14","","","14","","","11","","","14","",""],["","","","% Asian","","","10","","","10","","","13","","","7","",""],["","","","% Australian","","","2","","","2","","","3","","","6","",""],["","","","% American Indian / Alaska\nNative","","","<1","","","<1","","","<1","","","<1","",""],["","","","% Native Hawaiian / Pacific\nIslander","","","<1","","","<1","","","<1","","","<1","",""],["","","","% Australian Aboriginal","","","<1","","","<1","","","<1","","","1","",""],["","","","% Other","","","2","","","2","","","2","","","3","",""],["MRI Manufacturer","","","","Siemens","","","680","","","74","","","293","","","116",""],["","","","","GE Medical Systems","","","435","","","28","","","54","","","26",""],["","","","","Philips Medical Systems","","","82","","","29","","","41","","","25",""],["","","","","Canon","","","1","","","4","","","0","","","3",""],["","","","","Other (Toshiba) or Unknown","","","460","","","13","","","4","","","1",""]],"caption_candidate":"the data.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251682-p12-t0","doc_id":"K251682","page_num":12,"bbox":[36.96,49.35,576.26,736.96],"n_rows":115,"n_cols":12,"columns":["","","","","","","","","A","better","view of h","ealth"],"rows":[["","","","","","","","","A","better","view of h","ealth"],["","","","","","","","","","","",""],["","","","D","escrip(cid:415)ve","Sta(cid:415)s(cid:415)cs (","DSC) 95%","Confidence","Interval","","",""],["","","","","","","","","","","",""],["","Patholog","y Level","","MRI","Manufactu","rer","","","Age/Biolo","gic Sex",""],["","","","","","","","","","","",""],["ROI","Subgroup","Analysis","","Subgr","oup Analy","sis","","","Subgroup","Analysis",""],["","","","","","","","","","","",""],["","Healthy","Pa(cid:415)ent","Canon","GE","Philips","Siemens","Toshiba","Male 18-21","Male Over 21","Female 18-21 F","emale Over"],["","","","","","","","","Years","Years","years","years"],["","","","","","","","","","","",""],["piriformis","0.917 -0.936","0.88 -0.908","0.938 -0.959","0.865 -0.932","0.894 -0.924","0.917 -0.929","0.919 -0.935","0.883 -0.949","0.923 -0.932","0.914 -0.927","0.873 -0.912"],["","","","","","","","","","","",""],["popliteus","0.863 -0.889","0.846 -0.865","0.889 -0.911","0.852 -0.868","0.873 -0.887","0.849 -0.89","0.857 -0.876","0.895 -0.906","0.854 -0.895","0.84 -0.852","0.837 -0.854"],["","","","","","","","","","","",""],["psoas major","0.98 -0.982","0.943 -0.965","0.989 -0.993","0.974 -0.984","0.976 -0.98","0.961 -0.974","0.975 -0.979","0.979 -0.984","0.969 -0.98","0.978 -0.982","0.944 -0.97"],["","","","","","","","","","","",""],["quadratus femoris","0.905 -0.915","0.774 -0.833","0.859 -0.962","0.871 -0.903","0.876 -0.908","0.848 -0.887","0.867 -0.907","0.914 -0.925","0.878 -0.907","0.884 -0.9","0.759 -0.833"],["","","","","","","","","","","",""],["quadratus lumborum","0.926 -0.933","0.865 -0.896","0.93 -0.951","0.903 -0.924","0.914 -0.932","0.895 -0.917","0.922 -0.931","0.922 -0.944","0.911 -0.93","0.902 -0.919","0.87 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-0.981","0.962 -0.975","0.964 -0.984","0.98 -0.985","0.97 -0.98","0.975 -0.989","0.943 -0.968"],["","","","","","","","","","","",""],["tensor fasciae latae","0.955 -0.959","0.907 -0.937","0.943 -0.974","0.948 -0.956","0.939 -0.958","0.934 -0.953","0.943 -0.956","0.958 -0.965","0.939 -0.957","0.94 -0.95","0.919 -0.942"],["","","","","","","","","","","",""],["(cid:415)bia","0.98 -0.984","0.966 -0.974","0.993 -0.994","0.976 -0.983","0.979 -0.984","0.975 -0.98","0.958 -0.986","0.982 -0.986","0.98 -0.983","0.966 -0.983","0.966 -0.976"],["","","","","","","","","","","",""],["(cid:415)bialis anterior","0.965 -0.972","0.914 -0.94","0.979 -0.985","0.964 -0.971","0.959 -0.969","0.941 -0.96","0.931 -0.972","0.96 -0.977","0.956 -0.967","0.944 -0.97","0.917 -0.955"],["","","","","","","","","","","",""],["(cid:415)bialis posterior","0.957 -0.965","0.938 -0.95","0.973 -0.98","0.953 -0.965","0.955 -0.96","0.954 -0.961","0.912 -0.968","0.962 -0.968","0.957 -0.962","0.932 -0.968","0.941 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superficialis","3.182-4.100","1.073-2.202","1.589-4.840","1.793-3.813","2.243-4.204","3.078-4.141","2.122-3.556","3.429-4.946","1.629-4.795","2.189-3.432"],["","","","","","","","","","","",""],["flexor carpi ul","naris","2.773-3.806","1.569-3.320","0.894-7.997","1.413-2.903","1.795-3.323","2.924-4.283","1.476-3.476","3.203-5.026","2.434-4.133","2.018-3.055"],["","","","","","","","","","","",""],["flexor digitoru","m profundus","3.279-4.381","2.926-5.350","1.542-7.712","3.766-7.272","3.981-6.201","2.398-3.311","2.582-4.595","4.016-5.961","1.095-3.620","2.390-3.640"],["","","","","","","","","","","",""],["flexor pollicis","longus","1.232-1.568","1.003-1.930","0.458-1.711","1.160-1.995","1.190-1.896","1.122-1.526","1.036-1.664","1.267-1.790","0.883-2.151","1.005-1.558"],["","","","","","","","","","","",""],["pronator qua","dratus","0.729-1.022","0.629-1.110","1.114-3.129","0.614-1.494","0.694-1.136","0.595-0.890","0.552-1.273","0.893-1.344","0.270-0.573","0.499-0.810"],["","","","","","","","","","","",""],["vertebrae","","35.548-53.924","41.949-74.317","167.677-328.471","5.168-22.852","0.544-99.709","37.903-47.806","14.579-29.523","43.239-77.968","30.641-49.443","35.537-49.887"],["","","","","","","","","","","",""],["sternum","","2.333-3.051","3.047-5.426","0.085-6.579","1.063-3.544","1.253-3.122","2.567-3.357","1.855-3.542","2.927-4.047","1.316-2.846","1.897-3.203"],["","","","","","","","","","","",""],["ribs","","29.024-33.572","20.805-29.501","6.102-19.254","18.109-24.404","20.010-29.696","31.477-36.609","22.582-33.770","25.854-32.457","26.506-34.630","28.729-35.495"],["","","","","","","","","","","",""],["clavicle","","0.534-0.688","0.591-1.186","0.229-0.963","0.324-1.027","0.028-1.745","0.568-0.735","0.563-0.979","0.573-0.859","0.364-0.680","0.443-0.670"],["","","","","","","","","","","",""],["humerus","","2.498-3.527","1.659-6.106","0.694-2.834","1.641-4.226","1.294-2.376","2.775-4.373","1.022-1.634","2.323-4.853","2.733-5.027","2.692-4.052"],["","","","","","","","","","","",""],["ulna","","1.939-2.682","0.558-1.741","0.562-1.640","0.746-1.418","0.757-2.109","2.276-3.232","0.734-2.253","1.223-1.948","2.014-5.652","2.248-3.487"],["","","","","","","","","","","",""],["radius","","1.505-2.046","0.793-1.331","0.344-1.371","0.850-2.235","0.963-1.640","1.560-2.171","0.816-1.291","1.273-2.013","1.067-2.962","1.527-2.480"],["","","","","","","","","","","",""],["","","207.244-","106.995-","","","","239.630-","156.056-","180.188-","","149.165-"],["body from air","- core","384.757","206.879","32.459- 123.942","87.694- 163.101","96.423- 166.274","471.119","375.103","301.831","66.440- 149.328","537.570"],["","","","","","","","","","","",""],["body from air","- arms","130.010-198.021","64.650-147.712","48.962-329.982","74.854-165.761","69.941-150.750","130.576-215.971","235.729-448.566","105.542-184.596","25.855-111.108","51.560-118.393"],["","","","","","","","","","","",""],["outer abdomi","nal wall","261.758-368.565","7.790-892.968","13.916-114.822","172.644-434.905","256.828-372.548","-44.924-","180.302-558.447","268.271-418.848","118.037-213.084","115.674-626.266"],["","","","","","","","1096.033","","","",""],["","","","","","","","","","","",""],["abdominal ca","vity","32.99-47.46","-36.09-340.00","5.38-12.56","13.18-41.94","37.26-54.10","-70.21-418.23","27.54-56.05","34.59-56.68","12.11-27.03","-5.82-205.91"],["","","","","","","","","","","",""],["liver","","16.97-23.19","13.29-32.57","6.10-40.87","14.17-23.08","18.03-26.36","8.31-21.05","14.63-26.36","18.55-30.63","10.46-17.07","13.27-22.04"],["","","","","","","","","","","",""],["kidney","","3.566-5.784","3.717-7.537","0.697-4.917","2.323-6.041","3.598-5.953","3.357-9.276","2.592-5.928","3.685-7.165","2.099-5.302","3.056-6.340"],["","","","","","","","","","","",""],["breast_tissue","","28.88-347.08","-17.334-339.999","","1 0 5 . 7 1 9 - 2 3 2 . 5 7 4","2 1 . 1 6 0 - 3 8 0 . 3 3 4","9 . 3 1 2 - 1 5 0 . 3 6 1","","","1 6 . 6 2 2 - 7 7 . 7 4 6","4 7 . 2 9 6 - 3 7 8 . 9 8 2"],["","","","","","","","","","","",""],["thoracic cavit","y","45.790-66.024","38.193-84.029","50.426-95.380","13.074-47.188","54.118-78.310","22.208-51.752","30.907-78.146","54.057-88.529","10.539-28.431","37.792-61.142"]],"caption_candidate":"Pathology Level MRI Manufacturer Age/Biologic Sex","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251682-p16-t0","doc_id":"K251682","page_num":16,"bbox":[36.24,174.24,576.24,557.52],"n_rows":4,"n_cols":4,"columns":["Modification","Rationale","Modification Protocol","Impact Assessment"],"rows":[["Modification","Rationale","Modification Protocol","Impact Assessment"],["#1 - Retraining the AI/ML\nmodel for one or more ROIs\nusing additional training\ndata","To improve robustness and\ngeneralizability of the AI/ML\nmodel by training on\nadditional annotated\ndatasets.","Retraining of the AI/ML\nmodel with a mixture of old\nand new test datasets,\nfollowed by performance\ntesting to compare the\nretrained model to the\noriginal version.","Benefit: Improved model\ngeneralizability across\ndiverse cases.\nRisk: Introduction of bias,\noverfitting\nMitigation: Testing data\nsequestration and testing on\nnew data will ensure proper\nevaluation and mitigate risks\nof overfitting."],["#2 - Adjustment of AI Model\nSettings","To improve robustness and\ngeneralizability of the AI/ML\nmodel used to identify\nanatomical regions by\nmodifying a predefined set\nof training hyperparameters\nand pre/post processing\nmethods during re-training.","Adjustment of preprocessing\nparameters using existing\ndatasets, followed by\nperformance verification\nagainst baseline metrics to\nensure output consistency.","Benefit: Improved model\ngeneralizability across\ndiverse cases.\nRisk: Introduction of bias,\noverfitting\nMitigation: Predefined\nparameter boundaries and\ncomparison to the original\nmetrics mitigate risks of\noverfitting."],["#3 - Addition of data points\nto the Virtual Control Groups","To improve the statistical\nsignificance of the Virtual\nControl Group (VCG)\noutputs used to generate\nscored metrics.","Recalculation of linear\nregression equations using\nadditional subject data,\nfollowed by performance\nevaluation to ensure\nequivalent or improved\ncorrelation strength.","Benefit: Improved predictive\naccuracy\nRisk: Introduction of bias\nerror due to skewed\nsampling\nMitigation: Data collection\nprotocols align with those\ncontained within this\nsubmission"]],"caption_candidate":"MuscleView AI/ML models will be made in accordance with the PCCP summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p5-t0","doc_id":"K251747","page_num":5,"bbox":[87.89,621.6,524.11,647.88],"n_rows":2,"n_cols":9,"columns":["","510(k)","","","Product Name","","","Clearance Date",""],"rows":[["","510(k)","","","Product Name","","","Clearance Date",""],["K240582","","","VEA Align; spineEOS","","","June 2024","",""]],"caption_candidate":"3 LEGALLY MARKETED PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p8-t0","doc_id":"K251747","page_num":8,"bbox":[38.43,113.97,753.68,528.24],"n_rows":5,"n_cols":6,"columns":["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],["","","VEA Align (K240582)","","",""],["Indications for Use","This cloud-based software is intended for\northopedic applications in both pediatric and\nadult populations.\n2D X-ray images acquired in EOS imaging’s\nimaging systems is the foundation and resource\nto display the interactive landmarks overlayed\non the frontal and lateral images. These\nlandmarks are available for users to assess\npatient-specific global alignment.\nFor additional assessment, alignment\nparameters compared to published normative\nvalues may be available.\nThis product serves as a tool to aid in the\nanalysis of spinal deformities, degenerative\ndiseases, lower limb alignment disorders, and\ndeformities through precise angle and length\nmeasurements. It is suitable for use with adult\nand pediatric patients aged 7 years and older.\nClinical judgment and experience are required\nto properly use the software.","","","This cloud-based software is intended for\northopedic applications in both pediatric and\nadult populations.\n2D X-ray images acquired in EOS imaging’s\nimaging systems is the foundation and\nresource to display the interactive landmarks\noverlayed on the frontal and lateral images.\nThese landmarks are available for users to\nassess patient-specific global alignment.\nFor additional assessment, alignment\nparameters compared to published normative\nvalues may be available.\nThis product serves as a tool to aid in the\nanalysis of spinal deformities and degenerative\ndiseases, and lower limb alignment disorders\nand deformities through precise angle and\nlength measurements. It is suitable for use with\nadult and pediatric patients aged 7 years and\nolder.\nClinical judgment and experience are required\nto properly use the software.","YES"],["Contraindications","VEA Align is contraindicated for cases with\nvertebrae with severe congenital deformities\n(e.g., hemivertebrae, spina bifida, etc.) and\nsupernumerary/missing vertebrae.","","","VEA Align is contraindicated for cases with\nvertebrae with severe congenital deformities\n(e.g., hemivertebrae, spina bifida, etc.).","Similar\nThe change to the\ncontraindications simply reflects an\nenhancement of the software\nflexibility without affecting its core\ndesign, safety, or intended use."],["Regulatory\nClass/Code","Class II\nQIH\n(21 CFR 892.2050)","","","Class II\nQIH\n(21 CFR 892.2050)","YES"]],"caption_candidate":"Table 1: Summary of Predicate and Subject VEA Align Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p9-t0","doc_id":"K251747","page_num":9,"bbox":[38.41,92.49,753.7,537.96],"n_rows":12,"n_cols":6,"columns":["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],["","","VEA Align (K240582)","","",""],["Device\nClassification\nName","Automated Radiological Image Processing\nSoftware","","","Automated Radiological Image Processing\nSoftware","YES"],["Operating System","Windows + MAC","","","Windows + MAC","YES"],["User Population","VEA Align Alignment Assessment mode is\ndesigned for surgeons and clinical staff, such as\nphysician assistants, who have been trained to\nuse the application.\nVEA Align 3D mode is designed for 3D Services\nteam members.","","","VEA Align Alignment Assessment mode is\ndesigned for surgeons and clinical staff, such\nas physician assistants, who have been trained\nto use the application.\nVEA Align 3D mode is designed for 3D\nServices team members.","YES"],["Target Population","The device is indicated only for patients 7 years\nand older.","","","The device is indicated only for patients 7\nyears and older.","YES"],["Software\nFunctionalities /\nModalities","Global alignment assessments","","","Global alignment assessments","YES"],["","Includes landmarks associated with vertebral\nendplates needed to calculate coronal and\nsagittal clinical parameters. These landmarks\nare adjustable by the user.","","","Includes landmarks associated with vertebral\nendplates needed to calculate coronal and\nsagittal clinical parameters. These landmarks\nare adjustable by the user.","YES"],["","Includes landmarks associated with the pelvis\nand lower limbs needed to calculate coronal and\nsagittal clinical parameters. These landmarks\nare adjustable by the user.","","","Includes landmarks associated with the pelvis\nand lower limbs needed to calculate coronal\nand sagittal clinical parameters. These\nlandmarks are adjustable by the user.","YES"],["","Provides normative values used to assess\npatients’ global alignment","","","Provides normative values used to assess\npatients’ global alignment","YES"],["","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues","","","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues","YES"],["Image\nManipulation\nFunctions","2D images display and basic manipulation\n(zoom, panning)","","","2D images display and basic manipulation\n(zoom, panning)","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p10-t0","doc_id":"K251747","page_num":10,"bbox":[38.41,92.49,753.7,503.88],"n_rows":10,"n_cols":6,"columns":["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","Subject VEA Align","Substantially Equivalent?"],["","","VEA Align (K240582)","","",""],["Measurement\nFunctions","Distances and Angles","","","Distances and Angles","YES"],["Algorithms","Patient-specific clinical parameters and\ncalculations based on published literature.","","","Patient-specific clinical parameters and\ncalculations based on published literature.","YES"],["3D Reconstruction\nModel","Alignment mode: The 3D model supports the\ninitial placement of the patient anatomic\nlandmarks on the images using a machine\nlearning-based algorithm. It is not displayed to\nthe user and as such it is not part of the device\noutputs.\n3D mode: The 3D reconstruction model is\ndeformed manually by the user through control\npoints up to matching accurately the X-ray\ncontours.","","","Alignment mode: The 3D model supports the\ninitial placement of the patient anatomic\nlandmarks on the images using a machine\nlearning-based algorithm. It is not displayed to\nthe user and as such it is not part of the device\noutputs.\n3D mode: The 3D reconstruction model is\ndeformed manually by the user through control\npoints up to matching accurately the X-ray\ncontours.","YES"],["User Interface","Computer","","","Computer","YES"],["Obtaining an\nimage","Transferred from other devices","","","Transferred from other devices","YES"],["Software\nEnvironment","Cloud-based software","","","Cloud-based software","YES"],["Human\nIntervention for\ninterpretation and\nmanipulation of\nimages","Required","","","Required","YES"],["Control of life-\nsaving devices","None","","","None","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p12-t0","doc_id":"K251747","page_num":12,"bbox":[36.03,92.5,755.97,511.92],"n_rows":5,"n_cols":8,"columns":["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],["","","spineEOS (K240582)","","","spineEOS","",""],["","• With Windows 10 or 11: Google Chrome in\nversion 121 or higher, and Edge in version\n121 or higher.\n• With Mac OS Monterey or Ventura: Google\nChrome in version 121 or higher.\nPC Configuration:\nA stable high speed internet connection is\nrequired: DSL 100Mb/s connection or higher,\nWi-Fi or Ethernet.\nScreen Resolution:\nThe minimum screen resolution ensuring full\ndisplay of the interface is 1366 x 768.","","","• With Windows 10 or 11: Google Chrome in\nversion 130 or higher, and Edge in version\n130 or higher.\n• With Mac OS 15 Sequoia: Google Chrome in\nversion 130 or higher.\nPC Configuration:\nA stable high speed internet connection is\nrequired: DSL 100Mb/s connection or higher,\nWi-Fi or Ethernet.\nScreen Resolution:\nThe minimum screen resolution ensuring full\ndisplay of the interface is 1366 x 768.","","","compatible web browsers and\nMac Operating System."],["Input Data","Patient’s information\nX-rays images\n3D landmarks of the spine generated from VEA\nAlign","","","Patient’s information\nX-rays images\n3D landmarks of the spine generated from VEA\nAlign","","","YES"],["Product Workflow","3D spine reconstruction confirmation: allow\nusers to accept the 3D landmark input data or\nreject the 3D landmark input data and provide\nfeedback on corrective adjustments.\nPreoperative: allow user to consult the\npreoperative state of the patient\nPlanning: allow user to define patient specific\nsurgical strategy\nRod: allow user to define the design of rods","","","3D spine and sacrum model reconstruction\nconfirmation: allow users to accept the 3D\nlandmark input data or reject the 3D landmark\ninput data and provide feedback on corrective\nadjustments.\nPreoperative: allow user to consult the\npreoperative state of the patient\nPlanning: allow user to define patient specific\nsurgical strategy\nRod: allow user to define the design of rods\nThe product includes two workflows according\nto the patient’s age.\n• Pediatric workflow, for patient under 18 years\nold: The user has access to the 3D spine\nreconstruction confirmation and the\nPreoperative steps","","","Similar\nThe workflow steps are identical\ncompared to the predicate. The\npediatric workflow prevents the\nuser to have access to the\nplanning and rod steps.\nHowever, the user still has\naccess to the 3D spine\nreconstruction confirmation and\nthe preoperative steps, with all\nthe image manipulation\nfunctions available in these\nsteps."]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p13-t0","doc_id":"K251747","page_num":13,"bbox":[36.01,92.5,755.99,535.32],"n_rows":16,"n_cols":8,"columns":["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],["","","spineEOS (K240582)","","","spineEOS","",""],["","","","","• Adult workflow, for patient above 18 years\nold: The user has access to all the steps\ndescribed above","","",""],["Tools Available for\nPlanning","• Segmental Alignment\n• Interbody Implant\n• Osteotomy\n• Spondylolisthesis\n• Rod Curvature Management (From T1 to S1)","","","• Segmental Alignment\n• Interbody Implant\n• Osteotomy\n• Spondylolisthesis\n• Rod Curvature Management (From T1 to S2)","","","Similar\nModified spineEOS allows the\nuser to design a patient-specific\nrod until S2 vertebrae based on\nthe landmarks generated by\nVEA Align."],["Software\nFunctionalities /\nModalities","Obtains an image and 3D model transferred\nfrom other devices.","","","Obtains an image and 3D model transferred\nfrom other devices.","","","YES"],["","Provides normative values used to follow the\nimpact of the planning on the patient\nalignment.","","","Provides normative values used to follow the\nimpact of the planning on the patient\nalignment.","","","YES"],["","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues.","","","Provides color-coded clinical parameters to\ndisplay variance from the defined normative\nvalues.","","","YES"],["","Requires human intervention for\ninterpretation and manipulation of images.","","","Requires human intervention for\ninterpretation and manipulation of images.","","","YES"],["Image Manipulation\nFunctions","2D images and 3D spine display and basic\nmanipulation (zoom, panning, angles\nmeasurements, plumbline, and possibility to\nadd comments on the image).","","","","2D images and 3D spine display and basic","","YES"],["","","","","","manipulation (zoom, panning, angles","",""],["","","","","","measurements, plumbline, and possibility to","",""],["","","","","","add comments on the image).","",""],["Measurement\nFunctions","Distances and Angles","","","Distances and Angles","","","YES."],["User Interface","Computer","","","Computer","","","YES"],["Software\nEnvironment","Cloud-based software","","","Cloud-based software","","","YES"],["Clinical Parameters\nComputation","• Pelvic Tilt (PT)\n• Sacral Slope (SS)\n• Pelvic Incidence (PI)\n• Pelvic Obliquity (PO)\n• Sagittal Vertical Axis (SVA)\n• C7-CSL\n• PI-LL\n• T1 Pelvic Angle (TPA)","","","• Pelvic Tilt (PT)\n• Sacral Slope (SS)\n• Pelvic Incidence (PI)\n• Pelvic Obliquity (PO)\n• Sagittal Vertical Axis (SVA)\n• C7-CSL\n• PI-LL\n• T1 Pelvic Angle (TPA)","","","Similar\nExcept for the addition of L1PA,\nT4PA, the axial rotation, disc\nheight and disc segmental lordosis.\nL1PA and T4PA measure the\nsame angle but taking respectively\nL1 and T4 instead of T1. The"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251747-p14-t0","doc_id":"K251747","page_num":14,"bbox":[36.03,92.5,755.97,323.88],"n_rows":4,"n_cols":8,"columns":["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],"rows":[["Characteristic","","Primary Predicate","","","Subject Device","","Substantially Equivalent?"],["","","spineEOS (K240582)","","","spineEOS","",""],["","• Cobb Angle\n• Kyphosis/Lordosis Angle\n• Knee Flexion/Extension Angle\n• Lordosis Percentage Distributions\n• Spondylolisthesis grade (i.e., Slippage\npercentage)","","","• Cobb Angle\n• Kyphosis/Lordosis Angle\n• Knee Flexion/Extension Angle\n• Lordosis Percentage Distributions\n• Spondylolisthesis grade (i.e., Slippage\npercentage)\n• L1 Pelvic Angle (L1PA)\n• T4 Pelvic Angle (T4PA)\n• Axial rotation (not computed)\n• Disc height (anterior and posterior)\n• Disc segmental lordosis","","","subject device uses the same\nvalidated point as the predicate.\nThe axial rotation is displayed\nbased on the input data received\nfrom VEA Align. It is not computed\nat the planning step.\nDisc height and disc segmental\nlordosis are new clinical\nparameters linked to the disc.\nHowever, they aim to calculate\ndistances (height) and angles\n(lordosis), same as the other\nexisting clinical parameters."],["Control of Life-\nSaving Devices","None","","","None","","","YES"]],"caption_candidate":"K240582 - VEA Align / spineEOS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251763-p7-t0","doc_id":"K251763","page_num":7,"bbox":[85.34,352.96,527.02,481.92],"n_rows":3,"n_cols":2,"columns":["Predicate Device (K242461)","Subject Device (K251763)"],"rows":[["Predicate Device (K242461)","Subject Device (K251763)"],["Intended to receive DICOM compliant contrast-\nenhanced CT images, provide manual and machine\nlearning-enabled tools for image analysis and\nsegmentation, and creates an output file that can\nbe used to render a 3D model for preoperative\nsurgical planning and intraoperative display.","SAME intended use."],["","SIMILAR Indications for use:\nAdded MR indication for image analysis\nand non-ML manual segmentation of\nDICOM compliant MR images."]],"caption_candidate":"Comparison of Indications for Use and intended Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251763-p7-t1","doc_id":"K251763","page_num":7,"bbox":[85.34,516.64,527.02,706.08],"n_rows":8,"n_cols":3,"columns":["Description","Predicate Device (K242461)","Subject Device (K251763)"],"rows":[["Description","Predicate Device (K242461)","Subject Device (K251763)"],["Regulation Number","21 CFR §892.2050","21 CFR §892.2050"],["Classification","Class II","Class II"],["Product Code","Primary: QIH; Associate: LLZ","Primary: QIH; Associate: LLZ"],["Prescription use","Rx only","Rx only"],["Host Hardware\nCompatibility","General-purpose computer\nhardware","Same"],["Intended population","Adult patients (ML algorithm)","Same"],["Intended Users","Qualified Professionals","Same"]],"caption_candidate":"Comparison of Device Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251763-p8-t0","doc_id":"K251763","page_num":8,"bbox":[85.93,65.92,526.31,714.36],"n_rows":8,"n_cols":3,"columns":["Description","Predicate Device (K242461)","Subject Device (K251763)"],"rows":[["Description","Predicate Device (K242461)","Subject Device (K251763)"],["Intended Clinical\nDecision Support","The output file can be used to\nrender a 3D model for\npreoperative surgical planning\nand intraoperative display.\nThe output file is meant for\nvisual, non-diagnostic use and\nshall be reviewed by clinicians\nwho are responsible for all final\npatient management decisions.","Same"],["Configuration","Label names, label color\nparameters and label name\ntranslation for kidney CT scans","Equivalent to the predicate\ndevice\nDIFFERENCE: Updated label\nnames, label color parameters\nand label name translation for\nMR scans"],["Principles of Operations\n/ Workflow","Manual segmentation alone\nAuto-segmentation followed by\nmanual segmentation.","Equivalent to the predicate\ndevice\nDIFFERENCES: Manual\nsegmentation only for MR scans"],["User interface /\nEnvironment","Graphical user interface design.\nOffice setting (Segmentation\nSoftware Application running on\na general-purpose computer)","Same"],["Supported Input","DICOM-Compliant CT scans\n(Axial views, contrast enhanced)","Equivalent to the predicate\ndevice\nDIFFERENCES: addition of\nDICOM compliant MR scans"],["Supported Output","Segmentation files that can be\nused to render a 3D model for\npreoperative surgical planning\nand intraoperative display","Same"],["Supported Segmentation\nStructures","Kidney CT structures:\n• ML auto-segmentation -\nParenchyma, Artery, Vein and\nCollecting System\n• Manual segmentation -\nParenchyma, Artery, Vein,\nCollecting System and Mass","Same: Kidney CT structures\n(Manual and ML auto-\nsegmentation)\nDIFFERENCES (MR structures\nfor manual segmentation):\n-Kidney MR structures\n-Prostate MR structures\n-Rectal MR structures"]],"caption_candidate":"IRISeg 510(k) K251763 Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251763-p9-t0","doc_id":"K251763","page_num":9,"bbox":[86.08,65.92,526.3,375.72],"n_rows":5,"n_cols":3,"columns":["Description","Predicate Device (K242461)","Subject Device (K251763)"],"rows":[["Description","Predicate Device (K242461)","Subject Device (K251763)"],["ML Auto-Segmentation\nStructures and\nperformance","4 kidney CT structures:\nParenchyma, Artery, Vein and\nCollecting System\nPerformance: Machine Learning\nAuto-Segmentation Testing of\nkidney CT scans.","Same\nSame"],["Manual Tools and\nmanual segmentation\nperformance","Various segmentation and\nselection tools for manual\nsegmentation.\nPerformance: Manual\nsegmentation testing of kidney\nCT scans","Same\nSame (kidney CT scans)\nEquivalent manual\nsegmentation performance\nfor MR scans"],["2D and 3D Visualization\nFeatures","Volume rendering, 3D model\nvisualization, 2D slice\nvisualization.","Same"],["Segmentation Support\nFeatures","Metadata viewing","Same"]],"caption_candidate":"IRISeg 510(k) K251763 Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p7-t0","doc_id":"K251766","page_num":7,"bbox":[71.83,279.29,543.73,310.85],"n_rows":2,"n_cols":3,"columns":["","Training/Tuning Datasets","Validation Dataset"],"rows":[["","Training/Tuning Datasets","Validation Dataset"],["","(n=1156 samples)","(n=267 samples)"]],"caption_candidate":"race/ethnicity all reflect the broader U.S. population.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p8-t0","doc_id":"K251766","page_num":8,"bbox":[73.15,462.03,544.85,632.82],"n_rows":8,"n_cols":3,"columns":["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std. Dev.)"],"rows":[["Measurement Description","Units","Validation Testing\n(Mean Abs. Error ± Std. Dev.)"],["Tumor Volume (n=218)","cubic centimeters (cc)","5.2 ± 12.5"],["Tumor-to-breast volume ratio (n=218)","%","0.4 ± 1.2"],["Tumor longest dimension (n=242)","centimeters (cm)","1.32 ± 1.65"],["Tumor-to-nipple distance (n=241)","centimeters (cm)","1.17 ± 1.55"],["Tumor-to-skin distance (n=242)","centimeters (cm)","0.60 ± 0.52"],["Tumor-to-chest distance (n=242)","centimeters (cm)","0.86 ± 1.22"],["Tumor center of mass (n=218)","centimeters (cm)","0.60 ± 1.47"]],"caption_candidate":"between expert readers. Performance data for the automated measurements is summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p9-t0","doc_id":"K251766","page_num":9,"bbox":[72.82,147.17,546.11,200.21],"n_rows":3,"n_cols":3,"columns":["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],"rows":[["Performance Measurement","Metric","Validation Testing\n(Mean ± Std. Dev.)"],["Tumor segmentation (n=218)","Volumetric Dice","0.76 ± 0.26"],["","Surface Dice","0.92 ± 0.21"]],"caption_candidate":"Results of Dice and surface Dice are summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p9-t1","doc_id":"K251766","page_num":9,"bbox":[72.82,456.02,540.96,699.98],"n_rows":10,"n_cols":3,"columns":["Predicate Device Comparison","",""],"rows":[["Predicate Device Comparison","",""],["","Predicate Device\n(TumorSight Viz – version 1.2)","Subject Device\n(TumorSight Viz – version 1.3)"],["510(k)","K243189","K251766"],["Manufacturer","SimBioSys, Inc.","SimBioSys, Inc."],["Regulation Number","892.2050","892.2050"],["Regulation Name","Medical image management and\nprocessing system","Medical image management and\nprocessing system"],["Classification","2","2"],["Device Common Name","Image Processing System","Image Processing System"],["Product Code","QIH","QIH"],["Functions","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast","- Extract dynamic contrast\nenhanced MRI sequence from\nMRI images for the 3D display\nand visualization of the anatomy\nof patient’s breast"]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p10-t0","doc_id":"K251766","page_num":10,"bbox":[72.77,71.28,540.98,519.17],"n_rows":5,"n_cols":3,"columns":["Intended Use","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],"rows":[["Intended Use","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz.","TumorSight Viz is intended to\nbe used in the visualization and\nanalysis of breast magnetic\nresonance imaging (MRI)\nstudies for patients with biopsy\nproven early-stage or locally\nadvanced breast cancer.\nTumorSight Viz supports\nevaluation of dynamic MR data\nacquired from breast studies\nduring contrast administration.\nTumorSight Viz performs\nprocessing functions (such as\nimage registration, subtractions,\nmeasurements, 3D renderings,\nand reformats).\nTumorSight Viz also includes\nuser-configurable features for\nvisualizing and analyzing\nfindings in breast MRI studies.\nPatient management decisions\nshould not be made based solely\non the results of TumorSight\nViz."],["Data Source (Input)","MRI","MRI"],["Output/Accessibility","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity","Graphic and text results of\nbreast anatomy are accessed via\na device with internet\nconnectivity"],["Physical Characteristics","\"-non-invasive software package\n-DICOM compatible\"","\"-non-invasive software package\n-DICOM compatible\""],["Safety","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning.","Clinician review and assessment\nof analysis prior to use in pre-\noperative planning."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p11-t0","doc_id":"K251766","page_num":11,"bbox":[72.79,71.4,540.97,509.9],"n_rows":22,"n_cols":3,"columns":["Predicate Device Feature Comparison","",""],"rows":[["Predicate Device Feature Comparison","",""],["Feature","Predicate Device\n(TumorSight Viz – version 1.2)","Subject Device\n(TumorSight Viz – version 1.3)"],["Standard image viewing tools","Yes","Yes"],["MIPs","Yes","Yes"],["Reformats","Yes","Yes"],["Registration","Yes","Yes"],["Subtraction series","Yes","Yes"],["View 3D volume rendering","Yes","Yes"],["Kinetic curves","Yes","Yes"],["Parametric image maps","Yes","Yes"],["Manual DICOM import","Yes","Yes"],["Automated DICOM image\nimport","Yes","Yes"],["Updated segmentation model","Yes","Yes"],["View finding volume","Yes","Yes"],["View finding location","Yes","Yes"],["View finding size","Yes","Yes"],["View kinetic curve with\nhighest uptake","Yes","Yes"],["View finding distance to\nnipple","Yes","Yes"],["View finding distance to skin","Yes","Yes"],["View finding distance to chest","Yes","Yes"],["View adjusted finding size","No - Segmentation is not\neditable, but surgical margins\nare editable","No - Segmentation is not\neditable, but surgical margins\nare editable"],["Interactive rotation of 3D\nvolume rendering","Yes","Yes"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251766-p12-t0","doc_id":"K251766","page_num":12,"bbox":[73.19,71.59,536.81,416.24],"n_rows":12,"n_cols":7,"columns":["Performance","N","Metric","Predicate/","TumorSight","Predicate/","Inter-"],"rows":[["Performance","N","Metric","Predicate/","TumorSight","Predicate/","Inter-"],["Measurement","","","TumorSight","Viz/","Ground","radiologist"],["","","","Viz","Ground","Truth","Variability"],["","","","","Truth","",""],["","","","(Mean","(Mean ±","(Mean ±","(Mean"],["","","","± Std. Dev.)","Std. Dev.)","Std. Dev.)","± Std. Dev.)"],["","","","","","",""],["Longest\nDimension","192","Abs.\nDistance\nError","0.80 cm\n± 1.69 cm","1.27 cm\n± 1.71 cm","1.63 cm\n± 2.01 cm","1.02 cm\n± 1.33 cm"],["Tumor to Skin","192","Abs.\nDistance\nError","0.20 cm\n± 0.42 cm","0.58 cm\n± 0.50 cm","0.61 cm\n± 0.60 cm","0.42 cm\n± 0.45 cm"],["Tumor to\nChest","192","Abs.\nDistance\nError","0.40 cm\n± 0.86 cm","0.89 cm\n± 1.13 cm","0.98 cm\n± 1.16 cm","0.79 cm\n± 1.14 cm"],["Tumor to\nNipple","190","Abs.\nDistance\nError","0.61 cm\n± 1.47 cm","1.06 cm\n± 1.33 cm","1.15 cm\n± 1.40 cm","0.88 cm\n± 1.12 cm"],["Tumor Volume","170","Abs.\nVolume\nError","2.59 cc\n± 7.56 cc","4.21 cc\n± 13.06 cc","5.23 cc\n± 16.95 cc","NA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p10-t0","doc_id":"K251769","page_num":10,"bbox":[66.13,103.8,557.37,734.57],"n_rows":4,"n_cols":3,"columns":["Clinical Aspect","Submitted Device","Primary Predicate Device"],"rows":[["Clinical Aspect","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["Intended Use","§892.2060 Radiological\ncomputer-assisted diagnostic software\nfor lesions suspicious of cancer.\nA radiological computer-assisted\ndiagnostic software for lesions\nsuspicious of cancer is an image\nprocessing prescription device intended\nto aid in the characterization of lesions\nas suspicious for cancer identified on\nacquired medical images such as\nmagnetic resonance, mammography,\nradiography, or computed tomography.\nThe device characterizes lesions based\non features or information extracted from\nthe images and provides information\nabout the lesion(s) to the user.\nDiagnostic and patient management\ndecisions are made by the clinical user.","§892.2060 Radiological\ncomputer-assisted diagnostic\nsoftware for lesions suspicious of\ncancer.\nA radiological computer-assisted\ndiagnostic software for lesions\nsuspicious of cancer is an image\nprocessing prescription device\nintended to aid in the\ncharacterization of lesions as\nsuspicious for cancer identified on\nacquired medical images such as\nmagnetic resonance,\nmammography, radiography, or\ncomputed tomography. The device\ncharacterizes lesions based on\nfeatures or information extracted\nfrom the images and provides\ninformation about the lesion(s) to\nthe user. Diagnostic and patient\nmanagement decisions are made\nby the clinical user."],["Indications for Use","RevealAI-Lung Software is a computer\naided diagnostic (CADx) software\napplication intended for the\ncharacterization of incidentally-detected\nlung nodules on computed tomography\n(CT) scans. When a nodule is identified,\nthe Software automatically compares the\nnodule characteristics with a clinically\nestablished database of lung nodules\nand provides a similarity score to assist\nclinicians’ assessment of patients’\ncancer risk.\nThe mSI score is indicated for the\nevaluation of incidentally-detected\npulmonary nodules of diameter 6-15mm\nin patients aged 18 years or above. In\ncases where multiple abnormalities are\npresent, the mSI score can be used to\nassess each abnormality independently.\nRisk should be interpreted on an\nindividual patient level and mSI is a","Virtual Nodule Clinic (VNC) is a\nsoftware device used in the\ntracking, assessment and\ncharacterization of incidentally\ndetected pulmonary nodules.\nVNC includes a computer-aided\ndiagnosis (CADx) function,\navailable only to pulmonologists\nand radiologists. This automatically\nanalyzes user-selected regions of\ninterest (ROI) within lung CT data\nto provide volumetric and computer\nanalysis based on morphological\ncharacteristics. Using only imaging\nfeatures extracted from the CT\nimage data, an artificial intelligence\nalgorithm calculates a single value,\nthe LCP-CNN score, which is\ndisplayed to the user. The\nLCP-CNN score is analyzed\nrelative to LCP-CNN scores\ngenerated on a database of cases"]],"caption_candidate":"Table 1 Predicate Comparison Chart - Clinical Aspects","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p11-t0","doc_id":"K251769","page_num":11,"bbox":[66.25,86.43,557.42,733.58],"n_rows":3,"n_cols":3,"columns":["Clinical Aspect","Submitted Device","Primary Predicate Device"],"rows":[["Clinical Aspect","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["","relative risk score, not a percentage\ncancer risk.\nNote that mSI is not indicated for lung\ncancer screening. The validation data\nexcluded CT images with missing slices.","with known ground-truth using a\nhistogram display format. The\nLCP-CNN score may be useful in\nthe characterization of pulmonary\nnodules during image interpretation\nand may be used as one input to\nclinical decision making when\nfollowing published clinical\nguidelines.\nVNC’s LCP-CNN score is indicated\nfor the evaluation of incidentally\ndetected solid and semi-solid\npulmonary nodules of diameter\n5-30mm in patients aged 35 years\nor above. In cases where multiple\nabnormalities are present, VNC’s\nLCP-CNN score can be used to\nassess each abnormality\nindependently.\nNote that LCP-CNN is not\nindicated for lung cancer screening\nnor is it indicated for nodules of\npure ground glass opacity. In\naddition, high contrast CT images\nwere not used in clinical validation\n(as measured as >300HU median\nattenuation in the aortic arch) and\nthe validation data also excluded\nCT images with only calcified\nnodules (since these are typically\nconsidered to be benign), with\nimplants, motion artifacts, missing\nslices, or cases with greater than 5\nnodules. Finally, the validation data\nexcluded patients with history of\ncancer of less than 5 years to\navoid the presence of metastatic\nlesions.\nUsers other than radiologists and\npulmonologists, e.g. clinicians,\nnurses, nurse practitioners and\nnavigators, may use VNC to view\nCT images and reports, organize\npatient management workflow,\ntrack patients, record management"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p12-t0","doc_id":"K251769","page_num":12,"bbox":[66.13,86.43,557.42,731.45],"n_rows":7,"n_cols":3,"columns":["Clinical Aspect","Submitted Device","Primary Predicate Device"],"rows":[["Clinical Aspect","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["","","decisions and organize nodule\nclinics. For these users, the LCP-\nCNN score is unavailable."],["Intended Patient\nPopulation","The targeted population inclusion criteria\nare based on those where lung nodules\nare found on CT scans in clinical\npractice, and where product validation\nhas occurred, specifically where lung\nnodules have been identified incidentally\non CT.","Optellum Software is a software\ndevice used in the tracking,\nassessment, and characterization\nof incidentally detected pulmonary\nnodules."],["Contraindications","● Not indicated for use on modalities\nother than lung CT images\n● Not indicated for use on\nnon-lung-nodule image locations\n● Not indicated for unassisted reads\n(device output requires practitioner\nreview)\n● Not indicated for use where image\nquality or the presence of surgical\nor implanted artifacts obscures the\nlung nodule\n● Not indicated for use when CT\nimages were acquired at a slice\nspacing exceeding 5mm","● The Optellum LCP Score is not\nindicated for pure\nGround-Glass Opacities\n(GGO) or for calcified nodules.\n● The Optellum LCP Score is not\nindicated for patients with a\nhistory of cancer less than 5\nyears. The Optellum LCP\nScore is not indicated for\nnodules detected by lung\ncancer screening studies. The\nOptellum LCP Score is not\nindicated for patients with more\nthan five pulmonary nodules.\n● The Optellum LCP Score is not\nindicated for patients with\nthoracic implants that impact\nthe image appearance of the\nnodule.\n● The Optellum LCP Score is not\nindicated for patients younger\nthan 35 years."],["Intended Users","RevealAI-Lung Software is designed to\nbe used by radiologists who are licensed\nto make diagnostic or other follow-up\ndecisions using radiological imagery\nand/or radiology reports. The information\nprovided by RevealAI-Lung should only\nbe used in conjunction with other\nclinically accepted information to guide\nmedical decision-making at the\ndiscretion of the clinician.","A nodule clinic is typically led by a\npulmonologist and includes a\nmulti-disciplinary team of\nradiologists, thoracic surgeon and\nsometimes pathologist and\noncologist."],["Intended Use\nEnvironment","The Software is used in hospitals and\nhealthcare provider office settings.","Virtual Nodule Clinic is intended for\nuse in hospitals to support these\nclinics."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p13-t0","doc_id":"K251769","page_num":13,"bbox":[66.04,165.76,561.67,738.3],"n_rows":13,"n_cols":3,"columns":["Technical Features","Submitted Device","Primary Predicate Device"],"rows":[["Technical Features","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["Regulatory Classification","Regulation: 21 CFR 892.2060\nProduct Code: POK\nDevice Classification Name:\nComputer-Assisted Diagnostic\nSoftware for Lesions Suspicious for\nCancer","Regulation: 21 CFR 892.2060\nProduct Code: POK\nDevice Classification Name:\nComputer-Assisted Diagnostic\nSoftware for Lesions Suspicious for\nCancer"],["Product Features","Assists in malignancy assessment","Increases the accuracy of malignancy\nassessment"],["","Reduces variations between\nindividual physicians","Reduces variations between individual\nphysicians"],["","Improves clinical decision making","Improves clinical decision making"],["","Has been independently clinically\nvalidated in multi-center studies","Has been independently clinically\nvalidated in multi-center studies"],["Diagnostic Workflow","Patient scan: The CT data and any\nprior scans are automatically\nuploaded into the RevealAI-Lung\nsoftware.","Patient scan: The CT and any prior\nscans are automatically uploaded into\nthe Optellum Software."],["","Identify nodule: Easily review any\navailable CT and mark the nodule(s)\nof interest.","Identify nodule: Easily review any\navailable CT and mark the nodule(s) of\ninterest."],["","RevealAI-Lung mSI score: Within\nseconds, RevealAI-Lung analyzes\nthe CT image data to compute the\nscore.","Optellum Lung Cancer Prediction\nscore: Within seconds, the Optellum\nLung Cancer Prediction analyzes the\n3D image region around the nodule to\ncompute the score."],["","Optimal clinical decisions: With\nthe support of the RevealAI-Lung\nmSI score, make the optimal clinical\nmanagement decision for the\npatient.","Optimal clinical decisions: With the\nsupport of the Optellum LCP score,\nmake the optimal clinical management\ndecision for the patient."],["Patient Contact Materials","None. No patient contact","None. No patient contact"],["Device Characteristics","Provides a computer-aided\ndiagnosis (CADx) function to assist\nradiologists who are familiar with\nlung nodule management in the\nassessment and characterization of","Provides a computer-aided diagnosis\n(CADx) function to assist\npulmonologists and radiologists in the\nassessment and characterization of\nincidentally detected pulmonary\nnodules using CT image data."]],"caption_candidate":"Table 2 Predicate Comparison Chart - Technical Features","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p14-t0","doc_id":"K251769","page_num":14,"bbox":[66.17,86.43,561.63,736.58],"n_rows":8,"n_cols":3,"columns":["Technical Features","Submitted Device","Primary Predicate Device"],"rows":[["Technical Features","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["","pulmonary nodules using CT image\ndata.",""],["","Provides a score using machine\nlearning referred to as mSI or\nmalignancy similarity index.","Provides a score using machine\nlearning referred to as LCP-CNN\nalgorithm, or Lung Cancer Prediction\nConvolutional Neural Network."],["","The RevealAI-Lung software is\ndeployed on a server on-premise at\nthe healthcare facility or within\ncloud-based systems securely\nconnected to the facility network.","The LCP-CNN module is deployed on\na GPU-equipped server on hospital\npremises or in the cloud."],["","Connected to two other IT systems\nin the hospital: a DICOM-compatible\nPicture Archiving and\nCommunication System (MIMPS) for\naccessing images and to the\nRadiology Information System (RIS)\nor reporting system for accessing\nthe clinical reports.","Connected to two other IT systems in\nthe hospital: a DICOM-compatible\nPicture Archiving and Communication\nSystem (MIMPS) for accessing images\nand to the Radiology Information\nSystem (RIS) or reporting system for\naccessing the clinical reports."],["Use Environment","RevealAI-Lung is used in hospitals,\nimaging centers and other\nradiologist reader settings where\ndiagnostic evaluation of CT images\noccur.","Pulmonary nodule clinics are typically\nset up in hospitals, so that nodules can\nbe followed up or clinical investigations\ncan be prescribed to confirm the\ndiagnosis associated with the\npresence of pulmonary nodules. A\nnodule clinic is typically led by a\npulmonologist and includes a\nmulti-disciplinary team of radiologists,\nthoracic surgeon and sometimes\npathologist and oncologist. Virtual\nNodule Clinic is intended for use in\nhospitals to support these clinics."],["Computer-Aided\nDiagnosis","The CADx function automatically\nanalyzes user-selected lung nodules\nfrom lung CT data. This function\nextracts image data from the nodule\nto provide 3D analysis and computer\nanalytics based on morphological\ncharacteristics. These imaging (or\nradiomic) features are computed\nsolely from the image extract and\nthen synthesized by an artificial\nintelligence algorithm into a single\nvalue, the mSI score, which is\ndisplayed to the user. The score\ndisplayed is an integer between 0\nand 1 where 0 means very likely\nbenign and 1 means very likely","The CADx function automatically\nanalyzes user-selected regions of\ninterest (ROI) from lung CT data. This\nfunction extracts image data from the\nROI to provide 3D analysis and\ncomputer analytics based on\nmorphological characteristics. These\nimaging (or radiomic) features are\ncomputed solely from the image\nextract and then synthesized by an\nartificial intelligence algorithm into a\nsingle value, the LCP- CNN score,\nwhich is displayed to the user. The\nscore displayed is an integer between\n1 and 10 where 1 means very likely\nbenign and 10 means very likely"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p15-t0","doc_id":"K251769","page_num":15,"bbox":[66.14,86.43,561.63,735.33],"n_rows":6,"n_cols":3,"columns":["Technical Features","Submitted Device","Primary Predicate Device"],"rows":[["Technical Features","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["","malignant. The mSI score is not a\nprobability of malignancy but is\nintended to be analyzed relative to\nmSI scores generated on a\ndatabase of cases with known\nground-truth, using a histogram\ndisplay format.\nThe mSI score, in combination with\nother information may be used in the\ncharacterization of pulmonary\nnodules and may be used as one\ninput to clinical decision making\nwhen following published clinical\nguidelines.","malignant. The LCP-CNN score is not\na probability of malignancy but is\nintended to be analyzed relative to\nLCP-CNN scores generated on a\ndatabase of cases with known\nground-truth, using a histogram\ndisplay format.\nThe LCP-CNN score, in combination\nwith other information may be used in\nthe characterization of incidentally\ndetected pulmonary nodules and may\nbe used as one input to clinical\ndecision making when following\npublished clinical guidelines."],["Principles of Operation","RevealAI-Lung is accessed via\nintegration with a MIMPS system for\nradiologist use. Once generated,\nresults may be incorporated in\nreporting at the discretion of the\nradiologist.","Optellum Software is accessed via a\nweb browser on any PC or Apple\nworkstation in the hospital. The\nsoftware is validated with web\nbrowsers Google Chrome, Mozilla\nFirefox, Microsoft Edge, Microsoft\nInternet Explorer and Apple Safari."],["Image Analysis\nAlgorithm:\nInput","Input to RevealAI-Lung is a DICOM\nCT image and a spatial coordinate\ncentered on a lung nodule.\nInternally RevealAI-Lung creates 3D\nviews of the nodule location and\nwhole CT slice, and extracts\nthousands of machine vision\nfeatures including layers of\ntransformations into frequency and\nother signal processing domains.\nMachine learning relates these\nfeatures to confirmed diagnoses of\ninput nodules.","CNN and input: The LCP-CNN\nsystem is based on the Dense\nConvolutional Network, a widely used\ntype of deep learning CNN\narchitecture that was designed for\ncomputer vision tasks. LCP-CNN’s\nensemble of convolutional neural\nnetwork models ends with a fully\nconnected binary classification layer\n(malignant or benign). Input to\nLCP-CNN is a 3-dimensional crop of a\nCT image, centered on a lung nodule."],["Image Analysis\nAlgorithm:\nTraining Dataset","Training dataset: RevealAI-Lung\nwas trained on radiologist-identified\nlung nodules from 4-30mm in\ndiameter, with data augmentation to\nvary the spatial coordinate. The\nmedian age of the subjects was 63\n(55-74), with 43% of the subjects\nfemale.\nOnly nodules that were confidently\nmatched to a definitive diagnosis\nwere used for training, including","Training dataset: The LCP-CNN\nnetwork was trained using solid and\nsemi-solid nodules of at least 5mm in\ndiameter. The training data consisted\nof 8% malignant nodules and 92%\nbenign nodules and included both\nscreening (95%) and incidentally\ndetected (5%) nodules. The median\nage of the subjects was 62 (20-90)\nand included a mix of US (95%) and\nEU data (5%). The data included\nfemales (38%) and males (62%). Only"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p16-t0","doc_id":"K251769","page_num":16,"bbox":[66.14,86.43,561.63,622.58],"n_rows":6,"n_cols":3,"columns":["Technical Features","Submitted Device","Primary Predicate Device"],"rows":[["Technical Features","Submitted Device","Primary Predicate Device"],["","RevealDx\nRevealAI-Lung\n(This Submission)","Optellum Ltd.\nOptellum™ Software\n(K202300)"],["","following the patients for at least 5\nyears.","nodules that were confidently matched\nto a definitive diagnosis, as provided\nwith the data, were used for training."],["Image Analysis\nAlgorithm:\nOutput","RevealAI-Lung provides an mSI\nscore for relative malignancy risk\nwith a scale of 0 to 1, with 0\nrepresenting lowest risk and 1\nhighest risk. The score is shown with\ncontextual information to relate mSI\nto the training population’s confirmed\nnodule diagnoses and risk levels\nacross the scale.","CNN output: LCP-CNN’s output is a\ncontinuous value between 0 and 1;\nthis is mapped to an integer score\nbetween 1 and 10. This mapping was\nconstructed by computing the raw LCP\nscore on a dataset consisting of\nmalignant (10%) and benign nodules\n(90%) but which were not used during\nthe model training. The mapped\ninteger score is shown to the user\nalongside a plot detailing the cancer\nprevalence in each of 10 bins for a\npopulation with a 30% cancer\nprevalence."],["Design Verification &\nValidation: Nonclinical\nPerformance Testing","Standalone testing of RevealAI-Lung\ndemonstrated that it performed as\nexpected in discriminating between\nbenign and malignant nodules.\nTechnical validation is also\ndescribed for variation in nodule\ncoordinate and acquisition dose.","Standalone testing of the LCP-CNN\nmodel demonstrated that it performed\nas expected in discriminating between\nbenign and malignant nodules,"],["Design Verification &\nValidation: Clinical\nPerformance Testing","Concurrent use of RevealAI-Lung\nimproved radiologists accuracy for\nthe diagnosis of pulmonary nodules\nby an average of 18 points, from\n0.54 to 0.72 (p < 0.001)\nEvery radiologist improved their\nperformance when using\nRevealAI-Lung, and performance\nwas consistent across patient,\nnodule and technical parameters.","● Concurrent use of the LCP-CNN\nfeature in Optellum Virtual Nodule\nClinic software to read CT exams\nimproves radiologists’ and\npulmonologists’ accuracy for the\ndiagnosis of pulmonary nodules by\nan average of 6.85 AUC points (p\n< .001) (from 81.9 to 88.8 AUC)\n● Every radiologist and\npulmonologist improved their\naccuracy when using the Optellum\nLCP- CNN feature to assist their\nread."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251769-p23-t0","doc_id":"K251769","page_num":23,"bbox":[168.5,420.5,460.5,661.5],"n_rows":13,"n_cols":4,"columns":["","AUC","",""],"rows":[["","AUC","",""],["Reader #","without","with","∆"],["1","0.639","0.773","0.134"],["2","0.437","0.695","0.258"],["3","0.502","0.714","0.212"],["4","0.612","0.717","0.106"],["5","0.601","0.736","0.136"],["6","0.477","0.709","0.232"],["7","0.553","0.697","0.143"],["8","0.549","0.682","0.134"],["9","0.491","0.719","0.229"],["10","0.517","0.745","0.228"],["Mean:","0.538","0.719","0.181"]],"caption_candidate":"Every reader improved when using the device (range 0.11 - 0.26):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251822-p7-t0","doc_id":"K251822","page_num":7,"bbox":[72.26,72.6,494.44,702.1],"n_rows":47,"n_cols":3,"columns":["Classification:","II",""],"rows":[["Classification:","II",""],["Product Code:","Primary: LNH",""],["","Secondary: MOS",""],["","",""],["4. Legally Marketed Predicate Device","and Reference Devi","ce"],["","",""],["4.1 Predicate Device","",""],["","",""],["Trade name:","MAGNETOM Free.Ma","x"],["510(k) Number:","K231617",""],["Classification Name:","Magnetic Resonance","Diagnostic Devic"],["","(MRDD)",""],["Classification Panel:","Radiology",""],["CFR Code:","21 CFR § 892.1000",""],["Classification:","II",""],["Product Code:","Primary: LNH",""],["","Secondary: MOS",""],["","",""],["Trade name:","MAGNETOM Free.St","ar"],["510(k) Number:","K231617",""],["Classification Name:","Magnetic Resonance","Diagnostic Devic"],["","(MRDD)",""],["Classification Panel:","Radiology",""],["CFR Code:","21 CFR § 892.1000",""],["Classification:","II",""],["Product Code:","Primary: LNH",""],["","Secondary: MOS",""],["","",""],["4.2 Reference Device","",""],["Trade name:","MAGNETOM Sola",""],["510(k) Number:","K232535",""],["Classification Name:","Magnetic Resonance","Diagnostic Devic"],["","(MRDD)",""],["Classification Panel:","Radiology",""],["CFR Code:","21 CFR § 892.1000",""],["Classification:","II",""],["Product Code:","Primary: LNH",""],["","Secondary: LNI, MOS",""],["","",""],["Trade name:","syngo.via VB40A1",""],["510(k) Number:","K191040",""],["Classification Name:","Picture Archiving and","Communications"],["","System",""],["Classification Panel:","Radiology",""],["CFR Code:","21 CFR §892.2050",""],["Classification:","II",""],["Product Code:","LLZ",""]],"caption_candidate":"Classification: II","well_formed":true,"extraction_settings":"text"}
{"table_id":"K251822-p10-t0","doc_id":"K251822","page_num":10,"bbox":[72.49,375.65,498.58,773.14],"n_rows":9,"n_cols":2,"columns":["","Deep Resolve Boost"],"rows":[["","Deep Resolve Boost"],["Training and\nValidation data","• TSE: more than 25,000 slices\n• HASTE: pretrained on the TSE dataset and refined\nwith more than 10,000 HASTE slices\n• EPI Diffusion: more than 1,000,000 slices\nThe data covered a broad range of body parts, contrasts, fat\nsuppression techniques, orientations, and field strength."],["Sample source","In-house measurements and collaboration partners."],["Equipment","0.55T[1], 1.5T and 3T MRI scanners"],["Protocols","Representative protocols (T1, T2 and PD with and without\nfat saturation) which have been altered (e.g. to increase\nSNR, increase resolution or reduced acceleration)."],["Clinical\nsubgroups","No clinical subgroups have been defined for the datasets."],["Demongraphic\ndistribution","Due to reasons of data privacy, we did not record gender,\nage and ethnicity during data collection."],["Confounders","No confounders have been defined for the datasets."],["Test Statistics\nand Test\nResults\nSummary","The impact of the network has been characterized by several\nquality metrics such as peak signal-to-noise ratio (PSNR) and\nstructural similarity index (SSIM). Most importantly, the\nperformance was evaluated by visual comparisons to evaluate for\nexample, aliasing artifacts, image sharpness and denoising levels.\nThe quality metrics evaluation was performed by conventional\nreconstruction of a set of test data (gold standard). This test data"]],"caption_candidate":"Table 1. Training and validation dataset of Deep Resolve Boost","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251822-p11-t0","doc_id":"K251822","page_num":11,"bbox":[72.66,575.05,501.48,745.3],"n_rows":10,"n_cols":4,"columns":["Predicate Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Free.Max\nwith syngo MR XA60A","K231617, cleared on\nNovember 09, 2023","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["MAGNETOM Free.Star\nwith syngo MR XA60A","K231617, cleared on\nNovember 09, 2023","LNH,\nMOS","Siemens Shenzhen\nMagnetic Resonance Ltd."],["","FDA Clearance Number","Product",""],["Reference Device","","","Manufacturer"],["","and Date","Code",""],["","","",""],["MAGNETOM Sola with\nsyngo MR XA61A","K232535, cleared on\nDecember 22, 2023","LNH,\nLNI,\nMOS","Siemens Healthcare GmbH"],["syngo.via VB40A1","K191040, cleared on May\n16, 2019","LLZ","Siemens Healthcare GmbH"]],"caption_candidate":"Table 2. Predicate devices and reference devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251822-p12-t0","doc_id":"K251822","page_num":12,"bbox":[73.15,307.23,522.99,677.14],"n_rows":15,"n_cols":5,"columns":["","Subject Devices","","Predicate Devices",""],"rows":[["","Subject Devices","","Predicate Devices",""],["","","","",""],["","MAGNETOM","MAGNETOM","MAGNETOM","MAGNETOM"],["Hardware","Free.Max with","Free.Star with","Free.Max with","Free.Star with"],["","syngo MR XA80A","syngo MR XA80A","syngo MR XA60A","syngo MR"],["","","","(K231617)","XA60A"],["","","","","(K231617)"],["Magnet\nSystem","Yes, same as predicate device","","Yes",""],["RF System","Yes, same as predicate device","","Yes",""],["Transmission\ntechnique –\nRF Body Coil","Yes, same as predicate device","","Yes",""],["Gradient\nSystem","Yes, same as predicate device","","Yes",""],["Patient Table","Yes, same as predicate device","","Yes",""],["Computer","Yes, modified compared to predicate\ndevices:\n-new high-end host computer hardware\n-new syngo Workplace\n-modified MaRS hardware","","Yes",""],["Coils","Yes, new coil\ncompared to\npredicate device:\n-Dental coil","Yes, same as\npredicate device","Yes",""],["Other HW\ncomponents","Yes, modified compared to predicate\ndevice:\n-Select&GO display (TPAN 3G)","","Yes",""]],"caption_candidate":"Table 3. Hardware Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251822-p13-t0","doc_id":"K251822","page_num":13,"bbox":[72.6,85.42,522.47,742.18],"n_rows":32,"n_cols":5,"columns":["","Subject Devices","","Predicate Device",""],"rows":[["","Subject Devices","","Predicate Device",""],["","","","",""],["","MAGNETOM","MAGNETOM","MAGNETOM","MAGNETOM"],["Software","Free.Max with","Free.Star with","Free.Max with","Free.Star with"],["","software syngo","software syngo","software syngo","software syngo"],["","MR XA80A","MR XA80A","MR XA60A","MR XA60A"],["","","","(K231617)","(K231617)"],["Sequences","","","",""],["SE-based pulse\nsequence types","Yes, with new and modified features\ncompared to predicate devices:\n-Slice Overlapping for TSE and\nTSE_DIXON\n- Deep Resolve for HASTE\n- SPACE improvement with MTC prep\nmodule","","Yes",""],["GRE-\nbased/Steady-\nState Pulse\nSequence Types","Yes, with new pulse sequences\ncompared to predicate devices:\n-GRE_PHS\n-GRE_Proj","","Yes",""],["EPI-based Pulse\nSequence Types","Yes, with new pulse sequences and\nmodified features compared to\npredicate devices:\n-Deep Resolve for EP2D_DIFF\n-EP_SEG_PHS\n-EP_SEG_FID_PHS\n-EP2D_FID_PHS","","Yes",""],["Feature and Applications","","","",""],["Application Suites","Yes, with new\nfeature: Dental\nSuite","Yes, same as\npredicate device","Yes",""],["myExam AutoPilot","Yes, same as predicate device","","Yes",""],["myExam Assist","Yes, with new and\nmodified features:\n-myExam Dental\nAssist\n-myExam RT Assist","Yes, same as\npredicate device","",""],["","","","Yes",""],["","","","",""],["Inline\nPostprocessing\nFunctions","Yes, same as predicate device","","",""],["","","","Yes",""],["","","","",""],["Visualization","Yes, same as predicate device","","Yes",""],["Basic Post-\nProcessing","Yes, same as predicate device","","",""],["","","","Yes",""],["","","","",""],["Communication","Yes, same as predicate device","","Yes",""],["Application and\npost-processing","Yes, same as predicate device","","",""],["","","","Yes",""],["","","","",""],["Other Software\nFeature /\nApplication","","","Yes",""],["","Yes, same as predicate device","","",""],["","","","",""],["Software Platform\nand General\nWorkflow","Yes, with new and modified features:\n-Select&GO workflow extension\n-Eco Power Mode\n-Extended Gradient Eco Mode\n-System Startup Timer","","Yes",""]],"caption_candidate":"Table 4. Software Features Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251822-p15-t0","doc_id":"K251822","page_num":15,"bbox":[72.63,177.59,503.68,771.22],"n_rows":16,"n_cols":5,"columns":["","","","","Standards"],"rows":[["","","","","Standards"],["Recognition","Product","","Reference",""],["","","Title of Standard","","Development"],["Number","Area","","Number and date",""],["","","","","Organization"],["","","","",""],["19-46","General II\n(ES/\nEMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance","ES60601-\n1:2005/(R)2012 &\nA1:2012\nC1:2009/(R)2012 &\nA2:2010/(R)2012\n(Cons. Text) [Incl.\nAMD2:2021]","ANSI AAMI"],["19-36","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2 Edition\n4.1 2020-09","IEC"],["12-347","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Edition\n4.0 2022-08","IEC"],["5-125","General I\n(QS/\nRM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third Edition\n2 019-12","ISO"],["5-129","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1: 2015 +\nAMD1:2020","ANSI AAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","IEC 62304:2006 +\nAMD1:2015","IEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2020)","NEMA"],["12-352","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 - 3.20\n(2023e)","NEMA"],["2-258","Biocompati\nbility","biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process\n(Biocompatibility)","10993-1:2018","ISO"]],"caption_candidate":"standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p7-t0","doc_id":"K251837","page_num":7,"bbox":[73.09,216.86,545.02,736.87],"n_rows":15,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["","Salix Coronary Plaque\n(V1.0.0) is a web-based, non-\ninvasive software application\nthat is intended to be used for\nviewing, post-processing, and\nanalyzing cardiac computed\ntomography (CT) images\nacquired from a CT scanner in\na Digital Imaging and\nCommunications in Medicine\n(DICOM) Standard format.\nThis software provides\ncardiologists and radiologists\nwith interactive tools that can\nbe used for viewing and\nanalyzing cardiac computed\ntomography (CT) data for\nquantification and\ncharacterization of coronary\nplaques (i.e. atherosclerosis),\nstenosis and to perform\ncalcium scoring in non-\ncontrast cardiac CT\nSalix Coronary Plaque\n(V1.0.0) is intended to\ncomplement standard care as\nan adjunctive tool and is not\nintended as a replacement to\na medical professional’s\ncomprehensive diagnostic\ndecision-making process. The\nsoftware’s semi-automated\nfeatures are intended for an","CaRi-Plaque is\nintended to provide an\noptimized non-invasive\napplication to analyze\ncoronary anatomy and\npathology and aid in\ndetermining treatment\npaths from a set of\nComputed Tomography\n(CT) Angiographic\nimages.\nCaRi-Plaque is a web-\nbased image\nprocessing application.\nIt is a non-invasive\ndiagnostic reading\nsoftware intended for\nuse as an interactive\ntool for viewing and\nanalyzing cardiac CT\ndata for determining the\npresence and extent of\ncoronary plaques and\nluminal stenoses.\nCaRi-Plaque is\nintended for use by\ninternal operators who\nhave been appropriately\ntrained in the software's\nfunctions, capabilities\nand limitations.\nUsers should be aware","Salix Central is a web-\nbased software application\nthat is intended to be used\nfor viewing, post-\nprocessing, and analyzing\ncardiac computed\ntomography (CT) images\nacquired from a CT\nscanner in a Digital\nImaging and\nCommunications in\nMedicine (DICOM)\nStandard format.\nThis software provides\ntools that can be used for\nthe qualitative and\nquantitative assessment of\nphysician-identified\ncoronary plaques and\nstenosis in coronary\ncomputed tomography\nangiography (CCTA) and\nto perform calcium scoring\nin non-contrast cardiac CT.\nSalix Central is intended to\ncomplement standard care\nas an adjunctive tool and is\nnot intended as a\nreplacement to a medical\nprofessional’s\ncomprehensive diagnostic\ndecision-making process.\nThe software’s semi-"],["Intended Use /","","",""],["Indications for","","",""],["Use","","",""],["","","",""]],"caption_candidate":"below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p8-t0","doc_id":"K251837","page_num":8,"bbox":[73.11,67.38,545.06,737.34],"n_rows":24,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["","adult population and should\nonly be used by qualified\nmedical professionals\nexperienced in examining and\nevaluating cardiac CT images.\nUsers should be aware that\ncertain views make use of\ninterpolated data. These\ndata are created by the\nsoftware based on the\noriginal data set.\nInterpolated data may give\nthe appearance of healthy\ntissue in situations where\npathology that is near or\nsmaller than the scanning\nresolution may be present.","that certain views make\nuse of interpolated data.\nThis is data that is\ncreated by the software\nbased on the original\ndata set. Interpolated\ndata may give the\nappearance of healthy\ntissue in situations\nwhere pathology may\nbe present that is near\nor smaller than the\nscanning resolution.\nThe analysis results\nproduced by the\nsoftware and provided\nto the Healthcare\nProfessional are not\nintended to replace the\nskill and judgment of a\nqualified medical\npractitioner. The\nanalysis results should\nbe reviewed with other\nclinical information\nwhich may include but\nis not limited to: The\npatient's original CT\nimages, clinical history,\nsymptoms, clinical risk\nfactors, results of other\ndiagnostic tests, and\nthe clinical judgement of\nappropriately qualified\nHealthcare\nProfessionals.","automated features are\nintended for an adult\npopulation and should only\nbe used by qualified\nmedical professionals\nexperienced in examining\nand evaluating cardiac CT\nimages."],["Device Class","Class II","Class II","Class II"],["","LLZ, QIH","LLZ","QIH"],["Product Code","","",""],["","","",""],["","Cardiologists, Radiologists\nand Clinical Specialists","Cardiologists\nand\nRadiologists","Cardiologists, Radiologists\nand Clinical Specialists"],["Intended Users","","",""],["","","",""],["","Client-Server Google\nChrome Application","Client-Side\nGoogle Chrome\nApplication","Client-Server Google\nChrome Application"],["Operating","","",""],["Platform","","",""],["","","",""],["Stand-alone","Yes","Yes","Yes"],["Software","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p9-t0","doc_id":"K251837","page_num":9,"bbox":[73.12,67.38,545.08,721.85],"n_rows":55,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["","","",""],["DICOM Compliant","Yes; DICOM 3.0 or higher","DICOM 3","Yes; DICOM 3.0 or higher"],["Image Acquisition","CT","CT","CT"],["Secured Network","Yes","Yes","Yes"],["Server Integration","","",""],["Store Images","Yes","Yes","Yes"],["","Yes","Review of coronary\nvessels in 2D MPR,\ncurved MPR, and\nstraightened view.","Yes"],["2D Imaging","","",""],["","","",""],["","Similar","2D measurement tools of\nvessel diameter and\ncontour","Similar"],["2D Measurement","","",""],["","","",""],["","Review of structures in 3D","Same","Same"],["3D Imaging","","",""],["","","",""],["","Yes; this visualization method\nnot necessary for analyzing\nthe presence and extent of\ncoronary plaque and stenosis","N/A; this visualization\nmethod is not necessary\nfor analyzing the\npresence and extent of\ncoronary plaque and\nluminal stenosis","Yes"],["Maximum","","",""],["Intensity","","",""],["Projection (MIP)","","",""],["","","",""],["","Yes, MPR with oblique slicing\nand variable slab thickness is\nnot necessary analyzing the\npresence and extent of\ncoronary plaque and luminal\nstenosis","MPR with oblique slicing\nand variable slab\nthickness is not\nnecessary analyzing the\npresence and extent of\ncoronary plaque and\nluminal stenosis","Yes"],["Multiplanar","","",""],["Reformat (MPR)","","",""],["","","",""],["","Panning\nWindowing\nZooming\nSeries, slices, and phases","Similar","Panning\nWindowing\nZooming\nSeries, slices, and phases"],["Study Analysis –","","",""],["Navigation Tools","","",""],["","","",""],["Study Analysis","Centerline\nWall\nSignal Intensity Overlay","Similar","Centerline\nWall\nSignal Intensity Overlay"],["– Visualization","","",""],["and Editing","","",""],["Measurements","Distance & Area","Area","Distance & Area"],["Centerline","Manual and semi-automatic /\nuser-editable","Similar","Manual and semi-\nautomatic / user-editable"],["Extraction and","","",""],["Wall","","",""],["Segmentation","","",""],["Calcium Scoring","Yes","No","Yes"],["Reporting","Yes","Similar","Yes"],["","","",""],["Quantitative Measurements","","",""],["","","",""],["NCP volume: non-","Yes","Yes","Yes"],["calcified plaque","","",""],["volume","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p10-t0","doc_id":"K251837","page_num":10,"bbox":[73.14,78.86,545.08,731.7],"n_rows":55,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["CP volume:","Yes","Yes","Yes"],["calcified plaque","","",""],["volume","","",""],["LD-NCP volume:","Yes","Yes","Yes"],["low-density","","",""],["noncalcified","","",""],["plaque volume","","",""],["Total Plaque","Yes","Yes","No"],["Volume","","",""],["","No. This is calculated but not\nreported as a device output.","No. This is calculated\nbut not reported as a\ndevice output.","No"],["Vessel Volume","","",""],["","","",""],["Total plaque","Yes","Yes","No"],["burden: total","","",""],["plaque","","",""],["volume/analyzed","","",""],["vessel volume","","",""],["NCP burden:","Yes","No","No"],["noncalcified","","",""],["plaque","","",""],["volume/analyzed","","",""],["vessel volume","","",""],["LD-NCP burden:","Yes","No","No"],["low-density","","",""],["noncalcified","","",""],["plaque volume","","",""],["/analyzed vessel","","",""],["volume","","",""],["CP burden:","Yes","No","No"],["calcified plaque","","",""],["volume/analyzed","","",""],["vessel volume","","",""],["Plaque","Yes","No","No"],["composition","","",""],["Category","","",""],["(Noncalcified","","",""],["plaque, Calcified","","",""],["plaque, Mixed","","",""],["plaque)","","",""],["QCAD: Maximal","Yes; Similar (categorical),\nManual & Editable*","Yes, refers to a single\nreference","Yes; Similar, Manual &\nEditable"],["diameter stenosis,","","",""],["with respect to","","",""],["proximal and","","",""],["distal reference","","",""],["Area stenosis:","No; Calculated based on","Yes","No"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p11-t0","doc_id":"K251837","page_num":11,"bbox":[73.16,67.38,545.06,730.46],"n_rows":56,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["maximum","diameter stenosis","",""],["area stenosis, with","","",""],["respect to","","",""],["proximal and","","",""],["distal","","",""],["references","","",""],["Semi-Automated","Yes, Editable","No","No, Manual & Editable"],["CAD RADS","","",""],["Stenosis:","","",""],["Maximal","","",""],["diameter","","",""],["stenosis, with","","",""],["respect to","","",""],["proximal and","","",""],["distal reference","","",""],["Remodeling","No, Presence/absence of\npositive remodeling as a\nclassifier","Yes","No"],["index: ratio of","","",""],["maximum vessel","","",""],["area/proximal","","",""],["and distal","","",""],["references","","",""],["Plaque length:","No","Yes","No"],["diseased vessel","","",""],["length","","",""],["Contrast density","No","Yes","No"],["difference:","","",""],["maximum","","",""],["difference in","","",""],["contrast density","","",""],["over lesion with","","",""],["respect to","","",""],["proximal","","",""],["reference","","",""],["MLD: minimal","No (categorized stenosis only\ninto CAD RADS)","No. This is calculated\nbut not reported as a\ndevice output.","No"],["luminal diameter","","",""],["over lesion","","",""],["Vessel profile:","Yes, Similar\nVessel Profile: maximum and\nminimum diameter measures\nfrom selected vessel cross\nsections","Yes","Yes, Similar"],["Area,","","",""],["maximum","","",""],["diameter,","","",""],["minimum","","",""],["diameter","","",""],["measured","","",""],["from selected","","",""],["vessel cross","","",""],["section","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p12-t0","doc_id":"K251837","page_num":12,"bbox":[73.13,67.38,545.03,367.57],"n_rows":23,"n_cols":4,"columns":["Predicate Device Comparison","","",""],"rows":[["Predicate Device Comparison","","",""],["Topic","Proposed Device","Primary","Secondary"],["","","Predicate Device","Predicate Device"],["","","",""],["Manufacturer","Artrya Ltd.","Caristo","Artrya Ltd."],["","","",""],["","","",""],["Model Name","Salix Coronary Plaque (V1.0.0)","CaRi-Plaque","Salix Central"],["","","",""],["510(k) Number","Subject Device: K251837","K242240","K243038"],["Lumen profile:","Yes, Similar\nLumen Profile: maximum and\nminimum diameter measures\nfrom selected vessel cross\nsections","Yes","Yes, Similar"],["Area, maximum","","",""],["diameter,","","",""],["minimum","","",""],["diameter","","",""],["measured from","","",""],["selected lumen","","",""],["cross section","","",""],["","Yes. Semi-automatic with full\noption to manually edit with\noutput demonstrated to meet\npre-determined acceptance\ncriteria in clinical performance\nstudy.","Yes. Semi-automatic\n(threshold-based\nsegmentation with full\noption to edit); output\ndemonstrated to meet\npre-determined\nacceptance criteria in\nclinical performance\nstudy.","Deep learning based,\nvessel & lumen only;\nvalidated with ground truth\nby clinician expert readers,\nwith full option to edit."],["Vessel, plaque,","","",""],["and lumen","","",""],["segmentation","","",""],["","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251837-p14-t0","doc_id":"K251837","page_num":14,"bbox":[66.5,205.81,549.93,397.61],"n_rows":12,"n_cols":11,"columns":["","Salix Coronary Plaque","","Statistic","","Estimate","","","Acceptance","","Result"],"rows":[["","Salix Coronary Plaque","","Statistic","","Estimate","","","Acceptance","","Result"],["","Output","","","","[95% CI]","","","Criteria","",""],["Vessel Level Stenosis","","","Percentage within\none CAD-RADS\ncategory","95.8% [94.1%, 97.3%]","","","90%","","","Pass"],["Total plaque","","","ICC31","0.96 [0.94, 0.98]","","","0.70","","","Pass"],["Calcified plaque","","","ICC31","0.96 [0.90, 0.99]","","","0.80","","","Pass"],["Noncalcified plaque","","","ICC31","0.91 [0.84, 0.95]","","","0.55","","","Pass"],["Low attenuating plaque","","","ICC31","0.61 [0.41, 0.93]","","","0.30","","","Pass"],["Calcium Scoring","","","Pearson Correlation","0.958 [0.947, 0.966]","","","0.90","","","Pass"],["Centerline Extraction","","","Overlap score","0.8604 [0.8445, 0.8750]","","","0.80","","","Pass"],["Vessel Labelling","","","F1 Score","0.8264 [0.8047, 0.8479]","","","0.70","","","Pass"],["Lumen Wall Segmentation","","","Dice Score","0.8996 [0.8938, 0.9055]","","","0.80","","","Pass"],["Vessel Wall Segmentation","","","Dice Score","0.9016 [0.8962, 0.9070]","","","0.80","","","Pass"]],"caption_candidate":"Salix Coronary Plaque performance exceeded all the pre-defined acceptance criteria for all validation tests.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p8-t0","doc_id":"K251839","page_num":8,"bbox":[108.02,349.13,537.48,705.58],"n_rows":14,"n_cols":5,"columns":["ITEM","Proposed Device\nuMI Panvivo","","Predicate Device\nuMI Panvivo(K243538)",""],"rows":[["ITEM","Proposed Device\nuMI Panvivo","","Predicate Device\nuMI Panvivo(K243538)",""],["Model","uMI Panvivo","uMI Panvivo S","uMI Panvivo","uMI\nPanvivo S"],["Patient bore size","700mm","700mm","700mm","700mm"],["PET System","Scintillator\nmaterial: LYSO\nNumber of\ndetector rings:\n• 100\nAxial FOV:\n• 295 mm","Scintillator\nmaterial: LYSO\nNumber of\ndetector rings:\n• 80\nAxial FOV:\n• 235mm","Scintillator material:\nLYSO\nNumber of detector\nrings:\n• 100\nAxial FOV:\n• 295 mm","Scintillator\nmaterial:\nLYSO\nNumber of\ndetector\nrings:\n• 80\nAxial FOV:\n235mm"],["CT System","uCT 780","uCT 780","uCT 780","uCT 780"],["Maximum table\nload","250kg","250kg","250kg","250kg"],["Software function","","","",""],["Deep MAC","Yes","Yes","No","No"],["Digital Gating","Yes","Yes","No","No"],["OncoFocus","Yes","Yes","No","No"],["NeuroFocus","Yes","Yes","No","No"],["DEEPRECON.PET","Yes","Yes","No","No"],["uExcel DPR","Yes","Yes","No","No"],["ukinetics","Yes","Yes","No","No"]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p11-t0","doc_id":"K251839","page_num":11,"bbox":[108.39,281.86,537.07,526.75],"n_rows":19,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=20)","",""],["Gender, N(%)","",""],["Male","","13(65%)"],["Female","","7(35%)"],["Age, N(%): Min=5, Max=79, Avg.=59.95, Std.=18.28","",""],["0-29","","1(5%)"],["30-49","","5(25%)"],["50-69","","7(35%)"],[">=70","","7(35%)"],["Ethnicity, N(%)","",""],["White","","8(40%)"],["Asian","","11(55%)"],["Black","","1(5%)"],["Body Mass Index (BMI), N(%): Min=14.46, Max=40.51, Avg.=26.45, Std.=5.48","",""],["Underweight (<18.5)","","1(5%)"],["Healthy weight (18.5-24.9)","","7(35%)"],["Overweight (25.0-29.9)","","8(40%)"],["Obesity (>=30.0)","","4(20%)"]],"caption_candidate":"Table 2 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p13-t0","doc_id":"K251839","page_num":13,"bbox":[108.38,266.02,537.08,510.91],"n_rows":19,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=19)","",""],["Gender, N(%)","",""],["Male","","13(68.4%)"],["Female","","6(31.6%)"],["Age, N(%)","",""],["<18","","1(5.3%)"],["18-40","","3(15.8%)"],["41-65","","9(47.3%)"],[">65","","6(31.6%)"],["Ethnicity, N(%)","",""],["White","","7(36.8%)"],["Asian","","11(57.9%)"],["Black","","1(5.3%)"],["Body Mass Index (BMI), N(%)","",""],["Underweight (<18.5)","","1(5.3%)"],["Healthy weight (18.5-24.9)","","10(52.5%)"],["Overweight (25.0-29.9)","","4(21.1%)"],["Obesity (>=30.0)","","4(21.1%)"]],"caption_candidate":"Table 4 The demographic distribution of human subjects","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p13-t1","doc_id":"K251839","page_num":13,"bbox":[108.38,652.18,537.08,713.5],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["Quantitative\nevaluation","Contrast recovery (CR),\nbackground variability (BV),\nand contrast-to-noise ratio\n(CNR) were calculated using","The averaged CR, BV, and\nCNR of the uExcel DPR images\nshould be superior to those of\nthe OSEM images.","Pass"]],"caption_candidate":"Table 5 The performance evaluation report criteria of uExcel DPR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p15-t0","doc_id":"K251839","page_num":15,"bbox":[108.41,234.19,537.05,478.27],"n_rows":19,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=50)","",""],["Gender, N(%)","",""],["Male","","31(62%)"],["Female","","19(38%)"],["Age, N(%): Min=34, Max=90, Avg.=72.7, Std.=11.9","",""],["30-44","","2(4%)"],["45-64","","6(12%)"],[">=65","","39(78%)"],["unkown","","3(6%)"],["Ethnicity, N(%)","",""],["White","","34(68%)"],["Black","","3(6%)"],["Asian","","13(26%)"],["Body Mass Index (BMI), N(%): Min=15.1, Max=34.6, Avg.=24.0, Std.=3.8","",""],["Underweight (<18.5)","","2(4%)"],["Healthy weight (18.5-24.9)","","24(48%)"],["Overweight (25.0-29.9)","","23(46%)"],["Obesity (>=30.0)","","1(2%)"]],"caption_candidate":"Table 6 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p16-t0","doc_id":"K251839","page_num":16,"bbox":[108.57,154.94,537.16,336.41],"n_rows":3,"n_cols":4,"columns":["Evaluation\nItem","Evaluation Method","Criteria","Results"],"rows":[["Evaluation\nItem","Evaluation Method","Criteria","Results"],["Volume relative\nto no motion\ncorrection\n(∆Volume).","Calculate the volume\nrelative to no motion\ncorrection images","The ∆Volume\nvalue is less\nthan 0%.","Pass"],["Maximal\nstandardized\nuptake value\nrelative to no\nmotion\ncorrection\n(∆SUVmax)","Calculate the SUVmax\nrelative to no motion\ncorrection images","The ∆SUVmax\nvalue is large\nthan 0%.","Pass"]],"caption_candidate":"Table 7 The performance evaluation report criteria of OncoFocus","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p16-t1","doc_id":"K251839","page_num":16,"bbox":[108.57,683.91,537.16,708.16],"n_rows":2,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=20)","",""]],"caption_candidate":"Table 8 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p17-t0","doc_id":"K251839","page_num":17,"bbox":[108.25,77.58,537.15,226.58],"n_rows":12,"n_cols":2,"columns":["Gender, N(%)",""],"rows":[["Gender, N(%)",""],["Male","12(60%)"],["Female","8(40%)"],["Age, N(%)",""],["0-29","1(5%)"],["30-49","1(5%)"],["50-69","9(45%)"],[">=70","9(45%)"],["Ethnicity, N(%)",""],["Caucasian","1(5%)"],["Asian","18(90%)"],["Negroid","1(5%)"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251839-p17-t1","doc_id":"K251839","page_num":17,"bbox":[108.25,352.01,537.15,461.71],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["Quantitative\nevaluation","For PMMA phantom data, the\naverage CT value in the affected\narea of the metal substance and\nthe same area of the control image\nbefore and after DeepMAC was\ncompared.","After using DeepMAC,\nthe difference between\nthe average CT value in\nthe affected area of the\nmetal substance and the\nsame area of the control\nimage does not exceed\n10HU.","Pass"]],"caption_candidate":"Table 9 The performance evaluation report criteria of DeepMAC","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251873-p9-t0","doc_id":"K251873","page_num":9,"bbox":[159.17,80.49,479.08,465.3],"n_rows":28,"n_cols":2,"columns":["","All Cases (%)"],"rows":[["","All Cases (%)"],["",""],["Breast Density","99 (4.9)\n864 (43.2)\n901 (45.0)\n138 (6.9)"],["A",""],["B",""],["C",""],["D",""],["",""],["Patient Age","94.5\n59.1 (10.9)\n35.2"],["Max",""],["Mean (SD)",""],["Min",""],["",""],["Patient Ethnicity","155 (7.7)\n1667 (83.3)\n180 (9.0)"],["Hispanic/Latino",""],["Not Hispanic/Latino",""],["Unknown",""],["",""],["Patient Race",""],["American Indian/Alaska Native",""],["",""],["Asian",""],["Black/African American",""],["Multiple",""],["Native Hawaiian/Other Pacific Islander",""],["Other",""],["Unknown",""],["White",""]],"caption_candidate":"www.deephealth.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p5-t0","doc_id":"K251931","page_num":5,"bbox":[108.26,474.4,523.14,587.08],"n_rows":8,"n_cols":2,"columns":["510(K) Number","K240773"],"rows":[["510(K) Number","K240773"],["Trade Name","BioTraceIO Vision 1.4"],["Manufacturer","Techsomed Medical Technologies. LTD."],["Device Name","VisAble.IO"],["Regulation Number","892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Regulatory Class","Class II"],["Primary Product Code","QTZ, QIH, LLZ"]],"caption_candidate":"Predicate Devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p8-t0","doc_id":"K251931","page_num":8,"bbox":[72.45,280.77,535.53,520.06],"n_rows":7,"n_cols":6,"columns":["","Subject Device\nBioTraceIO Vision (Ver 1.7)","","Predicate Device","","Comments"],"rows":[["","Subject Device\nBioTraceIO Vision (Ver 1.7)","","Predicate Device","","Comments"],["","","","VisAble.IO (Ver 1.4)","",""],["","","","Renamed as BioTraceIO","",""],["","","","Vision","",""],["510(k)\nnumber","TBD","K240773","","",""],["Classification","Class II 892.2050 QTZ, QIH,\nLLZ","Class II 892.2050 QTZ, QIH,\nLLZ","","","Same"],["Intended Use","The intended patient\npopulation is patients chosen\nby interventional radiologists\nto undergo ablation\ntreatment (including patients\nwith soft tissue lesions).","The intended patient\npopulation is patients chosen\nby interventional radiologists\nto undergo ablation\ntreatment (including patients\nwith soft tissue lesions).","","","Same"]],"caption_candidate":"SUBSTANTIAL EQUIVALENCE COMPARISON TABLE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p9-t0","doc_id":"K251931","page_num":9,"bbox":[72.42,72.36,535.56,765.9],"n_rows":5,"n_cols":4,"columns":["","processing during ablation\nprocedures.\nBioTraceIO Vision is used to\nassist physicians in planning\nablation procedures,\nincluding identifying ablation\ntargets and virtual ablation\nneedle placement.\nBioTraceIO VIsion is used to\nassist physicians in\nconfirming ablation zones.\nThe software is not intended\nfor diagnosis. The software is\nnot intended to predict\nablation volumes or predict\nablation success.","processing during liver\nablation procedures.\nBioTraceIO Vision is used to\nassist physicians in planning\nablation procedures,\nincluding identifying ablation\ntargets and virtual ablation\nneedle placement.\nBioTraceIO Vision is used to\nassist physicians in\nconfirming ablation zones.\nThe software is not intended\nfor diagnosis. The software is\nnot intended to predict\nablation volumes or predict\nablation success.","ablation\nprocedures.\nExisting liver\nregistration\nalgorithms were\nadapted for kidney\nanatomy and\nsegmentation\nalgorithms were\ndeveloped for\nkidney anatomy.\nThese\nmodifications\nrepresent an\nextension of\nestablished\nfunctionality and\ndo not raise new\nquestions of safety\nor effectiveness.\nPerformance\ntesting of V1.7\nsupports\nequivalence to the\npredicate device."],"rows":[["","processing during ablation\nprocedures.\nBioTraceIO Vision is used to\nassist physicians in planning\nablation procedures,\nincluding identifying ablation\ntargets and virtual ablation\nneedle placement.\nBioTraceIO VIsion is used to\nassist physicians in\nconfirming ablation zones.\nThe software is not intended\nfor diagnosis. The software is\nnot intended to predict\nablation volumes or predict\nablation success.","processing during liver\nablation procedures.\nBioTraceIO Vision is used to\nassist physicians in planning\nablation procedures,\nincluding identifying ablation\ntargets and virtual ablation\nneedle placement.\nBioTraceIO Vision is used to\nassist physicians in\nconfirming ablation zones.\nThe software is not intended\nfor diagnosis. The software is\nnot intended to predict\nablation volumes or predict\nablation success.","ablation\nprocedures.\nExisting liver\nregistration\nalgorithms were\nadapted for kidney\nanatomy and\nsegmentation\nalgorithms were\ndeveloped for\nkidney anatomy.\nThese\nmodifications\nrepresent an\nextension of\nestablished\nfunctionality and\ndo not raise new\nquestions of safety\nor effectiveness.\nPerformance\ntesting of V1.7\nsupports\nequivalence to the\npredicate device."],["User\nPopulation","Qualified trained physicians","Qualified trained physicians","Same"],["Where used","The application’s use\nenvironment is the Operation\nRoom and the hospital\nhealthcare environment such\nas interventional radiology\ncontrol room","The application’s use\nenvironment is the Operation\nRoom and the hospital\nhealthcare environment such\nas interventional radiology\ncontrol room","Same"],["Energy Used","None – software only\napplication. The software\napplication does not deliver\nor depend on energy\ndelivered to or from patients","None – software only\napplication. The software\napplication does not deliver\nor depend on energy\ndelivered to or from patients","Same"],["Technological\nCharacteristics","BioTraceIO Vision is a stand-\nalone software application\nwith tools and features\ndesigned to assist users in\nplanning ablation procedures\nas well as tools for treatment\nconfirmation. The use\nenvironment the device is\nthe Operating Room and the\nhospital healthcare\nenvironment such as","BioTraceIO VIsion is a stand-\nalone software application\nwith tools and features\ndesigned to assist users in\nplanning liver ablation\nprocedures as well as tools\nfor treatment confirmation.\nThe use environment the\ndevice is the Operating Room\nand the hospital healthcare\nenvironment such as","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p10-t0","doc_id":"K251931","page_num":10,"bbox":[72.42,72.36,535.56,751.86],"n_rows":4,"n_cols":4,"columns":["","interventional radiology\ncontrol room. BioTraceIO\nVision has six distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument\nPlacement (Needle\nPlanning)\n• Ablation Zone\nSegmentation\n• Registration of Pre-\nProcedure Images\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-\nInterventional\nImages; Quantitative\nAnalysis)","interventional radiology\ncontrol room. BioTraceIO\nVision has six distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument\nPlacement (Needle\nPlanning)\n• Ablation Zone\nSegmentation\n• Registration of Pre-\nProcedure Images\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-\nInterventional\nImages; Quantitative\nAnalysis)",""],"rows":[["","interventional radiology\ncontrol room. BioTraceIO\nVision has six distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument\nPlacement (Needle\nPlanning)\n• Ablation Zone\nSegmentation\n• Registration of Pre-\nProcedure Images\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-\nInterventional\nImages; Quantitative\nAnalysis)","interventional radiology\ncontrol room. BioTraceIO\nVision has six distinct\nworkflow steps:\n• Data Import\n• Anatomic Structures\nSegmentation\n• Instrument\nPlacement (Needle\nPlanning)\n• Ablation Zone\nSegmentation\n• Registration of Pre-\nProcedure Images\n• Treatment\nConfirmation\n(Registration of Pre-\nand Post-\nInterventional\nImages; Quantitative\nAnalysis)",""],["Design:\nSupported\nmodalities","CT, MR","CT, MR","Same"],["Design: Data\nVisualization","Window and level, pan,\nzoom, cross- hairs, slice\nnavigation","Window and level, pan,\nzoom, cross- hairs, slice\nnavigation","Same"],["Design; Image\nSegmentation","Tools for segmenting 3D\nVOIs, including target tissues,\nice ball (for cryoablation),\nablation zones, vessels, liver\nand kidney.","Tools for segmenting 3D VOIs,\nincluding target tissues,\nablation zones, vessels and\nliver.","Addition of tools\nfor segmenting 3D\nVIOs for kidney.\nThese\nmodifications\nrepresent an\nextension of\nestablished\nfunctionality and\ndo not raise new\nquestions of safety\nor effectiveness.\nPerformance\ntesting of V1.7\nsupports\nequivalence to the\npredicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p11-t0","doc_id":"K251931","page_num":11,"bbox":[72.42,72.36,535.56,357.98],"n_rows":2,"n_cols":4,"columns":["Design: Image\nregistration","Registration of multiple\nimages and imaging\nmodalities into a single view.","Registration of multiple\nimages and imaging\nmodalities into a single view.","Same"],"rows":[["Design: Image\nregistration","Registration of multiple\nimages and imaging\nmodalities into a single view.","Registration of multiple\nimages and imaging\nmodalities into a single view.","Same"],["Design:\nAblation zone\nconfirmation","Registration of the planning\nscan, containing the\nidentified target tissue, with\nthe confirmation scan\nshowing the ablation zone.\nThe delineated target tissue\non the planning scan is then\nprojected onto the\nconfirmation scan and\noverlaid onto the delineated\nablation zone segmentation.\nThis helps the user in\nanalysing if the ablation zone\ncovers the target tissue with\nthe desired amount of\nmargin.","Registration of the planning\nscan, containing the\nidentified target tissue, with\nthe confirmation scan\nshowing the ablation zone.\nThe delineated target tissue\non the planning scan is then\nprojected onto the\nconfirmation scan and\noverlaid onto the delineated\nablation zone segmentation.\nThis helps the user in\nanalysing if the ablation zone\ncovers the target tissue with\nthe desired amount of\nmargin.","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251931-p13-t0","doc_id":"K251931","page_num":13,"bbox":[72.26,98.25,523.11,563.74],"n_rows":28,"n_cols":13,"columns":["","Imaging Modality","","","Algorithm","","","","Metric","","","Performance",""],"rows":[["","Imaging Modality","","","Algorithm","","","","Metric","","","Performance",""],["","Organ Segmentation","","","","","","","","","","",""],["CT","","","Liver Segmentation","","","","Mean DICE","","","0.98","",""],["MR","","","Liver Segmentation","","","","Mean DICE","","","0.93","",""],["CT","","","Kidney Segmentation****","","","","Mean DICE","","","0.91","",""],["","Ablation Target Segmentation","","","","","","","","","","",""],["CT","","","Liver Ablation Target Segmentation","","","","Mean DICE","","","0.82","",""],["CT","","","Kidney Ablation\nTarget Segmentation","","1 stroke***","","Mean DICE","","","0.79","",""],["","","","","","2 strokes***","","Mean DICE","","","0.79","",""],["","","","","","3 strokes***","","Mean DICE","","","0.79","",""],["MR","","","Liver Ablation Target Segmentation","","","","Mean DICE","","","0.76","",""],["","Ablation Zone Segmentation","","","","","","","","","","",""],["CT","","","Liver Ablation Zone Segmentation","","","","Mean DICE","","","0.88","",""],["CT","","","Kidney Ablation Zone\nSegmentation","","1 stroke***","","Mean DICE","","","0.76","",""],["","","","","","2 strokes***","","Mean DICE","","","0.77","",""],["","","","","","3 strokes***","","Mean DICE","","","0.78","",""],["CT","","","Kidney Ice Ball\nSegmentation","","1 stroke***","","Mean DICE","","","0.80","",""],["","","","","","2 strokes***","","Mean DICE","","","0.81","",""],["","","","","","3 strokes***","","Mean DICE","","","0.83","",""],["","Vessel Segmentation","","","","","","","","","","",""],["CT","","","Liver Vessels Segmentation*\n(HV+PV)","","","","Mean DICE","","","0.72","",""],["","","","","","","","Mean Centerline\nDICE","","","0.76","",""],["","Registration","","","","","","","","","","",""],["CT/MR","","","Liver Registration Pre-ablation MR –\nPre-ablation CT","","","","MCD**","","","5.04 mm","",""],["CT","","","Kidney Registration Diagnostic CT –\nPre-ablation CT","","","","MCD**","","","4.61 mm","",""],["CT","","","Liver Registration Pre-ablation CT –\nPost-ablation CT","","","","MCD**","","","4.09 mm","",""],["CT","","","Kidney Registration Pre-ablation CT\n– Post-ablation CT","","","","MCD**","","","3.06 mm","",""],["CT/MR","","","Liver Registration Pre-ablation MR –\nPost-ablation CT","","","","MCD**","","","4.75 mm","",""]],"caption_candidate":"The following table provides a summary of the validation results:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p5-t0","doc_id":"K251934","page_num":5,"bbox":[72.24,306.06,522.78,379.74],"n_rows":5,"n_cols":4,"columns":["Name of Device:","qXR-Detect","",""],"rows":[["Name of Device:","qXR-Detect","",""],["Classification Name:","Medical image Analyzer","",""],["Regulatory Class:","Class II","",""],["Regulation Number:","","21 CFR 892.2070",""],["Product Code:","MYN","",""]],"caption_candidate":"2 SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p5-t1","doc_id":"K251934","page_num":5,"bbox":[72.24,433.14,522.78,528.3],"n_rows":6,"n_cols":5,"columns":["Name of Device:","Chest CAD","","",""],"rows":[["Name of Device:","Chest CAD","","",""],["Manufacturer:","Imagen Technologies, Inc","","",""],["510(k) Number:","","K210666","",""],["Regulatory Class:","Class II","","",""],["Regulation Number:","","21 CFR 892.2070","",""],["Product Code","MYN","","",""]],"caption_candidate":"3 PREDICATE DEVICES","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p7-t0","doc_id":"K251934","page_num":7,"bbox":[72.42,72.36,545.88,432.9],"n_rows":9,"n_cols":3,"columns":["Image Modality","Chest Radiographs","Chest Radiographs"],"rows":[["Image Modality","Chest Radiographs","Chest Radiographs"],["Clinical Finding and\nClinical Output","Suspicious regions of interest (ROI)\nTo inform the primary diagnostic\nand patient management decisions\nthat are made by the clinical user.","Suspicious regions of interest (ROI)\nTo inform the primary diagnostic and\npatient management decisions that\nare made by the clinical user."],["Intended Users","ER physicians, Family medicine\npractitioners and radiologists","Physicians"],["Software and Technical Information","",""],["Machine\nLearning\nMethodology","Deep Learning","Deep Learning"],["Image Source","DICOM Source (e.g., imaging device,\nintermediate DICOM node, PACS\nsystem, etc.)","DICOM Source (e.g., imaging device,\nintermediate DICOM node, PACS\nsystem, etc.)"],["Image Viewing","PACS system\nImage annotations made on copy of\noriginal image.","PACS system\nImage annotations made on copy of\noriginal image or image annotations\ntoggled on/off"],["Deployment\nPlatform","Deployment on-premises or on\ncloud and connection to several\ncomputing platforms and X-ray\nimaging platforms such as X-ray\nradiographic systems, or PACS","Deployment on-premises or on\ncloud and connection to several\ncomputing platforms and X-ray\nimaging platforms such as X-ray\nradiographic systems, or PACS"],["Privacy","HIPAA Compliant","HIPAA Compliant"]],"caption_candidate":"Qure.ai 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p8-t0","doc_id":"K251934","page_num":8,"bbox":[72.93,636.82,527.2,766.34],"n_rows":5,"n_cols":2,"columns":["Category","AUC (95%CI)"],"rows":[["Category","AUC (95%CI)"],["Lung","0.893\n(0.879-0.907)"],["Pleura","0.95\n(0.94-0.96)"],["Mediastinum\n/Hila","0.891\n(0.875-0.907)"],["Bone","0.879\n(0.854-0.905)"]],"caption_candidate":"Standalone Performance metrics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p9-t0","doc_id":"K251934","page_num":9,"bbox":[72.66,72.88,527.24,129.32],"n_rows":2,"n_cols":2,"columns":["Hardware","0.958\n(0.95-0.966)"],"rows":[["Hardware","0.958\n(0.95-0.966)"],["Other","0.915\n(0.895-0.935)"]],"caption_candidate":"Qure.ai 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p10-t0","doc_id":"K251934","page_num":10,"bbox":[72.38,138.42,528.48,319.62],"n_rows":8,"n_cols":3,"columns":["ROI","wAFROC with 95% CI -\nUnaided","wAFROC with 95% CI - Aided"],"rows":[["ROI","wAFROC with 95% CI -\nUnaided","wAFROC with 95% CI - Aided"],["Overall","0.6894 (0.6453 -0.7335)","0.7505 (0.7029-0.7980)"],["Lung","0.7270 (0.6857-0.7682)","0.7908 (0.7525-0.8291)"],["Pleura","0.7829 (0.7427-0.8230)","0.8460 (0.8127-0.8794)"],["Mediastinum, Hila and Heart","0.6857 (0.6364-0.7350)","0.7773 (0.7298-0.8248)"],["Bone","0.7117 (0.6712-0.7522)","0.8133 (0.7745-0.8521)"],["Hardware","0.7232 (0.6930-0.7533)","0.7330 (0.7044-0.7616)"],["Other","0.7975 (0.7512-0.8437)","0.8329 (0.7929-0.8728)"]],"caption_candidate":"Table 4 wAFROC of reads unaided and aided by qXR-Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p10-t1","doc_id":"K251934","page_num":10,"bbox":[72.38,503.22,523.32,603.12],"n_rows":2,"n_cols":6,"columns":["AUROC 95% CI\n-Unaided","AUROC with\n95% CI - Aided","Sensitivity\n95% CI -\nUnaided","Sensitivity\nwith 95% CI -\nAided","Specificity\n95% CI -\nUnaided","Specificity\nwith 95% CI -\nAided"],"rows":[["AUROC 95% CI\n-Unaided","AUROC with\n95% CI - Aided","Sensitivity\n95% CI -\nUnaided","Sensitivity\nwith 95% CI -\nAided","Specificity\n95% CI -\nUnaided","Specificity\nwith 95% CI -\nAided"],["0.8466\n(0.8106-\n0.8826)","0.8720\n(0.8339-\n0.9100)","0.8896\n(0.8596-\n0.9195)","0.9338\n(0.9096-\n0.9579)","0.5556\n(0.4297-\n0.6814)","0.6219\n(0.5065-\n0.7373)"]],"caption_candidate":"Table 5 AUROC, Sensitivity and Specificity of reads unaided and aided by qXR-Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p11-t0","doc_id":"K251934","page_num":11,"bbox":[72.48,243.36,522.48,763.2],"n_rows":7,"n_cols":2,"columns":["Modifications Summary",""],"rows":[["Modifications Summary",""],["M1 – Data Driven Retraining",""],["Description","Modification 1 (M1) will involve retraining the\nexisting model using newly acquired, high-\nquality adult chest radiograph datasets to\nimprove device performance without altering\nthe underlying model architecture."],["Rationale","Improve the algorithm performance"],["Retraining Triggers","The availability of a new, high-quality dataset\nobtained from different parts of US, that\nimproves the diversity of the training data,\noffering a logical pathway to improve overall\nmodel performance."],["Testing Methods","Retraining with newly acquired, high-quality\nadult chest radiograph datasets, followed by\nlocked test-set evaluation and comparison to\nbaseline model using predefined acceptance\ncriteria. Performance evaluation for\nModification 1 will ensure that the retrained\nCNN-based model continues to operate safely,\neffectively, and within the boundaries of the\ndevice’s cleared indications for use. The\nupdated model will be evaluated using a\npredefined set of clinically meaningful and\nstatistically robust metrics to confirm that the\nperformance is improved without introducing\nany regression across the six existing condition\ncategories."],["Update Procedures/Implementation","Before deployment, each update is reviewed to\nensure it stays within the scope of the PCCP\nwith no new outputs, indications, or workflow\nchanges and is released only after all\nverification and validation confirm it meets\npredefined success criteria. If these criteria are"]],"caption_candidate":"Table 6 Details of Modification M1 and M2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p12-t0","doc_id":"K251934","page_num":12,"bbox":[72.48,72.48,522.48,763.02],"n_rows":7,"n_cols":2,"columns":["","met, the update is implemented through a\ncontrolled, manual deployment process and\nmade globally available to all end users.\nUsers will be notified of updates implemented\nunder the PCCP through formal communication\nchannels, including revised labelling, updated\nuser manuals, and detailed release notes.\nThese materials will clearly outline any changes\nto the device’s performance, functionality, or\nindications for use, and will be disseminated in\naccordance with established quality system\nprocedures to ensure timely, accurate, and\ncomprehensive stakeholder awareness."],"rows":[["","met, the update is implemented through a\ncontrolled, manual deployment process and\nmade globally available to all end users.\nUsers will be notified of updates implemented\nunder the PCCP through formal communication\nchannels, including revised labelling, updated\nuser manuals, and detailed release notes.\nThese materials will clearly outline any changes\nto the device’s performance, functionality, or\nindications for use, and will be disseminated in\naccordance with established quality system\nprocedures to ensure timely, accurate, and\ncomprehensive stakeholder awareness."],["Impact Assessment","Benefits: Improved detection and localization\nperformance across six clinically relevant\ncategories;\nRisks: Potential overfitting and unintended bias\nif new data are imbalanced; risk of minor\nperformance variability.\nRisk Mitigation: The modified model will be\ntested for non-inferiority on the performance\nstudy test dataset which will contain new\nunseen data."],["M2 – Architectural modification",""],["Description","Modification 2 (M2) will involve a controlled\narchitectural change through modular\nreplacement of the existing Convolutional\nNeural Network (CNN) encoder with a Vision\nTransformer (ViT)-based encoder, while\nmaintaining the remaining components and the\nworkflow of the model pipeline."],["Rationale","Enhance feature extraction and global context\nunderstanding to further improve diagnostic\nperformance"],["Retraining Triggers","Given the established potential of ViT models,\nModification 2 will be explored if a superior\nVision encoder becomes available. If the\nupdated architecture demonstrates\nimprovement as described in the Acceptance\nCriteria, the modification will be accepted."],["Testing Methods","For testing the M2 modification, candidate\nmodels (trained on ViT architecture) will\nundergo rigorous evaluation against the\nbaseline CNN model. The updated model will\nbe evaluated using a predefined set of clinically\nmeaningful and statistically robust metrics to\nconfirm that the performance is improved\nwithout introducing any regression across the\nsix existing condition categories. Testing"]],"caption_candidate":"Qure.ai 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251934-p13-t0","doc_id":"K251934","page_num":13,"bbox":[72.48,72.48,522.48,589.44],"n_rows":3,"n_cols":2,"columns":["","includes assessment of performance metrics-\n(AUC, Box level sensitivity, specificity, subgroup\nanalysis). This ensures that candidate model\ncontinues to operate safely, effectively, and\nwithin the boundaries of the device’s cleared\nindications for use."],"rows":[["","includes assessment of performance metrics-\n(AUC, Box level sensitivity, specificity, subgroup\nanalysis). This ensures that candidate model\ncontinues to operate safely, effectively, and\nwithin the boundaries of the device’s cleared\nindications for use."],["Update Procedures/Implementation","Before deployment, each update is reviewed to\nensure it stays within the scope of the PCCP\nwith no new outputs, indications, or workflow\nchanges and is released only after all\npredefined verification and validation confirm it\nmeets predefined success criteria. If these\ncriteria are met, the update is implemented\nthrough a controlled, manual deployment\nprocess and made globally available to all end\nusers.\nUsers will be notified of updates implemented\nunder the PCCP through formal communication\nchannels, including revised labelling, updated\nuser manuals, and detailed release notes.\nThese materials will clearly outline any changes\nto the device’s performance, functionality, or\nindications for use, and will be disseminated in\naccordance with established quality system\nprocedures to ensure timely, accurate, and\ncomprehensive stakeholder awareness."],["Impact Assessment","Benefits: Improved ROI classification accuracy\nand localization precision\nRisks: Possibility of new failure modes due to\narchitectural change and model instability; risk\nof decoder-compatibility errors.\nRisk Mitigation: Full integration verification;\nperformance comparison to baseline using\nidentical metrics and datasets"]],"caption_candidate":"Qure.ai 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251963-p5-t0","doc_id":"K251963","page_num":5,"bbox":[70.56,187.32,577.32,701.76],"n_rows":11,"n_cols":2,"columns":["Date:","October 27, 2025"],"rows":[["Date:","October 27, 2025"],["Submitter:","GE Medical Systems Ultrasound and Primary care Diagnostics, LLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Manufacturer:","GE Ultrasound Korea, Ltd.\n9, Sunhwan-ro 214 beon-gil, Jungwon-gu,\nSeongnam-si, Gyeonggi-do, 13204 Republic of Korea"],["Primary Contact Person:","Bryan Behn\nSr. Regulatory Affairs Director\nGE HealthCare\nT:(262)247-5502"],["Alternate Contact Person:","Qingmeng Chen\nRegulatory Affairs Leader\nGE HealthCare\nT: +86-18180590723"],["Device Trade Name:","LOGIQ E10s"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX, QIH (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550, 90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-IYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX\nautomated radiological image processing software, 21 CFR 892.2050,\n90-QIH"],["Primary Predicate Device:","K231989 LOGIQ E10s, LOGIQ Fortis Diagnostic Ultrasound System"],["Reference Device(s):","K232381 LOGIQ Totus Diagnostic Ultrasound System\nK231301 Vscan Air\nK201768 Voluson E10"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251963-p9-t0","doc_id":"K251963","page_num":9,"bbox":[72.48,351.84,539.33,696.24],"n_rows":3,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],["Information about clinical subgroups\nand confounders present in the\ndataset","• Gender: Male 24.2% (8), Female 75.8% (25)\n• Age: 60 ±15.7 (average and standard deviation) (24 Min, 83\nMax)\n• BMI: 27±5.6 (average and standard deviation) (16 Min, 38\nMax)\n• Ethnicity: not hispanic 96.4%(27), hispanic 3.6% (1)\n• Race : Asian 12.9% (4), White 77.4% (24), Black 9.7% (3)\n• Country: USA (100%)"],["Information about equipment and\nprotocols used to collect images","Mix of data from across three different probe models and three\ndifferent Console variants. The data collection protocol was\nstandardized."]],"caption_candidate":"Auto Abdominal Color Assistant 2.0:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251963-p11-t0","doc_id":"K251963","page_num":11,"bbox":[72.48,120.12,539.37,650.52],"n_rows":4,"n_cols":2,"columns":["Information about clinical subgroups\nand confounders present in the\ndataset","Long View Aorta:\n• Gender: 11 Male, 25 Female\n• Country: 16 Japan, 20 USA\n• Age: 60.50 ±14.24 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],"rows":[["Information about clinical subgroups\nand confounders present in the\ndataset","Long View Aorta:\n• Gender: 11 Male, 25 Female\n• Country: 16 Japan, 20 USA\n• Age: 60.50 ±14.24 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],["Information about equipment and\nprotocols used to collect images","Validation images were collected on LOGIQ Fortis with the C1-6\nprobe with a standardized protocol. Images acquired on LOGIQ\nFortis are acceptable for validation of LOGIQ E10 because the\ntransmit, receive, and back-end processing hardware are the\nsame. The acquisition software architecture is also the same.\nTherefore, the image quality of the two systems is comparable."],["Information about how the reference\nstandard was derived from the testing\ndataset (i.e. the “truthing” process)","• Before the process of data annotation, all information\ndisplayed on the device is removed and performed on\ninformation extracted purely from Ultrasound B-mode\nimages.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view – Number of keystrokes measured.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view using AI - Number of keystrokes\nmeasured.\n• Number of Keystrokes with and without AI is compared\nfor each reader.\n• Arbitrator to select most accurate measurement among\nall readers.\n• Arbitrator selected measurement is compared to AI\nbaseline measurement with and without on\nsegmentation editing for accuracy."],["Description of how independence of\ntest data from training data was\nensured","The exams used for regulatory validation purpose are separated\nfrom the ones used during model development process by exam\nsite origin ensuring there is no overlap between the two."]],"caption_candidate":"510(k) Summary- K251963","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251963-p12-t0","doc_id":"K251963","page_num":12,"bbox":[72.68,120.12,539.08,699.14],"n_rows":27,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","• The average reduction between keystrokes for\nmeasurements (diameter) made manually and with AI is\n1.62±0.375 (mean and standard deviation)\nPorta Hepatis measurement accuracy without segmentation scroll\nedit:\n• Average accuracy is 59.85% with 95% CI of +/- 17.86% and\naverage absolute error of 1.66 mm and 95% CI of 1.02 mm.\n• Limits of Agreement in millimeters are (-4.75,4.37) with\n95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","• The average reduction between keystrokes for\nmeasurements (diameter) made manually and with AI is\n1.62±0.375 (mean and standard deviation)\nPorta Hepatis measurement accuracy without segmentation scroll\nedit:\n• Average accuracy is 59.85% with 95% CI of +/- 17.86% and\naverage absolute error of 1.66 mm and 95% CI of 1.02 mm.\n• Limits of Agreement in millimeters are (-4.75,4.37) with\n95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],["","• Gender: Male 44% (11), Female 56% (14)"],["","• Age: 62 ±16.03 (average and standard deviation) (23 Min –"],["","83 Max)"],["Information about clinical subgroups and",""],["","• BMI: 23.48 ± 4.94 (average and standard deviation) (16.65"],["confounders present in the dataset",""],["","min – 36.73 max)"],["",""],["","• Race: Asian 64% (16), White 36% (9)"],["","• Country: USA (40%), Japan (60%)"],["Information about equipment and\nprotocols used to collect images","Validation images were collected on LOGIQ Fortis with the C1-6\nprobe with a standardized protocol. Images acquired on LOGIQ\nFortis are acceptable for validation of LOGIQ E10 because the\ntransmit, receive, and back-end processing hardware are the same.\nThe acquisition software architecture is also the same. Therefore,\nthe image quality of the two systems is comparable."],["","• Before the process of data annotation, all information"],["","displayed on the device is removed and performed on"],["","information extracted purely from Ultrasound B-mode"],["","images."],["","• Readers to ground truth the diameter of the CBD in the"],["","Porta Hepatis – Number of keystrokes measured."],["Information about how the reference","• Readers to ground truth the diameter of the CBD in the"],["standard was derived from the testing","Porta Hepatis using AI - Number of keystrokes measured."],["dataset (i.e. the “truthing” process)","• Number of Keystrokes with and without AI is compared for"],["","each reader."],["","• Arbitrator to select most accurate measurement among all"],["","readers."],["","• Arbitrator selected measurement is compared to AI"],["","baseline measurement with and without on segmentation"],["","editing for accuracy."]],"caption_candidate":"510(k) Summary- K251963","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p8-t0","doc_id":"K251983","page_num":8,"bbox":[42.6,422.21,553.06,508.27],"n_rows":6,"n_cols":2,"columns":["","study triage within existing patient pathways. It"],"rows":[["","study triage within existing patient pathways. It"],["does not replace any part of the current standard of care. It is designed to assist in prioritization of studies for",""],["reading within a worklist, in addition to any other pre-existing formal or informal methods of study prioritization in",""],["place. Specifically, it does not remove cases from a reading queue and operates in parallel to the standard of care.",""],["This device is not intended to replace the usual methods of communication and transfer of information in the",""],["current standard of care.",""]],"caption_candidate":"beyond notification.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p10-t0","doc_id":"K251983","page_num":10,"bbox":[42.5,706.78,503.37,761.98],"n_rows":4,"n_cols":12,"columns":["","Metrics","","","21 < Age < 50","","","50 ≤ Age < 70","","","Age ≥ 70",""],"rows":[["","Metrics","","","21 < Age < 50","","","50 ≤ Age < 70","","","Age ≥ 70",""],["","Total Positives","","","36","","","69","","","62",""],["","Sensitivity","","","94.44% (82.88-99.20)","","","98.55% (93.01-99.91)","","","95.16% (87.37-98.97)",""],["","Specificity","","","95.77% (88.90-99.10)","","","96.25% (90.10-99.21)","","","100% (88.74-100.00)",""]],"caption_candidate":"thickness and scanner manufacturer subgroups. Additional subgroup analysis is reported in the labelling.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p11-t0","doc_id":"K251983","page_num":11,"bbox":[42.55,100.46,500.02,140.66],"n_rows":3,"n_cols":8,"columns":["","Total Positives","","","79","","","88"],"rows":[["","Total Positives","","","79","","","88"],["","Sensitivity","","","96.20% (89.98-99.20)","","","96.59% (90.97-99-28)"],["","Specificity","","","98.78% (94.08-99.92)","","","94.57% (88.34-98.18)"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p11-t1","doc_id":"K251983","page_num":11,"bbox":[42.55,163.22,500.02,231.86],"n_rows":5,"n_cols":9,"columns":["Metrics","","","","Slice Thickness\n< 1.5 mm","1.5mm ≤ Slice Thickness\n< 3 mm","","","Slice Thickness"],"rows":[["Metrics","","","","Slice Thickness\n< 1.5 mm","1.5mm ≤ Slice Thickness\n< 3 mm","","","Slice Thickness"],["","","","","","","","","≥ 3 mm"],["","Total Positives","","","112","23","","","32"],["","Sensitivity","","","97.32% (92.84-99.44)","95.65% (80.63-99.73)","","","93.75% (80.94-99.09)"],["","Specificity","","","99.17% (95.94-99.95)","100.00% (86.70-100.00%)","","","85.29% (70.47-94.80)"]],"caption_candidate":"Specificity 98.78% (94.08-99.92) 94.57% (88.34-98.18)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p11-t2","doc_id":"K251983","page_num":11,"bbox":[42.55,254.31,500.02,326.93],"n_rows":4,"n_cols":9,"columns":["Metrics","","","GE MEDICAL SYSTEM","","Philips","","SIEMENS",""],"rows":[["Metrics","","","GE MEDICAL SYSTEM","","Philips","","SIEMENS",""],["","Total Positives","","","87","72","","","7"],["","Sensitivity","","","98.85% (94.41-99.92)","94.44% (87.12-98.47)","","","85.71% (49.44-98.90)"],["","Specificity","","","95.70% (89.92-98.83)","96.88% (90.02-99.58)","","","100.00% (84.61-100.00)"]],"caption_candidate":"Specificity 99.17% (95.94-99.95) 100.00% (86.70-100.00%) 85.29% (70.47-94.80)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p12-t0","doc_id":"K251983","page_num":12,"bbox":[42.6,100.64,503.74,145.38],"n_rows":3,"n_cols":9,"columns":["","Total Positives","","","13","39","","60",""],"rows":[["","Total Positives","","","13","39","","60",""],["","Sensitivity","","","84.62% (58.59-97.46)","74.36% (59.09-86.41)","","63.33% (50.62-74.88)",""],["","Specificity","","","94.74% (77.09-99.67)","89.09% (78.7-95.74)","","87.80% (75.07-95.75)",""]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p12-t1","doc_id":"K251983","page_num":12,"bbox":[42.6,167.9,503.74,229.26],"n_rows":4,"n_cols":8,"columns":["","Metrics","","Female","","","Male",""],"rows":[["","Metrics","","Female","","","Male",""],["","Total Positives","","48","","","64",""],["","Sensitivity","","75.0% (61.4-85.89)","","","65.62% (53.39-76.57)",""],["","Specificity","","88.14% (77.94-94.92)","","","91.07% (81.32-96.95)",""]],"caption_candidate":"Specificity 94.74% (77.09-99.67) 89.09% (78.7-95.74) 87.80% (75.07-95.75)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p12-t2","doc_id":"K251983","page_num":12,"bbox":[42.6,251.91,503.74,327.35],"n_rows":4,"n_cols":8,"columns":["Metrics","","","Slice Thickness\n< 1 mm","1 mm ≤ Slice Thickness\n< 3 mm","","Slice Thickness\n≥ 3 mm",""],"rows":[["Metrics","","","Slice Thickness\n< 1 mm","1 mm ≤ Slice Thickness\n< 3 mm","","Slice Thickness\n≥ 3 mm",""],["","Total Positives","","44","25","","42",""],["","Sensitivity","","61.36% (46.46-74.93)","80.00% (61.30-92.70)","","71.43% (56.52-83.7)",""],["","Specificity","","87.76% (76.29-95.19)","96.67% (84.74-99.79)","","86.11% (71.95-95.11)",""]],"caption_candidate":"Specificity 88.14% (77.94-94.92) 91.07% (81.32-96.95)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p12-t3","doc_id":"K251983","page_num":12,"bbox":[42.6,349.85,503.74,428.69],"n_rows":4,"n_cols":8,"columns":["Metrics","","","SIEMENS","GE MEDICAL SYSTEMS","Philips","",""],"rows":[["Metrics","","","SIEMENS","GE MEDICAL SYSTEMS","Philips","",""],["","Total Positives","","48","33","","27",""],["","Sensitivity","","62.5% (48.25-75.4)","72.73% (55.90-86.04)","","77.78% (59.56-90.82)",""],["","Specificity","","88.24% (77.15-95.39)","83.87% (67.93-94.24)","","96.97% (86.02-99.81)",""]],"caption_candidate":"Specificity 87.76% (76.29-95.19) 96.67% (84.74-99.79) 86.11% (71.95-95.11)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p13-t0","doc_id":"K251983","page_num":13,"bbox":[42.27,531.55,524.59,798.84],"n_rows":5,"n_cols":9,"columns":["","Characteristic/","","","Brainomix 360 Triage Stroke","","","Brainomix 360 Triage Stroke",""],"rows":[["","Characteristic/","","","Brainomix 360 Triage Stroke","","","Brainomix 360 Triage Stroke",""],["","Parameter","","","Predicate Device (K232496)","","","Subject Device",""],["Product Code","","","QAS","","","QAS","",""],["Regulation","","","21 CFR. §892.2080","","","21 CFR. §892.2080","",""],["Indications for Use","","","Brainomix 360 Triage Stroke is a\nradiological computer aided triage and\nnotification software indicated for use in\nthe analysis of non-contrast head CT\n(NCCT) images to assist hospital networks\nand trained clinicians in workflow triage by\nflagging and communicating suspected\npositive findings of head NCCT images for\nlarge vessel occlusion (LVO) of the\nintracranial ICA and M1 and intracranial\nhemorrhage (ICH). Specifically, the device\nis intended to be used for the triage of\nimages acquired from adult patients in the\nacute setting, within 24 hours of the onset\nof the acute symptoms, or where this is\nunclear, since last known well (LKW) time.\nIt is not intended to detect isolated","","","Brainomix 360 Triage Stroke is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the analysis of\nnon-contrast head CT (NCCT) images to\nassist hospital networks and trained\nclinicians in workflow triage by flagging and\ncommunicating suspected positive findings\nof head NCCT images for large vessel\nocclusion (LVO) of the intracranial ICA and\nM1 or intracranial hemorrhage (ICH).\nSpecifically, the device is intended to be\nused for the triage of images acquired from\nadult patients in the acute setting, within 24\nhours of the onset of the acute symptoms,\nor where this is unclear, since last known\nwell (LKW) time. It is not intended to detect","",""]],"caption_candidate":"A table comparing the key features of the subject and predicate devices is provided below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p15-t0","doc_id":"K251983","page_num":15,"bbox":[42.24,100.7,524.62,792.7],"n_rows":14,"n_cols":3,"columns":["","• Brainomix 360 Triage Stroke has been\nvalidated and is intended to be used on\nSiemens, GE and Philips scanners.\n• Brainomix 360 Triage Stroke is not\nintended to be used on patients with\nrecent (within 6 weeks) neurosurgery or\nendovascular neurointervention or\nrecent (within 4 weeks) previous\ndiagnosis of stroke.\n• Brainomix 360 Triage Stroke is not\nintended to detect isolated\nsubarachnoid hemorrhage and\nsymmetrical bilateral MCA occlusions.\nContraindications:\nBrainomix 360 Triage Stroke is not suitable\nfor use with scan data containing image\nfeatures associated with:\n• tumors or abscesses\n• coils, shunts, embolization or\nmovement artifacts\n• Brainomix 360 Triage Stroke is not\nintended to be used for analyzing CT\nimages in intracranial vascular\npathologies such as arterial aneurysms,\narteriovenous malformations or venous\nthrombosis.","workup - it provides workflow\nprioritization and notification only.\n3. Brainomix 360 Triage Stroke has\nbeen validated and is intended to\nbe used on Siemens, GE and Philips\nscanners.\n4. Brainomix 360 Triage Stroke is not\nintended to be used on patients\nwith recent (within 6 weeks)\nneurosurgery or endovascular\nneurointervention or recent (within\n4 weeks) previous diagnosis of\nstroke.\n5. Brainomix 360 Triage Stroke is not\nintended to detect symmetrical\nbilateral MCA occlusions.\nContraindications:\nBrainomix 360 Triage Stroke is not suitable\nfor use with scan data containing image\nfeatures associated with:\n• tumours or abscesses\n• coils, shunts, embolization or\nmovement artifacts\n• intracranial vascular pathologies\nsuch as arterial aneurysms,\narteriovenous malformations or\nvenous thrombosis."],"rows":[["","• Brainomix 360 Triage Stroke has been\nvalidated and is intended to be used on\nSiemens, GE and Philips scanners.\n• Brainomix 360 Triage Stroke is not\nintended to be used on patients with\nrecent (within 6 weeks) neurosurgery or\nendovascular neurointervention or\nrecent (within 4 weeks) previous\ndiagnosis of stroke.\n• Brainomix 360 Triage Stroke is not\nintended to detect isolated\nsubarachnoid hemorrhage and\nsymmetrical bilateral MCA occlusions.\nContraindications:\nBrainomix 360 Triage Stroke is not suitable\nfor use with scan data containing image\nfeatures associated with:\n• tumors or abscesses\n• coils, shunts, embolization or\nmovement artifacts\n• Brainomix 360 Triage Stroke is not\nintended to be used for analyzing CT\nimages in intracranial vascular\npathologies such as arterial aneurysms,\narteriovenous malformations or venous\nthrombosis.","workup - it provides workflow\nprioritization and notification only.\n3. Brainomix 360 Triage Stroke has\nbeen validated and is intended to\nbe used on Siemens, GE and Philips\nscanners.\n4. Brainomix 360 Triage Stroke is not\nintended to be used on patients\nwith recent (within 6 weeks)\nneurosurgery or endovascular\nneurointervention or recent (within\n4 weeks) previous diagnosis of\nstroke.\n5. Brainomix 360 Triage Stroke is not\nintended to detect symmetrical\nbilateral MCA occlusions.\nContraindications:\nBrainomix 360 Triage Stroke is not suitable\nfor use with scan data containing image\nfeatures associated with:\n• tumours or abscesses\n• coils, shunts, embolization or\nmovement artifacts\n• intracranial vascular pathologies\nsuch as arterial aneurysms,\narteriovenous malformations or\nvenous thrombosis."],["Environment of Use","Clinical/Hospital environment","Clinical/Hospital environment"],["User","Clinician","Clinician"],["Anatomical Region","Head","Head"],["Input Data","NCCT (ICH and LVO)","NCCT (ICH and LVO)"],["Technical\nImplementation","AI/ML/Neural Network","AI/ML/Neural Network"],["Diagnostic\napplication","Notification-only","Notification-only"],["Results of image\nanalysis","Internal no image marking","Internal no image marking"],["Segmentation of ROI","The device does not highlight or direct\nuser’s attention to a specific location in the\nimage file","The device does not highlight or direct user’s\nattention to a specific location in the image\nfile"],["Notification Display","Web user interface and mobile device","Web user interface and mobile device"],["Preview Images","Presentation of a preview of the study for\ninitial assessment not meant for diagnostic\npurposes.\nThe device operates in parallel with the\nstandard of care.","Presentation of a preview of the study for\ninitial assessment not meant for diagnostic\npurposes.\nThe device operates in parallel with the\nstandard of care."],["Annotation /\nLocalization","Device does not mark, highlight, or direct\nusers’ attention to a specific location in the\noriginal image","Device does not mark, highlight, or direct\nusers’ attention to a specific location in the\noriginal image"],["Prioritization\nNotification","Yes","Yes"],["Clinical SoC\nWorkflow","In parallel to","In parallel to"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251983-p16-t0","doc_id":"K251983","page_num":16,"bbox":[42.24,100.7,524.62,223.58],"n_rows":2,"n_cols":3,"columns":["Technical Pipeline","Two cascaded functions (ICH then LVO)\nusing three integrated algorithms","Triage Stroke Configuration: two cascaded\nfunctions (ICH then LVO) using three\nintegrated algorithms\nTriage ICH Configuration: ICH analysis\nfunction using one algorithm\nNCCT LVO Configuration: LVO analysis\nfunction using three integrated algorithms"],"rows":[["Technical Pipeline","Two cascaded functions (ICH then LVO)\nusing three integrated algorithms","Triage Stroke Configuration: two cascaded\nfunctions (ICH then LVO) using three\nintegrated algorithms\nTriage ICH Configuration: ICH analysis\nfunction using one algorithm\nNCCT LVO Configuration: LVO analysis\nfunction using three integrated algorithms"],["Removal of Cases\nfrom SoC review","No","No"]],"caption_candidate":"Oxford OX2 0JJ, United Kingdom","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251985-p5-t0","doc_id":"K251985","page_num":5,"bbox":[70.56,199.56,577.32,700.2],"n_rows":11,"n_cols":2,"columns":["Date:","October 27, 2025"],"rows":[["Date:","October 27, 2025"],["Submitter:","GE Medical Systems Ultrasound and Primary Care Diagnostics, LLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Manufacturer:","GE Medical Systems Ultrasound and Primary Care Diagnostics, LLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Primary Contact Person:","Bryan Behn\nSr. Regulatory Affairs Director\nGE HealthCare\nT:(262)247-5502"],["Alternate Contact Person:","Beth Wentworth\nRegulatory Affairs Leader\nGE HealthCare\nT: 2627883816"],["Device Trade Name:","LOGIQ E10"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX, QIH (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550, 90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-IYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX\nautomated radiological image processing software, 21 CFR 892.2050,\n90-QIH"],["Primary Predicate Device:","K231966 LOGIQ E10"],["Reference Device(s):","K232381 LOGIQ Totus Diagnostic Ultrasound System\nK201768 Voluson E10"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251985-p9-t0","doc_id":"K251985","page_num":9,"bbox":[72.48,297.6,539.37,694.8],"n_rows":4,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],["Information about clinical subgroups\nand confounders present in the\ndataset","• Gender: Male 24.2% (8), Female 75.8% (25)\n• Age: 60 ±15.7 (average and standard deviation) (24 Min, 83\nMax)\n• BMI: 27±5.6 (average and standard deviation) (16 Min, 38\nMax)\n• Ethnicity: not hispanic 96.4%(27), hispanic 3.6% (1)\n• Race : Asian 12.9% (4), White 77.4% (24), Black 9.7% (3)\n• Country: USA (100%)"],["Information about equipment and\nprotocols used to collect images","Mix of data from across three different probe models and three\ndifferent Console variants. The data collection protocol was\nstandardized."],["Information about how the reference\nstandard was derived from the testing\ndataset (i.e. the “truthing” process)","• Before the process of data annotation, all information\ndisplayed on the device is removed and performed on\ninformation extracted purely from Ultrasound B-mode\nimages."]],"caption_candidate":"Auto Abdominal Color Assistant 2.0:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251985-p10-t0","doc_id":"K251985","page_num":10,"bbox":[72.48,278.76,539.37,702.0],"n_rows":2,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","Long View Aorta:\n• The average keystrokes to obtain the Anteroposterior\n(AP) measurement (diameter) of the aorta in the long\nview is 4.132 +/- 0.291 without AI and 1.236 +/-0.340\nwith AI.\nShort View Aorta:\n• The average keystrokes to obtain the AP and Trans\nmeasurement (diameter) of the aorta in the short view is\n7.05 +/-0.158 without AI and 2.307 +/- 1.0678 with AI.\nLong View AP Measurement Accuracy:\n• Average accuracy is 87.2% with 95% CI of +/- 1.98% and\naverage absolute error of 0.253 cm and 95% CI of 0.049\ncm.\n• Limits of Agreement in centimeters are (-0.15, 0.60) with\n95% CI of (-0.26, 0.71).\nShort View AP Measurement Accuracy:\n• Average accuracy is 92.9% with a 95% CI of +/- 2.02%\nand an average absolute error of 0.128 cm and 95% CI of\n0.037 cm.\n• Limits of Agreement in centimeters are (-0.21, 0.36) with\n95% CI of (-0.29, 0.45).\nShort View Trans Measurement Accuracy:\n• Average accuracy is 86.9% with 95% CI of +/- 6.25% and\naverage absolute error of 0.235 cm and 95% CI of 0.110\ncm.\n• Limits of agreement in centimeters are (-0.86, 0.69) with\n95% CI (-1.06, 0.92)."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","Long View Aorta:\n• The average keystrokes to obtain the Anteroposterior\n(AP) measurement (diameter) of the aorta in the long\nview is 4.132 +/- 0.291 without AI and 1.236 +/-0.340\nwith AI.\nShort View Aorta:\n• The average keystrokes to obtain the AP and Trans\nmeasurement (diameter) of the aorta in the short view is\n7.05 +/-0.158 without AI and 2.307 +/- 1.0678 with AI.\nLong View AP Measurement Accuracy:\n• Average accuracy is 87.2% with 95% CI of +/- 1.98% and\naverage absolute error of 0.253 cm and 95% CI of 0.049\ncm.\n• Limits of Agreement in centimeters are (-0.15, 0.60) with\n95% CI of (-0.26, 0.71).\nShort View AP Measurement Accuracy:\n• Average accuracy is 92.9% with a 95% CI of +/- 2.02%\nand an average absolute error of 0.128 cm and 95% CI of\n0.037 cm.\n• Limits of Agreement in centimeters are (-0.21, 0.36) with\n95% CI of (-0.29, 0.45).\nShort View Trans Measurement Accuracy:\n• Average accuracy is 86.9% with 95% CI of +/- 6.25% and\naverage absolute error of 0.235 cm and 95% CI of 0.110\ncm.\n• Limits of agreement in centimeters are (-0.86, 0.69) with\n95% CI (-1.06, 0.92)."],["Information about clinical subgroups\nand confounders present in the\ndataset","Long View Aorta:\n• Gender: 11 Male, 25 Female\n• Country: 16 Japan, 20 USA\n• Age: 60.50 ±14.24 (average and standard deviation) (23\nMin – 81 Max)"]],"caption_candidate":"Auto Aorta Measure Assistant:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251985-p11-t0","doc_id":"K251985","page_num":11,"bbox":[72.48,120.12,539.42,599.04],"n_rows":4,"n_cols":2,"columns":["","• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],"rows":[["","• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],["Information about equipment and\nprotocols used to collect images","• Validation images were collected on LOGIQ Fortis with\nthe C1-6 probe with a standardized protocol. Images\nacquired on LOGIQ Fortis are acceptable for validation of\nLOGIQ E10 because the transmit, receive, and back-end\nprocessing hardware are the same. The acquisition\nsoftware architecture is also the same. Therefore, the\nimage quality of the two systems is comparable."],["Information about how the reference\nstandard was derived from the testing\ndataset (i.e. the “truthing” process)","• Before the process of data annotation, all information\ndisplayed on the device is removed and performed on\ninformation extracted purely from Ultrasound B-mode\nimages.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view – Number of keystrokes measured.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view using AI - Number of keystrokes\nmeasured.\n• Number of Keystrokes with and without AI is compared\nfor each reader.\n• Arbitrator to select most accurate measurement among\nall readers.\n• Arbitrator selected measurement is compared to AI\nbaseline measurement with and without on\nsegmentation editing for accuracy."],["Description of how independence of\ntest data from training data was\nensured","The exams used for regulatory validation purpose are separated\nfrom the ones used during model development process by exam\nsite origin ensuring there is no overlap between the two."]],"caption_candidate":"510(k) Summary- K251985","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251985-p12-t0","doc_id":"K251985","page_num":12,"bbox":[72.65,120.12,539.12,702.12],"n_rows":28,"n_cols":2,"columns":["performance","Porta Hepatis measurement accuracy without segmentation scroll\nedit:\n• Average accuracy is 59.85% with 95% CI of +/- 17.86% and\naverage absolute error of 1.66 mm and 95% CI of 1.02 mm.\n• Limits of Agreement in millimeters are (-4.75,4.37) with\n95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],"rows":[["performance","Porta Hepatis measurement accuracy without segmentation scroll\nedit:\n• Average accuracy is 59.85% with 95% CI of +/- 17.86% and\naverage absolute error of 1.66 mm and 95% CI of 1.02 mm.\n• Limits of Agreement in millimeters are (-4.75,4.37) with\n95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],["","• Gender: Male 44% (11), Female 56% (14)"],["","• Age: 62 ±16.03 (average and standard deviation) (23 Min –"],["","83 Max)"],["Information about clinical subgroups and",""],["","• BMI: 23.48 ± 4.94 (average and standard deviation) (16.65"],["confounders present in the dataset",""],["","min – 36.73 max)"],["",""],["","• Race: Asian 64% (16), White 36% (9)"],["","• Country: USA (40%), Japan (60%)"],["Information about equipment and\nprotocols used to collect images","Validation images were collected on LOGIQ Fortis with the C1-6\nprobe with a standardized protocol. Images acquired on LOGIQ\nFortis are acceptable for validation of LOGIQ E10 because the\ntransmit, receive, and back-end processing hardware are the same.\nThe acquisition software architecture is also the same. Therefore,\nthe image quality of the two systems is comparable."],["","• Before the process of data annotation, all information"],["","displayed on the device is removed and performed on"],["","information extracted purely from Ultrasound B-mode"],["","images."],["","• Readers to ground truth the diameter of the CBD in the"],["","Porta Hepatis – Number of keystrokes measured."],["Information about how the reference","• Readers to ground truth the diameter of the CBD in the"],["standard was derived from the testing","Porta Hepatis using AI - Number of keystrokes measured."],["dataset (i.e. the “truthing” process)","• Number of Keystrokes with and without AI is compared for"],["","each reader."],["","• Arbitrator to select most accurate measurement among all"],["","readers."],["","• Arbitrator selected measurement is compared to AI"],["","baseline measurement with and without on segmentation"],["","editing for accuracy."],["Description of how independence of test\ndata from training data was ensured","The exams used for regulatory validation purpose are separated\nfrom the ones used during model development process by exam\nsite origin ensuring there is no overlap between the two."]],"caption_candidate":"510(k) Summary- K251985","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251987-p3-t0","doc_id":"K251987","page_num":3,"bbox":[257.72,207.83,570.36,306.62],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"for","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251987-p7-t0","doc_id":"K251987","page_num":7,"bbox":[72.0,326.66,558.06,719.52],"n_rows":4,"n_cols":3,"columns":["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],"rows":[["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],["Regulation","21 CFR 892.2050; Medical image management\nand processing system","21 CFR 892.2050; Medical image management\nand processing system"],["Product Code","QIH","QIH"],["Intended\nUse/\nIndications for\nUse\nStatement","Rapid Aortic Measurements (AM) is an image\nanalysis and measurement device to evaluate\naortic and iliac arteries in contrast enhanced and\nnon-contrast CT imaging datasets acquired of\nthe chest, abdomen, and/or pelvis. The module\nsegments the aorta, iliacs, and major branching\nvessels and provides 2D and 3D visualizations\nof the segmented vessels.\nOutputs of the device include: Centerline\nmeasurements of the aorta and iliacs, Aortic\nZone Measurements (Maximum Oblique\nDiameter), Fixed Measurements of the aorta\nand left and right iliacs, 3D Volume\nRenderings, Rotations, Curved Planar\nReformations (CPRs) of the isolated left and\nright iliacs, aortic oblique Multiplanar\nReconstructions (MPRs), and Longitudinal\nTracking visualizations.\nRapid Aortic Measurements is an aid to\nphysician decision making. Its results are not\nintended to be used on a stand-alone basis for\nclinical decision-making or otherwise preclude\nclinical assessment.\nRapid Aortic Measurements is indicated for\nadults.","Rapid Neuro3D (RN3D) is an image analysis\nsoftware for imaging datasets acquired with\nconventional CT Angiography (CTA) from the\naortic arch to the vertex of the head). The module\nremoves bone, tissue, and venous vessels,\nproviding a 3D and 2D visualization of the\nneurovasculature supplying arterial blood to the\nbrain.\nOutputs of the device include 3D rotational\nmaximum intensity projections (MIPS), volume\nrenders (VR), along with the curved planar\nreformation (CPR) of the isolated left and right\ninternal carotid and vertebral arteries.\nRapid Neuro3D is designed to support the\nphysician in confirming the presence or absence\nof physician-identified lesions and evaluation,\ndocumentation, and follow-up of any such lesion\nand treatment planning.\nIts results are not intended to be used on a stand-\nalone basis for clinical decision-making or\notherwise preclude clinical assessment.\nRN3D is indicated for adults.\nPrecautions/Exclusions:"]],"caption_candidate":"Aortic Measurements software is substantially equivalent.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251987-p8-t0","doc_id":"K251987","page_num":8,"bbox":[72.0,75.84,558.06,677.68],"n_rows":8,"n_cols":3,"columns":["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],"rows":[["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],["","Precautions/Exclusions:\no Series containing excessive patient motion or\nmetal implants may impact module output\nquality.\no The AM module will not process series that\nmeet the following module exclusion criteria:\n• Series acquired w/cone-beam CT scanners (c-\narm CT)\n• Series that are non-axial or axial oblique\ngreater than 5 degrees\n• Series containing improperly ordered or\nmissing slices where the gap is larger than 3\ntimes the median inter-slice distance (e.g., as a\nresult of manual correction by an imaging\ntechnician)\n• Series with less than 3cm of target anatomical\nzones (e.g. aorta or right/left iliac artery)\n• NCCT, CECT, CTA, or CTPA datasets with:\n1) in-plane X and Y FOV < 160mm\n2) Z FOV (cranio-caudal transverse\nanatomical coverage) < 144 mm.\n3) in-plane pixel spacing (X & Y resolution)\n< 0.3 mm or > 1.0 mm.\n4) inter-slice distance of < 0.3 mm or > 3 mm.\n5) slice thickness > 3 mm.\n6) data acquired at x-ray tube voltage <\n70kVp or > 150kVp, including single energy,\ndual energy, or virtual monochromatic datasets","o Series containing excessive patient motion\nor metal implants may impact module output\nquality.\no The RN3D module will not process series\nthat meet the following module exclusion\ncriteria:\n• Series containing inadequate\ncontrast agent (<0.3 mL of right-\nhemisphere intracranial arterial\ncontrast media or <0.3 mL of left-\nhemisphere intracranial arterial\ncontrast media, above 120 HU)\n• Series acquired w/cone-beam CT\nscanners (c-arm CT)\n• Series that are non-axial\n• Series with a non-supine patient\nposition\n• Series containing missing or\nimproperly ordered slices (e.g., as a\nresult of manual correction by an\nimaging technician)\n• CTA datasets with:\n1) in-plane X and Y FOV < 160mm or > 400mm.\n2) Z FOV (cranio-caudal transverse anatomical\ncoverage) < 90 mm.\n3) in-plane pixel spacing (X & Y resolution) < 0.2\nmm or > 1.0 mm.\n4) Z slice spacing of < 0.2 mm or > 1.25 mm.\n5) slice thickness > 1.5mm.\n6) data acquired at x-ray tube voltage < 70 kVp\nor >150 kVp."],["Intended Users","Radiologists, cardiothoracic surgeons, vascular\nsurgeons, endovascular specialists, ED\nphysicians, or users with similar training.","Radiologists, neurovascular and neurosurgical\nspecialists, such as vascular neurosurgeons,\nneuro-interventional specialists, ED physicians,\nor users with similar training."],["Functionality","Software package (SaMD) which interfaces to a\nPACS/Viewer or allows viewing within the\napplication.","Software package (SaMD) which interfaces to a\nPACS/Viewer or allows viewing within the\napplication."],["Computer\nPlatform","Standard off-the-shelf Hardware: Cloud Hybrid","Standard off-the-shelf Hardware: On-Premises\nor Cloud Hybrid"],["Technical\nImplementation","AI/ML; traditional","AI/ML"],["Input DICOM\nImaging\nModality","CECT, CTA, CTPA, NCCT","CTA"],["Imaging Type","Chest, Abdomen, and/or Pelvis (aorta and iliacs)","Neurological (aortic arch to the vertex of the\nhead)"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K251987-p9-t0","doc_id":"K251987","page_num":9,"bbox":[72.0,75.84,558.06,186.38],"n_rows":2,"n_cols":3,"columns":["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],"rows":[["Product Name","Rapid Aortic Measurements (AM) (subject\ndevice)","Rapid Neuro3D (Marketed as Lumina3D)\n(K243350)"],["Software\nOutputs","• 2D/3D vessel visualization (VRs, CPRs,\nMPRs)\n• Automated segmentation and removal of\nobstructive bones and/or vessels\n• Automated vessel centerlines and\nmeasurements\n• Comparison/longitudinal tracking","• 2D/3D vessel visualization (Thins, MIPS, VR,\nCPR)\n• Automated segmentation and removal of\nobstructive bones and/or vessels"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252002-p6-t0","doc_id":"K252002","page_num":6,"bbox":[104.94,601.56,521.58,774.18],"n_rows":2,"n_cols":4,"columns":["Item","Predicate Device","Subject Device","Substantial\nEquivalence\nDiscussion"],"rows":[["Item","Predicate Device","Subject Device","Substantial\nEquivalence\nDiscussion"],["Indications","The Monaco system is used\nto make treatment plans for\npatients with prescriptions for\nexternal beam radiation\ntherapy. The system\ncalculates dose for photon,\nelectron and proton\ntreatment plans and\ndisplays, on screen and in\nhard-copy, two- or three-\ndimensional radiation dose\ndistributions inside the","The Monaco system is\nused to make treatment\nplans for patients with\nprescriptions for external\nbeam radiation therapy.\nThe system calculates\ndose for photon,\nelectron and proton\ntreatment plans and\ndisplays, on screen and\nin hard-copy, two- or\nthree-dimensional\nradiation dose","No change"]],"caption_candidate":".","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252002-p7-t0","doc_id":"K252002","page_num":7,"bbox":[104.94,81.6,521.58,778.45],"n_rows":8,"n_cols":4,"columns":["","patients for given treatment\nplan set-ups.\nThe Monaco product line is\nintended for use in radiation\ntreatment planning. It uses\ngenerally accepted methods\nfor:\n•Contouring\n•Image manipulation\n•Simulation\n•Image fusion\n•Plan optimization\n•QA and plan review","distributions inside the\npatients for given\ntreatment plan set-ups.\nThe Monaco product line\nis intended for use in\nradiation treatment\nplanning. It uses\ngenerally accepted\nmethods for:\n•Contouring\n•Image manipulation\n•Simulation\n•Image fusion\n•Plan optimization\n•QA and plan review",""],"rows":[["","patients for given treatment\nplan set-ups.\nThe Monaco product line is\nintended for use in radiation\ntreatment planning. It uses\ngenerally accepted methods\nfor:\n•Contouring\n•Image manipulation\n•Simulation\n•Image fusion\n•Plan optimization\n•QA and plan review","distributions inside the\npatients for given\ntreatment plan set-ups.\nThe Monaco product line\nis intended for use in\nradiation treatment\nplanning. It uses\ngenerally accepted\nmethods for:\n•Contouring\n•Image manipulation\n•Simulation\n•Image fusion\n•Plan optimization\n•QA and plan review",""],["Use\nEnvironment","Access-controlled\nHealthcare facilities","Access-controlled\nHealthcare facilities","No change"],["Dose\nCalculation\nAlgorithms","Monte Carlo - electron &\nphoton\nCollapsed Cone (photon)\nPencil Beam (only used\nwhen optimization)\nGPUMCD for photon (MR\nlinac)\nGPUMCD for proton\nProton Pencil Beam","Monte Carlo - electron &\nphoton\nCollapsed Cone\n(photon)\nPencil Beam (only used\nwhen optimization)\nGPUMCD for photon\n(both MR linac and\nconventional linac)\nGPUMCD for proton\nProton Pencil Beam","Substantially Equivalent\nGPUMCD extends from\nMR linac to\nconventional linac."],["Proton\nplanning","Yes","Yes","No change"],["Dose\ncalculation for\nMR-Linac\n(including\nmagnetic field,\ncoils &\ncryostat)","Yes","Yes","No change"],["Adaptive\nTherapy\nPlanning","Adaptive therapy planning\nfor MR linac","Adaptive therapy\nplanning for MR linac &\nconventional linac","Substantially Equivalent\nAdaptive Therapy\nPlanning functionalities\nare extended from MR\nlinac (UNITY) to\nconventional Linac\n(EMLA). Enables offline\nadaptive planning on\nEMLA."],["Auto Planning","No","Yes (for conventional\nlinac)","Substantially Equivalent\nAuto planning feature\nfor iterative modification\nof optimization cost\nfunction parameters\nintroduced in subject\ndevice."],["Contouring","Yes\n(with traditional algorithm)","Yes\n(with traditional and\nmachine learning\nalgorithm)","Substantially Equivalent\nThe Segmentation\nComponent utilizes\nmachine-learning based\nmodels to automatically\nsegment MR image\nsets introduced in\nsubject device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252002-p8-t0","doc_id":"K252002","page_num":8,"bbox":[104.94,81.6,521.58,607.92],"n_rows":11,"n_cols":4,"columns":["Distributed\nplanning\ndeployment","Yes (for conventional linac)","Yes (for conventional\nlinac)","No change"],"rows":[["Distributed\nplanning\ndeployment","Yes (for conventional linac)","Yes (for conventional\nlinac)","No change"],["Local\nBiological\nMeasure\nOptimization","Hypertion Optimizer\n(Constrained Optimization)","Next Generation\nOptimizer (GPU-\naccelerated Hypertion\nOptimizer)","Substantially Equivalent\nNext Generation\nOptimizer in the subject\ndevice is the GPU\nbased optimizer which\nuses Pseudo-Gradient\nDescent algorithm."],["Operating\nSystem","Windows 10","Windows 10","No change"],["DICOM RT\nSupport","Yes","Yes","No change"],["Programming\nLanguage","C, C++, C#","C, C++, C#","No change"],["Modalities\nSupported","Photon, Electron, Proton","Photon, Electron, Proton","No change"],["Beam\nmodelling","Beam modeling is performed\nby Elekta personnel.\nStandardized beam models\nare provided for some Elekta\nlinac energy options.","Beam modeling is\nperformed by Elekta\npersonnel. Standardized\nbeam models are\nprovided for some\nElekta linac energy\noptions.","No change"],["Scripting","UI based scripting","Both UI based and non-\nUI based scripting","Substantially Equivalent"],["Archive/\nRetrieve","Yes","Yes","No change"],["Standards\nCompliance","ISO 13485\nISO 14971\nIEC 62304\nIEC 62083\nIEC 82304-1\nIEC 61217\nIEC 62366-1\nISO 15223-1","ISO 13485\nISO 14971\nIEC 62304\nIEC 62083\nIEC 82304-1\nIEC 61217\nIEC 62366-1\nIEC 81001-5-1\nISO 15223-1\nISO 20417","Substantially Equivalent"],["Compatibility\nwith\nConnected\nSystems","• EMLA\n• MR-linac Unity\n• MOSAIQ\n• Smart flow","• EMLA\n• MR-linac Unity\n• MOSAIQ\n• Third party\ncontouring tools\n• Smart flow","Substantially Equivalent"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252002-p9-t0","doc_id":"K252002","page_num":9,"bbox":[104.97,294.42,515.84,774.48],"n_rows":3,"n_cols":6,"columns":["","Changes on scope of Monaco 6.3","","","Testing Performed to establish substantial equivalence",""],"rows":[["","Changes on scope of Monaco 6.3","","","Testing Performed to establish substantial equivalence",""],["Segmentation component for invoking\nMR auto-segmentation algorithms","","","For the AI-based segmentation component, performance\ntesting was conducted for the models – Female Pelvis\nIntact & Hysterectomy (trained on a joint image set of 529\nimages), Male Pelvis (trained on an image set of 250\nimages) and Head& Neck trained on an image set of 1862\nimages).\nThe primary metric for evaluating the model’s\nperformance is the Average Hausdorff Distance (AVD).\nThe acceptance threshold is set at 3 mm. A DICE or AUC\nvalue of 0.7 is also taken to represent a value of interest\nthat might indicate model performance with respect to a\nstructure or set of structures, however the DICE and AUC\nresults were not explicitly used as the pass/fail metric.\nQuantitative performance evaluation demonstrated that,\nfor all evaluated structures across all models, the mean\nAbsolute Volume Difference (AVD) was less than 3 mm.\nStructure specific statistical analyses supported this\nconclusion. In addition, for all structures and models, the\npatterns of failure for any structure that did not meet the\nDice Similarity Coefficient (DICE) confidence value of\ninterest of 0.7 were investigated and any findings were\nincluded as \"Limitations\".\nSub-group analysis is carried on the assessment of\nperformance in the patient size, pixel size, slice spacing\nand number of slices subgroups.\nAdditionally, qualitative analysis has also been executed\nbased on a 5-point Likert scale with a conclusion that the\nautomatically generated structures provided a valuable\nstarting point for clinical delineation.","",""],["Auto-planning","","","Verification testing was performed to evaluate the\nAutoPlanning functionality, including workflow\nperformance, protocol management, plan creation,\nintero‑perability, and error handling.\nValidation testing demonstrated that the Auto Planning\nfunctionality supports the creation of clinically acceptable\ntreatment plans for the intended use. Treatme‑nt plans\ngenerated using AutoPlanning were reviewed within the\nclinical workflow and determined to be suitable for\nclinical use, without in‑troducing new safety or","",""]],"caption_candidate":"510(k):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252002-p10-t0","doc_id":"K252002","page_num":10,"bbox":[104.94,81.6,515.88,644.46],"n_rows":3,"n_cols":2,"columns":["","effectiveness concerns. All testing met pre-defined\nacceptance criteria."],"rows":[["","effectiveness concerns. All testing met pre-defined\nacceptance criteria."],["Extending the adaptive planning\ncapabilities to EMLA for offline adaptive\nplanning","Verification testing was performed to evaluate the offline\nadaptive planning functionality using Monaco. Testing\nassessed correct system behavior during image\nregistration, structure propagation, dose recalculation/re-\noptimization, offline adaptive plan generation, and\nworkflow execution under representative clinical\nscenarios.\nThe purpose of testing was to confirm that offline\nadaptive planning functions operate as intended and\nsupport the creation of an updated treatment plan based\non CBCT imaging without compromising data integrity or\nworkflow performance. No defects, unexpected behavior,\nor data integrity issues were identified during testing.\nValidation testing demonstrated that offline adaptive\nplanning using CT toCBCT supports creation of\nclinically acceptable treatment plans for the intended\nuse. The offline ad‑ap‑tive plans generated using CBCT\nimaging were reviewed within the clinical workflow and\ndetermined to be suitable for use. Verification and\nvalidation testing met pre-defined acceptance criteria."],["Interoperability with 3rd party software\nfor image management and contouring","The device incorporates or interfaces with third party\ncontouring functionality intended to support radiotherapy\n‑\ntreatment planning.\nVerification and validation testing were conducted to\nconfirm that the thirdparty contouring performs as\nintended and does not adversely impact the safety or\n‑\neffectiveness of the overall system.\nVerification testing was conducted to confirm correct\nDICOM export functionality, preservation of data\nintegrity, and successful creation of an offline adaptive\nplan when using the third party contouring functionality.\n‑\nValidation testing was conducted to verify the treatment\nplanning workflows in a Treatment Planning System\n(TPS) and treatment preparation in Record and Verify\n(R&V) system.\nAcceptance criteria were defined to ensure that\nthirdparty contouring outputs are clinically acceptable\nand comparable to reference contours produced by\n‑\nqualified users.\nAll verification and validation testing met the predefined\nacceptance criteria. All planned Solution Interoperability\ntest cases have been successfully executed and passed."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252007-p5-t0","doc_id":"K252007","page_num":5,"bbox":[124.82,151.98,540.24,754.24],"n_rows":57,"n_cols":4,"columns":["....................................","................","..............................................................................","1"],"rows":[["....................................","................","..............................................................................","1"],["","","",""],["evice ...........................","................","..............................................................................","2"],["","","",""],["Device ........................","................","..............................................................................","2"],["","","",""],["Device .......................","................","..............................................................................","2"],["","","",""],["scription .....................","................","..............................................................................","3"],["","","",""],["for Use .......................","................","..............................................................................","3"],["","","",""],["dications ......................","................","..............................................................................","3"],["","","",""],["Patient Population ......","................","..............................................................................","4"],["","","",""],["User ...........................","................","..............................................................................","4"],["","","",""],["ment of Use ..................","................","..............................................................................","4"],["","","",""],["ble Ultrasounds ...........","................","..............................................................................","4"],["","","",""],["on of Technological C","haracteri","stics with the Predicate Device ...........................","4"],["","","",""],["ce Data ......................","................","..............................................................................","7"],["","","",""],["y of Non-Clinical Tests","................","..............................................................................","7"],["","","",""],["ation and Validation .....","................","..............................................................................","7"],["","","",""],["ssessment ..................","................","..............................................................................","7"],["","","",""],["security Assessment ....","................","..............................................................................","8"],["","","",""],["alone Performance Ass","essment ..","..............................................................................","8"],["","","",""],["y of Clinical Tests ........","................","..............................................................................","8"],["","","",""],["n .................................","................","..............................................................................","9"],["","","",""],["itter","","",""],["","","",""],["","Deep Bre","athe Inc.",""],["","","",""],["","45 King S","t #300",""],["","","",""],["","London, O","N N6A 1B8",""],["","","",""],["","Canada","",""],["","","",""],["ontact Person:","Robert Ar","ntfield",""],["","CEO and","Founder",""],["","Deep Bre","athe Inc.",""],["","Email: rob","@deepbreathe.ai",""],["","Phone: 51","96394941",""],["","","",""],["","","","1"]],"caption_candidate":"Submitter .................................................................................................................................. 1","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252007-p6-t0","doc_id":"K252007","page_num":6,"bbox":[77.06,78.66,493.53,705.37],"n_rows":47,"n_cols":4,"columns":["Secondary Contact Person:","Nima Akhlaghi","",""],"rows":[["Secondary Contact Person:","Nima Akhlaghi","",""],["","Director, Digital Health and Ima","ging Center","Lead"],["","MCRA","",""],["","Email: nakhlaghi@mcra.com","",""],["","Phone: 202-301-4443","",""],["","","",""],["Date Prepared:","2025-06-26","",""],["","","",""],["Subject Device","","",""],["","","",""],["Name of Device:","BlineSlide","",""],["","","",""],["Manufacturer:","Deep Breathe Inc.","",""],["","","",""],["Classification Name:","Automated Radiological Image","Processing","Software"],["","","",""],["Regulation Number:","21 CFR 892.2050","",""],["","","",""],["Regulatory Class:","II","",""],["","","",""],["Product Code:","QIH","",""],["","","",""],["Predicate Device","","",""],["","","",""],["Name of Device:","AI Platform","",""],["","","",""],["Premarket Notification:","K232501","",""],["","","",""],["Manufacturer:","Exo Imaging","",""],["","","",""],["Classification Name:","Automated Radiological Image","Processing","Software"],["","","",""],["Regulation Number:","21 CFR 892.2050","",""],["","","",""],["Regulatory Class:","II","",""],["","","",""],["Product Code:","QIH","",""],["","","",""],["Reference Device","","",""],["","","",""],["Name of Device:","Lumify Diagnostic Ultrasound S","ystem",""],["","","",""],["Premarket Notification:","K223771","",""],["","","",""],["Manufacturer:","Philips","",""],["","","",""],["Classification Name:","Ultrasonic Pulsed Doppler Imag","ing System",""]],"caption_candidate":"Secondary Contact Person: Nima Akhlaghi","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252007-p8-t0","doc_id":"K252007","page_num":8,"bbox":[72.5,503.23,540.58,714.94],"n_rows":2,"n_cols":5,"columns":["Feature","Subject Device\nBlineslide","Predicate\nDevice\nAI Platform\n(K232501)","Reference\nDevice\nLumify\nDiagnostic\nUltrasound\nSystem\n(K223771)","Discussion of\nDifferences"],"rows":[["Feature","Subject Device\nBlineslide","Predicate\nDevice\nAI Platform\n(K232501)","Reference\nDevice\nLumify\nDiagnostic\nUltrasound\nSystem\n(K223771)","Discussion of\nDifferences"],["Indications for\nUse","The device is\nintended for\nnoninvasive\nprocessing of\nultrasound\nimages to\ndetect, measure,\nand calculate","The device is\nintended for\nnoninvasive\nprocessing of\nultrasound\nimages to\ndetect, measure,\nand calculate","The device is\nintended for\ndiagnostic\nultrasound\nimaging in B\n(2D), Pulsed\nWave, Color\nDoppler,","Equivalent to\npredicate. The\nsubject device is\nintended for use\nin patients aged\n18 years and\nolder. The\npredicate device"]],"caption_candidate":"predicate, and reference device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252007-p9-t0","doc_id":"K252007","page_num":9,"bbox":[72.5,72.48,540.58,712.78],"n_rows":3,"n_cols":5,"columns":["","relevant medical\nparameters of\nstructures and\nfunction of\npatients aged 18\nyears or older\nwith suspected\ndisease.","relevant medical\nparameters of\nstructures and\nfunction of adult\npatients with\nsuspected\ndisease.","Combined\n(B+Color), and\nM modes.","is intended for\nadult patients\naged 22 years\nand older. This\ndifference in\nminimum patient\nage does not\nimpact the\nintended use or\nraise new\nquestions of\nsafety and\neffectiveness.\nComparisons\nwith the\nreference device\nare focused on\nits merged B line\nartifact detection\nsoftware feature."],"rows":[["","relevant medical\nparameters of\nstructures and\nfunction of\npatients aged 18\nyears or older\nwith suspected\ndisease.","relevant medical\nparameters of\nstructures and\nfunction of adult\npatients with\nsuspected\ndisease.","Combined\n(B+Color), and\nM modes.","is intended for\nadult patients\naged 22 years\nand older. This\ndifference in\nminimum patient\nage does not\nimpact the\nintended use or\nraise new\nquestions of\nsafety and\neffectiveness.\nComparisons\nwith the\nreference device\nare focused on\nits merged B line\nartifact detection\nsoftware feature."],["Principle of\noperation and\ntechnology","Ultrasound image\nprocessing software\nimplementing artificial\nintelligence including\nnon-adaptive machine\nlearning algorithms trained\nwith clinical data intended\nfor non-invasive analysis of\nultrasound data","","","Identical."],["Input","MP4","DICOM","","Equivalent. The\nchange in input\nformat does not\nchange the\nIntended Use.\nBoth formats\nstore the same\nultrasound\nimaging data\nrequired for\nclinical\ninterpretation.\nWhile DICOM\nincludes\nadditional\nmetadata, this is\nnot critical to the\nproposed\ndevice's"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252007-p10-t0","doc_id":"K252007","page_num":10,"bbox":[72.5,72.48,540.58,712.9],"n_rows":8,"n_cols":5,"columns":["","","","","functionality."],"rows":[["","","","","functionality."],["Scan type","Multi-frame\nultrasound\nimages (cines)","Single and multi-frame ultrasound\nimages","","Identical."],["Image review","Deep convolutional neural networks for segmentation\nor landmark detection","","","Identical."],["Editing of\noutputs by user\nallowed","Yes","","","Identical."],["Report creation","Yes. A table\nsummarizing the\ndevice outputs\nfor each\nuploaded cine is\ndisplayed to the\nuser.","Yes","","Identical."],["Anatomical\nSites","Lungs","Heart, Lungs","Lungs","Equivalent to\npredicate.\nRestricting the\nanatomical site\nto the lungs\ndoes not change\nthe Intended\nUse. Identical to\nreference\ndevice."],["Lung artifacts\ndetected","B line artifacts","A line artifacts, B\nline artifacts","B line artifacts","Identical."],["B line artifact\ndetection","Detects the\npresence or\nabsence of B\nlines","Counts B lines","Counts B lines\nand detects the\npresence or\nabsence of\nmerged B lines","Equivalent. The\nupdated task\nformulation does\nnot change the\nIntended Use.\nThe provided\nperformance\nassessment for\nthe B line artifact\ndetection\nmodule\ndemonstrates\nthat this\ndifference does\nnot raise any"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252007-p12-t0","doc_id":"K252007","page_num":12,"bbox":[72.57,468.35,540.58,539.11],"n_rows":5,"n_cols":4,"columns":["","","","Reliability"],"rows":[["","","","Reliability"],["","","",""],["","","",""],["Sensitivity","","","0.91 (0.88 – 0.94)"],["Specificity","","","0.84 (0.81 – 0.86)"]],"caption_candidate":"Table 2 below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p4-t0","doc_id":"K252018","page_num":4,"bbox":[18.92,19.44,593.09,468.24],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252018 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252018 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K252018",""],["Please provide the device trade name(s).","",""],["HERA Z20 Diagnostic Ultrasound System; HERA Z20e Diagnostic Ultrasound System; HERA Z20s\nDiagnostic Ultrasound System; R20 Diagnostic Ultrasound System; HERA Z30 Diagnostic Ultrasound\nSystem· R30 Diagnostic Ultrasound System","",""],["Please provide your Indications for Use below.","","?"],["HERA Z20 Diagnostic Ultrasound System; HERA Z20e Diagnostic Ultrasound System; HERA Z20s\nDiagnostic Ultrasound System; R20 Diagnostic Ultrasound System; HERA Z30 Diagnostic Ultrasound\nSystem; R30 Diagnostic Ultrasound System and probes are designed to obtain ultrasound images and\nanalyze body fluids.\nThe clinical applications include: Fetal/Obstetrics, Abdominal, Gynecology, Intra-operative, Pediatric, Small\nOrgan, Neonatal Cephalic, Adult Cephalic, Trans-rectal, Trans-vaginal, Muscular-Skeletal (Conventional,\nSuperficial), Urology, Cardiac Adult, Cardiac Pediatric, Thoracic, Trans-esophageal (Cardiac), Peripheral\nvessel and Ophthalmic.\nIt is intended for use by, or by the order of, and under the supervision of, an appropriately trained healthcare\nprofessional who is qualified for direct use of medical devices. It can be used in hospitals, private practices,\nclinics and similar care environment for clinical diagnosis of patients.\nModes of Operation: 2D mode, M mode, Color Doppler mode, Pulsed Wave (PW) Doppler mode,\nContinuous Wave (CW) Doppler mode, Tissue Doppler Imaging (TOI) mode, Tissue Doppler Wave (TOW)\nmode, Power Doppler (PD) mode, ElastoScan Mode, MV-Flow Mode, Multi Image mode(Dual, Quad),\nCombined modes, 3D/4D mode.","",""],["Please select the types of uses (select one or both, as ~ Prescription Use (Part 21 CFR 801 Subpart D)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p10-t0","doc_id":"K252018","page_num":10,"bbox":[111.64,419.21,543.92,688.3],"n_rows":7,"n_cols":6,"columns":["","Reference No.","","","Title",""],"rows":[["","Reference No.","","","Title",""],["IEC 60601-1","","","AAMI ANSI ES60601-1:2005/(R)2012 & A1:2012 C1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons. Text) [Incl. AMD2:2021], Medical electrical\nequipment - Part 1: General requirements for basic safety and essential\nperformance (IEC 60601-1:2005 MOD) [Including Amendment 2 (2021)]","",""],["IEC 60601-1-2","","","ANSI AAMI IEC 60601-1-2:2014 [Including AMD 1:2021], Medical\nelectrical equipment - Part 1-2: General requirements for basic safety and\nessential performance - Collateral Standard: Electromagnetic disturbances\n- Requirements and tests [Including Amendment 1 (2021)]","",""],["IEC 60601-2-37","","","IEC 60601-2-37 Edition 2.1 2015, Medical electrical equipment - Part 2-\n37: Particular requirements for the basic safety and essential performance\nof ultrasonic medical diagnostic and monitoring equipment","",""],["IEC 60601-4-2","","","IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -\nPart 4-2: Guidance and interpretation - Electromagnetic immunity:\nperformance of medical electrical equipment and medical electrical\nsystems","",""],["ISO10993-1","","","ANSI AAMI 10993-1 Fifth edition 2018-08, Biological evaluation of\nmedical devices - Part 1: Evaluation and testing within a risk management\nprocess","",""],["ISO14971","","","ANSI AAMI ISO 14971:2019, Medical devices - Application of risk\nmanagement to medical devices","",""]],"caption_candidate":"System and their applications comply with the following FDA-recognized standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p13-t0","doc_id":"K252018","page_num":13,"bbox":[134.54,78.0,528.45,186.02],"n_rows":7,"n_cols":2,"columns":["□ Gender: Male/Female",""],"rows":[["□ Gender: Male/Female",""],["□ Age: 20~40, 41~60, 60 over",""],["□ BMI: Normal or Underweight(BMI<=24.9), Overweight(25<=BMI<=29.9),",""],["Obese(30<=BMI)",""],["□ Ethnicity/Race : Asian, Black or African American, Hispanic or Latino, White",""],["□ Country: United States and Germany",""],["",""]],"caption_candidate":"Traditional 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p19-t0","doc_id":"K252018","page_num":19,"bbox":[134.82,351.29,528.45,464.11],"n_rows":8,"n_cols":2,"columns":["□ All ground truth (Measure, points, segmentation) were made by sonographer.",""],"rows":[["□ All ground truth (Measure, points, segmentation) were made by sonographer.",""],["□ Images for validation were first classified into the correct views by participating",""],["sonographer. Afterwards, corresponding anatomy areas were manually drawn for",""],["each of the image by two sonographers.",""],["□ The expert who classified views of the validation images has more than 10 years of",""],["experience. The sonographer who made the ground truth of the validation images",""],["have more than 10 years of experience.",""],["",""]],"caption_candidate":"(i.e. the “truthing” process):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p19-t1","doc_id":"K252018","page_num":19,"bbox":[83.66,476.95,528.45,518.83],"n_rows":3,"n_cols":2,"columns":["","□ Data used for test and training/tuning purpose are completely separated from the"],"rows":[["","□ Data used for test and training/tuning purpose are completely separated from the"],["","ones during training process and there is no overlap between the two."],["",""]],"caption_candidate":"▣ Description of how the independence of test data from training data was ensured:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p19-t2","doc_id":"K252018","page_num":19,"bbox":[134.82,569.59,528.45,649.42],"n_rows":6,"n_cols":2,"columns":["□ Detection test",""],"rows":[["□ Detection test",""],["","The feature demonstrated a localization accuracy success rate of 92.19% (95% CI:"],["","[90.03%, 94.34%]) and a processing speed of approximately 3.98 FPS. The success"],["","rate was defined as the percentage of frames within entire image sequences that"],["","achieve the pre-specified frame accuracy criteria, in accordance with a reference"],["","standard (truthing process)."]],"caption_candidate":"information supporting the appropriateness of the characterized performance.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p20-t0","doc_id":"K252018","page_num":20,"bbox":[136.7,90.86,528.45,161.9],"n_rows":5,"n_cols":2,"columns":["□ At least two nerve views were used per patient, with 2D sequences consisting of at",""],"rows":[["□ At least two nerve views were used per patient, with 2D sequences consisting of at",""],["least 10 images.",""],["□ The validation dataset consisted of at least 24 and up to 42 ultrasound images for",""],["each of the 10 nerves.",""],["",""]],"caption_candidate":"▣ The number of samples, if different from above, and the relationship between the two:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p20-t1","doc_id":"K252018","page_num":20,"bbox":[136.7,174.74,528.45,282.77],"n_rows":7,"n_cols":2,"columns":["□ Gender: Male/ Female",""],"rows":[["□ Gender: Male/ Female",""],["□ Age: 20-40, 41-60, 61 and over",""],["□ BMI: Normal/Underweight (BMI<25), Overweight (25≤BMI<30), Obese",""],["(BMI≥30)",""],["□ Race/Ethnicity: Asian, African American, Hispanic, White, Unknown",""],["□ Country: South Korea and United States",""],["",""]],"caption_candidate":"▣ Demographic distribution:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p20-t2","doc_id":"K252018","page_num":20,"bbox":[136.7,295.61,528.45,350.09],"n_rows":4,"n_cols":2,"columns":["□ We divided the nerve ultrasound images into ten nerve groups depending on the",""],"rows":[["□ We divided the nerve ultrasound images into ten nerve groups depending on the",""],["scanning region. The acquired data were further stratified by patient gender, age,",""],["BMI, clinical site, and race/ethnicity for subgroup analysis.",""],["",""]],"caption_candidate":"▣ Information about clinical subgroups and confounders present in the dataset:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p20-t3","doc_id":"K252018","page_num":20,"bbox":[136.7,362.93,528.45,430.13],"n_rows":5,"n_cols":2,"columns":["□ We acquired the data set with SAMSUNG MEDISON’s ultrasound system (R20,",""],"rows":[["□ We acquired the data set with SAMSUNG MEDISON’s ultrasound system (R20,",""],["RS85, V8, V7, V5) and probe (LA2-14A, LA2-9S, L3-22) in order to secure",""],["diversity of the data set: Mix of data from retrospective data collection and",""],["prospective data collection in clinical practice.",""],["",""]],"caption_candidate":"▣ Information about equipment and protocols used to collect images","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252018-p20-t4","doc_id":"K252018","page_num":20,"bbox":[136.7,455.59,528.45,586.03],"n_rows":10,"n_cols":2,"columns":["□ The reference standard for NerveTrack was established through a rigorous, multi-",""],"rows":[["□ The reference standard for NerveTrack was established through a rigorous, multi-",""],["expert process to ensure accuracy and objectivity. The process was initiated by two",""],["clinical experts, each with extensive experience in musculoskeletal ultrasound, who",""],["independently performed manual segmentation by drawing a Region of Interest",""],["(ROI) around the target nerve in each frame of the test data clips. A third, senior",""],["clinical expert, also with extensive experience in the field, then acted as an",""],["adjudicator. This senior expert reviewed the two independent segmentations and",""],["resolved any discrepancies to establish the single, definitive ground truth ROI for",""],["each frame used in the performance evaluation.",""],["",""]],"caption_candidate":"(i.e. the “Truthing” process):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252029-p9-t0","doc_id":"K252029","page_num":9,"bbox":[72.24,176.12,756.24,538.9],"n_rows":4,"n_cols":9,"columns":["Feature","Subject Device\nAI-CVD®","Predicate 1\nAutoChamber\nK240786","Predicate 2","Reference 1","","Reference 2","","Reference 3"],"rows":[["Feature","Subject Device\nAI-CVD®","Predicate 1\nAutoChamber\nK240786","Predicate 2","Reference 1","","Reference 2","","Reference 3"],["","","","Auto-BMD","AI-Rad","","Imbio","","Imbio"],["","","","K213760","K183268","","K230112","","K141069"],["Indication for\nUse\n/Intended Use","Estimate the volume of\ncardiac chambers,\nepicardial fat, aortic\nvalves, ascending aorta,\nand pulmonary artery in\nnon-contrast and contrast-\nenhanced CT scan images\nEstimate the percentage\nof liver voxels below\n40HU in non-contrast CT\nscan images\nEstimate the percentage\nof lung voxels below -950\nand above -250 in non-\ncontrast CT scan images","Estimate the volume\nof cardiac chambers\nin non-contrast and\ncontrast-enhanced\nCT scan images","Estimate bone\nmineral density\nwithin the spine","Estimate the\nvolume of the\nheart\nEstimate the\ntotal volume of\ncalcium in\ncoronary\narteries\nEstimate the\nmaximum\ndiameter of the\naorta at typical\nlandmarks","Estimate\ncoronary artery\ncalcium score","","","Estimate\npulmonary tissue\ndensity within\nthe lungs"]],"caption_candidate":"systems that raise new issues of safety and/or effectiveness. Thus, AI-CVD® is substantially equivalent to the predicate and reference devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252029-p10-t0","doc_id":"K252029","page_num":10,"bbox":[72.24,105.26,756.36,514.42],"n_rows":3,"n_cols":7,"columns":["","Estimate the volume of\nskeletal muscle,\nsubcutaneous fat, and\nvisceral fat in non-\ncontrast CT scan images\nEstimate coronary artery\ncalcium score, aortic wall\nand valve calcium scores,\nand mitral valve calcium\nscore in non-contrast\nECG-gate and non-gated\nchest CT scan images","","","","",""],"rows":[["","Estimate the volume of\nskeletal muscle,\nsubcutaneous fat, and\nvisceral fat in non-\ncontrast CT scan images\nEstimate coronary artery\ncalcium score, aortic wall\nand valve calcium scores,\nand mitral valve calcium\nscore in non-contrast\nECG-gate and non-gated\nchest CT scan images","","","","",""],["Modality","CT scan images\n(DICOM)","CT scan images\n(DICOM)","CT scan images\n(DICOM)","CT scan images\n(DICOM)","CT scan images\n(DICOM)","CT scan images\n(DICOM)"],["Body Part","Chest / Abdomen","Chest","Chest /\nAbdomen","Chest","Chest","Chest"]],"caption_candidate":"Houston, TX 77021","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252029-p11-t0","doc_id":"K252029","page_num":11,"bbox":[77.64,78.27,723.16,571.24],"n_rows":28,"n_cols":7,"columns":["","","","","","Houston,","TX 77021"],"rows":[["","","","","","Houston,","TX 77021"],["","","","","","",""],["Automatic","Yes, Deep Learning","Yes, Deep Learning","Yes, Deep","Yes, Deep","Yes, Deep","Yes, Deep"],["definition of","","","Learning","Learning","Learning","Learning"],["ROIs","","","","","",""],["","","","","","",""],["Device","Yes","Yes","Yes","Yes","Yes","Yes"],["measures","","","","","",""],["volume within","","","","","",""],["the Region of","","","","","",""],["Interest (ROI).","","","","","",""],["","","","","","",""],["Device","Yes","Yes","Yes","Yes","Yes","Yes"],["measures","","","","","",""],["densities","","","","","",""],["within the","","","","","",""],["Region of","","","","","",""],["Interest (ROI).","","","","","",""],["","","","","","",""],["User","Healthcare Provider","Healthcare Provider","Healthcare","Healthcare","Healthcare","Healthcare"],["","","","Provider","Provider","Provider","Provider"],["","","","","","",""],["Operating","Linux","Linux","Linux","Windows","Windows","Windows"],["System","","","","","",""],["","","","","","",""],["AI-CVD® is a registered trade","mark of the HeartLung Corporation. THIS DOC","UMENT IS THE PROPERTY OF","Pg",". 7 of 11","",""],["HEARTLUNG CORPORATI","ON.","","","","",""],["© HEARTLUNG CORPORA","TION. ALL RIGHTS RESERVED.","","","","",""]],"caption_candidate":"2450 Holcombe Blvd","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252041-p6-t0","doc_id":"K252041","page_num":6,"bbox":[72.29,554.82,517.45,585.0],"n_rows":2,"n_cols":9,"columns":["","510(k) Number","","","Device/Manufacturer","","","Predicate/Reference",""],"rows":[["","510(k) Number","","","Device/Manufacturer","","","Predicate/Reference",""],["DEN220040","","","Fibresolve / Imvaria, Inc","","","Predicate","",""]],"caption_candidate":"Fibresolve (with PCCP) is substantially equivalent to the following predicate:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252041-p10-t0","doc_id":"K252041","page_num":10,"bbox":[72.48,78.96,679.5,511.26],"n_rows":10,"n_cols":4,"columns":["","Age > 22 years old.\nPulmonary symptoms suggestive of possible\nILD including IPF.","Age > 22 years old.\nPulmonary symptoms suggestive of possible\nILD including IPF.",""],"rows":[["","Age > 22 years old.\nPulmonary symptoms suggestive of possible\nILD including IPF.","Age > 22 years old.\nPulmonary symptoms suggestive of possible\nILD including IPF.",""],["User population","Clinicians qualified in the care of lung disease,\nspecifically in caring for patients with ILD","Clinicians qualified in the care of lung disease,\nspecifically in caring for patients with ILD","Same"],["Target Population","Age > 22 years old.","Age > 22 years old.","Same"],["Anatomical region\nof interest","Chest","Chest","Same"],["Scan type and\nprotocol","DICOM-compliant lung CT scan","DICOM-compliant lung CT scan","Same"],["Software Inputs","CT scan\nPotentially age, sex, and pulmonary function\ntests (PFTs)","CT scan","Similar"],["Segmentation of\nregion\nof interest","No; device does not mark, annotate, or direct\nusers’ attention to a specific location in the\noriginal image","No; device does not mark, annotate, or direct\nusers’ attention to a specific location in the\noriginal image","Same"],["Algorithm","Machine learning pattern recognition","Machine learning pattern recognition","Same"],["Alteration of\noriginal image","No","No","Same"],["Data Displayed","Qualitative classification output of imaging\nfindings\nInputs that contribute to the diagnostic result","Qualitative classification output of imaging\nfindings","Similar"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252041-p12-t0","doc_id":"K252041","page_num":12,"bbox":[72.24,78.72,719.76,534.36],"n_rows":3,"n_cols":4,"columns":["Modification","Rationale","Testing Methods","Impact Assessment"],"rows":[["Modification","Rationale","Testing Methods","Impact Assessment"],["Model architecture\nmodification","With advancements in\nunderlying model architecture\nthrough new computer\nscience developments,\nnew model training allows for\nimprovements in performance\nin terms of overall metrics as\nwell as consistency and speed.","Substantial\nequivalence as\ncompared to the\nprior version.\nStatistical\nassessments\nfollowing same\nstandards used in\noriginal device\nclearance.","Revised\ngeneralizability or\ndiscriminatory capacity\nmetrics for\nthe system.\nBenefit-Risk Analysis:\nBenefit: Enhanced\nperformance;\ngeneralizability.\nRisk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."],["Introduction of new training\ndata","With new training data, new\nmodel training allows for\nimprovements in\ngeneralizability, robustness,\nand reductions in biases,\nwhich\nprovides greater","Substantial\nequivalence as\ncompared to the\nprior version.\nStatistical\nassessments\nfollowing same\nstandards used in\noriginal device","Revised\nsensitivity and specificity\nmetrics for\nthe system.\nBenefit-Risk Analysis:\nBenefit: Enhanced\nperformance;\ngeneralizability."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252041-p13-t0","doc_id":"K252041","page_num":13,"bbox":[72.24,78.72,719.76,533.88],"n_rows":2,"n_cols":4,"columns":["","clinical value. Performance\nimprovements may also be\nachieved.","clearance.","Risk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."],"rows":[["","clinical value. Performance\nimprovements may also be\nachieved.","clearance.","Risk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."],["Incorporation of ancillary\ninputs","Addition of non-imaging\nancillary inputs into the model\nto improve overall\nperformance with model\ncomponent contributions\ndisplayed with the final result.\nimprovements enhance\nperformance and overall\nclinical value.","Substantial\nequivalence as\ncompared to the\nprior version.\nStatistical\nassessments\nfollowing same\nstandards used in\noriginal device\nclearance","Revised\nsensitivity and specificity\nmetrics for\nthe system.\nBenefit-Risk Analysis:\nBenefit: Enhanced\nperformance;\ngeneralizability; explainability.\nRisk: Reduction in\nclinical performance\nor generalizability.\nRisk Mitigation:\nEvaluate device\nmodel on Test\ndataset metrics.\nExecute unit and\nintegration tests for\nthe product code."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252074-p6-t0","doc_id":"K252074","page_num":6,"bbox":[106.14,112.5,544.38,167.28],"n_rows":2,"n_cols":4,"columns":["Product","Marketed by","510(k) Number","Clearance Date"],"rows":[["Product","Marketed by","510(k) Number","Clearance Date"],["Aplio i900/i800/i700 Diagnostic\nUltrasound System, Software\nV8.5","Canon Medical\nSystems USA, Inc.","K242808","May 13, 2025"]],"caption_candidate":"8. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252074-p9-t0","doc_id":"K252074","page_num":9,"bbox":[100.74,85.68,539.76,385.5],"n_rows":3,"n_cols":2,"columns":["Demographic distribution","This study included representative images\nfrom 30 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 23-89 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 18.5-36.3 kg/m2,\nequally distributed across underweight\nor healthy, overweight, and obese\ncategories\n• Images were collected of various\nrepresentative abdominal organs and\nanatomical structures, as well as\nvarious representative focal\npathologies"],"rows":[["Demographic distribution","This study included representative images\nfrom 30 patients selected from among\npreviously acquired data\n• Gender: roughly equivalent number of\nmales and females\n• Age: Ranging from 23-89 years old\n• Ethnicity (Country): USA\n• BMI: ranging from 18.5-36.3 kg/m2,\nequally distributed across underweight\nor healthy, overweight, and obese\ncategories\n• Images were collected of various\nrepresentative abdominal organs and\nanatomical structures, as well as\nvarious representative focal\npathologies"],["Data collection","Minimum 294 images from demographically\ndiverse patients acquired at a U.S. clinical site"],["Evaluation Method","Three (3) board certified U.S. radiologists\nparticipate in a blind scoring and visibility\nevaluation in accordance with Canon’s study\ndesign"]],"caption_candidate":"Validation details:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p5-t0","doc_id":"K252084","page_num":5,"bbox":[71.11,167.24,544.8,297.62],"n_rows":8,"n_cols":2,"columns":["510(k) Sponsor","AI4MedImaging Medical Solutions S.A."],"rows":[["510(k) Sponsor","AI4MedImaging Medical Solutions S.A."],["Address","Rua do Parque Poente, lt 32\n4705-002 Sequeira, Braga Portugal"],["",""],["Correspondence Person","Sandra Soniec\nSenior consultant\nmeditec Consulting GmbH, Switzerland"],["",""],["Contact Information","Email: soniec@meditec-consulting.ch\nPhone: +41 31 535 3193"],["",""],["Date Prepared","February 10, 2026"]],"caption_candidate":"1 General Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p5-t1","doc_id":"K252084","page_num":5,"bbox":[71.11,349.76,544.8,449.08],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","AI4CMR v2.0"],"rows":[["Proprietary Name","AI4CMR v2.0"],["Common Name","AI4CMR"],["Classification Name","Automated radiological image processing software"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH, LLZ"],["Regulatory Class","II"]],"caption_candidate":"2 Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p5-t2","doc_id":"K252084","page_num":5,"bbox":[71.11,501.28,544.8,625.2],"n_rows":9,"n_cols":2,"columns":["Proprietary Name","AI4CMR v1.0"],"rows":[["Proprietary Name","AI4CMR v1.0"],["(Predicate Device)",""],["Premarket Notification","K220624"],["Common Name","AI4CMR"],["Classification Name","Automated radiological image processing software"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"3 Predicate and Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p9-t0","doc_id":"K252084","page_num":9,"bbox":[71.05,81.72,524.15,777.6],"n_rows":16,"n_cols":7,"columns":["Feature, Function","Subject device\nAI4CMR v2.0","Predicate\nDevice\nAI4CMR v1.0\n(K220624)","","Reference","","Comparison"],"rows":[["Feature, Function","Subject device\nAI4CMR v2.0","Predicate\nDevice\nAI4CMR v1.0\n(K220624)","","Reference","","Comparison"],["","","","","Device","",""],["","","","","Circle cvi42 (2D","",""],["","","","","Flow feature)","",""],["","","","","(K242781)","",""],["","third-party viewer","third-party viewer","third-party viewer","","",""],["Secondary\nCapture","N/A","N/A","N/A","","","Same"],["Segmentation of\nregion of interest","Automatic","Automatic","Automatic","","","Same"],["Phase Error\nCorrection","No","No","No","","","Same"],["Quantitative\nAnalysis, Flow","Yes, 2D Phase\nContrast","No","Similar,\ncomparative\nPerformance\nEvaluation\nconfirmed\nequivalence","","","Similar"],["Quantitative\nAnalysis,\nArea","No","No","No","","","Same"],["Quantitative\nAnalysis,\nDistance","No","No","No","","","Same"],["Quantitative\nAnalysis, Volume\nin 4D Flow\nWorkflow","No","No","No","","","Same"],["Directional/vector\ndisplay of the\nblood particle\ntravel","No","No","No","","","Same"],["Flow\nquantification\nof valves","No","No","No","","","Same"],["Automatic\nselection of the\nTemporal\nLandmark time\npoints","No","No","No","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p10-t0","doc_id":"K252084","page_num":10,"bbox":[71.04,114.36,524.16,772.32],"n_rows":5,"n_cols":2,"columns":["Model Overview","Model Name: 2D Flow Segmentation\nVersion: 1.0.0\nDeveloper / Manufacturer: AI4CMR\nModel Category: Convolutional Neural Network (U-Net architecture)\nPrimary Function: Automated segmentation of major cardiac vessels on 2D\nflow CMR (PC-MRI) images.\nRegulatory Classification: Class II, System, Image Processing, Radiological\nShort Description:\nThe model uses a U-Net convolutional neural network to generate pixel-wise\nsegmentation masks of cardiac vessels (aorta, pulmonary artery) on phase-\ncontrast MRI images. The segmentation supports calculation of flow and\nvelocity profiles and quantification."],"rows":[["Model Overview","Model Name: 2D Flow Segmentation\nVersion: 1.0.0\nDeveloper / Manufacturer: AI4CMR\nModel Category: Convolutional Neural Network (U-Net architecture)\nPrimary Function: Automated segmentation of major cardiac vessels on 2D\nflow CMR (PC-MRI) images.\nRegulatory Classification: Class II, System, Image Processing, Radiological\nShort Description:\nThe model uses a U-Net convolutional neural network to generate pixel-wise\nsegmentation masks of cardiac vessels (aorta, pulmonary artery) on phase-\ncontrast MRI images. The segmentation supports calculation of flow and\nvelocity profiles and quantification."],["Intended Users","AI4CMR shall be used by qualified medical professionals, experienced in\nexamining and evaluating magnetic resonance images as a support tool that\nprovides relevant clinical information. The software is not intended to\ndetermine or recommend a course of action or treatment for a patient."],["Indications for Use","AI4CMR supports clinical diagnostics by calculating flow measurements of\nvascular structures in 2D phase-encoded cardiac MR images. Its results are\nnot intended to be used on a stand-alone basis for clinical decision-making."],["Model Summary","AI4CMR uses a convolutional neural network–based segmentation model to\noutline vascular structures on magnitude and phase images. A user-\nselected seed point localizes the vessel, and generated contours may be\nmanually edited by the clinician.\nThe model is “locked,” meaning it does not adapt or change with new input\ndata."],["AI-based 2D Flow\nSegmentation –\nModel Development","The AI-based vessel segmentation model was developed using retrospective\nclinical data comprising 167 cardiac MR cases from 61 adult subjects (32%\nfemale, 68% male; age range 17–89 years, mean age 62), obtained from a\ntertiary Western European hospital. Images were acquired using standard\ncardiac MR 2D phase-contrast flow imaging protocols on 1.5T and 3T\nscanners. The dataset included both normal and pathological cases (e.g.,\ncardiomyopathies, aortic disease, and valvular disease) and preserved real-\nworld variability in anatomy, motion artifacts, and image quality, with no\nexclusions based solely on image quality.\nAn expert reader (EACVI level III) independently annotated all cases using\nstandard segmentation guidelines to ensure consistency and algorithm\ngeneralizability, with intra-reader reliability maintained by following\nestablished standards."]],"caption_candidate":"7 Model Card","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p11-t0","doc_id":"K252084","page_num":11,"bbox":[71.04,81.6,524.16,782.88],"n_rows":5,"n_cols":2,"columns":["","In total, 296 vessel samples (ascending aorta, descending aorta, and\npulmonary artery) were included. Data were stratified by vessel type and split\nat the subject level into training, validation, and independent test sets\n(70%/15%/15% of subjects), with all vessels and repeated acquisitions from\neach subject assigned exclusively to a single dataset to prevent data leakage.\nSegmentation performance was evaluated using the Dice Similarity\nCoefficient (DSC), with values greater than 0.70 defined a priori as the\nacceptance criterion based on established evidence of clinically usable vessel\ndelineation. On the independent test set, the model achieved DSC values of\n0.952 for the ascending aorta, 0.957 for the descending aorta, and 0.952 for\nthe pulmonary artery, exceeding the predefined acceptance threshold.\nModel generalizability was further supported through multi-vendor evaluation\nacross Siemens, GE, and Philips MRI systems and comparison with a legally\nmarketed reference device."],"rows":[["","In total, 296 vessel samples (ascending aorta, descending aorta, and\npulmonary artery) were included. Data were stratified by vessel type and split\nat the subject level into training, validation, and independent test sets\n(70%/15%/15% of subjects), with all vessels and repeated acquisitions from\neach subject assigned exclusively to a single dataset to prevent data leakage.\nSegmentation performance was evaluated using the Dice Similarity\nCoefficient (DSC), with values greater than 0.70 defined a priori as the\nacceptance criterion based on established evidence of clinically usable vessel\ndelineation. On the independent test set, the model achieved DSC values of\n0.952 for the ascending aorta, 0.957 for the descending aorta, and 0.952 for\nthe pulmonary artery, exceeding the predefined acceptance threshold.\nModel generalizability was further supported through multi-vendor evaluation\nacross Siemens, GE, and Philips MRI systems and comparison with a legally\nmarketed reference device."],["Performance\nSummary","Performance was evaluated using internally validated datasets and\nindependent multi-center data.\nSegmentation Performance:\n• Dice: 0.95\n• Precision: 0.96\n• Recall: 0.95\nAgreement With Predicate/Reference Measurements:\n(In multi-vendor, multi-center evaluation)\n• Total Forward Volume (TFV): ICC 0.95\n• Total Backward Volume (TBV): ICC 0.82\n• Maximum Velocity (Vmax): ICC 0.95"],["Generalizability","The model was evaluated on images from multiple centers and major MRI\nvendors, covering a broad range of adult patient presentations. Validation\nincluded diverse flow encoding settings and scanner configurations."],["Limitations","• Not validated on pediatric patients under 18 years\n• Not designed for 4D flow MRI\n• Not validated on congenital anomalies with extreme vessel distortion\n• Performance may decrease on images with very low signal-to-noise\nratio or poor contrast."],["Warnings &\nPrecautions","• The segmentation results must be reviewed and, if necessary,\ncorrected by a qualified clinician.\n• Segmentation inaccuracies may lead to incorrect flow quantification.\n• Not intended to provide a diagnosis or replace expert clinical\njudgment."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p12-t0","doc_id":"K252084","page_num":12,"bbox":[71.04,81.6,524.16,188.16],"n_rows":2,"n_cols":2,"columns":["User Interaction","• The user provides a seed point to identify the target vessel.\n• Segmentation contours are displayed on magnitude and phase\nimages.\n• Manual editing tools allow correction or refinement of the AI-\ngenerated contours."],"rows":[["User Interaction","• The user provides a seed point to identify the target vessel.\n• Segmentation contours are displayed on magnitude and phase\nimages.\n• Manual editing tools allow correction or refinement of the AI-\ngenerated contours."],["Version History","Version 1.0, Initial Release"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252084-p12-t1","doc_id":"K252084","page_num":12,"bbox":[197.76,84.15,277.32,183.24],"n_rows":11,"n_cols":2,"columns":["•","The user prov"],"rows":[["•","The user prov"],["",""],["•","Segmentation"],["",""],["","images."],["",""],["•","Manual editin"],["",""],["","generated con"],["",""],["ion","1.0, Initial Rel"]],"caption_candidate":"•","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252091-p4-t0","doc_id":"K252091","page_num":4,"bbox":[19.27,19.44,593.04,363.84],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252091 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252091 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K252091",""],["Please provide the device trade name(s).","",""],["Surgical Reality Viewer","",""],["Please provide your Indications for Use below.","","?"],["Surgical Reality Viewer is a medical imaging visualization software intended to assist trained healthcare\nprofessionals with preoperative and intraoperative visualizations, by displaying 2D and 3D renderings of\nDICOM compliant patient images and normal anatomic segmentations derived from patient images as well\nas functions for manipulation of segmentations and 3D models.\nSurgical Reality Viewer assists the trained healthcare professional who is responsible for making all final\npatient management decisions.\nThe machine learning algorithms in use by Surgical Reality Viewer are intended for use on adult patients\naaed 22 years and over.\nPlease select the types of uses (select one or both, as ~ Prescription Use (Part 21 CFR 801 Subpart D)\nD ?\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","",""],["","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p5-t0","doc_id":"K252091","page_num":5,"bbox":[69.41,167.76,521.28,221.64],"n_rows":4,"n_cols":2,"columns":["510(k) submission - Surgical Reality Viewer",""],"rows":[["510(k) submission - Surgical Reality Viewer",""],["Submission date","30.06.2025"],["Type of 510(k) Submission","Traditional"],["510(k) Number","K252091"]],"caption_candidate":"1 Company details","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p5-t1","doc_id":"K252091","page_num":5,"bbox":[69.41,316.89,441.0,443.04],"n_rows":10,"n_cols":4,"columns":["Contact person","","",""],"rows":[["Contact person","","",""],["Company contact","","","Chris Hordijk"],["Title","","","CEO"],["E-mail","","","chris@surgicalreality.com"],["Cell","","","+31 6 52 29 51 00"],["","","",""],["Submission correspondent","","",""],["Submission correspondent","","","L.J. Doorn"],["E-mail l","","","eondoorn@medqair.com"],["Cell","","","+31 61 10 66 42 1"]],"caption_candidate":"The Netherlands","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p5-t2","doc_id":"K252091","page_num":5,"bbox":[69.41,516.6,525.84,628.92],"n_rows":9,"n_cols":2,"columns":["Common name","Surgical Reality Viewer"],"rows":[["Common name","Surgical Reality Viewer"],["Proprietary / Trade name","Surgical Reality Viewer"],["Classification name","Automated Radiological Image Processing Software"],["Regulation number","892.2050"],["Product code","QIH"],["Device class","II"],["Review panel","Radiology"],["Special controls","None"],["510(k) number","K252091"]],"caption_candidate":"2.1 Device identification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p5-t3","doc_id":"K252091","page_num":5,"bbox":[69.41,661.92,542.28,758.36],"n_rows":8,"n_cols":2,"columns":["Trade name","Ceevra Reveal 3"],"rows":[["Trade name","Ceevra Reveal 3"],["Classification name","Automated Radiological Image Processing Software"],["Regulation number","892.2050"],["Product code","QIH"],["Device class","II"],["Review panel","Radiology"],["Submitter / 510(k) holder","Ceevra, Inc"],["510(k) number","K222676"]],"caption_candidate":"2.2 Predicate identification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p7-t0","doc_id":"K252091","page_num":7,"bbox":[70.8,654.0,524.4,704.26],"n_rows":4,"n_cols":6,"columns":["","Subject Device","","","Predicate",""],"rows":[["","Subject Device","","","Predicate",""],["","","","","",""],["","Surgical Reality Viewer","","","Ceevra Reveal 3",""],["","(K252091)","","","(K222676)",""]],"caption_candidate":"Table 1: Comparison of the Indications for Use between the subject device (Surgical Reality Viewer) and Ceevra Reveal 3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p8-t0","doc_id":"K252091","page_num":8,"bbox":[70.8,597.71,524.4,648.35],"n_rows":4,"n_cols":7,"columns":["Technological characteristic","","Subject Device","","","Predicate",""],"rows":[["Technological characteristic","","Subject Device","","","Predicate",""],["","","","","","",""],["","","Surgical Reality Viewer","","","Ceevra Reveal 3",""],["","","(K252091)","","","(K222676)",""]],"caption_candidate":"Device (Ceevra Reveal 3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p9-t0","doc_id":"K252091","page_num":9,"bbox":[70.8,145.0,524.4,184.87],"n_rows":3,"n_cols":5,"columns":["","Real-time inter-operative guidance,","","No","No"],"rows":[["","Real-time inter-operative guidance,","","No","No"],["","navigation or otherwise integrated with","","",""],["","surgical instruments","","",""]],"caption_candidate":"Intra-operative viewing of 3D images Yes Yes","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p9-t1","doc_id":"K252091","page_num":9,"bbox":[70.8,204.07,524.4,232.12],"n_rows":2,"n_cols":5,"columns":["","Built-in features for end-user to","","No","No"],"rows":[["","Built-in features for end-user to","","No","No"],["","compare CT/MRI to device output","","",""]],"caption_candidate":"Segmentation work performed by Medical Professional Internal Operator","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252091-p9-t2","doc_id":"K252091","page_num":9,"bbox":[70.8,263.11,524.4,291.16],"n_rows":2,"n_cols":5,"columns":["","Semi-automatic segmentation of","","No","No"],"rows":[["","Semi-automatic segmentation of","","No","No"],["","abnormal anatomy","","",""]],"caption_candidate":"device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p5-t0","doc_id":"K252103","page_num":5,"bbox":[109.88,474.85,528.37,554.83],"n_rows":5,"n_cols":12,"columns":["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],"rows":[["","510(k)","","","Product Code","","","Trade Name","","","Manufacturer",""],["","Primary Predicate Device","","","","","","","","","",""],["K234009","","","QIH, LLZ","","","Acorn 3D Software & 3DP Model","","","Mighty Oak Medical","",""],["","Subsequent Predicate Device","","","","","","","","","",""],["K240582","","","QIH, LLZ","","","VEA Align; spineEOS","","","EOS Imaging","",""]],"caption_candidate":"Acorn 3D Software & 3DP Model","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p6-t0","doc_id":"K252103","page_num":6,"bbox":[72.1,379.37,513.07,528.4],"n_rows":4,"n_cols":10,"columns":["","","Automatic","","","Semi-Automatic","","","Manual",""],"rows":[["","","Automatic","","","Semi-Automatic","","","Manual",""],["Definition","Algorithmic with little or no\ndirect human control","","","A combination of\nalgorithmic and direct\nhuman control","","","Directly controlled by a\nhuman","",""],["Tool Type","Machine Learning algorithm\nused to automatically\nsegment individual vertebrae\nand the pelvis","","","Algorithmic based tools that\ndo not incorporate machine\nlearning.","","","Manual tools requiring user\ninput.","",""],["Anatomical\nLocation (s)","Spinal anatomy:\n Thoracic (T1-T12)\n Lumbar (L1-L5)\n Sacrum","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","","","Musculoskeletal &\ncraniomaxillofacial bone:\n Short\n Long\n Flat\n Sesamoid\n Irregular","",""]],"caption_candidate":"musculoskeletal anatomy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p7-t0","doc_id":"K252103","page_num":7,"bbox":[141.89,471.79,470.18,514.41],"n_rows":3,"n_cols":9,"columns":["","X-Ray Technique","","","Median TRE (mm)","","","3rd Quartile TRE (mm)",""],"rows":[["","X-Ray Technique","","","Median TRE (mm)","","","3rd Quartile TRE (mm)",""],["Slot Beam","","","","1.70","","","2.74",""],["Cone Beam","","","","4.33","","","5.58",""]],"caption_candidate":"points for each x-ray technique, as summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p8-t0","doc_id":"K252103","page_num":8,"bbox":[49.34,390.65,562.76,717.1],"n_rows":7,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],"rows":[["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],["","Features↓","","","(K252103)","","","(K234009)","","","(K240582)",""],["Trade Name","","","Acorn 3D Software (AC-SEG-4009);\nAcorn 3DP Model (AC-101-XX)","","","Acorn 3D Software (AC-SEG-4009);\nAcorn 3DP Model (AC-101-XX)","","","VEA Align; spineEOS","",""],["Common\nName","","","Image processing system","","","Image processing system","","","Automated Radiological\nImage Processing Software","",""],["Premarket\nnotification","","","K252103","","","K234009","","","K240582","",""],["Manufacturer","","","Mighty Oak Medical","","","Mighty Oak Medical","","","EOS Imaging","",""],["Indications for\nUse Statement","","","Acorn 3D Software is a modular image\nprocessing software intended for use\nas an interface for visualization of\nmedical images, segmentation,\ntreatment planning, and production of\nan output file.\nThe Acorn 3D Segmentation module is\nintended for use as a software\ninterface and image segmentation\nsystem for the transfer of CT or CTA\nmedical images to an output file.\nAcorn 3D Software is also intended for\nmeasuring and treatment planning.\nThe Acorn 3D Segmentation output\ncan also be used for the fabrication of\nphysical replicas of the output file\nusing additive manufacturing\nmethods, Acorn 3DP Models. The\nphysical replica can be used for","","","Acorn Segmentation is intended for\nuse as a software interface and image\nsegmentation system for the transfer of\nCT or CTA medical images to an\noutput file. Acorn Segmentation is also\nintended for measuring and treatment\nplanning. The Acorn Segmentation\noutput can also be used for the\nfabrication of physical replicas of the\noutput file using additive\nmanufacturing methods, Acorn 3DP\nModels. The physical replica can be\nused for diagnostic purposes in the","","","VEA Align:\nThis cloud-based software is\nintended for orthopedic\napplications in both\npediatric and adult\npopulations.\n2D X-ray images acquired in\nEOS imaging’s imaging\nsystems is the foundation\nand resource to display the\ninteractive landmarks\noverlayed on the frontal\nand lateral images. These\nlandmarks are available for\nusers to assess patient-\nspecific global alignment.\nFor additional assessment,\nalignment parameters\ncompared to published","",""]],"caption_candidate":"Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p9-t0","doc_id":"K252103","page_num":9,"bbox":[49.33,72.36,562.77,721.9],"n_rows":9,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],"rows":[["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],["","Features↓","","","(K252103)","","","(K234009)","","","(K240582)",""],["","","","diagnostic purposes in the field of\nmusculoskeletal and\ncraniomaxillofacial applications.\nThe Acorn 3D Alignment and\nMeasurement module contains\nregistration capabilities and\nmeasurement functionality based on\nanatomical reference geometry. It is\nintended to allow the user to align\nanatomical structures between\ndatasets, perform spinopelvic\nmeasurements on 3D models of\nanatomy, and plan surgical\nprocedures in pediatric and adult\npatients.\nAcorn 3D Software and 3DP Models\nshould be used in conjunction with\nexpert clinical judgment.","","","field of musculoskeletal and\ncraniomaxillofacial applications.\nAcorn Segmentation and 3DP Models\nshould be used in conjunction with\nexpert clinical judgment.","","","normative values may be\navailable.\nThis product serves as a tool\nto aid in the analysis of\nspinal deformities and\ndegenerative diseases, and\nlower limb alignment\ndisorders and deformities\nthrough precise angle and\nlength measurements. It is\nsuitable for use with adult\nand pediatric patients aged\n7 years and older.\nClinical judgment and\nexperience are required to\nproperly use the software.\nspineEOS:\nspineEOS is indicated for\nassisting healthcare\nprofessionals with\npreoperative planning of\nspine surgeries. The product\nprovides access to EOS\nimages with associated 3D\ndatasets and\nmeasurements. spineEOS\nincludes surgical planning\ntools that enable users to\ndefine a patient specific\nsurgical strategy.","",""],["General\nintended use","","","Acorn 3D Software is an image\nprocessing software that allows the\nuser to import, visualize and segment\nmedical images, check and correct\nthe segmentations, conduct surgical\nplanning, and create and manipulate\ndigital 3D models.","","","Acorn Segmentation is image\nprocessing software that allows the\nuser to import, visualize and segment\nmedical images, check and correct\nthe segmentations, and create digital\n3D models.","","","spineEOS is indicated for\nassisting healthcare\nprofessionals with\npreoperative planning of\nspine surgeries. The product\nprovides access to EOS\nimages with associated 3D\ndatasets and\nmeasurements. spineEOS\nincludes surgical planning\ntools that enable users to\ndefine a patient specific\nsurgical strategy.","",""],["Product\nClassification","","","System, Image processing,\nRadiological","","","System, Image processing,\nRadiological","","","System, Image processing,\nRadiological","",""],["Regulatory\nClass","","","Class II","","","Class II","","","Class II","",""],["Regulation\nNumber","","","892.2050","","","892.2050","","","892.2050","",""],["Product Code","","","QIH and LLZ","","","QIH and LLZ","","","QIH and LLZ","",""],["Device\nDescription","","","Acorn 3D Software is an image\nprocessing software that allows the\nuser to import, visualize and segment\nmedical images, check and correct\nthe segmentations, and create digital\n3D models. The models can be used in\nAcorn 3D for measuring, treatment\nplanning and producing an output file","","","Acorn Segmentation is an image\nprocessing software that allows the\nuser to import, visualize and segment\nmedical images, check and correct\nthe segmentations, and create digital\n3D models. The models can be used in\nAcorn Segmentation for measuring,\ntreatment planning and producing an","","","VEA Align is a software\nindicated for assisting\nhealthcare professionals\nwith global alignment\nassessment through clinical\nparameters computation.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p10-t0","doc_id":"K252103","page_num":10,"bbox":[49.35,72.36,562.74,715.78],"n_rows":4,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],"rows":[["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],["","Features↓","","","(K252103)","","","(K234009)","","","(K240582)",""],["","","","to be used for additive manufacturing\n(3D printing). Acorn 3D Software is\nstructured as a modular package.\nThis includes the following functionality:\n Importing medical images in\nDICOM format\n Viewing images and DICOM data\n Selecting a region of interest using\ngeneric segmentation tools\n Segmenting specific anatomy\nusing dedicated semi-automatic\ntools or fully automatic algorithms\n Verifying and editing a region of\ninterest\n Calculating a digital 3D model\nand editing the model\n Measuring on images and 3D\nmodels\n Exporting 3D models to third-party\npackages\n Image registration\nThe Acorn 3D Segmentation module\ncontains both machine learning based\nauto segmentation as well as semi-\nautomatic and manual segmentation\ntools. The auto-segmentation tool is\nonly intended to be used for thoracic\nand lumbar regions of the spine (T1-T12\nand L1-L5). Semi-automatic and\nmanual segmentation tools are\nintended to be used for all\nmusculoskeletal anatomy.\nAcorn 3DP Model is an additively\nmanufactured physical replica of the\nvirtual 3D model generated in Acorn\n3D Segmentation. The output file from\nAcorn 3D Segmentation is used to\nadditively manufacture the Acorn 3DP\nModel.\nThe Acorn 3D Alignment and\nMeasurement module contains\nregistration capabilities and\nspinopelvic measurement\nfunctionality. It is intended to align\nspinopelvic anatomical structures\nbetween datasets. The module allows\nthe user to perform spinopelvic\nmeasurements on 3D models of\nanatomy, and to plan surgical\nprocedures.","","","output file to be used for additive\nmanufacturing (3D printing). Acorn\nSegmentation is structured as a\nmodular package.\nThis includes the following functionality:\n Importing medical images in\nDICOM format\n Viewing images and DICOM\ndata\n Selecting a region of interest\nusing generic segmentation tools\n Segmenting specific anatomy\nusing dedicated semi-automatic\ntools or fully automatic algorithms\n Verifying and editing a region of\ninterest\n Calculating a digital 3D model\nand editing the model\n Measuring on images and 3D\nmodels\n Exporting 3D models to third-party\npackages\nAcorn Segmentation contains both\nmachine learning based auto\nsegmentation as well as semi-\nautomatic and manual segmentation\ntools. The auto-segmentation tool is\nonly intended to be used for thoracic\nand lumbar regions of the spine (T1-T12\nand L1-L5). Semi-automatic and\nmanual segmentation tools are\nintended to be used for all\nmusculoskeletal anatomy.\nAcorn 3DP Model is an additively\nmanufactured physical replica of the\nvirtual 3D model generated in Acorn\nSegmentation. The output file from\nAcorn Segmentation is used to\nadditively manufacture the Acorn 3DP\nModel.","","","The product uses biplanar\n2D X-ray images, exclusively\ngenerated by EOS imaging's\nEOS (K152788) and\nEOSedge (K202394) systems\nand generates an initial\nplacement of the patient\nanatomic landmarks on the\nimages using a machine\nlearning-based algorithm.\nThe user may adjust the\nlandmarks to align with the\npatient's anatomy.\nLandmark locations require\nuser validation. The clinical\nparameters communicated\nto the user are inferred from\nthe landmarks and are\nrecalculated as the user\nadjusts the landmarks. 3D\ndatasets may be exported\nfor use in spineEOS for\nsurgical planning.\nThe product is hosted on a\ncloud infrastructure and\nrelies on VEA Portal for\nsupport capabilities, such as\nuser access control and\ndata access. 2D X-ray\nimage transmissions from\nhealthcare institutions to the\ncloud are managed by VEA\nPortal. VEA Portal is a Class I\n510(k)-exempt device\n(LMD).\nspineEOS is a software\nindicated for assisting\nhealthcare professionals\nwith preoperative planning\nof spine surgeries. EOS\nimages (generated from\nEOS imaging’s acquisition\nsystem) and associated 3D\ndatasets are used as inputs\nof the software. The product\nmanages clinical\nmeasurements and allows\nuser to access surgical\nplanning tools to define a\npatient specific surgical\nstrategy. The product is\nindicated for adolescent\nand adult patients.","",""],["Intended User","","","The Acorn 3D Segmentation module\ncan be used by biomedical engineers\nor personnel equivalent by training or\nexperience. Their results should be\nused in conjunction with expert\nclinical judgement.\nThe Acorn 3D Alignment &\nMeasurement module is intended for","","","Acorn Segmentation can be used by\nbiomedical engineers or personnel\nequivalent by training or experience.\nTheir results should be used in\nconjunction with expert clinical\njudgement.","","","spineEOS is a software\nindicated for assisting\nhealthcare professionals\nwith preoperative planning\nof spine surgeries.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p11-t0","doc_id":"K252103","page_num":11,"bbox":[49.35,72.36,562.74,723.22],"n_rows":4,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],"rows":[["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],["","Features↓","","","(K252103)","","","(K234009)","","","(K240582)",""],["","","","use by medical professionals, such as\nclinicians and surgeons, who are\ntrained in spinal procedures and the\ninterpretation of diagnostic imaging.","","","","","","","",""],["Technological\ncharacteristics","","","Acorn 3D Software is a standalone\nmodular software package. This\nsoftware package includes, but is not\nlimited to the following functions:\nAcorn 3D - Segmentation\nImage Import\n Importing medical images in\nDICOM format\nImage Processing\n Processing of images with\ncommon noise-reduction filters\n Editing of spatial arrangement of\nimages\nVisualization\n Viewing images and DICOM data\nSegmentation\n Selecting a region of interest\nusing generic segmentation tools\n Segmenting specific anatomy\nusing dedicated semi-automatic\ntools\n Segmenting specific vertebral\nanatomy using machine-learning-\nbased fully automatic algorithms\n Verifying and editing a region of\ninterest\nMeasurement\n Measuring on images and 3D\nmodels\nImage Export\n Exporting images and 3D models\nto third-party packages\n3D Models\n Calculating a digital 3D model\nand editing the model\n Smoothing a 3D model\n Importing 3D models\nTreatment Planning\n Importing of third-party STLs to\nvisualize planned interactions with\nanatomy as represented in\nDICOM images\nOther features\nUsing a collection of images and\nmasks as a training dataset for\nmachine-learning segmentation\nalgorithm\nAcorn 3D – Alignment and\nMeasurement\nRegistration","","","Acorn Segmentation is a standalone\nmodular software package. This\nmodule includes, but is not limited to\nthe following functions:\nImage Import\n Importing medical images in\nDICOM format\nImage Processing\n Processing of images with\ncommon noise-reduction filters\n Editing of spatial arrangement of\nimages\nVisualization\n Viewing images and DICOM data\nSegmentation\n Selecting a region of interest\nusing generic segmentation tools\n Segmenting specific anatomy\nusing dedicated semi-automatic\ntools\n Segmenting specific vertebral\nanatomy using machine-learning-\nbased fully automatic algorithms\n Verifying and editing a region of\ninterest\nMeasurement\n Measuring on images and 3D\nmodels\nImage Export\n Exporting images and 3D models\nto third-party packages\n3D Models\n Calculating a digital 3D model\nand editing the model\n Smoothing a 3D model\n Importing 3D models\nTreatment Planning\n Importing of third-party STLs to\nvisualize planned interactions with\nanatomy as represented in\nDICOM images\nOther features\nUsing a collection of images and\nmasks as a training dataset for\nmachine-learning segmentation\nalgorithm","","","spineEOS / VEA Align\nincludes the following\nfunctionality:\nImage Import\n Import of medical data\nVisualization\n Display of data\n Switching of view\norientation\n Basic manipulation\n(zoom, panning,\nannotations)\nMeasurement\n Distance and angle\nmeasurements on 2D\nimages and 3D models\n Clinical Parameters:\n• Pelvic Tilt (PT)\n• Sacral Slope (SS)\n• Pelvic Incidence\n(PI)\n• Pelvic Obliquity\n(PO)\n• Sagittal Vertical\nAxis (SVA)\n• C7-CSL\n• PI-LL\n• T1 Pelvic Angle\n(TPA)\n• Cobb Angle\n• Kyphosis/Lordosis\nAngle\n• Knee\nFlexion/Extension\nAngle\n• Lordosis\nPercentage\nDistributions\n• Spondylolisthesis\ngrade (i.e.,\nSlippage\npercentage)\nRegistration\n Initial placement of\nanatomic landmarks\non images using a\nmachine-learning-\nbased algorithm\n 3D reconstruction\nmodel initialized by AI\nalgorithm\n Manual deformation of\nresulting 3D model\nthrough control points","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p12-t0","doc_id":"K252103","page_num":12,"bbox":[49.34,72.36,562.76,545.35],"n_rows":6,"n_cols":12,"columns":["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],"rows":[["","Device→","","","Acorn 3D Software","","","Acorn 3D Software","","","spineEOS / VEA Align",""],["","Features↓","","","(K252103)","","","(K234009)","","","(K240582)",""],["","",""," Alignment of anatomical\nstructures between datasets\nMeasurement\n Standard and generic 3D\nmeasurements of spinopelvic\nanatomy based on user-defined\nreference geometry","","","","",""," Verification of\ndeformation result by\nmatching accurately\nthe X-ray contours\nData Export\n Export of medical data","",""],["Machine-\nLearning\nAlgorithms","","","The Acorn 3D Segmentation module\nautomates the segmentation of\nparticular anatomy (listed in IFU) by\nimplementing a 3D U-Net machine\nlearning model. Segmentation of the\nimages is completed by generating an\ninput image that is preprocessed\n(image processing methods) and then\nis run through an analysis (encoder)\npath and a synthesis (decoder) path.\nWhen the image is going through the\nanalysis path, the model is learning by\nfocusing on new information\npresented and by dynamically\nlearning which information from the\nimage is the most useful. The image\nthen goes through the synthesis path in\nwhich the model recovers spatial\nresolution and focus on salient features\nthat the analysis path coded. The\nparameters of the model were\nobtained through an algorithm\ndevelopment pipeline.","","","The Acorn 3D Segmentation module\nautomates the segmentation of\nparticular anatomy (listed in IFU) by\nimplementing a 3D U-Net machine\nlearning model. Segmentation of the\nimages is completed by generating an\ninput image that is preprocessed\n(image processing methods) and then\nis run through an analysis (encoder)\npath and a synthesis (decoder) path.\nWhen the image is going through the\nanalysis path, the model is learning by\nfocusing on new information\npresented and by dynamically\nlearning which information from the\nimage is the most useful. The image\nthen goes through the synthesis path in\nwhich the model recovers spatial\nresolution and focus on salient features\nthat the analysis path coded. The\nparameters of the model were\nobtained through an algorithm\ndevelopment pipeline.","","","N/A","",""],["Machine-\nLearning\nModels","","","Acorn 3D – Segmentation\n Vertebral model (T1-T12, L1-L5)\n Sacral model","","","Acorn Segmentation\n Vertebral model (T1-T12, L1-L5)","","","N/A","",""],["Bone Model","","","The Acorn 3D Segmentation output\ncan be used for the fabrication of\nphysical replicas of the output file\nusing additive manufacturing\nmethods. The physical replica can be\nused for diagnostic purposes and/or\nintraoperative reference of anatomy\nin the field of orthopedic and\nmusculoskeletal applications.","","","The Acorn Segmentation output can\nbe used for the fabrication of physical\nreplicas of the output file using\nadditive manufacturing methods. The\nphysical replica can be used for\ndiagnostic purposes and/or\nintraoperative reference of anatomy\nin the field of orthopedic and\nmusculoskeletal applications.","","","N/A","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p13-t0","doc_id":"K252103","page_num":13,"bbox":[60.9,72.36,551.21,114.74],"n_rows":2,"n_cols":6,"columns":["","Modification","","","Rationale",""],"rows":[["","Modification","","","Rationale",""],["Additional implementation\nof Sacral model","","","The sacrum is important to the spinopelvic pre-surgical planning workflow; auto-segmentation\nof the sacrum is intended to increase the speed and accuracy of the software.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p13-t1","doc_id":"K252103","page_num":13,"bbox":[72.29,249.68,526.54,375.88],"n_rows":6,"n_cols":12,"columns":["Model","Testing Dataset","Cases","","N","","Adult /\nPeds","M / F","","Acceptance","","Mean\nDSC"],"rows":[["Model","Testing Dataset","Cases","","N","","Adult /\nPeds","M / F","","Acceptance","","Mean\nDSC"],["","","","","(Lumbar /","","","","","Criteria","",""],["","","","","Thoracic)","","","","","(Threshold DSC)","",""],["Vertebral\n(T1-T12, L1-L5)","In-House\n(Mighty Oak Medical)","35","450\n(139 / 311)","","","15 / 20","12 / 23","> 0.88375","","","0.9331"],["","VERSE ‘20","36","401\n(144 / 257)","","","36 / 0","22 / 14","","","","0.94451"],["Sacral","In-House\n(Mighty Oak Medical)","40","40\n(N/A)","","","20 / 20","13 / 27","> 0.96045","","","0.96630"]],"caption_candidate":"(DSC), a well-established metric for measuring the spatial overlap of two objects.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252103-p14-t0","doc_id":"K252103","page_num":14,"bbox":[72.28,496.15,539.84,629.74],"n_rows":7,"n_cols":15,"columns":["","Model","","","Testing Dataset","","","Training","","","Tuning","","","Testing",""],"rows":[["","Model","","","Testing Dataset","","","Training","","","Tuning","","","Testing",""],["Vertebral\n(T1-T12, L1-L5)","","","In-House\n(Mighty Oak Medical)","","","147","","","55","","","35","",""],["","","","VERSE ‘20","","","0","","","0","","","36","",""],["","","","Total","","","147","","","55","","","71","",""],["Sacral","","","In-House\n(Mighty Oak Medical)","","","104","","","47","","","40","",""],["","","","CTPelvic1K","","","100","","","55","","","0","",""],["","","","Total","","","204","","","102","","","40","",""]],"caption_candidate":"and testing for each model is provided in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252105-p7-t0","doc_id":"K252105","page_num":7,"bbox":[71.27,122.58,531.63,519.43],"n_rows":13,"n_cols":3,"columns":["Attribute","Predicate Device: K210791","Subject Device"],"rows":[["Attribute","Predicate Device: K210791","Subject Device"],["Product Code","QIH","QIH"],["Regulation","892.2050","892.2050"],["Classification","II","II"],["Rx/OTC","Rx","Rx"],["Physical\nCharacteristics","Software package that operates\nutilizing off-the-shelf hardware","Software package that\noperates utilizing off-the-\nshelf hardware"],["User interface","The software is designed for use\non a personal computer that has\nreceived images from a\ncompatible PACS","The software is designed for\nuse on a personal computer\nthat has received images from\na compatible PACS"],["Automation\nlevel","Fully automated, including clip\nselection","Fully automated, including clip\nselection"],["User\nconfirmation /\nrejection of\nresult","Yes","Yes"],["Manual editing\nof automated\nresult by user","Yes","Yes"],["Input Data","Echocardiographic images","Echocardiographic images"],["Communicatio\nn protocol","DICOM Standard Compliance","DICOM Standard\nCompliance"],["Patient\nPopulations","Adults","Adults"]],"caption_candidate":"PREDICATE DEVICE (21 CFR 807.92(a)(5) & 21 CFR 807.92(a)(6))","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252105-p8-t0","doc_id":"K252105","page_num":8,"bbox":[72.62,477.45,533.37,718.5],"n_rows":9,"n_cols":2,"columns":["Participants characteristics",""],"rows":[["Participants characteristics",""],["Age, years","49.48 ± 13.56"],["Male, n (%)","319 (60.88%)"],["Female, n (%)","205 (39.12%)"],["Height, cm","173.36 ± 10.52"],["Weight, kg","88.92 ± 21.11"],["LVEF, %","34.45% ± 15.78%"],["Normal LVEF (>50%), n (%)","120 (22.90%)"],["Reduced LVEF (<50%), n (%)","404 (77.10%)"]],"caption_candidate":"characteristics of the cohort are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252105-p9-t0","doc_id":"K252105","page_num":9,"bbox":[72.25,85.31,531.63,190.5],"n_rows":4,"n_cols":2,"columns":["Participants characteristics",""],"rows":[["Participants characteristics",""],["Mildly reduced LVEF (40-50%), n (%)","64 (12.21%)"],["Moderately reduced LVEF (30-40%), n (%)","85 (16.22%)"],["Severely reduced LVEF (<30%), n (%)","255 (48.66%)"]],"caption_candidate":"Page 5 of 5","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p5-t0","doc_id":"K252148","page_num":5,"bbox":[71.5,508.5,539.5,714.5],"n_rows":7,"n_cols":3,"columns":["Classification Name(s)","Regulation Number","Product\nCode"],"rows":[["Classification Name(s)","Regulation Number","Product\nCode"],["Primary","",""],["Ultrasonic Pulsed Doppler Imaging System","21 CFR 892.1550","IYN"],["Secondary","",""],["Ultrasonic Pulsed Echo Imaging System","21 CFR 892.1560","IYO"],["Diagnostic Ultrasound Transducer","21 CFR 892.1570","ITX"],["Medical Image Management and Processing\nSystem","21 CFR 892.2050","QIH"]],"caption_candidate":"Regulation Description:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p6-t0","doc_id":"K252148","page_num":6,"bbox":[72.5,96.5,542.5,204.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","Butterfly iQ3 Ultrasound System"],"rows":[["Device Trade Name:","Butterfly iQ3 Ultrasound System"],["510(k) Number:","K232808"],["Submitter:","Butterfly Network, Inc."],["Classification Name:","Ultrasonic Pulsed Doppler Imaging System"],["Primary Product Code:","IYN – 21 CFR 892.1550"],["Secondary Product Code(s):","IYO – 21 CFR 892.1560\nITX – 21 CFR 892.1570\nQIH – 21 CFR 892.2050"]],"caption_candidate":"Primary Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p6-t1","doc_id":"K252148","page_num":6,"bbox":[72.5,253.5,542.5,349.5],"n_rows":6,"n_cols":2,"columns":["Device Trade Name:","Voluson Expert Series"],"rows":[["Device Trade Name:","Voluson Expert Series"],["510(k) Number:","K231965"],["Submitter:","GE Healthcare"],["Classification Name:","Ultrasonic Pulsed Doppler Imaging System"],["Primary Product Code:","IYN – 21 CFR 892.1550"],["Secondary Product Code(s):","IYO – 21 CFR 892.1560\nITX – 21 CFR 892.1570"]],"caption_candidate":"Reference Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p8-t0","doc_id":"K252148","page_num":8,"bbox":[71.5,71.5,539.5,506.5],"n_rows":8,"n_cols":2,"columns":["IEC 60601-1-11 Ed.\n2.1 b:2020","Medical electrical equipment - Part 1-11: General requirements\nfor basic safety and essential performance - Collateral Standard:\nRequirements for medical electrical equipment and medical\nelectrical systems used in the home healthcare environment\nCONSOLIDATED EDITION"],"rows":[["IEC 60601-1-11 Ed.\n2.1 b:2020","Medical electrical equipment - Part 1-11: General requirements\nfor basic safety and essential performance - Collateral Standard:\nRequirements for medical electrical equipment and medical\nelectrical systems used in the home healthcare environment\nCONSOLIDATED EDITION"],["IEC 60601-1-12 Ed.\n1.1 b:2020","Medical electrical equipment - Part 1-12: General requirements\nfor basic safety and essential performance - Collateral Standard:\nRequirements for medical electrical equipment and medical\nelectrical systems intended for use in the emergency medical\nservices environment CONSOLIDATED EDITION"],["IEC 60601-2-5 Ed\n3.0 2009-07","Medical electrical equipment - Part 2-5: Particular requirements\nfor the basic safety and essential performance of ultrasonic\nphysiotherapy equipment"],["IEC 60601-2-37 Ed.\n2.0 b: 2007","Medical Electrical Equipment – Part 2-37. Particular\nrequirements for the basic safety and essential performance of\nultrasonic medical diagnostic and monitoring equipment\nCONSOLIDATED EDITION"],["ISO 10993-1","Biological evaluation of medical devices — Part 1: Evaluation\nand testing within a risk management process"],["ISO 10993-5","Biological evaluation of medical devices — Part 5: Tests for in\nvitro cytotoxicity"],["ISO 10993-10","Biological evaluation of medical devices — Part 10: Tests for\nirritation and skin sensitization"],["ISO 14971","Medical devices - Application of risk management to medical\ndevices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p9-t0","doc_id":"K252148","page_num":9,"bbox":[71.89,514.73,528.66,704.5],"n_rows":12,"n_cols":6,"columns":["Site Number","Site 1","Site 2","Site 3","Site 4","Total"],"rows":[["Site Number","Site 1","Site 2","Site 3","Site 4","Total"],["Sample Size (n)","58","14","3","36","111"],["Age (min, max)","(26,\n41)","(25,\n37)","(27,\n30)","(23,\n40)","(23,\n41)"],["BMI","","","","",""],["BMI <25 (total)","5","3","0","5","13"],["BMI 25 to 29.9 (total)","33","6","1","24","64"],["BMI>30 (total)","20","5","2","7","34"],["Ethnicity","","","","",""],["Hispanic","6","2","0","15","23"],["Non-Hispanic","52","12","3","21","88"],["Race","","","","",""],["Asian","0","1","0","4","5"]],"caption_candidate":"Table 1: Subjects demographic information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p10-t0","doc_id":"K252148","page_num":10,"bbox":[71.72,71.5,528.6,231.5],"n_rows":10,"n_cols":6,"columns":["Black or African American","6","7","0","9","22"],"rows":[["Black or African American","6","7","0","9","22"],["Native Hawaiian or Other Pacific\nIslander","0","0","1","0","1"],["White","49","4","2","17","72"],["American Indian or Alaska Native","0","0","0","1","1"],["Other","3","2","0","5","10"],["Clinical Conditions","","","","",""],["Diabetes","0","1","0","0","1"],["Asthma","1","0","1","0","2"],["Other","0","0","0","4","4"],["None","57","13","2","32","104"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p10-t1","doc_id":"K252148","page_num":10,"bbox":[58.5,410.5,542.5,647.5],"n_rows":5,"n_cols":8,"columns":["","","Butterfly Gestational\nAge with iQ+ vs LMP in\ndays","","Biometry Gestational\nAge vs LMP in days","","Butterfly Gestational Age with iQ+ vs\nBiometry Gestational Age in days",""],"rows":[["","","Butterfly Gestational\nAge with iQ+ vs LMP in\ndays","","Biometry Gestational\nAge vs LMP in days","","Butterfly Gestational Age with iQ+ vs\nBiometry Gestational Age in days",""],["GA\nwindow","N","Bias [\n95% CI]","LOA (Lower\n[95% CI] /\nUpper [95%\nCI])","Bias [\n95%\nCI]","LOA (Lower\n[95% CI] /\nUpper [95%\nCI])","Bias [ 95% CI]","LOA (Lower\n[95% CI] / Upper\n[95% CI])"],["Week 16 to\n21 6/7","28","2.64\n[0.84 to\n4.45]","-6.92 [-10.05\nto -3.79] /\n12.20 [9.07 to\n15.33]","1.96\n[0.30\nto\n3.63]","-6.84 [-9.72 to\n-3.96] / 10.77\n[7.89 to 13.65]","0.68 [-0.69 to 2.05]","-6.24 [-8.60 to\n-3.87] / 7.59 [5.23\nto 9.96]"],["Week 22 to\n27 6/7","37","2.27\n[0.55 to\n3.99]","-8.20 [-11.14\nto -5.26] /\n12.74 [9.80 to\n15.68]","3.14\n[1.50\nto\n4.77]","-6.84 [-9.68 to\n-4.00] / 13.11\n[10.27 to\n15.95]","-0.86 [-2.46 to\n0.73]","-10.23 [-12.98 to\n-7.48] / 8.50 [5.75\nto 11.25]"],["Week 28 to\n37 6/7","45","0.51\n[-2.27 to\n3.29]","-18.16 [-22.98\nto -13.34] /\n19.18 [14.36\nto 24.00]","1.84\n[-0.92\nto\n4.61]","-16.70 [-21.49\nto -11.91] /\n20.39 [15.60\nto 25.17]","-1.33 [-3.04 to\n0.37]","-12.47 [-15.41 to\n-9.53] / 9.80 [6.86\nto 12.74]"]],"caption_candidate":"the Butterfly GA Tool with iQ+ against Biometry.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p11-t0","doc_id":"K252148","page_num":11,"bbox":[71.5,100.5,542.5,370.5],"n_rows":5,"n_cols":8,"columns":["","","Butterfly Gestational\nAge with iQ3 vs LMP\nin days","","Biometry Gestational\nAge vs LMP in days","","Butterfly Gestational Age with iQ3 vs\nBiometry Gestational Age in days",""],"rows":[["","","Butterfly Gestational\nAge with iQ3 vs LMP\nin days","","Biometry Gestational\nAge vs LMP in days","","Butterfly Gestational Age with iQ3 vs\nBiometry Gestational Age in days",""],["GA\nwindow","N","Bias\n[95%\nCI]","LOA\n(Lower\n[95% CI] /\nUpper\n[95% CI])","Bias\n[95%\nCI]","LOA\n(Lower\n[95% CI] /\nUpper\n[95% CI])","Bias [ 95% CI]","LOA (Lower\n[95% CI] / Upper\n[95% CI])"],["Week 16 to\n21 6/7","28","-0.50\n[-2.42 to\n1.42]","-10.68\n[-14.02 to\n-7.35] /\n9.68 [6.35\nto 13.02]","1.96\n[0.30 to\n3.63]","-6.84 [-9.72\nto -3.96] /\n10.77 [7.89\nto 13.65]","-2.46 [-3.66 to\n-1.27]","-8.49 [-10.55 to\n-6.43] / 3.56 [1.50\nto 5.62]"],["Week 22 to\n27 6/7","38","0.61\n[-0.93 to\n2.14]","-8.84\n[-11.49 to\n-6.19] /\n10.05 [7.40\nto 12.70]","3.08\n[1.48 to\n4.68]","-6.78 [-9.55\nto -4.01] /\n12.94 [10.17\nto 15.71]","-2.47 [-4.04 to\n-0.90]","-11.84 [-14.55 to\n-9.13] / 6.90 [4.19\nto 9.60]"],["Week 28 to\n37 6/7","45","-3.09\n[-5.61 to\n-0.56]","-20.03\n[-24.40 to\n-15.65] /\n13.85 [9.48\nto 18.22]","1.84\n[-0.92 to\n4.61]","-16.70\n[-21.49 to\n-11.91] /\n20.39 [15.60\nto 25.17]","-4.93 [-6.40 to\n-3.46]","-14.52 [-17.05 to\n-11.99] / 4.65 [2.12\nto 7.18]"]],"caption_candidate":"the Butterfly GA Tool with iQ3 against Biometry.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252148-p12-t0","doc_id":"K252148","page_num":12,"bbox":[71.92,71.3,527.87,706.5],"n_rows":12,"n_cols":4,"columns":["Model","Butterfly\nGestational Age\nTool (Subject\nDevice)","Butterfly iQ3\nUltrasound\nSystem\n(K232808,\nPredicate\nDevice)","Comparison"],"rows":[["Model","Butterfly\nGestational Age\nTool (Subject\nDevice)","Butterfly iQ3\nUltrasound\nSystem\n(K232808,\nPredicate\nDevice)","Comparison"],["Regulatory Information","","",""],["Regulation Number","892.1550","892.1550","Remains\nUnchanged"],["Device Classification\nName","Ultrasonic Pulsed\nDoppler Imaging\nSystem","Ultrasonic Pulsed\nDoppler Imaging\nSystem","Remains\nUnchanged"],["Classification","Class II","Class II","Remains\nUnchanged"],["Product Codes","IYN\nIYO\nITX\nQIH","IYN\nIYO\nITX\nQIH","Remains\nUnchanged"],["Intended Use","","",""],["Intended for use by\nqualified and trained\nhealthcare\nprofessionals to enable\ndiagnostic ultrasound\nimaging and\nmeasurement of\nanatomical structures\nand fluids of adult and\npediatric patients.","✔","✔","Remains\nUnchanged"],["General Device Description/Hardware","","",""],["Hand-held portable\ndiagnostic ultrasound\nsystem.","✔","✔","Remains\nUnchanged"],["Software Features","","",""],["Gestational Age Tool","✔","-","New feature -\nsimilar feature to\nmanual biometry\ncalculation on the\npredicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252188-p5-t0","doc_id":"K252188","page_num":5,"bbox":[56.34,160.7,373.27,607.29],"n_rows":48,"n_cols":4,"columns":["I.","SUBMITTER","","Elekta Solutions AB"],"rows":[["I.","SUBMITTER","","Elekta Solutions AB"],["","","","Hagaplan 4 Box"],["","","","7593 Stockholm,"],["","","",""],["","","","ZIP 113 68"],["","","",""],["","","","Sweden"],["","","",""],["","Contact:","","Lorenzo Muratori"],["","","","Lorenzo.Muratori@ele"],["","","","kta.com"],["","","",""],["","Establishment Registration #:","","3015232217"],["","","",""],["","510(k) Number:","","K252188"],["","","",""],["","Date Prepared:","","11 July 2025"],["","","",""],["II.","DEVICE","",""],["","","",""],["","Trade Name:","","EMLA (Elekta Evo);"],["","","",""],["","","","EMLA (VersaHD);"],["","","",""],["","","","EMLA (Elekta Harmon"],["","","",""],["","","","EMLA (Elekta Infintiy);"],["","","",""],["","","","EMLA (Elekta Harmon"],["","","",""],["","","","EMLA (Elekta Synergy"],["","","",""],["","Product Classification:","","Class II"],["","","",""],["","Common Name:","","Medical charged-partic"],["","","",""],["","Regulation Number:","","21 CFR § 892.5050"],["","","",""],["","Classification name:","","Accelerator, Linear, M"],["","","",""],["","Product Code:","","IYE"],["","","",""],["III.","PREDICATE DEVICE","",""],["","","",""],["","Predicate Device #:","","K210500"],["","","",""],["","Predicate Trade Name:","","Elekta Synergy, Elekta"],["","","","Versa HD"]],"caption_candidate":"I. SUBMITTER","well_formed":true,"extraction_settings":"text"}
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{"table_id":"K252188-p10-t0","doc_id":"K252188","page_num":10,"bbox":[19.09,71.56,826.37,519.37],"n_rows":32,"n_cols":13,"columns":["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],"rows":[["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],["","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Versa HD","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Elekta\nHarmony Pro","Versa HD","Elekta Evo","",""],["","","","","","","","","","","","","The other models: the subject devices have the"],["","","","","","","","","","","","","same characteristics as the predicate"],["Beam shaping","","","","","","","","","","","","The MLC forms the end of the gantry arm that"],["(MLC – Multi","","","","","","","","","","","","rotates around the treatment area of the"],["Leaves Collimator)","","","","","","","","","","","","patient and modifies the beam shape in"],["","","","","","","","","","","","","accordance with the predefined treatment plan to"],["","","","","","","","","","","","","accurately match the target volume."],["","Agility","","","","","","","","","","",""],["","BLD or","","","","","","","","","","","The predicate device Synergy supports both the"],["","","Agility BLD","","","Agility BLD","","","","","","Same",""],["","MLCi2","","","","","","","","","","","Agility BLD and MLCi2 BLD, while the subject"],["","","","","","","","","","","","",""],["","BLD","","","","","","","","","","","device Synergy supports the Agility BLD. The"],["","","","","","","","","","","","","performance of Agility covers the performance of"],["","","","","","","","","","","","","MLCi2."],["","","","","","","","","","","","",""],["","","","","","","","","","","","","The other models: the subject devices have the"],["","","","","","","","","","","","","same characteristics as the predicate"],["Delivery technique","Conformal Radiation Therapy (CRT) without","","","","","","","","","","",""],["","Image Guided adiation Therapy (IGRT),","","","","Conformal Radiation Therapy (CRT) without Image Guided adiation Therapy (IGRT),","","","","","","",""],["","Intensity-Modulated Radiation Therapy","","","","Intensity-Modulated Radiation Therapy (IMRT) or Volumetric Modulated Arc Therapy","","","","","","",""],["","","","","","","","","","","","","The subject devices have the same"],["","(IMRT) or Volumetric Modulated Arc","","","","(VMAT) delivered using IGRT","","","","","","Same",""],["","","","","","","","","","","","","characteristics as the predicate"],["","Therapy (VMAT) delivered using IGRT","","","","","","","","","","",""],["","","","","","","","","","","","",""],["","","","","","(Common to all models)","","","","","","",""],["","(Common to all models)","","","","","","","","","","",""],["Patient Support\nSystem with a\ncouch top","Precise\nTreatmen\nt Table\n(with\niBEAM®\nevo\nCouchtop\nEP)","4-axis\nTable\n(with\niBEAM®\nevo\nCouchtop\nEH)","Precise\nTreatmen\nt Table\n(with\niBEAM®\nevo\nCouchtop\nEP)","Precise\nTreatmen\nt Table\n(with\niBEAM®\nevo\nCouchtop\nEP)\nor\nPrecise\nTreatmen\nt Table\n(with\nHexaPOD\nevo RT\nSystem)","Precise\nTreatment\nTable\n(with iBEAM®\nevo Couchtop\nEP)","4-axis Table\n(with iBEAM®\nevo Couchtop\nEH)","Precise\nTreatment\nTable\n(with\niBEAM®\nevo\nCouchtop\nEP)","4-axis Table\n(with iBEAM®\nevo Couchtop\nEH)","Precise\nTreatment\nTable\n(with\niBEAM®\nevo\nCouchtop\nEP)\nor\nPrecise\nTreatment\nTable\n(with\nHexaPOD\nevo RT\nSystem)","Precise\nTreatment\nTable\n(with iBEAM®\nevo Couchtop\nEP)\nor\nPrecise\nTreatment\nTable\n(with\nHexaPOD evo\nRT System)","Same","Harmony Pro has the same Patient Support\nSystem with couch top as Harmony.\nElekta Evo has one of the two Patient Support\nSystem with couch top of Versa HD, i.e.\nHexaPOD evo RT System, which has the\nhighest performance.\nThe other models: the subject devices have the\nsame characteristics as the predicate"],["MV Imaging","The iViewGT™ imaging system is an","","","","The iViewGT™ imaging system is an Electronic Portal Imaging Device (EPID).","","","","","","Same","It provides the MV IGRT solution that uses the"]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252188-p11-t0","doc_id":"K252188","page_num":11,"bbox":[18.88,71.56,826.38,521.29],"n_rows":22,"n_cols":13,"columns":["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],"rows":[["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],["","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Versa HD","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Elekta\nHarmony Pro","Versa HD","Elekta Evo","",""],["device control\nsystem and\nimaging function","Electronic Portal Imaging Device (EPID).\n(Common to all models)","","","","(Common to all models)","","","","","","","X-ray radiation of the digital accelerator and an"],["","","","","","","","","","","","","MV detector panel to capture an image of the"],["","","","","","","","","","","","","patient. The image shows the position of the"],["","","","","","","","","","","","","patient in relation to the radiation beam."],["","","","","","","","","","","","",""],["","","","","","","","","","","","","The imaging function is the same. However, the"],["","","","","","","","","","","","","control system of the subject device has"],["","","","","","","","","","","","","improvements to cybersecurity."],["MV Imaging panel\ndeployment","Retractabl\ne and\nfoldable","Retractabl\ne","Retractabl\ne and\nfoldable","Retractabl\ne and\nfoldable","Retractable\nand foldable","Retractable","Retractable\nand foldable","Retractable","Retractable\nand foldable","Retractable\nand foldable","Identical","Harmony and Harmony Pro imaging panels can"],["","","","","","","","","","","","","not be folded, while maintaining the retractable"],["","","","","","","","","","","","","functionality."],["KV Imaging device\ncontrol system\nand imaging\nfunctions","The XVI imaging system is an electronic\nimaging device for kV image acquisition.\n(Common to all models)","","","","The XVI imaging system is an electronic\nimaging device for kV image acquisition.\n(Common to all models. Image quality\nimproved)","","","The XVI imaging system is an electronic\nimaging device for kV image acquisition.\n(Common to all models. Image quality\nimproved.\nA CBCT High Definition (HD) reconstruction\nsolution with further improved CBCT image\nquality is available in the pelvic anatomies,\ncommercially referenced as Iris)","","","Difference","The control system of the subject devices has\nimprovements to cybersecurity.\nThe volume reconstruction function of all the\nsubject devices has been improved.\nThe volume reconstruction method used in the\npredicate devices (based on the reconstruction\nalgorithm Feldkamp-Davis-Kress (FDK)) has\nbeen improved and adopted by all the subject\ndevices. This results in improved image quality.\nThe subject devices Versa HD, Elekta Harmony\nPro and Elekta Evo also support a new CBCT\nreconstruction method with further improved\nimage quality in the pelvic anatomies. It includes\nan AI-ML based component to estimate the\nscatter to enable its automatic removal from the\nprojection images acquired by the imager ahead\nof the volume reconstruction."],["KV Imaging panel\ndeployment","Retractabl\ne and\nfoldable","Retractabl\ne","Retractabl\ne and\nfoldable","Retractabl\ne and\nfoldable","Retractable\nand foldable","Retractable","Retractable\nand foldable","Retractable","Retractable\nand foldable","Retractable\nand foldable","Identical","Harmony and Harmony Pro imaging panels can\nnot be folded, while maintaining the retractable\nfunctionality."],["Beam Gating\ninterface to\nexternal Patient\nPositioning\nMonitoring\nSystems","","","","","","","","","","","","The predicate devices use the Elekta"],["","","","","","","","","","","","","Response, which is a proprietary interface."],["","","","","","","","","","","","",""],["","Elekta Response","","","","Elekta Integrated Beam Gating interface","","","","","","Difference","The subject devices use the Integrated gating"],["","","","","","","","","","","","","interface, which has been designed to comply"],["","","","","","","","","","","","","with the IEC60601-2-1:2020 standard and is"],["","","","","","","","","","","","","based on the NEMA RT 1-2014 standard."]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252188-p12-t0","doc_id":"K252188","page_num":12,"bbox":[18.86,71.56,826.64,164.77],"n_rows":6,"n_cols":13,"columns":["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],"rows":[["Technological\ncharacteristic","Predicate Device (K210500)","","","","Subject Device","","","","","","Same/Different","Summary of technological characteristic/\nSummary of comparison"],["","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Versa HD","Elekta\nSynergy","Elekta\nHarmony","Elekta\nInfinity","Elekta\nHarmony Pro","Versa HD","Elekta Evo","",""],["","","","","","","","","","","","","However, there are a few discrepancies"],["","","","","","","","","","","","","between the two standards and in such cases"],["","","","","","","","","","","","","the requirements of the IEC60601-2-1 standard"],["","","","","","","","","","","","","take precedence."]],"caption_candidate":"510(K) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252188-p13-t0","doc_id":"K252188","page_num":13,"bbox":[79.08,226.84,533.94,735.44],"n_rows":17,"n_cols":2,"columns":["Standards",""],"rows":[["Standards",""],["Standard No.","Standard Title"],["ANSI AMI ES60601-\n1:2005/(R)2012 and\nA1:2012","Medical electrical equipment - Part 1: General requirements for basic\nsafety and essential performance"],["IEC 60601-2-1 Edition\n4.0 2020-10","Medical electrical equipment - Part 2-1: Particular requirements for the\nsafety of electron accelerators in the range of 1 MeV to 50 MeV"],["IEC 60601-2-68\nEdition 1.0 2014-09","Medical electrical equipment - Part 2-68: Particular requirements for the\nbasic safety and essential performance of X-ray-based image-guided\nradiotherapy equipment for use with electron accelerators, light ion beam\ntherapy equipment and radionuclide beam therapy equipment"],["IEC 60601-1-3 (to the\nextent required\nnormatively by the\nIEC 60601-2-68)","Medical electrical equipment - Part 1-3: General requirements for basic\nsafety and essential performance - Collateral Standard: Radiation\nprotection in diagnostic X-ray equipment"],["IEC 61217:2011-12\nEdition 2.0","Radiotherapy equipment - Coordinates, movements and scales"],["IEC 60976:2007-10\nEdition 2.0","Medical electrical equipment. Medical electron accelerators. Functional\nperformance characteristics"],["IEC 60601-1-2:2014\nincluding AM1:2021","Medical electrical equipment - Part 1-2: General requirements for basic\nsafety and essential performance - Collateral Standard: Electromagnetic"],["ISO 14971:2019-12","Medical devices - Application of risk management to medical devices"],["IEC 60601-1-6 Edition\n3.1 2013-10","Medical electrical equipment - Part 1-6: General requirements for basic\nsafety and essential performance - Collateral standard: Usability"],["IEC 62366-1 Edition\n1.0 2015-02","Medical devices - Application of usability engineering to medical devices"],["IEC 62304:2006 /\nA1:2016","Medical device software - Software life-cycle processes"],["ISO 20417:2021-04\n1.0 Edition","Medical devices - Information to be supplied by the manufacturer"],["ISO 15223-1:2021-07\n4.0 Edition","Medical devices - Symbols to be used with information to be supplied by\nthe manufacturer - Part 1: General requirements"],["CR 34971:2022","Guidance on the Application of ISO 14971 to Artificial Intelligence and\nMachine Learning"],["ISO 10993-1:2018-08\n5th Edition","Biological evaluation of medical devices - Part 1: Evaluation and testing\nwithin a risk management process"]],"caption_candidate":"measures.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p5-t0","doc_id":"K252217","page_num":5,"bbox":[108.21,214.2,539.79,504.01],"n_rows":19,"n_cols":5,"columns":["Applicant Name","Canon Medical Informatics, Inc.","","",""],"rows":[["Applicant Name","Canon Medical Informatics, Inc.","","",""],["Applicant Address","","5850 Opus Parkway, Suite 300","",""],["","","Minnetonka MN 55343","",""],["","","United States of America","",""],["Applicant and\nCorrespondent","Jay Vaishnav, PhD, RAC, FRAPS\nDirector, Regulatory Affairs\nPhone 952-487-9530\nE-mail Jay.Vaishnav@mi.medical.canon","","",""],["Alternate Contacts","","Vincent Swenson","",""],["","","Senior Director, Quality and Regulatory","",""],["","","Phone 952-487-9548","",""],["","","E-mail Vincent.Swenson@mi.medical.canon","",""],["","","","",""],["","","Gargeyi Pavuluri","",""],["","","Senior Regulatory Affairs Specialist","",""],["","","Phone","952-487-9875",""],["","","E-mail Gargeyi.Pavuluri@mi.medical.canon","",""],["","","","",""],["","","Alisha Bouley","",""],["","","Associate Regulatory Affairs Specialist","",""],["","","Phone","952-487-9530",""],["","","E-mail Alisha.Bouley@mi.medical.canon","",""]],"caption_candidate":"Contact Details 21 CFR 807.92(a)(1)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p5-t1","doc_id":"K252217","page_num":5,"bbox":[108.21,567.66,539.79,695.1],"n_rows":5,"n_cols":2,"columns":["Device Trade Name","CT VScore+"],"rows":[["Device Trade Name","CT VScore+"],["Classification Name","Computed tomography x-ray system"],["Common Name","System, X-Ray, Tomography, Computed"],["Regulation Number","21 CFR 892.1750"],["Product Code(s)","JAK"]],"caption_candidate":"Device Name 21 CFR 807.92(a)(2)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p6-t0","doc_id":"K252217","page_num":6,"bbox":[108.29,134.88,539.71,173.26],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate Trade Name","Product Code"],"rows":[["Predicate #","Predicate Trade Name","Product Code"],["K213725","GE CardIQ Suite","JAK"]],"caption_candidate":"Legally Marketed Predicate Device 21 CFR 807.92(a)(3)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p8-t0","doc_id":"K252217","page_num":8,"bbox":[108.48,233.58,540.24,655.74],"n_rows":2,"n_cols":4,"columns":["Characteristic","Subject Device (CT VScore+)","Predicate Device (CardIQ\nSuite K213725)","Analysis"],"rows":[["Characteristic","Subject Device (CT VScore+)","Predicate Device (CardIQ\nSuite K213725)","Analysis"],["Indications\nfor Use","CT VScore+ is a software\napplication intended for non-\ninvasive evaluation of calcified\nlesions of the coronary arteries\nbased on ECG-gated, non-\ncontrast cardiac CT images for\npatients aged 30 years or older.\nThe device automatically\ngenerates calcium scores for the\ncoronary arteries (combined\nLM+LAD, RCA, LCX) and\nhighlights the segmented calcium\non the original CT image. The\ndevice also offers the option for\nthe user to display the calcium\nscores in the context of reference\ndata from the MESA and Hoff-\nKondos databases.\nThe segmented arteries include\ncombined LM+LAD, RCA, and\nLCX. To obtain separate LM and\nLAD results, the user must\nperform manual segmentation.\nThe segmentation map of\ncalcifications is intended for\ninformational use only and is not\nintended for detection or\ndiagnostic purposes. The 3D\nCalcium View output is provided\nstrictly as an informational and\nsupplementary output and should\nnever be used alone as the\nmethod of reviewing the calcium\nsegmentation.","CardIQ Suite is a non-invasive\nsoftware application designed to\nprovide an optimized application\nto analyze cardiovascular\nanatomy and pathology based\non 2D or 3D CT cardiac non\ncontrast and angiography\nDICOM data from acquisitions of\nthe heart. It provides capabilities\nfor the visualization and\nmeasurement of vessels and\nvisualization of chamber mobility.\nCardIQ Suite also aids in\ndiagnosis and determination of\ntreatment paths for\ncardiovascular diseases to\ninclude, coronary artery disease,\nfunctional parameters of the\nheart, heart structures and\nfollow-up for stent placement,\nbypasses and plaque imaging.\nCardIQ Suite provides calcium\nscoring, a non-invasive software\napplication, that can be used\nwith non-contrasted cardiac\nimages to evaluate calcified\nplaques in the coronary arteries,\nheart valves and great vessels\nsuch as the aorta. Calcium\nScoring may be used to monitor\nthe progression/regression of\ncalcium in coronary arteries\novertime, which may aid in the\nprognosis of cardiac disease.","The subject device has\na more restrictive IFU\nand includes a subset\nof the predicate\nfunctionality, non-\ninvasive evaluation of\ncalcified lesions of the\ncoronary arteries based\non ECG-gated, non-\ncontrast cardiac CT\nimages for patients\naged 30 years or older.\nThe predicate device\nalso performs other\nfunctions, including\nanalysis of CCTA\nimages. This change in\nthe IFU does not create\na new intended use."]],"caption_candidate":"predicate device and the proposed device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p9-t0","doc_id":"K252217","page_num":9,"bbox":[108.48,99.6,540.24,692.52],"n_rows":7,"n_cols":4,"columns":["Intended Use","The device is intended for use in\nadults aged 30 years and older. It\nautomatically generates calcium\nscores for the coronary arteries\nand highlights the segmented\ncalcifications on the original CT\nimages. The intended use is to\nquantify coronary artery calcium\nfrom ECG-gated, non-contrast\ncardiac CT images to support\nclinical interpretation of\nc ardiovascular risk.","CardIQ Suite is a collection of\nnon-invasive software features\nintended to analyze CT\ncardiovascular anatomy and\npathology and aid in determining\ntreatment paths.","Subject device has a\nmore restrictive IFU,\nsubset of predicate\nfunctionality. No new\nintended use."],"rows":[["Intended Use","The device is intended for use in\nadults aged 30 years and older. It\nautomatically generates calcium\nscores for the coronary arteries\nand highlights the segmented\ncalcifications on the original CT\nimages. The intended use is to\nquantify coronary artery calcium\nfrom ECG-gated, non-contrast\ncardiac CT images to support\nclinical interpretation of\nc ardiovascular risk.","CardIQ Suite is a collection of\nnon-invasive software features\nintended to analyze CT\ncardiovascular anatomy and\npathology and aid in determining\ntreatment paths.","Subject device has a\nmore restrictive IFU,\nsubset of predicate\nfunctionality. No new\nintended use."],["Device Input","Non-contrast, ECG-gated cardiac\nCT scans","Non-contrast, ECG gated cardiac\nCT scans or coronary CT\nangiography images (CCTA)","The subject device\nprocesses noncontrast\ncardiac CT coronary\nartery calcium (CAC)\nscans only, and does\nnot operate on CCTA\nimages.\nCAC and CCTA scans\nserve different clinical\nfunctions. This does not\nimpact the safety or\neffectiveness of the\nsubject device\ncompared to the\np redicate."],["Device\nOutput","DICOM images with calcium\nhighlighted. Total calcium scores\nas well as per-vessel scores for\nthe LM+LAD, LCX, and RCA","Same","Same"],["Identification\nof calcium","Yes","Same","Same."],["Comparison\nof calcium\nscores to\ncited\nliterature","Yes","Yes","Similar. Both devices\noffer the option for the\nuser to display the\ncalcium scores in the\ncontext of data from\nwell-established\nreference population\ndatabases (MESA;\nHoff-Kondos)."],["Associates\ncalcium with\nartery","Yes","Same","Similar. Both devices\nuse deep learning\nmethods to segment the\ncoronary artery regions."],["Methods","Deep learning methods used to\nsegment coronary regions and\nassign calcium","Same","Exact predicate\nmethods are unknown\nbut likely similar."]],"caption_candidate":"CT VScore+ Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252217-p10-t0","doc_id":"K252217","page_num":10,"bbox":[108.48,99.6,540.24,267.36],"n_rows":4,"n_cols":4,"columns":["Automation","Semi-automatic; Software\ninitializes coronary calcium\nresults.","Same","Same"],"rows":[["Automation","Semi-automatic; Software\ninitializes coronary calcium\nresults.","Same","Same"],["Interactive\ndefinition of\nROIs and\nassignment of\ncalcium","Users can manually edit results,\nincluding manually assigning\ncalcifications to anatomical\nstructures","Same","Same. Both devices\nallow users to manually\nedit calcifications and\nassign them to labeled\nanatomical structures"],["Export as\nDICOM SR","Yes","Same","Same"],["3D Calcium\nView","A 3D rendered image, showing\nan optional supplemental view of\nsegmented calcium in relation to\nfull anatomy.","Not specified","Subject device output is\nsupplementary only and\nshould not be used for\nprimary review."]],"caption_candidate":"CT VScore+ Traditional 510(k) Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252235-p6-t0","doc_id":"K252235","page_num":6,"bbox":[72.17,550.68,523.16,707.41],"n_rows":10,"n_cols":10,"columns":["Feature","","","PVAD IQ Software\n(Subject device)","","","","LVivo Software","","Conclusion"],"rows":[["Feature","","","PVAD IQ Software\n(Subject device)","","","","LVivo Software","","Conclusion"],["","","","","","","","Application","",""],["","","","","","","","(Predicate device)","",""],["","","","","","","","K210053","",""],["Classification\nName","","","","Medical image","","Same","Same","","Identical"],["","","","","management and","","","","",""],["","","","","processing system","","","","",""],["","Regulation Name","","","21 CFR 892.2050","","","Same","",""],["","Product code","","","QIH","","","Same","",""],["","Device Class","","","II","","","Same","",""]],"caption_candidate":"A table comparing the key features of the subject and the predicate devices is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252235-p7-t0","doc_id":"K252235","page_num":7,"bbox":[72.19,87.0,523.12,614.76],"n_rows":34,"n_cols":12,"columns":["Intended Use","","","","Non-invasive","","Same","","","Identical","",""],"rows":[["Intended Use","","","","Non-invasive","","Same","","","Identical","",""],["","","","","processing of","","","","","","",""],["","","","","ultrasound images","","","","","","",""],["Indications for use","","","","The PVAD IQ device is","","LVivo platform is\nintended for non-\ninvasive processing\nof ultrasound images\nto detect, measure,\nand calculate\nrelevant medical\nparameters of\nstructures and\nfunction of patients\nwith suspected\ndisease","","","Similar","",""],["","","","","intended for non-","","","","","","",""],["","","","","invasive analysis of","","","","","","",""],["","","","","ultrasound images to","","","","","","",""],["","","","","detect and measure","","","","","","",""],["","","","","structures from cardiac","","","","","","",""],["","","","","ultrasound of patients","","","","","","",""],["","","","","18 years old and above","","","","","","",""],["","","","","with Percutaneous","","","","","","",""],["","","","","Ventricular Assist","","","","","","",""],["","","","","Devices (PVAD). Such","","","","","","",""],["","","","","use typically utilized for","","","","","","",""],["","","","","clinical decision","","","","","","",""],["","","","","support by a qualified","","","","","","",""],["","","","","physician.","","","","","","",""],["Scan type","","","","Ultrasound (ultrasound","","Same","","","Identical","",""],["","","","","vendor neutral)","","","","","","",""],["Principle of\nOperation and\nTechnology","","","","Ultrasound image","","Same","","","Identical","",""],["","","","","processing software","","","","","","",""],["","","","","implementing non-","","","","","","",""],["","","","","adaptive machine","","","","","","",""],["","","","","learning algorithms","","","","","","",""],["","","","","trained with clinical","","","","","","",""],["","","","","data intended for non-","","","","","","",""],["","","","","invasive analysis of","","","","","","",""],["","","","","ultrasound data","","","","","","",""],["Algorithm","","","","Deep Convolutional","","Same","","","Identical","",""],["","","","","Neural Networks for","","","","","","",""],["","","","","Landmark Detection","","","","","","",""],["","","","","and Classification","","","","","","",""],["","Anatomical site","","","Heart","","","Same","","","Identical",""]],"caption_candidate":"510(k) SUMMARY Page: 3 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252235-p8-t0","doc_id":"K252235","page_num":8,"bbox":[71.81,87.0,523.12,350.27],"n_rows":17,"n_cols":6,"columns":["Main Output","Clinically relevant\nmeasurements of\nknown structure for\nmanagement support\nin cardiac patients.\nMeasurement:\nDistance between the\naortic annulus and the\nPVAD inlet","","Clinically relevant","","Similar output with\ndifferent\nmeasurements"],"rows":[["Main Output","Clinically relevant\nmeasurements of\nknown structure for\nmanagement support\nin cardiac patients.\nMeasurement:\nDistance between the\naortic annulus and the\nPVAD inlet","","Clinically relevant","","Similar output with\ndifferent\nmeasurements"],["","","","measurements of","",""],["","","","known structure for","",""],["","","","management","",""],["","","","support in cardiac","",""],["","","","patients.","",""],["","","","","",""],["","","","Measurement:","",""],["","","","Left ventricular","",""],["","","","ejection fraction","",""],["","","","(LVEF), global","",""],["","","","Longitudinal Strain","",""],["","","","Measure, Segmental","",""],["","","","Longitudinal Strain","",""],["","","","Measure, and","",""],["","","","Segmental wall","",""],["","","","motion evaluation","",""]],"caption_candidate":"510(k) SUMMARY Page: 4 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252235-p9-t0","doc_id":"K252235","page_num":9,"bbox":[71.84,519.6,561.6,718.08],"n_rows":2,"n_cols":3,"columns":["Modification","Description","Testing Method"],"rows":[["Modification","Description","Testing Method"],["Re-training","Model retraining for enhanced output\naccuracy and MLM performance,\nrefining annotations, and bounded\narchitecture optimization, to enhance\nrobustness, generalizability, and\nperformance, as part of the device\nlife cycle management.\nNo changes to device input or output","Verification testing will assess non-\nclinical performance using the\nestablished acceptance criteria. The\nevaluation includes distance\nmeasurement between the aortic\nannulus and the PVAD inlet, clip\nacceptability classification, inlet and\naortic-annulus visibility, and inlet and\naortic-annulus landmark position.\nThese metrics will be tested using the\nsame methods and thresholds defined"]],"caption_candidate":"ensure substantial equivalence of the device after the modification.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252235-p10-t0","doc_id":"K252235","page_num":10,"bbox":[71.94,86.88,561.6,716.16],"n_rows":3,"n_cols":3,"columns":["","","for the authorized device to confirm\nthat retraining maintains performance\nwithin the validated boundaries.\nSoftware testing: Per FDA’s Guidance\n“Content of Premarket Submissions for\nDevice Software Function”\nCybersecurity testing: Per FDA’s\nGuidance “Cybersecurity in Medical\nDevices: Quality System\nConsiderations and Content of\nPremarket Submissions”."],"rows":[["","","for the authorized device to confirm\nthat retraining maintains performance\nwithin the validated boundaries.\nSoftware testing: Per FDA’s Guidance\n“Content of Premarket Submissions for\nDevice Software Function”\nCybersecurity testing: Per FDA’s\nGuidance “Cybersecurity in Medical\nDevices: Quality System\nConsiderations and Content of\nPremarket Submissions”."],["Additional\nPVAD Devices","MLM will include datasets with\nPercutaneous Ventricular Assist\nDevices, that were not previously tested\nwith the authorized device, in order to\nexpand the use of the PVAD IQ software.\nThe additional PVAD devices should be\nFDA approved, indicated to support the\nleft ventricle, and within the device\npatient population.","Verification testing will assess non-\nclinical performance using the\nestablished acceptance criteria. The\nevaluation includes distance\nmeasurement between the aortic\nannulus and the PVAD inlet, clip\nacceptability classification, inlet and\naortic-annulus visibility, and inlet and\naortic-annulus landmark position.\nThese metrics will confirm that adding\nnew PVAD devices maintains\nperformance within the established\nboundaries.\nSoftware testing: Per FDA’s Guidance\n“Content of Premarket Submissions for\nDevice Software Function”\nCybersecurity testing: Per FDA’s\nGuidance “Cybersecurity in Medical\nDevices: Quality System\nConsiderations and Content of\nPremarket Submissions”."],["Additional\nUltrasound\nViews","MLM will include datasets from other\ncardiac ultrasound views (AP3, AP5, and\nSubcostal LVOT), allowing healthcare","Verification testing will assess non-\nclinical performance using the\nestablished acceptance criteria. The\nevaluation includes distance"]],"caption_candidate":"510(k) SUMMARY Page: 6 of 7","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252261-p6-t0","doc_id":"K252261","page_num":6,"bbox":[71.31,551.52,540.59,691.92],"n_rows":8,"n_cols":4,"columns":["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],"rows":[["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],["","","Multi-Modality Tumor",""],["","","Tracking (MMTT)",""],["","","application",""],["Application\nNumber","K252261","K162955","-"],["Product Code","QIH","LLZ","-"],["Class","Class II","Class II","Same"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same"]],"caption_candidate":"The subject device is substantially equivalent to the predicate device in the following ways:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252261-p7-t0","doc_id":"K252261","page_num":7,"bbox":[71.31,72.36,540.59,709.56],"n_rows":8,"n_cols":4,"columns":["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],"rows":[["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],["","","Multi-Modality Tumor",""],["","","Tracking (MMTT)",""],["","","application",""],["Indications for\nUse/ Intended use","InferCare RECIST is a post-\nprocessing software\napplication used to display,\nprocess, analyze, quantify\nand manipulate multi-time-\npoint CT images. It is\nintended to be used by\ntrained medical\nprofessionals in evaluating\nand managing tumors in\nvarious organs, tissues, and\nother anatomical structures\nbased on RECIST criteria.\nInferCare RECIST offers\nfunctionalities for lesion\nmeasurement, registration,\ntracking, and RECIST\nreport. It provides tools for\ninteractive segmentation,\nand 3D reconstruction\nvisualization.\nThe software utilizes\nartificial intelligence\nalgorithms for automated\nlesion segmentation and\nregistration, and the results\nrequire confirmation by a\nmedical professional. The\nsoftware's artificial\nintelligence algorithms are\nintended for patients aged 21\nyears and older.","Multi-Modality Tumor\nTracking (MMTT)\napplication is a post\nprocessing software\napplication used to display,\nprocess, analyze, quantify\nand manipulate anatomical\nand functional images, for\nCT, MR PET/CT and\nSPECT/CT images and/or\nmultiple time-points. The\nMMTT application is\nintended for use on tumors\nwhich are known/confirmed\nto be pathologically\ndiagnosed cancer. The results\nobtained may be used as a\ntool by clinicians in\ndetermining the diagnosis of\npatient disease conditions in\nvarious organs, tissues, and\nother anatomical structures.","Same. Both\ndevices are\nused for\nmedical image\nprocessing to\ndisplay,\nprocess,\nanalyze,\nquantify,\nmanipulate\nmulti-time-\npoint images\nand enable\nRECIST 1.1\ncategorization."],["Intended Users","Radiologists, oncologists,\nand others trained in reading\nmedical images and\napplying RECIST criteria","Radiologists, Technologist","Same"],["Where used","Healthcare facilities such as\nhospitals and clinics","Healthcare facilities such as\nhospitals and clinics","Same"],["Image Input","CT DICOM images","CT, MR, PET/CT and\nSPECT/CT DICOM images","Similar. The\npredicate\ndevice includes\na wider variety"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252261-p8-t0","doc_id":"K252261","page_num":8,"bbox":[71.17,72.36,540.72,505.56],"n_rows":14,"n_cols":4,"columns":["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],"rows":[["Item","Subject Device:\nInferCare RECIST","Predicate Device:","Comparison"],["","","Multi-Modality Tumor",""],["","","Tracking (MMTT)",""],["","","application",""],["","","","of imaging\nmodalities."],["2D DICOM\nviewing","Yes","Yes","Same"],["3D\nReconstruction","Automatic","Automatic","Same"],["Multi-Planar\nReconstructions\n(MPR)","Yes","Yes","Same"],["Registration","Automatic and manual","Automatic and manual","Same"],["Lesion\nsegmentation","Semi-automatic and manual","Semi-automatic and manual","Same"],["Segmentation\nediting tools","Add, Delete, Edit, Undo","Add, Delete, Edit, Undo","Same"],["Automatic\nsoftware\nmeasurement of\nsegmented lesion","Long axis, short axis,\nvolume, key slice.","Long axis, short axis,\nvolume, key slice, density,\netc.","Same"],["RECIST Report","Yes","Yes","Same"],["Algorithm\ncharacteristics","Artificial Intelligence (AI)\nalgorithm","Traditional algorithm","The algorithm\nperformance of\nthe subject\ndevice has been\nvalidated\nthrough\nperformance\ntesting."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252261-p9-t0","doc_id":"K252261","page_num":9,"bbox":[126.63,579.58,485.37,703.2],"n_rows":7,"n_cols":18,"columns":["","","","","","","","Primary endpoint","","","","","","Secondary endpoint","","","",""],"rows":[["","","","","","","","Primary endpoint","","","","","","Secondary endpoint","","","",""],["","","","","","","","Segmentation Accuracy","","","","","","Long/Short Diameter","","","",""],["","Item","","","N","","","Mean (Dice)","","","95% CI","","","MAE (%)","","","95% CI",""],["Lung nodule","","","42","","","0.913","","","0.895-0.932","","","3.2","","","2.2-4.2","",""],["Liver lesion","","","23","","","0.929","","","0.913-0.944","","","4.3","","","3.1-5.5","",""],["Kidney lesion","","","23","","","0.904","","","0.889-0.918","","","4.5","","","3.3-5.6","",""],["Lymph node","","","14","","","0.782","","","0.750-0.814","","","5.3","","","3.0-7.6","",""]],"caption_candidate":"node lesions. The result is listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p5-t0","doc_id":"K252294","page_num":5,"bbox":[67.5,118.5,485.5,288.5],"n_rows":7,"n_cols":2,"columns":["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],"rows":[["Applicant:","BrightHeart\n7-11 boulevard Haussmann\nParis 75009, France"],["",""],["Contact:","Christophe Gardella\nChief Technical Officer\nTel. +0033686543950\nEmail. christophe@brightheart.fr"],["",""],["Submission Correspondent:","Christophe Gardella"],["",""],["Date Prepared:","December 8, 2025"]],"caption_candidate":"UBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p5-t1","doc_id":"K252294","page_num":5,"bbox":[67.5,335.5,489.5,436.5],"n_rows":5,"n_cols":2,"columns":["Device Trade Name:","Fetal EchoScan (v1.2)"],"rows":[["Device Trade Name:","Fetal EchoScan (v1.2)"],["Device Common Name:","Medical image analyzer"],["Classification Name","Radiological computer-assisted diagnostic software for\nlesions suspicious for cancer 21 CFR 892.2060"],["Regulatory Class:","Class II"],["Product Code:","POK"]],"caption_candidate":"EVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p6-t0","doc_id":"K252294","page_num":6,"bbox":[66.25,541.87,545.37,704.5],"n_rows":8,"n_cols":3,"columns":["","Subject Device\nFetal EchoScan v1.2","Predicate Device\nFetal EchoScan v1.1"],"rows":[["","Subject Device\nFetal EchoScan v1.2","Predicate Device\nFetal EchoScan v1.1"],["510(k) Number","K252294","K242342"],["Applicant","BrightHeart","BrightHeart"],["Classification Regulation","892.2060","892.2060"],["Product Code","POK","POK"],["Device Type","SaMD","SaMD"],["Software algorithm","Machine Learning Model","Machine Learning Model"],["Imaging Modality","Fetal Ultrasound","Fetal Ultrasound"]],"caption_candidate":"Table 1. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p7-t0","doc_id":"K252294","page_num":7,"bbox":[66.33,72.13,545.42,675.5],"n_rows":6,"n_cols":3,"columns":["","Subject Device\nFetal EchoScan v1.2","Predicate Device\nFetal EchoScan v1.1"],"rows":[["","Subject Device\nFetal EchoScan v1.2","Predicate Device\nFetal EchoScan v1.1"],["Model Inputs","Fetal ultrasound studies containing\nthe following views in recordings: 4\nchamber, left ventricular outflow\ntract, right ventricular outflow tract","Fetal ultrasound recordings\ncontaining the following views: 4\nchamber, left ventricular outflow\ntract, right ventricular outflow tract"],["Model method","Suspicious radiographic findings\ncategorized into 2 groups:\n● “classification” features are\nbased on the identification of\nmorphological features within\nthe video clip.\n● “measurement” features are\nbased on the detection and\nsegmentation of key anatomic\npoints","Suspicious radiographic findings\ncategorized into 2 groups:\n● “classification” features are\nbased on the identification of\nmorphological features within\nthe video clip.\n● “measurement” features are\nbased on the detection and\nsegmentation of key anatomic\npoints"],["Model trained to identify","Video clips featuring the fetal heart.\nIdentifiable suspicious radiographic\nfindings of the fetal heart:\n● overriding artery\n● septal defect at the cardiac crux\n● abnormal relationship of the\noutflow tracts\n● enlarged cardiothoracic ratio\n● right ventricular to left\nventricular size discrepancy\n● tricuspid valve to mitral valve\nannular size discrepancy\n● pulmonary valve to aortic valve\nannular size discrepancy\n● cardiac axis deviation","Identifiable suspicious radiographic\nfindings of the fetal heart\n● overriding artery\n● septal defect at the cardiac crux\n● abnormal relationship of the\noutflow tracts\n● enlarged cardiothoracic ratio\n● right ventricular to left\nventricular size discrepancy\n● tricuspid valve to mitral valve\nannular size discrepancy\n● pulmonary valve to aortic valve\nannular size discrepancy\n● cardiac axis deviation"],["Model Output","For each frame the software\nevaluates whether the findings are:\npresent, absent, or inconclusive.\nAn “exam summary table” displays\na summary of the results for the\noverall study.","For each frame the software\nevaluates whether the findings are:\npresent, absent, or inconclusive.\nA “record summary table” displays\na summary of results for each video\nclip. An “exam summary table”\ndisplays a summary of the results for\nthe overall study."],["Output Display","● Annotated DICOMs within the\nuser PACS viewer\n● third-party user interface","● Annotated DICOMs within the\nuser PACS viewer\n● Device web interface"]],"caption_candidate":"510(k) Summary - K252294 Page 3 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p9-t0","doc_id":"K252294","page_num":9,"bbox":[70.5,514.81,541.5,718.36],"n_rows":10,"n_cols":5,"columns":["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],"rows":[["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],["","Sensitivity\n(Worst-Case)","Specificity\n(Best-Case)","Sensitivity\n(Best-Case)","Specificity\n(Worst-Case)"],["Any suspicious findings","0.984 (0.963 ; 0.993)","0.970 (0.952 ; 0.981)","0.990 (0.972 ; 0.997)","0.958 (0.938 ; 0.971)"],["Overriding artery","0.933 (0.868 ; 0.967)","0.988 (0.975 ; 0.994)","0.942 (0.880 ; 0.973)","0.979 (0.963 ; 0.988)"],["Cardiac crux septal defect","0.917 (0.838 ; 0.959)","0.995 (0.985 ; 0.998)","0.917 (0.838 ; 0.959)","0.995 (0.985 ; 0.998)"],["Abn. OT relationship","0.869 (0.781 ; 0.925)","0.988 (0.975 ; 0.994)","0.952 (0.884 ; 0.981)","0.982 (0.968 ; 0.990)"],["Enlarged CTR","0.955 (0.876 ; 0.985)","0.996 (0.987 ; 0.999)","0.955 (0.876 ; 0.985)","0.996 (0.987 ; 0.999)"],["Cardiac axis deviation","0.945 (0.851 ; 0.981)","1.000 (0.993 ; 1.000)","0.964 (0.877 ; 0.990)","1.000 (0.993 ; 1.000)"],["PV/AV size discrepancy","0.959 (0.921 ; 0.979)","0.986 (0.972 ; 0.993)","0.959 (0.921 ; 0.979)","0.986 (0.972 ; 0.993)"],["RV/LV size discrepancy","0.950 (0.900 ; 0.975)","1.000 (0.993 ; 1.000)","0.950 (0.900 ; 0.975)","1.000 (0.993 ; 1.000)"]],"caption_candidate":"possibly positive to other findings).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p10-t0","doc_id":"K252294","page_num":10,"bbox":[70.5,72.17,541.5,149.75],"n_rows":3,"n_cols":5,"columns":["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],"rows":[["","Inconclusive Exams\nCounted as Negative","","Inconclusive Exams\nCounted as Positive",""],["","Sensitivity\n(Worst-Case)","Specificity\n(Best-Case)","Sensitivity\n(Best-Case)","Specificity\n(Worst-Case)"],["TV/MV size discrepancy","0.950 (0.904 ; 0.974) 1.000 (0.993 ; 1.000) 0.950 (0.904 ; 0.974) 1.000 (0.993 ; 1.000)","","",""]],"caption_candidate":"510(k) Summary - K252294 Page 6 of 8","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252294-p11-t0","doc_id":"K252294","page_num":11,"bbox":[66.72,292.38,544.5,479.67],"n_rows":11,"n_cols":5,"columns":["","Aided","Unaided","Aided minus Unaided",""],"rows":[["","Aided","Unaided","Aided minus Unaided",""],["","Model Estimate AUC\n(95% CI)","Model Estimate AUC\n(95% CI)","Model Estimate Difference\n(95% CI)","DBM-OR\np-value"],["Any suspicious findings","0.974 (0.957 ; 0.990)\n0.953 (0.916 ; 0.990)\n0.971 (0.943 ; 0.999)\n0.972 (0.953 ; 0.992)\n0.960 (0.930 ; 0.989)\n0.967 (0.932 ; 1.000)\n0.979 (0.962 ; 0.997)\n0.991 (0.983 ; 0.999)\n0.964 (0.938 ; 0.990)","0.825 (0.741 ; 0.908)\n0.803 (0.719 ; 0.888)\n0.857 (0.782 ; 0.933)\n0.832 (0.738 ; 0.927)\n0.746 (0.666 ; 0.826)\n0.786 (0.704 ; 0.867)\n0.839 (0.756 ; 0.921)\n0.868 (0.801 ; 0.936)\n0.850 (0.779 ; 0.921)","0.149 (0.066 ; 0.232) 0.002\n0.150 (0.063 ; 0.237) 0.002\n0.114 (0.042 ; 0.186) 0.004\n0.140 (0.048 ; 0.232) 0.005\n0.214 (0.131 ; 0.297) <0.001\n0.181 (0.106 ; 0.256) <0.001\n0.140 (0.060 ; 0.221) 0.002\n0.123 (0.055 ; 0.190) 0.001\n0.114 (0.048 ; 0.179) 0.002",""],["Overriding artery","","","",""],["Cardiac crux septal defect","","","",""],["Abn. OT relationship","","","",""],["Enlarged CTR","","","",""],["Cardiac axis deviation","","","",""],["PV/AV size discrepancy","","","",""],["RV/LV size discrepancy","","","",""],["TV/MV size discrepancy","","","",""]],"caption_candidate":"analyzed finding but possibly positive to other findings.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p10-t0","doc_id":"K252304","page_num":10,"bbox":[40.26,124.61,751.76,521.5],"n_rows":6,"n_cols":13,"columns":["No.","","","Specification","","","Predicate Device (Primary)","","","Device Under Evaluation","","Equivalency",""],"rows":[["No.","","","Specification","","","Predicate Device (Primary)","","","Device Under Evaluation","","Equivalency",""],["","","","","","","syngo.via RT Image Suite (VB80)","","Syngo.via RT Image Suite VC10","Syngo.via RT Image Suite VC10","","",""],["","","","","","","510(k) Id # K232799","","","","","",""],["","1.0","","","Clinical Characteristics","","","","","","","",""],["1.1","","","Intended Purpose","","Image analysis software for evaluating image\ndata sets and preparing them for further use\nin therapy.","","","Image analysis software for evaluating image\ndata sets and preparing them for further use\nin therapy.","","","Equivalent",""],["1.2","","","Intended Use","","syngo.via RT Image Suite is intended to be\nused by trained medical professionals\nincluding, but not limited to, medical\nphysicists, RT technologists, physicians,\nradiologists, nuclear medicine physicians,\nand radiation oncologists.\nsyngo.via RT Image Suite is a medical\napplication for viewing, manipulation, 3D\nand 4D visualization, and comparison of\nmedical images from multiple imaging\nmodalities. The application enables the\nregistration of images and provides tools to\nhelp the user to identify volumes, regions\nand points of interest inside the patient\nanatomy. The application also enables the\ncreation of simple geometric plans. The\napplication may assist in the preparation of\nfurther radiation therapy treatment\nplanning. The application supports","","","syngo.via RT Image Suite is intended to be\nused by trained medical professionals\nincluding, but not limited to, medical\nphysicists, RT technologists, physicians,\nradiologists, nuclear medicine physicians, and\nradiation oncologists.\nsyngo.via RT Image Suite is a medical\napplication for viewing, manipulation, 3D and\n4D visualization, and comparison of medical\nimages from multiple imaging modalities. The\napplication enables the registration of images\nand provides tools to help the user to identify\nvolumes, regions and points of interest inside\nthe patient anatomy. The application also\nenables the creation of simple geometric\nplans. The application may assist in the\npreparation of further radiation therapy\ntreatment planning. The application supports\nanatomical datasets from CT, MR, CBCT, as","","","Equivalent",""]],"caption_candidate":"Comparison of Subject Device to Predicate Device syngo.via RT Image Suite VC10 and syngo.via RT Image Suite VB80","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p13-t0","doc_id":"K252304","page_num":13,"bbox":[40.2,105.74,751.78,528.34],"n_rows":5,"n_cols":5,"columns":["","","• Visualization and contouring of moving\ntumors and organs\n• Management of points of interest\nincluding but not limited to the isocenter\n• Creation of simple geometric treatment\nplans\n• Generation of a synthetic CT based on\nmultiple pre-define MR acquisitions","• Visualization and contouring of moving\ntumors and organs\n• Management of points of interest including\nbut not limited to the isocenter\n• Creation of simple geometric treatment\nplans\n• Generation of a synthetic CT based on pre-\ndefine MR acquisitions",""],"rows":[["","","• Visualization and contouring of moving\ntumors and organs\n• Management of points of interest\nincluding but not limited to the isocenter\n• Creation of simple geometric treatment\nplans\n• Generation of a synthetic CT based on\nmultiple pre-define MR acquisitions","• Visualization and contouring of moving\ntumors and organs\n• Management of points of interest including\nbut not limited to the isocenter\n• Creation of simple geometric treatment\nplans\n• Generation of a synthetic CT based on pre-\ndefine MR acquisitions",""],["1.4","Clinical condition\nintended to\ndiagnose, treat or\nmanage","Not restricted","Not restricted","Equivalent"],["1.5","Intended patient\npopulation","The intended patient population is not\nsubject to any restrictions. However,\nautomation support provided works best\nwith adult patients.","The intended patient population is not\nsubject to any restrictions. However,\nfunctionality like Auto-Contouring and Lung\nVentilation work best with adult patients.","Substantially\nEquivalent\nminor\ndeviation in\nwording"],["1.6","Contraindications","There are no known specific situations that\ncontraindicate the use of this device.","There are no known specific situations that\ncontraindicate the use of this device.","Equivalent"],["1.7","Operating\nEnvironment","The task is designed to be used embedded in\nthe scanner console or in a workstation next\nto it to perform patient virtual simulation in\nthe radiation therapy context. It can also be\nused in the contouring room or in the\nphysicians' office to perform treatment\npreparation (registration, contouring,","The task is designed to be used embedded in\nthe Reading/Control Room on a scanner\nconsole or in a workstation next to it to\nperform patient virtual simulation in the\nradiation therapy context. It can also be used\nin the Reading Room (contouring room or in\nthe physicians' office) to perform treatment\npreparation (registration, contouring,","Substantially\nEquivalent\nminor\ndeviation in\nwording"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p14-t0","doc_id":"K252304","page_num":14,"bbox":[40.25,105.74,751.76,524.38],"n_rows":10,"n_cols":9,"columns":["","","","","","adaption) or treatment assessment (decision\non treatment strategy).","adaption) or treatment assessment (decision\non treatment strategy).","",""],"rows":[["","","","","","adaption) or treatment assessment (decision\non treatment strategy).","adaption) or treatment assessment (decision\non treatment strategy).","",""],["1.","","","Intended Users","","Trained medical professionals including, but\nnot limited to,\nmedical physicists, RT technologists,\nphysicians, radiologists, nuclear medicine\nphysicians, and radiation oncologists.","Qualified persons with the necessary\nknowledge in accordance with country-\nspecific regulations, for example,\nradiotherapy technologists, medical\nphysicists, clinical administrators, or radiation\noncologists","Substantially\nEquivalent\nminor\ndeviation in\nwording",""],["","2.0","","","Technical Characteristics","","","",""],["","2.1","","","Basic Features of the Subject Device","","","",""],["","","","Routine Reading\nFunctionality","","VRT, MPR, MIP, thin VRT, thick MPR,\nInteraction: zoom, pan, rotate","VRT, MPR, MIP, thin VRT, thick MPR,\nInteraction: zoom, pan, rotate","Equivalent",""],["","","","Parallel Display","","Parallel Image Display, Image Visualization,\nImage Fusion, Correlated Cursors","Parallel Image Display, Image Visualization,\nImage Fusion, Correlated Cursors","Equivalent",""],["","","","Routine\nAnnotation\nFunctionality","","Distance line, ROI, VOI, pixel lens, angle;\nfindings","Distance line, ROI, VOI, pixel lens, angle;\nfindings","Equivalent",""],["","2.2","","","Image Registration","","","",""],["","","","Rigid Alignment","","Rigid registration of images of the same\npatient acquired with the same or different\nmodalities within the same or different\nimaging sessions. The transformation includes\nonly translation and rotation (6 degrees of\nfreedom).","Rigid registration of images of the same patient\nacquired with the same or different modalities\nwithin the same or different imaging sessions.\nThe transformation includes only translation\nand rotation (6 degrees of freedom).","Equivalent",""],["","","","Deformable\nAlignment","","Deformable registration of images of the\nsame patient acquired with the same or\ndifferent modalities within different imaging","Deformable registration of images of the same\npatient acquired with the same or different\nmodalities within different imaging sessions.","Equivalent",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p15-t0","doc_id":"K252304","page_num":15,"bbox":[40.24,105.74,751.77,523.78],"n_rows":4,"n_cols":7,"columns":["","","","sessions. The transformation allows for local\ndeformation to adapt to changing anatomy\n(many degrees of freedom). The feature\nincludes a tool for visual quality assurance.","The transformation allows for local\ndeformation to adapt to changing anatomy\n(many degrees of freedom). The feature\nincludes a tool for visual quality assurance.","",""],"rows":[["","","","sessions. The transformation allows for local\ndeformation to adapt to changing anatomy\n(many degrees of freedom). The feature\nincludes a tool for visual quality assurance.","The transformation allows for local\ndeformation to adapt to changing anatomy\n(many degrees of freedom). The feature\nincludes a tool for visual quality assurance.","",""],["2.3","","Contouring","","","",""],["","Routine\nContouring","","Routine Contouring tools (e. g. freehand\ndrawing tools, creation of margins, tool to\nconvert isodose lines from a DICOM RT dose\nfile to contours etc.)","Routine Contouring tools (e. g. freehand\ndrawing tools, creation of margins etc.)\nA tool was added to convert isodose lines\nfrom a DICOM RT dose file to contours.","Equivalent",""],["","Advanced\nContouring","","Advanced Contouring tools (automatic\ncontouring of structures, nudge 3D tool, etc.).\nSupport of Rapid Results Technology.\nStreamlined workflow to adapt contours\nfrom a prior to a current planning CT\n(“adaptive contouring”).","Advanced Contouring tools (automatic\ncontouring of structures, nudge 3D tool, etc.).\nSupport of Rapid Results Technology.\nStreamlined workflow to adapt contours\nfrom a prior to a current planning CT\n(“adaptive contouring”).\nAdditional structures and organs were added\nfor Auto Contouring to extend the organ\ncoverage and included additional\nsegmentation guidelines for CT images and\nInclusion of MR Images (MR autocontouring\nincluding brain metastasis) (The underlying\ndeep learning technology for this extension is\nunchanged. It reuses the same technology\nwhich was available in prior versions of the\nauto segmentation feature).","Existing\nfeature\nenhanced",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p16-t0","doc_id":"K252304","page_num":16,"bbox":[40.25,105.74,751.76,529.3],"n_rows":10,"n_cols":9,"columns":["","","","","","","Brain metastasis specific contouring model is\nlimited to previously diagnosed metastases,\nusing deep learning segmentation. Note:\nBrain metastases – only on MR Images)","",""],"rows":[["","","","","","","Brain metastasis specific contouring model is\nlimited to previously diagnosed metastases,\nusing deep learning segmentation. Note:\nBrain metastases – only on MR Images)","",""],["","","","Contouring on 4D\nImage Data","","Contouring tools on 4D image data (e. g.\ndisplay of a cine loop of images acquired\nthrough gated CT etc.)","Contouring tools on 4D image data (e. g.\ndisplay of a cine loop of images acquired\nthrough gated CT etc.)","Equivalent",""],["","","","Routine Structure\nOperations","","Structure editing tools (e. g. expansion or\nshrinking of a structure).","Structure editing tools (e. g. expansion or\nshrinking of a structure).","Equivalent",""],["","","","Duplication of\nStructures and\nPOIs","","Duplication of structures and POIs inside the\nsame structure set.","Duplication of structures and POIs inside the\nsame structure set.","Equivalent",""],["","2.4","","","Structure Set Management","","","",""],["","","","Structure Set\nManagement","","• Loading and storing of DICOM RT structure\nsets, creating, editing and deletion of\nstructures and POIs.\n• Creating, editing and deletion of structure\ntemplates.\n• Customize predefined structure database\nwith mapping to international\nnomenclature schemes.","• Loading and storing of DICOM RT structure\nsets, creating, editing and deletion of\nstructures and POIs.\n• Creating, editing and deletion of structure\ntemplates.\n• Customize predefined structure database\nwith mapping to international\nnomenclature schemes.","Equivalent",""],["","2.5","","","Reference Point Management","","","",""],["","","","Reference Point\nManagement","","Reference point creation and management","Reference point creation and management","Equivalent",""],["","2.6","","","Patient Marking","","","",""],["","","","Patient Marking","","Sending of reference points with offset\ndetails to a laser system.","Sending and receiving of reference points\nwith offset details and coordinates to and","Minor\ndifference -",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p17-t0","doc_id":"K252304","page_num":17,"bbox":[40.26,105.74,751.76,531.58],"n_rows":15,"n_cols":9,"columns":["","","","","","• Inclusion of a simplified workflow to place\nisocenters in the spine\n• Consistent use of user-configured\ndefault names throughout the\napplication","from a movable laser system.\n• Inclusion of a simplified workflow to place\nisocenters in the spine\n• Consistent use of user-configured default\nnames throughout the application","Existing\nfeature\nenhanced",""],"rows":[["","","","","","• Inclusion of a simplified workflow to place\nisocenters in the spine\n• Consistent use of user-configured\ndefault names throughout the\napplication","from a movable laser system.\n• Inclusion of a simplified workflow to place\nisocenters in the spine\n• Consistent use of user-configured default\nnames throughout the application","Existing\nfeature\nenhanced",""],["","2.7","","","Dose Evaluation","","","",""],["","","","Dose Evaluation","","Loading of any existing dose files; addition or\nsubtraction of two dose; show Dose Volume\nHistograms","Loading of any existing dose files; addition or\nsubtraction of two dose; show Dose Volume\nHistograms","Equivalent",""],["","2.8","","","Beam Placement","","","",""],["","","","Beam Placement","","Creation of new geometric treatment\nplans for photon radiotherapy","Creation of new geometric treatment plans\nfor photon radiotherapy","Equivalent",""],["","2.9","","","Synthetic CT","","","",""],["","","","Synthetic CT","","Generation of CT-density image series (2D\nmodel) out of multiple MR-image series for\nPelvis and Brain.","New Synthetic CT algorithm (3D model) for\nPelvis and Brain was provided","Existing\nfeature\nenhanced",""],["","2.10","","","Lung Ventilation","","","",""],["","","","Lung Ventilation","","Calculation of lobe-based lung ventilation\nfrom an inspiration and expiration CT scan","Calculation of lobe-based lung ventilation\nfrom an inspiration and expiration CT scan","Equivalent",""],["","2.11","","","Software","","","",""],["","","","User Interface","","syngo.via based GUI","syngo.via based GUI","Equivalent",""],["","","","Archiving / Storing","","MOD, CD-R, film; DVD","MOD, CD-R, film; DVD","Equivalent",""],["","","","Communication","","DICOM Compatible","DICOM Compatible","Equivalent",""],["","2.12","","","Model support","","","",""],["","","","Model support","","CT Scanners, syngo.via platform","CT Scanners, syngo.via platform","Equivalent",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p18-t0","doc_id":"K252304","page_num":18,"bbox":[90.78,374.95,701.35,508.9],"n_rows":4,"n_cols":8,"columns":["Specification","","Reference Device","","","Device Under Evaluation","","Equivalency"],"rows":[["Specification","","Reference Device","","","Device Under Evaluation","","Equivalency"],["","","VBrain (K203235)","","","syngo.via RT Image Suite VC10","",""],["Intended Use","Assists trained medical\nprofessionals in RT planning by\nproviding initial contours for\nknown brain tumors.","","","Software for multimodality viewing,\nregistration, and autocontouring\nincluding brain metastases.","","","Similar"],["Clinical Workflow\nRole","Provides initial GTV contours\nrequiring clinician review.","","","Provides editable automated contours;\nclinician review required.","","","Similar"]],"caption_candidate":"Comparison of Contour Metastases for VBrain and syngo.via RT Image Suite VC10","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p19-t0","doc_id":"K252304","page_num":19,"bbox":[90.76,105.92,701.37,301.37],"n_rows":10,"n_cols":8,"columns":["Specification","","Reference Device","","","Device Under Evaluation","","Equivalency"],"rows":[["Specification","","Reference Device","","","Device Under Evaluation","","Equivalency"],["","","VBrain (K203235)","","","syngo.via RT Image Suite VC10","",""],["Tumor Types\nSupported","Brain metastases, meningiomas,\nacoustic neuromas.","","","Brain metastases and brain OARs.","","","Similar"],["Imaging Modalities","T1 CE MRI","","","CT, MRI, CBCT, PET/CT, etc.","","","Similar"],["AI/ML Technology","Deep learning neural networks.","","","3D UNet/DI2IN-based DL models.","","","Similar"],["User Control","Fully editable","","","Fully editable","","","Similar"],["Performance\nSensitivity","90.3%","","","92.5%","","","Similar"],["False Positive Rate","0.681 tumors/case","","","1.30","","","Similar"],["Dice Coefficient","0.793","","","0.74","","","Similar"],["Hausdorff Distance","5.0% in terms of lesion size","","","1.41 mm (HD95)","","","Similar"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p21-t0","doc_id":"K252304","page_num":21,"bbox":[130.77,170.81,661.23,319.19],"n_rows":8,"n_cols":2,"columns":["Model / Feature","Number of Subjects"],"rows":[["Model / Feature","Number of Subjects"],["CT auto-contouring","469"],["MR brain metastasis model","30"],["MR brain organs-at-risk (OAR) model","46"],["MR pelvis OAR model","154"],["Synthetic CT model","51"],["Semi-automated isocenter estimation / laser-based isocenter definition (breast)","10"],["Semi-automated isocenter estimation / laser-based isocenter definition (vertebra)","10"]],"caption_candidate":"subjects, distributed across the following models and features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p23-t0","doc_id":"K252304","page_num":23,"bbox":[171.04,120.17,621.08,257.09],"n_rows":7,"n_cols":6,"columns":["","Subgroup","","","# Test data sets",""],"rows":[["","Subgroup","","","# Test data sets",""],["Data Source","","","Europe: 110, US: 149, Canada: 56, South America: 83, Australia:\n29, Asia: 33, unknown: 13","",""],["Body Region","","","Head&Neck: 114, Thorax&Abdomen: 266, Pelvis: 93","",""],["Gender","","","Male: 199, female: 216, Unknown: 58","",""],["Age","","","<=30: 1, [30-50]: 6, [50;70]: 46, >70: 22, unknown: 398","",""],["Slice thickness (in\nmm)","","","<=1:20, (1,2]: 220, (2,3]: 213, >3: 20","",""],["Manufacturer","","","Siemens: 148, GE: 100, Philips: 149, unknown/others: 76","",""]],"caption_candidate":"Distribution of test data across subgroups for CT auto-contouring","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p24-t0","doc_id":"K252304","page_num":24,"bbox":[149.42,209.57,642.7,529.54],"n_rows":19,"n_cols":5,"columns":["Structure","# Test\nCases","DICE","",""],"rows":[["Structure","# Test\nCases","DICE","",""],["","","Mean","Std.Dev","Lower 95th %\nConfidence Interval"],["Body","46","0.99","0.003","0.99"],["Spinal Canal","27","0.85","0.073","0.82"],["Spinal Cord","39","0.67","0.102","0.64"],["Brain","20","0.98","0.005","0.98"],["Brainstem Brouwer et al.","20","0.89","0.024","0.88"],["Brainstem DAHANCA1","30","0.88","0.025","0.88"],["Cochlea Left","25","0.75","0.164","0.68"],["Cochlea Right","25","0.8","0.049","0.78"],["Eye Globe Left","20","0.89","0.038","0.88"],["Eye Globe Right","20","0.89","0.027","0.88"],["Glottis Brouwer et al.","20","0.7","0.103","0.65"],["Glottis DAHANCA1","30","0.68","0.087","0.65"],["Lens Left","20","0.68","0.192","0.59"],["Lens Right","20","0.67","0.121","0.61"],["Lips","20","0.79","0.072","0.76"],["LN Level Ia Submental Triangle","59","0.64","0.157","0.6"],["LN Level Ib Submandibular Triangle Left","59","0.8","0.063","0.79"]],"caption_candidate":"Test results: passed for all organs. Table below shows the performance results.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p25-t0","doc_id":"K252304","page_num":25,"bbox":[149.42,105.74,642.7,528.34],"n_rows":21,"n_cols":5,"columns":["Structure","# Test\nCases","DICE","",""],"rows":[["Structure","# Test\nCases","DICE","",""],["","","Mean","Std.Dev","Lower 95th %\nConfidence Interval"],["LN Level Ib Submandibular Triangle Right","58","0.77","0.086","0.75"],["LN Level II Upper Jugular Nodes Left","59","0.82","0.051","0.81"],["LN Level II Upper Jugular Nodes Right","59","0.8","0.063","0.78"],["LN Level III Middle Jugular Nodes Left","59","0.79","0.067","0.77"],["LN Level III Middle Jugular Nodes Right","59","0.77","0.085","0.75"],["LN Level IVa Lower Jugular Group Left","59","0.71","0.109","0.68"],["LN Level IVa Lower Jugular Group Right","59","0.73","0.084","0.71"],["LN Level IVb Medial Supraclavicular Group\nLeft","59","0.66","0.159","0.62"],["LN Level IVb Medial Supraclavicular Group\nRight","59","0.7","0.11","0.67"],["LN Level IX Bucco-facial Group Left","59","0.64","0.08","0.62"],["LN Level IX Bucco-facial Group Right","59","0.62","0.096","0.59"],["LN Level V Posterior Triangle Group Left","59","0.71","0.117","0.68"],["LN Level V Posterior Triangle Group Right","59","0.69","0.122","0.66"],["LN Level Vc Lateral Supraclavicular Group\nLeft","59","0.56","0.156","0.52"],["LN Level Vc Lateral Supraclavicular Group\nRight","59","0.61","0.123","0.57"],["LN Level VIa Anterior Jugular Nodes","59","0.7","0.066","0.69"],["LN Level VIb Prelaryngeal, Pretracheal, &\nParatracheal Nodes","59","0.66","0.109","0.64"],["LN Level VIIa Retropharyngeal Nodes Left","59","0.53","0.1","0.5"],["LN Level VIIa Retropharyngeal Nodes Right","59","0.49","0.149","0.45"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p26-t0","doc_id":"K252304","page_num":26,"bbox":[149.42,105.74,642.7,531.94],"n_rows":24,"n_cols":5,"columns":["Structure","# Test\nCases","DICE","",""],"rows":[["Structure","# Test\nCases","DICE","",""],["","","Mean","Std.Dev","Lower 95th %\nConfidence Interval"],["LN Level VIIb Retro-styloid Nodes Left","59","0.73","0.079","0.71"],["LN Level VIIb Retro-styloid Nodes Right","59","0.74","0.095","0.71"],["LN Level VIII Parotid Group Left","59","0.85","0.037","0.84"],["LN Level VIII Parotid Group Right","59","0.84","0.042","0.83"],["LN Level Xa Retroauricular & Subauricular\nNodes Left","59","0.69","0.099","0.66"],["LN Level Xa Retroauricular & Subauricular\nNodes Right","59","0.73","0.075","0.71"],["LN Level Xb Occipital Nodes Left","59","0.57","0.111","0.54"],["LN Level Xb Occipital Nodes Right","59","0.56","0.136","0.52"],["Mandible","20","0.88","0.028","0.87"],["Optic Chiasm","20","0.37","0.183","0.29"],["Optic Nerve Left","20","0.63","0.121","0.57"],["Optic Nerve Right","20","0.63","0.103","0.58"],["Oral Cavity","20","0.89","0.049","0.87"],["Parotid Gland Left","20","0.85","0.081","0.82"],["Parotid Gland Right","20","0.85","0.072","0.81"],["Pharyngeal Constrictor Muscle Inferior","30","0.78","0.049","0.76"],["Pharyngeal Constrictor Muscle Middle","30","0.67","0.076","0.64"],["Pharyngeal Constrictor Muscle Superior","30","0.66","0.056","0.64"],["Submandibular Gland Left","19","0.87","0.045","0.84"],["Submandibular Gland Right","15","0.85","0.066","0.82"],["Supraglottic Larynx Brouwer et al.","20","0.77","0.091","0.73"],["Supraglottic Larynx DAHANCA1","30","0.8","0.059","0.78"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p27-t0","doc_id":"K252304","page_num":27,"bbox":[149.42,105.74,642.7,534.34],"n_rows":26,"n_cols":5,"columns":["Structure","# Test\nCases","DICE","",""],"rows":[["Structure","# Test\nCases","DICE","",""],["","","Mean","Std.Dev","Lower 95th %\nConfidence Interval"],["Thyroid","30","0.84","0.034","0.83"],["Aorta","35","0.87","0.032","0.86"],["Brachial Plexus Right","20","0.66","0.051","0.63"],["Brachial Plexus Left","20","0.63","0.089","0.59"],["Chest Wall Left","28","0.92","0.016","0.92"],["Chest Wall Right","28","0.93","0.013","0.92"],["Esophagus RTOG","34","0.81","0.059","0.79"],["Esophagus DAHANCA1","30","0.86","0.042","0.84"],["Female Breast Left RTOG","8","0.89","0.049","0.85"],["Female Breast Left ESTRO1","28","0.91","0.034","0.89"],["Female Breast Right RTOG","7","0.85","0.066","0.79"],["Female Breast Right ESTRO1","28","0.91","0.035","0.89"],["LN Axilla Level I Left","24","0.81","0.055","0.79"],["LN Axilla Level I Right","24","0.8","0.072","0.77"],["LN Axilla Level II Left","24","0.79","0.068","0.76"],["LN Axilla Level II Right","24","0.78","0.07","0.75"],["LN Axilla Level III Left","24","0.75","0.042","0.74"],["LN Axilla Level III Right","24","0.76","0.078","0.73"],["LN Internal Mammary Left","24","0.59","0.081","0.55"],["LN Internal Mammary Right","24","0.63","0.096","0.59"],["LN Supraclavicular Left","24","0.79","0.085","0.76"],["LN Supraclavicular Right","24","0.8","0.068","0.77"],["Lung Lobe Left Lower","18","0.9","0.125","0.84"],["Lung Lobe Left Upper","18","0.94","0.073","0.91"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p28-t0","doc_id":"K252304","page_num":28,"bbox":[35.76,121.34,601.58,575.95],"n_rows":57,"n_cols":7,"columns":["","","#","Test","","",""],"rows":[["","","#","Test","","",""],["","","","","","",""],["","Structure","C","ases","Mean","Low\nStd.Dev","er 95"],["","","","","","",""],["","","","","","Confide","nce"],["","","","","","",""],["","Lung Lobe Right","Lower","17","0.93","0.045","0.9"],["","","","","","",""],["","Lung Lobe Right","Middle","18","0.89","0.079","0.85"],["","","","","","",""],["","Lung Lobe Right","Upper","18","0.93","0.053","0.91"],["","","","","","",""],["","Proximal Bronch","ial Tree","27","0.84","0.051","0.82"],["","","","","","",""],["","Pulmonary Arter","y","27","0.8","0.058","0.78"],["","","","","","",""],["","Rib Left 1","","19","0.84","0.043","0.82"],["","","","","","",""],["","Rib Left 10","","19","0.77","0.189","0.68"],["","","","","","",""],["","Rib Left 11","","19","0.77","0.191","0.68"],["","","","","","",""],["","Rib Left 12","","18","0.8","0.073","0.76"],["","","","","","",""],["","Rib Left 2","","19","0.83","0.075","0.8"],["","","","","","",""],["","Rib Left 3","","19","0.82","0.038","0.8"],["","","","","","",""],["","Rib Left 4","","19","0.83","0.033","0.81"],["","","","","","",""],["","Rib Left 5","","19","0.83","0.032","0.82"],["","","","","","",""],["","Rib Left 6","","19","0.84","0.024","0.83"],["","","","","","",""],["","Rib Left 7","","19","0.83","0.031","0.82"],["","","","","","",""],["","Rib Left 8","","19","0.82","0.036","0.8"],["","","","","","",""],["","Rib Left 9","","19","0.82","0.023","0.81"],["","","","","","",""],["","Rib Right 1","","19","0.84","0.051","0.81"],["","","","","","",""],["","Rib Right 10","","19","0.79","0.194","0.69"],["","","","","","",""],["","Rib Right 11","","19","0.78","0.193","0.68"],["","","","","","",""],["","Rib Right 12","","18","0.82","0.044","0.8"],["","","","","","",""],["","Rib Right 2","","19","0.87","0.027","0.85"],["","","","","","",""],["","Rib Right 3","","19","0.85","0.039","0.83"],["","","","","","",""],["","Rib Right 4","","19","0.86","0.027","0.85"],["","","","","","",""],["510(k) Summary","","","","","",""],["Traditional 510(k) Appli","cation","","","","",""],["syngo.via RT Image Suite VC1","0","","","Page 23 of","42",""]],"caption_candidate":"DICE","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252304-p29-t0","doc_id":"K252304","page_num":29,"bbox":[149.42,105.74,642.7,534.34],"n_rows":26,"n_cols":5,"columns":["Structure","# Test\nCases","DICE","",""],"rows":[["Structure","# Test\nCases","DICE","",""],["","","Mean","Std.Dev","Lower 95th %\nConfidence Interval"],["Rib Right 5","19","0.86","0.026","0.85"],["Rib Right 6","19","0.86","0.026","0.85"],["Rib Right 7","19","0.85","0.031","0.84"],["Rib Right 8","19","0.81","0.109","0.76"],["Rib Right 9","19","0.79","0.2","0.69"],["Ribs","19","0.88","0.025","0.87"],["Sternum","34","0.88","0.032","0.87"],["Trachea","27","0.89","0.046","0.87"],["Vena Cava Inferior","27","0.76","0.128","0.71"],["Vena Cava Superior","27","0.79","0.069","0.76"],["Atrium Left","57","0.86","0.048","0.85"],["Atrium Right","57","0.79","0.089","0.77"],["Heart","57","0.93","0.02","0.93"],["CA Left Anterior Descending Artery (LAD)","55","0.42","0.097","0.39"],["Ventricle Left Endocardium","57","0.84","0.054","0.82"],["Ventricle Left","57","0.86","0.041","0.85"],["Ventricle Right","57","0.83","0.034","0.83"],["Abdominopelvic Cavity","21","0.96","0.032","0.94"],["Bowel Large","102","0.9","0.045","0.89"],["Bowel Small","76","0.89","0.042","0.88"],["Duodenum","76","0.77","0.104","0.75"],["Kidney Left","16","0.93","0.019","0.92"],["Kidney Right","16","0.91","0.07","0.87"],["Liver","23","0.96","0.013","0.95"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K252304-p43-t0","doc_id":"K252304","page_num":43,"bbox":[158.18,105.74,633.82,214.37],"n_rows":7,"n_cols":8,"columns":["T2 Pelvis","","","","","","",""],"rows":[["T2 Pelvis","","","","","","",""],["Anus","98","0.73","0.1","0.71","2.24","1.16","2.47"],["Bladder","98","0.9","0.08","0.88","1.36","0.85","1.53"],["Penile Bulb","95","0.81","0.09","0.79","0.91","0.76","1.07"],["Prostate","90","0.86","0.07","0.84","1.66","2.01","2.08"],["Rectum","98","0.86","0.06","0.85","1.92","2.01","2.32"],["Seminal Vesicles","89","0.72","0.14","0.69","1.78","1.25","2.05"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p43-t1","doc_id":"K252304","page_num":43,"bbox":[172.6,447.67,619.41,525.1],"n_rows":5,"n_cols":6,"columns":["","Subgroup","","","# Test data sets",""],"rows":[["","Subgroup","","","# Test data sets",""],["Data Source","","","US: 17; Europe: 18; Unknown: 16","",""],["Body Region","","","pelvis: 29, brain: 22","",""],["Sequence","","","T1 VIBE Dixon","",""],["Gender","","","Male: 24, female: 21, unknown: 6","",""]],"caption_candidate":"Distribution of test data across subgroups for synthetic CT","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p44-t0","doc_id":"K252304","page_num":44,"bbox":[171.83,105.92,620.24,218.45],"n_rows":4,"n_cols":5,"columns":["","Subgroup","","# Test data sets",""],"rows":[["","Subgroup","","# Test data sets",""],["Age","","","[21Y-40Y]:6\n[41Y-60Y]:11\n[61Y-80Y]:18\nUnknown:16",""],["Field strength","","","1.5T: 33, 3T: 18",""],["Siemens scanners","","","MAGNETOM Aera: 24, MAGNETOM Skyra: 5, MAGNETOM Vida:\n13, MAGNETOM Sola: 1, MAGNETOM Sola Fit: 1",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p44-t1","doc_id":"K252304","page_num":44,"bbox":[171.83,463.36,620.24,525.22],"n_rows":4,"n_cols":5,"columns":["","Subgroup","","# Test data sets",""],"rows":[["","Subgroup","","# Test data sets",""],["Data Source","","Europe: 142, US: 126, Asia: 131, unknown: 27","",""],["Body Region","","Head&Neck: 113, Thorax&Abdomen: 264, Pelvis: 92","",""],["Gender","","Male: 187, female: 74, Unknown: 165","",""]],"caption_candidate":"Distribution of test data across subgroups for Semi-automated isocenter estimates or defining isocenters via RTP lasers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p45-t0","doc_id":"K252304","page_num":45,"bbox":[171.02,105.74,621.1,195.29],"n_rows":3,"n_cols":2,"columns":["Age","[0-2]:5 , [3-12]: 25, [13-19]: 64, [20-29]:38 [30-39]:21 [40-49]:71\n[50-59]:46 [60-69]:80 [70-79]:49 [80-89]:12 unknown: 15"],"rows":[["Age","[0-2]:5 , [3-12]: 25, [13-19]: 64, [20-29]:38 [30-39]:21 [40-49]:71\n[50-59]:46 [60-69]:80 [70-79]:49 [80-89]:12 unknown: 15"],["Slice thickness (in\nmm)","<=1:20, (1,2]: 220, (2,3]: 209, >3: 20"],["Manufacturer","Siemens: 369, GE: 10, Philips: 28, Toshiba: 2; NeuoLogica: 14\nunknown/others: 3"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p45-t1","doc_id":"K252304","page_num":45,"bbox":[180.02,343.87,612.1,512.98],"n_rows":5,"n_cols":2,"columns":["Standard\nOrganization","Title"],"rows":[["Standard\nOrganization","Title"],["ISO 14971:2019","Medical devices - Application of risk management to medical\ndevices"],["ISO 15223-1:2021","Medical devices - Symbols to be used with medical device\nlabels, labelling and information to be supplied - Part 1:\nGeneral requirements"],["ISO 20417:2021","Information supplied by the manufacturer of medical devices"],["IEC 62304:2006 +\nA1:2016","Medical Device Software - Software Lifecycle processes"]],"caption_candidate":"safety and efficacy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252304-p46-t0","doc_id":"K252304","page_num":46,"bbox":[180.02,105.74,612.1,371.71],"n_rows":7,"n_cols":2,"columns":["IEC 62366-\n1:2015+A1:2020","Application of Usability Engineering to Medical Devices"],"rows":[["IEC 62366-\n1:2015+A1:2020","Application of Usability Engineering to Medical Devices"],["IEC 82304-1:2016","Health software Part 1: General requirements for product\nsafety"],["IEC 61217:2011","Radiotherapy Equipment, Coordinates, Movements and\nScales"],["IEC 62083:2009","Medical electrical equipment – Requirements for the safety\nof radiotherapy treatment planning systems"],["UL ANSI 2900-1:2017","Standard for Software Cybersecurity for Network-\nConnectable Products, Part 1: General Requirements"],["UL ANSI 2900-2-\n1:2017","Software Cybersecurity for Network-Connectable Products,\nPart 2-1: Particular Requirements for Network Connectable\nComponents of Healthcare and Wellness Systems"],["IEC 81001-5-1:2021","Health Software and Health IT Systems Safety, Effectiveness\nand Security - Part 5-1: Security - Activities In The Product\nLife Cycle"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p8-t0","doc_id":"K252328","page_num":8,"bbox":[222.44,236.01,558.62,699.45],"n_rows":2,"n_cols":4,"columns":["","","SonoLyst/SonolysLive 1st Trimester",""],"rows":[["","","SonoLyst/SonolysLive 1st Trimester",""],["Summary test\nStatistics","","",""]],"caption_candidate":"Note: Update to predicate Device only in Section Data Collection:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p8-t1","doc_id":"K252328","page_num":8,"bbox":[346.59,582.95,537.21,699.45],"n_rows":6,"n_cols":7,"columns":["Functionality","","CL2","","","Acceptan",""],"rows":[["Functionality","","CL2","","","Acceptan",""],["","","probe","","","ce",""],["","","group","","","Criteria",""],["SonoLystIR","0.93","","","0.80","",""],["SonoLystX","0.84","","","0.80","",""],["SonoLystLive","0.84","","","0.70","",""]],"caption_candidate":"Functionality accuracy","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p9-t0","doc_id":"K252328","page_num":9,"bbox":[328.68,339.36,553.2,544.08],"n_rows":5,"n_cols":7,"columns":["(%)","Transabdominal\n(TA)","","","Tra\nnsv\nagin\nal\n(TV)","Diff\nere\nnce\n(TA\nmean\n-TV)","95%\nConfid\nence\nInterva\nl"],"rows":[["(%)","Transabdominal\n(TA)","","","Tra\nnsv\nagin\nal\n(TV)","Diff\nere\nnce\n(TA\nmean\n-TV)","95%\nConfid\nence\nInterva\nl"],["","CL1","CL\n2","Me\nan","CLE","",""],["SonoL\nyst IR","93.\n7","94.\n5","94.\n1","97.3","-3.2","(-4.6,\n1.8)"],["SonoL\nyst X","91.\n6","93.\n1","92.\n4","92.6","-0.3","(-2.1,\n1.7)"],["SonoL\nyst\nLive","82.\n9","82.\n1","82.\n5","81.9","0.6","(-1.2,\n2.6)"]],"caption_candidate":"scanning","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p9-t1","doc_id":"K252328","page_num":9,"bbox":[328.68,569.16,553.2,689.66],"n_rows":3,"n_cols":5,"columns":["%","Europ\nUSA\nean","","Differen\nce (USA-\nEuropea\nn)","95%\nConfide\nnce\nInterval"],"rows":[["%","Europ\nUSA\nean","","Differen\nce (USA-\nEuropea\nn)","95%\nConfide\nnce\nInterval"],["SonoLy\nst IR","95.6","94.8","0.8","(-1.1,\n2.7)"],["SonoLy\nst X","92.9","92.4","0.5","(-\n1.9,2.9)"]],"caption_candidate":"Table: performance across regions","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p10-t0","doc_id":"K252328","page_num":10,"bbox":[222.44,82.08,558.72,713.08],"n_rows":2,"n_cols":2,"columns":["","SonoLy (-\n83.2 84.9 -1.7\nst Live 5.0,1.6)"],"rows":[["","SonoLy (-\n83.2 84.9 -1.7\nst Live 5.0,1.6)"],["Data Collection","- Systems: GE Voluson V730, P8, S6/S8, E6, E8,\nE10, Expert 22, Philips Epiq 7G\n- Formats: Still images were obtained in DICOM\n& JPEG format, cine loops in RAW data\nformat.\n- Countries: UK, Austria, India and USA\n- For training 122,711 labelled source images\nfrom 35,861 patients\n- For testing the following number of images\nwere used:\nSonoLyst 1st Trim IR: 7970\nSonoLyst 1st Trim X: 4931\nSonoLyst 1st Trim Live: 9111\nSonoBiometry CRL: 243\n- For Probegroup CL2 (which includes C1-6-D\nProbe) Data was collected from 396 patients.\nData was sampled so that a maximum of one sample\nwas taken per patient per view. The final samples\nevaluated were:\nImages per dataset for\nCL2 Probetypes\nView Category\nSonoLystIR SonoLyst\n& X Live\nSagittal Fetus\n(Crown rump 133 164\nlength)\nSagittal Bladder 140 142\nSagittal Head 153 164\n148 164\nTrans-thalamic 132 164\nAxial orbits 149 164\nCoronal orbits 164 164\nCoronal palate 150 164\nCoronal lips 147 165\nAxial heart 155 165\nAxial cord\n163 163\ninsertion\nAxial abdomen 133 164\nAxial kidneys 164 164\nAxial bladder 161 164\nCoronal kidneys 122 164\nSagittal spine 72 164"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p11-t0","doc_id":"K252328","page_num":11,"bbox":[222.33,82.08,558.72,712.92],"n_rows":2,"n_cols":2,"columns":["","Upper limbs 115 164\nLower limbs 130 164\nOthers 168 180\nTotal images 2699 3111\n- Demographic distribution including Gender,\nAge, and Ethnicity:\nWe are not able to provide exact demographic\ndistributions due to data privacy constraints.\nWhere collected, patient age is grouped into <20, 20-\n29, 30-39, 40-49, >50. The data set contains known\npatient ages from <20 till 30-39 and has been limited\nto reproductive ages of at least 18 years of age.\nData was collected from 396 patients for CL2\nevaluation, with 201 (51%) patients from USA sites and\n195 (49%) from European sites.\nFrom our earlier evaluation across the probe groups,\nwe also conducted a subset evaluation across different\nregions. In all cases the confidence intervals cross zero,\nindicating no statistically significant difference. These\nfindings demonstrate that the algorithm performs\nconsistently across regions.\nSee also Table: “performance across regions”"],"rows":[["","Upper limbs 115 164\nLower limbs 130 164\nOthers 168 180\nTotal images 2699 3111\n- Demographic distribution including Gender,\nAge, and Ethnicity:\nWe are not able to provide exact demographic\ndistributions due to data privacy constraints.\nWhere collected, patient age is grouped into <20, 20-\n29, 30-39, 40-49, >50. The data set contains known\npatient ages from <20 till 30-39 and has been limited\nto reproductive ages of at least 18 years of age.\nData was collected from 396 patients for CL2\nevaluation, with 201 (51%) patients from USA sites and\n195 (49%) from European sites.\nFrom our earlier evaluation across the probe groups,\nwe also conducted a subset evaluation across different\nregions. In all cases the confidence intervals cross zero,\nindicating no statistically significant difference. These\nfindings demonstrate that the algorithm performs\nconsistently across regions.\nSee also Table: “performance across regions”"],["Truthing process\nfor test datasets","In general for Sonolyst Software:\nTo ensure the quality of the curated data for\nverification, the following strategy is employed:\n1. The images were curated (sorted and\ngraded) by a single sonographer\n2. The images were sorted and graded by\nSonoLyst IR/X First Trimester.\nThis process resulted in some images\nbeing reclassified during sorting.\n3. The sorting process resulted in some\nimages being reclassified based upon the\nmajority view of the panel.Where they\ndiffered from the ground truth, the\ngraded images from step 1 were\nreviewed by a 5-sonographer review\npanel, in order to determine the grading\naccuracy of the system\nespecially for C1-6-D probe impmentation:\nA standardized imaging protocol was used based on\ninternationally recognized guidelines to ensure\nconsistency and quality across all scans. Specifically,\nthe following sources were used to inform the\nprotocol:"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p11-t1","doc_id":"K252328","page_num":11,"bbox":[328.47,82.08,553.16,141.12],"n_rows":4,"n_cols":9,"columns":["Upper limbs","","","115","","","164","",""],"rows":[["Upper limbs","","","115","","","164","",""],["Lower limbs","","","130","","","164","",""],["Others","","","168","","","180","",""],["","Total images","","","2699","","","3111",""]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252328-p12-t0","doc_id":"K252328","page_num":12,"bbox":[222.44,82.16,558.72,612.55],"n_rows":2,"n_cols":2,"columns":["","• AIUM Practice Parameter for the\nPerformance of Standard Diagnostic\nObstetric Ultrasound\nThis U.S.-based guideline defines the\nminimum criteria for a complete first-\ntrimester scan, with flexibility for\ntransabdominal or transvaginal approaches.\n• AIUM Detailed Protocol (12 Weeks 0 Days to\n13 Weeks 6 Days)\nUsed in cases where abnormalities were\nsuspected or in high-risk pregnancies, this\nprotocol provides more detailed criteria for\ndiagnostic imaging.\n• ISUOG Practice Guidelines: Performance of\nFirst-Trimester Fetal Ultrasound Scan\nThis guideline outlines the standard approach\nfor confirming fetal viability, accurately\nestablishing gestational age and determining\nthe number of fetuses.\n• ISUOG Detailed Protocol\nApplied in cases involving higher-risk\npregnancies, this protocol provides additional\ndetail to ensure comprehensive assessment\nduring the first-trimester scan.\n• Routine First-Trimester Ultrasound Screening\nUsing a Standardized Anatomical Protocol\n(Yimei Liao et al.)\nThis study informed the development of a\nroutine first-trimester scan protocol for\ndetecting structural abnormalities.\nTest data was collected on:\nGEHC Voluson Expert 22\nGEHC Voluson Expert 10"],"rows":[["","• AIUM Practice Parameter for the\nPerformance of Standard Diagnostic\nObstetric Ultrasound\nThis U.S.-based guideline defines the\nminimum criteria for a complete first-\ntrimester scan, with flexibility for\ntransabdominal or transvaginal approaches.\n• AIUM Detailed Protocol (12 Weeks 0 Days to\n13 Weeks 6 Days)\nUsed in cases where abnormalities were\nsuspected or in high-risk pregnancies, this\nprotocol provides more detailed criteria for\ndiagnostic imaging.\n• ISUOG Practice Guidelines: Performance of\nFirst-Trimester Fetal Ultrasound Scan\nThis guideline outlines the standard approach\nfor confirming fetal viability, accurately\nestablishing gestational age and determining\nthe number of fetuses.\n• ISUOG Detailed Protocol\nApplied in cases involving higher-risk\npregnancies, this protocol provides additional\ndetail to ensure comprehensive assessment\nduring the first-trimester scan.\n• Routine First-Trimester Ultrasound Screening\nUsing a Standardized Anatomical Protocol\n(Yimei Liao et al.)\nThis study informed the development of a\nroutine first-trimester scan protocol for\ndetecting structural abnormalities.\nTest data was collected on:\nGEHC Voluson Expert 22\nGEHC Voluson Expert 10"],["Independence of\nTest data","All training data is independent from the test data at a\npatient level.\nA statistically significant subset of the test data is\nindependent from the training data at a site level, with\nno test data collected at the site being used in training.\nIndependence of the test data has been insured by\ncollecting test data only from sites which were not\ni nvolved in the collection of data used for training."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p5-t0","doc_id":"K252362","page_num":5,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 1 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p5-t1","doc_id":"K252362","page_num":5,"bbox":[72.0,581.88,423.96,701.88],"n_rows":5,"n_cols":2,"columns":["Predicate Device Name","GBrain MRI"],"rows":[["Predicate Device Name","GBrain MRI"],["Manufacturer","Galileo CDS Inc"],["510(k) Number","K250416"],["Product Code","QIH, LLZ"],["Regulation Number","21 CFR 892.2050"]],"caption_candidate":"3. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p6-t0","doc_id":"K252362","page_num":6,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 2 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p6-t1","doc_id":"K252362","page_num":6,"bbox":[72.0,132.96,423.96,204.96],"n_rows":3,"n_cols":2,"columns":["Regulation Name","Medical image management and processing system"],"rows":[["Regulation Name","Medical image management and processing system"],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"Page 2 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p7-t0","doc_id":"K252362","page_num":7,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 3 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p8-t0","doc_id":"K252362","page_num":8,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 4 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p9-t0","doc_id":"K252362","page_num":9,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 5 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p9-t1","doc_id":"K252362","page_num":9,"bbox":[72.0,341.88,540.0,682.8],"n_rows":11,"n_cols":4,"columns":["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],["510K Number","N/A","K250416","-"],["Manufacturer","Galileo CDS Inc","Galileo CDS Inc","-"],["Classification","Class II","Class II","Same"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Same"],["Regulation\nDescription","Medical image management\nand processing system.","Medical image management\nand processing system.","Same"],["Classification\nName","Automated Radiological Image\nProcessing Software","Automated Radiological\nImage Processing Software","Same"],["Product code","QIH, LLZ","QIH, LLZ","Same"],["Intended Use","MR imaging data post\nprocessing software","MR imaging data post\nprocessing software","Same"],["Type of Imaging\nScan","MRI","MRI","Same"],["Intended Body\nPart","Brain","Brain","Same"]],"caption_candidate":"6.4. Device Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p10-t0","doc_id":"K252362","page_num":10,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 6 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p10-t1","doc_id":"K252362","page_num":10,"bbox":[72.0,132.96,540.0,710.88],"n_rows":5,"n_cols":4,"columns":["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],["Indications for\nUse","GBrain MRI is a post\nprocessing medical device\nsoftware intended for\nanalyzing and quantitatively\nreporting signal\nhyperintensities in the brain on\nT2w FLAIR MR images and\nT1w post contrast images in\nthe context of diagnostic\nradiology.\nGBrain MRI is intended to\nprovide automatic\nsegmentation, quantification,\nand reporting of derived image\nmetrics. It is not intended for\ndetection or specific diagnosis\nof any disease nor for the\ndetection of signal\nhyperintensities.\nGBrain MRI should not be\nused in-lieu of a full evaluation\nof the patient’s MRI scans. The\nphysician retains the ultimate\nresponsibility for making the\nfinal patient management and\ntreatment decisions.","GBrain MRI is a post\nprocessing medical device\nsoftware intended for\nanalyzing and quantitatively\nreporting signal\nhyperintensities in the brain\non FLAIR MR images in the\ncontext of diagnostic\nradiology.\nGBrain MRI is intended to\nprovide automatic\nsegmentation, quantification,\nand reporting of derived\nimage metrics. It is not\nintended for the detection or\nspecific diagnosis of any\ndisease nor for the detection\nof signal hyperintensities.\nGBrain MRI should not be\nused in-lieu of a full\nevaluation of the patient’s\nMRI scans. The physician\nretains the ultimate\nresponsibility for making the\nfinal patient management and\ntreatment decisions.","The indications for use are identical\nto the predicate device with the\naddition of post-contrast images.\nThe subject device analyzes signal\nhyperintensities regardless of\nlocation similar to the predicate.\nAs with the predicate, the subject\ndevice has a general indication and\nis not specific to a particular\ndisease or condition."],["Environment for\nuse","Hospital, Clinic, Imaging\nCenter, Medical Offices","Hospital, Clinic, Imaging\nCenter, Medical Offices","Same as Predicate"],["Intended Patient\nPopulation","Adult patients aged 21\nand above with a brain MRI\nstudy.","Adult patients aged 21\nand above with a brain MRI\nstudy.","Same as Predicate"],["Intended User","Radiologists, Imaging\nProfessionals, and other\nClinicians working with\nradiological images. The\napplication should be\nused as a support\ntool in assessment of\nstructural MRIs. Patient\nmanagement decisions should\nnot be based solely on the\nresults of the device.","Radiologists, Imaging\nProfessionals, and other\nClinicians working with\nradiological images. The\napplication should be\nused as a support\ntool in assessment of\nstructural MRIs. Patient\nmanagement decisions should\nnot be based solely on the\nresults of the device.","Same as Predicate"]],"caption_candidate":"Page 6 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p11-t0","doc_id":"K252362","page_num":11,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 7 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p11-t1","doc_id":"K252362","page_num":11,"bbox":[72.0,132.96,540.0,614.88],"n_rows":8,"n_cols":4,"columns":["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],"rows":[["Feature/Function","GBrain MRI","Predicate GBrain MRI\n(K250416)","Comments on Substantial\nEquivalence"],["Design and\nIncorporated\nTechnology","Automated segmentation using\ndeep learning followed by\nvolume calculations, and\nreport generation.\nResults displayed on PACS.","Automated segmentation\nusing deep learning followed\nby volume calculations, and\nreport generation.\nResults displayed on PACS.","Same as Predicate"],["Physical\nCharacteristics","Software package- Operates on\noff-the-shelf hardware\n(multiple vendors).","Software package- Operates\non on off-the-shelf hardware\n(multiple vendors).","Same as Predicate"],["Data Source","Supports DICOM format as\ninput from the MRI scanner or\nthe PACS.","Supports DICOM format as\ninput from the MRI scanner.","Same as Predicate"],["Output","Provides volumetric\nmeasurements of regions with\nhyperintense signal on T2w\nFLAIR and post contrast T1w\nimages.\nIncludes segmented color\noverlays and volumetric\nreports","Provides volumetric\nmeasurements of regions with\nhyperintense signal on T2w\nFLAIR images.\nIncludes segmented color\noverlays and volumetric\nreports","The subject device extends the\nfunctionality of the predicate\ndevice to include the measurement\nof contrast enhancing regions on\nT1w images."],["Reporting","Results displayed in text and\ngraphical formats","Results displayed in text and\ngraphical formats","Same as Predicate"],["DICOM\nCommunication","Yes","Yes","Same as Predicate"],["Safety","Automated quality control\nfunction: scan protocol\nverification.\nResults must be reviewed\nby a clinician with proper\ntraining.","Automated quality control\nfunction: scan protocol\nverification.\nResults must be reviewed\nby a clinician with proper\ntraining.","Same as Predicate"]],"caption_candidate":"Page 7 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p12-t0","doc_id":"K252362","page_num":12,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 8 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p12-t1","doc_id":"K252362","page_num":12,"bbox":[72.0,625.68,369.0,697.68],"n_rows":3,"n_cols":2,"columns":["Age","T1w Post Contrast Cases"],"rows":[["Age","T1w Post Contrast Cases"],["19-45","18"],["46-92","70"]],"caption_candidate":"Distribution of Validation cases across Age, Gender, and Ethnicity are shown in the tables below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t0","doc_id":"K252362","page_num":13,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 9 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t1","doc_id":"K252362","page_num":13,"bbox":[72.0,132.96,369.63,180.96],"n_rows":2,"n_cols":2,"columns":["Age","T1w Post Contrast Cases"],"rows":[["Age","T1w Post Contrast Cases"],["Unknown/Missing","43"]],"caption_candidate":"Page 9 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t2","doc_id":"K252362","page_num":13,"bbox":[72.0,207.96,369.63,303.96],"n_rows":4,"n_cols":2,"columns":["Gender","T1w Post Contrast Cases"],"rows":[["Gender","T1w Post Contrast Cases"],["Female","68"],["Male","52"],["Unknown/Missing","11"]],"caption_candidate":"Unknown/Missing 43","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t3","doc_id":"K252362","page_num":13,"bbox":[72.0,331.92,369.63,474.96],"n_rows":6,"n_cols":2,"columns":["Ethnicity/Race","T1w Post Contrast Cases"],"rows":[["Ethnicity/Race","T1w Post Contrast Cases"],["White","99"],["Black","11"],["Latino","4"],["Asian","5"],["Unknown/Missing/Other","12"]],"caption_candidate":"Unknown/Missing 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t4","doc_id":"K252362","page_num":13,"bbox":[72.0,517.92,369.63,613.92],"n_rows":4,"n_cols":2,"columns":["Manufacturer","T1w Post Contrast Cases"],"rows":[["Manufacturer","T1w Post Contrast Cases"],["GE","30"],["Philips","41"],["Siemens","59"]],"caption_candidate":"below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p13-t5","doc_id":"K252362","page_num":13,"bbox":[72.0,640.92,360.96,712.92],"n_rows":3,"n_cols":2,"columns":["Field Strength","T1w Post Contrast Cases"],"rows":[["Field Strength","T1w Post Contrast Cases"],["1.5T","73"],["3T","40"]],"caption_candidate":"Siemens 59","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p14-t0","doc_id":"K252362","page_num":14,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 10 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p14-t1","doc_id":"K252362","page_num":14,"bbox":[72.0,132.96,360.96,180.96],"n_rows":2,"n_cols":2,"columns":["Field Strength","T1w Post Contrast Cases"],"rows":[["Field Strength","T1w Post Contrast Cases"],["Unknown","18"]],"caption_candidate":"Page 10 of 11","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p14-t2","doc_id":"K252362","page_num":14,"bbox":[72.0,324.84,414.36,395.88],"n_rows":3,"n_cols":3,"columns":["Volume (cm3)","R2","Median DICE"],"rows":[["Volume (cm3)","R2","Median DICE"],["Small less than 4.2 cm3","0.68","0.73"],["Between 4.2-64.9 cm3","0.90","0.85"]],"caption_candidate":"Contrast Enhancement Measurement performance related to Hyperintensity Size","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p14-t3","doc_id":"K252362","page_num":14,"bbox":[72.0,423.84,414.36,543.96],"n_rows":5,"n_cols":3,"columns":["Z-score","R2","Median DICE"],"rows":[["Z-score","R2","Median DICE"],["0 – 1.49","0.87","0.69"],["1.5 – 1.99","1.00","0.79"],["2.0 – 2.99","0.96","0.81"],["3.0+","0.94","0.87"]],"caption_candidate":"Contrast Enhancement Measurement performance related to Hyperintensity Brightness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252362-p15-t0","doc_id":"K252362","page_num":15,"bbox":[72.0,51.48,546.0,117.48],"n_rows":2,"n_cols":3,"columns":["","510(k) Summary",""],"rows":[["","510(k) Summary",""],["","","Page 11 of 11"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252366-p4-t0","doc_id":"K252366","page_num":4,"bbox":[18.92,19.44,593.04,493.44],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252366 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK252366 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K252366",""],["Please provide the device trade name(s).","",""],["a2z-Unified-Triage","",""],["Please provide your Indications for Use below.","","?"],["a2z-Unified-Triage is a radiological computer-aided triage and notification software indicated for use in the\nanalysis of abdominal/pelvic CT images in adults aged 22 and older. The device is intended to assist\nhospital networks and appropriately trained medical specialists in workflow triage by flagging and\ncommunicating suspected positive cases of the 7 specified abdominopelvic findings: Acute Cholecystitis,\nAcute Pancreatitis, Unruptured Abdominal Aortic Aneurysm, Acute Diverticulitis, Free Air, Hydronephrosis,\nand Small Bowel Obstruction. These findings are intended to be used together as one device. The device\nsupports both cloud-based and on-premises deployment, with integration either directly with healthcare\nfacility systems or through third-party healthcare technology platforms.\na2z-Unified-Triage uses an artificial intelligence algorithm to analyze images and flag cases with detected\nfindings in parallel to the ongoing standard of care image interpretation. The device provides analysis\nresults that enable client systems to generate notifications for cases with suspected findings. These results\ncan include DICOM instance UIDs for key images, which are meant for informational purposes only and not\nintended for primary diagnosis beyond notification. The device does not alter the original medical image and\nis not intended to be used as a diagnostic device.\nThe results of a2z-Unified-Triage are intended to be used in conjunction with other patient information and\nbased on clinicians' professional judgment, to assist with triage/prioritization of medical images. Notified\nclinicians are resoonsible for viewinQ full imaQes per the standard of care.\nPlease select the types of uses (select one or both, as [gJ Prescription Use (Part 21 CFR 801 Subpart D)\nD ?\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","",""],["","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252371-p6-t0","doc_id":"K252371","page_num":6,"bbox":[90.26,631.9,519.46,705.34],"n_rows":2,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K243397)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680 (K243397)","Remark"],["indications\nfor use","The uMR 680 system is indicated\nfor use as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse,","The uMR 680 system is indicated for\nuse as a magnetic resonance\ndiagnostic device (MRDD) that\nproduces sagittal, transverse,","Same"]],"caption_candidate":"Table 1 Comparison of Indication for Use","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252371-p7-t0","doc_id":"K252371","page_num":7,"bbox":[90.26,264.77,519.46,645.82],"n_rows":21,"n_cols":4,"columns":["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K243397)","Remark"],"rows":[["ITEM","Proposed Device\nuMR 680","Predicate Device\nuMR 680(K243397)","Remark"],["General","","",""],["Magnet system","","",""],["Field Strength","1.5 Tesla","1.5 Tesla","Same"],["Type of Magnet","Superconducting","Superconducting","Same"],["Patient-accessible bore\ndimensions","70cm","70cm","Same"],["Type of Shielding","Actively shielded, OIS\ntechnology","Actively shielded, OIS\ntechnology","Same"],["Gradient system","","",""],["Max gradient amplitude","45mT/m","45mT/m","Same"],["Max slew rate","200T/m/s","200T/m/s","Same"],["Shielding","active","active","Same"],["Cooling","water","water","Same"],["RF system","","",""],["Resonant frequencies","63.87 MHz","63.87 MHz","Same"],["Number of transmit\nchannels","1","1","Same"],["Number of receive\nchannels","Up to 96","Up to 96","Same"],["Amplifier peak power\nper channel","18 kW","18 kW","Same"],["RF Coils","","",""],["Tx/Rx Head Coil","Yes","No","Note 1"],["Mobile Configuration","","",""],["Mobile configuration","Yes","No","Note 2"]],"caption_candidate":"Table 2 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252371-p9-t0","doc_id":"K252371","page_num":9,"bbox":[36.12,167.54,752.14,482.5],"n_rows":2,"n_cols":5,"columns":["Device Change","Risks","Verification/Validation Method(s)","Acceptance Criteria","Summary of Results"],"rows":[["Device Change","Risks","Verification/Validation Method(s)","Acceptance Criteria","Summary of Results"],["Add RF coils:\nTx/Rx Head Coil"," Biocompatibility\n EMC-immunity,\nelectrostatic discharge\n SNR and Uniformity\n Surface Heating\n Clinical image quality\n General\nelectrical/mechanical\nsafety\n SAR"," Biocompatibility evaluation in\nagreement with\nrecommendations in Use of\nInternational Standard ISO\n10993-1, \"Biological\nevaluation of medical devices -\nPart 1: Evaluation and testing\nwithin a risk management\nprocess\".\n Perform test according to IEC\n60601-1-2 and IEC 60601-4-2.\n Perform test according to\nNEMA MS 1, NEMA MS 3,\nNEMA MS 6 and NEMA MS\n9.\n Perform test according to\nNEMA MS 14.\n Evaluate the image generated\nby RF coils: Tx/Rx Head Coil\nwith the same method as the\npredicate device.\n Perform test according to\nANSI/AAMI ES60601-1.\n Perform test according to IEC\n60601-2-33 and NEMA MS 8."," Materials of construction and\nmanufacturing materials do not\nintroduce chemicals that raise a\nbiocompatibility concern.\n Conform with IEC 60601-1-2 and\nIEC 60601-4-2.\n SNR and Uniformity shall fulfill\nwith the design specification.\n The maximum temperature of all\ntemperature probes shall not\nexceed 41℃.\n Image quality is sufficient for\ndiagnostic use.\n Conform with ANSI/AAMI\nES60601-1.\n Conform with IEC 60601-2-33."," Biocompatibility testing is\nnot needed because device\ndoes not introduce a\nbiocompatibility risk.\n Pass\n Pass\n Pass\n The U.S. Board Certified\nradiologist confirms that\nimage quality is sufficient\nfor diagnostic use.\n Pass\n Pass"]],"caption_candidate":"The following performance data were provided in support of the substantial equivalence determination.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252379-p5-t0","doc_id":"K252379","page_num":5,"bbox":[86.76,162.12,552.24,430.56],"n_rows":10,"n_cols":2,"columns":["Date","December 19, 2025"],"rows":[["Date","December 19, 2025"],["Submitter","GE Medical Systems, LLC\n3200 N. Grandview Blvd.\nWaukesha, WI 53188"],["Primary Contact","Andrew Turner\nRegulatory Affairs Leader\n484-630-7798\nAndrew.Turner@gehealthcare.com"],["Secondary Contact","Glen Sabin\nRegulatory Affairs Director\n262-894-4968\nGlen.Sabin@gehealthcare.com"],["Device Trade Name","AIR Recon DL"],["Common/Usual Name","MR System"],["Classification Name","Magnetic Resonance Diagnostic Device"],["Regulation Number","21 CFR 892.1000"],["Product Code","LNH"],["Predicate Device(s)","AIR Recon DL (K213717)"]],"caption_candidate":"In accordance with 21 CFR 807.92, the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252421-p4-t0","doc_id":"K252421","page_num":4,"bbox":[21.25,20.06,593.68,665.63],"n_rows":7,"n_cols":4,"columns":["Indications for Use","","",""],"rows":[["Indications for Use","","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","","K252421","?"],["Please provide the device trade name(s).","","",".\n?."],["H.e\nJLK-NCCT\nlp.\nHTee","","",""],["Please provide your Indications for Use below.","","","lxpt\n?\nTe"],[".\nxt\nJLK-NCCT is a radiological computer-aided triage and notification software designed for analyzing non-\n.\ncontrast head CT (NCCT) images. The software assists hospital networks and trained clinicians by flagging\nHe\nand communicating them of findings suggestive of (1) Intracranial Hemorrhage (ICH) and (2) large vessel\nlp\nocclusion (LVO) involving the internal carotid artery (ICA), middle cerebral artery M1 (MCA-M1) and middle\nTe\ncerebral artery M2 (MCA-M2) on NCCT images.\nxt\nJLK-NCCT employs an artificial intelligence (AI) algorithm to analyze images and highlight cases with\ndetected (1) ICH or (2) LVO on an on-premises or cloud-based JLK server. This occurs in parallel with the\nongoing standard of care image interpretation. Users receive notifications for cases with suspected ICH and\nLVO findings via mobile devices. Notifications include compressed preview images for informational\npurposes only and not intended for diagnostic use beyond notification.\nThe device does not modify the original medical image, and is not intended to be used as a primary\ndiagnostic device. The results of JLK-NCCT are intended to be used in conjunction with other patient\ninformation and professional judgment to assist with triage and prioritization of medical images. Clinicians\nwho receive notifications are responsible for reviewing full images per the standard of care. JLK-NCCT is\nintended for adults use only.\nLimitations and warnings:\n• All patients should receive appropriate care, including a CT angiography (CTA) and/or relevant treatments\nas part of the standard stroke workup. The device is not intended to rule out any medical conditions,\ntherefore, cases without a “Suspected ICH” or \"Suspected LVO\" notification should not be assumed to\nexclude ICH or LVO. All cases should undergo a CTA as part of the standard stroke workup.\n• The device does not replace the need for CTA or MRA in ischemic stroke workup, it provides workflow\nprioritization and notification only.\nContraindications/Exclusions:\n• Patient Motion: excessive motion leading to artifacts that make the scan technically inadequate.\n• Hemorrhagic Transformation\n• Very thin or no Ventricles","","",""],["Please select the types of uses (select one or both, as\napplicable).","","","?\n."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252421-p5-t0","doc_id":"K252421","page_num":5,"bbox":[97.46,100.36,424.63,632.41],"n_rows":39,"n_cols":3,"columns":["","","K252421"],"rows":[["","","K252421"],["","",""],["ared","on: 2026-02-19",""],["","",""],["act","Details 21 CFR 807.92(a)(1)",""],["","",""],["can","t",""],["","",""],["","Name","JLK, Inc."],["","Address","JLK Tower, 5, Teheran-ro 33-g"],["","","Seoul n/a 06141 Korea, South"],["","Contact Telephone","(+82)1038507933"],["","Contact","Dr. Dongmin Kim"],["","Contact Email","dmkim@jlkgroup.com"],["","",""],["spo","ndent",""],["","",""],["","Name","Hogan Lovells"],["","Address","555 Thirteenth Street NW Wa"],["","","United States"],["","Contact Telephone","(+1)2026373638"],["","Contact","Dr. John Smith"],["","Contact Email","john.smith@hoganlovells.com"],["","",""],["e N","ame 21 CFR 807.92(a)(2)",""],["","",""],["","Device Trade Name","JLK-NCCT"],["","Common Name","Radiological computer aided"],["","","software"],["","Classification Name","Radiological computer aided"],["","","software"],["","Regulation Number","892.2080"],["","Product Code(s)","QAS"],["","",""],["lly M","arketed Predicate Devices 21 CF","R 807.92(a)(3)"],["","",""],["","Predicate #","K222884"],["","Predicate Trade Name","Rapid NCCT Stroke"],["","Product Code","QAS"]],"caption_candidate":"JLK, Inc.’s JLK-NCCT","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252433-p4-t0","doc_id":"K252433","page_num":4,"bbox":[21.03,19.92,593.67,359.56],"n_rows":7,"n_cols":4,"columns":["Indications for Use","","",""],"rows":[["Indications for Use","","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","","K252433","?"],["Please provide the device trade name(s).","","","?"],["Sonio Detect (v3)","","",""],["Please provide your Indications for Use below.","","","?"],["Sonio Detect is intended to analyze fetal ultrasound images and clips using machine learning\ntechniques to automatically detect views, detect anatomical structures within the views and verify\nquality criteria and characteristics of the views.\nThe device is intended for use as a concurrent reading aid during the acquisition and interpretation of fetal\nultrasound images.","","",""],["Please select the types of uses (select one or both, as\napplicable).","","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p5-t0","doc_id":"K252433","page_num":5,"bbox":[72.5,205.5,534.5,428.5],"n_rows":3,"n_cols":2,"columns":["Applicant:","Sonio\n147 rue d’Aboukir,\n75002, Paris France"],"rows":[["Applicant:","Sonio\n147 rue d’Aboukir,\n75002, Paris France"],["Primary Contact Person:","Florian Akpakpa\nDirector Regulatory Affairs and Compliance Officer\nSonio\nPhone: +33 6 66 66 19 89\nEmail: florian.akpakpa@sonio.ai"],["Date Prepared:","February 13, 2026"]],"caption_candidate":"I. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p5-t1","doc_id":"K252433","page_num":5,"bbox":[72.5,493.5,534.5,635.5],"n_rows":4,"n_cols":2,"columns":["Device Trade Name:","Sonio Detect"],"rows":[["Device Trade Name:","Sonio Detect"],["Classification Name:","21 CFR 892.1550 - accessory to Ultrasonic Pulsed Doppler Imaging System\n21 CFR 892.1560 - accessory to Ultrasonic Pulsed Echo Imaging System\n21 CFR 892.2050 - Medical Image Management and Processing System"],["Regulatory Class:","Class II"],["Product Code:","IYN (primary)\nIYO, QIH (Secondary)"]],"caption_candidate":"II. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p7-t0","doc_id":"K252433","page_num":7,"bbox":[72.25,221.8,523.5,764.5],"n_rows":3,"n_cols":2,"columns":["Trimester","View"],"rows":[["Trimester","View"],["First Trimester","1. Choroid Plexus\n2. Profile/Nuchal translucency\n3. Abdominal circumference\n4. Hand\n5. Foot\n6. Crown Rump Length\n7. Doppler 3VT\n8. Lower Arm\n9. Upper Leg\n10. Lower Leg\n11. Doppler 4CH\n12. Adnexa\n13. Ovaries\n14. Umbilical cord insertion"],["Second and Third\ntrimester","1. Transthalamic or Cavum septum pellucidum or Midline\nfalx/Transventricular or Choroid Plexus\n2. Transcerebellar view\n3. Profile\n4. Lips and Nose\n5. Orbits\n6. 4 Chambers\n7. LVOT\n8. Sagittal Spine\n9. Abdominal circumference\n10. Axial Bladder\n11. Axial Kidneys\n12. Cervix/Placenta\n13. Hand\n14. Foot\n15. External genitalia (female or male)\n16. 3 Vessels/3 Vessels and Trachea (3VV)\n17. 3 Vessels and Trachea (3VT)\n18. Doppler 3VT"]],"caption_candidate":"Table 1: List of views per trimester that can be automatically detected by Sonio Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p8-t0","doc_id":"K252433","page_num":8,"bbox":[72.33,74.17,523.5,460.5],"n_rows":2,"n_cols":2,"columns":["Trimester","View"],"rows":[["Trimester","View"],["","19. Humerus\n20. Femur\n21. Radius/Cubitus\n22. Tibia/Fibula\n23. Upper arm\n24. Lower arm\n25. Upper leg\n26. Adnexa\n27. Ovaries\n28. Placenta Cord Insertion\n29. Coronal Face\n30. Doppler 4CH\n31. Umbilical Cord Insertion\n32. Coronal Kidneys\n33. Diaphragm\n34. Maxilla\n35. Mandible\n36. Aortich Arch\n37. Ductal Arch\n38. Bicaval View\n39. Palate\n40. Corpus Callosum"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p9-t0","doc_id":"K252433","page_num":9,"bbox":[74.31,141.53,526.5,761.5],"n_rows":20,"n_cols":4,"columns":["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],"rows":[["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],["Brain views & structures","","",""],["Transthalamic\nTransventricular\nTranscerebellar\nChoroid plexus","Thalami on the transthalamic view","X","X"],["","Cavum septum pellucidum","-","X"],["","Sylvian fissure","-","X"],["","Choroid Plexus","-","X"],["","Cisterna Magna","-","X"],["","Cerebellum","-","X"],["","Vermis","-","X"],["Thorax and Heart views & structures","","",""],["4 chambers\n3VV\n3VT\nRVOT\nLVOT\nAbdominal\ncircumference\nAxial view of the\nkidneys\nDiaphragm\nCrown Rump length\nAbdominal cord\ninsertion","Adrenal gland","-","-"],["","Apex of the heart","-","X"],["","Descending aorta","-","X"],["","Interatrial septum","-","X"],["","Interventricular septum","X","X"],["","Kidneys","-","-"],["","Left atrium","X","X"],["","Left ventricle","X","X"],["","Right atrium","-","X"],["","Right ventricle","-","X"]],"caption_candidate":"Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p10-t0","doc_id":"K252433","page_num":10,"bbox":[74.37,74.23,526.5,761.5],"n_rows":23,"n_cols":4,"columns":["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],"rows":[["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],["","Spine","-","-"],["","Stomach (axial / sagittal)","X","X"],["","Superior vena cava","-","X"],["","Tricuspid valve","-","X"],["","Umbilical vein","-","X"],["","Aorta on LVOT View","-","X"],["","Aorta on RVOT or 3 vessels view","-","X"],["","Pulmonary artery trunk on 3 vessels View","-","X"],["","Pulmonary artery with visible bifurcation","-","X"],["","Portal sinus","-","X"],["","Bowels","X","X"],["","Spleen","-","X"],["","Gallbladder","-","X"],["","Bladder","X","X"],["","Trachea","-","-"],["","Liver","-","X"],["","Lungs","-","X"],["","Ribs","X","X"],["","Sagittal heart","X","-"],["CRL/NT/Profile views & structures","","",""],["CRL\nProfile/NT\nCorpus Callosum","Nasal bone","-","-"],["","Diencephalon","X","-"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p11-t0","doc_id":"K252433","page_num":11,"bbox":[74.33,74.23,526.5,761.5],"n_rows":23,"n_cols":4,"columns":["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],"rows":[["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],["","Fourth ventricle on NT view","X","-"],["","Nuchal translucency","-","-"],["","Palate","X","X"],["","Corpus Callosum","-","-"],["","Liquid space under the chin","X","-"],["","Midbrain tectum","-","-"],["","Choroid plexus on sagittal plane","-","-"],["","Cisterna magna on NT view","X","-"],["","Brainstem on NT view","X","-"],["","Tip of the mandible","-","-"],["Placenta views","","",""],["Placenta / Cervix","Cervix","-","X"],["","Maternal bladder","-","X"],["","Placenta","-","X"],["Spine views","","",""],["Sagittal spine","Cervical Spine","-","X"],["","Lumbar Spine","-","X"],["","Sacral Spine","-","X"],["Facial views","","",""],["Lips and nose\nOrbits\nCoronal face","Lenses","-","-"],["","Orbits","-","X"],["","Nose tip","-","X"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p12-t0","doc_id":"K252433","page_num":12,"bbox":[74.42,74.23,526.5,205.5],"n_rows":4,"n_cols":4,"columns":["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],"rows":[["View name","Structures to be detected","First Trimester\nT1","Second/Third\nTrimesters\nT2/T3"],["","Nare","-","X"],["","Upper lip","-","X"],["","Lower lip","-","X"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p12-t1","doc_id":"K252433","page_num":12,"bbox":[88.5,373.68,507.13,553.5],"n_rows":7,"n_cols":2,"columns":["View name","Structure name"],"rows":[["View name","Structure name"],["Brain views & structures",""],["Choroid plexus","Thalami/cerebral peduncles on axial view"],["Thorax and Heart views & structures",""],["-","Left Ventricle"],["","Left Atrium"],["","Ribs"]],"caption_candidate":"structures.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p13-t0","doc_id":"K252433","page_num":13,"bbox":[73.75,226.3,519.44,381.5],"n_rows":6,"n_cols":3,"columns":["Quality criteria","1st trimester","2nd/3rd Trimester"],"rows":[["Quality criteria","1st trimester","2nd/3rd Trimester"],["Presence of the cavum septum\npellucidum or of the pillars of\nthe fornix","-","X"],["Presence of the cavum septum\npellucidum","-","X"],["Presence of the Sylvian fissure","-","X"],["Absence of the cerebellum","-","X"],["Presence of the thalami","X","X"]],"caption_candidate":"Table 3: List of quality criteria that can be automatically verified by Sonio Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p13-t1","doc_id":"K252433","page_num":13,"bbox":[73.75,460.14,519.44,610.5],"n_rows":5,"n_cols":4,"columns":["View name","Characteristics","First trimester\nT1","Second/Third\nTrimester T2/T3"],"rows":[["View name","Characteristics","First trimester\nT1","Second/Third\nTrimester T2/T3"],["Genitalia view","Male","-","X"],["","Female","-","X"],["Placenta location","Anterior","-","X"],["","Posterior","-","X"]],"caption_candidate":"Table 4 : List of characteristics that can be automatically verified by Sonio Detect","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p14-t0","doc_id":"K252433","page_num":14,"bbox":[72.25,496.22,523.5,692.5],"n_rows":5,"n_cols":3,"columns":["Items","Predicate device: Sonio Detect v2","Proposed device : Sonio Detect v3"],"rows":[["Items","Predicate device: Sonio Detect v2","Proposed device : Sonio Detect v3"],["Manufacturer\nname","Sonio","Sonio"],["Device name","Sonio Detect","Sonio Detect"],["Regulation\nNumber","21 CFR 892.1550 - accessory to\nUltrasonic Pulsed Doppler Imaging\nSystem\n21 CFR 892.1560 - accessory to\nUltrasonic Pulsed Echo Imaging\nSystem\n21 CFR 892.2050 - Medical Image\nManagement and Processing System","21 CFR 892.1550 - accessory to\nUltrasonic Pulsed Doppler Imaging\nSystem\n21 CFR 892.1560 - accessory to\nUltrasonic Pulsed Echo Imaging\nSystem\n21 CFR 892.2050 - Medical Image\nManagement and Processing System"],["Product code","IYN (primary)\nIYO, QIH (Secondary)","IYN (primary)\nIYO, QIH (Secondary)"]],"caption_candidate":"Table 5: Comparison of technological characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p15-t0","doc_id":"K252433","page_num":15,"bbox":[72.33,74.21,523.5,305.5],"n_rows":4,"n_cols":3,"columns":["Items","Predicate device: Sonio Detect v2","Proposed device : Sonio Detect v3"],"rows":[["Items","Predicate device: Sonio Detect v2","Proposed device : Sonio Detect v3"],["Features","- Sonio Detect automatically detects\nviews\n- Sonio Detect automatically detects\nanatomical structures within the\nsupported views\n- Sonio Detect automatically verifies\nthe quality criteria and characteristics\nof the supported views.","- Sonio Detect automatically detect\nviews\n- Sonio Detect automatically detect\nanatomical structures within the\nsupported views\n- Sonio Detect automatically verifies\nthe quality criteria and characteristics\nof the supported views.\n- Sonio Detect automatically localizes\nviews and anatomical structures"],["Algorithm\nMethodology","Artificial Intelligence\nLecture of biometrics\nColorimetry for 3D and Doppler","Artificial Intelligence"],["Platform","Secure cloud-based and stand-alone\nsoftware compatible with ultrasound\nsystem from GE Medical, Samsung,\nCanon and Philips","Secure cloud-based and stand-alone\nsoftware compatible with ultrasound\nsystem from GE Medical, Samsung,\nCanon and Philips"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p17-t0","doc_id":"K252433","page_num":17,"bbox":[72.25,115.68,772.5,489.5],"n_rows":9,"n_cols":3,"columns":["Items (fetal ultrasound views, anatomical structures and characteristics\nautomatically detected)","Sensitivity\nPE (95%CI)","Specificity\nPE (95%CI)"],"rows":[["Items (fetal ultrasound views, anatomical structures and characteristics\nautomatically detected)","Sensitivity\nPE (95%CI)","Specificity\nPE (95%CI)"],["Automatic detection of 14 T1 fetal ultrasound images","0.886 (0.876-0.898)","0.981 (0.979-0.982)"],["Automatic detection of 40 T2/T3 fetal ultrasound images","0.901 (0.896-0.905)","0.993 (0.993-0.994)"],["Automatic localization of 1 view (T1)","mIoU: 0.777 (0.743-0.811)",""],["Automatic detection of 1 fetal brain anatomical structure on the view “Transthalamic” at\nT1","0.815 (0.751-0.871)","0.938 (0.901-0.973)"],["Automatic detection of 7 fetal brain anatomical structures on the views “Transthalamic”,\n“Transventricular”, “Transcerebellar” at T2/T3","0.941 (0.934-0.947)","0.951 (0.943-0.958)"],["Automatic detection of 8 fetal thorax and heart anatomical structures on the views “4\nchambers”, “LVOT”, “RVOT”, “Three vessels”, “Three vessels and trachea”, “Abdominal\nCircumference”, “Axial view of the kidneys”, “Diaphragm”, “Abdominal cord insertion”\nat T1","0.872 (0.848-0.892)","0.921 (0.913-0.928)"],["Automatic detection of 24 fetal thorax and heart anatomical structures on the views “Four\nchambers”, “LVOT”, “RVOT”, “Three vessels”, “Three vessels and trachea”, “Abdominal\nCircumference”, “Axial view of the kidneys”, “Diaphragm”, “Abdominal cord insertion”\nat T2/T3","0.914 (0.906-0.920)","0.963 (0.961-0.965)"],["Automatic detection of 3 fetal placenta anatomical structures on the view “Placenta /\nCervix” at T2/T3","0.887 (0.874-0.899)","0.962 (0.950-0.972)"]],"caption_candidate":"Table 6: results of the standalone performance testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252433-p18-t0","doc_id":"K252433","page_num":18,"bbox":[72.33,74.21,772.5,485.5],"n_rows":11,"n_cols":3,"columns":["Items (fetal ultrasound views, anatomical structures and characteristics\nautomatically detected)","Sensitivity\nPE (95%CI)","Specificity\nPE (95%CI)"],"rows":[["Items (fetal ultrasound views, anatomical structures and characteristics\nautomatically detected)","Sensitivity\nPE (95%CI)","Specificity\nPE (95%CI)"],["Automatic detection of 6 fetal Sagittal Fetus anatomical structures on the views “Crown\nRump Length”, “Profile” at T1","0.869 (0.849-0.896)","0.848 (0.822-0.875)"],["Automatic detection of 1 fetal Sagittal Fetus anatomical structures on the views “Profile”\nat T2/T3","0.883 (0.852-0.913)","0.800 (0.754-0.842)"],["Automatic detection of 5 fetal Coronal Face anatomical structures on the views “Lips and\nnose”, “Orbits”, “Coronal face” at T2/T3","0.922 (0.897-0.947)","0.901 (0.883-0.923)"],["Automatic detection of 3 fetal Spine anatomical structures on the view “Sagittal Spine” at\nT2/T3","0.839 (0.818-0.862)","0.852 (0.829-0.873)"],["Automatic localization of 1 brain anatomical structures (on T1)","mIoU: 0.683 (0.632-0.734)",""],["Automatic localization of 3 thorax and heart anatomical structures (on T1)","mIoU: 0.679 (0.653-0.705)",""],["Automatic detection of the Anterior placenta location for the view “Placenta / Cervix” at\nT2/T3","0.925 (0.894-0.949)","0.918 (0.885-0.948)"],["Automatic detection of the Posterior placenta location for the views “Placenta / Cervix”at\nT2/T3","0.918 (0.885-0.948)","0.925 (0.894-0.949)"],["Automatic detection of the “Female sex” for fetal sex for the view “External Genitalia” at\nT2/T3","1.000 (1.000-1.000)","0.985 (0.969-1.000)"],["Automatic detection of the “Male sex” for fetal sex for the view “External Genitalia” at\nT2/T3","0.985 (0.969-1.000)","1.000 (1.000-1.000)"]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p8-t0","doc_id":"K252452","page_num":8,"bbox":[68.87,150.0,742.62,492.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Product Code","QIH, LLZ","QIH, LLZ","Yes","---"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Yes","---"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","---"],["Intended\nuse/Indications for\nuse","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment are\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of\nplanning the 2D or 3D environment. The","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment are\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of\nplanning the 2D or 3D environment. The","Yes","---"]],"caption_candidate":"Table 1: Summary of Predicate and Subject Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p9-t0","doc_id":"K252452","page_num":9,"bbox":[68.84,112.4,742.71,494.5],"n_rows":8,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","system is designed for the medical\nspecialties within surgery, and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","system is designed for the medical\nspecialties within surgery, and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","",""],["Contraindications","No contraindications specific to this device.","No contraindications specific to this device.","Yes","---"],["Clinical purpose","The PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","The PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","Yes","---"],["Anatomical regions","The PeekMed web allows the surgeon to\nperform pre-surgical planning efficiently in\nthe following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","The PeekMed web allows the surgeon to\nperform pre-surgical planning efficiently in\nthe following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes","—"],["Patient Population","Adults","Adults","Yes","---"],["End users","Healthcare Professionals","Healthcare Professionals","Yes","---"],["Device availability","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run a web","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run a web","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p10-t0","doc_id":"K252452","page_num":10,"bbox":[68.9,112.4,742.71,491.5],"n_rows":12,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","browser","browser","",""],["Software\nArchitecture","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Yes","---"],["Workflow","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","Yes","---"],["Internet connection","Required","Required","Yes","---"],["Images source","Receives medical images from various\nsources","Receives medical images from various\nsources","Yes","---"],["Data processing","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","Yes","---"],["Digital overlap of\ntemplates","Allows the overlap of models and the\nintersection of the models","Allows the overlap of models and the\nintersection of the models","Yes","---"],["Interactive model\npositioning","Yes","Yes","Yes","---"],["Interactive model\ndimensioning","Yes","Yes","Yes","---"],["Model rotation","Yes","Yes","Yes","---"],["Support for digital\nprosthetic","Yes","Yes","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p11-t0","doc_id":"K252452","page_num":11,"bbox":[68.9,112.4,742.71,487.5],"n_rows":9,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["materials provided\nby the\nmanufacturers","","","",""],["Pre-surgical\nplanning","Yes","Yes","Yes","---"],["Type of\npre-surgical\nplanning","Automatic or Manual","Automatic or Manual","Yes","---"],["Contact with the\npatient","No","No","Yes","---"],["Control of life\nsupporting devices","No","No","Yes","---"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","Yes","---"],["Ability to add\nadditional modules\nwhen available","Yes","Yes","Yes","---"],["Automatic bone\nsegmentation","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray, CT scan, and MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray - AP & LAT view, CT scan,\nand MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes","The subject device includes new ML\nmodel variants for the segmentation of\nthe Knee in a Lateral view.\nBoth devices allow planning for the\nknee region with X-rays in an AP view,\nbut the subject device also offers a"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p12-t0","doc_id":"K252452","page_num":12,"bbox":[68.9,112.4,742.67,493.0],"n_rows":3,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","","","","new image perspective (Lateral view).\nThis does not constitute an intended\npurpose update, nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices.\nCompared to the predicate device, the\nsubject device includes updates to\nexisting ML variants and the\nintroduction of new ML variants, such\nas the segmentation and landmarking\nfor the knee region. In addition, certain\npreviously cleared variants have\nundergone updates to improve\nperformance while maintaining the\nsame intended use. These\nmodifications do not alter the overall\nintended use of the device"],["Type of\nlandmarking","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray, CT scan, and MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray - AP & LAT view, CT scan,\nand MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes","The subject device includes new ML\nmodel variants for landmarking for the\nKnee in a Lateral view.\nBoth devices allow planning for the\nknee region with X-rays in an AP view,\nbut the subject device also offers a\nnew image perspective (Lateral view).\nThis does not constitute an intended"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252452-p13-t0","doc_id":"K252452","page_num":13,"bbox":[68.9,112.4,742.59,436.0],"n_rows":2,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","","","","purpose update, nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices.\nCompared to the predicate device, the\nsubject device includes updates to\nexisting ML variants and the introduction\nof new ML variants, such as the\nsegmentation and landmarking for the\nknee region. In addition, certain\npreviously cleared variants have\nundergone updates to improve\nperformance while maintaining the same\nintended use. These modifications do\nnot alter the overall intended use of the\ndevice"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252482-p8-t0","doc_id":"K252482","page_num":8,"bbox":[114.05,169.02,541.45,241.74],"n_rows":4,"n_cols":2,"columns":["Standard","Title of Standard"],"rows":[["Standard","Title of Standard"],["IEC 62304","Software Development Life Cycle"],["21 CFR Part 820","FDA Regulatory Requirements and Design Controls"],["DICOM PS3.1","Digital Image and Communications in Medicine"]],"caption_candidate":"Table 1: Standards Applied","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252482-p9-t0","doc_id":"K252482","page_num":9,"bbox":[72.47,0.42,585.43,712.14],"n_rows":16,"n_cols":4,"columns":["","New Device","Predicate Device (1)",""],"rows":[["","New Device","Predicate Device (1)",""],["","","",""],["","","",""],["Trade Name","CogNet AI-MT+","CogNet QmTRIAGE",""],["","","",""],["510(k) Submitter","510(K) Summary\nMedCognetics","MedCognetics",""],["","","","Status"],["[Number]","[K252482]","[K220080]",""],["Indication for\nUse","The MedCognetics CogNet AI-MT+\nsoftware is a passive notification\nfor prioritization- only, parallel-\nworkflow software tool used by\nMQSA qualified interpreting\nphysicians to prioritize patients with\nsuspicious findings in a medical\ncare environment. CogNet AI- MT+\nutilizes an artificial intelligence\nalgorithm to analyze DBT\nscreening mammograms and flags\nthose that are suggestive of the\npresence of at least one suspicious\nfinding at the exam level. CogNet\nAI-MT+ produces an exam level\noutput to a PACS/Workstation for\nflagging the suspicious study and\nallows for worklist prioritization.\nMQSA qualified interpreting\nphysicians are responsible for\nreviewing each exam on a display\napproved for use in\nmammography, according to the\ncurrent standard of care. The\nCogNet AI-MT+ device is limited to\nthe categorization of exams, does\nnot provide any diagnostic\ninformation beyond triage and\nprioritization, does not remove\nimages from the interpreting\nphysician’s worklist, and should not\nbe used in lieu of full patient\nevaluation, or relied upon to make\nor confirm diagnosis.\nThe CogNet AI-MT+ device is\nintended for use with DBT\nmammography exams acquired\nusing validated equipment systems,\nonly.","The MedCognetics (CogNet)\nQmTRIAGE software is a passive\nnotification for prioritization only,\nparallel workflow software tool used\nby MQSA qualified interpre-ting\nphysicia-ns to prioritize patients with\nsuspicious findings in the medical care\nenvironment.\nQmTRIAGE utilizes an artificial\nintelligence algorithm to analyze 2D\nFFDM screening mammograms and\nflags those that are suggestive of the\npresence of at least one suspicious\nfinding at the exam level.\nQmTRIAGE produces an exam level\noutput to a PACS/Workstation for\nflagging suspicious study and allows\nfor worklist prioritization.\nMQSA qualified interpreting\nphysicians are responsible for\nreviewing each exam on a display\napproved for use in mammography,\naccording to the current standard of\ncare. The QmTRIAGE device is\nlimited to the categorization of\nexams, does not provide any\ndiagnostic information beyond triage\nand prioritization, does not remove\nimages from the interpreting\nphysician’s worklist, and should not\nbe used in lieu of full patient\nevaluation, or relied upon to make or\nconfirm diagnosis.\nThe QmTRIAGE device is intended for\nuse with 2D FFDM mammography\nexams acquired using validated FFDM\nsystems, only.","Similar"],["Product Code(s)","QFM","QFM","Same"],["Regulation(s)","892.2080","892.2080","Same"],["Notification Only","Yes","Yes","Same"],["Parallel Workflow","Yes","Yes","Same"],["User","MQSA Interpreting physician","MQSA Interpreting physician","Same"],["Alert to finding","Yes.\nPassive notification flagged for\nreview","Yes.\nPassive notification flagged for review","Same"],["Independent of SoC\nworkflow","Yes.\nNo cases are removed from","Yes.\nNo cases are removed from worklist","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252482-p10-t0","doc_id":"K252482","page_num":10,"bbox":[74.02,64.98,585.74,669.6],"n_rows":20,"n_cols":4,"columns":["","New Device","Predicate Device (1)",""],"rows":[["","New Device","Predicate Device (1)",""],["","","",""],["","","",""],["Trade Name","CogNet AI-MT+","CogNet QmTRIAGE",""],["","","",""],["510(k) Submitter","MedCognetics","MedCognetics",""],["","","","Status"],["[Number]","[K252482]","[K220080]",""],["","worklist","",""],["Modality","DBT screening mammograms","FFDM screening mammograms","Different"],["Equipment\nManufacturer","Hologic","Hologic","Same"],["Body Part","Breast","Breast","Same"],["AI algorithm","Yes","Yes","Same"],["Limited to analysis of\nimaging data","Yes","Yes","Same"],["Inclusion\nCriteria","• Standard DBT\nscreening mammograms\n• Biopsy proven cancer\nstudies (soft tissues and\nmicrocalcifications)\n• BIRADS 1 and 2 normal/benign\ncases with 2 year follow up of a\nnegative diagnosis\n• Female patie-n ts 22 and o-lder\n• Bilateral Studies with 4\nstandard views (LCC, LMLO,\nRCC, RMLO)","• Standard 2D FFDM\nscreening\nmammograms\n• Biopsy proven cancer studies\n(soft tissues and\nmicrocalcifications)\n• BIRADS 1 and 2 normal/benign\ncases with 2 year follow up of a\nnegative diagnosis\n• Female patien-ts 22 and old-er\n• Bilateral Studies with 4 standard\nviews (LCC, LMLO, RCC, RMLO)","Different"],["Aids in prompt\nidentification of\ncases with\nindicated findings","Yes","Yes","Same"],["Results Preview","Secondary Capture stored with\noriginal DICOM study and may be\nviewed with the study. The device\noperates in parallel with the\nstandard of care, which remains\nthe default option.","Encapsulated PDF stored with\noriginal DICOM study and may be\ndownloaded and viewed as a PDF.\nThe device operates in parallel with\nthe standard of care, which remains\nthe default option.","Different"],["Deployment","Cloud based","Cloud based","Same"],["Where results are\nreceived","PACS / Workstation","PACS / Workstation","Same"],["Patient Contact","No direct or indirect\ncontact","No direct or indirect contact","Same"]],"caption_candidate":"510(K) Summary: K252482","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252482-p11-t0","doc_id":"K252482","page_num":11,"bbox":[72.51,73.92,585.39,176.64],"n_rows":10,"n_cols":4,"columns":["","New Device","Predicate Device (1)",""],"rows":[["","New Device","Predicate Device (1)",""],["","","",""],["","","",""],["Trade Name","CogNet AI-MT+","CogNet QmTRIAGE",""],["","","",""],["510(k) Submitter","MedCognetics","MedCognetics",""],["","","","Status"],["[Number]","[K252482]","[K220080]",""],["Cleaning","Not applicable","Not applicable","Same"],["Sterilization","Not applicable","Not applicable","Same"]],"caption_candidate":"510(K) Summary: K252482","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252482-p11-t1","doc_id":"K252482","page_num":11,"bbox":[138.96,457.02,509.04,677.7],"n_rows":9,"n_cols":4,"columns":["Region","Total Patients","Positives","Negatives"],"rows":[["Region","Total Patients","Positives","Negatives"],["Europe","2,372","40","2,332"],["South Asia","126","125","1"],["South America","4,066","577","3,489"],["South Asia","1,024","374","650"],["Europe","23,036","8,651","14,385"],["Africa","102","6","96"],["United States","1,566","723","843"],["Totals","32,292\n(≈ 129,168 images)","10,496\n(≈ 41,984 images)","21,796\n(≈ 87,184 images)"]],"caption_candidate":"training set of modalities is beneficial to improving generalization.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252496-p5-t0","doc_id":"K252496","page_num":5,"bbox":[86.25,444.44,518.52,604.44],"n_rows":21,"n_cols":4,"columns":["","","","K252496"],"rows":[["","","","K252496"],["","510(k) Number","",""],["","","",""],["","","","Neurophet AQUA AD Plus"],["","Trade/Device/Model Name","",""],["","","",""],["","","","Automated Radiological Image Processing Software"],["","Device Classification Name","",""],["","","",""],["","","","21 CFR 892.2050"],["","Regulation Number","",""],["","","",""],["","","","QIH (primary), LLZ (subsequent)"],["","Classification Product Code","",""],["","","",""],["","","","Class II"],["","Device Class","",""],["","","",""],["","","","Radiology"],["","510(k) Review Panel","",""],["","","",""]],"caption_candidate":"3.Identification of Proposed Device(s) [21 CFR 807.92(a)(2)]","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252496-p6-t0","doc_id":"K252496","page_num":6,"bbox":[86.25,138.8,505.08,304.8],"n_rows":21,"n_cols":4,"columns":["","","","K241098"],"rows":[["","","","K241098"],["","510(k) Number","",""],["","","",""],["","","","NeuroQuant"],["","Trade/Device/Model Name","",""],["","","",""],["","","","Automated Radiological Image Processing Software"],["","Device Classification Name","",""],["","","",""],["","","","892.2050"],["","Regulation Number","",""],["","","",""],["","","","QIH (primary), LLZ (subsequent)"],["","Classification Product Code","",""],["","","",""],["","","","Class II"],["","Device Class","",""],["","","",""],["","","","Radiology"],["","510(k) Review Panel","",""],["","","",""]],"caption_candidate":"- Predicate device #1","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252496-p6-t1","doc_id":"K252496","page_num":6,"bbox":[86.25,347.12,505.08,513.02],"n_rows":21,"n_cols":4,"columns":["","","","K221405"],"rows":[["","","","K221405"],["","510(k) Number","",""],["","","",""],["","","","SCALE PET"],["","Trade/Device/Model Name","",""],["","","",""],["","","","Medical image management and processing system"],["","Device Classification Name","",""],["","","",""],["","","","892.2050"],["","Regulation Number","",""],["","","",""],["","","","LLZ"],["","Classification Product Code","",""],["","","",""],["","","","Class II"],["","Device Class","",""],["","","",""],["","","","Radiology"],["","510(k) Review Panel","",""],["","","",""]],"caption_candidate":"- Predicate device #2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252500-p8-t0","doc_id":"K252500","page_num":8,"bbox":[72.37,206.92,522.91,768.0],"n_rows":8,"n_cols":6,"columns":["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],"rows":[["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],["","","","Cydar EV Maps","","Comments"],["","","","(predicate device)","",""],["510(k) Number","K252500","K212442","","",""],["Regulation","21 CFR 892.1650","21 CFR 892.1650","","","Identical"],["Regulatory Class","Class II","Class II","","","Identical"],["Product Code","OWB","OWB","","","Identical"],["Intended Use/\nIndications for Use","The Cara System is intended\nfor preplanning and\nguidance of medical\ninterventions in an area\nknown to contain or be\nadjacent to the cardiac\nconduction system, such as\npercutaneous or surgical\nprocedures, for example,\ntranscatheter aortic valve\nreplacement (TAVR), as well\nas medical procedures\nwhere the physician desires\nto deliver therapy to the\npatient's cardiac conduction\nsystem or to a targeted\nlocation within it (CSP).\nThe Cara System uses\ncomputed tomography\nangiography (CTA)-based\nand user manually marked\nlandmarks to identify the\ncardiac conduction axis\nand generate a three-\ndimensional (3D) map of\nthe individual patient’s\ncardiac conduction system.\nThe system also overlays\nthe anatomical location of\nthe cardiac conduction\nsystem (generated by the\nCara Metis Simulator using\npre-procedure CT data)\nonto live fluoroscopic\nimages.","Cydar EV provides tools to:\n• Import and visualise CT\ndata\n• Segment and annotate\nvascular anatomy from\nCT data\n• Place and edit virtual\nguidewires and measure\nlengths on them\n• Make measurements of\nanatomical structures on\nplanar sections of the CT\ndata\n• Produce an operative\nplan from\nmeasurements and\nsegmentation of\npreoperative vessel\nanatomy\n• Overlay planning\ninformation such as\npreoperative vessel\nanatomy onto live\nfluoroscopic images,\naligned\n• based on the position of\nanatomical features\npresent in both\n• Non-rigidly transform\nthe visualisation of\nanatomy when intra-\noperative vessel\ndeformation is observed\n• Post-operatively\nreview data relating to\nprocedures where the\nsystem was used\nCydar EV is intended to assist\nfluoroscopic X-ray guided\nendovascular procedures in\nthe chest, abdomen, and","","","Substantially equivalent.\nBoth devices utilize the\nsame fundamental\ntechnology (CT-to-\nfluoroscopy overlay).\nThe anatomical focus\ndifference (cardiac\nconduction system vs.\ngeneral vasculature)\nrepresents a subset\napplication that does not\nintroduce new safety or\neffectiveness concerns, as\nboth rely on identical image\nregistration within the\nvascular system and overlay\nprinciples."]],"caption_candidate":"Substantial Equivalence Comparison Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252500-p9-t0","doc_id":"K252500","page_num":9,"bbox":[72.37,72.91,522.92,767.04],"n_rows":9,"n_cols":6,"columns":["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],"rows":[["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],["","","","Cydar EV Maps","","Comments"],["","","","(predicate device)","",""],["","The software utilizes AI/ML\nalgorithms to provide OCR\ndetection, automated\nsegmentation of anatomical\nstructures, and detection of\ncatheters.\nThe CARA System is\nintended for use in adult\npatients (18 years of age\nand older).","pelvis by presenting the\noperative plan in the context\nof intraoperative fluoroscopy.\nCydar EV is intended to be\nused for patients undergoing\na fluoroscopic X-ray guided\nendovascular surgery in the\nchest abdomen and pelvis,\nand who have had a pre-\noperative CT-scan.\nThe performance of the Cydar\nEV software in the presence\nof immature vertebral\nanatomy is unknown. The\nInstructions for Use explicitly\nstate this uncertainty and that\nthe software is therefore not\nrecommended for use in\npatients under the age of 18.\nIMPORTANT: Pre-\nOperative Maps show static\nanatomy derived from the\npre-operative CT. Real-time\nanatomy moves with the\ncardiorespiratory cycle;\nprogressive disease may\ncause the anatomy to change\nover time; and stiff wires,\nstents or other surgical\ninstruments, may straighten\nand displace blood vessels\nfrom the preoperative\nposition\nIt is therefore mandatory to\ncheck the real-time anatomy\nwith a suitable imaging\ntechnique, such as contrast\nangiography, before\ndeploying any invasive\nm edical device.","","",""],["User Population","Patients above the age of 18","Patients above the age of 18","","","Identical"],["Environment of Use","Operating room, office\n(during planning)","Operating room, office\n(during planning)","","","Identical"],["Major Components","Standard workstation (Cara\nBox)\nStandard Fluoroscopy\nsplitter\nStandard Monitor","Standard workstation\nStandard Fluoroscopy splitter","","","Similar, both use standard\nhardware; the addition of a\nstandard commercially\navailable monitor for the\nCara Medical System does\nnot raise new questions of\nsafety or effectiveness."],["Interface to Image\nSources","Local DICOM files","Local DICOM files or distant\nPACS server.","","","Similar, both systems\naccept DICOM files and\nprovide comparable image\nsource integration."],["Import of Patient\nData","Via DICOM imaging files","Via DICOM or PACS\nimaging files","","","Similar, both systems\nimport patient data from"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252500-p10-t0","doc_id":"K252500","page_num":10,"bbox":[72.37,72.91,522.93,765.36],"n_rows":13,"n_cols":6,"columns":["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],"rows":[["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],["","","","Cydar EV Maps","","Comments"],["","","","(predicate device)","",""],["","","","","","DICOM or PACS files with no\nfunctional differences\nimpacting safety or\neffectiveness."],["List Image\nFunctionality","Segment and annotate\ncardio-vascular anatomy\nfrom CT data","Segment and annotate vascular\nanatomy from CT data","","","Same"],["Anatomical Region","Cardiac conduction system","General vasculature","","","Similar; while these devices\ntarget different regions,\nthey are both designed to\nsegment and annotate\nvascular anatomy."],["Image Processing","Place and edit anatomical\nlandmarks and Make\nmeasurements of\nanatomical structures on\nplanar sections of the CT\ndata.","Place and edit virtual\nguidewires and measure\nlengths on them Make\nmeasurements of anatomical\nstructures on planar sections of\nthe CT data.","","","Same"],["Image and 3D\nDisplay","Overlay planning\ninformation onto live\nfluoroscopic images, aligned\nbased on the position of\nanatomical features and/or\ncatheters present in both.","Overlay planning information\nsuch as preoperative vessel\nanatomy onto live fluoroscopic\nimages, aligned based on the\nposition of anatomical features\npresent in both.","","","Similar, both systems\noverlay planning\ninformation onto\nfluoroscopic images based\non anatomical alignment,\nwith no differences\naffecting the intended\npurpose."],["DICOM Support","Import DICOM files","Import DICOM files","","","Identical"],["Preoperational\nPlanning","Import and visualize CT\ndata; Segment and annotate\ncardio-vascular anatomy\nfrom CT data; Place and edit\nanatomical landmarks;\nMake measurements of\nanatomical structures on\nplanar sections of the CT\ndata; Visualize the\nsegmented cardio-vascular\nanatomy.","Import and visualize CT data;\nSegment and annotate vascular\nanatomy from CT data; Place\nand edit virtual guidewires and\nmeasure lengths on them;\nMake measurements of\nanatomical structures on\nplanar sections of the CT data;\nVisualize the segmented\nvascular anatomy, annotations\n+/-\nmeasurements together (the\n‘Operative Plan’)","","","Similar, both systems\nsupport CT-based\npreoperative planning with\nannotation and\nmeasurement tools.\nDifferences reflect clinical\nfocus but do not alter core\nfunctionality or intended\nuse."],["Patient Contact","No","No","","","Identical"],["Human Intervention\nfor Interpretation of\nImages","Yes\nThe information and\nmeasurements displayed,\nexported or printed are\nvalidated and interpreted by\nPhysicians.","Yes\nThe information and\nmeasurements displayed,\nexported or printed are\nvalidated and interpreted by\nPhysicians.","","","Identical"],["Functionality","Generates a detailed 3D\nmodel of the patient's\ncardiac conduction system\ntailored to planned\nprocedure.\nOverlays the personalized\nanatomical location of the","Intra-operative (Fusion imaging\nfunctions): Overlay planning\ninformation such as\npreoperative vessel anatomy\nonto live fluoroscopic images,\naligned based on the position\nof anatomical features present\nin both; Non-rigidly transform","","","Similar, both systems\noverlay anatomical models\nonto live fluoroscopy based\non shared landmarks.\nDifferences reflect clinical\napplication but maintain\nthe same core imaging\nguidance function."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252500-p11-t0","doc_id":"K252500","page_num":11,"bbox":[72.39,72.91,522.87,362.16],"n_rows":5,"n_cols":6,"columns":["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],"rows":[["Feature","Cara Medical System\n(subject device)","","Cydar EV (Series B) and","",""],["","","","Cydar EV Maps","","Comments"],["","","","(predicate device)","",""],["","cardiac conduction system\nonto live fluoroscopic\nimages.","the visualization of anatomy\nwhen intra-operative vessel\ndeformation is observed.\nPost-operative (Review\nfunctions): Postoperatively\nreview data relating to\nprocedures where the system\nwas used.","","",""],["AI / ML\nSegmentation and\nImage Processing","AI/ML algorithms are used\nfor OCR metadata\nextraction, automated CT-\nbased anatomical\nsegmentation and\nfluoroscopic device\ndetection. Outputs require\nphysician review prior to\nclinical use.","Utilizes deep learning\nalgorithms for CT-based\nvascular segmentation and\nautomated volume analysis.\nFluoroscopic image registration\nand overlay are performed\nusing image processing and\ntracking methods as described\nin the User Manual.","","","Both devices incorporate\nautomated CT-based\nsegmentation and image\nregistration technologies to\ngenerate 3D anatomical\nmodels and support\nfluoroscopic overlay.\nDifferences relate to\nanatomical target and\nalgorithm implementation\nand do not alter the\nfundamental technological\nprinciples."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252500-p15-t0","doc_id":"K252500","page_num":15,"bbox":[72.26,521.88,523.06,768.36],"n_rows":7,"n_cols":11,"columns":["Feature","Intended\nFunction","","Test","","","Ground","","Primary\nMetric","Acceptance\nCriteria","Results"],"rows":[["Feature","Intended\nFunction","","Test","","","Ground","","Primary\nMetric","Acceptance\nCriteria","Results"],["","","","Dataset","","","Truth","","","",""],["","","","(n)","","","Method","","","",""],["Optical\nCharacter\nRecognition\n(OCR)","Extraction of\nfluoroscopic\nmetadata","61\nfluoroscopic\nimages","","","Manual\nverification of\nextracted\nparameters","","","Error rate","0 errors (≤5%\nupper 95% CI\nbound)","0 failures\nobserved"],["Anatomical\nSegmentation\n(Cardiac\nChambers)","CT-based 3D\nanatomical\nmodel\ngeneration","50\nretrospective\nCT scans","","","Manual\nsegmentation\nby trained\ntechnologists\nwith physician\nadjudication","","","Dice\nSimilarity\nCoefficient;\nAverage\nSurface\nDistance","DSC ≥ 0.85;\nASD ≤ 1.5 mm","All\nevaluated\nstructures\nmet\ncriteria"],["Aortic\nSegmentation","Fluoroscopic\naortic\nsegmentation\nfor\nregistration","480\nfluoroscopic\nimages","","","Manual\ncontour\nannotation\nwith physician\nadjudication","","","Dice\nSimilarity\nCoefficient","DSC ≥ 0.85","Mean\nDSC =\n0.962"],["Catheter &\nLead\nDetection","Distal tip\nlocalization","2,139\nfluoroscopic\nimages","","","Manual distal\ntip annotation","","","Median\ndistal tip","≤ 0.9 mm","All\nevaluated\ncatheter"]],"caption_candidate":"AI/ML Performance Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252538-p10-t0","doc_id":"K252538","page_num":10,"bbox":[90.25,268.88,587.37,739.5],"n_rows":9,"n_cols":4,"columns":["Parameter","CEPHX3D","Relu Creator\n(K233925)","Comparison"],"rows":[["Parameter","CEPHX3D","Relu Creator\n(K233925)","Comparison"],["Platform","Web\napplication","Web\napplication","Same"],["User Interface","Graphical user\ninterface","Graphical user\ninterface","Same"],["Component","Web\napplication","Web\napplication","Same"],["Input Data\nTypes","CBCT images","CBCT, intraoral\nscans (IOS),\nfacial scans (FS)","Similar – Both use CBCT as the primary input.\nCEPHX3D’s exclusive use of CBCT aligns with its\nvalidated scope and does not affect safety or\neffectiveness. See Section 8."],["Output Data\nFormats","STL, DICOM","STL, DICOM,\nPLY, OBJ","Similar – Both share STL and DICOM, sufficient\nfor treatment planning. Relu Creator’s\nadditional PLY and OBJ formats are optional\nand do not impact safety or effectiveness. See\nSection 8."],["Image\nMeasurement\nTools","Distance\nmeasurement\ns","Distance\nmeasurements","Same"],["Image Viewing","3D viewing\nand editing","3D viewing and\nediting","Same"],["Image\nManipulation","Brightness/co\nntrast\nadjustment","Brightness/\ncontrast\nadjustment","Same"]],"caption_candidate":"Table 1: Comparison of Technological Characteristics with Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252538-p11-t0","doc_id":"K252538","page_num":11,"bbox":[90.25,102.17,587.37,463.5],"n_rows":7,"n_cols":4,"columns":["Parameter","CEPHX3D","Relu Creator\n(K233925)","Comparison"],"rows":[["Parameter","CEPHX3D","Relu Creator\n(K233925)","Comparison"],["Image\nAnnotation","Available","Available","Same"],["Treatment\nPlanning &\nSimulation","3D simulation","3D simulation","Same"],["Supported\nAnatomical\nArea","Dental,\nmaxilla,\nmandible,\nairway","Dental, maxilla,\nmandible,\nairway","Same"],["Key Differences in Technological Characteristics","","",""],["Data Storage &\nTransfer","Relies on\nParent System\n(AWS)","Integrated\nStorage","Different, See Section 8."],["Image\nProcessing\nFocus","Processes and\ndisplays digital\nimages\n(AI-driven)","Displays and\nenhances\ndigital images","CEPHX3D emphasizes AI processing; Relu\nCreator prioritizes enhancement. Both achieve\ncomparable 3D modeling outcomes. See\nSection 8."]],"caption_candidate":"05/MAR/2026","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252539-p7-t0","doc_id":"K252539","page_num":7,"bbox":[72.25,308.78,550.5,703.5],"n_rows":14,"n_cols":3,"columns":["Characteristic","Predicate Device\n(Arterys MICA K203744)","Subject Device\n(Tempus Pixel)"],"rows":[["Characteristic","Predicate Device\n(Arterys MICA K203744)","Subject Device\n(Tempus Pixel)"],["Intended Use","Intended to be used as a support tool by trained\nhealthcare professionals to aid in diagnosis. It is\nintended to provide image and related\ninformation that is interpreted by a trained\nprofessional to render findings and/or\ndiagnosis.","Same"],["Intended Patient\nPopulation","Pediatric (neonate, infant, child and adolescent)\nand adult populations. For Pixel Lung only, the\nlung detection module is intended for the\nasymptomatic patient population 18 years of\nage and older.","Same"],["Rx / OTC","Rx Only","Same"],["Type of scans","Viewer/Pixel: Supported DICOM modalities\nCardio: MR\nOnco/Therapy Response Evaluation: MR and CT","Same"],["Image upload\nand storage","Yes. DICOMweb and legacy upload methods.\nJPEG and JPEG 2000 image compression.","Same"],["Studylist with\nfilter and\nsearching","Yes","Same"],["Image display\nand layouts","Yes, including 2D, 3D, MIP, MPR display and\nnumerous layout options.","Same"],["Image navigation\ntools","Pan, zoom, rotate, slice/time scroll, W/L, slab\nthickness, cine, flow direction, flip, W/L invert &\npresets.","Same"],["View DICOM\nmetadata","Patient, study, orientation, and pixel information.","Same"],["Measuring tools","Yes - linear, area, and volume.","Same"],["Display results of\nAI models","Arterys and 3rd party AI models.","Same"],["Reporting","All modules. Secondary captures. Dictation\nintegration.","Same"],["Cardiac views","Yes - automatically identified + user editable","Same"]],"caption_candidate":"Table 1. Comparison of Key Technological Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252539-p8-t0","doc_id":"K252539","page_num":8,"bbox":[72.33,92.82,550.5,451.5],"n_rows":9,"n_cols":3,"columns":["Characteristic","Predicate Device\n(Arterys MICA K203744)","Subject Device\n(Tempus Pixel)"],"rows":[["Characteristic","Predicate Device\n(Arterys MICA K203744)","Subject Device\n(Tempus Pixel)"],["Ventricular\nfunction","For short-axis stack. Automatically identified +\nuser editable.","Same"],["Cardio\nvisualization and\nquantification","Yes. 2D phase contrast, 4D flow, perfusion,\ndelayed enhancement, T1, T2, and T2*\nworkflows. Editable flow correction mask using\nML model.","Same"],["T1 and T2","For T1, the contouring of the LV Endo and LV Epi\ncan be obtained automatically using a deep\nlearning model or can be drawn manually by the\nuser. For T2, the user can manually contour the\nmyocardium structures using the same tools.\nEach step of the workflow for each of these\nfeatures can be reviewed and edited by the user.\nT1 and T2 maps are limited to user-defined\nregions of interest (ROIs) within the\nmyocardium and the left ventricle blood pool on\nthe original (raw) T1 and T2 series.","For T1, the contouring of the LV Endo and LV Epi\ncan be obtained automatically using a deep\nlearning model or can be drawn manually by the\nuser. For T2, the user can manually contour the\nmyocardium structures using the same tools.\nEach step of the workflow for each of these\nfeatures can be reviewed and edited by the user.\nFull device-generated T1 and T2 inline map\nfunctionality. One generated inline map is\nproduced for each slice of the raw input series."],["Cardio reporting","Yes, with numerous content configurations by\nuser.","Same"],["Oncology nodule\nmodification","Yes, with editing, creating, deleting, with sorting\noptions for list of nodules.","Same"],["Oncology\nlongitudinal\ntracking","Yes, with a graphical display. Improved workflow\nand linking.","Same"],["Oncology\nreporting -\nLung-RADS","Yes","Same"],["Machine-based\nlearning models","Locked/Static","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252539-p9-t0","doc_id":"K252539","page_num":9,"bbox":[72.25,128.84,730.5,507.5],"n_rows":2,"n_cols":4,"columns":["Test","Summary of Methods","Acceptance Criteria","Results"],"rows":[["Test","Summary of Methods","Acceptance Criteria","Results"],["T1/T2 Inline Map\nValidation","Validation was performed by comparing the Tempus Pixel\ngenerated inline maps to maps generated from FDA-cleared\nMR scanners using the same input series. For each test\nseries, the Pixel inline map was compared to the MR scanner\ngenerated inline map by placing a minimum of four regions\nof interest (ROI) on different parts of the myocardium.\nSample Size:\nT1: 30 series spread evenly across manufacturer and\nscanner type. There were 4 ROIs assessed per series,\nresulting in a total of 120 ROIs for T1.\nT2: 30 series spread evenly across manufacturer and\nscanner type. There were 4 ROIs assessed per series,\nresulting in a total of 120 ROIs for T2.\nFDA-cleared scanners used for comparison included:\nGE 1.5T\nSigna HDxt, SIGNA Artist,\nSIGNA Voyager, Optima MR450\nGE 3T\nSIGNA Premier, DISCOVERY MR750w, SIGNA Pioneer\nPhilips 1.5T\nIngenia Ambition X, Achieva\nPhilips 3T\nIngenia Elition X, Ingenia\nSiemens 1.5T\nMAGNETOM Sola, MAGNETOM Aera\nSiemens 3T\nMAGNETOM Vida, MAGNETOM Skyra","T1: The 95th percentile deviation\n(absolute error) between the Tempus\nPixel inline maps and scanner generated\ninline maps, as assessed across means\nfrom all 120 ROIs, must be within the\nrange from -30ms to +30ms. All\nmeasurements must be within 1.5 times\nthis range (-45ms to +45ms).\nT2: The 95th percentile deviation\n(absolute error) between the Tempus\nPixel inline maps and scanner generated\ninline maps, as assessed across means\nfrom all 120 ROIs, must be within the\nrange from -3ms to +3ms. All\nmeasurements must be within 1.5 times\nthis range (-4.5ms to +4.5ms).","T1: Across all 120 ROIs\n● Mean absolute error = 4.76 ms\n● 95th percentile absolute error =\n13.82 ms\n● Max absolute error = 28.57 ms\nPASS\nT2: Across all 120 ROIs\n● Mean absolute error = 0.85 ms\n● 95th percentile absolute error =\n2.48 ms\n● Max absolute error = 2.97 ms\nPASS"]],"caption_candidate":"Table 2. Summary of Non-Clinical Studies - Methods and Results","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252539-p10-t0","doc_id":"K252539","page_num":10,"bbox":[72.33,92.84,730.5,414.5],"n_rows":3,"n_cols":4,"columns":["Test","Summary of Methods","Acceptance Criteria","Results"],"rows":[["Test","Summary of Methods","Acceptance Criteria","Results"],["Human\nFactors/Design\nValidation","The Pixel user interface remains largely identical for the new\nT1/T2 inline mapping as compared to that for T1/T2 ROI\nmapping in the predicate device. As a conservative measure,\na limited-scope external validation of T1 and T2 inline map\ngeneration was conducted by three physicians experienced\nin assessing and quantifying parametric mapping data within\nPixel Cardio software. The physicians were instructed to\nopen studies, find automatically generated inline maps,\ncreate new inline maps and locate them in the series list.","● When a study with a parametric\nmapping raw data series (T1/T2) is\nopened, there will automatically be an\ninline map generated by Tempus\nlocated in the series list within the\nstudy.\n● When the user loads a parametric\nmapping raw data series into the\nviewer and opens the corresponding\nmodule, they will have the option to\ngenerate a new inline map.\n● When the user generates a new inline\nmap, the inline map will populate\nwithin the series list and will have a\ndistinct series description.\n● Users are able to quantify T1/T2\nvalues from the Pixel generated inline\nmap and verify these values against\nexpected anatomical/ pathological\nfindings.","PASS. No deviations or unexpected\nResults."],["Software\nVerification","Software unit and system verification testing for the T1/T2\ninline mapping was performed in accordance with Arterys\nsoftware design control procedures.","All test cases were required to meet\npre-established expected software\noutputs.","PASS. All testing passed and no\nnew anomalies were identified."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252557-p5-t0","doc_id":"K252557","page_num":5,"bbox":[93.48,175.62,504.48,337.62],"n_rows":4,"n_cols":2,"columns":["Manufacturer:","Philips Ultrasound LLC\n22100 Bothell Everett Hwy\nBothell, WA 98021-8431"],"rows":[["Manufacturer:","Philips Ultrasound LLC\n22100 Bothell Everett Hwy\nBothell, WA 98021-8431"],["Contact Person:","Gina Quiram\nPrincipal Regulatory Affairs Specialist\ngina.quiram@philips.com\nPhone: 1-310-745-2695"],["Secondary Contact:","Priscilla Herpai\nSenior Regulatory Affairs Manager\nPriscilla.Herpai@philips.com\nPhone: 1-610-533-7984"],["Date Prepared:","July 30, 2025"]],"caption_candidate":"1. Submitter’s name, address, telephone number, contact person(s)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252557-p5-t1","doc_id":"K252557","page_num":5,"bbox":[208.86,456.94,557.72,600.18],"n_rows":8,"n_cols":6,"columns":["Classification Description","","21 CFR Section","","Product",""],"rows":[["Classification Description","","21 CFR Section","","Product",""],["","","","","Code",""],["","Primary","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","892.1550","IYN","",""],["","Secondary","","","",""],["System, imaging, pulsed echo,\nultrasonic","","892.1560","IYO","",""],["Transducer, ultrasonic, diagnostic","","892.1570","ITX","",""],["Automated Radiological Image\nProcessing Software","","892.2050","QIH","",""]],"caption_candidate":"Common Name: Diagnostic ultrasound system and transducers","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252557-p10-t0","doc_id":"K252557","page_num":10,"bbox":[72.38,230.88,583.4,701.25],"n_rows":16,"n_cols":4,"columns":["Standard","Lumify","Lumify Diagnostic","Comparison"],"rows":[["Standard","Lumify","Lumify Diagnostic","Comparison"],["Feature","Diagnostic","Ultrasound System",""],["","Ultrasound","K223771",""],["","System","(Predicate Device)",""],["","K# (K252557)","",""],["","(Subject Device)","",""],["Scientific","Ultrasound Imaging","Ultrasound Imaging","Remains unchanged"],["Technology","","",""],["Intended use","Philips Lumify Diagnostic\nUltrasound System is\nintended for diagnostic\nultrasound imaging in B(2D),\nColor Doppler, Combined\n(B+Color), Pulsed Wave\nDoppler, and M-modes.","Philips Lumify Diagnostic\nUltrasound System is intended\nfor diagnostic ultrasound\nimaging in B(2D), Color\nDoppler, Combined\n(B+Color), Pulsed Wave\nDoppler, and M-modes.","Remains unchanged"],["","","",""],["Indications for","Lumify Diagnostic\nUltrasound System is\nindicated for diagnostic\nultrasound imaging and fluid\nflow analysis in the following\napplications:\nFetal/Obstetric, Abdominal,\nPediatric, Cephalic, Urology,\nGynecological, Cardiac Fetal\nEcho, Small Organ,\nMusculoskeletal, Peripheral\nVessel, Carotid, Cardiac, Lung.\nThe Lumify system is a\ntransportable ultrasound\nsystem intended for use in\nenvironments where healthcare\nis provided by healthcare\nprofessionals.","Lumify Diagnostic\nUltrasound System is\nindicated for diagnostic\nultrasound imaging and fluid\nflow analysis in the following\napplications:\nFetal/Obstetric, Abdominal,\nPediatric, Cephalic, Urology,\nGynecological, Cardiac Fetal\nEcho, Small Organ,\nMusculoskeletal, Peripheral\nVessel, Carotid, Cardiac, Lung.\nThe Lumify system is a\ntransportable ultrasound\nsystem intended for use in\nenvironments where healthcare\nis provided by healthcare\nprofessionals.","Remains unchanged"],["Use","","",""],["","","",""],["Modes of","B(2D), Color Doppler,\nCombined (B+Color), Pulsed\nWave Doppler, and M-modes","B(2D), Color Doppler,\nCombined (B+Color), Pulsed\nWave Doppler, and M-modes","Remains unchanged"],["Operations","","",""],["","","",""]],"caption_candidate":"Table 1: Summary of changes between proposed and predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252557-p11-t0","doc_id":"K252557","page_num":11,"bbox":[72.38,75.36,583.41,597.79],"n_rows":23,"n_cols":4,"columns":["Standard","Lumify","Lumify Diagnostic","Comparison"],"rows":[["Standard","Lumify","Lumify Diagnostic","Comparison"],["Feature","Diagnostic","Ultrasound System",""],["","Ultrasound","K223771",""],["","System","(Predicate Device)",""],["","K# (K252557)","",""],["","(Subject Device)","",""],["Principles of","The pleural line tool detects\nand assesses the appearance of\npleural lines in incoming\nultrasound frames. The lung\nview quality tool indicates\nwhether incoming ultrasound\nframes are adequate for\nsupporting interpretation of\nlung features.\nCineloop-level reporting is\nprovided by averaging results\nfrom each frame. Both features\nallow manual adjustment of\nsoftware results.","The B-lines tool detects B-lines\nin incoming ultrasound frames\nand classifies them as merged\nor not merged.\nCineloop-level reporting is\nprovided by averaging results\nfrom each frame. The feature\nallows manual adjustment of\nsoftware results.","Similar to predicate device.\nThe difference between the\nsubject device and the\npredicate device is the\naddition of the lung view\nquality and pleural line\nfeatures. The principles of\noperation for the two added\nfeatures, including live\nframe-level display and\ncineloop-level reporting,\nremain unchanged compared\nto the predicate device. The\ncore system software\narchitecture remains\nunchanged."],["Operation","","",""],["","","",""],["Users","Lumify Ultrasound System is\nused by healthcare\nprofessionals.","Lumify Ultrasound System is\nused by healthcare\nprofessionals.","Remains unchanged"],["","","",""],["User","The Lumify system is a\ntransportable ultrasound\nsystem intended for use in\nenvironments where healthcare\nis provided by healthcare\nprofessionals.","The Lumify system is a\ntransportable ultrasound\nsystem intended for use in\nenvironments where\nhealthcare is provided by\nhealthcare professionals.","Remains unchanged"],["Environment","","",""],["","","",""],["Transducers","S4-1\nC5-2\nL12-4","S4-1\nC5-2\nL12-4","Remains unchanged"],["","","",""],["Patient Contact","Not applicable.\nTransducers previously\ncleared.","Not applicable.\nTransducers previously\ncleared.","Remains unchanged"],["Materials","","",""],["","","",""],["Primary","IYN","IYN","Remains unchanged"],["Product Code","","",""],["Secondary","IYO, ITX, QIH","IYO, ITX, QIH","Remains unchanged"],["Product Code","","",""]],"caption_candidate":"Lumify Diagnostic Ultrasound System with Lung Application 3","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p5-t0","doc_id":"K252634","page_num":5,"bbox":[63.86,36.96,552.94,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p5-t1","doc_id":"K252634","page_num":5,"bbox":[69.26,180.98,408.89,562.21],"n_rows":31,"n_cols":5,"columns":["510(k) Owner’s Name",":","","S","OFTLINK INTERNATIONAL PRIVA"],"rows":[["510(k) Owner’s Name",":","","S","OFTLINK INTERNATIONAL PRIVA"],["","","","",""],["Address",":","","2","Anand Park, Aundh, Pune 41100"],["","","","",""],["Telephone",":","","","+91-20-66044444"],["","","","",""],["Fax Number",":","","","+91-20-25883784"],["","","","",""],["Contact person",":","","P","rakash S. Kamat"],["","","","",""],["Designation",":","","","Managing Director"],["","","","",""],["Contact Number",":","","","+91-98230821280"],["","","","",""],["Contact Email",":","","p","rakash@softlinkinternational.com"],["","","","",""],["Date of Summary Prepared",":","","0","1.08.2025"],["","","","",""],["I. DEVICE","","","",""],["","","","",""],["Trade Name","",":","","Imagine® Enterprise Suite"],["","","","",""],["Device Common Name","",":","","Medical image management and p"],["","","","",""],["Device Classification Name","",":","","Automated radiological image pro"],["","","","",""],["Class","",":","","Class II"],["","","","",""],["Regulation Number","",":","","21 CFR 892.2050"],["","","","",""],["Product Code","",":","","QIH, LLZ"]],"caption_candidate":"SOFTLINK INTERNATIONAL PRIVATE LIMITED","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252634-p5-t2","doc_id":"K252634","page_num":5,"bbox":[63.86,427.63,552.94,568.51],"n_rows":6,"n_cols":3,"columns":["Trade Name",":","Imagine® Enterprise Suite"],"rows":[["Trade Name",":","Imagine® Enterprise Suite"],["Device Common Name",":","Medical image management and processing system"],["Device Classification Name",":","Automated radiological image processing software"],["Class",":","Class II"],["Regulation Number",":","21 CFR 892.2050"],["Product Code",":","QIH, LLZ"]],"caption_candidate":"II. DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p6-t0","doc_id":"K252634","page_num":6,"bbox":[63.86,36.96,552.94,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p6-t1","doc_id":"K252634","page_num":6,"bbox":[63.86,162.86,552.94,318.05],"n_rows":7,"n_cols":3,"columns":["Predicate Device Name",":","MPXA-2000"],"rows":[["Predicate Device Name",":","MPXA-2000"],["510(k) Number",":","K222036"],["Device Classification Name",":","Automated Radiological Image Processing Software"],["Class",":","Class II"],["Regulation Name",":","Medical image management and processing system"],["Regulation Number",":","21 CFR 892.2050"],["Product Code",":","QIH"]],"caption_candidate":"Primary Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p6-t2","doc_id":"K252634","page_num":6,"bbox":[63.86,357.29,552.94,512.47],"n_rows":7,"n_cols":3,"columns":["Predicate Device Name",":","Syngo.via View&GO (Version VA40A)"],"rows":[["Predicate Device Name",":","Syngo.via View&GO (Version VA40A)"],["510(k) Number",":","K230196"],["Device Classification Name",":","System, image processing, radiological"],["Class",":","Class II"],["Regulation Name",":","Medical image management and processing system"],["Regulation Number",":","21 CFR 892.2050"],["Product Code",":","LLZ"]],"caption_candidate":"Reference Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p7-t0","doc_id":"K252634","page_num":7,"bbox":[63.86,36.96,552.94,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p8-t0","doc_id":"K252634","page_num":8,"bbox":[62.87,36.96,551.82,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p8-t1","doc_id":"K252634","page_num":8,"bbox":[62.87,120.84,551.82,723.58],"n_rows":7,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Primary Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Primary Predicate","","Result"],["","No","","","","","Device","",""],["1.","","","510(k) Number","-","K222036","","","NA"],["2.","","","Manufacturer","Softlink International\nPvt Ltd","Medipixel, Inc.","","","NA"],["3.","","","Classification","Class II","Class II","","","Same"],["4.","","","Product Code","QIH, LLZ","QIH","","","Same\nLLZ product code\nis covered in the\nother modules. i.e.\nIES_ENTVIEWER,\nIES_ECHOVIEWER,\nIES_RADVEIWER,\nIES_ZFPVIEWER."],["5.","","","Intended use","Imagine® Enterprise\nSuite (IES) is a medical\ndiagnostic device that\nreceives, stores, and\nshares the medical\nimages from and to\nDICOM-compliant\nentities such as\nimaging modalities\n(such as X-ray\nAngiograms (XA),\nEchocardiograms (US),\nMRI, CT, CR, DR, IVUS,\nOCT, PET and SPECT),\nexternal PACS, and\nother diagnostic\nworkstations. It is used\nin the display and\nquantification of\nmedical images, after\nimage acquisition from\nmodalities, for post-\nprocedure clinical\ndecision support. It\nconstitutes a PACS for\nthe communication\nand storage of medical\nimages and provides a\nworklist of stored\nmedical images that\ncan be used to open\npatient studies in one\nof its image viewers. It","MPXA-2000 is software\nintended to be used for\nperforming calculations\nin X-ray angiographic\nimages of the coronary\narteries. These\ncalculations are based on\nvessel contours which\nare automatically\ndetected by the software\nand subsequently\npresented for review and\nmanual editing. The\nanalysis results obtained\nwith MPXA-2000 are\nintended for use by\ncardiologists and\nradiologists:\n- to support clinical\ndecisions concerning the\ncoronary arteries.\n- to support the\nevaluation of\nintervention or drug\ntherapy applied for\nconditions of the\ncoronary arteries.","","","Same\nThe intended use\nof IES remains\nconsistent for both\nthe interpretation\nand quantification\nof images."]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p9-t0","doc_id":"K252634","page_num":9,"bbox":[63.05,36.96,552.0,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p9-t1","doc_id":"K252634","page_num":9,"bbox":[63.05,116.28,552.0,709.06],"n_rows":4,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Primary Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Primary Predicate","","Result"],["","No","","","","","Device","",""],["","","","","is intended to display\nimages and related\ninformation that are\ninterpreted by trained\nprofessionals to render\nfindings and/or\ndiagnosis, but it does\nnot directly generate\nany diagnosis or\npotential findings. Not\nintended for primary\ndiagnosis of\nmammographic\nimages. Not intended\nfor intra-procedural or\nreal-time use. Not\nintended for diagnostic\nuse on mobile devices.","","","",""],["6.","","","Indication For Use","Imagine® Enterprise\nSuite is a software\npackage that aids the\nvisualization and\nquantification of\nvarious medical\nimages in DICOM\nformat, when the\npatient is NOT in life-\nthreatening state of\nhealth, and the time\nfor medical decision is\nNOT critical. Typical\nusers of this system\nare trained\nprofessionals,\nincluding but not\nlimited to physicians,\nradiologists,\ncardiologists, nurses,\nmedical technicians,\nand assistants.","MPXA-2000 is indicated\nfor use in clinical settings\nwhere validated and\nreproducible quantified\nresults are needed to\nsupport the calculations\nin X-ray angiographic\nimages of the coronary\narteries, for use on\nindividual patients with\ncoronary artery disease\n(CAD). MPXA 2000 is\nindicated for use in adult\npatients only. When the\nquantified results\nprovided by MPXA-2000\nare used in a clinical\nsetting on X ray images\nof an individual patient,\nthey can be used to\nsupport the clinical\ndecision-making for the\ndiagnosis of the patient\nor the evaluation of the\ntreatment applied. In this\ncase, the results are\nexplicitly not to be\nregarded as the sole,\nirrefutable basis for\nclinical diagnosis, and\nthey are only intended","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p10-t0","doc_id":"K252634","page_num":10,"bbox":[62.71,36.96,551.67,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p10-t1","doc_id":"K252634","page_num":10,"bbox":[62.71,116.28,551.67,709.3],"n_rows":15,"n_cols":10,"columns":["","Sl.","","Features compared","","Proposed Device","","Primary Predicate","","Result"],"rows":[["","Sl.","","Features compared","","Proposed Device","","Primary Predicate","","Result"],["","No","","","","","","Device","",""],["","","","","","","for use by the\nresponsible clinicians.","","",""],["7.","","","Prescription Use or OTC Use","","Prescription use","Prescription use","","","Same"],["8.","","","DICOM-compliant","","Yes","Yes","","","Same"],["9.","","","List of Modality support","","X-ray Angiograms (XA)","X-ray","","","Same"],["10.","","","Web Diagnostic Viewer","","Standalone Software","Standalone software","","","Same"],["11.","","","Input Data type","","X-Ray angiography in\nDICOM format","X-Ray angiography in\nDICOM format (vendor\nindependent)","","","Same"],["12.","","","Manual editing of automatic results\nby user","","Yes","Yes","","","Same"],["13.","","","Calibration","","Automatic calibration\nbased on calibration\nfactor in DICOM file OR\nautomatic\nsegmentation of\ncatheter from image.","Automatic calibration\nbased on isocenter\ncalibration factor in\nDICOM file\nOther manual calibration\noptions (catheter\ncalibration)","","","Same"],["14.","","","Automatic angiographic series\nloading into the software from the\nangiography equipment","","The angiographic\nequipment or modality\nfirst exports the\nangiographic series to\nthe IES PACS in DICOM\nformat. Angiographic\nseries are loaded into\nthe software from the\nIES PACS.","Yes","","","Same"],["15.","","","Visualization/ Edit Tools","","Zooming, Panning,\nEditing Vessel\nContours.","Zooming, Panning,\nEditing Vessel Contours,\nAngle, Length, Area, Text\nAnnotation","","","Same"],["16.","","","Quantitative\nAnalysis","Automated 2D\narterial contour\nsegmentation","Yes","Yes","","","Same"],["","","","","Classification of\nvessel types","Manually by user","Yes\nLAD, LCX, and RCA","","","Same"],["","","","","Optional Stent\nanalysis including\nstent edges","No","No","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p11-t0","doc_id":"K252634","page_num":11,"bbox":[62.72,36.96,552.3,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p11-t1","doc_id":"K252634","page_num":11,"bbox":[62.72,116.28,552.3,557.71],"n_rows":11,"n_cols":10,"columns":["","Sl.","","Features compared","","Proposed Device","","Primary Predicate","","Result"],"rows":[["","Sl.","","Features compared","","Proposed Device","","Primary Predicate","","Result"],["","No","","","","","","Device","",""],["17.","","","Analysis\nResults","Results for multiple\nlesions and\nadditional user-\ndefined ROIa)","Results for multiple\nlesions. No user-\ndefined ROIs are\nsupported.","Results for multiple\nlesions and additional\nuser-defined ROIa)","","","Same"],["","","","","Vessel analysis","Main and side branch","main and side branch","","","Same"],["","","","","Vessel\nquantifications","% Diameter Stenosis,\nMinimum Lumen\nDiameter (MLD),\nProximal and Distal\nDiameters (at P- and D\nmarker positions),\nStenosis Length,\nReference Diameter","% Diameter Stenosis,\nMinimum Lumen\nDiameter (MLD),\nProximal and Distal\nDiameters (at P- and D\nmarker positions), ROIa)\nLength, Reference\nDiameter","","","Same"],["","","","","Stent-related\nstatistics","No","No","","","Same"],["18.","","","Ventricle analysis","","No","No","","","Same"],["19.","","","Automatically load and visualize\nECG data acquired from the DICOM\nfile","","No","Yes","","","Different"],["20.","","","Automatic EoD (End of Diastole)\nphase detection in DICOM file based\non ECG.","","No","Yes","","","Different"],["21.","","","Data Reporting","","Patient and Study\nDetails, Calibration,\nAnnotation,\nMeasurement, and\nAnalysis Details.","Patient and Study\nDetails, Calibration,\nAnnotation,\nMeasurement, and\nAnalysis details.","","","Same"],["22.","","","Export file formats","","PDF","PDF, Excel","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p11-t2","doc_id":"K252634","page_num":11,"bbox":[62.72,644.84,552.3,729.22],"n_rows":4,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["1.","","","510(k) Number","-","K230196","","","NA"],["2.","","","Manufacturer","Softlink International Pvt Ltd","Siemens Healthcare GmbH","","","NA"]],"caption_candidate":"modules of the Imagine® Enterprise Suite (IES) and the Syngo.via View&GO system.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p12-t0","doc_id":"K252634","page_num":12,"bbox":[62.97,36.96,554.24,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p12-t1","doc_id":"K252634","page_num":12,"bbox":[62.97,116.28,554.24,677.74],"n_rows":5,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["3.","","","Classification","Class II","Class II","","","Same"],["4.","","","Product Code","QIH, LLZ","LLZ","","","Same\nQIH product\ncode is covered\nin the\nAngioQuant\nModule"],["5.","","","Intended use","Imagine® Enterprise Suite (IES)\nis a medical diagnostic device\nthat receives, stores, and shares\nthe medical images from and to\nDICOM-compliant entities such\nas imaging modalities (such as\nX-ray Angiograms (XA),\nEchocardiograms (US), MRI, CT,\nCR, DR, IVUS, OCT, PET and\nSPECT), external PACS, and\nother diagnostic workstations. It\nis used in the display and\nquantification of medical images,\nafter image acquisition from\nmodalities, for post-procedure\nclinical decision support. It\nconstitutes a PACS for the\ncommunication and storage of\nmedical images and provides a\nworklist of stored medical\nimages that can be used to open\npatient studies in one of its\nimage viewers. It is intended to\ndisplay images and related\ninformation that are interpreted\nby trained professionals to\nrender findings and/or\ndiagnosis, but it does not directly\ngenerate any diagnosis or\npotential findings. Not intended\nfor primary diagnosis of\nmammographic images. Not\nintended for intra-procedural or\nreal-time use. Not intended for\ndiagnostic use on mobile\ndevices.","Syngo.via View&GO is a\nsoftware solution intended to\nbe used for viewing,\nmanipulation, communication,\nand storage of medical\nimages. It can be used as a\nstand-alone device or together\nwith a variety of cleared and\nunmodified syngo-based\nsoftware options. syngo.via\nView&GO supports\ninterpretation and evaluation\nof examinations within\nhealthcare institutions, for\nexample, in Radiology, Nuclear\nMedicine and Cardiology\nenvironments. The system is\nnot intended for the displaying\nof digital mammography\nimages for diagnosis in the\nU.S.","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p13-t0","doc_id":"K252634","page_num":13,"bbox":[62.81,36.96,554.48,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p13-t1","doc_id":"K252634","page_num":13,"bbox":[62.81,116.28,554.48,716.5],"n_rows":9,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["6.","","","Indication For Use","Imagine® Enterprise Suite is a\nsoftware package that aids the\nvisualization and quantification\nof various medical images in\nDICOM format, when the patient\nis NOT in life-threatening state of\nhealth, and the time for medical\ndecision is NOT critical. Typical\nusers of this system are trained\nprofessionals, including but not\nlimited to physicians,\nradiologists, cardiologists,\nnurses, medical technicians, and\nassistants.","Syngo.via View&GO is\nindicated for image rendering\nand post-processing of DICOM\nimages to support the\ninterpretation in the fields of\nradiology, nuclear medicine,\nand cardiology.","","","Same"],["7.","","","Prescription Use or OTC\nUse","Prescription use","Prescription use","","","Same"],["8.","","","Operating System","Server: Windows Server OS\n2022/Windows 11 Pro, 64 bit\nClient: Windows 11 Pro, 64 bit","Microsoft Windows 11- 64-bit\nor higher\nMicrosoft Windows 10- 64-bit\nor higher","","","Same"],["9.","","","DICOM-compliant","Yes","Yes","","","Same"],["10.","","","Software architecture","System is logically broken down\ninto IES PACS and IES viewers\nsubsystems. The IES Viewers\nfurther contain the\nIES_EntViewer, IES_RadViewer\nand IES_EchoViewer modules.","System that is logically broken\ndown to syngo.via View&GO\nsubsystems. Subsystems are\nfurther broken down to syngo\nmodules.","","","Same"],["11.","","","List of Modality support","X-ray Angiograms (XA),\nEchocardiograms (US), MRI, CT,\nCR, DR, IVUS, OCT, NM (PET and\nSPECT).","CT Image (Computed\nTomography), MR Image\n(Magnetic Resonance), NM\nImage (Nuclear Medicine), XA\nImage (X-Ray Angiography),\nUS Image (Ultrasound), DX\nImage (Digital Radiography),\nDICOM secondary capture\nobjects.","","","Same"],["12.","","","Web Diagnostic Viewer","Standalone software for\ndiagnostic use.\nWeb-based IES ZeroFootPrint\nViewer (IES_ZFPViewer) is\ndesigned solely for browser-\nbased viewing and is not\nintended for diagnostic purposes.","Stand-alone software","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p14-t0","doc_id":"K252634","page_num":14,"bbox":[62.97,36.96,554.24,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p14-t1","doc_id":"K252634","page_num":14,"bbox":[62.97,116.28,554.24,728.38],"n_rows":5,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["13.","","","Imaging Algorithms used","Multiplanar reconstruction\n(MPR), Maximum and Minimum\nIntensity Projection (MIP/MinIP),\nBasic Volume Rendering with\nClipBox, Multimodality\nregistration, automatic spine\nlabeling (no rib labeling),\nCardiothoracic Ratio.","Multiplanar reconstruction\n(MPR), Maximum and\nMinimum Intensity Projection\n(MIP/MinIP), Volume\nRendering Technique (VRT)\nwith additional edge and\nsurface enhancements and\ncontrol over rendering\nparameters, Shaded Surface\nDisplay (SSD), Digitally\nReconstructed Radiograph,\nEditor functionality (e.g.\nClipBox), Auto-Contour,\nRegistration, Anatomical\nregistration, Region growing,\nAutomatic Spine Labeling, also\nfor ribs in CT thorax scans\n(“Rib labeling”), Reprocessing\nX-ray projection images into\n3D image and Topograms,\nFASTAlign, Cinematic VRT1","","","Same"],["14.","","","Quantitative algorithms\nused","IES_EntViewer: Line\nMeasurement for ECG\nIES_Radviewer: Distance, Angle,\nCobb Angle, ROI\nIES_EchoViewer: Distance,\nAngle, Point, Area-MOD (method\nof disks), VTI (Velocity Time\nIntegral)","Distance, Angle & Angle [1]\non-stack, VOI, and ROI\nMeasurement","","","Similar"],["15.","","","Image data Compression","Receive & Store: Images are\nreceived and stored as received\nwithout any change in the\ncompression format.\nDisplay: Images are displayed\nas received without any change\nin the compression.\nLossy compression images are\ndisplayed with an indication to\nthe user with the compression\ntype (Transfer Syntax) used.\nExport: To DICOM Node:\nImages are sent as per the\nDICOM negotiation.\nUncompressed is preferred and\nlossy compression is not\nsupported. To Exchangeable\nmedia: Images exported as\nstored in the local storage.","Receive & Store: Images are\nreceived and stored as\nreceived without any change in\nthe compression format.\nDisplay: Images are\ndisplayed as received without\nany change in the\ncompression.\nLossy compression images are\ndisplayed with an indication to\nthe user with the compression\nratio.\nExport: To DICOM Node:\nImages are sent as per the\nDICOM negotiation.\nUncompressed is preferred\nand lossy compression is not\nsupported. To Exchangeable","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p15-t0","doc_id":"K252634","page_num":15,"bbox":[62.87,36.96,554.39,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p15-t1","doc_id":"K252634","page_num":15,"bbox":[62.87,116.28,554.39,721.3],"n_rows":7,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["","","","","Supported Compressions for\nexport:\n• JPEG 2000 Image\nCompression\n• JPEG Baseline (Process 1):\nDefault Transfer Syntax for\nLossy JPEG 8 Bit Image\nCompression\n• JPEG Extended (Process 2 &\n4): Default Transfer Syntax\nfor Lossy JPEG 12 Bit Image\nCompression - (Process 4\nonly)\n• JPEG Lossless, Non-\nHierarchical (Process 14)\n• JPEG Lossless, Non-\nHierarchical, First-Order\nPrediction (Process 14\n[Selection Value 1]): Default\nTransfer Syntax for Lossless\nJPEG Image Compression\n• JPEG-LS Lossless Image\nCompression\n• JPEG-LS Lossy (Near-\nLossless) Image\nCompression\n• RLE Lossless.","media: Images exported as\nstored in the local storage.\nSupported Compressions\nfor export: lossless\ncompression algorithms, JPEG,\nJPEG 2000, and RLE.","","",""],["16.","","","Software self-test /\nchecks","Return valid DICOM error codes\nto the associated Application\nEntity in case the data transfer is\ninterrupted.\nHardware/Operating System/\nFramework Compatibility Check\nduring Installation.\nDisplay Compatibility Check\nsupports the end user to qualify\nthe system for hardware-\naccelerated graphics using a\nGPU.","Alert the user in case the data\ntransfer is interrupted to the\nconnected DICOM node.\nHardware / Operating System\ncompatibility check during\nInstallation.\nDisplay Compatibility Check\nsupports the end user to\nqualify the system for proper\ndiagnostic use.","","","Same"],["Software functionalities","","","","","","","",""],["17.","","","Graphical User Interface","Yes, with text labels, and\nappropriate tooltips.","Yes, with a reduced color\npalette, clearer structure, and\ntext labels on icons.","","","Same"],["18.","","","Patient Browser","Yes, with simplified search\nfunctionality, Study & series level\nresults, and paging.","Yes, with simplified search\nfunctionality, clearer structure\nof search results, image\npreview, unlimited search\nresults, and periodic updates\nof search results.","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p16-t0","doc_id":"K252634","page_num":16,"bbox":[62.78,36.96,554.51,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p16-t1","doc_id":"K252634","page_num":16,"bbox":[62.78,116.28,554.51,728.26],"n_rows":10,"n_cols":9,"columns":["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],"rows":[["","Sl.","","Features compared","Proposed Device","","Reference Predicate","","Result"],["","No","","","","","Device","",""],["19.","","","Series Navigator","Series-level results can be\nenabled by the user. Shown in\npatient worklist with series\ndescription.","The Series Navigator lists all\ncurrently loaded data within a\nworkflow. Studies are marked\nwith colorized time points.","","","Same"],["20.","","","Findings / Reporting","No findings and reporting\nsupport","No, reporting support is\nprovided to create reports\nusing any 3rd party reporting\ntool. Hence the findings also\ncannot be navigated.","","","Same"],["21.","","","Imports and exports of\ndata","Import of DICOM data from\nnetwork nodes or external\nmedia, and of DICOM-compliant\ndata from external media and\nWindows file system. Export to\nUSB, CD/DVD, or other DICOM\nnodes.","Import of DICOM data from\nnetwork nodes or external\nmedia, and of DICOM-\ncompliant or non-DICOM-\ncompliant data from external\nmedia and Windows file\nsystem. Export to USB,\nWindows file system, or other\nDICOM nodes.","","","Same"],["22.","","","Archiving data","Data stored on IES PACS archive\nstorage.","Data can be sent to an archive\nif syngo.via View&GO is\nconnected to a PACS or\ncorresponding DICOM node.","","","Same"],["23.","","","Spine/Rib labeling","Yes, with suggested spine labels\nto be confirmed by the user, and\nadditional smart placement of\nlabels. No rib labeling.","Yes, with suggested spine\nlabels to be confirmed by the\nuser, and additional smart\nplacement of labels, also in\ninter-vertebra regions,\nsupport of 2D images, support\nof multi-series studies, and\nadded support for rib labels.","","","Same"],["24.","","","Online help system","Context-enabled help for the IES\nPACS worklist, ENT viewer and\nZFP Viewer. User manuals for\nRadViewer and EchoViewer.","Yes, with a reduced color\npalette, clearer structure, and\ntext labels on icons","","","Same"],["25.","","","Markers and annotations","Yes, with support for marking a\nposition on an image and textual\nannotations","Yes, with support for marking\na position on an image and\ntextual annotations","","","Same"],["26.","","","Hiding and Showing of\nImage Overlays","Show or hide graphical objects\nsuch as annotations and\nmarkers, show or hide reference\nlines","Show or hide image text, show\nor hide custom image text,\nshow or hide graphical objects\nsuch as annotations and\nmarkers, show or hide\nreference lines, show or hide\nshutter","","","Same"]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p17-t0","doc_id":"K252634","page_num":17,"bbox":[63.86,36.96,552.94,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252634-p18-t0","doc_id":"K252634","page_num":18,"bbox":[63.86,36.96,552.94,101.18],"n_rows":2,"n_cols":2,"columns":["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],"rows":[["","SOFTLINK INTERNATIONAL PRIVATE LIMITED\n2, Anand Park, Aundh, Pune - 411 007, India."],["510(k) SUMMARY",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p4-t0","doc_id":"K252665","page_num":4,"bbox":[98.89,19.92,593.26,359.65],"n_rows":9,"n_cols":6,"columns":["","Indications for Use","","","",""],"rows":[["","Indications for Use","","","",""],["","","n the marketing application/submission number, if it is known. This","","K243292",""],["","","e left blank for original applications/submissions.\ne the device trade name(s).","","",""],["","","","","",""],["","der Positioning","","","",""],["","","e your Indications for Use below.","","",""],["","","","","",""],["","der Positioning is intended to be used as an information tool to assist in the preoperative\nng and visualization of a primary total shoulder replacement.","","","",""],["","","t the types of uses (select one or both, as","Prescription Use (Part 21 CFR 801 Subpart D)\n[] Over-The-counter Use (21 CFR 801 Subpart C)","",""]],"caption_candidate":"I","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p6-t0","doc_id":"K252665","page_num":6,"bbox":[57.07,416.79,538.21,553.29],"n_rows":6,"n_cols":2,"columns":["510(k) Sponsor","Avatar Medical"],"rows":[["510(k) Sponsor","Avatar Medical"],["Address","11 rue de Lourmel\n75015 Paris France"],["Correspondence Person","FRANCOIS Adeline\nVP QARA and Clinical Affairs"],["Contact Information","Email: adeline@avatarmedical.ai"],["510(k) number","K252665"],["510(k) Summary Date","Aug 22, 2025"]],"caption_candidate":"Table 2A – Submission correspondent","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p7-t0","doc_id":"K252665","page_num":7,"bbox":[57.07,99.59,538.21,212.09],"n_rows":6,"n_cols":2,"columns":["Regulation Number","21 CFR 892.2050"],"rows":[["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code:","QIH, automated radiological image processing software"],["Subsequent Product Code:","LLZ, system, image processing, radiological"],["Regulatory Class","II"],["Classification Panel","Radiology"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p7-t1","doc_id":"K252665","page_num":7,"bbox":[57.07,313.44,538.21,482.19],"n_rows":9,"n_cols":2,"columns":["Trade name","FX SPS"],"rows":[["Trade name","FX SPS"],["Common Name","Planning software for Total Shoulder Arthroplasty"],["Premarket Notification","K213922"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","21 CFR 892.2050"],["Regulation Name","Medical Image Management and Processing System"],["Product Code","LLZ"],["Regulatory Class","II"],["Classification Panel","Radiology"]],"caption_candidate":"Table 2C – Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p8-t0","doc_id":"K252665","page_num":8,"bbox":[57.07,348.79,538.21,736.54],"n_rows":13,"n_cols":3,"columns":["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],"rows":[["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],["Intended Users","Healthcare Professionals","Healthcare Professionals"],["Intended Environment","Healthcare facilities such as hospitals and\nclinics","Healthcare facilities such as\nhospitals and clinics"],["Device Class","Class II","Class II"],["Type of software","Web-based software","Web-based software"],["Use time","Pre-operatively","Pre-operatively"],["Imaging used","CT-scan images","CT-scan images"],["Type of implants planned","Anatomical and reverse shoulder implants","Anatomical and reverse shoulder\nimplants"],["Manual/Automatic\nsegmentation","Manual segmentation performed.","Automatic segmentation\nperformed."],["User profiles","User profiles define the authorized actions\nfor the user.","User profiles define the\nauthorized actions for the user."],["Case management","List of cases","List of cases"],["Tools","Milling tool","Milling tool (called reaming)"],["Patient Information\nDisplay","Patient last name\nPatient first name\nPatient sex\nPatient birthdate\nShoulder side\nSurgery date","Patient last name\nPatient first name\nPatient sex\nPatient birthdate\nPatient age\nPatient height\nPatient weight"]],"caption_candidate":"Table 2D: Comparison of Characteristics","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p9-t0","doc_id":"K252665","page_num":9,"bbox":[57.07,99.59,538.21,736.34],"n_rows":9,"n_cols":3,"columns":["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],"rows":[["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],["","","Shoulder side\nSurgery date"],["Bone representation","3D and 2D representation of the humerus\nand the scapula","3D and 2D representation of the\nhumerus and the scapula."],["2D DICOM Viewer","2D DICOM view\nAxial views are displayed in 2D DICOM\nViewer interfaces.","The 2D DICOM Viewer Interface\ndisplays 2D DICOM images\nAxial and coronal views are\ndisplayed in two separate 2D\nDICOM Viewer interfaces."],["3D Viewer","3D reconstruction in an interactive viewing\ninterface","3D reconstruction in an\ninteractive viewing interface with\nsoft tissues (Pre-Position\nInterface only)"],["Planning step","Case details,\nSegmentation,\nGlenoid\nPlanning Report","Create plan,\nValidate Segmentations,\nPre-position with the\nvalidation of Shoulder\nLandmarks,\nImplant,\nGlenoid/humerus,\nPost position,\nSurgical planning Report"],["Landmarks /\nMeasurements","Manual Landmarks/Measurements\nperformed:\nShoulder Measurements, scapula neck\nlength, posterior subluxation, glenoid\nreaming depth.\nManual measurements performed:\nFeature that displays and calculates\nthe distance between two points.","Pre-positioning or Semi-\nautomatic Landmarks/\nMeasurements performed:\nShoulder Measurements,\nbackside seating, 3D subluxation,\nglenoid reaming depth.\nManual measurements\nperformed (Ruler Tool):\nFeature that displays and\ncalculates the distance\nbetween two points."],["Implant Initial Placement","Manual initial placement performed.","Pre-positioning or Semi-\nautomatic initial placement\nperformed."],["Planning report","Planning report comprising patient\ninformation, implant and measurements\nname, its preoperative value, and the\nplanned value. It also comprises images\nfrom the preoperative situation with\ndifferent camera angles, image showing\nthe drilling simulation pin, images showing\nthe scapula and the Glenoid implant.","Planning report comprising\npatient information, implant and\nmeasurements name, its value in\npre-position, and the value in\npost-position. It also comprises\nimages from the Pre-Position tab\nwith different camera angles,\nimages showing the K-Wire\nplacement, images showing the"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252665-p10-t0","doc_id":"K252665","page_num":10,"bbox":[57.07,99.59,538.21,239.84],"n_rows":3,"n_cols":3,"columns":["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],"rows":[["Feature/\nFunction","Predicate Device:\nFX SPS\n(K213922)","Subject Device:\nbrAIn™ Shoulder Positioning"],["","","Glenoid implant, and images\nfrom the Post-Position Interface\nshowing both the scapula and\nhumerus and the chosen implant\ncomponents."],["Recommandations","Does not include any predictions and\nrecommendations.","Does not include any predictions\nand recommendations."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p5-t0","doc_id":"K252670","page_num":5,"bbox":[93.62,127.34,552.7,175.94],"n_rows":2,"n_cols":2,"columns":["Alzevita 510(k) Premarket Submission",""],"rows":[["Alzevita 510(k) Premarket Submission",""],["Revision: 03","Date: DEC 19,2025"]],"caption_candidate":"www.topiamedtech.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p5-t1","doc_id":"K252670","page_num":5,"bbox":[74.54,160.34,356.98,685.06],"n_rows":41,"n_cols":3,"columns":["","Revision: 03 D","ate: DEC 19,2025"],"rows":[["","Revision: 03 D","ate: DEC 19,2025"],["","",""],["","","510(k) Summ"],["","",""],["I. S","ubmitter",""],["","",""],["","Name","TOPIA MEDTECH LIMITED"],["","",""],["","Address","14 Havelock Place (MS), Harrow"],["","",""],["","Contact Person","Akshay Sojitra"],["","",""],["","Telephone Number","+44 2081530878"],["","",""],["","Email","regulatory@topiamedtech.com"],["","",""],["II. D","evice",""],["","",""],["","Device Trade Name","Alzevita"],["","",""],["","Common Name","Medical Image Processing Soft"],["","",""],["","Classification Name","Medical Image Management a"],["","",""],["","Regulation Number","21 CFR 892.2050"],["","",""],["","Regulation Description","Picture Archiving and Commun"],["","",""],["","Product Code","QIH"],["","",""],["","Classification Panel","Radiology"],["","",""],["III. P","redicate Device",""],["","",""],["","Device","NEUROShield"],["","",""],["","510(k) Number","K220034"],["","",""],["","Manufacturer","In Med Prognostics L3C"],["","",""],["","Product Code","LLZ"]],"caption_candidate":"Revision: 03 Date: DEC 19,2025","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252670-p5-t2","doc_id":"K252670","page_num":5,"bbox":[93.62,417.31,552.7,564.19],"n_rows":7,"n_cols":2,"columns":["Device Trade Name","Alzevita"],"rows":[["Device Trade Name","Alzevita"],["Common Name","Medical Image Processing Software"],["Classification Name","Medical Image Management and Processing System"],["Regulation Number","21 CFR 892.2050"],["Regulation Description","Picture Archiving and Communications System"],["Product Code","QIH"],["Classification Panel","Radiology"]],"caption_candidate":"II. Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p5-t3","doc_id":"K252670","page_num":5,"bbox":[93.62,608.74,552.7,688.54],"n_rows":4,"n_cols":2,"columns":["Device","NEUROShield"],"rows":[["Device","NEUROShield"],["510(k) Number","K220034"],["Manufacturer","In Med Prognostics L3C"],["Product Code","LLZ"]],"caption_candidate":"III. Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p6-t0","doc_id":"K252670","page_num":6,"bbox":[93.38,525.43,547.54,709.3],"n_rows":9,"n_cols":4,"columns":["Details","Subject Device","Predicate Device","Remark"],"rows":[["Details","Subject Device","Predicate Device","Remark"],["Name of\nManufacturer","TOPIA MEDTECH LIMITED","In Med Prognostics L3C","-"],["Address of\nSubmitter","14 Havelock Place (MS), Harrow,\nUnited Kingdom, HA11LJ","4918 September Street, San Diego, CA\n92110, USA","-"],["Brand Name","Alzevita","NEUROShield","-"],["510 (K) Number","K252670","K220034","-"],["Generic Name","Medical Image Processing Software","Medical Image Processing software","Equivalent"],["Classification","Class II","Class II","Equivalent"],["Classification\nProduct Code","QIH","LLZ","Substantially\nEquivalent"],["Intended Use","Alzevita is intended for use by\nneurologists and radiologists","The NEUROShield medical image\nprocessing software is intended for","Substantially\nEquivalent"]],"caption_candidate":"VI. Comparison of Technological Characteristics with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p7-t0","doc_id":"K252670","page_num":7,"bbox":[93.38,87.02,547.54,603.94],"n_rows":7,"n_cols":4,"columns":["","experienced in the interpretation and\nanalysis of brain MRI scans. It enables\nautomated labelling, visualization, and\nvolumetric measurement of the\nhippocampus from high-resolution T1-\nweighted MRI images. The software\nfacilitates comparison of hippocampal\nvolume against a normative dataset\nderived from MRI scans of healthy\ncontrol subjects aged 55 to 90 years,\nacquired using standardized imaging\nprotocols on 1.5T/3T MRI scanners.","automatic labelling, visualization, and\nvolumetric quantification of the\nHippocampus brain structure from a\nset of MR images",""],"rows":[["","experienced in the interpretation and\nanalysis of brain MRI scans. It enables\nautomated labelling, visualization, and\nvolumetric measurement of the\nhippocampus from high-resolution T1-\nweighted MRI images. The software\nfacilitates comparison of hippocampal\nvolume against a normative dataset\nderived from MRI scans of healthy\ncontrol subjects aged 55 to 90 years,\nacquired using standardized imaging\nprotocols on 1.5T/3T MRI scanners.","automatic labelling, visualization, and\nvolumetric quantification of the\nHippocampus brain structure from a\nset of MR images",""],["Design and\nIncorporated\nTechnology","• A Software as a Medical Device\n(SaMD) designed for imaging and\nquantitative analysis of the\nhippocampal brain structure from\nMRI scans.\n• It is a fully automated, geometry-\nbased brain analytics tool and cloud\nplatform developed using advanced\n3D U-Net++ methodologies","• Software as a medical device to be\nused in the process of Imaging and\nquantification of the Hippocampus\nbrain structure from a set of MR\nimages\n• Fully automated brain geometry -\nbased quantifying analytics\ntool/cloud platform developed using\nDeepNet / U-Net methodologies","Substantially\nEquivalent"],["Physical\nCharacteristics","• Software Package (Accessible via\nWeb Browser)\n• Operates on off the shelf hardware\n(multiple vendors)","• Software Package (Accessible via\nWeb Browser)\n• Operates on off the shelf hardware\n(multiple vendors)","Equivalent"],["Supported\nOperating\nSystems","Supports Linux, Windows and Mac OS\nlatest","Supports Windows and Mac OS latest","Equivalent"],["Data Source","Alzevita requires compressed DICOM\nfiles or NIFTI files as Input","NEUROShield requires uncompressed\nDICOM files as input","Equivalent"],["Output","Software provides volumetric\nmeasurements of Hippocampus brain\nstructures","Provides volumetric measurements of\nHippocampus brain structures","Equivalent"],["Safety","• Automated quality control functions -\nScan protocol verification\n• Results must be reviewed by a\ntrained clinicians/ Radiologist/\nNeurologist","• Automated quality control functions -\nScan protocol verification\n• Results must be reviewed by a\ntrained clinicians/ Radiologist/\nNeurologist","Equivalent"]],"caption_candidate":"www.topiamedtech.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p8-t0","doc_id":"K252670","page_num":8,"bbox":[178.34,229.82,409.87,326.33],"n_rows":6,"n_cols":3,"columns":["Subgroups","","Count"],"rows":[["Subgroups","","Count"],["Magnetic field strength","1.5T","200"],["Slice thickness","1","200"],["Equipment","GE","200"],["Gender","Male","110"],["","Female","90"]],"caption_candidate":"Table 1 presents the distribution of subjects based on key imaging and demographic parameters.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p9-t0","doc_id":"K252670","page_num":9,"bbox":[237.05,104.66,375.19,229.7],"n_rows":7,"n_cols":2,"columns":["Age group","Count"],"rows":[["Age group","Count"],["55-64","20"],["65-69","37"],["70-74","74"],["75-79","82"],["80-84","58"],["85-90","27"]],"caption_candidate":"The mean age of subjects is found to be 76 ± 7 years.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p9-t1","doc_id":"K252670","page_num":9,"bbox":[128.78,280.13,454.9,551.35],"n_rows":14,"n_cols":5,"columns":["Subgroups","","Count","Mean\n(mL)","Standard\ndeviation (mL)"],"rows":[["Subgroups","","Count","Mean\n(mL)","Standard\ndeviation (mL)"],["Clinical Sub- groups","ADNI-control","132","7.0","1.0"],["","ADNI-MCI","103","5.6","1.3"],["","ADNI-AD","63","4.9","0.9"],["Gender","Male","150","5.8","1.3"],["","Female","148","6.4","1.4"],["Magnetic field strength","1.5T","128","5.5","1.3"],["","3T","170","6.05","1.1"],["Slice thickness","1","126","6.9","1.3"],["","1.2","172","5.6","1.3"],["Region","East USA","133","6.1","1.4"],["","West USA","56","6.2","1.5"],["","Central USA","90","6.2","1.4"],["","Canada","19","6.3","1.5"]],"caption_candidate":"The table below provides the categorization of subjects according to selection criteria:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p11-t0","doc_id":"K252670","page_num":11,"bbox":[142.94,252.89,479.86,328.37],"n_rows":3,"n_cols":4,"columns":["Measure","Threshold","Alzevita 95 % confidence\nintervals","Criteria\n(Pass/Fail)"],"rows":[["Measure","Threshold","Alzevita 95 % confidence\nintervals","Criteria\n(Pass/Fail)"],["Dice","0.75","(0.85, 0.86)","Pass"],["Hausdorff distance","6.1","(1.43, 1.59)","Pass"]],"caption_candidate":"respectively. The following table shows the 95% confidence interval for both.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p11-t1","doc_id":"K252670","page_num":11,"bbox":[142.94,375.05,547.06,547.03],"n_rows":5,"n_cols":7,"columns":["","Dice Score","","","Hausdorff Distance (mm)","",""],"rows":[["","Dice Score","","","Hausdorff Distance (mm)","",""],["Clinical\nsubgroups","Control","MCI","AD","Control","MCI","AD"],["Measured\nvalue","0.88","0.85","0.83","1.36","1.53","1.79"],["Alzevita 95 %\nconfidence\nintervals","(0.87, 0.88)","(0.84, 0.85)","(0.82, 0.84)","(1.32, 1.41)","(1.44, 1.62)","(1.48, 2.10)"],["Criteria","Pass","Pass","Pass","Pass","Pass","Pass"]],"caption_candidate":"a) Clinical subgroups","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p12-t0","doc_id":"K252670","page_num":12,"bbox":[157.1,117.86,490.3,272.57],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff Distance (mm)",""],"rows":[["","Dice score","","Hausdorff Distance (mm)",""],["Gender","Female","Male","Female","Male"],["Measured value","0.86","0.85","1.48","1.54"],["Alzevita 95 %\nconfidence\nintervals","(0.85, 0.87)","(0.84, 0.86)","(1.40, 1.57)","(1.41, 1.66)"],["Criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"b) Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p12-t1","doc_id":"K252670","page_num":12,"bbox":[157.1,304.01,490.3,444.67],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff Distance (mm)",""],"rows":[["","Dice score","","Hausdorff Distance (mm)",""],["MRI strength","3T","1.5T","3T","1.5T"],["Measured value","0.87","0.84","1.43","1.62"],["Alzevita 95 %\nconfidence\nintervals","(0.86, 0.87)","(0.83, 0.85)","(1.38, 1.47)","(1.45, 1.79)"],["Criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"c) Magnetic field strength","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p12-t2","doc_id":"K252670","page_num":12,"bbox":[157.1,476.11,490.3,616.78],"n_rows":5,"n_cols":5,"columns":["","Dice score","","Hausdorff Distance (mm)",""],"rows":[["","Dice score","","Hausdorff Distance (mm)",""],["Slice thickness","1 mm","1.2mm","1 mm","1.2mm"],["Average value","0.87","0.84","1.39","1.60"],["Alzevita 95 %\nconfidence\nintervals","(0.87, 0.88)","(0.84, 0.85)","(1.35, 1.43)","(1.47, 1.72)"],["Criteria","Pass","Pass","Pass","Pass"]],"caption_candidate":"d) Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252670-p13-t0","doc_id":"K252670","page_num":13,"bbox":[149.3,117.86,552.7,245.3],"n_rows":5,"n_cols":9,"columns":["","Dice score","","","","Hausdorff Distance (mm)","","",""],"rows":[["","Dice score","","","","Hausdorff Distance (mm)","","",""],["Region","East US","West US","Central US","Canada","East US","West US","Central US","Canada"],["Average value","0.85","0.86","0.86","0.85","1.57","1.45","1.41","1.71"],["Alzevita 95 %\nconfidence\nintervals","(0.84,0.86)","(0.85, 0.87)","(0.85, 0.87)","(0.82, 0.88)","(1.44,1.71)","(1.35,1.55)","(1.35, 1.47)","(1.07, 2.34)"],["Criteria","Pass","Pass","Pass","Pass","Pass","Pass","Pass","Pass"]],"caption_candidate":"e) US Geographical Region","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p8-t0","doc_id":"K252838","page_num":8,"bbox":[72.26,111.14,413.71,780.22],"n_rows":50,"n_cols":5,"columns":["Trade name:","MAGNETOM","Altea","",""],"rows":[["Trade name:","MAGNETOM","Altea","",""],["510(k) Number:","K232535","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","MAGNETOM","Viato.Mobile","",""],["510(k) Number:","K250443","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","MAGNETOM","Sola Fit","",""],["510(k) Number:","K250443","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["4.2. Reference Device","","","",""],["Trade name:","MAGNETOM","Vida Fit","",""],["510(k) Number:","K220939","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","MAGNETOM","Flow.Ace","",""],["510(k) Number:","K250436","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""],["CFR Code:","21 CFR § 892.","1000","",""],["Classification:","II","","",""],["Product Code:","Primary: LNH","","",""],["","Secondary: L","NI, MOS","",""],["","","","",""],["Trade name:","MAGNETOM","Skyra Fit","",""],["510(k) Number:","K250443","","",""],["Classification Name:","Magnetic Res","onance Diagnostic","Device","(MRDD)"],["Classification Panel:","Radiology","","",""]],"caption_candidate":"Trade name: MAGNETOM Altea","well_formed":true,"extraction_settings":"text"}
{"table_id":"K252838-p19-t0","doc_id":"K252838","page_num":19,"bbox":[72.73,378.29,486.08,625.9],"n_rows":8,"n_cols":4,"columns":["Predicate Devices","FDA Clearance","Product","Manufacturer"],"rows":[["Predicate Devices","FDA Clearance","Product","Manufacturer"],["","Number and Date","Code",""],["MAGNETOM Vida with syngo MR XA60A","K231560, cleared on\nOctober 23, 2023","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Lumina with syngo MR XA60A","K231560, cleared on\nOctober 23, 2023","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Sola with syngo MR XA61A","K232535, cleared on\nDecember 22, 2023","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Altea with syngo MR XA61A","K232535, cleared on\nDecember 22, 2023","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Viato.Mobile with syngo MR\nXA70A","K250443, cleared on\nJune 16, 2024","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Sola Fit with syngo MR XA70A","K250443, cleared on\nJune 16, 2024","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"]],"caption_candidate":"XB10 are substantially equivalent to the following devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p19-t1","doc_id":"K252838","page_num":19,"bbox":[72.73,641.14,486.08,776.86],"n_rows":4,"n_cols":7,"columns":["Reference Devices","","FDA Clearance","","","Product\nCode","Manufacturer"],"rows":[["Reference Devices","","FDA Clearance","","","Product\nCode","Manufacturer"],["","","Number and Date","","","",""],["MAGNETOM Flow.Ace with syngo MR\nXA70A","K250436, cleared on\nJune 16, 2024","","","LNH,\nLNI, MOS","","Siemens\nShenzhen\nMagnetic\nResonance\nLtd."],["MAGNETOM Free.Max with syngo MR\nXA60A","K231617, cleared on\nSeptember 11, 2023","","","LNH,\nMOS","","Siemens\nShenzhen\nMagnetic\nResonance"]],"caption_candidate":"GmbH","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p20-t0","doc_id":"K252838","page_num":20,"bbox":[72.71,95.9,487.66,219.98],"n_rows":4,"n_cols":4,"columns":["","","","Ltd."],"rows":[["","","","Ltd."],["MAGNETOM Skyra Fit with syngo MR XA70A","K250443, cleared on\nJune 16, 2024","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Vida Fit with syngo MR XA50A","K220939, cleared on\nApril 29, 2022","LNH,\nLNI, MOS","Siemens\nHealthcare\nGmbH"],["syngo.via VB40A","K191040","LLZ","Siemens\nHealthcare\nGmbH"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p20-t1","doc_id":"K252838","page_num":20,"bbox":[72.71,464.47,493.79,709.42],"n_rows":7,"n_cols":3,"columns":["Performance Test","Tested Hardware or Software","Source/Rationale for test"],"rows":[["Performance Test","Tested Hardware or Software","Source/Rationale for test"],["Software verification\nand validation","New or modified software\nfeatures","Guidance for the Content of\nPremarket Submissions for Software\nContained in Medical Devices"],["Sample clinical images","Coils, new or modified\nsoftware features","Guidance for submission of Premarket\nNotifications for Magnetic Resonance\nDiagnostic Devices"],["Image quality\nassessment by sample\nclinical images","- new / modified pulse\nsequence types.\n- comparison images between\nthe new / modified features\nand the predicate device\nfeatures",""],["Performance bench\ntest","New and modified hardware",""],["Biocompatibility","surface of applied parts","ISO 10993-1"],["Electrical safety and\nelectromagnetic\ncompatibility (EMC)","Complete systems\nMAGNETOM Flow. Platform","IEC 60601-1-2"]],"caption_candidate":"The following performance testing was conducted on the subject devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p21-t0","doc_id":"K252838","page_num":21,"bbox":[72.68,136.1,503.26,628.54],"n_rows":8,"n_cols":2,"columns":["Test result summary","The impact of the network has been characterized by several quality\nmetrics such as peak signal-to-noise ratio (PSNR), structural similarity\nindex (SSIM) and normalized mean squared error (NMSE). Additionally,\nimages were inspected visually to ensure that potential artefacts are\ndetected that are not well captured by the metrics.\nAfter successful passing of the quality metrics tests, work-in-progress\npackages of the network were delivered and evaluated in clinical settings\nwith collaboration partners."],"rows":[["Test result summary","The impact of the network has been characterized by several quality\nmetrics such as peak signal-to-noise ratio (PSNR), structural similarity\nindex (SSIM) and normalized mean squared error (NMSE). Additionally,\nimages were inspected visually to ensure that potential artefacts are\ndetected that are not well captured by the metrics.\nAfter successful passing of the quality metrics tests, work-in-progress\npackages of the network were delivered and evaluated in clinical settings\nwith collaboration partners."],["Test setup","Equipment: 3T and 1.5T MRI scanners.\nProtocols: representative protocols (T1, T2*, T2, T2 FLAIR).\nBody region: brain."],["","Sample size: 29,740 2D slices."],["","Sample source: in-house measurement.\nNote: Due to the network architecture, attributes like gender, age and\nethnicity are not relevant to the training data."],["","Dataset split:\nTraining:\n20,076 slices\nValidation:\n1.5T Validation: 3,616 slices (1.5T validation);\n3T Validation: 6,048 slices (3T validation).\nNote: Data split maintained similar data distribution (e.g. contrast,\norientation, field strength, …) in both training and validation datasets."],["Patient Characteristics","No clinical subgroups have been defined for the datasets."],["Reference standard","The acquired datasets represent the ground truth for the training and\nvalidation. Input data was retrospectively created from the ground truth\nby data manipulation and augmentation. This process includes further\nunder-sampling of the data by discarding k-space lines, lowering of the\nSNR level by addition of Gaussian noise to k-space data and uniformly-\nrandom cropping of the training data along the readout direction."],["Data independency","Datasets for training and testing were split prior to training (see Test Setup\nfield above)."]],"caption_candidate":"- Deep Resolve Swift Brain:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p21-t1","doc_id":"K252838","page_num":21,"bbox":[72.68,682.66,503.26,781.42],"n_rows":2,"n_cols":2,"columns":["Test result summary","Quantitative evaluations of structural similarity index (SSIM), peak signal-\nto-noise ratio (PSNR) and mean squared error (MSE) metrics showed a\nconvergence of the training and improvements compared to conventional\nparallel imaging. An inspection of the test images did not reveal any\nnegative impact to the image quality. The function has been used either to\nacquire images faster or to improve image quality."],"rows":[["Test result summary","Quantitative evaluations of structural similarity index (SSIM), peak signal-\nto-noise ratio (PSNR) and mean squared error (MSE) metrics showed a\nconvergence of the training and improvements compared to conventional\nparallel imaging. An inspection of the test images did not reveal any\nnegative impact to the image quality. The function has been used either to\nacquire images faster or to improve image quality."],["Test setup","Equipment: 0.55T, 1.5T and 3T scanners"]],"caption_candidate":"- Deep Resolve Boost for FL3D_VIBE and Deep Resolve Boost for SPACE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p22-t0","doc_id":"K252838","page_num":22,"bbox":[72.66,95.9,503.26,514.51],"n_rows":7,"n_cols":2,"columns":["","Protocols: representative measurement protocols (T1, T2 and PD with and\nwithout fat saturation) which have been altered for training (e.g. to\nincrease SNR, increase resolution or reduce acceleration).\nBody regions: broad range of body regions\nUsed coils: broad range of coils to cover the dedicated body regions"],"rows":[["","Protocols: representative measurement protocols (T1, T2 and PD with and\nwithout fat saturation) which have been altered for training (e.g. to\nincrease SNR, increase resolution or reduce acceleration).\nBody regions: broad range of body regions\nUsed coils: broad range of coils to cover the dedicated body regions"],["","Sample size: 27,679 3D patches from 1265 measurements"],["","Dataset split: Training: 81% of the 1265 measurements\nValidation: 19% of the 1265 measurements\nNote: Data split maintained similar data distribution (e.g., contrast,\norientation, field strength, …) in both training and validation datasets."],["","Sample source: in-house measurements (training and validation) and\ncollaboration partners (testing)"],["Patient Characteristics","Gender distribution:\n- Male: 53%\n- Female 47%\nAge: for training and validation.\n- 19 - 45: 14%\n- 46 - 65: 43%\n- 66 - 89: 43%\nClinical subgroups: No clinical subgroups have been defined for the\ndatasets."],["Reference standard","The acquired datasets (as described above) represent the ground truth for\nthe training and validation. Input data was retrospectively created from\nthe ground truth by data manipulation and augmentation. This process\nincludes further undersampling of the data by discarding k-space lines as\nwell as creating sub-volumes of the acquired data."],["Data independency","Datasets determined for training and validation were split prior to training\nalong individual acquisitions to ensure that there is no mixture of sub-\nvolumes stemming from the same acquisition."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p22-t1","doc_id":"K252838","page_num":22,"bbox":[72.66,555.19,503.26,776.48],"n_rows":4,"n_cols":2,"columns":["Test result summary","The impact of the Deep Resolve Sharp network has been characterized by\nseveral quality metrics such as peak signal-to-noise ratio (PSNR), structural\nsimilarity index (SSIM), and perceptual loss. The tests include rating and an\nevaluation of image sharpness by intensity profile comparisons of\nreconstruction with and without Deep Resolve Sharp. Both tests show\nincreased edge sharpness and reduced Gibb’s artifacts."],"rows":[["Test result summary","The impact of the Deep Resolve Sharp network has been characterized by\nseveral quality metrics such as peak signal-to-noise ratio (PSNR), structural\nsimilarity index (SSIM), and perceptual loss. The tests include rating and an\nevaluation of image sharpness by intensity profile comparisons of\nreconstruction with and without Deep Resolve Sharp. Both tests show\nincreased edge sharpness and reduced Gibb’s artifacts."],["Test setup","Equipment: 0.55T, 1.5T and 3T MRI scanners\nProtocols: representative measurement protocols (T1, T2 and PD with and\nwithout fat saturation) which have been altered (e.g. to increase SNR,\nincrease resolution or reduce acceleration)\nBody regions: broad range of different body regions.\nUsed coils: broad range of coils to cover the dedicated body regions"],["","Sample size: approx. 13,000 high resolution 3D patches from 500\nmeasurements."],["","Dataset split: Training: 70% of the 500 measurements."]],"caption_candidate":"- Deep Resolve Sharp for FL3D_VIBE and Deep Resolve Sharp for SPACE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p23-t0","doc_id":"K252838","page_num":23,"bbox":[72.72,95.9,503.26,415.85],"n_rows":5,"n_cols":2,"columns":["","Validation: 30% of the 500 measurements\nNote: Data split maintained similar data distribution (e.g., contrast,\norientation, field strength, …) in both training and validation datasets."],"rows":[["","Validation: 30% of the 500 measurements\nNote: Data split maintained similar data distribution (e.g., contrast,\norientation, field strength, …) in both training and validation datasets."],["","Sample source: in-house measurements"],["Patient Characteristics","Gender distribution:\n- Male: 66.6%\n- Female 33.4%\nAge: for training and validation.\n- 19 - 45: 8.4%\n- 46 - 65: 40.2%\n- 66 - 89: 51.4%\nClinical subgroups: No clinical subgroups have been defined for the\ndatasets."],["Reference standard","The acquired datasets represent the ground truth for the training and\nvalidation. Input data was retrospectively created from the ground truth\nby data manipulation. k-space data has been cropped such that only the\ncenter part of the data was used as input. With this method\ncorresponding low-resolution data as input and high-resolution data as\noutput / ground truth were created for training and validation."],["Data independency","The high-resolution datasets were split to 70% training and 30% validation\ndatasets before training to ensure independence of them. The input and\noutput variables of the network have been derived from the same dataset\nso that no confounders exist for the training methodology."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p23-t1","doc_id":"K252838","page_num":23,"bbox":[72.72,456.55,494.26,775.04],"n_rows":3,"n_cols":2,"columns":["Test result summary","The evaluation on the test dataset confirmed very similar metrics in\nterms of peak signal-to-noise ratio (PSNR), structural similarity index\n(SSIM) and learned perceptual image patch similarity metrics (LPIPS) for\nthe predicate and the modified network with both outperforming\nconventional GRAPPA as the reference. Visual evaluations confirmed\nstatistically significant reduction of banding artifacts with no significant\nchanges in sharpness and detail visibility. In addition, the radiologist\nevaluation revealed no difference in suitability for clinical diagnostics\nbetween updated and cleared predicate network.\nThe function as on the predicate devices was modified to the subject\ndevices but the training and testing from the predicate devices still fits."],"rows":[["Test result summary","The evaluation on the test dataset confirmed very similar metrics in\nterms of peak signal-to-noise ratio (PSNR), structural similarity index\n(SSIM) and learned perceptual image patch similarity metrics (LPIPS) for\nthe predicate and the modified network with both outperforming\nconventional GRAPPA as the reference. Visual evaluations confirmed\nstatistically significant reduction of banding artifacts with no significant\nchanges in sharpness and detail visibility. In addition, the radiologist\nevaluation revealed no difference in suitability for clinical diagnostics\nbetween updated and cleared predicate network.\nThe function as on the predicate devices was modified to the subject\ndevices but the training and testing from the predicate devices still fits."],["Test setup","Equipment: 0.55T, 1.5T and 3T MRI scanners\nProtocols: representative protocols (T1, T2 and PD with and without fat\nsaturation)\nBody regions: broad range of different body regions\nUsed coils: broad range of coils to cover the dedicated body regions\nTesting of the Deep Resolve Boost network has been described in the\nreference and predicate device submissions. Additional tests have been\nperformed to evaluate the banding artifact reduction capabilities of the\nupdated network."],["","Dataset split: Training: more than 23250 slices (93%)"]],"caption_candidate":"- Deep Resolve Boost for TSE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p24-t0","doc_id":"K252838","page_num":24,"bbox":[72.77,95.9,494.26,440.69],"n_rows":6,"n_cols":2,"columns":["","Validation: more than 1750 slices (7%)\nAdditional test dataset for banding artifact reduction:\nmore than 2000 slices\nFor training and validation of the network, the identical data was used as\nfor the initial device submission (K213693).\nNote: Data split maintained similar data distribution (e.g., contrast,\norientation, field strength, …) in both training and validation datasets."],"rows":[["","Validation: more than 1750 slices (7%)\nAdditional test dataset for banding artifact reduction:\nmore than 2000 slices\nFor training and validation of the network, the identical data was used as\nfor the initial device submission (K213693).\nNote: Data split maintained similar data distribution (e.g., contrast,\norientation, field strength, …) in both training and validation datasets."],["","Sample source: in-house measurements and collaboration partners"],["Patient Characteristics","Due to reasons of data privacy, gender, age and ethnicity during data\ncollection have not been recorded. Due to the network architecture,\nattributes like gender, age and ethnicity are not relevant to the training\ndata."],["","No clinical subgroups have been defined for the collected dataset"],["Reference standard","The acquired training/validation datasets (identical to the initial\nsubmission K213693) represent the ground truth for the training and\nvalidation. Input data was retrospectively created from the ground truth\nby data manipulation and augmentation. This process includes further\nundersampling of the data by discarding k-space lines, lowering of the\nSNR level by addition of noise and mirroring of k-space data."],["Data independency","Training and validation datasets were kept independent from each other\nduring training and validation. The acquired datasets (one dataset\nconsists of a group of multiple slices) were split into 93% training and 7%\nvalidation data prior to the training. A similar distribution was\nmaintained for training and validation data. The test dataset for banding\nartifact reduction was acquired after the release of the predicate\nnetwork and is therefore independent of the training/validation data."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252838-p25-t0","doc_id":"K252838","page_num":25,"bbox":[77.56,109.42,499.38,745.9],"n_rows":18,"n_cols":5,"columns":["","Product\nArea","","",""],"rows":[["","Product\nArea","","",""],["Recogniti","","","","Standards"],["","","","Reference",""],["on","","Title of Standard","","Development"],["","","","Number and date",""],["Number","","","","Organization"],["","","","",""],["","","","",""],["19-46","General II\n(ES/ EMC)","Medical electrical equipment - Part\n1: General requirements for basic\nsafety and essential performance\n(IEC 60601-1:2005, MOD)","ES60601-1:2005\n/(R)2012 &\nA1:2012,\nC1:2009/(R)2012\n&A2:2010/(R)201\n2 (Cons. Text)\n[Incl.AMD2:2021]","ANSI AAMI"],["19-36","General","Medical electrical equipment - Part\n1-2: General requirements for basic\nsafety and essential performance -\nCollateral Standard:\nElectromagnetic disturbances -\nRequirements and tests","60601-1-2 Edition\n4.1 2020-09","IEC"],["12-347","Radiology","Medical electrical equipment - Part\n2-33: Particular requirements for\nthe basic safety and essential\nperformance of magnetic\nresonance equipment for medical\ndiagnosis","60601-2-33\nEdition 4.0 2022-\n08","IEC"],["5-125","General I\n(QS/ RM)","Medical devices - Application of risk\nmanagement to medical devices","14971 Third\nedition 2019-12","ISO"],["5-129","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability engineering\nto medical devices","62366-1: 2015 +\nAMD1:2020","IEC"],["13-79","Software/\nInformatic\ns","Medical device software - Software\nlife cycle processes [Including\nAmendment 1 (2016)]","IEC 62304:2006 +\nAMD1:2015","IEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing Magnetic\nResonance Imaging Devices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased Array\nCoils for Diagnostic Magnetic\nResonance Images","MS 9-2008\n(R2020)","NEMA"],["12-352","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM)","PS 3.1 - 3.20\n(2023e)","NEMA"],["2-258","Biocompat\nibility","Biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk management\nprocess. (Biocompatibility)","10993-1: 2018","ANSI\nAAMI\nISO"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p8-t0","doc_id":"K252856","page_num":8,"bbox":[68.87,137.63,742.62,491.5],"n_rows":5,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Product Code","QIH, LLZ","QIH, LLZ","Yes","---"],["Regulation\nNumber","21 CFR 892.2050","21 CFR 892.2050","Yes","---"],["Regulation Name","Medical Image Management And\nProcessing System","Medical Image Management And\nProcessing System","Yes","---"],["Intended\nuse/Indications for\nuse","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment are\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of\nplanning the 2D or 3D environment. The\nsystem is designed for the medical","PeekMed web is a system designed to\nhelp healthcare professionals carry out\npre-operative planning for several surgical\nprocedures, based on their imported\npatients’ imaging studies. Experience in\nusage and a clinical assessment are\nnecessary for the proper use of the system\nin the revision and approval of the output\nof the planning. The multi-platform system\nworks with a database of digital\nrepresentations related to surgical\nmaterials supplied by their manufacturers.\nThis medical device consists of a decision\nsupport tool for qualified healthcare\nprofessionals to quickly and efficiently\nperform the pre-operative planning for\nseveral surgical procedures, using medical\nimaging with the additional capability of\nplanning the 2D or 3D environment. The\nsystem is designed for the medical","Yes","---"]],"caption_candidate":"Table 1: Summary of Predicate and Subject Device Characteristics to Demonstrate Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p9-t0","doc_id":"K252856","page_num":9,"bbox":[68.84,113.0,742.71,494.5],"n_rows":8,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","specialties within surgery, and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","specialties within surgery, and no specific\nuse environment is mandatory, whereas\nthe typical use environment is a room with\na computer. The patient target group is\nadult patients who have an injury or\ndisability diagnosed previously. There are\nno other considerations for the intended\npatient population.","",""],["Contraindications","No contraindications specific to this device.","No contraindications specific to this device.","Yes","---"],["Clinical purpose","The PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","The PeekMed web allows the surgeon to\nperform orthopedic pre-surgical planning\nefficiently in the musculoskeletal system\n(e.g., Hip procedures, Knee procedures)","Yes","---"],["Anatomical regions","The PeekMed web allows the surgeon to\nperform pre-surgical planning efficiently in\nthe following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","The PeekMed web allows the surgeon to\nperform pre-surgical planning efficiently in\nthe following anatomical regions:\n- Hip\n- Knee\n- Upper limb\n- Foot","Yes","—"],["Patient Population","Adults","Adults","Yes","---"],["End users","Healthcare Professionals","Healthcare Professionals","Yes","---"],["Device availability","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run a web\nbrowser","Software is cloud-based (not installable)\nand can be displayed on any personal\ndevice or workstation that can run a web\nbrowser","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p10-t0","doc_id":"K252856","page_num":10,"bbox":[68.9,113.0,742.71,486.5],"n_rows":11,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Software\nArchitecture","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Distributed system (cloud-based). This\ndistributed system is a combination of\nsoftware modules placed on servers that\nare able to communicate with each other.","Yes","---"],["Workflow","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","The workflow is as follows: Import case\nimages, configure images, identify the\ncase, pre-surgical planning, and export the\ncase.","Yes","---"],["Internet connection","Required","Required","Yes","---"],["Images source","Receives medical images from various\nsources","Receives medical images from various\nsources","Yes","---"],["Data processing","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","The software processes data to provide an\noverlap and dimensioning of digital\nrepresentations of the prosthetic material","Yes","---"],["Digital overlap of\ntemplates","Allows the overlap of models and the\nintersection of the models","Allows the overlap of models and the\nintersection of the models","Yes","---"],["Interactive model\npositioning","Yes","Yes","Yes","---"],["Interactive model\ndimensioning","Yes","Yes","Yes","---"],["Model rotation","Yes","Yes","Yes","---"],["Support for digital\nprosthetic\nmaterials provided","Yes","Yes","Yes","---"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p11-t0","doc_id":"K252856","page_num":11,"bbox":[68.9,113.0,742.71,488.5],"n_rows":9,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["by the\nmanufacturers","","","",""],["Pre-surgical\nplanning","Yes","Yes","Yes","---"],["Type of\npre-surgical\nplanning","Automatic or Manual","Automatic or Manual","Yes","---"],["Contact with the\npatient","No","No","Yes","---"],["Control of life\nsupporting devices","No","No","Yes","---"],["Human\nintervention for\nimage\ninterpretation","Yes","Yes","Yes","---"],["Ability to add\nadditional modules\nwhen available","Yes","Yes","Yes","---"],["Automatic bone\nsegmentation","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray, CT scan, and MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes\n- Hip (X-ray and CT scan)\n- Knee (X-ray - AP & LAT view, CT scan,\nand MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","Yes","The subject device includes new ML\nmodel variants for the segmentation of\nthe Knee in a Lateral view.\nBoth devices allow planning for the\nknee region with X-rays in an AP view,\nbut the subject device also offers a\nnew image perspective (Lateral view)."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p12-t0","doc_id":"K252856","page_num":12,"bbox":[68.9,113.0,742.67,489.0],"n_rows":3,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","","","","This does not constitute an intended\npurpose update, nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices.\nCompared to the predicate device, the\nsubject device includes updates to\nexisting ML variants and the introduction\nof new ML variants, such as the\nsegmentation and landmarking for the\nknee region. In addition, certain\npreviously cleared variants have\nundergone updates to improve\nperformance while maintaining the same\nintended use. These modifications do\nnot alter the overall intended use of the\ndevice"],["Type of\nlandmarking","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray, CT scan, and MRI)","Automatic or Manual\n- Hip (X-ray and CT scan)\n- Knee (X-ray - AP & LAT view, CT scan,","Yes","The subject device includes new ML\nmodel variants for landmarking for the\nKnee in a Lateral view."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p13-t0","doc_id":"K252856","page_num":13,"bbox":[68.9,113.0,742.59,496.0],"n_rows":2,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["","- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","and MRI)\n- Upper limb (CT scan)\n- Foot (X-ray and CT scan)","","Both devices allow planning for the\nknee region with X-rays in an AP view,\nbut the subject device also offers a\nnew image perspective (Lateral view).\nThis does not constitute an intended\npurpose update, nor does it raise\nquestions of safety and performance,\nsince the development, verification,\nvalidation, and deployment processes\nare the same for both devices.\nCompared to the predicate device, the\nsubject device includes updates to\nexisting ML variants and the introduction\nof new ML variants, such as the\nsegmentation and landmarking for the\nknee region. In addition, certain\npreviously cleared variants have\nundergone updates to improve\nperformance while maintaining the same\nintended use. These modifications do\nnot alter the overall intended use of the\ndevice"]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252856-p14-t0","doc_id":"K252856","page_num":14,"bbox":[68.9,113.0,742.59,382.0],"n_rows":2,"n_cols":5,"columns":["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],"rows":[["Characteristic","PeekMed web\nPredicate device K251096","PeekMed web\nSubject device","Substantially\nEquivalent?","Justification and rationale"],["Bone\nreconstruction","Yes – Reconstruction of 3D anatomical\nrepresentation from 3D imaging modalities\n(e.g., CT, MRI).","Yes\nReconstruction of 3D anatomical\nrepresentation from 3D imaging modalities\n(e.g., CT, MRI) and additionally from 2D\nimaging modalities (X-ray).","Yes","Both devices provide reconstruction\ncapabilities for generating an anatomical\nrepresentation. The subject device\nextends the input modalities to include 2D\nX-rays, enabling reconstruction of 3D\nmodels where only planar images are\navailable. This does not alter the intended\nuse or indications for use, as the function\nremains within pre-surgical planning for\nthe same anatomical regions. The\nreconstructed models can be integrated\ninto planning and analysis workflows. The\ncapability is decision-support only, with\noutputs subject to review and approval by\nhealthcare professionals. The\ndevelopment, verification, validation, and\ndeployment processes follow the same\nmethodology, and no new safety or\neffectiveness concerns are raised."]],"caption_candidate":"PeekMed web","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p5-t0","doc_id":"K252922","page_num":5,"bbox":[73.25,415.5,420.5,563.5],"n_rows":6,"n_cols":2,"columns":["Trade Name","Neosoma Brain Mets"],"rows":[["Trade Name","Neosoma Brain Mets"],["Common Name","Automated radiological image processing software"],["Product Code","QKB, QIH"],["Regulation Number","21 CFR 892.2050"],["Class","Class II"],["Panel","Radiology"]],"caption_candidate":"2 DEVICE INFORMATION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p5-t1","doc_id":"K252922","page_num":5,"bbox":[73.25,606.5,363.5,705.5],"n_rows":4,"n_cols":2,"columns":["Device Name","VBrain"],"rows":[["Device Name","VBrain"],["Manufacturer","Vysioneer Inc."],["510(k) Number","K203235"],["Product Code","QKB"]],"caption_candidate":"3 PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p6-t0","doc_id":"K252922","page_num":6,"bbox":[72.5,72.5,363.5,184.5],"n_rows":4,"n_cols":2,"columns":["Regulation Number","892.2050"],"rows":[["Regulation Number","892.2050"],["Regulation Name","Medical image management and\nprocessing system."],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p6-t1","doc_id":"K252922","page_num":6,"bbox":[72.5,227.5,363.5,438.5],"n_rows":8,"n_cols":2,"columns":["Device Name","NS-HGlio"],"rows":[["Device Name","NS-HGlio"],["Manufacturer","Neosoma Inc."],["510(k) Number","K221738"],["Product Code","QIH"],["Regulation Number","892.2050"],["Regulation Name","Medical image management and\nprocessing system."],["Regulatory Class","Class II"],["Review Panel","Radiology"]],"caption_candidate":"4 REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p8-t0","doc_id":"K252922","page_num":8,"bbox":[72.5,93.5,737.5,530.5],"n_rows":3,"n_cols":5,"columns":["Characteristic","Subject Device\nNeosoma Brain Mets","Predicate Device\nVBrain (K203235)","Reference Device\nNS-HGlio (K221738)","Substantial Equivalence Discussion"],"rows":[["Characteristic","Subject Device\nNeosoma Brain Mets","Predicate Device\nVBrain (K203235)","Reference Device\nNS-HGlio (K221738)","Substantial Equivalence Discussion"],["Regulation and\nProduct Code","21 CFR 892.2050\nQIH & QKB","21 CFR 892.2050\nQKB","21 CFR 892.2050\nQIH","All devices fall under the same regulation 21 CFR\n892.2050.\nThe subject device also falls under the same\nproduct codes as the predicate and reference\ndevices."],["Indications for\nUse","The Neosoma\nsoftware uses an\nartificial intelligence\nalgorithm (i.e., deep\nlearning neural\nnetworks) to contour\n(segment) known or\npreviously diagnosed\nbrain tumors on MRI\nimages for qualified\nand trained medical\nprofessionals.\nThe technology is\nmeant for\ninformational\npurposes only and not\nintended to replace\nthe clinician’s current\nstandard practice of\nmanual contouring.\nThe software does not","VBrain is a software\ndevice intended to\nassist trained medical\nprofessionals, during\ntheir clinical workflows\nof radiation therapy\ntreatment planning, by\nproviding initial object\ncontours of known\n(diagnosed) brain\ntumors (i.e., region of\ninterest, ROI) on axial\nTl contrast enhanced\nbrain MRI images.\nVBrain uses an\nartificial intelligence\nalgorithm (i.e., deep\nlearning neural\nnetworks) to contour\n(segment) brain\ntumors on MRI images","NS-HGlio is intended\nfor the semi-automatic\nlabeling, visualization,\nand volumetric\nquantification of\nhigh-grade brain\nglioma (WHO grade 3\nastrocytoma, WHO\ngrade 4\nastrocytoma and WHO\ngrade 4 glioblastoma)\nfrom a set of standard\nMRI images of male or\nfemale patients 18\nyears of age or older\nwho are known to\nhave pathologically\nproven\nhigh-grade glioma.\nVolumetric\nmeasurements may be","The indications for use of Neosoma software\nand VBrain are highly similar in scope, intended\nuser, and clinical application. Both devices are\nsoftware tools designed to assist trained medical\nprofessionals, particularly in the context of\nradiation therapy treatment planning and\nrelated clinical workflows, by providing\nsemi-automatic contouring of known or\npreviously diagnosed brain tumors on MRI\nimages. Both employ artificial intelligence (deep\nlearning neural networks) to generate Gross\nTumor Volume (GTV) contours, are intended for\ninformational purposes only, do not replace\nstandard manual contouring practices, do not\nalter the original MRI image, and are not\nintended for tumor detection or diagnosis."]],"caption_candidate":"7 SUBSTANTIAL EQUIVALENCE DISCUSSION","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p10-t0","doc_id":"K252922","page_num":10,"bbox":[72.5,72.5,737.5,537.5],"n_rows":8,"n_cols":5,"columns":["","treatment planning\nsystem.","","",""],"rows":[["","treatment planning\nsystem.","","",""],["Modality","MRI:\nT1 postcontrast","MRI:\nT1 postcontrast","MRI:\nT1 precontrast, T1\npostcontrast, T2 and\nT2-FLAIR","Same as the predicate device."],["Anatomical Target","Brain","Brain","Brain","Same."],["Image Review","2D and 3D","2D and 3D","2D and 3D","Same."],["Segmentation","ML based\nsemi-automatic\nsegmentation of brain\nmetastasis","ML based\nsemi-automatic and\nmanual segmentation\nof brain\nmetastasis","ML based\nsemi-automatic\nsegmentation of\nbrain high grade\nglioma","Same as the predicate device."],["Quantification","Volumetric\nmeasurement of the\nbrain metastasis","Volumetric\nmeasurement of the\nbrain metastasis","Volumetric\nmeasurement of\nthe brain high\ngrade glioma","Same as the predicate device."],["Output","Provides volumetric\nmeasurements of\nbrain metastasis.\nIncludes segmented\ncolor overlays of\nbrain metastasis\nand reports.","Provides volumetric\nmeasurements of\nbrain metastasis.\nIncludes segmented\ncolor overlays of\nbrain metastasis\nand reports.","Provides\nvolumetric\nmeasurements of brain\nhigh grade\nglioma. Includes\nsegmented color\noverlays.","Same as predicate device."],["Architecture","Leverages a common","Unknown.","Same pre and post","The subject device uses the same pre and post"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p12-t0","doc_id":"K252922","page_num":12,"bbox":[137.5,635.5,540.5,698.5],"n_rows":2,"n_cols":3,"columns":["Metric","Acceptance Criteria","Performance Results"],"rows":[["Metric","Acceptance Criteria","Performance Results"],["Sensitivity","≥ 0.85","0.90 with 95% CI of 0.87 -\n0.94"]],"caption_candidate":"between device and reference standard surfaces.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252922-p13-t0","doc_id":"K252922","page_num":13,"bbox":[137.5,72.5,540.5,224.5],"n_rows":4,"n_cols":3,"columns":["False Positive Rate","≤ 5 false positive lesions\nper MRI","0.57 lesions per MRI with\n95% CI of 0.35 - 0.80"],"rows":[["False Positive Rate","≤ 5 false positive lesions\nper MRI","0.57 lesions per MRI with\n95% CI of 0.35 - 0.80"],["DSC","≥ 0.70","0.86 with 95% CI of 0.83 -\n0.89"],["HD95","≤ 2.94 mm","1.78 mm with 95% CI of\n1.02 - 2.54"],["MSD","≤ 0.66 mm","0.36 mm with 95% CI of\n0.16 - 0.56"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252934-p7-t0","doc_id":"K252934","page_num":7,"bbox":[72.63,88.61,539.37,703.74],"n_rows":59,"n_cols":9,"columns":["Criteria","","","Diagnocat (Subject Device)","","","","Overjet Periapical Radiolucency",""],"rows":[["Criteria","","","Diagnocat (Subject Device)","","","","Overjet Periapical Radiolucency",""],["","","","","","","","Assist (Predicate Device) (K231678)",""],["Classification","","","","21 CFR 892.2070 (Medical Image","","","21 CFR 892.2070 (Medical Image",""],["","","","","Analyzer)","","","Analyzer)",""],["","Product Code","","","MYN","","","MYN",""],["Indications for\nUse","Indications for","","","Diagnocat software is a radiological,","","Overjet Periapical Radiolucency\n(PARL) Assist is a radiological,\nautomated, concurrent read computer-\nassisted detection software intended to\naid in the detection of periapical\nradiolucency on permanent teeth\ncaptured on periapical radiographs.\nThe device provides additional aid for\nthe dentist to use in their identification\nof periapical radiolucency. The device\nis not intended as a replacement for a\ncomplete dentist’s review or their\nclinical judgment that considers other\nrelevant information from the image or\npatient history. The system is to be\nused by professionally trained and\nlicensed dentists.\nThe Overjet Periapical Radiolucency\nAssist software is indicated for use on\npatients 12 years of age or older.","Overjet Periapical Radiolucency",""],["","Use","","","automated, concurrent read computer-","","","(PARL) Assist is a radiological,",""],["","","","","assisted detection software intended to","","","automated, concurrent read computer-",""],["","","","","","","","assisted detection software intended to",""],["","","","","aid in the detection of periapical","","","",""],["","","","","","","","aid in the detection of periapical",""],["","","","","radiolucency on permanent teeth","","","",""],["","","","","","","","radiolucency on permanent teeth",""],["","","","","captured on maxillofacial Cone Beam CT","","","",""],["","","","","","","","captured on periapical radiographs.",""],["","","","","images, using scans that were previously","","","",""],["","","","","","","","The device provides additional aid for",""],["","","","","acquired for clinically justified purposes","","","",""],["","","","","","","","the dentist to use in their identification",""],["","","","","independent of Diagnocat. Diagnocat","","","of periapical radiolucency. The device",""],["","","","","may be used only when a dental","","","is not intended as a replacement for a",""],["","","","","professional has independently","","","complete dentist’s review or their",""],["","","","","determined that CBCT imaging is","","","clinical judgment that considers other",""],["","","","","necessary for further evaluation of the","","","relevant information from the image or",""],["","","","","","","","patient history. The system is to be",""],["","","","","patient. The device provides additional","","","",""],["","","","","","","","used by professionally trained and",""],["","","","","aid for the dental professional to use in","","","",""],["","","","","","","","licensed dentists.",""],["","","","","their identification of periapical","","","",""],["","","","","","","","",""],["","","","","radiolucency. The device is not intended","","","The Overjet Periapical Radiolucency",""],["","","","","","","","Assist software is indicated for use on",""],["","","","","as a replacement for a complete dental","","","",""],["","","","","","","","patients 12 years of age or older.",""],["","","","","professional’s review or their clinical","","","",""],["","","","","judgment that considers other relevant","","","",""],["","","","","information from the patient or other","","","",""],["","","","","images or patient history. The system is","","","",""],["","","","","to be used by professionally trained and","","","",""],["","","","","licensed dental professionals with the","","","",""],["","","","","appropriate knowledge and training to","","","",""],["","","","","interpret maxillofacial CBCT images,","","","",""],["","","","","including at least two years of clinical","","","",""],["","","","","experience reading and assessing CBCT","","","",""],["","","","","scans.","","","",""],["","","","","","","","",""],["","","","","Diagnocat is indicated for use by dental","","","",""],["","","","","professionals for the second-read of","","","",""],["","","","","CBCT radiographs of permanent teeth in","","","",""],["","","","","patients 22 years of age or older.","","","",""],["","","","","","","","",""],["","Inputs","","","CBCT images","","","2D X-rays",""],["Automated\nDetection Outputs","Automated","","","1) Panoramic Reconstruction:","","","(1) Pathology Detection with",""],["","Detection Outputs","","","CBCT visualization","","","Localization: CADe of",""],["","","","","2) Pathology Detection with","","","suspected dental findings per",""],["","","","","Localization: CADe of suspected","","","tooth.",""],["","","","","periapical radiolucency per tooth.","","","",""],["","Dental Findings","","","Periapical radiolucency","","","Periapical radiolucency",""]],"caption_candidate":"Table 1: Comparison of Diagnocat and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252934-p8-t0","doc_id":"K252934","page_num":8,"bbox":[72.63,73.53,539.37,166.94],"n_rows":6,"n_cols":9,"columns":["Criteria","","","Diagnocat (Subject Device)","","","","Overjet Periapical Radiolucency",""],"rows":[["Criteria","","","Diagnocat (Subject Device)","","","","Overjet Periapical Radiolucency",""],["","","","","","","","Assist (Predicate Device) (K231678)",""],["","Reader Workflow","","","Concurrent Reading","","","Concurrent Reading",""],["","Algorithm","","","Supervised machine learning","","","Supervised machine learning",""],["","Image Format","","","DICOM , JPEG, TIFF, PNG","","","JPG, PNG, EOP, JIF, DICOM",""],["","Configuration","","","Web and Desktop application","","","Desktop application",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252934-p8-t1","doc_id":"K252934","page_num":8,"bbox":[117.27,545.84,494.73,608.04],"n_rows":4,"n_cols":9,"columns":["","Endpoint","","","Cohort","","","Mean DSC",""],"rows":[["","Endpoint","","","Cohort","","","Mean DSC",""],["Teeth Segmentation","","","Cohort 1","","","0.955","",""],["Teeth Segmentation","","","Cohort 2","","","0.947","",""],["Periapical Radiolucency Segmentation","","","Cohort 2","","","0.804","",""]],"caption_candidate":"defined performance goals (PG).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252934-p9-t0","doc_id":"K252934","page_num":9,"bbox":[200.26,109.4,411.68,155.94],"n_rows":3,"n_cols":6,"columns":["","Metric","","","Mean",""],"rows":[["","Metric","","","Mean",""],["Sensitivity","","","0.854","",""],["Specificity","","","0.991","",""]],"caption_candidate":"the pre-defined PGs.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252934-p9-t1","doc_id":"K252934","page_num":9,"bbox":[180.27,316.82,431.73,379.02],"n_rows":4,"n_cols":6,"columns":["","Reading Modality","","","AUC",""],"rows":[["","Reading Modality","","","AUC",""],["Unaided","","","0.8940","",""],["Aided","","","0.9213","",""],["AUC Difference","","","+0.027","",""]],"caption_candidate":"increased by 0.027 compared to unaided interpretation.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p8-t0","doc_id":"K252970","page_num":8,"bbox":[72.5,98.5,539.5,714.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],["Intended\nUse /\nIndication\ns for Use","BriefCase-Triage: CARE (Clinical AI\nReasoning Engine) Multi-Triage CT Body is a\nradiological computer aided triage and\nnotification software indicated for use in\nthe analysis of contrast and non-contrast CT\nimages of the chest, abdomen, and/or\npelvis, in adults or transitional adolescents\naged 18 and older. The device is intended to\nassist hospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communicating\nsuspected positive findings, per study, of:\n1. Diverticulitis;\n2. Abdominal-pelvic abscess;\n3. Appendicitis;\n4. Intestinal ischemia and/or\npneumatosis;\n5. Obstructive renal stone;\n6. Small bowel obstruction;\n7. Large bowel obstruction;\n8. Spleen injury;\n9. Liver injury;\n10. Kidney injury;\n11. Pelvic fracture.\nThe device flags cases with at least one\nsuspected finding to assist with\ntriage/prioritization of medical images. The\ndevice will provide a flag for each suspected\nfinding within this study. A preview image\nwill be provided for each distinct suspected\nfinding.\nBriefCase-Triage uses a foundation\nmodel-based artificial intelligence (AI)","BriefCase-Triage is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the analysis\nof CT chest, abdomen, or chest/abdomen\nexams with contrast (CTA and CT with\ncontrast) in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspected\npositive findings of Aortic Dissection (AD)\npathology.\nBriefCase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images that\nare meant for informational purposes\nonly and not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is\nnot intended to be used as a diagnostic\ndevice.\nThe results of BriefCase-Triage are\nintended to be used in conjunction with\nother patient information and based on\ntheir professional judgment, to assist\nwith triage/ prioritization."]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p9-t0","doc_id":"K252970","page_num":9,"bbox":[72.5,72.5,539.5,711.5],"n_rows":4,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],["","system to analyze images and highlight\ncases with detected findings in parallel to\nthe ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected\nfindings. Notifications include compressed\npreview images for each suspected finding\nthat are meant for informational purposes\nonly and not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical images and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase-Triage are intended\nto be used in conjunction with other patient\ninformation and based on their professional\njudgment to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care.",""],["User\npopulatio\nn","Hospital networks and appropriately trained\nmedical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Clinical\nIndication","1. Diverticulitis;\n2. Abdominal-pelvic abscess;\n3. Appendicitis;\n4. Intestinal ischemia and/or\npneumatosis;\n5. Obstructive renal stone;\n6. Small bowel obstruction;\n7. Large bowel obstruction;\n8. Spleen injury;\n9. Liver injury;\n10. Kidney injury;","1. Aortic Dissection"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p10-t0","doc_id":"K252970","page_num":10,"bbox":[72.5,72.5,539.5,561.5],"n_rows":7,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],["","11. Pelvic fracture.",""],["Anatomic\nal region\nof interest","Chest, abdomen, and/or pelvis","Chest, abdomen, or chest/abdomen"],["Data\nacquisitio\nn protocol","Contrast and non-contrast CT images","CTA and CT with contrast"],["Notificatio\nn-only\n(/notificati\non alerts),\nparallel\nworkflow\ntool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interferen\nce with\nstandard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p11-t0","doc_id":"K252970","page_num":11,"bbox":[72.5,72.5,539.5,705.5],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],"rows":[["","Subject Device\nAidoc BriefCase-Triage: CARE Multi-triage\nCT Body","Predicate Device\nAidoc Briefcase-Triage for AD (K251406)"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperforma\nnce\ntesting","Inclusion Criteria:\n● Patient population: CT scans\nperformed on adults/transitional\nadults ≥ 18 years of age\n● Slice thickness: 0.5 mm - 5.0 mm\naxial\n● Contrast-enhanced and\nnon-contrast CT images*\nExclusion Criteria\n● All studies that have an inadequate\nfield of view.\n*Contrast and non-contrast CT images of\nthe chest, abdomen, and/or pelvis, as\napplicable to indication-specific inclusion\ncriteria.","Inclusion Criteria\n● Scans performed on\nadults/transitional adolescents ≥\n18 years of age.\n● CT exams with contrast (CTA and\nCT with contrast) that include at\nleast part of the aorta\n● Slice thickness 0.5 mm - 5.0 mm\nExclusion Criteria\n● All studies that have an\ninadequate field of view."],["Additional\nOperating\nPoints","4 Additional Operating Points","4 Additional Operating Points"],["Algorithm","Multi-triage module, locked artificial\nintelligence algorithm fine tuned from a\nfoundation model.","Single-triage module, locked, artificial\nintelligence algorithm fine tuned from a\nfoundation model.."],["Structure","- Integrated with image routing module via\nimage communication platform (ICP) (image\nacquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and\nnon-diagnostic Image Viewer).","- Integrated with image routing module\nvia image communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application\nfor workflow integration (feed and\nnon-diagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p12-t0","doc_id":"K252970","page_num":12,"bbox":[72.13,541.66,539.31,714.5],"n_rows":10,"n_cols":9,"columns":["Indication 1: Diverticulitis","","","","","","","",""],"rows":[["Indication 1: Diverticulitis","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.9","99.7-100","98.6%","95.1%-99.8%","98.5%","94.7%-99.8%","280","146","134"],["Indication 2: Abdominal-pelvis abscess","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.2","98.5-99.7","95%","89.9%-98%","95.7%","91%-98.4%","280","139","141"],["Indication 3: Appendicitis","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""]],"caption_candidate":"Table 2. AUC, Sensitivity, Specificity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p13-t0","doc_id":"K252970","page_num":13,"bbox":[72.06,72.5,539.28,693.5],"n_rows":34,"n_cols":9,"columns":["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],"rows":[["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.5","98.6-100","97.9%","93.9%-99.6%","97.8%","93.8%-99.6%","280","141","139"],["Indication 4: Intestinal ischemia and/or pneumatosis","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["98.8","97.5-99.7","96.6%","92.2%-98.9%","96.3%","91.5%-98.8%","280","146","134"],["Indication 5: Obstructive renal stone","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["98.6","97.3-99.5","94%","88.9%-97.2%","96.9%","92.3%-99.2%","280","150","130"],["Indication 6: Small bowel obstruction","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["97.4","95.2-99.1","95.5%","90.9%-98.2%","96%","91%-98.7%","280","154","126"],["Indication 7: Large bowel obstruction","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.6","99.1-100","97.9%","94.1%-99.6%","99.3%","95.9%-100%","280","145","135"],["Indication 8: Spleen injury","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["100","99.9-100","99.3%","96.1%-100%","98.6%","94.9%-99.8%","280","140","140"],["Indication 9: Liver injury","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.9","99.7-100","98.6%","94.9%-99.8%","98.6%","94.9%-99.8%","280","140","140"],["Indication 10: Kidney injury","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.8","99.5-100","98.6%","94.9%-99.8%","99.3%","96.1%-100.0%","280","140","140"],["Indication 11: Pelvic fracture","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["98.9","97.6-99.8","96.5%","92.0%-98.9%","96.4%","91.7%-98.8%","280","143","137"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p14-t0","doc_id":"K252970","page_num":14,"bbox":[84.12,359.9,528.17,579.68],"n_rows":3,"n_cols":7,"columns":["Time-to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],"rows":[["Time-to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],["Predicate K251406\nProcessing Time","10.7","212","10.5","10.9","10.4","0.4"],["BriefCase-Triage and\ncompatible image\ncommunication\nplatform\nTime-to-notification","45","1523","43.4","46.5","38.1","24.7"]],"caption_candidate":"Table 3. Time-to- notification comparison for Briefcase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p15-t0","doc_id":"K252970","page_num":15,"bbox":[123.74,96.64,488.26,711.64],"n_rows":37,"n_cols":6,"columns":["Indication 1: Diverticulitis","","","","",""],"rows":[["Indication 1: Diverticulitis","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["57.7","16.7","19","60","90","280"],["Indication 2: Abdominal-pelvis abscess","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["53.6","18.6","18","54.5","90","280"],["Indication 3: Appendicitis","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["50.1","18.5","18","50","90","280"],["Indication 4: Intestinal ischemia and/or pneumatosis","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["61.8","18.6","19","65","90","280"],["Indication 5: Obstructive renal stone","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["53.4","18.5","18","54","90","280"],["Indication 6: Small bowel obstruction","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["60.5","18.8","18","64","90","280"],["Indication 7: Large bowel obstruction","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["61.5","18.3","18","65.5","90","280"],["Indication 8: Spleen injury","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["55.6","19.1","18","56","90","280"],["Indication 9: Liver injury","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["53.9","19.6","18","56","90","280"],["Indication 10: Kidney injury","","","","",""]],"caption_candidate":"Table 4. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p16-t0","doc_id":"K252970","page_num":16,"bbox":[123.67,72.5,488.31,191.29],"n_rows":7,"n_cols":6,"columns":["Age (Years)","","","","",""],"rows":[["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["58.1","18.7","18","61","90","280"],["Indication 11: Pelvic fracture","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["63.0","20.8","18","68","90","280"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252970-p16-t1","doc_id":"K252970","page_num":16,"bbox":[96.1,243.57,516.1,715.5],"n_rows":28,"n_cols":7,"columns":["Indication 1: Diverticulitis","","","","","",""],"rows":[["Indication 1: Diverticulitis","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","78","27.9%","68","24.3%","146","52.1%"],["Negative","75","26.8%","59","21.1%","134","47.9%"],["All","153","54.6%","127","45.4%","280","100.0%"],["Indication 2: Abdominal-pelvis abscess","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","52","18.6%","87","31.1%","139","49.6%"],["Negative","79","28.2%","62","22.1%","141","50.4%"],["All","131","46.8%","149","53.2%","280","100.0%"],["Indication 3: Appendicitis","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","59","21.1%","82","29.3%","141","50.4%"],["Negative","75","26.8%","64","22.9%","139","49.6%"],["All","134","47.9%","146","52.1%","280","100.0%"],["Indication 4: Intestinal ischemia and/or pneumatosis","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","70","25.0%","76","27.1%","146","52.1%"],["Negative","77","27.5%","57","20.4%","134","47.9%"],["All","147","52.5%","133","47.5%","280","100.0%"]],"caption_candidate":"Table 5. Descriptive Statistics for Gender","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K252992-p6-t1","doc_id":"K252992","page_num":6,"bbox":[90.24,154.1,522.28,263.9],"n_rows":8,"n_cols":2,"columns":["Trade Name:","Philips CT Big Bore"],"rows":[["Trade Name:","Philips CT Big Bore"],["Manufacturer:","Philips Medical Systems Nederland B.V."],["510(k) Clearance:","K171850"],["Classification Regulation:","21 CFR 892.1750"],["Classification Name:","Computed tomography x-ray system"],["Classification Panel:","Radiology"],["Device Class:","II"],["Product Code:","JAK"]],"caption_candidate":"Secondary Predicate Devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p6-t2","doc_id":"K252992","page_num":6,"bbox":[90.24,277.64,522.28,387.44],"n_rows":8,"n_cols":2,"columns":["Trade Name:","Spectral CT 7500 RT"],"rows":[["Trade Name:","Spectral CT 7500 RT"],["Manufacturer:","Philips Medical Systems Nederland B.V."],["510(k) Clearance:","K240844"],["Classification Regulation:","21 CFR 892.1750"],["Classification Name:","Computed tomography x-ray system"],["Classification Panel:","Radiology"],["Device Class:","II"],["Product Code:","JAK"]],"caption_candidate":"Product Code: JAK","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p6-t3","doc_id":"K252992","page_num":6,"bbox":[90.24,414.4,522.28,550.66],"n_rows":8,"n_cols":2,"columns":["Trade Name:","CT Collaboration Live"],"rows":[["Trade Name:","CT Collaboration Live"],["Manufacturer:","Philips Healthcare (Suzhou) Co., Ltd."],["510(k) Clearance:","K242329"],["Classification Regulation:","21 CFR 892.2050\n21 CFR 892.1750"],["Classification Name:","Medical image management and processing system\nComputed tomography x-ray system"],["Classification Panel:","Radiology"],["Device Class:","Class II"],["Product Code:","LLZ, JAK"]],"caption_candidate":"Reference device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p9-t0","doc_id":"K252992","page_num":9,"bbox":[90.12,230.96,521.98,714.06],"n_rows":14,"n_cols":4,"columns":["Category","Proposed Devices","Predicate\nDevice(s)","Basis for\nSubstantial\nEquivalence"],"rows":[["Category","Proposed Devices","Predicate\nDevice(s)","Basis for\nSubstantial\nEquivalence"],["Core technology","Whole-body CT x-ray system\nwith continuous rotation","CT5300","Same fundamental\ntechnology"],["Technical basis","Single-layer detector system","CT5300","Same technological\ncharacteristics"],["Use environment,\nusers, and patient\npopulation","Hospital use; trained\noperators; patients of all ages","CT5300","Comparable"],["Clinical\napplications","Diagnostic imaging including\noncology and radiation\ntherapy planning","CT5300, Philips\nCT Big Bore,\nSpectral CT\n7500 RT","Comparable\nintended use"],["Scan operation","Continuous rotation; axial and\nhelical scan modes","CT5300","Same fundamental\noperation"],["System\narchitecture","Gantry, tube, detector, couch,\nconsole","CT5300","Same fundamental\ndesign"],["Performance\ncharacteristics","Image quality, noise, slice\nthickness, dose management","CT5300","Comparable\nperformance"],["Dose management\nand standards","Complies with applicable\nNEMA and regulatory\nstandards","CT5300","Comparable"],["Software platform","Incisive Host Platform\n(updated version)","CT5300 (prior\nversion)","Modified; supported\nby verification and\nvalidation testing"],["Bore size /\ngeometry","85 cm bore","Philips CT Big\nBore","Comparable design\nsupported by\npredicate"],["Field of view\n(EFOV)","Up to 85 cm EFOV","Philips CT Big\nBore, Spectral\nCT 7500 RT","Modified; supported\nby predicate\ntechnology and\ntesting"],["Image resolution","Improved high-resolution\nperformance","CT5300","Modified; supported\nby testing"],["Detector","Updated detector elements","CT5300","Modified; supported"]],"caption_candidate":"Table 1. Summary of Technological Comparison and Basis for Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p10-t0","doc_id":"K252992","page_num":10,"bbox":[90.12,72.24,521.98,272.66],"n_rows":4,"n_cols":4,"columns":["configuration","","","by testing"],"rows":[["configuration","","","by testing"],["Oncology / RT\nworkflow","OnPlan and RT workflow\nenhancements","CT 5300,\nSpectral CT\n7500 RT,\nPhilips CT Big\nBore","Comparable\nfunctionality"],["Advanced imaging\nfeatures","Pulmonary gating (4D CT)\nExtended field of view\n(EFOV), CT Collaboration\nLive, Precise Position, Precise\nIntervention","CT 5300,\nSpectral CT\n7500 RT,\nPhilips CT Big\nBore","Comparable\nfunctionality"],["New software\nfeatures","MM Sim auto-launch,\nCANOpen injection, Body\nperfusion","Not present in\npredicate\ndevices","New features\nsupported by\nverification and\nvalidation testing"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p10-t1","doc_id":"K252992","page_num":10,"bbox":[90.12,603.76,521.98,684.1],"n_rows":2,"n_cols":3,"columns":["Standard","Title / Description","FDA Recognition\nNumber"],"rows":[["Standard","Title / Description","FDA Recognition\nNumber"],["AAMI / ANSI ES60601-\n1:2005/(R)2012 +\namendments (Incl.\nAMD2:2021)","Medical Electrical Equipment – Part 1:\nGeneral Requirements for Basic Safety and\nEssential Performance (IEC 60601-1:2005,\nMOD)","19-46"]],"caption_candidate":"Table 2. Applicable Standards","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p11-t0","doc_id":"K252992","page_num":11,"bbox":[90.12,72.24,521.98,395.66],"n_rows":12,"n_cols":3,"columns":["IEC 60601-1-2 Ed. 4.1\n(2020)","Medical Electrical Equipment –\nElectromagnetic disturbances (EMC)\nrequirements and tests","19-36"],"rows":[["IEC 60601-1-2 Ed. 4.1\n(2020)","Medical Electrical Equipment –\nElectromagnetic disturbances (EMC)\nrequirements and tests","19-36"],["IEC 60601-1-3 Ed. 2.2\n(2021)","Radiation protection in diagnostic X-ray\nequipment","12-336"],["IEC 60601-1-6 Ed. 3.2\n(2020)","Usability engineering for medical electrical\nequipment","5-132"],["IEC 60601-2-44 Ed. 3.2\n(2016)","Particular requirements for CT equipment\nsafety and performance","12-302"],["IEC 62304 Ed. 1.1 (2015)","Medical device software – Software lifecycle\nprocesses","13-79"],["IEC 62366-1 Ed. 1.1\n(2020)","Application of usability engineering to\nmedical devices","5-129"],["ISO 14971 (2019)","Application of risk management to medical\ndevices","5-125"],["ISO 10993-1 (2018)","Biological evaluation of medical devices –\nPart 1","2-258"],["NEMA XR 25-2019","CT Dose Check","12-325"],["NEMA XR 26:2020","Access Controls for CT: Identification,\nInterlocks, and Logs","—"],["NEMA XR 28-2018\n(R2023)","User information and system function\nrelated to dose in CT","12-330"],["NEMA XR 29-2013","Standard attributes related to dose\noptimization and management","—"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p11-t1","doc_id":"K252992","page_num":11,"bbox":[90.12,422.62,521.98,639.7],"n_rows":11,"n_cols":2,"columns":["Guidance Document","Issue Date"],"rows":[["Guidance Document","Issue Date"],["Guidance for the Content of Premarket Submissions for Device Software\nFunctions","June 14, 2023"],["Design Considerations and Pre-market Submission Recommendations for\nInteroperable Medical Devices","Sep 6, 2017"],["Cybersecurity in Medical Devices: Quality System Considerations and\nContent of Premarket Submissions","June 27, 2025"],["Pediatric Information for X-ray Imaging Device Premarket Notifications","Nov 28, 2017"],["Applying Human Factors and Usability Engineering to Medical Devices","Feb 3, 2016"],["Medical X-Ray Imaging Devices Conformance with IEC Standards","Feb 21, 2023"],["Appropriate Use of Voluntary Consensus Standards in Premarket\nSubmissions for Medical Devices","Sep 14, 2018"],["Electromagnetic Compatibility (EMC) of Medical Devices","June 6, 2022"],["Performance Standards for CT Equipment and Laser Products (21 CFR\n1020.33 and 21 CFR 1040.10)","—"],["Use of International Standard ISO 10993-1","Sep 8, 2023"]],"caption_candidate":"Table 3. Applicable Guidance Documents","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K252992-p12-t0","doc_id":"K252992","page_num":12,"bbox":[90.12,257.42,521.98,418.6],"n_rows":5,"n_cols":3,"columns":["Feature","Testing Performed","Summary of Results"],"rows":[["Feature","Testing Performed","Summary of Results"],["Pulmonary Gating (4D\nCT)","Phantom testing, system\nV&V, external image\nquality review","Demonstrated acceptable image quality\nand reduced motion artifacts for\nintended use"],["Extended Field of\nView (EFOV)","Phantom testing, system\nV&V, external image\nquality review","Demonstrated acceptable geometric\nand quantitative accuracy for RT\nplanning applications"],["Body Perfusion, MM\nSim auto-launch,\nOnPlan","System V&V","Demonstrated acceptable performance\nfor intended use"],["CANOpen Injection","Subsystem and system\nV&V","Demonstrated acceptable performance\nfor intended use"]],"caption_candidate":"Table 4. Summary of Non-Clinical Performance Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253009-p7-t0","doc_id":"K253009","page_num":7,"bbox":[72.02,172.82,559.88,580.89],"n_rows":24,"n_cols":7,"columns":["Operating point","Group","","Sensitivity1","95% confi-dence","Specificity","95% confi-"],"rows":[["Operating point","Group","","Sensitivity1","95% confi-dence","Specificity","95% confi-"],["","","","","interval","1","dence interval"],["","","","","","",""],["High\nsensitivity","Lesion","> 8 mm3","0.82","[0.79; 0.86]","0.93","[0.92; 0.94]"],["","","≤ 8 mm3","0.65","[0.59; 0.71]","0.93","[0.92; 0.94]"],["","Age","> 52 years","0.76","[0.71; 0.80]","0.95","[0.94; 0.96]"],["","","≤ 52 years","0.8","[0.75; 0.84]","0.92","[0.91; 0.93]"],["","Device","Orthophos S/\nSL","0.76","[0.72; 0.81]","0.93","[0.91; 0.94]"],["","","Axeos","0.80","[0.75;0.84]","0.94","[0.91; 0.94]"],["","Gender","Male","0.78","[0.73;0.83]","0.93","[0.92; 0.95]"],["","","Female","0.79","[0.74; 0.85]","0.93","[0.91; 0.95]"],["","Endodontic\ntreatment","Tooth treated","0.82","[0.78; 0.86]","0.82","[0.77; 0.87]"],["","","Tooth un-\ntreated","0.72","[0.67; 0.78]","0.94","[0.93; 0.95]"],["Standard\nsensitivity","Lesion","> 8 mm3","0.73","[0.68; 0.77]","0.97","[0.97; 0.98]"],["","","≤ 8 mm3","0.50","[0.43; 0.57]","0.97","[0.97; 0.98]"],["","Age","> 52 years","0.64","[0.58; 0.70]","0.98","[0.97; 0.98]"],["","","≤ 52 years","0.68","[0.62; 0.74]","0.97","[0.96; 0.98]"],["","Device","Orthophos S/\nSL","0.64","[0.58; 0.69]","0.97","[0.96; 0.98]"],["","","Axeos","0.70","[0.64; 0.76]","0.98","[0.97; 0.98]"],["","Gender","Male","0.67","[0.60; 0.73]","0.97","[0.96; 0.98]"],["","","Female","0.70","[0.64; 0.76]","0.97","[0.96; 0.98]"],["","Endodontic\ntreatment","Tooth treated","0.75","[0.70; 0.80]","0.90","[0.86; 0.94]"],["","","Tooth un-\ntreated","0.56","[0.50; 0.62]","0.98","[0.97; 0.98]"],["1 Result of a representative standalone study with 306 CBCTs","","","","","",""]],"caption_candidate":"included lesion size, age, device, gender, and endodontic treatment status, with results as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253009-p7-t1","doc_id":"K253009","page_num":7,"bbox":[72.02,627.22,541.06,710.26],"n_rows":7,"n_cols":4,"columns":["Number\nof U.S.\nreaders\n= 11","Unaided","Aided","Difference"],"rows":[["Number\nof U.S.\nreaders\n= 11","Unaided","Aided","Difference"],["","OR Model-Based AUC Estimates (95% CIs)","",""],["","0.415 (0.279, 0.550)","0.639 (0.529, 0.749)","0.224 (0.124, 0.324)"],["","Tooth Level Sensitivity (95% CIs)","",""],["","0.421 (0.281, 0.562)","0.649 (0.535, 0.763)","0.227 (0.124, 0.330)"],["","Tooth Level Specificity (95% CIs)","",""],["","0.962 (0.928, 0.995)","0.946 (0.915, 0.976)","-0.016 (-0.034, 0.002)"]],"caption_candidate":"The MRMC Tooth Level AUC results are as follows:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253023-p11-t0","doc_id":"K253023","page_num":11,"bbox":[95.02,131.27,484.53,624.27],"n_rows":13,"n_cols":6,"columns":["Reference Devices","","FDA Clearance","","Product\nCode","Manufactur\ner"],"rows":[["Reference Devices","","FDA Clearance","","Product\nCode","Manufactur\ner"],["","","Number and","","",""],["","","Date","","",""],["MAGNETOM Vida with syngo MR\nXA60A","K231560,\ncleared on\nOctober 23, 2023","","","LNH,\nLNI,\nMOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Cima.X with syngo MR\nXA61A","K231587,\ncleared on\nDecember 18,\n2023","","","LNH,\nLNI,\nMOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Sola with syngo MR\nXA61A","K232535,\ncleared on\nDecember 22,\n2023","","","LNH,\nLNI,\nMOS","Siemens\nHealthcare\nGmbH"],["Biograph Vision PET/CT with\nPETsyngo VG85A","K251671,\ncleared on July 3,\n2025","","","KPS,\nJAK","Siemens\nMedical\nSolutions,\nInc. USA"],["Biograph Trinion with PETsyngo\nVK20","K251561,\ncleared on July\n31, 2025","","","KPS,\nJAK","Siemens\nMedical\nSolutions,\nInc. USA"],["MAGNETOM Free.Max with syngo\nMR XA60A","K231617,\ncleared on\nSeptember 11,\n2023","","","LNH,\nMOS","Siemens\nShenzhen\nMagnetic\nResonance\nLtd."],["MAGNETOM Flow.Ace with syngo\nMR XA70A","K250436,\ncleared on June\n16, 2024","","","LNH,\nLNI,\nMOS","Siemens\nShenzhen\nMagnetic\nResonance\nLtd."],["MAGNETOM Sola Fit with syngo MR\nXA70A","K250443,\ncleared on June\n16, 2024","","","LNH,\nLNI,\nMOS","Siemens\nHealthcare\nGmbH"],["MAGNETOM Skyra Fit with syngo\nMR XA70A","K250443,\ncleared on June\n16, 2024","","","LNH,\nLNI,\nMOS","Siemens\nHealthcare\nGmbH"],["syngo.via VB40A","K191040,\ncleared on May\n16, 2019","","","LLZ","Siemens\nHealthcare\nGmbH"]],"caption_candidate":"2020 KPS GmbH","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253023-p13-t0","doc_id":"K253023","page_num":13,"bbox":[94.36,81.51,492.81,620.85],"n_rows":8,"n_cols":2,"columns":["","improvements compared to conventional parallel imaging. An\ninspection of the test images did not reveal any negative\nimpact to the image quality. The function has been used either\nto acquire images faster or to improve image quality."],"rows":[["","improvements compared to conventional parallel imaging. An\ninspection of the test images did not reveal any negative\nimpact to the image quality. The function has been used either\nto acquire images faster or to improve image quality."],["Test setup","Equipment: 0.55T, 1.5T and 3T scanners\nProtocols: representative measurement protocols (T1, T2 and\nPD with and without fat saturation) which have been altered\nfor training (e.g. to increase SNR, increase resolution or\nreduce acceleration).\nBody regions: broad range of body regions\nUsed coils: broad range of coils to cover the dedicated body\nregions"],["","Sample size: 27,679 3D patches from 1265 measurements"],["","Dataset split: Training: 81% of the 1265 measurements\nValidation: 19% of the 1265 measurements\nNote: Data split maintained similar data distribution (e.g.,\ncontrast, orientation, field strength, …) in both training and\nvalidation datasets."],["","Sample source: in-house measurements (training and\nvalidation) and collaboration partners (testing)"],["Patient Characteristics","Gender distribution:\n- Male: 53%\n- Female 47%\nAge: for training and validation.\n- 19 - 45: 14%\n- 46 - 65: 43%\n- 66 - 89: 43%\nClinical subgroups: No clinical subgroups have been defined\nfor the datasets."],["Reference standard","The acquired datasets (as described above) represent the\nground truth for the training and validation. Input data was\nretrospectively created from the ground truth by data\nmanipulation and augmentation. This process includes further\nundersampling of the data by discarding k-space lines as well\nas creating sub-volumes of the acquired data."],["Data independency","Datasets determined for training and validation were split prior\nto training along individual acquisitions to ensure that there is\nno mixture of sub-volumes stemming from the same\nacquisition."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253023-p14-t0","doc_id":"K253023","page_num":14,"bbox":[94.36,81.51,492.81,620.85],"n_rows":8,"n_cols":2,"columns":["","tests show increased edge sharpness and reduced Gibb’s\nartifacts."],"rows":[["","tests show increased edge sharpness and reduced Gibb’s\nartifacts."],["Test setup","Equipment: 0.55T, 1.5T and 3T MRI scanners\nProtocols: representative measurement protocols (T1, T2 and\nPD with and without fat saturation) which have been altered\n(e.g. to increase SNR, increase resolution or reduce\nacceleration)\nBody regions: broad range of different body regions.\nUsed coils: broad range of coils to cover the dedicated body\nregions"],["","Sample size: approx. 13,000 high resolution 3D patches from\n500 measurements."],["","Dataset split: Training: 70% of the 500 measurements.\nValidation: 30% of the 500 measurements\nNote: Data split maintained similar data distribution (e.g.,\ncontrast, orientation, field strength, …) in both training and\nvalidation datasets."],["","Sample source: in-house measurements"],["Patient Characteristics","Gender distribution:\n- Male: 66.6%\n- Female 33.4%\nAge: for training and validation.\n- 19 - 45: 8.4%\n- 46 - 65: 40.2%\n- 66 - 89: 51.4%\nClinical subgroups: No clinical subgroups have been defined\nfor the datasets."],["Reference standard","The acquired datasets represent the ground truth for the\ntraining and validation. Input data was retrospectively created\nfrom the ground truth by data manipulation. k-space data has\nbeen cropped such that only the center part of the data was\nused as input. With this method corresponding low-resolution\ndata as input and high-resolution data as output / ground truth\nwere created for training and validation."],["Data independency","The high-resolution datasets were split to 70% training and\n30% validation datasets before training to ensure\nindependence of them. The input and output variables of the\nnetwork have been derived from the same dataset so that no\nconfounders exist for the training methodology."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253023-p15-t0","doc_id":"K253023","page_num":15,"bbox":[94.38,81.51,492.81,716.01],"n_rows":8,"n_cols":2,"columns":["","statistically significant reduction of banding artifacts with no\nsignificant changes in sharpness and detail visibility. In\naddition, the radiologist evaluation revealed no difference in\nsuitability for clinical diagnostics between updated and cleared\npredicate network.\nThe function as on the predicate devices was modified to the\nsubject devices but the training and testing from the predicate\ndevices still fits."],"rows":[["","statistically significant reduction of banding artifacts with no\nsignificant changes in sharpness and detail visibility. In\naddition, the radiologist evaluation revealed no difference in\nsuitability for clinical diagnostics between updated and cleared\npredicate network.\nThe function as on the predicate devices was modified to the\nsubject devices but the training and testing from the predicate\ndevices still fits."],["Test setup","Equipment: 0.55T, 1.5T and 3T MRI scanners\nProtocols: representative protocols (T1, T2 and PD with and\nwithout fat saturation)\nBody regions: broad range of different body regions\nUsed coils: broad range of coils to cover the dedicated body\nregions\nTesting of the Deep Resolve Boost network has been\ndescribed in the reference and predicate device submissions.\nAdditional tests have been performed to evaluate the banding\nartifact reduction capabilities of the updated network."],["","Dataset split: Training: more than 23250 slices (93%)\nValidation: more than 1750 slices (7%)\nAdditional test dataset for banding artifact\nreduction: more than 2000 slices\nFor training and validation of the network, the identical data\nwas used as for the initial device submission (K213693).\nNote: Data split maintained similar data distribution (e.g.,\ncontrast, orientation, field strength, …) in both training and\nvalidation datasets."],["","Sample source: in-house measurements and collaboration\npartners"],["Patient Characteristics","Due to reasons of data privacy, gender, age and ethnicity\nduring data collection have not been recorded. Due to the\nnetwork architecture, attributes like gender, age and ethnicity\nare not relevant to the training data."],["","No clinical subgroups have been defined for the collected\ndataset"],["Reference standard","The acquired training/validation datasets (identical to the initial\nsubmission K213693) represent the ground truth for the\ntraining and validation. Input data was retrospectively created\nfrom the ground truth by data manipulation and augmentation.\nThis process includes further undersampling of the data by\ndiscarding k-space lines, lowering of the SNR level by addition\nof noise and mirroring of k-space data."],["Data independency","Training and validation datasets were kept independent from\neach other during training and validation. The acquired\ndatasets (one dataset consists of a group of multiple slices)\nwere split into 93% training and 7% validation data prior to the"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253023-p17-t0","doc_id":"K253023","page_num":17,"bbox":[98.75,81.51,495.93,657.48],"n_rows":10,"n_cols":5,"columns":["19-36","General","Medical electrical equipment -\nPart 1-2: General\nrequirements for basic safety\nand essential performance -\nCollateral Standard:\nElectromagnetic disturbances\n- Requirements and tests","60601-1-2\nEdition 4.1\n2020-09","IEC"],"rows":[["19-36","General","Medical electrical equipment -\nPart 1-2: General\nrequirements for basic safety\nand essential performance -\nCollateral Standard:\nElectromagnetic disturbances\n- Requirements and tests","60601-1-2\nEdition 4.1\n2020-09","IEC"],["12-347","Radiolog\ny","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33\nEdition 4.0\n2022-08","IEC"],["5-125","General I\n(QS/\nRM)","Medical devices - Application\nof risk management to\nmedical devices","14971 Third\nedition 2019-\n12","ISO"],["5-129","General I\n(QS/\nRM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical\ndevices","62366-1: 2015\n+ AMD1:2020","IEC"],["13-79","Software\n/\nInformati\ncs","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1\n(2016)]","IEC\n62304:2006 +\nAMD1:2015","IEC"],["12-232","Radiolog\ny","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiolog\ny","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008\n(R2020)","NEMA"],["12-352","Radiolog\ny","Digital Imaging and\nCommunications in Medicine\n(DICOM)","PS 3.1 - 3.20\n(2023e)","NEMA"],["2-258","Biocomp\natibility","Biological evaluation of\nmedical devices - part 1:\nevaluation and testing within a\nrisk management process.\n(Biocompatibility)","10993-1: 2018","ANSI\nAAMI\nISO"],["12-382","Radiolog\ny","Performance Measurements\nof Positron Emission\nTomographs","NU 2-2024","NEMA"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p9-t0","doc_id":"K253057","page_num":9,"bbox":[72.26,114.66,711.16,517.18],"n_rows":8,"n_cols":9,"columns":["Feature","Subject Device:\nAI-Rad Companion\nBrain MR VA60","","Predicate Device:","","","Reference","","Comparison Results"],"rows":[["Feature","Subject Device:\nAI-Rad Companion\nBrain MR VA60","","Predicate Device:","","","Reference","","Comparison Results"],["","","","AI-Rad Companion","","","Device:","",""],["","","","Brain MR VA50","","","icobrain","",""],["","","","(K232305)","","","(K192130)","",""],["Brain Morphometry\nSegmentation","Pre-processing\nfunctionality for automatic\nsegmentation and\nvolumetry of MPRAGE\ndata.","Pre-processing\nfunctionality for automatic\nsegmentation and\nvolumetry of MPRAGE\ndata.","","","Image\nprocessing for\nautomatic\nsegmentation\nand volumetry\nof MPRAGE\ndata.","","","Same as predicate"],["Brain Morphometry\nQuantification","Calculation of label maps\n(display of brain\nsegmentation) and partially\ncombined label maps\n(fused with the processed\nMPRAGE data).","Calculation of label maps\n(display of brain\nsegmentation) and partially\ncombined label maps\n(fused with the processed\nMPRAGE data).","","","Normalized and\nunnormalized\nvolume and\nvolume changes\nof different\nbrain structures.","","","Same as predicate"],["Brain\nMorphometry:\nDeviation Map","Calculation of deviation\nmap (representation of\nbrain status in relation to\nreference data) and\npartially combined\ndeviation maps (fused with\nthe processed MPRAGE\ndata) User customizable\ncolor labels for the overlay\nmap.","Calculation of deviation\nmap (representation of\nbrain status in relation to\nreference data) and\npartially combined\ndeviation maps (fused with\nthe processed MPRAGE\ndata) User customizable\ncolor labels for the overlay\nmap.","","","Not available","","","Same as predicate"],["Brain Morphometry\nFollow-Up","Automatic calculation of\nthe atrophy range in","Automatic calculation of\nthe atrophy range in","","","Not available","","","Same as predicate"]],"caption_candidate":"and effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p10-t0","doc_id":"K253057","page_num":10,"bbox":[72.23,72.83,711.18,519.18],"n_rows":6,"n_cols":5,"columns":["","percentage for each\nsegmented brain structure","percentage for each\nsegmented brain structure","",""],"rows":[["","percentage for each\nsegmented brain structure","percentage for each\nsegmented brain structure","",""],["Brain Morphometry\nFollow-Up Time\nBetween Studies","Configurable between 14-\n180 days","Configurable time interval\nbetween the current and the\nprior scan should be ≥ 180\ndays and < the\nretention period.","Not available","Enhanced from the\npredicate"],["Brain White Matter\nHyperintensities\nSegmentation","Pre-processing\nfunctionality for automatic\nsegmentation and\nvolumetry of MPRAGE\nand FLAIR data.","Pre-processing\nfunctionality for automatic\nsegmentation and\nvolumetry of MPRAGE\nand FLAIR data.","Image\nprocessing for\nautomatic\nsegmentation\nand volumetry\nof FLAIR data.","Same as predicate"],["Brain White Matter\nHyperintensities\nQuantification","Calculation of white\nmatter hyperintensities\ncount and volume as per 4\nbrain regions.","Calculation of white matter\nhyperintensities count and\nvolume as per 4 brain\nregions.","Unnormalized\nvolume and\nvolume changes\nof FLAIR white\nmatter\nhyperintensities\nas per 4 brain\nregions","Same as predicate"],["Brain White Matter\nHyperintensities\nMap","Calculation of white\nmatter hyperintensities\nmap fused with the\nprocessed FLAIR data\nUser customizable color\nlabels for the overlay map.","Calculation of white matter\nhyperintensities map fused\nwith the processed FLAIR\ndata User customizable\ncolor labels for the overlay\nmap.","Calculation of\nwhite matter\nhyperintensities\nmap overlaid\nwith the FLAIR\ndata","Same as predicate"],["Brain White Matter\nHyperintensities\nInput Data","T2-weighted 3D FLAIR\nimage series.","T1-weighted MPRAGE\nand T2-weighted 3D\nFLAIR image series","T1-weighted\nMPRAGE and\nT2-weighted 3D\nFLAIR image\nseries","Streamlined from the\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p11-t0","doc_id":"K253057","page_num":11,"bbox":[72.23,72.83,711.18,530.57],"n_rows":5,"n_cols":5,"columns":["White Matter\nHyperintensities\nFollow-Up","MR images from two time\npoints to identify new or\nenlarged areas. The results\nof follow-up scan are then\nrefined by using\nmorphological operations\nto generate WMH changed\nareas between baseline and\nfollow-up scan","MR images from two time\npoints to identify new or\nenlarged areas. The results\nof follow-up scan are then\nrefined by using\nmorphological operations\nto generate WMH changed\nareas between baseline and\nfollow-up scan","Assessment of\nNew/Enlarging\nLesion count","Same as predicate"],"rows":[["White Matter\nHyperintensities\nFollow-Up","MR images from two time\npoints to identify new or\nenlarged areas. The results\nof follow-up scan are then\nrefined by using\nmorphological operations\nto generate WMH changed\nareas between baseline and\nfollow-up scan","MR images from two time\npoints to identify new or\nenlarged areas. The results\nof follow-up scan are then\nrefined by using\nmorphological operations\nto generate WMH changed\nareas between baseline and\nfollow-up scan","Assessment of\nNew/Enlarging\nLesion count","Same as predicate"],["White Matter\nHyperintensities\nFollow Up Input\nData","WMH follow-up supports\n1.5T and 3T input data in\nboth prior and current\nstudy","WMH follow-up is only\nsupported for 3T input data\nin both prior and\ncurrent study.","Both 1.5T and\n3T is supported","Enhanced from the\npredicate"],["White Matter\nHyperintensities\nFollow-Up Data\nCriteria","Not mandatory to have the\nsame Slice Thickness,\nPixel Spacing, and\nMagnetic Field Strength\nconsistent between prior\nand current studies.\n*In case if the prior and\ncurrent Magnetic Field\nStrength (0018, 0087) are\nnot same, the system will\nprocess the input data with\nan information message.","Mandatory to have the\nsame Slice Thickness,\nPixel Spacing, and\nMagnetic Field Strength\nconsistent between prior\nand current studies.","Not available","Enhanced from the\npredicate"],["White Matter\nHyperintensities &\nFollow-Up\nMulti-Vendor\nSupport","Validated with data from\nSiemens Healthineers, GE\nand Philips","Only supports data\nacquired on 3 Tesla\nSiemens Healthineers MR\nscanners","Multi-vendor\nsupport","Enhanced from the\npredicate"],["Distribution &\nArchiving","Creation of an image series\nfor a morphometry report.\nAutomatic transfer of","Creation of an image series\nfor a morphometry report.\nAutomatic transfer of","Automatic\ntransfer of\ngenerated image","Same as predicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p12-t0","doc_id":"K253057","page_num":12,"bbox":[72.23,72.83,711.18,351.73],"n_rows":6,"n_cols":5,"columns":["","generated maps and\nmorphometry report to a\nPACS system.","generated maps and\nmorphometry report to a\nPACS system.","series and\nreport to a\nPACS system.",""],"rows":[["","generated maps and\nmorphometry report to a\nPACS system.","generated maps and\nmorphometry report to a\nPACS system.","series and\nreport to a\nPACS system.",""],["User Interface\nConfirmation","Confirmation UI with\nbasic visualization\nfunctionality","Confirmation UI with basic\nvisualization functionality","Not available.","Same as predicate"],["User Interface\nConfiguration","Configuration UI","Configuration UI","Not available","Same as predicate"],["Layouts","Simplified layout\ndedicated for confirmation\nof results","Simplified layout dedicated\nfor confirmation of results","Not available","Same as predicate"],["Architecture","Cloud solution and Edge\ncomponents deployed on\ncustomer premise.","Cloud solution and Edge\ncomponents deployed on\ncustomer premise.","Cloud only\nsolution with no\ncomponents\ndeployed on\ncustomer\npremise.","Same as predicate"],["DICOM SR","DICOM structured report\nrepresentation of a natural\nlanguage report","DICOM structured report\nrepresentation of a natural\nlanguage report","DICOM\nstructured\nreport","Same as predicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p13-t0","doc_id":"K253057","page_num":13,"bbox":[83.44,231.86,528.95,597.75],"n_rows":9,"n_cols":9,"columns":["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],"rows":[["Recognition\nNumber","Product\nArea","Title of Standard","","Reference","","","Standards",""],["","","","","Number and","","","Development",""],["","","","","Date","","","Organization",""],["5-129","General","Medical Devices – Application\nof usability engineering to\nmedical devices [including\nCorrigendum 1 (2016)]","IEC 62366-1\nEdition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","IEC","",""],["5-125","General","Medical Devices – application\nof risk management to\nmedical devices","ISO 14971 Third\nEdition 2019-12","","","ISO","",""],["13-79","Software/\nInformatics","Medical device software –\nsoftware life cycle processes\n[Including Amendment 1\n(2016)]","IEC 62304\nEdition 1.1\n2015-06\nCONSOLIDATED\nVERSION","","","AAMI\nANSI\nIEC","",""],["12-349","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM) Set","PS 3.1 – 3.20\n2021e","","","NEMA","",""],["5-134","General","Medical devices – symbols to\nbe used with information to\nbe supplied by the\nmanufacturer – Part 1:\nGeneral Requirements","15223-1\nFourth edition\n2021-07","","","ISO\nIEC","",""],["13-97","Software/\nInformatics","Health software – Part 1:\nGeneral requirements for\nproduct safety","82304-1\nEdition 1.0\n2016-10","","","IEC","",""]],"caption_candidate":"FDA recognized Consensus Standards listed in Table 2.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p15-t0","doc_id":"K253057","page_num":15,"bbox":[79.42,72.83,532.78,239.85],"n_rows":12,"n_cols":8,"columns":["","","Subject Device","","","","","Icobrain (K192130)"],"rows":[["","","Subject Device","","","","","Icobrain (K192130)"],["","","All","Gender","","Field Strength","",""],["","","","M","F","1.5 T","3.0 T",""],["# Data","","100","39","61","38","62","51"],["Dice","Mean","0.60","0.60","0.59","0.62","0.58","0.58"],["","Med","0.62","0.60","0.63","0.64","0.60","N.A."],["","STD","0.14","0.12","0.17","0.15","0.16","N.A."],["","95% CI","[0.57, 0.63]","[0.56, 0.64]","[0.54, 0.63]","[0.57, 0.66]","[0.54, 0.62]","N.A."],["ASSD","Mean","0.05","0.04","0.05","0.08","0.03","N.A."],["","Med","0.00","0.00","0.00","0.01","0.00","N.A."],["","STD","0.15","0.11","0.17","0.21","0.08","N.A."],["","95% CI","[0.02, 0.08]","[0.01, 0.08]","[0.02, 0.10]","[0.03, 0.16]","[0.01, 0.05]","N.A."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253057-p15-t1","doc_id":"K253057","page_num":15,"bbox":[140.85,254.87,471.35,408.1],"n_rows":11,"n_cols":5,"columns":["","","Subject Device","",""],"rows":[["","","Subject Device","",""],["","","Siemens","GE","Philips"],["# Data","","40","30","30"],["Dice","Mean","0.64","0.56","0.55"],["","Med","0.67","0.60","0.59"],["","STD","0.15","0.14","0.16"],["","95% CI","[0.60, 0.69]","[0.51, 0.61]","[0.50, 0.61]"],["ASSD","Mean","0.02","0.09","0.04"],["","Med","0.00","0.01","0.00"],["","STD","0.06","0.23","0.11"],["","95% CI","[0.00, 0.04]","[0.03, 0.19]","[0.00, 0.08]"]],"caption_candidate":"95% CI [0.02, 0.08] [0.01, 0.08] [0.02, 0.10] [0.03, 0.16] [0.01, 0.05] N.A.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p5-t0","doc_id":"K253091","page_num":5,"bbox":[65.59,457.46,576.66,538.73],"n_rows":3,"n_cols":16,"columns":["","Device Trade","","","Regulation","","Common name","","Device","","","Product","","","Classification",""],"rows":[["","Device Trade","","","Regulation","","Common name","","Device","","","Product","","","Classification",""],["","Name","","","Number","","","","Class","","","Code(s)","","","Name",""],["ART-Plan+\n(v3.1.0)","","","892.5050","","","Medical charged-particle\nradiation therapy system","Class II","","","MUJ\nAssociated\nProduct\nCode(s):\nQKB, LLZ","","","System,\nPlanning,\nRadiation\nTherapy\nTreatment","",""]],"caption_candidate":"Device Name:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p5-t1","doc_id":"K253091","page_num":5,"bbox":[108.29,594.43,527.02,645.07],"n_rows":2,"n_cols":3,"columns":["Predicate #","Predicate trade name\n(primary predicate is listed\nfirst)","Product code"],"rows":[["Predicate #","Predicate trade name\n(primary predicate is listed\nfirst)","Product code"],["K242822","ART-Plan","MUJ"]],"caption_candidate":"Legally marketed predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p6-t0","doc_id":"K253091","page_num":6,"bbox":[108.29,128.21,527.02,167.33],"n_rows":2,"n_cols":3,"columns":["Reference device #","Reference device trade\nname","Product code"],"rows":[["Reference device #","Reference device trade\nname","Product code"],["K234068","ART-Plan","MUJ"]],"caption_candidate":"Legally marketed reference devices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p9-t0","doc_id":"K253091","page_num":9,"bbox":[52.18,327.58,584.37,695.23],"n_rows":7,"n_cols":11,"columns":["System Information Comparison","","","","","","","","","",""],"rows":[["System Information Comparison","","","","","","","","","",""],["Property","","Proposed Device","","","Primary Predicate ART-","","","Reference Device n°2","","Comment"],["","","ART-Plan+ v3.1.0","","","Plan+ v3.0.0","","","ART-Plan v2.2.0","",""],["Method of Use","Standalone software\napplication accessed via\na compliant browser\n(Chrome, Mozilla Firefox\nand Edge) on a personal\ncomputer, tablet or\nphone (In case of\nconnection to the\nplatform with a screen of\na phone or a tablet, the\nuser must choose the\noption for the desktop\nsite of his communication\ndevice. The platform is\noptimally used with 17\ninches and up screen.\nFacilitates display and\nvisualization of data by\nuser.","","","Standalone software\napplication accessed via a\ncompliant browser (Chrome,\nMozilla Firefox and Edge) on a\npersonal computer, tablet or\nphone (In case of connection to\nthe platform with a screen of a\nphone or a tablet, the user\nmust choose the option for the\ndesktop site of his\ncommunication device. The\nplatform is optimally used with\n17 inches and up screen.\nFacilitates display and\nvisualization of data by user.","","","Standalone software\napplication accessed via a\ncompliant browser (Chrome,\nMozilla Firefox and Edge) on\na personal computer, tablet\nor phone (In case of\nconnection to the platform\nwith a screen of a phone or a\ntablet, the user must choose\nthe option for the desktop\nsite of his communication\ndevice. The platform is\noptimally used with 17\ninches and up screen.\nFacilitates display and\nvisualization of data by user.","","","The proposed device, the primary\npredicate and the reference\ndevices are standalone software."],["Delineation\nMethod","AI","","","AI (deep learning neural\nnetworks)","","","AI","","","The proposed device, primary\npredicate and the reference\ndevices share an AI delineation\nmethod."],["Synthetic CT","Generation of CT density\nimage series out of\nCBCT images","","","Not applicable","","","Generation of CT density\nimage series out of multiple\nMR-image series and CBCT\nimages","","","The proposed device and\nreference device share the same\nmodule named AdaptBox that can\ngenerate synthetic-CT from CBCT\nimages."],["Dose\ncomputation","Dose computation on CT\nand/or synthetic-CT\nimages for external beam\nirradiation with photon\nbeams","","","Not applicable","","","Dose computation on CT\nand/or synthetic-CT images\nfor external beam irradiation\nwith photon beams","","","The proposed device and the\nreference device share the same\nmodule named AdaptBox that can\nperform dose computation."]],"caption_candidate":"reference device that represent an additional claim for the proposed device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p10-t0","doc_id":"K253091","page_num":10,"bbox":[52.18,96.06,584.4,282.08],"n_rows":4,"n_cols":5,"columns":["Off-line\nadaptation\ndecision-\nmaking","Assisted CBCT-based\noff-line adaptation\ndecision-making for\nsupported anatomies","Not applicable","Assisted CBCT-based off-\nline adaptation decision-\nmaking for supported\nanatomies","The proposed device and the\nreference device share the same\nmodule named AdaptBox that can\nassist off-line adaptation decision-\nmaking."],"rows":[["Off-line\nadaptation\ndecision-\nmaking","Assisted CBCT-based\noff-line adaptation\ndecision-making for\nsupported anatomies","Not applicable","Assisted CBCT-based off-\nline adaptation decision-\nmaking for supported\nanatomies","The proposed device and the\nreference device share the same\nmodule named AdaptBox that can\nassist off-line adaptation decision-\nmaking."],["Supported\nModalities for\nsegmentation","Segmentation:\nCT (injected or not), MR\nimages, DICOM\nRTSTRUCT, synthetic-\nCT from CBCT","Segmentation:\nCT (injected or not), MR\nimages, DICOM RTSTRUCT,\nsynthetic-CT from CBCT","Segmentation:\nCT (injected or not), MR\nimages, DICOM\nRTSTRUCT, synthetic-CT\nfrom CBCT","The proposed device, the primary\npredicate and the reference\ndevices propose segmentation on\nmedical images of different\nmodalities."],["Data Export","Distribution of DICOM\ncompliant Images into\nother DICOM compliant\nsystems.","Distribution of DICOM\ncompliant Images into other\nDICOM compliant systems.","Distribution of DICOM\ncompliant Images into other\nDICOM compliant systems.","The proposed device, the primary\npredicate and the reference\ndevices have identical data export\ncapabilities with DICOM format."],["Compatibility","Compatible with data\nfrom any DICOM\ncompliant systems for the\napplicable modalities.","Compatible with data from any\nDICOM compliant systems for\nthe applicable modalities.","Compatible with data from\nany DICOM compliant\nscanners for the applicable\nmodalities.","The proposed device, the primary\npredicate and the reference\ndevices have identical\ncompatibility (DICOM format)"]],"caption_candidate":"ART-Plan+","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253091-p10-t1","doc_id":"K253091","page_num":10,"bbox":[108.53,305.92,509.56,681.91],"n_rows":6,"n_cols":7,"columns":["Technical Information","","","","","",""],"rows":[["Technical Information","","","","","",""],["Property","Proposed Device\nART-Plan v3.1.0","","","","Reference\nDevice\nART-Plan v2.2.0","Comment"],["","","","Primary","","",""],["","","","Predicate ART-","","",""],["","","","Plan v3.0.0","","",""],["Segmentation\nFeatures","Automatically\ndelineates OARs\nand lymph nodes\nand targets.\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n*head and neck (on\nCT and synthetic-\nCT from CBCT\nimages)\n*thorax / breast (for\nmale/female and\non CT and\nsynthetic-CT from\nCBCT images)\n*abdomen (on CT\nimages and MR\nimages)\n*pelvis male (on\nCT, MR and\nsynthetic-CT from\nCBCT images)\n*pelvis female (on\nCT and MR\nimages)\n*brain (on CT\nimages and MR\nimages)","Automatically\ndelineates OARs\nand lymph nodes\nand targets.\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n* head and neck\n(on CT)\n* thorax/breast\n(for male/female\nand on CT)\n* abdomen (on CT\nimages and MR\nimages)\n* pelvis male (on\nCT and MR)\n* pelvis female (on\nCT images)\n* brain (on CT\nimages and MR\nimages)","","","Automatically\ndelineates OARs\nand lymph nodes\nDeep learning\nalgorithm.\nAutomatic\nsegmentation\nincludes the\nfollowing\nlocalizations:\n* head and neck\n(on CT and\nsynthetic-CT from\nCBCT images)\n* thorax/breast\n(for male/female\nand on CT and\nsynthetic-CT from\nCBCT images)\n* abdomen (on CT\nimages and MR\nimages)\n* pelvis male (on\nCT, MR and\nsynthetic-CT from\nCBCT images)\n* pelvis female (on\nCT images)\n* brain (on CT\nimages and MR\nimages)","The proposed device, the\nprimary predicate and also\nthe reference device (when\nit comes to segmentation on\nsynthetic-CT from CBCT\nimage used within the\nshared module, AdaptBox)\npropose segmentation on\nthe same localizations with\nthe same medical images of\ndifferent modalities using\nAI."]],"caption_candidate":"applicable modalities. modalities. compatibility (DICOM format)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253173-p7-t0","doc_id":"K253173","page_num":7,"bbox":[60.36,355.97,570.82,738.34],"n_rows":3,"n_cols":4,"columns":["ITEM","Proposed Device\nuCT 780 with uWS-CT-\nDual Energy Analysis","Predicate Device\nuCT 780 with uWS-CT-\nDual Energy Analysis\n(K241079)","Discussion of Differences"],"rows":[["ITEM","Proposed Device\nuCT 780 with uWS-CT-\nDual Energy Analysis","Predicate Device\nuCT 780 with uWS-CT-\nDual Energy Analysis\n(K241079)","Discussion of Differences"],["High\nVoltage\nGenerator"," Model: uXG 100 for\nmobile,\nCT140N80X4889 for\nnon-mobile;\n Maximum power:\n100kW\n kV settings: 70kV,\n80kV, 100kV, 120kV,\n140kV"," Model:\nCT140N80X4889\n Maximum power:\n100kW\n kV settings: 70kV,\n80kV, 100kV, 120kV,\n140kV","The proposed device adds\nmobile configuration and\nintroduces a new high voltage\ngenerator (uXG 100) for\nmobile configuration. uXG 100\nhas consistent performance\nparameters as\nCT140N80X4889.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."],["Gantry"," 40mm Detector\n Rotation speed: up to\n0.3s/rotation\n 70cm bore"," 40mm Detector\n Rotation speed: up to\n0.3s/rotation\n 70cm bore","Gantry tilt lock is added for\nmobile configuration.\nPerformance parameters of\ngantry for mobile configuration\nis consistent as non-mobile\nconfiguration.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."]],"caption_candidate":"Table 1 Comparison to Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253173-p8-t0","doc_id":"K253173","page_num":8,"bbox":[60.36,81.96,570.82,511.99],"n_rows":3,"n_cols":4,"columns":["Patient\nTable"," Mobile: Standard\nconfig patient table\n Non-mobile: Standard\nconfig patient table\nand High config\npatient table"," Standard config\npatient table\n High config patient\ntable","Only standard config patient\ntable is used for mobile\nconfiguration. Patient table\nlock is added for mobile\nconfiguration. Patient table\nlock device does not change\nthe performance of the\nstandard config patient table.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."],"rows":[["Patient\nTable"," Mobile: Standard\nconfig patient table\n Non-mobile: Standard\nconfig patient table\nand High config\npatient table"," Standard config\npatient table\n High config patient\ntable","Only standard config patient\ntable is used for mobile\nconfiguration. Patient table\nlock is added for mobile\nconfiguration. Patient table\nlock device does not change\nthe performance of the\nstandard config patient table.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."],["VSM"," Mobile: Wireless\nVSM\n Non-mobile: Wireless\nVSM and Wired VSM"," Wired VSM\n Wireless VSM","Only Wireless VSM is used for\nmobile configuration.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."],["PSC","• Power voltage:\n380VAC/400VAC/41\n5VAC/440VAC/460V\nAC/480VAC\n• Power frequency:\n50/60 Hz","• Power voltage:\n380VAC/400VAC/41\n5VAC/440VAC/460V\nAC/480VAC\n• Power frequency:\n50/60 Hz","PSC is strengthened for mobile\nconfiguration and a shock-\nabsorbing base is added. Also,\nthe fixing method of PSC is\noptimized. Performance\nparameters of PSC for mobile\nconfiguration are consistent as\nnon-mobile configuration.\nThe difference did not raise\nnew safety and effectiveness\nconcerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253173-p9-t0","doc_id":"K253173","page_num":9,"bbox":[122.18,649.15,523.18,767.62],"n_rows":3,"n_cols":2,"columns":["Test Item","Bench Testing Performed"],"rows":[["Test Item","Bench Testing Performed"],["Pre-test","Before reliability test, a comprehensive test is conducted on\nthe mobile configuration of uCT 780, including device\nperformance and image performance.\nThe test results indicate that all test items have been passed."],["Reliability Test","Vibration and shock tests are conducted on key components\nof the above sample device such as gantry, patient table, and"]],"caption_candidate":"Table 2 Result for environmental Testing","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253173-p10-t0","doc_id":"K253173","page_num":10,"bbox":[122.18,81.96,523.18,354.89],"n_rows":2,"n_cols":2,"columns":["","PSC respectively according to IEC 60068-2-6, IEC 60068-2-\n27 and IEC 60068-2-64 .\nReliability test conditions:\n Sine sweep：2Hz~200Hz~2Hz as one cycle, 6 cycles in\nX/Y/Z direction, respectively.\n Random vibration: 36h in X/Y/Z direction, respectively.\n Shock: ±2.5g in X/Y direction, ±4g in Z direction; 400\ncycles in each direction.\nDuring reliability condition test, the appearance of the system\nis in good condition, and there is no loose, damage and\nfracture."],"rows":[["","PSC respectively according to IEC 60068-2-6, IEC 60068-2-\n27 and IEC 60068-2-64 .\nReliability test conditions:\n Sine sweep：2Hz~200Hz~2Hz as one cycle, 6 cycles in\nX/Y/Z direction, respectively.\n Random vibration: 36h in X/Y/Z direction, respectively.\n Shock: ±2.5g in X/Y direction, ±4g in Z direction; 400\ncycles in each direction.\nDuring reliability condition test, the appearance of the system\nis in good condition, and there is no loose, damage and\nfracture."],["Post-test","After reliability test, the system is re-integrated and the same\ntest as Pre-test is re-conducted, including device performance\nand image performance.\nThe test results indicate that all test items have been passed.\nThe vibration and shock don’t impact the device performance\nmetrics and image quality."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p7-t0","doc_id":"K253265","page_num":7,"bbox":[54.5,220.5,573.5,707.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],["Intended Use\n/ Indications\nfor Use","BriefCase-Triage is a radiological computer\naided triage and notification software\nindicated for use in the analysis of abdominal\nCT images in adults or transitional\nadolescents aged 18 and older. The device is\nintended to assist hospital networks and\nappropriately trained medical specialists in\nworkflow triage by flagging and\ncommunication of suspected positive findings\nof Intra-abdominal free gas (IFG) pathologies.\nBriefCase-Triage uses an artificial intelligence\nalgorithm to analyze images and highlight\ncases with the detected findings in parallel to\nthe ongoing standard of care image\ninterpretation. The user is presented\nwith notifications for cases with suspected\nfindings. Notifications include compressed\npreview images that are\nmeant for informational purposes only and\nnot intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase-Triage are intended\nto be used in conjunction with other\npatient information and based on their","BriefCase is a radiological computer aided\ntriage and notification software indicated for\nuse in the analysis of abdominal CT images. The\ndevice is intended to assist hospital networks\nand trained radiologists in workflow triage by\nflagging and communication of suspected\npositive findings of Intra-abdominal free gas\n(IFG) pathologies.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and highlight cases\nwith detected findings on a standalone desktop\napplication in parallel to the ongoing standard\nof care image interpretation. The user is\npresented with notifications for cases with\nsuspected findings. Notifications include\ncompressed preview images that are meant for\ninformational purposes only and not intended\nfor diagnostic use beyond notification. The\ndevice does not alter the original medical\nimage and is not intended to be used as a\ndiagnostic device.\nThe results of BriefCase are intended to be used\nin conjunction with other patient information\nand based on their professional judgment, to\nassist with triage/prioritization of medical"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p8-t0","doc_id":"K253265","page_num":8,"bbox":[54.5,72.5,573.5,630.5],"n_rows":8,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],["","professional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for viewing\nfull images per the standard of care.","images. Notified clinicians are responsible for\nviewing full images per the standard of care."],["User\npopulation","Hospital networks and appropriately trained\nmedical specialists","Hospital networks and appropriately trained\nmedical specialists"],["Anatomical\nregion of\ninterest","Abdomen","Abdomen"],["Data\nacquisition\nprotocol","Abdominal CT images","Abdominal CT images"],["Notification-o\nnly\n(/notification\nalerts),\nparallel\nworkflow tool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interference\nwith standard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p9-t0","doc_id":"K253265","page_num":9,"bbox":[54.5,72.5,573.5,620.5],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],"rows":[["","Subject Device\nAidoc Briefcase-Triage for IFG","Predicate Device\nAidoc Briefcase-Triage for IFG (K193298)"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperformance\ntesting","Inclusion criteria\n● CT studies of the abdomen.\n● Scans performed on\nadults/transitional adults ≥ 18 years\nof age.\n● Slice thickness 0.6 mm-5 mm.\nExclusion Criteria\n● All studies that have an inadequate\nfield of view","Inclusion criteria\n● Scans performed on\nadults/transitional adults ≥ 18 years of\nage.\n● Scans performed on CT scanners\nwith 64 or greater number of detectors.\n● CT studies of the abdomen.\n● Slice thickness 0.625 mm-5 mm\naxial.\nExclusion Criteria\n● All scans that are technically\ninadequate, including motion artifacts,\nsevere metal artifacts, or an inadequate\nfield of view."],["Additional\nOperating\nPoints","4 Additional Operating Points","N/A"],["Algorithm","Artificial intelligence algorithm with database\nof images.","Artificial intelligence algorithm with database of\nimages."],["Structure","- Integrated with image routing module via\nimage communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and\nnon-diagnostic Image Viewer).","- AHS module ( image acquisition);\n- ACS module (image processing);\n- Aidoc Desktop Application for workflow\nintegration (Feed/Worklist (alternate\nnames) and non-diagnostic Image Viewer)."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p11-t0","doc_id":"K253265","page_num":11,"bbox":[130.5,116.92,481.5,186.69],"n_rows":2,"n_cols":7,"columns":["","Mean","Std","Min","Median","Max","N"],"rows":[["","Mean","Std","Min","Median","Max","N"],["Age (Years)","56.7","18.7","18","60","90","394"]],"caption_candidate":"Table 2. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p11-t1","doc_id":"K253265","page_num":11,"bbox":[184.43,242.76,426.65,398.3],"n_rows":6,"n_cols":7,"columns":["Ground\nTruth\nResults","Gender","","","","All",""],"rows":[["Ground\nTruth\nResults","Gender","","","","All",""],["","Female","","Male","","",""],["","N","%","N","%","N","%"],["Positive","77","19.8%","93","23.9%","170","43.7%"],["Negative","130","33.4%","89","22.9%","219","56.3%"],["All","207","53.2%","182","46.8%","389","100.0%"]],"caption_candidate":"Table 3. Frequency Distribution of Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p11-t2","doc_id":"K253265","page_num":11,"bbox":[184.43,460.15,426.65,574.5],"n_rows":6,"n_cols":3,"columns":["Manufacturer","N","%"],"rows":[["Manufacturer","N","%"],["Philips","133","33.8%"],["SIEMENS","101","25.6%"],["GE MEDICAL SYSTEMS","90","22.8%"],["TOSHIBA","70","17.8%"],["Total","394","100%"]],"caption_candidate":"Table 4. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p11-t3","doc_id":"K253265","page_num":11,"bbox":[176.31,626.14,434.22,708.52],"n_rows":3,"n_cols":3,"columns":["Slice Thickness (mm)","N","%"],"rows":[["Slice Thickness (mm)","N","%"],["0.6-1.5","39","9.9%"],["1.5-2.5","139","35.3%"]],"caption_candidate":"Table 5. Frequency Distribution of Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p12-t0","doc_id":"K253265","page_num":12,"bbox":[176.35,72.13,435.2,147.12],"n_rows":3,"n_cols":3,"columns":["Slice Thickness (mm)","N","%"],"rows":[["Slice Thickness (mm)","N","%"],["2.5-5","216","54.8%"],["Total","394","100%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p12-t1","doc_id":"K253265","page_num":12,"bbox":[83.58,273.39,528.0,453.5],"n_rows":9,"n_cols":6,"columns":["Sensitivity","","","","",""],"rows":[["Sensitivity","","","","",""],["Site","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["Site 1","32","29","90.6%","75.0%","98.0%"],["Site 2","26","24","92.3%","74.9%","99.1%"],["Site 3","29","27","93.1%","77.2%","99.2%"],["Site 4","29","29","100.0%","88.1%","100.0%"],["Site 5","29","29","100.0%","88.1%","100.0%"],["Site 6","28","25","89.3%","71.8%","97.7%"],["all","173","163","94.2%","89.6%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p12-t2","doc_id":"K253265","page_num":12,"bbox":[83.58,505.56,528.0,686.5],"n_rows":9,"n_cols":6,"columns":["Specificity","","","","",""],"rows":[["Specificity","","","","",""],["Site","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["Site 1","35","34","97.1%","85.1%","99.9%"],["Site 2","34","32","94.1%","80.3%","99.3%"],["Site 3","36","35","97.2%","85.5%","99.9%"],["Site 4","37","33","89.2%","74.6%","97.0%"],["Site 5","42","39","92.9%","80.5%","98.5%"],["Site 6","37","36","97.3%","85.8%","99.9%"],["all","221","209","94.6%","90.7%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p13-t0","doc_id":"K253265","page_num":13,"bbox":[78.55,102.69,533.22,250.5],"n_rows":6,"n_cols":6,"columns":["Sensitivity","","","","",""],"rows":[["Sensitivity","","","","",""],["Slice\nThickness\n[mm]","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["0.6-1.5","22","20","90.9%","70.8%","98.9%"],["1.5-2.5","61","56","91.8%","81.9%","97.3%"],["2.5-5","90","87","96.7%","90.6%","99.3%"],["all","173","163","94.2%","89.6%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p13-t1","doc_id":"K253265","page_num":13,"bbox":[78.55,312.67,533.22,460.5],"n_rows":6,"n_cols":6,"columns":["Specificity","","","","",""],"rows":[["Specificity","","","","",""],["Slice\nThickness\n[mm]","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence\nLimit"],["0.6-1.5","17","16","94.1%","71.3%","99.9%"],["1.5-2.5","78","75","96.2%","89.2%","99.2%"],["2.5-5","126","118","93.7%","87.9%","97.2%"],["all","221","209","94.6%","90.7%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p13-t2","doc_id":"K253265","page_num":13,"bbox":[78.55,505.42,533.22,677.29],"n_rows":7,"n_cols":6,"columns":["Sensitivity","","","","",""],"rows":[["Sensitivity","","","","",""],["Protocol","Total N","Truly\nDiagnosed","Estimate","Lower\nConfidence\nLimit*","Upper\nConfidence\nLimit"],["W IV W Oral","38","35","92.1%","78.6%","98.3%"],["W IV WO Oral","82","78","95.1%","88.0%","98.7%"],["WO IV W Oral","11","11","100.0%","71.5%","100.0%"],["WO IV WO Oral","42","39","92.9%","80.5%","98.5%"],["all","173","163","94.2%","89.6%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p14-t0","doc_id":"K253265","page_num":14,"bbox":[70.86,133.63,541.25,305.51],"n_rows":7,"n_cols":6,"columns":["Specificity","","","","",""],"rows":[["Specificity","","","","",""],["Protocol","Total N","Truly Diagnosed","Estimate","Lower\nConfidence\nLimit*","Upper\nConfidence\nLimit"],["W IV W Oral","32","30","93.8%","79.2%","99.2%"],["W IV WO Oral","107","101","94.4%","88.2%","97.9%"],["WO IV W Oral","10","10","100.0%","69.2%","100.0%"],["WO IV WO Oral","72","68","94.4%","86.4%","98.5%"],["all","221","209","94.6%","90.7%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p14-t1","doc_id":"K253265","page_num":14,"bbox":[70.86,393.52,541.25,541.5],"n_rows":7,"n_cols":6,"columns":["Sensitivity","","","","",""],"rows":[["Sensitivity","","","","",""],["Scanner","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["GE","43","41","95.3%","84.2%","99.4%"],["Philips","61","56","91.8%","81.9%","97.3%"],["SIEMENS","40","39","97.5%","86.8%","99.9%"],["TOSHIBA","29","27","93.1%","77.2%","99.2%"],["all","173","163","94.2%","89.6%","97.2%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p14-t2","doc_id":"K253265","page_num":14,"bbox":[83.29,601.61,528.71,717.26],"n_rows":5,"n_cols":6,"columns":["Specificity","","","","",""],"rows":[["Specificity","","","","",""],["Scanner","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["GE","47","46","97.9%","88.7%","99.9%"],["Philips","72","69","95.8%","88.3%","99.1%"],["SIEMENS","61","55","90.2%","79.8%","96.3%"]],"caption_candidate":"Limits (Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p15-t0","doc_id":"K253265","page_num":15,"bbox":[83.33,72.25,528.67,171.71],"n_rows":4,"n_cols":6,"columns":["Specificity","","","","",""],"rows":[["Specificity","","","","",""],["Scanner","Total N","Truly\nDiagnosed","Estimate","Lower Confidence Limit","Upper Confidence Limit"],["TOSHIBA","41","39","95.1%","83.5%","99.4%"],["all","221","209","94.6%","90.7%","97.2%"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p15-t1","doc_id":"K253265","page_num":15,"bbox":[78.1,231.23,533.33,417.73],"n_rows":6,"n_cols":7,"columns":["","Sensitivity","","","","",""],"rows":[["","Sensitivity","","","","",""],["Covariate","Level","Total N","Truly\nDiagnosed","Estimate","Lower Confidence\nLimit","Upper Confidence\nLimit"],["Age","Age (Years) ≤70","125","120","96.0%","90.9%","98.7%"],["","Age (Years)>70","48","43","89.6%","77.3%","96.5%"],["Gender*","Male","93","86","92.5%","85.1%","96.9%"],["","Female","77","74","96.1%","89.0%","99.2%"]],"caption_candidate":"(Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p15-t2","doc_id":"K253265","page_num":15,"bbox":[73.5,480.37,538.5,667.21],"n_rows":6,"n_cols":7,"columns":["","Specificity","","","","",""],"rows":[["","Specificity","","","","",""],["Covariate","Level","Total N","Truly\nDiagnosed","Estimate","Lower Confidence\nLimit","Upper Confidence\nLimit"],["Age","Age (Years) ≤70","170","162","95.3%","90.9%","97.9%"],["","Age (Years)>70","51","47","92.2%","81.1%","97.8%"],["Gender*","Male","89","81","91.0%","83.1%","96.0%"],["","Female","130","127","97.7%","93.4%","99.5%"]],"caption_candidate":"(Efficacy Population)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253265-p16-t0","doc_id":"K253265","page_num":16,"bbox":[93.07,245.14,519.25,673.38],"n_rows":11,"n_cols":6,"columns":["Operating Point","Parameter","N","Estimate","95% Lower CL","95% Upper CL"],"rows":[["Operating Point","Parameter","N","Estimate","95% Lower CL","95% Upper CL"],["AOP1","Sensitivity","173","98.8%","95.9%","99.9%"],["","Specificity","221","91.9%","87.4%","95.1%"],["AOP2","Sensitivity","173","96.0%","91.8%","98.4%"],["","Specificity","221","92.8%","88.5%","95.8%"],["AOP3","Sensitivity","173","91.9%","86.8%","95.5%"],["","Specificity","221","95.0%","91.3%","97.5%"],["AOP4","Sensitivity","173","86.1%","80.1%","90.9%"],["","Specificity","221","95.9%","92.4%","98.1%"],["AOP5","Sensitivity","173","82.1%","75.5%","87.5%"],["","Specificity","221","96.8%","93.6%","98.7%"]],"caption_candidate":"Table 16. Sensitivity and Specificity with Associated Two-sided 95% Confidence Limits","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p7-t0","doc_id":"K253269","page_num":7,"bbox":[54.03,399.47,557.47,694.08],"n_rows":3,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["Image\nReceptor","21cm Amorphous Silicon (a-\nSi) Flat Panel Detector","","","21cm and 31cm CMOS Flat\nPanel Detector","","","Substantially Equivalent.\nThe change of the image\nreceptor is to enhance the\ndevice performance.\nBoth detector technology is\nwidely used in mobile\nfluoroscopic C-arm imaging\nsystem.\nAlso see comparation with\nthe cleared reference device\nOEC Elite (K172550) that\nusing the identical CMOS\ndetectors in Table 2 in the\nfollowing section\nThis change did not raise\nany new safety and\neffectiveness concerns."]],"caption_candidate":"Table 1 Comparison between the Subject Device and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p8-t0","doc_id":"K253269","page_num":8,"bbox":[54.03,76.91,557.49,701.28],"n_rows":5,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["Image\nMatrix Size","21cm: 1520×1520","","","21cm: 1536x1496\n31cm: 1548x1524","","","Substantially Equivalent.\nSlightly changed for 21cm\nFlat Panel Detector (FPD).\nThe image matrix size is\ndetermined by the physical\ndimensions of the detector.\n31cm FPD is larger than the\n21 cm FPD, therefore it is\ndifferent with OEC One\nASD.\nThis change did not raise\nany new safety and\ne ffectiveness concerns."],["Monoblock","Type: Stationary Anode Focal\nSpot (IEC60336):\n-Small Focal: 0.6 x 1.4\n-Large Focal: 1.4\nHousing Heat Capacity:\n900,000 HU\nHousing Cooling Rate: 12,500\nHU/min","","","Type: Stationary Anode Focal\nSpot (IEC60336):\n-Small Focal: 0.6\n-Large Focal: 1.2\nHousing Heat Capacity:\n1,200,000 HU\nHousing Cooling Rate: 20,000\nHU/min","","","Substantial Equivalent.\nThe focal spot size, heat\ncapacity and cooling rate\nhave been changed to\nenhance monoblock\nperformance.\nThe system verification and\nvalidation have been\nexecuted and passed.\nThese changes did not raise\nany new safety and\ne ffectiveness concern."],["X-ray\nGeneration","40 kHz High Frequency\nMax Power 2.5 kW\nPeak Tube Potential: 40-110\nkVp\nFluoroscopy: 0.1-8.0 mA\nHigh Level Fluoro: 0.2-25.0\nmA\nDigital Spot:2-10mA\n(for 100-120V system)","","","20 kHz High Frequency\nMax Power 4.0 kW\nPeak Tube Potential: 40-120\nkVp\nFluoroscopy: 0.1-12.0 mA\nHigh Level Fluoro: 0.2-40.0\nmA\nDigital Spot:2-15mA\n(for 100-120V system)","","","Substantial Equivalent.\nThe maximum power, kVp\nand mA updated to get the\nfull capability of the tube-\ninsert to enhance the system\nperformance.\nThe frequency of the X-ray\ngenerator is adjusted to fit\nthe 4kW max power.\nThese changes are\nperformance enhancement,\nand the X-ray generation"]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p9-t0","doc_id":"K253269","page_num":9,"bbox":[54.02,76.91,557.5,718.56],"n_rows":6,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["","","","","","","","control mechanism is not\nchanged.\nThe system verification and\nvalidation have been\nexecuted and passed.\nThese changes did not raise\nany new safety and\ne ffectiveness concern."],["X-ray\nControl\nModes","Auto Mode\nManual Mode\n(Normal Fluoro, Low Dose\nFluoro, High Level Fluoro)","","","Auto Mode\nManual Mode\n(Normal Fluoro, Low Dose\nFluoro, High Level Fluoro)","","","Identical."],["Imaging\nModes","Continuous – Fluoroscopy\n-Normal Dose\n-High Level Dose\n-Low Dose\nPulsed Fluoroscopy\n-Normal Dose\n-High Level Dose\n-Low Dose\nDigital Spot\n-Normal Dose\nSubtraction\n-Normal Dose\n-Low Dose","","","Continuous – Fluoroscopy\n-Normal Dose\n-High Level Dose\n-Low Dose\nPulsed Fluoroscopy\n-Normal Dose\n-High Level Dose\n-Low Dose\nDigital Spot\n-Normal Dose\nSubtraction\n-Normal Dose\n-Low Dose\nRoadmap\n-Normal Dose\n-Low Dose","","","Substantially Equivalent.\nRoadmap provides a\nmodified subtracted image\non the left area of the\nmonitor showing the\ndifference between the\ncurrent fluoroscopic image\nand a roadmap mask image.\nIt is useful for providing the\nanatomical location of\npathology for proper\nplacement of a catheter,\nballoon, or stent.\nRoadmap function is the\nsame as the cleared device\nOEC One (K182626).\nThis change did not raise\nany new safety and\neffectiveness concerns."],["Imaging\nFeatures","Auto X-Ray technique control\nNoise and motion reduction\n(TNR)\nAuto/Manual Brightness and\nContrast Control\nNegate\nSwap and auto-swap\nSave and auto-save\nLast image hold","","","Auto X-Ray technique control\nNoise and motion reduction\n(TNR)\nAuto/Manual Brightness and\nContrast Control\nNegate\nSwap and auto-swap\nSave and auto-save\nLast image hold","","","Identical."]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p10-t0","doc_id":"K253269","page_num":10,"bbox":[54.03,76.91,557.49,702.84],"n_rows":5,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["","Edge enhancement\nZoom (Live Zoom) & Roam\nImage rotation\nImage flip/ invert\nManual/Auto Smart Metal\nAutoTrak\nPatient Annotation\nMarkers\nMeasurement Functions\nPeak Opacification\nCine Recording/Playback\n· Cine Automatic Image\nPlayback\n· Cine Frame-by-Frame Review\n· Fluorostore\nRe-Registration\nVariable Landmarking\nMask save/Recall\nReference Image Hold\nDigital Pen","","","Edge enhancement\nZoom (Live Zoom) & Roam\nImage rotation\nImage flip/ invert\nManual/Auto Smart Metal\nAutoTrak\nPatient Annotation\nMarkers\nMeasurement Functions\nPeak Opacification\nCine Recording/Playback\n· Cine Automatic Image\nPlayback\n· Cine Frame-by-Frame Review\n· Fluorostore\nRe-Registration\nVariable Landmarking\nMask save/Recall\nReference Image Hold\nDigital Pen","","",""],["Collimator","Iris, Tungsten Dual Leaf\nShutter\nCollimator Iris Preview\nCollimator Shutter Preview\nSquircle shape secondary\ncollimator","","","Iris, Tungsten Dual Leaf\nShutter\nCollimator Iris Preview\nCollimator Shutter Preview\nSquircle shape secondary\ncollimator","","","Identical."],["Anti-scatter\nGrid","For 21cm detector:\n- Line Rate: 74L/cm\n- Ratio: 14:1\n- Focal Distance: 100 cm","","","For 21cm detector:\n- Line Rate: 74L/cm\n- Ratio: 14:1\n- Focal Distance: 100 cm\nFor 31cm detector:\n- Line Rate: 60L/cm\n- Ratio: 10:1\n- Focal Distance: 100 cm","","","Substantially Equivalent.\nIdentical for 21cm grid.\nAdding 31cm grid due to the\nintroduction of 31cm flat\npanel detector.\nThis change did not raise\nany new safety and\neffectiveness concerns."]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p11-t0","doc_id":"K253269","page_num":11,"bbox":[54.02,76.91,557.5,691.08],"n_rows":7,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["Image\nShape","Squircle","","","Squircle","","","Identical."],["Monitor\nDisplay","Colored 27” monitor\nResolution: 3840 x 2160\nBrightness: 600cd/m2\nTouch screen\n10 bit image display on\nmonitor","","","Colored 27” monitor\nResolution: 3840 x 2160\nBrightness: 600cd/m2\nTouch screen\n10 bit image display on\nmonitor","","","Identical."],["Display\nArticulation","180 degree swivel\n5 degrees tilt up\n25 degrees tilt down\nMonitor viewable from all 4\nsides\nHorizontal and Vertical\nviewing angle 178 degrees\n20cm up vertical travel\n20cm down vertical travel\nExtension arm rotation 210\ndegrees\nSpring arm rotation 180\ndegrees\nPosition monitor above C-arm\nby folding articulation arm\nwithin system footprint","","","180 degree swivel\n5 degrees tilt up\n25 degrees tilt down\nMonitor viewable from all 4\nsides\nHorizontal and Vertical\nviewing angle 178 degrees\n20cm up vertical travel\n20cm down vertical travel\nExtension arm rotation 210\ndegrees\nSpring arm rotation 180\ndegrees\nPosition monitor above C-arm\nby folding articulation arm\nwithin system footprint","","","Identical."],["Tech View\nTablet","Size: 10.1 inch\nResolution: 1280 × 800","","","Size: 12.1 inch\nResolution: 1280 × 800","","","Substantially Equivalent.\nThis change was driven by\nIT technology advancement\nby using a more state-of-the-\nart technology which\nachieves the same or better\nfunctionality.\nThis change did not raise\nany new safety and\neffectiveness concerns."],["Image\nStorage","150,000 Images","","","150,000 Images","","","Identical."]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p12-t0","doc_id":"K253269","page_num":12,"bbox":[54.02,76.91,557.5,710.4],"n_rows":8,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["C-Arm\nPhysical\nDimensions","Free Space in Arc: 30.7” (78\ncm)\nDepth of Arc: 26.0” (66 cm)\nSource Image Distance: 39.4”\n(100 cm)\nLateral Rotation: 410° (+205°\n/ -205°)\nWig/Wag: 25° (+12.5°/-12.5°)\nOrbital Rotation: 150° (95°\nunderscan /55° overscan)\nHorizontal Movement: 7.9”\n(20cm)\nVertical Travel: 17.5” (44 cm)","","","Free Space in Arc: 30.7” (78\ncm)\nDepth of Arc: 27.2” (69 cm)\nSource Image Distance: 39.4”\n(100 cm)\nLateral Rotation: 410° (+205°\n/ -205°)\nWig/Wag: 25° (+12.5°/-12.5°)\nOrbital Rotation: 180° (95°\nunderscan /90° overscan)\nHorizontal Movement: 7.9”\n（20cm）\nV ertical Travel: 17.5” (44 cm)","","","Substantial Equivalent.\nThe depth of arc and the\norbital rotation angle are\nchanged to a larger range to\nmake it easier for the user to\nuse the system.\nThese changes did not raise\nany new safety and\neffectiveness concern."],["Printing","Wireless Printing Module\nPrinters","","","Wireless Printing Module\nPrinters","","","Identical."],["Video\nDistributor","DP, BNC","","","DP, BNC","","","Identical."],["Laser Aimer","Green Laser\nFlat panel detector side/Tube\nside Laser aimer:\n- CLASS 2 laser product\n- Wavelength: 510nm-\n530nm\nOptical output power: 1mW","","","Green Laser\nFlat panel detector side/Tube\nside Laser aimer:\n- CLASS 2 laser product\n- Wavelength: 510nm-\n530nm\nOptical output power: 1mW","","","Identical."],["Image\nProcessing","Noise and motion artifact\nreduction, Autotrak, ABS\n(based on CPU)\nSmart window, smart metal,\nADRO (based on GPU)","","","Noise and motion artifact\nreduction, Autotrak, ABS\n(based on CPU)\nSmart window, smart metal,\nA DRO (based on GPU)","","","Identical"],["OEC One\nTouch\nTableside","N/A","","","Tech View Tablet\nIPX3","","","Substantially Equivalent.\nThe added optional OEC\nOne Touch Tableside"]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p13-t0","doc_id":"K253269","page_num":13,"bbox":[54.02,76.91,557.5,714.48],"n_rows":6,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["","","","","","","","provided identical\nfunction/feature that had\nalready existed on the tablet\non the system except for the\nability to adjust the\ncollimator during live X-\nrays.\nThis change did not raise\nany new safety and\neffectiveness concerns."],["Live Cast\n(wireless\nvideo)","N/A","","","Wireless video\n- Transmitter\n- Receiver\n-5.1-5.9 GHz","","","Substantially Equivalent.\nThis feature is to introduce\nan optional wireless video\nmodule which enables the\nuser to cast the system\ndisplays wirelessly to the\nselected external displays\nsimultaneously. It functions\nin the same way as the\ncleared device OEC Elite\n(K172550).\nThis change did not raise\nany new safety and\ne ffectiveness concerns."],["OEC\nDisplay Cart","27\" monitor\nResolution: 1920X1080\nNon-touch Screen","","","27\" monitor\nResolution: 1920X1080\nTouch Screen","","","Substantially Equivalent.\nThe added touch screen\nfeature provided identical\nfunction/feature that had\nalready existed on the\nsystem monitor. It cannot\nalter or control X-ray\nradiation of the system.\nThis change did not raise\nany new safety and\neffectiveness concerns."],["External\nVideo Input\n(Picture in\nPicture)","N/A","","","Yes","","","Substantially Equivalent.\nThis feature is to display the\nexternal video input on the\nright side of the C-arm\nsystem monitor while the"]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p14-t0","doc_id":"K253269","page_num":14,"bbox":[54.03,76.91,557.49,701.28],"n_rows":5,"n_cols":8,"columns":["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],"rows":[["","","Predicate Device","","","Subjected Device","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","OEC One CFD","",""],["","","","","","","","left side of monitor is the\nlive image from the X-ray\nmobile C-arm system. This\nfeature makes user more\nconvenient to view the\nimages from other devices\nsuch as endoscope etc.\nIt functions in the same way\nas the cleared device OEC\nElite (K172550).\nThis change did not raise\nany new safety and\neffectiveness concerns."],["Image\nStitching","N/A","","","Yes","","","Substantially Equivalent.\nImage Stitching is to create a\ncomposite view from\nmultiple image acquisitions\nto aid in surgical procedures\nof the spine, long bone, or\npelvis.\nThe verification and\nvalidation test to meet\ndesign inputs and user needs\nfor this feature have been\ntested and the result was\npassed.\nThis change did not raise\nany new safety and\neffectiveness concerns."],["Trajectory\nPointer","N/A","","","Yes","","","Substantially Equivalent.\nTrajectory Pointer is a\nfeature utilizing deep\nlearning technology to\nsegment the Kirschner-wire\nthen utilize a traditional\nalgorithm to present a visual\nguideline to aid in\npositioning Kirschner-wires\nor similar straight, solid\nmetallic devices."]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253269-p15-t0","doc_id":"K253269","page_num":15,"bbox":[54.03,76.91,557.47,232.32],"n_rows":3,"n_cols":7,"columns":["","","Predicate Device","","Subjected Device\nOEC One CFD","","Discussion of Differences"],"rows":[["","","Predicate Device","","Subjected Device\nOEC One CFD","","Discussion of Differences"],["","","OEC One ASD (K240828)","","","",""],["","","","","","","The verification and\nvalidation test to meet\ndesign inputs and user needs\nfor this feature have been\ntested and the result was\npassed.\nThis change did not raise\nany new safety and\neffectiveness concerns."]],"caption_candidate":"510(k) Premarket Notification Submission – OEC One CFD","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253270-p18-t0","doc_id":"K253270","page_num":18,"bbox":[58.81,143.25,553.31,662.55],"n_rows":27,"n_cols":8,"columns":["","Modification","","","Description","","Per-Structure Testing Method",""],"rows":[["","Modification","","","Description","","Per-Structure Testing Method",""],["#1","","","","The modification adds new\nmodels to K253270, providing a\nmore comprehensive set of\nanatomical contours to support\nclinicians in creating contours","Only structures that pass two or more of the following three\ntests could be included in the final models:\n1. MDA Metric Testing\n2. Dice Metric Testing\n3. User Beta Testing","",""],["","","New CT models","","","","",""],["","","or MR models","","","","",""],["","","","","","","",""],["#2","","New CBCT","","The modification adds new CBCT\nmodels to K253270, providing\nanatomical contours to support\nclinicians in creating contour on\nIRIS imaging CBCT data","Only structures that pass two or more of the following three\ntests could be included in the final models:\n1. MDA Metric Testing\n2. Dice Metric Testing\n3. User Beta Testing","",""],["","","models for CBCT","","","","",""],["","","IRIS imaging data","","","","",""],["","","(cleared in","","","","",""],["","","K252188)","","","","",""],["","","acquired from","","","","",""],["","","Elekta’s Evo,","","","","",""],["","","Versa HD, and","","","","",""],["","","Harmony Pro","","","","",""],["","","systems","","","","",""],["#3","","","","This modification includes\nroutine improvements to the\ncurrent device by utilizing\nhigher-quality or more diverse\nground truth training data to\nimprove overall segmentation\naccuracy or improve\nperformance on subgroups with\nchallenging anatomy","Only structures that pass two or more of the following three\ntests could be included in the final models:\n1. MDA Metric Testing\nAND\nMDA Non-inferiority Testing with Contour ProtégéAI+\n2. Dice Metric Testing\nAND\nDice Non-inferiority Testing with Contour ProtégéAI+\n3. User Beta Testing","",""],["","","Re-training","","","","",""],["","","models due to","","","","",""],["","","improvements in","","","","",""],["","","training data","","","","",""],["","","","","","","",""],["#4","","","","This modification includes\nroutine improvements to the\ncurrent device by re-training on\npreviously cleared\narchitectures to improve overall\nsegmentation accuracy or\nimprove performance on\nsubgroups with challenging\nanatomy and/or decrease\ncomputational time","Only structures that pass two or more of the following three\ntests could be included in the final models:\n1. MDA Metric Testing\nAND\nMDA Non-inferiority Testing with Contour ProtégéAI+\n2. Dice Metric Testing\nAND\nDice Non-inferiority Testing with Contour ProtégéAI+\n3. User Beta Testing","",""],["","","Re-training","","","","",""],["","","models on","","","","",""],["","","cleared","","","","",""],["","","architecture","","","","",""],["","","","","","","",""]],"caption_candidate":"Table 4 – Traceability of PCCP modifications and per-structure testing protocol","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253270-p19-t0","doc_id":"K253270","page_num":19,"bbox":[58.8,120.57,553.29,298.7],"n_rows":13,"n_cols":8,"columns":["","Modification","","","Description","","Per-Structure Testing Method",""],"rows":[["","Modification","","","Description","","Per-Structure Testing Method",""],["#5","","","","This modification entails\nreleasing previously released\nCT models, that are retested\nand renamed to provide\nanatomical contours to support\nclinicians in creating contours on\nIRIS imaging CBCT data","Only structures that pass two or more of the following three\ntests could be included in the final models:\n1. MDA Metric Testing\nAND\nMDA Non-inferiority Testing with Contour ProtégéAI+\n2. Dice Metric Testing\nAND\nDice Non-inferiority Testing with Contour ProtégéAI+\n3. User Beta Testing","",""],["","","Re-applying CT","","","","",""],["","","models for CBCT","","","","",""],["","","IRIS imaging data","","","","",""],["","","(cleared in","","","","",""],["","","K252188)","","","","",""],["","","acquired from","","","","",""],["","","Elekta’s Evo,","","","","",""],["","","Versa HD, and","","","","",""],["","","Harmony Pro","","","","",""],["","","systems","","","","",""],["","","","","","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253270-p19-t1","doc_id":"K253270","page_num":19,"bbox":[202.59,508.8,436.52,612.26],"n_rows":4,"n_cols":4,"columns":["Contour Size\nClassification","","","Dice Acceptance\nCriteria Threshold"],"rows":[["Contour Size\nClassification","","","Dice Acceptance\nCriteria Threshold"],["","Small","","0.5"],["","Medium","","0.65"],["","Large","","0.8"]],"caption_candidate":"Table 5 – Contour size categorization and associate Dice acceptance criteria threshold","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253366-p5-t0","doc_id":"K253366","page_num":5,"bbox":[70.56,158.88,577.32,694.92],"n_rows":11,"n_cols":2,"columns":["Date:","January 7, 2026"],"rows":[["Date:","January 7, 2026"],["Submitter:","GE Medical Systems Ultrasound and Primary care Diagnostics, LLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Manufacturer:","GE Ultrasound Korea, Ltd.\n9, Sunhwan-ro 214 beon-gil, Jungwon-gu,\nSeongnam-si, Gyeonggi-do, 13204 Republic of Korea"],["Primary Contact Person:","Lee Bush\nRegulatory Affairs Director\nGE HealthCare\nT:(262)309-9429"],["Alternate Contact Person:","Qingmeng Chen\nRegulatory Affairs Leader\nGE HealthCare\nT: +86-18180590723"],["Device Trade Name:","LOGIQ Fortis"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX, QIH (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550, 90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-IYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX;\nMedical Image Management and Processing System, 21 CFR 892.2050,\n90-QIH"],["Primary Predicate Device:","K231989 LOGIQ E10s, LOGIQ Fortis Diagnostic Ultrasound System"],["Reference Device(s):","K232381 LOGIQ Totus Diagnostic Ultrasound System\nK231301 Vscan Air\nK201768 Voluson E10\nK220882 Vivid E80, Vivid E90, Vivid E95\nK183575 Siemens Acuson S3000/S2000"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253366-p9-t0","doc_id":"K253366","page_num":9,"bbox":[72.48,282.24,539.37,712.32],"n_rows":4,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria\nor other information supporting the\nappropriateness of the characterized\nperformance","• The overall model detection accuracy (sensitivity and\nspecificity) and DICE score for the Aorta, Kidney,\nLiver/Spleen/inferior vena cava (IVC), Gallbladder\n(GB)/Urinary Bladder, Pancreas, and Air view is expected to\nbe as follows:\n Detection accuracy ≥ 80% (0.80)\n Sensitivity (True Positive Rate): ≥ 80% (0.80)\n Specificity (True Negative Rate): ≥ 80% (0.80)\n DICE Similarity Coefficient (Segmentation Accuracy): ≥\n0.80\n• The number of individual subjects: 49\n• The number of annotation images: 1186\n• The model achieved accuracy of 94.8%, with sensitivity of\n0.91, specificity of 0.98, and a DICE score of 0.82, all of which\nmeet the predefined acceptance criteria."],["Information about clinical subgroups\nand confounders present in the\ndataset","• Gender: Male 24.2% (8), Female 75.8% (25)\n• Age: 60 ±15.7 (average and standard deviation) (24 Min, 83\nMax)\n• BMI: 27±5.6 (average and standard deviation) (16 Min, 38\nMax)\n• Ethnicity: not hispanic 96.4% (27), hispanic 3.6% (1)\n• Race : Asian 12.9% (4), White 77.4% (24), Black 9.7% (3)\n• Country: USA (100%)"],["Information about equipment and\nprotocols used to collect images","Mix of data from across three different probe models and three\ndifferent Console variants. The data collection protocol was\nstandardized."],["Information about how the reference\nstandard was derived from the testing\ndataset (i.e. the “truthing” process)","• Before the process of data annotation, all information\ndisplayed on the device is removed and performed on\ninformation extracted purely from Ultrasound B-mode\nimages."]],"caption_candidate":"Auto Abdominal Color Assistant 2.0:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253366-p10-t0","doc_id":"K253366","page_num":10,"bbox":[72.48,276.36,539.37,705.36],"n_rows":2,"n_cols":2,"columns":["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","Long View Aorta:\n• The average keystrokes to obtain the Anteroposterior\n(AP) measurement (diameter) of the aorta in the long\nview is 4.132 +/- 0.291 without AI and 1.236 +/-0.340\nwith AI.\nShort View Aorta:\n• The average keystrokes to obtain the AP and Trans\nmeasurement (diameter) of the aorta in the short view is\n7.05 +/-0.158 without AI and 2.307 +/- 1.0678 with AI.\nLong View AP Measurement Accuracy:\n• Average accuracy is 87.2% with 95% CI of +/- 1.98% and\naverage absolute error of 0.253 cm and 95% CI of 0.049\ncm.\n• Limits of Agreement in centimeters are (-0.15, 0.60) with\n• 95% CI of (-0.26, 0.71).\nShort View AP Measurement Accuracy:\n• Average accuracy is 92.9% with a 95% CI of +/- 2.02%\nand an average absolute error of 0.128 cm and 95% CI of\n0.037 cm.\n• Limits of Agreement in centimeters are (-0.21, 0.36) with\n95% CI of (-0.29, 0.45).\nShort View Trans Measurement Accuracy:\n• Average accuracy is 86.9% with 95% CI of +/- 6.25% and\naverage absolute error of 0.235 cm and 95% CI of 0.110\ncm.\n• Limits of agreement in centimeters are (-0.86, 0.69) with\n95% CI (-1.06, 0.92)."],"rows":[["Summary test statistics or other test\nresults including acceptance criteria or\nother information supporting the\nappropriateness of the characterized\nperformance","Long View Aorta:\n• The average keystrokes to obtain the Anteroposterior\n(AP) measurement (diameter) of the aorta in the long\nview is 4.132 +/- 0.291 without AI and 1.236 +/-0.340\nwith AI.\nShort View Aorta:\n• The average keystrokes to obtain the AP and Trans\nmeasurement (diameter) of the aorta in the short view is\n7.05 +/-0.158 without AI and 2.307 +/- 1.0678 with AI.\nLong View AP Measurement Accuracy:\n• Average accuracy is 87.2% with 95% CI of +/- 1.98% and\naverage absolute error of 0.253 cm and 95% CI of 0.049\ncm.\n• Limits of Agreement in centimeters are (-0.15, 0.60) with\n• 95% CI of (-0.26, 0.71).\nShort View AP Measurement Accuracy:\n• Average accuracy is 92.9% with a 95% CI of +/- 2.02%\nand an average absolute error of 0.128 cm and 95% CI of\n0.037 cm.\n• Limits of Agreement in centimeters are (-0.21, 0.36) with\n95% CI of (-0.29, 0.45).\nShort View Trans Measurement Accuracy:\n• Average accuracy is 86.9% with 95% CI of +/- 6.25% and\naverage absolute error of 0.235 cm and 95% CI of 0.110\ncm.\n• Limits of agreement in centimeters are (-0.86, 0.69) with\n95% CI (-1.06, 0.92)."],["Information about clinical subgroups\nand confounders present in the\ndataset","Long View Aorta:\n• Gender: 11 Male, 25 Female\n• Country: 16 Japan, 20 USA\n• Age: 60.50 ±14.24 (average and standard deviation) (23\nMin – 81 Max)"]],"caption_candidate":"Auto Aorta Measure Assistant:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253366-p11-t0","doc_id":"K253366","page_num":11,"bbox":[72.48,117.72,539.42,537.12],"n_rows":4,"n_cols":2,"columns":["","• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],"rows":[["","• BMI: 25.11 ±5.69 (average and standard deviation)\n(16.65 – 37.60)\nShort View Aorta:\n• Gender: 11 Male, 24 Female\n• Country: 15 Japan, 20 USA\n• Age: 61.11 ±14.46 (average and standard deviation) (23\nMin – 81 Max)\n• BMI: 25.24 ±5.97 (average and standard deviation)\n(16.65 – 37.60)"],["Information about equipment and\nprotocols used to collect images","Validation images were collected on LOGIQ Fortis with the C1-6\nprobe with a standardized protocol."],["Information about how the reference\nstandard was derived from the testing\ndataset (i.e. the “truthing” process)","• Before the process of data annotation, all information\ndisplayed on the device is removed and performed on\ninformation extracted purely from Ultrasound B-mode\nimages.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view – Number of keystrokes measured.\n• Readers to ground truth the AP measurement of the\naorta long view and the AP and Trans measurement of\nthe aorta short view using AI - Number of keystrokes\nmeasured.\n• Number of Keystrokes with and without AI is compared\nfor each reader.\n• Arbitrator to select most accurate measurement among\nall readers.\n• Arbitrator selected measurement is compared to AI\nbaseline measurement with and without on\nsegmentation editing for accuracy."],["Description of how independence of\ntest data from training data was\nensured","The exams used for regulatory validation purpose are separated\nfrom the ones used during model development process by exam\nsite origin ensuring there is no overlap between the two."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253366-p12-t0","doc_id":"K253366","page_num":12,"bbox":[72.65,117.72,539.12,591.24],"n_rows":28,"n_cols":2,"columns":["","95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],"rows":[["","95% CI of (-6.17, 5.79).\nPorta Hepatis measurement accuracy with segmentation scroll\nedit:\n• Average accuracy is 80.56% with a 95% CI of +/- 8.83% and\nan average absolute error 0.91 mm and 95% CI of 0.45\nmm.\n• Limits of Agreement in millimeters are (-1.96, 3.25) with\n95% CI of (-2.85,4.14)."],["","• Gender: Male 44% (11), Female 56% (14)"],["","• Age: 62 ±16.03 (average and standard deviation) (23 Min -"],["","83 Max)"],["Information about clinical subgroups and",""],["","• BMI: 23.48 ± 4.94 (average and standard deviation) (16.65"],["confounders present in the dataset",""],["","min – 36.73 max)"],["",""],["","• Race: Asian 64% (16), White 36% (9)"],["","• Country: USA (40%), Japan (60%)"],["Information about equipment and\nprotocols used to collect images","Validation images were collected on LOGIQ Fortis with the C1-6\nprobe with a standardized protocol."],["","• Before the process of data annotation, all information"],["","displayed on the device is removed and performed on"],["","information extracted purely from Ultrasound B-mode"],["","images."],["","• Readers to ground truth the diameter of the CBD in the"],["","Porta Hepatis – Number of keystrokes measured."],["Information about how the reference","• Readers to ground truth the diameter of the CBD in the"],["standard was derived from the dataset","Porta Hepatis using AI - Number of keystrokes measured."],["(i.e. the “truthing” process)","• Number of Keystrokes with and without AI is compared for"],["","each reader."],["","• Arbitrator to select most accurate measurement among all"],["","readers."],["","• Arbitrator selected measurement is compared to AI"],["","baseline measurement with and without on segmentation"],["","editing for accuracy."],["Description of how independence of test\ndata from training data was ensured","The exams used for regulatory validation purpose are separated\nfrom the ones used during model development process by exam\nsite origin ensuring there is no overlap between the two."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253370-p4-t0","doc_id":"K253370","page_num":4,"bbox":[19.27,19.44,593.04,378.24],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK253370 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK253370 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K253370",""],["Please provide the device trade name(s).","",""],["LOGIQ Totus","",""],["Please provide your Indications for Use below.","","?"],["LOGIQ Totus is intended for use by a qualified physician for ultrasound evaluation of Fetal/Obstetrics;\nAbdominal(including Renal, Gynecology/Pelvic), Pediatric; Small organ(Breast, Testes, Thyroid); Neonatal\nCephalic; Adult Cephalic; Cardiac(Adult and Pediatric), Peripheral Vascular, Musculo-skeletal Conventional\nand Superficial; Urology(including Prostate); Transrectal; Transvaginal; Transesophageal and\nlntraoperative(Abdominal and Vascular).\nModes of operation includes: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power\nDoppler, Harmonic Imaging, Coded Pulse, 30/40 Imaging mode, Elastography, Shear Wave Elastography,\nAttenuation Imaging and Combined modes: B/M, B/Color, B/PWD, B/Color/PWD, B/Power/PWD.\nThe LOGIQ Totus is intended to be used in a hospital or medical clinic.","",""],["Please select the types of uses (select one or both, as [gJ Prescription Use (Part 21 CFR 801 Subpart D)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253370-p5-t0","doc_id":"K253370","page_num":5,"bbox":[64.92,126.72,519.6,705.6],"n_rows":11,"n_cols":2,"columns":["Date:","January 8, 2026"],"rows":[["Date:","January 8, 2026"],["Submitter:","GE Medical Systems Ultrasound and Primary care Diagnostics,\nLLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Manufacturer:","GE Ultrasound Korea, Ltd.\n9, Sunhwan-ro 214 beon-gil, Jungwon-gu,\nSeongnam-si, Gyeonggi-do, 13204 Republic of Korea"],["Primary Contact Person:","Lee Bush\nRegulatory Affairs Director\nGE HealthCare\nT:(262)309-9429"],["Alternate Contact\nPerson:","Chae-Rin, Song\nRegulatory Affairs Leader\nGE Ultrasound Korea, Ltd.\nT: +82-31-740-6310"],["Device Trade Name:","LOGIQ Totus"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX, QIH (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550,\n90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-\nIYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX;\nMedical Image Management and Processing System, 21 CFR\n892.2050, 90-QIH"],["Primary Predicate\nDevice:","K232381 LOGIQ Totus Diagnostic Ultrasound System"],["Reference Device(s):","K231989 LOGIQ E10s Diagnostic Ultrasound System\nK231301 Vscan Air\nK201768 Voluson E10\nK220882 Vivid E80, Vivid E90, Vivid E95\nK183575 Siemens Acuson S3000/S2000"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253413-p5-t0","doc_id":"K253413","page_num":5,"bbox":[36.06,349.38,438.57,549.63],"n_rows":14,"n_cols":3,"columns":["","Subject Device","Predicate Device"],"rows":[["","Subject Device","Predicate Device"],["510(k) number","K253413","K213960"],["Legal Manufacturer","Perspectum Ltd.","Perspectum Ltd."],["Device Trade Name","LiverMultiScan (v6.0)","LiverMultiScan (v5.0)"],["","Software as a Medical\nDevice","Software as a Medical\nDevice"],["Common Name","",""],["","",""],["Panel","Radiology","Radiology"],["Regulation","892.1000","892.1000"],["Risk Class","Class II","Class II"],["Product Class code","LNH","LNH"],["","Magnetic Resonance\nDiagnostic Device","Magnetic Resonance\nDiagnostic Device"],["Regulation Name","",""],["","",""]],"caption_candidate":"2 Subject and Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253413-p6-t0","doc_id":"K253413","page_num":6,"bbox":[36.36,435.48,535.32,772.44],"n_rows":7,"n_cols":4,"columns":["Attributes","Subject Device","Predicate Device","Comments"],"rows":[["Attributes","Subject Device","Predicate Device","Comments"],["Device trade name","LiverMultiScan v6.0","LiverMultiScan v5.0","N/A"],["Manufacturer","Perspectum Ltd","Perspectum Ltd","N/A"],["510(k) number (if\nassigned)","K253413","K213960","N/A"],["Regulation","892.1000","892.1000","No change"],["Product Code","LNH","LNH","No change"],["Indications for use","The device is indicated for\nuse as a magnetic\nresonance diagnostic\ndevice software\napplication for non-\ninvasive assessment of\nliver health and the\ngeneration, display and\nreview of magnetic\nresonance medical image\ndata.\nThe device produces\nquantified metrics and\ncomposite images from\nmagnetic resonance\nmedical image data\nwhich, when interpreted","LiverMultiScan v5 (LMSv5)\nis indicated for use as a\nmagnetic resonance\ndiagnostic device software\napplication for non-invasive\nliver evaluation that\nenables the generation,\ndisplay and review of 2D\nmagnetic resonance\nmedical image data and\npixel maps for MR\nrelaxation times.\nLMSv5 is designed to\nutilize DICOM 3.0\ncompliant magnetic\nresonance image datasets,\nacquired from compatible","Rephrased the\nindications for use for\nbetter readability without\nany change to its intent."]],"caption_candidate":"demonstrate substantial equivalence. Differences between the devices are commented.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253413-p7-t0","doc_id":"K253413","page_num":7,"bbox":[36.36,53.64,535.32,760.44],"n_rows":3,"n_cols":4,"columns":["","by a trained healthcare\nprofessional, yield\ninformation on liver tissue\ncharacteristics that\nmay assist in clinical\nd ecisions.","MR Systems, to display the\ninternal structure of the\nabdomen including the\nliver. Other physical\nparameters derived from\nthe images may also be\nproduced.\nLMSv5 provides several\ntools, such as automated\nliver segmentation and\nregion of interest (ROI)\nplacements, to be used for\nthe assessment of selected\nregions of an image.\nQuantitative assessment of\nselected regions includes\nthe determination of\ntriglyceride fat fraction in\nthe liver (PDFF), T2*, LIC\n(Liver Iron Concentration)\nand iron corrected T1 (cT1)\nmeasurements.\nThese images and the\nphysical parameters\nderived from the images,\nwhen interpreted by a\ntrained clinician, yield\ninformation that may assist\ni n diagnosis.",""],"rows":[["","by a trained healthcare\nprofessional, yield\ninformation on liver tissue\ncharacteristics that\nmay assist in clinical\nd ecisions.","MR Systems, to display the\ninternal structure of the\nabdomen including the\nliver. Other physical\nparameters derived from\nthe images may also be\nproduced.\nLMSv5 provides several\ntools, such as automated\nliver segmentation and\nregion of interest (ROI)\nplacements, to be used for\nthe assessment of selected\nregions of an image.\nQuantitative assessment of\nselected regions includes\nthe determination of\ntriglyceride fat fraction in\nthe liver (PDFF), T2*, LIC\n(Liver Iron Concentration)\nand iron corrected T1 (cT1)\nmeasurements.\nThese images and the\nphysical parameters\nderived from the images,\nwhen interpreted by a\ntrained clinician, yield\ninformation that may assist\ni n diagnosis.",""],["Intended users","• Perspectum\ntrained analysts use\nthe device\nto analyse MRI data\nand produce output.\n• Trained healthcare\nprofessionals interpret\nthe device\noutput for their clinical\ndecision pathways.","• Perspectum\ntrained analysts use the\ndevice to analyse MRI\ndata and produce\noutput.\n• Trained healthcare\nprofessionals interpret\nthe device\noutput for their clinical\ndecision pathways.","No change"],["Anatomy and\nmeasurements","Liver\nIron Corrected T1 (cT1)\nProton Density Fat\nFraction (PDFF)\nLiver Iron Concentration\n(LIC)","Liver\nIron Corrected T1 (cT1)\nProton Density Fat Fraction\n(PDFF)\nLiver Iron Concentration\n(LIC)","No change to the list of\nmeasurement output.\nHowever, the equation\nused to calculate the LIC\nvalue has changed in the\nsubject device to align\nwith the reference\narticle. And, the cT1\ncalculation in the subject\ndevice is updated to\naccount for T1 signal\nvariations due to elevated\nfat in addition to what"]],"caption_candidate":"VitruvianScan 510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253413-p8-t0","doc_id":"K253413","page_num":8,"bbox":[36.34,53.64,535.32,293.4],"n_rows":8,"n_cols":4,"columns":["","","","already existed in the\npredicate device."],"rows":[["","","","already existed in the\npredicate device."],["Target population","General population","General population","No change"],["Contraindications","None, Software only","None, Software only","No change"],["Imaging modality","Magnetic resonance\nimaging systems","Magnetic resonance\nimaging systems","No change"],["Data format","DICOM 3.0 compliant MR\nimage datasets from\ncompatible MR scanners","DICOM 3.0 compliant MR\nimage datasets from\ncompatible MR scanners","No change"],["MRI Scanners","GE, Siemens and Philips","GE, Siemens and Philips","No change"],["MR field strength","1.5T and 3T","1.5T and 3T","No change"],["MR Acquisition\nMethods","NOLLI (Non-MOLLI)\nMOLLI\nMOST\nIDEAL","MOLLI\nMOST\nIDEAL","Subject device is\nmodified to read MR scan\ndata acquired through\nNOLLI (non-MOLLI) in\nadditional to MOLLI\nmethod."]],"caption_candidate":"VitruvianScan 510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253413-p8-t1","doc_id":"K253413","page_num":8,"bbox":[36.34,533.46,162.88,641.1],"n_rows":7,"n_cols":3,"columns":["","Scanners Assessed",""],"rows":[["","Scanners Assessed",""],["","Siemens 1.5T",""],["","Siemens 3T",""],["","GE 1.5T",""],["","GE 3T",""],["","Philips 1.5T",""],["","Philips 3T",""]],"caption_candidate":"is at least as safe and effective as the predicate device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p6-t0","doc_id":"K253489","page_num":6,"bbox":[71.73,316.88,539.56,707.48],"n_rows":14,"n_cols":4,"columns":["","","Primary Predicate","Secondary Predicate"],"rows":[["","","Primary Predicate","Secondary Predicate"],["","Subject","",""],["","","Swoop Portable MR","Swoop Portable MR"],["Specification","","",""],["","Swoop Portable MR Imaging","Imaging System","Imaging System"],["","","",""],["","System","Model 2","Model 1"],["","","(K250236)","(K251276)"],["Intended Use/\nIndications for Use:","The Swoop Portable MR Imaging\nSystem is a portable, ultra-low\nfield magnetic resonance imaging\ndevice for producing images that\ndisplay the internal structure of\nthe head where full diagnostic\nexamination is not clinically\npractical. When interpreted by a\ntrained physician, these images\nprovide information that can be\nuseful in determining a diagnosis.","Same","Same"],["Patient Population:","Adult and pediatric patients (≥ 0\nyears)","Same","Same"],["Anatomical Sites:","Head","Same","Same"],["Environment of Use:","At the point of care in professional\nhealth care facilities such as\nemergency rooms,\nintensive/critical care units,\nhospitals, outpatient, or\nrehabilitation centers.","Same","Same"],["Energy Used and/or\ndelivered:","Magnetic Resonance","Same","Same"],["Magnet:","","",""]],"caption_candidate":"The table below compares the subject device to the predicate.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p7-t0","doc_id":"K253489","page_num":7,"bbox":[71.73,72.56,539.57,715.1],"n_rows":21,"n_cols":4,"columns":["","","Primary Predicate","Secondary Predicate"],"rows":[["","","Primary Predicate","Secondary Predicate"],["","Subject","",""],["","","Swoop Portable MR","Swoop Portable MR"],["Specification","","",""],["","Swoop Portable MR Imaging","Imaging System","Imaging System"],["","","",""],["","System","Model 2","Model 1"],["","","(K250236)","(K251276)"],["Field Strength","Model 1 Swoop System\n63.3 ± 2.0 mT\nModel 2 Swoop System\n64.9 mT (nominal)","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["Type","Permanent magnet","Same","Same"],["Patient accessible bore\nsize","Model 1 Swoop System\n24.0 in. width, 12.4 in. height\nModel 2 Swoop System\n36.0 in. width, 13.4 in. height","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["Magnet weight","Model 1 Swoop System\n705 lbs\nModel 2 Swoop System\n712 lbs","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["Gradient System:","","",""],["Maximum gradient\namplitude","Model 1 Swoop System\nX: 24 mT/m, Y: 23 mT/m, Z: 39\nmT/m\nModel 2 Swoop System\nX: 33.9 mT/m, Y: 33.2 mT/m, Z:\n66.2 mT/m","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["Rise Time","Model 1 Swoop System\nX: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms\nModel 2 Swoop System\nX: 1.8 ms, Y: 1.8 ms, Z: 5.1 ms","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["Slew Rate","Model 1 Swoop System\nX: 24 T/m/s, Y: 22 T/m/s, Z: 21\nT/m/s\nModel 2 Swoop System\nX: 18.8 T/m/s, Y: 18.4 T/m/s, Z:\n13.0 T/m/s","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["RF Coils:","","",""],["Coil Type","Transmit/receive","Same","Same"],["Coil Design","Linear","Same","Same"],["Other:","","",""],["Patient Weight Capacity","1.6kg-200 kg","Same","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p8-t0","doc_id":"K253489","page_num":8,"bbox":[71.71,72.56,539.57,706.6],"n_rows":18,"n_cols":4,"columns":["","","Primary Predicate","Secondary Predicate"],"rows":[["","","Primary Predicate","Secondary Predicate"],["","Subject","",""],["","","Swoop Portable MR","Swoop Portable MR"],["Specification","","",""],["","Swoop Portable MR Imaging","Imaging System","Imaging System"],["","","",""],["","System","Model 2","Model 1"],["","","(K250236)","(K251276)"],["Operation Temperature","15-30 C","Same","Same"],["Warm Up Time","<3 minutes","Same","Same"],["Temperature Control","No","Same","Same"],["Humidity Control","No","Same","Same"],["Sequences:","","",""],["T1W sequences","• T1 (Standard), T1\n(Gray/White)\n• Advanced Gridding\nreconstruction","Same","Same"],["T2W sequences","• T2, T2 (Fast)\n• Advanced Gridding\nreconstruction","Same","Same"],["FLAIR sequences","Model 1 Swoop System\n• FLAIR\n• Advanced Gridding\nreconstruction\nModel 2 Swoop System\n• FLAIR, FLAIR (Fast)\n• Advanced Gridding\nreconstruction","Same as Model 2 of\nsubject device","Same as Model 1 of\nsubject device"],["DWI sequences","Model 1 Swoop System\n• Single Direction DWI/ADC\n• Multi-direction DWI/ADC\n• Advanced Gridding + FISTA\nModel 2 Swoop System\n• Single Direction DWI/ADC,\n• Multi-direction DWI/ADC\n• Advanced Gridding + FISTA","• Single Direction\nDWI/ADC, Single\nDirection DWI/ADC\n(Fast)\n• Advanced Gridding +\nFISTA","• Single Direction\nDWI/ADC\n• Advanced Gridding +\nFISTA"],["Image Post-Processing\n(All sequences)","• Advanced Denoising\n• Image orientation transform\n• Geometric distortion\ncorrection\n• Receive coil intensity\ncorrection\n• Advanced Interpolation\n• ADC/Trace output (DWI)\n• DICOM output","• Advanced Denoising\n• Image orientation\ntransform\n• Geometric distortion\ncorrection\n• Receive coil intensity\ncorrection\n• Advanced\nInterpolation\n• ADC output (DWI)\n• DICOM output","• Advanced Denoising\n• Image orientation\ntransform\n• Geometric distortion\ncorrection\n• Receive coil intensity\ncorrection\n• Advanced\nInterpolation\n• ADC output (DWI)\n• DICOM output"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p9-t0","doc_id":"K253489","page_num":9,"bbox":[72.47,244.64,539.58,492.28],"n_rows":5,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Software\nVerification","Software verification testing in accordance with\nthe design requirements to ensure that the\nsoftware requirements were met.","• IEC 62304:2016\n• FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"],["Image Performance","Testing to verify the subject device meets all\nimage quality criteria.","• NEMA MS 1-2008 (R2020)\n• NEMA MS 3-2008 (R2020)\n• NEMA MS 9-2008 (R2020)\n• NEMA MS 12-2016\n• American College of Radiology\nstandards for named sequences"],["Cybersecurity","Testing to verify cybersecurity controls and\nmanagement.","• FDA Guidance, “Cybersecurity in\nMedical Devices: Quality System\nConsiderations and Content of\nPremarket Submissions”"],["Software\nValidation","Validation to ensure the subject device meets\nuser needs and performs as intended.","• FDA Guidance, “Content of Premarket\nSubmissions for Device Software\nFunctions”"]],"caption_candidate":"requirements and applicable standards to support substantial equivalence.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p9-t1","doc_id":"K253489","page_num":9,"bbox":[72.47,548.48,539.58,710.85],"n_rows":4,"n_cols":3,"columns":["Test","Test Description","Applicable Standard(s)"],"rows":[["Test","Test Description","Applicable Standard(s)"],["Biocompatibility","Biocompatibility testing of patient-contacting\nmaterials.","• ISO 10993-1:2018\n• ISO 10993-5:2009\n• ISO 10993-10:2010"],["Cleaning/\nDisinfection","Cleaning and disinfection validation of patient-\ncontacting materials.","• FDA Guidance, “Reprocessing Medical\nDevices in Health Care Settings:\nValidation Methods and Labeling”\n• ISO 17664:2017\n• ASTM F3208-17"],["Safety","Electrical Safety, EMC, and Essential Performance\ntesting.","• ANSI/AAMI ES 60601-1:2005/(R)2012\n• IEC 60601-1-2:2014\n• IEC 60601-1-6:2013"]],"caption_candidate":"modifications did not introduce a new worst-case configuration or scenario for testing.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p11-t0","doc_id":"K253489","page_num":11,"bbox":[72.47,72.59,538.28,379.24],"n_rows":4,"n_cols":6,"columns":["","Model /","","#Patients","#Images","Demographics"],"rows":[["","Model /","","#Patients","#Images","Demographics"],["","Sequence","","","",""],["","Group","","","",""],["DWI","","","8","31","Gender:\nFemale Male Unknown\n13% 87% 0%\nAge:\n0-2 2-18 18-35 35-60 60+ Unknown\n0% 0% 25% 0% 75% 0%\nEthnicity data not recorded.\nNumber of sites: 6\nEquipment:\nModel 1 Swoop System\nModel 2 Swoop System\n(V1.9)\n13% 87%\nIncluded pathology: Post-resection Tumor, ICH, Stroke, TBI, Post-\nCraniotomy."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p11-t1","doc_id":"K253489","page_num":11,"bbox":[235.87,122.42,533.54,153.67],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["13%","87%","0%"]],"caption_candidate":"DWI 8 31 Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p11-t2","doc_id":"K253489","page_num":11,"bbox":[235.87,181.42,533.54,212.7],"n_rows":2,"n_cols":6,"columns":["0-2","2-18","18-35","35-60","60+","Unknown"],"rows":[["0-2","2-18","18-35","35-60","60+","Unknown"],["0%","0%","25%","0%","75%","0%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p11-t3","doc_id":"K253489","page_num":11,"bbox":[235.87,286.73,449.82,327.23],"n_rows":2,"n_cols":2,"columns":["Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],"rows":[["Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],["13%","87%"]],"caption_candidate":"Equipment:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p12-t0","doc_id":"K253489","page_num":12,"bbox":[72.4,144.92,539.86,444.02],"n_rows":4,"n_cols":2,"columns":["Patients","12"],"rows":[["Patients","12"],["Images","45"],["ROIs","145"],["Demographics\nand other\nVariability","Gender:\nFemale Male Unknown\n25% 42% 33%\nAge:\n0-2 2-18 18-35 35-60 60+ Unknown\n0% 0% 8% 42% 33% 17%\nEthnicity data not recorded.\nNumber of sites: 5\nEquipment type:\nModel 1 Swoop System Model 1 Swoop System\nModel 2 Swoop System\n(V1.8) (V1.9)\n22% 22% 56%\nIncluded pathology: Acute/Subacute Stroke Stroke, Tumor, Post-operative Tumor, Cerebellar\nmetastatic disease, white matter disease, Acute/Subacute Infarct"]],"caption_candidate":"are shown below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p12-t1","doc_id":"K253489","page_num":12,"bbox":[156.45,204.46,535.11,235.71],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["25%","42%","33%"]],"caption_candidate":"Demographics Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p12-t2","doc_id":"K253489","page_num":12,"bbox":[156.45,248.45,481.57,279.72],"n_rows":2,"n_cols":6,"columns":["0-2","2-18","18-35","35-60","60+","Unknown"],"rows":[["0-2","2-18","18-35","35-60","60+","Unknown"],["0%","0%","8%","42%","33%","17%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p12-t3","doc_id":"K253489","page_num":12,"bbox":[156.45,353.74,535.11,394.49],"n_rows":2,"n_cols":3,"columns":["Model 1 Swoop System\n(V1.8)","Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],"rows":[["Model 1 Swoop System\n(V1.8)","Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],["22%","22%","56%"]],"caption_candidate":"Equipment type:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p13-t0","doc_id":"K253489","page_num":13,"bbox":[72.4,134.92,539.86,433.27],"n_rows":3,"n_cols":2,"columns":["Patients","34"],"rows":[["Patients","34"],["Images","102"],["Demographics\nand other\nVariability","Gender:\nFemale Male Unknown\n41% 35% 24%\nAge:\n0-2 2-18 18-35 35-60 60+ unknown*\n0% 0% 15% 26% 32% 26%\n*anonymized\nEthnicity data not recorded.\nNumber of sites: 8\nEquipment type:\nModel 1 Swoop System Model 1 Swoop System Model 2 Swoop System\n(V1.8) (V1.9)\n20% 10% 70%\nIncluded pathology: Acute Stroke, Subacute Stroke, Multiple Sclerosis, White matter disease,\nMetastatic disease, Post-operative glioma, Tumor, Hydrocephalus, ICH, IVH,"]],"caption_candidate":"DWI (trace-weighted or single direction), and ADC.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p13-t1","doc_id":"K253489","page_num":13,"bbox":[156.45,178.92,535.02,210.21],"n_rows":2,"n_cols":3,"columns":["Female","Male","Unknown"],"rows":[["Female","Male","Unknown"],["41%","35%","24%"]],"caption_candidate":"Demographics Gender:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p13-t2","doc_id":"K253489","page_num":13,"bbox":[156.45,222.95,535.02,254.2],"n_rows":2,"n_cols":6,"columns":["0-2","2-18","18-35","35-60","60+","unknown*"],"rows":[["0-2","2-18","18-35","35-60","60+","unknown*"],["0%","0%","15%","26%","32%","26%"]],"caption_candidate":"Age:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253489-p13-t3","doc_id":"K253489","page_num":13,"bbox":[156.45,342.97,535.02,395.74],"n_rows":2,"n_cols":3,"columns":["Model 1 Swoop System\n(V1.8)","Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],"rows":[["Model 1 Swoop System\n(V1.8)","Model 1 Swoop System\n(V1.9)","Model 2 Swoop System"],["20%","10%","70%"]],"caption_candidate":"Equipment type:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253520-p7-t0","doc_id":"K253520","page_num":7,"bbox":[72.12,560.88,539.87,716.82],"n_rows":6,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","Revolution Apex (K213715)","","","Photonova Spectra",""],["Contraindications","None","","","Same","",""],["Patient Population","Patients of all ages","","","Same","",""],["Gantry","• 80 cm patient bore\n• Rotation Speeds: 0.23, 0.28, 0.35,\n0.5, 0.6, 0.7, 0.8, 0.9, and 1.0\nseconds per rotation","","","• 80 cm patient bore\n• Rotation Speeds: 0.23, 0.28, 0.35,\n0.5, 0.6, 0.7, 0.8, 0.9, 1.0 & 2.0\nseconds per rotation","",""],["Detector","• Up to 160 mm in Z-direction with\nup to 50cm Scan field of view","","","• Up to 80 mm in Z-direction with up\nto 50 cm scan field of view","",""]],"caption_candidate":"preference.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253520-p8-t0","doc_id":"K253520","page_num":8,"bbox":[72.25,80.31,539.75,710.1],"n_rows":9,"n_cols":7,"columns":["Specification","","Predicate Device","","","Proposed Device",""],"rows":[["Specification","","Predicate Device","","","Proposed Device",""],["","","Revolution Apex (K213715)","","","Photonova Spectra",""],["","• 256 rows, 0.625 mm pixel pitch\n• Energy Integrating\n• Gemstone Scintillator Material\n• Detector Thermal System (DTS)\nwith high RPM fans","","","(40 mm option)\n• 192 rows, 0.2 mm pixel pitch in XY\nand 0.4 mm pixel pitch in Z\n• Photon Counting with 8 discrete\nenergy bins\n• Silicon Semiconductor Material\n• Detector Thermal System (DTS) with\nhigher RPM fans","",""],["X-Ray Tube","Quantix X-Ray Tube\n• 70, 80, 100, 120, 140 kVp\n• Focal Spot sizes: Extra Large,\nLarge, Small","","","Quantix X-Ray Tube\n• 120 kVp\n• Focal Spot sizes: Extra Large, Large,\nSmall, Extra Small","",""],["Collimator","Wolverine 2 Collimator\n• Diagnostic Bowties: Small,\nMedium, Large\n• Scout: SmartScout Filter\n• Calibration: No dedicated filter.","","","Badger Collimator\n• Diagnostic Bowties: Small, Large\n• Scout: SmartScout Filter\n• Calibration: Tungsten Filter","",""],["Patient Table","• Tables with scannable range of\n2000 mm & 1700mm\n• Load capacity 675 lbs","","","Same","",""],["Scan Modes","• Scout\n• Axial\n• Helical\n• Cine\n• Cardiac\n• Gated\n• High Definition\n• Fluoro (axial)\n• GSI\n• SmartScout\n• ECG-Less cardiac (K233750)","","","• Scout\n• Axial\n• Helical\n• Cardiac\n• Gated","",""],["Image\nReconstruction\nMatrix","512 x 512\n1024 x 1024","","","Same","",""],["Reconstruction\nAlgorithms","FBP\nASiR-V (K13640)\nDLIR (K213999)\nGSI-DLIR (K201745)","","","FBP with TrueFidelity DL for PCCT","",""]],"caption_candidate":"510(k) Premarket Notification Submission – Photonova Spectra","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253532-p4-t0","doc_id":"K253532","page_num":4,"bbox":[18.96,19.44,593.12,536.64],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\n1<253532 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\n1<253532 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","1<253532",""],["Please provide the device trade name(s).","",""],["TruSPECT Processing Station","",""],["Please provide your Indications for Use below.","","?"],["TruSPECT is intended for acceptance, transfer, display, storage, and processing of images for detection of\nradioisotope tracer uptakes in the patient's body. The device using various processing modes supported by\nthe various clinical applications and various features designed to enhance image quality. The emission\ncomputerized tomography data can be coupled with registered and/or fused CT/MR scans and with\nphysiological signals in order to depict, localize, and/or quantify the distribution of radionuclide tracers and\nanatomical structures in scanned body tissue for clinical diagnostic purposes. The acquired tomographic\nimage may undergo emission-based attenuation correction.\nVisualization tools include segmentation, colour coding, and polar maps. Analysis tools include Quantitative\nPerfusion SPECT (QPS), Quantitative Gated SPECT (QGS) and Quantitative Blood Pool Gated SPECT\n(QBS) measurements, Multi Gated Acquisition (MUGA) and Heart-to-Mediastinum activity ratio (H/M).\nThe system also includes reporting tools for formatting findings and user selected areas of interest. It is\ncapable of processing and displaying the acquired information in traditional formats, as well as in three-\ndimensional renderings, and in various forms of animated sequences, showing kinetic attributes of the\nimaged organs.\nTruSPECT is based on Windows operating system. Due to special customer requirements and the clinical\nfocus the TruSPECT can be configured with different combinations of Windows OS based software options\nand clinical applications which are intended to assist the physician in diagnosis and/or treatment planning.\nThis includes commercially available post-processing software packages.\nTruSPECT is a processing workstation primarily intended for, but not limited to cardiac applications. The\nworkstation can be integrated with the D-SPECT cardiac scanner system or used as a standalone post-\nprocessing station.","",""],["Please select the types of uses (select one or both, as [gJ Prescription Use (21 CFR 801 Subpart 0)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253532-p5-t0","doc_id":"K253532","page_num":5,"bbox":[72.02,142.22,256.36,474.91],"n_rows":12,"n_cols":3,"columns":["","Date of submission:",""],"rows":[["","Date of submission:",""],["Submitter:","",""],["","",""],["Submitter Contact:","",""],["","",""],["","Device Trade Name:",""],["","",""],["","Common Name/Classification:",""],["","Class:",""],["","Product Code:",""],["","Classification Panel:",""],["","Regulation No:",""]],"caption_candidate":"510(k) Number: K253532","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253532-p8-t0","doc_id":"K253532","page_num":8,"bbox":[72.29,159.62,539.83,294.17],"n_rows":4,"n_cols":9,"columns":["","Characteristic","","","Predicate device","","","Proposed device",""],"rows":[["","Characteristic","","","Predicate device","","","Proposed device",""],["Workflow","","","Manual and automated processes, pre-\ntrained neural networks in iterative\nreconstruction, traditional algorithms","","","Same","",""],["AI utilization","","","Non-adaptive machine learning algorithms\ntrained with clinical data","","","Same","",""],["Hardware","","","Preinstalled on Spectrum Dynamics\nworkstation or loaded onto customer’s\nworkstation meeting specifications","","","Same","",""]],"caption_candidate":"TruClear AI post-processing capability.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253532-p9-t0","doc_id":"K253532","page_num":9,"bbox":[72.29,127.94,539.84,247.58],"n_rows":7,"n_cols":8,"columns":["Parameter","Bland Altman\nMean (bias)","","Bland Altman","","Regression r\n(min)","Slope (range)","Intercept\n(limit)"],"rows":[["Parameter","Bland Altman\nMean (bias)","","Bland Altman","","Regression r\n(min)","Slope (range)","Intercept\n(limit)"],["","","","SD","","","",""],["","","","(precision)","","","",""],["LVEF","±3%","≤ 4%","","","> 0.8","0.9 – 1.1","± 10%"],["EDV","± 5 ml","≤ 8 ml","","","> 0.8","0.9 – 1.1","± 10 ml"],["Perfusion\nVolume","± 5 ml","≤ 8 ml","","","> 0.8","0.9 – 1.1","± 10 ml"],["TPD","± 3%","≤ 5%","","","> 0.8","0.9 – 1.1","± 10%"]],"caption_candidate":"Clinical Validation Acceptance Criteria (Prespecified)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p3-t0","doc_id":"K253551","page_num":3,"bbox":[257.81,182.83,570.36,279.05],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p5-t0","doc_id":"K253551","page_num":5,"bbox":[72.26,136.08,719.98,531.48],"n_rows":21,"n_cols":2,"columns":["Submitter Information",""],"rows":[["Submitter Information",""],["Applicant Name","DePuy Ireland UC"],["Applicant Address","Loughbeg Ringaskiddy Ireland"],["Applicant Contact Telephone","+1 574-404-8348"],["Applicant Contact","Ms. Erin Combs"],["Applicant Contact Email","ecombs@its.jnj.com"],["Correspondent Name","DePuy Ireland UC"],["Correspondent Address","Loughbeg Ringaskiddy Ireland"],["Correspondent Contact Telephone","+1 267-889-5354"],["Correspondent Contact","Ms. Anuradha Moholkar"],["Correspondent Contact Email","AMoholk1@its.jnj.com"],["Name of Device",""],["Device Trade Name","VELYS™ Hip Navigation"],["Common Name","Medical image management and processing system"],["Classification Name","System, Image Processing, Radiological"],["Regulation Number","892.2050"],["Product Code(s)","QIH, LLZ"],["Legally Marketed Predicate Devices",""],["Predicate","K160284"],["Predicate Trade Name","JointPoint"],["Product Code","LLZ; HAW"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p7-t0","doc_id":"K253551","page_num":7,"bbox":[77.82,141.42,725.22,426.36],"n_rows":10,"n_cols":4,"columns":["","Predicate","Subject Device:",""],"rows":[["","Predicate","Subject Device:",""],["Characteristics","Device:","","Discussion"],["","","VELYS™ Hip Navigation",""],["","JointPoint","",""],["","","K253551",""],["","K160284","",""],["Medical Specialty","Radiology","Radiology","Identical"],["Regulation","21 CFR 892.2050 Picture archiving and\ncommunications system","21 CFR 892.2050 Picture archiving and\ncommunications system","Identical"],["Product Code","LLZ System, image processing,\nradiological\nHAW Neurological stereotaxic instrument","QIH Automated radiological image\nprocessing software\nLLZ System, image processing,\nradiological","Equivalent. Both devices use\nanatomic landmarks identified from\nradiology images to assist in\npositioning total hip replacement\ncomponents intraoperatively, and to\nsupport preoperative planning in\ntotal hip and total knee procedures"],["Intended Use","JointPoint is a non-invasive software\n(Software as a Medical Device) intended\nto provide preoperative templating for\northopedic procedures and intraoperative\ndata for total hip arthroplasties (THA).","VELYS™ Hip Navigation is a non-\ninvasive software (Software as a Medical\nDevice) intended to provide preoperative\ntemplating for orthopedic procedures and\nintraoperative data for total hip\narthroplasties (THA).","Identical"]],"caption_candidate":"device support that there are no new questions of safety or effectiveness.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p8-t0","doc_id":"K253551","page_num":8,"bbox":[77.76,101.28,725.28,533.4],"n_rows":3,"n_cols":4,"columns":["Indications for\nUse","JointPoint is an image-processing\nsoftware indicated to assist in the\npositioning of total hip replacement\ncomponents. It is intended to assist in\nprecisely positioning total hip\nreplacement components intra-\noperatively by measuring their positions\nrelative to the bone structures of interest\nprovided that the points of interest can\nbe identified from radiology images.\nJointPoint is also indicated for assisting\nhealthcare professionals in preoperative\nplanning and postoperative analysis of\northopedic surgery in Total Hip\nReplacement, Total Knee Replacement,\nand Intertrochanteric Fracture\nReduction. The device allows for\noverlaying of prosthesis templates on\nradiological images and includes tools\nfor performing measurements on the\nimage and for positioning the template.\nClinical judgment and experience are\nrequired to properly use the software.\nThe software is not for primary image\ninterpretation. The software is not for\nuse on mobile phones.","VELYS™ Hip Navigation is an image-\nprocessing software indicated to assist in\nthe positioning of total hip replacement\ncomponents. It is intended to assist in\nprecisely positioning total hip replacement\ncomponents intra-operatively by\nmeasuring their positions relative to the\nbone structures of interest provided that\nthe points of interest can be identified\nfrom radiology images.\nVELYS Hip Navigation is also indicated\nfor assisting healthcare professionals in\npreoperative planning and postoperative\nanalysis of orthopedic surgery in Total\nHip Replacement and Total Knee\nReplacement. The device allows for\noverlaying of prosthesis templates on\nradiological images and includes tools for\nperforming measurements on the image\nand for positioning the template. Clinical\njudgment and experience are required to\nproperly use the software. The software is\nnot for primary image interpretation. The\nsoftware is not for use on mobile phones.","Identical. The indications for use\nof the subject device fall within the\nintended use of the predicate\ndevice."],"rows":[["Indications for\nUse","JointPoint is an image-processing\nsoftware indicated to assist in the\npositioning of total hip replacement\ncomponents. It is intended to assist in\nprecisely positioning total hip\nreplacement components intra-\noperatively by measuring their positions\nrelative to the bone structures of interest\nprovided that the points of interest can\nbe identified from radiology images.\nJointPoint is also indicated for assisting\nhealthcare professionals in preoperative\nplanning and postoperative analysis of\northopedic surgery in Total Hip\nReplacement, Total Knee Replacement,\nand Intertrochanteric Fracture\nReduction. The device allows for\noverlaying of prosthesis templates on\nradiological images and includes tools\nfor performing measurements on the\nimage and for positioning the template.\nClinical judgment and experience are\nrequired to properly use the software.\nThe software is not for primary image\ninterpretation. The software is not for\nuse on mobile phones.","VELYS™ Hip Navigation is an image-\nprocessing software indicated to assist in\nthe positioning of total hip replacement\ncomponents. It is intended to assist in\nprecisely positioning total hip replacement\ncomponents intra-operatively by\nmeasuring their positions relative to the\nbone structures of interest provided that\nthe points of interest can be identified\nfrom radiology images.\nVELYS Hip Navigation is also indicated\nfor assisting healthcare professionals in\npreoperative planning and postoperative\nanalysis of orthopedic surgery in Total\nHip Replacement and Total Knee\nReplacement. The device allows for\noverlaying of prosthesis templates on\nradiological images and includes tools for\nperforming measurements on the image\nand for positioning the template. Clinical\njudgment and experience are required to\nproperly use the software. The software is\nnot for primary image interpretation. The\nsoftware is not for use on mobile phones.","Identical. The indications for use\nof the subject device fall within the\nintended use of the predicate\ndevice."],["Anatomical Site\nand Target\nPopulation","Patients who are candidates for\northopedic procedures and total hip\nreplacement","Patients who are candidates for total hip\nreplacement and total knee replacement","Identical. The target population of\nthe subject device is within that of\nthe predicate device. There are no\nnew questions of safety or\nefficacy."],["Environment of\nUse","Physician’s office and operating room","Physician’s office and operating room","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p9-t0","doc_id":"K253551","page_num":9,"bbox":[77.32,101.46,724.76,503.16],"n_rows":6,"n_cols":4,"columns":["PRINCIPLES OF OPERATION","","",""],"rows":[["PRINCIPLES OF OPERATION","","",""],["","","",""],["Image Inputs","Preoperative and intraoperative\nradiographic patient images of the pelvis","Preoperative and intraoperative\nradiographic patient images of the pelvis","Identical"],["Pre-operative\nAnalysis","Preoperative templating:\n• Image import\n• Image calibration\n• User selected templates of\nimplants for THA or TKA\n• Digital annotations\n• Leg length analysis tool (THA)\n• Manual landmark selections","Preoperative templating:\n• Image import\n• Image calibration\n• User selected templates of implants\nfor THA or TKA\n• Digital annotations\n• Leg length analysis tool (THA)\n• Manual landmark selections","Identical"],["Intraoperative\nLandmark\nSelection","• User places anatomical landmarks\non patient images using digital\ntools (manual landmark selection)\n• Surgeon confirms placement\nof landmarks","• When enabled, an ML model\ndetermines the default landmark\nposition. The user confirms and/or\nadjusts the landmark position using\ndigital tools. This feature is available\nin Windows Version only.\n• Manual landmark selection is\navailable as an option\n• Surgeon confirms placement of\nlandmarks","Equivalent. With the subject device,\nwhen enabled, the default landmark\nlocation is determined by an ML\nmodel. In both the subject device and\nthe predicate device, the user can\nmove the landmark selections using\ndigital tools, and the surgeon must\nconfirm placement of the landmarks.\nPerformance testing did not raise new\nissues of safety or efficacy."],["Intraoperative\nWorkflow\nOutputs","• Software provides leg length\nand offset data for selected\nimplant constructs and\nalternatives\n• Software provides inclination\nand anteversion of the trial or\nfinal acetabular implant\n• Manual landmark selection","• Software provides leg length and\noffset data for selected implant\nconstructs and alternatives\n• Software provides inclination and\nanteversion of the trial or final\nacetabular implant\n• Manual landmark selection or\nAI assisted landmarking","Identical"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p10-t0","doc_id":"K253551","page_num":10,"bbox":[77.28,101.28,724.8,275.76],"n_rows":2,"n_cols":4,"columns":["Other Workflows","• Contralateral overlay allows an\nanterior-posterior (AP) image of\nthe non-operative side to be\ncompared to the operative side.\n• OneTrial® Manual\nlandmark selection","• Contralateral overlay allows an\nanterior-posterior (AP) image of the\nnon-operative side to be compared to\nthe operative side.\n• OneTrial® Manual\nlandmark selection","Identical"],"rows":[["Other Workflows","• Contralateral overlay allows an\nanterior-posterior (AP) image of\nthe non-operative side to be\ncompared to the operative side.\n• OneTrial® Manual\nlandmark selection","• Contralateral overlay allows an\nanterior-posterior (AP) image of the\nnon-operative side to be compared to\nthe operative side.\n• OneTrial® Manual\nlandmark selection","Identical"],["Operating System","Windows, iOS","Windows, iOS","Identical. With the subject device,\nthe AI assisted landmark placement\nis only available in the Windows\nversion. The iOS version of the\nsubject device is identical to the\npredicate device."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253551-p11-t0","doc_id":"K253551","page_num":11,"bbox":[72.0,269.16,677.04,341.52],"n_rows":4,"n_cols":4,"columns":["Model","mAR","mAP","mAP@0.75"],"rows":[["Model","mAR","mAP","mAP@0.75"],["OneTrial","0.9920","0.9852","0.9900"],["CupCheckGuidedBilateral","0.9880","0.9798","1.0000"],["CupCheckGuidedUnilateral","0.9985","0.9968","1.0"]],"caption_candidate":"• mAP@0.75: Indicates precision at a higher threshold of localization accuracy.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p8-t0","doc_id":"K253564","page_num":8,"bbox":[43.68,135.62,766.68,531.58],"n_rows":14,"n_cols":9,"columns":["ITEM","","Proposed Device\nuMI Panvivo","","","","Predicate Device\nuMI Panvivo(K251839)","","Remark"],"rows":[["ITEM","","Proposed Device\nuMI Panvivo","","","","Predicate Device\nuMI Panvivo(K251839)","","Remark"],["Model","","uMI Panvivo","uMI Panvivo S","uMI Panvivo ES","uMI Panvivo EX","uMI Panvivo","uMI Panvivo S",""],["Detector","Scintillator material","LYSO","LYSO","LYSO","LYSO","LYSO","LYSO","Same"],["","Scintillator dimensions","2.76mm×2.76\nmm×18.1mm","2.76mm×2.76\nmm×18.1mm","2.76mm×2.76m\nm×18.1mm","2.76mm×2.76m\nm×18.1mm","2.76mm×2.76\nmm×18.1mm","2.76mm×2.76m\nm×18.1mm","Same"],["","Detector ring diameter","734","734","734","734","734","734","Same"],["","Number of detector rings","100","80","180","240","100","80","Note 1"],["","Axial field of view","295 mm","235 mm","534mm","712mm","295 mm","235 mm",""],["","Coincidence window","4.6ns","4.6ns","4.9ns","4.9ns","4.6ns","4.6ns","Note 2"],["Spatial\nResolution","Axial FWHM@1cm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","Same"],["","Radial FWHM @1cm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm",""],["","Tangential FWHM @1cm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm","＜3.5mm",""],["","Axial FWHM@10cm","≤4.0mm","＜4.0mm","＜4.0mm","＜4.0mm","≤4.0mm","＜4.0mm",""],["","Radial FWHM @1cm","≤4.0mm","＜4.0mm","＜4.0mm","＜4.0mm","≤4.0mm","＜4.0mm",""],["","Tangential FWHM@10cm","≤4.0mm","＜4.0mm","＜4.0mm","＜4.0mm","≤4.0mm","＜4.0mm",""]],"caption_candidate":"Table 1 Comparison to Predicate device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p9-t0","doc_id":"K253564","page_num":9,"bbox":[43.68,108.02,766.68,507.58],"n_rows":9,"n_cols":9,"columns":["","Axial FWHM@20cm","≤5.0mm","＜5.0mm","＜5.0mm","＜5.0mm","≤5.0mm","＜5.0mm",""],"rows":[["","Axial FWHM@20cm","≤5.0mm","＜5.0mm","＜5.0mm","＜5.0mm","≤5.0mm","＜5.0mm",""],["","Radial FWHM @20cm","≤5.0mm","＜5.0mm","＜5.0mm","＜5.0mm","≤5.0mm","＜5.0mm",""],["","Tangential FWHM@20cm","≤5.0mm","＜5.0mm","＜5.0mm","＜5.0mm","≤5.0mm","＜5.0mm",""],["Sensitivity","","＞16cps/kBq","＞10cps/kBq","＞48ps/kBq","＞85ps/kBq","＞16cps/kBq","＞10cps/kBq","Note 3"],["NECR Peak Value","","＞300kcps","＞200kcps","＞900kcps","＞1550cps","＞300kcps","＞200kcps","Note 4"],["Peak True Count Rate","","＞1500kcps","＞800kcps","＞2000kcps","＞2000kcps","＞1500kcps","＞800kcps",""],["PET Scatter Fraction","","＜0.42","＜0.42","＜0.42","＜0.42","＜0.42","＜0.42","Same"],["Accuracy (absolute value)","","＜5%","＜5%","＜5%","＜5%","＜5%","＜5%","Same"],["Image Quality","","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Contrast\nRecovery\n10 mm Sphere\n＞45.0%\n13 mm Sphere\n＞55.0%\n17 mm Sphere\n＞65.0%","Same"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p10-t0","doc_id":"K253564","page_num":10,"bbox":[77.4,40.35,695.97,529.98],"n_rows":47,"n_cols":9,"columns":["Shanghai United Imaging Healthcare Co., Ltd.","","","","","","","",""],"rows":[["Shanghai United Imaging Healthcare Co., Ltd.","","","","","","","",""],["Tel: +86 (21) 67076888 Fax：+86 (21) 670768","89","","","","","","",""],["www.united-imaging.com","","","","","","","",""],["","","","","","","","",""],["","22 mm Sphere","22 mm Sphere","22 mm Sphere","","22 mm Sphere","","22 mm Sphere","22 mm Sphe"],["","","","","","","","",""],["","＞72.0%","＞72.0%","＞72.0%","","＞72.0%","","＞72.0%","＞72.0%"],["","","","","","","","",""],["","28 mm Sphere","28 mm Sphere","28 mm Sphere","","28 mm Sphere","","28 mm Sphere","28 mm Sphe"],["","","","","","","","",""],["","＞65.0%","＞65.0%","＞65.0%","","＞65.0%","","＞65.0%","＞65.0%"],["","","","","","","","",""],["","37 mm Sphere","37 mm Sphere","37 mm Sphere","","37 mm Sphere","","37 mm Sphere","37 mm Sphe"],["","","","","","","","",""],["","＞70.0%","＞70.0%","＞70.0%","","＞70.0%","","＞70.0%","＞70.0%"],["","","","","","","","",""],["","Lung Residual","Lung Residual","Lung Residual","","Lung Residual","","Lung Residual","Lung Resid"],["","","","","","","","",""],["","error ＜8.0%","error ＜8.0%","error ＜8.0%","","error ＜8.0%","","error ＜8.0%","error ＜8.0%"],["","","","","","","","",""],["","Background","Background","Background","","Background","","Background","Background"],["","","","","","","","",""],["","variability","variability","variability","","variability","","variability","variability"],["","","","","","","","",""],["","10mm Sphere","10mm Sphere","10mm Sphere","＜","10mm Sphere","＜","10mm Sphere","10mm Sphe"],["","","","","","","","",""],["","＜7.5%","＜7.5%","7.5%","","7.5%","","＜7.5%","＜7.5%"],["","","","","","","","",""],["","13mm Sphere","13mm Sphere","13mm Sphere","＜","13mm Sphere","＜","13mm Sphere","13mm Sphe"],["","","","","","","","",""],["","＜7.0%","＜7.0%","7.0%","","7.0%","","＜7.0%","＜7.0%"],["","","","","","","","",""],["","17mm Sphere","17mm Sphere","17mm Sphere","＜","17mm Sphere","＜","17mm Sphere","17mm Sphe"],["","","","","","","","",""],["","＜7.0%","＜7.0%","7.0%","","7.0%","","＜7.0%","＜7.0%"],["","","","","","","","",""],["","22mm Sphere","22mm Sphere","22mm Sphere","＜","22mm Sphere","＜","22mm Sphere","22mm Sphe"],["","","","","","","","",""],["","＜7.0%","＜7.0%","7.0%","","7.0%","","＜7.0%","＜7.0%"],["","","","","","","","",""],["","28mm Sphere","28mm Sphere","28mm Sphere","＜","28mm Sphere","＜","28mm Sphere","28mm Sphe"],["","","","","","","","",""],["","＜7.0%","＜7.0%","7.0%","","7.0%","","＜7.0%","＜7.0%"],["","","","","","","","",""],["","37mm Sphere","37mm Sphere","37mm Sphere","＜","37mm Sphere","＜","37mm Sphere","37mm Sphe"],["","","","","","","","",""],["","＜7.0%","＜7.0%","7.0%","","7.0%","","＜7.0%","＜7.0%"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K253564-p11-t0","doc_id":"K253564","page_num":11,"bbox":[49.08,40.35,748.3,455.5],"n_rows":29,"n_cols":9,"columns":["","Shanghai United Imaging Healthcare Co., Ltd.","","","","","","",""],"rows":[["","Shanghai United Imaging Healthcare Co., Ltd.","","","","","","",""],["","Tel: +86 (21) 67076888 Fax：+86 (21) 670768","89","","","","","",""],["","www.united-imaging.com","","","","","","",""],["","","","","","","","",""],["Time-","of-flight Resolution","＜ 245 ps","＜ 245 ps","＜ 245 ps","＜ 245 ps","＜ 245 ps","＜ 245 ps","Same"],["","","","","","","","",""],["PET-C","T Coregistration Accuracy","＜ 3.0 mm","＜ 3.0 mm","＜ 3.0 mm","＜ 3.0 mm","＜ 3.0 mm","＜ 3.0 mm","Same"],["","","","","","","","",""],["Table","Maximum table load","280kg","280kg","280kg","280kg","250kg","250kg","Note"],["","","","","","","","",""],["Advan","ced Funciton","","","","","","",""],["","","","","","","","",""],["Deep","MAC","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["Digital","Gating","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["OncoF","ocus","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["Neuro","Focus.Brain","No","No","Yes","Yes","No","No","Note"],["","","","","","","","",""],["uExcel","DPR","Yes","Yes","Yes","Yes","Yes","Yes","Note"],["","","","","","","","",""],["ukineti","cs","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["AI EF","OV","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["HYPE","R Iterative","Yes","Yes","Yes","Yes","Yes","Yes","Same"],["","","","","","","","",""],["Intellig","ent Assistant","No","No","Yes","Yes","No","No","Note8"]],"caption_candidate":"Shanghai United Imaging Healthcare Co., Ltd.","well_formed":true,"extraction_settings":"text"}
{"table_id":"K253564-p12-t0","doc_id":"K253564","page_num":12,"bbox":[86.42,91.46,554.38,682.18],"n_rows":9,"n_cols":2,"columns":["Justification",""],"rows":[["Justification",""],["Note 1","The number of detector rings and the axial Field of View (aFOV) of the poposed devices are\nlarger than that of the predicate devices. A longer aFOV can increase the scanning range per bed\nposition, thereby reducing the number of bed positions required for a whole-body scan and\nshortening the total scanning time.\nThe differences do not affect the clinical effectiveness and safety."],["Note 2","For systems with a longer aFOV, the coincidence timing window was increased based on\nsimulation analyses to accommodate the detection of more LORs (Line of Response). This\nadjustment is moderate and well-controlled, and does not affect the system's Image Quality (IQ)\nperformance.\nThe difference does not affect the clinical effectiveness and safety."],["Note 3","The Sensitivities of the proposed devices are larger than that of the predicate devices. Improved\nsystem sensitivity enables the acquisition of more counts under identical scan duration and\nradiotracer activity, which in turn leads to better image quality.\nThe difference does not raise new safety and effectiveness concerns."],["Note 4","The proposed devices provide larger NECR peak value and Peak True Count Rate to the Predicate\ndevices. The higher NECR Peak Value and Peak True Count Rate will let system acquire more\neffective data even in high activity concentration.\nThe difference does not raise new safety and effectiveness concerns."],["Note 5","Following system tests that confirmed the table's ability to support a 280 kg load, the maximum\nload specification has been increased. This revision is justified, as the original specifications\nincluded an excessive safety margin, with no changes to the bed's design.\nThe difference does not raise new safety and effectiveness concerns."],["Note 6","NeuroFocus.Brain is a brain-artifact elimination solution that employs a statistics-based motion\ndetection method to automatically select an optimal motion-free subset of counts for\nreconstruction.\nThe long-axial PET systems (uMI Panvivo EX and uMI Panvivo ES), unlike the previously\ncleared short-axial uMI Panvivo and uMI Panvivo S, provide inherently higher native sensitivity\nthat compensates for the discarded counts. The exclusive use of the optimal subset improves\nreconstruction efficiency.\nPerformance and clinical image evaluation were conducted on the proposed device. It is shown\nthat the difference did not raise new safety and effectiveness concerns."],["Note 7","The uExcel DPR implemented on the uMI Panvivo EX and uMI Panvivo ES systems is\nalgorithmically identical to the previously cleared uExcel DPR feature on the uMI Panvivo and\nuMI Panvivo S systems. The sole distinction lies in the declared intended use, uMI Panvivo ES\nand uMI Panvivo EX only support FDG (¹⁸F-FDG) while uMI Panvivo and uMI Panvivo S\nsupports several imaging agents.\nPerformance and clinical image evaluation were conducted on the proposed device. It is shown\nthat the difference did not raise new safety and effectiveness concerns."],["Note 8","The Intelligent Assistant is a local auxiliary query tool that responds to PETCT operation-related\nquestions based on validated knowledge (including user manuals and common issues). It does not\ncontrol or modify the system's hardware, core software, scanning parameters, or reconstruction\nprocesses, nor does it alter the original operational workflow.\nThe addition of this feature does not raise new safety and effectiveness concerns."]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p14-t0","doc_id":"K253564","page_num":14,"bbox":[107.94,684.15,540.06,708.4],"n_rows":2,"n_cols":4,"columns":["","Subjects' Characteristics","","N(%)"],"rows":[["","Subjects' Characteristics","","N(%)"],["","(N=20)","",""]],"caption_candidate":"Table 2 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p15-t0","doc_id":"K253564","page_num":15,"bbox":[108.25,77.58,539.75,226.58],"n_rows":12,"n_cols":2,"columns":["Gender, N(%)",""],"rows":[["Gender, N(%)",""],["Male","12(60%)"],["Female","8(40%)"],["Age, N(%)",""],["0-29","1(5%)"],["30-49","1(5%)"],["50-69","9(45%)"],[">=70","9(45%)"],["Ethnicity, N(%)",""],["Caucasian","1(5%)"],["Asian","18(90%)"],["Negroid","1(5%)"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p15-t1","doc_id":"K253564","page_num":15,"bbox":[108.25,352.01,539.75,461.71],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["Quantitative\nevaluation","For PMMA phantom data, the\naverage CT value in the affected\narea of the metal substance and\nthe same area of the control image\nbefore and after DeepMAC was\ncompared.","After using DeepMAC,\nthe difference between\nthe average CT value in\nthe affected area of the\nmetal substance and the\nsame area of the control\nimage does not exceed\n10HU.","Pass"]],"caption_candidate":"Table 3 The performance evaluation report criteria of DeepMAC","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p16-t0","doc_id":"K253564","page_num":16,"bbox":[108.46,266.02,539.6,458.11],"n_rows":15,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=8)","",""],["Gender, N(%)","",""],["Male","","5 (62.5%)"],["Female","","3 (37.5%)"],["Age, N(%)","",""],["<30","","2 (25.0%)"],["30-60","","3 (37.5%)"],[">60","","3 (37.5%)"],["Ethnicity, N(%)","",""],["Asian","","8 (100%)"],["Body Mass Index (BMI), N(%)","",""],["Healthy weight (18.5-24.9)","","4 (50.0%)"],["Overweight (25.0-29.9)","","3 (37.5%)"],["Obesity (>=30.0)","","1 (12.5%)"]],"caption_candidate":"Table 4 The demographic distribution of human subjects","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p16-t1","doc_id":"K253564","page_num":16,"bbox":[108.46,567.55,539.6,701.5],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["NEMA IQ phantom\nanalysis","Contrast recovery (CR),\nbackground variability\n(BV), and contrast-to-noise\nratio (CNR) were\ncalculated using NEMA IQ\nphantom data reconstructed\nwith uExcel DPR and\nOSEM under acquisition\nconditions of 1 to 5\nminutes per bed.","The averaged CR,\nBV, and CNR of\nthe uExcel DPR\nimages should be\nsuperior to those\nof the OSEM\nimages.","Pass"]],"caption_candidate":"Table 5 The performance evaluation report criteria of uExcel DPR","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p18-t0","doc_id":"K253564","page_num":18,"bbox":[107.34,91.39,538.64,268.85],"n_rows":13,"n_cols":2,"columns":["Subjects' Characteristics\n(N=13)","N(%)"],"rows":[["Subjects' Characteristics\n(N=13)","N(%)"],["Gender, N(%)",""],["Male","7(54%)"],["Female","6(46%)"],["Age, N(%): Min=34, Max=90, Avg.=72.7, Std.=11.9",""],["30-44","1(8%)"],["45-64","1(8%)"],[">=65","11(85%)"],["Ethnicity, N(%)",""],["Asian","13(100%)"],["Body Mass Index (BMI), N(%): Min=20.4, Max=29.4, Avg.=23.5, Std.=2.9",""],["Healthy weight (18.5-24.9)","10(77%)"],["Overweight (25.0-29.9)","3(23%)"]],"caption_candidate":"Table 6 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p18-t1","doc_id":"K253564","page_num":18,"bbox":[97.22,584.62,550.9,710.86],"n_rows":3,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["Volume relative to no\nrespiratory motion\ncorrection (∆Volume).","Calculating the OncoFocus volume\nchange relative to no respiratory\nmotion correction images","The ∆Volume\nvalue is less\nthan 0%.","Pass"],["Maximal standardized\nuptake value relative\nto no respiratory\nmotion correction\n(∆SUVmax)","Calculating the SUVmax obtained\nfrom the OncoFocus with that from\nthe corresponding non-corrected\nimage","The ∆SUVmax\nvalue is large\nthan 0%.","Pass"]],"caption_candidate":"Table 7 The performance evaluation report criteria of OncoFocus","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p19-t0","doc_id":"K253564","page_num":19,"bbox":[106.74,681.39,538.78,717.94],"n_rows":3,"n_cols":5,"columns":["","Subjects' Characteristics","","N(%)",""],"rows":[["","Subjects' Characteristics","","N(%)",""],["","(N=7)","","",""],["","Gender, N(%)","","",""]],"caption_candidate":"Table 8 Distribution of volunteer dataset","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p20-t0","doc_id":"K253564","page_num":20,"bbox":[107.34,77.52,539.04,218.3],"n_rows":11,"n_cols":2,"columns":["Male","5(71.4%)"],"rows":[["Male","5(71.4%)"],["Female","2(28.6%)"],["Age, N(%): Min=24 Max=79, Avg.=57.4, Std.=21.7",""],["20-44","2(28.6%)"],["45-64","1(14.2%)"],[">=65","4(57.1%)"],["Ethnicity, N(%)",""],["Asian","7(100%)"],["Body Mass Index (BMI), N(%): Min=20.9, Max=28.3, Avg.=24.5, Std.=2.5",""],["Healthy weight (18.5-24.9)","4(57.1%)"],["Overweight (25.0-29.9)","3(42.9%)"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p20-t1","doc_id":"K253564","page_num":20,"bbox":[107.34,500.35,539.04,708.82],"n_rows":3,"n_cols":4,"columns":["Evaluation\nItem","Evaluation Method","Criteria","Results"],"rows":[["Evaluation\nItem","Evaluation Method","Criteria","Results"],["Quantitative\nevaluation","Calculate ∆SUVmean in the high-\nuptake region for two MCS cases:\none with motion introduced during\nsimulation and reconstructed\nusing NeuroFocus.Brain, and one\nstationary reconstructed without\nNeuroFocus.Brain.","The ∆SUVmean\nvalue is less than\n10%.","Pass"],["","Calculate ∆SUVmean in the high-\nuptake region of the prefrontal\ncortex, relative to reconstruction\nwithout NeuroFocus.Brain for the\nsame clinical scan with head\nmotion.","The ∆SUVmean\nvalue is large\nthan 0%.","Pass"]],"caption_candidate":"Table 9 The performance evaluation report criteria of NeuroFocus.Brain","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p22-t0","doc_id":"K253564","page_num":22,"bbox":[108.46,77.57,539.6,269.69],"n_rows":15,"n_cols":3,"columns":["Subjects' Characteristics","","N(%)"],"rows":[["Subjects' Characteristics","","N(%)"],["(N=4)","",""],["Gender, N(%)","",""],["Male","","2 (50.0%)"],["Female","","2 (50.0%)"],["Age, N(%): Min=35 Max=73, Avg.=57.3, Std.=16.4","",""],["20-44","","1 (25.0%)"],["45-64","","1 (25.0%)"],[">=65","","2 (50.0%)"],["Ethnicity, N(%)","",""],["Asian","","4 (100%)"],["Body Mass Index (BMI), N(%): Min=26.1, Max=28.3, Avg.=27.3, Std.=0.9","",""],["Healthy weight (18.5-24.9)","","0 (0%)"],["Overweight (25.0-29.9)","","4 (100.0%)"],["Obesity (>=30.0)","","0 (0%)"]],"caption_candidate":"www.united-imaging.com","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253564-p22-t1","doc_id":"K253564","page_num":22,"bbox":[108.46,380.57,539.6,538.63],"n_rows":2,"n_cols":4,"columns":["Evaluation Item","Evaluation Method","Criteria","Results"],"rows":[["Evaluation Item","Evaluation Method","Criteria","Results"],["Quantitative\nevaluation","For phantom study, the water\nphantom outside of CT scan-\nFOV was tested to compare the\nAIEFOV algorithm with EFOV\nalgorithm.\nFor patient study, the SUV of\nsome ROIs in PET image with\nattenuation correction\nperformed with CT generated\nwith EFOV and AIEFOV\nalgorithm will be compared.","Compared to the ground truth, the\nuniformity and SUV deviation of\nPET image obtained by using\nAIEFOV for attenuation\ncorrection should be less than\n5%.\nAnd when the scanned object\ndoes not exceed the CT field of\nview, attenuation correction using\nCT generated either with\nAIEFOV or EFOV should result\nin consistent PET image SUV.","Pass"]],"caption_candidate":"Table 11 The performance evaluation report criteria of AIEFOV","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p6-t0","doc_id":"K253574","page_num":6,"bbox":[72.29,320.64,523.03,381.36],"n_rows":3,"n_cols":6,"columns":["","Product Name","","","Trade Name",""],"rows":[["","Product Name","","","Trade Name",""],["SOMATOM X.cite","","","SOMATOM X.cite","",""],["SOMATOM X.ceed","","","SOMATOM X.ceed","",""]],"caption_candidate":"Table 1: Subject Device Names","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p10-t0","doc_id":"K253574","page_num":10,"bbox":[72.29,613.68,523.03,728.04],"n_rows":3,"n_cols":6,"columns":["","Term","","","Definition",""],"rows":[["","Term","","","Definition",""],["Modified","","","This feature is modified from the predicate devices","",""],["Enabled","","","This feature is currently supported by other cleared Siemens CT systems or\ncleared Siemens stand-alone software applications. This feature will be\nsupported for the subject device with software version SOMARIS/10 syngo CT\nVB20 and is substantially equivalent compared to the cleared version of the\npredicate devices.","",""]],"caption_candidate":"Table 2: Overview of term definition.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p11-t0","doc_id":"K253574","page_num":11,"bbox":[72.26,169.8,523.05,605.88],"n_rows":12,"n_cols":10,"columns":["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],"rows":[["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],["","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB20","SOMATOM X.","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB10\n(K233650)","SOMATOM go.",""],["","","","","Platform","","","","Platform",""],["","","","","with syngo CT","","","","with syngo CT",""],["","","","","VB20","","","","VB20",""],["","","","","","","","","(K250822)",""],["1.","CARE Moodlight","HW/SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["2.","Interfaces for\nrespiratory gating\nsystems – Open\nOnline Interface","HW","enabled\n(same as in\nK250822)","","","n.a.1","","cleared",""],["3.","Eco Power Mode","HW/SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["4.","FAST 3D Camera/\nFAST Integrated\nWorkflow","SW","enabled2\n(same as in\nK250822)","","","cleared","","cleared",""],["5.","Oncology Exchange","SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["6.","DirectSetup Notes","SW","enabled","","","n.a.","","cleared",""]],"caption_candidate":"(SOMATOM X. Platform) with software version SOMARIS/10 syngo CT VB20 compared to the predicate devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p12-t0","doc_id":"K253574","page_num":12,"bbox":[72.26,95.52,523.05,613.92],"n_rows":12,"n_cols":10,"columns":["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],"rows":[["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],["","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB20","SOMATOM X.","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB10\n(K233650)","SOMATOM go.",""],["","","","","Platform","","","","Platform",""],["","","","","with syngo CT","","","","with syngo CT",""],["","","","","VB20","","","","VB20",""],["","","","","","","","","(K250822)",""],["","","","(same as in\nK250822)","","","","","",""],["7.","FAST Planning","SW","enabled3\n(same as in\nK250822)","","","cleared","","cleared",""],["8.","myExam\nCompanion –\nmyExam\nCompass/myExam\nCockpit","SW","enabled4\n(same as in\nK250822)","","","cleared","","cleared",""],["9.","HD FoV 5.0","SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["10.","CT guided\nintervention –\nmyAblation Guide\ninterface","SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["11.","Flex 4D Spiral","SW","modified\n(same as in\nK233650, with\nexception of the\nmodifications\nregarding scan\nrange and cycle\ntime which are","","","cleared","","cleared",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p13-t0","doc_id":"K253574","page_num":13,"bbox":[72.27,95.52,523.04,413.04],"n_rows":10,"n_cols":10,"columns":["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],"rows":[["","Technological\nproperty","HW/SW\nchange","","Subject devices","","","Predicate devices","",""],["","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB20","SOMATOM X.","","","SOMATOM X.\nPlatform\nwith syngo CT\nVB10\n(K233650)","SOMATOM go.",""],["","","","","Platform","","","","Platform",""],["","","","","with syngo CT","","","","with syngo CT",""],["","","","","VB20","","","","VB20",""],["","","","","","","","","(K250822)",""],["","","","introduced with\nsyngo CT VB20)","","","","","",""],["12.","ZeeFree RT","SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""],["13.","Direct Density","SW","enabled5\n(same as in\nK250822)","","","cleared","","cleared",""],["14.","myExam Contrast","SW","enabled\n(same as in\nK250822)","","","n.a.","","cleared",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p14-t0","doc_id":"K253574","page_num":14,"bbox":[72.25,123.48,523.07,767.88],"n_rows":19,"n_cols":12,"columns":["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT\nVB20","","","","","","","Primary predicate device\nSOMATOM X. Platform s\nwith SOMARIS/10 syngo CT\nVB10\n(K233650)\nSOMATOM SOMATOM\nX.cite X.ceed","","","Assessment of the"],"rows":[["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT\nVB20","","","","","","","Primary predicate device\nSOMATOM X. Platform s\nwith SOMARIS/10 syngo CT\nVB10\n(K233650)\nSOMATOM SOMATOM\nX.cite X.ceed","","","Assessment of the"],["","","","","","","","","","","","ubstantial"],["","","","","","","","","","","","equivalency (SE)"],["","","SOMATOM","","","SOMATOM","","","SOMATOM","","",""],["","","X.cite","","","X.ceed","","","X.cite","","",""],["scanner","Whole body Computed\nTomography (CT) Scanner\nSystem","","","","","","Whole body Computed S\nTomography (CT) Scanner\nSystem","","","","ame as the primary\npredicate devices"],["System\nConfiguration","Single Source","","","","","","Single Source S","","","","ame as the primary\npredicate devices"],["Environment\nof Use","Professional Healthcare Facility","","","","","","Professional Healthcare Facility S","","","","ame as the primary\npredicate devices"],["Generator\nMax. power\n(kW)","90 kW or 105\nkW","","","105 kW or 120\nkW","","","90 kW or 105\nkW","","","105 kW or 120 S\nkW","ame as the primary\npredicate devices"],["Detector\ntechnology","StellarInfinity","","","","","","StellarInfinity S","","","","ame as the primary\npredicate devices"],["Detector\nvolume\ncoverage","38.4 mm","","","","","","38.4 mm S","","","","ame as the primary\npredicate devices"],["Detector\nphysical rows","64","","","","","","64 S","","","","ame as the primary\npredicate devices"],["Detector\nSlice width","0.6 mm","","","","","","0.6 mm S","","","","ame as the primary\npredicate devices"],["Detector\nDAS channel\nno.","840","","","920","","","840","","","920 S","ame as the primary\npredicate devices"],["Detector\nImage slices","128","","","","","","128 S","","","","ame as the primary\npredicate devices"],["Tube\ntechnology","Vectron","","","","","","Vectron S","","","","ame as the primary\npredicate devices"],["Tube\nkV steps","70–140 kV in 10 kV steps","","","","","","70–140 kV in 10 kV steps S","","","","ame as the primary\npredicate devices"],["Tube\nMax. current","1100 mA (for\n90 kW)\n1200 mA (for\n105 kW)","","","1200 mA (for\n90 kW)\n1300 mA (for\n105 kW)","","","1100 mA (for\n90 kW)\n1200 mA (for\n105 kW)","","","1200 mA (for S\n90 kW)\n1300 mA (for\n105 kW)","ame as the primary\npredicate devices"],["Tube","• 0.6 x 0.7 / 8°","","","• 0.4 x 0.5 / 8°","","","• 0.6 x 0.7 / 8°","","","• 0.4 x 0.5 / 8° S","ame as the primary\npredicate devices"]],"caption_candidate":"with software version syngo CT VB20 and the primary predicate devices with software version syngo CT VB10 (K233650).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p18-t0","doc_id":"K253574","page_num":18,"bbox":[72.31,95.52,523.03,419.84],"n_rows":6,"n_cols":12,"columns":["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT\nVB20","","","","","","","Primary predicate device As\nSOMATOM X. Platform su\neq\nwith SOMARIS/10 syngo CT\nVB10\n(K233650)\nSOMATOM SOMATOM\nX.cite X.ceed","","","sessment of the"],"rows":[["Hardware\nproperty","Subject device\nSOMATOM X. Platform\nwith SOMARIS/10 syngo CT\nVB20","","","","","","","Primary predicate device As\nSOMATOM X. Platform su\neq\nwith SOMARIS/10 syngo CT\nVB10\n(K233650)\nSOMATOM SOMATOM\nX.cite X.ceed","","","sessment of the"],["","","","","","","","","","","","bstantial"],["","","","","","","","","","","","uivalency (SE)"],["","","SOMATOM","","","SOMATOM","","","SOMATOM","","",""],["","","X.cite","","","X.ceed","","","X.cite","","",""],["","• Open Online interface","","","","","","br\nth\nin\nco\npa\nga\nof\nIn\nO\nin\nO\nin\nfo\npr\nSO\nPl\nCT","","","","eathing signal of\ne patient,\nterfaces for\nnnecting of 3rd\nrty respiratory\nting devices are\nfered.\ntroduction of new\npen Online\nterface.\npen Online\nterface is cleared\nr the secondary\nedicate devices\nMATOM go.\natform with syngo\nVB20 in K250822."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p18-t1","doc_id":"K253574","page_num":18,"bbox":[72.31,493.26,523.03,750.94],"n_rows":8,"n_cols":8,"columns":["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate","Assessment of\nthe substantial\nequivalency\n(SE)"],"rows":[["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate","Assessment of\nthe substantial\nequivalency\n(SE)"],["","","","device","","","device",""],["","SOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10\nsyngo CT VB20","","SOMATOM X.cite","","","SOMATOM go.",""],["","","","SOMATOM X.ceed","","","Platform",""],["","","","with SOMARIS/10","","","with SOMARIS/10",""],["","","","syngo CT VB10","","","syngo CT VB20",""],["","","","(K233650)","","","(K250822)",""],["Operating\nSystem","Windows based\nSOMARIS/10 syngo\nCT VB20\nNote: the short\nversion syngo CT\nVB20 is also used as\nlabeling information","Windows based\nSOMARIS/10 syngo\nCT VB10\nNote: the short\nversion syngo CT\nVB10 is also used as\nlabeling information","","","Windows based\nSOMARIS/10 syngo\nCT VB20\nNote: the short\nversion syngo CT\nVB20 is also used as\nlabeling information","","Software\nversion\nupgraded due\nto new\nfunctionalities.\nSame as in the\nsecondary\npredicate\ndevice"]],"caption_candidate":"with software version syngo CT VB20 and the primary predicate devices with software version syngo CT VB10 (K233650).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p20-t0","doc_id":"K253574","page_num":20,"bbox":[72.28,95.52,523.04,760.56],"n_rows":9,"n_cols":8,"columns":["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate","Assessment of\nthe substantial\nequivalency\n(SE)"],"rows":[["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate","Assessment of\nthe substantial\nequivalency\n(SE)"],["","","","device","","","device",""],["","SOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10\nsyngo CT VB20","","SOMATOM X.cite","","","SOMATOM go.",""],["","","","SOMATOM X.ceed","","","Platform",""],["","","","with SOMARIS/10","","","with SOMARIS/10",""],["","","","syngo CT VB10","","","syngo CT VB20",""],["","","","(K233650)","","","(K250822)",""],["","• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy\nacquisition\n(TwinBeam DE\nand TwinSpiral\nDE)\n• Dynamic imaging\n(Flex 4D Spiral)\n• Protocols\nsupporting CT\nIntervention (scan\nmodes: 2D i-\nsequence, 3D i-\nsequence, i-spiral,\ni-Fluoro)\n• Protocols\nsupporting\nCardiac Scanning\n• Protocols for\nDirectBreathhold","• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy\nacquisition\n(TwinBeam DE\nand TwinSpiral\nDE)\n• Dynamic imaging\n(Flex 4D Spiral)\n• Protocols\nsupporting CT\nIntervention (scan\nmodes: 2D i-\nsequence, 3D i-\nsequence, i-spiral,\ni-Fluoro)\n• Protocols\nsupporting\nCardiac Scanning\n• Protocols for\nDirectBreathhold","","","respiratory gating\nsystem\n• Protocol\nsupporting\ncontrast bolus-\ntriggered data\nacquisition\n• Contrast media\nprotocols\n(including\ncoronary CTA)\n• Pediatric\nProtocols\n• Flex Dose Profile\n• Turbo Flash Spiral\n• Dual Energy\nacquisition\n(TwinBeam DE\nand TwinSpiral\nDE)\n• Dynamic imaging\n(Flex 4D Spiral)\n• Protocols\nsupporting CT\nIntervention (scan\nmodes: 2D i-\nsequence, 3D i-\nsequence, i-spiral,\ni-Fluoro)\n• Protocols\nsupporting\nCardiac Scanning\n• Protocols for\nDirectBreathhold","",""],["Advanced\nReconstruction","Recon&GO:\n- Spectral Recon\n(Dual Energy\nReconstruction\nincluding Virtual\nUnenhanced,\nMonoenergetic plus","Recon&GO:\n- Spectral Recon\n(Dual Energy\nReconstruction\nincluding Virtual\nUnenhanced,\nMonoenergetic plus","","","Recon&GO:\n- Spectral Recon\n(Dual Energy\nReconstruction\nincluding Virtual\nUnenhanced,\nMonoenergetic plus","","Same as the\nprimary and\nsecondary\npredicate\ndevices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p21-t0","doc_id":"K253574","page_num":21,"bbox":[72.29,95.52,523.05,767.73],"n_rows":10,"n_cols":8,"columns":["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate\ndevice","Assessment of\nthe substantial\nequivalency\n(SE)"],"rows":[["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate\ndevice","Assessment of\nthe substantial\nequivalency\n(SE)"],["","","","device","","","",""],["","SOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10\nsyngo CT VB20","","SOMATOM X.cite","","","SOMATOM go.\nPlatform\nwith SOMARIS/10\nsyngo CT VB20\n(K250822)",""],["","","","SOMATOM X.ceed","","","",""],["","","","with SOMARIS/10","","","",""],["","","","syngo CT VB10","","","",""],["","","","(K233650)","","","",""],["","- Inline Results DE\nSPP (Spectral Post-\nProcessing with\nphoton-counting\nimage data)\n- Inline Anatomical\nranges\n(Parallel/Radial) incl.\nVirtual Unenhanced,\nMonoenergetic plus\n- Inline Spine and Rib\nRanges\n- Inline table and\nbone removal","- Inline Results DE\nSPP (Spectral Post-\nProcessing with\nphoton-counting\nimage data)\n- Inline Anatomical\nranges\n(Parallel/Radial) incl.\nVirtual Unenhanced,\nMonoenergetic plus\n- Inline Spine and Rib\nRanges\n- Inline table and\nbone removal","","","- Inline Results DE\nSPP (Spectral Post-\nProcessing with\nphoton-counting\nimage data)\n- Inline Anatomical\nranges\n(Parallel/Radial) incl.\nVirtual Unenhanced,\nMonoenergetic plus\n- Inline Spine and Rib\nRanges\n- Inline table and\nbone removal","",""],["Image viewing","CT View&GO offers:\n- basic post-\nprocessing viewer (CT\nView&GO)\n- 2D and 3D (MPR,\nVRT, MIP and minIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive Spectral\nImaging (ISI)\n- Basic visualization\ntools: Endo View\n- Basic manipulation\ntools: DE ROI, ROI\nHU, Average","CT View&GO offers:\n- basic post-\nprocessing viewer (CT\nView&GO)\n- 2D and 3D (MPR,\nVRT, MIP and minIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive Spectral\nImaging (ISI)\n- Basic visualization\ntools: Endo View\n- Basic manipulation\ntools: DE ROI, ROI\nHU, Average","","","CT View&GO offers:\n- basic post-\nprocessing viewer (CT\nView&GO)\n- 2D and 3D (MPR,\nVRT, MIP and minIP)\n- Evaluation tools,\nFilming, Printing\n- Interactive Spectral\nImaging (ISI)\n- Basic visualization\ntools: Endo View\n- Basic manipulation\ntools: DE ROI, ROI\nHU, Average","","Same as the\nprimary and\nsecondary\npredicate\ndevices"],["Software\ninterface","• Recon&GO Inline\nResults\nSoftware interface to\npost-processing\nalgorithms which are\nunmodified when\nloaded onto the CT\nscanners and 510(k)","• Recon&GO Inline\nResults\nSoftware interface to\npost-processing\nalgorithms which are\nunmodified when\nloaded onto the CT\nscanners and 510(k)\ncleared as medical","","","• Recon&GO Inline\nResults\nSoftware interface to\npost-processing\nalgorithms which are\nunmodified when\nloaded onto the CT\nscanners and 510(k)","","Same as the\nsecondary\npredicate\ndevices\nIn software\nversion syngo\nCT VB20, the\nsubject devices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p23-t0","doc_id":"K253574","page_num":23,"bbox":[72.28,95.52,523.05,749.76],"n_rows":12,"n_cols":8,"columns":["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate\ndevice","Assessment of\nthe substantial\nequivalency\n(SE)"],"rows":[["Software\nproperty","Subject device","","Primary predicate","","","Secondary predicate\ndevice","Assessment of\nthe substantial\nequivalency\n(SE)"],["","","","device","","","",""],["","SOMATOM X.cite\nSOMATOM X.ceed\nwith SOMARIS/10\nsyngo CT VB20","","SOMATOM X.cite","","","SOMATOM go.\nPlatform\nwith SOMARIS/10\nsyngo CT VB20\n(K250822)",""],["","","","SOMATOM X.ceed","","","",""],["","","","with SOMARIS/10","","","",""],["","","","syngo CT VB10","","","",""],["","","","(K233650)","","","",""],["Cybersecurity","IT Hardening","IT Hardening","","","IT Hardening","","Same as the\nprimary and\nsecondary\npredicate\ndevices"],["HD FoV","HD FoV 4.0\nHD FoV 5.0","HD FoV 4.0","","","HD FoV 4.0\nHD FoV 5.0","","Same as the\nsecondary\npredicate\ndevices\nIn addition to\nHD FoV 4.0, the\nsubject devices\nSOMATOM X.\nPlatform with\nsyngo CT VB20\nsupport a new\ngeneration of\nextended field\nof view\nreconstruction\nalgorithm: HD\nFoV 5.0."],["Standard\ntechnologies","FAST technologies\nCARE technologies\nGO technologies","FAST technologies\nCARE technologies\nGO technologies","","","FAST technologies\nCARE technologies\nGO technologies","","Same as the\nprimary and\nsecondary\npredicate\ndevices"],["Iterative\nReconstruction\nMethods","ADMIRE\niMAR","ADMIRE\niMAR","","","ADMIRE\niMAR\nSAFIRE","","Same as the\nprimary\npredicate\ndevices"],["Matrix sizes","256 x 256 pixels\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels\n(Precision Matrix)","256 x 256 pixels\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels\n(Precision Matrix)","","","256 x 256 pixels\n512 x 512 pixels\n768 x 768 pixels\n1024 x 1024 pixels\n(Precision Matrix)","","Same as the\nprimary and\nsecondary\npredicate\ndevices"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p24-t0","doc_id":"K253574","page_num":24,"bbox":[151.32,266.64,232.0,291.12],"n_rows":2,"n_cols":2,"columns":["","stopping power"],"rows":[["","stopping power"],["ratio",""]],"caption_candidate":"relative mass density, relative mass density relative mass density, predicate","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p28-t0","doc_id":"K253574","page_num":28,"bbox":[72.28,337.92,523.04,769.44],"n_rows":5,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["FAST 3D Camera/\nFAST Integrated\nWorkflow","","","The FAST 3D camera sub-features FAST Isocentering, FAST Range, and\nFAST Direction have been optimized using additional data from adults\nand adolescence patients. The bench test evaluates and compares the\naccuracy of the three sub-features in software version syngo CT VB20 to\nthe accuracy of the predicate devices with syngo CT VB10.\nThe objectives of the bench tests are to demonstrate that the FAST 3D\ncamera achieves comparable or better results for both, adults and\nadolescents, as the predicate device for adults.\nOverall, the subject devices with syngo CT VB20 delivers comparable or\nimproved accuracy to the predicate devices with syngo CT VB10\npredicate device for adults and extends the support to adolescents."],["FAST Planning","","","The purpose of the test is to provide a clear reporting on the applied\nalgorithm, its product development, validation, and verification on\npatient data, which enable the claims.\nObjective of the test is to assess the fraction (percentage) of ranges\ncalculated by the FAST Planning algorithm that are correct and can be\napplied without change. Additionally, calculation time was measured to\ncheck whether it meets interactive requirements.\nThe test results show that the editing actions for the scanner technician\ncan be reduced to a minimum and that the calculation time is fast\nenough for interactive speed during scanning. For more than 90% of the\nranges no editing action was necessary to cover standard ranges. For\nmore than 95%, the speed of the algorithm was sufficient."],["HD FoV 5.0","","","The bench test contains a detailed description and evaluation of the new\nHD FoV 5. 0 algorithm for extended field of view reconstruction. Results"]],"caption_candidate":"Table 6: Non-clinical performance testing (bench testing).","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p29-t0","doc_id":"K253574","page_num":29,"bbox":[72.28,95.52,523.04,746.52],"n_rows":5,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","obtained with the new HD FoV 5. 0 algorithm are compared with its\npredecessor, the HD FoV 4. 0 algorithm, based on physical and\nanthropomorphic phantoms.\nIn addition to the bench test, the performance of the algorithm was\nevaluated by board-approved radio-oncologists and medical physicists by\nmeans of retrospective blinded rater study.\nThis comparison is conducted to demonstrate that the HD FoV 5. 0\nalgorithm is as safe and effective as the HD FoV 4. 0 algorithm."],["Flex 4D Spiral","","","The performed bench test report describes the technical background of\nFlex 4D Spiral and its functionalities with SOMATOM CT scanners,\ndemonstrate the proper function of those, and assess the image quality\nof Flex 4D Spiral."],["ZeeFree RT","","","The bench test evaluates the performance of the ZeeFree RT\nreconstruction. The objectives of the tests are to demonstrate that\ncompared to the Standard reconstruction, ZeeFree RT\n• introduces no relevant errors in terms of CT values and noise\nlevels measured in a homogeneous water phantom, and\n• introduces no relevant errors in terms of CT values measured in\na phantom with tissue-equivalent inserts, even in the presence\nof metals and in combination with the iMAR algorithm, and\n• introduces no relevant geometrical distortions in a static torso\nphantom, and\n• introduces no relevant deteriorations of the position or shape of\na dynamic thorax phantom when moving a spherical shape\naccording to regular, irregular, and patient breathing motion.\nIn addition, the performance of the algorithm was evaluated by board-\napproved radio-oncologists by means of a retrospective blinded rater\nstudy on 30 patient cases of respiratory 4D CT examinations.\nThe test results show that the ZeeFree RT reconstruction\n• can successfully be applied to 4D respiratory-gated sequence\nimages (Direct i4D), and\n• enables the optional reconstruction of stack artefact corrected\nimages, which reduce the strength of misalignment artefacts, if\nsuch stack alignment artefacts are identified in non-corrected\nstandard images, and\n• does not introduce relevant new artefacts, which were\npreviously not present in the non-corrected standard\nreconstruction, and"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p30-t0","doc_id":"K253574","page_num":30,"bbox":[72.28,95.52,523.04,482.88],"n_rows":4,"n_cols":4,"columns":["","Feature/Non-clinical","","Bench Testing performed"],"rows":[["","Feature/Non-clinical","","Bench Testing performed"],["","supportive testing","",""],["","","","• does not affect CT values and noise levels in a homogenous\nwater phantom outside of stack-transition areas compared to\nthe non-corrected standard reconstruction, and\n• can be successfully applied in combination with metal artifact\ncorrection (iMAR) and does not introduce new artifacts, which\nwere previously not present in the non-corrected standard\nreconstruction, even in presence of metals, and\n• can be successfully applied to phantom data if derived from a\nsuitable motion phantom demonstrating its correct technical\nfunction on the tested device, and\n• is independent from the physical detector width of the acquired\ndata. By design, input images for the correction part of the\nalgorithm are independent of kernel, slice thickness and\nincrement since those parameters are fixed."],["DirectDensity","","","The test results show for the iBHC variants Artificial120, eDDensity,\nmDDensity and StoppingPowerRatio a reduced dependence on tube\nvoltage and filtration compared to the corresponding quantitative kernel\n(Qr) with iBHC Bone for non-water-like tissues, such as adipose and\nbone. Furthermore, the iBHC variants Artificial120, eDDensity,\nmDDensity and StoppingPowerRatio generate image value closely\naligned with the respective material properties. In conclusion, the\nfeature DirectDensity at any kV has been validated for the release Som/X\nVB20 on all supported SOMATOM CT scanner models"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p30-t1","doc_id":"K253574","page_num":30,"bbox":[72.28,558.78,523.04,763.2],"n_rows":6,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/18/2023","12-352","NEMA","","","PS 3.1 - 3.20 2023e","","","Digital Imaging and\nCommunications in\nMedicine (DICOM) Set"],["07/06/2020","12-325","NEMA","","","XR 25-2019","","","Computed Tomography\nDose Check"],["07/06/2020","12-330","NEMA","","","XR 28-2018","","","Supplemental\nRequirements for User\nInformation and System\nFunction Related to Dose in\nCT"]],"caption_candidate":"Table 7: Recognized Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p31-t0","doc_id":"K253574","page_num":31,"bbox":[72.26,95.52,523.06,751.56],"n_rows":10,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/23/2019","12-328","IEC","","","61223-3-5 Edition\n2.0 2019-09","","","Evaluation and routine\ntesting in medical imaging\ndepartments - Part 3-5:\nAcceptance tests and\nconstancy tests - Imaging\nperformance of computed\ntomography X-ray\nequipment [Including:\nTechnical Corrigendum 1\n(2006)]"],["03/14/2011","12-226","IEC","","","61223-2-6 Second\nEdition 2006-11","","","Evaluation and routine\ntesting in medical imaging\ndepartments - Part 2-6:\nConstancy tests - Imaging\nperformance of computed\ntomography X-ray\nequipment"],["06/07/2021","12-336","IEC","","","60601-1-3 Edition\n2.2 2021-01\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-3:\nGeneral requirements for\nbasic safety and essential\nperformance – Collateral\nStandard: Radiation\nprotection in diagnostic X-\nray equipment"],["06/27/2016","12-302","IEC","","","60601-2-44 Edition\n3.2: 2016","","","Medical electrical\nequipment - Part 2-44:\nParticular requirements for\nthe basic safety and\nessential performance of x-\nray equipment for\ncomputed tomography"],["12/23/2019","5-125","ANSI AAMI\nISO","","","14971: 2019","","","Medical devices -\nApplications of risk\nmanagement to medical\ndevices"],["","","ISO","","","14971 Third Edition\n2019-12","","","Medical devices -\nApplication of risk\nmanagement to medical\ndevices"],["01/14/2019","13-79","ANSI AAMI\nIEC","","","62304:2006/A1:2016","","","Medical device software -\nSoftware life cycle"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p32-t0","doc_id":"K253574","page_num":32,"bbox":[72.26,95.52,523.06,755.16],"n_rows":11,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["","","","","","","","","processes [Including\nAmendment 1 (2016)]"],["","","IEC","","","62304 Edition 1.1\n2015-06\nCONSOLIDATED\nVERSION","","","Medical device software -\nSoftware life cycle\nprocesses"],["05/30/2022","19-46","ANSI AAMI","","","ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012\n(Cons. Text) [Incl.\nAMD2:2021]","","","Medical electrical\nequipment - Part 1:\nGeneral requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD) [Including\nAmendment 2 (2021)]"],["12/21/2020","19-36","ANSI AAMI\nIEC","","","60601-1-2:2014\n[Including AMD\n1:2021]","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements for\nbasic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances -\nRequirements and tests"],["","","IEC","","","60601-1-2 Edition\n4.1 2020-09\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-2:\nGeneral requirements for\nbasic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances -\nRequirements and tests"],["07/06/2020","5-129","ANSI AAMI\nIEC","","","62366-\n1:2015+AMD1:2020\n(Consolidated Text)","","","Medical devices Part 1:\nApplication of usability\nengineering to medical\ndevices, including\nAmendment 1"],["","","IEC","","","62366-1 Edition 1.1\n2020-06\nCONSOLIDATED\nVERSION","","","Medical devices - Part 1:\nApplication of usability\nengineering to medical\ndevices"],["07/09/2014","12-273","IEC","","","60825-1 Edition 2.0\n2007-03","","","Safety of laser products -\nPart 1: Equipment\nclassification, and\nrequirements"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p33-t0","doc_id":"K253574","page_num":33,"bbox":[72.28,95.52,523.04,389.88],"n_rows":6,"n_cols":9,"columns":["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],"rows":[["Date of Entry","Recognition\nNumber","","Standard","","","Standard","","Title of Standard"],["","","","Developing","","","Designation Number","",""],["","","","Organization","","","and Date","",""],["12/21/2020","5-132","IEC","","","60601-1-6 Edition\n3.2 2020-07\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Part 1-6:\nGeneral requirements for\nbasic safety and essential\nperformance - Collateral\nstandard: Usability"],["12/23/2019","12-309","IEC","","","60601-2-28 Edition\n3.0 2017-06","","","Medical electrical\nequipment - Part 2-28:\nParticular requirements for\nthe basic safety and\nessential performance of X-\nray tube assemblies for\nmedical diagnosis"],["12/20/2021","12-341","IEC","","","62563-1 Edition 1.2\n2021-07\nCONSOLIDATED\nVERSION","","","Medical electrical\nequipment - Medical image\ndisplay systems - Part 1:\nEvaluation methods"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p33-t1","doc_id":"K253574","page_num":33,"bbox":[72.28,465.84,523.04,758.4],"n_rows":6,"n_cols":6,"columns":["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard\nUsed"],"rows":[["","Standard","","Standard Designation\nNumber and Date","Title of Standard","How was Standard\nUsed"],["","Developing","","","",""],["","Organization","","","",""],["IEC","","","60601-\n1:2005+A1:2012+A2:2020","Medical electrical\nequipment - part 1:\ngeneral requirements for\nbasic safety and essential\nperformance","ANSI AAMI ES60601-\n1:2005/(R)2012 &\nA1:2012,\nC1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons.\nText) [Incl. AMD2:2021]"],["IEC/ISO","","","17050-1","Conformity Assessment –\nSupplier’s declaration of\nconformity – Part 1:\nGeneral requirements","Declaration of\nconformance to FDA\nrecognized consensus\nstandards."],["IEC/ISO","","","17050-2","Conformity assessment –\nSupplier’s declaration of\nconformity – Part 2:\nSupporting\ndocumentation.","General consensus\nstandards not currently\nrecognized by FDA."]],"caption_candidate":"Table 8: General Use Consensus Standards.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253574-p34-t0","doc_id":"K253574","page_num":34,"bbox":[72.26,151.32,523.07,531.24],"n_rows":14,"n_cols":4,"columns":["","FDA Guidance Document","Issue date",""],"rows":[["","FDA Guidance Document","Issue date",""],["User Fees and Refunds for Premarket Notification Submissions (510(k)s):\nGuidance for Industry and Food and Drug Administration Staff","","10/05/2022",""],["Refuse to Accept Policy for 510(k)s: Guidance for Industry and Food and Drug\nAdministration Staff","","04/21/2022",""],["Electronic Submission Template for Medical Device 510(k) Submissions","","10/2/2023",""],["Deciding When to Submit a 510(k) for a Change to an Existing Device","","10/25/2017",""],["The 510(k) Program: Evaluating Substantial Equivalence in Premarket\nNotifications [510(k)]","","07/28/2014",""],["Content of Premarket Submissions for Software Contained in Medical\nDevices","","06/14/2023",""],["Off-The-Shelf Software Use in Medical Devices","","08/11/2023",""],["Applying Human Factors and Usability Engineering to Medical Devices","","02/03/2016",""],["Pediatric Information for X-ray Imaging Device Premarket Notifications","","11/28/2017",""],["Cybersecurity in Medical Devices: Quality System Considerations and Content\nof Premarket Submissions","","06/27/2025",""],["Electromagnetic Compatibility (EMC) of Medical Devices","","06/06/2022",""],["Design Considerations and Pre-market Submission Recommendations for\nInteroperable Medical Devices","","09/06/2017",""],["Appropriate Use of Voluntary Consensus Standards in Premarket Submissions\nfor Medical Devices","","09/14/2018",""]],"caption_candidate":"Table 9: FDA Guidance Document and Effective Date","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p7-t0","doc_id":"K253578","page_num":7,"bbox":[63.5,315.5,531.5,800.5],"n_rows":2,"n_cols":3,"columns":["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],"rows":[["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],["Intended\nUse /\nIndication\ns for Use","BriefCase-Triage: CARE (Clinical AI\nReasoning Engine) Multi-Triage CT for\nPneumothorax; Pericardial effusion; Large\naortic aneurysm; Shoulder fracture or\ndislocation device is a radiological computer\naided triage and notification software\nindicated for use in the analysis of contrast\nand non-contrast CT images of the chest,\nabdomen, or chest/abdomen, in adults or\ntransitional adolescents aged 18 and older.\nThe device is intended to assist hospital\nnetworks and appropriately trained medical\nspecialists in workflow triage by flagging\nand communicating suspected positive\nfindings, per study, of:\n1. Pneumothorax;\n2. Pericardial effusion;\n3. Large aortic aneurysm\n4. Shoulder Fracture or Dislocation\nThe device flags cases with at least one\nsuspected finding to assist with\ntriage/prioritization of medical images. The\ndevice will provide a flag for each suspected","BriefCase-Triage is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the analysis\nof CT chest, abdomen, or chest/abdomen\nexams with contrast (CTA and CT with\ncontrast) in adults or transitional\nadolescents aged 18 and older. The\ndevice is intended to assist hospital\nnetworks and appropriately trained\nmedical specialists in workflow triage by\nflagging and communication of suspected\npositive findings of Aortic Dissection (AD)\npathology.\nBriefCase-Triage uses an artificial\nintelligence algorithm to analyze images\nand highlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images that\nare meant for informational purposes"]],"caption_candidate":"Table 1. Key Feature Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p8-t0","doc_id":"K253578","page_num":8,"bbox":[63.5,69.5,531.5,782.5],"n_rows":5,"n_cols":3,"columns":["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],"rows":[["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],["","finding within this study. A preview image\nwill be provided for each distinct suspected\nfinding.\nBriefCase-Triage uses a foundation\nmodel-based artificial intelligence (AI)\nsystem to analyze images and highlight\ncases with detected findings in parallel to\nthe ongoing standard of care image\ninterpretation. The user is presented with\nnotifications for cases with suspected\nfindings. Notifications include compressed\npreview images for each suspected finding\nthat are meant for informational purposes\nonly and not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical images and is not\nintended to be used as a diagnostic device.\nThe results of BriefCase-Triage are intended\nto be used in conjunction with other patient\ninformation and based on their professional\njudgment to assist with triage/prioritization\nof medical images. Notified clinicians are\nresponsible for viewing full images per the\nstandard of care.","only and not intended for diagnostic use\nbeyond notification. The device does not\nalter the original medical image and is\nnot intended to be used as a diagnostic\ndevice.\nThe results of BriefCase-Triage are\nintended to be used in conjunction with\nother patient information and based on\ntheir professional judgment, to assist\nwith triage/ prioritization."],["User\npopulatio\nn","Hospital networks and appropriately trained\nmedical specialists","Hospital networks and appropriately\ntrained medical specialists"],["Clinical\nIndication","1. Pneumothorax;\n2. Pericardial effusion;\n3. Large aortic aneurysm;\n4. Shoulder fracture or dislocation","1. Aortic Dissection"],["Anatomic\nal region\nof interest","Chest, abdomen, or chest/abdomen","Chest, abdomen, or chest/abdomen"]],"caption_candidate":"4 K253878","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p9-t0","doc_id":"K253578","page_num":9,"bbox":[63.5,69.5,531.5,795.5],"n_rows":6,"n_cols":3,"columns":["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],"rows":[["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],["Data\nacquisitio\nn protocol","Contrast and non-contrast CT images","CTA and CT with contrast"],["Notificatio\nn-only\n(/notificati\non alerts),\nparallel\nworkflow\ntool","Yes","Yes"],["Images\nformat","DICOM","DICOM"],["Interferen\nce with\nstandard\nworkflow","No. No cases are removed from\ndesktop app or deprioritized","No. No cases are removed from\ndesktop app or deprioritized"],["Inclusion/\nExclusion\ncriteria for\nclinical\nperforma\nnce\ntesting","Inclusion Criteria:\n● Patient population: CT scans\nperformed on adults/transitional\nadults ≥ 18 years of age\n● Slice thickness: 0.5 mm - 5.0 mm\naxial\n● Contrast-enhanced and\nnon-contrast CT images*\nExclusion Criteria\n● All studies that have an inadequate\nfield of view.\n*Contrast and non-contrast CT images of\nthe chest, abdomen, or chest/abdomen as\napplicable to indication-specific inclusion\ncriteria.","Inclusion Criteria\n● Scans performed on\nadults/transitional adolescents ≥\n18 years of age.\n● CT exams with contrast (CTA and\nCT with contrast) that include at\nleast part of the aorta\n● Slice thickness 0.5 mm - 5.0 mm\nExclusion Criteria\n● All studies that have an\ninadequate field of view."]],"caption_candidate":"5 K253878","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p10-t0","doc_id":"K253578","page_num":10,"bbox":[63.5,69.5,531.5,436.5],"n_rows":4,"n_cols":3,"columns":["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],"rows":[["","Subject Device\nAidoc’s BriefCase-Triage: CARE Multi-Triage\nCT for Pneumothorax; Pericardial effusion;\nLarge aortic aneurysm; Shoulder fracture\nor dislocation","Predicate Device\nAidoc’s Briefcase-Triage for AD\n(K251406)"],["Additional\nOperating\nPoints","4 Additional Operating Points","4 Additional Operating Points"],["Algorithm","Multi-triage module, locked artificial\nintelligence algorithm fine tuned from a\nfoundation model.","Single-triage module, locked, artificial\nintelligence algorithm fine tuned from a\nfoundation model."],["Structure","- Integrated with image routing module via\nimage communication platform (ICP) (image\nacquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application for\nworkflow integration (feed and\nnon-diagnostic Image Viewer).","- Integrated with image routing module\nvia image communication platform (ICP)\n(image acquisition).\n- Algorithm module (image processing)\n- Integrated with desktop application\nfor workflow integration (feed and\nnon-diagnostic Image Viewer)."]],"caption_candidate":"6 K253878","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p11-t0","doc_id":"K253578","page_num":11,"bbox":[36.1,234.31,503.3,522.5],"n_rows":16,"n_cols":9,"columns":["Indication 1: Pneumothorax","","","","","","","",""],"rows":[["Indication 1: Pneumothorax","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["98.9","97.8-99.7","94.8%","89.5%-97.9%","95.9%","91.3%-98.5%","280","134","146"],["Indication 2: Pericardial effusion","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.1","98.0-99.8","96.4%","91.7%-98.8%","96.5%","92.0%-98.8%","280","138","142"],["Indication 3: Large aortic aneurysm","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.5","98.9-99.9","97.1%","92.7%-99.2%","97.2%","92.9%-99.2%","280","138","142"],["Indication 4: Shoulder fracture or dislocation","","","","","","","",""],["AUC","","Sensitivity (Se)","","Specificity (Sp)","","Case Count","",""],["AUC","95% CI","Se","95% CI","Sp","95% CI","Total","Positiv\ne","Negat\nive"],["99.9","99.7-100","97.8%","93.7%-99.5%","99.3%","96.2%-100.0%","280","136","144"]],"caption_candidate":"Table 2. AUC, Sensitivity, Specificity","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p12-t0","doc_id":"K253578","page_num":12,"bbox":[75.13,126.08,519.17,345.73],"n_rows":3,"n_cols":7,"columns":["Time-to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],"rows":[["Time-to-notification","Mean\nEstimate\n(seconds)","N","95% Lower\nCL","95% Upper\nCL","Median","IQR"],["Predicate K251406\nProcessing Time","10.7","212","10.5","10.9","10.4","0.4"],["BriefCase-Triage and\ncompatible image\ncommunication\nplatform\nTime-to-notification","49.9","536","46.4","53.5","38.8","33.1"]],"caption_candidate":"Table 3. Time-to- notification comparison for Briefcase-Triage devices (Seconds)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p12-t1","doc_id":"K253578","page_num":12,"bbox":[114.72,492.51,479.28,759.51],"n_rows":16,"n_cols":6,"columns":["Indication 1: Pneumothorax","","","","",""],"rows":[["Indication 1: Pneumothorax","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["60.4","18.6","18","65","90","280"],["Indication 2: Pericardial effusion","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["61.2","17.7","18","64","90","280"],["Indication 3: Large aortic aneurysm","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["66.6","17.2","18","71","90","280"],["Indication 4: Shoulder fracture or dislocation","","","","",""],["Age (Years)","","","","",""],["Mean","Std","Min","Median","Max","N"],["61.5","17.3","18","65","90","280"]],"caption_candidate":"Table 4. Descriptive Statistics for Age","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p13-t0","doc_id":"K253578","page_num":13,"bbox":[87.1,94.48,507.1,595.5],"n_rows":28,"n_cols":7,"columns":["Indication 1: Pneumothorax\n*5 cases were unknown for gender, 4 positive and 1 negative","","","","","",""],"rows":[["Indication 1: Pneumothorax\n*5 cases were unknown for gender, 4 positive and 1 negative","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","47","17.1%","83","30.2%","130","47.3%"],["Negative","80","29.1%","65","23.6%","145","52.7%"],["All","127","46.2%","148","53.8%","275","100.0%"],["Indication 2: Pericardial effusion","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","76","27.1%","62","22.1%","138","49.3%"],["Negative","80","28.6%","62","22.1%","142","50.7%"],["All","156","55.7%","124","44.3%","280","100.0%"],["Indication 3: Large aortic aneurysm","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","42","15.0%","96","34.3%","138","49.3%"],["Negative","82","29.3%","60","21.4%","142","50.7%"],["All","124","44.3%","156","55.7%","280","100.0%"],["Indication 4: Shoulder fracture or dislocation\n*8 cases were unknown for gender, all positive","","","","","",""],["Gender","","","","","",""],["Ground\nTruth\nResults","Female","","Male","","All",""],["","N","%","N","%","N","%"],["Positive","48","17.6%","80","29.4%","128","47.1%"],["Negative","76","27.9%","68","25.0%","144","52.9%"],["All","124","45.6%","148","54.4%","272","100%"]],"caption_candidate":"Table 5. Descriptive Statistics for Gender","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p13-t1","doc_id":"K253578","page_num":13,"bbox":[184.5,636.33,409.5,790.5],"n_rows":10,"n_cols":3,"columns":["Indication 1: Pneumothorax","",""],"rows":[["Indication 1: Pneumothorax","",""],["Manufacturer","N","%"],["GE MEDICAL SYSTEMS","80","28.6%"],["Philips","68","24.3%"],["SIEMENS","69","24.6%"],["TOSHIBA","63","22.5%"],["Total","280","100%"],["Indication 2: Pericardial effusion","",""],["Manufacturer","N","%"],["GE MEDICAL SYSTEMS","100","35.70%"]],"caption_candidate":"Table 6. Frequency Distribution of Manufacturer","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p14-t0","doc_id":"K253578","page_num":14,"bbox":[184.5,69.5,409.5,353.5],"n_rows":18,"n_cols":3,"columns":["Philips","63","22.5%"],"rows":[["Philips","63","22.5%"],["SIEMENS","60","21.4%"],["TOSHIBA","57","20.4%"],["Total","280","100%"],["Indication 3: Large aortic aneurysm","",""],["Manufacturer","N","%"],["GE MEDICAL SYSTEMS","95","33.90%"],["Philips","63","22.5%"],["SIEMENS","66","23.60%"],["TOSHIBA","56","20.0%"],["Total","280","100"],["Indication 4: Shoulder fracture or dislocation","",""],["Manufacturer","N","%"],["GE MEDICAL SYSTEMS","92","32.9%"],["Philips","58","20.7%"],["SIEMENS","66","23.6%"],["TOSHIBA","64","22.9%"],["Total","280","100%"]],"caption_candidate":"10 K253878","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p14-t1","doc_id":"K253578","page_num":14,"bbox":[184.5,394.61,409.5,793.92],"n_rows":24,"n_cols":3,"columns":["Indication 1: Pneumothorax","",""],"rows":[["Indication 1: Pneumothorax","",""],["Slice Thickness (mm)","N","%"],["0.5-1","67","23.9%"],["1-2.5","71","25.4%"],["2.5-5","142","50.7%"],["Total","280","100%"],["Indication 2: Pericardial effusion","",""],["Slice Thickness (mm)","N","%"],["0.5-1","56","20.0%"],["1-2.5","91","32.5%"],["2.5-5","133","47.5%"],["Total","280","100%"],["Indication 3: Large aortic aneurysm","",""],["Slice Thickness (mm)","N","%"],["0.5-1","63","22.5%"],["1-2.5","84","30.0%"],["2.5-5","133","47.5%"],["Total","280","100%"],["Indication 4: Shoulder fracture or dislocation","",""],["Slice Thickness (mm)","N","%"],["0.5-1","85","30.4%"],["1-2.5","73","26.1%"],["2.5-5","122","43.6%"],["Total","280","100%"]],"caption_candidate":"Table 7. Frequency Distribution of Slice Thickness","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p15-t0","doc_id":"K253578","page_num":15,"bbox":[168.05,311.57,426.05,793.5],"n_rows":33,"n_cols":4,"columns":["Indication 1: Pneumothorax","","",""],"rows":[["Indication 1: Pneumothorax","","",""],["AOP1","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["98.5%","94.7%-99.8%","89.0%","82.8%-93.6%"],["AOP2","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["97.8%","93.6%-99.5%","93.2%","87.8%-96.7%"],["AOP3","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["90.3%","84.0%-94.7%","97.3%","93.1%-99.2%"],["AOP4","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["88.8%","82.2%-93.6%","98.6%","95.1%-99.8%"],["Indication 2: Pericardial effusion","","",""],["AOP1","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["97.1%","92.7%-99.2%","89.4%","83.2%-94.0%"],["AOP2","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["95.7%","90.8%-98.4%","97.2%","92.9%-99.2%"],["AOP3","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["94.2%","88.9%-97.5%","99.3%","96.1%-100.0%"],["AOP4","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"]],"caption_candidate":"Table 8. Sensitivity, Specificity for AOP1-AOP4","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253578-p16-t0","doc_id":"K253578","page_num":16,"bbox":[168.05,69.5,426.05,584.5],"n_rows":35,"n_cols":4,"columns":["91.3%","85.3%-95.4%","100.0%","97.4%-100.0%"],"rows":[["91.3%","85.3%-95.4%","100.0%","97.4%-100.0%"],["Indication 3: Large aortic aneurysm","","",""],["AOP1","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["97.8%","93.8%-99.5%","92.3%","86.6%-96.1%"],["AOP2","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["96.4%","91.7%-98.8%","98.6%","95.0%-99.8%"],["AOP3","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["94.9%","89.8%-97.9%","99.3%","96.1%-100.0%"],["AOP4","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["87.7%","81.0%-92.7%","99.3%","96.1%-100.0%"],["Indication 4: Shoulder fracture or dislocation","","",""],["AOP1","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["100.0%","97.3%-100.0%","95.1%","90.2%-98.0%"],["AOP2","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["99.3%","96.0%-100.0%","95.8%","91.2%-98.5%"],["AOP3","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["92.6%","86.9%-96.4%","100.0%","97.5%-100.0%"],["AOP4","","",""],["Sensitivity (Se)","","Specificity (Sp)",""],["Se","95% CI","Sp","95% CI"],["89.0%","82.5%-93.7%","100.0%","97.5%-100.0%"]],"caption_candidate":"12 K253878","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253584-p6-t0","doc_id":"K253584","page_num":6,"bbox":[89.02,287.19,421.94,455.86],"n_rows":10,"n_cols":6,"columns":["Trade Name","","","","Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6",""],"rows":[["Trade Name","","","","Alphenix, INFX-8000V/B, INFX-8000V/S, V9.6",""],["","","","","with αEvolve Imaging",""],["","Marketed by","","","Canon Medical Systems USA, Inc.",""],["","510(k) Number","","","K251602",""],["","Clearance Date","","","October 10, 2025",""],["Common Name","","","Interventional Fluoroscopic X-ray System","",""],["","Classification Name","","","Image-Intensified Fluoroscopic X-ray System",""],["Regulation Number","","","21 CFR 892.1650","",""],["Regulation Class","","","Class II","",""],["","Product Code","","","OWB",""]],"caption_candidate":"13. PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253584-p7-t0","doc_id":"K253584","page_num":7,"bbox":[83.61,322.97,529.85,432.31],"n_rows":6,"n_cols":9,"columns":["","","","","Predicate Device","","","Subject Device",""],"rows":[["","","","","Predicate Device","","","Subject Device",""],["Device Name, Model\nNumber","Device Name, Model","","","Alphenix, INFX-8000V/B,","","","Alphenix, INFX-8000V/B, INFX-8000V/S,",""],["","Number","","","INFX-8000V/S, V9.6 with","","","V9.6 with αEvolve Imaging (FOV",""],["","","","","αEvolve Imaging","","","Extension)",""],["","510(k) Number","","","K251602","","","This submission",""],["FOV of αEvolve\nImaging","","","8-inch, 6-inch (non-binning)","","","12-inch, 10inch (binning)\n8-inch, 6-inch (non-binning)\n3-inch (hi-def, non-binning)","",""]],"caption_candidate":"technological characteristics between the subject and the predicate device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p3-t0","doc_id":"K253593","page_num":3,"bbox":[257.81,320.45,570.36,417.07],"n_rows":7,"n_cols":2,"columns":["Jessica Lamb, Ph.D.",""],"rows":[["Jessica Lamb, Ph.D.",""],["Assistant Director",""],["Imaging Software Team",""],["","DHT8B: Division of Radiological Imaging Devices and"],["","Electronic Products"],["OHT8: Office of Radiological Health",""],["Office of Product Evaluation and Quality",""]],"caption_candidate":"Sincerely,","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p5-t0","doc_id":"K253593","page_num":5,"bbox":[72.31,244.32,539.75,272.04],"n_rows":2,"n_cols":8,"columns":["","Regulation Number","","Regulation Name","","","Product Code",""],"rows":[["","Regulation Number","","Regulation Name","","","Product Code",""],["21 CFR § 892.2050","","Medical Image Management and Processing System","","","QIH","",""]],"caption_candidate":"Regulation Number, Name and Product Code:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p5-t1","doc_id":"K253593","page_num":5,"bbox":[72.31,503.36,539.75,628.0],"n_rows":8,"n_cols":4,"columns":["Device Trade Name:","","","Caption Interpretation Automated Ejection Fraction\nSoftware"],"rows":[["Device Trade Name:","","","Caption Interpretation Automated Ejection Fraction\nSoftware"],["","510(k) Reference:","","K210747"],["","Manufacturer Name:","","Caption Health, Inc."],["","Regulation Name:","","Medical Image Management and Processing System"],["","Device Classification Name:","","Automated Radiological Image Processing Software"],["","Primary Product Code:","","QIH"],["","Regulation Number:","","21 CFR § 892.2050"],["","Regulatory Class:","","Class II"]],"caption_candidate":"Predicate Device Information:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p6-t0","doc_id":"K253593","page_num":6,"bbox":[72.05,485.36,540.24,526.51],"n_rows":2,"n_cols":4,"columns":["","Clarius Ultrasound Transducers","","PA HD3; PAL HD3; C3 HD3"],"rows":[["","Clarius Ultrasound Transducers","","PA HD3; PAL HD3; C3 HD3"],["Clarius App Software","","","Clarius Ultrasound App (Clarius App) for iOS;\nClarius Ultrasound App (Clarius App) for Android"]],"caption_candidate":"cleared in K213436 and K232704). Clarius Ejection Fraction AI is not a stand-alone software device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p8-t0","doc_id":"K253593","page_num":8,"bbox":[72.32,97.79,674.39,535.89],"n_rows":13,"n_cols":10,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],["","","","","","","","","",""],["Device Trade Name","","","Clarius Ejection Fraction AI","","","","Caption Interpretation","",""],["","","","","","","","Automated Ejection Fraction","",""],["","","","","","","","Software","",""],["","510(k) Holder/ Manufacturer","","Clarius Mobile Health Corp.","","","Caption Health, Inc.","","","Not applicable"],["","Submission Reference","","Current Submission","","","K210747","","","Not applicable"],["","Primary Product Code","","QIH","","","QIH","","","Same as predicate device."],["Device Classification Name","Device Classification Name","","Automated Radiological\nImage Processing Software","","","Automated Radiological\nImage Processing Software","","","Same as predicate device."],["Regulation Name","","","Medical Image Management and\nProcessing System","","","Medical Image Management and\nProcessing System","","","Same as predicate device."],["","Regulation Number","","21 CFR § 892.2050","","","21 CFR § 892.2050","","","Same as predicate device."],["Intended Use","Intended Use","","Intended for use as an assistive\ntool utilizing an artificial\nintelligence/machine learning-\nbased algorithm for semi-\nautomated measurement of\ncardiac ultrasound images for\ndetermination of left ventricular\nejection fraction.","","","Intended for use as an assistive\ntool utilizing an artificial\nintelligence/machine learning-\nbased algorithm for semi-\nautomated measurement of\ncardiac ultrasound images for\ndetermination of left ventricular\nejection fraction.","","","Same as predicate device."],["Indications for Use","","","Clarius Ejection Fraction AI is\nintended for semi-automatic\nnon-invasive measurement of\nthe left ventricular ejection\nfraction on ultrasound data\nacquired by the Clarius\nUltrasound Scanner (i.e.,\nphased array and curvilinear\nscanners). The user shall be a\nhealthcare professional\ntrained and qualified in\nultrasound. The user retains\nthe responsibility of\nconfirming the validity of the","","","The Caption Interpretation\nAutomated Ejection Fraction\nsoftware is used to process\npreviously acquired\ntransthoracic cardiac ultrasound\nimages, to store images, and to\nmanipulate and make\nmeasurements on\nimages using an ultrasound\ndevice, personal computer, or a\ncompatible DICOM-compliant\nPACS system in\norder to provide automated\nestimation of left ventricular","","","Equivalent to the predicate\ndevice. Both the subject device\nand the predicate device are\nindicated for automated/semi-\nautomated measurement of the\nleft ventricular ejection fraction\non ultrasound data acquired using\nultrasound devices. Both devices\nare intended for use as assistive\n“tools” to aid the clinician in\nperforming cardiac assessments.\nThe minor differences in the\nindications for use between the\nsubject device and the predicate"]],"caption_candidate":"Table 1 - Comparison of the Subject Device to the Legally Marketed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p9-t0","doc_id":"K253593","page_num":9,"bbox":[72.32,72.35,674.39,535.39],"n_rows":20,"n_cols":10,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],["","","","","","","","","",""],["Device Trade Name","","","Clarius Ejection Fraction AI","","","","Caption Interpretation","",""],["","","","","","","","Automated Ejection Fraction","",""],["","","","","","","","Software","",""],["","","","measurements based on\nstandard practices and clinical\njudgment. Clarius Ejection\nFraction Al is intended for use\nin adult patients only.","","","ejection fraction. This\nmeasurement can be used to\nassist the clinician in a cardiac\nevaluation.\nThe Caption Interpretation\nAutomated Ejection Fraction\nSoftware is indicated for use in\nadult patients.","","","device do not impact the safety\nand effectiveness of the subject\ndevice relative to the predicate\ndevice."],["","Radiological application/","","Ultrasound","","","Ultrasound","","","Same as predicate device."],["","Supported modality","","","","","","","",""],["Principle of Operation/\nTechnology","Principle of Operation/","","Ultrasound image processing\nsoftware implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms\ntrained with clinical and/or\nartificial data intended for\nmeasurements of cardiac\nultrasound data.","","","Ultrasound image processing\nsoftware implementing artificial\nintelligence utilizing non-adaptive\nmachine learning algorithms\ntrained with clinical and/or\nartificial data intended for\nmeasurements of cardiac\nultrasound data.","","","Same as predicate device."],["","Technology","","","","","","","",""],["","Quantitative and/or Qualitative","","LV EF measurement","","","LV EF measurement","","","Same as predicate device."],["","Analysis","","","","","","","",""],["Segmentation","Segmentation","","Yes – Segmentation of anatomical\nstructures (cardiac anatomy/\nheart)","","","Yes – Segmentation of anatomical\nstructures (cardiac anatomy/\nheart)","","","Same as predicate device."],["Measurement","","","Yes – Measurement of LV ejection\nfraction","","","Yes – Measurement of LV ejection\nfraction","","","Same as predicate device."],["Algorithm Methodology","","","Artificial Intelligence (AI)/Machine\nLearning (ML)","","","Artificial Intelligence (AI)/Machine\nLearning (ML)","","","Same as predicate device."],["","Automation","","Yes","","","Yes","","","Same as predicate device."],["","(Yes or No)","","","","","","","",""],["","Manual adjustment/Manual","","Yes","","","Yes","","","Same as predicate device."],["","editing capability","","","","","","","",""],["","(Yes or No)","","","","","","","",""]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p10-t0","doc_id":"K253593","page_num":10,"bbox":[72.32,72.35,674.38,203.23],"n_rows":9,"n_cols":10,"columns":["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],"rows":[["Criteria","","","","SUBJECT DEVICE","","PREDICATE DEVICE","","","RATIONALE\n(if subject device differs from\npredicate device)"],["","","","","","","","","",""],["Device Trade Name","","","Clarius Ejection Fraction AI","","","","Caption Interpretation","",""],["","","","","","","","Automated Ejection Fraction","",""],["","","","","","","","Software","",""],["Environment of Use","","","Professional healthcare setting\n(e.g., hospital, clinic)","","","Professional healthcare setting\n(e.g., hospital, clinic)","","","Same as predicate device."],["","Anatomical Site","","Heart","","","Heart","","","Same as predicate device."],["","Intended Users","","Licensed healthcare professionals","","","Licensed healthcare professionals","","","Same as predicate device."],["","Patient Population","","Adults","","","Adults","","","Same as reference device."]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p11-t0","doc_id":"K253593","page_num":11,"bbox":[72.26,181.44,539.74,293.64],"n_rows":7,"n_cols":4,"columns":["","Standard","","Title of Standard"],"rows":[["","Standard","","Title of Standard"],["","Recognition","",""],["","Number","",""],["13-79","","","IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes"],["5-125","","","ISO 14971:2019 Medical devices — Application of risk management to medical devices"],["5-129","","","IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to\nmedical devices"],["5-134","","","ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling\nand information to be supplied"]],"caption_candidate":"following FDA-recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p13-t0","doc_id":"K253593","page_num":13,"bbox":[72.37,247.14,325.79,719.4],"n_rows":30,"n_cols":5,"columns":["","Table 1: Geographic Data","","",""],"rows":[["","Table 1: Geographic Data","","",""],["","Location","","Number of Images",""],["United States","","72","",""],["Canada","","44","",""],["Germany","","22","",""],["Unknown","","21","",""],["Turkey","","18","",""],["United Kingdom","","10","",""],["Philippines","","9","",""],["Australia","","8","",""],["Italy","","7","",""],["Sweden","","7","",""],["Mexico","","6","",""],["Belgium","","5","",""],["Singapore","","5","",""],["El Salvador","","4","",""],["Lithuania","","4","",""],["Norway","","3","",""],["Venezuela","","3","",""],["Malaysia","","2","",""],["Switzerland","","2","",""],["South Africa","","2","",""],["Indonesia","","2","",""],["Greece","","2","",""],["Nigeria","","2","",""],["New Zealand","","2","",""],["Austria","","2","",""],["Morocco","","2","",""],["Iraq","","2","",""],["South Korea","","1","",""]],"caption_candidate":"data collected is shown in Table 1:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p14-t0","doc_id":"K253593","page_num":14,"bbox":[72.34,72.36,325.8,229.92],"n_rows":10,"n_cols":2,"columns":["Jamaica","1"],"rows":[["Jamaica","1"],["Israel","1"],["Taiwan","1"],["The Netherlands","2"],["Dominican Republic","1"],["Uganda","1"],["Ireland","1"],["Bahrain","1"],["Vatican","1"],["Total","279"]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p15-t0","doc_id":"K253593","page_num":15,"bbox":[72.27,72.24,539.73,146.52],"n_rows":2,"n_cols":6,"columns":["Fractional Area\nChange","PSAX","1.57e-36\n(97.5%CI: - inf, -\n2.18)","-18","10","-3.87"],"rows":[["Fractional Area\nChange","PSAX","1.57e-36\n(97.5%CI: - inf, -\n2.18)","-18","10","-3.87"],["Teicholz method","PLAX","1.12e-18\n(97.5%CI: -\ninf, -2.38)","-10","10","-5.92"]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p15-t1","doc_id":"K253593","page_num":15,"bbox":[72.27,198.0,539.73,274.08],"n_rows":6,"n_cols":9,"columns":["","Table 3: ICC values of Reviewers and Clarius Ejection Fraction AI","","","","","","",""],"rows":[["","Table 3: ICC values of Reviewers and Clarius Ejection Fraction AI","","","","","","",""],["","Comparison Pair","","","ICC","","","95% CI",""],["Reviewer1 vs. Reviewer2","","","0.67","","","[0.59 0.74]","",""],["Reviewer1 vs. Reviewer3","","","0.64","","","[0.53 0.71]","",""],["Reviewer2 vs. Reviewer3","","","0.54","","","[0.41 0.64]","",""],["AI_EF vs. Mean_Reviewers","","","0.78","","","[0.71 0.83]","",""]],"caption_candidate":"EF AI for the various views/measurement methods, as shown in Table 3 below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p16-t0","doc_id":"K253593","page_num":16,"bbox":[72.58,323.76,539.9,716.4],"n_rows":2,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["Modification of data\ninput sources (Clarius\nultrasound scanners)","","To add data from\ncurrent Clarius\nscanners and future\n510(k) cleared Clarius\nscanners to the Clarius\nEjection Fraction AI\nmodel so the model\ncan be deployed on\nmore scanners.","","","Internal testing, clinical\ndesign validation and\nusability validation to\nassess the model’s\nperformance and ensure\nit performs as intended\nto meet users’ needs.","","","By accommodating a\nwider array of image\ngeometries and\ncharacteristics with\nthe use of new\n510(k)-cleared\nClarius ultrasound\nscanners, the\nupdated Ejection\nFraction AI model\nwill be better\nequipped to handle\ndifferent transducer\nmodels of the\nClarius Ultrasound\nScanner used in\nvarying clinical\nscenarios.\nBenefit-Risk\nAnalysis:\nBenefits: Enhanced\ncompatibility;\nFlexibility for diverse\nclinical settings.\nRisks: Data skewing\nand concept drift.","",""]],"caption_candidate":"Summary of planned modifications to Clarius Ejection Fraction AI per the PCCP:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p17-t0","doc_id":"K253593","page_num":17,"bbox":[72.53,72.93,539.95,695.38],"n_rows":4,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","","","","Risk Mitigation:\nInternal testing to\nensure that data\nskewing and\nconcept drift are\nmitigated.","",""],["Modification of training\nhyperparameters (initial\nlearning rate, width\nmultiplier, dropout rate)","","Improvement and\noptimization of Clarius\nEjection Fraction AI’s\nperformance","","","Re-training of the\nEjection Fraction AI\nmodel with modified\nhyperparameters to\noptimize its performance\nfollowed by internal\ntesting and a comparison\nof the original Ejection\nFraction AI model to the\nmodified Ejection\nFraction AI model (using\nperformance metrics)\nfollowed with clinical\nperformance testing\n(verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nEjection Fraction AI\nmodel with\nincreased accuracy\nand more robust\nmeasurements\ndisplayed to users.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of post-\nprocessing steps","","Improvement and\noptimization of Clarius\nEjection Fraction AI’s\nperformance and\nrobustness","","","Internal testing and a\ncomparison of the\noriginal Ejection Fraction\nAI model to the modified\nEjection Fraction AI\nmodel (using\nperformance metrics)\nand clinical performance","","","Improved\nperformance\nmetrics of modified\nEjection Fraction AI\nmodel.\nBenefit-Risk\nAnalysis:","",""]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p18-t0","doc_id":"K253593","page_num":18,"bbox":[72.55,72.93,539.93,694.8],"n_rows":3,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","testing (verification and\nvalidation).","","","Benefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be\nemployed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""],["Modification of masked\nautoencoder\narchitecture and training","","Optimization of model\nrobustness, accuracy,\nand generalizability\nacross diverse patient\npopulations and\nscanning conditions","","","Internal testing and a\ncomparison of the\noriginal Ejection Fraction\nAI model to the modified\nEjection Fraction AI\nmodel (using\nperformance metrics)\nand clinical performance\ntesting (verification and\nvalidation).","","","Improved\nperformance\nmetrics of modified\nEjection Fraction AI\nmodel with\nincreased accuracy,\nimproved\ngeneralizability, and\nmore robust\nmeasurements\ndisplayed to users.\nBenefit-Risk\nAnalysis:\nBenefits: Improved\nperformance;\ngeneralization.\nRisks: Overfitting;\nunintended bias.\nRisk Mitigation:\nProper\nregularization\ntechniques and\ncross-validation and\ndropout will be","",""]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253593-p19-t0","doc_id":"K253593","page_num":19,"bbox":[72.58,72.93,539.9,183.48],"n_rows":2,"n_cols":11,"columns":["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],"rows":[["","Modification","","Rationale","","","Testing Methods","","","Impact Assessment",""],["","","","","","","","","employed to\nmitigate overfitting.\nInternal testing and\nverification will be\nconducted to\nmitigate unintended\nbiases.","",""]],"caption_candidate":"K253593","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253595-p6-t0","doc_id":"K253595","page_num":6,"bbox":[75.62,77.74,347.85,590.79],"n_rows":53,"n_cols":2,"columns":["510(k) Summary",""],"rows":[["510(k) Summary",""],["",""],["This summary of safety and","effectiveness of information is su"],["807.92.",""],["",""],["510(k) Number : K253595",""],["",""],["Date Prepared: March 25, 2","026"],["",""],["I. Submitter",""],["",""],["Manufacturer Name and","Philips Ultrasound LLC"],["",""],["Address","22100 Bothell Everett Hwy"],["",""],["","Bothell, WA 98021-8431 USA"],["",""],["Contact Person (Primary):","Lakshmi Sanjana Gondesi"],["","Senior Regulatory Affairs Specia"],["",""],["","Philips Ultrasound LLC"],["",""],["","22100 Bothell Everett Highway"],["",""],["","Bothell, WA 98021"],["",""],["","sanjana.gondesi@philips.com"],["",""],["","Phone: 1 425-482-8200"],["",""],["","Irma Sandoval-Watt"],["",""],["Contact Person","Senior Regulatory Manager"],["",""],["",""],["(Secondary):","Philips Ultrasound LLC"],["",""],["",""],["","22100 Bothell Everett Hwy"],["",""],["","Bothell, WA 98021-8431 USA"],["",""],["","irma.sandoval-watt@philips.com"],["",""],["","Phone: 1-303-453-3421"],["",""],["II. Device",""],["",""],["Proprietary Name","EPIQ Series Diagnostic Ultrasou"],["",""],["","Affiniti Series Diagnostic Ultraso"],["",""],["Common Name","Diagnostic Ultrasound System an"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"text"}
{"table_id":"K253595-p7-t0","doc_id":"K253595","page_num":7,"bbox":[203.15,85.58,518.1,235.03],"n_rows":8,"n_cols":9,"columns":["","Classification Description","","","21 CFR §","","","Product Code",""],"rows":[["","Classification Description","","","21 CFR §","","","Product Code",""],["","Primary","","","","","","",""],["System, imaging, pulsed doppler,\nultrasonic","","","892.1550","","","IYN","",""],["","Secondary","","","","","","",""],["System, imaging, pulsed echo,\nultrasonic","","","892.1560","","","IYO","",""],["Transducer, ultrasonic, diagnostic","","","892.1570","","","ITX","",""],["Automated Radiological Image\nProcessing Software","","","892.2050","","","QIH","",""],["Diagnostic Intravascular Catheter","","","870.1200","","","OBJ*","",""]],"caption_candidate":"Regulation Description","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253595-p10-t0","doc_id":"K253595","page_num":10,"bbox":[65.66,599.82,546.41,675.94],"n_rows":5,"n_cols":3,"columns":["","AI Auto Measure (cm)","Ground Truth (cm)"],"rows":[["","AI Auto Measure (cm)","Ground Truth (cm)"],["Measurement","Mean ± SD (Min, Max)","Mean ± SD (Min, Max)"],["Kidney Sagittal Length","10.55 ± 1.20 (7.54, 14.80)","10.50 ± 1.17 (7.20, 14.13)"],["Kidney Transverse Width","5.19 ± 0.60 (3.25, 7.26)","5.17 ± 0.71 (3.62, 7.30)"],["Kidney Transverse Height","5.11 ± 0.80 (2.95, 7.71)","5.10 ± 0.83 (2.84, 7.76)"]],"caption_candidate":"Table 1. Clinical measurement summary for AI Auto Measure Abdomen and Ground Truth","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253595-p11-t0","doc_id":"K253595","page_num":11,"bbox":[65.66,72.37,546.37,116.81],"n_rows":3,"n_cols":3,"columns":["","AI Auto Measure (cm)","Ground Truth (cm)"],"rows":[["","AI Auto Measure (cm)","Ground Truth (cm)"],["Measurement","Mean ± SD (Min, Max)","Mean ± SD (Min, Max)"],["Spleen Length","10.77 ± 2.41 (6.08, 20.36)","10.53 ± 2.39 (5.52, 19.59)"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253595-p11-t1","doc_id":"K253595","page_num":11,"bbox":[56.02,196.97,556.41,279.34],"n_rows":8,"n_cols":5,"columns":["","Mean Difference","","","Acceptance"],"rows":[["","Mean Difference","","","Acceptance"],["Measurement","","95% LoA","95% CI of LoA",""],["","± SD","","","Criteria"],["","","","",""],["Kidney Sagittal Length","0.46% ± 3.51%","(-6.41%, 7.33%)","(-7.10%, 8.02%)","[-14.3%, 14.3%]"],["Kidney Transverse Width","0.26% ± 8.79%","(-16.97%, 17.49%)","(-18.77%, 19.29%)","[-33.7%, 33.7%]"],["Kidney Transverse Height","0.54% ± 6.36%","(-11.92%, 13.00%)","(-13.22%, 14.30%)","[-30.1%, 30.1%]"],["Spleen Length","2.34% ± 4.90%","(-7.26%, 11.94%)","(-8.63%, 13.32%)","[-15.9%, 15.9%]"]],"caption_candidate":"between AI Auto Measure Abdomen and Ground Truth","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253614-p6-t0","doc_id":"K253614","page_num":6,"bbox":[155.88,510.0,520.92,741.84],"n_rows":2,"n_cols":3,"columns":["Change\nNumber","Feature/Change","Change and Rationale for change"],"rows":[["Change\nNumber","Feature/Change","Change and Rationale for change"],["1.","Addition of a\nnew function in\nEchoNavigator\nR5.0: M-TEER\ndevice\ndetection (also\nknown as device\ntracking) and\noverlay\nDeviceGuide\nfunctionality","Mitral Transcatheter Edge-to-Edge Repair\n(M−TEER) device detection and overlay involves\ndetecting the location of the M-TEER therapy\ndevice in the X-ray and echo images (enabled by\nArtificial Intelligence).\nThe TEER device detection and overlay function\nhas the following optional features:\n• visualization of the shape, trajectory, and\norientation of mitral TEER device overlaid on\nX-ray and/or echo images.\n• device focused echo views (on the TEER\ndevice) to optimize the visualization of the\nrelationship between device and surrounding\nanatomy.\nThe software element of this functionality"]],"caption_candidate":"Table 1: Overview of the changes for EchoNavigator R5.0","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253614-p7-t0","doc_id":"K253614","page_num":7,"bbox":[155.88,97.92,520.92,735.24],"n_rows":3,"n_cols":3,"columns":["","","contains the algorithms to detect/track the\nlocation and orientation of M-TEER therapy\ndevices (this release only supports Edwards’\nPASCAL Ace M-TEER therapy device).\n• Input: 2D X-ray image + geometry information\n+ 3D echo volume + TEE probe registration\nresult.\n• Output: 3D position, orientation and\nopenness angle of therapy device, including\ndetection status.\nThe intent of this function is to assist physicians in\ndevice guidance and navigation when performing\nTEER procedures. This is an -on demand function\nfor the physician.\nPlease note that all the other features and the\nunderlying algorithms of EchoNavigator R5.0 are\nthe same as the features and underlying\nalgorithms of the predicate device.\n(EchoNavigator R4.0, K221270)"],"rows":[["","","contains the algorithms to detect/track the\nlocation and orientation of M-TEER therapy\ndevices (this release only supports Edwards’\nPASCAL Ace M-TEER therapy device).\n• Input: 2D X-ray image + geometry information\n+ 3D echo volume + TEE probe registration\nresult.\n• Output: 3D position, orientation and\nopenness angle of therapy device, including\ndetection status.\nThe intent of this function is to assist physicians in\ndevice guidance and navigation when performing\nTEER procedures. This is an -on demand function\nfor the physician.\nPlease note that all the other features and the\nunderlying algorithms of EchoNavigator R5.0 are\nthe same as the features and underlying\nalgorithms of the predicate device.\n(EchoNavigator R4.0, K221270)"],["2.","UI\nHarmonization","Harmonization of the EchoNavigator UI with the\nUI offered on the EPIQ system (Ultrasound\nconsole):\n• Harmonize the presentation of echo views\noffered in EchoNavigator with those offered\non the EPIQ system, such that there are\nminimal differences between the echo views\nwhen the user switches between EPIQ system\nand EchoNavigator views.\n• Harmonize buttons and button presentation,\nbringing it in line with the EPIQ system."],["3.","Proposed\nProduct Claims","The proposed product claims for EchoNavigator\nR5.0 (which are new in comparison to the\npredicate device, (EchoNavigator R4.0, K221270))\nare as follows:\n• Automated visualization of trajectory and\norientation of mitral TEER device\n• Improved imaging workflow through a\ndedicated user interface for Mitral TEER.\n• Automatic device augmentation on echo\n(Augmented Reality)\n• DeviceGuide offers real-time automatic\ndevice detection, tracking and 3D pose-\nestimation in live Echo and live X-ray enabled\nby Artificial Intelligence which is built with\nDeep Learning technology."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253625-p5-t0","doc_id":"K253625","page_num":5,"bbox":[93.44,221.0,527.1,300.59],"n_rows":4,"n_cols":2,"columns":["Classification Name:","Magnetic Resonance Diagnostic Device"],"rows":[["Classification Name:","Magnetic Resonance Diagnostic Device"],["Regulation Number:","90-LNH (Per 21 CFR § 892.1000)"],["Trade Proprietary Name:","Vantage Fortian / Orian 1.5T, MRT-1550, V10.0 with AiCE\nReconstruction Processing Unit for MR"],["Model Number:","MRT-1550"]],"caption_candidate":"1. CLASSIFICATION and DEVICE NAME","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253625-p6-t0","doc_id":"K253625","page_num":6,"bbox":[90.26,512.11,365.11,600.1],"n_rows":5,"n_cols":2,"columns":["System","Predicate Device"],"rows":[["System","Predicate Device"],["","Vantage Fortian/Orian 1.5T, MRT-1550,\nV10.0 with AiCE Reconstruction Processing\nUnit for MR"],["Marketed By","Canon Medical Systems USA, Inc."],["510(k) Number","K250901"],["Clearance Date","July 22, 2025"]],"caption_candidate":"Unit for MR (K250901)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253625-p7-t0","doc_id":"K253625","page_num":7,"bbox":[90.26,119.78,531.7,207.86],"n_rows":5,"n_cols":3,"columns":["System","Reference Device 1","Reference Device 2"],"rows":[["System","Reference Device 1","Reference Device 2"],["","Vantage Orian 1.5T, MRT-1550, V9.0 with\nAiCE Reconstruction Processing Unit for\nMR","Vantage Orian 1.5T, MRT-1550, V6.0 with\nAiCE Reconstruction Processing Unit for\nMR"],["Marketed By","Canon Medical Systems USA, Inc.","Canon Medical Systems USA, Inc."],["510(k) Number","K240238","K191662"],["Clearance Date","April 12, 2024","July 23, 2019"]],"caption_candidate":"Reference Device:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253625-p8-t0","doc_id":"K253625","page_num":8,"bbox":[95.08,501.13,558.67,691.66],"n_rows":10,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Fortian/Orian 1.5T,","","","Vantage Fortian/Orian 1.5T,","",""],["","","MRT-1550, V10.0","","","MRT-1550, V10.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR","",""],["Static field strength","1.5T","","","1.5T","","","Same"],["Operational Modes","Normal and 1st Operating Mode","","","Normal and 1st Operating Mode","","","Same"],["i. Safety parameter\ndisplay","SAR, dB/dt","","","SAR, dB/dt","","","Same"],["ii. Operating mode\naccess requirements","Allows screen access to 1st level\noperating mode","","","Allows screen access to 1st level\noperating mode","","","Same"],["Maximum SAR","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","4W/kg for whole body (1st\noperating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015)","","","Same"]],"caption_candidate":"20. SAFETY PARAMETERS","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253625-p9-t0","doc_id":"K253625","page_num":9,"bbox":[95.1,84.38,558.65,220.1],"n_rows":7,"n_cols":8,"columns":["Item","","Subject Device:","","","Predicate Device:","","Notes"],"rows":[["Item","","Subject Device:","","","Predicate Device:","","Notes"],["","","Vantage Fortian/Orian 1.5T,","","","Vantage Fortian/Orian 1.5T,","",""],["","","MRT-1550, V10.0","","","MRT-1550, V10.0","",""],["","","with AiCE Reconstruction","","","with AiCE Reconstruction","",""],["","","Processing Unit for MR","","","Processing Unit for MR","",""],["Maximum dB/dt","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","1st operating mode specified in IEC\n60601-2-33:\n2010+A1:2013+A2:2015","","","Same"],["Potential emergency\ncondition and means\nprovided for shutdown","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Shutdown by Emergency Ramp\nDown Unit for collision hazard for\nferromagnetic objects","","","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253648-p8-t0","doc_id":"K253648","page_num":8,"bbox":[72.27,441.72,553.17,692.04],"n_rows":5,"n_cols":5,"columns":["","Recognition","","Standard Number and Date","Standard Name"],"rows":[["","Recognition","","Standard Number and Date","Standard Name"],["","Number","","",""],["12-347","","","IEC 60601-2-33 Edition 4.0\n2022-08","Medical electrical equipment - Part 2-33:\nParticular requirements for the basic safety and\nessential performance of magnetic resonance\nequipment for medical diagnosis"],["19-46","","","ES60601-1:2005/(R)2012 &\nA1:2012, C1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons. Text)\n[Incl. AMD2:2021]","Medical electrical equipment - Part 1: General\nrequirements for basic safety and essential\nperformance (IEC 60601-1:2005, MOD)\n[Including Amendment 2 (2021)]Medical\nelectrical equipment - Part 1: General\nrequirements for basic safety and essential\nperformance (IEC 60601-1:2005, MOD)"],["19-36","","","ANSI AAMI IEC 60601-1-\n2:2014 [Including AMD\n1:2021]","Medical electrical equipment - Part 1-2: General\nrequirements for basic safety and essential\nperformance - Collateral Standard:\nElectromagnetic disturbances - Requirements\nand tests [Including Amendment 1 (2021)]"]],"caption_candidate":"recognized consensus standards:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253648-p9-t0","doc_id":"K253648","page_num":9,"bbox":[72.26,65.52,553.18,330.6],"n_rows":7,"n_cols":5,"columns":["","Recognition","","Standard Number and Date","Standard Name"],"rows":[["","Recognition","","Standard Number and Date","Standard Name"],["","Number","","",""],["5-132","","","IEC 60601-1-6 Edition 3.2\n2020-07 CONSOLIDATED\nVERSION","Medical electrical equipment - Part 1-6: General\nrequirements for basic safety and essential\nperformance - Collateral standard: Usability"],["5-131","","","ANSI AAMI IEC 60601-1-\n8:2006 and A1:2012\n[Including AMD 2:2021]","Medical Electrical Equipment - Part 1-8:\nGeneral requirements for basic safety and\nessential performance - Collateral Standard:\nGeneral requirements tests and guidance for\nalarm systems in medical electrical equipment\nand medical electrical systems [Including\nAmendment 2 (2021)]"],["13-79","","","ANSI AAMI IEC\n62304:2006/A1:2016","Medical device software - Software life cycle\nprocesses [Including Amendment 1 (2016)]"],["5-129","","","ANSI AAMI IEC 62366-\n1:2015+AMD1:2020\n(Consolidated Text)","Medical devices Part 1: Application of usability\nengineering to medical devices including\nAmendment 1"],["5-125","","","ANSI AAMI ISO 14971: 2019","Medical devices – Application of risk\nmanagement to medical devices."]],"caption_candidate":"Bundled Abbreviated 510(k)","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p6-t0","doc_id":"K253649","page_num":6,"bbox":[34.8,140.52,484.87,755.52],"n_rows":29,"n_cols":3,"columns":["SUBMITER INFORMATION","",""],"rows":[["SUBMITER INFORMATION","",""],["Address","Philips Medical Systems Nederland B.V.\nVeenpluis 6,\n5684 PC Best,\nNetherlands",""],["Primary Contact","Siwar Assi\nRegulatory Affairs Team Lead\nPhone: +972-50-7494961\nE-Mail: Siwar.Assi@philips.com",""],["Secondary Contact","Carmit Shmuel\nRegulatory Affairs Manager and Site Lead\nPhone: +972-54-2109054\nE-Mail: Carmit.Shmuel@philips.com",""],["DEVICE IDENTIFICATION","",""],["Subject Device","",""],["Trade Name:","","Spectral CT Verida Family"],["Common name:","","System, X-ray, Tomography, Computed"],["Classification Name","","Computed tomography x-ray system"],["Classification Regulation:","","21 CFR 892.1750"],["Classification Panel:","","Radiology"],["Device Class:","","II"],["Product Code:","","JAK"],["Primary Predicate Device","",""],["Trade Name:","","Spectral CT 7500 RT"],["Manufacturer:","","Philips Medical Systems Nederland B.V."],["510(k) Clearance:","","K240844"],["Classification Name:","","Computed tomography x-ray system"],["Classification Regulation:","","21 CFR 892.1750"],["Classification Panel:","","Radiology"],["Device Class:","","Class II"],["Product Code:","","JAK"],["Reference Device","",""],["Trade Name:","","Spectral CT"],["Manufacturer:","","Philips Medical Systems Nederland B.V."],["510(k) Clearance:","","K203020"],["Classification Name:","","Computed tomography x-ray system"],["Classification Regulation:","","21 CFR 892.1750"],["Classification Panel:","","Radiology"]],"caption_candidate":"Date Prepared: March 27, 2026","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p7-t0","doc_id":"K253649","page_num":7,"bbox":[34.8,71.04,485.04,255.12],"n_rows":11,"n_cols":2,"columns":["Device Class:","Class II"],"rows":[["Device Class:","Class II"],["Product Code:","JAK"],["Reference Device",""],["Trade Name:","CT5300"],["Manufacturer:","Philips Medical Systems Nederland B.V."],["510(k) Clearance:","K232491"],["Classification Name:","Computed tomography x-ray system"],["Classification Regulation:","21 CFR 892.1750"],["Classification Panel:","Radiology"],["Device Class:","Class II"],["Product Code:","JAK"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p9-t0","doc_id":"K253649","page_num":9,"bbox":[71.04,270.96,517.56,598.32],"n_rows":10,"n_cols":2,"columns":["New/Modified Features","Description"],"rows":[["New/Modified Features","Description"],["Software Changes",""],["Spectral Precise Image\n(SPI)","AI-based image denoising and image-quality enhancement\nfunctionality integrated within the image reconstruction pipeline.\nSPI is derived from the previously cleared Precise Image framework\nand does not alter the fundamental image-formation process or\nintroduce new clinical decision-making functionality."],["Spectral Result Generation\nPipeline Optimization","Implemented this pipeline optimization to improve the Spectral\nImage Time-to-First-Image (TTFI)."],["Software Revision","Revision from Version 5.2 to Version 5.4 to accommodate for\nchanges made under this version control."],["Hardware Changes",""],["Noah RT-2 Couch","The proposed Spectral CT Verida Family system introduces Noah\nRT-2 Couch to replace the Noah HP Couch from the cleared to\nmarket primary predicate device, Spectral CT 7500 RT device\n(K240844)."],["Bayonet Head Holder","The Bayonet Head Holder provides additional scannable range\nwhen plugged into the couch head slot of the proposed Spectral CT\nVerida Family system."],["Console and CIRS Computers","Change from HP G4 to HP G5 due to EOL and performance\nimprovements"],["Oncology Tabletop","Change to support both Varian and Elekta indexing"]],"caption_candidate":"Table 1: New/Modified features in the proposed device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p10-t0","doc_id":"K253649","page_num":10,"bbox":[70.74,84.24,771.12,512.4],"n_rows":9,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["TECHNOLOGICAL CHARACTERISTICS","","","","",""],["Application","Head, Body, and Cardiac","Head, Body, and Cardiac","Head, Body, and Cardiac","Head, Body, and\nCardiac","Same as\nprimary\npredicate"],["Scan regime","Continuous Rotation","Continuous Rotation","Continuous Rotation","Continuous Rotation","Same as\nprimary\npredicate"],["Computer\nand CIRS\n(Common\nImage\nReconstructio\nn System)","PC computer based on Intel\nprocessors and custom\nMultiprocessor Array","PC computer based on Intel\nprocessors and custom\nMultiprocessor Array","PC computer based on\nIntel processors and\ncustom Multiprocessor\nArray","PC computer based on\nIntel processors and\ncustom Multiprocessor\nArray","Same as\nprimary\npredicate"],["Display","1280 x 1024","1280 x 1024","1280 x 1024","1920 x 1080","Same as\nprimary\npredicate"],["Number of\nSlices","Up to 128 slices of 0.625 mm","Up to 128 slices of 0.625 mm","Up to 128 slices of 0.625\nmm","Up to 128 slices of\n0.625 mm","Same as\nprimary\npredicate"],["Scan modes","Surview\nAxial-after-axial\nDynamic Scan\nHelical Scan","Surview\nAxial-after-axial\nDynamic Scan\nHelical Scan","Surview\nAxial-after-axial\nDynamic Scan\nHelical Scan","Surview\nAxial-after-axial\nHelical Scan","Same as\nprimary\npredicate"],["Minimum\nScan time","0.18 sec for 240° rotation,\n0.27 sec for 360° rotation","0.18 sec for 240° rotation,\n0.27 sec for 360° rotation","0.18 sec for 240° rotation,\n0.27 sec for 360° rotation","0.35 sec for 360°\nrotation","Same as\nprimary\npredicate"]],"caption_candidate":"Table 2 Technological Characteristics Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p11-t0","doc_id":"K253649","page_num":11,"bbox":[70.8,70.8,771.12,442.08],"n_rows":5,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["Scan\nCoverage","Scanner Center of Rotation\n(COR) is up to 80 mm","Scanner Center of Rotation\n(COR) is up to 80 mm","Scanner Center of\nRotation (COR) is up to 80\nmm","Focus-isocenter\ndistance: 570 mm","Same as\nprimary\npredicate"],["Image Matrix","Up to 1024 x 1024","Up to 1024 x 1024","Up to 1024 x 1024","Up to 1024 x 1024","Same as\nprimary\npredicate"],["Spatial\nResolution","16 lp/cm max (high mode)","16 lp/cm max (high mode)","16 lp/cm max (high mode)\n13 lp/cm max (standard\nmode)","16 lp/cm max (high\nmode)\n13 lp/cm max\n(standard mode)","Same as primary\npredicate"],["Low Contrast\nResolution","4.0 mm at 0.3% with 25 mGy\n(CTDIvol)","4.0 mm at 0.3% with 25 mGy\n(CTDIvol)","4.0 mm at 0.3% with 25\nmGy (CTDIvol)","Low-contrast\nresolution (with\niDose4): 2 mm @\n0.3%; ≤ 42mGy\nCTDIvol (body), 3 mm\n@ 0.3%; ≤ 22 mGy\nCTDIvol (body), 4 mm\n@ 0.3%; ≤ 15.5 mGy\nCTDIvol (body), 5 mm\n@ 0.3%; ≤ 14 mGy\nCTDIvol (body)\nLow-contrast\nresolution (with","Substantially\nequivalent;"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p12-t0","doc_id":"K253649","page_num":12,"bbox":[70.8,70.8,771.12,440.88],"n_rows":7,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","Precise Image): 5 mm\n@ 0.3%; ≤ 5.5 mGy\nCTDIvol (body)",""],["Noise in\nStandard\nMode (as\nmeasured on\n21.6 cm water-\nequivalent)","0.27% at 27 mGy","0.27% at 27 mGy","0.27% at 27 mGy","≤0.18% at 120kV,\n230mAs,\nCTDIcenter(head) ≤\n33mGy,\n10mm image\nthickness,\niDose4","Same as\nprimary\npredicate"],["DETECTORS","","","","",""],["DMS Detector","8 cm - Dual-Layer scintillator,\nup to 128 detector rows","8 cm - Dual-Layer scintillator, up\nto 128 detector rows","8 cm - Dual-Layer\nscintillator, up to 128\ndetector rows","Single layer ceramic\nscintillator plus a\nphotodiode","Same as primary\npredicate"],["Material","Solid-state yttrium-based\nscintillator, GOS + Photodiode","Solid-state yttrium-based\nscintillator, GOS + Photodiode","Solid-state yttrium-based\nscintillator, GOS +\nPhotodiode","Solid-state GOS with\n43,008\nelements","Same as primary\npredicate"],["Type","NanoPanel Prism Precise 3rd\nGen","NanoPanel Prism","NanoPanel Prism","NanoPanel Elite","Same as primary\npredicate\nThe brand name\nof the detector\nis updated in\nSpectral CT"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p13-t0","doc_id":"K253649","page_num":13,"bbox":[70.8,70.8,771.12,453.36],"n_rows":5,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","Verida Family to\nNanoPanel\nPrism Precise 3rd\nGen. No\ndifference in\ncharacteristics\nbetween\nproducts, no\nimpact to safety\nor effectiveness\nof the device."],["DMS\nstructure","Spherical DMS structure","Spherical DMS structure","Spherical DMS structure","Spherical DMS\nstructure","Same as primary\npredicate"],["Collimation","0.625 mm and various\ncombinations, such as:\n2x0.625, 16x0.625, 32x0.625,\n64x0.625, 96x0.625, 112x0.625,\n128x0.625 mm.","0.625 mm and various\ncombinations, such as:\n2x0.625, 16x0.625, 32x0.625,\n64x0.625, 96x0.625, 112x0.625,\n128x0.625 mm.","0.625 mm and various\ncombinations, such as:\n2x0.625, 16x0.625,\n32x0.625, 64x0.625,\n96x0.625, 112x0.625,\n128x0.625 mm.","0.625 mm and 1.25 mm\nvarious combinations,\nsuch as:\n2x0.625, 4x0.625,\n12x0.625, 16x0.625,\n32x0.625, 64x0.625,\n12x1.25, 32x1.25 mm","Same as primary\npredicate"],["Slice\nthickness","Various slice thickness options\navailable in the range of 0.67 -\n10 mm for helical mode and","Various slice thickness options\navailable in the range of 0.67 -\n10 mm for helical mode and","Various slice thickness\noptions available in the\nrange of 0.67 - 10 mm for","Helical: 0.67mm –\n5mm\nAxial: 0.625mm –","Same as primary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p14-t0","doc_id":"K253649","page_num":14,"bbox":[70.8,70.8,771.12,450.12],"n_rows":9,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","0.625 – 10 for axial mode","0.625 – 10 for axial mode","helical mode and 0.625 –\n10 for axial mode","10.0mm",""],["Scan field of\nview","Up to 500 mm","Up to 500 mm","Up to 500 mm","Up to 500 mm","Same as\nprimary\npredicate"],["EFOV-\nExtended\nField Of View","Yes; Up to 800 mm","Yes; Up to 800 mm","No","No","Same as\nprimary\npredicate"],["GENERATOR AND TUBE","","","","",""],["Gantry Bore\nAperture\ndiameter","800 mm","800 mm","800 mm","720mm","Same as\nprimary\npredicate"],["Gantry\nrotation\nspeed","0.27 sec -1.5 sec (360°\nrotation)\n0.18 sec, 0.2 sec (240°\nrotation)","0.27 sec -1.5 sec (360°\nrotation)\n0.18 sec, 0.2 sec (240° rotation)","0.27 sec -1.5 sec (360°\nrotation)\n0.18 sec, 0.2 sec (240°\nrotation)","171 RPM","Same as\nprimary\npredicate"],["Operator\nControls\nlocated on\nGantry","Touch Panel Controls","Touch Panel Controls","Touch Panel Controls","Touch Panel Controls","Same as\nprimary\npredicate"],["Eclipse","A-Plane","A-Plane","A-Plane","N/A","Same as"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p15-t0","doc_id":"K253649","page_num":15,"bbox":[70.8,70.8,771.12,448.44],"n_rows":7,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["Collimation","","","","","primary\npredicate"],["Power","Up to 120 kW","Up to 120 kW","Up to 120 kW","55kW/72kW/80kW","Same as\nprimary\npredicate"],["kV Setting","80, 100, 120, 140","80, 100, 120, 140","80, 100, 120, 140","70, 80, 100, 120, 140","Same as\nprimary\npredicate"],["mA Range","10-1000","10-1000","10-1000","5-667","Same as\nprimary\npredicate"],["Focal Spot","Dynamic Focal Spot in X and Z","Dynamic Focal Spot in X and Z","Dynamic Focal Spot in X\nand Z","Dynamic Focal Spot in\nX-axis","Same as\nprimary\npredicate"],["Conventional\nReconstruction\nSpeed","120 image per sec","40 images per sec","40 images per sec","Reconstruction speed\n(standard console)\nEssentials: Up to 80 IPS\nEssentials 64: Up to 60\nIPS\nReconstruction speed\n(enhanced console)\nUp to 100 IPS","Substantially\nequivalent;\nReconstruction\nperformance\nimprovements\nfor conventional\nCT is a part of\nthis change on\nthe proposed"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p16-t0","doc_id":"K253649","page_num":16,"bbox":[70.8,70.8,771.12,453.6],"n_rows":5,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","Spectral CT\nVerida Family.\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["X-Ray Tube\nType","iMRC","iMRC","iMRC","vMRC Performance","Same as primary\npredicate"],["COUCH (PATIENT SUPPORT)","","","","",""],["Couch","Noah RT-2 Couch","Noah HP Couch","Noah HP Couch","Standard Couch\nNoah HP Couch","Substantially\nequivalent;\nThe proposed\nSpectral CT\nVerida Family\nintroduces Noah\nRT-2 Couch to\nreplace Noah HP\nCouch in cleared"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p17-t0","doc_id":"K253649","page_num":17,"bbox":[70.8,70.8,771.12,449.4],"n_rows":4,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","to market\nprimary\npredicate device\nSpectral CT 7500\nRT system\n(K240844).\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["Horizontal\nposition\nprecision\nplanning","0.1mm","0.1 mm","0.1mm","± 0.25 mm","Same as primary\npredicate"],["Horizontal\nspeed","Maximum Speed = 600 mm/sec\nMinimum Speed = 1 mm/sec","Maximum Speed = 600 mm/sec\nMinimum Speed = 1 mm/sec","Maximum Speed = 600\nmm/sec\nMinimum Speed = 1\nmm/sec","Maximum Speed = 300\nmm/sec\nMinimum Speed = 1\nmm/sec","Same as primary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p18-t0","doc_id":"K253649","page_num":18,"bbox":[70.8,70.8,771.12,441.24],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["Couch Vertical\nRange","Minimum Height – 430 mm","Minimum Height – 430 mm","Minimum Height – 430 mm","530 mm – STD Couch\n430 mm – Noah HP\nCouch","Same as primary\npredicate"],["Couch\nHorizontal\nRange","0-2413 mm for patient pallet\n0-425 mm for sub pallet","2413 mm","2413 mm","With STD couch,\n1,830mm—helical\nscan\n1,860mm—Axial scan\nWith Noah couch,\n1,900mm—helical\nscan\n2,000mm—Axial scan","Substantially\nequivalent;\nThe proposed\nSpectral CT\nVerida Family\nsystem\nintroduces Noah\nRT-2 Couch to\nreplace the\nNoah HP Couch.\nCompared with\nNoah HP Couch,\nthere’s a sub\npallet in Noah\nRT-2 Couch\nwhich provides\nthe additional\nsupport to the\npatient pallet\nand can be\nmotorized"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p19-t0","doc_id":"K253649","page_num":19,"bbox":[70.8,70.8,771.12,451.68],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","moving.\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["Scannable\nSurview Range","w/o Bayonet Head Holder:\n1940mm\nw/ Bayonet Head Holder:\n2190mm","1940mm","1940mm","1940mm","Substantially\nequivalent;\nAdditional\nscannable range\nis due to\nBayonet Head\nholder plug in\nCouch head slot\nof the proposed\nSpectral CT\nVerida Family\nsystem.\nThe verification\nand validation"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p20-t0","doc_id":"K253649","page_num":20,"bbox":[70.8,70.8,771.12,448.8],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","for this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["Scannable\naxial Range","w/o Bayonet Head Holder:\n2000mm\nw/ Bayonet Head Holder: 2250\nmm","2000mm","2000mm","2000mm","Substantially\nequivalent;\nAdditional\nscannable range\nis due to\nBayonet Head\nholder plug in\nCouch head slot\nof the proposed\nSpectral CT\nVerida Family.\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p21-t0","doc_id":"K253649","page_num":21,"bbox":[70.8,70.8,771.12,448.8],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","new questions\non safety and/or\neffectiveness\nwill arise."],["Scannable\nhelical Range","w/o Bayonet Head Holder:\n1900mm\nw/ Bayonet Head Holder:\n2150mm","1900mm","1900mm","1900mm","Substantially\nequivalent;\nAdditional\nscannable range\nis due to\nBayonet Head\nholder plug in\nCouch head slot\nof the proposed\nSpectral CT\nVerida Family\nsystem.\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p22-t0","doc_id":"K253649","page_num":22,"bbox":[70.8,70.8,771.12,448.56],"n_rows":5,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","will arise."],["Acceleration","800 mm/Sec^2","800 mm/Sec^2","800 mm/Sec^2","800 mm/Sec^2","Same as\nprimary\npredicate"],["Couch Max\nLoad Capacity","675 lbs. (307 kg)\nUtilizing Oncology flat tabletop\noptional accessory: 628 lbs.\n(285 kg)","675 lbs. (307 kg)\nUtilizing Oncology flat tabletop\noptional accessory: 628 lbs. (285\nkg)","675 lbs. (307 kg)\nUtilizing Oncology flat\ntabletop optional\naccessory: 628 lbs. (285\nkg)","675 lbs. (307 kg)\nUtilizing Oncology flat\ntabletop optional\naccessory: 628 lbs.\n(285 kg)","Same as\nprimary\npredicate"],["Couch\naccessories","Infant Cradle, Paper roller,\nVarian Camera Adaptor,\nOncology flat tabletop, Bayonet\nHead holder","Infant Cradle, Paper roller,\nVarian Camera Adaptor,\nOncology flat tabletop","Infant Cradle, Paper roller,\nVarian Camera Adaptor,\nOncology flat tabletop","Infant Cradle, Paper\nroller, Oncology flat\ntabletop","Substantially\nequivalent;\nThe introduction\nof the Bayonet\nHead-holder on\nthe Spectral CT\nVerida Family\nsystem is to\nallow for\nadditional\nscannable\nrange.\nThe verification\nand validation\nfor this"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p23-t0","doc_id":"K253649","page_num":23,"bbox":[70.8,70.8,771.12,445.08],"n_rows":4,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","improvement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["GENERAL","","","","",""],["HOST Drives","One 1TB SSD for the OS and\nConsole Software plus one\n7.68TB U.2 PCle SSD for results","256GB OS disk plus one 7.68TB\nPCIE\nNVMe SSD","256GB OS disk plus one\n7.68TB PCIE\nNVMe SSD","One 2TB SSD for the\nOS and Console\nSoftware.","Substantially\nequivalent;\nThe proposed\nSpectral CT\nVerida Family\nsystem\nintroduces an\nimprovement to\nHost Drives\n(increased\ncapacity of\ncomputer\ndrives).\nThe verification\nand validation\nfor this"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p24-t0","doc_id":"K253649","page_num":24,"bbox":[70.8,70.8,771.12,453.72],"n_rows":5,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","improvement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["Host\nInfrastructure","Windows 10","Windows 10","Windows 10","Windows 10","Same as primary\npredicate"],["CIRS\nComputers","CIRS Rack that contains two HP\nZ8 servers.\nOption for two additional HP Z8\nServers in the same rack.","CIRS Rack that contains two HP\nZ8 servers.\nOption for two additional HP Z8\nServers in the same rack.","CIRS Rack that contains two\nHP Z8 servers.\nOption for two additional\nHP Z8 Servers in the same\nrack.","CIRS run in the same\nPC with Host\nin HP Z8","Same as primary\npredicate"],["CIRS CPUs","In each HP Z8: Single Intel Xeon\nW9-3475X with 36 cores at\n2.2GHz .","In each HP Z8: Dual Intel Gold\n6230 with 20 cores at 2.1GHz\neach.","In each HP Z8: Dual Intel\nGold 6230 with 20 cores at\n2.1GHz each.","CPU1: Intel Xeon Silver\n4214 processor 2.2\n12C\nCPU2: Intel Xeon Silver\n4214 processor 2.2\n12C","Substantially\nequivalent;\nThe proposed\nSpectral CT\nVerida Family\nsystem\nintroduces an\nimprovement to\nCIRS CPUs"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p25-t0","doc_id":"K253649","page_num":25,"bbox":[70.8,70.8,771.12,443.04],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","(increased cores\nand higher\nfrequency).\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["CIRS Drives","In each HP Z8:\n1TGB NVMe SSD for OS and\nCIRS software.\nTwo 2TB NVMe SSDs for raw\ndata in CIRS S1","In each HP Z8:\n512GB NVMe SSD for OS and\nCIRS software.\nTwo 2TB NVMe SSDs for raw\ndata in CIRS S1.","In each HP Z8:\n512GB NVMe SSD for OS\nand CIRS software.\nTwo 2TB NVMe SSDs for\nraw data in CIRS S1.","One 2TB SSD for the\nresults","Substantially\nequivalent;\nThe proposed\nSpectral CT\nVerida Family\nsystem\nintroduces an\nimprovement to\nCIRS drives\n(increased size\nfor OS and CIRS"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p26-t0","doc_id":"K253649","page_num":26,"bbox":[70.8,70.8,771.12,443.52],"n_rows":6,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","","","software).\nThe verification\nand validation\nfor this\nimprovement\nwere conducted\nand ensured no\nnew questions\non safety and/or\neffectiveness\nwill arise."],["Interventional\nControls","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["GENERAL (SPECTRAL)","","","","",""],["Technical Basis\nfor collection\nof two CT\nSpectra:","Dual Layer DMS (Spectral\nDetector)","Dual Layer DMS (Spectral\nDetector)","Dual Layer DMS (Spectral\nDetector)","Single Layer DMS","Same as\nprimary\npredicate"],["Spectral Base\nImages","• Low-energy\n• High-energy\n• Photoelectric\n• Compton Scatter","• Low-energy\n• High-energy\n• Photoelectric\n• Compton Scatter","• Low-energy\n• High-energy\n• Photoelectric\n• Compton Scatter","N/A","Same as\nprimary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p27-t0","doc_id":"K253649","page_num":27,"bbox":[70.8,70.8,771.12,450.36],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["Spectral results\navailable [kvp]","• 100kvp\n• 120kvp\n• 140kvp","• 100kvp\n• 120kvp\n• 140kvp","• 100kvp\n• 120kvp\n• 140kvp","N/A","Same as\nprimary\npredicate"],["Spectral\nResults Images","• Monoenergetic\n• Materials Basis/Density\nPairs, such as\nI / H20\no\nI / Ca\no\nCa / Uric Acid\no\n• Effective Atomic\nNumber\n• Material Separation/\nDifferentiation\n• Attenuation Curves\n• Density\nMeasurements/Visualiza\ntion\n• Reduction of Beam\nHardening\n• Reduction of Calcium\nBlooming\n• Calcium Suppression\nIndex\n• Electron Density","• Monoenergetic\n• Materials Basis/Density\nPairs, such as\nI / H20\no\nI / Ca\no\nCa / Uric Acid\no\n• Effective Atomic Number\n• Material Separation/\nDifferentiation\n• Attenuation Curves\n• Density\nMeasurements/Visualizat\nion\n• Reduction of Beam\nHardening\n• Reduction of Calcium\nBlooming\n• Calcium Suppression\nIndex\n• Electron Density\n• Spectral results for\nCardiac","• Monoenergetic\n• Materials\nBasis/Density Pairs,\nsuch as\nI / H20\no\nI / Ca\no\nCa / Uric\no\nAcid\n• Effective Atomic\nNumber\n• Material Separation/\nDifferentiation\n• Attenuation Curves\n• Density\nMeasurements/Visu\nalization\n• Reduction of Beam\nHardening\n• Reduction of\nCalcium Blooming\n• Calcium Suppression\nIndex","N/A","Same as\nprimary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p28-t0","doc_id":"K253649","page_num":28,"bbox":[70.8,70.8,771.12,453.36],"n_rows":8,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","• Spectral results for\nCardiac","","• Electron Density\n• Spectral results for\nCardiac","",""],["GENERAL (CONVENTIONAL AND SPECTRAL)","","","","",""],["Perfusion\nmodes","• Axial (increment of zero)\n• Axial Gated (increment\nof zero)\n• Axial Jog (two table\npositions)\n• Helical","• Axial (increment of zero)\n• Axial Gated (increment of\nzero)\n• Axial Jog (two table\npositions)\n• Helical","• Axial (increment of\nzero)\n• Axial Gated\n(increment of zero)\n• Axial Jog (two table\npositions)\n• Helical","• Axial\n(increment of\nzero)\n• Axial Jog (two\ntable positions)","Same as\nprimary\npredicate"],["Virtual Tilt\nViewer (VTV)","Yes","Yes","Yes","Interventional Viewer","Same as\nprimary\npredicate"],["Interventional\ncontrols","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Pulmonary\nGating","Yes","Yes","Yes","N/A","Same as\nprimary\npredicate"],["Pulmo & 4DCT\n(Four-\nDimension","Yes","Yes","No","No","Same as\nprimary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p29-t0","doc_id":"K253649","page_num":29,"bbox":[70.8,70.8,771.12,444.96],"n_rows":8,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["Computed\nTomography)","","","","",""],["Dose\nReduction","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Autovoice","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Localizer","3-axes laser localizer","3-axes laser localizer","3-axes laser localizer","N/A","Same as\nprimary\npredicate"],["Communication","DICOM-3.0","DICOM-3.0","DICOM-3.0","DICOM Compliance","Same as\nprimary\npredicate"],["Cardiac\nRetrospective\nTagging option","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Cardiac\nreconstruction\nmethod","Standard ECG Gated\nReconstruction method\nPrecise Cardiac (optional\nfeature)","Standard ECG Gated\nReconstruction method\nPrecise Cardiac (optional\nfeature)","Standard ECG Gated\nReconstruction method\nMotion Compensated\nReconstruction (MCR)","Standard ECG Gated\nReconstruction\nmethod\nPrecise Cardiac","Same as\nprimary\npredicate"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p30-t0","doc_id":"K253649","page_num":30,"bbox":[70.8,70.8,771.12,454.44],"n_rows":9,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["","","","(optional feature)","(optional feature)",""],["Cardiac Review\nand reporting","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Combine\nImages","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Test Injection\nBolus Timing\n(also known as\nTime Lapse)","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["BolusPro Ultra","Yes","Yes","Yes","No; CANOpen 4\nInjector","Same as\nprimary\npredicate"],["CT Viewer","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["Reporting","Yes","Yes","Yes","Yes","Same as\nprimary\npredicate"],["iDose4 (User\nselectable","Yes","Yes","Yes","Yes","Same as"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253649-p31-t0","doc_id":"K253649","page_num":31,"bbox":[70.8,70.8,771.12,424.68],"n_rows":3,"n_cols":6,"columns":["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],"rows":[["","Proposed Device\nSpectral CT Verida Family","Primary Predicate Device\nSpectral CT 7500 RT (K240844)","Reference Device\nSpectral CT (K203020)","Reference Device\nCT 5300 (K232491)","Note"],["filters)","","","","","primary\npredicate"],["Spectral\nPrecise Image","Yes","No","No","No","Substantially\nequivalent;\nThis algorithm is\nbuilt off the CT\n5300 (K232491)\nclearance that\ncontains the\nPrecise Image\nreconstruction\nalgorithm.\nPlease refer to\nthe Device\nDescription and\nSoftware\nsections, within\nthis eSTAR\nsubmission, for\nmore\ninformation."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253686-p7-t0","doc_id":"K253686","page_num":7,"bbox":[72.26,72.36,530.98,253.8],"n_rows":8,"n_cols":5,"columns":["Specification","","Predicate Device","","Proposed Device\nTrue Definition DL"],"rows":[["Specification","","Predicate Device","","Proposed Device\nTrue Definition DL"],["","","Deep Learning Image Reconstruction","",""],["","","(K213999)","",""],["Patient Population","Patients of all ages","","","Same"],["Reconstruction\nMatrix","512 x 512\n1024 x 1024","","","1024 x 1024"],["Anatomies","Head, Body (including bone and lung), Cardiac","","","Bone and lung"],["Hardware","DLIR is a recon option implemented on the\noperator console for Revolution Apex systems.","","","Same"],["Clinical workflow","Built into routine clinical workflow with 3\nstrengths to select from (Low, Medium, High)","","","Same"]],"caption_candidate":"510(k) Premarket Notification Submission - True Definition DL","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p6-t0","doc_id":"K253735","page_num":6,"bbox":[216.2,655.66,542.95,774.1],"n_rows":4,"n_cols":2,"columns":["Demographics","Number of patients (percentage)"],"rows":[["Demographics","Number of patients (percentage)"],["Geographics","North America: 58 (72.5%)\nEurope: 3 (3.75%)\nAsia: 19 (23.75%)\nNone of these testing data were from the same\nclinical sites which provided the training data."],["Sex","Male: 59 (73.75%)\nFemale: 21 (26.25%)"],["Age (years)","21-50: 2 (2.50%)\n51-70: 31 (38.75%)"]],"caption_candidate":"performance testing is:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p7-t0","doc_id":"K253735","page_num":7,"bbox":[243.05,381.05,369.21,443.11],"n_rows":5,"n_cols":2,"columns":["","Acceptance criteria"],"rows":[["","Acceptance criteria"],["3D","DSC > 0.9"],["2D","DSC > 0.9"],["","MSD < 1.0 mm"],["","HD < 3.0 mm"]],"caption_candidate":"performance statistics and acceptance criteria are:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p8-t0","doc_id":"K253735","page_num":8,"bbox":[45.02,268.91,561.2,777.94],"n_rows":15,"n_cols":8,"columns":["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],"rows":[["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],["","","","","Predicate Device","","",""],["","","","","Philips Medical","","",""],["","","","","Systems'","","",""],["","","","","Multimodality","","",""],["","","","","Advanced Vessel","","",""],["","","","","Analysis (MM","","",""],["","","","","AVA) application","","",""],["","","","","(K203216)","","",""],["Device Class","Class II","Class II","Class II","","","Class II","Identical"],["Classification\nPanel","Radiology","Radiology","Radiology","","","Radiology","Identical"],["Product\nCode","QIH, LLZ","LLZ","JAK","","","JAK, LLZ","Similar to\nprimary\npredicate\ndevice"],["Regulation\nDescription","Medical image\nmanagement and\nprocessing\nsystem","Medical image\nmanagement and\nprocessing\nsystem","Computed\ntomography x-ray\nsystem","","","Computed\ntomography x-ray\nsystem\nMedical image\nmanagement and\nprocessing\nsystem","Identical to\nprimary\npredicate\ndevice"],["Regulation\nNumber","892.2050","892.2050","892.1750","","","892.1750\n892.2050","Identical to\nprimary\npredicate\ndevice"],["Indications\nfor Use","AV Vascular is\nindicated to assist\nusers in the\nvisualization,\nassessment and\nquantification of\nvascular anatomy","3mensio\nWorkstation is a\nstandalone\nsoftware for\nmedical image\nanalysis intended\nfor advanced","The Multimodality\nAdvanced Vessel\nAnalysis (MM AVA)\napplication is\nintended for\nvisualization,\nassessment and","","","The Philips\nSpectral CT\nApplications\nsupport viewing\nand analysis of\nimages at\nenergies selected","Different"]],"caption_candidate":"Table 1. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p9-t0","doc_id":"K253735","page_num":9,"bbox":[45.05,72.36,561.17,766.42],"n_rows":10,"n_cols":8,"columns":["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],"rows":[["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],["","","","","Predicate Device","","",""],["","","","","Philips Medical","","",""],["","","","","Systems'","","",""],["","","","","Multimodality","","",""],["","","","","Advanced Vessel","","",""],["","","","","Analysis (MM","","",""],["","","","","AVA) application","","",""],["","","","","(K203216)","","",""],["","on CTA and/or\nMRA datasets, in\norder to assess\npatients with\nsuspected or\ndiagnosed\nvascular\npathology and to\nassist with pre-\nprocedural\nplanning for\nendovascular\ninterventions.","visualization and\nquantitative\nanalysis for\ndiagnostic and/or\nfor assistance\nduring treatment in\nthe field of\ncardiology or\nradiology by\nmeans of enabling\nvisualization and\nmeasurement of\nstructures of the\nheart and vessels\nfor:\n• Pre-operational\nplanning and\nsizing for\ncardiovascular\ninterventions\nand surgery\n• Postoperative\nevaluation\n• Support of\nclinical diagnosis\nby quantifying\ndimensions in\ncoronary arteries\n• Support of\nclinical diagnosis\nby quantifying\ncalcifications\n(calcium scoring)\nin the coronary\narteries\nTo facilitate the\nabove, the\n3mensio\nWorkstation\nprovides general\nfunctionality such\nas:","quantification of\nvascular datasets.","","","from the available\nspectrum in order\nto provide\ninformation about\nthe chemical\ncomposition of the\nbody materials\nand/or contrast\nagents. The\nSpectral CT\nApplications\nprovide for the\nquantification and\ngraphical display\nof attenuation,\nmaterial density,\nand effective\natomic number.\nThis information\nmay be used by a\ntrained healthcare\nprofessional as a\ndiagnostic tool for\nthe visualization\nand analysis of\nanatomical and\npathological\nstructures.\nThe Spectral\nenhanced\nAdvanced Vessel\nAnalysis (sAVA)\napplication is\nintended to assist\nclinicians in\nviewing and\nevaluating CT\nimages, for the\ninspection of\ncontrast-\nenhanced\nvessels.",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p10-t0","doc_id":"K253735","page_num":10,"bbox":[45.04,72.36,561.18,772.42],"n_rows":16,"n_cols":13,"columns":["Comparison\nFeature","","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","","","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)","",""],"rows":[["Comparison\nFeature","","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","","","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)","",""],["","","","","","Predicate Device","","","","","","",""],["","","","","","Philips Medical","","","","","","",""],["","","","","","Systems'","","","","","","",""],["","","","","","Multimodality","","","","","","",""],["","","","","","Advanced Vessel","","","","","","",""],["","","","","","Analysis (MM","","","","","","",""],["","","","","","AVA) application","","","","","","",""],["","","","","","(K203216)","","","","","","",""],["","","","• Segmentation of\ncardiovascular\nstructures\n• Automatic and\nmanual\ncenterline\ndetection\n• Visualization and\nimage\nreconstruction\ntechniques: 2D\nreview, Volume\nRendering,\nMPR, Curved\nMPR, Stretched\nCMRP,\nSlabbing, MIP,\nAIP, MinIP\n• Measurement\nand annotation\ntools\nReporting tools","","","","The Spectral\nenhanced\nComprehensive\nCardiac Analysis\n(sCCA)\napplication is\nintended to assist\nclinicians in\nviewing and\nevaluating\ncardiovascular CT\nimages.\nThe Spectral\nenhanced Tumor\nTracking (sTT)\napplication is\nintended to assist\nclinicians in\nviewing and\nevaluating CT\nimages, for the\ninspection of\ntumors.","","","","",""],["","Clinical Characteristics","","","","","","","","","","",""],["Intended\nbody part","","Head and neck,\nbody, peripherals","Heart and vessels","Head and neck,\nbody, peripherals","","","Head and neck,\nbody, peripherals","","","Identical to\nsecondary\npredicate\ndevice","",""],["Type of\nscans","","CTA and MRA","CT Angiography","CTA and MRA","","","CT Angiography","","","Identical to\nsecondary\npredicate\ndevice","",""],["","Technological features","","","","","","","","","","",""],["Spectral\ncapabilities","","Yes","No","No","","","Yes","","","Identical to\nreference\ndevice","",""],["Subclavian\nArtery","","Automatic vessel\ncenterline\nextraction of the\nhead, neck and","Automatic vessel\ncenterline\nextraction","Automatic vessel\ncenterline","","","Automatic vessel\ncenterline","","","Different","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253735-p11-t0","doc_id":"K253735","page_num":11,"bbox":[45.03,72.36,561.19,516.19],"n_rows":12,"n_cols":8,"columns":["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],"rows":[["Comparison\nFeature","Subject Device\nPhilips Medical\nSystems' AV\nVascular","Predicate Device\nPie Medical\nImaging’s\n3mensio\nStructural Heart /\n3mensio\nVascular\n(K153736)","","Secondary","","Reference\nDevice\nPhilips Medical\nSystems'\nSpectral CT\nApplications\n(K150665)","Comparison\nbetween the\nsubject and\npredicate\ndevices\n(identical/\ndifferent)"],["","","","","Predicate Device","","",""],["","","","","Philips Medical","","",""],["","","","","Systems'","","",""],["","","","","Multimodality","","",""],["","","","","Advanced Vessel","","",""],["","","","","Analysis (MM","","",""],["","","","","AVA) application","","",""],["","","","","(K203216)","","",""],["Centerline\nExtraction","body including\nshoulder region","","extraction of the\nhead and neck","","","extraction of the\nhead and neck",""],["Aorto-iliac\nOuter Wall\nSegmentatio\nn","Automatic non-AI\nbased vessel\ncontouring of\nmajor vessels.\nAutomatic AI-\nbased vessel\ncontouring\nspecifically for the\naorta and\ncommon and\nexternal iliac\narteries.","No","Automatic non-AI\nbased vessel\ncontouring of major\nvessels, including\nthe aorta and\ncommon and\nexternal iliac\narteries.","","","Automatic non-AI\nbased vessel\ncontouring of\nmajor vessels,\nincluding the\naorta and\ncommon and\nexternal iliac\narteries.","Different"],["Review\nMarker tool","Review Marker\ntool including\nmanual ring\nmarkers, and non-\nAI based\nautomatic ring\nmarkers for the\nostia of the SMA,\nLRA and RRA","Review Marker\ntool including\nmanual ring\nmarkers","Review Marker tool","","","Review Marker\ntool","Different"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253775-p5-t0","doc_id":"K253775","page_num":5,"bbox":[88.58,362.93,523.53,411.31],"n_rows":4,"n_cols":2,"columns":["","Predicate Device: SwiftMR – K230854 by AIRS Medical, Inc., Class II, CFR"],"rows":[["","Predicate Device: SwiftMR – K230854 by AIRS Medical, Inc., Class II, CFR"],["","892.2050, classification with product code LLZ."],["",""],["IV.DEVICE DESCRIPTION",""]],"caption_candidate":"III.PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253775-p7-t0","doc_id":"K253775","page_num":7,"bbox":[90.29,362.54,522.43,710.14],"n_rows":6,"n_cols":6,"columns":["Item","Subject Device\n(SwiftMR)","","Predicate Device #1","","Differences"],"rows":[["Item","Subject Device\n(SwiftMR)","","Predicate Device #1","","Differences"],["","","","(SwiftMR (K230854))","",""],["","","","","",""],["Regulation\nnumber /\nClassification","21 CFR 892.2050 / Class\nII","21 CFR 892.2050 /\nClass II","","","Equivalent"],["Product code","QIH","LLZ","","","Equivalent under\nsame regulation\nnumber"],["Indication for\nuse","SwiftMR is a stand-alone\nmedical imaging software\nsolution intended for the\nacceptance,\nenhancement, processing,\nreview, analysis,\ncommunication, and\ntransfer of all body parts\nMR images in DICOM\nformat. The software may\nbe used for the\nenhancement of medical\nimages, such as noise\nreduction and increased\nimage sharpness for MR\nimages.\nThe device is designed for\nuse by healthcare\nprofessionals and is\nintended to assist","SwiftMR is a stand-\nalone software solution\nintended to be used for\nacceptance,\nenhancement and\ntransfer of all body parts\nMR images in DICOM\nformat. It can be used\nfor noise reduction and\nincreasing image\nsharpness for MR\nimages. SwiftMR is not\nintended for use on\nmobile devices.","","","Equivalent\nThe subject device is\nsubstantially\nequivalent to the\nprimary predicate,\nSwiftMR (K230854),\nas they share the\nsame intended use\nand core technological\nprinciples for MR\nimage processing."]],"caption_candidate":"devices.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253775-p8-t0","doc_id":"K253775","page_num":8,"bbox":[90.26,91.46,522.46,370.49],"n_rows":6,"n_cols":4,"columns":["","clinicians, who remain\nresponsible for making all\nfinal patient management\ndecisions. The device is\nnot intended for use on\nmobile devices.\nThe available filed\nstrengths are as follows:\n0.25T, 0.31T, 0.4T, 0.55T,\n0.6T, 1.5T, and 3.0T.","",""],"rows":[["","clinicians, who remain\nresponsible for making all\nfinal patient management\ndecisions. The device is\nnot intended for use on\nmobile devices.\nThe available filed\nstrengths are as follows:\n0.25T, 0.31T, 0.4T, 0.55T,\n0.6T, 1.5T, and 3.0T.","",""],["Input data","MR images in DICOM\nformat","MR images in DICOM\nformat","Equivalent (MR input\nconsistent with both\npredicates)"],["Output","Enhanced / processed\nMR images in DICOM","Enhanced MR images in\nDICOM","Equivalent"],["Intended\nusers","Healthcare professionals;\nfinal clinical responsibility\nremains with clinician","Same","Equivalent"],["Intended\nenvironment","Healthcare environment","Healthcare environment","Equivalent"],["Enhancement","Noise reduction and\nincreased sharpness","Same (noise reduction,\nsharpening)","Equivalent to\nPredicate device #1\n(K230854)"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p4-t0","doc_id":"K253779","page_num":4,"bbox":[19.27,19.44,593.04,378.24],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK253779 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK253779 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K253779",""],["Please provide the device trade name(s).","",""],["SIGNA TM Sprint Select","",""],["Please provide your Indications for Use below.","","?"],["The SIGNA™ Sprint Select is a whole body magnetic resonance scanner designed to support high\nresolution, high signal-to-noise ratio, and short scan times. It is indicated for use as a diagnostic imaging\ndevice to produce axial, sagittal, coronal, and oblique images, spectroscopic images, parametric maps, and\nor spectra, dynamic images of the structures and/or functions of the entire body, including, but not limited\nto, head, neck, TMJ, spine, breast, heart, abdomen, pelvis, joints, prostate, blood vessels, and\nmusculoskeletal regions of the body. Depending on the region of interest being imaged, contrast agents\nmay be used.\nThe images produced by SIGNATM Sprint Select reflect the spatial distribution or molecular environment of\nnuclei exhibiting magnetic resonance. These images and/or spectra when interpreted by a trained physician\nyield information that mav assist in diaQnosis.\nPlease select the types of uses (select one or both, as [gJ Prescription Use (21 CFR 801 Subpart D)\nD ?\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","",""],["","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p5-t0","doc_id":"K253779","page_num":5,"bbox":[72.0,141.0,539.76,586.56],"n_rows":10,"n_cols":2,"columns":["Date","January 29, 2026"],"rows":[["Date","January 29, 2026"],["Submitter","GE Medical Systems, LLC\n3200 N. Grandview Blvd.\nWaukesha, WI USA 53188"],["Primary\nContact Person","Xinyu Song\nLead Specialist, Regulatory Affairs, MR\nGE HealthCare\nPhone: 86 186 1188 4503\nE-mail: Xinyu.Song@gehealthcare.com"],["Secondary\nContact Person","Glen Sabin\nDirector - Regulatory Affairs, MR Strategy\nGE HealthCare\nPhone: 262 894-4968\nE-mail: Glen.Sabin@gehealthcare.com"],["Device Trade\nName","SIGNATM Sprint Select"],["Common/Usual\nName","Magnetic Resonance Diagnostic Device"],["Classification\nNames","Magnetic Resonance Diagnostic Device per 21 CFR 892.1000"],["Product Code","LNH, LNI, MOS"],["Predicate\nDevice","SIGNATM Sprint (K251399)"],["Reference\nDevice","(1) SIGNATM Champion (K233728)\n(2) SIGNATM Victor (K223439)"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p7-t0","doc_id":"K253779","page_num":7,"bbox":[72.05,533.28,539.95,697.56],"n_rows":4,"n_cols":6,"columns":["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],["","","SIGNATM Sprint","","",""],["","","(K251399)","","",""],["Magnet","1.5T Superconducting\nMagnet with active\nshielding.","","","1.5T Superconducting\nMagnet with active\nshielding.\nThe proposed device\noffers two\nsuperconducting\nmagnet options: the\nIPM magnet and the\nDemeter magnet.","The IPM magnet is identical to the\npredicate device’s magnet.\nThe Demeter magnet is equivalent to\nthe predicate device’s magnet, and\nboth the Demeter and IPM magnets\nhave the same electromagnetic\nperformance."]],"caption_candidate":"predicate/reference devices, as summarized below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p8-t0","doc_id":"K253779","page_num":8,"bbox":[72.02,86.76,539.98,667.56],"n_rows":9,"n_cols":6,"columns":["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],["","","SIGNATM Sprint","","",""],["","","(K251399)","","",""],["Gradient\nSubsystem","A gradient coil with water-cooled, active-shielded\ndesign.","","","","The gradient subsystem of the\nproposed device is equivalent to that\nof the predicate device SIGNA™ Sprint\nand is identical to the gradient\nsubsystem of the reference device\nSIGNA™ Champion."],["RF Transmit\nSubsystem","1.5T Transmit with embedded body coil and local\nT/R coil.","","","","The RF transmit subsystem, excluding\nthe body coil, is identical to the\npredicate device, SIGNA™ Sprint.\nThe body coil is identical to that of the\nreference device, SIGNA™ Champion."],["RF Receive\nSubsystem","1.5T Direct Digital Interface (DDI) receive chain\narchitecture.","","","","The RF receive subsystem is\nsubstantially equivalent to the\npredicate device, SIGNA™ Sprint, with\nan updated FPGA."],["RF Coils –\ndetachable","Comprehensive suite of 1.5T detachable coils for\nimaging all anatomies.","","","","The detachable RF coils are identical to\nthose of the predicate device, SIGNA™\nSprint, with additional compatible coil\noptions."],["RF Coil –\nembedded","1.5T AIR Posterior\nArray","","","1.5T TDI Posterior\nArray or\n1.5T AIR Posterior\nArray","The 1.5T AIR Posterior Array coil is\nidentical to the predicate device,\nSIGNA™ Sprint’s PA coil.\nThe 1.5T TDI Posterior Array coil was\npreviously cleared under K161567."],["Software\nFeatures","Comprehensive suite of software features, pulse\nsequences, and image processing applications to\nsupport MR imaging of all anatomies.","","","","SIGNA™ Sprint Select uses equivalent\nsoftware with predicate and reference\ndevices.\nThe base software platform of the\nproposed device has been modified\nfrom that of the predicate device to\nprovide an updated user interface for\nthe MR system.\nThe proposed device software platform\nfeaturing various productivity\nenhancements that are designed to\nmaximize workflow and reduce scan\ntime."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p9-t0","doc_id":"K253779","page_num":9,"bbox":[72.05,86.76,539.95,168.12],"n_rows":4,"n_cols":6,"columns":["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],"rows":[["Subsystem or\nComponent","","Predicate Device","","Proposed Device\nSIGNATM Sprint Select","Comments"],["","","SIGNATM Sprint","","",""],["","","(K251399)","","",""],["Gating\nAccessories","Respiratory peripheral and cardiac gating with\nwired or wireless connection.","","","","SIGNA™ Sprint Select uses gating\naccessories identical to those of the\npredicate device."]],"caption_candidate":"510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253779-p10-t0","doc_id":"K253779","page_num":10,"bbox":[90.01,107.97,535.55,398.88],"n_rows":15,"n_cols":6,"columns":["","Organization","","","Designation Number and Edition/Date",""],"rows":[["","Organization","","","Designation Number and Edition/Date",""],["ANSI AAMI","","","ES60601-1:2005/(R)2012 & A1:2012, C1:2009/(R)2012 &\nA2:2010/(R)2012 (Cons. Text) [Incl. AMD2:2021]","",""],["IEC","","","60601-1 Edition 3.2 2020-08 CONSOLIDATED VERSION","",""],["IEC","","","60601-2-33 Edition 4.0 2022-08","",""],["ANSI AAMI IEC","","","60601-1-2: 2014 [Including AMD 1:2021]","",""],["ANSI AAMI IEC","","","62304: 2006/A1:2016","",""],["ANSI AAMI ISO","","","10993-1: 2018","",""],["IEC","","","62464-1 Edition 2.0 2018-12","",""],["NEMA","","","MS-1-2008 (R2020)","",""],["NEMA","","","MS 2-2008 (R2020)","",""],["NEMA","","","MS 3-2008 (R2020)","",""],["NEMA","","","MS 4-2023","",""],["NEMA","","","MS 5-2018","",""],["NEMA","","","MS 8-2016 (R2003)","",""],["NEMA","","","PS 3.1 - 3.20 2023e","",""]],"caption_candidate":"Testing to the following voluntary standards included:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253780-p5-t0","doc_id":"K253780","page_num":5,"bbox":[72.72,132.12,540.24,459.6],"n_rows":11,"n_cols":2,"columns":["Date","November 26, 2025"],"rows":[["Date","November 26, 2025"],["Submitter","GE Medical Systems, LLC\n3200 N. Grandview Blvd.\nWaukesha, WI 53188"],["Primary Contact","Emily Fang\nRegulatory Affairs Leader\n609-285-9878\nsigna.bolt.premarket@gehealthcare.com"],["Secondary Contact","Sandra Bahling\nSenior Regulatory Affairs Leader\n262-720-8872\nSandra.Westphal@gehealthcare.com\nGlen Sabin\nRegulatory Affairs Director\n262-894-4968\nGlen.Sabin@gehealthcare.com"],["Device Trade Name","SIGNATM Bolt"],["Common/Usual Name","MR System"],["Classification Name","Magnetic Resonance Diagnostic Device"],["Regulation Number","21 CFR 892.1000"],["Product Code","LNH, LNI, MOS"],["Predicate Device(s)","SIGNATM Premier (K193282)"],["Reference Device(s)","SIGNATM Victor (K223439)"]],"caption_candidate":"In according with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253780-p5-t1","doc_id":"K253780","page_num":5,"bbox":[106.37,610.92,506.47,706.92],"n_rows":4,"n_cols":3,"columns":["Specification","SIGNATM Bolt – SuperXG Gradient","SIGNATM Bolt – SuperXF Gradient"],"rows":[["Specification","SIGNATM Bolt – SuperXG Gradient","SIGNATM Bolt – SuperXF Gradient"],["Magnet","3.0T superconducting magnet with a wide (70 cm) bore size and\nactive shielding",""],["Maximum\nGradient Strength","80 mT/m","65 mT/m"],["Maximum Slew\nRate","200 T/m/s","200 T/m/s"]],"caption_candidate":"The SIGNATM Bolt system will be offered as two commercial configurations with the following features:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253780-p6-t0","doc_id":"K253780","page_num":6,"bbox":[106.35,76.56,506.49,295.92],"n_rows":7,"n_cols":3,"columns":["Specification","SIGNATM Bolt – SuperXG Gradient","SIGNATM Bolt – SuperXF Gradient"],"rows":[["Specification","SIGNATM Bolt – SuperXG Gradient","SIGNATM Bolt – SuperXF Gradient"],["RF Transmit","A liquid cooled In-Scan-Room RF transmit architecture with a\npeak power capability of 36 kW and 3.0T Platform Body Coil",""],["RF Receive Chain","162 Ch available","130 Ch available"],["Patient Table","Detachable SIGNA One Patient Table with embedded 3.0T AIR PA\nXL coil and up to four 32-channel high density auto-coil sensing\nconnection ports",""],["Power Rating","113 kVA","90 kVA"],["Software","Software platform featuring various productivity enhancement\nfeatures, designed to improve workflow and reduce scan time\n• AIRx (previously cleared in K183231) – AI-based\nautomated slice prescription tool now extended with new\ndeep learning models for spine and prostate imaging\n• SIGNA One Camera – Real-time AI-enabled image\nguidance that assists with automated patient positioning",""],["Gating Options","Wired, wireless, and contactless physiological gating options",""]],"caption_candidate":"Traditional 510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253780-p7-t0","doc_id":"K253780","page_num":7,"bbox":[72.3,76.56,539.73,718.56],"n_rows":12,"n_cols":4,"columns":["Subsystem or","Predicate Device","Proposed Device","Comments"],"rows":[["Subsystem or","Predicate Device","Proposed Device","Comments"],["","SIGNATM","",""],["Component","","SIGNATM Bolt",""],["","Premier","",""],["","","",""],["","(K193282)","",""],["Magnet","3.0T superconducting magnet with active shielding.","","Identical. SIGNATM Bolt uses the same\ntype of magnet as used in the\npredicate device."],["Gradient Coil","HRMW gradient coil with\nwater-cooled, active-\nshielded design.","ZRMW gradient coil with\nwater-cooled, active-\nshielded design.","Substantially Equivalent. The ZRMW\ngradient coil decreases heat\ngeneration and lowers the\ntemperature of the inner bore.\nThese differences do not impact\nsafety or efficacy."],["RF Transmit\nSubsystem","A liquid cooled RF\ntransmit architecture\nwith a peak power\ncapability of 30 kW and\n3.0T RF body coil.","A liquid cooled In-Scan-\nRoom RF transmit\narchitecture with a peak\npower capability of 36\nkW and 3.0T Platform\nBody Coil.","Substantially Equivalent. The\nPlatform Body Coil used in SIGNATM\nBolt is the same as the predicate\ndevice with design modifications to\nreduce heat dissipation. SIGNATM\nBolt also uses a newly designed In-\nScan-Room (ISR) Transmit Driver\nwhich moves all the transmit driver\ncomponents except the ISR Support\nUnit inside the scan room as\ncompared to the equipment room\nfor the predicate device. These\nmodifications do not raise any new\nconcern of safety or effectiveness."],["RF Receive\nSubsystem","3.0T Digitize-Per-Pin (DPP) receive chain architecture.","","Identical. SIGNATM Bolt uses the same\ntype of RF receive subsystem as used\nin the predicate device."],["Gating Options","Respiratory peripheral\nand cardiac gating with\nwired and wireless\nconnection.","Respiratory peripheral\nand cardiac gating with\nwired and wireless\nconnection. Contactless\nperipheral cardiac and\nrespiratory gating.","Substantially Equivalent. SIGNATM\nBolt offers the same wired and\nwireless gating capabilities as the\npredicate device. SIGNATM Bolt\nintroduces contactless gating,\nenabling peripheral cardiac and\nrespiratory triggered MR exams\nwithout the need for physical\nattachment of monitoring\naccessories. This modification does\nnot raise any new\nconcern of safety or effectiveness."],["Software\nFeatures","Comprehensive suite of software features, pulse\nsequences, and image processing applications to\nsupport MR imaging of all anatomies.","","Substantially Equivalent. SIGNATM\nBolt software is based off that of\nreference device SIGNATM Victor,\nbringing additional parity with\nfeatures available on the predicate\ndevice software platform along with\nmodifications and enhancements to\nexisting features. The modifications\ndo not raise any new concern of\nsafety or effectiveness."]],"caption_candidate":"Traditional 510(k) Premarket Notification","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253796-p5-t0","doc_id":"K253796","page_num":5,"bbox":[56.84,245.09,554.88,475.63],"n_rows":4,"n_cols":2,"columns":["Applicant Information","Lunit Inc.\n4-8 F, 374, Gangnam-daero, Gangnam-gu,\nSeoul, 06241, Republic of Korea\nTel: + 82-2-2138-0827\nFax: +82-2-6919-2702"],"rows":[["Applicant Information","Lunit Inc.\n4-8 F, 374, Gangnam-daero, Gangnam-gu,\nSeoul, 06241, Republic of Korea\nTel: + 82-2-2138-0827\nFax: +82-2-6919-2702"],["Primary Correspondent","Hyeseung Yoo,\nSr. Regulatory Affairs Specialist\nEmail: hsyoo@lunit.io"],["Secondary Correspondents","Juyoung Jung,\nRegulatory Affairs Specialist\nEmail: jjyoung@lunit.io\nSulgue Choi\nRegulatory Affairs Team Leader\nEmail: sulgue@lunit.io"],["Date Prepared","November 28, 2025"]],"caption_candidate":"1. Submitter","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253796-p5-t1","doc_id":"K253796","page_num":5,"bbox":[56.84,543.65,554.88,684.53],"n_rows":6,"n_cols":2,"columns":["Name of Device","Lunit INSIGHT DBT (V1.2)"],"rows":[["Name of Device","Lunit INSIGHT DBT (V1.2)"],["Version","1.2"],["Classification Name","Radiological Computer-Assisted Detection And Diagnosis Software"],["Regulation","21 CFR 892.2090"],["Classification","Class II"],["Product code","QDQ"]],"caption_candidate":"Subject Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253796-p7-t0","doc_id":"K253796","page_num":7,"bbox":[56.84,116.96,555.47,652.53],"n_rows":12,"n_cols":9,"columns":["Item","","","Subject Device","","","Predicate Device","",""],"rows":[["Item","","","Subject Device","","","Predicate Device","",""],["","","","","Lunit INSIGHT DBT v1.2","","","Lunit INSIGHT DBT v1.1",""],["Classification Name","","","Radiological Computer Assisted\nDetection/Diagnosis Software For Suspicious\nLesions For Cancer","","","Radiological Computer Assisted\nDetection/Diagnosis Software For Suspicious\nLesions For Cancer","",""],["Regulation","","","21 CFR 892.2090","","","21 CFR 892.2090","",""],["Regulatory Class","","","Class II","","","Class II","",""],["Product Code","","","QDQ","","","QDQ","",""],["Indication for Use","","","Lunit INSIGHT DBT is a computer-assisted\ndetection and diagnosis (CADe/x) software\nintended to be used concurrently by\ninterpreting physicians to aid in the detection\nand characterization of suspected lesions for\nbreast cancer in digital breast tomosynthesis\n(DBT) exams from compatible DBT systems.\nThrough the analysis, the regions of soft\ntissue lesions and calcifications are marked\nwith an abnormality score indicating the\nlikelihood of the presence of malignancy for\neach lesion. Lunit INSIGHT DBT uses screening\nmammograms of the female population.\nLunit INSIGHT DBT is not intended as a\nreplacement for a complete interpreting\nphysician’s review or their clinical judgment\nthat takes into account other relevant\ninformation from the image or patient\nhistory.","","","Lunit INSIGHT DBT is a computer-assisted\ndetection and diagnosis (CADe/x) software\nintended to be used concurrently by\ninterpreting physicians to aid in the detection\nand characterization of suspected lesions for\nbreast cancer in digital breast tomosynthesis\n(DBT) exams from compatible DBT systems.\nThrough the analysis, the regions of soft\ntissue lesions and calcifications are marked\nwith an abnormality score indicating the\nlikelihood of the presence of malignancy for\neach lesion. Lunit INSIGHT DBT uses screening\nmammograms of the female population.\nLunit INSIGHT DBT is not intended as a\nreplacement for a complete interpreting\nphysician’s review or their clinical judgment\nthat takes into account other relevant\ninformation from the image or patient\nhistory.","",""],["","Target patient","","Women undergoing mammography","","","Women undergoing mammography","",""],["","population","","","","","","",""],["Intended user","","","Physicians interpreting screening\nmammograms","","","Physicians interpreting screening\nmammograms","",""],["Input Image Source","","","DBT","","","DBT","",""],["Fundamental\nTechnological Basis","","","Lunit INSIGHT DBT is powered by artificial\nintelligence/machine learning-based software\nalgorithm","","","Lunit INSIGHT DBT is powered by artificial\nintelligence/machine learning-based software\nalgorithm","",""]],"caption_candidate":"5. Summary of Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p6-t0","doc_id":"K253818","page_num":6,"bbox":[72.32,149.24,539.76,248.2],"n_rows":5,"n_cols":4,"columns":["","Company Name","","Harrison-AI Medical Pty Ltd"],"rows":[["","Company Name","","Harrison-AI Medical Pty Ltd"],["Address","Address","","Level P, 24 Campbell Street\nSydney, NSW 2000\nAustralia"],["","Phone Number","","+61 1800-958487"],["","Contact Person","","Haylee Bosshard"],["","Date Prepared","","February 11, 2026"]],"caption_candidate":"SUBMITTER","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p6-t1","doc_id":"K253818","page_num":6,"bbox":[72.32,291.32,539.76,376.36],"n_rows":5,"n_cols":4,"columns":["","Manufacturer Name","","Harrison-AI Medical Pty Ltd"],"rows":[["","Manufacturer Name","","Harrison-AI Medical Pty Ltd"],["","Device Name","","Annalise Enterprise"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21 CFR 892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"SUBJECT DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p6-t2","doc_id":"K253818","page_num":6,"bbox":[72.32,419.48,539.76,518.92],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","iSchemaView, Inc."],"rows":[["","Manufacturer Name","","iSchemaView, Inc."],["","Device Name","","Rapid NCCT Stroke"],["","510(k) reference","","K222884"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21 CFR 892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"PREDICATE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p6-t3","doc_id":"K253818","page_num":6,"bbox":[72.32,575.72,539.76,675.16],"n_rows":6,"n_cols":4,"columns":["","Manufacturer Name","","Aidoc Medical, Ltd."],"rows":[["","Manufacturer Name","","Aidoc Medical, Ltd."],["","Device Name","","BriefCase"],["","510(k) reference","","K220709"],["Classification Name","Classification Name","","Radiological computer aided triage and notification software\n(21 CFR 892.2080)"],["","Regulatory Class","","II"],["","Product Code","","QAS"]],"caption_candidate":"REFERENCE DEVICE","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p11-t0","doc_id":"K253818","page_num":11,"bbox":[72.28,82.54,560.96,715.56],"n_rows":3,"n_cols":8,"columns":["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],"rows":[["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],["","","","Stroke, K222884)","","","K220709)",""],["Indications for\nuse","Intended context\nAnnalise Enterprise is a device designed\nto be used in the medical care\nenvironment to aid in triage and\nprioritization of studies with features\nsuggestive of the following findings:\n• acute infarct*\n*See Additional Information below.\nThe device analyzes studies using an\nartificial intelligence algorithm to\nidentify findings. It makes study-level\noutput available to an order and imaging\nmanagement system for worklist\nprioritization or triage.\nThe device is not intended to direct\nattention to specific portions of an image\nand only provides notification for\nsuspected findings.\nIts results are not intended:\n• to be used on a standalone basis for\nclinical decision making\n• to rule out specific findings, or\notherwise preclude clinical\nassessment of non-contrast\ncomputed tomography brain\nIntended modality\nAnnalise Enterprise identifies suspected\nfindings in non-contrast brain CT\nstudies.\nIntended user\nThe device is intended to be used by\ntrained clinicians who are qualified to\ninterpret CTB studies as part of their\nscope of practice.\nIntended patient population\nThe intended population is patients who\nare 22 years or older.\nAdditional information\nThe device includes acute infarct of the\ncerebral hemispheres or cerebellum, also\nincluding early signs of acute middle\ncerebral artery (MCA) infarct such as","Rapid NCCT Stroke is a radiological\ncomputer aided triage and notification\nsoftware indicated for use in the\nanalysis of (1) nonenhanced head CT\n(NCCT) images. The device is\nintended to assist hospital networks\nand trained clinicians in workflow\ntriage by flagging and communicating\nsuspected positive findings of (1) head\nCT images for Intracranial\nHemorrhage (ICH) and (2) NCCT\nlarge vessel occlusion (LVO) of the\nICA and MCA-M1.\nRapid NCCT Stroke uses an artificial\nintelligence algorithm to analyze\nimages and highlight cases with\ndetected (1) ICH or (2) NCCT LVO on\nthe Rapid server on premise or in the\ncloud in parallel to the ongoing\nstandard of care image interpretation.\nThe user is presented with notifications\nfor cases with suspected ICH or LVO\nfindings via PACS, email or mobile\ndevice. Notifications include\ncompressed preview images that are\nmeant for informational purposes only,\nand are not intended for diagnostic use\nbeyond notification.\nThe device does not alter the original\nmedical image, and it is not intended to\nbe used as a primary diagnostic device.\nThe results of Rapid NCCT Stroke are\nintended to be used in conjunction with\nother patient information and based on\nprofessional judgment to assist with\ntriage/prioritization of medical images.\nNotified clinicians are ultimately\nresponsible for reviewing full images\nper the standard of care. Rapid NCCT\nStroke is for Adults only.\nCautions:\n• All patients should get adequate\ncare for their symptoms\nincluding CTA and/or other\nappropriate care per the standard\nclinical practice, irrespective of\nthe device output.\n• The device is not intended to be a\nrule-out device and for cases that\nhave been processed by the\ndevice without notification for\n“Suspected LVO” should not be\nviewed as indicating that LVO is\nexcluded. All cases should\nundergo CTA, per the standard\nstroke workup.","","","BriefCase is a radiological computer\naided triage and notification software\nindicated for use in the analysis of\nhead CTA images in adults or\ntransitional adolescents aged 18 and\nolder. The device is intended to assist\nhospital networks and appropriately\ntrained medical specialists in workflow\ntriage by flagging and communication\nof suspected positive findings of\ncomplete Large Vessel Occlusion\n(LVO) - MCA-M1, PCA-P1, ACA-\nA1, ICA, Basilar; and Medium Vessel\nOcclusions (MeVO) - MCA-M2,\nMCA-proximal M3, PCA-P2, PCA-\nproximal P3, ACA-A2, ACA-proximal\nA3, and Vertebral-V4.\nBriefCase uses an artificial intelligence\nalgorithm to analyze images and\nhighlight cases with detected findings\non a standalone desktop application in\nparallel to the ongoing standard of care\nimage interpretation. The user is\npresented with notifications for cases\nwith suspected findings. Notifications\ninclude compressed preview images\nthat are meant for informational\npurposes only and not intended for\ndiagnostic use beyond notification.\nThe device does not alter the original\nmedical image and is not intended to\nbe used as a diagnostic device.\nThe results of BriefCase are intended\nto be used in conjunction with other\npatient information and based on their\nprofessional judgment, to assist with\ntriage/prioritization of medical images.\nNotified clinicians are responsible for\nviewing full images per the standard of\ncare.","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p12-t0","doc_id":"K253818","page_num":12,"bbox":[72.26,82.42,560.98,700.92],"n_rows":6,"n_cols":8,"columns":["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],"rows":[["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],["","","","Stroke, K222884)","","","K220709)",""],["","insular ribbon sign and disappearing\nbasal ganglia sign.\nThe infarct must be a completed infarct\n(i.e. include an ischemic core of ≥5mL).\nThe device also includes hyperdense\nartery in the anterior circulation but does\nnot include lacunar infarcts, brainstem\ninfarcts or venous infarcts.\nThe radiological device definition of\nacute infarct includes the following\nterritories and regions:\n• anterior cerebral artery (ACA)\n• middle cerebral artery (MCA)\n• posterior cerebral artery (PCA)\n• cerebellum\n• basilar artery occlusions\n• watershed regions\nSpecificity may be reduced in the\npresence of infarcts of <5mL.\nCaution:\n• All patients should get adequate\ncare for their symptoms, including\nadvanced imaging (e.g., CTA,\nCTP, MRI, etc.) and/or other\nappropriate care per standard\nclinical practice, irrespective of the\ndevice output.\n• The device is not intended to be a\nrule-out device and for cases that\nhave been processed by the device,\nan absence of a notification for\nsuspected acute infarct should not\nbe viewed as indicating that acute\ninfarct is excluded..\nLimitations:\n• The device does not replace the\nneed for advanced imaging in the\nstroke workup. It provides\nworkflow prioritization and\nnotification only.","Limitations:\n• Rapid NCCT Stroke does not\nreplace the need for CTA or\nMRA in ischemic stroke workup,\nit provides workflow\nprioritization and notification\nonly.\n• Rapid ICH has been shown to\nreliably identify hemorrhages of\n≥ 0.4ml.\nContraindications/Exclusions\n• Patient Motion: excessive motion\nleading to artifacts that make the\nscan technically inadequate.\n• Hemorrhagic Transformation,\nHematoma\n• Very thin or no Ventricles","","","","",""],["Target\npopulation","Adults only","Adults only","","","Adults or transitional adolescents aged\n18 and older","",""],["Anatomical site\nand modality","Non-contrast brain CT","Non-contrast brain CT","","","Head CTA","",""],["Intended user\nand clinical use\nenvironment","Trained clinicians who, as part of their\nscope of practice, are qualified to\ninterpret brain CT scans","Hospital networks and trained\nclinicians","","","Hospital networks and appropriately\ntrained medical specialists","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p13-t0","doc_id":"K253818","page_num":13,"bbox":[72.26,82.42,560.98,715.8],"n_rows":8,"n_cols":8,"columns":["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],"rows":[["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],["","","","Stroke, K222884)","","","K220709)",""],["Finding of\ninterest","Acute infarct of the cerebral hemispheres\nor cerebellum, also including early signs\nof acute middle cerebral artery (MCA)\ninfarct such as insular ribbon sign and\ndisappearing basal ganglia sign.\nThe infarct must be a completed infarct\n(i.e., include an ischemic core of ≥5mL).\nThe device also includes hyperdense\nartery in the anterior circulation but does\nnot include lacunar infarcts, brainstem\ninfarcts or venous infarcts.\nThe radiological device definition\nincludes the following territories and\nregions:\n• Anterior cerebral artery (ACA)\n• Middle cerebral artery (MCA)\n• Posterior cerebral artery (PCA)\n• Cerebellar regions\n• Basilar artery occlusion\n• Watershed regions","(Comparison made to only LVO\nportion of device)\nLarge vessel occlusions within the ICA\nand MCA-M1, identified by\nhyperdense vessel sign","","","Large Vessel Occlusion (LVO) -\nMCA-M1, PCA-P1, ACA-A1, ICA,\nBasilar; and Medium Vessel\nOcclusions (MeVO) - MCA-M2,\nMCA-proximal M3, PCA-P2, PCA-\nproximal P3, ACA-A2, ACA-proximal\nA3, and Vertebral-V4","",""],["Device input and\nradiological\nimage protocol","DICOM-compliant non-contrast brain\nCT scans\nAttributes model: Determines which\nseries the algorithm processes based on\npixel data to maximize the proportion of\nseries that are appropriately analyzed by\nAI","DICOM-compliant non-contrast brain\nCT scans","","","DICOM-compliant head CTA scans\naiOS: Determines which series the\nalgorithm processes based on pixel\ndata to maximize the proportion of\nstudies that are appropriately analyzed\nby AI","",""],["Device output\nand means of\nnotification to\nuser","Notifications via customizable\nworkflows into existing systems (e.g.,\nPACS, RIS, TigerConnect, Epic, etc.).\nA non-diagnostic viewer, where users\ncan preview DICOM image series, is\nprovided. This viewer is for\ninformational purposes only.","Notifications via PACS, email, or\nmobile device\nA non-diagnostic viewer, where users\ncan preview DICOM image series, is\nprovided. This viewer is for\ninformational purposes only.","","","Notifications via Aidoc Desktop\nApplication, a dedicated tool requiring\nnew workflows and integrations.\nA non-diagnostic viewer, where users\ncan preview DICOM image series, is\nprovided. This viewer is for\ninformational purposes only.","",""],["System\ncomponents","Software architecture (Integration\nAdapter and Backend API services)\nhandles image transmission,\nstorage/security management and output\nto medical worklist software.","AI/ML SaMD within the Rapid\nPlatform including DICOM\nprocessing, job management, imaging\nmodule execution and imaging output\nincluding the notification and\ncompressed image.","","","(1) Aidoc Hospital Server\n(AHS/Orchestrator) for image\nacquisition; (2) Aidoc Cloud Server\n(ACS) for image processing; and (3)\nAidoc Desktop Application for\nworkflow integration","",""],["Prioritization\nrelationship to\nstandard of care\nworkflow","Operates parallel to and independent of\nthe current clinical workflow\n(No cases are removed from the\nworklist)","Operates parallel to and independent of\nthe current clinical workflow\n(No cases are removed from the\nworklist)","","","Operates parallel to and independent of\nthe current clinical workflow\n(No cases are removed from the\nworklist)","",""],["Performance\nlevel – Sensitivity\nand Specificity","Operating point 1 (≤1.5mm):\nSe: 89.2% (95% CI: 85.8,92.6)\nSp: 84.1% (95% CI: 81.5,86.9)\nOperating point 2 (≤1.5mm):\nSe: 88.5 (95% CI: 84.8, 92.0)\nSp: 87.5 (95% CI: 85.0, 89.8)\nOperating point 3 (≤1.5mm):\nSe: 87.3 (95% CI: 83.6, 91.0)","Operating point 1:\nSe: 63.5% (95% CI: 54.4, 71.7)\nSp: 95.1% (95% CI: 89.1, 97.9)\n(For LVO indication only one\noperating point reported)","","","Operating point 1:\nSe: 91.3% (95% CI: 83.6, 96.2)\nSp: 85.6% (95% CI: 80.6, 89.7)\nOperating point 2:\nSe: 91.3% (95% CI: 83.58, 96.17)\nSp: 85.2% (95% CI: 80.18, 89.36).","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p14-t0","doc_id":"K253818","page_num":14,"bbox":[72.27,82.42,560.97,471.24],"n_rows":4,"n_cols":8,"columns":["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],"rows":[["Characteristics","Subject Device (Annalise Enterprise)","","Predicate Device (Rapid NCCT","","","Reference Device (Aidoc BriefCase,",""],["","","","Stroke, K222884)","","","K220709)",""],["","Sp: 89.8 (95% CI: 87.5, 91.9)\nOperating point 4 (≤1.5mm):\nSe: 86.1 (95% CI: 82.4,89.8)\nSp: 91.4 (95% CI: 89.3,93.4)\nOperating point 5 (≤1.5mm):\nSe: 84.5 (95% CI: 80.5, 88.5)\nSp: 93.1 (95% CI: 91.1, 95.0)\nOperating point 6 (>1.5mm&≤5.0mm):\nSe: 85.7 (95% CI: 81.9, 89.2)\nSp: 83.2 (95% CI: 80.3, 85.9)\nOperating point 7 (>1.5mm&≤5.0mm):\nSe: 85.7 (95% CI: 81.9, 89.2)\nSp: 84.4 (95% CI: 81.8, 87.0)\nOperating point 8 (>1.5mm&≤5.0mm):\nSe: 84.8 (95% CI: 81.0, 88.3)\nSp: 85.6 (95% CI: 82.9, 88.1)\nOperating point 9 (>1.5mm&≤5.0mm):\nSe: 83.4 (95% CI: 79.3, 87.2)\nSp: 87.0 (95% CI: 84.3, 89.3)\nOperating point 10 (>1.5mm&≤5.0mm):\nSe: 78.1 (95% CI: 73.8,82.5)\nSp: 91.9 (95% CI: 89.8,93.9)","","","","","",""],["Triage\neffectiveness\nperformance\nlevel – Turn-\naround time","81.6 (95% CI: 80.3 – 82.9) seconds","2.5 (95% CI: 2.4, 2.6) minutes","","","2.23 minutes (95% CI: 2.22-2.23)","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p15-t0","doc_id":"K253818","page_num":15,"bbox":[57.03,176.2,544.3,678.6],"n_rows":4,"n_cols":9,"columns":["","Characteristic","","","Benefit of difference","","","Risk of difference and mitigations",""],"rows":[["","Characteristic","","","Benefit of difference","","","Risk of difference and mitigations",""],["Modality: NCCT\nsame as Rapid\nNCCT Stroke but\ndifferent from\nAidoc (CTA)","","","In some advanced stroke imaging centers, CTA and CT perfusion may\nbe performed immediately after NCCT, while the patient is still on the\nscanner table. However, AHA/ASA guidelines recommend\ninterpretation of NCCT and determination of IV-tPA eligibility and,\nwhere indicated, immediate administration prior to advanced imaging\nto determine candidacy for endovascular treatment (Powers, et al.,\n2019).\nFor facilities following the steps recommended by these guidelines,\nprioritization and time savings based on the initial NCCT is critical.\nFurthermore, care coordination is dependent on the acquisition of\nCTA/CTP images. If notification can be initiated earlier, this could help\nspeed up surgical preparation teams and communication of the\nimpending patient to specialist teams.","","","NCCT is a less advanced imaging modality than\nCTA and based on literature it could be expected that\ninfarct detection on NCCT would have much poorer\nperformance. However, the infarct cases of the\npivotal study were ground truthed with availability\nof advanced imaging modality data. There are\nmultiple operating points that exceeded the typical,\nbut not prescriptive, 80% sensitivity/80% specificity\nbar in triage devices.","",""],["Territory\ncoverage: more\ncomprehensive\nthan Rapid NCCT\nStroke but similar\nto Aidoc Briefcase","","","Territories and regions compared to Rapid (primary predicate):\n• According to the 2019 Update to the Guidelines for the Early\nManagement of Acute Ischemic Stroke, mechanical\nthrombectomy may be considered in LVO patients outside of the\nICA and M1 segments, including the vessel regions triaged by the\nsubject device, if treatment can be initiated within 6 hours of\nsymptom onset.\n• Given that MCA infarcts due to LVO account for approximately\nonly 30% of patients with acute ischemic strokes (AIS)\n(Lakomkin, et al., 2019) (Rennert, et al., 2019) an additional\n~70% of AIS patients are currently not triaged on NCCT by the\nRapid NCCT Stroke device. Furthermore, the clinical benefit of\nIV-tPA may be limited in LVO patients (Hassan, 2021), whereas\npatients with posterior circulation stroke account for up to 36% of\nacute stroke patients receiving IV-tPA treatment (Keselman, et al.,\n2020).\nIn comparison to the Aidoc reference device, the territories and regions\nare similarly comprehensive. (The subject device also includes\ncerebellum and watershed regions in its Indications for Use.)","","","The subject device may not be performant in\nadditional territories or regions (especially the rarer\nlocations/regions for infarct), but that risk has been\nmitigated by subgroup analysis of a sufficient\nnumber of test cases across different territories and\nregions.","",""],["Conclusion","","","• Additional benefit compared to Rapid NCCT LVO because of\nadditional territories and regions, which may result in up to 70%\nmore AIS patients being triaged based on the literature quoted\nabove.\n• Additional benefit compared to Aidoc BriefCase because triage of\npatients with potential ischemic stroke can happen earlier in the\nclinical workflow, at least for a subset of patients that may not\nreceive CTA at the same time as NCCT.","","","• Lower risk than Rapid because of\ndemonstrated higher sensitivity (while\nmaintaining >80% specificity) at all available\noperating points.\n• Similar risk to Aidoc: While the triage is based\non NCCT (in comparison to CTA or other\nadvanced imaging which is recognized as\nmore sensitive in identifying ischemic stroke),\nthe ground truthing included availability of an\nadvanced imaging modality. Furthermore,\nmultiple operating points exceeded 80%\nsensitivity/80% specificity.","",""]],"caption_candidate":"Benefit/Risk Summary Compared to Predicate and Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p17-t0","doc_id":"K253818","page_num":17,"bbox":[62.66,272.8,551.38,730.2],"n_rows":6,"n_cols":6,"columns":["","Patient group","","","Current state",""],"rows":[["","Patient group","","","Current state",""],["Not immediately allocated to\na stroke workflow due to an\ninitial missed or delayed\ndiagnosis","","","Unsuspected infarct prior to NCCT: A retrospective study within the US that reviewed patient charts over a one-\nyear period at two separate hospitals, found ~20% of ischemic stroke patients were missed in the emergency\ndepartment despite presenting within the appropriate time window for thrombolytic treatment (Arch, et al., 2016).\nSuspected infarct prior to NCCT: Even for patients suspected of acute infarct prior to NCCT, not all are\nimmediately placed on a stroke workflow. For example, a clinician may consider multiple diagnoses when a patient\npresents with stroke-like symptoms. The presence of negative and positive neurologic symptoms may lead a\nclinician to suspect stroke and multiple other stroke mimics (Boushra & Lui., 2025). The positive predictive value\nfor infarct is lower in patients who are more stable, for example those who can ambulate and arrive at an emergency\ndepartment by personal vehicle. These patients are less likely to be immediately put on a stroke workflow, even if\nthey present with signs of stroke.","",""],["Hospital inpatients","","","Up to 17% of strokes occur in patients already hospitalized (Cumbler E. , 2015). Inpatients experiencing stroke\nhave worse outcomes than those who have stroke in the community (Cumbler E. , 2015) (Cumbler, et al., 2014). In\nmany cases in-hospital strokes are silent and only detected on routine post- operative imaging; symptomatic\npresentation is often non-specific and difficult to identify as patients are impacted by anesthesia, other medications\nor are intubated (Benesch, et al., 2021). The median time to treatment for in-patient strokes averaged 100 minutes\n(vs 76 minutes for community onset) (Zachrison, et al., 2022), and only one in five patients within-hospital stroke\nwere treated within the recommended 60-minute target, despite already being in a hospital setting (Cumbler, et al.,\n2014).","",""],["Regional, rural, or low-\nincome patients","","","Regional patients also have poorer outcomes and higher in-hospital mortality associated with longer time to\ntreatment. (Hammond, Luke, Elson, Towfighi, & Maddox, 2020).\nAn analysis of data from 2009 to 2019 found that hospitals located in low-income and rural communities had a\nlower likelihood of receiving stroke certification than hospitals in general communities. When adjusting the model\nfor population size, it was also discovered that patients in Black, racially segregated communities had the lowest\nlikelihood of access to stroke-certified hospitals (Shen, Sarkar, & Hsia, 2022).\nAnother study that looked at data of 5055 US hospitals from 2009 to 2022 found that hospitals in communities with\nthe greatest level of disadvantage had the lowest likelihood of adopting specialized stroke care services while those\nin the most advantaged communities had the highest likelihood. In fact, these were 20% to 42% less likely to\nbecome stroke-certified compared with hospitals near mixed-advantage communities (Shen, Sarkar, & Hsia, 2022).","",""],["Patients treated at hospitals\nwithout well-established\nstroke protocols","","","Of the 5533 hospital emergency departments on record in the United States, 56% do not include recognized stroke\ncenters, with services that can range from comprehensive stroke management to initiation of care before transferring\nto a larger hospital (Boggs, et al., 2022).\nA 2020-2021 survey of emergency departments participating in the ACEP Emergency Quality Network (E-QUAL)\nStroke Collaborative found that only 67% of respondents had a written acute stroke protocol (Zachrison, et al.,\n2022). A hospital without a stroke protocol may not have a well-established process for ensuring appropriate\nmembers of the care team are available, specifically a neuroradiologist is available to read the case as soon as the\nimage is acquired.","",""],["Patients admitted outside\nnormal hours","","","Patients may also experience disparities in stroke care based on the day or time of day of admission. For example,\nin a recent US study at an institution with a comprehensive stroke center and over 80,000 patient visits per year,","",""]],"caption_candidate":"consider the current state of care for a diverse patient population, as summarized below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p18-t0","doc_id":"K253818","page_num":18,"bbox":[62.67,69.4,551.37,222.0],"n_rows":3,"n_cols":6,"columns":["","Patient group","","","Current state",""],"rows":[["","Patient group","","","Current state",""],["","","","the median door to needle time was 22 minutes longer during night shift vs during day shift (59 min vs 37 min).\nWhen a dedicated stroke team was present, the median door to needle time was 36 min, compared to 51 min when\nthey were not present (Ganti, et al., 2023). Similar delays may be encountered at some facilities over weekends\nwhen staff are reduced.","",""],["Patients even in stroke centers","","","There's evidence that many stroke centers do not meet timeline goals for treatment of patients who are identified\nas suspected stroke. A recent retrospective cohort study involving AHA ‘'Get With the Guidelines-Stroke”\nparticipating hospitals, reported a median door to DTN time of 65 minutes (IQR, 49-88 minutes) (Man, Xian, &\nHolmes, 2020), indicating that the ≤ 60-minute target is unattainable even for those institutions committed to\nachieving this goal. Using the American Heart Association Get With The Guidelines-Stroke registry, one study\nevaluated 108 913 patients with acute stroke requiring inter-hospital transfer from 1925 hospitals and determined\nthat the median door-in to door-out time was 174 minutes, despite the current guidelines recommending no more\nthan 120 minutes at the transferring emergency department. Longer times were associated with groups of patients\nsuch as those over 80 years of age, women, Black, and Hispanic patients (Stamm, et al., 2023).","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p19-t0","doc_id":"K253818","page_num":19,"bbox":[62.67,662.43,549.43,713.28],"n_rows":3,"n_cols":12,"columns":["","Finding","","","Product Code","","","Slice Thickness","","","AUC (95% CI)",""],"rows":[["","Finding","","","Product Code","","","Slice Thickness","","","AUC (95% CI)",""],["Acute Infarct","","","QAS","","","≤ 1.5mm","","","0.952 (0.937, 0.965)","",""],["","","","QAS","","","> 1.5 & ≤5.0mm","","","0.933 (0.917, 0.949)","",""]],"caption_candidate":"adjudicator in the case of disagreement. The key results of the study are summarized in the table below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p20-t0","doc_id":"K253818","page_num":20,"bbox":[62.65,82.2,549.34,244.32],"n_rows":11,"n_cols":15,"columns":["","Finding","","","Slice Thickness","","","Operating Point","","","Sensitivity % (95% CI)","","","Specificity % (95% CI)",""],"rows":[["","Finding","","","Slice Thickness","","","Operating Point","","","Sensitivity % (95% CI)","","","Specificity % (95% CI)",""],["Acute Infarct","","","≤1.5mm","","","0.063800","","","89.2 (85.8,92.6)","","","84.1 (81.5,86.9)","",""],["","","","","","","0.076008","","","88.5 (84.8,92.0)","","","87.5 (85.0,89.8)","",""],["","","","","","","0.083412","","","87.3 (83.6,91.0)","","","89.8 (87.5,91.9)","",""],["","","","","","","0.091176","","","86.1 (82.4,89.8)","","","91.4 (89.3,93.4)","",""],["","","","","","","0.100900","","","84.5 (80.5,88.5)","","","93.1 (91.1,95.0)","",""],["","","",">1.5mm &\n≤5.0mm","","","0.087158","","","85.7 (81.9,89.2)","","","83.2 (80.3,85.9)","",""],["","","","","","","0.091176","","","85.7 (81.9,89.2)","","","84.4 (81.8,87.0)","",""],["","","","","","","0.095598","","","84.8 (81.0,88.3)","","","85.6 (82.9,88.1)","",""],["","","","","","","0.100900","","","83.4 (79.3,87.2)","","","87.0 (84.3,89.3)","",""],["","","","","","","0.119914","","","78.1 (73.8,82.5)","","","91.9 (89.8,93.9)","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p21-t0","doc_id":"K253818","page_num":21,"bbox":[62.67,95.2,549.45,395.76],"n_rows":4,"n_cols":6,"columns":["","Parameter","","","Target or reported value and range",""],"rows":[["","Parameter","","","Target or reported value and range",""],["Time to image interpretation after\nCT acquired","","","Patients on Code Stroke workflow\n• Per AHA/ASA guidelines target value: <=20 minutes (<=45 minutes if interpretation time measured from\nED arrival, but <=20 minutes is the relevant parameter for comparison to the subject device time to\nnotification)\n• Even highly experienced hospitals are reported to exceed the above time goal by 50 minutes (Honig, et\nal., 2014).\n• The predicate device 510(k) summary K222884 (also on NCCT) makes a comparison to “time to exam\nopen” for data collected for CTA LVO exams in DEN170073: 58.7 (95% CI: 51.5, 71.2) minutes. Just as\nin K222884, it is reasonable to assume that such CTA exams were collected in the context of a code stroke\nworkflow, and so the elapsed time on the image worklist is a relevant standard of care comparison.\nPatients not on Code Stroke workflow\n• Target example hospital guideline expectation for STAT workflow: <2 hours\n• Combined data for STAT and Routine workflows: National Radiology Data Registry GRID report for\nJan-Sept 2022, generated from data stored in a Qualified Clinical Data Registry (QCDR) for participating\nhospitals, reported the following aggregated time: Median (IQR) report TAT*** of 4.7 (2.1-11) hours (the\ntime when exam was completed until the time the final report was signed) (National Radiology Data\nRegistry).","",""],["Time to Notification of subject\ndevice","","","81.6 (95% CI: 80.3 – 82.9) seconds","",""],["Time savings comparison\nconclusion","","","The subject device can reduce the time to notification by up to ~1 hour or more, even for patients allocated to a\ncode stroke workflow. Time savings will vary greatly dependent on the institution, procedures, presenting\ncondition of the patient.","",""]],"caption_candidate":"510k Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253818-p22-t0","doc_id":"K253818","page_num":22,"bbox":[62.65,275.6,549.47,681.12],"n_rows":13,"n_cols":9,"columns":["","Description","","","Title","","","Year",""],"rows":[["","Description","","","Title","","","Year",""],["QMS (also in compliance with 21 CFR\n820)","","","ISO 13485/ EN ISO 13485 – medical device – Quality Management System\n(Compliance also help ensured through routine audits as part of the Medical Device\nSingle Audit Program)","","","2016","",""],["Risk management","","","ISO 14971/ EN ISO 14971 - Medical devices — Application of risk management to\nmedical devices","","","2019","",""],["Software best practices and submission\ncontent","","","FDA Guidance: Content of Premarket Submissions for Device Software Functions","","","2023","",""],["Software design & development","","","IEC 62304 - MEDICAL DEVICE SOFTWARE — SOFTWARE LIFE CYCLE\nPROCESSES","","","2006/A1:2015","",""],["Usability","","","IEC 62366-1 - medical devices - Application of usability engineering to medical\ndevices","","","2015/A1:2020","",""],["Cybersecurity","","","AAMI TIR 57 - Principles for medical device security—risk management","","","2016/(R)\n2019","",""],["","","","FDA Guidance: Cybersecurity in Medical Devices: Quality System Considerations\nand Content of Premarket Submissions","","","2025","",""],["Information Security Management","","","ISO/IEC 27001 - Information technology — Security techniques — Information\nsecurity management systems — Requirements","","","2022","",""],["Health Software","","","IEC 82304-1 – Health software - Part 1: General requirements for product safety","","","2016","",""],["Information Management","","","DICOM - Digital Imaging and Communications in Medicine","","","Current","",""],["Standalone testing methodology, bias, and\ngeneralizability considerations specific to\ncertain radiological imaging software\ndevices","","","FDA Guidance: Computer-Assisted Detection Devices Applied to Radiology\nImages and Radiology Device Data - Premarket Notification [510(k)] Submissions\n(utilized for recommendations relevant to CADt including standalone testing)","","","2022","",""],["Multidisciplinary expertise through\nproduct lifecycle, good software\nengineering and security, test set\nrepresentativeness, data set independence,\nreference standards, risk mitigations\ntailored to intended use, human-AI team,\nclinically relevant testing, user\ninformation, and deployment controls","","","Good Machine Learning Practice for Medical Device Development: Guiding\nPrinciples (U.S. Food and Drug Administration (FDA), Health Canada, and the\nUnited Kingdom’s Medicines and Healthcare products Regulatory Agency (MHRA)","","","2021","",""]],"caption_candidate":"Standards, Guidance, and Best Practices","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253898-p4-t0","doc_id":"K253898","page_num":4,"bbox":[21.25,20.06,593.68,359.63],"n_rows":7,"n_cols":4,"columns":["Indications for Use","","",""],"rows":[["Indications for Use","","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","","K253898","?"],["Please provide the device trade name(s).","","",".\n?."],["H.e\nQ T Scanner 2000 (Model A)\nlp.\nHTee","","",""],["Please provide your Indications for Use below.","","","lxpt\n?\nTe"],[".\nxt\nT he QT Scanner 2000 Model A is for use as an ultrasonic imaging system to provide reflection-mode and\n.\ntransmission-mode images of a patient's breast. The QT Scanner 2000 Model A software also calculates\nHe\nthe breast fibroglandular tissue volume (FGV) value and the ratio of FGV to total breast volume (TBV) value\nlp\nas determined from reflection-mode and transmission-mode ultrasound images of a patient's breast. The\nTe\ndevice is not intended to be used as a replacement for screening mammography.\nxt\nThe QT Scanner 2000 Model A is indicated for use by trained healthcare professionals in environments\nwhere healthcareis provided to enable breast imaging in adult patients.","","",""],["Please select the types of uses (select one or both, as\napplicable).","","","?\n."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253898-p7-t0","doc_id":"K253898","page_num":7,"bbox":[72.28,229.34,539.49,696.22],"n_rows":11,"n_cols":7,"columns":["Feature","","Predicate:","","","Subject Device:",""],"rows":[["Feature","","Predicate:","","","Subject Device:",""],["","","QT Ultrasound LLC","","","QT Imaging, Inc.",""],["","","QT Scanner 2000 Model A","","","QT Scanner 2000 Model A",""],["","","(K220933)","","","(K253898)",""],["Classification","§892.1560\nUltrasonic pulsed echo imaging system\nClass II","","","§892.1560\nUltrasonic pulsed echo imaging system\nClass II","",""],["Product Code","IYO, ITX, QIH","","","IYO, ITX, QIH","",""],["Indications for Use","The QT Scanner 2000 Model A is for\nuse as an ultrasonic imaging system to\nprovide reflection-mode and\ntransmission-mode images of a patient's\nbreast. The QT Scanner 2000 Model A\nsoftware also calculates the breast\nfibroglandular tissue volume (FGV)\nvalue and the ratio of FGV to total\nbreast volume (TBV) value as\ndetermined from reflection-mode and\ntransmission-mode ultrasound images of\na patient's breast. The device is not\nintended to be used as a replacement for\nscreening mammography.","","","Same","",""],["Ultrasound Diagnostic\nApplication","Small organ (breast)","","","Same","",""],["Ultrasound Track","Track 1","","","Same","",""],["Principles of Operation","• Reflection (B-Mode) and\nTransmission (Speed of Sound)\nUltrasound\n• Displays 2D slice images and\nvolume data\n• No compression – positions breast\nin pendulous position within a water\nbath","","","Same","",""],["Transducer Configuration\nand Orientation","3 Reflection Mode, 1 Transmission\nMode transmitter, and 1 Transmission\nMode Receiver","","","Same configuration. The orientation of\nthe transmission transmitter and receiver\nare tilted five degrees to improve\nincident field alignment.","",""]],"caption_candidate":"Both devices share the same basic system layout and operational principles.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K253898-p8-t0","doc_id":"K253898","page_num":8,"bbox":[72.28,75.12,539.49,541.87],"n_rows":13,"n_cols":7,"columns":["Feature","","Predicate:","","","Subject Device:",""],"rows":[["Feature","","Predicate:","","","Subject Device:",""],["","","QT Ultrasound LLC","","","QT Imaging, Inc.",""],["","","QT Scanner 2000 Model A","","","QT Scanner 2000 Model A",""],["","","(K220933)","","","(K253898)",""],["Global Maximum\nAcoustic Output Values","Max I = 1.89 mW/cm2\nSPTA","","","Same","",""],["Imaging Modes","Acquires and processes B-mode\n(reflection) and speed of sound\n(transmission) images of a patient’s\nbreast","","","Same","",""],["Image Processing\nMethods","• General Processing\n• Implant Processing\n• Reprocessing: remove blur,\nartifacts, and dark spots\nAll image processing/reprocessing can\nbe performed on the device or on an\noffboard image processor","","","• General Processing\n• Implant Processing\nAll image processing can be performed\non the device or on an offboard image\nprocessor.","",""],["Image Output","Outputs DICOM images to a QTviewer\nworkstation.","","","Same","",""],["Image Views","Coronal, axial, and sagittal","","","Same","",""],["Image Analysis Functions","Correlate\nProbe\nRegion of Interest (ROI)\nSegment\nLinear Measurement\nManual Annotation","","","Same","",""],["Patient Position","Positions patient in the prone position on\nexam table with patient’s breast in\npendulous position within an imaging\nchamber","","","Same","",""],["Fluid Environment","Positions patient’s breast in fluid\nenvironment to eliminate need for breast\ncompression and facilitate transmission\nof ultrasound waves.","","","Same","",""],["Breast Positioning","Positions patient’s breast by use of a\npatient positioning system comprised of\nbreast insert ring, retention rod and\ndevice to align a patient’s breast in\nimaging chamber","","","Same","",""]],"caption_candidate":"510(k) SUMMARY","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254001-p4-t0","doc_id":"K254001","page_num":4,"bbox":[19.08,19.44,593.12,392.64],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\n1<254001 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\n1<254001 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","1<254001",""],["Please provide the device trade name(s).","",""],["VERITON CT 300 Series Digital SPECT/CT System (VERITON CT 316/364)\nVERITON CT 400 Series Digital SPECT/CT System (VERITON CT 416/464)","",""],["Please provide your Indications for Use below.","","?"],["Spectrum Dynamics Medical's VERITON system is intended for use by trained healthcare professionals to\naid in the detection, localization, diagnosis, staging and restaging of lesions, diseases, and organ function.\nFor evaluating diseases and disorders such as cardiovascular disease, neurological disorders, and trauma.\nSystem outcomes can be used to plan, guide, and monitor therapy.\nSPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body\nor organ (physiology), using the following techniques: whole body and tomographic imaging.\nCT: The CT component is intended to produce cross-sectional images of the body by computer\nreconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different\nangles or spiral planes take at different angles.\nSPECT+ CT: The SPECT and CT components used together acquire SPECT/CT images. The SPECT\nimages can be corrected for attenuation with the CT images, and can be combined (image registration) to\nmerqe the patient's ohvsioloqical (SPECT) and anatomical (CT) imaqes.\nCZJ\nPlease select the types of uses (select one or both, as Prescription Use (21 CFR 801 Subpart 0)\nD ?\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","",""],["","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254016-p10-t0","doc_id":"K254016","page_num":10,"bbox":[72.02,354.47,467.14,701.52],"n_rows":9,"n_cols":6,"columns":["","Designation","","Title","Standards\nDevelopment\nOrganization","Recognition\nNumber"],"rows":[["","Designation","","Title","Standards\nDevelopment\nOrganization","Recognition\nNumber"],["","Number and","","","",""],["","Edition/Dat","","","",""],["","e","","","",""],["PS 3.1 - 3.20\n2023e","","","Digital Imaging and Communications in Medicine\n(DICOM) Set","NEMA","12-352"],["62304\nEdition 1.1\n2015-06\nCONSOLIDA\nTED\nVERSION","","","Medical Device Software –Software Life Cycle\nProcesses","AAMI, ANSI,\nIEC","13-79"],["14971 Third\nEdition\n2019-12","","","Medical devices – Application of risk management to\nmedical devices","ISO","5-125"],["62366-1\nEdition 1.1\n2020-06\nCONSOLIDA\nTED\nVERSION","","","Medical devices - Part 1: Application of usability\nengineering to medical devices","AAMI, ANSI,\nIEC","5-129"],["15223-1\nFourth\nedition\n2021-07","","","Medical devices - Symbols to be used with medical\ndevice labels, labelling, and information to be\nsupplied - Part 1: General requirements","ISO","5-134"]],"caption_candidate":"listed below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p5-t0","doc_id":"K254161","page_num":5,"bbox":[57.84,121.68,539.76,628.92],"n_rows":11,"n_cols":2,"columns":["510(k) Number","K254161"],"rows":[["510(k) Number","K254161"],["Date","March 26, 2026"],["Submitter","GE Medical Systems Ultrasound & Primary Care Diagnostics LLC\n3200 N Grandview Blvd.\nWaukesha, WI, 53188, United States"],["Primary Contact\nPerson","Zahra Ghanian\nEmail: zahra.ghanian@gehealthcare.com\nPhone: +1 (385)866-0594"],["Secondary Contact\nPerson","Tahir Rizvi, Sr. Director of Regulatory Affairs\nEmail: Tahir.rizvi@gehealthcare.com\nPhone: +1 (781)290-6264"],["Device Trade Name","Automated Aortic Stenosis Software"],["Common/Usual Name","AutoAS"],["Classification Name","892.2060 - Radiological computer-assisted diagnostic software for lesions\nsuspicious of cancer"],["Regulatory Class","Class II"],["Product Code","POK"],["Predicate Device","EchoGo Pro (K201555)\nUltromics Ltd"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p8-t0","doc_id":"K254161","page_num":8,"bbox":[57.87,74.66,539.73,491.88],"n_rows":4,"n_cols":3,"columns":["Test","Purpose","Result"],"rows":[["Test","Purpose","Result"],["Confidence\nMetric","AutoAS produces a confidence\nmetric, also known simply as\n“confidence”, whenever it\nmakes a prediction. With this\nmetric, the algorithm aims to\nhighly correlate with the true\nprobability of a successful\nbinary classification of the\nseverity of aortic stenosis.","Testing demonstrated a statistically monotonically\nincreasing relationship between the confidence\nvalue and the probability of accurately detecting\nwhether moderate / severe aortic stenosis was\npresent."],["Clip\nAnnotator","Before analysis, AutoAS\nevaluates each clip with a clip\nannotator. The function of the\nclip annotator is to confirm if\nthe clip is B-mode and part of\n“valid” views (such as PLAX,\nPSAX-AV etc.) and rejects any\nother views.","Testing demonstrated both a positive predictive\nvalue (PPV) and Sensitivity of 100% (95% CI: (98.5%,\n100.0%)) across all view types (i.e., PLAX, AP5, PSAX-\nAV, and all other views) when classifying the B-mode\nimage. For any image that was classified as B-mode,\nthe ability to accurately classify the view was also\ntested, and the verification test results revealed a\nPPV of at least 97.1% (95% CI: (94.2%, 98.8%)) and a\nSensitivity of at least 87.5% (95% CI: (83.1%, 91.2%))\nacross all view types."],["Heart Rate\nEstimation","AutoAS has the ability to predict\na patient’s heart period by\nlooking solely at the video clip.\nThe estimated heart rate is not\nreported to the user and is used\nonly internally to the software.","The verification testing demonstrated a statistically\nsignificantly lesser MAD / MAE than the established\nbenchmark for all views (AP5, PLAX, and PSAX).\nBased on these results, there were no clinically\nsignificant differences between the estimated heart\nrates by the software and the reference\nmeasurements."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p9-t0","doc_id":"K254161","page_num":9,"bbox":[91.97,321.56,505.63,696.72],"n_rows":16,"n_cols":3,"columns":["Area under the ROC Curve","",""],"rows":[["Area under the ROC Curve","",""],["Parameter","Sample Size","Point Estimate"],["Age (Years)","",""],["< 65 104 0.964","",""],["≥ 65 278 0.908","",""],["BMI","",""],["< 25 121 0.944","",""],["25 - 30 126 0.903","",""],["≥ 30 135 0.959","",""],["Gender","",""],["Female 187 0.947","",""],["Male 195 0.920","",""],["Site Location","",""],["Site: Group #1 218 0.922","",""],["Site: Group #2 116 0.945","",""],["Site: Group #3 48 0.953","",""]],"caption_candidate":"Table 1. Consistency of performance metrics across relevant sub-group parameters","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p10-t0","doc_id":"K254161","page_num":10,"bbox":[86.09,74.28,511.51,450.24],"n_rows":16,"n_cols":4,"columns":["Sensitivity","","",""],"rows":[["Sensitivity","","",""],["Parameter","Sample Size","Point Estimate",""],["Age (Years)","","",""],["< 65 45 0.711","","",""],["≥ 65 193 0.762","","",""],["BMI","","",""],["< 25 86 0.733","","",""],["25 - 30 73 0.740","","",""],["≥ 30 79 0.785","","",""],["Gender","","",""],["Female 113 0.726","","",""],["Male 125 0.776","","",""],["Site Location","","",""],["Site: Group #1 140 0.757","","",""],["Site: Group #2 73 0.699","","",""],["Site: Group #3 25 0.880","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p10-t1","doc_id":"K254161","page_num":10,"bbox":[86.09,470.4,511.51,729.24],"n_rows":11,"n_cols":4,"columns":["Specificity","","",""],"rows":[["Specificity","","",""],["Parameter","Sample Size","Point Estimate",""],["Age (Years)","","",""],["< 65 59 0.983","","",""],["≥ 65 85 0.882","","",""],["BMI","","",""],["< 25 35 1.000","","",""],["25 - 30 53 0.849","","",""],["≥ 30 56 0.946","","",""],["Gender","","",""],["Female 74 0.973","","",""]],"caption_candidate":"Site: Group #3 25 0.880","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p11-t0","doc_id":"K254161","page_num":11,"bbox":[86.07,74.52,511.53,191.64],"n_rows":5,"n_cols":4,"columns":["Male 70 0.871","","",""],"rows":[["Male 70 0.871","","",""],["Site Location","","",""],["Site: Group #1 78 0.885","","",""],["Site: Group #2 43 1.000","","",""],["Site: Group #3 23 0.913","","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p12-t0","doc_id":"K254161","page_num":12,"bbox":[57.87,87.28,734.13,534.11],"n_rows":4,"n_cols":4,"columns":["Category","Subject Device","Predicate Device","Discussion"],"rows":[["Category","Subject Device","Predicate Device","Discussion"],["Manufacturer","GE HealthCare","Ultromics Ltd.","N/A"],["Device","AutoAS","EchoGo Pro (K201555)","N/A"],["Intended\nUse/Indications\nfor Use","AutoAS is a software application intended\nto assist medical professionals in the\nassessment of moderate/severe aortic\nstenosis (AS). The software uses an\nartificial intelligence (AI) algorithm to\nprocess previously acquired two-\ndimensional transthoracic\nechocardiography (2D-TTE) images to\nprovide a suggestion of moderate/severe\naortic stenosis along with an associated\nconfidence metric that can be a diagnostic\naid to a physician in a point of care or\nsimilar setting in determining if further\nevaluation is needed, including whether a\nfull echocardiogram (2D, Doppler) needs\nto be performed.\nThe results of AutoAS are not intended to\nbe used on a stand-alone basis for clinical\ndecision making and are not intended to\nsupplement or replace a full\nechocardiographic examination. AutoAS\nresults, along with the obtained\nultrasound images, must be reviewed by a\nqualified physician.","EchoGo Pro v1.0.2 is a machine learning-\nbased decision support system, indicated\nas an adjunct to diagnostic stress\nechocardiography for patients undergoing\nassessment for coronary artery disease\n(CAD). When utilized by an interpreting\nphysician, this device provides information\nthat may be useful in rendering an accurate\ndiagnosis. Patient management decisions\nshould not be made solely on the results of\nthe EchoGo Pro v1.0.2 analysis. EchoGo Pro\nv1.0.2 is to be used with stress echo exam\nprotocols that contain A2C, A4C, and mid-\nventricular short-axis views at rest and at\npeak stress. EchoGo Pro v1.0.2 is not\nintended for the assessment of mild or\nmoderate myocardial ischemia, or\nlocalization of coronary artery disease, or\nfor the assessment of myocardial perfusion,\nmyocardial viability, or valve disease.\nLimitations: EchoGo Pro v1.0.2 has not\nbeen validated on patients who underwent\nprevious coronary artery bypass graft\n(CABG) surgery.","Similar. Both devices are intended\nto be used as diagnostic aids for\ncardiac evaluation. Both devices\nspecify in the indications for use\nthat patient management should\nnot be driven solely by the output\nof the devices. and both devices\nare intended to be used by the\nreading physician as part of\npatient evaluation i.e., obtained\nimages must be formally\ninterpreted and reported by a\nqualified physician. Therefore,\nboth devices are not intended to\nreplace the skill and judgment of\na qualified medical practitioner.\nThere is a minor difference in the\nspecific condition that is being\nautomatically detected between\nthe devices, with the predicate\nassessing coronary artery disease\n(CAD) and the subject device\nassessing AS; however, both\ndevices are designed to operate\nwithin the same anatomical area."]],"caption_candidate":"Table 2: Substantial Equivalence Comparison Chart","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p13-t0","doc_id":"K254161","page_num":13,"bbox":[57.85,74.68,734.15,542.64],"n_rows":9,"n_cols":4,"columns":["Category","Subject Device","Predicate Device","Discussion"],"rows":[["Category","Subject Device","Predicate Device","Discussion"],["","The AutoAS product is not intended to be\nused on patients who have prosthetic\nvalves and/or have had prior valve repair\nor replacement.\nAutoAS software is indicated for use in\nadult patients and is intended to be an\naccessory to compatible ultrasound\nsystems in environments where\nhealthcare is provided.","",""],["Classification\nName","Radiological computer-assisted diagnostic\nsoftware for lesions suspicious of cancer","Radiological computer-assisted diagnostic\nsoftware for lesions suspicious of cancer","Identical"],["Product Code","POK","POK","Identical"],["Regulation\nNumber","21 CFR 892.2060","21 CFR 892.2060","Identical"],["Modality","Ultrasound (Echocardiography)","Ultrasound (Echocardiography)","Identical"],["Anatomical Site","Cardiovascular","Cardiovascular","Identical"],["Clinical\nCondition","Aortic Stenosis","Coronary Plaques","Similar. Despite minor difference\nin specific conditions evaluated,\nthis distinction does not raise new\nsafety or efficacy concerns as\nboth clinical conditions are\ndiagnostic in nature in the same\nanatomical site."],["Echocardiogram\nViews","PLAX, PSAX-AV, AP5","A2C, A4C, Mid-ventricle AX","While the specific image views\nrequired differ slightly between\nthe devices, both incorporate\nquality-control measures to"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p14-t0","doc_id":"K254161","page_num":14,"bbox":[57.86,74.68,734.14,544.68],"n_rows":5,"n_cols":4,"columns":["Category","Subject Device","Predicate Device","Discussion"],"rows":[["Category","Subject Device","Predicate Device","Discussion"],["","","","ensure sufficient input data and\ngenerate user-facing reports to\nsupport cardiac evaluations."],["Machine-\nLearning Based\nAlgorithm","Yes","Yes","Substantially equivalent. Both\ndevices utilize deep-learning\nartificial intelligence as the core\ntechnology to provide diagnostic\naid to the user in the assessment\nof heart conditions."],["Clinical Output","Two-level (Binary) Output:\nSuggestive of moderate to severe AS\nOr\nNot suggestive of moderate to severe AS\nConfidence score generated at study-level.","Two-level (Binary) Output:\nSuggestive of a lower risk of prognostically\nsignificant coronary artery disease\nOr\nSuggestive of a higher risk of prognostically\nsignificant coronary artery disease.","Both devices process ultrasound\nimages to generate a two-level\ndiagnostic output intended to\nassist medical professionals. The\nsubject device includes a\nconfidence score whereas the\npredicate device does not. The\nconfidence score indicates how\ncertain the algorithm is in its\nprediction, based on the clips\nanalyzed.\nThis difference does not raise\nsafety or efficacy concerns\nbecause the confidence score is\nonly intended as supporting\ninformation but does not replace\nphysician responsibility for\ndiagnosis."],["Labelled for\nInterpreting\nPhysician Read","Yes","Yes","Identical. Both devices do not\nreplace clinical judgment,\nemphasizing that all exams must"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254161-p15-t0","doc_id":"K254161","page_num":15,"bbox":[57.89,74.68,734.11,125.16],"n_rows":2,"n_cols":4,"columns":["Category","Subject Device","Predicate Device","Discussion"],"rows":[["Category","Subject Device","Predicate Device","Discussion"],["","","","be reviewed by an interpreting\nreading physician."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254207-p8-t0","doc_id":"K254207","page_num":8,"bbox":[72.26,559.56,539.74,708.36],"n_rows":7,"n_cols":10,"columns":["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],"rows":[["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],["","Characteristi","","","AiORTA Plan 1.1","","","Plan 2.0","",""],["","c","","","(K250337)","","","(K254207)","",""],["Manufacturer","","","ViTAA Medical, Inc.","","","ViTAA Medical, Inc.","","","Identical"],["Classification","","","21 CFR 892.2050","","","21 CFR 892.2050","","","Identical"],["Product code","","","QIH","","","QIH","","","Identical"],["Intended use\nstatement","","","The AiORTA - Plan tool is\nan image analysis\nsoftware tool for\nvolumetric assessment.","","","The AiORTA - Plan tool is\nan image analysis\nsoftware tool for\nvolumetric assessment,","","","Addition of\n“patients 22\nyears old and\nolder” added to"]],"caption_candidate":"Substantial Equivalence Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254207-p9-t0","doc_id":"K254207","page_num":9,"bbox":[72.26,72.36,539.74,719.28],"n_rows":7,"n_cols":10,"columns":["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],"rows":[["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],["","Characteristi","","","AiORTA Plan 1.1","","","Plan 2.0","",""],["","c","","","(K250337)","","","(K254207)","",""],["","","","It provides volumetric\nvisualization and\nmeasurements based\non 3D reconstruction\ncomputed from\ncardiovascular CTA\nscans. The software\ndevice is intended to\nprovide adjunct\ninformation to a licensed\nhealthcare practitioner\n(HCP) in addition to\nclinical data and other\ninputs, as a\nmeasurement tool used\nin assessment of aortic\naneurysm, pre-operative\nevaluation, planning and\nsizing for cardiovascular\nintervention and surgery,\nand for post-operative\nevaluation.\nThe device is not\nintended to provide\nstand-alone diagnosis or\nsuggest an immediate\ncourse of action in\ntreatment or patient\nmanagement.","","","image analysis,\ngeometric analysis, and\npre-operative sizing and\nplanning. It provides\nvolumetric visualization\nand measurements\nbased on 3D\nreconstruction\ncomputed from\ncardiovascular CTA\nscans. The software\ndevice is intended to\nprovide adjunct\ninformation to a licensed\nhealthcare practitioner\n(HCP) in addition to\nclinical data and other\ninputs, as a\nmeasurement tool used\nin assessment of aortic\naneurysm, pre-operative\nevaluation, planning and\nsizing for cardiovascular\nintervention and surgery,\nand for post-operative\nevaluation in patients 22\nyears old and older.\nThe device is not\nintended to provide\nstand-alone diagnosis or\nsuggest an immediate\ncourse of action in\ntreatment or patient\nmanagement","","","intended use &\nindications for\nuse statement\nper FDA\nrecommendation\n."],["Use\nEnvironment","","","Hospital","","","Hospital","","","Identical"],["Intended end-\nuser","","","Healthcare Practitioner","","","Healthcare Practitioner","","","Identical"],["Anatomical\nscope","","","Abdominal aorta","","","Abdominal aorta +\nexternal iliac arteries","","","The region of\ninterest has been\nexpanded in v2.0"]],"caption_candidate":"ViTAA Medical Solutions, Inc. K254207: AiORTA – Plan v2.0 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254207-p10-t0","doc_id":"K254207","page_num":10,"bbox":[72.25,72.36,539.75,706.2],"n_rows":10,"n_cols":10,"columns":["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],"rows":[["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],["","Characteristi","","","AiORTA Plan 1.1","","","Plan 2.0","",""],["","c","","","(K250337)","","","(K254207)","",""],["","","","","","","and a larger portion of\nthe descending aorta","","","to give clinicians\nbetter ability to\nassess access\nvessels and\nsupra-renal\nconsiderations.\nThis expansion of\nROI does not\nintroduce new\nquestions of\nsafety or\neffectiveness."],["Image source","","","Cardiovascular CTA\nscans","","","Cardiovascular CTA\nscans","","","Identical"],["Operating\nsystem","","","Microsoft Windows","","","Microsoft Windows","","","Identical"],["System\nconfiguration","","","Web application","","","Web application","","","Identical"],["Analysis\nworkflow","","","Semi-automatic analysis\npipeline requiring input\nfrom ViTAA analysts.\nAnalysis is completed\nwithin 30 minutes under\nnormal conditions.","","","Fully automated\nanalysis pipeline.\nClinicians retain the\nability to edit outputs.","","","A full suite of\nimage analysis\ntools for manual\ncorrection by a\nclinician has\nbeen added. All\ncorrections and\nedits are\nperformed by the\nphysician."],["Vessel\ngeometry\nmeasurement\ntools","","","Provides tools for\nmeasuring vessel\ngeometry, including\ndiameters, lengths, and\nvolumes.","","","All relevant\nmeasurements are\nprovided automatically,\nalong with a detailed\nbreakdown targeting\nlanding zones and other\ncritical regions of\ninterest.","","","Additional tools\nare provided to\nguide the user,\nwhile users can\nstill edit or\noverride the\nautomated\noutputs."],["Segmentation","","","Semi-automatic\nsegmentation using\nauto-masking algorithm\nwith manual revisions","","","Automated\nsegmentation using\nmasking algorithm. The\nend-user (clinician) can","","","Users in v2.0\nhave the option\nof employing an\nautomated"]],"caption_candidate":"ViTAA Medical Solutions, Inc. K254207: AiORTA – Plan v2.0 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254207-p11-t0","doc_id":"K254207","page_num":11,"bbox":[72.26,72.36,539.74,704.64],"n_rows":7,"n_cols":10,"columns":["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],"rows":[["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],["","Characteristi","","","AiORTA Plan 1.1","","","Plan 2.0","",""],["","c","","","(K250337)","","","(K254207)","",""],["","","","performed by trained\nViTAA analysts. End-\nusers (clinicians) can\nview and edit the\nsegmentations.","","","view and edit these\nsegmentations using the\nincluded suite of editing\ntools.","","","algorithm instead\nof a ViTAA analyst\nfor segmentation.\nClinicians retain\ncontrol over the\nend result."],["Centerline\ndetection","","","Automatic centerline\ndetection within the\nanalysis pipeline. User\nedits of the centerline\nare not supported.","","","Automatic centerline\ndetection within the\nanalysis pipeline. User\nedits of the centerline\nare not supported.","","","Identical"],["Study\ncomparison","","","Allows users to visualize\ntwo studies side-by-side\nacross two viewports,\nenabling a direct\ncomparison of\nstructures between the\nstudies.\nProvides measurement\ncapabilities in\ncomparison mode,\nallowing users to\nquantify changes in\nvessel geometries\nbetween the two\nstudies.","","","Allows users to visualize\ntwo studies side-by-side\nacross two viewports,\nenabling a direct\ncomparison of\nstructures between the\nstudies.\nProvides measurement\ncapabilities in\ncomparison mode,\nallowing users to\nquantify changes in\nvessel geometries\nbetween the two\nstudies. Provides device\nsuggestions to the user\nbased on product tables\nprovided by the\ninstitution, using\nclinically-validated\nmeasurements.","","","Version 2.0\ncontains the\naddition of\ndevice\nsuggestions\nbased on look-up\ntables provided\nby the institution.\nThis additional\nhelpful\ninformation does\nnot raise new\nquestions of\nsafety or\neffectiveness."],["Change in\ngeometric\nanalysis","","","Reports automated\nmeasurements\ndescribing changes\nbetween two studies\nwithin the default\nvolume of interest,\nincluding:","","","All previous calculations\nwith the addition of C-\nARM calculations for\nproximal neck and distal\nleft and right common\niliac arteries.","","","Additional\ncalculations in\nthe v2.0 device\nare included to\naccommodate\nthe expanded\nROI."]],"caption_candidate":"ViTAA Medical Solutions, Inc. K254207: AiORTA – Plan v2.0 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K254207-p12-t0","doc_id":"K254207","page_num":12,"bbox":[72.26,72.36,539.74,602.76],"n_rows":9,"n_cols":10,"columns":["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],"rows":[["","Device","","","Predicate Device:","","","Subject Device: AiORTA","","Comparison"],["","Characteristi","","","AiORTA Plan 1.1","","","Plan 2.0","",""],["","c","","","(K250337)","","","(K254207)","",""],["","","","• Change in\nMaximum Lumen\nDiameter\n• Change in\nMaximum Aortic\nDiameter\n• Change in\nLumen Volume\n• Change in Aortic\nVolume","","","","","",""],["Storage of\nresults","","","• Report in PDF\nformat\n• Viewports:\nSession state","","","• Report in PDF\nformat\n• Viewports:\nSession state","","","Identical"],["VIEWPORT CONTROLS","","","","","","","","",""],["General\ncontrols","","","• Lock viewports\n• Switch to\nsingle/quad view\n• Take screenshot\n• Show/hide slice\nplane","","","• Lock viewports\n• Switch to\nsingle/quad view\n• Take screenshot\n• Show/hide slice\nplane","","","Identical"],["2d CT image\ncontrols","","","• Pan\n• Window\n• Level\n• Scroll slice\n• Zoom","","","• Pan\n• Window\n• Level\n• Scroll slice\n• Zoom","","","Identical"],["3D map\ncontrols","","","• Rotate\n(clockwise,\ncounterclockwise\n, free rotate)\n• Pan\n• Zoom","","","• Rotate\n(clockwise,\ncounterclockwise\n, free rotate)\n• Pan\n• Zoom","","","Identical"]],"caption_candidate":"ViTAA Medical Solutions, Inc. K254207: AiORTA – Plan v2.0 510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260078-p6-t0","doc_id":"K260078","page_num":6,"bbox":[108.0,67.68,573.84,158.88],"n_rows":2,"n_cols":7,"columns":["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],"rows":[["Product","Marketed by","Regulation\nNumber","Regulation\nName","Product\nCode","510(k)\nNumber","Clearance\nDate"],["Aquilion Serve SP\nV1.3","Canon Medical\nSystems USA","21 CFR\n§892.1750","Computed\nTomography\nSystem","JAK","K233334","12/06/2023"]],"caption_candidate":"10. PREDICATE DEVICE:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260078-p7-t0","doc_id":"K260078","page_num":7,"bbox":[67.68,228.93,544.32,372.12],"n_rows":6,"n_cols":9,"columns":["","","","","Subject Device","","","Predicate Device",""],"rows":[["","","","","Subject Device","","","Predicate Device",""],["","Device Name,","","","Aquilion ONE (TSX-308A/TSX-306A)","","Aquilion Serve SP (TSX-307B/1) V1.3","Aquilion Serve SP (TSX-307B/1) V1.3",""],["","Model Number","","","V2.0","","","",""],["","510(k) Number","","","This submission","","","K233334",""],["CLEAR Motion\nReconstruction\nSystem","","","Body and Lung scan reconstruction\ncapabilities","","","N/A – feature not available, but previously\ncleared under K242403.","",""],["PIQE\nReconstruction\nSystem","","","Cardiac, Body, and Lung scan\nreconstruction capabilities","","","N/A – feature not available, but previously\ncleared under K242403.","",""]],"caption_candidate":"device is included below.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p5-t0","doc_id":"K260166","page_num":5,"bbox":[97.76,281.34,470.76,370.93],"n_rows":5,"n_cols":2,"columns":["Proprietary Name","Bunkerhill Contrast CAC"],"rows":[["Proprietary Name","Bunkerhill Contrast CAC"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p5-t1","doc_id":"K260166","page_num":5,"bbox":[97.76,583.74,470.76,691.57],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Bunkerhill AVC"],"rows":[["Proprietary Name","Bunkerhill AVC"],["Premarket Notification","K243229"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Reference Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p7-t0","doc_id":"K260166","page_num":7,"bbox":[38.21,98.35,573.79,711.36],"n_rows":4,"n_cols":8,"columns":["","","Proposed Device:","","","Predicate Device:","","Reference: Device:\nBunkerhill AVC (K243229)"],"rows":[["","","Proposed Device:","","","Predicate Device:","","Reference: Device:\nBunkerhill AVC (K243229)"],["","","Bunkerhill Contrast","","","Bunkerhill iCAC Device","",""],["","","CAC","","","(K230223)","",""],["Intended use / Indications\nfor use","Bunkerhill Contrast CAC\nis a software device\nintended for use in\ndetecting presence and\nestimating quantity of\ncoronary artery\ncalcification for adult\npatients aged 30 years and\nabove. The device\nautomatically analyzes\nnon-gated, contrast-\nenhanced chest computed\ntomography (CT) images\ncollected during clinical\ncare and outputs the region\nof interest (intended for\ninformational purposes\nonly) and quantification of\ndetected calcium.\nThe output of the subject\ndevice is made available to\nthe physician on-demand\nas part of his or her\nstandard workflow. The\ndevice-generated\nquantification can be\nviewed in the patient\nreport at the discretion of\nthe physician, and the\nphysician also has the\noption of viewing the\ndevice-generated calcium\nregion of interest in a\ndiagnostic image viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or\nthe original non-gated,\ncontrast-enhanced CT\nscan; both are still","","","iCAC is a software\ndevice intended for use\nin estimating presence\nand quantity of coronary\nartery calcium for\npatients aged 30 years\nand above during routine\ncare. The device\nautomatically analyzes\nnon-gated, non-contrast\nchest computed\ntomography (CT) images\ncollected during routine\ncare and outputs a visual\nrepresentation of\nestimated coronary artery\ncalcium segmentation\n(intended for\ninformational purposes\nonly) and both exact and\nfour-category\nquantitative estimates of\nthe patient’s coronary\nartery calcium burden in\nAgatston units.\nThe output of the subject\ndevice is made available\nto the physician on-\ndemand as part of his or\nher standard workflow.\nThe device generated\ncalcium score or score\ngroup can be viewed in\nthe patient report at the\ndiscretion of the\nphysician, and the\nphysician also has the\noption of viewing the\ndevice-generated calcium\nsegmentation in a","","","Bunkerhill AVC is a\nsoftware device intended for\nuse in detecting presence\nand estimating quantity of\naortic valve calcification for\nadult patients aged 40 years\nand above. The device\nautomatically analyzes non-\ngated, non- contrast chest\ncomputed tomography (CT)\nimages collected during\nclinical care and outputs the\nregion of interest (intended\nfor informational purposes\nonly) and quantification of\ndetected calcium.\nThe output of the subject\ndevice is made available to\nthe physician on- demand as\npart of his or her standard\nworkflow.\nThe device-generated\nquantification can be\nviewed in the patient report\nat the discretion of the\nphysician, and the\nphysician also has the\noption of viewing the\ndevice- generated calcium\nregion of interest in a\ndiagnostic image viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or the\noriginal non- gated, non-\ncontrast CT scan; both are\nstill available to be viewed\nand used at the discretion of\nthe physician."]],"caption_candidate":"Table 1: Substantial Equivalence-Intended Use Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p8-t0","doc_id":"K260166","page_num":8,"bbox":[38.21,72.43,573.79,504.6],"n_rows":4,"n_cols":8,"columns":["","","Proposed Device:","","","Predicate Device:","","Reference: Device:\nBunkerhill AVC (K243229)"],"rows":[["","","Proposed Device:","","","Predicate Device:","","Reference: Device:\nBunkerhill AVC (K243229)"],["","","Bunkerhill Contrast","","","Bunkerhill iCAC Device","",""],["","","CAC","","","(K230223)","",""],["","available to be viewed and\nused at the discretion of\nthe physician.\nThe device is intended to\nprovide information to the\nphysician to provide\nassistance during review\nof the patient’s case.\nResults of the subject\ndevice are not intended to\nbe used on a stand-alone\nbasis and are solely\nintended to aid and\nprovide information to the\nphysician. In all cases,\nfurther action taken on a\npatient should only come\nat the recommendation of\nthe physician after further\nreviewing the patient’s\nresults.","","","diagnostic image viewer.\nThe subject device output\nin no way replaces the\noriginal patient report or\nthe original chest CT\nscan; both are still\navailable to be viewed\nand used at the discretion\nof the physician.\nThe device is intended to\nprovide information to the\nphysician to provide\nassistance during review\nof the patient’s case.\nResults of the subject\ndevice are not intended to\nbe used on a stand-alone\nbasis and are solely\nintended to aid and\nprovide information to the\nphysician. In all cases,\nfurther action taken on a\npatient should only come\nat the recommendation of\nthe physician after further\nreviewing the patient’s\nresults.","","","The device is intended to\nprovide information to the\nphysician to provide\nassistance during review of\nthe patient’s case.\nResults of the subject device\nare not intended to be used on\na stand- alone basis and are\nsolely intended to aid and\nprovide information to the\nphysician. In all cases, further\naction taken on a patient\nshould only come at the\nrecommendation of the\nphysician after further\nreviewing the patient’s\nresults."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p9-t0","doc_id":"K260166","page_num":9,"bbox":[23.83,368.66,588.17,714.36],"n_rows":11,"n_cols":5,"columns":["","Proposed Device:\nBunkerhill Contrast CAC","Predicate Device: iCAC\n(K230223)","Reference Device:\nBunkerhill AVC\n(K243229)","Summary\n(compared to\npredicate)"],"rows":[["","Proposed Device:\nBunkerhill Contrast CAC","Predicate Device: iCAC\n(K230223)","Reference Device:\nBunkerhill AVC\n(K243229)","Summary\n(compared to\npredicate)"],["Product code","JAK","JAK","JAK","Same"],["Regulation number","21 CFR §892.1750","21 CFR §892.1750","21 CFR §892.1750","Same"],["Modality","Computed tomography\n(CT)","Computed tomography\n(CT)","Computed\ntomography (CT)","Same"],["Image format","DICOM","DICOM","DICOM","Same"],["Supported CT Scan","Contrast-enhanced, Non-\ncardiac-gated CT scan","Non-contrast, Non-\ncardiac-gated CT scan","Non-contrast, Non-\ncardiac-gated CT scan","Similar"],["Slice thickness","Up to 5 mm","Up to 5 mm","Up to 5 mm","Same"],["Calcification\ndetection","Automatic","Automatic","Automatic","Same"],["Main image\nquality","DICOM","DICOM","DICOM","Same"],["Annotation of\ndetected calcium","Yes","Yes","Yes","Same"],["Visual Output\nformat","Visual output in the form a\nRegion of Interest or ROI\n(intended for informational\npurposes only). The\nestimated visual output can","Outputs a visual\nrepresentation of\nestimated coronary\nartery calcium\nsegmentation (intended","Visual output in the\nform a Region of\nInterest or ROI\n(intended for\ninformational purposes","Similar"]],"caption_candidate":"aspect of the subject device is most similar to the reference device.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260166-p10-t0","doc_id":"K260166","page_num":10,"bbox":[23.83,72.44,588.17,704.94],"n_rows":10,"n_cols":5,"columns":["","Proposed Device:\nBunkerhill Contrast CAC","Predicate Device: iCAC\n(K230223)","Reference Device:\nBunkerhill AVC\n(K243229)","Summary\n(compared to\npredicate)"],"rows":[["","Proposed Device:\nBunkerhill Contrast CAC","Predicate Device: iCAC\n(K230223)","Reference Device:\nBunkerhill AVC\n(K243229)","Summary\n(compared to\npredicate)"],["","be viewed by the physician\nin a diagnostic image\nviewer. The physician’s\nstandard method for\nviewing unaltered chest CT\nscans in PACS will remain\navailable to them even if\nthe subject device is being\nused. However, the\nphysician will also have an\noption to view the visual\noutput estimated by the\nsubject device as a separate\nseries within PACS.","for informational\npurposes only). The\nestimated calcium\nsegmentation can be\nviewed by the physician\nin a diagnostic image\nviewer. The physician’s\nstandard method for\nviewing unaltered chest\nCT scans in PACS will\nremain available to them\neven if the subject\ndevice is being used.\nHowever, the physician\nwill also have an option\nto view the calcium\nsegmentation estimated\nby the subject device as\na separate series within\nPACS.","only). The estimated\nvisual output can be\nviewed by the\nphysician in a\ndiagnostic image\nviewer. The physician’s\nstandard method for\nviewing unaltered chest\nCT scans in PACS will\nremain available to\nthem even if the subject\ndevice is being used.\nHowever, the physician\nwill also have an option\nto view the visual\noutput estimated by the\nsubject device as a\nseparate series within\nPACS.",""],["Generate patient\nreport","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary\nCapture","Optional to copy result\nto clipboard, insert in\nreport, DICOM\nSecondary Capture","Optional to copy result\nto clipboard, insert in\nreport, DICOM\nSecondary Capture","Same"],["Report of the\ncalcium score","Yes, estimated calcification\nvolume (mm3) score and\nbinary output\n(presence/absence)","Yes, Coronary\nCalcium Detection\nCategory and exact\nAgatston score\n4 detection categories","Yes, estimated exact\nAgatston-equivalent\nscore and binary output\n(presence/absence)","Similar"],["Type of\nInterpretation","Adjunctive information","Adjunctive information","Adjunctive information","Same"],["Intended User","Qualified medical\nprofessionals such as","Interpreting physicians","Qualified medical\nprofessionals such as","Same"],["Patient population","Patients aged 30 years and\nabove","Patients above the age\nof 30","Patients above the age\nof 40","Same"],["Anatomical\nlocation","Chest (Coronary Artery)","Chest (coronary artery)","Chest (aortic valve)","Same"],["Intended location","Medical facility","Medical facility","Medical facility","Same"],["Rx or OTC","Rx","Rx","Rx","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p5-t0","doc_id":"K260167","page_num":5,"bbox":[97.76,278.98,470.69,368.59],"n_rows":5,"n_cols":2,"columns":["Proprietary Name","Bunkerhill Contrast AVC"],"rows":[["Proprietary Name","Bunkerhill Contrast AVC"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p5-t1","doc_id":"K260167","page_num":5,"bbox":[97.76,421.06,470.69,528.96],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","Bunkerhill AVC"],"rows":[["Proprietary Name","Bunkerhill AVC"],["Premarket Notification","K243229"],["Classification Name","Computed tomography x-ray system"],["Regulation Number","21 CFR 892.1750"],["Product Code","JAK"],["Regulatory Class","II"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p7-t0","doc_id":"K260167","page_num":7,"bbox":[72.29,165.93,539.71,709.44],"n_rows":3,"n_cols":7,"columns":["","","Proposed Device: Bunkerhill","","","Predicate Device: Bunkerhill",""],"rows":[["","","Proposed Device: Bunkerhill","","","Predicate Device: Bunkerhill",""],["","","Contrast AVC","","","AVC (K243229)",""],["Intended use / Indications for\nuse","Bunkerhill Contrast AVC is a\nsoftware device intended for use\nin detecting presence and\nestimating quantity of aortic\nvalve calcification for adult\npatients aged 40 years and\nabove. The device automatically\nanalyzes non-gated, contrast-\nenhanced chest computed\ntomography (CT) images\ncollected during clinical care\nand outputs the region of\ninterest (intended for\ninformational purposes only)\nand quantification of detected\ncalcium.\nThe output of the subject device\nis made available to the\nphysician on-demand as part of\nhis or her standard workflow.\nThe device-generated\nquantification can be viewed in\nthe patient report at the\ndiscretion of the physician, and\nthe physician also has the option\nof viewing the device- generated\ncalcium region of interest in a\ndiagnostic image viewer. The\nsubject device output in no way\nreplaces the original patient\nreport or the original non-gated,\ncontrast-enhanced CT scan; both\nare still available to be viewed\nand used at the discretion of the\nphysician.","","","Bunkerhill AVC is a software\ndevice intended for use in\ndetecting presence and\nestimating quantity of aortic\nvalve calcification for adult\npatients aged 40 years and\nabove. The device\nautomatically analyzes non-\ngated, non- contrast chest\ncomputed tomography (CT)\nimages collected during\nclinical care and outputs the\nregion of interest (intended\nfor informational purposes\nonly) and quantification of\ndetected calcium.\nThe output of the subject\ndevice is made available to\nthe physician on- demand as\npart of his or her standard\nworkflow.\nThe device-generated\nquantification can be viewed\nin the patient report at the\ndiscretion of the physician,\nand the physician also has\nthe option of viewing the\ndevice- generated calcium\nregion of interest in a\ndiagnostic image viewer. The\nsubject device output in no\nway replaces the original\npatient report or the original\nnon- gated, non- contrast CT\nscan; both are still available","",""]],"caption_candidate":"Table 1: Substantial Equivalence-Intended Use Table","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p8-t0","doc_id":"K260167","page_num":8,"bbox":[72.29,72.36,539.71,365.46],"n_rows":3,"n_cols":7,"columns":["","","Proposed Device: Bunkerhill","","","Predicate Device: Bunkerhill",""],"rows":[["","","Proposed Device: Bunkerhill","","","Predicate Device: Bunkerhill",""],["","","Contrast AVC","","","AVC (K243229)",""],["","The device is intended to\nprovide information to the\nphysician to provide assistance\nduring review of the patient’s\ncase. Results of the subject\ndevice are not intended to be\nused on a stand- alone basis and\nare solely intended to aid and\nprovide information to the\nphysician. In all cases, further\naction taken on a patient should\nonly come at the\nrecommendation of the\nphysician after further reviewing\nthe patient’s results.","","","to be viewed and used at the\ndiscretion of the physician.\nThe device is intended to\nprovide information to the\nphysician to provide\nassistance during review of\nthe patient’s case.\nResults of the subject device are\nnot intended to be used on a\nstand- alone basis and are solely\nintended to aid and provide\ninformation to the physician. In\nall cases, further action taken on\na patient should only come at\nthe recommendation of the\nphysician after further reviewing\nthe patient’s results.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p9-t0","doc_id":"K260167","page_num":9,"bbox":[72.25,72.36,577.55,696.48],"n_rows":14,"n_cols":4,"columns":["","Proposed Device:\nBunkerhill Contrast AVC","Predicate Device:\nBunkerhill AVC (K243229)","Summary"],"rows":[["","Proposed Device:\nBunkerhill Contrast AVC","Predicate Device:\nBunkerhill AVC (K243229)","Summary"],["Product code","JAK","JAK","Same"],["Regulation\nnumber","21 CFR §892.1750","21 CFR §892.1750","Same"],["Modality","Computed tomography (CT)","Computed tomography (CT)","Same"],["Image format","DICOM","DICOM","Same"],["Supported CT\nScan","Contrast-enhanced, Non-cardiac-\ngated CT scan","Non-contrast, Non-cardiac-gated\nCT scan","Similar"],["Slice thickness","Up to 5 mm","Up to 5 mm","Same"],["Calcification\ndetection","Automatic","Automatic","Same"],["Main image\nquality","DICOM","DICOM","Same"],["Annotation of\ndetected calcium","Yes","Yes","Same"],["Visual Output\nformat","Visual output in the form a\nRegion of Interest or ROI\n(intended for informational\npurposes only). The estimated\nvisual output can be viewed by\nthe physician in a diagnostic\nimage viewer. The physician’s\nstandard method for viewing\nunaltered chest CT scans in\nPACS will remain available to\nthem even if the subject device is\nbeing used. However, the\nphysician will also have an option\nto view the visual output\nestimated by the subject device as\na separate series within PACS.","Visual output in the form a Region\nof Interest or ROI (intended for\ninformational purposes only). The\nestimated visual output can be\nviewed by the physician in a\ndiagnostic image viewer. The\nphysician’s standard method for\nviewing unaltered chest CT scans\nin PACS will remain available to\nthem even if the subject device is\nbeing used. However, the\nphysician will also have an option\nto view the visual output estimated\nby the subject device as a separate\nseries within PACS.","Similar"],["Generate patient\nreport","Optional to copy result to\nclipboard, insert in report,\nDICOM Secondary Capture","Optional to copy result to\nclipboard, insert in report, DICOM\nSecondary Capture","Same"],["Report of the\ncalcium score","Yes, estimated calcification\nvolume (mm3) score and binary\noutput (presence/absence)","Yes, estimated exact Agatston-\nequivalent score and binary output\n(presence/absence)","Similar"],["Type of\nInterpretation","Adjunctive information","Adjunctive information","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260167-p10-t0","doc_id":"K260167","page_num":10,"bbox":[72.26,72.36,577.54,263.7],"n_rows":6,"n_cols":4,"columns":["","Proposed Device:\nBunkerhill Contrast AVC","Predicate Device:\nBunkerhill AVC (K243229)","Summary"],"rows":[["","Proposed Device:\nBunkerhill Contrast AVC","Predicate Device:\nBunkerhill AVC (K243229)","Summary"],["Intended User","Qualified medical professionals\nsuch as","Qualified medical professionals\nsuch as","Same"],["Patient\npopulation","Patients aged 40 years and above","Patients aged 40 years and above","Same"],["Anatomical\nlocation","Chest (aortic valve)","Chest (aortic valve)","Same"],["Intended location","Medical facility","Medical facility","Same"],["Rx or OTC","Rx","Rx","Same"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260169-p9-t0","doc_id":"K260169","page_num":9,"bbox":[72.28,358.72,523.16,756.58],"n_rows":14,"n_cols":7,"columns":["Comparison\nFeature","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","Comparis",""],"rows":[["Comparison\nFeature","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","Comparis",""],["","","","","","on",""],["","","","","","between",""],["","","","","","the",""],["","","","","","subject",""],["","","","","","and",""],["","","","","","predicate",""],["","","","","","(identical/",""],["","","","","","different)",""],["Device Class","Class II","Class II","Class II","Identical","",""],["Classification\nPanel","Radiology","Radiology","Radiology","Identical","",""],["Product Code","JAK, QIH (subsequent)","JAK, LLZ (subsequent)","JAK, LLZ (subsequent)","Similar","",""],["Regulation\nDescription","Computed tomography\nx-ray system (primary).\nMedical image\nmanagement and\nprocessing system\n(subsequent).","Computed tomography\nx-ray system (primary)\nMedical image\nmanagement and\nprocessing system\n(subsequent)","Computed\ntomography x-ray\nsystem (primary)\nMedical image\nmanagement and\nprocessing system\n(subsequent)","Identical","",""],["Regulation\nNumber","21 CFR 892.1750\n21 CFR 892.2050","21 CFR 892.1750\n21 CFR 892.2050","21 CFR 892.1750\n21 CFR 892.2050","Identical","",""]],"caption_candidate":"Table 1. Substantial Equivalence","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260169-p10-t0","doc_id":"K260169","page_num":10,"bbox":[72.31,72.35,523.13,777.22],"n_rows":10,"n_cols":7,"columns":["Comparison\nFeature","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","Comparis",""],"rows":[["Comparison\nFeature","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","Comparis",""],["","","","","","on",""],["","","","","","between",""],["","","","","","the",""],["","","","","","subject",""],["","","","","","and",""],["","","","","","predicate",""],["","","","","","(identical/",""],["","","","","","different)",""],["Indications for\nUse","The AV Cardiac CT\napplications are\nintended to assist the\nuser in viewing,\nprocessing, analysis of\nCT datasets and in\npreparation of cardiac\ninterventions.\nThe CT Coronary\nAnalysis application is\nindicated to assist\nradiologists,\ncardiologists, and 3D\ntechnologists in the\nanalysis of coronary\nartery anatomy for\npatients with suspected\nor diagnosed cardiac\ndisease including\ncoronary artery disease.\nThe CT Functional\nAnalysis application is\nindicated to assist\nradiologists,\ncardiologists, and 3D\ntechnologists in the\nanalysis of heart\nanatomy and function,\nfor patients with\nsuspected or diagnosed\ncardiac diseases.","The Philips Spectral CT\nApplications support\nviewing and analysis of\nimages at energies\nselected from the\navailable spectrum in\norder to provide\ninformation about the\nchemical composition of\nthe body materials\nand/or contrast agents.\nThe Spectral CT\nApplications provide for\nthe quantification and\ngraphical display of\nattenuation, material\ndensity, and effective\natomic number. This\ninformation may be\nused by a trained\nhealthcare professional\nas a diagnostic tool for\nthe visualization and\nanalysis of anatomical\nand pathological\nstructures.\nThe Spectral enhanced\nAdvanced Vessel\nAnalysis (sAVA)\napplication is intended\nto assist clinicians in\nviewing and evaluating\nCT images, for the\ninspection of contrast-\nenhanced vessels.\nThe Spectral enhanced\nComprehensive Cardiac\nAnalysis (sCCA)\napplication is intended","CardlQ Suite is a non-\ninvasive software\napplication designed\nto provide an\noptimized application\nto analyze\ncardiovascular\nanatomy and\npathology based on\n2D or 3D CT cardiac\nnon contrast and\nangiography DICOM\ndata from\nacquisitions of the\nheart. It provides\ncapabilities for the\nvisualization and\nmeasurement of\nvessels and\nvisualization of\nchamber mobility.\nCardlQ Suite also aids\nin diagnosis and\ndetermination of\ntreatment paths for\ncardiovascular\ndiseases to include,\ncoronary artery\ndisease, functional\nparameters of the\nheart, heart\nstructures and\nfollow-up for stent\nplacement, bypasses\nand plaque imaging.\nCardlQ Suite provides\ncalcium scoring, a\nnon-invasive\nsoftware application,\nthat can be used with","Different","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260169-p11-t0","doc_id":"K260169","page_num":11,"bbox":[72.3,72.35,523.14,774.94],"n_rows":16,"n_cols":9,"columns":["Comparison\nFeature","","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","","Comparis",""],"rows":[["Comparison\nFeature","","Subject Device\nPhilips Medical Systems'\nAV Cardiac CT","Predicate Device\nPhilips Medical Systems'\nSpectral CT Applications\n(K150665)","Reference device GE\nMedical Systems’\nCardIQ Suite","","","Comparis",""],["","","","","","","","on",""],["","","","","","","","between",""],["","","","","","","","the",""],["","","","","","","","subject",""],["","","","","","","","and",""],["","","","","","","","predicate",""],["","","","","","","","(identical/",""],["","","","","","","","different)",""],["","","","to assist clinicians in\nviewing and evaluating\ncardiovascular CT\nimages.\nThe Spectral enhanced\nTumor Tracking (sTT)\napplication is intended\nto assist clinicians in\nviewing and evaluating\nCT images, for the\ninspection of tumors.","non-contrasted\ncardiac images to\nevaluate calcified\nplaques in the\ncoronary arteries,\nheart valves and\ngreat vessels such as\nthe aorta. Calcium\nScoring may be used\nto monitor the\nprogression/regressio\nn of calcium in\ncoronary arteries\novertime, which may\naid in the prognosis\nof cardiac disease.","","","",""],["","Clinical Characteristics","","","","","","",""],["Intended body\npart","","Cardiovascular anatomy\n(heart and coronary vess\nels)","Cardiovascular anatomy\n(heart and coronary vess\nels)","Cardiovascular\nanatomy\n(heart and coronary v\nessels)","","Identical","",""],["Type of scans","","CT scans\n(conventional and\nspectral)","CT scans\n(conventional and\nspectral)","CT scans","","Identical","",""],["","Technological features","","","","","","",""],["DICOM","","Yes","Yes","Yes","","Identical","",""],["Coronary\nartery\nsegmentation\nincluding\nautomated\ncenterline\nextraction,\nvessel\nlabelling,\nlumen, and","","Yes\nIncludes new algorithm\nfor centerline extraction\n(CNN - deep learning\ncomponent included),\nupdated vessel labelling\nalgorithm (model based)\nand new lumen\nsegmentation algorithm\n(KNN model). In","Yes\nIncludes legacy\nalgorithms (non-AI) for\ncenterline extraction,\nvessel labelling, lumen\nand wall segmentation.","Yes","","Different","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260217-p5-t0","doc_id":"K260217","page_num":5,"bbox":[85.5,442.29,534.5,548.54],"n_rows":7,"n_cols":2,"columns":["Proprietary Name","AI Platform 2.2 (AIP002)"],"rows":[["Proprietary Name","AI Platform 2.2 (AIP002)"],["Common Name","AI Platform 2.2"],["Premarket Notification","K260217"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"Proposed Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260217-p5-t1","doc_id":"K260217","page_num":5,"bbox":[85.5,588.51,534.5,679.76],"n_rows":6,"n_cols":2,"columns":["Proprietary Name","AI Platform 2.0 (AIP002)"],"rows":[["Proprietary Name","AI Platform 2.0 (AIP002)"],["Premarket Notification","K240953"],["Classification Name","Automated Radiological Image Processing Software"],["Regulation Number","21 CFR 892.2050"],["Product Code","QIH"],["Regulatory Class","II"]],"caption_candidate":"Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260217-p7-t0","doc_id":"K260217","page_num":7,"bbox":[73.63,399.87,540.25,710.5],"n_rows":3,"n_cols":3,"columns":["Feature/\nFunction","Subject Device\nExo AI Platform 2.2","Predicate Device:\nExo AI platform 2.0\n(K240953)"],"rows":[["Feature/\nFunction","Subject Device\nExo AI Platform 2.2","Predicate Device:\nExo AI platform 2.0\n(K240953)"],["Indications for Use","AI Platform 2.2 is intended for\nnoninvasive processing of ultrasound\nimages to detect, measure, and\ncalculate relevant medical parameters\nof structures and function of patients\nwith suspected disease. In addition, it\ncan provide Quality Score feedback to\nassist healthcare professionals, trained\nand qualified to conduct\nechocardiography, abdominal, and\nlung ultrasound scans in the current\nstandard of care while acquiring\nultrasound images. The device is\nintended to be used on images of\nadult patients.","AI Platform 2.0 is intended for\nnoninvasive processing of ultrasound\nimages to detect, measure, and\ncalculate relevant medical parameters\nof structures and function of patients\nwith suspected disease. In addition, it\ncan provide Quality Score feedback to\nassist healthcare professionals, trained\nand qualified to conduct\nechocardiography and lung ultrasound\nscans in the current standard of care\nwhile acquiring ultrasound images.\nThe device is intended to be used on\nimages of adult patients."],["Scan type","Single and Multi-frame ultrasound\nimages","Same as subject device. No changes\nwere made."]],"caption_candidate":"Comparison of Technological Characteristics with the Predicate Device","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260217-p8-t0","doc_id":"K260217","page_num":8,"bbox":[74.64,111.59,540.33,676.5],"n_rows":9,"n_cols":3,"columns":["Feature/\nFunction","Subject Device\nExo AI Platform 2.2","Predicate Device:\nExo AI platform 2.0\n(K240953)"],"rows":[["Feature/\nFunction","Subject Device\nExo AI Platform 2.2","Predicate Device:\nExo AI platform 2.0\n(K240953)"],["Principle of Operation\nand Technology","Ultrasound image processing software\nimplementing artificial intelligence,\nincluding non-adaptive machine\nlearning algorithms trained with clinical\ndata intended for non-invasive\nanalysis of ultrasound data","Same as subject device. No changes\nwere made."],["AI Algorithm","Deep Convolutional Neural Networks\nfor Segmentation, Landmark Detection\nand Classification","Same as subject device. No changes\nwere made."],["Cardiac\nMeasurements","LVEF\nIVC Minimum diameter on inspiration\nand Maximum diameter on expiration\nMyocardium wall thickness\n(Interventricular Septum and Posterior\nwall) from Plax view","Same as subject device. No changes\nwere made."],["Non Cardiac AI\nmodules","Absence/presence of A-lines\nB-lines count","Same as subject device. No changes\nwere made."],["Real-time feedback on\nquality","Yes","Same as subject device. No changes\nwere made."],["Anatomical Sites for\nQuality AI","Heart, Lungs, and Abdomen","Heart, Lungs"],["Retrospectively\nrecording of\nDiagnostic quality clip","Yes","Same as subject device. No changes\nwere made."],["AI modules are an\naccessory to\ncompatible general\npurpose diagnostic\nultrasound systems","Yes","Same as subject device. No changes\nwere made."]],"caption_candidate":"510(k) Summary - AI Platform 2.2","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p7-t0","doc_id":"K260265","page_num":7,"bbox":[110.22,316.18,540.52,491.05],"n_rows":7,"n_cols":3,"columns":["Type","Modification Type for","Feature"],"rows":[["Type","Modification Type for","Feature"],["","subject devices",""],["Hardware","New\ncompared to predicate","- Spine support respiratory (Cushion) as a part\nof BM Spine Coil Set 1.5T (including new\nsurface material)"],["","",""],["Software","New\nsame as predicate,\nbut with new Upgrade\nOption","- Gradient Configuration Upgrade"],["","",""],["Other\nModifications\nand / or Minor\nChanges","Modified\nsame as predicate,\nbut with new claim\nintroduced","- PETRA (new claim for the existing sequence)"]],"caption_candidate":"software is provided below:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p7-t1","doc_id":"K260265","page_num":7,"bbox":[110.22,560.02,532.47,734.34],"n_rows":5,"n_cols":3,"columns":["Type","Modification Type for","Feature"],"rows":[["Type","Modification Type for","Feature"],["","subject devices",""],["Hardware","New\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- BioMatrix Dockable Table\nwith / without eDrive\n- Comfort Sound: Cushion"],["","Modified\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- Comfort Sound: BM Head/Neck Coil\n- Relocatable Option"],["","",""]],"caption_candidate":"(K252838), to the subject devices without any modifications:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p8-t0","doc_id":"K260265","page_num":8,"bbox":[110.09,104.82,532.74,500.28],"n_rows":5,"n_cols":3,"columns":["Software","New\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- Open Workflow"],"rows":[["Software","New\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- Open Workflow"],["","Modified\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- BioMatrix Motion Sensor (SAMER)\n- CS_VIBE\n- SPAIR FatSat Improvements:\nSPAIR “Abdomen & Pelvis” mode and SPAIR\nBreast mode\n- Deep Resolve Boost for FL3D_VIBE and\nSPACE\n- Deep Resolve Sharp for FL3D_VIBE and\nSPACE\n- Preview functionality for Deep Resolve Boost\n- myExam Implant Suite\n- GRE_PC\n- Open Recon 2.0\n- Deep Resolve Boost for TSE\n- “MTC Mode” for SPACE"],["","",""],["Other\nModifications\nand / or Minor\nChanges","New\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- Eco Power Mode Pro"],["","Modified\ncompared to predicate,\nsame as reference\n(K252838)\n(transferred without\nmodifications)","- Off-Center Planning Support\n- Flip Angle Optimization (Lock TR and FA)\n- ID Gain (re-naming)\n- Marketing bundle “myExam Companion”"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p8-t1","doc_id":"K260265","page_num":8,"bbox":[110.09,569.55,540.1,662.94],"n_rows":4,"n_cols":4,"columns":["Predicate Devices","FDA Clearance Number","Product","Manufacturer"],"rows":[["Predicate Devices","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Flow.Ace with\nsyngo MR XA70A","K250436,\ncleared on\nJune 16, 2025","LNH\nLNI, MOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."],["MAGNETOM Flow.Plus\nwith Syngo MR XA70A","K250436,\ncleared on\nJune 16, 2025","LNH\nLNI, MOS","Siemens Shenzhen\nMagnetic Resonance\nLtd."]],"caption_candidate":"are substantially equivalent to the following predicate devices:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p9-t0","doc_id":"K260265","page_num":9,"bbox":[109.61,104.97,537.06,163.38],"n_rows":3,"n_cols":4,"columns":["Reference Device","FDA Clearance Number","Product","Manufacturer"],"rows":[["Reference Device","FDA Clearance Number","Product","Manufacturer"],["","and Date","Code",""],["MAGNETOM Flow.Neo\nwith Syngo MR XB10","K252838,\ncleared on\nDecember 19, 2025","LNH\nLNI, MOS","Siemens Healthineers\nAG"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p9-t1","doc_id":"K260265","page_num":9,"bbox":[109.61,422.9,537.06,732.6],"n_rows":19,"n_cols":6,"columns":["","","","","","Reference"],"rows":[["","","","","","Reference"],["","Subject Devices","","Predicate Devices","",""],["","","","","","Device"],["","","","","",""],["","MAGNETOM","","MAGNETOM","MAGNETOM","MAGNETOM"],["Hardware","","MAGNETOM","","",""],["","Flow.Ace with","","Flow.Ace with","Flow.Plus with","Flow.Neo with"],["","","Flow.Plus with","","",""],["","Syngo MR","","syngo MR","syngo MR","Syngo MR"],["","","Syngo MR XB10","","",""],["","XB10","","XA70A","XA70A","XB10"],["","","","","",""],["Magnet System","Yes, same as predicate,\nbut with relocatable option (same\nas reference)","","Yes","","Yes"],["RF System","Yes, same as predicate device","","Yes","","Yes"],["Transmission\ntechnique –\nRF Body Coil","Yes, same as predicate device","","Yes","","Yes"],["Gradient\nSystem","Yes, same as predicate device,\nbut with a new Gradient\nConfiguration Upgrade from B60 to\nG60","","Yes","","Yes"],["Patient Table","Yes, new compared to predicate,\nbut same as reference:\n- BioMatrix Dockable Table with\n/ without eDrive","","Yes","","Yes"],["Computer","Yes, same as predicate device","","Yes","","Yes"],["Coils","Yes, modified compared to\npredicate, but same as reference:\n- Comfort Sound for BM\nHead/Neck Coil","","Yes","","Yes"]],"caption_candidate":"Table 1: Hardware Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p10-t0","doc_id":"K260265","page_num":10,"bbox":[111.55,255.68,537.9,703.08],"n_rows":14,"n_cols":6,"columns":["","","","","","Reference"],"rows":[["","","","","","Reference"],["","Subject Devices","","Predicate Devices","",""],["","","","","","Device"],["","","","","",""],["","MAGNETOM","","MAGNETOM","MAGNETOM","MAGNETOM"],["Hardware","","MAGNETOM","","",""],["","Flow.Ace with","","Flow.Ace with","Flow.Plus with","Flow.Neo with"],["","","Flow.Plus with","","",""],["","Syngo MR","","syngo MR","syngo MR","Syngo MR"],["","","Syngo MR XB10","","",""],["","XB10","","XA70A","XA70A","XB10"],["","","","","",""],["Sequences","","","","",""],["SE-based pulse\nsequence types","Yes, modified compared to\npredicate, but same as reference:\nSE:\n- with ID Gain\nTSE:\n- with Deep Resolve Boost\nimprovement\n- with Preview functionality for\nDeep Resolve Boost\n- with SPAIR \"Abdomen&Pelvis\"\nmode and SPAIR Breast mode\n- with ID Gain\nTSE_DIXON:\n- with ID Gain\nHASTE:\n- with Deep Resolve Boost (e.g.\npreview functionality)\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode\nSPACE:\n- with \"MTC Mode\" improvement -\nwith Deep Resolve Boost (e.g.\npreview functionality)\n- with Deep Resolve Sharp\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode\nBLADE:\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode","","Yes","","Yes"]],"caption_candidate":"Table 2. Software Features Comparison","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p11-t0","doc_id":"K260265","page_num":11,"bbox":[110.87,104.82,538.38,736.5],"n_rows":12,"n_cols":4,"columns":["GRE-\nbased/Steady-\nState Pulse\nSequence Types","Yes, modified compared to\npredicate, but same as reference:\nFL3D_VIBE:\n- with Deep Resolve Boost (e.g.\npreview functionality)\n- with Deep Resolve Sharp\n- with Compressed Sensing (CS-\nVibe)\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode\nTurboFLASH (TFL):\n- with BioMatrix Motion Sensor\n(SAMER)\nGRE_PC:\n- in-plane generalized auto\ncalibrating parallel acquisition\n(GRAPPA)-based SMS formulation","Yes","Yes"],"rows":[["GRE-\nbased/Steady-\nState Pulse\nSequence Types","Yes, modified compared to\npredicate, but same as reference:\nFL3D_VIBE:\n- with Deep Resolve Boost (e.g.\npreview functionality)\n- with Deep Resolve Sharp\n- with Compressed Sensing (CS-\nVibe)\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode\nTurboFLASH (TFL):\n- with BioMatrix Motion Sensor\n(SAMER)\nGRE_PC:\n- in-plane generalized auto\ncalibrating parallel acquisition\n(GRAPPA)-based SMS formulation","Yes","Yes"],["EPI-based Pulse\nSequence Types","Yes, modified compared to\npredicate, but same as reference:\nEP2D_DIFF:\n- with Deep Resolve Boost (e.g.\npreview functionality)\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode\nRESOLVE:\n- with SPAIR “Abdomen&Pelvis”\nmode and SPAIR Breast mode","Yes","Yes"],["Spectroscopy\nPulse Sequence\nTypes","Yes, same as predicate device","Yes","Yes"],["Feature and Applications","","",""],["Inline post-\nprocessing\nfunctions","Yes, modified compared to\npredicate, but same as reference:\n- with Flip Angle Optimization\n(Lock TR and FA)","Yes","Yes"],["Application\nSuites","Yes, same as predicate device","Yes","Yes"],["myExam","Yes, same as predicate device","Yes","Yes"],["Other Imaging\nApplications","Yes, modified compared to\npredicate, but same as reference:\n- myExam Implant Suite","Yes","Yes"],["Other Tim\nSuites","Yes, same as predicate device","Yes","Yes"],["Visualization","Yes, same as predicate device","Yes","Yes"],["Basic Post-\nProcessing","Yes, same as predicate device","Yes","Yes"],["Communication","Yes, same as predicate device","Yes","Yes"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p12-t0","doc_id":"K260265","page_num":12,"bbox":[110.38,104.82,539.15,356.1],"n_rows":4,"n_cols":4,"columns":["Application and\npost-processing","Yes, new compared to predicate,\nbut same as reference:\n- Open Workflow Framework\nYes, modified compared to\npredicate, but same as reference:\n- Open Recon Framework","Yes","Yes"],"rows":[["Application and\npost-processing","Yes, new compared to predicate,\nbut same as reference:\n- Open Workflow Framework\nYes, modified compared to\npredicate, but same as reference:\n- Open Recon Framework","Yes","Yes"],["Other Software\nFeature /\nApplication","Yes, same as predicate device","Yes","Yes"],["Software\nPlatform and\nGeneral\nWorkflow","Yes, new compared to predicate,\nbut same as reference:\n- Eco Power Mode Pro","Yes","Yes"],["Other\nModifications /\nMinor Changes","Yes, same as predicate, but new\nclaim introduced\n- PETRA\nYes, modified compared to\npredicate, but same as reference:\n- Off-Center Planning Support\n- Marketing bundle “myExam\nCompanion”","Yes","Yes"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p13-t0","doc_id":"K260265","page_num":13,"bbox":[109.87,104.97,534.54,395.34],"n_rows":6,"n_cols":2,"columns":["Feature / Function","Clinical Publication"],"rows":[["Feature / Function","Clinical Publication"],["BioMatrix Motion\nSensor (SAMER)","[1] Polak D, Splitthoff DN, Clifford B, Lo W-C, Huang SY, Conklin J,\nWald LL, Setsompop K, Cauley S: Scout accelerated motion estimation\nand reduction (SAMER); Magn Reason Med 87:163-178 (2022).\nhttps://doi.org/10.1002/mrm.28971"],["","[2] Lang M, Tabari A, Polak D, Ford J, Clifford B, Lo W-C, Manzoor K,\nSplitthoff DN, Wald LL, Rapalino O, Schaefer P, Conklin P, Cauley S,\nHuang SY: Clinical Evaluation of Scout Accelerated Motion Estimation\nand Reduction Technique for 3D MR Imaging in the Inpatient and\nEmergency Department Settings; Am J Neuroradiol 44:125-133 (2023).\nhttps://doi.org/10.3174/ajnr.A7777"],["CS_VIBE","[3] Vreemann, S., Rodriguez-Ruiz, A., Nickel, D., Heacock, L., Appelman,\nL., van Zelst, J., Karssemeijer, N., Weiland, E., Maas, M., Moy, L., Kiefer,\nB., & Mann, R. M. (2017). Compressed Sensing for Breast MRI:\nResolving the Trade-Off Between Spatial and Temporal Resolution.\nInvestigative Radiology, 52(10), 574–582.\nhttps://doi.org/10.1097/rli.0000000000000384"],["PETRA","[4] Grodzki DM, Jakob PM, Heismann B. Ultrashort echo time imaging\nusing pointwise encoding time reduction with radial acquisition (PETRA).\nMagn Reson Med. 2012 Feb;67(2):510-8. doi: 10.1002/mrm.23017. Epub\n2011 Jun 30. PMID: 21721039."],["","[5] Li C, Magland JF, Zhao X, Seifert AC, Wehrli FW. Selective in vivo\nbone imaging with long-T2 suppressed PETRA MRI. Magn Reson Med.\n2017 Mar;77(3):989-997. doi: 10.1002/mrm.26178. Epub 2016 Feb 24.\nPMID: 26914767."]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260265-p14-t0","doc_id":"K260265","page_num":14,"bbox":[109.74,104.97,540.13,673.8],"n_rows":13,"n_cols":5,"columns":["Recogniti","on Product","Title of Standard","Reference","Standards"],"rows":[["Recogniti","on Product","Title of Standard","Reference","Standards"],["Number","Area","","Number and date","Development"],["","","","","Organization"],["19-46","General II\n(ES/ EMC)","Medical electrical equipment -\nPart 1: General requirements for\nbasic safety and essential\nperformance (IEC 60601-\n1:2005, MOD)","ES60601-1:2005\n/(R)2012 &\nA1:2012,\nC1:2009/(R)2012\n&A2:2010/(R)2012\n(Cons. Text)\n[Incl.AMD2:2021]","ANSI AAMI"],["19-36","General","Medical electrical equipment -\nPart 1-2: General requirements\nfor basic safety and essential\nperformance - Collateral\nStandard: Electromagnetic\ndisturbances - Requirements\nand tests","60601-1-2 Edition\n4.1 2020-09","IEC"],["12-347","Radiology","Medical electrical equipment -\nPart 2-33: Particular\nrequirements for the basic\nsafety and essential\nperformance of magnetic\nresonance equipment for\nmedical diagnosis","60601-2-33 Edition\n4.0 2022-08","IEC"],["5-125","General I\n(QS/ RM)","Medical devices - Application of\nrisk management to medical\ndevices","14971 Third edition\n2019-12","ISO"],["5-129","General I\n(QS/ RM)","Medical devices - Part 1:\nApplication of usability\nengineering to medical devices","62366-1: 2015 +\nAMD1:2020","ANSI\nAAMI\nIEC"],["13-79","Software/\nInformatics","Medical device software -\nSoftware life cycle processes\n[Including Amendment 1 (2016)]","IEC 62304:2006 +\nAMD1:2015","IEC"],["12-232","Radiology","Acoustic Noise Measurement\nProcedure for Diagnosing\nMagnetic Resonance Imaging\nDevices","MS 4-2010","NEMA"],["12-288","Radiology","Standards Publication\nCharacterization of Phased\nArray Coils for Diagnostic\nMagnetic Resonance Images","MS 9-2008 (R2020)","NEMA"],["12-352","Radiology","Digital Imaging and\nCommunications in Medicine\n(DICOM)","PS 3.1 - 3.20\n(2023e)","NEMA"],["2-258","Biocompati\nbility","Biological evaluation of medical\ndevices - part 1: evaluation and\ntesting within a risk\nmanagement process.\n(Biocompatibility)","10993-1: 2018","ANSI\nAAMI\nISO"]],"caption_candidate":"510(k) Summary","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p5-t0","doc_id":"K260509","page_num":5,"bbox":[72.25,215.43,540.25,455.5],"n_rows":9,"n_cols":2,"columns":["Table 1: Submitter’s Information",""],"rows":[["Table 1: Submitter’s Information",""],["Submitter’s Name:","Kevin Robinson"],["Company:","Radformation, Inc."],["Address:","261 Madison Avenue, 9th Floor\nNew York, NY 10016"],["Contact Person:","Kevin Robinson\nVP of Regulatory Affairs, Radformation"],["Phone:","585-500-6996"],["Fax:","—"],["Email:","regulatory@radformation.com"],["Date of Summary Preparation","2/13/2026"]],"caption_candidate":"1. Submitter’s Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p5-t1","doc_id":"K260509","page_num":5,"bbox":[72.25,514.59,540.25,719.5],"n_rows":8,"n_cols":2,"columns":["Table 2 : Device Information",""],"rows":[["Table 2 : Device Information",""],["Trade Name:","AutoContour Model RADAC V5"],["Common Name:","AutoContour, AutoContouring, AutoContour Agent,\nAutoContour Cloud Server"],["Classification Name:","Class II"],["Classification:","Medical image management and processing system"],["Regulation Number:","892.2050"],["Product Code:","QKB"],["Classification Panel:","Radiology"]],"caption_candidate":"2. Device Information","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p7-t0","doc_id":"K260509","page_num":7,"bbox":[72.13,217.48,552.69,723.5],"n_rows":9,"n_cols":4,"columns":["Table 11: Substantial Equivalence AutoContour Model RADAC V5 vs. AutoContour Model\nRADAC V4 (K242729)","","",""],"rows":[["Table 11: Substantial Equivalence AutoContour Model RADAC V5 vs. AutoContour Model\nRADAC V4 (K242729)","","",""],["Characteristic","Subject Device:\nAutoContour Model\nRADAC V5","Predicate Device:\nAutoContour Model\nRADAC V4 (K242729)","Reference Device\nLimbus Contour (K241837)\nUsed for Verification"],["AutoContour vs. PredicateDevices: Technological Characteristics","","",""],["Indications for\nUse","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in\npreparation for radiation\ntherapy treatment planning","AutoContour is intended to\nassist radiation treatment\nplanners in contouring and\nreviewing structures within\nmedical images in\npreparation for radiation\ntherapy treatment planning","Limbus Contour is a\nsoftware-only medical\ndevice intended for use by\ntrained radiation\noncologists, dosimetrists,\nand physicists to derive\noptimal contours for input to\nradiation treatment\nplanning."],["Target\nPopulation","Any patient type for whom\nrelevant modality scan\ndata is available.","Any patient type for whom\nrelevant modality scan data\nis available.","Any patient type for whom\nrelevant modality scan data\nis available."],["Energy Used\nand/or\nDelivered","None – software-only\napplication. The software\napplication does not\ndeliver or depend on\nenergy delivered to or\nfrom patients","None – software-only\napplication. The software\napplication does not deliver\nor depend on energy\ndelivered to or from patients","None – software-only\napplication. The software\napplication does not deliver\nor depend on energy\ndelivered to or from patients"],["Intended users","Trained radiation oncology\npersonnel","Trained radiation oncology\npersonnel","Trained radiation oncology\npersonnel"],["Design: Data\nVisualization/G\nraphical User\nInterface","Contains both an\nautomated processing\ncomponent and Data\nVisualization / Graphical\nUser Interface","Contains both an\nautomated processing\ncomponent and Data\nVisualization / Graphical\nUser Interface","Contains an automated\nprocessing component."],["Design: View\nmanipulation\nand Volume\nrendering","Window and level, pan,\nzoom, cross-hairs, slice\nnavigation, fused views.","Window and level, pan,\nzoom, cross-hairs, slice\nnavigation, fused views.","None"]],"caption_candidate":"RADAC V4.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p8-t0","doc_id":"K260509","page_num":8,"bbox":[72.25,72.5,552.63,741.5],"n_rows":3,"n_cols":4,"columns":["Design: Image\nregistration","Manual and Automatic\nRigid registration.\nAutomatic Deformable\nRegistration","Manual and Automatic\nRigid registration.\nAutomatic Deformable\nRegistration","None"],"rows":[["Design: Image\nregistration","Manual and Automatic\nRigid registration.\nAutomatic Deformable\nRegistration","Manual and Automatic\nRigid registration.\nAutomatic Deformable\nRegistration","None"],["AutoContour vs. Predicate and Reference: Model Comparison","","",""],["Regions and\nVolumes of\ninterest (ROI)","CT or MR input for\ncontouring of anatomical\nregions: Head and Neck,\nThorax, Abdomen and\nPelvis.\nMachine learning based\ncontouring of 420\nCT-based and 62\nMR-based models and\nmanual ROI manipulation\nCT Models:\n● A_Aorta\n● A_Aorta_Asc\n● A_Aorta_Dsc\n● A_Brachiocephls\n● A_Carotid_L\n● A_Carotid_R\n● A_Celiac*\n● A_Circumflex_L\n● A_Coronary_2d_R\n● A_Coronary_L\n● A_Coronary_R\n● A_LAD\n● A_Mesenteric_S*\n● A_Pulmonary*\n● A_Subclavian_L\n● A_Subclavian_R\n● Atrium_L*\n● Atrium_R*\n● AV_Node\n● Barrigel™\n● BileDuct_Common\n● Bladder*\n● Bladder_CBCT*\n● Bladder_F*\n● Body*\n● Body+Mask*\n● Bone_Hyoid*\n● Bone_Ilium*\n● Bone_Ilium_L*\n● Bone_Ilium_R*\n● Bone_Ischium_L*\n● Bone_Ischium_R*\n● Bone_Mandible*\n● Bone_Pelvic*\n● Bone_Pterygoid_L\n● Bone_Pterygoid_R","CT or MR input for\ncontouring of anatomical\nregions: Head and Neck,\nThorax, Abdomen and\nPelvis.\nMachine learning based\ncontouring of 260\nCT-based and 35\nMR-based models and\nmanual ROI manipulation\nCT Models:\n● A_Aorta\n● A_Aorta_Asc\n● A_Aorta_Dsc\n● A_Brachiocephls\n● A_Carotid_L\n● A_Carotid_R\n● A_Coronary\n● A_LAD\n● A_Pulmonary\n● A_Subclavian_L\n● A_Subclavian_R\n● Atrium_L\n● Atrium_R\n● Bladder\n● Bladder_F\n● Bone_Hyoid\n● Bone_Ilium_L\n● Bone_Ilium_R\n● Bone_Mandible\n● Bone_Pelvic\n● Bone_Skull\n● Bone_Sternum\n● Bone_Teeth\n● Bowel\n● Bowel_Bag\n● Bowel_Large\n● Bowel_Small\n● BrachialPlex_L\n● BrachialPlex_R\n● Brain\n● Brainstem\n● Breast_L\n● Breast_R\n● Breast_Prone\n● Bronchus\n● BuccalMucosa","CT or MR input for\ncontouring of anatomical\nregions: Head and Neck,\nThorax, Abdomen and\nPelvis.\nCT Models\n● A_Aorta\n● A_Aorta_Base\n● A_Aorta_I\n● A_Aorta_l\n● A_Celiac\n● A_LAD\n● A_Mesenteric_S\n● A_Pulmonary\n● Atrium_L\n● Atrium_R\n● Bag_Bowel\n● Bag_Bowel_Extend\n● Bag_Bowel_Full\n● Bag_Bowel_S\n● Bladder\n● Bladder_CBCT\n● Bladder_HDR\n● Body\n● Body+Mask\n● Bone_Hyoid\n● Bone_Hyoid\n● Bone_Ilium_L\n● Bone_Ilium\n● Bone_Ilium_L\n● Bone_Ilium_R\n● Bone_Ischium_L\n● Bone_Ischium_R\n● Bone_Mandible\n● Bone_Pelvic\n● BoneMarrow_Pelvic\n● Bowel\n● Bowel_Bag\n● Bowel_Bag_Extend\n● Bowel_Bag_Full\n● Bowel_Bag_Superior\n● Bowel_Extend\n● Bowel_Full\n● Bowel_HDR\n● Bowel_S\n● Bowel_Superior\n● BrachialPlex_L\n● BrachialPlex_R\n● BrachialPlexs\n● Brain\n● Brainstem\n● Breast_Implant_L\n● Breast_Implant_R\n● Breast_L"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p9-t0","doc_id":"K260509","page_num":9,"bbox":[157.5,79.35,528.24,730.51],"n_rows":63,"n_cols":6,"columns":["●","Bone_PubicSymphys*","●","Carina","●","Breast_R"],"rows":[["●","Bone_PubicSymphys*","●","Carina","●","Breast_R"],["●","Bone_Sacrum*","●","CaudaEquina","●","Breasts"],["●","Bone_Skull","●","Cavity_Oral","●","Bronchus"],["●","Bone_Sternum*","●","Cavity_Oral_Ext","●","Canal_Anal"],["","","","","●","Canal_Anal_HDR"],["●","Bone_Teeth","●","Chestwall_L","●","Carina"],["●","Bowel","●","Chestwall_OAR","●","CaudaEquina"],["●","Bowel_Bag*","●","Chestwall_R","●","Cavity_Oral"],["●","Bowel_Bag_F","●","Chestwall_RC_L","●","Cerebellum"],["●","Bowel_F","●","Chestwall_RC_R","●","Chestwall"],["●","Bowel_Large","●","Clavicle_L","●","Chestwall_L"],["","","","","●","Chestwall_R"],["●","Bowel_Large_F","●","Clavicle_R","●","Chestwalls"],["●","Bowel_Small","●","Cochlea_L","●","Clavicle_L"],["●","Bowel_Small_F","●","Cochlea_R","●","Clavicle_R"],["●","BrachialPlex_L","●","Colon_Sigmoid","●","Cochlea_L"],["●","BrachialPlex_R","●","Cornea_L","●","Cochlea_R"],["●","BrachialPlexs","●","Cornea_R","●","Colon_Sigmoid"],["●","Brain","●","Dental_Artifact","●","Colon_Sigmoid_HDR"],["","","","","●","Cornea_L"],["●","Brainstem","●","Duodenum","●","Cornea_R"],["●","Breast_Implant_L*","●","Ear_Internal_L","●","Duodenum"],["●","Breast_Implant_R*","●","Ear_Internal_R","●","Esophagus"],["●","Breast_L","●","Esophagus","●","Eye_L"],["●","Breast_Prone","●","External","●","Eye_R"],["●","Breast_R","●","Eye_L","●","Eyes"],["●","Breast_RTOG_L*","●","Eye_R","●","Femur_Head_L"],["","","","","●","Femur_Head_L_CBCT"],["●","Breast_RTOG_R*","●","Femur_Head_L","●","Femur_Head_R"],["●","Breast_Wire_L*","●","Femur_Head_R","●","Femur_Head_R_CBCT"],["●","Breast_Wire_R*","●","Femur_L","●","Femur_Heads"],["●","Breasts_RTOG*","●","Femur_R","●","Gallbladder"],["●","Bronchus","●","Femur_RTOG_L","●","Glnd_Lacrimal_L"],["●","BuccalMucosa","●","Femur_RTOG_R","●","Glnd_Lacrimal_R"],["","","","","●","Glnd_Submand_L"],["●","Canal_Anal*","●","Foley_Balloon","●","Glnd_Submand_R"],["●","Canal_Anal_F*","●","GallBladder","●","Glnd_Thyroid"],["●","Cardiac_Avoidance_Area","●","Genitals_F","●","GreatVes"],["●","Carina","●","Genitals_M","●","Heart"],["●","CaudaEquina","●","Glnd_Lacrimal_L","●","Heart+A_Pulm"],["●","Cavity_Oral*","●","Glnd_Lacrimal_R","●","Hippocampus_L"],["●","Cavity_Oral_Ext","●","Glnd_Submand_L","●","Hippocampus_R"],["","","","","●","Humerus_L"],["●","Cerebellum*","●","Glnd_Submand_R","●","Humerus_R"],["●","Chestwall_2cm_L*","●","Glnd_Thyroid","●","InternalAuditoryCanal_L"],["●","Chestwall_2cm_R*","●","HDR_Bladder","●","InternalAuditoryCanal_R"],["●","Chestwall_Anat*","●","HDR_Bowel","●","Kidney_L"],["●","Chestwall_Anat_L*","●","HDR_Cylinder","●","Kidney_R"],["●","Chestwall_Anat_R*","●","HDR_Rectum","●","Kidneys"],["●","Chestwall_ESTRO_L","●","Heart","●","Larynx"],["","","","","●","Lens_L"],["●","Chestwall_ESTRO_R","●","Heart_Prone","●","Lens_R"],["●","Chestwall_L","●","Hippocampus_L","●","Lips"],["●","Chestwall_OAR","●","Hippocampus_R","●","Liver"],["●","Chestwall_R","●","Humerus_L","●","LN_Ax_L1_L"],["●","Chestwall_RC_L","●","Humerus_R","●","LN_Ax_L1_R"],["●","Chestwall_RC_R","●","Iliac_Int_L","●","LN_Ax_L2_L"],["","","","","●","LN_Ax_L2_R"],["●","Clavicle_L*","●","Iliac_Int_R","●","LN_Ax_L3_L"],["●","Clavicle_R*","●","Iliac_L","●","LN_Ax_L3_R"],["●","Cochlea_L","●","Iliac_R","●","LN_Ax_Sclav_L"],["●","Cochlea_R","●","Kidney_L","●","LN_Ax_Sclav_R"],["●","Colon_Sigmoid","●","Kidney_R","●","LN_IMN_L"]],"caption_candidate":"● Bone_PubicSymphys* ● Carina ● Breast_R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p10-t0","doc_id":"K260509","page_num":10,"bbox":[157.5,79.35,516.49,730.51],"n_rows":63,"n_cols":6,"columns":["●","Colon_Sigmoid_F","●","Kidney_Outer_L","●","LN_IMN_R"],"rows":[["●","Colon_Sigmoid_F","●","Kidney_Outer_L","●","LN_IMN_R"],["●","Cornea_2d_L*","●","Kidney_Outer_R","●","LN_Neck_234_L"],["●","Cornea_2d_R*","●","Larynx","●","LN_Neck_234_R"],["●","Cornea_L","●","Larynx_Glottic","●","LN_Neck_2347AB_L"],["","","","","●","LN_Neck_2347AB_R"],["●","Cornea_R","●","Larynx_NRG","●","LN_Neck_IA"],["●","CorpusCallosum","●","Larynx_SG","●","LN_Neck_IA6"],["●","Cribriform","●","Lens_L","●","LN_Neck_IB_L"],["●","Dental_Artifact","●","Lens_R","●","LN_Neck_IB_R"],["●","Duodenum","●","Lips","●","LN_Neck_II_L"],["●","Ear_Internal_L","●","Liver","●","LN_Neck_II_R"],["●","Ear_Internal_R","●","LN_Ax_L","●","LN_Neck_III_L"],["","","","","●","LN_Neck_III_R"],["●","Esophagus","●","LN_Ax_L1_ESTRO_L","●","LN_Neck_IV_L"],["●","External","●","LN_Ax_L1_ESTRO_","●","LN_Neck_IV_R"],["●","Eye_L","","R","●","LN_Neck_L"],["●","Eye_R","●","LN_Ax_L1_L","●","LN_Neck_R"],["●","Eyes*","●","LN_Ax_L1_R","●","LN_Neck_V_L"],["●","Falx","●","LN_Ax_L2_ESTRO_L","●","LN_Neck_V_R"],["","","","","●","LN_Neck_VI"],["●","Femur_Head_L","●","LN_Ax_L2_ESTRO_","●","LN_Neck_VIIAB_L"],["●","Femur_Head_R","","R","●","LN_Neck_VIIAB_R"],["●","Femur_L","●","LN_Ax_L2_L","●","LN_Pelvics_CBCT"],["●","Femur_L_CBCT*","●","LN_Ax_L2_L3_L","●","LN_Pelvis"],["●","Femur_R","●","LN_Ax_L2_L3_R","●","LN_Sclav_L"],["●","Femur_R_CBCT*","●","LN_Ax_L2_R","●","LN_Sclav_R"],["●","Femur_RTOG_L*","●","LN_Ax_L3_ESTRO_L","●","Lung_L"],["","","","","●","Lung_R"],["●","Femur_RTOG_R*","●","LN_Ax_L3_ESTRO_","●","Lungs"],["●","Femurs_RTOG*","","R","●","Mesorectum"],["●","Foley_Balloon","●","LN_Ax_L3_L","●","Musc_Constrict"],["●","GallBladder","●","LN_Ax_L3_R","●","Musc_PecMinor_L"],["●","Genitals","●","LN_Ax_R","●","Musc_PecMinor_R"],["●","Glnd_Lacrimal_L*","●","LN_IMN_L","●","Musc_Sclmast_L"],["","","","","●","Musc_Sclmast_R"],["●","Glnd_Lacrimal_R*","●","LN_IMN_R","●","OpticChiasm"],["●","Glnd_Submand_L","●","LN_IMN_RC_L","●","OpticNrv_L"],["●","Glnd_Submand_R","●","LN_IMN_RC_R","●","OpticNrv_R"],["●","Glnd_Thyroid*","●","LN_Inguinofem_L","●","Optics"],["●","GreatVessels*","●","LN_Inguinofem_R","●","Pancreas"],["●","HDR_Bladder","●","LN_InPec_ESTRO_L","●","Parotid_L"],["●","HDR_Bowel","●","LN_InPec_ESTRO_R","●","Parotid_R"],["","","","","●","PelvisVessels"],["●","HDR_Canal_Anal*","●","LN_Neck_IA","●","PenileBulb"],["●","HDR_Colon_Sigmoid*","●","LN_Neck_IB_L","●","Pericardium"],["●","HDR_Cylinder*","●","LN_Neck_IB_R","●","Pericardium+A_Pulm"],["●","HDR_Rec-Canal_MR","●","LN_Neck_IB-V_L","●","Pituitary"],["●","HDR_Rectum","●","LN_Neck_IB-V_R","●","Prostate"],["●","HDR_Ring*","●","LN_Neck_II_L","●","Prostate_CBCT"],["●","HDR_Urethra*","●","LN_Neck_II_R","●","Prostate+SeminalVes"],["","","","","●","ProstateBed"],["●","Heart*","●","LN_Neck_II-IV_L","●","PubicSymphys"],["●","Heart_Prone","●","LN_Neck_II-IV_R","●","Rectum"],["●","Heart+A_Pulm*","●","LN_Neck_II-V_L","●","Rectum_CBCT"],["●","Hippocampus_L","●","LN_Neck_II-V_R","●","Rectum_HDR"],["●","Hippocampus_R","●","LN_Neck_III_L","●","Retina_L"],["●","Humerus_L","●","LN_Neck_III_R","●","Retina_R"],["●","Humerus_R","●","LN_Neck_IV_L","●","Ribs"],["","","","","●","Ribs Sacrum"],["●","Iliac_Int_L","●","LN_Neck_IV_R","●","Ribs_L"],["●","Iliac_Int_R","●","LN_Neck_V_L","●","Ribs_R"],["●","Iliac_L","●","LN_Neck_V_R","●","Sacrum"],["●","Iliac_R","●","LN_Neck_VIA","●","SeminalVes"]],"caption_candidate":"● Colon_Sigmoid_F ● Kidney_Outer_L ● LN_IMN_R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p11-t0","doc_id":"K260509","page_num":11,"bbox":[157.5,79.35,436.25,730.51],"n_rows":63,"n_cols":4,"columns":["● InternalAuditoryCanal_L*","●","LN_Neck_VIIA_L","● S"],"rows":[["● InternalAuditoryCanal_L*","●","LN_Neck_VIIA_L","● S"],["● InternalAuditoryCanal_R*","●","LN_Neck_VIIA_R","● S"],["● Kidney_L","●","LN_Neck_VIIB_L","● S"],["● Kidney_Outer_L*","●","LN_Neck_VIIB_R","● S"],["","","","● S"],["● Kidney_Outer_R*","●","LN_Paraaortic","● S"],["● Kidney_R*","●","LN_Pelvics_F","● S"],["● Kidneys","●","LN_Pelvics","● T"],["● Kidneys_Outer","●","LN_Pelvic_NRG","● U"],["● Larynx","●","LN_Post_Neck_L","● U"],["● Larynx_Glottic","●","LN_Post_Neck_R","● U"],["● Larynx_NRG","●","LN_Presacral","● V"],["","","","● V"],["● Larynx_SG","●","LN_Sclav_ESTRO_L","● V"],["● Lens_L","●","LN_Sclav_ESTRO_R","● V"],["● Lens_R","●","LN_Sclav_L","● V"],["● Lips*","●","LN_Sclav_R","● V"],["● Liver","●","LN_Sclav_RADCOM","● V"],["● LN_Ax_L","","P_L","● V"],["","","","● V"],["● LN_Ax_L1_2d_L*","●","LN_Sclav_RADCOM","● V"],["● LN_Ax_L1_2d_R*","","P_R","● V"],["● LN_Ax_L1_ESTRO_2d_L","●","Lobe_Temporal_L","● V"],["● LN_Ax_L1_ESTRO_2d_R","●","Lobe_Temporal_R","● V"],["● LN_Ax_L1_ESTRO_L","●","Lung_L","● V"],["● LN_Ax_L1_ESTRO_R","●","Lung_R","● V"],["● LN_Ax_L1_L","●","Macula_L","● V"],["","","","● V"],["● LN_Ax_L1_R","●","Macula_R","● V"],["● LN_Ax_L2_2d_L*","●","Marrow_Ilium_L","● V"],["● LN_Ax_L2_2d_R*","●","Marrow_Ilium_R","● V"],["● LN_Ax_L2_ESTRO_2d_L*","●","Musc_Constrict","● V"],["● LN_Ax_L2_ESTRO_2d_R*","●","Musc_Iliopsoas_L","● V"],["● LN_Ax_L2_ESTRO_L","●","Musc_Iliopsoas_R","● V"],["","","","● V"],["● LN_Ax_L2_ESTRO_R","●","Myocardium","● V"],["●","●","Nipple_L","● V"],["LN_Ax_L2_InPec_ESTRO_2","●","Nipple_Prone","● V"],["d_L*","●","Nipple_R","● V"],["●","●","OpticChiasm","● V"],["LN_Ax_L2_InPec_ESTRO_2","●","OpticNrv_L","● V"],["d_R*","●","OpticNrv_R",""],["● LN_Ax_L2_L","●","Pancreas",""],["","","","MR"],["● LN_Ax_L2_L3_L","●","Parotid_L",""],["● LN_Ax_L2_L3_R","●","Parotid_R","● B"],["● LN_Ax_L2_R","●","PenileBulb","● B"],["● LN_Ax_L3_2d_L*","●","Pericardium","● B"],["● LN_Ax_L3_2d_R*","●","Pharynx","● B"],["● LN_Ax_L3_ESTRO_2d_L*","●","Pituitary","● C"],["","","","● C"],["● LN_Ax_L3_ESTRO_2d_R*","●","Prostate","● C"],["● LN_Ax_L3_ESTRO_L","●","ProstateBed","● C"],["● LN_Ax_L3_ESTRO_R","●","Rectum","● E"],["● LN_Ax_L3_L","●","Rectum_F","● E"],["● LN_Ax_L3_R","●","Retina_L","● F"],["● LN_Ax_R","●","Retina_R","● F"],["● LN_Ax_Sclav_2d_L*","●","Rib","● H"],["","","","● H"],["● LN_Ax_Sclav_2d_R*","●","Rib01_L","● O"],["● LN_IMN_2d_L*","●","Rib01_R","● P"],["● LN_IMN_2d_R*","●","Rib02_L","● P"],["● LN_IMN_ESTRO_2d_L*","●","Rib02_R","● P"]],"caption_candidate":"● InternalAuditoryCanal_L* ● LN_Neck_VIIA_L ● SeminalVes_CBCT","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p12-t0","doc_id":"K260509","page_num":12,"bbox":[157.5,79.35,485.7,731.03],"n_rows":56,"n_cols":5,"columns":["● LN_IMN_ESTRO_2d_R*","●","Rib03_L","●","Rectum"],"rows":[["● LN_IMN_ESTRO_2d_R*","●","Rib03_L","●","Rectum"],["● LN_IMN_Expand_2d_L*","●","Rib03_R","●","Rectum_HDR"],["● LN_IMN_Expand_2d_R*","●","Rib04_L","●","Retina_L"],["●","●","Rib04_R","●","Retina_R"],["","","","●","Sacrum"],["LN_IMN_Expand_ESTRO_2","●","Rib05_L","●","SeminalVes"],["d_L*","●","Rib05_R","●","Urethra_HDR"],["●","●","Rib06_L","",""],["LN_IMN_Expand_ESTRO_2","●","Rib06_R","",""],["d_R*","●","Rib07_L","",""],["● LN_IMN_L","●","Rib07_R","",""],["● LN_IMN_R","●","Rib08_L","",""],["● LN_IMN_RC_L","●","Rib08_R","",""],["● LN_IMN_RC_R","●","Rib09_L","",""],["● LN_Inguinofem_L*","●","Rib09_R","",""],["● LN_Inguinofem_R*","●","Rib10_L","",""],["● LN_InPec_ESTRO_2d_L*","●","Rib10_R","",""],["● LN_InPec_ESTRO_2d_R*","●","Rib11_L","",""],["● LN_InPec_ESTRO_L","●","Rib11_R","",""],["● LN_InPec_ESTRO_R","●","Rib12_L","",""],["● LN_Mesorectum*","●","Rib12_R","",""],["● LN_Neck_2d_L","●","Rib_L","",""],["● LN_Neck_2d_R","●","Rib_R","",""],["● LN_Neck_CerVII_2d_L","●","SacralPlex_L","",""],["● LN_Neck_CerVII_2d_R","●","SacralPlex_R","",""],["● LN_Neck_IA","●","SeminalVes","",""],["● LN_Neck_IA_2d*","●","SpinalCanal","",""],["● LN_Neck_IA_VI_2d*","●","SpinalCord","",""],["● LN_Neck_IB_2d_L*","●","Spleen","",""],["● LN_Neck_IB_2d_R*","●","Stomach","",""],["● LN_Neck_IB_L","●","Trachea","",""],["● LN_Neck_IB_R","●","UteroCervix","",""],["● LN_Neck_IB-V_L","●","V_Brachioceph_L","",""],["● LN_Neck_IB-V_R","●","V_Brachioceph_R","",""],["● LN_Neck_II_2d_L*","●","V_Jugular_L","",""],["● LN_Neck_II_2d_R*","●","V_Jugular_R","",""],["● LN_Neck_II_L","●","V_Venacava_I","",""],["● LN_Neck_II_R","●","V_Venacava_S","",""],["● LN_Neck_III_2d_L*","●","VB","",""],["● LN_Neck_III_2d_R*","●","VB_C1","",""],["● LN_Neck_III_L","●","VB_C2","",""],["● LN_Neck_III_R","●","VB_C3","",""],["● LN_Neck_II-IV_2d_L*","●","VB_C4","",""],["● LN_Neck_II-IV_2d_R*","●","VB_C5","",""],["● LN_Neck_II-IV_L","●","VB_C6","",""],["● LN_Neck_II-IV_R","●","VB_C7","",""],["● LN_Neck_II-V_L","●","VB_L1","",""],["● LN_Neck_II-V_R","●","VB_L2","",""],["● LN_Neck_IV_2d_L*","●","VB_L3","",""],["● LN_Neck_IV_2d_R*","●","VB_L4","",""],["● LN_Neck_IV_L","●","VB_L5","",""],["● LN_Neck_IV_R","●","VB_T01","",""],["● LN_Neck_V_2d_L*","●","VB_T02","",""],["● LN_Neck_V_2d_R*","●","VB_T03","",""],["● LN_Neck_V_L","●","VB_T04","",""],["● LN_Neck_V_R","●","VB_T05","",""]],"caption_candidate":"● LN_IMN_ESTRO_2d_R* ● Rib03_L ● Rectum","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p13-t0","doc_id":"K260509","page_num":13,"bbox":[157.5,79.35,340.58,731.03],"n_rows":55,"n_cols":3,"columns":["●","LN_Neck_VI_2d*","● VB_"],"rows":[["●","LN_Neck_VI_2d*","● VB_"],["●","LN_Neck_VIA","● VB_"],["●","LN_Neck_VII_2d_L*","● VB_"],["●","LN_Neck_VII_2d_R*","● VB_"],["●","LN_Neck_VIIA_2d_L*","● VB_"],["●","LN_Neck_VIIA_2d_R*","● VB_"],["●","LN_Neck_VIIA_L","● VB_"],["●","LN_Neck_VIIA_R","● Vent"],["●","LN_Neck_VIIB_2d_L*","● Vent"],["●","LN_Neck_VIIB_2d_R*",""],["●","LN_Neck_VIIB_L MR","Models:"],["●","LN_Neck_VIIB_R","● A_P"],["●","LN_Paraaortic","● A_P"],["●","LN_Pelvics","● Blad"],["●","LN_Pelvics_CBCT*","● Blad"],["●","LN_Pelvics_F","● Brai"],["●","LN_Pelvics_NRG*","● Brai"],["●","LN_Post_Neck_L","● Cere"],["●","LN_Post_Neck_R","● Colo"],["●","LN_Presacral","● Exte"],["●","LN_Sclav_2d_L*","● Eye"],["●","LN_Sclav_2d_R*","● Eye"],["●","LN_Sclav_ESTRO_2d_L*","● Fem"],["●","LN_Sclav_ESTRO_2d_R*","● Fem"],["●","LN_Sclav_ESTRO_L","● Glnd"],["●","LN_Sclav_ESTRO_R","● Hipp"],["●","LN_Sclav_L","● Hipp"],["●","LN_Sclav_R","● Hyp"],["●","LN_Sclav_RC_L","● Hyp"],["●","LN_Sclav_RC_R","● Lens"],["●","Lobe_Temporal_L*","● Lens"],["●","Lobe_Temporal_R*","● NVB"],["●","Lung_L","● NVB"],["●","Lung_R","● Opti"],["●","Lungs","● Opti"],["●","Macula_L","● Opti"],["●","Macula_R","● Opti"],["●","Marrow_Ilium_L","● Opti"],["●","Marrow_Ilium_R","● Peni"],["●","Marrow_Pelvis*","● Pitui"],["●","Medulla","● Pros"],["●","Midbrain","● Rect"],["●","Musc_Constrict_2d*","● Rect"],["●","Musc_Constrict","● Sem"],["●","Musc_Iliopsoas_L","● Spin"],["●","Musc_Iliopsoas_R","● Uret"],["●","Musc_PecMinor_L*",""],["●","Musc_PecMinor_R*",""],["●","Musc_Sclmast_L*",""],["●","Musc_Sclmast_R*",""],["●","Myocardium",""],["●","Nipple_L",""],["●","Nipple_Prone",""],["●","Nipple_R",""],["●","OpticChiasm*",""]],"caption_candidate":"● LN_Neck_VI_2d* ● VB_T06","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p14-t0","doc_id":"K260509","page_num":14,"bbox":[157.5,79.35,275.73,731.03],"n_rows":55,"n_cols":2,"columns":["●","OpticNrv_L*"],"rows":[["●","OpticNrv_L*"],["●","OpticNrv_R*"],["●","Optics*"],["●","Pancreas*"],["●","Parametrium"],["●","Parotid_Glnd_L"],["●","Parotid_Glnd_R"],["●","Parotid_L"],["●","Parotid_R"],["●","PenileBulb"],["●","Pericardium"],["●","Pericardium_Inf*"],["●","Pericardium_Inf+A_Pulm*"],["●","Pharynx"],["●","Pituitary*"],["●","Pituitary_3d"],["●","Pons"],["●","Prostate*"],["●","Prostate_CBCT*"],["●","Prostate+SeminalVes*"],["●","Prostate+SV-Spacergel*"],["●","ProstateBed"],["●","ProstateFiducials*"],["●","Prostate-Gel_Fiducials*"],["●","Prostate-Spacergel_Vue*"],["●","Rectum"],["●","Rectum_CBCT*"],["●","Rectum_F"],["●","Rectum-Spacergel_Vue*"],["●","Retina_2d_L*"],["●","Retina_2d_R*"],["●","Retina_L"],["●","Retina_R"],["●","Rib*"],["●","Rib_L*"],["●","Rib_R*"],["●","Rib01_L"],["●","Rib01_R"],["●","Rib02_L"],["●","Rib02_R"],["●","Rib03_L"],["●","Rib03_R"],["●","Rib04_L"],["●","Rib04_R"],["●","Rib05_L"],["●","Rib05_R"],["●","Rib06_L"],["●","Rib06_R"],["●","Rib07_L"],["●","Rib07_R"],["●","Rib08_L"],["●","Rib08_R"],["●","Rib09_L"],["●","Rib09_R"],["●","Rib10_L"]],"caption_candidate":"● OpticNrv_L*","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p15-t0","doc_id":"K260509","page_num":15,"bbox":[157.5,79.35,272.0,731.55],"n_rows":56,"n_cols":2,"columns":["●","Rib10_R"],"rows":[["●","Rib10_R"],["●","Rib11_L"],["●","Rib11_R"],["●","Rib12_L"],["●","Rib12_R"],["●","SacralPlex_L"],["●","SacralPlex_R"],["●","SeminalVes*"],["●","SeminalVes_CBCT*"],["●","Sinuses"],["●","Skin*"],["",""],["●","SpaceOAR™Vue*"],["●","SpinalCanal"],["●","SpinalCord*"],["●","Spleen"],["●","Stomach"],["●","Tentorium"],["●","Trachea*"],["●","UteroCervix"],["●","V_Brachioceph_L"],["●","V_Brachioceph_R"],["●","V_Jugular_L"],["●","V_Jugular_R"],["●","V_Pulmonary"],["●","V_Venacava_I*"],["●","V_Venacava_I_UKSABR"],["●","V_Venacava_S"],["●","V_Venacava_S_UKSABR"],["●","Vagina*"],["●","Valve_Aortic"],["●","Valve_Mitral"],["●","Valve_Pulmonic"],["●","Valve_Tricuspid"],["●","VB"],["●","VB_C1"],["●","VB_C2"],["●","VB_C3"],["●","VB_C4"],["●","VB_C5"],["●","VB_C6"],["●","VB_C7"],["●","VB_L1"],["●","VB_L2"],["●","VB_L3"],["●","VB_L4"],["●","VB_L5"],["●","VB_T01"],["●","VB_T02"],["●","VB_T03"],["●","VB_T04"],["●","VB_T05"],["●","VB_T06"],["●","VB_T07"],["●","VB_T08"],["●","VB_T09"]],"caption_candidate":"● Rib10_R","well_formed":true,"extraction_settings":"text"}
{"table_id":"K260509-p17-t0","doc_id":"K260509","page_num":17,"bbox":[72.5,72.5,552.5,721.5],"n_rows":6,"n_cols":4,"columns":["","● OpticTract_R\n● PenileBulb*\n● PenileBulb_TRUFI\n● Pituitary\n● Pons\n● Prostate*\n● Rectal_Spacer\n● Rectum*\n● Retina_L*\n● Retina_R*\n● SeminalVes*\n● Sinuses\n● SpinalCord_Cerv\n● Tentorium\n● Thalamus\n● Urethra\n● Ventricle_Brain","",""],"rows":[["","● OpticTract_R\n● PenileBulb*\n● PenileBulb_TRUFI\n● Pituitary\n● Pons\n● Prostate*\n● Rectal_Spacer\n● Rectum*\n● Retina_L*\n● Retina_R*\n● SeminalVes*\n● Sinuses\n● SpinalCord_Cerv\n● Tentorium\n● Thalamus\n● Urethra\n● Ventricle_Brain","",""],["Design:\nRegion/volume\nof interest\nmeasurements\nand size\nmeasurements","None – not applicable","None – not applicable","None – not applicable"],["Design:\nRegion/Volume\nQuantification","None – not applicable","None – not applicable","None – not applicable"],["Design:\nSupported\nmodalities","CT or MR input for\ncontouring or\nregistration/fusion.\nPET/CT input for\nregistration/fusion only.\nDICOM RTSTRUCT and\nREGISTRATION for input","CT or MR input for\ncontouring or\nregistration/fusion.\nPET/CT input for\nregistration/fusion only.\nDICOM RTSTRUCT and\nREGISTRATION for input","CT or MR input for\ncontouring."],["Design:\nReporting and\ndata routing","No built-in reporting,\nsupports exporting DICOM\nRTSTRUCT,\nREGISTRATION and\nDOSE files for output.","No built-in reporting,\nsupports exporting DICOM\nRTSTRUCT,\nREGISTRATION and\nDOSE files for output.","No built-in reporting,\nsupports exporting DICOM\nRTSTRUCT files for output"],["Compatibility\nwith the\nenvironment\nand other\ndevices","Compatible with data from\nany DICOM compliant\nscanners for the\napplicable modalities.\nAgent Uploader\ncomponent compatible\nwith Microsoft Windows.\nCloud-based automatic\ncontouring service\ncompatible with Linux.","Compatible with data from\nany DICOM compliant\nscanners for the applicable\nmodalities.\nAgent Uploader component\ncompatible with Microsoft\nWindows.\nCloud-based automatic\ncontouring service\ncompatible with Linux.","No Limitation on scanner\nmodel, DICOM 3.0\ncompliance required."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p18-t0","doc_id":"K260509","page_num":18,"bbox":[72.25,72.5,552.5,232.5],"n_rows":3,"n_cols":4,"columns":["","Web application\nserver-based application\ncompatible with Linux.","Web application\nserver-based application\ncompatible with Linux.",""],"rows":[["","Web application\nserver-based application\ncompatible with Linux.","Web application\nserver-based application\ncompatible with Linux.",""],["Communication\ns/ Networking","TCP/IP","TCP/IP","N/A"],["Computer\nplatform &\nOperating\nSystem","Windows Operating\nSystem","Windows Operating System","Operating System Windows\n10 /\nWindows Server 2016 and\nAbove"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K260509-p26-t0","doc_id":"K260509","page_num":26,"bbox":[51.07,463.02,576.71,731.98],"n_rows":6,"n_cols":3,"columns":["Table 5: CT External Clinical Dataset References","",""],"rows":[["Table 5: CT External Clinical Dataset References","",""],["Model Group","Data Source ID","Data Citation"],["CT Pelvis","TCIA - Pelvic-Ref","Afua A. Yorke, Gary C. McDonald, David Solis Jr., Thomas Guerrero. (2019)\nPelvic Reference Data. The Cancer Imaging Archive. DOI:\n10.7937/TCIA.2019.woskq5oo"],["CT Head and\nNeck","TCIA -\nHead-Neck-PET-CT","Martin Vallières, Emily Kay-Rivest, Léo Jean Perrin, Xavier Liem, Christophe\nFurstoss, Nader Khaouam, Phuc Félix Nguyen-Tan, Chang-Shu Wang, Khalil\nSultanem. (2017). Data from Head-Neck-PET-CT. The Cancer Imaging Archive.\ndoi: 10.7937/K9/TCIA.2017.8oje5q00"],["CT Abdomen","TCIA -\nPancreas-CT-CB","Hong, J., Reyngold, M., Crane, C., Cuaron, J., Hajj, C., Mann, J., Zinovoy, M.,\nYorke, E., LoCastro, E., Apte, A. P., & Mageras, G. (2021). Breath-hold CT and\ncone-beam CT images with expert manual organ-at-risk segmentations from\nradiation treatments of locally advanced pancreatic cancer [Data set]. The\nCancer Imaging Archive. https://doi.org/10.7937/TCIA.ESHQ-4D90"],["CT Thorax:","TCIA - NSCLC","Aerts, H. J. W. L., Wee, L., Rios Velazquez, E., Leijenaar, R. T. H., Parmar, C.,\nGrossmann, P., Carvalho, S., Bussink, J., Monshouwer, R., Haibe-Kains, B.,\nRietveld, D., Hoebers, F., Rietbergen, M. M., Leemans, C. R., Dekker, A.,\nQuackenbush, J., Gillies, R. J., Lambin, P. (2019). Data From"]],"caption_candidate":"model training were added to the image sets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p27-t0","doc_id":"K260509","page_num":27,"bbox":[51.55,72.13,576.72,350.88],"n_rows":7,"n_cols":3,"columns":["","","NSCLC-Radiomics [Data set]. The Cancer Imaging Archive.\nhttps://doi.org/10.7937/K9/TCIA.2015.PF0M9REI"],"rows":[["","","NSCLC-Radiomics [Data set]. The Cancer Imaging Archive.\nhttps://doi.org/10.7937/K9/TCIA.2015.PF0M9REI"],["CT Thorax","TCIA - LCTSC","Yang, J., Sharp, G., Veeraraghavan, H., Van Elmpt, W., Dekker, A., Lustberg,\nT., & Gooding, M. (2017). Data from Lung CT Segmentation Challenge (Version\n3) [Data set]. The Cancer Imaging Archive.\nhttps://doi.org/10.7937/K9/TCIA.2017.3R3FVZ08"],["CT Thorax\nProne Female","TCIA- QIN-BREAST\nand Prone Thorax","Li, X., Abramson, R. G., Arlinghaus, L. R., Chakravarthy, A. B., Abramson, V.\nG., Sanders, M., & Yankeelov, T. E. (2016). Data From QIN-BREAST (Version\n2) [Data set]. The Cancer Imaging Archive.\nhttps://doi.org/10.7937/K9/TCIA.2016.21JUEBH0\nN/A- Testing data was shared from several institutions"],["CT HDR\nFemale","Female HDR Pelvis","N/A- Testing data was shared from 2 different institutions based in the United\nStates."],["CT\nProstatectomy","Pelvis ProstateBed","N/A- Testing data was shared from 1 institution based in the United States"],["CT Pelvis\nBarrigel","Barrigel™","N/A- Testing data was shared from several institutions in Australia"],["CT Pelvis\nSpaceOARVUE","SpaceOAR™_VUE","N/A- Testing data was shared from several institutions"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p27-t1","doc_id":"K260509","page_num":27,"bbox":[72.0,376.0,540.0,524.0],"n_rows":11,"n_cols":4,"columns":["DSC values were calculated between ground truth contour data and AutoContour structures and","","",""],"rows":[["DSC values were calculated between ground truth contour data and AutoContour structures and","","",""],["rated on the same DSC passing criteria used for the Training DSC validation. All structures","","",""],["passed the minimum DSC criteria for small, medium and large structures with a mean","","DSC of",""],["0.73+/-0.11, 0.84+/-0.09, and 0.93+/-0.05 respectively:","Additionally, the qualitative clinical","",""],["appropriateness of AutoContour structures generated on these scans was graded by clinical","","",""],["experts. Autocontour structures were graded on a scale from 1 to 5 where 5 refers to contour","","",""],["requiring no additional edits, and 1 refers to a score in which full manual re-contour of the","","",""],["structure would be required. An average score >= 3 was used to determine whether a structure","","",""],["model would ultimately be beneficial clinically. An average rating of 4.37 was found across all","","",""],["CT structure models demonstrating that only minor edits would be required in order to make the","","",""],["structure models acceptable for clinical use.","","",""]],"caption_candidate":"SpaceOARVUE","well_formed":true,"extraction_settings":"lines"}
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{"table_id":"K260509-p34-t0","doc_id":"K260509","page_num":34,"bbox":[72.1,202.71,540.67,725.5],"n_rows":26,"n_cols":8,"columns":["Table 8: MR Training Data Results for AutoContour Model RADAC V5","","","","","","",""],"rows":[["Table 8: MR Training Data Results for AutoContour Model RADAC V5","","","","","","",""],["MR Models","Size","Pass\nCriteria","# of\nTraining\nSets","# of\nTesting\nSets","DSC\n(Avg)","DSC\nStd Dev\n(Avg)","Lower\nBound 95%\nConfidence\nInterval"],["A_Pud_Int_L** (Update)","Small","0.50","221","56","0.69","0.08","0.56"],["A_Pud_Int_R** (Update)","Small","0.50","221","56","0.69","0.08","0.56"],["Amygdala_L","Small","0.50","493","133","0.73","0.07","0.61"],["Amygdala_R","Small","0.50","493","133","0.73","0.07","0.61"],["Bladder_Trigone** (Update)","Medium","0.65","256","65","0.72","0.05","0.64"],["Brainstem** (Update)","Medium","0.65","422","50","0.88","0.16","0.62"],["CorpusCallosum","Medium","0.65","56","15","0.72","0.25","0.31"],["Falx","Medium","0.65","178","45","0.83","0.03","0.78"],["HDR_Bowel","Medium","0.65","307","37","0.83","0.19","0.51"],["HDR_Colon_Sigmoid","Medium","0.65","240","24","0.81","0.21","0.46"],["Lens_L** (Update)","Small","0.50","208","52","0.81","0.09","0.66"],["Lens_R** (Update)","Small","0.50","208","52","0.81","0.09","0.66"],["Medulla*","Medium","0.65","N/A","N/A","N/A","N/A","N/A"],["Midbrain*","Medium","0.65","N/A","N/A","N/A","N/A","N/A"],["NVB_L** (Update)","Small","0.50","167","43","0.61","0.08","0.48"],["NVB_R** (Update)","Small","0.50","167","43","0.61","0.08","0.48"],["OpticNrv_L** (Update)","Small","0.50","164","32","0.64","0.08","0.51"],["OpticNrv_R** (Update)","Small","0.50","164","32","0.64","0.08","0.51"],["OpticTract_L** (Update)","Small","0.50","304","76","0.72","0.08","0.59"],["OpticTract_R** (Update)","Small","0.50","304","76","0.72","0.08","0.59"],["PenileBulb_TRUFI","Small","0.50","228","58","0.79","0.12","0.59"],["Pons *","Medium","0.65","N/A","N/A","N/A","N/A","N/A"],["Rectal_Spacer** (Update)","Small","0.50","233","26","0.82","0.24","0.43"],["Sinuses","Medium","0.65","178","45","0.83","0.04","0.762"]],"caption_candidate":"models, and 0.72+/- 0.09 for small models.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p35-t0","doc_id":"K260509","page_num":35,"bbox":[72.03,72.5,540.17,145.5],"n_rows":4,"n_cols":8,"columns":["Tentorium","Small","0.50","180","46","0.77","0.05","0.69"],"rows":[["Tentorium","Small","0.50","180","46","0.77","0.05","0.69"],["Thalamus","Medium","0.65","361","40","0.83","0.13","0.62"],["Urethra** (Update)","Small","0.50","390","100","0.68","0.09","0.53"],["Ventricle_Brain","Medium","0.65","182","47","0.90","0.04","0.8342"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p35-t1","doc_id":"K260509","page_num":35,"bbox":[51.06,291.04,576.44,557.59],"n_rows":15,"n_cols":4,"columns":["Table 9: MR External Clinical Dataset References","","",""],"rows":[["Table 9: MR External Clinical Dataset References","","",""],["Model Group","Data Source ID","Data Citation",""],["MR Brain","MR - Renown","N/A",""],["MR Pelvis","Gold Atlas Pelvis","Nyholm, Tufve, Stina Svensson, Sebastian Andersson, Joakim Jonsson, Maja",""],["","","Sohlin, Christian Gustafsson, Elisabeth Kjellén, et al. 2018. “MR and CT Data",""],["","","with Multi Observer Delineations of Organs in the Pelvic Area - Part of the Gold",""],["","","Atlas Project.” Medical Physics 12 (10): 3218–21. doi:10.1002/mp.12748",""],["MR Pelvis_2","SynthRad","Thummerer A, van der Bijl E, Galapon Jr A, Verhoeff JJ, Langendijk JA, Both S,",""],["","","van den Berg CAT, Maspero M. 2023. SynthRAD2023 Grand Challenge dataset:",""],["","","Generating synthetic CT for radiotherapy. Medical Physics, 50(7), 4664-4674.",""],["","","https://doi.org/10.1002/mp.16529",""],["MRLinac Pelvis","MR Linac","N/A- Testing data was shared by 2 institutions utilizing MR Linacs for image",""],["","","acquisitions.",""],["MR Female HDR\nBrachy","Female HDR MR\nPelvis","N/A- Testing data was shared by 1 institution in Canada",""],["MR Pelvis\nBarrigel","Barrigel","N/A- Testing data was shared by several institutions in Australia.",""]],"caption_candidate":"on image sets acquired that were unique to the training datasets.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p35-t2","doc_id":"K260509","page_num":35,"bbox":[72.03,568.0,540.17,739.0],"n_rows":12,"n_cols":5,"columns":["For the Brain models, datasets acquired via data-use agreement from a clinical partner were","","","",""],"rows":[["For the Brain models, datasets acquired via data-use agreement from a clinical partner were","","","",""],["acquired containing 20 MR T1 Ax post (BRAVO) image scans acquired with a GE MR750w","","","",""],["scanner. Images had an average slice thickness of 1.6mm, In-plane resolution between 0.94","","","",""],["mm, and acquisition parameters of TR=5.98ms, TE=96.8s. Data for testing of the MR Pelvis","","","",""],["structure models were acquired from 2 publicly available datasets, which contained images of","","","",""],["patients with prostate or rectal cancer, as well as 1 dataset shared from 2 institutions utilizing an","","","",""],["MR Linac.","Various scanner models and acquisition settings were used. Data for testing of the","","",""],["MR Pelvis HDR structure models were acquired from 1 institution using two different slice","","","",""],["thicknesses, 1mm and 4mm, and two different in-plane resolutions, 1mm and .72mm.","","","",""],["DSC values were calculated between ground truth contour data and AutoContour structures and","","","",""],["rated on the same DSC passing criteria as was used for the training DSC validation. All","","","",""],["structures, but one passed the minimum DSC criteria for small, and medium structures with a","","","",""]],"caption_candidate":"Barrigel","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p36-t0","doc_id":"K260509","page_num":36,"bbox":[72.0,72.0,539.85,207.0],"n_rows":10,"n_cols":3,"columns":["mean","DSC of 0.71+/-0.13, and 0.78+/-0.09 respectively.","Additionally, the qualitative clinical"],"rows":[["mean","DSC of 0.71+/-0.13, and 0.78+/-0.09 respectively.","Additionally, the qualitative clinical"],["appropriateness of AutoContour structures generated on these scans was graded by clinical","",""],["experts. Autocontour structures were graded on a scale from 1 to 5 where 5 refers to contour","",""],["requiring no additional edits, and 1 refers to a score in which full manual re-contour of the","",""],["structure would be required. An average score >= 3 was used to determine whether a structure","",""],["model would ultimately be beneficial clinically. An average rating of 4.3 was found across all MR","",""],["structure models demonstrating that only minor edits would be required in order to make the","",""],["structure models acceptable for clinical use. The single structure that did not pass the minimum","",""],["DSC criteria was also evaluated by clinical experts and scored an average of 3.90, which","",""],["demonstrates the clinical effectiveness of this model.","",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p36-t1","doc_id":"K260509","page_num":36,"bbox":[55.5,233.7,539.85,726.58],"n_rows":24,"n_cols":8,"columns":["Table 10: MR External Reviewer Results for AutoContour Model RADAC V5","","","","","","",""],"rows":[["Table 10: MR External Reviewer Results for AutoContour Model RADAC V5","","","","","","",""],["MR Models","Size","Pass\nCriteria","#\nExternal\nTest Data\nSets","Average\nDSC","Average\nDSC\nStd. Dev","Lower\nBound 95%\nConfidence\nInterval","External\nReviewer\nAverage\nRating (1-5)"],["A_Pud_Int_L (Update)","Small","0.50","39","0.57","0.11","0.39","4.30"],["A_Pud_Int_R (Update)","Small","0.50","39","0.59","0.07","0.48","4.40"],["Amygdala_L","Small","0.50","20","0.65","0.17","0.37","4.30"],["Amygdala_R","Small","0.50","19","0.66","0.17","0.48","4.10"],["Bladder_Trigone (Update)","Medium","0.65","45","0.56","0.17","0.28","4.20"],["Brainstem (Update)","Medium","0.65","20","0.93","0.02","0.90","4.80"],["CorpusCallosum","Medium","0.65","20","0.76","0.08","0.63","4.80"],["Falx","Medium","0.65","20","0.79","0.09","0.64","4.50"],["HDR_Bowel","Medium","0.65","7","0.50","0.14","0.26","3.90"],["HDR_Colon_Sigmoid","Medium","0.65","8","0.80","0.12","0.60","4.40"],["Lens_L (Update)","Small","0.50","18","0.74","0.13","0.53","4.80"],["Lens_R (Update)","Small","0.50","19","0.68","0.16","0.41","4.80"],["Medulla","Medium","0.65","19","0.82","0.09","0.67","4.40"],["Midbrain","Medium","0.65","20","0.84","0.06","0.74","4.40"],["NVB_L (Update)","Small","0.50","6","0.81","0.09","0.66","4.20"],["NVB_R (Update)","Small","0.50","6","0.83","0.04","0.76","4.10"],["OpticNrv_L (Update)","Small","0.50","20","0.75","0.17","0.47","4.20"],["OpticNrv_R (Update)","Small","0.50","20","0.70","0.17","0.42","4.40"],["OpticTract_L (Update)","Small","0.50","20","0.78","0.18","0.49","4.20"],["OpticTract_R (Update)","Small","0.50","20","0.80","0.16","0.54","4.10"],["PenileBulb_TRUFI","Small","0.50","39","0.74","0.09","0.59","4.40"],["Pons","Medium","0.65","20","0.90","0.04","0.83","4.40"]],"caption_candidate":"demonstrates the clinical effectiveness of this model.","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260509-p37-t0","doc_id":"K260509","page_num":37,"bbox":[55.5,72.25,539.83,182.75],"n_rows":6,"n_cols":8,"columns":["Rectal_Spacer (Update)","Small","0.50","18","0.80","0.09","0.65","4"],"rows":[["Rectal_Spacer (Update)","Small","0.50","18","0.80","0.09","0.65","4"],["Sinuses","Medium","0.65","20","0.79","0.18","0.49","4.30"],["Tentorium","Small","0.50","20","0.67","0.18","0.37","4.30"],["Thalamus","Medium","0.65","20","0.81","0.08","0.68","4.50"],["Urethra (Update)","Small","0.50","39","0.55","0.13","0.33","4.50"],["Ventricle_Brain","Medium","0.65","20","0.91","0.03","0.86","4.30"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260673-p5-t0","doc_id":"K260673","page_num":5,"bbox":[70.56,150.84,577.32,657.96],"n_rows":11,"n_cols":2,"columns":["Date:","March 19, 2026"],"rows":[["Date:","March 19, 2026"],["Submitter:","GE Medical Systems Ultrasound and Primary care Diagnostics, LLC\n3200 N Grandview Blvd\nWaukesha, WI 53188 USA"],["Manufacturer:","GE Medical Systems (China) Co., Ltd.\nNo. 19, Changjiang Road,\nWuxi National High-Tech Development Zone,\n214028 Jiangsu P. R. China"],["Primary Contact Person:","Lee Bush\nRegulatory Affairs Director\nGE HealthCare\nT:(262)309-9429"],["Alternate Contact Person:","Qingmeng Chen\nRegulatory Affairs Leader\nGE HealthCare\nT: +86-18180590723"],["Device Trade Name:","LOGIQ Vita, LOGIQ Vita Pro, LOGIQ Vita Express, LOGIQ Vita Plus,\nLOGIQ Vita Power, LOGIQ S20, LOGIQ S20 Pro, LOGIQ S20\nExpress, LOGIQ S20 Plus, LOGIQ S20 Power"],["Common / Usual Name:","Diagnostic Ultrasound System"],["Classification Names:","Class II"],["Product Code:","IYN (primary), IYO, ITX, QIH (secondary)\nUltrasonic Pulsed Doppler Imaging System. 21CFR 892.1550, 90-IYN;\nUltrasonic Pulsed Echo Imaging System, 21CFR 892.1560, 90-IYO;\nDiagnostic Ultrasound Transducer, 21 CFR 892.1570, 90-ITX\nMedical Image Management and Processing System, 21 CFR 892.2050,\n90-QIH"],["Primary Predicate Device:","K253366 LOGIQ Fortis Diagnostic Ultrasound System"],["Reference Device(s):","K250087 Vscan Air\nK253370 LOGIQ Totus Diagnostic Ultrasound System"]],"caption_candidate":"In accordance with 21 CFR 807.92 the following summary of information is provided:","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260673-p8-t0","doc_id":"K260673","page_num":8,"bbox":[77.79,320.42,531.33,732.12],"n_rows":7,"n_cols":6,"columns":["Characteristic","Proposed Device\nLOGIQ Vita / S20 Series","","Predicate Device","","Comparison"],"rows":[["Characteristic","Proposed Device\nLOGIQ Vita / S20 Series","","Predicate Device","","Comparison"],["","","","LOGIQ Fortis","",""],["","","","(K253366)","",""],["Touch Panel","14-inch touch panel","12.1-inch touch panel","","","Proposed devices\nuse 14-inch Touch\nPanel from LOGIQ\nTotus (K253370)."],["Monitors","23.8” High Resolution\nHDU monitor\n23.8-inch High Resolution\nLCD monitor","23.8” High contrast LED\nLCD monitor (or 23.8-\ninch High Resolution LED\nLCD monitor as an option)","","","The proposed\nLOGIQ Vita uses\n23.8inch HDU\nmonitor from\npredicate LOGIQ\nFortis (K253366)\nand the proposed\nLOGIQ S20 uses\nthe 23.8inch LCD\nmonitor from\nLOGIQ Totus\n(K253370)."],["Key Software features","Ultrasound-Guided\nAttenuation Parameter\n(UGAP), Ultrasound\nGuided Fat Fraction\n(UGFF), Auto Preset\nAssistant, Auto\nAbdominal Color\nAssistant 2.0, Auto\nAbdominal Measure\nAssistant (Renal, Aorta,\nCBD)","Ultrasound-Guided\nAttenuation Parameter\n(UGAP), Ultrasound\nGuided Fat Fraction\n(UGFF), Auto Preset\nAssistant, Auto\nAbdominal Color\nAssistant 2.0, Auto\nAbdominal Measure\nAssistant (Renal, Aorta,\nCBD), KOIS Lite","","","Identical* except\nproposed devices\ndo not support\nKoios Lite."],["Options/Utilities","Biopsy w/guidelines, Scan\nAssistant, ECG,\nFootswitch, Histogram,","Biopsy w/guidelines, Scan\nAssistant, ECG,\nFootswitch, Histogram,","","","Identical except\nproposed devices\ndo not support\nUPS."]],"caption_candidate":"Comparison table of technological characteristics with predicate device(s):","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260673-p9-t0","doc_id":"K260673","page_num":9,"bbox":[77.81,109.7,531.31,343.56],"n_rows":5,"n_cols":6,"columns":["Characteristic","Proposed Device\nLOGIQ Vita / S20 Series","","Predicate Device","","Comparison"],"rows":[["Characteristic","Proposed Device\nLOGIQ Vita / S20 Series","","Predicate Device","","Comparison"],["","","","LOGIQ Fortis","",""],["","","","(K253366)","",""],["","Video out, Service\nModem, Respirometer,\nRFID reader","Video out, Service\nModem, Respirometer,\nRFID reader, UPS","","",""],["Connectivity and\nArchive","DVR, CD/RW & DVD;\nIP/DICOM, USB; DICOM\nCompression, Modem,\nEthernet network, Multiple\nand Multiple Frame send,\nmemory stick, Vscan Air\nCL support, Send Images\nvia Email, ViewPoint on\nLOGIQ","B/W & Color printing,\nDVR, CD/RW & DVD;\nIP/DICOM, USB; DICOM\nCompression, Modem,\nEthernet network, Multiple\nand Multiple Frame send,\nmemory stick, Koios DS\nConnectivity, Vscan Air\nCL support, Send Images\nvia Email, ViewPoint on\nLOGIQ, Digital Expert\nConnectivity","","","Identical except\nproposed devices\ndo not support\nKoios DS\nConnectivity,\nDigital Expert\nConnectivity, or\nintegrated printers."]],"caption_candidate":"510(k) Premarket Notification Submission","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p4-t0","doc_id":"K260746","page_num":4,"bbox":[19.27,19.44,593.04,360.24],"n_rows":7,"n_cols":3,"columns":["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK260746 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],"rows":[["Indications for Use\nPlease type in the marketing application/submission number, if it is known. This\nK260746 ?\ntextbox will be left blank for original applications/submissions.\nPlease provide the device trade name(s). ?","",""],["Please type in the marketing application/submission number, if it is known. This\ntextbox will be left blank for original applications/submissions.","K260746",""],["Please provide the device trade name(s).","",""],["S-scan Open (100001800)","",""],["Please provide your Indications for Use below.","","?"],["The general-purpose magnetic resonance imaging (MRI) device is designed to scan any targeted area of\nthe body, to collect, display and analyse MR images and other real-time imaging procedures.\nThe indications for use are the following: imaging portions of the upper limb, including the hand, wrist,\nforearm, elbow, arm and shoulder, imaging portions of the lower limb, including the foot, ankle, calf, knee,\nthigh, hip, imaging the temporomandibular joint, imaging the cervical, the thoracic, the lumbar and the\nsacral sections as portions of the spinal column, and imaging the head.","",""],["Please select the types of uses (select one or both, as ~ Prescription Use (21 CFR 801 Subpart D)\nD\napplicable). Over-The-Counter Use (21 CFR 801 Subpart C)","","?"]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p5-t0","doc_id":"K260746","page_num":5,"bbox":[21.92,18.0,591.16,97.48],"n_rows":3,"n_cols":2,"columns":["510(k) Summary\n510(k) #: K260746 Prepared on: 2026-03-23",""],"rows":[["510(k) Summary\n510(k) #: K260746 Prepared on: 2026-03-23",""],["Contact Details 21 CFR 807.92(a)(1)",""],["","Esaote S.p.A."]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p5-t1","doc_id":"K260746","page_num":5,"bbox":[21.92,189.0,591.16,265.18],"n_rows":3,"n_cols":2,"columns":["","fda@esaote.com"],"rows":[["","fda@esaote.com"],["Device Name 21 CFR 807.92(a)(2)",""],["","S-scan Open (100001800)"]],"caption_candidate":"Applicant Contact Ms. Antonia Perrella","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p5-t2","doc_id":"K260746","page_num":5,"bbox":[21.92,358.2,591.16,408.89],"n_rows":2,"n_cols":2,"columns":["","LNH"],"rows":[["","LNH"],["Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)",""]],"caption_candidate":"Regulation Number 892.1000","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p5-t3","doc_id":"K260746","page_num":5,"bbox":[21.92,433.8,591.16,760.14],"n_rows":4,"n_cols":2,"columns":["K161973","LNH"],"rows":[["K161973","LNH"],["Device Description Summary 21 CFR 807.92(a)(4)",""],["'The S-scan Open device is a Magnetic Resonance (MR) system that produces cross-section images of the internal structures of the body.\nImages correspond to the spatial distribution of protons (hydrogen nuclei) that determine magnetic resonance properties and are\ndependent on the MR parameters, including spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity\nand chemical shift. When interpreted by a medical expert trained in use of MR equipment, the images can provide diagnostically useful\ninformation.\nS-scan Open represents the evolution of its predicate device, the Esaote S-scan, cleared under K161973 (initial clearance K063207).\nCompared to the predicate device, the following modifications have been introduced:\n-Changes to the external design and shape, and an update of the electronics.\n-Integration of the new software version MRI EVOlution 25, which provides compatibility with updated electronics, improvements in\ncybersecurity management, bug fixing and optimization, and includes the following features: management of new coils, 3D viewer,\nprone patient positioning management, SPED sequence, updated operating system, new graphical user interface, flow compensation\nfeature extension, operator-selectable gradients direction, DWI (Diffusion Weighted Imaging) sequence, 2D SST1 sequence, and\nHyperClarity. Note: the subject device integrates the AI-based algorithm HyperClarity (SwiftMR, K230854) without any modification. The\nalgorithm is classified under a different regulation in its 510(K) and this is out-of-scope from the current submission of the subject device.\n-Introduction of a patient alert system.\n-Addition of new receiving Coils: XL flex L-Spine coil 10, Flex Coil 11, Knee Coil 21.\nS-scan Open is substantially equivalent to the predicate device with respect to intended use, technical specifications, fundamental\nscientific technology and principle of operation.",""],["Intended Use/Indications for Use 21 CFR 807.92(a)(5)",""]],"caption_candidate":"Predicate # Predicate Trade Name (Primary Predicate is listed first) Product Code","well_formed":true,"extraction_settings":"lines"}
{"table_id":"K260746-p6-t0","doc_id":"K260746","page_num":6,"bbox":[19.73,18.5,593.58,772.6],"n_rows":7,"n_cols":2,"columns":["The general-purpose magnetic resonance imaging (MRI) device is designed to scan any targeted area of the body, to collect, display and\nanalyse MR images and other real-time imaging procedures.\nThe indications for use are the following: imaging portions of the upper limb, including the hand, wrist, forearm, elbow, arm and\nshoulder, imaging portions of the lower limb, including the foot, ankle, calf, knee, thigh, hip, imaging the temporomandibular joint,\nimaging the cervical, the thoracic, the lumbar and the sacral sections as portions of the spinal column, and imaging the head.",""],"rows":[["The general-purpose magnetic resonance imaging (MRI) device is designed to scan any targeted area of the body, to collect, display and\nanalyse MR images and other real-time imaging procedures.\nThe indications for use are the following: imaging portions of the upper limb, including the hand, wrist, forearm, elbow, arm and\nshoulder, imaging portions of the lower limb, including the foot, ankle, calf, knee, thigh, hip, imaging the temporomandibular joint,\nimaging the cervical, the thoracic, the lumbar and the sacral sections as portions of the spinal column, and imaging the head.",""],["","Indications for Use Comparison 21 CFR 807.92(a)(5)"],["The indications for use of the S-scan Open device are identical to those of the S-scan previously cleared (K161973).",""],["","Technological Comparison 21 CFR 807.92(a)(6)"],["S-scan Open is substantially equivalent to the S-scan already cleared (K161973), with regard to the technological characteristics, safety\nand effectiveness.\nThe indented use of the S-scan Open remains unchanged from the predicate device.\nS-scan Open and its predicate device have the same application environment and intended users.\nS-scan Open employs the same fundamental scientific technology as the predicate device.\nCore technical specifications, including the magnet characteristics and the filed strength, remain unchanged from the predicate device.\nThere are some differences summarized below.\nIntegration of the new software version MRI EVOlution 25 (F130001), which provides compatibility with updated electronics,\nimprovements in cybersecurity management, bug fixing and optimization, and includes the following features:\n- HyperClarity, an AI-based algorithm (SwiftMR, K230854) integrated without any modification; note: the algorithm is classified under a\ndifferent regulation in its 510(k) and this is out-of-scope from the current submission of the subject device.\n- 3D Viewer, already cleared with G-scan Brio (K180592).\n- Prone Patient Positioning option already available on the cleared Magnifico (K251901).\n- SPED (Spin-Echo with Dixon reconstruction technique) sequence: included in the “Spin Echo Fat & Water Separation” option, already\navailable on the cleared Magnifico (K251901).\n- New Operating System Windows 10, already implemented on the cleared Magnifico (K251901).\n- New Graphic User Interface, already available on the cleared Magnifico (K251901).\n- Flow compensation, already available on S-scan (K161973) and extended to all FSE family sequences.\n- Operator-selectable direction of imaging gradients, already available on the cleared Magnifico (K251901).\n- DWI LS acquisition, already available on the cleared Magnifico (K251901).\n- 2D SST1 sequence (Gradient Echo “steady state” sequence).\nThe software modifications consist of features previously cleared on Esaote MRI systems and incremental enhancements to existing\ncapabilities. These changes do not modify the intended use or the fundamental scientific technology.\nNew items listed below:\n- Patient Alert System, providing the patient with a means to alert the operator if needed.\n- New coils:\n> XL flex L-Spine Coil is the same Esaote XL flex L-Spine Coil already cleared with the G-scan Brio (K142421).\n> Knee coil 21 is the same Esaote Knee coil already available on the cleared Magnifico device (K251901).\n> Flex coil is equivalent to the Esaote Hip coil n. 6 already cleared (K080968 and K042236).\nAll necessary performance tests have been performed to ensure the safety of the subject device. Verification and validation activities\nresults demonstrate that the S-scan Open device meets its intended use, meets all applicable safety and performance standards and\ndoes not raise new questions of safety or effectiveness, compared to the predicate device.\nReference devices:\nIn addition to the predicate device (K161973), three legally marketed devices were used as reference devices to support specific\ntechnological aspects:\n- G-scan Brio (K180592)\n- Magnifico Open (K251901)\n- SwiftMR (K230854)",""],["","Non-Clinical and/or Clinical Tests Summary & Conclusions 21 CFR 807.92(b)"],["Summary of Non-Clinical Tests:\nThe S-scan Open device has been evaluated and found to comply with the applicable requirements of the following standards:\n- IEC 60601-1\n- IEC 60601-1-2\n- IEC 60601-2-33",""]],"caption_candidate":"","well_formed":true,"extraction_settings":"lines"}